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Predicting the binding of ligands to the human proteome via reverse‐docking methods enables the understanding of ligand's interactions with potential protein targets in the human body, thereby facilitating drug repositioning and the evaluation of potential off‐target effects or toxic side effects of drugs. In this study, we constructed 11 reverse docking pipelines by integrating site prediction tools (PointSite and SiteMap), docking programs (Glide and AutoDock Vina), and scoring functions (Glide, Autodock Vina, RTMScore, DeepRMSD, and OnionNet‐SFCT), and then thoroughly benchmarked their predictive capabilities. The results show that the Glide_SFCT (PS) pipeline exhibited the best target prediction performance based on the atomic structure models in AlphaFold2 human proteome. It achieved a success rate of 27.8% when considering the top 100 ranked prediction. This pipeline effectively narrows the range of potential targets within the human proteome, laying a foundation for drug target prediction, off‐target assessment, and toxicity prediction, ultimately boosting drug development. By facilitating these critical aspects of drug discovery and development, our work has the potential to ultimately accelerate the identification of new therapeutic agents and improve drug safety. [ABSTRACT FROM AUTHOR]

Purpose: To develop a deep neural network system for the automatic segmentation and risk stratification prediction of gastrointestinal stromal tumors (GISTs). Methods: A total of 980 ultrasound (US) images from 245 GIST patients were retrospectively collected. These images were randomly divided (6:2:2) into a training set, a validation set, and an internal test set. Additionally, 188 US images from 47 prospective GIST patients were collected to evaluate the segmentation and diagnostic performance of the model. Five deep learning‐based segmentation networks, namely, UNet, FCN, DeepLabV3+, Swin Transformer, and SegNeXt, were employed, along with the ResNet 18 classification network, to select the most suitable network combination. The performance of the segmentation models was evaluated using metrics such as the intersection over union (IoU), Dice similarity coefficient (DSC), recall, and precision. The classification performance was assessed based on accuracy and the area under the receiver operating characteristic curve (AUROC). Results: Among the compared models, SegNeXt‐ResNet18 exhibited the best segmentation and classification performance. On the internal test set, the proposed model achieved IoU, DSC, precision, and recall values of 82.1, 90.2, 91.7, and 88.8%, respectively. The accuracy and AUC for GIST risk prediction were 87.4 and 92.0%, respectively. On the external test set, the segmentation models exhibited IoU, DSC, precision, and recall values of 81.0, 89.5, 92.8, and 86.4%, respectively. The accuracy and AUC for GIST risk prediction were 86.7 and 92.5%, respectively. Conclusion: This two‐stage SegNeXt‐ResNet18 model achieves automatic segmentation and risk stratification prediction for GISTs and demonstrates excellent segmentation and classification performance. [ABSTRACT FROM AUTHOR]

Disulfide bonds, covalently formed by sulfur atoms in cysteine residues, play a crucial role in protein folding and structure stability. Considering their significance, artificial disulfide bonds are often introduced to enhance protein thermostability. Although an increasing number of tools can assist with this task, significant amounts of time and resources are often wasted owing to inadequate consideration. To enhance the accuracy and efficiency of designing disulfide bonds for protein thermostability improvement, we initially collected disulfide bond and protein thermostability data from extensive literature sources. Thereafter, we extracted various sequence‐ and structure‐based features and constructed machine‐learning models to predict whether disulfide bonds can improve protein thermostability. Among all models, the neighborhood context model based on the Adaboost‐DT algorithm performed the best, yielding "area under the receiver operating characteristic curve" and accuracy scores of 0.773 and 0.714, respectively. Furthermore, we also found AlphaFold2 to exhibit high superiority in predicting disulfide bonds, and to some extent, the coevolutionary relationship between residue pairs potentially guided artificial disulfide bond design. Moreover, several mutants of imine reductase 89 (IR89) with artificially designed thermostable disulfide bonds were experimentally proven to be considerably efficient for substrate catalysis. The SS‐bond data have been integrated into an online server, namely, ThermoLink, available at guolab.mpu.edu.mo/thermoLink. [ABSTRACT FROM AUTHOR]

Surface ablation temperature and linear ablation rate are two crucial indicators for ceramic coatings under ultrahigh temperatures service, yet the results collection of such two indicators in the process is difficult due to the long‐period material preparation and the high‐cost test. In this work, four kinds of machine learning models are applied to predict the above two indicators. The Random Forest (RF) model exhibits a high accuracy of 87% in predicting surface ablation temperature, while a low accuracy of 60% in linear ablation rate. To optimize the model, the novel features are constructed based on the original features by the sum of the importance weights in the model. Thereafter, the importance of the newly constructed features increases significantly, and the accuracy of the optimized RF model is improved by 11%, exceeding 70% in accuracy. By validation with available data and experiments, the optimized model demonstrates precise predictions of the target variables. [ABSTRACT FROM AUTHOR]

The construction of olefin‐linked chiral covalent organic frameworks (COFs) with high crystallinity is highly desirable while remains great challenge due to the poor reversibility of the formation reaction for the olefin linkages during the in situ structural self‐healing process. Herein, we successfully synthesized two sets of enantiomeric olefin‐linked COFs. The chiral catalytic groups are uniformly distributed on the pore walls of COFs, resulting in the full exposure of catalytic sites to the reactants in asymmetric catalysis. The as‐prepared (R)/(S)‐CCOF8 exhibits excellent catalytic performance with exceeding 99 % enantiomeric excess in the enantioselective electrophilic amination reaction. Moreover, the heterogeneous chiral catalysts are conveniently recycled and could maintain the performance after ten catalytic cycles. Our findings expand the scope to construct stable and crystalline chiral COFs for the asymmetric catalysis. [ABSTRACT FROM AUTHOR]

Natural redox‐regulated channel proteins often utilize disulfide bonds as redox sensors for adaptive regulation of channel conformations in response to diverse physiological environments. In this study, we developed novel synthetic ion channels capable of reversibly switching their ion‐transport capabilities by incorporating multiple disulfide bonds into artificial systems. X‐ray structural analysis and electrophysiological experiments demonstrated that these disulfide‐bridged molecules possess well‐defined tubular cavities and can be efficiently inserted into lipid bilayers to form artificial ion channels. More importantly, the disulfide bonds in these molecules serve as redox‐tunable switches to regulate the formation and disruption of ion‐permeation pathways, thereby achieving a transition in the transmembrane transport process between the ON and OFF states. [ABSTRACT FROM AUTHOR]

High‐resolution (HR) crack images offer more detailed information for evaluating the structural condition and formulating effective maintenance or rehabilitation plans. However, the meticulous segmentation of HR crack images has been a challenge due to the limitations of mainstream deep learning algorithms that extract features in a discrete manner, as well as the constraints of computing resources. To address this issue, a novel implicit function‐integrated architecture, called the crack continuous refinement network (CCRN), was proposed for meticulous segmentation of cracks from HR images using a continuous representation manner. First, a crack continuous alignment module with a position encoding function was proposed to encode the tiny crack pixels that are easily lost in the sampling process. Then, a lightweight decoder embedded with implicit functions was customized to recover crack details from the aligned latent features and continuous position encoding information. Afterward, the gap between low‐resolution training images and HR inference results was bridged by the proposed continuous inference strategy. Finally, the robustness and practicability of the well‐trained CCRN were demonstrated by a parallel comparison and an unmanned aerial vehicle‐based field experiment. [ABSTRACT FROM AUTHOR]

