Find research datasets worth reusing

opencc-by-nc-4.0Mar 2022View details →

Figure 2 in Circadian activity patterns and temporal overlap among cracids (Aves: Cracidae) within a vegetation mosaic in the Pantanal of Rio Negro, Brazil

Figure 2. Circadian activity patterns of three cracid species in the Pantanal of Rio Negro, Aquidauana, Mato Grosso do Sul. The red line represents the mean circular vector (mμ) with CI95% of the distributions.

opencc-by-4.0Sep 2017View details →

Pigment-Dispersing Factor expressing neurons provide an infrastructure for conveying circadian information in the honey bee brain

A movie of a 360° view of the 3D-reconstructed PDF (Pigment Dispersing Factor) network in the honey bee brain. (avi file to be opened with for example Fiji ImageJ)

opencc-by-4.0May 2024View details →

Data for "Testing for variation in photoperiodic plasticity in a butterfly: inconsistent effects of circadian genes between geographic scales" (Ecology and Evolution, accepted manuscript)

Raw data and analysis scripts belonging to Testing for variation in photoperiodic plasticity in a butterfly: inconsistent effects of circadian genes between geographic scales (Ecology and Evolution, accepted manuscript). Includes data from a photoperiodic assay with larvae of the speckled wood butterfly, Pararge aegeria, as well as a small bioinformatic analysis of SNP variation in two circadian candidate genes. List of files: <table> <tbody> <tr> <td>statistics_and_figures.R</td> <td>Statistical analysis of phenotyping experiment; drawing figures</td> </tr> <tr> <td>variant_calling.sh</td> <td>Shell script for mapping sequencing reads; calling and tabulating SNPs</td> </tr> <tr> <td>experiment_diapause.txt</td> <td>Data from phenotyping experiment, for analysis of diapause induction</td> </tr> <tr> <td>experiment_larval</td> <td>Data from phenotyping experiment, for analysis of larval development</td> </tr> <tr> <td>snptable_timeless</td> <td>Tabulated allele frequencies for exonic SNPs in timeless</td> </tr> <tr> <td>snptable_period</td> <td>Tabulated allele frequencies for exonic SNPs in period</td> </tr> </tbody> </table>

opencc-zeroJun 2024View details →

Reorganisation of circadian activity and the pacemaker circuit under novel light regimes

Many environmental features are cyclic, with predictable changes across the day, seasons and latitudes. Additionally, anthropogenic, artificial light-induced changes in photoperiod or shiftwork-driven novel light/dark cycles also occur. Endogenous timekeepers or circadian clocks help organisms cope with such changes. The remarkable plasticity of clocks is evident in the waveforms of behavioural and molecular rhythms they govern. Despite detailed mechanistic insights into the functioning of the circadian clock, practical means to manipulate activity waveform are lacking. Previous studies using a nocturnal rodent model showed that novel light regimes caused locomotor activity to bifurcate such that mice showed two bouts of activity restricted to the dimly lit phases. Here, we explore the generalizability of these findings and leverage the genetic toolkit of Drosophila melanogaster to obtain mechanistic insights into this unique phenomenon. We find that dim scotopic illumination of specific durations induces circadian photoreceptor CRYPTOCHROME-dependent activity bifurcation in male flies. We show circadian re-organisation of the pacemaker circuit wherein the 'evening' neurons regulate the timing of both bouts of activity under novel light regimes. Our findings indicate that environmental regimes can be exploited to design light regimes to ease the circadian waveform into synchronising with challenging conditions.

opencc-by-4.0Sep 2022View details →

Fig. 1 in Circadian activity patterns of the Red fox (Vulpes vulpes) and the Stone marten (Martes foina) in agricultural landscape of Northwestern Bulgaria during autumn-winter period

Fig. 1. Location of the protected area "Zlatiyata" in Northwestern Bulgaria.

opencc-by-4.0Mar 2024View details →

Collective flow of circadian clock information in honeybee colonies (Data)

This repository contains the data used in the paper "Collective flow of circadian clock information in honeybee colonies".   Paper: Collective flow of circadian clock information in honeybee colonies   Code and more details are provided in the README file of<a href="https://github.com/BioroboticsLab/speedtransfer.git"> speedtransfer</a> repository.   <h2>Description of included files</h2> All data sets exist for the period 01.08.-25.08.2016 and 20.08-14.09.2019.   <h3>mean_velocity_2016.csv and mean_velocity_2019.csv</h3> The mean velocity for each bee and age is averaged over 10-minute time windows. Keys: <ul> <li> velocity: Mean euclidean distance of two consecutive points of a bee's hive position. </li> <li> datetime: Date in year-month-day hour:minute:seconds+ms:ns format. </li> <li> age: Age in days. Can be NaN if the bee has no associated death_date. </li> </ul>   <h3>velocity_2088_2019.csv and velocity_5101_2019.csv</h3> The movement speed [mm/s] of two individual bees with the bee id 2088 and the bee id 5101 for the period 2019. Keys: <ul> <li> velocity: Euclidean distance of two consecutive points of a bee's hive position. </li> <li>time_passed: Time [s] in between the datetime of that current and the last previous detection.</li> <li> datetime: Date in year-month-day hour:minute:seconds+ms:ns format. </li> </ul>   <h3>cosinor_2016.csv and cosinor_2019.csv</h3> A cosinor fit of the velocity per bee for a time window of 3 consecutive days according to the method proposed by <a href="https://doi.org/10.1186/1742-4682-11-16">Cornelissen</a>. Keys: <ul> <li> mesor: Rhythm-adjusted mean of a cosine with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> amplitude: Amplitude of a cosine with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> phase: Acrophase of a cosine with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_value: P-value of an F-test for overall significance of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_mesor: P-value of the mesor coefficient of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_amplitude: P-value of the amplitude coefficient of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_acrophase: P-value of the phase coefficient of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_reject: P-value of a F-test for model validity. </li> <li> r_squared: R² value of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> r_squared_adj: Adjusted R² value of a cosinor fit with a period of one day fitted to the velocity data of the individual over three days. Can be NaN if the fit did not converge due to a lack of data points. </li> <li> p_ks: P-value of a Kalgomorov-Smirnoff test of residual normality. </li> <li> p_hom: P-Value of F-test of variance homogeneity of cosinor fit. </li> <li> dw: Durbin-Watson statistic for the independence of the residuals. </li> <li> p_runs: P-value of runs test of independence of residuals. </li> <li> RSS: Residual sum of squared - the sum of squared differences between the data and the estimated values from the fitted model </li> <li> SSPE: Pure error sum of squares of cosinor fit. </li> <li> bee_id: Numeric unique identifier per individual bee. </li> <li> age: Age in days. Can be NaN if the bee has no associated death_date. </li> <li> date: Date and time in year-month-day hour:minute:seconds+ms:ns format. The hour is always 12. </li> <li> n_data_points: Number of data points per cosinor fit. </li> <li> data_point_dist_max: Maximum temporal distance between two consecutive timepoints of velocity data. </li> <li> data_point_dist_min: Minimum temporal distance between two consecutive timepoints of velocity data. </li> <li> data_point_dist_mean: Mean temporal distance between two consecutive timepoints of velocity data. </li> <li> data_point_dist_median: Median temporal distance between two consecutive timepoints of velocity data. </li> <li> day_mean: Mean velocity during the daytime defined as the time between 9 and 18 o'clock. </li> <li> day_std: Standard deviation of velocity during the daytime defined as the time between 9 and 18 o'clock. </li> <li> night_mean: Mean velocity during the nighttime defined as the time between 21 and 6 o'clock. </li> <li> night_std: Standard deviation of velocity during the nighttime defined as time between 21 and 6 o'clock. </li> <li> ad_fuller: P-value of augmented Dickey-Fuller test for testing whether the velocity data is stationary. </li> <li> fit_type: Median time bin in seconds used for fit, e.g. 3600 means that the median over a time window of 3600s is used for the fit. </li> <li> ci_acrophase_lower: Confidence interval lower bound for the acrophase fit value. </li> <li> ci_acrophase_upper: Confidence interval upper bound for the acrophase fit value. </li> <li> ci_mesor_lower: Confidence interval lower bound for the mesor fit