Facile synthesis of Persian gum-graphene oxide composite as a novel adsorbent for CO2 capture: characterization and optimization.

Burning fossil fuels releases toxic gases into the environment and has negative effects on it. In this study, Persian gum@Graphene oxide (Pg@GO) was synthesized and used as a novel adsorbent for CO2 capture. The characterization of materials was determined through XRD, FTIR, FE-SEM, and TGA analysis. The operating parameters including temperature, Pressure, and adsorbent weight were studied and optimized by response surface methodology via Box-Behnken design (RSM-BBD). The highest amount of CO2 adsorption capacity was 4.80 mmol/g, achieved at 300 K and 7.8 bar and 0.4 g of adsorbent weight. To identify the behavior and performance of the Pg@GO, various isotherm and kinetic models were used to fit with the highest correlation coefficient (R2) amounts of 0.955 and 0.986, respectively. The results proved that the adsorption of CO2 molecules on the adsorbent surface is heterogeneous. Based on thermodynamic results, as the value of ΔG° is - 8.169 at 300 K, the CO2 adsorption process is exothermic, and spontaneous.

Comprehensive investigation of isotherm, RSM, and ANN modeling of CO2 capture by multi-walled carbon nanotube.

Chemical vapor deposition was used to produce multi-walled carbon nanotubes (MWCNTs), which were modified by Fe-Ni/AC catalysts to enhance CO2 adsorption. In this study, a new realm of possibilities and potential advancements in CO2 capture technology is unveiled through the unique combination of cutting-edge modeling techniques and utilization of the recently synthesized Fe-Ni/AC catalyst adsorbent. SEM, BET, and FTIR were used to analyze their structure and morphology. The surface area of MWCNT was found to be 240 m2/g, but after modification, it was reduced to 11 m2/g. The modified MWCNT showed increased adsorption capacity with higher pressure and lower temperature, due to the introduction of new adsorption sites and favorable interactions at lower temperatures. At 25 °C and 10 bar, it reached a maximum adsorption capacity of 424.08 mg/g. The optimal values of the pressure, time, and temperature parameters were achieved at 7 bar, 2646 S and 313 K. The Freundlich and Hill models had the highest correlation with the experimental data. The Second-Order and Fractional Order kinetic models fit the adsorption results well. The adsorption process was found to be exothermic and spontaneous. The modified MWCNT has the potential for efficient gas adsorption in fields like gas storage or separation. The regenerated M-MWCNT adsorbent demonstrated the ability to be reused multiple times for the CO2 adsorption process, as evidenced by the study. In this study, a feed-forward MLP artificial neural network model was created using a back-propagation training approach to predict CO2 adsorption. The most suitable and efficient MLP network structure, selected for optimization, consisted of two hidden layers with 25 and 10 neurons, respectively. This network was trained using the Levenberg-Marquardt backpropagation algorithm. An MLP artificial neural network model was created, with a minimum MSE performance of 0.0004247 and an R2 value of 0.99904, indicating its accuracy. The experiment also utilized the blank spreadsheet design within the framework of response surface methodology to predict CO2 adsorption. The proximity between the Predicted R2 value of 0.8899 and the Adjusted R2 value of 0.9016, with a difference of less than 0.2, indicates a high level of similarity. This suggests that the model is exceptionally reliable in its ability to predict future observations, highlighting its robustness.

Efficient CO2 adsorption using chitosan, graphene oxide, and zinc oxide composite.

This study was deeply focused on developing a novel CTS/GO/ZnO composite as an efficient adsorbent for CO2 adsorption process. To do so, design of experiment (DOE) was done based on RSM-BBD technique and according to the DOE runs, various CTS/GO/ZnO samples were synthesized with different GO loading (in the range of 0 wt% to 20 wt%) and different ZnO nanoparticle's loading (in the range of 0 wt% to 20 wt%). A volumetric adsorption setup was used to investigate the effect of temperature (in the range of 25-65 °C) and pressure (in the range of 1-9 bar) on the obtained samples CO2 uptake capability. A quadratic model was developed based on the RSM-BBD method to predict the CO2 adsorption capacity of the composite sample within design space. In addition, CO2 adsorption process optimization was conducted and the optimum values of the GO, ZnO, temperature, and pressure were obtained around 23.8 wt%, 18.2 wt%, 30.1 °C, and 8.6 bar, respectively, with the highest CO2 uptake capacity of 470.43 mg/g. Moreover, isotherm and kinetic modeling of the CO2 uptake process were conducted and the Freundlich model (R2 = 0.99) and fractional order model (R2 = 0.99) were obtained as the most appropriate isotherm and kinetic models, respectively. Also, thermodynamic analysis of the adsorption was done and the ∆H°, ∆S°, and ∆G° values were obtained around - 19.121 kJ/mol, - 0.032 kJ/mol K, and - 9.608 kJ/mol, respectively, indicating exothermic, spontaneously, and physically adsorption of the CO2 molecules on the CTS/GO/ZnO composite's surface. Finally, a renewability study was conducted and a minor loss in the CO2 adsorption efficiency of about 4.35% was obtained after ten cycles, demonstrating the resulting adsorbent has good performance and robustness for industrial CO2 capture purposes.

Forecasting Sauter mean droplet size and examining the range of droplet sizes in a Tenova liquid-liquid extraction column.

A new type of Tenova pulsed extraction column was introduced in 2017. It is the newest generation of pulsed columns. Due to the internal equipment of this column and the lack of moving parts and the simplicity and speed of repairs and maintenance, it has been the focus of researchers in recent years. No correlations for predicting the mean drop size and drop size distribution of the Tenova column have been reported. The Sauter mean drop diameter and drop size distribution are investigated for a Tenova pulsed column with a diameter and an active height of 7.4 and 73 cm, respectively. Three standard chemical systems of isobutyl acetate-water, isobutanol-water, and toluene-water have been used. The effects of pulse intensity, dispersed and continuous phase flow rates have been taken into account. In each experiment, 200-300 drops have been analyzed in a total of 10,000 drops. The investigation covered a spectrum of physical properties, notably surface tension (within a range of 1.75-36 mN/m). Operating conditions including pulse intensity (in the range of 0.2-2 cm/s) and the flow rate of continuous and dispersed phases (in the range of 8-30 L/h) have been investigated. Methods based on artificial intelligence (AI) such as multilayer perceptron neural networks and gene expression programming were combined with a dimensional analysis approach to provide a new approach to estimating the mean drop diameter (d32). Experimental results have been compared with the equations found by other researchers in similar columns. The variation of drop size distribution has also been experimentally obtained.Methods based on artificial intelligence (AI) such as multilayer perceptron neural networks and gene expression programming were combined with a dimensional analysis approach to provide a new approach to estimating the mean drop diameter (d32). Experimental results have been compared with the equations found by other researchers in similar columns. The variation of drop size distribution has also been experimentally obtained.

Assessment of metal extraction from e-waste using supported IL membrane with reliable comparison between RSM regression and ANN framework.

Recently, efficient techniques to remove indium ions from e-waste have been described due to their critical application. This paper illustrates the recovery of indium ions from an aqueous solution using a liquid membrane. CyphosIL 104 described the excellent potential for the extraction of indium ions. Evaluation of the five process parameters, such as indium concentration (10-100 mg/L), carrier concentration (0.05-0.2 mol/L), feed phase acidity (0.01-3 mol/L), chloride ion concentration (0.5-4 mol/L) and the stripping agent concentration (0.1-5 mol/L) were conducted. The interactive impacts of the various parameters on the extraction efficiency were investigated. The response surface methodology (RSM) and artificial neural network (ANN) were employed to model and compare the FS-SLM process results. RSM model with a quadratic equation (R2 = 0.9589) was the most suitable model for describing the efficiency. ANN model with six neurons showed a prediction of extraction efficiency with R2 = 0.9860. The best-optimized data were: 73.92 mg/L, 0.157 mol/L, 1.386 mol/L, 2.99 mol/L, and 3.06 mol/L for indium concentration, carrier concentration, feed phase acidity, chloride ion concentration, and stripping agent concentration. The results achieved by RSM and ANN led to an experimentally determined extraction efficiency of 93.91%, and 94.85%, respectively. It was close to the experimental data in the optimization condition (95.77%). Also, the evaluation shows that the ANN model has a better prediction and fitting ability to reach outcomes than the RSM model.

Biodiesel production from Mastic oil via electrolytic transesterification: optimization using response surface methodology and engine test.

This study aimed to synthesize the biodiesel from Mastic oil by electrolysis method. Mastic gum is a potential and inexpensive feedstock for the biodiesel production. The oil content of Mastic gum was ~ 20% of the total gum weight. The gas chromatography-mass spectrometry (GC-MS) analysis was exploited to measure the oil's fatty acid profile. The response surface methodology (RSM) via Box-Behnken design (BBD) was utilized to specify the best processing condition of the electrolytic transesterification process. According to the RSM-BBD results, the highest predicted biodiesel yield was 95% at the reaction time of 1 h, methanol to oil ratio of 4:1, and catalyst weight of 1.2 wt%. Under these conditions, the produced Mastic oil biodiesel was blended with the neat diesel at different volume ratios of 5:95 (B5), 10:90 (B10), and 15:85 (B15). These fuel mixtures were tested in a single-cylinder engine to assess engine performance and exhaust emissions. The experiments exhibited that blending biodiesel with diesel can slightly improve the engine performance. Moreover, the application of blends with high volumes of biodiesel decreased the exhaust emissions, such as carbon monoxide (CO), carbon dioxide (CO2), and unburned hydrocarbons (UHC) by 54.54%, 41%, and 39.3%, respectively. However, the nitrogen oxide (NOx) emission increased because of the higher oxygen content of the biodiesel. It was also found that the physical and chemical characteristics of the Mastic oil biodiesel are the same as diesel, consistent with the ASTM standard. The Fourier transform infrared (FTIR) analysis also confirmed the biodiesel production.

Improved water purification by PVDF ultrafiltration membrane modified with GO-PVA-NaAlg hydrogel.

This work presents a modified polyvinylidene fluoride (PVDF) ultrafiltration membrane blended with graphene oxide-polyvinyl alcohol-sodium alginate (GO-PVA-NaAlg) hydrogel (HG) and polyvinylpyrrolidone (PVP) prepared by the immersion precipitation induced phase inversion approach. Characteristics of the membranes with different HG and PVP concentrations were analyzed by field emission scanning electron microscopy (FESEM), Atomic force microscopy (AFM), contact angle measurement (CA), and Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). The FESEM images showed an asymmetric structure of the fabricated membranes, and possessing a thin dense layer over the top and a layer finger-like. With increasing HG content, membrane surface roughness increases so that highest surface roughness for the membrane containing 1wt% HG is with a Ra value of 281.4 nm. Also, the contact angle of the membrane reaches from 82.5° in bare PVDF membrane to 65.1° in the membrane containing 1wt% HG. The influences of adding HG and PVP to the casting solution on pure water flux (PWF), hydrophilicity, anti-fouling ability, and dye rejection efficiency were evaluated. The highest water flux reached 103.2 L/m2 h at 3 bar for the modified PVDF membranes containing 0.3 wt% HG and 1.0wt% PVP. This membrane exhibited a rejection efficiency of higher than 92%, 95%, and 98% for Methyl Orange (MO), Conge Red (CR), and Bovine Serum Albumin (BSA), respectively. All nanocomposite membranes possessed a flux recovery ratio (FRR) higher than bare PVDF membranes, and the best anti-fouling performance of 90.1% was relevant to the membrane containing 0.3 wt% HG. The improved filtration performance of the HG-modified membranes was due to the enhanced hydrophilicity, porosity, mean pore size, and surface roughness after introducing HG.

Intelligent prediction models based on machine learning for CO2 capture performance by graphene oxide-based adsorbents.

Designing a model to connect CO2 adsorption data with various adsorbents based on graphene oxide (GO) which is produced from various forms of solid biomass, can be a promising method to develop novel and efficient adsorbents for CO2 adsorption application. In this work, the information of several GO-based solid sorbents were extracted from 17 articles aimed to develop a machine learning based model for CO2 adsorption capacity prediction. The extracted data including specific surface area, pore volume, temperature, and pressure were considered as input parameter, and CO2 uptake capacity was defined as model response, alsoseven different models, including support vector machine, gradient boosting, random forest, artificial neural network (ANN) based on multilayer perceptron (MLP) and radial basis function (RBF), Extra trees regressor and extreme gradient boosting, were employed to estimate the CO2 adsorption capacity. The best performance was obtained for ANN based on MLP method (R2 > 0.99) with hyperparameters of the following: hidden layer size = [45 35 45 45], optimizer = Adam, the learning rate = 0.003, ß1 = 0.9, ß2 = 0.999, epochs = 1971, and batch size = 32. To investigate CO2 uptake dependency on mentioned effective parameters, three dimensional diagrams were reported based on MLP network, also the MLP network characteristics including weight and bias matrices were reported for further application of CO2 adsorption process design. The accurately predicted capability of the generated models may considerably minimize experimental efforts, such as estimating CO2 removal efficiency as the target based on adsorbent properties to pick more efficient adsorbents without increasing processing time. Current work employed statistical analysis and machine learning to support the logical design of porous GO for CO2 separation, aiding in screening adsorbents for cleaner manufacturing.

Production of biodiesel from salvia mirzayanii oil via electrolysis using KOH/Clinoptilolite as catalyst.

Backgrounds: In recent years, fossil fuels are the main energy supply in both transportation and industry. Their increasing consumption has been causing global warming and acid raining. One of the alternative fuels that is considered today is biodiesel, which is clean and eco-friendly. The main method for biodiesel production is transesterification reaction of triglyceride oil with methanol in the presence of a suitable catalyst. Method: In this research, biodiesel was produced from Salvia mirzayanii oil in the presence of KOH/Clinoptilolite catalyst. The impregnation, hydrothermal, and incipient wetness methods were used for loading KOH on the Clinoptilolite support to produce biodiesel via electrolysis method. The characteristics of the KOH/Clinoptilolite catalyst were examined through scanning electron microscopy (SEM), energy dispersive X-ray Spectroscopy (EDX), X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET) analyses. The effects of key parameters including catalyst amount, methanol to oil molar ration, reaction time, reaction temperature, co-solvent type and its proportion, electrolysis voltage, catalyst reusability, and KOH concentration were examined on the biodiesel yield. Results: The results of elemental analysis confirmed that KOH was well loaded on Clinoptilolite support. The highest yield of biodiesel was obtained 79% in the presence of 10 wt% catalyst, alcohol to oil ratio of 9:1, acetone concentration of 10 wt%, temperature of 60 °C, and voltage of 10 V. The results of GC-MS, FTIR and H-NMR analyses illustrated that biodiesel as a product was produced with good quality. Conclusion: Based on the obtained results, in all three methods of catalyst synthesis KOH was loaded on Clinoptilolite support but at the end of the transesterification reaction only the catalyst synthesis via incipient wetness method could be reused three times under optimum reaction conditions. The produced biodiesel had high quality, whose physical and chemical properties had good agreement with ASTM, EN 14214, IS 15607 standards. Since the salvia mirzayanii oil is an appropriate feedstock source for biodiesel production, it is suggested to use salvia mirzayanii oil and KOH/Clinoptilolite catalyst to produce biodiesel on industrial scale.

Mean drop behavior in the standard liquid-liquid extraction systems on an L-shaped pulsed sieve-plate column: experiment and modeling.

In this study, the effect of operating parameters on drop behavior was investigated experimentally in an L-shaped pulsed sieve-plate column (LPSPC). LPSPC offers enhanced efficiency due to a high mixing rate provided by pneumatic or hydraulic pulsation of the liquids, which makes the dispersed phase drops coalesce and break. The response surface methodology (RSM) based on the central composite design (CCD) approach was applied for experimental modeling of three standard systems including toluene-water, butyl acetate-water, and butanol-water. Four parameters including pulsation intensity, interfacial tension, dispersion, and continuous phase velocities were examined in the experiments. Experimental results indicated that an increase in the pulsation intensity led to a decrease in Sauter mean diameter (SMD), and an increase in the flow rates of the phase cause an increase in SMD, although the effect of the flow rates on SMD was much lower than the pulsation intensity. Based on the obtained experimental data, new correlations have been proposed to predict SMD in two sections of the column tested by the goodness-of-fit statistics through analysis of variance. The coefficient of determination was achieved at 0.998 and 0.978 for horizontal and vertical sections, respectively, which demonstrated that the presented models estimated the experimental values very well. The optimum SMDs were obtained at 0.789 mm and 0.639 mm for the horizontal and vertical sections, respectively.

Modelling tyramine extraction from wastewater using a non-dispersive solvent extraction process.

Wastewater effluent from alkaloid processing plants has the potential adverse environmental influences. Mathematical modelling and simulations were carried out using computational fluid dynamics of mass and momentum transfer in a hollow fibre membrane extractor. Conservation equations were derived for tyramine extraction in the membrane extractor and solved based on the finite element method. Model findings based on the computational fluid dynamics validated well with the experimental data. The results showed that increase in organic-phase flow rate, as well as the fibre length and its porosity, has a positive impact on the performance of the extractor, whereas the enhancement of aqueous-phase flow rate led to the reduction of tyramine extraction.

The ameliorative effect of carvacrol on oxidative stress and germ cell apoptosis in testicular tissue of adult diabetic rats.

BACKGROUND: Diabetes is one of the most chronic and widespread diseases causing the damages to the male reproductive system. Nowadays, several studies have been performed to show the role of phenolic compounds in reducing the complications of diabetes. Carvacrol is a phenolic monoterpene which has been shown to have much therapeutic efficacy in various diseases. METHODS: Thirty-two adult male Wistar rats (n = 8 in each group) were used in this experimental study. The induction of diabetes was performed using a single intraperitoneal (IP) injection of STZ (50 mg/kg). Rats were assigned into the following groups: control group, diabetic group, diabetic group daily fed with carvacrol at a dose of 75 mg/kg for 8 weeks, and the control group daily fed with carvacrol at a dose of 75 mg/kg for 8 weeks. RESULTS: Treatment with carvacrol significantly improved the histological morphology of the testis, reduced the tissue activity of superoxide dismutase (SOD) and glutathione peroxidase (GPx) enzymes, and diminished the elevated levels of tissue malondialdehyde (MDA) (p < 0.05). Moreover, our results showed that carvacrol significantly decreased Bax and increased Bcl-2 at the levels of gene and protein expression. It also significantly (p < 0.05) reduced the rate of germ cell apoptosis. CONCLUSION: It seems that the treatment with carvacrol mitigates testicular tissue damage in diabetic rats possibly through its antioxidant properties.

Regulation and modulation of PTEN activity.

PTEN (Phosphatase and tensin homolog deleted on chromosome ten) is a tumor suppressor that is frequently mutated in most human cancers. PTEN is a lipid and protein phosphatase that antagonizes PI3K/AKT pathway through lipid phosphatase activity at the plasma membrane. More recent studies showed that, in addition to the putative role of PTEN as a PI(3,4,5)P3 3-phosphatase, it is a PI(3,4)P2 3-phosphatase during stimulation of class I PI3K signaling pathway by growth factor. Although PTEN tumor suppressor function via it's lipid phosphatase activity occurs primarily in the plasma membrane, it can also be found in the nucleus, in cytoplasmic organelles and extracellular space. PTEN has also shown phosphatase independent functions in the nucleus. PTEN can exit from the cell through exosomal export or secretion and has a tumor suppressor function in adjacent cells. PTEN has a critical role in growth, the cell cycle, protein synthesis, survival, DNA repair and migration. Understanding the regulation of PTEN function, activity, stability, localization and its dysregulation outcomes and also the intracellular and extracellular role of PTEN and paracrine role of PTEN-L in tumor cells as an exogenous therapeutic agent can help to improve clinical conceptualization and treatment of cancer.

Low Level Pro-inflammatory Cytokines Decrease Connexin36 Gap Junction Coupling in Mouse and Human Islets through Nitric Oxide-mediated Protein Kinase Cδ.

Pro-inflammatory cytokines contribute to the decline in islet function during the development of diabetes. Cytokines can disrupt insulin secretion and calcium dynamics; however, the mechanisms underlying this are poorly understood. Connexin36 gap junctions coordinate glucose-induced calcium oscillations and pulsatile insulin secretion across the islet. Loss of gap junction coupling disrupts these dynamics, similar to that observed during the development of diabetes. This study investigates the mechanisms by which pro-inflammatory cytokines mediate gap junction coupling. Specifically, as cytokine-induced NO can activate PKCδ, we aimed to understand the role of PKCδ in modulating cytokine-induced changes in gap junction coupling. Isolated mouse and human islets were treated with varying levels of a cytokine mixture containing TNF-α, IL-1ß, and IFN-γ. Islet dysfunction was measured by insulin secretion, calcium dynamics, and gap junction coupling. Modulators of PKCδ and NO were applied to determine their respective roles in modulating gap junction coupling. High levels of cytokines caused cell death and decreased insulin secretion. Low levels of cytokine treatment disrupted calcium dynamics and decreased gap junction coupling, in the absence of disruptions to insulin secretion. Decreases in gap junction coupling were dependent on NO-regulated PKCδ, and altered membrane organization of connexin36. This study defines several mechanisms underlying the disruption to gap junction coupling under conditions associated with the development of diabetes. These mechanisms will allow for greater understanding of islet dysfunction and suggest ways to ameliorate this dysfunction during the development of diabetes.

Chemometric assisted ultrasound leaching-solid phase extraction followed by dispersive-solidification liquid-liquid microextraction for determination of organophosphorus pesticides in soil samples.

Ultrasound leaching-solid phase extraction (USL-SPE) followed by dispersive-solidification liquid-liquid microextraction (DSLLME) was developed for preconcentration and determination of organophosphorus pesticides (OPPs) in soil samples prior gas chromatography-mass spectrometry analysis. At first, OPPs were ultrasonically leached from soil samples by using methanol. After centrifugation, the separated methanol was diluted to 50 mL with double-distillated water and passed through the C18 SPE cartridge. OPPs were eluted with 1 mL acetonitrile. Thus, 1 mL acetonitrile extract (disperser solvent) and 10 µL 1-undecanol (extraction solvent) were added to 5 mL double-distilled water and a DSLLME technique was applied. The variables of interest in the USL-SPE-DSLLME method were optimized with the aid of chemometric approaches. First, in screening experiments, fractional factorial design (FFD) was used for selecting the variables which significantly affected the extraction procedure. Afterwards, the significant variables were optimized using response surface methodology (RSM) based on central composite design (CCD). Under the optimum conditions, the enrichment factors were 6890-8830. The linear range was 0.025-625 ng g(-1) and limits of detection (LODs) were between 0.012 and 0.2 ng g(-1). The relative standard deviations (RSDs) were in the range of 4.06-8.9% (n=6). The relative recoveries of OPPs from different soil samples were 85-98%.

The effect of BSO-induced oxidative stress on histologic feature of testis: testosterone secretion and semen parameters in mice.

OBJECTIVES: Buthionine sulfoximine (BSO) inhibits synthesis of glutathione as the main intracellular antioxidant. The aim of the present study is to investigate the effect of BSO-induced oxidative stress on histological structure of testis, testosterone secretion and semen parameters. MATERIALS AND METHODS: Thirty male BALB/c mice were divided into 3 groups. In control group, the mice did not receive any chemical. In the experimental group, the mice received 2 mmol/kg BSO for 35 days. In the sham group, the mice received the solvent of BSO (0.9% saline). After the treatment, the mice were sacrificed. Their testes were fixed in Buein's fixative, embedded in paraffin and prepared for histological studies. To assess semen parameters, the sperms were collected from cauda epididymis. Blood samples were used for determination of super oxide dismutase (SOD), malondialdehyde (MDA), glutathione peroxidase (GPX), glutathione (GSH), catalase (CAT) and the serum testosterone level. The data analyzed using ANOVA and Dunnett's tests and SPSS software, version11.5. P- values at 0.05 level considered significant. RESULTS: Data showed that in experimental group in comparison to control group; the concentration of CAT, GPX, SOD,GSH and the total level of testosterone is reduced while MDA level is increased significantly. The number of sperms with progressive motility were decreased (P<0.001) but sperms with abnormal morphology were increased (P<0.001). Histological studies revealed that the values for tubal differentiation index and spermatogenic index in experimental group were reduced (P<0.001). CONCLUSION: It is concluded that exposure to oxidative stress induced by BSO could affect testicular structure and semen parameters.

Fluorescence recovery after photobleaching reveals regulation and distribution of connexin36 gap junction coupling within mouse islets of Langerhans.