Photocyclization is demonstrated as a powerful tool for building complicated polycyclic molecules. And efficient photocyclization is competent as an artful strategy to develop photo‐responsive smart materials. Herein, an efficient free radical‐mediated photocyclization for triphenylphosphindole oxide (TPPIO) derivatives to generate tribenzophosphindole oxide (TBPIO) derivatives at ambient condition is reported. The reaction mechanism and substituent effect on photocyclization efficiency are thoroughly investigated. Additionally, photophysical and photochemical properties of TPPIO and TBPIO derivatives are measured for comparison and deeply deciphered by theoretical calculation. TPPIO derivatives own typical aggregation‐induced emission feature but barely generate reactive oxygen species (ROS), while TBPIO derivatives experience aggregation‐caused quenching but show efficient Type I ROS generation capacity. Further, in vitro experiments demonstrate that this photo‐conversion can efficiently occur in situ in living cells to activate photodynamic therapy (PDT) effect to trigger lipid peroxidation with selective fluorescence "light up" in lipid droplet area under continuous irradiation. This work extends the optoelectronically and biologically interesting phosphindole oxide‐containing π‐conjugated systems through an efficient synthetic strategy, provides in‐depth mechanistic descriptions in the aspects of reaction and property, and further presents their great potentials for photoactivated and self‐reported PDT. [ABSTRACT FROM AUTHOR]

Cold is a major environmental factor that restrains potato production. Abscisic acid (ABA) can enhance freezing tolerance in many plant species, but powerful evidence of the ABA‐mediated signalling pathway related to freezing tolerance is still in deficiency. In the present study, cold acclimation capacity of the potato genotypes was enhanced alongside with improved endogenous content of ABA. Further exogenous application of ABA and its inhibitor (NDGA) could enhance and reduce potato freezing tolerance, respectively. Moreover, expression pattern of downstream genes in ABA signalling pathway was analysed and only ScAREB4 was identified with specifically upregulate in S. commersonii (CMM5) after cold and ABA treatments. Transgenic assay with overexpression of ScAREB4 showed that ScAREB4 promoted freezing tolerance. Global transcriptome profiling indicated that overexpression of ScAREB4 induced expression of TPS9 (trehalose‐6‐phosphate synthase) and GSTU8 (glutathione transferase), in accordance with improved TPS activity, trehalose content, higher GST activity and accumulated dramatically less H2O2 in the ScAREB4 overexpressed transgenic lines. Taken together, the current results indicate that increased endogenous content of ABA is related to freezing tolerance in potato. Moreover, ScAREB4 functions as a downstream transcription factor of ABA signalling to promote cold tolerance, which is associated with increased trehalose content and antioxidant capacity. Summary Statement: The cold acclimation capacity of the potato genotypes was enhanced alongside with improved endogenous content of ABA and ScAREB4 was identified to promotes potato constitutive and acclimated freezing tolerance. [ABSTRACT FROM AUTHOR]

Background: Myosin plays a crucial role in cellular processes, while its dysfunction can lead to organismal malfunction. Phenamacril (PHA), a highly species‐specific and non‐competitive inhibitor of myosin I (FgMyoI) from Fusarium graminearum, has been identified as an effective fungicide for controlling plant diseases caused by partial Fusarium pathogens, such as wheat scab and rice bakanae. However, the molecular basis of its action is still unclear. Results: This study used multiple computational approaches first to elucidate the allosteric inhibition mechanism of FgMyoI by PHA at the atomistic level. The results indicated the increase of adenosine triphosphate (ATP) binding affinity upon PHA binding, which might impede the release of hydrolysis products. Furthermore, simulations revealed a broadened outer cleft and a significantly more flexible interface for actin binding, accompanied by a decrease in signaling transduction from the catalytic center to the actin‐binding interface. These various effects might work together to disrupt the actomyosin cycle and hinder the ability of motor to generate force. Our experimental results further confirmed that PHA reduces the enzymatic activity of myosin and its binding with actin. Conclusion: Therefore, our findings demonstrated that PHA might suppress the function of myosin through a synergistic mechanism, providing new insights into myosin allostery and offering new avenues for drug/fungicide discovery targeting myosin. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Annotation work is burdensome and challenging for developing a façade defects detector, especially when the raw data set is large but not all useful. To alleviate the problem, this study proposes an informativeness‐guided active learning methodology to effectively select informative data to train a robust façade defects detector. A novel data annotation workflow is developed to ensure the high quality of labels. Then, an active learning–based model training strategy is adopted to enable the model to have both the abilities of generalization and discrimination on different defect features. Besides, an innovative informativeness assessment method is proposed by flexibly combining the degree of uncertainty and the degree of representativeness. Through the proposed method, the performance of façade defects detection can be further boosted with the same amount but more informative training data so that the cost‐efficiency of human annotation work can be improved. [ABSTRACT FROM AUTHOR]

Summary: This study aimed to investigate a stratified approach based on hepatitis B virus (HBV) surface antibody (anti‐HBs) for managing HBV reactivation (HBVr) in lymphoma patients with serological protection against HBV. A retrospective analysis was conducted on 209 lymphoma patients with a baseline anti‐HBs titre of ≥10 iu/L, who were either positive or negative for HBV core antibody (anti‐HBc). The results revealed that 15.7% of patients lost serological protection following 6‐month anti‐lymphoma therapy. With a median follow‐up of 28.1 months, the cumulative rates of HBVr at 6 months, 2 years and 4 years were 2.9%, 4.7% and 6.3% respectively. Without intervention, the overall rate of reactivation was 2.0% for patients with isolated anti‐HBs and 10.5% for those with positive anti‐HBs and anti‐HBc. To identify patients at high risk of losing seroprotection and susceptible to HBVr, a predictive model was developed. The high‐risk group had significantly higher rates of serological protection loss (27.8% vs. 2.2%) and cumulative incidence of HBVr (22.0% vs. 0%) compared to the low‐risk group. Overall, this study highlights the risk of HBVr in lymphoma patients with positive anti‐HBs, with or without positive anti‐HBc, and recommends periodic monitoring for low‐risk patients and early intervention for high‐risk patients. [ABSTRACT FROM AUTHOR]

Biological membranes (biomembranes) are one of the most complicated structures that allow life to exist. Investigating their structure, dynamics, and function is crucial for advancing our knowledge of cellular mechanisms and developing novel therapeutic strategies. However, experimental investigation of many biomembrane phenomena is challenging due to their compositional and structural complexity, as well as the inherently multi‐scalar features. Computational approaches, particularly molecular dynamics (MD) simulations, have emerged as powerful tools for addressing the atomic details of biomembrane systems, driving breakthroughs in our understanding of biomembranes and their roles in cellular function. This review presents an overview of the latest advancements in related computational approaches, from force fields and model construction to MD simulations and trajectory analysis. We also discussed current hot research topics and challenges. Finally, we outline future directions, emphasizing the integration of force field development, enhanced sampling techniques, and data‐driven approaches to accelerate the growth of this field in the years to come. We aim to equip readers with an understanding of the promise and limitations of emerging computational technologies in biomembrane systems and offer valuable recommendations for future research endeavors. This article is categorized under:Structure and Mechanism > Computational Biochemistry and BiophysicsMolecular and Statistical Mechanics > Molecular Dynamics and Monte‐Carlo Methods [ABSTRACT FROM AUTHOR]

Summary: To solve the problem that the efficiency of a wireless power transfer system decreases with increasing transmission distance, metamaterial (MTM) has offered an effective solution. In this paper, a novel compact MTM with negative permeability is designed to improve the transfer efficiency of wireless power transfer at the operating frequency of 13.56 MHz. By placing the MTM slab at different positions between coils, the transmission coefficient of the wireless power transfer system with one MTM slab is calculated. Also, the impact of transmission distance is studied. Based on the two‐port network method, the transfer efficiency of wireless power transfer is respectively calculated for the system with one MTM slab and with two MTM slabs. The results demonstrate that transfer efficiency at the transmission distance of 150, 200, and 250 mm are, respectively, 82.4%, 67.8%, and 47.3% when one MTM slab is introduced. For the system with two MTM slabs, the corresponding transfer efficiency is 84.9%, 77.3%, and 66.1% separately. Compared with the system without MTM, it is found that there is a large improvement in transfer efficiency especially when two MTM slabs are positioned between coils at the transmission distance of 250 mm. The magnetic field distribution of the system with one or two MTM slabs introduced is investigated. The results show that magnetic coupling between coils is strengthened, which is favorable for transfer efficiency enhancement. [ABSTRACT FROM AUTHOR]

We report an azide‐functionalized cobaloxime proton‐reduction catalyst covalently tethered into the Wurster‐type covalent organic frameworks (COFs). The cobaloxime‐modified COF photocatalysts exhibit enhanced photocatalytic activity for hydrogen evolution reaction (HER) in alcohol‐containing solution with no presence of a typical sacrificial agent. The best performing cobaloxime‐modified COF hybrid catalyzes hydrogen production with an average HER rate up to 38 μmol h−1 in ethanol/phosphate buffer solution under 4 h illumination. Ultrafast transient optical spectroscopy characterizations and charge carrier analysis reveal that the alcohol contents functioning as hole scavengers could be oxidized by the photogenerated holes of COFs to form aldehydes and protons. The consumption of the photogenerated holes thus suppresses exciton recombination of COFs and improves the ratio of free electrons that were effectively utilized to drive catalytic reaction for HER. This work demonstrates a great potential of COF‐catalyzed HER using alcohol solvents as hole scavengers and provides an example toward realizing the accessibility to the scope of reaction conditions and a greener route for energy conversion. [ABSTRACT FROM AUTHOR]

In order to enhance the resource utilisation of the netted radar system, a receiving resource allocation (RRA) strategy for target localisation is developed in this article. Receiving resource refers to the receiving node and the processing approach adopted. The aim of the proposed RAA strategy is to select the receiver node and corresponding processing approach to minimise the resource cost while satisfying the desired target localisation accuracies. The resource cost includes the implementation cost of the processing approaches and the distance cost of data transmission. The Cramer‐Rao bound (CRB) incorporating the above controllable parameters is derived and used as the target localisation performance metric in the netted radar system. Whereafter, the RRA problem is modelled as a non‐convex constrained optimisation problem with the discrete variables. A scheme based on the modified depth‐first search is proposed to solve this problem. Simulation results demonstrate that the proposed scheme can effectively reduce resource consumption under the desired target localisation performance constraints. [ABSTRACT FROM AUTHOR]

Rationale: Embedding resins are widely used to fix carbonates for high‐precision sample preparation and high‐resolution sampling. However, these embedding materials are difficult to remove after sample preparation and are known to affect the accuracy of carbonate stable isotope analyses. Nevertheless, their impact on clumped isotope analysis, which is particularly sensitive to contamination artifacts, has so far not been tested. The observation that running resin‐containing samples decreased the reproducibility of clumped isotope values for internal laboratory carbonate standards and increased the external standard deviation (SD 0.061–0.088‰) compared to the long‐term observations (0.034‰), prompted us to set up an experiment to test the influence of resin addition on instrument performance. Methods: Here we analyzed the stable and clumped isotope composition of a pure calcium carbonate standard (ETH‐4) mixed with three types of embedding resins in 2:1 and 1:1 proportions. Our aim was to assess how resin addition affects isotope analyses. Results: We found that none of the stable isotopic values were significantly different. The δ13C values were −10.22 ± 0.07‰ (mean ± SD) for pure ETH‐4, while the δ13C values of ETH‐4 mixed with embedding resins in 2:1 and 1:1 proportions were −10.21 ± 0.06‰ and −10.18 ± 0.06‰, respectively (p > 0.05). The δ18O values were −18.82 ± 0.11‰ for pure ETH‐4 versus −18.81 ± 0.09‰ and −18.82 ± 0.08‰ for 2:1 and 1:1 ETH‐4:resin mixtures, respectively (p > 0.05). Given the large uncertainty in our results, we did not find significant differences between different mixtures in the carbonate clumped isotope values (Δ47), with 0.458 ± 0.107‰, 0.464 ± 0.086‰, and 0.417 ± 0.089‰ in pure ETH‐4 and ETH‐4 with 2:1 and 1:1 resin mixtures, respectively (p > 0.05). However, a resin‐related bias in the results might be masked by the large uncertainty. The measured ETH‐4 values in our study are similar to the InterCarb values (δ13C = −10.20‰, δ18O = −18.81‰, Δ47 = 0.450‰, InterCarb‐Carbon Dioxide Equilibrium Scale). However, the external SD of Δ47 in sessions measuring ETH‐4 with resins is higher than in sessions without deliberate resin addition for the same measuring period. Conclusions: We find that the potential contamination from the resin addition leads to a larger variability for Δ47 values in sessions measuring ETH‐4 including resins. We therefore recommend purification of embedded samples using a contamination trap with Porapak prior to analysis, if possible, or avoiding resins during sample preparation and workup, as well as monitoring the measurement quality during and after sessions with samples containing embedding resins. [ABSTRACT FROM AUTHOR]

Deep‐red (DR) and near‐infrared (NIR) organic light‐emitting diodes (OLEDs) based on purely organic materials hold great potential in various frontier applications, but purely organic DR/NIR materials are far from satisfactory. Herein, a series of tailor‐made delayed fluorescence luminophores comprised of electron‐withdrawing dipyrido[3,2‐a:2″,3″‐c]phenazine‐11,12‐dicarbonitrile and various electron‐donating triarylamines are developed, and their thermal and electrochemical stabilities, electronic structures, photophysical properties and electroluminescence (EL) performances are investigated. They exhibit strong NIR emissions (758−767 nm) in neat films and DR/NIR emissions (680−691 nm) with good photoluminescence quantum yields (48−60%) in doped films, and prefer ordered horizontal alignment with high horizontal dipole ratios of 82−90%, which are attributed to the hybrid transition components of excited states, extended molecular plane and intramolecular hydrogen‐bonding. Their non‐doped OLEDs emit purely NIR light peaking at 820−834 nm with maximum external quantum efficiencies (ηext,maxs) of 0.66−1.06%, and thier doped OLEDs radiate DR/NIR emissions peaking at 656−748 nm with superb ηext,maxs of 14.4–31.0%. They present even better EL performances in sensitized OLEDs, with DR emissions peaking at 648−656 nm and higher ηext,maxs of 29.7−32.9%. These state‐of‐the‐art EL performances demonstrate the great potential of the developed DR/NIR delayed fluorescence luminophores in practical application. [ABSTRACT FROM AUTHOR]

Summary: In this paper, an efficient wireless power transmission (WPT) system that incorporates a new negative permeability metamaterial is presented. The operating principle of the metamaterial with negative permeability is first analyzed. To improve transmission efficiency of the WPT system at the operating frequency of 13.56 MHz, a new metamaterial with three open rings is designed. By respectively placing a single metamaterial slab and double metamaterial slabs at different positions between transmitting coil and receiving coil, the performance of the proposed WPT system is evaluated by simulation work. The corresponding magnetic field distribution is also analyzed. Besides, comparison is made with the conventional WPT system without metamaterial. It is found that transmission efficiency of the proposed WPT system is obviously improved when incorporating the metamaterial since the designed metamaterial effectively focuses magnetic field towards the receiving coil. Comparing with the conventional system, the results also show that the proposed WPT system is more robust to lateral and angular misalignment of the receiving coil. With the designed metamaterial, it is found that the proposed system with double metamaterial slabs performs better than that with a single metamaterial slab. [ABSTRACT FROM AUTHOR]

Glycerol dialkyl glycerol tetraethers (GDGTs), both archaeal isoprenoid GDGTs (isoGDGTs) and bacterial branched GDGTs (brGDGTs), have been used in paleoclimate studies to reconstruct environmental conditions. Since GDGTs are produced in many types of environments, their relative abundances also depend on the depositional setting. This suggests that the distribution of GDGTs also preserves useful information that can be used more broadly to infer these depositional environments in the geological past. Here, we combined existing iso‐ and brGDGT relative abundance data with newly analyzed samples to generate a database of 1,153 samples from several modern sedimentary settings. We observed a robust relationship between the depositional environment and the relative abundances of GDGTs in our samples. This data set was used to train and test the Branched and isoGDGT Machine learning Classification (BIGMaC) algorithm, which identifies the environment a sample comes from based on the distribution of GDGTs with high precision and recall (F1 = 0.95). We tested the model on the sedimentary record from the Giraffe kimberlite pipe, an Eocene maar in subantarctic Canada, and found that the BIGMaC reconstruction agrees with independent stratigraphic and palynological information, provides new information about the paleoenvironment of this site, and helps improve its paleotemperature reconstruction. In contrast, we also include an example from the PETM‐aged Cobham lignite as a cautionary example that illustrates the limitations of the algorithm. We propose that in cases where paleoenvironments are unknown or are changing, BIGMaC can be applied in concert with other proxies to generate more refined paleoclimate records. Key Points: The distribution of glycerol dialkyl glycerol tetraethers (GDGTs) is particular to each depositional environment and has unique responses to environmental factorsThe BIGMaC algorithm captures the relationship between both branched and isoprenoid GDGTs (isoGDGTs) with depositional environmentsOur approach can provide paleoclimatological and paleoenvironmental information based only on GDGTs [ABSTRACT FROM AUTHOR]

Tactile sensors capable of quantifying mechanical stimuli through physical contact play a pivotal role in healthcare, prosthetics, and humanoid robotics. To enable conformal contact with objects of different surface morphologies, tactile sensors with high mechanical flexibility are extensively explored. Despite recent advances, most of the currently available flexible tactile sensors are based on electrical properties of functional materials, which often suffer from intrinsic limitations such as hysteresis, parasitic effects and electromagnetic interference. Herein, a flexible optical tactile sensor is presented by harnessing the unique optical properties of a soft and plasmonic optical fiber, made from composites of gold nanoparticles and elastomers. The tactile sensor is constructed by assembling the nanocomposite fiber in a sandwich structure, where sensitive and instantaneous sensing of contact force with high precision, low hysteresis, and tunable sensitivity is achieved by transducing mechanical stimuli into interpretable light signals. As demonstrations of its potential, the tactile sensor is utilized for real‐time monitoring of blood pressure, respiration, as well as providing tactile mapping of diverse hand motions. To further verify the feasibility of mimicking tactile perception of human skin, the proposed sensors integrated onto a robotic hand are demonstrated to perceive hardness, roughness, and shape of objects. [ABSTRACT FROM AUTHOR]

Different types of natural K+ channels share similar core modules and cation permeability characteristics. In this study, we have developed novel artificial K+ channels by rebuilding the core modules of natural K+ channels in artificial systems. All the channels displayed high selectivity for K+ over Na+ and exhibited a selectivity sequence of K+≈Rb+ during the transport process, which is highly consistent with the cation permeability characteristics of natural K+ channels. More importantly, these artificial channels could be efficiently inserted into cell membranes and mediate the transmembrane transport of K+, disrupting the cellular K+ homeostasis and eventually triggering the apoptosis of cells. These findings demonstrate that, by rebuilding the core modules of natural K+ channels in artificial systems, the structures, transport behaviors, and physiological functions of natural K+ channels can be mimicked in synthetic channels. [ABSTRACT FROM AUTHOR]

BACKGROUND: Amitraz is one of the critical acaricides/insecticides for effective control of pest infestation of Varroa destructor mite, a devastating parasite of Apis mellifera, because of its low toxicity to honeybees. Previous assays verified that a typical G protein‐coupled receptor, β‐adrenergic‐like octopamine receptor (Octβ2R), is the unique target of amitraz, but the honeybee Octβ2R resists to amitraz. However, the underlying molecular mechanism of the enhanced sensitivity or toxicity of amitraz to mutated honeybee Octβ2RE208V/I335T/I350V is not fully understood. Here, molecular dynamics simulations are employed to explore the implied mechanism of the enhanced sensitivity to amitraz in mutant honeybee Octβ2R. RESULTS: We found that amitraz binding stabilized the structure of Octβ2R, particularly the intracellular loop 3 associated with the Octβ2R signaling. Then, it was further demonstrated that both mutations and ligand binding resulted in a more rigid and compact amitraz binding site, as well as the outward movement of the transmembrane helix 6, which was a prerequisite for G protein coupling and activation. Moreover, mutations were found to promote the binding between Octβ2R and amitraz. Finally, community analysis illuminated that mutations and amitraz strengthened the residue–residue communication within the transmembrane domain, which might facilitate the allosteric signal propagation and activation of Octβ2R. CONCLUSION: Our results unveiled structural determinants of improved sensitivity in the Octβ2R‐amitraz complex and may contribute to further structure‐based drug design for safer and less toxic selective insecticides. © 2022 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Clumped isotope thermometry can independently constrain the formation temperatures of carbonates, but a lack of precisely temperature‐controlled calibration samples limits its application on aragonites. To address this issue, we present clumped isotope compositions of aragonitic bivalve shells grown under highly controlled temperatures (1–18°C), which we combine with clumped isotope data from natural and synthetic aragonites from a wide range of temperatures (1–850°C). We observe no discernible offset in clumped isotope values between aragonitic foraminifera, mollusks, and abiogenic aragonites or between aragonites and calcites, eliminating the need for a mineral‐specific calibration or acid fractionation factor. However, due to non‐linear behavior of the clumped isotope thermometer, including high‐temperature (>100°C) datapoints in linear clumped isotope calibrations causes them to underestimate temperatures of cold (1–18°C) carbonates by 2.7 ± 2.0°C (95% confidence level). Therefore, clumped isotope‐based paleoclimate reconstructions should be calibrated using samples with well constrained formation temperatures close to those of the samples. Plain Language Summary: Clumped isotope analysis is a highly accurate method for reconstructing temperatures in Earth's past climate from calcium carbonate fossils of calcifying organisms. Unfortunately, calibration studies so far were predominantly based on samples of calcite, a common calcium carbonate mineral. It is therefore unknown whether these clumped isotope calibrations yield accurate temperature reconstructions when applied to aragonite, another carbonate mineral which corals and many shells consist of. Therefore, we grew mollusks that build their shell out of aragonite in a lab at constant water temperatures to test the clumped isotope method on aragonitic shells. We find no significant difference in the temperature sensitivity of the method between our aragonites and the previous calibrations and show that the temperature calibration can be improved by combining data from different minerals. However, we find subtle differences in the temperature dependence of clumped isotopes between hot (>100°C) carbonates and cold (<30°C) carbonates, which cause previous calibrations to underestimate temperatures of colder carbonates. We conclude that using carbonate samples grown at temperatures close to the temperatures of the samples used in climate reconstructions can eliminate a bias of 2.7°C, resulting in more accurate reconstructions of past temperatures. Key Points: Precise control on carbonate formation temperatures enables more accurate clumped isotope‐temperature calibrationsIsotopic ordering and acid fractionation in aragonite have a similar temperature dependence as in calcite, enabling combined calibrationsThe Δ47−1T2 $-\frac{1}{{T}^{2}}$ relation in carbonate is non‐linear, therefore adding hot calibration data offsets calibrations in the cold temperature range [ABSTRACT FROM AUTHOR]

Histogram equalization (HE) is a classic and widely used image contrast enhancement algorithm for its good performance and high efficiency. However, over‐enhancement caused by high peak in the histogram affects the subjective quality of the image processed by HE to a large extent. In this paper, a detail weighted histogram equalization (DWHE) method is proposed based on a novel histogram modification (HM) model named partial statistic and global mapping (PSGM) to alleviate high peak and suppress over‐enhancement. Moreover, the authors implement a refined version of gamma correction (GC) named texture enhancement function (TEF) on high‐frequency images to reduce the noise amplification effect. At last, the authors propose a novel adaptively weighted pixel‐level image fusion method to further reduce the phenomenon of over‐enhancement and improve brightness distribution. Both subjective and quantitative evaluations are conducted on images containing a variety of scenes. Compared with several state‐of‐the‐art image enhancement methods, the proposed framework obtained generally the best performance in aspects of both subjective appearance and objective evaluation indices. Therefore, it is proved that the proposed methods can effectively alleviate the over‐enhancement, enrich image details, and efficiently improve the visual quality while preserving the brightness of the image. [ABSTRACT FROM AUTHOR]

Although prion infections cause cognitive impairment and neuronal death, transcriptional and translational profiling shows progressive derangement within glia but surprisingly little changes within neurons. Here we expressed PrPC selectively in neurons and astrocytes of mice. After prion infection, both astrocyte and neuron‐restricted PrPC expression led to copious brain accumulation of PrPSc. As expected, neuron‐restricted expression was associated with typical prion disease. However, mice with astrocyte‐restricted PrPC expression experienced a normal life span, did not develop clinical disease, and did not show astro‐ or microgliosis. Besides confirming that PrPSc is innocuous to PrPC‐deficient neurons, these results show that astrocyte‐born PrPSc does not activate the extreme neuroinflammation that accompanies the onset of prion disease and precedes any molecular changes of neurons. This points to a nonautonomous mechanism by which prion‐infected neurons instruct astrocytes and microglia to acquire a specific cellular state that, in turn, drives neural dysfunction. [ABSTRACT FROM AUTHOR]

Façade defect is an unavoidable and considerable problem to existing buildings and can cause great influence to building owners. The traditional manual façade inspection method is costly, inefficient, and unsafe. Although recent studies achieved the classification of façade defects from images, pixel‐level façade defect segmentation has not been tackled. Therefore, this study proposed and implemented a balanced copy–paste method with the Mask Region‐based Convolutional Neural Network (Mask R‐CNN) model to realize automatic detection and segmentation of façade defects. The proposed balanced copy–paste method was able to improve the recognition accuracy for minority classes and small objects. The proposed method was applied to a façade defect dataset with 2286 images that contained six common categories of defects. Comparisons with three other methods demonstrated that the proposed method could achieve the highest accuracy in defect detection (mean average precision (mAP) = 33.33) and segmentation (mAP = 27.26). Furthermore, compared to the original dataset, the proposed method could result in the greatest accuracy improvement for both minority classes (31% in detection and 32% in segmentation) and small objects (23% in detection and 19% in segmentation). Compared to the traditional over‐sampling method and other methods based on algorithm level, the proposed method also showed higher computational efficiency. [ABSTRACT FROM AUTHOR]

A series of silicide cages with high content of transition metal atoms, CunSi12 (n = 30, 38, and 60) clusters, have been systematically investigated in the framework of density functional theory. Among them, Cu30Si12 with a higher Eb and a lager HOMO‐LUMO gap has been discussed in detail. The hollow cage‐like structure Cu30Si12, which adopts an Ih‐symmetry, can be described as the combination of 12 Cu5Si. Molecular dynamics simulations and vibrational frequency analysis have been conducted to verify its stability. Electron density analysis, natural bond orbitals analysis, and partial density of states analysis have been done to explore the binding characters of Cu30Si12. The results indicate that the σ bonds between Cu and Si atoms are of great importance for structural stability. More importantly, on one hand, CunSi12 (n = 30, 38, and 60) can encapsulate atoms or molecules to regulate their properties. On the other hand, CunSi12 (n = 30, 38, and 60) may be rather tempting for the further semiconductor devices due to the existence of silicon. [ABSTRACT FROM AUTHOR]

