Publications by authors named "E F Verdu"
Treatments for androgenetic alopecia (AGA) include different drugs, but a treatment based on stabilized hyaluronic acid has not been tested. The aim of this study is to clinically evaluate the effect of six sessions of injections using a hyaluronic acid compound supplemented with vitamins, ions, and amino acids (CH) on hair density and quality in volunteers. For this purpose, twenty-six healthy volunteers of both sexes with moderate AGA were injected with 3 mL of CH using the micro-papule technique.
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- Recent research is exploring how the gut microbiome (GMB) may influence schizophrenia (SCZ), including its development, symptoms, and treatment responses.
- Studies indicate that the GMB composition in animal models of SCZ differs from control groups and correlates with SCZ-like behaviors.
- Fecal microbiota transplantation (FMT) from SCZ patients to rodents has shown altered brain functions and behaviors similar to those seen in SCZ, suggesting these models may help deepen our understanding of the disorder, though further validation is needed.
Spinal cord injury (SCI) often leads to central neuropathic pain, a condition associated with significant morbidity and is challenging in terms of the clinical management. Despite extensive efforts, identifying effective biomarkers for neuropathic pain remains elusive. Here we propose a novel approach combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with artificial neural networks (ANNs) to discriminate between mass spectral profiles associated with chronic neuropathic pain induced by SCI in female mice.
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- Facial emotion recognition (FER) is important for applications like human-computer interaction and emotion detection, but current methods struggle with accuracy.
- The paper introduces a new framework called extended walrus-based deep learning with Botox feature selection network (EWDL-BFSN) that aims to accurately detect facial emotions by optimizing feature selection and classifier parameters.
- The EWDL-BFSN model uses advanced techniques like gradient wavelet anisotropic filtering and SqueezeNet for feature extraction, achieving impressive accuracy rates of 99.37% and 99.25% on the CK+ and FER-2013 datasets, outperforming existing methods.