Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children

Diagnostic tools for paediatric tuberculosis remain limited, with heavy reliance on clinical algorithms which include chest x-ray. Computer aided detection (CAD) for tuberculosis on chest x-ray has shown promise in adults. We aimed to measure and optimise the performance of an adult CAD system, CAD4TB, to identify tuberculosis on chest x-rays from children with presumptive tuberculosis. Chest x-rays from 620 children <13 years enrolled in a prospective observational diagnostic study in South Africa, were evaluated. All chest x-rays were read by a panel of expert readers who attributed each with a radiological reference of either 'tuberculosis' or 'not tuberculosis'. Of the 525 chest x-rays included in this analysis, 80 (40 with a reference of 'tuberculosis' and 40 with 'not tuberculosis') were allocated to an independent test set. The remainder made up the training set. The performance of CAD4TB to identify 'tuberculosis' versus 'not tuberculosis' on chest x-ray against the radiological reference read was calculated. The CAD4TB software was then fine-tuned using the paediatric training set. We compared the performance of the fine-tuned model to the original model. Our findings were that the area under the receiver operating characteristic curve (AUC) of the original CAD4TB model, prior to fine-tuning, was 0.58. After fine-tuning there was an improvement in the AUC to 0.72 (p = 0.0016). In this first-ever description of the use of CAD to identify tuberculosis on chest x-ray in children, we demonstrate a significant improvement in the performance of CAD4TB after fine-tuning with a set of well-characterised paediatric chest x-rays. CAD has the potential to be a useful additional diagnostic tool for paediatric tuberculosis. We recommend replicating the methods we describe using a larger chest x-ray dataset from a more diverse population and evaluating the potential role of CAD to replace a human-read chest x-ray within treatment-decision algorithms for paediatric tuberculosis

Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material

© 2020. The American Astronomical Society. All rights reserved.. We present a survey of the early evolution of 12 Type IIn supernovae (SNe IIn) at ultraviolet and visible light wavelengths. We use this survey to constrain the geometry of the circumstellar material (CSM) surrounding SN IIn explosions, which may shed light on their progenitor diversity. In order to distinguish between aspherical and spherical CSM, we estimate the blackbody radius temporal evolution of the SNe IIn of our sample, following the method introduced by Soumagnac et al. We find that higher-luminosity objects tend to show evidence for aspherical CSM. Depending on whether this correlation is due to physical reasons or to some selection bias, we derive a lower limit between 35% and 66% for the fraction of SNe IIn showing evidence for aspherical CSM. This result suggests that asphericity of the CSM surrounding SNe IIn is common - consistent with data from resolved images of stars undergoing considerable mass loss. It should be taken into account for more realistic modeling of these events

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Genome-wide association study identifies loci associated with liability to alcohol and drug dependence that is associated with variability in reward-related ventral striatum activity in African- and European-Americans.

Genetic influences on alcohol and drug dependence partially overlap, however, specific loci underlying this overlap remain unclear. We conducted a genome-wide association study (GWAS) of a phenotype representing alcohol or illicit drug dependence (ANYDEP) among 7291 European-Americans (EA; 2927 cases) and 3132 African-Americans (AA: 1315 cases) participating in the family-based Collaborative Study on the Genetics of Alcoholism. ANYDEP was heritable (h 2 in EA = 0.60, AA = 0.37). The AA GWAS identified three regions with genome-wide significant (GWS; P &lt; 5E-08) single nucleotide polymorphisms (SNPs) on chromosomes 3 (rs34066662, rs58801820) and 13 (rs75168521, rs78886294), and an insertion-deletion on chromosome 5 (chr5:141988181). No polymorphisms reached GWS in the EA. One GWS region (chromosome 1: rs1890881) emerged from a trans-ancestral meta-analysis (EA + AA) of ANYDEP, and was attributable to alcohol dependence in both samples. Four genes (AA: CRKL, DZIP3, SBK3; EA: P2RX6) and four sets of genes were significantly enriched within biological pathways for hemostasis and signal transduction. GWS signals did not replicate in two independent samples but there was weak evidence for association between rs1890881 and alcohol intake in the UK Biobank. Among 118 AA and 481 EA individuals from the Duke Neurogenetics Study, rs75168521 and rs1890881 genotypes were associated with variability in reward-related ventral striatum activation. This study identified novel loci for substance dependence and provides preliminary evidence that these variants are also associated with individual differences in neural reward reactivity. Gene discovery efforts in non-European samples with distinct patterns of substance use may lead to the identification of novel ancestry-specific genetic markers of risk

The effectiveness of interventions to change six health behaviours: a review of reviews

Background: Several World Health Organisation reports over recent years have highlighted the high incidence of chronic diseases such as diabetes, coronary heart disease and cancer. Contributory factors include unhealthy diets, alcohol and tobacco use and sedentary lifestyles. This paper reports the findings of a review of reviews of behavioural change interventions to reduce unhealthy behaviours or promote healthy behaviours. We included six different health-related behaviours in the review: healthy eating, physical exercise, smoking, alcohol misuse, sexual risk taking (in young people) and illicit drug use. We excluded reviews which focussed on pharmacological treatments or those which required intensive treatments (e. g. for drug or alcohol dependency). Methods: The Cochrane Library, Database of Abstracts of Reviews of Effectiveness (DARE) and several Ovid databases were searched for systematic reviews of interventions for the six behaviours (updated search 2008). Two reviewers applied the inclusion criteria, extracted data and assessed the quality of the reviews. The results were discussed in a narrative synthesis. Results: We included 103 reviews published between 1995 and 2008. The focus of interventions varied, but those targeting specific individuals were generally designed to change an existing behaviour (e. g. cigarette smoking, alcohol misuse), whilst those aimed at the general population or groups such as school children were designed to promote positive behaviours (e. g. healthy eating). Almost 50% (n = 48) of the reviews focussed on smoking (either prevention or cessation). Interventions that were most effective across a range of health behaviours included physician advice or individual counselling, and workplace- and school-based activities. Mass media campaigns and legislative interventions also showed small to moderate effects in changing health behaviours. Generally, the evidence related to short-term effects rather than sustained/longer-term impact and there was a relative lack of evidence on how best to address inequalities. Conclusions: Despite limitations of the review of reviews approach, it is encouraging that there are interventions that are effective in achieving behavioural change. Further emphasis in both primary studies and secondary analysis (e.g. systematic reviews) should be placed on assessing the differential effectiveness of interventions across different population subgroups to ensure that health inequalities are addressed.</p

Linguistic measures of chemical diversity and the &quot;keywords&quot; of molecular collections

Computerized linguistic analyses have proven of immense value in comparing and searching through large text collections (&quot;corpora&quot;), including those deposited on the Internet-indeed, it would nowadays be hard to imagine browsing the Web without, for instance, search algorithms extracting most appropriate keywords from documents. This paper describes how such corpus-linguistic concepts can be extended to chemistry based on characteristic &quot;chemical words&quot; that span more than traditional functional groups and, instead, look at common structural fragments molecules share. Using these words, it is possible to quantify the diversity of chemical collections/databases in new ways and to define molecular &quot;keywords&quot; by which such collections are best characterized and annotated

Estimation of minimally important differences in EQ-5D utility and VAS scores in cancer

<p>Abstract</p> <p>Background</p> <p>Understanding what constitutes an important difference on a HRQL measure is critical to its interpretation. The aim of this study was to provide a range of estimates of minimally important differences (MIDs) in EQ-5D scores in cancer and to determine if estimates are comparable in lung cancer.</p> <p>Methods</p> <p>A retrospective analysis was conducted on cross-sectional data collected from 534 cancer patients, 50 of whom were lung cancer patients. A range of minimally important differences (MIDs) in EQ-5D index-based utility (UK and US) scores and VAS scores were estimated using both anchor-based and distribution-based (1/2 standard deviation and standard error of the measure) approaches. Groups were anchored using Eastern Cooperative Oncology Group performance status (PS) ratings and FACT-G total score-based quintiles.</p> <p>Results</p> <p>For UK-utility scores, MID estimates based on PS ranged from 0.10 to 0.12 both for all cancers and for lung cancer subgroup. Using FACT-G quintiles, MIDs were 0.09 to 0.10 for all cancers, and 0.07 to 0.08 for lung cancer. For US-utility scores, MIDs ranged from 0.07 to 0.09 grouped by PS for all cancers and for lung cancer; when based on FACT-G quintiles, MIDs were 0.06 to 0.07 in all cancers and 0.05 to 0.06 in lung cancer. MIDs for VAS scores were similar for lung and all cancers, ranging from 8 to 12 (PS) and 7 to 10 (FACT-G quintiles).</p> <p>Discussion</p> <p>Important differences in EQ-5D utility and VAS scores were similar for all cancers and lung cancer, with the lower end of the range of estimates closer to the MID, i.e. 0.08 for UK-index scores, 0.06 for US-index scores, and 0.07 for VAS scores.</p

Analysis of AML genes in dysregulated molecular networks

<p>Abstract</p> <p>Background</p> <p>Identifying disease causing genes and understanding their molecular mechanisms are essential to developing effective therapeutics. Thus, several computational methods have been proposed to prioritize candidate disease genes by integrating different data types, including sequence information, biomedical literature, and pathway information. Recently, molecular interaction networks have been incorporated to predict disease genes, but most of those methods do not utilize invaluable disease-specific information available in mRNA expression profiles of patient samples.</p> <p>Results</p> <p>Through the integration of protein-protein interaction networks and gene expression profiles of acute myeloid leukemia (AML) patients, we identified subnetworks of interacting proteins dysregulated in AML and characterized known mutation genes causally implicated to AML embedded in the subnetworks. The analysis shows that the set of extracted subnetworks is a reservoir rich in AML genes reflecting key leukemogenic processes such as myeloid differentiation.</p> <p>Conclusion</p> <p>We showed that the integrative approach both utilizing gene expression profiles and molecular networks could identify AML causing genes most of which were not detectable with gene expression analysis alone due to the minor changes in mRNA level.</p