In endovascular treatment of peripheral arterial disease, paclitaxel-coated device (PCD) have been widely used to reduce vascular restenosis, yet their safety remains controversial. Some scholars have suggested that PCD might increase long-term mortality, sparking widespread concern and debate. In recent years, a number of studies have provided support for the safety of PCD, believing that PCD have advantages in terms of re-intervention, patency rate, and reduction of amputation risk, and do not increase the risk of death. There is no direct relationship between the paclitaxel dose and mortality. Overall, the safety controversy primarily stems from methodological limitations in early studies. The latest research has provided safety evidence for their clinical application. However, further investigations are required to define the boundary conditions for their long-term safety, elucidate variations in responses across different patient populations, and clarify paclitaxel′s mechanisms of action in vivo. Such efforts will facilitate optimal balancing of therapeutic efficacy and safety in clinical applications.

Background: Salvia miltiorrhiza Bunge, commonly known as “Danshen” in China due to the distinctive red color of its roots, is one of the most widely used traditional Chinese medicines. It is cultivated in various regions across China, and environmental differences among these regions can affect the secondary metabolites of plants, thereby influencing the quality of S. miltiorrhiza. In recent years, increasing demand for S. miltiorrhiza has exacerbated the problem of origin fraud. Therefore, ensuring the authenticity of its geographical origin is crucial for the sustainable development of the industry. Objective: The red coloration of S. miltiorrhiza is closely associated with the content of its primary active compounds, particularly tanshinones. Therefore, both its internal chemical composition and external color characteristics serve as key indicators for quality assessment. This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S. miltiorrhiza. Methods: Spectral data reflecting the internal chemical properties of S. miltiorrhiza were integrated with color information representing its external features through 3 levels of data fusion. These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification. Results: The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72% by integrating image color and short-wave infrared spectral data. Conclusion: This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S. miltiorrhiza.

In recent years, the rapid development of transportation and sports industries, coupled with the accelerated population aging in China, has led to a steady increase in the incidence of articular cartilage injuries, wear, and degenerative changes. Currently, the clinical treatment options for cartilage defects primarily include conservative therapies and surgical interventions, both of which have certain limitations. Cartilage tissue engineering (CTE), as a novel technology, provides an infinite prospect for cartilage regeneration and repair. Because of the abilities of scaffolds to mimic the natural cartilage structure, exhibit excellent biocompatibility and biomimetic mechanical properties, and promote cell adhesion and proliferation, scaffolds are considered effective delivery systems for growth factors, genes, and drugs. This review summarizes the clinical treatments for cartilage defects and their limitations, discusses the materials and preparation techniques of scaffolds used in CTE, with a particular focus on drug-loaded scaffold delivery systems in cartilage repair and regeneration, and offers a perspective on the future application of drug-loaded CTE. The aim is to provide theoretical guidance and new approaches for the repair of cartilage defects.
Tissue Engineering/methods* ; Humans ; Tissue Scaffolds ; Drug Delivery Systems/methods* ; Regeneration ; Cartilage, Articular/physiology* ; Animals ; Biocompatible Materials

Obesity and overweight remain major global public health challenges.In this paper,we examine current applications of digital nutrition technologies in weight management using the scoping review framework of Arksey and O'Malley.Visual recognition technologies have evolved from early-stage food image recognition into more advanced systems,although the vast diversity of food types continues to pose challenges for accuracy and generalizability.The combination of wearable devices and non-wearable sensors has increased the diversity of collected data and improved user comfort.Data integration and analysis tools,such as digital virtual twins,support personalized interventions by integrating multidimensional data.In addition,emerging applications have demonstrated encouraging clinical outcomes.However,existing studies have limitations,such as small sample sizes,high levels of information bias,and low evidence quality.Barriers,such as limited accessibility and high initial costs,further constrain the scalability of digital nutrition tools.Future studies should focus on expanding sample sizes,improving population diversity,and developing effective assessment methods and adjustments for specific target populations.Privacy and data security concerns must also be addressed to ensure safe implementation.Overall,digital nutrition technologies offer a promising approach to weight management,but continuous efforts in research and cost reduction are needed to fully realize their potential in weight management and to promote health for all.

The rapid development of digital intelligence technology has brought profound changes to medical edu-cation.Against this background,this study mainly focuses on the characteristics of digital and intelligent medical talent training and to analyzes its impact on teachers' teaching methodology.This puts forward some innovative sug-gestions based on the current technology development and application in order to improve the strategy development and capacity building in terms of support medical education and reformation with digital and intelligence technology.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.

Coronary heart disease with angina pectoris,characterized by myocardial ischemic injury as its fundamental pathological mechanism,represents a prevalent cardiovascular condition.The"State-Target Differential Diagnosis and Treatment"presents a holistic regulatory framework,integrating macroscopic state regulation with microscopic targeting.Guided by this approach,the pathological evolution of coronary heart disease is examined through four dimensions:"state-target-cause-effect."The"cause"encompasses both the pathogenesis and etiological factors of traditional Chinese and Western medicine.The"effect"manifests as adverse cardiovascular events,including myocardial infarction and heart failure.The"state"delineates the progressive development pattern of qi to blood to deficiency,beginning with qi stagnation and cold congealment in the initial stage,followed by blood stasis and phlegm obstruction in the intermediate stage,and culminating in qi-blood deficiency in the advanced stage.The"target"encompasses multi-level therapeutic interventions addressing both symptomatic manifestations and clinical indicators.Building on this theoretical foundation,this research focuses on the pattern of qi sinking and blood stasis commonly observed in late-stage angina,systematically elucidating its state regulation and targeting therapeutic strategies.Using the clinical empirical formula Shengxian Quyu Decoction as the baseline state prescription,an in-depth investigation was conducted to determine optimal combination patterns of symptom-and biomarker-targeted medications.This study aims to establish a modernized differential treatment system for angina pectoris with the pattern of qi sinking and blood stasis,providing novel research perspectives and theoretical foundations for enhancing clinical efficacy and reducing the risk of cardiovascular events.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Background:Salvia miltiorrhiza Bunge,commonly known as"Danshen"in China due to the distinctive red color of its roots,is one of the most widely used traditional Chinese medicines.It is cultivated in various regions across China,and environmental differences among these regions can affect the secondary metabolites of plants,thereby influencing the quality of S.miltiorrhiza.In recent years,increasing demand for S.miltiorrhiza has exacerbated the problem of origin fraud.Therefore,ensuring the authenticity of its geo-graphical origin is crucial for the sustainable development of the industry.Objective:The red coloration of S.miltiorrhiza is closely associated with the content of its primary active compounds,particularly tanshinones.Therefore,both its internal chemical composition and external color characteristics serve as key indicators for quality assessment.This study utilized hyperspectral imaging technology to evaluate its potential in classifying the geographical origin of S.miltiorrhiza.Methods:Spectral data reflecting the internal chemical properties of S.miltiorrhiza were integrated with color information represent-ing its external features through 3 levels of data fusion.These fused datasets were then combined with deep learning algorithms to achieve accurate origin classification.Results:The results demonstrated that the Transformer model combined with soft-voting decision-level fusion achieved the highest classification accuracy of 98.72％by integrating image color and short-wave infrared spectral data.Conclusion:This study demonstrates that integrating hyperspectral imaging spectral data with color information provides a reliable and innovative approach for verifying the authenticity and traceability of S.miltiorrhiza.