dedup-isc-ft-v107-score
float64 0.3
1
| uid
stringlengths 32
32
| text
stringlengths 1
17.9k
| paper_id
stringlengths 8
11
| original_image_filename
stringlengths 7
69
|
|---|---|---|---|---|
0.492814 | 92190501a9d149aebea4a824039261cc | Spearman’s correlation between scores of clinical scales and spatiotemporal variabilities of local scalp regions in microstate networks.a Spearman’s correlation between scores of MoCA and temporal variability of local scalp region at electrode channel ‘F4’. b Spearman’s correlation between scores of MoCA and spatial variability of local scalp region at electrode channel ‘T7’. c Spearman’s correlation between scores of UPDRS-III and spatial variability of local scalp region at electrode channel ‘P8’. The red point indicates the region in which the temporal and spatial variability of microstate brain networks in healthy controls are obviously higher than that in early PD patients. FDR correction was performed for p-values. | PMC10086042 | 41531_2023_498_Fig5_HTML.jpg |
0.527727 | d5e7c20e23154ac2a3deb3bc3baa30f6 | Illustration of spatiotemporal variability algorithm with microstate A networks as an example.a Illustration of computational processes for temporal variability and spatial variability of specific scalp location (electrical channel i). b The schematic of temporal variability of the functional architecture. c The schematic of spatial variability of the functional architecture. The solid line width represents the strength of the functional connectivity between two regions (electrical channel’s scalp location) and the dashed line represents fairly weak functional connectivity. v indicates the number of microstate A networks. | PMC10086042 | 41531_2023_498_Fig6_HTML.jpg |
0.421283 | a7aae33719784973aef52285ad951a6a | Functional connectivity network construction based on EEG microstate analysis.a EEG microstate analysis is used to form the microstate sequence corresponding to EEG sequence. b The microstate windows are used to construct functional connectivity networks based on microstate sequences. c The functional connectivity networks based on microstate classes. GFP global field power, SVM support vector machine, PLI phase lag index. | PMC10086042 | 41531_2023_498_Fig7_HTML.jpg |
0.424524 | dc99e4d8ce8a49a792e289eb6d3af120 | Features calculated by different methods are taken in a common SVM classifier for disease classification. | PMC10086042 | 41531_2023_498_Fig8_HTML.jpg |
0.441718 | 6c8f905d6d534f85b9fd52a951cbf03b | Flowchart of the data selection in terms of Sarcoptes scabiei infestation in Iran, during 2000–2022 | PMC10086448 | JAD-16-180-g001.jpg |
0.426394 | f0dc8cb49fb44485816455f18f488bbd | Human cases of scabies reported in different provinces of Iran; Further to investigations conducted during 2000–2022, scabies has been reported in humans in at least 21 provinces | PMC10086448 | JAD-16-180-g002.jpg |
0.392975 | 35e02a35479f4d479062a0ec8337dc8e | Forest plot of the prevalence of Sarcoptes scabiei infestation in Iran during 2000–2022; Total prevalence of mite infestation in Iran during 2000–2022 was 7% (95% CI 4.7%–10.3%, P< 0.001) | PMC10086448 | JAD-16-180-g003.jpg |
0.436172 | 98190cb34dc04a70b6f638006b33448b | Funnel plot of standard error by logit event rate for Sarcoptes scabiei infestation in Iran during 2000–2022; Most of the studies are distributed at the top of the graph in a balanced way, which indicates a negligible publication bias | PMC10086448 | JAD-16-180-g004.jpg |
0.475596 | 4c2af82b5c944ae8925be2785b5b271c | Meta-regression chart showing the logic event rate of Sarcoptes scabiei infestation in Iran according to sample size during 2000–2022; A significant heterogeneity was associated with sample size (the number of mites) | PMC10086448 | JAD-16-180-g005.jpg |
0.388192 | 1910107c6cfa439b93d1e47978e10b59 | CONSORT chart of patient selection. CONSORT, Consolidated Standards of Reporting Trials; DMT, disease-modifying therapy; EDSS, Expanded Disability Status Scale; EQ-5D, EuroQol-5 Dimensions; MSIS, Multiple Sclerosis Impact Scale. | PMC10086460 | jnnp-2022-330169f01.jpg |
0.430076 | ff0e105fdeda4e858ec24b1c52cf0507 | Fig. 6C legend(C) Normal and ERα-positive tumor tissues were subjected to immunohistochemical analysis. The large boxes (scale bar = 500 µm) show the magnified view of the small boxes (scale bar = 100 µm). | PMC10086552 | molce-46-4-256-f6.jpg |
0.412848 | f5f3cd54b5ea4d5da075e7fe08c0badb | Analysis of seminal PSA via orthogonal approaches; (A)
intact protein,
(B) middle-up, and (C) bottom-up. (A1) Electrophoretic profile of
seminal PSA with XIE peaks 1–7. Only proteoforms with the most
abundant glycoform H5N4F1S2 are shown. Asterisk (*) denotes XIEs from
overlapping m/z that are present
in the charge envelopes of several different proteoforms. The table
in (A2) shows the underlying proteoforms including the peak number
(#), intact mass (Da), number of cleavages (#C), cleavage site (C),
amino acid loss (-AA), and masses (Fragments) that support the assignment
from the middle- and bottom-up approaches. PSA fragments found during
middle-up analysis are shown in (B1–B6) whereby the first and
last residue of the fragment as well as the glycoform are represented
above the deconvoluted spectra. The average mass is illustrated except
when isotopic resolution is achieved, in which case the mass of the
most abundant isotope is demonstrated. In B4, two fragments are shown,
I25–N108, containing H5N4F1S2 (11759.1
Da) as illustrated by the double asterisk (**), and F110–P261 (16542.0 Da). Two PSA tryptic peptides that
were found as a result of prior internal cleavage of the protein at
and loss of R77 are shown (C1 and C2). | PMC10088042 | pr2c00762_0001.jpg |
0.49082 | f30f2103ed1546c28ad2b832d8bf0656 | Linear regression plot of relative abundances
for common proteoforms
quantified by deconvolution and XIE methods. (A) Intra- and interday
(n = 9) data set. There are 26 common proteoforms
detected by both processing methods. (B) Patient (n = 8) data set. There are 19 common proteoforms detected by both
processing methods. Relative abundances determined by XIE quantification
is represented on the y-axis and relative abundances
