ObjectiveIn the realm of forensic science, dust is a valuable type of trace evidence with immense potential for intricate investigations. With the development of DNA sequencing technologies, there is a heightened interest among researchers in unraveling the complex tapestry of microbial communities found within dust samples. Furthermore, striking disparities in the microbial community composition have been noted among dust samples from diverse geographical regions, heralding new possibilities for geographical inference based on microbial DNA analysis. The pivotal role of microbial community data from dust in geographical inference is significant, underscoring its critical importance within the field of forensic science. This study aims to delve deeply into the nuances of fungal community composition across the urban landscapes of Beijing, Fuzhou, Kunming, and Urumqi in China. It evaluates the accuracy of biogeographic inference facilitated by the internal transcribed spacer 2 (ITS2) fungal sequencing while concurrently laying a robust foundation for the operational integration of environmental DNA into geographical inference mechanisms. MethodsITS2 region of the fungal genomes was amplified using universal primers known as 5.8S-Fun/ITS4-Fun, and the resulting DNA fragments were sequenced on the Illumina MiSeq FGx platform. Non-metric multidimensional scaling analysis (NMDS) was employed to visually represent the differences between samples, while analysis of similarities (ANOSIM) and permutational multivariate analysis of variance (PERMANOVA) were utilized to statistically evaluate the dissimilarities in community composition across samples. Furthermore, using Linear Discriminant Analysis Effect Size (LEfSe) analysis to identify and filter out species that exhibit significant differences between various cities. In addition, we leveraged SourceTracker to predict the geographic origins of the dust samples. ResultsAmong the four cities of Beijing, Fuzhou, Kunming and Urumqi, Beijing has the highest species richness. The results of species annotation showed that there were significant differences in the species composition and relative abundance of fungal communities in the four cities. NMDS analysis revealed distinct clustering patterns of samples based on their biogeographic origins in multidimensional space. Samples from the same city exhibited clear clustering, while samples from different cities showed separation along the first axis. The results from ANOSIM and PERMANOVA confirmed the significant differences in fungal community composition between the four cities, with the most pronounced distinctions observed between Fuzhou and Urumqi. Notably, the biogeographic origins of all known dust samples were successfully predicted. ConclusionSignificant differences are observed in the fungal species composition and relative abundance among the cities of Beijing, Fuzhou, Kunming, and Urumqi. Employing fungal ITS2 sequencing on dust samples from these urban areas enables accurate inference of biogeographical locations. The high feasibility of utilizing fungal community data in dust for biogeographical inferences holds particular promise in the field of forensic science.

Attention deficit hyperactivity disorder （ADHD）， also known as hyperactivity disorder in children， is a behavioral disorder commonly found in children， particularly preschool-aged children. This disorder can lead to cognitive impairment， learning difficulties， conduct disorders， and other mental health issues， severely impacting the quality of life for affected children. Moreover， the global prevalence of ADHD continues to rise. Establishing an animal model that closely aligns with clinical symptoms and the pathogenesis of the disease is crucial for advancing research on the prevention and treatment of ADHD. In recent years， research on animal models of ADHD has rapidly developed. Researchers have developed nearly 20 animal models from genetic and environmental perspectives. However， most of these models are still in the exploratory stage， and there is insufficient research to thoroughly investigate their pathogenesis， core characteristics， and drug effects. The spontaneously hypertensive rat （SHR） is currently the most commonly used animal model for ADHD because of its excellent face validity and developmental stage that better corresponds to childhood. In addition， dopamine transporter （DAT） knockout mice， LPHN3 knockout rats， and neonatal rat hypoxia models have also shown good face validity. Some researchers have injected SHRs with daily doses of levothyroxine sodium， which not only induces typical ADHD symptoms in the rats but also exhibits signs of Yin deficiency and Yang hyperactivity， which successfully simulates the Yin deficiency and Yang hyperactivity syndrome type of ADHD， providing a new approach for constructing and evaluating ADHD animal models that combine both traditional Chinese and western medicine. This article reviewed ADHD animal models reported in China and abroad over the past decade， summarized rodent models of ADHD into three major categories： genetic models， chemically induced models， and environmentally induced models， and analyzed each category to provide a reference for selecting and exploring appropriate models for experimental ADHD research.

