Cardiovascular risk factors among older persons with cognitive frailty in middle income country

BACKGROUND Cognitive frailty,characterized by the coexistence of cognitive impairment and physical frailty,represents a multifaceted challenge in the aging population.The role of cardiovascular risk factors in this complex interplay is not yet fully understood.AIM To investigate the relationships between cardiovascular risk factors and older persons with cognitive frailty by pooling data from two cohorts of studies in Malaysia.METHODS A comprehensive approach was employed,with a total of 512 communitydwelling older persons aged 60 years and above,involving two cohorts of older persons from previous studies.Datasets related to cardiovascular risks,namely sociodemographic factors,and cardiovascular risk factors,including hypertension,diabetes,hypercholesterolemia,anthropometric characteristics and biochemical profiles,were pooled for analysis.Cognitive frailty was defined based on the Clinical Dementia Rating scale and Fried frailty score.Cardiovascular risk was determined using Framingham risk score.Statistical analyses were conducted using SPSS version 21.RESULTS Of the study participants,46.3%exhibited cognitive frailty.Cardiovascular risk factors including hypertension(OR:1.60;95%CI:1.12-2.30),low fat-free mass(OR:0.96;95%CI:0.94-0.98),high percentage body fat(OR:1.04;95%CI:1.02-1.06),high waist circumference(OR:1.02;95%CI:1.01-1.04),high fasting blood glucose(OR:1.64;95%CI:1.11-2.43),high Framingham risk score(OR:1.65;95%CI:1.17-2.31),together with sociodemographic factors,i.e.,being single(OR 3.38;95%CI:2.26-5.05)and low household income(OR 2.18;95%CI:1.44-3.30)were found to be associated with cognitive frailty.CONCLUSION Cardiovascular-risk specific risk factors and sociodemographic factors were associated with risk of cognitive frailty,a prodromal stage of dementia.Early identification and management of cardiovascular risk factors,particularly among specific group of the population might mitigate the risk of cognitive frailty,hence preventing dementia.

On the Rule of Law Path for Inclusive Education to Empower Education Assistance for Persons with Disabilities

Inclusive education is the mainstream of developing education for persons with disabilities worldwide.It advocates the recognition and protection of the right of persons with disabilities to receive inclusive education in mainstream schools.From the perspective of inclusive education,the educational assistance system for persons with disabilities represents a theoretical innovation in traditional educational support methods,playing a crucial role in integrating persons with disabilities into society,reversing their disadvantaged status,and maintaining educational equity.At present,China's legal system for inclusive education assistance for persons with disabilities needs improvement,and faces several obstacles,including conceptual“limited capacity”,“monotonous”subjects,“crowding-out”obstacles and supervision“absence”obstacles.It is urgent to begin with the transformation of the rule of law concept,clarify the legal positioning of multiple responsibility subjects,achieve mutual reinforcement of education law and education aid legislation,establish a supervision system for inclusive education assistance,and improve the legal framework for educational assistance for persons with disabilities.This will ensure that persons with disabilities can successfully realize their right to education,share in the benefits of social development,and ultimately contribute to achieving common prosperity.

多主体协同开发社区教育课程的PERSONAL模式探索——基于“我爱我家”的个案研究

通过对“我爱我家”这一社区自发课程的跟踪调查,发现社区自发课程开发实质上是一个组织学习过程,经过个体直觉、知识解释、知识整合等环节实现组织的制度化学习,在推动学习型无边界组织生成的同时,生成社区教育课程。在这一过程中,政策(policies)支持、专家(expert)指导、区域需求和区域特征(regional)、社区系统(system)、组织化(organization)等多要素叠加发挥作用,通过不断拓展新鲜(new)领域的积极行动(action)整合所有资源,并推动跨越边界的学习(learning)贯穿始终。因此,多主体协同的社区自发课程可以不完全地概括为PERSONAL模式。要以PERSONAL模式发展社区自发课程,需要以学习者为中心,注重发展人际互动,营造有利于跨组织交互学习的教育生态系统。

Personal Thermal Management by Radiative Cooling and Heating

Maintaining thermal comfort within the human body is crucial for optimal health and overall well-being.By merely broadening the setpoint of indoor temperatures,we could significantly slash energy usage in building heating,ventilation,and air-conditioning systems.In recent years,there has been a surge in advancements in personal thermal management(PTM),aiming to regulate heat and moisture transfer within our immediate surroundings,clothing,and skin.The advent of PTM is driven by the rapid development in nano/micro-materials and energy science and engineering.An emerging research area in PTM is personal radiative thermal management(PRTM),which demonstrates immense potential with its high radiative heat transfer efficiency and ease of regulation.However,it is less taken into account in traditional textiles,and there currently lies a gap in our knowledge and understanding of PRTM.In this review,we aim to present a thorough analysis of advanced textile materials and technologies for PRTM.Specifically,we will introduce and discuss the underlying radiation heat transfer mechanisms,fabrication methods of textiles,and various indoor/outdoor applications in light of their different regulation functionalities,including radiative cooling,radiative heating,and dual-mode thermoregulation.Furthermore,we will shine a light on the current hurdles,propose potential strategies,and delve into future technology trends for PRTM with an emphasis on functionalities and applications.

Dynamic Hand Gesture-Based Person Identification Using Leap Motion and Machine Learning Approaches

Person identification is one of the most vital tasks for network security. People are more concerned about theirsecurity due to traditional passwords becoming weaker or leaking in various attacks. In recent decades, fingerprintsand faces have been widely used for person identification, which has the risk of information leakage as a resultof reproducing fingers or faces by taking a snapshot. Recently, people have focused on creating an identifiablepattern, which will not be reproducible falsely by capturing psychological and behavioral information of a personusing vision and sensor-based techniques. In existing studies, most of the researchers used very complex patternsin this direction, which need special training and attention to remember the patterns and failed to capturethe psychological and behavioral information of a person properly. To overcome these problems, this researchdevised a novel dynamic hand gesture-based person identification system using a Leap Motion sensor. Thisstudy developed two hand gesture-based pattern datasets for performing the experiments, which contained morethan 500 samples, collected from 25 subjects. Various static and dynamic features were extracted from the handgeometry. Randomforest was used to measure feature importance using the Gini Index. Finally, the support vectormachinewas implemented for person identification and evaluate its performance using identification accuracy. Theexperimental results showed that the proposed system produced an identification accuracy of 99.8% for arbitraryhand gesture-based patterns and 99.6% for the same dynamic hand gesture-based patterns. This result indicatedthat the proposed system can be used for person identification in the field of security.

Liver function in transgender persons:Challenges in the COVID-19 era

Transgender persons constitute a non-negligible percentage of the general population.Physical gender-transitioning in trans persons is mainly achieved with hormonal cross-sex therapy and sex reassignment surgeries that aim to align bodily appearance with gender identity.Hormonal treatment acts via suppressing the secretion of the endogenous sex hormones and replacing them with the hormones of the desired sex.The administration of testosterone is the typical masculinizing treatment in trans men,whilst trans women are routinely treated with estradiol agents in combination with anti-androgens or gonadotrophinreleasing hormone agonists if testes are present.Exogenous androgenic steroids,estradiol agents,and anti-androgens have been implicated in a series of hepatotoxic effects.Thus,liver integrity is a major concern with the long-term administration of cross-sex therapy.Hepatic tissue is susceptible to coronavirus disease 19(COVID-19)through various pathophysiological mechanisms.Special consideration should be paid to minimize the risk of hepatic damage from the potential cumulative effect of COVID-19 and gender-affirming treatment in transgender patients.Appropriate care is significant,with continuous laboratory monitoring,clinical observation and,if needed,specific treatment,especially in severe cases of infection and in persons with additional liver pathologies.The pandemic can be an opportunity to provide equal access to care for all and increase the resilience of the transgender population.

Depression and Suicidal Ideations among Older Persons Living with HIV/AIDS in Mbarara City, Southwest Uganda

Background: Due to the increase in longevity and use of antiretroviral treatment, Uganda has had a growing population of older persons living with HIV/AIDS. However, there is a paucity of information on the mental health of the elderly living with HIV/AIDS. In this cross-sectional study, we determined the prevalence of, and associated factors for depression and suicidal ideation among older persons living with HIV/AIDS in Mbarara city, southwest Uganda. Methods: Older persons (150 females, 115 males), with mean age = 64.2 (±5.1) years, accessing health services from three purposively selected HIV/AIDS care centers in Mbarara city, southwest Uganda were recruited. Data on depression and suicidal ideation were collected using a Patient Health Questionnaire (PHQ-9) validated in Uganda, and a structured questionnaire was used to collect data on clinical and socio-demographic characteristics. Data were analysed using logistic regression. Results: Approximately 8.3% and 12.1% had depression and suicidal ideation, respectively. The factors associated with lowering the likelihood of depression were: an increase in the number of family members they stayed with and having no having any problems with their ARVs. On the other hand, earning more than 100,000 Uganda shillings was associated with reducing the risk of suicidal ideations among the participants. Conclusion: Approximately 8 to 12 in 100 older persons living with HIV/AIDS in Uganda have experienced depression or suicidal ideation. Family support and financial control were instrumental factors associated with depression and suicidal ideations, respectively. We recommended strengthening family structures and creating more avenues for financial independence among older persons living with HIV/AIDS to reduce the burden of depression, and suicidal behaviours among this vulnerable population.

Gut Bacteria and Nutritional Status of Nigerian Children at an Internally Displaced Persons’ Camp in Benue State, Nigeria: A Pilot Study

This study was conducted to determine the gut bacteria and nutritional status of children (n = 30) aged 2 - 11 in Benue’s largest internally displaced persons (IDP) camp since information on this is lacking. Gut bacteria were identified using culture techniques, while Body Mass Index (Kg/m2), Weight-for-Height (WHZ), and Weight-for-Age (WAZ) z scores were computed from anthropometric measurements. Socio-demographic and economic variables were collected via structured questionnaires. IBM SPSS v25 was used to analyze the data, with p Salmonella spp., Shigella spp., and Escherichia coli compared to children from a nearby private school (n = 10), except for E. coli, where the prevalence was equal. The results for BMI revealed that 23 (57.5%) of the children had a healthy weight while 17 (42.5%) were underweight.WAZ z-scores were between (-0.02 - 2.51) with evidence of mildly underweight (20%) and mildly overweight (5%) children. WHZ z-scores were between -0.03 - 2.37, with moderately wasted (30%) and severely wasted (5%) found. To ensure better health outcomes for residents, conditions in the camp must be improved.

Impact of community-based rehabilitation on quality of life and self-esteem of persons with physical disabilities and their family members

Objective:Community-based rehabilitation(CBR)is a strategy by which persons living with disability(PWDs)access comprehensive rehabilitation services with limited evidence regarding its impact on the quality of life(QOL)and self-esteem(SE)of PWDs and their family members.This study compared the QOL and SE of Nigerian PWDs in communities with and without a CBR programme(CBR and non-CBR respectively),and the family quality of life(FQOL)of their family members.Methods:Cross-sectional study involving 2604 PWDs(1302 in CBR and 1302 in non-CBR);5208 family members of PWDs(2604 in CBR and 2604 non-CBR),recruited from four randomly selected geo-political zones in Nigeria,purposive/consecutive selection of eight CBR programmes,PWDs and their family members(CBR and non-CBR).Outcomes assessed using Rosenberg Self-Esteem Scale(RSES),World Health Organization Quality of Life Instrument-short form(WHOQOL-BREF)and Beach Centre Family Quality of Life Instrument(BCFQOL).Mann-Whitney U test and Spearman's rank order correlation were used to analyse data at P<0.05.Results:PWDs in CBR scored higher in all domains of WHOQOL-BREF(P<0.0001 in all cases)and RSES than non-CBR group(P<0.0001).The CBR families scored significantly higher than non-CBR families in all domains(P<0.05)except Emotional Well-Being of the BCFQOL.The CBR group scores on Psychological and Social Health domains of the WHOQOL-BREF showed significant positive correlation with CBR families'Family Interaction(P=0.06)and Parenting(P=0.07)domains and total FQOL(P=0.07).Conclusion:Community-based rehabilitation positively impacted on SE and QOL of PWDs and their family members.

