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The phosphate salt of octaaminotetraphenylene (OATP), [(H4OATP4+)(H2PO4–)4], was prepared. Single crystals were isolated with a crystal formula of (H4OATP4+)(H2PO4–)4(H3PO4)0.25·2.5H2O, whereas the powder sample at 300 K formed an amorphous salt of (H4OATP4+)(H2PO4–)4.0·nH2O with n= 1–2. In the anhydrous solids (n= 0), the formation of a hydrogen-bonding network of H2PO4–anions and the dielectric relaxation associated with the motional freedom of H2PO4–were observed. Adsorption–desorption isotherms of H2O at 298 K showed the transformation between anhydrous amorphous (H4OATP4+)(H2PO4–)4and hydrous crystalline (H4OATP4+)(H2PO4–)4·6H2O, and the proton conductivity increased by 2 orders of magnitude after H2O adsorption. The proton conductivity of hydrous salt reached 7.58 × 10–5S cm–1. The cation–anion salt in the amorphous–crystalline transformation exhibited proton conductivity switching phenomena with an ON/OFF ratio of about 100 upon H2O adsorption–desorption.

The family lives of children and their early childhood development outcomes are attributable to the level of socio-economic disadvantage and relative isolation. This study aims to investigate how the disadvantage of the local area (i.e., socio-economic indexes for areas (SEIFA)) and the remoteness (i.e., accessibility/remoteness index of Australia (ARIA)) contribute to improved prevalence estimates of child development vulnerability in statistical areas level 3 (SA3) and 4 (SA4) across Australia. Data from the 2018 Australian Early Development Census (AEDC) has been used. The study included 308,953 children involved in the AEDC 2018 where one-in-ten of them were considered to be developmentally vulnerable, nationally. We developed models in a hierarchical Bayesian framework at the SA3 level using SEIFA and ARIA indices as covariates to account for spatial and unobserved heterogeneity. The performances of developed models are examined based on the consistency at SA3, SA4, and state level. The results reveal that SEIFA makes a significant contribution to explaining the spatial variation in childhood development vulnerability across small domains in Australia. Further, the inclusion of the ARIA score improves the model performance and provides better accuracy, particularly in remote and very remote regions. In these regions, the spatial model fails to distinguish the remoteness characteristics. The chosen non-spatial model accounting for heterogeneity at higher hierarchies performs best. The utilization of socio-economic disadvantage and geographic remoteness of the finer level domains helps to explain the geographic variation in child development vulnerability, particularly in sparsely populated remote regions in Australia.

With the advancement of modern science and technology, large scientific facilities are increasingly oriented toward demand and application, and can be used for basic research as well as serving multiple disciplines. Developing large scientific facilities and related analytical technologies enhances understanding of large scientific facilities and popularizes their application in research across multiple disciplines. The combination of light or neutron sources from large scientific facilities and advanced analytical technologies can be achieved for materials structure information, dynamics study of chemical reactions, high dissociation of biomolecules, 3D visualization of energy materials or biological samples, etc. We first introduce the progress of domestic large scientific facilities of synchrotron radiation (SR) and free electron lasers (FELs) with different wavelengths and neutron sources. We further discuss the comparison between Chinese and typical foreign facilities in X-ray radiation from X-ray tubes, synchrotrons, X-ray FELs, and neutron sources based on physical parameters of light and neutron sources. In addition, we focus on the technological progress and perspectives combined with advanced X-ray radiation and neutron sources of large scientific facilities in China, especially in the nanoscience fields of energy catalysis and biological science. We hope that this roadmap will provide references on technology and methods to experimental users, as well as prospects for future development of technologies based on large research infrastructure facilities. Comprehensive studies and guidelines for basic research to practical application in various disciplines can be made with the assistance of large scientific facilities.

Selenosulfones, as pivotal pharmaceutical molecule frameworks, have become a research hotspot in modern organic synthesis due to their vital need for efficient preparation. Herein, we have developed an iron-catalyzed four-component controllable radical tandem reaction of allenes involving cycloketone oxime esters, 1,4-diazabicyclo[2.2.2]octane bis(sulfur dioxide) adduct (DABSO), and diphenyl diselenides for the synthesis of complex selenosulfones. This is the first case of achieving the 1,2-selenosulfonylation of allenes via a radical process, wherein precise control of radical rates and polarity matching enhance high regioselective conversion. The reaction conditions are ecofriendly and mild with step-efficiency by forming two new C–S bonds and one C–Se bond in one pot. Moreover, the 1,2-selenosulfonylation of allenes can be achieved by replacing cycloketone oxime esters with aryldiazonium tetrafluoroborates in this system.

Objective: The Jiangmen Underground Neutrino Observatory, which is currently being constructed in South China, will be a cutting-edge liquid scintillator detector for neutrino physics in the coming decade. The read-out electronics will be installed in close proximity to the large photomultipliers and directly inside the water pool surrounding the detector. Once installed, these electronics will not be accessible for repair or replacement; therefore, ensuring their reliability is of utmost importance. A crucial aspect of this reliability analysis involves evaluating the failure rate of custom-designed analog-to-digital converter and front-end chips used in underwater read-out electronics. Methods: The Arrhenius model shall be utilized to compute the reliability failure rate value. During ageing, the ambient temperature of the setup system was set at 115 °C. The high-gain and low-gain output channels were chosen as references for detecting failures in the tested sample for front-end chips of Jiangmen Underground Neutrino Observatory, while for analog-to-digital converters, effective number of bits are considered as reference parameters. Results: After ageing, all chips were re-measured. The ADC and FEC tests revealed no failures. As a result, the upper limit for the failure rate of front-end chips is 0.43 failures in time, and the upper limit for analog-to-digital converters is 0.42 failures in time at 30 °C. Conclusion: The reliability test result shows that custom-designed chips can be used in underwater read-out electronics of Jiangmen Underground Neutrino Observatory.

There is growing acknowledgment that the properties of the electrochemical interfaces play an increasingly pivotal role in improving the performance of the hydrogen evolution reaction (HER). Here, we present, for the first time, direct dynamic spectral evidence illustrating the impact of the interaction between interfacial water molecules and adsorbed hydroxyl species (OHad) on the HER properties of Ni(OH)2using Au/core-Ni(OH)2/shell nanoparticle-enhanced Raman spectroscopy. Notably, our findings highlight that the interaction between OHadand interfacial water molecules promotes the formation of weakly hydrogen-bonded water, fostering an environment conducive to improving the HER performance. Furthermore, the participation of OHadin the reaction is substantiated by the observed deprotonation step of Au@2 nm Ni(OH)2during the HER process. This phenomenon is corroborated by the phase transition of Ni(OH)2to NiO, as verified through Raman and X-ray photoelectron spectroscopy. The significant redshift in the OH-stretching frequency of water molecules during the phase transition confirms that surface OHaddisrupts the hydrogen-bond network of interfacial water molecules. Through manipulation of the shell thickness of Au@Ni(OH)2, we additionally validate the interaction between OHadand interfacial water molecules. In summary, our insights emphasize the potential of electrochemical interfacial engineering as a potent approach to enhance electrocatalytic performance.

Ammonia, a feedstock platform for fertilizer and pharmaceutical production, is regarded as a zero-carbon energy carrier. The electrochemical synthesis of ammonia, powered by clean and renewable electricity, has garnered increased attention as an alternative to the Haber-Bosch process. Very recently, single-atom catalysts (SACs) have become highly effective electrocatalysts for such electrochemical transformation, where the isolated metal sites ensure the high atomic utilization efficiency as well as the prevention of nitrogen-nitrogen coupling. In this review, we focus on the recent progress of single-atom catalysts in electrochemical ammonia synthesis and briefly introduce nitrogen cycles in both natural and artificial ecosystems, followed by a discussion of catalyst design by theoretical and experimental methods. Synthesis routes from different nitrogen sources, including dinitrogen (N2) and nitrogen oxides (NOx), are also highlighted. Besides, the catalysis dynamics as an indispensable section is presented and discussed in-depth. Finally, we tackle challenges and offer perspectives, aspiring to provide insightful guidance for researchers in this community striving for advanced ammonia electrosynthesis.

Mimicking the function of human skin is highly desired for electronic skins (e-skins) to perceive the tactile stimuli by both their intensity and spatial location. The common strategy using pixelated pressure sensor arrays and display panels greatly increases the device complexity and compromises the portability of e-skins. Herein, we tackled this challenge by developing a user-interactive iontronic skin that simultaneously achieves electrical pressure sensing and on-site, nonpixelated pressure mapping visualization. By merging the electrochromic and iontronic pressure sensing units into an integrated multilayer device, the interlayer charge transfer is regulated by applied pressure, which induces both color shifting and a capacitance change. The iontronic skin could visualize the trajectory of dynamic forces and reveal both the intensity and spatial information on various human activities. The integration of dual-mode pressure responsivity, together with the scalable fabrication and explicit signal output, makes the iontronic skin highly promising in biosignal monitoring and human–machine interaction.

Metal-nitrogen-carbon single-atom catalysts (M-N-C SACs) have emerged as a highly promising material for ammonia synthesis from electrocatalytic nitrate reduction due to their isolated metal site and capacity to prevent the N–N coupling. However, understanding the structure-activity relationship at molecular level remains challenging because of the inhomogeneous MNxstructure presented in current synthesized M-N-C catalysts. In this study, we utilized metal phthalocyanine (MPc) as a model platform catalyst containing a uniform and well-defined MN4center to unravel their intrinsic activity tendency toward ammonia synthesis from nitrate reduction, both experimentally and theoretically. Our experimental results exhibit a significant activity difference for ammonia production in the order of FeN4> CuN4> NiN4> MnN4> CoN4> ZnN4, and among which the FeN4site delivers much higher faradic efficiency and the highest turnover frequency of 83.3% and 4395.2 h–1at –1.0 V vs. RHE, respectively. Density-functional theory calculations indicates that, compared to CoN4and MnN4, the FeN4site not only has appropriate adsorption strength for NOxintermediate species, but also has certain inhibitory effects on hydrogen evolution reaction process. These findings provide systematic and reliable guidance for catalyst synthesis toward nitrate reduction to NH3from both the experimental and computational perspectives.

Natural products are a rich resource for the discovery of innovative drugs. Microbial cocultivation enables discovery of novel natural products through tandem enzymatic catalysis between different fungi. In this study, Monascus purpureus, as a food fermentation strain capable of producing abundant natural products, was chosen as an example of a cocultivation pair strain. Cocultivation screening revealed that M. purpureusand Aspergillus oryzaeled to the production of two novel cyclohexyl-furans, Monaspins A and B. Optimization of the cocultivation mode and media enhanced the production of Monaspins A and B to 1.2 and 0.8 mg/L, respectively. Monaspins A and B were structurally elucidated by HR-ESI-MS and NMR. Furthermore, Monaspin B displayed potent antiproliferative activity against the leukemic HL-60 cell line by inducing apoptosis, with a half-maximal inhibitory concentration (IC50) of 160 nM. Moreover, in a mouse leukemia model, Monaspin B exhibited a promising in vivo antileukemic effect by reducing white blood cell, lymphocyte, and neutrophil counts. Collectively, these results indicate that Monaspin B is a promising candidate agent for leukemia therapy.

Starting from the seminal work of Fully Convolutional Networks (FCN), there has been significant progress on semantic segmentation. However, deep learning models often require large amounts of pixelwise annotations to train accurate and robust models. Given the prohibitively expensive annotation cost of segmentation masks, we introduce a self-training framework in this paper to leverage pseudo labels generated from unlabeled data. In order to handle the data imbalance problem of semantic segmentation, we propose a centroid sampling strategy to uniformly select training samples from every class within each epoch. We also introduce a fast training schedule to alleviate the computational burden. This enables us to explore the usage of large amounts of pseudo labels. Our Centroid Sampling based Self-Training framework (CSST) achieves state-of-the-art results on Cityscapes and CamVid datasets. On PASCAL VOC 2012 test set, our models trained with the original train set even outperform the same models trained on the much bigger augmented train set. This indicates the effectiveness of CSST when there are fewer annotations. We also demonstrate promising few-shot generalization capability from Cityscapes to BDD100K and from Cityscapes to Mapillary datasets.

This research presents an innovative approach to accurately predict the nugget diameter in resistance spot welding (RSW) by leveraging machine learning and transfer learning methods. Initially, low-fidelity (LF) data were obtained through finite element numerical simulation and design of experiments (DOEs) to train the LF machine learning model. Subsequently, high-fidelity (HF) data were collected from RSW process experiments and used to fine-tune the LF model by transfer learning techniques. The accuracy and generalization performance of the models were thoroughly validated. The results demonstrated that combining different fidelity datasets and employing transfer learning could significantly improve the prediction accuracy while minimize the costs associated with experimental trials, and provide an effective and valuable method for predicting critical process parameters in RSW.

We analyze the local structure of the moduli space of genus one stable quasimaps. Combining it with the p-fields theory developed by Chang and Li (2020), we prove the splitting formula for the virtual cycle of stable quasimaps to complete intersections in ℙn.

Accurate and efficient road recognition is very important for the control of mobile robots and autonomous vehicles. In this article, a new road surface recognition method based on 24-GHz millimeter-wave radar is proposed, which has better environmental adaptability compared with machine vision and absolute cost advantage compared with lidar. The core of our method is to propose a radar feature fusion method based on prior knowledge and data-driven. First, the echo signal of radar is subjected to statistical analysis, thereby confirming the distinguishability of radar signals for various road types. Then, we extract 8-D statistical features as prior knowledge features based on statistics. Second, we have designed a new representation method of radar data, which reconstructs the radar data in time series based on graphical modeling and transforms the discrete radar data into an image representation. Then, the efficient network Inception-v3 and transfer learning are used to extract data-driven features from graphical radar data. Subsequently, the feature-level fusion of prior knowledge features and data-driven features is performed to generate the feature vector that can be trained. Finally, we built the road recognition classifier based on the advanced machine learning model and used different road environments to test the effectiveness of the model. The experimental results show that our method achieves 90.6% recognition accuracy and 32-frames/s inference speed under a 24-GHz radar with a cost of only U.S. ${\$}$ 16, which can be widely used in mobile robots and autonomous vehicles.

Sepsis, a life-threatening health issue, lacks effective medicine targeting the septic response. In China, treatment combining the intravenous herbal medicine XueBiJing with conventional procedures reduces the 28-day mortality of critically ill patients by modulating septic response. In this study, we identified the combined active constituents that are responsible for the XueBiJing’s anti-sepsis action. Sepsis was induced in rats by cecal ligation and puncture (CLP). The compounds were identified based on their systemic exposure levels and anti-sepsis activities in CLP rats that were given an intravenous bolus dose of XueBiJing. Furthermore, the identified compounds in combination were assessed, by comparing with XueBiJing, for levels of primary therapeutic outcome, pharmacokinetic equivalence, and pharmacokinetic compatibility. We showed that a total of 12 XueBiJing compounds, unchanged or metabolized, circulated with significant systemic exposure in CLP rats that received XueBiJing. Among these compounds, hydroxysafflor yellow A, paeoniflorin, oxypaeoniflorin, albiflorin, senkyunolide I, and tanshinol displayed significant anti-sepsis activities, which involved regulating immune responses, inhibiting excessive inflammation, modulating hemostasis, and improving organ function. A combination of the six compounds, with the same respective doses as in XueBiJing, displayed percentage survival and systemic exposure in CLP rats similar to those by XueBiJing. Both the combination and XueBiJing showed high degrees of pharmacokinetic compatibility regarding interactions among the six active compounds and influences of other circulating XueBiJing compounds. The identification of XueBiJing’s pharmacologically significant constituents supports the medicine’s anti-sepsis use and provides insights into a polypharmacology-based approach to develop medicines for effective sepsis management.

Di-(2-ethylhexyl) phthalate (DEHP) is frequently used as a plasticizer in industrial and agricultural products. DEHP can cause severe neurotoxicity, such as impaired learning and memory function. Lycopene (LYC) as a carotenoid exerts excellent antioxidant capacity and therapeutic effects in neurodegenerative diseases. However, whether LYC can prevent the cognitive impairment induced by DEHP and the specific mechanisms are unclear. In the present study, the behavioral test results suggested that LYC alleviated the learning and memory impairment induced by DEHP. The histopathological data revealed that LYC attenuated DEHP-induced disordered arrangement of the neurons in the CA1 and CA3 regions of the hippocampus tissue. Moreover, LYC inhibited the occurrence of DEHP-induced ferroptosis via regulating iron metabolism, inhibiting lipid peroxidation, and activating the cysteine transporter and nuclear factor erythroid 2-related factor 2/heme oxygenase-1 (NrF2/HO-1) signaling pathway. Overall, the study contributes novel perspectives into the potential mechanisms of LYC preventing phthalate-induced cognitive impairment in the hippocampus.

The architecture of transformers, which recently witness booming applications in vision tasks, has pivoted against the widespread convolutional paradigm. Relying on the tokenization process that splits inputs into multiple tokens, transformers are capable of extracting their pairwise relationships using self-attention. While being the stemming building block of transformers, what makes for a good tokenizer has not been well understood in computer vision. In this work, we investigate this uncharted problem from an information trade-off perspective. In addition to unifying and understanding existing structural modifications, our derivation leads to better design strategies for vision tokenizers. The proposed Modulation across Tokens (MoTo) incorporates inter-token modeling capability through normalization. Furthermore, a regularization objective TokenProp is embraced in the standard training regime. Through extensive experiments on various transformer architectures, we observe both improved performance and intriguing properties of these two plug-and-play designs with negligible computational overhead. These observations further indicate the importance of the commonly-omitted designs of tokenizers in vision transformer.

Stimuli-responsive polymer nanocarriers, capable of exploiting subtle changes in the tumor microenvironment for controlled drug release, have gained significant attention in cancer therapy. Notably, NAD(P)H: quinone oxidoreductase 1 (NQO1), found to be upregulated in various solid tumors, represents a promising therapeutic target due to its effective capability to enzymatically reduce trimethyl-locked (TML) benzoquinone structures in a physiological condition. In this study, a novel redox-sensitive carbonate monomer, MTC, was synthesized, and its amphiphilic block copolymers were prepared through ring-opening polymerization. By successfully self-assembling poly(ethylene glycol)-b-PMTC micelles, the model drug doxorubicin (DOX) was encapsulated with high efficiency. The micelles exhibited redox-responsive behavior, leading to rapid drug release. In vitro assessments confirmed their excellent biocompatibility and hemocompatibility. Furthermore, the inhibition of the NQO1 enzyme reduced drug release in NQO1-overexpressed cells but not in control cells, resulting in decreased cytotoxicity in the presence of NQO1 enzyme inhibitors. Overall, this study showcases the potential of MTC-based polycarbonate micelles to achieve targeted and specific drug release in the NQO1 enzyme-mediated tumor microenvironment. Therefore, the self-assembly of MTC-based polymers into nanomicelles holds immense promise as intelligent nanocarriers in drug delivery applications.

Text messages are a feasible delivery channel for breastfeeding promotion, but only a few articles have examined their effectiveness.

