In September 2023， the Measures for Scientific and Technological Ethics Review （Trial Implementation） was issued， revising the provisions related to the simplified procedure for ethical review in Chapter 3， Section 3. This revision of these provisions provides systematic guarantees for further optimizing ethical review work， ensuring that ethical review procedure is well-regulated， and improving scientific research efficiency. The “simplified procedure” does not mean reducing the quality and requirements of the review. Instead， based on always following internationally recognized ethical standards and emphasizing not violating national laws and regulations， improving the efficiency of ethical review and subsequent research work， and promoting the development of life sciences and medical research involving humans. In practical work， it introduces numerous new opportunities and challenges for the improvement of ethics review ability， such as new tests on the judgment and decision-making power of ethics committees， how to ensure the reliability and controllability of the conditions related to the simplified review procedure， and how to determine the basic conditions for adopting the simplified review procedure for review. Therefore， to actively respond to the challenges and possible risks brought by the simplified procedure review， efforts should be made to achieve three “unifications”， including the unification of researchers’ moral autonomy and the heteronomy of supervision implemented by relevant departments； the unification of the standard formulation of the simplified procedure review and the review work in practice； and the unification of ethical responsibility and legal responsibility.

Objective To explore the potential causal relationship between occupational pneumoconiosis (hereinafter referred to as "pneumoconiosis") and five mental disorders (depression, bipolar disorder, schizophrenia, insomnia and anxiety) using the two-sample Mendelian randomization (MR) method. Methods Single nucleotide polymorphisms (SNPs) loci associated with pneumoconiosis and five mental disorders were screened from Genome-Wide Association Studies. Inverse variance weighting (IVW), weighted median (WM) and MR-Egger regression methods were used to evaluate the significance of the causal relationship between pneumoconiosis and five mental disorders. Sensitivity analysis was used to evaluate the accuracy and reliability of the research results. Results After matching data of pneumoconiosis and the five mental disorders, 16 SNPs were ultimately included as instrumental variables in this study. The result of MR analysis revealed a positive causal relationship between pneumoconiosis and both depression [IVW: odds ratio (OR) and 95% confidence interval (CI) was 1.017 (1.000-1.035), P<0.05] and bipolar disorder [IVW: OR(95%CI)was 1.046(1.009-1.083), P<0.05; WM: OR (95%CI) was 1.055(1.007-1.105), P<0.05]. Result of sensitivity analysis indicated there was no heterogeneity and horizontal pleiotropy in the above results. There was no causal association observed between pneumoconiosis and schizophrenia, insomnia, or anxiety disorders (all P>0.05). Conclusion This study provides genetic evidence supporting a positive causal relationship between pneumoconiosis and both depression and bipolar disorder.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

Zishen Huoxue decoction (ZSHX) enhances cardiomyocyte viability following hypoxic stress; however, its upstream therapeutic targets remain unclear. Network pharmacology and RNA sequencing analyses revealed that ZSHX target genes were closely associated with mitophagy and apoptosis in the mitochondrial pathway. In vitro, ZSHX inhibited pathological mitochondrial fission following hypoxic stress, regulated FUN14 domain-containing protein 1 (FUNDC1)-related mitophagy, and increased the levels of mitophagy lysosomes and microtubule-associated protein 1 light chain 3 beta II (LC3II)/translocase of outer mitochondrial membrane 20 (TOM20) expression while inhibiting the over-activated mitochondrial unfolded protein response. Additionally, ZSHX regulated the stability of beta-tubulin through Sirtuin 5 (SIRT5) and could modulate FUNDC1-related synergistic mechanisms of mitophagy and unfolded protein response in the mitochondria (UPR^mt) via the SIRT5 and -β-tubulin axis. This targeting pathway may be crucial for cardiomyocytes to resist hypoxia. Collectively, these findings suggest that ZSHX can protect against cardiomyocyte injury via the SIRT5-β-tubulin axis, which may be associated with the synergistic protective mechanism of SIRT5-β-tubulin axis-related mitophagy and UPR^mt on cardiomyocytes.
Mitophagy/drug effects* ; Tubulin/genetics* ; Animals ; Myocytes, Cardiac/metabolism* ; Drugs, Chinese Herbal/pharmacology* ; Sirtuins/genetics* ; Unfolded Protein Response/drug effects* ; Myocardial Ischemia/genetics* ; Rats ; Humans ; Rats, Sprague-Dawley ; Apoptosis/drug effects* ; Male

