Dairying, diseases and the evolution of lactase persistence in Europe

In European and many African, Middle Eastern and southern Asian populations, lactase persistence (LP) is the most strongly selected monogenic trait to have evolved over the past 10,000 years1. Although the selection of LP and the consumption of prehistoric milk must be linked, considerable uncertainty remains concerning their spatiotemporal configuration and specific interactions2,3. Here we provide detailed distributions of milk exploitation across Europe over the past 9,000 years using around 7,000 pottery fat residues from more than 550 archaeological sites. European milk use was widespread from the Neolithic period onwards but varied spatially and temporally in intensity. Notably, LP selection varying with levels of prehistoric milk exploitation is no better at explaining LP allele frequency trajectories than uniform selection since the Neolithic period. In the UK Biobank4,5 cohort of 500,000 contemporary Europeans, LP genotype was only weakly associated with milk consumption and did not show consistent associations with improved fitness or health indicators. This suggests that other reasons for the beneficial effects of LP should be considered for its rapid frequency increase. We propose that lactase non-persistent individuals consumed milk when it became available but, under conditions of famine and/or increased pathogen exposure, this was disadvantageous, driving LP selection in prehistoric Europe. Comparison of model likelihoods indicates that population fluctuations, settlement density and wild animal exploitation-proxies for these drivers-provide better explanations of LP selection than the extent of milk exploitation. These findings offer new perspectives on prehistoric milk exploitation and LP evolution.

Evaluation of correlated studies using liquid cell‐ and cryo‐transmission electron microscopy: Hydration of calcium sulfate and the phase transformation pathways of bassanite to gypsum

Insight into the nucleation, growth and phase transformations of calcium sulphate could improve the performance of construction materials, reduce scaling in industrial processes and aid understanding of its formation in the natural environment. Recent studies have suggested that the calcium sulphate pseudo polymorph, gypsum (CaSO₄ ·2H₂ O) can form in aqueous solution via a bassanite (CaSO₄ ·0.5H₂ O) intermediate. Some in situ experimental work has also suggested that the transformation of bassanite to gypsum can occur through an oriented assembly mechanism. In this work, we have exploited liquid cell transmission electron microscopy (LCTEM) to study the transformation of bassanite to gypsum in an undersaturated aqueous solution of calcium sulphate. This was benchmarked against cryogenic TEM (cryo-TEM) studies to validate internally the data obtained from the two microscopy techniques. When coupled with Raman spectroscopy, the real-time data generated by LCTEM, and structural data obtained from cryo-TEM show that bassanite can transform to gypsum via more than one pathway, the predominant one being dissolution/reprecipitation. Comparisons between LCTEM and cryo-TEM also show that the transformation is slower within the confined region of the liquid cell as compared to a bulk solution. This work highlights the important role of a correlated microscopy approach for the study of dynamic processes such as crystallisation from solution if we are to extract true mechanistic understanding.

Accurate compound-specific 14C dating of archaeological pottery vessels

Pottery is one of the most commonly recovered artefacts from archaeological sites. Despite more than a century of relative dating based on typology and seriation¹, accurate dating of pottery using the radiocarbon dating method has proven extremely challenging owing to the limited survival of organic temper and unreliability of visible residues^2-4. Here we report a method to directly date archaeological pottery based on accelerator mass spectrometry analysis of ¹⁴C in absorbed food residues using palmitic (C_16:0) and stearic (C_18:0) fatty acids purified by preparative gas chromatography^5-8. We present accurate compound-specific radiocarbon determinations of lipids extracted from pottery vessels, which were rigorously evaluated by comparison with dendrochronological dates^9,10 and inclusion in site and regional chronologies that contained previously determined radiocarbon dates on other materials^11-15. Notably, the compound-specific dates from each of the C_16:0 and C_18:0 fatty acids in pottery vessels provide an internal quality control of the results⁶ and are entirely compatible with dates for other commonly dated materials. Accurate radiocarbon dating of pottery vessels can reveal: (1) the period of use of pottery; (2) the antiquity of organic residues, including when specific foodstuffs were exploited; (3) the chronology of sites in the absence of traditionally datable materials; and (4) direct verification of pottery typochronologies. Here we used the method to date the exploitation of dairy and carcass products in Neolithic vessels from Britain, Anatolia, central and western Europe, and Saharan Africa.

Application of automated electron microscopy imaging and machine learning to characterise and quantify nanoparticle dispersion in aqueous media

For many nanoparticle applications it is important to understand dispersion in liquids. For nanomedicinal and nanotoxicological research this is complicated by the often complex nature of the biological dispersant and ultimately this leads to severe limitations in the analysis of the nanoparticle dispersion by light scattering techniques. Here we present an alternative analysis and associated workflow which utilises electron microscopy. The need to collect large, statistically relevant datasets by imaging vacuum dried, plunge frozen aliquots of suspension was accomplished by developing an automated STEM imaging protocol implemented in an SEM fitted with a transmission detector. Automated analysis of images of agglomerates was achieved by machine learning using two free open‐source software tools: CellProfiler and ilastik. The specific results and overall workflow described enable accurate nanoparticle agglomerate analysis of particles suspended in aqueous media containing other potential confounding components such as salts, vitamins and proteins.

Lay Description

In order to further advance studies in both nanomedicine and nanotoxicology, we need to continue to understand the dispersion of nanoparticles in biological fluids. These biological environments often contain a number of components such as salts, vitamins and proteins which can lead to difficulties when using traditional techniques to monitor dispersion. Here we present an alternative analysis which utilises electron microscopy. In order to use this approach statistically relevant large image datasets were collected from appropriately prepared samples of nanoparticle suspensions by implementing an automated imaging protocol. Automated analysis of these images was achieved through machine learning using two readily accessible freeware; CellProfiler and ilastik. The workflow presented enables accurate nanoparticle dispersion analysis of particles suspended in more complex biological media.