OBJECTIVE To ensure the safety of patients’ drug use and control the risk of medical insurance expenditure by upgrading the pre-prescription review system to conduct pre-review on prescriptions from internet hospitals and external prescriptions， as well as to review the payment methods of drugs （including in-hospital and external drug dispensing）. METHODS The data interfaces of prescriptions from internet hospitals and external prescriptions were integrated to achieve real-time rational drug use intervention. Additionally， an intelligent review project for payment method was added to precisely intervene in the medical insurance payment methods of drugs. The effect of the system upgrade was evaluated by comparing the qualification rates of prescriptions from internet hospitals and external prescriptions and the suspected amounts of drug violations from January to April 2025 （before the system upgrade） and May to August 2025 （after the system upgrade）. RESULTS After the upgrade of the pre-prescription review system， the qualification rates of prescriptions from internet hospitals and external prescriptions increased by 3.5% [95% confidence interval （CI）＝0.3%-6.7%， P ＝0.037 ] ； the suspected amounts of drug violations decreased to 52.9% of the pre-upgrade level （95%CI＝31.6%-88.5%， P ＝0.026）， and the average monthly sequential decrease was 29.5% （95%CI＝12.2%-43.4%， P ＝0.012）. Moreover， the addition of the intelligent review project for payment methods promoted the management of off-label drug use in our hospital. After the upgrade， a total of 79 filling valid applications for off-label drug use were received and archived. CONCLUSIONS The upgrade of the pre-prescription review system effectively improves the review qualification rates of prescriptions from internet hospitals and external prescriptions and the accuracy of medical insurance payment for drugs， and strengthens the supervision of off-label drug use， achieving dual guarantees of clinical rationality and medical insurance compliance.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

Objective: To optimize the technology and process for recovering immune cells from discarded leukocyte filter through reverse flushing, and to investigate the effects of different reverse flushing solutions and physical conditions (temperature, soaking, and ultrasound) on the cell recovery rate. Additionally, to evaluate the feasibility and quality of isolating and culturing NK cells from the recovered cells. Methods: Normal saline, PBS, and PBS-EDTA were used as reverse flushing solutions to backwash the filter, and the white blood cell recovery rates were compared. The reverse flushing efficiency was optimized by adjusting the temperature of the reverse flushing solution, filter soaking treatment and ultrasonic treatment. The Ficoll separation method was employed to isolate peripheral blood mononuclear cells (PBMCs) from the elution solution and conduct in vitro expansion and culture. Lymphocyte subsets were identified and quantified using flow cytometry. Results: The physiological saline served as the backflush fluid was the most stable. The reverse temperature had a significant impact on the recovery rate of white blood cell subgroups. The recovery rates of lymphocytes and monocytes at 37℃ were significantly higher than those at 4℃ [(35.56±5.55)% vs (22.88±0.31)%, (32.42±4.82)% vs (8.00±1.6)%, t=5.581 and 5.758, respectively, both P<0.001)], and at 25℃ [(35.56±5.55)% vs (22.42±6.13)%, t=5.904, P<0.001; (32.4±4.82)% vs (21.11±1.23)%, t=2.629, P=0.030)]. The recovery rates of white blood cell subgroups after 37℃ immersion were higher than those after direct reverse flow at 37℃, but the difference was not statistically significant (P>0.05). The recovery rate of cells after ultrasonic immersion at 25℃ was further increased compared to that after immersion at 25℃, but the difference was not statistically significant (P>0.05). The purity of the NK cells obtained through sorting reached (94.2±4.5)%, and the viability was (94.8±0.9)%. After 15 days of culture, the cell count was expanded approximately 450 times, yielding more than 10 /mL highly active NK cells. Conclusion: By optimizing the backflushing process, immune cells can be efficiently recovered from discarded filters. The 37℃ backflow liquid has the best backflow effect; soaking and ultrasonic treatment can be used as auxiliary methods to improve recovery rates. The NK cells from this source have high purity, good activity, and strong expansion ability, and can be used as a reliable cell source for immunotherapy research, and in line with the circular economy concept of resource reuse.

Objective To analyze the basic conditions and pathological characteristics of the samples in the Human Brain Bank of Hebei Medical University,which were pathologically diagnosed as cerebral amyloid angiopathy,and to provide reference for the research of related diseases.Methods The basic data of gender,age,apolipoprotein E genotype,pathological classification of cerebral amyloid angiopathy,Alzheimer's disease-related pathological change score,comorbidities and other pathological information were analyzed.Results Up to October 2024,twenty samples were confirmed by pathological diagnosis,with a male to female ratio of 3:1 and an average age of(80.90±8.08)years.Involve three kinds of apolipoprotein E subtype,5 kinds of genotypes(ε2/ε3 xε2/ε4、ε3/ε3 xε3/ε4、ε4/ε4);There were 2 pathologic types,including 6 cases of type 1 and 14 cases of type 2.The pathological grade included 3 grades.The severity grade and subtype classification of cerebral amyloid vascular disease were correlated with the degree of pathological changes of Alzheimer's disease.Cerebral amyloid angiopathy samples could coexist with other degenerative diseases with high comorbidity.Conclusion The incidence of cerebral amyloid angiopathy is higher in the aged samples collected based on Brain Bank,which coexists with conditions such as Alzheimer's disease and microbleeds,etc.It provides more detailed pathological diagnosis basis for further scientific research sharing of samples.

Objective: To explore the therapeutic mechanism of puerarin in treating rheumatoid arthritis (RA) rats based on the serine/tyrosine protein kinase B (AKT)-phosphorylated forkhead box protein O1 (FOXO1)-interleukin-9 (AKT-FOXO1-IL-9) signaling pathway. Methods : 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . 36 rats were randomly divided into a blank group , a model group , a positive control group , and low , medium , and high dose groups of puerarin. Except for the blank group , the other groups were induced with type Ⅱ collagen to establish a RA rat model. After successful modeling , different doses of puerarin and methotrexate were given to treat the rats. The body mass and toe thickness of the rats were measured , and biochemical indicators of rat blood rheology were detected. X-ray was used to observe changes in rat joint morphology. Safranin green staining were used to observe the pathology of rat joint tissue. ELISA was used to detect the levels of IL-9 and rheumatoid factors in rat serum , and Western blot was used to detect changes in levels of AKT and FOXO1 . Results: Compared with the blank group , the model group had the lowest toe thickness , and X-ray images showed more obvious segmental stenosis and more severe marginal bone invasion ; scaly like changes appeared at the edges of joints stained with safranin green , accompanied by the exudation of inflammatory cells and increased proliferation and secretion of chondrocytes ; the expression levels of inflammatory factors IL-9 and rheumatoid factors were the highest , and the expression levels of AKT and FOXO1 proteins were the highest (P < 0. 05) . Compared with the model group , the toe thickness of rats treated with different doses of puerarin decreased ; X-ray images showed that the puerarin treatment group of rats showed improvement in plantar joint stenosis and marginal bone invasion ; the results of safranin green staining showed that after treatment with different doses of puerarin , the infiltration of inflammatory cells decreased , and the expression levels of inflammatory factor IL-9 , rheumatoid factors , AKT , and FOXO1 proteins decreased significantly ( P < 0. 05 ) , with the high-dose puerarin group showing the most significant difference. Compared with the high-dose puerarin group , the positive control group showed a significant decrease in the above results and statistical differences (P < 0. 05) . Conclusion Puerarin has a good therapeutic effect on rats with RA by inhibiting the AKT-FOXO1-IL-9 pathway. The high-dose puerarin group (60 mg/kg) has the best therapeutic effect and the results show a dose-response relationship.

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.

Current experimental and computational methods have limitations in accurately and efficiently classifying ion channels within vast protein spaces. Here we have developed a deep learning algorithm, GPT2 Ion Channel Classifier (GPT2-ICC), which effectively distinguishing ion channels from a test set containing approximately 239 times more non-ion-channel proteins. GPT2-ICC integrates representation learning with a large language model (LLM)-based classifier, enabling highly accurate identification of potential ion channels. Several potential ion channels were predicated from the unannotated human proteome, further demonstrating GPT2-ICC's generalization ability. This study marks a significant advancement in artificial-intelligence-driven ion channel research, highlighting the adaptability and effectiveness of combining representation learning with LLMs to address the challenges of imbalanced protein sequence data. Moreover, it provides a valuable computational tool for uncovering previously uncharacterized ion channels.

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence