Synthesis of Reviews on Auscultation, Approaches, and Methods for Engineering Structures

Topometric auscultation is used to monitor the durability of structures, measure deformations linked to the structure of a structure or to the movement of the ground over a part of the globe, set up warning systems, etc. It first appeared as a visual method and rapidly evolved through the various techniques used. Some of these techniques using topography are used in several fields (civil engineering, geodesy, topography, mechanics, nuclear engineering, hydraulics, physics, etc.). These topometric techniques have undergone major changes as a result of technological advances, growing needs in the monitoring of movements or deformations, increased requirements and new challenges. The methodology adopted depends on the measuring instrument used, the parameters to be estimated and access to the area to be measured. There are two types of methods: destructive and non-destructive. In addition to the visual method, they can also be classified as mechanical, physico-chemical, dynamometric, electrophysical and geometric. The estimated parameter varies according to the methodology adopted. It can be defined by coordinates, distances, potential, electrical resistance, etc.

Efficacy evaluation of standardized Rheum rhaponticum root extract(ERr 731®)on symptoms of menopause:A systematic review and meta-analysis study

Menopause is characterized by various physical,mental and emotional symptoms.ERr 731®is a standardized extract from Rheum rhaponticum root and has been clinically studied for its role in reducing menopausal symptoms.The current systematic review and meta-analysis aimed to evaluate the efficacy of ERr 731®supplementation in alleviating the severity of menopausal symptoms.In this review,we searched across three online databases up to March 2023,evaluated the quality of the included studies by the Physiotherapy Evidence Database scale,and assessed the risk of bias by the Cochrane Risk of Bias tool.We then performed a metaanalysis using RevMan software to estimate the pooled mean difference(MD).The study protocol was registered in the Prospective Register of Systematic Reviews(CRD42023416808).After screening and evaluation,we included four high-quality studies(a total of 390 participants;the ERr 731®group:193 participants;the control group:197 participants)in the meta-analysis.The results showed that ERr 731®supplementation significantly reduced the Menopause Rating Scale score(MD:–15.12;P<0.001),compared with control therapy.Sensitivity analysis revealed no effect of individual studies on the overall pooled estimate or overall observed heterogeneity.The current review provides evidence that ERr 731®supplementation is effective in reducing menopause symptoms.Potential bias and high heterogeneity in the results warrant further clinical studies.

Outcomes of long-acting injectable antipsychotics use in pregnancy:A literature review

BACKGROUND Women with a history of serious psychotic disorders are at increased risk of disease relapse during pregnancy.Long-acting injectable(LAI)antipsychotics have been widely used to improve adherence and prevent relapse in patients with various severe psychotic disorders,but there is a lack of high-quality data from previous research on the safety of LAI antipsychotics during pregnancy.AIM To summarize relevant data on maternal,pregnancy,neonatal,and developmental outcomes from published cases of LAI antipsychotic use in pregnancy.METHODS A literature search was performed through November 11,2023,using three online databases:PubMed/MEDLINE,Scopus,and Web of Science.Case reports or case series that reported information about the outcomes of pregnancy in women who used LAI antipsychotics at any point in pregnancy,with available full texts,were included.Descriptive statistics,narrative summation,and tabulation of the extracted data were performed.RESULTS A total of 19 publications satisfied the inclusion criteria:3 case series,15 case reports,and 1 conference abstract.They reported the outcomes of LAI antipsychotic use in 74 women and 77 pregnancies.The use of secondgeneration LAI antipsychotics was reported in the majority(n=47;61.0%)of pregnancies.First-generation LAI antipsychotics were administered during 30 pregnancies(39.0%).Most of the women(approximately 64%)had either satisfactory control of symptoms or no information about relapse,while approximately 12%of them had developed gestational diabetes mellitus.A minority of cases reported adverse outcomes such as stillbirth,spontaneous abortion,preterm birth,low birth weight,congenital anomalies,and neurological manifestations in newborns.However,there were no reports of negative long-term developmental outcomes.CONCLUSION Currently available data seem reassuring,but further well-designed studies are required to properly evaluate the risks and benefits of LAI antipsychotic use during pregnancy.

Chinese herbal medicine combined with Western medicine for Mycoplasma pneumoniae pneumonia in children:An overview of systematic reviews

Objective:To summarize the characteristics and evaluate the quality of the methodology and evidence within systematic reviews(SRs)of Chinese herbal medicine(CHM)for Mycoplasma pneumoniae pneumonia(MPP)inchildren.Methods:SRs of randomized controlled trials were searched using PubMed,the Cochrane Library,Embase,the Chinese National Knowledge Infrastructure Databases(CNKI),the Chinese Scientific Journals Database(VIP),Wanfang,and the SinoMed Database.SRs on the use of CHM alone or in combination with Western medications for MPP in children were included.The study compared the effects of Western medicine alone with those of CHM.The evidence quality using the A Measurement Tool to Assess Systematic Reviews(AMSTAR)2,the Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)2020,and the Grading of Recommendations,Assessment,Development,and Evaluation(GRADE)criteria.The primary indicators were the total effective rate,fever subsidence time,and cough disappearance time.The secondary outcomes were pulmonary rale disappearance time,average hospitalization time,lung X-ray infiltrate disappearance time,immunological indices,and inflammatory cytokine levels.Results:Twelve relevant SRs were included;75%(9/12)were assessed as very low quality,and 25%(3/12)Were rated as low quality using the AMSTAR 2 criteria.According to the PRISMA 2020 checklist,the average SR score was 20.3 out of a 27 point maximum.In all SRs,CHM demonstrated improvement in symptoms and signs among children with MPP.The evidence quality using the GRADE criteria ranged from"very low"(>50%)to"moderate"(<5%).The most common downgrading factor was imprecision,followed by publication bias and inconsistency.Conclusion:This overview highlights the limited quality of the methodology and evidence of the included SRs.Although the included studies showed the beneficial effects of CHM on MPP in children,it was difficult to draw firm conclusions owing to methodological flaws.

The Review of Land Use/Land Cover Mapping AI Methodology and Application in the Era of Remote Sensing Big Data

With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.

Gut microbiome in alcohol use disorder:Implications for health outcomes and therapeutic strategies-a literature review

Alcohol use disorder(AUD)represents a major public health issue which affects millions of people globally and consist a chronic relapsing condition associated with substantial morbidity and mortality.The gut microbiome plays a crucial role in maintaining overall health and has emerged as a significant contributor to the pathophysiology of various psychiatric disorders.Recent evidence suggests that the gut microbiome is intimately linked to the development and progression of AUD,with alcohol consumption directly impacting its composition and function.This review article aims to explore the intricate relationship between the gut microbiome and AUD,focusing on the implications for mental health outcomes and potential therapeutic strategies.We discuss the bidirectional communication between the gut microbiome and the brain,highlighting the role of microbiotaderived metabolites in neuroinflammation,neurotransmission,and mood regulation.Furthermore,we examine the influence of AUD-related factors,such as alcohol-induced gut dysbiosis and increased intestinal permeability,on mental health outcomes.Finally,we explore emerging therapeutic avenues targeting the gut microbiome in the management of AUD,including prebiotics,probiotics,and fecal microbiota transplantation.Understanding the complex interplay between the gut microbiome and AUD holds promise for developing novel interventions that could improve mental health outcomes in individuals with AUD.

Blastocystis hominis as a cause of chronic diarrhea in low-resource settings:A systematic review

BACKGROUND Blastocystis hominis(B.hominis),an anaerobic unicellular protist parasite,is known for its diverse clinical manifestations upon infecting the human gastrointestinal tract.Although globally distributed,it is particularly prevalent in developing nations.Examining the symptoms and treatment outcomes of B.hominis infection in low-resource settings holds immense significance,providing healthcare practi-tioners with valuable insights to enhance patient care.AIM To synthesize existing evidence on the symptomatology and treatment outcomes of B.hominis infection in low-resource settings.METHODS Following the Preferred Reporting Items for Systematic Review and Meta-Analysis guidelines,a systematic review was conducted.The search spanned electronic databases including PubMed,Scopus,and Google Scholar.After a comprehensive screening process,a thorough examination of the papers,adhering to inclusion and exclusion criteria,and data extraction from eligible studies was conducted.The findings underwent summarization through simple descriptive analysis.RESULTS The search yielded 1200 papers,with 17 meeting inclusion criteria.Chronic diarrhea due to B.hominis infection was reported in only two studies,while abdominal pain,diarrhea,flatulence,constipation,and nausea/vomiting emerged as the most commonly documented symptoms.Recovery rates after one week of treatment ranged from 71.8%to 100%,and after two weeks,from 60%to 100%.CONCLUSION In low-resource settings,chronic diarrhea resulting from B.hominis infection is infrequent.Common symptoms include abdominal pain,diarrhea,flatulence,constipation,and nausea/vomiting.Post-treatment,clinical outcomes are notably favorable,supporting the recommendation for treatment.Metronidazole is advocated as the first-line agent,with consideration for switching to a second-line option in cases of treatment failure or poor response.

