Forensic medicine has been designated as a first-level discipline,presenting new opportunities and challenges for the development of forensic medicine.Since the 1980s,the establishment of foren-sic medicine discipline and the cultivation of high-level forensic talents have become hot topics in the development of forensic medicine in China.Since the 13th Five-Year Plan,the forensic team of Shanxi Medical University has been aiming at the forefront,proposing the development goals of"Five First-class"and the discipline development path"Six Major Achievements".It has selected benchmark disci-plines,identified gaps in disciplinary development,unified thoughts,formulated completion timelines,concentrated superior resources,assigned tasks to individuals,and created an"Organized Fill-in-the-Blank Format"forensic medicine discipline construction model with the characteristics of the new era.The construction model of forensic medicine has achieved good results in the goals,discipline frame-work,scientific research,talent cultivation,discipline team and platform construction,forming a rela-tively complete discipline construction and management system,and accumulating valuable experience for the construction of first-level discipline and high-level talent cultivation of forensic medicine.

Doxorubicin is a commonly used antitumor drug for the treatment of various cancers.How-ever,its clinical application is greatly restricted by its severe cardiotoxicity.At present,doxorubicin-induced cardiotoxicity is categorized into acute and chronic forms,depending on the dosage and dura-tion of exposure,which may eventually lead to the occurrence of heart failure.The pathogenesis of doxorubicin cardiotoxicity is associated with oxidative stress,mitochondrial damage,calcium overload,dysregulation of autophagy,and apoptosis.In forensic medical practice,cases of poisoning or even car-diac death caused by doxorubicin showed no obvious changes in cardiac morphology through routine forensic pathological examinations.The paper aims to summarize the research on the mechanisms of action of doxorubicin-induced cardiotoxicity in recent years,analyze and discuss the possible pathways of cardiomyocyte injury caused by doxorubicin,and provide references for research on the mechanisms of doxorubicin-induced cardiotoxicity and forensic application.

OBJECTIVE: Recombination events are common and serve as the primary driving force of diverse human adenovirus (HAdV), particularly in children with acute respiratory tract infections (ARIs). Therefore, continual monitoring of these events is essential for effective viral surveillance and control. METHODS: Respiratory specimens were collected from children with ARIs between January 2022 and December 2023. The penton base, hexon, and fiber genes were amplified from HAdV-positive specimens and sequenced to determine the virus type. In cases with inconsistent typing results, genes were cloned into the pGEM-T vector to detect recombination events. Metagenomic next-generation sequencing (mNGS) was performed to characterize the recombinant HAdV genomes. RESULTS: Among 6,771 specimens, 277 (4.09%, 277/6,771) were positvie for HAdV, of which 157 (56.68%, 157/277) were successfully typed, with HAdV-B3 being the dominant type (91.08%, 143/157), and 14 (5.05%, 14/277) exhibited inconsistent typing results, six of which belonged to species B. The penton base genes of these six specimens were classified as HAdV-B7, whereas their hexon and fiber genes were classified as HAdV-B3, resulting in a recombinant genotype designated P7H3F3, which closely resembled HAdV-B114. Additionally, a partial gene encoding L1 52/55 kD was identified, which originated from HAdV-B16. CONCLUSION A novel recombinant, P7H3F3, was identified, containing sequences derived from HAdV-B3 and HAdV-B7, which is similar to HAdV-B114, along with additional sequences from HAdV-B16.
Humans ; Adenoviruses, Human/isolation & purification* ; Respiratory Tract Infections/epidemiology* ; Child, Preschool ; Child ; Recombination, Genetic ; Male ; Beijing/epidemiology* ; Infant ; Female ; Phylogeny ; Adenovirus Infections, Human/epidemiology* ; Acute Disease ; Genome, Viral

