Early in vivo detection of denervation-induced atrophy by luminescence transient nanothermometry.

Denervation induces skeletal muscle atrophy due to the loss of control and feedback with the nervous system. Unfortunately, muscle atrophy only becomes evident days after the denervation event when it could be irreversible. Alternative diagnosis tools for early detection of denervation-induced muscle atrophy are, thus, required. In this work, we demonstrate how the combination of transient thermometry, a technique already used for early diagnosis of tumors, and infrared-emitting nanothermometers makes possible the in vivo detection of the onset of muscle atrophy at short (<1 day) times after a denervation event. The physiological reasons behind these experimental results have been explored by performing three dimensional numerical simulations based on the Pennes' bioheat equation. It is concluded that the alterations in muscle thermal dynamics at the onset of muscle atrophy are consequence of the skin perfusion increment caused by the alteration of peripheral nervous autonomous system. This work demonstrates the potential of infrared luminescence thermometry for early detection of diseases of the nervous system opening the venue toward the development of new diagnosis tools.

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.

Exploring the Origin of the Thermal Sensitivity of Near-Infrared-II Emitting Rare Earth Nanoparticles.

Rare-earth doped nanoparticles (RENPs) are attracting increasing interest in materials science due to their optical, magnetic, and chemical properties. RENPs can emit and absorb radiation in the second biological window (NIR-II, 1000-1400 nm) making them ideal optical probes for photoluminescence (PL) in vivo imaging. Their narrow emission bands and long PL lifetimes enable autofluorescence-free multiplexed imaging. Furthermore, the strong temperature dependence of the PL properties of some of these RENPs makes remote thermal imaging possible. This is the case of neodymium and ytterbium co-doped NPs that have been used as thermal reporters for in vivo diagnosis of, for instance, inflammatory processes. However, the lack of knowledge about how the chemical composition and architecture of these NPs influence their thermal sensitivity impedes further optimization. To shed light on this, we have systematically studied their emission intensity, PL decay time curves, absolute PL quantum yield, and thermal sensitivity as a function of the core chemical composition and size, active-shell, and outer-inert-shell thicknesses. The results revealed the crucial contribution of each of these factors in optimizing the NP thermal sensitivity. An optimal active shell thickness of around 2 nm and an outer inert shell of 3.5 nm maximize the PL lifetime and the thermal response of the NPs due to the competition between the temperature-dependent back energy transfer, the surface quenching effects, and the confinement of active ions in a thin layer. These findings pave the way for a rational design of RENPs with optimal thermal sensitivity.

3D Optical Coherence Thermometry Using Polymeric Nanogels.

In nanothermometry, the use of nanoparticles as thermal probes enables remote and minimally invasive sensing. In the biomedical context, nanothermometry has emerged as a powerful tool where traditional approaches, like infrared thermal sensing and contact thermometers, fall short. Despite the strides of this technology in preclinical settings, nanothermometry is not mature enough to be translated to the bedside. This is due to two major hurdles: the inability to perform 3D thermal imaging and the requirement for tools that are readily available in the clinics. This work simultaneously overcomes both limitations by proposing the technology of optical coherence thermometry (OCTh). This is achieved by combining thermoresponsive polymeric nanogels and optical coherence tomography (OCT)-a 3D imaging technology routinely used in clinical practice. The volume phase transition of the thermoresponsive nanogels causes marked changes in their refractive index, making them temperature-sensitive OCT contrast agents. The ability of OCTh to provide 3D thermal images is demonstrated in tissue phantoms subjected to photothermal processes, and its reliability is corroborated by comparing experimental results with numerical simulations. The results included in this work set credible foundations for the implementation of nanothermometry in the form of OCTh in clinical practice.

Optomagnetic nanofluids for controlled brain hyperthermia: a critical study.

Optomagnetic nanofluids (OMNFs) are colloidal dispersions of nanoparticles (NPs) with combined magnetic and optical properties. They are especially appealing in biomedicine since they can be used as minimally invasive platforms for controlled hyperthermia treatment of otherwise difficultly accessible tumors such as intracranial ones. On the one hand, magnetic NPs act as heating mediators when subjected to alternating magnetic fields or light irradiation. On the other hand, suitably tailored luminescent NPs can provide a precise and remote thermal readout in real time. The combination of heating and thermometric properties allows, in principle, to precisely monitor the increase in the temperature of brain tumors up to the therapeutic level, without causing undesired collateral damage. In this work we demonstrate that this view is an oversimplification since it ignores the presence of relevant interactions between magnetic (γ-Fe2O3 nanoflowers) and luminescent nanoparticles (Ag2S NPs) that result in a detrimental alteration of their physicochemical properties. The magnitude of such interactions depends on the interparticle distance and on the surface properties of nanoparticles. Experiments performed in mouse brains (phantoms and ex vivo) revealed that OMNFs cannot induce relevant heating under alternating magnetic fields and fail to provide reliable temperature reading. In contrast, we demonstrate that the use of luminescent nanofluids (containing only Ag2S NPs acting as both photothermal agents and nanothermometers) stands out as a better alternative for thermally monitored hyperthermia treatment of brain tumors in small animal models.

