Hasil untuk "Neurophysiology and neuropsychology"

Elaheh Gheybi, Mohammad Jalili‑Nik, Pejman Hosseinzadeh et al.

Abstract Folate receptors, which mediate the cellular uptake of folic acid (FA) for essential processes such as DNA synthesis and repair, are expressed on neurons affected in Parkinson’s disease (PD). While the etiology of PD remains incompletely understood, oxidative stress is implicated as a key contributor. Alpha-lipoic acid (ALA) is a potent antioxidant; however, its therapeutic application is limited by instability, low bioavailability, and an unpleasant odor. Nanotechnology offers a promising strategy to overcome these limitations. This study aimed to develop and characterize folic acid-conjugated chitosan nanoparticles encapsulating ALA (FA-CS-ALA NPs) and to evaluate their efficacy against 6-hydroxydopamine (6-OHDA)-induced neurotoxicity. The FA-CS-ALA NPs, characterized by transmission electron microscopy, exhibited an irregular spherical morphology. Dynamic light scattering (DLS) analysis determined an average particle size of 658.13 nm and a polydispersity index (PDI) of 0.17, indicating moderate size distribution. In vitro studies using SH-SY5Y neuroblastoma cells demonstrated that 6-OHDA exposure significantly increased oxidative stress, neuroinflammation, and apoptosis. Both free ALA and FA-CS-ALA NPs effectively mitigated these deleterious effects. Notably, the FA-CS-ALA NPs exhibited superior neuroprotective efficacy compared to free ALA, suggesting that the folate-conjugated nanocarrier enhances therapeutic delivery.

Yuli Zhou, Guolei Sun, Yawei Li et al.

Abstract This study investigates the application and performance of the Segment Anything Model 2 (SAM2) in the challenging task of video camouflaged object segmentation (VCOS). VCOS involves detecting objects that blend seamlessly in the surroundings for videos due to similar colors and textures and poor light conditions. Compared to the objects in normal scenes, camouflaged objects are much more difficult to detect. SAM2, a video foundation model, has shown potential in various tasks. However, its effectiveness in dynamic camouflaged scenarios remains under-explored. This study presents a comprehensive study on SAM2’s ability in VCOS. First, we assess SAM2’s performance on camouflaged video datasets using different models and prompts (click, box, and mask). Second, we explore the integration of SAM2 with existing multimodal large language models (MLLMs) and VCOS methods. Third, we specifically adapt SAM2 by fine-tuning it on the video camouflaged dataset. Our comprehensive experiments demonstrate that SAM2 has the excellent zero-shot ability to detect camouflaged objects in videos. We also show that this ability could be further improved by specifically adjusting SAM2’s parameters for VCOS.

Juan Pablo Chart-Pascual, Miguel Angel Alvarez-Mon, Maria Montero-Torres et al.

Abstract Background Although lithium is considered the gold standard for the maintenance treatment of bipolar disorder (BD), its prescription has declined in recent decades. At the same time, second-generation antipsychotics (SGAs), such as quetiapine, and other mood stabilisers such as valproic acid, have been increasingly used. Social media platforms such as X (formerly Twitter) provide real-time insights into public and professional perceptions of these treatments, which may influence their use and adherence. Aims To analyse how lithium, quetiapine, and valproic acid have been represented on X, by focusing on user type, engagement levels, and thematic content of tweets. Method We conducted a mixed-methods, observational study of tweets published in English and Spanish between 2008 and 2022. Tweets containing the generic or commercial names of lithium, valproic acid, and quetiapine were retrieved and analysed using a validated codebook and semi-supervised machine-learning models. Tweets were categorised by user type and clinical and non-clinical content themes. Results Among the 236,797 analysed tweets, quetiapine was the most frequently mentioned drug (69.4%), followed by valproic acid (19.1%) and lithium (11.5%). Lithium tweets showed the highest engagement (54.0 likes and 18.0 retweets per tweet). Patients mainly focused on quetiapine (47.0%), while healthcare professionals more often discussed lithium (58.1%). Tweets containing clinical content were more common in English (78.0%) than in Spanish (54.7%), especially regarding side effects (53.1% vs 8.2%). Tweets on effectiveness were more frequently discussed in English (48.8%), especially for quetiapine (54.7%), but were less common in Spanish (9.8%). Discussion about drug shortages was more prevalent in Spanish tweets (31.6% vs 0.5%), particularly for valproic acid (55.8%). Conclusions Despite lithium being the least mentioned drug, it generated the highest level of engagement, particularly among healthcare professionals. In contrast, quetiapine was widely mentioned by patients, which reflects a more socially widespread and, at times, problematic use. These findings highlight the value of listening to conversations on social media to better understand perceptions, concerns, and attitudes that may influence adherence and prescribing trends in mental health.

Dhafar HO, Awadh AA, Aleissi SA et al.

Hamza O Dhafar,1 Ali A Awadh,2 Salih A Aleissi,1 Galal Eldin Abbas Eltayeb,3 Samar Z Nashwan,1 Ahmed S BaHammam1,4 1The University Sleep Disorders Center, Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia; 2Seha Virtual Hospital, Ministry of Health, Riyadh, Saudi Arabia; 3Department of Management Information Systems, College of Business and Economics, Qassim University, Buraydah, Saudi Arabia; 4The Strategic Technologies Program of the National Plan for Sciences and Technology and Innovation in the Kingdom of Saudi Arabia, Riyadh, Saudi ArabiaCorrespondence: Ahmed S BaHammam, University Sleep Disorders Center, Department of Medicine, College of Medicine, King Saud University, Box 225503, Riyadh, 11324, Saudi Arabia, Email ashammam2@gmail.comPurpose: Data on the prevalence and correlates of rapid eye movement (REM)–related obstructive sleep apnea (REM-OSA) in narcolepsy remains limited. This study aimed to assess the prevalence and independent associated factors with OSA and REM-OSA in patients with narcolepsy, and to compare the distribution of REM-OSA between patients with narcolepsy and matched controls without narcolepsy.Patients and Methods: This retrospective study of a prospectively collected cohort included 190 adult patients with narcolepsy (narcolepsy type 1 [NT1] = 119, narcolepsy type 2 [NT2] = 71) who underwent polysomnography and multiple sleep latency test at the University Sleep Disorders Center, King Saud University Medical City, between January 2007 and February 2022. REM-OSA was defined as an apnea–hypopnea index (AHI) ≥ 5, AHI-REM/AHI–non–rapid eye movement (NREM) ≥ 2, AHI-NREM < 8, and REM sleep duration > 10.5 minutes. A total of 106 patients with narcolepsy were diagnosed with OSA. A control group of 122 patients with OSA but without narcolepsy, matched by age, sex, AHI, and BMI, was used for comparison. Logistic regression identified independent associated factors with OSA and REM-OSA.Results: OSA was diagnosed in 106 patients with narcolepsy (55.8%). REM-OSA was present in 26.4% of these cases, with a slightly higher prevalence in NT2 (30%) than in NT1 (24%). REM-OSA showed a trend toward higher prevalence in the narcolepsy group compared to controls (26.4% vs 17.2%, OR: 1.73, 95% CI: 0.91– 3.27, p = 0.09). Male sex, BMI, and arousal index were independent correlates of OSA among patients with narcolepsy. REM-OSA was independently associated with arousal index and REM sleep duration.Conclusion: OSA and REM-OSA are common in patients with narcolepsy. REM-OSA was more prevalent in the narcolepsy group than in matched controls, suggesting a potential association between narcolepsy and REM-OSA that warrants investigation in larger cohorts.Plain Language Summary: People with narcolepsy often struggle with excessive daytime sleepiness and disrupted nighttime sleep. When another sleep disorder, such as obstructive sleep apnea (OSA), occurs alongside narcolepsy, it can make symptoms worse. A specific form of OSA, known as REM-OSA (which primarily occurs during rapid eye movement sleep), has been associated with an increased risk of heart and metabolic conditions. However, studies examining REM-OSA in people with narcolepsy remain limited.In this study, we evaluated 190 adults with narcolepsy and found that more than half had OSA. Among those with OSA, over one in four also had REM-OSA. We compared these patients to a group of individuals who had OSA but not narcolepsy. The two groups were matched by age, sex, apnea severity, and body mass index (BMI). We found that REM-OSA was more common in people with narcolepsy than in the matched controls. Although the difference was not statistically significant, the trend suggests a possible link worth further investigation.Understanding the relationship between narcolepsy and REM-OSA is important for improving diagnosis and treatment. A better understanding of this overlap may help improve patient outcomes. More research in larger groups is needed to confirm this connection.Keywords: sleep-disordered breathing, REM sleep, arousal index, sleep fragmentation, polysomnography, multiple sleep latency test

