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0.416252 | 7f318fd9b3e14654b5554253fa7a48a0 | Human tissue microarray of normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Morphology of representative H&E staining from the human tissue microarray of esophageal cases, from left to right: normal squamous, BE-NFD, BE-LGD, BE-HGD, and EAC. (B) Morphology of representative PAS staining from the human tissue microarray of esophageal cases, same sequence as in (A). (C) Morphology of representative H&E staining from the human tissue microarray of gastric cases, from left to right: normal gastric corpus (left inset from base of the glands, right inset from the surface of the glands), GIM, and GA. (D) Morphology of representative PAS staining from the human tissue microarray of gastric cases, in the same sequence as in (C). All scale bars, 500 μm. | PMC10040611 | fcell-11-1151790-g001.jpg |
0.481874 | cec711f7735d452db1b8ffd230eaf807 | TFF2 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of TFF2 staining in human tissue microarray esophageal cases, from left to right: normal squamous, BE-NFD, BE-LGD, BE-HGD, and EAC. (B) Immunohistochemistry of TFF2 staining in human tissue microarray gastric cases, from left to right: normal gastric corpus (left inset from base of the glands, right inset from the surface of the glands), GIM, and GA. All scale bars, 500 μm. (C) Analysis of the human esophageal tissue microarray with normal squamous, BE-NFD, BE-LGD, BE-HGD, and EAC tissue cores stained by immunohistochemistry for TFF2. Top: the TFF2 average IHC intensity score of each esophageal phenotype is plotted. For staining intensity, score 0 (undetectable) to 3 (most intense). Bottom: the TFF2 fraction of esophageal tissue cores with each score is plotted. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Analysis of the human gastric tissue microarray with normal, GIM, and GA tissue cores stained by immunohistochemistry for TFF2. Top: the TFF2 average IHC intensity score of each gastric phenotype is plotted. For staining intensity, score 0 (undetectable) to 3 (most intense). Bottom: the TFF2 fraction of gastric tissue cores with each score is plotted. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g002.jpg |
0.452245 | 3bcb73eb0e72479aa68b83e749381353 | TFF3 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of TFF3 staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of TFF3 staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the TFF3 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the TFF3 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the TFF3 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the TFF3 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g003.jpg |
0.469614 | 4b76c46c05e74948bd20794465ca9ed0 | MUC2 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of MUC2 staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of MUC2 staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the MUC2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the MUC2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the MUC2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the MUC2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g004.jpg |
0.426894 | 98fba437fa3f4dc19446c5ec3975623a | MUC5AC expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of MUC5AC staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of MUC5AC staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the MUC5AC average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the MUC5AC fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the MUC5AC average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the MUC5AC fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g005.jpg |
0.435333 | 314ad15cdb3f4e089dda449bf75f1915 | MUC6 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of MUC6 staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of MUC6 staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the MUC6 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the MUC6 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the MUC6 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the MUC6 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g006.jpg |
0.458289 | b9d4622cb7a44bb69a954fe34730f72f | CDX2 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of CDX2 staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of CDX2 staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the CDX2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the CDX2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the CDX2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the CDX2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g007.jpg |
0.456327 | 59cc7aa60ab04df693525623f6464109 | SOX2 expression in normal squamous-BE-EAC and normal gastric gland-GIM-GA progression sequence. (A) Immunohistochemistry of SOX2 staining in human tissue microarray esophageal cases, in the same sequence as in Figure 2A. (B) Immunohistochemistry of SOX2 staining in human tissue microarray gastric cases, in the same sequence as in Figure 2B. All scale bars, 500 μm. (C) Top: the SOX2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2C. Bottom: the SOX2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2C. Each phenotype’s total tissue core number is provided at the bottom of each column. (D) Top: the SOX2 average IHC intensity score of each esophageal phenotype is plotted in the same sequence as in Figure 2D. Bottom: the SOX2 fraction of esophageal tissue cores with each score is plotted in the same sequence as in Figure 2D. Each phenotype’s total tissue core number is provided at the bottom of each column. | PMC10040611 | fcell-11-1151790-g008.jpg |