Background: Early clinical trials indicate that patients with anaplastic lymphoma kinase (ALK)‐driven non‐small cell lung cancer (NSCLC) have a lower response rate to programmed cell death protein 1 (PD‐1) antibody therapy. However, the specific mechanism underlying this remains unclear. To further explore the characteristics of the tumor microenvironment and determine the potential mechanism of immunotherapy resistance in patients with ALK, we selected another important immune‐related molecule, major histocompatibility complex class I (HLA‐I), as the focus of our study. Methods: We collected the biopsy samples of 140 patients with NSCLC. The number of CD8+ T cells and HLA‐I/programmed cell death 1 ligand 1 (PD‐L1) expression were determined by immunohistochemistry. Disease‐free survival (DFS) and overall survival (OS) were analyzed using the Kaplan–Meier method, and their relationship with patient clinical characteristics analyzed using Cox proportional hazards regression. In addition, we treated ALK‐positive lung cancer cells with ALK inhibitors in vitro to observe changes of HLA‐I. Results: ALK positivity was associated with low membrane PD‐L1 and HLA‐I expression. However, these two indicators were not associated with the prognosis of patients with stage I–IIIa NSCLC. Inhibition of ALK could upregulate HLA‐I membrane expression to a certain extent. Conclusion: Patients with ALK fusion showed downregulation of PD‐L1 and HLA‐I expression on the tumor cell membrane. Inhibition of ALK and its downstream signaling pathway can reverse it. These results suggest that the appropriate combination therapy should be considered for patients with ALK fusion and using targeted therapy at the proper time may increase patient benefits. [ABSTRACT FROM AUTHOR]

Epidermal growth factor receptor (EGFR) is an intensively focused drug target for non‐small cell lung cancer (NSCLC). JBJ‐04–125–02 is an effective ATP‐noncompetitive and T790M/L858R‐selective inhibitor of EGFR, but the implied negative regulation mechanism is not fully clarified. Here, computational approaches were employed to address this. We find that JBJ‐04–125–02 induces contrary effects on the binding of adenosine and phosphate moieties of ATP. The allosteric inhibitor lowers the stability of the hinge region, affecting the anchor of the adenosine portion of ATP, while a more closed conformation of P‐loop is observed and might be unfavorable for the phosphotransfer and product release. The umbrella sampling simulations further demonstrate that less free energy is needed for the initial dissociation of ATP (the adenosine group) from the inactive EGFR in the presence of JBJ‐04–125–02, but more for the phosphate groups egressing from the active cavity. Together, these findings provide a deeper understanding of the negative regulation of JBJ‐04–125–02. Moreover, the key inter‐molecular interactions contributing to ATP binding are identified. Our work might pave the way for designing allosteric drugs targeting EGFR for lung cancer patients, and also suggests that computational techniques are effective for investigating the allosteric mechanism. [ABSTRACT FROM AUTHOR]

Organic light‐emitting diodes (OLEDs) radiating near ultraviolet (NUV) light are of high importance but rarely reported due to the lack of robust organic short‐wavelength emitters. Here, we report a short π‐conjugated molecule (POPCN‐2CP) with high thermal and morphological stabilities and strong NUV photoluminescence. Its neat film exhibits an electroluminescence (EL) peak at 404 nm with a maximum external quantum efficiency (ηext,max) of 7.5 % and small efficiency roll‐off. The doped films of POPCN‐2CP in both non‐polar and polar hosts at a wide doping concentration range (10–80 wt%) achieve high‐purity NUV light (388–404 nm) and excellent ηext,maxs of up to 8.2 %. The high‐level reverse intersystem crossing improves exciton utilization and accounts for the superb ηext,maxs. POPCN‐2CP can also serve as an efficient host for blue fluorescence, thermally activated delayed fluorescence and phosphorescence emitters, providing excellent EL performance via Förster energy transfer. [ABSTRACT FROM AUTHOR]

Developing orange to red purely organic luminescent materials having external quantum efficiencies (ηexts) exceeding 30% is challenging because it generally requires strong intramolecular charge transfer, efficient reverse intersystem crossing (RISC), high photoluminescence quantum yield (ΦPL), and large optical outcoupling efficiency (Φout) simultaneously. Herein, by introducing benzoyl to dibenzo[a,c]phenazine acceptor, a stronger electron acceptor, dibenzo[a,c]phenazin‐11‐yl(phenyl)methanone, is created and employed for constructing orange–red delayed fluorescence molecules with various acridine‐based electron donors. The incorporation of benzoyl leads to red‐shifted photoluminescence with accelerated RISC, reduced delayed lifetimes, and increased ΦPLs, and the adoption of spiro‐structured acridine donors promotes horizontal dipole orientation and thus renders high Φouts. Consequently, the state‐of‐the‐art orange–red organic light‐emitting diodes are achieved, providing record‐high electroluminescence (EL) efficiencies of 33.5%, 95.3 cd A−1, and 93.5 lm W‒1. By referring the control molecule without benzoyl, it is demonstrated that the presence of benzoyl can exert significant positive effect over improving delayed fluorescence and enhancing EL efficiencies, which can be a feasible design for robust organic luminescent materials. [ABSTRACT FROM AUTHOR]

Tailor‐made red thermally activated delayed fluorescence (TADF) molecules comprised of an electron‐withdrawing pyrazino[2,3‐f][1,10]phenanthroline‐2,3‐dicarbonitrile core and various electron‐donating triarylamines are developed. They can form intramolecular hydrogen‐bonding, which is conducive to improving emission efficiency and promoting horizontal orientation and show near infrared (NIR) emissions (692–710 nm) in neat films and red delayed fluorescence (606–630 nm) with high photoluminescence quantum yields (73–90%) in doped films. They prefer horizontal orientation with large horizontal dipole ratios in films, rendering high optical out‐coupling factors (0.39–0.41). Their non‐doped OLEDs exhibit NIR lights (716–748 nm) with maximum external quantum efficiencies (ηext,max) of 1.0–1.9%. And their doped OLEDs radiate red lights (606–648 nm) and achieve record‐beating ηext,max of up to 31.5%. These new red TADF materials should have great potentials in display and lighting devices. [ABSTRACT FROM AUTHOR]

Introduction: Cervical cancer has high mortality, high recurrence and poor prognosis. Although prognostic biomarkers such as clinicopathological features have been proposed, their accuracy and precision are far from satisfactory. Therefore, novel biomarkers are urgently needed for disease surveillance, prognosis prediction and treatment selection. Materials: Differentially expressed genes (DEGs) between cervical cancer and normal tissues from three microarray datasets extracted from the Gene Expression Omnibus platform were identified and screened. Based on these DEGs, a six‐gene prognostic signature was constructed using cervical squamous cell carcinoma and endocervical adenocarcinoma data from The Cancer Genome Atlas. Next, the molecular functions and related pathways of the six genes were investigated through gene set enrichment analysis and co‐expression analysis. Additionally, immunophenoscore analysis and the QuartataWeb Server were employed to explore the therapeutic value of the six‐gene signature. Results: We discovered 178 overlapping DEGs in three microarray datasets and established a six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) prognostic signature with stable and excellent performance in predicting overall survival in different subgroups. Intriguingly, the six‐gene signature was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature might be used for predicting response to immune checkpoint inhibitors (ICIs) and the six genes may serve as new drug targets for cervical cancer. Conclusion: Our study established a novel six‐gene (APOC1, GLTP, ISG20, SPP1, SLC24A3 and UPP1) signature that was closely associated with the immune response and tumour immune microenvironment. The six‐gene signature was indicative of aggressive features of cervical cancer and therefore might serve as a promising biomarker for predicting not only overall survival but also ICI treatment effectiveness. Moreover, three genes (UPP1, ISG20 and GLTP) within the six‐gene signature have the potential to become novel drug targets. [ABSTRACT FROM AUTHOR]

