Metabolic associated fatty liver disease (MAFLD) is fundamentally driven by an imbalance in hepatic fatty-acid flux: the influx of fatty acids exceeds the liver’s capacity for disposal, resulting in excessive hepatic lipid accumulation, predominantly in the form of triglycerides (TGs). The occurrence and progression of MAFLD depend on disordered regulation across multiple metabolic steps, including fatty-acid uptake, de novo lipogenesis (DNL), fatty-acid oxidation (FAO), and very low-density lipoprotein (VLDL) export. Forkhead box protein O1 (FOXO1) is a key transcriptional regulator within the hepatic network coordinating glucose and lipid metabolism. Under metabolic stress and insulin resistance (IR), FOXO1 expression is frequently increased, whereas its inhibitory phosphorylation is reduced. These changes enhance FOXO1 nuclear localization and transcriptional activity, thereby reprogramming the expression of genes related to metabolism in the liver. Because hepatic lipid deposition is the central pathological feature of MAFLD, the functional status of FOXO1 directly influences hepatic lipid homeostasis. Growing evidence suggests that FOXO1 can exert bidirectional, environment-dependent effects on hepatic lipid accumulation; however, the molecular basis for this functional switch remains incompletely understood. This review systematically summarizes the biological functions and regulatory mechanisms of FOXO1 and its roles in hepatic lipid metabolism, with a particular focus on its crosstalk with insulin signaling. FOXO1 expression is shaped by RNA modifications and epigenetic regulation mediated by non-coding RNAs. Its transcriptional output is precisely governed by post-translational modifications—such as phosphorylation and acetylation—as well as by coordinated nucleocytoplasmic shuttling. Notably, these regulatory patterns vary markedly across nutritional states, degrees of insulin resistance, and stages of disease. In the fed state, insulin/IGF-1 signaling activates the PI3K-AKT pathway, promoting the inhibitory phosphorylation of FOXO1 and facilitating additional modifications, including acetylation, methylation, and ubiquitination. Together, these events drive FOXO1 export from the nucleus and dampen its transcriptional activity, suppressing gluconeogenesis and constraining lipogenic programs. Conversely, during fasting or when insulin signaling is weakened, FOXO1 inhibition is relieved. FOXO1 accumulates in the nucleus, binds to DNA, and regulates the transcription of downstream target genes. Mechanistically, FOXO1 can aggravate hepatic lipid accumulation by activating genes involved in TG synthesis while repressing FAO-related pathways, thereby favoring storage over oxidation. However, under specific conditions, FOXO1 may also alleviate the hepatic lipid burden by promoting TG hydrolysis and enhancing VLDL secretion, thereby reducing the net hepatic lipid load. In addition, lipotoxic signals mediated by ceramides and diacylglycerols (Cer/DAG) activate atypical protein kinase C (aPKC), further exacerbating the disruption of the AKT-FOXO1 axis. This vicious cycle ultimately produces a metabolic paradox in which increased hepatic glucose output coexists with persistent, insulin-independent lipogenesis, accelerating MAFLD progression. Importantly, FOXO1 regulation is not uniform: during early metabolic overload, insulin-mediated suppression may remain effective, whereas in advanced insulin resistance, the loss of AKT control permits sustained FOXO1 activity. Such stage-dependent dynamics may help explain why FOXO1 can either promote steatosis or, in certain contexts, support programs that facilitate lipid turnover. Accordingly, interventions should be liver-specific and tuned to the disease stage, aiming to curb maladaptive FOXO1 signaling while preserving its capacity to promote triglyceride hydrolysis and VLDL secretion when advantageous. Overall, this review offers an important perspective on MAFLD pathogenesis, emphasizing FOXO1 as a potential therapeutic target and providing a theoretical basis for developing liver-specific, disease-course-dependent precision interventions.

ObjectiveDonkey hide is the sole legally designated raw material for the preparation of the traditional Chinese medicine Ejiao. The quality stability of donkey hide during preservation directly determines the efficacy and safety of Ejiao. This study focuses on the dynamic succession of microbial communities during the preservation of donkey hides from different origins, aiming to clarify the correlation between microbial biodiversity difference and the degradation profiles of hide collagen and critical biochemical components, thereby providing a theoretical foundation for developing targeted preservation strategies based on microbial regulation. MethodsDonkey hides originating from four different regions were subjected to an accelerated microbial aging assay to simulate the spoilage process. The microbial community succession was analyzed using high-throughput sequencing. Microstructure changes and pore structure characteristics were assessed by scanning electron microscopy and mercury intrusion porosimetry, respectively. Additionally, the content of major components, including lipids, proteins, and sugars were determined by biochemical methods. ResultsAfter 96 h of aging, the collagen fiber structure in Africa donkey hides (ADH) exhibited significant degradation and collapse, followed by Xinjiang donkey hides (XDH). Instead, the microstructure of Dong’e black donkey hides (DDH) and Peru donkey hides (PDH) remained relatively intact. The porosities of DDH, XDH, PDH, and ADH increased from 27.9%, 15.7%, 30.3%, and 46.2% to 36.5%, 52.6%, 42.8%, and 57.7%, respectively, during the aging process, which suggested that the originally compact fiber structure was disrupted by microbial aging. Fourier transform infrared spectrometer analysis revealed the amide bands in XDH exhibited relatively weak intensity, and no collagen amide I band was observed in ADH. Meanwhile, the lipid and protein contents decreased in all four types of donkey hides, indicating that these components served as the primary nutrient sources for the growth of microorganism. Notably, the most severe collagen degradation was observed in XDH and ADH. A substantial increase was detected in the total soluble sugar in PDH aging solution and hydroxyproline in the ADH aging solution, respectively. These results indicated that donkey hides exhibit distinct patterns of structural degradation and nutrient utilization. Furthermore, the viable cells number of donkey hides increased sharply after 48 h of aging. Metagenomic analysis revealed that the relative abundance of Euryarchaeota in ADH, PDH and XDH declining from initial 93.19%, 97.73% and 30.08% to 0.79%, 1.43% and 0.02% after 96 h, respectively. Conversely, a significantly increase was observed in the abundance of Bacillota, with a marked increase in ADH, peaking at 92.75%. Additionally, the abundance of Pseudomonadota in PDH increased from 0.10% to 87.84%, suggesting that Bacillota and Pseudomonadota may be key factors exacerbating donkey hide spoilage. Unlike the other three types of donkey hides, the dominant bacterial phylum in DDH shifted from Pseudomonadota to Bacteroidota, characterized by a substantial abundance increase of Bacteroidota from 0.13% to 44.22%. ConclusionRegional variation in origin significantly influence the microbial aging of donkey hides, leading to distinct patterns of structural deterioration and differential nutrient utilization. Therefore, implementing origin-specific preservation strategies, through the precisely controlling environmental factors to suppress harmful phyla such as Bacillota and Pseudomonadota, is crucial for enhancing the storage quality of donkey hides.

