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0.450288 | 5289d87f94f5475782545fc0ac4f872c | Biochemical features of neonatal Dubin-Johnson syndrome (nDJS) patients.Total bilirubin (TB), direct bilirubin (DB), total bile acids (TBA), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT) and alkaline phosphatase (ALP) values in 53 neonatal DSJ patients were compared with 133 biliary atresia (BA) patients and 94 cholestasis controls. | PMC9647112 | JCTH-11-163-g001.jpg |
0.436515 | 998344b628a94c5c8d3d3fd972914790 | Histopathologic findings in the livers of five patients.Hematoxylin and eosin staining showed giant-cell transformation of hepatocytes and hepatocyte ballooning, steatosis (arrow) and slight intracanalicular and intracytoplasmic cholestasis with bile plugs, circles). Presence of inflammation was observed in P20, as confirmed by Masson staining (line 2). No inflammation, fibrosis, cirrhosis, or melanin-like pigment deposits in hepatocytes were observed in P25, P27, P28, and P53. | PMC9647112 | JCTH-11-163-g002.jpg |
0.469767 | 6f061c8f6f1e4f6aa89791bd64e48973 | Receiver operating characteristic curve analysis of discriminatory features in 20 neonatal Dubin-Johnson syndrome (nDJS) patients and 80 biliary atresia (BA) patients in the discovery cohort.The areas under the curve (AUC) for serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are >0.9 for differentiating nDJS from BA. The AUCs are shown with 95% CIs. | PMC9647112 | JCTH-11-163-g003.jpg |
0.427877 | 274fe0f77ce54c3d8f87738c9023ad29 | High-Performance Liquid Chromatography (HPLC) Analysis of DDT. (A) HPLC chromatograms of mixed standards with UV detection conducted at 254 nm. 1: Gallic acid, 2: Amygdalin, 3: Sennoside B, 4: Rhein-8-O-β-D-glucopyranoside, 5: Sennoside A, 6: Aloeemodin, 7: Rhein, 8: Emodin, 9: Physcion. (B) HPLC chromatogram of DDT. (C) HPLC fingerprints for 10 batches of DDT. | PMC9647469 | gr1.jpg |
0.441893 | dba9bd3d84c745569131fdf2f312ae64 | The construction of DDT-target-ICH. (A) Venn diagram describing targets distribution of DDT and ICH. (B) DDT-target-ICH network. The outer circle represents target proteins associated with ICH, and the inner circle refers to DDT active ingredients. | PMC9647469 | gr2.jpg |
0.402356 | b9b7d93b69fb4abc91c3eb868cbb7bbc | Protein-protein interaction (PPI) network of DDT target for the treatment of ICH. (A) Hub genes of DDT for ICH. The top 35 key targets were screened by degree value using the CytoNCA plugin. (B) STRING analysis of the PPI network of DDT targets for treating ICH. Different colored spheres represent target genes, with protein structures inside. Lines indicate interactions between protein targets. The thicker lines represent the more considerable degree of the target node. (C) Statistical analysis of (B) The X-axis represented the name of the protein, and the Y-axis represented the number of network neighbor nodes. | PMC9647469 | gr3.jpg |
0.386851 | 596fa98bf4ad44eeb25fdf314a859bad | GO and KEGG Enrichment Analyses. (A) Three types of GO gene and gene product attributes in the database were shown (blue, cellular component; green, molecular function; yellow, biological process). (B) GO annotation analysis for the top 20 targets. (C) KEGG annotation analysis for the top 20 targets. (D) The most correlated signaling pathway related to DDT treatment of ICH in KEGG mapper - MAPK signaling pathway (has:04010) and apoptosis signaling pathway (has:04210). | PMC9647469 | gr4.jpg |
0.409792 | 7a0e82861e5445cabcd2d4b8b90c7c2d | DDT relieves nerve damage of ICH. (A) Diagram of the animal study for the ICH model or the DDT treatment groups. (B) Representative images of tunel staining of brain tissues (n = 5, Original magnification ×400). (C) Statistical analysis of tunel staining was shown. (D) IL-1β level was measured by Elisa kit. ∗∗∗p < 0.001 vs. sham group; #p < 0.05, ###p < 0.001 vs. ICH model group. | PMC9647469 | gr5.jpg |
