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Synergistic factors can enhance the toxicity of Bt toxins and delay the development of Bt resistance. Previous research has demonstrated that a Helicoverpa armigeracadherin fragment (HaCad-TBR) increased the toxicity of Cry1Ac in Plutella xylostellalarvae but did not have a synergistic effect on Cry1B, Cry1C, and Cry1F toxins. In this study, a fusion protein (HaCad-TBR-2D3 VL) derived from HaCad-TBR and a Bt Cry1-specific antibody peptide was expressed in Escherichia coli. The HaCad-TBR-2D3 VLenhanced Cry1Ac toxicity more efficiently in insects and Sf9 cells than HaCad-TBR and also significantly increased the toxicity of Cry1B, Cry1C, and Cry1F toxins in insects. Further investigation indicated that the improved stability in insect midguts and higher binding capacity with Bt toxins contributed to the enhanced synergism of HaCad-TBR-2D3 VLover HaCad-TBR. This study suggested that Bt antibody fragments can potentially broaden the synergistic range of Bt receptor fragments, providing a theoretical foundation for developing broad-spectrum synergists for other biopesticides.

The goal of infrared and visible image fusion (IVIF) is to combine complementary information from the source images. However, due to the absence of ground truth, most fusion algorithms just utilize information from source images, which cannot provide targeted guidance for network learning, leading to suboptimal outcomes. Moreover, numerous methods focus solely on modifying network architecture to improve fusion performance, without optimizing fusion algorithms from other perspectives. To tackle these problems, we propose a real-time end-to-end IVIF network based on an adaptive guidance module (AGMFusion). On the one hand, by combining the state-of-the-art (SOTA) methods and best fusion outcomes during the training process, the adaptive guidance module (AGM) effectively facilitates collaborative guidance for network training. Additionally, based on the AGM, we devise a loss function that includes content loss and guidance loss. We further balance these two loss components with the adaptive weight to boost the performance of our framework. On the other hand, AGMFusion is a lightweight image fusion framework that can generate highly perceptual fused images while maintaining excellent real-time performance, which can be potentially deployed as a preprocessing unit for various vision tasks. According to extensive comparative and generalization experiments, AGMFusion exceeds existing methods in visual appeal and quantitative metrics. Importantly, performance comparisons of numerous frameworks in running efficiency and object detection highlight the advantages of our approach. The source code will be released at https://github.com/liushh39/AGMFusion.

ABSTRACTInfrared small target detection (ISTD) is a significant technique for search and rescue applications. The lack of intrinsic target features and complex backgrounds make small target detection challenging. Furthermore, existing deep learning-based methods overlook the imbalance among categories when designing supervision method. For robust detection, we propose a Pyramid Attention U-shaped network (PAU2-Net) in this paper. Specifically, we designed a pyramid attention encoder to establish long-range channel dependencies and enhance the interaction between local and global information. It extracts small target features and enhances high-level understanding of the scene at the same time, which helps reduce false alarm rates. In our proposed adaptive multiscale supervision method, we generate a group of multiscale labels by pooling to guide the deep outputs of the network. The labels maintain the target position information at different scales and help preserving the target information as the network deepens. Comparison experiments on SIRST-V2 and NUDT-SIRST datasets show that our method can achieve superior performance in terms of detection rate and precision compared with the state-of-the-art algorithms.

Semiconducting carbon nanotubes (s-CNTs) have emerged as a promising alternative to traditional silicon for ultrascaled field-effect transistors (FETs), owing to their exceptional properties. Aligned s-CNTs (A-CNTs) are particularly favored for practical applications due to their ability to provide higher driving current and lower contact resistance compared with individual s-CNTs or random networks. Achieving high-semiconducting-purity A-CNTs typically involves conjugated polymer wrapping for selective separation of s-CNTs, followed by self-assembly techniques. However, the presence of the polymer wrapper on A-CNTs can adversely impact electrical contact, gating efficiency, carrier transport, and device-to-device variations, necessitating its complete removal. While various methods have been explored for polymer removal, accurately characterizing the extent of removal remains a challenge. Traditional techniques such as absorption spectroscopy and X-ray photoelectron spectroscopy (XPS) may not accurately depict the remaining polymer content on A-CNTs due to their inherent detection limits. Consequently, the performance of FETs based on pure polymer-wrapper-free A-CNTs is unclear. In this study, we present an approach for preparing high-semiconducting-purity and polymer-wrapper-free A-CNTs using poly[(9,9-dioctylfluorenyl-2,7-dinitrilomethine)-(9,9-dioctylfluorenyl-2,7-dimethine)] (PFO-N-PFO), a degradable polymer, in conjunction with a modified dimension-limited self-alignment process (m-DLSA). Comprehensive transmission electron microscopy (TEM) characterizations, complemented by absorption and XPS characterizations, provide robust evidence of the successful near-complete removal of the polymer wrapper via a cleaning procedure involving acidic degradation, hot solvent rinsing, and vacuum annealing. Furthermore, top-gated FETs based on these high-semiconducting-purity and polymer-wrapper-free A-CNTs exhibit good performance metrics, including an on-current (Ion) of 2.2 mA/μm, peak transconductance (gm) of 1.1 mS/μm, low contact resistance (Rc) of 191 Ω·μm, and negligible hysteresis, representing a significant advancement in the CNT-based FET technology.

A deep understanding of the interface states in metal–oxide–semiconductor (MOS) structures is the premise of improving the gate stack quality, which sets the foundation for building field-effect transistors (FETs) with high performance and high reliability. Although MOSFETs built on aligned semiconducting carbon nanotube (A-CNT) arrays have been considered ideal energy-efficient successors to commercial silicon (Si) transistors, research on the interface states of A-CNT MOS devices, let alone their optimization, is lacking. Here, we fabricate MOS capacitors based on an A-CNT array with a well-designed layout and accurately measure the capacitance–voltage and conductance–voltage (C–V and G–V) data. Then, the gate electrostatics and the physical origins of interface states are systematically analyzed and revealed. In particular, targeted improvement of gate dielectric growth in the A-CNT MOS device contributes to suppressing the interface state density (Dit) to 6.1 × 1011cm–2eV–1, which is a record for CNT- or low-dimensional semiconductors-based MOSFETs, boosting a record transconductance (gm) of 2.42 mS/μm and an on–off ratio of 105. Further decreasing Ditbelow 1 × 1011cm–2eV–1is necessary for A-CNT MOSFETs to achieve the expected high energy efficiency.

Investigating the ternary relationship among nanoparticles (NPs), their immediate molecular environment, and test organisms rather than the direct interaction between pristine NPs and test organisms has been thrust into the mainstream of nanotoxicological research. Diverging from previous work that predominantly centered on surrounding molecules affecting the toxicity of NPs by modulating their nanoproperties, this study has unveiled a novel dimension: surrounding molecules altering bacterial susceptibility to NPs, consequently impacting the outcomes of nanobio interaction. The study found that adding nitrate as the surrounding molecules could alter bacterial respiratory pathways, resulting in an enhanced reduction of ceria NPs (nanoceria) on the bacterial surfaces. This, in turn, increased the ion-specific toxicity originating from the release of Ce3+ions at the nanobio interface. Further transcriptome analysis revealed more mechanistic details underlying the nitrate-induced changes in the bacterial energy metabolism and subsequent toxicity patterns. These findings offer a new perspective for the deconstruction of nanobio interactions and contribute to a more comprehensive understanding of NPs’ environmental fate and ecotoxicity.

The formation and dynamics of granitoids in an intra-continental setting are crucial for understanding the architecture and evolution of continental crust. Here, we report geochronological, geochemical and Sr–Nd–Hf isotopic data for newly discovered late Mesozoic granitic intrusions in the Tianshan belt, northwestern China. These granitoids are I-type granites derived from an igneous precursor and were emplaced at c. 145–132 Ma. They have positive ε Nd(t) values and young Nd model ages, together with relatively low Sr/Y ratios, indicating that they might have originated from partial melting of the juvenile lower crust. There is a prominent decoupling between zircon Hf and bulk-rock Nd isotopes, which may have resulted from the early crystallization of Ti-rich minerals. These granitic intrusions also display subduction-related geochemical characteristics, which are probably inherited from Paleozoic crustal sources that were metasomatized by subduction-related fluids. We conclude that these late Mesozoic granitoids were emplaced in an intra-continental setting, and were probably triggered by thermal relaxation owing to crustal shortening and thickening. These data further imply that the Tianshan changed into crustal reworking during the Mesozoic from its prominent crustal growth in the Paleozoic. Supplementary material: LA-ICP-MS zircon U–Pb dating results, whole-rock major and trace element compositions, whole-rock Sr–Nd isotopic data and zircon Lu–Hf isotopic data are available at https://doi.org/10.6084/m9.figshare.c.7167890 Thematic collection: This article is part of the Mesozoic and Cenozoic tectonics, landscape and climate change collection available at: https://www.lyellcollection.org/topic/collections/mesozoic-and-cenozoic-tectonics-landscape-and-climate-change [ABSTRACT FROM AUTHOR]