Expert Review on Usefulness of an Integrated Checklist-based Mobile Usability Evaluation Framework

Previous mobile usability studies are only pertinent in the context of ergonomics,physical user interface,and mo­bility aspects.In addition,much of the previous mobile usability conception was built on desktop computing measure­ments,such as desktop and web application checklists,or scarcely addressed the mobile user interface.Moreover,the studies focus mainly on interface features for desktop applications and do not reflect comprehensive mobile interface features such as navigation drawers and spinners.Therefore,conducting usability evaluation using conventional us­ability measurement would result in irrelevant results.In addition,the resulting works are tailored for usability testing,which requires highly skilled evaluators and usability specialists(e.g.,usability testers and user experience designers),who are rarely integrated into a development team.The lack of expertise could lead to unreliable usability evaluations.This paper presents a review from industrial experts on a comprehensive and feasible usability evaluation framework developed in our previous work.The framework is dedicated to smartphone apps,which integrate evaluator skills and design concerns.However,there is no evidence of its usefulness in practice.Therefore,the usefulness of the frame­work measurement for evaluating apps’usability in the eyes of non-usability specialists is empirically assessed in this paper through an expert review.The expert review involved eleven industrial developers and was complemented by a semi-structured interview.The method is replicated in comparison with a framework from another study.The findings show that the formulated framework significantly outperformed the framework(p=0.0286)from other studies with large effect sizes(r=1.81)in terms of usefulness.

Effects of Explanation Type on Consumers' Perceived Usefulness of Online Reviews and Their Boundary Conditions

In making purchasing decisions, consumers look to online reviews posted by others who have used or experienced the product/service. Most existing studies on online reviews only focused on their content without addressing how their explanation type influences purchasing decisions, not to mention the boundary conditions for such effects. Based on three experimental studies, this paper examines how explanation type affects the perceived usefulness of online reviews and purchasing decisions, and discusses the boundary conditions for such effects. Our findings show that positive explanation type has a positive effect on the perceived usefulness of online reviews, while negative explanation has an insignificant impact. For search products, there is a positive correlation between the online reviews of explained actions and the perceived usefulness of consumer reviews. For experience products, there is a positive correlation between the online reviews of explained reactions and the perceived usefulness of consumer reviews. Further research found that temporal distance may moderate the effects of explanation type and product type on the perceived usefulness of online reviews. This study also provides a new approach for research on the word-of-mouth(WOM) with meaningful implications for e-commerce firms.

Reviewer Locator模块在科技期刊中的应用实践与发展前景——以《中国肺癌杂志》为例

科技期刊作为科技传播的重要力量,其对重要科研成果的发布速度影响着科学技术的传播效力,而编辑工作效率直接决定稿件发表周期,提高编辑工作效率是科技期刊发展的推进器。为此,从同行评议审稿人储备和遴选方面入手,重点阐述如何准确高效地多维度遴选优质审稿人,归纳并探析Reviewer Locator模块在科技期刊办刊工作中的实际应用经验,助力出版业实现质量更好、效率更高的发展。

Delivering substance use prevention interventions for adolescents in educational settings:A scoping review

Currently,a proportion of adolescents use alcohol,tobacco,and illicit drugs,which inevitably harms their health and academic progress.Adolescence is a peak period for substance use initiation and a critical time for preventing substance use problems.Various entities,such as families,schools,and communities,have implemented a variety of interventions to alleviate adolescent substance use problems,and schools play a unique role.To explore the types,characteristics,and effectiveness of substance use interventions in educational settings for adolescents,we conducted a scoping review and identified 32 studies after screening.We divided the 32 studies according to intervention type,including curriculum interventions focusing on cognitive-behavioral skill enhancement,exercise interventions,peer interventions and family-school cooperation,and electronic interventions.Except for the mixed results on electronic interventions,the results showed that the other interventions were beneficial to different extents in alleviating adolescent substance use problems.In addition,we analyzed and summarized the advantages and challenges of intervening in adolescent substance use in educational settings.Schools can use equipment and human resources to provide adolescents with various types of intervention measures,but they also face challenges such as stigmatization,ineffective coordination among multiple resources,and poor implementation effects.In the future,school-based intervention measures can fully utilize big data and artificial intelligence technology and collaborate with families and communities to intervene appropriately while paying attention to the comorbidity risks of substance use disorders and psychological health issues.

