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Introduction: Identifying individuals at high risk of dementia is critical to optimized clinical care, formulating effective preventative strategies, and determining eligibility for clinical trials. Since our previous systematic reviews in 2010 and 2015, there has been a surge in dementia risk prediction modelling. The aim of this study was to update our previous reviews to explore, and critically review, new developments in dementia risk modelling. Methods: MEDLINE, Embase, Scopus, and Web of Science were searched from March 2014 to June 2022. Studies were included if they were population- or community-based cohorts (including electronic health record data), had developed a model for predicting late-life incident dementia, and included model performance indices such as discrimination, calibration, or external validation. Results: In total, 9,209 articles were identified from the electronic search, of which 74 met the inclusion criteria. We found a substantial increase in the number of new models published from 2014 (>50 new models), including an increase in the number of models developed using machine learning. Over 450 unique predictor (component) variables have been tested. Nineteen studies (26%) undertook external validation of newly developed or existing models, with mixed results. For the first time, models have also been developed in low- and middle-income countries (LMICs) and others validated in racial and ethnic minority groups. Conclusion: The literature on dementia risk prediction modelling is rapidly evolving with new analytical developments and testing in LMICs. However, it is still challenging to make recommendations about which one model is the most suitable for routine use in a clinical setting. There is an urgent need to develop a suitable, robust, validated risk prediction model in the general population that can be widely implemented in clinical practice to improve dementia prevention.
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Cognitive impairment is common early after stroke but trajectories over the long term are variable. Some stroke survivors make a full recovery, while others retain a stable impairment or decline. This study explored the perceived advantages and disadvantages of discussing potential cognitive trajectories with stroke survivors and their family members. Stroke survivors at least six-months post-stroke were purposively sampled from an existing pool of research volunteers recruited originally for the OCS-Recovery study. They were invited, alongside a family member, to participate in a semi-structured interview. Interviews were audio recorded, transcribed, and analyzed using reflexive thematic analysis. Twenty-six stroke survivors and eleven family members participated. We identified one overarching theme and three related subthemes. The overarching theme was: One size does not fit all. The subthemes were: (1) Hearing about potential cognitive trajectories helps to develop realistic expectations; (2) Discussions about cognitive trajectories may be motivating; (3) Cognitive decline and post-stroke dementia discussions may be anxiety-provoking and depressing. Healthcare professionals should adopt a person-centred approach to sharing information about post-stroke cognitive trajectories. Discussions should be tailored to individual needs and preferences, with dementia-related topics in particular addressed with the utmost selectivity and sensitivity.
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The ATP-binding cassette, subfamily A (ABC1), member 7 (ABCA7) gene is associated with Alzheimer's disease (AD) risk in populations of African, Asian, and European ancestry1-5. Numerous ABCA7 mutations contributing to risk have been identified, including a 44 base pair deletion (rs142076058) specific to individuals of African ancestry and predicted to cause a frameshift mutation (p.Arg578Alafs) (Cukier et al., 2016). The UMi043-A human induced pluripotent stem cell line was derived from an African American individual with AD who is heterozygous for this deletion and is a resource to further investigate ABCA7 and how this African-specific deletion may influence disease pathology.
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Enfermedad de Alzheimer , Línea Celular , Células Madre Pluripotentes Inducidas , Humanos , Enfermedad de Alzheimer/genética , Enfermedad de Alzheimer/metabolismo , Transportadoras de Casetes de Unión a ATP/genética , Negro o Afroamericano/genética , Células Madre Pluripotentes Inducidas/citología , MutaciónRESUMEN
INTRODUCTION: A wide range of modifiable risk factors for dementia have been identified. Considerable debate remains about these risk factors, possible interactions between them or with genetic risk, and causality, and how they can help in clinical trial recruitment and drug development. Artificial intelligence (AI) and machine learning (ML) may refine understanding. METHODS: ML approaches are being developed in dementia prevention. We discuss exemplar uses and evaluate the current applications and limitations in the dementia prevention field. RESULTS: Risk-profiling tools may help identify high-risk populations for clinical trials; however, their performance needs improvement. New risk-profiling and trial-recruitment tools underpinned by ML models may be effective in reducing costs and improving future trials. ML can inform drug-repurposing efforts and prioritization of disease-modifying therapeutics. DISCUSSION: ML is not yet widely used but has considerable potential to enhance precision in dementia prevention. HIGHLIGHTS: Artificial intelligence (AI) is not widely used in the dementia prevention field. Risk-profiling tools are not used in clinical practice. Causal insights are needed to understand risk factors over the lifespan. AI will help personalize risk-management tools for dementia prevention. AI could target specific patient groups that will benefit most for clinical trials.
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Inteligencia Artificial , Demencia , Humanos , Aprendizaje Automático , Factores de Riesgo , Desarrollo de Medicamentos , Demencia/prevención & controlRESUMEN
Background: Dementia is a significant global health issue, particularly for low-income and middle-income countries which majorly contribute to the dementia cases reported globally (67%). We estimated the prevalence of dementia among older people in Bangladesh and compared the estimate across different sociodemographic characteristics and divisions. Methods: A cross-sectional study was conducted in 2019 among individuals aged 60 years or older in seven administrative divisions in Bangladesh. Equal numbers of male and female participants were recruited from each division through a multi-stage random sampling technique. Recruitment was proportionally distributed in urban and rural areas in each division. Following consent, the Mini Mental State Examination (MMSE) was performed on all participants. Dementia was defined as an MMSE score of <24 out of 30. Data on age, sex, education, marital status, occupation, socioeconomic status, and type of community (urban or rural) were obtained using a structured questionnaire to compare the prevalence of dementia across different sociodemographic characteristics. Findings: Between January and December 2019, 2795 individuals were recruited including â¼400 from each of the seven administrative divisions. The mean age was 67 years (SD: 7), 68% were from rural areas and 51% were female. The prevalence of dementia was 8.0% (95% CI: 7.0-8.9%) with variations across age, sex, education, marital status, occupation, and division. No variations in prevalence were observed across urban/rural locations or socioeconomic status. After adjusting for age, sex, education, occupation and marital status, the odds of dementia was two times higher in females than males (OR: 2.15, 95% CI: 1.43-3.28); nine times higher in people aged ≥90 years than people aged 60-69 years (OR: 9.62, 95% CI: 4.79-19.13), and three times higher in people with no education compared to those who had completed primary school (OR: 3.10, 95% CI: 1.95-5.17). Interpretations: The prevalence of dementia is high in Bangladesh and varies across sociodemographic characteristics with a higher prevalence among females, older people, and people with no education. There is an urgent need to identify the key risk factors for dementia in developing countries, such as Bangladesh, to inform the development of context-relevant risk reduction and prevention strategies. Funding: None.
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INTRODUCTION: Artificial intelligence (AI) and neuroimaging offer new opportunities for diagnosis and prognosis of dementia. METHODS: We systematically reviewed studies reporting AI for neuroimaging in diagnosis and/or prognosis of cognitive neurodegenerative diseases. RESULTS: A total of 255 studies were identified. Most studies relied on the Alzheimer's Disease Neuroimaging Initiative dataset. Algorithmic classifiers were the most commonly used AI method (48%) and discriminative models performed best for differentiating Alzheimer's disease from controls. The accuracy of algorithms varied with the patient cohort, imaging modalities, and stratifiers used. Few studies performed validation in an independent cohort. DISCUSSION: The literature has several methodological limitations including lack of sufficient algorithm development descriptions and standard definitions. We make recommendations to improve model validation including addressing key clinical questions, providing sufficient description of AI methods and validating findings in independent datasets. Collaborative approaches between experts in AI and medicine will help achieve the promising potential of AI tools in practice. HIGHLIGHTS: There has been a rapid expansion in the use of machine learning for diagnosis and prognosis in neurodegenerative disease Most studies (71%) relied on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset with no other individual dataset used more than five times There has been a recent rise in the use of more complex discriminative models (e.g., neural networks) that performed better than other classifiers for classification of AD vs healthy controls We make recommendations to address methodological considerations, addressing key clinical questions, and validation We also make recommendations for the field more broadly to standardize outcome measures, address gaps in the literature, and monitor sources of bias.
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Enfermedad de Alzheimer , Enfermedades Neurodegenerativas , Humanos , Enfermedad de Alzheimer/diagnóstico por imagen , Pronóstico , Inteligencia Artificial , Encéfalo/diagnóstico por imagen , Neuroimagen/métodosRESUMEN
OBJECTIVE: To investigate the relationship between burn-out and spiritual health among medical doctors. DESIGN: Systematic literature review and narrative synthesis of cross-sectional studies. SETTING: Any setting, worldwide. DATA SOURCES: Five databases were searched from inception to March 2022, including Medline, Embase, PsycINFO, Scopus and Web of Science. ELIGIBILITY CRITERIA: Any study design that involved medical doctors (and other healthcare staff if assessed alongside medical doctors), that measured (in any way) both burn-out (or similar) and spiritual health (or similar) medical doctors. DATA EXTRACTION AND SYNTHESIS: All records were double screened. Data extraction was performed by one reviewer and a proportion (10%) checked by a second reviewer. Quality was assessed using the Appraisal of Cross-sectional Studies tool. Due to the heterogeneity of the included studies, a narrative review was undertaken without a meta-analysis. RESULTS: Searches yielded 1049 studies. 40 studies met eligibility criteria and were included in this review. Low reported levels of spirituality were associated with high burn-out scores and vice versa. Religion was not significantly associated with lower levels of burn-out. Few studies reported statistically significant findings, few used validated spiritual scores and most were vulnerable to sampling bias. CONCLUSIONS: Published research suggests that burn-out is linked to spiritual health in medical doctors but not to religion. Robust research is needed to confirm these findings and develop effective interventions. PROSPERO REGISTRATION NUMBER: CRD42020200145.
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Agotamiento Profesional , Médicos , Humanos , Estudios TransversalesRESUMEN
INTRODUCTION: The use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as "deep phenotyping" cohorts with multi-omics health data become available. METHODS: This narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors. RESULTS: This review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high-throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health. DISCUSSION: Such approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch-based accelerometry).
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Inteligencia Artificial , Demencia , Humanos , Salud Digital , Aprendizaje Automático , Demencia/diagnóstico , Demencia/epidemiologíaRESUMEN
OBJECTIVES: Clinical guidelines recommend early cognitive assessment after stroke to inform rehabilitation and discharge decisions. However, little is known about stroke survivors' experiences of the cognitive assessment process. This qualitative study aimed to explore patients' experiences of poststroke cognitive assessments. DESIGN: Stroke survivors were purposively sampled in an iterative process through a pool of research volunteers who had previously taken part in the Oxford Cognitive Screen Recovery study. Stroke survivors and their family caregivers were invited to participate in a semistructured interview steered by a topic guide. Interviews were audio recorded, transcribed and analysed using reflexive thematic analysis. Demographic, clinical and cognitive data were acquired from patients' previous research data. SETTING: Stroke survivors were originally recruited from the acute inpatient unit at Oxford University Hospital (John Radcliffe), UK. Participants were interviewed after discharge either at their homes or via telephone or videocall. PARTICIPANTS: Twenty-six stroke survivors and eleven caregivers participated in semi-structured interviews. RESULTS: We identified three key phases of the cognitive assessment process and themes pertaining to each phase. The phases (numbered) and themes (lettered) were as follows: (1) before the cognitive assessment: (A) lack of explanation, (B) considering the assessment useless; (2) during the cognitive assessment: varied emotional responses, moderated by (D) perception of the purpose behind cognitive assessment, (E) perception of cognitive impairment, (F) confidence in cognitive abilities, (G) assessment administration style and (3) after the cognitive assessment: (H) feedback can impact self-confidence and self-efficacy, (I) vague feedback and clinical jargon are unhelpful. CONCLUSIONS: Stroke survivors require clear explanations about the purpose and outcomes of poststroke cognitive assessments, including constructive feedback, to promote engagement with the process and protect their psychological wellbeing.
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Pacientes Internos , Medicina , Humanos , Investigación Cualitativa , Registros , CogniciónRESUMEN
BACKGROUND: Psychiatric medications play a vital role in the management of mental health disorders. However, the COVID-19 pandemic and subsequent lockdown limited access to primary care services, leading to an increase in remote assessment and treatment options to maintain social distancing. This study aimed to investigate the impact of the COVID-19 pandemic lockdown on the use of psychiatric medication in primary care settings. METHODS: We conducted a retrospective claims-based analysis of anonymized monthly aggregate practice-level data on anxiolytics and hypnotics use from 322 general practitioner (GP) practices in the North East of England, where health disparities are known to be higher. Participants were all residents who took anxiolytics and hypnotics from primary care facilities for two financial years, from 2019/20 to 2020/21. The primary outcome was the volume of Anxiolytics and Hypnotics used as the standardized, average daily quantities (ADQs) per 1000 patients. Based on the OpenPrescribing database, a random-effect model was applied to quantify the change in the level and trend of anxiolytics and hypnotics use after the UK national lockdown in March 2020. Practice characteristics extracted from the Fingertips data were assessed for their association with a reduction in medication use following the lockdown. RESULTS: This study in the North East of England found that GP practices in higher health disparate regions had a lower workload than those in less health disparate areas, potentially due to disparities in healthcare utilization and socioeconomic status. Patients in the region reported higher levels of satisfaction with healthcare services compared to the England average, but there were differences between patients living in higher versus less health disparate areas. The study highlights the need for targeted interventions to address health disparities, particularly in higher health disparate areas. The study also found that psychiatric medication use was significantly more common in residents living in higher health disparate areas. Daily anxiolytics and hypnotics use decreased by 14 items per 1000 patients between the financial years 2019/20 and 2020/21. A further nine items per 1000 decreased for higher health disparate areas during the UK national lockdown. CONCLUSIONS: People during the COVID-19 lockdown were associated with an increased risk of unmet psychiatric medication demand, especially for higher health disparate areas that had low-socioeconomic status.
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Ansiolíticos , COVID-19 , Médicos Generales , Humanos , COVID-19/epidemiología , Ansiolíticos/uso terapéutico , Pandemias , Estudios Retrospectivos , Control de Enfermedades Transmisibles , Hipnóticos y Sedantes , Inglaterra/epidemiologíaRESUMEN
BACKGROUND: COVID-19 has exacerbated the significant and longstanding mental health inequalities for ethnic minorities, who were less likely to access mental health support in primary care but more likely to end up in crisis care compared to the majority ethnic group. Services were poorly offered and accessed to respond to the increased mental health challenges. AIM: To 1) establish evidence on which changes to mental health services provided in response to COVID-19 are beneficial for ethnic minorities who experience mental health difficulties in the North of England, and 2) to inform what and how culturally competent mental health services should be routinely provided. METHODS: A mixed methods approach comprising 1) a rapid review to map services and models of care designed or adjusted for mental health during the pandemic, 2) an observational study of retrospective routine data to assess changes to mental health services and associated outcomes, 3) qualitative interviews to understand experiences of seeking care and factors associated with high-quality service provision, and 4) a Delphi study to establish consensus on key features of culturally competent services. From the selected areas in the North of England, adults from ethnic minorities who experience mental health difficulties will be identified from the primary, community and secondary care services and local ethnic minority communities. DISCUSSION: This study will identify ways to tackle health inequalities and contribute to mental health service recovery post pandemic by providing practice recommendations on equitable and effective services to ensure culturally competent and high-quality care. A list of services and features on what and how mental health services will be provided. Working with study collaborators and public and patient involvement partners, the study findings will be widely disseminated through presentations, conferences and publications and will inform the subsequent funding application for intervention development and evaluation.
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COVID-19 , Servicios de Salud Mental , Adulto , Humanos , COVID-19/epidemiología , COVID-19/terapia , Competencia Cultural , Etnicidad/psicología , Grupos Minoritarios/psicología , Estudios Observacionales como Asunto , Estudios Retrospectivos , Literatura de Revisión como AsuntoRESUMEN
Introduction: Cardiovascular diseases (CVDs) have been associated with an increased risk of dementia; yet the evidence is mixed. This review critically appraises and synthesises current evidence exploring associations between dementia risk and CVD and their risk factors, including coronary heart disease, heart failure, atrial fibrillation, hypertension, hyperlipidaemia, and arterial stiffness. Methods: MEDLINE, Embase, PsycINFO, and the Cochrane Database of Systematic Reviews were searched to identify systematic reviews with meta-analyses investigating the association between at least one of the CVDs of interest and dementia risk. The Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Systematic Reviews was used to assess methodological quality. Results: Twenty-five meta-analyses published between 2007 and 2021 were included. Studies largely consisted of cohorts from North America and Europe. Findings were variable, with coronary heart disease, heart failure, and atrial fibrillation consistently associated with increased risk for all-cause dementia, but results were inconsistent for Alzheimer's disease. Hypertension was more frequently associated with dementia during mid-life compared to late life. Findings concerning cholesterol were complex, and while results were inconsistent for low-density lipoprotein cholesterol and total cholesterol, there appeared to be no associations between triglycerides and high-density lipoprotein cholesterol. All meta-analyses investigating hypercholesterolaemia showed significant increases in dementia risk. There was a paucity of research on the association between arterial stiffness and dementia risk. Conclusion: Targeted CVD dementia prevention strategies could reduce dementia prevalence. Future research should determine the underpinning mechanisms linking heart and brain health to determine the most effective strategies for dementia risk reduction in CVD populations.
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Academic engagement in recent years has become the focus of determining student learning and achievement. However,despite this growing awareness that has revolutionized academic policies and educational approaches, literature on engagement in the academic context is still in its infancy. This study seeks to remedy this through the confirmation of the Utrecht Work Engagement Scale for Students' (UWES-S) promising psychometric properties and by providing empirical evidence on the relationship between academic engagement, personality traits, and social media addiction, a determinant that has yet to be explored. Our findings indicate that of the five personality traits analyzed, agreeableness had the strongest negative correlation with academic engagement, and perhaps equally as striking is the positive, albeit insignificant, association between social media and academic engagement. Furthermore, the most informative and least informative items for academic engagement were identified using IRT analysis. Finally, this study also addresses several gaps in the literature by determining that the one-factor construct of the UWES-S is an adequate measure of academic engagement compared to its three-factor counterpart and by demonstrating the measurement invariance of the UWES-S across gender, class year, and academic major in our sample of Taiwanese undergraduates.
