The field of post-marketing benefit-risk assessment for traditional Chinese medicine（TCM） is still in its nascent stage， lacking a universally accepted and cohesive evaluation framework and standards. This study presented a strategy developed for the benefit-risk assessment of post-marketing of TCM， and explored the critical techniques and specific implementation steps involved in the assessment process. Initially， appropriate qualitative assessment frameworks and quantitative analysis models were selected for the integrated qualitative and quantitative benefit-risk assessment. Subsequently， key technologies were outlined， including the establishment of a benefit-risk indicator system， the assignment of indicator weights， and the definition of criteria attributes. Furthermore， the implementation steps were elaborated， which involved defining decision-making issues， data collection， evaluation methodologies， variability factors， and sensitivity analysis. Finally， a case study of the benefit-risk assessment of a TCM injection for hepatitis B treatment was conducted to validate the feasibility of the proposed strategy. The objective of this research was to provide theoretical support and practical references for the development of a comprehensive post-marketing benefit-risk assessment system for TCM.

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.

ObjectiveTo explore the effect of Tanreqing injection combined with Ceftazide on the clinical efficacy， lung function， and laboratory inflammatory index of patients suffering from phlegm heat obstructing lung syndrome in acute exacerbation of chronic obstructive pulmonary disease （AECOPD）. MethodFrom June 2021 to June 2023， 76 patients diagnosed with phlegm heat obstructing lung syndrome in AECOPD were enrolled in the respiratory and critical medical department of Jieshou Hospital of Traditional Chinese Medicine. They were randomly divided into a control group and an observation group with 38 cases each. The control group used Ceftazidime intravenous drip and other conventional oxygen inhalation and antispasmodic treatment measures of western medicine. The observation group received Tanreqing injection intravenous drip based on the treatment of the control group， with a course of 10 days. The changes of laboratory indicators such as hs-CRP， calcitonin （PCT）， and interleukin-6 （IL-6） before and after treatment were analyzed， and the improvement of forced expiratory volume in the first second （FEV₁）， forced vital capacity （FVC）， one second rate （FEV₁/FVC）， assessment and improvement of the British Medical Research Society’s dyspnea index （mMRC）， self-evaluation test of chronic obstructive pulmonary disease patients （CAT）， and traditional Chinese medicine syndrome score was compared. In addition， the total effective rate between the two groups after treatment was compared. ResultAfter treatment， the hs-CRP， PCT， IL-6， FEV₁， FVC， FEV₁/FVC， mMRC， CAT scores， and traditional Chinese medicine syndrome evaluation of both groups improved （P<0.01）. After treatment， compared with the control group， the observation group showed more significant improvements in hs-CRP， PCT， IL-6， FEV₁， FVC， FEV₁/FVC， mMRC， CAT scores， and traditional Chinese medicine syndrome evaluation， and the difference was statistically significant （P<0.05，P<0.01）. The total clinical effective rate of the control group was 86.84% （33/38）， while that of the observation group was 94.74% （36/38）. The therapeutic effect of the observation group was better than that of the control group （χ²=8.471， P<0.05）. ConclusionTanreqing injection combined with Ceftazidime has obvious efficacy in the treatment of phlegm heat obstructing lung syndrome in AECOPD， which is better than the treatment of Ceftazidime antibiotics alone. It can reduce the risk of acute exacerbation， alleviate clinical symptoms， and delay the decline of lung function.

It is proposed that the disease mechanism evolution of systemic lupus erythematosus can be summarized into four stages： initial invasion and latency， the pathogenesis remains concealing； latent toxin accumulation， the disease gradually becomes apparent； active toxin begins damaging， the disease manifests aggressively； damage resulting to deficiency， the disease course prolonged. Based on the stages of latent toxin evolution， the syndrome differentiation and treatment of systemic lupus erythematosus can be summarized as follows： during the initial latent stage， characterized by latent dampness and heat stagnation， modified Sanren Decoction （三仁汤） should be used； in the toxin outbreak stage， marked by intense heat toxin， modified Xijiao Dihuang Decoction （犀角地黄汤） combined with modified Qingwen Baidu Decoction （清瘟败毒饮） should be used； during the toxin damage stage， which presents as latent toxin damaging zang-fu organs， modified Qinghao Biejia Decoction （青蒿鳖甲汤） should be used； in the healthy qi deficiency stage， characterized by deficiencies of qi， blood， yin， and yang， modified Xieli Shiquan Ointment （燮理十全膏） should be used.

ObjectiveTo develop traditional Chinese medicine （TCM） formulae for the treatment of nonsevere coronavirus disease 2019 （COVID-19） and to explore its anti-inflammatory mechanism. MethodsThe dysregulated signaling pathways were determined in macrophages from bronchoalveolar lavage fluid of COVID-19 patients and in lung epithelial cells infected with SARS-CoV-2 in vitro based on transcriptome analysis. A total of 102 TCM formulae for the clinical treatment of nonsevere COVID-19 were collected through literature. The pathway-reversing rates of these formulae in macrophages and lung epithelial cells were evaluated based on signature signaling pathways， and the basic formula was determined in conjunction with TCM theory. The commonly used Chinese materia medica for nonsevere COVID-19 were summarized from the 102 TCM formulae as abovementioned. And together with the screening results from the Pharmacopoeia of the People's Republic of China， a “Chinese materia medica pool” was esta-blished for the development of TCM formulae for COVID-19. The regulatory effects of each herb on signaling pathways were obtained based on targeted transcriptome analysis. Oriented at reversing dysregulated signaling pathways of COVID-19， the calculation was carried out， and the artificial intelligent methods for compositing formulae， that are exhaustive method and parallel computing， were used to obtain candidate compound formulas. Finally， with reference to professional experience， an innovative formula for the treatment of nonsevere COVID-19 was developed. The ethanol extract of the formula was evaluated for its anti-inflammatory effects by detecting the mRNA expression of interleukin 1b （Il1b）， C-X-C motif chemokine ligand 2 （Cxcl2）， C-X-C motif chemokine ligand 10 （Cxcl10）， C-C motif chemokine ligand 2 （Ccl2）， nitric oxide synthase 2 （Nos2）， and prostaglandin-endoperoxide synthase 2 （Ptgs2） using reverse transcription-quantitative polymerase chain reaction （RT-qPCR） in RAW264.7 cells treated with lipopolysaccharide （LPS）. ResultsIn macrophages and lung epithelial cells， 34 dysregulated signaling pathways associated with COVID-19 were identified respectively. The effects of the 102 formulae for clinical treatment of nonsevere COVID-19 were evaluated based on the dysregulated signaling pathways and targeted transcriptome， and the result showed that Yinqiao Powder and Pingwei Powder （银翘散合平胃散， YQPWP） ranked first， reversing 91.18% of the dysregulated signaling pathways in macrophages and 100% of the dysregulated signaling pathways in lung epithelial cells. Additionally， YQPWP had the function of scattering wind and clearing heat， resolving toxins and removing dampness in accordance with the pathogenesis of wind-heat with dampness in COVID-19. It was selected as the basic formula， and was further modified and optimized to develop an innovative fomula Qiaobang Zhupi Yin （翘蒡术皮饮， QBZPY） based on expert experience and artificial intelligence in composing formulae. QBZPY can reverse all the dysregulated signaling pathways associated with COVID-19 in macrophages and lung epithelial cells， with the reversing rates of 100%. The chief medicinal of QBZPY， including Lianqiao （Fructus Forsythiae）， Xixiancao （Herba Siegesbeckiae） and Niubangzi （Fructus Arctii）， can down-regulate multiple signaling pathways related with virus infection， immune response， and epithelial damage. RT-qPCR results indicated that compared with the model group， the QBZPY group down-regulated the mRNA expression of Il1b， tumor necrosis factor （Tnf）， Cxcl2， Cxcl10， Ccl2， Nos2 and Ptgs2 induced by LPS in RAW264.7 cells （P＜0.05 or P＜0.01）. ConclusionBased on targeted transcriptome analysis， expert experience in TCM and artificial intelligence， QBZPY has been developed for the treatment of nonsevere COVID-19. The ethanol extract of QBZPY has been found to inhibit mRNA expression of several pro-inflammatory genes in a cellular inflammation model.

Objective To summarize and evaluate the characteristics of current recurrent spontaneous abortion(RSA)animal models at home and abroad,and to provide reference and guidance for the standardized preparation of RSA models.Methods"Recurrent spontaneous abortion"and"animal model"were used as co-keywords in CNKI,Wanfang,VIP,PubMed and Web of Science databases to search the RSA animal experimental literature,covering the period up to January 20,2024,and a total of 1 411 articles were collected.The analysis focused on construction methods and essential elements of RSA animal models,the modeling process and result evaluation,as well as the application of these models in pharmacological and pharmacodynamic research.An Excel table was established for systematic analysis and discussion.Results A total of 138 experimental studies were obtained after screening.In constructing RSA animal models,immunological models were the most widely used in Western medicine(96.92％),with the Clark model being the main one(92.31％).In traditional Chinese medicine(TCM)models,70.00％were kidney deficiency-luteal inhibition-syndrome combination models,20.00％were kidney deficiency and blood stasis models,and 10.00％were deficiency-heat syndrome models.Most animals were selected at 6-8 weeks(33.86％)and 8 weeks(32.28％)of age.The majority of animals were paired for mating at 18:00 on the day of cage pairing.In 81.03％of literatures,vaginal plugs were checked once the following morning,with 8:00 being the most common time(17.02％).The most commonly used drug administration cycle was 14 days of continuous gavage after pregnancy.Among the tested drugs,Western drugs were mainly protein-based(29.17％),while TCM drugs were mainly TCM decoction(81.11％).The most frequently used methods for detecting indicators included visual observation of embryos(22.54％),western blot(15.96％),PCR(13.58％),ELISA(12.91％),HE staining(10.80％)and immunohistochemistry(9.39％).Conclusion The etiology of RSA is complex,and corresponding animal models should be established based on different etiologies.Clark model is commonly used in the construction of Western medicine model,while the kidney deficiency-luteal inhibition-syndrome combination model is predominant in TCM.RSA animal model is widely used in related research,but systematic evaluation needs to be strengthened.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Objective:To test the reliability and validity of the general procrastination scale (GPS) in the application of middle school students.Methods:The Chinese version of GPS, the irrational procrastination scale(IPS), and the Maslach burnout inventory(MBI) were utilized to survey 10 825 middle school students in Harbin City through stratified random sampling, and 4 498 students were retested after 4 weeks. Statistical analysis was performed using SPSS 27.0 and Mplus 8.0.Results:The entries were well differentiated.Exploratory and confirmatory factor analysis indicated that GPS was composed of two factors, including active avoidance and lack of planning.The model fit was good (CFI=0.914, TLI=0.901, RMSEA=0.069, SRMR=0.072). GPS was positively correlated with the total scores of IPS and MBI ( r=0.753, 0.677, both P<0.001). The Cronbach's α coefficient of GPS was 0.864, the folded half reliability was 0.870, and the retest reliability after 4 weeks was 0.756. Conclusion:The GPS has good reliability and validity among middle school students, which provides a standard for measuring the procrastination level of middle school students and carrying out related research.

Objective To observe the clinical efficacy of self-formulated Shenqi Buwei Decoction(derived from Huangqi Renshen Decoction)in treating patients with stable chronic obstructive pulmonary disease(COPD)differentiated as lung-spleen qi deficiency syndrome.Methods A total of 110 patients with stable COPD differentiated as lung-spleen qi deficiency syndrome were randomly divided into a control group and an observation group,with 55 patients in each group.The control group was given Tiotropium Bromide Inhalation Powder for the inhalation treatment,and the observation group was given Shenqi Buwei Decoction on the basis of treatment for the control group,and the course of treatment covered 3 months.The changes of pulmonary function indicators of forced expiratory volume in one second(FEV1),forced vital capacity(FVC),and one-second rate of FEV1/FVC,modified Medical Research Council index(mMRC)dyspnea scores,6-minute walk test(6MWT),COPD Assessment Test(CAT)scores,and traditional Chinese medicine(TCM)syndrome scores in the two groups were observed before and after treatment.After treatment,the clinical efficacy and safety of the two groups were evaluated.Results(1)During the trial,one patient was excluded and two patients fell off from the observation group,and three patients fell off from the control group.Eventually,52 patients in each of the two groups were included in the efficacy statistics.(2)After 3 months of treatment,the total effective rate of the observation group was 80.77%(42/52)and that of the control group was 67.31%(35/52).The intergroup comparison(tested by chi-square test)showed that the therapeutic effect of the observation group was slightly superior to that of the control group,but the difference was not statistically significant(P＞0.05).(3)In terms of indexes,After treatment,the levels of pulmonary function indicators of FEV1,FEV1/FVC in the control group and FEV1,FVC,FEV1/FVC in the observation group were significantly improved compared with those before treatment(P＜0.05),and the improvement of FEV1,FVC,FEV1/FVC in the observation group was significantly superior to that in the control group(P＜0.05).(4)After treatment,the 6MWT,mMRC and CAT scores of the two groups were significantly improved compared with those before treatment(P＜0.05),and the improvement in the observation group was significantly superior to that in the control group(P＜0.05).(5)After treatment,the TCM syndrome scores of the two groups of patients were significantly decreased in comparison with those before treatment(P＜0.05),and the decrease in the observation group was significantly superior to that in the control group(P＜0.05).(6)During the treatment process,no obvious adverse reactions occurred in the two groups of patients,there were no abnormal changes in the safety indicators,either.Conclusion On the basis of conventional western medicine treatment,the combined use of Shenqi Buwei Decoction exerts certain efficacy in the treatment of patients with stable COPD differentiated as lung-spleen qi deficiency syndrome.The combined therapy can effectively improve the ventilation function,relieve the clinical symptoms,improve the quality of life and delay the decline of lung function of the patients.

Objective:To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer.Methods:Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5–10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy.Results:The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing.Conclusion:The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.