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Hamel, A.

Publications and source records attributed to Hamel, A..

5 recordsLinked to original sources

Maps of historical forests in France and their temporal continuity since the first half of the 19th century

AbstractIntegrating environmental history is essential for understanding present-day ecosystem dynamics and guiding modern conservation strategies, particularly under the EU Biodiversity Strategy for 2030. This data paper presents the nationwide digitisation and vectorisation of the French General Ordnance survey map (1818-1866), capturing the countrys forest cover at its historical minimum (a pivotal moment known as the "forest transition"). The original manuscript sheets surveyed at a 1:40,000 scale (976 sheets) were scanned, georeferenced and vectorised. They offer higher thematic accuracy than the older Cassini map and are far more feasible for nationwide vectorisation than the highly detailed Napoleonic cadastre. The area-weighted mean survey date is 1843, and the dataset covers 99.6% of modern mainland France. To correct for paper deformation, historical surveying errors and coordinate system transformations, a rigorous workflow was established. This shifted from a global 6-parameter affine transformation (root mean square error of 60 m) to a local elastic transformation based on thousands of control points, for 21% of the territory, which reduced the positioning error to 34 m. We assessed data quality by comparing the General Ordnance Survey maps with the Napoleonic cadastre--the standard reference for 19th-century land-use data--across more than 600 municipalities. The correlation between the two sources regarding forest cover percentages was exceptionally high (r>0.9). Because forests formed large, compact blocks of significant strategic interest to military engineers, they were mapped with high precision. Localised inaccuracies were primarily found in remote areas, most notably in the mountains. The resulting historical vector layer was intersected with contemporary forest data (BD Foret(R) v2, 2005-2019). Historical polygons smaller than 0.5 ha were filtered out to comply with modern FAO forest definitions. This spatial overlay generated a new dataset detailing four distinct land-use trajectories: . ancient forests (44.8% of present day forest): land classified as forest in both the 19th century and the present day (indicating maximum temporal continuity). . recent forests (55.2% of present day forest): land that was non-forested in the 19th century but has since undergone reforestation. . deforested areas (18.9% of 19th-century forest): land recorded as forest in the 19th century but subsequently converted to other land uses. . stable non-forest areas: land that has remained unforested across both periods. Our results suggest that the forest area of mainland France at its historical minimum should be revised upward to 9.9 million ha. A preliminary analysis further indicates that current spatial variation in forest cover is explained more by land-use dynamics occurring since the forest transition than by the initial extent of forest cover. These two open-access national datasets (the 19th-century forest layer and the land-use transition map) open the door to a better understanding of present-day forests : e.g. their biodiversity, soil quality, tree growth and belowground water quality. Furthermore, they provide decision-support tools for conservation planning. Key messageIn this data paper, we provide a map of 19th-century forests in France based on the digitisation of the military topographic map (1818-1866). By overlaying this historical source with the present-day forest map, we built a second map which allows the identification of ancient forests, recent forests, and deforestation. These maps offer avenues for historical ecology and the design of conservation strategies.

ecology↗

Multimodal analysis of osteoarthritic chondrocytes reveals mitochondrial alterations and patient-specific OxPhos response to bezafibrate