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 investigate the risk factors,clinical characteristics,and bacterial resistance of bloodstream infections caused by Streptococcus mitis in children with hematological disease,so as to provide a reference for infection control.Methods:The clinical information and laboratory findings of pediatric patients complicated with blood cultures positive for Streptococcus mitis from January 2018 to December 2020 in the Institute of Hematology & Blood Diseases Hospital were searched and collected.The clinical characteristics,susceptibility factors,and antibiotic resistance of the children were retrospectively analyzed.Results:Data analysis from 2018 to 2020 showed that the proportion of Streptococcus mitis isolated from bloodstream infections in children(≤14 years old)with hematological diseases was the highest(19.91％)and significantly higher than other bacteria,accounting for 38.64％of Gram-positive cocci,and presented as an increasing trend year by year.A total of 427 children tested positive blood cultures,including 85 children with bloodstream infections caused by Streptococcus mitis who tested after fever.Most children experienced a recurrent high fever in the early and middle stages(≤6 d)of neutropenia and persistent fever for more than 3 days.After adjusting the antibiotics according to the preliminary drug susceptibility results,the body temperature of most children(63.5％)returned to normal within 4 days.The 85 children were mainly diagnosed with acute myeloid leukemia(AML),accounting for 84.7％.The proportion of children in the neutropenia stage was 97.7％.The incidence of oral mucosal damage,lung infection,and gastrointestinal injury symptoms was 40％,31.8％,and 27.1％,respectively.The ratio of elevated C-reactive protein(CRP)and procalcitonin was 65.9％and 9.4％,respectively.All isolated strains of Streptococcus mitis were not resistant to vancomycin and linezolid,and the resistance rate to penicillin,cefotaxime,levofloxacin,and quinupristin-dalfopristin was 10.6％,8.2％,9.4％,and 14.1％,respectively.None of children died due to bloodstream infection caused by Streptococcus mitis.Conclusion:The infection rate of Streptococcus mitis is increasing year by year in children with hematological diseases,especially in children with AML.Among them,neutropenia and oral mucosal damage after chemotherapy are high-risk infection factors.The common clinical symptoms include persistent high fever,oral mucosal damage,and elevated CRP.Penicillin and cephalosporins have good sensitivity.Linezolid,as a highly sensitive antibiotic,can effectively control infection and shorten the course of disease.

Mitochondrial transcription factor B1(TFB1M)is mainly involved in mitochondrial DNA transcription and related to the development of hepatocellular carcinoma and breast cancer.However,its role in colon cancer is unclear.In this study,the expression level of TFB1M in colon cancer and its prognosis were analyzed based on TCGA and other databases and IHC assays.Differentially expressed genes(DEGs)were screened and subjected to the analysis of functional enrichment,mutation analysis,immune cell infiltration,and drug sensitivity analysis.CCK-8 and flow cytometry were used to detect the effects of overexpression of TFB1M on the viability,apoptosis and cell cycle distribution of colon cancer cells.Our results showed that the expression level of TFB1M was significantly up-regulated in colon canc-er,and its expression level was correlated with the N stage and TNM stage(P＜0.05).The prognosis of colorectal cancer patients in the high TFB1M expression group was worse.Functional enrichment results showed that TFB1M was related to leukocyte-mediated immunity,immunoglobulin production and other signaling pathways.Mutation results showed that high-frequency mutated genes,such as ZFHX4,RYR2,PIK3CA and FAT4,had significantly higher mutation frequencies in the TFB1M high-expression group(all P＜0.05).In addition,the expression level of TFB1M was significantly higher in the PIK3CA and FAT4 mutation groups(all P＜0.05).Immune infiltration results showed that the percentage of CD4+memory activated T cells was increased in the TFB1M high expression group,while the percentage of Treg cells was reduced.The drug sensitivity results showed that patients in the TFB1M high expression group might be more sensitive to Tozasertib,cytarabine,vincristine,etc.,while patients in the TFB1M low expression group might be more sensitive to Dasatinib,JQ1,ERK_2440,etc.The results of cellular experiments showed that over-expression of TFB1M enhanced viability,reduced apoptosis and increased the percentage of S-phase and G2/M-phase cells in colon cancer cells.Altogether,the results indicated that TFB1M might play a key role in the growth of colon cancer cells by regulating immune cell infiltration and function.

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 effects of combination therapy with aqueous extract of corn silk(CS)and training on exercise capacity and glycolipid metabolism in mice with metabolic syndrome(MS).Methods:In this study,db/db mice were used as the animal model of MS.The mice were administered aqueous extract of CS via gavage and subjected to different intensities of training for 12 weeks(3 months).The specific experimental design was as follows:24 db/db mice were randomly divided into four groups on average:negative control group(NC),aqueous extract of CS group(CS),aqueous extract of CS+moderate-intensity training group(CS+MT),and CS aqueous extract of CS+high-intensity training group(CS+HT).The maximum running speed,forelimb grip strength,body weight and fasting blood glucose of mice were measured before and after treatment.After the intervention,oral glucose tolerance test(OGTT)and insulin tolerance test(ITT)were conducted to assess glucose metabolism,while serum triglyceride(TG),total cholesterol(TC),high-density lipoprotein cholesterol(HDL-C),and low-density lipoprotein cholesterol(LDL-C)levels were measured to evaluate lipid metabolism.Results:After 3 months of intervention,there were significant differences in the maximum running speed and forelimb grip strength among the four groups(P＜0.05).The maximum running speed and forelimb grip strength of CS group,CS+MT group and CS+HT group were higher than those of NC group(P＜0.05).The CS+MT group exhibited higher forelimb grip strength,and the CS+HT group showed higher maximum running speed and forelimb grip strength compared to the CS group(P＜0.05),while no significant difference was found between the CS+MT and CS+HT groups(P＞0.05).Significant differences in body weight were observed among the four groups after 3 months of intervention(P＜0.05).Specifically,the CS+MT and CS+HT groups exhibited significantly lower body weight compared to both the NC and CS groups(P＜0.05),with the CS+MT group having the lowest body weight(P＜0.05).Fasting blood glucose levels also differed significantly among the groups after 2 and 3 months of intervention(P＜0.05).The CS,CS+MT,and CS+HT groups had lower fasting blood glucose levels compared to the NC group(P＜0.05),with the CS+MT and CS+HT groups showing the lowest levels(P＜0.05).No significant difference was found between the CS+MT and CS+HT groups(P＞0.05).After 3 months of intervention,significant differences in the area under the curve(AUC)of OGTT and ITT were observed among the four groups(P＜0.05).The AUC of OGTT and ITT were significantly lower in the CS,CS+MT,and CS+HT groups compared to the NC group(P＜0.05).The CS+MT and CS+HT groups exhibited the lowest AUC values for both OGTT and ITT(P＜0.05),with the CS+MT group showing the lowest AUC for OGTT(P＜0.05).Significant differences in serum lipid levels were observed among the four groups after 3 months of intervention(P＜0.05).TG,TC,and LDL-C levels were significantly lower,while HDL-C levels were higher in the CS,CS+MT,and CS+HT groups compared to the NC group(P＜0.05).The CS+MT group had the lowest TG levels and the highest HDL-C levels compared to the CS+HT group(P＜0.05),with no significant differences in TC and LDL-C levels between these two groups(P＞0.05).Conclusion:Aqueous extract of CS combined with different intensity training can significantly improve the exercise capacity and glycolipid metabolism of MS mice and reduce body weight,especially CS combined with MT treatment is more effective in improving lipid metabolism.In addition,when combined with HT,aqueous extract of CS can also play an auxiliary role in reducing the side effects of high-intensity exercise and improving the therapeutic effect.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.
Humans ; Male ; Azoospermia/diagnostic imaging* ; Deep Learning ; Testis/pathology* ; Retrospective Studies ; Adult ; Ultrasonography/methods* ; Sperm Retrieval ; Sertoli Cell-Only Syndrome/diagnostic imaging*