Evaluation and statistical optimization of a method for methylated cell-free fetal DNA extraction from maternal plasma

Purpose: Methylated cell-free fetal DNA (cffDNA) in maternal plasma can potentially be used as a biomarker for accurate noninvasive prenatal testing (NIPT) of fetal disorders. Recovery and purification of cffDNA are key steps for downstream applications. In this study, we aimed to developed and evaluated different aspects of an optimized method and compared its efficiency with common methods used for extraction of methylated cffDNA. Methods: Single factor experiments, Plackett-Burman (PB) design, and response surface methodology (RSM) were conducted for conventional Triton/Heat/Phenol (cTHP) method optimization. The total cell-free DNA (cfDNA) was extracted from pooled maternal plasma using the optimized method called the Triton/Heat/Phenol/Glycogen (THPG), cTHP method, a column-based kit, and a magnetic bead-based kit. In the next step, methylated cfDNA from the extracted total cfDNA was enriched using a methylated DNA immunoprecipitation (MeDIP) kit. Real-time quantitative polymerase chain reaction was performed on the RASSF1 gene and hyper region to determine the genomic equivalents per milliliter (GEq/ml) values of the methylated cfDNA and cffDNA, respectively. Results: The optimum values of the significant factors affecting cfDNA extraction from 200 μl of plasma were 3% SDS, 1% Triton X-100, 0.9 μg/μl glycogen, and 0.3 M sodium acetate. The GEq/ml values of methylated cffDNA extracted using the THPG method were significantly higher than for the tested extraction methods (p < 0.001). Conclusions: Our results indicate that the THPG method is more efficient than the other tested methods for extraction of low copy number methylated cffDNA from a small volume of maternal plasm

River Flow Prediction Using the Nearest Neighbor Probabilistic Ensemble Method

Introduction: In the recent years, researchers interested on probabilistic forecasting of hydrologic variables such river flow.A probabilistic approach aims at quantifying the prediction reliability through a probability distribution function or a prediction interval for the unknown future value. The evaluation of the uncertainty associated to the forecast is seen as a fundamental information, not only to correctly assess the prediction, but also to compare forecasts from different methods and to evaluate actions and decisions conditionally on the expected values. Several probabilistic approaches have been proposed in the literature, including (1) methods that use resampling techniques to assess parameter and model uncertainty, such as the Metropolis algorithm or the Generalized Likelihood Uncertainty Estimation (GLUE) methodology for an application to runoff prediction), (2) methods based on processing the forecast errors of past data to produce the probability distributions of future values and (3) methods that evaluate how the uncertainty propagates from the rainfall forecast to the river discharge prediction, as the Bayesian forecasting system. Materials and Methods: In this study, two different probabilistic methods are used for river flow prediction.Then the uncertainty related to the forecast is quantified. One approach is based on linear predictors and in the other, nearest neighbor was used. The nonlinear probabilistic ensemble can be used for nonlinear time series analysis using locally linear predictors, while NNPE utilize a method adapted for one step ahead nearest neighbor methods. In this regard, daily river discharge (twelve years) of Dizaj and Mashin Stations on Baranduz-Chay basin in west Azerbijan and Zard-River basin in Khouzestan provinces were used, respectively. The first six years of data was applied for fitting the model. The next three years was used to calibration and the remained three yeas utilized for testing the models. Different combinations of recorded data were used as the input pattern to streamflow forecasting. Results and Discussion: Application of the used approaches in ensemble form (in order to choice the optimized parameters) improved the model accuracy and robustness in prediction. Different statistical criteria including correlation coefficient (R), root mean squared error (RMSE) and Nash–Sutcliffe efficiency coefficient (E) were used for evaluating the performance of models. The ranges of parameter values to be covered in the ensemble prediction have been identified by some preliminary tests on the calibration set. Since very small values of k have been found to produce unacceptable results due to the presence of noise, the minimum value is fixed at 100 and trial values are taken up to 10000 (k = 100, 200, 300,500, 1000, 2000, 5000, 10000). The values of mare chosen between 1 and 20 and delay time values γ are tested in the range [1,5]. With increasing the discharge values, the width of confidence band increased and the maximum confidence band is related to maximum river flows. In Dizaj station, for ensemble numbers in the range of 50-100, the variation of RMSE is linear. The variation of RMSE in Mashin station is linear for ensemble members in the range of 100-150. It seems the numbers of ensemble members equals to 100 is suitable for pattern construction. The performance of NNPE model was acceptable for two stations. The number of points excluded 95% confidence interval were equal to 108 and 96 for Dizaj and Mashin stations, respectively. The results showed that the performance of model was better in prediction of minimum and median discharge in comparing maximum values. Conclusion: The results confirmed the performance and reliability of applied methods. The results indicated the better performance and lower uncertainty of ensemble method based on nearest neighbor in comparison with probabilistic nonlinear ensemble method. Nash–Sutcliffe model efficiency coefficient (E) for nearest neighbor probabilistic ensemble method in Dizaj and Mashin Stations during test period of model obtained 0.91 and 0.93, respectively.The investigation on the performance of models in different basins showed that the models have better performance in Zard river basin compared to Baranduz-Chaybasin. Furthermore the variation of discharge values during test period in Zard basin was lower in comparison of Baranduz-Chay basin. The real advantage of including streamflow forecasts requires detailed and specific investigations, but the preliminary results suggest the good potentiality of probabilistic NLP method. Using ensemble prediction method can help to decision makers in order to determine the uncertainty of prediction in water resources field

Selenium as an adjuvant for modification of radiation response

Ionizing radiation plays a central role in several medical and industrial purposes. In spite of the beneficial effects of ionizing radiation, there are some concerns related to accidental exposure that could pose a threat to the lives of exposed people. This issue is also very critical for triage of injured people in a possible terror event or nuclear disaster. The most common side effects of ionizing radiation are experienced in cancer patients who had undergone radiotherapy. For complete eradication of tumors, there is a need for high doses of ionizing radiation. However, these high doses lead to severe toxicities in adjacent organs. Management of normal tissue toxicity may be achieved via modulation of radiation responses in both normal and malignant cells. It has been suggested that treatment of patients with some adjuvant agents may be useful for amelioration of radiation toxicity or sensitization of tumor cells. However, there are always some concerns for possible severe toxicities and protection of tumor cells, which in turn affect radiotherapy outcomes. Selenium is a trace element in the body that has shown potent antioxidant and radioprotective effects for many years. Selenium can potently stimulate antioxidant defense of cells, especially via upregulation of glutathione (GSH) level and glutathione peroxidase activity. Some studies in recent years have shown that selenium is able to mitigate radiation toxicity when administered after exposure. These studies suggest that selenium may be a useful radiomitigator for an accidental radiation event. Molecular and cellular studies have revealed that selenium protects different normal cells against radiation, while it may sensitize tumor cells. These differential effects of selenium have also been revealed in some clinical studies. In the present study, we aimed to review the radiomitigative and radioprotective effects of selenium on normal cells/tissues, as well as its radiosensitive effect on cancer cells. © 2019 Wiley Periodicals, Inc

Exosome loaded alginate hydrogel promotes tissue regeneration in full-thickness skin wounds: An in vivo study

Wound healing is known as one of the most complicated biological processes for injured skin caused by surgical, trauma, burns, or diabetic diseases, which causes a nonfunctioning mass of fibrotic tissue. Recent reports have suggested that exosomes (EXOs) secreted by this type of stem cells may contribute to their paracrine effect. In this study, the EXOs were isolated from the supernatant of cultured adipose-derived stem cells (ADSCs) via ultracentrifugation and filtration. The EXO loaded in the alginate-based hydrogel was used as a bioactive scaffold to preserve the EXO in the wound site in the animal model. The physical and biochemical properties of EXO loaded Alg hydrogel were characterized and results proved that fabricated structure was biodegradable and biocompatible. This bioactive wound dressing technique has significantly improved wound closure, collagen synthesis, and vessel formation in the wound area. Results offer a new viewpoint and a cell-free therapeutic strategy, for wound healing through the application of the composite structure of EXO encapsulated in alginate hydrogel. © 2019 Wiley Periodicals, Inc

Sildenafil enhances cisplatin-induced apoptosis in human breast adenocarcinoma cells

Introduction: Cyclic nucleotide phosphodiesterase (PDE) enzymes are a large superfamily of enzymes that catalyze the conversion reaction of cyclic adenosine monophosphate (AMP) and cyclic guanosine monophosphate (GMP) to AMP and GMP, respectively. In some cancer cells, PDE-5 has been shown to be overexpressed in multiple human carcinomas. It seems that the inhibition of PDE-5 may has anticancer effects. Cisplatin is one of the prevalent chemo-agents to treat solid tumors. However, its clinical usefulness is hindered by dose-limiting toxicities, especially on the kidneys (nephrotoxicity) and ears (ototoxicity). In this study, the antitumor activity of the sildenafil as a PDE-5 inhibitor alone and in combination with cisplatin on human mammary adenocarcinomas and MCF-7 and MDA-MB-468 was assessed. Materials and Methods: Sildenafil as PDE type 5 (PDE5) inhibitor is the drugs that we combined with the cisplatin (chemotherapeutic agent), in vitro. Human mammary adenocarcinomas and MCF-7 and MDA-MB-468 cell lines were cultured in standard conditions. At time point, following 24 h and 48 h incubation, the cell lines were treated by cisplatin in the presence/absence of sildenafil. Cell viability, apoptosis, and reactive oxygen species (ROS) were measured using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, real-time polymerase chain reaction, and Western blot; and fluorimetric methods, respectively. Statistical analysis was performed using SPSS software SPSS (SPSS Inc., Chicago, IL, USA). Results: In MCF-7 cell line, following 24 h incubation, combinations of sildenafil with cisplatin (P < 0.001) showed decreased cell viability when compared to sildenafil and cisplatin alone. Moreover in MDA-MB-468 cell line, following 24 h incubation, data did not show any significant changes on cell viability when treated with cisplatin, in the presence or absence of sildenafil. However, following 48 h incubation, combinations of cisplatin with sildenafil (P < 0.001) were showed decreased cell viability when compared to cisplatin and sildenafil alone in both MCF-7 and MDA-MB-468 cell lines. Concerning the ROS production and apoptosis, data showed that both processes increase significantly in the presence of the sildenafil in comparison absent it. Conclusion: Our data showed that the combination of sildenafil with cisplatin can improve cell toxicity and anticancer effect of cisplatin. And also sildenafil as a PDE-5 inhibitor could be used as additive treatment in combination with cisplatin to make a reduction in cisplatin dosage and its side effects. © 2020 Journal of Cancer Research and Therapeutics | Published by Wolters Kluwer - Medknow

Novel Hybrid Data-Intelligence Model for Forecasting Monthly Rainfall with Uncertainty Analysis

In this research, three different evolutionary algorithms (EAs), namely, particle swarm optimization (PSO), genetic algorithm (GA) and differential evolution (DE), are integrated with the adaptive neuro-fuzzy inference system (ANFIS) model. The developed hybrid models are proposed to forecast rainfall time series. The capability of the proposed evolutionary hybrid ANFIS was compared with the conventional ANFIS in forecasting monthly rainfall for the Pahang watershed, Malaysia. To select the optimal model, sixteen different combinations of six different lag attributes taking into account the effect of monthly, seasonal, and annual history were considered. The performances of the forecasting models were assessed using various forecasting skill indicators. Moreover, an uncertainty analysis of the developed forecasting models was performed to evaluate the ability of the hybrid ANFIS models. The bound width of 95% confidence interval (d-factor) and the percentage of observed samples which was enveloped by 95% forecasted uncertainties (95PPU) were used for this purpose. The results indicated that all the hybrid ANFIS models performed better than the conventional ANFIS and for all input combinations. The obtained results showed that the models with best input combinations had the (95PPU and d-factor) values of (91.67 and 1.41), (91.03 and 1.41), (89.74 and 1.42), and (88.46 and 1.43) for ANFIS-PSO, ANFIS-GA, ANFIS-DE, and the conventional ANFIS, respectively. Based on the 95PPU and d-factor, it is concluded that all hybrid ANFIS models have an acceptable degree of uncertainty in forecasting monthly rainfall. The results of this study proved that the hybrid ANFIS with an evolutionary algorithm is a reliable modeling technique for forecasting monthly rainfall.Validerad;2019;Nivå 2;2019-04-12 (johcin)</p