150259 research outputs found
Sort by
The impact of smoking cessation on multiple sclerosis disease progression.
No full textThe negative impact of smoking in multiple sclerosis is well established; however, there is much less evidence as to whether smoking cessation is beneficial to progression in multiple sclerosis. Adults with multiple sclerosis registered on the United Kingdom Multiple Sclerosis Register (2011-20) formed this retrospective and prospective cohort study. Primary outcomes were changes in three patient-reported outcomes: normalized Multiple Sclerosis Physical Impact Scale (MSIS-29-Phys), normalized Multiple Sclerosis Walking Scale (MSWS-12) and the Hospital Anxiety and Depression Scale (HADS). Time to event outcomes were clinically significant increases in the patient-reported outcomes. The study included 7983 participants; 4130 (51.7%) of these had ever smoked, of whom 1315 (16.5%) were current smokers and 2815/4130 (68.2%) were former smokers. For all patient-reported outcomes, current smokers at the time of completing their first questionnaire had higher patient-reported outcomes scores indicating higher disability compared to those who had never smoked (∼10 points difference in MSIS-29-Phys and MSWS-12; 1.5-1.8 points for HADS-Anxiety and HADS-Depression). There was no improvement in patient-reported outcomes scores with increasing time since quitting in former smokers. Nine hundred and twenty-three participants formed the prospective parallel group, which demonstrated that MSIS-29-Phys [median (IQR) 5.03 (3.71, 6.34)], MSWS-12 [median (IQR) 5.28 (3.62, 6.94)] and HADS-Depression [median (IQR) 0.71 (0.47, 0.96)] scores worsened over a period of 4 years, whereas HADS-Anxiety remained stable. Smoking status was significant at Year 4; current smokers had higher MSIS-29-Phys and HADS-Anxiety scores [median (IQR) 3.05 (0.22, 5.88) and 1.14 (0.52, 1.76), respectively] while former smokers had a lower MSIS-29-Phys score of -2.91 (-5.03, -0.79). A total of 4642 participants comprised the time to event analysis. Still smoking was associated with a shorter time to worsening event in all patient-reported outcomes (MSIS-29-Phys: n = 4436, P = 0.0013; MSWS-12: n = 3902, P = 0.0061; HADS-Anxiety: n = 4511, P = 0.0017; HADS-Depression: n = 4511, P < 0.0001). Worsening in motor disability (MSIS-29-Phys and MSWS-12) was independent of baseline HADS-Anxiety and HADS-Depression scores. There was no statistically significant difference in the rate of worsening between never and former smokers. When smokers quit, there is a slowing in the rate of motor disability deterioration so that it matches the rate of motor decline in those who have never smoked. This suggests that smoking cessation is beneficial for people with multiple sclerosis
The inverse association between circulatory placental biomarkers in early pregnancy and maternal body mass index.
No full textUNLABELLED: High maternal body-mass-index (BMI) is linked to adverse pregnancy outcomes, partly through impaired placental development. An inverse association between BMI and placental biomarkers has been described, however it is unclear whether this relationship is restricted to obesity or occurs across the full-BMI range. We assessed the relationship between maternal BMI and placental biomarkers across multiple cohorts. METHODS: We analysed three UK cohorts: ALSPAC (n = 994), CBGS (n = 1202) and POPS (n = 3869). Concentrations of growth-differentiation-factor15 (GDF15), beta-human chorionic gonadotropin (βhCG), pregnancy-associated plasma protein-A (PAPP-A), and alpha-fetoprotein (AFP) were measured at 8-16 weeks of gestation in maternal serum and expressed as gestational age-adjusted z-scores. Cohort-specific regression and individual-participant-data-meta-analyses (IPD-MA) were used. RESULTS: Across cohorts, each 1SD increase in maternal BMI was associated with significant reduction in: GDF15 (β: -0.16, 95%CI: -0.23 to -0.10; p<0.001), βhCG (β: -0.26, 95%CI: -0.28 to -0.23; p<0.001), PAPP-A (β: -0.38 95%CI: -0.41 to -0.36; p<0.001), and AFP (β: -0.21, 95%CI: -0.24 to -0.18; p<0.001). Associations were linear across the full BMI range, not driven solely by obesity. Biomarker levels correlated more strongly with early-pregnancy BMI than with estimated blood volume and associated directionally with the maternal polygenic-risk-scores (PRS) for BMI. CONCLUSIONS: Maternal BMI across its full range was inversely associated with biomarkers arising from, or transferred through, the placenta. We propose that the maternal caloric environment may regulate the development of the materno-fetal interface and its capacity for nutrient transfer, supporting similar rates of early fetal-growth in the face of substantial inter-individual variation in maternal body mass
PymiRa: A rapid and accurate classification tool for small non-coding RNAs, including microRNAs
No full textSmall non-coding RNAs (sncRNA; <200 nucleotide length) are of increasing research interest due to their key regulatory roles in a host of fundamental biological processes. For example, microRNAs (miRNAs), a specific class of sncRNAs, regulate gene expression through messenger RNA (mRNA) interactions, and their dysregulation is associated with disease. Classifying sncRNAs is an important bioinformatic task in small RNA-sequencing pipelines. Here we have developed an aligner called PymiRa, written in Python, to identify and quantify miRNAs from FASTA/FASTQ sequencing files. Unlike other approaches, PymiRa utilises a Burrows-Wheeler algorithm to align an input file against a reference hairpin precursor FASTA file derived from miRBase, the online miRNA registry, permitting up to two mismatches at the 3’ end of a read. Previous tools used either a Burrows-Wheeler genome alignment or dynamic programming alignment to precursors; we demonstrate that combining both approaches yields improved results and efficiency. Importantly, the PymiRa aligner accounts for 3’ post-transcriptional modifications to miRNAs that typically occur. PymiRa is a fast, accurate, and publically accessible aligner available via GitHub and/or a webserver for sncRNA identification, including miRNAs, enabling accurate counts to be produced as part of a small RNA-sequencing pipeline. PymiRa will undergo relevant revisions over time e.g., with miRBase version updates. The PymiRa aligner will facilitate a deeper biological understanding of the landscape of sncRNA expression in normal physiological conditions and their dysregulation in disease states, including cancer
Epstein-Barr virus transformed B cells from systemic lupus erythematosus and multiple sclerosis patients differ in EBV lytic and latency marker expression
No full textEpstein-Barr virus (EBV) is an important environmental risk factor in the development of several autoimmune conditions, with the mechanisms still to be fully elucidated. EBV primarily infects memory B cells, transitioning between lytic (active) and latent (dormant) phases of infection. Our group has previously proposed two molecular mechanisms linking EBV pathogenesis to autoimmunity: one indicates that EBV lytic switching contributes to systemic lupus erythematosus (SLE) pathogenesis, while another posits that latency III is more crucial in the development of multiple sclerosis (MS). In this study, we tested the proposed molecular model using a cohort of EBV-transformed lymphoblastoid cell lines (LCLs) derived from individuals with either SLE, MS or healthy controls. Measuring the expression levels of a panel of EBV genes, representing the different phases of the EBV lifecycle, we found compelling proof-of-concept evidence validating our proposed model. This discovery highlights promising signatures for further investigation, where the same approach can be explored across other EBV-associated immune conditions, deepening our understanding of the virus's lifecycle dysregulation in autoimmunity etiology and ultimately aiding in the design of new treatments
Prediction of Relapse and Glucocorticoid Dependence in Eosinophilic Granulomatosis with Polyangiitis: Findings from a Large European Cohort.
No full textBACKGROUND: Eosinophilic granulomatosis with polyangiitis (EGPA) is a small vessel vasculitis characterized by eosinophilia, asthma, and ear, nose, throat (ENT) involvement. Although glucocorticoids (GCs) are effective in controlling symptoms, relapses and GC dependence are common. The aim of this study was to develop predictive models for vasculitis relapse and GC-dependent asthma and/or ENT symptoms. METHODS: This multicenter European retrospective cohort study included EGPA patients fulfilling the 2022 ACR/EULAR criteria. Using the PMSAMPSIZE algorithm, we developed two multivariable prediction models: one for vasculitis relapse and another for GC-dependent asthma and/or ENT symptoms at 2 years. Internal validation was performed using bootstrapping. RESULTS: A total of 809 patients were followed for a median of 72 months (interquartile range, IQR 37-115). Vasculitis relapse occurred in 228 patients with a 12-year cumulative incidence of 41.2% (95% CI 36.3-46.8). GC-dependent asthma and/or ENT symptoms were observed in 66.4% at 2 years. Predictors of vasculitis relapse included age (nonlinear), GC-dependent asthma before EGPA diagnosis (hazard ratio, HR 1.57), arthralgia (HR 1.27), myocarditis (HR 1.74), peripheral neuropathy (HR 1.39), MPO-ANCA (HR 1.56), and baseline eosinophil count (nonlinear). Predictors of GC-dependent asthma and/or ENT symptoms included older age (odds ratio, OR 0.98 per year), GC-dependent asthma at diagnosis (OR 1.50), chronic sinusitis (OR 1.78), and baseline eosinophil count (OR 0.70 per 109/L). CONCLUSION: Using a large EGPA cohort, we developed predictive models for vasculitis relapse and GC-dependent asthma and/or ENT symptoms. These tools may help guide treatment decisions. Prospective external validation in the current therapeutic era is warranted
Multi-omic based production strain improvement (MOBpsi) for bio-manufacturing of toxic chemicals.
No full textRobust systematic approaches for the metabolic engineering of cell factories remain elusive. The available models for predicting phenotypical responses and mechanisms are incomplete, particularly within the context of compound toxicity that can be a significant impediment to achieving high yields of a target product. This study describes a Multi-Omic Based Production Strain Improvement (MOBpsi) strategy that is distinguished by integrated time-resolved systems analyses of fed-batch fermentations. As a case study, MOBpsi was applied to improve the performance of an Escherichia coli cell factory producing the commodity chemical styrene. Styrene can be bio-manufactured from phenylalanine via an engineered pathway comprised of the enzymes phenylalanine ammonia lyase and ferulic acid decarboxylase. The toxicity, hydrophobicity, and volatility of styrene combine to make bio-production challenging. Previous attempts to create styrene tolerant E. coli strains by targeted genetic interventions have met with modest success. Application of MOBpsi identified new potential targets for improving performance, resulting in two host strains (E. coli NST74ΔaaeA and NST74ΔaaeA cpxPo) with increased styrene production. The best performing re-engineered chassis, NST74ΔaaeA cpxPo, produced ∼3 × more styrene and exhibited increased viability in fed-batch fermentations. Thus, this case study demonstrates the utility of MOBpsi as a systematic tool for improving the bio-manufacturing of toxic chemicals
Formulating likelihood functions for infectious disease dynamics for neglected tropical diseases
No full textReliable inference in infectious disease modelling requires careful treatment of both model structure and the relationship between latent infection dynamics and observed data. Likelihood functions, which link model parameters to empirical observations, can be formulated either to explicitly represent underlying disease transmission and reporting processes (process-based) or to summarize statistical patterns in aggregated outcomes (observation-based). Stochastic models capture inherent variability in transmission and detection, whereas deterministic models describe average system behaviour and often rely on statistical assumptions to account for residual uncertainty. Using two neglected tropical disease models, we compare parameter estimation based on complete individual-level events with inference using aggregated counts. By generating synthetic outbreak data from stochastic simulations and analyzing it under alternative modelling frameworks, we show how different combinations of model formulation and likelihood structure influence both point estimates and uncertainty quantification. Our findings indicate that, even when detailed process information is unavailable, observation-based likelihoods can produce robust parameter estimates and credible uncertainty intervals, highlighting their usefulness for practical decision-making in contexts with limited or aggregated surveillance data
Geochemical Analysis of Diachronous V‐Shaped Ridges and Troughs That Flank the Reykjanes Ridge South of Iceland
No full textAbstract
It is recognized that mantle plumes play a direct role in generating regional uplift and producing immense volumes of basaltic magmatism, both of which can influence paleoclimate. The Icelandic Plume, beneath the North Atlantic Ocean, is of particular importance due to its size and position at a significant paleoceanographic gateway. It is transected by a mid‐oceanic ridge system, which has generated a series of V‐shaped ridges and troughs that flank the Reykjanes Ridge south of Iceland. The origin of these diachronous features is debated—do they reflect thermal fluctuations within the plume head or have they formed as a result of compositional variations within the buoyant convecting mantle? To address these and other hypotheses, the International Ocean Discovery Program (IODP) carried out three drilling expeditions, which recovered basalt cores from a sequence of V‐shaped ridges and troughs. Here, we show that the petrology and geochemistry of fifty whole‐rock samples taken from boreholes that penetrate different ridges and troughs reveal systematic differences in major, trace and rare earth element concentrations. By combining forward and inverse modeling based upon polybaric fractional melting, we show that these geochemical variations can be explained by varying melt fraction as a function of depth for plausible mantle source compositions. Our results suggest that temperature differences of 25–30C between cooler troughs and hotter ridges play a dominant role. We conclude that the drilled basaltic rocks reveal a chronology of resolvable temperature perturbations that should help to elucidate the fluid dynamics of flow within this major plume.</jats:p
Comparing Morphosyntactic and Semantic-Pragmatic Competence in Polish-English Bilinguals: Toward a Language-Neutral Assessment
No full textEvidence that certain semantic and pragmatic skills follow a similar developmental trajectory cross-linguistically suggests an important role for semantic-pragmatic tasks in the assessment of bilingual children. This study investigates whether quantifiers constitute a language-neutral linguistic category in this context. Forty-three Polish–English bilingual children aged 4–7 years completed the Quantifier Comprehension Task
(QCT) and the Test for Reception of Grammar (TROG-2), a standardized morphosyntactic assessment, in both languages. The results indicated that children’s
performance on QCT is strongly correlated between their two languages. This correlation
was significantly stronger than that observed for the TROG-2, indicating that quantifier
comprehension may be less language-dependent than general grammar comprehension
measures. These findings highlight the diagnostic value of semantic-pragmatic tasks,
particularly quantifier interpretation, in evaluating bilingual language development.
While the children in this study are all typically developing bilinguals, our goal is to
explore whether quantifier comprehension tasks can support the development of
language-neutral tools for assessing bilingual language skill