Systematic Review of Literature for Smartphones Technology Acceptance Using Unified Theory of Acceptance and Use of Technology Model (UTAUT)

Systematic Review and Meta-analysis are techniques which attempt to associate the findings from similar studies and deliver quantitative summaries of the research literature [1]. The Systematic review of research literature identifies the common research methods, research design, sample size, parameters used, survey instruments, etc. used by the group of researchers. This study intends to fulfill this purpose in order to identify common research mythologies, dependent variables, sample sizes, moderators and mediators used in the field of analysing technology adoption based studies that utilizes the UTAUT2 model. This research collected over 59 published articles and conducted descriptive analytics. The results have revealed performance expectancy/perceived usefulness, trust and habit as the best predictors of consumer behavioural intentions towards the adoption of mobile application. Behavioural intention was the best predictor of use behaviour among the 57 articles selected. 274 was the mean sample size of research with 25 mean questionnaire items. SPSS and AMOS were the most common softwares used in all 57 studies, and 32 of those studies used UTAUT1 model while 14 researches incorporated the UTAUT2 model. There were also two promising predictors such as perceived risk on behavioural intention and habit on use behaviour.

Machine learning techniques for prediction of capacitance and remaining useful life of supercapacitors: A comprehensive review

Supercapacitors are appealing energy storage devices for their promising features like high power density,outstanding cycling stability,and a quick charge–discharge cycle.The exceptional life cycle and ultimate power capability of supercapacitors are needed in the transportation and renewable energy generation sectors.Hence,predicting the capacitance and lifecycle of supercapacitors is significant for selecting the suitable material and planning replacement intervals for supercapacitors.In addition,system failures can be better addressed by accurately forecasting the lifecycle of SCs.Recently,the use of machine learning for performance prediction of energy storage materials has drawn increasing attention from researchers globally because of its superiority in prediction accuracy,time efficiency,and costeffectiveness.This article presents a detailed review of the progress and advancement of ML techniques for the prediction of capacitance and remaining useful life(RUL)of supercapacitors.The review starts with an introduction to supercapacitor materials and ML applications in energy storage devices,followed by workflow for ML model building for supercapacitor materials.Then,the summary of machine learning applications for the prediction of capacitance and RUL of different supercapacitor materials including EDLCs(carbon based materials),pesudocapacitive(oxides and composites)and hybrid materials is presented.Finally,the general perspective for future directions is also presented.

Colorectal cancer screening:A review of current knowledge and progress in research

Colorectal cancer(CRC)is one of the most prevalent malignancies worldwide,being the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths globally.Despite the progress in screening,early diagnosis,and treatment,approximately 20%-25%of CRC patients still present with metastatic disease at the time of their initial diagnosis.Furthermore,the burden of disease is still expected to increase,especially in individuals younger than 50 years old,among whom early-onset CRC incidence has been increasing.Screening and early detection are pivotal to improve CRC-related outcomes.It is well established that CRC screening not only reduces incidence,but also decreases deaths from CRC.Diverse screening strategies have proven effective in decreasing both CRC incidence and mortality,though variations in efficacy have been reported across the literature.However,uncertainties persist regarding the optimal screening method,age intervals and periodicity.Moreover,adherence to CRC screening remains globally low.In recent years,emerging technologies,notably artificial intelligence,and non-invasive biomarkers,have been developed to overcome these barriers.However,controversy exists over the actual impact of some of the new discoveries on CRC-related outcomes and how to effectively integrate them into daily practice.In this review,we aim to cover the current evidence surrounding CRC screening.We will further critically assess novel approaches under investigation,in an effort to differentiate promising inno-vations from mere novelties.

