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In this revised version, we further explain the lack of scales for biophilic design evaluation. Please find the revised sentences as below: Revision in Page 3 Line 122-128: “Actually, these are standard research methods of investigative POE; nevertheless, there are no existing POE scales that focus on biophilic design in the workplace. According to the research objectives of this study (i.e., evaluate the subjective health impacts of biophilic design in workplace), we need to refer the well-developed scales from other disciplinary (e.g., Environmental Psychology). And finally, a scale that integrated health evaluation and building environment evaluation (i.e., POE) is developed for investigation.” Point 2: In consideration to their response #8, I understood and agreed with why half the seven of the 14 papers were discarded, but it did not provide much insight into why the Patterns of Biophilic Design was still used.
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For their response to comment #6, while I generally agreed with the authors, I felt that it didn’t quite address what I tried to originally convey. POE scales do not likely target biophilic elements in architectural designs directly, since a direct question (e.g., how satisfied are you with the biophilic features) may not accurately depict every beneficial nuance they offer (e.g., psychological recovery). Mayer’s connectedness to nature scale) to help measure them. My generally feeling is that scales, from other domains (i.e., outside of POE studies) have been adopted for this reason, and a short sentence explaining the rationale supporting the lack of scales for biophilic design could be provided to briefly mentioned this. Instead studies may elect to use, for example, other relatable scales, which may not have originally been designed for POE surveys (e.g.
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In the revised version, sentences are added to further explain that there are too few framework available, and these two frameworks are the mainstream biophilic design frameworks that are widely applied in the practical biophilic design projects. Revision in Page 3 Line 122-128: “The 24 Biophilic Design Attributes and the 14 Patterns of Biophilic Design are the two mainstream biophilic design which are widely applied in the practical biophilic design projects. Hence, these two frameworks are the most suitable to be selected as the basis of this experiment.”
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If this was the case, perhaps this could be succinctly mentioned. In consideration to their response #8, I understood and agreed with why half the seven of the 14 papers were discarded, but it did not provide much insight into why the Patterns of Biophilic Design were still used. A more useful example, which may have elucidated this more, was whether are there too few frameworks available, and/or none others could have been used.
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1) Further explanations of “Biophilia” are added in the Introduction. Revision in Page 1 Line 27-29: “The term "Biophilia" is evolved from human evolution research and is coined to describe humans' inherent love affinity for the living things in the natural world [1,2]. It explained why we prefer nature because it is an instinct deeply rooted in the human brain.” 2) Literatures are added in the revised version to combine “workplace design” and “Biophilic Design”. Revision in Page 2 Line 48-53: “Workplace is one of the typologies that attracts the attentions of researchers. Scholars who research the relationship between the built environment and health found that the environment not merely directly or indirectly affects human health but also affects their work and study performance [59]. Studies proofed that biophilic design benefits workers’ health and productivity in an office environment [60, 61, 62, 63].” Citations are added in the Reference list: Derek, C. C., 2003. Environmental Quality and the Productive Workplace. In C. J. Anumba (Ed.), Innovative Developments in Architecture, Engineering and Construction. Rotterdam: Millpress Science Publishers. Lei, Q.H., Yuan, C., Lau, S.S.Y., 2021.
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The introduction can be optimized appropriately.The introduction of the term "Biophilia" can be more detailed and easy to understand .By contrast, the introduction of “Biophilic Design”is very substantial.It may be better to find some literature to combine workplace design and “Biophilic Design”,and then to explore the relationship between them.
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Observation Results-Biophilic Design Attributes in the Selected Offices is moved to be Section 2.3.2. It is because the 2.3.1 is the selection of office, and the Section 2.3.2 provides observation details of the selected offices. After re-construction, Section 3. Questionnaire Results focus on illustrating the questionnaire results. Hence, all the means (SD) are replaced as medians (IQR). And the corresponding figures (Figure 1 in Page 13 Line 359-361 and Figure 4 in Page 16-17 of the original manuscript) are removed in the revised version. Revision in Page 13 Line 381-394: The Cronbach’s α coefficient value of the main scale is 0.72, while those of the subscales GH, NR, and BDE in order are obtained as 0.68, 0.79, and 0.63, indicating that the questionnaire is reliable (i.e., an acceptable reliability: Cronbach's α>0.6) [57, 58] (Table 8). According to the quantitative results presented in Table 8, the medians (Interquartile Range, IQR) of the assessment show moderately high opinions toward the health and wellbeing of biophilic offices (HWBO), at 71.00 (8.00) (the score range from min. 20 to max. 100). Concerning the self-related evaluation scales GH and NR, the score range of GH and HR are minimum 4 to maximum 20, and the obtained results illustrate moderately high opinions, the values of 15.00 (2.00) and 14.00 (3.00) for GH and NR. The median (IQR) value of the POE scale BDE is evaluated as 42.00 (5.00) (range of total value: min. 12 to max. 60). Table 8. Medians, Interquartile Range (IQR), Mean, standard deviation, and α coefficient values of workers’ evaluation based on HWBO, GH, NR, and BDE. Comparison of independent variables (Gender, Age, Educational Levels, Weekly Work Hours, Daily Sedentary Time, Work Desk Locations, Working Years, Office Locations) on self-reported GH, NR, and BDE. Thanks for your suggestion. The figures and pictures have been adjusted in the revised manuscript. The Section 3 Questionnaire Results and Section 4 are rewritten in the revised version: a) the statistical analysis is modified; b) to reduce elaboration in the text. Please kindly refer the following revisions: 1) The original Section 3.1. 2) In the revised version, the formulars in Section 3.3 2. Quantitative Results of Impacts of Biophilic Design for Workplace are removed due to the statistical analysis is modified: The means (SD) are only applied when the assumption of normality applies for the datasets. Revision in Page 18 Table 9: Table 9. *p<.05, The significance level is .05.3) Elaboration for the Figure 2. Stacked graph with percentage responses for individually arranged items (from the bottom with a high percentage of disagreement to the top with high percentage of agreement) is reduced, because the illustrations are obvious in the figure. Revision in Page 15-17 Line 399-433: The analysis of individual items provides more details into the works' responses. As can be seen in percentage responses for individual items (Figure 2 in revision), most of the responses are distributed in the items "Neutral" and "Agree". The questionnaire results reveal that the employees from the understudy companies hold a relatively positive opinion on wellbeing, nature-relatedness, indoor environmental quality, and biophilic design for their health promotion. According to the arrangement, at the top of this, stacked graph are the evaluation of satisfaction of the work capacities and relationships in the workplace. About 73.2% of respondents agree that the workers of the companies under investigation are satisfied with their work capacity (GH3-Q10) and relationships (GH4-Q11). In the subscale nature relatedness, 62.2% and 61.7% of workers responded (agree/strongly agree) that their actions affect the environment (NR2-Q13), and they take notice of the wildlife in their daily lives (NR3-Q14). Nevertheless, only 47.8% of them selected agreed/strongly agree regarding the statements that their ideal spot for vacation would be a wilderness area (NR1-Q12). Regarding the POE results in the subscale BDE, 63.2% of workers agree/strongly agree that the natural light is an essential biophilic attribute and their offices are bright (BDE2-Q17). Furthermore, 60.7 % of the workers agreed that introducing natural colors in the office benefits workplace health and wellbeing (BDE11-Q26). More than 60 percent (approximately 60.7%) of respondents believe that greenery is a biophilic design that benefits office wellbeing (BDE6-Q21). Their feedback would be valuable for designers to note that application of the biophilic design attributes in the office design can enhance the experiences and evaluations of workers. The quantitative results of the questionnaire survey demonstrate that the workers agree that the biophilic design attributes in the office have positive effects on their subjective wellbeing. Stacked graph with percentage responses for individually arranged items (from the bottom with a high percentage of disagreement to the top with high percentage of agreement).
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Some of the results in the illustrations are obvious and can be reduced to less elaboration. Overall work of the article is sufficient, the results is has the certain significance, but its limitation is obvious to all.
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Thank you for your comments. These considerations are the limitations of this study. 1) these two cases are limited in representing all the workplace biophilic designs. As mentioned in the Conclusion, in the future study, we will include more offices and locations as experiment samples. In the future study, the research scope should be narrow down for intensive investigation.
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The result of biophilic design frameworks for specific workplace typology is of certain value. The location of the workplace selected in this article is limited, the related biophilic factors are scientifically screened, and the researchers have made a detailed classification study. However, the huge research scope has certain obstacles to the relevant results, and the general and targeted conclusions will be worse.
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Thank you for your suggestion. The description of the necessity of research is highlight in the revised version. Please kindly refer the following revisions: Revision in Page 2 Line 56-66: “Although the importance of biophilic design seems to be well-acknowledged, and some international or regional green building and healthy building standards incorporate biophilic design elements into the rating system, such as WELL building standard version 2 and Singapore Green Mark [53]. However, further research on developing building typology-based biophilic design guide-lines and assessment methods are necessary. Additionally, the effectiveness of such design in practical design projects for user wellbeing still requires confirmation. More importantly, building typology-based biophilic design guidelines should be appropriately developed because it would affect the designer's prioritization of design attributes selection in design practice.” Point 6:
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It is best to supplement and describe the necessity of research. At the same time, it will be more complete if the results are reflected in the summary.
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The different genders and different ages are included in the study. The age ranges included 21-25, 26-35, 36-45, 46-60. The detailed description of the demographic information is in Section 3.1. Demographic Information.
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The object of the questionnaire should be composed of people with different ages and genders, which is best explained in the article.
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b) Additionally, the study provides novel design guidelines for designers with emphasizing on weight for workplace design practices. The weighting results of this study would be especially applicable to the workplace typology. The 14 Patterns of Biophilic Design has a broader range of usage for all building typologies and is more suitable for general design applications. Therefore, the weighting results of this experiment are not employed to deny the ranking in the 14 Patterns of Biophilic Design. These are exploited to show a new biophilic design framework for the workplace according to the users’ points of view (based on the POE results). c) Furthermore, the questionnaire results enhance our knowledge on the practical ap-plication of biophilic design frameworks for the workplace and contributed to more framework design consideration. d) The correlation results support the importance of biophilic design from the user perspectives. There is a significant correlation between office biophilic design and self-reported health of employees (r=.270**, p < .01). 2) The investigative POE studies evaluated the self-reported health (GH), nature-relatedness (NR), and biophilic design in the workplace (BDE). The objective of the study is to evaluate the typical biophilic design attributes in office environment and the correlation between biophilic design and office health. Hence, the research scope is relatively extensive. 1) The Conclusion is rewritten to highlight the relationship between biophilic design and occupant health and wellbeing: Revision in Page 23 Line 516-540: “The significant research outputs from the present scrutiny are shown as following: a) The authors develop a POE questionnaire for evaluating the biophilic design for workplace health and wellbeing. e) The study results contribute to provide designers with evidence-based design at-tributes for workplace design (i.e., the nine selected workplace biophilic design attributes).” 2) The Conclusion is reconstructed and a separate section-- Section 6. Limitation and Future Studies is added in the revised version: Revision in Page 23 Line 542-551: “6. Limitation and Future Studies There are limitations in this study, first, these two cases are limited in representing all the workplace biophilic designs due to the sample size limitations. Further studies could include more offices and locations as experiment samples. In the future study, the research scope should be narrow down for intensive investigation.” Point 8:
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Adding some explanations, examples and data comparison to the conclusion will be more intuitive and convincing, just as discussed earlier in the article. Perhaps this makes this article more complete and credible. At the same time, the conclusion only summarizes the article, and lasks discussions and explanations for the future research direction.
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The investigation explains that combined literature review and POE results are one of the practical methodologies to establish biophilic design frameworks for specific workplace typology. And the questionnaire can be applied in future biophilic design research for investigation. The applications of the results are highlighted in Section 1.4. Objectives and in Section 5 Conclusion: In Section 1.4. Objectives, the three practical applications of the results are mentioned: first, a POE questionnaire for assessing the biophilic design for workplace accounting for health and wellbeing. Second, the study will provide a new biophilic design guidelines for workplaces, which can effectively assist researchers and designers to improve office biophilic design practices and decision-making on design attributes selection. The Conclusion is rewritten to highlight the contribution and implementation of the results: Revision in Page 23 Line 516-540: “The significant research outputs from the present scrutiny are shown as following: a) The authors develop a POE questionnaire for evaluating the biophilic design for workplace health and wellbeing. … “c) Furthermore, the questionnaire results enhance our knowledge on the practical ap-plication of biophilic design frameworks for the workplace and contributed to more framework design consideration.” … “e) The study results contribute to provide designers with evidence-based design at-tributes for workplace design (i.e., the nine selected workplace biophilic design attributes).” Point 9: It is better to supplement the temperature, humidity, and other parameters of the selected office in the part of the experiment, so as to facilitate readers' reference rather than just giving the location.
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The theoretical part of the presentation is extensive, but the application part is relatively poorly described.
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Basic information of the understudy offices. The supplemental Information (i.e., office temperature, number of employees) are added in the revised version. Revision in Table 5: Table 5.
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It is better to supplement the temperature, humidity and other parameters of the selected office in the part of the experiment, so as to facilitate readers' reference rather than just giving the location.
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We agree with the comment. A quantitative study for indoor workplace biophilic design to improve health and productivity performance. Journal of Cleaner Production. 324, 129168. Yin, J., Zhua, S., MacNaughton, P., Joseph, G., Allen, J.G., Spengler, J.D., 2018. Physiological and cognitive performance of exposure to biophilic indoor environment. Build. Environ. 132, 255–262. Yin, J., Arfaei, N., MacNaughton, P., Catalano, P.J., Allen, J.G., Spengler, J.D., 2019. Effects of biophilic interventions in office on stress reaction and cognitive function: a randomized crossover study in virtual reality. Indoor Air 29, 1028–1039. https:// doi.org/10.1111/ina.12593. Yin, J., Yuan, J., Arfaei, N., Catalano, P.J., Allen, G.J., Spengler, J.D., 2020. Effects of biophilic indoor environment on stress and anxiety recovery: a between-subjects experiment in virtual reality. Environ. Int. 136, 105427. https://doi.org/10.1016/j. envint.2019.105427. Previous studies proofed that biophilic design in workplaces benefits both psychological and physiological health [60, 61, 62, 63]. This study is a questionnaire survey that focus on investigating the subjective evaluation on workplace biophilic design and of workers. Physiological measurements will be included in the future study to investigate the impacts of the psychological factors on physiological comfort. References: Lei, Q.H., Yuan, C., Lau, S.S.Y., 2021.
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The author can think about the impact of such a pro biological design model on the psychology of different experimental personnel. I think psychological factors will also affect human physiological comfort.
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Thank you for your comment. Figure 1 is updated in this version.
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Figure 1 should be improved regarding the arrow.
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All the photos in Table 6 are taken by the designers. And we added an annotation under Table 6.
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Photo in table 6 should check the copyright of these photo.
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Thank you for your suggestions. The references are added in the manuscript. In-text citations in Page 1 Line 27-28: “The term "Biophilia" is evolved from human evolution research and is coined to de-scribe humans' inherent love affinity for the living things in the natural world [1,2,64].” In-text citations in Page 1 Line 40: “…the modern built environment' as 'Biophilic Design' [24,25,65].” In-text citations in Page 2 Line 69-70: “…occupant satisfaction, health, and wellbeing after occupancy of buildings [27, 28, 67].” Citations are added in the Reference list: Parsaee, M., Demers, M. H. C., Potvin, A., Hébert, M., Lalonde, J.F., Window View Access in Architecture: Spatial Visualization and Probability Evaluations Based on Human Vision Fields and Biophilia. 2021. Buildings, 11(12), 627. https://doi.org/10.3390/buildings11120627 Mollazadeh, M., Zhu, YM., Application of Virtual Environments for Biophilic Design: A Critical Review. 2021. Buildings, 11(4), 148; https://doi.org/10.3390/buildings11040148 Gillis, K., Gatersleben, B., 2015. A Review of Psychological Literature on the Health and Wellbeing Benefits of Biophilic Design. Buildings. 5(3), 948-963. https://doi.org/10.3390/buildings5030948 Candido, C., Chakraborty, P., Tjondronegoro, D., 2019. The Rise of Office Design in High-Performance, Open-Plan Environments. 9(4), 100. https://doi.org/10.3390/buildings9040100 Author Response File: Author Response.docx
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Please bring strong relevance to the scope of journal "Buildings" by investigating most recent literature.
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The “inherent affinity” is more appropriate, and the term is updated in the manuscript. Revision in Page 1 Line 28:“The term "Biophilia" is evolved from human evolution research and is coined to de-scribe humans' inherent love affinity for the living things in the natural world [1,2].” Point 2:
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The definition of biophilia is described as an “inherent love” toward nature. While this is somewhat accurate, it might be more appropriate to elucidate this as an “inherent affinity”.
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Biophilia: Does Visual Contact with Nature Impact on Health and Well-Being? International Journal of Environmental Research and Public Health. Ulrich, 1993. Biophilia, biophobia, and natural landscapes. Ko et al., 2020. A window view quality assessment framework. LEUKOS. In-text citation in Page 1 Line 44: “Some scholars summarized and classified the natural design features into biophilic design frameworks to guide design activities [25, 39, 40, 50, 51, 52].” Three references are added in the References List: Ulrich, 1993. Biophilia, biophobia, and natural landscapes. The Biophilia hypothesis. USA: Island Press: Washington, D.C. Bjørn et al., 2009. Biophilia: Does Visual Contact with Nature Impact on Health and Well-Being? International Journal of Environmental Research and Public Health. 6, 2332-2343. Ko et al., 2021. A Window View Quality Assessment Framework. Leukos. 1-26. DOI: 10.1080/15502724.2021.1965889. Ko et al., 2021.
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P1, L39-41: Please provide references to these frameworks. Reading further to page 3, I believe these are the 24 biophilic design attributes [ref. 25,39], and the 14 patterns of biophilic design [ref.40]. Further references around the biophilic concept could also be provided, e.g.: Bjørn et al., 2009. The latter reference reviewed many international standards that advocate nature and biophilic design for view and building spaces, with examples given to the Singapore context. This somewhat overlaps with my next comment.
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There are general biophilic design frameworks (e.g., the 24 Biophilic Design Attributes and the 14 Patterns of Biophilic Design) and green building, healthy building standards (e.g., WELL v2 and Singapore Green Mark) that include biophilia into the certification systems in nowadays. And the issue raised by the authors is that these biophilic design frameworks (design guidelines or standards) are general design frameworks (design guidelines or standards) which can be applied to all building typologies (i.e., residential buildings, workplaces, retails, etc). Further research needs to be conducted to develop the design guideline specific for workplace. The sentence was rewritten to demonstrate this argument. Revision in Page 2 Line 56-61: “Although the importance of biophilic design seems to be well-acknowledged, and some international or regional green building and healthy building standards incorporate biophilic design elements into the rating system, such as WELL building standard version 2 and Singapore Green Mark [53]. However, further research on developing building typology-based biophilic design guidelines and assessment methods are necessary.” Point 4:
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P2, 47-53: Although in the past there were few guidelines, nowadays, there may be more standards that focus on nature integration within the built environment. WELL v2 has several features for Nature and Mind, and Biophilia – Parts I and II, with quantitative assessment methods provided. Similarly, the Green Mark system uses the green plot ratio, assigning credits to greenery provision to enhance biodiversity and visual relief. Other standards likely incorporate biophilic elements in building architecture and could be worth highlighting. The general issue raised by the authors do not necessarily imply a lack of guidelines for biophilic design, since there are several readily available, but may point toward prioritization or emphasis of criteria to meet certain varying expectations, which was alluded to on lines 52-53. If the authors agree with this, perhaps this could be revised here to reflect this.
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Lessons learned from 20 years of CBE’s occupant surveys. A data-driven analysis of occupant workspace dissatisfaction. Occupant satisfaction with the indoor environment in seven commercial buildings in Singapore. We agree with this comment. Apart from the design evaluation, POE is also one of the mainstream research methods that can effectively diagnosing operation problems. The description and citations were inserted in the updated manuscript. Revision in Page 2 Line 77 ~ 80: “Moreover, from the perspective of building operation, the POE results also provide evaluation and feedback from occupants to the stakeholders and building managers on workplace biophilic design. Since POE is one of the mainstream research methods that can effectively diagnosing operation problems [54, 55, 56].” Citations are added in the Reference list: Graham, L.T., Parkinson, T., Schiavon, S., 2021. Buildings and Cities 2(1):166-184. DOI: 10.5334/bc.76 Kent, M., Parkinson, T., Kim, J., Schiavon, S., 2021. Building and Environment 205, 108270 Cheung, T., Schiavon, S., Graham, L.T., Tham, K.W., 2021. Building and environment (188). DOI:10.1016/j.buildenv.2020.107443 Point 5:
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P2, L63: Although I wouldn’t completely rule this out, POE surveys may not always provide feedback to the architect, since they are implemented post design-stage and the building would be operated by facility management or the owner. In my view, POE information had more utility diagnosing operation problems, which can be solved when running the building, identifying prominent sources of dissatisfaction that can prompt action to resolve these issues. Recently POE studies, also using office data, advocate this as benefit to their implementation, albeit not necessarily being the only reason: žGraham et al., 2020. Building & Cities. Kent et al., 2021. Building and Environment. Cheung et al. 2021.
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The sentence was rewritten in the updated version. Revision in Page 3 Line 109: “It has helped experts to obtain user’s feedbacks over the last five decades [31,32].” Point 6:
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P3, L92: I think refers to “has helped” given the five decades predating this.
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Yes, the existing psychological scales are well-developed, but scales for investigating “workplace biophilic design” had not been developed before. Hence, in this study, we develop a method that focus on evaluating the biophilic design elements in workplace. The major scale of the questionnaire consists of three parts (subscales): general health (GH), nature relatedness (NR), and biophilic design evaluation (BDE). The questions in the first and the second subscales are referred to the validated scales--The World Health Organization Quality of Life (WHOQOL) and the nature relatedness (NR). The third scale is focus on evaluation on the biophilic design elements. Hence, the questions in the final section are designed based on the selection of the biophilic design elements/attributes that typically applied in the office design, which are not mentioned in the previous scales.
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P3, L106: While I generally agree with, questions could be raised to whether POE scales should be used to evaluate biophilic design evaluation. Biophilic design is known to elicit mental and physical health benefits, as stated by the authors on page 1, lines 29-32. Therefore, it would be more appropriate to use psychological scales (e.g., PANAS or psychological restoration), instead of design orientated question or survey. If the authors agree with this, this aspect could be revised.
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The method of selection of the biophilic design attributes/patterns for workplace is: ŸStep one, find out the correlated biophilic design characteristics from the two mainstream biophilic design frameworks. ŸStep two, we neglect the patterns which are not representative in office environment (please find the detailed explanations in the respond for Comment #8) and specify the selected design patterns to nine biophilic design attributes. The detailed process is shown in Section 2.1 and Figure 1. ŸStep three, verify the selection of the nine biophilic attributes matches the validated eight factors that affect workers’ satisfaction and productivity (please find the detailed explanations in the respond for Comment #11). In terms of the reviewer think that the listed attributes span across different domains and the communal features are not that apparent, we believe it is due to the research perspective of biophilic design is different from the perspectives of building science and traditional POE studies (please find the detailed explanations in the respond for Comment #9).
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Something I felt would useful would at the beginning would be a clear definition for what “biophilic attributes” refers to. Figure 1 provides some insights into this, but these listed attributes span across different domains and the communal features are not that apparent. This becomes an issue later, since some aspects referring to biophilic design become unclear.
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The authors gave the reason after the sentence in Page 4, Line 173-174 of the original manuscript “Second, the authors neglect seven design patterns from the 14 Patterns of Biophilic Design which are not representative of the workplace design.” to explain why the seven of the patterns from the 14 patterns of biophilic design were discarded: For instance, the patterns “Presence of Water”, “Prospect”, “Refuge”, “Mystery”, and “Risk” (i.e., itemized patterns 5, 11, 12, 13, and 14 in Column B) are recommended but not demonstrative in this building typology (workplace). Those are usually applicable in other building typologies, such as hotels or residential. To further explain why these patterns are recommended but are discarded: 1) First, these design patterns (i.e., the seven discarded patterns of the 14 biophilic design patterns) are recommended because they are proofed that benefits health. 2) However, these patterns are not common in most offices. For instance, in most cases, the employers would not create an office environment that makes the workers feel “Prospect”, “Refuge”, “Mystery”, and “Risk”. 3) Therefore, we only included those biophilic design patterns that relatively easy to apply in the workplace (e.g., greenery, natural light, artworks), and discard those which are not representative in an office design. And the sentences are revised to further explain the discard of the seven patterns. Please see the revised contents in the updated manuscript below: Revision in Page 5 Line 191-197: “For instance, the patterns “Presence of Water”, “Prospect”, “Refuge”, “Mystery”, and “Risk” (i.e., itemized patterns 5, 11, 12, 13, and 14 in Column B) are recommended because they are proofed that benefits health. For instance, in most cases, the employers would not create an office environment that makes the workers feel “Prospect”, “Refuge”, “Mystery”, and “Risk”.” Point 9:
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P4, L173-174: The authors state that seven of the patterns from the 14 patterns of biophilic design were discarded. If this was the case, then please better articulate its overarching utility in this study, considering that half of the patterns were not relevant to the research scope.
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We believe that there is no conflict between the different classifications. The same parameters (e.g., daylight, thermal comfort, and air-quality, office layout and building form) can be classified in different classifications (i.e., the traditional POE frameworks and the biophilic design frameworks) by different perspectives. 1) From perspective of building science, building performance, and traditional POE, these parameters (e.g., daylight, thermal comfort, and air-quality) are considered as indoor environment parameters, and office layout and building form are considered a physical and architectural parameters. 2) On the other hand, from the perspective of biophilia and biophilic design, (e.g., factors workers’ satisfaction and productivity), these parameters are re-classified and defined as the factors affecting workplace health. Both classifications validated by previous literatures.
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P4, L180-183: In traditional POE studies and general building science research, daylight, thermal comfort, and air-quality, would be considered as indoor environment parameters (as examples, please see refs. in comment #4), while office layout and building form would be considered a physical and architectural parameters. Reading further to page 5, lines 189-192, the authors begin to suggest to this, but referred to them and others indoor environmental parameters as factors for the workplace. I would suggest better rationalizing the connections between the nine design parameters to biophilia to make these more overt.
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We revised the Figure 1. The connections between 24 Biophilic Design Attributes (Column A) and 14 Patterns of Biophilic Design (Column B); The nine biophilic design attributes for the workplace (Column C). First, to simplify the image, we put all the definitions into a new table in the appendix (Appendix A. Definitions of biophilic design attributes and patterns). In case that there are some readers are not familiar with the biophilic design attributes or patterns: Revision in Page 4 Line 164: “These two biophilic frameworks are chosen as research references (definitions of the at-tributes and patterns are in Appendix A).” Appendix A in Page 22: “Appendix A. Definitions of biophilic design attributes and patterns” Second, we fill the correlated boxes with same solid colours to make them more recognizable: Revision in Page 6 Line 207: Point 11:
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Figure 1: The image presenting all the linkages is very interesting and is worth emphasizing, but contains an overwhelming degree of information, and the text and line sizes are too small for readership. Please consider simplifying the figure. For example, some text boxes many do not need further explanation (e.g., presence of water); also, the lines connecting column A to the same patterns in column 4 could be color coordinated.
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Table 2 made a comparison between the selected nine biophilic design patterns for workplace in this study and the validated eight factors that affect workers’ satisfaction and productivity. There are overlaps between the nine biophilic design attributes and these eight influential factors for the workplace. These overlapped factors highlight the nine biophilic design attributes that are critical to the office design. Hence, the validation of the selection of the nine biophilic attributes are proofed by the previous literature. Sentences are added in the paragraph to clarify the demonstration. Revision in Page 6 Line 215-220: “Table 2 made a comparison between the selected nine biophilic design attributes for workplace in this study and the validated eight factors that affect workers’ satisfaction and productivity. These overlapped factors highlight the nine biophilic design at-tributes that are critical to the office design. The validation of the selection of the nine biophilic attributes are proofed by the previous literature [37].” Point 12:
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Table 2: Please consider providing further explanations for this table. It was not clear what the authors wanted to show.
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1) The reasons why the two offices are selected for investigation: a) the urban contexts are similar: both the cities (Singapore and Shenzhen) are typical compact, high density Asian mega-cities; b) both the offices are open-plan offices. Revision in Page 9 Line 277-280: “The two offices have similar features: 1) the urban contexts are similar: both the cities (Singapore and Shenzhen) are typical compact, high density Asian mega-cities; b) both the offices are open-plan offices.” 2) The supplemental Information (i.e., temperature, number of employees) are added in the revised version. Revision in Page 9 Table 5: Table 5. Basic information of the understudy offices. The structure is re-constructed in the revised version. The original Section 3.1.
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P8, L245: Please specify why these two offices were of interest (e.g., were they comparable or had specify architectural features worthy of study). If possible, please provide more characteristics (e.g., size, floor area, furniture layout (e.g., open-plan or enclosed), etc.) for each office. Later (P10, L299), it says 201 questionnaires were collected, with 161 occupants taking part in the Singaporean office. This led me to believe that this office was much larger than the building studied in China. An image showing the indoor conditions and outdoor façade for each might be beneficial. Many of the explanations found in section 3.1 could be moved into this part of the manuscript, since they many describe and show the existing office conditions and to do necessarily form part of the main results.
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We agree with the comment. The means (SD) are only applied when the assumption of normality applies for the datasets. According to the quantitative results presented in Table 8, the medians (Interquartile Range, IQR) of the assessment show moderately high opinions toward the health and wellbeing of biophilic offices (HWBO), at 71.00 (8.00) (the score range from min. 20 to max. 100). Concerning the self-related evaluation scales GH and NR, the score range of GH and HR are minimum 4 to maximum 20, and the obtained results illustrate moderately high opinions, the values of 15.00 (2.00) and 14.00 (3.00) for GH and NR. The median (IQR) value of the POE scale BDE is evaluated as 42.00 (5.00) (range of total value: min. 12 to max. 60). Table 8. Medians, Interquartile Range (IQR), Mean, standard deviation, and α coefficient values of workers’ evaluation based on HWBO, GH, NR, and BDE. Revision in Page 18-20 Table 9: Table 9. Comparison of independent variables (Gender, Age, Educational Levels, Weekly Work Hours, Daily Sedentary Time, Work Desk Locations, Working Years, Office Locations) on self-reported GH, NR, and BDE.
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Section 3.3. Although I appreciated the thoroughness to which the descriptive statistical was explained, I wasn’t convinced the mean was the best indicator for the data, considering that evaluation scores were collected on a 5-point scale and not a continuous linear one. In-lieu of the mean, please consider using the median and inter-quartile range as the central tendency and dispersion indicators. Figures 1 and 4 can be removed, as the assumption of normality no longer applies (also on P15, L399-400), or replaced with boxplots.
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Thank you for your suggestion. The Cronbach’s Alpha with an Alpha>0.6 considered acceptable internal consistency in this study. The statement and the references are added in the revised version. Revision in Page 13 Line 381-383: “The Cronbach’s α coefficient value of the main scale is 0.72, while those of the sub-scales GH, NR, and BDE in order are obtained as 0.68, 0.79, and 0.63, indicating that the questionnaire is reliable (i.e., an acceptable reliability: Cronbach's α>0.6) [57, 58] (Table 8).” Citations are added in the Reference list: Morgan, P. J., Cleave‐Hogg, D., DeSousa, S., Tarshis, J., 2004. High‐fidelity patient simulation: validation of performance checklists. British Journal of Anesthesia, Volume 92, (3) 388–392. Cronbach, L.J., 1951. Coefficient Alpha and the Internal Structure of tests, Psychometrika. Vol. 297-334.
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Table 8: Please consider applying benchmarks for what constitute reasonable levels for internal consistency, when using the Cronbach’s Alpha (e.g., α>0.7): Please see, for example: Taber, 2018. The use of Cronbach’s Alpha when developing and reporting research instruments in science education. Research in Science Education. Tavakol et al. Making sense of Cronbach’s Alpha. International Journal of Medical Education.
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1) Abbreviated labels referring to the actual questions are added in the Figure 3 (Figure 2 in the revision). But 2) we keep the original percentages (round to one decimal place). We think it is not hard for the readers to understand, and the original percentages (round to one decimal place) is more accurate. Revision in Page 17 Line 431: Point 16:
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Figure 3. The plot is well presented. A few minor notes for improvement: 1) Please consider adding short or abbreviated labels referring to the actual question, instead of codes (e.g., GH3-Q10). This would make it easier for the reader; 2) Round the percentages to the nearest whole number.
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Thanks for the reminder, the error has been corrected in the revised version. Revision in Page 21 Line 473: “According to Table 10, Pearson correlations indicate that…” Point 17:
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P17, L434: Please correct the unfortunate citation error on this line.
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Spearman’s correlation test was conducted, and the revised contents are shown in the updated version. Revision in Page 17 Line 440: “Second, Spearman's correlation analysis is utilized to examine the correlation between three subscales.” Revision in Page 21 Line 472-483: 4.2. Intercorrelation between the three subscales (GH, NR, BDE) “According to Table 10, Spearman's correlations indicate that works' nature relatedness (NR) was positively correlated with self-evaluated GH (r = .264**, p < .01). This result also confirms the previously obtained results that people who had a higher evaluation in nature relatedness are also had a higher evaluation on their health. When the occupants feel that they have a strong sense of relationship with nature, it is observed that the biophilic environment would have positive impacts on their health. More importantly, significant correlation is also found in between biophilic design evaluation and self-reported health (GH), r=.270**, p < .01, indicating that office biophilic design has positive values on workers’ psychological health.” Table 10. Intercorrelations between responses of three subscales. Correlation is significant at the 0.01 level (2-tailed) Point 18:
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P18, section 4.2: Similar to comment #13, the data may be more suited to a Spearman’s correlation test, instead of the Pearson’s correlation coefficient. Due to the reasonable size of the dataset collected, it may not change the interpretation, but would help improve the analytical rigor.
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Thank you for your comment. The above contents have been corrected in the revised version.
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P18, L448-450: Please check whether the sentence is accurate and correct the table caption numbers; I believe these should be Tables 10 and 11 and 12, not 1, 2 and 3. The sentence reads: Homogenous subsets with significant discrepancies (differences?) across subsets, leading to no significant differences across subsets. The above is not easy to grasp. If the information is accurate, please consider amending this to make this clearer.
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The Conclusion is rewritten to highlight the relationship between biophilic design and occupant health and wellbeing: Revision in Page 23 Line 514-540: “The significant research outputs from the present scrutiny are shown as following: a) The authors develop a POE questionnaire for evaluating the biophilic design for workplace health and wellbeing. The investigation explains that combined literature review and POE results are one of the practical methodologies to establish biophilic design frameworks for specific workplace typology. And the questionnaire can be applied in future biophilic design research for investigation. b) Additionally, the study provides novel design guidelines for designers with emphasizing on weight for workplace design practices. The weighting results of this study would be especially applicable to the workplace typology. The 14 Patterns of Biophilic Design has a broader range of usage for all building typologies and is more suitable for general design applications. Therefore, the weighting results of this experiment are not employed to deny the ranking in the 14 Patterns of Biophilic Design. These are exploited to show a new biophilic design framework for the workplace according to the users’ points of view (based on the POE results). c) Furthermore, the questionnaire results enhance our knowledge on the practical ap-plication of biophilic design frameworks for the workplace and contributed to more framework design consideration. d) The correlation results support the importance of biophilic design from the user perspectives. There is a significant correlation between office biophilic design and self-reported health of employees (r=.270**, p < .01). e) The study results contribute to provide designers with evidence-based design at-tributes for workplace design (i.e., the nine selected workplace biophilic design attributes).” Author Response File: Author Response.docx
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While the conclusions were well structured, I felt the authors could have highlighted more the main takeaway messages from their endeavors, in particularly the relationship between biophilic design and occupant health and wellbeing. This seems to be a core aspect of their work but did really emerge from the final section of their work in the same way it was emphasized in the abstract.
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1) Further explanations of “Biophilia” are added in the Introduction. Revision in Page 1 Line 27-29: “The term "Biophilia" is evolved from human evolution research and is coined to describe humans' inherent love affinity for the living things in the natural world [1,2]. It explained why we prefer nature because it is an instinct deeply rooted in the human brain.”
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The introduction can be optimized appropriately.The introduction of the term "Biophilia" can be more detailed and easy to understand .By contrast, the introduction of “Biophilic Design”is very substantial.It may be better to find some literature to combine workplace design and “Biophilic Design”,and then to explore the relationship between them.
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2) Literatures are added in the revised version to combine “workplace design” and “Biophilic Design”. Revision in Page 2 Line 48-53: “Workplace is one of the typologies that attracts the attentions of researchers. Scholars who research the relationship between the built environment and health found that the environment not merely directly or indirectly affects human health but also affects their work and study performance [59]. Studies proofed that biophilic design benefits workers’ health and productivity in an office environment [60, 61, 62, 63].” Citations are added in the Reference list:
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The introduction can be optimized appropriately.The introduction of the term "Biophilia" can be more detailed and easy to understand .By contrast, the introduction of “Biophilic Design”is very substantial.It may be better to find some literature to combine workplace design and “Biophilic Design”,and then to explore the relationship between them.
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Derek, C. C., 2003. Environmental Quality and the Productive Workplace. In C. J. Anumba (Ed.), Innovative Developments in Architecture, Engineering and Construction. Rotterdam: Millpress Science Publishers. Lei, Q.H., Yuan, C., Lau, S.S.Y., 2021. A quantitative study for indoor workplace biophilic design to improve health and productivity performance. Journal of Cleaner Production. 324, 129168. Yin, J., Zhua, S., MacNaughton, P., Joseph, G., Allen, J.G., Spengler, J.D., 2018. Physiological and cognitive performance of exposure to biophilic indoor environment. Build. Environ. 132, 255–262. Yin, J., Arfaei, N., MacNaughton, P., Catalano, P.J., Allen, J.G., Spengler, J.D., 2019. Effects of biophilic interventions in office on stress reaction and cognitive function: a randomized crossover study in virtual reality. Indoor Air 29, 1028–1039. https:// doi.org/10.1111/ina.12593. Yin, J., Yuan, J., Arfaei, N., Catalano, P.J., Allen, G.J., Spengler, J.D., 2020. Effects of biophilic indoor environment on stress and anxiety recovery: a between-subjects experiment in virtual reality. Int. 136, 105427. https://doi.org/10.1016/j. envint.2019.105427. 61.7% of workers responded (agree/strongly agree) that their actions affect the environment (NR2-Q13), and they take notice of the wildlife in their daily lives (NR3-Q14). 63.2% of workers agree/strongly agree that the natural light is an essential biophilic attribute and their offices are bright (BDE2-Q17). 60.7 % of the workers agreed that introducing natural colors in the office benefits workplace health and wellbeing (BDE11-Q26). Citations are added in the Reference list: 59.
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The introduction can be optimized appropriately.The introduction of the term "Biophilia" can be more detailed and easy to understand .By contrast, the introduction of “Biophilic Design”is very substantial.It may be better to find some literature to combine workplace design and “Biophilic Design”,and then to explore the relationship between them.
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Observation Results-Biophilic Design Attributes in the Selected Offices is moved to be Section 2.3.2. It is because the 2.3.1 is the selection of office, and the Section 2.3.2 provides observation details of the selected offices. After re-construction, Section 3. Questionnaire Results focus on illustrating the questionnaire results. Hence, all the means (SD) are replaced as medians (IQR). And the corresponding figures (Figure 1 in Page 13 Line 359-361 and Figure 4 in Page 16-17 of the original manuscript) are removed in the revised version. Thanks for your suggestion. The figures and pictures have been adjusted in the revised manuscript. The Section 3 Questionnaire Results and Section 4 are rewritten in the revised version: a) the statistical analysis is modified; b) to reduce elaboration in the text. Please kindly refer the following revisions: 1) The original Section 3.1. 2) In the revised version, the formulars in Section 3.3 2. Quantitative Results of Impacts of Biophilic Design for Workplace are removed due to the statistical analysis is modified: The means (SD) are only applied when the assumption of normality applies for the datasets.
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Some of the results in the illustrations are obvious and can be reduced to less elaboration. Overall work of the article is sufficient, the results is has the certain significance, but its limitation is obvious to all.
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Revision in Page 13 Line 381-394: The Cronbach’s α coefficient value of the main scale is 0.72, while those of the subscales GH, NR, and BDE in order are obtained as 0.68, 0.79, and 0.63, indicating that the questionnaire is reliable (i.e., an acceptable reliability: Cronbach's α>0.6) [57, 58] (Table 8).
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Some of the results in the illustrations are obvious and can be reduced to less elaboration. Overall work of the article is sufficient, the results is has the certain significance, but its limitation is obvious to all.
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Revision in Page 18 Table 9: Table 9.
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Some of the results in the illustrations are obvious and can be reduced to less elaboration. Overall work of the article is sufficient, the results is has the certain significance, but its limitation is obvious to all.
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Revision in Page 15-17 Line 399-433: The analysis of individual items provides more details into the works' responses.
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Some of the results in the illustrations are obvious and can be reduced to less elaboration. Overall work of the article is sufficient, the results is has the certain significance, but its limitation is obvious to all.
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Figure 1 is updated in this version.
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Figure 1 should be improved regarding the arrow.
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All the photos in Table 6 are taken by the designers. And we added an annotation under Table 6.
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Photo in table 6 should check the copyright of these photo.
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Thank you for your suggestions. The references are added in the manuscript.
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Please bring strong relevance to the scope of journal "Buildings" by investigating most recent literature.
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Subtotal resection is usually defined as a resection of 95-90%, with <90% defined as partial. We addended the submission in line 93-95 as well as table 4 as recommended.
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How is subtotal resection defined in chordoma (% of volume remaining?)
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We are grateful to the reviewer for catching these mistakes. Both volume reduction and pathology associated numbers are formatting errors and we addended the table to correct these mistakes.
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What means Pathology 0 in table 4?
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We agree with the reviewer that useful tools and techniques are available in different modalities and certainly surgeons dealing with various tumors utilize these as needed. We are fortunate to have access to this multi-modality image guided operating suite, and here we report on its use in specific rare tumors, chordomas and chondrosarcomas. We agree that the use of the PET-CT has no use in these cases, and we mentioned it only as part of the general introduction of the AMIGO suite. We addended the manuscript (line 260-264) as recommended
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Thus it would be helpful for the authors to clarify this. The AMIGO suite has great capabilities, but when it comes to intraoperative imaging, it is CT and MRI scans that are made, and then using Brain Lab and possibly other software, that information is processed and redisplayed including 3D reconstructions.
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We agree with the reviewer that it is the acquisition of multimodality (CT and MRI), with registration of preoperative imaging then intraoperative co-registration. We shared these steps in the “Operative and perioperative management” section (line 60).
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This does not detract from the value of the technique, but it is important to clarify that what really is happening is a variety of preoperative imaging is imported and co-registered into the Brain Lab, and then intraoperative MR and occasionally CT data is again obtained and processed and analyzed.
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As acknowledged in the limitation section and noted by the reviewer, the rarity of these tumors and the small number of patients in most series, including ours, limits analysis. Hence, we did not aim to generalize our outcome. Our focus was on how the use of these modern tools can facilitate maximum safe tumor removal which is considered a pivotal factor in the management of chordoma and chondrosarcoma.
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It is therefore difficult to state that the results were clearly improved or to even compare to other series, without larger numbers and direct comparison or classification of individual tumor locations and characteristics in differing series.
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Subtotal resection is usually defined as a resection of 95-90%, with <90% defined as partial. We addended the submission in line 93-95 as well as table 4 as recommended.
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How is subtotal resection defined in chordoma (% of volume remaining?)
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We are grateful to the reviewer for catching these mistakes. Both volume reduction and pathology associated numbers are formatting errors and we addended the table to correct these mistakes.
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What means Pathology 0 in table 4?
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We agree with the reviewer that it is the acquisition of multimodality (CT and MRI), with registration of preoperative imaging then intraoperative co-registration. We shared these steps in the “Operative and perioperative management” section (line 60).
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when one reads it initially it would appear that there are many different modalities available for intraoperative imaging. However, the PET scan does not appear to have actually been used for intraoperative repeat imaging to assess resection, and fluoroscopy and 3D reconstructions using Brain Lab software are standard fare in many operating rooms. Intraoperative angiography might have been used in the case of vascular injury but this also is available in many institutions. The authors appear to really only use CT and MRI intraoperatively, with the other modalities imported preoperatively into the Brain Lab navigational system. 3D reconstructions of newly acquired data is a capability of the software, and is available in many places. Thus it would be helpful for the authors to clarify this. The AMIGO suite has great capabilities, but when it comes to intraoperative imaging, it is CT and MRI scans that are made, and then using Brain Lab and possibly other software, that information is processed and redisplayed including 3D reconstructions. Making this clear is important for others who either use the technique or who want to do so. All that is needed is easy intra-operative access to CT and MR imaging and the ability to import and reconstruct the data real time. That is plenty and a challenge for many, but the other imaging modalities used are either standard fare in many centers (x-ray imaging, endoscopy) or do not need to be in adjacent rooms (PET scanning and angiography (can be done in the primary Or). This does not detract from the value of the technique, but it is important to clarify that what really is happening is a variety of preoperative imaging is imported and co-registered into the Brain Lab, and then intraoperative MR and occasionally CT data is again obtained and processed and analyzed.
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As acknowledged in the limitation section and noted by the reviewer, the rarity of these tumors and the small number of patients in most series, including ours, limits analysis. Hence, we did not aim to generalize our outcome. Our focus was on how the use of these modern tools can facilitate maximum safe tumor removal which is considered a pivotal factor in the management of chordoma and chondrosarcoma.
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The results, while admirable, cannot easily be compared to other series, as the numbers are small and each case has its own complex series of characteristics that make it unique. It is therefore difficult to state that the results were clearly improved or to even compare to other series, without larger numbers and direct comparison or classification of individual tumor locations and characteristics in differing series.
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As suggested, we analyzed the distribution of IRS (immunoreactivity score) across the cohort. In Figure 1 it can be clearly seen that there are two groups forming here, those with 0-4 and those with 6-12 IRS. In addition, we calculated the survival probability depending on the IRS (Figure 2). Patients with an IRS of 6 or higher have a similar bad prognosis compared to patients with an IRS below 5. A better survival correlates with lower MACC1 IRS. Patients with an IRS of 0 have the best prognosis. Based on these two analyses, the decision for cut-off value of 5 was made. Additionally, ROC curve analysis showed, that the IRS value of 5 has the highest Youden Index and is therefore the most suitable cut-off value. 0.408) (Figure 3 and Table 1). Looking at MACC1 expression in cell lines and tissue samples, the variability looks similar. Nevertheless, it must be considered that the investigation of the homogeneous cell lines is a purely quantitative analysis of the expression by Western plot and RT-PCR. The analysis of the tissue samples by immunoreactivity score analyses both the strength of expression and the inhomogeneity of expression. Figure 1: Distribution of the IRS across the cohort Figure 2: Overall Survival depending on the IRS Figure 3: ROC Curve for IRS cut-off analysis (AUC 0.716 [0.656 – 0.776]) Table 1: Sensitivity, specificity and Youden Index for different IRS cut-off values.
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Based on the cell line RNA and protein data the expression level of MACC1 is highly variable rather than being present or not. Is there a similar variability present among the tissue samples? Please provide the distribution of the IRS scores of the patient cohort and explain how was IRS 5 chosen as cut off?
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We thank the reviewer for raising this point. However, to respond to this question appropriately, we currently can provide only the results from proliferation assays for one cell line model (FLO1-EV vs FLO1-MACC1) over the time period of 72 h. This assay was with no statistically significant difference in cell proliferation between FLO1-EV vs FLO1-MACC1 (see Figure 4). Figure 4: Proliferation of FLO1 EV and FLO1 MACC1 over 72 h. Analysis of in vitro proliferation assay. Unfortunately, the short revision period of 10 days limits the generation of additional data sets for proliferation in further tumor cell lines.
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The authors argue that MACC1 expression did not significantly influenced cell proliferation in the two cell line models. However, cell proliferation was analyzed only in a 24-hour long period even though most cancer cells have a doubling time around 24 hours. In order to draw a conclusion about the proliferation effect a longer (48 or 72 hours) measurement is necessary.
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We thank the reviewer for this question. The concept of MACC1 inhibition was originally developed by our group for the treatment of MACC1 positive colorectal cancers and was recently published (Kobelt et al. Oncogene 2021). In this study we transferred our experience with MACC1 inhibition by selumetinib on AGE/S. Therefore, we chose the same doses for in vitro and in vivo experiments, and which was also used by other authors (Huynh et al. Mol Cancer Therapy. 2007). Further, we knew that the selected selumetinib concentrations of 10 µM has no cytotoxic effect in vitro and showed no reduction of migration in the MACC1 negative clones (FLO1-EV and OEshMACC1). Regarding the different dosages in the context of xenografted mice treatment in vivo and the clinically used dosages, the FDA recommends multiplying the dosage by a factor of 0.08 when transferring from mouse to human (Niar et al. Journal of basic and clinical pharmacy 2016). According to this calculation, the dosage of 50 mg selumetinib /kg mouse used would equal a dosage of 4 mg/kg in humans. The clinical dose of 75mg twice daily corresponds to a dose of 2x1mg per kg assuming a patient weight of 75kg. Using the aforementioned calculation, this dose equals then 12.5 mg/kg for treatment of mice. In our study, we refer again to the work of Huynh et al. Here, in which a dosage of 12 mg/kg selumetinib showed only a low level of effectiveness. At 100 mg/kg, a very good effectiveness was seen, however combined with an increased toxicity. Thus, we used in our study the dosage of 50 mg/kg as an effective dosage with low toxicity for the mice. Overall, we are considering here a pre-clinical model. The possibility of MEK1 inhibition to inhibit MACC1-induced effects in AGE/S was examined. Further, extended in vivo studies might then reveal the ideal dosage in vivo, being thereafter translated to use in humans. The use of trametinib is an interesting suggestion and might well be adapted to its use in forthcoming studies References: Kobelt, D., Perez-Hernandez, D., Fleuter, C., Dahlmann, M., Zincke, F., Smith, J., ... & Stein, U. (2021). The newly identified MEK1 tyrosine phosphorylation target MACC1 is druggable by approved MEK1 inhibitors to restrict colorectal cancer metastasis. Oncogene, 40(34), 5286-5301. Huynh H, Soo KC, Chow PK, Tran E. Targeted inhibition of the extracellular signal-regulated kinase kinase pathway with AZD6244 (ARRY-142886) in the treatment of hepatocellular carcinoma. Mol Cancer Ther. 2007 Jan;6(1):138-46.. Nair, Anroop B.; Jacob, Shery. (2016). A simple practice guide for dose conversion between animals and human. Journal of basic and clinical pharmacy, 7. Jg., Nr. 2, S. 27.
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It would be nice to know the selumetinib sensitivity of the two used cell lines. The concentration used from selumetinib both for the cell line experiments (10 microM) and for the animal experiments (50mg/kg) are quite high. Please discuss how the applied concentrations are related to the clinicaly used dosage (75 mg administered orally twice https://clinicaltrials.gov/ct2/show/NCT02448290) and why not the more efficient MEK1 inhibitor trametinib was used for the experiments.
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We thank the reviewer for this comment. The IRS cut-off value 5 reaches a sensitivity of 76.6% and a specificity of 64.2% (Youden Index. We include the arguments into the methods section page 3: To define the cut-off value a ROC curve analysis was performed. 0.408) and was chose as cut-off value (see supplement Figure S1 and Table S1). Additionally, we added the ROC curve and the table with sensitivity, specificity and Youden Index into a supplement section as figure S1 and table S1 Figure S1: ROC Curve for IRS cut-off analysis (AUC 0.716 [0.656 – 0.776]) Positive if Greater than or Equal to Sensitivity 1- Specificity Specificity Youden Index -1 1 1 0 0 1 0,869 0,500 0,500 0,369 3 0,864 0,483 0,517 0,381 5 0,766 0,358 0,642 0,408 7 0,729 0,342 0,658 0,387 8,5 0,421 0,217 0,783 0,204 10,5 0,411 0,200 0,800 0,211 13 0 0 1 0 Table S1: Sensitivity, specificity and Youden Index for different IRS cut-off values.
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The authors´answer regarding the cut off is sufficient, please include this argument either in the methods section or as supplementary information.
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thank you for this comment: we added the proliferation analyses by MTT into the method section page 5: Additionally, proliferation for FLO-1/EV and FLO-1/MACC1 was analyzed over 72 h by MTT. 4x103 cells were plated into 96-well-plates and were allowed to accommodate for 24 h. after 48 and 72 h formazan crystals were dissolved in 150 μl of DMSO and the absorption was measured at 560 nm in the absorbance reader (Tecan infinite 200 PRO). Each cell proliferation experiment was performed in triplicates. We added the results of the MTT analyses into the results section page 11: The additional analysis of the proliferation over 72 h showed no significant differences between FLO-1/EV (100% ± 4.886) and FLO-1/MACC1 (112.3% ± 12.24; p=0.113) (see supplement Figure S3). We added the MTT plot as figure S2 into the supplement section Figure S2: Proliferation of FLO1 EV and FLO1 MACC1 over 72 h. Analysis of in vitro proliferation assay.
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The authors refer to a data "Proliferation of FLO1 EV and FLO1 MACC1 over 72 h", however I couldn´t find the figure either in the manuscript file or here in the answer.
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We apologize for the inconvenience. Figure 4 can be found on page 14 in the submitted version. We inserted Figure 4 in the revised manuscript again to solve the technical issue.
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[1] Figure 4 is missing. In the pdf I reviewed, the caption is there, but the figure is not.
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We address this question in the results part MACC1 expression: “ Due to the procedure of cutting and staining, some samples could not be used for the evaluation. Samples with insufficiently representative tumor tissue were also excluded from the evaluation. Cores with representative tumor material and evaluable staining were available in 266 of 360 samples (73.9%)…”. To avoid misunderstandings, we corrected the abstract to: 266 Samples of 360 AGE/S patients were analyzed for MACC1 expression.
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[2] Abstract says 266 patients were analyzed (line 36), while result says 360 patients were analyzed (line 249). Please fix this inconsistency.
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We thank the reviewer for this correction. This formatting issue was corrected throughout the entire manuscript.
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[3] Throughout the paper, 10^x wrongly displays as 10x (e.g. "105" instead of "10^5" in lines 152 and 170, "106" instead of "10^6" in line 217, "X2" instead of "X^2" in line 241, "108" instead of "10^8" in lines 353, 354, 365, 366, 367, 368, 370, 371).
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We thank the reviewer for this valuable hint. As suggested, we included p-values in Figure 3G and 3H. In Figure 3G there is a significant increase in migration of cells without MACC1 expression. This is based on a sufficiently large N, that renders even small differences statistically significant. Further, this increase is rather small and is outperformed by the MACC1-mediated increase in migration and the reduction in the MACC1-mediated migration by selumetinib. The data show, that selumetinib does not reduce migration of the MACC1-negative FLO1 and that MACC1 induces migration in this cell line that can be inhibited by selumetinib.
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[4] In Figures 3G and 3H, please specify p-values for untreated vs selumetinib in FLO-1/EV and OE33/shMACC1 respectively. If the difference is statistically significant, please briefly explain/speculate why.
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We thank the reviewer for this suggestion to improve the visual quality of the manuscript. The legends of 3F and I have been enlarged and the resolution of the figure has been increased.
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[5] If possible, please use a higher resolution version of Figures 3F and 3I (the legends are blurry and hard to read in the current version).
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We thank the reviewer for this discussion. The empty vector control clone was transduced and selected afterwards. During the selection procedure it is possible that a subclone was generated that expresses slightly more (or less) of any mRNA and protein. It differs from the wildtype by handling (transduction, selection etc) and somewhat by age (cell divisions). Therefore, for all comparisons the empty vector clone was used, as this clone was generated in parallel to the MACC1 clone.
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[6] In line 306/307, please explain/speculate briefly why the control clone had higher MACC1 expression than the wildtype.
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We thank the reviewer for pointing this out: Survival reports were changed in median survival and the 95% confidence interval were included. Additionally, disease-specific survival results were reported.
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[7] In line 272/273: (i) please report median survival in each group (instead of mean survival), (ii) please specify Hazard ratio with 95% confidence interval (in addition to p values), (iii) please report both overall survival result and disease-specific survival result (since you showed both in Figures).
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We thank the reviewer for pointing this out: OR with the confidence interval is now included.
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[8] In line 274, please change "OR 1.51" to "OR 1.51 [... - ...]", i.e. specify the 95% confidence interval.
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We thank the reviewer for pointing this out: all survival reports were changed in median survival and the 95% confidence interval were included.
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[9] In line 277-279: (i) please report median survival in each group (instead of mean survival), (ii) please specify Hazard ratio with 95% confidence interval (in addition to p values). Same for lines 425/426.
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Thank you for this valuable comment. The journal requires an unstructured abstract. As suggested by the reviewer, we have therefore reorganized the abstract and improved the flow of reading: Abstract: Esophageal and Gastric Adenocarcinomas (AGE/S) are characterized by early metastasis and poor survival. MACC1 (Metastasis Associated in Colon Cancer 1) acts in colon cancer as a metastasis inducer, linked to reduced survival. This project illuminates the role and potential of inhibition of MACC1 in AGE/S. Using 266 of 360 TMAs and survival data of AGE/S patients we confirm the value of MACC1 as an independent negative prognostic marker in AGE/S patients. MACC1 gene expression correlated with survival and morphological characteristics. In vitro analysis of lentivirally MACC1 manipulated subclones of FLO-1 and OE33 showed enhanced migration induced by MACC1 in both cell line models, which could be inhibited by the MEK1 inhibitor selumetinib. In vivo, the efficacy of selumetinib on tumor growth and metastasis of MACC1-overexpressing FLO-1 cells xenografted intrasplenically in NOG mice was tested. Mice with high MACC1 expressing cells developed faster and larger distant metastases. Treatment with selumetinib led to a significant reduction of metastasis exclusively in the MACC1 positive xenografts.
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[10] If the journal allows it, please break up the abstract into Introduction, Methods, Results, Conclusion. If the journal requires an unstructured abstract instead, please reorganize the current abstract so that the content flows uninterrupted (e.g. "MACC1 is an independent negative prognostic marker in AGE/S patients." should be after "Expression was correlated with survival and morphological characteristics." and before "To analyze the role of MACC1 in vitro the cell lines FLO-1 and OE33 were lentivirally manipulated." and so on).
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There were no more open questions in the second review.
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The authors have satisfactorily addressed my comments.
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As suggested, we analyzed the distribution of IRS (immunoreactivity score) across the cohort. In Figure 1 it can be clearly seen that there are two groups forming here, those with 0-4 and those with 6-12 IRS. In addition, we calculated the survival probability depending on the IRS (Figure 2). Patients with an IRS of 6 or higher have a similar bad prognosis compared to patients with an IRS below 5. A better survival correlates with lower MACC1 IRS. Patients with an IRS of 0 have the best prognosis. Based on these two analyses, the decision for cut-off value of 5 was made. Additionally, ROC curve analysis showed, that the IRS value of 5 has the highest Youden Index and is therefore the most suitable cut-off value. 0.408) (Figure 3 and Table 1). Looking at MACC1 expression in cell lines and tissue samples, the variability looks similar. Nevertheless, it must be considered that the investigation of the homogeneous cell lines is a purely quantitative analysis of the expression by Western plot and RT-PCR. The analysis of the tissue samples by immunoreactivity score analyses both the strength of expression and the inhomogeneity of expression. Figure 1: Distribution of the IRS across the cohort Figure 2: Overall Survival depending on the IRS Figure 3: ROC Curve for IRS cut-off analysis (AUC 0.716 [0.656 – 0.776]) Table 1: Sensitivity, specificity and Youden Index for different IRS cut-off values.
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Based on the cell line RNA and protein data the expression level of MACC1 is highly variable rather than being present or not. Is there a similar variability present among the tissue samples? Please provide the distribution of the IRS scores of the patient cohort and explain how was IRS 5 chosen as cut off?
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We thank the reviewer for raising this point. However, to respond to this question appropriately, we currently can provide only the results from proliferation assays for one cell line model (FLO1-EV vs FLO1-MACC1) over the time period of 72 h. This assay was with no statistically significant difference in cell proliferation between FLO1-EV vs FLO1-MACC1 (see Figure 4). Figure 4: Proliferation of FLO1 EV and FLO1 MACC1 over 72 h. Analysis of in vitro proliferation assay. Unfortunately, the short revision period of 10 days limits the generation of additional data sets for proliferation in further tumor cell lines.
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The authors argue that MACC1 expression did not significantly influenced cell proliferation in the two cell line models. However, cell proliferation was analyzed only in a 24-hour long period even though most cancer cells have a doubling time around 24 hours. In order to draw a conclusion about the proliferation effect a longer (48 or 72 hours) measurement is necessary.
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We thank the reviewer for this question. The concept of MACC1 inhibition was originally developed by our group for the treatment of MACC1 positive colorectal cancers and was recently published (Kobelt et al. Oncogene 2021). In this study we transferred our experience with MACC1 inhibition by selumetinib on AGE/S. Therefore, we chose the same doses for in vitro and in vivo experiments, and which was also used by other authors (Huynh et al. Mol Cancer Therapy. 2007). Further, we knew that the selected selumetinib concentrations of 10 µM has no cytotoxic effect in vitro and showed no reduction of migration in the MACC1 negative clones (FLO1-EV and OEshMACC1). Regarding the different dosages in the context of xenografted mice treatment in vivo and the clinically used dosages, the FDA recommends multiplying the dosage by a factor of 0.08 when transferring from mouse to human (Niar et al. Journal of basic and clinical pharmacy 2016). According to this calculation, the dosage of 50 mg selumetinib /kg mouse used would equal a dosage of 4 mg/kg in humans. The clinical dose of 75mg twice daily corresponds to a dose of 2x1mg per kg assuming a patient weight of 75kg. Using the aforementioned calculation, this dose equals then 12.5 mg/kg for treatment of mice. In our study, we refer again to the work of Huynh et al. Here, in which a dosage of 12 mg/kg selumetinib showed only a low level of effectiveness. At 100 mg/kg, a very good effectiveness was seen, however combined with an increased toxicity. Thus, we used in our study the dosage of 50 mg/kg as an effective dosage with low toxicity for the mice. Overall, we are considering here a pre-clinical model. The possibility of MEK1 inhibition to inhibit MACC1-induced effects in AGE/S was examined. Further, extended in vivo studies might then reveal the ideal dosage in vivo, being thereafter translated to use in humans. The use of trametinib is an interesting suggestion and might well be adapted to its use in forthcoming studies References: Kobelt, D., Perez-Hernandez, D., Fleuter, C., Dahlmann, M., Zincke, F., Smith, J., ... & Stein, U. (2021). The newly identified MEK1 tyrosine phosphorylation target MACC1 is druggable by approved MEK1 inhibitors to restrict colorectal cancer metastasis. Oncogene, 40(34), 5286-5301. Huynh H, Soo KC, Chow PK, Tran E. Targeted inhibition of the extracellular signal-regulated kinase kinase pathway with AZD6244 (ARRY-142886) in the treatment of hepatocellular carcinoma. Mol Cancer Ther. 2007 Jan;6(1):138-46.. Nair, Anroop B.; Jacob, Shery. (2016). A simple practice guide for dose conversion between animals and human. Journal of basic and clinical pharmacy, 7. Jg., Nr. 2, S. 27.
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It would be nice to know the selumetinib sensitivity of the two used cell lines. The concentration used from selumetinib both for the cell line experiments (10 microM) and for the animal experiments (50mg/kg) are quite high. Please discuss how the applied concentrations are related to the clinicaly used dosage (75 mg administered orally twice https://clinicaltrials.gov/ct2/show/NCT02448290) and why not the more efficient MEK1 inhibitor trametinib was used for the experiments.
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We thank the reviewer for this comment. The IRS cut-off value 5 reaches a sensitivity of 76.6% and a specificity of 64.2% (Youden Index. We include the arguments into the methods section page 3: To define the cut-off value a ROC curve analysis was performed. 0.408) and was chose as cut-off value (see supplement Figure S1 and Table S1). Additionally, we added the ROC curve and the table with sensitivity, specificity and Youden Index into a supplement section as figure S1 and table S1 Figure S1: ROC Curve for IRS cut-off analysis (AUC 0.716 [0.656 – 0.776]) Positive if Greater than or Equal to Sensitivity 1- Specificity Specificity Youden Index -1 1 1 0 0 1 0,869 0,500 0,500 0,369 3 0,864 0,483 0,517 0,381 5 0,766 0,358 0,642 0,408 7 0,729 0,342 0,658 0,387 8,5 0,421 0,217 0,783 0,204 10,5 0,411 0,200 0,800 0,211 13 0 0 1 0 Table S1: Sensitivity, specificity and Youden Index for different IRS cut-off values.
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The authors´answer regarding the cut off is sufficient, please include this argument either in the methods section or as supplementary information.
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thank you for this comment: we added the proliferation analyses by MTT into the method section page 5: Additionally, proliferation for FLO-1/EV and FLO-1/MACC1 was analyzed over 72 h by MTT. 4x103 cells were plated into 96-well-plates and were allowed to accommodate for 24 h. after 48 and 72 h formazan crystals were dissolved in 150 μl of DMSO and the absorption was measured at 560 nm in the absorbance reader (Tecan infinite 200 PRO). Each cell proliferation experiment was performed in triplicates. We added the results of the MTT analyses into the results section page 11: The additional analysis of the proliferation over 72 h showed no significant differences between FLO-1/EV (100% ± 4.886) and FLO-1/MACC1 (112.3% ± 12.24; p=0.113) (see supplement Figure S3). We added the MTT plot as figure S2 into the supplement section Figure S2: Proliferation of FLO1 EV and FLO1 MACC1 over 72 h. Analysis of in vitro proliferation assay.
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The authors refer to a data "Proliferation of FLO1 EV and FLO1 MACC1 over 72 h", however I couldn´t find the figure either in the manuscript file or here in the answer.
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We apologize for the inconvenience. Figure 4 can be found on page 14 in the submitted version. We inserted Figure 4 in the revised manuscript again to solve the technical issue.
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[1] Figure 4 is missing. In the pdf I reviewed, the caption is there, but the figure is not.
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We address this question in the results part MACC1 expression: “ Due to the procedure of cutting and staining, some samples could not be used for the evaluation. Samples with insufficiently representative tumor tissue were also excluded from the evaluation. Cores with representative tumor material and evaluable staining were available in 266 of 360 samples (73.9%)…”. To avoid misunderstandings, we corrected the abstract to: 266 Samples of 360 AGE/S patients were analyzed for MACC1 expression.
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[2] Abstract says 266 patients were analyzed (line 36), while result says 360 patients were analyzed (line 249). Please fix this inconsistency.
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We thank the reviewer for this correction. This formatting issue was corrected throughout the entire manuscript.
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[3] Throughout the paper, 10^x wrongly displays as 10x (e.g. "105" instead of "10^5" in lines 152 and 170, "106" instead of "10^6" in line 217, "X2" instead of "X^2" in line 241, "108" instead of "10^8" in lines 353, 354, 365, 366, 367, 368, 370, 371).
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We thank the reviewer for this valuable hint. As suggested, we included p-values in Figure 3G and 3H. In Figure 3G there is a significant increase in migration of cells without MACC1 expression. This is based on a sufficiently large N, that renders even small differences statistically significant. Further, this increase is rather small and is outperformed by the MACC1-mediated increase in migration and the reduction in the MACC1-mediated migration by selumetinib. The data show, that selumetinib does not reduce migration of the MACC1-negative FLO1 and that MACC1 induces migration in this cell line that can be inhibited by selumetinib.
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[4] In Figures 3G and 3H, please specify p-values for untreated vs selumetinib in FLO-1/EV and OE33/shMACC1 respectively. If the difference is statistically significant, please briefly explain/speculate why.
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We thank the reviewer for this suggestion to improve the visual quality of the manuscript. The legends of 3F and I have been enlarged and the resolution of the figure has been increased.
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[5] If possible, please use a higher resolution version of Figures 3F and 3I (the legends are blurry and hard to read in the current version).
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We thank the reviewer for this discussion. The empty vector control clone was transduced and selected afterwards. During the selection procedure it is possible that a subclone was generated that expresses slightly more (or less) of any mRNA and protein. It differs from the wildtype by handling (transduction, selection etc) and somewhat by age (cell divisions). Therefore, for all comparisons the empty vector clone was used, as this clone was generated in parallel to the MACC1 clone.
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[6] In line 306/307, please explain/speculate briefly why the control clone had higher MACC1 expression than the wildtype.
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We thank the reviewer for pointing this out: Survival reports were changed in median survival and the 95% confidence interval were included. Additionally, disease-specific survival results were reported.
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[7] In line 272/273: (i) please report median survival in each group (instead of mean survival), (ii) please specify Hazard ratio with 95% confidence interval (in addition to p values), (iii) please report both overall survival result and disease-specific survival result (since you showed both in Figures).
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We thank the reviewer for pointing this out: OR with the confidence interval is now included.
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[8] In line 274, please change "OR 1.51" to "OR 1.51 [... - ...]", i.e. specify the 95% confidence interval.
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We thank the reviewer for pointing this out: all survival reports were changed in median survival and the 95% confidence interval were included.
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[9] In line 277-279: (i) please report median survival in each group (instead of mean survival), (ii) please specify Hazard ratio with 95% confidence interval (in addition to p values). Same for lines 425/426.
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Thank you for this valuable comment. The journal requires an unstructured abstract. As suggested by the reviewer, we have therefore reorganized the abstract and improved the flow of reading: Abstract: Esophageal and Gastric Adenocarcinomas (AGE/S) are characterized by early metastasis and poor survival. MACC1 (Metastasis Associated in Colon Cancer 1) acts in colon cancer as a metastasis inducer, linked to reduced survival. This project illuminates the role and potential of inhibition of MACC1 in AGE/S. Using 266 of 360 TMAs and survival data of AGE/S patients we confirm the value of MACC1 as an independent negative prognostic marker in AGE/S patients. MACC1 gene expression correlated with survival and morphological characteristics. In vitro analysis of lentivirally MACC1 manipulated subclones of FLO-1 and OE33 showed enhanced migration induced by MACC1 in both cell line models, which could be inhibited by the MEK1 inhibitor selumetinib. In vivo, the efficacy of selumetinib on tumor growth and metastasis of MACC1-overexpressing FLO-1 cells xenografted intrasplenically in NOG mice was tested. Mice with high MACC1 expressing cells developed faster and larger distant metastases. Treatment with selumetinib led to a significant reduction of metastasis exclusively in the MACC1 positive xenografts.
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[10] If the journal allows it, please break up the abstract into Introduction, Methods, Results, Conclusion. If the journal requires an unstructured abstract instead, please reorganize the current abstract so that the content flows uninterrupted (e.g. "MACC1 is an independent negative prognostic marker in AGE/S patients." should be after "Expression was correlated with survival and morphological characteristics." and before "To analyze the role of MACC1 in vitro the cell lines FLO-1 and OE33 were lentivirally manipulated." and so on).
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There were no more open questions in the second review.
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The authors have satisfactorily addressed my comments.
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We thank the reviewer for this important question and would be happy to clarify. TTFields are alternating electric fields in the range of 100 to 500 kHz, with maximal efficacy seen at a different frequency for different tumor types. Since TTFields cannot be applied at several different frequencies simultaneously, one specific frequency needs to be selected, and so the first step in examination of a new tumor type is a frequency scan. The effect of TTFields is not dichotomic, such that only one frequency is effective while the other are not at all. From the frequencies showing efficacy the purpose is to select the most effective one. It should be clarified that higher frequencies of the alternating electric fields do not mean higher energy, and hence there is no disadvantage in working with higher frequencies and no added toxicity or increased side effects for higher frequencies within the TTFields frequency range. Of note, TTFields at 200 kHz is already approved and has been applied to more than 18,000 patients with glioblastoma, with skin irritation being the main treatment related adverse event. TTFields at 150 kHz is approved for treatment of unresectable malignant pleural mesothelioma. To address these issues, we have rephrased the discussion: “It has been previously shown that maximal effectivity of TTFields occurs at a different frequency for different cancer types, owing to the specific electrical properties of the cells [15, 28]. Hence, the first step in applying TTFields to a new tumor type includes frequency scans.” and “The lower TTFields intensity required for treatment of HepG2 relative to Huh-7D12 cells for achieving the same level of efficacy suggest higher sensitivity of the former to TTFields.” Point 2: What is the ‘n’ number of the samples and experiments in each group?
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What is the rationale of using 150 kHz TTFields? TTFields at 100 kHz has also shown significant differences as cytotoxicity at p<0.01 and p<0.001 in HepG2 and Huh-7D12 cells which have around 60% and 50% of cell survival. Why did the authors use high frequency of TTFields though the cytotoxicity was also observed in lower dose (Fig 1A).
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We thank the reviewer for pointing this was not clear. As mentioned in the statistical analysis sub-section within the methods part, all in vitro experiments were repeated at least 3 times, and so depicted values are mean (N ≥ 3) ± SEM. We have now added this also to the legends of figures 1, 2, and 3. Per the in vivo study, as was mentioned in the methods (sub-section 2.8), 52 animals were included in the study. The specific numbers in each treatment group are now mentioned in the results (sub-section 3.4): “During the treatment period, average tumor volumes of control animals (n = 11) increased 5.9-fold (Figure 4b and 4c; and Figure S3 for tumor images). For animals treated with TTFields (n = 15) or sorafenib (n = 10), tumor growth was significantly lower, 3.3- and 2.3-fold, respectively. In the TTFields-sorafenib combination group (n = 16), a 1.6-fold increase in tumor volume within the treatment period was observed, a growth significantly lower than that for control or for each treatment alone.” It is also mentioned in the legend of figure 4: “Rats (n = 52) were inoculated orthotopically with rat HCC N1S1 cells, and treated with sham-vehicle (n = 11), TTFields alone (n = 15), sorafenib alone (n = 10), or TTFields + sorafenib (n = 16), according to the depicted timeline (a).” Point 3: LC3 is increased in all the groups except in control tissue, however, cell death was increased only in combined group.
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What is the ‘n’ number of the samples and experiments in each group? Also mention the ‘n’ number in all the experiments involved for invitro and invivo.
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First, we would like to emphasize that indications of autophagy were diverse and determined from increased cellular granularity, amplified lipidation of LC3 (from LC3-I to LC3-II) detected by Western blot, and elevated levels of LC3 foci observed by fluorescent staining. Nevertheless, to better explain the correlation between autophagy and apoptosis we have performed additional examinations to include more markers and additional time points. As per the reviewer’s request, these examinations were performed for the combined treatment as compared to TTFields and sorafenib alone. We thank the reviewer for this comment, as these additions add much clarity to the mechanism of action of TTFields in combination with sorafenib and provide a more coherent explanation for the in vivo results. These additions may be seen in Figure 3 and are described in results sub-section 3.4, Autophagy-apoptosis Interplay For Treatment with Concomitant TTFields and Sorafenib: “In order to investigate the mechanism of action of TTFields-sorafenib co-application, HepG2 and Huh-7D12 cells were treated for 6, 24, or 48 hours with TTFields, sorafenib (3µM), or the two modalities together, and then examined for expression levels of various proteins. For HepG2 cells, the autophagy marker beclin-1 demonstrated elevation after 6 hours of treatment, which was later replaced with diminished expression levels (Figure 3d). This type of behavior was seen in all treatment groups, but was most pronounced for TTFields-sorafenib co-application. The autophagy marker LC3 also displayed such bi-phasic characteristics, but with a somewhat slower kinetics, showing some elevation at 6 hours of treatment, but higher elevation at the 24 hours time point (Figure 3d). As in the case of beclin-1, the magnitude of the effect was higher for co-treatment of TTFields and sorafenib relative to the monotherapies. GRP78, a marker of ER stress, remained low in all treatment groups for 6 and 24 hours of treatment, but demonstrated elevated levels at the later, 48-hours time point (Figure 3e). The apoptosis marker cleaved PARP displayed increased expression in the combined group already after 24 hours, elevating even further after 48 hours of treatment. For the monotherapies, cleaved PARP increase was only evident at 48 hours of treatment, and to a lower extent than that in the co-treatment group (Figure 3f). The slower kinetics of the autophagy-apoptosis path in the Huh-7D12 cells, as seen from the elevation of LC3 after as much as 48 hours (Figure 2c and d), prevented from detecting such changes in the levels of these markers in this cell line (Figure S1).” And in the discussion part “Kinetic examination in the HepG2 cells revealed elevation in autophagy levels as early as 6 hours of TTFields or sorafenib treatment, which diminished and were replaced with ER stress and apoptosis for 48 hours of treatment. These results are in line with a previous study that focused on the effects of sorafenib on such markers in HepG2 cells [32]. The higher changes in expression levels and faster kinetics when TTFields and sorafenib were applied together rather than alone indicate higher stress levels imposed on the cells in the former case.” Figure 3.
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LC3 is increased in all the groups except in control tissue, however, cell death was increased only in combined group. How can the authors correlate autophagy with apoptosis? It is not so trustworthy that the only expression of LC3B indicate the treated condition have increased autophagy in the tumor tissue. Other important autophagy and degradation markers like Beclin1 and P62 need to be shown to reflect the regulatory mechanism of TTFields, as well as for the combined treatment with Sorafenib.
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Per the reviewer’s request we show below images of the tumors within the liver, which we have also provided now in the supporting material of the paper. As may be seen, the liver itself is much larger than the tumor, and so we did not see value in measuring total liver weight, and hence cannot provide these values. While we tried to reduce variability between the animals by excluding those that at treatment initiation had tumor volumes not within the range 30–100 mm3, there was still divergence between the animals that resulted in the standard deviation bars depicted in the figure. It is however important to mention that there was a very good correlation between tumor volume (as measured by MRI) versus tumor weight at the end of the study, as may be seen in the graph below.
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Several data have shown very high error bars in each group (especially Fig Can the author provide the tumor images which were harvested from mice?
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IHC tests the presence of a protein already expressed in the tissue, and 30 min are sufficient to allow recognition and binding of the antibody to the target protein. The secondary antibody is an HRP conjugated goat anti rabbit, that is a part of the Leica HRP-refine detection kit (Cat # DS9800). We have added the missing antibody information to section 2.10. We unfortunately do not have any tissue left to allow for performing WB analysis from the in vivo study, but we have conducted additional cell line studies and added WB analysis of cleaved PARP for the in vitro examinations and additional IHC examinations for autophagy and ER stress markers (as shown in response 3).
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In the IHC experiment for PARP, the authors have incubated with primary antibody only for 30 min? Is that timing enough to get protein expression? What source of secondary antibody was used? In addition to IHC, I suggest performing western blot using PARP antibody where the full length and cleaved bands are observed in the same blot.
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We thank the reviewer for identifying this mistake, and have corrected this, changing the label of the LC3 data to e.
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The figure number is mislabeled in Fig 4D-LC3 Immunofluorescence.
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Error bars are not missing for the control groups, rather they are null, as the values displayed in these figures are relative to control, and so per definition all control experiments have the exact same value of 100 or 1 (for percentage or fold change, respectively).
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Why there is no error bar in the control group of all bar graphs? Please include error bars and re-calculate the statistical analysis for all the data wherever missing.
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We apologize for this mistake, and have now corrected the figure legend. The quantification of immunofluorescence of LC3 foci formation is c, and immunoblotting showing LC3-II to LC3-I ratio is d. Point 9: There is no data in Fig 4A.
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Figure legends of Fig2D is missing. Fig C is repeated in the legend. Please label the figures appropriately. It is so frustrating to understand.
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We apologize for accidently omitting Fig 4A. This figure depicts the timeline of the in vivo experiment for easier understanding of the study designed. We have now corrected this.
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There is no data in Fig 4A. Whole data is missing but have explained in the result section and in figure legends.??
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We understand from the reviewer’s comments that the sentence “The higher effects seen in the presence of CQ reveal that the observed phenomenon is due to increased autophagic flux, rather than decreased autolysosome degradation” is not clear enough. We have hence rephrased the sentence to be more accurate and better deliver the message: “CQ is an inhibitor of lysosome degradation, commonly used to decipher whether the elevation of LC3 is due to upregulation of the autophagy process or reduced autophagosome turnover [30]. The higher TTFields-induced elevation of LC3 seen in the presence of CQ suggest that the observed phenomenon is due to increased autophagic flux, rather than decreased autolysosome degradation.” Point 11: Typos: Line 111, ‘invitro’ spelling is not correct.
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Line 337 seems over statement since the data are not shown in the manuscript.
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The “inovitro” in line 111 is not a typo, it is the name of the system used for applying TTFields in vitro. In line 342 we removed the duplicate “and”, and thank the reviewer for catching this typo.
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Typos: Line 111, ‘invitro’ spelling is not correct. Double ‘and’ in Line 342. Need language and grammar check.
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We thank the reviewer for the positive review.
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This is an interesting scientific study, as it concerns the issue of hepatocellular carcinoma, it also has a clinical aspect. The materials and methods section are elaborated in the details. Therefore, I expect further additional examination in the future. References contain mostly publications printed in the last 10 years. The authors indicated that TTFields had potential to be a new treatment option of hepatocellular carcinoma. The present study was examined in terms of autophagy and apoptosis in the antitumor effects of TTFields and sorafenib. However, the exact mechanism of the combination therapy induced cell death is not yet known as the activation of autophagy in the combination therapy was not increased.
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For the in vitro experiments with TTFields (sub-section 2.3) we tried not to elaborate too much and referenced previous work describing all details. We understand that we have cut off too many details, and are happy to add them “HepG2 and Huh-7D12 cell suspensions (500 µl, 25 x 103 cells/plate) were placed as a drop in the center of 35-mm inovitro™ dishes composed of high dielectric constant ceramic (lead magnesium niobate–lead titanate [PMN-PT]), with two perpendicularly pairs of transducer arrays printed on their outer walls. Cells were incubated overnight at 37 °C to allow attachment to the dish, and then 2 ml of fresh media were added.” Regarding the number of rats included in the final analysis, we apologize this information was not clear. The 52 rats mentioned in the text were in fact the actual final number of animals in the analysis, since “all rats reached the required usage limit of ≥18 h/day”, as is now explicitly stated in the results sub-section 3.4.” Point 2: What is puzzling in this investigation is showing functional data using two human cell lines and in vivo data using rat cells.
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In vitro experiments sub-section in Methods sections lacks many experimental details (e.g., type of plate/flask, plating overnight or not before experiment, number of plated cells). A very important missing is not showing the actual number of rats included in the final analyses (the ones who successfully received therapy for more than 18 hours/day). This must be added.
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cancers14122959_makarova
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We thank the reviewer for raising this important issue. Using a xerograph model is indeed a good suggestion, however it would require working in immunosuppressed mice. It is currently not feasible for us to perform studies in which we apply TTFields to immunosuppressed animals, as these animals are of smaller weight thus the burden of wearing the electrodes may induce too much stress. Furthermore, these animals are more prone to contract infections during the process of electrodes placement and replacement on the animals. On the other hand, using the rat cells for in vitro experiments in the inovitro dishes turned out to be very technically challenging, as the cells were non-adherent, and so we could not pursue this important avenue. Nevertheless, we agree with the reviewer that there is a possibility that the optimal frequency may differ in the N1S1 relative to the human cell lines. Therefore, we have addressed this issue by including results of an additional frequency scan experiments done with N1S1 cells. We now mention this in the text, results sub-section 3.4: “The efficacy of combining TTFields with sorafenib relative to each modality alone was examined in the N1S1 HCC rat orthotopic model (timeline in Figure 4a). In vitro experiments confirmed that the 150 kHz TTFields frequency found optimal for treatment of the human cell lines was also optimal for treatment of the murine N1S1 cells used for the in vivo study (Figure S2).” We provide the relevant frequency scan figure in the supplementary material. Per the good question by the reviewer regarding the p53 status of the N1S1 cells we added: “It is also worth mentioning that the N1S1 murine cells used for this study, like the HepG2 cells, are p53 wild type.” Figure S2.
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What are the p53 status and the apoptosis signaling pathway function in N1S1 cells? Maybe the cytotoxicity data will reveal a different better frequency.
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cancers14122959_makarova
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We thank the reviewer for this comment, and apologize that the illustration of the timeline was accidentally missing from the submission (we have now added it). The limiting factor for study duration was the well being of the animals. The tumors in the control group were very large, causing stress and weight loss of the animals. The arrays placed on the animals, together with the individual housing needed to prevent wire entanglement, adds even more stress and increases animal weight loss. Overall, it was non-ethical to continue the study further. We have now added this explanation to the discussion section to clarify this limitation of the study: “In the HCC animal model, the acute effects of TTFields and sorafenib were examined. Due to the large tumors developed in the control group and the stress experienced by the animals as a result of the individual housing and motility limitations imposed by the sham and TTFields arrays, longer treatment durations were not feasible.” Point 4: There is no explanation why the most effective dose was 150 kHz and higher does actually decreases the killing.
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Another puzzling experiment is the schedule for the in vivo work. Since the authors missed to add Figure 4A for timeline, based on Methods section the rats were treated for 5 days with TTFields and or sorafenib and a day later the rays were sacrificed. While a short “acute” follow-up is welcome the most important experiment should allow the follow-up for much more days to indeed observe the effect of TTFields added to sorafenib. I could not find an explanation for not including a long term follow-up. In my opinion, this is a key therapeutically experiment which must be done and included in the study.
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cancers14122959_makarova
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It is important to understand that the TTFields frequency is not the treatment dose, and hence increased frequency does not mean increased efficacy. In the case of TTFields, intensity, duration, and usage are the factors that contribute to the “treatment dose”. Nevertheless, we have added to the discussion an explanation on this issue of optimal frequency: “It has been previously shown that maximal effectivity of TTFields occurs at a different frequency for different cancer types, owing to the specific electrical properties of the cells [15, 28]. Hence, the first step in applying TTFields to a new tumor type includes frequency scans.” Regarding the option that the optimal frequency will differ between in vitro and in vivo setting, this is indeed a concern. However, as shown by the in vitro frequency scans, the effect of TTFields is not dichotomic, and effectiveness can be seen at more than one frequency. Therefore, the relatively low expected differences between animals treated with different TTFields frequencies together with the variability inherent to animal studies, makes it technically problematic to perform frequency scans in vivo. As of today, in vitro frequency scans are the common practice for determining the optimal TTFields frequency for delivery to animals and to humans. In fact, in vitro frequency scans were the basis for the clinical studies leading to FDA approval of TTFields at 200 kHz for the treatment of GBM and at 150 kHz for the treatment of MPM. We have added this issue to the discussion as a limitation of the study: “Since the optimal TTFields frequency has been shown to be dependent on the electrical properties of the cells and it is not clear how much effect the tumor microenvironment has on these properties, and because it is technically problematic to perform TTFields frequency scans in vivo, the frequency detected in the cell cultures was also employed for the animal studies.” Point 5: Why the in vitro experiment was performed for 72 hours and in in vivo for 120 hours?
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There is no explanation why the most effective dose was 150 kHz and higher does actually decreases the killing. Can this dose observed in vitro on only tumor cells be translated to in vivo work where the tumor microenvironment is total different?
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cancers14122959_makarova
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