Epinephelus coioides NLRP3 inhibits SGIV infection by upregulating Capspase-1 activity.

NLRP3 has an important role in the immune response and viral infection as an essential inflammasome component. However, it is unclear whether the grouper immune system is regulated by NLRP3 inflammasome. In this study, we cloned the NLRP3 gene from Epinephelus coioides. Ec-NLRP3 encodes 893 amino acids and contains two major structural domains, the NACHT domain (69-234aa) and the LRR domain (477-893aa). Tissue distribution analysis showed that Ec-NLRP3 was expressed in all tissues tested, with the spleen exhibiting the highest expression. Additionally, after being infected with SGIV, the expression of the Ec-NLRP3 gene was significantly increased. The results of subcellular localization revealed that Ec-NLRP3 was distributed throughout GS cells. In addition, Ec-NLRP3 co-localized with Ec-ASC and was observed as a cytosolic speck. Ec-NLRP3 overexpression significantly inhibited SGIV infection, which was further inhibited by co-overexpression of Ec-NLRP3 and Ec-ASC. Further studies revealed that overexpression of Ec-NLRP3 significantly upregulated caspase-1 activity, and co-overexpression of Ec-NLRP3 and Ec-ASC further upregulated caspase-1 activity. In addition, inhibition of Caspase-1 activity with VX-765 significantly increased the infection of SGIV. Furthermore, the NLRP3 inflammasome activator Nigericin was able to inhibit the infection of SGIV significantly. The above findings suggest that Ec-NLRP3 inhibits SGIV infection by upregulating caspase-1 activity.

YAP Alleviates Pulmonary Fibrosis Through Promoting Alveolar Regeneration via Modulating the Stemness of Alveolar Type 2 Cells.

Idiopathic pulmonary fibrosis (IPF) is a progressive lung disease with no cure except transplantation. Abnormal alveolar epithelial regeneration is a key driver of IPF development. The function of Yes1 Associated Transcriptional Regulator (YAP) in alveolar regeneration and IPF pathogenesis remains elusive. Here, we first revealed the activation of YAP in alveolar epithelium 2 cells (AEC2s) from human IPF lungs and fibrotic mouse lungs. Notably, conditional deletion of YAP in mouse AEC2s exacerbated bleomycin-induced pulmonary fibrosis. Intriguingly, we showed in both conditional knockout mice and alveolar organoids that YAP deficiency impaired AEC2 proliferation and differentiation into alveolar epithelium 1 cells (AEC1s). Mechanistically, YAP regulated expression levels of genes associated with cell cycle progression and AEC1 differentiation. Furthermore, overexpression of YAP in vitro promoted cell proliferation. These results indicate the critical role of YAP in alveolar regeneration and IPF pathogenesis. Our findings provide new insights into the regulation of alveolar regeneration and IPF pathogenesis, paving the road for developing novel treatment strategies.

GMMID: genetically modified mice information database.

Genetically engineered mouse models (GEMMs) are vital for elucidating gene function and disease mechanisms. An overwhelming number of GEMM lines have been generated, but endeavors to collect and organize the information of these GEMMs are seriously lagging behind. Only a few databases are developed for the information of current GEMMs, and these databases lack biological descriptions of allele compositions, which poses a challenge for nonexperts in mouse genetics to interpret the genetic information of these mice. Moreover, these databases usually do not provide information on human diseases related to the GEMM, which hinders the dissemination of the insights the GEMM provides as a human disease model. To address these issues, we developed an algorithm to annotate all the allele compositions that have been reported with Python programming and have developed the genetically modified mice information database (GMMID; http://www.gmmid.cn), a user-friendly database that integrates information on GEMMs and related diseases from various databases, including National Center for Biotechnology Information, Mouse Genome Informatics, Online Mendelian Inheritance in Man, International Mouse Phenotyping Consortium, and Jax lab. GMMID provides comprehensive genetic information on >70 055 alleles, 65 520 allele compositions, and ∼4000 diseases, along with biologically meaningful descriptions of alleles and allele combinations. Furthermore, it provides spatiotemporal visualization of anatomical tissues mentioned in these descriptions, shown alongside the allele compositions. Compared to existing mouse databases, GMMID considers the needs of researchers across different disciplines and presents obscure genetic information in an intuitive and easy-to-understand format. It facilitates users in obtaining complete genetic information more efficiently, making it an essential resource for cross-disciplinary researchers. Database URL: http://www.gmmid.cn.

Identification and prediction of frailty among community-dwelling older Japanese adults based on Bayesian network analysis: a cross-sectional and longitudinal study.

BACKGROUND: Frailty is a multifactorial syndrome; through this study, we aimed to investigate the physiological, psychological, and social factors associated with frailty and frailty worsening in community-dwelling older adults. METHODS: We conducted a cross-sectional and longitudinal study using data from the "Community Empowerment and Well-Being and Healthy Long-term Care: Evidence from a Cohort Study (CEC)," which focuses on community dwellers aged 65 and above in Japan. The sample of the cross-sectional study was drawn from a CEC study conducted in 2014 with a total of 673 participants. After excluding those who were frail during the baseline assessment (2014) and at the 3-year follow-up (2017), the study included 373 participants. Frailty assessment was extracted from the Kihon Checklist, while social relationships were assessed using the Social Interaction Index (ISI). Variable selection was performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression and their predictive abilities were tested. Factors associated with frailty status and worsening were identified through the Maximum-min Hillclimb algorithm applied to Bayesian networks (BNs). RESULTS: At baseline, 14.1% (95 out of 673) participants were frail, and 24.1% (90 out of 373) participants experienced frailty worsening at the 3-years follow up. LASSO regression identified key variables for frailty. For frailty identification (cross-sectional), the LASSO model's AUC was 0.943 (95%CI 0.913-0.974), indicating good discrimination, with Hosmer-Lemeshow (H-L) test p = 0.395. For frailty worsening (longitudinal), the LASSO model's AUC was 0.722 (95%CI 0.656-0.788), indicating moderate discrimination, with H-L test p = 0.26. The BNs found that age, multimorbidity, function status, and social relationships were parent nodes directly related to frailty. It revealed an 85% probability of frailty in individuals aged 75 or older with physical dysfunction, polypharmacy, and low ISI scores; however, if their social relationships and polypharmacy status improve, the probability reduces to 50.0%. In the longitudinal-level frailty worsening model, a 75% probability of frailty worsening in individuals aged 75 or older with declined physical function and ISI scores was noted; however, if physical function and ISI improve, the probability decreases to 25.0%. CONCLUSION: Frailty and its progression are prevalent among community-dwelling older adults and are influenced by various factors, including age, physical function, and social relationships. BNs facilitate the identification of interrelationships among these variables, quantify the influence of key factors. However, further research is required to validate the proposed model.

Integrating serum pharmacochemistry, network pharmacology and untargeted metabolomics strategies to reveal the material basis and mechanism of action of Feining keli in the treatment of chronic bronchitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Feining keli (FNKL) is herbal preparation mainly made from Senecio cannabifolius Less., In recent years, more and more studies have found that FNKL has excellent therapeutic effects on chronic bronchitis (CB). Nevertheless, its pharmacodynamic material basis and mechanism of action are still unknown. AIM OF THE STUDY: This study aimed to explore the pharmacodynamic material basis and mechanism of action of FNKL in treating CB. MATERIALS AND METHODS: The CB rat model was induced using nasal drops of lipopolysaccharide (LPS) in combination with smoking. Various assessments including behavioral and body mass examination, lung index measurement, enzyme linked immunosorbent assay (ELISA), as well as histological analyses using hematoxylin and eosin (H&E) and Masson staining were conducted to validate the reliability of the CB model. The serum components of FNKL in CB rats were identified using ultra-high-performance liquid chromatography Orbitrap Exploris mass spectrometer (UHPLC-OE-MS). Network pharmacology was used to predict the network of action of the active ingredients in FNKL based on these serum components. Signaling pathways were enriched and analyzed, and molecular docking was conducted for key targets. Molecular dynamics simulations were performed using GROMACS software. The mechanism was confirmed through a series of experiments including Western blot (WB), immunofluorescence (IF), and reverse transcription (RT)-PCR. Additionally, untargeted metabolomics was employed to identify biomarkers and relevant metabolic pathways associated with the treatment of CB with FNKL. RESULTS: In CB rats, FNKL improved body mass, lung index, and pathological damage of lung tissues. It also decreased interleukin (IL)-6, tumor necrosis factor-alpha (TNF-α), malonaldehyde (MDA) levels, and percentage of lung collagen fiber area. Furthermore, FNKL increased IL-10 and superoxide dismutase (SOD) levels, which helped alleviate bronchial inflammation in the lungs. A total of 70 FNKL chemical components were identified in CB rat serum. Through network pharmacology analysis, 5 targets, such as PI3K, AKT, NF-κB, HIF-1α, and MYD88, were identified as key targets of FNKL in the treatment of CB. Additionally, the key signaling pathways identified were PI3K/AKT pathway、NF-κB/MyD88 pathway、HIF-1α pathway. WB, IF, and RT-PCR experiments were conducted to confirm the findings. Molecular docking studies demonstrated successful docking of 16 potential active components with 5 key targets. Additionally, molecular dynamics simulations indicated the stability of quercetin-3-galactoside and HIF-1α. Metabolomics analysis revealed that FNKL primarily regulated pathways related to alpha-linolenic acid metabolism, primary bile acid biosynthesis, bile secretion, arachidonic acid metabolism, neuroactive ligand-receptor interaction, and folate biosynthesis. Furthermore, the expression levels of traumatic acid, traumatin, alpha linolenic acid, cholic acid, 2-arachidonoylglycerol, deoxycholic acid, 7,8-dihydroneopterin, and other metabolites were found to be regulated. CONCLUSION: FNKL exhibits positive therapeutic effects on CB, with quercetin-3-galactoside identified as a key active component. The mechanism of FNKL's therapeutic action on CB involves reducing inflammatory response, oxidative stress, and regulating metabolism, and its molecular mechanism was better elucidated in a holistic manner. This study serves as a reference for understanding the pharmacodynamic material basis and mechanism of action of FNKL in treating CB, and provides avenues for exploring the effects of compounded herbal medicines on CB.

Acupuncture as adjunctive treatment for linezolid-induced peripheral neuropathy: a case series report.

Background: The treatment of multidrug-resistant tuberculosis (MDR-TB) and pre-extensively drug-resistant tuberculosis (pre-XDR-TB) remains challenging due to the limited availability of effective drugs. Linezolid has emerged as a promising therapeutic option for these cases. However, its long-term use can lead to complications such as peripheral and optic neuropathies. Acupuncture, a cornerstone of traditional Chinese medicine, has been shown to be effective in the treatment of peripheral neuropathy (PN). This study examines the potential benefits of acupuncture in the treatment of linezolid-induced peripheral neuropathy (LIPN). Methods: Four patients, aged 27 to 60 years, diagnosed with LIPN, underwent daily acupuncture treatments. The main endpoint was to assess the efficacy of acupuncture in reducing neuropathic pain associated with LIPN in patients. This was primarily measured using changes in the Short Form McGill Pain Questionnaire (SF-MPQ) scores before and after acupuncture treatment. Results: Three of the patients experienced significant symptom remission, while one experienced marginal improvement. Treatments ranged from 7 to 18 sessions. Specifically, the first patient reported substantial relief with a score reduction from 33 to 13; the second patient observed minimal change; the third patient's score decreased dramatically from 10 to 2 after eight sessions; the last patient had a score reduction from 21 to 12 after five sessions, but did not continue treatment for a second assessment. Conclusion: Acupuncture is a promising therapeutic approach for LIPN. However, larger and more thorough studies are needed to determine its full potential.

Current status and prospect of the DNA double-strand break repair pathway in colorectal cancer development and treatment.

Colorectal cancer (CRC) is one of the most common malignancies worldwide. Double-strand break (DSB) is the most severe type of DNA damage. However, few reviews have thoroughly examined the involvement of DSB in CRC. Latest researches demonstrated that DSB repair plays an important role in CRC. For example, DSB-related genes such as BRCA1, Ku-70 and DNA polymerase theta (POLQ) are associated with the occurrence of CRC, and POLQ even showed to affect the prognosis and resistance for radiotherapy in CRC. This review comprehensively summarizes the DSB role in CRC, explores the mechanisms and discusses the association with CRC treatment. Four pathways for DSB have been demonstrated. 1. Nonhomologous end joining (NHEJ) is the major pathway. Its core genes including Ku70 and Ku80 bind to broken ends and recruit repair factors to form a complex that mediates the connection of DNA breaks. 2. Homologous recombination (HR) is another important pathway. Its key genes including BRCA1 and BRCA2 are involved in finding, pairing, and joining broken ends, and ensure the restoration of breaks in a normal double-stranded DNA structure. 3. Single-strand annealing (SSA) pathway, and 4. POLθ-mediated end-joining (alt-EJ) is a backup pathway. This paper elucidates roles of the DSB repair pathways in CRC, which could contribute to the development of potential new treatment approaches and provide new opportunities for CRC treatment and more individualized treatment options based on therapeutic strategies targeting these DNA repair pathways.

Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.

Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we combined metabolomics and machine learning (ML) to develop a generalized future liver remnant assessment model for multiple liver backgrounds. The liver index was calculated at 0, 6, 24, 48, 72 and 168 h after 70 % PH in healthy mice and mice with nonalcoholic steatohepatitis or liver fibrosis. The serum levels of 39 amino acids (AAs) were measured using UPLC-MS/MS. The dataset was randomly divided into training and testing sets at a 2:1 ratio, and orthogonal partial least squares regression (OPLS) and minimally biased variable selection in R (MUVR) were used to select a metabolite signature of AAs. To assess liver remnant growth, nine ML models were built, and evaluated using the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). The post-Pareto technique for order preference by similarity to the ideal solution (TOPSIS) was employed for ranking the ML algorithms, and a stacking technique was utilized to establish consensus among the superior algorithms. Compared with those of OPLS, the signature AAs set identified by MUVR (Thr, Arg, EtN, Phe, Asa, 3MHis, Abu, Asp, Tyr, Leu, Ser, and bAib) are more concise. Post-Pareto TOPSIS ranking demonstrated that the majority of ML algorithm in combinations with MUVR outperformed those with OPLS. The established SVM-KNN consensus model performed best, with an R2 of 0.79, an MAE of 0.0029, and an RMSE of 0.0035 for the testing set. This study identified a metabolite signature of 12 AAs and constructed an SVM-KNN consensus model to assess future liver remnant growth after PH in mice with different liver backgrounds. Our preclinical study is anticipated to establish an alternative and generalized assessment method for liver regeneration.

Functions and Clinical Significance of Myocardial Cell-Derived Immunoglobulins.

Immunoglobulins (Igs) have been widely accepted to be exclusively expressed by B cells. Nonetheless, this theory is challenged by mounting evidence which suggests that Igs can also be generated by non B cells (non B-Ig), including cardiomyocytes (CM). Non B-Ig exhibits unique physical and chemical characteristics, unique variable region sequences and functions, which diverge from those of B-Ig. For instance, non B-Ig demonstrates hydrophobicity, limited diversity in the variable region, and extracellular matrix protein activity. Likewise, cardiomyocytes can express different classes of Igs, including IgM, IgG, and free Igκ light chains (cardiomyocyte derived-Igs, CM-Igs). In particular, CM-Igs can be secreted into the extracellular space in various cardiovascular diseases, such as myocardial ischaemia and myocardial fibrosis where they might be involved in complement activation and direct damage to cardiomyocytes. Nevertheless, the precise pathological activity of CM-Igs remains unclear. Recently, Zhu et al. focused on studying the sequence characteristics and functions of CM-Igκ; they discovered that the CM-Igκ exhibits a unique VJ recombination pattern, high hydrophobicity, and is principally located on the intercalated discs and cross striations of the cardiomyocytes. Interestingly, loss of Igκ in cardiomyocytes results in structural disorders in intercalated discs and dysfunction in myocardial contraction and conduction. Mechanically, Igκ promotes the stabilisation of plectin, a cytoskeleton cross-linker protein that connects desmin to desomsome, to maintain the normal structure of the intercalated disc. This finding indicates that CM-Igκ plays an integral role in maintaining cytoskeleton structure. Consequently, it is imperative to reveal the physiological functions and mechanisms of pathological injury associated with CM-Igs.

GWAS-based polygenic risk scoring for predicting cerebral artery dissection in the Chinese population.

