ObjectiveTo investigate the microbial contamination status of commercially available ready-to-eat (RTE) foods in Songjiang District of Shanghai, to verify the potential food safety hazards, so as to provide a scientific basis for the local regulation of RTE foods and the prevention of foodborne diseases. MethodsA total of 882 food samples from 9 categories of RTE foods were collected in Shanghai from 2017 to 2022. Salmonella, Listeria monocytogenes, Vibrio parahaemolyticus, Staphyloccus aureus and Bacillus cereus were detected according to the standard operating procedures in the Manual for China National Food Contamination and Harmful Factors Risk Monitoring, and which were determined with reference to relevant standards. ResultsA total of 77 samples were found to carry foodborne pathogens, with a total detection rate of 8.73%. Among the 5 foodborne pathogens, Bacillus cereus had the highest detection rate (8.35%), followed by Vibrio parahaemolyticus (5.05%), and the difference of detection rates among the 5 foodborne pathogens was statistically significant (χ²=112.307, P<0.001). Among the 9 categories of RTE food products, the detection rate of foodborne pathogens in RTE fermented/non-fermented soybean products was the highest (27.50%), followed by cold noodles (17.33%) and raw edible aquatic products (9.50%), and the difference in the detection rates of foodborne pathogens among different RTE food categories was statistically significant (χ²=45.909, P<0.001). The detection rate of foodborne pathogens in the third quarter of the year was 10.99%, significantly higher than that in other quarters (χ²=10.329, P=0.016). The detection rate of foodborne pathogens in samples from supermarkets was highest (15.08%), followed by snack bars (11.58%), with a statistically significant difference (χ²=14.108, P=0.015). ConclusionFoodborne pathogens contamination is found in commercially available RTE foods in Songjiang District of Shanghai, especially in RTE fermented/non-fermented soybean products, RTE cold noodles and raw edible aquatic products from supermarkets, snack bars and farm products markets during summer and autumn. Therefore, it is crucial to strengthen supervision and management to avoid the foodborne diseases.

Objective To identify and analyze risk factors for acute renal failure (ARF) following lung transplantation and to develop a predictive model. Methods Data for this study were obtained from the United Network for Organ Sharing (UNOS) database, encompassing patients who underwent unilateral or bilateral lung transplantation between 2015 and 2022. We analyzed both preoperative and postoperative clinical characteristics of the patients. A combined approach utilizing random forest and least absolute shrinkage and selection operator (LASSO) regression was employed to identify key factors associated with the incidence of ARF post-transplantation, based on which a nomogram model was developed. The predictive performance of the constructed model was evaluated in both training and validation sets, using receiver operating characteristic (ROC) curves and area under the curve (AUC) metrics to verify and compare model effectiveness. Results A total of 15 110 lung transplantation patients were included in the study, consisting of6 041 males and 9 069 females, with a median age of 62.00 years (interquartile range: 54.00 to 67.00). The analysis revealed statistically significant differences between postoperative renal dialysis and non-dialysis patients regarding preoperative lung diagnosis, estimated glomerular filtration rate (eGFR), mechanical ventilation, preoperative ICU treatment, extracorporeal membrane oxygenation (ECMO) support, infections occurring within two weeks prior to transplantation, Karnofsky Performance Status (KPS) score, waitlist duration, double-lung transplantation, and ischemia time (P<0.05). Five key variables associated with ARF after lung transplantation were identified through random forest and LASSO regression: recipients’ eGFR, preoperative ICU treatment, ECMO support, bilateral lung transplantation, and ischemia time. A nomogram model was subsequently established. Model evaluation demonstrated that the constructed predictive model achieved high accuracy in both training and validation sets, with favorable AUC values, confirming its validity and reliability. Conclusion This study identifies common risk factors for ARF following lung transplantation and introduces an effective predictive model with potential clinical applications.

In recent years, robot-assisted esophagectomy has become increasingly widespread, but the esophagogastric anastomosis step remains relatively complex and cumbersome. Currently, commonly used gastrointestinal reconstruction anastomosis techniques include end-to-end anastomosis, end-to-side anastomosis, and side-to-side anastomosis. Depending on the anastomosis method, they can be further divided into manual anastomosis and mechanical anastomosis, with common instruments including circular staplers and linear staplers. In esophageal cancer surgery, the choice of esophagogastric anastomosis technique is typically based on the tumor’s location and size as well as the surgeon’s preference. Each anastomosis technique has its advantages and disadvantages. With continuous improvements in anastomosis techniques and updates in stapling instruments, the incidence of complications after esophagogastric anastomosis has been effectively reduced. However, safely and efficiently completing gastrointestinal reconstruction during surgery remains a significant challenge. Scholars have made extensive explorations in this field, actively proposing and achieving various reconstruction methods, leading to significant progress. This article reviews the research progress of robot-assisted esophagogastric anastomosis techniques from both the anastomosis techniques and methods perspectives.

ObjectiveTo investigate the role of 4-week high-intensity interval training (HIIT) in modulating the metabolic homeostasis of the pyruvate-lactate axis in the hippocampus of rats with chronic unpredictable mild stress (CUMS) to improve their depressive-like behavior. MethodsForty-eight SPF-grade 8-week-old male SD rats were randomly divided into 4 groups: the normal quiet group (C), the CUMS quiet group (M), the normal exercise group (HC), and the CUMS exercise group (HM). The M and HM groups received 8 weeks of CUMS modeling, while the HC and HM groups were exposed to 4 weeks of HIIT starting from the 5th week (3 min (85%-90%) S_max+1 min (50%-55%) S_max, 3-5 cycles, S_max is the maximum movement speed). A lactate analyzer was used to detect the blood lactate concentration in the quiet state of rats in the HC and HM groups at week 4 and in the 0, 2, 4, 8, 12, and 24 h after exercise, as well as in the quiet state of rats in each group at week 8. Behavioral indexes such as sucrose preference rate, number of times of uprightness and number of traversing frames in the absenteeism experiment, and other behavioral indexes were used to assess the depressive-like behavior of the rats at week 4 and week 8. The rats were anesthetized on the next day after the behavioral test in week 8, and hippocampal tissues were taken for assay. LC-MS non-targeted metabolomics, target quantification, ELISA and Western blot were used to detect the changes in metabolite content, lactate and pyruvate concentration, the content of key metabolic enzymes in the pyruvate-lactate axis, and the protein expression levels of monocarboxylate transporters (MCTs). Results4-week HIIT intervention significantly increased the sucrose preference rate, the number of uprights and the number of traversed frames in the absent field experiment in CUMS rats; non-targeted metabolomics assay found that 21 metabolites were significantly changed in group M compared to group C, and 14 and 11 differential metabolites were significantly dialed back in the HC and HM groups, respectively, after the 4-week HIIT intervention; the quantitative results of the targeting showed that, compared to group C, lactate concentration in the hippocampal tissues of M group, compared with group C, lactate concentration in hippocampal tissue was significantly reduced and pyruvate concentration was significantly increased, and 4-week HIIT intervention significantly increased the concentration of lactate and pyruvate in hippocampal tissue of HM group; the trend of changes in blood lactate concentration was consistent with the change in lactate concentration in hippocampal tissue; compared with group C, the LDHB content of group M was significantly increased, the content of PKM2 and PDH, as well as the protein expression level of MCT2 and MCT4 were significantly reduced. The 4-week HIIT intervention upregulated the PKM2 and PDH content as well as the protein expression levels of MCT2 and MCT4 in the HM group. ConclusionThe 4-week HIIT intervention upregulated blood lactate concentration and PKM2 and PDH metabolizing enzymes in hippocampal tissues of CUMS rats, and upregulated the expression of MCT2 and MCT4 transport carrier proteins to promote central lactate uptake and utilization, which regulated metabolic homeostasis of the pyruvate-lactate axis and improved depressive-like behaviors.

ObjectiveThis study aimed to investigate the effects of 4-week high-intensity interval training (HIIT) on synaptic plasticity in the prefrontal cortex (PFC) of rats exposed to chronic unpredictable mild stress (CUMS), and to explore its potential mechanisms. MethodsA total of 48 male Sprague-Dawley rats were randomly divided into 4 groups: control (C), model (M), control plus HIIT (HC), and model plus HIIT (HM). Rats in groups M and HM underwent 8 weeks of CUMS to establish depression-like behaviors, while groups HC and HM received HIIT intervention beginning from the 5th week for 4 consecutive weeks. The HIIT protocol consisted of repeated intervals of 3 min at high speed (85%-90% maximal training speed, S_max) alternated with one minute at low speed (50%-55% S_max), with 3 to 5 sets per session, conducted 5 d per week. Behavioral assessments and tail-vein blood lactate levels were measured at the end of the 4th and 8th weeks. After the intervention, rat PFC tissues were collected for Golgi staining to analyze synaptic morphology. Enzyme-linked immunosorbent assays (ELISA) were employed to detect brain-derived neurotrophic factor (BDNF), monocarboxylate transporter 1 (MCT1), lactate, and glutamate levels in the PFC, as well as serotonin (5-HT) levels in serum. Additionally, Western blot analysis was conducted to quantify the expression of synaptic plasticity-related proteins, including c-Fos, activity-regulated cytoskeleton-associated protein (Arc), and N-methyl-D-aspartate receptor 1 (NMDAR1). ResultsCompared to the control group (C), the CUMS-exposed rats (group M) exhibited significant reductions in sucrose preference rates, number of grid crossings, frequency of upright postures, and entries into and duration spent in open arms of the elevated plus maze, indicating marked depressive-like behaviors. Additionally, the group M showed significantly reduced dendritic spine density in the PFC, along with elevated levels of c-Fos, Arc, NMDAR1 protein expression, and increased concentrations of lactate and glutamate. Conversely, BDNF and MCT1 contents in the PFC and 5-HT levels in serum were significantly decreased. Following HIIT intervention, rats in the group HM displayed considerable improvement in behavioral indicators compared with the group M, accompanied by significant elevations in PFC MCT1 and lactate concentrations. Furthermore, HIIT notably normalized the expression levels of c-Fos, Arc, NMDAR1, as well as glutamate and BDNF contents in the PFC. Synaptic spine density also exhibited significant recovery. ConclusionFour weeks of HIIT intervention may alleviate depressive-like behaviors in CUMS rats by increasing lactate levels and reducing glutamate concentration in the PFC, thereby downregulating the overexpression of NMDAR, attenuating excitotoxicity, and enhancing synaptic plasticity.

Objective To explore predictive factors of severe community-acquired pneumonia (CAP) complicated with respiratory failure (RF) and to develop and internally validate a clinical prediction model. Methods A retrospective study was conducted on 350 patients with severe CAP admitted to Tianyou Hospital Affiliated to Wuhan University of Science and Technology from September 2022 to December 2024. Patients were randomly divided into a training set (n＝245) and a validation set (n＝105) in a 7∶3 ratio, and further categorized into RF and non-RF groups. LASSO regression was applied to optimize variable selection. Multivariate logistic analysis was used to construct the prediction model, followed by internal validation. Results Univariate regression analysis identified male, hypertension, diabetes, coronary heart disease, age, CURB-65 score, white blood cell count, neutrophil count, C-reactive protein (CRP), serum amyloid A, procalcitonin, and hospital stay as risk factors for RF in severe CAP, while albumin level was a protective factor. LASSO regression selected CURB-65 score, albumin level, and CRP for inclusion in the final model. The area under the receiver operating characteristic curve was 0.903 in the training set and 0.919 in the validation set. Calibration curve analysis demonstrated excellent agreement between predicted and observed probabilities in both sets, and Hosmer-Lemeshow goodness-of-fit tests indicated no significant deviations. Threshold probabilities ranged from 0.01 to 0.99 in both training and validation sets. Conclusions CURB-65 score, albumin level, and CRP are independent predictors of RF in severe CAP. The clinical prediction model based on these factors exhibits strong discrimination, calibration, goodness-of-fit, and clinical utility.

OBJECTIVE To systematically investigate the current status and effectiveness of the standardized on-the-job training program for community clinical pharmacists in Shanghai， and to provide a scientific basis for optimizing the training scheme. METHODS A questionnaire survey was conducted to collect the data from trainees and mentor pharmacists who participated in the program between 2016 and 2024. The survey examined their basic information， evaluations of the training scheme， satisfaction with training outcomes， and suggestions for improvement. Statistical analyses were also conducted. RESULTS A total of 420 valid responses were collected， including 340 from trainees and 80 from mentor pharmacists. Before training， only 30.29% of trainees were engaged in clinical pharmacy-related work， whereas this proportion increased to 73.24% after training. Most mentor pharmacists had extensive experience in clinical pharmacy （76.25% with ≥5 years of experience） and mentoring （78.75% with ≥3 teaching sessions）. Totally 65.59% of trainees and 55.00% of mentor pharmacists believed that blended training yielded the best learning outcomes. Over 80.00% of both trainees and mentor pharmacists considered the overall training duration， theoretical study time， and practical training time to be reasonable. More than 95.00% of trainees and mentor pharmacists agreed that the homework and assessment schemes were appropriate. Trainees rated the relevance of training content to their actual work highly （with an average relevance score ＞4.5）， though they perceived the chronic disease medication therapy management module as significantly more challenging than the prescription review and evaluation module and the home-based pharmaceutical care module. The average satisfaction score of trainees and mentor pharmacists with the training effectiveness of each project was above 4 points， indicating a high overall satisfaction. Inadequate provision of teaching resources was unanimously recognized by trainees and mentor pharmacists as the key area requiring improvement. CONCLUSIONS The standardized on-the-job training program for community clinical pharmacists in Shanghai has contributed to improving pharmaceutical services in community healthcare settings. However， ongoing improvements must concentrate on content design， resource development， and faculty cultivation.