0.442457 | 04fec771a94a47e395e020979e40e56c | DDT reduces neuronal apoptosis via ASK1/MKK7/JNK signaling pathway in rats. (A) Western Blotting analysis of p-Src (Sup F. 1), Src (Sup F. 2), c-Myc (Sup F. 3), MMP-9 (Sup F. 4) and IL-1β (Sup F. 5). On the basis of normalization to GAPDH (Sup F. 6), the relative expression levels of each protein were calculated and is shown on the right. (B) The expression of apoptotic related proteins Bcl-2 (Sup F. 7), Bax (Sup F. 8) and cleaved-Caspase 3 (Sup F. 9) by western blotting, with quantitative analysis on the right (using GAPDH (Sup F. 10) as a control). (C) The expression of JNK signaling related proteins p-ASK1 (Sup F. 11), ASK1 (Sup F. 12), p-MKK7 (Sup F. 13), MKK7 (Sup F. 14), p-JNK (Sup F. 15), JNK (Sup F. 16), p-c-JUN (Sup F. 17), c-JUN (Sup F. 18) by Western blot analysis. Quantitative analysis of the protein production levels was shown on the right. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001 vs. sham group; #p < 0.05, ##p < 0.01, ###p < 0.001 vs. ICH model group. | PMC9647469 | gr6.jpg |
0.441052 | ebb669e04a244f9a8b3a2f7c21f3f49c | DDT increased the cell viability and inhibited IL-1β release in CoCl2-induced PC12 cells. (A) The neurotoxic effect of CoCl2 with different concentrations (31.25, 62.5, 125, 250, 500, and 1000 μg/mL) for 24 h was determined by an CCK8 assay. (B) After 24 h incubation with CoCl2, IL-1β level was measured by Elisa. (C) After treatment with DDT and/or CoCl2, cell viability of PC12 was assessed by an CCK8 assay. (D) IL-1β level was measured using an Elisa assay kit. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001 vs. Ctrl group; #p < 0.05, ##p < 0.01, ###p < 0.001 vs. CoCl2 model group. | PMC9647469 | gr7.jpg |
0.435956 | 55286b7abaef488783bd347604ed27b9 | DDT protected against CoCl2-induced PC12 cells apoptosis. (A) Western Blotting analysis of p-Src (Sup F. 19), Src (Sup F. 20), MMP-9 (Sup F. 21), c-Myc (Sup F. 22), IL-1β (Sup F. 23) and GAPDH (Sup F. 24). (B) Expression ration of p-Src, Src, MMP-9, c-Myc and IL-1β. (C, D) Typical histogram of apoptosis ratio was determined by flow cytometry. (E) Western blotting of Bcl-2 (Sup F. 25), Bax (Sup F. 26) and cleaved-Caspase 3 (Sup F. 27) with GADPH (Sup F. 28) as the internal control. (F) Quantitative analysis of the protein production levels. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001 vs. Ctrl group; #p < 0.05, ##p < 0.01, ###p < 0.001 vs. CoCl2 model group. | PMC9647469 | gr8.jpg |
0.464093 | 7ce5d9e0500c40ddbedc8286999ef081 | DDT ameliorated CoCl2-induced PC12 cells apoptosis via ASK1/MKK7/JNK signaling pathway. (A) The expression of JNK signaling-related proteins p-ASK1 (Sup F. 29), ASK1 (Sup F. 30), p-MKK7 (Sup F. 31), MKK7 (Sup F. 32), p-JNK (Sup F. 33), JNK (Sup F. 34), p-c-JUN (Sup F. 35), c-JUN (Sup F. 36) by Western blot analysis. (B) Quantitative analysis of the protein production levels of (A). (C) PC12 cells were pretreated with the JNK inhibitor, SP600125 (20 μM) for 1 h, followed by exposure to CoCl2, and/or DDT for 12 h. p-JNK (Sup F. 37), JNK (Sup F. 38), Bax (Sup F. 39) and cleaved-Caspase 3 (Sup F. 40) were evaluated by Western blot analysis with GADPH (Sup F. 41) as the internal control. (D) Densitometric results for Western blot are resented in the right panels. ∗∗p < 0.01, ∗∗∗p < 0.001 vs. Ctrl group; #p < 0.05, ##p < 0.01, ###p < 0.001 vs. CoCl2 model group. △△△p < 0.001 vs. DDT group. | PMC9647469 | gr9.jpg |
0.489037 | 64efec13820240fcafc26253ae8eb368 | A schematic illustration of the synthetic route
of PMF networks. | PMC9647782 | ao2c05072_0002.jpg |
0.492676 | d258ee72dfdc48f5a2f0b48a6898dc41 | TG curves
of PF, MF, and PMF resins. | PMC9647782 | ao2c05072_0003.jpg |
0.443143 | a58f0e77635048869e69c48801bbe323 | SEM images of (a) CA,
(b) NCA-4-1, (c) NCA-2-1, (d) NCA-1-1, and
(e) NCA-1-2. | PMC9647782 | ao2c05072_0004.jpg |
0.39002 | bcee0fd1f9f8459f963a7fbc5ef5dab4 | TEM micrographs of the NCA-2-1. | PMC9647782 | ao2c05072_0005.jpg |
0.456868 | 88c9a62f35984e91831a4660b87b8a6e | (a) Nitrogen adsorption
and desorption curve at −196 °C
for the carbon aerogels. (b) Pore size distribution (PSD) curve. | PMC9647782 | ao2c05072_0006.jpg |
0.442817 | 4448d29b97494eb288ad6f019f08c7ea | FTIR spectra of NCA samples. | PMC9647782 | ao2c05072_0007.jpg |
0.414855 | a48fde4b9b7d4e6587cbd04a3b71075e | (a) XRD patterns of as-prepared materials after
acid treatment.
