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0.434903 | 26a340e377894e18bab3fcbcb01f7577 | Base map of the test area in Central Europe. | PMC10054486 | jimaging-09-00061-g002.jpg |
0.443326 | d20d1189a62e4b079125e8cc465dec19 | ReUse’s AGB predictions with raw bands in Central Europe. | PMC10054486 | jimaging-09-00061-g003.jpg |
0.424002 | cc8c17af60334d4d80b8e297f4818702 | ReUse’s AGB predictions with raw bands and feature extraction in Central Europe. | PMC10054486 | jimaging-09-00061-g004.jpg |
0.453261 | 3271679a518f46ac9d3c0a00129cf1b5 | Predictions of AGB using the machine learning approach [10] in Central Europe. | PMC10054486 | jimaging-09-00061-g005.jpg |
0.473282 | f23f23a3426c40e1b5af1d5838722aec | Predictions of AGB using the machine learning approach [14] in Central Europe. | PMC10054486 | jimaging-09-00061-g006.jpg |
0.44774 | 52116cab8e354560865d7d633a36d9db | On the left is the predicted above-ground biomass raster of the Astroni nature reserve before the July 2017 fire; on the right is the predicted above-ground biomass raster after a major fire event for the same area. | PMC10054486 | jimaging-09-00061-g007.jpg |
0.409649 | 78001baad81f4c5ab532032fd507f739 | Visual representation of perfusion in CE-MDCT scans in the upper kidney pole with marked ROI (cyan oval). Cortical blood flow = 153.7 ± 52.9 mL/100 g/min; ROI area = 33.0 mm2. | PMC10054581 | jcm-12-02111-g001.jpg |
0.398462 | 9760c3a3f2a34c0e91efab7e26654156 | Visual representation of perfusion in CE-MDCT scans in the middle kidney pole with marked ROI (cyan oval). Cortical blood flow = 177.9 ± 43.9 mL/100 g/min; ROI area = 35.9 mm2. | PMC10054581 | jcm-12-02111-g002.jpg |
0.402481 | ace028c962e44aad83667aae76e33263 | Visual representation of perfusion in CE-MDCT scans in the lower kidney pole with marked ROI (cyan oval). Cortical blood flow = 156.9 ± 43.9 mL/100 g/min; ROI area = 36.6 mm2. | PMC10054581 | jcm-12-02111-g003.jpg |
0.461704 | 213e6a6adc3d47548ddfcb68885dab69 | Ultrasound measurement of resistive index in the triplex (2D, color Doppler and pulse wave Doppler) mode. | PMC10054581 | jcm-12-02111-g004.jpg |
0.495266 | 1297deb2aec94f40bfc8a645891b64c1 | Ultrasound color Doppler visualization of renal cortex perfusion with marked (magenta rectangle) ROI. | PMC10054581 | jcm-12-02111-g005.jpg |
0.411083 | bd3df5d53f094191ba51be89944fd991 | Comparison of CE-MDCT cortical blood flow in different kidney poles. | PMC10054581 | jcm-12-02111-g006.jpg |
0.436223 | 6fe28a500d7c43c1b66ca00dd1162667 | Concentration of fAsn in the grain of 36 bread wheat varieties grown in 2018–2019 in the three locations Foggia, Grosseto, and Voghera. FF: improver wheat; FPS: superior bread making wheat; FP: ordinary bread making wheat; FB: wheat for biscuits. | PMC10054617 | plants-12-01349-g001.jpg |
0.437953 | 1ad36ad2d8aa4dffb5be205e54a7418d | Concentration of fAsn in the grain of 36 bread wheat varieties grown in 2019–2020 in the three locations Foggia, Grosseto, and Voghera. FF: improver wheat; FPS: superior bread making wheat; FP: ordinary bread making wheat; FB: wheat for biscuits. | PMC10054617 | plants-12-01349-g002.jpg |
0.473267 | 4a71807e1095470a8864bfcff424369c | Box plots of fAsn measurements in the six considered field trials, considering the data from the 18 genotypes common to the six field trials. | PMC10054617 | plants-12-01349-g003.jpg |
0.417864 | 193b515c971b4792953492e53fea7c02 | Box plots of fAsn measurements from the 18 genotypes present in the six field trials. | PMC10054617 | plants-12-01349-g004.jpg |
0.434282 | e47f9c20669441f6a5b5bf2c07437e7c | Structures of Compounds 1 and 2. | PMC10054748 | pharmaceuticals-16-00452-g001.jpg |
0.438476 | b7bde3a5ebdc4f16b0c0906535a855fc | Key 2D NMR correlations of 1 and 2. | PMC10054748 | pharmaceuticals-16-00452-g002.jpg |
0.453008 | e9563a51bb2e419e826add54ef0e08e6 | The 13C NMR chemical shift calculation results of a pair of C-5 epimers of (5R, 7R, 8S) −1 (1a) and (5S, 7R, 8S) −1 (1b). | PMC10054748 | pharmaceuticals-16-00452-g003.jpg |
0.44753 | a0c85be11ad24025a126ee2d0a7d6481 | Experimental and calculated ECD spectra of 1. | PMC10054748 | pharmaceuticals-16-00452-g004.jpg |
0.509235 | aba914e9429642e89450606f3baf6e29 | ORTEP diagram of Compound 2. | PMC10054748 | pharmaceuticals-16-00452-g005.jpg |
0.385904 | fe569fe4a7f640889203785e918d7137 | Effects of Compound 1 on the proliferation of glucose-induced HRMCs (* p < 0.05, vs. the 30 mM glucose group; *** p < 0.001, vs. the 30 mM glucose group; ## p < 0.01, vs. the control group). | PMC10054748 | pharmaceuticals-16-00452-g006.jpg |
0.445078 | 43d806ffc47c44ac9633bb0998d0f7df | Proposed biosynthetic pathways for 1 and 2. | PMC10054748 | pharmaceuticals-16-00452-sch001.jpg |
0.431714 | 03222a9c6f2f483d9545ad05b4490d9d | Transcriptomic analysis of astrocyte-containing tissues in bilaterally naïve mice. (A) Experimental design of the study. Three tissue regions of bilaterally naïve mice were micro-dissected for comparison: 1) myelinated optic nerve (MON), 2) unmyelinated optic nerve (UON), and 3) retina. Tissue from four mice were collected and the sex replicates for each tissue group were pooled after RNA extraction for library preparation and 150 bp paired end Illumina sequencing. (B) Principal component analysis (PCA) of bilaterally naïve tissue regions. Each symbol represents a single sample, where symbol colors denote the tissue region and symbol shapes signify sex. (C) FPKM (Fragments Per Kilobase of transcript per Million mapped reads) expression of cell type markers characteristic of each tissue region: glial (Gja1, encodes for Connexin-43), oligodendrocyte (Mbp, encodes for myelin basic protein), retinal (Rho, encodes for Rhodopsin), microglial (Cd68, encodes for Cluster of Differentiation 68), and capillary/endothelial (Flt1, encodes for VEGFR1). Dots represent a single sample and lines represent the median FPKM of the replicate samples. (D) Expression of astrocyte genes in three naïve tissue regions: UON, MON, and retina. Left y-axis and filled bars represent FPKM (from RNA-seq data), while right y-axis and empty bars indicate relative expression via qPCR of independent tissue samples. Error bars indicate standard deviation. For RNA-seq, n = 2 (pooled) samples per tissue type. For qPCR, n = 6 samples from 3 mice per tissue group. | PMC10054954 | nihpp-2023.02.21.529410v3-f0001.jpg |
0.441285 | 3cccb8b1347c463db2ab06585af0b097 | Region-specific gene signatures in the naïve ON. (A) Venn diagrams showing the number of significantly enriched genes in naïve UON compared to MON and retina (top) and MON compared to UON and retina (bottom). (B) KEGG analysis of enriched UON (top) and MON (bottom) genes compared to all other tissue regions. (C) Clustered heatmaps of significantly upregulated UON genes within the extracellular matrix (ECM)–receptor interactions (top) and MON-enriched genes in the steroid biosynthesis (bottom) KEGG pathways. (D) Volcano plot showing differential expression analysis comparing naïve UON and MON. Dotted lines indicate threshold cut-off for a significantly changed gene (log2FC ± 1, in addition to adjusted p < 0.05). Genes with log2FC > 1 were considered enriched in UON, and genes with log2FC < −1 signified MON-enriched genes. (E) KEGG pathways enriched in UON and MON genes. | PMC10054954 | nihpp-2023.02.21.529410v3-f0002.jpg |
0.427091 | 1313c8c07ebd4622be0151533063f754 | Differential responses to ON crush. (A) Experimental design for studying gene expression responses following ON crush in UON, MON, and retinal tissue. (B) PCA of tissue during the ON crush time course. (C) Venn diagrams showing relationships of differentially expressed genes (DEGs) between UON, MON, and retina three days (left, 3D) and two weeks (right, 2W) after crush. (D) KEGG pathway analysis of UON and MON DEGs at early (top) and late (bottom) crush time points. (E) Venn diagrams showing relationships of UON (top) and MON (bottom) responses to ON crush. (F) Number of upregulated and downregulated genes in UON and MON at each crush time point. (G-H) Gene expression changes in UON (G) and MON (H) during the ON crush time course. | PMC10054954 | nihpp-2023.02.21.529410v3-f0003.jpg |
0.412079 | fbf96167f530414d8399dbb03f9bb1d8 | Differential responses to glaucoma. (A) Experimental design for RNA-seq experiments in the bead-induced glaucoma model. (B) PCA of control and experimental glaucoma tissue time points. (C) Venn diagrams showing relationships of DEGs between UON, MON, and retina three days, two weeks, and six weeks after IOP elevation. (D) KEGG pathway analysis of UON and MON DEGs at different time points following IOP elevation. (E) Venn diagrams showing relationships of UON (left) and MON (right) responses to bead-induced glaucoma. (F) Number of up/down genes in UON and MON at each glaucoma time point. (G-H) Gene expression changes in UON (G) and MON (H) during the glaucoma time course. | PMC10054954 | nihpp-2023.02.21.529410v3-f0004.jpg |
0.414027 | ed7a6c068f3a4598841ed8fb95a65bd2 | Shared responses to ON injury. (A) Venn diagrams comparing DEGs in ON crush and glaucoma injuries in UON (top) and MON (bottom) tissue regions. DEGs are both upregulated and downregulated in at least one time point. (B-C) Gene expression of select UON (B) and MON (C) DEGs in ON crush and glaucoma injury. (D) Heatmap showing PAN-reactive, A1-specific, and A2-specific astrocyte markers in naïve and injured UON and MON regions. UON tissue did not express a dominant A1 or A2 characteristic phenotype in crush or glaucoma, while MON exhibited slightly more consistent A1/A2-specific gene expression compared to UON tissue. | PMC10054954 | nihpp-2023.02.21.529410v3-f0005.jpg |
0.407041 | b4e54e563f764a5da4e2ff9a1a0de554 | An illustration of the analytic framework.A) Gene expression data from the Allen Human Brain Atlas was summarised to the Desikan-Killiany Atlas. B) We conducted PCA on the gene expression matrices (68 regions * 8235 genes) and two components were justified with validity checks. C) We rotated these two components, and the component scores show the relative positions of the 68 Desikan-Killany regions on these components. D) g ~ brain cortical morphometry associations were calculated for three cohorts. E) The g ~ brain cortical morphometry associations were meta-analysed with random effects models. F) The meta-analysed standardised β values of each regional morphometry metric (cortical volume, surface area and thickness) show their associations with g. G) Spatial associations were tested between the brain-regional component scores for gene expression and the regional g ~ brain cortical morphometry associations. Then, controlling for the regional component scores, g-associations for individual genes were calculated. | PMC10055068 | nihpp-2023.03.16.532915v1-f0001.jpg |
0.430669 | 732a5b596d074f9683548194c9384a7e | Validating gene expression components.A) Raw gene expression values for the 34 regions for the left and right hemispheres, for the 8235 consistent genes. B) Correlation plot of the 8235 genes across the 68 cortical regions (8235 * 8235). C) Absolute factor congruence coefficients for the first 10 components between “train” and “test” folds (~54–55 regions, and ~12–13 regions), over 50 repetitions. D) Absolute factor congruence coefficients from different pipelines with PC1 and PC2 of the current dataset of interest, using the Desikan-Killiany atlas. * denotes that PC3 from that pipeline is compared with PC2. E) Absolute factor congruence coefficients for two external datasets with PC1 and PC2 of the current dataset of interest. * denotes that PC3 from is compared with PC2. F) Absolute factor congruence coefficients for three alternative parcellations with the PC1 and PC2 of the current dataset (which uses the Desikan-Killiany atlas). | PMC10055068 | nihpp-2023.03.16.532915v1-f0002.jpg |
0.45343 | fa9a20d6f5c940efbf493b5e7eac26c5 | Two major components of cortical gene expression.Top and middle panels (Component 1 and Component 2, respectively) left: Regional z scores mapped to the cerebral cortex (scaled for each hemisphere) and right: word clouds of the statistical over-representation results. The relative direction of component scores is arbitrary (dictated by the PCA), and here, the colour scale is flipped between components so that the directions of upregulation/downregulation match. Bottom panel: Density distribution plots of loadings on Component 1 and Component 2 coloured by cell type. | PMC10055068 | nihpp-2023.03.16.532915v1-f0003.jpg |
0.426114 | b24f7a2d7ada4dd0b11e8ebca1e12d04 | Meta-analysed brain regional associations with g.A) Standardised β estimates mapped to the cerebral cortex. B) Meta-analysed standardised β estimates for g-volume, g-surface area and g-thickness. Those for which p < .05 are filled in, and those for which p > .05 are outlined. The y-axis is ordered by the meta-analysed β values. | PMC10055068 | nihpp-2023.03.16.532915v1-f0004.jpg |
0.522795 | 3f44841652dc43779e66a2c30c3007f6 | Associations between regional-g profiles and the two gene expression components.LOESS functions are plotted (the quadratic model results are comparable to the absolute score correlations, and are presented in Table S25). A vertical line at component scores of 0 represents a balance between upregulation and downregulation ends of each component. The colour scale is flipped between Components, so that the direction of downregulation and upregulation match. | PMC10055068 | nihpp-2023.03.16.532915v1-f0005.jpg |
0.485618 | e362587554c54204b740300c84c33189 | Specific associations between regional g-morphometry profiles and individual gene expression profiles.Standardised β for specific individual gene profiles (i.e. corrected for general components of gene expression) for which FDR Q > .05 for all three cortical morphometry associations with g. | PMC10055068 | nihpp-2023.03.16.532915v1-f0006.jpg |
