Reanalysis and reclassification of rare genetic variants associated with inherited arrhythmogenic syndromes

Background: Accurate interpretation of rare genetic variants is a challenge for clinical translation. Updates in recommendations for rare variant classification require the reanalysis and reclassification. We aim to perform an exhaustive re-analysis of rare variants associated with inherited arrhythmogenic syndromes, which were classified ten years ago, to determine whether their classification aligns with current standards and research findings. Methods: In 2010, the rare variants identified through genetic analysis were classified following recommendations available at that time. Nowadays, the same variants have been reclassified following current American College of Medical Genetics and Genomics recommendations. Findings: Our cohort included 104 cases diagnosed with inherited arrhythmogenic syndromes and 17 post-mortem cases in which inherited arrhythmogenic syndromes was cause of death. 71.87% of variants change their classification. While 65.62% of variants were classified as likely pathogenic in 2010, after reanalysis, only 17.96% remain as likely pathogenic. In 2010, 18.75% of variants were classified as uncertain role but nowadays 60.15% of variants are classified of unknown significance. Interpretation: Reclassification occurred in more than 70% of rare variants associated with inherited arrhythmogenic syndromes. Our results support the periodical reclassification and personalized clinical translation of rare variants to improve diagnosis and adjust treatment

Potential of heat pipe technology in nuclear seawater desalination

The official published version of this article can be found at the link below.Heat pipe technology may play a decisive role in improving the overall economics, and public perception on nuclear desalination, specifically on seawater desalination. When coupled to the Low-Temperature Multi-Effect Distillation process, heat pipes could effectively harness most of the waste heat generated in various types of nuclear power reactors. Indeed, the potential application of heat pipes could be seen as a viable option to nuclear seawater desalination where the efficiency to harness waste heat might not only be enhanced to produce larger quantities of potable water, but also to reduce the environmental impact of nuclear desalination process. Furthermore, the use of heat pipe-based heat recovery systems in desalination plant may improve the overall thermodynamics of the desalination process, as well as help to ensure that the product water is free from any contamination which occur under normal process, thus preventing operational failure occurrences as this would add an extra loop preventing direct contact between radiation and the produced water. In this paper, a new concept for nuclear desalination system based on heat pipe technology is introduced and the anticipated reduction in the tritium level resulting from the use of heat pipe systems is discussed

Spin-hybrid-phonon resonance in anisotropic quantum dots

We have studied the absorption of electromagnetic radiation of an anisotropic quantum dot taking into account the spin-flip processes that is associated with the interaction of the electrons with optical phonons. It is shown that these processes lead to the resonance absorption. Explicit formula is derived for the absorption coefficient. The positions of the resonances peaks are found

The value of source data verification in a cancer clinical trial

Background Source data verification (SDV) is a resource intensive method of quality assurance frequently used in clinical trials. There is no empirical evidence to suggest that SDV would impact on comparative treatment effect results from a clinical trial. Methods Data discrepancies and comparative treatment effects obtained following 100% SDV were compared to those based on data without SDV. Overall survival (OS) and Progression-free survival (PFS) were compared using Kaplan-Meier curves, log-rank tests and Cox models. Tumour response classifications and comparative treatment Odds Ratios (ORs) for the outcome objective response rate, and number of Serious Adverse Events (SAEs) were compared. OS estimates based on SDV data were compared against estimates obtained from centrally monitored data. Findings Data discrepancies were identified between different monitoring procedures for the majority of variables examined, with some variation in discrepancy rates. There were no systematic patterns to discrepancies and their impact was negligible on OS, the primary outcome of the trial (HR (95% CI): 1.18(0.99 to 1.41), p = 0.064 with 100% SDV; 1.18(0.99 to 1.42), p = 0.068 without SDV; 1.18(0.99 to 1.40), p = 0.073 with central monitoring). Results were similar for PFS. More extreme discrepancies were found for the subjective outcome overall objective response (OR (95% CI): 1.67(1.04 to 2.68), p = 0.03 with 100% SDV; 2.45(1.49 to 4.04), p = 0.0003 without any SDV) which was mostly due to differing CT scans. Interpretation Quality assurance methods used in clinical trials should be informed by empirical evidence. In this empirical comparison, SDV was expensive and identified random errors that made little impact on results and clinical conclusions of the trial. Central monitoring using an external data source was a more efficient approach for the primary outcome of OS. For the subjective outcome objective response, an independent blinded review committee and tracking system to monitor missing scan data could be more efficient than SDV

Multi-omics differentially classify disease state and treatment outcome in pediatric Crohn's disease

Background: Crohn's disease (CD) has an unclear etiology, but there is growing evidence of a direct link with a dysbiotic microbiome. Many gut microbes have previously been associated with CD, but these have mainly been confounded with patients' ongoing treatments. Additionally, most analyses of CD patients' microbiomes have focused on microbes in stool samples, which yield different insights than profiling biopsy samples. Results: We sequenced the 16S rRNA gene (16S) and carried out shotgun metagenomics (MGS) from the intestinal biopsies of 20 treatment-naïve CD and 20 control pediatric patients. We identified the abundances of microbial taxa and inferred functional categories within each dataset. We also identified known human genetic variants from the MGS data. We then used a machine learning approach to determine the classification accuracy when these datasets, collapsed to different hierarchical groupings, were used independently to classify patients by disease state and by CD patients' response to treatment. We found that 16S-identified microbes could classify patients with higher accuracy in both cases. Based on follow-ups with these patients, we identified which microbes and functions were best for predicting disease state and response to treatment, including several previously identified markers. By combining the top features from all significant models into a single model, we could compare the relative importance of these predictive features. We found that 16S-identified microbes are the best predictors of CD state whereas MGS-identified markers perform best for classifying treatment response. Conclusions: We demonstrate for the first time that useful predictors of CD treatment response can be produced from shotgun MGS sequencing of biopsy samples despite the complications related to large proportions of host DNA. The top predictive features that we identified in this study could be useful for building an improved classifier for CD and treatment response based on sufferers' microbiome in the future. The BISCUIT project is funded by a Clinical Academic Fellowship from the Chief Scientist Office (Scotland)-CAF/08/01

Quantitative Three-Dimensional Tissue Cytometry to Study Kidney Tissue and Resident Immune Cells

Analysis of the immune system in the kidney relies predominantly on flow cytometry. Although powerful, the process of tissue homogenization necessary for flow cytometry analysis introduces bias and results in the loss of morphologic landmarks needed to determine the spatial distribution of immune cells. An ideal approach would support three-dimensional (3D) tissue cytometry: an automated quantitation of immune cells and associated spatial parameters in 3D image volumes collected from intact kidney tissue. However, widespread application of this approach is limited by the lack of accessible software tools for digital analysis of large 3D microscopy data. Here, we describe Volumetric Tissue Exploration and Analysis (VTEA) image analysis software designed for efficient exploration and quantitative analysis of large, complex 3D microscopy datasets. In analyses of images collected from fixed kidney tissue, VTEA replicated the results of flow cytometry while providing detailed analysis of the spatial distribution of immune cells in different regions of the kidney and in relation to specific renal structures. Unbiased exploration with VTEA enabled us to discover a population of tubular epithelial cells that expresses CD11C, a marker typically expressed on dendritic cells. Finally, we show the use of VTEA for large-scale quantitation of immune cells in entire human kidney biopsies. In summary, we show that VTEA is a simple and effective tool that supports unique digital interrogation and analysis of kidney tissue from animal models or biobanked human kidney biopsies. We have made VTEA freely available to interested investigators via electronic download

Oxaliplatin for the treatment of cisplatin-resistant cancer: a systematic review

Oxaliplatin is widely regarded as being active in cisplatin-resistant cancer. We undertook a systematic review of the literature to identify, describe and critique the clinical and pre-clinical evidence for the use of oxaliplatin in patients with “cisplatin-resistant” cancer. We identified 25 pre-clinical cell models of platinum resistance and 24 clinical trials reporting oxaliplatin based salvage therapy for cisplatin-resistant cancer. The pre-clinical data suggests that there is cross-resistance between cisplatin and oxaliplatin in low-level resistance models. In models with high level resistance (>10 fold) there is less cross resistance between cisplatin and oxaliplatin, which may be a reason why oxaliplatin is thought to be active in cisplatin-resistant cancer. In clinical trials where oxaliplatin has been used as part of salvage therapy for patients who have failed cisplatin or carboplatin combination chemotherapy, there was a much lower response rate in patients with platinum-refractory or resistant cancers compared to platinum-sensitive cancers. This suggests that there may be cross-resistance between cisplatin and oxaliplatin in the clinic. Oxaliplatin as a single agent had a poor response rate in cisplatin refractory and resistant cancer. Oxaliplatin performed better in combination with other agents for the treatment of platinum resistant/refractory cancer suggesting that the benefit of oxaliplatin may lie in its more favourable toxicity and ability to be combined with other drugs rather than an underlying activity in cisplatin resistance. Oxaliplatin therefore should not be considered broadly active in cisplatin-resistant cancer

A Point-of-Use Quality Assurance Tool for Digital Pathology Remote Working

Pathology services are facing pressures due to the COVID-19 pandemic. Digital pathology has the capability to meet some of these unprecedented challenges by allowing remote diagnoses to be made at home, during periods of social distancing or self-isolation. However, while digital pathology allows diagnoses to be made on standard computer screens, unregulated home environments may not be conducive for optimal viewing conditions. There is also a paucity of experimental evidence available to support the minimum display requirements for digital pathology. This study presents a Point-of-Use Quality Assurance (POUQA) tool for remote assessment of viewing conditions for reporting digital pathology slides. The tool is a psychophysical test combining previous work from successfully implemented quality assurance tools in both pathology and radiology to provide a minimally intrusive display screen validation task, before viewing digital slides. The test is specific to pathology assessment in that it requires visual discrimination between colors derived from hematoxylin and eosin staining, with a perceptual difference of ±1 delta E (dE). This tool evaluates the transfer of a 1 dE signal through the digital image display chain, including the observers’ contrast and color responses within the test color range. The web-based system has been rapidly developed and deployed as a response to the COVID-19 pandemic and may be used by anyone in the world to help optimize flexible working conditions at: http://www.virtualpathology.leeds.ac.uk/res earch/systems/pouqa/

Classic and spatial shift-share analysis of state-level employment change in Brazil

This paper combines classic and spatial shift-share decompositions of 1981 to 2006 employment change across the 27 states of Brazil. The classic shift-share method shows higher employment growth rates for underdeveloped regions that are due to an advantageous industry-mix and also due to additional job creation, commonly referred to as the competitive effect. Alternative decompositions proposed in the literature do not change this broad conclusion. Further examination employing exploratory spatial data analysis (ESDA) shows spatial correlation of both the industry-mix and the competitive effects. Considering that until the 1960s economic activities were more concentrated in southern regions of Brazil than they are nowadays, these results support beta convergence theories but also find evidence of agglomeration effects. Additionally, a very simple spatial decomposition is proposed that accounts for the spatially-weighted growth of surrounding states. Favourable growth in northern and centre-western states is basically associated with those states’ strengths in potential spatial spillover effect and in spatial competitive effect