OBJECTIVE To explore a model for constructing a platform for medical institution formulation and provide insights for promoting their development. METHODS By systematically reviewing the development status and challenges of medical institution preparations in China， and based on the theory of industry-university-research collaborative innovation， the organizational structure， collaborative processes， and safeguard mechanisms of the platform were designed. RESULTS & CONCLUSIONS Medical institution formulations in China mainly faced challenges such as weak research and development （R&D） capacity， uneven quality standards， and blocked transformation pathways. This study established a full-chain， whole- industry collaborative innovation network covering the government， medical institutions， universities/research institutes， pharmaceutical enterprises， and the market， forming a new “government-industry-university-research-application” five-in-one platform model for medical institution formulations. By establishing mechanisms such as multi-entity collaborative cooperation， full- chain intellectual property management， contribution-based benefit distribution， staged risk-sharing， and third-party evaluation， the model clarified the responsibilities and collaborative pathways of all parties. The new model highlights the whole-process transformation of clinical experience-based prescriptions， enabling precise alignment between clinical needs and technological R&D， as well as between preparation achievements and industrial transformation. While breaking down the barriers of traditional platform construction， it effectively achieves optimal resource allocation and complementary advantages， addresses problems emerging in the development of medical institution preparations， and provides reference value for the formulation of relevant systems.

Objective To preliminarily investigate the safety and efficacy of donor pancreas needle biopsy in simultaneous pancreas-kidney transplantation. Methods Clinical data of 7 cases undergoing donor pancreas biopsy were collected retrospectively. All cases underwent donor pancreas biopsy before or during simultaneous pancreas-kidney transplantation. Frozen section or paraffin sectioning techniques were used for tissue preparation, and hematoxylin-eosin and Masson staining were performed to histologically evaluate the donor pancreas. The quality of donor pancreas was comprehensively assessed by combining histological findings with the donor's clinical data. Postoperative follow-up data of 5 simultaneous pancreas-kidney transplant recipients were collected to summarize the safety of donor pancreas biopsy and the prognosis of transplant recipients. Results The 7 pancreas donors were aged 28 to 62 years, with a body mass index ranging from 20.76 to 27.68 kg/m². Liver ultrasound indicated fatty liver in 3 cases, while pancreatic ultrasound did not reveal any significant abnormalities. Among them, biopsy was performed on 2 donors after completion of pancreatic procurement and processing, and the frozen section histology showed moderate acute pancreatitis changes (edema of acinar cells, necrosis and inflammatory cell infiltration). Combined with a serum amylase level elevated more than 3 times the upper limit of normal value, these two donor pancreases were finally discarded. The remaining 5 cases underwent biopsy immediately after pancreatic vascular anastomosis during simultaneous pancreas-kidney transplantation, and histological evaluation was performed on paraffin-embedded sections. No biopsy-related complications (such as bleeding, pancreatic fistula, etc.) occurred after transplantation. One recipient died of severe infection 2 months after transplantation, while the other 4 recipients were followed up for more than 5 years, with well-functioning transplant kidneys and pancreases. Conclusions Donor pancreas biopsy is relatively safe, and the risk of biopsy-related complications after transplantation is controllable. Comprehensive assessment of donor pancreas quality by combining histological evaluation with the donor's clinical indicators is conducive to improving the accuracy of donor pancreas selection and organ utilization.

