Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Polymer metal complexes of poly ethylene glycol acetal and Ag (I), Cu (II), Ni (II), Mn (II), Co (III) and Hg (II) were prepared from the reaction of PEG with aldehyde derived fromErythro-ascorbic acid (pentulosono-ɣ-lactone-2, 3- enedianisoate). All these compounds were characterized by Thin Layer Chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR,13CNMR, and mass spectra. It has been established that, the polymer and its metal complexes showedgood activities against four pathogenic bacteria (Escherichia coli , Klebsiellapneumonae,Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast). The polymer metal complexes showed higher activity than the free polymer.Theorder

Background: Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease mediated by autoreactive T cells against myelin-basic proteins. Cytokines are suggested to play a role in the etiopathogenesis of the disease. Among these cytokines is interleukin-2 (IL-2). Aim of the study: To investigate the association between IL2+166 G/T single nucleotide polymorphism (SNP: rs2069763) and MS in Iraqi patients. Serum level of IL-2 was also detected. Anti-rubella IgG antibody was further determined in the sera of patients. Patients and methods: Eighty MS patients (28 males and 52 females; age mean ± SD: 39.2 ± 16.1 years) and 80 healthy control matched patients for age (32.15 ± 16.13 years) and gender (28 males and 52 females) were en

Polymer metal complexes of poly ethylene glycol acetal and Ag (I), Cu (II), Ni (II), Mn (II), Co (III) and Hg (II) were prepared from the reaction of PEG with aldehyde derived from Erythro-ascorbic acid (pentulosono-ɣ-lactone-2, 3- enedianisoate). All these compounds were characterized by Thin Layer Chromatography (TLC) and FTIR spectra and aldehyde was also characterized by (U.V-Vis), 1HNMR,13CNMR, and mass spectra. It has been established that, the polymer and its metal complexes showed good activities against four pathogenic bacteria (Escherichia coli ,Klebsiellapneumonae, Staphylococcusaureus, Staphylococcus Albus) and two fungal (Aspergillus Niger,Yeast). The polymer metal complexes showed higher activity than the free polymer. The

The corona virus epidemic outbreak has urged an extreme worldwide effort for re‐purposing obtainable approved medications for its treatment. In this review, we're focusing on the chemicals properties andpharmacologicaleffectiveness of medicationsofsmallmolecule that are presently being evaluated in clinical trials for the management of corona virus (COVID‐19). The current review sheds light on a number of drugs that have been diagnosed to treat COVID‐19 and their biological effects.

Traumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental