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Introduction: Superficial fungal infections, which are considered as the most common risk factor for mucocutaneous infections, are still an important consideration of human health. Tinea pedis and onychomycosis are two common types of superficial fungal infections. Increased recurrence of these infections in certain subjects led us speculate the common factors that might contribute to our observations. In this study, we aimed to investigate the relationship between blood types and two types of fungal infections tinea pedis and onychomycosis. Material and Method: In our study, we questioned blood types of 171 tinea pedis and onychomycosis patients, who applied to our clinic between October 2015 and December 2016. Diagnoses were confirmed using mycotic examination and fungal cultures. We measured patients’ hemogram, alanine aminotransferase, aspartate aminotransferase, urea and creatinine levels to determine their treatments. Patients were monitored during their treatments. Results: We analyzed our results to determine the effectiveness of treatments, recurrence, and the relationship between our result and patients’ blood types. We could not find any significant relation between blood types and gender, educational status, residence addresses of patients, infected region, duration of fungal infection (p>0.05). Then we could not find also a significant relation between blood types of the patients and infection status of the family members that patients lived together with (p>0.05). Conclusion: Our study shows that AB0 blood types are not significantly correlated with neither tinea pedis nor onychomycosis, which are dermatophytes, causing superficial fungal infections., Giriş: Mukokutanöz enfeksiyonlar için en yaygın risk faktörü olarak kabul edilen yüzeysel mantar enfeksiyonları, insan sağlığı için hala önemli bir husustur. Tinea pedis ve onikomikoz iki yaygın yüzeysel mantar enfeksiyonu türüdür. Bazı konularda bu enfeksiyonların artan tekrarlaması, gözlemlerimize katkıda bulunabilecek ortak faktörleri speküle etmemize yol açtı. Bu çalışmada iki tip mantar enfeksiyonu olan tinea pedis ve onikomikoz arasındaki ilişkiyi araştırmayı amaçladık.Gereç ve Yöntem: Çalışmamızda Ekim 2015-Aralık 2016 tarihleri arasında kliniğimize başvuran 171 tinea pedis ve onikomikoz hastalarının kan tiplerini sorguladık. Mikolojik muayene ve mantar kültürleri kullanılarak tanı konuldu. Tedavilerini belirlemek için hastaların hemogramı, alanin aminotransferaz, aspartat aminotransferaz, üre ve kreatinin düzeylerini ölçtük. Hastalar tedavileri sırasında izlendi.Bulgular: Tedavilerin etkinliğini, nüksünü ve sonucumuz ile hastaların kan grupları arasındaki ilişkiyi belirlemek için sonuçlarımızı analiz ettik. Kan grupları ile cinsiyet, kan gruplarıyla eğitim durumu, kan gruplarıyla hastaların yaşadığı bölge, kan gruplarıyla enfekte bölge,kan gruplarıyla mantar enfeksiyonunun süresi arasında anlamlı bir ilişki bulamadık (p>0,05). Daha sonrasında kan gruplarıyla, beraber yaşadıkları aile üyelerinin enfeksiyon durumu arasında da anlamlı bir ilişki bulamadık.Sonuç: Çalışmamız, AB0 kan tiplerinin yüzeysel mantar enfeksiyonlarına neden olan dermatofitler olan ne tinea pedis ne de onikomikoz ile anlamlı bir ilişki içinde olmadığını göstermektedir.

Objective: The aim of this study was to investigate the urine prolactin and serum/urine prolactin ratio for accuracy diagnosis of macroprolactinemia. Methods: In the retrospective cross-sectional analysis, prolactin levels (high or normal) in the reproductive period of men and women were included in the study. Polyethylene glycol (PEG) precipitation method was used for the detection of macroprolactinemia. Then, patients were divided into three groups as macroprolactinemia, prolactinoma and healthy control group. In patients, prolactin values in spot urine with simultaneous serum prolactin values were calculated. The non-parametric Kruskal-Wallis test was used to compare the groups. The receiver-operating characteristic (ROC) curve was determined to evaluate the predictive power of serum/urine prolactin ratio Results: A total of 41 patients were included in the study. Female/male:36 (87.8%)/ 5 (12.2%). Urinary prolactin median(minimum-maximum) values were macroprolactinemia, prolactinoma and control group, respectively; 0.06(0.05-0.10), 0.11(0.02-0.95), 0.08(0.05-0.25) ng/ml. Serum/urine ratio median (minium-maximum) values were macroprolactinemia, prolactinoma, and control group, respectively; 633(51-1032), 990(104-9635), 395.5(138-953). When the groups were compared, the patients with prolactinoma had higher urinary prolactin levels(p 549,5 AUC=0.83) p 549,5 AUC = 0.83) p