Byline: Jing. Tian, Tiankai. Bai, Zhiyong. Zhang, Xuan. Zhai, Kangmin. Wang, Xingyi. Gao, Bin. Yan Pancreatic cancer (PC) is a highly malignant tumor with an increasing incidence rate in recent [...]

Coordination engineering was employed to optimize the coordination environment of the zirconium (Zr) atom anchored on the porphyrins (PP), serving as single-atom catalysts (SACs). Five promising ZrPP-A (A = C3O, N4, N2C2-o, C2O2-o, and C2O2-n) candidates as electrocatalysts for nitrogen reduction reaction (NRR) were identified through a “four-step” screening strategy, from a pool of 15 designed models. Performance evaluation of these candidates for NRR was conducted using first-principles calculations. A comprehensive examination of reaction pathways unveiled a predilection for a hybrid pathway when employing the selected catalysts for the NRR. The stability and notable catalytic activity of ZrPP-A stemmed from orbital hybridization and charge transfer mechanisms, occurring both between Zr and its coordinated atoms, as well as between ZrPP-A and the adsorbed N2molecule. Zr played a pivotal role in orchestrating charge transfer during the NRR process. Simultaneously, coordinating atoms and the PP moiety collectively facilitated supplementary charge transfers to or from the adsorbate. Because of the robust coupling between O and its neighboring carbon atoms, no significant bonds were detected between the central Zr and the coordinating O atoms. An asymmetric coordination environment results in an uneven charge distribution within the substrate, inducing polarization of N2molecules and their migration toward regions of asymmetric charge aggregation. This study underscores the significance of not only focusing on the single-atom catalyst itself but also its coordination environment when designing catalysts for enhanced efficiency.

Objective To characterise the morphology of temporal bone in patients with craniofacial microsomia (CFM).Design A retrospective study.Setting A craniofacial centre.Patients Ninety-four patients with unilateral craniofacial microsomia.Interventions Mimics 21.0 (Materialise Inc., Belgium) was used to locate temporal bone landmarks on preoperative computed tomography data. The spatial Cartesian coordinate system was established in 3-matic 13.0 (Materialise Inc., Belgium). The coordinates of each landmark and the distances and angles between the landmarks were calculated. A classification system was used to quantify the severity of the zygomatic arch deformity.Main outcome measure(s) The bilateral differences in coordinates, linear and angular measurements, and the severity of temporal bone deformity (TTL δ, Psag δ, Paxiδ, and Tsag δ) among the groups were compared using the paired t-test and Kruskal-Wallis test, respectively.Results Compared to those of the unaffected side, the landmarks of the inner ear and petrous part on the affected side showed a decrease in the Z-coordinate or an increase in the X-coordinate. A superolateral rotation tendency of the temporal bone on the affected side was found. There were no significant differences in the linear and angular measurements between the groups. The degree of zygomatic arch deformation was lower in the mild group; however, no significant difference was found between the moderate and severe groups.Conclusions In patients with CFM, asymmetry of the temporal bone and its inner organs (vestibulocochlear organ, facial nerve, and vessels) exists in multiple dimensions; its severity is not completely consistent with the degree of mandibular involvement.

