Background: Influenza A virus (IAV) is a negative-sense RNA virus of the Orthomyxoviridae family and is the etiological agent of a highly contagious acute respiratory disease that can lead to acute lung injury. Objective: To elucidate the molecular mechanisms of IAV infection, an integrative research approach combining gene expression profiling, multinetwork analysis, and in vivo experimental validations was employed. Methods: First, a series of network-based analyses were performed, including protein-protein interaction network construction, weighted gene co-expression network analysis, and subsequent gene set enrichment analysis, to identify the major underlying mechanisms of IAV infection. Following gene expression analysis, core targets, both direct and indirect regulators, were screened. An IAV (H1N1) strain A/PR/8/34-induced acute lung injury mouse model was constructed for in vivo validations. Batch one included two groups to evaluate findings from the multi-network analysis: Mock (n = 10; 5 males and 5 females) and IAV (n = 10; 5 males and 5 females). Batch two included three groups to assess the role of toll-like receptor 3 (TLR3) in IAV infection: Mock (n = 6; 3 males and 3 females), IAV (n = 6; 3 males and 3 females), and TLR3 inhibitor (n = 6; 3 males and 3 females). Body weight was measured on days 0, 3, and 5 after infection. On day 5, lung tissues were collected to assess viral load and histopathological changes. Key targets were examined using enzyme-linked immunosorbent assay, Western blotting, and immunofluorescence staining, both in sera and lung tissues. Results: IAV infection was significantly associated with dysregulation of the immune-inflammation system, such as the LTR, nucle-otide-binding oligomerization domain-(NOD) like receptor, retinoic acid-inducible gene I-like receptor, and nuclear factor kappa-B signaling pathways. Gene set enrichment analysis further indicated that the TLR and necroptosis signaling pathways played crucial roles in the progression of IAV infection (TLR signaling pathway normalized enrichment score = 2.3941, P = 1.00 × 10 ⁻¹⁰; necroptosis normalized enrichment score = 1.9421, P = 6.21 × 10 ⁻⁷). Among the core targets, TLR3 and mixed lineage kinase domain-like protein (MLKL) may regulate gene expression at the transcriptional level (all P < 0.05). In vivo validation using an IAV (PR8) infected acute lung injury mouse model demonstrated increased viral load and lung index, alveolar structural damage, and inflammatory cell infiltration. Immunofluorescence staining exhibited large gaps in Lamin B1 staining and breaches in Emerin signals following IAV-PR8 infection. Expression levels of TLR3, p-receptor-interacting serine/threonine-protein kinase 3 (RIPK3)/RIPK3, and p-mixed lineage kinase domain-like protein (MLKL)/MLKL proteins in lung tissues, as well as proinflammatory factors and mediators in sera, were significantly elevated after IAV infection. Moreover, enhanced neutrophil infiltration (myeloperoxidase) and citrullinated histone H3 (a neutrophil extracellular trap-specific marker), both established indicators of neutrophil extracellular trap formation, were observed. Notably, treatment with a TLR3 inhibitor significantly ameliorated IAV-induced acute lung injury by regulating necroptosis-related targets. Conclusion: Our study provides network-based in vivo evidence that TLR3-receptor-interacting serine/threonine-protein kinase 3-MLKL-mediated necroptosis may underlie IAV-induced acute lung injury and could serve as a potential therapeutic target in severe influenza cases.

Lung cancer remains one of the leading causes of cancer-related morbidity and mortality worldwide, and its treatment continues to face major challenges such as therapeutic resistance and tumor recurrence. Pyroptosis, a newly characterized form of programmed cell death, induces tumor cell death through gasdermin-mediated membrane pore formation and is accompanied by the release of inflammatory mediators, thereby playing complex roles in lung cancer initiation, progression, and modulation of the tumor microenvironment. Active components and herbal formulas derived from traditional Chinese medicine can modulate pyroptosis-related signaling pathways through multi-target mechanisms, showing potential advantages in inducing lung cancer cell death, inhibiting proliferation and migration, and reversing chemoresistance. This review systematically summarizes relevant studies from domestic and international sources, focusing on the molecular mechanisms of pyroptosis, its roles in lung cancer development and tumor microenvironment remodeling, and the current research progress on traditional Chinese medicine-based interventions targeting pyroptosis, with the aim of providing references for the prevention and treatment of lung cancer using traditional Chinese medicine.

