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The ability of various cerebroplacental ratio thresholds to predict adverse neonatal outcomes in term fetuses exhibiting late-onset fetal growth restriction
(Walter De Gruyter Gmbh, 2021) Melekoglu, Rauf; Yilmaz, Ercan; Yasar, Seyma; Hatipoglu, Irem; Kahveci, Bekir; Sucu, Mete
Objectives: Our primary aim was to evaluate the ability of various cerebroplacental ratio (CPR) reference values suggested by the Fetal Medicine Foundation to predict adverse neonatal outcomes in term fetuses exhibiting lateonset fetal growth restriction (LOFGR). Our secondary aim was to evaluate the effectiveness of other obstetric Doppler parameters used to assess fetal well-being in terms of predicting adverse neonatal outcomes. Methods: This was a retrospective cohort study of 317 pregnant women diagnosed with LOFGR at 37-40 weeks of gestation between January 1, 2016, and September 1, 2019. Receiver operating characteristic (ROC) curves were drawn to determine the predictive performance of CPR <1, CPR <5th or <10th percentile, and umbilical artery pulsatility (PI) >95th percentile in terms of predicting adverse neonatal outcomes. Results: Pregnant women exhibiting LOFGR who gave birth in our clinic during the study period at a mean of 38 gestational weeks (minimum 37+0; maximum 40+6 weeks); the median CPR was 1.51 [interquartile range (IQR) 1.12-1.95] and median birthweight 2,350 g (IQR 2,125-2,575 g). The CPR <5th percentile best predicted adverse neonatal outcomes [area under the curve (AUC) 0.762, 95% confidence interval (CI) 0.672-0.853, p<0.0001] and CPR <1 was the worst predictor (AUC 0.630, 95% CI 0.515-0.745, p=0.021). Of other Doppler parameters, neither the umbilical artery systole/diastole ratio nor the mid-cerebral artery to peak systolic velocity ratio (MCA-PSV) predicted adverse neonatal outcomes (AUC 0.598, 95% CI 0 .480 - 0.598, p=0.104; AUC 0.521, 95% CI 0.396-0.521, p=0.744 respectively). Conclusions: The CPR values below the 5th percentile better predicted adverse neonatal outcomes in pregnancies complicated by LOFGR than the UA PI and CPR <1 by using Fetal Medicine Foundation reference ranges.
Artificial Intelligence-Based Prediction of Covid-19 Severity on the Results of Protein Profiling
(Elsevier Ireland Ltd, 2021) Yasar, Seyma; Colak, Cemil; Yologlu, Saim
Background: COVID-19 progresses slowly and negatively affects many people. However, mild to moderate symptoms develop in most infected people, who recover without hospitalization. Therefore, the development of early diagnosis and treatment strategies is essential. One of these methods is proteomic technology based on the blood protein profiling technique. This study aims to classify three COVID-19 positive patient groups (mild, severe, and critical) and a control group based on the blood protein profiling using deep learning (DL), random forest (RF), and gradient boosted trees (GBTs). Methods: The dataset consists of 93 samples (60 COVID-19 patients, 33 control), and 370 variables obtained from an open-source website. The current dataset contains age, gender, and 368 protein, used to predict the relationship between disease severity and proteins using DL and machine learning approaches (RF, GBTs). An evolutionary algorithm tunes hyperparameters of the models and the predictions are assessed through accuracy, sensitivity, specificity, precision, F1 score, classification error, and kappa performance metrics. Results: The accuracy of RF (96.21%) was higher as compared to DL (94.73%). However, the ensemble classifier GBTs produced the highest accuracy (96.98%). TGB1BP2 in the cardiovascular II panel and MILR1 in the inflammation panel were the two most important proteins associated with disease severity. Conclusions: The proposed model (GBTs) achieved the best prediction of disease severity based on the proteins compared to the other algorithms. The results point out that changes in blood proteins associated with the severity of COVID-19 may be used in monitoring and early diagnosis/treatment of the disease. Background: COVID-19 progresses slowly and negatively affects many people. However, mild to moderate symptoms develop in most infected people, who recover without hospitalization. Therefore, the development of early diagnosis and treatment strategies is essential. One of these methods is proteomic technology based on the blood protein profiling technique. This study aims to classify three COVID-19 positive patient groups (mild, severe, and critical) and a control group based on the blood protein profiling using deep learning (DL), random forest (RF), and gradient boosted trees (GBTs). Methods: The dataset consists of 93 samples (60 COVID-19 patients, 33 control), and 370 variables obtained from an open-source website. The current dataset contains age, gender, and 368 protein, used to predict the relationship between disease severity and proteins using DL and machine learning approaches (RF, GBTs). An evolutionary algorithm tunes hyperparameters of the models and the predictions are assessed through accuracy, sensitivity, specificity, precision, F1 score, classification error, and kappa performance metrics. Results: The accuracy of RF (96.21%) was higher as compared to DL (94.73%). However, the ensemble classifier GBTs produced the highest accuracy (96.98%). TGB1BP2 in the cardiovascular II panel and MILR1 in the inflammation panel were the two most important proteins associated with disease severity. Conclusions: The proposed model (GBTs) achieved the best prediction of disease severity based on the proteins compared to the other algorithms. The results point out that changes in blood proteins associated with the severity of COVID-19 may be used in monitoring and early diagnosis/treatment of the disease. ? 2021 Elsevier B.V. All rights reserved.
Assessment of Sepsis Risk at Admission to the Emergency Department: Clinical Interpretable Prediction Model
(Mdpi, 2024) Aygun, Umran; Yagin, Fatma Hilal; Yagin, Burak; Yasar, Seyma; Colak, Cemil; Ozkan, Ahmet Selim; Ardigo, Luca Paolo
This study aims to develop an interpretable prediction model based on explainable artificial intelligence to predict bacterial sepsis and discover important biomarkers. A total of 1572 adult patients, 560 of whom were sepsis positive and 1012 of whom were negative, who were admitted to the emergency department with suspicion of sepsis, were examined. We investigated the performance characteristics of sepsis biomarkers alone and in combination for confirmed sepsis diagnosis using Sepsis-3 criteria. Three different tree-based algorithms-Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), Adaptive Boosting (AdaBoost)-were used for sepsis prediction, and after examining comprehensive performance metrics, descriptions of the optimal model were obtained with the SHAP method. The XGBoost model achieved accuracy of 0.898 (0.868-0.929) and area under the ROC curve (AUC) of 0.940 (0.898-0.980) with a 95% confidence interval. The five biomarkers for predicting sepsis were age, respiratory rate, oxygen saturation, procalcitonin, and positive blood culture. SHAP results revealed that older age, higher respiratory rate, procalcitonin, neutrophil-lymphocyte count ratio, C-reactive protein, plaque, leukocyte particle concentration, as well as lower oxygen saturation, systolic blood pressure, and hemoglobin levels increased the risk of sepsis. As a result, the Explainable Artificial Intelligence (XAI)-based prediction model can guide clinicians in the early diagnosis and treatment of sepsis, providing more effective sepsis management and potentially reducing mortality rates and medical costs.
Automated Classification of Brain Tumors by Deep Learning-Based Models on Magnetic Resonance Images Using a Developed Web-Based Interface
(Duzce Univ, Fac Medicine, 2021) Tetik, Bora; Ucuzal, Hasan; Yasar, Seyma; Colak, Cemil
Objective: Primary central nervous system tumors (PCNSTs) compose nearly 3% of newly diagnosed cancers worldwide and are more common in men. The incidence of brain tumors and PCNSTs-related deaths are gradually increasing all over the world. Recently, many studies have focused on automated machine learning (AutoML) algorithms which are developed using deep learning algorithms on medical imaging applications. The main purposes of this study are -to demonstrate the use of artificial intelligence-based techniques to predict medical images of different brain tumors (glioma, meningioma, pituitary adenoma) to provide techicalsupport to radiologists and -to develop a user-friendly and free web-based software to classify brain tumors for making quick and accurate clinical decisions. Methods: Open-sourced T1-weighted magnetic resonance brain tumor images were achieved from Nanfang Hospital, Guangzhou, China, and General Hospital, Tianjin Medical University, To construct the proposed system which web-based interface and the deep learning-based models, the Keras/Auto-Keras library, which is employed in Python's programming language, is used. Accuracy, sensitivity, specificity, G-mean, F-score, and Matthews correlation coefficient metrics were used for performance evaluations. Results: While 80% (2599 instances) of the dataset was used in the training phase, 20% (465 instances) was employed in the testing phase. All the performance metrics were higher than 98% for the classification of brain tumors on the training data set. Similarly, all the evaluation metrics were higher than 91% except for sensitivity and MCC for meningioma on the testing dataset. Conclusions: The results from the experiment reveal that the proposed software can be used to detect and diagnose three types of brain tumors. This developed web-based software can be accessed freely in both English and Turkish at http://biostatapps.inonu.edu.tr/BTSY/.
