Mitochondrial DNA depletion syndrome presenting with ataxia and external ophthalmoplegia: Case report

The mitochondrial DNA depletion syndromes are autosomal recessive disorders characterized by decreased mitochondrial DNA copy number in affected tissues.Mutations in 2 genes involved in deoxyribonucleotide metabolism, the deoxyguanosine kinase gene and the thymidine kinase 2 gene, had been related to this syndrome. This study aims to describe the clinical, histochemical, biochemical and molecular diagnosis of one Egyptian pediatric patient with the myopathic form of mitochondrial depletion syndrome. The patient presented to Cairo University Pediatric Hospital with the clinical suspicion of mitochondrial encephalomyopathy. Histochemical and biochemical studies of the respiratory chain complexes were performed on the muscle biopsy specimen from the patient. Molecular diagnosis was done by quantitative radioactive Southern blot and sequencing analysis of the whole coding regions of the TK2 gene. Histochemical staining revealed cytochrome oxidase negative fibers and increased staining for succinate dehydrogenase. The activity of complex I was not detected and complex IV activity was about 46%of age matched controls. Southern blot analysis showed reduction of the mitochondrial/nuclear DNA ratio, the degree of depletion was around 30% of aged-matched controls. Sequencing analysis of the TK2 gene revealed no sequence variation. Targeted molecular diagnosis based on the biochemical analysis of the respiratory chain enzymes makes the molecular evaluation of mitochondrial disorders much easier. Involvement of other nuclear genes rather than TK2 gene in the pathogenesis of the myopathic form of mitochondrial depletion syndrome should be considered.Keywords: Mitochondrial; Nuclear; Sequencing; Depletion; Mutation

Application of a gene modular approach for clinical phenotype genotype association and sepsis prediction using machine learning in meningococcal sepsis

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The research used Weighted Gene Co-expression Network Analysis (WGCNA) to establish links between gene expression and clinical parameters in infants admitted to the Pediatric Critical Care Unit with MSS. Additionally, various machine learning (ML) algorithms, including Support Vector Machine (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Decision Tree, Random Forest, and Artificial Neural Network (ANN) were implemented to predict sepsis survival. The findings revealed a transition in gene function pathways from nuclear to cytoplasmic to extracellular, corresponding with Pediatric Logistic Organ Dysfunction score (PELOD) readings at 0, 24, and 48 h. ANN was the most accurate of the six ML models applied for survival prediction. This study successfully correlated PELOD with transcriptomic data, mapping enriched GE modules in acute sepsis. By integrating network analysis methods to identify key gene modules and using machine learning for sepsis prognosis, this study offers valuable insights for precision-based treatment strategies in future research. The observed temporal-spatial pattern of cellular recovery in sepsis could prove useful in guiding clinical management and therapeutic interventions

A Methodology for Evaluating the Fidelity of Ground-Based Flight Simulators

An analytical and experimental investigation was undertaken to model the manner in which pilots perceive and utilize visual, proprioceptive, and vestibular cues in a ground-based flight simulator. The study was part of a larger research effort which has the creation of a methodology for determining flight simulator fidelity requirements as its ultimate goal. The study utilized a closed-loop feedback structure of the pilot/simulator system which included the pilot, the cockpit inceptor, the dynamics of the simulated vehicle and the motion system. With the exception of time delays which accrued in visual scene production in the simulator, visual scene effects were not included in this study. The NASA Ames Vertical Motion Simulator was used in a simple, single-degree of freedom rotorcraft bob-up/down maneuver. Pilot/vehicle analysis and fuzzy-inference identification were employed to study the changes in fidelity which occurred as the characteristics of the motion system were varied over five configurations. The data from three of the five pilots that participated in the experimental study were analyzed in the fuzzy-inference identification. Results indicate that both the analytical pilot/vehicle analysis and the fuzzy-inference identification can be used to reflect changes in simulator fidelity for the task examined

Miskolc Mathematical Notes HU e-ISSN 1787-2413 Vol. 8 (2007), No. 1, pp. 99–105 A GENERALIZATION OF GENERALIZED BANACH FIXED-POINT THEOREM IN A WEAK LEFT SMALL SLF-DISTANCE SPACE

Abstract. In this paper we generalize the multivalued contraction theorem of S. B. Nadler [8]. As corollaries we obtain fixed point theorems for a multivalued function in complete dislocated metric spaces and complete partial metric space

Les peptides-hydrolases des Lactobacillus du groupe Betabacterium. Mise en evidence chez Lactobacillus brevis, L.fermentum, L.buchneri et L.cellobiosus

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Characterization of spatial variability of soil physicochemical properties and its impact on Rhodes grass productivity

Characterization of soil properties is a key step in understanding the source of spatial variability in the productivity across agricultural fields. A study on a 16 ha field located in the eastern region of Saudi Arabia was undertaken to investigate the spatial variability of selected soil properties, such as soil compaction ‘SC’, electrical conductivity ‘EC’, pH (acidity or alkalinity of soil) and soil texture and its impact on the productivity of Rhodes grass (Chloris gayana L.). The productivity of Rhodes grass was investigated using the Cumulative Normalized Difference Vegetation Index (CNDVI), which was determined from Landsat-8 (OLI) images. The statistical analysis showed high spatial variability across the experimental field based on SC, clay and silt; indicated by values of the coefficient of variation (CV) of 22.08%, 21.89% and 21.02%, respectively. However, low to very low variability was observed for soil EC, sand and pH; with CV values of 13.94%, 7.20% and 0.53%, respectively. Results of the CNDVI of two successive harvests showed a relatively similar trend of Rhodes grass productivity across the experimental area (r = 0.74, p = 0.0001). Soil physicochemical layers of a considerable spatial variability (SC, clay, silt and EC) were utilized to delineate the experimental field into three management zones (MZ-1, MZ-2 and MZ-3); which covered 30.23%, 33.85% and 35.92% of the total area, respectively. The results of CNDVI indicated that the MZ-1 was the most productive zone, as its major areas of 50.28% and 45.09% were occupied by the highest CNDVI classes of 0.97–1.08 and 4.26–4.72, for the first and second harvests, respectively