The semiconducting carbon nanotube (CNT) has been considered a promising candidate for future radiofrequency (RF) electronics due to its excellent electrical properties of high mobility and small capacitance. After decades of development, great progress has been achieved on CNT-based RF field-effect transistors (FETs). However, almost all elevations are owing to advancement of the CNT materials and fabrication process, while the study of device architecture is seldom considered and reported. In this work, we innovatively combined device architecture and related doping processes to further optimize CNT-based RF FETs by guiding process or materials with collaborative optimization for the first time and explore their effect on device performance carefully and statistically. Based on more mature random-oriented CNT materials, we fabricated CNT-based RF FETs having three different gate positions of device architecture variation accompanied by suitable doping schemes. The optimized FETs obtained 2–3 times of current density (transconductance) and 1.3 times the cutoff frequency and maximum oscillation frequency compared with unoptimized devices at the same channel length. After transistor-level verification of effect, we further built a CNT RF amplifier and demonstrated almost 10 dB of transducer gain improvement operating at 8 GHz for X-band application. The achieved results from this work would help further improve CNT RF performance beyond the materials and process point of view.

Aiming at the problem of adopting the same level of privacy protection for sensitive data in the process of data collection and ignoring the difference in privacy protection requirements, the authors propose an adaptive personalized randomized response method based on local differential privacy (LDP-APRR). LDP-APRR determines the sensitive level through the user scoring strategy, introduces the concept of sensitive weights for adaptive allocation of privacy budget, and realizes the personalized privacy protection of sensitive attributes and attribute values. To verify the distorted data availability, LDP-APRR is applied to frequent items mining scenarios and compared with mining associations with secrecy konstraints (MASK), and grouping-based randomization for privacy-preserving frequent pattern mining (GR-PPFM). Results show that the LDP-APRR achieves personalized protection of sensitive attributes and attribute values with user participation, and the maxPrivacy and avgPrivacy are improved by 1.2% and 4.3%, respectively, while the availability of distorted data is guaranteed.

Electrostatic discharge is one of the ignition sources that cause aircraft fuel tank fires and explosions. The airworthiness regulations and advisory circulars propose the design of a piccolo diffuser to limit the fuel flow velocity to prevent the occurrence of sparks or arc discharges in fuel tanks due to fuel flow. However, the airworthiness regulations and advisory circulars do not provide specific guidance on how to carry out the design of piccolo diffusers, and at the same time, the current perforated tube design method cannot be used to obtain a diffuser that meets the airworthiness technical requirements. Therefore, combined with the knowledge of fluid mechanics, the design method of piccolo tube diffuser is analyzed and discussed in this paper. Taking the design of piccolo tube diffuser for a certain type of aircraft as an example, the structural parameters of piccolo tube such as the diameter of the holes, the method of distributing the orifices, and the position and height of the baffle plates are optimized based on the computational fluid dynamics (CFD) method, and the design result that meets the requirements of fuel flow velocity limitation is obtained. The results show that the diffuser design method with built-in baffle plates can regulate the pressure inside the tube and solve the problem of uneven distribution of outlet flow velocity, compared with the current design method of perforated tubes. Based on the calculation results, the design principle of built-in baffle plates is concluded, and a universal design method of piccolo tube fuel diffuser with built-in baffle plates is proposed, which can meet the double requirements of high refueling efficiency and low flow velocity limitation at the same time. It makes up for the lack of design details in AC 25.981-1D and provides useful guidance for the design of piccolo tube diffusers that meet airworthiness requirements.

In the existing statistics-based PRI estimation method, it is difficult to improve the PRI estimation accuracy due to the contradiction between the width of the statistical interval and the PRI extraction accuracy. In order to improve the accuracy of PRI estimation, a radar signal PRI estimation and deinterleaving method based on the density-based clustering is proposed in this paper. The dense area of the time of arrival (TOA) difference sequence near the true PRI value is extracted out by density-based clustering. The intra-class mean value is taken as the PRI estimation value and the intra-class point dispersion interval length as the PRI jitter amplitude. Combined with the sequence searching method with dynamic tolerance, the pulse sequence with a large number of pulses and small PRI jitter is preferentially extracted, which can improve the accuracy of signal deinterleaving. The simulation results show that the proposed method can significantly improve the accuracy of PRI estimation and the success rate of signal deinterleaving in the case of PRI jitter and false pulse interference.

