Radar-based non-contact health monitoring technology (RBNHMT) has emerged as a transformative paradigm in continuous health sensing, enabling non-invasive and continuous monitoring of physiological parameters and behavioral patterns by transmitting electromagnetic waves, analyzing the reflected signals, and detecting subtle bodily movements—ranging from millimeter-scale chest wall displacements due to respiration to micro-scale vibrations associated with cardiac activity—ultimately transforming them into quantifiable health data. Distinguished by its non-contact operation, inherent privacy preservation, and adaptability to diverse scenarios, RBNHMT exhibits stronger resistance to environmental interference than conventional contact-based monitoring, and has solidified its position as a prominent and dynamic research focus in the field of non-contact health monitoring. Currently, significant and multifaceted progress has been made across several key areas. In human activity recognition (HAR), systems leveraging micro-Doppler signatures or point cloud sequences achieve high-precision detection of gait, gestures, and fall events, with state-of-the-art deep learning-based models achieving accuracy rates exceeding 99% in controlled experimental settings. For vital sign and sleep monitoring, it not only tracks respiratory and heart rates continuously but also extracts clinically relevant metrics such as heart rate variability (HRV) for autonomic nervous system assessment and estimates blood pressure through indirect methods like pulse transit time analysis, while maintaining robustness in dynamic settings through advanced motion compensation algorithms. In sleep monitoring, it further enables sleep posture classification and apnea event detection. In emotion and stress recognition, it provides a non-intrusive approach for psychological assessment by analyzing autonomic-response physiological signal patterns or behavioral features. Furthermore, its applications in auxiliary medical diagnosis have expanded to promising interdisciplinary areas such as non-contact heart sound auscultation, radar-based screening for obstructive sleep apnea (OSA), and emerging research into breast cancer detection using microwave and millimeter-wave imaging techniques. However, several challenges impede its practical deployment. Signal quality is significantly compromised by multipath interference in complex indoor environments and clutter from static objects, and by motion artifacts in dynamic scenarios where gross body movements obscure the subtle physiological signals. Algorithmically, separating signals from multiple targets in close proximity and calibrating for substantial individual physiological differences, such as body habitus, baseline vital signs, remain difficult and limit generalizability. Hardware design also faces the challenge of balancing power consumption, cost, integration, and performance, often requiring trade-offs that constrain miniaturization, battery life, or measurement sensitivity. Future advancement, therefore, requires collaborative and targeted innovation across multiple dimensions. Algorithmically, developing adaptive signal processing models based on emerging paradigms such as few-shot learning (for user-specific calibration with minimal data) and reinforcement learning (for dynamic noise suppression) is essential. At the hardware level, highly integrated radar SoCs with embedded processing capabilities and advanced packaging technologies are crucial for achieving the dual goals of device miniaturization and cost reduction without sacrificing performance. At the system level, fusing radar data with complementary modalities such as infrared and acoustic sensing can create a synergistic, multi-modal framework that significantly enhances perceptual robustness and reliability in complex, real-world environments. This review provides a comprehensive synthesis that systematically summarizes the relevant theoretical foundations and application progress, and offers an in-depth analysis of the current technical bottlenecks. It aims to provide a clear development path and a foundational academic reference for the in-depth integration and practical application of RBNHMT in critical scenarios including rehabilitation engineering, smart elderly care, in-vehicle health monitoring, and beyond, thereby offering innovative technical support for the vision of universal, proactive, and personalized health management.

