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.

Diabetes is a very complex endocrine disease whose common feature is the increase in blood glucose concentration. Persistent hyperglycemia can lead to blindness, kidney and heart disease, neurodegeneration, and many other serious complications that have a significant impact on human health and quality of life. The number of people with diabetes is increasing yearly. The global diabetes prevalence in 20-79 year olds in 2021 was estimated to be 10.5% (536.6 million), and it will rise to 12.2% (783.2 million) in 2045. The main modes of intervention for diabetes include medication, dietary management, and exercise conditioning. Medication is the mainstay of treatment. Marketed diabetes drugs such as metformin and insulin, as well as GLP-1 receptor agonists, are effective in controlling blood sugar levels to some extent, but the preventive and therapeutic effects are still unsatisfactory. Peptide drugs have many advantages such as low toxicity, high target specificity, and good biocompatibility, which opens up new avenues for the treatment of diabetes and other diseases. Currently, insulin and its analogs are by far the main life-saving drugs in clinical diabetes treatment, enabling effective control of blood glucose levels, but the risk of hypoglycemia is relatively high and treatment is limited by the route of delivery. New and oral anti-diabetic drugs have always been a market demand and research hotspot. Inhibitor cystine knot (ICK) peptides are a class of multifunctional cyclic peptides. In structure, they contain three conserved disulfide bonds (C3-C20, C7-C22, and C15-C32) form a compact “knot” structure, which can resist degradation of digestive protease. Recent studies have shown that ICK peptides derived from legume, such as PA1b, Aglycin, Vglycin, Iglycin, Dglycin, and aM₁, exhibit excellent regulatory activities on glucose and lipid metabolism at the cellular and animal levels. Mechanistically, ICK peptides promote glucose utilization by muscle and liver through activation of IR/AKT signaling pathway, which also improves insulin resistance. They can repair the damaged pancrease through activation of PI3K/AKT/Erk signaling pathway, thus lowering blood glucose. The biostability and hypoglycemic efficacy of the ICK peptides meet the requirements for commercialization of oral drugs, and in theory, they can be developed into natural oral anti-diabetes peptide drugs. In this review, the structural properties, activity and mechanism of ICK pattern peptides in regulating glucose and lipid metabolism were summaried, which provided a reference for the development of new oral peptides for diabetes.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.

Objective To investigate the effect of Lactobacillus plantarum LB12 on kidney calcium oxalate stones in rats.Methods A total of 24 male SD rats aged 6～8 weeks were randomly divided into four groups:control group,model group,LB12 group,and LB12 intervention group,with 6 rats in each group.The control group and LB12 group had free access to water,and were gavaged with 2 mL of normal saline in the morning.In the evening,the control group received 2 mL of normal saline,while the LB12 group received 2 mL of Lactobacillus plantarum LB12 suspension.The model group and LB12 intervention group were given 1%ethylene glycol in drink-ing water and 2 mL of 2%ammonium chloride solution via gavage in the morning.In the evening,both groups received 2 mL of normal saline and 2 mL of Lactobacillus plantarum LB12 suspension,respectively.After the experiment,the body weight change trend of the rats was recorded,and the levels of urinary calcium,urinary oxalate,serum creatinine,blood urea nitrogen,renal SOD,and MDA were measured.Additionally,H&E staining,VK staining,immunohistochemistry,ROS fluorescence analysis,and Western blot(WB)were performed on kidney tissues.Results Lactobacillus plantarum LB12 demonstrated a 12.34%oxalate degradation rate in vitro.Further animal experiments indicated that Lactobacillus plantarum LB12 alleviated the weight loss trend in the model rats and reduced the levels of urinary calcium,urinary oxalate,serum creatinine,urea nitrogen,and MDA,while increasing SOD levels(P<0.05).Histopathological analysis revealed that the LB12 intervention group had signifi-cantly fewer renal crystals compared to the model group,with lower expressions of IL-6 and ROS(P<0.01).Western blot analysis demonstrated that Lactobacillus plantarum LB12 inhibited the expression of TLR4,NF-κB,and OPN proteins(P<0.01).Conclusions Lactobacillus plantarum LB12 can effectively alleviate the oxidative stress damage caused by calcium oxalate stones to the kidneys and reduce kidney crystal formation in rats.Further-more,it inhibits the expression of TLR4/NF-κB and OPN,making it a potential therapeutic approach for the prevention and treatment of kidney calcium oxalate stones.

Objective:To quantitatively analyze the motivation behind U.S.development assistance for health(DAH)in Sub-Saharan Africa since the 21st century,using a previously developed index system for DAH motivation analysis.The goal is to gain deeper insights into U.S.DAH motivation and provide scientific evidence and policy recommendations to inform the optimization of China's DAH strategies.Methods:Based on panel data of U.S.DAH to selected Sub-Saharan African countries from 2002 to 2021,a comprehensive feasible generalized least squares(FGLS)regression model was constructed to examine the determinants influencing the allocation of U.S.DAH.Results:The commercial trade benefits(β=0.325,P＜0.05)and the closeness of political relationship(β=0.334,P＜0.01)had significant positive influence on U.S.DAH allocation.In contrast,recipients'health resources(β=-0.162,P＜0.01)and health status(β=-0.411,P＜0.01)were found to have significant negative influence on U.S.DAH allocation.Conclusion:U.S.DAH to Sub-Saharan Africa is primarily driven by its own political,economic,and security interests.China should promote the global outreach of Chinese public health goods,leverage DAH to strengthen ties with recipients in alignment with national development strategies,and enhance the security of assistance environments in recipients..

Objective To investigate the feasibility of magnetic tracer technique for locating pulmonary nodules.Methods A tracer magnet and a matching puncture instrument were designed by ourselves for locating pulmonary nodules.After preliminarily verifying the feasibility of the operation in the isolated lung,four beagle dogs were used as animal models to perform puncture localization of the assumed lesions in the upper lobe of the right lung under the guidance of X-ray by using self-designed tracer magnets and puncture instruments,and the positioning effect was observed and evaluated after thorax opening.The operation time required for the tracer magnet implantation,whether there is bleeding at the puncture site,whether the tracer magnet is displaced,and the positioning time of pulmonary nodules after thorax opening were recorded.Results Two tracer magnets were successfully inserted into the upper lobe of the right lung under X-ray guidance in four beagle dogs,and the magnets were successfully attracted and fixed.The median insertion time of the tracer magnet was 5 minutes(4 to 7 minutes),and the insertion process was smooth without bleeding at the puncture site.After thorax opening,oval forceps were used to conveniently locate the location of the tracer magnet,achieving accurate positioning of pulmonary nodules with a median positioning time of 13 seconds(10 to 17 seconds),and the tracer magnet did not shift during the whole process.Conclusion The magnetic tracer technique is simple to operate and pricise for localization of pulmonary nodules.With further optimization of the operation process,this technique is expected to be applied in clinic.

Objective To investigate the reliability and validity of the Chinese version of speech,spatial and qualities of hearing scale(SSQ).Methods The SSQ was translated into Chinese using the translation and back-translation method.Self-assessment with the scale was conducted for 50 adults with normal hearing and 28 adults with hearing impairment who had bilateral hearing aids fitted.Two weeks after the initial assessment,10 individuals with bilateral hearing aids fitted were randomly selected to be re-assessed using the same scale.The Cronbach's αcoefficients of the scores of each dimension and the total score of the scale was used to evaluate the internal consis-tency of the scale,and the correlation coefficient of the results of the two assessments was used to test the test-retest reliability of the scale.The expert evaluation method was adopted to test the content validity of the scale,and the correlation coefficients of the scores of each dimension and the total score were used to test the construct validity of the scale.The score differences of each item and each dimension between adults with normal hearing and adults with bilateral hearing aids fitted were compared to test the discriminant validity.Results Valid responses were obtained from all 78 participants.① The test-retest reliability coefficients of the total scale and the three dimensions were all greater than 0.750(P＜0.01),indicating excellent test-retest reliability.The Cronbach's α coefficients of the total scale and the three dimensions were all greater than 0.700,suggesting excellent internal consistency.② All four ex-perts indicated that the content of each item in the three dimensions of the SSQ scale was in line with the measure-ment requirements,showing excellent content validity.The correlation coefficients between the scores of the three dimensions and the total scale were between 0.809 and 0.890,indicating a high degree of correlation.There were statistically significant differences in the scores of the three dimensions between the normal group and the group with bilateral hearing aids fitted(P＜0.05),and the overall discriminant validity of the scale was excellent.Conclusion The Chinese version of the SSQ has good reliability and validity,and can be used as a subjective auditory assessment in clinical practice.

Kv1.3,a voltage-gated potassium channel,is highly expressed in T lymphocytes,the nervous system,and vascular smooth muscle cells.It plays a critical role in membrane excitability and electrical signal transduction,serving as an important target for studying T-cell function and providing a promising direction for developing therapeutics against autoimmune and inflammatory diseases.Therefore,the de-velopment of specific inhibitors of Kv1.3 channel has emerged as a novel therapeutic strategy for these disorders.In this study,we isolated and purified a novel Kv1.3-inhibitory peptide toxin,LmKTx13,from the venom of the scorpion Lychas mucronatus using reversed-phase high-performance liquid chroma-tography(RP-HPLC).LmKTx13 consists of 38 amino acid residues,including six cysteines that form three disulfide bonds.Whole-cell patch-clamp recordings revealed that LmKTx13 potently inhibited Kv1.3 with an IC50 of 7.92±3.0 nmol/L.Selectivity analysis showed that 2 μmol/L LmKTx13 also in-hibited Kv1.2 and Kv1.7,but exhibited no significant effects on other potassium channel subtypes or voltage-gated sodium channels.Further investigation into the mechanism demonstrated that LmKTx13 acts as a pore-blocking inhibitor of Kv1.3.By analyzing the effects of LmKTx13 on Kv1.3 channel gating ki-netics and performing sequence alignment of the pore regions of Kv1.3 and Kv1.5,we constructed site-directed mutants and identified the pore region of Kv1.3 as the critical binding site for LmKTx13.Key residues involved in the interaction included T425,G427,and H451.In summary,we discovered a no-vel pore-blocking Kv1.3 inhibitor,LmKTx13,from L.mucronatus venom,which exhibits high affinity and selectivity for Kv1.3.These findings highlight its potential as a potential lead molecule for developing Kv1.3-targeted therapeutics.

Objective To investigate the relationship between vertical laminar fracture(VLF)in thoracolumbar burst fractures and both neurological injury and dural tear.Methods A retrospective analysis was conducted on the clinical data and multi spiral computed tomography(MSCT)coronal images of 255 patients of thoracolumbar burst fractures.The patients were divided into three groups based on the presence of VLF[Ⅰ group(complete VLF group),Ⅱ group(partial VLF group),and Ⅲ group(normal lamina group)].Statistical analysis was performed using analysis of variance and Fisher's exact test to compare radiological parameters,inci-dence of dural tear,and neurological injury among the groups.Results The Ⅰ group showed significant differences in spinal canal sagittal diameter,pedicle distance,and spinal canal area compared with the other two groups(P<0.05).However,there was no sig-nificant difference in vertebral body compression rate between the Ⅰ group and the Ⅱ group(P>0.05).The Ⅰ group had the high-est incidence of severe neurological injury[American Spinal Injury Association(ASIA)impairment scale grades A and B]and dural tear(P<0.05).Conclusion The severity of VLF is closely related to dural tear and neurological injury.MSCT coronal images can clearly display the extent of VLF,providing an important basis for clinical evaluation and treatment plan.

Objective To investigate the natural progression of pulmonary ground-glass nodule(GGN)to invasive adenocarcinoma(IAC)and the diagnostic value of follow-up CT.Methods A retrospective analysis was performed on 45 GGN in 45 patients who were followed up for more than 2 years,surgically resected and pathologically confirmed.They were divided into IAC group(n=25)and non-IAC group(n=20),and the clinical and imaging characteristics between the two groups were compared.Results Significant differences were observed in initial volume(P=0.025),initial mass(P=0.005),margin(P=0.027),and time to GGN progression(P=0.005)between the IAC group and the non-IAC group.Multivariate logistic regression analysis indicated that initial mass and time to GGN progression were independent predictors for the diagnosis of IAC.The receiver operating characteristic(ROC)curve analysis results revealed that when using a maximum Youden's index of 0.456,the optimal cutoff for time to GGN progression was 30 months,with a sensitivity of 75.0%and a specificity of 70.6%,and an area under the curve(AUC)of 0.761[95%confidence interval(CI)0.606-0.916](P=0.005).When the maximum Youden's index reached 0.615,the sensitivity,specificity and AUC of the logistic regression model in the diagnosis of IAC were 79.2%,82.4%,and 0.860(95%CI 0.743-0.977)(P=0.001),respectively.The calibration curves demonstrated an excellent consistency between predicted and observed probabilities.Conclusion The optimal observation window for GGN is 30 months,during which IAC generally progresses.Close monitoring is recommended after the initiation of lesion growth.