The gut-microbiome-brain axis is now recognized as an essential part in the regulation of systemic metabolism and homeostasis. Accumulating evidence has demonstrated that dietary patterns can influence the development of metabolic alterations and inflammation through the effects of nutrients on a multitude of variables, including microbiome composition, release of microbial products, gastrointestinal signaling molecules, and neurotransmitters. These signaling molecules are, in turn, implicated in the regulation of the immune system, either promoting or inhibiting the production of pro-inflammatory cytokines and the expansion of specific leukocyte subpopulations, such as Th17 and Treg cells, which are relevant in the development of neuroinflammatory and neurodegenerative conditions. Metabolic diseases, like obesity and type 2 diabetes mellitus, are related to inadequate dietary patterns and promote variations in the aforementioned signaling pathways in patients with these conditions, which have been linked to alterations in neurological functions and mental health. Thus, maintenance of adequate dietary patterns should be an essential component of any strategy aiming to prevent neurological pathologies derived from systemic metabolic alterations. The present review summarizes current knowledge on the role of nutrition in the modulation of the immune system and its impact in the development of neuroinflammation and neurological disease.

Leishmania parasites have the ability to modify macrophage signaling pathways in order to survive and multiply within its mammalian host. They are also known to invade other cells including neutrophils, fibroblasts and dendritic cells (DCs). DCs have an important role in immunity as the link between innate and adaptive immunity, necessary for the development of an effective response; however, the impact of Leishmania mexicana infection on DCs has been poorly studied. Herein, we report that Leishmania infection rapidly induced DC protein tyrosine phosphatases activity, leading to MAP kinases inactivation. In line with this, L. mexicana was found to decrease the nuclear translocation of transcription factors such as AP-1 and NF-κB. Concomitantly, L. mexicana-infected DCs showed reduced expression of several surface antigen-presenting and co-stimulatory molecules upon LPS stimulation. Leishmania-induced interference on DC maturation was further reflected by their reduced capacity to present OVA antigen to OVA-specific T cells, as shown by abrogation of IL-2 production by the T cells. Collectively, our data revealed that DC infection by L. mexicana appears to affect the cellular and immunological mechanisms necessary for the development of an effective and protective immune response, therefore favouring the survival and propagation of the parasite within its host. Parasites of the Leishmania genus have developed many strategies to survive inside their host. Initially, they were only considered capable of infecting macrophages; however, it has been observed that Leishmania is able to infect other cell types, such as fibroblast, neutrophils and dendritic cells (DCs). DCs are well known for their antigen-presentation capabilities, and they are considered as the fundamental bridge between the innate and adaptive immune responses. In this study, we attempted to elucidate the effect of L. mexicana promastigotes on DCs. Our results showed that L. mexicana inactivates signaling cascades responsible for the expression of immune effector molecules, such as cytokines, concomitantly with the activation of protein phosphatases in the host. Furthermore, we observed that promastigote-infected cells had lower expression of MHC and co-stimulatory molecules on their surface, as well as decreased antigen-presentation capacity. In conclusion, our study showed that Leishmania parasites are able to inactivate the immunological mechanisms of DCs, as they do in macrophages, in order to survive inside its host.

The present review examines the relationship between iron deficiency and central nervous system (CNS) development and cognitive impairment, focusing on the cellular and molecular mechanisms related to the expression and function of growth factors, particularly the insulin-like growth factors I and II (IGF-I/II) and brain-derived neurotrophic factor (BDNF), in the CNS. Nutritional deficiencies are important determinants in human cognitive impairment. Among these, iron deficiency has the highest prevalence worldwide. Although this ailment is known to induce psychomotor deficits during development, the precise molecular and cellular mechanisms underlying these alterations have not been properly elucidated. This review summarizes the available information on the effect of iron deficiency on the expression and function of growth factors in the CNS, with an emphasis on IGF-I/II and BDNF. Recent studies have shown that specific growth factors, such as IGF-I/II and BDNF, have an essential role in cognition, particularly in processes involving learning and memory, by the activation of intracellular-signaling pathways involved in cell proliferation, differentiation, and survival. It is known that nutritional deficiencies promote reductions in systemic and CNS concentrations of growth factors, and that altered expression of these molecules and their receptors in the CNS leads to psychomotor and developmental deficits. Iron deficiency may induce these deficits by decreasing the expression and function of IGF-I/II and BDNF in specific areas of the brain.

Transgenic (Tg) mice that overexpress the costimulatory ligand B7.2/CD86 on microglia spontaneously develop a T cell-mediated demyelinating disease. Characterization of the inflammatory infiltrates in the nervous tissue revealed a predominance of CD8⁺ T cells, suggesting a prominent role of this T cell subset in the pathology. In this study, we show that the same neurological disease occurred in Tg mice deficient in the generation of CD4⁺ T cells, with an earlier time of onset. Analysis of the CD8⁺ T cell repertoire at early stage of disease revealed the presence of selected clonal expansions in the CNS but not in peripheral lymphoid organs. We further show that Tg animals deficient in IFN-γ receptor expression were completely resistant to disease development. Microglia activation that is an early event in disease development is IFN-γ dependent and thus appears as a key element in disease pathogenesis. Collectively, our data indicate that the spontaneous demyelinating disease in this animal model occurs as a consequence of an inflammatory response initiated through the activation of CNS-specific CD8⁺ T cells by Tg expression of B7.2 within the target organ. Thus, autoreactive CD8⁺ T cells can contribute directly to the pathogenesis of neuroinflammatory diseases such as multiple sclerosis.

Malware targeting user privacy has seen a surge in recent times, attributed to evolving global regulations and the boost of electronic commerce and online services. Moreover, recognizing privacy malware that employs obfuscation as evasion mechanism presents a major challenge due to its dynamics, resilience, and polymorphism at runtime, necessitating the application of forensic techniques such as memory dumping analysis in order to reveal suitable patterns and behaviors that enable its subsequent detection and classification. In this paper, we present three obfuscated privacy malware classifiers trained on the CIC-MalMem-2022 dataset. These solutions include a binary classifier to distinguish benign from malicious samples using logistic regression (LR), a multiclass classifier that further categorizes benign, spyware, ransomware, and trojan horse obfuscated privacy malware; and a more detailed multiclass classifier capable of discriminating benign samples from fifteen specific obfuscated privacy malware families. Multiclass classifiers were built using several traditional machine learning algorithms and a novel Deep Neural Network (DNN). We applied the Synthetic Minority Oversampling Technique (SMOTE) to address data imbalances. In particular, our results demonstrate that DNN outperforms traditional machine learning algorithms, yielding statistically significant improvements in key metrics. These achievements reach practical thresholds, suggesting the potential for enhanced malware protection systems. The dataset and all the coding files required for experiments reproducibility are publicly available at https://github.com/dcevallossalas/PrivacyMalwareClassifiers.