Radiation exposure determination in a secure, cloud-based online environment.

Rapid sample processing and interpretation of estimated exposures will be critical for triaging exposed individuals after a major radiation incident. The dicentric chromosome (DC) assay assesses absorbed radiation using metaphase cells from blood. The Automated Dicentric Chromosome Identifier and Dose Estimator System (ADCI) identifies DCs and determines radiation doses.

Likely community transmission of COVID-19 infections between neighboring, persistent hotspots in Ontario, Canada.

This study aimed to produce community-level geo-spatial mapping of confirmed COVID-19 cases in Ontario Canada in near real-time to support decision-making. This was accomplished by area-to-area geostatistical analysis, space-time integration, and spatial interpolation of COVID-19 positive individuals. COVID-19 cases and locations were curated for geostatistical analyses from March 2020 through June 2021, corresponding to the first, second, and third waves of infections.

Pathway-extended gene expression signatures integrate novel biomarkers that improve predictions of patient responses to kinase inhibitors.

Cancer chemotherapy responses have been related to multiple pharmacogenetic biomarkers, often for the same drug. This study utilizes machine learning to derive multi-gene expression signatures that predict individual patient responses to specific tyrosine kinase inhibitors, including erlotinib, gefitinib, sorafenib, sunitinib, lapatinib and imatinib. Support vector machine (SVM) learning was used to train mathematical models that distinguished sensitivity from resistance to these drugs using a novel systems biology-based approach.

Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures.

Purpose: Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning (ML) based signatures (with 8-20% misclassification rates). These signatures can quantify therapeutically relevant as well as accidental radiation exposures. The prodromal symptoms of acute radiation syndrome (ARS) overlap those present in influenza and dengue fever infections.

Differentially accessible, single copy sequences form contiguous domains along metaphase chromosomes that are conserved among multiple tissues.

Background: During mitosis, chromatin engages in a dynamic cycle of condensation and decondensation. Condensation into distinct units to ensure high fidelity segregation is followed by rapid and reproducible decondensation to produce functional daughter cells. Factors contributing to the reproducibility of chromatin structure between cell generations are not well understood.

Readability of online sources of information regarding epilepsy surgery and its impact on decision-making processes.

Introduction: People with epilepsy can have cognitive deficits, including difficulty with reading tasks. This can potentially impact on how written information is understood. Websites increasingly provide information about different medical interventions including epilepsy surgery.

A proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections.

Certain riboviruses can cause severe pulmonary complications leading to death in some infected patients. We propose that DNA damage induced-apoptosis accelerates viral release, triggered by depletion of host RNA binding proteins (RBPs) from nuclear RNA bound to replicating viral sequences. Information theory-based analysis of interactions between RBPs and individual sequences in the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), Influenza A (H3N2), HIV-1, and Dengue genomes identifies strong RBP binding sites in these viral genomes.

"The Brain Society": The First Two Years of an Undergraduate Neuroscience Society in Northern Ireland.

The Queen's University Belfast Brain Society was set up in September 2018 to promote interest in the human brain. There were three main goals: firstly to provide opportunities for medical students to learn from neurologists and neurosurgeons outside their formal curriculum; secondly the Brain Society aimed to organise events that included students from other disciplines and to members of the general public who were interested in learning about aspects of neuroscience; thirdly to tackle neurophobia. In the last two years, there have been 14 events, ranging from formal lectures, to practical sessions and to patient-focused information evenings.

Estimating partial-body ionizing radiation exposure by automated cytogenetic biodosimetry.

Purpose: Inhomogeneous exposures to ionizing radiation can be detected and quantified with the dicentric chromosome assay (DCA) of metaphase cells. Complete automation of interpretation of the DCA for whole-body irradiation has significantly improved throughput without compromising accuracy, however, low levels of residual false positive dicentric chromosomes (DCs) have confounded its application for partial-body exposure determination.

Materials And Methods: We describe a method of estimating and correcting for false positive DCs in digitally processed images of metaphase cells.

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices.

Purpose: The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways to novel treatments. Yet the clinical cancer genomics field has been hindered by redundant efforts to meaningfully collect and interpret disparate data types from multiple high-throughput modalities and integrate into clinical care processes. Bespoke data models, knowledgebases, and one-off customized resources for data analysis often lack adequate governance and quality control needed for these resources to be clinical grade.

Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling.

Background: Accurate radiation dose estimates are critical for determining eligibility for therapies by timely triaging of exposed individuals after large-scale radiation events. However, the universal assessment of a large population subjected to a nuclear spill incident or detonation is not feasible. Even with high-throughput dosimetry analysis, test volumes far exceed the capacities of first responders to measure radiation exposures directly, or to acquire and process samples for follow-on biodosimetry testing.

Expression Changes Confirm Genomic Variants Predicted to Result in Allele-Specific, Alternative mRNA Splicing.

Splice isoform structure and abundance can be affected by either noncoding or masquerading coding variants that alter the structure or abundance of transcripts. When these variants are common in the population, these nonconstitutive transcripts are sufficiently frequent so as to resemble naturally occurring, alternative mRNA splicing. Prediction of the effects of such variants has been shown to be accurate using information theory-based methods.

Pan-cancer repository of validated natural and cryptic mRNA splicing mutations.

