A literature search tool for intelligent extraction of disease-associated genes

Objective: To extract disorder-associated genes from the scientific literature in PubMed with greater sensitivity for literature-based support than existing methods. Methods: We developed a PubMed query to retrieve disorder-related, original research articles. Then we applied a rule-based text-mining algorithm with keyword matching to extract target disorders, genes with significant results, and the type of study described by the article. Results: We compared our resulting candidate disorder genes and supporting references with existing databases. We demonstrated that our candidate gene set covers nearly all genes in manually curated databases, and that the references supporting the disorder–gene link are more extensive and accurate than other general purpose gene-to-disorder association databases. Conclusions: We implemented a novel publication search tool to find target articles, specifically focused on links between disorders and genotypes. Through comparison against gold-standard manually updated gene–disorder databases and comparison with automated databases of similar functionality we show that our tool can search through the entirety of PubMed to extract the main gene findings for human diseases rapidly and accurately

Detecting biological network organization and functional gene orthologs

SUMMARY: We developed a package TripletSearch to compute relationships within triplets of genes based on Roundup, an orthologous gene database containing >1500 genomes. These relationships, derived from the coevolution of genes, provide valuable information in the detection of biological network organization from the local to the system level, in the inference of protein functions and in the identification of functional orthologs. To run the computation, users need to provide the GI IDs of the genes of interest

Cost-Effective Cloud Computing: A Case Study Using the Comparative Genomics Tool, Roundup

Background Comparative genomics resources, such as ortholog detection tools and repositories are rapidly increasing in scale and complexity. Cloud computing is an emerging technological paradigm that enables researchers to dynamically build a dedicated virtual cluster and may represent a valuable alternative for large computational tools in bioinformatics. In the present manuscript, we optimize the computation of a large-scale comparative genomics resource—Roundup—using cloud computing, describe the proper operating principles required to achieve computational efficiency on the cloud, and detail important procedures for improving cost-effectiveness to ensure maximal computation at minimal costs. Methods Utilizing the comparative genomics tool, Roundup, as a case study, we computed orthologs among 902 fully sequenced genomes on Amazon's Elastic Compute Cloud. For managing the ortholog processes, we designed a strategy to deploy the web service, Elastic MapReduce, and maximize the use of the cloud while simultaneously minimizing costs. Specifically, we created a model to estimate cloud runtime based on the size and complexity of the genomes being compared that determines in advance the optimal order of the jobs to be submitted. Results We computed orthologous relationships for 245,323 genome-to-genome comparisons on Amazon's computing cloud, a computation that required just over 200 hours and cost $8,000 USD, at least 40% less than expected under a strategy in which genome comparisons were submitted to the cloud randomly with respect to runtime. Our cost savings projections were based on a model that not only demonstrates the optimal strategy for deploying RSD to the cloud, but also finds the optimal cluster size to minimize waste and maximize usage. Our cost-reduction model is readily adaptable for other comparative genomics tools and potentially of significant benefit to labs seeking to take advantage of the cloud as an alternative to local computing infrastructure

Anterior Cruciate Ligament Injuries in National Football League Athletes From 2010 to 2013: A Descriptive Epidemiology Study.

