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Abstract The Caribbean & Mesoamerica Biogeochemical Isotope Overview (CAMBIO) is an archaeological data community designed to integrate published biogeochemical data from the Caribbean, Mesoamerica, and southern Central America to address questions about dynamic interactions among humans, animals, and the environment in the region over the past 10,000 years. Here we present the CAMBIO human dataset, which consists of more than 16,000 isotopic measurements from human skeletal tissue samples (δ¹³C, δ¹⁵N, δ³⁴S, δ¹⁸O,⁸⁷Sr/⁸⁶Sr,^206/204Pb,^207/204Pb,^208/204Pb,^207/206Pb) from 290 archaeological sites dating between 7000 BC to modern times. The open-access dataset also includes detailed chronological, contextual, and laboratory/sample preparation information for each measurement. The collated data are deposited on the open-access CAMBIO data community via the Pandora Initiative data platform (https://pandoradata.earth/organization/cambio). 

Abstract With the efflorescence of palaeoscientific approaches to the past, historians have been confronted with a wealth of new evidence on both human and natural phenomena, from human disease and migration through to landscape change and climate. These new data require a rewriting of our narratives of the past, questioning what constitutes an authoritative historical source and who is entitled to recount history to contemporary societies. Humanities-based historical inquiry must embrace this new evidence, but to do so historians need to engage with it in a critical manner, just as they engage critically with textual and material sources. This article highlights the most vital methodological issues, ranging from the spatiotemporal scales and heterogeneity of the new evidence to the new roles attributed to quantitative methods and the place of scientific data in narrative construction. It considers areas of study where the palaeosciences have “intruded” into fields and subjects previously reserved for historians, especially socioeconomic, climate, and environmental history. The authors argue that active engagement with new approaches is urgently needed if historians want to contribute to our evolving understanding of the challenges of the Anthropocene. 

The T cell receptor (TCR) initiates the elimination of pathogens and tumors by T cells. To avoid damage to the host, the receptor must be capable of discriminating between wild-type and mutated self and nonself peptide ligands presented by host cells. Exactly how the TCR does this is unknown. In resting T cells, the TCR is largely unphosphorylated due to the dominance of phosphatases over the kinases expressed at the cell surface. However, when agonist peptides are presented to the TCR by major histocompatibility complex proteins expressed by antigen-presenting cells (APCs), very fast receptor triggering, i.e., TCR phosphorylation, occurs. Recent work suggests that this depends on the local exclusion of the phosphatases from regions of contact of the T cells with the APCs. Here, we developed and tested a quantitative treatment of receptor triggering reliant only on TCR dwell time in phosphatase-depleted cell contacts constrained in area by cell topography. Using the model and experimentally derived parameters, we found that ligand discrimination likely depends crucially on individual contacts being ∼200 nm in radius, matching the dimensions of the surface protrusions used by T cells to interrogate their targets. The model not only correctly predicted the relative signaling potencies of known agonists and nonagonists but also achieved this in the absence of kinetic proofreading. Our work provides a simple, quantitative, and predictive molecular framework for understanding why TCR triggering is so selective and fast and reveals that, for some receptors, cell topography likely influences signaling outcomes.