Abstract Diabetic nephropathy (DN) is a prevalent chronic microvascular diabetic complication. As inflammation plays a vital role in the development and progress of DN the macrophages migration inhibitory factor (MIF), a proinflammatory multifunctional cytokine approved to play a critical function in inflammatory responses in various pathologic situations like DN. This study aimed To assess serum levels of MIF in a sample of Iraqi diabetic patients with nephropathy supporting its validity as a marker for predicting nephropathy in T2DM patients. In addition, to evaluate the nephroprotective effect of angiotensin-converting enzyme (ACE) inhibitors in terms of their influence on MIF levels. This is a case-control study involving ninety

This study is concerned with the recent changes that occurred in the last three years (2017-2019) in the marshes region in southern Iraq as a result of the changes in the global climate, the study included all the water bodies in the five governorates that are located in the southern regions of Iraq (Wasit, Maysan, Dhi-Qar, Qadisiyah and Basrah), which represent the marshes lands in Iraq. Scenes of the Landsat 8 satellite are used to create a mosaic to cover the five governorates within a time window with the slightest difference between the date of the scene capture, not to exceed 8 days. The results of calculating the changes in water areas were obtained using the classifier support vector machine, where high accuracy ratios were recorded

Food industries are variety to include number of agricultural products (plantbotential and animal) which can be manufactured locally, thus, Iraqi market is full by different types of food products from neighbor countries, because of un equivalence and inability of competence, in away to cover (90%) average of local request need under commercial  opening.

In Iraq although its importance, this industry suffers from difficulties, the most important one is the rising  in  products costs, shortage in agricultural products, experience, and qualification, besides, the challenges , by flooding market in food products and what are contained of higher competitive features from quality and prices side

Atheists have spread in the modern era, so that atheism has become a bad phenomenon in the world in general and in Islamic societies in particular, so the research aims to study the individual and social effects left by atheism on the atheists themselves, and the research included multiple axes: atheism linguistically and idiomatically, atheism in the Qur’an Noble and Modern (and Contemporary) Atheism Statistics: and the reasons for atheism: Studying the phenomenon of atheism in Iraq as a model, then studying the effects of atheism: on the individual first, then atheism and its impact on society, then the conclusion, recommendations, sources and references

AbstractBackgroundLeishmaniasis is endemic in Iraq, where both cutaneous and visceral forms of the disease are reported.ObjectivesTo determine the prevalence of cutaneous leishmaniasis (CL) and to identify associations of CL with age, sex, season, and provinces depending on some demographic and climatic aspects.MethodsThis study is retrospective and includes reported cases of infections using the available surveillance database taken from the Iraqi Ministry of Health for the years 2011, 2012, and 2013 for all provinces of Iraq.ResultsMen and boys were found to be at higher risk for CL compared with women and girls. The majority of cases were recorded among those in age groups 5–14 and 15–45 years old. Most cases were recorded from lowla

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system