Changes in physical activity and all-cause mortality in the oldest old population: Findings from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).

BACKGROUND: Insufficient or decreasing physical activity is common in older adults. Most studies on physical activity changes and mortality were conducted in adults younger than 80 years old in developed countries. We aimed to investigate the relationship between changes in physical activity and longevity in the oldest old (80 years or older) population using the Chinese Longitudinal Healthy Longevity Survey. METHODS: Participants aged 80 or older at baseline were categorized into four groups: 1) remaining physically inactive (n = 14,287), 2) remaining physically active (n = 5411), 3) shifting from being inactive to active (n = 1364), and 4) shifting from being active to inactive (n = 1401). We fitted accelerated failure time Weibull survival regression models, adjusting for baseline sociodemographics, lifestyle factors and disease status. We further examined whether the associations differed by subgroups. RESULTS: A total of 15,707 participants died during follow-up (median duration of follow-up = 3.0 years). Compared with participants who remained physically inactive, those who remained active (fully adjusted event time ratio (ETR): 1.14, 95%CI: 1.11-1.17) or shifted from being inactive to active (fully adjusted ETR: 1.14, 95%CI: 1.08-1.20) had statistically significant longer survival time. No significant association was observed between remaining physically inactive and shifting from being active to inactive. Subgroup analyses showed consistent associations in nearly all strata. CONCLUSION: Maintaining frequent physical activity or shifting from being physically inactive to active was consistently associated with longer survival time in the oldest old population. Our findings provide evidence for encouraging older adults to regularly engage in physical activity to gain longevity benefits.

An extensive benchmark study on biomedical text generation and mining with ChatGPT.

MOTIVATION: In recent years, the development of natural language process (NLP) technologies and deep learning hardware has led to significant improvement in large language models (LLMs). The ChatGPT, the state-of-the-art LLM built on GPT-3.5 and GPT-4, shows excellent capabilities in general language understanding and reasoning. Researchers also tested the GPTs on a variety of NLP-related tasks and benchmarks and got excellent results. With exciting performance on daily chat, researchers began to explore the capacity of ChatGPT on expertise that requires professional education for human and we are interested in the biomedical domain. RESULTS: To evaluate the performance of ChatGPT on biomedical-related tasks, this article presents a comprehensive benchmark study on the use of ChatGPT for biomedical corpus, including article abstracts, clinical trials description, biomedical questions, and so on. Typical NLP tasks like named entity recognization, relation extraction, sentence similarity, question and answering, and document classification are included. Overall, ChatGPT got a BLURB score of 58.50 while the state-of-the-art model had a score of 84.30. Through a series of experiments, we demonstrated the effectiveness and versatility of ChatGPT in biomedical text understanding, reasoning and generation, and the limitation of ChatGPT build on GPT-3.5. AVAILABILITY AND IMPLEMENTATION: All the datasets are available from BLURB benchmark https://microsoft.github.io/BLURB/index.html. The prompts are described in the article.

Evaluating the effectiveness and cost-effectiveness of free influenza vaccination policy for older adults in Yinzhou, China: Study protocol of a real-world analyses.

BACKGROUND: Influenza causes excessive morbidity and mortality among older adults. While influenza vaccine provides protection against its infection, the vaccination coverage in China among older adults has been very low. Previous evidence on the cost-effectiveness of government-sponsored free influenza vaccination programs in China was primarily based on literature data, which might not always reflect real-world patient populations. The Yinzhou Health Information System (YHIS) is a regional database that captures electronic health records, insurance claims data, etc. for all residents in Yinzhou district, Zhejiang province, China. We will use YHIS to study the effectiveness, influenza-related direct medical cost and cost-effectiveness analysis (CEA) of the free influenza vaccination program for older adults. In this paper, we describe the study design and innovations in detail. METHODS: We will establish a retrospective cohort of permanent older residents aged 65 and over, using YHIS between 2016 and 2021. We will estimate the vaccine coverage rate, influenza incidence rate and influenza-related direct medical cost from 2016 to 2021. Regression discontinuity will be used to estimate vaccine effectiveness for the 2020/2021 season. We will build a decision tree model to compare the cost-effectiveness of three influenza vaccination options (free trivalent influenza vaccine, free quadrivalent influenza vaccine, and no policy) from both societal and health system perspectives. Parameter inputs will be gathered from both YHIS and published literature. We will calculate the incremental cost-effectiveness ratio with cost and quality-adjusted life years (QALYs) discounted at 5 % annually. DISCUSSION: Our CEA solidifies multiple sources including regional real-world data and literature for a rigorous evaluation of the government-sponsored free influenza vaccination program. The results will provide real-world evidence from real-world data on the cost-effectiveness of a real-world policy. Our findings are expected to support evidence-based policy making and to promote health for older adults.

Pharmacophoric-constrained heterogeneous graph transformer model for molecular property prediction.

Informative representation of molecules is a crucial prerequisite in AI-driven drug design and discovery. Pharmacophore information including functional groups and chemical reactions can indicate molecular properties, which have not been fully exploited by prior atom-based molecular graph representation. To obtain a more informative representation of molecules for better molecule property prediction, we propose the Pharmacophoric-constrained Heterogeneous Graph Transformer (PharmHGT). We design a pharmacophoric-constrained multi-views molecular representation graph, enabling PharmHGT to extract vital chemical information from functional substructures and chemical reactions. With a carefully designed pharmacophoric-constrained multi-view molecular representation graph, PharmHGT can learn more chemical information from molecular functional substructures and chemical reaction information. Extensive downstream experiments prove that PharmHGT achieves remarkably superior performance over the state-of-the-art models the performance of our model is up to 1.55% in ROC-AUC and 0.272 in RMSE higher than the best baseline model) on molecular properties prediction. The ablation study and case study show that our proposed molecular graph representation method and heterogeneous graph transformer model can better capture the pharmacophoric structure and chemical information features. Further visualization studies also indicated a better representation capacity achieved by our model.

Machine learning-based prediction of infarct size in patients with ST-segment elevation myocardial infarction: A multi-center study.

BACKGROUND: Cardiac magnetic resonance imaging (CMR) is the gold standard for measuring infarct size (IS). However, this method is expensive and requires a specially trained technologist to administer. We therefore sought to quantify the IS using machine learning (ML) based analysis on clinical features, which is a convenient and cost-effective alternative to CMR. METHODS AND RESULTS: We included 315 STEMI patients with CMR examined one week after morbidity in final analysis. After feature selection by XGBoost on fifty-six clinical features, we used five ML algorithms (random forest (RF), light gradient boosting decision machine, deep forest, deep neural network, and stacking) to predict IS with 26 (selected by XGBoost with information gain greater than average level of 56 features) and the top 10 features, during which 5-fold cross-validation were used to train and optimize models. We then evaluated the value of actual and ML-IS for the prediction of adverse remodeling. Our finding indicates that MLs outperform the linear regression in predicting IS. Specifically, the RF with five predictors identified by the exhaustive method performed better than linear regression (LR) with 10 indicators (R2 of RF: 0.8; LR: 0). The finding also shows that both actual and ML-IS were independently associated with adverse remodeling. ML-IS ≥ 21% was associated with a twofold increase in the risk of LV remodeling (P < 0.01) compared with patients with reference IS (1st tertile). CONCLUSION: ML-based methods can predict IS with widely available clinical features, which provide a proof-of-concept tool to quantitatively assess acute phase IS.

Mediation analysis of leisure activities on the association between cognitive function and mortality: a longitudinal study of 42,942 Chinese adults 65 years and older.

OBJECTIVES: Previous studies have established associations of cognitive function and leisure activities with mortality. This study aimed to evaluate whether leisure activities causally mediate these associations. METHODS: This longitudinal study included 42,246 participants aged over 65 years from the Chinese Longitudinal Healthy Longevity Survey. The Mini-Mental State Examination and a self-reported scale were used to measure cognitive status and leisure activities, respectively. We examined the associations of cognitive function and leisure activities with mortality using Cox proportional hazards models. Causal mediation analysis was used to assess whether leisure activities mediated the association between cognitive function and mortality. RESULTS: Cognitive function and leisure activities were inversely associated with mortality. Leisure activities accounted for 28.3% (95% confidence interval [CI], 25.6 to 31.1) of the total effect of cognitive function and mortality. A higher mediated proportion (PM) was observed for physical leisure activities (PM, 20.1%; 95% CI, 18.0 to 22.3) than for social leisure activities (PM, 17.7%; 95% CI, 15.7 to 19.7). The mediating effect was higher among participants at younger ages (PM, 41.5%; 95% CI, 21.3 to 65.4), those with higher education levels (PM, 30.5%; 95% CI, 25.3 to 36.2), and residents of rural China (PM, 42.5%; 95% CI, 25.4 to 62.5). CONCLUSIONS: Cognitive function was associated with inverse mortality. Leisure activities significantly mediated this association. Participation in leisure activities at the early stages of mild cognitive impairment could reduce the risk of mortality, which has a major impact on interventional strategies for healthy aging.

Pre-Training of Equivariant Graph Matching Networks with Conformation Flexibility for Drug Binding.

The latest biological findings observe that the motionless "lock-and-key" theory is not generally applicable and that changes in atomic sites and binding pose can provide important information for understanding drug binding. However, the computational expenditure limits the growth of protein trajectory-related studies, thus hindering the possibility of supervised learning. A spatial-temporal pre-training method based on the modified equivariant graph matching networks, dubbed ProtMD which has two specially designed self-supervised learning tasks: atom-level prompt-based denoising generative task and conformation-level snapshot ordering task to seize the flexibility information inside molecular dynamics (MD) trajectories with very fine temporal resolutions is presented. The ProtMD can grant the encoder network the capacity to capture the time-dependent geometric mobility of conformations along MD trajectories. Two downstream tasks are chosen to verify the effectiveness of ProtMD through linear detection and task-specific fine-tuning. A huge improvement from current state-of-the-art methods, with a decrease of 4.3% in root mean square error for the binding affinity problem and an average increase of 13.8% in the area under receiver operating characteristic curve and the area under the precision-recall curve for the ligand efficacy problem is observed. The results demonstrate a strong correlation between the magnitude of conformation's motion in the 3D space and the strength with which the ligand binds with its receptor.

Aldehyde dehydrogenase 2 rs671 polymorphism and multiple diseases: protocol for a quantitative umbrella review of meta-analyses.

BACKGROUND: The mutant allele (*2) of aldehyde dehydrogenase type 2 (ALDH2) caused by a single nucleotide variant (rs671) inhibits enzymatic activity and is associated with multiple diseases. In recent years, an explosive number of original studies and meta-analyses have been conducted to examine the associations of ALDH2 rs671 polymorphism with diseases. Due to conflicting results, the overall associations of ALDH2 rs671 polymorphism and multiple diseases remain unclear. METHODS: A quantitative umbrella review will be conducted on meta-analyses of genetic association studies to examine the pleiotropic effects of ALDH2 rs671, mainly including cardio-cerebral vascular disease, diabetes mellitus, cancer, neurodegenerative disease, and alcohol-induced medical disease. A search of relevant literature according to comprehensive search strategies will be performed on studies published before July 1st, 2022 in PubMed, MEDLINE Ovid, Embase, Cochrane Database of Systematic Reviews, and Web of Science. Study selection, data extraction, methodology quality assessment, and strength of evidence assessment will be conducted by two reviewers independently and in duplicate. Included meta-analyses will be grouped by outcomes. Data conflicts and overlap between meta-analyses will be managed through updated standardized and customized methods including the calculation of CCA for study selection reference, application of Doi plots to assess small-study effects and others. Evidence from included meta-analyses will be quantitatively synthesized by overlap-corrected analyses and meta-analysis using primary studies. DISCUSSION: This umbrella review is expected to generate systematic evidence on the association between ALDH2 rs671 and diseases. Specific approaches were developed to address key challenges in conducting an umbrella review, including assessment tools of methodology and evidence quality of meta-analyses, methods to manage overlap between meta-analyses, a "stop-light" plot to summarize key findings. These approaches provide applicable methods for future umbrella reviews of meta-analyses on genetic association studies. TRIAL REGISTRATION: CRD42021223812.

The association between self-rated health and all-cause mortality and explanatory factors in China's oldest-old population.

Background: Self-rated health (SRH) is considered a condensed summary of information about bodily conditions that involves people's biological, cognitive, and cultural status, but has been under-studied in the oldest old population. This study aimed to investigate the association between SRH and all-cause mortality among the oldest-old population in China and to explore potential explanatory factors in this association. Methods: The study was based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 1998 to 2018 and included 30 222 participants aged 80 years or older (ie, the oldest old) in the analysis. We used Cox models to assess the association between SRH and mortality in this population and its subgroups, and used the Percentage Excess Risk Mediated approach to identify potential contributing factors. Results: After adjustment of confounders, people with "good" "neutral", and "bad/very bad" SRH were significantly associated with 8% (95% confidence interval (CI) = 3%-13%), 23% (95% CI = 18%-29%), and 52% (95% CI = 44%-61%) higher hazard of mortality respectively, compared with those with "very good" SRH. The significant SRH-mortality associations were exclusive to men and those with at least primary education. The adjustment of "regular physical activity", "leisure activity", "activities of daily living (ADL)", and "cognitive function" all led to noticeable attenuation to the SRH-mortality association, with "leisure activity" causing the most attenuation (64.9%) in the "Good SRH" group. Conclusions: Self-rated health is significantly associated with all-cause mortality among the oldest old population in China, particularly among men and the educated, and is considerably explained by regular physical activity, leisure activity, ADL, and cognitive function. We advocate the use of SRH as a simple and efficient tool in research and (potentially) health care practices.

Healthy eating and all-cause mortality among Chinese aged 80 years or older.

BACKGROUND: There is little evidence of the influence of dietary patterns on mortality risk among adults 80 years or older ("oldest-old"). We evaluated the association between the Simplified Healthy Eating index (SHE-index) and mortality among Chinese oldest-old. METHODS: Population-based cohort study from the Chinese Longitudinal Healthy Longevity Survey (CLHLS 1998-2014, n = 35 927), conducted in 22 Chinese provinces, were pooled for analysis. The first seven waves of the CLHLS (1998, 2000, 2002, 2005, 2008-09, 2011-12, and 2013-2014) were utilized, with follow-up to the last wave (2018) (range 0-21 years). The SHE-index was collected in each wave, and was constructed from intake frequency of nine dietary variables, with a higher score indicating better diet quality. Cox proportional hazards model with dietary patterns as a time-varying exposure was employed to analyze the relationship between SHE-index and mortality. RESULTS: At baseline, the median age of all participants was 92 years (25th percentile, 85 years; 75th percentile, 100 years). In multivariable models, the hazard ratios (95% confidence intervals) for SHE-index quartile 2, quartile 3 and quartile 4 versus quartile1 were 0.91 (0.88, 0.93), 0.89 (0.86, 0.92) and 0.82 (0.78, 0.85), respectively. Results were generally consistent for men and women and in a large number of sensitivity analyses. CONCLUSIONS: Healthier eating patterns were associated with a significant reduction in the risk of all-cause mortality among Chinese oldest-old, lending support to the importance of life-long adherence to healthy diet into advanced old age.

Retinal microvascular changes in white matter hyperintensities investigated by swept source optical coherence tomography angiography.

