Stroke is a severe neurological disorder in humans that results from an interruption of the blood supply to the brain. Worldwide, stoke affects over 100 million people each year and is the second largest contributor to disability. Dyslipidemia is a modifiable risk factor for stroke that is associated with an increased risk of the disease. Traditional and non-traditional lipid measures are proposed as biomarkers for the better detection of subclinical disease. In the central nervous system, lipids and lipid mediators are essential to sustain the normal brain tissue structure and function. Pathways leading to post-stroke brain deterioration include the metabolism of polyunsaturated fatty acids. A variety of lipid mediators are generated from fatty acids and these molecules may have either neuroprotective or neurodegenerative effects on the post-stroke brain tissue; therefore, they largely contribute to the outcome and recovery from stroke. In this review, we provide an overview of serum lipids associated with the risk of ischemic stroke. We also discuss the role of lipid mediators, with particular emphasis on eicosanoids, in the pathology of ischemic stroke. Finally, we summarize the latest research on potential targets in lipid metabolic pathways for ischemic stroke treatment and on the development of new stroke risk biomarkers for use in clinical practice.

Psoriasis is an ancient, universal chronic skin disease with a significant geographical variability, with the lowest incidence rate at the equator, increasing towards the poles. Insights into the mechanisms responsible for psoriasis have generated an increasing number of druggable targets and molecular drugs. The development of relevant in vitro and in vivo models of psoriasis is now a priority and an important step towards its cure. In this review, we summarize the current cellular and animal systems suited to the study of psoriasis. We discuss the strengths and limitations of the various models and the lessons learned. We conclude that, so far, there is no one model that can meet all of the research needs. Therefore, the choice model system will depend on the questions being addressed.

This review discusses how lipophagy and cytosolic lipolysis degrade cellular lipids, as well as how these pathway ys communicate, how they affect lipid metabolism and energy homeostasis in cells and how their dysfunction affects the pathogenesis of lipid storage and lipid metabolism diseases. Answers to these questions will likely uncover novel strategies for the treatment of aforementioned human diseases, but, above all, will avoid destructive effects of high concentrations of lipids—referred to as lipotoxicity—resulting in cellular dysfunction and cell death.

Obstacles to effective therapies for mucopolysaccharidoses (MPSs) determine the need for continuous studies in order to enhance therapeutic strategies. Dimethyl sulfoxide (DMSO) is frequently utilised as a solvent in biological studies, and as a vehicle for drug therapy and the in vivo administration of water-insoluble substances. In the light of the uncertainty on the mechanisms of DMSO impact on metabolism of glycosaminoglycans (GAGs) pathologically accumulated in MPSs, in this work, we made an attempt to investigate and resolve the question of the nature of GAG level modulation by DMSO, the isoflavone genistein solvent employed previously by our group in MPS treatment. In this work, we first found the cytotoxic effect of DMSO on human fibroblasts at concentrations above 3%. Also, our results displayed the potential role of DMSO in the regulation of biological processes at the transcriptional level, then demonstrated a moderate impact of the solvent on GAG synthesis. Interestingly, alterations of lysosomal ultrastructure upon DMSO treatment were visible. As there is growing evidence in the literature that DMSO can affect cellular pathways leading to numerous changes, it is important to expand our knowledge concerning this issue.

Research in recent years has shown that sphingolipids are essential signalling molecules for the proper biological and structural functioning of cells. Long-term studies on the metabolism of sphingolipids have provided evidence for their role in the pathogenesis of a number of diseases. As many inflammatory diseases, such as lysosomal storage disorders and some dermatologic diseases, including psoriasis, atopic dermatitis and ichthyoses, are associated with the altered composition and metabolism of sphingolipids, more studies precisely determining the responsibilities of these compounds for disease states are required to develop novel pharmacological treatment opportunities. It is worth emphasizing that knowledge from the study of inflammatory metabolic diseases and especially the possibility of their treatment may lead to insight into related metabolic pathways, including those involved in the formation of the epidermal barrier and providing new approaches towards workable therapies.

Controlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched to groups of various MII oocyte counts using ranking, correspondence analysis, and self-organizing map methods. The gradient boosting machine technique was used to train models on a clinical dataset of 8,574 or a clinical-genetic dataset of 516 ovarian stimulations. The clinical-genetic model predicted the number of MII oocytes better than that based on clinical data. Anti-Müllerian hormone level and antral follicle count were the two most important predictors while a genetic feature consisting of sequence variants in the GDF9, LHCGR, FSHB, ESR1, and ESR2 genes was the third. The combined contribution of genetic features important for the prediction was over one-third of that revealed for anti-Müllerian hormone. Predictions of our clinical-genetic model accurately matched individuals’ actual outcomes preventing over- or underestimation. The genetic data upgrades the personalized prediction of ovarian stimulation outcomes, thus improving the in vitro fertilization procedure.