BACKGROUND:Degenerative scoliosis is defined as a condition that occurs in adulthood with a coronal cobb angle of the spine>10° accompanied by sagittal deformity and rotational subluxation,which often produces symptoms of spinal cord and nerve compression,such as lumbar pain,lower limb pain,numbness,weakness,and neurogenic claudication.The finite element method is a mechanical analysis technique for computer modelling,which can be used for spinal mechanics research by building digital models that can realistically restore the human spine model and design modifications. OBJECTIVE:To review the application of finite element method in the etiology and treatment of degenerative scoliosis. METHODS:The literature databases CNKI,PubMed,and Web of Science were searched for articles on the application of finite element method in degenerative scoliosis published before October 2023.Search terms were"finite element analysis,biomechanics,stress analysis,degenerative scoliosis,adult spinal deformity"in Chinese and English.Fifty-four papers were finally included. RESULTS AND CONCLUSION:(1)The biomechanical findings from the degenerative scoliosis model constructed using the finite element method were identical to those from the in vivo experimental studies,which proves that the finite element method has a high practical value in degenerative scoliosis.(2)The study of the etiology and treatment of degenerative scoliosis by the finite element method is conducive to the prevention of the occurrence of the scoliosis,slowing down the progress of the scoliosis,the development of a more appropriate treatment plan,the reduction of complications,and the promotion of the patients'surgical operation.(3)The finite element method has gradually evolved from a single bony structure to the inclusion of soft tissues such as muscle ligaments,and the small sample content is increasingly unable to meet the research needs.(4)The finite element method has much room for exploration in degenerative scoliosis.

Objective:To analyze the current status of red blood cell transfusion in very preterm infants (VPI) (gestational age at birth <32 weeks) from Chinese Neonatal Network (CHNN) in 2022.Methods:This cross-sectional study was based on the CHNN VPI cohort. It included 6 985 VPI admitted to CHNN 89 participating centers within 24 hours after birth in 2022. VPI with major congenital anomalies or those transferred to non-CHNN centers for treatment or discharged against medical advice were excluded. VPI were categorized based on whether they received red blood cell transfusions, their gestational age at birth, the type of respiratory support received during transfusion, and whether the pre-transfusion hemoglobin levels exceeded the thresholds. General characteristics, red blood cell transfusion rates, number of transfusions, timing of the first transfusion, and pre-transfusion hemoglobin levels were compared among different groups. The incidence of adverse outcomes between the group of VPI who received transfusions above the threshold and those who received transfusions below the threshold were compared. Comparison among different groups was conducted using χ2 tests, Kruskal-Wallis H tests, Mann-Whitney U test, and so on. Trends by gestational age at birth were evaluated by Cochran-Armitage tests and Jonckheere-Terpstra tests for trend. Results:Among the 6 985 VPI, 3 865 cases(55.3%) were male, with a gestational age at birth of 30.0 (28.6, 31.0) weeks and a birth weight of (1 302±321) g. Overall, 3 617 cases (51.8%) received red blood cell transfusion, while 3 368 cases (48.2%) did not. The red blood cell transfusion rate was 51.8% (3 617/6 985), with rates of 77.7% (893/1 150) for those born before 28 weeks gestational age and 46.7% (2 724/5 835) for those born between 28 and 31 weeks gestational age. A total of 9 616 times red blood cell transfusions were administered to 3 617 VPI, with 632 times missing pre-transfusion hemoglobin data, and 8 984 times included in the analysis. Of the red blood cell transfusions, 25.6% (2 459/9 616) were administered when invasive respiratory support was required, 51.3% (4 934/9 616) were receiving non-invasive respiratory support, while 23.1% (2 223/9, 616) were given when no respiratory support was needed. Compared to the non-transfusion group, the red blood cell transfusion group had a higher rate of pregnancy-induced hypertension in mothers, lower rates of born via cesarean section and mother′s antenatal steroid administration, smaller gestational age, lower birth weight, a higher proportion of small-for-gestational-age, multiple births, and proportions of Apgar score at the 5 th minute after birth ≤3 (all P<0.05). They were also less likely to be female, born in hospital or undergo delayed cord clamping (all P<0.01). Additionally, higher transport risk index of physiologic stability score at admission were observed in the red blood cell transfusion group ( P<0.001). The number of red blood cell transfusion was 2 (1, 3) times, with the first transfusion occurring at an age of 18 (8, 29) days, and a pre-transfusion hemoglobin level of 97 (86, 109) g/L. For VPI ≤7 days of age, the pre-transfusion hemoglobin levels for invasive respiratory support, non-invasive respiratory support, or no respiratory support, respectively, with no statistically significant differences between groups ( H=5.59, P=0.061). For VPI aged 8 to 21 days and≥22 days, the levels with statistically differences between groups (both P<0.01). Red blood cell transfusions above recommended thresholds were observed in all respiratory support categories at different stages of life, with the highest prevalence in infants aged 8 to 21 days and≥22 days who did not require respiratory support, at 90.1% (264/273) and 91.1%(1 578/1 732), respectively. The rate of necrotizing enterocolitis was higher in the above-threshold group ( χ2=10.59, P=0.001), and the duration of hospital stay was longer in the above-threshold group ( Z=4.67, P<0.001) compared to the below-threshold group. Conclusions:In 2022, the red blood cell transfusion rate was relatively high among VPI from CHNN. Pre-transfusion hemoglobin levels frequently exceeded recommended transfusion thresholds.

By analyzing the current application of multi-modal data in the diagnosis of gastric "inflammation-cancer" transformation， this study explored the feasibility and strategies for constructing a disease-syndrome integrated diagnosis and treatment system. Based on traditional Chinese medicine （TCM） phenomics， we proposed utilizing multi-modal data from literature research， cross-sectional studies， and cohort follow-ups， combined with artificial intelligence technology， to establish a multi-dimensional diagnostic and treatment index system. This approach aims to uncover the complex pathogenesis and transformation patterns of gastric "inflammation-cancer" progression. Additionally， by dynamically collecting TCM four-diagnostic information and modern medical diagnostic information through a long-term follow-up system， we developed three major modules including information extraction， multi-modal phenotypic modeling， and information output， to make it enable real-world clinical data-driven long-term follow-up and treatment of chronic atrophic gastritis. This system can provide technical support for clinical diagnosis， treatment evaluation， and research， while also offering insights and methods for intelligent TCM diagnosis.

ObjectiveTo explore the construction of a machine learning model for the diagnosis of traditional Chinese medicine （TCM） syndromes in chronic cough and the optimization of this model using the Voting ensemble algorithm. MethodsA retrospective analysis was conducted using clinical data from 921 patients with chronic cough treated at the Respiratory Department of Dongfang Hospital， Beijing University of Chinese Medicine. After standardized processing， 84 clinical features were extracted to determine TCM syndrome types. A specialized dataset for TCM syndrome diagnosis in chronic cough was formed by selecting syndrome types with more than 50 cases. The synthetic minority over-sampling technique （SMOTE） was employed to balance the dataset. Four base models， logistic regression （LR）， decision tree （dt）， multilayer perceptron （MLP）， and Bagging， were constructed and integrated using a hard voting strategy to form a Voting ensemble model. Model performance was evaluated using accuracy， recall， precision， F1-score， receiver operating characteristic （ROC） curve， area under the curve （AUC）， and confusion matrix. ResultsAmong the 921 cases， six syndrome types had over 50 cases each， phlegm-heat obstructing the lung （294 cases）， wind pathogen latent in the lung （103 cases）， cold-phlegm obstructing the lung （102 cases）， damp-heat stagnating in the lung （64 cases）， lung yang deficiency （54 cases）， and phlegm-damp obstructing the lung （53 cases）， yielding a total of 670 cases in the specialized dataset. High-frequency symptoms among these patients included cough， expectoration， odor-induced cough， throat itchiness， itch-induced cough， and cough triggered by cold wind. Among the four base models， the MLP model showed the best diagnostic performance （test accuracy： 0.9104； AUC： 0.9828）. Compared with the base models， the Voting ensemble model achieved superior performance with an accuracy of 0.9289 on the training set and 0.9253 on the test set， showing a minimal overfitting gap of 0.0036. It also achieved the highest AUC （0.9836） in the test set， outperforming all base models. The model exhi-bited especially strong diagnostic performance for damp-heat stagnating in the lung （AUC： 0.9984） and wind pathogen latent in the lung （AUC： 0.9970）. ConclusionThe Voting ensemble algorithm effectively integrates the strengths of multiple machine learning models， resulting in an optimized diagnostic model for TCM syndromes in chronic cough with high accuracy and enhanced generalization ability.

