ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.

Objective This study aimed to provide an effective scientific basis for prevention and control of cockroaches on aircrafts by identifying cockroach-carried pathogens,and assess the insecticidal efficacy of gel bait mediated cockroach control on aircrafts,to provide technical guidance for aircraft disinsection.Methods Cassette-trapping was used to trap cockroaches,and the carried pathogens were detected using bacterial cultivation techniques.The gel bait mediated killing rate was calculated after 1,7,and 30 d by field application of gel bait.Results A total of 411 cockroaches were captured,and all were identified as Blattella germanica.26 strains of pathogenic bacteria were isolated from the trapped cockroaches.The killing rates of cockroaches were 58.8％-96.3％with 1-30 day application of gel bait.Statistically significant differences were observed in cockroach killing rates on different days(χ2=58.95,P<0.01).Conclusions B.germanica carry a large variety of pathogenic bacteria and opportunistic pathogens and are thus important infectious disease carriers.Gel bait agents have proven to be very effective against cockroaches on aircrafts.

Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

Objective: To investigate the characteristics and trend of stroke incidence in Yixing City, Jiangsu Province from 2016 to 2023, so as to provide the reference for formulating prevention and control strategies of stroke. Methods: Data of stroke case in Yixing City from 2016 to 2023 were collected from the National Health Information Platform of Yixing City, including sex, age, time of onset, and diagnostic subtypes. Crude incidence was standardized using the data from the 2010 Chinese National Population Census to analyze the characteristics of stroke incidence. The incidence trend of stroke was analyzed by average annual percent change (AAPC). Results: A total of 54 157 stroke cases were reported in Yixing City from 2016 to 2023, with a crude incidence of 629.52/100 000 and a standardized incidence of 299.50/100 000, showing an upward trend (AAPC=9.744% and 5.955%, both P<0.05). The crude and standardized incidence of stroke in males were significantly higher than those in females (695.30/100 000 vs. 565.79/100 000, 328.73/100 000 vs. 270.71/100 000, both P<0.05). Stroke incidence exhibited an age-dependent increase (P<0.05), peaking in the ≥60 years age group (1 820.43/100 000). The crude and standardized incidence of ischemic stroke (555.46/100 000 and 262.26/100 000) were significantly higher than those of hemorrhagic stroke (52.80/100 000 and 28.03/100 000, both P<0.05). From 2016 to 2023, the standardized incidences of stroke in males, females, the 0-<40 years age group, the 40-<60 years age group, the ≥60 years age group, and ischemic stroke all showed an upward trend (AAPC=6.692%, 4.925%, 5.607%, 5.777%, 5.698%, and 8.481%, respectively, all P<0.05). No significant temporal trend was observed for hemorrhagic stroke incidence (P>0.05). Conclusions The incidence of stroke among residents in Yixing City showed an upward trend from 2016 to 2023, with males and elderly individuals being high-risk populations. Ischemic stroke emerged as the predominant subtype, while a concerning trend of increasing stroke incidence among younger adults was observed.

