Biology subjects

Morvan, M.

Publications and source records attributed to Morvan, M..

5 recordsLinked to original sources

bioRxiv2026

BraiNN: A Modern Simulator for Clinically Feasible Personalized Whole-Brain Network Modeling

Personalized whole-brain modeling aims to transform treatment planning for neurological disorders by enabling patient-specific simulations of brain network dynamics. Neural mass models (NMMs) offer a tractable compromise between biophysical detail and computational cost and can be directly linked to macroscopic observables such as EEG. However, scaling NMMs to whole-brain networks with realistic connectivity, conduction delays, and cortical surface resolution--and fitting them to individual patient data--imposes computational demands that existing frameworks cannot meet at clinically relevant timescales. Here we introduce BraiNN, a JAX-based Python framework for large-scale neural mass modeling that achieves speedups of up to two to three orders of magnitude over existing tools by leveraging GPU/TPU-accelerated, XLA-compiled array computation. BraiNN combines a region-level Jansen-Rit network with a subject-specific cortical surface mesh of coupled neural mass models and biophysically grounded EEG forward modeling via reciprocity-based lead fields. Its fully differentiable computational graph enables a hybrid personalization pipeline that pairs Bayesian optimization for global parameter exploration with gradient-based refinement, completing EEG-driven spectral fitting of an eight-dimensional parameter space in approximately 2-3 hours on a single consumer GPU--compared to multiple days with conventional neural mass modeling software. Numerical verification against established benchmarks confirms that BraiNN faithfully reproduces canonical synchronization and bifurcation dynamics of Jansen-Rit networks. By reducing the time requirements for personalizing a high-detail whole-brain surface model from days to a few hours on consumer-grade hardware, BraiNN brings personalized brain network modeling closer to practical use in clinical contexts. We anticipate that BraiNN will serve as a foundation for patient-specific digital twins and EEG-guided neuromodulation planning.

neuroscience↗

bioRxiv2026

SexPeptID: an automated and reproducible workflow for paleoproteomics sex estimation in archaeological enamel

Accurate biological sex estimation is a key objective in archaeological and bioanthropological research but remains challenging when skeletal remains are fragmented, juvenile, or poorly preserved. Paleoproteomics approaches based on the detection of sex-specific amelogenin peptides (AMELX/AMELY) have emerged as a powerful alternative to osteological and genetic methods. However, current workflows often lack standardized criteria for peptide-level confidence assessment, potentially affecting the reproducibility and reliability of sex assignments. In this study, I evaluated the impact of peptide-level confidence filtering on paleoproteomics-based sex estimation through the reanalysis of 164 Homo sapiens individuals from 10 published datasets and 26 Bos taurus individuals from 3 datasets, spanning contexts from the Pleistocene to the present. To address methodological inconsistencies, I developed SexPeptID, an R/Shiny-based framework that integrates Posterior Error Probability (PEP) filtering, standardized peptide selection, and explicit uncertainty assessment. Application of SexPeptID revealed that peptide-level filtering substantially affects sex assignment outcomes: 17 previously classified males (10.4%) were reclassified as non-conclusive, while 5 individuals (3.1%) were identified as potentially female. Despite this sensitivity, AMELX/AMELY-based sex estimation remained robust overall, with stable signal ratios observed across archaeological periods. Variability in peptide intensities was primarily associated with dataset-specific factors rather than temporal differences, highlighting the influence of analytical workflows and preservation conditions. By incorporating confidence-based filtering and a non-conclusive classification category, SexPeptID improves the transparency, reproducibility, and reliability of palaeoproteomics sex estimation, providing a standardized framework for future archaeological and bioanthropological studies. HighlightsO_LISexPeptID provides a reproducible framework for amelogenin-based sex estimation. C_LIO_LIPeptide-level confidence filtering significantly affects paleoproteomics sex estimates. C_LIO_LI13.4% of published male assignments were revised after confidence filtering. C_LIO_LIAMELX/AMELY ratios show temporal stability from modern to Pleistocene samples. C_LIO_LIStandardized uncertainty assessment strengthens palaeoproteomics inference. C_LI

evolutionary biology↗

bioRxiv2026

First paleoproteomics evidence of Panicum miliaceum consumption in human dental calculus

