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.

ObjectiveTo analyze the infection characteristics of human respiratory syncytial virus (HRSV) among children hospitalized with acute lower respiratory tract infection (ALRTI) in a specialized pediatric hospital in Shanghai, so as to provide evidence-based support for optimizing the prevention and control strategies and clinical diagnosis and treatment of respiratory tract infections in children in this region. MethodsA retrospective analysis was performed to the clinical and etiological data of 29 260 children hospitalized for ALRTI in Shanghai Children’s Hospital from January 2021 to December 2024. HRSV and 12 other common respiratory pathogens were detected with multiplex polymerase chain reaction (PCR) and capillary electrophoresis. Demographic and clinical data were collected for statistical analyses. A total of2 412 cases with positive HRSV were divided into the severe group and the non-severe group. Clinical characteristics between the two groups were compared using the Mann-Whitney U test and the chi- square (χ²) test. Additionally, the related influencing factors of severe HRSV infection were explored. ResultsThe overall positivity rate of HRSV from 2021 to 2024 was 8.24% (2 412/29 260), with statistically significant differences observed across the four years (χ²=389.42, P<0.001). The highest positivity rate was in 2021 (14.76%), with a high prevalence throughout the year. In 2022, when non-pharmaceutical interventions (NPIs) were implemented, the HRSV positivity rate was the lowest (4.93%), with a winter-dominant epidemic pattern. In 2023, after the NPIs were lifted, the HRSV positivity rate showed a slight rebound (8.14%), presenting a double-peak pattern. In 2024, the HRSV positivity rate slightly decreased compared to that in 2023 (6.29%), exhibiting a winter and spring-dominant epidemic pattern. Among the hospitalized children with ALRTI, the HRSV positivity rate in males (8.85%) was higher than that in females (7.51%), and the difference was statistically significant (χ²=17.33, P<0.001). Age distribution showed that 82.26% (1 984/2 412) of HRSV infections occurred in children aged 3 years old and below. Besides, as age increased, the infection rate of HRSV showed a gradually decreasing trend (P<0.001). Among the 2 412 children with HRSV infection, the proportion of severe cases was 22.31% (538/2 412), while the non-severe cases accounted for 77.69% (1 874/2 412). Compared with non-severe cases, severe cases were more frequently presented with high fever, longer duration of wheezing, as well as higher rates of underlying diseases or co-infection with Mycoplasma pneumoniae (P<0.001). ConclusionThe prevalence intensity of HRSV varied yearly from 2021 to 2024. After the removal of NPIs in 2023, a slight rebound with a double-peak epidemic pattern was observed. HRSV remained a common pathogen in children hospitalized for ARLTI, and children aged 3 years old and below constituted the highest proportion for infection. Compared with non-severe cases, those with severe HRSV infections were more prone to presenting with high fever and a longer duration of wheezing. Children with positive HRSV who had underlying diseases or co-infection with Mycoplasma pneumonia were more likely to develop severe conditions.

