Optimization of synthetic oscillatory biological networks through Reinforcement Learning

In the expanding realm of computational biology, Reinforcement Learning (RL) emerges as a novel and promising approach, especially for designing and optimizing complex synthetic biological circuits. This study explores the application of RL in controlling Hopf bifurcations within ODE-based systems, particularly under the influence of molecular noise. Through two case studies, we demonstrate RL’s capabilities in navigating biological systems’ inherent non-linearity and high dimensionality. Our findings reveal that RL effectively identifies the onset of Hopf bifurcations and preserves biological plausibility within the optimized networks. However, challenges were encountered in achieving persistent oscillations and matching traditional algorithms’ computational speed. Despite these limitations, the study highlights RL’s significant potential as an instrumental tool in computational biology, offering a novel perspective for exploring and optimizing oscillatory dynamics within complex biological systems. Our research establishes RL as a promising strategy for manipulating and designing intricate behaviors in biological networks

Polysomnographic Findings in a Cohort of Chronic Insomnia Patients with Benzodiazepines Abuse

Study objectives: to evaluate sleep modifications induced by chronic benzodiazepines (BDZs) abuse. Methods: cohort study, comparison of sleep measures between BDZs abusers and controls. Drug Addiction Unit (Institute of Psychiatry) and Unit of Sleep Disorder (Institute of Neurology) of the Catholic University in Rome. Six outpatients were enrolled, (4 men and 2 7 women, mean age 53.3\ub114.8, range: 34 - 70 years) affected by BDZ chronic abuse; 55 healthy controls (23 men and 32 women, mean age 54.2 \ub113.0, range: 27\u201376 years). All patients underwent clinical evaluation, psychometric measures, ambulatory polysomnography, scoring of sleep macrostructure and microstructure (power spectral fast-frequency EEG arousal, Cyclic Alternating Pattern - CAP), Heart Rate Variability. Results: BDZs abusers had relevant modification of sleep macrostructure and a marked reduction of fast-frequency EEG arousal in NREM (Patients: 6.6\ub13.7 events/hour, Controls 13.7\ub14.9 events/hour, U-test: 294, p=0.002) and REM (Patients: 8.4\ub12.4 events/hour, Controls 13.3\ub15.1 events/hour, U-test: 264, p=0.016), and of CAP rate (Patients: 15.0\ub18.6 %, Controls: 51.2\ub112.1 %, U-test: 325, p<0.001). Discussion: BDZs abusers have reduction of arousals associated with increased number of nocturnal awakenings and severe impairment of sleep architecture. The effect of chronic BDZs abuse on sleep may be described as a severe impairment of arousal dynamics; the result is the inability to modulate levels of vigilance