Various Methods for Removal, Treatment, and Detection of Emerging Water Contaminants

This review covers various methods to remove, treat, and detect emerging contaminants (ECs) in water and wastewater. ECs have drawn the attention of many countries due to their potential threat to human health as well as the environment. They are found in many human everyday products that are continuously released into the environment and will accumulate over time. In order to remove ECs, a number of methods have been developed, which include adsorption, membrane technology, biological treatment, and advanced oxidation process. In addition, advances in detection techniques and instrumentation are now able to detect ECs in which they occur at low concentrations. All the removal, treatment, and detection methods will be covered in this review. The removal, treatment, and detection of ECs and their transformation products in water and wastewater are challenging tasks due to their complexity in water samples. Therefore, such information should be emphasized in order to improve the current methods and develop new advanced methods

Formulation of herbal cream based on Ziziphus Mauritiana leaves extract and evaluation on physicochemical properties

Plant derived substances and herbal medicines have recently attracted the great interest towards their versatile application, as medicinal plants used in traditional and modern medicine. The aim of the current study was to investigate the antioxidant activity of Ziziphus mauritiana leaves extract followed with the formulation of herbal creams based on ZM methanolic extract then evaluate the physical characteristic and stability of the creams. After the methanolic extract was obtained by using Soxhlet extraction, the extract was assessed for antioxidant activity by using stable 2,2- Diphenyl-1-picrylhydrazyl (DPPH) which showed the IC50 value of the ZM extract is 10.57 µg/ml, while IC50 value for ascorbic acid is 4.19 µg/ml. Four formulations of water in oil (w/o) emulsion based cream was formulated based on Ziziphus mauritiana leaves extract which are F1, F2, F3 and F4. Several physical properties were evaluated such as organoleptic, pH, viscosity, homogeneity, washability and emmolliency which proved that all formulations have good homogeneity, non greasy and under suitable pH and viscosity. Based on thermal stability test (45 °C ± 70 % RH, for 48 hours), it showed that F4 is not stable at high temperature compared to other formulations. Therefore, the present study indicated that the Ziziphus mauritiana leaves extract has great potential for personal care product development

Direct Ionic Liquid Extractant Injection for Volatile Chemical Analysis - A Gas Chromatography Sampling Technique

A green sampling approach by direct injection of ionic liquid (IL) solvent containing a variety of analytes using programmable temperature vaporisation (PTV) injection with gas chromatography (GC) is presented. The method was developed using test mixtures of n-alkanes, n-alcohols and polyaromatic compounds, whilst back extraction of isolated compounds from the IL with organic solvent is not required. In the final method, 2 μL of IL, 1-butyl-3 methylimidazolium bis(trifluoromethylsulfonyl)amide containing analytes, was diluted to different volumes (ranging from 10 to 70%) with solvent then injected into the system. Several PTV injector parameters were investigated to ensure analyte volatilisation and transfer into the GC column. Concentration calibration curves (10–150 μg mL−1 and 10–100 μg mL−1 for n-alkanes and n-alcohols, respectively) were constructed, and showed addition of IL increased the peak area of each analyte, with good precision, and acceptable linearity with correlation coefficient, r2 > 0.93. This method was successfully applied in analysis of a polynuclear aromatic hydrocarbons (PAHs) mixture, with addition of IL in the mixture and suitable operation of the PTV injector. The method was also applied to eucalyptus leaf essential oil compounds as a test sample in a single drop microextraction experiment

The roles of acidity, peroxide and non-peroxide compounds in antibacterial properties of Malaysian Kelulut, Tualang and Acacia honey

In this study, three putative factors that commonly contribute to antibacterial properties in honey were determined, namely acidity (pH level), peroxide compounds and non-peroxide compounds. Methodology and results: Honey samples were prepared based on the known factors of acidity, peroxide compounds, and non-peroxide compounds to identify factors that contribute to the antibacterial properties of the honey based on agar diffusion assay. Liquid chromatography quadropole time-of-flight mass spectrometry was employed to detect and quantify the presence of acidic, peroxide, and non-peroxide compounds in the honey samples. Acidity and non-peroxide compounds were identified as the significant factors contributing to the antibacterial properties of Kelulut, Tualang and Acacia honey. No peroxide compound was detected in this study across all honey samples. In Kelulut, the presence of the additional compounds (reptoside, platycogenic acid and kauranoic acid) may explain its higher antibacterial properties against Escherichia coli and Staphylococcus aureus as compared to Tualang and Acacia honey based on the inhibition zones on the agar plates. Conclusion, significance and impact of study: The presence of multiple antibacterial factors in honey is notably important as it gives an advantage of using honey compared to antibiotics in preventing the growth of a wide range of bacterial species with multiple modes of action

Prediction of blood-brain barrier permeability of compounds by machine learning algorithms

In the drug development for the Central Nervous System (CNS), the discovery of the compounds that can pass through the brain across the Blood-Brain Barrier (BBB) is the most challenging assessment. Almost 98% of small molecules are unable to permeate BBB, reducing the pharmacokinetics of the drugs in the CNS by affecting its absorption, distribution, metabolism, and excretion (ADME) mechanisms. Since the CNS is often inaccessible to many complex procedures and performing in-vitro permeability studies for thousands of compounds can be laborious, attempts were made to predict the permeation of compounds through BBB by implementing the Machine Learning (ML) approach. In this work, using the KNIME Analytics platform, 4 predictive models were developed with 4 ML algorithms followed by a ten-fold cross-validation approach to predict the external validation set. Among 4 ML algorithms, Extreme Gradient Boosting (XGBoost) overperformed in BBB permeability prediction and was chosen as the prediction model for deployment. Data pre-processing and feature selection enhanced the prediction of the model. Overall, the model achieved 86.7% and 88.5% of accuracy and 0.843 and 0.927 AUC, respectively in the training set and external validation set, proving that the model with high stability in prediction

Analysis of phenolic and flavonoid compounds in Malaysia propolis extracts by LC-Q-TOFMS

Propolis is a natural bee product which is resinous sticky wax (bee glue) that synthesized by the stingless bees from the mixtures of exudates of plants and bee enzymes. The chemical compounds of propolis mainly consists of phenolic acids and flavonoids. Since propolis has been consumed for ages as a traditional medicine and research on the Malaysia propolis is still lacking, this study was conducted. Therefore, propolis was 1 extracted by Soxhlet Extraction (using two different solvents) and 2 determined their chemical profiling by using LC-QTOFMS which 3 focusing on potential API that can be used in pharmaceutical product

In-vitro drug release studies of chitosan-alginate nanoparticles loaded with non-volatile extracts of cymbopogon species

The conventional topical dosage forms have plenty of drawbacks which cause patient inconveniences as well as treatment failure. To overcome these complications, drug design engineering is emphasizing on nanoparticle technology for its better drug carrier activity and targeted delivery in desired site of body. The objective of this study was to develop and evaluate topical formulation containing chitosan-alginate nanoparticles loaded with non-volatile extracts of Cymbopogon species. Among all of the test samples, nanoparticles loaded with 6 mg of extraction exhibited best entrapment capacity. This formulation successfully captured around 36.56% drug in nanoparticles. Thermo Gravimetric Analysis also showed thermal stability of the drug loaded nanoparticles. Furthermore, the formulation of nano cream that contained 6 mg of Cymbopogon sp. nanoparticles yielded the smallest nano-cream, with a particle size of 157.3 ± 20.80 nm. Using the basket dialysis approach, nanoparticle formulations loaded with 12 mg and 24 mg extracts showed a release rate of roughly 25%. On the other hand, the dialysis bag approach revealed that the drug released from the 24 mg of Cymbopogon sp. loaded in nanoparticles was about 37%. Lastly, the antioxidant study's findings indicate that cream-loaded nanoparticles containing 6 mg might be capable of scavenging radicals, with an IC50 value of 19.411g/ml. Chitosan-alginate nanoparticles loaded with Cymbopogon species exhibited significant drug release and antioxidant activity, indicating that this method could be useful for the formulation development of nanoparticles for skincare products

A Comparison of Assays for Accurate Copy Number Measurement of the Low-Affinity Fc Gamma Receptor Genes FCGR3A and FCGR3B

The FCGR3 locus encoding the low affinity activating receptor FcγRIII, plays a vital role in immunity triggered by cellular effector and regulatory functions. Copy number of the genes FCGR3A and FCGR3B has previously been reported to affect susceptibility to several autoimmune diseases and chronic inflammatory conditions. However, such genetic association studies often yield inconsistent results; hence require assays that are robust with low error rate. We investigated the accuracy and efficiency in estimating FCGR3 CNV by comparing Sequenom MassARRAY and paralogue ratio test-restriction enzyme digest variant ratio (RT-REDVR). In addition, since many genetic association studies of FCGR3B CNV were carried out using real-time quantitative PCR, we have also included the evaluation of that method’s performance in estimating the multi-allelic CNV of FCGR3B. The qPCR assay exhibited a considerably broader distribution of signal intensity, potentially introducing error in estimation of copy number and higher false positive rates. Both Sequenom and PRT-REDVR showed lesser systematic bias, but Sequenom skewed towards copy number normal (CN = 2). The discrepancy between Sequenom and PRT-REDVR might be attributed either to batch effects noise in individual measurements. Our study suggests that PRT-REDVR is more robust and accurate in genotyping the CNV of FCGR3, but highlights the needs of multiple independent assays for extensive validation when performing a genetic association study with multi-allelic CNVs

Application of dispersive liquid-liquid microextraction based on solidification of floating organic droplet in the analysis of anti-depressant drugs

A new simple and rapid sample preparation method based on dispersive liquid-liquid microextraction-solidification of floating organic drop (DLLME-SFO) combined with gas chromatograph-mass spectrometry (GC-MS) has been developed for the extraction and analysis of anti-depressant drugs in water samples. The DLLME-SFO method uses organic solvent with low density and less toxicity. In the method, the disperser solvent (0.5 mL acetonitrile) containing 30 tL n-hexadecane was rapidly injected by a syringe into the 5.0 mL water in a glass tube. Upon centrifugation for 7 min at 3500 rpm, the glass tube was transferred into a beaker containing crushed ice for cooling step. After 5 mm, the solidified n-hexadecane solvent was transferred into a conical vial, where its melts quickly at room temperature and 2 L of it is injected into a gas chromatograph for analysis. Several DLLME-SFO parameters were optimized, including the type and volume of the extraction solvent and disperser solvent, extraction time and salt effect. Under optimum conditions, the method showed good linearity in the range of 0.04 to 0.12 pg/mL for amitriptyline and chlorpromazine, with correlation of determination (r) in the range of 0.992 to 0.995. The limits of detections (LODs) were in the range 0.0085 to 0.0285 igImL. The extraction recoveries of amitriptyline and chlorpromazine from water samples at spiking level of 0.08 tg!mL were 71.34 to 73.52% and 73.83 to 91.09%, respectively. The relative standard deviations (RSDs) were in the range of 4.97 to 6.85% for amitriptyline and 4.84 to 7.49% for chlorpromazine. The method was successfully applied to the determination of antidepressant drugs in drinking water, lake water and tap water samples

Application of dipersive liquid-liquid microextraction based on solidification of floating organic droplet in the analysis of anti depressant drugs

A new simple and rapid sample preparation method based on dispersive liquid-liquid microextraction-solidification of floating organic drop (DLLME-SFO) combined with gas chromatograph-mass spectrometry (GC-MS) has been developed for the extraction and analysis of anti-depressant drugs in water samples. The DLLME-SFO method uses organic solvent with low density and less toxicity. In the method, the disperser solvent (0.5 mL acetonitrile) containing 30 tL n-hexadecane was rapidly injected by a syringe into the 5.0 mL water in a glass tube. Upon centrifugation for 7 min at 3500 rpm, the glass tube was transferred into a beaker containing crushed ice for cooling step. After 5 mm, the solidified n-hexadecane solvent was transferred into a conical vial, where its melts quickly at room temperature and 2 L of it is injected into a gas chromatograph for analysis. Several DLLME-SFO parameters were optimized, including the type and volume of the extraction solvent and disperser solvent, extraction time and salt effect. Under optimum conditions, the method showed good linearity in the range of 0.04 to 0.12 pg/mL for amitriptyline and chlorpromazine, with correlation of determination (r) in the range of 0.992 to 0.995. The limits of detections (LODs) were in the range 0.0085 to 0.0285 igImL. The extraction recoveries of amitriptyline and chlorpromazine from water samples at spiking level of 0.08 tg!mL were 71.34 to 73.52% and 73.83 to 91.09%, respectively. The relative standard deviations (RSDs) were in the range of 4.97 to 6.85% for amitriptyline and 4.84 to 7.49% for chlorpromazine. The method was successfully applied to the determination of antidepressant drugs in drinking water, lake water and tap water samples