Communications health最新文献

{"title":"Adverse childhood experiences, early menopause, cognition, and dementia in older adults in the United States.","authors":"Miharu Nakanishi, Jordan DeVylder, Gemma Knowles, Masato Hasegawa, Marcus Richards, Atsushi Nishida","doi":"10.1038/s44528-026-00003-8","DOIUrl":"10.1038/s44528-026-00003-8","url":null,"abstract":"<p><strong>Background: </strong>Adverse childhood experiences (ACEs) may accelerate early menopause and influence neurodegenerative processes, contributing to sex-specific dementia risk. This study examined associations with cognitive decline and incident dementia in ACEs and early menopause.</p><p><strong>Methods: </strong>We studied 6093 women and 5784 men aged ≥50 years from the Health and Retirement Study, a US cohort spanning between 2010 and 2022. Incident dementia was based on self-report of physician-diagnosed dementia. Cognition was measured using a composite score of immediate and delayed recall, serial sevens subtraction, and counting backwards (range, 0-27). ACEs were assessed using seven items and classified into none, 1, 2, and ≥3 ACEs. Age at menopause was classified into <47, 47 to 52, and ≥53 years. We included men and defined the four categories of sex and age at menopause, assessing varying levels of female hormones with age at menopause serving as the proxy indicator of those differences. Covariates included lifestyle risk factors for dementia. We used a longitudinal panel design with each observation containing baseline covariates and 2-year follow-up outcomes. We applied a random-effects model to survival analysis for incident dementia and to linear regression analysis for cognition.</p><p><strong>Results: </strong>Here we show that experiencing 2 (hazard ratio: 1.32 [95% CI: 1.07-1.62]) or ≥3 ACEs (1.32 [1.03-1.68]) is associated with higher dementia risk compared with no ACEs. Dementia risk does not differ by sex and age at menopause in women. Women with early menopause (<i>β</i> = -0.22 [95%CI: -0.41 to -0.03]) and men (-0.92 [-1.06 to -0.78]) have worse cognition than women with late menopause. ACE level is not associated with cognition. No mediation by early menopause is observed between multiple ACEs, dementia, or cognition in women.</p><p><strong>Conclusions: </strong>Mechanisms linking ACEs and early menopause to dementia risk may differ. Risk reduction strategies should consider preventing and addressing ACEs and early menopause, respectively.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"3"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148428542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Population-based cohort study of modifiable risk factors for dementia and Alzheimer disease mortality in Spain.","authors":"Julián Benito-León, José Ignacio Serrano, María Dolores Del Castillo, Álex Escolà-Gascón, Carla María Benito-Rodríguez, Cristina Ramo-Tello, Ritwik Ghosh, Félix Bermejo-Pareja","doi":"10.1038/s44528-026-00022-5","DOIUrl":"10.1038/s44528-026-00022-5","url":null,"abstract":"<p><strong>Background: </strong>Although many modifiable factors are linked to dementia risk, their association with dementia and Alzheimer disease (AD) mortality remains unclear. We aimed to identify late-life modifiable factors associated with these outcomes and assess sex differences.</p><p><strong>Methods: </strong>In the population-based Neurological Disorders in Central Spain (NEDICES) cohort, we followed 3085 older adults enrolled in 1994-1995 through 2017. We examined 13 modifiable factors measured at study entry. Dementia and AD deaths were defined by the underlying cause recorded on death certificates. Fine-Gray competing risk models accounted for death from other causes and generated subdistribution hazard ratio (SHR) estimates and adjusted population attributable fractions (PAFs).</p><p><strong>Results: </strong>During follow-up, there were 182 dementia-coded deaths (including 105 AD-coded deaths) and 2423 deaths from other causes. Here we show that depressive symptoms are associated with higher dementia-coded mortality in women (SHR 1.52, 95% confidence interval [CI] 1.00-2.30; PAF 13.6%, 95% CI 0.0-28.4) and higher AD-coded mortality overall (SHR 1.76, 95% CI 1.11-2.79; PAF 15.4%, 95% CI 2.6-29.9), with a stronger association in women (SHR 2.23, 95% CI 1.28-3.88; PAF 27.2%, 95% CI 7.8-46.7). Several exposures show inverse associations (e.g., smoking, obesity, and arterial hypertension in men), consistent with competing mortality and late-life reverse causation. Combined positive PAFs are 10.8% for dementia-coded mortality and 18.2% for AD-coded mortality overall, reaching 41.1% in women for AD-coded mortality.</p><p><strong>Conclusions: </strong>Late-life depressive symptoms, particularly among women, emerged as the most prominent modifiable correlate of dementia- and AD-coded mortality, supporting improved recognition and management of depressive symptoms in older adults.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"26"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13585118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148993687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Practical considerations for social determinant-based disease prediction in the All of Us research program.","authors":"Micah R Hysong, Alisa K Manning, Michael D Green, Iain R Konigsberg, Luciana B Vargas, Jayati Sharma, Leslie Lange, Megan M Shuey, LáShauntá M Glover, Genevieve L Wojcik, Sandra Lee, Laura M Raffield, Sara J Cromer","doi":"10.1038/s44528-026-00018-1","DOIUrl":"10.1038/s44528-026-00018-1","url":null,"abstract":"<p><strong>Background: </strong>Growing recognition that social determinants of health (SDoH) strongly influence health outcomes has expanded their inclusion in biomedical research, underscoring the need to evaluate how best to incorporate these data into disease prediction models.</p><p><strong>Methods: </strong>The <i>All of Us (AoU) Research Program</i> is a large, diverse biomedical research dataset that includes participants from across the United States and links electronic health records (EHRs) with extensive survey data covering a wide range of health, lifestyle, and social factors. We assessed selection bias in the SDoH surveys by comparing demographic characteristics across cohorts with varying EHR and survey completion requirements. We additionally used a series of logistic regression models to evaluate the predictive utility of SDoH for nine chronic conditions, compared these results to models using only socioeconomic status (SES), self-reported race and ethnicity, or additional area-level SDoH factors, and discussed the associated trade-offs.</p><p><strong>Results: </strong>Here we show that requiring sufficient individual-level SDoH survey data results in significant selection bias and sample reduction in AoU. We also show that SES alone captures a substantial proportion of the predictive signal from individual-level SDoH data while preserving sample size and mitigating selection bias. Moreover, SES measures provide greater predictive utility than self-reported race and ethnicity, without excluding underrepresented groups. We find disease-specific patterns of association with SDoH and that area-level SDoH metrics contribute to disease prediction independently of individual-level measures.</p><p><strong>Conclusions: </strong>Altogether, we emphasize key analytical considerations and disease-specific trade-offs for the integration of SDoH data into disease prediction models in AoU and similar cohorts.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"17"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13447101/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148690733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health inequalities in infectious disease modelling.","authors":"Rosalind M Eggo, Alexis Robert, Kamlesh Khunti, Hannah E Clapham","doi":"10.1038/s44528-026-00011-8","DOIUrl":"10.1038/s44528-026-00011-8","url":null,"abstract":"<p><p>Infectious disease transmission is unequal, with some groups experiencing long-standing higher burdens of infection and disease. Here, we discuss the urgent need for the field of transmission modelling to develop methods, collaborations and understanding of the drivers and dynamics of infectious disease inequalities to support policymaking that aims to mitigate inequalities.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"5"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347796/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148428625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Longitudinal assessment of physiological and mental health changes following acute COVID-19 in Uganda.","authors":"Jennifer A Rooney, Ashley Sharma, Faustine Ceasor, Sara R Schenkel, Andrew Mutekanga, Peter D Jackson, Olive Kabajaasi, Matthew O Wiens, Patricia L Hibberd, D K Arvind, Cathryn Tonne, William Worodria, Peter P Moschovis","doi":"10.1038/s44528-026-00024-3","DOIUrl":"https://doi.org/10.1038/s44528-026-00024-3","url":null,"abstract":"<p><strong>Background: </strong>Recovery following acute COVID-19 varies widely, yet early recovery patterns remain understudied in Africa. Given the high burden of post-infection morbidity in resource-limited settings, there is a need to characterize recovery trajectories and identify those at risk for delayed recovery.</p><p><strong>Methods: </strong>We enrolled 151 adults between July 2021 and July 2022 with confirmed SARS-CoV-2 infection from healthcare facilities in Uganda and followed them for 12 weeks. Outcomes included pulmonary function, exercise capacity, symptom burden, and mental health, and were analyzed descriptively and using mixed-effects models.</p><p><strong>Results: </strong>Participants with severe acute COVID-19 had the greatest impairments during recovery. At 12 weeks, forced expiratory volume in 1 second (FEV1), diffusing capacity of the lungs for carbon monoxide (DLCO), and six-minute walk distance remained lower in severe versus mild cases (mean (SD): 98.45 (22.22) vs 105.26 (12.29); 78.99 (18.83) vs 107.72 (20.44); 409.28 (71.18) vs 506.82 (70.87)), consistent with adjusted models showing lower FEV1 (β = -13.10, 95% CI: -24.13, -2.07), DLCO (β = -40.75, 95% CI: -53.84, -27.66), and six-minute walk distance (β = -95.87, 95% CI: -136.66, -55.08). Continued COVID-19 and mental health symptoms were reported across all groups; mild cases had worse mental health scores (23.19 (12.65) vs 16.95 (13.98)), while severe cases had a broader range of persistent symptoms, including fatigue, breathlessness, and cognitive complaints.