Amaç: Bu çalışmada hiperlipidemi hastalarının Toplam Kolesterol, LDL, Trigliserit, HDL seviyelerinin farklı regresyon modelleriyle tahmini ve yaşa göre değişiminin belirlenmesi amaçlanmıştır. Bu amaçla, doğrusal ve doğrusal olmayan regresyon modelleri ile analiz yapılmıştır. Yöntemler: Çalışmamız, İnönü Üniversitesi Turgut Özal Tıp Merkezi Kardiyoloji bölümüne müracaat eden 1278 hiperlipidemili hasta üzerinde gerçekleştirilmiştir. Retrospektif çalışmamızda veri toplama aracı olarak hasta dosyaları ve vaka kayıtları kullanılmıştır. Kayıtlardan toplanan veriler paket programlarla analiz edilerek modellemeler yapılmıştır. Bulgular: Araştırmamızda 1278 hiperlipidemili hastanın 671’i (%52,4) erkek ve 607’si (%47,6) kadındır. Büyüme eğrilerinin uyumunun incelenmesinde açıklayıcılık katsayısı (R2), Hata Kareler Ortalaması (HKO), Akaike Bilgi Kriteri ( AIC) ve Schwarz Bilgi Kriteri (SIC) hesapları dikkate alındığında, kadın hastalarda; Kolesterol değerleri için en iyi büyüme modeli Kuadratik model, LDL için Gompertz model, Trigliserit için Lojistik model, HDL için Ustel modeldir. Erkek hastalarda ise; Kolesterol değerleri için en iyi büyüme modeli Gompertz model, LDL için Doğrusal model, Trigliserit için Üstel model, HDL için Doğrusal modeldir. Sonuç: Doğrusal olmayan hiperlipidemik değerlerin tahmininde değişik modellerin farklı performans gösterdiği belirlenmiştir. Hiperlipidemi değerleri izleminde bu modellerden elde edilen büyüme eğrilerinin kullanılmasının, Kolesterol, LDL, HDL ve Trigliserit değerlerinin tahmin edilebilmesinde ayrıca normal değerlerden sapmaların değerlendirilmesinde yararlı olacağı düşünülmektedir Objective: In the present study, it is aimed to specify the changes in the Total cholesterol, LDL, Triglyceride and HDL levels of hyperlipidemia patients according to age and estimation through several regression models. For that purpose, the analysis was made through linear and non-linear regression models. Methods: Our study was conducted with 1278 hyperlipidemia patients who applied to İnönü Unversity Turgut Özal Medicine Center Cardiology Department. For our retrospective study, patient folders and case records were used as data gathering tools. The data gathered from records were analyzed through packet programmes for modelling. Results: In our research, of the 1278 patients, 671 were males (52.4%) and 607 were females (47.6%). While analyzing the conformity of the growth curves, for female patients, the best growth model is Quadratic Model for cholesterol values; Gompertz Model for LDL; Logistic Model for Triglyceride; Exponential Model for HDL considering explanatory factor (R2), Error Sum of Squares (ESS), Akaike Information Criterion (AIC) and Schwarz Information Criterion (SIC). For male patients, the best growth model for cholesterol values is Gompertz Model; Linear Model for LDL; Exponential Model for Triglyceride and Linear Model for HDL. Conclusion: It was found out that several models show different performance in the estimation of non-linear hyperlipidemic values. In the follow-ups for hyperlipidemia values, it is thought that using growth curves obtained from those models could be useful for not only estimating cholesterol, LDL, HDL and Triglyceride levels but also analyzing deviations from normal values.

Aim: In this study, the attitudes of teaching staff of Fac-ulty of Medicine, Dicle University, in the 2005-2006 aca-demic year about technology was intended to be exam-ined. This research is a study on how teaching staff are affected with their different characteristics.Materials and Methods: Our study 224 persons were taken. Of the persons, 68 were professor, 40 were As-soc Professor, 44 were Assistant Professors, 58 were research assistants and 14 were expert. In our study, how the attitude variables were connected to the de-pendent (target) variables was determined. The emer-gence of attitudes of different items has been intended to be studied on. Likert type form was applied for attitude items.Results: The attitudes on the wish of the teaching staff to join technology fairs were found to be different. Re-search assistants were found to have positive attitudes compared to the higher rank teaching staff. It was seen that the teaching staff who were indecisive to join the technological fairs wanted new instructive technologies to be used in their areas. Their departments determined their attitudes. It can be said that the teaching staff are indecisive about the opinion that ‘technology will take place of human beings’. It was found that the ones who did not agree with this item were mostly from Surgery Department. Conclusion: In general, the academic staff have posi-tive attitudes towards technology.

Variable structures are the essential factors to be considered in the first stage of the statistical analysis. If they do not take the stepwise analysis into consideration, researchers make publications full of many errors. Variable structures determine the statistical methods to be chosen. Researchers with limited knowledge about variable structures are apt to have troubles in making decisions about variables.In this study, we aimed to investigate the strong relation between variable structures and statistical methods, those assumed to be the strongest assumptions in statistics. Although researchers deal with either univariate or multivariate structures in their studies, today, it is the reality that the multivariate effects are observed more frequently. All of the univariate or multivariate biostatistical methods propose assumptions related to variables. The basic assumption of the parametric tests is the normal distribution of the variables. The most important characteristic of the normal distribution is being a distribution of the continuous variables. Univariate or multivariate parametric methods need continuous variables. Since they are not normally distributed, non-continuous variables should be treated with “distribution-free methods.”The most important characteristic of the non-parametric methods is that they have no limitation for the researchers. This characteristic provides easiness for the researchers. As these advantages are used correctly, it is obvious that the results of the analysis will be more accurate and stronger.Before the analysis, explicitly definition of the variable structures provides us getting the correct results in the method selection.

The orthodontic "finishing" phase is recognized for the many details necessary to accomplish an excellent result. A high percentage of finishing-phase difficulties arise because of tooth size imbalances that could have been discovered and considered during the initial diagnosis and treatment planning. The aim of our study was to determine whether there is a prevalent tendency for intermaxillary tooth size discrepancies among different malocclusion groups. This study involved 60 subjects who served as the normal occlusion group and 300 patients divided into five malocclusion groups (ie, Class I, Class II, Class II division 1, Class II division 2, and Class III). Tooth size measurements were performed on the models of the normal occlusion group and the pretreatment models of the patients. The tooth size ratios and the one-way analysis of variance test showed no sexual dimorphism for these ratios in each of five groups, so the sexes were combined for each group. Then, these ratios were compared among different malocclusion groups. The results showed no significant difference between subcategories of malocclusion, so these groups were combined as Class I, Class II, and Class III. No significant difference was found for all the ratios between the groups.