Anthracyclines, especially doxorubicin and daunorubicin, are the drugs of first choice in the treatment of patients with hematologic malignancies, soft-tissue sarcomas, and solid tumors. Unfortunately, the use of anthracyclines is limited by their dose-dependent and cumulative cardiotoxicity. The molecular mechanism responsible for anthracycline-induced cardiotoxicity remains poorly understood, although experimental and clinical studies have shown that oxidative stress plays the main role. Hence, antioxidant agents, especially dexrazoxane, and also other drug classes (statins, β-blockers) proved to have a beneficial effect in protecting against anthracycline-induced cardiotoxicity. According to previous clinical trials, the major high-risk factors for anthracycline-induced cardiotoxicity are age, body weight, female gender, radiotherapy, and other diseases such as Down syndrome, familial dilated cardiomyopathy, diabetes and hypertension. Consequently, further studies are needed to elucidate the molecular pathogenesis of anthracycline-induced cardiotoxicity and also to discover new cardioprotective agents against anthracycline-induced cardiotoxicity.

Pain is one of the main problems for modern society and medicine, being the most common symptom described by almost all patients. When pain becomes chronic, the life of the patients is dramatically affected, being associated with significant emotional distress and/or functional disability. A complex biopsychosocial evaluation is necessary to better understand chronic pain, where good results can be obtained through interconnected biological, psychological, and social factors. The aim of this study was to find the most relevant articles existent in the PubMed database, one of the most comprehensive databases for medical literature, comprising dietary patterns to alleviate chronic pain. Through a combined search using the keywords “chronic pain” and “diet” limited to the last 10 years we obtained 272 results containing the types of diets used for chronic pain published in the PubMed database. Besides classical and alternative methods of treatment described in literature, it was observed that different diets are also a valid solution, due to many components with antioxidant and anti-inflammatory qualities capable to influence chronic pain and to improve the quality of life. Thirty-eight clinical studies and randomized controlled trials are analyzed, in an attempt to characterize present-day dietary patterns and interventions to alleviate chronic pain.

Background and Objectives: The consumption of dietary supplements has increased over the last decades among pregnant women, becoming an efficient resource of micronutrients able to satisfy their nutritional needs during pregnancy. Furthermore, gestational drug administration might be necessary to treat several pregnancy complications such as hypertension. Folic acid (FA) and folate (FT) supplementation is highly recommended by clinicians during pregnancy, especially for preventing neural tube birth defects, while labetalol (LB) is a β-blocker commonly administered as a safe option for the treatment of pregnancy-related hypertension. Currently, the possible toxicity resulting from the co-administration of FA/FT and LB has not been fully evaluated. In light of these considerations, the current study was aimed at investigating the possible in vitro cardio- and hepato-toxicity of LB-FA and LB-FT associations. Materials and Methods: Five different concentrations of LB, FA, FT, and their combination were used in myoblasts and hepatocytes in order to assess cell viability, cell morphology, and wound regeneration. Results: The results indicate no significant alterations in terms of cell viability and morphology in myoblasts (H9c2(2-1)) and hepatocytes (HepaRG) following a 72-h treatment, apart from a decrease in the percentage of viable H9c2(2-1) cells (~67%) treated with LB 150 nM–FT 50 nM. Additionally, LB (50 and 150 nM)–FA (0.2 nM) exerted an efficient wound regenerating potential in H9c2(2-1) myoblasts (wound healing rates were >80%, compared to the control at 66%), while LB-FT (at all tested concentrations) induced no significant impairment to their migration. Conclusions: Overall, our findings indicate that LB-FA and LB-FT combinations lack cytotoxicity in vitro. Moreover, beneficial effects were noticed on H9c2(2-1) cell viability and migration from LB-FA/FT administration, which should be further explored.

Background and Objectives: Autonomic nervous system (ANS) dysfunction is present in early stages of alcohol abuse and increases the likelihood of cardiovascular events. Given the nonlinear pattern of dynamic interaction between sympathetic nervous system (SNS) and para sympathetic nervous system (PNS) and the complex relationship with lifestyle factors, machine learning (ML) algorithms are best suited for analyzing alcohol impact over heart rate variability (HRV), because they allow the analysis of complex interactions between multiple variables. This study aimed to characterize autonomic nervous system dysfunction by analysis of HRV correlated with cardiovascular risk factors in young individuals by using machine learning. Materials and Methods: Total of 142 young adults (28.4 ± 4.34 years) agreed to participate in the study. Alcohol intake and drinking patterns were assessed by the AUDIT (Alcohol Use Disorders Identification Test) questionnaire and the YAI (Yearly Alcohol Intake) index. A short 5-min HRV evaluation was performed. Post-hoc analysis and machine learning algorithms were used to assess the impact of alcohol intake on HRV. Results: Binge drinkers presented slight modification in the frequency domain. Heavy drinkers had significantly lower time-domain values: standard deviation of RR intervals (SDNN) and root mean square of the successive differences (RMSSD), compared to casual and binge drinkers. High frequency (HF) values were significantly lower in heavy drinkers (p = 0.002). The higher low-to-high frequency ratio (LF/HF) that we found in heavy drinkers was interpreted as parasympathetic inhibition. Gradient boosting machine learner regression showed that age and alcohol consumption had the biggest scaled impact on the analyzed HRV parameters, followed by smoking, anxiety, depression, and body mass index. Gender and physical activity had the lowest impact on HRV. Conclusions: In healthy young adults, high alcohol intake has a negative impact on HRV in both time and frequency-domains. In parameters like HRV, where a multitude of risk factors can influence measurements, artificial intelligence algorithms seem to be a viable alternative for correct assessment.