bluuebunny/crossref_metadata_2025_split huggingface dataset:
0071 A Medullary Circuit Controlling REM Sleep
Authors: Schott A , Baik J , Chung S , Weber F 
Published: May 2020

Abstract

Introduction
Rapid eye movement (REM) sleep is a distinct brain state known for its association with vivid dreaming in humans, though it is also crucial for other mental processes such as memory consolidation and emotion regulation. REM sleep is punctuated by phasic neurophysiological events known as pontine (P)-waves, which are thought to contribute to the cognitive functions of REM sleep. However, little is known about the neural circuits regulating these P-waves, or those responsible for initiating REM sleep itself. Here, we show that a yet unstudied population of medullary neurons expressing corticotropin-releasing-hormone (CRH) are important for controlling both the induction of REM sleep and its phasic events.

Methods
To measure the endogenous activity of CRH+ neurons in the dorsomedial medulla (dmM), we injected the calcium indicator GCaMP6 in the dmM of CRH-Cre mice. To optogenetically manipulate dmM CRH+ neuron activity, we delivered either an excitatory (ChR2) or inhibitory (iC++) opsin to the dmM of CRH-Cre mice. To record P-waves, we implanted microelectrodes to record local field potentials in the subcoeruleus region of the pons.

Results
Fiber photometry recordings showed that dmM CRH+ neurons are selectively active during REM sleep, and optogenetic stimulation and inhibition of this population is sufficient to promote and reduce REM sleep, respectively. Additionally, dmM CRH+ neuron activity is correlated with P-waves in the pons, and optogenetic activation of dmM CRH+ cells reliably triggers P-waves during REM sleep. Finally, histological examination of fluorescently labeled dmM CRH+ axons revealed strong projections to several pontine areas involved in P-wave generation as well as modulation of the theta rhythm during REM sleep.

Conclusion
Our results suggest that dmM CRH+ neurons are involved in controlling REM sleep initiation as well as phasic events within REM sleep. These neurons thus constitute an important component of the brainstem circuitry regulating REM sleep.

Support
National Institutes of Health (R01 HL149133)
0075 Neural Correlates of Cognitive Fatigue in Parkinson Disease
Authors: Liu W , Bhavsar R , Mamikonyan E , Yang F N , Lei H , Weintraub D , Detre J A , Rao H 
Published: May 2020

Abstract

Introduction
Parkinson’s disease (PD) is a common neurodegenerative disease affecting millions of people world-wide. Fatigue is a prevalent and debilitating non-motor symptom in PD. However, the neural correlates underlying cognitive fatigue are poorly understood. Our previous studies suggested that continuous performance of a simple but mentally demanding psychomotor vigilance task (PVT) induced cognitive fatigue, operationalized as subjective exhaustion and time-on-task performance decline. Here we used arterial spin labeling (ASL) perfusion fMRI to investigate regional cerebral blood flow (CBF) changes in PD patients during cognitive fatigue induced by continuous performance of 20-min PVT.

Methods
Twenty-one PD patients completed a 20-min PVT during the ASL scan and two additional 4-min resting-state ASL scans before and after PVT. Reaction times (RTs) and regional CBF changes throughout the PVT as well as during pre- and post-task resting baselines were measured. Cognitive fatigue was analyzed by dividing the entire PVT performance into five quintiles in addition to the immediate measurement of self-rated fatigue before and after PVT.

Results
PD patients demonstrated significantly increased self-reported fatigue ratings after the task (p &lt; 0.05) and progressively slower RTs across quintiles (p &lt; 0.05). Perfusion data showed that the PVT activates the right middle frontal cortex, right inferior parietal lobe, right insula, bilateral occipital cortex, and right cerebellum (FDR corrected). Moreover, the bilateral middle frontal gyri were less active during the post-task rest compared to the pre-task rest.

Conclusion
These results demonstrated that cognitive fatigue has an ongoing effect on brain activity after a period of continuous mental effort and supported the critical role of prefrontal cortex in mediating cognitive fatigue in PD. The findings also suggest the utility of continuous PVT as an appropriate paradigm to induce and examine cognitive fatigue in PD.

Support
Supported in part by Parkinson’s Foundation Translational Research Grant and NIH grants R01-MH107571, R21-AG051981, and P30-NS045839.
1009 Sleep Apnea and Colorectal Adenoma in the Veteran Population: A Case-Control Study
Authors: Guan L , Jiao L , Malhotra S 
Published: May 2020

Abstract

Introduction
Colorectal cancer is the third most common cancer in the United States, with over half of colorectal cancers estimated to be the result of modifiable risk factors. Studies relating sleep apnea (SA) and colorectal adenoma (CRA) are limited and the findings are equivocal. The objective of this study was to examine the association between SA and risk of CRA.

Methods
This was a retrospective cross-sectional case-control study of data collected from 460 veterans, ages 50-79, seen in the colonoscopy clinic at the Michael E. DeBakey VA Medical Center between 2014 and 2018. Information on demographics, sleep history, and co-morbidities were obtained through lifestyle questionnaire. Self-reported SA was diagnosed by a prior sleep study. Cases consisted of 297 participants had pathologically confirmed adenoma (including 117 participants having advanced CRA with villous component or diameter of polyp &gt; 1 cm). Controls consisted of 173 polyp-free participants. The distribution of demographics and lifestyle factors were compared between CRA and non-CRA using the Student’s t or chi-square tests. Odds ratios (OR) and 95% confidence intervals (CI) of CRA in association with CRA were calculated using univariate and multivariate unconditional logistic regression models. The confounding factors included age, sex, ethnicity, obesity, smoking status, alcohol use, hypertension, and sleep duration.

Results
Compared with non-SA, the multivariable OR (95% CI) for CRA was 0.92 (0.58-1.48); for non-advanced CRA was 1.14 (0.68-1.91), and for advanced CRA was 0.61 (0.32-1.17) in SA participants. Adjustment of sleep duration in the model did not change the risk estimates.

Conclusion
Sleep-study diagnosed SA was not associated with development of CRA in this veteran population. Further studies are needed to confirm this observation and incorporate the severity and treatment of SA, and undiagnosed SA in risk assessment.

Support
This research is supported in part by the Gillson Longenbaugh Foundation, and Golfers Against Cancer organization (to LJ), the Cancer Prevention Research Institute of Texas (CPRIT) (RP#140767, to LJ).
1012 Urologic Features Related to the First Uninterrupted Sleep Period (FUSP) in Nocturia
Authors: Monaghan T F , Agudelo C W , Rahman S N , Michelson K P , Lazar J M , Everaert K , Weiss J P , Bliwise D L 
Published: May 2020

Abstract

Introduction
In nocturia, longer FUSP (time to first void) correlates with better quality sleep (Bliwise et al, JCSM 2015;11:53-5) and, with treatment, longer FUSP is associated with decreased nightly voids (Epstein et al, Neurourol Urodyn 2018;37:186-91). We examined urologic correlates of FUSP in an outpatient nocturia population without comorbidities (CHF, OSA, ESRD, diuretics).

Methods
Participants (n=119; men) kept a home flow/volume diary, tracking clock time and quantity of each urination across a 24-hr period. FUSP was defined as time between going to bed and time of first void. We analyzed the urine volume at first nocturnal void (FNVV) (i.e., at end of FUSP). We also analyzed all nighttime volumes and divided by reported hours of sleep to impute nocturnal urine production (NUP) (in ml/hr, classified as high [&gt;90 ml/hr] [n=49] vs low [&lt;90 ml/hr] [n=60])—a measure correlated with number of nocturia episodes (van Doorn et al, J Urol 2014;191:1034-9). Nocturnal maximal voided volume (NMVV) at any single nocturnal void defined maximal functional nocturnal bladder capacity. Data were analyzed non-parametrically.

Results
For 53 of 119 patients, FNVV was identical to NMVV. This was more likely in patients with NUP &gt;90 ml/hr vs &lt;90 ml/hr (59% vs 40%, p=.046). High (vs low) NUP rates were also associated with higher FNVV (300 [225-420] vs 135 [100-200] ml, p&lt;.001), as well as higher number of voids (3 vs. 2, p=.03).

Conclusion
For nearly half of these nocturia patients, the volume at first void occurred at their maximal nocturnal volume. In nocturia, higher FNVV also reflects greater overall nocturnal volume of urine produced, and excess urine volume (as opposed to insufficient bladder capacity) likely plays a central role in the pathogenesis of nocturia in these patients. The extent to which these higher initial volumes represent free-water vs solute-driven clearance is currently under investigation.

Support
N/A
0105 Working Memory Impairment Due to Chronic Sleep Restriction, Dose Response to Recovery and Re-Exposure
Authors: Kaizi-Lutu M , Jones C , Mange A , Basner M , Dinges D F 
Published: May 2020

Abstract

Introduction
Chronic sleep restriction negatively effects working memory. Recovery sleep following sleep restriction partially restores working memory performance. This study examines the impact of chronic sleep restriction and subsequent recovery sleep dose on the N-Back Task (N-Back), a valid measure of working memory.

Methods
N=223 participants (29.9±6.9 years; 48.4% female), completed two baseline nights of 8h time in bed (TIB), followed by five nights of 4h TIB, and were then randomized to a sleep dose of 0, 2, 4, 6, 8, 10, or 12 h TIB. A subset of participants (n=73) were re-exposed to another five nights of 4h TIB. Participants completed the three versions of the N-Back (i.e. 1-Back, 2-Back, and B-back) every two hours during wakefulness and daily averages were computed. Mixed effects and linear regression models were used to assess the impact of sleep restriction and the sleep dose response on percent correct on the N-Back corrected for baseline.

Results
N=219 participants had valid working memory data. The 2-Back (β =-4.5%; P&lt;0.0001) and the 3-Back (β =-12.5%; P&lt;0.0001) were more difficult than the 1-Back. Working memory performance declined across days of sleep restriction for all N-Backs: 1-Back (β =-1.10%; P&lt;0.0001), 2-Back (β =-0.99%; P&lt;0.0001), and 3-Back (β =-1.10%; P&lt;0.0001). The sleep dose analysis revealed a positive association with N-Back performance for all N-Back versions, 1-Back (β =0.99%; P=0.0002), 2-Back (β =1.46%; P&lt;0.0001), and 3-Back (β =1.43%; P&lt;0.0001). Re-exposure to only one night of 4h TIB following recovery sleep resulted in performance decrements equal to performance prior to recovery sleep for all N-Back versions (Ps&gt;0.41).

Conclusion
These data indicate that working memory is adversely impacted by sleep restriction, and that sufficient recovery sleep, possibly across consecutive days, is necessary to maintain optimal working memory performance.

Support
Funded by National Institute of Health NIH R01NR004281 and National Space and Biomedical Research Institute NSRBI NCC 5–98
1034 Should We Recommend More Sleep To Prevent Obesity?
Authors: Kim D S , Foster B E , Collen J F , Eliasson A H 
Published: May 2020

Abstract

Introduction
According to the 2015-2016 National Health and Nutrition Examination Survey (NHANES), the national adult obesity rate was 40% with the incidence of adult obesity having increased by 70% over the last 30 years. Paralleling the obesity epidemic have been worsening sleep deprivation and eroding sleep quality. We analyzed data from a Cardiovascular Health Registry to explore a link between total sleep time and obesity.

Methods
Registry participants underwent anthropometrics and completed validated questionnaires assessing health behaviors and symptoms including total sleep time (TST), Epworth Sleepiness Scale (ESS), Fatigue Severity Scale (FSS), Pittsburgh Sleep Quality Index (PSQI), Perceived Stress Scale (PSS), and exercise time. Differences between subjects with sufficient (≥7 hours) and insufficient (&lt;7 hours) sleep were analyzed using T-tests.

Results
Registry participants (n=630) had mean age 55.3±9.9 years (45% men, 391W, 182B, 26H, 12A, 19O). The subgroup with sufficient sleep (n=261, 48% men), had mean BMI 29.3±5.6 while the subgroup with insufficient sleep (n=369, 44% men) had mean BMI of 30.5±5.3, p=0.008. The insufficient sleep group was noted to be sleepier (ESS 9.7±4.9 vs 7.4±4.6, p&lt;0.001), more fatigued (FSS 4.9±2.3 vs 3.5±2.4, p&lt;0.001) and have worse sleep quality (PSQI 8.6±3.7 vs 4.7±2.8, p&lt;0.001). Insufficient sleepers also perceived greater stress levels (PSS 22.2±8.4 vs 18.9±6.2, p&lt;0.001), and showed a trend toward less exercise per week (143±134 vs 163±106 minutes, p=0.13).

Conclusion
Participants with insufficient sleep were significantly more overweight on average and were more symptomatic for insufficient sleep. While current approaches to weight management focus largely on diet and physical activity, the data from this study suggest that insufficient sleep should also be considered as a risk factor for obesity and should be incorporated into management plans for obesity.

Support
1075 Sleep-stage Independent Electroencephalography Features For Classification Of Veterans With Post-traumatic Stress Disorder
Authors: Laxminarayan S , Wang C , Oyama T , Cashmere D , Germain A , Reifman J 
Published: May 2020

Abstract

Introduction
Prior sleep studies have suggested that electroencephalography (EEG) spectral power and synchrony features in certain sleep stages differ significantly at the group-average level between subjects with and without post-traumatic stress disorder (PTSD). Here, we investigated whether a multivariate combination of sleep-stage independent EEG features could objectively identify individual subjects with PTSD.

Methods
We analyzed EEG data recorded from 78 combat-exposed veteran men with (n = 31) and without (n = 47) PTSD during two consecutive nights of sleep. For each subject we computed 780 features from 10 EEG channels covering the whole brain, by averaging the values over the entire night regardless of sleep stage. Using a training set consisting of the first 47 consecutive subjects (18 with PTSD) of the study, we performed univariate feature selection and backward feature elimination using a logistic regression model. We then evaluated the model on the test set, which consisted of the remaining 31 subjects (13 with PTSD). We assessed model performance by computing the area under the receiver operating characteristic curve (AUC).

Results
Feature elimination using the logistic regression model yielded three uncorrelated features that were consistently discriminative of PTSD across the two consecutive nights. When we trained the logistic model consisting of these three features using data from both nights of the training set, the model yielded test-set AUCs of 0.84 and 0.80 for Night 1 and Night 2, respectively. These values were considerably larger than the test-set AUCs of the three individual features, which ranged from 0.55 to 0.74 across both nights.

Conclusion
We identified robust, stage-independent, whole-night features and combined them in a logistic regression model to discriminate subjects with and without PTSD. The model yielded AUCs above 0.80 on the test data, showing promise as an objective approach to diagnose PTSD at the individual level.

Support
This work was sponsored by U.S. Defense Health Program (grant No. W81XWH-14-2-0145) and managed by the U.S. Army Military Operational Medicine Program Area Directorate, Ft. Detrick, MD. The study was also supported by the Clinical and Translational Science Institute at the University of Pittsburgh (UL1 TR001857).
1084 Depression and Stress Generation: Can Sleep Quality Bridge the Gap?
Authors: Summers C , Ciesla J , Bean C 
Published: May 2020

Abstract

Introduction
The stress generation literature has established a bidirectional relationship between depression and stress. Not only do stressful life events predict depressive episodes, but a depressive history is also linked to increased, future stressors. One relevant mechanism that has received little attention to account for this relationship is sleep. Sleep difficulties are intertwined with depression, both as a predictive and maintenance factor. Beyond depression, sleep disruption is also a factor in a plethora of stressful events, from an increased risk of automotive accidents to higher reports of interpersonal conflict. The present study explored the role of sleep quality to account for depression’s association with stressors.

Methods
Ninety-six college students (Age: M = 19.56, SE = .20) reported on their depressive symptoms before undergoing a two-week, online diary, where they reported on sleep quality and the number of stressors experienced. A generalized structural equation model (GSEM) was used to test the relevance of sleep quality to account for baseline depressive symptoms predicting average differences in stressors over the diary. Within the GSEM, a multilevel model was used to explore the daily, within-person association between sleep quality and the number of stressors reported.

Results
Baseline depression was predictive of poorer sleep quality (b = .01, p &lt; .001) and more stressors across the diary (b = .02, p = .017). Sleep quality mediated the effect of depression on stress generation (b = .002, p = .036), accounting for 13% of the variance. On a daily level, poorer sleep quality the night before predicted more stressors the next day (b = .16, p = .027).

Conclusion
The results suggest that sleep quality is a relevant mechanism in the prediction of future stressors from depression. Sleep difficulties may represent a pivotal area of future research and intervention target in breaking the cycle between depression and stress generation.

Support
Hammen, C. (1991). Generation of stress in the course of unipolar depression. Journal of Abnormal Psychology, 100, 555-561.
Tsuno, N., Besset, A., & Ritchie, K. (2005). Sleep and depression. The Journal of Clinical Psychiatry, 66, 1254-1269.
1090 Self-Reported Sleep Quality is a Robust Predictor of Depression in Women With Irregular Menstrual Cycles
Authors: Meers J M , Bower J L , Alfano C A 
Published: May 2020

Abstract

Introduction
Menstrual cycle regularity is an important marker of women’s health. Abnormalities are associated with serious health complaints, e.g., infertility, cardiovascular, and metabolic disorders. Cycle irregularity is also linked to depression, anxiety and poor quality sleep. In fact, poor sleep and circadian misalignment may precede menstrual irregularity for some. This study describes sleep and affective characteristics of women with menstrual cycle irregularity compared to regularly cycling women and examined the individual contributions of sleep and menstrual regularity to affective symptoms.

Methods
N=314 (Mage=20.95, SD=2.35) women provided reports of menstrual health characteristics (frequency, duration, related symptoms), sleep over the past month (Pittsburgh Sleep Quality Index; PSQI) and on the previous night, as well as mood (Center for Epidemiologic Studies Depression Scale) and anxiety (State Trait Anxiety Inventory) symptoms.

Results
Among the 20.4% (n=64) of women who endorsed “always irregular” periods, mean cycle length (m=31.33 days, sd=8.5) was significantly greater than among women more regular periods (m= 27.93, sd=3.83, t(55.37)=-2.78, p=.007). This subgroup also reported higher PSQI scores (t(181)=-2.56, p=.011), longer SOL (t(282)=-3.00, p=.003), poorer sleep quality overall (t(299)=-2.35, p=.02), and poorer sleep quality on the previous night (t(300)=2.70, p=.007). Irregular cyclers reported significantly more depressive (t(284)=-2.18, p=.03) but not anxiety symptoms. When sleep and menstrual irregularity were entered into a hierarchical linear regression to examine their relative influence on depressive symptoms (F[2,174]=13.15, p&lt;.001, R2=.13), sleep remained the only significant predictor (b= 1.13, p &lt;.001) and menstrual cycle effects were no longer significant.

Conclusion
In line with previous studies, cycle irregularity was associated with poorer sleep quality and depressive symptoms. Sleep quality was found to be a more robust predictor of depression than menstrual cycle irregularity, suggesting that sleep may underlie the affective disturbances in women with more irregular menstrual cycles.

Support
n/a
1098 Altered Actigraphic Behavioral Activity Rhythm In Depression
Authors: Chen I Y , Neikrug A B , Adams J , McMillan L , Yassa M A , Benca R M 
Published: May 2020

Abstract

Introduction
Disturbances in sleep and behavioral activity rhythms (BAR) are frequently observed in individuals with depression. However, it remains unclear how activity variability across the 24-hour period is specifically associated with this disorder. The present study aimed to examine actigraphy-measured sleep and BAR in depression.

Methods
As part of a larger study, fourteen patients with DSM-5 major depressive episode (27.8±7.7 years, 69.2% female) and 13 healthy controls (21.8±1.2 years, 76.5% female) were evaluated with 7-14 days of wrist-actigraphy. Actigraphy-derived sleep parameters included total sleep time (TST), sleep onset latency (SOL), wake after sleep onset (WASO), and sleep efficiency (SE). Minute-by-minute activity counts were aggregated into hour-by-hour bins; hourly mean activity levels were then generated to depict 24-hour activity patterns (i.e., BAR). Factorial (GroupxTime) mixed models were conducted to examine whether BAR differed between patients with MDD and controls. Generalized Additive Models (GAM), by fitting smoothed nonlinear curves to log-transformed aggregated activity, were performed as exploratory analyses to characterize onset (UP slope) and offset (DOWN slope) of BAR.

Results
Compared to healthy controls, patients with MDD exhibited greater actigraphic TST (p=.026); no other between-group differences were detected for the remaining sleep parameters. Significant between-group differences were observed for mean activity during wakefulness (p&lt;.001). Mixed models assessing hour-by-hour daily activity revealed a significant GroupxTime interaction (p=.001) with significant main effects of group (p=.017) and time (p&lt;.001); patients with MDD had lower activity from 6 to 9 pm (ps&lt;.005). Exploratory GAMs results showed an attenuated DOWN slope in patients with MDD (p=.014), indicating a slower decrease in activity during the evening.

Conclusion
Altered BAR, characterized by an overall dampened activity pattern that was most prominent during the evening, was associated with depression. Furthermore, patients with MDD took longer to wind down in the evening. Future studies are needed to explore the potential benefits of adjunctive interventions addressing both BAR along with sleep in mitigating symptoms of depression.

Support
Research supported by National Institutes of Health R01 MH102392.