ObjectiveThis paper proposes a novel real-time bedside pulmonary ventilation monitoring method for the diagnosis of chronic obstructive pulmonary disease (COPD), based on electrical impedance tomography (EIT). Four indicators—center of ventilation (CoV), global inhomogeneity index (GI), regional ventilation delay inhomogeneity (RVDI), and the ratio of forced expiratory volume in one second to forced vital capacity (FEV₁/FVC)—are calculated to enable the spatiotemporal assessment of COPD. MethodsA simulation of the respiratory cycles of COPD patients was first conducted, revealing significant differences in certain indicators compared to healthy individuals. The effectiveness of these indicators was then validated through experiments. A total of 93 subjects underwent multiple pulmonary function tests (PFTs) alongside simultaneous EIT measurements. Ventilation heterogeneity under different breathing patterns—including forced exhalation, forced inhalation, and quiet tidal breathing—was compared. EIT images and related indicators were analyzed to distinguish healthy individuals across different age groups from COPD patients. ResultsSimulation results demonstrated significant differences in CoV, GI, FEV₁/FVC, and RVDI between COPD patients and healthy individuals. Experimental findings indicated that, in terms of spatial heterogeneity, the GI values of COPD patients were significantly higher than those of the other two groups, while no significant differences were observed among healthy individuals. Regarding temporal heterogeneity, COPD patients exhibited significantly higher RVDI values than the other groups during both quiet breathing and forced inhalation. Moreover, during forced exhalation, the distribution of FEV₁/FVC values further highlighted the temporal delay heterogeneity of regional lung function in COPD patients, distinguishing them from healthy individuals of various ages. ConclusionEIT technology effectively reveals the spatiotemporal heterogeneity of regional lung function, which holds great promise for the diagnosis and management of COPD.

Objective To track and evaluate the implementation and application of the occupational health standard Radiation shielding requirements for radiotherapy room—Part 4: Radiotherapy room of ²⁵²Cf neutron afterloading (GBZ/T 201.4-2015) by radiation health technical service agencies, medical institutions, health supervision agencies, and radiotherapy facility design units, and to provide a scientific basis for the further revision and implementation of this standard. Methods Following the Guideline for health standards tracking evaluation (WS/T 536-2017) and the project implementation plan, relevant practitioners were randomly selected for a questionnaire survey. The survey primarily focused on their awareness, standard training, application, and revision suggestions of GBZ/T 201.4-2015. The results were summarized and analyzed. Results A total of 168 evaluation questionnaires were collected from relevant practitioners in 28 provinces. Only 31.6% of the respondents reported being “well familiar” or “ familiar” with the standard, 27.4% of the respondents believed that the standard was widely used, and 45.2% of the respondents believed that the standard could meet the needs of their work. Only 14.9% of the respondents had received relevant training on the standard, more than half of the respondents had not applied the standard within the past 10 years, and 45.2% of the respondents believed that the standard "needs to be revised". Conclusion Due to the small number of californium-252 neutron afterloading radiotherapy devices in operation on the market, the overall awareness of the standard is low, suggesting that relevant authorities need to strengthen training and publicity of the standard, and that certain sections of the standard need to be revised or merged.

BACKGROUND: Arsenic trioxide (ATO) is indicated as a broad-spectrum medicine for a variety of diseases, including cancer and cardiac disease. While the role of ATO in hepatic ischemia/reperfusion injury (HIRI) has not been reported. Thus, the purpose of this study was to identify the effects of ATO on HIRI. METHODS: In the present study, we established a 70% hepatic warm I/R injury and partial hepatectomy (30% resection) animal models in vivo and hepatocytes anoxia/reoxygenation (A/R) models in vitro with ATO pretreatment and further assessed liver function by histopathologic changes, enzyme-linked immunosorbent assay, cell counting kit-8, and terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay. Small interfering RNA (siRNA) for extracellular signal-regulated kinase (ERK) 1/2 was transfected to evaluate the role of ERK1/2 pathway during HIRI, followed by ATO pretreatment. The dynamic process of autophagic flux and numbers of autophagosomes were detected by green fluorescent protein-monomeric red fluorescent protein-LC3 (GFP-mRFP-LC3) staining and transmission electron microscopy. RESULTS: A low dose of ATO (0.75 μmol/L in vitro and 1 mg/kg in vivo ) significantly reduced tissue necrosis, inflammatory infiltration, and hepatocyte apoptosis during the process of hepatic I/R. Meanwhile, ATO obviously promoted the ability of cell proliferation and liver regeneration. Mechanistically, in vitro  studies have shown that nontoxic concentrations of ATO can activate both ERK and phosphoinositide 3-kinase-serine/threonine kinase (PI3K-AKT) pathways and further induce autophagy. The hepatoprotective mechanism of ATO, at least in part, relies on the effects of ATO on the activation of autophagy, which is ERK-dependent. CONCLUSION Low, non-toxic doses of ATO can activate ERK/PI3K-AKT pathways and induce ERK-dependent autophagy in hepatocytes, protecting liver against I/R injury and accelerating hepatocyte regeneration after partial hepatectomy.
Animals ; Arsenic Trioxide ; Autophagy/physiology* ; Reperfusion Injury/prevention & control* ; Mice ; Male ; Proto-Oncogene Proteins c-akt/physiology* ; Arsenicals/therapeutic use* ; Oxides/therapeutic use* ; Liver/metabolism* ; Extracellular Signal-Regulated MAP Kinases/metabolism* ; Mice, Inbred C57BL