A study of digital image analysis on the acrylamide derivative monomers induced apoptosis in rat cerebrum

Nowadays, apoptosis is mostly evaluated visually in histological studies. By using the quantitative digital image analysis, this study aimed to investigate the effect of acrylamide‐based monomers (acrylamide [AAm], methacrylamide [MAAm], N‐isopropylacrylamide [NIPAm]) on the cerebrum tissues in rats, which are the most common water‐soluble monomers in the production of polymeric hydrogels used as biomaterials. The Wistar albino rats weighing ~220–240 g were divided into control and three test groups. The control group received 1 mL of saline, and the test groups received 1 mL of aqueous 50 mg/kg/day intramuscular injection of AAm, MAAm, and NIPAm, respectively. At the end of the experiments, brain tissues of all rats euthanized by intramuscular injection of sodium pentobarbital were removed. Terminal deoxynucleotide transferase dUTP nick and labeling (TUNEL) method was applied to brain tissue sections. The monomers have been shown to cause apoptosis due to oxidative stress in cerebrum tissue. Based on apoptosis by tunneling method, quantitative digital image analysis of cell fragments was performed with Olympus cellSens Dimension 1.15 software, and the number, total count area, selected area, average area, and ROI% values of the fragments were found. In addition, the total area and ROI% values of the fragments increased linearly with increasing the molar mass of monomers from the digital image analysis data. Quantitative digital image analysis can facilitate the monitoring of apoptosis caused by the oxidative stress of monomers used in the production of the biomaterials.     

Production and characterization of carbon-based adsorbents from waste lignocellulosic biomass: their effectiveness in heavy metal removal

Abstract

In this study, hazelnut shell and walnut shell which are the agricultural wastes existent abundantly in many countries were pyrolyzed at different temperatures in the temperature range of 400–700?°C in order to optimize the physicochemical properties of biochars. The biochars with large surface area were used to removal of lead (Pb²⁺) ions, one of the most important heavy metal pollutant, from aqueous solutions. The characterization of raw biomass and also biochars produced by pyrolysis were performed using FT-IR, BET, SEM, partial and elemental analysis techniques. In order to determine the adsorption characteristics of both biochars, batch adsorption experiments were carried out under different experimental conditions. The optimum conditions were determined by investigating the effect of adsorption parameters (initial heavy metal concentration, temperature, adsorbent amount, pH, contact time and mixing speed) for efficient removal of Pb²⁺ ions from aqueous solution. The experimental results were investigated in terms of Langmuir, Freundlich and Temkin isotherm models. Together with the calculated thermodynamic parameters, the adsorption mechanism was tried to be explained. In order to determine the kinetic model of the adsorption process, the experimental data were applied to pseudo first-order, pseudo second-order and intra-particle diffusion model, and the model constants were investigated.     

Electron beam penetration of poly (methyl methacrylate)/colemanite composite irradiated at low earth orbit space radiation environment

Poly (methyl methacrylate) modification by colemanite (CMT) addition has ensured beta shielding improvement. This study has connected with space environmental utilization with Kibo Japanese Experiment Module on International Space Station at low earth orbit. Space environment experiment was performed by using Kibo Experiment Handrail Attachment Mechanism–ExHAM. The changes in beta transmission of the composite were examined (by Sr-90 radioisotope) before and after space environmental utilization and details on beta penetration capacity was examined to protect the equipment (used in aviation and aerospace industries) from space radiation. Beta attenuation variations have indicated composite densification with beta attenuation enhancement after CMT addition.     

Designing effective professional development for technology integration in schools

This study aims to explore the critical factors for effective professional development (PD) activities to support teachers' technology integration and suggests a design model: flipped PD. The following questions are investigated: What are the core features of effective teacher PD, what are the implications of core features in effective technology integration PD, and what are the best practices for designing a flipped PD model for preparing teachers to integrate technology into their classrooms? First, we discuss the core features of effective teacher PD: content focus, active learning, coherence, duration, collective participation, and the role of context. Second, we explore design factors in recent technology integration PD studies: learner centred, relevance and reflection, evidence of student learning, support and follow-up, student voice, and initial implementation with teacher leaders. Finally, we present a discussion of our recommendations for a flipped model for technology integration PD.     

Au/Pt Bimetallic Nanoparticle Decorated Microparticle Hybrid Catalyst System for Heterogeneous Hydrogenation of Styrene

Catalysis Letters - Poly(methacryloyloxy quinoline) microparticles were synthesized and used as reducing and stabilizing agents to prepare Au/Pt bimetallic nanoparticle (NP) decorated microparticle...     

Theophylline‐loaded pectin‐based hydrogels. I. Effect of medium pH and preparation conditions on drug release profile

In this study, a series of theophylline‐loaded calcium pectin gel films were prepared in three different Ca⁺² concentrations with three different methods for wound dressing applications. Drug release performance of the films were investigated in four different medium pH in order to mimic wound healing pH conditions. Hydrogel films were characterized by Fourier transform infrared spectroscopy, differential scanning calorimetry, scanning electron microscopy and atomic force microscopy. Their absorbency (fluid handling), swelling behavior, dehydration rate, dispersion characteristic, dressing pH determination, water vapor permeability, oxygen permeability, surface contact angle, flexibility, Shore A hardness, mean mass per unit area and thickness were determined. The effect of the hydrogels on wound healing was evaluated with an in vitro wound healing assay. After evaluating all data, we suggested that the hydrogel film prepared with swelling method using 7% or 10% crosslinker and dried at 26 °C is more suitable for controlled drug release process. We showed that between pH 3.25 and 7.12 the form of the hydrogel did not change, and drug release was continuous. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46731.     

Pulsed ultrasound-assisted extraction of natural antioxidants from mandarin (Citrus deliciosa Tenore) leaves: Experimental and modeling study

Pulsed ultrasound-assisted extraction (PUAE) of flavonoids and polyphenols from mandarin (Citrus deliciosa Tenore) leaves was examined. The response surface methodology (RSM) via face-centered central composite design (FCCD) was used to investigate the effects of extraction time (15–75?min), output amplitude (30–70%), and pH (4–10) to optimize the extraction process. The total phenolic material (TPM) and the total flavonoid material (TFM) and also the consumed energy of horn were measured as responses. Additionally, calorimetric calculations were done to evaluate the ultrasound energy dissipated into the solution. The calculated quadratic models were highly significant (p?R²) of 0.9722, 0.9805, and 0.9983. The results of the present study suggest that 65?min, 68.72?min, 15.00 extraction time, 61%, 59%, and 30% of ultrasound amplitude and 4, 6.7, and 4 pH of solution should be considered as optimal extraction conditions to get the optimum TPM (37.845?mg-GAE/g-DL), TFM (10.709?mg-CE/g-DL), and energy consumption (6130.275 Joule) for PUAE of mandarin leaves, respectively.     

Effects of environmental factors on seasonal and spatial changes in surface zooplankton in Golden Horn Estuary (Istanbul,Turkey)

The abundance and spatial distribution of zooplankton at monthly intervals were studied in polluted Golden Horn Estuary (Istanbul, Turkey), from July 2006 to December 2007. Selected water quality parameters also were measured. The zooplankton community was characterized by the presence of freshwater, estuarine and marine species, with a total of 59 taxa. Rotifers were the most important fraction of the total zooplankton, comprising 36.52% of all the samples. The zooplankton exhibited seasonal patterns, with the highest abundance occurring in the summer (979 ind. L^?1) and the lowest in the spring (856 ind. L^?1). Rotifera was the most abundant group in the upper and middle estuary, whereas Copepoda usually reaches the maximum densities in the higher salinity waters in the lower estuary. The study results indicated that both the sampling time (seasons) and sampling sites jointly had significant effects on the zooplankton densities (manova P < 0.05), and horizontal patterns were related to electrical conductivity, water temperature, dissolved oxygen, suspended particulate matter, pH and chlorophyll a measured in the estuary.     

Blood glucose level prediction for diabetes based on modified fuzzy time series and particle swarm optimization

Blood glucose control is an essential goal for the patients who have Type‐1 diabetes (T1D). The prediction of the blood glucose levels for the next 30‐minute is crucial. If the predicted blood glucose level is in the critical ranges, and these predictions can be known in advance, then the patients can take the necessary cautions to prevent from it. In this article, we propose a modified fuzzy particle swarm optimization algorithm for the prediction of blood glucose levels of 30‐minute after the last measurement. We form the average and patient‐specific models to predict the blood glucose level of the patients. Both models are tested on two different datasets which contain patients with T1D. The experimental results are evaluated in terms of root mean squared error and Clarke error grid analysis metrics. The results indicate that our proposed modified algorithm is feasible to be applied to the prediction of blood glucose levels. In addition, this approach can assist patients with T1D for their blood glucose control.