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Background: The regulatory mechanisms guiding CD4 T cell differentiation are complex and are further influenced by intrinsic cell variability along with that of microenvironmental cues, such as cytokine and nutrient availability. Objective: This study aims to expand our understanding of CD4 T cell differentiation by examining the influence of intrinsic noise on cell fate. Methodology: A model based on a complex regulatory network of early signaling events involved in CD4 T cell activation and differentiation was described in terms of a set of stochastic differential equation to assess the effect of noise intensity on differentiation efficiency to the Th1, Th2, Th17, Treg, and TFH effector phenotypes under defined cytokine and nutrient conditions. Results: The increase of noise intensity decreases differentiation efficiencies. In a microenvironment of Th1-inducing cytokines and optimal nutrient conditions, noise levels of 3%, 5% and 10% render Th1 differentiation efficiencies of 0.87, 0.76 and 0.62, respectively, underscoring the sensitivity of the network to random variations. Further increments of noise reveal that the network is relatively stable until noise levels of 20%, where the resulting cell phenotypes becomes heterogeneous. Notably, Treg differentiation showed the highest robustness to noise perturbations. A combined Th1-Th2 cytokine environment with optimal nutrient levels induces a dominant Th1 phenotype; however, removal of glutamine shifts the balance towards the Th2 phenotype at all noise levels, with an efficiency similar to that obtained under Th2-only cytokine conditions. Similarly, combinations of Th1/Treg and Treg/Th17-inducing cytokines along with the removal of either tryptophan or oxygen shift the dominant Th1 and Treg phenotypes towards Treg and Th17 respectively. Model results are consistent with differentiation efficiency patterns obtained under wellcontrolled experimental settings reported in the literature. Conclusion: The stochastic CD4 T cell mathematical model presented here demonstrates a noise-dependent modulation of T cell differentiation induced by cytokines and nutrient availability. Modeling results can be explained by the network topology, which assures that the system will arrive at stable states of cell functionality despite variable levels of biological intrinsic noise. Moreover, the model provides insights into the robustness of the T cell differentiation process. [ABSTRACT FROM AUTHOR]

The need for new drugs to treat human infections is a global health concern. Diseases like tuberculosis, trypanosomiasis, amoebiasis, and AIDS remain significant problems, especially in developing countries like Mexico. Despite existing treatments, issues such as resistance and adverse effects drive the search for new alternatives. Herein, we introduce the NUATEI research consortium, made up of experts from the Institute of Biomedical Research at UNAM, who identify and obtain natural and synthetic compounds and test their effects against human pathogens using in vitro and in vivo models. The consortium has evaluated hundreds of natural extracts and compounds against the pathogens causing tuberculosis, trypanosomiasis, amoebiasis, and AIDS, rendering promising results, including a patent with potential for preclinical studies. This paper presents the rationale behind the formation of this consortium, as well as its objectives and strategies, emphasizing the importance of natural and synthetic products as sources of antimicrobial compounds and the relevance of the diseases studied. Finally, we briefly describe the methods of the evaluation of the compounds in each biological model and the main achievements. The potential of the consortium to screen numerous compounds and identify new therapeutic agents is highlighted, demonstrating its significant contribution to addressing these infectious diseases. [ABSTRACT FROM AUTHOR]

Upon antigen stimulation and co-stimulation, CD4+ T lymphocytes produce soluble factors that promote the activity of other immune cells against pathogens or modified tissues; this task must be performed in presence of a variety of environmental cytokines, nutrient, and oxygen conditions, which necessarily impact T cell function. The complexity of the early intracellular processes taking place upon lymphocyte stimulation is addressed by means of a mathematical model based on a network that integrates variable microenvironmental conditions with intracellular activating, regulatory, and metabolic signals. Besides the phenotype subsets considered in previous works (Th1, Th2, Th17, and Treg) the model includes the main early events in differentiation to the TFH phenotype. The model describes how cytokines, nutrients and oxygen availability regulate the differentiation of naïve CD4+ T cells into distinct subsets. Particularly, it shows that elevated amounts of an alltype mixture of effector cytokines under optimal nutrient and oxygen availability conduces the system towards a highly-polarized Th1 or Th2 state, while reduced cytokine levels allow the expression of the Th17, Treg or TFH subsets, or even hybrid phenotypes. On the other hand, optimal levels of an alltype cytokine mixture in combination with glutamine or tryptophan restriction implies a shift from Th1 to Th2 expression, while decreased levels of the Th2-inducing cytokine IL-4 leads to the rupture of the Th1-Th2 axis, allowing the manifestation of different (or hybrid) subsets. Modeling proposes that, even under reduced levels of pro-inflammatory cytokines, the sole action of hypoxia boost Th17 expression. [ABSTRACT FROM AUTHOR]

The HIV-1 reverse transcriptase (RT) enzyme is responsible for the transcription of viral RNA to produce a double-stranded DNA copy, which is subsequently integrated into the genome of target cells. The pyridin-2(1H)-one ring is a central structure for the development of new non-nucleoside reverse transcriptase inhibitors, because kinetic studies and mutation analysis indicate that these derivatives bind at the allosteric site of RT, showing activity against wild-type and mutant strains of HIV. Pyridinone-derived type quantitative structure-activity relationship (QSAR) models and virtual screening were developed and used to design new analogs with activity against RT-HIV-1. Twenty derivatives were synthesized and tested for cytotoxicity, inhibition against RT by biochemical assay, and activity against HIV-1 using a CD4+ T indicator cell line combined with flow cytometry. The results illustrate the utility of computer-aided drug design in the search for new small compounds against HIV-1. Biological tests allow analysis of structural determinants of antiviral effect to guide enhancement of antiviral effect. [ABSTRACT FROM AUTHOR]