OBJECTIVE To introduce the development of an intelligent prescription review decision-support system for anti-tumor drugs and assess its clinical application outcomes. METHODS Relevant data sources， including national and local pharmaceutical administration policies， clinical practice guidelines/consensus， hospital information systems data， and genetic testing results， were integrated. Adhering to the principles of structure， standardization and dynamic updating， a knowledge base covering chemotherapeutic， targeted and immunotherapeutic agents was constructed using a dual-dimensional modeling approach that combined “drug attributes” and “clinical contexts”. This knowledge base was then embedded into the hospital’s electronic medical order system to establish the prescription review decision-support system. The application and performance of the system were evaluated at Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine. RESULTS A knowledge base containing 18 318 prescription review rules for anti-tumor drugs was constructed， and a closed-loop prescription review system was successfully established， encompassing pre-prescription real-time intervention， in-process interactive review， and post-prescription evaluation and analysis. From 2021 to 2024， the system generated a total of 57 879 alerts for prescriptions of five typical categories of anti-tumor drugs. For platinum-containing prescriptions， 22 577 alerts were generated， with Cisplatin for injection （lyophilized） being the most frequently alerted drug （13 445 alerts）， and “ototoxicity risk due to combined use” alerts remained high （7 682 alerts）. For methotrexate-containing prescriptions， 3 721 alerts were recorded， primarily related to “precaution-related issues” （76.4%， 2 843/3 721）. For doxorubicin-containing prescriptions， 17 301 alerts were triggered， primarily related to “dosage and administration” （14 315 alerts）. For human epidermal growth factor receptor 2-targeted agents-containing prescriptions， 1 007 alerts were issued， mostly related to “reimbursement restrictions” （956 alerts）. For programmed death-1/programmed death-ligand 1 inhibitors-containing prescriptions， the alerts increased year by year， totaling 13 273 alerts， primarily related to “inappropriate indication” （9 118 alerts）. Over the 4 years， the physician response rates to system alerts were 21.4%， 27.1%， 33.5% and 51.6%， respectively. CONCLUSIONS An intelligent decision-support system for anti-tumor drug prescription review， encompassing a closed-loop process of “real-time pre-event intervention， interactive in-event prescription review， post-event evaluation and analysis”， has been successfully constructed and implemented throughout the entire workflow. There is a discernible trend in this hospital， where the focus on monitoring anti-tumor drugs is shifting towards immunotherapy drugs. Additionally， the acceptance rate of physicians regarding prescription review opinions has been steadily increasing year by year.

Objective To identify factors affecting and key environmental factors of the Oncomelania hupensis snail density in the Yangtze River Delta region using machine learning methods. Methods Administrative village-level O. hupensis snail survey data in the Yangtze River Delta (including Shanghai Municipality, Jiangsu Province, Zhejiang Province and Anhui Province) from 2011 to 2021 were retrieved from the Information Management System for Parasitic Disease Control of Chinese Center for Disease Control and Prevention. Environmental factor data were captured from the Google Earth Engine platform, including elevation, slope, terrain, normalized difference vegetation index (NDVI), vegetation type, soil type, total petroleum hydrocarbon (TPH), ammonium nitrogen, inorganic nitrogen, dissolved oxygen, pH of water, chemical oxygen demand (COD) and inorganic phosphorus, and climatic factor data in the study region were retrieved from the Copernicus Climate Data Store, including annual precipitation, aridity index and annual mean temperature (AMT). O. hupensis snail survey data in the Yangtze River Delta region from 2011 to 2021 were randomly divided into a training set (70%) and a test set (30%), and five machine learning models were selected for machine learning model construction and comparative analysis of the O. hupensis snail density using the software R 4.3.0, including random forest (RF), eXtreme gradient boosting (XGBoost), support vector machine (SVM), gradient boosting machine (GBM) and neural network (NN). The XGBoost model was employed to construct a predictive model for the O. hupensis snail density, and the impact of each environmental factor on O. hupensis snail distribution was quantified. The SHapley Additive exPlanations (SHAPs) values were calculated to estimate the average contribution of each variable to the model prediction, and the core environmental factors affecting the O. hupensis snail population density were screened. Results Among the five machine learning models, the XGBoost model exhibited the optimal comprehensive performance, with the coefficient of determination (R²) of 0.855, mean squared error (MSE) of 0.188, root mean squared error (RMSE) of 0.434 and mean absolute error (MAE) of 0.155, respectively. Analysis of factors affecting the O. hupensis snail density with the XGBoost model showed that among the 16 environmental factors, the top four high-impact factors ranked by SHAPs values included annual precipitation, elevation, aridity index and NDVI, with cumulative SHAPs contributions of 75%, which was higher than that of other environmental factors. If NDVI was higher than 0.6, the O. hupensis snail density increased with NDVI and peaked if NDVI was 0.8 (1.60 snails/0.1 m²). The O. hupensis snail density increased with elevation if the elevation ranged from 14 to 40 m, and slowly rose if the annual precipitation ranged from 900 to 1 300 mm, and then increased rapidly to the peak (1.52 snails/0.1 m²) if the annual precipitation ranged from 1 300 to 1 500 mm. In addition, the O. hupensis snail density increased rapidly to the maximum (1.60 snails/0.1 m²) if the aridity index ranged from 0.8 to 1.1, and decreased gradually if the aridity index exceeded 1.1. Conclusions The XGBoost model shows excellent performance in prediction of the O. hupensis snail density and identification of key environmental factors in the Yangtze River Delta region. Annual precipitation, elevation, aridity index and NDVI are key environmental factors affecting the distribution and density of O. hupensis snails in the Yangtze River Delta region.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective To explore the safety and feasibility of 5G remote robot-assisted thoracoscopic anatomic lobectomy and segmentectomy. Methods A retrospective analysis was conducted on patients who underwent 5G remote robot-assisted thoracoscopic anatomic lobectomy or segmentectomy between July and September 2024. The surgeries were performed collaboratively by Shanghai Chest Hospital, Affiliated Hospital of Yangzhou University, and The First Affiliated Hospital of Nanchang University. Perioperative outcomes were recorded and analyzed. Results Ten patients were included, comprising 4 anatomic lobectomies and 6 segmentectomies. The median age was 61.0 (56.0, 72.0) years. The median intraoperative bi-directional network latency was 52.5 (39.0, 54.0) ms. There were no instances of network interruption, robot-related adverse events, or conversions to open thoracotomy. The median postoperative chest tube drainage volume was 500.0 (375.0, 600.0) mL, and the median hospital stay was 5.5 (4.0, 6.0) days. No complications of Clavien-Dindo grade Ⅱor higher occurred. All patients were recurrence-free and alive during the 6-month postoperative follow-up period. Conclusion 5G remote robot-assisted thoracoscopic surgery demonstrates high safety and operational stability. This technology shows promising potential for clinical application and is worthy of further development and utilization.

Objective To investigate the effect and mechanism of methyl oxofulnonone A(META)on high glucose(HG)-induced H9c2 cell injury.Methods H9c2 cells were divided into control group(normal culture),model group(55 mmol·L-1 glucose)and experimental-L,-M,-H groups(55 mmol·L-1 glucose+12.5,25.0,50.0 μmol·L-1 META).Cell viability was detected by cell counting kit-8;intracellular reactive oxygen species(ROS)level was detected by DCFH-DA fluorescent probe;intracellular adenosine triphosphate(ATP)content was detected by luciferase;and autophagy-related protein expression was detected by Western blotting.Results The optical density values of 72-hour cells in the control group,model group and experimental-M,-H groups were 0.91±0.03,0.61±0.01,0.69±0.02 and 0.72±0.03;the ROS levels were(40.75±1.53)％,(43.73±1.30)％,(30.87±1.27)％and(28.28±1.43)％;the ATP contents were(8.16±0.71),(4.03±0.29),(5.29±0.31)and(5.83±0.31)nmol·mg-1;the relative expression levels of autophagy-related gene 5 protein were 1.05±0.06,1.46±0.09,0.98±0.11 and 0.89±0.09;the relative expression levels of ubiquitin-binding protein were 1.05±0.10,0.55±0.13,0.89±0.04 and 0.98±0.04;the ratios of microtubule-associated protein 1 light chain 3 11/Ⅰ protein were 1.09±0.09,1.82±0.05,1.67±0.29 and 1.09±0.15,respectively.Among the above indicators,there were statistically significant differences between the model group and the control and experimental-M,-H groups(P＜0.05,P＜0.01).Conclusion META significantly ameliorates H9c2 cardiomyocyte damage caused by high glucose,ameliorates oxidative stress,protects mitochondrial respiration and inhibits autophagy.

