Peptide-based drug discovery through artificial intelligence: towards an autonomous design of therapeutic peptides.

With their diverse biological activities, peptides are promising candidates for therapeutic applications, showing antimicrobial, antitumour and hormonal signalling capabilities. Despite their advantages, therapeutic peptides face challenges such as short half-life, limited oral bioavailability and susceptibility to plasma degradation. The rise of computational tools and artificial intelligence (AI) in peptide research has spurred the development of advanced methodologies and databases that are pivotal in the exploration of these complex macromolecules. This perspective delves into integrating AI in peptide development, encompassing classifier methods, predictive systems and the avant-garde design facilitated by deep-generative models like generative adversarial networks and variational autoencoders. There are still challenges, such as the need for processing optimization and careful validation of predictive models. This work outlines traditional strategies for machine learning model construction and training techniques and proposes a comprehensive AI-assisted peptide design and validation pipeline. The evolving landscape of peptide design using AI is emphasized, showcasing the practicality of these methods in expediting the development and discovery of novel peptides within the context of peptide-based drug discovery.

Regional Brain Perfusion Is Associated with Endothelial Dysfunction Markers in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) is an important independent risk factor for cardiovascular disease. Cumulative data suggest that depressive patients exhibit derangement in regional cerebral blood flow (rCBF), although underlying mechanisms remain mostly unknown. Endothelial dysfunction (ED), defined as different forms of abnormal endothelial activity, plays a key role in the pathogenesis of vascular disease. ED is associated with several clinical conditions characterized by high cardiovascular risk. Diverse ED markers have been found in mood disorders. PURPOSE: To evaluate the association between rCBF and peripheral ED markers in MDD patients, at baseline and after selective serotonin receptor inhibitors (SSRIs) therapy. PATIENTS AND METHODS: Twenty-seven untreated unipolar MDD patients in their first episode were evaluated with the Hamilton Depression Rating Scale (HAM-D) and brain perfusion SPECT at baseline and after 2 months of SSRIs. Statistical Parametric Mapping (SPM) was employed to evaluate rCBF; circulating endothelial cells (CECs), plasma soluble intercellular adhesion molecule (sICAM), and high-sensitivity C-reactive protein (hsCRP) were used as independent covariates. RESULTS: Baseline CECs and sICAM were increased in MDD patients compared with matching controls (p = 0.0001) and hsCRP (p = 0.03). HAM-D scores (21 items) and CECs diminished after SSRI therapy in MDD patients (p < 0.0001). There was a significant rCBF decrease, mainly in deep central structures. HAM-D change was associated with rCBF decrease at the left amygdala, right striatum levels, and Brodmann area 25. CEC change was associated with rCBF at deep brain level and sICAM with large rCBF areas at the left caudate and tectum; hsCRP was associated, to a lesser extent, with the left dorsal striatum and mesencephalic tectum. CONCLUSION: ED markers in patients with MDD are associated with significant changes in rCBF which are features of depression. These findings suggest that systemic damage/activation of the endothelium may contribute to the abnormal rCBF observed in MDD patients.

Desfribilador automatico implantado y marcapaso epicardico en el manejo de taquicardia ventricular polimorfa pausa-dependiente / Cardio-desfibrillator implanted into the endocardium and epicardial pacemaker in the treatment of a patient with pause-dependent polymorphic

Se presenta el primer caso de la utilización de un cardiodesfíbrilador implantado por vía endocárdica y marcapaso epicárdico en el manejo de un paciente con taquicardia ventricular polimorfa pausa-dependiente. Se revisa la literatura en cuanto a la interacción de los dos dispositivos, encontrándose que con adecuada programación y localización de los electrodos, se disminuye la posibilidad de interferencia en el funcionamiento de cada uno de ellos