Association between physical activity and risk of gastroesophageal reflux disease:A systematic review and meta-analysis

Background:Lifestyle plays an important role in preventing and managing gastroesophageal reflux disease(GERD).In response to the conflicting results in previous studies,we performed a systematic review and meta-analysis to investigate this association.Methods:Relevant studies published until January 2023 were retrieved from 6 databases,and the prevalence of symptomatic gastroesophageal reflux(GER)or GERD was determined from the original studies.A random effects model was employed to meta-analyze the association by computing the pooled relative risk(RR)with 95%confidence intervals(95%CIs).Furthermore,subgroup and dose-response analyses were performed to explore subgroup differences and the association between cumulative physical activity(PA)time and GERD.Results:This meta-analysis included 33 studies comprising 242,850 participants.A significant negative association was observed between PA and the prevalence of symptomatic GER(RR=0.74,95%CI:0.66-0.83;p<0.01)or GERD(RR=0.80,95%CI:0.76-0.84;p<0.01),suggesting that engaging in PA might confer a protective benefit against GERD.Subgroup analyses consistently indicated the presence of this association across nearly all subgroups,particularly among the older individuals(RR_(<40 years):RR_(≥40 years)=0.85:0.69,p<0.01)and smokers(RR_(smoker):RR_(non-smoker)=0.67:0.82,p=0.03).Furthermore,a dose-response analysis revealed that individuals who engaged in 150 min of PA per week had a 72.09%lower risk of developing GERD.Conclusion:Maintaining high levels of PA decreased the risk of GERD,particularly among older adults and smokers.Meeting the recommended PA level of 150 min per week may significantly decrease the prevalence of GERD.

Effects of mindfulness-based interventions on depressive symptoms in patients with substance use disorders:a systematic review and meta-analysis

Objective:We examined the effects of mindfulness-based interventions(MBIs)on depressive symptoms in patients with substance use disorders(SUDs)and explored the moderating effects of participant,method,and intervention characteristics.Methods:We systematically searched 8 databases from their inception till November 2021.The inclusion criteria were primary studies evaluating MBIs in patients with SUDs with depression measured as an outcome,those including a control group,and those written in English.We used a random-effects model to compute effect sizes(ESs)using Hedges’g,a forest plot,and Q and I2 statistics as measures of heterogeneity;we also examined moderator analyses.Results:Nineteen studies included 1352 participants(age:38.6±7.0 years).Overall,MBIs showed significantly improved depression(g=0.67,95%confidence interval[CI]:0.29,1.05,I2=89%)compared to controls.With regard to moderators,providing MBIs as an individual plus group intervention had a greater effect(g=2.13)on reducing depressive symptoms than providing MBIs as a group intervention(g=0.64)or an individual intervention only(g=0.33,P=0.034).Using concealed allocation tended to reduce depressive symptoms(g=1.22)as compared to not using concealed allocation(g=0.48,P=0.086).No other quality indicators were demonstrated to have a moderating influence on the value of the ES.Conclusions:MBIs improved depressive symptoms in patients with SUDs.MBIs might be used as an adjunctive or alternative to conventional treatment for depressed patients with SUDs.

The influence of resistance exercise training prescription variables on skeletal muscle mass,strength,and physical function in healthy adults:An umbrella review

Purpose:The aim of this umbrella review was to determine the impact of resistance training(RT)and individual RT prescription variables on muscle mass,strength,and physical function in healthy adults.Methods:Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses(PRISMA)guidelines,we systematically searched and screened eligible systematic reviews reporting the effects of differing RT prescription variables on muscle mass(or its proxies),strength,and/or physical function in healthy adults aged>18 years.Results:We identified 44 systematic reviews that met our inclusion criteria.The methodological quality of these reviews was assessed using A Measurement Tool to Assess Systematic Reviews;standardized effectiveness statements were generated.We found that RT was consistently a potent stimulus for increasing skeletal muscle mass(4/4 reviews provide some or sufficient evidence),strength(4/6 reviews provided some or sufficient evidence),and physical function(1/1 review provided some evidence).RT load(6/8 reviews provided some or sufficient evidence),weekly frequency(2/4 reviews provided some or sufficient evidence),volume(3/7 reviews provided some or sufficient evidence),and exercise order(1/1 review provided some evidence)impacted RT-induced increases in muscular strength.We discovered that 2/3 reviews provided some or sufficient evidence that RT volume and contraction velocity influenced skeletal muscle mass,while 4/7 reviews provided insufficient evidence in favor of RT load impacting skeletal muscle mass.There was insufficient evidence to conclude that time of day,periodization,inter-set rest,set configuration,set end point,contraction velocity/time under tension,or exercise order(only pertaining to hypertrophy)influenced skeletal muscle adaptations.A paucity of data limited insights into the impact of RT prescription variables on physical function.Conclusion:Overall,RT increased muscle mass,strength,and physical function compared to no exercise.RT intensity(load)and weekly frequency impacted RT-induced increases in muscular strength but not muscle hypertrophy.RT volume(number of sets)influenced muscular strength and hypertrophy.

