Adsorptive removal of azithromycin from aqueous solutions using raw and saponin-modified nano diatomite.

This study aims to investigate the performance and mechanism of raw (R-ND) and saponin-modified nano diatomite (M-ND) in the removal of azithromycin from aqueous solutions. Adsorbent characterization was performed using X-ray fluorescence, Brunauer-Emmett-Teller (BET), scanning electron spectroscopy, dynamic light scattering and energy-dispersive X-ray analyses. It was shown that the specific surface area of R-ND was 119.5 m2/g, 14-fold higher than that for raw diatomite, and for M-ND it was 90.1 m2/g. Various adsorption conditions, i.e. adsorbent dosage, pH, initial concentration and contact time were investigated. According to the results, despite reducing the specific surface area by 25%, modification of nano diatomite by saponin markedly enhanced its performance in the removal of azithromycin. The maximum adsorption capacity of R-ND and M-ND in the removal of azithromycin was 68 and 91.7 mg/g, respectively. Fourier transform infrared spectroscopy results revealed that azithromycin was adsorbed by O-H groups on the diatomite surface. Weber-Morris intra-particle diffusion (IPD) model suggested that while IPD is not the rate-controlling step in high concentrations of azithromycin, it is the only step that controls the rate of adsorption in low concentrations. In comparison to R-ND, M-ND showed a higher efficiency in the removal of azithromycin and, therefore, it can be used as a promising low-cost adsorbent to remove azithromycin from aqueous solutions.

Application of nanoperlite as a new natural sorbent in the preconcentration of three organophosphorus pesticides by microextraction in packed syringe coupled with gas chromatography and mass spectrometry.

A rapid, low-cost, and simple method is proposed based on a miniaturized solid-phase extraction named microextraction in packed syringe coupled with gas chromatography and mass spectrometry for the preconcentration and determination of some organophosphorous pesticides including diazinon, ethion, and malathion. For the first time, natural nanoperlite is used as a safe sorbent. Based on this technique, the analytes are adsorbed on the solid phase and then eluted by a desorbing solvent. The influence of some important parameters such as the solution pH, type, and volume of the organic desorption solvent on the microextraction efficiency of the selected pesticide technique is investigated. The proposed method showed a good linearity in the range of 1.0-35.0 µg/L for ethion and 0.4-30.0 µg/L for both diazinon and malathion. The limits of detection in the range of 0.1-0.38 µg/L were obtained using the selected ion-monitoring mode of the mass spectrometer. The reproducibility of the method was found to be in the range of 2.8-8.9% for the studied pesticides. To evaluate the matrix effect, the developed method is also applied to the preconcentration and determination of the selected pesticides in real water samples.

Quantitative structure-property relationships of retention indices of some sulfur organic compounds using random forest technique as a variable selection and modeling method.

In this work, a noble quantitative structure-property relationship technique is proposed on the basis of the random forest for prediction of the retention indices of some sulfur organic compounds. In order to calculate the retention indices of these compounds, the theoretical descriptors produced using their molecular structures are employed. The influence of the significant parameters affecting the capability of the developed random forest prediction power such as the number of randomly selected variables applied to split each node (m) and the number of trees (nt ) is studied to obtain the best model. After optimizing the nt and m parameters, the random forest model conducted for m = 70 and nt = 460 was found to yield the best results. The artificial neural network and multiple linear regression modeling techniques are also used to predict the retention index values for these compounds for comparison with the results of random forest model. The descriptors selected by the stepwise regression and random forest model are used to build the artificial neural network models. The results achieved showed the superiority of the random forest model over the other models for prediction of the retention indices of the studied compounds.

Optimization of modified dispersive liquid-liquid microextraction coupled with high-performance liquid chromatography for the simultaneous preconcentration and determination of nitrazepam and midazolam drugs: An experimental design.

A simple, sensitive, and rapid microextraction method, namely, ultrasound-assisted surfactant-enhanced emulsification microextraction based on the solidification of floating organic droplet method coupled with high-performance liquid chromatography was developed for the simultaneous preconcentration and determination of nitrazepam and midazolam. The significant parameters affecting the extraction efficiency were considered using Plackett-Burman design as a screening method. To obtain the optimum conditions with consideration of the selected significant variables, a Box-Behnken design was used. The microextraction procedure was performed using 29.1 µL of 1-undecanol, 1.36% (w/v) of NaCl, 10.0 µL of sodium dodecyl sulfate (25.0 µg mL(-1)), and 1.0 µL of Tween80 (25.0 µg mL(-1)) as an emulsifier in an extraction time of 20.0 min at pH 7.88. In order to investigate the validation of the developed method, some validation parameters including the linear dynamic range, repeatability, limit of detection, and recoveries were studied under the optimum conditions. The detection limits of the method were 0.017 and 0.086 ng mL(-1) for nitrazepam and midazolam, respectively. The extraction recovery percentages for the drugs studied were above 91.0 with acceptable relative standard deviation. The proposed methodology was successfully applied for the determination of these drugs in a number of human serum samples.

Development of coupled ultrasound-assisted and reversed-phase dispersive liquid-liquid microextraction before high-performance liquid chromatography for the sensitive determination of vitamin A and vitamin E in oil samples.

A new approach based on the ultrasound-assisted reversed-phase dispersive liquid-liquid microextraction technique is developed for the extraction and determination of vitamin A and vitamin E from oil matrices before high-performance liquid chromatography analysis. A methodology based on the full factorial design is carried out to choose the significant parameters. Then the significant factors affecting the extraction efficiency including pH, volume of extraction solvent, and volume of disperser solvent are optimized using a Box-Behnken design. After analyzing the results obtained, the optimum conditions were: pH 4.5, 80-20 µL of the ethanol/water solvent mixture as extraction solvent, 110 µL of 1,4-dioxane as the disperser solvent, and a sonication time of 10 min. For validation of the developed method, the linear dynamic range, repeatability, limit of detection, and recoveries were obtained under the optimum conditions. The detection limits of the method were 1.6 and 2.3 ng/mL for vitamin A and vitamin E, respectively. The extraction recovery percentages for the studied drugs were above 91%, with acceptable relative standard deviation. The proposed methodology was successfully applied for the determination of the vitamins in different oil samples.

Application of chemometrics tools for removal of crystal violet and methylene blue in binary solution by eco-friendly magnetic adsorbent modified on Heracleum persicum waste.

Synthetic dyes can be hazardous to the ecosystem, even at low concentrations in the effluent. In this research, the Heracleum persicum stems-Fe3O4 (MHPS) adsorbent performance for the removal of crystal violet (CV) and methylene blue (MB) from binary aqueous solutions was investigated in a batch method under the influence of different parameters. In addition, predictive models for the adsorption process were developed using machine learning techniques such as artificial neural networks and random forests. ANN and RF models achieved high R2 values of 0.9501 and 0.9797 for CV, 0.9471, and 09,834 for MB, respectively, and obtained low MSE values of 0.07107 and 0.03405 for CV, 0.09933, and 0.02908 for MB. The proposed adsorbent is cheap and eco-friendly and, on the other hand, is easily collected by the magnetic field. The adsorbent was characterized by applying FESEM-EDX, FESEM, BET, and FTIR. Various isotherm and kinetics models for the simultaneous adsorption of CV and MB were investigated in aqueous solutions. The adsorption isotherm and kinetics studies explain that the extended Langmuir model and pseudo-second-order models are best suited for CV and MB in the binary solution. The exothermic adsorption was achieved in the temperature range of 5-45 °C.

Application of random forest for modeling batch and continuous fixed-bed removal of crystal violet from aqueous solutions using Gypsophila aretioides stem-based biosorbent.

