Sleep最新文献

{"title":"The association of objective daytime sleepiness with impaired glucose metabolism in patients with obstructive sleep apnea: a multi-omics study.","authors":"Le Chen, Baixin Chen, Yanyuan Dai, Qimeng Sun, Jun Wu, Dandan Zheng, Alexandros N Vgontzas, Xiangdong Tang, Yun Li","doi":"10.1093/sleep/zsae240","DOIUrl":"10.1093/sleep/zsae240","url":null,"abstract":"<p><strong>Study objectives: </strong>To examine the joint effect of obstructive sleep apnea (OSA) and objective excessive daytime sleepiness (EDS) on glucose metabolism and the underlying mechanisms.</p><p><strong>Methods: </strong>We included 127 patients with OSA. The multiple sleep latency test (MSLT) and Epworth sleepiness scale (ESS) were used to assess objective and subjective EDS, respectively. Disordered glucose metabolism was defined as either a physician diagnosis or having fasting blood glucose levels ≥5.6 mmol/L. Values of fasting insulin and homeostasis model assessment of insulin resistance (HOMA-IR) higher than the median values of our sample were defined as high fasting insulin and insulin resistance. Serum metabolomics and fecal microbiota were used to explore underlying mechanisms.</p><p><strong>Results: </strong>Lower MSLT values were associated with higher levels of fasting blood glucose, fasting insulin, and HOMA-IR. Furthermore, objective EDS was associated with increased odds of disordered glucose metabolism, elevated fasting insulin, and insulin resistance. Dysregulation of serum valine degradation and dysbiosis of fecal Bacteroides thetaiotaomicron were associated with impaired glucose metabolism in OSA with objective EDS. No association between subjective EDS and impaired glucose metabolism was observed.</p><p><strong>Conclusions: </strong>OSA with objective, but not subjective, EDS is associated with an increased risk of disordered glucose metabolism and insulin resistance. Dysregulation of valine degradation and dysbiosis of B. thetaiotaomicron appear to link objective EDS and disordered glucose metabolism in OSA.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142644699","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":"Sleep EEG biomarkers of psychopathology: are we finally making progress?","authors":"Elizabeth A Klingaman, Philip R Gehrman","doi":"10.1093/sleep/zsae270","DOIUrl":"10.1093/sleep/zsae270","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142676831","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":"Effects of night-to-night variations in objectively measured sleep on blood glucose in healthy university students.","authors":"Alyssa S C Ng, E Shyong Tai, Michael W L Chee","doi":"10.1093/sleep/zsae224","DOIUrl":"10.1093/sleep/zsae224","url":null,"abstract":"<p><strong>Study objectives: </strong>We examined associations between daily variations in objectively measured sleep and blood glucose in a sample of non-diabetic young adults to complement laboratory studies on how sleep affects blood glucose levels.</p><p><strong>Methods: </strong>One hundred and nineteen university students underwent sleep measurement using an Oura Ring 2 and continuous glucose monitoring (CGM) for up to 14 days. In 69 individuals who consumed a standardized diet across the study, multilevel models examined associations between sleep duration, timing, efficiency, and daily CGM profiles. Separately, in 58 individuals, multilevel models were used to evaluate postprandial glycaemic responses to a test meal challenge on 7 days. Participants also underwent oral glucose tolerance testing once after a night of ad libitum sleep, and again following a night of sleep restriction by 1-2 hours relative to that individual's habitual sleep duration. Between-condition glucose and insulin excursions, HOMA-IR and Matsuda index were compared.</p><p><strong>Results: </strong>Nocturnal sleep did not significantly influence following-day CGM profiles, postprandial glucose, or nocturnal mean glucose levels (all ps > .05). Longer sleep durations were associated with lower same-night glucose variability (all ps < .001). However, the range of variation in sugar levels was small and unlikely to be of functional significance. Considering naps in the analysis did not alter the findings. Sleep restriction by an average of 1.73 hours (SD = 0.97) did not significantly impact excursions in glucose or insulin or insulin sensitivity the following morning (all ps > .05).</p><p><strong>Conclusions: </strong>Glucose handling in young, healthy adults may be more resilient to real-life fluctuations in sleep patterns than previously thought.</p><p><strong>Clinical trial information: </strong>Monitoring Sleep and Glucose Among University Students https://clinicaltrials.gov/study/NCT04880629, ID: NCT04880629.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142354175","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":"Impaired sleep-dependent memory consolidation in pediatric narcolepsy type 1.","authors":"Kiran Maski, Gillian Heckler, Jennifer Worhach, Dimitrios Mylonas, Grace Wang, Klara Szilagyi, Bo Zhang, Cecilia Diniz Behn, Thomas E Scammell, Robert Stickgold","doi":"10.1093/sleep/zsae238","DOIUrl":"10.1093/sleep/zsae238","url":null,"abstract":"<p><strong>Study objectives: </strong>Disrupted nighttime sleep is common in pediatric narcolepsy type 1, yet its cognitive impact is unknown. As N2 sleep spindles are necessary for sleep-dependent memory consolidation, we hypothesized that narcolepsy type 1 impairs memory consolidation via N2 sleep fragmentation and N2 sleep spindle alterations.</p><p><strong>Methods: </strong>We trained 28 pediatric narcolepsy type 1 participants and 27 healthy controls (HCs) on a spatial declarative memory task before a nocturnal in-lab polysomnogram and then gave them a cued recall test upon awakening in the morning. We extracted wake and sleep stage bout numbers and N2 spindle characteristics from the polysomnogram and conducted mixed model analysis of sleep-dependent memory consolidation to identify group differences.</p><p><strong>Results: </strong>Narcolepsy type 1 participants had shorter N2 bout durations and associated shorter N2 spindles versus HC, but other N2 spindle features were similar. Narcolepsy type 1 participants had worse memory performance postsleep than HCs after adjusting for age and gender (mean memory consolidation HC: -3.1% ± 18.7, NT1: -15.6 ± 24.8, main effect group × time of testing F = 5.3, p = .03). We did not find significant relationships between sleep-dependent memory consolidation and N2 spindle characteristics. Notably, increased N1% was associated with worse sleep-dependent memory consolidation with results driven by the narcolepsy type 1 group.</p><p><strong>Conclusions: </strong>Sleep-dependent memory consolidation is mildly impaired in youth with narcolepsy type 1 and findings may be attributed to increases in N1 sleep. Further studies are needed to determine if these findings are generalizable and reversible with sleep-based therapies.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807881/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142475109","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":"Mortality risk assessment using deep learning-based frequency analysis of electroencephalography and electrooculography in sleep.","authors":"Teitur Óli Kristjánsson, Katie L Stone, Helge B D Sorensen, Andreas Brink-Kjaer, Emmanuel Mignot, Poul Jennum","doi":"10.1093/sleep/zsae219","DOIUrl":"10.1093/sleep/zsae219","url":null,"abstract":"<p><strong>Study objectives: </strong>To assess whether the frequency content of electroencephalography (EEG) and electrooculography (EOG) during nocturnal polysomnography (PSG) can predict all-cause mortality.</p><p><strong>Methods: </strong>Power spectra from PSGs of 8716 participants, including from the MrOS Sleep Study and the Sleep Heart Health Study, were analyzed in deep learning-based survival models. The best-performing model was further examined using SHapley Additive Explanation (SHAP) for data-driven sleep-stage specific definitions of power bands, which were evaluated in predicting mortality using Cox Proportional Hazards models.</p><p><strong>Results: </strong>Survival analyses, adjusted for known covariates, identified multiple EEG frequency bands across all sleep stages predicting all-cause mortality. For EEG, we found an all-cause mortality hazard ratio (HR) of 0.90 (CI: 95% 0.85 to 0.96) for 12-15 Hz in N2, 0.86 (CI: 95% 0.82 to 0.91) for 0.75-1.5 Hz in N3, and 0.87 (CI: 95% 0.83 to 0.92) for 14.75-33.5 Hz in rapid-eye-movement sleep. For EOG, we found several low-frequency effects including an all-cause mortality HR of 1.19 (CI: 95% 1.11 to 1.28) for 0.25 Hz in N3, 1.11 (CI: 95% 1.03 to 1.21) for 0.75 Hz in N1, and 1.11 (CI: 95% 1.03 to 1.20) for 1.25-1.75 Hz in wake. The gain in the concordance index (C-index) for all-cause mortality is minimal, with only a 0.24% increase: The best single mortality predictor was EEG N3 (0-0.5 Hz) with a C-index of 77.78% compared to 77.54% for confounders alone.</p><p><strong>Conclusions: </strong>Spectral power features, possibly reflecting abnormal sleep microstructure, are associated with mortality risk. These findings add to a growing literature suggesting that sleep contains incipient predictors of health and mortality.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142295978","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":"Attenuated melanopsin-mediated post-illumination pupillary response is associated with reduced actigraphic amplitude and mesor in older adults.","authors":"Joey W Y Chan, Chun-Tung Li, Steven Wai Ho Chau, Ngan Yin Chan, Tim Man-Ho Li, Bei Huang, Joshua Tsoh, Shirley X Li, Kelvin K L Chong, Kathryn A Roecklein, Yun Kwok Wing","doi":"10.1093/sleep/zsae239","DOIUrl":"10.1093/sleep/zsae239","url":null,"abstract":"<p><strong>Study objectives: </strong>This study aimed to explore the relationship between post-illumination pupillary response (PIPR) with sleep and circadian measures in a community sample of healthy older adults.</p><p><strong>Methods: </strong>Eligible participants were invited to complete a 1 week sleep diary and actigraphy, and provide an overnight urine sample to measure urinary 6-sulfatoxymelatonin (aMT6s). PIPR was defined as the (1) pupil constriction at 6 second poststimulus (PIPR-6s) and (2) for -30s beginning 10 seconds after stimulus (PIPR-30s), normalized as a percentage to the baseline pupil diameter, after 1 second of blue and 1 second of red light stimulus, respectively. The Net-PIPRs were reported by subtracting the PIPR to red stimulus from the PIPR to blue stimulus. The relationship between PIPR metrics to aMT6s and actigraphic rest-activity rhythm parameters was examined by generalized linear models.</p><p><strong>Results: </strong>A total of 48 participants were recruited (mean age: 62.6 ± 7.1 years, male: 44%). Both Net PIPR-6s and Net PIPR-30s were significantly associated with actigraphic rest-activity amplitude (B = 0.03, p = .001 and B = 0.03, p = .01, respectively) and actigraphic rest-activity mesor (B = 0.02, p = .001 and B = 0.03, p = .004, respectively). Additionally, the Net PIPR-30s were positively associated with overnight aMT6s level (B = 0.04, p = .03) and negatively associated with actigraphic rest-activity acrophase (B = -0.01, p = .004) in the fully adjusted models.</p><p><strong>Conclusions: </strong>Attenuated PIPR is associated with a reduced actigraphic amplitude and mesor. The reduced retinal light responsivity may be a potential pathway contributing to impaired photic input to the circadian clock and resulted in age-related circadian changes in older adults.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142393487","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":"A spectrum of altered non-rapid eye movement sleep in schizophrenia.","authors":"Nataliia Kozhemiako, Chenguang Jiang, Yifan Sun, Zhenglin Guo, Sinéad Chapman, Guanchen Gai, Zhe Wang, Lin Zhou, Shen Li, Robert G Law, Lei A Wang, Dimitrios Mylonas, Lu Shen, Michael Murphy, Shengying Qin, Wei Zhu, Zhenhe Zhou, Robert Stickgold, Hailiang Huang, Shuping Tan, Dara S Manoach, Jun Wang, Mei-Hua Hall, Jen Q Pan, Shaun M Purcell","doi":"10.1093/sleep/zsae218","DOIUrl":"10.1093/sleep/zsae218","url":null,"abstract":"<p><p>Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations, are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, aging, cognitive profiles, and medication regimens. Using newly collected high-density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported group-level differences between patients and controls (original N = 130) during the N2 stage. Then in the combined sample (N = 301 including 175 patients), we characterized patient-to-patient variability. We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (area under the receiver operating characteristic curve [AUC] = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics. Although multiple clinical and cognitive factors were associated with NREM metrics, collectively they did not account for much of the general increase in patient-to-patient variability. The medication regimen was a greater contributor to variability. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on the sleep EEG; further, among patients, certain medications exacerbated these effects, in particular olanzapine. Collectively, our results point to a spectrum of N2 sleep deficits among SCZ patients that can be measured objectively and at scale, with relevance to both the etiological heterogeneity of SCZ as well as potential iatrogenic effects of antipsychotic medication.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807884/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142295976","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":"The role of obstructive sleep apnea/hypopnea for leukoaraiosis and its cognitive consequences: a discussion still open!","authors":"Frédéric Roche, Sébastien Celle, Nathalie Perek, Pauline Guillot","doi":"10.1093/sleep/zsae283","DOIUrl":"10.1093/sleep/zsae283","url":null,"abstract":"","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11807890/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142829847","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":"Novel susceptibility genes and biomarkers for obstructive sleep apnea: insights from genetic and inflammatory proteins.","authors":"Yang Zhao, Yinyin Jiang, Yaxi Wang, Haiying Zhang, Jun Zhu, Xu Jiang, Bo Shen, Yaning Chen, Dongfeng Li, Yang Pan, Feng Han, Li Zhang","doi":"10.1093/sleep/zsae169","DOIUrl":"10.1093/sleep/zsae169","url":null,"abstract":"<p><strong>Study objectives: </strong>Numerous observational studies link obstructive sleep apnea (OSA) to inflammatory proteins, yet the directionality of these associations remains ambiguous. Therefore, we aimed to clarify the potential associations of gene-predicted inflammatory proteins with OSA.</p><p><strong>Methods: </strong>Based on genome-wide association study data, we applied Mendelian randomization (MR) to explore potential connections between circulating inflammatory proteins and OSA, primarily using the inverse-variance weighting method for robustness. Cochran's Q test, MR‒Egger intercept test, MR-PRESSO, and leave-one-out method were used to perform sensitivity tests for pleiotropy and heterogeneity. Replication analyses and meta-analyses were performed using other independent data. Steiger tests and multivariate MR assessed the independent effects of exposure factors, and the functional mapping and annotation (FUMA) platform was used to identify key genes to enhance the understanding of genetics.</p><p><strong>Results: </strong>Our investigation revealed 21 circulating inflammatory proteins significantly associated with OSA-related phenotypes. Notably, IL-10RA, IL-18R1, TNFSF14, CCL23, ADA, and SLAMF1 had significant effects on multiple phenotypes. After FDR correction, IL-18R1, SLAMF1, IL-10RA, and IL-17C were identified as important candidates for OSA, and multivariate MR analysis strengthened the independent heritability of 20 inflammatory factors. The FUMA platform revealed seven overlapping genes: ROBO1, PRIM1, NACA, SHBG, HSD17B6, RBMS2, and WWOX. All reverse MR analyses and sensitivity analyses confirmed the robustness of these associations.</p><p><strong>Conclusions: </strong>Our results underscore crucial associations between inflammatory proteins and OSA pathogenesis, revealing new correlates and susceptibility genes. These findings advance biomarker identification for OSA risk and highlight the importance of genetic and inflammatory profiles in OSA management.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11808066/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141861001","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":"Pupillometric and perceptual approaches provide independent estimates of melanopsin activity in humans.","authors":"Tom Woelders, Altug Didikoglu, Lucien Bickerstaff, Timothy M Brown, Robert J Lucas","doi":"10.1093/sleep/zsae289","DOIUrl":"10.1093/sleep/zsae289","url":null,"abstract":"<p><strong>Study objectives: </strong>Melanopsin-expressing retinal ganglion cells, which provide light information to time sleep and entrain circadian clocks, also influence perceived brightness raising the possibility that psychophysical paradigms could be used to explore the origins and implications of variability in melanopic sensitivity. We aimed to develop accessible psychophysical tests of melanopic vision and relate outcomes with a pupillometric measure of melanopsin function (post-illumination pupil response) and prior light exposure.</p><p><strong>Methods: </strong>Individually calibrated pairs of isoluminant stimuli differing in melanopic radiance from a four primary source were presented sequentially with superimposed random color offsets in a two alternative forced choice brightness preference paradigm to 41 naïve adult participants with personal light exposure data for the prior 7 days and post-illumination pupil response measures defined by comparing maintained pupil constriction for luminance matched \"red\" vs \"blue\" pulses.</p><p><strong>Results: </strong>Across participants we observed the expected tendency to report positive melanopsin contrast stimuli as \"brighter\" (one-tailed t-test p < 0.001), but with substantial inter-individual variability in both sensitivity (melanopsin contrast at criterion preference p = 0.75) and amplitude (preference at maximum melanopic contrast). There was little correlation between these psychophysical outcomes and post-illumination pupil response magnitude, or between either psychophysical or post-illumination pupil response measures and light history metrics (pairwise Pearson correlation coefficients -0.5> < 0.5). Random forest machine learning failed to satisfactorily predict outcome for either psychophysical or post-illumination pupil response measures based upon these inputs.</p><p><strong>Conclusions: </strong>Our findings reveal that estimates of melanopic function provided by perceptual and pupillometric paradigms can be largely independent of one another and of recent history of light exposure.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":5.6,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11808064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821750","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}