Background: Heart failure is a global major healthcare problem with millions of hospitalizations annually and with a very high mortality. There is an increased interest in finding new and reliable biomarkers for the diagnostic, prognostic and therapeutic guidance of patients hospitalized for acute heart failure; Our review aims to summarize in an easy-to-follow flow recent relevant research evaluating the possible use and the clinical value of measuring CA 125 serum levels in acute HF. Methods: A thorough search in the main international databases identified a relevant pool of 170 articles, providing recently published data for this narrative review that used PRISMA guidelines. Results: There are data to sustain the role of carbohydrate antigen 125 (CA 125), a worldwide used marker of ovarian cancer, in patients with heart failure. Several studies have shown links between CA 125 levels and congestion seen in acute heart failure, high mortality and readmission rates at 6 months follow-up after discharge from acute heart failure and also a role of CA 125 in the guidance of heart failure therapy. There are also clinical trials that showed that several particularities of CA 125 make it even better than N-terminal pro b-type natriuretic peptide (NT-pro BNP)—a classical and more utilized marker of heart failure) in several scenarios of acute heart failure. Conclusions: Although the mechanism behind the upregulation of serum CA 125 in patients with congestive HF has not been confirmed nor fully understood.

Artificial intelligence (AI) is a reality of our times, and it has been successfully implemented in all fields, including medicine. As a relatively new domain, all efforts are directed towards creating algorithms applicable in most medical specialties. Pathology, as one of the most important areas of interest for precision medicine, has received significant attention in the development and implementation of AI algorithms. This focus is especially important for achieving accurate diagnoses. Moreover, immunohistochemistry (IHC) serves as a complementary diagnostic tool in pathology. It can be further augmented through the application of deep learning (DL) and machine learning (ML) algorithms for assessing and analyzing immunohistochemical markers. Such advancements can aid in delineating targeted therapeutic approaches and prognostic stratification. This article explores the applications and integration of various AI software programs and platforms used in immunohistochemical analysis. It concludes by highlighting the application of these technologies to pathologies such as breast, prostate, lung, melanocytic proliferations, and hematologic conditions. Additionally, it underscores the necessity for further innovative diagnostic algorithms to assist physicians in the diagnostic process.

Sweet syndrome (SS) is a rare disease described as a febrile neutrophilic dermatosis with acute onset, the pathogenesis of which has not yet been elucidated. The syndrome is characterized by the sudden onset of erythematous infiltrated papules or plaques located on the upper body and is associated with fever, leukocytosis and neutrophilia. The lesions show a dense dermal infiltration with mature neutrophils. The condition is responsive to systemic steroids. The central nervous system, bones, muscles, eyes, ears, mouth, heart, lung, liver, kidneys, intestines, and spleen may be affected by SS as extracutaneous manifestations. More and more cases have been found to be associated with malignancies, particularly myelodysplastic syndrome, and, less frequently, other hematologic malignancies or solid tumors. Approximately 21% of patients with SS have an associated malignancy and up to 80% of MASS cases are associated with hematological diseases, predominantly myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Myelodysplastic syndrome is a clonal disease of the bone marrow characterized by inefficient hematopoiesis, dysplasia of the bone marrow and peripheral cytopenias. Affected patients have a high risk of leukemic transformation. After analyzing later studies and current practical aspects regarding MDS-related SS, we suggest an algorithm for evaluating these patients.

Heart failure is one of the main morbidity and mortality factors in the general population and especially in elderly patients. Thus, at the European level, the prevalence of heart failure is 1% in people under 55 years of age but increases to over 10% in people over 70 years of age. The particularities of the elderly patient, which make the management of heart failure difficult, are the presence of comorbidities, frailty, cognitive impairment and polypharmacy. However, elderly patients are under-represented in clinical trials on the diagnosis and treatment of heart failure. The need for complementary methods (biomarkers) for differential and early diagnosis of heart failure is becoming more and more evident, even in its subclinical stages. These methods need to have increased specificity and sensitivity and be widely available. Natriuretic peptides, in particular B-type natriuretic peptide (BNP) and its fraction NTproBNP, have gained an increasingly important role in the screening, diagnosis and treatment of heart failure in recent years.

Basal cell carcinoma (BCC) is a malignant tumor with a rising incidence and is the beneficiary of several innovative evaluation techniques. Histopathology remains the gold standard for assessment, having the possibility of addressing multiple high-risk factors such as perineural invasion (PNI). The current study included a number of 244 BCC patients and targeted the identification of positive PNI and its suggestive signs, and whether they correlated or not with other high-risk tumor signs. PNI was found in 20.1% of patients, with 30.7% of patients having perineural chronic inflammation (PCI), which is a suggestive sign of PNI. PNI was also found in larger tumors, with deeper Clark levels, in high-risk BCCs and high-grade tumors. PNI and PCI are both important for pathology reporting, aiding in treatment choice and further patient management, with possibly positive outcomes concerning morbidity and mortality.

Heart failure is a global major healthcare problem with millions of hospitalizations annually and with a very high mortality. There is an increased interest in finding new and reliable biomarkers for the diagnostication, prognostication and therapeutical guidance of patients hospitalized for acute heart failure. There is data to sustain the role of CA 125, a worldwide used marker of ovarian cancer, in patients with heart failure. Several studies have shown links between CA 125 levels and congestion seen in acute heart failure, high mortality and readmission rates at 6 months follow up after discharge from acute heart failure and also a role of CA 125 in the guidance of heart failure therapy. There are also clinical trials that showed that several particularities of CA 125 make it even better than NTpro BNP ( a classical and more utilised marker of heart failure) in several scenarios of acute heart failure.