Luminescence Thermometry for Brain Activity Monitoring: A Perspective

Neural Networks Push the Limits of Luminescence Lifetime Nanosensing

Luminescence lifetime-based sensing is ideally suited to monitor biological systems due to its minimal invasiveness and remote working principle. Yet, its applicability is limited in conditions of low signal-to-noise ratio (SNR) induced by, e.g., short exposure times and presence of opaque tissues. Herein this limitation is overcome by applying a U-shaped convolutional neural network (U-NET) to improve luminescence lifetime estimation under conditions of extremely low SNR. Specifically, the prowess of the U-NET is showcased in the context of luminescence lifetime thermometry, achieving more precise thermal readouts using Ag2 S nanothermometers. Compared to traditional analysis methods of decay curve fitting and integration, the U-NET can extract average lifetimes more precisely and consistently regardless of the SNR value. The improvement achieved in the sensing performance using the U-NET is demonstrated with two experiments characterized by extreme measurement conditions: thermal monitoring of free-falling droplets, and monitoring of thermal transients in suspended droplets through an opaque medium. These results broaden the applicability of luminescence lifetime-based sensing in fields including in vivo experimentation and microfluidics, while, hopefully, spurring further research on the implementation of machine learning (ML) in luminescence sensing.

Ion-induced bias in Ag2S luminescent nanothermometers

Luminescence nanothermometry allows measuring temperature remotely and in a minimally invasive way by using the luminescence signal provided by nanosized materials. This technology has allowed, for example, the determination of intracellular temperature and in vivo monitoring of thermal processes in animal models. However, in the biomedical context, this sensing technology is crippled by the presence of bias (cross-sensitivity) that reduces the reliability of the thermal readout. Bias occurs when the impact of environmental conditions different from temperature also modifies the luminescence of the nanothermometers. Several sources that cause loss of reliability have been identified, mostly related to spectral distortions due to interaction between photons and biological tissues. In this work, we unveil an unexpected source of bias induced by metal ions. Specifically, we demonstrate that the reliability of Ag2S nanothermometers is compromised during the monitoring of photothermal processes produced by iron oxide nanoparticles. The observed bias occurs due to the heat-induced release of iron ions, which interact with the surface of the Ag2S nanothermometers, enhancing their emission. The results herein reported raise a warning to the community working on luminescence nanothermometry, since they reveal that the possible sources of bias in complex biological environments, rich in molecules and ions, are more numerous than previously expected.

Spotlight on Luminescence Thermometry: Basics, Challenges, and Cutting-Edge Applications

Luminescence (nano)thermometry is a remote sensing technique that relies on the temperature dependency of the luminescence features (e.g., bandshape, peak energy or intensity, and excited state lifetimes and risetimes) of a phosphor to measure temperature. This technique provides precise thermal readouts with superior spatial resolution in short acquisition times. Although luminescence thermometry is just starting to become a more mature subject, it exhibits enormous potential in several areas, e.g., optoelectronics, photonics, micro- and nanofluidics, and nanomedicine. This work reviews the latest trends in the field, including the establishment of a comprehensive theoretical background and standardized practices. The reliability, repeatability, and reproducibility of the technique are also discussed, along with the use of multiparametric analysis and artificial-intelligence algorithms to enhance thermal readouts. In addition, examples are provided to underscore the challenges that luminescence thermometry faces, alongside the need for a continuous search and design of new materials, experimental techniques, and analysis procedures to improve the competitiveness, accessibility, and popularity of the technology.