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.

OBJECTIVE To optimize the extraction process of flavonoids from Potentilla discolor .METHODS Deep eutectic solvents （DESs） were used as the extraction solvent to prepare test sample solutions. The contents of rutin， quercitrin， and kaempferol were determined by ultra-performance liquid chromatography. The analytic hierarchy process combined with the criteria importance through intercriteria correlation weighting method was employed to assign comprehensive weights to the contents of the three flavonoids， and calculate the comprehensive score. The optimal DESs were screened based on the comprehensive score.Mean while， using the comprehensive score as the response variable and the liquid-to-solid ratio， ultrasonic time， and urltrasonic temperature as the influencing factors， the extraction technology of flavonoids from P.discolor was optimized by Box-Behnken response surface methodology and subsequently validated.RESULTS The comprehensive weight coefficients of rutin， quercitrin， and kaempferol were 0.646 7， 0.207 5， and 0.145 8， respectively. The optimal DESs were choline chloride-lactic acid （molar ratio 1∶4） with a water content of 40%. The optimal extraction conditions were determined as follows： liquid-to-solid ratio of 25∶1， ultrasonic time of 40 min， and ultrasonic temperature of 50 ℃. The validation results showed that the average comprehensive score of three batches of samples was 99.28， with an RSD of 0.54% （ n ＝3）.CONCLUSIONS The optimal extraction technology of flavonoids from P. discolor based on DESs obtained in this study was stable and feasible.

Objective To investigate the factors influencing the prognosis of patients with cere-bral infarction(CI)and nursing risk management measures.Methods A retrospective analysis was conducted in 80 CI patients as study subjects.All patients underwent risk management,and their prognosis was assessed,with 58 patients in good prognosis group and 22 patients in poor prognosis group.General patient data and disease-related characteristics were collected,and differences were ana-lyzed using the Logistic regression equation to identify factors influencing patient prognosis.A receiver operating characteristic(ROC)curve was plotted to analyze the predictive value of these factors for poor prognosis.Results There were statistically significant differences between the poor prognosis group and the good prognosis group in terms of age,baseline National Institutes of Health Stroke Scale(NIHSS)score,and the presence of comorbid hypertension(P＜0.05).Logistic regression analysis revealed that these indicators were all influencing factors for poor prognosis in patients,with area under the curve val-ues ranging from 0.676 to 0.723,indicating high sensitivity and specificity.Conclusion Multiple factors,such as age,baseline NIHSS score,and comorbid hypertension,influence poor prognosis in CI patients and have certain predictive value for poor prognosis.

Acute kidney injury (AKI) has high morbidity and mortality, but effective clinical drugs and management are lacking. Previous studies have suggested that macrophages play a crucial role in the inflammatory response to AKI and may serve as potential therapeutic targets. Emerging evidence has highlighted the importance of forkhead box protein O1 (FoxO1) in mediating macrophage activation and polarization in various diseases, but the specific mechanisms by which FoxO1 regulates macrophages during AKI remain unclear. The present study aimed to investigate the role of FoxO1 in macrophages in the pathogenesis of AKI. We observed a significant upregulation of FoxO1 in kidney macrophages following ischemia-reperfusion (I/R) injury. Additionally, our findings demonstrated that the administration of FoxO1 inhibitor AS1842856-encapsulated liposome (AS-Lipo), mainly acting on macrophages, effectively mitigated renal injury induced by I/R injury in mice. By generating myeloid-specific FoxO1-knockout mice, we further observed that the deficiency of FoxO1 in myeloid cells protected against I/R injury-induced AKI. Furthermore, our study provided evidence of FoxO1's pivotal role in macrophage chemotaxis, inflammation, and migration. Moreover, the impact of FoxO1 on the regulation of macrophage migration was mediated through RhoA guanine nucleotide exchange factor 1 (ARHGEF1), indicating that ARHGEF1 may serve as a potential intermediary between FoxO1 and the activity of the RhoA pathway. Consequently, our findings propose that FoxO1 plays a crucial role as a mediator and biomarker in the context of AKI. Targeting macrophage FoxO1 pharmacologically could potentially offer a promising therapeutic approach for AKI.

