Inferring causality in biological oscillators.

MOTIVATION: Fundamental to biological study is identifying regulatory interactions. The recent surge in time-series data collection in biology provides a unique opportunity to infer regulations computationally. However, when components oscillate, model-free inference methods, while easily implemented, struggle to distinguish periodic synchrony and causality. Alternatively, model-based methods test the reproducibility of time series given a specific model but require inefficient simulations and have limited applicability. RESULTS: We develop an inference method based on a general model of molecular, neuronal and ecological oscillatory systems that merges the advantages of both model-based and model-free methods, namely accuracy, broad applicability and usability. Our method successfully infers the positive and negative regulations within various oscillatory networks, e.g. the repressilator and a network of cofactors at the pS2 promoter, outperforming popular inference methods. AVAILABILITY AND IMPLEMENTATION: We provide a computational package, ION (Inferring Oscillatory Networks), that users can easily apply to noisy, oscillatory time series to uncover the mechanisms by which diverse systems generate oscillations. Accompanying MATLAB code under a BSD-style license and examples are available at https://github.com/Mathbiomed/ION. Additionally, the code is available under a CC-BY 4.0 License at https://doi.org/10.6084/m9.figshare.16431408.v1. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Revisiting a synthetic intracellular regulatory network that exhibits oscillations.

In 2000, Elowitz and Leibler introduced the repressilator-a synthetic gene circuit with three genes that cyclically repress transcription of the next gene-as well as a corresponding mathematical model. Experimental data and model simulations exhibited oscillations in the protein concentrations across generations. Müller et al. (J Math Biol 53(6):905-937, 2006) generalized the model to an arbitrary number of genes and analyzed the resulting dynamics. Their new model arose from five key assumptions, two of which are restrictive given current biological knowledge. Accordingly, we propose a new repressilator system that allows for general functions to model transcription, degradation, and translation. We prove that, with an odd number of genes, the new model has a unique steady state and the system converges to this steady state or to a periodic orbit. We also give a necessary and sufficient condition for stability of steady states when the number of genes is even and conjecture a condition for stability for an odd number. Finally, we derive a new rate function describing transcription that arises under more reasonable biological assumptions than the widely used single-step binding assumption. With this new transcription-rate function, we compare the model's amplitude and period with that of a model with the conventional transcription-rate function. Taken together, our results enhance our understanding of genetic regulation by repression.

Pliocene reversal of late Neogene aridification.

The Pliocene epoch (5.3-2.6 Ma) represents the most recent geological interval in which global temperatures were several degrees warmer than today and is therefore considered our best analog for a future anthropogenic greenhouse world. However, our understanding of Pliocene climates is limited by poor age control on existing terrestrial climate archives, especially in the Southern Hemisphere, and by persistent disagreement between paleo-data and models concerning the magnitude of regional warming and/or wetting that occurred in response to increased greenhouse forcing. To address these problems, here we document the evolution of Southern Hemisphere hydroclimate from the latest Miocene to the middle Pliocene using radiometrically-dated fossil pollen records preserved in speleothems from semiarid southern Australia. These data reveal an abrupt onset of warm and wet climates early within the Pliocene, driving complete biome turnover. Pliocene warmth thus clearly represents a discrete interval which reversed a long-term trend of late Neogene cooling and aridification, rather than being simply the most recent period of greater-than-modern warmth within a continuously cooling trajectory. These findings demonstrate the importance of high-resolution chronologies to accompany paleoclimate data and also highlight the question of what initiated the sustained interval of Pliocene warmth.

Post-mortem oxygen isotope exchange within cultured diatom silica.

RATIONALE: Potential post-mortem alteration to the oxygen isotope composition of biogenic silica is critical to the validity of palaeoclimate reconstructions based on oxygen isotope ratios (δ18 O values) from sedimentary silica. We calculate the degree of oxygen isotope alteration within freshly cultured diatom biogenic silica in response to heating and storing in the laboratory. METHODS: The experiments used freshly cultured diatom silica. Silica samples were either stored in water or dried at temperatures between 20 °C and 80 °C. The mass of affected oxygen and the associated silica-water isotope fractionation during alteration were calculated by conducting parallel experiments using endmember waters with δ18 O values of -6.3 to -5.9 ‰ and -36.3 to -35.0 ‰. Dehydroxylation and subsequent oxygen liberation were achieved by stepwise fluorination with BrF5 . The 18 O/16 O ratios were measured using a ThermoFinnigan MAT 253 isotope ratio mass spectrometer. RESULTS: Significant alterations in silica δ18 O values were observed, most notably an increase in the δ18 O values following drying at 40-80 °C. Storage in water for 7 days between 20 and 80 °C also led to significant alteration in δ18 O values. Mass balance calculations suggest that the amount of affected oxygen is positively correlated with temperature. The estimated oxygen isotope fractionation during alteration is an inverse function of temperature, consistent with the extrapolation of models for high-temperature silica-water oxygen isotope fractionation. CONCLUSIONS: Routinely used preparatory methods may impart significant alterations to the δ18 O values of biogenic silica, particularly when dealing with modern cultured or field-collected material. The significance of such processes within natural aquatic environments is uncertain; however, there is potential that similar processes also affect sedimentary diatoms, with implications for the interpretation of biogenic silica-hosted δ18 O palaeoclimate records.

Carbon isotope discrimination in leaves of the broad-leaved paperbark tree, Melaleuca quinquenervia, as a tool for quantifying past tropical and subtropical rainfall.

Quantitative reconstructions of terrestrial climate are highly sought after but rare, particularly in Australia. Carbon isotope discrimination in plant leaves (Δleaf ) is an established indicator of past hydroclimate because the fractionation of carbon isotopes during photosynthesis is strongly influenced by water stress. Leaves of the evergreen tree Melaleuca quinquenervia have been recovered from the sediments of some perched lakes on North Stradbroke and Fraser Islands, south-east Queensland, eastern Australia. Here, we examine the potential for using M. quinquenervia ∆leaf as a tracer of past rainfall by analysing carbon isotope ratios (δ(13) C) of modern leaves. We firstly assess Δleaf variation at the leaf and stand scale and find no systematic pattern within leaves or between leaves due to their position on the tree. We then examine the relationships between climate and Δleaf for a 11-year time series of leaves collected in a litter tray. M. quinquenervia retains its leaves for 1-4 years; thus, cumulative average climate data are used. There is a significant relationship between annual mean ∆leaf and mean annual rainfall of the hydrological year for 1-4 years (i.e. 365-1460 days) prior to leaf fall (r(2)  = 0.64, P = 0.003, n = 11). This relationship is marginally improved by accounting for the effect of pCO2 on discrimination (r(2)  = 0.67, P = 0.002, n = 11). The correlation between rainfall and Δleaf , and the natural distribution of Melaleuca quinquenervia around wetlands of eastern Australia, Papua New Guinea and New Caledonia offers significant potential to infer past rainfall on a wide range of spatial and temporal scales.

An algorithm to identify patients aged 0-3 with rare genetic disorders.

BACKGROUND: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders. RESULTS: Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy. CONCLUSIONS: The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.

Does active participation via integrated questions in large lectures matter?

This paper investigates whether the intensity of participation in large lecture quizzes in a tertiary education context, facilitated and monitored by an online platform, is associated with better examination performance. The platform mirrors lecture slides onto student devices and uses integrated "clicker" style questions within the lecture to quiz students on concepts learned. Using regression, we find that the intensity of quiz participation is positively related to students' performance. Student study perceptions, based on study and career plans, moderate the results. These findings are relevant to educators, especially in a post-COVID-19 learning environment, where the online quiz function could be used to foster participation.

A structured, telephone-delivered intervention to reduce methamphetamine use: study protocol for a parallel-group randomised controlled trial.

