BACKGROUND:Radiotherapy significantly improves survival rates in patients with various malignant tumors.However,with prolonged post-treatment survival,many patients face the risk of radiation-related cardiac toxicity.This is especially true after chest radiotherapy,where the risk of radiation-induced heart disease significantly increases,becoming one of the most severe complications affecting prognosis survival.OBJECTIVE:To identify diagnostic markers of endothelial cellular senescence in radiation-induced heart disease through systematic transcriptomic analysis.METHODS:Firstly,genes associated with cellular senescence were screened from the CellAge database and intersected with the transcriptomic training dataset of a mouse model of radiation-induced heart disease to identify differentially expressed senescence-related genes.Secondly,weighted gene co-expression network analysis and machine learning were used to identify key hub genes that play critical roles in radiation-induced heart disease.The expression of these genes was validated using a dataset of radiation-induced endothelial injury.Additionally,the quanTlseq method was employed to assess the immune infiltration status related to radiation-induced heart disease.The expression levels of key genes and their association with survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy were explored through the analysis of The Cancer Genome Atlas database.RESULTS AND CONCLUSION:(1)Systematic transcriptomic analysis identified CCND1 as the core gene of endothelial cellular senescence in radiation-induced heart disease,and this finding was validated in the mouse model of radiation-induced heart disease.(2)The diagnostic model constructed from these data indicated that CCND1 had high specificity and sensitivity for diagnosing radiation-induced heart disease.(3)Immune infiltration analysis revealed significant immune response dysregulation in the mouse model of radiation-induced heart disease,and CCND1 was closely related to various immune cells.(4)Kaplan-Meier survival analysis showed that CCND1 was associated with poorer disease-specific survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy.This study systematically uncovers,for the first time,the pivotal role of CCND1 in endothelial cell senescence associated with radiation-induced heart disease.CCND1,a gene integral to cell cycle regulation,can induce cellular senescence when abnormally expressed.Furthermore,the findings highlight its potential as an early diagnostic marker.

BACKGROUND:Radiotherapy significantly improves survival rates in patients with various malignant tumors.However,with prolonged post-treatment survival,many patients face the risk of radiation-related cardiac toxicity.This is especially true after chest radiotherapy,where the risk of radiation-induced heart disease significantly increases,becoming one of the most severe complications affecting prognosis survival.OBJECTIVE:To identify diagnostic markers of endothelial cellular senescence in radiation-induced heart disease through systematic transcriptomic analysis.METHODS:Firstly,genes associated with cellular senescence were screened from the CellAge database and intersected with the transcriptomic training dataset of a mouse model of radiation-induced heart disease to identify differentially expressed senescence-related genes.Secondly,weighted gene co-expression network analysis and machine learning were used to identify key hub genes that play critical roles in radiation-induced heart disease.The expression of these genes was validated using a dataset of radiation-induced endothelial injury.Additionally,the quanTlseq method was employed to assess the immune infiltration status related to radiation-induced heart disease.The expression levels of key genes and their association with survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy were explored through the analysis of The Cancer Genome Atlas database.RESULTS AND CONCLUSION:(1)Systematic transcriptomic analysis identified CCND1 as the core gene of endothelial cellular senescence in radiation-induced heart disease,and this finding was validated in the mouse model of radiation-induced heart disease.(2)The diagnostic model constructed from these data indicated that CCND1 had high specificity and sensitivity for diagnosing radiation-induced heart disease.(3)Immune infiltration analysis revealed significant immune response dysregulation in the mouse model of radiation-induced heart disease,and CCND1 was closely related to various immune cells.(4)Kaplan-Meier survival analysis showed that CCND1 was associated with poorer disease-specific survival in esophageal squamous cell carcinoma patients receiving chest radiotherapy.This study systematically uncovers,for the first time,the pivotal role of CCND1 in endothelial cell senescence associated with radiation-induced heart disease.CCND1,a gene integral to cell cycle regulation,can induce cellular senescence when abnormally expressed.Furthermore,the findings highlight its potential as an early diagnostic marker.

Artificial intelligence (AI) technology enhances the function of acupuncture clinical decision support system (CDSS) by promoting the accuracy of its diagnosis, assisting the formulation of personalized therapeutic regimen, and realizing the scientific and precise evaluation of its therapeutic effect. This paper deeply analyzes the unique advantages of AI-based acupuncture CDSS, including the intelligence and high efficiency. Besides, it points out the challenges of data security, the lack of model interpretation and the complexity of interdisciplinary cooperation in the development of acupuncture CDSS. With the continuous development and improvement of AI technology, acupuncture CDSS is expected to play a more important role in the fields of personalized medicine, telemedicine and disease prevention, and to further advance the efficiency and effect of acupuncture treatment, drive the modernization of acupuncture, and enhance its position and influence in the global healthcare system.
Humans ; Acupuncture Therapy ; Artificial Intelligence ; Decision Support Systems, Clinical

BACKGROUND: Generalized pustular psoriasis (GPP), a rare and recurrent autoinflammatory disease, imposes a substantial burden on patients and society. Awareness of GPP in China remains limited. METHODS: This cross-sectional survey, conducted between September 2021 and May 2023 across 14 hospitals in China, included GPP patients of all ages and disease phases. Data collected encompassed demographics, clinical characteristics, economic impact, disease severity, quality of life, and treatment-related complications. Risk factors for GPP recurrence were analyzed. RESULTS: Among 127 patients (female/male ratio = 1.35:1), the mean age of disease onset was 25 years (1st quartile [Q1]-3rd quartile [Q3]: 11-44 years); 29.2% had experienced GPP for more than 10 years. Recurrence occurred in 75.6% of patients, and nearly half reported no identifiable triggers. Younger age at disease onset ( P  = 0.021) and transitioning to plaque psoriasis ( P  = 0.022) were associated with higher recurrence rates. The median diagnostic delay was 8 months (Q1-Q3: 2-41 months), and 32.3% of patients reported misdiagnoses. Comorbidities were present in 53.5% of patients, whereas 51.1% experienced systemic complications during treatment. Depression and anxiety affected 84.5% and 95.6% of patients, respectively. During GPP flares, the median Dermatology Life Quality Index score was 19.0 (Q1-Q3: 13.0-23.5). This score showed significant differences between patients with and without systemic symptoms; it demonstrated correlations with both depression and anxiety scores. Treatment costs caused financial hardship in 55.9% of patients, underscoring the burden associated with GPP. CONCLUSIONS The substantial disease and economic burdens among Chinese GPP patients warrant increased attention. Patients with early onset disease and those transitioning to plaque psoriasis require targeted interventions to mitigate the high recurrence risk.
Humans ; Male ; Female ; Psoriasis/pathology* ; Adult ; Cross-Sectional Studies ; Adolescent ; Child ; Young Adult ; Quality of Life ; Middle Aged ; China/epidemiology* ; Recurrence ; Risk Factors ; Surveys and Questionnaires ; East Asian People

ObjectiveTo explore the effects of the Tai Chi training on bone density， bone turnover markers， and heart rate variability for people with high-risk osteoporosis， and to provide evidence for the prevention of osteoporosis at early stage. MethodsSixty-six cases of people with high risk of osteoporosis were included， and they were divided into 33 cases each in the intervention group and the control group using the random number table method. The control group received osteoporosis health education three times a week， and the intervention group received Tai Chi training under the guidance of a trainer three times a week for 40 mins each time on the basis of the control group， and both groups were intervened for 12 weeks. Dual-energy X-ray absorptiometry was used to measure the bone density of L₁~L₄ vertebrae， bilateral femoral necks and bilateral total hips in the two groups before and after the intervention； enzyme-linked immunosorbent assay was used to determine bone turnover markers before and after the intervention， including pro-collagen type Ⅰ pro-amino-terminal prepropyl peptide （P1NP） and β-collagen type Ⅰ cross-linking carboxy-terminal peptide （β-CTX）. Seven cases with good compliance in the intervention group were selected. After wearing the heart rate sensor， they successively performed Tai Chi training and walking activities recommended by the guideline for 20 mins each， and the heart rate variability （HRV） during exercise was collected， including time-domain indexes such as standard deviation of normal sinus intervals （SDNN）， root-mean-square of the difference between adjacent RR intervals （RMSSD）， frequency-domain metrics such as low-frequency power （LF）， high-frequency power （HF）， and low-frequency/high-frequency power ratio （LF/HF）， as well as nonlinear metrics such as approximate entropy （ApEn）， sample entropy （SampEn）. ResultsFinally， 63 cases were included in the outcome analysis， including 30 cases in the intervention group and 33 cases in the control group. After the intervention， the differences of L₁~L₄ vertebrae， bone density of bilateral femoral neck and bilateral total hip in the intervention group were not statistically significant when compared with those before intervention （P＞0.05）， while the bone density of all parts of the control group decreased significantly compared with that before intervention （P＜0.05）， and the difference in the bone density of the L₁~L₄ vertebrae， bilateral femoral neck， and the right total hip before and after the intervention of the intervention group was smaller than that of the control group （P＜0.05）. The differences in P1NP and β-CTX between groups before and after intervention was not statistically significant （P＞0.05）. Compared with walking exercise， LF decreased， HF increased and LF/HF decreased during Tai Chi exercise （P＜0.05）； the time domain indexes and non-linear indexes between groups had no statistically significant difference （P＞0.05）. ConclusionTai Chi exercise can maintain lumbar， hip， and femoral bone density and improve sympathetic/parasympathetic balance in people at high risk for osteoporosis， but cannot significantly improve bone turnover markers.

OBJECTIVE To provide reference for the establishment and optimization of add-on payment policy in China. METHODS The two-party evolutionary game model was constructed， involving medical insurance and medical institutions，and simulation experiments were conducted. The effects of factors such as whether the establishment of add-on payment policy by the medical insurance department， the compensation ratio， and the cost and incremental utility of new technology on the adoption of innovative technologies by medical institutions were analyzed under the backdrop of the reform of the diagnosis-related groups （DRG） payment system. RESULTS & CONCLUSIONS The add-on payment policy can effectively incentivize the utilization of innovative technologies， but it also carries the risk of overuse or misuse of new technologies. The compensation ratio， unit price of new technology， and cost savings derived from the improved effectiveness of new technologies， as well as the incremental utility of new technology， will all affect the equilibrium state of the evolutionary game， potentially even reversing it. It is recommended to optimize the selection criteria for the scope of add-on payment， so as to incentivize the use of innovative technologies while controlling the risk of their misuse. Additionally， a reasonable approach should be taken to adopt either standalone payment or supplementary payment models based on the surplus level of medical insurance funds in the coordinated regions. Meanwhile， a regular adjustment mechanism should be established to ensure smooth integration between the add-on payment and the DRG payment system.

Objective To investigate the effects of Toxoplasma gondii type Iand IIrhoptry protein 16 (ROP16) on the polarization and inflammatory response of mouse alveolar macrophages, so as to provide the scientific evidence for unveiling the immunoregulatory mechanisms following T. gondii infection in host cells and the clinical diagnosis and treatment of pulmonary toxoplasmosis. MethodsMouse alveolar macrophages served as blank controls, and mouse alveolar macrophages transfected with the empty lentiviral expression vector served as negative controls, and mouse alveolar macrophages transfected with lentiviral vectors overexpressing T. gondii type I and II ROP16 served as the type I and II ROP16 overexpression groups. Following puromycin selection, stably transfected cells that overexpressed type Iand IIROP16 were generated, observed for green fluorescence expression under a fluorescence microscope and verified using PCR, Western blotting and real-time quantitative reverse transcription PCR (RT-qPCR) assays. The expression of ROP16, inducible nitric oxide synthase (iNOS), arginase (Arg)-1, mannose receptor (CD206), cluster of differentiation 86 (CD86), NOD-like receptor thermal protein domain associated protein 3 (NLRP3), caspase-1, apoptosis-associated speck-like protein containing a CARD (ASC), and interleukin (IL)-1β proteins was determined in mouse alveolar macrophages using Western blotting assay, and the mRNA levels of ROP16, iNOS, IL-1β, IL-4, IL-12, IL-18, Arg-1, IL-10, IL-6, tumor necrosis factor (TNF)-α and transforming growth factor (TGF)-β were detected in mouse alveolar macrophages using RT-qPCR assay. Results Fluorescence microscopy showed 90% of mouse alveolar macrophages producing green fluorescent signals in the type Iand II ROP16 overexpression groups and the negative control group. The relative ROP16 protein expression was 1.000 ± 0.000, 1.003 ± 0.020, 1.349 ± 0.055, and 1.376 ± 0.080 in mouse alveolar macrophages in the blank control group, negative control group, and type Iand IIROP16 overexpression groups (F = 35.30, P < 0.01), and the relative ROP16 mRNA expression was 1.007 ± 0.172, 2.030 ± 0.356, 1 409.579 ± 75.960, and 1 413.581 ± 27.712 in the blank control group, negative control group, and type Iand II ROP16 overexpression groups (F = 811.00, P < 0.01). The ROP16 expression was significantly higher in the type Iand IIROP16 overexpression groups than in the blank control group at both protein and mRNA levels (all P value < 0.01). Western blotting assay detected significant differences among the four groups in terms of iNOS, Arg-1, CD86, CD206, NLRP3, caspase-1, ASC, and IL-1β protein expression (F = 124.70, 82.40, 79.82, 919.40, 84.74, 39.85, 2 354.00 and 65.96, all P values < 0.05), and the expression of Arg-1, CD206, NLRP3, caspase-1, ASC, and IL-1β proteins was significantly higher in the type I ROP16 overexpression group than in the blank control group (all P values < 0.001), while the expression of iNOS, CD86, NLRP3, caspase-1, ASC, and IL-1β proteins was significantly higher in the type II ROP16 overexpression group than in the blank control group (all P values < 0.01). RT-qPCR assay detected significant differences among the four groups in terms of iNOS, IL-1β, IL-4, IL-12, IL-18, Arg-1, IL-10, IL-6, TNF-α, and TGF-β mRNA expression (F = 407.00, 1 528.00, 833.10, 267.90, 989.80, 161.80, 461.10, 5 529.00, 849.60 and 8 836.00, all P values < 0.05), and the Arg-1, IL-4, IL-10, and TGF-β mRNA expression was significantly higher in the type I ROP16 overexpression group than in the blank control group (all P values < 0.001), while the iNOS, IL-1β, IL-12, IL-18, IL-6, and TNF-α mRNA expression was significantly higher in the type II ROP16 overexpression group than in the blank control group (all P values < 0.001). Conclusions T. gondii type IROP16 may induce M2-dominant phenotypes of mouse alveolar macrophages, and type II ROP16 may induce M1-dominant phenotypes of mouse alveolar macrophages. Both T. gondii type I and II ROP16 may activate NLRP3, and mediate the activation of ASC, caspase-1 and IL-1β to promote inflammatory responses.

OBJECTIVE To explore the pharmacokinetic characteristics of 3 blood-absorbed components of Xiangshao sanjie oral liquid in rats with hyperplasia of mammary gland （HMG）. METHODS Female SD rats were divided into control group and HMG group according to body weight， with 6 rats in each group. The HMG group was given estrogen+progesterone to construct HMG model. After modeling， two groups were given 1.485 g/kg of Xiangshao sanjie oral liquid （calculated by crude drug） intragastrically， once a day， for 7 consecutive days. Blood samples were collected before the first administration （0 h）， and at 5， 15， 30 minutes and 1， 2， 4， 8， 12， 24 hours after the last administration， respectively. Using chlorzoxazone as the internal standard， the plasma concentrations of ferulic acid， paeoniflorin and rosmarinic acid in rats were detected by UPLC-Q/TOF-MS. The pharmacokinetic parameters [area under the drug time curve （AUC0－24 h， AUC0－∞）， mean residence time （MRT0－∞）， half-life （t1/2）， peak time （tmax）， peak concentration （cmax）] were calculated by the non-atrioventricular model using Phoenix WinNonlin 8.1 software. RESULTS Compared with the control group， the AUC0－24 h， AUC0－∞ and cmax of ferulic acid in the HMG group were significantly increased （P＜0.05）； the AUC0－24 h， AUC0－∞ ， MRT0－∞ ， t1/2 and cmax of paeoniflorin increased， but there was no significant difference between 2 groups （P＞0.05）； the AUC0－24 h and MRT0-∞ of rosmarinic acid were significantly increased or prolonged （P＜0.05）. C ONCLUSIONS In HMG model rats， the exposure of ferulic acid， paeoniflorin and rosmarinic acid in Xiangshao sanjie oral liquid all increase， and the retention time of rosmarinic acid is significantly prolonged.

Objective To observe the effects of Yixintai on lipid metabolism and the protein expressions of CPT-1 and CD36 in rats with heart failure;To explore the mechanism of its treatment of heart failure.Methods 106 out of 120 SD rats were selected to establish the heart failure model induced by myocardial infarction by ligating the left anterior descending coronary artery,and 14 rats were selected as the sham-operation group.The successful model rats were randomly divided into model group,trimetazidine group and Yixintai low-,medium-and high-dosage groups,with 14 rats in each group.The administration group was given corresponding drugs by gavage once a day for 4 weeks.LVEF,LVFS,LVIDd and LVIDs were measured by color doppler ultrasonography,the contents of ANP,BNP,LA and FFA in serum were detected by ELISA,the contents of TG,TC,LDL and HDL were detected by automatic biochemical analyzer,HE and Masson staining were used to observe the morphology of myocardial tissue,the expressions of CPT-1 and CD36 protein in myocardial tissue were detected by Western blot.Results Compared with the sham-operation group,LVEF and LVFS in the model group decreased(P<0.05),the LVIDs and LVIDd increased(P<0.05);the contents of serum ANP,BNP,LA,FFA,TG,TC and LDL increased(P<0.05),while the content of HDL decreased(P<0.05),with myocardial edema,irregular arrangement of myocardial fibers,increased inflammatory cell infiltration and collagen fiber deposition;the protein expressions of CPT-1 and CD36 in myocardial tissue decreased(P<0.05).Compared with the model group,the LVEF and LVFS in Yixintai each dosage groups and trimetazidine group increased(P<0.05),LVIDs and LVIDd decreased(P<0.05);the contents of ANP,BNP,LA,FFA,TG,TC and LDL in serum of Yixintai medium-and high-dosage groups and trimetazidine group decreased(P<0.05),the content of HDL increased(P<0.05);myocardial edema was improved,inflammatory cell infiltration was reduced,collagen fiber deposition was reduced,and the protein expressions of CPT-1 and CD36 in myocardial tissue increased(P<0.05).Conclusion Yixintai may improve myocardial energy metabolism and treat heart failure by increasing the expression of CPT-1 and CD36 protein in myocardial tissue and promoting fatty acid β oxidation.

