We present a study of the optical second-order nonlinearity of type I collagen fibers grown in vitro via second harmonic generation (SHG) experiments and analyze the observed polarization-resolved SHG signal using previously reported SHG analytical expressions obtained for anisotropic tissue. Our results indicate that the effective second-order nonlinearity measured in the grown fibers is one order of magnitude lower than that of native collagen fibers. This is attributed to the formation of loose and dispersive fibrillar networks of thinner collagen fibrils that constitute the reassembled collagen fibers. This is confirmed by scanning electronic microscopy (SEM) imaging and the polarization dependence of the SHG signal. The measured values of the anisotropy parameter ρ of the reassembled collagen fibers are found to be similar to that obtained for native fibers on the relevant sub-µm scale.

In the present study, poly(ethylene glycol)-b-poly(N,N-diethylaminoethyl methacrylate) (PEG-b-PDEAEM) amphiphilic block copolymers were synthetized by reversible addition-fragmentation chain transfer (RAFT) polymerization using two different macro chain transfer agents containing PEG of 2000 and 5000 g/mol and varying the length of the PDEAEM segment. From the obtained block copolymers, polymersome type nanometric aggregates were obtained by two different techniques. By direct dispersion, particle diameters around 200 nm were obtained, while by solvent exchange using THF and water, the obtained diameters were around 100 nm. These block copolymers were used to encapsulate gold nanorods and doxorubicin (DOX) with good efficiencies to obtain nanomaterials with potential use as dual stimuli-sensitive drug delivery systems for combined anticancer therapies. Drug delivery studies showed that the release rate of DOX was accelerated when the pH was lowered from 7.4 to 5.8 and also when the systems were irradiated with a NIR laser at pH 7.4. The combination of lower pH and near infrared (NIR) irradiation resulted in higher drug release only in the case of polymersomes with lower molecular weight PEG.

Dual-function nanogels (particle size from 98 to 224 nm) synthesized via surfactant-free emulsion polymerization (SFEP) were tested as smart carriers toward synergistic chemo- and photothermal therapy. Cisplatin (CDDP) or doxorubicin (DOX) and gold nanorods (GNRDs) were loaded into galacto-functionalized PNVCL-based nanogels, where the encapsulation efficiency for CDDP and DOX was around 64 and 52%, respectively. PNVCL-based nanogels were proven to be an efficient delivery vehicle under conditions that mimic the tumor site in vitro. The release of CDDP or DOX was slower at pH 7.4 and 37 °C than at tumor conditions of pH 6 and 40 °C. On the other hand, in the systems with GNRDs at pH 7.4 and 37 °C, the sample was irradiated with a 785 nm laser for 10 min every hour, obtaining that the release profiles were even higher than in the conditions that simulated a cancer tissue (without irradiation). Thus, the present study demonstrates the synergistic effect of chemo- and photothermal therapy as a promising dual function in the potential future use of PNVCL nanogels loaded with GNRDs and CDDP/DOX to achieve an enhanced chemo/phototherapy in vivo.

Cortical dysplasias are alterations in the organization of the layers of the brain cortex due to problems in neuronal migration during development. The neuronal component has been widely studied in experimental models of cortical dysplasias. In contrast, little is known about how glia are affected. In the cerebellum, Bergmann glia (BG) are essential for neuronal migration during development, and in adult they mediate the control of fine movements through glutamatergic transmission. The aim of this study was to characterize the morphology and intracellular calcium dynamics of BG and astrocytes from mouse cerebellum and their modifications in a model of cortical dysplasia induced by carmustine (BCNU). Carmustine-treated mice were affected in their motor coordination and balance. Cerebellar dysplasias and heterotopias were more frequently found in lobule X. Morphology of BG cells and astrocytes was affected, as were their spontaneous [Ca²⁺]ⁱ transients in slice preparation and in vitro.

We present a combination of light-sheet excitation and two-dimensional fluorescence intensity ratio (FIR) measurements as a simple and promising technique for three-dimensional temperature mapping. The feasibility of this approach is demonstrated with samples fabricated with sodium yttrium fluoride nanoparticles co-doped with rare-earth ytterbium and erbium ions (NaYF₄:Yb³⁺/Er³⁺) incorporated into polydimethylsiloxane (PDMS) as a host material. In addition, we also evaluate the technique using lipid-coated NaYF₄:Yb³⁺/Er³⁺ nanoparticles immersed in agar. The composite materials show upconverted (UC) fluorescence bands when excited by a 980 nm near-infrared laser light-sheet. Using a single CMOS camera and a pair of interferometric optical filters to specifically image the two thermally-coupled bands (at 525 and 550 nm), the two-dimensional FIR and, hence, the temperature map can be readily obtained. The proposed method can take optically sectioned (confocal-like) images with good optical resolution over relatively large samples (up to the millimetric scale) for further 3D temperature reconstruction.

The implementation of embedded systems for myoelectric signal classification is key to the development of prosthetic and other real-time assistive technologies. This work presents a hand gesture classification system based on an artificial neural network (ANN) deployed on an ESP32 microcontroller. In contrast to approaches that require multiple acquisition channels or complex configurations, the proposed system uses a single surface electromyography (sEMG) channel, reducing cost and complexity. Data were collected from eight participants performing eight hand and wrist gestures. The system achieved classification accuracies of up to 93.05% for six gestures, including rest. Furthermore, the ESP32 implementation demonstrated inference times compatible with real-time operation, achieving an average inference time of 0.17 ms. When using a majority voting strategy, classification accuracy increased to 99%, confirming the feasibility of implementing efficient and accurate gesture recognition on low-cost embedded hardware. These results support its integration into portable and autonomous systems for prosthetic control and other interactive applications.