BACKGROUND: Australia has one of the highest rates of methamphetamine (MA) use in the world; however, uptake of in-person psychological treatment remains extremely low due to numerous individual (e.g. stigma, shame) and structural (e.g. service accessibility, geographical location) barriers to accessing care. Telephone-delivered interventions are ideally placed to overcome many of the known barriers to treatment access and delivery. This randomised controlled trial (RCT) will examine the efficacy of a standalone, structured telephone-delivered intervention to reduce MA problem severity and related harms. METHODS: This study is a double-blind, parallel-group RCT. We will recruit 196 ± 8 individuals with mild to moderate MA use disorder from across Australia. After eligibility and baseline assessments, participants will be randomly allocated to receive either the Ready2Change-Methamphetamine (R2C-M) intervention (n = 98 ± 4; four to six telephone-delivered intervention sessions, R2C-M workbooks and MA information booklet) or control (n = 98 ± 4; four to six ≤5-min telephone check-ins and MA information booklet including information on accessing further support). Telephone follow-up assessments will occur at 6 weeks and 3, 6 and 12 months post-randomisation. The primary outcome is change in MA problem severity (Drug Use Disorders Identification Test, DUDIT) at 3 months post-randomisation. Secondary outcomes are as follows: MA problem severity (DUDIT) at 6 and 12 months post-randomisation, amount of methamphetamine used, methamphetamine use days, methamphetamine use disorder criteria met, cravings, psychological functioning, psychotic-like experiences, quality of life and other drug use days (at some or all timepoints of 6 weeks and 3, 6 and 12 months post-randomisation). Mixed-methods program evaluation will be performed and cost-effectiveness will be examined. DISCUSSION: This study will be the first RCT internationally to assess the efficacy of a telephone-delivered intervention for MA use disorder and related harms. The proposed intervention is expected to provide an effective, low-cost, scalable treatment for individuals otherwise unlikely to seek care, preventing future harms and reducing health service and community costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT04713124 . Pre-registered on 19 January 2021.

Evolution of the repression mechanisms in circadian clocks.

BACKGROUND: Circadian (daily) timekeeping is essential to the survival of many organisms. An integral part of all circadian timekeeping systems is negative feedback between an activator and repressor. However, the role of this feedback varies widely between lower and higher organisms. RESULTS: Here, we study repression mechanisms in the cyanobacterial and eukaryotic clocks through mathematical modeling and systems analysis. We find a common mathematical model that describes the mechanism by which organisms generate rhythms; however, transcription's role in this has diverged. In cyanobacteria, protein sequestration and phosphorylation generate and regulate rhythms while transcription regulation keeps proteins in proper stoichiometric balance. Based on recent experimental work, we propose a repressor phospholock mechanism that models the negative feedback through transcription in clocks of higher organisms. Interestingly, this model, when coupled with activator phosphorylation, allows for oscillations over a wide range of protein stoichiometries, thereby reconciling the negative feedback mechanism in Neurospora with that in mammals and cyanobacteria. CONCLUSIONS: Taken together, these results paint a picture of how circadian timekeeping may have evolved.

Ready2Change: Preliminary effectiveness of a telephone-delivered intervention program for alcohol, methamphetamine and cannabis use problems.

INTRODUCTION: Telehealth has considerable potential to overcome many of the barriers to accessing care for substance use problems, thereby increasing the opportunity for earlier intervention. The Ready2Change program is a multiple-session outbound telephone-delivered cognitive and behavioural intervention for mild-to-moderate substance use disorders, embedded within a long-established 24/7 alcohol and drug helpline. We sought to analyse routinely collected program data in a preliminary study to examine the effectiveness of Ready2Change in reducing substance use problem severity and psychological distress. METHODS: A retrospective analysis of program data from December 2013 to June 2018 was performed. Analysed cases were 249 clients living in Victoria, Australia with alcohol (n = 191), methamphetamine (n = 40) or cannabis (n = 18) as their primary drug of concern. A within-subjects design was used to examine pre- and post-intervention substance use problem severity and psychological distress. RESULTS: For alcohol cases, there was a statistically significant decrease in alcohol problem severity [AUDIT, mean difference = -12.7, 95% confidence interval (CI) -14.0, -11.5]. Statistically significant reductions in drug problem severity (DUDIT) were observed for methamphetamine (mean difference = -17.3, 95% CI -20.9, -13.7) and cannabis (mean difference = -15.9, 95% CI -22.3, -9.6) cases. All groups showed reductions in problem severity for other substances used (P < 0.05) and psychological distress (P < 0.001). DISCUSSION AND CONCLUSIONS: Results suggest Ready2Change benefits clients with alcohol, methamphetamine and cannabis use problems, with the potential to improve treatment access for health inequity groups including those living in remote areas. These findings warrant further investigation into the effectiveness of this program.

Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression.

Consumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate. This work establishes an innovative data analytic approach to monitor disease progression remotely using consumer-grade wearables.

Effectiveness of a Stand-alone Telephone-Delivered Intervention for Reducing Problem Alcohol Use: A Randomized Clinical Trial.

Importance: Despite the magnitude of alcohol use problems globally, treatment uptake remains low. Telephone-delivered interventions have potential to overcome many structural and individual barriers to help seeking, yet their effectiveness as a stand-alone treatment for problem alcohol use has not been established. Objective: To examine the effectiveness of the Ready2Change telephone-delivered intervention in reducing alcohol problem severity up to 3 months among a general population sample. Design, Setting, and Participants: This double-blind, randomized clinical trial recruited participants with an Alcohol Use Disorders Identification Test (AUDIT) score of greater than 6 (for female participants) and 7 (for male participants) from across Australia during the period of May 25, 2018, to October 2, 2019. Telephone assessments occurred at baseline and 3 months after baseline (84.9% retention). Data collection was finalized September 2020. Interventions: The telephone-based cognitive and behavioral intervention comprised 4 to 6 telephone sessions with a psychologist. The active control condition comprised four 5-minute telephone check-ins from a researcher and alcohol and stress management pamphlets. Main Outcomes and Measures: The primary outcome was change in alcohol problem severity, measured with the AUDIT total score. Drinking patterns were measured with the Timeline Followback (TLFB) instrument. Results: This study included a total of 344 participants (mean [SD] age, 39.9 [11.4] years; range, 18-73 years; 177 male participants [51.5%]); 173 participants (50.3%) composed the intervention group, and 171 participants (49.7%) composed the active control group. Less than one-third of participants (101 [29.4%]) had previously sought alcohol treatment, despite a high mean (SD) baseline AUDIT score of 21.5 (6.3) and 218 (63.4%) scoring in the probable dependence range. For the primary intention-to-treat analyses, there was a significant decrease in AUDIT total score from baseline to 3 months in both groups (intervention group decrease, 8.22; 95% CI, 7.11-9.32; P < .001; control group decrease, 7.13; 95% CI, 6.10-8.17; P < .001), but change over time was not different between groups (difference, 1.08; 95% CI, -0.43 to 2.59; P = .16). In secondary analyses, the intervention group showed a significantly greater reduction in the AUDIT hazardous use domain relative to the control group at 3 months (difference, 0.58; 95% CI, 0.02-1.14; P = .04). A greater reduction in AUDIT total score was observed for the intervention group relative to the control group when adjusting for exposure to 2 or more sessions (difference, 3.40; 95% CI, 0.36-6.44; P = .03) but not 1 or more sessions (per-protocol analysis). Conclusions and Relevance: Based on the primary outcome, AUDIT total score, this randomized clinical trial did not find superior effectiveness of this telephone-based cognitive and behavioral intervention compared with active control. However, the intervention was effective in reducing hazardous alcohol use and reduced alcohol problem severity when 2 or more sessions were delivered. Trial outcomes demonstrate the potential benefits of this highly scalable and accessible model of alcohol treatment. Trial Registration: ANZCTR Identifier: ACTRN12618000828224.

Inpatient Administration of Alpha-1-Adrenergic Receptor Blocking Agents Reduces Mortality in Male COVID-19 Patients.

Apha-1-adrenergic receptor antagonists (α1-blockers) can suppress pro-inflammatory cytokines, thereby potentially improving outcomes among patients with COVID-19. Accordingly, we evaluated the association between α1-blocker exposure (before or during hospitalization) and COVID-19 in-hospital mortality. We identified 2,627 men aged 45 or older who were admitted to Mount Sinai hospitals with COVID-19 between February 24 and May 31, 2020, in New York. Men exposed to α1-blockers (N = 436) were older (median age 73 vs. 64 years, P < 0.001) and more likely to have comorbidities than unexposed men (N = 2,191). Overall, 777 (29.6%) patients died in hospital, and 1,850 (70.4%) were discharged. Notably, we found that α1-blocker exposure was independently associated with improved in-hospital mortality in a multivariable logistic analysis (OR 0.699; 95% CI, 0.498-0.982; P = 0.039) after adjusting for patient demographics, comorbidities, and baseline vitals and labs. The protective effect of α1-blockers was stronger among patients with documented inpatient exposure to α1-blockers (OR 0.624; 95% CI 0.431-0.903; P = 0.012). Finally, age-stratified analyses suggested variable benefit from inpatient α1-blocker across age groups: Age 45-65 OR 0.483, 95% CI 0.216-1.081 (P = 0.077); Age 55-75 OR 0.535, 95% CI 0.323-0.885 (P = 0.015); Age 65-89 OR 0.727, 95% CI 0.484-1.092 (P = 0.124). Taken together, clinical trials to assess the therapeutic value of α1-blockers for COVID-19 complications are warranted.

Genomic heterogeneity affects the response to Daylight Saving Time.

Circadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual's ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well.

Magnetic resonance imaging analysis of human skull diploic venous anatomy.

BACKGROUND: The skull diploic venous space (DVS) represents a potential route for cerebrospinal fluid (CSF) diversion and absorption in the treatment of hydrocephalus. The goal of this study was to carry out a detailed characterization of the drainage pattern of the DVS of the skull using high-resolution MRI, especially the diploic veins draining to the lacunae laterales (LLs) since the LLs constitute an important channel for the CSF to access the superior sagittal sinus and subsequently the systemic circulation. The objective was to identify those skull regions optimally suited for an intraosseous CSF diversion system. METHODS: High-resolution, T1-weighted MRI scans from 20 adult and 16 pediatric subjects were selected for analysis. Skulls were divided into four regions, that is, frontal, parietal, temporal, and occipital. On each scan, a trained observer counted all diploic veins in every skull region. Each diploic vein was also followed to determine its final drainage pathway (i.e., dural venous sinus, dural vein, LL, or indeterminate). RESULTS: In the adult age group, the frontal and occipital skull regions showed the highest number of diploic veins. However, the highest number of draining diploic veins connecting to the lacunae lateralis was found in the frontal and parietal skull region, just anterior and just posterior to the coronal suture. In the pediatric age group, the parietal skull region, just posterior to the coronal suture, showed the highest overall number of diploic veins and also the highest number of draining diploic veins connecting to the LL. CONCLUSION: This study suggested that diploic venous density across the skull varies with age, with more parietal diploic veins in the pediatric age range, and more occipital and frontal diploic veins in adults. If the DVS is ultimately used for CSF diversion, our anatomical data point to optimal sites for the insertion of specially designed intraosseous infusion devices for the treatment of hydrocephalus. Likely the optimal sites for CSF diversion would be the parietal region just posterior to the coronal suture in children, and in adults, frontal and/or parietal just anterior or just posterior to the coronal suture.

Distinct Circadian Assessments From Wearable Data Reveal Social Distancing Promoted Internal Desynchrony Between Circadian Markers.

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body.

A method for characterizing daily physiology from widely used wearables.

Millions of wearable-device users record their heart rate (HR) and activity. We introduce a statistical method to extract and track six key physiological parameters from these data, including an underlying circadian rhythm in HR (CRHR), the direct effects of activity, and the effects of meals, posture, and stress through hormones like cortisol. We test our method on over 130,000 days of real-world data from medical interns on rotating shifts, showing that CRHR dynamics are distinct from those of sleep-wake or physical activity patterns and vary greatly among individuals. Our method also estimates a personalized phase-response curve of CRHR to activity for each individual, representing a passive and personalized determination of how human circadian timekeeping continually changes due to real-world stimuli. We implement our method in the "Social Rhythms" iPhone and Android app, which anonymously collects data from wearable-device users and provides analysis based on our method.

Monitoring beliefs and physiological measures in students at risk for COVID-19 using wearable sensors and smartphone technology: Protocol for a mobile health study.

