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      Enhancing mummy ‘palaeobiographies’ through the use of multidisciplinary techniques and approaches

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          THE INTCAL20 NORTHERN HEMISPHERE RADIOCARBON AGE CALIBRATION CURVE (0–55 CAL kBP)

          Radiocarbon ( 14 C) ages cannot provide absolutely dated chronologies for archaeological or paleoenvironmental studies directly but must be converted to calendar age equivalents using a calibration curve compensating for fluctuations in atmospheric 14 C concentration. Although calibration curves are constructed from independently dated archives, they invariably require revision as new data become available and our understanding of the Earth system improves. In this volume the international 14 C calibration curves for both the Northern and Southern Hemispheres, as well as for the ocean surface layer, have been updated to include a wealth of new data and extended to 55,000 cal BP. Based on tree rings, IntCal20 now extends as a fully atmospheric record to ca. 13,900 cal BP. For the older part of the timescale, IntCal20 comprises statistically integrated evidence from floating tree-ring chronologies, lacustrine and marine sediments, speleothems, and corals. We utilized improved evaluation of the timescales and location variable 14 C offsets from the atmosphere (reservoir age, dead carbon fraction) for each dataset. New statistical methods have refined the structure of the calibration curves while maintaining a robust treatment of uncertainties in the 14 C ages, the calendar ages and other corrections. The inclusion of modeled marine reservoir ages derived from a three-dimensional ocean circulation model has allowed us to apply more appropriate reservoir corrections to the marine 14 C data rather than the previous use of constant regional offsets from the atmosphere. Here we provide an overview of the new and revised datasets and the associated methods used for the construction of the IntCal20 curve and explore potential regional offsets for tree-ring data. We discuss the main differences with respect to the previous calibration curve, IntCal13, and some of the implications for archaeology and geosciences ranging from the recent past to the time of the extinction of the Neanderthals.
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            Multi-omics approaches to disease

            High-throughput technologies have revolutionized medical research. The advent of genotyping arrays enabled large-scale genome-wide association studies and methods for examining global transcript levels, which gave rise to the field of “integrative genetics”. Other omics technologies, such as proteomics and metabolomics, are now often incorporated into the everyday methodology of biological researchers. In this review, we provide an overview of such omics technologies and focus on methods for their integration across multiple omics layers. As compared to studies of a single omics type, multi-omics offers the opportunity to understand the flow of information that underlies disease.
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              Discussion Reporting of 14C Data

              Count rates, representing the rate of 14C decay, are the basic data obtained in a 14C laboratory. The conversion of this information into an age or geochemical parameters appears a simple matter at first. However, the path between counting and suitable 14C data reporting (table 1) causes headaches to many. Minor deflections in pathway, depending on personal interpretations, are possible and give end results that are not always useful for inter-laboratory comparisons. This discussion is an attempt to identify some of these problems and to recommend certain procedures by which reporting ambiguities can be avoided.
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                Author and article information

                Journal
                Journal of Archaeological Science: Reports
                Journal of Archaeological Science: Reports
                Elsevier BV
                2352409X
                February 2023
                February 2023
                : 47
                : 103784
                Article
                10.1016/j.jasrep.2022.103784
                fd36ce15-50f8-4b2c-b312-0a1f160c65b2
                © 2023

                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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