The ability to suppress fuel tank ignition and explosion is related to passenger safety and aircraft survivability. To enhance aircraft fuel tank safety, the on-board fuel tank inerting technology is applied to reduce the probability of fuel tank ignition and explosion, whether the fuel tank has open or closed vent system. This paper takes the single-bay fuel tank of a certain type of aircraft as the research object, establishes mathematical models of the inerting process of open and closed vent systems fuel tanks, and writes programs to carry it out based on MATLAB R2019b combined with the numerical calculation method of microelement integration according to the actual on-board hollow fiber membrane separation performance. On this basis, this paper analyzes the variation of oxygen concentration in the ullage of open and closed vent systems fuel tanks, compares their advantages and disadvantages, and explores the influence of factors on the inerting effect, such as initial oxygen concentration, fuel loading, aeration pressure, and valve diameter. The results show that for the same nitrogen-enriched air (NEA) flow rate and concentration, the inerting effect of the closed vent system fuel tank is better than the open vent system fuel tank, which can better meet the airworthiness regulations requirements on the flammability exposure time. The initial fuel loading and oxygen concentration have a more significant effect on the initial stage of inerting. Within the range of the vent valve diameters considered in this study, any appreciable difference in the oxygen concentration behavior could not be identified. When the tank pressure conditions permit, it is recommended to use a larger valve threshold to better utilize the good inerting effect of the closed vent system fuel tank.

Factor analysis is widely utilized to identify latent factors underlying the observed variables. This paper presents a comprehensive comparative study of two widely used methods for determining the optimal number of factors in factor analysis, the K1 rule, and parallel analysis, along with a more recently developed method, the bass-ackward method. We provide an in-depth exploration of these techniques, discussing their historical development, advantages, and limitations. Using a series of Monte Carlo simulations, we assess the efficacy of these methods in accurately determining the appropriate number of factors. Specifically, we examine two cessation criteria within the bass-ackward framework: BA-maxLoading and BA-cutoff. Our findings offer nuanced insights into the performance of these methods under various conditions, illuminating their respective advantages and potential pitfalls. To enhance accessibility, we create an online visualization tool tailored to the factor structures generated by the bass-ackward method. This research enriches the understanding of factor analysis methodology, assists researchers in method selection, and facilitates comprehensive interpretation of latent factor structures.

With the increment of data sets and models sizes, distributed deep learning has been proposed to accelerate training and improve the accuracy of DNN models. The parameter server framework is a popular collaborative architecture for data-parallel training, which works well for homogeneous environments by properly aggregating the computation/communication capabilities of different workers. However, in heterogeneous environments, the resources of different workers vary a lot. Some stragglers may seriously limit the whole speed, which impacts the overall training process. In this paper, we propose an adaptive multi-stage distributed deep learning training framework, named ASHL, for heterogeneous environments. First, a profiling scheme is proposed to capture the capabilities of each worker to reasonably plan the training and communication tasks on each worker, and lay the foundation for the formal training. Second, a hybrid-mode training scheme (i.e., coarse-grained and fined-grained training) is proposed to balance the model accuracy and training speed. The coarse-grained training scheme (named AHL) adopts an asynchronous communication strategy, which involves less frequent communications. Its main goal is to make the model quickly converge to a certain level. The fine-grained training stage (named SHL) uses a semi-asynchronous communication strategy and adopts a high communication frequency. Its main goal is to improve the model convergence effect. Finally, a compression-based communication scheme is proposed to further increase the communication efficiency of the training process. Our experimental results show that ASHL reduces the overall training time by more than 35% to converge to the same degree and has better generalization ability compared with state-of-the-art schemes like ADSP.

Recently, deep learning has been widely employed to improve the quality of low-light videos. However, most existing low-light video enhancement methods fail to effectively explore temporal dependence, and the enhanced videos may suffer from severe noise, loss of detailed texture, and temporal inconsistency. In this paper, we propose a novel SNR-prior Guided Trajectory-aware Transformer (SGTT) to enable effective video representation learning for low-light video enhancement. Specifically, signal-to-noise ratio prior and cosine similarity are introduced to build the trajectory-aware dual-attention for exploiting the dependence of long-range spatio-temporal information, which searches for sharper and highly correlated patches within the same trajectory to assist in enhancing the target frames. Moreover, to adaptively fuse spatio-temporal information of support frames propagated bidirectionally, an attention-guided spatio-temporal feature aggregation module is proposed to perceive and enhance the specific high-quality features. The evaluation of both dynamic and static videos shows the effectiveness of our network, which significantly outperforms the state-of-the-art methods.

