Conference Agenda

Anxiety and depression are highly prevalent and frequently comorbid mental disorders, suggesting the existence of shared cognitive and affective patterns. The Goldberg Anxiety and Depression Scale (GADS) is a widely used tool for their detection, supported by adequate validity and reliability indices in the Salvadoran population. However, the need to optimize screening processes justifies the search for methods that reduce the length of questionnaires without compromising their diagnostic capacity. The objective of this study was to evaluate whether the items of one GADS subscale are sufficient to predict the presence of symptoms in the opposite subscale using artificial neural networks. Two models were trained: one that used anxiety items to predict depressive symptoms and another that used depression items to predict anxiety. Both models showed solid performance, with F1-scores between 0.84 and 0.85 and AUC values above 0.82, demonstrating adequate discriminatory capacity. The results indicate that it is possible to significantly reduce the number of questions while maintaining accurate classification, which opens the door to the development of abbreviated versions based on deep learning for rapid mental health screening.

Conventional physical therapies for patients with motor limitations are often repetitive and lack motivational elements, which hinders adherence and reduces treatment effectiveness. This study focused on the development of an interactive system based on electromyographic (EMG) signals to control video games designed in Unity, with the aim of enhancing patient motivation and facilitating motor rehabilitation through gamification. The system generates real-time control commands that enable interaction with video games specifically designed to promote the repetition of functional movements. Experimental validation showed improvements in patient performance across the games, while user satisfaction questionnaires reported positive experiences in ease of use, functional stimulation, and motivation. The system was also validated by a clinical professional, confirming its therapeutic potential. These results indicate that EMG-controlled video games not only enhance motivation but also strengthen treatment effectiveness, offering an innovative alternative to traditional therapies.

Xenon, a noble gas anesthetic, has been studied for its potential neuroprotective effects during surgical anesthesia. This systematic review synthesizes findings from 30 clinical, preclinical, and mechanistic studies evaluating xenon’s role in preventing postoperative neurocognitive disorders (PNDs), including delirium and cognitive dysfunction. Clinical evidence from randomized trials and meta-analyses (≈3,200 patients) shows that xenon improves hemodynamic stability, reduces vasopressor requirements, and accelerates emergence from anesthesia, but does not consistently lower PND incidence or enhance postoperative cognitive performance. In contrast, preclinical studies across models of traumatic brain injury, ischemia, seizures, stroke, and Alzheimer’s disease demonstrate robust neuroprotection, with reduced neuronal loss, apoptosis, oxidative stress, and cognitive deficits, as well as restoration of synaptic plasticity. Mechanistic insights highlight xenon’s antagonism of NMDA and HCN2 channels, modulation of oxidative and inflammatory pathways, and synaptic preservation, with innovative delivery strategies (e.g., nanobubbles) enhancing efficacy. Despite compelling preclinical results and perioperative benefits in humans, xenon’s clinical neuroprotective effects remain inconclusive, partly due to heterogeneous patient populations and methodological limitations. High cost and limited availability further restrict its widespread use. Future large-scale, standardized trials and advanced delivery approaches are needed to clarify xenon’s therapeutic role and bridge the translational gap between experimental promise and clinical practice.

This study explores the repositioning of non-antibiotic drugs as potential inhibitors of Staphylococcus aureus; a clinically significant pathogen associated with antibiotic resistance. Molecular docking analysis was performed on 34 compounds targeting the tyrosyl-tRNA synthetase enzyme (PDB ID: 1JIJ), and 15 promising candidates were identified. Among these, six compounds—Meloxicam, Piroxicam, Quetiapine, Fluoxetine, Duloxetine, and Atorvastatin—were selected based on their strong binding affinity to key residues within the active site of the target protein. Initial in vitro evaluations at low concentrations (0.0002–0.0008 mg/mL and 5–20 mg/mL) did not yield significant antimicrobial effects. Consequently, four compounds were tested at higher concentrations (20–50 mg/mL). Piroxicam demonstrated consistent, dose-dependent antimicrobial activity at all concentrations tested, with inhibition zones in the range of 0.4 to 0.6 cm. Atorvastatin showed selective activity at 40 mg per ml, resulting in an inhibition zone of 0.7 cm. By contrast, fluoxetine and quetiapine did not show inhibitory activity at any concentrations. Positive results with Piroxicam and atorvastatin support the potential of repositioning drugs as a viable strategy for identifying new antimicrobial agents. By repurposing well-characterized, approved drugs, this approach offers a promising way to overcome conventional resistance mechanisms and help develop novel therapies in the global fight against antimicrobial resistance.