In this work, the Gypsophila aretioides (GYP-A) stem is used as a biosorbent to remove crystal violet (CV) by the static and dynamic systems from aqueous solutions; the biosorbent is interesting in green chemistry and, on the other hand, cheaper than activated carbon and does not have the limitation of industrialization. The effects of different operating parameters such as pH(3-9), biosorbent dosage(0.4-1.8 mg/L), and initial concentration of CV(100-250 mg/L) and time for the batch method and the bed height, inlet CV concentration(75-250 mg/L), and flow rate(3-8) on the breakthrough curves for the continuous method is investigated. The result of CV adsorption onto GYP-A using the batch method indicates that the model fits Freundlich > Temkin > Langmuir > R-D, and R2 equal 0.9953, 0.9847, 0.9161, 0.7909 were obtained for isotherm model, respectively. A pseudo-second-order model (R2 = 0.9995-0.9997) is recommended to describe the adsorption kinetics. The Thomas and Yoon-Nelson models were analyzed to study the adsorption kinetics. The random forest model shows an excellent ability to predict the parameters involved in the CV adsorption process with appropriate accuracy and useable for large data, robust against noise; it can be very effective in selecting important variables.

Application of Tandem Dispersive Liquid-Liquid Microextraction as an Efficient Method for Preconcentration of Two Antidepressant Drugs in Real Samples Combined with High Performance Liquid Chromatography.

In the present work, tandem dispersive liquid-liquid microextraction (TDLLME) coupled with liquid chromatography was used for the determination of the two antidepressant drugs citalopram (CIT) and sertraline (SER) in complicated matrices. Indeed, the present approach was used to improve the suitability and appropriateness of the dispersive liquid-liquid microextraction (DLLME) method in complicated matrices. Firstly, 10 mL of the sample solution containing the two understudied drugs was extracted into an organic solvent (200 µL of 1,2-dichloromethane) using the DLLME method. Then the extracted analytes were back-extracted into 100 µL of an aqueous acceptor phase. The total extraction time of this method is about 6 min. To achieve the best efficiency for this method, efficient parameters like the kind and volume of the organic solvent and the effect of the ionic strength on the effectiveness of extraction were reviewed and improved. Under the optimized experimental conditions, TDLLME showed good linearity in the range of 100.0-7000.0 ng mL-1. The limits of detection were found to be 10.0 ng mL-1 for CIT and 2.0 ng mL-1 for SER. The relative standard deviation (RSD) is obtained in the range of 0.7-4.1%.

Individuals with Major Depressive Disorder Report High Scores of Insecure-Avoidant and Insecure-Anxious Attachment Styles, Dissociative Identity Symptoms, and Adult Traumatic Events.

OBJECTIVE: Individuals with major depressive disorder (MDD) report more issues in social interaction compared to the general population. Moreover, dimensions of dissociation are considered dysfunctional strategies to cope with adverse life events. In this regard, current symptoms of MDD could be associated with traumatic events that occurred in childhood and in adult life. Given this background, the aim of the present study was to explore the associations between attachment styles as a proxy of quality of social interaction, dimensions of dissociation, and childhood and adult traumatic life events among individuals with MDD. METHOD: A total of 300 individuals with MDD (mean age: 31.31 years; 58.7% female) took part in this study. They completed a series of questionnaires on sociodemographic information, attachment styles, dimensions of dissociation, and childhood and adult traumatic life events. RESULTS: Prevalence rates for attachment styles were as follows: anxious/ambivalent attachment style-71.7%; avoidant/dependent attachment style-13%; secure/close attachment style-15.3%. Compared to the general population, the participants reported higher prevalence rates of insecure attachment styles. Current symptoms of dissociation were associated with adult but not childhood traumatic life events. An anxious attachment style was associated with higher scores of dissociation. CONCLUSION: Psychotherapeutic treatment of individuals with MDD should consider the individuals' challenging attachment styles and their risk of dissociation. While it is important to consider both adult and childhood traumatic events, in this research, more recent trauma occurring in adulthood was associated with current symptoms of dissociation.

When Much Is Too Much-Compared to Light Exercisers, Heavy Exercisers Report More Mental Health Issues and Stress, but Less Sleep Complaints.

BACKGROUND: Physical inactivity has become a global somatic and mental health issue. To counterbalance, promoting regular physical activity appears plausible, above all among adults, where physical inactivity is particularly high. However, some, but sparse, research also indicates that excessive exercising might be associated with unfavorable mental health dimensions. Here, we tested the hypothesis that excessive exercising was associated with more mental health issues. To this end, we assessed mental health issues, stress, mental toughness, and sleep disturbances among heavy and light adult exercisers. METHODS: A total of 200 adults (mean age: 35 years; 62% females) took part in the study. Of those, 100 were heavy exercisers (18-22 h/week), and 100 were light exercisers (1-6 h/week). Participants completed questionnaires covering sociodemographic information, mental health issues, perceived stress, mental toughness, and sleep disturbances. RESULTS: Compared with light exercisers, heavy exercisers reported higher mental health issues, more stress, but also higher mental toughness scores and less sleep disturbances. Higher age, lower mental toughness scores, heavy exerciser-status, and more sleep disturbances predicted higher mental health complaints. CONCLUSIONS: Compared with light exercising, heavy exercising might be associated with more mental health issues. As such, it appears that the association between exercise frequency, intensity, and duration and psychological well-being might be related to an optimum point, but not to a maximum point. In a similar vein, heavily exercising athletes, their coaches, parents, and representatives of sports associations should get sensitized to possible adverse psychological effects of excessive physical activity patterns.

Using artificial neural network and multivariate calibration methods for simultaneous spectrophotometric analysis of Emtricitabine and Tenofovir alafenamide fumarate in pharmaceutical formulation of HIV drug.

Spectrophotometric analysis method based on artificial neural network (ANN), partial least squares regression (PLS) and principal component regression (PCR) models was proposed for the simultaneous determination of Emtricitabine (ETB) and Tenofovir alafenamide fumarate (TAF) in human immunodeficiency virus (HIV) drug. An artificial neural network consisting of two, five, and seven layers with 2,3,5,7, and 9 neurons was trained by applying a feed forward back-propagation learning. In this method, Levenberg-Marquardt (LM) and gradient descent with momentum and adaptive learning rate back propagation (GDX) algorithms were used. Statistical parameters indicated that the ability of LM was better than GDX algorithm. Also, root mean square error (RMSE) and recovery (%) of the PLS and PCR methods showed that PLS has worked better than PCR. The proposed models were compared to the high- performance liquid chromatography (HPLC) as a reference method. Furthermore, the obtained results of the one-way analysis of variance (ANOVA) test at the 95% confidence level represented that there was no significant difference between the proposed and reference methods.

Comparing opium tincture and methadone for medication-assisted treatment of patients with opioid use disorder: Protocol for a multicenter parallel group noninferiority double-blind randomized controlled trial.

OBJECTIVES: This is the first study to compare the safety and efficacy of opium tincture (OT) with methadone for treatment of opioid use disorder. METHODS: In this multicenter, double-blind, noninferiority controlled trial, a stratified sample of 204 participants with opioid use disorder were recruited from community outreach, drop-in centers, and triangular clinics. Participants were excluded in case of active participation in another treatment program for opioid use disorder, hypersensitivity to trial medications, pregnancy, and certain serious medical conditions. They were randomized to receive either OT or methadone with an allocation ratio of 1:1 using a patient-centered flexible dosing strategy. Eligible participants were followed for a period of 12 weeks. Primary outcome is the difference in percentage of patients retained in the treatment. Secondary outcomes are craving, withdrawal symptoms, physical health, mental health, quality of life, and severity of substance use problems, cognitive function, safety profile, cost-effectiveness, and participants' satisfaction. Both intention-to-treat and per-protocol analyses will be conducted. The Ethics Board of the University of British Columbia and Tehran University of Medical Sciences approved the study. (clinicaltrials.gov; NCT02502175). RESULTS: To be reported after final analysis. CONCLUSIONS: If shown to be effective, OT will diversify the options for medication-assisted treatment of opioid use disorder.

Application of linear and non-linear methods for modeling removal efficiency of textile dyes from aqueous solutions using magnetic Fe3O4 impregnated onto walnut shell.

The performance of the Nano-magnetite Fe3O4 impregnated onto walnut shell (Fe3O4-WNS), which possessed the adsorption features of walnut shell and the magnetic property of Fe3O4, was investigated for the elimination of the methyl violet and Rhodamine 6G from contaminated aqueous solutions. The effects of different experimental variables on the removal efficiency of the cited dyes were examined. Then these variables were used as the inputs to generate linear and non-linear models such as the multiple linear regression, random forest, and artificial neural network to predict the removal efficiency of these dye species at different experimental conditions. The validation studies of these models were performed using the test set, which was not present in the modeling procedure. It was found that ANN had a higher ability to predict the adsorption process under different experimental conditions, and could be applied for the development of an automated dye wastewater removal plant. Also the maximum adsorption capacity (qmax) indicated that the qmax value for Fe3O4-WNS for removal of cationic dyes was comparable or better than that for some reported adsorbents. Also it should be cited that exhausted Fe3O4-WNS was regenerated using dishwashing liquid, and reused for removal of the cited dye species from aqueous solutions.

Application of Ultrasound-Assisted Surfactant-Enhanced Emulsification Microextraction Based on Solidification of Floating Organic Droplets and High Performance Liquid Chromatography for Preconcentration and Determination of Alprazolam and Chlordiazepoxide in Human Serum Samples.

An improved microextraction method is proposed on the basis of ultrasound-assisted surfactant-enhanced emulsification and solidification of a floating organic droplet procedure combined with high performance liquid chromatography for the preconcentration and quantification of alprazolam (ALP) and chlordiazepoxide (CHL) present in a number of human serum samples. Several parameters affecting the extraction efficiency were investigated by the Plackett -Burman factorial design as the screening design. Then the response surface methodology based on the Box-Behnken design was used to optimize the effective parameters in the proposed procedure. The limits of detection for the proposed method were found to be 3.0 and 3.1 ng mL-1 for CHL and ALP, respectively. The calibration curves obtained for the method were linear in the ranges of 10.0-3,500.0 and 10.0-3,000.0 ng mL-1 for CHL and ALP, respectively, with a good determination coefficient. The recoveries of the drugs in the spiked human serum samples were above 93.0%. The developed method was successfully applied to the analysis of these studied drugs in human serum samples. The pre-treatment of the serum samples was performed using acetonitrile to remove the proteins. The proposed procedure was an accurate and reliable one for the determination and preconcentration of these drugs in blood samples.

Determination of Three Organochlorine Pesticides in Aqueous Samples by Solid-Phase Extraction Based on Natural Nano Diatomite in Packed Syringe Coupled to Gas Chromatography-Mass Spectrometry.

A rapid, simple, and sensitive technique is proposed based on a miniaturized solid-phase extraction method named mictroextraction in a packed syringe coupled with gas chromatography-mass spectrometry for the preconcentration and determination of three organochlorine pesticides. These include hexachlorobenzene, heptachlor and aldrine in aqueous samples. For the first time, the natural nano diatomite is used a sorbent. Based on this technique, 6.0 mg of the nano sorbent is inserted in a syringe between two polypropylene frits. The analytes would be adsorbed on the solid phase, and would subsequently be eluted using organic solvents. The influence of some important parameters, such as the solution pH, type and volume of the organic desorption solvent, and amount of sorbent on the extraction efficiency of the selected pesticides, is investigated. The proposed method shows good linearity in the range of 0.1 - 40.0 µg L-1, and at low limits of detection in the range of 0.02 - 0.13 µg L-1 using the selected ion-monitoring mode. The reproducibility of this method was found to be in the range of 3.5 - 11.1% for the understudied pesticides. In order to evaluate the matrix effect, the developed method is also applied to the preconcentration and determination of the selected pesticides in different water samples.

Investigation of the structural directing effect of (2-hydroxyethyl)trimethylammonium on distribution of the silicate anions using 29Si NMR spectroscopy.

The effect of (2-hydroxyethyl)trimethylammonium (2-HETMA) cation on the equilibrium of silicate oligomers in aqueous alkaline silicate solutions was investigated using (29)Si NMR spectra. The results indicate role of structural directing of 2-HETMA in which it particularly directs the silicate species to the Q(4)(1)Q(4)(3)Q(4)(4) silicate anion. Results reveal that composition of the alcohols in solution affect the distribution of anionic species. The effect of methanol concentration is also discussed.

