Objective To investigate the feasibility of the spatiotemporal filtering model in analysis of reported schistosomiasis cases, so as to provide insights into analysis of complicated data pertaining to schistosomiasis control. Methods Demographic and epidemiological data of reported schistosomiasis cases in Anhui Province from 1997 to 2010 were collected from Anhui Provincial Center for Disease Control and Prevention, and the annual prevalence of Schistosoma japonicum human infections was calculated. The meteorological data were captured from meteorological stations in counties (cities, districts) of Anhui Province where schistosomiasis cases were reported from 1997 to 2010 at the National Meteorological Information Center, including monthly average air temperature and precipitation. Meteorological data were interpolated using the inverse-distance weighting method, and the annual average air temperature and annual precipitation were calculated in each county (city, district). The centroid of the county (city, district) where schistosomiasis cases were reported was extracted using the software ArcGIS 10.0, and the Euclidean distance from each centroid to the Yangtze River was calculated as the distance between that county (city, district) and the Yangtze River. The global Moran’s I of the prevalence of S. japonicum human infections in Anhui Province for each year from 1997 to 2010 were calculated to analyze the spatial autocorrelation. A spatial weight matrix was constructed using Rook adjacency, and a first-order temporal weight matrix was built to quantify the relationship between disease changes over time. Subsequently, a spatiotemporal structure matrix was constructed. A negative binomial model was built based on the spatiotemporal structure matrix and data pertaining to reported schistosomiasis cases, and a linear model was created between the residual of the model and candidate set feature vectors to determine the optimal subset composition of the spatiotemporal filter through stepwise regression. Then, a spatio-temporal filtering model was constructed using the negative binomial model. Negative binomial models, Bayesian spatial models, and Bayesian spatiotemporal models were constructed and compared with the spatiotemporal filtering model to validate the performance of the spatiotemporal filtering model, and cross-validation was conducted for each model. The goodness of fit was evaluated using the deviance information criterion (DIC) and Watanabe-Akaike information criterion (WAIC), and the effectiveness of model validation was assessed using mean squared error (MSE), while the accuracy of assessment results was assessed using coefficients and their 95% confidence intervals (CI), and the computational efficiency was assessed based on the running time of the model. The four feature vectors with the largest Moran’s I values were selected to identify regions with autocorrelation through their schematic diagrams to investigate the differences in spatiotemporal patterns of specific regions. Results Of all models created, the spatiotemporal filtering model exhibited the highest goodness of fit (DIC = 3 240.70, WAIC = 3 257.80), the best model validation effectiveness (MSE = 42 617.52), and the runtime was 3.18 s, exhibiting the optimal performance. Across all modeling results, the distance from the Yangtze River showed a negative correlation with the number of reported schistosomiasis cases (coefficient values = −4.93 to −3.78, none of the 95% CIs included 0), and annual average air temperature or average precipitation posed no significant effects on numbers of reported schistosomiasis cases (both of the 95% CIs included 0). Schematic diagrams of feature vectors showed that the transmission of schistosomiasis might be associated with water systems in Anhui Province, and localized clustering patterns were primarily concentrated in the northern and western parts of schistosomiasis-endemic areas in the province. Conclusion The spatiotemporal filtering model is an effective spatiotemporal analysis characterized by simple modeling, user-friendly operation, accurate results and good flexibility, which may serve as an efficient alternative to conventional complex spatiotemporal models for data analysis in schistosomiasis researches.

A teaching clinic is an outpatient clinic specialized for teaching, where trainees are responsible for medical activities such as medical history taking, physical examination, and diagnosis and treatment, under the assistance and guidance of teachers. Only a few hospitals in China have built up teaching clinics for standardized training of pediatric residents. This paper summarizes the experience in the operation management of the standardized residency training teaching clinic in Children's Hospital, Zhejiang University School of Medicine. The teaching clinic takes teaching as its core task, adheres to humanistic care, and follows the principle of hierarchical progression. Its operation involves organizational approval, preliminary arrangements, outpatient appointments, the implementation of teaching activities, and other processes, which are carried out under organizational management and quality management. We have explored a preliminary strategy for evaluating the teaching effects of teaching clinics, and proposed some suggestions for the future development of pediatric residency training teaching clinics such as increasing objective evaluation methods and increasing pediatric subspecialty teaching clinics.

Objective:To observe and evaluate the clinical efficacy and safety of albumin-bound paclitaxel as first-line treatment for patients with advanced pancreatic cancer in China, and to explore the prognosis-related molecules in pancreatic cancer based on next-generation sequencing (NGS) of tumor tissues.Methods:From December 2018 to December 2020, patients with locally advanced or metastatic pancreatic cancer were recruited to accept albumin-bound paclitaxel as first-line treatment in the oncology departments of 24 hospitals in East China. The primary endpoints were overall survival (OS) and treatment related adverse events, and the secondary endpoint was progression-free survival (PFS). Adverse effects were graded using Common Terminology Criteria for Adverse Events 5.0 (CTCAE 5.0). NGS sequencing on the primary or metastatic tissue samples of pancreatic cancer obtained through surgical resection or biopsy was performed.Results:This study recruited 229 patients, including 70 patients with locally advanced pancreatic cancer (LAPC) and 159 patients with metastatic pancreatic cancer (mPC). The disease control rate was 79.9% and the objective response rate is 36.3%.The common adverse effects during treatment were anaemia (159 cases), leucopenia (170 cases), neutropenia (169 cases), increased aminotransferases (110 cases), and thrombocytopenia (95 cases), and the incidence of grade 3-4 neutropenia is 12.2% (28/229). The median follow-up time was 21.2 months (95% CI: 18.5-23.1 months). The median PFS (mPFS) was 5.3 months (95% CI: 4.37-4.07 months) and the median OS (mOS) was 11.2 months (95% CI: 9.5-12.9 months). The mPFS of patients with LAPC was 7.4 months (95% CI: 6.6-11.2 months), and their mOS was 15.5 months (95% CI: 12.6-NA months). The mPFS of patients with mPC was 3.9 months (95% CI: 3.4-5.1 months), and their mOS was 9.3 months (95% CI: 8.0-10.8 months). Multivariate Cox regression analysis showed that clinical stage ( HR=1.47, 95% CI: 1.06-2.04), primary tumor site ( HR=0.64, 95% CI: 0.48-0.86), Eastern Cooperative Oncology Group Performance Status (ECOG PS) score ( HR=2.66, 95% CI: 1.53-4.65), and whether to combine radiotherapy ( HR=0.65, 95% CI: 0.42-1.00) were independent influencing factors for the PFS of these patients. The primary tumor site ( HR=0.68, 95% CI: 0.48-0.95), ECOG score ( HR=5.82, 95% CI: 3.14-10.82), and whether to combine radiotherapy ( HR=0.58, 95% CI: 0.35-0.96) were independent influencing factors of the OS of these patients. The most frequent gene mutations in these advanced stage pancreatic patients were KRAS (89.66%), TP53 (77.01%), CDKN2A (32.18%), and SMAD4 (21.84%) by NGS of tumor tissues from 87 pancreatic cancer patients with sufficient specimens. Further analysis revealed that mutations in CDKN2B, PTEN, FGF6, and RBBP8 genes were significantly associated with an increased risk of death ( P＜0.05). Conclusion:Albumin-bound paclitaxel as first-line treatment demonstrated feasible anti-tumor efficacy and manageable safety for patients with advanced pancreatic cancer in China.

Objective:To observe and evaluate the clinical efficacy and safety of albumin-bound paclitaxel as first-line treatment for patients with advanced pancreatic cancer in China, and to explore the prognosis-related molecules in pancreatic cancer based on next-generation sequencing (NGS) of tumor tissues.Methods:From December 2018 to December 2020, patients with locally advanced or metastatic pancreatic cancer were recruited to accept albumin-bound paclitaxel as first-line treatment in the oncology departments of 24 hospitals in East China. The primary endpoints were overall survival (OS) and treatment related adverse events, and the secondary endpoint was progression-free survival (PFS). Adverse effects were graded using Common Terminology Criteria for Adverse Events 5.0 (CTCAE 5.0). NGS sequencing on the primary or metastatic tissue samples of pancreatic cancer obtained through surgical resection or biopsy was performed.Results:This study recruited 229 patients, including 70 patients with locally advanced pancreatic cancer (LAPC) and 159 patients with metastatic pancreatic cancer (mPC). The disease control rate was 79.9% and the objective response rate is 36.3%.The common adverse effects during treatment were anaemia (159 cases), leucopenia (170 cases), neutropenia (169 cases), increased aminotransferases (110 cases), and thrombocytopenia (95 cases), and the incidence of grade 3-4 neutropenia is 12.2% (28/229). The median follow-up time was 21.2 months (95% CI: 18.5-23.1 months). The median PFS (mPFS) was 5.3 months (95% CI: 4.37-4.07 months) and the median OS (mOS) was 11.2 months (95% CI: 9.5-12.9 months). The mPFS of patients with LAPC was 7.4 months (95% CI: 6.6-11.2 months), and their mOS was 15.5 months (95% CI: 12.6-NA months). The mPFS of patients with mPC was 3.9 months (95% CI: 3.4-5.1 months), and their mOS was 9.3 months (95% CI: 8.0-10.8 months). Multivariate Cox regression analysis showed that clinical stage ( HR=1.47, 95% CI: 1.06-2.04), primary tumor site ( HR=0.64, 95% CI: 0.48-0.86), Eastern Cooperative Oncology Group Performance Status (ECOG PS) score ( HR=2.66, 95% CI: 1.53-4.65), and whether to combine radiotherapy ( HR=0.65, 95% CI: 0.42-1.00) were independent influencing factors for the PFS of these patients. The primary tumor site ( HR=0.68, 95% CI: 0.48-0.95), ECOG score ( HR=5.82, 95% CI: 3.14-10.82), and whether to combine radiotherapy ( HR=0.58, 95% CI: 0.35-0.96) were independent influencing factors of the OS of these patients. The most frequent gene mutations in these advanced stage pancreatic patients were KRAS (89.66%), TP53 (77.01%), CDKN2A (32.18%), and SMAD4 (21.84%) by NGS of tumor tissues from 87 pancreatic cancer patients with sufficient specimens. Further analysis revealed that mutations in CDKN2B, PTEN, FGF6, and RBBP8 genes were significantly associated with an increased risk of death ( P＜0.05). Conclusion:Albumin-bound paclitaxel as first-line treatment demonstrated feasible anti-tumor efficacy and manageable safety for patients with advanced pancreatic cancer in China.

Cognitive dysfunction refers to dysfunction of individual perception,memory,understanding,learning,creation and other dysfunctions caused by abnormal brain function and structure.Based on the fact that the spleen can't regulate transportation and transformation,govern blood and send up essential substance,combined with the microbiota-gut-brain axis,this article discussed the etiology and pathogenesis of intestinal flora imbalance affecting cognitive dysfunction in TCM.It was proposed that the spleen in TCM and intestinal flora are connected in physiology and pathology:the spleen regulates spirit and governs cognition,when the spleen fails to function normally that it can't dominate transportation and transformation,govern blood and send up essential substance will cause that the brain spirit can not be nourished;intestinal flora is closely related to the spleen in TCM,and affects brain function through the nervous system,endocrine,immune and metabolic mechanisms.This article can provide explore new ideas for the clinical research and treatment of cognitive dysfunction of traditional Chinese and Western medicine.

In recent years,radiation therapy has become a cornerstone in the treatment of head and neck tumors,significantly improving patient survival rates.However,the issue of radiation-induced carotid artery stenosis has garnered increasing attention.Characterized by multiple,long-segment,and unstable lesions,radiation-induced carotid stenosis presents unique challenges that traditional therapeutic approaches struggle to address.This review systematically summarized the pathological features and underlying mechanisms of radiation-induced carotid stenosis,with a focus on the roles of endothelial cells,smooth muscle cells,and vasa vasorum damage.Future research directions and preventive strategies are also discussed.

To analyze the prevalence, genomic characteristics and clinical relevance of carbapenem-resistant bacteria in untreated hospital wastewater, and to provide a reference basis for in-hospital assessment of public health situation and prevention of cross-infection. In March 2023, untreated wastewater in the wastewater treatment station of the Second Affiliated Hospital of Soochow University and wastewater in the U-shaped wastewater pipes of the hand-washing sinks in 26 wards were collected, centrifuged and diluted, and the drug-resistant bacteria were isolated by using LB solid plates containing meropenem (2 μg/ml) for species identification, drug sensitivity analysis, carbapenenase gene PCR detection and whole genome sequencing. The genome sequence was identified for drug resistance genes. Retrospective research was used, combining multilocus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis, to compare their homology with clinical isolates of the same quarter. The results showed that 56 carbapenem-resistant gram-negative bacteria were isolated from hospital wastewater, originating from 13 genera, of which 17 were isolated from the total hospital wastewater, with Aeromonas spp. as the most dominant genus (35.3%, 6/17), and 39 were isolated from the wastewater of 17 wards, with Pseudomonas spp. as the most dominant genus (30.8%, 12/39). All common wastewater isolates from our hospital were multidrug-resistant bacteria, with up to 100% resistant to some second-and third-generation cephalosporins. A total of 8 carbapenemase genes originated from wastewater isolates, including blaKPC, blaNDM, blaIMP, blaVIM, blaIND, blaOXA-58-like, blaOXA-48-like, and blaOXA-427-like. 39 wastewater isolates carried the carbapenemase genes, and the total wastewater of the hospital carried the highest isolation rate of blaKPC-2 bacteria (35.3%, 6/17) and the highest isolation rate of blaIMP-8 bacteria (31.8%, 7/22) were found in the wastewater from 26 wards. 14 wastewater isolates were found to carry both carbapenemase genes, with a total of 6 combinations. A new blaIMP-101 isoform was also identified for the first time. 4 wastewater isolates and 11 clinical isolates were screened for inclusion in the SNP analysis, in which only 15 SNPs differed between the two strains of ST11 Klebsiella pneumoniae of clinical and wastewater origin, which was highly homologous. In conclusion, the presence of multiple multi-drug resistant conditionally pathogenic bacteria in untreated hospital wastewater has the potential risk of spreading drug-resistant genes in the environment. The highly homologous Klebsiella pneumoniae isolated from hospital wastewater and clinics indicates the close association between hospital wastewater and clinical infections. Hospitals need to strengthen the monitoring of drug-resistant bacteria and drug-resistant genes in the wastewater environment, to prevent the widespread dissemination of drug-resistant bacteria and drug-resistant genes in hospital wastewater and to prevent nosocomial infections caused by drug-resistant bacteria in wastewater.

