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.

BACKGROUND: The FAVOR (Comparison of Quantitative Flow Ratio Guided and Angiography Guided Percutaneous Intervention in Patients with Coronary Artery Disease) III China trial demonstrated that percutaneous coronary intervention (PCI) lesion selection using quantitative flow ratio (QFR) measurement, a novel angiography-based approach for estimating fractional flow reserve, improved two-year clinical outcomes compared with standard angiography guidance. This study aimed to assess the cost-effectiveness of QFR-guided PCI from the perspective of the current Chinese healthcare system. METHODS: This study is a pre-specified analysis of the FAVOR III China trial, which included 3825 patients randomized between December 25, 2018, and January 19, 2020, from 26 centers in China. Patients with stable or unstable angina pectoris or those ≥72 hours post-myocardial infarction who had at least one lesion with a diameter stenosis between 50% and 90% in a coronary artery with a ≥2.5 mm reference vessel diameter by visual assessment were randomized to a QFR-guided strategy or an angiography-guided strategy with 1:1 ratio. During the two-year follow-up, data were collected on clinical outcomes, quality-adjusted life-years (QALYs), estimated costs of index procedure hospitalization, outpatient cardiovascular medication use, and rehospitalization due to major adverse cardiac and cerebrovascular events (MACCE). The primary analysis calculated the incremental cost-effectiveness ratio (ICER) as the cost per MACCE avoided. An ICER of ¥10,000/MACCE event avoided was considered economically attractive in China. RESULTS: At two years, the QFR-guided group demonstrated a reduced rate of MACCE compared to the angiography-guided group (10.8% vs . 14.7%, P <0.01). Total two-year costs were similar between the groups (¥50,803 ± 21,121 vs . ¥50,685 ± 23,495, P = 0.87). The ICER for the QFR-guided strategy was ¥3055 per MACCE avoided, and the probability of QFR being economically attractive was 64% at a willingness-to-pay threshold of ¥10,000/MACCE avoided. Sensitivity analysis showed that QFR-guided PCI would become cost-saving if the cost of QFR were below ¥3682 (current cost: ¥3800). Cost-utility analysis yielded an ICER of ¥56,163 per QALY gained, with a 53% probability of being cost-effective at a willingness-to-pay threshold of ¥85,000 per QALY gained. CONCLUSION: In patients undergoing PCI, a QFR-guided strategy appears economically attractive compared to angiographic guidance from the perspective of the Chinese healthcare system. TRIAL REGISTRATION ClinicalTrials.gov , NCT03656848.
Humans ; Cost-Benefit Analysis ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Angiography/methods* ; Middle Aged ; Aged ; Coronary Artery Disease/surgery* ; Quality-Adjusted Life Years ; Fractional Flow Reserve, Myocardial/physiology*

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

This study aimed to investigate the effects of Zhiwei Fuwei Pills on mitochondrial apoptosis in the rat model of precancerous lesions of gastric cancer(PLGC) based on the microRNA-21(miRNA-21)/B-cell lymphoma-2(Bcl-2) signaling pathway. Eighty-five 5-week-old male SPF-grade SD rats were selected, of which 75 were fed with N-methyl-N'-nitro-N-nitrosoguanidine(MNNG) for multifactorial modeling, and the PLGC model was established after 26 weeks. The rats were randomly grouped as follows: model, folic acid(0.002 g·kg~(-1)), low-dose(0.42 g·kg~(-1)) Zhiwei Fuwei Pills, medium-dose(0.84 g·kg~(-1)) Zhiwei Fuwei Pills, and high-dose(1.67 g·kg~(-1)) Zhiwei Fuwei Pills, with 15 rats in each group. Additionally, 10 rats were assigned to a blank group and administrated with an equivalent volume of normal saline by gavage. After four weeks of continuous drug administration, the gastric mucosal tissue was collected. Hematoxylin-eosin(HE) staining was performed to reveal the pathological changes in the gastric mucosa. Terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL) was employed to detect apoptosis in gastric mucosal epithelial cells. RT-PCR was adopted to determine the mRNA levels of miRNA-21, phosphatase and tensin homolog(PTEN), Bcl-2, Bcl-2-associated X protein(Bax), and cysteinyl aspartate-specific protease 3(caspase-3). Western blot was employed to determine the protein levels of PTEN, Bcl-2, Bax, and caspase-3. Immunohistochemistry(IHC) was used to detect the positive expression of PTEN, Bcl-2, and Bax in the gastric mucosal tissue. Transmission electron microscopy(TEM) was employed to observe the morphological and structural changes in mitochondria. The results showed that compared with model group, the drug administration groups showed alleviated pathological changes, with increased apoptotic cells, down-regulated mRNA levels of miRNA-21 and Bcl-2, up-regulated mRNA and protein levels of PTEN, Bax, and caspase-3, and down-regulated protein level of Bcl-2. In addition, the drug administration groups exhibited mitochondrial swelling and rupture and reduction of cristae, which indicated mitochondrial apoptosis. These findings suggest that Zhiwei Fuwei Pills can effectively improve mitochondrial apoptosis in PLGC cells by regulating the miRNA-21/Bcl-2 signaling pathway.
Animals ; MicroRNAs/metabolism* ; Male ; Apoptosis/drug effects* ; Stomach Neoplasms/physiopathology* ; Proto-Oncogene Proteins c-bcl-2/genetics* ; Rats ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; Mitochondria/genetics* ; Signal Transduction/drug effects* ; Precancerous Conditions/drug therapy* ; Humans ; PTEN Phosphohydrolase/genetics*

Immune checkpoints include a series of receptor-ligand pairs that play a key role in the proliferation, activation, and immune regulatory responses of immune cells. Although immune checkpoint inhibitors (ICIs), such as programmed death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) have achieved good therapeutic effects in clinical practice, some patients still experience ineffective treatment and immune resistance. A large amount of evidence has shown that immune checkpoint proteins are related to cell metabolism during immune regulation. On the one hand, immune checkpoints connect to alter the metabolic reprogramming of tumor cells to compete for nutrients required by immune cells. On the other hand, immune checkpoints regulate the metabolic pathways of immune cells, such as phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) to affect the activation of immune cells. Based on a review of the literature, this article reviews the mechanisms by which PD-1, CTLA-4, T cell immunoreceptor with Ig and ITIM domains (TIGIT), T cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), cluster of differentiation 47 (CD47), and indoleamine 2,3-dioxygenase 1 (IDO1) regulate cell metabolic reprogramming, and looks forward to whether targeting the ligand-receptor pairs of immune checkpoints in a "dual regulation" manner and inhibiting metabolic pathways can effectively solve the problem of tumor immune resistance.
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Humans ; Neoplasms/genetics* ; Metabolic Networks and Pathways/immunology* ; Animals ; Immune Checkpoint Inhibitors/pharmacology*

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 investigate the impact of early invasive arterial blood pressure (IBP) monitoring on survival and neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients undergoing extracorporeal cardiopulmonary resuscitation (ECPR).Methods:This retrospective cohort study analyzed 44 OHCA patients receiving ECPR between January 2021 and January 2023. Patients were divided into: Early intervention group : IBP established within 3 min of ECMO initiation; Late intervention group : IBP established after ICU admission. Baseline characteristics, ECMO parameters, and clinical outcomes were compared. Multivariable logistic regression (adjusted for age, initial rhythm, etc.) and Spearman's correlation were used.Results:This study included a total of 44 patients treated with OHCA and ECPR, divided into an early intervention group of 23 cases and a late intervention group of 21 cases. The early intervention group showed significantly higher: Survival to discharge (43.5% vs. 9.5%, P<0.05), Good neurological recovery (CPC 1-2: 34.8% vs. 9.5%, P<0.05).Early intervention independently predicted survival (adjusted OR=18.84, 95% CI:1.97-179.98, P=0.01). Stratified analysis by pH (cutoff 7.0) demonstrated consistent benefits in both pH>7.0 ( aOR=0.392, 95% CI:0.106-0.678) and pH≤7.0 subgroups ( aOR=0.385, 95% CI: 0.075-0.695; interaction P=0.183). Early IBP positively correlated with CPC scores ( ρ=0.40, P=0.007). Conclusions:Early IBP monitoring significantly improves survival and neurological outcomes in OHCA-ECPR patients, supporting its integration into standardized protocols.

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 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.