OBJECTIVE: Cerebral artery dissection (CeAD) is a rare but serious disease. Genetic risk assessment for CeAD is lacking in Chinese population. We performed genome-wide association study (GWAS) and computed polygenic risk score (PRS) to explore genetic susceptibility factors and prediction model of CeAD based on patients in Huashan Hospital. METHODS: A total of 210 CeAD patients and 280 controls were enrolled from June 2017 to September 2022 in Department of Neurology, Huashan Hospital, Fudan University. We performed GWAS to identify genetic variants associated with CeAD in 140 CeAD patients and 210 control individuals according to a case and control 1:1.5 design rule in the training dataset, while the other 70 patients with CeAD and 70 controls were used as validation. Then Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses were utilized to identify the significant pathways. We constructed a PRS by capturing all independent GWAS SNPs in the analysis and explored the predictivity of PRS, age, and sex for CeAD. RESULTS: Through GWAS analysis of the 140 cases and 210 controls in the training dataset, we identified 13 leading SNPs associated with CeAD at a genome-wide significance level of P < 5 × 10- 8. Among them, 10 SNPs were annotated in or near (in the upstream and downstream regions of ± 500Kb) 10 functional genes. rs34508376 (OR2L13) played a suggestive role in CeAD pathophysiology which was in line with previous observations in aortic aneurysms. The other nine genes were first-time associations in CeAD cases. GO enrichment analyses showed that these 10 genes have known roles in 20 important GO terms clustered into two groups: (1) cellular biological processes (BP); (2) molecular function (MF). We used genome-wide association data to compute PRS including 32 independent SNPs and constructed predictive model for CeAD by using age, sex and PRS as predictors both in training and validation test. The area under curve (AUC) of PRS predictive model for CeAD reached 99% and 95% in the training test and validation test respectively, which were significantly larger than the age and sex models of 83% and 86%. CONCLUSIONS: Our study showed that ten risk loci were associated with CeAD susceptibility, and annotated functional genes had roles in 20 important GO terms clustered into biological process and molecular function. The PRS derived from risk variants was associated with CeAD incidence after adjusting for age and sex both in training test and validation.

Biotransformation of Ginsenoside Rb1 to Ginsenoside Rd and 7 Rare Ginsenosides Using Irpex lacteus with HPLC-HRMS/MS Identification.

The biotransformation of ginsenosides using microorganisms represents a promising and ecofriendly approach for the production of rare ginsenosides. The present study reports on the biotransformation of ginsenoside Rb1 using the fungus Irpex lacteus, resulting in the production of ginsenoside Rd and seven rare ginsenosides with novel structures. Employing high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry, the identities of the transformation products were rapidly determined. Two sets of isomers with molecular weights of 980.56 and 962.55 were discovered among the seven rare ginsenosides, which were generated through the isomerization of the olefin chain in the protopanaxadiol (PPD)-type ginsenoside skeleton. Each isomer exhibited characteristic fragment ions and neutral loss patterns in their tandem mass spectra, providing evidence of their unique structures. Time-course experiments demonstrated that the transformation reaction reached equilibrium after 14 days, with Rb1 initially generating Rd and compound 5, followed by the formation of other rare ginsenosides. The biotransformation process catalyzed by I. lacteus was found to involve not only the typical deglycosylation reaction at the C-20 position but also hydroxylation at the C-22 and C-23 positions, as well as hydrogenation, transfer, and cyclization of the double bond at the C-24(25) position. These enzymatic capabilities extend to the structural modification of other PPD-type ginsenosides such as Rc and Rd, revealing the potential of I. lacteus for the production of a wider range of rare ginsenosides. The transformation activities observed in I. lacteus are unprecedented among fungal biotransformations of ginsenosides. This study highlights the application of a medicinal fungi-based biotransformation strategy for the generation of rare ginsenosides with enhanced structural diversity, thereby expanding the variety of bioactive compounds derived from ginseng.

Dyadic effects of financial toxicity and social support on the fear of cancer recurrence in breast cancer patients and caregivers: an actor-partner interdependence mediation model.

PURPOSE: In this study, the actor-partner interdependence mediation model (APIMeM) was applied to breast cancer patients and their caregivers to assess the factors that affect the fear of cancer recurrence. In particular, the purpose of this study was to evaluate the mediating effect of social support on financial toxicity and the fear of cancer recurrence, providing an effective basis for developing plans to reduce the level of fear of cancer recurrence. METHODS: This study employed a cross-sectional design, and 405 dyads of breast cancer patients and their caregivers were enrolled. Financial toxicity, social support, and fear of cancer recurrence were assessed by computing comprehensive scores for financial toxicity based on patient-reported outcome measures, the Social Support Rating Scale, and the Fear of Cancer Recurrence Inventory Short Form, respectively. The data were analysed using SPSS 24.0 and AMOS 23.0. RESULTS: The results showed that the fear of cancer recurrence of breast cancer patients and their caregivers was significantly related to dyadic financial toxicity and social support. In addition, the financial toxicity of breast cancer patients and their caregivers had significant actor effects and partner effects on the fear of cancer recurrence through dyadic social support. CONCLUSIONS: The financial toxicity of breast cancer patients and their caregivers could produce actor and partner effects on the fear of cancer recurrence through the mediation of social support, which provided empirical support for improving reducing the level of fear of cancer recurrence among patients and caregivers at the dyadic level.