0.429762 | d5fe5801d80244f4811e8f3c8ca00f26 | Co-resistance with other antimicrobials is highest among isolates with chromosomally-encoded resistance to tetracyclines.Isolates were classified as susceptible (MIC ≤ 0.25 μg/mL), intermediate (0.25 < MIC < 2 μg/mL), resistant (2 ≤ MIC ≤ 8 μg/mL), or high-level resistant (MIC > 8 μg/mL) in 5,644 global N. gonorrhoeae isolates (A) and 1,041 isolates collected in the United States in 2018 (B). Background shading corresponds to susceptible (white), intermediate (light gray), and resistant/non-susceptible (dark gray) MICs for each antimicrobial. | PMC10055447 | nihpp-2023.03.14.23287223v1-f0001.jpg |
0.500592 | 4e0c8a7515dc4313bba025450b5af066 | Maximum intensity projection (MIP) of decay-corrected SUV images of the baseline scans.The baseline scans of COVID-19 convalescent patients and healthy control subjects are compared at three imaging timepoints. Sub01 and Sub03 skipped dynamic imaging. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0001.jpg |
0.489464 | b35c2d98fa664578919815d515f963a8 | MIP of decay-corrected SUV images of the 4-month follow-up scans.The follow-up scans of the COVID-19 convalescent patients are shown at three imaging timepoints. Sub01 and Sub03 skipped dynamic imaging. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0002.jpg |
0.429164 | 8a85788bb30043399edfcf0ef364cea1 | Decay-corrected TACs of different organs of interest.(A) The TACs representing the delivery, retention, and clearance of the tracer over the 48-h time course of the study are shown for bone marrow (cervical, thoracic, and lumbar vertebrae, sacrum, and ilium), spleen, liver, lymph nodes, tonsils, lungs, nasal cavity, and the left ventricle (LV) blood pool, in addition to (B) zoomed-in plots on the first 90-mins after tracer administration for all subjects. Control and COVID-19 subjects are in shades of red and blue, respectively. The lymph node TACs show an example lymph node selected from the occipital region of each subject (PET/CT images shown in Fig. S2). The occipital region was selected as a common area where all subjects showed quantifiable uptake and the TACs were not affected by spill-over from adjacent lymph nodes or blood vessels. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0003.jpg |
0.381582 | 54e10e8c16b94751a45158abf6d86594 | TBRs of different organs-of-interest.TBRs are compared between COVID-19 and control subjects in lymph nodes, tonsils, spleen, bone marrow, liver, lungs, and nasal cavity (A) during the 30–90 min of the dynamic scans and (B) at the 6–7 h timepoint. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0004.jpg |
0.425097 | 106ebcdeeabf4a7cb70cf4ad731184af | Longitudinal changes of TBRs in different organs-of-interest of COVID-19 convalescent patients.Percentage changes of TBR at 4-month follow-up scans of the COVID-19 patients relative to their baseline scans is shown in lymph nodes, tonsils, spleen, bone marrow, liver, lungs, and nasal cavity at (A) 30–90 min, and (B) 6–7 h. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0005.jpg |
0.41831 | 87a8cbe6eabe403cae425d0d3b3912a3 | Net influx rate of the 2T5P model.Net influx rate (Ki) obtained by 2T5P model fits on lungs, spleen, and sacrum and ilium bone marrow are compared in all subjects with dynamic scans. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0006.jpg |
0.421136 | 9eba149b09074d058ff45a86991cc1ce | PET/CT image slices of thymus uptake.Selected transverse PET/CT image slices of one control subject and one COVID-19 patient (at baseline and follow-up scan) showing thymus uptake at 48-h timepoint of imaging. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0007.jpg |
0.477411 | c2b06152ee69441bb4f3beb236e06959 | Peripheral blood CD8+ T cell phenotyping.(A) Percentage of CD8+ T cells within the live CD3+ population, (B) percentage of activated CD8+ T cells characterized by CD38 and HLA-DR co-expression and (C) CD56 expression, and (D) percentage of exhausted CD8+ T cells characterized by PD-1 expression are compared in all subjects. | PMC10055575 | nihpp-2023.03.14.23287121v1-f0008.jpg |
0.369804 | ec250afb9a65428b8f4348a69cde3c7b | Map of the study sites | PMC10055656 | nihpp-rs2692688v1-f0001.jpg |
0.470321 | c57bc3f0550b4038887a8b28fc419c8b | Proportion of submicroscopic infections among asymptomatic and symptomatic by parasite species in Arjo and Gambella, Ethiopia. (Individuals with malaria related symptoms or asymptotic during or 48h prior to mass blood survey). | PMC10055656 | nihpp-rs2692688v1-f0002.jpg |
0.392497 | 25e0663467db4c8ab88bad0d55a832a0 | Parasite density in symptomatic and asymptomatic Plasmodium-infections by microscopy in Arjo and Gambella, Ethiopia. | PMC10055656 | nihpp-rs2692688v1-f0003.jpg |
