bluuebunny/crossref_metadata_2025_split huggingface dataset:
0100 Excretion of the Dual Orexin Receptor Antagonist Daridorexant into Breast Milk of Healthy Lactating Women
Authors: Kaufmann Priska , Anliker-Ort Marion , Siebers Nicholas , Muehlan Clemens , Dingemanse Jasper 
Published: April 2024

Abstract

Introduction
Daridorexant is a dual orexin receptor antagonist approved for the treatment of adult patients with insomnia. Following single-dose administration to healthy lactating female subjects, pharmacokinetics (PK) of daridorexant and its major metabolites were assessed in breast milk and plasma.

Methods
A single oral dose of 50 mg daridorexant was administered in the morning to 10 healthy lactating subjects (fasted state). To evaluate the transfer of daridorexant and its major metabolites into breast milk, all secreted breast milk over 72 h post dose as well as several plasma samples were collected. The PK of daridorexant in milk and plasma were assessed including the cumulative amount and fraction of dose excreted, estimation of the daily infant dose, and the relative, i.e., weight-adjusted infant dose that would be consumed by the breastfed child. Safety and tolerability were also investigated.

Results
All 10 subjects completed the study and were evaluable for PK and safety. Daridorexant was rapidly absorbed and distributed from plasma. Parent daridorexant and its major metabolites could be quantified in breast milk of all subjects. The shape of the individual milk concentration-time profiles of daridorexant closely followed the corresponding plasma profiles, and area under the curve and peak concentrations in breast milk were approximately 45- and 50-fold lower than in plasma. The cumulative total amount of daridorexant excreted over 72 h was 0.010 mg, which corresponds to 0.02% of the maternal dose. Overall, a mean daily infant dose of 0.009 mg/day and a relative infant dose of less than 0.22% over 24 h were determined. The known safety profile of daridorexant was confirmed. Headache was the most frequently reported adverse event (4 subjects).

Conclusion
Daridorexant was safe and well tolerated in healthy lactating women and presence of daridorexant and its major metabolites in breast milk is very low. However, despite the minimal excretion of daridorexant into breastmilk, a risk of somnolence to the breastfed infant cannot be excluded.

Support (if any)
At time of study conduct, Priska Kaufmann, Marion Anliker-Ort, Clemens Muehlan, and Jasper Dingemanse were employees of Idorsia Pharmaceuticals Ltd (sponsor). Nicholas Siebers was the Principal Investigator at Labcorp.
1000 The Association Between Sleep Problems and Self-Rated Psychotic Experiences
Authors: Grabner Palmer , Huskey Alisa , Hildebrand Lindsey , Grandner Michael , Killgore William 
Published: April 2024

Abstract

Introduction
Schizophrenia spectrum and other psychotic disorders are associated with a wide variety of functional impairments that interfere with daily functioning. Sleep is one domain that is disturbed in almost 80% of people experiencing schizophrenia and similar symptoms. We hypothesized that self-reported sleep disturbances would significantly predict tendencies consistent with schizophrenia and its associated subdomains—psychotic experiences, social detachment, and thought disorder symptoms. Social detachment and thought disorder symptoms are transdiagnostic traits that span many psychopathologies. We further hypothesized that each subdomain may be differentially associated with unique types of sleep disturbances.

Methods
Our sample comprised 190 participants with a mean age of 25 years old (SD=6.81) and a sex ratio of 71 males to 119 females. Each participant completed the Personality Assessment Inventory (PAI) to assess aspects of mental health consistent with schizophrenia spectrum disorders and the Pittsburgh Sleep Quality Index (PSQI) to assess sleep disturbances according to seven facets: subjective sleep quality, latency, duration, efficiency, disturbance, sleep medication use, and daytime dysfunction (DD). We used a stepwise linear regression to predict schizophrenia domain severity from sleep problems. Bivariate correlations were run to clarify the associations between schizophrenia and sleep disturbance subdomains.