To address the challenge of label-scarce images captured by sensor in foggy weather condition with limited labeled data for autonomous driving, domain adaptation can be applied to transfer information from a label-rich clear-weather dataset to a label-scarce adverse weather dataset. This article proposes a novel approach named curriculum pseudo label transformer (CPLT) for domain adaptive object detection (DAOD). CPLT incorporates two effective techniques to enhance the transformer’s ability to detect objects across domain. First, distribution alignment curriculum (DAC) pseudo label is proposed. The key idea of DAC is to flexibly adjust class-specific thresholds by aligning the class distribution over the course of training. The second technique employed in CPLT is called instance-level feature optimal transport (IFOT), which applies sliced Wasserstein distance to minimize domain discrepancy in instance-level features while preserving the location information. Importantly, neither of these modules introduce additional trainable parameters in the network. Experimental results on five challenging benchmarks demonstrate that CPLT significantly improves domain adaptation object detection performance.

Molecular diffusion and leakage impede the long-term retention of probes/drugs and may cause potential adverse effects in theranostic fields. Spatiotemporally manipulating the organelle-immobilization behavior of probes/drugs for prolonged tumor retention is indispensable to achieving effective cancer diagnosis and therapy. Herein, we propose a rational strategy that could realize near-infrared light-activated ribonucleic acids (RNAs) cross-linking for prolonged tumor retention and simultaneously endogenous hydrogen sulfide (H2S) monitoring in colorectal tumors. Profiting from efficient singlet oxygen (1O2) generation from Cy796 under 808 nm light irradiation, the 1O2-animated furan moiety in Cy796 could covalently cross-link with cytoplasmic RNAs via a cycloaddition reaction and realize organelle immobilization. Subsequently, specific thiolysis of Cy796 assisted with H2S resulted in homologous product Cy644 with reduced 1O2generation yields and enhanced absolute fluorescence quantum yields (from 7.42 to 27.70%) with blue-shifted absorption and emission, which avoided the molecular oxidation fluorescence quenching effect mediated by 1O2and validated fluorescence imaging. Furthermore, studies have demonstrated that our proposed strategy possessed adequate capacity for fluorescence imaging and endogenous H2S detection in HCT116 cells, particularly accumulated at the tumor sites, and retained long-term imaging with excellent biocompatibility. The turn-on fluorescence mode and turn-off 1O2generation efficiency in our strategy successfully realized a diminished fluorescence cross-talk and oxidation quenching effect. It is adequately envisioned that our proposed strategy for monitoring biomarkers and prolonged tumor retention will contribute tremendous dedication in the clinical, diagnostic, and therapeutic fields.

This paper proposes a hierarchical framework for industrial Internet device authentication and trusted access as well as a mechanism for industrial security state perception, and designs a cross-domain authentication scheme for devices on this basis. The scheme obtains hardware device platform configuration register (PCR) values and platform integrity measure through periodic perception, completes device identity identification and integrity measure verification when device accessing and data transmission requesting, ensures secure and trustworthy access and interoperation of devices, and designs a cross-domain authentication model for trustworthy access of devices and related security protocols. Through the security analysis, this scheme has good anti-attack abilities, and it can effectively protect against common replay attacks, impersonation attacks, and man-in-the-middle attacks.

In the era of big data, the growing demand for data transmission capacity requires the communication band to expand from the traditional optical communication windows (∼1.3–1.6 μm) to the 2 μm band (1.8–2.1 μm). However, the largest bandwidth (∼30 GHz) of the current high-speed photodetectors for the 2 μm window is considerably less than the developed 1.55 μm band photodetectors based on III–V materials or germanium (>100 GHz). Here, we demonstrate a high-performance carbon nanotube (CNT) photodetector that can operate in both the 2 and 1.55 μm wavelength bands based on high-density CNT arrays on a quartz substrate. The CNT photodetector exhibits a high responsivity of 0.62 A/W and a large 3 dB bandwidth of 40 GHz (setup-limited) at 2 μm. The bandwidth is larger than that of existing photodetectors working in this wavelength range. Moreover, the CNT photodetector operating at 1.55 μm exhibits a setup-limited 3 dB bandwidth over 67 GHz at zero bias. Our work indicates that CNT photodetectors with high performance and low cost have great potential for future high-speed optical communication at both the 2 and 1.55 μm bands.

