Serum alpha Amylase, Serum Lipase and Stool Fat as A Measure of Exocrine Pancreatic Function in Sudanese Children with Protein Energy Malnutrition

Pancreatic exocrine dysfunction in PEM has been a frequent observation in many past records. The enzyme synthesis by the pancreas is affected by the nutritional deprivation. This study was designed to determine the pancreatic exocrine function, namely serum amylase, lipase and stool fat in PEM and its types. An important aim was to correlate the defect present to some clinical and biochemical data with special emphasis on the effect of nutritional rehabilitation. The study was a prospective hospital based case and control study. Fifty children with severe Protein Energy Malnutrition (PEM) and fifteen healthy age and sex matched group were enrolled in the study. The cases, including 21 with marasmus, 19 with kwashiorkor (KWO) and10 with marasmic kwashiorkor (MKWO) were recruited from Gaafar Ibn Auf Specialized Children Hospital. Full history and thorough clinical examination including anthropometric measurements were performed in all cases and controls. Serum amylase, lipase and stool fat were estimated together with other biochemical investigations namely serum albumin and globulin and hemoglobin, on presentation and two weeks later. The mean age of presentation in cases was 18.88+6.6 months with slight female preponderance (52%). The bulk of cases were from Western states (58%). v Illiteracy, inappropriate weaning practices and inadequate nutrition were the major risk factors. The most frequent presenting symptoms were diarrhoea in 88% and vomiting in 78% with hair depigmentation (98%), sparsity (90%) and pallor (94%) as major clinical signs. All anthropometric measurements were significantly lower in cases when compared to controls. Regarding pancreatic exocrine function, serum amylase and lipase levels were low in all subtypes of malnutrition, being remarkably low in oedematous cases. The indices improved after nutritional rehabilitation. Hypoalbuminaemia, frequent diarrhoea and oedema were the major determining factors for pancreatic enzyme level. Non survivors had even more declining indices especially for serum amylase. The presence of stool fat in cases augmented pancreatic dysfunction but still could be due to other pathologies. In conclusion, pancreatic exocrine dysfunction in PEM may be an overlooked factor contributing to ongoing malnutrition in Sudanese children. Estimation of PEF level is recommended as part of the evaluation of patients with PEM

Geometric inequalities via a symmetric differential operator defined by quantum calculus in the open unit disk

The present investigation covenants with the concept of quantum calculus besides the convolution operation to impose a comprehensive symmetric q-differential operator defining new classes of analytic functions. We study the geometric representations with applications. The applications deliberated to indicate the certainty of resolutions of a category of symmetric differential equations type Briot-Bouquet

Genetic evaluation of some sesame genotypes for seed yield and its components

To study genetic variation, genetic parameters and selection criteria of seventeen sesame genotypes, a field experiment was conducted across different environments represented by two summer seasons of 2018 (E1) and 2019 (E2) at Etay-El-Baroud/Behaira Agricultural Research Station and one summer season of 2019 (E3) at Kafr-El-Hamam/Sharkia Agricultural Research Station, Agricultural Research Center, Egypt using a randomized complete block design with three replications for each environment. The promising sesame genotypes were  L25 for earliness in flowering at E1 and across environments, L101 for plant height and fruiting zone length when grown at E2 and L110 across environments, L35 for number of branches plant and seed yield per feddan when grown at E2 and across environments, L48 for capsules length when grown at E2  and L2 across environments, L82 for 1000-seed weight when grown at E3 and L35 across environments, L2 for seed weight per plant when grown at E1 and across environments and  L101 for seed oil content when grown at E1 and across environments. Among the most effective traits in improving seed weight per plant were fruiting zone length and number of branches per plant, as verified through correlation and path analyses at phenotypic and genotypic levels.These traits had the highest broad-sense heritability and genetic advance as percent of mean. Keywords: Correlation, Genetic variability, Heritability, Path analysi

Microwave characterization of bio-composites materials based finite element and Nicholson-Ross-Weir methods

In this work, Bio-composite of oil palm empty fruit bunch fibre (OPEFB)-filler and polycaprolactone (PCL)-polymer has been prepared and characterized. The functional groups and morphology of the prepared samples were characterized by Fourier transform infrared spectroscopy (FT-IR). By using the Nicholson- Ross-Weir (NRW) mode, both of real and imaginary relative permittivity values of the samples were obtained simultaneously from the reflection and transmission coefficient measurements of the materials. Whereas, the attenuation with the field distribution at the waveguide filled with a sample were considered by using the Finite Element Method (FEM). The magnitude of the reflection and transmission (R/T) coefficients of the composite with different filler percentages were measured using rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in X-band range of frequency. The computations of the S-parameters were achieved by using the FEM technique along with NRW mode. Then, the obtained results were compared with the measured R/T coefficients. Relative error results nominated the FEM mode due to its highly accurate results than the other method

MRI brain classification using the quantum entropy LBP and deep-learning-based features

Brain tumor detection at early stages can increase the chances of the patient’s recovery after treatment. In the last decade, we have noticed a substantial development in the medical imaging technologies, and they are now becoming an integral part in the diagnosis and treatment processes. In this study, we generalize the concept of entropy di erence defined in terms of Marsaglia formula (usually used to describe two di erent figures, statues, etc.) by using the quantum calculus. Then we employ the result to extend the local binary patterns (LBP) to get the quantum entropy LBP (QELBP). The proposed study consists of two approaches of features extractions of MRI brain scans, namely, the QELBP and the deep learning DL features. The classification of MRI brain scan is improved by exploiting the excellent performance of the QELBP–DL feature extraction of the brain in MRI brain scans. The combining all of the extracted features increase the classification accuracy of long short-term memory network when using it as the brain tumor classifier. The maximum accuracy achieved for classifying a dataset comprising 154 MRI brain scan is 98.80%. The experimental results demonstrate that combining the extracted features improves the performance of MRI brain tumor classification.N/