FastMRI Prostate: A Publicly Available, Biparametric MRI Dataset to Advance Machine Learning for Prostate Cancer Imaging

The fastMRI brain and knee dataset has enabled significant advances in exploring reconstruction methods for improving speed and image quality for Magnetic Resonance Imaging (MRI) via novel, clinically relevant reconstruction approaches. In this study, we describe the April 2023 expansion of the fastMRI dataset to include biparametric prostate MRI data acquired on a clinical population. The dataset consists of raw k-space and reconstructed images for T2-weighted and diffusion-weighted sequences along with slice-level labels that indicate the presence and grade of prostate cancer. As has been the case with fastMRI, increasing accessibility to raw prostate MRI data will further facilitate research in MR image reconstruction and evaluation with the larger goal of improving the utility of MRI for prostate cancer detection and evaluation. The dataset is available at https://fastmri.med.nyu.edu.Comment: 4 pages, 1 figur

Evidence from sperm whale clans of symbolic marking in non-human cultures

Culture, a pillar of the remarkable ecological success of humans, is increasingly recognized as a powerful force structuring nonhuman animal populations. A key gap between these two types of culture is quantitative evidence of symbolic markers—seemingly arbitrary traits that function as reliable indicators of cultural group membership to conspecifics. Using acoustic data collected from 23 Pacific Ocean locations, we provide quantitative evidence that certain sperm whale acoustic signals exhibit spatial patterns consistent with a symbolic marker function. Culture segments sperm whale populations into behaviorally distinct clans, which are defined based on dialects of stereotyped click patterns (codas). We classified 23,429 codas into types using contaminated mixture models and hierarchically clustered coda repertoires into seven clans based on similarities in coda usage; then we evaluated whether coda usage varied with geographic distance within clans or with spatial overlap between clans. Similarities in within-clan usage of both “identity codas” (coda types diagnostic of clan identity) and “nonidentity codas” (coda types used by multiple clans) decrease as space between repertoire recording locations increases. However, between-clan similarity in identity, but not nonidentity, coda usage decreases as clan spatial overlap increases. This matches expectations if sympatry is related to a measurable pressure to diversify to make cultural divisions sharper, thereby providing evidence that identity codas function as symbolic markers of clan identity. Our study provides quantitative evidence of arbitrary traits, resembling human ethnic markers, conveying cultural identity outside of humans, and highlights remarkable similarities in the distributions of human ethnolinguistic groups and sperm whale clans

Dynamic summarization of bibliographic-based data

<p>Abstract</p> <p>Background</p> <p>Traditional information retrieval techniques typically return excessive output when directed at large bibliographic databases. Natural Language Processing applications strive to extract salient content from the excessive data. Semantic MEDLINE, a National Library of Medicine (NLM) natural language processing application, highlights relevant information in PubMed data. However, Semantic MEDLINE implements manually coded schemas, accommodating few information needs. Currently, there are only five such schemas, while many more would be needed to realistically accommodate all potential users. The aim of this project was to develop and evaluate a statistical algorithm that automatically identifies relevant bibliographic data; the new algorithm could be incorporated into a dynamic schema to accommodate various information needs in Semantic MEDLINE, and eliminate the need for multiple schemas.</p> <p>Methods</p> <p>We developed a flexible algorithm named Combo that combines three statistical metrics, the Kullback-Leibler Divergence (KLD), Riloff's RlogF metric (RlogF), and a new metric called PredScal, to automatically identify salient data in bibliographic text. We downloaded citations from a PubMed search query addressing the genetic etiology of bladder cancer. The citations were processed with SemRep, an NLM rule-based application that produces semantic predications. SemRep output was processed by Combo, in addition to the standard Semantic MEDLINE genetics schema and independently by the two individual KLD and RlogF metrics. We evaluated each summarization method using an existing reference standard within the task-based context of genetic database curation.</p> <p>Results</p> <p>Combo asserted 74 genetic entities implicated in bladder cancer development, whereas the traditional schema asserted 10 genetic entities; the KLD and RlogF metrics individually asserted 77 and 69 genetic entities, respectively. Combo achieved 61% recall and 81% precision, with an F-score of 0.69. The traditional schema achieved 23% recall and 100% precision, with an F-score of 0.37. The KLD metric achieved 61% recall, 70% precision, with an F-score of 0.65. The RlogF metric achieved 61% recall, 72% precision, with an F-score of 0.66.</p> <p>Conclusions</p> <p>Semantic MEDLINE summarization using the new Combo algorithm outperformed a conventional summarization schema in a genetic database curation task. It potentially could streamline information acquisition for other needs without having to hand-build multiple saliency schemas.</p