0.428272 | e96bd3b044f44774a7a22b9ed946cef3 | Release profiles of L-ascorbic acid derivatives from investigated emulgels (ASP1, MAP1, ASP2 and MAP2). | PMC10056080 | pharmaceutics-15-00813-g001.jpg |
0.460713 | 38b039b5ac694c9a8ebd335149d7c3a6 | In vivo determined mean values with standard deviation of pH for non-treated control (NC), placebo emulgel (PE), and the investigated emulgels (ASP1, MAP1, ASP2 and MAP2) after 7, 14, and 28 days of application, and 2 days after the cessation of application. Significant differences are marked with * (p < 0.05). | PMC10056080 | pharmaceutics-15-00813-g002.jpg |
0.498556 | 4678e7486bcb4e6d8f5f5d028e24da5f | In vivo determined mean values with a standard deviation of trans-epidermal water loss (TEWL) for non-treated control (NC), placebo emulgel (PE) and investigated emulgels (ASP1, MAP1, ASP2 and MAP2) after 7, 14, and 28 days of application, and 2 days after the cessation of application. | PMC10056080 | pharmaceutics-15-00813-g003.jpg |
0.425569 | 98ee0c42b843425e856c6b60fa96a25e | In vivo determined mean values with a standard deviation of electrical capacitance (EC) for non-treated control (NC), placebo emulgel (PE) and investigated emulgels (ASP1, MAP1, ASP2 and MAP2) after 7, 14, and 28 days of application, and 2 days after the cessation of application. Significant differences are marked with * (p < 0.05). | PMC10056080 | pharmaceutics-15-00813-g004.jpg |
0.42337 | 5c00195fcea84beca7aeb57d88f8fac4 | Hyperpigmentation caused by dihydroxyacetone and lightening of the skin caused by the application of MAP1 and MAP2. | PMC10056080 | pharmaceutics-15-00813-g005.jpg |
0.456833 | e640d3df78544ea98d241719d584d283 | In vivo determined mean values with a standard deviation of melanin index (MI) for non-treated control (NC), placebo emulgel (PE) and investigated emulgels (ASP1, MAP1, ASP2 and MAP2) after 3 and 7 days of application. Significant differences are marked with * (p < 0.05). | PMC10056080 | pharmaceutics-15-00813-g006.jpg |
0.519796 | b38dfc044f9b47d4becebc741797520d | The results of the sensory analysis of the investigated samples during application. | PMC10056080 | pharmaceutics-15-00813-g007.jpg |
0.530447 | 6e7915ba8e5745f49e3c7c526dd318a6 | The results of sensory analysis of the investigated samples after application. | PMC10056080 | pharmaceutics-15-00813-g008.jpg |
0.389714 | f66985e967e243bfa74a6c3e5f67475a | Comparison of the energy storage mechanisms of different materials [45]. | PMC10056300 | nanomaterials-13-00979-g001.jpg |
0.394228 | f940e355fd324995a520bc94a49d2c70 | (a) XRD pattern and FE-SEM image (inset) of as-prepared (i) CoMoO4·xH2O and (ii) MnMoO4 (The asterisk refers to the diffraction peak position of MoO3 phase); (b) CV curves of α-NiMoO4, MnMoO4, and CoMoO4·xH2O at a scan rate of 5 mV s−1; (c) CoMoO4·xH2O and (d) MnMoO4 at different scan rates from 5 to 50 mV s−1; (e) the SC as a function of the scan rate; (f) variation in the SC with cycle number at 12 A g−1 for α-NiMoO4, MnMoO4, and CoMoO4 [69]. | PMC10056300 | nanomaterials-13-00979-g002.jpg |
0.424668 | 6229c242fac649eea63d49df68fc1953 | SEM images of (a,b) precursors and (c,d) NiS [83]. | PMC10056300 | nanomaterials-13-00979-g003.jpg |
0.406548 | d8b61943db44493b8d75dc5eff8f725d | Formation process of NiS microflowers [84]. | PMC10056300 | nanomaterials-13-00979-g004.jpg |
0.428375 | 327e53df46f94738aec48b97bd1b8a76 | (a) Cycle stability [85]. (b) Rate performances of S-1 and S-2 [89]. (c) Cycle performance and Coulombic efficiency [92]. | PMC10056300 | nanomaterials-13-00979-g005.jpg |
0.404956 | c9962d87fdbf4d4a8f42f14d9c844742 | SEM images of (a) the bare NF and (b–d) NiS@NF at low and high magnifications [93]. (e) Cycles for NiS-P and NiS-C [94]. (f) Cycle performance of MXene and MXene-NiS-1 electrodes. The inset shows the last 20 cycles of an MXene/NiS-1 electrode [96]. | PMC10056300 | nanomaterials-13-00979-g006.jpg |
0.507519 | 658b572d36d84e71b005cf650a87399a | (a,b) When the growth time was further extended to 5 h, the nanobranches were densely oriented on the NiS nanopillars (indicated by the yellow circles), and the adhesion of the nanobranches was observed to be poor due to the overcoating of the material and the surface cracks [98]. (c,d) FE-SEM images of the NiS thin film surface at magnifications of 10,000× and 25,000×, respectively [99]. | PMC10056300 | nanomaterials-13-00979-g007.jpg |
0.452722 | 9e37f2e676914dcf9b6112de376575ce | (a,b) FE−SEM images of NSG nanostructures at various nanometric scales. (c) TEM images of NSG nanostructure at different magnifications. (d) HRTEM images of NSG. (e) CV curves of prepared electrodes at 100 mV s−1. CV curves at various scan rates of (f) NSG and (g) PNS [109]. | PMC10056300 | nanomaterials-13-00979-g008.jpg |
0.429946 | 8ae0ce2c92ec468b88485ea6aa55b0da | (a) Typical SEM images of NiS/MoS2 @N-rGO [112]. (b) SEM images of Ni3S4@rGO-20 [113]. (c) SEM images of NiO/NiS nanosheets with nanoparticles on Ni foam [114]. (d) SEM images of NiS/SnS2@CC [114]. | PMC10056300 | nanomaterials-13-00979-g009.jpg |
0.447549 | f13bd150f7ea4184bd8a6c78cba19172 | Scheme for the preparation of NiS@NF and NiS/CNTs@NF electrodes [119]. | PMC10056300 | nanomaterials-13-00979-g010.jpg |
0.399307 | 88e7fa12305b44be829ae1317e4de0e7 | SEM images of (a,b) CNFs-NiS, (c) Raman spectra of CNFs-NiOx (black) and CNFs-NiS (red) [123]. (d) CNTs/NiS, (e) CNTs/NiS/CoS [124], (f) Raman spectra of NiS/CF@NiS, (g) NiSNF/CF@NiSNP-1, (h) NiSNF/CF@NiSNP-2, (i) NiSNF/CF@NiSNP-4, and (j) NiSNF/CF@NiSNP-5 [125]. | PMC10056300 | nanomaterials-13-00979-g011.jpg |
0.376632 | 32b9c39bc45e4465b15b2f209675f0f0 | (a,b) SEM morphologies of NiS–NG. (c) XRD and (d) Raman profiles for NiS–NG. Galvanostatic charge–discharge studies: (e) discharge plots of NiS–NG; (f) comparative GCD plots for NG, NiS, and NiS–NG. NG//NiS–NG asymmetric device performance: (g) cyclic stability [127]. | PMC10056300 | nanomaterials-13-00979-g012.jpg |
0.494038 | 2760e176a025473b9e3478a56cb1a591 | (a) Raman spectra of the NiS, NiS/rGO−20, NiS/rGO−40, NiS/rGO−60, NiS/rGO−80, and rGO samples [128]. (b) Raman spectra of GO and calcined NS/G−10 [130]. | PMC10056300 | nanomaterials-13-00979-g013.jpg |
0.424494 | de4675be99e144ffb09af1a9fd16050e | (a) Schematic representation showing the possible working mechanism of ANM-NiS- rGO as a supercapacitor electrode [140]. (b) Schematic diagram of an ASC [141]. (c) Schematic diagram of an ASC [146]. (d) Schematic representation of a fabricated all-solid-state flexible asymmetric supercapacitor cell [147]. | PMC10056300 | nanomaterials-13-00979-g014.jpg |
0.434223 | 69e67ec6c701450d9df15120eea5eb5a | (a) Illustration of the synthesis of a MnFe2O4−NiS−PC nanocomposite. (b) Synthesized MnFe2O4−NiS−PC nanocomposite. (c) Cycling stability test (inset shows the GCD curves of 10 representative cycles) after 10,000 cycles. (d−g) All−solid−state ASC devices under different bending angles, demonstrating their flexible character [147]. | PMC10056300 | nanomaterials-13-00979-g015.jpg |
0.47246 | f8a3b223bd5d44c39374799b8c98553d | Clinical signs observed at a foot-and-mouth disease outbreak identified in Orenburg oblast in December 2021. (A) lesions on the treats, (B) aphts in the mouth. | PMC10056362 | viruses-15-00598-g001.jpg |
0.460032 | 1af7b8a908334235a38a30d4fd3bd986 | Map showing foot-and-mouth disease outbreaks in 2021 and 2022 in the subregion. | PMC10056362 | viruses-15-00598-g002.jpg |
0.457863 | 88698f9a896d48fc8a3c6c04b53f0680 | Time course of Type O foot-and-mouth disease outbreaks in Russia, Kazakhstan, and Mongolia from 2013 to 2022 (dated 1 April 2022). | PMC10056362 | viruses-15-00598-g003.jpg |
0.416407 | 8fc81dd6ffab44209440b5fbeecd9f68 | Maximum likelihood tree reflecting the phylogenetic relationship among Russian, Kazakhstan, and Mongolian foot-and-mouth disease viral isolates collected in 2021 and 2022 on the basis of full-length VP1 gene sequences. The studied isolates are in bold. | PMC10056362 | viruses-15-00598-g004.jpg |
0.402177 | 51ed53002d134760aafc9836c9f0c849 | Time course of changes in the range of foot-and-mouth disease outbreaks from 2015 to 2018 and from 2019 to 2022 in Russia, Kazakhstan, Mongolia, and China. | PMC10056362 | viruses-15-00598-g005.jpg |
0.415749 | 8721fdc8faf441e39c8531cba368d5ee | Immunofluorescence antibody staining for virus-infected PAMs by IFA. (A) Mock-inoculated and PRRSV-infected PAMs were stained with PRRSV N protein (red)-specific monoclonal antibody. (B) Mock-inoculated and PCV2-infected PAMs were stained with PCV2 Cap protein (green)-specific monoclonal antibody. Magnification: ×100. | PMC10058123 | viruses-15-00777-g001.jpg |
0.450196 | b6ec4c8fe9ec4553a7c3cbc83b112efb | PRRSV viral load of different infection groups. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co−infected group (PCV2−PRRSV, PRRSV−PCV2 and PCV2 + PRRSV) were inoculated with PRRSV and/or PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI−1640 medium. Then, PAMs from these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post−infection, respectively. (A) The levels of viral RNA were measured by RT−qPCR. (B) The viral titer of PRRSV in the supernatants was analyzed by TCID50. Data are expressed as means ± SD of three independent experiments. Statistically significant differences for the PCV2 and PRRSV co−infected groups vs. the mock−inoculated group and the PCV2 alone group are indicated (*** p < 0.001). Significant differences between groups are also represented (** p < 0.01, * p < 0.05). | PMC10058123 | viruses-15-00777-g002.jpg |
0.432971 | 9f86b3af443948bc8eb5a4e4bbf90b0d | PCV2 viral load of different infection groups. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co−infected groups (PCV2−PRRSV, PRRSV−PCV2 and PCV2 + PRRSV) were inoculated with PRRSV and/or PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI−1640 medium. Then, PAMs in these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post−infection, respectively. (A) The levels of viral DNA were measured by RT−qPCR. (B) The viral titers of PCV2 in the cell culture supernatants were analyzed by TCID50. Data are expressed as means ± SD of three independent experiments. Statistically significant differences for the PCV2 and PRRSV co−infected groups vs. the mock−inoculated group and the PRRSV alone group (* p < 0.05, *** p < 0.001). No significant differences were observed for the PCV2 alone group vs. the PCV2 and PRRSV co−infected groups (ns). | PMC10058123 | viruses-15-00777-g003.jpg |
0.40367 | 25009ce2b7d040d1979222ccda2e4414 | Relative mRNA expression of IFN-α and IFN-γ. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co-infected groups (PCV2–PRRSV, PRRSV–PCV2 and PCV2 + PRRSV) were inoculated with PRRSV or/and PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI-1640 medium. Then, PAMs from these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post-infection, respectively. RT-qPCR analysis of IFN-α (A) and IFN-γ (B) mRNAs in PAMs from different groups. Data are expressed as means ± SD of three independent experiments. Significant differences between groups are represented (* p < 0.05). | PMC10058123 | viruses-15-00777-g004.jpg |
0.440433 | c1d44d6fc1db472a82466744be177924 | Relative mRNA expression of TNF-α and IL-1β. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co-infected groups (PCV2–PRRSV, PRRSV–PCV2 and PCV2 + PRRSV) were inoculated with PRRSV or/and PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI-1640 medium. Then, PAMs from these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post-infection, respectively. RT-qPCR analysis of TNF-α (A) and IL-1β (B) mRNAs in PAMs with different groups. Data are expressed as means ± SD of three independent experiments. Significant differences between groups are represented (* p < 0.05). | PMC10058123 | viruses-15-00777-g005.jpg |
0.414618 | 35918c6f5bac4066b756ea837e096881 | Relative mRNA expression of IL-10 and TGF-β. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co-infected groups (PCV2–PRRSV, PRRSV–PCV2 and PCV2 + PRRSV) were inoculated with PRRSV and/or PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI-1640 medium. Then, PAMs in these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post-infection, respectively. RT-qPCR analysis of TNF-α (A) and IL-1β (B) mRNA in PAMs from different groups. Data are expressed as means ± SD of three independent experiments. Significant differences between groups are represented (** p < 0.01, * p < 0.05). | PMC10058123 | viruses-15-00777-g006.jpg |
0.456349 | 9726b35a43294a0b9dc9d5d366103f4d | Relative mRNA expression of immune checkpoints. PAMs in the PCV2 alone group (PCV2), the PRRSV alone group (PRRSV) and the PCV2 and PRRSV co-infected groups (PCV2–PRRSV, PRRSV–PCV2 and PCV2 + PRRSV) were inoculated with PRRSV and/or PCV2 at a MOI of 1, respectively. PAMs in the mock group were inoculated with equal RPMI-1640 medium. Then, PAMs from these groups were collected at 6 h, 12 h, 24 h, 36 h and 48 h post-infection, respectively. RT-qPCR analysis of PD-1 (A), CTLA4 (B), LAG3 (C) and TIM3 (D) mRNAs in PAMs from different groups. Data are expressed as means ± SD of three independent experiments. Significant differences between groups are represented (** p < 0.01, * p < 0.05). | PMC10058123 | viruses-15-00777-g007.jpg |
0.544014 | 91bfc79a127c4cb68a2d217503292c6c | (a) Ground-state (S0) and (b) excited-state (S1) of 2-(2′-hydroxyphenyl)benzimidazole (HBI), structure and atomic numbering. A total of 27 substituted HBI structures were generated, including 1: HBI, 2: 3-Br-HBI, 3: 3-Et2N-HBI, 4: 3-HO-HBI, 5: 3-MeO-HBI, 6: 4-F-HBI, 7: 4-Cl-HBI, 8: 4-Br-HBI, 9: 4-CN-HBI, 10: 4-Me-HBI, 11: 4-MeO-HBI, 12: 10-Cl-HBI, 13: 10-Br-HBI, 14: 10-CN-HBI, 15: 10-Me-HBI, 16: 10-CF3-HBI, 17: 10-Ph-HBI, 18: 12-Ph-HBI, 19: 10-(p-MeO-Ph)-HBI, 20: 10-(p-MeCO2-Ph)-HBI, 21: 12-(p-MeO-Ph)-HBI, 22: 12-(p-MeCO2-Ph)-HBI, 23: 4-Me-10-Cl-HBI, 24: 4-Me-10-CF3-HBI, 25: 10-Ph-12-Ph-HBI, 26: 2-(CH2CH2CH=CH2)-8-(CH2CH2Ph)-HBI, 27: 2-F-3-F-4-F-5-F-HBI. Color code: hydrogen in white, carbon in grey, nitrogen in blue, and oxygen in red. | PMC10058485 | molecules-28-02576-sch001.jpg |
