Objective To highlight the main demographic characteristics and clinical profiles of female patients registered with breast cancer in Iraq; focusing on the impact of age.Methods This retrospective study enrolled 1172 female patients who were diagnosed with breast cancer at the Main Center for Early Detection of Breast Cancer/Medical City Teaching Hospital in Baghdad. Data were extracted from an established information system, developed by the principal author under supervision of WHO, that was based on valid clinical records of Iraqi patients affected by breast cancer. The recorded information regarding clinical examination comprised positive palpable lumps, bloody nipple discharge, skin changes, bilateral breast involvement, tumor size, lymph node status, and the stage of the disease.Results The mean age at the presentation was 51 years; patients under the age of 50 constituted 46.8%. Overall 9.8% were not married, 22.4% were illiterate whereas 19.2% graduated from universities. About 72% of the patients had more than two children, merely 7.5% delivered their first child after the age of 35 years and only 11% were nulliparous. History of lactation and hormonal therapy was recorded in 57.6% and 19.4% respectively. Family history of cancer was positive in 28.8% and breast cancer specifically in 18.7%. Clinically, the most common presenting symptom was breast lumps (95%) followed by skin changes/ulcerations (6.7%) and bloody nipple discharge (4.3%).Bilateral breast involvement was encountered in 4.7%. More than two-thirds of the patients (68.2%) had palpable axillary lymph nodes; classifying 40.5% into advanced stages III and IV. In general stages I–IV comprised 12%, 47.5%, 31.9%, and 8.6% respectively. Upon stratifying the studied sample with respect to age at diagnosis, it was observed that the frequency of unmarried patients was significantly higher among younger women under the age of 50 years, whereas illiteracy and nulliparity features were statistically lower (p < 0.05).Conclusion A considerable proportion of breast cancer patients in Iraq still present with locally advanced disease at the time of diagnosis. That justifies the necessity to promote public awareness educational campaigns to strengthen our national early detection program. Excluding the marital status, level of education and number of parity, there was no statistical difference regarding the impact of age on the demographic and clinical profiles of breast cancer among premenopausal versus postmenopausal Iraqi patients.
The optimum conditions for the production of neutral protease from local strain Aspergillus niger var carbonarius by solid – state fermentation system (Wheat bran) moisted with 0.2 M phosphate buffer (PH7.0) . the hydration ratio was 1:5 (V:W) . the concentration of inoculum was 1×106 spores per 10 gram of solid materials , initial P H 6.5 and 96 hours of incubation period at 30? C .the enzyme activity was 1300 unit / ml and specific activity was 1550 unit / mg protein .
KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1
Methylotrophs bacteria are ubiquitous, and they have the ability to consume single carbon (C1) which makes them biological conversion machines. It is the first study to find facultative methylotrophic bacteria in contaminated soils in Iraq. Conventional PCR was employed to amplify MxaF that encodes methanol dehydrogenase enzyme. DNA templates were extracted from bacteria isolated from five contaminated sites in Basra. The gene specific PCR detected Methylorubrum extorquens as the most dominant species in these environments. The ability of M. extorquens to degrade aliphatic hydrocarbons compound was tested at the laboratory. Within 7 days, gas chromatographic (GC) studies of remaining utilize
... Show MoreCatalytic reduction is considered an effective approach for the reduction of toxic organic pollutants from the environment, but finding an active catalyst is still a big challenge. Herein, Ag decorated CeO2 catalyst was synthesized through polyol reduction method and applied for catalytic reduction (conversion) of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP). The Ag decorated CeO2 catalyst displayed an outstanding reduction activity with 99% conversion of 4-NP in 5 min with a 0.61 min−1 reaction rate (k). A number of structural characterization techniques were executed to investigate the influence of Ag on CeO2 and its effect on the catalytic conversion of 4-NP. The outstanding catalytic performances of the Ag-CeO2 catalyst can be assigne
... Show MoreIn this work, enhancement to the fluorescence characteristics of laser dye solutions hosting highly-pure titanium dioxide nanoparticles as random gain media. This was achieved by coating two opposite sides of the cells containing these media with nanostructured thin films of highly-pure titanium dioxide. Two laser dyes; Rhodamine B and Coumarin 102, were used to prepare solutions in hexanol and methanol, respectively, as hosts for the nanoparticles. The nanoparticles and thin films were prepared by dc reactive magnetron sputtering technique. The enhancement was observed by the narrowing of fluorescence linewidth as well as by increasing the fluorescence intensity. These parameters were compared to those of the dye only and the dye solution
... Show MoreIn this study, a packed bed was used to remove pathogenic bacteria from synthetic contaminated water. Two types of packing material substrates, sand and zeolite, were used. These substrates were coated with silver nanoparticles (AgNPs), which were prepared by decomposition of Ag ions from AgNO3 solution. The prepared coated packings were characterized using scanning electron microscopy, energy-dispersive X-ray spectroscopy and transmission electron microscopy. The packed column consisted of a PVC cylinder of 2 cm diameter and 20 cm in length. The column was packed with silver nanoparticlecoated substrates (sand or zeolite) at a depth of 10 cm. Four types of bacteria were studied: Escherichia coli, Shigella dysenteriae, Pseudomonas aerugi
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
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