Objective To construct and validate a risk prediction model for delayed healing of venous leg ulcer(VLU),so as to provide a reference basis for early identification of people at high risk of delayed healing.Methods Using a convenience sampling method,331 VLU patients attending vascular surgery departments in 2 tertiary A hospitals in Sichuan Province from January 2018 to December 2022 were selected as a modeling group and an internal validation group,and 112 patients admitted to another tertiary A hospital were selected as an external validation group.Risk factors for delayed healing in VLU patients were screened using univariate analysis,LASSO regression,and multivariate logistic regression analysis,and a risk prediction model was constructed using R software,and the predictive effects of the models were examined using the area under the receiver operating characteristic curve,the Hosmer-Lemeshow test,decision curve,and the bootstrap resampling for internal validation and spatial external validation were performed,respectively.Results The predictors that ultimately entered the prediction model were diabetes(OR=4.752),deep vein thrombosis(OR=4.104),lipodermatosclerosis(OR=5.405),ulcer recurrence(OR=3.239),and ankle mobility(OR=5.520).The model had good discrimination(AUC:0.819 for internal validation and 0.858 for external validation),calibration(Hosmer-Lemeshow test:χ2=13.517,P=0.095 for internal validation and χ2=3.375,P=0.909 for external validation)and clinical validity.Conclusion The model constructed in this study has good differentiation and calibration,and it can effectively predict people at high risk of delayed healing of VLU,which facilitates targeted clinical interventions to improve ulcer outcomes and reduce the risk of delayed ulcer healing.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective·To construct and verify the mouse model that can mimic the vitamin A deficiency(VAD)-like craniofacial skeletal deformity and do not cause embryonic death.Methods·Based on the Cre-LoxP system,the OsxCre;Rosa26dn/dn mice expressing osteoblast-specific dominant-negative retinoid acid receptor α(dnRARα)mutation were obtained by hybridization through OsxCre and Rosa26dnRARa/ddnRARa mice,to achieve the conditional inhibition of retinoic acid signaling to simulate VAD disease.Femur bone mesenchymal stem cells(BMSCs)and parietal bone cells of OsxCre;Rosa26dn/dn mice and their control littermates were isolated and underwent osteogenic induction,to assess the expression of retinoid acid receptor α(RARα)protein through Western blotting.Osteoblasts induced from parietal bone cells of OsxCre;Rosa26dn/dn mice and their control littermates were isolated and the effect of retinoic acid signaling inhibition was verified through dual luciferase gene reporter assay.Meanwhile,Ad-eGFP or Ad-Cre adenovirus-infected femur BMSCs and parietal bone cells of Rosa26dn/dnmice underwent osteogenic induction to assess the expression of dominant-negative mutant protein and the inhibition of the retinoic acid signaling pathway in vitro by Western blotting and dual luciferase gene reporter assay.Moreover,the skulls of 6-week-old OsxCre;Rosa26dn/dn mice were collected,and Micro-CT scanning and three-dimensional(3D)reconstruction were performed to verify the craniofacial skeletal deformities of the mouse model.Results·Western blotting results demonstrated that the level of RARα protein increased in the femur and parietal osteoblasts of OsxCre;Rosa26dn/dn mice compared to that of their control littermates,and also increased in the Ad-Cre-infected femur and parietal osteoblasts of Rosa26dn/dn mice compared to that in the Ad-eGFP-infected group(P＜0.05).Dualluciferase gene reporter assay results indicated that the activity of retinoid acid response element(RARE)was inhibited in the osteoblasts of OsxCre;Rosa26dn/dn mice compared to their control littermates,and was also inhibited in the Ad-Cre-infected group compared to the Ad-eGFP-infected group(P＜0.05).Micro-CT and 3D reconstruction suggested that the skull of 6-week-old OsxCre;Rosa26dn/dn mice exhibited VAD-like craniofacial skeletal deformities,including smaller size of the skull and osteogenesis imperfecta compared to their control littermates.Conclusion·An osteoblast-specific dnRARα expressing mouse model that can mimic VAD-like craniofacial skeletal deformity is successfully constructed,therefore providing a new model for exploring the pathogenesis and therapeutic targets of VAD-like craniofacial skeletal deformity in the future.

