Charge density study with the Maximum Entropy Method on model data of silicon. A search for non-nuclear attractors

1990 Sakata and Sato applied the maximum entropy method (MEM) to a set of structure factors measured earlier by Saka and Kato with the Pendellösung method. They found the presence of non-nuclear attractors, i.e., maxima in the density between two bonded atoms. We applied the MEM to a limited set of Fourier data calculated from a known electron density distribution (EDD) of silicon. The EDD of silicon was calculated with the program ADF-BAND. This program performs electronic structure calculations, including periodicity, based on the density functional theory of Hohenberg and Kohn. No non-nuclear attractor between two bonded silicon atoms was observed in this density. Structure factors were calculated from this density and the same set of structure factors that was measured by Saka and Kato was used in the MEM analysis. The EDD obtained with the MEM shows the same non-nuclear attractors that were later obtained by Sakata and Sato. This means that the non-nuclear attractors in silicon are really an artefact of the MEM

Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening

Background: Unexplained Left Ventricular Hypertrophy (ULVH) may be caused by genetic and non-genetic etiologies (e.g., sarcomere variants, cardiac amyloid, or Anderson-Fabry's disease). Identification of ULVH patients allows for early targeted treatment and family screening. Aim: To automatically identify patients with ULVH in electronic health record (EHR) data using two computer methods: text-mining and machine learning (ML). Methods: Adults with echocardiographic measurement of interventricular septum thickness (IVSt) were included. A text-mining algorithm was developed to identify patients with ULVH. An ML algorithm including a variety of clinical, ECG and echocardiographic data was trained and tested in an 80/20% split. Clinical diagnosis of ULVH was considered the gold standard. Misclassifications were reviewed by an experienced cardiologist. Sensitivity, specificity, positive, and negative likelihood ratios (LHR+ and LHR-) of both text-mining and ML were reported. Results: In total, 26,954 subjects (median age 61 years, 55% male) were included. ULVH was diagnosed in 204/26,954 (0.8%) patients, of which 56 had amyloidosis and two Anderson-Fabry Disease. Text-mining flagged 8,192 patients with possible ULVH, of whom 159 were true positives (sensitivity, specificity, LHR+, and LHR- of 0.78, 0.67, 2.36, and 0.33). Machine learning resulted in a sensitivity, specificity, LHR+, and LHR- of 0.32, 0.99, 32, and 0.68, respectively. Pivotal variables included IVSt, systolic blood pressure, and age. Conclusions: Automatic identification of patients with ULVH is possible with both Text-mining and ML. Text-mining may be a comprehensive scaffold but can be less specific than machine learning. Deployment of either method depends on existing infrastructures and clinical applications

Association testing by haplotype-sharing methods applicable to whole-genome analysis

We propose two new haplotype-sharing methods for identifying disease loci: the haplotype sharing statistic (HSS), which compares length of shared haplotypes between cases and controls, and the CROSS test, which tests whether a case and a control haplotype show less sharing than two random haplotypes. The significance of the HSS is determined using a variance estimate from the theory of U-statistics, whereas the significance of the CROSS test is estimated from a sequential randomization procedure. Both methods are fast and hence practical, even for whole-genome screens with high marker densities. We analyzed data sets of Problems 2 and 3 of Genetic Analysis Workshop 15 and compared HSS and CROSS to conventional association methods. Problem 2 provided a data set of 2300 single-nucleotide polymorphisms (SNPs) in a 10-Mb region of chromosome 18q, which had shown linkage evidence for rheumatoid arthritis. The CROSS test detected a significant association at approximately position 4407 kb. This was supported by single-marker association and HSS. The CROSS test outperformed them both with respect to significance level and signal-to-noise ratio. A 20-kb candidate region could be identified. Problem 3 provided a simulated 10 k SNP data set covering the whole genome. Three known candidate regions for rheumatoid arthritis were detected. Again, the CROSS test gave the most significant results. Furthermore, both the HSS and the CROSS showed better fine-mapping accuracy than straightforward haplotype association. In conclusion, haplotype sharing methods, particularly the CROSS test, show great promise for identifying disease gene loci

‘The war is a money making show’: Working-Class Attitudes to World War II and Australian Nationalism

This paper will address the conference themes of ‘class, power and social structure’ through examining industrial and ideological conflict during World War II. The paper will also address the theme of ‘class and culture’ through an examination of working-class cultural expression as a means of resistance to the government’s wartime offensive. What is overlooked in most histories of World War II is the working-class experience of the war and their understanding of nationalism, particularly as nationalism was cynically exploited by the government to undermine working-class identity and solidarity. The paper will investigate the experience of one of the most militant sections of the Australian working class: the Miners. Primary source material such as the Miners’ journal Common Cause and union records reveal opposition to the war and a much more ambiguous attitude to the national sentiment used to justify Australia’s involvement. The Miners provide an interesting case study as the union was led by the Communist Party. Therefore the union leadership initially opposed to the war then became enthusiastic supporters when Russia entered the war on the allied side. It is clear that the Miners’ union leadership found it difficult to convince the rank and file to support the war. The paper will focus upon rank and file attitudes to the war and Australian nationalism particularly during times of industrial unrest.The symposium is organised on behalf of AAHANZBS by the Business and Labour History Group, The University of Sydney, with the financial support of the University’s Faculty of Economics and Business

CAG Repeat Size Influences the Progression Rate of Spinocerebellar Ataxia Type 3

Objective: In spinocerebellar ataxia type 3/Machado-Joseph disease (SCA3/MJD), the expanded cytosine adenine guanine (CAG) repeat in ATXN3 is the causal mutation, and its length is the main factor in determining the age at onset (AO) of clinical symptoms. However, the contribution of the expanded CAG repeat length to the rate of disease progression after onset has remained a matter of debate, even though an understanding of this factor is crucial for experimental data on disease modifiers and their translation to clinical trials and their design. Methods: Eighty-two Dutch patients with SCA3/MJD were evaluated annually for 15 years using the International Cooperative Ataxia Rating Scale (ICARS). Using linear growth curve models, ICARS progression rates were calculated and tested for their relation to the length of the CAG repeat expansion and to the residual age at onset (RAO): The difference between the observed AO and the AO predicted on the basis of the CAG repeat length. Results: On average, ICARS scores increased 2.57 points/year of disease. The length of the CAG repeat was positively correlated with a more rapid ICARS progression, explaining 30% of the differences between patients. Combining both the length of the CAG repeat and RAO as comodifiers explained up to 47% of the interpatient variation in ICARS progression. Interpretation: Our data imply that the length of the expanded CAG repeat in ATXN3 is a major determinant of clinical decline, which suggests that CAG-dependent molecular mechanisms similar to those responsible for disease onset also contribute to the rate of disease progression in SCA3/MJD. ANN NEUROL 2020