Objective: To determine the effectiveness of hypothermia on renal functions for patients undergoing
coronary artery bypass graft CABG surgery.
Methodology: A purposive (non-probability) sample of (50) patients undergoing Isolated coronary artery
bypass graft surgery consecutively admitted to the surgical ward, and they were followed up in the
intraoperative, Intensive Care Unit (ICU) and in the postoperative (surgical ward). Post-operative renal function
test (glumeruler filteration rate (GFR) by using the Crockroft-Gault formula and serum creatinine level) was
determined first week post operative and post operative renal function was classified on the base of peak of
the serum creatinine level and decline of glomeruler filteration rate(GFR) as following : normal renal function
serum creatinine concentration and decline in(GFR) less than 25% from preoperative, moderate renal
dysfunction increase serum creatinine concentration and decline in(GFR) 25%-50% from preoperative, sever
renal dysfunction increase serum creatinine concentration and decline in(GFR) more than 50% from
preoperative test.
Results: results of this study show that (78%) from the sample develop post operative renal dysfunction and
the highly percentage of them are male (50%), advance age 60-70 (60%), smoking (47.0%), diabetes mellitus
DM (68%), cardiopulmonary bypass 180 and more (57.20%), New York Heart Association calcification NYHA
class III(47.5%) and patient without Intra Aortic Balloon Pump IABP(50,0%) . We conclude from the study that
highly percentage of patient undergoing isolated CABG may develop postoperative renal dysfunction even
when using hypothermic strategy as a protective measure and the patients with DM, male, advance age,
smoker, prolong time of CPB (more than 180 minutes), NYHA class III and patient without IABP are considered
as patient at high risk to develop postoperative renal dysfunction.
Recommendations: The researcher recommended that to find addition strategy rather than hypothermia
to protect renal function especially with the high risk patients during isolated CABG surgery.
The pancreatic ductal adenocarcinoma (PDAC), which represents over 90% of pancreatic cancer cases,
has the highest proliferative and metastatic rate in comparison to other pancreatic cancer compartments. This
study is designed to determine whether small nucleolar RNA, H/ACA box 64 (snoRNA64) is associated with
pancreatic cancer initiation and progression. Gene expression data from the Gene Expression Omnibus (GEO)
repository have shown that snoRNA64 expression is reduced in primary and metastatic pancreatic cancer as
compared to normal tissues based on statistical analysis of the in Silico analysis. Using qPCR techniques,
pancreatic cancer cell lines include PK-1, PK-8, PK-4, and Mia PaCa-2 with differ
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The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences
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Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste
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Empirical equations for estimating thickening time and compressive strength of bentonitic - class "G" cement slurries were derived as a function of water to cement ratio and apparent viscosity (for any ratios). How the presence of such an equations easily extract the thickening time and compressive strength values of the oil field saves time without reference to the untreated control laboratory tests such as pressurized consistometer for thickening time test and Hydraulic Cement Mortars including water bath ( 24 hours ) for compressive strength test those may have more than one day.
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The flexible joint robot (FJR) typically experiences parametric variations, nonlinearities, underactuation, noise propagation, and external disturbances which seriously degrade the FJR tracking. This article proposes an adaptive integral sliding mode controller (AISMC) based on a singular perturbation method and two state observers for the FJR to achieve high performance. First, the underactuated FJR is modeled into two simple second-order fast and slow subsystems by using Olfati transformation and singular perturbation method, which handles underactuation while reducing noise amplification. Then, the AISMC is proposed to effectively accomplish the desired tracking performance, in which the integral sliding surface is designed to reduce cha
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