Forage grass growth under future climate change scenarios affects fermentation and ruminant efficiency

With an increasing human population access to ruminant products is an important factor in global food supply. While ruminants contribute to climate change, climate change could also affect ruminant production. Here we investigated how the plant response to climate change affects forage quality and subsequent rumen fermentation. Models of near future climate change (2050) predict increases in temperature, CO2, precipitation and altered weather systems which will produce stress responses in field crops. We hypothesised that pre-exposure to altered climate conditions causes compositional changes and also primes plant cells such that their post-ingestion metabolic response to the rumen is altered. This “stress memory” effect was investigated by screening ten forage grass varieties in five differing climate scenarios, including current climate (2020), future climate (2050), or future climate plus flooding, drought or heat shock. While varietal differences in fermentation were detected in terms of gas production, there was little effect of elevated temperature or CO2 compared with controls (2020). All varieties consistently showed decreased digestibility linked to decreased methane production as a result of drought or an acute flood treatment. These results indicate that efforts to breed future forage varieties should target tolerance of acute stress rather than long term climate

Global surgery, obstetric, and anaesthesia indicator definitions and reporting: An Utstein consensus report

Background Indicators to evaluate progress towards timely access to safe surgical, anaesthesia, and obstetric (SAO) care were proposed in 2015 by the Lancet Commission on Global Surgery. These aimed to capture access to surgery, surgical workforce, surgical volume, perioperative mortality rate, and catastrophic and impoverishing financial consequences of surgery. Despite being rapidly taken up by practitioners, data points from which to derive the indicators were not defined, limiting comparability across time or settings. We convened global experts to evaluate and explicitly define—for the first time—the indicators to improve comparability and support achievement of 2030 goals to improve access to safe affordable surgical and anaesthesia care globally. Methods and findings The Utstein process for developing and reporting guidelines through a consensus building process was followed. In-person discussions at a 2-day meeting were followed by an iterative process conducted by email and virtual group meetings until consensus was reached. The meeting was held between June 16 to 18, 2019; discussions continued until August 2020. Participants consisted of experts in surgery, anaesthesia, and obstetric care, data science, and health indicators from high-, middle-, and low-income countries. Considering each of the 6 indicators in turn, we refined overarching descriptions and agreed upon data points needed for construction of each indicator at current time (basic data points), and as each evolves over 2 to 5 (intermediate) and >5 year (full) time frames. We removed one of the original 6 indicators (one of 2 financial risk protection indicators was eliminated) and refined descriptions and defined data points required to construct the 5 remaining indicators: geospatial access, workforce, surgical volume, perioperative mortality, and catastrophic expenditure. A strength of the process was the number of people from global institutes and multilateral agencies involved in the collection and reporting of global health metrics; a limitation was the limited number of participants from low- or middle-income countries—who only made up 21% of the total attendees. Conclusions To track global progress towards timely access to quality SAO care, these indicators—at the basic level—should be implemented universally as soon as possible. Intermediate and full indicator sets should be achieved by all countries over time. Meanwhile, these evolutions can assist in the short term in developing national surgical plans and collecting more detailed data for research studies.publishedVersio

Physical activity for people with dementia: A scoping study

Background: This scoping study aimed to identify how physical activity may benefit people with dementia; how and/or if current service provide these benefits; and what support they need to do so. Methods: Methods included an evidence review using literature; mapping current service provision through a survey; and in-depth interviews with a sample of service providers. Results: The 26 studies included in the review indicated the potential effectiveness of physical activity for people with dementia, including improvements in cognition and mood, behaviour and physical condition. Mechanisms of action and the link with outcomes were poorly defined and implemented. The mapping survey and related interviews showed that service providers were delivering a range of services broadly consistent with the scientific evidence. They tended to take a holistic view of possible benefits, and focused on enjoyment and well-being, more than specific cognitive, physical and behavioural outcomes highlighted in literature. Service providers needed more evidence based information and resources to develop services and realise their potential. Conclusion: Despite potential benefits demonstrated in literature and practice, there is a need for further research to optimise interventions and to consider some neglected issues including delivery at home and in communities; impacts for carers; physical activities through ADLs; and individual needs. Studies are needed which take a more holistic approach to the effects of physical activity, and outcomes should be broader and include mental health and wellbeing

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Metabolite fingerprinting of rumen interactome fractions using Fourier Transform Infra-Red spectroscopy.