As a novel micro-propulsion system for small satellites (from micro to nano), the ionic liquid electrospray propulsion system is a promising candidate. However, performance measurement and evaluation of the Ionic Liquid Electrospray Thruster (ILET) is one of the most challenging issues for practical application, due to the difficulties in the development of a prototype and direct measurements of micro-thrust and small flow rate. To address this issue, a Modular Ionic Liquid Electrospray Thruster (MILET) prototype is constructed, and a diagnostic system for thrust and mass flow rate is specially developed based on an analytical balance method. With the ionic liquid 1-ethyl-3-methylimidazolium tetrafluoroborate as the propellant, a series of experiments is carried out on the MILET prototype under a wide operating condition through changing the applied voltage to control the thrust. Under different applied voltages, the thrust and the mass flow rate of the propellant are directly measured. The propulsive performance parameters of the thruster, such as thrust, specific impulse, thrust-to-power ratio, thruster efficiency, etc., are comprehensively analyzed. Then, a performance comparison is made between the MILET and other representative ILETs. With a relatively low applied voltage ranging from 1550 V to 2000 V, the MILET achieves a quasi-constant specific impulse of 1263 s with the averaged thrust-to-power ratio of 65.2 μN/W and thruster efficiency of 40.7%. The performance of ILET is also compared with other typical electric propulsions. The results demonstrate that the ILET exhibits an excellent ability of minimalization with high specific impulse and thruster efficiency, which guarantees a great superiority in micro propulsions. Finally, the ways to further improve the performance of ILET are discussed, which further confirms the potential prospect of ILET. The present result helps to advance the development and application of ILET.

The development of orally bioavailable, furanopyrimidine-based double-mutant (L858R/T790M) EGFR inhibitors is described. First, selectivity for mutant EGFR was accomplished by replacing the (S)-2-phenylglycinol moiety of 12with either an ethanol or an alkyl substituent. Then, the cellular potency and physicochemical properties were optimized through insights from molecular modeling studies by implanting various solubilizing groups in phenyl rings A and B. Optimized lead 52shows 8-fold selective inhibition of H1975 (EGFRL858R/T790Moverexpressing) cancer cells over A431 (EGFRWToverexpressing) cancer cells; western blot analysis further confirmed EGFR mutant-selective target modulation inside the cancer cells by 52. Notably, 52displayed in vivoantitumor effects in two different mouse xenograft models (BaF3 transfected with mutant EGFR and H1975 tumors) with TGI = 74.9 and 97.5% after oral administration (F= 27%), respectively. With an extraordinary kinome selectivity (S(10) score of 0.017), 52undergoes detailed preclinical development.

Di(2-ethylhexyl) phthalate (DEHP) is a highly harmful and persistent environmental pollutant. Due to its unique chemical composition, it frequently dissolves and enters the environment to endanger human and animal health. Lycopene is a natural bioactive component that can potentially reduce the risk of environmental factor-induced chronic diseases. The present study sought to explore the role and underlying mechanism of lycopene (LYC) on DEHP-induced renal inflammatory response and apoptosis. In this study, mice were orally treated with LYC (5 mg/kg BW/day) and/or DEHP (500 or 1000 mg/kg BW/day) for 28 days. Our results indicated that LYC prevented DEHP-induced histopathological alterations and ultrastructural injuries, including decreased mitochondrial membrane potential (ΔΨm), PINK1/Parkin pathway-mediated mitophagy, and mitochondrial energetic deficit. When damaged mitochondria release mitochondrial DNA (mtDNA) into cytosol, LYC can alleviate inflammation and apoptosis caused by DEHP exposure by activating the cyclic GMP-AMP synthase-stimulator of interferon gene (cGAS–STING) signal pathway. Collectively, our data demonstrate that LYC can reduce mitophagy caused by DEHP exposure by activating the PINK1/Parkin pathway and then reduce renal inflammation and apoptosis through the cGAS–STING pathway.

The entropy of the codes usually serves as the rate loss in the recent learned lossy image compression methods. Precise estimation of the probabilistic distribution of the codes plays a vital role in reducing the entropy and boosting the joint rate-distortion performance. However, existing deep learning based entropy models generally assume the latent codes are statistically independent or depend on some side information or local context, which fails to take the global similarity within the context into account and thus hinders the accurate entropy estimation. To address this issue, we propose a special nonlocal operation for context modeling by employing the global similarity within the context. Specifically, due to the constraint of context, nonlocal operation is incalculable in context modeling. We exploit the relationship between the code maps produced by deep neural networks and introduce the proxy similarity functions as a workaround. Then, we combine the local and the global context via a nonlocal attention block and employ it in masked convolutional networks for entropy modeling. Taking the consideration that the width of the transforms is essential in training low distortion models, we finally produce a U-net block in the transforms to increase the width with manageable memory consumption and time complexity. Experiments on Kodak and Tecnick datasets demonstrate the priority of the proposed context-based nonlocal attention block in entropy modeling and the U-net block in low distortion situations. On the whole, our model performs favorably against the existing image compression standards and recent deep image compression models.

Toxic and odorous iodophenols are commonly identified as disinfection by-products (DBPs) in drinking water. Herein, ng/L levels of iodophenols were identified in river water, wastewater treatment plant effluent, and medical wastewater, with the simultaneous identification of μg/L to mg/L levels of iodide (I–) and total organic iodine (TOI). Oxidation experiment suggested that the I–, TOI, and iodophenols could be oxidized by ferrate [Fe(VI)], and more than 97% of TOI had been transformed into stable and nontoxic IO3–. Fe(VI) initially cleaved the C–I bond of iodophenols and led to the deiodination of iodophenols. The resulted I–was swiftly oxidized into HOI and IO3–, with the intermediate phenolic products be further oxidized into lower molecular weight products. The Gibbs free energy change (ΔG) of the overall reaction was negative, indicating that the deiodination of iodophenols by Fe(VI) was spontaneous. In the disinfection of iodine-containing river water, ng/L levels of iodophenols and chloro-iodophenols formed in the reaction with NaClO/NH2Cl, while Fe(VI) preoxidation was effective for inhibiting the formation of iodinated DBPs. Fe(VI) exhibited multiple functions for oxidizing organic iodine, abating their acute toxicity/cytotoxicity and controlling the formation of iodinated DBPs for the treatment of iodide/organic iodine-containing waters.

The number of patients who benefit from acquired immunotherapy is limited. Stimulator of interferon genes (STING) signal activation is a significant component to enhance innate immunity, which has been used to realize broad-spectrum immunotherapy. Here, M@P@HA nanoparticles, as a STING signal amplifier, are constructed to enhance innate immunotherapy. Briefly, when M@P@HA was targeted into tumor cells, the nanoparticles decomposed with Mn2+and activated the release of protoporphyrin (PpIX). Under light irradiation, the generated reactive oxygen species disrupt the cellular redox homeostasis to lead cytoplasm leakage of damaged mitochondrial double-stranded (ds) DNA, which is the initiator of the STING signal. Simultaneously, Mn2+as the immunoregulator could significantly increase the activity of related protein of a STING signal, such as cyclic GMP-AMP synthase (cGAS) and STING, to further amplify the STING signal of tumor cells. Subsequently, the STING signal of tumor-associated macrophages (TAM) is also activated by capturing dsDNA and Mn2+that escaped from tumor cells, so as to enhance innate immunity. It is found that, by amplifying the STING signal of tumor tissue, M@P@HA could not only activate innate immunity but also cascade to activate CD8+T cell infiltration even in a tumor with low immunogenicity.

