Mike De Vrieze

Chemical profiling of the major components in natural waxes to elucidate their role in liquid oil structuring

Elucidating the composition of waxes is of utmost importance to explain their behavior in liquid oil structuring. The chemical components (hydrocarbons - HCs, free fatty acids - FFAs, free fatty alcohols - FALs and wax esters - WEs) of natural waxes were analyzed using HPLC-ELSD and GC-MS followed by evaluation of their oil structuring properties. The gel strength, including the average storage modulus and oscillation yield stress, displayed a negative correlation with FALs and a positive correlation with HCs, FFAs and WEs. The components dictating the gel strength are HCs, FFAs and WEs in a descending order of importance. The consistency of the oleogels increased with the increasing amount of FFAs and HCs and the decreasing amount of WEs and FALs. The presence of more WEs results in a strong but brittle gel with a high initial flow yield stress. We believe these results might be useful in selecting the right waxes to combine in certain fat-based food products.

In vitro prediction of human intestinal absorption and blood–brain barrier partitioning: development of a lipid analog for micellar liquid chromatography

Over the past decades, several in vitro methods have been tested for their ability to predict either human intestinal absorption (HIA) or penetration across the blood–brain barrier (BBB) of drugs. Micellar liquid chromatography (MLC) has been a successful approach for retention time measurements of drugs to establish models together with other molecular descriptors. Thus far, MLC approaches have only made use of commercial surfactants such as sodium dodecyl sulfate (SDS) and polyoxyethylene (23) lauryl ether (Brij35), which are not representative for the phospholipids present in human membranes. Miltefosine, a phosphocholine-based lipid, is presented here as an alternative surfactant for MLC measurements. By using the obtained retention factors and several computed descriptors for a set of 48 compounds, two models were constructed: one for the prediction of HIA and another for the prediction of penetration across the BBB expressed as log BB. All data were correlated to experimental HIA and log BB values, and the performance of the models was evaluated. Log BB prediction performed better than HIA prediction, although HIA prediction was also improved a lot (from 0.5530 to 0.7175) compared to in silico predicted HIA values.

Evaluation of sphingomyelin, cholester, and phosphatidylcholine-based immobilized artificial membrane liquid chromatography to predict drug penetration across the blood-brain barrier

AbstractOver the past decades, several in vitro methods have been tested for their ability to predict drug penetration across the blood-brain barrier. So far, in high-performance liquid chromatography, most attention has been paid to micellar liquid chromatography and immobilized artificial membrane (IAM) LC. IAMLC has been described as a viable approach, since the stationary phase emulates the lipid environment of a cell membrane. However, research in IAMLC has almost exclusively been limited to phosphatidylcholine (PC)-based stationary phases, even though PC is only one of the lipids present in cell membranes. In this article, sphingomyelin and cholester stationary phases have been tested for the first time towards their ability to predict drug penetration across the blood-brain barrier. Upon comparison with the PC stationary phase, the sphingomyelin- and cholester-based columns depict similar predictive performance. Combining data from the different stationary phases did not lead to improvements of the models. FigureSchematic representation of how IAM-LC is used to predict drug penetration across the blood-brain barrier.

Model-based determination of the influence of textile fabric on bioassay analysis and the effectiveness of a textile slow-release system of DEET in mosquito control

BACKGROUND Determining the effectiveness of a product in repelling mosquitoes or other flying insects is a difficult task. One approach is to use a bioassay with textile fabric. We investigated the role of the textile substrate in a bioassay with a numerical model, and compared the outcome with known results for DEET. The model was then used to determine the effectiveness of textile slow-release formulations based on coatings, and results were compared with those of a field study in the Cameroon. Slow-release formulations are difficult to evaluate with standard tests, as the compound needs a build-up time not present in these tests. RESULTS We found excellent correspondence between the model and the known DEET results without matching parameters. Slow-release approaches are deemed possible but have several drawbacks. Modelling can help in identifying optimal use conditions. The field test with a slow-release system performed better than anticipated by the model, with initially more than 90% repellency. DEET-coated textile was considered not to be marketable, however. CONCLUSION We advise that bioassays characterise in more detail the type of textile fabric used so as to allow conclusions to be drawn by textile modelling. As regards coated-textile slow-release systems, more research is needed. We nevertheless advise usage mainly at entry points, e.g. as scrims.