Electrocardiography Classification with Leaky Integrate-and-Fire Neurons in an Artificial Neural Network-Inspired Spiking Neural Network Framework.

Monitoring heart conditions through electrocardiography (ECG) has been the cornerstone of identifying cardiac irregularities. Cardiologists often rely on a detailed analysis of ECG recordings to pinpoint deviations that are indicative of heart anomalies. This traditional method, while effective, demands significant expertise and is susceptible to inaccuracies due to its manual nature. In the realm of computational analysis, Artificial Neural Networks (ANNs) have gained prominence across various domains, which can be attributed to their superior analytical capabilities. Conversely, Spiking Neural Networks (SNNs), which mimic the neural activity of the brain more closely through impulse-based processing, have not seen widespread adoption. The challenge lies primarily in the complexity of their training methodologies. Despite this, SNNs offer a promising avenue for energy-efficient computational models capable of displaying a high-level performance. This paper introduces an innovative approach employing SNNs augmented with an attention mechanism to enhance feature recognition in ECG signals. By leveraging the inherent efficiency of SNNs, coupled with the precision of attention modules, this model aims to refine the analysis of cardiac signals. The novel aspect of our methodology involves adapting the learned parameters from ANNs to SNNs using leaky integrate-and-fire (LIF) neurons. This transfer learning strategy not only capitalizes on the strengths of both neural network models but also addresses the training challenges associated with SNNs. The proposed method is evaluated through extensive experiments on two publicly available benchmark ECG datasets. The results show that our model achieves an overall accuracy of 93.8% on the MIT-BIH Arrhythmia dataset and 85.8% on the 2017 PhysioNet Challenge dataset. This advancement underscores the potential of SNNs in the field of medical diagnostics, offering a path towards more accurate, efficient, and less resource-intensive analyses of heart diseases.

Groundnut harbours non-nodulating non-rhizobial plant growth-promoting bacterial endophytes.

The present study was carried out to assess the growth-promoting ability of non-rhizobial endophytes in groundnut (Arachis hypogaea). Thirteen endophytic bacteria with different morphologies were isolated from the root and nodules of groundnut. These isolates significantly enhanced the growth of groundnut in sterilised vermiculite, though the isolates were unable to nodulate the host plant. The endophytic nature of these isolates was confirmed by their re-isolation from the sterilised and macerated roots of the plants. The isolates exhibited in vitro tricalcium phosphate and zinc solubilization, production of siderophores, auxins and ammonia as well as growth on different nitrogen-free media. The phosphate solubilization and auxin production varied from 50 to 196 and 17 to 71 µg/ml, respectively by the isolates. Based on phenotypic tests and 16S rRNA gene sequencing, four potential strains were identified as Klebsiella sp. R3, Pseudomonas putida R6, Klebsiella oxytoca GRE5 and Pseudomonas proteolytica GRE6. A significant increase in plant growth, chlorophyll content, nodule count and shoot nutrient content of groundnut was observed with these bacterial inoculations over the uninoculated control in greenhouse. The bacterial treatments resulted in increased N, P and K content in the shoot up to 87, 96 and 44%, respectively, over the control. Physico-chemical properties and available nutrient content of soil were also improved on bacterial inoculations. The results indicated that groundnut harbours beneficial non-rhizobial bacterial endophytes with the potential to be used as microbial inoculants in groundnut. Klebsiella oxytoca as a non-nodulating nodule endophyte of groundnut is reported for the first time.

Disruption of the serine/threonine protein kinase H affects phthiocerol dimycocerosates synthesis in Mycobacterium tuberculosis.

Mycobacterium tuberculosis possesses a complex cell wall that is unique and essential for interaction of the pathogen with its human host. Emerging evidence suggests that the biosynthesis of complex cell-wall lipids is mediated by serine/threonine protein kinases (STPKs). Herein, we show, using in vivo radiolabelling, MS and immunostaining analyses, that targeted deletion of one of the STPKs, pknH, attenuates the production of phthiocerol dimycocerosates (PDIMs), a major M. tuberculosis virulence lipid. Comparative protein expression analysis revealed that proteins in the PDIM biosynthetic pathway are differentially expressed in a deleted pknH strain. Furthermore, we analysed the composition of the major lipoglycans, lipoarabinomannan (LAM) and lipomannan (LM), and found a twofold higher LAM/LM ratio in the mutant strain. Thus, we provide experimental evidence that PknH contributes to the production and synthesis of M. tuberculosis cell-wall components.

Ppm1-encoded polyprenyl monophosphomannose synthase activity is essential for lipoglycan synthesis and survival in mycobacteria.

The biosynthesis of mycobacterial mannose-containing lipoglycans, such as lipomannan (LM) and the immunomodulator lipoarabinomanan (LAM), is carried out by the GT-C superfamily of glycosyltransferases that require polyprenylphosphate-based mannose (PPM) as a sugar donor. The essentiality of lipoglycan synthesis for growth makes the glycosyltransferase that synthesizes PPM, a potential drug target in Mycobacterium tuberculosis, the causative agent of tuberculosis. In M. tuberculosis, PPM has been shown to be synthesized by Ppm1 in enzymatic assays. However, genetic evidence for its essentiality and in vivo role in LM/LAM and PPM biosynthesis is lacking. In this study, we demonstrate that MSMEG3859, a Mycobacterium smegmatis gene encoding the homologue of the catalytic domain of M. tuberculosis Ppm1, is essential for survival. Depletion of MSMEG3859 in a conditional mutant of M. smegmatis resulted in the loss of higher order phosphatidyl-myo-inositol mannosides (PIMs) and lipomannan. We were also able to demonstrate that two other M. tuberculosis genes encoding glycosyltransferases that either had been shown to possess PPM synthase activity (Rv3779), or were involved in synthesizing similar polyprenol-linked donors (ppgS), were unable to compensate for the loss of MSMEG3859 in the conditional mutant.

Arabinogalactan and lipoarabinomannan biosynthesis: structure, biogenesis and their potential as drug targets.

Mycobacterium tuberculosis, the etiological agent of TB, remains the leading cause of mortality from a single infectious organism. The persistence of this human pathogen is associated with its distinctive lipid-rich cell wall structure that is highly impermeable to hydrophilic chemical drugs. This highly complex and unique structure is crucial for the growth, viability and virulence of M. tuberculosis, thus representing an attractive target for vaccine and drug development. It contains a large macromolecular structure known as the mycolyl-arabinogalactan-peptidoglycan complex, as well as phosphatidyl-myo-inositol derived glycolipids with potent immunomodulatory activity, notably lipomannan and lipoarabinomannan. These cell wall components are often the targets of effective chemotherapeutic agents against TB, such as ethambutol. This review focuses on the structural details and biosynthetic pathways of both arabinogalactan and lipoarabinomannan, as well as the effects of potent drugs on these important (lipo)polysaccharides.