Biology subjects

Sampson, A.

Publications and source records attributed to Sampson, A..

3 recordsLinked to original sources

bioRxiv2026

The Pan-European Impact of the Balkan Hunter-Gatherers

During the Last Glacial Maximum (LGM) 26-19 thousand years ago (kya), Europe had three principal refugia not covered by ice: the Iberian, Italian, and Balkan peninsulas1,2. While the Iberian and Italian refugia have been studied with ancient DNA3-7, the legacy of the Balkan refugium has remained a mystery due to a lack of genetic data 30-12 kya. We present genome-wide data from nine newly reported individuals: three Epipaleolithic from Romania, one Epipaleolithic from Bosnia and Herzegovina, three Mesolithic from Greece, one Epipaleolithic from Southern Italy, and one Mesolithic from Sardinia. We find that the Epipaleolithic individuals from Romania and the Mesolithic individual from mainland Greece were from a previously unsampled population that was the primary source for later European hunter-gatherers. Westward expansion of Balkan Epipaleolithic people into the Italian Peninsula and mixture with a minority contribution from pre-LGM Italians, produced a population that then spread further west to become the primary ancestry of west-ern European Mesolithic people. Northeastward expansion, bypassing Italy, contributed the European ancestry source of Scandinavian and Eastern European hunter-gatherers. Southeastward expansion to the Aegean led to Anatolian-European mixtures before the spread of farming.

genetics↗

bioRxiv2025

MICRO-TAG enzyme complementation enables quantification of cellular drug-target engagement in temperature series

Drug discovery for challenging drug targets necessitates the proteomic complexities of the cellular milieu for contextual target folding and function. Conventional biophysical methods for assessing drug interaction with a target are often not sufficiently suited for drug discovery as they impose acellular environment on the target and rely on recombinant purified protein material. In contrast, cell target engagement offers a powerful paradigm for drug discovery, through measurement of transitions in the thermodynamic state of a target protein, as it engages with drug molecules in the cell. Split-enzyme cell target engagement methods offer scaled utility during early drug discovery. Here, we describe a novel highly sensitive and scalable fluorescence-based cell target engagement method that leverages complementation of split-RNase S. This offers a unique combination of procedural and biophysical advantages, enabling its seamless integration with various instruments and applications designed for fluorescence detection. Most importantly, this new method allows for quantitation of cell target engagement in programmable temperature series format, consistent with conventional thermal shift assays, rather than at a single melting temperature. We demonstrate the sensitivity and versatility of this approach for drug discovery using targets MAPK1, KRAS, and UBE2N.

biochemistry↗

bioRxiv2020

Overt visual attention and value computation in complex risky choice

Traditional models of decision making under uncertainty explain human behavior in simple situations with a minimal set of alternatives and attributes. Some of them, such as prospect theory, have been proven successful and robust in such simple situations. Yet, less is known about the preference formation during decision making in more complex cases. Furthermore, it is generally accepted that attention plays a role in the decision process but most theories make simplifying assumptions about where attention is deployed. In this study, we replace these assumptions by measuring where humans deploy overt attention, i.e. where they fixate. To assess the influence of task complexity, participants perform two tasks. The simpler of the two requires participants to choose between two alternatives with two attributes each (four items to consider). The more complex one requires a choice between four alternatives with four attributes each (16 items to consider). We then compare a large set of model classes, of different levels of complexity, by considering the dynamic interactions between uncertainty, attention and pairwise comparisons between attribute values. The task of all models is to predict what choices humans make, using the sequence of observed eye movements for each participant as input to the model. We find that two models outperform all others. The first is the two-layer leaky accumulator which predicts human choices on the simpler task better than any other model. We call the second model, which is introduced in this study, TNPRO. It is modified from a previous model from management science and designed to deal with highly complex decision problems. Our results show that this model performs well in the simpler of our two tasks (second best, after the accumulator model) and best for the complex task. Our results suggest that, when faced with complex choice problems, people prefer to accumulate preference based on attention-guided pairwise comparisons.

neuroscience↗