Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Abstract Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome‐scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF‐target gene modules associated with age‐ and CAG repeat length‐dependent gene expression changes in Htt CAG knock‐in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF‐target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD‐related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP‐seq) of mouse striatum. We found CAG repeat length‐dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Periodontal vaccine: A dream or reality

Recent advances in cellular and molecular biology have led to the development of new strategies for vaccines against many types of infectious diseases. It has long been recognized that individuals who recovered from a disease developed subsequent resistance to the same. In the late 18th century, Edward Jenner developed and established the principle of vaccination using the cross protection conferred by cowpox virus, which is non-pathogenic in humans. With the rapid growth of microbial genome sequencing and bioinformatics analysis tools we have the potential to examine all the genes and proteins from any human pathogen. This technique has the capability to provide us with new targets for anti-microbial drugs and vaccines. However, to realize this potential new bioinformatics and experimental approaches to select these targets from the myriad of available candidates are required. Vaccination is a process that induces specific immune resistance to a bacterial or viral infection

Gene therapy and its implications in Periodontics

Gene therapy is a field of Biomedicine. With the advent of gene therapy in dentistry, significant progress has been made in the control of periodontal diseases and reconstruction of dento-alveolar apparatus. Implementation in periodontics include: -As a mode of tissue engineering with three approaches: cell, protein-based and gene delivery approach. -Genetic approach to Biofilm Antibiotic Resistance. Future strategies of gene therapy in preventing periodontal diseases: -Enhances host defense mechanism against infection by transfecting host cells with an antimicrobial peptide protein-encoding gene. -Periodontal vaccination. Gene therapy is one of the recent entrants and its applications in the field of periodontics are reviewed in general here