0.444881 | 7dbb24439fa54d11a008454dc899f7db | (A) Absorbance spectrum of the colloidal AgNs and (B–D) TEM images of nanostars on a carbon grid. | PMC10040700 | gr1.jpg |
0.446501 | bc626fbe9d3743a2a87d4041d2dcc8ea | AgNs film characterization: (A) Optical absorbance (B) Photographs of the AgNs films surface on the glass substrates (C) SEM images: (a) 1 layer of AgNs film (b) 5 layers of AgNs film (c) 10 layers of AgNs films. | PMC10040700 | gr2.jpg |
0.378352 | dc18197721e14b739a26bd25aa5cfc20 | (A) Raman spectrum of the imidacloprid powder using 100% power laser and the chemical structure of the imidacloprid (B) SERS spectrum of imidacloprid on 1 layer, 5 layers, 10 layers and 15 layers of AgNs surface using 1% power laser. The spectrum on bare glass is provided for reference using 1% power laser. | PMC10040700 | gr3.jpg |
0.445536 | ed0d05e0ba1d42628e3d399ec1702f13 | (A) SERS measurement of imidacloprid (1 mg/ml) for 5 different spots on the 10 layer substrate (a complete set of spectra from 20 spots is provided in the SI, Fig. S2(A)) (B) RSD for three peaks from the 20 different spots (C) SERS measurements for 5 different samples of imidacloprid (1 mg/ml) on 10 layers of AgNs surface (a complete set of spectra from 20 samples is provided in the SI, Fig. S2(B)) (D) RSD for 20 different samples of imidacloprid (1 mg/ml) on 10 layers of AgNs surface. | PMC10040700 | gr4.jpg |
0.440559 | 884a869383c84a6abddd3bcb785235c1 | Sections of the segmented patient model (gray) at the original resolution of 1mm, with superimposed target volume (cyan). | PMC10000505 | cancers-15-01447-g001.jpg |
0.423064 | 95962db05f2d4a44a03761f9b66ebfb4 | Self-grounded bow-tie antenna optimized for the 250–500 MHz band. The antenna’s polarization axis u is aligned with the x axis (red), while its main directivity axis w is aligned with the z axis (blue). The center of the antenna’s local coordinate system corresponds to the center of its ground plate, which is also the center of the circular feed opening. The overall dimensions are 8.7cm along x, 6.2cm along y, and 2.4cm along z. | PMC10000505 | cancers-15-01447-g002.jpg |
0.451267 | d1027746be9f4fb39df2a5479967f3b8 | Patient model (gray) down-sampled to a 4mm resolution, together with the water bolus shape (blue). The ellipsoid is designed to maintain a bolus thickness as close as possible to 5cm around the scalp and is clipped right above the shoulders and nostrils to allow for breathing. The resulting bolus dimensions are 25.0cm along the left-right axis, 28.4cm along the anterior-posterior axis, and 22.1cm along the cranial-caudal axis. | PMC10000505 | cancers-15-01447-g003.jpg |
0.429879 | 32fe458278cc4fe99621ce39fa48ea59 | Reference schematic for the arrangement of a single antenna. Note that the angle ϕ, while following the classic right-hand convention, is shown here on the negative y half-space for readability. The figure refers to a local coordinate system centered at the ellipsoid’s center and aligned with the global cartesian axes. | PMC10000505 | cancers-15-01447-g004.jpg |
0.499586 | 72fe1339d4784ec8a4b73c9eda1796a2 | Interpolation grid made of 221 points (black) uniformly distributed around the child patient model (gray) and lying on the surface of a fitted ellipsoid. The average distance between pairs of nearby points is 2.6cm. | PMC10000505 | cancers-15-01447-g005.jpg |
0.428185 | 60fc87cc0cb042d1a51150b6217f793e | Reference schematic for the field interpolation procedure, using a less dense grid to facilitate reading. The ellipsoid is shown in its entirety to highlight the different radii. However, in the actual simulation model, the bolus was clipped at the level of the shoulders. We show the ellipsoid center C and its radii a, b, c. The interpolation grid is shown with black circles. The selected interpolation patch (O1,O2,O3) for an antenna at location Oa is highlighted with thick black edges and yellow vertices. The local coordinate systems of the selected grid points are also shown. An equivalent system was built for the query antenna location Oa. | PMC10000505 | cancers-15-01447-g006.jpg |
0.421037 | b1410607af0a45e29fd271c6e473c47f | Procedure to determine the coupling between antenna pairs. A spherical brain phantom (a) was inserted into a spherical bolus (b). An active (A) and a passive (P) antenna were added inside the bolus. First, the individual fields EA and EP of each antenna were determined without the presence of the other antenna. Subsequently, the active antenna was excited with the presence of the passive antenna and the overall coupled field EA+P was determined. A correlation factor between the coupled field EA+P and the passive antenna field EP was determined. This was found to be proportional to the projection on UP of the individual field EA at the location of the passive antenna (c). | PMC10000505 | cancers-15-01447-g007.jpg |
0.427722 | d4d709c994124afdaf092d42e4105950 | Correlation between the projection eAP of the active antenna’s field EA on the passive antenna’s polarization axis UP at OP′, and the coupling coefficient kAP obtained by decorrelation of the remainder field EA+P−EA with respect to EP. The results are reported for each frequency in the operating set. The solid black lines show the fitted complex coupling coefficient c, while the legends report the correlation coefficients for each fit. The fit was carried out on the complex values. | PMC10000505 | cancers-15-01447-g008.jpg |
0.463379 | 713b3d4cbe7b4cf894c687ee805d8288 | Location sweep for the sensitivity analysis of the field interpolation error. The black circles represent the interpolation grid points. The yellow dots are the grid points selected for interpolation, and are the corners of the triangular patch of largest area. The gray shade is the patient in bird’s eye view. The local coordinate systems of each antenna location to be approximated are shown as superimposed triplets. | PMC10000505 | cancers-15-01447-g009.jpg |
0.415617 | ed588f8d07eb46af985124cfd47db92b | Applicator optimization procedure to determine the best antenna arrangement for a given patient. The procedure begins at the red step and ends at the green step. The steps highlighted in blue involve the sub-steps shown in (b) to determine the cost-function value of a certain array arrangement. | PMC10000505 | cancers-15-01447-g010.jpg |
0.479494 | 11da9442021844969c0c8f477f14e584 | Canonical applicator designs with increasing number of antenna elements (nc) for the medulloblastoma pediatric patient model (gray) using the fitted ellipsoidal water bolus shape (blue). | PMC10000505 | cancers-15-01447-g011.jpg |
0.415174 | 35bbf7c1a6b74e21bee4aaf66412e6c7 | Comparison of the normalized SAR distributions obtained via approximation (INT) and full simulation (SIM) for the optimized applicator design of order nc=08. Sections of the SAR distribution inside the patient model, taken at the target center. The volumes in magenta represent the highest q-percentile in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile in the target (cold spot). The difference (DIF) distribution is relative to the simulated one, i.e., SARDIF=|SARSIM−SARINT|/|SARSIM|. In (b,e), the volumes in magenta represent hot-spot coverage (HSIM∩HINT), while the volumes in cyan represent cold-spot coverage (CSIM∩CINT). The volumes in red represent hot-spot exclusion (HSIM⊕HINT), while the volumes in blue represent cold-spot exclusion (CSIM⊕CINT). | PMC10000505 | cancers-15-01447-g012.jpg |
0.446964 | bdf5dcf5d58e4cf2ae8fc51b71cf38b5 | Optimized applicator designs with increasing number of antenna elements (nc) for the medulloblastoma pediatric patient model (gray) using the fitted ellipsoidal water bolus shape (blue). | PMC10000505 | cancers-15-01447-g013.jpg |
0.504156 | d64f7b7227264f92991f69a18402d588 | Average relative error between the interpolated and simulated E-field distributions of a single antenna at increasing distance from a grid point for different frequencies across the operating band. The step indicates the position of the antenna within the interpolation patch, where zero corresponds to one of the simulated corners. A phase error ϵANG of 100% means that the fields are in opposition. A direction error ϵDIR of 100% means that the fields are orthogonal. | PMC10000505 | cancers-15-01447-g014.jpg |
0.453782 | 63b7458d4cb94f0abb54686fa4976dec | Values of HCQ, T50 and T90 relative to the treatment plans prepared using canonical and optimized applicator designs of increasing order (line plots). The values for the canonical applicator designs are also reported as scatter plots. In SAR, the value of HCQ predicted by the field approximation is compared against the value from the actual simulated field. | PMC10000505 | cancers-15-01447-g015.jpg |
0.3974 | a2f6c3109d744c1fa369df47ae89eb35 | Normalized SAR distributions relative to each optimized applicator design with increasing number of antenna elements (nc). Sections taken at target center. The white line delineates the target volume. The volumes in magenta represent the highest q-percentile (2.8%) in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile (50%) in the target (cold spot). | PMC10000505 | cancers-15-01447-g016.jpg |
0.408019 | 8df233f4e64d4d91b64a471bb9c2fef8 | Temperature distributions relative to each optimized applicator design with increasing number of antenna elements (nc). Sections taken at target center. The views are flipped to show the side where the temperature peak in the healthy tissue is located, marked with a black dot, which is located off plane with respect to the sections. The white line delineates the target volume. | PMC10000505 | cancers-15-01447-g017.jpg |
0.430272 | f3dd49d719c8458ebaf8d393e0f74b96 | Comparison of the normalized SAR distributions obtained via approximation (INT) and full simulation (SIM) for the canonical applicator design of order nc=10. Sections of the SAR distribution inside the patient model, taken at the target center. The volumes in magenta represent the highest q-percentile in the remaining healthy tissue (hot spot), while the volumes in cyan represent the lowest p-percentile in the target (cold spot). The difference (DIF) distribution is relative to the simulated one, i.e., SARDIF=|SARSIM−SARINT|/|SARSIM|. In (b,e), the volumes in magenta represent hot-spot coverage (HSIM∩HINT), while the volumes in cyan represent cold-spot coverage (CSIM∩CINT). The volumes in red represent hot-spot exclusion (HSIM⊕HINT), while the volumes in blue represent cold-spot exclusion (CSIM⊕CINT). The white circle in (d–f) highlights the location of the hot-spot misidentification. | PMC10000505 | cancers-15-01447-g018.jpg |
0.443109 | 105c0007c1a64be2b535270b76cac49b | Geometrical setup for the canonical applicator design of order nc=10. The patient model (gray) is shown together with the antenna local coordinate systems, where the red vector is U, the green vector is V, and the blue vector is W. The antenna center is represented by a black dot and labeled with the channel number. The target volume is highlighted in yellow. | PMC10000505 | cancers-15-01447-g019.jpg |
0.422459 | 4c7fb6907a804f028791c8505eb20c2c | Schematic illustration of nanoparticle formation using ultrasonication and coating of shrimp using the LPE-added alginate-based nanoparticle edible coating. | PMC10000639 | foods-12-01103-g001.jpg |
