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Objective To investigate the diversity and composition of gut microbiota in patient with cholestatic liver disease, and explore their correlation with clinical parameters. Methods Fresh stool samples from 16 patients with cholestatic liver disease and 19 healthy controls were collected, and 16S rRNA sequencing was used to analyze the diversity of gut microbiota and composition characteristics. Pearson analysis was employed to analyze the correlation between the different bacteria and clinical parameters. Results There were no statistical differences in the baseline data, such as sex, age and body mass index (BMI) in study subjects (P>0.05), but significant differences were observed in serum indexes among them (P < 0.01). The results of α diversity showed that Chao1 and Shannon indexes were lower in the study group, but there was no statistical difference (P>0.05). β diversity results indicated that the species diversity had significant difference between 2 group (P < 0.01). Further analysis of microbiota composition showed largely relative abundance of Bacteroides, Lachnoclostridium, Veillonella, Roseburia and Escherichia shigella (P < 0.05), while the abundance of Blautia were dramatically decreased (P < 0.05). Pearson analysis displayed that Lachnoclostridium was strongly correlated with serum level of alkaline phosphatase (ALP) (P < 0.01) and gamma-glutamyl transferase (GGT) (P < 0.05), and Veillonella was also strongly correlated with GGT (P < 0.05). Conclusion Compared with healthy controls, the patients with cholestatic liver disease have obvious characteristic changes in the gut microbiota. The relatively high abundance of Veillonella is closely assocatied with cholestatic liver disease.

This article introduces a novel preference learning framework that simultaneously considers both the intended and the perceived labels while addressing the mismatches between them. Based on analyzing the discrepancies and agreements between the intended and the perceived labels in different modalities of audio-only, visual-only, and audio-visual, as well as the consistency among the perceptual ratings of all raters, we propose three sets of pair-wise ranking rules to generate multi-scale relevant scores for preference learning, scaling from sketchy manner to detailed manner. Three ranking models with support vector machine (SVM), deep neural networks (DNN), and gradient boosting decision trees (GBDT) are developed. Our results demonstrate that all three preference learning models significantly outperform the conventional classifiers baselines, and the LambdaMART model with gradient boosting decision trees achieves the best performance. The improvement from the preference learning models confirm the benefits of complementary information provided by different types of labels. We also observe additional improvement from the detailed ‘complex ranking rules’, particular with the best LambdaMART model, which suggests that we should treat intended and perceived labels in single-model & multi-modal differently. We further discuss the complementary of different ranking models, and obtain the best overall accuracy of 85.06% on CREMA-D dataset when combining the two best ranking models–LambdaMART and RankNet–together, which is significantly better than the 76.19% accuracy attained by the baseline models. Finally, we perform the cross-corpus emotion recognition experiments by training emotion rankers on CREMA-D dataset and tested the ranking-based emotion classifier on the SAVEE dataset that do not have perceived labels annotated. [ABSTRACT FROM AUTHOR]

Transmission electron microscopy studies in both the scanning and parallel illumination mode on samples of two generic types of self-assembled semiconductor quantum dots are reported. III-V and II-VI quantum dots as grown in the Stranski-Krastanow mode are typically alloyed and compressively strained to a few %, possess a more or less random distribution of the cations and/or anions over their respective sublattices, and have a spatially non-uniform chemical composition distribution. Sn quantum dots in Si as grown by temperature and growth rate modulated molecular beam epitaxy by means of two mechanisms possess the diamond structure and are compressively strained to the order of magnitude 10%. These lattice mismatch strains are believed to trigger atomic rearrangements inside quantum dots of both generic types when they are stored at room temperature over time periods of a few years. The atomic rearrangements seem to result in long-range atomic order, phase separation, or phase transformations. While the results suggest that some semiconductor quantum dots may be structurally unstable and that devices based on them may fail over time, triggering and controlling structural transformations in self-assembled semiconductor quantum dots may also offer an opportunity of creating atomic arrangements that nature does not otherwise provide.