JMJD1C (Jumonji Domain Containing 1C), a member of the lysine demethylase 3 (KDM3) family, is universally required for the survival of several types of acute myeloid leukemia (AML) cells with different genetic mutations, representing a therapeutic opportunity with broad application. Yet how JMJD1C regulates the leukemic programs of various AML cells is largely unexplored. Here we show that JMJD1C interacts with the master hematopoietic transcription factor RUNX1, which thereby recruits JMJD1C to the genome to facilitate a RUNX1-driven transcriptional program that supports leukemic cell survival. The underlying mechanism hinges on the long N-terminal disordered region of JMJD1C, which harbors two inseparable abilities: condensate formation and direct interaction with RUNX1. This dual capability of JMJD1C may influence enhancer-promoter contacts crucial for the expression of key leukemic genes regulated by RUNX1. Our findings demonstrate a previously unappreciated role for the non-catalytic function of JMJD1C in transcriptional regulation, underlying a mechanism shared by different types of leukemias.
Core Binding Factor Alpha 2 Subunit/genetics* ; Humans ; Leukemia, Myeloid, Acute/pathology* ; Jumonji Domain-Containing Histone Demethylases/chemistry* ; Gene Expression Regulation, Leukemic ; Oxidoreductases, N-Demethylating/genetics* ; Cell Line, Tumor

OBJECTIVE: The study aim was to investigate the effects of exposure to multiple environmental organic pollutants on cardiopulmonary health with a focus on the potential mediating role of oxidative stress. METHODS: A repeated-measures randomized crossover study involving healthy college students in Beijing was conducted. Biological samples, including morning urine and venous blood, were collected to measure concentrations of 29 typical organic pollutants, including hydroxy polycyclic aromatic hydrocarbons (OH-PAHs), bisphenol A and its substitutes, phthalates and their metabolites, parabens, and five biomarkers of oxidative stress. Health assessments included blood pressure measurements and lung function indicators. RESULTS: Urinary concentrations of 2-hydroxyphenanthrene (2-OH-PHE) ( β = 4.35% [95% confidence interval ( CI): 0.85%, 7.97%]), 3-hydroxyphenanthrene ( β = 3.44% [95% CI: 0.19%, 6.79%]), and 4-hydroxyphenanthrene (4-OH-PHE) ( β = 5.78% [95% CI: 1.27%, 10.5%]) were significantly and positively associated with systolic blood pressure. Exposures to 1-hydroxypyrene (1-OH-PYR) ( β = 3.05% [95% CI: -4.66%, -1.41%]), 2-OH-PHE ( β = 2.68% [95% CI: -4%, -1.34%]), and 4-OH-PHE ( β = 3% [95% CI: -4.68%, -1.29%]) were negatively associated with the ratio of forced expiratory volume in the first second to forced vital capacity. These findings highlight the adverse effects of exposure to multiple pollutants on cardiopulmonary health. Biomarkers of oxidative stress, including 8-hydroxy-2'-deoxyguanosine and extracellular superoxide dismutase, mediated the effects of multiple OH-PAHs on blood pressure and lung function. CONCLUSION Exposure to multiple organic pollutants can adversely affect cardiopulmonary health. Oxidative stress is a key mediator of the effects of OH-PAHs on blood pressure and lung function.
Humans ; Oxidative Stress/drug effects* ; Male ; Cross-Over Studies ; Female ; Young Adult ; Environmental Pollutants/toxicity* ; Environmental Exposure/adverse effects* ; Biomarkers/blood* ; Adult ; Blood Pressure/drug effects* ; Polycyclic Aromatic Hydrocarbons/urine* ; Beijing