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0.41859 | f348ed4b1f2e43a49ee605fdbef3f9fa | Percentage of patients with spherical equivalent (within ±0.5D) at postoperative follow-up visit in 10 study hospitals (H1–H10). | PMC10314652 | bmjopen-2023-071860f04.jpg |
0.458072 | 06e780a7a5ed4271897a58919eec08ed | Patient’s pedigree showing a family history of cancer and the patient’s history of multiple cancers. The arrow indicates the presenting patient. Filled circles or squares indicate individuals who developed cancer. Ca. cancer, MFH malignant fibrous histiocytoma, y year-old, d. dead | PMC10314830 | 10014_2023_461_Fig1_HTML.jpg |
0.484317 | 7909187d198845a09b2a72af1b86c706 | T2-weighted magnetic resonance images of the tumor at different stages of its development. a preoperatively; b 1 month postoperatively; c at first recurrence, 4 months postoperatively; d at second recurrence, 3 months after irradiation. The tumor has recurred outside the irradiated area; e 9 months after the first irradiation. The tumor has extended into the left cavernous sinus; f the tumor extends toward the maxillary sinus 16 months after initial irradiation; g 18 months after the first irradiation, the tumor continues to grow; h after two doses of an immune checkpoint inhibitor (pembrolizumab), the tumor is still growing; and i after the third dose of pembrolizumab, the tumor begins to shrink. It continues to shrink for the remainder of the course of treatment (seven doses in total) | PMC10314830 | 10014_2023_461_Fig2_HTML.jpg |
0.42288 | 7bc3202015b14abb8612b977cc47a891 | Histopathology. H&E staining at a 100x, b 400x, and c 400x. Findings of the immunohistochemical staining (all 200x) for d brachyury, e INI1, f BRG1, g Ki-67, h PD-1, and i PD-L1. Typical histological features of conventional chordoma with abundant extracellular matrix a, b the area is composed of cohesive sheets of larger epithelioid cells with relatively severe nuclear atypia and pleomorphism. No myxoid stroma is present (c). Diffuse nuclear staining for brachyury (d). Intact INI1 (e) and BRG1 (f) expression. PD-1-positive intratumoral lymphocytes (h). PD-L1-positive tumor cells (i). H&E hematoxylin and eosin; PD-L1 programmed death-ligand 1 | PMC10314830 | 10014_2023_461_Fig3_HTML.jpg |
0.434787 | f6994efc03544f69aab4ddebcf26a0c0 | Requirements of ideal absorption with a single-mirror structure.Maximum absorbance vs. the real part of the 2D optical conductivity \documentclass[12pt]{minimal}
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\begin{document}$${\sigma }^{{\prime} }$$\end{document}σ′ of a a freestanding 2D material and b a 2D material with Salisbury screen. In both panels, the gray shaded areas highlight ideal absorption conditions (absorbance greater than 99% with Salisbury screen) where \documentclass[12pt]{minimal}
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\begin{document}$${\sigma }^{{\prime} }$$\end{document}σ′ ranges from 2.17 mS to 3.24 mS. c Calculated \documentclass[12pt]{minimal}
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\begin{document}$${\sigma }^{{\prime} }$$\end{document}σ′ of various freestanding 1L TMD materials obtained by first-principles calculations. | PMC10314950 | 41467_2023_39450_Fig1_HTML.jpg |
0.46912 | 1c37edaceae54b1f88073bf223505d65 | Degradation of band nesting due to the interlyaer coupling.a Electronic band structures, b momentum-resolved band nesting maps, c real part of 2D optical conductivities, and d absorbances of freestanding mono and bilayer MoS2. a Green arrows highlight an excellent band nesting of monolayer MoS2, whereas red arrows show the destruction of the band nesting in the bilayer due to the interlayer coupling. b The color contour map indicates the energy difference between the energy of the lowest conduction, EC, and the highest valence band, EV, and the solid green lines show the first Brillouin zone. c, d A gray dashed line indicates an artificial bilayer structure having no interlayer coupling. | PMC10314950 | 41467_2023_39450_Fig2_HTML.jpg |
0.427602 | 7f3c410bf9bd48da8b9e44eb939bdcf2 | Absorption enhancement through optimizing band nesting.a Schematic diagram of absorption enhancement strategies; layer twisting and inserting a buffer layer between the top and bottom layers. Green, yellow, and black spheres indicate molybdenum, sulfur, and carbon atoms. Theoretically calculated absorbances and experimentally measured optical contrast of (b, c) twisted 2L MoS2 and (d, e) 2L MoS2 with an intermediate buffer layer. b–e We also show spectra of 1L and 2L MoS2 shown as dashed black and red lines, respectively. c The inset shows the angle-dependent optical contrast of twisted 2L MoS2 near the 30° twisted angle. | PMC10314950 | 41467_2023_39450_Fig3_HTML.jpg |
0.501375 | 979b8b274c6c4aa9b547a7ae71ac9162 | Realization of near-perfect light absorbers with Salisbury screen.a Schematic representation of our Salisbury screen structure. The thickness of the SiO2 was 199 nm, satisfying the critical coupling condition for the photon energy of the C exciton (2.83 eV). b Calculated and c experimentally measured absorbance spectra of various MoS2 structures with Salisbury screen. c Absorbance can be obtained from 1-R/R0, where R and R0 are the reflectances of the substrate with and without the 2D heterostructure, and the inset shows the raw data of reflectances for MoS2/Gr/MoS2 heterostructures. | PMC10314950 | 41467_2023_39450_Fig4_HTML.jpg |
0.412943 | 9cdc40dcc7c34ff9a356ebd1b42f0c60 | Near-perfect light absorbers over a wide frequency.Calculated absorbance spectra on a SiO2/Ag cavity structure of various 2D materials with a 1L, b 2L, and c 2L with buffer. We note that the thickness of the SiO2 was optimized for each material, as summarized in Supplementary Fig. S19. | PMC10314950 | 41467_2023_39450_Fig5_HTML.jpg |
0.439311 | 60e4a572d2894e07899190cc7a72bff9 | Overview of macrophage interactions with planktonic S. aureus and biofilm. Different stages of S. aureus infection influence macrophage polarization and cytokine secretion toward pro-inflammatory or anti-inflammatory. Planktonic S. aureus can be recognized by TLRs and phagocytosed by macrophages, which destroy the bacteria through antimicrobial mechanisms, leading to pro-inflammatory responses. However, biofilm can evade these mechanisms and proliferate within macrophages, driving macrophages toward an anti-inflammatory phenotype, leading to bacterial persistence, host cell death, and chronic infection. This process is driven by the infection microenvironment and biofilm-derived signals that are largely unknown (indicated by question mark). Furthermore, MDSCs inhibit T cell and macrophage immunity, inducing immune tolerance and exacerbating the infection. PAMPs, pathogen-associated molecular patterns; TLR-2, toll-like receptor 2; TLR-9, toll-like receptor 9; iNOS, inducible nitric oxide synthase; Arg-1, arginase 1; ROS, reactive oxygen species; IL-1β, interleukin-1β; TNF-α, tumor necrosis factor-α; IFN-γ, interferon-γ; MDSCs, myeloid-derived suppressor cells; IL-4, interleukin-4; IL-10, interleukin-10; IL-12, interleukin-12; IL-17, interleukin-17; TGF-β, transforming growth factor-β. | PMC10315156 | jin530385_f01.jpg |
0.384649 | 52cfad8e03d2456091a8ad0d9649c5f3 |