Results
When considered in combination, self-reported DD was the only significant predictor of schizophrenic domain severity (β=.489, p&lt;.001; R^2=.239: F(1)=54.874, p&lt;.001). Individually, the psychotic experiences domain was correlated with DD (r=.230, p=.002) and sleep disturbances (r=.201, p=.007). Self-reported thought disorder traits were significantly related to sleep disturbances (r=.254, p&lt;.001), DD (r=.491, p&lt;.001), sleep medication use (r=.178, p=.016), and subjective sleep quality (r=.312, p&lt;.001). Social detachment was correlated with DD (r=.322, p&lt;.001) and sleep efficiency (r=-.162, p=.030).

Conclusion
Sleep-related daytime impairment predicted greater severity on the schizophrenia scale of the PAI and was associated with all related subdomains. Additionally, each of the subdomains were correlated with sleep disturbances, which could reflect the hyperarousal found with positive symptoms disturbing sleep maintenance. Sleep related interventions could contribute to reducing schizophrenia symptom severity. As hypothesized, specific sleep disturbance facets were differentially associated with schizophrenia subdomains. Each of these sleep facets may serve as important therapeutic targets in minimizing symptom severity in schizophrenia spectrum disorders.

Support (if any)
USAMRAA: W81XWH1210386
1002 Heart Rate Variability During Sleep and Future Risk of Parkinson’s Disease in Community-dwelling Older Men
Authors: Milton Sasha , Sun Haoqi , Kaffashi Farhad , Loparo Kenneth , Stone Katie , Yaffe Kristine , Westover M Brandon , Leng Yue 
Published: April 2024

Abstract

Introduction
Autonomic dysfunction is common in early stages of Parkinson’s disease (PD), providing an opportunity for early diagnosis and disease prediction. However, little is known about the longitudinal association between overnight—and sleep stage specific—heart rate variability (HRV), a marker of autonomic function, and incident PD.

Methods
Our sample consisted of 2470 older men (mean [SD] age = 76.1 [5.4] years) without PD who underwent polysomnography between 2003 and 2005 and were followed until 2016 for incident self-reported PD as part of the Osteoporotic Fractures in Men (MrOS) prospective study. HRV was calculated from the electrocardiogram in 5-minute epochs across the whole night and during rapid eye movement (REM) sleep and non-REM stages N2 and N3 (N2N3) alone. HRV metrics included measures of overall HRV (SDNN, standard deviation of NN intervals), short-term HRV/parasympathetic influence (RMSSD, root mean square of successive NN interval differences; HF, high frequency power), long-term HRV/sympathetic, parasympathetic, and baroreflex influence (LF, low frequency power), and long-term to short-term HRV balance (LF/HF; LFnu, normalized LF power, LF/[HF+LF]), which may represent sympatho-vagal balance. Associations between tertiles of HRV metrics and incident PD were assessed using multivariable logistic regression.

Results
During 11 years of follow-up, 60 incident PD cases were identified. After adjustment for covariates including age and comorbidities, men in the lowest tertile of LFnu measured across the whole night [OR (95% CI) = 2.13 (1.09,4.35)] and during REM alone [OR (95% CI) = 2.44 (1.23,5.55)] had approximately twice the odds of developing PD compared to those in the highest tertile. Results were similar for LF/HF, though the association was only significant during REM [OR (95% CI) = 2.33 (1.08,5.55)]. Further adjustment for apnea-hypopnea index did not attenuate these associations. HRV metrics assessed during N2N3 were not associated with incident PD, nor were SDNN, RMSSD, HF, and LF.

Conclusion
Individuals with decreased long-term to short-term HRV balance (possibly representing low sympatho-vagal balance) had higher risk of developing PD. REM may be a particularly important sleep stage for measurement of autonomic dysfunction in early PD and assessment of future PD risk.

Support (if any)
Support comes from the National Institute on Aging (R21AG085495).
1004 Predicting Incident Parkinson’s Disease and Dementia with Lewy Bodies from Nocturnal Wrist Actigraphy
Authors: Wickramaratne Sajila , Brink-Kjaer Andreas , Marwaha Salonee , Parekh Ankit , During Emmanuel 
Published: April 2024

Abstract

Introduction
“Isolated” REM sleep behavior disorder (iRBD) is an early marker of Parkinson’s disease (PD) and dementia with Lewy bodies (DLB) that affects 1-2% of individuals after 60 years of age. We published on a classifier using nocturnal wrist actigraphy data which achieved &gt;90% accuracy for iRBD detection. Here, we applied the same iRBD classifier in a population sample, the UK Biobank data to predict risk of incident PD or DLB.

Methods
30,000 records were randomly selected from the United Kingdom Biobank (UKBB) cohort dataset and were included based on age&gt;60 years, no neurological diagnosis and &gt;3-day valid nocturnal actigraphy data. Our published models were used to generate an iRBD score through automated detection of sleep periods and movement features from the accelerometer data. The iRBD score was generated for all the subjects and divided into: top 1%tile (predicted iRBD) and bottom 90%tile (predicted no-iRBD). The outcomes of interest were: 1) PD; 2) possible DLB. Odds ratio were then calculated using the iRBD scores (predictor) and the outcomes of interest (1 or 2).

Results
In the 10,087 records that met inclusion criteria, mean age was 63.8±2.8 years and subjects had on average 6.4±0.9 nights of valid actigraphy data. 109 subjects developed PD, and 67 DLB after 5.1±2.1 years. In the top 1%tile (n=101), 10 of 109 incident PD, and 18 of 67 DLB were accurately predicted by the calculated iRBD scores (sensitivity 9.2% and 26.8%, respectively). In the bottom 90%tile (n=9,078), 8,952 were accurately predicted to not develop PD or DLB (specificity 98.6%). Odds ratio were 9.1 [4.0 – 20.1] for PD, 40.2 [21.3 – 75.7] for DLB, and 19.8 [11.9 – 32.76] for either PD or DLB.

Conclusion
These results provide proof of concept that the existing iRBD detection model can be used to predict neurodegenerative outcomes in the community setting using ≥3 nights of actigraphy data. Future studies may assess additional actigraphy features related to 24h rest-activity rhythms (RAR) and gait patterns.

Support (if any)
Michael J Fox Foundation
1005 Improved Sleep Apnea Screening After Stroke Using Multimodal Wearable Sensors and Machine Learning
Authors: Sindorf Jacob , O’Brien Megan , Sunderrajan Aashna , Knutson Kristen , Zee Phyllis , Wolfe Lisa , Fiala Justin , Arora Vineet , Jayaraman Arun 
Published: April 2024

Abstract

Introduction
Sleep apnea affects over half of stroke survivors, impacting post-stroke recovery and outcomes. Early intervention through continuous positive airway pressure (CPAP) can reduce the impact of sleep apnea, motivating the need for accurate sleep apnea screening tools. Current screening tools such as home sleep apnea tests (HSATs) are difficult to use and uncomfortable due to bulky acquisition systems, electrodes, straps, and/or nasal cannulas, whereas questionnaires (i.e., STOP, STOP-BANG, Berlin OSA) suffer from lack of reliability and low sensitivity. Wireless, multimodal wearable sensors are promising tools to address these gaps; however, stroke-specific algorithms are essential to account for post-stroke physiological changes. The objective of this study was to develop and validate an apnea screening system using wearable sensors and machine learning during early stroke recovery.

Methods
Patients wore an HSAT (ApneaLink Air) and the Advanced NeoNatal Epidermal (ANNE) Chest and Limb sensors for one night within a week of admission to an acute rehabilitation facility. ANNE sensors are flexible, light-weight (&lt; 17 grams), adhesive based sensors capable of continuous monitoring (up to 7 days). Sleep-based features derived from physiological signals were extracted from ANNE sensors and paired with the ground truth apnea indication from the ApneaLink Air. A logistic regression machine learning model was trained to classify no apnea (normal, AHI&lt; 5) from apnea (mild, moderate, severe, AHI≥5).

