Sleep Patterns and Affect Dynamics Among College Students During the COVID-19 Pandemic: Intensive Longitudinal Study.

BACKGROUND: Sleep disturbance is a transdiagnostic risk factor that is so prevalent among young adults that it is considered a public health epidemic, which has been exacerbated by the COVID-19 pandemic. Sleep may contribute to mental health via affect dynamics. Prior literature on the contribution of sleep to affect is largely based on correlational studies or experiments that do not generalize to the daily lives of young adults. Furthermore, the literature examining the associations between sleep variability and affect dynamics remains scant. OBJECTIVE: In an ecologically valid context, using an intensive longitudinal design, we aimed to assess the daily and long-term associations between sleep patterns and affect dynamics among young adults during the COVID-19 pandemic. METHODS: College student participants (N=20; female: 13/20, 65%) wore an Oura ring (Oura Health Ltd) continuously for 3 months to measure sleep patterns, such as average and variability in total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, and sleep onset latency (SOL), resulting in 1173 unique observations. We administered a daily ecological momentary assessment by using a mobile health app to evaluate positive affect (PA), negative affect (NA), and COVID-19 worry once per day. RESULTS: Participants with a higher sleep onset latency (b=-1.09, SE 0.36; P=.006) and TST (b=-0.15, SE 0.05; P=.008) on the prior day had lower PA on the next day. Further, higher average TST across the 3-month period predicted lower average PA (b=-0.36, SE 0.12; P=.009). TST variability predicted higher affect variability across all affect domains. Specifically, higher variability in TST was associated higher PA variability (b=0.09, SE 0.03; P=.007), higher negative affect variability (b=0.12, SE 0.05; P=.03), and higher COVID-19 worry variability (b=0.16, SE 0.07; P=.04). CONCLUSIONS: Fluctuating sleep patterns are associated with affect dynamics at the daily and long-term scales. Low PA and affect variability may be potential pathways through which sleep has implications for mental health.

Using Multimodal Assessments to Capture Personalized Contexts of College Student Well-being in 2020: Case Study.

BACKGROUND: The year 2020 has been challenging for many, particularly for young adults who have been adversely affected by the COVID-19 pandemic. Emerging adulthood is a developmental phase with significant changes in the patterns of daily living; it is a risky phase for the onset of major mental illness. College students during the pandemic face significant risk, potentially losing several protective factors (eg, housing, routine, social support, job, and financial security) that are stabilizing for mental health and physical well-being. Individualized multiple assessments of mental health, referred to as multimodal personal chronicles, present an opportunity to examine indicators of health in an ongoing and personalized way using mobile sensing devices and wearable internet of things. OBJECTIVE: To assess the feasibility and provide an in-depth examination of the impact of the COVID-19 pandemic on college students through multimodal personal chronicles, we present a case study of an individual monitored using a longitudinal subjective and objective assessment approach over a 9-month period throughout 2020, spanning the prepandemic period of January through September. METHODS: The individual, referred to as Lee, completed psychological assessments measuring depression, anxiety, and loneliness across 4 time points in January, April, June, and September. We used the data emerging from the multimodal personal chronicles (ie, heart rate, sleep, physical activity, affect, behaviors) in relation to psychological assessments to understand patterns that help to explicate changes in the individual's psychological well-being across the pandemic. RESULTS: Over the course of the pandemic, Lee's depression severity was highest in April, shortly after shelter-in-place orders were mandated. His depression severity remained mildly severe throughout the rest of the months. Associations in positive and negative affect, physiology, sleep, and physical activity patterns varied across time periods. Lee's positive affect and negative affect were positively correlated in April (r=0.53, P=.04) whereas they were negatively correlated in September (r=-0.57, P=.03). Only in the month of January was sleep negatively associated with negative affect (r=-0.58, P=.03) and diurnal beats per minute (r=-0.54, P=.04), and then positively associated with heart rate variability (resting root mean square of successive differences between normal heartbeats) (r=0.54, P=.04). When looking at his available contextual data, Lee noted certain situations as supportive coping factors and other situations as potential stressors. CONCLUSIONS: We observed more pandemic concerns in April and noticed other contextual events relating to this individual's well-being, reflecting how college students continue to experience life events during the pandemic. The rich monitoring data alongside contextual data may be beneficial for clinicians to understand client experiences and offer personalized treatment plans. We discuss benefits as well as future directions of this system, and the conclusions we can draw regarding the links between the COVID-19 pandemic and college student mental health.

Assessing the Mental Health of Emerging Adults Through a Mental Health App: Protocol for a Prospective Pilot Study.

BACKGROUND: Individuals can experience different manifestations of the same psychological disorder. This underscores the need for a personalized model approach in the study of psychopathology. Emerging adulthood is a developmental phase wherein individuals are especially vulnerable to psychopathology. Given their exposure to repeated stressors and disruptions in routine, the emerging adult population is worthy of investigation. OBJECTIVE: In our prospective study, we aim to conduct multimodal assessments to determine the feasibility of an individualized approach for understanding the contextual factors of changes in daily affect, sleep, physiology, and activity. In other words, we aim to use event mining to predict changes in mental health. METHODS: We expect to have a final sample size of 20 participants. Recruited participants will be monitored for a period of time (ie, between 3 and 12 months). Participants will download the Personicle app on their smartphone to track their activities (eg, home events and cycling). They will also be given wearable sensor devices (ie, devices that monitor sleep, physiology, and physical activity), which are to be worn continuously. Participants will be asked to report on their daily moods and provide open-ended text responses on a weekly basis. Participants will be given a battery of questionnaires every 3 months. RESULTS: Our study has been approved by an institutional review board. The study is currently in the data collection phase. Due to the COVID-19 pandemic, the study was adjusted to allow for remote data collection and COVID-19-related stress assessments. CONCLUSIONS: Our study will help advance research on individualized approaches to understanding health and well-being through multimodal systems. Our study will also demonstrate the benefit of using individualized approaches to study interrelations among stress, social relationships, technology, and mental health. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/25775.

Quantitative Proteomic Analysis of Germination of Nosema bombycis Spores under Extremely Alkaline Conditions.

The microsporidian Nosema bombycis is an obligate intracellular pathogen of the silkworm Bombyx mori, causing the epidemic disease Pebrine and extensive economic losses in sericulture. Although N. bombycis forms spores with rigid spore walls that protect against various environmental pressures, ingested spores germinate immediately under the extremely alkaline host gut condition (Lepidoptera gut pH > 10.5), which is a key developmental turning point from dormant state to infected state. However, to date this process remains poorly understood due to the complexity of the animal digestive tract and the lack of genetic tools for microsporidia. Here we show, using an in vitro spore germination model, how the proteome of N. bombycis changes during germination, analyse specific metabolic pathways employed in detail, and validate key functional proteins in vivo in silkworms. By a label-free quantitative proteomics approach that is directly based on high-resolution mass spectrometry (MS) data, a total of 1136 proteins were identified with high confidence, with 127 proteins being significantly changed in comparison to non-germinated spores. Among them, structural proteins including polar tube protein 1 and 3 and spore wall protein (SWP) 4 and 30 were found to be significantly down-regulated, but SWP9 significantly up-regulated. Some nucleases like polynucleotide kinase/phosphatase and flap endonucleases 1, together with a panel of hydrolases involved in protein degradation and RNA cleavage were overrepresented too upon germination, which implied that they might play important roles during spore germination. The differentially regulated trends of these genes were validated, respectively, by quantitative RT-PCR and 3 proteins of interest were confirmed by Western blotting analyses in vitro and in vivo. Furthermore, the pathway analysis showed that abundant up- and down-regulations appear involved in the glycolysis, pentose phosphate pathway, purine, and pyrimidine metabolism, suggesting preparations of energy generation and substance synthesis for the following invasion and proliferation inside the host. This report, to our knowledge, provides the first proteomic landscape of N. bombycis spores, and also a stepping stone on the way to further study of the unique infection mode of this economically important pathogen and other microsporidia in general.

Biodiversity and Activity of the Gut Microbiota across the Life History of the Insect Herbivore Spodoptera littoralis.

Microbes that live inside insects play critical roles in host nutrition, physiology, and behavior. Although Lepidoptera (butterflies and moths) are one of the most diverse insect taxa, their microbial symbionts are little-studied, particularly during metamorphosis. Here, using ribosomal tag pyrosequencing of DNA and RNA, we investigated biodiversity and activity of gut microbiotas across the holometabolous life cycle of Spodoptera littoralis, a notorious agricultural pest worldwide. Proteobacteria and Firmicutes dominate but undergo a structural "metamorphosis" in tandem with its host. Enterococcus, Pantoea and Citrobacter were abundant and active in early-instar, while Clostridia increased in late-instar. Interestingly, only enterococci persisted through metamorphosis. Female adults harbored high proportions of Enterococcus, Klebsiella and Pantoea, whereas males largely shifted to Klebsiella. Comparative functional analysis with PICRUSt indicated that early-instar larval microbiome was more enriched for genes involved in cell motility and carbohydrate metabolism, whereas in late-instar amino acid, cofactor and vitamin metabolism increased. Genes involved in energy and nucleotide metabolism were abundant in pupae. Female adult microbiome was enriched for genes relevant to energy metabolism, while an increase in the replication and repair pathway was observed in male. Understanding the metabolic activity of these herbivore-associated microbial symbionts may assist the development of novel pest-management strategies.