Geohealth最新文献

{"title":"Nuclear Magnetic Resonance–Based Urinary Metabolic Profiling for Assessing Heat Stress–Related Incident Kidney Injury in Health-Care Workers","authors":"Cheng-Yu Ting,&nbsp;Chi-Tsung Chen,&nbsp;Tzu-Hsin Yen,&nbsp;Jason Kai Wei Lee,&nbsp;Sheng-Han Lee,&nbsp;Shang-Jen Chang,&nbsp;Tzu-Han Hung,&nbsp;Hao-Jan Liang,&nbsp;Hsiao-Yu Yang,&nbsp;Ching-Yu Lin","doi":"10.1029/2025GH001583","DOIUrl":"https://doi.org/10.1029/2025GH001583","url":null,"abstract":"<p>During the COVID-19 pandemic, heat stress (HS) was a serious occupational risk for health-care workers (HCWs) wearing personal protective equipment, which limits heat dissipation and increases the risk of kidney injury. In this exploratory study, we assessed HS-related changes in the urinary metabolites of 38 HCWs working at mobile COVID-19 screening units in Taiwan and their possible role in incident kidney injury (IKI). Urine samples were collected before and after their shifts. Nuclear magnetic resonance-based metabolomics was applied to measure urinary metabolic perturbations associated with HS, and these findings were subsequently correlated with clinical markers of IKI. Data were analyzed through multivariate and univariate analyses. We found that HS-related changes in taurine and trimethylamine N-oxide (TMAO) levels showed a trend associated with postshift IKI. Preshift urinary citrate, acetone, and 4-hydroxybenzoate levels tended to be higher in the IKI population than the non-IKI population. Compared to the non-IKI population, the IKI population exhibited a trend toward lower postshift levels of glutarate and valine, but higher postshift levels of citrate, taurine, TMAO, and histidine. Metabolites whose levels were altered after HS included creatine, methylguanidine, formate, methylmalonate, 4-hydroxybenzoate, adenine, hippurate, and tryptophan. Our preliminary findings suggest that higher postshift urinary taurine levels in the IKI population are potentially related to oxidative stress. In contrast, elevated TMAO levels possibly indicate disturbances in the gut-kidney axis affecting renal health. Higher baseline urinary citrate and acetone may suggest increased susceptibility to HS-related IKI. Finally, elevated urinary glutarate in the non-IKI population may represent a protective metabolic response.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001583","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heatwaves and Mortality: The Influence of Choice of Definition and Lag","authors":"Yazan Alwadi,&nbsp;Fayez Abdulla,&nbsp;Yousef Khader,&nbsp;Wael K. Al-Delaimy","doi":"10.1029/2025GH001675","DOIUrl":"https://doi.org/10.1029/2025GH001675","url":null,"abstract":"<p>To investigate whether the reported additional effects of heatwaves on mortality are truly independent or instead reflect incomplete control for lagged temperature effects, and to assess whether this relationship varies by heatwave definition (e.g., minimum duration and intensity thresholds), as a potential explanation for heterogeneity in findings across the literature. We collected daily all-cause mortality records spanning 19 years (2000–2018) in Amman, Jordan. Heatwaves were identified using 20 definitions with varying temperature thresholds (percentile-based) and durations (2–5 consecutive days). Generalized Additive Models with penalized splines and Distributed Lag Non-linear Models were used to assess temperature-mortality associations and investigate how lag adjustment impacts the observed heatwave added effect. Without accounting for the lagged effects of temperature, heatwaves showed a significant additional effect on mortality in 7 out of 20 definitions. However, after properly controlling for these lagged effects, none of the heatwave definitions based on duration and threshold demonstrated a significant additional effect on mortality beyond what can be attributed to the cumulative (same day plus lagged) effect of daily temperature. The apparent added effect of heatwaves on mortality is largely explained by the cumulative impact of daily temperatures, suggesting that research and efforts might be more effective if focused on the cumulative effect of temperatures instead.