Empowering AI-Diagnosis: Deep Learning Abilities for Accurate Atrial Fibrillation Classification

Artificial intelligence (AI) is a powerful technology that can enhance clinical decision-making and the efficiency of global health systems. An AI-enabled electrocardiogram (ECG) is an essential tool for diagnosing heart abnormalities such as arrhythmias. The most prevalent arrhythmia globally is atrial fibrillation (AF), which is an irregular heart rhythm that originates in the atria and can lead to other heart-related complications. A trusted AI classification of AF is explored in this study. Deep learning (DL) has been used to analyze large amounts of publicly available ECG datasets in order to classify normal sinus rhythm (NSR), AF, and other types of arrhythmias. A convolutional neural network (CNN) has been proposed to extract ECG features and classify ECG signals. Based on a 10-fold cross-validation strategy, we conducted experiments involving three scenarios for AF classification: (i) a balanced set, an imbalanced set, and an extremely imbalanced set; (ii) a comparison of ECG denoising algorithms; and (iii) the classification of AF, NSR, and other arrhythmia types (15 classes). As a result, we have achieved 100% accuracy, sensitivity, specificity, precision, and F1-score for the AF, NSR, and non-AF classifications, both for balanced and imbalanced sets. In addition, for the classification of AF, NSR, and other types of arrhythmia (15 classes), the performance results achieved an accuracy of 99.77%, sensitivity of 96.48%, specificity of 99.87%, precision of 97.03%, and F1-score of 96.68%. The results can empower AI diagnosis and assist clinicians in classifying AF on routine screening ECGs

Proteomic Analysis Reveals That Iron Availability Alters the Metabolic Status of the Pathogenic Fungus Paracoccidioides brasiliensis

Paracoccidioides brasiliensis is a thermodimorphic fungus and the causative agent of paracoccidioidomycosis (PCM). The ability of P. brasiliensis to uptake nutrients is fundamental for growth, but a reduction in the availability of iron and other nutrients is a host defense mechanism many pathogenic fungi must overcome. Thus, fungal mechanisms that scavenge iron from host may contribute to P. brasiliensis virulence. In order to better understand how P. brasiliensis adapts to iron starvation in the host we compared the two-dimensional (2D) gel protein profile of yeast cells during iron starvation to that of iron rich condition. Protein spots were selected for comparative analysis based on the protein staining intensity as determined by image analysis. A total of 1752 protein spots were selected for comparison, and a total of 274 out of the 1752 protein spots were determined to have changed significantly in abundance due to iron depletion. Ninety six of the 274 proteins were grouped into the following functional categories; energy, metabolism, cell rescue, virulence, cell cycle, protein synthesis, protein fate, transcription, cellular communication, and cell fate. A correlation between protein and transcript levels was also discovered using quantitative RT-PCR analysis from RNA obtained from P. brasiliensis under iron restricting conditions and from yeast cells isolated from infected mouse spleens. In addition, western blot analysis and enzyme activity assays validated the differential regulation of proteins identified by 2-D gel analysis. We observed an increase in glycolytic pathway protein regulation while tricarboxylic acid cycle, glyoxylate and methylcitrate cycles, and electron transport chain proteins decreased in abundance under iron limiting conditions. These data suggest a remodeling of P. brasiliensis metabolism by prioritizing iron independent pathways

Epigenetic polypharmacology: from combination therapy to multitargeted drugs

The modern drug discovery process has largely focused its attention in the so-called magic bullets, single chemical entities that exhibit high selectivity and potency for a particular target. This approach was based on the assumption that the deregulation of a protein was causally linked to a disease state, and the pharmacological intervention through inhibition of the deregulated target was able to restore normal cell function. However, the use of cocktails or multicomponent drugs to address several targets simultaneously is also popular to treat multifactorial diseases such as cancer and neurological disorders. We review the state of the art with such combinations that have an epigenetic target as one of their mechanisms of action. Epigenetic drug discovery is a rapidly advancing field, and drugs targeting epigenetic enzymes are in the clinic for the treatment of hematological cancers. Approved and experimental epigenetic drugs are undergoing clinical trials in combination with other therapeutic agents via fused or linked pharmacophores in order to benefit from synergistic effects of polypharmacology. In addition, ligands are being discovered which, as single chemical entities, are able to modulate multiple epigenetic targets simultaneously (multitarget epigenetic drugs). These multiple ligands should in principle have a lower risk of drug-drug interactions and drug resistance compared to cocktails or multicomponent drugs. This new generation may rival the so-called magic bullets in the treatment of diseases that arise as a consequence of the deregulation of multiple signaling pathways provided the challenge of optimization of the activities shown by the pharmacophores with the different targets is addressed

Use of low-power He-Ne laser therapy to accelerate regeneration processes of injured sciatic nerve in rabbit.

BackgroundPhotostimulation using low-power laser had been used for nervous repair with interesting results. This study aimed to evaluate the influence of 20 mW low-power He-Ne laser on the regeneration of a peripheral sciatic nerve after trauma using the Albino rabbit as an animal model for experimental treatment.MethodsSix adult male rabbits were randomly assigned into two equal groups (control- and laser-treated). General anesthesia was administered intramuscularly, and exploration of the sciatic nerve was done in the lateral aspect of the legs. Complete longitudinal and reverse sections of the nerve were performed, which was followed by crushing of the neural sheath. Treatment was carried out directly after the trauma. Irradiation doses of low-level laser therapy (LLLT-31.5 J/cm2 ) with once a day application for 10 consecutive days and observed for 30 days. The animals were followed up for an extra 2 weeks. Two important factors were examined histopathology and functionality of the nerve.ResultsCompared to the control group, significant variations in regeneration were observed, including thicker nerve fibers, and more regular myelin layers in the treated group.ConclusionsThe results of the present study suggest that laser therapy may be a viable approach for nerve regeneration and repair

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

A cross-ancestry genome-wide association meta-analysis of amyotrophic lateral sclerosis (ALS) including 29,612 patients with ALS and 122,656 controls identifies 15 risk loci with distinct genetic architectures and neuron-specific biology. Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons

Common and rare variant association analyses in amyotrophic lateral sclerosis identify 15 risk loci with distinct genetic architectures and neuron-specific biology

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a lifetime risk of one in 350 people and an unmet need for disease-modifying therapies. We conducted a cross-ancestry genome-wide association study (GWAS) including 29,612 patients with ALS and 122,656 controls, which identified 15 risk loci. When combined with 8,953 individuals with whole-genome sequencing (6,538 patients, 2,415 controls) and a large cortex-derived expression quantitative trait locus (eQTL) dataset (MetaBrain), analyses revealed locus-specific genetic architectures in which we prioritized genes either through rare variants, short tandem repeats or regulatory effects. ALS-associated risk loci were shared with multiple traits within the neurodegenerative spectrum but with distinct enrichment patterns across brain regions and cell types. Of the environmental and lifestyle risk factors obtained from the literature, Mendelian randomization analyses indicated a causal role for high cholesterol levels. The combination of all ALS-associated signals reveals a role for perturbations in vesicle-mediated transport and autophagy and provides evidence for cell-autonomous disease initiation in glutamatergic neurons