Solvent-dependent formation kinetics of L,L-diphenylalanine micro/nanotubes.

Investigating the molecular mechanism underlying the aggregation process of amyloid fibers is of great importance both for its implications in several degenerative diseases and for the design of new materials based on self-assembly. In particular, micro/nanotubes of L,L-diphenylalanine have been investigated as a model of amyloid plaques in Alzheimer's disease and also for their broad range of physical properties, e.g., good thermo- and mechanical stability, semiconductivity, piezoelectricity and optical properties. It has been reported that the assembly/disassembly dynamics of L,L-diphenylalanine crystals is influenced by the solvent composition being triggered by evaporation of solvents. In fact the solvatomorphism of this peptide-based nanomaterial is complex and rich attracting great attention. Here we investigated the growing kinetics of the micro/nanotubes of L,L-diphenylalanine in samples prepared with toluene, ethanol, and acetic acid solvents by time-resolved Raman spectroscopy. Our results indicated that the self-assembly in this case competes with the water evaporation process contrary to what is reported by samples prepared with widely used solvent 1,1,1,3,3,3-hexafluoro-2-propanol. We note that exclusively tubular structures (being hollow for the toluene solvent case) were observed. Interestingly our results support the fact that for acetic acid, ethanol, and toluene the micro/nanotube formation process is autocatalytic instead of being nucleation-dominating as reported for samples prepared using solvent 1,1,1,3,3,3-hexafluoro-2-propanol.

Confined Water Dynamics in the Scaffolds of Polylactic Acid.

Resorbable polylactic acid (PLA) ultrathin fibers have been applied as scaffolds for tissue engineering applications due to their micro- and nanoporous structure that favor cell adhesion, besides inducing cell proliferation and upregulating gene expression related to tissue regeneration. Incorporation of multiwalled carbon nanotubes into PLA fibers has been reported to increase the mechanical properties of the scaffold, making them even more suitable for tissue engineering applications. Ideally, scaffolds should be degraded simultaneously with tissue growth. Hydration and swelling are factors related to scaffold degradation. Hydration would negatively impact the mechanical properties since PLA shows hydrolytic degradation. Water absorption critically affects the catalysis and allowance of the hydrolysis reactions. Moreover, either mass transport and chemical reactions are influenced by confined water, which is an unexplored subject for PLA micro- and nanoporous fibers. Here, we probe and investigate confined water onto highly porous PLA microfibers containing few amounts of incorporated carbon nanotubes by Fourier transform infrared (FTIR) spectroscopy. A hydrostatic pressure was applied to the fibers to enhance the intermolecular interactions between water molecules and C=O groups from polyester bonds, which were evaluated over the wavenumber between 1600 and 2000 cm-1. The analysis of temperature dependence of FTIR spectra indicated the presence of confined water which is characterized by a non-Arrhenius to Arrhenius crossover at T0 = 190 K for 1716 and 1817 cm-1 carbonyl bands of PLA. These bands are sensitive to a hydrogen bond network of confined water. The relevance of our finding relies on the challenge detecting confined water in hydrophobic cavities as in the PLA one. To the best of our knowledge, we present the first report referring the presence of confined water in a hydrophobic scaffold as PLA for tissue engineering. Our findings can provide new opportunities to understand the role of confined water in tissue engineering applications. For instance, we argue that PLA degradation may be affected the most by confined water. PLA degradation involves hydrolytic and enzymatic degradation reactions, which can both be sensitive to changes in water properties.

Multiplex coherent anti-Stokes Raman scattering microspectroscopy of brain tissue with higher ranking data classification for biomedical imaging.

Multiplex coherent anti-Stokes Raman scattering (MCARS) microscopy was carried out to map a solid tumor in mouse brain tissue. The border between normal and tumor tissue was visualized using support vector machines (SVM) as a higher ranking type of data classification. Training data were collected separately in both tissue types, and the image contrast is based on class affiliation of the single spectra. Color coding in the image generated by SVM is then related to pathological information instead of single spectral intensities or spectral differences within the data set. The results show good agreement with the H&E stained reference and spontaneous Raman microscopy, proving the validity of the MCARS approach in combination with SVM.