OBJECTIVE: To develop a method for identifying high-risk patients among septic populations requiring mechanical ventilation, and to conduct phenotypic analysis based on this method. METHODS: Data from four sources were utilized: the Medical Information Mart for Intensive Care (MIMIC-IV 2.0, MIMIC-III 1.4), the Philips eICU-Collaborative Research Database 2.0 (eICU-CRD 2.0), and the Anhui Medical University Second Affiliated Hospital dataset. The adult patients in intensive care unit (ICU) who met Sepsis-3 and received invasive mechanical ventilation (IMV) on the first day of first admission were enrolled. The MIMIC-IV dataset with the highest data integrity was divided into a training set and a test set at a 6:1 ratio, while the remaining datasets were served as validation sets. The demographic information, comorbidities, laboratory indicators, commonly used ICU scores, and treatment measures of patients were extracted. Clinical data collected within first day of ICU admission were used to calculate the sequential organ failure assessment (SOFA) score. K-means clustering was applied to cluster SOFA score components, and the sum of squared errors (SSE) and Davies-Bouldin index (DBI) were used to determine the optimal number of disease subtypes. For clustering results, normalized methods were employed to compare baseline characteristics by visualization, and Kaplan-Meier curves were used to analyze clinical outcomes across phenotypes. RESULTS: This study enrolled patients from MIMIC-IV dataset (n = 11 166), MIMIC-III dataset (n = 4 821), eICU-CRD dataset (n = 6 624), and a local dataset (n = 110), with the four datasets showing similar median ages and male proportions exceeding 50%; using 85% of the MIMIC-IV dataset as the training set, 15% as the test set, and the rest dataset as the validation set. K-means clustering based on the six-item SOFA score was performed to determine the optimal number of clusters as 3, and patients were finally classified into three phenotypes. In the training set, compared with the patients with phenotype II and phenotype III, those with phenotype I had the more severe circulatory and respiratory dysfunction, a higher proportion of vasoactive drug usage, more obvious metabolic acidosis and hypoxia, and a higher incidence of congestive heart failure. The patients with phenotype II was dominated by respiratory dysfunction with higher visceral injury. The patients with phenotype III had relatively stable organ function. The above characteristics were consistent in both the test and validation sets. Analysis of infection-related indicators showed that the patients with phenotype I had the highest SOFA score within 7 days after ICU admission, initial decreases and later increases in platelet count (PLT), and higher counts of neutrophils, lymphocytes, and monocytes as compared with those with phenotype II and phenotype III, their blood cultures had a higher positivity rates for Gram-positive bacteria, Gram-negative bacteria and fungi as compared with those with phenotype II and phenotype III. The Kaplan-Meier curve indicated that in the training, test, and validation sets, the 28-day cumulative mortality of patients with phenotype I was significantly higher than that of patients with phenotypes II and phenotype III. CONCLUSIONS Three distinct phenotypes in septic patients receiving IMV based on unsupervised machine learning is derived, among which phenotype I, characterized by cardiorespiratory failure, can be used for the early identification of high-risk patients in this population. Moreover, this population is more prone to bloodstream infections, posing a high risk and having a poor prognosis.
Humans ; Machine Learning ; Sepsis/therapy* ; Respiration, Artificial ; Intensive Care Units ; Organ Dysfunction Scores ; Male ; Female ; Middle Aged ; Adult

OBJECTIVE: Hepatocellular carcinoma (HCC) is sensitive to ferroptosis, a new form of programmed cell death that occurs in most tumor types. However, the mechanism through which ferroptosis modulates HCC remains unclear. This study aimed to investigate the oncogenic role and prognostic value of FANCD2 and provide novel insights into the prognostic assessment and prediction of immunotherapy. METHODS: Using clinicopathological parameters and bioinformatic techniques, we comprehensively examined the expression of FANCD2 macroscopically and microcosmically. We conducted univariate and multivariate Cox regression analyses to identify the prognostic value of FANCD2 in HCC and elucidated the detailed molecular mechanisms underlying the involvement of FANCD2 in oncogenesis by promoting iron-related death. RESULTS: FANCD2 was significantly upregulated in digestive system cancers with abundant immune infiltration. As an independent risk factor for HCC, a high FANCD2 expression level was associated with poor clinical outcomes and response to immune checkpoint blockade. Gene set enrichment analysis revealed that FANCD2 was mainly involved in the cell cycle and CYP450 metabolism. CONCLUSION To the best of our knowledge, this is the first study to comprehensively elucidate the oncogenic role of FANCD2. FANCD2 has a tumor-promoting aspect in the digestive system and acts as an independent risk factor in HCC; hence, it has recognized value for predicting tumor aggressiveness and prognosis and may be a potential biomarker for poor responsiveness to immunotherapy.
Humans ; Carcinoma, Hepatocellular/diagnosis* ; Liver Neoplasms/diagnosis* ; Immunotherapy ; Fanconi Anemia Complementation Group D2 Protein/metabolism* ; Prognosis ; Male ; Female ; Middle Aged ; Biomarkers, Tumor/metabolism*

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.

Objective To establish an inductively coupled plasma-mass spectrometry(ICP-MS)method for the analysis of 29 mineral elements in Artemisiae Argyi Folium(AAF),and to develop a model for judging the origin of AAF based on the elemental fingerprint combined with chemometrics.Methods The variance method was used to compare the contents of 29 mineral elements in AAF samples from Qichun of Hubei province,Hebei province and Henan province,respectively.The discriminant models of AAF from different habitats were established by discriminant analysis,PLS-DA and PCA-Logistic regression algorithms.Results The differences of the 22 elements(V,Cr,Ni,As,Se,Rb,Mo,Cd,Sb,Ba,Hg,Pb,K,Li,B,Mg,Al,P,Ca,Fe,Zn,and Ga)in samples from Qichun of Hubei province,Hebei province and Henan province are extremely significant(P＜0.01).The discriminant analysis model showed that eight kinds of element variables(P,Cr,K,Li,Hg,Ba,Mg,and Mo),which have a significant effect on the origin discrimination are gradually introduced into the discriminant model,and the correct rate of back test is 100％.The correct rate of"leave one method"cross-validation is 96.7％.The PLS-DA model showed good prediction ability,and the variable importance projection values of K,P and Mg elements were greater than one,which could be used as the difference marker of AAF from different habitats.The accuracy of the origin discrimination model constructed by PC A-Logistic regression analysis was 100％.The elements with high first principal component loadings were Li,B,Mg,Al,P,K,Ca,V,Cr,Fe,Ni,Zn,As,Rb,Cd,Sb,and Ba.Conclusion This study shows that elemental fingerprint technology combined with chemometric analysis can identify AAF from Qichun of Hubei province,Hebei province,or Henan,providing technical support for the traceability of the origin of Artemisia argyi.

