Background Bacteria are the most diverse and widely sourced microorganisms in the indoor air of subway stations, where pathogenic bacteria can spread through the air, leading to increased health risks. Objective To understand the status and distribution characteristics of indoor air bacterial pollution in subway stations and compartments in a city of Central South China, and to provide a scientific basis for formulating intervention measures to address indoor air bacteria pollution in subways. Methods Three subway stations and the compartments of trains parking there in a city in Central South China were selected according to passenger flow for synchronous air sampling and monitoring. Temperature, humidity, wind speed, carbon dioxide (CO₂), fine particulate matter (PM_2.5), and inhalable particulate matter (PM₁₀) were measured by direct reading method. In accordance with the requirements of Examination methods for public places-Part 3: Airborne microorganisms (GB/T 18204.3-2013), air samples were collected at a flow rate of 28.3 L·min⁻¹, and total bacterial count was estimated. Bacterial microbial species were identified with a mass spectrometer and pathogenic bacteria were distinguished from non-pathogenic bacteria according to the Catalogue of pathogenic microorganisms transmitted to human beings issued by National Health Commission. Kruskal-Wallis H test was used to compare the subway hygiene indicators in different regions and time periods, and Bonferroni test was used for pairwise comparison. Spearman correlation test was used to evaluate the correlation between CO₂ concentration and total bacterial count. Results The pass rates were 100.0% for airborne total bacteria count, PM_2.5, and PM₁₀ in the subway stations and train compartments, 94.4% for temperature and wind speed, 98.6% for CO₂, but 0% for humidity. The overall median (P₂₅, P₇₅) total bacteria count was 177 (138,262) CFU·m⁻³. Specifically, the total bacteria count was higher in station halls than in platforms, and higher during morning peak hours than during evening peak hours (P<0.05). A total of 874 strains and 82 species were identified by automatic microbial mass spectrometry. The results of identification were all over 9 points, and the predominant bacteria in the air were Micrococcus luteus (52.2%) and Staphylococcus hominis (9.8%). Three pathogens, Acinetobacter baumannii (0.3%), Corynebacterium striatum (0.1%), and Staphylococcus epidermidis bacilli (2.2%) were detected in 23 samples (2.6%), and the associated locations were mainly distributed in train compartments during evening rush hours. Conclusion The total bacteria count in indoor air varies by monitoring sites of subway stations and time periods, and there is a risk of opportunistic bacterial infection. Attention should be paid to cleaning and disinfection during peak passenger flow hours in all areas.

As an emerging discipline that combines traditional diagnostic methods with modern scientific technology,micro syndrome differentiation has good prospects for development,but there are some controversies in the research process.Based on ancient and modern literature,this article reviewed the origin and flow of research on micro syndrome differentiation,and summarized the problems to be improved in the process of research on micro syndrome differentiation from three aspects:application of disease type,guiding ideology and micro indicators.Based on this,the article further expounded the new thinking on"near-micro"syndrome differentiation from three aspects:connotation,scope of application,and links to traditional identification and micro-identification,and pointed out that the modern medical detection basis should be incorporated into the field of TCM syndrome differentiation,and at the same time,it should be based on the overall thinking mode of TCM,which would provide a new idea for the development of modern TCM diagnosis technology.