Wang M, Wang H, Feng Z et al.

Mengmeng Wang,1 Huanhuan Wang,1,2 Zhaoyan Feng,1 Shuai Wu,1 Bei Li,1,2 Fang Han,1 Fulong Xiao1 1Division of Sleep Medicine, Peking University People’s Hospital, Beijing, People’s Republic of China; 2School of Nursing, Peking University, Beijing, People’s Republic of ChinaCorrespondence: Fulong Xiao; Fang Han, Division of Sleep Medicine, Peking University People’s Hospital, Beijing, 100044, People’s Republic of China, Email xiaofulong1681@163.com; hanfang1@hotmail.comObjective: Depression is a common psychiatric issue among patients with narcolepsy type 1 (NT1). Effective management requires accurate screening and prediction of depression in NT1 patients. This study aims to identify relevant factors for predicting depression in Chinese NT1 patients using machine learning (ML) approaches.Methods: A total of 203 drug-free NT1 patients (aged 5– 61), diagnosed based on the ICSD-3 criteria, were consecutively recruited from the Sleep Medicine Center at Peking University People’s Hospital between September 2019 and April 2023. Depression, daytime sleepiness, and impulsivity were assessed using the Center for Epidemiologic Studies Depression Scale for Children (CES-DC) or the Self-Rating Depression Scale (SDS), the Epworth Sleepiness Scale for adult or children and adolescents (ESS or ESS-CHAD), and the Barratt Impulse Scale (BIS-11). Demographic characteristics and objective sleep parameters were also analyzed. Three ML models-Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)-were used to predict depression. Model performance was evaluated using receiver operating curve (AUC), accuracy, precision, recall, F1 score, and decision curve analysis (DCA).Results: The LR model identified hallucinations (OR 2.21, 95% CI 1.01– 4.90, p = 0.048) and motor impulsivity (OR 1.10, 95% CI 1.02– 1.18, p = 0.015) as predictors of depression. Among the ML models, SVM showed the best performance with an AUC of 0.653, accuracy of 0.659, sensitivity of 0.727, and F1 score of 0.696, reflecting its effectiveness in integrating sleep-related and psychosocial factors.Conclusion: This study highlights the potential of ML models for predicting depression in NT1 patients. The SVM model shows promise in identifying patients at high risk of depression, offering a foundation for developing a data-driven, personalized decision-making tool. Further research should validate these findings in diverse populations and include additional psychological variables to enhance model accuracy.Keywords: narcolepsy type 1, depression, machine learning, support vector machine

Tal Bechor Ariel, Ben Ariel, Michael Ben-Acon et al.

Description of three cases of 4–7-year-old male children presenting with a seizure without a prior history of epilepsy, 2–4 weeks after recovering from COVID-19.All three children were admitted to the pediatric department at Laniado Hospital in Netanya, Israel, and presented with seizures without fever.We found common characteristics among the children that can imply a predisposition for neurological complications of Covid-19.

Artur Eduardo Martio, Pedro de Moraes Rêgo Soares, Octávio Ruschel Karam et al.

Objective: The present study seeks to overcome the lack of data on Covid-19 associated intracranial hemorrhage (ICH) in Brazil. Methods: This is a retrospective, single-center case series of consecutive patients. It is a subanalysis of a larger study still in progress, which covers all neurological manifestations that occurred in patients admitted between March 1st, 2020 and June 1st, 2022, with active SARS-CoV-2 infection confirmed by polymerase chain reaction test. All patients with non-traumatic ICH were included. Results: A total of 1675 patients were evaluated: 917 (54.75 %) had one or more neurological symptoms and 19 had non-traumatic ICH, comprising an incidence of 1.13 %. All patients had one or more risk factors for ICH. The presence of neurological manifestations before the ICH and ICU admission showed a statistically significant relationship with the occurrence of ICH (X2 = 6.734, p = 0.0095; OR = 4.47; CI = 1.3–15.4; and FET = 9.13; p = <0.001; OR = 9.15; CI = 3.27–25.5 respectively). Conclusion: Our findings were largely congruent with the world literature. We believe that the assessment of risk factors can accurately predict the subgroup of patients at increased risk of ICH, but further studies are needed to confirm these hypotheses.

Cornelius Weiller, Tobias Bormann, Dorothee Kuemmerer et al.

Holly Rayson, Ranjan Debnath, Sanaz Alavizadeh et al.

Developmental EEG research often involves analyzing signals within various frequency bands, based on the assumption that these signals represent oscillatory neural activity. However, growing evidence suggests that certain frequency bands are dominated by transient burst events in single trials rather than sustained oscillations. This is especially true for the beta band, with adult ‘beta burst’ timing a better predictor of motor behavior than slow changes in average beta amplitude. No developmental research thus far has looked at beta bursts, with techniques used to investigate frequency-specific activity structure rarely even applied to such data. Therefore, we aimed to: i) provide a tutorial for developmental EEG researchers on the application of methods for evaluating the rhythmic versus transient nature of frequency-specific activity; and ii) use these techniques to investigate the existence of sensorimotor beta bursts in infants. We found that beta activity in 12-month-olds did occur in bursts, however differences were also revealed in terms of duration, amplitude, and rate during grasping compared to adults. Application of the techniques illustrated here will be critical for clarifying the functional roles of frequency-specific activity across early development, including the role of beta activity in motor processing and its contribution to differing developmental motor trajectories.

Ashley F.P. Sanders, Graham L. Baum, Michael P. Harms et al.

The human cerebral cortex undergoes considerable changes during development, with cortical maturation patterns reflecting regional heterogeneity that generally progresses in a posterior-to-anterior fashion. However, the organizing principles that govern cortical development remain unclear. In the current study, we characterized age-related differences in cortical thickness (CT) as a function of sex, pubertal timing, and two dissociable indices of socioeconomic status (i.e., income-to-needs and maternal education) in the context of functional brain network organization, using a cross-sectional sample (n = 789) diverse in race, ethnicity, and socioeconomic status from the Lifespan Human Connectome Project in Development (HCP-D). We found that CT generally followed a linear decline from 5 to 21 years of age, except for three functional networks that displayed nonlinear trajectories. We found no main effect of sex or age by sex interaction for any network. Earlier pubertal timing was associated with reduced mean CT and CT in seven networks. We also found a significant age by maternal education interaction for mean CT across cortex and CT in the dorsal attention network, where higher levels of maternal education were associated with steeper age-related decreases in CT. Taken together, our results suggest that these biological and environmental variations may impact the emerging functional connectome.

Hamfrey Sanhokwe, Simon Takawira

Limited research has been done on the utility of the resilience at work (RAW) scale in the global south. Furthermore, no study has modelled the general factor of the RAW scale. This is a huge gap given the need for organizational leaders to effectively to constantly monitor and nurture employee resilience if they are to enjoy adaptive advantages and flourish. The reliability, construct validity, dimensionality, and invariance of the RAW Scale were analysed. The levels of resilience at work were also measured. A sample of 213 employees was drawn from employees in government (34%), non-governmental organizations (NGOs, 33%), and the private sector (33%). Statistical software R, and the Bifactor Indices Calculator were used for the analysis. The RAW scale exhibited adequate psychometric properties. Exploratory factor analysis produced a seven-factor structure with 57% total variance explained. The higher model of the seven-factor scale had adequate fit indices. The results of the bifactor model also confirmed the multidimensional structure of the scale, albeit with six latent factors. Gender did not differentiate resilience at work scores. The results suggest that each of the six latent factors captures unique information beyond the full scale. As such, organizational researchers and leaders should use the RAW subscale average scores when measuring, interpreting, and evaluating resilience at work-related remediation actions. The scale was invariant across sectors hence its utility in national workplace surveys.

Nil Z. Gurel, Matthew T. Wittbrodt, Hewon Jung et al.

Objective: Exacerbated autonomic responses to acute stress are prevalent in posttraumatic stress disorder (PTSD). The purpose of this study was to assess the effects of transcutaneous cervical VNS (tcVNS) on autonomic responses to acute stress in patients with PTSD. The authors hypothesized tcVNS would reduce the sympathetic response to stress compared to a sham device. Methods: Using a randomized double-blind approach, we studied the effects of tcVNS on physiological responses to stress in patients with PTSD (n = 25) using noninvasive sensing modalities. Participants received either sham (n = 12) or active tcVNS (n = 13) after exposure to acute personalized traumatic script stress and mental stress (public speech, mental arithmetic) over a three-day protocol. Physiological parameters related to sympathetic responses to stress were investigated. Results: Relative to sham, tcVNS paired to traumatic script stress decreased sympathetic function as measured by: decreased heart rate (adjusted β = −5.7%; 95% CI: ±3.6%, effect size d = 0.43, p < 0.01), increased photoplethysmogram amplitude (peripheral vasodilation) (30.8%; ±28%, 0.29, p < 0.05), and increased pulse arrival time (vascular function) (6.3%; ±1.9%, 0.57, p < 0.0001). Similar (p < 0.05) autonomic, cardiovascular, and vascular effects were observed when tcVNS was applied after mental stress or without acute stress. Conclusion: tcVNS attenuates sympathetic arousal associated with stress related to traumatic memories as well as mental stress in patients with PTSD, with effects persisting throughout multiple traumatic stress and stimulation testing days. These findings show that tcVNS has beneficial effects on the underlying neurophysiology of PTSD. Such autonomic metrics may also be evaluated in daily life settings in tandem with tcVNS therapy to provide closed-loop delivery and measure efficacy.ClinicalTrials.gov Registration # NCT02992899.

Khademi A, EL-Manzalawy Y, Master L et al.

