Neuro-genetic multioptimization of the determination of polychlorinated biphenyl congeners in human milk by headspace solid phase microextraction coupled to gas chromatography with electron capture detection

Determination of Polychlorinated Biphenyls in Water Samples Using a Needle Trap Device Combined with Gas Chromatography

In this study, a fiber-packed needle trap device (NTD) was developed by packing heat-resistant fibers with a polyethylene glycol sol-gel coating into a 21-gauge, stainless steel needle. The polyethylene glycol sol-gel coating has numerous advantages, including uniform roughness and a large specific surface area. The prepared NTD was used for headspace extraction of five polychlorinated biphenyls (PCBs) in water samples, determined by gas chromatography with a flame ionization detector (GC-FID). The main experimental parameters, including the extraction and desorption conditions, ionic strength, and fiber bundles, were investigated to improve the extraction efficiency. After optimization, satisfactory linearity (r > 0.99) in the concentration range of 0.02–500 μg/L was obtained, and the enrichment factor of NTD for the five PCBs was between 1150 and 9537 times. The limit of detection (S/N = 3) of five PCBs were measured in ranges of 0.0021–0.01 μg/L. Furthermore, the fiber-packed NTD has excellent durability, and can be reused for 60 cycles. After being stored at room temperature for three days, the storage ability of the NTD had a loss of PCBs less than 10%, and the relative standard deviation (RSD) was less than 10%. When analyzing the PCBs in real water samples, good accuracies (spiked recoveries were in the range of 92.19–98.56%) and precision (the RSD was lower than 12.8%) was obtained.

Doehlert design in the optimization of procedures aiming food analysis - A review

In the present paper is presented a review on the application of Doehlert design in the optimization of some of the steps of analytical procedures aimed the analysis of food samples. The theoretical principles and the main characteristics of this type of design are described. In addition, the main advantages and limitations of Doehlert design over other designs (Central Composite Design and Box-Behnken) and its application in the area of food analysis are discussed. Finally, to illustrate its potential, some examples of Doehlert design application in other areas of food chemistry without the purpose of analytical determination will be briefly presented.

Quantification of Volatile Compounds in Wines by HS-SPME-GC/MS: Critical Issues and Use of Multivariate Statistics in Method Optimization

The aim of this review is to explore and discuss the two main aspects related to a HeadSpace Solid Phase Micro-Extraction Gas-Chromatography/Mass-Spectrometry (HS-SPME-GC/MS) quantitative analysis of volatile compounds in wines, both being fundamental to obtain reliable data. In the first section, recent advances in the use of multivariate optimization approaches during the method development step are described with a special focus on factorial designs and response surface methodologies. In the second section, critical aspects related to quantification methods are discussed. Indeed, matrix effects induced by the complexity of the volatile profile and of the non-volatile matrix of wines, potentially differing between diverse wines in a remarkable extent, often require severe assumptions if a reliable quantification is desired. Several approaches offering different levels of data reliability including internal standards, model wine calibration, a stable isotope dilution analysis, matrix-matched calibration and standard addition methods are reported in the literature and are discussed in depth here.

Polychlorinated biphenyls (PCBs) residues in commercial pasteurized cows' milk in Tehran, Iran

BACKGROUND

To date, despite the facts that pasteurized milk is the most consumed dairy product in Iran and its consumption has increased almost two fold during the last 10 years, no data are available concerning the concentrations of polychlorinated biphenyls (PCBs) in commercial cow milk in Iran market.

METHODS

This study designed to determine the levels of PCBs in these products and to assess population exposure to PCBs by estimating the daily intakes. Pasteurized cows' milk samples (10 brands) were collected from local markets at two different seasons and analyzed using sensitive and reliable methods.

RESULTS

Based on the results all the indicator PCBs were detected and quantified in all of the samples, the mean ± SD concentration for the sum of the six congeners was 18.92 ± 14.36 ng g^-1 fat. None of the samples surpassed the provisional value established by the EU of 40 ng g^-1 fat. The sum of dioxin-like congeners, expressed as WHO-TEQ was 0.492 pg/g of fat which was considerably lower than the defined limit 3 pg/g fat, set for cow's milk. Furthermore, a similar DL-PCBs profile as other studies was found for analyzed samples. The results indicated that concentrations of DL-PCBs were very low, and all of milk samples were compliant with EC legislation. In addition, seasonal variations were not observed for DL- and NDL-PCBs levels (p values >0.05).

