Sleep disturbances are common in various neurological pathologies, including amyotrophic lateral sclerosis (ALS), multiple system atrophy (MSA), hereditary ataxias, Huntington’s disease (HD), progressive supranuclear palsy (PSP), and dementia with Lewy bodies (DLB). This article reviews the prevalence and characteristics of sleep disorders in these conditions, highlighting their impact on patients’ quality of life and disease progression. Sleep-related breathing disorders, insomnia, restless legs syndrome (RLS), periodic limb movement syndrome (PLMS), and rapid eye movement sleep behavior disorder (RBD) are among the common sleep disturbances reported. Both pharmacological and non-pharmacological interventions play crucial roles in managing sleep disturbances and enhancing overall patient care.

(1) Background: Perilla frutescens (L.) Britt. is an important pharmaceutical crop that remains a focus point for researchers worldwide due to its complex phytochemical constituents, medicinal effects, and nutraceutical properties. The literature data are based on animal and cell culture studies, so the clinical evidence for the therapeutic effects is poorly outlined. The aim of this review was to provide an updated and thorough understanding of Perilla frutescens applications in clinical practice using data derived from human studies, and to outline the potential directions and perspectives for further studies on this crop. (2) Methods: Medline, Embase, and Cochrane databases were used to find relevant studies. All interventional studies that evaluated the effect of Perilla frutescens in human subjects were assessed. (3) Results: The main perspectives that can be contoured from the presented literature evaluation are an important clinical effect of Perilla frutescens extracts on allergic rhinoconjuctivitis, especially in young populations, a potent hypolipemiant effect that, in conjunction with increased serum biological antioxidant potential, determines significant improvements in cognitive function and a wide variety of miscellaneous clinical effects that need further exploration. (4) Conclusions: Supplementary research is needed in order to demonstrate the therapeutic effects of Perilla frutescens in controlled clinical settings.

(1) Background: The identification of patients at risk for hepatitis B and C viral infection is a challenge for the clinicians and public health specialists. The aim of this study was to evaluate and compare the predictive performances of four machine learning-based models for the prediction of HBV and HCV status. (2) Methods: This prospective cohort screening study evaluated adults from the North-Eastern and South-Eastern regions of Romania between January 2022 and November 2022 who underwent viral hepatitis screening in their family physician’s offices. The patients’ clinical characteristics were extracted from a structured survey and were included in four machine learning-based models: support vector machine (SVM), random forest (RF), naïve Bayes (NB), and K nearest neighbors (KNN), and their predictive performance was assessed. (3) Results: All evaluated models performed better when used to predict HCV status. The highest predictive performance was achieved by KNN algorithm (accuracy: 98.1%), followed by SVM and RF with equal accuracies (97.6%) and NB (95.7%). The predictive performance of these models was modest for HBV status, with accuracies ranging from 78.2% to 97.6%. (4) Conclusions: The machine learning-based models could be useful tools for HCV infection prediction and for the risk stratification process of adult patients who undergo a viral hepatitis screening program.

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.

Cancer is a leading cause of death globally, claiming millions of lives each year. Despite the availability of numerous anticancer drugs, the need for new treatment options remains essential. Many current therapies come with significant toxicity, lead to various side effects, or do not consistently deliver the expected therapeutic results. Purines and pyrimidines are fundamental building blocks of nucleic acids and play crucial roles in cellular metabolism and signaling. Recent advances in medicinal chemistry have led to the development and synthesis of various derivatives that exhibit selective cytotoxic effects against cancer cells while minimizing toxicity to healthy tissues. Purine and pyrimidine scaffolds, due to their well-established biological roles and structural versatility, have emerged as key pharmacophoric fragments in anticancer drug discovery. In recent years, the rational design of hybrid molecules incorporating these heterocycles has shown promise in overcoming drug resistance, improving target selectivity, and enhancing pharmacological profiles. Purine and pyrimidines scaffolds hold significant potential as foundations for novel antitumor drugs, with established representatives in cancer treatment, including 5-fluorouracil, cladribine, capecitabine, and several others. In addition, the article discusses the challenges and future developments of purine and pyrimidine derivatives and hybrid molecules as antitumor drugs and emphasizes the need for continued research to optimize their effectiveness and reduce side effects. Overall, the innovative use of these compounds represents a major advance in targeted cancer therapy and holds promise for improving the therapeutic efficacy of malignant diseases.

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.