<p>Fourier Transform Infra-Red (FTIR) spectra of fractions of rumen microbe-plant fermentation mixes fractionated into (<b>A</b>) residue (plant residue including colonising micro-organisms), (<b>B</b>) pellet (bacterial pellet recovered from planktonic phase) and (<b>C</b>) footprint (cell free planktonic phase liquor). Areas of the spectra corresponding to discrete chemical groups are highlighted in grey; sugars (wavenumbers 900-950 cm^-1), amides (wavenumbers 1680-1655 cm^-1 [Amide I] and 1530-1550cm^-1 [Amide II]) and fatty acids (wavenumbers 3100-2800 cm^-1). Principal Component Analyses (PCA) of FTIR spectra from (<b>D</b>) residue, (<b>E</b>) footprint and (<b>F</b>) pellet samples. Discriminant Function Analyses (DFA) based on 3 PCs from FTIR spectra for (<b>G</b>) residue, (<b>H</b>) footprint and (<b>I</b>) pellet samples. Total explained variance (TEV) by 3 PCs for each DFA model is indicated. Green/ P = Premium; blue/ D = AberDart; red/ M = AberMagic. 0, 2, 4, 6 12 and 24 refers to the corresponding hours after addition of rumen microbes to plant genotypes. </p

Metabolite fingerprinting of the footprint fraction of the rumen microbe-plant genotype interactome.

<p>Principal Component Analyses (PCA) of FTIR spectra from (<b>A</b>) Premium, (<b>B</b>) AberDart and (<b>C</b>) AberMagic. Discriminant Function Analyses (DFA) based on 3 PCs for (<b>D</b>) Premium, (<b>E</b>) AberDart and (<b>F</b>) AberMagic. Total explained variance (TEV) by 3 PCs for each DFA model is indicated. P = Premium; D = AberDart; M = AberMagic. 0 (blue circles), 2 (green cross), 4 (black cross), 6 (blue down triangle), 12 (red square) and 24 (cyan triangle) refers to the corresponding hours after addition of rumen microbes to plant genotypes. The loading vectors indicating major sources of variation within DF1 in (<b>G</b>) Premium, (<b>H</b>) AberDart and (<b>I</b>) AberMagic. The horizontal red lines (G, H, I) indicate the points were wavenumbers are making no contribution to DF1. Areas of the spectra corresponding to discrete chemical groups are highlighted in grey; sugars (wavenumbers 900-950 cm^-1), amides (wavenumbers 1680-1655 cm^-1 [Amide I] and 1530-1550cm^-1 [Amide II]), fatty acids (wavenumbers 3100-2800 cm^-1) and substituted alkanes (wavenumbers 1750-1800 cm^-1).</p

Metabolite fingerprinting of the residue fraction of the rumen microbe-plant genotype interactome.

<p>Principal Component Analyses (PCA) of FTIR spectra from (<b>A</b>) Premium, (<b>B</b>) AberDart and (<b>C</b>) AberMagic. Discriminant Function Analyses (DFA) based on 3 PCs for (<b>D</b>) Premium, (<b>E</b>) AberDart and (<b>F</b>) AberMagic. Total explained variance (TEV) by 3 PCs for each DFA model is indicated. P = Premium; D = AberDart; M = AberMagic. 0 (blue circles), 2 (green cross), 4 (black cross), 6 (blue down triangle), 12 (red square) and 24 (cyan triangle) refers to the corresponding hours after addition of rumen microbes to plant genotypes. The loading vectors indicating major sources of variation within DF1 in (<b>G</b>) Premium, (<b>H</b>) AberDart and (<b>I</b>) AberMagic. The horizontal red lines (G, H, I) indicate the points where wavenumbers are making no contribution to DF1. Areas of the spectra corresponding to discrete chemical groups are highlighted in grey; sugars (wavenumbers 900-950 cm^-1), amides (wavenumbers 1680-1655 cm^-1 [Amide I] and 1530-1550cm^-1 [Amide II]), fatty acids (wavenumbers 3100-2800 cm^-1) and substituted alkanes (wavenumbers 1750-1800 cm^-1).</p