Cardiovascular disease is most frequently caused by the development and progression of atherosclerosis. When coronary arteries are afflicted, and the stenoses caused by atherosclerotic plaques are severe enough, the metabolic supply-and-offer balance is disturbed, leading to myocardial ischemia. If atherosclerotic plaques become unstable and local thrombosis develops, a myocardial infarction occurs. Sometimes, myocardial ischemia and infarction may result in significant and irreversible heart failure. To prevent severe complications, such as acute coronary syndromes and ischemia-related heart failure, extensive efforts have been made for developing biomarkers that would help identify patients at increased risk for cardiovascular events. In this two-part study, we attempted to provide a review of existing knowledge of blood biomarkers that may be used in this setting. The first part of this work was dedicated to conventional biomarkers, which are already used in clinical practice. In the second part, here presented, we discuss emerging biomarkers which have not yet become mainstream.

Biomarkers are crucial in cancer diagnostics, prognosis, and surveillance. Extensive research has been dedicated to identifying biomarkers that are broadly applicable across multiple cancer types and can be easily obtained from routine investigations such as blood cell counts. One such biomarker, the neutrophil-to-lymphocyte ratio (NLR), has been established as a prognostic marker in cancer. However, due to the dynamic nature of cancer diagnosis and treatment, periodic updates are necessary to keep abreast of the vast amount of published data. In this review, we searched the PubMed database and analyzed and synthesized recent literature (2018–February 2024) on the role of NLR in predicting clinical outcomes in nonhematologic malignancies. The search was conducted using the PubMed database. We included a total of 88 studies, encompassing 28,050 human subjects, and categorized the findings into four major groups: gastrointestinal cancer, cancers of the urinary tract and reproductive system, lung cancer, and breast cancer. Our analysis confirms that NLR is a reliable prognostic indicator in cancer, and we discuss the specific characteristics, limitations, and exceptions associated with its use. The review concludes with a concise Q&A section, presenting the most relevant take-home messages in response to five key practical questions on this topic.

Type 1 diabetes mellitus (T1D) is an incurable autoimmune disease characterized by the destruction of pancreatic islet cells, resulting in lifelong dependency on insulin treatment. There is an abundance of review articles addressing the prediction of T1D; however, most focus on the presymptomatic phases, specifically stages 1 and 2. These stages occur after seroconversion, where therapeutic interventions primarily aim to delay the onset of T1D rather than prevent it. This raises a critical question: what happens before stage 1 in individuals who will eventually develop T1D? Is there a “stage 0” of the disease, and if so, how can we detect it to increase our chances of truly preventing T1D? In pursuit of answers to these questions, this narrative review aimed to highlight recent research in the field of early detection and prediction of T1D, specifically focusing on biomarkers that can predict T1D before the onset of islet autoimmunity. Here, we have compiled influential research from the fields of epigenetics, omics, and microbiota. These studies have identified candidate biomarkers capable of predicting seroconversion from very early stages to several months prior, suggesting that the prophylactic window begins at birth. As the therapeutic landscape evolves from treatment to delay, and ideally from delay to prevention, it is crucial to both identify and validate such “stage 0” biomarkers predictive of islet autoimmunity. In the era of precision medicine, this knowledge will enable early intervention with the potential for delaying, modifying, or completely preventing autoimmunity and T1D in at-risk children.

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by progressive loss of motor neurons. Emerging evidence suggests a potential link between metabolic dysregulation and ALS pathogenesis. This study aimed to investigate the relationship between metabolic hormones and disease progression in ALS patients. A cross-sectional study was conducted involving 44 ALS patients recruited from a tertiary care center. Serum levels of insulin, total amylin, C-peptide, active ghrelin, GIP (gastric inhibitory peptide), GLP-1 active (glucagon-like peptide-1), glucagon, PYY (peptide YY), PP (pancreatic polypeptide), leptin, interleukin-6, MCP-1 (monocyte chemoattractant protein-1), and TNFα (tumor necrosis factor alpha) were measured, and correlations with ALSFRS-R, evolution scores, and biomarkers were analyzed using Spearman correlation coefficients. Subgroup analyses based on ALS subtypes, progression pattern of disease, and disease progression rate patterns were performed. Significant correlations were observed between metabolic hormones and ALS evolution scores. Insulin and amylin exhibited strong correlations with disease progression and clinical functional outcomes, with insulin showing particularly robust associations. Other hormones such as C-peptide, leptin, and GLP-1 also showed correlations with ALS progression and functional status. Subgroup analyses revealed differences in hormone levels based on sex and disease evolution patterns, with male patients showing higher amylin and glucagon levels. ALS patients with slower disease progression exhibited elevated levels of amylin and insulin. Our findings suggest a potential role for metabolic hormones in modulating ALS progression and functional outcomes. Further research is needed to elucidate the underlying mechanisms and explore the therapeutic implications of targeting metabolic pathways in ALS management.

Atherosclerosis is the main cause of cardiovascular disease worldwide. The progression of coronary atherosclerosis leads to coronary artery disease, with impaired blood flow to the myocardium and subsequent development of myocardial ischemia. Acute coronary syndromes and post-myocardial infarction heart failure are two of the most common complications of coronary artery disease and are associated with worse outcomes. In order to improve the management of patients with coronary artery disease and avoid major cardiovascular events, several risk assessment tools have been developed. Blood and imaging biomarkers, as well as clinical risk scores, are now available and validated for clinical practice, but research continues. The purpose of the current paper is to provide a review of recent findings regarding the use of humoral biomarkers for risk assessment in patients with heart disease.

Objective : Peripheral blood mononuclear cells (PBMC) are extremely important in the body’s immune response. Their isolation represents a major step in many immunological experiments. In this two phase study, we aimed to establish an optimum protocol for PBMC isolation by density-gradient centrifugation. Methods : During Phase-1, we compared two commercially available PBMC isolation protocols, Stemcell Technologies (ST) and Miltenyi Biotec (MB), in terms of PBMC recovery and purity. Twelve blood samples were assigned to each protocol. Each sample was divided in three subsamples of 1ml, 2ml and 3ml in order to assess the influence of blood sample volume on isolation performance. During Phase-2, a hybrid protocol was similarly tested, processing six blood samples. Additionally, we performed a flow cytometric analysis using an Annexin-V/Propidium-Iodide viability staining protocol. Results : Phase-1 results showed that, for all subsample volumes, ST had superior PBMC recovery (mean values: 56%, 80% and 87%, respectively) compared to MB (mean values: 39%, 54% and 43%, respectively). However, platelet removal was significantly higher for MB (mean value of 96.8%) than for ST (mean value of 75.2%). Regarding granulocyte/erythrocyte contamination, both protocols performed similarly, yielding high purity PBMC (mean values: 97.3% for ST and 95.8% for MB). During Phase-2, our hybrid protocol yielded comparable results to MB, with an average viability of 89.4% for lymphocytes and 16.9% for monocytes. Conclusions : ST yields higher cell recovery rates and MB excels at platelet removal, while the hybrid protocol is highly similar to MB. Both cell recovery and viability increase with blood sample volume.