BACKGROUND/OBJECTIVES: Unhealthy diets are associated with chronic stress. An allostatic load (AL) is a comprehensive physiological index that measures the chronic stress response of the body. As a healthy dietary pattern, the role of Dietary Approaches to Stop Hypertension (DASH) in the development of an AL during pregnancy remains unclear. This study examined the relationship between the DASH dietary pattern and AL during pregnancy. SUBJECTS/METHODS: This study was a prospective study. From January 2024 to November 2024, 134 pregnant women in the second trimester (23–27 weeks) and third trimester (32–36 weeks) of pregnancy who met the inclusion and exclusion criteria in the obstetrics clinic of a tertiary general hospital in Anhui Province were selected for a questionnaire survey, physical examination, and laboratory examination. The DASH dietary pattern was assessed using the DASH scoring tool, and the total AL score was calculated using nine biomarkers that represent the cardiovascular, metabolic, and immune systems. Logistic regression was used to analyze the relationship between the DASH score and AL. RESULTS: One hundred and thirty-four pregnant women were included in this study. At the second and third trimesters, 41.8% and 37% of pregnant women, respectively, were in the high AL group. The binary logistic regression results showed that the DASH score was negatively correlated with the AL in the unadjusted model (odds ratio [OR], 0.878; 95% confidence interval [CI], 0.807–0.957; P = 0.003) and adjusted model (OR, 0.878; 95% CI, 0.792–0.973; P = 0.013) in the second trimester, the DASH score was negatively correlated with the AL in the unadjusted model (OR, 0.832; 95% CI, 0.758–0.913; P < 0.001) and adjusted model (OR, 0.806; 95% CI, 0.716–0.908; P < 0.001) in the third trimester. CONCLUSION The DASH score was negatively correlated with the AL in pregnant women.A low DASH score may increase the risk of a high AL, which may have adverse effects on physical and mental health.

Background Under the background of global warming, research on association between ambient temperature and risk of injury is needed. Objective To examine the effect of temperature on injury in Bao'an district, Shenzhen and identify the sensitive population, thereby providing a scientific basis for formulating prevention and control strategies and measures of injury. Methods The injury reports from the Injury Surveillance System and the meteorological data of Bao'an District between 2018 to 2022 were collected. The meteorological data were sourced from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) land reanalysis data. Based on time-stratified case-crossover design, conditional logistic regression combined with distributed lag nonlinear model was used to evaluate the exposure-response association between ambient temperature and injury. The stratified analyses were further conducted by gender, age, and causes of injury. Results A total of 156205 injury cases were collected from the injury surveillance sentinel hospitals in Bao'an District of Shenzhen from 2018 to 2022, and the median of daily average temperature during the same period was 20.0 ℃. The exposure-response curve showed that the risk of injury was positively correlated with temperature. The linearized analysis revealed that each 1°C increase in temperature was associated with a 1.05% (95%CI: 0.68%, 1.42%) rise in injury risk (ER). Notably, the effect was greater in females (ER=1.31%, 95%CI: 0.67%, 1.94%) than males (ER=0.92%, 95%CI: 0.47%, 1.37%). Among age groups, adults ＞60 years faced the highest risk (ER=1.91%, 95%CI: −0.36%, 4.24%). The top three temperature-associated injury risks were sharp instrument injuries (ER=2.19%, 95%CI: 1.16%, 3.22%), animal injuries (ER=1.71%, 95%CI: 0.86%, 2.56%), and blunt injuries (ER=071%, 95%CI: −0.08%, 1.51%). The impact of temperature on unintentional injuries (ER=1.11%, 95%CI: 0.72%, 1.49%) was higher than that on intentional injuries (ER=0.43%, 95%CI: −0.85%, 1.72%). Severe injuries (ER=2.20%, 95%CI: −3.09%, 7.77%) were more affected by temperature than mild injuries (ER=1.00%, 95%CI: 0.58%, 1.43%) and moderate injuries (ER=1.15%, 95%CI: 0.42%, 1.89%). Conclusion The increase in ambient temperature associates with injury occurrence, and the impact of temperature exhibits obvious heterogeneity among different populations, indicating that targeted intervention measures should be taken for different populations and types of injuries.