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 investigate the factors affecting the distribution of Pomacea and project the trends in the spread of suitable distribution areas of Pomacea in 2050 and 2070 in Dali Bai Autonomous Prefecture, so as to provide insights into Pomacea control in the prefecture. Methods The longitudes and latitudes of Pomacea sampling sites were captured based on Pomacea field survey data in 12 cities (counties) of Dali Bai Autonomous Prefecture from 2023 to 2024. A total of 19 climatic factors (annual mean temperature, mean diurnal range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the warmest month, mean temperature of the coldest month, annual precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, mean temperature of the warmest quarter, and mean temperature of the coldest quarter) and representative concentration pathways (RCPs) were retrieved from the world climate database (www.worldclim.org). All climatic variables were employed to create a maximum entropy (MaxEnt) model. The predictive accuracy of the model was assessed with the area under the receiver operating characteristic (ROC) curve (AUC), and the contributions of these 19 climatic factors to the distribution of Pomacea were analyzed in Dali Bai Autonomous Prefecture using Jackknife test. In addition, the suitable distribution areas of Pomacea were predicted with the MaxEnt model in Dali Bai Autonomous Prefecture in 2024 and in 2050 and 2070 under RCP4.5. Results Data pertaining to 91 Pomacea sampling sites were captured. ROC analysis revealed the MaxEnt model had an AUC value of 0.885 ± 0.088 for predicting the suitable distribution areas of Pomacea in Dali Bai Autonomous Prefecture. Of the 19 climatic factors, the maximum temperature of the warmest month had the highest contribution to the distribution of Pomacea in Dali Bai Autonomous Prefecture, followed by mean temperature of the driest quarter, mean temperature of the wettest quarter and minimum temperature of the coldest month. The suitable distribution area of Pomacea was predicted to be 14 555.69 km² in Dali Bai Autonomous Prefecture in 2024, and would expand gradually to the southeastern part of the prefecture in the future due to climatic factors. The suitable distribution areas of Pomacea were projected to expand to 21 475.61 km² in 2050 and 25 782.52 km² in 2070 in Dali Bai Autonomous Prefecture, respectively. Conclusions Temperature is an important contributor to the distribution of Pomacea in Dali Bai Autonomous Prefecture, and the suitable distribution area of Pomacea will gradually expand to the southeastern part of the prefecture in 2050 and 2070.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

ObjectiveTo investigate the protective effects and mechanisms of Zhenzhu Tiaozhi capsules on the kidneys in the mouse model of diabetic kidney disease. MethodsThirty male C57BL/6J mice were selected as experimental objects. The model of diabetic kidney disease was induced by intraperitoneal injection of streptozotocin （STZ） at 40 mg·kg^-1 for 5 days combined with a high-fat diet （HFD）. Fasting blood glucose （FBG） ≥ 11.1 mmol·L^-1， increased urine volume， and continuous appearance of proteinuria indicated successful modeling. Mice were grouped as follows： Blank， model， low- and high-dose （0.98 and 1.96 g·kg^-1， respectively） Zhenzhu Tiaozhi capsules， and losartan potassium （30 mg·kg^-1）， with six mice in each group. After 12 weeks of continuous gavage， urine and kidney specimens were collected， and the 24-h urinary protein and the urinary albumin-to-creatinine ratio （UACR） in mice were measured. Hematoxylin-eosin （HE） staining， periodic acid-Schiff （PAS） staining， and Masson staining were performed for observation of histopathological changes in kidneys. Immunofluorescence assay was employed to detect the positive expression of the podocyte marker protein nephrin. Oil red O staining was used to detect renal lipid deposition. Enzyme linked immunosorbent assay was employed to measure the levels of interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and tumor necrosis factor-α （TNF-α） in the renal tissue. Western blot was employed to determine the expression levels of sterol regulatory element-binding protein cleavage-activating protein （SCAP）， sterol regulatory element-binding protein-1c （SREBP-1c）， and NOD-like receptor protein 3 （NLRP3） in the renal tissue. ResultsCompared with the blank group， the model group showed increases in 24-h urinary protein and UACR （P<0.05）， glomeruli exhibiting capsule adhesion， collagen fiber deposition， mesangial proliferation， and inflammatory cell infiltration， elevated levels of IL-1β， IL-6， and TNF-α （P<0.05）， reduced positive expression of nephrin （P<0.05）， increased lipid deposition （P<0.05）， and up-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. Compared with the model group， the treatment with losartan potassium or high-dose Zhenzhu Tiaozhi capsules for 12 weeks decreased 24-h urinary protein and UACR （P<0.05）， and the treatment with low-dose Zhenzhu Tiaozhi capsules for 12 weeks reduced the 24-h urinary protein （P<0.05）. Pathological staining results revealed that kidney damage in mice from all treatment groups was alleviated， with reduced inflammatory infiltration， collagen fiber deposition， and mesangial proliferation， and increased positive expression of nephrin in the renal tissue （P<0.05）. In addition， all the treatment groups showed reduced lipid droplets （P<0.05）， lowered levels of IL-1β， IL-6， and TNF-α （P<0.05）， and down-regulated expression of SCAP， SREBP-1c， and NLRP3 （P<0.05） in the renal tissue. ConclusionZhenzhu Tiaozhi capsules can ameliorate kidney damage in the mouse model of diabetic kidney disease by inhibiting the activation of the SCAP-SREBP-1c/NLRP3 signaling pathway， which reduces renal lipid deposition and inflammation.

