Viking Age garden plants from southern Scandinavia: diversity, taphonomy and cultural aspects

Plant finds recovered from archaeological sites in southern Scandinavia dated to the Viking Age reflect the diversity of useful plants that were cultivated and collected. This review presents the results of 14 investigations of deposits that are dated between AD 775 and 1050. The site types are categorized as agrarian, urban, military and burials. Garden plants are unevenly distributed, as the greatest diversity is recorded in features from urban contexts. We argue that taphonomic processes played an important role in the picture displayed. Archaeobotanical research results from neighbouring regions suggest that Viking Age horticulture has its roots in older traditions, and that the spectrum of garden plants is influenced by central and north-western European horticultural customs, which were to a great extent shaped by Roman occupation

Cost-effectiveness of replacing versus discarding the nail in children with nail bed injury

Every year in the UK, around 10 000 children need to have operations to mend injuries to the bed of their fingernails. Currently, most children have their fingernail placed back on the injured nail bed after the operation. The NINJA trial found that children were slightly less likely to have an infection if the nail was thrown away rather than being put back, but the difference between groups was small and could have be due to chance. This study looked at whether replacing the nail is cost-effective compared with throwing it away. Using data from the NINJA trial, we compared costs, healthcare use, and quality of life and assessed the cost-effectiveness of replacing the nail. It was found that throwing the nail away after surgery would save the National Health Service (NHS) £75 (€85) per operation compared with placing the nail back on the nail bed. Changing clinical practice could save the NHS in England £720 000 (€819 000) per year

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Suppression of Skeletal Muscle Turnover in Cancer Cachexia: Evidence from the Transcriptome in Sequential Human Muscle Biopsies

Purpose: The mechanisms underlying muscle wasting in patients with cancer remain poorly understood, and consequently there remains an unmet clinical need for new biomarkers and treatment strategies.Experimental Design: Microarrays were used to examine the transcriptome in single biopsies from healthy controls (n ¼ 6) and in paired biopsies [pre-resection baseline (weight-loss 7%) and 8 month postresection follow-up (disease-free/weight-stable for previous 2 months)] from quadriceps muscle of patients with upper gastrointestinal cancer (UGIC; n ¼ 12).Results: Before surgery, 1,868 genes were regulated compared with follow-up (false discovery rate, 6%). Ontology analysis showed that regulated genes belonged to both anabolic and catabolic biologic processes with overwhelming downregulation in baseline samples.Noliterature-derived genes from preclinical cancer cachexia models showed higher expression in baseline muscle. Comparison with healthy control muscle (n¼6) revealed that despite differences in the transcriptome at baseline (941 genes regulated), the muscle of patients at follow-up was similar to control muscle (2 genes regulated). Physical activity (step count per day) did not differ between the baseline and follow-up periods (P ¼ 0.9), indicating that gene expression differences reflected the removal of the cancer rather than altered physical activity levels. Comparative gene expression analysis using exercise training signatures supported this interpretation.Conclusions: Metabolic and protein turnover–related pathways are suppressed in weight-losing patients with UGIC whereas removal of the cancer appears to facilitate a return to a healthy state, independent of changes in the level of physical activity