bluuebunny/crossref_metadata_2025_split huggingface dataset:
0083 A Thermoregulated Pillow Improves Sleep: Results from Real-Life Data
Authors: Testa Damien , Stoikovitch David 
Published: May 2022

Abstract

Introduction
Sleep is regulated by homeostatic mechanisms and circadian rhythms.Thermal environment is one of the most important factors that can affect human sleep. This real-life study aims to evaluate the effects of temperature regulation on sleep quality using a thermoregulated pillow.

Methods
The Moona device has been used to control the temperature of a pillow pad from 64°F to 95°F. Users with more than 7 uses of the device and who completed the initial questionnaire (18 profile questions) participated in this study from October 2019 to July 2021. Participants rated their sleep quality on a scale of 1 to 5. Comparison between the sleep quality before the first use and the average of the last seven uses of the device has been done. A survey has been sent to all users from June to November 2021. To date, 206 answers have been collected including 32 users who reported having been diagnosed with insomnia. Improvement of their insomnia has been assessed by a 5-point scale (from ‘much better’ to ‘much worse’). Statistical analyses have been performed on Python 3.7. Mean comparisons have been measured by student t-test.

Results
The sleep quality significantly increased with the use of the device from 2.6/5 to 3.7/5 (p&lt;0.001) in the general population (N=620). This significant difference has been also measured in several subgroups who have temperature issues. That is the case for overweight/obese users (N=321, from 2.6/5 to 3.7/5, p&lt;0.001), women over 45 (N=97, from 2.4/5 to 3.6/5, p&lt;0.001) and users who feel hot during the night more than several times a week (N=523, from 2.5/5 to 3.8/5, p&lt;0.001). Moreover, 30 out of 32 insomniacs have reported an improvement of their insomnia since using this active cooling pillow pad.

Conclusion
The present study findings showed that an active thermoregulated pillow could improve sleep of insomnia patients and several subgroups of patients with issues at controlling temperature at night.

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0089 Feasibility of Rapid Measurement of Brain Metabolites in Obstructive Sleep Apnea
Authors: Saucedo Andres , Aysola Ravi , Macey Paul , Thomas Michael 
Published: May 2022

Abstract

Introduction
Obstructive Sleep Apnea (OSA) affects over 15% of the adult population and is associated with brain dysfunction. Although the dysfunction is well-identified and presents brain morphological changes as shown with structural imaging, it is unclear what pathology underlies these neural alterations. Magnetic resonance spectroscopic imaging (MRSI) can non-invasively measure several metabolites from multiple brain regions in vivo. However, the clinical practicality of the standard MRSI techniques (Cartesian phase-encoding or echo-planar [EP]) is hindered by long scan times. In order to assess clinical populations, our group developed an alternative MRSI technique, “radial” EP-MRSI. To assess the feasibility and calculate effect sizes we did a pilot study of brain metabolites in OSA using radial EP-MRSI.

Methods
Radial EP-MRSI data with a speed-up (undersampling) factor of 2.5 (compared to a fully-sampled Cartesian MRSI scan) were acquired in 5 OSA patients (3 males, 37±11 yrs., Apnea Hypopnea Index (AHI): 8.2±5.5) and 10 healthy controls (5 males, 28±7 yrs.). Spectra from twelve brain regions were selected from each subject and five metabolites–total choline, myo-inositol (mI), total N-acetylaspartate, glutamine+glutamate (Glx) and lactate (Lac)–were quantified as ratios with respect to creatine (Cr), using “LC Model” software. The brain regions include left/right of: basal ganglia, insula, and gray/white of the frontal and occipital regions. Mean group differences were calculated and compared with independent samples t-tests.

Results
Glx/Cr was significantly decreased (27%; p&lt;0.05) in OSA vs. control in the left posterior insula. Other metabolites did not show significant differences. mI/Cr trends were consistent with previous findings (higher in OSA) and Lac/Cr trended higher OSA.

Conclusion
This feasibility study showed that it is possible to measure multiple metabolites in multiple regions and detect effects of OSA. The accelerated technique enabled measurements to be completed in under 4 minutes.

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0099 Comparison of two actigraphy-based algorithms for detecting daytime and nighttime sleep
Authors: Gao Chenlu , Li Peng , Morris Christopher , Zheng Xi , Ulsa Ma Cherrysse , Gao Lei , Scheer Frank , Hu Kun 
Published: May 2022

Abstract

Introduction
The Actiware software that comes with Philips Respironics’ actiwatches tends to overestimate sleep, due to its poor accuracy in distinguishing immobility from sleep. Re-scoring rules were introduced in the Cole-Webster algorithm to overcome this issue. Previous validation of the two algorithms was based on nighttime sleep, and their performance in daytime sleep detection is unknown. This study aims to test/compare the performance of the two algorithms in detecting daytime sleep and nighttime sleep.

Methods
We analyzed actigraphy and polysomnography data that were simultaneously collected from 25 participants (14 non-shift-workers and 11 shift-workers; age: 30.93±8.96 [mean±SD]; female: 14 [56%]) each in two in-lab visits with scheduled nighttime or daytime sleep. The sleep/wake epochs scored by the Cole-Webster algorithm and Actiware (using medium wake threshold) were compared to those obtained from polysomnography. We conducted linear mixed-effects regression models to compare the sensitivity, specificity, and F1-score (a measure of performance less affected by imbalanced datasets) in detecting daytime and nighttime sleep and between the two algorithms.

Results
The Cole-Webster algorithm (mean±SE: daytime=0.66±0.02, nighttime=0.60±0.02) yielded lower sensitivity than Actiware (daytime=0.96±0.02, nighttime=0.96±0.02; p&lt;0.0001), which was consistent for both daytime and nighttime sleep (daytime/nighttime×algorithm interaction: p=0.2). The Cole-Webster algorithm (daytime=0.91±0.04, nighttime=0.94±0.05) yielded higher specificity than Actiware (daytime=0.45±0.04, nighttime=0.56±0.05; p&lt;0.0001), which was consistent for both daytime and nighttime sleep (daytime/nighttime×algorithm interaction: p=0.2). Both sensitivity and specificity did not differ between daytime and nighttime sleep (p&gt;0.05). F1 scores of the Cole-Webster algorithm were lower (daytime=0.77±0.02, nighttime=0.74±0.02) than those of Actiware (daytime=0.92±0.02, nighttime=0.97±0.02; p&lt;0.0001) for both daytime and nighttime sleep. There was a significant daytime/nighttime×algorithm interaction on F1 score (p=0.02). Specifically, the Cole-Webster algorithm performed better in scoring daytime than nighttime sleep, whereas Actiware performed better in scoring nighttime than daytime sleep.

Conclusion
For both algorithms, the performance was similar in detecting daytime and nighttime sleep. Compared to Actiware, the Cole-Webster algorithm was generally better at detecting wake (i.e., high specificity) but worse at detecting sleep epochs (i.e., low sensitivity) and yielded worse overall performance (i.e., low F1). Future studies should test/validate other Actigraphy-based algorithms’ performance in scoring daytime sleep.

Support (If Any)
NIH R01HL094806, RF1AG064312, RF1AG059867, BrightFocus Foundation A2020886S
0100 Daytime Sleep-Tracking Performance of Four Wearable Devices During Unrestricted Home Sleep
Authors: Chinoy Evan , Cuellar Joseph , Jameson Jason , Markwald Rachel 
Published: May 2022

Abstract

Introduction
Many previous studies, from our group and others, have tested the sleep-tracking performance of commercial wearable devices and generally found that many can track sleep-wake patterns on most nights in laboratory or home settings with equal or better performance as actigraphy. However, nearly all previous studies tested devices under fixed time in bed (TIB) and only during nighttime sleep. Despite the relevance for night shift workers, device algorithms are programmed/optimized for tracking nighttime sleep, and daytime sleep-tracking performance largely remains unexplored. We therefore tested the sleep-tracking performance of devices during unrestricted home daytime sleep.

Methods
Participants were 16 healthy young adults (6 men, 10 women; 26.6±4.6 years, mean±SD) with habitual daytime sleep schedules (i.e., slept between 06:00 and 22:00 for ≥1 hour at least twice weekly). Participants slept at home for 1 week under unrestricted conditions (i.e., self-selecting TIB) using a set of four commercial wearable sleep-tracking devices and completed sleep diaries. Wearables included the Fatigue Science Readiband, Fitbit Inspire HR, Oura Ring, and Polar Vantage V Titan. TIB biases and missed daytime sleep episodes were assessed against sleep diaries.

Results
In total, 86 episodes met criteria for “daytime sleep,” ranging from 2-10 episodes per participant. Percentage of daytime sleep episodes with TIB biases ≤15 and ≤60 minutes, and percentage of missed episodes in total and for short TIB (i.e., &lt;4 hours), respectively, were as follows: Readiband (33.8%, 90.8%, 11.0%, 85.7%), Inspire HR (60.4%, 87.7%, 2.4%, 6.3%), Ring (39.5%, 90.7%, 35.8%, 85.7%), and Vantage V Titan (49.0%, 92.2%, 38.6%, 100%).

Conclusion
The commercial wearable devices generally had similar performance for tracking daytime sleep episode TIB. Like our previous findings when the devices were tested during nighttime sleep, TIB biases were also low for most daytime sleep episodes. However, the devices missed detecting several daytime episodes, which occurred more often when TIB was &lt;4 hours. Preliminary findings suggest that daytime sleep TIB tracking is largely achievable with different commercial wearable devices; however, device sleep algorithms are not as reliable as when tracking nighttime sleep. Daytime sleep-tracking performance should be explored further.

Support (If Any)
Office of Naval Research, Code 34
0104 Acoustic enhancement of slow-wave sleep in healthy adolescents
Authors: Jones Stephanie , Flaherty Bethany , Myers Annika , Riedner Brady 
Published: May 2022

Abstract

Introduction
Adolescents have a stable sleep-need of between 9-10 hours a night, yet a pattern of markedly restricted sleep duration, particularly on school nights, has given rise to an epidemic of sleep deprivation in this population. As demonstrated by large numbers of studies, insufficient, irregular, and/or poor-quality sleep is a risk factor for both mental health problems and learning difficulties. Enhancing slow-wave sleep through non-pharmacological means may be a mechanism for alleviating daytime functional deficits in youth. In this study, we tested the feasibility of enhancing slow-wave sleep in healthy adolescents using a closed-loop, sleep-wearable device (SmartSleep, Phillips-Respironics) which monitors the EEG signal to automatically detect sleep stages, slow-waves, and micro-arousals to deliver acoustic stimulation to enhance SWA.

Methods
Seventeen healthy adolescents (15.5±1.8 years; 11 female) who endorsed sleep restriction and symptoms of daytime sleepiness participated in a randomized, cross-over study. Participation included wearing SmartSleep for two consecutive 4-night periods at home—one period with acoustic stimulation (STIM) and one without (SHAM). During STIM, SmartSleep monitors the EEG in real-time and delivers acoustic tones (50 ms, 1 second interval between) through embedded headphones at an intensity dynamically modulated by sleep depth. Stimulation is stopped when an arousal or sleep stage-shift is detected. During SHAM recording, the same stimulation protocol is applied with tones played at zero volume.

Results
No differences were observed in any measure of sleep architecture. A mixed effects linear regression model was used to analyze the impact of condition (STIM vs SHAM) on both cumulative and average SWA during N2N3 and N3 sleep. At the group level, cumulative SWA during N2N3 and average SWA during N3 were significantly increased in STIM relative to SHAM (p=0.01; p=0.02, respectively), while age (p=0.67) and sex (p=0.71) had no effect. Despite the significant group effects, not all youth were responders; an average increase in cumulative SWA (11.5 ± 7.1%) in the STIM condition was observed in 12/17 participants.

Conclusion
Consecutive nights of acoustic stimulation enhanced SWA in otherwise healthy, sleep-restricted adolescents. These data suggest that acoustic stimulation during sleep may be a viable method for optimizing slow-wave activity and minimizing the emotional and cognitive consequences of sleep restriction during this sensitive developmental period.

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0117 Two-Year Memory Change is Associated with Sleep Disorders in a Survey of Older Adults
Authors: Wills Chloe , Mason Brooke , Tubbs Andrew , Killgore William , Grandner Michael 
Published: May 2022

Abstract

Introduction
Insufficient sleep and sleep disorders have been previously associated with worse cognitive outcomes, such as worse memory performance. This analysis aims to assess the relationship between diagnosed sleep disorder and memory change over a period of two years.

Methods
N=17,156 older adults residing in the United States were assessed using the Health and Retirement Survey (Core) in 2018, with additional variables obtained in the previous wave (2016 on the same participants). Those who reported no sleep disorder in either wave were categorized as “no sleep disorder,” and they were compared to those who reported a sleep disorder in both waves (“sustained sleep disorder”) or one wave but not the other (“new sleep disorder” or “remitted sleep disorder.” Memory change was assessed using a survey item asking if the respondent’s memory was “worse”, “better”, or “the same” as compared to two years prior. Multinomial logistic regression was used to assess the relationship between these variables, and results were adjusted for sex, age, race, ethnicity, and depression.

Results
In adjusted results, those who reported that their memory improved were 124% (OR=2.24; 95%CI[1.51, 3.31]; p&lt;0.001) more likely to have a sleep disorder that was remitted in the past 2 years. Those who reported that their memory worsened were 103% more likely to have a new sleep disorder (OR=2.03; 95%CI[1.65,2.50]; p&lt;0.001), and 58% more likely to have a sustained sleep disorder (OR=1.58; 95%CI[1.40,1.77]; p&lt;0.001). Interestingly, those whose memory worsened were also 39% more likely to have a remitted sleep disorder (OR=1.35; 95%CI[1.10,1.77]; p=0.006).

Conclusion
In older adults, there is a relationship between change in memory function and sleep disorders, such that improved memory is associated with improved sleep and worsened memory is associated with worse sleep or sustained sleep problems. Unfortunately, the specific sleep disorders associated were not reported. Future work should examine these effects in terms of specific sleep disorders, additional effect modifiers/covariates, and the role of sleep health in improving memory function.

Support (If Any)
The HRS (Health and Retirement Study) is sponsored by the National Institute on Aging (grant number NIA U01AG009740) and is conducted by the University of Michigan.
0121 Sleep facilitates memory, but not navigation across the pubertal transition in the novel Minecraft Memory and Navigation Task
Authors: Simon Katharine , Fenger Alexis , Warren Laura , Choukas Nathaniel , Choi Dean , Zhang Jing , Clemenson Gregory , Mednick Sara 
Published: May 2022

Abstract

Introduction
The hippocampus uniquely supports the acquisition and retention of spatial information, and sleep supports the consolidation of hippocampal-dependent memories. However, support for the role of sleep in spatial memory and navigation is mixed. We developed and tested a novel Minecraft Memory and Navigation (MMN) task in adults which showed that sleep uniquely supports the memory for spatial locations, but navigation improved regardless of delay condition (Simon et al., submitted). Here, we tested participants during the developmental transition from childhood to adolescence, a time known for structural and functional hippocampal maturation.

Methods
Thirty-one youth (Mage = 10.6, SD = 1.56, 9-13 years, grouped: child, early adolescent, adolescent) were administered the MNN task. Training included two free-explorations trials to learn 12 unique object-locations associations in an open-field Minecraft environment. At test, participants were cued to place objects from randomly teleported locations. They were tested twice, immediately and 12-hours later, after a period of sleep or wake. Conditions and environments were counterbalanced in a within-subject design. Each step-by-step movement was recorded for navigation analyses including path length, orientation angle, and search behaviors.

Results
We found a significant benefit of sleep, compared to wake, on the spatial location accuracy when accounting for age group (F(1,27) = 6.153, p = .02), such that similar to young adults, youth’s metric accuracy of spatial locations improved. We found no change in navigation performances from Test 1 to Test 2 in either condition. Between the start and target locations, youth initiated and maintained similar trajectory angles with similar total path lengths (p’s &gt; .068). Spatial location memory did not correlate with any navigation metrics (p’s &gt; .361). Navigation metrics correlated among themselves, which withstood correction (p’s &lt; .005).

Conclusion
Youth demonstrated similar sleep-dependent benefits for the metric accuracy of the spatial locations. In contrast to adults, youth’s navigation performance did not improve over delay, regardless condition. Our findings are in line with sleep’s promotion of hippocampal-dependent information, with retention of the spatial locations. Our data are consistent with the hypothesis that sleep does not facilitate navigation, and points to potential developmental maturation required to support navigation behaviors.

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0127 Brain bacterial peptidoglycan is region-specific and changes after ischemic stroke
Authors: Dykstra-Aiello Cheryl , English Erika , Savenkova Marina , Karatsoreos Ilia , Krueger James 
Published: May 2022

Abstract

Introduction
Sleep disorders and ischemic stroke (IS) are large health burdens. Almost half the USA population reports disturbed sleep and 795,000 Americans suffer a stroke annually. Despite dysregulated sleep being a stroke risk factor that can exacerbate injury and prolong recovery, sleep deprivation immediately preceding experimental stroke is neuroprotective. Bacteria and microbial products associate with (patho-)physiologies, including sleep phenotypes and IS. Peptidoglycans (PGs) are bacterial cell wall components found in diseased and healthy adults, and in developing and sleep-deprived brains. Although they influence atherosclerosis, an IS risk factor, PGs have not been characterized in post-stroke brain.

Methods
Aged (63 weeks) male wildtype mice (n=5) underwent permanent left middle cerebral artery occlusion, a model that mimics atherosclerotic IS, the most common type in humans. Surgeries began at Zeitgeber time (ZT) 12, lasted 30-40 minutes, and were followed by a 2-2.5-hour recovery period before sacrifice at ZT15. Brain stem (BS), somatosensory and prefrontal cortices (Sctx, PFC) were dissected, homogenized in phosphate buffered saline, and centrifuged. A standardized murine peptidoglycan ELISA (MyBioSource) was used for PG/MP quantification in resultant supernates. Brain areas in the left (L) IS, and right (R) control, hemispheres were compared by two-way ANOVA and Tukey’s HSD tests.

Results
Mean PG values are expressed as ng/mg tissue wet weight ± SEM. Post-IS PG in the injured L Sctx (4.28±0.48) was lower (F(2,21)=49.29, p&lt;0.05) than the uninjured R Sctx (5.66±0.29; p=0.048). There were no hemispheric PG differences in either BS or PFC. L hemispheric PG was greater in BS (7.59±0.40) versus Sctx (p=0.0008) and PFC (3.82±0.21, p=0.0002). R hemispheric PG was also greater in BS (8.26±0.53) versus Sctx (p=0.005) and PFC (3.56±0.56, p=0.0006) and in Sctx versus PFC (p=0.02).

Conclusion
This study confirms our parallel study, presented in a separate abstract herein (English et al), that PG regulation is unique within brain areas. Additionally, PG values in uninjured Sctx and in BS were similar between studies. Finally, current results suggest that reduced cerebral blood flow induced by IS reduces PG in the affected brain area. Further, PG may have a role in sleep deprivation-related IS injury and recovery.

Support (If Any)
W.M. Keck Foundation and NIH (NS025378)
0128 Maternal Sleep Quality Across Pregnancy Predicts Newborn Neurodevelopment
Authors: Nevarez-Brewster Melissa , Demers Catherine , Mejia Alexandra , Hasse Mercedes Hoeflich , Styner Martin , Bagonis Maria , Kim SunHyung , Gilmore John , Hoffman M , Hankin Benjamin , Davis Elysia 
Published: May 2022

Abstract

Introduction
The prenatal period is characterized by immense fetal neuronal growth. Such rapid growth can increase fetal susceptibility to prenatal environmental insults (Barker, 1998). A promising prenatal process that may alter fetal development is maternal prenatal sleep quality. Poor prenatal sleep quality is a public health concern affecting approximately 78% of pregnant individuals (Lucena et al., 2018). In rodents, maternal sleep deprivation across gestation predicts offspring hippocampal neurogenesis, with pups exposed to sleep deprivation early and late in pregnancy exhibiting more anxiety and depression-like behaviors (Peng et al., 2015). In humans, poor sleep quality in other developmental stages predicts hippocampi and amygdalae changes (Marshall & Born, 2007; Saghir et al., 2018). However, the relation between prenatal sleep quality and offspring brain development in humans remains poorly understood. The present study examined associations between maternal sleep quality in early, mid, and late pregnancy, and newborn hippocampal and amygdala volume, regions implicated in memory and emotion.

Methods
Pregnant individuals (N=94; Mage=30.5; SDage=5.3) reported on sleep quality three times during pregnancy. Newborn (Mageinweeks=5.1; SDageinweeks=2.7) hippocampi and amygdalae volumes were assessed during an unsedated sleep cycle using magnetic resonance imaging (MRI). Tissue segmentation was collected using a multiatlas iterative algorithm that individually segmented the regions of interest and subsequently combined T1- and T2-weighted high-resolution images (See neonate multiatlas at https://www.nitrc.org/projects/unc_brain_atlas/). Bivariate correlations examined the association between prenatal sleep quality and hippocampus and amygdala volume. Partial correlations examined these associations in the presence of significant cofounding variables including intracranial volume, body weight percentile, sex, and postconceptional age.

Results
Partial correlations revealed that poor maternal sleep quality early in pregnancy predicted larger newborn bilateral hippocampal volume (all rs&lt;.25; ps&lt;.038). Associations with sleep later in gestation persisted for the right hippocampus (all rs&lt;.25; ps&lt;.038). Prenatal maternal sleep quality did not significantly predict newborn amygdala volume (all rs&lt;-.06; ps&gt;.58).

Conclusion
This study provides novel evidence linking prenatal sleep quality and newborn hippocampal volume in humans, suggesting the presence of an intergenerational link between prenatal sleep health and offspring well-being.

Support (If Any)
Support (if any): NIMH R01MH109662, NHLBI R01HL155744, and diversity training supplement for 1st author; F32MH125572 for 2nd author.