Results
Forty-seven patients were screened with ApneaLink; over 60% had sleep apnea. Models using data from the ANNE Limb sensor performed best, with an F1 score (F1=0.75) outperforming the STOP (F1=0.62), STOP-BANG (F1=0.63), Berlin-OSA (F1=0.62) and a naive classifier (F1=0.38). Model performance increased when distinguishing between AHI&lt; 5 versus AHI≥15 (F1=0.94), whereas the surveys and naive classifier (F1=0.67, F1=0.58, F1=0.58, F1=0.33, respectively) saw a decline in performance.

Conclusion
Wearable sensors and stroke-specific machine learning models outperformed traditional questionnaires for sleep apnea screening, approaching HSAT-level accuracy (ApneaLink Air). The accessibility, comfort, and ease of use of sensors are well-suited for early application and continuous sleep monitoring compared to commercial HSAT devices.

Support (if any)
NIH R01HD097786-01A1.
1008 Daytime Sleepiness Is Associated with Increased Cerebrospinal Fluid Tau Proteins in Alzheimer’s Disease
Authors: Okamoto Cynthia , Sordo Lorena , Neikrug Ariel , Grill Joshua , Head Elizabeth , Benca Ruth , Sultzer David , Mander Bryce 
Published: April 2024

Abstract

Introduction
Sleep disturbance increases Alzheimer’s disease (AD) biomarkers, but it remains unclear whether the magnitiude of this effect differs by cognitive status. Addressing this unknown will elucidate when it is most critical to intervene to moderate AD pathophysiology and slow or arrest clinical progression.

Methods
A total of 155 participants, enrolled in Alzheimer Disease Research Center studies at University of California, Irvine (mean age 72.34 ± 7.07 years, 60.0% female) completed subjective assessment of sleep and cerebrospinal fluid (CSF) collection. Participants were divided into four cognitive status groups (Cognitively Normal, n=89; Questionable Cognitive Impairment, n=19; Mild Cognitive Impairment, n=33; and mild to moderately severe AD dementia, n=14). The Medical Outcomes Study Sleep Scale (MOS-SS) subscales assessed multiple sleep domains: Sleep Disturbance, Sleep Adequacy, Sleep Somnolence, Sleep Problems Index I, and Sleep Problems Index II. CSF biomarkers included β-amyloid 42 (Aβ42), total tau (t-tau), and phosphorylated tau (p-tau181). Moderation by cognitive status on the relationships among sleep scores and CSF biomarkers was assessed using the PROCESS macro in SPSS, adjusting for age and sex. Moderation by sleep scores in the cognitive status-CSF biomarkers relationship was also tested.

Results
After adjusting for age and sex, moderation analyses revealed significant interactions between sleep somnolence and cognitive status on CSF t-tau (F=3.3, p=0.023) and p-tau181 (F=2.9, p=0.035) but not Aβ42 (F=0.057, p=0.98) protein levels. The associations between sleep somnolence and t-tau (B = 4.18, SE = 1.51, t = 2.76, p = 0.01) and p-tau181 (B = 0.50, SE = 0.18, t = 2.69, p = 0.01) were positive and stronger in the AD group in comparison to all other cognitive status groups (all p&gt;0.35).

Conclusion
These findings indicate that in AD patients, greater subjective daytime sleepiness is associated with higher levels of t-tau and p-tau181 protein levels. As tau proteins are associated with neurodegeneration and cognitive decline, daytime sleepiness, whether or not due to the presence of sleep disorders such as sleep apnea, may be a risk factor or indicator of symptomatic progression of dementia in AD. Future studies should explore the efficacy of sleep-based interventions in slowing AD dementia progression.

Support (if any)
NIH K01AG068353, NIH T35AG076424, ADRC P30AG066519
1009 Association of Circadian Rhythm with 27-Hydroxycholesterol in Amnestic Mild Cognitive Impairment (aMCI) Patients
Authors: Kim Seong Jae , Lee Jung Hie , Jang Jae-Won , Choi Min Seo , Suh In Bum 
Published: April 2024

Abstract

Introduction
The 27-hydroxycholesterol(27-OH) has been proposed as a factor mediating the risk of Alzheimer's disease(AD) through oxidative cholesterol metabolism associated with cognitive impairment. Meanwhile, circadian disturbance has been implicated in accelerated aging and incident dementia, mediating metabolic dysregulation, which may lead to neurodegenerative diseases like AD. However, the relationship between circadian rhythm and cholesterol metabolism in MCI is poorly understood. We aimed to compare circadian parameters between amnestic MCI(aMCI) patients and normal controls(NC), and to examine whether changes in circadian parameters can be related with 27-OH levels.

Methods
Participants over 50 years were recruited from the Memory Clinic at Kangwon National University Hospital, and two public Dementia Care Centers. The diagnosis of aMCI was made according to Petersen’s criteria. Actigraphy monitoring was conducted at home for five days. Nonparametric variables including the inter-daily stability(IS), intra-daily variability(IV) and relative amplitude(RA) were calculated for rest-activity rhythm(RAR) and light exposure rhythm(LER), respectively. DLMO was determined from five hourly saliva samples obtained before sleep onset. The 27-OH levels were measured using high performance liquid chromatography/mass spectrometry(HPLC/MS). Eighteen aMCI patients(76.6 ±6.1 years) and 21 NCs(70.4±6.7years) were finally analyzed. Generalized linear models(GLMs) were used to assess the main effects of circadian parameters on 27-OH levels and their interactions with group.

Results
There were no significant differences in the RAR and LER variables(IV, IS and RA), and the DLMO between the aMCI and NC groups. In GLMs, significant main effects of RA in RAR and IV in LER on 27-OH levels were shown (β = -461.43, p=.036; β = -149.35, p=.001, respectively). There was no difference in the effects of circadian parameters on 27-OH levels between the aMCI and NC groups (p&gt;.05).

Conclusion
In our study, a strong 24-hour activity rhythm was associated with lower 27-OH levels, indicating less cholesterol metabolic dysfunction. It suggests that changes in circadian rhythm may affect cholesterol metabolism in preclinical AD patients.

Support (if any)
Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Science and ICT(2020R1F1A1050416);Learning & Academic research institution for Master’s·PhD students, and Postdocs(LAMP) Program of the National Research Foundation of Korea(NRF) grant funded by the Ministry of Education(No. RS-2023-00285353).
1010 Bruxism and Non-functional Jaw Muscular Activity in the Disorders of Consciusness
Authors: Marelli Sara , Sattin Davide , Castelnuovo Alessandra , Barbadoro Filippo , Ippoliti Camilla , Magnani Francesca Giulia , Cacciatore Martina , Leonardi Matilde , Sebastiano Davide Rossi , Strambi Luigi Ferini 
Published: April 2024

Abstract

Introduction
In the last decades, the role of the neurophysiological techniques in the assessment of Disorders of Consciousness (DOCs) after severe acquired brain injuries has been enhanced, leading to a growing interest in this challenging field. However, only few works focused on the presence of bruxism or non-functional jaw muscular activity (NFJMA) in these patients. Here we present our experience in 32 patients assessed with a long lasting polygraphy (PG).

Methods
Thirty-two patients (14 females and 18 males, mean age 55.3 + 11.7 years) with prolonged or chronic DOC were consecutively enrolled as part of a national, multicentric clinical trial aimed at evaluating the tolerance and the efficacy of treatments for sleep disorders in DOC patients. All the patients underwent to a 24h PG visually inspected in order to determine the periods of wakefulness or sleep on the basis of PG pattern(s), as well as the occurrence of bruxism or NFJMA.

