ObjectiveTo assess the current status of medical waste management in Jinshan District of Shanghai, China, to identify existing issues, and to provide a scientific basis for formulating targeted strategies. MethodsData were collected from the routine supervision and inspection records of the Jinshan District Health Commission Supervision Institute from 2017 to 2021, covering all aspects of medical waste management, including collection, classification, transportation, storage, and administrative penalties. ResultsThe compliance rates for the establishment of institutional frameworks, staffing, internal handover, and registration in medical and healthcare institutions all exceeded 95.00%. However, only 2.31% of the medical and healthcare institutions met the 48-hour storage limit requirement for medical waste. Private institutions had significantly lower compliance rates (P<0.05) in aspects such as proper classification and collection, maintaining records for three years, adhering to the 48-hour storage limit, refraining from commercial transactions, timely disinfection and cleaning, and implementing emergency measures for waste loss. Compliance rates also varied among different types of institutions regarding the establishment of temporary storage facilities and the implementation of the transfer manifest system, with community healthcare institutions exhibiting relatively lower compliance rates (P<0.05). Over the past five years, private medical and healthcare institutions accounted for 63.33% of administrative penalty cases. ConclusionWhile medical waste management in Jinshan District, Shanghai, has gradually become more standardized, challenges remain. To address the issue of medical waste being stored for over 48 hours, medical waste transfer stations should be established to improve transfer efficiency and ensure complete waste collection. Additionally, for private and community healthcare institutions, weak links in management should be addressed by establishing medical waste quality control teams, enhancing supervision through digital tools, and optimizing management processes to comprehensively elevate medical waste management.

Amyotrophic lateral sclerosis (ALS) is an irreversible, fatal neurodegenerative disorder whose incidence is positively correlated with the aging population. ALS is characterized by the progressive loss of motor neurons, leading to muscle weakness, atrophy, and ultimately respiratory failure. The pathogenesis of ALS involves multiple factors, including genetic and environmental influences, with genetic factors playing a particularly significant role. To date, several causative genes have been identified in ALS, such as the Cu/Zn superoxide dismutase 1 (Cu/Zn SOD1, also known as SOD1) gene, transactive response DNA-binding protein 43 (TDP-43) gene, fused in sarcoma (FUS) gene, and chromosome open reading frame 72 (C9orf72). Mutations in these genes have been found not only in familial ALS but also in sporadic ALS. Based on the identified ALS risk genes, various ALS animal models have been established through multiple approaches, including transgenic models, gene knockout/knock-in models, and adeno-associated virus-mediated overexpression models. These models simulate some typical pathological features of human ALS, such as motor neuron loss, ubiquitinated inclusions, and neuromuscular junction degeneration. However, these models still have limitations: (1) single-gene mutation models are insufficient to fully replicate the complex multi-factorial pathogenesis of sporadic ALS; (2) significant differences in microenvironmental regulation mechanisms and the rate of neurodegeneration between model organisms and humans may affect the accurate reproduction of disease phenotypes and the reliable evaluation of drug efficacy. To better understand the pathogenesis of ALS and promote the development of effective therapies, constructing and optimizing ALS animal models is crucial. This review aims to summarize commonly used ALS gene mutation mouse models, analyze their phenotypes and pathological characteristics, including transgenic mouse models, gene knockout/knock-in mouse models, and adeno-associated virus-mediated overexpression mouse models, and further discuss their specific applications in ALS pathogenesis research and drug development by comparing the advantages and limitations of each model.

Amyotrophic lateral sclerosis (ALS) is an irreversible, fatal neurodegenerative disorder whose incidence is positively correlated with the aging population. ALS is characterized by the progressive loss of motor neurons, leading to muscle weakness, atrophy, and ultimately respiratory failure. The pathogenesis of ALS involves multiple factors, including genetic and environmental influences, with genetic factors playing a particularly significant role. To date, several causative genes have been identified in ALS, such as the Cu/Zn superoxide dismutase 1 (Cu/Zn SOD1, also known as SOD1) gene, transactive response DNA-binding protein 43 (TDP-43) gene, fused in sarcoma (FUS) gene, and chromosome open reading frame 72 (C9orf72). Mutations in these genes have been found not only in familial ALS but also in sporadic ALS. Based on the identified ALS risk genes, various ALS animal models have been established through multiple approaches, including transgenic models, gene knockout/knock-in models, and adeno-associated virus-mediated overexpression models. These models simulate some typical pathological features of human ALS, such as motor neuron loss, ubiquitinated inclusions, and neuromuscular junction degeneration. However, these models still have limitations: (1) single-gene mutation models are insufficient to fully replicate the complex multi-factorial pathogenesis of sporadic ALS; (2) significant differences in microenvironmental regulation mechanisms and the rate of neurodegeneration between model organisms and humans may affect the accurate reproduction of disease phenotypes and the reliable evaluation of drug efficacy. To better understand the pathogenesis of ALS and promote the development of effective therapies, constructing and optimizing ALS animal models is crucial. This review aims to summarize commonly used ALS gene mutation mouse models, analyze their phenotypes and pathological characteristics, including transgenic mouse models, gene knockout/knock-in mouse models, and adeno-associated virus-mediated overexpression mouse models, and further discuss their specific applications in ALS pathogenesis research and drug development by comparing the advantages and limitations of each model.

Identifying drug-drug interactions (DDIs) is essential to prevent adverse effects from polypharmacy. Although deep learning has advanced DDI identification, the gap between powerful models and their lack of clinical application and evaluation has hindered clinical benefits. Here, we developed a Multi-Dimensional Feature Fusion model named MDFF, which integrates one-dimensional simplified molecular input line entry system sequence features, two-dimensional molecular graph features, and three-dimensional geometric features to enhance drug representations for predicting DDIs. MDFF was trained and validated on two DDI datasets, evaluated across three distinct scenarios, and compared with advanced DDI prediction models using accuracy, precision, recall, area under the curve, and F1 score metrics. MDFF achieved state-of-the-art performance across all metrics. Ablation experiments showed that integrating multi-dimensional drug features yielded the best results. More importantly, we obtained adverse drug reaction reports uploaded by Xiangya Hospital of Central South University from 2021 to 2023 and used MDFF to identify potential adverse DDIs. Among 12 real-world adverse drug reaction reports, the predictions of 9 reports were supported by relevant evidence. Additionally, MDFF demonstrated the ability to explain adverse DDI mechanisms, providing insights into the mechanisms behind one specific report and highlighting its potential to assist practitioners in improving medical practice.

Background:Pancreatic exocrine insufficiency(PEI)after gastrectomy can lead to weight loss,diarrhea,abdominal distension,fat malabsorption and other symptoms,which seriously affects patients'quality of life.Aims:To investigate the incidence of PEI after gastrectomy and the efficacy of pancreatic enzyme replacement therapy(PERT).Methods:Studies on PEI after gastrectomy and/or efficacy of PERT were retrieved from PubMed,Embase,Web of Science,CNKI,Wanfang Data and VIP databases from the date of database establishment to January 2024.Two researchers independently screened the literature,extracted data,and assessed the risk of bias about included studies.Meta-analysis was conducted by Stata 12.0 software.Results:A total of 16 studies involving 974 patients were included in the meta-analysis,of which 14 studies reported the incidence of PEI after gastrectomy,and 2 studies reported the efficacy of PERT.The incidence of PEI after gastrectomy was 43.8%(95%CI:0.295-0.585).Subgroup analysis showed that the incidence of PEI after gastric cancer surgery was 82.1%(95%CI:0.541-0.991),the incidence of PEI in patients underwent total gastrectomy with Roux-en-Y reconstruction and partial gastrectomy with Billroth Ⅱ reconstruction were 60.4%(95%CI:0.489-0.719)and 63.5%(95%CI:0.511-0.759),respectively,and the incidence of PEI after bariatric surgery with billiopancreatic diversion with duodenal switch(BPD/DS)was 67.3%(95%CI:0.542-0.804).Early intervention of PERT after total gastrectomy could reduce fecal fat content at 24 hours(SMD=-1.24,95%CI:-1.56--0.91,P<0.001)and 72 hours(SMD=-1.41,95%CI:-1.74--1.07,P<0.001),and the number of patients with 24-hour fecal fat content＞7 g(OR=0.21,95%CI:0.09-0.53,P=0.001).Conclusions:PEI is common after gastrectomy,and clinicians should pay more attention on it,especially in gastric cancer patients undergoing gastrectomy,Roux-en-Y reconstruction after total gastrectomy,Billroth Ⅱ reconstruction after partial gastrectomy and bariatric surgery with BPD/DS.Fat malabsorption caused by PEI in patients after total gastrectomy can be improved by PERT.

Objective To investigate the causal relationship between gastroesophageal reflux disease(GERD)and different phenotypes of asthma based on Mendelian randomization(MR).Methods The dataset was pooled by genome-wide association studies(GWAS),in which the GERD data contained 602 604 cases,the unspecified asthma data contained 156 078 cases,139 591 cases of obesity-associated asthma,138 474 cases of pediatric asthma,140 308 cases of allergic asthma and 136 633 cases of eosinophilic asthma.The inverse va-riance weighting method was used as the main method of MR analysis,and the weighted median method,sim-ple model,weighted models and MR-Egger conducted the supplement,and the sensitivity analysis was carried out to assess the stability of the results.Results The MR analysis showed that unspecified asthma(OR=1.61,95％CI:1.45-1.77,P＜0.01),obesity-related asthma(OR=2.40,95％CI:1.98-2.90,P＜0.01),Childhood asthma(OR=1.56,95％CI:1.25-1.94,P＜0.01)and allergic asthma(OR=1.47,95％CI:1.25-1.74,P＜0.01)present the forward cause effect,but eosinophilic asthma had no causal relation with GERD(OR=1.31,95％CI:0.95-1.81,P=0.10).The sensitivity analysis showed that the horizontal pleiot-ropy and heterogeneity in the results did not exist.Conclusion GERD could lead to an increased risk of un-specified asthma asthma,obesity-associated asthma,pediatric asthma and allergic asthma,while the effect on eosinophilic asthma is not significant.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:To investigate the feasibility of predicting the risk of spontaneous preterm birth in singleton pregnancy women with low risk of preterm birth by transabdominal-transvaginal ultrasound cervical length sequential screening in the second trimester.Methods:This prospective longitudinal cohort study included singleton pregnant women at 11-13 +6 gestational weeks who were admitted to Nanjing Drum Tower Hospital from January 2023 to September 2023. Transabdominal and transvaginal cervical lengths were measured during the mid-trimester fetal ultrasound scan at 18-24 weeks, and pregnancy outcomes were obtained after delivery. A short cervix was defined as a transvaginal cervical length of ≤25 mm, and the outcomes were defined as spontaneous preterm birth occurs between 20 and 36 +6 weeks and extremely preterm birth before 32 weeks. The area under the receiver operating characteristic (ROC) curve was used to evaluate the effectiveness of predicting spontaneous preterm birth by transabdominal and transvaginal cervix length, as well as the effectiveness of predicting short cervix by transabdominal cervical length. The relationship between transabdominal and transvaginal cervical length was evaluated using a scatter plot. Results:A total of 562 cases were included in this study, comprising 33 cases of spontaneous preterm birth (7 cases occurring before 32 weeks) and 529 cases of term birth. (1) Compared to the term birth group, transabdominal cervical length (median: 37.6 vs 33.2 mm; Z=-3.838, P<0.001) and transvaginal cervical length (median: 34.0 vs 29.9 mm, Z=-3.030, P=0.002) in the spontaneous preterm birth group were significantly shorter. (2) The areas under the ROC curve for predicting spontaneous preterm birth by transabdominal and transvaginal cervical length were 0.699 (95% CI: 0.588-0.809) and 0.657 (95% CI: 0.540-0.774), respectively. The sensitivity, specificity and positive predictive value of transvaginal cervical length Conclusions:In singleton pregnancy women with low risk of preterm birth, transabdominal-transvaginal cervical length sequential screening can reduce unnecessary transvaginal ultrasounds by approximately 41% without missing the diagnosis of pregnant women with a short cervix. This method also enhances the effectiveness of transvaginal cervical length to spontaneous preterm birth.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.

Objective:The clinical data of prenatal stillbirth were analyzed in order to increase the understand-ing of the causes of stillbirth.Methods:Prenatal stillbirth cases that terminated pregnancy in Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University from January 2018 to December 2022 were col-lected,and the distribution characteristics of clinical data and the stillbirth causes were analyzed.The causes of death were classified according to the standards developed by the Stillbirth Collaborative Research Network(SCRN)in the United States,and they were divided into clear cause-of-death group and unknown cause-of-death group.The different characteristics of the two groups were compared and analyzed.Results:There were 210 ca-ses of prenatal stillbirth during the study period,and 104 cases met the inclusion criteria.Among them,33 cases(31.7%)had autopsy results,39 cases(37.5%)had genetic results,and 75 cases(72.1%)had placental pathol-ogy.According to the classification of SCRN standard,55 cases(52.9%)were probably related to the cause of death,33 cases(31.7%)were classified as possible,13 cases(12.5%)were probably unrelated,and 3 cases(2.9%)could not be attributed to the cause of death,that is,84.6%(88 cases)in the clear cause of death group and 15.4%(16 cases)in the unknown cause of death group.The rate of placental pathological examination in the clear cause of death group was significantly higher than that in the unknown cause of death group(78.4%).In the classification of causes of death,placental pathological changes accounted for the largest proportion,account-ing for 26.9%(28 cases),followed by pregnancy complications accounting for 25.0%(26 cases),and 15.4%of the cases were still unexplained.Conclusions:Placental pathology is of great significance for clarifying the cause of stillbirth.It is feasible to use SCRN to classify the etiology of stillbirth.Pathological placental conditions account for a relatively high proportion in the classification of stillbirth causes.It is recommended that each case of stillbirth placenta should undergo pathological examination.