value. </li> <li> ci_mesor_upper: Confidence interval upper bound for the mesor fit value. </li> <li> ci_amplitude_lower: Confidence interval lower bound for the amplitude fit value. </li> <li> ci_amplitude_upper: Confidence interval upper bound for the amplitude fit value. </li> </ul>   <h3>interactions_side0_2016.csv, interactions_side0_2019.csv and interactions_side1_2016.csv, interactions_side1_2019.csv</h3> The bee interactions and their post-interaction velocity change. An interaction between two bees (bee0 and bee1) is defined when two bees are detected simultaneously in the hive with a confidence threshold of 0.25, the distance between the markings on their thorax bodies is no more than 14 mm. These interactions are combined into one interaction if the same detections occur within a time interval of 1 second or less between them. The resulting interaction data frames per bee are concatenated with the estimates of the cosinor dataframe. Keys: <ul> <li> bee_id0: Numeric unique identifier per individual bee. </li> <li> bee_id1: Numeric unique identifier per individual bee. </li> <li> interaction_start: Timestamp indicating interaction start time point. </li> <li> interaction_end: Timestamp indicating interaction end time point. </li> <li> x_pos_start_bee0: Numeric x-position of bee relative to hive at interaction start. </li> <li> y_pos_start_bee0: Numeric y-position of bee relative to hive at interaction start. </li> <li> theta_start_bee0: Numeric angle of bee relative to hive at interaction start. </li> <li> x_pos_start_bee1: Numeric x-position of bee relative to hive at interaction start. </li> <li> y_pos_start_bee1: Numeric y-position of bee relative to hive at interaction start. </li> <li> theta_start_bee1: Numeric angle of bee relative to hive at interaction start. </li> <li> x_pos_end_bee0: Numeric x-position of bee relative to hive at interaction end. </li> <li> y_pos_end_bee0: Numeric y-position of bee relative to hive at interaction end. </li> <li> theta_end_bee0: Numeric angle of bee relative to hive at interaction end. </li> <li> x_pos_end_bee1: Numeric x-position of bee relative to hive at interaction end. </li> <li> y_pos_end_bee1: Numeric y-position of bee relative to hive at interaction end. </li> <li> theta_end_bee1: Numeric angle of bee relative to hive at interaction end. </li> <li> vel_change_bee0: Numeric post-interaction absolute change of velocity: abs = vafter-vbefore with vbefore and vafter are calculated as the mean velocity 30s before and after the interaction. </li> <li> rel_change_bee0: Numeric post-interaction relative change of velocity: rel = (vafter-vbefore)/vbefore with vbefore and vafter are calculated as the mean velocity 30s before and after the interaction. </li> <li> vel_change_bee1: Numeric post-interaction absolute change of velocity: abs = vafter-vbefore with vbefore and vafter are calculated as the mean velocity 30s before and after the interaction. </li> <li> rel_change_bee1:  Numeric post-interaction relative change of velocity:rel = (vafter-vbefore)/vbefore with vbefore and vafter are calculated as the mean velocity 30s before and after the interaction. </li> </ul> Modeling bees as rectangular mask to determine if bees body overlap when interacting - see more details in <a href="https://github.com/BioroboticsLab/speedtransfer.git">speedtransfer repository</a>: <ul> <li> x_trans_focal_bee0: Translated and rotated x-position relative to hive. </li> <li> y_trans_focal_bee0: Translated and rotated y-position relative to hive. </li> <li> theta_trans_focal_bee0: Translated and rotated theta relative to hive. </li> <li> x_trans_focal_bee1: Translated and rotated x-position relative to hive. </li> <li> y_trans_focal_bee1: Translated and rotated y-position relative to hive. </li> <li> theta_trans_focal_bee1: Translated and rotated theta relative to hive. </li> <li> overlapping: Bool indicating whether rectangular masks modeling the body of bees overlap. </li> </ul> Cosinor fit parameters - see more detailed in <a href="https://docs.google.com/document/d/1PHJWc9HqbYgndjX9WjkfSQoks81AR-E9cHC25xZgP84/edit#heading=h.wjr1wzfvmipm">Cosinor</a> data frame: <ul> <li> amplitude_bee0: Amplitude of the cosinor fit per bee of the day of the interaction. </li> <li> phase_bee0: Phase of the cosinor fit per bee of the day of the interaction. </li> <li> p_value_bee0: P-value of the cosinor fit per bee of the day of the interaction. </li> <li> r_squared_bee0: R² value of the cosinor fit per bee of the day of the interaction. </li> <li> amplitude_bee1: Amplitude of the cosinor fit per bee of the day of the interaction. </li> <li> phase_bee1: Phase of the cosinor fit per bee of the day of the interaction. </li> <li> p_value_bee1: P-value of the cosinor fit per bee of the day of the interaction. </li> <li> r_squared_bee1: R² of the cosinor fit per bee