1.Research and Outlook on The Application of Radar-based Non-contact Health Monitoring Technology
Jia-Bin ZHONG ; Qing ZHANG ; Shuai-Wei QIAN
Progress in Biochemistry and Biophysics 2026;53(4):982-999
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.
2.Recurrent Diabetic Ketoacidosis: Predictors and Clinical Outcomes in a 24-Year Retrospective Cohort
Liang Wei Wong ; Lisa Mohamed Nor ; Raja Nurazni binti Raja Azwan ; Adilah Zulaikha binti Abd Latib ; Hidayatil Alimi bin Keya Nordin ; Qin Zhi Lee ; Kean Heng Lim ; Jia Ling Low ; Mohd Fyzal bin Bahrudin ; Syaza binti Izhar Hisham ; Jia Whey Jacelyn Ong ; Chin Voon Tong
Journal of the ASEAN Federation of Endocrine Societies 2026;41(S1):33-34
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
3.Diabetic Ketoacidosis in Pregnancy: Clinical Triggers, Outcomes, and Missed Opportunities—A Case Series
Jia Whey Jacelyn Ong ; Chin Voon Tong ; Raja Nurazni binti Raja Azwan ; Adilah Zulaikha binti Abd Latib ; Hidayatil Alimi bin Keya Nordin ; Qin Zhi Lee ; Kean Heng Lim ; Jia Ling Low ; Mohd Fyzal bin Bahrudin ; Syaza binti Izhar Hisham ; Liang Wei Wong ; Lisa Mohamed Nor ; Nurain Mohd Noorr
Journal of the ASEAN Federation of Endocrine Societies 2026;41(S1):48-49
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
4.Associations of Exposure to Typical Environmental Organic Pollutants with Cardiopulmonary Health and the Mediating Role of Oxidative Stress: A Randomized Crossover Study.
Ning GAO ; Bin WANG ; Ran ZHAO ; Han ZHANG ; Xiao Qian JIA ; Tian Xiang WU ; Meng Yuan REN ; Lu ZHAO ; Jia Zhang SHI ; Jing HUANG ; Shao Wei WU ; Guo Feng SHEN ; Bo PAN ; Ming Liang FANG
Biomedical and Environmental Sciences 2025;38(11):1388-1403
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
5.Sandstorm-driven Particulate Matter Exposure and Elevated COPD Hospitalization Risk in Arid Regions of China: A Spatiotemporal Epidemiological Analysis.
Hao ZHAO ; Ce LIU ; Er Kai ZHOU ; Bao Feng ZHOU ; Sheng LI ; Li HE ; Zhao Ru YANG ; Jia Bei JIAN ; Huan CHEN ; Huan Huan WEI ; Rong Rong CAO ; Bin LUO
Biomedical and Environmental Sciences 2025;38(11):1404-1416
OBJECTIVE:
Chronic obstructive pulmonary disease (COPD) is a major health concern in northwest China; however, the impact of particulate matter (PM) exposure during sand-dust storms (SDS) remains poorly understood. Therefore, this study aimed to investigate the association between PM exposure on SDS days and COPD hospitalization risk in arid regions.
METHODS:
Data on daily COPD hospitalizations were collected from 323 hospitals from 2018 to 2022, along with the corresponding air pollutant and meteorological data for each city in Gansu Province. Employing a space-time-stratified case-crossover design and conditional Poisson regression, we analyzed 265,379 COPD hospitalizations.
RESULTS:
PM exposure during SDS days significantly increased COPD hospitalization risk [relative risk ( RR) for PM 2.5, lag 3:1.028, 95% confidence interval ( CI): 1.021-1.034], particularly among men and the elderly, and during the cold season. The burden of PM exposure on COPD hospitalization was substantially high in Northwest China, especially in the arid and semi-arid regions.
CONCLUSION
Our findings revealed a positive correlation between PM exposure during SDS episodes and elevated hospitalization rates for COPD in arid and semi-arid zones in China. This highlights the urgency of developing region-specific public health strategies to address adverse respiratory outcomes associated with SDS-related air quality deterioration.
Humans
;
China/epidemiology*
;
Pulmonary Disease, Chronic Obstructive/chemically induced*
;
Particulate Matter/analysis*
;
Hospitalization/statistics & numerical data*
;
Male
;
Female
;
Middle Aged
;
Aged
;
Air Pollutants/analysis*
;
Environmental Exposure/adverse effects*
;
Spatio-Temporal Analysis
;
Adult
;
Sand
;
Air Pollution
6.Changing antimicrobial resistance profiles of Burkholderia cepacia in hospitals across China:results from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Chunyue GE ; Yunjian HU ; Xiaoman AI ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Hui LI ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(5):557-562
Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1%(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5%,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3%(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1%)were isolated from sputum and respiratory secretions,followed by urine(10.7%)and blood samples(8.1%).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1%.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4%in the patients<18 years old to 20.6%in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.
7.Changing prevalence and antibiotic resistance profiles of carbapenem-resistant Enterobacterales in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Wenxiang JI ; Tong JIANG ; Jilu SHEN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yuanhong XU ; Ying HUANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yingchun XU ; Xiaojiang ZHANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Yunsong YU ; Jie LIN ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Hong ZHANG ; Chun WANG ; Wenhui HUANG ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE
Chinese Journal of Infection and Chemotherapy 2025;25(4):445-454
Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43%(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38%,9.73%,and 8.47%,respectively.The prevalence of CRE strains in Escherichia coli was 1.99%.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)%,followed by blood(20.88±3.40)%and urine(18.40±3.45)%.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)%.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.
