'What is this corpus about?': Using topic modelling to explore a specialised corpus

This paper introduces topic modelling, a machine learning technique that automatically identifies 'topics' in a given corpus. The paper illustrates its use in the exploration of a corpus of academic English. It first offers the intuitive explanation of the underlying mechanism of topic modelling and describes the procedure for building a model, including the decisions involved in the model-building process. The paper then explores the model. A topic in topic models is characterised by a set of co-occurring words, and we will demonstrate that such topics bring us rich insights into the nature of a corpus. As exemplary tasks, this paper identifies the prominent topics in different parts of papers, investigates the chronological change of a journal, and reveals different types of papers in the journal. The paper further compares topic modelling to two more traditional techniques in corpus linguistics, semantic annotation and keywords analysis, and highlights the strengths of topic modelling.We believe that topic modelling is particularly useful in the initial exploration of a corpus

Association of maternal circulating 25(OH)D and calcium with birth weight: A mendelian randomisation analysis

Systematic reviews of randomised controlled trials (RCTs) have suggested that maternal vitamin D (25[OH]D) and calcium supplementation increase birth weight. However, limitations of many trials were highlighted in the reviews. Our aim was to combine genetic and RCT data to estimate causal effects of these two maternal traits on offspring birth weight

Model Selection in Time Series Studies of Influenza-Associated Mortality

Background: Poisson regression modeling has been widely used to estimate influenza-associated disease burden, as it has the advantage of adjusting for multiple seasonal confounders. However, few studies have discussed how to judge the adequacy of confounding adjustment. This study aims to compare the performance of commonly adopted model selection criteria in terms of providing a reliable and valid estimate for the health impact of influenza. Methods: We assessed four model selection criteria: quasi Akaike information criterion (QAIC), quasi Bayesian information criterion (QBIC), partial autocorrelation functions of residuals (PACF), and generalized cross-validation (GCV), by separately applying them to select the Poisson model best fitted to the mortality datasets that were simulated under the different assumptions of seasonal confounding. The performance of these criteria was evaluated by the bias and root-mean-square error (RMSE) of estimates from the pre-determined coefficients of influenza proxy variable. These four criteria were subsequently applied to an empirical hospitalization dataset to confirm the findings of simulation study. Results: GCV consistently provided smaller biases and RMSEs for the influenza coefficient estimates than QAIC, QBIC and PACF, under the different simulation scenarios. Sensitivity analysis of different pre-determined influenza coefficients, study periods and lag weeks showed that GCV consistently outperformed the other criteria. Similar results were found in applying these selection criteria to estimate influenza-associated hospitalization. Conclusions: GCV criterion is recommended for selection of Poisson models to estimate influenza-associated mortality and morbidity burden with proper adjustment for confounding. These findings shall help standardize the Poisson modeling approach for influenza disease burden studies. © 2012 Wang et al.published_or_final_versio

Using human genetics to understand the disease impacts of testosterone in men and women.

Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22-1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33-1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76-0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses.A.R.W. and T.M.F. are supported by the European Research Council grant: SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. R.B. is funded by the Wellcome Trust and Royal Society grant 104150/Z/14/Z. J.T. is supported by the Academy of Medical Sciences Springboard award which is supported by the Wellcome Trust and GCRF [SBF004\1079]. This work was supported by the Medical Research Council [Unit Programme numbers MC_UU_12015/1 and MC_UU_12015/2]

Individual common variants exert weak effects on the risk for autism spectrum disorders.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Detecting forest response to droughts with global observations of vegetation water content

Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analog of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions-which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

An exploration of lifestyle beliefs and lifestyle behaviour following stroke: findings from a focus group study of patients and family members

<p>Abstract</p> <p>Background</p> <p>Stroke is a major cause of disability and family disruption and carries a high risk of recurrence. Lifestyle factors that increase the risk of recurrence include smoking, unhealthy diet, excessive alcohol consumption and physical inactivity. Guidelines recommend that secondary prevention interventions, which include the active provision of lifestyle information, should be initiated in hospital, and continued by community-based healthcare professionals (HCPs) following discharge. However, stroke patients report receiving little/no lifestyle information.</p> <p>There is a limited evidence-base to guide the development and delivery of effective secondary prevention lifestyle interventions in the stroke field. This study, which was underpinned by the Theory of Planned Behaviour, sought to explore the beliefs and perceptions of patients and family members regarding the provision of lifestyle information following stroke. We also explored the influence of beliefs and attitudes on behaviour. We believe that an understanding of these issues is required to inform the content and delivery of effective secondary prevention lifestyle interventions.</p> <p>Methods</p> <p>We used purposive sampling to recruit participants through voluntary sector organizations (29 patients, including 7 with aphasia; 20 family members). Using focus group methods, data were collected in four regions of Scotland (8 group discussions) and were analysed thematically.</p> <p>Results</p> <p>Although many participants initially reported receiving no lifestyle information, further exploration revealed that most had received written information. However, it was often provided when people were not receptive, there was no verbal reinforcement, and family members were rarely involved, even when the patient had aphasia. Participants believed that information and advice regarding healthy lifestyle behaviour was often confusing and contradictory and that this influenced their behavioural intentions. Family members and peers exerted both positive and negative influences on behavioural patterns. The influence of HCPs was rarely mentioned. Participants' sense of control over lifestyle issues was influenced by the effects of stroke (e.g. depression, reduced mobility) and access to appropriate resources.</p> <p>Conclusions</p> <p>For secondary prevention interventions to be effective, HCPs must understand psychological processes and influences, and use appropriate behaviour change theories to inform their content and delivery. Primary care professionals have a key role to play in the delivery of lifestyle interventions.</p