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Vascular Ehlers Danlos Syndrome (vEDS) is a connective tissue disorder caused by COL3A1 mutations for which there are no treatments due to a limited understanding of underlying mechanisms. We aimed to identify the molecular insults of mutations, focusing on collagen folding, to establish if targeting protein folding represents a potential therapeutic approach. Analysis of two novel COL3A1 glycine mutations, G189S and G906R, in primary patient fibroblast cultures revealed secretion of misfolded collagen III and intracellular collagen retention leading to lower extracellular collagen levels. This was associated with matrix defects, endoplasmic reticulum (ER) stress, reduced cell proliferation and apoptosis. The ER stress was mediated by activation of IRE1 and PERK signalling arms with evidence of allelic heterogeneity. To establish if promoting ER protein folding capacity or protein degradation represents novel therapeutic avenues, we investigated the efficacy of FDA-approved small molecules. The chemical chaperone 4-phenylbutyric acid (PBA) rescued the ER stress and thermostability of secreted collagen leading to reduced apoptosis and matrix defects, and its efficacy was influenced by duration, dosage and allelic heterogeneity. Targeting protein degradation with carbamazepine (CBZ), or PBA-CBZ in combination did not increase treatment efficacy. These data establish that ER stress is a molecular mechanism in vEDS that can be influenced by the position of COL3A1 mutation. It combines with matrix defects due to reduced collagen III levels and/or mutant protein secretion to vEDS pathogenesis. Targeting protein folding using FDA-approved chemical chaperones represents a putative mechanism-based therapeutic approach for vEDS that can rescue intra- and extracellular defects.

IntroductionPost-COVID-19 syndromes remain a medical enigma. A disconnect between objective clinical markers and subjective symptoms complicates diagnosis and management for these patients in clinical practice. Catecholamines mediate the host stress response to illness. We therefore hypothesised dysregulation of catecholamine pathways influences the illness trajectory following COVID-19 infection.MethodsThis was a prospective, multicentre cohort study in the West of Scotland, involving post-COVID-19 patients enrolled during their hospitalisation or shortly after discharge (CISCO-19; NCT04403607). Participants underwent serial assessments, including during the index admission and then again 28–60 days after discharge. The design involved a self-controlled time-series of multisystem evaluations. We conducted a plasma proteomics analysis using the SOMAscan® assay v4.1, measuring 7288 proteins in a cohort of 155 participants who had undergone prospective, multisystem phenotyping (MRI, Siemens 3.0T PRISMA; CT chest and pulmonary angiography, Canon Aquilion ONE), incorporating clinical data gathered during the original study period. The statistical analysis of SOMAscan probe-sets, referred to as ‘proteins,’ was performed using R (v4.4.1) and Python (v3.11.5) using the Searchlight2 workflow. Differences in protein expression were assessed using the Wilcoxon rank-sum test. Over-representation analysis was conducted using the MSigDB 2024.1.Hs release for Gene Ontology (GO ) biological processes (GO-BP), GO cellular components (GO-CC), Hallmark, Reactome and STRING.A threshold of Benjamini-Hochberg adjusted p-value (p.adj) < 0.05 was established to determine statistical significance.ResultsAmong the participants (mean age: 55 years; 43% female), 72 (47%) had a history of cardiovascular disease, and 57 (37%) belonged to the highest quintile of social deprivation. Principal component analysis of 401 catecholamine proteins in GO-BP catecholamine pathways identified a distinct participant cluster (n=25, figure 1) characterised by protein expression indicative of heightened catecholamine activity, oxidative stress (Hallmark Reactive Oxygen Species, p.adj=0.03,figure 2) and mitochondrial dysfunction (Reactome, Mitochondrial Protein Degradation, p.adj<0.001) independent of disease severity. This group was characterised by heightened illness perception and reduced cardiorespiratory function, as measured by validated patient reported outcome measures, despite the absence of objective evidence of more severe disease on multisystem, cardio-renal and respiratory imaging in comparison to the remaining cohort (n=130).Abstract BS26 Figure 1Principal component analysis[Image Omitted. See PDF.]Abstract BS26 Figure 2Reactive oxygen species proteins. Blue/Turquoise=Group 1. Brown/Orange=Group 2[Image Omitted. See PDF.]ConclusionTargeted therapies aimed at reducing reactive oxygen species while also improving nitric oxide utilisation and addressing mitochondrial dysfunction within the vasculature could be areas warranting attention in Long-COVID.

More than 50 y of research have provided great insight into the physiology, metabolism, and molecular biology of Salmonella enterica serovar Typhimurium (S. Typhimurium), but important gaps in our knowledge remain. It is clear that a precise choreography of gene expression is required for Salmonella infection, but basic genetic information such as the global locations of transcription start sites (TSSs) has been lacking. We combined three RNA-sequencing techniques and two sequencing platforms to generate a robust picture of transcription in S. Typhimurium. Differential RNA sequencing identified 1,873 TSSs on the chromosome of S. Typhimurium SL1344 and 13% of these TSSs initiated antisense transcripts. Unique findings include the TSSs of the virulence regulators phoP, slyA, and invF. Chromatin immunoprecipitation revealed that RNA polymerase was bound to 70% of the TSSs, and two-thirds of these TSSs were associated with σ70 (including phoP, slyA, and invF) from which we identified the –10 and –35 motifs of σ70-dependent S. Typhimurium gene promoters. Overall, we corrected the location of important genes and discovered 18 times more promoters than identified previously. S. Typhimurium expresses 140 small regulatory RNAs (sRNAs) at early stationary phase, including 60 newly identified sRNAs. Almost half of the experimentally verified sRNAs were found to be unique to the Salmonella genus, and <20% were found throughout the Enterobacteriaceae. This description of the transcriptional map of SL1344 advances our understanding of S. Typhimurium, arguably the most important bacterial infection model.

Feed accounts for the greatest proportion of egg production costs and there is substantial variation in feed to egg conversion ratio (FCR) efficiency between individual hens. Despite this understanding, there is a paucity of information regarding layer hen feeding behaviour, diet selection and its impact on feed efficiency. It was hypothesised that variation in feed to egg conversion efficiency between hens may be influenced by feeding behaviour. For this experiment, two 35-bird groups of ISA Brown layers were selected from 450 individually caged hens at 25-30 weeks of age for either low FCR < 1.8 ± 0.02 (high feed efficiency (HFE) or high FCR > 2.1 ± 0.02 (low feed efficiency (LFE)). For each of these 70 hens, intake of an ad-libitum mash diet at 2-minute time intervals, 24 h a day, for 7 days was determined alongside behavioural assessment and estimation of the selection of components of the mash. The group selected for HFE had a lower feed intake, similar egg mass and associated lower FCR when compared with the LFE group. Whilst feed intake patterns were similar between HFE and LFE hens, there was a distinct intake pattern for all layer hens with intake rate increasing from 0300 to 1700 h with a sharp decline to 2200 h. High feed efficiency hens selected a diet with 25% more ash and 4% less gross energy than LFE hens. The LFE hens also spent more time eating with more walking events, but less time spent resting, drinking, preening and cage pecking events as compared with HFE hens. In summary, there was no contrasting diurnal pattern of feed consumption behaviour between the groups ranked on feed efficiency, however high feed efficiency hens consumed less feed and selected a diet with greater ash content and lower gross energy as compared with LFE hens. Our work is now focused on individual hen diet selection from mash diets with an aim of formulating precision, targeted diets for greater feed efficiency.