Quantitative Comparison of the Light-to-Heat Conversion Efficiency in Nanomaterials Suitable for Photothermal Therapy.

Functional colloidal nanoparticles capable of converting between various energy types are finding an increasing number of applications. One of the relevant examples concerns light-to-heat-converting colloidal nanoparticles that may be useful for localized photothermal therapy of cancers. Unfortunately, quantitative comparison and ranking of nanoheaters are not straightforward as materials of different compositions and structures have different photophysical and chemical properties and may interact differently with the biological environment. In terms of photophysical properties, the most relevant information to rank these nanoheaters is the light-to-heat conversion efficiency, which, along with information on the absorption capacity of the material, can be used to directly compare materials. In this work, we evaluate the light-to-heat conversion properties of 17 different nanoheaters belonging to different groups (plasmonic, semiconductor, lanthanide-doped nanocrystals, carbon nanocrystals, and metal oxides). We conclude that the light-to-heat conversion efficiency alone is not meaningful enough as many materials have similar conversion efficiencies─in the range of 80-99%─while they significantly differ in their extinction coefficient. We therefore constructed their qualitative ranking based on the external conversion efficiency, which takes into account the conventionally defined light-to-heat conversion efficiency and its absorption capacity. This ranking demonstrated the differences between the samples more meaningfully. Among the studied systems, the top-ranking materials were black porous silicon and CuS nanocrystals. These results allow us to select the most favorable materials for photo-based theranostics and set a new standard in the characterization of nanoheaters.

Luminescence Thermometry for Brain Activity Monitoring: A Perspective.

Minimally invasive monitoring of brain activity is essential not only to gain understanding on the working principles of the brain, but also for the development of new diagnostic tools. In this perspective we describe how brain thermometry could be an alternative to conventional methods (e.g., magnetic resonance or nuclear medicine) for the acquisition of thermal images of the brain with enough spatial and temperature resolution to track brain activity in minimally perturbed animals. We focus on the latest advances in transcranial luminescence thermometry introducing a critical discussion on its advantages and shortcomings. We also anticipate the main challenges that the application of luminescent nanoparticles for brain thermometry will face in next years. With this work we aim to promote the development of near infrared luminescence for brain activity monitoring, which could also benefit other research areas dealing with the brain and its illnesses.

Thermoresponsive Polymeric Nanolenses Magnify the Thermal Sensitivity of Single Upconverting Nanoparticles.

Lanthanide-based upconverting nanoparticles (UCNPs) are trustworthy workhorses in luminescent nanothermometry. The use of UCNPs-based nanothermometers has enabled the determination of the thermal properties of cell membranes and monitoring of in vivo thermal therapies in real time. However, UCNPs boast low thermal sensitivity and brightness, which, along with the difficulty in controlling individual UCNP remotely, make them less than ideal nanothermometers at the single-particle level. In this work, it is shown how these problems can be elegantly solved using a thermoresponsive polymeric coating. Upon decorating the surface of NaYF4 :Er3+ ,Yb3+ UCNPs with poly(N-isopropylacrylamide) (PNIPAM), a >10-fold enhancement in optical forces is observed, allowing stable trapping and manipulation of a single UCNP in the physiological temperature range (20-45 °C). This optical force improvement is accompanied by a significant enhancement of the thermal sensitivity- a maximum value of 8% °C+1 at 32 °C induced by the collapse of PNIPAM. Numerical simulations reveal that the enhancement in thermal sensitivity mainly stems from the high-refractive-index polymeric coating that behaves as a nanolens of high numerical aperture. The results in this work demonstrate how UCNP nanothermometers can be further improved by an adequate surface decoration and open a new avenue toward highly sensitive single-particle nanothermometry.

Less is more: dimensionality reduction as a general strategy for more precise luminescence thermometry.

Thermal resolution (also referred to as temperature uncertainty) establishes the minimum discernible temperature change sensed by luminescent thermometers and is a key figure of merit to rank them. Much has been done to minimize its value via probe optimization and correction of readout artifacts, but little effort was put into a better exploitation of calibration datasets. In this context, this work aims at providing a new perspective on the definition of luminescence-based thermometric parameters using dimensionality reduction techniques that emerged in the last years. The application of linear (Principal Component Analysis) and non-linear (t-distributed Stochastic Neighbor Embedding) transformations to the calibration datasets obtained from rare-earth nanoparticles and semiconductor nanocrystals resulted in an improvement in thermal resolution compared to the more classical intensity-based and ratiometric approaches. This, in turn, enabled precise monitoring of temperature changes smaller than 0.1 °C. The methods here presented allow choosing superior thermometric parameters compared to the more classical ones, pushing the performance of luminescent thermometers close to the experimentally achievable limits.

New opportunities for light-based tumor treatment with an "iron fist".

The efficacy of photodynamic treatments of tumors can be significantly improved by using a new generation of nanoparticles that take advantage of the unique properties of the tumor microenvironment.

Bismuth Selenide Nanostructured Clusters as Optical Coherence Tomography Contrast Agents: Beyond Gold-Based Particles.

Optical coherence tomography (OCT) is an imaging technique currently used in clinical practice to obtain optical biopsies of different biological tissues in a minimally invasive way. Among the contrast agents proposed to increase the efficacy of this imaging method, gold nanoshells (GNSs) are the best performing ones. However, their preparation is generally time-consuming, and they are intrinsically costly to produce. Herein, we propose a more affordable alternative to these contrast agents: Bi2Se3 nanostructured clusters with a desert rose-like morphology prepared via a microwave-assisted method. The structures are prepared in a matter of minutes, feature strong near-infrared extinction properties, and are biocompatible. They also boast a photon-to-heat conversion efficiency of close to 50%, making them good candidates as photothermal therapy agents. In vitro studies evidence the prowess of Bi2Se3 clusters as OCT contrast agents and prove that their performance is comparable to that of GNSs.

Boosting the Near-Infrared Emission of Ag2S Nanoparticles by a Controllable Surface Treatment for Bioimaging Applications.

Ag2S nanoparticles are the staple for high-resolution preclinical imaging and sensing owing to their photochemical stability, low toxicity, and photoluminescence (PL) in the second near-infrared biological window. Unfortunately, Ag2S nanoparticles exhibit a low PL efficiency attributed to their defective surface chemistry, which curbs their translation into the clinics. To address this shortcoming, we present a simple methodology that allows to improve the PL quantum yield from 2 to 10%, which is accompanied by a PL lifetime lengthening from 0.7 to 3.8 µs. Elemental mapping and X-ray photoelectron spectroscopy indicate that the PL enhancement is related to the partial removal of sulfur atoms from the nanoparticle's surface, reducing surface traps responsible for nonradiative de-excitation processes. This interpretation is further backed by theoretical modeling. The acquired knowledge about the nanoparticles' surface chemistry is used to optimize the procedure to transfer the nanoparticles into aqueous media, obtaining water-dispersible Ag2S nanoparticles that maintain excellent PL properties. Finally, we compare the performance of these nanoparticles with other near-infrared luminescent probes in a set of in vitro and in vivo experiments, which demonstrates not only their cytocompatibility but also their superb optical properties when they are used in vivo, affording higher resolution images.

Reliable and Remote Monitoring of Absolute Temperature during Liver Inflammation via Luminescence-Lifetime-Based Nanothermometry.

Temperature of tissues and organs is one of the first parameters affected by physiological and pathological processes, such as metabolic activity, acute trauma, or infection-induced inflammation. Therefore, the onset and development of these processes can be detected by monitoring deviations from basal temperature. To accomplish this, minimally invasive, reliable, and accurate measurement of the absolute temperature of internal organs is required. Luminescence nanothermometry is the ideal technology for meeting these requirements. Although this technique has lately undergone remarkable developments, its reliability is being questioned due to spectral distortions caused by biological tissues. In this work, how the use of bright Ag2 S nanoparticles featuring temperature-dependent fluorescence lifetime enables reliable and accurate measurement of the absolute temperature of the liver in mice subjected to lipopolysaccharide-induced inflammation is demonstrated. Beyond the remarkable thermal sensitivity (≈ 3% °C-1 around 37 °C) and thermal resolution obtained (smaller than 0.3 °C), the results included in this work set a blueprint for the development of new diagnostic procedures based on the use of intracorporeal temperature as a physiological indicator.

Spectral Shape Recovery and Analysis Via Data-driven Connections.

