9 research outputs found
Machine learning-based ovarian cancer prediction with XGboost and stochastic gradient boosting models
Ovarian cancer is one of the most common types of gynecological malignancies with its high mortality rate, silent and occult tumor growth, late onset of symptoms and diagnosis in advanced stages. Therefore, the need to develop new diagnostic techniques to predict the course of the disease and the prognosis of this malignancy has increased. In this study, ovarian cancer and benign ovarian tumor samples will be classified to create an accurate diagnostic predictive model using the machine learning method XGBoost and Stochastic Gradient Boosting and disease-related risk factors will be determined. This current study considered the open-access ovarian cancer and benign ovarian tumor samples data set. For this purpose, data from 349 patients were included. The data set was divided as 80:20 as a training and test dataset. XGBoost and Stochastic Gradient Boosting were constructed for the classification via five-fold cross-validation. Accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, and negative predictive value performance metrics were evaluated for model performance. Among the performance criteria in the test stage obtained from the XGBoost model that has the best classification result; accuracy, balanced accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score were obtained as 89.5%, 88.7%, 85.7%, 91.7%, 85.7%, 91.7%, and 85.7%, respectively. According to the variable importance obtained as a result of the model, the variables most associated with the diagnosis were CA72-4, HE4, LYM%, ALB, EO%, BUN, RBC, NEU, and MCV, respectively. The applied machine learning model successfully classified ovarian cancer and created a highly accurate diagnostic prediction model. The results from the study revealed effective parameters that can diagnose ovarian cancer with high accuracy. With the parameters determined as a result of the modeling, the clinician will be able to simplify and facilitate the decision-making process for the diagnosis of ovarian cancer. [Med-Science 2023; 12(1.000): 231-7
Myocardial necrosis markers in myocardial ischemia reperfusion (MI/R) injury: a review
Myocardial ischemia/reperfusion injury is one of the main causes of morbidity and mortality in the world. This injury is experienced by patients suffering from cardiovascular diseases such as coronary heart diseases and subsequently undergoing reperfusion treatments in order to manage the conditions. Ischemia can be especially detrimental to the heart due to its high energy demand. Several cellular alterations have been observed upon the onset of ischemia. The danger created by cardiac ischemia is somewhat paradoxical in that a return of blood to the tissue, termed reperfusion, can result in further damage. The serum markers of myocardial injury are used to help in establishing the diagnosis of myocardial infarction. Use of various biochemical markers, including lactate dehydrogenase (LDH), creatine kinase (CK) total enzyme activity, CK-MB activity, Myoglobin, CK-MB mass, cardiac troponin I (cTnI), and cardiac troponin T (cTnT) have been investigated for noninvasive assessment of reperfusion. It is hoped that further studies will help refine the clinical use of new biomarkers like hs-cTn immunoassays in myocardial injury. [Med-Science 2017; 6(1.000): 163-71
Beneficial effects of melatonin on acetylsalicylic acid induced liver damage in rats
We investigated the effects of acute high doses of acetylsalicylic acid (ASA) on liver tissue and the protective and therapeutic effects of melatonin on ASA related damage. Forty rats were randomly divided into five groups of eight: group 1, control; group 2, administered 200 mg/kg ASA; group 3, administered 5 mg/kg melatonin 45 min before ASA; group 4, administered 5 mg/kg melatonin 45 min after ASA; group 5, administered 5 mg/kg melatonin. We measured malondialdehyde (MDA), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), reduced glutathione (GSH), myeloperoxidase (MPO) aspartate aminotransferase (AST) and alanine transaminase (ALT) in the liver. ASA treatment significantly increased MDA and MPO production, whereas it significantly decreased levels of SOD, CAT, GPx and GSH in the liver. Melatonin significantly decreased MDA and MPO production, whereas it caused increased levels of antioxidants. AST and ALT levels were higher after ASA treatment, whereas these levels were reduced significantly after melatonin administration. Our histopathological findings, including apoptosis, were consistent with the biochemical results. Melatonin exhibits beneficial effects against high dose ASA induced hepatotoxicity. [Med-Science 2017; 6(4.000): 653-658
Cardiovascular effects of JWH-018 from synthetic cannabinoids [Sentetik kannabinoidlerden JWH-018in kardiyovaskuler etkileri]
The content of synthetic cannabinoids (SC) which are known in Europe as Spice, in the U.S.A. as K2, and in Turkey as Bonsai or Jamaica is not standard. Also SC are known to contain approximately 400 chemical compounds which vary from country to country. SC mimics the effect of Δ9-tetrahydrocannabinol (THC) which is the major effective content of Cannabis or Marijuana by cannabinoid-1 (CB1) and cannabinoid-2 (CB2) receptors in the body cell. Although the new SC are synthesized and the number of new variants is increased in every day; JWH-018 among these variants exerts full agonist effect on both CB1 and CB2 receptors also it has a short-term effect as 2 hours. For this reason, JWH-018 is the most commonly used as SC. There are a few data in the literature regarding to the pharmacokinetic and pharmacodynamic effects of SC. Furthermore, most of the existing data are based on in vitro experiments. In the JWH-018 report, at Critical Review Report Agenda item 4.5 Expert Committee on Drug Dependence of World Health Organization (WHO), Thirty‐sixth Meeting Geneva, 16‐20 June 2014, is declared that despite a marked elevation of the heart rate is one of the clinical signs very often seen after intoxication with SC, there is no available study data regarding effects of SC on cardiovascular, respiratory, gastrointestinal, liver, kidneys and genitourinary systems. The aim of this review is to highlight cardiovascular effects of JW-018 which is considered to be the prototype for synthetic cannabinoids to prepare the ground for new work to be done. [Med-Science 2016; 5(4.000): 1049-54
Effects of mirtazapine on cisplatin cardiotoxicity in rats
Atypical antidepressant mirtazapine (MIR) is primarily used to treat major depressive disorder. It has not been clarified whether cardiovascular uncertainties and mechanisms of action emerge as problems during the use of mirtazapine. Cisplatin (CIS) is an effective anti-cancer medication used to treat a variety of human malignancies. There were four groups of 32 Wistar albino male rats in all. Rats were split into 4 groups at random. 1. Control Group, 2. CIS Group, 3. MIR Group, 4. MIR+CIS Group. On the 15th day of the study, ECG, heart rate, and blood pressure were determined. Histopathological and biochemical analyses were carried out on cardiac and vascular tissue samples. Comparing the CIS group to the other groups, blood pressure was considerably lower in the CIS group (p [Med-Science 2023; 12(2.000): 579-86
Dexpanthenol prevents ovarian ischemic damage via antioxidant mechanisms in rats
Ovarian torsion is a gynecological emergency characterized by ovarian ischemic damage. This study aimed to investigate the possible protective effects of dexpanthenol (DEX)-an antioxidant molecule-against ovarian ischemic damage in rats. The rats were simple randomly grouped into (1) Sham group (n=8); (2) Ischemia (I) group (n=8) (2 hours of I in ovaries); (3) DEX+I group (n=8) (500 mg/kg DEX administration 30 minutes before 2 hours of I.) The removed ovaries were examined histopathologically and biochemically. In the DEX+I group, necrosis-pycnosis severity was significantly reduced compared to the I group; but congestion-hemorrhage severity was similar. In the I group, malondialdehyde (MDA) and total oxidant status (TOS) levels were slightly increased, and glutathione (GSH) levels were significantly decreased compared to the Sham group. In the DEX+I group, MDA and TOS levels were slightly reduced and GSH levels were slightly increased compared to the I group. DEX prevents ischemic damage in rat ovaries via an antioxidant effect. Further research is needed to support our findings. [Med-Science 2023; 12(4.000): 1213-7
The protective and therapeutic effects of agmatine on isoproterenol-induced myocardial injury in rats
Chronic inflammation and oxidative stress can contribute to the development of cardiovascular diseases. Isoproterenol (ISO), a synthetic catecholamine, is used to study the effects of drugs on cardiotoxicity. Agmatine (AGM) is a type of biogenic amine produced through the decarboxylation of arginine. The purpose of the current study was to evaluate the effects of AGM against ISO-induced cardiotoxicity due to the described roles of AGM in cardiovascular disease. Four groups of thirty-two Wistar Albino rats were divided equally as control, ISO, AGM+ISO, and ISO+AGM. ISO was administered intraperitoneally (i.p.) twice at a dose of 150 mg/kg, at 24-hour intervals. Prior to and after ISO injection, 20 mg/kg of AGM was injected i.p. Hemodynamic measurements and serum and tissue biochemical analyses were evaluated at the end of the experiment. The levels of glutathione (GSH), catalase (CAT), superoxide dismutase (SOD), and malondialdehyde (MDA) in the tissue were measured. In the ISO group, levels of lactate dehydrogenase (LDH) and creatine kinase (CK) were increased significantly (p [Med-Science 2023; 12(4.000): 1290-6
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