Integrating Porous Silicon Nanoneedles within Medical Devices for Nucleic Acid Nanoinjection.

Porous silicon nanoneedles can interface with cells and tissues with minimal perturbation for high-throughput intracellular delivery and biosensing. Typically, nanoneedle devices are rigid, flat, and opaque, which limits their use for topical applications in the clinic. We have developed a robust, rapid, and precise substrate transfer approach to incorporate nanoneedles within diverse substrates of arbitrary composition, flexibility, curvature, transparency, and biodegradability. With this approach, we integrated nanoneedles on medically relevant elastomers, hydrogels, plastics, medical bandages, catheter tubes, and contact lenses. The integration retains the mechanical properties and transfection efficiency of the nanoneedles. Transparent devices enable the live monitoring of cell-nanoneedle interactions. Flexible devices interface with tissues for efficient, uniform, and sustained topical delivery of nucleic acids ex vivo and in vivo. The versatility of this approach highlights the opportunity to integrate nanoneedles within existing medical devices to develop advanced platforms for topical delivery and biosensing.

Two-Photon Light Trigger siRNA Transfection of Cancer Cells Using Non-Toxic Porous Silicon Nanoparticles.

The concept of using two-photon excitation in the NIR for the spatiotemporal control of biological processes holds great promise. However, its use for the delivery of nucleic acids has been very scarcely described and the reported procedures are not optimal as they often involve potentially toxic materials and irradiation conditions. This work prepares a simple system made of biocompatible porous silicon nanoparticles (pSiNP) for the safe siRNA photocontrolled delivery and gene silencing in cells upon two-photon excitation. PSiNP are linked to an azobenzene moiety, which possesses a lysine group (pSiNP@ICPES-azo@Lys) to efficiently complex siRNA. Non-linear excitation of the two-photon absorber system (pSiNP) followed by intermolecular energy transfer (FRET) to trans azobenzene moiety, result in the photoisomerization of the azobenzene from trans to cis and in the destabilization of the azobenzene-siRNA complex, thus inducing the delivery of the cargo siRNA to the cytoplasm of cells. Efficient silencing in MCF-7 expressing stable firefly luciferase with siRNAluc against luciferase is observed. Furthermore, siRNA against inhibitory apoptotic protein (IAP) leads to over 70% of MCF-7 cancer cell death. The developed technique using two-photon light allows a unique high spatiotemporally controlled and safe siRNA delivery in cells in few seconds of irradiation.

Biomaterials-based approaches to model embryogenesis.

Understanding, reproducing, and regulating the cellular and molecular processes underlying human embryogenesis is critical to improve our ability to recapitulate tissues with proper architecture and function, and to address the dysregulation of embryonic programs that underlies birth defects and cancer. The rapid emergence of stem cell technologies is enabling enormous progress in understanding embryogenesis using simple, powerful, and accessible in vitro models. Biomaterials are playing a central role in providing the spatiotemporal organisation of biophysical and biochemical signalling necessary to mimic, regulate and dissect the evolving embryonic niche in vitro. This contribution is rapidly improving our understanding of the mechanisms underlying embryonic patterning, in turn enabling the development of more effective clinical interventions for regenerative medicine and oncology. Here we highlight how key biomaterial approaches contribute to organise signalling in human embryogenesis models, and we summarise the biological insights gained from these contributions. Importantly, we highlight how nanotechnology approaches have remained largely untapped in this space, and we identify their key potential contributions.

Determination of the Geographical Origin of Maltese Honey Using 1H NMR Fingerprinting.

The price of honey, as a highly consumed natural product, depends on its botanical source and its production environment, causing honey to be vulnerable to adulteration through mislabeling and inappropriate, fraudulent production. In this study, a fast and simple approach is proposed to tackle this issue through non-target one dimensional zg30 and noesypr1d 1H NMR fingerprint analysis, in combination with multivariate data analysis. Results suggest that composition differences in sugars, amino acids, and carboxylic acid were sufficient to discriminate between the tested honey of Maltese origin and that of non-local origin. Indeed, all chemometric models based on noesypr1d analysis of the whole fraction honey showed better prediction in geographical discrimination. The possibility of discrimination was further investigated through analysis of the honey's phenolic extract composition. The partial least squares models were deemed unsuccessful to discriminate, however, some of the linear discriminant analysis models achieved a prediction accuracy of 100%. Lastly, the best performing models of both the whole fraction and the phenolic extracts were tested on five samples of unknown geographic for market surveillance, which attained a high agreement within the models. Thus, suggesting the use of non-target 1H NMR coupled with the multivariate-data analysis and machine learning as a potential alternative to the current time-consuming analytical methods.