Accurate and efficient remaining useful life prediction of batteries enabled by physics-informed machine learning

The safe and reliable operation of lithium-ion batteries necessitates the accurate prediction of remaining useful life(RUL).However,this task is challenging due to the diverse ageing mechanisms,various operating conditions,and limited measured signals.Although data-driven methods are perceived as a promising solution,they ignore intrinsic battery physics,leading to compromised accuracy,low efficiency,and low interpretability.In response,this study integrates domain knowledge into deep learning to enhance the RUL prediction performance.We demonstrate accurate RUL prediction using only a single charging curve.First,a generalisable physics-based model is developed to extract ageing-correlated parameters that can describe and explain battery degradation from battery charging data.The parameters inform a deep neural network(DNN)to predict RUL with high accuracy and efficiency.The trained model is validated under 3 types of batteries working under 7 conditions,considering fully charged and partially charged cases.Using data from one cycle only,the proposed method achieves a root mean squared error(RMSE)of 11.42 cycles and a mean absolute relative error(MARE)of 3.19%on average,which are over45%and 44%lower compared to the two state-of-the-art data-driven methods,respectively.Besides its accuracy,the proposed method also outperforms existing methods in terms of efficiency,input burden,and robustness.The inherent relationship between the model parameters and the battery degradation mechanism is further revealed,substantiating the intrinsic superiority of the proposed method.

Knee osteoarthritis:A review of animal models and intervention of traditional Chinese medicine

Background:Knee osteoarthritis(KOA)characterized by degeneration of knee cartilage and subsequent bone hyperplasia is a prevalent joint condition primarily affecting aging adults.The pathophysiology of KOA remains poorly understood,as it involves complex mechanisms that result in the same outcome.Consequently,researchers are interested in studying KOA and require appropriate animal models for basic research.Chinese herbal compounds,which consist of multiple herbs with diverse pharmacological properties,possess characteristics such as multicomponent,multipathway,and multitarget effects.The potential benefits in the treatment of KOA continue to attract attention.Purpose:This study aims to provide a comprehensive overview of the advantages,limitations,and specific considerations in selecting different species and methods for KOA animal models.This will help researchers make informed decisions when choosing an animal model.Methods:Online academic databases(e.g.,PubMed,Google Scholar,Web of Science,and CNKI)were searched using the search terms“knee osteoarthritis,”“animal models,”“traditional Chinese medicine,”and their combinations,primarily including KOA studies published from 2010 to 2023.Results:Based on literature retrieval,this review provides a comprehensive overview of the methods of establishing KOA animal models;introduces the current status of advantages and disadvantages of various animal models,including mice,rats,rabbits,dogs,and sheep/goats;and presents the current status of methods used to establish KOA animal models.Conclusion:This study provides a review of the animal models used in recent KOA research,discusses the common modeling methods,and emphasizes the role of traditional Chinese medicine compounds in the treatment of KOA.

Impact of frailty on outcomes of elderly patients undergoing percutaneous coronary intervention: A systematic review and metaanalysis

BACKGROUND Frailty is a common condition in elderly patients who receive percutaneous coronary intervention(PCI).However,how frailty affects clinical outcomes in this group is unclear.AIM To assess the link between frailty and the outcomes,such as in-hospital complic-ations,post-procedural complications,and mortality,in elderly patients post-PCI.METHODS The PubMed/MEDLINE,EMBASE,Cochrane Library,and Web of Science databases were screened for publications up to August 2023.The primary outcomes assessed were in-hospital and all-cause mortality,major adverse cardiovascular events(MACEs),and major bleeding.The Newcastle-Ottawa Scale was used for quality assessment.RESULTS Twenty-one studies with 739693 elderly patients undergoing PCI were included.Frailty was consistently associated with adverse outcomes.Frail patients had significantly higher risks of in-hospital mortality[risk ratio:3.45,95%confidence interval(95%CI):1.90-6.25],all-cause mortality[hazard ratio(HR):2.08,95%CI:1.78-2.43],MACEs(HR:2.92,95%CI:1.85-4.60),and major bleeding(HR:4.60,95%CI:2.89-7.32)compared to non-frail patients.CONCLUSION Frailty is a pivotal determinant in the prediction of risk of mortality,development of MACEs,and major bleeding in elderly individuals undergoing percutaneous coronary intervention.