0.45234 | 363799fd317c4e189456ba2113c1e61a | Representative examples of commonly used ESIPT fluorophores. | PMC10058485 | molecules-28-02576-sch002.jpg |
0.662024 | b71a326ed84b4b54af6a082a127fdd4d | Molecules used to validate the transferability of the linear regression models. 37: 7-hydroxy-2,3-dihydro-1H-inden-1-one, 38: 1-hydroxy-9H-fluoren-9-one, 39: 1-hydroxy-11H-benzo[b]flu oren-11-one, 40: methyl salicylate, 41: 7-(2-pyridyl)indole, 42: 4,6-dimethyl-2-mercaptopyrimidine, 43: 10-malononitrile-benzo[h]quinoline. | PMC10058485 | molecules-28-02576-sch003.jpg |
0.447979 | f2a98de3f4064b76a1d15de1793e4d37 | Overlapping distribution of the Chikungunya virus and the probability of occurrence of Aedes mosquitos (A. aegypti and A. albopictus). Originally identified in Tanzania in 1952 (red), CHIKV has been reported in over 100 countries in Africa, Asia, the Pacific, Oceania, the Americas, and the Caribbean (light green). The expansion of CHIKV’s geographical distribution across the globe has been perpetuated by the presence of Aedes mosquitos in non-endemic regions. The widespread distribution of CHIKV’s most common vectors (A. aegypti and A. albopictus) puts half of the world’s population at risk of infection (dark green). | PMC10058558 | vaccines-11-00568-g001.jpg |
0.412436 | 30c693a474074f328bcdddc3a133f1f0 | Subsystems in VMD Process. | PMC10058618 | membranes-13-00339-g001.jpg |
0.371462 | 48e43384cdb545fca673f4ec0c31448b | Vacuum Membrane Distillation Process. | PMC10058618 | membranes-13-00339-g002.jpg |
0.488416 | 00a0babbadef43cd95675b7d989b1fd7 | Schematic for experimental setup: 1. Feedwater Pump, 2. Valve, 3. Feedwater Valve, 4. VMD Module, 5. Vacuum Pump, 6. Pressure Sensors, 7. Computer, 8. Flow Gauge, 9. Heater. | PMC10058618 | membranes-13-00339-g003.jpg |
0.430804 | f58796c00d294babb397667ef86d3ffe | Experimental Bench for VMD. | PMC10058618 | membranes-13-00339-g004.jpg |
0.473668 | 6ba71387e58c47128f5be6429ed66581 | Permeate flux for temperatures 50 °C, i.e., 333 K against feed concentration for different Pressure and Velocity Values for NaCl and KCl where, P1 = 30 kPa, P2 = 20 kPa, V1 = 3.48 m/s, and V2 = 5.22 m/s. | PMC10058618 | membranes-13-00339-g005.jpg |
0.501603 | 60a0bf64a2c84220905284d1a83a1a1a | Permeate flux for temperatures 60 °C, i.e., 343 K against feed concentration for different Pressure and Velocity Values for NaCl and KCl where, P1 = 30 kPa, P2 = 20 kPa, V1 = 3.48 m/s and V2 = 5.22 m/s. | PMC10058618 | membranes-13-00339-g006.jpg |
0.494063 | 61845c1a3ea1436eb12223d6037bf551 | Permeate flux for temperatures 70 °C, i.e., 353 K against feed concentration for different Pressure and Velocity Values for NaCl and KCl where, P1 = 30 kPa, P2 = 20 kPa, V1 = 3.48 m/s and V2 = 5.22 m/s. | PMC10058618 | membranes-13-00339-g007.jpg |
0.488921 | 64a72876ae4e44ee91743de1856a589a | Process Driving force. | PMC10058618 | membranes-13-00339-g008.jpg |
0.538666 | fb0d49adb6d64535aeac57d29dc966ad | Capital Cost of VMD plant as a function of distilled water production capacity in Liters per hour (L/H). | PMC10058618 | membranes-13-00339-g009.jpg |
0.483419 | fd368329fc6f4448b6951225e86b2e00 | Operating cost of VMD plant in (USD/L) as a function of production capacity. | PMC10058618 | membranes-13-00339-g010.jpg |
0.394874 | ecaccd31fa4f48d59cb2c1e249df2b50 | Breakeven for VMD plant of various scales. | PMC10058618 | membranes-13-00339-g011.jpg |
0.401132 | 13bb0c623a554f4f8a99156d11675219 | Proposed layout of VMD plants range of integration: (a) 64 VMD units and (b) 4 multi-effect vacuum membrane units. | PMC10058618 | membranes-13-00339-g012a.jpg |
0.467114 | c25697a4319844eea07ba4d1ae80ff92 | (I). Axial CT brain demonstrating measurement of the intercarotid distance. (II). Sagittal CT head, bone window in the mid-sagittal plane demonstrating measurement of the (a) thickness of the clivus at the level of the sellar floor as well as (b) at the thickest portion measurable and (c) height of the clivus from sellar floor to basion. | PMC10059731 | life-13-00601-g001.jpg |
0.447903 | 6a7fb999f4c24f0b9859bc6fbd45ce92 | (I) Proposed external array configuration demonstrating the clival array wiring exiting the nose in red. (II) Sagittal view of the clival array placement with transnasal wiring. (Created with BioRender.com). | PMC10059731 | life-13-00601-g002.jpg |
0.409796 | a74c56a5d6e04468aa9c7433f59b4950 | Transnasal view of proposed placement of a flexible array affixed to the clivus. | PMC10059731 | life-13-00601-g003.jpg |
Subsets and Splits