Biology subjects

Heller, H. C.

Publications and source records attributed to Heller, H. C..

3 recordsLinked to original sources

bioRxiv2025

Automated sleep scoring in hibernating and non-hibernating American black bears

Hibernating bears show remarkable metabolic suppression. Their decline in core body temperature (Tb) is moderate (from 38{degrees}C to 30-35{degrees}C), but their metabolism declines as much as 75%. To understand the role of sleep in this hypometabolic state, we recorded biotelemetrically EEG, EOG and EMG data over 3500 days from 16 captive American black bears in and out of hibernation under semi-natural conditions. This data set is too large to score manually for Wake, REM- and NREM sleep, so we tested two machine learning classifiers: (1) Somnotate trained on multiple one-day recordings, and (2) Somnivore, trained on a small subset from each recording. As automated scoring methods have not been applied to hibernating species before, a major concern is the effect changing brain temperature has on the EEG and on the machine learning based detection. Therefore, we selected reference data using consensus by 3 manual sleep scorers from each of 6 bears, two one-day recordings at the highest and lowest body temperatures during hibernation when Tb was oscillating in multiday cycles, and a non-hibernating one-day recording in summer. Somnotate results were excellent when trained separately for hibernating and non-hibernating data. Training Somnotate separately for high and low Tb within hibernation did not improve results further. Sleep times in hibernation were about 2x that in summer for both automated scores and manual scores (p<0.0001). There were no significant differences in occupancy of vigilance states between automated and manual scores in hibernation (p>0.05), but a small overestimate of sleep time in summer (p<0.05). Both applications yielded F-measures against manual scores in the 0.90-0.98 range. Outliers in the 0.67-0.88 range were correlated between the two applications, indicating that specific files are more challenging to annotate. We conclude that both applications have accuracies approaching that of manual scorers when trained on high quality data.

neuroscience↗

bioRxiv2020

Inhibiting USP16 rescues stem cell aging and memory in an Alzheimer's model

Alzheimers disease (AD) is a progressive neurodegenerative disease observed with aging that represents the most common form of dementia. To date, therapies targeting end-stage disease plaques, tangles, or inflammation have limited efficacy. Therefore, we set out to identify an earlier targetable phenotype. Utilizing a mouse model of AD and human fetal cells harboring mutant amyloid precursor protein, we show cell intrinsic neural precursor cell (NPC) dysfunction precedes widespread inflammation and amyloid plaque pathology, making it the earliest defect in the evolution of disease. We demonstrate that reversing impaired NPC self-renewal via genetic reduction of USP16, a histone modifier and critical physiological antagonist of the Polycomb Repressor Complex 1, can prevent downstream cognitive defects and decrease astrogliosis in vivo. Reduction of USP16 led to decreased expression of senescence gene Cdkn2a and mitigated aberrant regulation of the BMP pathway, a previously unknown function of USP16. Thus, we reveal USP16 as a novel target in an AD model that can both ameliorate the NPC defect and rescue memory and learning through its regulation of both Cdkn2a and BMP signaling. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Schematic summarizing therapeutic approaches to mitigate the effects of mutant APP through targeting of Cdkn2a, BMI1, USP16 and BMP.

molecular biology↗

bioRxiv2020

Disordered phasic relationships between hippocampal place cells, theta, and gamma rhythms in the Ts65Dn mouse model of Down Syndrome

Down Syndrome (DS) in humans is caused by trisomy of chromosome 21 and is marked by prominent difficulties in learning and memory. Decades of research have demonstrated that the hippocampus is a key structure in learning and memory, and recent work with mouse models of DS have shown changes in spectral coherence in the field potentials of hippocampus and regions important for executive function such as prefrontal cortex. One of the primary functional differences in DS is thought to be an excess of GABAergic innervation from Medial Septum (MS) to regions such as hippocampus. In these experiments, we probe in detail the activity of region CA1 of the hippocampus using in vivo electrophysiology in the Ts65Dn mouse model of DS in comparison to their non-trisomic 2N littermates. We find changes in hippocampal phenomenology that suggest that MS output, which drives theta rhythm in the hippocampus, is strongly altered. Moreover, we find that this change affects the phasic relationship of both CA1 place cells and gamma rhythms to theta. Since the phasic relationship of both of these aspects of hippocampal phenomenology to theta are thought to be critical for the segregation of encoding and retrieval epochs within hippocampus, it is likely that these changes are the neural substrates of the learning and memory deficits seen both in human DS and animal models such as Ts65Dn.

neuroscience↗