There is little evidence on variation in radiotherapy use in different countries, although it is a key treatment modality for some patients with cancer. Here we aimed to examine such variation. This population-based study used data from Norway, the four UK nations (England, Northern Ireland, Scotland, and Wales), nine Canadian provinces (Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, and Saskatchewan), and two Australian states (New South Wales and Victoria). Patients aged 15–99 years diagnosed with cancer in eight different sites (oesophageal, stomach, colon, rectal, liver, pancreatic, lung, or ovarian cancer), with no other primary cancer diagnosis occurring within the 5 years before to 1 year after the index cancer diagnosis or during the study period were included in the study. We examined variation in radiotherapy use from 31 days before to 365 days after diagnosis and time to its initiation, alongside related variation in patient group differences. Information was obtained from cancer registry records linked to clinical or patient management system data, or hospital administration data. Random-effects meta-analyses quantified interjurisdictional variation using 95% prediction intervals (95% PIs). Between Jan 1, 2012, and Dec 31, 2017, of 902 312 patients with a new diagnosis of one of the studied cancers, 115 357 (12·8%) did not meet inclusion criteria, and 786,955 were included in the analysis. There was large interjurisdictional variation in radiotherapy use, with wide 95% PIs: 17·8 to 82·4 (pooled estimate 50·2%) for oesophageal cancer, 35·5 to 55·2 (45·2%) for rectal cancer, 28·6 to 54·0 (40·6%) for lung cancer, and 4·6 to 53·6 (19·0%) for stomach cancer. For patients with stage 2–3 rectal cancer, interjurisdictional variation was greater than that for all patients with rectal cancer (95% PI 37·0 to 84·6; pooled estimate 64·2%). Radiotherapy use was infrequent but variable in patients with pancreatic (95% PI 1·7 to 16·5%), liver (1·8 to 11·2%), colon (1·6 to 5·0%), and ovarian (0·8 to 7·6%) cancer. Patients aged 85–99 years had three-times lower odds of radiotherapy use than those aged 65–74 years, with substantial interjurisdictional variation in this age difference (odds ratio [OR] 0·38; 95% PI 0·20–0·73). Women had slightly lower odds of radiotherapy use than men (OR 0·88, 95% PI 0·77–1·01). There was large variation in median time to first radiotherapy (from diagnosis date) by cancer site, with substantial interjurisdictional variation (eg, oesophageal 95% PI 11·3 days to 112·8 days; pooled estimate 62·0 days; rectal 95% PI 34·7 days to 77·3 days; pooled estimate 56·0 days). Older patients had shorter median time to radiotherapy with appreciable interjurisdictional variation (−9·5 days in patients aged 85–99 years vs 65–74 years, 95% PI −26·4 to 7·4). Large interjurisdictional variation in both use and time to radiotherapy initiation were observed, alongside large and variable age differences. To guide efforts to improve patient outcomes, underlying reasons for these differences need to be established. International Cancer Benchmarking Partnership (funded by the Canadian Partnership Against Cancer, Cancer Council Victoria, Cancer Institute New South Wales, Cancer Research UK, Danish Cancer Society, National Cancer Registry Ireland, The Cancer Society of New Zealand, National Health Service England, Norwegian Cancer Society, Public Health Agency Northern Ireland on behalf of the Northern Ireland Cancer Registry, DG Health and Social Care Scottish Government, Western Australia Department of Health, and Public Health Wales NHS Trust).

Large predators often play important roles in structuring marine communities. To understand the role that these predators play in ecosystems, it is crucial to have knowledge of their interactions and the degree to which their trophic roles are complementary or redundant among species. We used stable isotope analysis to examine the isotopic niche overlap of dolphins Tursiops cf. aduncus, large sharks (>1.5 m total length), and smaller elasmobranchs (sharks and batoids) in the relatively pristine seagrass community of Shark Bay, Australia. Dolphins and large sharks differed in their mean isotopic values for δ13C and δ15N, and each group occupied a relatively unique area in isotopic niche space. The standard ellipse areas (SEAc; based on bivariate standard deviations) of dolphins, large sharks, small sharks, and rays did not overlap. Tiger sharks Galeocerdo cuvier had the highest δ15N values, although the mean δ13C and δ15N values of pigeye sharks Carcharhinus amboinensis were similar. Other large sharks (e.g. sicklefin lemon sharks Negaprion acutidens and sandbar sharks Carcharhinus plumbeus) and dolphins appeared to feed at slightly lower trophic levels than tiger sharks. In this seagrass-dominated ecosystem, seagrassderived carbon appears to be more important for elasmobranchs than it is for dolphins. Habitat use patterns did not correlate well with the sources of productivity supporting diets, suggesting that habitat use patterns may not necessarily be reflective of the resource pools supporting a population and highlights the importance of detailed datasets on trophic interactions for elucidating the ecological roles of predators.

AbstractObjectiveTo develop and validate a pragmatic risk score to predict mortality in patients admitted to hospital with coronavirus disease 2019 (covid-19).DesignProspective observational cohort study.SettingInternational Severe Acute Respiratory and emerging Infections Consortium (ISARIC) World Health Organization (WHO) Clinical Characterisation Protocol UK (CCP-UK) study (performed by the ISARIC Coronavirus Clinical Characterisation Consortium—ISARIC-4C) in 260 hospitals across England, Scotland, and Wales. Model training was performed on a cohort of patients recruited between 6 February and 20 May 2020, with validation conducted on a second cohort of patients recruited after model development between 21 May and 29 June 2020.ParticipantsAdults (age ≥18 years) admitted to hospital with covid-19 at least four weeks before final data extraction.Main outcome measureIn-hospital mortality.Results35 463 patients were included in the derivation dataset (mortality rate 32.2%) and 22 361 in the validation dataset (mortality rate 30.1%). The final 4C Mortality Score included eight variables readily available at initial hospital assessment: age, sex, number of comorbidities, respiratory rate, peripheral oxygen saturation, level of consciousness, urea level, and C reactive protein (score range 0-21 points). The 4C Score showed high discrimination for mortality (derivation cohort: area under the receiver operating characteristic curve 0.79, 95% confidence interval 0.78 to 0.79; validation cohort: 0.77, 0.76 to 0.77) with excellent calibration (validation: calibration-in-the-large=0, slope=1.0). Patients with a score of at least 15 (n=4158, 19%) had a 62% mortality (positive predictive value 62%) compared with 1% mortality for those with a score of 3 or less (n=1650, 7%; negative predictive value 99%). Discriminatory performance was higher than 15 pre-existing risk stratification scores (area under the receiver operating characteristic curve range 0.61-0.76), with scores developed in other covid-19 cohorts often performing poorly (range 0.63-0.73).ConclusionsAn easy-to-use risk stratification score has been developed and validated based on commonly available parameters at hospital presentation. The 4C Mortality Score outperformed existing scores, showed utility to directly inform clinical decision making, and can be used to stratify patients admitted to hospital with covid-19 into different management groups. The score should be further validated to determine its applicability in other populations.Study registrationISRCTN66726260

