Advances in clinical chemistry最新文献

Non-coding RNAs (ncRNAs) belong to a class of untranslated nucleic acids involved in regulation of gene expression. ncRNAs are categorized as small (<200 ribonucleotides in length), i.e., microRNAs (miRNAs), and long ncRNAs (lncRNAs) (200 to thousands of ribonucleotides in length) and circular RNAs (circRNAs). In contrast to miRNAs, the roles of lncRNAs in general and circRNAs in bone metabolism specifically are not well understood. As such, a comprehensive understanding of these RNA species in bone turnover could be of great value in the development of new diagnostic tools and therapeutic targets. Unfortunately, measurement of these unique RNAs lacks standardization, a component critical to clinical translation. This review examines the potential role of lncRNA and circRNA as bone biomarkers, the need for validated and standardized measurement and challenges thereof.

The World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a global pandemic in March 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is the reference technique for molecular diagnosis of SARS-CoV-2 infection. The SARS-CoV-2 virus is constantly mutating, and more transmissible variants have emerged, making genomic surveillance a crucial tool for investigating virus transmission dynamics, detecting novel genetic variants, and assessing mutation impact. The S gene, which encodes the spike protein, is frequently mutated, and it plays an important role in transmissibility. Spike protein mutations affect infectivity and vaccine effectiveness. SARS-CoV-2 variants are tracked using whole genome sequencing (WGS) and S-gene analysis. WGS, Sanger sequencing, and many S-gene-targeted RT-PCR methods have been developed. WGS and Sanger sequencing are standard methods for detecting mutations and can be used to identify known and unknown mutations. Melting curve analysis, endpoint genotyping assay, and S-gene target failure are used in the RT-PCR-based method for the rapid detection of specific mutations in SARS-CoV-2 variants. Therefore, these assays are suitable for high-throughput screening. The combinatorial use of RT-PCR-based assays, Sanger sequencing, and WGS enables rapid and accurate tracking of SARS-CoV-2 variants. In this review, we described RT-PCR-based detection and surveillance techniques for SARS-CoV-2.

Familial hypercholesterolemia (FH), a semi-dominant genetic disease affecting more than 25 million people worldwide, is associated with severe hypercholesterolemia and premature atherosclerotic cardiovascular disease. Over the last decade, advances in data analysis, screening, diagnosis and cardiovascular risk stratification has significantly improved our ability to deliver precision medicine for these patients. Furthermore, recent updates on guideline recommendations and new therapeutic approaches have also proven to be highly beneficial. It is anticipated that both ongoing and upcoming clinical trials will offer further insights for the care and treatment of FH patients.

Minimal residual disease (MRD) has been defined as a very small numbers of cancer cells that remain in the body after curative treatment. Its presence or absence will ultimately determine prognosis. With the introduction of new technologies the presence of MRD in patients with solid tumours can be detected and characterized. As MRD predicts future relapse, be it early or late treatment failure, in an otherwise asymptomatic patient its treatment and when to start treatment remains to be determined. Thus the concepts of personalized medicine using different biomarkers to classify the biological properties of MRD maybe come possible. Based on this determinations it may be possible to use targeted therapies rather than all patients with the same type of cancer receiving a standard treatment. However, it is important to understand the limitations of the different technologies, what these techniques are detecting and how they may help in the treatment of patients with cancer. The majority of published studies are in patients with metastatic cancer and there are few reports in patients with MRD. In this chapter the concept of MRD, the methods used to detect it and what treatments may be effective based on the biological characteristics of the tumour cells as determined by different biomarkers is reviewed. MRD depends on the phenotypic properties of the tumour cells to survive in their new environment and the anti-tumour immune response. This is a dynamic process and changes with time in the wake of immunosuppression caused by the tumour cells and/or the effects of treatment to select resistant tumour cells. With the use of biomarkers to typify the characteristics of MRD and the development of new drugs a personalized treatment can be designed rather than all patients given the same treatment. Patients who are initially negative for MRD may not require further treatment with liquid biopsies used to monitor the patients during follow-up in order to detect those patients who may become MRD positive. The liquid biopsy used during the follow up of MRD positive patients can be used to detect changes in the biological properties of the tumour cells and thus may need treatment changes to overcome tumour cell resistance.

Soluble urokinase plasminogen activator receptor (suPAR), the soluble counterpart of urokinase plasminogen activator receptor, is found in the circulation at various levels. suPAR and its parent molecule, cell surface uPAR, exhibit similar structure and extracellular functional roles facilitating fibrinolysis, cellular adhesion, and migration. Studies have assessed the correlation between suPAR in cardiovascular disease (CVD). It is postulated that suPAR may serve as an indicator of inflammatory activation and burden during CVD progression. Increased suPAR independently predicts poorer outcomes in acute coronary syndromes, in heart failure, as well as in coronary artery disease and atherosclerosis. To guide translation into clinical utization, suPAR has been assessed in numerous CVD settings for improved risk discrimination independently or in association with established traditional risk factors. Whilst the involvement of suPAR has been explored in other diseases such as kidney diseases and cancer, there is only emerging evidence of suPAR's mechanistic involvement in cardiovascular disease. In this review, we provide a background into suPAR and its potential role as a biomarker in CVD.

Osteopontin (OPN) is a heavily post-translationally modified protein with a molecular weight of 44-70 kDa, depending on the degree of glycosylation. OPN is involved in various biological processes, including bone remodeling, immune response, cell adhesion, migration, and survival. It is essential for controlling osteoclast and osteoblast activity for maintaining bone mass and bone strength. Additionally, OPN has been linked to cardiovascular, inflammatory illnesses, as well as the onset and progression of cancer. OPN is a multifunctional protein that can interact with a variety of cell surface receptors, such as integrins, CD44, the urokinase-type plasminogen activator receptor (uPAR), as well as extracellular matrix (ECM) components (e.g. collagen and hydroxyapatite). These interactions contribute to its wide range of biological functions in general and has significant implications for bone biology, immunology and cancer, specifically. In this chapter, we summarize the structure of OPN with a focus on its molecular mechanisms of action in various cancers.

Chronic obstructive pulmonary disease (COPD), a global healthcare and socioeconomic burden, is a multifaceted respiratory disorder that results in substantial decline in health status and life quality. Acute exacerbations of the disease contribute significantly to increased morbidity and mortality. Consequently, the identification of reliable and effective biomarkers for rapid diagnosis, prediction, and prognosis of exacerbations is imperative. In addition, biomarkers play a crucial role in monitoring responses to therapeutic interventions and exploring innovative treatment strategies. Although established markers such as CRP, fibrinogen and neutrophil count are routinely used, a universal marker is lacking. Fortunately, an increasing number of studies based on next generation analytics have explored potential biomarkers in COPD. Here we review those advances and the need for standardized validation studies in the appropriate clinical setting.

The ever-increasing life expectancy of the global population introduces a critical perspective on the impact of aging as an immutable cardiovascular risk factor, particularly manifesting in the alterations observed in the pulmonary artery (PA). Mechanisms contributing to aging-induced changes in PA include endothelial dysfunction, chronic inflammation, and structural changes in the arterial wall over time. These alterations extend beyond mere elasticity, exerting profound effects on pulmonary hemodynamics. The propensity of PAs to develop atherosclerotic plaques underscores an intriguing facet of vascular aging, although the available literature is currently insufficient to comprehensively assess their true incidence. While recognizing the inherent risk of periprocedural complications, right heart catheterization (RHC) stands out as the gold standard for precise hemodynamic evaluation. Echocardiography, a widely employed method, proves valuable for screening pulmonary hypertension (PH), yet falls short of diagnostic capability. Technological advancements usher in a new era with non-invasive modalities such as cardiac magnetic resonance (CMR) imaging emerging as promising tools. These innovations demonstrate their prowess in providing accurate assessments of PA stiffness and hemodynamics, offering a glimpse into the future landscape of diagnostic methodologies. As we navigate the intersection of aging and pulmonary vascular health, this review aims to address mechanisms and techniques for assessing PA aging, highlighting the need for comprehensive assessments to guide clinical decision making in an increasingly aging population.

Gout and hyperuricemia (HU) have generated immense attention due to increased prevalence. Gout is a multifactorial metabolic and inflammatory disease that occurs when increased uric acid (UA) induce HU resulting in monosodium urate (MSU) crystal deposition in joints. However, gout pathogenesis does not always involve these events and HU does not always cause a gout flare. Treatment with UA-lowering therapeutics may not prevent or reduce the incidence of gout flare or gout-associated comorbidities. UA exhibits both pro- and anti-inflammation functions in gout pathogenesis. HU and gout share mechanistic and metabolic connections at a systematic level, as shown by studies on associated comorbidities. Recent studies on the interplay between UA, HU, MSU and gout as well as the development of HU and gout in association with metabolic syndromes, non-alcoholic fatty liver disease (NAFLD), and cardiovascular, renal and cerebrovascular diseases are discussed. This review examines current and potential therapeutic regimens and illuminates the journey from disrupted UA to gout.

Patient-Based Real-Time Quality Control involves monitoring an assay using patient samples rather than external material. If the patient population does not change, then a shift in the long-term assay population results represents the introduction of a change in the assay. The advantages of this approach are that the sample(s) are commutable, it is inexpensive, the rules are simple to interpret and there is virtually continuous monitoring of the assay. The disadvantages are that the laboratory needs to understand their patient population and how they may change during the day, week or year and the initial change of mindset required to adopt the system. The concept is not new, having been used since the 1960s and widely adopted on hematology analyzers in the mid-1970s. It was not widely used in clinical chemistry as there were other stable quality control materials available. However, the limitations of conventional quality control approaches have become more evident. There is a greater understanding of how to collect and use patient data in real time and a range of powerful algorithms which can identify changes in assays. There are more assays on more samples being run. There is also a greater interest in providing a theoretical basis for the validation and integration of these techniques into routine practice.