BACKGRO: To assess the microvascular changes in the macular region and the foveal avascular zone (FAZ) area in participants with white matter hyperintensities (WMHs) using swept source optical coherence tomography angiography (SS OCTA). METHODS: This cross-sectional study included a total of 23 WMH participants (45 eyes) and 20 age-matched healthy participants (40 eyes). SS OCTA (VG200; SVision Imaging, Ltd., Luoyang, China) was used to assess the retinal vessel density (VD) and the FAZ area. VD was measured in the superficial vascular plexus (SVP), intermediate capillary plexus (ICP) and deep capillary plexus (DCP) within a 6 × 6-mm scan centred on the macula using a 5-mm Macula circle. The FAZ area was automatically measured on the inner retina layer within a 3 × 3-mm scan in the macular region. RESULTS: There was no significant difference in VD in the SVP between the two groups. However, VD in both the ICP and DCP was significantly decreased in WMH participants (P = 0.028, P = 0.016). The FAZ area was significantly enlarged in WMH participants (P = 0.030). The signal quality was significantly lower in WMH participants (P < 0.001). CONCLUSIONS: This study suggested that WMH participants have retinal microvascular and foveal avascular zone area changes compared with healthy controls. Further longitudinal studies with larger sample sizes are warranted to identify the value of our findings in the early evaluation of WMHs.

Association between indoor ventilation frequency and cognitive function among community-dwelling older adults in China: results from the Chinese longitudinal healthy longevity survey.

BACKGROUNDS: Emerging evidence suggested that indoor air pollution caused long-term adverse effects on cognitive function among older adults who spend more than 85% of their time indoors. Although high indoor ventilation can mitigate the effect of indoor air pollution on cognition among the younger population, limited evidence revealed the association between indoor ventilation and cognition among older adults. METHODS: A total of 11,853 participants aged 65 and over (female, 54.5%; mean age, 83.6 years) were included from the 2017-2018 wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Indoor ventilation frequency was measured by the self-reported frequency of opening windows per week in each season. Cognitive function was evaluated by the Mini-Mental State Examination (MMSE). Multivariate Poisson regression with robust error variance was applied to assess the association between overall indoor ventilation frequency and cognitive function. We fitted in two adjusted models: Model 1 was adjusted for demographic; model 2 was further adjusted for lifestyle, socioeconomic status, health conditions, and environmental factors. The same models were also applied to measure the association between seasonal indoor ventilation frequency and cognitive function. RESULTS: Of 11,853 older adults, 3035 (25.6%) had cognitive impairment. A high overall indoor ventilation frequency (indoor ventilation frequency: 6-8) was significantly associated with a 9% lower likelihood of cognitive impairment than low overall indoor ventilation frequency (indoor ventilation frequency: 0-3) among Chinese older adults [Relative risk (RR): 0.91, 95% Confidential Interval (CI): 0.83-0.99] in the full adjusted model. In the subgroup analysis in four seasons, high and intermediate indoor ventilation frequency in winter were significantly associated with 8% (RR: 0.92; 95%CI: 0.86-0.99) and 16% (RR: 0.84; 95%CI: 0.78-0.90) lower probability of cognitive impairment than low indoor ventilation frequency in the fully adjusted model among Chinese older adults, respectively. CONCLUSIONS: In this nationally representative cohort, a higher frequency of house ventilation by opening windows was significantly associated with a lower risk of cognitive impairment among Chinese older adults aged 65 and over. These results offered robust evidence for policymaking and health intervention to prevent older adults from cognitive impairment or dementia in developing regions.

A Machine Learning-Based Aging Measure Among Middle-Aged and Older Chinese Adults: The China Health and Retirement Longitudinal Study.

Objective: Biological age (BA) has been accepted as a more accurate proxy of aging than chronological age (CA). This study aimed to use machine learning (ML) algorithms to estimate BA in the Chinese population. Materials and methods: We used data from 9,771 middle-aged and older Chinese adults (≥45 years) in the 2011/2012 wave of the China Health and Retirement Longitudinal Study and followed until 2018. We used several ML algorithms (e.g., Gradient Boosting Regressor, Random Forest, CatBoost Regressor, and Support Vector Machine) to develop new measures of biological aging (ML-BAs) based on physiological biomarkers. R-squared value and mean absolute error (MAE) were used to determine the optimal performance of these ML-BAs. We used logistic regression models to examine the associations of the best ML-BA and a conventional aging measure-Klemera and Doubal method-BA (KDM-BA) we previously developed-with physical disability and mortality, respectively. Results: The Gradient Boosting Regression model performed the best, resulting in an ML-BA with an R-squared value of 0.270 and an MAE of 6.519. This ML-BA was significantly associated with disability in basic activities of daily living, instrumental activities of daily living, lower extremity mobility, and upper extremity mobility, and mortality, with odds ratios ranging from 1 to 7% (per 1-year increment in ML-BA, all P < 0.001), independent of CA. These associations were generally comparable to that of KDM-BA. Conclusion: This study provides a valid ML-based measure of biological aging for middle-aged and older Chinese adults. These findings support the application of ML in geroscience research and may help facilitate preventive and geroprotector intervention studies.

Cognitive impairment and all-cause mortality among Chinese adults aged 80 years or older.

OBJECTIVES: The oldest-old (aged ≥80 years) are the fastest growing population segment and age is related to cognitive impairment. We aimed to estimate the association between cognitive impairment and all-cause mortality, in addition to the relationship with different cognitive subdomains among the oldest-old in China. METHODS: We analyzed 25,285 participants recruited from 22 out of 30 provinces in the Chinese Longitudinal Healthy Longevity Survey (CLHLS) from 1998 to 2008, with mortality follow-up until 2014. Cognitive function was measured by the Chinese-version 30-item Mini-Mental State Examination (MMSE), classified as no (MMSE score: 25-30), mild (18-24), moderate (10-17), and severe (0-9) impairment. We used time-dependent Cox model to evaluate the relationship between time-varying cognition and mortality. RESULTS: The relationship between cognition and mortality showed a dose-response pattern among the overall population. Compared to those with no impairment, participants with moderate (HR = 1.41, 95% CI 1.28-1.56) and severe (HR = 1.77, 95% CI 1.59-1.96) cognitive impairment showed increased mortality risk. Impairment in the subdomain of orientation was independently associated with increased mortality risk (HR = 1.20, 95% CI 1.05-1.36) among participants without overall cognitive impairment. Urban and rural residents had similar mortality risk. CONCLUSIONS: A consistent dose-response pattern existed between cognitive impairment and all-cause mortality. Orientation was associated with mortality in the population without cognitive impairment. Similar mortality regardless of residence areas indicated scarce health care and treatment for cognitive impairment in China from 1998 to 2014.

Association between body mass index, its change and cognitive impairment among Chinese older adults: a community-based, 9-year prospective cohort study.

To examine the association of baseline body mass index (BMI) and BMI change with cognitive impairment among older adults in China. The study included data from the Chinese Longitudinal Healthy Longevity Study, a national community-based prospective cohort study from 2002 to 2018. Baseline BMI and BMI change were available for 12,027 adults aged older than 65 years. Cognitive impairment was defined as Chinese version of the Mini Mental State Examination score lower than 18. Multivariable Cox proportional hazard model was used. Among 12,027 participants (mean age was 81.23 years old and 47.48% were male), the proportion of underweight, normal, overweight and obese at baseline was 33.87%, 51.39%, 11.39% and 3.34%, respectively. During an average of 5.9 years' follow-up, 3086 participants (4.35 per 100 person-years) with incident cognitive impairment were identified. Compared with normal weight group, adjusted hazard ratio (AHR) for cognitive impairment was 0.86 (95% CI 0.75-0.99) among overweight group, whereas corresponding AHR was 1.02 (95% CI 0.94-1.10) in underweight and 1.01 (95% CI 0.80-1.28) in obese participants. Large weight loss (< -10%) was significantly associated with an increased risk of cognitive impairment (AHR, 1.42, 95% CI 1.29-1.56), compared to stable weight status group (-5% ~ 5%). In the restricted cubic spline models, BMI change showed a reverse J-shaped association with cognitive impairment. BMI-defined overweight, but not obesity, was associated with a lower risk of cognitive impairment among elderly Chinese adults, while large weight loss was associated with an increased risk. These findings are consistent with weight loss in the prodromal phase of dementia.

Apolipoprotein E Genotype, Meat, Fish, and Egg Intake in Relation to Mortality Among Older Adults: A Longitudinal Analysis in China.

