This study was conducted to detect C.sakazakii PIF and raw milk. Two hundred samples of PIF were taken from the infected hospital infants who used this type of milk and from the local markets in addition to 16 sample of raw milk were collected. The study is the first to report the isolation of C. sakazakii and Enterobacter spp. from raw milk in Iraq. The distribution of C.sakazakii and Enterobacter spp. among the presumptive isolates using Vitek-GN2 system gave 1/16(6.25%) isolates of C.sakazakii and 4/16 (25%) isolates of Enterobacter spp. Enterobacter spp. isolates include (E.cloacae ssp. cloacae and E.cloacae ssp. dissolvens, E.hormaechei, and E.ludwigii) that isolate from raw milk Differences in between percentages of each isolate persence were non-significant (P<0.05). The results of antibioticsusceptibility were determined using Vitek-2GN system; .sakazakii isolates showed 100% resistance to cefazolin and cefoxitin, but were highly sensitive to many antibiotics includes (Imipenem, Meropenem, Amikacin, Gentamicin, Tobramycin, Ciprofloxacin, Levofloxacin, Nitrofurantion, Trimethoprim sulfamethoxazole, Ampicillin, Ampicillin sulbactam, Pipercillin Tazobactam, Ceftazidime, Ceftriaxone, Cefepime Azetreonam and augmentin ). The present study did not determine C.sakazakii in all the samples of PIF that is available in the local markets.
Multi-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the Al-Razzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.
Background: Obesity is a serious public health concern that has reached epidemic proportions; the prevalence, as well as the severity of obesity in adolescents is increasing at an alarming rate. A close relationship was found between weight status and dental caries. Thus this research aimed to assess the prevalence and severity of dental caries among overweight adolescent females in relation to physicochemical characteristics of stimulated whole saliva in comparison with normal weight adolescent females. Materials and methods: The total sample involved for nutritional status assessment is composed of 2678 females aged 13-15 years. This was performed using Body Mass Index specific for age and gender according to CDC growth chart (2000). The
... Show MoreMulti-spectral satellite images of the Landsat satellite by the tow sensitive Thematic Mapper (TM) and Thematic Mapper Enhancement (ETM+), which covered the study area located south east of Iraq. In this research; used the sixth thermal spectral band (Thermal Band) for study the water cover in the AlRazzaza Lake located within the province of Karbala. We intended to study the cover a case of the study area, used satellite images showing the status of region during the period from 1990 to 2001 and 2007. From this study we conclude that cover the water of the study area change in sequence case to decrease during these years.
Considering the expanding frequency of breast cancer and high incidence of vitamin D3 [25(OH)D3] insufficiently, this investigate pointed to explain a relation between serum [25(OH)D3] (the sunshine vitamin) level and breast cancer hazard. The current study aimed to see how serum levels of each [25(OH)D3], HbA1c%, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and triglyceride (TG) were affected a woman’s risk of getting breast cancer. In 40 healthy volunteers and 69 untreated breast cancer patients with clinical and histological evidence which include outpatients and hospitalized admissions patients at the Oncology Center, Medical City / Baghdad - Iraq. Venous blood samp
... Show MoreBackground: Depression is a common mental disorder that presents with depressed mood;it can become chronic or recurrent and affect dental health .Thus this research aimed to assess the prevalence and severity of dental caries among students with different grade of depression in relation to physicochemical characteristics of stimulated whole saliva. Materials and methods: The total sample involved for depression status assessment is composed of 800 students for both gender aged 15 years old that were selected randomly , This was performed using children depression inventory (CDI) index that divided the students into four groups of depression(low or average grade, high average grade, elevated grade and very elevated grade). The diagnosis and
... Show MoreCoronavirus disease 2019 (COVID-19) is a flu-like infection caused by a novel virus known as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). After the widespread around the world, it was announced by the World Health Organization (WHO) as a global pandemic. The symptoms of COVID-19 may arise within 2 weeks and the severity ranged from mild with signs of respiratory infection to severe cases of organ failure and even death. Management of COVID-19 patients includes supportive treatment and pharmacological medications expected to be effective with no definitive cure of the disease. The aims of this study are highlighting the management protocol and supportive therapy especially vitamin D and manifesting the clinical symptoms b
... Show MoreAutism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreEchocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.
Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b