Solving nonlinear equation systems (NESs) is one of the most important tasks in numerical computing. The NESs usually have multiple roots, and quickly locating their roots in a single algorithm run with a limited number of iterations has always been the algorithm improvement direction. In order to further enhance the efficiency of the existing methods, a density clustering-based differential evolution algorithm (DCDE) for the NESs problem solving is proposed in this paper. Firstly, density-based spatial clustering of applications with noise (DBSCAN) is used to divide the population into clusters and noises, which provides a better direction for population evolution. Secondly, a cluster evaluation factor is proposed, which not only divides the clusters into excellent clusters and non-excellent clusters, but also prevents the migration of excellent clusters and maintain the diversity of populations. Then, a migration strategy and individual generation mechanism are proposed to guide non-excellent clusters to migrate to promising regions. Finally, combined with an archive technique, the individuals which satisfy the solution requirements are archived and randomly initialized to further improve population diversity. To verify the effectiveness of the proposed algorithm, comparative experimental results of the propsoed DCDE with other state-of-the-art algorithms for thirty NESs problems solving show that the proposed DCDE is the most effective algorithm to locate more roots in a single run. [ABSTRACT FROM AUTHOR]

Introduction: While minimally invasive surgery (MIS) is frequently utilized to remove small gastric gastrointestinal stromal tumors (GIST), MIS surgery for tumors ≥ 5 cm is currently not endorsed by national guidelines as standard of care due to concerns of safety and inferior oncologic outcomes. Hence this study investigates the perioperative and long-term outcomes of MIS for T3 gastric GIST measuring 5–10 cm. Methods: The National Cancer Database (NCDB) 2017 was queried for gastric GIST measuring 5–10 cm or T3 category. Inclusion criteria were known: stage, size, comorbidities, grade, lymphovascular invasion, type of surgery, approach, conversion info, margin status, mitotic rate, neoadjuvant and adjuvant treatment, hospital stay, readmission, 30- and 90-day mortality, complete follow-up, type of institution, and hospital gastric surgery case volume. Binary logistic regression, linear regression models, and Kaplan–Meier survival analysis were used. Results: In 3765 patients, mean tumor size was 67.3 mm; 26.3% MIS; and 73.8% open. Median hospital stay was shorter for MIS (4.77 vs 7.04 days, p< 0.001). There was no significant difference in incidence of R1 margins [2.9% MIS vs. 3.1% open (p= 0.143)], unplanned readmission [2.9% MIS and 4.1% open (OR 0.474 p= 0.025)], 30-day mortality [0.5% MIS vs 1.2% open (OR 0.325, p= 0.031)], and 90-day mortality [0.9% MIS vs 2.1% open (OR 0.478 p= 0.036)]. Cox regression models for OS showed no difference in survival (p= 0.137, HR 0.808). Conclusion: This analysis provides substantial evidence that MIS for gastric GIST ≥ 5–10 cm may not only offer improved postoperative morbidity but also oncologic safety. Moreover, as both approaches lead to similar long-term survival, national guidelines may need to incorporate this new information. Graphical abstract:

Lycopene (Lyc) has anti-inflammatory and antioxidant biological functions. Di-2-ethylhexyl phthalate (DEHP) is an extremely harmful and persistent environmental pollutant and is a threat to animal health. The toll-like receptor (TLR)/MyD88 pathway is an important pathway in the inflammatory response. To illustrate the potential antagonistic action of Lyc against DEHP by the TLR/MyD88 pathway, 140 ICR mice were randomly assigned groups and continuously gavaged with corn oil, distilled water, different DEHP concentrations (500 or 1000 mg/kg BW/day), and/or Lyc (5 mg/kg BW/day) for 28 days. The data show that Lyc effectively attenuates the DEHP-induced activation of the TLR/MyD88 pathway, the upregulation of JNK expression, the content of IL-6 and TNF-α, and the downregulation of the IL-10 content, which eventually inhibit the inflammatory response and mitochondrial injuries. These findings underline the TLR/MyD88 pathway as a potential therapeutic target in DEHP and Lyc as a new therapeutic method to inhibit DEHP toxicity.

We reported for the first time the utilization of hexadentate benzothiazole-based diamine-bisphenolate ligands to synthesize structurally well-characterized dinickel dicarboxylate complexes and studied their catalysis for copolymerization of carbon dioxide with epoxides. Dinickel carboxylate complexes having a 1,3-diamine-bridged backbone were demonstrated to be high-performance catalysts for alternating copolymerization of CO2and cyclohexene oxide (CHO) with high product selectivity. Particularly, acetate-supported nickel complex 2enabled us to promote such CO2-copolymerization of this kind with a maximum turnover frequency of up to 2600 h–1and gave good molecular weight controllability under high-pressure conditions. It is worth noting that bimetallic Ni catalyst 2was also capable of mediating the catalytic CO2-polymerization of alicyclic epoxides at atmospheric pressure. Kinetic investigations of CO2/CHO copolymerization by 2allowed us to determine the rate equation of −d[CHO]/dt= kp[2]1[CHO]1, and such catalysis exhibited a first-order dependence on both dinickel complex and CHO concentrations.

