Machine learning for automated quality assurance in radiotherapy: A proof of principle using EPID data description

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149320/1/mp13433_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149320/2/mp13433.pd

A method for the identification of COVID-19 biomarkers in human breath using Proton Transfer Reaction Time-of-Flight Mass Spectrometry

Background: COVID-19 has caused a worldwide pandemic, making the early detection of the virus crucial. We present an approach for the determination of COVID-19 infection based on breath analysis. Methods: A high sensitivity mass spectrometer was combined with artificial intelligence and used to develop a method for the identification of COVID-19 in human breath within seconds. A set of 1137 positive and negative subjects from different age groups, collected in two periods from two hospitals in the USA, from 26 August, 2020 until 15 September, 2020 and from 11 September, 2020 until 11 November, 2020, was used for the method development. The subjects exhaled in a Tedlar bag, and the exhaled breath samples were subsequently analyzed using a Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-ToF-MS). The produced mass spectra were introduced to a series of machine learning models. 70% of the data was used for these sub-models\u27 training and 30% was used for testing. Findings: A set of 340 samples, 95 positives and 245 negatives, was used for the testing. The combined models successfully predicted 77 out of the 95 samples as positives and 199 out of the 245 samples as negatives. The overall accuracy of the model was 81.2%. Since over 50% of the total positive samples belonged to the age group of over 55 years old, the performance of the model in this category was also separately evaluated on 339 subjects (170 negative and 169 positive). The model correctly identified 166 out of the 170 negatives and 164 out of the 169 positives. The model accuracy in this case was 97.3%. Interpretation: The results showed that this method for the identification of COVID-19 infection is a promising tool, which can give fast and accurate results

Automating linear accelerator quality assurance

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/135049/1/mp1415.pd

Use of Genomic DNA as an Indirect Reference for Identifying Gender-Associated Transcripts in Morphologically Identical, but Chromosomally Distinct, Schistosoma mansoni Cercariae

BACKGROUND: The use of DNA microarray technology to study global Schistosoma gene expression has led to the rapid identification of novel biological processes, pathways or associations. Implementation of standardized DNA microarray protocols across laboratories would assist maximal interpretation of generated datasets and extend productive application of this technology. METHODOLOGY/PRINCIPAL FINDINGS: Utilizing a new Schistosoma mansoni oligonucleotide DNA microarray composed of 37,632 elements, we show that schistosome genomic DNA (gDNA) hybridizes with less variation compared to complex mixed pools of S. mansoni cDNA material (R = 0.993 for gDNA compared to R = 0.956 for cDNA during ‘self versus self’ hybridizations). Furthermore, these effects are species-specific, with S. japonicum or Mus musculus gDNA failing to bind significantly to S. mansoni oligonucleotide DNA microarrays (e.g R = 0.350 when S. mansoni gDNA is co-hybridized with S. japonicum gDNA). Increased median fluorescent intensities (209.9) were also observed for DNA microarray elements hybridized with S. mansoni gDNA compared to complex mixed pools of S. mansoni cDNA (112.2). Exploiting these valuable characteristics, S. mansoni gDNA was used in two-channel DNA microarray hybridization experiments as a common reference for indirect identification of gender-associated transcripts in cercariae, a schistosome life-stage in which there is no overt sexual dimorphism. This led to the identification of 2,648 gender-associated transcripts. When compared to the 780 gender-associated transcripts identified by hybridization experiments utilizing a two-channel direct method (co-hybridization of male and female cercariae cDNA), indirect methods using gDNA were far superior in identifying greater quantities of differentially expressed transcripts. Interestingly, both methods identified a concordant subset of 188 male-associated and 156 female-associated cercarial transcripts, respectively. Gene ontology classification of these differentially expressed transcripts revealed a greater diversity of categories in male cercariae. Quantitative real-time PCR analysis confirmed the DNA microarray results and supported the reliability of this platform for identifying gender-associated transcripts. CONCLUSIONS/SIGNIFICANCE: Schistosome gDNA displays characteristics highly suitable for the comparison of two-channel DNA microarray results obtained from experiments conducted independently across laboratories. The schistosome transcripts identified here demonstrate, for the first time, that gender-associated patterns of expression are already well established in the morphologically identical, but chromosomally distinct, cercariae stage

A Systematically Improved High Quality Genome and Transcriptome of the Human Blood Fluke Schistosoma mansoni

Schistosomiasis is one of the most prevalent parasitic diseases, affecting millions of people in developing countries. Amongst the human-infective species, Schistosoma mansoni is also the most commonly used in the laboratory and here we present the systematic improvement of its draft genome. We used Sanger capillary and deep-coverage Illumina sequencing from clonal worms to upgrade the highly fragmented draft 380 Mb genome to one with only 885 scaffolds and more than 81% of the bases organised into chromosomes. We have also used transcriptome sequencing (RNA-seq) from four time points in the parasite's life cycle to refine gene predictions and profile their expression. More than 45% of predicted genes have been extensively modified and the total number has been reduced from 11,807 to 10,852. Using the new version of the genome, we identified trans-splicing events occurring in at least 11% of genes and identified clear cases where it is used to resolve polycistronic transcripts. We have produced a high-resolution map of temporal changes in expression for 9,535 genes, covering an unprecedented dynamic range for this organism. All of these data have been consolidated into a searchable format within the GeneDB (www.genedb.org) and SchistoDB (www.schistodb.net) databases. With further transcriptional profiling and genome sequencing increasingly accessible, the upgraded genome will form a fundamental dataset to underpin further advances in schistosome research

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder