Open Access

Tunneling nanotubes (TNTs) are thin, dynamic, long membrane protrusions that allow intercellular exchanges of signaling clues, molecules and organelles. The presence of TNTs and their involvement as drug delivery channels have been observed in several types of cancer, including glioblastoma. Recently, increased attention has been directed toward nanoparticles (NPs) that can be transported in TNTs. However, few data are available on the role of physical parameters of nanoparticles, such as size, shape, charge and flexibility, in determining their transfer efficiency between cells by TNTs. Here, we focused our attention on NP shape, manufacturing spherical, discoidal and deformable negatively charged lipid-based NPs with sizes <120 nm and similar stiffness. The TNT-mediated transfer of NPs was investigated in 2D and 3D culture models of human glioblastoma cells. The permeability and biocompatibility of the blood–brain barrier (BBB) were also assessed. Results showed that discoidal NPs displayed the highest TNT-mediated transfer efficiency between cancer cells, with a maximum velocity of 69 nm s−1, and a higher endothelial permeability (1.29 × 10−5 cm min−1) across the BBB in an in vitro model. This depends on the NP shape because discoidal NPs have a larger surface area exposed to the flow along the TNT channel. Overall, the results suggest that the shape of NPs is the game-changer for more efficient TNT-mediated transfer between cancer cells, thus introducing a sustainable solution to improve the diffusion rate at which the NPs spread in the tumour microenvironment, opening the possibility of ameliorating drug distribution to difficult-to-reach cancer cell populations.

The laser welding of Cu–Al alloys for battery applications in the automotive industry presents significant challenges due to the high reflectivity of copper. Inadequate bonding and low mechanical strength may occur when the laser radiation is directed toward the copper side in an overlap configuration welding. To tackle these challenges, a laser surface treatment technique is implemented to enhance the absorption characteristics and overcome the reflective nature of the copper material. However, elevating the surface roughness and heat-energy input over threshold values leads to heightened temperature and extreme weld. This phenomenon escalates the formation of detrimental intermetallic compounds (IMC), creating defects like cracks and porosity. Metallurgical analysis, which is time-consuming and expensive, is usually used in studies to detect these phases and defects. However, to comprehensively evaluate the weld quality and discern the impact of surface structure, adopting a more innovative approach that replaces conventional cross-sectional metallography is essential. This article proposes a model based on the image feature extraction of the welds to study the effect of the laser-based structure and the other laser parameters. It can detect defects and identify the weld quality by weld classification. However, due to the complexity of the photo features, the system requires image processing and a convolutional neural network (CNN). Results show that the predictive model based on trained data can detect different weld categories and recognize unstable welds. The project aims to use a monitoring model to guarantee optimized and high-quality weld series production. To achieve this, a deeper study of the parameters and the microstructure of the weld is utilized, and the CNN model analyzes the features of 1310 pieces of weld photos with different weld parameters.

The dragonfish is a voracious predator of the deep sea with an arsenal of tools to hunt prey and remain concealed. In contrast to its dark pigmented skin, the dragonfish is equipped with transparent teeth. Here, we establish the structure, composition, and mechanical properties of the transparent teeth for the first time. We find the enamel-like layer to consist of nanocrystalline hydroxyapatite domains (∼20 nm grain size) embedded in an amorphous matrix, whereas in the dentin layer the nanocrystalline hydroxyapatite coats nanoscale collagen fibrils forming nanorods. This nanoscale structure is responsible for the much-reduced Rayleigh light scattering, which is further ensured by the sufficiently thin walls. Here, we suggest that the nanostructured design of the transparent dragonfish teeth enables predatory success as it makes its wide-open mouth armed with saber-like teeth effectively disappear, showing no contrast to the surrounding blackness of the fish nor the background darkness of the deep sea.

Pseudomonas aeruginosa (PA) is a major healthcare concern due to its tolerance to antibiotics when enclosed in biofilms. Tobramycin (Tob), an effective cationic aminoglycoside antibiotic against planktonic PA, loses potency within PA biofilms due to hindered diffusion caused by interactions with anionic biofilm components. Loading Tob into nano-carriers can enhance its biofilm efficacy by shielding its charge. Polyion complex vesicles (PIC-somes) are promising nano-carriers for charged drugs, allowing higher drug loadings than liposomes and polymersomes. In this study, a new class of nano-sized PIC-somes, formed by Tob-diblock copolymer complexation is presented. This approach replaces conventional linear PEG with brush-like poly[ethylene glycol (methyl ether methacrylate)] (PEGMA) in the shell-forming block, distinguishing it from past methods. Tob paired with a block copolymer containing hydrophilic PEGMA induces micelle formation (PIC-micelles), while incorporating hydrophobic pyridyldisulfide ethyl methacrylate (PDSMA) monomer into PEGMA chains reduces shell hydrophilicity, leads to the formation of vesicles (PIC-somes). PDSMA unit incorporation enables unprecedented dynamic disulfide bond-based shell cross-linking, significantly enhancing stability under saline conditions. Neither PIC-somes nor PIC-micelles show any relevant cytotoxicity on A549, Calu-3, and dTHP-1 cells. Tob's antimicrobial efficacy against planktonic PA remains unaffected after encapsulation into PIC-somes and PIC-micelles, but its potency within PA biofilms significantly increases.

Cobaltocenium-containing polymers, an emerging class of materials, have historically been challenging to prepare due to their chemical robustness. In this work, we introduce a novel and highly efficient method for their preparation based on methacrylate-containing block copolymers (BCPs), allowing segment-selective introduction of functional moieties. The catalyst-free and quantitative hydroamination reaction we introduce has proven successful for the post-modification of amine-containing polymers with cobaltocenium. To demonstrate the versatility of this method, we successfully synthesized a series of BCPs consisting of polystyrene and a 5 to 20 wt% poly(tert-butyl aminoethyl methacrylate) (PtBAEMA) segment by living anionic polymerization. The selective functionalization with ethynyl-cobaltocenium hexafluorophosphate results in adjustable 5 to 40 wt% cobaltocenium units in the polymer as part of the PtBAEMA block segment. The success was monitored by IR spectroscopy, and the quantitative incorporation of the cobaltocenium moiety was verified by 1H NMR, UV-Vis spectroscopy, and TGA. DSC proved the block-selective cobaltocenium introduction by an additional glass transition temperature at 154 °C, and the strong microphase separation character of the amphiphilic BCPs leads to lamellar structures in the bulk state, as proven by TEM investigations. Finally, the water contact angle on polymer films is compared, showing polarity inversion and tunability upon conversion of hydrophilic amine to hydrophobic cobaltocenium hexafluorophosphate moieties. This successful synthesis and characterization of cobaltocenium-containing BCPs not only paves the way for a new class of metallopolymers but also offers functionalization possibilities for a variety of other responsive moieties, providing access to functional BCPs.