BACKGROUND: The COVID-19 pandemic has impacted lives significantly and greatly affected an already vulnerable population, college students, in relation to mental health and public safety. Social distancing and isolation have brought about challenges to student's mental health. Mobile health apps and wearable sensors may help to monitor students at risk for COVID-19 and support their mental well-being. OBJECTIVE: Through the use of a wearable sensor and smartphone-based survey completion, this study aimed to monitor students at risk for COVID-19. METHODS: We conducted a prospective study of students, undergraduate and graduate, at a public university in the Midwest. Students were instructed to download the Fitbit, Social Rhythms, and Roadmap 2.0 apps onto their personal mobile devices (Android or iOS). Subjects consented to provide up to 10 saliva samples during the study period. Surveys were administered through the Roadmap 2.0 app at five timepoints - at baseline, 1-month later, 2-months later, 3-months later, and at study completion. The surveys gathered information regarding demographics, COVID-19 diagnoses and symptoms, and mental health resilience, with the aim of documenting the impact of COVID-19 on the college student population. RESULTS: This study enrolled 2,158 college students between September 2020 and January 2021. Subjects are currently being followed on-study for one academic year. Data collection and analysis are ongoing. CONCLUSIONS: This study examined student health and well-being during the COVID-19 pandemic. It also assessed the feasibility of wearable sensor use and survey completion in a college student population, which may inform the role of our mobile health tools on student health and well-being. Finally, using wearable sensor data, biospecimen collection, and self-reported COVID-19 diagnosis, our results may provide key data towards the development of a model for the early prediction and detection of COVID-19. CLINICALTRIAL: ClinicalTrials.gov NCT04766788.

Monitoring Health Care Workers at Risk for COVID-19 Using Wearable Sensors and Smartphone Technology: Protocol for an Observational mHealth Study.

BACKGROUND: Health care workers (HCWs) have been working on the front lines of the COVID-19 pandemic with high risks of viral exposure, infection, and transmission. Standard COVID-19 testing is insufficient to protect HCWs from these risks and prevent the spread of disease. Continuous monitoring of physiological data with wearable sensors, self-monitoring of symptoms, and asymptomatic COVID-19 testing may aid in the early detection of COVID-19 in HCWs and may help reduce further transmission among HCWs, patients, and families. OBJECTIVE: By using wearable sensors, smartphone-based symptom logging, and biospecimens, this project aims to assist HCWs in self-monitoring COVID-19. METHODS: We conducted a prospective, longitudinal study of HCWs at a single institution. The study duration was 1 year, wherein participants were instructed on the continuous use of two wearable sensors (Fitbit Charge 3 smartwatch and TempTraq temperature patches) for up to 30 days. Participants consented to provide biospecimens (ie, nasal swabs, saliva swabs, and blood) for up to 1 year from study entry. Using a smartphone app called Roadmap 2.0, participants entered a daily mood score, submitted daily COVID-19 symptoms, and completed demographic and health-related quality of life surveys at study entry and 30 days later. Semistructured qualitative interviews were also conducted at the end of the 30-day period, following completion of daily mood and symptoms reporting as well as continuous wearable sensor use. RESULTS: A total of 226 HCWs were enrolled between April 28 and December 7, 2020. The last participant completed the 30-day study procedures on January 16, 2021. Data collection will continue through January 2023, and data analyses are ongoing. CONCLUSIONS: Using wearable sensors, smartphone-based symptom logging and survey completion, and biospecimen collections, this study will potentially provide data on the prevalence of COVID-19 infection among HCWs at a single institution. The study will also assess the feasibility of leveraging wearable sensors and self-monitoring of symptoms in an HCW population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04756869; https://clinicaltrials.gov/ct2/show/NCT04756869. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/29562.

Real-time, personalized medicine through wearable sensors and dynamic predictive modeling: a new paradigm for clinical medicine.

Accurately predicting the onset and course of a disease in an individual is a major unmet challenge in medicine due to the complex and dynamic nature of disease progression. Continuous data from wearable technologies and biomarker data with a fine time resolution provide a unique opportunity to learn more about disease evolution and to usher in a new era of personalized and real-time medicine. Herein, we propose the potential of real-time, continuously measured physiological data as a noninvasive biomarker approach for detecting disease transitions, using allogeneic hematopoietic stem cell transplant (HCT) patient care as an example. Additionally, we review a recent computational technique, the landscape dynamic network biomarker method, that uses biomarker data to identify transition states in disease progression and explore how to use it with both biomarker and physiological data for earlier detection of graft-versus-host disease specifically. Throughout, we argue that increased collaboration across multiple fields is essential to realizing the full potential of wearable and biomarker data in a new paradigm of personalized and real-time medicine.