The fabrication of commercial cellulose nanofibrils (CNFs) into arrays with long-range ordering is of great significance for their extended applications, which, however, is severely hindered by their high disorder, aggregation, and hornified features. Herein, sub-nanoscale anionic metal oxide clusters (phosphotungstic acid, H3PW12O40, PTA) are applied to complex with commercial CNFs (dried powder DCNF and aqueous suspension WCNF) in aqueous media, and a long-range ordered layer structure can be facilely fabricated viatypical unidirectional freezing. The surface complexation of the commercial CNFs and PTA can be confirmed through the small-angle scattering studies of the complex hydrogels. The hydrogels present similar correlation lengths in small-angle X-ray and neutron scattering measurements, suggesting the homogeneous distribution of PTA along the commercial CNFs. This gives rise to the negatively charged surface feature and further leads to strong repulsion among the commercial CNFs. Due to the disparity in sizes, the influence of PTA on the density of hydrogel networks is suppressed, and the network density is mainly dependent on the mass content of CNFs. The studies provide guidance to fabricate hydrogels with catalytic and photosensitive properties and also to design and stabilize long-range ordered structured aerogels during the removal of the nonfreezing bound water absorbed by the commercial CNFs after unidirectional freezing. This facile strategy shows great potential to broaden the application of commercial CNFs in thermal insulators, super-adsorbent materials, and supercapacitors in electrical devices.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.aos.2008.08.002 Byline: Antonio Davila (a), George Foster (b), Mu Li (c) Abstract: Recent theoretical and empirical work indicates that management control systems (MCS) are an important element in enhancing innovation. We extend this research thrust examining the adoption of MCS in product development, arguably one of the business processes where innovation plays a major role. Using a sample of 69 early-stage entrepreneurial companies, data are collected from questionnaires and interviews with each of the CEO, financial officer, and business development managers pertaining to product development MCS. We examine seven different systems: project milestones, reports comparing actual progress to plan, budget for development projects, project selection process, product portfolio roadmap, product concept testing process, and project team composition guidelines. We address three distinct questions: (1) What are the reasons-for-adoption of these systems? The nature of our sample allows us to trace back to the adoption point and develop a set of reasons-for-adoption from the analysis of the data. While MCS fulfill certain roles as described in the literature, these reasons-for-adoption are distinct from these roles. Results indicate that certain events lead managers to adopt these systems and address the challenges that they face. They include contracting and legitimizing the process with external parties and internal reasons-for-adoption such as managers' background, learning by doing, need to focus the organization, or reaction to problems. (2) Are these reasons-for-adoption associated with differences across companies in the time from their founding date until these systems are adopted (time-to-adoption)? Prior research has looked at the covariance of various organizational variables with this timing; this study goes a step further by looking at the effect of different reasons-for-adoption on this timing. Our evidence finds an association between these two variables. (3) Are these reasons-for-adoption relevant to performance? We find that the reason-for-adoption is associated with the on-time dimension of product development performance. Author Affiliation: (a) IESE, University of Navarra, Spain (b) Graduate School of Business, Stanford University, United States (c) Applied Micro Devices, United States

Cold chain logistics is the process of transporting fresh products from producer to consumer in a constant low-temperature environment. Cold chain logistics efficiency is directly related to food safety and energy consumption. At present, cold chain logistics equipment mainly relies on diesel engine-driven vapor compression refrigeration system, which has high energy consumption, high equipment cost, and other defects. Phase change cold storage technology is a kind of technology that utilizes the property of absorbing and releasing heat during the phase change process of phase change materials (PCM) to realize the storage and release of cold energy. The combination of phase change cold storage technology and cold chain logistics equipment can effectively reduce cold chain logistics costs, energy consumption, emissions. Utilizing its property of maintaining a constant temperature during phase change, the temperature of the cold chain logistics process can be maintained uniformly, thus prolonging the fresh products preservation time. This paper reviews phase change cold storage technology and its application in fresh products cold chain logistics, summarizes the classification, performance optimization technology, and selection method of phase change materials, and describes the application scenarios and equipment types of phase change cold storage technology in cold chain logistics. Finally, it looks forward to the development direction of phase change cold storage technology applied in cold chain logistics and puts forward the problems that need to be solved to promote its development.

Australia, which spends 8.5% of its GDP on healthcare, is one of the healthiest countries in the world, although health in the indigenous population is below the country's overall standard. Other countries in the Asia-Pacific region, however, face epidemics of infectious diseases, nutritional deficiencies and diseases associated with economic and industrial development. These countries need international aid, and expertise from health professionals.

Soybean mosaic virus (SMV) affects seed quality and production of soybean (Glycine max(L.) Merr.) worldwide. SC18 is one of the dominant SMV strains in South China, and accession Zhonghuang 24 displayed resistance to SC18. The F1, F2and 168 F11recombinant inbred lines (RILs) population derived from a hybridization between Zhonghuang 24 (resistant, R) and Huaxia 3 (susceptible, S) were used in this study. According to the segregation ratios of the F2generation (3R:1S) and the recombinant inbred lines (RILs) population (1R:1S), one dominant locus may regulate the resistance to SC18 in Zhonghuang 24. By using composite interval mapping (CIM), Rsc18was mapped to a 415.357-kb region on chromosome 13. Three candidate genes, including one NBS-LRR type gene and two serine/threonine protein type genes, were identified according to the genetic annotations, which may be related to the resistance to SC18. The qRT-PCR demonstrated that these genes were up-regulated in the R genotype compared to the control. In conclusion, the findings of this research enhanced the understanding about the R genes at the Rsc18locus. Moreover, our results will provide insights for designing molecular markers to improve marker-assisted selection and developing new varieties with resistance to SC18.

Fungal azaphilones have attracted considerable interest as they exhibit great potential in food and pharmacological industries. However, there is a severe bottleneck in the low production in wild strains and the ability to genetically engineer azaphilone-producing fungi. Using Monascusazaphilones (MAs) as an example, we demonstrate a systematic metabolic engineering strategy for improving the production of MAs. In this study, Monascus purpureusHJ11 was systematically engineered through a combination of promoter engineering, gene knockout, rate-limiting enzyme overexpression, repression of the competing pathway, enzyme engineering, and metabolic rebalance. The maximum yield and titer of MAs successfully increased to 906 mg/g dry cell weight (DCW) and 14.6 g/L, respectively, 2.6 and 3.7 times higher than those reported in the literature. Our successful model not only offers a practical and efficient way to improve the azaphilone production but also sheds light on the potential of systematic metabolic engineering in nonmodel fungi as a chassis for the production of high-value chemicals.

Neuroblastoma (NB) is a huge threat to children's health. Adipose‐derived stem cells‐derived extracellular vesicles (ADSC‐Evs) can regulate tumor progression. This study aimed to identify the role of ADSC‐Evs in NB. Following ADSC‐Ev isolation and identification, PKH26‐labeled ADSC‐Evs were cocultured with NB cells to observe the internalization of ADSC‐Evs. ADSC‐Ev effects on NB cell proliferation, invasion, and migration were assessed. The regulatory molecules related to NB development were predicted. The expressions of and relations among LINC00622, transcriptional factor androgen receptor (AR), and gamma‐aminobutyric acid B‐type receptor 1 (GABRR1) were detected and verified. LINC00622 was inhibited in ADSCs to evaluate ADSC‐Ev effects on NB cells. Xenograft tumor experiment in nude mice was further performed to evaluate the effects of ADSC‐Evs‐carried LINC00622 on NB in vivo. ADSC‐Evs inhibited NB cell proliferation, invasion, and migration. ADSC‐Evs increased GABBR1 expression in NB cells. ADSC‐Evs‐carried LINC00622 mediated AR to promote GABBR1 expression. Silencing LINC00622 in ADSCs weakened the inhibition of ADSC‐Evs on NB cell malignant behaviors. ADSC‐Evs reduced tumor growth in nude mice, which was restored after inhibiting LINC00622 expression in ADSCs. We highlighted that ADSC‐Evs carried LINC00622 into NB cells to inhibit transcription factor AR and promote GABBR1 expression, thus inhibiting NB cell growth. Adipose‐derived stem cell‐derived extracellular vesicles inhibited neuroblastoma (NB) cell growth by carrying LINC00622 into NB cells to inhibit transcription factor androgen receptor and to promote gamma‐aminobutyric acid B‐type receptor 1 expression.

Unsupervised extractive summarization aims to extract salient sentences from documents without labeled corpus. Existing methods are mostly graph-based by computing sentence centrality. These methods have two main problems: facet bias and redundant problems. Facet bias problem leads summarization models tend to select sentences within the same facet, which often leads to the ignoring of other vital facets, especially on long-document and multi-documents. First, to address the facet bias problem, we proposed a novel Facet-Aware centrality-based Ranking model (FAR). We let the model pay more attention to different facets by introducing a sentence-document weight. The weight is added to the sentence centrality score. FAR can alleviate redundancy to some extent. Then, to further reduce redundancy, we proposed a novel Redundancy- and Facet-Aware Ranking model (RFAR) which jointly models facet and redundancy by incorporating Determinantal Point Process (DPP) into the previous proposed FAR. We evaluate our FAR and RFAR on a wide range of summarization tasks that include 8 representative benchmark datasets. Experimental results show that FAR and RFAR consistently outperforms strong baselines, especially in long- and multi-document scenarios, and even perform comparably to some supervised models. Besides, we find that our methods can alleviate the position bias problem.

Coordination nanocages (CNCs) are under intense research in nanoscience and supramolecular chemistry for their enriched surface functionalities and micro-porosity; however, the understanding of their formation mechanism is still poor due to the difficulty in probing their solution structures. Herein, the CNC formation process from the coordination complexation of the macromolecular isophthalic acid (IPA) ligand and Cu2+is studied via isothermal titration calorimetry, and its entropy-driven feature is revealed to be originated from the collapse of solvation layers of the assembly units. The CNC formation is thermodynamically less favored with smaller binding constants when the sizes of macromolecular IPA ligands are larger, which originated from the space crowding of macromolecules of the ligands on CNC surfaces and the resulting entropy loss of polymer chain conformations. Meanwhile, the chemical equilibrium of CNC formation can be tuned upon altering the Cu2+/IPA ratio, and the yield of CNCs, suggested from size exclusion chromatography studies, decreases when excessive Cu2+is applied, providing guidelines for CNC design and synthesis.

ABSTRACTMicroRNAs (miRNAs) are essential non-coding riboregulators of gene expression in plants and animals. In plants, miRNAs guide their effector protein named ARGONAUTE (AGO) to find target RNAs for gene silencing through target RNA cleavage or translational inhibition. miRNAs are derived from primary miRNA transcripts (pri-miRNAs), most of which are transcribed by the DNA-dependent RNA polymerase II. In plants, an RNase III enzyme DICER-LIKE1-containing complex processes pri-miRNAs in the nucleus into miRNAs. To ensure proper function of miRNAs, plants use multiple mechanisms to control miRNA accumulation. On one hand, pri-miRNA levels are controlled through transcription and stability. On the other hand, the activities of the DCL1 complex are regulated by many protein factors at transcriptional, post-transcriptional and post-translational levels. Notably, recent studies reveal that pri-miRNA structure/sequence features and modifications also play important roles in miRNA biogenesis. In this review, we summarize recent progresses on the mechanisms regulating miRNA biogenesis.

Though numerous cyanation reactions have been developed for the synthesis of benzonitriles, the construction of valuable fully substituted benzonitriles is still a challenging task. Herein, we reported a tertiary amine-catalyzed [3 + 3]-benzannulation for the green synthesis of CF3-functionalized fully substituted benzonitriles. This strategy features exclusive chemoselectivity, high atom-economy, and good step-economy with environment-friendly reagents and mild conditions. Unique triphenyl-substituted dicyanobenzoate products could be rapidly constructed using this method. The practicality and reliability of this reaction were proved by the successful scale-up synthesis. A mechanistic study indicates that the [3 + 3]-benzannulation was initiated by an intermolecular Rauhut–Currier reaction.

Purpose: To explore the value of contrast-enhanced malignancy imaging features in secondary grade diagnosis of Breast Imaging Reporting and Data System for Ultrasonography (BI-RADS-US) type 4 breast lesions.Methods: After initial diagnosis by ultrasound, 124 BI-RADS-US type 4 patients with 130 lesions were examined by contrast-enhanced ultrasound (CEUS) and were classified again before surgery according to five contrast-enhanced malignancy imaging features: inhomogeneous enhancement, peripheral ring-like enhancement, expansive enhancement, internal filling defects, and surrounding radioactive convergence. Lesions with no contrast-enhanced features of malignancy were categorized as type 3; lesions with one, two, or three features of malignancy were categorized as type 4A, 4B, or 4C, respectively; and lesions with four or more indices of malignancy were categorized as type 5. The value of contrasted imaging features of malignancy in diagnosing BI-RADS-US type 4 breast lesions was analyzed.Results: The accuracy of CEUS diagnosis for type 3 lesions was 93.8% (46/49), 76.9% (10/13) for type 4A, 71.4% (5/7) for type 4B, 75.0% (9/12) for type 4C, and 93.8% (46/49) for type 5 lesions. The sensitivity of CEUS in diagnosing malignant lesions was 90.4%, specificity was 83.6%, and accuracy was 86.9%. CEUS decreased the benign lesion biopsy ratio to 68.5% (46/67) and increased the diagnosis ratio of malignant lesions to 73.0% (46/63).Conclusions: CEUS can further optimize the classification of BI-RADS-US type 4 breast lesions and may provide a better reference basis for clinical diagnosis and treatment of those breast lesions.

Acoustic velocities and elasticity of stoichiometric submicron polycrystalline δ-MoN have been reported at high pressure using ultrasonic measurements and first-principles calculations. Using the finite-strain equation-of-state approach, the bulk modulus and shear rigidity, as well as their pressure derivatives, are derived from the current experimental data, yielding BS0= 360.0(8) GPa, G0= 190.0(5) GPa, ∂BS/∂P= 3.4(2), and ∂G/∂P= 1.4(1). Based on our experimental data and the velocity–elasticity correlated models, the mechanical/thermal properties (i.e., hardness, fracture toughness, Grüneisen parameter, Debye temperature, Poisson’s ratio) are also derived. Interestingly, we find that hexagonal δ-MoN is almost as incompressible as superhard cubic boron nitride (cBN) (∼384 GPa) and its hexagonal ε-NbN (∼373 GPa) counterpart, and its shear rigidity (G= 190 GPa) is comparable to that of the superhard diamond composite (G= 204 GPa). Moreover, the fracture toughness of submicron δ-MoN polycrystals is achieved up to ∼4.3 MPa·m1/2, which is comparable to superhard diamond (4–7 MPa·m1/2) and cBN (2–5 MPa·m1/2). The Vickers hardness of submicron δ-MoN is estimated to be Hv≈ 17.4 GPa using Chen’s model, which is found to be almost as hard as hexagonal ε-NbN and δ-WN, and may be very important for its applications in extreme environments.

Shapes from the diffuse polarization method effectively realize the three-dimensional (3D) reconstruction of the object surface by using the polarization information of the diffuse reflection light. However, due to the nonconvexity of the particle surface, the reconstruction often falls into a local optimal solution. Indeed, the depth image obtained by the scanning electron microscope has serious stripe noise, which distorts the surface texture of the particle. In this Letter, a variable exponential function regularization method is proposed to realize 3D reconstruction for the nonconvexity of the surface and inclination of the particles. We focus on the gradient unintegrability caused by the skew and surface undulation of the specimen. An adaptive 3D reconstruction method is proposed based on variable exponential function regularization to fit the surface function of the particle. Experimental results of finite-difference time-domain simulations and actual imaging demonstrate the effectiveness of the method.

Four new triazole-decorated silver(I)-based cationic metal–organic frameworks (MOFs), {[Ag(L1)](BF4)}n(1), {[Ag(L1)](NO3)}n(2), {[Ag(L2)](BF4)}n(3), and {[Ag(L2)](NO3)}n(4), have been synthesized using two newly designed ligands, 3-fluoro-5-(4H-1,2,4-triazol-4-yl)pyridine (L1) and 3-(4H-1,2,4-triazol-4-yl)-5-(trifluoromethyl)pyridine (L2). When the fluorine atom was changed to a trifluoromethyl group at the same position, tremendous enhancement in the MOF dimensionality was achieved [two-dimensional to three-dimensional (3D)]. However, changing the metal salt (used for the synthesis) had no effect. The higher electron-withdrawing tendency of the trifluoromethyl group in L2 aided in the formation of higher-dimensional MOFs with different properties compared with those of the fluoro derivatives. The fluoride group was introduced in the ligand to make highly electron-deficient pores inside the MOFs that can accelerate the anion-exchange process. The concept was proved by density functional theory calculation of the MOFs. Both 3D cationic MOFs were used for dye adsorption, and a remarkable amount of dye was adsorbed in the MOFs. In addition, owing to their cationic nature, the MOFs selectively removed anionic dyes from a mixture of anionic, cationic, and neutral dyes in the aqueous phase. Interestingly, the present MOFs were also highly effective for the removal of oxoanions (MnO4–and Cr2O72–) from water.

Topmetal-M2 is a large-area pixel sensor chip fabricated using the GSMC 130nmCMOS process in 2021. The pixel array of Topmetal-M2 consists of pixels of 400 rows ×512 columns with a pixel pitch of 45μm×45μm. The array is divided into 16 subarrays, with pixels of 400 rows ×32 columns per subarray. Each pixel incorporates two charge sensors: a diode sensor and a Topmetal sensor. The in-pixel circuit primarily consists of a charge-sensitive amplifier for energy measurements, a discriminator with a peak-holding circuit, and a time-to-amplitude converter for time-of-arrival measurements. The pixel of Topmetal-M2 has a charge input range of ∼0-3ke-, a voltage output range of ∼0-180mV, and a charge-voltage conversion gain of ∼59.56μV/e-. The average equivalent noise charge of Topmetal-M2, which includes the readout electronic system noise, is ∼43.45e-. In the scanning mode, the time resolution of Topmetal-M2 is 1LSB=1.25μs, and the precision is ∼7.41μs. At an operating voltage of 1.5V, Topmetal-M2 has a power consumption of ∼49mW/cm2. In this article, we provide a comprehensive overview of the chip architecture, pixel working principles, and functional behavior of Topmetal-M2. Furthermore, we present the results of preliminary tests conducted on Topmetal-M2, namely, alpha-particle and soft X-ray tests.

Objective:The treatment of oral squamous cell carcinoma (OSCC) is dominated by surgery and radiochemotherapy, but its prognosis is still unsatisfactory, with around five tenths of 5-year survival. This study aimed to assess the prognosis of OSCC patients treated with surgery with and without postoperative radiotherapy. Study Design:Retrospective study. Methods:The clinicopathological information and follow-up datasets on patients with OSCC (T1-4and/or N+) registered from 2010 to 2015 were downloaded from the Surveillance, Epidemiology, and End Results database. Totally 7231 enrolled subjects were divided into a case group (surgery alone, n = 4167) and a control group (surgery combined with postoperative radiotherapy, n = 3064). One-to-one matching was performed by propensity score matching to make the baseline data comparable between the 2 subgroups. Multivariate Coxregression analysis was used to calculate hazard ratios (HR) of various clinicopathological features. The Kaplan–Meiermethod and log-ranktest were used to plot the survival curves. Results:The majority of patients in case group were tumor stage I (n = 2569, 61.7%), whereas most patients in control group were stages III to IV (n = 2360, 77.1%). In the case group, the 1-, 3-, and 5-year overall survival (OS; 76%, 59.5%, 53.7%) were significantly lower than those of the control group (85.1%, 64.1%, 55.8%; P< .0001). Similarly, the 1-, 3-, and 5-year cancer-specific survival (CSS) of the case group (80.2%, 66.6%, 63.3%) were significantly lower than those of the control group (87.2%, 69.3%, 63.9%, respectively; P< .0001). Coxmultivariate analysis indicated that age, differentiation, clinical stage, and tumor-node-metastasis stage affected the prognosis of OSCC patients, while postoperative radiotherapy was a protective factor (OS: HR = 0.649, P< .001; CSS: HR = 0.702, P< .001). Conclusions:Postoperative radiation was an independent protective factor, hence, the combination of surgery plus radiotherapy is more beneficial for the survival of patients with OSCC, particularly for advanced cases.