In recent years, significant progress has been made in the treatment of chronic constipation, with high-quality studies emerging in areas such as fecal microbiota transplantation (FMT), sacral neuromodulation (SNM), acupuncture, and surgical techniques. The therapeutic approach is shifting from a traditional "medication and surgery" model toward an integrated strategy that includes dietary and defecation habit adjustment, FMT, SNM, acupuncture, pharmacotherapy, and surgery. Although FMT can partially improve stool frequency and consistency, its standardization and long-term efficacy require further validation. SNM demonstrates limited effectiveness in treating chronic constipation and is relatively cost-inefficient. Electroacupuncture remains controversial, though some studies support its value. Biofeedback therapy is recommended by multiple guidelines as the first-line treatment for dyssynergic defecation (DD), with portable home-based biofeedback systems showing considerable potential. For internal rectal prolapse (IRP) and rectocele (RC), various surgical options exist without a clear superiority, though laparoscopic ventral rectopexy (VMR) is increasingly favored due to its low recurrence rate and high patient satisfaction. In the surgical management of slow transit constipation (STC), total colectomy with ileorectal anastomosis remains the mainstream approach, while subtotal colectomy is gaining attention as an alternative.

Objective To systematically review the safety of budesonide inhalation aerosol in the treatment of chronic obstructive pulmonary disease.Methods PubMed,Cochrane Library,Web of Science,Embase,CNKI,WanFang Data,VIP and SinoMed databases were electronically searched to collect randomized controlled trials on budesonide inhalation aerosol in the treatment of chronic obstructive pulmonary disease from inception to June 30,2024.Two reviewers independently screened literature,extracted data,and assessed the risk of bias of included studies.The Meta-analysis was performed by using RevMan 5.3 software.Results A total of 52 studies with 16,768 patients were included.Meta-analysis results showed that the incidence of respiratory system adverse drug reaction(ADR)was higher in the budesonide group than in the control group,with a statistically significant difference[OR=1.18,95％CI(1.10,1.27),P＜0.001].There was no statistically significant difference in the incidence of overall ADR,central and peripheral nervous system ADR,gastrointestinal system ADR,skin ADR,urinary system ADR,infectious disease ADR,and musculoskeletal system ADR between the two groups of patients(P＞0.05).According to the subgroup analysis of the treatment course,in the 3-6 month subgroup,the incidence of ADR was higher in the budesonide group than in the control group,with a statistically significant difference[OR=1.43,95％CI(1.18,1.74),P＜0.001].In the studies with a treatment duration of more than 6 months,the incidence of ADR was higher in the budesonide group than in the control group,with a statistically significant difference[OR=1.54,95％CI(1.16,2.03),P=0.002].In the study of unknown treatment course,the incidence of ADR in the budesonide group was lower than that in the control group,and the difference was statistically significant[OR=0.39,95％CI(0.20,0.76),P=0.005].In the studies with a treatment duration of less than 3 months,the incidence of ADR in the budesonidegroup was comparable to that in the control group(P＞0.05).Conclusion The incidence of respiratory ADR caused by budesonide is higher than that of the control group.Although the incidence of overall ADR is not statistically significant,the occurrence of systemic adverse reactions should continue to be closely monitored in the future treatment of chronic obstructive pulmonary disease.

The academic literature on near-infrared brain functional imaging in the field of resuscitation medicine published in the Web of Science core collection,MEDLINE and PubMed databases from January 2006 to May 2025 were collected,which underwent statistical and visualized analyses with CiteSpace and VOSviewer software in terms of annual publication trends,authors,countries/regions,institutions,co-cited literature and keyword co-occurrence,clustering and emergence.It was pointed out that the overall number of publications in this research field had been on the rise in the past two decades.Stroke patients were the core research group in this field,and cortical activation mechanisms had always been the focus of research.Motor imagery was a high-frequency research content in this field,and multimodal technology integration was the trend of research in this field.New research ideas and methods were provided for relevent research in the field of rehabilitation medicine in China.