The rational design and fabrication of 2D heterojuctions are proven a promising strategy for boosting the performance of electrocatalysts. Although 2D platinum diselenide (PtSe2) exhibits catalytic activity for hydrogen evolution reaction (HER), the catalytic performance is still unsatisfactory due to its inert basal plane, wide bandgap, and poor electron transfer ability. Herein, a new strategy is reported to construct PtSe2/PtCo heterojunctions by partial selenization of PtCo alloy for high‐efficiency HER electrocatalyst, which exhibits a low overpotential of 38 mV at the current density of 10 mA cm−2, a small Tafel slope of 22 mV dec−1, and a superior stability over 24 h and 1000 cycles. The outstanding HER activity of the catalyst arises from the strong electronic interactions between PtSe2 and PtCo in the heterojunctions, which induce electron transferring from PtSe2 to PtCo and the d‐band center down shifting, and thus optimize the H* adsorption/desorption. This work provides a novel strategy for constructing highly efficient heterostructure electrocatalysts, which facilitates the applications of hydrogen energy conversion. [ABSTRACT FROM AUTHOR]

The increasing scale of the network and the demand for data privacy‐preserving have brought several challenges for existing intrusion detection schemes, which presents three issues: large computational overhead, long training period, and different feature distribution which leads low model performance. The emergence of transfer learning has solved the above problems. However, the existing transfer learning‐based schemes can only operate in plaintext when different domains and clouds are untrusted entities, the privacy during data processing cannot be preserved. Therefore, this paper designs a privacy‐preserving multi‐source transfer learning intrusion detection system (IDS). Firstly, we used the Paillier homomorphic to encrypt models which trained from different source domains and uploaded to the cloud. Then, based on privacy‐preserving scheme, we first proposed a multisource transfer learning IDS based on encrypted XGBoost (E‐XGBoost). The experimental results show that the proposed scheme can successfully transfer the encryption models from multiple source domains to the target domain, and the accuracy rate can reach 93.01% in ciphertext, with no significant decrease in detection performance compared with works in plaintext. The training time of the model is significantly reduced from the traditional hour‐level to the minute‐level. [ABSTRACT FROM AUTHOR]

Developing a classifier to identify the defects from façade images using deep learning requires abundant labeled images. However, it is time‐consuming and uneconomical to label the collected images. Hence, it is desired to train an accurate classifier with only a small amount of labeled data. Therefore, this study proposes a semi‐supervised learning algorithm that uses only a small amount of labeled data for training, but still achieves high classification accuracy. In addition, based on the mean teacher algorithm, this study develops a novel uncertainty filter to select reliable unlabeled data for initial training epochs to further improve the classification accuracy. Validation experiments demonstrate that the proposed method can improve the model accuracy from 79.26% to 84.36% compared to the traditional supervised learning algorithm with 10% of labeled data in a dataset. From another perspective, compared to supervised learning algorithm, the proposed technique can help reduce the time and cost for preparing the labeled data. [ABSTRACT FROM AUTHOR]

This study observed the activities of bromelain in the presence of various cationic surfactants at different temperatures and the conformational changes in bromelain by 1H NMR spectroscopy. We found that the bromelain activity was enhanced by tens to hundreds of micromoles per liter of the surfactant. In the presence of the surfactants, bromelain exhibited good tolerance to a range of substrate temperatures and its thermal stability was also increased. The 1H NMR experiments indicated that when the temperature was increased from 25.0 to 45.0 °C, the protons of bromelain having chemical shifts (δ) between 3.7 and 5.2 ppm moved upfield, while those having δ values between 3.2 and 3.7 ppm moved downfield. In the bromelain/cationic surfactant mixture, the values of δ for the protons in both bromelain and the cationic surfactants decreased, accompanied by the broadening of the half‐peak width of the surfactant protons. These results indicated that both increasing temperature and adding a cationic surfactant made the bromelain chain more flexible and hence, increased the bromelain activity. To the best of our knowledge, this was the first time that the relationship between the protein activity and the 1H NMR data was expounded. [ABSTRACT FROM AUTHOR]

Façade inspection is a regular but necessary maintenance task to ensure the safety, functioning, and aesthetics of a building. Traditional visual identification of façade defects is dangerous, time‐consuming, and insufficient. Based on an image dataset and deep learning algorithms, an automatic façade defects classification technique is developed in this research. A layer‐based categorization rule is proposed to categorize façade defects. To handle the problem of imbalanced data size among defect classes, a meta learning‐based method is applied, which reassigns weights to the training data. Experiments demonstrated that the proposed method had a stronger capacity to deal with the imbalanced dataset problem comparing with previous methods by improving the classification accuracy from 71.43% of a basic convolutional neural network (CNN) model to 82.86% of a meta learning‐based CNN model. [ABSTRACT FROM AUTHOR]

Integration of multiple agent therapy (MAT) into one probe is promising for improving therapeutic efficiency for cancer treatment. However, MAT probe, if entering the cell as a whole, may not be optimal for each therapeutic agent (with different physicochemical properties), to achieve their best performance, hindering strategy optimization. A peptide‐conjugated‐AIEgen (FC‐PyTPA) is presented: upon loading with siRNA, it self‐assembles into FCsiRNA‐PyTPA. When approaching the region near tumor cells, FCsiRNA‐PyTPA responds to extracellular MMP‐2 and is cleaved into FCsiRNA and PyTPA. The former enters cells mainly by macropinocytosis and the latter is internalized into cells mainly through caveolae‐mediated endocytosis. This two‐part strategy greatly improves the internalization efficiency of each individual therapeutic agent. Inside the cell, self‐assembly of nanofiber precursor F, gene interference of CsiRNA, and ROS production of PyTPA are activated to inhibit tumor growth. [ABSTRACT FROM AUTHOR]

