BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

BACKGROUND:Rapid and accurate segmentation of brain tissue in medical images is of great significance for three-dimensional biomechanical modeling and diagnosis of craniocerebral injuries.Currently,artificial intelligence(AI)-based baseline models exhibit excellent generalization capabilities on large-scale datasets.However,due to the specificity and complexity of craniocerebral tissues,these models have certain limitations in their application to craniocerebral tissue segmentation.Additionally,the scarcity of craniocerebral tissue samples makes it difficult for baseline models to achieve precise segmentation results through fine-tuning.OBJECTIVE:To construct a craniocerebral tissue segmentation model based on texture feature retrieval enhancement to improve segmentation accuracy under a small number of samples.METHODS:Segment Anything in Medical Images(MedSAM)model was selected as the basic framework,and texture features were combined with deep learning to build a brain tissue segmentation model based on texture feature retrieval enhancement(DP-MedSAM).Dice Coefficient and mean intersection over union(MIoU)were selected to evaluate the efficiency of image segmentation results.In comparison with the original MedSAM model,the ablation experiment systematically evaluated the influence of key components on the model performance.The sensitivities of MedSAM,the Segment Anything Model(SAM)for medical image segmentation(SAM-Med2D)and DP-MedSAM in the mandible,left optic nerve,and left parotid gland were compared.RESULTS AND CONCLUSION:(1)By verifying the impact of the number of point prompts on segmentation results on the HaN-Seg dataset,the experimental results indicated that the optimal Dice score was achieved with the addition of three points.(2)DP-MedSAM demonstrated performance improvements compared with MedSAM and SAM-Med2D on two datasets(HaN and Public Domain Database for Computational Anatomy).Especially on the Public Domain Database for Computational Anatomy dataset,in terms of the MIoU metric,DP-MedSAM outperformed MedSAM by 6.59％and SAM-Med2D by 37.35％;in terms of the Dice metric,DP-MedSAM outperformed MedSAM and SAM-Med2D by 4.34％and 25.32％,respectively.(3)The ablation experiment results showed that removing the texture feature extraction module in the DP-MedSAM model,relying solely on original image features,led to a significant decrease in results on the test set.Furthermore,removing the vector cache database and its retrieval enhancement function from the model,which deprived the ability of the model to perform similarity retrieval using an external knowledge base,further reduced model performance.(4)Under conditions of limited data resources,the DP-MedSAM model outperformed the other two models in all evaluation metrics.The DP-MedSAM model performed excellently when processing simple and moderately difficult samples,demonstrating a clear advantage over the other two models and indicating good generalization ability.Processing the fine structures of difficult samples placed higher demands on the model's segmentation capabilities.Although the performance of the DP-MedSAM model declined slightly,it still outperformed the other two models.(5)This study proposes an innovative craniocerebral tissue segmentation model,DP-MedSAM,which improves the baseline model's performance in capturing local details and global structural information in medical images by introducing target region texture feature extraction.Through vector similarity retrieval technology,DP-MedSAM can retrieve the feature vector most similar to the current target region from a pre-constructed vector database,providing more precise guiding information for the segmentation process.

Dipsaci Radix is a commonly used yang tonifying medicine in clinical practice.Ancient books record that its preparation methods are diverse,mainly concentrated in the Ming and Qing dynasties,including wine soaking,wine washing,wine baking,wine stir frying,stir frying,wine mixing,and salt water stir frying.Wine roasting can promote blood circulation,dispel cold stagnation,and has been used throughout history;salt roasting has been seen in modern times,which can induce Chinese materia medica to descend and enhance liver and kidney tonifying effects;at present,it is mainly used for slicing raw materials,but there are also processed products such as wine fried products,salt fried products,stir fried slices,and charcoal slices.This article reviewed the herbal monographs,TCM ancient books,processing standards and modern literature,and combed the related elaboration of the processing history and modern processing research of Dipsaci Radix in the literature,so as to provide references for the processing mechanism,method research,clinical application and resource development and utilization of Dipsaci Radix.