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INTRODUCTION: Hyperlipidaemia contributes a significant proportion of modifiable cardiovascular disease (CVD) risk, which is a condition that disproportionally affects disadvantaged socioeconomic communities, with death rates in the most deprived areas being four times higher than those in the least deprived. With the national CVD Prevention programme being delivered to minimise risk factors, no evidence is available on what has been implemented in primary care for deprived populations. This study describes the protocol for the development of a tailored intervention aiming to optimise lipid management in primary care settings to help reduce inequalities in CVD risks and improve outcomes in deprived communities. METHODS AND ANALYSIS: A mixed-methods approach will be employed consisting of four work packages: (1) rapid review and logic model; (2) assessment and comparison of CVD risk management for deprived with non-deprived populations in Northern England to England overall; (3) interviews with health professionals; and (4) intervention development. A systematic search and narrative synthesis will be undertaken to identify evidence-based interventions and targeted outcomes in deprived areas. General practice-level data will be assessed to establish the profile of lipid management, compared with the regional and national levels. Health professionals involved in the organisation and delivery of routine lipid management to deprived populations will be interviewed to understand the implementation and delivery of current lipid management and associated challenges. The prototype intervention will be informed by the evidence generated from workpackages 1-3, which will be reviewed and assessed using the nominal group technique to reach consensus. Training and skills development materials will also be developed as needed. ETHICS AND DISSEMINATION: Ethics approval has been obtained from the Faculty of Medical Sciences Research Ethics Committee at Newcastle University, UK. Findings will be disseminated to the participating sites, participants, commissioners, and in peer-reviewed journals and academic conferences.
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Enfermedades Cardiovasculares , Protocolos Clínicos , Enfermedades Cardiovasculares/prevención & control , Inglaterra , Humanos , Lípidos , Atención Primaria de Salud , Proyectos de Investigación , Gestión de RiesgosRESUMEN
BACKGROUND: Dementia is a major public health priority. Although there is abundant evidence of an association between dementia and poor cardiovascular health, findings have been inconsistent and uncertain in identifying which factors increase dementia risk in those with cardiovascular disease. Indeed, multiple variables including sociodemographic, economic, health, lifestyle and education may indicate who is at higher vs. lower dementia risk and could be used in prediction modelling. Therefore, the aim of this review is to synthesise evidence on the key risk factors for dementia in those with a history of cardiovascular disease. METHODS: This is an overview of reviews protocol, registered on PROSPERO (CRD42021265363). Four electronic databases including MEDLINE, EMBASE, PsycINFO, and the Cochrane Database of Systematic Reviews will be searched. Studies will be included if they are systematic reviews and/or meta-analyses that have investigated the risk of incident dementia (all-cause and subtypes including Alzheimer's disease and vascular dementia) in people with a history of coronary heart disease, heart failure, atrial fibrillation, hypertension, hyperlipidaemia, and vascular stiffness. Study selection will be completed by two independent researchers according to the eligibility criteria, and conflicts resolved by a third reviewer. References will be exported into Covidence for title and abstract sifting, full-text review, and data extraction. Methodological quality will be assessed using the AMSTAR-2 criteria and confidence of evidence will be assessed using the GRADE classification. This overview of reviews will follow PRISMA guidelines. If there is sufficient homogeneity in the data, the results will be pooled, and a meta-analysis conducted to determine the strength of association between each risk factor and incident all-cause dementia and its subtypes for each cardiovascular diagnoses separately. DISCUSSION: We will create a comprehensive summary of the key risk factors linking cardiovascular diseases to risk of incident dementia. This knowledge is essential for informing risk predictive model development as well as the development of risk reduction and prevention strategies.
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Enfermedad de Alzheimer , Enfermedades Cardiovasculares , Demencia Vascular , Enfermedad de Alzheimer/diagnóstico , Enfermedades Cardiovasculares/epidemiología , Enfermedades Cardiovasculares/etiología , Humanos , Metaanálisis como Asunto , Literatura de Revisión como Asunto , Factores de RiesgoRESUMEN
BACKGROUND: Although numerous studies have reported a decrease in dementia risk in the last two decades, it is unclear whether dementia-free cognitive function is also changing across generations. OBJECTIVE: The objective was to systematically evaluate the published data on generational differences in cognitive function in the older population. METHODS: Searches were performed on PubMed, Embase, and PsychInfo for articles published in English before 28 June 2021. Included studies were from population-based samples that reported generational differences in cognition in individuals without dementia, aged ≥60 years. RESULTS: 28,101 studies were identified and 15 selected covering the period from 1971 to 2015: including studies from China, Europe, and the USA. The results show generally consistent findings of improvements or stability in dementia free cognitive function in later versus earlier born generations, but not for all cognitive domains. Prevalence of mild cognitive impairment and cognitive impairment no dementia has remained stable in the USA, UK, and China over the last two decades. RESULTS: Prevalence of vascular related mild cognitive impairment has increased in China. Improvements in cognition may only partially be explained by increased educational attainment across generations. CONCLUSION: This review provides evidence for generational effects in dementia-free cognitive function, predominately stability or improvements in performance, in later compared to earlier born individuals across different world regions. There is an urgent need to determine the factors driving such changes and whether they are being experienced in all world regions, particularly low- and middle-income countries where the burden of cognitive impairment is greatest and rising.
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Cognición , Disfunción Cognitiva , Anciano , China/epidemiología , Disfunción Cognitiva/epidemiología , Europa (Continente) , Humanos , PrevalenciaRESUMEN
Cellular respiration is essential for multiple bacterial pathogens and a validated antibiotic target. In addition to driving oxidative phosphorylation, bacterial respiration has a variety of ancillary functions that obscure its contribution to pathogenesis. We find here that the intracellular pathogen Listeria monocytogenes encodes two respiratory pathways which are partially functionally redundant and indispensable for pathogenesis. Loss of respiration decreased NAD+ regeneration, but this could be specifically reversed by heterologous expression of a water-forming NADH oxidase (NOX). NOX expression fully rescued intracellular growth defects and increased L. monocytogenes loads >1000-fold in a mouse infection model. Consistent with NAD+ regeneration maintaining L. monocytogenes viability and enabling immune evasion, a respiration-deficient strain exhibited elevated bacteriolysis within the host cytosol and NOX expression rescued this phenotype. These studies show that NAD+ regeneration represents a major role of L. monocytogenes respiration and highlight the nuanced relationship between bacterial metabolism, physiology, and pathogenesis.
Cellular respiration is one of the main ways organisms make energy. It works by linking the oxidation of an electron donor (like sugar) to the reduction of an electron acceptor (like oxygen). Electrons pass between the two molecules along what is known as an 'electron transport chain'. This process generates a force that powers the production of adenosine triphosphate (ATP), a molecule that cells use to store energy. Respiration is a common way for cells to replenish their energy stores, but it is not the only way. A simpler process that does not require a separate electron acceptor or an electron transport chain is called fermentation. Many bacteria have the capacity to perform both respiration and fermentation and do so in a context-dependent manner. Research has shown that respiration can contribute to bacterial diseases, like tuberculosis and listeriosis (a disease caused by the foodborne pathogen Listeria monocytogenes). Indeed, some antibiotics even target bacterial respiration. Despite being often discussed in the context of generating ATP, respiration is also important for many other cellular processes, including maintaining the balance of reduced and oxidized nicotinamide adenine dinucleotide (NAD) cofactors. Because of these multiple functions, the exact role respiration plays in disease is unknown. To find out more, Rivera-Lugo, Deng et al. developed strains of the bacterial pathogen Listeria monocytogenes that lacked some of the genes used in respiration. The resulting bacteria were still able to produce energy, but they became much worse at infecting mammalian cells. The use of a genetic tool that restored the balance of reduced and oxidized NAD cofactors revived the ability of respiration-deficient L. monocytogenes to infect mammalian cells, indicating that this balance is what the bacterium requires to infect. Research into respiration tends to focus on its role in generating ATP. But these results show that for some bacteria, this might not be the most important part of the process. Understanding the other roles of respiration could change the way that researchers develop antibacterial drugs in the future. This in turn could help with the growing problem of antibiotic resistance.