Acinetobacter baumannii (named in honor of the American bacteriologists Paul and Linda Baumann) is a Gram-negative, multidrug-resistant (MDR) pathogen that causes nosocomial infections, especially in intensive care units (ICUs) and immunocompromised patients with central venous catheters. A. baumannii has developed a broad spectrum of antimicrobial resistance, associated with a higher mortality rate among infected patients compared with other non-baumannii species. In terms of clinical impact, resistant strains are associated with increases in both in-hospital length of stay and mortality. A. baumannii can cause a variety of infections; most involve the respiratory tract, especially ventilator-associated pneumonia, but bacteremia and skin wound infections have also been reported, the latter of which has been prominently observed in the context of war-related trauma. Cases of meningitis associated with A. baumannii have been documented. The most common risk factor for the acquisition of MDR A baumannii is previous antibiotic use, following by mechanical ventilation, length of ICU/hospital stay, severity of illness, and use of medical devices. Current efforts focus on addressing all the antimicrobial resistance mechanisms described in A. baumannii, with the objective of identifying the most promising therapeutic scheme. Bacteriophage- and artilysin-based therapeutic approaches have been described as effective, but further research into their clinical use is required

Traumatic brain injury (TBI) survivors exhibit motor and cognitive symptoms from the primary injury that can become aggravated over time because of secondary cell death. In the presentin vivostudy, we examined the beneficial effects of human adipose-derived stem cells (hADSCs) in a controlled cortical impact model of mild TBI using young (6 months) and aged (20 months) F344 rats. Animals were transplanted intravenously with 4 × 10⁶hADSCs (Tx), conditioned media (CM), or vehicle (unconditioned media) at 3 h after TBI. Significant amelioration of motor and cognitive functions was revealed in young, but not aged, Tx and CM groups. Fluorescent imagingin vivoandex vivorevealed 1,1′ dioactadecyl-3-3-3′,3′-tetramethylindotricarbocyanine iodide-labeled hADSCs in peripheral organs and brain after TBI. Spatiotemporal deposition of hADSCs differed between young and aged rats, most notably reduced migration to the aged spleen. Significant reduction in cortical damage and hippocampal cell loss was observed in both Tx and CM groups in young rats, whereas less neuroprotection was detected in the aged rats and mainly in the Tx group but not the CM group. CM harvested from hADSCs with silencing of either NEAT1 (nuclear enriched abundant transcript 1) or MALAT1 (metastasis associated lung adenocarcinoma transcript 1), long noncoding RNAs (lncRNAs) known to play a role in gene expression, lost the efficacy in our model. Altogether, hADSCs are promising therapeutic cells for TBI, and lncRNAs in the secretome is an important mechanism of cell therapy. Furthermore, hADSCs showed reduced efficacy in aged rats, which may in part result from decreased homing of the cells to the spleen.

Dendritic cells (DCs) are a type of cells derived from bone marrow that represent 1% or less of the total hematopoietic cells of any lymphoid organ or of the total cell count of the blood or epithelia. Dendritic cells comprise a heterogeneous population of cells localized in different tissues where they act as sentinels continuously capturing antigens to present them to T cells. Dendritic cells are uniquely capable of attracting and activating naïve CD4⁺ and CD8⁺ T cells to initiate and modulate primary immune responses. They have the ability to coordinate tolerance or immunity depending on their activation status, which is why they are also considered as the orchestrating cells of the immune response. The purpose of this review is to provide a general overview of the current knowledge on ontogeny and subsets of human dendritic cells as well as their function and different biological roles.

There are many types of cell death, each involving multiple and complex molecular events. Cell death can occur accidentally when exposed to extreme physical, chemical, or mechanical conditions, or it can also be regulated, which involves a genetically coded complex machinery to carry out the process. Apoptosis is an example of the latter. Apoptotic cell death can be triggered through different intracellular signalling pathways that lead to morphological changes and eventually cell death. This is a normal and biological process carried out during maturation, remodelling, growth, and development in tissues. To maintain tissue homeostasis, regulatory, and inhibitory mechanisms must control apoptosis. Paradoxically, these same pathways are utilized during infection by distinct intracellular microorganisms to evade recognition by the immune system and therefore survive, reproduce and develop. In cancer, neoplastic cells inhibit apoptosis, thus allowing their survival and increasing their capability to invade different tissues and organs. The purpose of this work is to review the generalities of the molecular mechanisms and signalling pathways involved in apoptosis induction and inhibition. Additionally, we compile the current evidence of apoptosis modulation during cancer and Leishmania infection as a model of apoptosis regulation by an intracellular microorganism.

The novel COVID-19, detected in Wuhan, China, has reached almost every city across the globe, and researchers from many countries have used several epidemiologic models to describe the epidemic trends. In this context, it is also important to know the geographic extent of the infected population. Following this approach, a Gumpertz model was adapted with official data from the state of Hidalgo, Mexico, in order to estimate the people infected during this COVID-19 pandemic. We found, based on the adjusted data, the highest value in infected people according to official and theoretical data. Furthermore, using a geographical analysis based on geostatistical measures related to density of demographic and economic data, traffic level and geolocation, raster files were generated to estimate probability of coronavirus cases occurrence using the areas where the contagion may occur. We also distributed the maximum contagion obtained by the epidemic model, using these raster files, and a regression model to weight factors according their importance. Based on this estimated distribution, we found that most of the infected people were located in the southern border, a trend related to the economic strip in the southern part of Hidalgo State, associated with its vicinity to the Megacity of Mexico.