Objective:To evaluate the impact of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality and calculate the attributable mortality burden.Methods:This study collected road traffic mortality data from the Disease Surveillance System in Guangdong, Hunan, Zhejiang, Yunnan, and Jilin Provinces from 2013 to 2018. A time-stratified case-crossover design was used in this study, with the death date for each case serving as the case day. Control days were selected from the same year, month, and day of the week as the case day. A conditional logistic regression model was employed to estimate the cumulative associations of short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves on the risk of road traffic mortality (lag 0-1 day) and to calculate the attributable fractions (AF).Results:Compared to non-heatwave days, the excess risk ( ER) of road traffic mortality on daytime heatwave days, nighttime heatwave days, and compound heatwave days was 5.3% (95% CI: 0.5%-10.2%), 4.9% (95% CI: 0.5%-9.4%) and 7.5% (95% CI: 2.3%- 12.9%), with corresponding AF of 5.0% (95% CI: 0.5%-9.3%), 4.7% (95% CI: 0.5%-8.6%), and 6.9% (95% CI: 2.3%-11.4%), respectively. Stratified analysis showed that the risk of traffic mortalities caused by daytime heatwaves was higher in females ( ER=15.7%, 95% CI: 5.8%-26.5%) than in males ( ER=1.8%, 95% CI: -3.6%-7.4%). Elderly individuals over 64 years old ( ER=10.9%, 95% CI: 0.3%- 22.6%) had a higher risk of road traffic mortalities from compound heatwaves than those under 45 years old ( ER=2.6%, 95% CI: -5.4%-11.2%). The risk of road traffic injury mortality from motor vehicle accidents caused by compound heatwaves ( ER=16.6%, 95% CI:2.4%-32.7%) was higher than that from non-motor vehicle accidents ( ER=5.7%, 95% CI:0.1%-11.5%). Conclusions:Short-term exposure to daytime heatwaves, nighttime heatwaves, and compound heatwaves was associated with an increased risk of road traffic mortality, with the strongest association observed for compound heatwaves. The mortality burden attributable to compound heatwaves was higher than that for daytime and nighttime heatwaves. Heatwaves were more significantly associated with road traffic mortality risk among females, elderly individuals over 64 years old, and motor vehicle accidents.

Objective:To summarize the progress in the research of textual quality evaluation of health-related media reports.Methods:A systematic literature retrieval about textual quality evaluation of health-related media reports based on PubMed, Web of Science, Embase, Wanfang database, and China National Knowledge Infrastructure was conducted. Information regarding the textual quality definition, evaluation dimensions, indicators and methods of included papers was extracted.Results:A total of 29 study papers were included in this analysis, in which 26 were about retrospective textual quality evaluation of health-related media reports, and 3 were about the model or tool development for textual quality evaluation of health-related media reports. The topics of news reports included: 16 studies on injury, 3 on general health, 3 on infectious disease, 3 on cancer screening and treatment, 3 on chronic non-communicable disease, and 1 on medication risk. The definition of textual quality of health-related media reports and the dimensions of the quality evaluation varied across the studies. The quality evaluation indicators of media reports can be divided into three categories: availability of surveillance information, availability of professional information, and adherence to principles of media reporting. Most studies conducted the quality evaluation manually, with only 2 studies employing semi-automated or automated evaluation methods.Conclusions:No unified definition, set of dimensions, indicators, or automated algorithms exist for evaluating the textual quality of health-related media reports, which limits assessing massive news data effectively. It is necessary to conduct methodological studies on the textual quality evaluation of health-related media reports based on journalism and communication theory, infodemiology, deep learning, natural language processing, text mining, as well as specific disease and injury prevention theory.