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:Inter-limb asymmetry is a common phenomenon observed during human growth and development.Prolonged specialized training can lead to specific adaptations in inter-limb asymmetry among athletes.OBJECTIVE:To review the formation causes,manifestations,and impacts of inter-limb asymmetry on sports performance,and provide an overview of the relevant assessment methods and intervention strategies.METHODS:A literature search was conducted in the CNKI,WanFang,PubMed,and Web of Science databases from their inception to September 2024.The search terms included"asymmetry,asymmetries,asymmetric,asymmetrical,imbalance,strength,power,force,jump,sprint,athletic performance,anthropometry,injury"in English and Chinese.After excluding duplicate publications,irrelevant content,and conference papers,a total of 131 articles were finally included for analysis.RESULTS AND CONCLUSION:(1)Inter-limb asymmetry can be influenced by various factors including genetics,task demands,training regimens,injuries,fatigue,and limb preference.These factors lead to being primarily manifested in anatomical structure,strength performance,and task-specific asymmetry.(2)An increase in inter-limb asymmetry can result in impaired performance in bilateral in-phase symmetric movements.However,the relationship between increased inter-limb asymmetry and bilateral out-of-phase symmetric movements remains unclear and requires further investigation.(3)Training interventions have been shown to effectively mitigate inter-limb asymmetry,with unilateral training demonstrating superior outcomes compared with bilateral training.The choice of training methods and content should be tailored to meet the specific demands of the sport.(4)To further clarify the relationship between inter-limb asymmetry and athletic performance,it is recommended that future research adopt the concept of"task specificity"in inter-limb asymmetry.This includes standardizing study designs,selecting sensitive testing methods and indicators,unifying calculation methods to provide more high-quality evidence,and establishing categorized warning threshold standards for inter-limb asymmetry in different sports.

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.

ObjectiveTo investigate the effects of modified Buyang Huanwu Tang on cerebral ischemia-reperfusion injury （CI/RI） in mice via the PTEN-induced putative kinase 1/E3 ubiquitin ligase （PINK1/Parkin） signaling pathway-mediated mitophagy， and to explore the underlying mechanism by which modified Buyang Huanwu Tang improves CI/RI. MethodsSeventy-two male C57BL/6J mice were randomly divided into six groups （n = 12 per group）： Sham-operated group， middle cerebral artery occlusion/reperfusion （MCAO/R） model group， low-， medium-， and high-dose modified Buyang Huanwu Tang groups （8.84， 17.68， 35.36 g·kg^-1·d^-1）， and an aspirin group （13.00 mg·kg^-1·d^-1）. Neurological deficit scores were assessed using the Zea-Longa method. Cerebral infarct volume ratio was measured by 2，3，5-triphenyltetrazolium chloride （TTC） staining. Histopathological changes and neuronal injury in brain tissues were observed using hematoxylin-eosin （HE） staining and Nissl staining. Apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL） assay. Mitochondrial ultrastructure in brain tissue was observed by transmission electron microscopy （TEM）. Serum levels of superoxide dismutase （SOD） and malondialdehyde （MDA） were determined by enzyme-linked immunosorbent assay （ELISA）. The mRNA and protein expression levels of PINK1， Parkin， microtubule-associated protein 1 light chain 3B （LC3B， LC3Ⅱ/Ⅰ）， and p62 in brain tissues were detected by real-time quantitative reverse transcription PCR （Real-time PCR） and Western blot， respectively. ResultsCompared with the sham-operated group， the MCAO/R model group showed significantly increased neurological deficit scores and cerebral infarct volume ratios （P<0.01）. Severe cortical injury on the infarct side was observed， characterized by decreased neuronal density， cytoplasmic vacuolation， nuclear pyknosis， a marked reduction in Nissl bodies， dissolution of Nissl bodies in the cytoplasm of some pyramidal neurons， and blurred cellular boundaries. The number of TUNEL-positive cells increased significantly （P<0.01）. Mitochondria exhibited cristae membrane rupture and matrix vacuolation， with rupture of the outer mitochondrial membrane and formation of autophagosomes， the number of which increased significantly. Serum SOD activity decreased significantly （P<0.01）， while MDA content increased significantly （P<0.01）. In infarcted brain tissues of model mice， the relative mRNA expression and protein levels of PINK1， Parkin and LC3B were significantly increased （P<0.05， P<0.01）， whereas p62 mRNA and protein expression were significantly decreased （P<0.05， P<0.01）， showing statistical significance. Compared with the model group， all treatment groups showed significantly decreased neurological deficit scores and cerebral infarct volume ratios （P<0.01）. Neuronal density increased significantly， cytoplasmic vacuolation was alleviated， nuclear morphology tended to be more regular and clearer， Nissl body density increased significantly with reduced dissolution and improved contour clarity. The mitochondrial cristae structure was partially restored， with some mitochondria showing autophagosome encapsulation， and the degree of mitochondrial damage was alleviated. Serum SOD activity increased significantly （P<0.01）， while MDA content decreased significantly. The mRNA and protein expression levels of PINK1， Parkin， and LC3Ⅱ/Ⅰ were significantly increased （P<0.05， P<0.01）， while p62 mRNA and protein expression in the low- and medium-dose modified Buyang Huanwu Tang groups were significantly decreased （P<0.05， P<0.01）， showing statistical significance. ConclusionModified Buyang Huanwu Tang can upregulate the protein expression levels of PINK1， Parkin， and LC3Ⅱ/Ⅰ and downregulate p62 protein expression， suggesting that it may improve CI/RI by regulating the expression of proteins related to the PINK1/Parkin signaling pathway. Regulation of the mitophagy pathway may be one of the mechanisms by which modified Buyang Huanwu Tang alleviates CI/RI in mice.

National biological standards for antibiotics are critical components of the antibiotic quality control system and serve as reference materials for measuring and calibrating the biological activity of antibiotics. This article systematically reviews the classification, definition of potency units, and current research status of commercially available national antibiotic biological standards in China. At present, these standards can be categorized based on chemical structure, number of components, and development methods. The definition of potency units has evolved from an early “arbitrarily assigned unit” to “being represented by the mass of the antibiotic salt” and, more recently, to the current mainstream approach of “being represented by the mass of the active ingredient”. This evolution reflects a shift in quality control philosophy from primarily biological analysis to a system dominated by chemical analysis supplemented by biological methods. Current research focuses on optimizing potency determination methods, studying the unification of content and potency, and implementing dual quality control of both the potency and the ratio/content of active components in multi-component antibiotics. For complex multi-component antibiotics, the microbiological assay based on biological activity remains irreplaceable in quality control. Future efforts should emphasize further method optimization, ensuring batch-to-batch consistency of standards, and advancing precision quality control as key research priorities for antibiotic biological standards.

Narcotic plants are strictly regulated worldwide due to their ability to extract drug alkaloids and drug precursor components. Besides the three traditional core species, cannabis, opium poppy, and coca, the misuse of psychoactive plants with addictive properties has become increasingly prevalent globally in recent years, and the establishment of accurate identification methods for such plants has become an urgent need in the field of narcotics control. Within existing identification frameworks, the conventional morphological and chemical analysis methods, despite their long-term application, have demonstrated considerable limitations. In contrast, DNA-based molecular identification techniques have achieved significant advancement in recent years due to their high specificity and stability. This review comprehensively examines current DNA-based identification approaches for narcotic plants through three key dimensions: DNA molecular marker technology, DNA barcoding technology, and emerging molecular biological techniques, and elaborates on the principles, technical characteristics, application scenarios, and research progress of each technology, providing some reference for the scientific selection of DNA identification strategies for narcotic plants in different specific scenarios.

This study aimed to investigate the effects of zidovudine (AZT) on high-fat diet (HFD)-induced metabolic disturbances in rats and its underlying mechanisms. The HFD rat model was established, and the animals were divided into the control group, the model group, and the AZT-treated group at low (25 mg/kg) and high (50 mg/kg) doses. Metabolic phenotype, hepatic lipid deposition, oxidative stress, mitochondrial function, and peroxisome proliferator-activated receptor (PPAR) signaling were evaluated. AZT treatment significantly mitigated HFD-induced body weight gain and reduced both the mass and adipocyte size of inguinal and epididymal white adipose tissues; it also enhanced metabolic flexibility and improved glucose tolerance without elevating blood lactate levels. High-dose AZT further lowered hepatic triglyceride accumulation, ameliorated steatosis, and additionally, attenuated hepatic oxidative stress by increasing superoxide dismutase (SOD) activity and decreasing malondialdehyde (MDA) levels. Western blot analysis revealed that AZT upregulated hepatic PPARα and carnitine palmitoyltransferase 1α (CPT1α), while downregulating PPARγ expression. In conclusion, AZT effectively ameliorates HFD-induced metabolic disorders without inducing mitochondrial toxicity, which may be related to the promotion of fatty acid oxidation, the reduction of oxidative stress, and the modulation of both the PPAR signaling pathway and pyrimidine metabolism.

The therapeutic effect of human umbilical cord mesenchymal stem cells (hUCMSCs) combined with intestinal probiotics on the wound healing of diabetic mice and its potential mechanism were explored. A diabetic wound mouse model was established, and 25 male C57BL/6J mice were randomly divided into five groups: blank control group, model group, hUCMSCs treatment group, probiotics treatment group, and hUCMSCs combined with probiotics treatment group. The wound healing conditions were photographed and recorded on days 0, 3, 6, 9, and 12 after modeling, and the differences in wound healing rates among the groups were analyzed. HE and Masson staining were used to observe the histopathological changes and collagen deposition. CD31 immunofluorescence was used to detect angiogenesis. Collagen I immunohistochemistry was used to evaluate the formation of type I collagen. ELISA was used to detect the expression levels of anti-inflammatory factors (Arg1) and pro-inflammatory factors (IL-6, IL-1β, TNF-α) in wounded skin tissue and serum. The results showed that on day 12 after modeling, compared with the other groups, the combined treatment group had the most significant wound contraction and the fastest healing rate. HE and Masson staining showed that the combined treatment group had the fastest epithelialization and the most collagen deposition. Immunofluorescence and immunohistochemistry showed that the combined treatment group had the highest expression levels of CD31 and Collagen I. ELISA results indicated that the combined treatment group had higher expression levels of Arg1 in wound skin tissue and serum than the other groups, while the expression levels of IL-6, IL-1β, and TNF-α were significantly lower. These results suggest that the combined treatment of hUCMSCs and intestinal probiotics can accelerate wound healing in diabetic mice through mechanisms such as promoting angiogenesis, enhancing collagen deposition, and regulating the inflammatory microenvironment. The therapeutic effect was significantly better than that of single treatment, providing a new potential strategy for the clinical treatment of diabetic foot.

Abstract Adverse childhood experiences (ACEs) exposure is a pressing and severe global public health issue. Children and adolescents exposed to multiple ACEs are highly susceptible to toxic stress and impaired physiological functioning, which significantly jeopardize their physical and mental health. Effective prevention and intervention strategies can reduce the prevalence of ACEs and mitigate their severe impacts, thereby minimizing the long term detrimental consequences on future outcomes. The review provides a comprehensive review of intervention strategies across four dimensions: individual, family, school, and public services/policy, so as to establish a theoretical foundation for implementing effective interventions for children and adolescents exposed to adverse childhood experiences.

ObjectiveTo investigate the regulatory effect of overexpressed protein tyrosine phosphatase non-receptor type 2 （Ptpn2） on the inflammatory response of mouse alveolar macrophages （MH-S） induced by SiO₂. MethodsCells with overexpressed Ptpn2 were constructed and induced by SiO₂. The experimental groups were divided into four groups： the negative control group with an empty vector （NC）， the overexpressed Ptpn2 group （P）， the negative control group with an empty vector + SiO₂ induction （NS）， and the overexpressed Ptpn2 + SiO₂ induction group （PS）. Isobaric tags for relative and absolute quantification （iTRAQ） combined with liquid chromatography-tandem mass spectrometry （LC-MS/MS） were used to screen differential proteins， followed by Gene Ontology （GO） and Kyoto Encyclopedia of Genes and Genomes （KEGG） database analyses. Immunofluorescence staining was used to detect the expressions of Tumor necrosis factor （TNF） α， Gasdermin D （GSDMD）， and Transforming growth factor （TGF）-β1. Western blot was used to detect the protein expression levels of PTPN2， Toll-like receptor 4 （TLR4）， tumor necrosis factor-α （TNF-α）， nucleotide-binding oligomerization domain-like receptor protein 3 （NLRP3）， and proteins related to the TGF-β1 signaling pathway in the cells of each group. ResultsiTRAQ results identified 144 differential proteins among the four groups. GO analysis showed that in biological processes （BP）， these differential proteins were mainly enriched in IκB kinase/nuclear factor-κB （NF-κB） signaling， cell activation and signal transduction involved in immune responses， and regulation of receptor signaling pathways by signal transducer and activator of transcription （STAT）， etc. KEGG analysis revealed that the differential proteins were mainly enriched in Toll-like receptor signaling pathway， NF-κB signaling pathway， NOD-like receptor signaling pathway， TGF-β signaling pathway， and TNF signaling pathway. The results of immunofluorescence staining showed that compared with the NC group， the expressions of TNF α， GSDMD， and TGF-β1 in the cells of the NS group increased （P < 0.05）； compared to the NS group， the expression of the aforementioned proteins in the PS group decreased in cellular proteins（P < 0.05）. The results of Western blot showed that compared with the NC group， the protein expression levels of PTPN2， p-NF-κB，MyD88，TLR4，NLRP3，GSDMD，Caspase-1，IL-1β， TGF-βR1， TGF-βR，p-Smad2/3 in the NS group were significantly upregulated （P < 0.05）； compared with the NS group， the expression levels of the aforementioned proteins in the PS group were significantly downregulated （P < 0.05）. ConclusionOverexpression of Ptpn2 can inhibit the protein expressions of TLR4-TNF-α signaling， NLRP3 signaling， and TGF-β1 signaling closely related to inflammatory response in SiO₂-mediated MH-S macrophages.