Computational selection and prioritization of candidate genes for Fetal Alcohol Syndrome

<p>Abstract</p> <p>Background</p> <p>Fetal alcohol syndrome (FAS) is a serious global health problem and is observed at high frequencies in certain South African communities. Although <it>in utero </it>alcohol exposure is the primary trigger, there is evidence for genetic- and other susceptibility factors in FAS development. No genome-wide association or linkage studies have been performed for FAS, making computational selection and -prioritization of candidate disease genes an attractive approach.</p> <p>Results</p> <p>10174 Candidate genes were initially selected from the whole genome using a previously described method, which selects candidate genes according to their expression in disease-affected tissues. Hereafter candidates were prioritized for experimental investigation by investigating criteria pertinent to FAS and binary filtering. 29 Criteria were assessed by mining various database sources to populate criteria-specific gene lists. Candidate genes were then prioritized for experimental investigation using a binary system that assessed the criteria gene lists against the candidate list, and candidate genes were scored accordingly. A group of 87 genes was prioritized as candidates and for future experimental validation. The validity of the binary prioritization method was assessed by investigating the protein-protein interactions, functional enrichment and common promoter element binding sites of the top-ranked genes.</p> <p>Conclusion</p> <p>This analysis highlighted a list of strong candidate genes from the TGF-β, MAPK and Hedgehog signalling pathways, which are all integral to fetal development and potential targets for alcohol's teratogenic effect. We conclude that this novel bioinformatics approach effectively prioritizes credible candidate genes for further experimental analysis.</p

The glial growth factors deficiency and synaptic destabilization hypothesis of schizophrenia

BACKGROUND: A systems approach to understanding the etiology of schizophrenia requires a theory which is able to integrate genetic as well as neurodevelopmental factors. PRESENTATION OF THE HYPOTHESIS: Based on a co-localization of loci approach and a large amount of circumstantial evidence, we here propose that a functional deficiency of glial growth factors and of growth factors produced by glial cells are among the distal causes in the genotype-to-phenotype chain leading to the development of schizophrenia. These factors include neuregulin, insulin-like growth factor I, insulin, epidermal growth factor, neurotrophic growth factors, erbB receptors, phosphatidylinositol-3 kinase, growth arrest specific genes, neuritin, tumor necrosis factor alpha, glutamate, NMDA and cholinergic receptors. A genetically and epigenetically determined low baseline of glial growth factor signaling and synaptic strength is expected to increase the vulnerability for additional reductions (e.g., by viruses such as HHV-6 and JC virus infecting glial cells). This should lead to a weakening of the positive feedback loop between the presynaptic neuron and its targets, and below a certain threshold to synaptic destabilization and schizophrenia. TESTING THE HYPOTHESIS: Supported by informed conjectures and empirical facts, the hypothesis makes an attractive case for a large number of further investigations. IMPLICATIONS OF THE HYPOTHESIS: The hypothesis suggests glial cells as the locus of the genes-environment interactions in schizophrenia, with glial asthenia as an important factor for the genetic liability to the disorder, and an increase of prolactin and/or insulin as possible working mechanisms of traditional and atypical neuroleptic treatments

Pathway curator: an online webserver extracting genes and interactions from figures

In the biomedical literature, gene pathways are frequently included. Many high-quality gene pathways are illustrated in the form of visuals and text, making them valuable study tools for biological processes and precision medicine. Pathway maps and literature texts provide researchers with access to a huge number of new biological treatments. For general usage, these pathway maps should be logically ordered, coordinated, and converted into a computer-readable format. Currently, keeping up with the rapid increase of the literature requires laborious extraction of information from a publication at a time. A gene pathway map recognition system is devised and implemented in this study. Based on the pathway map and relevant information supplied by users, the system extracts gene identity and gene interaction information, and the automated extraction from pathway maps is efficient. Furthermore, the tool offers users with a full view of a certain illness's pathway, which is useful for researchers and can speed up the research process in a variety of biomedical applications. This thesis first explains the project's goal and provides the background information. The project's design ideas are then presented, as well as an analysis of the system and introductions to related platforms. After that, the system's implementations are described one by one, together with the deployment and testing processes. Finally, potential improvements and future work are discussed.Includes bibliographical references

Bibliometrics Methods in Detecting Citations to Questionable Journals

In recent times, there has been a proliferation of questionable practices in research publishing, for example, via predatory journals, hijacked journals, plagiarism, tortured phrases and paper mills. This paper intends to analyse whether journals that had been removed from the Directory of Open Access Journals (DOAJ) in 2018 due to suspected misconduct were cited within journals indexed in the Scopus database. Our analysis showed that Scopus contained over 15 thousand references to the removed journals identified. The majority of the publications citing these journals came from the area of Engineering. It is important to note that although we cannot assume that all the journals removed followed unethical practices, it is still essential that researchers are aware of the issues around citing journals that have been suspected of misconduct. We suggest that research libraries play a crucial role in training, advising and providing information to researchers about these ethical issues of publication malpractice and misconduct

Augmenting biological pathway extraction with synthetic data and active learning

The corpus of biomedical literature is growing rapidly as many papers are recorded in PubMed every day. These papers often contain high-quality biological pathways in their figures/text, which are great resources for studying biological mechanisms and precision medicine. However, it can take a long time for many of these works to be put into practical use as each paper's contributions need to be curated by experts. This, often lengthy, process causes professional practice to lag behind research. To speed up this process, I helped develop a pipeline that integrates NLP and object detection processing to extract gene relationships reported in articles' figures and text. This pipeline was able to extract such relationships with high precision and recall on a small, annotated set. However, extending this pipeline for improved generalization and new settings was limited by the number of high-quality annotations available. Such labeled data is very time consuming to collect and traditional augmentations were observed to generate diminishing returns. To address this shortcoming, I developed an approach for generating purely synthetic data for object detection on biological pathway diagrams based on a set of rules and domain knowledge. Our method iteratively generates each pathway relationship uniquely and is demonstrated to improve the generalization of our object detection model significantly across a variety of settings. Additionally, with the capability to generate unique and informative samples, we integrated our synthetic generation methodology into an active learning setting. While traditional active learning relies on a pool of unlabeled data to draw from with an acquisition function, our method is pool-less and does not require any acquisition function. Instead, we generate each batch of data uniquely based on the training losses from the previous batch. Pool-less Active Learning (PAL) via synthetic data generation is demonstrated to reduce the number of iterations required for model convergence during training on pathway figures.Includes bibliographical references

General resources in Genetics and/or Oncology

Review on General resources in Genetics and/or Oncolog

The Structure of Knowledge Diffusion in Sciences and Consequences

The enterprise of modern science evolves alongside its underlying structure, encompassing interactions among scientists, institutions, and culture, as well as the development of scientific ideas and discoveries. The increasing availability of digitized scholarly data, coupled with enhanced computational power, offers unprecedented opportunities to characterize, critically examine, and untangle how these complex, intertwined entities shape the inner workings of science. Through three empirical studies, this dissertation investigates how underlying social and infrastructural elements can influence the production, diffusion, and consumption of scientific ideas and discoveries. The introduction outlines the three studies. The first chapter tackles the question of how tacitly encoded configurations and undocumented components can influence the estimates from randomized clinical trials, demonstrating the role of socio-epistemic bubbles in the production of scientific medical knowledge. The results suggest why meta-analyses may not mechanically resolve scientific disagreements and disputes, contrary to widespread expectations. The second chapter extends the analogy of bubbles to the realm of attention in biomedical scientific knowledge, reflecting the phenomenon of bubbles and collapses in financial asset markets. It reveals that restricted diffusion within social and scientific 'bubbles' can precede sudden collapses in scientific attention, offering a straightforward framework for identifying early signs of these bubbles in science. The third study explores how the presence of code repositories alongside machine learning research affects the citation rates of papers. It finds that the popularity of ML frameworks, such as PyTorch and TensorFlow, used in these repositories can have second-order network effects, underscoring the latent role of technological artifacts and infrastructure in scientific dissemination. The final chapter concludes the dissertation with reflections and outlines future research directions

The Sonic hedgehog and Wnt signalling pathways in interstitial lung disease and CD4⁺T cell activation

The Sonic Hedgehog (Shh) signalling pathway plays an important role in lung development where it promotes branching morphogenesis through epithelialmesenchymal interactions. Increased Shh expression promotes epithelial and mesenchymal proliferation in vitro and in vivo. TGFß is also expressed in embryonic lung where it acts to inhibit branching morphogenesis. TGFß overexpression results in lung hypoplasia, a similar phenotype to that seen in Shh⁻/⁻ mutants; suggesting that Shh and TGFß have opposing roles. Evidence to date would suggest that although TGFß and Shh may not directly interact in lung development, they probably have common targets and may function in a shared regulatory circuit.Interstitial lung disease (ILD) is the end result of a multiplicity of pathological processes. It has been recently proposed that the commonest form, Idiopathic Pulmonary Fibrosis (IPF) or Usual Interstitial Pneumonia (UIP), is due to abnormal wound healing in the lung, characterized by epithelial-fibroblast interactions; a process similar to foetal lung branching and epithelialization. TGFß has been strongly linked with ELD in both animal models and human disease. Based on the link between TGFß and Shh in lung morphogenesis, the initial aim of this thesis was to determine whether or not Shh signalling was upregulated in ILD. The work presented confirms that Shh and TGFß expression are increased in the airway epithelium of fibrotic but not non-fibrotic lung both in the murine FITC model of ILD and in biopsy sections from patients with IPF. Expression of Patched (Ptc), the Shh receptor, is unchanged in epithelial cells. Notably, Ptc is present both in alveolar macrophages and lymphocytic infiltrates. However, there is no discernible difference in the fibrotic response in the lungs of mice containing heterozygous mutations of Gli2 and 3, used as models of dysregulated Shh signalling, nor in mice treated with intra-tracheal SPC-Shh cDNA.The Shh pathway has recently been shown to play a role in thymocyte development. The findings presented demonstrate that both Shh and Ptc are expressed in human T cells. In addition, upregulation of Shh signalling enhances and blocking of endogenous Shh inhibits T cell receptor mediated T cell activation, respectively, as determined by proliferation, cytokine production and CD25 and CD69 expressionWnt signalling is also thought to play a role in lung branching morphogenesis. It is known to interact both with Shh signalling and TGFß. However, using presently available antibodies, there is no evidence of upregulation of Wnt signalling in ILD. In an attempt to drive the Wnt Pathway, a replication-deficient adenovirus expressing Dvll (Ad5-MCMV-Dvll) was successfully rescued. Although the virus drives Dvll mRNA and protein expression in vitro and in vivo, it does not consistently mimic Wnt signalling, nor does it appear to affect Shh or TGFß signalling. Furthermore such Dvll overexpression has little effect on cell proliferation either in vitro or in vivo, and does not cause lung fibrosis in mice.Thus Shh signalling appears to be upregulated in fibrotic lung in mice and humans. However the work presented does not define whether or not the pathway plays a specific role in the pathogenesis of ILD. There is also no evidence relating Wnt signalling or Dvll upregulation to ILD. Finally, Shh is shown to influence TCR mediated signalling and clonal expansion. It may be that damaged epithelial cells and the immune system communicate via this pathway