Biology subjects

Figueredo, G.

Publications and source records attributed to Figueredo, G..

3 recordsLinked to original sources

bioRxiv2025

Molecular biointerface characterisation for an implanted medical device using cryogenic orbitrap secondary ion mass spectrometry (Cryo-OrbiSIMS)

Implanted medical devices often fail due to foreign body reaction (FBR), a process still not fully understood. This work presents a new depth profiling approach to provide insight into the spatial metabolomics of the biointerface of implants, revealing biomolecular strata representative of the host response. This study examines silicone rubber poly(dimethyl siloxane) catheters implanted in mice for 1 and 28 days. Cryo-OrbiSIMS was used in combination with ToF-SIMS to identify metabolite profiles from the biological deposit found on the implants after removal from the tissue which were previously unattainable using tissue sectioning. Machine learning and statistical analysis of the profiles were used to help identify early biointerface responses to the implant, including at 1 day of implantation the observation of elevated sugars and itaconate an immunomodulatory metabolite that modulates FBR. At day 28 inflammation associated markers were observed such as urate and palmitic acid (FA 16:0). Depth profiling revealed two distinct molecular layers in the deposits: amino acids, and nucleic acids were preferentially seen towards the host tissue, consistent with the observation of a cell monolayer in the tissue sections, whereas certain lipids and fatty acids where either at the catheter-deposit interface or towards the host tissue after 28 days. The stratification was less well developed at 1-day implantation, but common lipids were seen at the deposit-implant interface across both time points. These insights advance understanding of FBR and support the development of improved implant materials.

bioinformatics↗

bioRxiv2020

Topographical biomaterials instruct bacterial surface attachment and the in vivo host-pathogen response

Bio-instructive materials that prevent bacterial biofilm formation and drive an appropriate host immune response have the potential to significantly reduce the burden of medical device-associated infections. Since bacterial surface attachment is known to be sensitive to surface topography, we experimentally survey 2,176 combinatorially generated shapes using an unbiased high-throughput micro topographical screen on polystyrene. This identifies topographies that reduce colonization in vitro by up to 15-fold compared with a flat surface for both motile and non-motile bacterial pathogens. Equivalent reductions are achieved on polyurethane, a polymer commonly used in medical devices. Using machine learning methods, a set of design rules based on generalisable descriptors is established for predicting bacteria-resistant micro topographies. In a murine foreign body infection model, anti-attachment topographies are shown to be refractory to P. aeruginosa and to recruit a productive host response, highlighting the potential of simple topographical patterning of non-eluting implants for preventing medical device associated infections.

microbiology↗

bioRxiv2020

Synergistic Material-Topography Combinations to Achieve Immunomodulatory Osteogenic Biomaterials

Human mesenchymal stem cells (hMSCs) are widely represented in ongoing regenerative medicine clinical trials due to their ease of autologous implantation. In bone regeneration, crosstalk between macrophages and hMSCs is critical with macrophages playing a key role in the recruitment and differentiation of hMSCs. However, engineered biomaterials able to both direct hMSC fate and modulate macrophage phenotype have not yet been identified. A novel combinatorial chemistry-microtopography screening platform, the ChemoTopoChip, is used to identify materials suitable for bone regeneration by screening with human immortalized mesenchymal stem cells (hiMSCs) and human macrophages. The osteoinduction achieved in hiMSCs cultured on the "hit" materials in basal media is comparable to that seen when cells are cultured in osteogenic media, illustrating that these materials offer a materials-induced alternative in bone-regenerative applications. These also exhibit immunomodulatory effects, concurrently polarizing macrophages towards a pro-healing phenotype. Control of cell response is achieved when both chemistry and topography are recruited to instruct the required cell phenotype, combining synergistically. The large library of materials reveals that the relative roles of microtopography and material chemistry are similar, and machine learning identifies key material and topographical features for cell-instruction.

bioengineering↗