BACKGROUND: Based on the China-VHD database, this study sought to develop and validate a Valvular Heart Disease- specific Age-adjusted Comorbidity Index (VHD-ACI) for predicting mortality risk in patients with VHD. METHODS & RESULTS: The China-VHD study was a nationwide, multi-centre multi-centre cohort study enrolling 13,917 patients with moderate or severe VHD across 46 medical centres in China between April-June 2018. After excluding cases with missing key variables, 11,459 patients were retained for final analysis. The primary endpoint was 2-year all-cause mortality, with 941 deaths (10.0%) observed during follow-up. The VHD-ACI was derived after identifying 13 independent mortality predictors: cardiomyopathy, myocardial infarction, chronic obstructive pulmonary disease, pulmonary artery hypertension, low body weight, anaemia, hypoalbuminaemia, renal insufficiency, moderate/severe hepatic dysfunction, heart failure, cancer, NYHA functional class and age. The index exhibited good discrimination (AUC, 0.79) and calibration (Brier score, 0.062) in the total cohort, outperforming both EuroSCORE II and ACCI (P < 0.001 for comparison). Internal validation through 100 bootstrap iterations yielded a C statistic of 0.694 (95% CI: 0.665-0.723) for 2-year mortality prediction. VHD-ACI scores, as a continuous variable (VHD-ACI score: adjusted HR (95% CI): 1.263 (1.245-1.282), P < 0.001) or categorized using thresholds determined by the Yoden index (VHD-ACI ≥ 9 vs. < 9, adjusted HR (95% CI): 6.216 (5.378-7.184), P < 0.001), were independently associated with mortality. The prognostic performance remained consistent across all VHD subtypes (aortic stenosis, aortic regurgitation, mitral stenosis, mitral regurgitation, tricuspid valve disease, mixed aortic/mitral valve disease and multiple VHD), and clinical subgroups stratified by therapeutic strategy, LVEF status (preserved vs. reduced), disease severity and etiology. CONCLUSION The VHD-ACI is a simple 13-comorbidity algorithm for the prediction of mortality in VHD patients and providing a simple and rapid tool for risk stratification.

This study aimed to identify ideal pharmaceutical candidates featuring strong anti-HIV-1 activity and desirable drug-like characteristics. Our endeavor involved the implementation of a bioisosterism strategy, leading to the discovery of an assemblage of halogen-containing biphenyl-diarylpyrimidines as potent HIV-1 non-nucleoside reverse transcriptase inhibitors. Notably, compound A12 demonstrated exceptional efficacy against both WT HIV-1 (EC₅₀ = 1.9 nmol/L) and seven mutant strains (EC₅₀ = 1.7-157 nmol/L), surpassing that of the lead compound 6 and comparable to etravirine. Furthermore, this analog exhibited minimal adverse effects with significantly reduced cytotoxicity (CC₅₀ = 195 μmol/L) and a high selectivity index (SI = 102,608), superior to those of etravirine (CC₅₀ > 4.6 μmol/L, SI > 1436) and rilpivirine (CC₅₀ = 3.98 μmol/L, SI = 3989). It displayed low inhibition of CYP (IC₅₀ = 6.99-25 μmol/L) and hERG (IC₅₀ > 40 μmol/L), indicating a safer profile compared to etravirine and rilpivirine. No acute toxicity or organ pathological damage was observed at a single dose of 2 g/kg. Additionally, A12 exhibited favorable oral bioavailability (F = 29.2%) and an extended elimination half-life (T _1/2 = 13.56 h), enabling convenient oral administration at minimal doses. These findings indicated that A12 could serve as a promising drug candidate for HIV treatment.

OBJECTIVE: To elucidate the specific mechanisms by which electroacupuncture (EA) alleviates anxiety and fear behaviors associated with posttraumatic stress disorder (PTSD), focusing on the role of lipocalin-2 (Lcn2). METHODS: The PTSD mouse model was subjected to single prolonged stress and shock (SPS&S), and the animals received 15 min sessions of EA at Shenmen acupoint (HT7). Behavioral tests were used to investigate the effects of EA at HT7 on anxiety and fear. Western blotting and enzyme-linked immunosorbent assay were used to quantify Lcn2 and inflammatory cytokine levels in the prefrontal cortex (PFC). Additionally, the activity of PFC neurons was evaluated by immunofluorescence and in vivo electrophysiology. RESULTS: Mice subjected to SPS&S presented increased anxiety- and fear-like behaviors. Lcn2 expression in the PFC was significantly upregulated following SPS&S, leading to increased expression of the proinflammatory cytokines tumor necrosis factor-α and interleukin-6 and suppression of PFC neuronal activity. However, EA at HT7 inhibited Lcn2 release, reducing neuroinflammation and hypoexcitability in the PFC. Lcn2 overexpression mitigated the effects of EA at HT7, resulting in anxiety- and fear-like behaviors. CONCLUSION EA at HT7 can ameliorate PTSD-associated anxiety and fear, and its mechanism of action appears to involve the inhibition of Lcn2-mediated neural activity and inflammation in the PFC. Please cite this article as: Yang YD, Zhong W, Chen M, Tang QC, Li Y, Yao LL, et al. Electroacupuncture alleviates behaviors associated with posttraumatic stress disorder by modulating lipocalin-2-mediated neuroinflammation and neuronal activity in the prefrontal cortex. J Integr Med. 2025; 23(5):537-547.
Electroacupuncture ; Stress Disorders, Post-Traumatic/metabolism* ; Animals ; Lipocalin-2/metabolism* ; Prefrontal Cortex/physiopathology* ; Male ; Mice ; Neurons/physiology* ; Disease Models, Animal ; Fear ; Behavior, Animal ; Mice, Inbred C57BL ; Neuroinflammatory Diseases/metabolism* ; Anxiety/therapy* ; Acupuncture Points

Objective To analyze the medication rules of Chinese herbal concentrated-granule for the treatment of hypertension nationwide using data mining and knowledge graph methods,thus to provide evidence for expanding its application in treating hypertension.Methods From January 2022 to March 2023,Chinese herbal concentrated-granule prescriptions for hypertension prescribed by traditional Chinese medicine experts nationwide were collected.Microsoft Excel was used to analyze the frequency,properties and flavors,meridian tropism,and efficacy categories of the medicinals.Hierarchical clustering was applied for cluster analysis,and the Neo4j graph database was utilized to construct an information knowledge graph illustrating the relationships between regions and medicinals.Results A total of 2 600 Chinese herbal concentrated-granule prescriptions were included,involving 370 medicinals.The top six frequently-used medicinals were Poria(Fuling),Glycyrrhizae Radix et Rhizoma(Gancao),Atractylodis Macrocephalae Rhizoma(Baizhu),Citri Reticulatae Pericarpium(Chenpi),Paeoniae Radix Alba(Baishao),and Angelicae Sinensis Radix(Danggui).The properties of the medicinals were mainly warm and mild,and their flavors were usually sweet,pungent,and bitter.The medicinals frequently have the meridian tropism of the spleen,lung,and liver meridians.Hierarchical clustering yielded seven clusters.The information knowledge graph of region-medicinals relationships revealed that medicinals used in five or more regions were Baishao,Baizhu,Chenpi,Pinelliae Rhizoma(Banxia),Fuling,Gastrodiae Rhizoma(Tianma),Bupleuri Radix(Chaihu),Chuanxiong Rhizoma(Chuanxiong),Salviae Miltiorrhizae Radix et Rhizoma(Danshen),Danggui,Gancao,and Astragali Radix(Huangqi).Conclusion Chinese herbal concentrated-granule for hypertension usually consist of tonifying medicinals,with sweet and warm properties,and having the meridian tropism of the spleen meridian.And the medicinals composed of the prescriptions often have the actions of calming the liver and suppressing yang,strengthening the spleen and removing dampness,and nourishing the liver and kidney.

Objective To analyze the relationship between the visceral adiposity index(VAI)and nocturia in the US adult population.Methods A cross-sectional study was performed.Data from subjects aged≥20 years in the National Health and Nutrition Examination Survey(NHANES)database from 2007 to 2020 were collected,including waist circumference,triglyceride,body mass index(BMI),high-density lipoprotein,age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,cancer,and nocturnal urination frequency.Weighted analysis,multivariate logistic regression,generalized additive model(GAM),and curve fitting were employed to evaluate the association between VAI and nocturia,adjusting for age,gender,race,poverty income ratio,education level,marital status,smoking,alcohol consumption,sleep disorders,depression,occupation,hypertension,diabetes,congestive heart failure,and cancer.Subgroup analyses were conducted based on age,gender,race,hypertension and diabetes to further evaluate the relationship between VAI and the risk of nocturia.Results A total of 29,196 American adults were included.All subjects were divided into 4 groups based on VAI quartiles:Q1 group(0.32≤VAI<1.01),Q2 group(1.01≤VAI<1.70),Q3 group(1.70≤VAI<2.95),and Q4 group(2.95≤VAI<13.59),with nocturia prevalence rates of 28.5%,31.4%,33.3%,and 34.9%,respectively.In subgroup analyses,the risk of nocturia significantly increased with higher VAI in the 20-40 age group,females and other Hispanics(OR=1.04,95%CI 1.01-1.08,P=0.006;OR=1.02,95%CI 1.00-1.04,P=0.035;OR=1.05,95%CI 1.01-1.09,P=0.026).GAM analysis results showed a nonlinear relationship between VAI and nocturia.Conclusion VAI is positively associated with the risk of nocturia,and may be an effective indicator for predicting the risk of nocturia occurrence.

Objective:To propose suggestions for the revision of quality standard of steviol glycosides through research on its major manufacturer's products.Methods:The inspection items in the current quality standards were inspected,with domestic and international quality standard of steviol glycosides.Results:Specific rotation was from-33.39° to-39.50°,pH was from 5.3 to 6.7,impurity absorbency was lower than 0.096 0,while the contents of weight loss on drying were lower than 5.0％,residue on ignition were lower than 0.043％,methanol residual were lower than 0.01％,ethanol residual were lower than 0.06％,residue on arsenic were lower than 0.000 054％,lead wasn't detected.The content of rebaudioside A and 13 kinds of steviol glycosides were 8.23％-68.48％and 85.78％-96.13％.Conclusion:The main components of the commercial steviol glycosides products were rebaudioside A and stevioside,with low safety risk of elemental impurities and solvent residues.It provided suggestions for the revision of quality standard of steviol glycosides in the Chinese Pharmacopoeia.

Small RNAs (sRNAs), the key components of RNA interference (RNAi) or RNA silencing, can mediate cell-autonomous gene silencing and function as signaling molecules across species. Microbe-induced gene silencing (MIGS), which is based on interspecies RNAi, is an effective approach for controlling fungal diseases in crops. The enolase gene VdEno is essential for the growth and development of the fungal pathogen Verticillium dahliae, which causes cotton Verticillium wilt. In this study, we engineered Trichoderma harzianum (Th) to express the double-stranded RNA (dsRNA) targeting VdEno. The engineered strain Th-VdEnoi successfully generated VdEno-specific small interfering RNA (siVdEno). We further confirmed that Th-VdEnoi effectively induced VdEno silencing at the translational level. The results of crop protection assays revealed that the cotton plants co-inoculated with V. dahliae (strain V592) and Th-VdEnoi presented significantly reduced disease severity and lower fungal biomass in their roots than the control plants inoculated with V. dahliae alone or with V. dahliae and Th-GFPi (a control strain expressing GFP-targeting dsRNA). Collectively, our findings demonstrate that VdEno is an effective target for controlling cotton Verticillium wilt and confirm that MIGS is a promising strategy for managing soil-borne fungal pathogens in crops. MIGS provides strong technical support for reducing the application of conventional chemical pesticides, developing eco-friendly biopesticides, and facilitating the sustainable development of agriculture.
Gossypium/microbiology* ; Plant Diseases/prevention & control* ; Gene Silencing ; Ascomycota/genetics* ; RNA Interference ; RNA, Double-Stranded/genetics* ; Hypocreales/genetics* ; RNA, Small Interfering/genetics* ; Verticillium/genetics* ; Fungal Proteins/genetics*

An implantable cardiac monitor(ICM)is a subcutaneous electronic device for recording and remotely transmitting electrocardiographic events.New-generation ICM,like the Reveal LINQ,have extended arrhythmia monitoring duration and improved diagnostic yield through miniaturization,large storage capacity,and easy implantation.They provide comprehensive monitoring data for cardiovascular disease diagnosis and treatment,optimize individualized treatment plans,and enhance patient prognosis.In recent years,research on ICM in cardiovascular fields has deepened,and their clinical application scope has expanded.They show significant advantages and unique value and are widely used in early cardiovascular disease diagnosis and prognostic management.In the future,ICM are expected to play a bigger role in boosting diagnostic and prognostic capabilities for cardiovascular disease patients,offering stronger support for early disease detection,accurate diagnosis,and effective management.