Objective:To evaluate the long-term outcomes and predictors of coronary atherosclerotic lesions deemed functionally non-ischemic (quantitative flow ratio(QFR)>0.80) and deferred from intervention.Methods:This study is a post-hoc analysis of the FAVOR Ⅲ China trial, which enrolled 3 825 patients with stable or unstable angina pectoris or with myocardial infarction occurring at least 72 hours prior to screening, between December 5, 2018 and January 9, 2020 from 26 research centers in China. Coronary vessels with QFR>0.80 and without interventional treatment were analyzed in this study. The primary endpoint was 3-year target vessel revascularization. Vessels with revascularization (revascularized group) during follow-up were matched 1∶1 using propensity score matching to comparable vessels without revascularization (non-revascularized group). Multivariate Cox regression analysis was used to identify the risk factors for target vessel revascularization (TVR).Results:A total of 6 212 functionally negative vessels with deferred intervention were included in the final analysis, among which 153 vessels (2.5%) underwent TVR during a 3-year follow-up. Prior to propensity score matching, 6 059 vessels comprised the non-revascularized group. At the vessel level, compared to the non-revascularized group, the revascularized group exhibited a significantly higher proportion of males (79.1% (121/153) vs. 70.2% (4 253/6 059), P=0.018), higher body mass index ((25.6±4.0) kg/m2 vs. (24.3±5.2) kg/m2, P=0.003), and a higher prevalence of hypertension (73.9% (113/153) vs. 65.1% (3 944/6 059), P=0.025). And 152 pairs of vessels were successfully matched. Multivariate Cox regression analysis identified in-stent restenosis lesions ( HR=2.59, 95% CI 1.28-5.23, P=0.008) as an independent risk factor for target vessel revascularization. Conclusions:Coronary lesions classified as functionally non-ischemic at baseline are not entirely stable and may progress to lesions that requiring revascularization over time. In-stent restenosis emerges as a critical independent predictor of revascularization.

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.

Objective:To analyze the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in Beijing in 2024, to investigate the infection status of reservoir hosts, vector organisms, and baseline human populations, and provide a scientific basis for formulating prevention and control strategies.Methods:Epidemiological surveys were conducted on all confirmed cases. Serum samples from healthy populations and reservoir hosts were collected for SFTSV antibody detection. Questing ticks were monitored using the flagging method. Real-time fluorescent quantitative PCR was employed to detect SFTSV in cases, reservoir hosts, and ticks. Positive samples underwent whole-genome sequencing and genetic evolution analysis.Results:In 2024, Beijing reported 15 locally infected cases with 4 deaths. The age of onset ranged from 50 to 80 years (median: 66 years). Cases showed a certain degree of geographical clustering, with June being the peak month of onset. The affected population was predominantly farmers, with a male-to-female ratio of 3∶2. Animal contact history emerged as a significant risk factor alongside tick bites. Parthenogenetic tick populations were identified in Pinggu district, while SFTSV-carrying ticks were detected in endemic areas (Mentougou, Shijingshan, and Fengtai Districts). Viral presence was also confirmed in ticks or dogs from non-endemic areas. Sequencing and phylogenetic analysis revealed stable clustering of strains into two distinct genotypes (A and B). Antibody-positive individuals were identified in healthy populations from non-endemic areas.Conclusions:The incidence of SFTS in Beijing is increasing, with natural viral circulation already established in non-endemic regions. Enhanced surveillance and adjusted prevention strategies are urgently needed.

Dipsaci Radix is a commonly used yang tonifying medicine in clinical practice.Ancient books record that its preparation methods are diverse,mainly concentrated in the Ming and Qing dynasties,including wine soaking,wine washing,wine baking,wine stir frying,stir frying,wine mixing,and salt water stir frying.Wine roasting can promote blood circulation,dispel cold stagnation,and has been used throughout history;salt roasting has been seen in modern times,which can induce Chinese materia medica to descend and enhance liver and kidney tonifying effects;at present,it is mainly used for slicing raw materials,but there are also processed products such as wine fried products,salt fried products,stir fried slices,and charcoal slices.This article reviewed the herbal monographs,TCM ancient books,processing standards and modern literature,and combed the related elaboration of the processing history and modern processing research of Dipsaci Radix in the literature,so as to provide references for the processing mechanism,method research,clinical application and resource development and utilization of Dipsaci Radix.

Gastric cancer is a common malignant tumor of the digestive tract and can be classified as “fullness of the stomach”， “epigastric pain”， “noise” and other categories in the field of traditional Chinese medicine. Sijunzi decoction is composed of Panax ginseng， Poria cocos， Atractylodes macrocephala， and honey-fried Glycyrrhiza uralensis， and it has the effect of tonifying qi and strengthening the spleen. This article summarizes the active ingredients， mechanism of action， and clinical application research progress of Sijunzi decoction in treating gastric cancer. The results show that the main active ingredients of Sijunzi decoction include ginsenosides， atractylenolide， pachymic acid， glycyrrhizic acid， etc.； Sijunzi decoction and its effective ingredients can play an anti-gastric cancer role by inhibiting the proliferation of gastric cancer cell， inducing apoptosis of gastric cancer cell， enhancing gastric cancer cell chemotherapy sensitivity， and inhibiting invasion and metastasis of gastric cancer cell. In addition， Sijunzi decoction can enhance the efficacy of chemotherapy drugs， strengthen the immune function of the body and lower serum cancer marker levels during the clinical treatment of gastric cancer.

Objective To evaluate the efficacy and safety of concurrent chemoradiotherapy versus sequential chemoradiotherapy in the treatment of locally advanced non-small cell lung cancer. Methods The relevant literature was searched in PubMed, Web of Science, CNKI and Wanfang databases from the inception to October 15, 2023, and the literature was screened according to the inclusion and exclusion criteria. Review Manager 5.3 software was used for meta-analysis of the literature, and the Cochrane bias risk assessment tool was used to evaluate the quality of the literature. Results Finally, 14 randomized controlled studies were included covering a total of 1048 patients. The results of meta-analysis showed that the overall response rate [OR=2.39, 95%CI (1.83, 3.11)], 1-year survival rate [OR=1.81, 95%CI (1.39, 2.35)], 2-year survival rate [OR=1.75, 95%CI (1.27, 2.42)] and 3-year survival rate [OR=2.33, 95%CI (1.49, 3.66)] were superior to sequential chemoradiotherapy (P<0.001). In terms of safety, concurrent chemoradiotherapy increased the incidence of radiation esophagitis (P<0.05), but there was no statistical difference in the incidence of leukopenia and radiation pneumonia (P>0.05). Conclusion For patients with locally advanced non-small cell lung cancer, the short-term efficacy of concurrent chemoradiotherapy is better than that of sequential chemoradiotherapy and can improve the 1-, 2- and 3-year survival rates, but the toxic side effects of the treatment are slightly greater than those of the sequential chemoradiotherapy.

Objective To analyze the risk of bias during the experimental process and the shortcomings of the research report by evaluating the methodological and reporting quality of animal experimental studies on the prevention and treatment of precancerous lesions of gastric cancer(PLGC)using TCM compounds.To provide reference for improving the quality of animal experimental research on the prevention and treatment of PLGC with TCM compounds.Methods Experimental literature about the prevention and treatment of PLGC with TCM compounds was retrieved from CNKI,Wanfang Data,VIP,CBM,PubMed,Cochrane Library,Web of science and Embase from January 1,2014 to February 23,2024.SYRCLE assessment tool and ARRIVE 2.0 guideline were used to score the included literature and calculate the"low-risk"compliance rate for each item.Results Totally 213 articles were finally included,including 189 Chinese articles and 24 English articles.The SYRCLE tool score was(12.86±1.29)points,and the"low risk"compliance rate was 32.79％.The score of the necessary items of the ARRIVE 2.0 guideline was(24.15±2.80)points,and the"low risk"compliance rate was 49.08％;the score of the recommended items was(11.28±3.40)points,and the"low risk"compliance rate was 30.27％.In the SYRCLE tool evaluation,144(67.61％)studies did not elaborate on the method of generating the allocation sequence.All studies did not describe the adequacy of allocation concealment and the blinding method in the implementation of bias.Only 51 studies(23.94％)explicitly proposed the success criteria for PLGC modeling,only 66 studies(30.96％)provided detailed information on the statistical methods used,29 studies(13.62％)provided complete ethical statements,and 22 studies(10.33％)reported conflicts of interest.Conclusion There are many problems in the methodological quality and reporting quality of animal experimental literature on the prevention and treatment of PLGC with TCM compounds published from 2014 to 2024,especially the implementation of the random blinding strategy during the experimental process,the calculation details of the sample size,and the reporting of inclusion and exclusion criteria,etc.There are many deficiencies in this aspect.It is recommended to refer to the SYRCLE evaluation tool and the ARRIVE 2.0 guideline list to design and report the research plan,thereby improving the credibility and standardization of the PLGC animal experimental research results.