There are few data on international variation in chemotherapy use, despite it being a key treatment type for some patients with cancer. Here, we aimed to examine the presence and size of such variation. This population-based study used data from Norway, the four UK nations (England, Northern Ireland, Scotland, and Wales), eight Canadian provinces (Alberta, British Columbia, Manitoba, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, and Saskatchewan), and two Australian states (New South Wales and Victoria). Patients aged 15–99 years diagnosed with cancer in eight different sites (oesophageal, stomach, colon, rectal, liver, pancreatic, lung, or ovarian cancer), with no other primary cancer diagnosis occurring from within the 5 years before to 1 year after the index cancer diagnosis or during the study period were included in the study. We examined variation in chemotherapy use from 31 days before to 365 days after diagnosis and time to its initiation, alongside related variation in patient group differences. Information was obtained from cancer registry records linked to clinical or patient management system data or hospital administration data. Random-effects meta-analyses quantified interjurisdictional variation using 95% prediction intervals (95% PIs). Between Jan 1, 2012, and Dec 31, 2017, of 893 461 patients with a new diagnosis of one of the studied cancers, 111 569 (12·5%) did not meet the inclusion criteria, and 781 892 were included in the analysis. There was large interjurisdictional variation in chemotherapy use for all studied cancers, with wide 95% PIs: 47·5 to 81·2 (pooled estimate 66·4%) for ovarian cancer, 34·9 to 59·8 (47·2%) for oesophageal cancer, 22·3 to 62·3 (40·8%) for rectal cancer, 25·7 to 55·5 (39·6%) for stomach cancer, 17·2 to 56·3 (34·1%) for pancreatic cancer, 17·9 to 49·0 (31·4%) for lung cancer, 18·6 to 43·8 (29·7%) for colon cancer, and 3·5 to 50·7 (16·1%) for liver cancer. For patients with stage 3 colon cancer, the interjurisdictional variation was greater than that for all patients with colon cancer (95% PI 38·5 to 78·4; 60·1%). Patients aged 85–99 years had 20-times lower odds of chemotherapy use than those aged 65–74 years, with very large interjurisdictional variation in this age difference (odds ratio 0·05; 95% PI 0·01 to 0·19). There was large variation in median time to first chemotherapy (from diagnosis date) by cancer site, with substantial interjurisdictional variation, particularly for rectal cancer (95% PI –15·5 to 193·9 days; pooled estimate 89·2 days). Patients aged 85–99 years had slightly shorter median time to first chemotherapy compared with those aged 65–74 years, consistently between jurisdictions (–3·7 days, 95% PI –7·6 to 0·1). Large variation in use and time to chemotherapy initiation were observed between the participating jurisdictions, alongside large and variable age group differences in chemotherapy use. To guide efforts to improve patient outcomes, the underlying reasons for these patterns need to be established. International Cancer Benchmarking Partnership (funded by the Canadian Partnership Against Cancer, Cancer Council Victoria, Cancer Institute New South Wales, Cancer Research UK, Danish Cancer Society, National Cancer Registry Ireland, The Cancer Society of New Zealand, National Health Service England, Norwegian Cancer Society, Public Health Agency Northern Ireland on behalf of the Northern Ireland Cancer Registry, DG Health and Social Care Scottish Government, Western Australia Department of Health, and Public Health Wales NHS Trust).

PurposeTo prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19.MethodsProspective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups.Results76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, –0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions.ConclusionBoth 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making.Trial registration number ISRCTN66726260.