To analyze the prevalence, genomic characteristics and clinical relevance of carbapenem-resistant bacteria in untreated hospital wastewater, and to provide a reference basis for in-hospital assessment of public health situation and prevention of cross-infection. In March 2023, untreated wastewater in the wastewater treatment station of the Second Affiliated Hospital of Soochow University and wastewater in the U-shaped wastewater pipes of the hand-washing sinks in 26 wards were collected, centrifuged and diluted, and the drug-resistant bacteria were isolated by using LB solid plates containing meropenem (2 μg/ml) for species identification, drug sensitivity analysis, carbapenenase gene PCR detection and whole genome sequencing. The genome sequence was identified for drug resistance genes. Retrospective research was used, combining multilocus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis, to compare their homology with clinical isolates of the same quarter. The results showed that 56 carbapenem-resistant gram-negative bacteria were isolated from hospital wastewater, originating from 13 genera, of which 17 were isolated from the total hospital wastewater, with Aeromonas spp. as the most dominant genus (35.3%, 6/17), and 39 were isolated from the wastewater of 17 wards, with Pseudomonas spp. as the most dominant genus (30.8%, 12/39). All common wastewater isolates from our hospital were multidrug-resistant bacteria, with up to 100% resistant to some second-and third-generation cephalosporins. A total of 8 carbapenemase genes originated from wastewater isolates, including blaKPC, blaNDM, blaIMP, blaVIM, blaIND, blaOXA-58-like, blaOXA-48-like, and blaOXA-427-like. 39 wastewater isolates carried the carbapenemase genes, and the total wastewater of the hospital carried the highest isolation rate of blaKPC-2 bacteria (35.3%, 6/17) and the highest isolation rate of blaIMP-8 bacteria (31.8%, 7/22) were found in the wastewater from 26 wards. 14 wastewater isolates were found to carry both carbapenemase genes, with a total of 6 combinations. A new blaIMP-101 isoform was also identified for the first time. 4 wastewater isolates and 11 clinical isolates were screened for inclusion in the SNP analysis, in which only 15 SNPs differed between the two strains of ST11 Klebsiella pneumoniae of clinical and wastewater origin, which was highly homologous. In conclusion, the presence of multiple multi-drug resistant conditionally pathogenic bacteria in untreated hospital wastewater has the potential risk of spreading drug-resistant genes in the environment. The highly homologous Klebsiella pneumoniae isolated from hospital wastewater and clinics indicates the close association between hospital wastewater and clinical infections. Hospitals need to strengthen the monitoring of drug-resistant bacteria and drug-resistant genes in the wastewater environment, to prevent the widespread dissemination of drug-resistant bacteria and drug-resistant genes in hospital wastewater and to prevent nosocomial infections caused by drug-resistant bacteria in wastewater.

Acute lung injury (ALI), as a common clinical emergency, is pulmonary edema and diffuse lung infiltration caused by inflammation. The lack of non-invasive alert strategy, resulting in failure to carry out preventive treatment, means high mortality and poor prognosis. Stimulator of interferon genes (STING) is a key molecular biomarker of innate immunity in response to inflammation, but there is still a lack of STING-targeted strategy. In this study, a novel STING-targeted PET tracer, [¹⁸F]FBTA, was labeled with high radiochemical yield (79.7 ± 4.3%) and molar activity (32.5 ± 2.9 GBq/μmol). We confirmed that [¹⁸F]FBTA has a strong STING binding affinity (K_d = 26.86 ± 6.79 nmol/L) and can be used for PET imaging in ALI mice to alert early lung inflammation and to assess the efficacy of drug therapy. Our STING-targeted strategy also reveals that [¹⁸F]FBTA can trace ALI before reaching the computed tomography (CT) diagnostic criteria, and demonstrates its better specificity and distribution than [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG).

In recent years, artificial intelligence-related technologies have been deeply combined with many medical fields, and the intersection of medicine and engineering has become a hot topic. There are problems with heavy data and difficulty making decisions in orthopedic disease diagnosis and treatment. Machine learning is an important method of artificial intelligence. Since it can automatically analyze and predict medical big data, it is widely used in the field of orthopedics. It also assists physicians in completing disease diagnosis and treatment efficiently. In this review paper, the application and progress of machine learning in preoperative, intraoperative, and postoperative diagnosis and treatment in orthopedics are reviewed, providing new ways for exploring more rational diagnosis and treatment strategies.