BACKGROUND: There is a high incidence of anterior cruciate ligament (ACL) injuries among National Football League (NFL) athletes; however, the incidence of reinjury in this population is unknown. PURPOSE: This retrospective epidemiological study analyzed all publicly disclosed ACL tears occurring in NFL players between 2010 and 2013 to characterize injury trends and determine the incidence of reinjury. STUDY DESIGN: Descriptive epidemiological study. METHODS: A comprehensive online search identified any NFL player who had suffered an ACL injury from 2010 to 2013. Position, playing surface, activity, and date were recorded. Each player was researched for any history of previous ACL injury. The NFL games database from USA Today was used to determine the incidence of ACL injuries on artificial turf and grass fields. Databases from Pro Football Focus and Pro Football Reference were used to determine the injury rate for each position. RESULTS: NFL players suffered 219 ACL injuries between 2010 and 2013. Forty players (18.3%) had a history of previous ACL injury, with 27 (12.3%) retears and 16 (7.3%) tears contralateral to a previous ACL injury. Five players (2.28%) suffered their third ACL tear. Receivers (wide receivers and tight ends) and backs (linebackers, fullbacks, and halfbacks) had significantly greater injury risk than the rest of the NFL players, while perimeter linemen (defensive ends and offensive tackles) had significantly lower injury risk than the rest of the players. Interior linemen (offensive guards, centers, and defensive tackles) had significantly greater injury risk compared with perimeter linemen. ACL injury rates per team games played were 0.050 for grass and 0.053 for turf fields (P \u3e .05). CONCLUSION: In this retrospective epidemiological study of ACL tears in NFL players, retears and ACL tears contralateral to a previously torn ACL constituted a substantial portion (18.3%) of total ACL injuries. The significant majority of ACL injuries in players with a history of previous ACL injury were retears. Skilled offensive players and linebackers had the greatest injury risk, and significantly more ACL tears occurred among interior linemen than perimeter linemen. The month of August had the highest incidence of ACL injuries, probably because of expanded roster sizes at that point in the NFL season

A Scoping Review of Injuries in Amateur and Professional Men\u27s Ice Hockey.

Background: Orthopaedic injuries are common in ice hockey at all levels and can result in physical and psychological adverse effects on these athletes. Purpose: Primarily, to summarize published data on orthopaedic hockey injuries at the junior through professional level. Secondarily, to characterize the literature based on anatomic site injured, return-to-play rates, cause/mechanism of injury, time lost, and treatments used. Study Design: Scoping review; Level of evidence, 4. Methods: PubMed, EMBASE, Cochrane library, and SCOPUS were searched using the terms hockey and injuries using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, and 4163 studies involving orthopaedic injuries were identified. Our inclusion criteria consisted of accessible full-text articles that evaluated orthopaedic injuries in men\u27s ice hockey athletes of all levels. We excluded case reports and articles evaluating women\u27s ice hockey injuries, as well as those evaluating nonorthopaedic injuries, such as concussions; traumatic brain injuries; and facial, dental, and vascular injuries, among others. Studies were divided based on level of play and anatomic site of injury. Level of evidence, year published, country of corresponding author, method of data collection, incidence of injury per athlete-exposure, and time lost were extracted from each article. Results: A total of 92 articles met the inclusion criteria and were performed between 1975 and 2020, with the majority published between 2015 and 2020. These were divided into 8 anatomic sites: nonanatomic-specific (37%), intra-articular hip (20.7%), shoulder (9.8%), knee (8.7%), trunk/pelvis (7.6%), spine (7.6%), foot/ankle (6.5%), and hand/wrist (2.2%). Of these studies, 71% were level 4 evidence. Data were obtained mostly via surveillance programs and searches of publicly available information (eg, injury reports, player profiles, and press releases). Conclusion: This scoping review provides men\u27s hockey players and physicians taking care of elite ice hockey athletes of all levels with a single source of the most current literature regarding orthopaedic injuries. Most research focused on nonanatomic-specific injuries, intra-articular hip injuries, knee injuries, and shoulder injuries, with the majority having level 4 evidence

The Vela Pulsar and its Synchrotron Nebula

(Abridged) We present high-resolution Chandra X-ray observations of PSR B0833-45, the 89 ms pulsar associated with the Vela supernova remnant. We have acquired two observations separated by one month to search for changes in the pulsar and its environment following an extreme glitch in its rotation frequency. We find a well-resolved nebula with a toroidal morphology remarkably similar to that observed in the Crab Nebula, along with an axial Crab-like jet. Between the two observations the flux from the pulsar is found to be steady to within 0.75%; the 3 sigma limit on the fractional increase in the pulsar's X-ray flux is < ~10^-5 of the inferred glitch energy. We use this limit to constrain parameters of glitch models and neutron star structure. We do find a significant increase in the flux of the nebula's outer arc; if associated with the glitch, the inferred propagation velocity is > 0.7c, similar to that seen in the brightening of the Crab Nebula wisps. We propose an explanation for the X-ray structure of the Vela synchrotron nebula based on a model originally developed for the Crab Nebula. In a departure from the Crab model, the magnetization parameter "sigma" of the Vela pulsar wind is allowed to be of order unity; this is consistent with the simplest MHD transport of magnetic field from the pulsar to the nebula, where B < 4 X 10^-4 G. We review effects that may enhance the probability of alignment between the spin axis and space velocity of a pulsar, and speculate that short-period, slowly moving pulsars are just the ones best-suited to producing synchrotron nebulae with such aligned structures.Comment: 16 pages with 8 figures, uses LaTex, emulateapj.sty. Refereed version. To appear in The Astrophysical Journa

Contemplative Science: An Insider's Prospectus

This chapter describes the potential far‐reaching consequences of contemplative higher education for the fields of science and medicine

The Potential of Accelerating Early Detection of Autism through Content Analysis of YouTube Videos

Abstract Autism is on the rise, with 1 in 88 children receiving a diagnosis in the United States, yet the process for diagnosis remains cumbersome and time consuming. Research has shown that home videos of children can help increase the accuracy of diagnosis. However the use of videos in the diagnostic process is uncommon. In the present study, we assessed the feasibility of applying a gold-standard diagnostic instrument to brief and unstructured home videos and tested whether video analysis can enable more rapid detection of the core features of autism outside of clinical environments. We collected 100 public videos from YouTube of children ages 1–15 with either a self-reported diagnosis of an ASD (N = 45) or not (N = 55). Four non-clinical raters independently scored all videos using one of the most widely adopted tools for behavioral diagnosis of autism, the Autism Diagnostic Observation Schedule-Generic (ADOS). The classification accuracy was 96.8%, with 94.1% sensitivity and 100% specificity, the inter-rater correlation for the behavioral domains on the ADOS was 0.88, and the diagnoses matched a trained clinician in all but 3 of 22 randomly selected video cases. Despite the diversity of videos and non-clinical raters, our results indicate that it is possible to achieve high classification accuracy, sensitivity, and specificity as well as clinically acceptable inter-rater reliability with nonclinical personnel. Our results also demonstrate the potential for video-based detection of autism in short, unstructured home videos and further suggests that at least a percentage of the effort associated with detection and monitoring of autism may be mobilized and moved outside of traditional clinical environments

Genotator: A disease-agnostic tool for genetic annotation of disease

<p>Abstract</p> <p>Background</p> <p>Disease-specific genetic information has been increasing at rapid rates as a consequence of recent improvements and massive cost reductions in sequencing technologies. Numerous systems designed to capture and organize this mounting sea of genetic data have emerged, but these resources differ dramatically in their disease coverage and genetic depth. With few exceptions, researchers must manually search a variety of sites to assemble a complete set of genetic evidence for a particular disease of interest, a process that is both time-consuming and error-prone.</p> <p>Methods</p> <p>We designed a real-time aggregation tool that provides both comprehensive coverage and reliable gene-to-disease rankings for any disease. Our tool, called Genotator, automatically integrates data from 11 externally accessible clinical genetics resources and uses these data in a straightforward formula to rank genes in order of disease relevance. We tested the accuracy of coverage of Genotator in three separate diseases for which there exist specialty curated databases, Autism Spectrum Disorder, Parkinson's Disease, and Alzheimer Disease. Genotator is freely available at <url>http://genotator.hms.harvard.edu</url>.</p> <p>Results</p> <p>Genotator demonstrated that most of the 11 selected databases contain unique information about the genetic composition of disease, with 2514 genes found in only one of the 11 databases. These findings confirm that the integration of these databases provides a more complete picture than would be possible from any one database alone. Genotator successfully identified at least 75% of the top ranked genes for all three of our use cases, including a 90% concordance with the top 40 ranked candidates for Alzheimer Disease.</p> <p>Conclusions</p> <p>As a meta-query engine, Genotator provides high coverage of both historical genetic research as well as recent advances in the genetic understanding of specific diseases. As such, Genotator provides a real-time aggregation of ranked data that remains current with the pace of research in the disease fields. Genotator's algorithm appropriately transforms query terms to match the input requirements of each targeted databases and accurately resolves named synonyms to ensure full coverage of the genetic results with official nomenclature. Genotator generates an excel-style output that is consistent across disease queries and readily importable to other applications.</p