Use of nCounter mRNA profiling to identify at-arrival gene expression patterns for predicting bovine respiratory disease in beef cattle.

BACKGROUND: Transcriptomics has identified at-arrival differentially expressed genes associated with bovine respiratory disease (BRD) development; however, their use as prediction molecules necessitates further evaluation. Therefore, we aimed to selectively analyze and corroborate at-arrival mRNA expression from multiple independent populations of beef cattle. In a nested case-control study, we evaluated the expression of 56 mRNA molecules from at-arrival blood samples of 234 cattle across seven populations via NanoString nCounter gene expression profiling. Analysis of mRNA was performed with nSolver Advanced Analysis software (p < 0.05), comparing cattle groups based on the diagnosis of clinical BRD within 28 days of facility arrival (n = 115 Healthy; n = 119 BRD); BRD was further stratified for severity based on frequency of treatment and/or mortality (Treated_1, n = 89; Treated_2+, n = 30). Gene expression homogeneity of variance, receiver operator characteristic (ROC) curve, and decision tree analyses were performed between severity cohorts. RESULTS: Increased expression of mRNAs involved in specialized pro-resolving mediator synthesis (ALOX15, HPGD), leukocyte differentiation (LOC100297044, GCSAML, KLF17), and antimicrobial peptide production (CATHL3, GZMB, LTF) were identified in Healthy cattle. BRD cattle possessed increased expression of CFB, and mRNA related to granulocytic processes (DSG1, LRG1, MCF2L) and type-I interferon activity (HERC6, IFI6, ISG15, MX1). Healthy and Treated_1 cattle were similar in terms of gene expression, while Treated_2+ cattle were the most distinct. ROC cutoffs were used to generate an at-arrival treatment decision tree, which classified 90% of Treated_2+ individuals. CONCLUSIONS: Increased expression of complement factor B, pro-inflammatory, and type I interferon-associated mRNA hallmark the at-arrival expression patterns of cattle that develop severe clinical BRD. Here, we corroborate at-arrival mRNA markers identified in previous transcriptome studies and generate a prediction model to be evaluated in future studies. Further research is necessary to evaluate these expression patterns in a prospective manner.

'Why would we not want to keep everybody safe?' The views of family members of people who use drugs on the implementation of drug consumption rooms in Scotland.

BACKGROUND: People who use drugs in Scotland are currently experiencing disproportionately high rates of drug-related deaths. Drug consumption rooms (DCRs) are harm reduction services that offer a safe, hygienic environment where pre-obtained drugs can be consumed under supervision. The aim of this research was to explore family member perspectives on DCR implementation in Scotland in order to inform national policy. METHODS: Scotland-based family members of people who were currently or formerly using drugs were invited to take part in semi-structured interviews to share views on DCRs. An inclusive approach to 'family' was taken, and family members were recruited via local and national networks. A convenience sample of 13 family members were recruited and interviews conducted, audio-recorded, transcribed, and analysed thematically using the Structured Framework Technique. RESULTS: Family members demonstrated varying levels of understanding regarding the existence, role, and function of DCRs. While some expressed concern that DCRs would not prevent continued drug use, all participants were in favour of DCR implementation due to a belief that DCRs could reduce harm, including saving lives, and facilitate future recovery from drug use. Participants highlighted challenges faced by people who use drugs in accessing treatment/services that could meet their needs. They identified that accessible and welcoming DCRs led by trusting and non-judgemental staff could help to meet unmet needs, including signposting to other services. Family members viewed DCRs as safe environments and highlighted how the existence of DCRs could reduce the constant worry that they had of risk of harm to their loved ones. Finally, family members emphasised the challenge of stigma associated with drug use. They believed that introduction of DCRs would help to reduce stigma and provide a signal that people who use drugs deserve safety and care. CONCLUSIONS: Reporting the experience and views of family members makes a novel and valuable contribution to ongoing public debates surrounding DCRs. Their views can be used to inform the implementation of DCRs in Scotland but also relate well to the development of wider responses to drug-related harm and reduction of stigma experienced by people who use drugs in Scotland and beyond.

Toward a more holistic method of genome assembly assessment.

BACKGROUND: A key use of high throughput sequencing technology is the sequencing and assembly of full genome sequences. These genome assemblies are commonly assessed using statistics relating to contiguity of the assembly. Measures of contiguity are not strongly correlated with information about the biological completion or correctness of the assembly, and a commonly reported metric, N50, can be misleading. Over the years, multiple research groups have rejected the overuse of N50 and sought to develop more informative metrics. RESULTS: This paper presents a review of problems that arise from relying solely on contiguity as a measure of genome assembly quality as well as current alternative methods. Alternative methods are compared on the basis of how informative they are about the biological quality of the assembly and how easy they are to use. A comprehensive method for using multiple metrics of measuring assembly quality is presented. CONCLUSIONS: This study aims to report on the status of assembly assessment methods and compare them, as well as to offer a comprehensive method that incorporates multiple facets of quality assessment. Weaknesses and strengths of varying methods are presented and explained, with recommendations based on speed of analysis and user friendliness.

Transcribed microsatellite allele lengths are often correlated with gene expression in natural sunflower populations.

Microsatellites are common in genomes of most eukaryotic species. Due to their high mutability, an adaptive role for microsatellites has been considered. However, little is known concerning the contribution of microsatellites towards phenotypic variation. We used populations of the common sunflower (Helianthus annuus) at two latitudes to quantify the effect of microsatellite allele length on phenotype at the level of gene expression. We conducted a common garden experiment with seed collected from sunflower populations in Kansas and Oklahoma followed by an RNA-Seq experiment on 95 individuals. The effect of microsatellite allele length on gene expression was assessed across 3,325 microsatellites that could be consistently scored. Our study revealed 479 microsatellites at which allele length significantly correlates with gene expression (eSTRs). When irregular allele sizes not conforming to the motif length were removed, the number of eSTRs rose to 2,379. The percentage of variation in gene expression explained by eSTRs ranged from 1%-86% when controlling for population and allele-by-population interaction effects at the 479 eSTRs. Of these eSTRs, 70.4% are in untranslated regions (UTRs). A gene ontology (GO) analysis revealed that eSTRs are significantly enriched for GO terms associated with cis- and trans-regulatory processes. Our findings suggest that a substantial number of transcribed microsatellites can influence gene expression.

Transcriptome profiles of sunflower reveal the potential role of microsatellites in gene expression divergence.

The mechanisms by which natural populations generate adaptive genetic variation are not well understood. Some studies propose that microsatellites can function as drivers of adaptive variation. Here, we tested a potentially adaptive role for transcribed microsatellites with natural populations of the common sunflower (Helianthus annuus L.) by assessing the enrichment of microsatellites in genes that show expression divergence across latitudes. Seeds collected from six populations at two distinct latitudes in Kansas and Oklahoma were planted and grown in a common garden. Morphological measurements from the common garden demonstrated that phenotypic variation among populations is largely explained by underlying genetic variation. An RNA-Seq experiment was conducted with 96 of the individuals grown in the common garden and differentially expressed (DE) transcripts between the two latitudes were identified. A total number of 825 DE transcripts were identified. DE transcripts and nondifferentially expressed (NDE) transcripts were then scanned for microsatellites. The abundance of different motif lengths and types in both groups were estimated. Our results indicate that DE transcripts are significantly enriched with mononucleotide repeats and significantly depauperate in trinucleotide repeats. Further, the standardized mononucleotide repeat motif A and dinucleotide repeat motif AG were significantly enriched within DE transcripts while motif types, C, AT, ACC and AAC in DE transcripts, are significantly differentiated in microsatellite tract length between the two latitudes. The tract length differentiation at specific microsatellite motif types across latitudes and their enrichment within DE transcripts indicate a potential functional role for transcribed microsatellites in gene expression divergence in sunflower.

Testis specific histone 2B is associated with sperm chromatin dynamics and bull fertility-a pilot study.

BACKGROUND: Bull fertility is the degree of sperm's ability to fertilize and activate the egg and support embryo development, and this is critical for herd reproductive performance. We used the bull as a unique model organism for the study of male fertility because cattle genetics and physiology is similar to those of other mammals including humans. Moreover, reliable fertility data along with well-established in vitro systems are available for bovine. The objective of this original study was to ascertain evolutionary diversification and expression dynamics of Testis Specific Histone 2B (TH2B) in sperm from Holstein bulls with different fertility scores. METHODS: The intensity of TH2B was determined by using flow cytometry in sperm from 13 high and 13 low fertility bulls. Expression levels of TH2B were measured using immunofluorescence and Western blotting in sperm from five high and five low fertility bulls. Sequence identity, evolutionary distance and interactome of TH2B were evaluated by dotmatcher, STRING and Cytoscape. Data were analyzed using linear mixed effects model and regression plots were drawn. RESULTS: The intensity of TH2B as measured by flow cytometry was significantly affected by an interaction between fertility group and fertility score (P = 0.0182). The intensity of TH2B in sperm from the high fertility group decreased (P = 0.0055) as fertility increased. TH2B was constantly detectable in sperm and expression levels of TH2B decreased in relation to fertility in sperm from the high fertility group (P = 0.018). TH2B biological functions include male gamete generation, chromosome organization, DNA packaging, DNA conformation change, chromatin organization, nucleosome organization, chromatin disassembly, spermatid nucleus elongation, spermatid nucleus differentiation, sperm motility, chromatin organization, chromatin condensation, chromatin silencing, nucleus organization, and chromatin remodeling (P < 0.05). CONCLUSIONS: We elucidated the cellular localization and molecular physiology of TH2B using both computational and cell biology approaches. In addition to advancing the fundamental science of mammalian male gamete, the present findings can be potentially used to evaluate semen quality and predict male fertility in the future. TRIAL REGISTRATION: This study did not involve any live animals. We did not perform any anesthesia, euthanasia, or any kind of animal sacrifice. The cryopreserved semen samples were obtained from Alta Genetics, Inc., Watertown, WI, USA. All samples were preserved in liquid nitrogen.

Using genome-wide associations to identify metabolic pathways involved in maize aflatoxin accumulation resistance.

BACKGROUND: Aflatoxin is a potent carcinogen that can contaminate grain infected with the fungus Aspergillus flavus. However, resistance to aflatoxin accumulation in maize is a complex trait with low heritability. Here, two complementary analyses were performed to better understand the mechanisms involved. The first coupled results of a genome-wide association study (GWAS) that accounted for linkage disequilibrium among single nucleotide polymorphisms (SNPs) with gene-set enrichment for a pathway-based approach. The rationale was that the cumulative effects of genes in a pathway would give insight into genetic differences that distinguish resistant from susceptible lines of maize. The second involved finding non-pathway genes close to the most significant SNP-trait associations with the greatest effect on reducing aflatoxin in multiple environments. Unlike conventional GWAS, the latter analysis emphasized multiple aspects of SNP-trait associations rather than just significance and was performed because of the high genotype x environment variability exhibited by this trait. RESULTS: The most significant metabolic pathway identified was jasmonic acid (JA) biosynthesis. Specifically, there was at least one allelic variant for each step in the JA biosynthesis pathway that conferred an incremental decrease to the level of aflatoxin observed among the inbred lines in the GWAS panel. Several non-pathway genes were also consistently associated with lowered aflatoxin levels. Those with predicted functions related to defense were: leucine-rich repeat protein kinase, expansin B3, reversion-to-ethylene sensitivity1, adaptor protein complex2, and a multidrug and toxic compound extrusion protein. CONCLUSIONS: Our genetic analysis provided strong evidence for several genes that were associated with aflatoxin resistance. Inbred lines that exhibited lower levels of aflatoxin accumulation tended to share similar haplotypes for genes specifically in the pathway of JA biosynthesis, along with several non-pathway genes with putative defense-related functions. Knowledge gained from these two complementary analyses has improved our understanding of population differences in aflatoxin resistance.

Sperm superoxide dismutase is associated with bull fertility.

Decreasing mammalian fertility and sperm quality have created an urgent need to find effective methods to distinguish non-viable from viable fertilising spermatozoa. The aims of the present study were to evaluate expression levels of ?-tubulin 2C (TUBB2C), heat shock protein 10 (HSP10), hexokinase 1 (HXK1) and superoxide dismutase 1 (SOD1) in spermatozoa from Holstein bulls with varying fertility using western blotting and to analyse the biological networks of these key sperm proteins using a bioinformatics software (Metacore; Thomson-Reuters, Philadelphia, PA, USA). The rationales behind this study were that the sperm proteins play crucial roles in fertilisation and early embryonic development in mammals and ascertaining the biological networks of the proteins helps us better understand sperm physiology and early mammalian development. The results showed that expression of SOD1 was higher in spermatozoa from high fertility bulls (PPin vivo bull fertility. The findings are important because they illuminate molecular and cellular determinants of sperm viability and the identified protein markers can be used to determine bull fertility.

