Fertility-enhancing effects of inositol & vitamin C on cisplatin induced ovarian and uterine toxicity in rats via suppressing oxidative stress and apoptosis.

Cisplatin can lead to infertility due to its negative impact on the uterus and ovaries. This study aimed to explore the effects of Inositol and vitamin C on cisplatin-induced infertility. Forty-eight adult female Wistar rats were divided into eight groups (N = 6) and orally treated for 21 days. The treatments were as follows: negative control (saline), positive control (saline and cisplatin injected into the abdomen on day 15), T1-T3: rats given vitamin C (150 mg/kg), Inositol (420 mg/kg), and vitamin C + Inositol, respectively, along with cisplatin injected into the abdomen on day 15, T4-T6: rats given only vitamin C, Inositol, and vitamin C + Inositol, respectively. Vitamin C and Inositol enhanced cisplatin-induced histopathological improvements in the uterus and ovaries, raising progesterone and estradiol serum levels. Furthermore, the supplements enhanced ESR1 gene expression in the uterus and ovary, reducing uterine and ovarian apoptosis caused by cisplatin through modulation of caspase 3, 8, and Bcl-2 gene levels. These substances decreased ovarian and uterine malondialdehyde levels, boosted total antioxidant capacity and superoxide dismutase, and alleviated oxidative stress. The findings reveal that vitamin C and Inositol shield against cisplatin-related infertility by reducing oxidative stress and apoptosis in the uterus and ovaries.

EEG Electrode Selection for a Two-Class Motor Imagery Task in a BCI Using fNIRS Prior Data.

This study investigated the possibility of using functional near infrared spectroscopy (fNIRS) during right- and left-hand motor imagery tasks to select an optimum set of electroencephalography (EEG) electrodes for a brain computer interface. fNIRS has better spatial resolution allowing areas of brain activity to more readily be identified. The ReliefF algorithm was used to identify the most reliable fNIRS channels. Then, EEG electrodes adjacent to those channels were selected for classification. This study used three different classifiers of linear and quadratic discriminant analyses, and support vector machine to examine the proposed method.Clinical Relevance- Reducing the number of sensors in a BCI makes the system more usable for patients with severe disabilities.

Discrimination of Two-Class Motor Imagery in a fNIRS Based Brain Computer Interface.

The purpose of this study was to discriminate between left- and right-hand motor imagery tasks. We recorded the brain signals from two participants using a fNIRS system and compared different feature extraction (mean, peak, minimum, skewness and kurtosis) and classification techniques (linear (LDA) and quadratic discriminant analysis (QDA), support vector machine (SVM), logistic regression, K-nearest-neighbor (KNN), and neural networks with Levenberg-Marquardt (LMA), Bayesian Regularization (BRANN) and Scaled Conjugate Gradient (SCGA) training algorithms). The results showed poor classification accuracies (<; 58%) when skewness and kurtosis were used. When mean, peak, and minimum were used as features, QDA, SVM and KNN produced higher classification accuracies relative to LDA and logistic regression. Overall, BRANN led to the highest accuracies (>98%) when mean, peak and minimum were used as features.

Determination of fast neutron RBE using a fully mechanistic computational model.

This work presents a model previously developed for estimating relative biological effectiveness (RBE) associated with high-LET particles. It is based on the combination of Monte Carlo simulations of particle interactions when traversing an atomic resolution DNA geometrical model. In addition, the model emulates the induction of lethal damage from the interaction of two sublethal lesions, taken as double-strand breaks. The Geant4-DNA package was used for simulations with liquid water as the transport medium. The RBE of neutron beams with energies ranging from 0.1 MeV up to 14 MeV was studied. The model succeeded in reproducing the general behavior of RBE as a function of neutron energy, including the RBE peak reported by experiments at approximately 0.4 MeV. Furthermore, the results of the model agree rather well with some experimental works. However, our results underestimate RBE for neutron energies above approximately 5 MeV due to the current limitations of Geant4-DNA for the tracking of heavy ions below 0.5 MeV/u.

Computational approach to determine the relative biological effectiveness of fast neutrons using the Geant4-DNA toolkit and a DNA atomic model from the Protein Data Bank.

This study proposes an innovative approach to estimate relative biological effectiveness (RBE) of fast neutrons using the Geant4 toolkit. The Geant4-DNA version cannot track heavy ions below 0.5 MeV/nucleon. In order to explore the impact of this issue, secondary particles are simulated instead of the primary low-energy neutrons. The Evaluated Nuclear Data File library is used to determine the cross sections for the elastic and inelastic interactions of neutrons with water and to find the contribution of each secondary particle spectrum. Two strategies are investigated in order to find the best possible approach and results. The first one takes into account only light particles, protons produced from elastic scattering, and α particles from inelastic scattering. Geantino particles are shot instead of heavy ions; hence all heavy ions are considered in the simulations, though their physical effects on DNA not. The second strategy takes into account all the heavy and light ions, although heavy ions cannot be tracked down to very low energies (E<0.5 MeV/nucleon). Our model is based on the combination of an atomic resolution DNA geometrical model and a Monte Carlo simulation toolkit for tracking particles. The atomic coordinates of the DNA double helix are extracted from the Protein Data Bank. Since secondary particle spectra are used instead of simulating the interaction of neutrons explicitly, this method reduces the computation times dramatically. Double-strand break induction is used as the end point for the estimation of the RBE of fast neutrons. ^{60}Co Î³ rays are used as the reference radiation quality. Both strategies succeed in reproducing the behavior of the RBE_{max} as a function of the incident neutron energy ranging from 0.1 to 14 MeV, including the position of its peak. A comparison of the behavior of the two strategies shows that for neutrons with energies less than 0.7 MeV, the effect of heavy ions would not be very significant, but above 0.7 MeV, heavy ions have an important role in neutron RBE.

Assessment of EDDS and vermicompost for the phytoextraction of Cd and Pb by sunflower (Helianthus annuus L.).

The effects of Ethylenediamine disuccinic acid (EDDS) (0 and 5 mmol·kg-1) as a synthetic chemical amendment, vermicompost (0 and 5%w/w) as an organic amendment and their combined application were evaluated for the phytoextraction by sunflower (Helianthus annuus L.) of cadmium (Cd) and lead (Pb) at three artificial contamination levels in soils (0, 50, and 100 mg·kg-1 for Cd and 0, 100, and 200 mg·kg-1 for Pb). The results showed that the application of EDDS was the most effective method to increase Pb and Cd concentrations in both parts of the plant. The results also showed that the application of EDDS increased 9.27% shoot Pb content at 200 mg·kg-1 but decreased 15.95% shoot Cd content at 100 mg·kg-1 contamination level with respect to the respective controls. The bioavailable concentrations of Cd at 100 mg·kg-1 and Pb at 200 mg·kg-1 contamination level in the soil at the end of experiment increased 25% and 26%, respectively after the application of EDDS but vermicompost decreased 43.28% the bioavailable Pb concentration relative to their controls. Vermicompost increased the remediation factor index of Cd, thus making it the best treatment for the phytoextraction of Cd. The combined application of EDDS and vermicompost was the best amendment for Pb phytoextraction.

Simulated response of a multi-element thick gas electron multiplier-based microdosimeter to high energy neutrons.

The response of a microdosimeter for neutrons above 14 MeV is investigated. The mean quality factors and dose-equivalents are determined using lineal energy distributions calculated by Monte Carlo simulations (Geant4 toolkit). From 14 MeV to 5 GeV, the mean quality factors were found to vary between 6.00 and 9.30 and the dose-equivalents were in agreement with the true ambient dose-equivalent at the depth of 10 mm inside the ICRU sphere, H*(10). An energy-independent dose-equivalent response around a median value of 0.86 within 22% uncertainty was obtained. Therefore, the microdosimeter is appropriate for dose-equivalent measurement of high-energy neutrons.

Potential drug-drug interactions at a referral hematology-oncology ward in Iran: a cross-sectional study.

PURPOSE: To assess the pattern and probable risk factors for moderate and major drug-drug interactions in a referral hematology-oncology ward in Iran. METHODS: All patients admitted to hematology-oncology ward of Dr. Shariati Hospital during a 6-month period and received at least two anti-cancer or non-anti-cancer medications simultaneously were included. All being scheduled anti-cancer and non-anti-cancer medications both prescribed and administered during ward stay were considered for drug-drug interaction screening by Lexi-Interact On-Desktop software. RESULTS: One hundred and eighty-five drug-drug interactions with moderate or major severity were detected from 83 patients. Most of drug-drug interactions (69.73 %) were classified as pharmacokinetics. Fluconazole (25.95 %) was the most commonly offending medication in drug-drug interactions. Interaction of sulfamethoxazole-trimethoprim with fluconazole was the most common drug-drug interaction (27.27 %). Vincristine with imatinib was the only identified interaction between two anti-cancer agents. The number of administered medications during ward stay was considered as an independent risk factor for developing a drug-drug interaction. CONCLUSIONS: Potential moderate or major drug-drug interactions occur frequently in patients with hematological malignancies or related diseases. Performing larger standard studies are required to assess the real clinical and economical effects of drug-drug interactions on patients with hematological and non-hematological malignancies.