(b) Raman spectra of the obtained materials. (c) High-resolution XPS
spectra of the deconvoluted N1s peak. | PMC9647782 | ao2c05072_0008.jpg |
0.496039 | f5801b5b0b564392a54aefde0c06eeef | CO2 adsorption isotherms at (a) 0
°C and (b) 25
°C. Correlation between CO2 adsorption capacity and
textural characteristics of various adsorbents at 0 °C and 1
bar: (c) CO2 adsorption capacity vs surface areas. (d)
CO2 adsorption capacity vs Vultra (<1 nm) and Dp. | PMC9647782 | ao2c05072_0009.jpg |
0.465113 | d48ce5c6c71e42c79fef5f1b680cd4d0 | (a) CO2 adsorption capacity vs N content. (b) Isosteric
heat of adsorption at different CO2 loadings of NCAs. | PMC9647782 | ao2c05072_0010.jpg |
0.440375 | 1465f0a25f904cd7a3655aea819bf9d0 | (a) CO2 and N2 adsorption isotherms
of NCA-1-2
at 25 °C. (b) IAST-predicted adsorption selectivity of CO2/N2 at 25 °C. | PMC9647782 | ao2c05072_0011.jpg |
0.377197 | 7f73e9f418ac468284aee79c2a267098 | (a) Breakthrough curves of CO2 sorption at 0 °C
using a stream of 15 vol % CO2 in N2. (b) Recycle
runs of CO2 adsorption at 25 °C and 1.01 bar, and
regeneration. | PMC9647782 | ao2c05072_0012.jpg |
0.460932 | 2c8af2b58b82414eaa535ab223331194 | (a) Breakthrough curves
of CO2 adsorption at 25 °C
and 1.01 bar using a stream of CO2/H2O/N2 = 15/3/82 vol %. Cycle 0 represents dry feed gas. Cycles
1–5 represent wet feed gas. (b) Breakthrough capacities of
cyclic experiments with wet feed gas. | PMC9647782 | ao2c05072_0013.jpg |
0.433025 | c099ab6dd5a44d3badcc8a2f091a9c0e | SEM images of (a) lignin char, (b) EL–SA,
(c) EL–MSA,
and (d) spent EL–MSA. | PMC9648150 | ao2c04693_0002.jpg |
0.409703 | e146ff8d66e0410ab1984ba75cbaab9a | TEM images of (a) EL–SA, (b) EL–MSA,
and (c) spent
EL–MSA. | PMC9648150 | ao2c04693_0003.jpg |
0.506647 | 2928e9d9a5874feeaa195adb95b7bd1e | Effect of different catalysts on methyl stearate yield
from the
esterification at 200 °C for 5 min with a methanol-to-stearic-acid
molar ratio of 3:1. | PMC9648150 | ao2c04693_0004.jpg |
0.531049 | db37ced351134d388b7a417b9ce1769b | Proposed reaction
mechanism of stearic acid esterification over
the sulfonated carbon-based catalyst. | PMC9648150 | ao2c04693_0005.jpg |
0.490585 | bb5bb5ae29034ba482d6e7beca36b904 | Effect
of reaction temperature on the methyl stearate yield from
the esterification with and without the presence of the EL–MSA
catalyst at the reaction time of 5 min and a methanol-to-stearic-acid
molar ratio of 3:1. | PMC9648150 | ao2c04693_0006.jpg |
0.506928 | b48abf3309a94e10afa91b59db717d19 | Effect of reaction time on the methyl stearate yield from the esterification
with and without the presence of the EL–MSA catalyst at 260
°C and a methanol-to-stearic-acid molar ratio of 3:1. | PMC9648150 | ao2c04693_0007.jpg |
0.480523 | ad13f2694dfe48f1813dee42e9edc091 | Effect of the methanol-to-stearic-acid molar ratio on
the methyl
stearate yield upon esterification with and without the presence of
the EL–MSA catalyst at 260 °C with a reaction time of
5 min. | PMC9648150 | ao2c04693_0008.jpg |
0.502432 | c9ab6ddaaa894150b0fa7173fc4abb19 | Effect
of catalyst loading on the methyl stearate yield from esterification
at 260 °C for 5 min with a methanol-to-stearic-acid molar ratio
of 9:1. | PMC9648150 | ao2c04693_0009.jpg |
0.501208 | 7ef352aa3cfd4c69a1558f8d6c671a8c | Effect of the
toluene amount on the methyl stearate yield upon
esterification at 260 °C for 5 min, a methanol-to-stearic-acid
molar ratio of 9:1, and an EL–MSA catalyst loading of 5 wt
%. | PMC9648150 | ao2c04693_0010.jpg |
0.42194 | 8656cae04a174617871f06fc2ca733b9 | Effect of reusability and the cosolvent on product yield in five
consecutive runs over EL–MSA at 260 °C for 5 min and methanol-to-stearic-acid
molar ratios of 9:1. | PMC9648150 | ao2c04693_0011.jpg |
0.495896 | 207e66886da149f2a34f663d4203ed2e | FT-IR spectra of fresh
and spent EL–MSA catalysts. | PMC9648150 | ao2c04693_0012.jpg |
0.507379 | 9a2cbb89558a4239afb8ded6fe4ceb03 | Ester yield obtained from the esterification of stearic
acid with
different types of alcohol at 260 °C for 5 min, a methanol-to-stearic-acid
molar ratio of 9:1, and an EL–MSA catalyst loading of 5 wt
%. | PMC9648150 | ao2c04693_0013.jpg |
0.401089 | 46131b5063e6493091f9c415a1d7948a | Overview of study protocol. The study consisted of a Preparation Phase, the Montreal Imaging Stress Task (MIST), and a Resting Phase. S0–S6 indicate the time points at which saliva samples were taken. | PMC9649023 | 41598_2022_23222_Fig1_HTML.jpg |
0.382377 | 0e8d96f80ca2477ebb3717089719d81d | Left: Course of heart rate during the different MIST phases for both conditions combined, each consisting of Baseline (BL), Resting Period / Cold Face Intervention (RP/CFI), Arithmetic Tasks (AT), and Feedback (FB) subphases. Right: Average heart rate per MIST subphase during the conduction of the MIST. Values are depicted as mean and standard error. | PMC9649023 | 41598_2022_23222_Fig2_HTML.jpg |