S. aureus infection affects macrophage metabolism to regulate the inflammatory response. Macrophages respond to planktonic infections via TLRs, triggering the expression of markers such as iNOS, CD80, CD86, and MHC-II and the release of inflammatory factors, such as IL-1β, TNF-α, IFN-γ, IL-6, and IL-12. Glycolysis-based metabolic processes provide anabolic intermediates for the pro-inflammatory response, and the fatty acid synthesis and pentose phosphate pathway are also involved, which are associated with the disruption of the TCA and formation of ROS. In contrast, biofilm infection polarizes macrophages to an anti-inflammatory state. The cellular metabolism is dominated by oxidative phosphorylation (OxPhos) and fatty acid oxidation (FAO), which may involve several receptors associated with anti-inflammatory cytokines (i.e., CD36, IL-10R, IL-4R, IL-13R, A2R) as well as transcription factors (i.e., STAT3, STAT6, PPARγ), which leads to the production of cytokines, such as Arg-1, TGF-β, IL-10, IL-4, IL-13, IL-8, and VEGFA. Nutrient and oxygen gradients in the tissue microenvironment also influence the macrophage inflammatory response phenotype, which is closely related to the metabolic state of macrophages. Given the distinct immune metabolism modes of macrophages during planktonic and biofilm infections, a promising therapeutic approach for biofilm infection would be to regulate immune function by interfering with key nodes of the macrophage metabolic pathway, which have been marked in red (glycolysis, OxPhos, and IDH and SDH in Krebs cycle). G-6-P, glucose-6-phosphate; PPP, pentose phosphate pathway; FAS, fatty acid synthesis; OxPhos, oxidative phosphorylation; TCA, tricarboxylic acid cycle; HIF-1α, hypoxia inducible factor-1α; IDH, isocitrate dehydrogenase; SDH, succinate dehydrogenase; Acetyl-CoA, acetyl-coenzyme A; α-KG, alpha-ketoglutarate; u-PFK2, ubiquitous 6-phosphofructo-2-kinase/fructose bisphosphatase-2; iNOS, inducible nitric oxide synthase; NO, nitric oxide; Arg-1, arginase 1; NADPH, nicotinamide adenine dinucleotide phosphate; ROS, reactive oxygen species; MHC-II, major histocompatibility complex class 2; STAT3, signal transducer and activator of transcription 3; STAT6, signal transducer and activator of transcription 6; PPARγ, peroxisome proliferator-activated receptor-γ; FAO, fatty acid oxidation; IL-1β, interleukin-1β; IL-6, interleukin-6; IL-12, interleukin-12; TNF-α, tumor necrosis factor-α; IFN-γ, interferon-γ; TGF-β, transforming growth factor-β; VEGFA, vascular endothelial growth factor A; IL-10, interleukin-10; IL-4, interleukin-4; IL-13, interleukin-13; IL-8, interleukin-8; IL-4R, interleukin-4 receptor; IL-10R, interleukin-10 receptor; A2R, adenosine receptor. | PMC10315156 | jin530385_f02.jpg |
0.417813 | fa465aabbd684dacaa77ab43e05605e4 | Strategies to facilitate macrophage-mediated S. aureus biofilm clearance. Biofilm can be eradicated by using a combination of antimicrobial agents and new drug delivery systems, such as exosomes, liposomes, and nanoparticles, which can penetrate into the biofilm and disrupt it. Physical and chemical methods, biological enzymes, and proteins have also been applied to disperse biofilm. Improving host responses via targeting the immune system and key nodes of immune-related pathways is also a useful biofilm treatment strategy. Modifying implant materials to protect implants from S. aureus attachment and to modulate the phenotype of macrophages is a promising way to prevent biofilm formation. MΦ, macrophage; US-PCCA, ultrasound-stimulated phase-change contrast agent; LSW, laser shockwave; US, ultrasound; PDT, photodynamic therapy; d-AA, d-amino acid. | PMC10315156 | jin530385_f03.jpg |
0.446557 | 8a9e9d692afd46c9aea6a7c870cd6e9c | The biogenesis of Extracellular Vesicles (EVs). Extracellular vesicles are membrane vesicles from various origins. Recently, EVs are classified into two distinct groups-exosomes and microvesicles. Microvesicles are formed by budding of plasma membrane and exosomes are generated from intraluminal vesicles within the lumen of multivesicular body (MVB) that are sequentially fused with the plasma membrane. Several proteins are implicated in exosome biogenesis such as Rab GTPases, ESCRT proteins, and other proteins that are also used as markers for exosomes (e.g. tetraspanins, TSG101, Alix). Exosomes include tetraspanins (e.g. CD63, CD81, CD9), MHC complex, transmembrane receptor, and adhesion proteins in their surface. It has been reported that exosomes contain different types of intracellular proteins, DNA, and RNA including non-coding RNAs (ncRNA). | PMC10315562 | bmb-56-6-335-f1.jpg |
0.483457 | 2cfbe52aeaf24c2fb44d753d8f5b0149 | The dual roles of EVs during HIV-1 infection. The EVs released upon HIV-1 infection have shown to have antiviral and proviral functions. EVs contribute to suppress HIV infection by limiting viral replication or enhancing antiviral immunity. CD4-containing EV may serve as a decoy for CD4 T cells and neutralize HIV-1 virions. Exosomal cargo such as APOBEC3G (A3G) inhibit HIV-1 replication. EVs can transport ISGs such as ISG15, ISG56, and MX2 trigger antiviral immunity and EVs derived from bodily fluids such as breast milk, semen, and vaginal fluids can hider HIV-1 infection. However, EVs also can promote HIV-1 infection and pathogenesis. Co-receptors such as CCR5 or CXCR4 can be delivered to neighboring cells via EVs, enhancing susceptibility to HIV-1 infection. TIM-4-containing EVs assit trafficking of HIV-1 to immune cells. EVs can carry TAR element RNA to enhance susceptibility to HIV-1 infection in undifferentiated immune cells. Transport viral component by EVs may enhance viral entry and infectivity. EV-mediated transport of HIV-1 Nef protein may lead viral-mediated apoptosis of immune cells. Well-known TNFα converting enzyme ADAM17 can be loaded into EVs. These EVs can contribute to chronic inflammation by secretion of mature TNFα. Host-derived miRNAs or viral miRNAs can be transported by EVs, resulting in enhancement of HIV-1 infection and chronic immune activation, leading to HIV-1 pathogenesis. | PMC10315562 | bmb-56-6-335-f2.jpg |
0.423243 | 3839e64c28424446929dfcfca72d5963 | MM cells are selectively sensitive to CDK7 inhibition. (A) Primary cells from patients newly diagnosed with MM (n = 4), MM cell lines (n = 30), PHA-activated PBMCs (n = 9), and nontransformed human cell lines (GMO5756, IMR90, HEEpiC, and HS-5 cell lines) were treated with different concentrations of YKL-5-124 for 48 hours and assessed for cell viability using CellTiter-Glo (CTG). IC50 analysis was performed with GraphPad software. Data are shown as the mean value ± SD; ∗∗∗P < .001. (B) H929 and AMO1 cells were engineered with a dTAG epitope (dTAG-CDK7WT). Cell viability was measured in H929 dTAG-CDK7WT and AMO1 dTAG-CDK7WT cells after treatment with dTAG˅-1 by CTG and represented as fold change increase compared with time of seeding (T0). (C) Control and YKL-5-124–treated MM cells were subjected to global quantitative TMT-based proteomic and phosphoproteomic analyses. KSEA for prediction of kinase activity was applied to identify activated (green bars) and inhibited kinases (red bar) in the YKL-5-124–treated group compared with control cells. (D) Whole-cell lysates from H929 cells treated with several concentrations of YKL-5-124 for 24 hours were subjected to western blot (WB) analysis and probed with indicated antibodies, with GAPDH or tubulin as a loading control (left). The ratio of phosphorylated/total forms of indicated CDKs was analyzed with Image J software and represented as fold change from untreated cells. Mean values ± SD in 3 MM cell lines is shown in the graph (right). (E) Whole-cell lysates from H929 cells treated with several concentrations of YKL-5-124 for different times (1, 4, 6, and 16 hours) were subjected to WB analysis and probed with selected antibodies (upper). The ratio of phosphorylated/total RNA polymerase II was analyzed with Image J software and represented as fold change from untreated cells. Mean values ± SD in 3 MM cell lines is shown in the graph (lower). IC50, 50% inhibitory; KSEA, kinase-substrate enrichment analysis; PBMCs, peripheral blood mononuclear cells; PHA, phytohemagglutinin; SD, standard deviation; TMT, tandem mass tag; WT, wild type. | PMC10315622 | BLOOD_BLD-2022-018885-gr1.jpg |