Objective:To construct classification models of traumatic brain injury (TBI) based on the injury data collected at the scene of the accidents and validate its efficacy.Methods:A retrospective cohort study was conducted to analyze the pre-hospital treatment data of 368 TBI patients admitted to the Second Affiliated Hospital of Army Military Medical University from January 2019 to December 2023, including 243 males and 125 females, aged 18-82 years [(48.1±20.8)years]. The patients′ Glasgow coma scale (GCS) scores were 3-15 points [11.0(3.0, 15.0)points] at emergency medical service arrival. The patients were randomly assigned to the training set ( n=257) and test set ( n=111) at a ratio of 7∶3. According to the admission diagnosis, the patients fell into the mild TBI group ( n=62), medium TBI group ( n=137), severe TBI group ( n=120), and extremely severe TBI group ( n=49). In the training set, 44 patients fell into mild TBI group, 98 into medium TBI group, 82 into severe TBI group and 33 into extremely severe TBI group, while in the test set, 18 patients fell into mild TBI group, 39 into medium TBI group, 38 into severe TBI group and 16 into extremely severe TBI group. The following 12 kinds of injury data, including MARCH [massive hemorrhage (M), airway obstruction (A), respiratory failure (R), circulatory failure (C) and hypothermia (H)], GCS, pre-hospital index (PHI), shock index (SI), reverse SI multiplied by GCS (rSIG), optic nerve sheath diameter (ONSD) measured by ultrasound, scalp and skull injuries were collected at the scene of the accidents. Three machine algorithm including random forest (RF), support vector machine (SVM) and logistic regression (LR) were used to construct scene data-based TBI classification models. The accuracy rate, precision rate, recall rate, F1 value and area under receiver operating characteristic (ROC) curve (AUC) of the 3 models were used to verify the efficiency of the models for TBI classification. Shapley additive explanations (SHAP) method was used to interpret the results of the optimal model. The 12 kinds of injury data in the models were sorted according to their contribution to the TBI classification and the injury data with greater contribution were selected. Results:In the test set, the accuracy rate of the RF, SVM and LR models was 0.93, 0.92 and 0.87, respectively; the precision rate was 0.93, 0.92 and 0.89, respectively; the recall rate was 0.93, 0.92 and 0.87, respectively; the F1 value was 0.93, 0.92 and 0.87, respectively. In the mild, medium, severe and extremely severe TBI groups in the test set, the AUC of the RF model was 0.96 (95% CI 0.92, 0.98), 0.98 (95% CI 0.94, 0.99), 0.97 (95% CI 0.95, 0.98), and 0.97 (95% CI 0.96, 0.98), respectively; the AUC of the SVM model was 0.90 (95% CI 0.88, 0.94), 0.95 (95% CI 0.92, 0.97), 0.96 (95% CI 0.94, 0.98), and 0.95 (95% CI 0.92, 0.99), respectively; the AUC of the LR model was 0.90 (95% CI 0.83, 0.96), 0.90 (95% CI 0.84, 0.95), 0.96 (95% CI 0.95, 0.98), and 0.95 (95% CI 0.94, 0.97), respectively. The RF model demonstrated optimal discriminative performance for TBI classification. As the SHAP′s interpretation of the RF model indicated, among the 12 kinds of injury data, those with greater contributions to the TBI classification were GCS, rSIG, SI, PHI, respiratory failure, ONSD, and circulatory failure in sequence. Conclusions:Of the scene data-based TBI classification models, the RF model achieves good predictive performance for TBI classification when compared with the SVM model and LR model. Besides, GCS, rSIG, SI, PHI, respiratory failure, ONSD and circulatory failure contribute significantly to the classification of TBI in the RF model, which may assist emergency medical personnel in field triage and management of TBI at accident scenes.