About Me
João Meneses graduated with an Integrated Master's in Bioengineering with a specialization in Biomedical Engineering from the Faculty of Engineering of the University of Porto (FEUP, Portugal), in collaboration with the Biomedical Sciences Institute of Abel Salazar (ICBAS, Portugal) in October 2020. His master's thesis was developed in collaboration with the University Medical Center Utrecht (UMC, The Netherlands) and was entitled "3D Printing of Polycaprolactone/Graphene-based Materials Scaffolds for Tissue Engineering". From March 2021 until August 2023, he worked as a Junior Research Fellow at the International Iberian Nanotechnology Laboratory (INL, Portugal) in the Nanosafety Research Group. The work focused on developing computational methods to achieve Safe-and-Sustainable advanced nanomaterials (NMs). To this aim, he took advantage of (i) supervised and (ii) unsupervised machine learning (ML) algorithms, (iii) quantitative structure-activity relationships (QSAR), and (iv) quantitative structure-property relationships (QSPR) models. Overall, the work paved the way for efficient decision-making, prediction, and mitigation of the potential occupational and environmental risks of NMs. Moreover, he performed a secondment at IBM Research Europe (Zurich, Switzerland). The work focused on integrating an AI-assisted microcontroller-based chemical sensor with blockchain. Such a secondment allowed him to continue developing skills in developing interpretable and interoperable ML algorithms and gain knowledge on electrochemical sensors and blockchain technology. Since September 2023, he started as a PhD candidate at the University of Twente (Dep. of Advanced Organ Bioengineering and Therapeutics, The Netherlands) to work on (i) Organs-on-chips, (ii) high-content data analysis, and (iii) AI.
Organisations
Publications
Recent
Cedillo-Servin, G., Dahri, O.
, Meneses, J., van Duijn, J., Moon, H., Sage, F., Silva, J., Pereira, A., Magalhães, F. D., Malda, J., Geijsen, N., Pinto, A. M., & Castilho, M. (2023).
3D Printed Magneto-Active Microfiber Scaffolds for Remote Stimulation and Guided Organization of 3D In Vitro Skeletal Muscle Models.
Small.
https://doi.org/10.1002/smll.202307178
Toropova, A. P.
, Meneses, J., Alfaro-Moreno, E., & Toropov, A. A. (2023).
The system of self-consistent models based on quasi-SMILES as a tool to predict the potential of nano-inhibitors of human lung carcinoma cell line A549 for different experimental conditions.
Drug and Chemical Toxicology. Advance online publication.
https://doi.org/10.1080/01480545.2023.2174986
Meneses, J., González-Durruthy, M., Fernandez-de-Gortari, E., Toropova, A. P., Toropov, A. A., & Alfaro-Moreno, E. (2023).
A Nano-QSTR model to predict nano-cytotoxicity: an approach using human lung cells data.
Particle and Fibre Toxicology,
20, Article 21.
https://doi.org/10.1186/s12989-023-00530-0
Meneses, J., Kemp, T. V. D., Costa-Almeida, R., Pereira, R. F., Magalhães, F. D., Castilho, M., & Pinto, A. M. (2022).
Fabrication of Polymer/Graphene Biocomposites for Tissue Engineering.
Polymers,
14(5), Article 1038.
https://doi.org/10.3390/polym14051038
Lima, T. S. M., souza, W. D., Geaquinto, L., Sanches, P., Stepien, E.
, Meneses, J., Gortari, E. F., Meisner-Kober, N., Himly, M., Granjeiro, J. M., & Ribeiro, A. R. (2022).
Nanomaterial Exposure, Extracellular Vesicle Biogenesis and Adverse Cellular Outcomes: A Scoping Review.
Nanomaterials,
12(7), Article 1231.
https://doi.org/10.3390/nano12071231
Lebre, F., Chatterjee, N., Costa, S., Fernández-de-Gortari, E., Lopes, C.
, Meneses, J., Ortiz-Galvez, L. M., Ribeiro, A. R., Vilas-Boas, V., & Alfaro-Moreno, E. (2022).
Nanosafety: An Evolving Concept to Bring the Safest Possible Nanomaterials to Society and Environment.
Nanomaterials,
12(11), Article 1810.
https://doi.org/10.3390/nano12111810
Costa-Almeida, R., Bogas, D., Fernandes, J. R., Timochenco, L., Silva, F. A. L. S.
, Meneses, J., Gonçalves, I. C., Magalhães, F. D., & Pinto, A. M. (2020).
Near-infrared radiation-based mild photohyperthermia therapy of non-melanoma skin cancer with PEGylated reduced nanographene oxide.
Polymers,
12(8), Article 1840.
https://doi.org/10.3390/polym12081840
UT Research Information System
Google Scholar Link
In the press
- A novel Machine Learning model to predict the toxicity of nanomaterials: an approach using human lung cells data (https://inl.int/inl-researchers-develop-a-new-model-to-predict-toxicity-of-nanomaterials/)
Contact Details
Visiting Address
University of Twente
Faculty of Science and Technology
Horst - Zuidhorst
(building no. 28)
De Horst 2
7522LW Enschede
The Netherlands
Mailing Address
University of Twente
Faculty of Science and Technology
Horst - Zuidhorst
P.O. Box 217
7500 AE Enschede
The Netherlands