0.489407 | b673d19e0f4048d484cc6c7887930a3b | Impairment of T-loop phosphorylation by CDK7 inhibition causes cell cycle arrest and Rb activation in MM cells. (A) MM cell lines (n = 8) were treated with the indicated concentrations of YKL-5-124 for 24 hours. Cell cycle was evaluated by propidium iodide staining followed by flow cytometric analysis and analyzed with ModFit LT 5.0 software. (B) Whole-cell lysates from H929 and AMO1 cells treated with the indicated concentrations of YKL-5-124 for 24 hours were subjected to WB analysis and probed with antibodies against Rb and p-Rb, and GAPDH as a loading control. The ratio of phosphorylated/total forms of indicated Rb was analyzed with Image J software and represented as fold change from untreated cells. Mean values ± SD in 4 MM cell lines is shown in the graph. (C) H929 cells stably expressing E2F1 luciferase reporter were treated with 50 nM YKl-5-124 for 24 hours. E2F1 activity was assessed using the Promega luciferase reporter assay system, and fold change of E2F1 activity compared with untreated cells is displayed (mean ± SD). ∗∗∗P < .001. (D) H929 and AMO1 cells were treated with 250 nM YKL-5-124 for 24 hours, and the nuclear extract was analyzed by EMSA. The shifted probe caused by E2F1 binding is indicated by the band labeled E2F1. (E) H929 and AMO1 cells were treated with 500 nM YKL-5-124 for 24 hours and chromatin immunoprecipitated using E2F1 or control mouse IgG antibodies. The crosslinked DNA was subjected to quantitative polymerase chain reaction using primers specific for a representative set of E2F1 target genes. Data are represented as the percentage of input. (F) E2F score was calculated by using E2F1 genes identified previously.11 After RNA-seq normalization, we converted expression values for each gene to z scores, with a mean of 0 and SD of 1. After scaling the expression, we calculated the total score as the sum of scaled scores from all the genes. A Pearson correlation coefficient was calculated between E2F score and CDK7 expression. (G) AMO1 cells expressing control vector (PCW) or T121 were treated with doxycycline for 24 hours, followed by YKL-5-124 (500 nM) for 6 hours, and then chromatin immunoprecipitated using E2F1 or control mouse IgG antibodies. The crosslinked DNA was subjected to quantitative polymerase chain reaction using primers specific for a representative set of E2F1 target genes. Data are represented as the percentage of input. (H) AMO1 cells expressing either PCW or T121 plasmid were treated with doxycycline for 24 hours, followed by YKL-5-124 for 24 hours. The cell cycle was evaluated by propidium iodide staining followed by flow cytometric analysis. (I-J) MM cells expressing either control or T121 plasmid were treated with doxycycline for 24 hours followed by YKL-5-124 treatment for 48 hours. Cell viability was measured by CTG assay (I) and apoptosis by annexin V+ staining (J). Data represent the mean of 4 independent experiments. IgG, immunoglobulin G; SD, standard deviation. | PMC10315622 | BLOOD_BLD-2022-018885-gr2.jpg |
0.409587 | 0c3cb996c06e469f9c6af431315f0319 | YKL-5-124 treatment disrupts oncogenic gene expression programs in MM. (A) Scatter plot visualizing gene set enrichment analysis normalized enrichment score comparisons between H929 and AMO1 cells treated with DMSO or YKL-5-124 (100 nM) for 24 hours. The bar graph shows NES for the top 18 gene signatures in both cell lines after treatment with YKL-5-124. (B) Biological upstream regulators associated with CDK7 inhibition were identified using ingenuity pathway analysis (IPA). (C) Whole-cell lysates from AMO1 and H929 cells treated with YKL-5-124 for 0.5 to 4 hours were subjected to WB analysis and probed with MYC antibody, with GAPDH as a loading control. The ratio of MYC/GAPDH was analyzed with Image J software and represented as fold change from untreated cells. Mean values ± SD in 2 MM cell lines is shown in the graph. (D) The diagram depicts the intermediates of glycolysis, and the enzymes regulated by CDK7 (red bars). Mean of log2-fold change for H929 and AMO1 cells after treatment with YKL-5-124 are shown (∗P < .05). (E) Bubble plot showing the differentially expressed proteins involved in the glycolytic pathway after treatment with YKL-5-124 for 24 hours. The x-axis displays the log2 (fold change), and the y-axis represents the negative log of the adjusted P value. (F) A panel of cells treated with YKL-5-124 for 24 hours was subjected to western blot analysis and probed with antibodies against HK2 and β-actin as a loading control (upper panel). The ratio of HK2/actin was analyzed with Image J software and represented as fold change from untreated cells (lower panel). Mean values ± SD in 5 MM cell lines are shown in the graph. (G) ChIP-seq tracks showing MYC signal on individual loci for LDHA and HK2. The x-axis shows genomic coordinates with gene model depicted below. The y-axis shows signal in units of rpm/bp. (H) MM1S cells were treated with YKL-5-124 for 6 hours and subjected to ChIP with a MYC or IgG antibody. HK2, LDHA, and a negative control region were amplified by polymerase chain reaction. Data are shown as mean ± SD of triplicates and represented as the percentage of input. bp, base pair; ChIP, chromatin immunoprecipitation; CHIP, clonal hematopoiesis of indeterminate potential; DMSO, dimethyl sulfoxide; FDR, false discovery rate; IgG, immunoglobulin G; NES, normalized enrichment score; rpm, units of reads per million; SD, standard deviation. | PMC10315622 | BLOOD_BLD-2022-018885-gr3.jpg |
0.405838 | 41e4f5509ffa400fb38a23a82174e80c | MYC-dependent aerobic glycolysis is impaired in CDK7-inhibited MM cells. (A) DepMap CRISPR screen (Avana library 18Q4) dependency data indicating that MM cell lines are among the most sensitive to HK2 depletion based on cell line rank. Mean of chronos scores for each disease type are shown in the graph. (B-C) H929 and AMO1 cells were treated with DMSO or YKL-5-124 and analyzed with a glycolysis stress assay on a Seahorse XFe96 extracellular flux analyzer. (B-C) ECAR was detected at baseline, after injection of glucose, oligomycin, and 2-deoxy-D-glucos e (2-DG). Basal glycolytic rate and spare glycolytic capacity were analyzed by overall ECAR in control and YKL-5-124–treated groups at different concentrations of YKL-5-124. (D) Representative 18F-FDG PET-computed tomography images (upper panel) and quantification (lower panel) of H929 cell xenografts in mice after treatment (10 mg/kg YKL-5-124 or vehicle, for 3 days). Bar graphs represent the SUV maximum and corresponding TV for mice. (E) LDH activity was measured in cell lysate from AMO1 cells treated with YKL-5-124 for 24 hours. (F) Culture supernatant (5 μL) from both untreated cells after 6 and 24 hours of culture, and 24 hour–treated cells was used to measure lactate secretion using Lactate-Glo assay. (G) H929 and AMO1 cells were transduced with empty vector or HK2-overexpression vector and subjected to western blot analysis or treated with YKL-5-124 for 72 hours for cell killing assessment. IC50 values are shown in the graph. (H) H929 and AMO1 cells were cultured in glucose or galactose (10 mM) media for a week and treated with DMSO or increasing concentrations of YKL-5-124. Cellular viability was determined by CTG assay. (I) Three MM cell lines (H929, AMO1, and MM1S) were cultured in the presence of different concentrations of YKL-5-124 with or without bortezomib (2.5 nM), lenalidomide (5 μM), melphalan (2.5 μM), or carfilzomib (1 nM), and cell survival was assessed by CTG. Data are presented as CI values evaluated using the Calcusyn software. CI, combination index; DMSO, dimethyl sulfoxide; ECAR, extracellular acidification rate; IC50, 50% inhibitory; PET, positron emission tomography; SUV, standardized uptake value; TV, tumor volume. | PMC10315622 | BLOOD_BLD-2022-018885-gr4.jpg |
0.535996 | 7ffb96a0e0044342aa94288cde13ef3e | CDK7 inhibition reduces myeloma burden and enhances survival in vivo mouse models of MM. (A) BMMNC from 3 patients with relapsed MM were treated with 500 nM YKL-5-124 or DMSO for 24 hours. Cell viability in the CD138+ and CD138− cell populations was evaluated by flow cytometry analysis. (B) Primary CD138+ cells were cultured in the absence or presence of YKL-5-124 for 3 days, and apoptotic cell death was assessed by flow cytometric analysis. Percentages of annexin V+/DAPI− (early apoptosis) and annexin V+/DAPI+ (late apoptosis) cells are shown in the graphs. (C) A schematic diagram for the subcutaneous SCID model. (D) In the early treatment model, mice injected with H929 cells were randomized and treated with either YKL-5-124 or vehicle at first detection of tumor (tumor volume ∼100 mm3). Mice received 3 different doses of YKL-5-124 for 5 consecutive days per week for 2 weeks. Tumor volume was measured in 2 perpendicular dimensions by caliper once every week. Baseline values were not significantly different among groups. (E) Sublethally irradiated SCID mice were injected subcutaneously with AMO1 cells expressing CDK7WT (left) or CDK7C312S (right). Mice were randomized to a 5 or 10 mg/kg group, for 5 consecutive days per week for 2 weeks. Tumor volume was evaluated by caliper measurement. P values indicate significant difference between groups. ∗∗∗P < .001. (F) Western blot analysis was performed in cell lysates from tumors excised from representative mice and blotted with Rb and p-Rb antibodies. (G) Western blot analysis was performed in cell lysates from tumors excised from representative mice and blotted with indicated antibodies. Images were analyzed with Image J software and signals normalized to loading control. (H-J) NSG mice were orthotopically xenografted after intravenous injection with Molp8-luc cells. Upon detection of MM lesions (∼2 weeks after tumor cell injection), mice were randomly assigned to receive YKL-5-124 (2.5 or 5 mg/kg, intraperitoneal, 5 days per week, for 4 weeks) or vehicle control. Whole-body bioluminescence images (BLI) (H) and measurements (mean ± SEM) (I) are shown. Survival was evaluated from the first day of treatment until death. Survival curves (Kaplan-Meier) were analyzed using GraphPad analysis software (log-rank test, P = .0002) (J). (K) Monoclonal, tumor-derived, immunoglobulin (M-protein) levels were evaluated in MM-bearing Vk∗MYC mice before and after YKL-5-124 treatment (5 and 10 mg/kg) and normalized to time 0. BMMNC, bone marrow mononuclear cells; DMSO, dimethyl sulfoxide; NSG, NOD/SCID-γ; SCID, severe combined immunodeficiency. | PMC10315622 | BLOOD_BLD-2022-018885-gr5.jpg |
0.588075 | adcb70ee118a44b7882e75d431a8aeb9 | Association between the number of MTs and the overall population reduction rate. Adjusted R2 = 0.81, P = 0.03, MT: Mechanical thrombectomy. | PMC10316200 | SNI-14-207-g001.jpg |
0.505624 | 1384df66326c4864b5fb1bf75d68f880 | Association between the number of MTs and the increasing rate of the population over 65 years old. Adjusted R2 = 0.74, P= 0.06, MT: Mechanical thrombectomy. | PMC10316200 | SNI-14-207-g002.jpg |
0.523203 | de069ef9dbe648d08315c65e8fd83ed7 | PRISMA flow diagram.From: Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ 2021;372:n71. Doi: 10.1136/bmj.n71. For more information, visit: http://www.prisma-statement.org/. | PMC10317240 | pone.0286678.g001.jpg |
0.433409 | 2da12321837d4a448530d565dcd77bf3 | Decision-making algorithm for the management of large intermediate hepatocellular carcinoma.AFP, alphafetoprotein; HCC, hepatocellular carcinomacer; HVPG, hepatic vein pressure gradient; LR, liver resection; SRLV, standard remnant liver volume; TACE, transcatether arterial chemoembolisation; TRC, platelets; PV, portal vein. | PMC10318282 | JCTH-11-757-g001.jpg |
0.424384 | 1c246ec459ea41ed95358ca4bc4dffca | Bar chart showing the number of doses (Hepatitis B vaccine) in the participants across the secondary and tertiary health facilities in Nigeria from January-June 2021 | PMC10318692 | 13690_2023_1142_Fig1_HTML.jpg |
0.411197 | 16b6248285db4d7b9b265e6fd093dcf4 | Selection of surgical therapy for trigeminal neuralgia after insufficient conservative treatment | PMC10319675 | 701_2023_5656_Fig1_HTML.jpg |
0.408796 | 7719b06894cf47f2bdb1e4d786b62995 | Fluoroscopy-guided percutaneous balloon compression in lateral view. A) The tip of the cannula slightly enters the foramen ovale, while the deflated Fogarty® embolectomy catheter is positioned with its tip at the border of the clivus. B) When the balloon is inflated, it ideally adopts the shape of the trigeminal cistern and reaches a pear-like shape with its tip lying in the trigeminal pore | PMC10319675 | 701_2023_5656_Fig2_HTML.jpg |
0.42539 | 30633d7b333e4025a314b630c67ef5e7 | Selection criteria for patients with trigeminal neuralgia treated by percutaneous balloon compression or radiofrequency thermocoagulation and performed analysis | PMC10319675 | 701_2023_5656_Fig3_HTML.jpg |
0.42432 | dc7ee0fda5eb46db90d0eb70afa8c689 | Kaplan-Meier survival analysis of patients with trigeminal neuralgia shows a slight advantage for percutaneous balloon compression over radiofrequency thermocoagulation in the probability of pain recurrence. Median pain recurrence was 481 days after percutaneous balloon compression in comparison to 421 days after radiofrequency thermocoagulation. While the classification of trigeminal neuralgia shows no influence, pronounced postoperative hypesthesia is likely to be a positive predictor on the duration of the postoperative pain-free interval. BNI, Barrow Neurologic Institute | PMC10319675 | 701_2023_5656_Fig4_HTML.jpg |
0.423829 | 623bf2b6a13c432e8e06b1ecfa5f0bf8 | Map of the barklice sampling sites in Georgia within the CaBOL project 2018–2022. | PMC10320554 | zookeys-1168-077_article-103666__-g001.jpg |
0.445549 | eff84d2959704a6494d4a6cce3e302c2 | Species ratio within the families of the Georgian barklice (n = 47). | PMC10320554 | zookeys-1168-077_article-103666__-g002.jpg |
0.461534 | 0c433fd25b18460eb3c7550bee42c7f6 | General habitus in lateral view of AKolbiaquisquiliarum Bertkau, 1882, male BCaeciliusfuscopterus (Latreille, 1799), male CEctopsocusbriggsi McLachlan, 1899, female DLachesillapedicularia (Linnaeus, 1758), male. Scale bars: 1 mm. | PMC10320554 | zookeys-1168-077_article-103666__-g003.jpg |
0.460987 | b9fb53fd5d1a4518a695e4622c642384 | General habitus of APeripsocusalboguttatus (Dalman, 1823), male, lateral view BAaroniellabadonneli (Danka, 1950), female, dorsal view CTrichadenotecnumsexpunctatum (Linnaeus, 1768), male, lateral view DGraphopsocuscruciatus (Linnaeus, 1768), male, lateral view. Scale bars: 1 mm. | PMC10320554 | zookeys-1168-077_article-103666__-g004.jpg |
0.412335 | c93c164ec1bf481eaad8e828111634d3 | Chemical structures of naturally occurring Nrf2 inhibitors. | PMC10321279 | ijbsv19p3029g001.jpg |
0.474388 | d33e8c9e2dfe4b2f9758037b9fdbbe71 | Schematic presentation of the role of Nrf2 in cancer progression. | PMC10321279 | ijbsv19p3029g002.jpg |
0.468025 | b789d6ead84d46ef9b477e0da77b1e8b | Schematic presentation of the molecular mechanisms underlying the cancer prevention and treatment of natural compounds via inhibiting Nrf2 pathway. | PMC10321279 | ijbsv19p3029g003.jpg |
0.438314 | e35e62ae93df4031901e555263d66121 | Biological response of M1 plants to different doses of CIB irradiation. (A–D) Relative values of developmental index at seedling stage. (E–H) Relative values of photosynthetic pigment contents at tillering stage. (I–L) Relative values of chlorophyll fluorescence parameters at tillering stage. (M–P) Relative values of indicators at maturity period. Data represent the mean ± SD of three replicates. Different lowercase letters represent significant differences among treatments (P<0.05) by ANOVA analysis. The single-hit multi-target (SHMT) model equation is S = 1 − (1 − EXP(−D/D0))N. (A–K), (M, P) were fitted by nonlinear curves based on a SHMT model. (L, N, O) were fitted by nonlinear curves based on a dose-response-stimulation model. | PMC10322207 | fpls-14-1213807-g001.jpg |
0.489482 | 06fc7bfd7ce04b26b8346898512ba8b8 | Genomic mutations induced by CIB at each dose in M2 population. (A) Genome-wide distribution of mutations induced by six CIB doses in M2 population. The circular tracks (from inner to outer) represent the 12 rice chromosomes on a megabase scale; GC ratio and gene density are on 100-kb windows of the reference genome KitaakeX; Tracks iv to X represent the mutations induced by doses of 25, 50, 75, 100, 125, and 150 Gy, as well as the number of all mutations induced by six doses of CIB within a non-overlapping 100-kb range of chromosomes. The highest signal heights in these tracks represent nine mutations/100-kb, seven mutations/100-kb, seven mutations/100-kb, nine mutations/100-kb, eight mutations/100-kb, nine mutations/100-kb, and nine mutations/100-kb. The color bar represents gene density within a 100-kb chromosome region, with red indicating an increase in gene density and the highest point representing 27 genes/100-kb. Blue represents a decrease in gene density, with the lowest point representing zero genes/100-kb. (B) Percentages of SBSs, deletions and insertions in each dose group. (C) Average number of induced mutations. (D) Mutation frequency at each dose. (E) Zygosity of induced mutations. (F) Average number of affected genes. (C, D, F) data represent the mean ± SD of three replicates. Different lowercase letters represent significant differences among treatments (P<0.05) by ANOVA analysis. | PMC10322207 | fpls-14-1213807-g002.jpg |
0.505019 | d297c9d482124a5a91e78d736a18690d | Characteristic of SBSs and InDels induced by each dose of CIB. (A) Type and proportion of SBSs, the color bar values represent the normalized using data row scale. (B) Size distribution of InDels, the color bar values represent the normalized using data row scale. NA represents no such mutation found. (C) Genes highly impacted by SBSs and InDels. (D) Heatmap of all amino acid variations induced by CIB. The color bar represents the frequency of the amino acid variation, with darker shades of blue indicating a higher frequency of the amino acid variation. The highest mutation frequency is 5%. | PMC10322207 | fpls-14-1213807-g003.jpg |
0.48663 | 4067f956fbec4e518cd65c3c3ef3fab6 | Rates of mutation unique to each panicle or shared by different panicles of the same M1 plant. (A) Rates of shared and unique mutations at each CIB dose. (B) Numbers of shared mutations and unique mutations in three panicles of a single M1 plant from all CIB groups. | PMC10322207 | fpls-14-1213807-g004.jpg |
0.40711 | 4ff21c78ed7d4f909626096229cc63ac | Three mutants showing higher yields. Morphologies of whole plant, panicle, and grain, and yields of mutants A25 (A), A28 (B), and A96 (C) and Kitaake control. Scale bars of plants = 20 cm, scale bars of panicles = 5 cm, and scale bars of grains = 1 cm. Yields were calculated per square meter (m2) containing 50 plants in rice paddy fields with three replications. The asterisk represents a significant difference (P<0.05) by Student’s T Test. | PMC10322207 | fpls-14-1213807-g005.jpg |
0.529041 | 1e2ec6d1f7e6445db8d6cc7edb86e26a | Genomic variations and candidate genes of phenotypically stable M4 mutants. (A) Percentage of SBSs, deletions, and insertions. (B) Number of mutations in each mutant line. (C) Ts/Tv value in each mutant. (D) Proportion of various types of SBSs. (E) Size distribution of InDels. (F) Proportion of homozygous and heterozygous mutations in M4 generation. (G) Zygosity of each mutant. (H) Total number of affected genes in each mutant. (I) Highly and moderately impacted genes in each mutant. (J) Circos diagrams of mutations in M4. From the outer track to the inner track: the 12 chromosomes of rice represented on a megabase scale with the candidate genes on them, gene density on 100-kb windows of reference genome KitaakeX, and distribution of mutations on each chromosome in 11 mutants. The color bar represents gene density within a 100-kb chromosome region, with red indicating an increase in gene density and the highest point representing 27 genes/100-kb. Blue represents a decrease in gene density, with the lowest point representing zero genes/100-kb. The colors of the candidate genes, A25, A28, A96 and A66 for the mutants were highlighted with the colors being purple, green, red, and blue respectively. The candidate genes for the other mutants were displayed in black. | PMC10322207 | fpls-14-1213807-g006.jpg |
0.434477 | f35a892b02fe4ac68d7a9025888853df | Overview of the mutagenic effects of different CIB doses on successive multi-generations of rice. First, after the Kitaake M0 seeds were irradiated by ten CIB doses (25 – 300 Gy), the biological effects of different doses in the whole life cycle of M1 generation were systematically studied. Second, each single panicle (M2 seeds) of the same plant was separately harvested at the mature stage. Furthermore, the genomic variations in M2 plants and mutations unique to a single panicle or shared by different panicles of the same M1 plant induced by six CIB doses (25 – 150 Gy) were studied. Third, we also constructed M2 mutant populations from eight CIB doses (25 – 200 Gy). By examining the biological effects in M1 generation induced by ten CIB doses, the mutation characteristics in M2 generation induced by six CIB doses, and the M2 phenotypic mutation rates induced by eight CIB doses, we conclude that the optimal dosage should cause 75 – 100% Dq or 67 – 90% LD50. In addition, we selected a variety of phenotypic mutants in the M2 mutant population and verified the isolated mutants in M3 - M4 generations. Finally, we selected 11 M4 phenotypic mutants to study their mutation characteristics and candidate genes. | PMC10322207 | fpls-14-1213807-g007.jpg |
0.459489 | 8d47569e97f7444fac07bbfc8e21c08b | Applications of quantum dynamics learning.a Quantum dynamics learning of an experimental process using a quantum computer. b Quantum dynamics learning with a more specialized experimental system with potentially a limited gate set. c, d Quantum compilation of a known unitary on a quantum computer and classical computer, respectively. | PMC10322910 | 41467_2023_39381_Fig1_HTML.jpg |
0.460781 | c88e8f6d308b4898a8b8e6061e449e09 | Locally scrambled ensembles.Venn diagram showing how the class of ensembles that are locally scrambled up to the second moment, \documentclass[12pt]{minimal}
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\begin{document}$${{\mathbb{S}}}_{{{{{{{{\rm{LS}}}}}}}}}^{(2)}$$\end{document}SLS(2), divides naturally into training ensembles and testing ensembles. For the formal definitions of each of the ensembles referenced see Supplementary Note 1. | PMC10322910 | 41467_2023_39381_Fig2_HTML.jpg |
0.529142 | 60b2da1b7c6c4a5eba01157c61f384a8 | Out-of-Distribution Generalization for Hamiltonian Learning.Here we present our results from learning the Hamiltonian specified in Eq. (12) by training on only 2 product states. As the number of layers L in the ansatz is increased the obtainable cost function value decreases. We plot the correlation between the optimized cost \documentclass[12pt]{minimal}
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\begin{document}$${C}_{{{{{{{{{\mathcal{D}}}}}}}}}_{{{{{{{{\mathcal{Q}}}}}}}}}(2)}({{{{{{{\boldsymbol{{\alpha }}}}}}}_{{{{{{{{\rm{opt}}}}}}}}}}})$$\end{document}CDQ(2)(αopt) with \documentclass[12pt]{minimal}
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\begin{document}$${{{{{{{\mathcal{Q}}}}}}}}={{{{{{{{\mathcal{S}}}}}}}}}_{{{{{{{{{\rm{Haar}}}}}}}}}_{1}^{\otimes n}}$$\end{document}Q=SHaar1⊗n, and the (in-distribution) risk over product states, \documentclass[12pt]{minimal}
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\begin{document}$${R}_{{{{{{{{{\mathcal{S}}}}}}}}}_{{{{{{{{{\rm{Haar}}}}}}}}}_{1}^{\otimes n}}}$$\end{document}RSHaar1⊗n, and (out-of-distribution) risk over the Haar measure, \documentclass[12pt]{minimal}
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\begin{document}$${R}_{{{{{{{{{\mathcal{S}}}}}}}}}_{{{{{{{{{\rm{Haar}}}}}}}}}_{n}}}$$\end{document}RSHaarn. The lines indicate the joined values for L = 2, 3, 4, 5 for the different values of n indicated in the legend. | PMC10322910 | 41467_2023_39381_Fig3_HTML.jpg |
0.471091 | 5661152f6a5441019ec0c6a330c80622 | Training in the presence of noise.The cost function is optimized for two types of training data: (i) product states (red lines) and (ii) states prepared with deep circuits (blue lines). We performed 20 independent optimizations, each time initializing the optimization differently and selecting a different random training set. The shaded region represents the standard deviation of all 20 runs. Dotted (solid) lines represent in-distribution (out-of-distribution) risk. | PMC10322910 | 41467_2023_39381_Fig4_HTML.jpg |
0.487818 | 74de58db71844155b9d4f09ea3476328 | Study profile of children with Giardia duodenalis infection in a subset of children aged 9–36 months presenting with diarrhea at Mulago Hospital, Uganda. | PMC10324004 | ajtmh.22-0436f1.jpg |
0.510081 | 3aaa39e270ec474c8598ef1dcca26814 | Prevalence of Giardia duodenalis in Ugandan children aged 9–36 months during different months of the year. | PMC10324004 | ajtmh.22-0436f2.jpg |
0.469588 | e50e091f843f49519afe66a7ad094d40 |
Potential strategies for improving dysbiosis in preterm infants (PTIs).
