This study was aimed to investigate the protective effect of vitamin D on L-arginine induced acute pancreatitis in rats. Twenty eight white Albino rats of both sexes were divided into 4 equal groups. Negative control rats (group I) intra-peritoneally injected with normal saline, positive control (group II) rats induced acute pancreatitis with L- arginine, group III rats treated with a single dose of vitamin D, and group IV treated with single dose of vitamin D prior to first dose of L- arginine. Serum amylase, lipase and cytokines such as tumour necrosis factor –alpha (TNF-α), interleukin-1 beta (IL1β); in addition, my eloperoxidase (MPO) enzyme activity in the pancreas were measured. In acute pancreatitis group (group II), there was a

The cyanobacterial neurotoxinβ-N-methylamino-L-alanine (BMAA) is considered to be an “excitotoxin,” and its suggested mechanism of action is killing neurons. Long-term exposure to L-BMAA is believed to lead to neurodegenerative diseases including Parkinson’s and Alzheimer’s diseases and amyotrophic lateral sclerosis (Lou Gehrig’s disease). Objectives of this study were to determine the presumptive median lethal dose (LD₅₀), the Lowest-Observed-Adverse-Effect Level (LOAEL), and histopathologic lesions caused by the naturally occurring BMAA isomer, L-BMAA, in mice. Seventy NIH Swiss Outbred mice (35 male and 35 female) were used. Treatment group mice

    In this work, the spirurid nematode Hartertia gallinarum was reported in the intestine of the spotted sandgrouse, Pterocles senegallus, collected in three different locations: Ga'ara Depression, Iraqi Western Desert, Zurbatiyah and Al-Attariyah, Middle of Iraq. Description and measurements of the nematode were given. The role of termites in the infection of P. senegallus with H. gallinarum was discussed. Occurrence of H. gallinarum in P. senegallus represents a new host record.

Pathogenic microorganisms from hospitals, communities, and the environment remain great threats to human health. The increasing concern about antibiotic resistance has also necessitated the search for robust alternatives. Therefore, this study aims to isolate, screen and evaluate the antibiotic susceptibility of Pseudomonas aeruginosa isolated from a soil sample taken from northern, western and eastern parts of Kelana Jaya Lake against four antibiotics (gentamycin, tetracycline, ampicillin, and penicillin) on a Mueller-Hinton Agar media plate. Pseudomonas identification was done by using API 20 kit. Disc diffusion was employed as well as the oxidase test. From the positive oxidase result, the isolated bacteria were identified as Burkhold

A total of 50 fertile human hydatid cases {33(66%) females and (34%) males}, obtained from Al-Ramadi public Hospital during the period from December 2003 to July 2004 were examined to study any bacterial infections. The specimens were obtained from hydatid fluid and then cultured on appropriate culture media to distinguish some species of bacteria which resulted in obtaining: Staphylococcus aureus (18%), Pseudomonas aeruginosa(12%), Escherichia coli(6%) and Streptococcus pneumonia (4%). These bacteria were confirmed by isolation from interacyst fluid and blood culture technique. The possible routs of infection may be through blood, biliary ducts and bronchioles .The selectivity permeable of the cyst wall may be absent and that may allow

The presence of hydrocarbons in the soil is considered one of the main problems of pollution. In our current study, eight samples isolated from soil saturated with hydrocarbons were taken from different areas of Baghdad, Iraq. In this study, 5 isolates belonging to Pseudomonas aeruginosa by 99%, 4 isolates to Klebsiella pneumoniae by 98%, and 3 isolates to Enterobacter hormaechei by 97% were diagnosed in different ways. A molecular examination was also conducted by 16sRNA. We recorded P. aeruginosa, K. Pneumoniae and E. hormaechei as new local isolates in NCBI. In addition, a comparison was made between our isolates and the global isolates to determine the degree of convergence in the evolutionary line. The genes alkB and nahAc7 were diagno

Classifying butterfly species is crucial in biodiversity studies and environmental monitoring. However, manual classification is often a laborious process that requires specialized expertise and is prone to error, especially when species have similar visual characteristics. To address these drawbacks, this paper presents a hybrid approach that combines machine learning with deep learning for feature extraction. To enhance the visibility of important features, preprocessing techniques such as background removal and binarization are applied to butterfly images. Feature extraction was performed using the SqueezeNet convolutional neural network, pretrained on the ImageNet dataset. By discarding the final classification layer, the networ