A unified consensus statement on medication-related osteonecrosis of the jaw (MRONJ) has not yet been established among the Asian member countries or regions of the Asian Federation of Osteoporosis Societies (AFOS). This study aimed to develop a consensus on MRONJ in patients with osteoporosis across these countries and regions. In this study, the term “Asia-Pacific” refers specifically to the Asian member countries and regions of AFOS. A structured survey consisting of nine MRONJ-related questions was distributed across 10 countries and regions to assess the level of agreement and summarize regional perspectives. In addition, a manual literature review and voting were conducted to evaluate the current evidence on MRONJ. The key aspects of MRONJ, including definition, staging, diagnosis, pathogenesis, risk factors, management, and prevention, were generally consistent among the AFOS countries and regions. The annual incidence and incidence rate of MRONJ associated with low-dose antiresorptive therapy in patients with osteoporosis ranged from 0.025% to 0.136% and 21 to 283 cases per 100,000 person-years, respectively. However, evidence regarding the benefits of drug discontinuation before dental surgery, such as tooth extraction, remains insufficient. Large-scale, multinational studies across AFOS countries and regions are warranted to determine the incidence of MRONJ better and evaluate the impact of antiresorptive drug discontinuation before dental procedures. These findings may contribute to the devel opment of effective evidence-based strategies for preventing MRONJ in patients with osteoporosis.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Objective To explore the mediating role of activities of daily living (ADL) in pain and depressive symptoms in the elderly in China. Methods Utilizing the data from 2020 China Health and Retirement Longitudinal Study, 4403 Chinese elderly individuals aged ≥ 60 years old were selected as the research subjects. Depression Scale (CES-D 10) of the Center for Epidemiological Survey and ADL scale were used in the study. The PROCESS4.1 macro was used to test the mediating effect of daily living activities between pain and depressive symptoms, and the Bootstrap method was applied for verification of the mediating variables. Results A total of 2368 cases of depressive symptoms were detected in the elderly in China, with a detection rate of 53.78%. Pain was positively correlated with depressive symptoms (r=0.27, P<0.01), and activities of daily living were negatively correlated with pain and depressive symptoms (r=-0.27, -0.337, P<0.01). The results showed that the total effect value of pain on depressive symptoms was 0.33, the direct effect value was 0.24, and the mediating effect value of daily living activities was 0.09, accounting for 27.27%. Conclusion Pain and activities of daily living are important factors influencing depressive symptoms in the elderly, and activities of daily living play a partial mediating role in the relationship between pain and depressive symptoms in the elderly.

Objective To investigate the status of management of iodinated contrast media(ICM)extravasation in Henan Province,as well as nurses' knowledge and influencing factors,in order to provide a basis for optimizing management strategies.Methods A self-designed questionnaire was applied,employing convenience sampling,to survey nursing administrators and nurses in the radiology departments of 55 tertiary hospitals across 16 regions of Henan Province,from December 2024 to January 2025.Multiple linear regression analysis was conducted to explore the factors influencing nurses' knowledge.Results A total of 55 nursing administrators and 64 nurses participated,with a valid questionnaire response rate of 100％.The survey results reveal that only 5.45％of radiology depart-ments utilized high-pressure central venous catheters,and 32.73％employed vascular visualization techniques.When setting the high-pressure injection speed for ICM,only 54.55％of radiology departments required an assessment of the type and model of intravenous access.Additionally,only 9.09％of radiology departments mandated an observa-tion for 2 to 4 hours following ICM extravasation.Furthermore,only 50.91％of radiology departments had estab-lished an information system for ICM use.The nurses' knowledge score regarding the prevention and management of ICM extravasation was(90.00±17.59),influenced by years of experience in radiology and professional titles(P＜0.05).Conclusion The prevention and management measures for ICM in radiology departments in Henan Province need further improvement.Nursing administrators should optimize management strategies,improve relevant training systems,and continuously enhance nurses' knowledge and practical abilities.

Objective To summarize the magnetic resonance imaging(MRI)features of spinal adnexal tuberculosis in order to improve its early diagnosis.Methods Totally 21 spinal adnexal tuberculosis patients confirmed at some hospital from January 2019 to October 2023 had their clinical data and MRI images analyzed retrospectively to determine the basic clinical characteristics and MRI features.Results Of the 21 patients,8 ones had sudden lower extremity weakness and pyramidal tract signs,and the remaining 13 ones had no significant symptoms of neurologic deficit.The lesion involvement ranged from C4 to L5 vertebrae,with the involvement of lumbar segments in 13 cases,thoracic segments in 6 cases and cervical segments in 2 cases.There were 15 cases that had tuberculosis involving in only a single spinal adnexa and peripheral soft tissue,4 cases in 2 vertebrae and 2 cases in 3 vertebrae.There were 9 cases involving in pedicles,8 cases in vertebral plates and some cases involving in sphenoid process,transverse process or facet joints.The MRI features of spinal adnexal tuberculosis included the tuberculosis-infected bone showing slightly low signals on T1WI while slightly high signals on T2WI,edge enhancement by enhanced scan and edema and abscess of paravertebral soft tissue and intra-and extradural tuberculous abscess displayed clearly by the fat suppression and diffusion weighted imaging sequences of T2WI.Conclusion MRI effectively detects the abnormal signs of bone and soft tissue of spinal adnexal tuberculosis.The MRI findings of spinal adnexal tuberculosis are of characteristics,and MRI can be used as the first choice for imaging examination and differential diagnosis to realize early detection of spinal adnexal tuberculosis.[Chinese Medical Equipment Journal,2025,46(1):55-59]

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.

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.

Objective To explore the reproductive health literacy of young female sailors,investigate the influence of long voyage on the health,and propose strategies on health education.Methods A total of 49 young female sailors were enrolled.Their healthy status was evaluated by annual medical records.The questionnaire survey was also conducted to evaluate general status related to reproductive health,knowledge pertaining to reproductive health,and health status after long voyage.Results Some female sailors had symptoms of thyroid diseases,such as hypothyroidism(32.65%),benign thyroid nodules(59.18%),and suspected papillary carcinoma(in one sailor,2.04%).Ultrasonography revealed breast nodules in 5 subjects(10.00%),mammary gland hyperplasia in 46 subjects(93.88%)and reproductive benign diseases in 6 subjects(12.24%).The physical and mental states significantly changed in the late stage of long voyage.The changes in work and living environment were the main factors affecting the emotional and psychological status in the long voyage.The discomfort in menstrual cycle piled up with the above-mentioned changes during a long voyage,and the menstruation significantly affected the duty of 36.73%of female sailors during a long voyage.Female sailors had little knowledge about the prevention and examination of breast cancer and thyroid cancer.Conclusion The living and work environment during a long voyage may affect the health of the thyroid,mammary gland and reproductive system of young female sailors.Active health education via online and offline ways is helpful to improve the health literacy and self-care of female sailors,subsequently enhancing the combat effectiveness.

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires