Traveling Waves in Quasi-One-Dimensional Neuronal Minicolumns

Traveling waves of neuronal activity in the cortex have been observed in vivo. These traveling waves have been correlated to various features of observed cortical dynamics, including spike timing variability and correlated fluctuations in neuron membrane potential. Although traveling waves are typically studied as either strictly one-dimensional or two-dimensional excitations, here we investigate the conditions for the existence of quasi-one-dimensional traveling waves that could be sustainable in parts of the brain containing cortical minicolumns. For that, we explore a quasi-one-dimensional network of heterogeneous neurons with a biologically influenced computational model of neuron dynamics and connectivity. We find that background stimulus reliably evokes traveling waves in networks with local connectivity between neurons. We also observe traveling waves in fully connected networks when a model for action potential propagation speed is incorporated. The biological properties of the neurons influence the generation and propagation of the traveling waves. Our quasi-one-dimensional model is not only useful for studying the basic properties of traveling waves in neuronal networks; it also provides a simplified representation of possible wave propagation in columnar or minicolumnar networks found in the cortex.

P089 Loneliness and sleep duration among healthy older adults in Southeast Queensland, Australia

Introduction The relationship between sleep duration and loneliness among healthy older adults is not fully understood. Shorter sleep duration and increased variability of sleep timing (sleep onset and wake time) have recently been shown to have adverse health outcomes in younger adults. While physiological stressors associated with loneliness are likely distinct, we hypothesise that older adults who identify as lonely have reduced sleep duration and increased variability of sleep timing. Methods Older individuals (N=60) without significant co-morbidities were recruited via convenience sampling. Participants completed the de Jong Giervield Loneliness Scale and wore an actigraph for up to 2 weeks. Sleep metrics from actigraphy (sleep onset and wake times, and SD) were determined by algorithm assisted human scoring. Results Valid data was retrieved from N=37 participants (age 83±6.8 years [mean±SD]). There were no significant differences in demographics between those in the lonely (N=19) and not lonely (N=18) groupings. There was substantial heterogeneity in individual participant’s sleep metrics, both within and between groupings. The average sleep onset time was similar between groups, however lonely participants typically woke earlier resulting in slightly shorter sleep duration. Variability in sleep onset and wake times was reduced in lonely participants. Discussion While shorter sleep duration was expected, we did not anticipate the reduction in sleep timing variability amongst those defined as lonely; more regular sleep periods have previously been associated with better outcomes. We did not see statistically significant differences between our groups, possibly due to sample size limitations, however, the unexpected trend warrants further investigation.

Comprehensive analysis of DNA replication timing in genetic diseases and gene knockouts identifies MCM10 as a novel regulator of the replication program

Cellular proliferation depends on the accurate and timely replication of the genome. Several genetic diseases are caused by mutations in key DNA replication genes; however, it remains unclear whether these genes influence the normal program of DNA replication timing. Similarly, the factors that regulate DNA replication dynamics are poorly understood. To systematically identify trans-acting modulators of replication timing, we profiled replication in 184 cell lines from three cell types, encompassing 60 different gene knockouts or genetic diseases. Through a rigorous approach that considers the background variability of replication timing, we concluded that most samples displayed normal replication timing. However, mutations in two genes showed consistently abnormal replication timing. The first gene was RIF1, a known modulator of replication timing. The second was MCM10, a highly conserved member of the pre-replication complex. MCM10 mutant cells demonstrated replication timing variability comprising 46% of the genome and at different locations than RIF1 knockouts. Replication timing alterations in MCM10-mutant cells was predominantly comprised of replication initiation defects. Taken together, this study demonstrates the remarkable robustness of the human replication timing program and reveals MCM10 as a novel modulator of DNA replication timing.

Rapid changes in overnight blood pressure after transitioning to early-morning shiftwork

Risk for adverse cardiovascular events increases when blood pressure does not decrease at night (“non-dipping”, <10% decrease from daytime blood pressure). Shiftwork alters relationships between behaviors and endogenous circadian rhythms (i.e., circadian disruption along with variable sleep timing), and chronic shiftwork increases cardiovascular disease risk. To determine whether transitioning into shiftwork changes the overnight blood pressure dipping pattern, we leveraged a natural experiment that occurs when newly-hired bus operators transition from a daytime training schedule into an early-morning shiftwork or daywork schedule. Twenty participants were studied in a 90-day protocol upon new employment and underwent cardio-metabolic health assessments, including ambulatory blood pressure monitoring, and weekly sleep-wake diaries. Measurements were repeated after ~30 and 90 days after transitioning to a day or an early-morning shiftwork schedule. Newly-hired shiftworkers displayed dramatic changes in overnight blood pressure, with 62% converting from a healthy dipping blood pressure to the non-dipping pattern, resulting in 93% of shiftworkers displaying a non-dipping phenotype at 90-days. In contrast, 50% of dayworkers had a non-dipping profile at baseline and this decreased to 0% at 90-days, a significant difference from shiftworkers (p=0.001). At 90-days, overnight blood pressure dipping was ~7% less in shiftworkers than dayworkers (-6.3% [95%CI -3.7 to -8.8%] vs -13.1% [-10.3 to -15.9%]: p<0.01), with changes in dipping associated with changes in sleep timing variability (r 2=0.28, p=0.03). The observed changes in overnight blood pressure dipping in newly-hired early-morning shiftworkers, which were associated with sleep timing variability, may be an early warning sign of increased cardiovascular risk among shiftworkers.

High-throughput analysis of DNA replication in single human cells reveals constrained variability in the location and timing of replication initiation

DNA replication occurs throughout the S phase of the cell cycle, initiating from replication origin loci that fire at different times. Debate remains about whether origins are a fixed set of loci used across all cells or a loose agglomeration of potential origins used stochastically in individual cells, and about how consistent their firing time during S phase is across cells. Here, we develop an approach for profiling DNA replication in single human cells and apply it to 2,305 replicating cells spanning the entire S phase. The resolution and scale of the data enabled us to specifically analyze initiation sites and show that these sites have confined locations that are consistently used among individual cells. Further, we find that initiation sites are activated in a similar, albeit not fixed, order across cells. Taken together, our results suggest that replication timing variability is constrained both spatially and temporally, and that the degree of variation is consistent across human cell lines.

214 Longitudinal Changes in Sleep Duration, Timing, Variability, and Stages during the COVID-19 Pandemic: Large-Scale Fitbit Data

Introduction The COVID-19 pandemic has resulted in societal-level changes to sleep and other behavioral patterns. Objective, longitudinal data would allow for a greater understanding of sleep-related changes at the population level. Methods N= 163,524 deidentified active Fitbit users from 6 major US cities contributed data, representing areas particularly hard-hit by the pandemic (Chicago, Houston, Los Angeles, New York, San Francisco, and Miami). Sleep variables extracted include nightly and weekly mean sleep duration and bedtime, variability (standard deviation) of sleep duration and bedtime, and estimated arousals and sleep stages. Deviation from similar timeframes in 2019 were examined. All analyses were performed in Python. Results These data detail how sleep duration and timing changed longitudinally, stratified by age group and gender, relative to previous years’ data. Overall, 2020 represented a significant departure for all age groups and both men and women (P<0.00001). Mean sleep duration increased in nearly all groups (P<0.00001) by 5-11 minutes, compared to a mean decrease of 5-8 minutes seen over the same period in 2019. Categorically, sleep duration increased for some and decreased for others, but more extended than restricted. Sleep phase shifted later for nearly all groups (p<0.00001). Categorically, bedtime was delayed for some and advanced for others, though more delayed than advanced. Duration and bedtime variability decreased, owing largely to decreased weekday-weekend differences. WASO increased, REM% increased, and Deep% decreased. Additional analyses show stratified, longitudinal changes to sleep duration and timing mean and variability distributions by month, as well as effect sizes and correlations to other outcomes. Conclusion The pandemic was associated with increased sleep duration on average, in contrast to 2019 when sleep decreased. The increase was most profound among younger adults, especially women. The youngest adults also experienced the greatest bedtime delay, in line with extensive school-start-times and chronotype data. When given the opportunity, the difference between weekdays and weekends became smaller, with occupational implications. Sleep staging data showed that slightly extending sleep minimally impacted deep sleep but resulted in a proportional increase in REM. Wakefulness during the night also increased, suggesting increased arousal despite greater sleep duration. Support (if any) This research was supported by Fitbit, Inc.

Long-term temporal analysis of four Pyrenean catchments with a gradient of land-cover

<p>Land cover and historical land use practices are the leading drivers of the hydrological response in most catchments systems. Timing, periodicity and magnitude of precipitation-discharge feedbacks are thus impacted by such site-specific characteristics. We analysed the long-term precipitation and discharge databases of four experimental catchments located in the Central Spanish Pyrenees and thus similar in their climate. Furthermore, they have a gradient of land cover (from a relatively pristine forested catchment, through an abandoned cultivated catchment with progressive plant recolonization, to an afforested catchment and ending by a bare degraded badland catchment); so, form a solid benchmark to assess such dynamic changes. For the analysis of the long-term precipitation and discharge time-series we use the wavelet transform methodology, which proves valuable to segregate the continuous hydrological response of the catchments in different and non-similar dominant time-scales. Precipitation and discharge events are not just identified and analysed in terms of magnitude or correlation relationships but also the time-localization of each transient precipitation and discharge events is retrieved. We thus no impose any fixed periodicity in the occurrence of hydrological events and ultimately, we are able to infer the real and site-specific temporal variability of each dataset through which we can infer the timing, variability and physical mechanisms of water storage/transport in each catchment. Thereby, this analysis reveals the land-cover-discharge feedbacks that takes place at different time-scales.</p>