Objective:This study aims to explore the predictive value of T2-weighted imaging (T2WI), apparent diffusion coefficient (ADC), and early-delayed phases enhanced magnetic resonance imaging (DCE-MRI) radiomics prediction model in determining human epidermal growth factor receptor 2 status in breast cancer.Methods:A retrospective study was conducted, involving 187 patients with confirmed breast cancer by postsurgical pathology at Zhenjiang First People's Hospital during January 2021 and May 2023. Immunohistochemistry or fluorescence in situ hybridization was used to determine the HER-2 status of these patients, with 48 cases classified as HER-2 positive and 139 cases as HER-2 negative. The training set was used to construct the prediction models and the validation set was used to verify the prediction models. Layers of T2WI, ADC, and early-delayed phase DCE-MRI images were used to delineate the volumeof interest and 960 radiomic features were extracted from each case using Pyradiomic. After screening and dimensionality reduction by intraclass correlation coefficient, Pearson correlation analysis, least absolute shrinkage, and selection operator, the radiomics labels were established. Logistic regression analysis was used to construct the T2WI radiomics model, ADC radiomics model, DCE-2 radiomics model, DCE-6 radiomics model, and the joint sequence radiomics model to predict the HER-2 expression status of breast cancer, respectively. Based on the clinical, pathological, and MRI image characteristics of patients, univariate and multivariate logistic regression analysis wasused to construct a clinicopathological MRI feature model. The radscore of every patient and the clinicopathological MRI features which were statistically significant after screening were used to construct a nomogram model. The receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each model and the decision curve analysis wasused to evaluate the clinical usefulness.Results:The T2WI, ADC, DCE-2, DCE-6, and joint sequence radiomics models, the clinicopathological MRI feature model, and the nomogram model were successfully constructed to predict the expression status of HER-2 in breast cancer. ROC analysis showed that in the training set and validation set, the areas under the curve (AUC) of the T2WI radiomics model were 0.797 and 0.760, of the ADC radiomics model were 0.776 and 0.634, of the DCE-2 radiomics model were 0.804 and 0.759, of the DCE-6 radiomics model were 0.869 and 0.798, of the combined sequence radiomics model were 0.908 and 0.847, of the clinicopathological MRI feature model were 0.703 and 0.693, and of the nomogram model were 0.938 and 0.859, respectively. In the training set, the combined sequence radiomics model outperformed the clinicopathological features model ( P＜0.001). In the training and validation sets, the nomogram outperformed the clinicopathological features model ( P＜0.05). In addition, the diagnostic performance of the nomogram was better than that of the four single-modality radiomics models in the training cohort ( P＜0.05) and was better than that of DCE-2 and ADC models in the validation cohort ( P＜0.05). Decision curve analysis indicated that the value of individualized prediction models was higher than clinical and pathological prediction models in clinical practice. The calibration curve showed that the multimodal radiomics model had a high consistency with the actual results in predicting HER-2 expression. Conclusions:T2WI, ADC and early-delayed phase DCE-MRI imaging histology models for HER-2 expression status in breast cancer are expected to provide a non-invasive virtual pathological basis for decision-making on preoperative neoadjuvant regimens in breast cancer.

Objective To explore the expression and diagnostic value of circulating microRNA(miR)-126-3p in non-small cell lung cancer(NSCLC).Methods Multi-centred miR chips and sequencing data were col-lected to investigate the differential expression of circulating miR-126-3p in NSCLC.In order to evaluate the comprehensive expression level of circulating miR-126-3p in the cycle,the standardized mean difference(SMD)and summary receiver operating characteristic(sROC)curve were calculated,and the area under curve(AUC)of sROC curve was analyzed.Sensitivity,specificity,positive negative likelihood ratio were ex-plored,and the expression of circulating miR-126-3p was further comprehensively analyzed in combination with tissue.By using miRDB,starBase v2.0,and TargetScan 7.1,combined with up-regulated differentially expressed genes in NSCLC,potential target genes of circulating miR-126-3p were screened using complemen-tary sequence method.Results Based on six circulating miR datasets,the expression level of circulating miR-126-3p was higher than that of the control group,and the difference was statistically significant(P＜0.05).The receiver operating characteristic curves showed that circulating miR-126-3p had strong diagnostic efficacy(AUC＞0.5),and the comprehensive expression of circulating miR-126-3p was lower in 199 cases of NSCLC group than in the control group(SMD=-1.46).The sROC curve showed that circulating miR-126-3p distin-guished the NSCLC group from the control group with high accuracy(AUC=0.91),Egger's test showed no publication bias(P＞0.05),with sensitivity and specificity 0.80,and positive likelihood ratio and negative likelihood ratio were 5.37 and 0.18,respectively.In addition,a comprehensive analysis of the circulation and tissue of 1 320 NSCLC samples from 26 datasets showed that circulating miR-126-3p expression was lower in NSCLC group than in the control group(SMD=-2.07).The sROC curve showed that low-expression circu-lating miR-126-3p had high accuracy in distinguishing between the NSCLC group and the control group(AUC=0.97).In addition,potential target genes ADAM9 and SLC7A5 were screened for circulating miR-126-3p,and their expression in NSCLC group was higher than that in the control group.Conclusion Low ex-pression of circulating miR-126-3p in the circulation may be an important biomarker for high-precision screen-ing of NSCLC.

In the field of healthcare service, it is crucial to optimize medical innovation services by combining the preferences of health service providers and demanders (i.e., stakeholders). The best-worst scaling (BWS) method is a recently developed stated preference method for assessing preferences with distinctive advantages. Nevertheless, there is a lack of a comprehensive introduction to stakeholder preference assessment using BWS, thus constraining its applications and promotion. This paper introduces the process of using BWS to assess service providers' preferences for the Shared Medical Appointment for diabetes (SMART), an integrated healthcare service of medicine and health management, in the hope of providing reference for researchers for promoting the use of BWS in implementation research.