Using Online Social Media for Recruitment of Human Immunodeficiency Virus-Positive Participants: A Cross-Sectional Survey

Background

There are many challenges in recruiting and engaging participants when conducting research, especially with HIV-positive individuals. Some of these challenges include geographical barriers, insufficient time and financial resources, and perceived HIV-related stigma.

Objective

This paper describes the methodology of a recruitment approach that capitalized on existing online social media venues and other Internet resources in an attempt to overcome some of these barriers to research recruitment and retention.

Methods

From May through August 2013, a campaign approach using a combination of online social media, non-financial incentives, and Web-based survey software was implemented to advertise, recruit, and retain participants, and collect data for a survey study with a limited budget.

Results

Approximately US $5,000 was spent with a research staff designated at 20% of full-time effort, yielding 2034 survey clicks, 1404 of which met the inclusion criteria and initiated the survey, for an average cost of US $3.56 per survey initiation. A total of 1221 individuals completed the survey, yielding 86.97% retention.

Conclusions

These data indicate that online recruitment is a feasible and efficient tool that can be further enhanced by sophisticated online data collection software and the addition of non-financial incentives.     

The development of an artificial neural network – genetic algorithm model (ANN-GA) for the adsorption and photocatalysis of methylene blue on a novel sulfur–nitrogen co-doped Fe2O3 nanostructure surface

In this study, a new sulfur–nitrogen co-doped Fe₂O₃ nanostructure was synthesized via a simple and efficient method and characterized via UV-Vis spectrophotometry, X-ray diffraction, field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, and Brunauer–Emmett–Teller surface area analysis. The as-synthesized nanoparticles showed high efficiency for the removal of methylene blue. The experimental conditions including the dose of the nanoparticle, the concentration of the dye, pH and the light dose were studied and optimized. The removal percentage was approximately 95% in a short time (5 min). A three-layer artificial neural network (ANN) model was proposed for predicting the efficiency of the dye removal. The network was trained using the obtained experimental data at optimum values. Some training functions were tested and their ability to predict different numbers of neurons was evaluated. The coefficient of determination (R-squared) and the mean squared error (MSE) were measured for comparison. In order to improve the accuracy of the prediction and to remove its dependency on the number of neurons, the ANN parameters were optimized using the genetic algorithm (GA). The final model results showed an acceptable agreement with experimental data. Furthermore, the relative importance of the dose of the nanoparticle, the concentration of the dye, and pH on the efficiency were obtained as 39%, 46%, and 15%, respectively. Moreover, interestingly, the obtained results showed that this newly synthesized nanoparticle has some photocatalytic properties with a band gap of 1.65 eV and therefore, it can be proposed as a low-cost visible light-driven photocatalyst for engineering applications.

In this research an S-N doped Fe₂O₃ nanostructure is synthesized and its adsorption ability and photocatalytic activity were evaluated. The optimum experimental conditions were obtained and an ANN-GA model was proposed for predicting experimental values.     

Rosmarinus plants: Key farm concepts towards food applications

Rosmarinus species are aromatic plants that mainly grow in the Mediterranean region. They are widely used in folk medicine, food, and flavor industries and represent a valuable source of biologically active compounds (e.g., terpenoids, flavonoids, and phenolic acids). The extraction of rosemary essential oil is being done using three main methods: carbon dioxide supercritical extraction, steam distillation, and hydrodistillation. Furthermore, interesting antioxidant, antibacterial, antifungal, antileishmanial, anthelmintic, anticancer, anti‐inflammatory, antidepressant, and antiamnesic effects have also been broadly recognized for rosemary plant extracts. Thus the present review summarized data on economically important Rosmarinus officinalis species, including isolation, extraction techniques, chemical composition, pharmaceutical, and food applications.     

A label-free electrochemical biosensor based on 3D cubic Eu3+/Cu2O nanostructures with clover-like faces for the determination of anticancer drug cytarabine

The present research utilized a simplified procedure for developing a novel electro-chemical DNA biosensor based on a carbon paste electrode (CPE) modified with three-dimensional (3D) cubic Eu³⁺/Cu₂O nanostructures with clover-like faces (Eu³⁺/Cu₂O CLFNs). The modified electrode was applied to monitor electro-chemical interactions between dsDNA and cytarabine for the first time. Then, the decreased oxidation signal of guanine following the interactions between cytarabine and dsDNA was utilized as an indicator for selectively determining cytarabine using differential pulse voltammetry (DPV). According to the findings, the oxidation peak current of guanine was linearly proportionate with the cytarabine concentration in the range between 0.01 and 90 μM. Additionally, the limit of quantification (LOQ) and the limit of detection (LOD) respectively equaled 9.4 nM and 2.8 nM. In addition, the repeatability, applicability and reproducibility of this analysis to drug dosage forms and human serum samples were investigated. Furthermore, UV-vis spectroscopy, DPV, docking and viscosity measurements were applied to elucidate the interaction mechanism of dsDNA with cytarabine. It was found that this DNA biosensor may be utilized to sensitively, accurately and rapidly determine cytarabine.

Electrochemical biosensor based on three-dimensional (3D) cubic of Eu³⁺/Cu₂O with clover-like face nano-structures and ds-DNA modified carbon paste electrode for detecting cytarabine was fabricated.     

CHA2DS2‐VASc and PESI scores are associated with right ventricular dysfunction on computed tomography pulmonary angiography in patients with acute pulmonary thromboembolism

BackgroundAccurate risk stratification is the most important step in the management of patients with acute pulmonary thromboembolism (PTE). Pulmonary embolism severity index (PESI) is a clinical tool for PTE risk stratification. CHA₂DS₂‐VASc score, a risk assessment tool in patients with atrial fibrillation, is recently considered for acute PTE. The presence of right ventricular (RV) dysfunction in imaging is more efficient in acute PTE risk evaluation.HypothesisThis study aims to evaluate the association between CHA₂DS₂‐VASc and PESI score and each of them with RV dysfunction on computed tomography pulmonary angiography (CTPA).MethodsOne hundred eighteen patients with a definite diagnosis of PTE were entered. The CHA₂DS₂‐VASc and PESI scores were calculated for all of them. RV dysfunction including an increase in RV to left ventricular diameter ratio, interventricular septal bowing, and reflux of contrast medium into the inferior vena cava was examined by CTPA.ResultsPESI and CHA₂DS₂‐VASc scores were significantly associated with RV dysfunction. In addition, different classes of PESI scores were correlated with RV dysfunction. Moreover, this study showed that the CHA₂DS₂‐VASc score and PESI score had a positive correlation. The area under the curve value for the CHA₂DS₂‐VASc score was 0.625 with 61.54% sensitivity and 60.0% specificity for predicting RV dysfunction while for PESI score was 0.635 with 66.7% sensitivity and 60.0% specificity.ConclusionThis study showed that not only CHA₂DS₂‐VASc and PESI scores are positively correlated, but they are both associated with RV dysfunction diagnosed by CTPA. CHA₂DS₂‐VASc and PESI scores are able to predict RV dysfunction.     

Electrochemical reduction of NO catalyzed by boron-doped C60 fullerene: a first-principles study

The electrochemical reduction of nitrogen monoxide (NO) is one of the most promising approaches for converting this harmful gas into useful chemicals. Using density functional theory calculations, the work examines the potential of a single B atom doped C₆₀ fullerene (C₅₉B) for catalytic reduction of NO molecules. The results demonstrate that the NO may be strongly activated over the B atom of C₅₉B, and that the subsequent reduction process can result in the formation of NH₃ and N₂O molecules at low and high coverages, respectively. Based on the Gibbs free energy diagram, it is inferred that the C₅₉B has excellent catalytic activity for NO reduction at ambient conditions with no potential-limiting. At normal temperature, the efficient interaction between the *NOH and NO species might lead to the spontaneous formation of the N₂O molecule. Thus, the findings of this study provide new insights into NO electrochemical reduction on heteroatom doped fullerenes, as well as a unique strategy for fabricating low-cost NO reduction electrocatalysts with high efficiency.

Using DFT calculations, the potential of B-doped C₆₀ fullerene is evaluated for electrochemical reduction of nitrogen monoxide. The B-doped C₆₀ exhibits exceptional catalytic activity and high selectivity for reduction of nitrogen monoxide.