Bridged NHC-Pd(II) complexes: Synthesis, DFT calculations, molecular docking, and investigation of catalytic and biological activities
(Elsevier Science Sa, 2024) Firat, Tuba; Bugday, Nesrin; Yasar, Seyma; Boulebd, Houssem; Mansour, Lamjed; Koko, Waleed S.; Hamdi, Naceur
Six palladium(II) ( 3a -f ) complexes of the type [Pd 2 ( mu-Cl) 2 (NHC)] were prepared by transmetallation of the corresponding Ag-NHC and [PdCl 2 (CH 3 CN) 2 ] complexes, and their structures were successfully characterised by 1 H NMR, 13 C NMR, HRMS, FTIR and elemental analysis. Density functional theory (DFT) calculations were also realised for the complexes. The prepared complexes were assessed for their catalytic activity in the C -H arylation of 2-isobuthylthiazole as well as for their biological activities. As results, these complexes were found to be potent catalysts in the creation of C5-arylated 2-isobuthylthiazole derivatives via C -H bond activation reaction. Furthermore, biological activity analysis revealed that complex 3a exhibits high cytotoxicity towards both human colon carcinoma cell lines (HCT-116) and hepatocellular carcinoma cell lines (HepG-2) with IC 50 values of 4.2 and 9.3 mu MmL -1 , respectively. Complex 3b also showed antioxidant activity comparable to that of BHT through DPPH and ABTS assays. Both complexes 3d and 3f also showed significant inhibitory activity towards the AChE enzyme with IC 50 values of 5.06 and 2.52 mu MmL -1 , respectively. Finally, all complexes showed excellent antiparasitic activity, with 3b exhibiting strong antileishmanial activity against both L. major promastigotes and amastigotes. The interaction between the most cytotoxic complexes and DNA, envisaged as a potential mechanism of toxicity, was explored by means of docking studies. In summary, these prepared complexes have the potential to serve as potent catalysts for the synthesis of arylated 2-isobutylthiazole and biologically active agents, paving the way for numerous prospects in the fields of medicinal chemistry and organic synthesis.
Classification of healthy controls and Covid-19 cases established on transcriptomic analysis using proposed ensemble model
(2021) Kucukakcali, Zeynep; Yasar, Seyma; Çolak, Cemil
COVID-19, which is a highly contagious disease, has different symptoms in humans. Therefore, the scientific and genetic status of the virus should be clarified as soon as possible. This study aims to classify COVID-19 and determine the important genes related to the disease by applying the ensemble learning techniques on the public COVID-19 dataset. The data set consists of 579 genes belonging to 32 individuals. While 10 of these people are not COVID-19, 22 are people with COVID-19. In this study Lasso, one of the feature selection methods was used. The ensemble learning methods (Bagging, Boosting, and Stacking) were applied to the public dataset. The performance of the models used was evaluated with accuracy, sensitivity, specificity, positive predictive value, and negative predictive value. Of the constructed ensemble models, the Stacking technique produced the best classification performance compared to the Bagging and Boosting methods. Accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and F1 score obtained from the Stacking technique were 99.85%, 99.91%, 99.82%, 99.64%, 99.95%, and 99.89respectively. CD22, CD19, C4BPA, ARHGDIB, AICDA, CCR5, CCL7, CCL26, CCL22 and CCL16 genes calculated from the Stacking method were the most important genes related to COVID-19. The genes determined from the model may be determinants for early diagnosis and treatment of the COVID-19 disease.
Coblation cryptolysis method in treatment of tonsil caseum-induced halitosis
(W B Saunders Co-Elsevier Inc, 2021) Erdur, Omer; Celik, Turgut; Gul, Osman; Koca, Cigdem Firat; Yasar, Seyma
Purpose: Halitosis, is a social problem affecting many patients seeking help from clinicians. Tonsil stones can cause halitosis and especially occur in crypts of palatine tonsils. Coblation cryptolysis is an alternative method for tonsil caseum treatment. The coblation technology includes passing a radiofrequency bipolar electrical current through a medium of normal saline which results in the production of a plasma field of sodium ions. In this study, our aim was to investigate the effectiveness of coblator cryptolysis treatment method in chronic caseous tonsillitis-induced halitosis. Methods: We included in our study 28 patients who underwent coblator cryptolysis surgery for halitosis due to chronic caseous tonsillitis. The efficacy of treatment and the presence of caseoma were evaluated with the Finkelstein test, organoleptic test and VAS before the procedure and at the 6th month control after the treatment was completed. Results: At the 6th month follow-up after the procedure (a single coblation cryptolysis) we found that 23 of the patients (82.1%) had no caseum. There was a statistically significant change in Finkelstein measurements before and after the procedure (p < 0.001). Organoleptic measurements demonstrated that 21 patients had no halitosis postoperatively and the mean organoleptic test score was calculated as 0.39 +/- 0.79 after the procedure. The recovery was statistically significant (p < 0.001). The mean VAS score before coblation cryptolysis was 8.0 +/- 1.33 (range 5-10). On the other hand 6 months after a single coblation cryptolysis session, the mean VAS score was 1.25 +/- 1.78 (range: 0-6). This difference was statistically significant (p < 0.001). Conclusions: Our results suggest that coblation crptolysis is an effective, safe, minimally invasive and practical alternative method in treatment of halitosis due to tonsil caseums. We did not observe any complication after the procedure.
Comparison of preoperative serum neopterin, periostin, indoleamine 2,3-dioxygenase, YKL-40, and tenascin-C levels with current tumor markers for early-stage endometrial cancer
(Wiley, 2021) Unuvar, Songul; Melekoglu, Rauf; Turkmen, Nese B.; Yilmaz, Ercan; Yasar, Seyma; Yuce, Hande
Objective: To compare the predictive value of serum levels of neopterin, periostin, YKL-40, tenascin-C (TNC), and indoleamine 2,3-dioxygenase (IDO) with current tumor markers for the primary diagnosis of early-stage endometrial cancer. Methods: A prospective cross-sectional study was conducted between January 2020 and November 2020. A total of 59 patients (38 women newly diagnosed with early-stage endometrial cancer [study group] and 21 women with benign endometrial pathologies [control group]) were enrolled. Blood samples were collected prior to surgery and underwent immunoassay analysis. Results: Carcinoembryonic antigen (CEA), periostin, and IDO levels were significantly higher in the study group than the control group (P = 0.008, P = 0.034, and P = 0.003, respectively). Receiver operating characteristic curve analysis revealed that IDO, periostin, and CEA were good predictors of early-stage endometrial cancer (AUC = 0.733, 95% CI, 0.602-0.840, P < 0.002; AUC = 0.668, 95% CI, 0.533-0.785, P = 0.018; and AUC = 0.709, 95% CI, 0.576-0.820, P = 0.002, respectively). Correlation analysis revealed no significant correlation of any biomarker with age or body mass index in either the control or study group. Conclusion: Serum CEA, periostin, and IDO levels were significantly higher in women with endometrial cancer than in those without cancer. These results may help identify new markers for diagnosing endometrial cancer.
Delta Neutrophil Index as a Diagnostic Marker of Neonatal Sepsis
(Georg Thieme Verlag Kg, 2021) Melekoglu, Nuriye Asli; Yasar, Seyma; Keskin, Mehmet
Objective Sepsis diagnosis is challenging due to nonspecific symptomatology in newborns. Timely diagnosis is essential for reducing sepsis-related morbidity and mortality. This study was performed to determine the diagnostic value of the delta neutrophil index (DNI) for detection of neonatal sepsis and to compare its efficacy with other conventional markers. Methods This study was conducted at a tertiary hospital in newborns with confirmed sepsis (n = 59), suspected sepsis (n = 46), and in age- and weight-matched controls (n = 49). DNI, white blood cell count, C-reactive protein (CRP) level, and platelet measurements were determined, and blood cultures were performed at the onset of symptoms. Results The mean DNI was significantly higher in confirmed and clinical sepsis groups compared with the control group. (6.9 +/- 9.3, 1.9 +/- 2.1, and 0.4 +/- 0.5, respectively, p < 0.001). ROC curve analysis also showed that the combination of DNI and CRP had the highest sensitivity (86%), specificity (100%), and positive predictive value (100%) for predicting neonatal sepsis. DNI values were significantly higher in nonsurvivors (p < 0.05). Conclusion DNI could be used as a reliable diagnosticmarker for neonatal sepsis, and high DNI could predict sepsis development and unfavorable outcomes. The diagnostic capability of DNI may be increased by assessing CRP measurements simultaneously.
Determination of biomarker candidates for the placenta accreta spectrum by plasma proteomic analysis
(Nature Portfolio, 2024) Melekoglu, Rauf; Yasar, Seyma; Colak, Cemil; Kasap, Murat; Dogan, Umran Karabulut; Yologlu, Saim; Yilmaz, Ercan
Placenta accreta spectrum (PAS) presents a significant obstetric challenge, associated with considerable maternal and fetal-neonatal morbidity and mortality. Nevertheless, it is imperative to acknowledge that a noteworthy subset of PAS cases remains undetected until the time of delivery, thereby contributing to an augmented incidence of morbidity among the affected individuals. The delayed identification of PAS not only hinders timely intervention but also exacerbates the associated health risks for both the maternal and fetal outcomes. This underscores the urgency to innovate strategies for early PAS diagnosis. In this study, we aimed to explore plasma proteins as potential diagnostic biomarkers for PAS. Integrated transcriptome and proteomic analyses were conducted to establish a novel diagnostic approach. A cohort of 15 pregnant women diagnosed with PAS and delivering at Inonu University Faculty of Medicine between 01/04/2021 and 01/01/2023, along with a matched control group of 15 pregnant women without PAS complications, were enrolled. Plasma protein identification utilized enzymatic digestion and liquid chromatography-tandem mass spectrometry techniques. Proteomic analysis identified 228 plasma proteins, of which 85 showed significant differences (P < 0.001) between PAS and control cases. We refined this to a set of 20 proteins for model construction, resulting in a highly accurate classification model (96.9% accuracy). Notable associations were observed for proteins encoded by P01859 (Immunoglobulin heavy constant gamma 2), P02538 (Keratin type II cytoskeletal 6A), P29622 [Kallistatin (also known as Serpin A4)], P17900 (Ganglioside GM2 activator Calmodulin-like protein 5), and P01619 (Immunoglobulin kappa variable 3-20), with fold changes indicating their relevance in distinguishing PAS from control groups. In conclusion, our study has identified novel plasma proteins that could serve as potential biomarkers for early diagnosis of PAS in pregnant women. Further research and validation in larger PAS cohorts are necessary to determine the clinical utility and reliability of these proteomic biomarkers for diagnosing PAS.
A Developed web-based software can easily fulfill the assumptions of correlation, classification and regression tasks in data processing
(Ieee, 2019) Yasar, Seyma; Arslan, A. Kadir; Colak, Cemil; Yologlu, Saim
There are many assumptions that should be provided in regression and correlation analyses. If the assumptions are not met, the results of the analysis lead to errors. Multivariate regression analyses are performed by many software. However, many of this software are commercial and platform dependent. In this study, open source web-based software is developed to test the assumptions of simple/multiple linear regression, simple/multiple logistic regression analysis and correlation analysis, which are classification and regression techniques in machine learning. This software also provides a statistical interpretation of the results to researchers.
Does SARS-CoV-2 affect cochlear functions in children?
(Saudi Med J, 2022) Koca, Cigdem F.; Celik, Turgut; Simsek, Agit; Aydin, Sukru; Kelles, Mehmet; Yasar, Seyma; Erdur, Omer
Objectives: To determine the influence of coronavirus disease-19 (COVID-19) on cochlear tasks of children who had COVID-19 previously, and the relevance among disease seriousness and cochlear involvement by otoacoustic emissions (OAEs). Methods: The study included 24 hospitalized children after COVID-19 diagnosis, 23 pediatrics that received outpatient treatment, and 21 children who were without COVID-19 diagnosis as the control group between June 2021 and July 2021. Transient evoked otoacoustic emission ( TEOAE), distortion product otoacoustic emission, and contrlateral suppression of otoacoustic emission measurements were carried out for each child. Symptoms of patients, the treatments they received, and the duration of hospitalization of the children in the hospitalized group were recorded. Results: The comparison of TEOAE test results under masking showed a considerable difference between 3 groups at 1 kHz (p=0.033) and 4 kHz (p=0.021) frequencies (p<0.05). Distortion product otoacoustic emission test results of hospitalized outpatient and control group showed a statistically significant difference at 2 kHz among themselves (p=0.009). Conclusion: Our results suggest that severe acute respiratory syndrome coronavirus-2 may influence the medial olivocochlear system of children and have irreversible effects on the cochlear functions. Early detection of problems that may affect cochlear functions is a special critical task, especially in children, who are a particularly vulnerable group in terms of hearing and related speech problems.
Dose dependent cytotoxic activity of patulin on neuroblastoma, colon and breast cancer cell line
(2021) Turkmen, Nese Basak; Yuce, Hande; Ozek, Dilan Askin; Aslan, Sumeyye; Yasar, Seyma; Unuvar, Songul
Aim: Patulin, a mycotoxin, is an organic compound classified as a polypeptide. Patulin, which is generally detected in moldy fruits and their derivatives, has been suggested to have anticancer activity. Some studies have shown that it induces apoptosis in the cell. This study aims to investigate the anticancer activity of patulin in SH-SY5Y (human neuroblastoma cell line), HCT116 (human colon cancer cell line), and MCF-7 (human breast cancer cell line) cell lines. Materials and Methods: SH-SY5Y, HCT116, MCF-7, and L929 (healthy fibroblast) cell lines were used for cytotoxicity experiments. Cells were added in 96-well plates at 5x103 cells per well. Serial dilutions of patulin at a dose of 1, 2.5, 5, 10, 25, 50, and 100 µM were added to the waiting cells in 24 hours incubation. All cell lines were exposed to patulin for 24 and 48 hours. The cytotoxic activity of patulin in cancer and healthy cell lines was determined in vitro by the MTS (3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulphophenyl)-2H-tetrazolium) cell viability test. The results of the toxicity tests were measured spectrophotometrically (450 nm) in ELISA at intervals of 24 hours for 2 days. Results: Patulin caused cytotoxic activity in all cell lines at a concentration of 100 µM. Patulin showed cytotoxic activity at low doses only in the SH-SY5Y cell line. At doses of 25 and 50 µM, HCT116 caused more than 50% death in the cell line, while higher concentrations induced cell death in the MCF-7 cell line. Conclusion: Patulin showed anticancer activity at high concentrations in colon and breast cancer cell lines, and both low and high concentrations in the SH-SY5Y cell line. Patulin may be a new candidate molecule in the treatment of neuroblastoma, colon, and breast cancers, depending on the dose.
The effect of the severity of COVID-19 on the sequelae of the audiovestibular system
(Sage Publications Inc, 2023) Aydin, Sukru; Koca, Cigdem Firat; Celik, Turgut; Kelles, Mehmet; Yasar, Seyma; Oguzturk, Saadet
Objectives: The neurotropic and neuroinvasive properties of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have been described. It remains unknown how SARS-CoV-2 affects the audiovestibular system when it causes mild or severe disease. In this study, the sequelae effect of SARS-CoV-2 on the audiovestibular systems of different patient groups was investigated using objective and subjective test batteries. Methods: In this present study, we evaluated vestibulocochlear functions of patients who previously had Coronavirus Disease-2019 (COVID-19) with pure tone audiometry, ocular vestibular-evoked myogenic potential (o-VEMP), and cervical vestibular-evoked myogenic potential (c-VEMP) tests to identify possible sequelae by comparing them with the control group. Results: We found that the amplitude of p13-n23 was lower in both groups of patients than in the control group (p < 0.001). In the results of the left ear c-VEMP, the amplitude of p13-n23 was statistically different between the outpatient, inpatient, and control groups. The amplitude of p13-n23 was lower in both groups of patients than in the control group (p < 0.001). In the evaluation of the o-VEMP in the left ear, we observed a statistically significant difference in the latency of n10 (p = 0.006) and the amplitude of n10-p15 (p < 0.001) between the groups. The n10 latency was prolonged in both groups of patients compared to the control group and there was no statistically significant difference between groups of patients. Furthermore, the amplitude of n10-p15 was lower in both groups of patients compared to the control group and there were no statistically demonstrable differences between the groups of patients. Conclusions: In conclusion, our results suggest that SARS-CoV-2 may affect the vestibulocochlear system. But we could not find a direct relationship according to the severity of the disease.
Effects of the COVID-19 Pandemic on Pediatric Nasal Fractures
(Sage Publications Inc, 2022) Koca, Cigdem Firat; Celik, Turgut; Aydin, Sukru; Kelles, Mehmet; Yasar, Seyma
Objectives Nasal bone fracture is a frequent entity consulted to the otolaryngologists, approximately accounting for 39% of all facial bone fractures. The most frequent mechanisms of injury consist of assault, sport-related injuries, falls, and motor vehicle accidents. In this study, we examined the effects of the COVID-19 pandemic on pediatric nasal fractures. Methods Children with nasal fracture who applied to Malatya Training and Research Hospital during the year before the first case and the following year were included in this study. Data of 172 patients for the pre-pandemic period and 79 patients for pandemic were available and included in the study. Demographic information, clinical features, nasal fracture etiology, nasal fracture type, type and time of intervention, and other accompanying pathologies were recorded. Results While falls was the leading cause of fracture etiology before the pandemic (64 patients [37.21%]), assault seems to be the leading cause during the pandemic period (27 children [34.18%]). In the pre-pandemic period, the intervention for patients with nasal fractures was performed on an average of 5 days, while this period was calculated as an average of 6 days during the pandemic period. When the 2 groups are compared in terms of nasal fracture intervention time, it was seen that the intervention time was statistically significantly later in the pandemic period (P < .001). According to the results of the analysis, the most cases in the pandemic period were seen in the fourth month, which indicated a-month period between 11 June and 11 July. Conclusions In conclusion, our number of nasal fracture cases was decreased during the pandemic period compared to the 1-year period before the pandemic. We observed the most common type IIA nasal fracture. We gave outpatient treatment to most of the patients. Our most common cause of fracture was assault. We intervened in our cases in an average of 6 days and preferred closed reduction most frequently. We could not find any study on the same subject in the literature, and we aimed to contribute to the literature with this study.
Ensemble learning-based prediction of COVID-19 positive patient groups determined by IL-6 levels and control individuals based on the proteomics data
(2021) Yasar, Seyma; Kucukakcali, Zeynep; Doganer, Adem
Coronavirus disease (COVID-19) is a newly found coronavirus that causes an infectious disease. COVID-19, which has a detrimental impact on many people, has varied effects on different people. Therefore, proteomic analysis is an important approach used to develop early diagnosis and treatment strategies. This research to classify COVID-19 positive patient groups represented by interleukin 6 (IL-6) levels (low, medium, high) and control groups based on proteomic analysis using ensemble learning methods (Adaboost, Bagging, Stacking, and Voting). The public dataset from a website consists of 49 subjects (31 COVID-19 positives and 18 controls) and 493 proteins achieved from blood samples. The dataset was handled to estimate the relation between disease severity and proteins using ensemble learning approaches (Adaboost, Bagging, Stacking, and Voting) using ten-fold cross-validation. Predictions were evaluated with accuracy, sensitivity,etc. performance metrics. The accuracy of Adaboost (96.00%) was higher as compared to Voting (93.88%) and Bagging (91.84%). However, the Stacking ensemble learning method produced the highest accuracy (97.92%). IL6, SERPINA3, SERPING1, SERPINA1, and GSN were the five most important proteins associated with disease severity. In comparison to the other methods, the suggested ensemble learning model (Stacking) produced the best estimation of disease severity based on proteins. The results indicate that changes in blood protein levels correlated with the severity of COVID-19 may be benefited to follow early diagnosis/treatment of the COVID-19 disease.
Evaluation of clinical characteristics and outcomes of postoperative infections in living liver donors
(Wiley, 2021) Kose, Adem; Altunisik Toplu, Sibel; Akbulut, Sami; Yasar, Seyma; Sarici, Kemal Baris; Duman, Yucel; Kutlu, Ramazan
Aim To analyze developing infections after living donor hepatectomy (LDH) in living liver donors (LLDs). Methods Demographic and clinical characteristics of 1106 LLDs were retrospectively analyzed in terms of whether postoperative infection development. Therefore, LLDs were divided into two groups: with (n = 190) and without (n = 916) antimicrobial agent use. Results The median age was 29.5 (min-max: 18-55). A total of 257 (23.2%) infection attacks (min-max: 1-8) was developed in 190 (17.2%) LLDs. The patients with the infection that were longer intensive care unit (ICU) and hospital stays, higher hospital admissions, emergency transplantation, invasive procedures for ERCP, PTC biloma, and abscess drainage, and the presence of relaparatomies and transcystic catheters. Infection attacks are derived from a 58.3% hepatobiliary system, 13.2% urinary system, 6.6% surgical site, and 5.8% respiratory system. The most common onset symptoms were fever, abdominal pain, nausea, and vomiting. A total of 125 positive results was detected from 77 patients with culture positivity. The most detected microorganisms from the cultures taken are Extended-Spectrum beta-lactamases (ESBL) producing Klebsiella pneumonia (16.8%) and Escherichia coli (16%), Methicillin-Resistant Staphylococcus aureus [(MRSA) (9.6%)], Methicillin-susceptible S aureus [(MSSA) (9.6%)], and Pseudomonas aeruginosa (8.8%), respectively. The average number of ICU hospitalization days was 3 +/- 2 (min 1-max 30, IQR:1) and hospitalization days was 14 +/- 12 (min 3-max 138, IQR: 8). All infection attacks were successfully treated. No patients died because of infection or another surgical complication. Conclusion Infections commonly observed infected biloma, cholangitis, and abscess arising from the biliary system and other nosocomial infections are the feared complications in LLDs. These infections should be managed multidisciplinary without delay and carefully.
Evaluation of cochlear functions in infants exposed to SARS-CoV-2 intrauterine
(W B Saunders Co-Elsevier Inc, 2021) Celik, Turgut; Simsek, Agit; Koca, Cigdem Firat; Aydin, Sukru; Yasar, Seyma
Purpose: The novel coronavirus (SARS-CoV-2) caused an acute respiratory illness named COVID-19 and the disease spread all over the World. Fever, cough, fatigue, gastrointestinal infection symptoms form the main clinical symptoms. Pregnants and newborns form a vulnerable population and urgent measures must be addressed. Studies about the effect of COVID-19 on pregnant women, developing fetuses, and infants are limited. Various viral diseases can cause congenital or acquired, unilateral or bilateral hearing loss. Methods: 37 infants whose mother was pregnant between March 2020 and December 2020 and were born after the diagnosis of COVID- 19 during pregnancy and 36 healthy infants were included in the study. Transient evoked otoacoustic emission (TEOAE), distortion product otoacoustic emission (DPOAE) and contralateral suppression of OAE (CLS OAE) tests were performed on all infants. Results: According to the TEOAE results of patients and controls in the silent a statistically significant difference was observed between the two groups at 3 kHz and 4 kHz (p < 0.05). Contralateral suppression of OAE test results of patients and controls a statistically significant difference was found in all frequencies (p< 0.05). Suppression was much more effective at all frequencies in the normal group than patient group. This difference was found to be more significant at higher frequencies (2,3 and 4 kHz) (p < 0.001). Conclusions: Our results suggest an insufficiency in medial olivocochlear efferent system in infants exposed to SARS-CoV-2 intrauterine. Cochlear functions should be examined in infants whose mothers had COVID-19.
Evaluation of dyslipidemia in preeclamptic pregnant women and determination of the predictive value of the hemato-lipid profile: A prospective, cross- sectional, case-control study
(Galenos Yayincilik, 2022) Melekoglu, Rauf; Yasar, Seyma; Celik, Nesibe Zeyveli; Ozdemir, Halis
Objective: In this study, we examined the serum hematologic and lipid parameters of pregnant women with preeclampsia and an age-and gestational-age matched normotensive control group. We also compared the ratios of hemato-lipid parameters defined as systemic inflammatory markers and determined the predictive value of these values in preeclampsia. Materials and Methods: All patients diagnosed with late-onset preeclampsia or severe preeclampsia between 34 and 40 weeks of gestation at Inonu University Faculty of Medicine between March 2019 and October 2020 were included. Results: A total of 253 pregnant women were included in the study period. When the study groups were compared in terms of hematological and blood lipid profile; while serum lymphocyte, triglyceride, and total cholesterol levels were significantly higher in the preeclampsia group than in the control group (p<0.001, p<0.001, p=0.013, respectively); high-density lipoprotein (HDL)-cholesterol levels were found to be significantly lower (p=0.017). The cut-off value for the monocyte/HDL ratio in predicting severe preeclampsia was 16.65 with 59.0% sensitivity and 85.4% specificity [the area under the receiver operating characteristic 0.756, 95% confidence interval (CI) 0.681-0.821, p<0.001]. Multivariate analysis showed that the monocyte/HDL ratio was independently associated with both preeclampsia and severe preeclampsia [odds ratio (OR): 1.094; 95% CI 1.009-1.185 and OR: 1.731; 95% CI 1.218-2.459, respectively]. Conclusion: This study demonstrated that serum triglyceride and total cholesterol levels were significantly higher and serum HDL-cholesterol levels were significantly lower in pregnant women with late-onset preeclampsia compared to normotensive pregnant women. Additionally, this study revealed that the measurement of monocyte/HDL ratio in the pregnant population could be a useful clinical tool for predicting preeclampsia.
Evaluation of serum neopterin, periostin, Tenascin-C, tissue inhibitor of metalloproteinase-1 and matrix metalloproteinase-2 levels in obese pregnant women
(Galenos Publ House, 2022) Melekoglu, Rauf; Unuvar, Songul; Turkmen, Nese Basak; Cetin, Asli; Celik, Nesibe Zeyveli; Yuce, Hande; Yasar, Seyma
Objective: To investigate the role of extracellular matrix proteins in the molecular mechanism of inflammatory response in obese pregnant women by comparing serum levels of neopterin, periostin, Tenascin-C, tissue inhibitor of metalloproteinase-1, and matrix metalloproteinase-2 between obese and normal weight pregnant women in the third trimester. Materials and Methods: A prospective cross-sectional study was conducted between April 2021 and December 2021. A total of 84 pregnant women were included and three groups were formed with 28 participants in each group. Results: Serum levels of neopterin, periostin, Tenascin-C and tissue inhibitor of metalloproteinase-1 were significantly higher in class II-III obese pregnant women than in class I obese and normal-weight women (p=0.002, p<0.001, p<0.001, and p<0.001, respectively). There was no significant difference in serum matrix metalloproteinase-2 levels between the groups (p=0.769). Receiver operating characteristic curve analysis showed that Tenascin-C and periostin were effective in predicting pre-eclampsia [area under the curve (AUC)=0.82, 95% confidence interval (CI), 0.72-0.90, p<0.001 and AUC=0.71, 95% CI, 0.60-0.80, p=0.007, respectively]. Conclusion: This study demonstrated that class II-III obese pregnant women had significantly higher serum levels of neopterin, periostin, Tenascin-C, and tissue inhibitor of metalloproteinase-1 in the third trimester. These higher serum levels may be associated with the adverse perinatal effects of obesity during pregnancy.

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