Photoacoustic generation by a gold nanosphere: From linear to nonlinear thermoelastics in the long-pulse illumination regime

We investigate theoretically the photoacoustic generation by a gold nanosphere in water in the thermoelastic regime. Specifically, we consider the long-pulse illumination regime, in which the time for electron-phonon thermalisation can be neglected and photoacoustic wave generation arises solely from the thermo-elastic stress caused by the temperature increase of the nanosphere or its liquid environment. Photoacoustic signals are predicted computed based on the successive resolution of a thermal diffusion problem and a thermoelastic problem, taking into account the finite size of the gold nanosphere and the temperature-dependence of the thermal expansion coefficient of water. For sufficiently high illumination fluences, this temperature dependence yields a nonlinear relationship between the photoacoustic amplitude and the fluence. For nanosecond pulses in the linear regime, we show that more than 90 % of the emitted photoacoustic energy is generated in water, and the thickness of the generating layer around the particle scales close to the square root of the pulse duration. Our results demonstrate that the point-absorber model introduced by Calasso et al.[17] significantly overestimates the amplitude of photoacoustic waves in the nonlinear regime. We therefore provide quantitative estimates of a critical energy, defined as the absorbed energy required such that the nonlinear contribution is equal to that of the linear contribution. Our results suggest that the critical energy scales as the volume of water over which heat diffuses during the illumination pulse. Moreover, thermal nonlinearity is shown to be expected only for sufficiently high ultrasound frequency. Finally, we show that the relationship between the photoacoustic amplitude and the equilibrium temperature at sufficiently high fluence reflects the thermal diffusion at the nanoscale around the gold nanosphere.Comment: Published in Physical Review B, 16 pages, 14 figure

Author Correction: Federated learning enables big data for rare cancer boundary detection.

10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Federated Learning Enables Big Data for Rare Cancer Boundary Detection

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

Improved Halogenation of Methyl Aromatics and Methyl Heteroaromatics: Unexpected Reactivity of Tetrahalogeno-diphenylglycolurils

International audience1,3,4,6-Tetrachloro (TCDGU) and 1,3,4,6-tetrabromo-3α,6α-diphenylglycolurils smooth halogen oxidizers have been exploited in a new direction as reagents for free radical substitution toward some N-halosuccinimide nonreactive bis-heterocycles. An unexpected selectivity and reactivity were observed with methyl benzenes, methyl heterocycles, and methyl-bis-heterocycles of interest. A chemometric study has been performed to optimize five independent factors of the chlorination reaction with TCDGU. The predictive model was established either for the halogenation conversion and the ratio of monochlorination

An unprecedented 7-membered ring enamide cyclization through hypervalent iodine phenolic oxidation

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Application of Chiral Sulfinamides into Formation and Reduction of Sulfinylketimines to Obtain Valuable α-Chiral Primary Amines

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1,2-Additions on Chiral N-Sulfinylketimines: An Easy Access to Chiral α-Tertiary Amines

International audienceAbstract Chiral α-tertiary amines, a motif present in α,α-disubstituted α-amino acids, in a wide range of natural products, and many drugs and drug candidates, are important targets in organic chemistry. Among the possible strategies, 1,2-addition to chiral N-sulfinyl­ketimines is one of the best routes to form chiral α-tertiary amines with a high level of stereoselectivity. In this review, we focus first on the addition of organometallic reagents or other nucleophiles as enols or ylides to chiral N-sulfinylketimines. Then secondly we cover a selection of applications of these additions in the synthesis of valuable biologically active compounds. 1 Introduction 2 1,2-Addition Reaction Methodologies 2.1 Organolithium Reagent Additions 2.2 Grignard Additions 2.3 Organozinc Reagent Additions 2.4 Organoindium Reagent Additions 2.5 Organoboron Reagent Additions 2.6 Strecker Reactions 2.7 Palladium-Catalyzed Reactions 2.8 Enols, Enolates, and Other Deprotonated Reagent Additions 2.9 Ylide Additions 2.10 Heteroatom Nucleophiles 2.11 Miscellaneous Reactions 3 Applications to the Synthesis of Biologically Active Molecules 4 Conclusion

Multiaxial fatigue criteria applied to a polychoroprene rubber

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