Results
Bruxism or NFJMA were found in 9 out of 31 patients, during periods of sleep (3 patients), awake (3 patients) or both (3 patients). We detected two forms of NFJMA in our case-series: a) a sustained (tonic) contraction of masseter and mylohyoid progressively weaker until returning to previous muscle tone in 2-10 seconds; b) phasic contractions of masseter and mylohyoid, detectable as a biphasic, waxes and wanes activity, typically lasting 0.25-0.5 seconds and usually repeated with pseudo-rhythmic intervals of 0.5-1.5 seconds and often limited to 4-15 events. In 3 patients muscular activity was continuous or subcontinuous for a very long time (up to 1.5 hours), always maintaining 0.75-1.5 Hz frequency.

Conclusion
Although much is unknown about the non-functional jaw muscular activity, our work demonstrated that the bruxism and NFJMA are very frequent in DOC patients.

Support (if any)
This research was funded by the Italian Ministry of Health GR-2016-02365049—Pilot Study on sleep pathologies treatments in patients with Vegetative and Minimally Conscious State diagnosis for improving Consciousness level: the STRIVE project.
1013 Cross Validation of Sleep Biomarker Based Phenotyping of Neurodegenerative Disorders
Authors: Levendowski Daniel , Neylan Thomas , Walsh Christine , Yack Leslie , Tsuang Debby , Lee-Iannotti Joyce , Berka Chris , Mazeika Gandis , Boeve Bradley , Louis Erik St 
Published: April 2024

Abstract

Introduction
n this cross-validation study, the distributions of sleep biomarker-based neurodegenerative disorder (NDD) risk were evaluated across a spectrum of NDD patients and presumed controls which were independent of the model development dataset.

Methods
Variables that included age, time-REM, non-REM hypertonia, autonomic-activation index, spindle-duration, atypical-N3, time-supine, sleep-efficiency, relative-theta, and theta/alpha obtained with Sleep Profiler were used to train a 4-class machine learning algorithm that generated probabilities of NDD risk for the groups: Alzheimer’s dementia (AD), Lewy body disorder (LBD), prodromal synucleinopathy (pSYN based on REM sleep behavior disorder patients), and controls (CG). Records with CG output probabilities &gt;70% were labeled Probably-normal, and from 45-70% Likely-normal with indications of a NDD added when the LBD, AD or pSYN risks exceeded approximately 25%. Similar thresholds were used to assign Likely- or Probable- LBD, AD, pSYN or Mixed based on the group probabilities. This cross-validation study was designed to use datasets that were independent of those used to train the classification algorithm. Thus, NDD risk distributions were evaluated in patients with mild cognitive impairment (MCI=71), Parkinson’s disease (PD=16), progressive supranuclear palsy (PSP=21) and control subjects (NC=41) with Mini-Mental State Exam scores&gt;28 and/or normal for MCI by Petersen criteria.

Results
In the MCI group, NDD risk assignments were Probable-AD=26%, -Mixed=10%, -LBD=1%, Likely-AD= 7%, -Mixed=6%, -LBD=3%, -pSYN=1%, Likely-Normal indications-AD=9%, -pSYN=7%, -Mixed=4%, and Probably-Normal=26% In the PSP group, Probable-LBD=43%, -Mixed=29% and -pSYN=4%, Likely-Mixed=10%, Likely-Normal indications AD=10%, and Probably-Normal=4%. In the PD group, Probable-LBD=13%, -pSYN=13%, -AD=6%, Likely-Mixed=19%, -pSYN=6%, Likely-Normal Indications-pSYN=19%, -AD=12%, Likely-Normal=6% and Probably-Normal=6% In the NC group, 83% were assigned minimal NDD risk with Probably-Normal=70%, Likely-Normal plus indications=13%, but with Likely NDD=13% and Probable NDD=4%.

Conclusion
NDD risks were disbursed in a manner consistent with the range of severities expected In MCI and PD groups, with 25% exhibiting relatively normal sleep patterns. Over 70% of the PSP patients exhibited probable NDD risk, with patterns similar to those with LBD. The NC NDD risk distributions were consistent with those assigned to the CG used for model development.

Support (if any)
NIH grants R44AG050326, R44AG054256, RO1AG060477, R33AG064271, ULRR024150, R34AG056639.