Revealing the Molecular Mechanism of Sageretia theezans in the Treatment of Hemorrhoids based on Network Pharmacology.

OBJECTIVE: Sageretia theezans is one of the classic medicines in ancient times, which is commonly used to treat scabies, lacquer sores, acute and chronic pharyngitis, Tonsillitis, Cholecystitis, secondary infection of hemorrhoids, and other symptoms. However, the potential molecular mechanism of Sageretia theezans is still unclear. In this study, we explored the active compounds of Sageretia theezans in the treatment of hemorrhoids (HD), predicted the potential targets of drugs, and verified their functions through network pharmacology and in vivo and in vitro experiments. METHODS: First, we identified the active compounds and key targets of Sageretia theezans in treating HD through network pharmacology. The key signaling pathways related to the role of Sageretia theezans were analyzed. HUVEC Human umbilical vein endothelial cells were used to study the function of Sageretia theezans and its target in vitro. In addition, we also used the SD rat hemorrhoid model to explore the efficacy of Sageretia theezans in HD in vivo. RESULT: A total of 159 drug targets were obtained from the TCMSP, ETCM, and PubChem databases. Constructing a drug component target network; differential analysis using sequencing data identified 1046 differentially expressed genes. Intersecting drug targets and differentially expressed genes obtained four intersection targets (GOT1, SLC25A10, SUCLG1, CLEC4E). Perform single gene GSEA functional enrichment analysis on intersection targets, select KEGG and GO of the top 10 for display, and merge the results. In order to investigate the interaction between intersecting genes and differentially expressed genes, we conducted a PPI protein interaction analysis on 1046 differentially expressed genes. Finally, a network of Chinese medicine active molecule intersection genes was proposed, and the genes and their corresponding active molecules (Successful acid, Taraxerone, Taraxerol) were Macromolecular docking, respectively. The results showed that these four genes could be successfully docked with the responsive active molecules and had high binding affinity. In vivo, the low-dose treatment group of Sageretia theezans, the medium-dose treatment group of Sageretia theezans, and the high-dose treatment group of Bromelia can inhibit the proliferation of HUVECs cells. In vitro, the middle dose of Sageretia theezans has the best therapeutic effect on hemorrhoids, and the treatment of Sageretia theezans on hemorrhoids is correlated with the expression of GOT1, SLC25A10, SUCLG1, and CLEC4E. CONCLUSION: To sum up, Sageretia theezans can alleviate the symptoms of hemorrhoids and is related to the expression of GOT1, SLC25A10, SUCLG1, and CLEC4E.

Amino acid metabolomics and machine learning for assessment of post-hepatectomy liver regeneration.

Objective: Amino acid (AA) metabolism plays a vital role in liver regeneration. However, its measuring utility for post-hepatectomy liver regeneration under different conditions remains unclear. We aimed to combine machine learning (ML) models with AA metabolomics to assess liver regeneration in health and non-alcoholic steatohepatitis (NASH). Methods: The liver index (liver weight/body weight) was calculated following 70% hepatectomy in healthy and NASH mice. The serum levels of 39 amino acids were measured using ultra-high performance liquid chromatography-tandem mass spectrometry analysis. We used orthogonal partial least squares discriminant analysis to determine differential AAs and disturbed metabolic pathways during liver regeneration. The SHapley Additive exPlanations algorithm was performed to identify potential AA signatures, and five ML models including least absolute shrinkage and selection operator, random forest, K-nearest neighbor (KNN), support vector regression, and extreme gradient boosting were utilized to assess the liver index. Results: Eleven and twenty-two differential AAs were identified in the healthy and NASH groups, respectively. Among these metabolites, arginine and proline metabolism were commonly disturbed metabolic pathways related to liver regeneration in both groups. Five AA signatures were identified, including hydroxylysine, L-serine, 3-methylhistidine, L-tyrosine, and homocitrulline in healthy group, and L-arginine, 2-aminobutyric acid, sarcosine, beta-alanine, and L-cysteine in NASH group. The KNN model demonstrated the best evaluation performance with mean absolute error, root mean square error, and coefficient of determination values of 0.0037, 0.0047, 0.79 and 0.0028, 0.0034, 0.71 for the healthy and NASH groups, respectively. Conclusion: The KNN model based on five AA signatures performed best, which suggests that it may be a valuable tool for assessing post-hepatectomy liver regeneration in health and NASH.

