One of the most common lipids in the human body is palmitic acid (PA), a saturated fatty acid with essential functions in brain cells. PA is used by cells as an energy source, besides being a precursor of signaling molecules and protein tilting across the membrane. Although PA plays physiological functions in the brain, its excessive accumulation leads to detrimental effects on brain cells, causing lipotoxicity. This mechanism involves the activation of toll-like receptors (TLR) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, with the consequent release of pro-inflammatory cytokines, increased production of reactive oxygen species (ROS), endoplasmic reticulum (ER) stress, and autophagy impairment. Importantly, some of the cellular changes induced by PA lead to an augmented susceptibility to the development of Alzheimer’s and Parkinson´s diseases. Considering the complexity of the response to PA and the intrinsic differences of the brain, in this review, we provide an overview of the molecular and cellular effects of PA on different brain cells and their possible relationships with neurodegenerative diseases (NDs). Furthermore, we propose the use of other fatty acids, such as oleic acid or linoleic acid, as potential therapeutic approaches against NDs, as these fatty acids can counteract PA’s negative effects on cells.

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

Microglial cells are extremely important for homeostasis of the CNS. Upon brain damage, microglia become reactive in response to inflammatory stimuli and lead to the secretion of inflammatory cytokines. Because microglia have the ability of adjusting their steady state to an active phenotype that modulates the CNS environment, chronic activation of microglia has an important role in mediating neuroinflammatory brain diseases. Depending upon the nature and degree of the injury stimulus, microglial activity may alternate, either to acute and mild responses -sometimes beneficial- or chronic and severe that may result in neurodegeneration. In this context, proper and controlled activation of microglia should be considered as a potential neuroprotective strategy against neurodegeneration. More recently, the use of estrogenic compounds to regulate microgliosis has shown promising results, and is currently being investigated due to their potential pharmacologic ability in the regulation of inflammation. In this review, we highlight the role of microgliamediated damage and discuss the effect of neurosteroids in reducing the adverse impact of inflammation in the brain.

Mucopolysaccharidosis type I (MPSI) is a rare autosomal recessive disorder caused by mutations in the gene encoding the lysosomal enzyme α-l-iduronidase (IDUA), which is instrumental in the hydrolysis of the glycosaminoglycans, dermatan and heparan sulfate. The accumulation of unhydrolyzed glycosaminoglycans leads to pathogenesis in multiple tissue types, especially those of skeletal, nervous, respiratory, cardiovascular, and gastrointestinal origin. Although molecular diagnostic tools for MPSI have been available since the identification and characterization of the IDUA gene in 1992, Colombia, Ecuador, and Peru have lacked such methodologies. Therefore, the mutational profile of the IDUA gene in these countries has largely been unknown. The goal of this study was to characterize genotypes in 14 patients with MPSI from Colombia, Ecuador, and Peru. The most common mutation found at a frequency of 42.8% was W402X. Six patients presented with seven novel mutations, a high novel mutational rate in this population (32%). These novel mutations were validated using bioinformatic techniques. A model of the IDUA protein resulting from three of the novel missense mutations (Y625C, P385L, R621L) revealed that these mutations alter accessible surface area values, thereby reducing the accessibility of the enzyme to its substrates. This is the first characterization of the mutational profile of the IDUA gene in patients with MPSI in Colombia, Ecuador, and Peru. The findings contribute to our understanding of IDUA gene expression and IDUA enzyme function, and may help facilitate early and improved diagnosis and management for patients with MPSI.