Deep Transfer Learning Driven Automated Fall Detection for Quality of Living of Disabled Persons

Mobile communication and the Internet of Things(IoT)technologies have recently been established to collect data from human beings and the environment.The data collected can be leveraged to provide intelligent services through different applications.It is an extreme challenge to monitor disabled people from remote locations.It is because day-to-day events like falls heavily result in accidents.For a person with disabilities,a fall event is an important cause of mortality and post-traumatic complications.Therefore,detecting the fall events of disabled persons in smart homes at early stages is essential to provide the necessary support and increase their survival rate.The current study introduces a Whale Optimization Algorithm Deep Transfer Learning-DrivenAutomated Fall Detection(WOADTL-AFD)technique to improve the Quality of Life for persons with disabilities.The primary aim of the presented WOADTL-AFD technique is to identify and classify the fall events to help disabled individuals.To attain this,the proposed WOADTL-AFDmodel initially uses amodified SqueezeNet feature extractor which proficiently extracts the feature vectors.In addition,the WOADTLAFD technique classifies the fall events using an extreme Gradient Boosting(XGBoost)classifier.In the presented WOADTL-AFD technique,the WOA approach is used to fine-tune the hyperparameters involved in the modified SqueezeNet model.The proposedWOADTL-AFD technique was experimentally validated using the benchmark datasets,and the results confirmed the superior performance of the proposedWOADTL-AFD method compared to other recent approaches.

Personalized Perioperative Care for a Patient with a 10-Year-Old Postpartum Old Thrombus after Neoadjuvant Therapy for Breast Cancer

Breast cancer is one of the most common malignant tumors in women, and has become the main cause threatening women’s health. A case of breast cancer with neoadjuvant chemotherapy was discharged after active treatment and nursing.

Correlation of personality with individual reproductive success in shrub-nesting birds depends on their life history style

Two questions in the research of animal personality—whether there is a correlation between a personality trait and individual reproductive success,and what is the genetic basis underlying a personality trait—remain unresolved.We addressed these two questions in three shrub-nesting birds,the Azure-winged Magpie(Cyanopica cyanus,AM),White-collared Blackbird(Turdus albocinctus,WB),and Brown-cheeked Laughingthrush(Trochalopteron henrici,BL).The personality type of an individual was first identified according to its response to a territorial intruder.Then,we compared the fleeing distance,breeding parameters,and differential expressed genes(DEGs) in the brain transcriptome between bold and shy breeders.In the three species,bold breeders exhibited more aggressiveness towards an intruder of their territory than did shy breeders.The reproductive success of bold breeders was significantly higher than that of shy breeders in AM but not in WB and BL.The three species shared one DEG,crabp1,which was up-regulated in bold relative to in shy individuals.By regulating the expression of corticotropin-releasing hormone,higher crabp1 gene expression can decrease cellular response to retinoic acid.Therefore,bold individuals are insensitive to external stresses and able to exhibit more aggressiveness to intruders than their shier counterparts.Aggressiveness is beneficial to bold individuals in AM but not in WB and BL because the former could evoke neighbors to make the same response of defending against intruders but the latter could not.Although a personality trait may have the same genetic basis across species,its correlation with reproductive success depends largely on the life history style of a species.

Self-supervised recalibration network for person re-identification

The attention mechanism can extract salient features in images,which has been proved to be effective in improving the performance of person re-identification(Re-ID).However,most of the existing attention modules have the following two shortcomings:On the one hand,they mostly use global average pooling to generate context descriptors,without highlighting the guiding role of salient information on descriptor generation,resulting in insufficient ability of the final generated attention mask representation;On the other hand,the design of most attention modules is complicated,which greatly increases the computational cost of the model.To solve these problems,this paper proposes an attention module called self-supervised recalibration(SR)block,which introduces both global and local information through adaptive weighted fusion to generate a more refined attention mask.In particular,a special"Squeeze-Excitation"(SE)unit is designed in the SR block to further process the generated intermediate masks,both for nonlinearizations of the features and for constraint of the resulting computation by controlling the number of channels.Furthermore,we combine the most commonly used Res Net-50 to construct the instantiation model of the SR block,and verify its effectiveness on multiple Re-ID datasets,especially the mean Average Precision(m AP)on the Occluded-Duke dataset exceeds the state-of-the-art(SOTA)algorithm by 4.49%.

Mutations in Ras homolog family member A in patients with peripheral T-cell lymphoma and implications for personalized medicine

Genome sequencing has revealed frequent mutations in Ras homolog family member A(RHOA)among various cancers with unique aberrant profiles and pathogenic effects,especially in peripheral T-cell lymphoma(PTCL).The discrete positional distribution and types of RHOA amino acid substitutions vary according to the tumor type,thereby leading to different functional and biological properties,which provide new insight into the molecular pathogenesis and potential targeted therapies for various tumors.However,the similarities and discrepancies in characteristics of RHOA mutations among various histologic subtypes of PTCL have not been fully elucidated.Herein we highlight the inconsistencies and complexities of the type and location of RHOA mutations and demonstrate the contribution of RHOA variants to the pathogenesis of PTCL by combining epigenetic abnormalities and activating multiple downstream pathways.The promising potential of targeting RHOA as a therapeutic modality is also outlined.This review provides new insight in the field of personalized medicine to improve the clinical outcomes for patients.

Exploring Frontier Technologies in Video-Based Person Re-Identification:A Survey on Deep Learning Approach

Video-based person re-identification(Re-ID),a subset of retrieval tasks,faces challenges like uncoordinated sample capturing,viewpoint variations,occlusions,cluttered backgrounds,and sequence uncertainties.Recent advancements in deep learning have significantly improved video-based person Re-ID,laying a solid foundation for further progress in the field.In order to enrich researchers’insights into the latest research findings and prospective developments,we offer an extensive overview and meticulous analysis of contemporary video-based person ReID methodologies,with a specific emphasis on network architecture design and loss function design.Firstly,we introduce methods based on network architecture design and loss function design from multiple perspectives,and analyzes the advantages and disadvantages of these methods.Furthermore,we provide a synthesis of prevalent datasets and key evaluation metrics utilized within this field to assist researchers in assessing methodological efficacy and establishing benchmarks for performance evaluation.Lastly,through a critical evaluation of the experimental outcomes derived from various methodologies across four prominent public datasets,we identify promising research avenues and offer valuable insights to steer future exploration and innovation in this vibrant and evolving field of video-based person Re-ID.This comprehensive analysis aims to equip researchers with the necessary knowledge and strategic foresight to navigate the complexities of video-based person Re-ID,fostering continued progress and breakthroughs in this challenging yet promising research domain.

Autoimmune hepatitis:Towards a personalized treatment

Autoimmune hepatitis is an uncommon condition that affects both adults and children and is characterized by chronic and recurrent inflammatory activity in the liver.This inflammation is accompanied by elevated IgG and autoantibody levels.Historically,treatment consists of steroids with the addition of azathioprine,which results in remission in approximately 80%of patients.Despite significant advancements in our understanding of the immune system over the past two decades,few modifications have been made to treatment algorithms,which have remained largely unchanged since they were first proposed more than 40 years ago.This review summarized the various treatment options currently available as well as our experiences using them.Although steroids are the standard treatment for induction therapy,other medications may be considered.Cyclosporin A,a calcineurin inhibitor that decreases T cell activation,has proven effective for induction of remission,but its long-term side effects limit its appeal for maintenance.Tacrolimus,a drug belonging to the same family,has been used in patients with refractory diseases with fewer side effects.Sirolimus and everolimus have interesting effects on regulatory T cell populations and may become viable options in the future.Mycophenolate mofetil is not effective for induction but is a valid alternative for patients who are intolerant to azathioprine.B celldepleting drugs,such as rituximab and belimumab,have been successfully used in refractory cases and are useful in both the short and long term.Other promising treatments include anti-tumor necrosis factors,Janus kinases inhibitors,and chimeric antigen receptor T cell therapy.This growing armamentarium allows us to imagine a more tailored approach to the treatment of autoimmune hepatitis in the near future.

Personalized Lower Limb Gait Reconstruction Modeling Based on RFA-ProMP

Personalized gait curves are generated to enhance patient adaptability to gait trajectories used for passive training in the early stage of rehabilitation for hemiplegic patients.The article utilizes the random forest algorithm to construct a gait parameter model,which maps the relationship between parameters such as height,weight,age,gender,and gait speed,achieving prediction of key points on the gait curve.To enhance prediction accuracy,an attention mechanism is introduced into the algorithm to focus more on the main features.Meanwhile,to ensure high similarity between the reconstructed gait curve and the normal one,probabilistic motion primitives(ProMP)are used to learn the probability distribution of normal gait data and construct a gait trajectorymodel.Finally,using the specified step speed as input,select a reference gait trajectory from the learned trajectory,and reconstruct the curve of the reference trajectoryusing the gait keypoints predictedby the parametermodel toobtain the final curve.Simulation results demonstrate that the method proposed in this paper achieves 98%and 96%curve correlations when generating personalized lower limb gait curves for different patients,respectively,indicating its suitability for such tasks.

Enhancing Unsupervised Domain Adaptation for Person Re-Identification with the Minimal Transfer Cost Framework

In Unsupervised Domain Adaptation(UDA)for person re-identification(re-ID),the primary challenge is reducing the distribution discrepancy between the source and target domains.This can be achieved by implicitly or explicitly constructing an appropriate intermediate domain to enhance recognition capability on the target domain.Implicit construction is difficult due to the absence of intermediate state supervision,making smooth knowledge transfer from the source to the target domain a challenge.To explicitly construct the most suitable intermediate domain for the model to gradually adapt to the feature distribution changes from the source to the target domain,we propose the Minimal Transfer Cost Framework(MTCF).MTCF considers all scenarios of the intermediate domain during the transfer process,ensuring smoother and more efficient domain alignment.Our framework mainly includes threemodules:Intermediate Domain Generator(IDG),Cross-domain Feature Constraint Module(CFCM),and Residual Channel Space Module(RCSM).First,the IDG Module is introduced to generate all possible intermediate domains,ensuring a smooth transition of knowledge fromthe source to the target domain.To reduce the cross-domain feature distribution discrepancy,we propose the CFCM Module,which quantifies the difficulty of knowledge transfer and ensures the diversity of intermediate domain features and their semantic relevance,achieving alignment between the source and target domains by incorporating mutual information and maximum mean discrepancy.We also design the RCSM,which utilizes attention mechanism to enhance the model’s focus on personnel features in low-resolution images,improving the accuracy and efficiency of person re-ID.Our proposed method outperforms existing technologies in all common UDA re-ID tasks and improves the Mean Average Precision(mAP)by 2.3%in the Market to Duke task compared to the state-of-the-art(SOTA)methods.

Personality Trait Detection via Transfer Learning

Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains,including education,e-commerce,or human resources.Tra-ditional machine learning techniques have been broadly employed for personality trait identification;nevertheless,the development of new technologies based on deep learning has led to new opportunities to improve their performance.This study focuses on the capabilities of pre-trained language models such as BERT,RoBERTa,ALBERT,ELECTRA,ERNIE,or XLNet,to deal with the task of personality recognition.These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making them appropriate for the development of user-centric applications.

Personalized treatment of perihilar cholangiocarcinoma based on tumor genetic and molecular characteristics

This editorial discusses the article written by Tchilikidi et al that was published in the latest edition of the World Journal of Gastrointestinal Surgery.Genetic and molecular profiling of perihilar cholangiocarcinoma(pCCA)has identified a number of key abnormalities that drive tumor growth and spread,including pyruvate kinase M2,proline rich 11,and transcription factor 7,etc.pCCA has specific genetic and molecular features that can be used to develop personalized treatment plans.Personalized treatment approaches offer new opportunities for effectively targeting the underlying drivers of tumor growth and progression.The findings based on tumor genetic and molecular characteristics highlight the importance of developing personalized treatment strategies.