Objective To build a dataset encompassing a large number of stained tongue coating images and process it using deep learning to automatically recognize stained tongue coating images. Methods A total of 1 001 images of stained tongue coating from healthy students at Hunan University of Chinese Medicine and 1 007 images of pathological(non-stained)tongue coat-ing from hospitalized patients at The First Hospital of Hunan University of Chinese Medicine with lung cancer,diabetes,and hypertension were collected.The tongue images were randomi-zed into the training,validation,and testing datasets in a 7:2:1 ratio.A deep learning model was constructed using the ResNet50 for recognizing stained tongue coating in the training and validation datasets.The training period was 90 epochs.The model's performance was evaluated by its accuracy,loss curve,recall,F1 score,confusion matrix,receiver operating characteristic(ROC)curve,and precision-recall(PR)curve in the tasks of predicting stained tongue coating images in the testing dataset.The accuracy of the deep learning model was compared with that of attending physicians of traditional Chinese medicine(TCM). Results The training results showed that after 90 epochs,the model presented an excellent classification performance.The loss curve and accuracy were stable,showing no signs of overfitting.The model achieved an accuracy,recall,and F1 score of 92%,91%,and 92%,re-spectively.The confusion matrix revealed an accuracy of 92%for the model and 69%for TCM practitioners.The areas under the ROC and PR curves were 0.97 and 0.95,respectively. Conclusion The deep learning model constructed using ResNet50 can effectively recognize stained coating images with greater accuracy than visual inspection of TCM practitioners.This model has the potential to assist doctors in identifying false tongue coating and prevent-ing misdiagnosis.

More than 70%of tumor patients require radiotherapy.Medical electron linear accelerators are important high-end radiotherapy equipment for tumor radiotherapy.With the application of artificial intelligence technology in medical electron linear accelerator,radiotherapy has evolved from ordinary radiotherapy to today's intelligent radiotherapy.This study introduces the development history,working principles and system composition of medical electron linear accelerators.It outlines the key technologies for improving the performance of medical linear electron accelerators,including beam control,multi-leaf collimator,guiding technology and dose evaluation.It also looks forward to the development trend of major radiotherapy technologies,such as biological guided radiotherapy,FLASH radiotherapy and intelligent radiotherapy,which provides references for the development of medical electron linear accelerators.

Objective:To explore the risk factors related to delayed pleural effusion in multiple trauma patients.Methods:A retrospective cohort study was conducted to analyze the clinical data of 145 multiple trauma patients admitted to the First Affiliated Hospital of Soochow University from January 2022 to October 2023, including 99 males and 46 females, aged 18-81 years [56.0(46.5, 64.5)years]. Based on whether delayed pleural effusion developed after injury, the patients were divided into delayed pleural effusion group ( n=66) and non-delayed pleural effusion group ( n=79). The clinical data of the patients in both groups were collected, including gender, age, underlying disease (diabetes mellitus and hypertension), cause of injury (traffic injury, blow injury, fall from height, and others), comorbid injuries (traumatic brain injury, maxillofacial fracture, clavicular fracture, scapular fracture, sternal fracture, spinal fracture, multiple rib fracture, pneumothorax, lung contusion, and pelvic fracture), severity of injury [injury severity score (ISS) and abbreviated injury scale (AIS) score for the chest], location and number of rib fractures, vital signs at admission (body temperature, heart rate, respiration, systolic blood pressure, diastolic blood pressure), and clinical test indices [white blood cells (WBC), hemoglobin (Hb), platelets (PLT), total protein (TP), albumin (ALB), C-reactive protein (CRP), procalcitonin (PCT), fibrinogen (FIB), fibrin degradation product (FDP), D-dimer (D-D), aspartate transaminase (AST), alanine transferase (ALT), and creatinine (Cr)]. Univariate analysis was conducted to assess the correlation between the forementioned factors and the development of delayed pleural effusion after multiple traumas. Multivariate Logistic regression analysis was used to determine the independent risk factors for the development of delayed pleural effusion after multiple traumas. Results:The results of univariate analysis showed that multiple rib fracture, pneumothorax, pulmonary contusion, chest AIS score, posterior rib fracture, number of rib fractures, TP, ALB, CRP, PCT and FDP were correlated with delayed pleural effusion in multiple trauma patients ( P<0.05 or 0.01); whereas gender, age, underlying disease, cause of injury, sternal fracture, spinal fracture, clavicular fracture, scapular fracture, pelvic fracture, maxillofacial fracture, traumatic brain injury, anterior rib fracture, ISS, vital signs at admission, WBC, Hb, PLT, FIB, D-D, AST, ALT, and Cr were not correlated with delayed pleural effusion in multiple trauma patients ( P>0.05). The results of multivariate Logistic regression analysis revealed that lung contusion ( OR=3.96, 95% CI 1.59, 9.85, P<0.01), ALB ( OR=0.79, 95% CI 0.66, 0.94, P<0.01), and CRP ( OR=1.02, 95% CI 1.01, 1.03, P<0.01) were significantly correlated with delayed pleural effusion in multiple trauma patients. Conclusion:Lung contusion, ALB, and CRP are the independent risk factors for delayed pleural effusion in multiple trauma patients.

