Biology subjects

Tsaneva-Atanasova, K.

Publications and source records attributed to Tsaneva-Atanasova, K..

3 recordsLinked to original sources

bioRxiv2018

A mathematical model of the hypothalamic network controlling the ultradian secretion of reproductive hormones.

Fertility critically depends on the gonadotropin-releasing hormone (GnRH) pulse generator, a neural construct comprised of hypothalamic neurons co-expressing kisspeptin, neurokoinin-B and dynorphin that drives the pulsatile release of GnRH. How this neural network generates and controls the appropriate ultradian frequency essential for gametogenesis and ovulation is unknown. Here, we present a mathematical model of the GnRH pulse generator with theoretical evidence and in vivo experimental data showing that robust pulsatile release of luteinizing hormone, a proxy for GnRH, emerges abruptly as we increase the basal activity of the neuronal network using continuous low frequency optogenetic stimulation of the neural construct. Further increases in basal activity markedly increase pulse frequency. Model predictions that such behaviors are concomitant of non-linear positive and negative feedback interactions mediated through neurokinin-B and dynorphin signaling respectively are confirmed neuropharmacologically. Our mathematical model sheds light on the long-elusive GnRH pulse generator offering new horizons for fertility regulation.

physiology↗

bioRxiv2017

Acetylcholine reconfigures hippocampal circuits to enable rapid formation of overlapping memory ensembles

In the hippocampus, episodic memories are thought to be encoded by the formation of ensembles of synaptically coupled CA3 pyramidal cells driven by sparse but powerful mossy fiber inputs from dentate gyrus granule cells. Since CA3 network capacity is finite, a mechanism for enhancing memory encoding during important events would ensure greater efficiency, but the salient signal that might determine this memory selectivity filter is unknown. Using experimental and computational methods we show that the cholinergic system can operate as a memory selectivity filter by combining 3 separate mechanisms: disinhibition of feed-forward mossy fiber inhibition enables synaptic plasticity at CA3-CA3 recurrent synapses; Increasing cellular excitability lowers the threshold for ensemble formation; Reduction of overall CA3-CA3 recurrent synapse strength allows for an increase in overlap between ensembles. Thus, we show that acetylcholine release enables the selective encoding of salient high-density episodic memories in the hippocampus.

neuroscience↗

bioRxiv2017

Modelling of the cardiopulmonary responses to maximal aerobic exercise in patients with cystic fibrosis

Cystic fibrosis (CF) is a debilitating chronic condition, which requires complex and expensive disease management. Exercise has now been recognised as a critical factor in improving health and quality of life in patients with CF. Hence, cardiopulmonary exercise testing (CPET) is used to determine aerobic fitness of young patients as part of the clinical management of CF. However, at present there is a lack of conclusive evidence for one limiting system of aerobic fitness for CF patients at an individual patient level.\n\nHere, we perform detailed data analysis that allows us to identify important systems-level factors that affect aerobic fitness. We use patients data and principal component analysis to confirm the dependence of CPET performance on variables associated with ventilation and metabolic rates of oxygen consumption. We find that the time at which participants cross the anaerobic threshold (AT) is well correlated with their overall performance. Furthermore, we propose a predictive modelling framework that captures the relationship between ventilatory dynamics, lung capacity and function and performance in CPET within a group of children and adolescents with CF. Specifically, we show that using Gaussian processes (GP) we can predict AT at the individual patient level with reasonable accuracy given the small sample size of the available group of patients. We conclude by presenting future perspectives for improving and extending the proposed framework.\n\nOur modelling and analysis have the potential to pave the way to designing personalised exercise programmes that are tailored to specific individual needs relative to patients treatment therapies.

physiology↗