Aria Khademi,1&ndash;3 Yasser EL-Manzalawy,1,4 Lindsay Master,5 Orfeu M Buxton,5&ndash;9 Vasant G Honavar1&ndash;3,6,10,11 1College of Information Sciences and Technology, The Pennsylvania State University, University Park, PA, USA; 2Artificial Intelligence Research Laboratory, The Pennsylvania State University, University Park, PA, USA; 3Center for Big Data Analytics and Discovery Informatics, The Pennsylvania State University, University Park, PA, USA; 4Department of Imaging Science and Innovation, Geisinger Health System, Danville, PA, 17822, USA; 5Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA, USA; 6Clinical and Translational Sciences Institute, The Pennsylvania State University, University Park, PA, USA; 7Division of Sleep Medicine, Harvard University, Boston, MA, USA; 8Department of Social and Behavioral Sciences, Harvard Chan School of Public Health, Boston, MA, USA; 9Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women&rsquo;s Hospital, Boston, MA, USA; 10Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA, USA; 11Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USACorrespondence: Orfeu M BuxtonThe Pennsylvania State University, University Park, PA 16802, USATel +1 814 865 3141Email orfeu@psu.eduBackground: The current gold standard for measuring sleep is polysomnography (PSG), but it can be obtrusive and costly. Actigraphy is a relatively low-cost and unobtrusive alternative to PSG. Of particular interest in measuring sleep from actigraphy is prediction of sleep-wake states. Current literature on prediction of sleep-wake states from actigraphy consists of methods that use population data, which we call generalized models. However, accounting for variability of sleep patterns across individuals calls for personalized models of sleep-wake states prediction that could be potentially better suited to individual-level data and yield more accurate estimation of sleep.Purpose: To investigate the validity of developing personalized machine learning models, trained and tested on individual-level actigraphy data, for improved prediction of sleep-wake states and reliable estimation of nightly sleep parameters.Participants and methods: We used a dataset including 54 participants and systematically trained and tested 5 different personalized machine learning models as well as their generalized counterparts. We evaluated model performance compared to concurrent PSG through extensive machine learning experiments and statistical analyses.Results: Our experiments show the superiority of personalized models over their generalized counterparts in estimating PSG-derived sleep parameters. Personalized models of regularized logistic regression, random forest, adaptive boosting, and extreme gradient boosting achieve estimates of total sleep time, wake after sleep onset, sleep efficiency, and number of awakenings that are closer to those obtained by PSG, in absolute difference, than the same estimates from their generalized counterparts. We further show that the difference between estimates of sleep parameters obtained by personalized models and those of PSG is statistically non-significant.Conclusion: Personalized machine learning models of sleep-wake states outperform their generalized counterparts in terms of estimating sleep parameters and are indistinguishable from PSG labeled sleep-wake states. Personalized machine learning models can be used in actigraphy studies of sleep health and potentially screening for some sleep disorders.Keywords: actigraphy, polysomnography, personalized, machine learning, sleep parameters

Bo Hu, Xiaomin Zhang, Guangtao Xu et al.

Background/Aims: Several factors influencing postoperative pain and the effect of opioid analgesics have been investigated on an individual level. The aim of this study was to clarify the impact of catecholamine-O-methyltransferase (COMT) gene Val158Met on opioid consumption in postoperative patients. Methods: A systematic review and meta-analysis of the literature up to September 30, 2017, were performed by using PubMed, Cochrane Library, ISI Web of Science, and Chinese National Knowledge Infrastructure (CNKI) database. The meta-analysis examined all studies involving the association between genetic polymorphisms of COMT Val158Met and opioid consumption during the acute postoperative period. Results: Of the 153 identified studies, 23 studies were retrieved for systematic review and 10 studies were retrieved for meta-analysis. However, it was impossible to conduct meta-analysis on the association between COMT Val158Met polymorphism and postoperative pain because of heterogeneity of the data. Overall, meta-analysis showed that COMT Val/Met carriers consumed less opioid for analgesia within the first 24 hours after surgery (SMD = 0.14, 95% CI = [0.03, 0.25], P = 0.01) but not within 48 hours (SMD = 0.14, 95% CI = [0.08, 0.36], P = 0.21). There was no significant difference in opioid consumption between Val/ Val and Met/Met patients. Conclusion: Patients with Val/Met but not Met/Met allele variant consumed less opioid, though larger and better-designed studies are required to obtain an exclusive conclusion about the correlation between postoperative pain and COMT Val158Met polymorphism.

حسن آذرگون, محمدباقر کجباف, امیر قمرانی

Aim and Background: Gratitude is one of positive features of personality that has attracted many psychologists in recent years. The purpose of this study was to evaluate the effectiveness of Emmons gratitude practice on the quality of life and mental health. Methods and Materials: This was a semi-experimental study with pretest, posttest, and follow-up design, and with the experimental and control groups. 20 young couples in Nishabur City, Iran, were selected using convenience sampling method, and were randomly divided into 2 groups. The experimental group received gratitude training based on the Emmons method for 9 sessions. Data were analyzed using analysis of covariance test via SPSS software. Findings: After the intervention, there were significant differences between the mean scores of quality of life and mental health between the groups, after the adjustment of the pretest (P < 0.050); the experimental group showed higher mental health and quality of life, after receiving Emmons gratitude intervention. Conclusions: It can be stated that Emmons gratitude practice increases quality of life and mental health by increasing the positive characteristics of couples, overall positive orientation, positive cognitive processes, and positive emotional functioning.

Heather L. Bennett, Yulia Khoruzhik, Dustin Hayden et al.

Abstract Background Sleep deprivation impairs learning, causes stress, and can lead to death. Notch and JNK-1 pathways impact C. elegans sleep in complex ways; these have been hypothesized to involve compensatory sleep. C. elegans DAF-16, a FoxO transcription factor, is required for homeostatic response to decreased sleep and DAF-16 loss decreases survival after sleep bout deprivation. Here, we investigate connections between these pathways and the requirement for sleep after mechanical stress. Results Reduced function of Notch ligand LAG-2 or JNK-1 kinase resulted in increased time in sleep bouts during development. These animals were inappropriately easy to arouse using sensory stimulation, but only during sleep bouts. This constellation of defects suggested that poor quality sleep bouts in these animals might activate homeostatic mechanisms, driving compensatory increased sleep bouts. Testing this hypothesis, we found that DAF-16 FoxO function was required for increased sleep bouts in animals with defective lag-2 and jnk-1, as loss of daf-16 reduced sleep bouts back to normal levels. However, loss of daf-16 did not suppress arousal thresholds defects. Where DAF-16 function was required differed; in lag-2 and jnk-1 animals, daf-16 function was required in neurons or muscles, respectively, suggesting that disparate tissues can drive a coordinated response to sleep need. Sleep deprivation due to mechanical stimulation can cause death in many species, including C. elegans, suggesting that sleep is essential. We found that loss of sleep bouts in C. elegans due to genetic manipulation did not impact their survival, even in animals lacking DAF-16 function. However, we found that sleep bout deprivation was often fatal when combined with the concurrent stress of mechanical stimulation. Conclusions Together, these results in C. elegans confirm that Notch and JNK-1 signaling are required to achieve normal sleep depth, suggest that DAF-16 is required for increased sleep bouts when signaling decreases, and that failure to enter sleep bouts is not sufficient to cause death in C. elegans, unless paired with concurrent mechanical stress. These results suggest that mechanical stress may directly contribute to death observed in previous studies of sleep deprivation and/or that sleep bouts have a uniquely restorative role in C. elegans sleep.

K.A. Sagar, M.K. Dahlgren, A. Gönenç et al.

Marijuana (MJ) use is on the rise, particularly among teens and emerging adults. This poses serious public health concern, given the potential deleterious effects of MJ on the developing brain. We examined 50 chronic MJ smokers divided into early onset (regular MJ use prior to age 16; n = 24) and late onset (age 16 or later; n = 26), and 34 healthy control participants (HCs). All completed a modified Stroop Color Word Test during fMRI. Results demonstrated that MJ smokers exhibited significantly poorer performance on the Interference subtest of the Stroop, as well as altered patterns of activation in the cingulate cortex relative to HCs. Further, early onset MJ smokers exhibited significantly poorer performance relative to both HCs and late onset smokers. Additionally, earlier age of MJ onset as well as increased frequency and magnitude (grams/week) of MJ use were predictive of poorer Stroop performance. fMRI results revealed that while late onset smokers demonstrated a more similar pattern of activation to the control group, a different pattern was evident in the early onset group. These findings underscore the importance of assessing age of onset and patterns of MJ use and support the need for widespread education and intervention efforts among youth.

Catherine P. Cook-Cottone