Advances in clinical chemistry最新文献

The detection of volatile organic compounds (VOCs) in breath has become a potential method for early cancer screening. Although this approach has attracted increasing attention from the both scientific and medical communities, it has not received appreciable traction in the clinical setting. There are two main obstacles. One involves the identification of specific biomarkers or combinations thereof especially in early cancer. The other is the lack the specialized equipment for breath analysis having the appropriate sensitivity and specificity. Using metabolomics, this chapter examines the research strategies involving gas biomarkers in cancer patient breath, cancer cell gas metabolites and synthetic biomarkers. We briefly explore gas biomarkers of seven cancers and introduce principles of detection and clinical application. Large analytical instruments and small sensor technology are highlighted. Challenges to VOC analysis are presented including clinical use, extraction and detection, miniaturization efforts and examination of metabolic VOC pathways. Finally, VOCs in cancer and in exhaled breath detection technology are summarized and future prospects explored.

Posttraumatic stress disorder (PTSD) is characterized by exposure to traumatic events and involves symptom domains such as intrusive thoughts, avoidant behaviors, negative mood, and cognitive dysfunction. The disorder can be chronic and debilitating, and the heterogenous nature and varied presentation of PTSD has afforded difficulty in determining efficacious treatment. The ability to identify biomarkers for PTSD risk, prognosis, or for the purposes of treatment, would be highly valuable. There is evidence for peripheral biomarkers related to the hypothalamic-pituitary-adrenal axis, the immune system, neurotransmitters and neurohormones, while genome and epigenome wide association studies have identified genes of interest relating to neurocircuitry, monoaminergic function, and the immune system. Importantly, however, reproducibility is a persistent issue. Considerations for future research include the need for well-powered and well-designed studies to determine directionality, in addition to considering biomarkers as they relate to symptom domains and the spectrum of symptom severity rather than dichotomous diagnostic outcomes. We conclude by recommending the staging of biological processes and PTSD symptoms, from subsyndromal to chronic, which could eventually facilitate selection of personalized treatment interventions for individuals with PTSD, in addition to serving as a future framework for biomarker data.

Over the last four decades, cardiac natriuretic peptides have changed our understanding of patients with chronic heart failure. From the discovery of the heart as an endocrine organ with its own hormones and receptors, the biochemistry and physiology of the system have been translated into useful biomarkers and drug targets in cardiovascular disease. The purpose of this review is to provide medical researchers not working in the field with a simple introduction to the system and its molecular components, its quantitative methods, and its physiology and pathophysiology. The hope is that this overview may help to broaden the knowledge of the endocrine heart with the intent that researchers in other areas of medical research will be inspired to seek new facets of the system, both in translational science and in clinical practice.

Physiologically, extracellular vesicles (EVs) have been implicated as crucial mediators of immune response, cell homeostasis, angiogenesis, cell differentiation and growth, and tissue repair. In heart failure (HF) they may act as regulators of cardiac remodeling, microvascular inflammation, micro environmental changes, tissue fibrosis, atherosclerosis, neovascularization of plaques, endothelial dysfunction, thrombosis, and reciprocal heart-remote organ interaction. The chapter summaries the nomenclature, isolation, detection of EVs, their biologic role and function physiologically as well as in the pathogenesis of HF. Current challenges to the utilization of EVs as diagnostic and predictive biomarkers in HF are also discussed.

Mitochondria, as an endosymbiont of eukaryotic cells, controls multiple cellular activities, including respiration, reactive oxygen species production, fatty acid synthesis, and death. Though the majority of functional mitochondrial proteins are translated through a nucleus-controlled process, very few of them (∼10%) are translated within mitochondria through their own machinery. Germline and somatic mutations in mitochondrial and nuclear DNA significantly impact mitochondrial homeostasis and function. Such modifications disturbing mitochondrial biogenesis, metabolism, or mitophagy eventually resulted in cellular pathophysiology. In this chapter, we discussed the impact of mitochondria and its dysfunction on several non-communicable diseases like cancer, diabetes, neurodegenerative, and cardiovascular problems. Mitochondrial dysfunction and its outcome could be screened by currently available omics-based techniques, flow cytometry, and high-resolution imaging. Such characterization could be evaluated as potential biomarkers to assess the disease burden and prognosis.

Cortisol, a stress hormone, plays a crucial role in regulating metabolic, hemodynamic, inflammatory, and behavioral processes. Its secretion is governed by the hypothalamic-pituitary-adrenal axis. However, prolonged activation of this axis and increased cortisol bioavailability in tissues can result in detrimental metabolic effects. Chronic exposure to excessive cortisol is associated with insulin resistance and visceral obesity, both significant contributors to metabolic syndrome. This review delves into the regulation of the hypothalamic-pituitary-adrenal axis, the molecular mechanisms underlying cortisol synthesis and its actions, as well as the key factors influencing cortisol bioavailability. Furthermore, it provides a summary of available clinical research data on the involvement of cortisol in metabolic syndrome, alongside a discussion on the various biomatrices used for cortisol measurement in clinical settings.

Fibrinogen is the primary precursor protein for the fibrin clot, which is the final target of blood clotting. It is also an acute phase reactant that can vary under physiologic and inflammatory conditions. Disorders in fibrinogen concentration and/or function have been variably linked to the risk of bleeding and/or thrombosis. Fibrinogen assays are commonly used in the management of bleeding as well as the treatment of thrombosis. This chapter examines the structure of fibrinogen, its role in hemostasis as well as in bleeding abnormalities and measurement thereof with respect to clinical management.

The blood-brain barrier (BBB) is a dynamic interface that regulates the exchange of molecules and cells between the brain parenchyma and the peripheral blood. The BBB is mainly composed of endothelial cells, astrocytes and pericytes. The integrity of this structure is essential for maintaining brain and spinal cord homeostasis and protection from injury or disease. However, in various neurological disorders, such as traumatic brain injury, Alzheimer's disease, and multiple sclerosis, the BBB can become compromised thus allowing passage of molecules and cells in and out of the central nervous system parenchyma. These agents, however, can serve as biomarkers of BBB permeability and neuronal damage, and provide valuable information for diagnosis, prognosis and treatment. Herein, we provide an overview of the BBB and changes due to aging, and summarize current knowledge on biomarkers of BBB disruption and neurodegeneration, including permeability, cellular, molecular and imaging biomarkers. We also discuss the challenges and opportunities for developing a biomarker toolkit that can reliably assess the BBB in physiologic and pathophysiologic states.

Digital biomarker (DB) assessments provide objective measures of daily life tasks and thus hold promise to improve diagnosis and monitoring of Parkinson's disease (PD) patients especially those with advanced stages. Data from DB studies can be used in advanced analytics such as Artificial Intelligence and Machine Learning to improve monitoring, treatment and outcomes. Although early development of inertial sensors as accelerometers and gyroscopes in smartphones provided encouraging results, the use of DB remains limited due to lack of standards, harmonization and consensus for analytical as well as clinical validation. Accordingly, a number of clinical trials have been developed to evaluate the performance of DB vs traditional assessment tools with the goal of monitoring disease progression, improving quality of life and outcomes. Herein, we update current evidence on the use of DB in PD and highlight potential benefits and limitations and provide suggestions for future research study.