Dataset Information

Classification of the universe of immune epitope literature: representation and knowledge gaps.

ABSTRACT:

Background

A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continually updated by monitoring PubMed for new, potentially relevant references.

Methodology

Herein we detail the classification of all epitope-specific literature in over 100 different immunological domains representing Infectious Diseases and Microbes, Autoimmunity, Allergy, Transplantation and Cancer. The relative number of references in each category reflects past and present areas of research on immune reactivities. In addition to describing the overall landscape of data distribution, this particular characterization of the epitope reference data also allows for the exploration of possible correlations with global disease morbidity and mortality data.

Conclusions/significance

While in most cases diseases associated with high morbidity and mortality rates were amongst the most studied, a number of high impact diseases such as dengue, Schistosoma, HSV-2, B. pertussis and Chlamydia trachoma, were found to have very little coverage. The data analyzed in this fashion represents the first estimate of how reported immunological data corresponds to disease-related morbidity and mortality, and confirms significant discrepancies in the overall research foci versus disease burden, thus identifying important gaps to be pursued by future research. These findings may also provide a justification for redirecting a portion of research funds into some of the underfunded, critical disease areas.

SUBMITTER: Davies V

PROVIDER: S-EPMC2747625 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Classification of the universe of immune epitope literature: representation and knowledge gaps.

Davies Vince V Vaughan Kerrie K Damle Rohini R Peters Bjoern B Sette Alessandro A

PloS one 20090914 9

<h4>Background</h4>A significant fraction of the more than 18 million scientific articles currently indexed in the PubMed database are related to immune responses to various agents, including infectious microbes, autoantigens, allergens, transplants, cancer antigens and others. The Immune Epitope Database (IEDB) is an online repository that catalogs immune epitope reactivity data derived from articles listed in the National Library of Medicine PubMed database. The IEDB is maintained and continua ...[more]

PMID: 19774228

Similar Datasets

Project description:A valuable strategy to support conservation planning is to assess knowledge gaps regarding primary species occurrence data to identify and select areas for future biodiversity surveys. Currently, increasing accessibility to these data allows a cost-effective method for boosting knowledge about a country's biodiversity. For understudied countries where the lack of resources for conservation is more pronounced to resort to primary biodiversity data can be especially beneficial. Here, using a primary species occurrence dataset, we assessed and mapped Mozambique's knowledge gaps regarding terrestrial mammal species by identifying areas that are geographically distant and environmentally different from well-known sites. By comparing gaps from old and recent primary species occurrence data, we identified: (i) gaps of knowledge over time, (ii) the lesser-known taxa, and (iii) areas with potential for spatiotemporal studies. Our results show that the inventory of Mozambique's mammal fauna is near-complete in less than 5% of the territory, with broad areas of the country poorly sampled or not sampled at all. The knowledge gap areas are mostly associated with two ecoregions. The provinces lacking documentation coincide with areas over-explored for natural resources, and many such sites may never be documented. It is our understanding that by prioritising the survey of the knowledge-gap areas will likely produce new records for the country and, continuing the study of the well-known regions will guarantee their potential use for spatiotemporal studies. The implemented approach to assess the knowledge gaps from primary species occurrence data proved to be a powerful strategy to generate information that is essential to species conservation and management plan. However, we are aware that the impact of digital and openly available data depends mostly on its completeness and accuracy, and thus we encourage action from the scientific community and government authorities to support and promote data mobilisation.

Project description:Extracorporeal life support (ECLS) for acute respiratory failure encompasses veno-venous extracorporeal membrane oxygenation (V-V ECMO) and extracorporeal carbon dioxide removal (ECCO2R). V-V ECMO is primarily used to treat severe acute respiratory distress syndrome (ARDS), characterized by life-threatening hypoxemia or ventilatory insufficiency with conventional protective settings. It employs an artificial lung with high blood flows, and allows improvement in gas exchange, correction of hypoxemia, and reduction of the workload on the native lung. On the other hand, ECCO2R focuses on carbon dioxide removal and ventilatory load reduction ("ultra-protective ventilation") in moderate ARDS, or in avoiding pump failure in acute exacerbated chronic obstructive pulmonary disease. Clinical indications for V-V ECLS are tailored to individual patients, as there are no absolute contraindications. However, determining the ideal timing for initiating extracorporeal respiratory support remains uncertain. Current ECLS equipment faces issues like size and durability. Innovations include intravascular lung assist devices (ILADs) and pumpless devices, though they come with their own challenges. Efficient gas exchange relies on modern oxygenators using hollow fiber designs, but research is exploring microfluidic technology to improve oxygenator size, thrombogenicity, and blood flow capacity. Coagulation management during V-V ECLS is crucial due to common bleeding and thrombosis complications; indeed, anticoagulation strategies and monitoring systems require improvement, while surface coatings and new materials show promise. Moreover, pharmacokinetics during ECLS significantly impact antibiotic therapy, necessitating therapeutic drug monitoring for precise dosing. Managing native lung ventilation during V-V ECMO remains complex, requiring a careful balance between benefits and potential risks for spontaneously breathing patients. Moreover, weaning from V-V ECMO is recognized as an area of relevant uncertainty, requiring further research. In the last decade, the concept of Extracorporeal Organ Support (ECOS) for patients with multiple organ dysfunction has emerged, combining ECLS with other organ support therapies to provide a more holistic approach for critically ill patients. In this review, we aim at providing an in-depth overview of V-V ECMO and ECCO2R, addressing various aspects of their use, challenges, and potential future directions in research and development.

Project description:The segmentation of prostate in CT images is of essential importance to external beam radiotherapy, which is one of the major treatments for prostate cancer nowadays. During the radiotherapy, the prostate is radiated by high-energy x rays from different directions. In order to maximize the dose to the cancer and minimize the dose to the surrounding healthy tissues (e.g., bladder and rectum), the prostate in the new treatment image needs to be accurately localized. Therefore, the effectiveness and efficiency of external beam radiotherapy highly depend on the accurate localization of the prostate. However, due to the low contrast of the prostate with its surrounding tissues (e.g., bladder), the unpredicted prostate motion, and the large appearance variations across different treatment days, it is challenging to segment the prostate in CT images. In this paper, the authors present a novel classification based segmentation method to address these problems.To segment the prostate, the proposed method first uses sparse representation based classification (SRC) to enhance the prostate in CT images by pixel-wise classification, in order to overcome the limitation of poor contrast of the prostate images. Then, based on the classification results, previous segmented prostates of the same patient are used as patient-specific atlases to align onto the current treatment image and the majority voting strategy is finally adopted to segment the prostate. In order to address the limitations of the traditional SRC in pixel-wise classification, especially for the purpose of segmentation, the authors extend SRC from the following four aspects: (1) A discriminant subdictionary learning method is proposed to learn a discriminant and compact representation of training samples for each class so that the discriminant power of SRC can be increased and also SRC can be applied to the large-scale pixel-wise classification. (2) The L1 regularized sparse coding is replaced by the elastic net in order to obtain a smooth and clear prostate boundary in the classification result. (3) Residue-based linear regression is incorporated to improve the classification performance and to extend SRC from hard classification to soft classification. (4) Iterative SRC is proposed by using context information to iteratively refine the classification results.The proposed method has been comprehensively evaluated on a dataset consisting of 330 CT images from 24 patients. The effectiveness of the extended SRC has been validated by comparing it with the traditional SRC based on the proposed four extensions. The experimental results show that our extended SRC can obtain not only more accurate classification results but also smoother and clearer prostate boundary than the traditional SRC. Besides, the comparison with other five state-of-the-art prostate segmentation methods indicates that our method can achieve better performance than other methods under comparison.The authors have proposed a novel prostate segmentation method based on the sparse representation based classification, which can achieve considerably accurate segmentation results in CT prostate segmentation.

Dataset Information

Classification of the universe of immune epitope literature: representation and knowledge gaps.

Background

Methodology

Conclusions/significance

Publications

Classification of the universe of immune epitope literature: representation and knowledge gaps.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets