BackgroundWith the rapid development of the networking technologies， internet addiction has increasingly become a serious mental health issue. Previous studies have revealed the link between childhood trauma and internet addiction， while the mediating role of perceived stress in this link is not yet clear. ObjectiveTo investigate the role of medical students' perceived stress in the relationship between childhood trauma and internet addiction， so as to provide references for the intervention of internet addiction. MethodsFrom February to March 2023， a random sampling technique was used to select 1 232 undergraduate students from the School of Clinical Medical Sciences of Southwest Medical University as research subjects. The Childhood Trauma Questionnaire-Short Form （CTQ-SF）， Perceived Stress Scale （PSS）， Internet Gaming Disorder Scale （IGDS）， and Bergen Social Media Addiction Scale （BSMAS） were used for assessment. Pearson's correlation coefficients were calculated. The mediation effect of perceived stress in the relationship between childhood trauma and internet addiction was tested using Model 4 in the SPSS Process 4.1， and Bootstrapping procedure involving 5 000 replicates was employed to confirm the statistical significance. ResultsA total of 1 016 （82.47%） valid completed questionnaires were gathered. The CTQ-SF scores of medical students were positively correlated with PSS scores， IGD scores， and BSMAS scores （r=0.583， 0.474， 0.465， P<0.01）. PSS scores were positively correlated with IGD scores and BSMAS scores （r=0.369， 0.479， P<0.01）. Childhood trauma in medical students was found to positively predict perceived stress （β=0.191， P<0.01）， social media addiction （β=0.160， P<0.01）， and internet gaming disorder （β=0.106， P<0.01）. Perceived stress played a significant mediating role in the relationship between childhood trauma and internet gaming disorder， indirect effect value was 0.018 （95% CI： 0.009~0.027）， accounting for 16.98%. Perceived stress also exhibited a significant mediating role in the relationship between childhood trauma and social media addiction， indirect effect value was 0.063 （95% CI： 0.048~0.079）， accounting for 39.38%. ConclusionChildhood trauma in medical students may affect internet gaming disorder and social media addiction through perceived stress. ［Funded by 2022 Annual Research Project of Sichuan Applied Psychology Research Center，（number，CSXL-22102）］

ObjectiveTo characterize the seasonal patterns of influenza in Kunming City, Yunnan Province before, during, and after the COVID-19 pandemic, and provide scientific evidence for optimizing influenza prevention and control strategies. MethodsInfluenza-like illness (ILI) and etiological surveillance data for influenza from the 14^th week of 2010 to the 13^th week of 2024 in Kunming City of Yunnan Province were collected. Harmonic regression models were constructed to analyze the epidemic characteristics and seasonal patterns of influenza before (2010/2011‒2019/2020 influenza seasons), during (2020/2021‒2022/2023 influenza seasons), and after (2023/2024 influenza season) the COVID-19 pandemic. ResultsBefore the COVID-19 pandemic, influenza in Kunming City mainly exhibited an annual cyclic pattern without a significant semi-annual periodicity, peaking from December to February of the next year, with an epidemic duration of 20‒30 weeks. During the pandemic, influenza seasonality shifted, with an increase in semi-annual periodicity and an approximate one month delay in annual peaks. However, after the pandemic, the annual amplitude of influenza increased compared with that before the pandemic, and the epidemic duration extended by about one month. Although the annual peak largely reverted to the pre-pandemic levels, the annual peaks for different influenza subtypes/lineages had not fully recovered. ConclusionInfluenza seasonality in Kunming City underwent substantial alterations following the COVID-19 pandemic and has not yet fully reverted to pre-pandemic levels. Continuous surveillance on different subtypes/lineages of influenza viruses remains essential, and prevention and control strategies should be adjusted and optimized in a timely manner based on current epidemic trends.

BackgroundPatients with depressive disorder often exhibit impaired decision-making functions. However， the relationship between decision-making abilities and depressive and anxiety symptoms in these patients remains unclear. ObjectiveTo explore the characteristics of decision-making behavior in patients with depressive disorder， and to analyze its relationship with clinical symptoms. MethodsA total of 48 patients diagnosed with depressive disorder according to the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） were recruited from the Department of Psychosomatic Medicine of the Affiliated Hospital of Southwest Medical University from October 2020 to May 2023. Concurrently， 52 healthy individuals matched for age and gender were recruited from Luzhou as the control group. Beck Depression Inventory （BDI） and Beck Anxiety Inventory （BAI） were used for assessment， and decision-making behavior was evaluated using Probabilistic Reversal Learning （PRL） task. Indicators assessed included the number of trials to criterion， perseverative errors， win-stay rate and lose-shift rate. Spearman correlation analysis was used to assess the correlation between BDI and BAI scores and PRL task indicators. ResultsThe depression group showed a significantly higher lose-shift rate compared with the control group （t=3.684， P<0.01）. There were no statistically significant differences between two groups in trials to criterion， perseverative errors and win-stay rate （t=0.329， 0.132， 0.609， P>0.05）. In depression group， BDI and BAI scores were positively correlated with the win-stay rate（r=0.450， 0.398， P<0.01）. ConclusionPatients with depressive disorder are more likely to change their decision-making strategies following negative outcomes. Furthermore， the severity of depressive and anxiety symptoms is associated with a greater propensity to maintain existing decisions after receiving positive feedback. ［Funded by 2019 Joint Project of Luzhou Science and Technology Bureau-Southwest Medical University （number， 2019LZXNYDJ39］

Glucose-6-phosphate dehydrogenase(G6PD)deficiency is one of the most common monogenic genetic diseases in the world.China is the high incidence area of this disease.G6PD heterozygote is the main form of G6PD deficiency in females,which belongs to X-linked incomplete dominant inheritance.Therefore,the enzyme activities of female heterozygotes vary widely,showing normal to mild to moderate enzyme activi-ties.There is no unified calibrators for G6PD enzymatic detection reagents commonly used in clinical practice,and the results of the same sample detected by different kits from different manufacturers are different,so there is a phenomenon of missed detection in clinical screening of female G6PD heterozygotes.Although G6PD gene detection can effectively improve the detection rate of female heterozygotes,its clinical application is lim-ited due to cost and other reasons.Therefore,the development of detection methods that can improve the de-tection rate of female heterozygotes and are suitable for large-scale screening and clinical application will be an urgent need to be solved in clinical practice.This article reviews the epidemiology of G6PD deficiency,genetic characteristics of female G6PD gene,clinical manifestations and detection methods of G6PD female heterozy-gotes.

Objective To investigate the risk factors for pneumonia complicating infectious mononucleosis(IM)in adults and construct a nomogram prediction model.Methods A retrospective analysis was conducted on 198 IM patients admitted to the Second Affiliated Hospital of Air Force Medical University from January 2015 to December 2021.Patients were divided into pneumonia group(n=52)and non-pneumonia group(n=146)based on whether pulmonary infection occurred during hospitalization.The baseline data(age,gender,place of onset,etc.),clinical manifestations(maximum body temperature,lymph node enlargement,splenomegaly,etc.),and inflammatory indicators[white blood cell count(WBC),C-reactive protein(CRP),etc.]were compared between the two groups.Kaplan-Meier curves were plotted to analyze the key indicators affecting the hospital stay of IM patients.Multivariate logistic regression was used to analyze the independent risk factors for pneumonia complicating IM in adults and construct a nomogram prediction model based on the identified risk factors.The predictive efficacy of the model was evaluated using the receiver operating characteristic(ROC)curve and the consistency of the model was assessed using the calibration curve.The fit of the model was evaluated using the Hosmer-Lemeshow test.Additionally,the sensitivity,specificity,and accuracy of the model were assessed using confusion matrix.Results Compared with non-pneumonia group,the pneumonia group had a significantly higher proportion of patients from rural areas,with body mass index(BMI)≥24 kg/m2,smoking history,hepatomegaly,fever duration of≥7 d,as well as increased total hospitalization costs and average daily hospitalization costs,and prolonged hospital stay(P<0.05).The proportion of patients with a history of antibiotic use was lower in the pneumonia group(P<0.05).Kaplan-Meier survival analysis showed that patients from rural areas,with BMI≥24 kg/m2,smoking history,no prophylactic use of antibiotics,fever duration≥7 d,and hepatomegaly had significantly prolonged hospital stays(P<0.05).Multivariate logistic regression analysis revealed that living in a rural area(OR=4.089,P<0.05),hepatomegaly(OR=4.082,P<0.05),and elevated WBC(OR=1.205,P<0.05)were independent risk factors for pneumonia complicating IM in adults,while the prophylactic use of antibiotics(OR=0.142,P<0.05)was an independent protective factor.The area under the ROC curve of the constructed nomogram prediction model was 0.827(95%CI 0.762-0.892),and the slope of the calibration curve was close to 1,and the Hosmer-Lemeshow test showed χ2=5.299,P=0.725,indicating good consistency and fit of the prediction model.The results of the confusion matrix assessment showed that the sensitivity of the model was 0.669(0.624-0.773),the specificity was 0.827(0.724-0.930),and the accuracy was 0.732(0.665-0.793).Conclusion The nomogram prediction model based on place of onset,hepatomegaly,the prophylactic use of antibiotics and WBC has excellent fit and discrimination,providing an effective quantitative tool for prognosis assessment of IM.

