Acute lung injury （ALI） is a life-threatening condition characterized by uncontrolled pulmonary inflammatory responses， presenting high morbidity and mortality rates that pose serious threats to patient health. The pathogenesis of ALI involves complex interactions among pathological mechanisms including immune-inflammatory responses， disruption of the alveolar-capillary barrier， mesenchymal stem cell dysfunction， metabolic disorders， ferroptosis， and alterations in the gut microbiota. The dysregulation of programmed cell death （PCD） has increasingly emerged as a research focus. PCD represents a genetically regulated autonomous process of cell death， crucial for maintaining the internal stability of organisms. Recent studies indicate that multiple PCD modes， including apoptosis， pyroptosis， necroptosis， autophagy， and ferroptosis， participate in the development and progression of ALI by mediating pathological processes such as alveolar epithelial cell injury and vascular endothelial barrier disruption. Current therapeutic approaches for ALI encompass lung-protective ventilation， body fluid management， mesenchymal stem cell therapy， and pharmacological interventions. While these measures may alleviate clinical symptoms， they remain unable to reverse the pathological progression of lung injury. Traditional Chinese medicine （TCM） possesses the unique advantages of a holistic perspective and syndrome differentiation-based treatment， achieving breakthrough progress in targeted PCD intervention for ALI. It can mitigate pulmonary tissue injury by suppressing inflammatory responses， regulating immune function， and improving coagulation disorders， thereby delaying the onset and progression of ALI. This paper delves into the molecular mechanisms of PCD in ALI， systematically reviewing the effects of TCM extracts， active constituents （terpenoids， saponins， flavonoids， and phenols）， and compound formulas （e.g.， Qingjie Huagong prescription， Maxing Kugan Tang， and Yifei Jianpi prescription） in improving pulmonary epithelial cell function and mitigating lung injury by modulating PCD pathways. This review aims to provide theoretical underpinnings and novel directions for drug development in the clinical prevention and treatment of ALI.

Acute lung injury （ALI） is a life-threatening condition characterized by uncontrolled pulmonary inflammatory responses， presenting high morbidity and mortality rates that pose serious threats to patient health. The pathogenesis of ALI involves complex interactions among pathological mechanisms including immune-inflammatory responses， disruption of the alveolar-capillary barrier， mesenchymal stem cell dysfunction， metabolic disorders， ferroptosis， and alterations in the gut microbiota. The dysregulation of programmed cell death （PCD） has increasingly emerged as a research focus. PCD represents a genetically regulated autonomous process of cell death， crucial for maintaining the internal stability of organisms. Recent studies indicate that multiple PCD modes， including apoptosis， pyroptosis， necroptosis， autophagy， and ferroptosis， participate in the development and progression of ALI by mediating pathological processes such as alveolar epithelial cell injury and vascular endothelial barrier disruption. Current therapeutic approaches for ALI encompass lung-protective ventilation， body fluid management， mesenchymal stem cell therapy， and pharmacological interventions. While these measures may alleviate clinical symptoms， they remain unable to reverse the pathological progression of lung injury. Traditional Chinese medicine （TCM） possesses the unique advantages of a holistic perspective and syndrome differentiation-based treatment， achieving breakthrough progress in targeted PCD intervention for ALI. It can mitigate pulmonary tissue injury by suppressing inflammatory responses， regulating immune function， and improving coagulation disorders， thereby delaying the onset and progression of ALI. This paper delves into the molecular mechanisms of PCD in ALI， systematically reviewing the effects of TCM extracts， active constituents （terpenoids， saponins， flavonoids， and phenols）， and compound formulas （e.g.， Qingjie Huagong prescription， Maxing Kugan Tang， and Yifei Jianpi prescription） in improving pulmonary epithelial cell function and mitigating lung injury by modulating PCD pathways. This review aims to provide theoretical underpinnings and novel directions for drug development in the clinical prevention and treatment of ALI.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective To study the plasma metabolomics of mice poisoned by different dosage of the combination of diazepam and ethanol,and to reveal the toxicological mechanisms of combined poisoning of diazepam and ethanol.Methods Female Kunming mice were randomly divided into blank group,single and combined poisoning group(n=6),Based on the LD50 of diazepam co-administered with graded ethanol doses,mice in the single-drug and combined groups received oral gavage at 1/2,1,and 2 × LD50.Retro-orbital blood samples(～500 μL)were collected within 24 hours post-administration and analyzed by UPLC-QE-MS technology.Principal component analysis and orthogonal partial least squares discriminant analysis were used to identify differential metabolites and associated metabolic pathways.Results A total of 387 differential metabolites were identified in the combined poisoning group of diazepam and ethanol implicating the key pathways including tryptophan metabolism,phenylalanine metabolism,arginine and proline metabolism,Glycerophospholipid metabolism,phenylalanine,tyrosine and tryptophan biosynthesis.Conclusion Combined diazepam and ethanol poisoning exerts significant systemic effects by disrupting neurotransmitters conduction,exacerbating oxidative stress response and dysregulating energy metabolism.

Objective:To systematically review the effect of preoperative pulmonary rehabilitation on postoperative pulmonary complications in patients with lung cancer.Methods:The randomized controlled trials of preoperative pulmonary rehabilitation for lung cancer published in the past 10 years were retrieved in China Biomedical Literature Database, China National Knowledge Infrastructure, VIP, WanFang Data, PubMed, Embase, Web of Science, Cochrane Library and Wiley Online Library. The search limit was from January 1, 2010 to January 1, 2021. The quality evaluation and data extraction of the included article were carried out, and the Meta-analysis of the outcome indicators of postoperative pulmonary complications was conducted.Results:A total of 12 articles were included. Meta-analysis showed that the incidence of postoperative pulmonary complications in the intervention group was lower than that in the control group, and the difference was statistically significant [ RR=0.42, 95% CI (0.32, 0.55) , P<0.01]. Subgroup analysis was performed according to the duration of intervention, and the results showed that when the intervention duration was one week, the difference between the intervention group and the control group was statistically significant [ RR=0.36, 95% CI (0.24, 0.55) , P<0.01], when the intervention duration was more than one week, the difference between the intervention group and the control group was statistically significant [ RR=0.48, 95% CI (0.33, 0.68) , P<0.01) ]. Subgroup analysis was conducted with different evaluation time after operation, and the results showed that when the evaluation time was one month, the difference between the intervention group and the control group was statistically significant [ RR=0.48, 95% CI (0.34, 0.68) , P<0.01], when the evaluation time was more than one month, there was no significant difference between the intervention group and the control group [ RR=0.39, 95% CI (0.08, 1.85) , P=0.24]. Except for pneumonia or pulmonary infection, atelectasis, and bronchopleural fistula, there was no significant difference in the incidence of postoperative pulmonary complications in patients with lung cancer ( P>0.05) . Conclusions:Exercise that includes breathing training for at least one week is a common intervention for preoperative pulmonary rehabilitation. Preoperative pulmonary rehabilitation is beneficial to reduce the overall and one month postoperative pulmonary complications after lung cancer surgery, but the impact on postoperative pulmonary complications evaluated for more than one month and specific complications requires further study.

Objective:To evaluate the application of a multi-task learning-based light-weight convolution neural network (MTLW-CNN) for the automatic segmentation of organs at risk (OARs) in thorax.Methods:MTLW-CNN consisted of several layers for sharing features and 3 branches for segmenting 3 OARs. 497 cases with thoracic tumors were collected. Among them, the computed tomography (CT) images encompassing lung, heart and spinal cord were included in this study. The corresponding contours delineated by experienced radiation oncologists were ground truth. All cases were randomly categorized into the training and validation set ( n=300) and test set ( n=197). By applying MTLW-CNN on the test set, the Dice similarity coefficients (DSCs) of 3 OARs, training and testing time and space complexity (S) were calculated and compared with those of Unet and DeepLabv3+ . To evaluate the effect of multi-task learning on the generalization performance of the model, 3 single-task light-weight CNNs (STLW-CNNs) were built. Their structures were totally the same as the corresponding branches in MTLW-CNN. After using the same data and algorithm to train STLW-CNN, the DSCs were statistically compared with MTLW-CNN on the testing set. Results:For MTLW-CNN, the averages (μ) of lung, heart and spinal cord DSCs were 0.954, 0.921 and 0.904, respectively. The differences of μ between MTLW-CNN and other two models (Unet and DeepLabv3+ ) were less than 0.020. The training and testing time of MTLW-CNN were 1/3 to 1/30 of that of Unet and DeepLabv3+ . S of MTLW-CNN was 1/42 of that of Unet and 1/1 220 of that of DeepLabv3+ . The differences of μ and standard deviation (σ) of lung and heart between MTLW-CNN and STLW-CNN were approximately 0.005 and 0.002. The difference of μ of spinal cord was 0.001, but σof STLW-CNN was 0.014 higher than that of MTLW-CNN.Conclusions:MTLW-CNN spends less time and space on high-precision automatic segmentation of thoracic OARs. It can improve the application efficiency and generalization performance of the models.

To evaluate the efficacy and safety of left atrial appendage occlusion (LAAO) in patients with atrial fibrillation (AF) over 75 years. A total of 82 patients with AF who underwent LAAO successfully in Beijing Anzhen Hospital from March 2014 to March 2019 were divided into two groups according to age: the elderly group (aged>75 years) and the young group (aged ≤75 years). Risk of perioperative complications and incidence of ischemic stroke and major bleeding during follow-up were retrospectively analyzed. The results showed that there were no significant differences in procedure-related ischemic stroke(0 vs.1.6%, P=0.768) and major bleeding (0 vs.1.6%, P=0.768) during perioperative period between the two groups. No complications as death or pericardial tamponade occurred in the two group. During a (25.9±15.9) months period of followed up, ischemic stroke event rate was 3.6/100 person-years in the elderly group and 4.9/100 person-years in the young group, respectively. Major bleeding event rate was 2.5/100 person-years in the elderly group and 0/100 person-years in the young group, respectively. Compared with the expected ones, the relative risk reduction (RRR) of stroke in the elderly group was more profound than that in the young group (32.0% vs. 25.0%), while the risk of major bleeding in the young group was significantly lower than that in the elderly group (RRR 100% vs. 56.9%). Therefore, LAAO might be suitable for stroke prevention in the elderly AF patients.

Objective:To explore a three-dimensional dose distribution prediction method for the left breast cancer radiotherapy planning based on full convolution network (FCN), and to evaluate the accuracy of the prediction model.Methods:FCN was utilized to achieve three-dimensional dose distribution prediction. First, a volumetric modulated arc therapy (VMAT) plan dataset with 60 cases of left breast cancer was built. Ten cases were randomly chosen from the dataset as the test set, and the remaining 50 cases were used as the training set. Then, a U-Net model was built with the organ structure matrix as inputs and dose distribution matrix as outputs. Finally, the model was adopted to predict the dose distribution of the cases in the test set, and the predicted 3D doses were compared with actual planned results.Results:The mean absolute differences of PTV, ipsilateral lung, heart, whole lung and spinal cord for 10 cases were (119.95±9.04) cGy, (214.02±9.04) cGy, (116.23±30.96) cGy, (127.67±69.19) cGy, and (37.28±18.66) cGy, respectively. The Dice similarity coefficient (DSC) of the prediction dose and the planned dose in the 80% and 100% prescription dose range were 0.92±0.01 and 0.92±0.01. The γ rate of 3 mm/3% in the area of 80% and 10% prescription dose range were 0.85±0.03 and 0.84±0.02. Conclusion:FCN can be used to predict the three-dimensional dose distribution of left breast cancer patients undergoing VMAT.

Objective: To study a lung dose prediction method for the early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy based on machine learning algorithm, and to evaluate the feasibility of application in planning quality assurance. Methods: A machine learning algorithm was utilized to achieve DVH prediction. First, an expert plan dataset with 125 cases was built, and the geometric features of ROI, beam angle and dose-volume histogram(DVH) parameters in the dataset were extracted. Following a correlation model was established between the features and DVHs. Second, the geometric and beam features from 10 cases outside the training pool were extracted, and the model was adopted to predict the achievable DVHs values of the lung. The predicted DVHs values were compared with the actual planned results. Results: The mean squared errors of external validation for the 10 cases in mean lung dose (MLD)MLD and V₂₀ of the lung were 91.95 cGy and 3.12%, respectively. Two cases whose lung doses were higher than the predicted values were re-planned, and the results showed that the the lung doses were reduced. Conclusion It is feasible to utilize the anatomy and beam angle features to predict the lung DVH parameters for plan evaluation and quality assurance in early stage NSCLC patients treated with stereotactic body radiotherapy

Objective: To investigate the effect of different mechanisms of liver-protection drugs in clinic and compare which one is best for the proliferation of irradiated HL-7702, laying the basis of liver-protection drugs choose in clinic on theory and practice. Methods: Human liver parenchyma cells HL-7702 were given single 6 MV X ray irradiation at a dose of 10Gy, the cells’ morphology were detected under an inverted microscope at 24h, 48h and 72h. Then, MTT was used to assess the survival rate of the cells to evaluate the effect of the X ray. The representive medicines which mechanism may relate to RILD were chosen and diluted into various concentrations with culture medium according to clinical and relative reports. Different concentrations of medicines were used to protect the cells damaged by the X ray. Comparing the effect with MTT and measure SOD, MDA for the best one. Further research on its protection of oxidative damage. T-test, F test and non- paramiter test were used for statistical analysis. Results: 2.5 mg/ml and 1 mg/ml of magnesium isoglycyrrhizinate both have an effect on the proliferation of liver cells, especially the concentration of 1 mg/ml. The injection of polyene phosphatidyl choline show trivial effect at the concentrations of 250 μmol/L and reduced glutathione(GSH) did not demonstrate relative functions. Further research on the magnesium isoglycyrrhizinate, found its protection at 48h to oxidative damage (P < 0.05), but the effect is weak at 24h and 48h. Conclusions In three kinds of representing medicines, magnesium isoglycyrrhizinate has preferable effects on liver parenchyma cells and show a bright future in the treatment of RILD.