0.470072 | a2f3f7a715d149f08e57cf5865dd6b4e | The pH (A), viscosity (B), and turbidity (C) of the alginate coating and alginate-based nanoparticle coating with different concentration of LPE. C: distilled water; T1: alginate coating; T2, T3, and T4: alginate-based nanoparticle coating with 0.5, 1.0, and 1.5% LPE, respectively. The different alphabets shown on the bar diagram indicate significant differences. | PMC10000639 | foods-12-01103-g002.jpg |
0.460004 | 228e183ca16a45358f07e2141868b5d4 | Whiteness index (A), particle size (B), polydispersity index (C) of the alginate coating and alginate-based nanoparticle coating with different concentration of LPE. C: distilled water; T1: alginate coating; T2, T3, and T4: alginate-based nanoparticle coating with 0.5, 1.0, and 1.5% LPE, respectively. The different alphabets shown on the bar diagram indicates significant differences. | PMC10000639 | foods-12-01103-g003.jpg |
0.487476 | d924a22ec2124ba6855dfc91dcb618b4 | Changes in weight loss (A) and pH (B) of the shrimps coated with different coatings during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g004.jpg |
0.433236 | 007b63180b5b4c109e40237a2074b147 | Changes in polyphenol oxidase of the shrimps coated with different coatings during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g005.jpg |
0.46303 | 5f8f86014a134ebfb6ae0f1bd2c673f2 | Changes in total sulfhydral content (A), reactive sulfhydral content (B), and carbonyl content (C) of the shrimps coated with different coatings during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g006.jpg |
0.501426 | 2b84a2464c584c0abaa47281906249e6 | Changes in PV (A), TBARS (B), p-anisidine value (C), and totox value (D) of the shrimp coated with different coating during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g007.jpg |
0.429206 | c8399c3facf1491397ee1aecb2f4d0c1 | Changes in TVB-N value of the shrimps coated with different coatings during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g008.jpg |
0.499638 | efc6de17cdb74f5a80875fde05609666 | Changes in TVC (A), Lactic acid bacteria (B), Enterobacteriacea (C), and Psychrotrophic bacteria (D) of the shrimps coated with different coating during storage of 14 days at 4 °C. C: shrimp dipped in distilled water as control; T1: shrimp coated with alginate coating; T2, T3, and T4: shrimp coated with 0.5, 1.0, and 1.5% LPE, respectively. | PMC10000639 | foods-12-01103-g009.jpg |
0.444542 | bd2a8230bd344ee9b8c2e46da6b423ec | Principal component analysis (PCA). | PMC10000647 | foods-12-01089-g001.jpg |
0.382185 | 569dc14594da4b05a676ce73adc4025f | Salami in the last seasoning period. | PMC10000647 | foods-12-01089-g0A1.jpg |
0.410388 | a8a7f46906a749b08a453a75da290111 | (a) A simplified flow chart of the patient selection process. (b) A simplified flow chart for constructing the MRI image feature model to predict α-and β-genotypes in TM patients. | PMC10000720 | diagnostics-13-00958-g001.jpg |
0.505466 | bb2a2d6fed7f4efc83ea6a524586ccdf | (a,b) ROC curves of α- and β-genotyping of thalassemia patients in the T2 model, clinical model, and joint model. (c,d) ROC curves of each radiomics model. Note—T2 flade fs = T2 fblade fs/T2 ssfse tra bh. | PMC10000720 | diagnostics-13-00958-g002.jpg |
0.481856 | b0f13ecb80fb40eb8f3a0ef0788dcfb8 | Radiomics feature dimensionality reduction LASSO coefficient distribution map ((a–f) correspond to the T2, T2*, T1 vibe dixon opp, T1 vibe dixon in, T1 vibe dixon F, and T1 vibe dixon W models, respectively). Each curve represents the change trajectory of the independent variable coefficient corresponding to different penalty coefficients, and the dotted lines are the minimum penalty coefficients. | PMC10000720 | diagnostics-13-00958-g003a.jpg |
0.466059 | 248c51df269c4c17a5edddb97dbf7066 | The best omics features of different image omics models are as follows: T2 model Rad score (a) = 3.53346224020733 × lbp_3D_k_firstorder_Skewness + 1.07465494102622 × log_sigma_3_0_mm_3D_glcm_MCC + 1.78127454519169 × 10−2 × wavelet_HHL_firstorder_Kurtosis + 8.36953869311654 × 10−4 × wavelet_LLH_glrlm_LongRunHighGrayLevelEmphasis + 7.22569069179091 × 10−4 × original_glrlm_LongRunLowGrayLevelEmphasis − 1.77115252453958 × 10−3 × original_gldm_LargeDependenceHighGrayLevelEmphasis − 7.0101953054909 × 10−3 × lbp_3D_k_glszm_SizeZoneNonUniformity − 2.62091113931379 × wavelet_HHH_firstorder_Skewness − 3.11332596350631 × lbp_3D_k_gldm_DependenceNonUniformityNormalized − 6.20776724661879 × (Intercept) − 6.66761355299743 × log_sigma_2_0_mm_3D_glcm_Imc1 − 17.566640428635 × wavelet_LHH_ngtdm_Contrast. T2* model Rad-score; (b) = 2.50144266068886 × (Intercept) − 1.24913107460922 × 10−5 × original_gldm_LargeDependenceHighGrayLevelEmphasis − 6.24916156246217 × 10−5 × wavelet_LLL_glrlm_LongRunHighGrayLevelEmphasis − 4.08064312178882 × 10−4 × original_glrlm_LongRunHighGrayLevelEmphasis − 1.75768099910874 × original_glcm_Correlation. T1 vibe dixon opp model Rad-score; (c) = 6.27425742182574 × original_glcm_Imc1 + 5.37994776377167 × (Intercept) + 3.70616662130978 × wavelet_LHH_firstorder_Mean + 0.516626652535698 × wavelet_LHL_firstorder_Median + 0.0565285647399182 × wavelet_LLL_firstorder_Skewness − 0.00597233533241726 × wavelet_HHL_firstorder_Kurtosis − 0.0176135434925847 × original_glcm_MCC-3.83246459948815 × original_shape_Elongation. T1 vibe dixon in model Rad-score; (d) = 127.086320720469 × wavelet_HLH_ngtdm_Strength + 18.667830611436 × wavelet_LHH_gldm_SmallDependenceEmphasis + 5.72164956963507 × (Intercept) + 4.87874941478956 × wavelet_HLL_glcm_MCC + 2.65747466451841 × wavelet_LHL_ngtdm_Strength + 0.087457883090257 × wavelet_HHH_glrlm_ShortRunHighGrayLevelEmphasis + 0.0356125450830294 × wavelet_LHL_firstorder_Kurtosis − 10.1682627437812 × wavelet_LLL_glcm_MCC-88.0170431265614 × lbp_3D_k_glcm_Imc1. T1 vibe dixon F