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Cysteine is the most intrinsically nucleophilic amino acid in proteins, where its reactivity is tuned to perform diverse biochemical functions. The absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here we describe a proteomics method to profile quantitatively the intrinsic reactivity of cysteine residues en masse directly in native biological systems. Hyper-reactivity was a rare feature among cysteines and it was found to specify a wide range of activities, including nucleophilic and reductive catalysis and sites of oxidative modification. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotic phylogeny that we show is required for yeast viability and is involved in iron-sulphur protein biogenesis. We also demonstrate that quantitative reactivity profiling can form the basis for screening and functional assignment of cysteines in computationally designed proteins, where it discriminated catalytically active from inactive cysteine hydrolase designs. The cysteines that really count Cysteine residues are often active in the catalytic or regulatory sites of proteins because of the extremely nucleophilic nature of their thiol side chains. Side-chain reactivity varies widely depending on the local protein micro-environment, but a new technique termed 'quantitative reactivity profiling', combining activity-based small-molecule probes with mass spectrometry, makes it possible to measure the intrinsic reactivity of cysteine residues. Hyper-reactive cysteines were identified in several proteins of unknown function, including a residue conserved across eukaryotes that is required for yeast viability and is involved in iron-sulphur protein biogenesis. Cysteine is the most intrinsically nucleophilic amino acid in proteins, but the absence of a consensus sequence that defines functional cysteines in proteins has hindered their discovery and characterization. Here, a proteomics method to quantitatively profile the intrinsic reactivity of cysteine residues directly in native biological systems is described. Hyper-reactive cysteines were identified in several proteins of uncharacterized function, including a residue conserved across eukaryotes that is shown to be required for yeast viability and involved in iron–sulphur protein biogenesis.

A bstract We describe a technique to learn the underlying structure of collider events directly from the data, without having a particular theoretical model in mind. It allows to infer aspects of the theoretical model that may have given rise to this structure, and can be used to cluster or classify the events for analysis purposes. The unsupervised machine-learning technique is based on the probabilistic (Bayesian) generative model of Latent Dirichlet Allocation. We pair the model with an approximate inference algorithm called Variational Inference, which we then use to extract the latent probability distributions describing the learned underlying structure of collider events. We provide a detailed systematic study of the technique using two example scenarios to learn the latent structure of di-jet event samples made up of QCD background events and either t t ¯ or hypothetical W ′ → ( ϕ → WW ) W signal events.

Background: The problems of adherence to energy restriction in humans are well known. Objective: To compare the feasibility and effectiveness of intermittent continuous energy (IER) with continuous energy restriction (CER) for weight loss, insulin sensitivity and other metabolic disease risk markers. Design: Randomized comparison of a 25% energy restriction as IER (approximately 2710 kJ/day for 2 days/week) or CER (approximately 6276 kJ/day for 7 days/week) in 107 overweight or obese (mean (+/-s.d.) body mass index 30.6 (+/-5.1) kg m-2) premenopausal women observed over a period of 6 months. Weight, anthropometry, biomarkers for breast cancer, diabetes, cardiovascular disease and dementia risk; insulin resistance (HOMA), oxidative stress markers, leptin, adiponectin, insulin-like growth factor (IGF)-1 and IGF binding proteins 1 and 2, androgens, prolactin, inflammatory markers (high sensitivity C-reactive protein and sialic acid), lipids, blood pressure and brain-derived neurotrophic factor were assessed at baseline and after 1, 3 and 6 months. Results: Last observation carried forward analysis showed that IER and CER are equally effective for weight loss: mean (95% confidence interval ) weight change for IER was -6.4 (-7.9 to -4.8) kg vs -5.6 (-6.9 to -4.4) kg for CER (P-value for difference between groups=0.4). Both groups experienced comparable reductions in leptin, free androgen index, high-sensitivity C-reactive protein, total and LDL cholesterol, triglycerides, blood pressure and increases in sex hormone binding globulin, IGF binding proteins 1 and 2. Reductions in fasting insulin and insulin resistance were modest in both groups, but greater with IER than with CER; difference between groups for fasting insulin was -1.2 (-1.4 to -1.0) micromoll-1 and for insulin resistance was -1.2 (-1.5 to -1.0) micromol-1 l-1 (both P=0.04). Conclusion: IER is as effective as CER with regard to weight loss, insulin sensitivity and other health biomarkers, and may be offered as an alternative equivalent to CER for weight loss and reducing disease risk.

Objective methods like accelerometers are feasible for large studies and may quantify variability in day-to-day physical activity better than self-report. The variability between days suggests that day of the week cannot be ignored in the design and analysis of physical activity studies. The purpose of this paper is to investigate the optimal number of days needed to obtain reliable estimates of weekly habitual physical activity using the wrist-worn GENEActiv accelerometer. Data are from a subsample of the Mitchelstown cohort; 475 (44.6% males; mean aged 59.6±5.5 years) middle-aged Irish adults. Participants wore the wrist GENEActiv accelerometer for 7-consecutive days. Data were collected at 100Hz and summarised into a signal magnitude vector using 60s epochs. Each time interval was categorised according to intensity based on validated cut-offs. Spearman pairwise correlations determined the association between days of the week. Repeated measures ANOVA examined differences in average minutes across days. Intraclass correlations examined the proportion of variability between days, and Spearman-Brown formula estimated intra-class reliability coefficient associated with combinations of 1-7 days. Three hundred and ninety-seven adults (59.7±5.5yrs) had valid accelerometer data. Overall, men were most sedentary on weekends while women spent more time in sedentary behaviour on Sunday through Tuesday. Post hoc analysis found sedentary behaviour and light activity levels on Sunday to differ to all other days in the week. Analysis revealed greater than 1 day monitoring is necessary to achieve acceptable reliability. Monitoring frame duration for reliable estimates varied across intensity categories, (sedentary (3 days), light (2 days), moderate (2 days) and vigorous activity (6 days) and MVPA (2 days)). These findings provide knowledge into the behavioural variability in weekly activity patterns of middle-aged adults. Since Sunday differed from all other days in the week this suggests that day of the week cannot be overlooked in the design and analysis of physical activity studies and thus should be included in the study monitoring frames. Collectively our data suggest that six days monitoring, inclusive of Saturday and Sunday, are needed to reliably capture weekly habitual activity in all activity intensities using the wrist-worn GENEActiv accelerometer.

Recent advances in next generation sequencing technologies enable reading DNA molecules hundreds of kilobases in length and motivate development of DNA amplification methods capable of producing long amplicons. In vivo, DNA replication is performed not by a single polymerase enzyme, but multiprotein complexes called replisomes. Here, we investigate strand-displacement amplification reactions using the T7 replisome, a macromolecular complex of a helicase, a single-stranded DNA binding protein, and a DNA polymerase. The T7 replisome may initiate processive DNA synthesis from DNA nicks, and the reaction of a 48 kilobase linear double stranded DNA substrate with the T7 replisome and nicking endonucleases is shown to produce discrete DNA amplicons. To gain a mechanistic understanding of this reaction, we utilized Oxford Nanopore long-read sequencing technology. Sequence analysis of the amplicons revealed chimeric DNA reads and uncovered a connection between template switching and polymerase exonuclease activity. Nanopore sequencing provides insight to guide the further development of isothermal amplification methods for long DNA, and our results highlight the need for high-specificity, high-turnover nicking endonucleases to initiate DNA amplification without thermal denaturation.

A bstract The decay of a massive pseudoscalar, scalar and U(1) boson into an electron-positron pair in the presence of strong electromagnetic backgrounds is calculated. Of particular interest is the constant-crossed-field limit, relevant for experiments that aim to measure high-energy axion-like-particle conversion into electron-positron pairs in a magnetic field. The total probability depends on the quantum nonlinearity parameter — a product of field and lightfront momentum invariants. Depending on the seed particle mass, different decay regimes are identified. In the below-threshold case, we find the probability depends on a non-perturbative tunneling exponent depending on the quantum parameter and the particle mass. In the above-threshold case, we find that when the quantum parameter is varied linearly, the probability oscillates nonlinearly around the spontaneous decay probability. A strong-field limit is identified in which the threshold is found to disappear. In modelling the fall-off of a quasi-constant-crossed magnetic field, we calculate probabilities beyond the constant limit and investigate when the decay probability can be regarded as locally constant.

Background Sedentary behaviour, obesity and insulin resistance are associated with pro-inflammatory status. Limited data on whether physical activity modulates inflammatory status and counteracts obesity and insulin resistance associated low-grade inflammation exist. Our objective was to investigate associations between objectively measured physical activity and inflammatory status, and specifically whether substituting daily sedentary behaviour with light activity or moderate to vigorous physical activity (MVPA), is associated with beneficial alterations to the inflammatory profile among middle-aged adults and those at increased cardiometabolic risk (obese and insulin resistant subjects). Methods Data are from a sub-sample of the Mitchelstown cohort; a population-based cross-sectional sample of 2047 Irish adults. Physical activity intensity and duration were measured in 396 participants for 7-consecutive days using the GENEActiv accelerometer. Isotemporal regression analysis examined the associations between replacing 30 min per day of sedentary behaviour with equal amounts of light activity and MVPA on inflammatory factors (serum acute-phase reactants, adipocytokines, pro-inflammatory cytokines and white blood cells (WBC)). Results Reallocating 30 min of sedentary time with MVPA was associated with a more favourable inflammatory profile characterized by higher adiponectin and lower complement component C3 (C3), leptin, interleukin 6 (IL-6) and WBC concentrations ( P  < 0.05). No significant effects were noted with substitution of sedentary time with light activity. Among the obese subjects replacing sedentary behaviour with an equivalent amount of MVPA was associated with lower WBC counts ( P  < 0.05); no associations were detected among the insulin resistant (HOMA-IR >75th percentile) subjects. Among the non-obese and non-insulin resistant subjects substituting 30 min of sedentary behaviour with MVPA was associated with decreased C3, IL-6 and WBC concentrations. Conclusions Replacing sedentary behaviour with MVPA modulates pro-inflammatory status. These findings, which highlight the need for the developing randomized trials aimed at lowering cardiometabolic risk, warrant further investigation.

The purpose of the current study was to examine the internal consistency and structure of the English version of the Statistical Anxiety Rating Scale (STARS). Participants were 202 (79% females) psychology undergraduates was recruited from James Cook University's Singapore (71%) and Australia (29%) campuses. Acceptable internal consistency reliabilities, ranging from .81 to .94, were found in this sample. Approximate fit indices suggest that a correlated six first-order factor model best describes the data in contrast to theoretical considerations suggesting that a six factor model with two correlated superordinate factors (i.e., statistics anxiety and attitudes toward statistics) best describes the data. Researchers are recommended to use part one of the STARS to assess statistics anxiety and part two to assess attitudes toward statistics.

To explore how airborne microbial patterns change with height above the Earth’s surface, we flew NASA’s C-20A aircraft on two consecutive days in June 2018 along identical flight paths over the US Sierra Nevada mountain range at four different altitudes ranging from 10,000 ft to 40,000 ft. Bioaerosols were analyzed by metagenomic DNA sequencing and traditional culturing methods to characterize the composition and diversity of atmospheric samples compared to experimental controls. The relative abundance of taxa changed significantly at each altitude sampled, and the diversity profile shifted across the two sampling days, revealing a regional atmospheric microbiome that is dynamically changing. The most proportionally abundant microbial genera were Mycobacterium and Achromobacter at 10,000 ft; Stenotrophomonas and Achromobacter at 20,000 ft; Delftia and Pseudoperonospora at 30,000 ft; and Alcaligenes and Penicillium at 40,000 ft. Culture-based detections also identified viable Bacillus zhangzhouensis , Bacillus pumilus , and Bacillus spp. in the upper troposphere. To estimate bioaerosol dispersal, we developed a human exposure likelihood model (7-day forecast) using general aerosol characteristics and measured meteorological conditions. By coupling metagenomics to a predictive atmospheric model, we aim to set the stage for field campaigns that monitor global bioaerosol emissions and impacts.