Background: Parkinson's disease (PD) is a neurodegenerative aging disease, with idiopathic PD being most common. Gastrointestinal tract disorders (GITD) and microbiota changes may trigger idiopathic PD. Neurotoxins from microbiota can travel from the gut to the brain via the brain-gut axis (BGA), leading to α-syn protein misfolding and dopaminergic neuron death. Methods: The aim of the current study was to investigate the link between PD and GITD by measuring several biochemical and immunological markers in 142 patients. The biochemical markers measured were vitamins B6, B12, and D, calcium, serotonin, ghrelin, dopamine, and α-syn protein. The immunological markers included transforming growth factor-beta (TGF-β), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and interferon-gamma (IFN-γ). All markers were measured using the Enzyme-Linked Immunosorbent Assay (ELISA) technique. Results: PD patients were significantly older (63.76±12.29 years) compared to GITD and control groups (41.00±15.54 and 41.25±18.30 years, respectively). Males predominated in the PD group (74.5%), while females were more common in the GITD and control groups. PD and GITD patients showed significantly lower levels of vitamins and neurotransmitters but higher calcium and α synuclein compared to controls. Immunological markers were elevated in PD and GITD groups, with significant differences between them (P-value < 0.001). Conclusion: The study concluded that certain biochemical and immunological markers provide strong evidence of the brain-gut axis's involvement in the initiation of idiopathic Parkinson's disease.
Ternary polymer blend of chitosan/poly vinyl alcohol/ poly vinyl pyrrolidone was prepared by solution castingmethod, nanocomposite was prepared by sonication method with nano Ag and Zn. All prepared compounds have been characterizedby FT-IR, SEM, DSC, as well as Biological activity. Antimicrobialactivity related to prepared blendsand Nanocomposites againstsix types of bacteria namely, Staphylococcus aureas, E. faecalis, S.typhi, P. aeruginosa, Bacillus subtilis, Escherichia coli andC. albicans fungal were examined and evaluated. The results reveal that the prepared polymer blends and nanocompositeshavegood antimicrobial activity against all kinds of microbials.
Liquid-Liquid Extraction of Cu(II) ion in aqueous solution by dicyclohexyl-18-crown-6 as extractant in dichloroethane was studied .The extraction efficiency was investigated by a spectrophometric method. The reagent form a coloured complex which has been a quantitatively extracted at pH 6.3. The method obeys Beer`s law over range from (2.5-22.5) ppm with the correlation coefficient of 0.9989. The molar absorptivity the stoichiometry of extracted complex is found to be 1:2. the proposed method is very sensitive and selective.
The concept of fully pseudo stable Banach Algebra-module (Banach A-module) which is the generalization of fully stable Banach A-module has been introduced. In this paper we study some properties of fully stable Banach A-module and another characterization of fully pseudo stable Banach A-module has been given.
Parents who give their sons arole in making parental decisions and admiring their views are the ones who build confidence and the feeling of competence within themselves and then their edgiest- rent with themselves becones better .
The (A.B) person-ality type is the core base of most psychological and educational studies because it is one of the most important subjects Concerning with the study of growth aspects whether they are physical, mental or Social. The present Study ains to measure the level of parental treatment among high School students, measure the level of (A) Personality type concept among them, recognize Statistically Significant differences in the level of parentaltreatment according gender variable and recognize the C
were prepared by condensation of 6-R-2amino bcnzothiazol with Salicyldehyde.These Schiff bases were found to reach with maleic anhydride and citraconic to give
Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.