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Objective: To examine whether the effect of a 3-year lifestyle intervention on body weight and cardiometabolic risk factors differs by prediabetes metabolic phenotype.Research Design and Methods: This post hoc analysis of the multicenter, randomized trial, PREVention of diabetes through lifestyle interventions and population studies In Europe and around the World (PREVIEW), included 1,510 participants with prediabetes (BMI ≥25 kg ⋅ m-2; defined using oral glucose tolerance tests). Of these, 58% had isolated impaired fasting glucose (iIFG), 6% had isolated impaired glucose tolerance (iIGT), and 36% had IFG+IGT; 73% had normal hemoglobin A1c (HbA1c; <39 mmol ⋅ mol-1) and 25% had intermediate HbA1c (39-47 mmol ⋅ mol-1). Participants underwent an 8-week diet-induced rapid weight loss, followed by a 148-week lifestyle-based weight maintenance intervention. Linear mixed models adjusted for intervention arm and other confounders were used.Results: In the available-case and complete-case analyses, participants with IFG+IGT had greater sustained weight loss after lifestyle intervention (adjusted mean at 156 weeks -3.5% [95% CI, -4.7%, -2.3%]) than those with iIFG (mean -2.5% [-3.6%, -1.3%]) relative to baseline (P = 0.011). Participants with IFG+IGT and iIFG had similar cardiometabolic benefits from the lifestyle intervention. The differences in cardiometabolic benefits between those with iIGT and IFG+IGT were minor or inconsistent in different analyses. Participants with normal versus intermediate HbA1c had similar weight loss over 3 years and minor differences in cardiometabolic benefits during weight loss, whereas those with normal HbA1c had greater improvements in fasting glucose, 2-h glucose (adjusted between-group difference at 156 weeks -0.54 mmol ⋅ L-1 [95% CI -0.70, -0.39], P < 0.001), and triglycerides (difference -0.07 mmol ⋅ L-1 [-0.11, -0.03], P < 0.001) during the lifestyle intervention.Conclusions: Individuals with iIFG and IFG+IGT had similar improvements in cardiometabolic health from a lifestyle intervention. Those with normal HbA1c had greater improvements than those with intermediate HbA1c. [ABSTRACT FROM AUTHOR]

The illustration of the process of the PCBDA@AgNPs-MF for antibiofouling water disinfection. [Display omitted] Mature microfiltration (MF) membrane is a low-cost, effective, and promising technology to provide affordable purified water for people living in developing countries. However, the lack of disinfection ability and inherent membrane fouling problems have seriously restricted the large-scale application of conventional MF treatment system in producing safe drinking water. In this work, zwitterionic silver nanoparticles (AgNPs) with surface modification of poly(carboxybetaine acrylate- co -dopamine methacryamide) (PCBDA) copolymers were robustly immobilized onto commercial polyamide MF membrane via mussel-inspired chemistry for water disinfection. The designed microfiltration membrane, named as PCBDA@AgNPs-MF, exhibited integrated properties of high and stable payload of AgNPs, broad-spectrum anti-adhesive and antimicrobial activities, and easy removal of inactivated microbial cells from membrane surface. Ascribing to the synergetic effect of anti-adhesive and antimicrobial features brought by zwitterionic PCBDA@AgNPs, the biofilms growth on polyamide membrane surface was significantly inhibited, which showed potential access to achieve long-term biofouling resistance and maintain water flux for conventional MF membrane. As water disinfection device, these attributes enabled PCBDA@AgNPs-MF to effectively disinfect the model and natural bacteria-contaminated water. [ABSTRACT FROM AUTHOR]

Objective: To examine longitudinal and dose-dependent associations of dietary glycemic index (GI), glycemic load (GL), and fiber with body weight and glycemic status during 3-year weight loss maintenance (WLM) in adults at high risk of type 2 diabetes.Research Design and Methods: In this secondary analysis we used pooled data from the PREVention of diabetes through lifestyle Intervention and population studies in Europe and around the World (PREVIEW) randomized controlled trial, which was designed to test the effects of four diet and physical activity interventions. A total of 1,279 participants with overweight or obesity (age 25-70 years and BMI ≥25 kg ⋅ m-2) and prediabetes at baseline were included. We used multiadjusted linear mixed models with repeated measurements to assess longitudinal and dose-dependent associations by merging the participants into one group and dividing them into GI, GL, and fiber tertiles, respectively.Results: In the available-case analysis, each 10-unit increment in GI was associated with a greater regain of weight (0.46 kg ⋅ year-1; 95% CI 0.23, 0.68; P < 0.001) and increase in HbA1c. Each 20-unit increment in GL was associated with a greater regain of weight (0.49 kg ⋅ year-1; 0.24, 0.75; P < 0.001) and increase in HbA1c. The associations of GI and GL with HbA1c were independent of weight change. Compared with those in the lowest tertiles, participants in the highest GI and GL tertiles had significantly greater weight regain and increases in HbA1c. Fiber was inversely associated with increases in waist circumference, but the associations with weight regain and glycemic status did not remain robust in different analyses.Conclusions: Dietary GI and GL were positively associated with weight regain and deteriorating glycemic status. Stronger evidence on the role of fiber is needed. [ABSTRACT FROM AUTHOR]

Excess body weight (EBW) increases the risk of colorectal cancer (CRC) and is linked to lower colonoscopy compliance. Here, we extensively analyzed 981 metagenome samples from multiple cohorts to pinpoint the specific microbial signatures and their potential capability distinguishing EBW patients with CRC. The gut microbiome displayed considerable variations between EBW and lean CRC. We identify 44 and 37 distinct multi-kingdom microbial species differentiating CRC and controls in EBW and lean populations, respectively. Unique bacterial-fungal associations are also observed between EBW-CRC and lean-CRC. Our analysis revealed specific microbial functions in EBW-CRC, including D-Arginine and D-ornithine metabolism, and lipopolysaccharide biosynthesis. The best-performing classifier for EBW-CRC, comprising 12 bacterial and three fungal species, achieved an AUROC of 0.90, which was robustly validated across three independent cohorts (AUROC = 0.96, 0.94, and 0.80). Pathogenic microbial species, Anaerobutyricum hallii, Clostridioides difficile and Fusobacterium nucleatum, are EBW-CRC specific signatures. This work unearths the specific multi-kingdom microbial signatures for EBW-CRC and lean CRC, which may contribute to precision diagnosis and treatment of CRC. Metagenomic analysis reveals distinctive multi-kingdom species, functional signatures and bacteria-fungi interactions pattern between excess body weight CRC and lean CRC in gut microbiome, which contribute to precision medicine of CRC. [ABSTRACT FROM AUTHOR]

Purpose: To compare the glycaemic response of whole grain oat kernels and pearled oats cooked under normal pressure or higher pressure and examine whether replacing half of the rice in a given meal with either of the two oat grains could make a difference in acute glycaemic responses. Methods: In a randomised crossover trial, ten healthy subjects consumed two groups of test meals: (1) oat grain-only, including whole grain oats cooked under normal pressure (WONP) and higher pressure (WOHP) as well as their pearled oat counterparts, PONP and POHP; and (2) mixed meals of aforementioned oat grains and cooked rice (OG + R), including WONP + R, WOHP + R, PONP + R and POHP + R. A postprandial blood glucose test, texture profile analysis and in vitro carbohydrate digestion assay were carried out for each test meal. Results: Compared with the rice reference, oat grain-only meals induced lower glucose levels at all time points, lower peak values and smaller glucose excursions at 120 min (P < 0.05), but OG + Rs did not have the abovementioned effects. The oat grain-only meals had glycaemic indexes (GIs) ranging from 51 to 58, while those of OG + Rs ranged from 59 to 70. WONP + R had a 21% lower iAUC0–60 and a 40% lower iAUC60–120 value than those of rice (P < 0.05). Oat-rice mixed meals had lower iAUC0–60 values compared with that of the rice control (P < 0.05), except for POHP + R. Excellent consistency between the hydrolysis index and the GI was observed (r = 0.969, P < 0.001) in oat grain-only meals. Conclusions: All oat grain-only meals could be included in the glycaemic management diet, regardless of the oat grain type or cooking treatment. In oat-rice mixed meals, whole grain oats and normal pressure cooking ensured a favourable glycaemic effect. [ABSTRACT FROM AUTHOR]

Excess body weight (EBW) increases the risk of colorectal cancer (CRC) and is linked to lower colonoscopy compliance. Here, we extensively analyzed 981 metagenome samples from multiple cohorts to pinpoint the specific microbial signatures and their potential capability distinguishing EBW patients with CRC. The gut microbiome displayed considerable variations between EBW and lean CRC. We identify 44 and 37 distinct multi-kingdom microbial species differentiating CRC and controls in EBW and lean populations, respectively. Unique bacterial-fungal associations are also observed between EBW-CRC and lean-CRC. Our analysis revealed specific microbial functions in EBW-CRC, including D-Arginine and D-ornithine metabolism, and lipopolysaccharide biosynthesis. The best-performing classifier for EBW-CRC, comprising 12 bacterial and three fungal species, achieved an AUROC of 0.90, which was robustly validated across three independent cohorts (AUROC = 0.96, 0.94, and 0.80). Pathogenic microbial species, Anaerobutyricum hallii, Clostridioides difficile and Fusobacterium nucleatum, are EBW-CRC specific signatures. This work unearths the specific multi-kingdom microbial signatures for EBW-CRC and lean CRC, which may contribute to precision diagnosis and treatment of CRC. Metagenomic analysis reveals distinctive multi-kingdom species, functional signatures and bacteria-fungi interactions pattern between excess body weight CRC and lean CRC in gut microbiome, which contribute to precision medicine of CRC. [ABSTRACT FROM AUTHOR]

Potassium channels participate in many critical biological functions and play important roles in a variety of diseases. In recent years, many significant discoveries have been made which motivate us to review these achievements. The focus of our review is mainly on three aspects. Firstly, we try to summarize the latest developments in structure determinants and regulation mechanism of all types of potassium channels. Secondly, we review some diseases induced by or related to these channels. Thirdly, both qualitative and quantitative approaches are utilized to analyze structural features of modulators of potassium channels. Our analyses further prove that modulators possess some certain natural-product scaffolds. And pharmacokinetic parameters are important properties for organic molecules. Besides, with in silico methods, some features that can be used to differentiate modulators are derived. There is no doubt that all these studies on potassium channels as possible pharmaceutical targets will facilitate future translational research. All the strategies developed in this review could be extended to studies on other ion channels and proteins as well. [ABSTRACT FROM AUTHOR]

With the growth of aging population all over the world, a rising incidence of Alzheimer’s disease (AD) has been recently observed. In contrast to FDA-approved western drugs, herbal medicines, featured as abundant ingredients and multi-targeting, have been acknowledged with notable anti-AD effects although the mechanism of action (MOA) is unknown. Investigating the possible MOA for these herbs can not only refresh but also extend the current knowledge of AD pathogenesis. In this study, clinically tested anti-AD herbs, their ingredients as well as their corresponding target proteins were systematically reviewed together with applicable bioinformatics resources and methodologies. Based on above information and resources, we present a systematically target network analysis framework to explore the mechanism of anti-AD herb ingredients. Our results indicated that, in addition to the binding of those symptom-relieving targets as the FDA-approved drugs usually do, ingredients of anti-AD herbs also interact closely with a variety of successful therapeutic targets related to other diseases, such as inflammation, cancer and diabetes, suggesting the possible cross-talks between these complicated diseases. Furthermore, pathways of Ca2+ equilibrium maintaining upstream of cell proliferation and inflammation were densely targeted by the anti-AD herbal ingredients with rigorous statistic evaluation. In addition to the holistic understanding of the pathogenesis of AD, the integrated network analysis on the MOA of herbal ingredients may also suggest new clues for the future disease modifying strategies. [ABSTRACT FROM PUBLISHER]

Background: Public resources of chemical compound are in a rapid growth both in quantity and the types of data-representation. To comprehensively understand the relationship between the intrinsic features of chemical compounds and protein targets is an essential task to evaluate potential protein-binding function for virtual drug screening. In previous studies, correlations were proposed between bioactivity profiles and target networks,especially when chemical structures were similar. With the lack of effective quantitative methods to uncover such correlation, it is demanding and necessary for us to integrate the information from multiple data sources to produce an comprehensive assessment of the similarity between small molecules, as well as quantitatively uncover the relationship between compounds and their targets by such integrated schema.Results: In this study a multi-view based clustering algorithm was introduced to quantitatively integrate compounds similarity from both bioactivity profiles and structural fingerprints. Firstly, a hierarchy clustering was performed with the fused similarity on 37 compounds curated from PubChem. Compared to clustering in a single view, the overall common target number within fused classes has been improved by using the integrated similarity, which indicated that the present multi-view based clustering is more efficient by successfully identifying clusters with its members sharing more number of common targets. Analysis in certain classes reveals that mutual complement of the two views for compound description helps to discover missing similar compound when only single view was applied.Then, a large-scale drug virtual screen was performed on 1267 compounds curated from Connectivity Map (CMap)dataset based on the fused similarity, which obtained a better ranking result compared to that of single-view. These comprehensive tests indicated that by combining different data representations; an improved assessment of target-specific compound similarity can be achieved.Conclusions: Our study presented an efficient, extendable and quantitative computational model for integration of different compound representations, and expected to provide new clues to improve the virtual drug screening from various pharmacological properties. Scripts, supplementary materials and data used in this study are publicity available at http://lifecenter.sgst.cn/fusion/. [ABSTRACT FROM AUTHOR]

R3241 --> Background: Fusobacterium nucleatumis well known as an important pathogenic gut bacterium associated with colorectal cancer (CRC) and the distribution of F. nucleatum and other Fusobacterium species displayed a strong biogeography‐specific pattern. However, their capabilities for diagnosing CRC across multi‐populations remains unclear. Here we assessed the potential of these Fusobacterium species for CRC diagnosis using whole metagenomic sequencing (WMS) and 16S rRNA data. Design: Included in this study were published raw sequencing data, containing WMS data of 1202 subjects from seven countries and 16S rRNA sequencing data of 556 subjects from four countries. MetaPhlAn2 was used to obtain the Fusobacterium species abundance profiles of WMS data. 16S rRNA data were processed with QIIME2 platform. Random forest models were constructed to evaluate the efficiency of Fusobacterium species for CRC diagnosis. Results: Compared to western populations, we found that non‐nucleatum Fusobacterium species (F. mortiferum, F. ulcerans andF. varium) were more prevalent and abundant in Chinese populations. F. nucleatum was commonly detected in all cohorts across regional and ethnic variations. After adjustment for potential confounding factors, both WMS and 16S data showed that only F.nucleatum was significantly elevated in CRC patients in most populations. The diagnostic models constructed with all Fusobacterium taxa achieved an average area under the receiver operating characteristic curve (AUROC) score of 0.70 with the study cohorts. Similarly, the average AUROC based on 16S rRNA data was 0.74. Then we analyzed the contributions of each Fusobacterium species to the classification models. As expected, F. nucleatumcontributed most in all but the Italy cohort.F.nucleatumwas also the most important feature in models built with 16S rRNA data. Consequently, the models constructed withF. nucleatumperformed better than those with other single non‐nucleatum Fusobacterium species with an average AUROC of 0.64 (WMS) and 0.66 (16S rRNA). Conclusion: Our study validated that F. nucleatumcould act as the universal and reproducible microbial marker for CRC. It has been universally detected in different populations albeit being less abundant than other Fusobacterium species, and is likely one of the "keystone" species in the CRC pathogenesis. In contrast, non‐nucleatum Fusobacterium species were region‐specific and with relatively lower capability for diagnosing CRC. Keyworks: CRC, Fusobacterium nucleatum, prescreening, keystone [ABSTRACT FROM AUTHOR]

Cyclic peptides offer a range of notable advantages, including potent antibacterial properties, high binding affinity and specificity to target molecules, and minimal toxicity, making them highly promising candidates for drug development. However, a comprehensive database that consolidates both synthetically derived and naturally occurring cyclic peptides is conspicuously absent. To address this void, we introduce CyclicPepedia (https://www.biosino.org/iMAC/cyclicpepedia/), a pioneering database that encompasses 8744 known cyclic peptides. This repository, structured as a composite knowledge network, offers a wealth of information encompassing various aspects of cyclic peptides, such as cyclic peptides' sources, categorizations, structural characteristics, pharmacokinetic profiles, physicochemical properties, patented drug applications, and a collection of crucial publications. Supported by a user-friendly knowledge retrieval system and calculation tools specifically designed for cyclic peptides, CyclicPepedia will be able to facilitate advancements in cyclic peptide drug development. [ABSTRACT FROM AUTHOR]

• Novel mussel-inspired zwitterionic PCBDA@AgNPs were synthesized. • Antibacterial PCBDA@AgNPs-CG dressing was fabricated via mussel-inspired chemistry. • This dressing effectively inhibited wound infection to promote wound healing. Silver nanoparticles (AgNPs) decorated medical cotton gauze (CG) is a promising antibacterial wound dressing designed to prevent bacterial infection and promote the wound healing. However, in clinical application, the silver loading stability of these AgNPs decorated CGs is currently still a challenge because the leaching of AgNPs from CG may not only cause gradual loss of antibacterial activity but also bring potential side effects. Herein, we developed zwitterionic AgNPs which were one-step synthesized by using poly (carboxybetaine-co-dopamine methacrylamide) copolymer (PCBDA) as a reducing and stabilizing agent under alkaline condition. Taking advantage of the mussel-inspired catechol/amino chemistry, the zwitterionic PCBDA@AgNPs can be facilely and robustly immobilized onto amino-modified CG via both covalent and noncovalent interactions. Owing to the zwitterionic interface of immobilized AgNPs and the sustained release of Ag+, the as-prepared PCBDA@AgNPs-CG not only exhibited excellent bacterial antiadhesive and bactericidal activity but also inhibited biofilm formation in vitro. In addition, this PCBDA@AgNPs-CG possessed good hemocompatibility and cytocompatibility, which is beneficial to be wound dressing. More importantly, in vivo wound healing assay confirmed that this PCBDA@AgNPs-CG dressing could effectively inhibit the wound infection, reduce the inflammatory response and hence promote wound healing. Therefore, such PCBDA@AgNPs-CG dressing has great potential for use in infectious wound management. [ABSTRACT FROM AUTHOR]

Currently, chromium-containing wastewater from tanning process has seriously restricted the sustainable development of the leather industry. This problem can be solved by high-exhaustion chrome tanning technology and chrome-less tanning technology. However, these techniques not only fail to achieve a uniform tanning effect but also reduce the performance of the leather. In this work, pH-sensitive and chromium (III)-loaded nanoparticles were fabricated by self-assembly of poly [poly (ethylene glycol) methyl ether acrylate-co-acrylic acid-co-glycidyl methacrylate (PEGMA-co-AA-co-GMA)] terpolymers templated Cr(OH) 3 mineralization, which were defined as Cr-PPAG NPs and utilized as smart high chrome exhaustion and chrome-less tanning agents. Due to the core-shell structure, these Cr-PPAG NPs exhibit a 'Trojan horses' behavior which can protect Cr3+ from reacting with skin collagen during the penetration process, leading to effective and uniform delivery of Cr3+ to the rawhide's interior. Then, the released Cr3+ from Cr-PPAG NPs could cross-link the carboxyl groups both on the skin collagen and poly (PEGMA- co -AA- co -GMA), thereby producing the high-exhaustion chrome tanning effect. Furthermore, the GMA moieties of poly (PEGMA- co -AA- co -GMA) could further react with amino groups of collagen fiber. The synergy between chrome tanning and the organic tanning effects provided by Cr-PPAG NPs resulted in a chrome-less tanning technology. Finally, the final leather tanned with Cr-PPAG NPs exhibiting improved hygienic characteristics with excellent antiadhesive properties against E. coli and S. aureus bacterial strains. Image 1 • pH-sensitive and chromium (III)-loaded nanoparticles (Cr-PPAG NPs) were fabricated as a smart tanning system. • Cr-PPAG NPs tanning system is the unity of chrome-less tanning technology and high-exhaustion chrome tanning technology. • Cr-PPAG NPs adopt a transmission strategy similar to 'Trojan horses', leading to uniform chrome tanning effect. • The final leather tanned by Cr-PPAG NPs exhibiting improved hygienic characteristics. [ABSTRACT FROM AUTHOR]

Achieving adhesion of hydrogels to universal materials with desirable strength remains a challenge despite emerging application of hydrogels. Herein we present a mussel foot protein (Mfp) inspired polyelectrolyte hydrogel of poly(ethylenimine)/poly(acrylic acid)-dopamine (PEI/PAADA) developed for universal tough adhesion. The highly-concentrated electrostatic and hydrogen-bonding interactions in PEI/PAADA hydrogel resulted in a tensile strength, strain at break, and toughness of 0.297 MPa, 2784 % and 5.440 MJ m−3, respectively. Moreover, the hydrogel can heal itself from physical damages, even can be recycled after totally dried via rehydration because of the high flexibility and reversibility of its dynamic bonds. Combining the strategies of topological stitching and direct bonding, Mfp-derived catechol and PEI/PAA backbone in PEI/PAADA corporately facilitated robust adhesion of universal materials with shear strength of up to 4.4 MPa and peeling strength of 870 J m−2, which is over 10 times greater than that of commercial fibrin gel. The adhesive also exhibited self-healing capability for at least 5 cycles, good stability in 1 M NaCl solution and characteristic debonding catalyzed by calcium. Moreover, in vitro cell behavior and in vivo wound healing assays suggested the potential of PEI/PAADA as wound dressing. [Display omitted] [ABSTRACT FROM AUTHOR]

Berberine has been identified with anti-proliferative effects on various cancer cells. Many researchers have been trying to elucidate the anti-cancer mechanisms of berberine based on differentially expressed genes. However, differentially alternative splicing genes induced by berberine might also contribute to its pharmacological actions and have not been reported yet. Moreover, the potential functional cross-talking between the two sets of genes deserves further exploration. In this study, RNA-seq technology was used to detect the differentially expressed genes and differentially alternative spliced genes in BEL-7402 cancer cells induced by berberine. Functional enrichment analysis indicated that these genes were mainly enriched in the p53 and cell cycle signalling pathway. In addition, it was statistically proven that the two sets of genes were locally co-enriched along chromosomes, closely connected to each other based on protein-protein interaction and functionally similar on Gene Ontology tree. These results suggested that the two sets of genes regulated by berberine might be functionally cross-talked and jointly contribute to its cell cycle arresting effect. It has provided new clues for further researches on the pharmacological mechanisms of berberine as well as the other botanical drugs. [ABSTRACT FROM AUTHOR]

The success of RNA interference (RNAi) depends on the interaction between short interference RNAs (siRNAs) and mRNAs. Design of highly efficient and specific siRNAs has become a challenging issue in applications of RNAi. Here, we present a detailed survey on the state-of-the-art siRNAs design, focusing on several key issues with the current in silico RNAi studies, including: (i) inconsistencies among the proposed guidelines for siRNAs design and the incomplete list of siRNAs features, (ii) improper integration of the heterogeneous cross-platform siRNAs data, (iii) inadequate consideration of the binding specificity of the target mRNAs and (iv) reduction in the ‘off-target’ effect in siRNAs design. With these considerations, the popular in silico siRNAs design rules are reexamined and several inconsistent viewpoints toward siRNAs feature identifications are clarified. In addition, novel computational models for siRNAs design using state-of-art machine learning techniques are discussed, which focus on heterogeneous data integration, joint feature selection and customized siRNAs screening toward highly specific targets. We believe that addressing such issues in siRNA study will provide new clues for further improved design of more efficient and specific siRNAs in RNAi. [ABSTRACT FROM AUTHOR]

Irritable bowel syndrome (IBS) is a common functional gastrointestinal disease. Although visceral hypersensitivity (VH) and disturbed gastrointestinal motility are typical pathophysiological features of IBS, the pathological mechanisms underlying this disease remain unclear. Serotonin system abnormalities are considered to play an important role in the pathomechanisms of IBS. Here, we hypothesize that similar alterations, including VH and colonic motility, induced by serotonin transporter (SERT) knockout result from altered serotonin signaling. We sought to determine the molecular mechanism underlying VH and colonic dysmotility induced by SERT knockout. We found that female SERT (slc6a4)‐knockout (KO; ie, slc6a4−/−) rats exhibited lower pain pressure thresholds (PPTs) than wild‐type (WT; ie, slc6a4+/+) rats in response to colorectal distension (CRD). Significantly increased fecal pellet output and reduced concentration of serum tryptophan were observed in the female SERT KO rats. The concentrations of 5‐hydroxytryptamine (5‐HT) in platelet‐rich plasma (PRP) and serum in SERT KO rats were lower than those in WT rats, but the numbers of enterochromaffin cells (ECs) and the concentrations of 5‐HT in colon of SERT KO rats were higher than those of WT rats. Finally, increased expression levels of 5‐HT1B receptors, 5‐HT2C receptors, 5‐HT3A receptors, 5‐HT3B receptors, 5‐HT6 receptors, 5‐HT7 receptors, and glycosylated dopamine transporters (DATs) were found in the female SERT KO rats. We concluded that alterations in the serotonin system induced by the knockout of slc6a4 might result in VH and accelerated gastrointestinal motility in female SERT KO rats, which can be used as an animal model of IBS. [ABSTRACT FROM AUTHOR]

Fibrosis is a key component in the pathogenic mechanism of a variety of diseases. These diseases involving fibrosis may share common mechanisms and therapeutic targets, and therefore common intervention strategies and medicines may be applicable for these diseases. For this reason, deliberately introducing anti-fibrosis characteristics into predictive modeling may lead to more success in drug repositioning. In this study, anti-fibrosis knowledge base was first built by collecting data from multiple resources. Both structural and biological profiles were then derived from the knowledge base and used for constructing machine learning models including Structural Profile Prediction Model (SPPM) and Biological Profile Prediction Model (BPPM). Three external public data sets were employed for validation purpose and further exploration of potential repositioning drugs in wider chemical space. The resulting SPPM and BPPM models achieve area under the receiver operating characteristic curve (area under the curve) of 0.879 and 0.972 in the training set, and 0.814 and 0.874 in the testing set. Additionally, our results also demonstrate that substantial amount of multi-targeting natural products possess notable anti-fibrosis characteristics and might serve as encouraging candidates in fibrosis treatment and drug repositioning. To leverage our methodology and findings, we developed repositioning prediction platform, drug repositioning based on anti-fibrosis characteristic that is freely accessible via https://www.biosino.org/drafc. [ABSTRACT FROM AUTHOR]

Summary: A challenge in biodata analysis is to understand the underlying phenomena among many interactions in signaling pathways. Such study is formulated as the pathway enrichment analysis, which identifies relevant pathways functional enriched in high-throughput data. The question faced here is how to analyze different data types in a unified and integrative way by characterizing pathways that these data simultaneously reveal. To this end, we developed integrative Pathway Enrichment Analysis Platform, iPEAP, which handles transcriptomics, proteomics, metabolomics and GWAS data under a unified aggregation schema. iPEAP emphasizes on the ability to aggregate various pathway enrichment results generated in different high-throughput experiments, as well as the quantitative measurements of different ranking results, thus providing the first benchmark platform for integration, comparison and evaluation of multiple types of data and enrichment methods.Availability and implementation: iPEAP is freely available at http://www.tongji.edu.cn/∼qiliu/ipeap.html.Contact: qiliu@tongji.edu.cn or zwcao@tongji.edu.cnSupplementary information: Supplementary data are available at Bioinformatics online. [ABSTRACT FROM PUBLISHER]

Metagenomic studies permit the exploration of microbial diversity in a defined habitat, and binning procedures enable phylogenomic analyses, taxon description, and even phenotypic characterizations in the absence of morphological evidence. Such lineages include asgard archaea, which were initially reported to represent archaea with eukaryotic cell complexity, although the first images of such an archaeon show simple cells with prokaryotic characteristics. However, these metagenome-assembled genomes (MAGs) might suffer from data quality problems not encountered in sequences from cultured organisms due to two common analytical procedures of bioinformatics: assembly of metagenomic sequences and binning of assembled sequences on the basis of innate sequence properties and abundance across samples. Consequently, genomic sequences of distantly related taxa, or domains, can in principle be assigned to the same MAG and result in chimeric sequences. The impacts of low-quality or chimeric MAGs on phylogenomic and metabolic prediction remain unknown. Debates that asgard archaeal data are contaminated with eukaryotic sequences are overshadowed by the lack of evidence indicating that individual asgard MAGs stem from the same chromosome. Here, we show that universal proteins including ribosomal proteins of asgard archaeal MAGs fail to meet the basic phylogenetic criterion fulfilled by genome sequences of cultured archaea investigated to date: These proteins do not share common evolutionary histories to the same extent as pure culture genomes do, pointing to a chimeric nature of asgard archaeal MAGs. Our analysis suggests that some asgard archaeal MAGs represent unnatural constructs, genome-like patchworks of genes resulting from assembly and/or the binning process. [ABSTRACT FROM AUTHOR]

Qishen granules (QSG) are a famous formula with cardioprotective properties to heart failure (HF). The aim of this study was to investigate the underlying mechanism of QSG on apoptosis and fibrosis in the treatment of HF. HF model was induced by left anterior descending artery ligation on Sprague-Dawley rats. Transcriptome analysis was used to investigate the regulatory pathways of QSG on HF. Interestingly, downregulated genes of QSG were significantly enriched in Hippo pathway which plays a crucial role in regulating cell apoptosis and proliferation. We found that QSG inhibited the expressions of proapoptotic key proteins P-53 and fibrosis-related proteins TGF-β1, SMAD3, and CTGF. Further, we conducted research on the key proteins in the Hippo pathway upstream of CTGF and P-53. The results showed that MST1, P-MST1, P-LATS1, and RASSF1A that exert proapoptotic function were downregulated after QSG intervention. Similarly, P-YAP and P-TAZ, mediating self-degradation and apoptosis, were both observably decreased after QSG administration. Taken together, QSG are shown to be likely to exert cardioprotective effects by inhibiting the progression of apoptosis and fibrosis through Hippo pathway. [ABSTRACT FROM AUTHOR]

