Biology subjects

Hamann, M.

Publications and source records attributed to Hamann, M..

3 recordsLinked to original sources

bioRxiv2026

Rules of disengagement: orexin-arousal and dopamine-utility as separable axes

Staying on task, leaving it, and coming back to it are processes we experience daily. They depend on task utility and arousal, but the neurochemical processes behind this interplay are unknown. In mice performing a decision-making task with shifting reward size, we identified latent engagement states and the transitions between them. Pupil-linked arousal and dopaminergic utility coding predicted these transitions along separable axes. Orexin antagonism with almorexant disengaged mice at low reward, an effect mediated by pupil-linked arousal and not by dopamine. GLP-1 receptor agonism with semaglutide reduced the gain with which accumbal dopamine integrates reward history, which predicted the progressive disengagement it caused, with no detectable contribution from arousal or orexin. Fast striatal and slow accumbal dopamine codes predicted engagement on their own timescales. These results decouple orexin-driven arousal from dopamine-mediated utility coding in task engagement, with implications for two widely used drug classes and for disorders of motivation.

neuroscience↗

bioRxiv2020

Disease Risk Analysis in sea turtles: A baseline study to inform conservation efforts

The impact of a range of different threats has resulted in the listing of six out of seven sea turtle species on the IUCN Red List of endangered species. Disease risk analysis (DRA) tools are designed to provide objective, repeatable and documented assessment of the disease risks for a population and measures to reduce these risks through management options. To the best of our knowledge, DRAs have not previously been published for sea turtles, although disease is reported to contribute to sea turtle population decline. Here, a comprehensive list of health hazards is provided for all seven species of sea turtles. The possible risk these hazards pose to the health of sea turtles were assessed and "One Health" aspects of interacting with sea turtles were also investigated. The risk assessment was undertaken in collaboration with more than 30 experts in the field including veterinarians, microbiologists, social scientists, epidemiologists and stakeholders, in the form of two international workshops and one local workshop. The general finding of the DRA was the distinct lack of knowledge regarding a link between the presence of pathogens and diseases manifestation in sea turtles. A higher rate of disease in immunocompromised individuals was repeatedly reported and a possible link between immunosuppression and environmental contaminants as a result of anthropogenic influences was suggested. Society based conservation initiatives and as a result the cultural and social aspect of interacting with sea turtles appeared to need more attention and research. A risk management workshop was carried out to acquire the insights of local policy makers about management options for the risks relevant to Queensland and the options were evaluated considering their feasibility and effectiveness. The sea turtle DRA presented here, is a structured guide for future risk assessments to be used in specific scenarios such as translocation and head-starting programs.

ecology↗

bioRxiv2017

Two C++ Libraries for Counting Trees on a Phylogenetic Terrace

MotivationThe presence of terraces in phylogenetic tree space, that is, a potentially large number of distinct tree topologies that have exactly the same analytical likelihood score, was first described by Sanderson et al, (2011). However, popular software tools for maximum likelihood and Bayesian phylogenetic inference do not yet routinely report, if inferred phylogenies reside on a terrace, or not. We believe, this is due to the unavailability of an efficient library implementation to (i) determine if a tree resides on a terrace, (ii) calculate how many trees reside on a terrace, and (iii) enumerate all trees on a terrace.\n\nResultsIn our bioinformatics programming practical we developed two efficient and independent C++ implementations of the SUPERB algorithm by Constantinescu and Sankoff (1995) for counting and enumerating the trees on a terrace. Both implementations yield exactly the same results and are more than one order of magnitude faster and require one order of magnitude less memory than a previous 3rd party python implementation.\n\nAvailabilityThe source codes are available under GNU GPL at https://github.com/terraphast\n\nContactAlexandros.Stamatakis@h-its.org

evolutionary biology↗