Objective:To investigate the clinical value of enhanced magnetic resonance imaging (MRI)-based deep learning model in preoperative prediction of proliferative hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinical data of 906 HCC patients who were admitted to The First Affiliated Hospital of Army Medical University and The Second Affiliated Hospital of Chongqing Medical University from May 2017 to October 2022 were collected. There were 769 males and 137 females, aged (53.2±10.9)years. Of the 906 patients, 815 cases who were admitted to The First Affiliated Hospital of Army Medical University were divided into the training set of 634 patients and the internal validation set of 181 patients using a random number table method with a ratio of 8:2, and 91 patients who were admitted to The Second Affiliated Hospital of Chongqing Medical University were divided into the external validation set. The training set was used to construct the prediction model, while the validation set was used to validate the prediction model. Observation indicators: (1) analysis of factors influencing the pathological classification of HCC patients; (2) deep learning imaging features of HCC patients; (3) evaluation of the efficacy of prediction model for proliferative HCC; (4) validation of the prediction model for proliferative HCC; (5) prognosis of HCC patients. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test. Comparison of count data between groups was conducted using the chi-square test. Multivariate analysis was conducted using the binary Logistic regression model. The model perfor-mance was evaluated through five-fold cross-validation, and receiver operating characteristic (ROC) curve was plotted to assess the diagnostic value of the model based on the area under curve (AUC), sensitivity, and specificity. The Delong test was used to compare the diagnostic performance of models. The Hosmer-Lemeshow test was employed to evaluate the calibration of models. The optimal cutoff value of the prediction model was determined by the maximum Youden index, with the value >0.175 indicating high-risk patients and value ≤0.175 indicating low-risk patients.The Kaplan-Meier method was used to calculate the survival rate and the Log-rank test was used for survival analysis. Results:(1) Analysis of factors influencing the pathological classification of HCC patients. Of 634 patients in the training set, there were 190 cases of proliferative HCC and 444 cases of non-proliferative HCC. Results of multivariate analysis showed that alpha fetoprotein (AFP) ≥400 μg/L and tumor diameter >5 cm were independent risk factors for pathological type of HCC as proli-ferative [ odds ratio=1.73, 1.88, 95% confidence interval ( CI) as 1.19-2.50, 1.30-2.71, P<0.05]. (2) Deep learning imaging features of HCC patients. In the training set of 634 patients, the probability predicted by MRI-based deep learning model was 84.8%(30.5%,95.4%) for proliferative HCC and 5.8%(3.2%,12.5%) for non-proliferative HCC, showing a significant difference between them ( Z=-16.01, P<0.05). (3) Evaluation of the efficacy of prediction model for proliferative HCC. In the training set, the AUC of clinical prediction model for proliferative HCC was 0.63(95% CI as 0.59-0.68, P<0.05), with sensitivity of 54.74% and specificity of 64.19%. The AUC of MRI-based deep learning prediction model was 0.90(95% CI as 0.87-0.93, P<0.05), with sensitivity of 80.53% and specificity of 86.94%. The AUC of combined MRI-based deep learning with clinical prediction model was 0.90 (95% CI as 0.87-0.93, P<0.05), with sensitivity of 83.16% and specificity of 86.04%. Results of Delong test showed that there was a significant difference between the combined MRI-based deep learning with clinical prediction model and the clinical prediction model ( P<0.05), and there was no signifi-cant difference between the combined MRI-based deep learning with clinical prediction model and the MRI-based deep learning prediction model ( P>0.05). Results of Hosmer-Lemeshow test showed good calibration for the clinical prediction model, the MRI-based deep learning prediction model and the combined MRI-based deep learning with clinical prediction model ( χ2=0.84, 6.38, 3.93, P>0.05), indicating that the predicted probabilities of these three prediction models matched the actual risk well. (4) Validation of the prediction model for proliferative HCC. Results of validation of the prediction model in internal validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.84(95% CI as 0.77-0.91, P<0.05), with sensitivity of 82.35% and specificity of 77.69%. Results of validation of the prediction model in external validation set showed the AUC of MRI-based deep learning prediction model for proliferative HCC was 0.81(95% CI as 0.71-0.92, P<0.05), with sensitivity of 70.00% and specificity of 81.69%. (5) Prognosis of HCC patients. Of the 906 patients, the 1-, 3-, and 5-year recurrence-free survival rates for 645 proliferative HCC patients were 56.9%, 31.4%, and 29.1%, respectively, and the 1-, 3-, and 5-year recurrence-free survival rates for 261 non-proliferative HCC patients were 88.8%, 68.6%, and 56.0%, respectively. There were significant differences in recurrence-free survival time between proliferative HCC and non-proliferative HCC patients of the training set, internal validation set and external validation set ( P<0.05). The 1-, 3-, 5-year recurrence-free survival rates for 331 high-risk HCC patients were 64.6%, 50.4%, 43.6%, versus 88.5%, 71.9%, 62.7% for 575 low-risk HCC patients. There were significant differences in recurrence-free survival time between high-risk HCC patients and low-risk HCC patients of the training set, internal validation set and external validation set ( P<0.05). Conclusion:The MRI-based deep learning model can effectively predict proliferative HCC and recurrence-free survival of patients before the surgery.

Objective To explore the effect of endoscopic ultrasonography(EUS)with different probes on the measurement of gastrointestinal submucosal tumor(SMT)diameter.Methods The clinical data of 356 patients(with a total of 372 lesions)initially diagnosed as SMT by EUS at the Second Affiliated Hospital of Army Medical University from January 2023 to June 2024 were analyzed retrospectively.The basic characteristics of the origin layers and pathological distribution of SMT were analyzed.The differences between the EUS-measured diameters and the actual diameters of SMT at different diameter ranges of lesions were compared.Taking the postoperative pathological diagnosis results as the gold standard,the effects of different clinicopathological features and probe types on the relative error in EUS-measured diameters of SMT were analyzed.Results Among the 372 gastrointestinal SMT lesions,lesions were more frequent in female patients,gastric lesions was the most common,and leiomyoma was the predominant pathological type.The accuracy of EUS in diagnosing SMT was 94.4%.A statistically significant difference was observed between the EUS-measured diameters and the actual diameters of SMT(P<0.05).There were significantly differences in various ranges of lesions between the EUS-measured diameters and the actual diameters(P<0.05).The gender,age,lesion location,and pathological type had no significant effect on the relative error of EUS-measured diameters(P>0.05);while probe types had a significant effect on the relative error of EUS-measured diameters(P<0.05).For lesions with an actual diameter of 2.0 to 3.9 cm,the relative error of SMT diameters measured by small-probe EUS was significantly greater than that by large-probe EUS(P<0.05).Conclusion Large-probe EUS exhibits a smaller relative error in measuring the diameter of SMT with a diameter of≥2.0 cm.Therefore,large-probe EUS is recommended for the examination of SMT with an estimated diameter exceeding 2.0 cm.

Objective To explore the mechanism of malt alcohol extract improving depression-like behavior induced by CUMS in rats by regulating gut microbiota.Methods The depression model of rats was established using an 8-weeks CUMS procedure,and the administration group was given low(59.6 mg·kg-1)and high(178.8 mg·kg-1)doses of malt alcohol extract,respectively.The depression-like behavior of rats was evaluated by classic behavioral test.The composition of intestinal microbiota of rats was analyzed by 16S rRNA sequencing.The morphological changes of colon were observed by hematoxylin and eosin(HE),the expression of ZO-1 and Occludin in colon was detected by immunofluorescence(IF),and the expression of IL-10,IL-1βand 5-HT were detected by ELISA.Results The low dose of malt alcohol extract attenuated the depressive behavior and restored the expression of 5-HT in the brain of CUMS rats.16S rRNA sequencing results showed that the diversity and relative abundance of gut microbiota changed after treatment with the low dose of malt alcohol extract.ELISA results showed that the low dose of malt alcohol extract significantly reversed the CUMS-induced reduction of IL-10 and elevation of IL-1 β.HE results showed that the low dose of malt alcohol extract significantly ameliorated CUMS-induced structural damage in colon.IF results showed increased protain expression of intestinal epithelial barrier tight junction proteins ZO-1 and Occludin by the low dose of malt alcohol extract.Conclusion The low dose of malt alcohol extract can ameliorate CUMS-induced depressive-like behavior in rats by modulating intestinal flora,restoring 5-HT expression in the brain,inhibiting inflammation,and repairing the intestinal barrier.

Objective To analyze the association between lifestyle and the risk of type 2 diabetes(T2D)among adult residents.Methods The data was sourced from the Shanghai Suburban Adult Cohort and Biobank.A total of 42 096 adult residents who had not developed T2D were recruited from four districts of Shanghai(Songjiang,Jiading,Minhang,and Xuhui)between 2016 and 2019.The follow-up ended on Feb 28,2023.A structured questionnaire was used to collect information on six lifestyle-related items,including smoking,alcohol consumption,BMI,waist circumference(WC),physical activity,and diet.The unhealthy lifestyle scores(UHLS)were calculated by counting the number of all the unhealthy lifestyle items,with a range of 0-6.New-onset T2D events diagnosed by physicians were obtained through the medical information system.Cox proportional hazards regression model and restricted cubic spline model were utilized to evaluate the association between unhealthy lifestyles and the risk of T2D incidence.Results About 28.1%of the participants led 4-6 unhealthy lifestyles.A total of 1 752 new T2D cases were identified during 218 513.4 person-years of follow-up.Analysis of single unhealthy lifestyle showed that abnormal WC(HR=1.5,95%CI:1.4-1.7)and abnormal BMI(HR=1.3,95%CI:1.2-1.5)were associated with an increased risk of T2D.Compared with individuals with a UHLS of 0-1,those with a UHLS of 3 and 4-6 had 30%(95%CI:1.1-1.6)and 50%(95%CI:1.2-1.8)higher risks of T2D,respectively.Each additional unhealthy lifestyle was associated with a 10%increase in T2D incidence risk(HR=1.1,95%CI:1.1-1.2).Conclusion The risk of T2D in adult residents increases with the cumulative number of unhealthy lifestyles.Adult residents with abnormal WC or BMI,or have three or more unhealthy lifestyles accumulated,will increase the risk of new-onset T2D.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To systematically evaluate the impact of continuous renal replacement therapy(CRRT)on the pharmacokinetics of polymyxin B,explore its possible impacting factors.Methods PubMed,Embase,Co-chrane Library,Web of Science,VIP database,China National Knowledge Infrastructure(CNKI),SinoMed,and Wanfang data were retrieved.The study subjects were patients receiving CRRT and polymyxin B.Observational studies,case reports,and reviews were included.The outcome indicators included therapeutic drug monitoring re-sults,pharmacokinetic parameters,and CRRT parameters.The retrieval time was from the inception of each data-base to January 2025.The quality of literatures was evaluated with ClinPK tool.Two researchers independently conducted literature screening,data extraction,and quality evaluation.Results A total of 12 literatures were ulti-mately included in analysis,including 1 review,3 case reports,and 8 observational studies.Five studies showed that the clearance rate during CRRT period(1.3-6.66 L/h)was higher than that during non-CRRT period(0.5-3.9 L/h).Five studies reported that the area under the steady-state 24-hour drug concentration-time curve(AUCss,24h)during CRRT period(21.58-75.1 mg·h/L)was lower than that during non-CRRT period(60.6-118 mg·h/L).Two studies detected drugs in ultrafiltrate or dialysate,with in vitro drug recovery rates ranging from 5.62％to 24.0％.Two studies reported a decrease in drug concentration after passing through a blood filter.Conclusion During CRRT period,polymyxin B presents higher clearance rate and lower blood drug concentration,and some patients have lower AUCss.24h than the therapeutic target.The mechanism of this change during CRRT is not yet clear,the therapy mode and filter type may be potential impacting factors,further research are needed to promote precise anti-infective treatment.