Journal of internal medicine
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Review
Epigenetic regulation of insulin action and secretion - role in the pathogenesis of type 2 diabetes.
The prevalence of type 2 diabetes (T2D) is rapidly increasing worldwide. Obesity, physical inactivity and ageing increase the risk of T2D. Epigenetic modifications can change due to environmental exposures and may thereby predispose to disease. ⋯ Several of these SNPs are also associated with T2D. Recent data also support that DNA methylation of some sites in blood may be developed into biomarkers that predict T2D since methylation of, for example TXNIP, ABCG1 and SREBF1 associated with future T2D. Future studies should use this information for development of new therapies and biomarkers and thereby improve prediction, prevention and treatment of T2D and its complications.
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Given the increasing availability of large data set, small single-institutional series raise decreasing attention. Rapid expansion of technology from electronic medical records to easily accessible internet access, and widespread use and acceptance of registries in the medical world has allowed for research and quality improvement efforts using 'big data'. Big data, although technically not defined, typically refers to large databases that can be used to investigate common or rare disease processes or outcomes, describe variation in clinical practices across and between different specialties at various practice location, whilst allowing important information about trends over time. ⋯ Within vascular surgery specifically, big data have expanded over the last decade and now includes regional, national and global registries that have major benefits of gathering specific clinical and procedural information within vascular surgery. In this review, we highlight the main vascular surgery registries and recap a few success stories of how the registries have been leveraged to benefit discovery, quality improvement and ultimately patient care. Additionally, we outline future directions that will be imperative for continued expansion, acceptance and adoption of 'big data' utilization inpatients with vascular disease.
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Pathology is the cornerstone of cancer care. The need for accuracy in histopathologic diagnosis of cancer is increasing as personalized cancer therapy requires accurate biomarker assessment. The appearance of digital image analysis holds promise to improve both the volume and precision of histomorphological evaluation. ⋯ Furthermore, deep learning models have also been demonstrated to be able to predict status of some molecular markers in lung, prostate, gastric and colorectal cancer based on standard HE slides. Moreover, prognostic (survival outcomes) deep neural network models based on digitized HE slides have been demonstrated in several diseases, including lung cancer, melanoma and glioma. In this review, we aim to present and summarize the latest developments in digital image analysis and in the application of artificial intelligence in diagnostic pathology.
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Aortic pathologies such as aneurysm, dissection and trauma are relatively common and potentially fatal diseases. Over the past two decades, we have experienced unprecedented technical and medical developments in the field. Despite this, there is a great need, and great opportunities, to further explore the area. ⋯ A key limitation of contemporary treatment strategies of AAA is the lack of therapy directed at small AAA, to prevent AAA expansion and need for surgical repair, as well as to reduce the risk for aortic rupture. Currently, the most promising potential drug candidate to slow AAA growth is metformin, and RCTs to verify or reject this hypothesis are warranted. In addition, the role of endovascular treatment for ascending pathologies and for uncomplicated type B aortic dissection needs to be clarified.
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Abdominal aortic aneurysm (AAA) rupture is a common cause of death in adults. Current AAA treatment is by open surgical or endovascular aneurysm repair. Rodent model and human epidemiology, and genetic and observational studies over the last few decades have highlighted the potential of a number of drug therapies, including medications that lower blood pressure, correct dyslipidaemia, or inhibit thrombosis, inflammation or matrix remodelling, as approaches to managing small AAA. ⋯ Three further trials assessed the effect of a mast cell inhibitor, fibrate or platelet aggregation inhibition and reported no effect on AAA growth or clinical events. Past trials were noted to have a number of design issues, particularly small sample sizes and limited follow-up. Much larger trials are needed to properly test potential therapeutic approaches if a convincingly effective medical therapy for AAA is to be identified.