Ancient proteins provide a direct window into past diets by enabling the identification of consumed foods through the analysis of dental calculus. While previous studies have reliably detected animal-derived proteins such as milk, plant-derived proteins remain markedly underrepresented, leaving a significant gap in our understanding of the role of plants in past human diets. Here, we re-analyze open-access paleoproteomics datasets using an expanded protein database approach. This approach incorporates both reviewed and unreviewed entries, enabling the detection of species-specific protein sequences not validated in commonly used databases. We focus on the proteome of Panicum miliaceum and revisit two archaeological dental calculus datasets spanning the Eneolithic to Iron Age from the Pontic-Caspian region and the Levantine coast (n = 63 individuals). We identify 60 unique peptides derived from 60 previously overlooked proteins of Panicum miliaceum in 39 individuals. All peptides are taxonomically unique to Panicum miliaceum and were confidently assigned using a stringent multi-tier validation strategy. These results provide the first paleoproteomic evidence of its consumption in human dental calculus, thereby revising its chronology and dispersal pathways across Eurasia. More broadly, this study demonstrates that expanding protein databases beyond current annotations enables the detection of underrepresented plant taxa and provides a generalizable framework for improving plant identification in paleoproteomics.

evolutionary biology↗

bioRxiv2026

High-throughput targeted paleoproteomics sex estimation on medieval Great Moravia individuals using MALDI-CASI-FTICR mass spectrometry

The estimation of the biological sex of archeological remains is crucial information in bioarchaeology and forensic anthropology. In recent years, proteomics based on molecular sexual dimorphism have emerged as a preferred method, particularly because of its minimally-invasive approach to extracting amelogenin X and Y proteins from tooth enamel. However, there is an increasing demand to accelerate this process while facilitating the analysis of large archaeological assemblages. This study presents a novel high-throughput targeted paleoproteomics method for biological sex estimation using MALDI-CASI-FTICR mass spectrometry. This approach combines the strengths of existing methods, including ultra-high resolution, significantly reduced processing times, targeted analysis, and scalability to large archaeological sample sets. The method was initially validated on modern individuals with known sex and subsequently applied to 130 adult and juvenile individuals from medieval Great Moravia (present-day Czech Republic). Biological sex was successfully estimated for all but one of the individuals. The results not only provide a more efficient biological sex estimation but also help to resolve a few errors in sex assessment previously encountered with osteomorphological and tooth morphometric techniques. The implementation of this method significantly improves the accuracy and efficiency of biological sex estimation, offering a powerful tool for anthropological research. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC="FIGDIR/small/706309v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@1ede7e6org.highwire.dtl.DTLVardef@13d2f5org.highwire.dtl.DTLVardef@17ee44dorg.highwire.dtl.DTLVardef@1be9dd9_HPS_FORMAT_FIGEXP M_FIG C_FIG

evolutionary biology↗

bioRxiv2022

Involvement of an IgE/Mast cell/B cell amplification loop in abdominal aortic aneurysm progression

AimsIgE type immunoglobulins and their specific effector cells, mast cells (MCs), are associated with abdominal aortic aneurysm (AAA) progression. In parallel, immunoglobulin-producing B cells, organised in tertiary lymphoid organs (TLOs) within the aortic wall, have also been linked to aneurysmal progression. We aimed at investigating the potential role and mechanism linking local MCs, TLO B cells, and IgE production in aneurysmal progression. Methods and ResultsThrough histological assays conducted on human surgical samples from AAA patients, we uncovered that activated MCs were enriched at sites of unhealed haematomas, due to subclinical aortic wall fissuring, in close proximity to adventitial IgE+ TLO B cells. Remarkably, in vitro the IgEs deriving from these samples enhanced MC production of IL-4, a cytokine which favors IgE class-switching and production by B cells. Finally, the role of MCs in aneurysmal progression was further analysed in vivo in ApoE-/- mice subjected to angiotensin II infusion aneurysm model, through MC-specific depletion after the establishment of dissecting aneurysms. MC-specific depletion improved intramural haematoma healing and reduced aneurysmal progression. ConclusionsOur data suggest that MC located close to aortic wall fissures are activated by adventitial TLO B cell-produced IgEs and participate to their own activation by providing support for further IgE synthesis through IL-4 production. By preventing prompt repair of aortic subclinical fissures, such a runaway MC activation loop could precipitate aneurysmal progression, suggesting that MC-targeting treatments may represent an interesting adjunctive therapy for reducing AAA progression.

pathology↗