CONCLUSIONS

The estimated dietary intake for target population was 0.06 pg TEQ/kg of body weight/day, much smaller than the amounts declared by the World Health Organization as tolerable daily intake.

Switching neuronal state: optimal stimuli revealed using a stochastically-seeded gradient algorithm

Inducing a switch in neuronal state using energy optimal stimuli is relevant to a variety of problems in neuroscience. Analytical techniques from optimal control theory can identify such stimuli; however, solutions to the optimization problem using indirect variational approaches can be elusive in models that describe neuronal behavior. Here we develop and apply a direct gradient-based optimization algorithm to find stimulus waveforms that elicit a change in neuronal state while minimizing energy usage. We analyze standard models of neuronal behavior, the Hodgkin-Huxley and FitzHugh-Nagumo models, to show that the gradient-based algorithm: (1) enables automated exploration of a wide solution space, using stochastically generated initial waveforms that converge to multiple locally optimal solutions; and (2) finds optimal stimulus waveforms that achieve a physiological outcome condition, without a priori knowledge of the optimal terminal condition of all state variables. Analysis of biological systems using stochastically-seeded gradient methods can reveal salient dynamical mechanisms underlying the optimal control of system behavior. The gradient algorithm may also have practical applications in future work, for example, finding energy optimal waveforms for therapeutic neural stimulation that minimizes power usage and diminishes off-target effects and damage to neighboring tissue.

Determination of polychlorinated biphenyls in ocean water and bovine milk using crosslinked polymeric ionic liquid sorbent coatings by solid-phase microextraction

Crosslinked polymeric ionic liquid (PIL)-based sorbent coatings were employed in the extraction of 21 polychlorinated biphenyls (PCBs) from ocean water and bovine milk using solid-phase microextraction (SPME). The extraction temperature, time, and concentration of sodium chloride added to the matrix were optimized in order to determine the best extraction conditions for the extraction of PCBs. The analytical performance of the crosslinked PIL-based SPME fibers was compared with a commercial 7 µm polydimethylsiloxane (PDMS) fiber using gas chromatography (GC) employing an electron capture detector (ECD) and mass spectrometric detection (MS). Higher sensitivities for PCBs were achieved using PIL-based fibers when compared to PDMS fiber due to the incorporation of benzyl moieties into the PIL structures. The limits of detection (LOD) for all PCBs were determined to be in the low ng L(-1) range using the three studied coatings. Recovery studies were performed for PCBs in ocean water and bovine milk to validate the applicability of the current SPME method.

Application of Kohonen neural network for evaluation of the contamination of Brazilian breast milk with polychlorinated biphenyls

Due to the tendency of polychlorinated biphenyls (PCB) to accumulate in matrixes with high lipid content, the contamination of the breast milk with these compounds is a serious issue, mainly to the newborn. In this study, milk samples were collected from breastfeeding mothers belonging to 4 Brazilian regions (south, southeast, northeast and north). Twelve PCB were analyzed by HS-SPME-GC-ECD and the corresponding peak areas were correlated to the answers to a questionnaire of general habits, breastfeeding and characteristics of the living places. To realize this exploratory analyze, self-organizing maps generated applying Kohonen neural network were applied. It was possible to verify the occurrence of different PCB congeners in the breast milk relating to the region of the Brazil that the breastfeeding lives, the proximity to an industry, the proximity to a contaminated river or sea, the type of milk (colostrum, foremilk and hindmilk) and the number of past pregnancies.

Headspace microextraction: recent bioanalytical applications and issues

Headspace microextraction has already been established as the method of choice for analyzing volatiles blended in complex matrices, such as environmental, food and biological samples. The modern trend of analytical chemistry for ‘going small’ has led to the successful development of various sorbing materials and microextraction techniques. As it is anticipated, microextraction is usually combined with powerful separation and optical techniques permitting enhanced recoveries of analytes, selectivity and sensitivity. In addition, derivatization reactions are often employed for improved detectability of several classes of compounds. Volatile compounds of biological significance are key substances due to the fact that they may constitute a characteristic of the status of the organism. A closer look at the biological applications of the headspace microextraction techniques (solid-phase and single drop microextraction) is the primary aim of this review. The variability of biological samples and analytes are considered primarily, while derivatization and optimization strategies are also discussed.