</p><p><strong>Conclusions: </strong>In this longitudinal study in Uganda, COVID-19 was associated with persistent physiological and psychosocial impacts, particularly among those with severe illness. Initial severity may help identify individuals at risk for delayed recovery and guide targeted post-COVID care in resource-limited settings.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"32"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13630552/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149122983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting multimorbidity in aging people with HIV using a microsimulation model.","authors":"Viviane D Lima, Jielin Zhu, Tian Shen, Jason Trigg, Silvia Guillemi, Robert S Hogg, Kate A Salters, Julio S G Montaner","doi":"10.1038/s44528-026-00004-7","DOIUrl":"10.1038/s44528-026-00004-7","url":null,"abstract":"<p><strong>Background: </strong>While life expectancy has significantly increased among people living with HIV (PLWH) due to effective antiretroviral therapy, aging-related non-communicable diseases and multimorbidity have emerged as critical challenges. Understanding the evolving health needs of PLWH is essential to guiding healthcare planning and interventions.</p><p><strong>Methods: </strong>We developed a new microsimulation model that integrates longitudinal clinical and administrative data to project the health trajectories of PLWH in British Columbia from 2019 to 2034. High prevalence conditions, such as cardiovascular disease (CVD), non-AIDS-related cancers, chronic liver disease (CLD), hypertension, chronic obstructive pulmonary disease (COPD), and mood and anxiety disorders (MANX), were included in the model. Results were stratified by age and sex.</p><p><strong>Results: </strong>Here we show that by 2034, nearly half of PLWH will be aged 60 years or older, and more than one-quarter will live with at least three additional chronic conditions. CVD is projected to nearly double (8.4-14.8%), cancers to rise from 8.9 to 17.2%, while MANX will remain the most common comorbidity, affecting about half of PLWH. Sex differences are pronounced; females show higher rates of multimorbidity involving MANX, CLD, and COPD, whereas males show higher prevalence of non-AIDS-related cancers and CVD.</p><p><strong>Conclusions: </strong>These findings highlight the urgency of preparing for a sharp increase in multimorbidity and demonstrate the value of forecasting tools to guide integrated models of care for aging PLWH.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"7"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13347798/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148428620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How understanding the diversity of perspectives and systems in governments can increase the impact of scientific research.","authors":"Liza Hadley, Slimane Ben Miled, Hannah E Clapham, Bimandra A Djaafara, Louise Dyson, Sebastian Funk, Julia R Gog, Hans Heesterbeek, Edward M Hill, Emily Howerton, Valerie Isham, Amira Kebir, Matt Keeling, Stephen M Kissler, Justin Lessler, Kathy Leung, Emma McBryde, James M McCaw, Chris Erwin G Mercado, Denis Mollison, S M Thumbi, Wirichada Pan-Ngum, Lorenzo Pellis, Francisco J Pérez-Reche, Michael J Plank, Robin N Thompson, Cécile Tran-Kiem","doi":"10.1038/s44528-026-00009-2","DOIUrl":"10.1038/s44528-026-00009-2","url":null,"abstract":"<p><p>The COVID-19 crisis required scientists worldwide to contribute to complex, hectic, and unfamiliar governmental decision-processes. In this Perspective, we reflect on this intense interaction between science and health policy for pandemic response, drawing from the experience of infectious disease modellers across the world. We highlight the diversity of actors and interests in government, aiming to demystify the elusive 'policy makers'. We present a general taxonomy to help research scientists more effectively support evidence-based policy. We stress the importance of building and maintaining relationships appropriate to the diverse pool of government actors. Not recognising this diversity may lead to miscommunication and reduce the positive impacts of scientific evidence for public policy in crisis and non-crisis situations.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"13"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13391366/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148582101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural fragility in digital public health communication.","authors":"Miao Feng, Zizi Papacharissi, Chandler C Carter, Mateusz Borowiecki, Simon Page, Ganna Kostygina, Natalie Wang, Yoonsang Kim, Brandon Sepulvado, Sherry L Emery","doi":"10.1038/s44528-026-00037-y","DOIUrl":"10.1038/s44528-026-00037-y","url":null,"abstract":"<p><strong>Background: </strong>Digital public health campaigns often report robust reach and engagement metrics, yet these metrics obscure deeper structural vulnerabilities. We define structural fragility as the declining capacity of actors to maintain network visibility in competitive digital communication environments, and assess it in Twitter/X discourse on U.S. e-cigarette prevention (2014-2023).</p><p><strong>Methods: </strong>Accounts were classified into five categories (Health, Commercial, Vape Community, Organic, Other). Longitudinal network analysis tracked three dimensions of structural fragility: positional (amplification and centrality), community (fragmentation and homophily), and core (k-core presence). Annual directed retweet networks were constructed, and modularity, in-degree, PageRank, eigenvector centrality, and k-core composition were computed. Regression models were adjusted for the number of participating accounts.</p><p><strong>Results: </strong>Here we show the network contracted from 36,204 accounts in 2014 to 800 in 2022, a 97.8% reduction. It fragmented into increasingly homophilous clusters (modularity 0.16 to 0.81; within-category retweeting 6.7% to 42.6%). Health accounts fell from 59.1% of the deepest k-core in 2014 to 3.8% in 2015, as Vape Community accounts rose to 78.8%. Per-capita amplification declined 95.7%, and Health PageRank share fell from 0.41 to 0.34, with amplification concentrated among a few accounts (eigenvector Gini ≥ 0.93). These declines persisted after adjustment for account numbers.</p><p><strong>Conclusions: </strong>Health actors remained active while losing structural position, a \"bunker effect\" of broadcasting without amplification. These findings challenge exposure-based evaluation models. Core embedding, within-category concentration, and PageRank share are computable from public network data and offer practical measures for campaign evaluation and platform transparency.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"36"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645615/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149140387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal variation in sleep apnea and other sleep parameters from diagnostic polysomnography data, 2003-2024.","authors":"Md Rashidul Hasan, David M Umbach, Min Shi, Chao Gu, Deryck Yeung, Amlan Talukder, Zheng Fan, Leping Li","doi":"10.1038/s44528-026-00013-6","DOIUrl":"10.1038/s44528-026-00013-6","url":null,"abstract":"<p><strong>Background: </strong>Seasonal variation in daylength, temperature, and humidity may influence the sleep cycle. We investigated how sleep apnea, measured by the apnea-hypopnea index (AHI) and five other sleep parameters vary across seasons.</p><p><strong>Methods: </strong>Our cross-sectional analysis used diagnostic in-laboratory polysomnography studies from adults without major diseases (3965 female; 2886 male) between 2003 and 2024 at a tertiary hospital in North Carolina, USA. We assessed seasonality separately in males and females using regression models with periodic spline terms and adjustment for age, body mass index, and calendar time.</p><p><strong>Results: </strong>We show that AHI is higher in males than females throughout the year and exhibits a single yearly cycle in both sexes (Likelihood Ratio Test [LRT]: <i>p</i> = 0.049, 0.058, respectively) with the peak for males in March and the nadir in early September; respective extremes in females occur about a month later. Sleep efficiency exhibits two cycles per year in both males and females (LRT: <i>p</i> = 0.003, 0.051, respectively). In males, the peaks are in April and September with troughs in early January and June, with respective extremes in females about a month later. Total sleep time shows no evidence of seasonality in females (LRT: <i>p</i> = 0.91) but two cycles per year in males (LRT: <i>p</i> = 0.005). We find no strong evidence of seasonality for the proportions of N3 sleep, REM sleep, or N2 sleep for either sex.</p><p><strong>Conclusion: </strong>Seasonal patterns for AHI and sleep efficiency are common to both sexes, whereas patterns for other sleep parameters differ between sexes or lack convincing evidence of seasonality.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"15"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13441896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148687601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Challenges for the effectiveness of infectious disease interventions during global change.","authors":"Justin Sheen, Emily Howerton, Holly A Burrows, Benjamin L Rice, Chadi M Saad-Roy","doi":"10.1038/s44528-026-00044-z","DOIUrl":"10.1038/s44528-026-00044-z","url":null,"abstract":"<p><p>Global change is expected to have complex effects on pathogen biology, yet how it will affect interventions has received less attention. Here, we explore how global change challenges the ability of interventions to act as ecological suppressors of transmission.</p>","PeriodicalId":524124,"journal":{"name":"Communications health","volume":"1 1","pages":"34"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645669/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149140391","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}