of the day of the interaction. </li> </ul>   <h3>interactions_side0_null_model_2016.csv and interactions_side0_null_model_2019.csv</h3> A null model for bee interactions and their post-interaction velocity change. The interaction null model is created by taking the distribution of the start and end times of a given interaction dataframe and selecting two random bees at those times that the bees were detected in the hive at that time. These pairs of bees are considered as "interacting" and their post-interaction speed change is calculated. The resulting interaction data frames per bee are concatenated with the estimates of the cosinor dataframe. The position data is relative to pixels not to the hive coordinates. As this is a null model the following keys are the same as described in the <a href="https://docs.google.com/document/d/1PHJWc9HqbYgndjX9WjkfSQoks81AR-E9cHC25xZgP84/edit#heading=h.728ge538e768">Interaction</a> data frame. Keys: <ul> <li> bee_id0 </li> <li> bee_id1 </li> <li> interaction_start </li> <li> interaction_end </li> <li> x_pos_start_bee0 </li> <li> y_pos_start_bee0 </li> <li> theta_start_bee0 </li> <li> x_pos_start_bee1 </li> <li> y_pos_start_bee1 </li> <li> theta_start_bee1 </li> <li> x_pos_end_bee0 </li> <li> y_pos_end_bee0 </li> <li> theta_end_bee0 </li> <li> x_pos_end_bee1 </li> <li> y_pos_end_bee1 </li> <li> theta_end_bee1 </li> <li> vel_change_bee0 </li> <li> rel_change_bee0 </li> <li> vel_change_bee1 </li> <li> rel_change_bee1 </li> <li> age_bee0 </li> <li> phase_bee0 </li> <li> amplitude_bee0 </li> <li> r_squared_bee0 </li> <li> p_value_bee0 </li> <li> age_bee1 </li> <li> amplitude_bee1 </li> <li> r_squared_bee1 </li> <li> p_value_bee1 </li> <li> phase_bee1 </li> </ul>   <h3>interaction_tree_paths_2016.csv and interactions_tree_paths_2019.csv</h3> Graph-theoretic interaction tree paths. By tracing back interactions that positively influenced the speed of a focal bee, we constructed a graph-theoretic tree structure starting from a young rhythmic bee and recursively adding activating (velocity change parent > 0) individuals. We examined the impact of sequential interactions among bees occurring between 10 am and 3 pm, focusing on a subgroup of n = 1000 bees that are significantly rhythmic, younger than 5 days old, and peak in activity after 12 pm. We limited the time window between interactions to 30 minutes and capped the cascade duration at 2 hours to ensure causal relevance. The resulting interaction trees are collected and each node of all paths in the interaction trees are concatenated to this dataframe. Keys: <ul> <li> bee_id: Numeric unique identifier per individual bee which is a node in the tree. </li> <li> datetime: Date in year-month-day hour:minute:seconds+ms:ns format when the interaction takes place. </li> <li> x_pos: Numeric x-position of bee relative to hive at interaction start. </li> <li> y_pos: Numeric y-position of bee relative to hive at interaction start. </li> <li> vel_change_parent: <a href="https://docs.google.com/document/d/1PHJWc9HqbYgndjX9WjkfSQoks81AR-E9cHC25xZgP84/edit#heading=h.728ge538e768">Absolute velocity change</a> of bee of parent node. </li> <li> age: Age in days of node bee. Can be NaN if the bee has no associated death date. </li> <li> is_root: Bool indicating if node is root of tree. </li> <li> depth: Depth of node in tree. E.g. depth of root is 0. </li> <li> is_leaf: Bool indicating if node is leaf of tree. </li> <li> n_children: Number of children of the subtree of the node. </li> <li> parent: Numeric bee_id of parent node. </li> <li> tree_id: Numeric unique identifier of tree. </li> <li> time_gap: Python datetime.timedelta object of time delta in between the parent and child node interaction. </li> <li> path_id: Numeric unique identifier of path. </li> </ul> Cosinor fit parameters - see more detailed in <a href="https://docs.google.com/document/d/1PHJWc9HqbYgndjX9WjkfSQoks81AR-E9cHC25xZgP84/edit#heading=h.wjr1wzfvmipm">Cosinor</a> data frame: <ul> <li>  r_squared: R² value of the cosinor fit per bee of the day of the interaction. </li> <li>  phase: Phase of the cosinor fit per bee of the day of the interaction. </li> </ul>   <h2>Software used to acquire and analyze the data:</h2> <a href="https://github.com/BioroboticsLab/speedtransfer.git">speedtransfer: Cosinor fit and interaction calculation and further analyses.</a> <a href="https://github.com/BioroboticsLab/bb_rhythm">bb_rhythm: Cosinor fit and interaction calculation and further analyses.</a> <a href="https://github.com/BioroboticsLab/bb_behavior">bb_behavior: Database interaction and data (pre)processing, velocity calculation.</a> <a href="https://github.com/BioroboticsLab/bb_utils">bb_utils: Database settings and interaction.</a> <a href="https://github.com/walachey/slurmhelper">slurmhelper: A package for slurm script handling.</a>

opencc-by-4.0Nov 2023View details →

Data associated with the manuscript "Complex epistatic interactions between ELF3, PRR9, and PRR7 regulates the circadian clock and plant physiology"

Datasets associated with the figures in the paper entilted: "Complex epistatic interactions between ELF3, PRR9, and PRR7 regulates the circadian clock and plant physiology"

opencc-by-4.0Jul 2021View details →

Indoor lighting design for healthier workplaces natural and electric light assessment for suitable circadian stimulus

Dataset of "Indoor lighting design for healthier workplaces natural and electric light assessment for suitable circadian stimulus" research

opencc-zeroAug 2021View details →

Circadian and circatidal rhythms of protein abundance in the California mussel (Mytilus californianus)

Coastal habitats fluctuate with the 12.4 h tidal and 24 h light/dark cycle to predictably alter conditions such as air exposure, temperature, and food availability. Intertidal sessile bivalves exhibit behavioral and physiological adjustments to minimize the challenges of this environment. We investigated a high-resolution time course of the changes in protein abundance in the gill tissue of the intertidal mussel Mytilus californianus in a simulated tidal environment of 12:12 h light:dark cycles and a matching 6:6 h high:low tide cycle within each 12 h period. Approximately 38% of detected proteins showed significant rhythms in their abundances, with diversity in the phases of rhythmic isoforms. The circadian rhythm was dominant in protein abundance changes, particularly with oxidative metabolism. A tidal cycle elicited changes within functional groups, including in cytoskeletal proteins, chaperones, and oxidative stress proteins. In addition to protein abundance changes, we found the possibility for post-translational modifications driving rhythms, including methylation, mitochondrial peptide processing (proteolysis), and acylation. Dynamic changes in the proteome across functional categories demonstrate the importance of the tidal environment in entraining cellular processes, confirming that differential expression studies should not assume a static baseline of cellular conditions in intertidal organisms.

opencc-zeroJan 2023View details →

Circadian rhythm entrainment of the jewel wasp, Nasonia vitripennis, by antagonistic interactions of multiple spectral inputs

Circadian light entrainment in some insects is regulated by blue-light sensitive cryptochrome (CRY) protein that is expressed in the clock neurons, but this is not the case in hymenopterans. The hymenopteran clock does contain CRY, but it appears to be light-insensitive. Therefore, we investigated the role of retinal photoreceptors in the photic entrainment of the jewel wasp Nasonia vitripennis. Application of monochromatic light stimuli at different light intensities caused phase shifts in the wasp's circadian activity from which an action spectrum with three distinct peaks was derived. Electrophysiological recordings from the compound eyes and ocelli revealed the presence of three photoreceptor classes, with peak sensitivities at 340 nm (ultraviolet), 450 nm (blue), and 530 nm (green). An additional photoreceptor class in the ocelli with sensitivity maximum at 560–580 nm (red) was found. Whereas a simple sum of photoreceptor spectral sensitivities could not explain the action spectrum of the circadian phase shifts, modelling of the action spectrum indicates antagonistic interactions between pairs of spectral photoreceptors, residing in the compound eyes and the ocelli. Our findings imply that the photic entrainment mechanism in N. vitripennis encompasses the neural pathways for measuring the absolute luminance as well as the circuits mediating colour opponency.

opencc-by-4.0May 2023View details →

Data and supplementary information: Effects of lithium on locomotor activity and circadian rhythm of honey bees

Data and supplementary files for publication:Erdem, B., Arslan, O.C., Sevin, S. Gozen, A. G., Agosto-Rivera, J. L., Tugrul, G., & Alemdar, H. (2023). Effects of lithium on locomotor activity and circadian rhythm of honey bees. Scientific Reports, 13, 19861. https://doi.org/10.1038/s41598-023-46777-7 AcuteExp_Dark_ActivityData.xlsx - Total LMA counts of acute experiment in dark condition.AcuteExp_Light_ActivityData.xlsx - Total LMA counts of acute experiment in light condition.ChronicExp_ActivityData.xlsx - Total LMA counts of the chronic experiment.ChronicExp_MortalityData.xlsx - Mortality data of the chronic experiment.ChronicExp_PeriodRhytmData.xlsx - Defines rhythmic and arrhythmic individuals and the circadian periods (h) of the rhythmic individuals in chronic experiment.LD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the 12 h light / 12 h dark condition.DD_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant dark condition.LL_doubleplots.pdf - Double-plotted actograms of the individuals in the chronic experiment in the constant light condition. In the double-plotted actograms, NR indicates "non-rhythmic" individuals.

opencc-zeroAug 2023View details →

The circadian clock of the bacterium B. subtilis evokes properties of complex, multicellular circadian systems

Circadian clocks are pervasive throughout nature, yet only recently has this adaptive regulatory program been described in non-photosynthetic bacteria. Here, we describe an inherent complexity in the Bacillus subtilis circadian clock. We find that B. subtilis entrains to blue and red light and that circadian entrainment is separable from masking through fluence titration and frequency demultiplication protocols. We identify circadian rhythmicity in constant light, consistent with Aschoff's Rule, and entrainment aftereffects, both of which are properties described for eukaryotic circadian clocks. We report that circadian rhythms occur in wild isolates of this prokaryote, thus establishing them as a general property of this species, and that its circadian system responds to the environment in a complex fashion that is consistent with multicellular eukaryotic circadian systems.

opencc-zeroSep 2023View details →

Parametric effects of light acting via multiple photoreceptors contribute to circadian entrainment in Drosophila melanogaster

Circadian rhythms in physiology and behavior have near 24-hour periodicities that must adjust to the exact 24-hour geophysical cycles on earth to ensure adaptive daily timing. Such adjustment is called entrainment. One major mode of entrainment is via the continuous modulation of circadian period by the prolonged presence of light. Although Drosophila melanogaster is a prominent insect model of chronobiology, there is little evidence for such continuous effects of light in the species. In this study, we demonstrate that prolonged light exposure at specific times of the day shapes the daily timing of activity in flies. We also establish that continuous blue- and UV-blocked light lengthens the circadian period of Drosophila and provide evidence that this is produced by the combined action of multiple photoreceptors which, includes the cell autonomous photoreceptor cryptochrome. Finally, we introduce ramped light cycles as an entrainment paradigm that produces light entrainment that lacks the large light-driven startle responses typically displayed by flies and requires multiple days for entrainment to shifted cycles. These features are reminiscent of entrainment in mammalian models systems and make possible new experimental approaches to understanding the mechanisms underlying entrainment in the fly.

opencc-zeroSep 2023View details →

Dataset: Disease-associated KCNMA1 variants decrease circadian clock robustness in channelopathy mouse models

KCNMA1 encodes the voltage- and calcium-activated K+ (BK) channel, which regulates suprachiasmatic nucleus (SCN) neuronal firing and circadian behavioral rhythms. Gain-of-function (GOF) and loss-of-function (LOF) alterations in BK channel activity disrupt circadian behavior, but the effect of human disease-associated KCNMA1 channelopathy variants has not been studied on clock function. Here, we assess circadian behavior in two GOF and one LOF mouse lines. Heterozygous Kcnma1N999S/WT and homozygous Kcnma1D434G/D434G mice are validated as GOF models of paroxysmal dyskinesia (PNKD3), but whether circadian rhythm is affected in this hypokinetic locomotor disorder is unknown. Conversely, homozygous LOF Kcnma1H444Q/H444Q mice do not demonstrate PNKD3. We assessed circadian behavior by locomotor wheel running activity. All three mouse models were rhythmic, but Kcnma1N999S/WT and Kcnma1D434G/D434G showed reduced circadian amplitude and decreased wheel activity, corroborating prior studies focused on acute motor coordination. In addition, Kcnma1D434G/D434G mice had a small decrease in period. However, the phase-shifting sensitivity for both GOF mouse lines was abnormal. Both Kcnma1N999S/WT and Kcnma1D434G/D434G mice displayed increased responses to light pulses and took fewer days to re-entrain to a new light:dark cycle. In contrast, the LOF Kcnma1H444Q/H444Q mice showed no difference in any of the circadian parameters tested. The enhanced sensitivity to phase-shifting stimuli in Kcnma1N999S/WT and Kcnma1D434G/D434G mice was similar to other Kcnma1 GOF mice. Together with previous studies, these results suggest that increasing BK channel activity decreases circadian clock robustness, without rhythm ablation.

closedIPD-NOFeb 2026View details →

The Effects of Light Therapy on Circadian Rhythms, Sleep, and Mood in Postpartum Depression

ClinicalTrials.gov study NCT02769858. IPD Sharing: NO. Countries: 1. Publications: 1.

restrictedIPD-UNDECIDEDFeb 2026View details →

Safety and Efficacy of VEC-162 on Circadian Rhythm in Healthy Adult Volunteers

ClinicalTrials.gov study NCT00490945. IPD Sharing: Not stated. Countries: 1. Publications: 1.

controlledIPD-YESFeb 2026View details →

Sleep and Circadian Rhythm Biomarkers of Postoperative Delirium

ClinicalTrials.gov study NCT06052397. IPD Sharing: YES. Countries: 1. Publications: 10.

restrictedIPD-UNDECIDEDFeb 2026View details →

A Transdiagnostic Sleep and Circadian Treatment to Improve Community SMI Outcomes

ClinicalTrials.gov study NCT02469233. IPD Sharing: Not stated. Countries: 1. Publications: 4.

restrictedIPD-UNDECIDEDFeb 2026View details →

Exploratory Study of Circadian Relationships Between Social Behavior, Blood Pressure and Metabolomics

ClinicalTrials.gov study NCT02249793. IPD Sharing: Not stated. Countries: 1. Publications: 1.