We present a major public resource of mRNA splicing mutations validated according to multiple lines of evidence of abnormal gene expression. Likely mutations present in all tumor types reported in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) were identified based on the comparative strengths of splice sites in tumor versus normal genomes, and then validated by respectively comparing counts of splice junction spanning and abundance of transcript reads in RNA-Seq data from matched tissues and tumors lacking these mutations. The comprehensive resource features 341,486 of these validated mutations, the majority of which (69.

Multigene signatures of responses to chemotherapy derived by biochemically-inspired machine learning.

Pharmacogenomic responses to chemotherapy drugs can be modeled by supervised machine learning of expression and copy number of relevant gene combinations. Such biochemical evidence can form the basis of derived gene signatures using cell line data, which can subsequently be examined in patients that have been treated with the same drugs. These gene signatures typically contain elements of multiple biochemical pathways which together comprise multiple origins of drug resistance or sensitivity.

Transcription factor binding site clusters identify target genes with similar tissue-wide expression and buffer against mutations.

The distribution and composition of -regulatory modules composed of transcription factor (TF) binding site (TFBS) clusters in promoters substantially determine gene expression patterns and TF targets. TF knockdown experiments have revealed that TF binding profiles and gene expression levels are correlated. We use TFBS features within accessible promoter intervals to predict genes with similar tissue-wide expression patterns and TF targets using Machine Learning (ML).

Predicting responses to platin chemotherapy agents with biochemically-inspired machine learning.

The selection of effective genes that accurately predict chemotherapy responses might improve cancer outcomes. We compare optimized gene signatures for cisplatin, carboplatin, and oxaliplatin responses in the same cell lines and validate each signature using data from patients with cancer. Supervised support vector machine learning is used to derive gene sets whose expression is related to the cell line GI values by backwards feature selection with cross-validation.

RADIATION DOSE ESTIMATION BY COMPLETELY AUTOMATED INTERPRETATION OF THE DICENTRIC CHROMOSOME ASSAY.

Accuracy of the automated dicentric chromosome (DC) assay relies on metaphase image selection. This study validates a software framework to find the best image selection models that mitigate inter-sample variability. Evaluation methods to determine model quality include the Poisson goodness-of-fit of DC distributions for each sample, residuals after calibration curve fitting and leave-one-out dose estimation errors.

Survival outcome differences based on treatments used and knowledge of the primary tumour site for patients with cancer of unknown and known primary in Ontario.

Introduction: Patients with cancer of unknown primary (cup) have pathologically confirmed metastatic tumours with unidentifiable primary tumours. Currently, very little is known about the relationship between the treatment of patients with cup and their survival outcomes. Thus, we compared oncologic treatment and survival outcomes for patients in Ontario with cup against those for a cohort of patients with metastatic cancer of known primary site.

BRCA1 and BRCA2 5' noncoding region variants identified in breast cancer patients alter promoter activity and protein binding.

The widespread use of next generation sequencing for clinical testing is detecting an escalating number of variants in noncoding regions of the genome. The clinical significance of the majority of these variants is currently unknown, which presents a significant clinical challenge. We have screened over 6,000 early-onset and/or familial breast cancer (BC) cases collected by the ENIGMA consortium for sequence variants in the 5' noncoding regions of BC susceptibility genes BRCA1 and BRCA2, and identified 141 rare variants with global minor allele frequency < 0.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches.

The Potential Clinical and Economic Value of Primary Tumour Identification in Metastatic Cancer of Unknown Primary Tumour: A Population-Based Retrospective Matched Cohort Study.

Purpose: Several genomic tests have recently been developed to identify the primary tumour in cancer of unknown primary tumour (CUP). However, the value of identifying the primary tumour in clinical practice for CUP patients remains questionable and difficult to prove in randomized trials.

Objective: We aimed to assess the clinical and economic value of primary tumour identification in CUP using a retrospective matched cohort study.

Assessment of the functional impact of germline BRCA1/2 variants located in non-coding regions in families with breast and/or ovarian cancer predisposition.

Purpose: The molecular mechanism of breast and/or ovarian cancer susceptibility remains unclear in the majority of patients. While germline mutations in the regulatory non-coding regions of BRCA1 and BRCA2 genes have been described, screening has generally been limited to coding regions. The aim of this study was to evaluate the contribution of BRCA1/2 non-coding variants.

The clinical significance of occult gynecologic primary tumours in metastatic cancer.

Objective: We estimated the frequency of occult gynecologic primary tumours (gpts) in patients with metastatic cancer from an uncertain primary and evaluated the effect on disease management and overall survival (os).

Methods: We used Manitoba administrative health databases to identify all patients initially diagnosed with metastatic cancer during 2002-2011. We defined patients as having an "occult" primary tumour if the primary was classified at least 6 months after the initial diagnosis.

Accurate cytogenetic biodosimetry through automated dicentric chromosome curation and metaphase cell selection.

Accurate digital image analysis of abnormal microscopic structures relies on high quality images and on minimizing the rates of false positive (FP) and negative objects in images. Cytogenetic biodosimetry detects dicentric chromosomes (DCs) that arise from exposure to ionizing radiation, and determines radiation dose received based on DC frequency. Improvements in automated DC recognition increase the accuracy of dose estimates by reclassifying FP DCs as monocentric chromosomes or chromosome fragments.