Functional Adaptation in the Brain Habenulo-Mesencephalic Pathway During Cannabinoid Withdrawal.

The mesolimbic reward system originating from dopamine neurons in the ventral tegmental area (VTA) of the midbrain shows a profound reduction in function during cannabinoid withdrawal. This condition may underlie aversive states that lead to compulsive drug seeking and relapse. The lateral habenula (LHb) exerts negative control over the VTA via the GABA rostromedial tegmental nucleus (RMTg), representing a potential convergence point for drug-induced opponent processes.

Effectiveness of probabilistic contact tracing in epidemic containment: The role of superspreaders and transmission path reconstruction.

The recent COVID-19 pandemic underscores the significance of early stage nonpharmacological intervention strategies. The widespread use of masks and the systematic implementation of contact tracing strategies provide a potentially equally effective and socially less impactful alternative to more conventional approaches, such as large-scale mobility restrictions. However, manual contact tracing faces strong limitations in accessing the network of contacts, and the scalability of currently implemented protocols for smartphone-based digital contact tracing becomes impractical during the rapid expansion phases of the outbreaks, due to the surge in exposure notifications and associated tests.

The Atypical Dopamine Transporter Inhibitor CE-158 Enhances Dopamine Neurotransmission in the Prefrontal Cortex of Male Rats: A Behavioral, Electrophysiological, and Microdialysis Study.

Background: Dopamine plays a key role in several physiological functions such as motor control, learning and memory, and motivation and reward. The atypical dopamine transporter inhibitor S,S stereoisomer of 5-(((S)-((S)-(3-bromophenyl)(phenyl)methyl)sulfinyl)methyl)thiazole (CE-158) has been recently reported to promote behavioral flexibility and restore learning and memory in aged rats.

Methods: Adult male rats were i.

DCAlign v1.0: aligning biological sequences using co-evolution models and informed priors.

Summary: DCAlign is a new alignment method able to cope with the conservation and the co-evolution signals that characterize the columns of multiple sequence alignments of homologous sequences. However, the pre-processing steps required to align a candidate sequence are computationally demanding. We show in v1.