ABSTRACT : Alzheimer’s disease (AD) is one of the most common inflammatory neurodegenerative diseases linked with dementia, it is characterized by the deposition of amyloid beta-peptide (Ab) in the brain. The present study aims to innovate a biochemical relationship between AD and interleukin 38 (IL-38) as an anti-inflammatory cytokine, expose novel mechanisms and concepts regarding other biochemical parameters studied previously or recently in AD patients and also examine the biochemical action of memantine (10 mg daily) on AD patients. Sixty (60) diagnosed AD patients participated in the present study and classified into four (4) groups: G3 were composed of (15) newly diagnosed males (52-78) years / without treatment, G4 composed of (15) newly diagnosed females (64-90) years/ without treatment, G5 composed of (15) males (60-85) years / under treatment with memantine and G6 composed of (15) females (65-73) years also under treatment with memantine. Patients were compared with healthy subjects as two control groups: G1 composed of (15) males /(52-80) years and G2 composed of (15) females / (64-82) years. Blood samples were collected from the patients and control subjects from November 20th, 2019 to February 26th, 2020. The biochemical parameters determined in the sera of all groups are Interleukin 38, ornithine, and TSH. Results of the present study have revealed that IL-38 level was highly significantly increased in G3 and G4 compared with G1 and G2 respectively while it was highly significant increased in G5 compared with G3 and non significantly increased in G6 compared with G4, the difference between (G5 and G1) and between (G6 and G2) was highly significant while the difference between G4 and G3 was nonsignificant. Ornithine level was highly significantly increased in G3 and G4 compared with G1 and G2 respectively, while it was non significantly decreased in G5 and G6 compared with G3 and G4, respectively. The difference between (G5 and G1) and between (G6 and G2) was highly significant while it was non-significant between G4 and G3. TSH level was highly significant decreased in G3 compared with G1, while it was non significantly decreased in G4 compared with G2. However, it was highly significantly increased in G5 and G6 compared with G3 and G4, respectively, the difference between (G5 and G1) and between (G4 and G3) was nonsignificant while, it was highly significant between (G6 and G2). The present study is the first to report that IL-38 is a novel biochemical marker for AD and also the first elucidating the biochemical action of memantine on IL-38 (by highlighting the anti-inflammatory responses) and ornithine based on the reversible biochemical relationship between arginine, ornithine and glutamate.
Three scolopacids out of 150 are found infected with Haemoproteus scolopaci Galli-
Valerio 1929 and H. tringae n. sp. A detailed description of the new taxon is presented along
with a comparison of the diagnostic measurements between the two species.
Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacter
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
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This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
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Polycystic ovary syndrome (PCOS) is reproductive, endocrine, and metabolic disorder affecting females. The pathology of PCOS is complicated and associated to chronic low-grade inflammation, this includes a disruption in pro-inflammatory factor production, leukocytosis, and endothelial cell dysfunction, also associated with high level of pro-inflammatory cytokines, chemokines and leukocyte count. In addition, PCOS is characterized by hormonal and immunological dysfunction. Inflammation of the ovary affects ovulation and induces or aggravates systemic inflammation. Macrophage inflammatory protein-1 (MIP-1), a pro-inflammatory chemokine, is crucial in the recruitment of inflammatory and immunological cells to the place of inflammation
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