Predicting Implantation Outcome from Imbalanced IVF Dataset

Abstract-Predicting implantation outcomes of invitro fertilization (IVF) embryos is critical for the success of the treatment. We have applied Naive Bayes classifier to an original IVF dataset in order to discriminate embryos according to implantation potentials. The dataset we analyzed represents an imbalanced distribution of positive and negative instances. In order to deal with the problem of imbalance, we examined the effects of over sampling the minority class, under sampling the majority class and adjustment of the decision threshold on the classification performance. We have used features of Receiver Operating Characteristics (ROC) curves in the evaluation of experiments. Our results revealed that it is possible to obtain optimum True Positive and False Positive Rates simply by adjusting the decision threshold. Under-sampling experiments show that we can achieve same prediction performance with less data as well as 736 embryo samples

Modeling and optimizing microwave-assisted extraction of antioxidants from Thymbra Spicata L. and characterization of their phenolic constituents

Response surface methodology was used for modeling and optimizing microwave-assisted extraction of antioxidants from Thymbra spicata L. as a factor of temperature, extraction time, solvent concentration, and solvent-to-solid ratio. The prepared extracts showed maximum antioxidant properties, including total phenolic content (TPC), total antioxidant capacity (TAC), and radical scavenging activity (RSA) at the optimum operating conditions. All models calculated for the three responses that are TPC, TAC, and RSA were noteworthy (p < 0.0001) and showed a significant relationship between the response and independent parameters. There was a close relationship between the experimental and the predicted values obtained using the proposed method. The phenolic antioxidant profile of Thymbra spicata L. extract was characterized with the UPLC-PDA-ESI-MS/MS system and rosmarinic acid was found as a major component (1089.2 +/- 10.9 mg/100 g-DS). In the future, this optimized and modeled MAE method can be applied in food and pharmaceutical industries to effectively extract antioxidants from edible Thymbra spicata L. plant

Is there a relationship between microvascular complications and the severity of type 2 diabetes mellitus?

Objective: The aim of this study was to determine the relationship between microvascular Type 2 diabetes mellitus (T2DM) complications and the severity and duration of diabetes in the light of sociodemographic and lifestyle variables. Materials and Methods: This is a prospective cohort study based on 899 (527 females, 372 males) patients with T2DM aged 25-70 years. Patient information including socio-demographic variables; body mass index (BMI); lifestyle habits and duration of diabetes; treatment of diabetes; values for hemoglobin A1c (HbA1c); development of diabetes complications; and the presence of neuropathy, nephropathy, and retinopathy were recorded. A univariate and multivariate statistical analysis were performed. Results: Significant differences were found between diabetics with HbA1c 7 in terms of the education level, occupation, household income, duration of diabetes, the number of children, smoking, physical exercise, eating fast food, control regularity, and diabetes education. A total of 17.1% of patients had diabetic retinopathy, 17.0% had neuropathy, and 13.7% had nephropathy. Among diabetics, 2.3% had three microvascular complications, whereas 66.6% had none of them. The prevalence of diabetes complications was lower in patients who had good glycemic control than those who had poor glycemic control. Furthermore, the highest reduction in the level of HbA1c was for sulfonylurea usage. Conclusion: A high prevalence of diabetes complications is a burden for both the patients and the health care system. Screening, early diagnosis, management of the glucose level, and the follow-up may result in delayed diabetes complications

Novel optical sensor-based method for determining total tocopherol content in serum

Lipid-soluble endogenous antioxidants, such as tocopherols, protect biological structures from oxidative damage through their chain-breaking ability and thus the development of a simple method for tocopherol determination is important. In this study, a novel optical sensor-based method was proposed for determining total tocopherol content (TTC) of serum, with selectivity for alpha-tocopherol over beta-carotene. The proposed method is based on the use of a copper(II)-neocuproine complex (Cu(II)-Nc) reagent immobilized onto a Nafion membrane, and the absorbance changes associated with the formation of Cu(I)-Nc chelate on the membrane strip as a result of reaction with serum tocopherols were measured at 450 nm. The calibration graph of a-tocopherol was linear with a slope of 1.96 x 10(4) L mol(-1) cm(-1). The limit of detection and limit of quantification for tocopherol in the proposed method were found as 0.50 and 1.67 mu M, respectively. The TTC value of synthetic serum samples was determined with the use of the proposed method, and the obtained results were comparable to those of the CUPRAC spectrophotometric method. The proposed method enables simple, rapid, and in situ determination of total tocopherol content of serum by taking advantage of optical sensors