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001675","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital-Based Cross-Sectional Study of Burkholderia pseudomallei Seroreactivity Among Febrile Patients in Northernmost Vietnam: Near-Neighbor Bloodstream Isolates, Environmental Correlates, and Spatial Clustering","authors":"Morgan C. Metrailer,&nbsp;Tran Thi Le Quyen,&nbsp;Khang Van Pham,&nbsp;Tan Minh Luong,&nbsp;Treenate Jiranantasak,&nbsp;Andrew P. Bluhm,&nbsp;Frank J. Tuozzo II,&nbsp;Thi Thu Ha Hoang,&nbsp;Minh Hoa Luong,&nbsp;Bich Ngoc Do,&nbsp;Thanh Hai Pham,&nbsp;Madison E. A. Harman,&nbsp;Michael H. Norris,&nbsp;Trinh Thanh Trung,&nbsp;Jason K. Blackburn","doi":"10.1029/2025GH001606","DOIUrl":"https://doi.org/10.1029/2025GH001606","url":null,"abstract":"<p>Melioidosis is a potentially fatal tropical disease caused by the environmentally mediated bacterium, <i>Burkholderia pseudomallei</i>. In Vietnam, melioidosis is not nationally reportable and little is known regarding its epidemiology and distribution in the northernmost mountainous provinces. To address this gap, a hospital-based cross-sectional study was conducted across six northernmost provinces of Vietnam: Son La, Dien Bien, Lai Chau, Lao Cai, Ha Giang, and Cao Bang. Objectives were to (a) elucidate the distribution and environmental correlates of <i>B. pseudomallei</i> seroreactivity, and (b) identify bacteria isolated from subset of admitted patients. <i>Burkholderia pseudomallei</i>-specific IgG ELISAs were used to identify elevated serological responses in febrile (≥38°C, unknown cause) hospital patients (<i>n</i> = 2,440; 2020–2023). Exploratory blood culturing and whole genome sequencing (WGS) from a small subset of patients was performed. A commune-scale presence-absence analysis examined environmental associations to seropositivity via a generalized linear model with Moran's eigenvector spatial filtering. Spatial distributions of the proportion of patients IgG seropositive (+2 SD above mean) to Hcp1/OPS were smoothed using spatial Bayes and clusters were detected with local Moran's I. WGS revealed <i>B. pseudomallei</i> near-neighbor species in some blood cultures; organisms that persist in similar environments, infect opportunistically, and are difficult to diagnose. A seasonal pattern was identified with more seropositivity among febrile hospital patients admitted in the wet season. At commune-scale, seropositivity correlated to higher rainfall averages, proximity to major waterways, and low soil nutrients. Seropositivity was spatially heterogeneous and several spatial clusters (seropositivity hotspots) were detected, indicating a need for local or regional surveillance.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148099330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pediatric Risk Mapping From Co-Exposure to Extreme Temperatures and Air Pollutants","authors":"Jagadeesh Puvvula,&nbsp;Jonathan J. Szeto,&nbsp;Jabeen Taiba,&nbsp;Jennifer Ko,&nbsp;Jesse E. Bell,&nbsp;Wei-Ting Hwang,&nbsp;Rebecca A. Simmons,&nbsp;Marilyn Howarth,&nbsp;Sameed Ahmed M. Khatana,&nbsp;Kyle Jackson,&nbsp;Aimin Chen","doi":"10.1029/2025GH001743","DOIUrl":"https://doi.org/10.1029/2025GH001743","url":null,"abstract":"<p>Exposure to extreme temperatures and fine particulate matter is hazardous to human health, especially among children. With growing evidence on the impact of these environmental hazards on child health—including increased risks of respiratory illnesses, heat-related illnesses, and developmental challenges—there is a substantial need to identify high-risk areas for potential adverse pediatric health outcomes. In this study, we developed pediatric vulnerability indices at the census tract scale across the contiguous United States (CONUS) using five dimensionality reduction methods, including unsupervised machine learning and deep learning approaches. We integrated these indices with data on extreme temperature (2012–2024), PM_2.5, and black carbon exposures from 2010 to 2020, enabling spatial analysis of environmental hazards and pediatric vulnerability. Among the five methods tested, principal component analysis (PCA) was selected for its balanced representation of 12 vulnerability factors, which explained 23% of the variance in the data. We observed that co-exposure to extreme temperature and air pollutant exposures were highest in the West, Southwest, and certain parts of the South and Northeast. Approximately 36% of the CONUS showed statistically significant hotspots of co-exposures to higher temperatures and air pollutants, concentrated in the West, Northwest, and Southwest. High-risk areas for pediatric vulnerability and co-exposure to environmental hazards were identified in both urban and rural communities, including indigenous lands and agricultural regions. These findings can aid policymakers and public health officials as a preliminary resource in developing heat action plans and allocating cooling centers to protect children living in the most affected communities.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001743","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148099325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Re-Evaluating Springtime as Southern Arizona's Dust Season","authors":"Ellis S. Robinson,&nbsp;Labiba J. Noushin,&nbsp;Carolina Martinez Guajardo,&nbsp;Chris Chaeha Lim,&nbsp;Avelino Arellano,&nbsp;Armin Sorooshian","doi":"10.1029/2025GH001745","DOIUrl":"https://doi.org/10.1029/2025GH001745","url":null,"abstract":"&lt;p&gt;The existing literature largely identifies spring as Arizona's predominant dust season, when synoptic-scale dust events are most frequent and “Fine Soil” measurements from the IMPROVE (Interagency Monitoring of Protected Visual Environments) network reach a yearly maximum. Because IMPROVE observations are primarily derived from remote monitoring sites, however, they may not reflect exposure-relevant dust seasonality in Arizona's urban areas, where anthropogenic activities can strongly influence coarse particulate matter (PM) concentrations. Consistent with this possibility, the notion of “spring as dust season” is less clear in other surface data sets that serve as dust proxies, including PM coarse and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;PM&lt;/mtext&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{PM}}_{10}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt;. Here we analyze (a) regulatory monitoring of hourly &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;PM&lt;/mtext&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{PM}}_{10}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and PM coarse concentrations, (b) IMPROVE measurements of 24-hr Fine Soil and PM coarse concentrations, and (c) sub-hourly PM coarse concentrations from a low-cost urban sensor network (SUNSET, Sonoran Unified Network of Sensors for Environmental Tracking). Our analysis reveals a different picture of dust seasonality. Summer has the highest concentrations of regulatory &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;PM&lt;/mtext&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{PM}}_{10}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; and PM coarse, followed by fall and then spring, whereas IMPROVE-measured Fine Soil peaks in spring. Summer also has the most &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;semantics&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mtext&gt;PM&lt;/mtext&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;annotation&gt; ${text{PM}}_{10}$&lt;/annotation&gt;\u0000 &lt;/semantics&gt;&lt;/math&gt; NAAQS exceedances. Seasonal patterns differ between urban and rural environments, and concentrations are generally higher in more anthropogenically influenced areas. Diurnal cycles, weekday–weekend differences, a COVID-era anomaly in 2020, and urban spatial gradients further indicate strong anthropogenic influences. Together, these results suggest that while springtime dust is climatologically important at remo","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001745","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148098654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emergency Department Presentations During Dry and Humid Heatwaves: A Case-Crossover Study in the Northern Territory, Australia","authors":"Rowena Boyd,&nbsp;Alyson Wright,&nbsp;Nicolas Borchers-Arriagada,&nbsp;Paul Fox-Hughes,&nbsp;Fay H. Johnston,&nbsp;Paul Burgess,&nbsp;Tracy Ward,&nbsp;Sharon L. Campbell","doi":"10.1029/2025GH001562","DOIUrl":"https://doi.org/10.1029/2025GH001562","url":null,"abstract":"<p>In a rapidly warming climate, heatwaves pose an increasing threat to human health. However, there is limited knowledge of heatwave impacts on health outcomes, or the role of humidity in the tropical and arid climates of Australia's Northern Territory (NT). Using a space-time-stratified case-crossover design and conditional Poisson regression models, we analysed the association between heatwaves and emergency department (ED) presentations from 2001 to 2023, across all six NT public hospitals. Heatwaves were identified using the Excess Heat Factor (EHF) method, with both temperature-only (heatwaves_T) and temperature-plus-humidity, heat-index (heatwaves_TH) metrics. We undertook sub-group analyses by sociodemographic characteristics and principal diagnosis. All-cause ED presentations increased by 4.4% (RR = 1.044, 95%CI 1.018–1.071) for severe/extreme and 1.6% (RR = 1.016, 95%CI 1.002–1.030) for low-intensity heatwaves_T. For heatwaves_TH, presentations increased by 6.1% (RR = 1.061, 95%CI 1.025–1.098, severe/extreme) and 0.9% (RR = 1.009, 95%CI 0.995–1.024, low-intensity). Subpopulation increases for severe/extreme heatwaves_T occurred for ages 19–49 years (RR = 1.052; 95%CI 1.018–1.087), visitors (RR = 1.162, 95%CI 1.038–1.301) and skin conditions (RR = 1.116, 95%CI 1.048–1.189). Specific to severe/extreme heatwaves_TH, presentations increased for Aboriginal peoples (RR = 1.059, 95%CI 1.006–1.114), ages 50–64 years (RR = 1.141, 95%CI 1.059–1.230) and cardiovascular conditions (RR = 1.111, 95%CI 1.015–1.216). Comparing heatwave indexes, 57.1% of heatwave_T days were not captured by heatwave_TH, and conversely 49.6% of heatwaves_TH days were not captured by heatwave_T. These findings call for dual heatwave warning systems in the NT, incorporating both EHF temperature and heat-index, and further humidity-inclusive studies in varied climates. Preventative interventions should target high-risk populations, prioritizing resources for severe and extreme heatwaves.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 6","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2025GH001562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148097002","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 5","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148120871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Exposure to Ambient Air Pollution and Hospitalization Risks and Costs on Type 2 Diabetes With Three Typical Comorbidities in Sichuan, China: A Time-Stratified Case-Crossover Study.","authors":"Wanyanhan Jiang, Han Chen, Yuelin Zhou, Hongwei Li, Lulu Lian, Lian Yang","doi":"10.1029/2025GH001629","DOIUrl":"10.1029/2025GH001629","url":null,"abstract":"<p><p>This study is aimed at examining the associations and hospitalization costs between air pollutants and hospital admissions (HAs) for type 2 diabetes mellitus (T2DM) with three typical comorbidities, namely cardiovascular disease (CVD), hypertension, and peripheral vascular disease (PVD). Conditional Poisson regression based on Poisson distribution was used to confirm the relationship between air pollution and HAs for T2DM with comorbidities. Potential effect modifiers, such as age and gender, were also involved. The attributable hospitalization number and costs due to air pollutants exposure were estimated, using WHO's air quality guidelines as reference. In total, 92,381 T2DM HAs were recorded, of which 6,855 patients with CVD, 23,403 with hypertension, and 21,207 with PVD, respectively. The significant short-term effects of NO₂, PM₁₀, PM_2.5 and SO₂ on HAs for T2DM with CVD, hypertension and PVD were different, mainly concentrated on lag 6 and lag 7. Stratified analysis demonstrated that mainly female and elder people (≥45 years) were more vulnerable to air pollutants. Total hospitalization costs attributable to air pollution were substantial. For T2DM patients with CVD, the hospitalization costs linked to NO₂, PM₁₀, and PM_2.5 were 7.43, 3.04, and 6.79 million China Yuan (CNY), respectively. For the hypertension comorbidity group, costs reached 12.17 million CNY for NO₂ and 10.89 million CNY for PM₁₀. Additionally, NO₂ exposure for 10.82 million CNY in hospitalization costs for T2DM patients with PVD. These findings underscore that air pollution not only exacerbates health risks but also imposes a significant financial strain on the healthcare system for vulnerable populations.</p>","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 5","pages":"e2025GH001629"},"PeriodicalIF":5.0,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13240063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148200843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 5","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148090160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"","authors":"","doi":"","DOIUrl":"","url":null,"abstract":"","PeriodicalId":48618,"journal":{"name":"Geohealth","volume":"10 5","pages":""},"PeriodicalIF":3.8,"publicationDate":"2026-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148119127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}