Increase of OH radical yields due to the decomposition of hydrogen peroxide by gold nanoparticles under X-ray irradiation.

We elucidate the decomposition mechanism of hydrogen peroxide, which is formed by water radiolysis, by gold nanoparticles (GNPs) under X-ray irradiation. The variations in yields of hydrogen peroxide generated in the presence of GNPs are evaluated using the Ghormley technique. The increase of yields of OH radicals has been quantified using Ampliflu® Red solutions. Almost all hydrogen peroxide generated by irradiation of <25 Gy is decomposed by GNPs, while the yield of OH radicals increases by 1.6 times. The amount of OH radicals thus obtained is almost equivalent to that of the decomposed hydrogen peroxide. The decomposition of hydrogen peroxide is an essential reaction to produce additional OH radicals efficiently in the vicinity of GNPs.

Quantitative, precise and multi-wavelength evaluation of the light-to-heat conversion efficiency for nanoparticular photothermal agents with calibrated photoacoustic spectroscopy.

Biomedical photothermal therapy with optical nanoparticles is based on the conversion of optical energy into heat through three steps: optical absorption, thermal conversion of the absorbed energy and heat transfer to the surrounding medium. The light-to-heat conversion efficiency (LHCE) has become one of the main metrics to quantitatively characterize the last two steps and evaluate the merit of nanoparticules for photothermal therapy. The estimation of the LHCE is mostly performed by monitoring the temperature evolution of a solution under laser irradiation. However, this estimation strongly depends on the experimental set-up and the heat balance model used. We demonstrate here, theoretically and experimentally, that the LHCE at multiple wavelengths can be efficiently and directly determined, without the use of models, by calibrated photoacoustic spectroscopy. The method was validated using already characterized colloidal suspensions of silver sulfide nanoparticles and maghemite nanoflowers and an uncertainty of 3 to 7% was estimated for the LHCE determination. Photoacoustic spectroscopy provides a new, precise and robust method of analysis of the photothermal capabilities of aqueous solutions of nanoagents.

PeakForce AFM Analysis Enhanced with Model Reduction Techniques.

PeakForce quantitative nanomechanical AFM mode (PF-QNM) is a popular AFM technique designed to measure multiple mechanical features (e.g., adhesion, apparent modulus, etc.) simultaneously at the exact same spatial coordinates with a robust scanning frequency. This paper proposes compressing the initial high-dimensional dataset obtained from the PeakForce AFM mode into a subset of much lower dimensionality by a sequence of proper orthogonal decomposition (POD) reduction and subsequent machine learning on the low-dimensionality data. A substantial reduction in user dependency and subjectivity of the extracted results is obtained. The underlying parameters, or "state variables", governing the mechanical response can be easily extracted from the latter using various machine learning techniques. Two samples are investigated to illustrate the proposed procedure (i) a polystyrene film with low-density polyethylene nano-pods and (ii) a PDMS film with carbon-iron particles. The heterogeneity of material, as well as the sharp variation in topography, make the segmentation challenging. Nonetheless, the underlying parameters describing the mechanical response naturally offer a compact representation allowing for a more straightforward interpretation of the high-dimensional force-indentation data in terms of the nature (and proportion) of phases, interfaces, or topography. Finally, those techniques come with a low processing time cost and do not require a prior mechanical model.

Three-phase material mapping with incomplete X-ray diffraction spectral information.

An equiatomic nickel-titanium shape-memory alloy specimen subjected to a uniaxial tensile load undergoes a two-step phase transformation under stress, from austenite (A) to a rhombohedral phase (R) and further to martensite (M) variants. The pseudo-elasticity that goes accompanies the phase transformation induces spatial inhomogeneity. To unravel the spatial distribution of the phases, in situ X-ray diffraction analyses are performed while the sample is under tensile load. However, the diffraction spectra of the R phase, as well as the extent of potential martensite detwinning, are not known. A novel algorithm, based on a proper orthogonal decomposition and incorporating inequality constraints, is proposed in order to map out the different phases and simultaneously yield the missing diffraction spectral information. An experimental case study illustrates the methodology.

Evaluation of Radiosensitization and Cytokine Modulation by Differentially PEGylated Gold Nanoparticles in Glioblastoma Cells.

Glioblastoma (GBM) is known as the most aggressive type of malignant brain tumour, with an extremely poor prognosis of approximately 12 months following standard-of-care treatment with surgical resection, radiotherapy (RT), and temozolomide treatment. Novel RT-drug combinations are urgently needed to improve patient outcomes. Gold nanoparticles (GNPs) have demonstrated significant preclinical potential as radiosensitizers due to their unique physicochemical properties and their ability to pass the blood-brain barrier. The modification of GNP surface coatings with poly(ethylene) glycol (PEG) confers several therapeutic advantages including immune avoidance and improved cellular localisation. This study aimed to characterise both the radiosensitizing and immunomodulatory properties of differentially PEGylated GNPs in GBM cells in vitro. Two GBM cell lines were used, U-87 MG and U-251 MG. The radiobiological response was evaluated by clonogenic assay, immunofluorescent staining of 53BP1 foci, and flow cytometry. Changes in the cytokine expression levels were quantified by cytokine arrays. PEGylation improved the radiobiological efficacy, with double-strand break induction being identified as an underlying mechanism. PEGylated GNPs also caused the greatest boost in RT immunogenicity, with radiosensitization correlating with a greater upregulation of inflammatory cytokines. These findings demonstrate the radiosensitizing and immunostimulatory potential of ID11 and ID12 as candidates for RT-drug combination in future GBM preclinical investigations.

Explainable COVID-19 Detection Based on Chest X-rays Using an End-to-End RegNet Architecture.

COVID-19,which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is one of the worst pandemics in recent history. The identification of patients suspected to be infected with COVID-19 is becoming crucial to reduce its spread. We aimed to validate and test a deep learning model to detect COVID-19 based on chest X-rays. The recent deep convolutional neural network (CNN) RegNetX032 was adapted for detecting COVID-19 from chest X-ray (CXR) images using polymerase chain reaction (RT-PCR) as a reference. The model was customized and trained on five datasets containing more than 15,000 CXR images (including 4148COVID-19-positive cases) and then tested on 321 images (150 COVID-19-positive) from Montfort Hospital. Twenty percent of the data from the five datasets were used as validation data for hyperparameter optimization. Each CXR image was processed by the model to detect COVID-19. Multi-binary classifications were proposed, such as: COVID-19 vs. normal, COVID-19 + pneumonia vs. normal, and pneumonia vs. normal. The performance results were based on the area under the curve (AUC), sensitivity, and specificity. In addition, an explainability model was developed that demonstrated the high performance and high generalization degree of the proposed model in detecting and highlighting the signs of the disease. The fine-tuned RegNetX032 model achieved an overall accuracy score of 96.0%, with an AUC score of 99.1%. The model showed a superior sensitivity of 98.0% in detecting signs from CXR images of COVID-19 patients, and a specificity of 93.0% in detecting healthy CXR images. A second scenario compared COVID-19 + pneumonia vs. normal (healthy X-ray) patients. The model achieved an overall score of 99.1% (AUC) with a sensitivity of 96.0% and specificity of 93.0% on the Montfort dataset. For the validation set, the model achieved an average accuracy of 98.6%, an AUC score of 98.0%, a sensitivity of 98.0%, and a specificity of 96.0% for detection (COVID-19 patients vs. healthy patients). The second scenario compared COVID-19 + pneumonia vs. normal patients. The model achieved an overall score of 98.8% (AUC) with a sensitivity of 97.0% and a specificity of 96.0%. This robust deep learning model demonstrated excellent performance in detecting COVID-19 from chest X-rays. This model could be used to automate the detection of COVID-19 and improve decision making for patient triage and isolation in hospital settings. This could also be used as a complementary aid for radiologists or clinicians when differentiating to make smart decisions.

Radiosensitization with Gadolinium Chelate-Coated Gold Nanoparticles Prevents Aggressiveness and Invasiveness in Glioblastoma.

Purpose: This study aimed to evaluate the radiosensitizing potential of Au@DTDTPA(Gd) nanoparticles when combined with conventional external X-ray irradiation (RT) to treat GBM. Methods: Complementary biological models based on U87 spheroids including conventional 3D invasion assay, organotypic brain slice cultures, chronic cranial window model were implemented to investigate the impact of RT treatments (10 Gy single dose; 5×2 Gy or 2×5 Gy) combined with Au@DTDTPA(Gd) nanoparticles on tumor progression. The main tumor mass and its infiltrative area were analyzed. This work focused on the invading cancer cells after irradiation and their viability, aggressiveness, and recurrence potential were assessed using mitotic catastrophe quantification, MMP secretion analysis and neurosphere assays, respectively. Results: In vitro clonogenic assays showed that Au@DTDTPA(Gd) nanoparticles exerted a radiosensitizing effect on U87 cells, and in vivo experiments suggested a benefit of the combined treatment "RT 2×5 Gy + Au@DTDTPA(Gd)" compared to RT alone. Invasion assays revealed that invasion distance tended to increase after irradiation alone, while the combined treatments were able to significantly reduce tumor invasion. Monitoring of U87-GFP tumor progression using organotypic cultures or intracerebral grafts confirmed the anti-invasive effect of Au@DTDTPA(Gd) on irradiated spheroids. Most importantly, the combination of Au@DTDTPA(Gd) with irradiation drastically reduced the number, the viability and the aggressiveness of tumor cells able to escape from U87 spheroids. Notably, the combined treatments significantly reduced the proportion of escaped cells with stem-like features that could cause recurrence. Conclusion: Combining Au@DTDTPA(Gd) nanoparticles and X-ray radiotherapy appears as an attractive therapeutic strategy to decrease number, viability and aggressiveness of tumor cells that escape and can invade the surrounding brain parenchyma. Hence, Au@DTDTPA(Gd)-enhanced radiotherapy opens up interesting perspectives for glioblastoma treatment.

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.

Insights into a dual-phase steel microstructure using EBSD and image-processing-based workflow.

Quantitative metallography to understand the morphology of different crystallographic phases in a material often rests on the segmentation and classification of electron backscatter diffraction (EBSD) maps. Image analysis offers rich toolboxes to perform such tasks based on 'scalar' images. Embracing the entire wealth of information provided by crystallography, operations such as erosion, dilation, interpolation, smoothing and segmentation require generalizations to do justice to the very nature of crystal orientations (e.g. preserving properties like frame indifference). The present study gives such extensions based on quaternion representation of crystal orientations. A dual-phase stainless steel specimen is used to illustrate the different steps of such a procedure.

In situ tomographic study of a 3D-woven SiC/SiC composite part subjected to severe thermo-mechanical loads.

A high-temperature multi-axial test is carried out to characterize the thermo-mechanical behaviour of a 3D-woven SiC/SiC composite aeronautical part under loads representative of operating conditions. The sample is L-shaped and cut out from the part. It is subjected to severe thermal gradients and a superimposed mechanical load that progressively increases up to the first damage. The sample shape and its associated microstructure, the heterogeneity of the stress field and the limited accessibility to regions susceptible to damage require non-contact imaging modalities. An in situ experiment, conducted with a dedicated testing machine at the SOLEIL synchrotron facility, provides the sample microstructure from computed micro-tomographic imaging and thermal loads from infrared thermography. Experimental constraints lead to non-ideal acquisition conditions for both measurement modalities. This article details the procedure of correcting artefacts to use the volumes for quantitative exploitation (i.e. full-field measurement, model validation and identification). After proper processing, despite its complexity, the in situ experiment provides high-quality data about a part under realistic operating conditions. The influence of the mesostructure on fracture phenomena can be inferred from the tomography in the damaged state. Experiments show that the localization of damage initiation is driven by the geometry, while the woven structure moderates the crack propagation. This study widens the scope of in situ thermo-mechanical experiments to more complex loading states, closer to in-service conditions.

Bridging steady-state and stick-slip fracture propagation in glassy polymers.

Both an experimental and a theoretical investigation of fracture propagation mechanisms acting at the process zone scale in glassy polymers are presented. The main aim is to establish a common modeling for different kinds of glassy polymers presenting either steady-state fracture propagation or stick-slip fracture propagation or both, depending on loading conditions and sample shapes. From the experimental point of view, new insights are provided by the in situ AFM measurements of viscoplastic strain fields acting within the micrometric process zone in a brittle epoxy resin, which highlight an extremely slow unexpected steady-state regime with finite plastic strains of about 30% around a blunt crack tip, accompanied by propagating shear lips. From the theoretical point of view, we apply to glassy polymers some recently developed models for describing soft dissipative fracture that are pertinent with the observed finite strains. We propose a unified modeling of fracture energy for both the steady-state and stick-slip fracture propagation based on the evaluation of energy dissipation density at a characteristic strain rate induced in the process zone by a competition between the crack propagation velocity and the macroscopic sample loading rate.

Quantifying Non-Stationarity with Information Theory.

