Polyhydroxyalkanoates (PHAs) have gained much attention as biodegradable polymers, many efforts are being made to minimize the cost of PHAs by finding cheap carbon source depending on the type of microorganism and fermentation conditions. The aims of this study were to evaluate the effects of different glucose concentrations and other important conditions on the PHA production by Bacillus cereus isolated from soil. Polyhydroxyalkanoates PHAs accumulated by soil microorganisms were examined by screening the isolated bacteria using Sudan B Black and Nile Blue staining process. A Gram positive strain was identified using the 16s rRNA gene, deposited in the NCBI GenBank sequence database. Different growth conditions (favorite glucose concentrations 1-8 % (w/v), temperatures and pH) were tested and the growth parameters (sugar consumption, cell counting and Cell Dry Weight CDW) were studied. The extracted polymers were analyzed and characterized using an FTIR spectrophotometer followed by a GC-MS analysis. The pure bacterial strain isolated from soil was deposited in the NCBI GenBank database B. cereus strain ARY73, which showed significant black colored granules (or dark blue) using Sudan B Black stain, it also showed positive to Nile blue A as a high indicator stain for PHA accumulation. B. cereus ARY73 showed high production of PHA using (w/v): 2% glucose and 1% nitrogen source at 35 °C and pH7 yields 79% per Cell Dry Weight and 96 h of incubation. The extracted polymers were analyzed and characterized using an FTIR spectrophotometer confirming the PHA structure. The FTIR spectrophotometer, followed by a GC-MS analysis indicated the Scl-co-mcl PHA structure. This research demonstrates that the isolated strain B. cereus ARY73 was a good candidate for PHA production with a better quality for use in biomedical and other applications. The use of biopolymer in soil, enhanced the accumulation of the microorganisms (such as bacteria) capable of degrading biopolymer or biodegradation by-products yields by other species which were isolated in this
The objective of this work was to analyze the involvement of AhR in bone metabolism using a rat model of experimental osteoporosis and to analyze the mechanisms behind its activity. Rats were assigned randomly to the subsequent groups; Control, received no treatment; ovariectomized (OVX) rats; Sham; Sham+RES received resveratrol; OVX+RES and OVX+CH received AhR’s antagonist, CH223191 (CH); and finally OVX+CHR group received both AhR antagonist along with resveratrol. Resveratrol and AhR antagonist treatment started 7 days after surgery and continued to 45 days. The serum of osteocalcin (OC) and Ca+2 was measured by ELISA and spectrophotometer, respectively. X-ray was used to estimate bone density of rats. In molecular levels,
... Show MoreBACKGROUND: Polycystic ovary syndrome(PCOS) is one of the most common endocrine disorder affecting women in reproductive age. No single etiologic factor fully accounts for the spectrum of abnormalities in the polycystic ovary syndrome. Different changes in hormonal, metabolism and the inflammatory markers as squealy of PCOS with adverse effect on the women life. OBJECTIVE: To study the relationship between polycystic ovary syndrome and levels of C-reactive protein, human interleukin and hormonal and metabolic alteration in women with PCOS PATIENTS AND METHODS: Thirty women with Polycystic Ovary syndrome (PCOS) and other thirty women without PCOS were included. Venous blood samples were taken in early follicular phase of menstrual cycle [day
... Show MoreVisceral leishmaniasis is a neglected tropical disease on the rise in different regions of Iraq, especially in areas with poor hygiene and among refugee populations. The effectiveness of existing chemotherapy for leishmaniasis is constrained by its high toxicity, cost, and the development of drug resistance. The current research examined various concentrations (ranging from 125 to 1000 μM) of lupeol to evaluate its ability to boost the generation of nitric oxide, which has anti-leishmanial properties, in an ex-vivo macrophage model. Griess assay was used to detect the nitric oxide (NO) production in Leishmania donovani infected U937 cell-line macrophages along 24 and 48 hours post treated. The nitric oxide concentration was signifi
... Show MoreQuality of e-service is one of the critical factors that decide the success or failure of organizations. It may increase competitive advantages as well as enhance the relationships with the customers. Achieving high e-service quality and user satisfaction are challenging since they depend fundamentally on user perception and expectation which can be tricky at times. To date, there is no agreement as to what service quality is, and how it should be measured, whether it is a function of statistical measures of quality including physical defects or managerial judgment, or it is a function of customer perception about the services. This paper deep-dived the quality of e-services offered b
Researchers used different methods such as image processing and machine learning techniques in addition to medical instruments such as Placido disc, Keratoscopy, Pentacam;to help diagnosing variety of diseases that affect the eye. Our paper aims to detect one of these diseases that affect the cornea, which is Keratoconus. This is done by using image processing techniques and pattern classification methods. Pentacam is the device that is used to detect the cornea’s health; it provides four maps that can distinguish the changes on the surface of the cornea which can be used for Keratoconus detection. In this study, sixteen features were extracted from the four refractive maps along with five readings from the Pentacam software. The
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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