Background: Pleural effusion is a common clinical
problem.
Objective: The aim of the study was to evaluate the
diagnostic utility of Carcino embryonic antigen
(CEA), CA 15- 3, and alpha-feto protein ( AFP ) as
a tumor markers in serum and pleural effusion and
evaluate the value of combining them as a diagnostic
tools that are complementary to cytology in the
diagnosis of malignancies .
Methods: Forty patients (18 malignant and 22 benign
pleural effusion) were included in this study .The
serum and effusion levels of CEA, CA 15 – 3 and
AFP were measured using immunoradiometric assay
Results: from the 40 effusions studied 26 were
exudates and 14 were transudates. The level of
pleural effusions of CEA, CA 15 – 3 and AFP were
increased above the cutoffs in 72.5%, 94.4 % and 5.5
% of tested samples with malignancies respectively.
A direct strong significant correlation between serum
and pleural fluid CEA, CA 15 – 3 and AFP was
noted.
Conclusion: Pleural effusion CEA is the most
accurate marker for the diagnostic separation of
malignant and benign. The combination of both CEA,
CA 15 – 3 improves the sensitivity by up to 11 %.
AFP has no role in the process
This paper presents a computer simulation model of a thermally activated roof (TAR) to cool a room using cool water from a wet cooling tower. Modeling was achieved using a simplified 1-D resistance-capacitance thermal network (RC model) for an infinite slab. Heat transfer from the cooling pipe network was treated as 2-D heat flow. Only a limited number of nodes were required to obtain reliable results. The use of 6th order RC-thermal model produced a set of ordinary differential equations that were solved using MATLAB - R2012a. The computer program was written to cover all possible initial conditions, material properties, TAR system geometry and hourly solar radiation. The cool water supply was considered time
... Show MoreThe ability of beans (Phaseolus vulgaris L.) to uptake three pharmaceuticals (diclofenac, mefenamic acid and metronidazole) from two types of soil (clay and sandy soil) was investigated in this study to explore the human exposure to these pharmaceuticals via the consumption of beans. A pot experiment was conducted with beans plants which were grown in two types of soil for six weeks under controlled conditions. During the experiment period, the soil pore water was collected weekly and the concentrations of the test compounds in soil pore water as well as in plant organs (roots, stems and leaves) were weekly determined.
The results showed that the studied pharmaceuticals were detected in all plant tissues; their concentration
This study depicts the removal of Manganese ions (Mn2+) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm2, time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis
... Show MoreThis study depicts the removal of Manganese ions (Mn2+) from simulated wastewater by combined electrocoagulation/ electroflotation technologies. The effects of initial Mn concentration, current density (C.D.), electrolysis time, and different mesh numbers of stainless steel screen electrodes were investigated in a batch cell by adopting Taguchi experimental design to explore the optimum conditions for maximum removal efficiency of Mn. The results of multiple regression and signal to noise ratio (S/N) showed that the optimum conditions were Mn initial concentration of 100 ppm, C.D. of 4 mA/cm2, time of 120 min, and mesh no. of 30 (wire/inch). Also, the relative significance of each factor was attained by the analysis of variance (ANO
... Show MoreErratum for Organic acid concentration thresholds for ageing of carbonate minerals: Implications for CO2 trapping/storage.
A new, simple, sensitive and fast developed method was used for the determination of methyldopa in pure and pharmaceutical formulations by using continuous flow injection analysis. This method is based on formation a burgundy color complex between methyldopa andammonium ceric (IV) nitrate in aqueous medium using long distance chasing photometer NAG-ADF-300-2. The linear range for calibration graph was 0.05-8.3 mmol/L for cell A and 0.1-8.5 mmol/L for cell B, and LOD 952.8000 ng /200 µL for cell A and 3.3348 µg /200 µL for cell B respectively with correlation coefficient (r) 0.9994 for cell A and 0.9991 for cell B, RSD % was lower than 1 % for n=8. The results were compared with classical method UV-Spectrophotometric at λ max=280 n
... Show MoreThis work presents a completely new develop an analyzer, named NAG-5SX1-1D-SSP, that is simple, accurate, reproducible, and affordable for the determination of cefotaxime sodium (CFS) in both pure and pharmaceutical drugs. The analyzer was designed according to flow injection analysis, and conducted to turbidimetric measurements. Ammonium cerium nitrate was utilized as a precipitating agent. After optimizing the conditions, the analysis system exhibited a linear range of 0.008-27 mmol. L-1 (n=29), with a limit of detection of 439.3 ng/sample, a limit of quantification of 0.4805 mg/sample, and a correlation coefficient of 0.9988. The repeatability of the responses was assessed by performing six successive injections of CFS at concentra
... Show MoreComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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