INTRODUCTION: We aimed to understand the awareness and attitudes of elderly Southeast Asians towards telehealth services during the coronavirus disease 2019 (COVID-19) pandemic in this study. METHODS: In this qualitative study, 78 individuals from Singapore (51.3% female, mean age 73.0 ± 7.6 years) were interviewed via telephone between 13 May 2020 and 9 June 2020 during Singapore's first COVID-19 'circuit breaker'. Participants were asked to describe their understanding of telehealth, their experience of and willingness to utilise these services, and the barriers and facilitators underlying their decision. Transcripts were analysed using thematic analysis, guided by the United Theory of Acceptance Use of Technology framework. RESULTS: Of the 78 participants, 24 (30.8%) were able to describe the range of telehealth services available and 15 (19.2%) had previously utilised these services. Conversely, 14 (17.9%) participants thought that telehealth comprised solely home medication delivery and 50 (51.3%) participants did not know about telehealth. Despite the advantages offered by telehealth services, participants preferred in-person consultations due to a perceived lack of human interaction and accuracy of diagnoses, poor digital literacy and a lack of access to telehealth-capable devices. CONCLUSION Our results showed poor overall awareness of the range of telehealth services available among elderly Asian individuals, with many harbouring erroneous views regarding their use. These data suggest that public health education campaigns are needed to improve awareness of and correct negative perceptions towards telehealth services in elderly Asians.
Humans ; COVID-19/epidemiology* ; Female ; Telemedicine ; Aged ; Male ; Singapore/epidemiology* ; Qualitative Research ; Health Knowledge, Attitudes, Practice ; SARS-CoV-2 ; Aged, 80 and over ; Middle Aged ; Pandemics ; Awareness ; Asian People ; Southeast Asian People

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

Nursing practice is an important component of the healthcare service system and plays a crucial role in achieving the strategic goal of"Healthy China Initiative".Facing the growing health needs and increasingly complex health issues,the concept of Population Medicine,which aims to maximize the overall and long-term health benefits of the population,is expected to provide new theoretical foundations for the nursing practice in China.Integrating the concept of Population Medicine into nursing practice can give full play to the professional value of nursing workers,improve nursing quality,and promote the construction of Healthy China.This review summarized the development of the concept of Population Medicine,its specific connotation and its application in the field of nursing practice,and relevant suggestions are put forward,providing references for scholars to deepen the integration and application of Population Medicine in nursing practice and promote the development of nursing in China.

Objective Under the operation background of Diagnosis-Intervention Packet(DIP),whether there is interaction between reducing medical cost and average length of stay combined with pre-hospitalization mode,and whether there is difference between different departments and diseases in interaction.Methods Based on real-world data from 71 453 patients admitted to Guizhou Provincial People's Hospital from July to December 2021,a two-way analysis of variance was employed.When the interaction effect was statistically significant,parameter estimation was used to determine the magnitude and direction of the interaction effect,followed by subgroup analyses by department and disease.Results Without adjustment,both total medical costs and average length of stay exhibited a negative interaction effect(P＜0.05).Subgroup analyses revealed that in terms of total medical costs,the effect size for the surgical system was 0.18％,lower than that for the internal medicine system(0.70％);for core diseases,it was 6.62％,lower than that for comprehensive diseases(7.71％).Regarding average length of stay,the effect size for the surgical system was 0.55％,better than that for the internal medicine system(0.22％);for core diseases,it was 8.70％,higher than that for comprehensive diseases(2.90％).Conclusion The combination of DIP payment reform and pre-admission management model demonstrates a synergistic effect,effectively reducing patients' medical costs and length of stay.This effect is influenced by disease complexity and the standardization of diagnostic and treatment processes.

Dental implantology has developed rapidly for over half a century,since pure titanium(99.7％)dental cylindrical threaded implants were exploited and osseointegration was introduced in 1960s by Prof.Br?nemark.The long term retention rates of 10 years or more are over 95％.However,the biological complications jeopardize the long term effects of dental implant treatment seriously.The prevalence of dental implant biological complications varies greatly among different reports resulting from the disparities on the defini-tions of dental implant biological complications.After analyzing and summarizing the major opinions proposed internationally in recent years,the consensus for the definition of dental implant biological complications has been reached.Generally the dental implant biologi-cal implications can be classified into early stage(before restoration)biological complications and late stage(after restoration)biological complications.The early stage biological complications include acute and chronic infections,pain,soft tissue deficiency,and osseointegration failure,etc.The late stage complications include peri-implant diseases(peri-implant mucositis and peri-implantitis),soft tissue deficiency around implant,implant loosening and dropping off,etc.The various risk factors related to different dental implant biological complications,the strategies of the prevention and treatment for the dental implant biological complications have been discussed comprehensively,and the consensus has been reached.It is aimed to advocate the dentist to pay more attention to the early prevention of the biological implant complications,to promote more researches on the implant biological complications,and to help elevate the level of dental implantology in our country.

