Fluorimetric detection of DNA methylation by cerium oxide nanoparticles for early cancer diagnosis.

In this study, a very sensitive fluorescence nano-biosensor was developed using CeO2 nanoparticles for the rapid detection of DNA methylation. The characteristics of CeO2 nanoparticles were determined by transmission electron microscopy (TEM), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD) spectroscopy, UV-visible spectroscopy, and fluorescence spectroscopy. The CeO2 nanoparticles were reacted with a single-stranded DNA (ssDNA) probe, and then methylated and unmethylated target DNAs hybridized with an ssDNA probe, and the fluorescence emission was measured. Upon adding the target unmethylated and methylated ssDNA, the fluorescence intensity increased in the linear range of concentration from 2 × 10-13 - 10-18 M. The limit of detection (LOD) was 1.597 × 10-6 M for methylated DNA and 1.043 × 10-6 M for unmethylated DNA. The fluorescence emission intensity of methylated sequences was higher than of that unmethylated sequences. The fabricated DNA nanobiosensor showed a fluorescence emission at 420 nm with an excitation wavelength of 280 nm. The impact of CeO2 binding on methylated and unmethylated DNA was further demonstrated by agarose gel electrophoresis. Finally, the actual sample analysis suggested that the nanobiosensor could have practical applications for detecting methylation in the human plasma samples.

Colorimetric sensor array for versatile detection and discrimination of model analytes with environmental relevance.

In the current work, a rapid, simple, low-cost, and sensitive smartphone-based colorimetric sensor array coupled with pattern-recognition methods was proposed for the determination and differentiation of some organic and inorganic bases (i.e., OH-, CO32-, PO43-, NH3, ClO-, diethanolamine, triethanolamine) as model compounds. The sensing system has been designed based on color-sensitive dyes (Fuchsine, Giemsa, Thionine, and CoCl2) which were used as sensor elements. The color changes of a sensor array were observed by the naked eye. The color patterns were recorded using digital imaging in a three-dimensional (red, green, and blue) space and quantitatively analyzed with color calibration techniques. Distinctive colorimetric patterns for target bases via linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA) were observed. The results indicated that the analytes related to each class (at the different concentration levels in the range of 0.001-1.0 mol L-1) were clustered together in the canonical discriminant plot and HCA dendrogram with high sensitivity and an overall precision of 85%. Furthermore, the first function factor of LDA correlated with the concentration of each target analyte in a correlation coefficient (R2) range of 0.864-0.996. These described procedures based on the colorimetric sensor array technique could be a promising candidate for practical applications in package technology and facile detection of pollutants.

Electrophysiological correlates of cognitive control and performance monitoring in risk propensity: An event-related potential study.

Investigating the cognitive control processes and error detection mechanisms involved in risk-taking behaviors is essential for understanding risk propensity. This study investigated the relationship between risk propensity and cognitive control processes using an event-related potentials (ERP) approach. The study employed a Cued Go/Nogo paradigm to elicit ERP components related to cognitive control processes, including contingent negative variation (CNV), P300, error-related negativity (ERN), and error positivity (Pe). Healthy participants were categorized into high-risk and low-risk groups based on their performance in the Balloon Analogue Risk Task (BART). The results revealed risk-taking behavior influenced CNV amplitudes, indicating heightened response preparation and inhibition for the high-risk group. In contrast, the P300 component showed no group differences but revealed enhanced amplitudes in Nogo trials, particularly in high-risk group. Furthermore, despite the lack of difference in the Pe component, the high-risk group exhibited smaller ERN amplitudes compared to the low-risk group, suggesting reduced sensitivity to error detection. These findings imply that risk-taking behaviors may be associated with a hypoactive avoidance system rather than impaired response inhibition. Understanding the neural mechanisms underlying risk propensity and cognitive control processes can contribute to the development of interventions aimed at reducing risky behaviors and promoting better decision-making.

Machine learning-based classifying of risk-takers and risk-aversive individuals using resting-state EEG data: A pilot feasibility study.

BACKGROUND: Decision-making is vital in interpersonal interactions and a country's economic and political conditions. People, especially managers, have to make decisions in different risky situations. There has been a growing interest in identifying managers' personality traits (i.e., risk-taking or risk-averse) in recent years. Although there are findings of signal decision-making and brain activity, the implementation of an intelligent brain-based technique to predict risk-averse and risk-taking managers is still in doubt. METHODS: This study proposes an electroencephalogram (EEG)-based intelligent system to distinguish risk-taking managers from risk-averse ones by recording the EEG signals from 30 managers. In particular, wavelet transform, a time-frequency domain analysis method, was used on resting-state EEG data to extract statistical features. Then, a two-step statistical wrapper algorithm was used to select the appropriate features. The support vector machine classifier, a supervised learning method, was used to classify two groups of managers using chosen features. RESULTS: Intersubject predictive performance could classify two groups of managers with 74.42% accuracy, 76.16% sensitivity, 72.32% specificity, and 75% F1-measure, indicating that machine learning (ML) models can distinguish between risk-taking and risk-averse managers using the features extracted from the alpha frequency band in 10 s analysis window size. CONCLUSIONS: The findings of this study demonstrate the potential of using intelligent (ML-based) systems in distinguish between risk-taking and risk-averse managers using biological signals.

Immunomodulatory role of Nanocurcumin in COVID-19 patients with dropped natural killer cells frequency and function.

The ongoing COVID-19 pandemic is still a challenging problem in the case of infection treatment. The immunomodulatory effect of Nanocurcumin was investigated in the present study in an attempt to counterbalance the immune response and improve the patients' clinical symptoms. 60 confirmed COVID-19 patients and 60 healthy controls enrolled in the study. COVID-19 patients were divided into Nanocurcumin and placebo received groups. Due to the importance of the role of NK cells in this disease, the frequency, cytotoxicity, receptor gene expression of NK cells, and serum secretion levels of inflammatory cytokines IL-1ß, IL-6, TNF-α, as well as circulating C5a as a chemotactic factor an inflammatory mediator was evaluated by flow cytometry, real-time PCR and enzyme-linked immunosorbent assay in both experimental groups before and after the intervention. Given the role of measured factors in the progression and pathogenesis of COVID-19 disease, the results can help find appropriate treatments. The results of this study indicated that the Nanocurcumin could significantly increase the frequency and function of NK cells compared to the placebo-treated group. As an immunomodulatory agent, Nanocurcumin may be a helpful choice to improve NK cell function in COVID-19 patients and improve the clinical outcome of patients.

Development of reinforced aldehyde-modified kappa-carrageenan/gelatin film by incorporation of halloysite nanotubes for biomedical applications.

Recently, with the progression in tissue engineering, the importance of biocompatible nanocomposite film with suitable properties for potential applications in the biomedical area has been more developed. In this work, nanocomposite films of aldehyde-modified Carrageenan/Gelatin/halloysite nanotubes (AD-Carr/Gel/HNTs) nanocomposite films were successfully fabricated by the solution casting process. Halloysite nanotubes (HNTs) with different concentrations (0.5, 1.0, and 1.5 wt%) loaded into the aldehyde-modified Carrageenan/Gelatin (AD-Carr/Gel). Meanwhile, the developed AD-Carr/Gel/HNTs nanocomposite films were characterized by scanning electron microscopy (SEM), thermogravimetric analysis (TGA), mechanical property, water adsorption as well as in vitro degradation. The feasibility and capability of the nanocomposite films were further evaluated by hemocompatibility study, which showed that these nanocomposite films are hemocompatible. Besides, MTT assay revealed that the nanocomposite films are non-toxic, presenting the films as a good candidate to be used for tissue engineering purposes.

Ultrastructural and morphometrical study of preimplantation endometrium in superovulated mice treated with progesterone or Sildenafil.

BACKGROUND: Endometrial development has an important role in blastocyst adhesion and implantation. During IVF cycles, endometrial development is enhanced by progesterone. OBJECTIVE: The aim of this study was to compare ultrastructural and morphometrical characteristics of mice uterine endometrium in natural cycle with those in superovulated cycles received progesterone or Sildenafil. MATERIALS AND METHODS: In This study, 60 female bulb/c mice were divided into 4 groups: a control and 3 experimental; gonadotropin, gonadotropin+ Sildenafil and gonadotropin+ progesterone. In experimental groups the mice superovulated mated. In the gonadotropin+ progesterone and gonadotropin+ Viagra groups, the mice respectively received 1mg progesterone and 3 mg Sildenafil citrate. Their uterine specimens were prepared for morphometrical and ultrastructural study. Height of the epithelial cells was measured, using motic software. Statistical analysis was performed using ANOVA. RESULTS: Microscopy revealed that in control group the cells had numerous apical microvilli and the height of the cells was 20.52±2.43 µm. In gonadotropin+ progesterone group, the granules were found in basal and apical portions and cellular height were 17.91±2.78 µm which were significantly shorter than in the control and gonadotropin groups (p<0.001). In this group, the apical membrane also contained pinopodes. In gonadotropin +Sildenafil group, the granules were found in both apical and basal portions and the height of the cells were 17.60±2.49 µm which were significantly shorter than in the control and gonadotropin groups (p<0.001). In this group, pinopodes appeared slightly extensive than the other groups. CONCLUSION: It is concluded that superovulatory drugs in mice stimulate endometrial maturation but injection of Sildenafil is nearly more positive. This article extracted from Ph.D. thesis. (Bahman Rashedee).