BackgroundOsteoarthritis (OA) is the most common joint disease and is characterized by bone remodeling, cartilage degradation and synovial inflammation. To date, no effective treatment is available for this debilitating condition. Recent evidence suggests that mitochondrial dysfunction, including oxidative phosphorylation (OxPhos) failure, accumulates within OA chondrocytes and may contribute to pathogenesis. In this context, mitochondrial dysfunction may be associated with observable changes in mitochondrial number, size and shape. However, a comprehensive characterization of mitochondria-related features during OA, from tissue-to-cell level, is still lacking. Addressing these gaps could inform therapeutic strategies, such as the partial restoration of OxPhos, which has been proposed as a therapeutic approach. MethodsHere, we employed a multimodal approach that included Fourier-transform infrared spectroscopy (FTIR), scanning transmission electron microscopy (STEM) and real-time cellular metabolic assays (Seahorse technology) to better characterize mitochondrial parameters in cartilage during OA. Two types of experimental models were used using human cartilage: (1) undamaged versus damaged OA zones, and (2) non-OA versus OA samples. In addition, we investigated the potential of repurposing bezafibrate, an approved peroxisome proliferator-activated receptor (PPAR) agonist, as a mitochondria-based therapy to restore OxPhos in OA chondrocytes. ResultsWe identified that OA chondrocytes exhibit a decrease in glycogen deposits surface, and an increased number of mitochondria alongside an OxPhos dysfunction compared to non-OA chondrocytes. A similar trend toward glycogen storage deficiency and increased mitochondria number was observed in OA chondrocytes from damaged cartilage areas. Furthermore, multivariate analyses revealed that the clinical profiles of OA patients allowed OA chondrocytes to be separated into responders and non-responders to bezafibrate. ConclusionWe provide evidence that OA chondrocytes display decreased glycogen deposits surface, increased mitochondrial number and OxPhos dysfunction. Additionally, we identified that bezafibrate, a PPAR agonist, improved OxPhos function in a subgroup of OA chondrocytes derived from patients.

pathology↗

Resting-state functional connectivity and fast spindle temporal organization contribute to episodic memory consolidation in healthy aging

Episodic memory consolidation relies on the functional specialization of brain networks and sleep quality, both of which are affected by aging. Functional connectivity during wakefulness is crucial to support the integration of newly acquired information into memory networks. Additionally, the temporal dynamics of sleep spindles facilitates overnight memory consolidation by promoting hippocampal replay and integration of memories within neocortical structures. This study aimed at exploring how resting-state functional connectivity during wakefulness contributes to sleep-dependent memory consolidation in aging, and whether spindles clustered in trains modulates this relationship. Forty-two healthy older adults (68.82 {+/-} 3.03 years), enrolled in the Age-Well clinical trial, were included. Sleep-dependent memory consolidation was assessed using a visuo-spatial memory task performed before and after a polysomnography night. Resting-state functional connectivity data were analyzed using graph theory applied to the whole brain, specific brain networks and the hippocampus. Lower limbic network integration and higher centrality of the anterior hippocampus were associated with better memory consolidation. Spindle trains modulated these effects, such that older participants with longer spindle trains exhibited a stronger negative association between limbic network integration and memory consolidation. These results indicate that lower functional specialization at rest is associated with weaker memory consolidation during sleep. This aligns with the dedifferentiation hypothesis, which posits that aging is associated with reduced brain specificity, leading to less efficient cognitive functioning. These findings reveal a novel mechanism linking daytime brain network organization and sleep-dependent memory consolidation, and suggest that targeting spindle dynamics could help preserve cognitive functioning in aging.

neuroscience↗

Allelic variation in Class I HLA determines pre-existing memory responses to SARS-CoV-2 that shape the CD8+ T cell repertoire upon viral exposure

Effective presentation of antigens by HLA class I molecules to CD8+ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multi-omic technology to generate the first unified ex vivo characterization of the CD8+ T cell response to SARS-CoV-2 across 4 major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCR /{beta} sequence diversity, and the utilization of pre-existing SARS-CoV-2 reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations influence pre-existing immunity to SARS-CoV-2 and shape the immune repertoire upon subsequent viral exposure. One-Sentence SummaryWe perform a unified, multi-omic characterization of the CD8+ T cell response to SARS-CoV-2, revealing pre-existing immunity conditioned by HLA genotype.

immunology↗

Cell type specific genetic regulation of gene expression across human tissues

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci (cis-QTLs) for the majority of genes across a wide range of human tissues. However, the interpretation of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. Here, we map interactions between computational estimates of cell type abundance and genotype to identify cell type interaction QTLs for seven cell types and show that cell type interaction eQTLs provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations to 87 complex traits show a contribution from cell type interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.\n\nOne Sentence SummaryEstimated cell type abundances from bulk RNA-seq across tissues reveal the cellular specificity of quantitative trait loci.

genomics↗