An uncommon variant of rare type of muscular dystrophy

The muscular dystrophies are a group of hereditary degenerative diseases characterised by progressive myopathy. Emery-Dreifuss muscular dystrophy (EDMD) is a rare genetically heterogenous type of muscular dystrophy characterized by early contractures (especially in the neck, elbows and ankles), slowly progressing muscle weakness more prominent in humeroperoneal region, onset in early childhood and cardiac problems. Emery-Dreifuss muscular dystrophy is commonly inherited in an X linked recessive pattern and rarely autosomal dominant inheritance or autosomal recessive fashion. Here we report a case of autosomal recessive type of Emery-Dreifuss muscular dystrophy from our hospital

Adapting the HHL algorithm to (non-unitary) quantum many-body theory

Rapid progress in developing near- and long-term quantum algorithms for quantum chemistry has provided us with an impetus to move beyond traditional approaches and explore new ways to apply quantum computing to electronic structure calculations. In this work, we identify the connection between quantum many-body theory and a quantum linear solver, and implement the Harrow-Hassidim-Lloyd (HHL) algorithm to make precise predictions of correlation energies for light molecular systems via the (non-unitary) linearised coupled cluster theory. We alter the HHL algorithm to integrate two novel aspects- (a) we prescribe a novel scaling approach that allows one to scale any arbitrary symmetric positive definite matrix A, to solve for Ax = b and achieve x with reasonable precision, all the while without having to compute the eigenvalues of A, and (b) we devise techniques that reduce the depth of the overall circuit. In this context, we introduce the following variants of HHL for different eras of quantum computing- AdaptHHLite in its appropriate forms for noisy intermediate scale quantum (NISQ), late-NISQ, and the early fault-tolerant eras, as well as AdaptHHL for the fault-tolerant quantum computing era. We demonstrate the ability of the NISQ variant of AdaptHHLite to capture correlation energy precisely, while simultaneously being resource-lean, using simulation as well as the 11-qubit IonQ quantum hardware

Improvement in diagnosis of breast tumour using ultrasound elastography and echography: A phantom based analysis

Due to the isoechoic nature of lesions and their poor contrast with neighbouring tissue, a lesion may remain undetected in ultrasound B mode imaging for cancerous tissue. Imaging of the elastic properties of tissue provides new information which is collateral to tissue pathology. This study provides quantitative analysis of improvements in tumour diagnosis when the ultrasound B mode imaging is combined with elastography. Quantification was based on the textural parameters measured from the ultrasound B mode image and strain measured from the elastogram. The ability of a parameter to discriminate between diseased cases and normal cases was evaluated using receiver operating characteristic (ROC) analysis. Polyacrylamide gel based tissue mimicking phantoms with embedded inclusions of varying stiffness were used for the analysis

Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals

We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12-16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI's magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57