Exploring molecular design strategy for efficient luminescent materials is of high academic and industrial significance. In this work, it is demonstrated that the introduction of the functional group 4‐(phenoxazin‐10‐yl)benzoyl to the conventional chromophores of carbazole‐substituted fluorene derivatives can generate robust luminogens with aggregation‐induced delayed fluorescence (AIDF), and subtle molecular structure modulation can result in prodigious differences in photoluminescence (PL) and electroluminescence (EL). The obtained new AIDF materials exhibit high thermal and electrochemical stabilities, but their PL quantum yields and delayed fluorescence can be altered greatly. In consequence, these luminogens show varied EL performances in nondoped organic light‐emitting diodes (OLEDs) with external quantum efficiencies (ηext) ranging from 19.0% to 3.3%. In doped OLEDs, these luminogens can afford higher ηext values of 21.7−24.4% because of enhanced PL efficiencies and/or improved exciton recombination efficiencies. Noticeably, both nondoped OLEDs and doped OLEDs at high doping concentrations enjoy very small efficiency roll‐offs. These findings reveal that the proposed design strategy is feasible and applicable for constructing new AIDF luminogens for the fabrication of high‐performance OLEDs with greatly advanced efficiency stability. [ABSTRACT FROM AUTHOR]

The authors analyse the security threats caused by personal wireless local area network (WLAN) sharing, propose schemes under two different conditions, and evaluate the performance of their schemes. WLAN is a widely used low‐cost wireless networking technology. Most personal WLANs use the Wi‐Fi‐protected access II (WPA2)‐personal to ensure robust security. Exposing the passphrase of WLAN is the only way to share it. Passphrase exposure can cause three threats, i.e. eavesdropping, evil twin attack, and resource abuse. This study addresses these threats by proposing two schemes under different device upgrade difficulties. For devices that are difficult to upgrade, their scheme only upgrades wireless routers. All WPA2‐personal certified user devices can address these threats without any changes. For easy‐upgrade and new devices, their scheme uses the attribute‐based key exchange to address threats and provide ease of use, anonymity, and fine‐grained access control. To solve the problem practically, they propose a mutual authentication method based on trust‐on‐first‐use and a convenient attribute assignment method based on the existence of social information. The attribute authority already has numerous social information to provide services and cannot obtain more private information from participants in their scheme. The analysis shows that these proposed schemes are secure and practical. [ABSTRACT FROM AUTHOR]

Prion immunotherapy may hold great potential, but antibodies against certain PrP epitopes can be neurotoxic. Here, we identified > 6,000 PrP‐binding antibodies in a synthetic human Fab phage display library, 49 of which we characterized in detail. Antibodies directed against the flexible tail of PrP conferred neuroprotection against infectious prions. We then mined published repertoires of circulating B cells from healthy humans and found antibodies similar to the protective phage‐derived antibodies. When expressed recombinantly, these antibodies exhibited anti‐PrP reactivity. Furthermore, we surveyed 48,718 samples from 37,894 hospital patients for the presence of anti‐PrP IgGs and found 21 high‐titer individuals. The clinical files of these individuals did not reveal any enrichment of specific pathologies, suggesting that anti‐PrP autoimmunity is innocuous. The existence of anti‐prion antibodies in unbiased human immunological repertoires suggests that they might clear nascent prions early in life. Combined with the reported lack of such antibodies in carriers of disease‐associated PRNP mutations, this suggests a link to the low incidence of spontaneous prion diseases in human populations. Synopsis: This study assessed the anti‐prion protein (PrP) immunoreactivity in human immunoglobulin repertoires and patient samples. Anti‐PrP autoimmunity can exist in human communities, appears to be innocuous, and may protect against prion infections. >6,000 antibodies against various PrP epitopes were recovered from a synthetic human antibody (Fab) phage library.Of the phage display derived Fabs, 49 Fabs were characterized in detail. Fabs directed against the N‐terminal flexible tail of PrP conferred neuroprotection against infectious prions.HCDR3 sequences similar to a protective phage‐derived Fab were identified in published repertoires of B cells from healthy humans. When expressed recombinantly, these antibodies reacted to human PrP.By interrogating a large cohort of 37,894 hospital patients, twenty‐one individuals with high‐titer anti‐PrP autoreactivity in the plasma were found.The presence of anti‐PrP autoantibodies did not correlate to any neurological condition or any other diseases. [ABSTRACT FROM AUTHOR]

Designing gradient energy levels is an effective method to improve the photocatalytic performance of the semiconductor materials. In this work, we propose a core‐shell structured material with micro‐sized spherical SrTiO3/TiO2 (abbreviated as SrT) as the core material, and the rod‐shaped ZnO shell attaching on the surface of SrT, which forms a hierarchical spherical composite with rambutan‐like shape. During the synthesis process, ZnO seeds are coated on the surface of SrT microspheres firstly, and then they transfer to nanorods with a diameter of 60–70 nm and a length of less than 100 nm under the growth solution medium at 90 °C with the volume ratio of zinc nitrate to hexamethylenetetramine (abbreviated as HMT) is 1 : 1 and the concentration is 0.05 mol/L. This structure may further facilitate the separation of the photo‐generated electron‐hole pairs and widen the photocatalytic applications of perovskite structured SrTiO3 or anatase structured TiO2 with visible excitation response. [ABSTRACT FROM AUTHOR]

Objective: To compare survival outcomes of minimally invasive surgery (MIS) and laparotomy in early‐stage cervical cancer (CC) patients. Methods: A multicenter retrospective cohort study was conducted with International Federation of Gynecology and Obstetrics (FIGO, 2009) stage IA1 (lymphovascular invasion)‐IIA1 CC patients undergoing MIS or laparotomy at four tertiary hospitals from 2006 to 2017. Propensity score matching and weighting and multivariate Cox regression analyses were performed. Survival was compared in various matched cohorts and subgroups. Results: Three thousand two hundred and fifty‐two patients (2439 MIS and 813 laparotomy) were included after matching. (1) The 2‐ and 5‐year recurrence‐free survival (RFS) (2‐year, hazard ratio [HR], 1.81;95% confidence interval [CI], 1.09‐3.0; 5‐year, HR, 2.17; 95% CI, 1.21‐3.89) or overall survival (OS) (2‐year, HR, 1.87; 95% CI, 1.03‐3.40; 5‐year, HR, 2.57; 95% CI, 1.29‐5.10) were significantly worse for MIS in patients with stage I B1, but not the cohort overall (2‐year RFS, HR, 1.04; 95% CI, 0.76‐1.42; 2‐year OS, HR, 0.99; 95% CI, 0.70‐1.41; 5‐year RFS, HR, 1.12; 95% CI, 0.76‐1.65; 5‐year OS, HR, 1.20; 95% CI, 0.79‐1.83) or other stages (2) In a subgroup analysis, MIS exhibited poorer survival in many population subsets, even in patients with less risk factors, such as patients with squamous cell carcinoma, negative for parametrial involvement, with negative surgical margins, negative for lymph node metastasis, and deep stromal invasion < 2/3. (3) In the cohort treated with (2172, 54%) or without adjuvant treatment (1814, 46%), MIS showed worse RFS than laparotomy in patients treated without adjuvant treatment, whereas no differences in RFS and OS were observed in adjuvant‐treatment cohort. (4) Inadequate surgeon proficiency strongly correlated with poor RFS and OS in patients receiving MIS compared with laparotomy. Conclusions: MIS exhibited poorer survival outcomes than laparotomy group in many population subsets, even in low‐risk subgroups. Therefore, laparotomy should be the recommended approach for CC patients. [ABSTRACT FROM AUTHOR]