model Rad-score; (e) = 51.3219769208571 × lbp_3D_m2_glrlm_ShortRunLowGrayLevelEmphasis + 17.3682101660547 × wavelet_HLH_firstorder_Mean + 3.95718718046264 × (Intercept) + 3.52431026532541 × wavelet_LLH_glszm_SmallAreaEmphasis + 2.87681895035553 × wavelet_LLL_glcm_Imc1 − 9.7943125275996×10−5 × wavelet_LLH_gldm_DependenceNonUniformity − 0.0338412742628526 × wavelet_LLH_glrlm_RunVariance − 5.8097236730315 × 10−2 × lbp_3D_m1_firstorder_InterquartileRange − 2.49038445966763 × wavelet_HLH_ngtdm_Contrast − 5.42813421361219 × lbp_3D_k_glszm_SizeZoneNonUniformityNormalized. T1 vibe dixon W model Rad-score; (f) = 5.26762029862077 × (Intercept) + 2.73411114054784 × lbp_3D_k_glcm_Correlation + 0.839563442800306 × wavelet_LHH_glcm_MCC + 0.227753966581487 × original_firstorder_Skewness + 0.106672491336863 × wavelet_HHH_firstorder_Kurtosis − 2.23550830619043×10−4 × wavelet_LHH_ngtdm_Busyness − 0.205280111379976 × wavelet_HLL_glcm_ClusterShade − 4.44029239333195 × wavelet_HLL_glszm_SmallAreaLowGrayLevelEmphasis − 5.25648829872901 × wavelet_LLL_glcm_MCC. Nomogram map of the joint model constructed from T2 image features and clinical features is as Figure 4g. | PMC10000720 | diagnostics-13-00958-g004a.jpg |
0.480666 | 3b2f1c4bc5c8428fbbac7b1bc3a4c64f | Calibration curve and decision curve analysis. The calibration curves of the training group (a) and the validation group (b) prove that the Rad scores of the T2 model, the clinical model, and the joint model have good fitness. (c) Decision curve analysis of the T2 model, the clinical model, and the joint model. The Y-axis represents the net benefit, which is calculated by adding up the benefits (gaining true positives) and subtracting the weighted harms (deleting false positives). A model is considered the best method for feature selection if it has the highest net benefit. Note—T2 flade fs = T2 fblade fs/T2 ssfse tra bh. | PMC10000720 | diagnostics-13-00958-g005a.jpg |
0.484023 | a7f187f9cef04ff7a031239eddb7fdb8 | (a–f) represent the Rad score distributions of the training group and the validation group in the T2, T2*, T1 vibe dixon opp, T1 vibe dixon in, T1 vibe dixon F, and T1 vibe dixon W models, respectively. Box plots showed significant differences in Rad scores between Label 0 (α- genome) and Label 1 (β- genome) in different models (p < 0.05). | PMC10000720 | diagnostics-13-00958-g006a.jpg |
0.414276 | d0615cea2cc84c288016beae9e12a7b5 | (a) (Adult) is the original MRI image of the largest cross section of the liver T2 sequence. (b) (Adult) is a sequence image of liver T2 manually segmented by ITK-SNAP. (c) (Fetus) is the original MRI image of the largest cross section of the liver T2 sequence. (d) (Fetus) is a sequence image of liver T2 manually segmented by ITK-SNAP. | PMC10000720 | diagnostics-13-00958-g0A1.jpg |
0.478847 | d947f3c3c1994de8959b2a2a82b4dd42 | Hypothesised relation between 3D printing and OPS (time, cost, quality, public health and safety and environment). | PMC10000831 | ijerph-20-03800-g001.jpg |
0.436786 | c85aca5efaac497798d1305ff83f1f6f | Research methodology flowchart. | PMC10000831 | ijerph-20-03800-g002.jpg |
0.397873 | 65f8f64e8f744edbb6711f5e00a77c54 | Demographic profile. | PMC10000831 | ijerph-20-03800-g003.jpg |
0.462157 | daece5b28d7c45eebfbd7e5526e64be7 | Structural model with path coefficients. | PMC10000831 | ijerph-20-03800-g004.jpg |
0.434715 | e9d4abf8c9cc4ffdb38473a007455318 | Bootstrapping analysis showing outer path indicating loading and p-values and inner weights with p-values. | PMC10000831 | ijerph-20-03800-g005.jpg |
0.396917 | 3b1101d34b7941f492b5233b05b63c6e | Proposed pathway for the interaction of OA with xenobiotic metabolism in HepaRG cells. OA is able to activate NF-κB, which leads to the translocation of p50 and p60 into the nucleus, where they act as transcription factors, leading to the expression of cytokines. The cytokines, such as IL-6 or TNFα, are released into the surrounding medium by the cells, where they can bind to a cytokine receptor of the same or a neighboring cell. The cytokine receptor is associated with a JAK. Binding of the cytokine leads to dimerization of the receptors, which in turn leads to the JAKs phosphorylating each other. STATs are then able to bind to the JAK, where they are also phosphorylated. Phosphorylated STATs dimerize and translocate into the nucleus, where they can act as a transcription factor to other proteins influencing the CYPs and to SOCS3, a direct target of the JAK/STAT signaling pathway, which is able to deactivate JAK signaling in a feedback loop. | PMC10000888 | cells-12-00770-g001.jpg |
0.448604 | 0b84357f0dfb4f068aabf91b4b01bfca | Relative expression of CYP1A1, CYP2B6 and CYP3A4, PXR, and RXRα. (A): Differentiated HepaRG cells were treated with 11, 33, and 100 nM OA or with the respective solvent control for 24 h. Analysis of RNA levels of CYP1A1, CYP2B6, CYP3A4, PXR, and RXRα in HepaRG cells after exposure to OA was performed by qPCR. The bar charts show the resulting fold changes as mean of three independent replicates, relative to the solvent control. (B): Transactivation of PXR and RXRα in HEK-T cells. The cells were transfected with plasmids before incubation with OA for 24 h. SR12813 (10 µM) and CD2608 (100 nM) were used as positive controls. The cytotoxicity assay in HEK-T cells relevant for the chosen OA concentrations for the transactivation assay can be found in Figure S1. The bar charts show the resulting fold changes as mean of three independent replicates, relative to the solvent control. Statistical analysis for all charts (n = 3) was performed using one-way ANOVA followed by Dunnett’s post-hoc test (* p < 0.05; ** p < 0.01; *** p < 0.001). | PMC10000888 | cells-12-00770-g002.jpg |
0.478435 | f60c4cc126e945aa85f3dd0838c0dccf | Activation of NF-κB in HepaRG cells. Differentiated HepaRG cells were treated with 33 and 100 nM OA alone or 33 µM OA in combination with 30 µM JSH-23, or 30 µM Methysticin, two NF-κB activation inhibitors, or with the respective solvent control for 24 h. (A): Nuclei were stained with DAPI, and the actin cytoskeleton was stained using ActinGreen™ 488 ReadyProbes™ reagent. Immunostaining of NF-κB was carried out using a primary antibody against NF-κB subunit p65 and stained using a secondary antibody conjugated with the fluorophore Alexa Fluor™ 633. Fluorescence was detected using a confocal laser scanning microscope at ex wavelengths of 405 nm (DAPI, blue), 488 nm (ActinGreen, green), and 633 nm (NF-κB, red). Z-stacks spanning through the entire cell layer were recorded at 63× magnification. Brightness was increased by 15% for the green channel, 60% for the blue channel, and 70% for the red channel in each image. (B): The nuclear fluorescence ratio was determined using ImageJ 1.53e. Nuclei were marked as ROI and the fluorescence intensity of the red and blue channels in each ROI was determined separately. A ratio of NF-κB/DAPI signal intensity was then calculated and normalized to the mean of the solvent controls. The nuclei were divided into groups based on their signal intensity. Results show the number of nuclei per signal intensity group for each treatment group. Between 65 and 99 nuclei were evaluated per condition. Statistical analysis was performed using Wilcoxon rank-sum test (** p < 0.01; *** p < 0.001). (C): Results of the DigiWest analysis for p100/p52, IκBα, IKKβ, and RelB. Results were obtained using 3 pooled replicates. | PMC10000888 | cells-12-00770-g003.jpg |
0.441398 | b317cd0b6af24b01b1989208fe2706c9 | RNA expression and release of Interleukins in HepaRG cells after exposure to OA. Differentiated HepaRG cells were treated with 11, 33, and 100 nM OA alone or 33 µM OA in combination with 30 µM JSH-23, or 30 µM Methysticin, two NF-κB activation inhibitors, or with the respective solvent control for 24 h. (A): Analysis of mRNA levels of interleukins was performed by qPCR. The heatmap shows the log2 values of the resulting fold changes as mean of six (heatmap left) or three independent replicates, relative to the solvent control. Statistical analysis (n = 6, n = 3) was performed against the solvent control (heatmap left) or the 33 nM OA sample (rest) using one-way ANOVA followed by Dunnett’s post-hoc test (* p < 0.05; ** p < 0.01; *** p < 0.001). (B): Release of IL-6 and IL-8 from HepaRG cells into the cell culture supernatant after exposure to OA. The IL-content in the cell culture supernatant was quantified using Luminex multiplex assay. Statistical analysis (n = 3) was performed against the solvent control using one-way ANOVA followed by Dunnett’s post-hoc test (* p < 0.05; ** p < 0.01; *** p < 0.001). LLOQ IL-6: 12.89 pg/mL; LLOQ IL-8: 2.54 pg/mL. (C): Release of IL-6 and IL-8 from HepaRG cells into the cell culture supernatant after exposure to OA in combination with the inhibitors. The content in the supernatant was analyzed as described in Figure 2B. (D): Analysis of RNA levels of CYP1A1, CYP2B6, and CYP3A4 by qPCR in HepaRG cells after exposure to OA and the inhibitors. The bar charts show the resulting fold changes as mean of three independent replicates, relative to the solvent control. Statistical analysis for both (C) and (D) (n = 3) was performed against the 33 nM OA sample using one-way ANOVA followed by Dunnett’s post-hoc test (* p < 0.05; ** p < 0.01; *** p < 0.001). | PMC10000888 | cells-12-00770-g004.jpg |
0.396094 | 9d27968d9d0840ca933a0e68a59ccfea | Activation of JAK/STAT signaling in HepaRG cells after exposure to OA. Differentiated HepaRG cells were treated with 33 and 100 nM OA alone or 33 µM OA in combination with 40 µM Decernotinib, or 40 µM Tofacitinib, two JAK activation inhibitors or with the respective solvent control for 24 h. (A): Nuclei were stained with DAPI, and the actin cytoskeleton was stained using ActinGreen™ 488 ReadyProbes™ reagent. Immunostaining of STAT3 was carried out using a primary antibody against phosphorylated STAT3 and stained using a secondary antibody conjugated with the fluorophore Alexa Fluor™ 633. Fluorescence was detected using a confocal laser scanning microscope at ex wavelengths of 405 nm (DAPI, blue), 488 nm (ActinGreen, green), and 633 nm (phosphoSTAT3, red). Z-stacks spanning through the entire cell layer were recorded at 63× magnification. Brightness was increased by 40% for the blue and red channels in each image. (B): The nuclear fluorescence ratio was determined using ImageJ 1.53e. Nuclei were marked as ROI and the fluorescence intensity of the red and blue channels in each ROI was determined separately. A ratio of pSTAT3/DAPI signal intensity was then calculated and normalized to the mean of the solvent controls. The nuclei were divided into groups based on their signal intensity. Results show the number of nuclei per signal intensity group for each treatment group. Between 96 and 142 nuclei were evaluated per condition. Statistical analysis was performed against the solvent control using Wilcoxson rank-sum test (*** p < 0.001). (C): Western blot of lysed HepaRG cells against phosphorylated STAT3. Cells were incubated as described above with the addition of 30 µM JSH-23 and 30 µM Methysticin alone or in combination with 33 nM OA. Western blot were obtained using the wet blot method. Three biological replicates were independently analyzed and normalized against the housekeeper GAPDH. Afterwards, all samples were normalized against their respective solvent control. (D): Analysis of RNA levels of CYP1A1, CYP2B6, and CYP3A4 by qPCR in HepaRG cells after exposure to OA and the inhibitors. The bar charts show the resulting fold changes as mean of three independent replicates, relative to the solvent control. Statistical analysis (n = 3) was performed against the 33 nM OA sample using one-way ANOVA followed by Dunnett’s post-hoc test (* p < 0.05; ** p < 0.01; *** p < 0.001). (E): DigiWest results for JAK1 and JAK2. Three independent replicates were incubated and combined before measuring. (F): The nuclear fluorescence ratio was determined as in (B). Between 109 and 142 nuclei were evaluated for each condition. Statistical analysis was performed against the 33 nM OA sample using Wilcoxson rank-sum test (** p < 0.01; *** p < 0.001). | PMC10000888 | cells-12-00770-g005.jpg |
