Repeated plague infections across six generations of Neolithic Farmers.

In the period between 5,300 and 4,900 calibrated years before present (cal. BP), populations across large parts of Europe underwent a period of demographic decline1,2. However, the cause of this so-called Neolithic decline is still debated. Some argue for an agricultural crisis resulting in the decline3, others for the spread of an early form of plague4. Here we use population-scale ancient genomics to infer ancestry, social structure and pathogen infection in 108 Scandinavian Neolithic individuals from eight megalithic graves and a stone cist. We find that the Neolithic plague was widespread, detected in at least 17% of the sampled population and across large geographical distances. We demonstrate that the disease spread within the Neolithic community in three distinct infection events within a period of around 120 years. Variant graph-based pan-genomics shows that the Neolithic plague genomes retained ancestral genomic variation present in Yersinia pseudotuberculosis, including virulence factors associated with disease outcomes. In addition, we reconstruct four multigeneration pedigrees, the largest of which consists of 38 individuals spanning six generations, showing a patrilineal social organization. Lastly, we document direct genomic evidence for Neolithic female exogamy in a woman buried in a different megalithic tomb than her brothers. Taken together, our findings provide a detailed reconstruction of plague spread within a large patrilineal kinship group and identify multiple plague infections in a population dated to the beginning of the Neolithic decline.

HyperPCM: Robust Task-Conditioned Modeling of Drug-Target Interactions.

A central problem in drug discovery is to identify the interactions between drug-like compounds and protein targets. Over the past few decades, various quantitative structure-activity relationship (QSAR) and proteo-chemometric (PCM) approaches have been developed to model and predict these interactions. While QSAR approaches solely utilize representations of the drug compound, PCM methods incorporate both representations of the protein target and the drug compound, enabling them to achieve above-chance predictive accuracy on previously unseen protein targets. Both QSAR and PCM approaches have recently been improved by machine learning and deep neural networks, that allow the development of drug-target interaction prediction models from measurement data. However, deep neural networks typically require large amounts of training data and cannot robustly adapt to new tasks, such as predicting interaction for unseen protein targets at inference time. In this work, we propose to use HyperNetworks to efficiently transfer information between tasks during inference and thus to accurately predict drug-target interactions on unseen protein targets. Our HyperPCM method reaches state-of-the-art performance compared to previous methods on multiple well-known benchmarks, including Davis, DUD-E, and a ChEMBL derived data set, and particularly excels at zero-shot inference involving unseen protein targets. Our method, as well as reproducible data preparation, is available at https://github.com/ml-jku/hyper-dti.

Task-sharing spinal anaesthesia care in three rural Indian hospitals: a non-inferiority randomised controlled clinical trial.

BACKGROUND: Task-sharing of spinal anaesthesia care by non-specialist graduate physicians, termed medical officers (MOs), is commonly practised in rural Indian healthcare facilities to mitigate workforce constraints. We sought to assess whether spinal anaesthesia failure rates of MOs were non-inferior to those of consultant anaesthesiologists (CA) following a standardised educational curriculum. METHODS: We performed a randomised, non-inferiority trial in three rural hospitals in Tamil Nadu and Chhattisgarh, India. Patients aged over 18 years with low perioperative risk (ASA I & II) were randomised to receive MO or CA care. Prior to the trial, MOs underwent task-based anaesthesia training, inclusive of remotely accessed lectures, simulation-based training and directly observed anaesthetic procedures and intraoperative care. The primary outcome measure was spinal anaesthesia failure with a non-inferiority margin of 5%. Secondary outcome measures consisted of incidence of perioperative and postoperative complications. FINDINGS: Between 12 July 2019 and 8 June 2020, a total of 422 patients undergoing surgical procedures amenable to spinal anaesthesia care were randomised to receive either MO (231, 54.7%) or CA care (191, 45.2%). Spinal anaesthesia failure rate for MOs (7, 3.0%) was non-inferior to those of CA (5, 2.6%); difference in success rate of 0.4% (95% CI=0.36-0.43%; p=0.80). Additionally, there were no statistically significant differences observed between the two groups for intraoperative or postoperative complications, or patients' experience of pain during the procedure. INTERPRETATION: This study demonstrates that failure rates of spinal anaesthesia care provided by trained MOs are non-inferior to care provided by CAs in low-risk surgical patients. This may support policy measures that use task-sharing as a means of expanding anaesthesia care capacity in rural Indian hospitals. TRIAL REGISTRATION NUMBER: NCT04438811.

Human genetic structure in Northwest France provides new insights into West European historical demography.

The demographical history of France remains largely understudied despite its central role toward understanding modern population structure across Western Europe. Here, by exploring publicly available Europe-wide genotype datasets together with the genomes of 3234 present-day and six newly sequenced medieval individuals from Northern France, we found extensive fine-scale population structure across Brittany and the downstream Loire basin and increased population differentiation between the northern and southern sides of the river Loire, associated with higher proportions of steppe vs. Neolithic-related ancestry. We also found increased allele sharing between individuals from Western Brittany and those associated with the Bell Beaker complex. Our results emphasise the need for investigating local populations to better understand the distribution of rare (putatively deleterious) variants across space and the importance of common genetic legacy in understanding the sharing of disease-related alleles between Brittany and people from western Britain and Ireland.