Introduction: A Pap test can detect pre-cancerous and cancerous cells in the vagina and uterine cervix. Cervical cancer is the easiest gynecologic cancer to be prevented and diagnosed using regular screening tests and follow-up. This study aimed to estimate the cytological changes and the precancerous lesions using Pap smear test and visual inspection of the cervices of Iraqi women, and also to determine the possible relationship of this cancer with patients’ demographic characteristics. Methods: The study included 140 women aged (18-67) years old referred to the National Cancer Research Center (NCRC), Baghdad, Iraq, during the period 2011-2016. Both visual inspections of the uterine cervix and Papanicolaou smear screening were performed for all of the participants. Results: Only 14% of the women under study were in postmenopausal, and 86% were in premenopausal period. Visual inspection of the cervix showed that 48.6% of the women had erosion lesions. Upon cytology examination, 92.8% of the women showed non-specific inflammation, 70% revealed reactive squamous metaplasia, 27% had Koilocytotic atypia, and 17% suffered from cervical intraepithelial neoplasia (CIN1) or low grade squamous intraepithelial lesion (LGSIL). Contraception was used by 68% of those women, while 34.3% of them used pills. Most women, 79%, had multiple births. The abnormal vaginal discharge occurred in 34% of the participants that is why they attended the center compared with only 25.7% who came for routine checking. Finally, 67% of the participated women did not make this test previously. Conclusion: We conclude routine screening and Pap smear testing for uterine cervix and vagina might be useful especially for sexually active women for preventing the occurrence of precancerous and later cancerous lesions in these organs.
Aim: This study aims to determine both the level of knowledge, attitude, and practice in clinical breast examination in women and the relationship between knowledge and practice.Data collection was performed within a three-month period starting from February 2019 on. Subjects and Method: A cross-sectional analytical study included 657 non-randomly selected women visiting primary health care centers in Baghdad city with an average of age between (20-59) years old. Results: Only 51.8% ever heard of clinical breast examination. The mean knowledge score for clinical breast examination was (51.2±44). Only 5.5% of women performed regular clinical breast examinations. Participants who adequately practice clinical breast examinatio
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Background: There is plenty of evidence
suggesting that involvement of several groups of
viruses in the development and / or acceleration of
Type 1 Diabetes Mellitus (T1DM).
Objective: To analyze the T- cell proliferation in
the presence of Coxsackie virus B5 (CVB5), Polio
and Adenovirus antigens in addition to assessment
of Interferon- gamma (IFN-γ), Interleukins (IL-10
and IL-6).
Methods: In 60 Iraqi T1DM children with recent
onset of T1DM, Lymphocyte proliferation was
analyzed using Methylthiazol tetrazolium (MTT)
assay by culturing Peripheral Blood Lymphocytes
(PBLs) with Coxsackie Virus B5 (CVB5),
Adenovirus, and Polio vaccine. Serum Interferon-γ,
IL-10 and IL-6 were quantified by sandw
Rutting is mainly referring to pavement permanent deformation, it is a major problem for flexible pavement and it is a complicated process and highly observed along with many segments of asphalt pavement in Iraq. The occurrence of this defect is related to several variables such as elevated temperatures and high wheel loads. Studying effective methods to reduce rutting distress is of great significance for providing a safe and along-life road. The asphalt mixture used to be modified by adding different types of additives. The addition of additives typically excesses stiffness, improves temperature susceptibility, and reduces moisture sensitivity. For this work, steel fibres have been used for modifying asphalt mixture as they incorp
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The current work is characterized by simplicity, accuracy and high sensitivity Dispersive liquid - Liquid Micro Extraction (DLLME). The method was developed to determine Telmesartan (TEL) and Irbesartan (IRB) in the standard and pharmaceutical composition. Telmesartan and Irbesartan are separated prior to treatment with Eriochrom black T as a reagent and formation ion pair reaction dye. The analytical results of DLLME method for linearity range (0.2- 6.0) mg /L for both drugs, molar absorptivity were (1.67 × 105- 5.6 × 105) L/ mole. cm, limit of detection were (0.0242and0.0238), Limit of quantification were (0.0821and0.0711), the Distribution coefficient were
... Show MoreBackground: Neonatal hyperbilirubinemia is a common disease in neonates especially in early days of birth that requires a good and successful treatment for reducing the severity and its complications that can produce important and irreversible effects.
Objectives: To evaluate the effectiveness of conventional phototherapy, intensive phototherapy and exchange transfusion on outcomes of neonatal jaundice at Fatima Al-Zahra Hospital for maternity and child care in Baghdad.
Patients & Methods: A retrospective study was carried out using medical records of neonates with diagnosis of unconjugated jaundice, admitted in the septic neonatal care unit of Fatima Al-Zahra hospital over 6 months period b
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During 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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During 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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