Assessing the early influence of COVID-19 in an analysis of the immediate implementation of Minimum Pricing for Alcohol on drinkers in Wales.

Background: The Welsh Government has commissioned a number of projects to consider the influence their implementation of Minimum Pricing for Alcohol (MPA) legislation in March 2020 had on the alcohol consumption and related behaviours of drinkers. Given the MPA's overlap with the COVID-19 pandemic and its related lockdown measures and restrictions, this rapidly became a story about the early impact of COVID-19 as it did MPA. This paper captures the core thematic messages from this specific strand of work, and in doing so reflects on (1) how early experiences of COVID-19 and the first lockdown influenced consumption and purchasing of alcohol behaviours and, in turn, (2) how relevant the introduction of MPA was for any of these. Methods: Semi-structured interviews were conducted by telephone with 32 drinkers 9 months after the implementation of the legislation in March 2020. The sample was recruited from three sources: the National Survey for Wales; a third sector organisation offering housing support to the homeless; and through an online survey on MPA. Results: COVID-19 had more relevance than MPA to drinkers. Furthermore, when MPA did have an influence on their behaviour, it was felt most keenly by the harmful drinkers in the study. These drinkers described spending more on alcohol, switching to other potentially more harmful substances, such as crack cocaine and synthetic cannabinoids, and more involvement in acquisitive crime and begging after the price increase. While our results might be an early indication of the influence of MPA on harmful drinkers, the small sample of this group in our study limits the generalisability of the findings. Conclusion: To date, the implementation of MPA has had little influence on the drinking patterns or lives of the drinkers in our sample. It is important that future research examines the longer-term influences of MPA before any conclusions on its effectiveness can be drawn.

Proceedings of the 2013 MidSouth Computational Biology and Bioinformatics Society (MCBIOS) Conference.

The tenth annual conference of the MidSouth Computational Biology and Bioinformatics Society (MCBIOS 2013), "The 10th Anniversary in a Decade of Change: Discovery in a Sea of Data", took place at the Stoney Creek Inn & Conference Center in Columbia, Missouri on April 5-6, 2013. This year's Conference Chairs were Gordon Springer and Chi-Ren Shyu from the University of Missouri and Edward Perkins from the US Army Corps of Engineers Engineering Research and Development Center, who is also the current MCBIOS President (2012-3). There were 151 registrants and a total of 111 abstracts (51 oral presentations and 60 poster session abstracts).

Gene expression analysis of copper tolerance and wood decay in the brown rot fungus Fibroporia radiculosa.

High-throughput transcriptomics was used to identify Fibroporia radiculosa genes that were differentially regulated during colonization of wood treated with a copper-based preservative. The transcriptome was profiled at two time points while the fungus was growing on wood treated with micronized copper quat (MCQ). A total of 917 transcripts were differentially expressed. Fifty-eight of these genes were more highly expressed when the MCQ was protecting the wood from strength loss and had putative functions related to oxalate production/degradation, laccase activity, quinone biosynthesis, pectin degradation, ATP production, cytochrome P450 activity, signal transduction, and transcriptional regulation. Sixty-one genes were more highly expressed when the MCQ lost its effectiveness (>50% strength loss) and had functions related to oxalate degradation; cytochrome P450 activity; H(2)O(2) production and degradation; degradation of cellulose, hemicellulose, and pectin; hexose transport; membrane glycerophospholipid metabolism; and cell wall chemistry. Ten of these differentially regulated genes were quantified by reverse transcriptase PCR for a more in-depth study (4 time points on wood with or without MCQ treatment). Our results showed that MCQ induced higher than normal levels of expression for four genes (putative annotations for isocitrate lyase, glyoxylate dehydrogenase, laccase, and oxalate decarboxylase 1), while four other genes (putative annotations for oxalate decarboxylase 2, aryl alcohol oxidase, glycoside hydrolase 5, and glycoside hydrolase 10) were repressed. The significance of these results is that we have identified several genes that appear to be coregulated, with putative functions related to copper tolerance and/or wood decay.

Views on minimum unit pricing for alcohol before its introduction among people with alcohol dependence in Scotland: A qualitative interview study.

INTRODUCTION: Scotland implemented a minimum price per unit of alcohol (MUP) of £0.50 in May 2018 (1 UK unit = 10 mL/8 g ethanol). Some stakeholders expressed concerns about the policy having potential negative consequences for people with alcohol dependence. This study aimed to investigate anticipated impacts of MUP on people presenting to alcohol treatment services in Scotland before policy implementation. METHODS: Qualitative interviews were conducted with 21 people with alcohol dependence accessing alcohol treatment services in Scotland between November 2017 and April 2018. Interviews examined respondents' current and anticipated patterns of drinking and spending, effects on their personal life, and their views on potential policy impact. Interview data were thematically analysed using a constant comparison method. RESULTS: Three key themes were identified: (i) strategies used to manage the cost of alcohol and anticipated responses to MUP; (ii) broader effects of MUP; and (iii) awareness and preparedness for MUP. Respondents expected to be impacted by MUP, particularly those on low incomes and those with more severe dependence symptoms. They anticipated using familiar strategies including borrowing and reprioritising spending to keep alcohol affordable. Some respondents anticipated negative consequences. Respondents were sceptical about the short-term benefits of MUP for current drinkers but felt it might prevent harm for future generations. Respondents had concerns about the capacity of treatment services to meet support needs. DISCUSSION AND CONCLUSIONS: People with alcohol dependence identified immediate concerns alongside potential long-term benefits of MUP before its introduction. They also had concerns over the preparedness of service providers.

A systematic comparison of genome-scale clustering algorithms.

BACKGROUND: A wealth of clustering algorithms has been applied to gene co-expression experiments. These algorithms cover a broad range of approaches, from conventional techniques such as k-means and hierarchical clustering, to graphical approaches such as k-clique communities, weighted gene co-expression networks (WGCNA) and paraclique. Comparison of these methods to evaluate their relative effectiveness provides guidance to algorithm selection, development and implementation. Most prior work on comparative clustering evaluation has focused on parametric methods. Graph theoretical methods are recent additions to the tool set for the global analysis and decomposition of microarray co-expression matrices that have not generally been included in earlier methodological comparisons. In the present study, a variety of parametric and graph theoretical clustering algorithms are compared using well-characterized transcriptomic data at a genome scale from Saccharomyces cerevisiae. METHODS: For each clustering method under study, a variety of parameters were tested. Jaccard similarity was used to measure each cluster's agreement with every GO and KEGG annotation set, and the highest Jaccard score was assigned to the cluster. Clusters were grouped into small, medium, and large bins, and the Jaccard score of the top five scoring clusters in each bin were averaged and reported as the best average top 5 (BAT5) score for the particular method. RESULTS: Clusters produced by each method were evaluated based upon the positive match to known pathways. This produces a readily interpretable ranking of the relative effectiveness of clustering on the genes. Methods were also tested to determine whether they were able to identify clusters consistent with those identified by other clustering methods. CONCLUSIONS: Validation of clusters against known gene classifications demonstrate that for this data, graph-based techniques outperform conventional clustering approaches, suggesting that further development and application of combinatorial strategies is warranted.

Short-read sequencing for genomic analysis of the brown rot fungus Fibroporia radiculosa.

The feasibility of short-read sequencing for genomic analysis was demonstrated for Fibroporia radiculosa, a copper-tolerant fungus that causes brown rot decay of wood. The effect of read quality on genomic assembly was assessed by filtering Illumina GAIIx reads from a single run of a paired-end library (75-nucleotide read length and 300-bp fragment size) at three different stringency levels and then assembling each data set with Velvet. A simple approach was devised to determine which filter stringency was "best." Venn diagrams identified the regions containing reads that were used in an assembly but were of a low-enough quality to be removed by a filter. By plotting base quality histograms of reads in this region, we judged whether a filter was too stringent or not stringent enough. Our best assembly had a genome size of 33.6 Mb, an N50 of 65.8 kb for a k-mer of 51, and a maximum contig length of 347 kb. Using GeneMark, 9,262 genes were predicted. TargetP and SignalP analyses showed that among the 1,213 genes with secreted products, 986 had motifs for signal peptides and 227 had motifs for signal anchors. Blast2GO analysis provided functional annotation for 5,407 genes. We identified 29 genes with putative roles in copper tolerance and 73 genes for lignocellulose degradation. A search for homologs of these 102 genes showed that F. radiculosa exhibited more similarity to Postia placenta than Serpula lacrymans. Notable differences were found, however, and their involvements in copper tolerance and wood decay are discussed.

Dynamics of microRNAs in bull spermatozoa.

BACKGROUND: MicroRNAs are small non-coding RNAs that regulate gene expression and thus play important roles in mammalian development. However, the comprehensive lists of microRNAs, as well as, molecular mechanisms by which microRNAs regulate gene expression during gamete and embryo development are poorly defined. The objectives of this study were to determine microRNAs in bull sperm and predict their functions. METHODS: To accomplish our objectives we isolated miRNAs from sperm of high and low fertility bulls, conducted microRNA microarray experiments and validated expression of a panel of microRNAs using real time RT-PCR. Bioinformatic approaches were carried out to identify regulated targets. RESULTS: We demonstrated that an abundance of microRNAs were present in bovine spermatozoa, however, only seven were differentially expressed; hsa-aga-3155, -8197, -6727, -11796, -14189, -6125, -13659. The abundance of miRNAs in the spermatozoa and the differential expression in sperm from high vs. low fertility bulls suggests that the miRNAs possibly play important functions in the regulating mechanisms of bovine spermatozoa. CONCLUSION: Identification of specific microRNAs expressed in spermatozoa of bulls with different fertility phenotypes will help better understand mammalian gametogenesis and early development.

Clustering of High Throughput Gene Expression Data.

High throughput biological data need to be processed, analyzed, and interpreted to address problems in life sciences. Bioinformatics, computational biology, and systems biology deal with biological problems using computational methods. Clustering is one of the methods used to gain insight into biological processes, particularly at the genomics level. Clearly, clustering can be used in many areas of biological data analysis. However, this paper presents a review of the current clustering algorithms designed especially for analyzing gene expression data. It is also intended to introduce one of the main problems in bioinformatics - clustering gene expression data - to the operations research community.

No-boundary thinking: a viable solution to ethical data-driven AI in precision medicine.

Today Artificial Intelligence (AI) supports difficult decisions about policy, health, and our personal lives. The AI algorithms we develop and deploy to make sense of information, are informed by data, and based on models that capture and use pertinent details of the population or phenomenon being analyzed. For any application area, more importantly in precision medicine which directly impacts human lives, the data upon which algorithms are run must be procured, cleaned, and organized well to assure reliable and interpretable results, and to assure that they do not perpetrate or amplify human prejudices. This must be done without violating basic assumptions of the algorithms in use. Algorithmic results need to be clearly communicated to stakeholders and domain experts to enable sound conclusions. Our position is that AI holds great promise for supporting precision medicine, but we need to move forward with great care, with consideration for possible ethical implications. We make the case that a no-boundary or convergent approach is essential to support sound and ethical decisions. No-boundary thinking supports problem definition and solving with teams of experts possessing diverse perspectives. When dealing with AI and the data needed to use AI, there is a spectrum of activities that needs the attention of a no-boundary team. This is necessary if we are to draw viable conclusions and develop actions and policies based on the AI, the data, and the scientific foundations of the domain in question.

Hematological and gene co-expression network analyses of high-risk beef cattle defines immunological mechanisms and biological complexes involved in bovine respiratory disease and weight gain.

Bovine respiratory disease (BRD), the leading disease complex in beef cattle production systems, remains highly elusive regarding diagnostics and disease prediction. Previous research has employed cellular and molecular techniques to describe hematological and gene expression variation that coincides with BRD development. Here, we utilized weighted gene co-expression network analysis (WGCNA) to leverage total gene expression patterns from cattle at arrival and generate hematological and clinical trait associations to describe mechanisms that may predict BRD development. Gene expression counts of previously published RNA-Seq data from 23 cattle (2017; n = 11 Healthy, n = 12 BRD) were used to construct gene co-expression modules and correlation patterns with complete blood count (CBC) and clinical datasets. Modules were further evaluated for cross-populational preservation of expression with RNA-Seq data from 24 cattle in an independent population (2019; n = 12 Healthy, n = 12 BRD). Genes within well-preserved modules were subject to functional enrichment analysis for significant Gene Ontology terms and pathways. Genes which possessed high module membership and association with BRD development, regardless of module preservation ("hub genes"), were utilized for protein-protein physical interaction network and clustering analyses. Five well-preserved modules of co-expressed genes were identified. One module ("steelblue"), involved in alpha-beta T-cell complexes and Th2-type immunity, possessed significant correlation with increased erythrocytes, platelets, and BRD development. One module ("purple"), involved in mitochondrial metabolism and rRNA maturation, possessed significant correlation with increased eosinophils, fecal egg count per gram, and weight gain over time. Fifty-two interacting hub genes, stratified into 11 clusters, may possess transient function involved in BRD development not previously described in literature. This study identifies co-expressed genes and coordinated mechanisms associated with BRD, which necessitates further investigation in BRD-prediction research.

Drug Consumption Rooms and Public Health Policy: Perspectives of Scottish Strategic Decision-Makers.

There is widespread support for the introduction of Drug Consumption Rooms (DCRs) in Scotland as part of a policy response to record levels of drug-related harm. However, existing legal barriers are made more complex by the division of relevant powers between the UK and Scottish Governments. This paper reports on a national, qualitative study of key decision-makers in both local and national roles across Scotland. It explores views on the political barriers and enablers to the adoption of Drug Consumption Rooms and the potential role of these facilities in the wider treatment system. It also considers approaches to evidence, especially the types of evidence that are considered valuable in supporting decision-making in this area. The study found that Scottish decision-makers are strongly supportive of DCR adoption; however, they remain unclear as to the legal and political mechanisms that would make this possible. They view DCRs as part of a complex treatment and support system rather than a uniquely transformative intervention. They see the case for introduction as sufficient, on the basis of need and available evidence, thus adopting a pragmatic and iterative approach to evidence, in contrast to an appeal to traditional evidence hierarchies more commonly adopted by the UK Government.

Genes and regulatory mechanisms associated with experimentally-induced bovine respiratory disease identified using supervised machine learning methodology.

Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental factors. Advancements in RNA sequencing and associated analytical methods are improving our understanding of host response related to BRD pathophysiology. Supervised machine learning (ML) approaches present one such method for analyzing new and previously published transcriptome data to identify novel disease-associated genes and mechanisms. Our objective was to apply ML models to lung and immunological tissue datasets acquired from previous clinical BRD experiments to identify genes that classify disease with high accuracy. Raw mRNA sequencing reads from 151 bovine datasets (n = 123 BRD, n = 28 control) were downloaded from NCBI-GEO. Quality filtered reads were assembled in a HISAT2/Stringtie2 pipeline. Raw gene counts for ML analysis were normalized, transformed, and analyzed with MLSeq, utilizing six ML models. Cross-validation parameters (fivefold, repeated 10 times) were applied to 70% of the compiled datasets for ML model training and parameter tuning; optimized ML models were tested with the remaining 30%. Downstream analysis of significant genes identified by the top ML models, based on classification accuracy for each etiological association, was performed within WebGestalt and Reactome (FDR ≤ 0.05). Nearest shrunken centroid and Poisson linear discriminant analysis with power transformation models identified 154 and 195 significant genes for IBR and BRSV, respectively; from these genes, the two ML models discriminated IBR and BRSV with 100% accuracy compared to sham controls. Significant genes classified by the top ML models in IBR (154) and BRSV (195), but not BVDV (74), were related to type I interferon production and IL-8 secretion, specifically in lymphoid tissue and not homogenized lung tissue. Genes identified in Mannheimia haemolytica infections (97) were involved in activating classical and alternative pathways of complement. Novel findings, including expression of genes related to reduced mitochondrial oxygenation and ATP synthesis in consolidated lung tissue, were discovered. Genes identified in each analysis represent distinct genomic events relevant to understanding and predicting clinical BRD. Our analysis demonstrates the utility of ML with published datasets for discovering functional information to support the prediction and understanding of clinical BRD.