Objective The density and species composition of cockroaches in Suzhou,China as well as their seasonal fluctuations were investigated to provide a theoretical basis for their scientific control.Methods The sticking trap method was used to survey the population of cockroaches in the city.The chi-square test was used to compare the rates of adhesion to the sticky sheets,and the Kruskal-Wallis H test was used to compare the density of cockroaches.Results From 2019 to 2023,a total of 27 576 sticky sheet traps were placed in various areas of Suzhou.Of these,2 248 yielded positive captures of 15 963 cockroaches in total,with an adhesion rate of 8.15%and density of 0.58 insects per sheet.Blattella germanica predominated,accounting for 95.76%of the cockroach species in Suzhou.The adhesion rate and density of cockroaches decreased from 2019 to 2023,with the difference between the years being statistically significant(χ2=96.913,P<0.001).The highest adhesion rate and density(25.89%and 2.36 insects per sheet,respectively)were found in farm product markets.The adhesion rates differed significantly among different habitats(χ2=2 458.309,P<0.001).Cockroaches were active throughout the year,and the month of peak density differed in different years,with the overall peak density being 0.66 insects per sheet in November.Additionally,the seasonal fluctuation in cockroach density differed significantly among the different years(H=23.976,P<0.001).Conclusions The survey results showed that the adhesion rate and density of cockroaches in Suzhou have been decreasing annually.Cockroaches were active throughout the year,being mainly present in farm product markets.The seasonal fluctuations in cockroach density in different years differed significantly.Therefore,the characteristics of each habitat should be considered to effectively reduce the cockroach population density.

This paper aimed to use non-targeted urine metabolomics to reveal the potential biomarkers of toxicity in rats with hepatic injury induced by aqueous extracts of Dictamni Cortex(ADC). Forty-eight SD rats were randomly assigned to a blank group and high-dose, medium-dose, and low-dose ADC groups, with 12 rats in each group(half male and half female), and they were administered orally for four weeks. The hepatic injury in SD rats was assessed by body weight, liver weight/index, biochemical index, L-glutathione(GSH), malondialdehyde(MDA), and pathological alterations. The qPCR was utilized to determine the expression of metabolic enzymes in the liver and inflammatory factors. Differential metabolites were screened using principal component analysis(PCA) and partial least squares-discriminant analysis(PLS-DA), followed by a metabolic pathway analysis. The Mantel test was performed to assess differential metabolites and abnormally expressed biochemical indexes, obtaining potential biomarkers. The high-dose ADC group showed a decrease in body weight and an increase in liver weight and index, resulting in hepatic inflammatory cell infiltration and hepatic steatosis. In addition, this group showed elevated levels of MDA, cytochrome P450(CYP) 3A1, interleukin-1β(IL-1β), and tumor necrosis factor-α(TNF-α), as well as lower levels of alanine transaminase(ALT) and GSH. A total of 76 differential metabolites were screened from the blank and high-dose ADC groups, which were mainly involved in the pentose phosphate pathway, tryptophan metabolism, purine metabolism, pentose and glucuronic acid interconversion, galactose metabolism, glutathione metabolism, and other pathways. The Mantel test identified biomarkers of hepatotoxicity induced by ADC in SD rats, including glycineamideribotide, dIDP, and galactosylglycerol. In summary, ADC induced hepatotoxicity by disrupting glucose metabolism, ferroptosis, purine metabolism, and other pathways in rats, and glycineamideribotide, dIDP, and galactosylglycerol could be employed as the biomarkers of its toxicity.
Animals ; Male ; Rats, Sprague-Dawley ; Rats ; Metabolomics ; Biomarkers/metabolism* ; Liver/metabolism* ; Drugs, Chinese Herbal/adverse effects* ; Female ; Chemical and Drug Induced Liver Injury/metabolism* ; Glutathione/metabolism* ; Humans

Small animal multimodal biomedical imaging refers to the integration of multiple imaging techniques within the same system or device to acquire comprehensive physiological and pathological information of small animals, such as mice and rats. With the continuous advancement of biomedical research, this cutting-edge technology has attracted extensive attention. Multimodal imaging techniques, based on diverse imaging principles, overcome the limitations of single-modal imaging through information fusion, significantly enhancing the overall system's sensitivity, temporal/spatial resolution, and quantitative accuracy. In the future, the integration of new materials and artificial intelligence will further boost its sensitivity and resolution. Through interdisciplinary innovation, this technology is expected to become the core technology of personalized medicine and expand its applications to drug development, environmental monitoring, and other fields, thus reshaping the landscape of biomedical research and clinical practice. This review summarized the progress on the application and investigation of multimodal biomedical imaging techniques, and discussed its development in the future.
Animals ; Multimodal Imaging/trends* ; Rats ; Mice ; Artificial Intelligence ; Diagnostic Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed