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Frontiers in Endocrinology 2023The discovery of insulin in 1921 introduced a new branch of research into insulin activity and insulin resistance. Many discoveries in this field have been applied to... (Review)
Review
The discovery of insulin in 1921 introduced a new branch of research into insulin activity and insulin resistance. Many discoveries in this field have been applied to diagnosing and treating diseases related to insulin resistance. In this mini-review, the authors attempt to synthesize the updated discoveries to unravel the related mechanisms and inform the development of novel applications. Firstly, we depict the insulin signaling pathway to explain the physiology of insulin action starting at the receptor sites of insulin and downstream the signaling of the insulin signaling pathway. Based on this, the next part will analyze the mechanisms of insulin resistance with two major provenances: the defects caused by receptors and the defects due to extra-receptor causes, but in this study, we focus on post-receptor causes. Finally, we discuss the recent applications including the diseases related to insulin resistance (obesity, cardiovascular disease, Alzheimer's disease, and cancer) and the potential treatment of those based on insulin resistance mechanisms.
Topics: Humans; Insulin; Insulin Resistance; Signal Transduction; Alzheimer Disease; Binding Sites
PubMed: 37664840
DOI: 10.3389/fendo.2023.1226655 -
European Respiratory Review : An... Jun 2023COPD and adult-onset asthma (AOA) are the most common noncommunicable respiratory diseases. To improve early identification and prevention, an overview of risk factors... (Review)
Review
BACKGROUND
COPD and adult-onset asthma (AOA) are the most common noncommunicable respiratory diseases. To improve early identification and prevention, an overview of risk factors is needed. We therefore aimed to systematically summarise the nongenetic (exposome) risk factors for AOA and COPD. Additionally, we aimed to compare the risk factors for COPD and AOA.
METHODS
In this umbrella review, we searched PubMed for articles from inception until 1 February 2023 and screened the references of relevant articles. We included systematic reviews and meta-analyses of observational epidemiological studies in humans that assessed a minimum of one lifestyle or environmental risk factor for AOA or COPD.
RESULTS
In total, 75 reviews were included, of which 45 focused on risk factors for COPD, 28 on AOA and two examined both. For asthma, 43 different risk factors were identified while 45 were identified for COPD. For AOA, smoking, a high body mass index (BMI), wood dust exposure and residential chemical exposures, such as formaldehyde exposure or exposure to volatile organic compounds, were amongst the risk factors found. For COPD, smoking, ambient air pollution including nitrogen dioxide, a low BMI, indoor biomass burning, childhood asthma, occupational dust exposure and diet were amongst the risk factors found.
CONCLUSIONS
Many different factors for COPD and asthma have been found, highlighting the differences and similarities. The results of this systematic review can be used to target and identify people at high risk for COPD or AOA.
Topics: Adult; Humans; Child; Pulmonary Disease, Chronic Obstructive; Asthma; Risk Factors; Air Pollution; Dust; Environmental Exposure
PubMed: 37137510
DOI: 10.1183/16000617.0009-2023 -
BMJ (Clinical Research Ed.) Aug 2023
Topics: Humans; Delivery of Health Care; Health Facilities
PubMed: 37586727
DOI: 10.1136/bmj.p1820 -
Progress in Brain Research 2024The chapter reviews certain topics in outline. It starts with a brief account of the nature of surgery. This is followed by a short account of modern management of...
The chapter reviews certain topics in outline. It starts with a brief account of the nature of surgery. This is followed by a short account of modern management of cranial trauma including the evolution of notions of anatomy and pathophysiology. It is emphasized that these principles are and must be irrelevant to the management of cranial trauma in the period covered in this book from Hippocrates to the end of the 18th century. Historical errors arising from assuming modern principles applied in historical practice are mentioned. Finally, the risks inherent in accepting images without questioning their authorship and provenance is also mentioned.
Topics: Humans; Craniocerebral Trauma
PubMed: 38609288
DOI: 10.1016/bs.pbr.2024.02.001 -
BMJ (Clinical Research Ed.) Jun 2023
PubMed: 37385652
DOI: 10.1136/bmj.p1458 -
Journal of Biomedical Semantics Jul 2023Clinical decision support systems have been widely deployed to guide healthcare decisions on patient diagnosis, treatment choices, and patient management through...
BACKGROUND
Clinical decision support systems have been widely deployed to guide healthcare decisions on patient diagnosis, treatment choices, and patient management through evidence-based recommendations. These recommendations are typically derived from clinical practice guidelines created by clinical specialties or healthcare organizations. Although there have been many different technical approaches to encoding guideline recommendations into decision support systems, much of the previous work has not focused on enabling system generated recommendations through the formalization of changes in a guideline, the provenance of a recommendation, and applicability of the evidence. Prior work indicates that healthcare providers may not find that guideline-derived recommendations always meet their needs for reasons such as lack of relevance, transparency, time pressure, and applicability to their clinical practice.
RESULTS
We introduce several semantic techniques that model diseases based on clinical practice guidelines, provenance of the guidelines, and the study cohorts they are based on to enhance the capabilities of clinical decision support systems. We have explored ways to enable clinical decision support systems with semantic technologies that can represent and link to details in related items from the scientific literature and quickly adapt to changing information from the guidelines, identifying gaps, and supporting personalized explanations. Previous semantics-driven clinical decision systems have limited support in all these aspects, and we present the ontologies and semantic web based software tools in three distinct areas that are unified using a standard set of ontologies and a custom-built knowledge graph framework: (i) guideline modeling to characterize diseases, (ii) guideline provenance to attach evidence to treatment decisions from authoritative sources, and (iii) study cohort modeling to identify relevant research publications for complicated patients.
CONCLUSIONS
We have enhanced existing, evidence-based knowledge by developing ontologies and software that enables clinicians to conveniently access updates to and provenance of guidelines, as well as gather additional information from research studies applicable to their patients' unique circumstances. Our software solutions leverage many well-used existing biomedical ontologies and build upon decades of knowledge representation and reasoning work, leading to explainable results.
Topics: Humans; Decision Support Systems, Clinical; Software; Knowledge Bases; Biological Ontologies; Publications
PubMed: 37464259
DOI: 10.1186/s13326-023-00285-9 -
BMJ (Clinical Research Ed.) Oct 2023
Topics: Humans; Social Identification; Qualitative Research; Biomedical Research; Students, Medical
PubMed: 37871940
DOI: 10.1136/bmj.p2410 -
BMJ (Clinical Research Ed.) Aug 2023
Topics: Humans; Whistleblowing; Patient Safety
PubMed: 37643769
DOI: 10.1136/bmj.p1972 -
Sensors (Basel, Switzerland) Jul 2023Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that... (Review)
Review
Data provenance means recording data origins and the history of data generation and processing. In healthcare, data provenance is one of the essential processes that make it possible to track the sources and reasons behind any problem with a user's data. With the emergence of the General Data Protection Regulation (GDPR), data provenance in healthcare systems should be implemented to give users more control over data. This SLR studies the impacts of data provenance in healthcare and GDPR-compliance-based data provenance through a systematic review of peer-reviewed articles. The SLR discusses the technologies used to achieve data provenance and various methodologies to achieve data provenance. We then explore different technologies that are applied in the healthcare domain and how they achieve data provenance. In the end, we have identified key research gaps followed by future research directions.
Topics: Biomedical Research; Delivery of Health Care
PubMed: 37514788
DOI: 10.3390/s23146495 -
BMJ (Clinical Research Ed.) Apr 2024
Topics: Humans; Canada; Insurance, Pharmaceutical Services; COVID-19
PubMed: 38649176
DOI: 10.1136/bmj.q887