Hydrogels with high sacrifice efficiency of sacrificial bonds and with high strength and toughness due to dense entanglements of polymer chains.

Introducing sacrificial bonds is a common method for increasing the toughness of hydrogels. Many sacrificial bonds have been extensively investigated, but the sacrifice efficiency has never been studied. In this study, polyacrylamide hydrogels with highly entangled polymer chains containing carboxyl-zirconium (-COO--Zr4+) sacrificial bonds are prepared to study the effect of polymer chain entanglement on the sacrificial bond efficiency. Unlike chemical crosslinking points, the dense physical entanglements do not affect the toughness (∼43 MJ/m3) of hydrogels but significantly improve the tensile strength (by two times) and Young's modulus (by six times). Physical entanglements enable the chains to slide and adjust the network structure under stress, which enables more polymer chains and sacrificial bonds to participate in the deformation process. Therefore, dense entanglements will greatly improve the sacrifice efficiency. However, a high density of chemical crosslinking points will limit the improvement in the sacrifice efficiency, which is attributed to the sliding limitations because of physical entanglement. The highly entangled polyacrylamide hydrogels toughened by -COO--Zr4+ have an excellent load-bearing capacity. This study provides a novel strategy for designing hydrogels with ultra-high strength and toughness, which paves the way for the development of many hydrogels used in engineering materials.

The evaluation of cytokines in predicting the organ injury of critically pediatric patients: a retrospective study.

Background: The current early warning model for organ damage in critically ill patients has certain limitations. Based on the pathological mechanism, the establishment of an early warning system for organ damage in critically ill children using cytokines profile has not been explored. The aim of this study is to explore the predicting value of cytokines in critically ill patients. Methods: There were 200 critically pediatric patients and 49 general patients between August 22, 2018 and April 28, 2023 from Children's Hospital of Soochow University enrolled in this study. The clinical information was retrospectively collected and analyzed. The cytokine profiles of these patients were detected by flow cytometry. Receiver operating characteristic (ROC) curves were plotted to determine the association between the cytokines and organ injury. Results: There were no statistically significant differences in gender, age and underlying disease between critically ill patients and general patients. The interleukin (IL)-6 (P<0.001), IL-10 (P<0.001), IL-17A (P=0.001), tumor necrosis factor-α (TNF-α) (P=0.02) and interferon-γ (IFN-γ) (P=0.02) level in the critically patients were significantly higher than those in the general patients. The results showed that the incidence of acute gastrointestinal injury (AGI) and acute kidney injury (AKI) in critically ill patients was 39% and 23.5%, respectively. Moreover, there were 4% and 3.5% patients with the occurrence of cardiac arrest and acute live injury. The IFN-γ level was increased in these patients with acute liver injury compared to those without these organ injuries, but reduced in the patients with AGI compared to those without. The patients with AKI showed a significant increase in IL-10 in contrast to those without. The IL-2, IL-4, IL-6, IL-10 and IL-17A were higher in patients with acute liver failure (ALF), but TNF-α was reduced, compared to those without. The IL-2, IL-4, IL-6 and IL-10 were significantly increased in the patients with cardiac arrest compared to those without. When IL-10 was higher than 279.45 pg/mL, the sensitivity and specificity for predicting cardiac arrest were 0.875 and 0.927, respectively. While the sensitivity and specificity of IL-6 (more than 1,425.6 pg/mL) were 0.625 and 0.844, respectively. However, no synergistic effect of IL-6 and IL-10 was observed for predicting cardiac arrest. Additionally, the IL-17A (more than 21.6 pg/mL) was a good predictor for the incidence of ALF (sensitivity =0.714, specificity =0.876). Conclusions: The cytokines profile was different between critically ill patients with organ injury and those without organ injury. The IL-6 and IL-10 levels were good predictors for cardiac arrest in critically ill patients. Additionally, higher IL-17A predicted the incidence of ALF of the critically ill patients.

Enhanced microbiota profiling in patients with quiescent Crohn's disease through comparison with paired healthy first-degree relatives.