0.448959 | 4b6be98917c9436b8262edb6580be482 | Study design. | PMC10001139 | diagnostics-13-00903-g001.jpg |
0.37934 | c215f55a8b674905ace60c8da0dd018e | Differences in periodontal clinical parameters at baseline and 1 month after anti-infective periodontal treatment. The linear regression line is shown in different colors for each subject: (A) PD = probing depth; (B) BOP = bleeding on probing; (C) CAL = clinical attachment level; (D) PI = plaque index. | PMC10001139 | diagnostics-13-00903-g002a.jpg |
0.437954 | 373828d69d8f4e63a39edcd651c95bd1 | Scatter plots of the association of anti-infective periodontal treatment with smoking versus non-smoking subjects: (A) PD = probing depth; (B) BOP = bleeding on probing; (C) CAL = clinical attachment level; (D) PI = plaque index. | PMC10001139 | diagnostics-13-00903-g003a.jpg |
0.428339 | cc0691a622b2430caa3dcb96ed47444e | Differences in the mean levels of diagnostic marker aMMP-8 (Oralyzer®), IFMA aMMP-8: Pretreatment—baseline; Post-treatment—1 month following anti-infective periodontal treatment. (A) Estimated Marginal Means of aMMP-8 PoC test; (B) Estimated Marginal Means of aMMP-8 IFMA. | PMC10001139 | diagnostics-13-00903-g004.jpg |
0.422475 | fce07d4d950d486b9f19da372adbb05b | Scatter plot diagrams showing the effect of anti-infective periodontal treatment on aMMP-8 levels: (A) Oralyzer®’ (B) IFMA; (C) regression lines of means. | PMC10001139 | diagnostics-13-00903-g005a.jpg |
0.439578 | 6e0f2305dce94abb8934f729f484c188 | Receiver operating characteristic (ROC) analysis tested for screening diagnostic ability of aMMP-8 PoC and IFMA tests to discriminate between periodontitis and periodontal health. | PMC10001139 | diagnostics-13-00903-g006.jpg |
0.481122 | 0ba9efd7eb2d4413bb9c002b7d7a0544 | Representative Western immunoblot for molecular forms and species of MMP-8/collagenase-2 in the studied mouth rinse samples: (A) Lane 1: recombinant human MMP-8 (100 ng), monoclonal antibody; Lane 2: mouth rinse sample of systemically and orally healthy subject, monoclonal antibody; Lane 3: mouth rinse sample of systemically and orally/periodontally diseased subject before anti-infective treatment, monoclonal antibody; Lane 4: mouth rinse sample of systemically and orally diseased subject after anti-infective treatment; PMN indicates polymorphonuclear leukocyte; pMMP-8 indicates latent proMMP-8; aMMP-8 indicates active MMP-8; fragments indicate lower (<50 kDa) molecular size MMP-8 species due the activation and related fragmentation; (B) negative (−, one line, <20 ng/mL aMMP-8, Lane 1) and positive (+, two lines, ≥20 ng/mL aMMP-8, Lane 2) chairside (PoC) lateral-flow immunotest outcomes indicated by arrows on the right. | PMC10001139 | diagnostics-13-00903-g007.jpg |
0.444418 | 04fa49191ef64797b73c1ad7080c5e2e | Schematic diagram of division: (a) production and marketing sub-regions; (b) physical geographic divisions. | PMC10001151 | foods-12-00956-g001.jpg |
0.421841 | cbc1b7e640594d96a6f16c71df70cd8b | Trends in regional food caloric production from 1978 to 2020: (a) nationwide; (b) production and marketing sub-regions; (c) physical geographic divisions. Note the values in the brackets indicate the growth rate of the food calories (unit: 1012 kcal/year), with the signs referring to the significance level (***: p < 0.001; *: p < 0.05). | PMC10001151 | foods-12-00956-g002.jpg |
0.476676 | 1482e07438a14de3a880011934b35386 | Food caloric production in different categories of food: (a) food calorie contribution for different categories of food from 1978 to 2020; (b) calorie production of six categories of food in production and marketing sub-regions and physical geographic divisions in 2020. | PMC10001151 | foods-12-00956-g003.jpg |
0.426798 | 95f6990411fc460caa536d8fd4b2f003 | Distribution pattern of food production and classification in China: (a) food calorie production pattern in 1978; (b) food calorie production pattern in 2020; (c) classification of food caloric growth rate from 1978 to 2020. | PMC10001151 | foods-12-00956-g004.jpg |
0.410572 | 45db0fde0be24bb68a1c4d4557c9183e | The proportion of each flow direction of food calories and the evolution of supply–demand in China: (a) the proportion of each flow direction of food calories; (b) the feedable population and supply–demand gaps across the country over time. | PMC10001151 | foods-12-00956-g005.jpg |
0.449571 | f8d602124521465d9e0a833347712363 | Food caloric supply–demand gap changes in (a) production and marketing sub-regions and (b) physical geographic divisions. The box marks the last year when the supply deficiency occurred and its deficiency (million persons). | PMC10001151 | foods-12-00956-g006.jpg |
0.407991 | e6125c6bec554b17bf32ee7a2b3a9473 | Spatial distribution of food calorie supply–demand equilibrium in China, 1978, 2000, and 2020. | PMC10001151 | foods-12-00956-g007.jpg |