0.494014 | 8b1c575837e34df29ae18298a7a13c7f | Cortisol response to the MIST of Control and CFT condition, respectively. Values are depicted as mean and standard error over all participants within one condition. | PMC9649023 | 41598_2022_23222_Fig3_HTML.jpg |
0.494618 | 5033c23ffce040a0a6d6708d3219b01d | Differences in \documentclass[12pt]{minimal}
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\begin{document}$$\Delta HR$$\end{document}ΔHR (left) and \documentclass[12pt]{minimal}
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\begin{document}$$\hat{t}_{Glo}(HR)$$\end{document}t^Glo(HR) (right) between Control and CFT condition during BL for each MIST phase. | PMC9649023 | 41598_2022_23222_Fig4_HTML.jpg |
0.450358 | 1708f46b296d4813a0fc67011dbc7854 | Schematic illustration of the 3D-bioprinted void-forming hydrogel constructs for implantation. I) An aqueous emulsion bioink, in which dextran solution drop-like distributes within GelMA solution, was prepared by the mixture of GelMA, Dextran, and stem cells for 3D bioprinting of void forming hydrogel to II) repair the cranial defect. | PMC9649380 | gr1.jpg |
0.439527 | fbae6bf223f34afcb5f0b1df62ccdb40 | 3D bioprinting of void-forming hydrogels. (A) Schematic diagram of the DLP-based bioprinting approach. (B) Fluorescence microscopy (i, scale bar: 30 μm) and SEM (ii, scale bar: 100 μm) images of 3D-printed hydrogels. (C) Compressive stress-strain curve of 3D-printed hydrogels. (D) Diffusion of the BSA from the hydrogels (scale bar: 200 μm). | PMC9649380 | gr2.jpg |
0.457767 | fcd3bc87834648599c20b07b07edbadb | The bioactivity of the encapsulated cells in 3D-bioprinted hydrogels. (A) Fluorescent images of live/dead stained BMSCs within printed hydrogels (scale bar: 100 μm). (B) Cell viability after incubation for 1, 3, and 5 days using CCK-8 assay (mean ± SD, n = 3, two-way ANOVA). (C) The quantitative analysis of migrated cells (mean ± SD, n = 3, two-way ANOVA). (D) Images of migrated BMSCs after 5 and 10 days of culture (scale bar: 100 μm). ∗P < 0.05, ∗∗∗P < 0.001. | PMC9649380 | gr3.jpg |
0.400569 | c9705438a5fd48e8944901b385968773 | 3D bioprinting of void-forming hydrogels promote cell-scaffold interaction. (A) Cell spreading within the printed hydrogels at day 7 (scale bar: 100 μm). (B) Representative immunofluorescence for YAP distribution in BMSCs (scale bar: 25 μm). (C) Quantification of gene expression of YAP targeted genes (CYR61, CTGF, and CDH2) after 7 days of culture (mean ± SD, n = 3, two-way ANOVA). (D) ALP activity of the encapsulated BMSCs at day 7 and 14 (mean ± SD, n = 3, two-way ANOVA). Summarized data showing the effect of porous structure on mRNA expression of (E) osteogenic differentiation related genes including osterix (OSX) and (F) runt-related transcription factor 2 (RUNX2) at day 7 and 14 (mean ± SD, n = 3, two-way ANOVA). Ns was determined as P > 0.05 with no statistical difference, ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001. | PMC9649380 | gr4.jpg |
0.470189 | 56443223b7b34c26a1afdb5b9e4ac569 | In vivo evaluation of bone regeneration after void-forming hydrogels treatment using cranial defects in a rat model. (A) 3D reconstruction micro-CT images showing regenerated bone around the defects without treatment and those treated with standard and void-forming 3D-bioprinted hydrogels constructs. (B) Quantification of the area of newly formed bone (mean ± SD, n = 6, one-way ANOVA). Representative (C) H&E (scale bar at low magnification: 200 μm, scale bar at high magnification: 100 μm) and (D) Masson staining images of the regenerated bone tissues (scale bar at low magnification: 200 μm, scale bar at high magnification: 50 μm). ∗∗P < 0.01, ∗∗∗P < 0.001. | PMC9649380 | gr5.jpg |
0.493394 | 1b211f8e73b345c3a891ffaf479637be | Representative images for immunohistochemical staining of COL-1 (A) and OCN (B). (scale bar at low magnification: 200 μm, scale bar at high magnification: 50 μm). | PMC9649380 | gr6.jpg |
0.543366 | dbb9add2c8ec46be982fc1afa6c0a446 | Electrocardiogram: ectopic atrial rhythm, left anterior hemiblock, signs of left ventricular hypertrophy. | PMC9650383 | fcvm-09-1020054-g001.jpg |
0.443588 | 9d2cd40c5ac346e3a22b587a7e12dc1b | Two-dimensional trans-thoracic echocardiogram continuous wave Doppler representation of LVOT peak gradient at rest and during Valsalva maneuver. | PMC9650383 | fcvm-09-1020054-g002.jpg |
0.396361 | 786d152b1f874e3488dc56a2dbea1743 | Trans-esophageal echocardiogram mid-esophageal 5-C view demonstrating, in panel (A), basal interventricular septum severe hypertrophy, SAM of AML, chordal rupture, and the related PML-flail. Panel (B) shows the two different jets there were at color Doppler. The posteriorly directed jet was due to SAM-related MR. The anteriorly directed jet was related to PML-flail. | PMC9650383 | fcvm-09-1020054-g003.jpg |