Prior studies indicate no correlation between the gut microbes of healthy first-degree relatives (HFDRs) of patients with Crohn's disease (CD) and the development of CD. Here, we utilize HFDRs as controls to examine the microbiota and metabolome in individuals with active (CD-A) and quiescent (CD-R) CD, thereby minimizing the influence of genetic and environmental factors. When compared to non-relative controls, the use of HFDR controls identifies fewer differential taxa. Faecalibacterium, Dorea, and Fusicatenibacter are decreased in CD-R, independent of inflammation, and correlated with fecal short-chain fatty acids (SCFAs). Validation with a large multi-center cohort confirms decreased Faecalibacterium and other SCFA-producing genera in CD-R. Classification models based on these genera distinguish CD from healthy individuals and demonstrate superior diagnostic power than models constructed with markers identified using unrelated controls. Furthermore, these markers exhibited limited discriminatory capabilities for other diseases. Finally, our results are validated across multiple cohorts, underscoring their robustness and potential for diagnostic and therapeutic applications.

Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder.

Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder's adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ).

CyclicPepedia: a knowledge base of natural and synthetic cyclic peptides.

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.

Tough double network hydrogels with rapid self-reinforcement and low hysteresis based on highly entangled networks.

Most tough hydrogels are reinforced by introducing energy dissipation mechanisms, but simultaneously realizing a high toughness and low hysteresis is challenging because the energy dissipation structure cannot recover rapidly. In this work, high mechanical performance highly entangled double network hydrogels without energy dissipation structure are fabricated, in which physical entanglements act as the primary effective crosslinking in the first network. This sliding entanglement structure allows the hydrogel network to form a highly uniform oriented structure during stretching, resulting in a high tensile strength of ~3 MPa, a fracture energy of 8340 J m-2 and a strain-stiffening capability of 47.5 in 90% water content. Moreover, almost 100% reversibility is obtained in this hydrogel via energy storage based on entropy loss. The highly entangled double network structure not only overcomes the typical trade-off between the high toughness and low hysteresis of hydrogels, but more importantly, it provides an insight into the application of entanglement structures in high-performance hydrogels.

Global fungal-host interactome mapping identifies host targets of candidalysin.

Candidalysin, a cytolytic peptide toxin secreted by the human fungal pathogen Candida albicans, is critical for fungal pathogenesis. Yet, its intracellular targets have not been extensively mapped. Here, we performed a high-throughput enhanced yeast two-hybrid (HT-eY2H) screen to map the interactome of all eight Ece1 peptides with their direct human protein targets and identified a list of potential interacting proteins, some of which were shared between the peptides. CCNH, a regulatory subunit of the CDK-activating kinase (CAK) complex involved in DNA damage repair, was identified as one of the host targets of candidalysin. Mechanistic studies revealed that candidalysin triggers a significantly increased double-strand DNA breaks (DSBs), as evidenced by the formation of γ-H2AX foci and colocalization of CCNH and γ-H2AX. Importantly, candidalysin binds directly to CCNH to activate CAK to inhibit DNA damage repair pathway. Loss of CCNH alleviates DSBs formation under candidalysin treatment. Depletion of candidalysin-encoding gene fails to induce DSBs and stimulates CCNH upregulation in a murine model of oropharyngeal candidiasis. Collectively, our study reveals that a secreted fungal toxin acts to hijack the canonical DNA damage repair pathway by targeting CCNH and to promote fungal infection.

Multi-kingdom microbial signatures in excess body weight colorectal cancer based on global metagenomic analysis.

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.

Universal adhesion using mussel foot protein inspired hydrogel with dynamic interpenetration for topological entanglement.

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.

Host-microbiota interactions contributing to the heterogeneous tumor microenvironment in colorectal cancer.

Colorectal cancer (CRC) exhibits pronounced heterogeneity and is categorized into four widely accepted consensus molecular subtypes (CMSs) with unique tumor microenvironments (TMEs). However, the intricate landscape of the microbiota and host-microbiota interactions within these TMEs remains elusive. Using RNA-sequencing data from The Cancer Genome Atlas, we analyzed the host transcriptomes and intratumoral microbiome profiles of CRC samples. Distinct host genes and microbial genera were identified among the CMSs. Immune microenvironments were evaluated using CIBERSORTx and ESTIMATE, and microbial coabundance patterns were assessed with FastSpar. Through LASSO penalized regression, we explored host-microbiota associations for each CMS. Our analysis revealed distinct host gene signatures within the CMSs, which encompassed ferroptosis-related genes and specific immune microenvironments. Moreover, we identified 293, 153, 66, and 109 intratumoral microbial genera with differential abundance, and host-microbiota associations contributed to distinct TMEs, characterized by 829, 1,270, 634, and 1,882 robust gene-microbe associations for each CMS in CMS1-CMS4, respectively. CMS1 featured inflammation-related HSF1 activation and gene interactions within the endothelin pathway and Flammeovirga. Integrin-related genes displayed positive correlations with Sutterella in CMS2, whereas CMS3 spotlighted microbial associations with biosynthetic and metabolic pathways. In CMS4, genes involved in collagen biosynthesis showed positive associations with Sutterella, contributing to disruptions in homeostasis. Notably, immune-rich subtypes exhibited pronounced ferroptosis dysregulation, potentially linked to tissue microbial colonization. This comprehensive investigation delineates the diverse landscapes of the TME within each CMS, incorporating host genes, intratumoral microbiota, and their complex interactions. These findings shed light on previously uncharted mechanisms underpinning CRC heterogeneity and suggest potential therapeutic targets.NEW & NOTEWORTHY This study determined the following: 1) providing a comprehensive landscape of consensus molecular subtype (CMS)-specific tumor microenvironments (TMEs); 2) constructing CMS-specific networks, including host genes, intratumoral microbiota, and enriched pathways, analyzing their associations to uncover unique patterns that demonstrate the intricate interplay within the TME; and 3) revealing a connection between immune-rich subtypes and ferroptosis activation, suggesting a potential regulatory role of the microbiota in ferroptosis dysregulation of the colorectal cancer TME.

NAFLDkb: A Knowledge Base and Platform for Drug Development against Nonalcoholic Fatty Liver Disease.

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease with a broad spectrum of histologic manifestations. The rapidly growing prevalence and the complex pathologic mechanisms of NAFLD pose great challenges for treatment development. Despite tremendous efforts devoted to drug development, there are no FDA-approved medicines yet. Here, we present NAFLDkb, a specialized knowledge base and platform for computer-aided drug design against NAFLD. With multiperspective information curated from diverse source materials and public databases, NAFLDkb presents the associations of drug-related entities as individual knowledge graphs. Practical drug discovery tools that facilitate the utilization and expansion of NAFLDkb have also been implemented in the web interface, including chemical structure search, drug-likeness screening, knowledge-based repositioning, and research article annotation. Moreover, case studies of a knowledge graph repositioning model and a generative neural network model are presented herein, where three repositioning drug candidates and 137 novel lead-like compounds were newly established as NAFLD pharmacotherapy options reusing data records and machine learning tools in NAFLDkb, suggesting its clinical reliability and great potential in identifying novel drug-disease associations of NAFLD and generating new insights to accelerate NAFLD drug development. NAFLDkb is freely accessible at https://www.biosino.org/nafldkb and will be updated periodically with the latest findings.

Multimodal metagenomic analysis reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer.

Microbial signatures show remarkable potentials in predicting colorectal cancer (CRC). This study aimed to evaluate the diagnostic powers of multimodal microbial signatures, multi-kingdom species, genes, and single-nucleotide variants (SNVs) for detecting precancerous adenomas. We performed cross-cohort analyses on whole metagenome sequencing data of 750 samples via xMarkerFinder to identify adenoma-associated microbial multimodal signatures. Our data revealed that fungal species outperformed species from other kingdoms with an area under the ROC curve (AUC) of 0.71 in distinguishing adenomas from controls. The microbial SNVs, including dark SNVs with synonymous mutations, displayed the strongest diagnostic capability with an AUC value of 0.89, sensitivity of 0.79, specificity of 0.85, and Matthews correlation coefficient (MCC) of 0.74. SNV biomarkers also exhibited outstanding performances in three independent validation cohorts (AUCs = 0.83, 0.82, 0.76; sensitivity = 1.0, 0.72, 0.93; specificity = 0.67, 0.81, 0.67, MCCs = 0.69, 0.83, 0.72) with high disease specificity for adenoma. In further support of the above results, functional analyses revealed more frequent inter-kingdom associations between bacteria and fungi, and abnormalities in quorum sensing, purine and butanoate metabolism in adenoma, which were validated in a newly recruited cohort via qRT-PCR. Therefore, these data extend our understanding of adenoma-associated multimodal alterations in the gut microbiome and provide a rationale of microbial SNVs for the early detection of CRC.

Associations of obesity phenotypes with weight change, cardiometabolic benefits, and type 2 diabetes incidence during a lifestyle intervention: results from the PREVIEW study.

BACKGROUND/OBJECTIVES: Some individuals with overweight/obesity may be relatively metabolically healthy (MHO) and have a lower risk of cardiovascular disease than those with metabolically unhealthy overweight/obesity (MUO). We aimed to compare changes in body weight and cardiometabolic risk factors and type 2 diabetes incidence during a lifestyle intervention between individuals with MHO vs MUO. METHODS: This post-hoc analysis included 1012 participants with MHO and 1153 participants with MUO at baseline in the randomized trial PREVIEW. Participants underwent an eight-week low-energy diet phase followed by a 148-week lifestyle-based weight-maintenance intervention. Adjusted linear mixed models and Cox proportional hazards regression models were used. RESULTS: There were no statistically significant differences in weight loss (%) between participants with MHO vs MUO over 156 weeks. At the end of the study, weight loss was 2.7% (95% CI, 1.7%-3.6%) in participants with MHO and 3.0% (2.1%-4.0%) in those with MUO. After the low-energy diet phase, participants with MHO had smaller decreases in triglyceride (mean difference between MHO vs MUO 0.08 mmol·L-1 [95% CI, 0.04-0.12]; P < 0.001) but similar reductions in fasting glucose and HOMA-IR than those with MUO. However, at the end of weight maintenance, those with MHO had greater reductions in triglyceride (mean difference -0.08 mmol·L-1 [-0.12--0.04]; P < 0.001), fasting glucose, 2-hour glucose (difference -0.28 mmol·L-1 [-0.41--0.16]; P < 0.001), and HOMA-IR than those with MUO. Participants with MHO had smaller decreases in diastolic blood pressure and HbA1c and greater decreases in HDL cholesterol after weight loss than those with MUO, whereas the statistically significant differences disappeared at the end of weight maintenance. Participants with MHO had lower 3-year type 2 diabetes incidence than those with MUO (adjusted hazard ratio 0.37 [0.20-0.66]; P < 0.001). CONCLUSIONS: Individuals with MUO had greater improvements in some cardiometabolic risk factors during the low-energy diet phase, but had smaller improvements during long-term lifestyle intervention than those with MHO.

Microbial genes outperform species and SNVs as diagnostic markers for Crohn's disease on multicohort fecal metagenomes empowered by artificial intelligence.

Dysbiosis of gut microbial community is associated with the pathogenesis of CD and may serve as a promising noninvasive diagnostic tool. We aimed to compare the performances of the microbial markers of different biological levels by conducting a multidimensional analysis on the microbial metagenomes of CD. We collected fecal metagenomic datasets generated from eight cohorts that altogether include 870 CD patients and 548 healthy controls. Microbial alterations in CD patients were assessed at multidimensional levels including species, gene, and SNV level, and then diagnostic models were constructed using artificial intelligence algorithm. A total of 227 species, 1047 microbial genes, and 21,877 microbial SNVs were identified that differed between CD and controls. The species, gene, and SNV models achieved an average AUC of 0.97, 0.95, and 0.77, respectively. Notably, the gene model exhibited superior diagnostic capability, achieving an average AUC of 0.89 and 0.91 for internal and external validations, respectively. Moreover, the gene model was specific for CD against other microbiome-related diseases. Furthermore, we found that phosphotransferase system (PTS) contributed substantially to the diagnostic capability of the gene model. The outstanding performance of PTS was mainly explained by genes celB and manY, which demonstrated high predictabilities for CD with metagenomic datasets and was validated in an independent cohort by qRT-PCR analysis. Our global metagenomic analysis unravels the multidimensional alterations of the microbial communities in CD and identifies microbial genes as robust diagnostic biomarkers across geographically and culturally distinct cohorts.

Effect of Non- and Low-Caloric Sweeteners on Substrate Oxidation, Energy Expenditure, and Catecholamines in Humans-A Systematic Review.

The use of non- and low-caloric sweetener(s) (NCS and LCS) as a means to prevent overweight and obesity is highly debated, as both NCS and LCS have been proposed to have a negative impact on energy homeostasis. This systematic review aimed to assess the impact of NCS and LCS on fasting and postprandial substrate oxidation, energy expenditure, and catecholamines, compared to caloric sweeteners or water, across different doses and types of NCS and LCS, acutely and in the longer-term. A total of 20 studies were eligible: 16 studies for substrate oxidation and energy expenditure and four studies for catecholamines. Most studies compared the acute effects of NCS or LCS with caloric sweeteners under non-isoenergetic conditions. These studies generally found higher fat oxidation and lower carbohydrate oxidation with NCS or LCS than with caloric sweeteners. Findings for energy expenditure were inconsistent. With the limited number of studies, no convincing pattern for the remaining outcomes and comparisons could be seen. In conclusion, drinks or meals with NCS or LCS resulted in higher fat and lower carbohydrate oxidation compared to caloric sweeteners. No other conclusions could be drawn due to insufficient or inconsistent results. Further studies in this research field are warranted.