Post-viral chronic fatigue syndrome （CFS） is a condition characterized by persistent fatigue during the recovery phase of infectious diseases. It is marked by prolonged duration， not be recovered by sleep， significant brain fog， and post-exertional malaise. This paper has proposed that the core pathogenesis lies in deficiency of pectoral and defensive qi， that is insufficiency in the generation and transformation of pectoral qi and disordered circulation of defensive qi. This results in a state of post-epidemic deficiency fatigue， where both physical form and qi are impaired. Pectoral and defensive qi thrive on "movement without depletion". Consequently， internal treatment emphasizes on replenishing original qi and promoting its circulation to restore pectoral qi by self-designed Pingbu Yihou Xulao Formula （平补疫后虚劳方）. External treatment focuses on regulating the qi collaterals to facilitate defensive qi circulation， achieved through practices such as Baduanjin exercises， maintaining regular daily activity， and breathing techniques to promote the smooth flow of defensive qi.

Quantum dots (QDs), nanoscale semiconductor crystals, have emerged as a revolutionary class of nanomaterials with unique optical and electrochemical properties, making them highly promising for applications in disease diagnosis and treatment. Their tunable emission spectra, long-term photostability, high quantum yield, and excellent charge carrier mobility enable precise control over light emission and efficient charge utilization, which are critical for biomedical applications. This article provides a comprehensive review of recent advancements in the use of quantum dots for disease diagnosis and therapy, highlighting their potential and the challenges involved in clinical translation. Quantum dots can be classified based on their elemental composition and structural configuration. For instance, IB-IIIA-VIA group quantum dots and core-shell structured quantum dots are among the most widely studied types. These classifications are essential for understanding their diverse functionalities and applications. In disease diagnosis, quantum dots have demonstrated remarkable potential due to their high brightness, photostability, and ability to provide precise biomarker detection. They are extensively used in bioimaging technologies, enabling high-resolution imaging of cells, tissues, and even individual biomolecules. As fluorescent markers, quantum dots facilitate cell tracking, biosensing, and the detection of diseases such as cancer, bacterial and viral infections, and immune-related disorders. Their ability to provide real-time, in vivo tracking of cellular processes has opened new avenues for early and accurate disease detection. In the realm of disease treatment, quantum dots serve as versatile nanocarriers for targeted drug delivery. Their nanoscale size and surface modifiability allow them to transport therapeutic agents to specific sites, improving drug bioavailability and reducing off-target effects. Additionally, quantum dots have shown promise as photosensitizers in photodynamic therapy (PDT). When exposed to specific wavelengths of light, quantum dots interact with oxygen molecules to generate reactive oxygen species (ROS), which can selectively destroy malignant cells, vascular lesions, and microbial infections. This targeted approach minimizes damage to healthy tissues, making PDT a promising strategy for treating complex diseases. Despite these advancements, the translation of quantum dots from research to clinical application faces significant challenges. Issues such as toxicity, stability, and scalability in industrial production remain major obstacles. The potential toxicity of quantum dots, particularly to vital organs, has raised concerns about their long-term safety. Researchers are actively exploring strategies to mitigate these risks, including surface modification, coating, and encapsulation techniques, which can enhance biocompatibility and reduce toxicity. Furthermore, improving the stability of quantum dots under physiological conditions is crucial for their effective use in biomedical applications. Advances in surface engineering and the development of novel encapsulation methods have shown promise in addressing these stability concerns. Industrial production of quantum dots also presents challenges, particularly in achieving consistent quality and scalability. Recent innovations in synthesis techniques and manufacturing processes are paving the way for large-scale production, which is essential for their widespread adoption in clinical settings. This article provides an in-depth analysis of the latest research progress in quantum dot applications, including drug delivery, bioimaging, biosensing, photodynamic therapy, and pathogen detection. It also discusses the multiple barriers hindering their clinical use and explores potential solutions to overcome these challenges. The review concludes with a forward-looking perspective on the future directions of quantum dot research, emphasizing the need for further studies on toxicity mitigation, stability enhancement, and scalable production. By addressing these critical issues, quantum dots can realize their full potential as transformative tools in disease diagnosis and treatment, ultimately improving patient outcomes and advancing biomedical science.