Spatial clustering and hot spot analysis of the COVID-19 pandemic in Malatya province

It was revealed that what caused the disease that emerged with respiratory symptoms (fever, cough, shortness of breath) towards the end of 2019 in Wuhan city of China's Hubei province, and later named as COVID-19 by WHO was SARS-CoV-2 virus. The COVID-19 epidemic affected Turkey very quickly as it did the entire world, and the first official case in Turkey was detected in March 2020. In this study, how the COVID-19 cases are clustered in the districts of Malatya and the structure of this clustering as well as whether the cluster has changed over time was revealed by using the spatial exploratory analysis approach. For this purpose, Global and Local Moran I statistics that measure spatial interaction were used. For the hot spot analysis, Getis-Ord’s Gi* statistic was used. Moran I, which measures the spread of COVID-19 among districts, is statistically significant, and the spread effect is close to medium, although not very strong. It has been determined that Yazıhan and Akçadağ districts are the riskiest districts on average as of the period under consideration according to Lokal Moran I statistics. According to the Getis-Ord’s Gi* statistics, Yazıhan district is the one that is most suitable for the spread of the epidemic for Malatya, again being a hot spot location. It has been observed that Yazıhan district is frequently in the hot spot according to the monthly analysis of the Gi*statistics. In this context, it is important for Yazıhan district to increase the necessary measures in the coming periods and to make efforts to raise awareness of the citizens

Clinical Aspects and Emergent Management of Snake Bites Presented to Emergency Department

Evaluating the epidemiologic characteristics and management of snake bites presenting to emergency departments. Material and Method: In this retrospective study 74 cases of snakebites admitted to Emergency Department of Diyarbakir Training and Research Hospital between 2008 and 2009 were retrospectively evaluated. Results: Fourty-six (62.2%) of patients were male and 28 (37.8%) were female. Mean age of the study population was 34.85 +/- 19.17 (min 7-max 80) years. Most of the snakebites occurred between 18.00 to 06.00 hours and at home (73%). 79.7% of snake bites occurred to upper extremities. %93 of cases had intravenous administration of antivenin (one dose). Neither none of the patients needed recurrent administration. Discussion: Snake bites are still a major public health problem especially in rural areas. Particularly emergency care physicians should be adequately capable and sophisticated in multidisciplinary management of snake bites

Assessment of demographic, clinical and histopathological features of patients who underwent appendectomy due to a presumed diagnosis of acute appendicitis

BACKGROUND: To compare the clinical, biochemical, and histopathological features of patients who underwent appendectomy due to a presumed diagnosis of acute appendicitis (AAp)

Modeling Based on Ensemble Learning Methods for Detection of Diagnostic Biomarkers from LncRNA Data in Rats Treated with Cis-Platinum-Induced Hepatotoxicity

Background: The first aim of this study is to perform bioinformatic analysis of lncRNAs obtained from liver tissue samples from rats treated with cisplatin hepatotoxicity and without pathology. Another aim is to identify possible biomarkers for the diagnosis/early diagnosis of hepatotoxicity by modeling the data obtained from bioinformatics analysis with ensemble learning methods. Methods: In the study, 20 female Sprague-Dawley rats were divided into a control group and a hepatotoxicity group. Liver samples were taken from rats, and transcriptomic and histopathological analyses were performed. The dataset achieved from the transcriptomic analysis was modeled with ensemble learning methods (stacking, bagging, and boosting). Modeling results were evaluated with accuracy (Acc), balanced accuracy (B-Acc), sensitivity (Se), specificity (Sp), positive predictive value (Ppv), negative predictive value (Npv), and F1 score performance metrics. As a result of the modeling, lncRNAs that could be biomarkers were evaluated with variable importance values. Results: According to histopathological and immunohistochemical analyses, a significant increase was observed in the sinusoidal dilatation and Hsp60 immunoreactivity values in the hepatotoxicity group compared to the control group (p < 0.0001). According to the results of the bioinformatics analysis, 589 lncRNAs showed different expressions in the groups. The stacking model had the best classification performance among the applied ensemble learning models. The Acc, B-Acc, Se, Sp, Ppv, Npv, and F1-score values obtained from this model were 90%, 90%, 80%, 100%, 100%, 83.3%, and 88.9%, respectively. lncRNAs with id rna-XR_005492522.1, rna-XR_005492536.1, and rna-XR_005505831.1 with the highest three values according to the variable importance obtained as a result of stacking modeling can be used as predictive biomarker candidates for hepatotoxicity. Conclusions: Among the ensemble algorithms, the stacking technique yielded higher performance results as compared to the bagging and boosting methods on the transcriptomic data. More comprehensive studies can support the possible biomarkers determined due to the research and the decisive results for the diagnosis of drug-induced hepatotoxicity

Histopathological examination of acute appendicitis tissue in children during the COVID-19 pandemic

In this study, we prospectively investigated the histopathological features of the removed appendix tissue in pediatric patients who were operated on with the preliminary diagnosis of appendicitis. A catarrhal appendicitis group (n=43), a phlegmonous appendicitis group (n=28), a gangrenous appendicitis group (n=19), a perforated appendicitis group (n=35), and an appendicitis +COVID-19 group (n=7) were formed. The control group consisted of 21 children. A section of each patient&apos;s appendix tissue from the part with the highest diameter was taken for histopathological examination. The sections were routinely stained with hematoxylin and eosin (H&E). The two pathologists evaluated all H&E sections in a light microscope. The evaluation results were analyzed statistically. No significant differences in age and gender were found between all groups. The results of neutrophil and lymphocyte counts in all tissue layers of all groups were significantly different. Neutrophil count in the mucosa and muscularis propria in the appendix tissues of the control group were found to be zero. Among all groups, the highest number of neutrophil counts in the mucosa and muscularis propria were found in the perforated group. Among all groups, the highest number of lymphocyte counts in mucosa and muscularis propria were found in the Covid-19 group. The mucosal erosion, intraluminal neutrophils, and reactive lymphoid hyperplasia were negative in all samples in the control group. Neutrophil accumulation in the mucosa and muscularis propria layers in appendix tissue together with other inflammation findings are important in the histopathological diagnosis of appendicitis. In patients with Covid-19 infection, appendicitis may occur, in which case, severe accumulation of lymphocytes appears in the mucosal layer in addition. [Med-Science 2022; 11(4.000): 1527-33