Free variable selection QSPR study to predict (19)F chemical shifts of some fluorinated organic compounds using Random Forest and RBF-PLS methods.

In this work, two new and powerful chemometrics methods are applied for the modeling and prediction of the (19)F chemical shift values of some fluorinated organic compounds. The radial basis function-partial least square (RBF-PLS) and random forest (RF) are employed to construct the models to predict the (19)F chemical shifts. In this study, we didn't used from any variable selection method and RF method can be used as variable selection and modeling technique. Effects of the important parameters affecting the ability of the RF prediction power such as the number of trees (nt) and the number of randomly selected variables to split each node (m) were investigated. The root-mean-square errors of prediction (RMSEP) for the training set and the prediction set for the RBF-PLS and RF models were 44.70, 23.86, 29.77, and 23.69, respectively. Also, the correlation coefficients of the prediction set for the RBF-PLS and RF models were 0.8684 and 0.9313, respectively. The results obtained reveal that the RF model can be used as a powerful chemometrics tool for the quantitative structure-property relationship (QSPR) studies.

Application of a thin film of poly(solochrome black T) as a redox mediator for the electro-catalytic simultaneous determination of dopamine and acetaminophen in the pharmaceutical and biological samples.

Glassy carbon electrode was successfully modified with a thin film of poly(solochrome black T) and applied for the sensitive and selective voltammetric simultaneous determination of dopamine and acetaminophen. The preparation and basic electrochemical behavior of poly(solochrome black T) film on the glassy carbon electrode were investigated in details. The modified electrode with polymeric thin film exhibits excellent electro-catalytic activity toward the oxidation of dopamine and acetaminophen. The anodic peaks of the both species were well defined with lowered oxidation potential and enhanced oxidation peak currents. The modified electrode was used as a voltammetric sensor for sensitive simultaneous determination of dopamine and acetaminophen free from ascorbic acid and uric acid interferences. Under the optimum conditions, the detection limits were 0.092 and 0.142 µmol L(-1) for DA and AP, respectively. The proposed sensor has been successfully used in analysis of pharmaceutical and biological samples.

Selective spectrophotometric determination of periodate based on its reaction with methylene green and its application to indirect determination of ethylene glycol and glycerol.

A rapid, simple, accurate, and highly selective spectrophotometric method is proposed for the determination of periodate in water samples. This method is based on the reaction of methylene green with periodate in the presence of iodide. The decrease in the absorbance of methylene green is used to monitor the reaction spectrophotometrically at 613 nm. Under the optimum conditions, periodate could be determined in the concentration range 0.18-6.0 microg mL(-1). The detection limit for the method is 0.010 microg mL(-1). The influence of various foreign species was studied, and it was found that iodate did not interfere with the determination even in the presence of 200-fold of periodate. The relative standard deviations for six replicate determinations of 0.30, 0.50, 1.0, 1.5, 4.0, and 5.5 microg mL(-1) of periodate were 3.33, 2.0, 1.6, 1.33, 0.50, and 0.55%, respectively. The proposed method was applied to the determination of periodate in water samples and indirect determination of ethylene glycol in antifreeze and glycerol in vegetable oil via malaprade reaction, and satisfactory results were obtained.

Solvent microextraction-flame atomic absorption spectrometry (SME-FAAS) for determination of ultratrace amounts of cadmium in meat and fish samples.

A simple, low cost and highly sensitive method based on solvent microextraction (SME) for separation/preconcentration and flame atomic absorption spectrometry (FAAS) was proposed for the determination of ultratrace amounts of cadmium in meat and fish samples. The analytical procedure involved the formation of a hydrophobic complex by mixing the analyte solution with an ammonium pyrrolidinedithiocarbamate (APDC) solution. In suitable conditions, the complex of cadmium-APDC entered the micro organic phase, and thus, separation of the analyte from the matrix was achieved. Under optimal chemical and instrumental conditions, a detection limit (3 sigma) of 0.8 ng L(-1) and an enrichment factor of 93 were achieved. The relative standard deviation for the method was found to be 2.2% for Cd. The interference effects of some anions and cations were also investigated. The developed method has been applied to the determination of trace Cd in meat and fish samples.