ObjectiveTo investigate the genetic polymorphism and structure of 47 autosomal microhaplotypes in the Han population in Changshu City, Jiangsu Province, and to evaluate the forensic efficiencies and forensic parameters. MethodsThe DNA library of unrelated individual samples was prepared according to MHSeqTyper47 kit manual and sequenced on the MiSeq FGx platform. Microhaplotype genotyping and sequencing depth statistics were processed using MHTyper. The genetic information of samples was then evaluated. The fixation index and genetic distance between the Jiangsu Changshu population and the reference populations in the 1000 Genomes Project phase 3 (1KG) were calculated, and forensic parameters were evaluated. ResultsThe fixation index and genetic distance between the Han population in Changshu, Jiangsu, and the CHB (Han Chinese in Beijing, China) reference population in 1KG were the lowest. The effective allele number (A_e) of each locus is also the closest between the two populations. The combined matching probability (CMP) of the Changshu Han population is close to the 5 populations of the East Asian reference super-population in 1KG, which is 1.25×10^-36, and the combined probability of exclusion reached 0.999 999 999 964 1. ConclusionThis study reported the genetic polymorphism and allele frequency of 47 microhaplotypes in a Han population in Changshu City, Jiangsu Province. This information provides a data basis for 47 microhaplotypes in forensic applications. In addition, the polymorphism differences between the 1KG reference population and the Han population in Changshu, Jiangsu were compared, and the genetic structure of 47 microhaplotypes in the Han population in Changshu, Jiangsu was revealed. In general, the reference data of the East Asian super-population in 1KG is more in line with the genetic characteristics of Han population in Changshu, Jiangsu.

Objective To investigate the application value of the MHSeqTyper47 kit in kinship identification.Methods Multiplexed amplification and library preparation were performed for DNA samples from 113 related individuals by using the MHSeqTyper47 kit.The libraries were sequenced on a MiSeq FGx sequencer,and the data were analyzed using MHTyper for microhaplotype genotyping.The kinship indexes were calculated to evaluate the application efficiency of this kit in kinship identification and compared with those of the GlobalFilerTM kit.Results For the MHSeqTyper47 kit,the CPI values in trio identification were 1.43× 1011～6.15×1018.The CPI values in duo identification were 1.02× 105～1.53× 1013.The CFSI values in full sibling identification were 7.73×101～2.59×1016.Trios,duos and full siblings could be completely distinguished from unrelated pairs.The combined efficiency of these two kits in 2nd-degree kinship identification was 0.466 2.Conclusion The application value of MHSeqTyper47 kit is relatively higher in the identification of lst-degree kinships.If jointly used with the GlobalFilerrM kit,2nd-degree kinship identification could be achieved in some cases.

DNA genetic markers have always played important roles in individual identification, kinship analysis, ancestry inference and phenotype characterization in the field of forensic medicine. DNA methylation has unique advantages in biological age inference, body fluid identification and prediction of phenotypes. The majority of current studies independently examine DNA and DNA methylation markers using various workflows, and they use various analytical procedures to interpret the biological information these two markers present. Integrated methods detect DNA and DNA methylation markers simultaneously through a single experimental workflow using the same preparation of sample. Therefore, they can effectively reduce consumption of time and cost, streamline experimental procedures, and preserve valuable DNA samples taken from crime scenes. In this paper, the integrated detection approaches of DNA and DNA methylation markers on different detection platforms were reviewed. In order to convert methylation modifications to detectable forms, several options were available for pretreatment of genomic DNA, including digestion with methylation-sensitive restriction enzyme, affinity enrichment of methylated fragments, conversion of methylated or unmethylated cytosine. Multiplexed primers can be designed for DNA markers and converted DNA methylation markers for co-amplification. The schemes of using capillary electrophoresis platform for integrated detection add the pretreatment of genomic DNA on the basis of detecting DNA genetic markers. DNA and DNA methylation markers are then integrated by co-amplification. But the limited number of fluorescent options available and the length of amplicons restrict the type and quantity of markers that can be integrated into a panel. Pyrophosphate sequencing also supports integrated detection of DNA and DNA methylation markers. On this platform, due to the conversion of unmethylated cytosine to thymine after treatment with bisulfite, the methylation level of CpG site can be directly calculated using the peak height ratio of cytosine bases and thymine bases. Therefore, the methylation levels and SNP typing can be simultaneously obtained. However, due to the limited read length of sequencing, the detection of markers with longer amplicons is restricted. It is not conducive to fully interpret the complete information of the target sequence. Next-generation sequencing also supports integrated detection of DNA and DNA methylation markers. A preliminary experimental process including DNA extraction, pretreatment of genomic DNA, co-preparation of DNA and DNA methylation library and co-sequencing, has been formed based on the next-generation sequencing platform. It confirmed the feasibility of next-generation sequencing technology for integrated detection of DNA and DNA methylation markers. In field of biomedicine, various integrated detection schemes and corresponding data analysis approaches of DNA and DNA genetic markers developed based on the above detection process.Co-analysis can simultaneously obtain the genomic genetic and epigenetic information through a single analytic process. These schemes suggest that next-generation sequencing may be an effective method for achieving more accurate and highly integrated detection, helping to explore the potential for application in forensic biological samples. We finally explore the impact of interactions between sites and different pretreatment methods on the integrated detection of DNA and DNA methylation markers, and also propose the challenge of applying third-generation sequencing for integrated detection in forensic samples.

Objective To observe the safety and efficacy of perioperative short-duration platelet membrane glycoprotein Ⅱ b/Ⅲ a receptor antagonist(GPI)in elderly patients undergoing primary percutaneous coronary intervention(PPCI)for acute ST-segment elevation myocardial infarction(STEMI)with high thrombotic burden.Methods A total of 140 elderly patients with acute STEMI admitted to our department from October 2021 to January 2024 were recruited and ran-domly divided into experimental group(short duration)and control group(standard duration),with 70 cases in each group.The occurrence of MACE,complete rate of ST segment resolution 2 h after surgery,blood flow classification thrombolysis in myocardial infarction(TIMI),left ventric-ular ejection fraction(LVEF),N-terminal pro-B-type natriuretic peptide(NT-proBNP),inhibition of platelet aggregation(IPA)by thromboelastography(TEG),maximum amplitude of adenosine diphosphate receptor pathway(MAADP),platelet-related indicators,and incidences of thrombocy-topenia and bleeding events were observed in the 2 groups after operation.Results There were no significant differences in postoperative recurrence of angina pectoris,acute heart failure,malignant arrhythmia,rate of ST segment resolution,TIMI blood flow grade 3,no reflow,LVEF,NT-proBNP level before discharge,and incidences of severe hemorrhage and thrombocytopenia during hospi-talization between the two groups(P＞0.05).The experimental group had significantly lower IPA[(76.1±15.3)％vs(96.3+19.4)％,P=0.016]and higher MAADP(45.6±8.2 mm vs 26.7±9.7 mm,P=0.028)in 18 h after operation,and lower incidence of minor bleeding(7.1％vs 24.3％,P＜0.05)during hospitalization when compared with the control group.Conclusion Under the premise of using a novel oral purinergic receptor P2Y12 inhibitor,short-term GPI is not inferior to the standard time course in achievement of IPA,with similar efficacy and relatively better safety.

The geographical origin of forensic evidence provides important information for crime investigation and solving cases,and is one of the key elements of criminal cases.Previous studies have shown significant differences in the distribution of microorganisms in different regions.Detecting environmental DNA samples and inferring the geographical and spatial sources can provide clues and evidence for case handling.However,due to the diversity of criminal environments and the trace amount of frequently encountered exhibits,stable and reliable technical methods for inferring geographical origin from environmental DNA are not yet available.This article summarizes the sample collection and DNA extraction methods for four types of environmental samples:dust,soil,water,and air.It compares the differences between amplicon sequencing and metagenomic sequencing in studying environmental biological populations,outlines the full process of high-throughput sequencing-based data analysis,and focuses on reviewing the research progress in inferring geographical sources of environmental samples based on bacteria,fungi,and other eukaryotes,to provide references for establishing sequencing and analysis methods for environmental DNA in forensic DNA laboratories and exploring environmental DNA information for forensic applications.

Objective Sequencing depth is a key parameter in next generation sequencing,which is closely related to the accuracy of sequencing results.Forensic biological evidence examination requires extremely high accuracy.It is crucial to scientifically and reasonably set the sequencing depth analysis threshold for forensic next generation sequencing testing.Methods This study used targeted sequencing data of microhaplotypes from 50 samples with known genotypes.By calculating the accuracy,precision,recall,and F1 score of each locus under various threshold conditions,two types of analysis threshold setting methods,which were based on fixed read count and fixed sequencing depth ratio,were studied extensively.Results The results showed that false positives were observed when the analysis threshold was set at 50×or 100×.When the analysis threshold was set at 200×,false negatives were observed.When the analysis threshold was set at 1.5%,3.0%,or 4.5%,false positives were observed.This study further proposed a third type of analysis threshold setting method,which was based on sequencing depth ratio scatter plots.With this method,no false positive or false negative was observed in the results.This article then explored four factors that lead to significant differences in the sequencing depth of forensic next generation sequencing experiments,compared with the analysis threshold setting method for capillary electrophoresis technology,and discussed the correlation between analysis thresholds and the ability to distinguish mixed DNA.Conclusion Employing the sequencing depth ratio scatter plot method to set analysis threshold has significant application value in next generation sequencing-based forensic genetic marker genotyping.

Objective To systematically evaluate the application efficacy of failure mode and effect analysis(FMEA)management mode in the prevention and control of healthcare-associated infection(HAI).Methods Li-terature on the application of FMEA management mode in HAI prevention and control were retrieved from PubMed,Embase,the Cochrane Library,China National Knowledge Infrastructure(CNKI),VIP Database,Wanfang Data-base,and China Biomedical Literature Database(CBM).Two researchers independently screened the literature,ex-tracted data,and conducted cross checking.Risk and quality assessments were performed on the included studies of randomized controlled trials by ROB tool,the included cohort studies were scored by Newcastle-Ottawa(NOS)scale,and Meta-analysis was conducted by RevMan 5.4 software.Results A total of 22 studies involving 42 815 patients were included in the analysis,with 21 784 in the FMEA management mode group and 21 031 in the control group.Meta-analysis results showed that the incidence of HAI in the FMEA management mode group was lower than that in the control group(OR=0.31,95％CI[0.24,0.40]).Compared with the conventional management mode,incidences of superficial surgical site infection(OR=0.53,95％CI[0.36,0.78]),respiratory system infec-tion(OR=0.44,95％CI[0.35,0.56]),urinary system infection(OR=0.45,95％CI[0.38,0.53]),and blood system infection(OR=0.29,95％CI[0.18,0.45])in the FMEA management mode group were all lower(all P＜0.01).Conclusion The application of FMEA management mode in HAI prevention and control can reduce the inci-dence of HAI,which should be actively promoted in hospital management.

Objective To analyze the clinical characteristics of high energy metabolism in lung cancer patients and its correlation with body composition,nutritional status,and quality of life,and to develop a corresponding risk prediction model.Methods Retrospectively analyzed 132 primary lung cancer patients admitted to the First Hospital of Shanxi Medical University from January 2022 to May 2023,and categorized into high(n=94)and low energy metabolism group(n=38)based on their metabolic status.Differences in clinical data,body composition,Patient Generated Subjective Global Assessment(PG-SGA)scores,and European Organization for Research and treatment of Cancer(EORTC)Quality of Life Questionnaire-Core 30(QLQ-C30)scores were compared between the two groups.Logistic regression was used to identify the risk factors for high energy metabolism in lung cancer patients,and a risk prediction model was established accordingly;the Hosmer-Lemeshow test was used to assess the model fit,and the ROC curve was used to test the predictive efficacy of the model.Results Of the 132 patients with primary lung cancer,94(71.2%)exhibited high energy metabolism.Compared with low energy metabolism group,patients in high-energy metabolism group had a smoking index of 400 or higher,advanced disease staging of stage Ⅲ or Ⅳ,and higher levels of IL-6 level,low adiposity index,low skeletal muscle index,and malnutrition(P<0.05),and lower levels of total protein,albumin,hemoglobin level,and prognostic nutritional index(PNI)(P<0.05).There was no significant difference in age,gender,height,weight,BMI and disease type between the two groups(P>0.05).Logistic regression analysis showed that smoking index≥400,advanced disease stage,IL-6≥3.775 ng/L,and PNI<46.43 were independent risk factors for high energy metabolism in lung cancer patients.The AUC of the ROC curve for the established prediction model of high energy metabolism in lung cancer patients was 0.834(95%CI 0.763-0.904).Conclusion The high energy metabolic risk prediction model of lung cancer patients established in this study has good fit and prediction efficiency.