A systematic forest survey showing an association of Saccharomyces paradoxus with oak leaf litter.

Although we understand the genetics of the laboratory model yeast Saccharomyces cerevisiae very well, we know little about the natural ecology and environment that shaped its genome. Most isolates of Saccharomyces paradoxus, the wild relative of S. cerevisiae, come from oak trees, but it is not known whether this is because oak is their primary habitat. We surveyed leaf litter in a forest in Northern Germany and found a strong correlation between isolation success of wild Saccharomyces and the proximity of the nearest oak. We compared the four most common tree genera and found Saccharomyces most frequently in oak litter. Interestingly, we show that Saccharomyces is much more abundant in oak leaf litter than on oak bark, suggesting that it grows in litter or soil rather than on the surfaces of oaks themselves. The distribution and abundance of Saccharomyces over the course of a year shows that oak leaf litter provides a stable habitat for the yeast, although there was significant tree-to-tree variation. Taken together, our results suggest that leaf litter rather than tree surfaces provide the better habitat for wild Saccharomyces, with oak being the preferred tree genus. 99.5% of all strains (633/636) isolated were S. paradoxus

Measuring microbial fitness in a field reciprocal transplant experiment

Microbial fitness is easy to measure in the laboratory, but difficult to measure in the field. Laboratory fitness assays make use of controlled conditions and genetically modified organisms, neither of which are available in the field. Among other applications, fitness assays can help researchers detect adaptation to different habitats or locations. We designed a competitive fitness assay to detect adaptation of Saccharomyces paradoxus isolates to the habitat they were isolated from (oak or larch leaf litter). The assay accurately measures relative fitness by tracking genotype frequency changes in the field using digital droplet PCR (DDPCR). We expected locally adapted S. paradoxus strains to increase in frequency over time when growing on the leaf litter type from which they were isolated. The DDPCR assay successfully detected fitness differences among S. paradoxus strains, but did not find a tendency for strains to be adapted to the habitat they were isolated from. Instead, we found that the natural alleles of the hexose transport gene we used to distinguish S. paradoxus strains had significant effects on fitness. The origin of a strain also affected its fitness: strains isolated from oak litter were generally fitter than strains from larch litter. Our results suggest that dispersal limitation and genetic drift shape S. paradoxus populations in the forest more than local selection does, although further research is needed to confirm this. Tracking genotype frequency changes using DDPCR is a practical and accurate microbial fitness assay for natural environments

Reionization and cosmic dawn astrophysics from the Square Kilometre Array:impact of observing strategies

Interferometry of the cosmic 21-cm signal is set to revolutionize our understanding of the epoch of reionization (EoR) and the cosmic dawn (CD). The culmination of ongoing efforts will be the upcoming Square Kilometre Array (SKA), which will provide tomography of the 21-cm signal from the first billion years of our Universe. Using a galaxy formation model informed by high-z luminosity functions, here we forecast the accuracy with which the first phase of SKA-low (SKA1-low) can constrain the properties of the unseen galaxies driving the astrophysics of the EoR and CD. We consider three observing strategies: (i) deep (1000 h on a single field); (ii) medium-deep (100 h on 10 independent fields); and (iii) shallow (10 h on 100 independent fields). Using the 21-cm power spectrum as a summary statistic, and conservatively only using the 21-cm signal above the foreground wedge, we predict that all three observing strategies should recover astrophysical parameters to a fractional precision of 3c0.1-10 per cent. The reionization history is recovered to an uncertainty of \u394z 7e 0.1 (1\u3c3 ) for the bulk of its duration. The medium-deep strategy, balancing thermal noise against cosmic variance, results in the tightest constraints, slightly outperforming the deep strategy. The shallow observational strategy performs the worst, with up to an 3c10-60 per cent increase in the recovered uncertainty. We note, however, that non-Gaussian summary statistics, tomography, as well as unbiased foreground removal would likely favour the deep strategy

Physical Activity Intervention for Loneliness (PAIL) in community-dwelling older adults: protocol for a feasibility study

Background Low-quality social relationships in older adults are strongly associated with feelings of loneliness. Physical activity interventions could reduce loneliness and improve psychological well-being, among other health benefits. The aim of this study is to examine the feasibility of a Physical Activity Intervention for Loneliness (PAIL) in community-dwelling older adults at risk for loneliness. Methods/design This feasibility study is a two-arm randomised controlled trial (RCT) with a wait-list control group using a mixed-methods research design. The primary aim of the feasibility study is to estimate recruitment, retention and adherence rates; the appropriateness of the intervention design and its practicality; the acceptability of the intervention by participants; and the set of instruments and measures and primary outcome measures to inform a future large-scale randomised trial. After eligibility screening, randomisation will be conducted using computer-based random sequence generation. Baseline and post-intervention assessments for intervention and control groups will include height, weight, body mass index, resting blood pressure, physical activity using accelerometry, loneliness, social support, social networks, anxiety and depression, self-efficacy for exercise, satisfaction with social contacts, and expected outcomes and barriers for exercise using questionnaires. Focus groups will be conducted at the mid-point and post-intervention period using a phenomenological approach to analyse the participants’ experiences of taking part in PAIL. Discussion This trial will provide important information regarding the feasibility of PAIL in community-dwelling older adults at risk for loneliness using a mixed-methods approach combining quantitative and qualitative research methods

New methods for unmixing sediment grain size data

Grain size distribution (GSD) data are widely used in Earth sciences and although large data sets are regularly generated, detailed numerical analyses are not routine. Unmixing GSDs into components can help understand sediment provenance and depositional regimes/processes. End-member analysis (EMA), which fits one set of end-members to a given data set, is a powerful way to unmix GSDs into geologically meaningful parts. EMA estimates end-members based on covariability within a data set and can be considered as a nonparametric approach. Available EMA algorithms, however, either produce suboptimal solutions or are time consuming. We introduce unmixing algorithms inspired by hyperspectral image analysis that can be applied to GSD data and which provide an improvement over current techniques. Nonparametric EMA is often unable to identify unimodal grain size subpopulations that correspond to single sediment sources. An alternative approach is single-specimen unmixing (SSU), which unmixes individual GSDs into unimodal parametric distributions (e.g., lognormal). We demonstrate that the inherent nonuniqueness of SSU solutions renders this approach unviable for estimating underlying mixing processes. To overcome this, we develop a new algorithm to perform parametric EMA, whereby an entire data set can be unmixed into unimodal parametric end-members (e.g., Weibull distributions). This makes it easier to identify individual grain size subpopulations in highly mixed data sets. To aid investigators in applying these methods, all of the new algorithms are available in AnalySize, which is GUI software for processing and unmixing grain size data

Attending work with chronic pain is associated with higher levels of psychosocial stress

Background & Aims Much is known about the impact of pain in terms of medical costs and missed work. Less is known about its associations when individuals are present for work. This study examines “presenteeism” by analysing the psychosocial costs of pain in the workplace, using the 2015 European Working Conditions Survey (EWCS). Methods We conducted cross-sectional analysis of 2,384 individuals with chronic pain, and 2,263 individuals without pain (matched by age and sex), using data from the European Working Condition Survey (2015). We compared groups in terms of the following psychosocial factors: Supervisor Support, Job Responsibility, Team Cohesion, Discrimination, Threats/Abuse, Job Competency, Job Reward, Sexual Harassment, Stress, and Job Security. The groups were also compared in terms of days lost due to illness. Results People with pain were 64% less likely to view their job as rewarding (OR .61, 95% CI .57-.65), 47% more likely to be subjected to threats/abuse in the workplace (OR .68, 95% CI .63-.73), 30% more likely to report poor supervisor support (OR .77, 95% CI .73-.82), and 28% more likely to perceive discrimination in the workplace (OR .78, 95% CI .71-.85). People with pain missed approximately 9 more days of work per year than the non-pain respondents

Clinical and public health implications of increasing notifications of LEE-negative Shiga toxin-producing Escherichia coli in England, 2014–2022

Introduction. Shiga toxin-producing Escherichia coli (STEC) belong to a diverse group of gastrointestinal pathogens. The pathogenic potential of STEC is enhanced by the presence of the pathogenicity island called the Locus of Enterocyte Effacement (LEE), including the intimin encoding gene eae. Gap statement. STEC serotypes O128:H2 (Clonal Complex [CC]25), O91:H14 (CC33), and O146:H21 (CC442) are consistently in the top five STEC serotypes isolated from patients reporting gastrointestinal symptoms in England. However, they are eae/LEE-negative and perceived to be a low risk to public health, and we know little about their microbiology and epidemiology. Aim. We analysed clinical outcomes and genome sequencing data linked to patients infected with LEE-negative STEC belonging to CC25 (O128:H2, O21:H2), CC33 (O91:H14) and, and CC442 (O146:H21, O174:H21) in England to assess the risk to public health. Results. There was an almost ten-fold increase between 2014 and 2022 in the detection of all STEC belonging to CC25, CC33 and CC442 (2014 n=38, 2022 n=336), and a total of 1417 cases. There was a higher proportion of female cases (55–70 %) and more adults than children, with patients aged between 20–40 and >70 most at risk across the different serotypes. Symptoms were consistent across the three dominant serotypes O91:H14 (CC33), O146:H21 (CC442) and O128:H2 (CC25) (diarrhoea >75 %; bloody diarrhoea 25–32 %; abdominal pain 64–72 %; nausea 37–45 %; vomiting 10–24 %; and fever 27–30 %). Phylogenetic analyses revealed multiple events of acquisition and loss of different stx-encoding prophage. Additional putative virulence genes were identified including iha, agn43 and subA. Conclusions. Continued monitoring and surveillance of LEE-negative STEC infections is essential due to the increasing burden of infectious intestinal disease, and the risk that highly pathogenic strains may emerge following acquisition of the Shiga toxin subtypes associated with the most severe clinical outcomes