We introduce an index based on information theory to quantify the stationarity of a stochastic process. The index compares on the one hand the information contained in the increment at the time scale τ of the process at time t with, on the other hand, the extra information in the variable at time t that is not present at time t-τ. By varying the scale τ, the index can explore a full range of scales. We thus obtain a multi-scale quantity that is not restricted to the first two moments of the density distribution, nor to the covariance, but that probes the complete dependences in the process. This index indeed provides a measure of the regularity of the process at a given scale. Not only is this index able to indicate whether a realization of the process is stationary, but its evolution across scales also indicates how rough and non-stationary it is. We show how the index behaves for various synthetic processes proposed to model fluid turbulence, as well as on experimental fluid turbulence measurements.

Two step promotion of a hot tumor immune environment by gold decorated iron oxide nanoflowers and light-triggered mild hyperthermia.

Nanoparticle-mediated photothermal therapy (PTT) is an emerging modality to treat tumors with both spatial and temporal control provided by light activation. Gold decorated iron oxide nanoflowers (GIONF) are good candidates for PTT due to their biocompatibility, biodegradability and light-to-heat conversion. Profound changes in the tumor immune environment might be early induced by the gold and iron oxide metallic agents in addition to the photothermal effects. This study aims to elucidate the outcome of GIONF on their own, and of GIONF-induced mild hyperthermia in the tumor immune infiltrate in a murine model of triple negative breast cancer. First we explored the effects of 24 h GIONF exposure on bone-marrow derived macrophages (BMDM), revealing significant effects on the BMDM phenotype and secretion, 6 days post-incubation, with important downregulation of several cytokines and MHCII expression, predominantly towards a pro-inflammatory response. Intratumoral administration of GIONF promoted an increase in monocyte recruitment at day 1 post-administration, shifting towards a pro-inflammatory anti-tumor microenvironment with lower Treg population and a 4 fold lower CD4/CD8 ratio compared to the control at day 12. On top of the GIONF effects, mild hyperthermia (43 °C for 15 min), although it does not induce significant changes in tumor growth, resulted in an additional increase of CD8+ T lymphocytes and pro-inflammatory cytokines. The combination of a timely controlled immune response to GIONF and to mild hyperthermia could be used as a remotely triggered adjuvant treatment to immunotherapy approaches at the best favorable time-window.

Projection-based dynamic tomography.

Objective. This paper proposes a 4D dynamic tomography framework that allows a moving sample to be imaged in a tomograph as well as the associated space-time kinematics to be measured with nothing more than a single conventional x-ray scan.Approach. The method exploits the consistency of the projection/reconstruction operations through a multi-scale procedure. The procedure is composed of two main parts solved alternatively: a motion-compensated reconstruction algorithm and a projection-based measurement procedure that estimates the displacement field directly on each projection.Main results. The method is applied to two studies: a numerical simulation of breathing from chest computed tomography (4D-CT) and a clinical cone-beam CT of a breathing patient acquired for image guidance of radiotherapy. The reconstructed volume, initially blurred by the motion, is cleaned from motion artifacts.Significance. Applying the proposed approach results in an improved reconstruction quality showing sharper edges and finer details.

Distance to Healthy Metabolic and Cardiovascular Dynamics From Fetal Heart Rate Scale-Dependent Features in Pregnant Sheep Model of Human Labor Predicts the Evolution of Acidemia and Cardiovascular Decompensation.

The overarching goal of the present work is to contribute to the understanding of the relations between fetal heart rate (FHR) temporal dynamics and the well-being of the fetus, notably in terms of predicting the evolution of lactate, pH and cardiovascular decompensation (CVD). It makes uses of an established animal model of human labor, where 14 near-term ovine fetuses subjected to umbilical cord occlusions (UCO) were instrumented to permit regular intermittent measurements of metabolites lactate and base excess, pH, and continuous recording of electrocardiogram (ECG) and systemic arterial blood pressure (to identify CVD) during UCO. ECG-derived FHR was digitized at the sampling rate of 1,000 Hz and resampled to 4 Hz, as used in clinical routine. We focused on four FHR variability features which are tunable to temporal scales of FHR dynamics, robustly computable from FHR sampled at 4 Hz and within short-time sliding windows, hence permitting a time-dependent, or local, analysis of FHR which helps dealing with signal noise. Results show the sensitivity of the proposed features for early detection of CVD, correlation to metabolites and pH, useful for early acidosis detection and the importance of coarse time scales (2.5-8 s) which are not disturbed by the low FHR sampling rate. Further, we introduce the performance of an individualized self-referencing metric of the distance to healthy state, based on a combination of the four features. We demonstrate that this novel metric, applied to clinically available FHR temporal dynamics alone, accurately predicts the time occurrence of CVD which heralds a clinically significant degradation of the fetal health reserve to tolerate the trial of labor.

Characterization and biodistribution of Au nanoparticles loaded in PLGA nanocarriers using an original encapsulation process.

Due to their imaging and radiosensitizing properties, ultrasmall gadolinium chelate-coated gold nanoparticles (AuNP) represent a promising approach in the diagnosis and the treatment of tumors. However, their poor pharmacokinetic profile, especially their rapid renal clearance prevents from an efficient exploitation of their potential for medical applications. The present study focuses on a strategy which resides in the encapsulation of AuNP in large polymeric NP to avoid the glomerular filtration and then to prolong the vascular residence time. An original encapsulation procedure using the polyethyleneimine (PEI) was set up to electrostatically entrap AuNP in biodegradable poly(lactic-co-glycolic acid) (PLGA) and polyethylene glycol -PLGA (PLGA-PEG) NP. Hydrodynamic diameters of NP were dependent of the PEI/Au ratio and comprised between 115 and 196 nm for ratios equal or superior to 4. Encapsulation yield was close to 90 % whereas no loading was observed without PEI. No toxicity was observed after 24 h exposure in hepatocyte cell-lines. Entrapement of AuNP in polymeric nanocarriers facilitated the passive uptake in cancer cells after only 2 h incubation. In healthy rat, the encapsulation allowed increasing the gold concentration in the blood within the first hour after intravenous administration. Polymeric nanoparticles were sequestered in the liver and the spleen rather than the kidneys. T1-weighted magnetic resonance demonstrated that encapsulation process did not alter the contrast agent properties of gadolinium. The encapsulation of the gold nanoparticles in PLGA particles paves the way to innovative imaging-guided anticancer therapies in personalized medicine.

The detrimental invasiveness of glioma cells controlled by gadolinium chelate-coated gold nanoparticles.

Glioblastoma are characterized by an invasive phenotype, which is thought to be responsible for recurrences and the short overall survival of patients. In the last decade, the promising potential of ultrasmall gadolinium chelate-coated gold nanoparticles (namely Au@DTDTPA(Gd)) was evidenced for image-guided radiotherapy in brain tumors. Considering the threat posed by invasiveness properties of glioma cells, we were interested in further investigating the biological effects of Au@DTDTPA(Gd) by examining their impact on GBM cell migration and invasion. In our work, exposure of U251 glioma cells to Au@DTDTPA(Gd) led to high accumulation of gold nanoparticles, that were mainly diffusely distributed in the cytoplasm of the tumor cells. Experiments pointed out a significant decrease in glioma cell invasiveness when exposed to nanoparticles. As the proteolysis activities were not directly affected by the intracytoplasmic accumulation of Au@DTDTPA(Gd), the anti-invasive effect cannot be attributed to matrix remodeling impairment. Rather, Au@DTDTPA(Gd) nanoparticles affected the intrinsic biomechanical properties of U251 glioma cells, such as cell stiffness, adhesion and generated traction forces, and significantly reduced the formation of protrusions, thus exerting an inhibitory effect on their migration capacities. Consistently, analysis of talin-1 expression and membrane expression of beta 1 integrin evoke the stabilization of focal adhesion plaques in the presence of nanoparticles. Taken together, our results highlight the interest in Au@DTDTPA(Gd) nanoparticles for the therapeutic management of astrocytic tumors, not only as a radio-enhancing agent but also by reducing the invasive potential of glioma cells.

Principal image decomposition for multi-detector backscatter electron topography reconstruction.

Scanning Electron Microscopes (SEMs) often generate images with a shaded appearance which gives a natural 3D impression. Ergo, quite a few methods to reconstruct the 3D surface topography from these using shape-from-shading methods are available in the literature. Here, a novel approach is discussed which uses BackScatter Electron (BSE) images from multiple detectors to reconstruct the topography. Classically, algorithms exist which resort to a quad-BSE detector setup. However, other detector configurations are often found in SEMs. A set of images of these non-conforming detectors still contains enough information to allow for reconstruction, but requires a more general algorithm to do so. This article discusses a method based on a modal decomposition of the principal image components. The resulting method is shown to be efficient and independent of the number of detectors or their orientation. In fact, the orientation is identified as part of the algorithm and thus requires very little calibration.