8.Changing distribution and antibiotic resistance profiles of the respiratory bacterial isolates in hospitals across China:data from CHINET Antimicrobial Resistance Surveillance Program,2015-2021
Ying FU ; Yunsong YU ; Jie LIN ; Yang YANG ; Fupin HU ; Demei ZHU ; Yingchun XU ; Xiaojiang ZHANG ; Fengbo ZHANG ; Ping JI ; Yi XIE ; Mei KANG ; Chuanqing WANG ; Pan FU ; Yuanhong XU ; Ying HUANG ; Ziyong SUN ; Zhongju CHEN ; Yuxing NI ; Jingyong SUN ; Yunzhuo CHU ; Sufei TIAN ; Zhidong HU ; Jin LI ; Bin SHAN ; Yan DU ; Sufang GUO ; Lianhua WEI ; Fengmei ZOU ; Hong ZHANG ; Chun WANG ; Yunjian HU ; Xiaoman AI ; Chao ZHUO ; Danhong SU ; Dawen GUO ; Jinying ZHAO ; Hua YU ; Xiangning HUANG ; Wen'en LIU ; Yanming LI ; Yan JIN ; Chunhong SHAO ; Xuesong XU ; Chao YAN ; Shanmei WANG ; Yafei CHU ; Lixia ZHANG ; Juan MA ; Shuping ZHOU ; Yan ZHOU ; Lei ZHU ; Jinhua MENG ; Fang DONG ; Zhiyong LÜ ; Fangfang HU ; Han SHEN ; Wanqing ZHOU ; Wei JIA ; Gang LI ; Jinsong WU ; Yuemei LU ; Jihong LI ; Jinju DUAN ; Jianbang KANG ; Xiaobo MA ; Yanping ZHENG ; Ruyi GUO ; Yan ZHU ; Yunsheng CHEN ; Qing MENG ; Shifu WANG ; Xuefei HU ; Jilu SHEN ; Ruizhong WANG ; Hua FANG ; Bixia YU ; Yong ZHAO ; Ping GONG ; Kaizhen WENG ; Yirong ZHANG ; Jiangshan LIU ; Longfeng LIAO ; Hongqin GU ; Lin JIANG ; Wen HE ; Shunhong XUE ; Jiao FENG ; Chunlei YUE ; Wenhui HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(4):431-444
Objective To characterize the changing species distribution and antibiotic resistance profiles of respiratory isolates in hospitals participating in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Methods Commercial automated antimicrobial susceptibility testing systems and disk diffusion method were used to test the susceptibility of respiratory bacterial isolates to antimicrobial agents following the standardized technical protocol established by the CHINET program.Results A total of 589 746 respiratory isolates were collected from 2015 to 2021.Overall,82.6%of the isolates were Gram-negative bacteria and 17.4%were Gram-positive bacteria.The bacterial isolates from outpatients and inpatients accounted for(6.0±0.9)%and(94.0±0.1)%,respectively.The top microorganisms were Klebsiella spp.,Acinetobacter spp.,Pseudomonas aeruginosa,Staphylococcus aureus,Haemophilus spp.,Stenotrophomonas maltophilia,Escherichia coli,and Streptococcus pneumoniae.Each microorganism was isolated from significantly more males than from females(P<0.05).The overall prevalence of methicillin-resistant S.aureus(MRSA)was 39.9%.The prevalence of penicillin-resistant S.pneumoniae was 1.4%.The prevalence of extended-spectrum β-lactamase(ESBL)-producing E.coli and K.pneumoniae was 67.8%and 41.3%,respectively.The overall prevalence of carbapenem-resistant E.coli,K.pneumoniae,Enterobacter cloacae,Pseudomonas aeruginosa,and Acinetobacter baumannii was 3.7%,20.8%,9.4%,29.8%,and 73.3%,respectively.The prevalence of β-lactamase was 96.1%in Moraxella catarrhalis and 60.0%in Haemophilus influenzae.The H.influenzae isolates from children(<18 years)showed significantly higher resistance rates to β-lactam antibiotics than the isolates from adults(P<0.05).Conclusions Gram-negative bacteria are still predominant in respiratory isolates associated with serious antibiotic resistance.Antimicrobial resistance surveillance should be strengthened in clinical practice to support accurate etiological diagnosis and appropriate antimicrobial therapy based on antimicrobial susceptibility testing results.
9.Protective effects of Shuangyi Qushi Tongluo Capsules on dexamethasone-induced osteoporosis in mice
Yi LI ; Jian-bin HE ; Jia-xiu XIE ; Quan-mou LUO ; Dong-mei LI ; Jun-hui HE ; Dong-mei WEI ; Chao WEI ; Hong-cong QIU ; Gui-ning WEI ; Bo WANG
Chinese Traditional Patent Medicine 2025;47(6):1834-1842
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.
10.Application of VWF Antigen and Activity Testing Based on ABO Blood Group in Risk Assessment of Deep Vein Thrombosis
Bin YAN ; Tian-Xi HU ; Sha LI ; Jia-Wei LI ; Wei-Peng DU ; Hui-Xin ZOU ; Ya WANG ; Tao TAO
Journal of Experimental Hematology 2025;33(6):1688-1693
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.


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