This study was aimed at preliminarily investigating the genetic and antimicrobial resistance characteristics of Salmonella Alachua isolates through whole-genome analyses.Five Salmonella Alachua isolates from various sources(both hu-man and non-human)were collected and identified.Phenotype and serotype verification,antimicrobial susceptibility testing,and whole-genome sequencing were performed.Virulence genes,antimicrobial resistance genes,and plasmid replicons were predicted according to globally available Salmonella Alachua genomic data.A phylogenetic tree was constructed to explore the genetic background.The first report of Salmonella Alachua in China emerged in Shanghai in 2015,and patients presented pri-marily with diarrhea.The isolates have been found predominantly in the eastern and southern coastal regions.Among the five i-solates analyzed,four belonged to sequence type(ST)2061,and one belonged to ST1298.All isolates were susceptible to most commonly used clinical antibiotics.Whole-genome analyses revealed that two ST2061 strains carried the blaKPC-2 gene,and one ST1298 strain carried the fosA7 gene.Phylogenetic analysis of global Salmonella Alachua populations indicated that the ST2061 clone belonged to the C1 clade,which was closely related to strains from the UK,whereas the ST1298 clone was found in the C4 clade,a globally disseminated fosA 7-positive lineage.This study provides initial insights into the genetic and antimi-crobial resistance characteristics of Salmonella Alachua in China,highlighting the presence of strains carrying blaKPC-2 and fo-sA7 genes.These findings may provide a reference for future large-scale molecular epidemiological surveillance and source-trac-ing efforts,and they underscore the importance of enhanced resistance monitoring for Salmonella Alachua.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Neurosyphilis is a group of clinical syndromes caused by treponema pallidum invading the central nervous system and causing varying degrees of damage to the brain parenchyma, brain (spinal) membrane or spinal cord. Cerebral syphilitic gumma is the rarest form of neurosyphilis, and its clinical manifestations lack specificity, which is easily confused with other intracranial space occupying lesions on imaging. In this article, a patient with cognitive dysfunction, intracranial hypertension, and imaging findings similar to multicentric glioma was diagnosed as cerebral syphilitic gumma by serology, cerebrospinal fluid test and brain histopathology. The symptoms basically disappeared after treatment with standard penicillin. This report aims to raise awareness of cerebral syphilitic gumma in order to reduce missed diagnosis and misdiagnosis.

Objective To explore whether creatine therapy regulates neuronal ferroptosis by inhibiting the activation of STAT1 signaling pathway associated with suppressor of cytokine signaling 1(SOCS1)in Alzheimer's disease.Methods Immunohistochemical staining and counting of positive results using paraffin sections of human brain frontal lobes were employed to determine the trend of changes in the target proteins.Further validation was performed by immunofluorescence and Western blotting.STAT1 phosphorylation was inhibited by creatine injection using eleven FAD4T mice and by cerebellar medullary pool puncture,and the expression of target proteins was examined by immunohistochemistry and immunofluorescence after postmortem sampling.Results Compared with the age controls,interferon-γ(IFN-γ),an activating cytokine of the STAT1 signaling pathway,and SOCS1,a negative regulator of STAT1 activation,were both significantly up-regulated,STAT1 phosphorylation was enhanced,and the ferroptosis markers ferritin light chain(FTL)and cystine/glutamate transporter(xCT)increased markedly in the cortex of AD human brains;Creatine treatment of FAD4T mice resulted in a reduction of both IFN-γ and SOCS1,and a significant decrease in the ferroptosis markers FTL and xCT(SLC7A11).Conclusion Creatine ameliorates neuronal ferroptosis in AD model mice by reducing neuronal STAT1-SOCS1 signalling activation.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Cold has been a long-term survival challenge in the evolutionary process of mammals. In response to cold stress, in addition to brown adipose tissue (BAT) dissipating energy as heat through glucose and lipid oxidation to maintain body temperature, cold stimulation can strongly activate thermogenesis and energy expenditure in beige fat cells, which are widely distributed in the subcutaneous layer. However, the effects of cold stimulation on other tissues and systemic lipid metabolism remain unclear. Our previous research indicated that, under cold stress, BAT not only produces heat but also secretes numerous exosomes to mediate BAT-liver crosstalk. Whether subcutaneous fat has a similar mechanism is still unknown. Therefore, this study aimed to investigate the alterations in lipid metabolism across various tissues under cold exposure and to explore whether subcutaneous fat regulates systemic glucose and lipid metabolism via exosomes, thereby elucidating the regulatory mechanisms of lipid metabolism homeostasis under physiological stress. RT-qPCR, Western blot, and H&E staining methods were used to investigate the physiological changes in lipid metabolism in the serum, liver, epididymal white adipose tissue, and subcutaneous fat of mice under cold stimulation. The results revealed that cold exposure significantly enhanced the thermogenic activity of subcutaneous adipose tissue and markedly increased exosome secretion. These exosomes were efficiently taken up by hepatocytes, where they profoundly influenced hepatic lipid metabolism, as evidenced by alterations in the expression levels of key genes involved in lipid synthesis and catabolism pathways. This study has unveiled a novel mechanism by which subcutaneous fat regulates lipid metabolism through exosome secretion under cold stimulation, providing new insights into the systemic regulatory role of beige adipocytes under cold stress and offering a theoretical basis for the development of new therapeutic strategies for obesity and metabolic diseases.
Animals ; Lipid Metabolism/physiology* ; Mice ; Exosomes/metabolism* ; Cold Temperature ; Subcutaneous Fat/physiology* ; Thermogenesis/physiology* ; Adipose Tissue, Brown/metabolism* ; Male

This study aims to explore the mechanism of lung and gut protection by Tanreqing Capsules on the mice infected with influenza virus based on "the lung-gut axis". A total of 110 C57BL/6J mice were randomized into control group, model group, oseltamivir group, and low-and high-dose Tanreqing Capsules groups. Ten mice in each group underwent body weight protection experiments, and the remaining 12 mice underwent experiments for mechanism exploration. Mice were infected with influenza virus A/Puerto Rico/08/1934(PR8) via nasal inhalation for the modeling. The lung tissue was collected on day 3 after gavage, and the lung tissue, colon tissue, and feces were collected on day 7 after gavage for subsequent testing. The results showed that Tanreqing Capsules alleviated the body weight reduction and increased the survival rate caused by PR8 infection. Compared with model group, Tanreqing Capsules can alleviate the lung injury by reducing the lung index, alleviating inflammation and edema in the lung tissue, down-regulating viral gene expression at the late stage of infection, reducing the percentage of neutrophils, and increasing the percentage of T cells. Tanreqing Capsules relieved the gut injury by restoring the colon length, increasing intestinal lumen mucin secretion, alleviating intestinal inflammation, and reducing goblet cell destruction. The gut microbiota analysis showed that Tanreqing Capsules increased species diversity compared with model group. At the phylum level, Tanreqing Capsules significantly increased the abundance of Firmicutes and Actinobacteria, while reducing the abundance of Bacteroidota and Proteobacteria to maintain gut microbiota balance. At the genus level, Tanreqing Capsules significantly increased the abundance of unclassified＿f＿Lachnospiraceae while reducing the abundance of Bacteroides, Eubacterium, and Phocaeicola to maintain gut microbiota balance. In conclusion, Tanreqing Capsules can alleviate mouse lung and gut injury caused by influenza virus infection and restore the balance of gut microbiota. Treating influenza from the lung and gut can provide new ideas for clinical practice.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Lung/metabolism* ; Mice, Inbred C57BL ; Capsules ; Orthomyxoviridae Infections/virology* ; Gastrointestinal Microbiome/drug effects* ; Male ; Humans ; Female ; Influenza A virus/physiology* ; Influenza, Human/virology*