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.

Introduction: Diabetic ketoacidosis (DKA) is a life-threatening complication associated with significant morbidity and healthcare burden. Despite advances in diabetes care, recurrent DKA remains common, often reflecting gaps in treatment adherence and patient education. Identifying predictors of recurrence is crucial for risk stratification and targeted intervention. Methodology: We conducted a retrospective observational study of all adult DKA admissions to a tertiary centre between 2001 and 2025. Electronic medical records were reviewed for demographic data, biochemical parameters, precipitating factors, and clinical outcomes. DKA was defined using standard biochemical criteria. Recurrent DKA was defined as ≥2 admissions during the study period. Factors associated with recurrent DKA admissions were analyzed. Patients under the age of 18 years and those with missing vital information were excluded. Results: A total of 667 DKA admissions, comprising 566 patients, were identified, of which 101 admissions (15.1%) were recurrent, involving 65 patients. Among recurrent DKA episodes, the most common precipitating factors were infection (64.4%) and insulin omission (62.4%). After multivariate analyses, patients with type 1 diabetes mellitus (T1DM) were more likely to develop recurrent DKA compared to those with type 2 diabetes mellitus (aOR 4.16; 95% confidence interval [CI] 2.58–6.70; p <0.001). Insulin omission was strongly associated with recurrent DKA (aOR 2.29; 95% CI 1.46–3.60; p <0.001). In contrast, baseline glycated hemoglobin and chronic kidney disease were not significantly associated with recurrence. Diabetic counseling during the first DKA admission did not reduce recurrent DKA. There were no significant differences in mortality (3.9% vs 6.2%, p = 0.524) or critical care admission rates (40.6% vs 38.7%, p = 0.718) between recurrent and first DKA episodes. Conclusion Recurrent DKA accounts for a substantial proportion of DKA admissions and is strongly associated with insulin omission and T1DM. Our findings suggest that recurrent DKA is driven predominantly by behavioral and adherencerelated factors, indicating the need for multidisciplinary interventions beyond standard inpatient counseling.
Diabetic Ketoacidosis ; Retrospective Studies

Introduction: Diabetic ketoacidosis (DKA) in pregnancy is an uncommon yet life-threatening emergency, with disproportionate risks to both mother and fetus. Pregnancy-specific physiological changes predispose patients to rapid metabolic decompensation, often with atypical presentations. Despite this, local data remain limited. We describe the clinical profile, precipitating factors, and outcomes of DKA in pregnancy in a tertiary centre, with emphasis on potentially preventable triggers. Cases: Nine pregnant patients with DKA were identified from a retrospective review of all cases admitted for DKA from 2002 to 2025. Mean age was 31.67 ± 5.20 years; all were Malay. The majority had type 2 diabetes mellitus (55.6%), followed by type 1 diabetes (33.3%) and latent autoimmune diabetes in adults (11.1%). The mean period of amenorrhea was 19.67 ± 12.62 weeks. Infection was the leading precipitant (44.4%), with additional triggers including insulin omission (22.2%), hyperemesis gravidarum, preterm labor, steroid exposure, and perioperative fasting. Most diagnoses were made in the emergency department (55.6%). Biochemical parameters reflected significant severity (mean bicarbonate 7.89 ± 2.98 mmol/L; anion gap 25.00 ± 5.81), with 88.9% classified as severe DKA. Intensive Care Unit (ICU) care was required in 77.8% of cases. The majority (77.8%) were admitted to the ICU unit, with a median time to resolution of 13.00 ± 12.00 hours (interquartile range [IQR]), and the median hospital length of stay was 7.00 ± 5.00 days (IQR). Complications during treatment included hypokalemia (33.3%), acute kidney injury (22.2%), and hypoglycemia (11.1%). Rebound DKA occurred in one-third of patients. All patients were discharged clinically stable. Outcome data demonstrated pregnancy loss in three cases and one preterm birth. Conclusion DKA in pregnancy remains a severe and resource-intensive condition. This series highlights missed opportunities in prevention, with modifiable precipitants such as infection and insulin omission commonly identified. The high severity at presentation suggests delays in recognition. Early detection, optimized metabolic care, and targeted preventive strategies are crucial to improving maternal and fetal outcomes.
Female ; Pregnancy ; Diabetic Ketoacidosis

AIM To investigate the protective effects of Shuangyi Qushi Tongluo Capsules(Shuangyi Capsules)on Dexamethasone(Dex)induced osteoporosis in mice.METHODS The C57BL/6J mice were randomly divided into the control group,the model group,the Xianling Gubao Capsules group(1.5 g/kg),and the low-dose,moderate-dose,and high-dose Shuangyi Capsules groups(0.6,1.2,and 2.4 g/kg).The mouse model of osteoporosis was induced by 8-week intraperitoneal injection of Dex sodium phosphate injection(5 mg/kg).The mice had their femur osteogenesis observed with hematoxylin and eosin(HE)staining and tartrate-resistant acid phosphatase(TRAP)staining;their serum alkaline phosphatase(ALP)and osteocalcin(BGP)activities detected by ELISA;their femoral mRNA expressions of Col-Ⅰ,OCN,and OPN detected by RT-qPCR;and their femoral protein expressions of OPG and RANKL detected by Western blot.Upon the MC3T3-E1 cells exposed to Dex and Shuangyi Capsules,their viability was evaluated by CCK-8 assay;their mineralization determined by alkaline phosphatase staining and alizarin red staining(ARS);and their intracellular ROS level detected using DCFH-DA probe.RESULTS Compared with the model group,Shuangyi Capsules groups demonstrated improved fracture of femoral trabeculae and reduced number of osteoclasts;increased serum ALP and BGP activities(P＜0.05,P＜0.01);increased femoral expressions of Col-Ⅰ mRNA and OPG protein(P＜0.05,P＜0.01);and decreased RANKL protein expression(P＜0.05).Compared with the MC3T3-E1 cells stimulated by Dex,those underwent further treatment of Shuangyi Capsules demonstrated increased cell viability and ALP activity(P＜0.05,P＜0.01);increased mineralization and calcium nodule formation;increased expressions of Col-Ⅰ,OCN,OPN mRNA and OPG protein(P＜0.05,P＜0.01);decreased RANKL protein expression(P＜0.05,P＜0.01);and reduced ROS levels.CONCLUSION Shuangyi Capsules ameliorate Dex-induced osteoporosis in mice by suppressing osteoclast overactivation,enhancing osteoblast activity,and stimulating bone formation through modulation of Col-Ⅰ,OCN,OPN mRNA and OPG/RANKL protein levels.

Objective:To explore the clinical value of plasma von Willebrand factor antigen(VWF:Ag)and VWF activity(VWF:GPIbM)based on ABO blood group in the risk assessment of deep vein thrombosis(DVT).Methods:A total of 163 patients with DVT who sought medical treatment from March 2021 to December 2022 were selected as the case group,and 135 healthy volunteers during the same period were selected as the control group.The differences of ABO blood groups,plasma VWF:Ag and VWF:GPIbM levels between the two groups were compared.Receiver operating characteristic(ROC)curves were used to evaluate the clinical value of VWF testing in predicting DVT events.Logistic regression analysis was applied to identify risk factors for DVT.Results:The levels of plasma VWF:Ag and VWF:GPIbM in the DVT group were significantly higher than those in the control group both overall and across ABO blood type subgroups(P＜0.01).Within the DVT group,the levels of plasma VWF:Ag and VWF:GPIbM in patients with non-O blood type were significantly higher than those with blood type O[VWF:Ag:219.74％±63.64％vs 162.21％±56.03％,P＜0.01;VWF:GPIbM:228.10％(185.15％,249.10％)vs 148.25％(116.48％,225.48％),P＜0.01].The area under the ROC curve(AUC)of VWF:Ag for predicting DVT events was 0.855,with a cut-off value of 142.4％,sensitivity of 82.2％and specificity of 72.6％;the AUC of VWF:GPIbM was 0.861,with a cut-off value of 141.2％,sensitivity of 84.7％,and specificity of 71.1％.Univariate analysis showed that both VWF:Ag and VWF:GPIbM were influencing factors for DVT events(P＜0.05).Multivariate logistic regression analysis indicated that VWF:Ag＞142.4％(OR=13.961,95％CI:7.654-25.464,P＜0.01)and VWF:GPIbM＞141.2％(OR=17.615,95％CI:9.155-33.892,P＜0.01)were independent risk factors for DVT events.Conclusion:Levels of VWF:Ag and VWF:GPIbM are significantly elevated in non-O blood type DVT patients.VWF:Ag＞142.4％and VWF:GPIbM＞141.2％are independent risk factors for DVT events.VWF testing based on ABO blood group aids in the precision prevention and control of DVT.