Schistosomiasis is prevalent in 78 countries and territories worldwide, while the eastern and western parts of sub-Sahara Africa bear the highest disease burden due to schistosomiasis. Recently, climate change, international trade and travel, urbanization and war have increased the risk of cross-boundary importation and transmission of schistosomiasis, and schistosomiasis has increasingly become a public health concern in non-endemic countries and territories. Biomphalaria straminea, the intermediate host of Schistosoma mansoni, has colonized in southern China and its habitats continue to move northward. In addition, cross-boundary imported cases of schistosomiasis have been reported occasionally in China. However, the real number of cases may be underestimated greatly due to insufficient diagnostic capacity and weak awareness of case reporting for overseas imported schistosomiasis in healthcare facilities. It is necessary to establish a multi-party collaborative mechanism, improve corresponding systems and technical specifications, reinforce surveillance and early warning, and border management, enhance technical reserves and capability building, and improve the awareness of schistosomiasis prevention and healthcare-seeking among entry-exit personnel, in order to effectively address the threat of cross-boundary imported schistosomiasis.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

BACKGROUND: There is little literature describing the artificial intelligence (AI)-aided diagnosis of severe pneumonia (SP) subphenotypes and the association of the subphenotypes with the ventilatory treatment efficacy. The aim of our study is to illustrate whether clinical and biological heterogeneity, such as ventilation and gas-exchange, exists among patients with SP using chest computed tomography (CT)-based AI-aided latent class analysis (LCA). METHODS: This retrospective study included 413 patients hospitalized at Xinhua Hospital diagnosed with SP from June 1, 2015 to May 30, 2020. AI quantification results of chest CT and their combination with additional clinical variables were used to develop LCA models in an SP population. The optimal subphenotypes were determined though evaluating statistical indicators of all the LCA models, and clinical implications of them such as guiding ventilation strategies were further explored by statistical methods. RESULTS: The two-class LCA model based on AI quantification results of chest CT can describe the biological characteristics of the SP population well and hence yielded the two clinical subphenotypes. Patients with subphenotype-1 had milder infections ( P <0.001) than patients with subphenotype-2 and had lower 30-day ( P <0.001) and 90-day ( P <0.001) mortality, and lower in-hospital ( P = 0.001) and 2-year ( P <0.001) mortality. Patients with subphenotype-1 showed a better match between the percentage of non-infected lung volume (used to quantify ventilation) and oxygen saturation (used to reflect gas exchange), compared with patients with subphenotype-2. There were significant differences in the matching degree of lung ventilation and gas exchange between the two subphenotypes ( P <0.001). Compared with patients with subphenotype-2, those with subphenotype-1 showed a relatively better match between CT-based AI metrics of the non-infected region and oxygenation, and their clinical outcomes were effectively improved after receiving invasive ventilation treatment. CONCLUSIONS A two-class LCA model based on AI quantification results of chest CT in the SP population particularly revealed clinical heterogeneity of lung function. Identifying the degree of match between ventilation and gas-exchange may help guide decisions about assisted ventilation.
Humans ; Tomography, X-Ray Computed/methods* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Artificial Intelligence ; Aged ; Pneumonia/diagnosis* ; Latent Class Analysis ; Adult