Dehydrodipeptide hydrogelators containing naproxen N‑Capped tryptophan: self-assembly, hydrogel characterization, and evaluation as potential drug nanocarriers

In this work, we introduce dipeptides containing tryptophan N-capped with the nonsteroidal anti-inflammatory drug naproxen and C-terminal dehydroamino acids, dehydrophenylalanine (ΔPhe), dehydroaminobutyric acid (ΔAbu), and dehydroalanine (ΔAla) as efficacious protease resistant hydrogelators. Optimized conditions for gel formation are reported. Transmission electron microscopy experiments revealed that the hydrogels consist of networks of micro/nanosized fibers formed by peptide self-assembly. Fluorescence and circular dichroism spectroscopy indicate that the self-assembly process is driven by stacking interactions of the aromatic groups. The naphthalene groups of the naproxen moieties are highly organized in the fibers through chiral stacking. Rheological experiments demonstrated that the most hydrophobic peptide (containing C-terminal ΔPhe) formed more elastic gels at lower critical gelation concentrations. This gel revealed irreversible breakup, while the C-terminal ΔAbu and ΔAla gels, although less elastic, exhibited structural recovery and partial healing of the elastic properties. A potential antitumor thieno[3,2-b]pyridine derivative was incorporated (noncovalently) into the gel formed by the hydrogelator containing C-terminal ΔPhe residue. Fluorescence and Förster resonance energy transfer measurements indicate that the drug is located in a hydrophobic environment, near/associated with the peptide fibers, establishing this type of hydrogel as a good drug-nanocarrier candidate.

An optimized reverse-phase high performance liquid chromatographic method for evaluating percutaneous absorption of glucosamine hydrochloride

A relatively simple, selective, precise and accurate high performance liquid chromatography (HPLC) method based on a reaction of phenylisothiocyanate (PITC) with glucosamine (GL) in alkaline media was developed and validated to determine glucosamine hydrochloride permeating through human skin in vitro. It is usually problematic to develop an accurate assay for chemicals traversing skin because the excellent barrier properties of the tissue ensure that only low amounts of the material pass through the membrane and skin components may leach out of the tissue to interfere with the analysis. In addition, in the case of glucosamine hydrochloride, chemical instability adds further complexity to assay development. The assay, utilising the PITC-GL reaction was refined by optimizing the reaction temperature, reaction time and PITC concentration. The reaction produces a phenylthiocarbarnyl-glucosamine (PTC-GL) adduct which was separated on a reverse-phase (RP) column packed with 5 mu m ODS (C-18) Hypersil particles using a diode array detector (DAD) at 245 nm. The mobile phase was methanol-water-glacial acetic acid (10:89.96:0.04 v/v/v, pH 3.5) delivered to the column at 1 ml min(-1) and the column temperature was maintained at 30 degrees C Using a saturated aqueous solution of glucosamine hydrochloride, in vitro permeation studies were performed at 32 +/- 1 degrees C over 48 h using human epidermal membranes prepared by a heat separation method and mounted in Franz-type diffusion cells with a diffusional area 2.15 +/- 0.1 cm(2). The optimum derivatisation reaction conditions for reaction temperature, reaction time and PITC concentration were found to be 80 degrees C, 30 min and 1 % v/v, respectively. PTC-Gal and GL adducts eluted at 8.9 and 9.7 min, respectively. The detector response was found to be linear in the concentration range 0-1000 mu g ml(-1). The assay was robust with intra- and inter-day precisions (described as a percentage of relative standard deviation, %R.S.D.) < 12. Intra- and inter-day accuracy (as a percentage of the relative error, %RE) was <=-5.60 and <=-8.00, respectively. Using this assay, it was found that GL-HCI permeates through human skin with a flux 1.497 +/- 0.42 mu g cm(-2) h(-1), a permeability coefficient of 5.66 +/- 1.6 x 10(-6) cm h(-1) and with a lag time of 10.9 +/- 4.6 h. (c) 2005 Elsevier B.V. All rights reserved.

An optimized ERP brain–computer interface based on facial expression changes

Objective. Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain–computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. Approach. Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. Main results. The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). Significance. The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.

An optimized ERP Brain-computer interface based on facial expression changes

OBJECTIVE: Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain-computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. APPROACH: Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. MAIN RESULTS: The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). SIGNIFICANCE: The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.