Recent genetic advances in our knowledge of colorectal cancer genetics are beginning to pay translational dividends in the management of this common clinical problem. We are now able to accurately screen and counsel individuals at risk of rare inherited cancer syndromes. We have recently introduced two of what are sure to be numerous biologic-based therapies, and have shown that colorectal neoplasia risk can be modestly reduced by various chemopreventative agents. Finally, our advancing knowledge has led to significant inroads into understanding what genetic alterations define prognosis and predict response to specific chemotherapeutic agents, and we are beginning to explore the utility of this knowledge in mass genetic-based clinical screening efforts. Enthusiasm must be tempered, however, by the extraordinary cost that often accompanies relatively modest gains. Finally, although genetic-based therapy often receives the greatest attention, molecular genetics, will likely have the greatest cost-effective impact in primary prevention and early diagnosis.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.suc.2006.05.007 | DOI Listing |
Viruses
December 2024
Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.
Hepatitis C virus (HCV) disproportionately affects certain sub-populations, including people with experience of incarceration (PWEI). Little is known about how perceptions of HCV and treatment have changed despite simplifications in testing and treatment in carceral settings. Nineteen semi-structured interviews were conducted with people living with or having a history of HCV infection released from Quebec provincial prison.
View Article and Find Full Text PDFVaccines (Basel)
December 2024
World Health Organization, 20 Avenue Appia, 1211 Geneva, Switzerland.
: Yellow fever (YF) outbreaks continue to affect populations that are not reached by routine immunization services, such as workers at a high risk of occupational exposure to YF. In the Central African Republic (CAR), YF cases were detected in districts characterized by the presence of workers in forest areas. We developed an innovative approach based on a local partnership with private companies of the extractive industry to administer YF vaccine to workers in remote areas during the response to an outbreak.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Automation, North China Electric Power University, Baoding 071003, China.
To address the difficulty in detecting workers' violation behaviors in electric power construction scenarios, this paper proposes an innovative method that integrates knowledge reasoning and progressive multi-level distillation techniques. First, standards, norms, and guidelines in the field of electric power construction are collected to build a comprehensive knowledge graph, aiming to provide accurate knowledge representation and normative analysis. Then, the knowledge graph is combined with the object-detection model in the form of triplets, where detected objects and their interactions are represented as subject-predicate-object relationship.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Division of Computer Science & Artificial Intelligence, Dongguk University, Seoul 04620, Republic of Korea.
Anomaly detection is critical in safety-sensitive fields, but faces challenges from scarce abnormal data and costly expert labeling. Time series anomaly detection is relatively challenging due to its reliance on sequential data, which imposes high computational and memory costs. In particular, it is often composed of real-time collected data that tends to be noisy, making preprocessing an essential step.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Computer Science and Informatics, Cardiff University, Cardiff CF24 4AG, UK.
Poaching poses a significant threat to wildlife and their habitats, necessitating advanced tools for its prediction and prevention. Existing tools for poaching prediction face challenges such as inconsistent poaching data, spatiotemporal complexity, and translating predictions into actionable insights for conservation efforts. This paper presents PoachNet, a novel predictive system that integrates deep learning with Semantic Web reasoning to infer poaching likelihood.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!