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Drug delivery technology is still a dynamically developing field of medicine. The main direction in nanotechnology research (nanocarriers, nanovehicles, etc.) is efficient drug delivery to target cells with simultaneous drug reduction concentration. However, nanotechnology trends in reducing the carrier sizes to several nanometers limit the volume of the loaded substance and may pose a danger of uncontrolled access into the cells. On the other hand, nanoparticles larger than 200 nm in diameter have difficulties to undergo rapid diffusional transport through cell membranes. The main advantage of large nanoparticles is higher drug encapsulation efficiency and the ability to deliver a wider array of drugs. Our present study contributes a new approach with large Tween 80 solid lipid nanoparticles SLN (i.e., hydrodynamic GM-SLN—glycerol monostearate, GM, as the lipid and ATO5-SLNs—glyceryl palmitostearate, ATO5, as the lipid) with diameters DH of 379.4 nm and 547 nm, respectively. They are used as drug carriers alone and in combination with electroporation (EP) induced by millisecond pulsed electric fields. We evaluate if EP can support the transport of large nanocarriers into cells. The study was performed with two cell lines: human colon adenocarcinoma LoVo and hamster ovarian fibroblastoid CHO-K1 with coumarin 6 (C6) as a fluorescent marker for encapsulation. The biological safety of the potential treatment procedure was evaluated with cell viability after their exposure to nanoparticles and EP. The EP efficacy was evaluated by FACS method. The impact on intracellular structure organization of cytoskeleton was visualized by CLSM method with alpha-actin and beta-tubulin. The obtained results indicate low cytotoxicity of both carrier types, free and loaded with C6. The evaluation of cytoskeleton proteins indicated no intracellular structure damage. The intracellular uptake and accumulation show that SLNs do not support transport of C6 coumarin. Only application of electroporation improved the transport of encapsulated and free C6 into both treated cell lines.Electronic supplementary materialThe online version of this article (doi:10.1007/s00232-016-9906-1) contains supplementary material, which is available to authorized users.

These days identification of a person is an integral part of many computer-based solutions. It is a key characteristic for access control, customized services, and a proof of identity. Over the last couple of decades, many new techniques were introduced for how to identify human faces. This approach investigates the human face identification based on frontal images by producing ratios from distances between the different features and their locations. Moreover, this extended version includes an investigation of identification based on side profile by extracting and diagnosing the feature sets with geometric ratio expressions which are calculated into feature vectors. The last stage involves using weighted means to calculate the resemblance. The approach considers an explainable Artificial Intelligence (XAI) approach. Findings, based on a small dataset, achieve that the used approach offers promising results. Further research could have a great influence on how faces and face-profiles can be identified. Performance of the proposed system is validated using metrics such as Precision, False Acceptance Rate, False Rejection Rate, and True Positive Rate. Multiple simulations indicate an Equal Error Rate of 0.89. This work is an extended version of the paper submitted in ACIIDS 2020.