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Background The aim to develop a highly stable near-infrared (NIR) photoinduced tumor therapy agent stems from its considerable potential for biological application. Due to its long wavelength, biological imaging exhibits a high signal-to-background ratio, deep tissue penetration and maximum permissible light power, which can minimize damage to an organism during photoinduced tumor therapy. Results A class of stable NIR-II fluorophores (NIR998, NIR1028, NIR980, NIR1030, and NIR1028-S) based on aza–boron–dipyrromethene (aza-BODIPY) dyes with donor–acceptor-donor structures have been rationally designed and synthesized by harnessing the steric relaxation effect and intramolecular photoinduced electron transfer (IPET). These fluorophores exhibit an intense range of NIR-II emission, large Stokes shift (≥ 100 nm), excellent photothermal conversion performance, and superior stability against photobleaching. Among the NIR-II fluorophores, NIR998 possesses better NIR-II emission and photothermal conversion performance. NIR998 nanoparticles (NIR998 NPs) can be encapsulated by liposomes. NIR998 NPs show superior stability in the presence of light, heat, and reactive oxygen nitrogen species than that of indocyanine green NPs, as well as a higher photothermal conversion ability (η = 50.5%) compared to other photothermal agents. Finally, under the guidance of photothermal imaging, NIR998 NPs have been proven to effectively eliminate tumors via their excellent photothermal conversion performance while presenting negligible cytotoxicity. Conclusions Utilizing IPET and the steric relaxation effect can effectively induce NIR-II emission of aza-BODIPY dyes. Stable NIR998 NPs have excellent photothermal conversion performance and negligible dark cytotoxicity, so they have the potential to act as photothermal agents in biological applications.

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This paper reports the complete chloroplast genome of Achnatherum inebrians, a poisonous herb that is widely distributed in the rangelands of Northern China. The genome is 137,714 bp in total, and consists of a large single-copy (LSC, 81,758 bp) and small single-copy (SSC, 12,682 bp) region separated by a pair of inverted repeats (IRs, 21,637 bp). The genome contains 130 genes, including 84 protein-coding genes, 38 tRNA genes and 8 ribosomal RNA genes, and the GC content is 36.17%. We subsequently performed comparative analysis of complete genomes from A.inebrians and other Poaceae related species from GenBank. Thirty-eight simple sequence repeats (SSRs) were identified, further demonstrating rapid evolution in Poaceae. Finally, the phylogenetic trees of 37 species of Poaceae and two species of Amaranthaceae were constructed by using Maximum likelihood (ML) and Bayesian Inference (BI) methods, based on the genes of the complete chloroplast genome. We identified hotspots which can be used as molecular markers and barcodes for phylogenetic analysis as well as for species identification. Phylogenetic analysis indicated that A. inebrians is a member of the genus Stipa rather than Achnatherum.

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Hardware security primitives that preserve secrets are playing a crucial role in the Internet-of-Things (IoT) era. Existing physical unclonable function (PUF) instantiations, exploiting static randomness, generate challenge-response pairings (CRPs) to produce unique security keys that can be used to authenticate devices linked to the IoT. Reconfigurable PUFs (RPUFs) with dynamically refreshable CRPs can enhance the security and robustness of conventional PUFs. The in-plane current-driven perpendicular polarized nanomagnet switching via spin-orbit torque (SOT) possesses great potential for application to memory and logic, as the write-current path is separate from the read-current path, which naturally resolves the write-read interference. However, the stochastic switching of perpendicular magnetization, without an additional symmetry-breaking field, would significantly hinder the technological viability of commercial implementations. Here, we report an initialization-free physical RPUF implemented by SOT-induced stochastic switching of perpendicularly magnetized Ta/CoFeB/MgO nanodevices. Using a 15 × 15 nanomagnet array, we experimentally demonstrate a security primitive that offers a near-ideal 50% uniqueness over 100 reconfiguration cycles, as well as a low correlation coefficient between every two reconfiguration cycles. Our results show that current-induced nanomagnets switching paves the way for developing highly reliable and energy-efficient reconfigurable cryptographic primitives with a smaller footprint.

Hardware implementations of Artificial Neural Networks (ANNs) using conventional binary arithmetic units are computationally expensive and energy-intensive together with large area footprints. Stochastic computing (SC) is an unconventional computing paradigm that operates on stochastic bit streams. It can offer low-power and area-efficient hardware implementations and has shown promising results when applied to ANN hardware circuits. SC relies on stochastic number generators (SNGs) to map input binary numbers to stochastic bit streams. The SNGs are conventionally implemented using random number generators (RNGs) and comparators. Linear feedback shifted registers (LFSRs) are typically used as the RNGs, which need far more area and power than the SC core, counteracting the latter's main advantages. To mitigate this problem, in this Letter, RNGs employing Spin–Orbit Torque (SOT)-induced stochastic switching of perpendicularly magnetized Ta/CoFeB/MgO nanodevices have been proposed. Furthermore, the SOT true random number generator (TRNG) is integrated with the simple CMOS stochastic computing circuits to perform a stochastic artificial neural network. To further optimize power and area efficiency, a fully parallel architecture and TRNG-sharing scheme are presented. The proposed stochastic ANN using the SOT-based TRNG obtains a negligible inference accuracy loss, compared with the binary version, and achieves 9× and 25× improvement in terms of area and power, respectively, compared with the ANN using LFSRs.