A transparent p-coumaric acid-grafted-chitosan coating with antimicrobial, antioxidant and antifogging properties for fruit packaging applications.

The study aimed to develop a novel, transparent and non-toxic coating with antimicrobial, antioxidant, and antifogging properties. The p-coumaric acid-grafted chitosan (CS-PCA) was synthesized via a carbodiimide coupling reaction and then characterized. The CS-PCA coatings were further prepared using the casting method. The CS-PCA coatings obtained exhibited excellent transparency, UV-light barrier ability, and antifogging properties, as confirmed by spectroscopy and antifogging tests. The CS-PCA coatings showed stronger antioxidant capacity and antimicrobial properties against Escherichia coli, Staphylococcus aureus and Botrytis cinerea compared to CS. The multifunctional coatings were further coated on the polyethylene cling film and their effectiveness was confirmed through a strawberry preservation test. The decay of the strawberries was reduced by CS-PCA coated film at room temperature.

The toxic effects induced by benzethonium chloride on Daphnia carinata over two generations: Resistance and higher sublethal toxicity.

With the widespread utilization of the sanitizing product benzethonium chloride (BEC) throughout the coronavirus pandemic, concerns have emerged regarding its potential hazards. Nevertheless, the long-term and multigenerational toxic effects of BEC on aquatic organisms remains unexplored. This study investigates acute and chronic toxicity, oxidative stress, mitochondrial membrane potential, ATP concentrations, and gene expression using Daphnia carinata as the model organism. Meanwhile, hierarchical clustering analysis was utilized to investigate phenotypic effects among different treatment groups. The integrated biomarker response index version 2 (IBRv2) was employed to estimate the deviation in toxic effects over two generations. These results indicated that D. carinata in the second generation exhibited higher survival rate and lower levels of oxidative stress than the first generation. However, the higher sublethal effects were found in the second generation as follows, the weakened growth performance, mitochondrial membrane potential depolarization, reduced ATP concentrations, and down-regulated gene expression. The mitochondrial toxicity induced by BEC may account for the distinct toxic effects exhibited in two generations. The findings here can assist with the evaluation of potential risk for BEC on aquatic organisms, and provide new insight into the cross-generational toxicity mechanisms of pollutants in aquatic ecosystems.

Comprehensive Evaluation of the Physicochemical Attributes, Antioxidant Capacity, and pH-Responsive Behavior of Starch Films Enhanced by Laver Incorporation.

Herein, a new starch film incorporating laver was developed to address issues related to inadequate water resistance and suboptimal preservation quality in food packaging. The integration of laver into starch film formulations offers a compelling avenue for creating biodegradable, active, and smart food packaging. Scanning electron microscope (SEM) analysis revealed that the starch film with a laver concentration of 70% exhibited a uniformly flat microstructure, as expected. Fourier-transform infrared spectroscopy (FTIR) confirmed the presence of intermolecular interactions and hydrogen bonding between the starch and laver. Viscoelastic tests demonstrated the superior film-forming performance of the starch/laver composite films. Moreover, it was found that the most favorable concentration of incorporated laver was 10%. Specifically, the S7-3 film emerged as a promising candidate for food packaging applications, boasting the highest contact angle (CA) value of 114.98 ± 1.28°, the lowest water solubility (WS) value of 15.38%, and a reduced water vapor transmission rate (WVTR) value of 2.52 g/m2 × h. Additionally, the S3-7 film displayed an extraordinary tensile strength of 32.47 MPa, an elongation at break of 19.04%, and a Young's modulus of 606.83 MPa. Furthermore, the starch/laver composite films exhibited outstanding UV-blocking capabilities, exceptional pH-responsive behavior, and significant antioxidant activity, underscoring their potential for packaging applications with laver integration.

Online interpretable dynamic prediction models for clinically significant posthepatectomy liver failure based on machine learning algorithms: A retrospective cohort study.

BACKGROUND: Posthepatectomy liver failure (PHLF) is the leading cause of mortality in patients undergoing hepatectomy. However, practical models for accurately predicting the risk of PHLF are lacking. This study aimed to develop precise prediction models for clinically significant PHLF. METHODS: A total of 226 patients undergoing hepatectomy at a single center were recruited. The study outcome was clinically significant PHLF. Five pre- and postoperative machine learning (ML) models were developed and compared with four clinical scores, namely, the MELD, FIB-4, ALBI, and APRI scores. The robustness of the developed ML models was internally validated using 5-fold cross-validation by calculating the average of the evaluation metrics and was externally validated on an independent temporal dataset, including the area under the curve (AUC) and the area under the precision‒recall curve (AUPRC). SHapley Additive exPlanations analysis was performed to interpret the best performance model. RESULTS: Clinically significant PHLF was observed in 23 of 226 patients (10.2%). The variables in the preoperative model included creatinine, total bilirubin, and Child‒Pugh grade. In addition to the above factors, the extent of resection was also a key variable for the postoperative model. The pre- and postoperative artificial neural network (ANN) models exhibited excellent performance, with mean AUCs of 0.766 and 0.851, respectively, and mean AUPRC values of 0.441 and 0.645, whereas the MELD, FIB-4, ALBI, and APRI scores reached AUCs of 0.714, 0.498, 0.536 and 0.551, respectively, and AUPRC values of 0.204, 0.111, 0.128 and 0.163, respectively. In addition, the AUCs of the pre- and postoperative ANN models were 0.720 and 0.731, respectively, and the AUPRC values were 0.380 and 0.408, respectively, on the temporal dataset. CONCLUSION: Our online interpretable dynamic ML models outperformed common clinical scores and could function as a clinical decision support tool to identify patients at high risk of PHLF pre- and postoperatively.

The chromatin landscape of pathogenic transcriptional cell states in rheumatoid arthritis.

Synovial tissue inflammation is a hallmark of rheumatoid arthritis (RA). Recent work has identified prominent pathogenic cell states in inflamed RA synovial tissue, such as T peripheral helper cells; however, the epigenetic regulation of these states has yet to be defined. Here, we examine genome-wide open chromatin at single-cell resolution in 30 synovial tissue samples, including 12 samples with transcriptional data in multimodal experiments. We identify 24 chromatin classes and predict their associated transcription factors, including a CD8 + GZMK+ class associated with EOMES and a lining fibroblast class associated with AP-1. By integrating with an RA tissue transcriptional atlas, we propose that these chromatin classes represent 'superstates' corresponding to multiple transcriptional cell states. Finally, we demonstrate the utility of this RA tissue chromatin atlas through the associations between disease phenotypes and chromatin class abundance, as well as the nomination of classes mediating the effects of putatively causal RA genetic variants.

Cloning and characterization of a novel mesophilic xylanase gene Fgxyn3 from Fusarium graminearum Z-1.

In order to search for high specific activity and the resistant xylanases to XIP-I and provide more alternative xylanases for industrial production, a strain of Fusarium graminearum from Triticum aestivum grains infected with filamentous fungus produced xylanases was isolated and identified. Three xylanase genes from Fusarium graminearum Z-1 were cloned and successfully expressed in E. coli and P. pastoris, respectively. The specific activities of Fgxyn1, EFgxyn2 and EFgxyn3 for birchwood xylan were 38.79, 0.85 and 243.83 U/mg in E. coli, and 40.11, 0 and 910.37 U/mg in P. pastoris, respectively. EFgxyn3 and PFgxyn3 had the similar optimum pH at 6.0 and pH stability at 5.0-9.0. However, they had different optimum temperature and thermal stability, with 30 °C for EFgxyn3 and 40 °C for PFgxyn3, and 4-35 °C for EFgxyn3 and 4-40 °C for PFgxyn3, respectively. The substrate spectrum and the kinetic parameters showed that the two xylanases also exhibited the highest xylanase activity and catalytic efficiency (kcat/km) toward birchwood xylan, with 243.83 U/mg and 61.44 mL/mg/s for EFgxyn3 and 910.37 U/mg and 910.37 mL/mg/s for PFgxyn3, respectively. This study provided a novel mesophilic xylanase with high specific activity and catalytic efficiency, thus making it a promising candidate for extensive applications in animal feed and food industry. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-024-03973-0.