HPC+ in the medical field: Overview and current examples.

BACKGROUND: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together "HPC+"). OBJECTIVE: This overview article aims to show state-of-the-art examples of studies supported by the National Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications. METHOD: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures. RESULTS: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research. CONCLUSION: HPC+ support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research.

An analytical expression for the D.I.P.-P.I.P. flexion interdependence in human fingers.

UNLABELLED: Empirical evidence shows that a strong correlation exists between the flexion angles of the distal and proximal interphalangeal (D.I.P., P.I.P.) joints of the human finger. Several authors measured this functional dependence, stating that the interdependence of D.I.P. and P.I.P. flexion is different for healthy individuals and patients displaying pathologies. The purpose of our study is to find an analytical expression for this correlation. METHODS: Following closely the anatomical in situ relations, we developed a two-dimensional kinematical model which expresses analytically the D.I.P.-P.I.P. angle correlation. Numerical values for the model were extracted from one healthy and one pathological case data set. RESULTS: The analytical form of the model allows for any P.I.P. angle not only to calculate the corre- sponding D.I.P. angle, but after first order differentiation with respect to the P.I.P. angle, it also shows the rate of change of the D.I.P. flexion. The model reproduces well the differences in the angular correlation of D.I.P. flexion of the two healthy-pathological data sets. Displaying the rate of change of D.I.P. flexion versus P.I.P. flexion provides an additional, clear-cut discriminatory tool between normal and pathological states. CONCLUSIONS: Information on differences between normal and pathological flexion of fingers is more pronounced and easier accessible from the derivatives of the D.I.P.-P.I.P. flexion behaviour than from direct angular correlation data. The analytical form of our model allows one to establish the rate of change of the D.I.P. angles, resulting in a better analysis of the situations at hand.

Reliable gene expression analysis by reverse transcription-quantitative PCR: reporting and minimizing the uncertainty in data accuracy.

Reverse transcription-quantitative PCR (RT-qPCR) has been widely adopted to measure differences in mRNA levels; however, biological and technical variation strongly affects the accuracy of the reported differences. RT-qPCR specialists have warned that, unless researchers minimize this variability, they may report inaccurate differences and draw incorrect biological conclusions. The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines describe procedures for conducting and reporting RT-qPCR experiments. The MIQE guidelines enable others to judge the reliability of reported results; however, a recent literature survey found low adherence to these guidelines. Additionally, even experiments that use appropriate procedures remain subject to individual variation that statistical methods cannot correct. For example, since ideal reference genes do not exist, the widely used method of normalizing RT-qPCR data to reference genes generates background noise that affects the accuracy of measured changes in mRNA levels. However, current RT-qPCR data reporting styles ignore this source of variation. In this commentary, we direct researchers to appropriate procedures, outline a method to present the remaining uncertainty in data accuracy, and propose an intuitive way to select reference genes to minimize uncertainty. Reporting the uncertainty in data accuracy also serves for quality assessment, enabling researchers and peer reviewers to confidently evaluate the reliability of gene expression data.

Phylogenetic diversity of Sri Lankan freshwater crabs and its implications for conservation.

As part of a Global Biodiversity Hotspot, the conservation of Sri Lanka's endemic biodiversity warrants special attention. With 51 species (50 of them endemic) occurring in the island, the biodiversity of freshwater crabs is unusually high for such a small area (65,600 km(2)). Freshwater crabs have successfully colonized most moist habitats and all climatic and elevational zones in Sri Lanka. We assessed the biodiversity of these crabs in relation to the different elevational zones (lowland, upland and highland) based on both species richness and phylogenetic diversity. Three different lineages appear to have radiated simultaneously, each within a specific elevational zone, with little interchange thereafter. The lowland and upland zones show a higher species richness than the highland zone while--unexpectedly--phylogenetic diversity is highest in the lowland zone, illustrating the importance of considering both these measures in conservation planning. The diversity indices for the species in the various IUCN Red List categories in each of the three zones suggest that risk of extinction may be related to elevational zone. Our results also show that overall more than 50% of Sri Lanka's freshwater crab species (including several as yet undescribed ones), or approximately 72 million years of evolutionary history, are threatened with extinction.