The human milk microbiome and human milk oligosaccharides (HMOs) can effectively protect the gut microbiota (GM) in PTIs. Probiotics administration and fecal microbiota transplantation (FMT) can be used to improve preterm intestinal dysbiosis | PMC10324143 | 10020_2023_689_Fig1_HTML.jpg |
0.457016 | aa938fc4e35243aabf34cae92f2514ce |
Factors shaping the preterm infant (PTI) gut microbiota during early life and evolution
During the first weeks after birth, the human infant gut is colonized by facultative anaerobes, such as Enterobacteriaceae, Streptococcus, Enterococcus, and Staphylococcus. PTIs are more highly colonized by Staphylococcus than are full-term infants (FTIs) during this period, and PTIs gradually become dominated by anaerobic genera, including Bifidobacterium, Bacteroides, and Clostridium. Between 10 days and 3 months of age, Enterococcaceae and Lactobacilli dominance is observed in premature babies. After cessation of breastfeeding and the addition of solid foods, the gut microbiota gradually becomes dominated mainly by members of the anaerobic class Clostridia, a process required for maturation into an adult-like microbiota | PMC10324143 | 10020_2023_689_Fig2_HTML.jpg |
0.411471 | eca23c09132d496899580a72ef21d95d |
Entero-mammary pathway
Dendritic cells send dendrites out of the epithelium through tight junctions. Dendritic cells carrying bacteria migrate to the mesenteric lymph nodes, lactate mammary glands, and ultimately into milk. Through this entero-mammary pathway, the maternal gut microbiota (GM) finally reaches the gut of preterm infants (PTIs) | PMC10324143 | 10020_2023_689_Fig3_HTML.jpg |
0.459026 | a7d913073cd746bf8dc4bc11898aa31e |
Human milk oligosaccharides (HMOs) promote the growth of “good bacteria” and inhibit pathogenic colonization
HMOs help establish a healthy gut microbiota (GM) in at least two ways. First, HMOs exhibit a probiotic effect, promoting the growth of beneficial bacteria and inhibiting the growth of pathogens. Second, HMOs act as decoy receptors and bind pathogens, competing with them through adhesion to their receptors on epithelial cells, suppressing the colonization of pathogenic bacteria | PMC10324143 | 10020_2023_689_Fig4_HTML.jpg |
0.453173 | 429b734ee3e140f39bb22cc9815cf926 | A Pronase digestion of the paraffin tissue by denaturized cell membranes demonstrated the presence of intracytoplasmic monoclonal kappa light chains in the tubular cells. B Acid Fucsin Orange G (AFOG) staining (4x) demonstrated the presence of intratubular casts helping the diagnosis of Myeloma Cast Nephropathy | PMC10324208 | 12882_2023_3237_Fig1_HTML.jpg |
0.457411 | e8fdde38811c409db8a4b18b7f3dfc3a | Serum level of K-FLC Before and after each dialysis session. Percentages represented in the figure are referred to the reduction ratio per session (RR) for K-FLC, RR = (T0—T1-corr)/ T0 × 100. T0 was K FLC level before dialysis, T1 at dialysis end. The values measured at T1 were corrected for haemoconcentration due to the patient’s weight loss according to Bergström and Wehle’s formula [2] | PMC10324208 | 12882_2023_3237_Fig2_HTML.jpg |
0.450134 | befa82a4368f49b4bd6f564fb8a3595a | The first HRCT which shows mild pneumonia signs | PMC10324208 | 12882_2023_3237_Fig3_HTML.jpg |
0.458794 | 6e6e181cc066461b8bd4583e7787bd14 | The second HRCT with severe and bilateral Sars Cov2 interstitial pneumonia | PMC10324208 | 12882_2023_3237_Fig4_HTML.jpg |
0.382484 | 487e3d6c9add4fd786ff2cee645f6ccb | Seroconverted sentinel hamsters (i.e. passively vaccinated through transmission of Nsp1-K164A/H165A) are protected from BA.2.12.1 challenge.a Seroconverted sentinel hamsters (4.5 months after exposure to WA1-2020 and Nsp1- K164A/H165A) were challenged with 104 PFU of BA.2.12.1. A group of 8 age-matched naïve hamsters were also included in the challenge study as controls. Weight change was recorded for 7 days post-challenge. b–d Infectious virus titers from nasal swabs (*p = 0.0393, *p = 0.0416, **p = 0.0059, ***p = 0.0008) (b), BALF (c), and lung homogenates (d) were measured by focus-forming assays. e Viral sgRNA levels in the lungs were quantified by RT-pPCR 4 DPC and 7 DPC (**p = 0.0043, ***p = 0.0004). Dot plots represent samples collected from individual animals in a single experiment. Percentage of consolidation (*p = 0.0490, *p = 0.0326, *p = 0.0269) (f) and pathology scores in lungs (g) of sentinel hamsters (n = 6 for Nsp1-K164A/H165A, n = 7 for WA1/2020, and n = 8 for naïve controls) at 4 and 7 DPC with 104 PFU of BA.2.12.1. Individual lung pathologies at 4 DPC (h) and 7 DPC (i) are presented in heat maps. Dot plots in this graph represent samples collected from individual animals in a single experiment. Statistical differences were calculated using ordinary two-way analysis of variance (ANOVA) in GraphPad Prism 9.4.0 with Tukey’s multiple comparisons tests. For statistical significance, ****p < 0.0001. DPC days post-challenge. | PMC10250859 | 41467_2023_39090_Fig8_HTML.jpg |
0.443257 | d52d259713bf4e49a6d24defcd777f0c | Intranasal immunization of Syrian hamsters with 100 PFU Nsp1-K164A/H165A is protective against Omicron BA.5 challenge.a Syrian hamsters (male, 5 months old) were vaccinated with 100 PFU Nsp1-K164A/H165A 60 days prior to challenge with 104 PFU BA.5 (isolate hCoV-19/USA/COR-22-063113/2022) (n = 8) on day 0. b Changes in weight were followed in Nsp1-K164A/H165A vaccinated and unvaccinated (n = 8 each) challenged hamsters 0–7 DPC, with **p = 0.0030 and ****p < 0.0001. c from 1 to 5 DPC, infectious virus from nasal wash samples was quantified by focus-forming assays for vaccinated and unvaccinated hamsters (n = 4) with **p = 0.0066 and ****p < 0.0001. d–f Infectious virus titers of nasal turbinates (d), bronchoalveolar lavage fluid (BALF, e), and lung homogenates (f) at 4 (n = 4) and 7 (n = 4) DPC were determined by focus-forming assays. g Viral sgRNA levels in lung and nasal turbinate samples from 4 DPC (n = 4) were measured by qRT-PCR. Sum clinical scores (h) and percentage of consolidation (i) were also compared for lungs collected at 4 and 7 DPC. P-values are indicated in the graph where appropriate (p < 0.05). Heat-map presentation of individual pathologies in lungs collected at 4 DPC (j) and 7 DPC (k). Graphs for b and g indicate mean values from a single experiment with standard deviations shown as error bars. Dot plots represent samples collected from individual animals in a single experiment, horizontal bars indicate mean values with standard deviations shown as error bars. Statistical differences were calculated using ordinary two-way analysis of variance (ANOVA) in GraphPad Prism 9.4.0 with Tukey’s multiple comparisons tests. | PMC10250859 | 41467_2023_39090_Fig9_HTML.jpg |
0.416727 | 9837959b95334252aab40cc254013cf4 | Treatment discontinuation indications. | PMC10251341 | mco-19-01-02648-g00.jpg |
0.46075 | bde3e446ef6946a282fe2c6033dd3451 | Overall survival. | PMC10251341 | mco-19-01-02648-g01.jpg |
0.424655 | 7f0e57c49aeb4f9586c79811ac898e85 | Control constructs and analysis scheme. (A) Standard ChIP-seq procedure performed here. Red stars represent the protein of interest and blue stars represent other proteins. Red rectangles represent unique barcode sequences and orange rectangles indicate universal indexes. (B) Schematic representation of DNA elements comprising the different control constructs, not showing the plasmid vectors. The ADE2 and TRP1 sequences target integration of the constructs as shown upstream of the promoter regions of these loci; P and T represent promoter and terminator sequences and LexA-OP2/4 represent two or four LexA binding sequences. (C) Schematic representation of ratio normalization (RN) to remove background signal. | PMC10252487 | ijms-24-09271-g001.jpg |
0.480289 | 039c93f06578484b9f22a811679a6f4c | Enrichment of non-specific ChIP signals in control IPs. Strains MPy105 (MOP), MPy35 (FLOP), and MPy39 (HOP) were grown to log-phase, harvested, and analyzed using ChIP-seq. (A) Plots of ChIP signals across chromosomes XV and IV, which harbor the MOP, FLOP, and HOP loci, respectively indicated by red dots; panels to the right show zoomed-in view. (B) Distribution boxplots of ChIP signals (500 bp bins) across the whole genome and for specific sets of loci; results of Mann–Whitney tests of difference in distributions indicated by asterisks ** p < 0.01. Outliers are indicated with + and the number of positive outliers is indicated for each in red. (C) Two-dimensional scatter plots of ChIP signals for all bins for Untag versus MOP, FLOP, or HOP for each set of IPs. | PMC10252487 | ijms-24-09271-g002.jpg |
0.448542 | 1ea742b6406c4431bd657168b48629d0 | Ratio normalization using control reduces non-specific enrichment. Strains SSy161 (WT), MPy105 (MOP), MPy166 (FKH1-9xMYC), MPy108 (FKH1-9xMYC(MOP)), MPy35 (FLOP), OAy1100 (FKH1-3xFLAG), and MPy55 (FKH1-3xFLAG(FLOP)) were grown to log-phase, harvested, and analyzed using ChIP-seq. (A) Distribution boxplots of ChIP signals (500 bp bins) across the whole genome and for specific loci; RN is the ratio normalized signal. (B) Heatmaps of averaged ChIP signal across 5 kb regions centered on the indicated features. | PMC10252487 | ijms-24-09271-g003.jpg |
0.420166 | 0761fb4a1cd9465186f1b2a011d62341 | Improved detection of Fkh1 binding loci. Strains MPy105 (MOP), MPy108 (FKH1-9xMYC(MOP)), MPy35 (FLOP), and MPy55 (FKH1-3xFLAG(FLOP)) were synchronized in G1 phase, harvested, and analyzed using ChIP-seq. (A) Plots of ChIP signal across chromosomes III-L and IX with potential Fkh1 binding sites indicated as colored circles on one track and called peaks indicated on the lower track. (B) Stack graphs of peak calls overlapping with potential origins according to their categorization in oriDB or with other loci presumed not to contain replication origins. (C) Venn diagrams showing overlap of called peaks with origin sets and the MYC/MOP versus FLAG/FLOP sets. (D) Heatmaps of averaged ChIP signal across 5 kb regions centered on the indicated features. | PMC10252487 | ijms-24-09271-g004.jpg |
0.426389 | 24373f8983704202b7724b2401787b9c | Improved accuracy in detection of ORC and MCM binding loci. Strains MPy39 (HOP), MPy199 (ORC1-3xHA(HOP)), and MPy102 (MCM4-3xHA(HOP)) were synchronized in G1 phase, harvested, and analyzed using ChIP-seq. (A) Plots of ChIP signal across chromosomes III-L and IX with potential origins indicated as gray circles on one track and called peaks indicated on the lower track in red and CEN indicated by arrowhead. (B) Stack graphs of peak calls overlapping with potential origins according to their categorization in oriDB or with other loci presumed not to contain replication origins. (C) Venn diagrams showing origin overlap of peaks called using RN and uncontrolled datasets against confirmed origins. (D) Heatmaps of averaged ChIP signal across 5 kb regions centered on the indicated features. | PMC10252487 | ijms-24-09271-g005.jpg |
0.436166 | e6769c091a164c58a0f6f7c052065046 | Sir2 detection within hyperChIPable rDNA locus and genome-wide. (A) Plots of ChIP signals overlaid across the rDNA region for G1-synchronized strains MPy108 (FKH1-9xMYC(MOP)), MPy199 (ORC1-HA(HOP)), MPy102 (MCM4-3xHA(HOP)), and YHy29 (SIR2-3xFLAG(FLOP)) before and after RN. (B) Plot of ChIP signals for all bins according to distance from the nearest telomere; bins mapping to the indicated loci are highlighted. (C) Plots of ChIP signals across chromosome III, with expanded view of HML and HMR silencer regions and silencer elements (E and I) indicated; correlation of replicates shown in Figure S6. Because the reference genome is MATα, while the analysis strain is MATa, we deleted ⍺ gene sequences at the MAT locus in the reference sequence to properly map all ⍺ gene sequence reads to HMLα. | PMC10252487 | ijms-24-09271-g006.jpg |
0.445978 | 2c5d5bca0f5247d7956408381e60334f | DNA-binding mutant control may be ideal. Strains MPy166 (FKH1-9xMYC), MPy169 (fkh1-dbm-9xMYC), MPy172 (fkh1-dbm-3xFLAG), and OAy1100 (FKH1-3xFLAG) were grown to log-phase, harvested, and analyzed using ChIP-seq. (A) Heatmaps of averaged ChIP signal across 5 kb regions centered on the indicated features. (B) Venn diagrams showing overlap of called peaks with origin and CLB2 cluster sets comparing dbm-controlled against MOP- and FLOP-controlled sets analyzed in Figure 3. | PMC10252487 | ijms-24-09271-g007.jpg |
0.45552 | 64ea5f420e7c478396ee10b58e85e699 | Flow diagram for screening and inclusion of relevant articles. | PMC10252667 | ijerph-20-05984-g001.jpg |
0.453542 | 3b9ade92147f4d568fdb1668c84aa59f | Study workflow. | PMC10253100 | ijerph-20-05933-g001.jpg |
0.391188 | 985a49f94a4c4649868147e2e2ed2843 | Changes of CAC according to categorical BMI. | PMC10253414 | jcm-12-03770-g001.jpg |
0.523293 | b9479ff20d264c5f9830ba4b817f2f4d | CAC progression related to normal SBPmaintain in categorical BMI. | PMC10253414 | jcm-12-03770-g002.jpg |
0.454606 | a2a49e8ced2c4bf58696ce4d5a744cbf | Number of segmented distant metastases per anatomical site in patients treated with immunotherapy vs. no immunotherapy. | PMC10253507 | jcm-12-03725-g001.jpg |
0.470087 | b4e5b1ea9e8b4a288c64d9b295a06d90 | ROC curve capturing the performance of the generated model including biomarkers predictive of clinical benefit in patients treated with immunotherapy. AUC: Area under the curve (95% confidence interval). | PMC10253507 | jcm-12-03725-g002.jpg |
0.517411 | 4390fc2ec50b450d9331a97445bbb736 | ROC curve capturing the performance of the generated model including biomarkers predictive of clinical benefit in patients treated with no immunotherapy. AUC: Area under the curve (95% confidence interval). | PMC10253507 | jcm-12-03725-g003.jpg |
0.43642 | 6c3fdb280e3445cfba15137e565d9a12 | Search Protocol: Embase Classic + Embase via Ovid. * is a truncation symbol. | PMC10253859 | jcm-12-03738-g001.jpg |
0.431211 | 0812afe6b5804fecafffe8f3067c2887 | PRISMA flow diagram showing the outcome of database searches and the process of selection of included studies. | PMC10253859 | jcm-12-03738-g002.jpg |
0.382674 | 95e504fa0e024a45a3a47c7a9c59866c | Prevalence (%) of severe neonatal jaundice (SNJ) among hospitalized neonates according to World Health Organization (WHO) regions. CI: Confidence interval; SNJ: Severe Neonatal Jaundice; References: [6,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97]. | PMC10253859 | jcm-12-03738-g003.jpg |
0.499865 | 4d59242f7ad042d1a76b351cc54c3075 | Prevalence (%) of severe neonatal jaundice (SNJ) with exchange transfusions (EBT) among hospitalized neonates according to WHO regions. CI: Confidence interval; EBT: Exchange Blood Transfusion; References: [15,17,18,19,21,22,23,24,25,26,27,29,30,31,32,33,36,37,38,39,46,47,49,51,53,55,57,58,59,60,62,66,67,68,69,75,77,78,79,80,82,83,84,85,86,88,91,92,96,97]. | PMC10253859 | jcm-12-03738-g004.jpg |
0.441566 | 3d2113035c61423b997376bf191025e0 | Prevalence (%) of severe neonatal jaundice (SNJ) with acute bilirubin encephalopa-thy/kernicterus (ABE) among hospitalized neonates according to WHO regions. ABE: Acute Bilirubin Encephalopathy; CI: Confidence interval. References: [6,16,17,23,24,30,31,33,36,37,38,39,47,48,50,51,57,60,67,69,70,72,75,77,78,79,82,85,86,87,91]. | PMC10253859 | jcm-12-03738-g005.jpg |
0.455272 | 33f3bfce58d34fc3affdd6f5b4fc6972 | Prevalence (%) of abnormal Brainstem Auditory Evoked Response (aBAER) among hospitalized neonates. aBAER: abnormal Brainstem Auditory Evoked Response (aBAER); CI: Confidence interval; References: [6,33,34,39,45,64,87,89,91]. | PMC10253859 | jcm-12-03738-g006.jpg |
0.43358 | 39a4814865ed421393ba3361a29faa0a | Prevalence (%) of abnormal Brainstem Auditory Evoked Response (aBAER) among neonates admitted with jaundice. aBAER: abnormal Brainstem Auditory Evoked Response (aBAER); CI: Confidence interval; References: [6,33,34,39,45,64,87,89,91]. | PMC10253859 | jcm-12-03738-g007.jpg |
0.463002 | 98778385157c4d5d9c2c33626080b6bb | Funnel plot of studies included in the meta-analysis. The unshaded triangle represents the region within which 95% of studies would be expected to lie to lie if the studies are all estimating the same underlying effect. References: [6,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97]. | PMC10253859 | jcm-12-03738-g008.jpg |
0.478471 | 422f390a3f1b4bb8a49f9bd413be9370 | Screening and diagnostic process of GDM in Germany. Initially a 50 g oral glucose challenge test (oGCT) is offered to every pregnant woman between 24 and 28 gestational weeks (GW). Depending on the blood glucose level, further testing for GDM is required. In women with risk factors for GDM according to the Deutsche Diabetes Gesellschaft (DDG) or signs of GDM, a 75 g oral glucose tolerance test (oGTT) as a first-line diagnostic test is possible. | PMC10254013 | jcm-12-03709-g001.jpg |
0.429568 | ec8fa1bb50754bcf89a03662050f7a81 | Obstetric data from 3123 pregnant women were collected and analyzed anonymously. A total of 1664 cases were eligible for analysis. | PMC10254013 | jcm-12-03709-g002.jpg |
0.463493 | 45691ea9f2f3435381969499450db57d | Attributes of each subtype: Isolated fasting hyperglycemia (GDM-IFH), isolated postprandial hyperglycemia (GDM-IPH), combined hyperglycemia (GDM-CH). Thresholds for pathological glucose levels were ≥92 mg/dL (5.1 mmol/L) fasting, ≥180 mg/dL (10 mmol/L) one hour after glucose application and ≥153 mg/dL (8.5 mmol/L) two hours after [2]. | PMC10254013 | jcm-12-03709-g003.jpg |
0.437042 | 458dcec4f2df4968a33dacf6253493fa | An overview of significant differences between women of the three subtypes regarding parity, BMI and weight gain, insulin therapy, mode of delivery and fetal growth. | PMC10254013 | jcm-12-03709-g004.jpg |
0.443665 | e3ac1271f22e49f2bea8049b63bf642e | The process flow for synthesizing Ag/SU-8 nanocomposites. | PMC10254310 | nanomaterials-13-01784-g001.jpg |
0.392735 | b2b4705d3a264eabad29a8cbe422f43f | (a–c) Optical images of the Ag/SU-8 nanocomposites after one, two, and three photoreductions. The concentration of AgNO3 was 0.5 mM. (d,e) Cross-sectional TEM images of the Ag/SU-8 nanocomposites photoreduced from 0.5 and 50 mM AgNO3, respectively. (f) EDS elemental analysis of Ag/SU-8 nanocomposites photoreduced from 50 mM AgNO3. The scale bars in the insets at the bottom of (d,e) measure 20 nm. | PMC10254310 | nanomaterials-13-01784-g002.jpg |
0.417473 | 3c7d4d57febf4dd4a44ff1c16e5adaba | Extinction spectra of the Ag/SU-8 nanocomposites under various experimental conditions. (a) PI was added to SU-8 at concentrations ranging from 0 to 10 wt% with a fixed AgNO3 concentration of 0.5 mM. (b) PI concentration was fixed at 5 wt% with AgNO3 concentrations ranging from 0.5 to 50 mM. (c) Photoreduction was performed from one to six cycles with fixed concentrations of PI and AgNO3 at 5 wt% and 0.5 mM, respectively. (d) Cross-sectional TEM image of the Ag/SU-8 nanocomposites photoreduced from 50 mM AgNO3 on SU-8 nanopillars. The bottom inset shows EDS elemental analysis of the silver element. | PMC10254310 | nanomaterials-13-01784-g003.jpg |
0.399306 | 115099e1431e4704b53179489e9080f5 | (a) The schematic of the composite surface made up of gold nanodisks and Ag/SU-8 nanocomposites. (b) The top-view SEM image of the composite surface. (c) The measured extinction spectra of the composite surface with the reduction in AgNPs from 0 to 4 cycles. (d) The CIE 1931 color space calculated from the measured spectra of the various Ag/SU-8 nanocomposites and composite surfaces. | PMC10254310 | nanomaterials-13-01784-g004.jpg |
0.421242 | 6e35f61ef60a43c192b1ac43ae3b5aa0 | Antibacterial inhibition zones of various Ag/SU-8 nanocomposites against antibiotic-sensitive Escherichia coli, antibiotic-resistant Escherichia coli, and antibiotic-sensitive Staphylococcus aureus. | PMC10254310 | nanomaterials-13-01784-g005.jpg |
0.420329 | ffa03ed0b5df49ee8cbc351ee4513d5d | A many-body basis state |Φm〉 of Frenkel Hamiltonian. | PMC10254768 | molecules-28-04502-g001.jpg |
0.424083 | ea27289368df4582b6bcada32838104a | A many-body basis state |ΦFm,j,m′〉, in which a core electron occupied a vacant HOMO orbital after absorption of an X-ray photon. | PMC10254768 | molecules-28-04502-g002.jpg |
0.427544 | 61c69afc5bf946e4bf5bcf12deb34d2e | A many-body basis state |ΦFm,j,m′,m″〉, in which a core electron occupied a vacant LUMO orbital after absorption of an X-ray photon. | PMC10254768 | molecules-28-04502-g003.jpg |
0.484041 | 7975e4a4e05d4968983a3c5f3785b62f | Populations ρm,m for all molecules in the chain and the real part of the coherences 2Re(ρm,m+1) for all nearest neighbours depending on time. | PMC10254768 | molecules-28-04502-g004.jpg |
0.417854 | 87015f5e42634ba6a69b51bce3b2c82f | (a) Normalized cross section at the time delay of 500 as as a function of energy. X-ray probe pulse is assumed to be resonant with the transition energy of an electron from the 1 s orbital of Carbon into outermost orbitals below Fermi level. (b) Normalized time evolution of the change in the cross section after the delay time of 500 as, σ˜(tp)=σ(tp)−σ(0.5fs), as a function of energy and time. (c) Time evolution evolution of the normalized delocalization degree hinter(t). | PMC10254768 | molecules-28-04502-g005.jpg |
0.515454 | d36e6f2797f0465ea8ea9df751ca9d63 | Diet–Microbiome–Health Interactions. Direct effect arrows are black, indirect effect arrow is red. Diet has direct effects on both health and the gut microbiome. The gut microbiome also has a direct effect on health as a result of changes in the community composition and/or function due to diet. However, the gut microbiome can also modulate (indirect effect) the effects of diet on health independent of diet-related changes in composition or function. | PMC10255073 | nutrients-15-02451-g001.jpg |
0.421634 | 500fc545724044ce9a66ece60950d5d9 | The characterization of the pristine and modified LVO. (a) XRD pattern; (b) UV-vis diffuse reflectance spectrum (the inset shows the image of pristine LVO and P-LVO); (c) nitrogen adsorption/desorption isotherms; (d) TGA analysis; (e) FTIR spectrum; and (f) Raman spectrum of the pristine LVO and P-LVO. | PMC10255298 | polymers-15-02502-g001.jpg |
0.41186 | 25b2955df7014410a7749fc4686bc06b | The morphological investigation of the P-LVO. The SEM images of (a) LVO and (b) P-LVO; the EDS spectra of (c) LVO and (d) P-LVO; (e) representative SEM image with the associated EDS mapping of the P-LVO (yellow square); (f–h) EDS mapping of (f) V, (g) O, and (h) S elements in the P-LVO powder; and the high-resolution TEM images of (i) LVO and (j) P-LVO. | PMC10255298 | polymers-15-02502-g002.jpg |
0.425753 | b7595c66382c43f9bc7a8a957850240b | Chemical valence state of LVO and P-LVO. (a) XPS survey of the LVO and P-LVO; (b) V 2p XPS spectrum of P-LVO; S 2p XPS spectrum of (c) LVO and (d) P-LVO; and O 1s XPS spectrum of (e) LVO and (f) P-LVO. | PMC10255298 | polymers-15-02502-g003.jpg |
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