0.384488 | 1b99538a6f1f4989b373ca36488ff253 | Migration pattern of the centers of gravity of the actual population and food calorie supply from 1978 to 2020: (a) population; (b) calorie supply; (c) trajectory comparison. | PMC10001151 | foods-12-00956-g008.jpg |
0.477449 | 5d31415a2eed4747a3aaba7345a14c46 | Conceptual framework of this study. | PMC10001152 | ijerph-20-03859-g001.jpg |
0.451886 | d9901fb50b2d4a17972da6bfcbd386c8 | Study sites around MMNR. Note: this figure is cited from Mojo et al. [23]. | PMC10001152 | ijerph-20-03859-g002.jpg |
0.482619 | 0c6874e0682249a6ab57535ccb2983f4 | Distribution of the sample by gender (men and women). | PMC10001487 | ijerph-20-04470-g001.jpg |
0.457805 | 8fd6b0e98918459b8524e43ea1767374 | Distribution of the sample by age (Group 1: ≤39 years; Group 2: ≥40 years). | PMC10001487 | ijerph-20-04470-g002.jpg |
0.469264 | 2abea7c89b2d4b6f9580434405c1f18b | Information System Research (ISR) framework for design of mHealth technology adopted from [17]. | PMC10001855 | ijerph-20-04219-g001.jpg |
0.509349 | 27b1ad7edc2749478934bdf6e6924717 | Particle size distribution of the corundum grains for preparing the ceramic membranes. | PMC10001914 | ijerph-20-04558-g001.jpg |
0.509358 | 42095bfc1cd04186be141770282dd073 | Schematic diagram of the MBR system. | PMC10001914 | ijerph-20-04558-g002.jpg |
0.522169 | d3f7ed733bf94f52b7057946d3bac608 | XRD of the ceramic membranes with different pore sizes. | PMC10001914 | ijerph-20-04558-g003.jpg |
0.421995 | fdc0c82d9ffc45e3bfb141a62f4ec53f | SEM and AFM images of different membranes: (a1–d2) C5, C7, C13, C20; (e) pore size distribution of different membranes. | PMC10001914 | ijerph-20-04558-g004a.jpg |
0.496396 | 3203055478b14e81a22bf253808c715a | Pollutants removal in the CMBR by different membranes: (a) COD; (b) TP; (c) NH4+-N; (d) TN. | PMC10001914 | ijerph-20-04558-g005.jpg |
0.358304 | 5397a65d81904098ba8fd847e4c4b426 | TMP changes of different membranes in the CMBR (a–d): C5, C7, C13, C20. | PMC10001914 | ijerph-20-04558-g006.jpg |
0.426982 | 2c4efa2e5a4b4d44a40605ab7bde4ac4 | Distribution of membrane fouling resistances for different ceramic membranes in the CMBR: (a) pore blockage and cake layer resistances; (b) reversible and irreversible resistances. | PMC10001914 | ijerph-20-04558-g007.jpg |
0.413505 | d7e4019c88a3448ab0a44ee0271be34d | 3D EEM of dissolved foulants extracted from (a–d) C5, C7, C13, C20. (peak A and B represent tryptophan-like substance and tyrosine-like substance, respectively). | PMC10001914 | ijerph-20-04558-g008.jpg |
0.386837 | b4eb97847c164f7d86527d3e6df037bb | Protein, polysaccharide and DOC content on different membranes. | PMC10001914 | ijerph-20-04558-g009.jpg |
0.387611 | a602dff7c4ce4ec787b1643a4ae34729 | SEM images of the cake layer on the membranes with different pore sizes (a1,a2): C5 membrane; (b1,b2): C7 membrane; (c1,c2): C13 membrane; (d1,d2): C20 membrane). | PMC10001914 | ijerph-20-04558-g010.jpg |
0.458308 | 99c9f71b315f4bae870dfb8bd15740c3 | The relative abundance of the microbial community at the phylum level (a) and class level (b). (the arrows represent the bacterial classes belong to the corresponding bacterial phyla). | PMC10001914 | ijerph-20-04558-g011.jpg |
0.48262 | 3f0ed7fa08e048fd8d0505a30fbfb5c7 | Research framework. | PMC10002033 | ijerph-20-03972-g001.jpg |
0.40405 | 6bcec4d6126e44f7ba886d70b53734a3 | Post number of TGS from 2011 to 2022. | PMC10002033 | ijerph-20-03972-g002.jpg |
0.437821 | c8bdef91e585400f97acb92f3019522d | Regional distribution of verified users (left) and the number of posts (right). | PMC10002033 | ijerph-20-03972-g003.jpg |
0.433184 | f0965bd98fa74328abfcbb5d9d069bff | Number of positive and negative emotions and total number of posts in TGS during 2012−2022. | PMC10002033 | ijerph-20-03972-g004.jpg |
0.444076 | 2ce961d70a9f41859bbe28be72d2d548 | Distribution of topic intensity values. | PMC10002033 | ijerph-20-03972-g005.jpg |
0.508537 | 5b7aea45c8254fd09202d3475dcf369d | Topic 4 of topic models (positive sentiment) [51,52]. | PMC10002033 | ijerph-20-03972-g006.jpg |
0.525351 | 575f956600fe48da99177153e3b91513 | Topic 2 of topic models (negative sentiment) [51,52]. | PMC10002033 | ijerph-20-03972-g007.jpg |
0.439773 | 9e94345bbad34e4ea9b0af96c26eaf96 | Design of the experimental conditions: participants engaged in five designed sessions at least seven days apart, a familiarization and four experimental sessions to randomly test four compositions of hip and knee joint angles during quadriceps femoris musculature (QF). Twelve MVICs were required at each visit. Legend: MVIC: Maximal Voluntary Isometric Contraction; SUP60: supine with 60° of knee flexion; SIT60: seated with 60° of knee flexion; SUP20: supine with 20° of knee flexion; SIT20: seated with 20° of knee flexion. | PMC10002253 | ijerph-20-03947-g001.jpg |
0.448195 | cb565173fd0f4a238c5b3e753218f9d9 | Representative ultrasound image of the vastus lateralis at rest (A) and during a maximum voluntary isometric contraction (B) in a seated position with the knee flexed at 60°. | PMC10002253 | ijerph-20-03947-g002.jpg |
0.383214 | b64238acb3164e38829272e5dce76ffe | The overlapping images technique enables the measurement of patellar tendon length at rest (A1 + A2) and in increments of 10% force up to maximum voluntary isometric contraction (B1 + B2) when the entire length cannot be captured in a single frame due to the limited size of the ultrasound probe. A skin marker (adhesive tape) that creates a hypoechoic shadow is used to define the measurement bounds: the length from TI to the center of the skin marker in A1 and the length from the center of the skin marker to PI in A2 are added. The same procedure is repeated for each 10% increase in force, leading to B1 and B2. | PMC10002253 | ijerph-20-03947-g003.jpg |