This study assessed the role and mechanism of the recombinant Bacillus Calmette-Gue?rin vaccine(rBCG)with c-di-AMP adjuvant in regulating metabolism and immunity in epididymal white adipose(eWAT)in mice.Male C57BL/6 mice were intravenously immunized with BCG and rBCG,and their body weights were monitored.eWAT was isolated from the mice,and the stromal vascular fractions(SVFs)cell number was counted with a hemocytometer.Sections of mouse adipose tissue were prepared,and the size,number,and morphology of eWAT adipocytes and crown-like structure(CLS)formation were compared under a microscope after HE staining.The transcription levels of lipid metabolism-associated factors,cytokines and aging-associated genes in each group were determined with qRT-PCR.The body weights of mice gradually increased after immunization with BCG and rBCG.The proportions of eWAT increased,and the SVFs cell number decreased,in rBCG immunized mice.HE staining indicated that BCG immunization promoted hyperplasia,whereas rBCG immunization promoted hypertrophy of eWAT adipocytes;moreover,both BCG and rBCG immunization induced CLS formation in eWAT.The qRT-PCR results indicated that rBCG immunization inhibited the expression of genes associated with lipolysis and energy expenditure in eWAT.BCG immunization had little effect on cytokine transcription,whereas rBCG significantly induced the transcription of IFN-γ and IL-1Ra,and inhibited that of IL-15 and IL-2,but did not induce the expression of aging-associated genes.Thus,rBCG immunization induced eWAT adipocyte hypertrophy,which was associated with the inhibition of eWAT lipolysis and the regulation of cytokine expression.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:To investigate the miRNA-mRNA regulatory network in a rat model of Tourette syndrome(TS)using transcriptomic technology and to screen key signaling pathways and potential traditional Chinese medicine(TCM)candidates for intervention.Methods:A TS rat model was established using iminodipropionitrile(IDPN).RNA sequencing was performed to identify differentially expressed miRNAs and mRNAs in the brain tissues of TS rats.Bioinformatics analysis was applied to construct interaction networks,and network pharmacology was further employed to screen potential TCM compounds.Results:After 7 days of IDPN modeling,the model group exhibited motor and stereotypical behavioral changes,with behavioral scores greater than 3 points.Hema toxylin-eosin(HE)staining revealed irregular neuronal nuclear morphology,uneven chromatin distribution,nuclear pyknosis,and increased glial cell density.KEGG enrichment analysis identified key pathways:calcium signaling pathway,neuroactive ligand-receptor interaction,p53 signaling pathway,ECM-receptor interaction,and TGF-β signaling pathway.miR-125a-3p,miR-106-3p,and miR-760-3p were identified as pivotal miRNAs.Potential TCM candidates included Ajuga decumbens,Acanthopanax bark,Codonopsis pilosula,Stephania japonica,Os Draconis,Notopterygium root,Siraitia grosvenorii,Zanthoxylum nitidum root,Morinda officinalis,and Corydalis yanhusuo.Conclusion:The miRNAs miR-106-3p,miR-125a-3p,and miR-760-3p may mediate TS pathogenesis by altering critical signaling networks,including the calcium signaling pathway,neuroactive ligand-receptor interaction,and ECM-receptor interaction pathways,leading to neuroimmune inflammation and dopaminergic system dysregulation.TCM compounds such as Corydalis yanhusuo and Ajuga decumbens may exert therapeutic effects through multi-component synergistic regulation of these miRNAs and downstream pathways.

Medical ultrasound technology is widely used for diagnosis and therapy in clinical practice.Ultrasound probes,which are directly contact with patients,pose a potential risk of pathogen transmission.This expert consen-sus was developed by a multidisciplinary team based on international guidelines,standards in China,and the results of a national survey,aiming to reduce the risk of healthcare-associated infection through standardizing reprocessing of medical ultrasound probes,and formulating consensus recommendations with the Delphi method.The consensus clarifies the reprocessing principles for three types of ultrasound probes of different infection risks:external-use ul-trasound probes,interventional percutaneous ultrasound probes,and internal-use ultrasound probes,puts forward systematic suggestions on the reprocessing standards and disinfection levels of ultrasound probe isolation covers and coupling agents,the reprocessing procedures and methods of ultrasound probes,as well as architectural layout and management of reprocessing,so as to provide a scientific prevention and control framework for ensuring ultrasound diagnosis and therapy safety.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.