OBJECTIVE To study the unknown impurity in potassium aspartate and magnesium aspartate injection by heart-cutting two-dimensional liquid chromatography coupled with Quadrupole time-of-flight mass spectrometry (2D-LC-Q-TOF-MS). METHODS The Waters ACQUITY UPLC 2D system and Xevo G2-XS QTof-MS system were used. One- dimensional chromatographic conditions were as listed. An Agilent ZORBAX-NH2 column was used, and potassium dihydrogen thophosphate(0.05 mol·L-1)-acetonitrile(37∶63) as the mobile phase, at a flow rate of 1.3 mL·min-1. The detection wavelength was set at 200 nm. Two-dimensional chromatographic conditions were as listed. A Waters ACQUITY UPLC HSS T3 column was used, and 0.1% formic acid solution(ESI+)/5 mmol·L-1 ammonium formate(ESI-) as the mobile phase A, and acetonitrile as the mobile phase B, in gradient mode. The mass spectrometry used an electro spray ionization source(ESI) for positive and negative ion mode detection. RESULTS Combined the high resolution mass, MS2 fragment ions and the UNIFI software, the possible structure of the unknown impurity in potassium aspartate and magnesium aspartate injection was infered. CONCLUSION The 2D-LC-Q-TOF-MS method can be used to identify impurities in potassium aspartate and magnesium aspartate injection, which provides reference for the improvement of quality control and process optimization of potassium aspartate and magnesium aspartate injection.

Background::Understanding the characteristics of newly diagnosed primary human deficiency virus-1 (HIV-1) infection in the context of the post-antiretroviral therapy era and HIV drug prophylaxis is essential for achieving the new target of 95-95-95-95 by 2025. This study reported the characteristics of newly diagnosed primary HIV-1 infection in Shenzhen.Methods::This is a real-world retrospective study. Eighty-seven newly diagnosed primary HIV-1-infected patients were recruited from January 2021 to March 2022 at the Third People’s Hospital of Shenzhen. Demographic, epidemiological, diagnostic, drug resistance, and medical data were described and analyzed.Results::Overall, 96.6% (84/87) of the newly identified primary HIV-1-infected patients were male, including 88.5% (77/87) men have sex with men (MSM), with a median age of 29.0 years (Q 1-Q 3: 24.0-34.0 years); of these, 85.1% (74/87) reported high-risk sexual behaviors with casual partners. The rate of condom usage was only 28.7% (25/87). The overall rate of pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP) was 8.0% (7/87, including 4 PrEP and 3 PEP cases) around the potential exposure, although 41.4% of the patients had prior awareness of such interventions. Moreover, only 19.5% (17/87) had previously used PrEP or PEP. Of those, 58.8% (10/17) of the patients obtained drugs from the internet, and only 35.3% (6/17) reported good compliance. A total of 54.0% (47/87) of subjects were diagnosed by the HIV nucleic acid test. Acute retroviral syndrome appeared in 54.0% (47/87) of patients. The prevalence of transmitted drug resistance (TDR) mutation was 33.9% (19/56), including 6 (10.7%) against nucleoside reverse transcriptase inhibitor (NRTI) plus non-nucleoside reverse transcriptase inhibitor (NNRTI), 8 (14.3%) against NNRTI, and 5 (8.9%) against protease inhibitor (PI) only. Conclusions::Owing to the low utilization rate and incorrect usage of PrEP and PEP, massive efforts are needed to promote HIV-preventive strategies in the MSM population. The extremely high prevalence of TDR mutation in this population implies the need for future pretreatment drug resistance surveillance.

In order to afford new antiplatelet agents with higher potency, a series of paeonol oxime derivatives (4a-4y) were designed and synthesized from paeonol.Their structures were confirmed by HRMS, 1H NMR spectra.The anti-platelet aggregation activity of the target compounds was evaluated.The results revealed that most of them had moderate to good anti-platelet aggregation activity.Among them, compound 4h and 4j were the most potent on adenosine diphosphate (ADP)-induced platelet aggregation and collagen-induced platelet aggregation. Furthermore, the target compound 4h not only showed strong antiplatelet aggregation activity, but also exhibited good water-solubility and drug-like properties, which can be used as a new antiplatelet active compound for further research.

Abdomen/diagnostic imaging* ; Artificial Intelligence ; Body Composition ; Magnetic Resonance Imaging ; Practice Guidelines as Topic

Objective:To investigate the differences of gastric mucosa microbiota between children with chronic gastritis and duodenal ulcer under the condition of Helicobacter pylori (Hp) infection. Methods:This prospective cohort study involved 57 children with Hp infection diagnosed by gastric endoscopy who were admitted to the Children′s Hospital of Zhejiang University School of Medicine due to "abdominal pain, abdominal distension and vomiting" between January 2018 to August 2018. According to gastroscopy and pathological examination, the children were divided into chronic gastritis group and duodenal ulcer group. Gastric mucosa from Hp infected patients were sampled, and the flora DNA was analyzed by high-throughput sequencing. The statistical difference of α diversity, β diversity between two groups were analyzed. The relative abundance of the two groups in each taxonomic level was analyzed statistically. T test, Rank sum test or χ 2 test was used for comparison between the two groups. Results:A total of 57 children diagnosed with Hp infection were enrolled in this study, including 42 cases of chronic gastritis (the age was (9.3±2.8) years, 22 males and 20 females) and 15 cases of duodenal ulcer (the age was (11.1±3.3) years, 9 males and 6 females). Alpha diversity index Chao and ACE in Hp infected chronic gastritis group were significantly higher than those in Hp infected duodenal ulcer group (217±50 vs. 183±64, t=2.088, P=0.009;218±47 vs. 192±76, t=1.566, P=0.016, respectively). The Beta-diversity index such as nonmetric multidimensional scaling (NMDS) analysis were significantly different in the two groups (analysis of similarity R=0.304, P=0.028). Among the main bacteria genera, there were 6 genera with significant differences between the two groups, which were Prevotella (0.190% (0.008%-1.983%) vs. 0.021% (0.005%-2.398%), Z=-2.537, P=0.011), Alloprevotella (0.097% (0.010%-0.813%) vs. 0.015% (0.003%-0.576%), Z=-2.492, P=0.013), Haemophilus (0.109% (0.004%-0.985%) vs. 0.014% (0.004%-0.356%), Z=-2.900, P=0.004), Neisseria (0.074% (0.004%-0.999%) vs. 0.024% (0.003%-0.255%), Z=-2.718, P=0.007), Streptococcus (0.166% (0.008%-1.869%) vs. 0.045% (0.006%-0.879%), Z=-2.537, P=0.010), and an unclassified- Microbacteriaceae (0.214% (0.060%-1.762%) vs. 0.117% (0.010%-0.954%), Z=-2.120, P=0.034). Linear discriminant analysis (LDA) effect sized analysis showed that at the genus level, only Prevotella was significantly enriched in the duodenal ulcer group (LDA=2.90, P=0.010), while Streptococcus, Neisseria and Haemophilus were significantly enriched in the chronic gastritis group (LDA=2.83, 2.82, 2.69, P=0.011, 0.007, 0.004, respectively). Conclusions:The gastric mucosal microbiota in duodenal ulcer associated with Hp is significantly different from that in chronic gastritis. Hp may promote the occurrence of peptic ulcer together with gastric microbiota.