The early history of life harbours many unresolved evolutionary questions, none more important than the genomic origin and cellular evolution of eukaryotes. An issue central to eukaryote origin concerns the position of eukaryotes in the tree of life and the relationship of the host lineage that acquired the mitochondrion some two billion years ago to lineages of modern-day archaea. Recent analyses indicate that the host lineage branches within the Archaea, prompting the search for novel archaeal lineages that can improve our understanding of the cellular evolution of eukaryotes. Here we give a brief review of the studies on Archaea, the tree of life and the cellular evolution of eukaryotes, which is followed by an overview of recent progress fueled by new genomic technologies and recent status of archaeal research in China. Future directions for the study of early evolution are considered. [ABSTRACT FROM AUTHOR]

HuoXueJieDu (HXJD) formula exerts protective effects against diabetic retinopathy (DR) in rats, but its underlying mechanism remains unknown. In the present study, the diabetic rats were established using streptozocin. The administration of HXJD was initiated at 20 weeks after diabetes induction and continued for 12 weeks. Whole genome expression profiles in rat retinas were examined using microarray technology. Differential gene expression and pathway enrichment analysis were conducted on the microarray data, with validation through real-time PCR and immunohistochemical staining. The results showed that 170 genes and several IPA canonical pathways related to inflammation, matrix metabolism, and phototransduction were regulated by HXJD. PCR validation of selected genes, including SOCS3, STAT3, TIMP1, and A2M, confirmed the gene expression changes influenced by HXJD. In addition, the immunohistochemical staining results suggested that critical members of the SOCS3-STAT3 pathway were also affected by HXJD. Taken together, these results indicated that SOCS3-STAT3 and TIMP1-A2M pathways might mediate the alleviation of HXJD activities in rats with diabetic retinopathy. [ABSTRACT FROM AUTHOR]

Archaea are cosmopolitan in aerated soils around the world. While the dominance of Thaumarchaeota has been reported in most soils, the methanogens are recently found to be ubiquitous but with low abundances in the aerated soil globally. However, the seasonal changes of Archaea community in the aerated soils are still in the mist. In this study, we investigated the change of Archaea in the context of environmental variables over a period of 12 months in a subtropical soil on the Chongming Island, China. The results showed that Nitrososphaera spp. were the dominant archaeal population while the methanogens were in low proportions but highly diverse (including five genera: Methanobacterium, Methanocella, Methanosaeta, Methanosarcina, and Methanomassiliicoccus) in the aerated soil samples determined by high throughput sequencing. A total of 126 LSA correlations were found in the dataset including all the 72 archaeal OTUs and 8 environmental factors. A significance index defined as the pagerank score of each OTU divided by its relative abundance was used to evaluate the significance of each OTU. The results showed that five out of 17 methanogen OTUs were significantly positively correlated with temperature, suggesting those methanogens might increase with temperature rather than being dormant in the aerated soils. Given the metabolic response of methanogens to temperature under aerated soil conditions, their contribution to the global methane cycle warrants evaluation. [ABSTRACT FROM AUTHOR]

• Flame temperature and soot characteristics are measured via optical diagnostics. • Adding propylene causes the transition from a non-smoking flame to a smoking flame. • The synergistic effect on soot particle diameter is found when blending propane. • Earlier inception time and longer growth time account for the synergistic effect. Soot evolution of the ethylene-based laminar coflow diffusion flame doping with methane, propane, and propylene with the blending ratio ranging from 0 to 50% has been investigated experimentally. These fuels were selected for their different fuel structure. Spatially resolved distribution maps of the flame temperature, soot volume fraction, the fluorescence signals of polycyclic aromatic hydrocarbons (PAHs), and primary soot particle diameter and number density were determined utilizing laser-induced incandescence (LII), laser-induced fluorescence (LIF), and ratio pyrometry (RP). It was found that the flame height surged and the flame temperature dropped dramatically when the propylene blending ratio was 20% while they were almost constant with the increasing addition of methane or propane. The soot/PAHs loading decreased monotonically with the addition of methane and the opposite was true in the cases of blending propylene. The synergistic effect of mixing propane into ethylene was found on both the soot/PAHs loading. The same trends were observed in the percentage of carbon conversion to soot and the primary soot particle diameter. It can be seen from the soot evolution analysis that methane addition suppressed the soot nucleation and surface growth simultaneously. The enhanced soot surface growth for the flames doping with propane at a low addition level and for the whole flame sets doping with propylene were attributed to the earlier inception time and the longer mass growth time. The preferential diffusion and weakened oxidation of soot particles because of the decreased flame temperature perhaps accounted for the transition from a non-smoking flame to a smoking flame when the propylene blending ratio was greater than 40%. [ABSTRACT FROM AUTHOR]

Motivation: Protein-binding sites prediction lays a foundation for functional annotation of protein and structure-based drug design. As the number of available protein structures increases, structural alignment based algorithm becomes the dominant approach for protein-binding sites prediction. However, the present algorithms underutilize the ever increasing numbers of three-dimensional protein-ligand complex structures (bound protein), and it could be improved on the process of alignment, selection of templates and clustering of template. Herein, we built so far the largest database of bound templates with stringent quality control. And on this basis, bSiteFinder as a protein-binding sites prediction server was developed. Results: By introducing Homology Indexing, Chain Length Indexing, Stability of Complex and Optimized Multiple-Templates Clustering into our algorithm, the efficiency of our server has been significantly improved. Further, the accuracy was approximately 2-10 % higher than that of other algorithms for the test with either bound dataset or unbound dataset. For 210 bound dataset, bSiteFinder achieved high accuracies up to 94.8 % (MCC 0.95). For another 48 bound/unbound dataset, bSiteFinder achieved high accuracies up to 93.8 % for bound proteins (MCC 0.95) and 85.4 % for unbound proteins (MCC 0.72). Our bSiteFinder server is freely available at , and the source code is provided at the methods page. Conclusion: An online bSiteFinder server is freely available at . Our work lays a foundation for functional annotation of protein and structure-based drug design. With ever increasing numbers of three-dimensional protein-ligand complex structures, our server should be more accurate and less time-consuming.[Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

The issue of herb-drug interactions has been widely reported. Herbal ingredients can activate nuclear receptors and further induce the gene expression alteration of drug-metabolizing enzyme and/or transporter. Therefore, the herb-drug interaction will happen when the herbs and drugs are coadministered. This kind of interaction is called inductive herb-drug interactions. Pregnane X Receptor (PXR) and drug-metabolizing target genes are involved in most of inductive herb-drug interactions. To predict this kind of herb-drug interaction, the protocol could be simplified to only screen agonists of PXR from herbs because the relations of drugs with their metabolizing enzymes are well studied. Here, a combinational in silico strategy of pharmacophore modelling and docking-based rank aggregation (DRA) was employed to identify PXR’s agonists. Firstly, 305 ingredients were screened out from 820 ingredients as candidate agonists of PXR with our pharmacophore model. Secondly, DRA was used to rerank the result of pharmacophore filtering. To validate our prediction, a curated herb-drug interaction database was built, which recorded 380 herb-drug interactions. Finally, among the top 10 herb ingredients from the ranking list, 6 ingredients were reported to involve in herb-drug interactions. The accuracy of our method is higher than other traditional methods. The strategy could be extended to studies on other inductive herb-drug interactions. [ABSTRACT FROM AUTHOR]

R4363 --> 826.6 --> Background: Previous studies reported inconsistent results regarding altered gut microbiome in patients with Crohn's disease (CD), likely due to the large impact of genetic polymorphisms and environmental factors on the structure of the gut microbiota. We aim to investigate the altered microbiome in CD with a cohort that minimizes the impact of irrelevant genetic and environmental factors on the gut microbiota. Method: Stool samples and clinical records were collected from 91 patients withCD and their healthy siblings in the Sixth Affiliated Hospital of Sun Yat‐sen University in Guangzhou, China, between March 2014 and December 2018. Fecal DNA was isolated and the V5‐V6 region of the 16S rRNA gene was sequenced on a MiSeq platform. Data was processed with QIIME2. Spearman analysis was performed to identify the microbial features correlated with inflammatory markers. Result: Compared to healthy siblings, CD patients exhibited reduced alpha diversities based on the metrics of Chao1, Shannon, and observed speciesat the ASV level (P<0.05). Beta diversity was significantly different between study groups according to UniFrac based principle coordinate analysis (P<0.001). Altered abundances were observed at various taxonomic levels comparing between CD patients and their healthy siblings, including increased abundance in Escherichia‐Shigella and Veillonella, and decreased abundance in Lachnospiraceae, Prevotella 9 and Faecalibacterium in CD patients. Spearman analysis identified significant correlations between Escherichia‐ Shigella and Lachnospiraceae with inflammatory markers erythrocyte sedimentation rate, C‐reactive protein, and white blood cell count (Fig.1). Discussion: By comparing between CD patients with their siblings, the impact of the compounding genetic and environmental factors on the gut microbita was minimized. This approach allowed the identification of CD specific microbial fearures that are correlated with inflammatory markers. Further study along this line may establish CD specific microbial targets for diagnostic and therapeutic purposes. [ABSTRACT FROM AUTHOR]

R3041 --> 377.5 --> Background: The early detection of colorectal cancer (CRC), especially at precancerous adenoma stage, significantly reduces its incidence. Gut microbiome has become a promising non‐invasive tool for CRC screening, whereas the potential of microbial multidimensional signatures remains poorly understood. Here we performed a cross‐cohort analysis to evaluate the capability of microbial multidimensional biomarkers for adenoma detection. Design: Whole metagenome sequencing data of four public datasets including 183 adenoma patients and 439 healthy controls were reprocessed consistently to obtain taxonomic‐, functional‐ and single‐nucleotide variants (SNVs)‐profiling. With MMUPHin, differential multidimensional signatures were identified after adjusting confounders, based on which random forest (RF) models were constructed and then optimized by recursive feature elimination. Finally, internal validation and external validation with in‐house dataset (10 controls and 6 adenomas) and five resampled datasets were conducted to further assess the robustness of the best biomarker panel. Results: The integrated analysis identified 103 multi‐kingdom differential species between adenoma and control group, of which 15 optimal species were selected to construct a RF model achieving an AUC of 0.75. Meanwhile, the model constructed with 31 optimal biomarkers out of 386 differential KO genes reached an AUC of 0.74. Notably, the diagnostic model with 75 SNVs from 10 species showed superior accuracy (AUC = 0.85) with high specificity to adenoma. Co‐abundance analysis revealed intensive bacterial‐fungal associations in line with functional abnormalities related to microbial quorum sensing, purine and butanoate metabolism. Conclusion: Microbial SNV biomarkers outperform other biomarkers and display high specificity to adenoma, which may serve as a novel non‐invasive tool for early detection of CRC. Furthermore, multidimensional signatures provide potential therapeutic targets for adenoma. [ABSTRACT FROM AUTHOR]

Despite the high specificity between antigen and antibody binding, similar epitopes can be recognized or cross-neutralized by paratopes of antibody with different binding affinities. How to accurately characterize this slight variation which may or may not change the antigen-antibody binding affinity is a key issue in this area. In this report, by combining cylinder model with shell structure model, a new fingerprint was introduced to describe both the structural and physical-chemical features of the antigen and antibody protein. Furthermore, beside the description of individual protein, the specific epitope-paratope interaction fingerprint (EPIF) was developed to reflect the bond and the environment of the antigen-antibody interface. Finally, Proteochemometric Modeling of the antigen-antibody interaction was established and evaluated on 429 antigen-antibody complexes. By using only protein descriptors, our model achieved the best performance () among peers. Further, together with EPIF as a new cross-term, our model () can significantly outperform peers with multiplication of ligand and protein descriptors as a cross-term (). Results illustrated that: 1) our newly designed protein fingerprints and EPIF can better describe the antigen-antibody interaction; 2) EPIF is a better and specific cross-term in Proteochemometric Modeling for antigen-antibody interaction. The fingerprints designed in this study will provide assistance to the description of antigen-antibody binding, and in future, it may be valuable help for the high-throughput antibody screening. The algorithm is freely available on request. [ABSTRACT FROM AUTHOR]

PPIs are mainly metabolized by CYP2C19. It has a stereoselectivity effect on R- and S-isomers of PPIs according to previous studies. However, no study has been reported to elucidate the binding mechanism at the atomic level based on the CYP2C19 crystal structure. Recently, the advent of the first crystal structure of CYP2C19 allowed us to take in silico approaches including MD simulation, MM/ GBSA calculation, energy decomposition, and alanine scanning to explore the stereoselectivity of CYP2C19 on R- and S-isomers of PPIs. The key residues responsible for the selective binding for R- and S-isomers of omeprazole, lansoprazole, and pantoprazole are disclosed by free energy and alanine scanning analysis. Structural analysis showed that chiral isomers of PPIs alter their conformations to have strong binding affinities with CYP2C19. Furthermore, a theoretical pharmacophore model of PPIs was obtained with the importance of pharmacophore feature being weighted, basing on our results. Our results are valuable for designing and synthesizing new generation of PPIs in the future. [ABSTRACT FROM AUTHOR]

Berberine is an isoquinoline alkaloid that has drawn extensive attention because it possesses various biological activities. Several mechanisms have been proposed to interpret the anticancer activity of berberine. However, these explanations are mostly based on its downstream-regulated genes or proteins; information on the direct target proteins that mediate the antiproliferative action of berberine remains unclear. In this study, a computational pipeline based on a ligand-protein inverse docking program and mining of the 'Connectivity MAP' data was adopted to explore the potential target proteins for berberine. The results showed that four proteins, that is calmodulin, cytochrome P450 3 A4, sex hormone-binding globulin, and carbonic anhydrase II, were suggested to be the potential targets of berberine. The anticalmodulin property of berberine was demonstrated with an in vitro phosphodiesterase activity assay. Flow cytometric analysis found that G1 cell cycle arrest induced by berberine in Bel7402 cells was enhanced by cotreatment with calmodulin inhibitors. Western blotting results indicated that berberine treatment decreased phosphorylation of calmodulin kinase II and blocked subsequent MEK1 activation as well as p27 protein degradation. These results suggested that calmodulin might play crucial roles in berberine-induced cell cycle arrest in cancer cells. [ABSTRACT FROM AUTHOR]

Abstract: G protein-coupled receptors (GPCRs) are the most frequently addressed drug targets in the pharmaceutical industry. However, achieving highly safety and efficacy in designing of GPCR drugs is quite challenging since their primary amino acid sequences show fairly high homology. Systematic study on the interaction spectra of inhibitors with multiple human GPCRs will shed light on how to design the inhibitors for different diseases which are related to GPCRs. To reach this goal, several proteochemometric models were constructed based on different combinations of two protein descriptors, two ligand descriptors and one ligand–receptor cross-term by two kinds of statistical learning techniques. Our results show that support vector regression (SVR) performs better than Gaussian processes (GP) for most combinations of descriptors. The transmembrane (TM) identity descriptors have more powerful ability than the z-scale descriptors in the characterization of GPCRs. Furthermore, the performance of our PCM models was not improved by introducing the cross-terms. Finally, based on the TM Identity descriptors and 28-dimensional drug-like index, two best PCM models with GP and SVR (GP-S-DLI: R 2 =0.9345, Q 2 test =0.7441; SVR-S-DLI: R 2 =1.0000, Q 2 test =0.7423) were derived respectively. The area of ROC curve was 0.8940 when an external test set was used, which indicates that our PCM model obtained a powerful capability for predicting new interactions between GPCRs and ligands. Our results indicate that the derived best model has a high predictive ability for human GPCR–inhibitor interactions. It can be potentially used to discover novel multi-target or specific inhibitors of GPCRs with higher efficacy and fewer side effects. [Copyright &y& Elsevier]

Abstract: Uricase was lost in hominoids during primate evolution, but the inactivation mechanism remains controversial. To investigate the inactivation process of hominoid uricase, chimeric constructions between canine and human uricase were employed to screen the target regions that may contain labile or inactivated mutations in deduced human uricase. Four chimeric uricases were constructed and showed different enzymatic characteristics. Homology modeling, rational site-directed mutagenesis and DNA alignment were used to analyze the changes. Arg119 is conserved in functional mammalian uricases and its side-chains are crucial in maintaining the stability of the β-barrel core. A single CGT (Arg) to CAT (His) mutation at codon 119 that is shared by the human and great ape clade greatly reduces this stability and could cause the loss of uricase activity. We speculate that this missense mutation occurred first and inactivated the uricase protein in humans and great apes and that later the known nonsense mutation at codon 33 occurred and silenced the uricase gene. A single GTC (Val) to GCC (Ala) mutation at codon 296 in canine uricase is regarded as deleterious structural mutation, but such kinds of deleterious mutations have been widely accumulated in extant mammalian uricases. We speculate that a reduction in uricase activity has been an evolutionary tendency in mammals. Moreover, from structure–activity analysis of helix 2 in ancestral primate uricase, we suggest that before the inactivation of hominoid uricase, deleterious structural evolutionary changes had occurred in ancestral primates. The loss of hominoid uricase should be caused by progressive multistep mutations rather than a single mutation event. [Copyright &y& Elsevier]

Background: Histone deacetylase (HDAC) is a novel target for the treatment of cancer and it can be classified into three classes, i.e., classes I, II, and IV. The inhibitors selectively targeting individual HDAC have been proved to be the better candidate antitumor drugs. To screen selective HDAC inhibitors, several proteochemometric (PCM) models based on different combinations of three kinds of protein descriptors, two kinds of ligand descriptors and multiplication cross-terms were constructed in our study. Results: The results show that structure similarity descriptors are better than sequence similarity descriptors and geometry descriptors in the characterization of HDACs. Furthermore, the predictive ability was not improved by introducing the cross-terms in our models. Finally, a best PCM model based on protein structure similaritydescriptors and 32-dimensional general descriptors was derived (R2 = 0.9897, Qtest2 = 0.7542), which shows a powerful ability to screen selective HDAC inhibitors.Conclusions: Our best model not only predict the activities of inhibitors for each HDAC isoform, but also screen and distinguish class-selective inhibitors and even more isoform-selective inhibitors, thus it provides a potential way to discover or design novel candidate antitumor drugs with reduced side effect. [ABSTRACT FROM AUTHOR]

Background: The Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway. Results: In this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway. Conclusions: Our model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1. [ABSTRACT FROM AUTHOR]

Abstract: The toxicity of melamine has attracted much attention since the outbreak of nephrolithiasis among children ingesting melamine-contaminated infant formula in China. However, there is little knowledge about the molecular mechanisms underlying the melamine-induced toxicity. In this paper, a ligand–protein docking method (INVDOCK) was applied to predict the toxicity-related target proteins for melamine and its metabolite, cyanuric acid. As a result, 23 and 35 proteins were finally identified as the potential target proteins for melamine and cyanuric acid, respectively. Through an enrichment analysis, it was found that nephrotoxicity and lung toxicity might be the most significant toxicities induced by melamine and cyanuric acid. Four target proteins (glutathione peroxidase 1, beta-hexosaminidase subunit beta, l-lactate dehydrogenase and lysozyme C) may be related to the molecular basis of the nephrotoxicity induced by melamine except for known kidney crystals formation. After mapping all these toxicity-related target proteins onto cellular pathways, it was indicated that the toxicities of melamine and cyanuric acid might also be caused by breaking down redox balance, perturbing the arginine and proline metabolism and damaging the homeostasis of energy production system. To further explore the mechanisms underlying the toxicities of melamine and cyanuric acid, a biological signal cascades network constructed by some of the toxicity-related target proteins was discussed. [Copyright &y& Elsevier]

Antibody molecules interact with antigen proteins through the epitope area, where the epitope residues are found to be discontinuous or spatial or conformational rather than linear on the protein surface. There are various computational algorithms to predict the spatial epitopes, and each of them have an outstanding performance based on their individual testing dataset. In this work, an independent dataset was created through collection of the epitope residual sites which have been confirmed by experiments. Based on this dataset, 6 popular web-servers developed for B-cell structural epitope prediction, including SEPPA, CEP, DiscoTope, ElliPro, PEPOP and BEpro, were evaluated and compared according to sensitivity, the positive predictive value, the successful pick-up rate and the area under the curve of the receiver operator characteristic (AUC). The results showed that the general performance of spatial epitope prediction tools did obtain substantial advancement, and SEPPA gave the best performance among the 6 tools. However, the current prediction accuracy was still far from satisfaction. Moreover, our comparison elucidated that the performance of the web-servers was significantly affected by their training datasets and the algorithms adopted. In this sense, the results of our research may improve the design of B-cell epitope prediction tools and provide additional clues when the users utilize these tools in their related research. [ABSTRACT FROM AUTHOR]

R3269 --> Background: Inflammatory bowel disease(IBD),including Crohn's Disease(CD) and ulcerative colitis (UC), is closely linked with altered gut microbiota.Roles of bacteria in IBD have been widely investigated, whereas other microbial kingdoms, fungi, archaea, virus, are less explored. Here, we aim to investigate the multi‐kingdom microbial alterations and their capabilities for IBD diagnosis. Methods: A total of 968 stool samples (292 CD, 305 UC and 371 controls) of untreated patients from iHMP were collected. Differential microorganisms were identified via wilcoxon test followed by adjustment for confounders. Inter‐kingdom co‐occurrence interactions analysis was performed by SparCC then microorganism modules were clustered by "MCODE". Subsequently, neural networks algorithm was used to build diagnostic models for CD or UC with single‐ or multi‐kingdom microbial features and the best panel of biomarkers was further identified by recursive feature elimination. Moreover, diagnostic models were validated in additional independent cohorts. Differential microbial pathways were analyzed to further explore functional alterations in CD and UC. Results: In CD and UC, the microbial compositional change was identified in different kingdoms. Compared to controls, we identified 41 bacteria, 37 fungi, 40 archaea and 50 viruses with differential abundance in CD. Similarly, 63 bacteria, 52 fungi, 58 archaea and 39 viruses with differential abundance were detected in UC. Moreover, inter‐kingdom interactions were more complex in IBD than controls, especially the interactions between fungal Aspergillusand BeAn 58058 virus. Notably, the diagnostic models constructed with multi‐kingdom microbial features performed better (AUC of 0.90 in CD and 0.91 in UC) than that with single kingdom microbial features. The diagnostic models also showed reliable accuracy in independent cohorts with an average AUC of 0.93 (CD) and 0.74 (UC), respectively. Among these biomarkers, bacterial Bacteroidesand fungalAspergillusare the main contributors to the distinguishing ability in both CD and UC diagnostic models. In addition, pathways related to lipid and terpenoids metabolism and immune response were altered in CD and UC, such as glycosphingolipid biosynthesis, carotenoid biosynthesis and IL‐17 signaling pathway. Conclusions: Our study investigated comprehensivepathogenic microbiota of IBD, which encompasses bacteria, fungi, virus and archaea. And the combination of multi‐kingdom microbial biomarkers may serve as effective tools for CD and UC diagnosis, which outperforms single kingdom biomarkers. The alterations of microbial inter‐kingdom interactions and cross‐kingdom functional changes provide new insight in understanding pathological mechanisms of IBD. [ABSTRACT FROM AUTHOR]

Background: Prior studies reported that 5 ~ 32% COVID-19 patients were critically ill, a situation that poses great challenge for the management of the patients and ICU resources. We aim to identify independent risk factors to serve as prediction markers for critical illness of SARS-CoV-2 infection.Methods: Fifty-two critical and 200 non-critical SARS-CoV-2 nucleic acid positive patients hospitalized in 15 hospitals outside Wuhan from January 19 to March 6, 2020 were enrolled in this study. Multivariable logistic regression and LASSO logistic regression were performed to identify independent risk factors for critical illness.Results: Age older than 60 years, dyspnea, respiratory rate > 24 breaths per min, leukocytosis > 9.5 × 109/L, neutrophilia > 6.3 × 109/L, lymphopenia < 1.1 × 109/L, neutrophil-to-lymphocyte ratio > 3.53, fibrinogen > 4 g/L, d-dimer > 0.55 μg/mL, blood urea nitrogen > 7.1 mM, elevated aspartate transaminase, elevated alanine aminotransferase, total bilirubin > 21 μM, and Sequential Organ Failure Assessment (SOFA) score ≥ 2 were identified as risk factors for critical illness. LASSO logistic regression identified the best combination of risk factors as SOFA score, age, dyspnea, and leukocytosis. The Area Under the Receiver-Operator Curve values for the risk factors in predicting critical illness were 0.921 for SOFA score, 0.776 for age, 0.764 for dyspnea, 0.658 for leukocytosis, and 0.960 for the combination of the four risk factors.Conclusions: Our findings advocate the use of risk factors SOFA score ≥ 2, age > 60, dyspnea and leukocytosis > 9.5 × 109/L on admission, alone or in combination, to determine the optimal management of the patients and health care resources. [ABSTRACT FROM AUTHOR]

Recipes (Qingre Jiedu (QJ), Wenyang Yiqi (WYYQ) and Huo Xue (HX)) in Qishen granules (QSG) are believed to synergistically exert cardio-protective effects. However, the underlying pattern of each decomposed recipe in QSG and their synergistic effects in the treatment of heart failure (HF) are not clear. The purpose of this study is to explore the biological contributions of decomposed recipes to therapeutic effects of QSG and reveal the pharmacological mechanism of QSG in treating HF. The therapeutic effects of QSG or its recipes on heart failure were examined in wet-lab at both transcription and phenotypic level using HF Sprague-Dawley rats. Sequencing and transcriptome analyses were performed using in silico approaches including identification of differentially expressed genes, pathway enrichment and protein-protein interaction network studies. Specially, an optimized in silico quantitative pathway analysis that maximally extracted gene expression information was developed to reveal differentially expressed pathways (DEPs) among various groups, and is publicly available as R package QPA on GitHub (https://github.com/github-gs/QPA). Finally, the HF-related genes predicted using DEP approach were validated by quantitative real-time polymerase chain reaction and western blot. Multiple key genes and the associated signaling pathways were shown to be highly relevant for the therapeutic effect of QSG. Decreased expression of Spp1 gene required for inflammatory signaling and profibrotic signaling were observed in failing hearts treated with QJ, WYYQ and HX. Decreased expression of Cx3cr1 gene required for inflammatory signaling was observed in failing hearts treated with WYYQ and HX. Decreased expression of Myc gene required for oxidative stress and Fgfr2 gene required for profibrotic signaling were observed in failing hearts treated with HX and WYYQ, respectively. Increased expression of Adcy1 gene required for cAMP-PKA signaling cascade was observed in failing hearts treated with WYYQ and HX. Our study suggests that QJ, WYYQ and HX recipes in QSG achieve synergistic and complementary therapeutic effects through alleviating inflammatory responses, attenuating ventricular remodeling and enhancing myocardial energy supply. Image 1 [ABSTRACT FROM AUTHOR]

Qishen granules (QSG) have beneficial therapeutic effects for heart failure, but the effects of decomposed recipes, including Wenyang Yiqi Huoxue (WYH) and Qingre Jiedu (QJ), are not clear. In this study, the efficacy of WYH and QJ on heart failure is evaluated by using transverse aortic constriction (TAC) induced mice and the significantly changed genes in heart tissues were screened with a DNA array. Furthermore, a new quantitative pathway analysis tool is developed to evaluate the differences of pathways in different groups and to identify the pharmacological contributions of the decomposed recipes. Finally, the related genes in the significantly changed pathways are verified by a real-time polymerase chain reaction and a Western blot. Our data show that both QJ and WYH improve the left ventricular ejection fraction, which explain their contributions to protect against heart failure. In the energy metabolism, QJ achieves the therapeutic effects of QSG through nicotinamide nucleotide transhydrogenase (Nnt)-mediated mechanisms. In ventricular remodeling and inflammation reactions, QJ and WYH undertake the therapeutic effects through 5′-nucleotidase ecto (Nt5e)-mediated mechanisms. Together, QJ and WYH constitute the therapeutic effects of QSG and play important roles in myocardial energy metabolism and inflammation, which can exert therapeutic effects for heart failure. [ABSTRACT FROM AUTHOR]

Traditional Chinese Medicine (TCM) treatment has been commonly used to treat Chronic Hepatitis B (CHB) in Asian countries based on TCM syndrome diagnosis, also called 'ZHENG'. The syndrome is identified through the four-diagnostic methods, with certain degree of subjectivity and ambiguity from individual doctors. Normally those CHB patients also receive series of parameters from modern clinical examination, while they are routinely believed to be unrelated with the TCM syndrome diagnosis. In this study, we investigated whether these biomedical indexes in modern medicine could be beneficial to TCM syndrome diagnostics in an integrative way. Based on 634 patient samples from health controls and three subtypes of CHB syndromes, a two-view based hierarchical classification model was tested for TCM syndromes prediction based on totally 222 parameters integrated from both TCM practice and modern clinical tests. The results indicated that the performance of syndrome classification based on a proper integration of TCM and modern clinical indexes was significantly higher than those based on one view of parameters only. Furthermore, those indexes correlated with CHB syndrome diagnosis were successfully identified for CM indexes and biochemical indexes respectively, where potential associations between them were hinted to the MAPK signaling pathway. [ABSTRACT FROM AUTHOR]