NK cells are essential components of innate immune system and play crucial roles in combating tumors and infec-tions by directly eliminating target cells and supporting other immune cells.However,tumors and chronic infections often result in exhaustion of NK cells,which diminishes their effector functions and hampers their ability to control progression of tumors and infec-tions.NK cell exhaustion is accompanied by alterations in surface receptors,cytokines and transcription factors.A comprehensive investigation into characteristics of NK cell exhaustion not only enhances our understanding of fundamental biological properties of NK cells but also facilitates development of novel immunotherapy approaches utilizing NK cells.This article provides an overview of cur-rent understanding of NK cell exhaustion,including its characterization and relevant knowledge,and explores its potential applica-tions in immunotherapy.

Depression and anxiety are the two most common mental disorders, which have severe negative impacts on individuals and society. Early and accurate identification of these disorders is crucial for symptom control and positive prognosis. Traditional identification approaches such as scale screening and interviews rely on patients' self-reporting and the comprehensive judgment of psychiatrists. These methods inherently have limitations such as subjectivity and dependence on the availability and convenience of medical resources. Therefore, seeking objective means to assist in the identification of depression and anxiety disorders has become a research focus in recent years. Electroencephalogram (EEG), which describes changes in potential difference on the scalp surface, offers advantages such as objectivity, quantification and high temporal resolution. EEG has become one of the potential objective indicators for identifying depression and anxiety disorders.Machine learning algorithms are key technologies for extracting EEG signal features and improving identification accuracy. The combination of EEG collection and machine learning algorithms is expected to become a new method for identifying depression and anxiety disorders. In addition, portable EEG collection provides the possibility for rapid identification of mental disorders and large-scale screening activities. This article reviews the application of EEG for depression and anxiety disorders identification, providing a reference for scholars in related fields, with the aim of promoting the development of mental disorder identification towards objectivity and visualization in China.

AIM To explore the differential metabolites of different aged Citrus reticulate'Chachi'and their processed cakes.METHODS Non-targeted metabolomics technology of GC-TOF-MS was used to analyze the chemical constituents.The data was processed by principal component analysis and orthogonal partial least squares discriminant analysis,and the differential metabolites were identified.RESULTS A total of 74 differential metabolites were identified,including 16 glycosides,14 organic acids and their derivatives,11 amino acids and their derivatives,and 4 flavonoids.Comparative analysis revealed 40 and 30 differential metabolites between fresh C.reticulate'℃hachi'and 3-year or 5-year aged samples,respectively.Furthermore,27 and 34 differential metabolites were identified between the 3-year or 5-year aged samples and their corresponding processed cakes,respectively.Differential metabolites among fresh,aged C.reticulate'Chachi',and processed cakes were predominantly enriched in 6 metabolic pathways,including the biosynthesis of secondary metabolites.Specifically,differential metabolites between 3-year aged C.reticulate'Chachi'and its processed cake were significantly enriched in 4 pathways,such as ABC transporters.Differential metabolites between 5-year aged C.reticulate'Chachi'and its processed cake were mainly enriched in 5 pathways,including carbon metabolism.CONCLUSION Non-targeted metabolomics technology can elucidate the chemical compositional differences among fresh/aged and processed cakes of C.reticulate'Chachi',laying a foundation for the research into C.reticulate'Chachi'aging processing techniques and the development of processed products.

AIM To study the chemical constituents from Inula japonica Thunb.and their anti-asthmatic activity.METHODS Separation and purification were performed using silica gel and Sephadex LH-20,then the structures of obtained compounds were identified by physicochemical properties and spectral data.The effect of compounds on the release rate of β-Hex was evaluated by substrate coloration method.RESULTS Twenty-three compounds were isolated and identified as dehydrodontic acid(1),vitexin(2),alternariol(3),globuxanthone(4),1,3,6,7-tetrahydroxyxanthone(5),hydroxyhydrolapachol(6),isoscopoletin(7),elephanmollen(8),benzoylcholine(9),hoconobiflavone(10),clovandiol(11),hydroxydihydrobovolide(12),5,7-dihydroxycoumarin(13),scopoletin(14),orlichenol glucoside(15),urolignoside(16),9-angeloyloxythymol(17),6,3′,4′-trihydroxyaurone(18),flufuran(19),sweroside(20),guajadial(21),5,7,4′-trimethoxy-4-phenylcoumarin(22),dibutylphthalate(23).After intervention with compounds 9 and 16,the release rates of β-Hex were(56.64±2.37)％and(58.07±2.29)％,respectively.CONCLUSION Compounds 1-23 are isolated from Ⅰ.japonica for the first time.Compounds 9 and 16 have anti-asthmatic activity.

As a key link in data governance,data asset auditing is of great significance in improving data quality,ensuring data asset security,optimizing data asset management,and meeting compliance requirements.Based on the full lifecycle perspective of data assets in public hospitals,combined with the characteristics and functional responsibilities of internal auditing in public hospitals,a mechanism for implementing data asset auditing in public hospitals is constructed,including locking the data asset auditing mode with a supervision and operation mechanism,conducting targeted analysis of key areas of data asset auditing with a review and evaluation mechanism,promoting standardized management of hospital data assets with a feedback improvement mechanism,and providing guarantees for the high-quality and effective development of data asset auditing with a quality improvement mechanism.Aiming to achieve closed-loop management of the entire process of data asset auditing in public hospitals,using auditing as a driving force to fully unleash the value of hospital data assets and assist in the high-quality development of public hospitals.