The pancreatic islets are central to the maintenance of glucose homeostasis through insulin secretion. Glucose­stimulated insulin secretion is tightly linked to electrical activity in ß cells within the islet. Gap junctions, composed of connexin36 (Cx36), form intercellular channels between ß cells, synchronizing electrical activity and insulin secretion. Loss of gap junction coupling leads to altered insulin secretion dynamics and disrupted glucose homeostasis. Gap junction coupling is known to be disrupted in mouse models of pre­diabetes. Although approaches to measure gap junction coupling have been devised, they either lack cell specificity, suitable quantification of coupling or spatial resolution, or are invasive. The purpose of this study was to develop fluorescence recovery after photobleaching (FRAP) as a technique to accurately and robustly measure gap junction coupling in the islet. The cationic dye Rhodamine 123 was used with FRAP to quantify dye diffusion between islet ß cells as a measure of Cx36 gap junction coupling. Measurements in islets with reduced Cx36 verified the accuracy of this technique in distinguishing between distinct levels of gap junction coupling. Analysis of individual cells revealed that the distribution of coupling across the islet is highly heterogeneous. Analysis of several modulators of gap junction coupling revealed glucose­ and cAMP­dependent modulation of gap junction coupling in islets. Finally, FRAP was used to determine cell population specific coupling, where no functional gap junction coupling was observed between α cells and ß cells in the islet. The results of this study show FRAP to be a robust technique which provides the cellular resolution to quantify the distribution and regulation of Cx36 gap junction coupling in specific cell populations within the islet. Future studies utilizing this technique may elucidate the role of gap junction coupling in the progression of diabetes and identify mechanisms of gap junction regulation for potential therapies.

Response surface methodology based on central composite design as a chemometric tool for optimization of dispersive-solidification liquid-liquid microextraction for speciation of inorganic arsenic in environmental water samples.

Dispersive-solidification liquid-liquid microextraction (DSLLME) coupled with electrothermal atomic absorption spectrometry (ETAAS) was developed for preconcentration and determination of inorganic arsenic (III, V) in water samples. At pH=1, As(III) formed complex with ammonium pyrrolidine dithiocarbamate (APDC) and extracted into the fine droplets of 1-dodecanol (extraction solvent) which were dispersed with ethanol (disperser solvent) into the water sample solution. After extraction, the organic phase was separated by centrifugation, and was solidified by transferring into an ice bath. The solidified solvent was transferred to a conical vial and melted quickly at room temperature. As(III) was determined in the melted organic phase while As(V) remained in the aqueous layer. Total inorganic As was determined after the reduction of the pentavalent forms of arsenic with sodium thiosulphate and potassium iodide. As(V) was calculated by difference between the concentration of total inorganic As and As(III). The variable of interest in the DSLLME method, such as the volume of extraction solvent and disperser solvent, pH, concentration of APDC (chelating agent), extraction time and salt effect, was optimized with the aid of chemometric approaches. First, in screening experiments, fractional factorial design (FFD) was used for selecting the variables which significantly affected the extraction procedure. Afterwards, the significant variables were optimized using response surface methodology (RSM) based on central composite design (CCD). In the optimum conditions, the proposed method has been successfully applied to the determination of inorganic arsenic in different environmental water samples and certified reference material (NIST RSM 1643e).

Pleomorphic adenoma of the cervical heterotopic salivary gland: a case report.

Introduction. Although pleomorphic adenoma is the most common neoplasm of the salivary glands, this tumor most commonly involves the minor salivary glands of palatal and rarely occurs in cervical region. Case Report. A 21-year-old female referred to our clinic due to painless mass of right upper region of neck. After paraclinical and pathologic evaluation, it was diagnosed as cervical pleomorphic adenoma. Conclusion. Pleomorphic adenoma may be rarely involving the neck. Although the prognosis is good, the choice treatment is the complete resection of the tumor.

Intermittent hydrostatic pressure enhances growth factor-induced chondroinduction of human adipose-derived mesenchymal stem cells.

Hydrostatic pressure (HP) plays an essential role in regulating function of chondrocytes and chondrogenic differentiation. The objective of this study was to examine effects of intermittent HP on chondrogenic differentiation of human adipose-derived mesenchymal stem cells (hASCs) in the presence or absence of chemical chondrogenic medium. Cells were isolated from abdominal fat tissue and confirmed for expression of ASC surface proteins and differentiation potential. Passage 3 pellets were treated with chemical (growth factor), mechanical (HP of 5 MPa and 0.5 Hz with duration of 4 h/day for 7 consecutive days), and combined chemical-mechanical stimuli. Using real-time polymerase chain reaction, the expression of Sox9, collagen II, and aggrecan as three major chondrogenic markers were quantified among three experimental groups and compared to those of stem cells and human cartilage tissue. In comparison to the chemical and mechanical groups, the chemical-mechanical group showed the highest expression for all three chondrogenic genes close to that of cartilage tissue. Results show the beneficial role of intermittent HP on chondrogenic differentiation of hASCs, and that this loading regime in combination with chondrogenic medium can be used in cartilage tissue engineering.