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Untapping multiparametric 2D luminescence sensing through MACHine LEarning and Spectral Sorting

Project description

2D luminescence sensing to study cell health and function

Cellular health depends on factors such as temperature, oxygen concentration, and pH. Luminescence sensing offers a minimally invasive method to monitor these parameters intracellularly with high spatial resolution. However, its reliability is hindered by sensor variability, cross-sensitivity, and the absence of fast 2D mapping technology. The ERC-funded MAtCHLESS project aims to advance luminescence sensing technology for multiparameter cell studies, improving insights into processes including cancer treatment. The project will develop composite submicrometric luminescent sensors, eliminate interparticle fluctuations through spectral sorting, and leverage machine learning to transform cross-sensitivity into a useful feature. Additionally, it will create a high-resolution 2D mapping setup for real-time parameter monitoring. The technology will be tested on mammalian cell lines and extremophilic microorganisms adapted to extreme environments.

Objective

Cellular organisms are complex machines whose health and functioning are dictated by parameters including temperature, oxygen concentration, and pH. Luminescence nanosensing is a technology that promises all the features required to reliably monitor these parameters at the intracellular level: minimal invasiveness, remote working principle, and submicrometric spatial resolution. These features are ensured by the use of sub-micrometric sensors (particles) whose luminescence is sensitive to changes in the parameters to be sensed. Yet, despite the hype about luminescence nanosensing, its reliability in the study of cells is limited by interparticle variability in optical properties and sensing performance, simultaneous response to several parameters (cross-sensitivity), and lack of a measurement technology that enables fast 2D mapping of multiple parameters with sub-second temporal resolution. MAtCHLESS tackles heads on these limitations to develop a reliable luminescence sensing technology for multiparameteric sensing in cell studies. This project entails: design of a novel family of composite submicrometric luminescent sensors, elimination of interparticle fluctuations in optical properties using a spectral sorting strategy, introduction of the paradigm shift of making cross-sensitivity a desirable feature via machine learning, and use of a novel optical technology to build a setup for 2D mapping of multiple parameters with high temporal and spatial resolution. MAtCHLESS will test the reliability of the sensing approach in mammalian cell lines and extremophiles microorganisms that can withstand extreme conditions of, e.g. temperature, oxygen concentration, and pH. These investigations will show the potential of the developed technology to monitor both slight and extreme changes in biological parameters, towards a deeper understanding of, e.g. how cancer can be more effectively treated, as well as how Life evolved on Earth and can be adapted beyond our planet.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-STG

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Host institution

UNIVERSITA CA' FOSCARI VENEZIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 450 000,00
Address
DORSODURO 3246
30123 VENEZIA
Italy

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Region
Nord-Est Veneto Venezia
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 450 000,00

Beneficiaries (2)

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