The GATA1s isoform is normally down-regulated during terminal haematopoietic differentiation and over-expression leads to failure to repress MYB, CCND2 and SKI during erythroid differentiation of K562 cells

Background: Although GATA1 is one of the most extensively studied haematopoietic transcription factors little is currently known about the physiological functions of its naturally occurring isoforms GATA1s and GATA1FL in humans—particularly whether the isoforms have distinct roles in different lineages and whether they have non-redundant roles in haematopoietic differentiation. As well as being of general interest to understanding of haematopoiesis, GATA1 isoform biology is important for children with Down syndrome associated acute megakaryoblastic leukaemia (DS-AMKL) where GATA1FL mutations are an essential driver for disease pathogenesis. <p/>Methods: Human primary cells and cell lines were analyzed using GATA1 isoform specific PCR. K562 cells expressing GATA1s or GATA1FL transgenes were used to model the effects of the two isoforms on in vitro haematopoietic differentiation. <p/>Results: We found no evidence for lineage specific use of GATA1 isoforms; however GATA1s transcripts, but not GATA1FL transcripts, are down-regulated during in vitro induction of terminal megakaryocytic and erythroid differentiation in the cell line K562. In addition, transgenic K562-GATA1s and K562-GATA1FL cells have distinct gene expression profiles both in steady state and during terminal erythroid differentiation, with GATA1s expression characterised by lack of repression of MYB, CCND2 and SKI. <p/>Conclusions: These findings support the theory that the GATA1s isoform plays a role in the maintenance of proliferative multipotent megakaryocyte-erythroid precursor cells and must be down-regulated prior to terminal differentiation. In addition our data suggest that SKI may be a potential therapeutic target for the treatment of children with DS-AMKL

Seasonal change in the daily timing of behaviour of the common vole, Microtus arvalis

1. Seasonal effects on daily activity patterns in the common vole were established by periodic trapping in the field and continuous year round recording of running wheel and freeding activity in cages exposed to natural meteorological conditions. 2. Trapping revealed decreased nocturnality in winter as compared to summer. This was paralelled by a winter reduction in both nocturnal wheel running and feeding time in cages. 3. Frequent trap checks revealed a 2 h rhythm in daytime catches in winter, not in summer. Cage feeding activity in daytime was always organized in c. 2 h intervals, but day-to-day variations in phase blurred the rhythm in summer in a summation of individual daily records. Thus both seasonal and short-term temporal patterns are consistent between field trappings and cage feeding records. 4. Variables associated with the seasonal change in daily pattern were: reproductive state (sexually active voles more nocturnal), age (juveniles more nocturnal), temperature (cold days: less nocturnal), food (indicated by feeding experiments), habitat structure (more nocturnal in habitat with underground tunnels). 5. Minor discrepancies between field trappings and cage feeding activity can be explained by assuming increased trappability of voles in winter. Cage wheel running is not predictive of field trapping patterns and is thought to reflect behavioral motivations not associated with feeding but with other activities (e.g., exploratory, escape, interactive behaviour) undetected by current methods, including radiotelemetry and passage-counting. 6. Winter decrease in nocturnality appears to involve a reduction in nocturnal non-feeding and feeding behaviour and is interpreted primarily as an adaptation to reduce energy expenditure in adverse but socially stable winter conditions.

Defining the phenotypes of sickle cell disease.

The sickle cell gene is pleiotropic in nature. Although it is a single gene mutation, it has multiple phenotypic expressions that constitute the complications of sickle cell disease. The frequency and severity of these complications vary considerably both latitudinally in patients and longitudinally in the same patient over time. Thus, complications that occur in childhood may disappear, persist or get worse with age. Dactylitis and stroke, for example, occur mostly in childhood, whereas leg ulcers and renal failure typically occur in adults. It is essential that the phenotypic manifestations of sickle cell disease be defined accurately so that communication among providers and researchers facilitates the implementation of appropriate and cost-effective diagnostic and therapeutic modalities. The aim of this review is to define the complications that are specific to sickle cell disease based on available evidence in the literature and the experience of hematologists in this field

Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

Applying an extended theory of planned behaviour to predict breakfast consumption in adolescents

BACKGROUND/OBJECTIVES: Breakfast skipping increases during adolescence and is associated with lower levels of physical activity and weight gain. Theory-based interventions promoting breakfast consumption in adolescents report mixed findings, potentially because of limited research identifying which determinants to target. This study aimed to: (i) utilise the Theory of Planned Behaviour (TPB) to identify the relative contribution of attitudes (affective, cognitive and behavioural) to predict intention to eat breakfast and breakfast consumption in adolescents and (ii) determine whether demographic factors moderate the relationship between TPB variables, intention and behaviour. SUBJECTS/METHODS: Questionnaires were completed by 434 students (mean 14+/-0.9 years) measuring breakfast consumption (0-2, 3-6 or 7 days), physical activity levels and TPB measures. Data were analysed by breakfast frequency and demographics using hierarchical and multinomial regression analyses. RESULTS: Breakfast was consumed everyday by 57% of students, with boys more likely to eat a regular breakfast, report higher activity levels and report more positive attitudes towards breakfast than girls (P<0.001). The TPB predicted 58% of the variation in intentions. Overall, the model was predictive of breakfast behaviours (P<0.001), but the relative contribution of TPB constructs varied depending on breakfast frequency. Interactions between gender and intentions were significant when comparing 0-2- and 3-6-day breakfast eaters only highlighting a stronger intention-behaviour relationship for girls. CONCLUSIONS: Findings confirm that the TPB is a successful model for predicting breakfast intentions and behaviours in adolescents. The potential for a direct effect of attitudes on behaviours should be considered in the implementation and design of breakfast interventions

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Early Detection of Alzheimer\u27s Disease with Blood Plasma Proteins Using Support Vector Machines

\ua9 2013 IEEE. The successful development of amyloid-based biomarkers and tests for Alzheimer\u27s disease (AD) represents an important milestone in AD diagnosis. However, two major limitations remain. Amyloid-based diagnostic biomarkers and tests provide limited information about the disease process and they are unable to identify individuals with the disease before significant amyloid-beta accumulation in the brain develops. The objective in this study is to develop a method to identify potential blood-based non-amyloid biomarkers for early AD detection. The use of blood is attractive because it is accessible and relatively inexpensive. Our method is mainly based on machine learning (ML) techniques (support vector machines in particular) because of their ability to create multivariable models by learning patterns from complex data. Using novel feature selection and evaluation modalities, we identified 5 novel panels of non-amyloid proteins with the potential to serve as biomarkers of early AD. In particular, we found that the combination of A2M, ApoE, BNP, Eot3, RAGE and SGOT may be a key biomarker profile of early disease. Disease detection models based on the identified panels achieved sensitivity (SN) &gt; 80%, specificity (SP) &gt; 70%, and area under receiver operating curve (AUC) of at least 0.80 at prodromal stage (with higher performance at later stages) of the disease. Existing ML models performed poorly in comparison at this stage of the disease, suggesting that the underlying protein panels may not be suitable for early disease detection. Our results demonstrate the feasibility of early detection of AD using non-amyloid based biomarkers

Pharmacogenomics in diabetes mellitus:insights into drug action and drug discovery

Genomic studies have greatly advanced our understanding of the multifactorial aetiology of type 2 diabetes mellitus (T2DM) as well as the multiple subtypes of monogenic diabetes mellitus. In this Review, we discuss the existing pharmacogenetic evidence in both monogenic diabetes mellitus and T2DM. We highlight mechanistic insights from the study of adverse effects and the efficacy of antidiabetic drugs. The identification of extreme sulfonylurea sensitivity in patients with diabetes mellitus owing to heterozygous mutations in HNF1A represents a clear example of how pharmacogenetics can direct patient care. However, pharmacogenomic studies of response to antidiabetic drugs in T2DM has yet to be translated into clinical practice, although some moderate genetic effects have now been described that merit follow-up in trials in which patients are selected according to genotype. We also discuss how future pharmacogenomic findings could provide insights into treatment response in diabetes mellitus that, in addition to other areas of human genetics, facilitates drug discovery and drug development for T2DM.</p

A change in the optical polarization associated with a gamma-ray flare in the blazar 3C 279

It is widely accepted that strong and variable radiation detected over all accessible energy bands in a number of active galaxies arises from a relativistic, Doppler-boosted jet pointing close to our line of sight. The size of the emitting zone and the location of this region relative to the central supermassive black hole are, however, poorly known, with estimates ranging from light-hours to a light-year or more. Here we report the coincidence of a gamma-ray flare with a dramatic change of optical polarization angle. This provides evidence for co-spatiality of optical and gamma-ray emission regions and indicates a highly ordered jet magnetic field. The results also require a non-axisymmetric structure of the emission zone, implying a curved trajectory for the emitting material within the jet, with the dissipation region located at a considerable distance from the black hole, at about 10^5 gravitational radii.Comment: Published in Nature issued on 18 February 2010. Corresponding authors: Masaaki Hayashida and Greg Madejsk