We introduce a novel learning-based method to recover shapes from their Laplacian spectra, based on establishing and exploring connections in a learned latent space. The core of our approach consists in a cycle-consistent module that maps between a learned latent space and sequences of eigenvalues. This module provides an efficient and effective link between the shape geometry, encoded in a latent vector, and its Laplacian spectrum. Our proposed data-driven approach replaces the need for ad-hoc regularizers required by prior methods, while providing more accurate results at a fraction of the computational cost. Moreover, these latent space connections enable novel applications for both analyzing and controlling the spectral properties of deformable shapes, especially in the context of a shape collection. Our learning model and the associated analysis apply without modifications across different dimensions (2D and 3D shapes alike), representations (meshes, contours and point clouds), nature of the latent space (generated by an auto-encoder or a parametric model), as well as across different shape classes, and admits arbitrary resolution of the input spectrum without affecting complexity. The increased flexibility allows us to address notoriously difficult tasks in 3D vision and geometry processing within a unified framework, including shape generation from spectrum, latent space exploration and analysis, mesh super-resolution, shape exploration, style transfer, spectrum estimation for point clouds, segmentation transfer and non-rigid shape matching. SUPPLEMENTARY INFORMATION: The online version supplementary material available at 10.1007/s11263-021-01492-6.

In Vivo Near-Infrared Imaging Using Ternary Selenide Semiconductor Nanoparticles with an Uncommon Crystal Structure.

The implementation of in vivo fluorescence imaging as a reliable diagnostic imaging modality at the clinical level is still far from reality. Plenty of work remains ahead to provide medical practitioners with solid proof of the potential advantages of this imaging technique. To do so, one of the key objectives is to better the optical performance of dedicated contrast agents, thus improving the resolution and penetration depth achievable. This direction is followed here and the use of a novel AgInSe2 nanoparticle-based contrast agent (nanocapsule) is reported for fluorescence imaging. The use of an Ag2 Se seeds-mediated synthesis method allows stabilizing an uncommon orthorhombic crystal structure, which endows the material with emission in the second biological window (1000-1400 nm), where deeper penetration in tissues is achieved. The nanocapsules, obtained via phospholipid-assisted encapsulation of the AgInSe2 nanoparticles, comply with the mandatory requisites for an imaging contrast agent-colloidal stability and negligible toxicity-and show superior brightness compared with widely used Ag2 S nanoparticles. Imaging experiments point to the great potential of the novel AgInSe2 -based nanocapsules for high-resolution, whole-body in vivo imaging. Their extended permanence time within blood vessels make them especially suitable for prolonged imaging of the cardiovascular system.

Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine.

OBJECTIVE: Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core symptoms. We apply support vector machine, a supervised machine learning method, in order to identify specific cortical thickness alterations in ASD subjects. METHODS: A sample of 76 subjects (9.5 ± 3.4 years old) has been selected, 40 diagnosed with ASD and 36 typically developed subjects. All children underwent a magnetic resonance imaging (MRI) examination; T1-MPRAGE sequences were analyzed to extract features for the characterization and parcellation of regions of interests (ROI); average cortical thickness (CT) has been measured for each ROI. For the classification process, the extracted features were used as input for a classifier to identify ASD subjects through a "learning by example" procedure; the features with best performance was then selected by "greedy forward-feature selection." Finally, this model underwent a leave-one-out cross-validation approach. RESULTS: From the training set of 68 ROIs, five ROIs reached accuracies of over 70%. After this phase, we used a recursive feature selection process in order to identify the eight features with the best accuracy (84.2%). CT resulted higher in ASD compared to controls in all the ROIs identified at the end of the process. CONCLUSION: We found increased CT in various brain regions in ASD subjects, confirming their role in the pathogenesis of this condition. Considering the brain development curve during ages, these changes in CT may normalize during development. Further validation on a larger sample is required.

Infrared-Emitting Multimodal Nanostructures for Controlled In Vivo Magnetic Hyperthermia.

Deliberate and local increase of the temperature within solid tumors represents an effective therapeutic approach. Thermal therapies embrace this concept leveraging the capability of some species to convert the absorbed energy into heat. To that end, magnetic hyperthermia (MHT) uses magnetic nanoparticles (MNPs) that can effectively dissipate the energy absorbed under alternating magnetic fields. However, MNPs fail to provide real-time thermal feedback with the risk of unwanted overheating and impeding on-the-fly adjustment of the therapeutic parameters. Localization of MNPs within a tissue in an accurate, rapid, and cost-effective way represents another challenge for increasing the efficacy of MHT. In this work, MNPs are combined with state-of-the-art infrared luminescent nanothermometers (LNTh; Ag2 S nanoparticles) in a nanocapsule that simultaneously overcomes these limitations. The novel optomagnetic nanocapsule acts as multimodal contrast agents for different imaging techniques (magnetic resonance, photoacoustic and near-infrared fluorescence imaging, optical and X-ray computed tomography). Most crucially, these nanocapsules provide accurate (0.2 °C resolution) and real-time subcutaneous thermal feedback during in vivo MHT, also enabling the attainment of thermal maps of the area of interest. These findings are a milestone on the road toward controlled magnetothermal therapies with minimal side effects.