A randomised double-blind placebo-controlled feasibility trial of flavonoid-rich cocoa for fatigue in people with relapsing and remitting multiple sclerosis

The impact of flavonoids on fatigue has not been investigated in Relapsing and Remitting Multiple Sclerosis (RRMS). Objective: To determine the feasibility and estimate the potential effect of flavonoid-rich cocoa on fatigue and fatigability in RRMS. Methods: A randomised double-blind placebo-controlled feasibility study in people recently diagnosed with RRMS and fatigue, throughout the Thames Valley (ISRCTN: 69897291). During a six week intervention participants consumed a high or low flavonoid cocoa beverage daily. Fatigue and fatigability were measured at three visits (weeks 0, 3 and 6). Feasibility and fidelity were assessed through recruitment and retention, adherence and a process evaluation. Results: 40 pwMS (10 men, 30 women, age 44 ± 10 yrs) were randomised and allocated to high (n=19) or low (n=21) flavonoid groups and included in analysis. Missing data was 75%. There was a small effect on fatigue (Neuro-QoL: effect size {ES} 0.04; confidence interval {CI} -0.40-0.48) and a moderate effect on fatigability (six-minute walk test: ES 0.45; CI -0.18 - 1.07). There were seven adverse events (four control, three intervention), only one of which was possibly related and it was resolved. Conclusion: A flavonoid beverage demonstrates the potential to improve fatigue and fatigability in RRMS

Designing medical technology for developing countries

Resource-poor countries have markedly different healthcare systems. Many developed nations donate medical supplies to these countries, but this often does not meet the needs of the recipients. Our goal is to develop simple healthcare solutions that can be produced in-country so the developing area does not depend on outside sources for its supplies. Our group works on many projects, including sustainable woven grass neck braces and a variety of low-cost sensors. Our designs do not require frequent donations, minimize the use of consumables, and provide better detection and/or treatment of prevalent medical concerns. Our baby monitor will detect skin temperature and control a heating element based on the needs of the infant. Our low-cost glucometer operates with the use of test strips that can be printed for a penny with a standard inkjet printer. This will allow the hospital or clinic to print the strips themselves rather than depend on donated strips. Our bacterial sensor will measure resistance to quickly detect the quantity of bacteria in a sample. We seek sustainable solutions for in-house manufacturing to advance more self-sufficient healthcare systems

Tutor and teacher timescapes : lessons from a home-school partnership

A partnership project was developed in which parents volunteered to support teachersin training years 1-3 children in computer skills at a primary school in a small, lowsocio-economic community. This article identifies the ways teachers and the &lsquo;tutors&rsquo;(as the volunteers were called) understood the value of the project. &lsquo;Being a teacher&rsquo;and &lsquo;being a volunteer&rsquo; were structured by different forms of social engagement,which in turn influenced the ways individuals were able to work with each other incollaborative processes. We argue that the discursive practices encoded in homeschool-community partnership rhetoric represent ruling-class ways of organising andnetworking that may be incompatible with those of people from low socio-economicbackgrounds. When such volunteers work in schools their attendance may be sporadicand short-term whereas teachers would like &lsquo;reliable&rsquo; ongoing commitment. Thismismatch wrought of teachers&rsquo; and volunteers&rsquo; differing everyday realities needs to beunderstood before useful models for partnerships in disadvantaged communities maybe realised.<br /

Aboveground Biomass Accumulation in a Tropical Wet Forest in Nicaragua Following a Catastrophic Hurricane Disturbance 1

Among their effects on forest structure and carbon dynamics, hurricanes frequently create large-scale canopy gaps that promote secondary growth. To measure the accumulation of aboveground biomass (AGBM) in a hurricane damaged forest, we established permanent plots 4 mo after the landfall of Hurricane Joan on the Atlantic coast of Nicaragua in October 1988. We quantified AGBM accumulation in these plots by correlating diameter measurements to AGBM values using a published allometric regression equation for tropical wet forests. In the first measurement year following the storm, AGBM in hurricane-affected plots was quite variable, ranging from 26 to 153 Mg/ha, with a mean of 78 (±15) Mg/ha. AGBM was substantially lower than in two control plots several kilometers outside the hurricane's path (331 ±15 Mg/ha). Biomass accumulation was slow (5.36 ± 0.74 Mg/ha/yr), relative to previous studies of forest regeneration following another hurricane (Hugo) and agricultural activity. We suggest that large-scale, homogenous canopy damage caused by Hurricane Joan impeded the dispersal and establishment of pioneer trees and led to a secondary forest dominated by late successional species that resprouted and survived the disturbance. With the relatively slow rate of biomass accumulation, any tightening in disturbance interval could reduce the maximum capacity of the living biomass to store carbon.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73646/1/j.1744-7429.2005.00077.x.pd

Reconciling carbon-cycle concepts, terminology, and methods

Author Posting. © The Author(s), 2006. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Ecosystems 9 (2006): 1041-1050, doi:10.1007/s10021-005-0105-7.Recent patterns and projections of climatic change have focused increased scientific and public attention on patterns of carbon (C) cycling and its controls, particularly the factors that determine whether an ecosystem is a net source or sink of atmospheric CO2. Net ecosystem production (NEP), a central concept in C-cycling research, has been used to represent two different concepts by C-cycling scientists. We propose that NEP be restricted to just one of its two original definitions—the imbalance between gross primary production (GPP) and ecosystem respiration (ER), and that a new term—net ecosystem carbon balance (NECB)—be applied to the net rate of C accumulation in (or loss from; negative sign) ecosystems. NECB differs from NEP when C fluxes other than C fixation and respiration occur or when inorganic C enters or leaves in dissolved form. These fluxes include leaching loss or lateral transfer of C from the ecosystem; emission of volatile organic C, methane, and carbon monoxide; and soot and CO2 from fire. C fluxes in addition to NEP are particularly important determinants of NECB over long time scales. However, even over short time scales, they are important in ecosystems such as streams, estuaries, wetlands, and cities. Recent technological advances have led to a diversity of approaches to measuring C fluxes at different temporal and spatial scales. These approaches frequently capture different components of NEP or NECB and can therefore be compared across scales only by carefully specifying the fluxes included in the measurements. By explicitly identifying the fluxes that comprise NECB and other components of the C cycle, such as net ecosystem exchange (NEE) and net biome production (NBP), we provide a less ambiguous framework for understanding and communicating recent changes in the global C cycle. Key words: Net ecosystem production, net ecosystem carbon balance, gross primary production, ecosystem respiration, autotrophic respiration, heterotrophic respiration, net ecosystem exchange, net biome production, net primary production

SARS-CoV-2 spike N-terminal domain modulates TMPRSS2-dependent viral entry and fusogenicity

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike N-terminal domain (NTD) remains poorly characterized despite enrichment of mutations in this region across variants of concern (VOCs). Here, we examine the contribution of the NTD to infection and cell-cell fusion by constructing chimeric spikes bearing B.1.617 lineage (Delta and Kappa variants) NTDs and generating spike pseudotyped lentivirus. We find that the Delta NTD on a Kappa or wild-type (WT) background increases S1/S2 cleavage efficiency and virus entry, specifically in lung cells and airway organoids, through use of TMPRSS2. Delta exhibits increased cell-cell fusogenicity that could be conferred to WT and Kappa spikes by Delta NTD transfer. However, chimeras of Omicron BA.1 and BA.2 spikes with a Delta NTD do not show more efficient TMPRSS2 use or fusogenicity. We conclude that the NTD allosterically modulates S1/S2 cleavage and spike-mediated functions in a spike context-dependent manner, and allosteric interactions may be lost when combining regions from more distantly related VOCs

Longitudinal analysis reveals that delayed bystander CD8+ T cell activation and early immune pathology distinguish severe COVID-19 from mild disease

The kinetics of the immune changes in COVID-19 across severity groups have not been rigorously assessed. Using immunophenotyping, RNA sequencing, and serum cytokine analysis, we analyzed serial samples from 207 SARS-CoV2-infected individuals with a range of disease severities over 12 weeks from symptom onset. An early robust bystander CD8+ T cell immune response, without systemic inflammation, characterized asymptomatic or mild disease. Hospitalized individuals had delayed bystander responses and systemic inflammation that was already evident near symptom onset, indicating that immunopathology may be inevitable in some individuals. Viral load did not correlate with this early pathological response but did correlate with subsequent disease severity. Immune recovery is complex, with profound persistent cellular abnormalities in severe disease correlating with altered inflammatory responses, with signatures associated with increased oxidative phosphorylation replacing those driven by cytokines tumor necrosis factor (TNF) and interleukin (IL)-6. These late immunometabolic and immune defects may have clinical implications

Monitoring the EU protected Geomalacus maculosus (Kerry Slug): what are the factors affecting catch returns in open and forested habitats?

Geomalacus maculosus is a slug species protected under EU law with a distribution limited to the west of Ireland and north-west Iberia. The species, originally thought to be limited within Ireland to deciduous woodland and peatland, has been found in a number of commercial conifer plantations since 2010. While forest managers are now required to incorporate the protection of the species where it is present, no clear species monitoring protocols are currently available. This study examines the efficacy of De Sangosse refuge traps across three habitats frequently associated with commercial forest plantations in Ireland and compares them with hand searching, a commonly used method for slug monitoring. Catch data during different seasons and under different weather conditions are also presented. Results indicate that autumn is the optimal time for sampling G. maculosus but avoiding extremes of hot or cold weather. While refuge traps placed at 1.5 m on trees in mature conifer plantations and directly on exposed rock in blanket peatlands result in significantly greater catches, hand searching is the most successful approach for clear-fell areas. Hand searches in clear-fell preceded by rain are likely to result in greater numbers caught. The results of this study form, for the first time, the basis for G. maculosus monitoring guidelines for forestry managers. © 2016, The Ecological Society of Japa

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers