Influence of maturity stage on nutritive value of typha for ruminants

The study evaluated the influence of maturity on the nutritive value and fermentation parameters of Typha. Typha samples were collected at two different stages of growth, as indicated by the height of the plants: either 0.5 m (Low Typha; LT, age 3-6months) or 1.5 m (High Typha; HT, age 9-12 months). Samples were analyzed for chemical composition, and incubated in vitro with ruminal fluid from sheep to determine the main fermentation parameters. As maturity advanced, the dry matter, fiber and lignin content (25.30%, 70.40%, 47.30% and 10.58%) in the Typha increased, whereas the content of ashes and protein (12.18% and 12.24%) decreases. The changes in chemical composition caused a significant reduction in both the in vitro ruminal degradability after 96 h of incubation (38.6 and 22.9% for LT and HT, respectively) and the production of volatile fatty acids after 24 h of incubation (6.08 and 5.87 mmol/g dry matter incubated), indicating that the nutritive value of the Typha declines with advancing maturity. The results indicate that Typha plants for ruminant feeding should be preferably harvested at early growth stages

First documentation of canine dipylidiasis by molecular detection in Baghdad City, Iraq

Canine dipylidiasis is a zoonotic intestinal cestode infects cands, fields and rarely human. The goal of this study was to determine morphological characteristics by traditional parasitological methods and molecular techniques among stray dogs in Baghdad, Iraq. Totally, thirty-two adults of D.caninum were isolated from 15 small intestines that were naturally infected obtained from 100 necropsied stray dogs (15%) and used for morphological description after using Semichon-acetocarmine stain, on the basis of morphological description of the scolex, immature, mature, and gravid segments of D.caninum The results revealed a significant difference (p> 0.01) in the dipylidiasis infection based on the dogs' sex, females had a higher infection rate (28%) than males (10.7%). In between aged groups, infection rates showed a relatively significant difference (P≤0.01) with a higher rate in puppies (20%) than in adults (13.8%). The records of D.caninum increased in March compared to the other months, with nil infection in August. By using the DC28SrRNA region at size (653bp) se, Polymerase Chain Reaction (PCR), DNA sequencing, and phylogeny were used for identification and genetic variation between thirty-two local D.caninum and NCBI.&nbsp

Determinants and outcome of esophageal caustic stricture interventions

This book is based on the research which is done by one the first female pediatric surgeons of a war torn country and her tireless struggles in giving hope of life to the society specially the children and trying to provide high stranded treatment in-spite of limited resources provided. Children makes one third our populations today, and our all future.Thinking about health of children today, will give us a healthy population tomorrow. Afghanistan has been in 40 years of unwanted wars, and counts as one of five young developing countries, beside researching the conflicts and outcomes of war, we need to study silent killers such as caustic ingestion. As we know,we can prevent from mortality and morbidity of caustic ingestion by taking very ordinary measures but unfortunately no such measures are being taking care of, and the incidence are significant, so we are hoping this study be the first step for start to work in such area and create general awareness.*https://ecommons.aku.edu/books/1091/thumbnail.jp

Treatment of BK virus with a stepwise immunosuppression reduction and intravenous immunoglobulin in pediatric kidney transplant

BackgroundBKV and BKVN are common in pediatric kidney transplant, but there is limited data on treatment approaches. Our objective was to study the prevalence of BKV and BKVN utilizing only plasma qPCR and report treatment outcomes with stepwise IR and IVIG.MethodsA retrospective study of all pediatric kidney transplants from 2013 to 2020. Excluded patients >21 years at transplant and immediate graft failure. Surveillance was conducted using only plasma BK qPCR at 1, 3, 6, 9, 12, 18, and 24 months and annually. BKV defined as ≥250 copies/ml and resolution as 10 000 copies/ml despite IR; and BKVN if confirmed on histology.ResultsFifty-six patients were included in the study; 20 (35.7%) had BKV. BKV was associated with longer duration of stent, 40 vs. 33.5 days (p = .004). Two patients (3.5%) had confirmed, and 2(3.5%) had presumed BKVN. The first-line treatment was IR in 100% of patients. BKVN confirmed and presumed received IVIG every month for six doses. Viral resolution was achieved in 70%, and no difference was noted in estimated glomerular filtration rate between BKV and non-BKV group (p = .438). There were no rejection episodes, and graft survival was 100% over median follow-up of 3 years.ConclusionsPlasma qPCR alone is adequate for screening and monitoring treatment of BKV and BKVN. A stepwise IR and IVIG resulted in BKV resolution in the majority of patients. Larger studies are required to study the role of IVIG in the treatment of BKVN.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/172850/1/petr14241_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/172850/2/petr14241.pd

Prediction of saturation exponent for subsurface oil and gas reservoirs using soft computing methods

The most widely used equation to calculate water saturation or suitable shaly water saturation in clean or shaly formation, respectively, is the modified Archie formula. The quality of Archie parameters including saturation exponent affects the preciseness of water saturation, and thus estimated oil and gas in place. Therefore, estimating the saturation exponent by the soft computation methods deems to be necessary. In this study, intelligent models such as multilayer perceptron neural network, least squares support vector machine, radial basis function neural network, and adaptive neuro-fuzzy inference system are developed to predict saturation exponent in terms of petrophysical data including porosity, absolute permeability, water saturation, true resistivity, and resistivity index by utilizing a databank for middle east oil and gas reservoirs. The introduced models are optimized using particle swarm optimization, genetic algorithm, and levenberg marquardt techniques. Graphical and statistical methods are used to demonstrate the capability of the constructed models. Based on the statistical indexes obtained for each model, it is found that radial basis function neural network, multilayer perceptron neural network, and least squares support vector machine are the most robust models as they possess the smallest mean squared error, root mean squared error and average absolute relative error as well as highest coefficient of determination. Moreover, the sensitivity analysis indicates that water saturation has the most effect and porosity has the least effect on the saturation exponent. The developed models are simple-to-use and time-consuming tools to predict saturation exponent without needing laboratory methods which are tedious and arduous