determined via deconvoluted quantification is shown on the x-axis. The equation of the trendline and R2 are displayed. | PMC10088042 | pr2c00762_0002.jpg |
0.429065 | 1933fc8b9dec45338a07ab1544309e9e | Overview of the Cleaved Proteoforms
Found in Seminal and Urinary
PSANoncleaved, active
PSA undergoes
internal cleavage which inactivates the protein. Cleaved PSA proteoforms
arise at one (single cleavage) or two (double cleavage) of four cleavage
sites, as well as further truncated variants. Notably, PSA contains
five disulfide bonds in total whereas the red dotted lines are shown
here to represent how the overall structure of the protein is kept
intact following cleavage via the disulfide bonds. Ten cleaved proteoforms
are observed in total across seminal and urinary PSA, in addition
to the glycoforms for each proteoform (Supporting Information Tables S6 and S7). Only the most abundant glycoform,
H5N4F1S2, is illustrated here. The legend may be found in the blue
box. | PMC10088042 | pr2c00762_0003.jpg |
0.389809 | e883133adaea4777948631e96fb3282d | A basic positioning of Rapid Insight within the evaluation landscape. | PMC10088506 | fsoc-08-993342-g0001.jpg |
0.459101 | 9e5a116de9034e09ab05a4fceddf5b0c | Example of mind map. Extracted and modified from RI Report: NHS England—South west region rapid insight and learning from the COVID-19 mass vaccination programme—NHS England—South west region rapid insight and learning from the COVID-19 mass vaccination programme, Wessex AHSN, April 2021. | PMC10088506 | fsoc-08-993342-g0002.jpg |
0.441098 | 01febd4f1e3b4ce1b234d701db607496 | Analysis of specificity with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig10_HTML.jpg |
0.44908 | edb8906390e847ebb1f08305716b7dcd | Analysis of precision with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig11_HTML.jpg |
0.440773 | b8b41cb07a14446ea677642617263a34 | Analysis of f1-score with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig12_HTML.jpg |
0.452473 | da62be0130334b82a80fae544fe2ccc4 | Analysis of MCC with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig13_HTML.jpg |
0.415935 | 3d296e8452d24c45bbc7d07e8cee0b97 | Analysis of AUC with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig14_HTML.jpg |
0.442813 | 32a009f99cac477395e1ac956635f3fa | Comparison of ROC with proposed EDHA and existing techniques. a CXR dataset. b CT dataset | PMC10088783 | 530_2023_1072_Fig15_HTML.jpg |
0.509045 | 1eeb0de15e3741e68b0bfad1329814c9 | Training and testing accuracy for proposed EDHA | PMC10088783 | 530_2023_1072_Fig16_HTML.jpg |
0.471009 | ad9b7f324ee04e53bd6a62ed6ea9b521 | Training and testing loss for proposed EDHA | PMC10088783 | 530_2023_1072_Fig17_HTML.jpg |
0.42628 | 55ee0941061e42bc9dd5ae9cc12a2d28 | Learning rate analysis. a CXR dataset. b CT dataset | PMC10088783 | 530_2023_1072_Fig18_HTML.jpg |
0.440447 | 2999da91eee443129e5e91fc41eb953e | Analysis of computation time with proposed EDHA and existing techniques | PMC10088783 | 530_2023_1072_Fig19_HTML.jpg |
0.516282 | af230f1f9cd34681ab5894b214e1d16d | DenseNet201 | PMC10088783 | 530_2023_1072_Fig1_HTML.jpg |
0.44396 | 2f29d0e2c50e4e739b6670cf9a7b520f | Simulated results of proposed EDHA for COVID-19 prediction | PMC10088783 | 530_2023_1072_Fig20_HTML.jpg |
0.495432 | 45b25a29c2044f3c8d9cbbf4828b4efa | Analysis based on various datasets | PMC10088783 | 530_2023_1072_Fig21_HTML.jpg |
0.385748 | 92c50606a10942d1bdda80bf0d27e5ed | Block diagram of ShuffleNet Units. (i) Bottleneck unit with depth-wise convolution (DWConv). (ii) ShuffleNet unit with channel shuffle and point-wise group convolution (GConv). (iii) ShuffleNet unit with stride = 2 | PMC10088783 | 530_2023_1072_Fig2_HTML.jpg |
0.458218 | 85fa716673ff41979a1696448d78a5b5 | SqueezeNet Model | PMC10088783 | 530_2023_1072_Fig3_HTML.jpg |
0.435316 | f954befecca148478dcb5070e4cb6083 | Block diagram of the proposed EDHA | PMC10088783 | 530_2023_1072_Fig4_HTML.jpg |
0.42907 | 7e70c63d3c7e444e854ce3cbfb046b44 | CXR images. a COVID-19 positive subjects. b COVID-19 negative subjects | PMC10088783 | 530_2023_1072_Fig5_HTML.jpg |
0.453173 | e68c1aa40e6b40cba2b58502783877a2 | CT images. a COVID-19 positive subjects. b COVID-19 negative subjects | PMC10088783 | 530_2023_1072_Fig6_HTML.jpg |
0.436397 | 50de1085a7094e15b333cfeae808a91e | Confusion Matrix of proposed EDHA for COVID-19 prediction. a CXR dataset. b CT dataset | PMC10088783 | 530_2023_1072_Fig7_HTML.jpg |
0.412651 | e280e5bdbd0148fd93d5d264b7495a41 | Analysis of accuracy with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig8_HTML.jpg |
0.429597 | 564b8aa2d5e440e594f6009a8d113f25 | Analysis of sensitivity with proposed EDHA and existing techniques (color figure online) | PMC10088783 | 530_2023_1072_Fig9_HTML.jpg |
0.448949 | 722580ca10d14e6ea5dc6af88c22e2be | Image of leaf disc locations. | PMC10089318 | pone.0277725.g001.jpg |
0.390689 | 43802423c61f44a3a182dc495f95b48e | Heatmap representation of Ct values from duplicate RT-qPCR assays of each disc for a specific leaf. | PMC10089318 | pone.0277725.g002.jpg |
0.441784 | 668912e711a84611a1a74007fcae36ec | Relationship between number of leaves in a mixed batch of leaves and increase in Ct where batches comprise a single ASBVd-infected leaf pooled with healthy avocado leaves. | PMC10089318 | pone.0277725.g003.jpg |
0.395291 | 57b9c9c546bb48b1a984f5e07b5db03d | Local overall emergency department (ED) patient attendance and patients with chest pain attendance during the initial pandemic period in 2020, compared with the same period in 2019. | PMC10089617 | gr1_lrg.jpg |
0.42646 | ad161b1bf3f14931b33bc0ee165dfebd | Typicality of chest pain as per National Institute for Health and Care Excellence CG9516 | PMC10089617 | gr2_lrg.jpg |
0.527094 | e309ad221eb64da1b5b7a8ea0f683f86 | Macroscopic photographs of a type 1 big bubble (BB) in canine cornea after pneumodissection (corneal endothelium facing up). (A) A large central type 1 BB is present. White arrows point to the bubbles of air escaping from the periphery along the pigmented tissue. These bubbles are likely to enter the anterior chamber during big bubble deep anterior lamellar keratoplasty. (B) The Descemet’s membrane (DM) is being peeled off the BB revealing the posterior surface of the canine pre-Descemet’s layer (cPDL) (star). (C) On further peeling the DM tears as a broad strip, revealing more of the cPDL (star). (D) A broad central strip of the DM is peeled off. The edge of the remaining DM is clearly seen (black arrows). The DM was stained with vision blue dye (B–D). | PMC10090133 | 41598_2022_24438_Fig1_HTML.jpg |
0.468267 | e992f8c7e652412ea3b3ffa184a9123c | Anterior segment optical coherence tomography (AS-OCT) (Topcon Europe medical BV, Netherland) of the canine corneas after intrastromal air injection. (A) Anterior scan from the epithelial surface. The epithelium is demarcated from the underlying hyper-reflective aerated stroma. (B) Air has entered the epithelium creating and air vesicle. (C) Scan performed from the posterior surface of the cornea after creating a type 1 big bubble (BB). The posterior wall of the type 1 BB made of the canine pre-Descemet’s layer (cPDL) and Descemet’s membrane (DM). The AS-OCT scan does not distinguish between the two layers. (D) Similar scan as in ‘C’ of a type 1 BB. On the right side, the DM was peeled off over a section of the bubble and replaced prior to the scan. The anterior DM and posterior cPDL are clearly visible but are indistinguishable in the left two thirds of the scan where the DM and cPDL are closely apposed. | PMC10090133 | 41598_2022_24438_Fig2_HTML.jpg |
0.424872 | 33b03bb18a904068bd5912e6fa7cbe8f | Histology of the canine cornea after air injection. (A) The anterior stroma and epithelium are illustrated. Air bubbles, larger posteriorly and smaller anteriorly are seen to fill the stroma. The air bubbles extend very close to the posterior surface of the epithelium. (B) The posterior stroma shows larger intrastromal bubbles. Arrows point to thin strands of collagen that extend between posterior stroma and the separating canine pre-Descemet’s layer (cPDL). (C) The separated cPDL (light blue) and the overlying Descemet’s membrane (DM) are illustrated. The cPDL shows horizontally aligned darker staining linear section of keratocytes. (D) The ‘rough’ appearing surface of the wall of a type 1 big bubble (BB) is illustrated. This appearance is related to the broken strands of collagen illustrated in ‘B’ above, that lie on the anterior surface of the cPDL within the BB. The histology sections are stained with toluidine blue (A–C). | PMC10090133 | 41598_2022_24438_Fig3_HTML.jpg |
0.411768 | 2672e6a1178842f4bcc569b0e53cdd4d | Histology of the canine pre-Descemet’s layer (cPDL). (A) Toluidine blue stained section of the cPDL and the Descemet’s membrane (DM). The DM is attached to part of the section of the cPDL. (Bar = 200 microns with 50-micron sections). (B) Transmission electron microscopy (TEM) of the wall of the type 1 big bubble (BB). The cPDL, DM and endothelial cells (EC) are illustrated. (Bar = 50 micros with 10-micron sections). (C) TEM of the cPDL anterior to the DM. A keratocyte is seen (white arrow). The compactly arranged horizontal and vertical lamellae are seen. Some oblique fibres are also visible (up and left) (Bar = 10 microns). (D) TEM of another section of cPDL, anterior to DM, showing keratocytes (white arrows) (Bar = 10 microns). | PMC10090133 | 41598_2022_24438_Fig4_HTML.jpg |
0.440862 | 2d95d566a76d4dcca122ccdeb81433d5 | Histology of the interfacial matrix between the Descemet’s membrane (DM) and the canine pre-Descemet’s layer (cPDL). (A) Transmission electron microscopy (TEM) of the DM and the cPDL. The compacted alternating layers of the varying thickness of the cPDL are visible. (EC = endothelial cells. DM–NBZ = non-banded zone of the DM. DM–BZ = banded zone of the DM). The boxed area with the interfacial matrix is illustrated in high magnification in ‘B’. (Bar = 10 microns). (B) The interface between the DM and the cPDL is demonstrated. Fine fibrils are seen extending between the anterior surface of the PDL and the posterior surface of the banded zone of the DM (DM–BZ). Such fibrils are visible through most of the interfacial matrix (IFM) (Bar = 1 micron). | PMC10090133 | 41598_2022_24438_Fig5_HTML.jpg |
0.466719 | fbca3af985be40f58695bb80aa5ae45d | The plasma levels of amino acids in CKD patients. Levels of D- (a) and L-amino acids (b) in plasma from CKD patients and healthy control were analyzed with 2D HPLC. c Also, the percentage of D-amino acid were shown. Data are shown as means ± SEM. Statistical analysis was performed using Student's t test. *p < 0.05, **p < 0.01, ***p < 0.001. | PMC10090982 | kdd-0009-0118-g01.jpg |
0.442423 | 092c5c658da642928d791a5bd8559efa | The evaluation of intra-brain levels of D-/L-Ser, -Ala, -Asn, and -Pro. Intra-brain levels of D-Ser, -Ala, -Asn, and -Pro (a) and L-Ser, -Ala, -Asn, and -Pro (b) were evaluated. c Also the percentage of D-Ser, -Ala, -Asn, and -Pro are shown. Statistical analysis was performed using Student's t test. *p < 0.05, **p < 0.01, ***p < 0.001. | PMC10090982 | kdd-0009-0118-g02.jpg |
0.442686 | e85aa2b09b7d4ebfbb102524f9b842fb | The correlation between intra-brain levels of L-Ser and kidney function. a The association between intra-brain L-AAs levels and kidney functions were evaluated. Intra-brain levels of L-Ser were correlated with kidney function. b Also, the association of intra-brain D-AAs levels and kidney functions were evaluated. Intra-brain levels of D-Asn were correlated with kidney function. | PMC10090982 | kdd-0009-0118-g03.jpg |
0.420076 | 7aede4dfc0a04a6899380808cf15560f | The correlation between levels of intra-brain L-Ser and JART score in patients with lower kidney function. a The patients both with the eGFR of lesser than 90 mL/min/1.73 m2 and intra-brain L-Ser of lower than 600 nmol/g tended to show the lower JART score than those with the eGFR of higher than 90 mL/min/1.73 m2 or intra-brain L-Ser of more than 600 nmol/g. b Also, JART score was associated with kidney function, indicated by serum creatinine and eGFR in patients with eGFR of lesser than 90 mL/min/1.73 m2. c JART score is positively correlates with intra-brain levels of L-Ser. No correlation was detected between JART score and intra-brain levels of D-Ser. | PMC10090982 | kdd-0009-0118-g04.jpg |
0.412032 | 44bb44fe915b449991e75bcf93685d97 | Intra-brain expressions of DAO and SRR. a DAO and SRR are detected on astrocyte and neuron in brain, respectively. Representative images of tissue samples stained with HE, DAO, and SRR are shown. Scale bar, 100 μm. Arrowheads indicate DAO positive astrocyte. Arrows indicate SRR positive neuron. b The frequency of DAO positive cells is not correlated with kidney function. Also, the frequency of SRR positive cells is not correlated with kidney function. | PMC10090982 | kdd-0009-0118-g05.jpg |
0.447437 | 701e3237abe74aec928f46cbecc8f4f5 | The plasma levels of D-/L-Ser, Ala, Asn, and Pro in hemodialyzed patients with/without dementia. The comparison of plasma levels of D-/L-Ser, Ala, Asn, and Pro in hemodialyzed patients with/without dementia. The plasma levels of L-Ser were also lower in the hemodialyzed patients with cognitive decline as compared to those with non-cognitive impairment both in patients with/without DKD. AAs were analyzed with 2D HPLC. A score of less than 20 for HDS-R wad defined as dementia. Statistical analysis was performed using Student's t test. *p < 0.05, **p < 0.01. | PMC10090982 | kdd-0009-0118-g06.jpg |
0.406455 | 1a812873f2c84a6d9381e1a5fe072658 | Flow diagram for study retrieval and identification for network meta- analysis as per the PRISMA 2020 statements | PMC10090989 | CEH-9-50402-g001.jpg |
0.489623 | d22161de7ae84d89935e5e58099f6a25 | Network plots for number of A) patients with gastric variceal obliteration, B) patients with overall rebleeding, C) patients with moderate-severe adverse events (AEs), D) patients with all-cause mortality | PMC10090989 | CEH-9-50402-g002.jpg |
0.43311 | 0146e185bc3c4c14ab9015b7ffca8324 | The surface under the cumulative ranking curve (SUCRA) plot for A) patients with gastric variceal obliteration, B) patients with overall rebleeding C) patients with moderate–severe adverse events (AEs), D) patients with all-cause mortality | PMC10090989 | CEH-9-50402-g003a.jpg |
0.479102 | 6071b38fd6d44235b42579295a0dbdcf | Differences in CAFs induce differences in PC cell proliferation. (A) Graphical representation of the fluorescence intensity of PC cells co-cultured with each CAF sample. Values represent the mean ± SD from three independent experiments. (B) Tabular representation of the same data. Fluorescence Intensity Ratio (#X)=Fluorescence Intensity (#X)/Fluorescence Intensity (#1). *P<0.005 and **P<0.001. CAF, cancer-associated fibroblasts; PC, pancreatic cancer. | PMC10091076 | or-49-05-08535-g00.jpg |
0.417484 | 15802af6b0274ac5a369ddfb1970f65f | Correlation between FIR in co-culture assays and clinical data before treatment. Graph shows the FIR on the horizontal axis, and clinical data on the vertical axis. (A) Data regarding tumor size, serum CA19-9 level, and SUV max of fluorodeoxyglucose-positron emission tomography. (B) Data regarding tumor size ratio. (C) Data regarding age of patients. The square of the correlation coefficient and the P-value are shown. *N=6 (excluding the two Lewis antigen-negative patients). #N=6 (only for patients who received preoperative chemotherapy). Each symbol legend appears at the right below. FIR, fluorescence intensity ratio; CA19-9, carbohydrate antigen. | PMC10091076 | or-49-05-08535-g01.jpg |
0.43235 | 370552664b78484d97f101238fa0f23b | Expression of cellular senescence- and senescence-associated secretory phenotype-related genes in CAFs is related to PC cell proliferation. (A) Top 30 genes expressed by CAFs, for which the RNA level (fold-change) strongly correlates with the FIR in co-culture assays. (B) Graphical representation of the correlation between the RNA level (fold-change) of each gene and FIR. The P-value is shown on the vertical axis, and the absolute value of the correlation coefficient on the horizontal axis. Red plot: positive correlation; Blue plot: negative correlation. (C) Pathway analysis for the top 30 genes using the KEGG and Reactome databases. Text on the left indicates the enriched pathway. The ball size indicates the number of the genes enriched, and the color indicates the level of enrichment. CAF, cancer-associated fibroblasts; PC, pancreatic cancer; FIR, fluorescence intensity ratio; KEGG, Kyoto Encyclopedia of Genes and Genomes. | PMC10091076 | or-49-05-08535-g02.jpg |
0.512984 | 345b810327754197a9c7faed21cb05f1 | Correlation between FIR in co-culture assays and RNA level of cellular senescence- and SASP-related genes. (A) Data regarding four genes associated with the p53/p21 and p16/RB pathways. (B) Data regarding seven genes associated with SASP. Graph shows FIR on the horizontal axis, and RNA level (fold-change) of each gene on the vertical axis. The square of the correlation coefficient and the P-value are shown. Each symbol legend appears at the right below. FIR, fluorescence intensity ratio; SASP, senescence-associated secretory phenotype. | PMC10091076 | or-49-05-08535-g03.jpg |
0.443128 | 0a8efcda6da84370b5575d0cdee7af62 | Correlation between TSR and RNA level of cellular senescence- and SASP-related genes. (A) Data regarding four genes associated with the p53/p21 and p16/RB pathways. (B) Data regarding seven genes associated with SASP. Graph shows RNA level (fold-change) of each gene on the horizontal axis, and TSR on the vertical axis. The square of the correlation coefficient and the P-value are shown. Data were obtained for the six patients who received preoperative chemotherapy. Each the symbol legend appears at the right below. TSR, tumor size ratio; SASP, senescence-associated secretory phenotype. | PMC10091076 | or-49-05-08535-g04.jpg |
0.445112 | d7dfe147285040ef8fc6bd49a4a6ef3a | Treatment of CAFs with PFT-alpha reduces PC cell proliferation and the IL-6 concentration in the co-culture supernatant. (A) Fluorescence intensity of PC cell lines when co-cultured with DMSO-treated CAFs or PFT-alpha-treated CAFs. (B) IL-6 concentration (pg/ml) in the co-culture supernatant following co-culture with DMSO-treated CAFs or PFT-alpha-treated CAFs. The graphs show data for 3 cases, #2, #7 and #8, respectively. *P<0.05 and **P<0.01. CAF, cancer-associated fibroblast; PFT-alpha, pifithrin-alpha; PC, pancreatic cancer. | PMC10091076 | or-49-05-08535-g05.jpg |
0.43 | fd4f749b1a9948258e36377e1b37fb34 | Flowchart of study information. | PMC10091905 | fendo-14-1111430-g001.jpg |
0.427746 | 9f987810f5a04e4485f532772751cdad | Methodological quality (A) and risk of bias (B) for trials included in systematic review. | PMC10091905 | fendo-14-1111430-g002.jpg |
0.450726 | 518f35fd27b745f1a03b7e607dea662a | Changes in histology with pioglitazone: (A) fibrosis, (B) hepatocellular ballooning, (C) lobular inflammation, and (D) steatosis. | PMC10091905 | fendo-14-1111430-g003.jpg |
0.467742 | ae1bf8c586f5451a936e72b40bda60d9 | Changes in metabolism with pioglitazone: (A) HDL, (B) LDL, (C) total cholesterol, and (D) triglycerides. | PMC10091905 | fendo-14-1111430-g004.jpg |
0.433399 | 1b2a1f86d1e14b9f90113d565e102c37 | CmC3H1 directly activates CmMAF2 expression in response to low temperatures. (a,b) Expression of CmC3H1 was analyzed by qRT‐PCR in leaves (a) and shoot tips (b). (c) Interaction between CmC3H1 and different regions in the CmMAF2 promoter, as shown by a yeast one‐hybrid assay. All interactions were examined on SD/−Leu medium supplemented with 100 mg μl−1 AbA. (d) ChIP analysis of the indicated fragments (P1–P7) in the CmMAF2 promoter. The chromatin of pSuper::CmC3H1‐GFP chrysanthemum plants was immunoprecipitated with an anti‐GFP antibody and pSuper::GFP chrysanthemum plants served as a negative control. The amount of the indicated DNA fragment was determined by qRT‐PCR and normalized to the pSuper::GFP control (set to 1 for each fragment). (e,f) Interaction between CmC3H1 and the CmMAF2 promoter, as shown using a dual‐luciferase reporter assay in Nicotiana benthamiana leaves. A 774‐bp CmMAF2 promoter sequence was used. Representative photographs of firefly luciferase fluorescence signals are shown in (e) and the relative LUC/REN ratio is shown in (f). (g) Transcript abundance of CmC3H1 in transiently CmC3H1‐silenced chrysanthemum plants. (h) Representative photographs of WT plants infected with CaLCuV or CaLCuV‐amiR‐CmC3H1 after 14 weeks of flower blooming under LD conditions. (i) Days to initial flower bud emergence were recorded (n > 5). (j) Expression of CmMAF2 and CmGA20ox1 in transiently CmC3H1‐silenced chrysanthemum plants. Error bars indicate standard deviation. Asterisks indicate significant differences according to a Student's t‐test (**P < 0.01). Red scale bars, 1 cm; white scale bars, 5 cm. | PMC10092002 | TPJ-112-1159-g001.jpg |
0.500649 | d76bc44cce144fd3a40cd4049d00f25d | CmMAF2 represses the expression of CmGA20ox1 by binding to its promoter. (a) Schematic representation of three CArG‐box sequences and their positions in the 600‐bp sequence immediately upstream from the CmGA20ox1 transcription start site (TSS). (b) Interaction between CmMAF2 and the three CArG‐boxes in the CmGA20ox1 promoter, shown by a Y1H assay. The p53‐AbAi bait vector and the p53 fragment prey vector were used as positive controls. All interactions were examined on SD/−Leu medium supplemented with 100 mg μl−1 AbA. (c) CmMAF2 affects the transcriptional activity of CmGA20ox1, as shown using a dual‐luciferase reporter assay in Nicotiana benthamiana leaves. A 680‐bp CmGA20ox1 promoter sequence was used. mPro‐GA20ox is the same promoter fragment with the three CArG cis‐elements mutated. LUC indicates the pGreenII 0800‐LUC empty vector containing the REN gene under the control of the 35S promoter. SK indicates the empty pGreenII 0029 62‐SK vector. Samples were infiltrated into N. benthamiana leaves, and LUC and REN activities were assayed 3 days after infiltration. Three independent experiments were performed, and error bars indicate standard deviation. (d) The interaction of CmMAF2 and biotin‐labeled CArG cis‐elements as shown by EMSA. The oligonucleotide sequences of three CArG‐boxes from the CmGA20ox1 promoter were used as probes. The core sequences are underlined. The purified protein (2 μg) was incubated with 40 nmol of labeled WT or mutated probes. Non‐labeled probes at various concentrations (10–100‐fold) were added for the competition test. (e) Transcript abundance of CmGA20ox1 in WT and CmMAF2‐RNAi plants infected with CaLCuV or CaLCuV‐amiR‐CmGA20ox1. (f,h) Representative photographs of WT and CmMAF2‐RNAi plants infected with CaLCuV or CaLCuV‐amiR‐CmGA20ox1 after 15 weeks of growth (f) and at flower blooming (h) under LD conditions. (g,i) Plant heights (g) and days to initial flower bud emergence (i) were recorded (n > 5). Error bars indicate standard deviation. Asterisks indicate significant differences according to a Student's t‐test (*P < 0.05, **P < 0.01). Different letters indicate significant differences according to Duncan's multiple range test (P < 0.05). Red scale bars, 1 cm; white scale bars, 5 cm. | PMC10092002 | TPJ-112-1159-g002.jpg |
0.466443 | c38faae824bd45ad8fa9c1b9fdf09605 | The effects of GAs on flowering in CmMAF2‐RNAi and WT chrysanthemum plants. (a) GA contents in 10‐week‐old WT and CmMAF2‐RNAi plants grown under LD conditions. (b) Phenotypes of CmMAF2‐RNAi lines treated with the GA biosynthesis inhibitor PAC under LD conditions after 6 weeks and of WT plants treated with the GA biosynthesis inhibitor PAC under LD conditions after 15 weeks. Scale bars, 5 cm. (c) The effect of PAC treatment on the height of 5‐week‐old RNAi and WT plants. (d) Effects of PAC treatment on the time until initial flower bud emergence in RNAi and WT plants. R24, R31, and R24 correspond to three independent CmMAF2‐RNAi lines. Mock treatment with 10% ethanol solution was used as a control. (e,f) Expression analyses of genes related to GA biosynthesis under LD (e) and SD (f) conditions, as determined by qRT‐PCR. UBIQUITIN was used as an internal control. The results are the means of three biological replicates with standard deviations. (g) In situ hybridization analysis of CmGA20ox1 expression in the apical meristems of WT and CmMAF2‐RNAi plants grown under LD conditions. The negative control SP6 was hybridized with the sense probe. Scale bars, 200 μm. The results are the means of three biological replicates with standard deviations. Asterisks indicate statistically significant differences (Student's t‐test, **P < 0.01). | PMC10092002 | TPJ-112-1159-g003.jpg |
0.451464 | 8e0ae25b2d4e46faa1f90ed486fa3edf |
CmMAF2, CmGA20ox1, and CmLFY expression in response to low temperature (LT). (a,b) Expression of CmMAF2 was analyzed by qRT‐PCR in leaves (a) and shoot tips (b). (c,d) Expression of CmGA20ox1 was analyzed by qRT‐PCR in leaves (c) and shoot tips (d). (e) In situ hybridization of CmGA20ox1 in chrysanthemum apical meristems at LT5 and at LT5 + N1. Plants grown under normal temperature for 5 and 6 weeks (C5 and C6) were used as controls. Scale bars, 200 μm. (f) CmLFY expression was analyzed by qRT‐PCR in shoot tips. UBIQUITIN was used as the reference gene. The results are the means of three biological replicates with standard deviations. LT1–5, 1–5 weeks of low‐temperature treatment. LT5 + N1, LT5 + N2, and LT5 + N5 indicate 1 week, 2 weeks, and 5 weeks of normal temperature after a 5‐week low‐temperature treatment, respectively. | PMC10092002 | TPJ-112-1159-g004.jpg |
0.426435 | e92f0454c2a141939f26a74162541dcc |
CmMAF2‐RNAi plant flowering. (a,b) Expression of CmMAF2 (a) and MADS‐box family homologs (b) in WT and CmMAF2‐RNAi plants as determined by qRT‐PCR. UBIQUITIN was used as the internal control. (c,h) Plant heights of 4‐week‐old (c) and 12‐week‐old (h) WT and CmMAF2‐RNAi plants grown under LD and SD conditions. (d,i) The number of stem nodes was recorded after 9 weeks of LD (d) and 18 weeks of SD (i) conditions. (e,j) Representative photographs of WT and CmMAF2‐RNAi plants at flower bud emergence after 9 weeks of LD (e) and 18 weeks of SD (j) conditions. (f,k) Flower blooming in WT and CmMAF2‐RNAi plants after 15 weeks of LD (f) and 20 weeks of SD (k) conditions. (g,l) Days until initial flower bud emergence in WT and CmMAF2‐RNAi plants grown under LD (g) and SD (l) conditions. (m) Phenotypes of WT and CmMAF2‐RNAi plants treated for 5 weeks with low temperature at week 16 after transplanting. (n) Plant heights of WT and CmMAF2‐RNAi plants treated for 5 weeks with low temperature under LD conditions. (o) Days until initial flower bud emergence in WT and CmMAF2‐RNAi plants treated for 5 weeks with low temperature under LD conditions. R24, R31, and R24 correspond to three independent CmMAF2‐RNAi lines. The results are the means of three biological replicates with standard deviations. Asterisks indicate statistically significant differences (Student's t‐test, *P < 0.05, **P < 0.01). Scale bars, 5 cm. | PMC10092002 | TPJ-112-1159-g005.jpg |
0.461245 | e951c679fcfa486ea8e8862c54075612 | Chrysanthemum flowering in response to low temperature. (a) Plants were grown for 5 weeks at low temperature (LT1–5) and then returned to normal temperature for recovery (LT5 + N1–N5). Control plants (C1–10) were grown under normal temperature and LD conditions. The phenotypes were observed daily. Scale bars, 5 cm. (b) Plant heights after 5 weeks of growth at low temperature (LT1–5) and 1–5 weeks after returning to normal temperature (LT5 + N1–N5). (c) Scanning electron microscopy images of apex development in plants grown at low temperatures for 5 weeks or at normal temperatures under LD conditions. C5–10, 5–10‐week control; LT5, 5‐week low‐temperature treatment; LT5 + N1–5, 1–5 weeks after returning to normal temperature; LF, leaf primordium; IN, involucre; BL, bract leaf primordium. Scale bars, 200 μm. (d) Scanning electron microscopy images of inflorescence and flower bud morphology in plants treated for 5 weeks with low temperature (LT + LD) or without low temperature (LD) after 11 weeks and 14 weeks under LD conditions. Scale bars, 5 cm. (e) Blooming phenotype in plants treated for 5 weeks with low temperature (LT5) or without low temperature (LD) after 18 weeks under LD conditions. Scale bars, 5 cm. (f) Days until initial flower bud emergence in plants treated for 5 weeks with low temperature or without low temperature. (g) The phenotype of plants treated for 5 weeks with low temperature (LT + natural environment [NE]) or without low temperature (NE) after 9 weeks and 13 weeks in the field and photographed on 6 June and 30 June, respectively (Beijing, China). Scale bars, 5 cm. (h) Days until initial flower bud emergence in plants treated for 5 weeks with low temperature (LT + NE) or without low temperature (NE). The results are the means of five biological replicates with standard deviations. Asterisks indicate statistically significant differences (Student’s t‐test, **P < 0.01). | PMC10092002 | TPJ-112-1159-g006.jpg |
0.430289 | e2a7b48136ce4a1d849cdde247741d40 | A schematic model describing the C3H1–MAF2 module and its response to low temperatures to induce flowering in temperature‐sensitive chrysanthemum ecotypes. Under low‐temperature conditions, CmMAF2 expression is upregulated by CmC3H1 to repress the expression of CmGA20ox1, reducing bioactive GA levels. When returning to warm temperatures, CmMAF2 expression is reduced to release the expression of CmGA20ox1, and high bioactive GA levels rapidly induce CmLFY expression, thereby initiating floral transition. | PMC10092002 | TPJ-112-1159-g007.jpg |
0.435517 | 61c0a90623da468ea9ac6f1ee9bdc8ce | Effects of GA treatments on chrysanthemum flowering under LD conditions. (a) GA content in the shoot tips of plants at LT5 and at LT5 + N2. Plants grown for 5 or 7 weeks under normal temperature and LD conditions were used as controls (C5 and C7). (b) The effects of exogenous GA4/7 treatment and 5‐week low‐temperature treatment (LT5) on plant height of 8‐week‐old chrysanthemum. GA was given twice per week for 2 months. (c) The effects of exogenous GA4/7 treatments and 5‐week low‐temperature treatments (LT5) on initial flower bud appearance in control and treated plants. (d) Phenotypes of control and treated plants were observed after 14 weeks. The results are the means of three biological replicates with standard deviations. Asterisks indicate statistically significant differences (Student's t‐test, **P < 0.01). Different letters indicate significant differences according to Duncan's multiple range test (P < 0.05). Scale bars, 5 cm. | PMC10092002 | TPJ-112-1159-g008.jpg |
0.453314 | a562f8c62016477ba25f32073fa4a801 | Contrast-enhanced CT demonstrating an incidental well-circumscribed 2.3 cm pancreatic mass (red arrow). The mass is enhanced relative to pancreatic parenchyma, consistent with a nonfunctioning pancreatic neuroendocrine tumor. | PMC10093271 | cancers-15-02006-g001.jpg |
0.462558 | cbd7e303da1d4f4ca8e873a823ade5fa | Gallium-68 Dotatate PET/CT (of the patient featured in Figure 1) demonstrating intense dotatate uptake in the pancreatic lesion and expected background activity, consistent with a somatostatin receptor positive/dotatate-avid neuroendocrine tumor. | PMC10093271 | cancers-15-02006-g002.jpg |
0.438886 | f8925ce4063b4d9697c2aeeca69e11ba | Enucleation specimen of a 2-cm insulinoma in the proximal pancreatic body without pancreatic duct involvement and localized on a preoperative MRI. | PMC10093271 | cancers-15-02006-g003.jpg |
0.398851 | 88e8c1389cb74832a86ffd895ce6a037 | Distal pancreatectomy performed for a symptomatic, but diminutive (4 mm), insulinoma in the pancreatic tail that was not well visualized on cross-sectional imaging or endoscopic ultrasound, but localized with selective arterial calcium stimulation angiography. | PMC10093271 | cancers-15-02006-g004.jpg |
0.506024 | 85645a9608824a2087e8b7501b6efbef | Key metabolic pathways of amino acids in the gut. Through the function of fermentation, the ketogenic and glucogenic metabolic pathways are processed to produce ammonia and SCFAs (butyrate and propionate). In detail, as for the ketogenic process, the amino acids are converted to lysine, and some bacteria then cause the production of ammonia (Lysine pathway). In addition, lysine is metabolized to butyryl-CoA for the production of butyrate (CoA-transferase, succinate, and butyrate kinase pathway). Concerning the glucogenic pathway, the microbiota is mainly for the final synthesis of butyrate, and the production of propionate by the succinate pathway. | PMC10093363 | cancers-15-01942-g001.jpg |
0.469719 | 5be34ad8efe64be18cc2189761668736 | Application of microbiome/metabolomics in multiple myeloma. Eligible MM cohorts with matched baselines are recruited for sampling, then collected along with clinical characteristics for further analysis. Samples of serum, bone marrow aspirate and feces are performed with metabolomics, while paired fecal samples are utilized for microbiome sequencing. Furthermore, an analysis of differential metabolites and microbiota associated with MM is conducted, and then, in vivo and in vitro experiments are performed for further verification and mechanistic study. | PMC10093363 | cancers-15-01942-g002.jpg |
0.428022 | 785ae14e0b45426f8e1b37d2d746bbab | Interaction of gut microbiota and host amino acid metabolism in multiple myeloma. The amino acids are converted to ammonia. Conversely, ammonia is re-utilized by nitrogen bacteria to produce glutamine, wherein the bone marrow, glutamine, which is addicted to MM cells, is utilized by MM cells for proliferation. When it accumulates in the lung, glutamine contributes to the proliferation of lung normal fibroblast cells and elevated secretion of TNF-α for inflammatory infiltration. In addition, the SCFAs produced in the gut are adsorbed and distributed in the bone marrow, alleviating the proliferation of MM cells. | PMC10093363 | cancers-15-01942-g003.jpg |
0.403018 | 3218e0c6394b47dfa5f91a8e2ab55ab7 | Simplified diagram of the Tryptophan (Trp) metabolism through serotonin (5-HT) and kynurenine (Kyn) pathways and direct metabolism by microorganisms. Pro-inflammatory cytokines, which upregulate enzyme activity of indoleamine 2,3-dioxygenase1 (IDO1) and tryptophan 2,3-dioxygenase (TDO), are highlighted by “+”. The triangle shows enzymes. Trapezoid with dotted line shows intestinal microbial pathway. TPH, tryptophan hydroxylase; KMO, kynurenine 3-monooxygenase; KATs, kynurenine aminotransferases; KYNU, kynureninase; QPRT, quinolinic phosphoribosyltransferase; TNA, tryptophanase; AraT, aromatic amino acid aminotransferase; TMO, tryptophan 2-monooxygenase. * Aryl hydrocarbon receptor (AhR) ligands, ** potential AhR ligand. | PMC10093447 | cells-12-01087-g001.jpg |
0.420609 | 188b0762341f4479a8eb956323551de8 | Summary of the review. | PMC10093447 | cells-12-01087-g002.jpg |
0.470649 | 401fe9fa8b114bd1aad03820aae68fc5 | Schematic representation of the division of canine hemangiosarcoma into visceral and non-visceral. | PMC10093745 | cancers-15-02025-g001.jpg |
0.447765 | 3fbd9af90a2b4a9a901b6645bd994438 | Most reported non-visceral HSA subtypes in dogs. | PMC10093745 | cancers-15-02025-g002.jpg |
0.437705 | 4302ee79a58449229427434b66a64f66 | Multiple actinic lesions in a Pit Bull dog that had a history of chronic sun exposure. | PMC10093745 | cancers-15-02025-g003.jpg |
0.441946 | 024edb0e79024109bceb0979e23fe34f | Canine patient diagnosed with multiple cutaneous HSA nodules; ECT with systemic BLM was administered. Multiple skin lesions are observed in the ventral abdomen and medial surface of the pelvic limb (A,B). Crust and ulceration 7 days after ECT (C–E). Complete remission 30 days after ECT with areas of scar tissue (F). | PMC10093745 | cancers-15-02025-g004.jpg |
0.430952 | 10a3e7713ee14ee19dbbb49186121561 | Canine patient diagnosed with multiple cutaneous HSA who underwent ECT with systemic BLM. Multiple skin lesions are observed in the region of the pelvic limb (A). Crust and ulceration 7 days after ECT (B,C). Necrosis and tissue loss 15 days after ECT (D). Complete remission 30 days after ECT with areas of scar tissue (E). | PMC10093745 | cancers-15-02025-g005.jpg |
0.453657 | d41c28a1d9da4c8c99c5b01051e2002e | Differential diagnosis algorithm for splenic sarcomas based on immunohistochemical markers. | PMC10093745 | cancers-15-02025-g006.jpg |
0.48663 | 454a693a09bb4e6492278071a1a737ea | Majority race and identified industrial areas by community settlement in Chicago at the time of the 1918 influenza pandemic. | PMC10094019 | ijerph-20-05248-g001.jpg |
0.400763 | 90d3b532af69412e95a8b649d346c581 | Map of the 1918 influenza and pneumonia mortality rates and census tract characteristics. | PMC10094019 | ijerph-20-05248-g002.jpg |
0.480902 | d44d20ff8b9149f78cbe2253f34ea790 | COVID-19 mortality and neighborhood characteristics by census tracts. | PMC10094019 | ijerph-20-05248-g003.jpg |
0.439083 | 11bba171958a440ba08441242ff649a8 | The mortality rate of the historic 1918 pandemic in Chicago. (a) Influenza mortality rate by race and industry area proximity, (b) Pneumonia mortality rate by race and industry area proximity, (c) COVID-19 cumulative incidence rate by race: comparison between the majority race neighbor-based estimation and true rate, and (d) COVID-19 mortality rate by race: comparison between the majority race neighbor-based estimation and true rate. (*** p < 0.001). | PMC10094019 | ijerph-20-05248-g004.jpg |
0.466015 | ae23425bd5ea4427bd57b80140300802 | (a) School-level distribution of average NO2 concentration in parts per billion (ppb): 2011–2015; (b) school-level distribution of road noise level in A-weighted decibels (dB(A)): 2016. | PMC10094516 | ijerph-20-05308-g001.jpg |
0.411876 | 4240571f2f6b4998a57f7ed64729acb2 | miR-182-3p expression increases in cervical cancer. (A) miR-182-3p expression in CC and normal tissue samples from the GSE30656 dataset. (B) miR-182-3p expression in CC and normal tissue samples from the GSE86100 dataset. (C) Diagnostic value of miR-182-3p. (D) Kaplan–Meier curves of OS according to the miR-182-3p expression in CC samples of patients with CC from the TCGA dataset. (E) FLI1 mRNA is a potential target in the miR-182-3p, miRTargetLink Human and miRDB databases. (G) Pairing between the target region and miRNA from the TargetScanHuman7.0 database. (F) Biological processes of these 330 target mRNAs of miR-182-3p. (H) Correlation between FLI-1 and miR-182-3p expression in patients with CC from the TCGA dataset. Median cut-off. * p-value ˂ 0.05 and ** p-value ˂ 0.01. | PMC10094573 | ijms-24-06032-g001.jpg |
0.389742 | 0c5a109871dd417089dcdfa87a2a6264 | FLI-1 expression increases in cervical cancer. (A) FLI-1 expression in the CC and normal tissue samples from the TCGA dataset. (B) FLI-1 expression in the CC and normal tissue samples from the GSE7803 dataset. (C) FLI-1 expression in the CC, CIN3, CIN2, CIN1, and normal tissue samples from the GSE63514 dataset. (D) FLI-1 expression in the CC and normal tissue samples from the GSE56363 dataset. (E) Kaplan–Meier curves of OS according to FLI-1 expression in the CC samples of patients with CC from the TCGA dataset. (F) Kaplan–Meier curves of RFS according to FLI-1 expression in the CC samples of patients with CC from the TCGA dataset. CIN: Cervical intra-epithelial neoplasia. * p-value ˂ 0.05, ** p-value ˂ 0.01 and *** p-value < 0.001. | PMC10094573 | ijms-24-06032-g002.jpg |
0.378485 | 6419461d6d3b4f21ba7a9f01d6753320 | Methylation in the FLI-1 promoter increases in cervical cancer tissue. (A) CpG island at the FLI-1 promoter. The CpG island is located in a region ±2 kb around the TSS. Red box: localization of probe cg13755070. Green box: localization of probe cg17872757. (B) Methylation level at FLI-1 promoter in the CC and normal tissue samples from the TCGA dataset. (C) Methylation level at the FLI-1 promoter in the CC and normal tissue samples from the GSE30760 dataset (probe cg17872757). (D) Methylation level at the FLI-1 promoter in the CC and normal tissue samples from the GSE46306 dataset (probe cg17872757). (E) Methylation level at the FLI-1 promoter in the CC and normal tissue samples from the GSE30760 dataset (probe cg13755070). (F) Methylation level at the FLI-1 promoter in the CC and normal tissue samples from the GSE46306 dataset (probe cg13755070). (G) Correlation between the methylation and FLI-1 expression in patients with CC from the TCGA dataset. * p-value ˂ 0.05, *** p-value < 0.001 and **** p-value < 0.0001. | PMC10094573 | ijms-24-06032-g003.jpg |
0.401911 | 2def3a52a8b24e20a0f0bcf06b0e215b | AP2α expression increases in cervical cancer. (A) Identification of binding sites for the SP1 and AP2α transcription factors in the FLI1 promoter using the CONSITE and ALIBABA databases. (B) Validation of binding sites for SP1 and AP2α transcription factors in the FLI-1 promoter using the ALLGEN-PROMO database. (C) AP2α expression in the CC and normal tissue samples from the TCGA dataset. (D) AP2α expression in the CC and normal tissue samples from the GSE7803 dataset. (E) AP2α expression in the CC and normal tissue samples from the HPA dataset. (F) Kaplan–Meier curves of OS according to AP2α expression in the CC samples of patients with CC from the TCGA dataset. (G) Kaplan–Meier curves of RFS according to AP2α expression in the CC samples of patients with CC from the TCGA dataset. * p-value ˂ 0.05. | PMC10094573 | ijms-24-06032-g004.jpg |
0.417232 | 74772da1dcfc43498dc9ea4a03f2b1f5 | FLI-1 regulates the gene expression participating in the immune response in cervical cancer. (A) Identification of pathways according to genes that positively correlate with FLI-1 using the MSigDB Hallmark 2020 library in the Enrich database. (B) Validation of identified pathways of genes that positively correlate with FLI-1 using the KEGG 2021 Human library in the Enrich database. (C) Identification of the biological processes of genes that positively correlate with FLI-1 using the Biological Process 2021 library in the Enrich database. (D) Identification of genes in common considering the regular potential and expression correlation of target genes using the CISTROME database. (E) Identification of pathways of genes identified in (D) using the MSigDB Hallmark 2020 library in the Enrich database. (F) Validation of the identified pathways of genes selected in (D) using the KEGG 2021 Human library in the Enrich database. (G) Identification of biological processes of genes identified in (D) using the Biological Process 2021 library in the Enrich database. | PMC10094573 | ijms-24-06032-g005.jpg |
0.410094 | 0ac0f3b014784036a2bdf8071963fba3 | High FLI-1 expression is associated with pathways related to immune response in cervical cancer. (A) FLI-1 expression in CC patients with high FLI-1 expression (top 30) and low FLI-1 expression (top 30) from the TCGA dataset. (B) DEGs between the CC patients with low FLI-1 and high FLI-1 expression from the TCGA dataset. (C) Heatmap with DEGs from the TCGA dataset. (D) Identification of pathways enriched considering DEGs using GSEA software. (E) Two graphs representative of the GSEA analysis are shown. **** p-value < 0.0001. | PMC10094573 | ijms-24-06032-g006.jpg |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.