Introduction: The interactions between apolipoprotein E (APOE) genotype and diet pattern changes were found significant in several trials, implying that APOE gene may modify the effect of animal protein-rich food on health outcomes. We aim to study the interaction of APOE genotype with the effect of meat, fish and egg intake on mortality. Methods: This population-based study enrolled 8,506 older adults (mean age: 81.7 years, 52.3% female) from the Chinese Longitudinal Healthy Longevity Study. The intake frequency of meat, fish and egg was assessed by 3-point questions at baseline. Cox regression was conducted to calculate the hazard ratios for all-cause mortality of intake levels of meat, fish and egg. The analyses were stratified by APOE genotype and sex. The analyses were performed in 2020. Results: In the multivariable-adjusted models, meat and fish intake was associated with all-cause mortality (high vs. low intake: meat: HR: 1.14, 95% CI: 1.01, 1.28; fish: HR: 0.83, 95% CI: 0.73, 0.95). APOE genotype have significant interactions with meat and fish intake (Ps < 0.05). Compared with low fish intake, high fish intake was associated with lower risk of mortality (HR: 0.74, 95% CI: 0.56-0.98) only among the APOE ε4 carriers. High meat intake was significantly associated with higher risks of mortality (HR: 1.13, 95% CI: 1.04-1.25) only among the APOE ε4 non-carriers. The interactive relationship was restricted among the male. No significant findings were observed between egg and mortality among carriers or non-carriers. Conclusions: Among Chinese older adults, the significance of associations of mortality with reported meat or fish intake depended on APOE-E4 carriage status. If validated by other studies, our findings provide evidence for gene-based "precision" lifestyle recommendations.

HeTDR: Drug repositioning based on heterogeneous networks and text mining.

Using existing knowledge to carry out drug-disease associations prediction is a vital method for drug repositioning. However, effectively fusing the biomedical text and biological network information is one of the great challenges for most current drug repositioning methods. In this study, we propose a drug repositioning method based on heterogeneous networks and text mining (HeTDR). This model can combine drug features from multiple drug-related networks, disease features from biomedical corpora with the known drug-disease associations network to predict the correlation scores between drug and disease. Experiments demonstrate that HeTDR has excellent performance that is superior to that of state-of-the-art models. We present the top 10 novel HeTDR-predicted approved drugs for five diseases and prove our model is capable of discovering potential candidate drugs for disease indications.

Interaction of greenness and polygenic risk score of Alzheimer's disease on risk of cognitive impairment.

Studies have shown contact with nature has positive psychological, neurological, and cognitive benefits. Whether the built environment can affect genetic predisposition of Alzheimer's disease (AD) should be explored. We aimed to examine whether greenness around the residential environment can modify the effect of genetic AD risk on cognitive function. We used a genetic sub-study of the Chinese Longitudinal Healthy Longevity Survey including 1199 older adults (mean age: 100.3 ± 3.4 years) aged 90 years old or older. We used Polygenic Risk Score (PRS) to quantify the genetic AD risk and two types of measurements based on Normalized Difference Vegetation Index (NDVI) to access the residential greenness (contemporaneous and annual average NDVI). Contemporaneous NDVI values were the NDVI value collected at the corresponding survey, and the annual average NDVI was the average value of NDVI during the year before the corresponding survey. We defined cognitive impairment as having a Mini-Mental State Examination score below 25. In the multivariable logistics regression models, contemporaneous NDVI and genetic AD risk were associated with cognitive impairment. Among those with low genetic AD risk, the risk of cognitive impairment was lower in those living around higher greenness (contemporaneous NDVI OR: 0.55, 95% CI: [0.34, 0.86]; Pinteraction: 0.071; annual average NDVI OR: 0.49, 95% CI: [0.31, 0.79]; Pinteraction: 0.040). We did not observe significant associations between greenness and cognitive impairment among those with high genetic AD risk. Prevention efforts using PRS warrant a higher granularity of environmental exposures and biological etiology data.

Changes in Levels and Determinants of Maternal Health Service Utilization in Ethiopia: Comparative Analysis of Two Rounds Ethiopian Demographic and Health Surveys.

BACKGROUND: Antenatal care (ANC), delivery by skilled birth attendants, and postnatal care (PNC) are critical components of maternal health services for reducing maternal mortality. The study aimed to compare the utilization of maternal health services in the two most recent rounds of Ethiopia Demographic and Health Surveys (EDHS) and identify the factors influencing the utilization of these services using the 2016 EDHS. METHODS: Two rounds of EDHS data in 2011 and 2016 were used to estimate the proportion of women who had ANC, delivered by skilled birth attendants, and had a postnatal checkup and other characteristics of the surveyed population. The most recent round of data-the 2016 EDHS-was used to examine the socio-cultural and reproductive health factors associated with the three maternal health services utilization. Chi-square tests and multivariate logistic regression analyses with adjusted Odds Ratios (AOR) were conducted using Stata 15.0. RESULTS: The use of ANC services and skilled birth attendants increased significantly between 2011 and 2016 EDHS, utilization of ANC services increased from 34.0 to 65.5%, and use of skilled birth attendants increased from 11.7 to 35.9%, respectively. The use of postnatal care decreased from 9.3 to 6.9%. Utilization of maternal health service was significantly associated with urban residence, Protestant religion, Oromo ethnicity, more education, more household wealth, and less parity. Furthermore, women who had ANC visits during pregnancy were more likely to subsequently use skilled birth attendants (AOR 5.5, p < 0.001) and PNC (AOR 2.9, p < 0.001). CONCLUSION: The study highlighted the inequalities in the utilization of maternal health services between rural and urban areas, and the need of addressing the social, economic, and physical barriers that prevent women from using these services. Further, programs should be targeted at promoting the use of professional birth and postnatal services in Ethiopia.

Association of APOE ε4 genotype and lifestyle with cognitive function among Chinese adults aged 80 years and older: A cross-sectional study.

BACKGROUND: Apolipoprotein E (APOE) ε4 is the single most important genetic risk factor for cognitive impairment and Alzheimer disease (AD), while lifestyle factors such as smoking, drinking, diet, and physical activity also have impact on cognition. The goal of the study is to investigate whether the association between lifestyle and cognition varies by APOE genotype among the oldest old. METHODS AND FINDINGS: We used the cross-sectional data including 6,160 oldest old (aged 80 years old or older) from the genetic substudy of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) which is a national wide cohort study that began in 1998 with follow-up surveys every 2-3 years. Cognitive impairment was defined as a Mini-Mental State Examination (MMSE) score less than 18. Healthy lifestyle profile was classified into 3 groups by a composite measure including smoking, alcohol consumption, dietary pattern, physical activity, and body weight. APOE genotype was categorized as APOE ε4 carriers versus noncarriers. We examined the associations of cognitive impairment with lifestyle profile and APOE genotype using multivariable logistic regressions, controlling for age, sex, education, marital status, residence, disability, and numbers of chronic conditions. The mean age of our study sample was 90.1 (standard deviation [SD], 7.2) years (range 80-113); 57.6% were women, and 17.5% were APOE ε4 carriers. The mean MMSE score was 21.4 (SD: 9.2), and 25.0% had cognitive impairment. Compared with those with an unhealthy lifestyle, participants with intermediate and healthy lifestyle profiles were associated with 28% (95% confidence interval [CI]: 16%-38%, P < 0.001) and 55% (95% CI: 44%-64%, P < 0.001) lower adjusted odds of cognitive impairment. Carrying the APOE ε4 allele was associated with 17% higher odds (95% CI: 1%-31%, P = 0.042) of being cognitively impaired in the adjusted model. The association between lifestyle profiles and cognitive function did not vary significantly by APOE ε4 genotype (noncarriers: 0.47 [0.37-0.60] healthy versus unhealthy; carriers: 0.33 [0.18-0.58], P for interaction = 0.30). The main limitation was the lifestyle measurements were self-reported and were nonspecific. Generalizability of the findings is another limitation because the study sample was from the oldest old in China, with unique characteristics such as low body weight compared to populations in high-income countries. CONCLUSIONS: In this study, we observed that healthier lifestyle was associated with better cognitive function among the oldest old regardless of APOE genotype. Our findings may inform the cognitive outlook for those oldest old with high genetic risk of cognitive impairment.