0.405985 | c872eaa2a5984eeab1eee2ddbbff7213 | Schematic representation of parasternal long axis view showing two different types of mitral regurgitation jets, SAM-related and flail-related. Panel (A) shows the posteriorly directed jet in SAM-related MR. Panel (B) shows the anteriorly directed jet of MR in PML-flail. In red the different motions of PML related to the two different jets. Panel (C) shows the two different color jets found in the reported case; red arrows correlate the two color jets with the respective schematic representation. | PMC9650383 | fcvm-09-1020054-g004.jpg |
0.496355 | 91ba1b81370c42149e0a23219d895aa8 | Proposed Stochastic RL Framework. Here, in the policy network, the coupled states \documentclass[12pt]{minimal}
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\begin{document}$\mathbf {s}_{t}\in \mathbb {R}^{l \times (m+1) \times (d+1)}$\end{document}st∈ℝl×(m+1)×(d+1) are considered as input states to be fed into a policy encoder network (upper green block). Later, the encoded state vector is dropped into the FC layers (upper purple block) to generate means, standard deviation and mixture weights of the output action \documentclass[12pt]{minimal}
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\begin{document}$\mathbf {a}_{t} \in \mathbb {R}^{d+1}$\end{document}at∈ℝd+1. The sampled actions at are realized by performing a reparameterization trick. Subsequently, the new generated action at is simultaneously fed into the critic encoder network (lower green block) and the financial environment (left blue block), with which it can interact, to obtain reward rt and generate a new state st+ 1. In the critic network, the encoded layer (lower green block) input by st and at is then fed into the FC layers (lower purple block) to generate the quantile numbers of the value distribution Qt. Finally, after estimating Qt and Qt+ 1, value distribution is learned by using temporal difference | PMC9651127 | 10489_2022_4217_Fig1_HTML.jpg |
0.42408 | b01858cb4fd8402b9f923ed25e098471 | The Cumulative Wealth in U.S. market on the validation set for different models | PMC9651127 | 10489_2022_4217_Fig2_HTML.jpg |
0.450522 | dfa28cc4ed5c428a83cc350d7d5dd817 | The Cumulative Wealth in U.S. market on the test set for different models | PMC9651127 | 10489_2022_4217_Fig3_HTML.jpg |
0.410715 | bb25fdfb19074a278683357901d12d8f | Learning curves for Q-Max. Q-Max for TD3 and DDPG is calculated by maximizing Q-value in each batch. Q-max for SPDQ is calculated by maximizing the average of all the quantiles in each batch | PMC9651127 | 10489_2022_4217_Fig4_HTML.jpg |
0.42173 | 0f5f2384b28a4c348c270ee40f262afa | A case study of the Adobe after training 50 episodes | PMC9651127 | 10489_2022_4217_Fig5_HTML.jpg |
0.431407 | 0279a434a0534bb19e49a7370d993d26 | Reward learning curves on validation sets for different parameters | PMC9651127 | 10489_2022_4217_Fig6_HTML.jpg |
0.380959 | 4fa1a7cc26db43cdab3bdbb74ab4170d | SPDQ for portfolio optimization. | PMC9651127 | 10489_2022_4217_Figh_HTML.jpg |
0.442425 | be315abd6d3144c1ac658e2afb321b53 | Process of study selection. | PMC9652703 | BMRI2022-6712625.001.jpg |
0.453918 | df7542fc980f4849975fd0bffde39a52 | SEN and SPE of lncRNA assay for diagnosis of GC. The pooled SEN: 0.71 (95% CI: 0.67-0.74); the pooled SPE: 0.76 (95% CI: 0.71-0.79). | PMC9652703 | BMRI2022-6712625.002.jpg |
0.491148 | 1688aba050d44aa1b58da43f2890a59c | SROC for lncRNA expression in GC diagnosis. One cycle represents an individual study. The AUC is 0.79. | PMC9652703 | BMRI2022-6712625.003.jpg |
0.556377 | d2f1b7f88aad4ce5bd607fcedd171afe | Funnel plot for the assessment of potential publication bias of the diagnostic studies. Each point represents a study, and the line is the regression line. The P value is 0.74, indicating that there was no publication bias. | PMC9652703 | BMRI2022-6712625.004.jpg |
0.457087 | 6e6d3cec2072488aac18a330fafd5d21 | Fagan's nomogram of the lncRNA test for diagnosis of GC. | PMC9652703 | BMRI2022-6712625.005.jpg |
0.43705 | 4715ec20c9b04e7d85e963b802142e12 | Diagnostic efficacy of single lncRNAs and combined model. (a) The ROC of 9 differentially expressed lncRNAs with the same trend in meta- and TCGA analysis for GC diagnosis. (b) The ROC of lncRNAs combined models: the AUC is 0.972. | PMC9652703 | BMRI2022-6712625.006.jpg |
0.441276 | 30712c031e5f4c678a78d75862fdcb91 | Bubble Periods in the Cryptoassets. The colored areas in the figure highlight the explosive periods identified by the PS framework for the cryptocurrencies (BTC and ETH) in orange, the 9 DeFi tokens and coins in blue, and 3 NFTs in green. The black line represents the cryptoasset price in USD. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) | PMC9653299 | gr1_lrg.jpg |
0.389193 | fa63bed2103d4a5f9cd902765ebd8918 | Monthly Detected Bubble Days Per Cryptoasset. The figure reports the total detected number of bubble days per month for each cryptoasset. DeFi and NFTs are represented by the purple and green color palettes, respectively. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.) | PMC9653299 | gr2_lrg.jpg |