AIM To investigate the protective effects of Shuangyi Qushi Tongluo Capsules(Shuangyi Capsules)on Dexamethasone(Dex)induced osteoporosis in mice.METHODS The C57BL/6J mice were randomly divided into the control group,the model group,the Xianling Gubao Capsules group(1.5 g/kg),and the low-dose,moderate-dose,and high-dose Shuangyi Capsules groups(0.6,1.2,and 2.4 g/kg).The mouse model of osteoporosis was induced by 8-week intraperitoneal injection of Dex sodium phosphate injection(5 mg/kg).The mice had their femur osteogenesis observed with hematoxylin and eosin(HE)staining and tartrate-resistant acid phosphatase(TRAP)staining;their serum alkaline phosphatase(ALP)and osteocalcin(BGP)activities detected by ELISA;their femoral mRNA expressions of Col-Ⅰ,OCN,and OPN detected by RT-qPCR;and their femoral protein expressions of OPG and RANKL detected by Western blot.Upon the MC3T3-E1 cells exposed to Dex and Shuangyi Capsules,their viability was evaluated by CCK-8 assay;their mineralization determined by alkaline phosphatase staining and alizarin red staining(ARS);and their intracellular ROS level detected using DCFH-DA probe.RESULTS Compared with the model group,Shuangyi Capsules groups demonstrated improved fracture of femoral trabeculae and reduced number of osteoclasts;increased serum ALP and BGP activities(P＜0.05,P＜0.01);increased femoral expressions of Col-Ⅰ mRNA and OPG protein(P＜0.05,P＜0.01);and decreased RANKL protein expression(P＜0.05).Compared with the MC3T3-E1 cells stimulated by Dex,those underwent further treatment of Shuangyi Capsules demonstrated increased cell viability and ALP activity(P＜0.05,P＜0.01);increased mineralization and calcium nodule formation;increased expressions of Col-Ⅰ,OCN,OPN mRNA and OPG protein(P＜0.05,P＜0.01);decreased RANKL protein expression(P＜0.05,P＜0.01);and reduced ROS levels.CONCLUSION Shuangyi Capsules ameliorate Dex-induced osteoporosis in mice by suppressing osteoclast overactivation,enhancing osteoblast activity,and stimulating bone formation through modulation of Col-Ⅰ,OCN,OPN mRNA and OPG/RANKL protein levels.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.

Objective To investigate the antimicrobial resistance of clinical isolates from elderly patients(≥65 years)in major medical institutions across China.Methods Bacterial strains were isolated from elderly patients in 52 hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program during the period from 2015 to 2021.Antimicrobial susceptibility test was carried out by disk diffusion method and automated systems according to the same CHINET protocol.The data were interpreted in accordance with the breakpoints recommended by the Clinical and Laboratory Standards Institute(CLSI)in 2021.Results A total of 514 715 nonduplicate clinical isolates were collected from elderly patients in 52 hospitals from January 1,2015 to December 31,2021.The number of isolates accounted for 34.3％of the total number of clinical isolates from all patients.Overall,21.8％of the 514 715 strains were gram-positive bacteria,and 78.2％were gram-negative bacteria.Majority(90.9％)of the strains were isolated from inpatients.About 42.9％of the strains were isolated from respiratory specimens,and 22.9％were isolated from urine.More than half(60.7％)of the strains were isolated from male patients,and 39.3％isolated from females.About 51.1％of the strains were isolated from patients aged 65-＜75 years.The prevalence of methicillin-resistant strains(MRSA)was 38.8％in 32 190 strains of Staphylococcus aureus.No vancomycin-or linezolid-resistant strains were found.The resistance rate of E.faecalis to most antibiotics was significantly lower than that of Enterococcus faecium,but a few vancomycin-resistant strains(0.2％,1.5％)and linezolid-resistant strains(3.4％,0.3％)were found in E.faecalis and E.faecium.The prevalence of penicillin-susceptible S.pneumoniae(PSSP),penicillin-intermediate S.pneumoniae(PISP),and penicillin-resistant S.pneumoniae(PRSP)was 94.3％,4.0％,and 1.7％in nonmeningitis S.pneumoniae isolates.The resistance rates of Klebsiella spp.(Klebsiella pneumoniae 93.2％)to imipenem and meropenem were 20.9％and 22.3％,respectively.Other Enterobacterales species were highly sensitive to carbapenem antibiotics.Only 1.7％-7.8％of other Enterobacterales strains were resistant to carbapenems.The resistance rates of Acinetobacter spp.(Acinetobacter baumannii 90.6％)to imipenem and meropenem were 68.4％and 70.6％respectively,while 28.5％and 24.3％of P.aeruginosa strains were resistant to imipenem and meropenem,respectively.Conclusions The number of clinical isolates from elderly patients is increasing year by year,especially in the 65-＜75 age group.Respiratory tract isolates were more prevalent in male elderly patients,and urinary tract isolates were more prevalent in female elderly patients.Klebsiella isolates were increasingly resistant to multiple antimicrobial agents,especially carbapenems.Antimicrobial resistance surveillance is helpful for accurate empirical antimicrobial therapy in elderly patients.

Objective To investigate the ameliorative effects and mechanisms of six types of tea(green tea,cyan tea,red tea,white tea,black tea and yellow tea)on metabolic disorders in obesity mice induced by high-fat diet(HFD).Methods Four-week-old male C57BL/6J mice were randomly divided into 8 groups with 7 mice per group.An HFD-induced obese mouse model was established,and the mice in control group maintained on standard diet followed by intragastric administration of different teas for 5 weeks.The body weight,liver weight ratio,fasting blood glucose,and lipid profile of the mice were measured to assess glucose and lipid metabolism.Serum inflammatory factors including IL-6,tumor necrosis factor-alpha(TNF-α)and oxidative stress markers[malondialdehyde(MDA)and superoxide dismutase(SOD)were measured.Additionally,liver histopathology and the expression of key glycolipid metabolism-related genes,adenosine monophosphate-activated protein kinase(AMPK)and carnitine palmitoyltransferase 1(CPT-1),were analyzed to explore underlying mechanisms.Results Cyan tea significantly suppressed weight gain,demonstrating superior weight control.White tea markedly reduced fasting blood glucose levels and decreased the area under the curve of oral glucose tolerance test(OGTT)and insulin tolerance test(ITT),indicating synergistic improvements in glucose metabolism and insulin sensitivity.Yellow tea exhibited exceptional anti-inflammatory and antioxidant effects,reducing hepatic IL-6 and MDA while enhancing SOD activity.Green tea activated the lipid oxidation pathway by upregulating AMPK/CPT-1 expression.All kinds of tea significantly attenuated hepatic lipid droplet accumulation.Conclusion All six types of tea alleviated metabolic disorders by reducing hepatic fat content in obesity mice.However,different types of tea exert their unique effects on improving metabolic disorders through differential mechanisms such as glucose metabolism regulation,lipid oxidation,and anti-inflammatory and antioxidant actions.

Objective To investigate the distribution and antimicrobial resistance profiles of common pathogens isolated from cerebrospinal fluid(CSF)in CHINET program from 2015 to 2021.Methods The bacterial strains isolated from CSF were identified in accordance with clinical microbiology practice standards.Antimicrobial susceptibility test was conducted using Kirby-Bauer method and automated systems per the unified CHINET protocol.Results A total of 14 014 bacterial strains were isolated from CSF samples from 2015 to 2021,including the strains isolated from inpatients(95.3％)and from outpatient and emergency care patients(4.7％).Overall,19.6％of the isolates were from children and 80.4％were from adults.Gram-positive and Gram-negative bacteria accounted for 68.0％and 32.0％,respectively.Coagulase negative Staphylococcus accounted for 73.0％of the total Gram-positive bacterial isolates.The prevalence of MRSA was 38.2％in children and 45.6％in adults.The prevalence of MRCNS was 67.6％in adults and 69.5％in children.A small number of vancomycin-resistant Enterococcus faecium(2.2％)and linezolid-resistant Enterococcus faecalis(3.1％)were isolated from adult patients.The resistance rates of Escherichia coli and Klebsiella pneumoniae to ceftriaxone were 52.2％and 76.4％in children,70.5％and 63.5％in adults.The prevalence of carbapenem-resistant E.coli and K.pneumoniae(CRKP)was 1.3％and 47.7％in children,6.4％and 47.9％in adults.The prevalence of carbapenem-resistant Acinetobacter baumannii(CRAB)and Pseudomonas aeruginosa(CRPA)was 74.0％and 37.1％in children,81.7％and 39.9％in adults.Conclusions The data derived from antimicrobial resistance surveillance are crucial for clinicians to make evidence-based decisions regarding antibiotic therapy.Attention should be paid to the Gram-negative bacteria,especially CRKP and CRAB in central nervous system(CNS)infections.Ongoing antimicrobial resistance surveillance is helpful for optimizing antibiotic use in CNS infections.