Diagnosis-related groups (DRG) payment is an important component of deepening the reform of medical insurance payment methods. In June 2023, a tertiary hospital launched an intelligent DRG grouping audit system to enhance grouping accuracy. By establishing a multi departmental collaborative organizational structure, building a standardized knowledge base and a rule base covering five categories (diagnosis, fees, testing, nursing, and pathology), and integrating electronic medical records, medical orders, testing, and imaging data throughout the entire diagnosis and treatment process, the intelligent DRG grouping audit system with data collection, identification, extraction, comparison, and output modules was constructed to achieve intelligent audit. At the same time, it was formed a closed-loop management system for pre reporting quality control, in-process group entry control, and post data analysis and assessment, which would prevent the risk of differentiated behaviors such as high coding and high sets, and ensure the reasonable use of medical insurance funds. By January 2024, the system had covered 89 ADRG groups, and improved the efficiency and quality of DRG grouping audit. Compared with February to May 2023, the monthly average rejection rate of medical records on the first page decreased by 9.4% after the system was put into operation (June to December 2023), and core medical indicators such as the number of DRG groups, medical insurance settlement cases, and time consumption index continued to improve. The practical experience could provide reference and inspiration for other hospitals in China.

Objective:To evaluate the applicability of a new anti-G capability assessment trainer (AG-CAT) in high-performance (HP) anti-G maneuver training and positive pressure breathing for high-G (PHP) training for pilots.Methods:A total of 142 fighter pilots who were subjected to anti-G maneuver training at Dujiangyan Special Crew Sanatorium of PLA Air Force between January and November 2023 were enrolled. According to the Guidelines for Aviation Physiological Training, 123 pilots underwent both HP anti-G maneuver training and PHP positive pressure breathing training, 15 received only HP training, and 4 received only PHP training. Based on the training devices used, these pilots were divided into AG-CAT group and an anti-G and anti-hypoxia capability detection instrument (GHyCDI) group. The 2 groups were compared regarding the pedal force of lower limbs, blood pressure, and improvement of +G z tolerance during training. Results:Of the 138 pilots undergoing HP training, 88 used AG-CAT and 50 used GHyCDI. One hundred and twenty-seven pilots participated in PHP training, with 73 in the AG-CAT group and 54 in the GHyCDI group. During HP training, the pedal force of left lower limbs in the AG-CAT group was greater than that of the right limbs and of the GHyCDI group ( t=4.38, 2.64, P<0.001, =0.009). In PHP training, the AG-CAT group exhibited greater pedal force in left limbs than in right ones, while the GHyCDI group showed an opposite trend ( t=2.25, 3.37, P=0.029, 0.002). Systolic and diastolic blood pressures during HP training (with or without anti-G suits) were higher in the AG-CAT group than in the GHyCDI group ( t=3.50, 3.72, 2.55, 4.21, P=0.001,<0.001,=0.012,<0.001). Similarly, during PHP training, both systolic and diastolic pressures were higher in the AG-CAT group ( t=2.03, 3.81, P=0.045,<0.001). The AG-CAT group demonstrated superior improvements in +G z tolerance during HP training (without/with anti-G suits: Z=2.14, 3.21, P=0.049, 0.001) and PHP training ( Z=2.56, P=0.010) compared with the GHyCDI group. Conclusions:AG-CAT shows excellent applicability in aviation physiological training of pilots. Its ergonomic design, practical functionalities and enhanced compatibility with personnel protective equipment can better meet training requirements compared to conventional devices.

Metabolic dysfunction-associated fatty liver disease (MAFLD), characterized by fatty acid overload, secondary chronic inflammation, and fibrosis, has become the most prevalent chronic liver disease globally. While no effective pharmacotherapy exists for MAFLD, mitigating inflammatory responses represents a promising approach to preventing the progression from steatosis to severe steatohepatitis. The NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, which detects endogenous danger and stress signals, has emerged as a significant target for inflammatory disease treatment, as transcriptional inactivation of its components demonstrates the therapeutic potential for MAFLD. Natural products targeting NLRP3 inflammasome activation have shown promising efficacy in MAFLD therapy. This review synthesizes the current understanding of NLRP3 inflammasome activation and therapeutic targets for NLRP3 homeostasis. Additionally, natural products reported to inhibit NLRP3 inflammasome for MAFLD improvement are categorized according to their mechanisms of action. The review also addresses limitations and future directions regarding natural products targeting NLRP3 inflammasome in MAFLD treatment. Enhanced understanding of NLRP3 inflammasome activation mechanisms in MAFLD and the identification of novel natural products supported by mechanistic research will significantly advance MAFLD treatment.
Humans ; NLR Family, Pyrin Domain-Containing 3 Protein/immunology* ; Inflammasomes/metabolism* ; Biological Products/therapeutic use* ; Animals ; Fatty Liver/immunology*

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Diagnosis-related groups (DRG) payment is an important component of deepening the reform of medical insurance payment methods. In June 2023, a tertiary hospital launched an intelligent DRG grouping audit system to enhance grouping accuracy. By establishing a multi departmental collaborative organizational structure, building a standardized knowledge base and a rule base covering five categories (diagnosis, fees, testing, nursing, and pathology), and integrating electronic medical records, medical orders, testing, and imaging data throughout the entire diagnosis and treatment process, the intelligent DRG grouping audit system with data collection, identification, extraction, comparison, and output modules was constructed to achieve intelligent audit. At the same time, it was formed a closed-loop management system for pre reporting quality control, in-process group entry control, and post data analysis and assessment, which would prevent the risk of differentiated behaviors such as high coding and high sets, and ensure the reasonable use of medical insurance funds. By January 2024, the system had covered 89 ADRG groups, and improved the efficiency and quality of DRG grouping audit. Compared with February to May 2023, the monthly average rejection rate of medical records on the first page decreased by 9.4% after the system was put into operation (June to December 2023), and core medical indicators such as the number of DRG groups, medical insurance settlement cases, and time consumption index continued to improve. The practical experience could provide reference and inspiration for other hospitals in China.

Objective:To evaluate the applicability of a new anti-G capability assessment trainer (AG-CAT) in high-performance (HP) anti-G maneuver training and positive pressure breathing for high-G (PHP) training for pilots.Methods:A total of 142 fighter pilots who were subjected to anti-G maneuver training at Dujiangyan Special Crew Sanatorium of PLA Air Force between January and November 2023 were enrolled. According to the Guidelines for Aviation Physiological Training, 123 pilots underwent both HP anti-G maneuver training and PHP positive pressure breathing training, 15 received only HP training, and 4 received only PHP training. Based on the training devices used, these pilots were divided into AG-CAT group and an anti-G and anti-hypoxia capability detection instrument (GHyCDI) group. The 2 groups were compared regarding the pedal force of lower limbs, blood pressure, and improvement of +G z tolerance during training. Results:Of the 138 pilots undergoing HP training, 88 used AG-CAT and 50 used GHyCDI. One hundred and twenty-seven pilots participated in PHP training, with 73 in the AG-CAT group and 54 in the GHyCDI group. During HP training, the pedal force of left lower limbs in the AG-CAT group was greater than that of the right limbs and of the GHyCDI group ( t=4.38, 2.64, P<0.001, =0.009). In PHP training, the AG-CAT group exhibited greater pedal force in left limbs than in right ones, while the GHyCDI group showed an opposite trend ( t=2.25, 3.37, P=0.029, 0.002). Systolic and diastolic blood pressures during HP training (with or without anti-G suits) were higher in the AG-CAT group than in the GHyCDI group ( t=3.50, 3.72, 2.55, 4.21, P=0.001,<0.001,=0.012,<0.001). Similarly, during PHP training, both systolic and diastolic pressures were higher in the AG-CAT group ( t=2.03, 3.81, P=0.045,<0.001). The AG-CAT group demonstrated superior improvements in +G z tolerance during HP training (without/with anti-G suits: Z=2.14, 3.21, P=0.049, 0.001) and PHP training ( Z=2.56, P=0.010) compared with the GHyCDI group. Conclusions:AG-CAT shows excellent applicability in aviation physiological training of pilots. Its ergonomic design, practical functionalities and enhanced compatibility with personnel protective equipment can better meet training requirements compared to conventional devices.

Objective:To explore the genetic basis and clinical phenotype of a Chinese pedigree affected with Focal segmental glomerulosclerosis (FSGS).Methods:A male patient who was admitted to the First Affiliated Hospital of Zhengzhou University on July 26, 2018 was selected as the study subject. Clinical data of the patient was collected. Next generation sequencing and Sanger sequencing were carried out to detect the variant sites. Bioinformatic software was used to simulate the effect of candidate variants on the protein functions.Results:Ultrasound exam of the patient showed enhanced echo for the renal parenchyma. Kidney biopsy had confirmed the pathological diagnosis of FSGS (non-specific). Electronic microscopy displayed segmental sclerosis of the glomeruli, mild hyperplasia of mesangial cells and matrix. The proband was found to harbor two novel variants of the PLCE1 gene, namely c. 3199delA (p.N1067Mfs*15) and c.4441_4443delATC (p.1481_1481del), which were respectively inherited from his mother and father. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), both variants were rated as pathogenic (PVS1+ PM2_Supporting+ PP3; PM2_Supporting+ PM3+ PP3). Bioinformatic simulation suggested that both variants could significantly affect the tertiary structure of the PLCE1 protein. Conclusion:The c. 4441_4443delATC and c. 3199delA variants of the PLCE1 gene probably underlay the pathogenesis of the FSGS in this pedigree.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Purpose: The risk stratification of pediatric anaplastic large cell lymphoma (ALCL) has not been standardized. In this study, new risk factors were included to establish a new risk stratification system for ALCL, and its feasibility in clinical practice was explored. Materials and Methods: On the basis of the non-Hodgkin’s lymphoma Berlin–Frankfurt–Munster 95 (NHL-BFM-95) protocol, patients with minimal disseminated disease (MDD), high-risk tumor site (multiple bone, skin, liver, and lung involvement), and small cell/lymphohistiocytic (SC/LH) pathological subtype were enrolled in risk stratification. Patients were treated with a modified NHL-BFM-95 protocol combined with an anaplastic lymphoma kinase inhibitor or vinblastine (VBL). Results: A total of 136 patients were enrolled in this study. The median age was 8.8 years. The 3-year event-free survival (EFS) and overall survival of the entire cohort were 77.7% (95% confidence interval [CI], 69.0% to 83.9%) and 92.3% (95% CI, 86.1% to 95.8%), respectively. The 3-year EFS rates of low-risk group (R1), intermediate-risk group (R2), and high-risk group (R3) patients were 100%, 89.5% (95% CI, 76.5% to 95.5%), and 67.9% (95% CI, 55.4% to 77.6%), respectively. The prognosis of patients with MDD (+), stage IV cancer, SC/LH lymphoma, and high-risk sites was poor, and the 3-year EFS rates were 45.3% (95% CI, 68.6% to 19.0%), 65.7% (95% CI, 47.6% to 78.9%), 55.7% (95% CI, 26.2% to 77.5%), and 70.7% (95% CI, 48.6% to 84.6%), respectively. At the end of follow-up, one of the five patients who received maintenance therapy with VBL relapsed, and seven patients receiving anaplastic lymphoma kinase inhibitor maintenance therapy did not experience relapse. Conclusion This study has confirmed the poor prognostic of MDD (+), high-risk site and SC/LH, but patients with SC/LH lymphoma and MDD (+) at diagnosis still need to receive better treatment (ClinicalTrials.gov number, NCT03971305).