The task of this article is to harness the wisdom of a crowd without calibration. We assume each expert to form predictions by linearly combining various information cues inspired by the lens model, and use Gaussian process to account for sampling and judgmental errors in quantile judgments. Without knowing the experts' observed information cues, we develop a three-step estimation algorithm to factor quantile judgments into "variable profiles" (latent cues underlying each variable of interest) and "expert profiles" (each expert's weights over these cues). We can inquire about expert similarity using their weights of the latent cues, which preserve the same clustering results as the actual weights of the observed cues up to a full-rank linear transform. We can then depict the diversity and dependency among experts explicitly and retain a subcrowd by picking delegates from each subgroup of experts based on the estimated weights. Simulation and case studies demonstrate that a subcrowd selected this way can represent the entire expert panel well. [ABSTRACT FROM AUTHOR]

Background: With the development of educational philosophy, physical exercise is considered to be an important factor in the development of individual cognitive abilities in adolescents. However, the effects of physical exercise on non-cognitive abilities in adolescents remain inadequate. Objective: This study examined the effect of physical exercise on non-cognitive ability and further examined the differences in this effect in different groups. Methods: Survey data on non-cognitive ability, physical exercise and covariates were collected in the China Education Panel Survey (2014–2015) from a nationally representative sample of adolescents (n = 7904) in the eighth (follow-up) grade. Results: The results show that, after controlling for the influence of other factors, physical exercise has a promoting effect on six non-cognitive abilities—social behavior (p < 0.001), communication ability (p < 0.01), perseverance (p < 0.05), school adaptation (p < 0.001), educational expectation (p < 0.01) and creative thinking (p < 0.01)—and there is no significant effect on emotional control (p > 0.05). Furthermore, the development of non-cognitive ability in physical exercise shows certain group differences. Conclusions: There are gender differences in the performance of non-cognitive ability. Girls perform better than boys in non-cognitive ability. Physical exercise is an important means to develop non-cognitive ability, which indicates that non-cognitive ability has plasticity in adolescence. Future intervention may improve the non-cognitive ability of Chinese adolescents by increasing physical exercise. [ABSTRACT FROM AUTHOR]

Gait stability in exercise is an inevitable and vexing problem in mechanics, artificial intelligence, sports, and rehabilitation medicine research. With the rapid development and popularization of science and technology, it becomes a reality for researchers to obtain large-scale human motion data sets in real time with higher efficiency. However, at present, the analysis of gait stability of moving joints is still based on image recognition technology, which is ten times less accurate and inefficient. In this paper, Vicon 3D motion capture system, dynamometer, and surface electromyography system were used to obtain the parameters of the lower limbs of the subjects. Using Anywhere modeling and simulation system, simulation experiments were carried out, and the reaction force data of lower limb joints under two environments were obtained. The gait characteristics of human gait were analyzed from the angle of internal and external adjustment mechanism. Combining one-way ANOVA and incremental occupancy rate, the adjustment process of gait stability is described comprehensively. The findings of this study can provide a theoretical basis for the research of lower limb con-assistive devices and can guide the design and development of bipedal anthropomorphic robots. [ABSTRACT FROM AUTHOR]

Background: Well-balanced interactions between gut microbiota and the immune system are essential to prevent chronic intestinal inflammation, as observed in inflammatory bowel diseases (IBD). Toll-like receptor 4 (TLR4) functions as a sensor mediating the crosstalk between the intestinal commensal microbiome and host immunity, but the influence of TLR4 on the shaping of intestinal microbiota and immune responses during colon inflammation remains poorly characterized. We investigated whether the different susceptibilities to colitis between wild-type (WT) and TLR4−/− mice were gut microbiota-dependent and aimed to identify the potential immunity modulation mechanism. Methods: We performed antibiotic depletion of the microbiota, cohousing experiments, and faecal microbiota transplantation (FMT) in WT and TLR4−/− mice to assess the influence of TLR4 on intestinal microbial ecology. 16S rRNA sequencing was performed to dissect microbial discrepancies, and dysbiosis-associated immune perturbation was investigated by flow cytometry. Akkermansia muciniphila (A. muciniphila)-mediated immune modulation was confirmed through the T-cell transfer colitis model and bone marrow chimaera construction. Results: TLR4−/− mice experienced enhanced susceptibility to DSS-induced colitis. 16S rRNA sequencing showed notable discrepancy in the gut microbiota between WT and TLR4−/− mice. In particular, A. muciniphila contributed most to distinguishing the two groups. The T-cell transfer colitis model and bone marrow transplantation (BMT) consistently demonstrated that A. muciniphila ameliorated colitis by upregulating RORγt+ Treg cell-mediated immune responses. Mucosal biopsies from human manifested parallel outcomes with colon tissue from WT mice, as evidenced by the positive correlation between TLR4 expression and intestinal A. muciniphila colonization during homeostasis. Conclusions: Our results demonstrate a novel protective role of TLR4 against intestinal inflammation, wherein it can modulate A. muciniphila-associated immune responses. These findings provide a new perspective on host-commensal symbiosis, which may be beneficial for developing potential therapeutic strategies. CehHU1DpMuC43wfy6GXbFM Video abstract. [ABSTRACT FROM AUTHOR]

Salt stress is an important environmental factor limiting plant growth and crop production. Plant adaptation to salt stress can be improved by chemical pretreatment. This study aims to identify whether hydrogen peroxide (H2O2) pretreatment of seedlings affects the stress tolerance of Arabidopsis thaliana seedlings. The results show that pretreatment with H2O2 at appropriate concentrations enhances the salt tolerance ability of Arabidopsis seedlings, as revealed by lower Na+ levels, greater K+ levels, and improved K+/Na+ ratios in leaves. Furthermore, H2O2 pretreatment improves the membrane properties by reducing the relative membrane permeability (RMP) and malonaldehyde (MDA) content in addition to improving the activities of antioxidant enzymes, including superoxide dismutase, and glutathione peroxidase. Our transcription data show that exogenous H2O2 pretreatment leads to the induced expression of cell cycle, redox regulation, and cell wall organization-related genes in Arabidopsis, which may accelerate cell proliferation, enhance tolerance to osmotic stress, maintain the redox balance, and remodel the cell walls of plants in subsequent high-salt environments. [ABSTRACT FROM AUTHOR]

Background: The early-stage lung adenocarcinoma (LUAD) incidence has increased with heightened public awareness and lung cancer screening implementation. Lipid metabolism abnormalities are associated with lung cancer initiation and progression. However, the comprehensive features and clinical significance of the immunometabolism landscape and lipid metabolism-related genes (LMRGs) in cancer recurrence for early-stage LUAD remain obscure. Methods: LMRGs were extracted from Gene Set Enrichment Analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Samples from The Cancer Genome Atlas (TCGA) were used as training cohort, and samples from four Gene Expression Omnibus (GEO) datasets were used as validation cohorts. The LUAD recurrence-associated LMRG molecular pattern and signature was constructed through unsupervised consensus clustering, time-dependent receiver operating characteristic (ROC), and least absolute shrinkage and selection operator (LASSO) analyses. Kaplan-Meier, ROC, and multivariate Cox regression analyses and prognostic meta-analysis were used to test the suitability and stability of the signature. We used Gene Ontology (GO), KEGG pathway, immune cell infiltration, chemotherapy response analyses, gene set variation analysis (GSVA), and GSEA to explore molecular mechanisms and immune landscapes related to the signature and the potential of the signature to predict immunotherapy or chemotherapy response. Results: First, two LMRG molecular patterns were established, which showed diverse prognoses and immune infiltration statuses. Then, a 12-gene signature was identified, and a risk model was built. The signature remained an independent prognostic parameter in multivariate Cox regression and prognostic meta-analysis. In addition, this signature stratified patients into high- and low-risk groups with significantly different recurrence rates and was well validated in different clinical subgroups and several independent validation cohorts. The results of GO and KEGG analyses and GSEA showed that there were differences in multiple lipid metabolism, immune response, and drug metabolism pathways between the high- and low-risk groups. Further analyses revealed that the signature-based risk model was related to distinct immune cell proportions, immune checkpoint parameters, and immunotherapy and chemotherapy response, consistent with the GO, KEGG, and GSEA results. Conclusions: This is the first lipid metabolism-based signature for predicting recurrence, and it could provide vital guidance to achieve optimized antitumor for immunotherapy or chemotherapy for early-stage LUAD. [ABSTRACT FROM AUTHOR]

Background: Early identification of nasopharyngeal carcinoma (NPC) patients with high risk of failure to induction chemotherapy (IC) would facilitate prompt individualized treatment decisions and thus reduce toxicity and improve overall survival rate. This study aims to investigate the value of amide proton transfer (APT) imaging in predicting short-term response of NPC to IC and its potential correlation with well-established prognosis-related clinical characteristics. Methods and Materials: A total of 80 pathologically confirmed NPC patients receiving pre-treatment APT imaging at 3T were retrospectively enrolled. Using asymmetry analysis, APT maps were calculated with mean (APTmean), 90th percentile (APT90) of APT signals in manually segmented NPC measured. APT values were compared among groups with different histopathological subtypes, clinical stages (namely, T, M, N, and overall stages), EBV-related indices (EBV-DNA), or responses to induction chemotherapy, using Mann–Whitney U test or Kruskal–Wallis H test. Results: NPC showed significantly higher APTmean than normal nasopharyngeal tissues (1.81 ± 0.62% vs. 1.32 ± 0.56%, P < 0.001). APT signals showed no significant difference between undifferentiated and differentiated NPC subtypes groups, different EBV-DNA groups, or among T, N, M stages and overall clinical stages of II, III, IVA and IVB (all P > 0.05). Similarly, baseline APT-related parameters did not differ significantly among different treatment response groups after IC, no matter if evaluated with RECIST criteria or sum volumetric regression ratio (SVRR) (all P > 0.05). Conclusion: NPC showed significantly stronger APT effect than normal nasopharyngeal tissue, facilitating NPC lesion detection and early identification. However, stationary baseline APT values exhibited no significant correlation with histologic subtypes, clinical stages and EBV-related indices, and showed limited value to predict short-term treatment response to IC. [ABSTRACT FROM AUTHOR]

Cancer‐associated fibroblasts (CAF) are a heterogeneous cell population within the tumor microenvironment,and play an important role in tumor development. By regulating the heterogeneity of CAF, transforming growth factor β (TGFβ) influences tumor development. Here, we explored oncogenes regulated by TGFβ1 that are also involved in signaling pathways and interactions within the tumor microenvironment. We analyzed sequencing data of The Cancer Genome Atlas (TCGA) and our own previously established RNA microarray data (GSE53625), as well as esophageal squamous cell carcinoma (ESCC) cell lines with or without TGFβ1 stimulation. We then focused on laminin subunit gamma 1 (LAMC1), which was overexpressed in ESCC cells, affecting patient prognosis, which could be upregulated by TGFβ1 through the synergistic activation of SMAD family member 4 (SMAD4) and SP1. LAMC1 directly promoted the proliferation and migration of tumor cells, mainly via Akt–NFκB–MMP9/14 signaling. Additionally, LAMC1 promoted CXCL1 secretion, which stimulated the formation of inflammatory CAF (iCAF) through CXCR2–pSTAT3. Inflammatory CAF promoted tumor progression. In summary, we identified the dual mechanism by which the upregulation of LAMC1 by TGFβ in tumor cells not only promotes ESCC proliferation and migration, but also indirectly induces carcinogenesis by stimulating CXCL1 secretion to promote the formation of iCAF. This finding suggests that LAMC1 could be a potential therapeutic target and prognostic marker for ESCC. [ABSTRACT FROM AUTHOR]

Dysregulated expression of S100A7 is found in several cancers and plays an important role in tumor progression; however, its carcinogenic role in esophageal squamous carcinoma (ESCC) is still poorly understood. Here, we identified that the levels of S100A7 were remarkably upregulated in 341 tumor tissues (P <.001) and 274 serum samples (P <.001) of ESCC patients compared with normal control. It was an independent prognostic factor (P =.026). Furthermore, a new diagnostic model for ESCC based on serum S100A7, SCC, and crfra21‐1 was established with area under curve (AUC) up to 0.863 (95% CI: 0.802‐0.925). Mechanically, we found upregulated S100A7 could promote cell migration and proliferation through intracellular binding to JAB1 and paracrine interaction with RAGE receptors and then activates the downstream signaling pathways. In addition, exocrine S100A7 could promote M2 macrophage infiltration and polarization by up‐regulating M2 macrophage associated proteins, and tumor angiogenesis by enhancing the activation of p‐ErK and p‐FAK pathways. Further animal experiments confirmed the role of S100A7 in promoting M2 macrophage infiltration and angiogenesis in ESCC. In conclusion, these findings highlighted the potential diagnostic and prognostic value of S100A7 in patients with ESCC. Meanwhile, our results reveal that S100A7 promotes tumor progression by activating oncogenic pathways and remodeling tumor microenvironment, which paving the way for the progress of S100A7 as a therapeutic target for cancer treatment. [ABSTRACT FROM AUTHOR]

Chronic gastritis caused by Helicobacter pylori (H. pylori) infection has been widely recognized as the most important risk factor for gastric cancer. Analysis of the interaction between the key participants in gastric mucosal immunity and H. pylori infection is expected to provide important insights for the treatment of chronic gastritis and the prevention of gastric cancer. Heparanase is an endoglycosidase that degrades heparan sulfate, resulting in remodeling of the extracellular matrix thereby facilitating the extravasation and migration of immune cells towards sites of inflammation. Heparanase also releases heparan sulfate-bound cytokines and chemokines that further promote directed motility and recruitment of immune cells. Heparanase is highly expressed in a variety of inflammatory conditions and diseases, but its role in chronic gastritis has not been sufficiently explored. In this study, we report that H. pylori infection promotes up-regulation of heparanase in gastritis, which in turn facilitates the colonization of H. pylori in the gastric mucosa, thereby aggravating gastritis. By sustaining continuous activation, polarization and recruitment of macrophages that supply pro-inflammatory and pro-tumorigenic cytokines (i.e., IL-1, IL-6, IL-1β, TNF-α, MIP-2, iNOS), heparanase participates in the generation of a vicious circle, driven by enhanced NFκB and p38-MAPK signaling, that supports the development and progression of gastric cancer. These results suggest that inhibition of heparanase may block this self-sustaining cycle, and thereby reduce the risk of gastritis and gastric cancer. [ABSTRACT FROM AUTHOR]

Background: Evidence of the association between dietary pattern and outcomes of breast cancer was limited in Asian women, including Chinese. Patients and Methods: A prospective cohort study was initiated among Chinese breast cancer patients to investigate lifestyle habits and outcomes of breast cancer. At each follow-up, validated food frequency questionnaires (FFQ) were used to assess patients' dietary intake. This study included 1226 patients with invasive early-stage breast cancer with detailed data at 18-month follow-up after cancer diagnosis. Factor analysis was used to derive dietary patterns, whereby two dietary patterns were identified. Cox proportional hazards models were used to investigate associations between dietary patterns and time to outcome, including breast cancer recurrence, overall mortality and breast cancer-specific mortality. Results: With a median follow-up time of 54.1 months, 165 patients had breast cancer recurrence and 98 deaths occurred. Two dietary patterns were identified: "Western dietary pattern" characterized by high intake of refined grains and cakes, red and processed meat and oil; "healthy dietary pattern" characterized by high consumption of vegetables and fruits. Participants in the highest tertile of "Western dietary pattern" did not have a higher risk of breast cancer recurrence (Ptrend = 0.89), overall mortality (Ptrend = 0.48) and breast cancer-specific mortality (Ptrend = 0.75). Similarly, a null association existed between "healthy dietary pattern" and outcomes of breast cancer. Conclusion: Neither dietary pattern was associated with risk of breast cancer recurrence, all-causes death or death from breast cancer. Prospective follow-up is still needed to further confirm the association between specific dietary pattern and outcomes of breast cancer. [ABSTRACT FROM AUTHOR]

Objectives: The tumor mutational burden (TMB) is closely related to immunotherapy outcome. However, the cost of TMB detection is extremely high, which limits its use in clinical practice. A new indicator of genomic instability, the average copy number variation (CNVA), calculates the changes of 0.5‐Mb chromosomal fragments and requires extremely low sequencing depth. Methods: In this study, 50 samples (23 of which were from patients who received immunotherapy) were subjected to low‐depth (10X) chromosome sequencing on the MGI platform. CNVA was calculated by the formula avg (abs (copy number‐2)). In addition, CNVA and TMB were compared with regard to their ability to predict immune infiltration in 509 patients from TCGA. Results: The high‐CNVA group had higher expression levels of PD‐L1, CD39 and CD19 and a higher degree of infiltration of CD8+ T cells and CD3 + T cells. Among the 23 patients treated with immunotherapy, the average CNVA value of the stable disease/partial response group was higher than that of the progressive disease group (P < 0.05). Whole‐genome sequencing data of 509 patients from TCGA and RT‐PCR results of 22 frozen specimens showed that CNVA is more effective than TMB in indicating infiltration of CD8+ T cells and expression of PD‐L1, and CNVA also showed a specific positive correlation with TMB (r = 0.2728, P < 0.0001). Conclusions: Copy number variation can be a good indicator of immune infiltration and immunotherapy efficacy, and with its low cost, it is expected to become a substitute for TMB. [ABSTRACT FROM AUTHOR]

Correlation between fecal calprotectin (FC) and endoscopic activity assessed by Ulcerative Colitis Endoscopic Index of Severity (UCEIS) in acute severe colitis (ASC) patients was explored to evaluate the predictive value of FC in clinical outcomes. Seventy-one ASC patients were retrospectively evaluated. FC level within 3 days of colonoscopy was measured with ELISA. Demographic and clinical data, laboratory parameters, and medical therapy were documented, and the endoscopic severity of disease was rated by UCEIS. The end points were the rate of failed corticosteroid therapy, colectomy, and mortality. There was significant correlation between UCEIS and FC level (r=0.729, P<0.001), which was superior to CRP, ESR, and hemoglobin. FC level between endoscopic mild activity (UCEIS, 3-4) and endoscopic moderate activity (UCEIS, 5-6), and endoscopic moderate activity (UCEIS, 5-6) and endoscopic severe activity (UCEIS, 7-8) were significantly different. FC levels were associated with different outcomes (failed corticosteroid therapy or surgery); when FC >1672 µg/g, sensitivity and specificity were 80.2 and 66.7%, respectively, in prediction for colectomy using receiver operating characteristics analysis. The results indicated that FC, as a non-invasive indicator, correlates positively with the UCEIS. Baseline FC level predicts clinical outcomes in ASC patients, which make a timely treatment strategy conversion possible after accurately forecasting the likelihood of failure of intravenous steroid therapy. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM), characterized by insulin resistance and unclear pathogenesis, is a serious menace to human health. Bile acids are the end products of cholesterol catabolism and play an important role in maintaining cholesterol homeostasis. Furthermore, increasing studies suggest that bile acids may regulate glucose tolerance, insulin sensitivity, and energy metabolism, suggesting that bile acids may represent a potential therapeutic target for T2DM. This study summarizes the metabolism of bile acids and, more importantly, changes in their concentrations, constitution, and receptors in diabetes. Furthermore, we provide an overview of the mechanisms underlying the role of bile acids in glucose and lipid metabolism, as well as the occurrence and development of T2DM. Bile acid-targeted therapy may represent a valid approach for T2DM treatment. [ABSTRACT FROM AUTHOR]