Characteristics of successfully implemented telemedical applications

<p>Abstract</p> <p>Background</p> <p>There has been an increased interest in the use of telemedical applications in clinical practice in recent years. Considerable effort has been invested in trials and experimental services. Yet, surprisingly few applications have continued beyond the research and development phase. The aim of this study is to explore characteristics of successfully implemented telemedical applications.</p> <p>Methods</p> <p>An extensive search of telemedicine literature was conducted in order to identify relevant articles. Following a defined selection process, a small number of articles were identified that described characteristics of successfully implemented telemedical applications. These articles were analysed qualitatively, drawing on central procedures from Grounded Theory (GT), including condensation and categorisation. The analysis resulted in a description of features found to be of importance for a successful implementation of telemedicine. Subsequently, these features were discussed in light of Science and Technology studies (STS) and the concept of 'social negotiation'.</p> <p>Results</p> <p>Telemedical applications introduced into routine practice are typically characterised by the following six features: 1) local service delivery problems have been clearly stated, 2) telemedicine has been seen as a benefit, 3) telemedicine has been seen as a solution to political and medical issues, 4) there was collaboration between promoters and users, 5) issues regarding organizational and technological arrangements have been addressed, and 6) the future operation of the service has been considered.</p> <p>Conclusion</p> <p>Our findings support research arguing that technologies are not fixed entities moving from invention through diffusion and into routine use. Rather, it is the interplay between technical and social factors that produces a particular outcome. The success of a technology depends on how this interplay is managed during the process of implementation.</p

OpenDMAP: An open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression

<p>Abstract</p> <p>Background</p> <p>Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering.</p> <p>Results</p> <p>OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport), protein-protein interaction assertions (interaction) and assertions that a gene is expressed in a cell type (expression). Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85). Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. </p> <p>Conclusion</p> <p>OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for information extraction. The open source OpenDMAP code library is freely available at <url>http://bionlp.sourceforge.net/</url></p

A Semantic Problem Solving Environment for Integrative Parasite Research: Identification of Intervention Targets for Trypanosoma cruzi

Effective research in parasite biology requires analyzing experimental lab data in the context of constantly expanding public data resources. Integrating lab data with public resources is particularly difficult for biologists who may not possess significant computational skills to acquire and process heterogeneous data stored at different locations. Therefore, we develop a semantic problem solving environment (SPSE) that allows parasitologists to query their lab data integrated with public resources using ontologies. An ontology specifies a common vocabulary and formal relationships among the terms that describe an organism, and experimental data and processes in this case. SPSE supports capturing and querying provenance information, which is metadata on the experimental processes and data recorded for reproducibility, and includes a visual query-processing tool to formulate complex queries without learning the query language syntax. We demonstrate the significance of SPSE in identifying gene knockout targets for T. cruzi. The overall goal of SPSE is to help researchers discover new or existing knowledge that is implicitly present in the data but not always easily detected. Results demonstrate improved usefulness of SPSE over existing lab systems and approaches, and support for complex query design that is otherwise difficult to achieve without the knowledge of query language syntax

Genome-Wide Tissue-Specific Occupancy of the Hox Protein Ultrabithorax and Hox Cofactor Homothorax in Drosophila

The Hox genes are responsible for generating morphological diversity along the anterior-posterior axis during animal development. The Drosophila Hox gene Ultrabithorax (Ubx), for example, is required for specifying the identity of the third thoracic (T3) segment of the adult, which includes the dorsal haltere, an appendage required for flight, and the ventral T3 leg. Ubx mutants show homeotic transformations of the T3 leg towards the identity of the T2 leg and the haltere towards the wing. All Hox genes, including Ubx, encode homeodomain containing transcription factors, raising the question of what target genes Ubx regulates to generate these adult structures. To address this question, we carried out whole genome ChIP-chip studies to identify all of the Ubx bound regions in the haltere and T3 leg imaginal discs, which are the precursors to these adult structures. In addition, we used ChIP-chip to identify the sites bound by the Hox cofactor, Homothorax (Hth). In contrast to previous ChIP-chip studies carried out in Drosophila embryos, these binding studies reveal that there is a remarkable amount of tissue- and transcription factor-specific binding. Analyses of the putative target genes bound and regulated by these factors suggest that Ubx regulates many downstream transcription factors and developmental pathways in the haltere and T3 leg. Finally, we discovered additional DNA sequence motifs that in some cases are specific for individual data sets, arguing that Ubx and/or Hth work together with many regionally expressed transcription factors to execute their functions. Together, these data provide the first whole-genome analysis of the binding sites and target genes regulated by Ubx to specify the morphologies of the adult T3 segment of the fly

Average Household Exposure to Newspaper Coverage about the Harmful Effects of Hormone Therapy and Population-Based Declines in Hormone Therapy Use

BACKGROUND: The news media facilitated the rapid dissemination of the findings from the estrogen plus progestin therapy arm of the Women’s Health Initiative (EPT-WHI). OBJECTIVE: To examine the relationship between the potential exposure to newspaper coverage and subsequent hormone therapy (HT) use. DESIGN/POPULATION: Population-based cohort of women receiving mammography at 7 sites (327,144 postmenopausal women). MEASUREMENTS: The outcome was the monthly prevalence of self-reported HT use. Circulation data for local, regional, and national newspapers was used to create zip-code level measures of the estimated average household exposure to newspaper coverage that reported the harmful effects of HT in July 2002. RESULTS: Women had an average potential household exposure of 1.4 articles. There was substantial variation in the level of average household exposure to newspaper coverage; women from rural sites received less than women from urban sites. Use of HT declined for all average potential exposure groups after the publication of the EPT-WHI. HT prevalence among women who lived in areas where there was an average household exposure of at least 3 articles declined significantly more (45 to 27%) compared to women who lived in areas with <1 article (43 to 31%) during each of the subsequent 5 months (relative risks 0.86–0.92; p < .006 for all). CONCLUSIONS: Greater average household exposure to newspaper coverage about the harms associated with HT was associated with a large population-based decline in HT use. Further studies should examine whether media coverage directly influences the health behavior of individual women