The identification or design of biocatalysts to mitigate the accumulation of plastics, including sub-micro- and nano-sized polyethylene terephthalate (nPET), is becoming a global challenge. Here we computationally incorporated two hydrolytic active sites with geometries similar to that of Idionella sakaiensis PET hydrolase, to fragaceatoxin C (FraC), a membrane pore-forming protein. FraC_m1/m2 could be assembled into octameric nanopores (7.0 nm high × 1.6–6.0 nm entry), which deconstructed (40 °C, pH 7.0) nPET from GoodFellow, commodities and plastic bottles. FraC_m1 and FraC_m2 degrade nPET by endo- and exo-type chain scission. While FraC_m1 produces bis(2-hydroxyethyl) terephthalate as the main product, FraC_m2 yields a high diversity of oligomers and terephthalic acid. Mechanistic and biochemical differences with benchmark PET hydrolases, along with pore and nPET dynamics, suggest that these pore-forming protein catalytic nanoreactors do not deconstruct macro-PET but are promising in nanotechnology for filtering, capturing and breaking down nPET, for example, in wastewater treatment plants.

Raman spectroscopy is a fast-growing and increasingly powerful analytical technique applied across diverse disciplines such as materials science, chemistry, biology and medicine. This growth is driven by advances in Raman instrumentation and greatly supported by the flourishing of chemometrics and artificial intelligence (AI). However, the full potential of this technique is often hampered by challenges related to data acquisition, processing, interpretation, and sharing. This review paper addresses how a concerted effort toward digitalization, incorporating principles of Open Science and FAIR data (Findable, Accessible, Interoperable, and Reusable), is essential to develop and implement robust, standardized, and accessible digital workflows. These workflows are key to unlock the full power of Raman spectroscopy in combination with AI. We explore the current landscape of digital tools and open resources in Raman spectroscopy, highlighting both existing solutions as well as critical gaps. Despite these advances, the field remains fragmented, with many initiatives developed in isolation, limiting interoperability and slowing progress. In this regard, we assess the trends in Raman spectroscopy hardware and control software as well as the role of AI in improving data collection, automating data analysis, extracting meaningful insights, and enabling predictive modeling. We review challenges such as data quality and model interpretability that constrain the effectiveness and applicability of AI in Raman spectroscopy. Furthermore, we emphasize the importance of standardized data formats, metadata schemas, and domain-specific ontologies to ensure machine-actionability, database federation and interoperability as well as to facilitate collaborative research. We provide curated lists of existing open hardware, databases and standards relevant to Raman spectroscopy. Finally, we propose a roadmap toward an open and FAIR ecosystem for Raman spectroscopy, emphasizing the need for sustainable infrastructure, collaborative development, and community involvement.

The challenges inherent to the extraction of micro- and nanoplastics (MNPs) from the environment and the limited range of commercially available MNPs have prompted an increasing number of researchers to generate in-house reference and test MNPs.

Although coronary stents have improved the early and long-term consequences of arterial lesions, the prevention of restenosis and late stent thrombosis is key to prevent a new obstruction of the vessel. Here we aimed at improving the tissue response to stents through surface modification. For that purpose, we used two different approaches, the use of nanostructuration by electrochemical anodization and the addition of a quercitrin (QR) coating to the Ti surface. Four surfaces (Ti, NN, TiQR and NNQR) were characterized by atomic force microscopy, scanning electronic microscopy and contact angle analysis and QR content was evaluated by fluorescent staining. Cell adhesion, cytotoxicity, metabolic activity and nitric oxide (NO) production was evaluated on primary human umbilical cord endothelial cells (HUVECs). Platelet adhesion, hemolysis rate and Staphylococcus epidermidis CECT 4184 adhesion at 30 min were analyzed. Nanostructuration induced an increase on surface roughness, and QR coating decreased the contact angle. All surfaces were biocompatible, with no hemolysis rate and lower platelet adhesion was found in NN surfaces. Finally, S. epidermidis adhesion was lower on TiQR surfaces compared to Ti. In conclusion, our results suggest that NN structuration could improve biocompatibility of bare metal stents on endothelial cells and reduce platelet adhesion. Moreover, QR coating could reduce bacterial adhesion.

Considering the increasing production of engineered nanomaterials (ENMs), new approach methodologies (NAMs) are essential for safe-by-design approaches and risk assessment. Our aim was to enhance screening strategies with a focus on reactivity-triggered toxicities. We applied in vitro tests to 10 selected benchmark ENMs in two cell models, lung epithelial A549 and differentiated THP-1 macrophage-like cells. Previously, we categorized ENMs based on surface reactivity. Here we elucidated their reactivity-triggered cytotoxicity and mode of action using the WST-1 assay (metabolic activity), LDH assay (cell membrane integrity), autophagosome detection, and proteomics. Nonreactive SiO₂ NM-200 showed no significant impact on cell viability. Conversely, highly reactive CuO and ZnO (NM-110 and NM-111) disrupted cell homeostasis. Interestingly, moderately reactive TiO₂ (NM-101 and NM-105) and CeO₂ (NM-211 and NM-212), apparently without an adverse effect, induced autophagosome formation, evidencing autophagy as a defensive mechanism. Our improved in vitro testing strategy, combined with state-of-the-art reactivity information, screens ENMs for potential reactivity-triggered toxicity.

Implementation of the safe and sustainable by design framework using cement mortar containing an SiO₂@ZnO multi-component nanomaterial for NO_x degradation as a case study.