0.477471 | b24d6bcb95a5427ba9ea805cd494854a | Rough-rolling mill with the first flying shear arrangement. | PMC9653682 | materials-15-07735-g001.jpg |
0.473795 | bdaec325336845aebc9984964ae5c6c4 | Intermediate-rolling mill with the second flying shear arrangement. | PMC9653682 | materials-15-07735-g002.jpg |
0.500981 | 0ea4b84a75a44809ac8ecb8f4e8b7e9c | Schematic of the rough-rolling and specimen-cutting process. | PMC9653682 | materials-15-07735-g003.jpg |
0.520209 | 857f0e69981c47d6800a9a9ae48feb5f | Schematic of the intermediate-rolling and specimen-cutting process. | PMC9653682 | materials-15-07735-g004.jpg |
0.453251 | 2d6cfd69bc5e458db961a496d4288471 | Surface morphology of the rough- and intermediate-rolled specimens and clad rebar. | PMC9653682 | materials-15-07735-g005.jpg |
0.415648 | 34f63c81c1814ab5b270a6bfab72555c | Schematic of the operation of the shear jig (data from Ref. [23]). | PMC9653682 | materials-15-07735-g006.jpg |
0.569063 | a0e0fea41b294557a92516df5627ebe4 | Dimensions of the shear specimens. | PMC9653682 | materials-15-07735-g007.jpg |
0.43089 | 5a1aae9e5d4d41d99deddfb1b9fa0815 | Tensile experiment flow. | PMC9653682 | materials-15-07735-g008.jpg |
0.469801 | 94211932c51249d09d5fdcacab310aad | Dimensions of the tensile specimens. | PMC9653682 | materials-15-07735-g009.jpg |
0.402547 | d95fb7f453394290a8b4df5bf84cf113 | End-face profiles of the specimens: (a) Rough-rolled specimen; (b) intermediate-rolled specimen; (c) clad rebar (data from Ref. [22]); (d) HRB400 reinforcement. | PMC9653682 | materials-15-07735-g010.jpg |
0.392162 | d802e86bd1624a92b6880f4c2796c809 | Metallographic images of the specimens: (a) Carbon-steel side of the rough-rolled specimen; (b) stainless-steel side of the rough-rolled specimen; (c) carbon-steel side of the intermediate-rolled specimen; (d) stainless-steel side of the intermediate-rolled specimen; (e) carbon-steel side of the clad rebar; (f) stainless-steel side of the clad rebar. | PMC9653682 | materials-15-07735-g011.jpg |
0.392682 | 33a028dc951a464fa54e6b9b8e402639 | Schematic of the grain size of structures on the composite interface: (a) EBSD image of the rough-rolled specimen; (b) grain size statistics of the rough-rolled specimen; (c) EBSD image of the intermediate-rolled specimen; (d) grain size statistics of the intermediate-rolled specimen; (e) EBSD image of the clad rebar; (f) grain size statistics of the clad rebar. | PMC9653682 | materials-15-07735-g012.jpg |
0.387197 | f2e61bb3d8314de294a5aba8de8d6449 | Recrystallization grain ratios of structures on the composite interface: (a) DefRex diagram for rough-rolled specimens; (b) recrystallization grain statistics for rough-rolled specimens; (c) DefRex diagram for intermediate-rolled specimens; (d) recrystallization grain statistics for intermediate-rolled specimens; (e) DefRex diagram for clad rebars; (f) recrystallization grain statistics for clad rebars. | PMC9653682 | materials-15-07735-g013.jpg |
0.399494 | 93fe0bcf6e014a77aa7ef6a5a7019dd5 | Distribution of elements on the composite interface of the specimens: (a) EPMA image of the composite interface of the rough-rolled specimen; (b) line scan result of the rough-rolled specimen; (c) EPMA image of the composite interface of the intermediate-rolled specimen; (d) line scan result of the intermediate-rolled specimen; (e) EPMA image of the composite interface of the clad rebar; (f) line scan result of the clad rebar. | PMC9653682 | materials-15-07735-g014.jpg |
0.396709 | cfecd90309ed48249081f2f4a2a1b2d6 | ΔG0–Temperature diagram of the metal oxidation reaction. | PMC9653682 | materials-15-07735-g015.jpg |
0.408074 | b3cc079fd823418cbcdeb71996ba3a6e | Shear fracture profiles of each specimen: (a) Shear fracture diagram of the rough-rolled specimen; (b) shear fracture diagram of the intermediate-rolled specimen; (c) shear fracture diagram of the clad rebar; (d) shear fracture profile of the rough-rolled specimen; (e) shear fracture profile of the intermediate-rolled specimen; (f) shear fracture profile of the clad rebar. | PMC9653682 | materials-15-07735-g016.jpg |
0.488668 | 6d570f7d470343528519db2144aa679d | Tensile fracture profiles of rough- and intermediate-rolled specimens: (a) Schematic of the tensile fracture of rough-rolled specimens; (b) schematic of the tensile fracture of intermediate-rolled specimens; (c) tensile fracture profiles of the carbon-steel side of rough-rolled specimens; (d) tensile fracture profiles of the carbon-steel side of intermediate-rolled specimens; (e) tensile fracture profiles of the stainless-steel side of rough-rolled specimens; (f) tensile fracture profiles of the stainless-steel side of intermediate-rolled specimens. | PMC9653682 | materials-15-07735-g017.jpg |
0.396529 | 02e188e8b6c845129eb468064e7f6d4d | Formation process of the composite interface of the clad rebar: (a) Heating state; (b) forming process; (c) surface structure after rolling. | PMC9653682 | materials-15-07735-g018.jpg |
0.446754 | 7fa09e06632c46309cf87f1251b4eaf8 | Alpha Diversity Index of the microbial communities of healthy and B. xylophilus–infected P. massoniana. (A) Endophytic bacteria. (B) Endophytic fungi. Nematode-infected Wilted pines are designated as P. massoniana. EBH, healthy pine endophytic bacteria; EBW, wilted pine endophytic bacteria; EFH, healthy pine endophytic fungi; EFW, wilted pine endophytic fungi. | PMC9653782 | plants-11-02849-g001.jpg |
0.448775 | 1552441be25941849de2765740885fc1 | Clustering of the microbial communities of healthy and B. xylophilus−infected P. massoniana using PCoA and UPGMA (unweighted pair-group method with arithmetic means). (A) PCoA plots based on Bray–Curtis metrics for bacterial communities of healthy and B. xylophilus−infected P. massoniana. (B) UPGMA clustering of bacterial communities of healthy and B. xylophilus−infected P. massoniana. (C) PCoA plots based on unweighted Bray–Curtis metrics for fungal communities of healthy and B. xylophilus−infected P. massoniana. (D) UPGMA clustering of fungal communities of healthy and B. xylophilus−infected P. massoniana. | PMC9653782 | plants-11-02849-g002.jpg |
0.417269 | 57f5627c20ea46f1849e3cd5965e7785 | Venn diagrams of the unique and shared operational taxonomic units (OTUs) of sequenced samples and LEfSe diagrams between all the samples from healthy pines and wilted pines. (A) Bacterial data among all samples from healthy pines and wilted pines. (B) Fungal data from all the samples from healthy pines and wilted pines. (C) LEfSe analysis diagrams of bacteria data between all the samples from healthy pines and wilted pines. (D) LEfSe analysis diagrams of fungal data between all the samples from healthy pines and wilted pines. | PMC9653782 | plants-11-02849-g003.jpg |
0.523112 | f35b0a0dba9e40728342374fcd715e18 | PCA analysis of differential metabolites. The horizontal coordinate PC1 and the vertical coordinate PC2 indicate the scores of the first and second principal components, while different colors indicate samples from different treatments, and the confidence ellipse is 95%. (C,D) PLS-DA classification validation plots. The horizontal coordinates indicate the correlation between random group Y and original group Y, while the vertical coordinates indicate the scores of R2 and Q2. (A,C) positive model, (B,D) negative model. | PMC9653782 | plants-11-02849-g004.jpg |
0.492764 | 41a1ac9eb3cc43249cf3fb32de778ae3 | Volcano plots and KEGG metabolic pathway enrichment map of differential metabolites. (A,C) Positive ion mode, (B,D) Negative ion mode; each point represents a metabolite: horizontal coordinates indicate different multiplicities of differential metabolites (log2 values), vertical coordinates indicate p-values (−log10 values), grey indicates metabolites with no significant differences (NoDiff), red indicates up–regulated metabolites (UP), green indicates down–regulated metabolites (DW), and the size of the points indicates VIP values. The abscissa in the figure is x/y (the number of differential metabolites in the corresponding metabolic pathway/the total number of metabolites identified in the pathway), and the larger the value, the higher the enrichment of differential metabolites in the pathway. The color of the point represents the p-value of the hypergeometric test. The smaller the value, the more reliable and statistically significant the test is. The size of the dots represents the number of differential metabolites in the corresponding pathway; the larger the number, the more differential metabolites in the pathway. | PMC9653782 | plants-11-02849-g005.jpg |
0.387783 | 6504e1a06e5b4146b8c9225a62a13208 | LIPID MAPS category annotation and heatmap analysis of differential metabolites of polyketides. (A) Positive ion mode, (B) Negative ion mode: the horizontal coordinate represents the number of metabolites, and the vertical coordinate represents the LIPID MAPS lipid categories annotated to; this figure shows the number of metabolites annotated to the Main_Class under the eight major lipid categories in LIPID MAPS; (C) Heatmap display of the different substances of polyketides. | PMC9653782 | plants-11-02849-g006a.jpg |
0.446272 | 1ff2429dc5f64bd8b0e6b62197226ff7 | Tumour sizes observed in the four histologic groups. Box and whisker plots showing the distribution of tumour sizes stratified by histologic subtypes of testicular neoplasms. The boxes display the first quartile, median and third quartile. The whiskers are defined as the largest or lowest observed value that falls within 1.5 times the interquartile range measured from Q3 or Q1, respectively. Area of box relates to sample size. □ outliers; + denotes arithmetic mean; SE seminoma; NS nonseminoma; BT benign tumours; OM other malignancies. | PMC9653836 | cancers-14-05447-g001.jpg |
0.426309 | 83314dab136944079fa6bfcfaa90c2bd | Typical subcentimeter testicular neoplasm. Surgical specimen of a 6 mm sized benign Leydig cell tumour excised by testis sparing surgery. | PMC9653836 | cancers-14-05447-g002.jpg |
0.392695 | 07a51050e1b34a3cbc5fadca319b01ed | Proportions of histologic subgroups in testicular tumours sized >10 mm and ≤10 mm. | PMC9653836 | cancers-14-05447-g003.jpg |
0.410482 | fd485b0947914fbfb7a0c4275db72d1a | ROC analysis for predicting histology of a testicular neoplasm by its size. | PMC9653836 | cancers-14-05447-g004.jpg |
0.401435 | d851eade2a5a4d95828b84aa35ea3127 | Probability curve for prediction of malignant histology of a testicular neoplasm. The logistic regression curve indicates the probability of a given tumour size to predict malignancy. Shadowed area represents 95% confidence intervals. Neoplasms with a size of ≤8 mm involve a 50% probability of malignancy, while tumour sizes of ≥25 mm, ≥33 mm, and ≥39 mm involve probabilities of 95%, 99%, and 100%, respectively. | PMC9653836 | cancers-14-05447-g005.jpg |
0.4345 | 2f0d358f23694716b9b6571bd2e8c242 | Tumour sizes in clinical stages in germ cell tumours. Box and whisker plots showing the distribution of tumour sizes stratified by clinical stages of testicular neoplasms. The boxes display the first quartile, median and third quartile. The whiskers are defined as the largest or lowest observed value that falls within 1.5 times the interquartile range measured from Q3 or Q1, respectively. Area of box denotes sample size. □ outliers; + denotes arithmetic mean; CS clinical stage. | PMC9653836 | cancers-14-05447-g006.jpg |
0.504531 | df128ca7aa7442d7bf53a67b2b3834f1 | Expression rates of M371 and AFP and/or bHCG in germ cell tumours in relation to size of primary tumour in seminoma (A) and in nonseminoma (B). Blue columns denote expression rates of AFP and/or bHCG in five categories of tumour size, red columns indicate expression rates of M371. Overall, the expression rates of all tumour markers were higher in nonseminoma than in seminoma. All markers showed a significant trend towards lower expression rates with decreasing tumour size. M371 had higher expression rates than the other markers even in the smallest tumour size category. Error bars represent 95% CIs. | PMC9653836 | cancers-14-05447-g007.jpg |
0.43022 | 0031403c50b143aaaccc75ed5da09c39 | The function of ZFPs in regulating the cellular biological processes of colon cancer. ZFPs play important roles in the regulation of cell proliferation, epithelial–mesenchymal transition (EMT), invasion and metastasis, inflammation, cell cycle, cancer stem cells and DNA methylation in colon cancer cells. (This figure was created with biorender.com). | PMC9654003 | cancers-14-05242-g001.jpg |
0.458354 | 1993651be7434ce78239e386bb5625a8 | The possible mechanisms of ZFPs in regulating the cell cycle of colon cancer. There are various zinc finger proteins involved in cell cycle processes, such as ZFP91, ZFP278, ZFP692, Slug, KLF6-SV2, and P52-ZER6. The underlying mechanisms involve cyclin D, cyclin E, E2F, p21, p53, Bax, and MDM2. The underlying mechanism affects multiple molecules, such as cyclin D, cyclin E, E2F, p21, p53, Bax, and MDM2, eventually inducing cell progression or inhibiting cell proliferation in colon cancer. These ZFPs have great potential as novel therapeutic targets for colon cancer. (This figure was created with biorender.com). | PMC9654003 | cancers-14-05242-g002.jpg |
0.430177 | fae46165785f41e9aa215797e3f39026 | In colon cancer, MZF1 plays dual and opposite roles in different signaling pathways: (a) MZF1 transcriptionally activates the downstream target gene Axl and stimulates various signaling pathways, such as PI3K, FAK, Grb2/Ras, MEK/ERK, advancing cell proliferation, EMT transformation, invasion, and metastasis in colon cancer. (b) MZF1 transcriptionally activates the downstream target gene p55PIK; stimulates diverse signaling pathways such as PI3K/Akt and PI3K/RAC; and activates a series of downstream target genes such as CDC2, ALDH, BCL2, TWIST, SNAIL, and SLUG, promoting cell proliferation, EMT transformation, invasion, and metastasis in colon cancer. (c) MZF1 transcriptionally triggers the downstream target gene c-myc and multiple downstream target genes, such as MINA53, ID2, BCL2, and PTMA, promoting proliferation in colon cancer. (d) Sulfide sulindac sulfide induces the upregulation of MZF1. MZF1 promotes the expression of DR5 that interacts with FADD to activate caspases, promoting cell apoptosis and eventually inhibiting metastasis in colon cancer. (This figure was created with biorender.com). | PMC9654003 | cancers-14-05242-g003.jpg |
0.439117 | f88fcbb9ff954826836de6b26bbc35e6 | Comparison of the concentration of α-syn between patients with AD, DLB and NC. ***: p < 0.001. | PMC9654229 | ijms-23-13488-g001.jpg |
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