An aligned semiconducting carbon nanotube (A-CNT) array has been considered an excellent channel material to construct high-performance field-effect transistors (FETs) and integrated circuits (ICs). The purification and assembly processes to prepare a semiconducting A-CNT array require conjugated polymers, introducing stubborn residual polymers and stress at the interface between A-CNTs and substrate, which inevitably affects the fabrication and performance of the FETs. In this work, we develop a process to refresh the Si/SiO2substrate surface underneath the A-CNT film by wet etching to clean the residual polymers and release the stress. Top-gated A-CNT FETs fabricated with this process show significant performance improvement especially in terms of saturation on-current, peak transconductance, hysteresis, and subthreshold swing. These improvements are attributed to the increase in carrier mobility from 1025 to 1374 cm2/Vs by 34% after the substrate surface refreshing process. Representative 200 nm gate-length A-CNT FETs exhibit an on-current of 1.42 mA/μm and a peak transconductance of 1.06 mS/μm at a drain-to-source bias of 1 V, subthreshold swing (SS) of 105 mV/dec, and negligible hysteresis and drain-induced barrier lowering (DIBL) of 5 mV/V.

N6‐methyl adenosine (m6A) modifications of mRNA and long non‐coding RNA (lncRNAs) are known to play a significant role in regulation of gene expression and organismal development. Besides writer and eraser proteins of this dynamic modification, the YT521‐B homology (YTH) domain can recognize the modification involved in numerous cellular processes. The function of proteins containing YTH domain and its binding mode with N6‐Methyladenosine RNA has attracted considerable attention. However, the structural and dynamic characteristics of the YTH domain in complex with m6A RNA is still unknown. This work presents results of accelerated molecular dynamics (aMD) simulations at the timescale of microseconds. Principal component analysis (PCA), molecular mechanics generalized Born surface area (MM/GBSA) calculations, contact analysis and contact‐based principal component analysis (conPCA) provide new insights into structure and dynamics of the YTH‐RNA complex. The aMD simulations indicate that the recognition loop has a larger movement away from the binding pocket in the YTH‐A3 RNA than that in the YTH‐m6A3 RNA. In aMD trajectories of the apo YTH, there is a significant close‐open transition of the recognition loop, that is to say, the apo YTH can take both the closed and open structure. We have found that the YTH domain binds more favorably to the methylated RNA than the non‐methylated RNA. The per‐residue free energy decomposition and conPCA suggest that hydrophobic residues including W380, L383‐V385, W431‐P434, M437, and M441‐L442, may play important roles in favorable binding of the m6A RNA to the YTH domain, which is also supported by aMD simulations of a double mutated system (L383A/M437A). The results are in good agreement with higher structural stability of the YTH‐m6A RNA than that of the YTH‐A3 RNA. The addition of a methylation group on A3 can enhance its binding to the hydrophobic pocket in the YTH domain. Our simulations support a ‘conformational selection’ mechanism between the YTH‐RNA binding. This work may aid in our understanding of the structural and dynamic characteristics of the YTH protein in complex with the methylated RNA. Author summary:N6‐methyl adenosine (m6A) modifications play an important role in the regulation of RNA decay and gene expression at the post‐transcriptional level. The YT521‐B homology (YTH) domain‐containing proteins can recognize m6A in numerous cellular processes. However, the binding mode of the YTH domain to m6A RNA is still unknown. In this work, we present an atomic description of the YTH‐m6A RNA complex using computer simulations. The results have revealed the molecular mechanism of the RNA binding to the YTH domain. Our findings may be helpful for understanding the structural and dynamic characteristics of the YTH‐m6A RNA complex.

Recent advances in carbon nanotube (CNT)-based integrated circuits have shown their potential in deep space exploration. In this work, the mechanism governing the heavy-ion-induced displacement damage (DD) effect in semiconducting single-walled CNT field effect transistors (FETs), which is one of the factors limiting device robustness in space, was first and thoroughly investigated. CNT FETs irradiated by a Xe ion fluence of 1012ions/cm2can maintain a high on/off current ratio, while transistors’ performance failure is observed as the ion fluence increased to 5 × 1012ions/cm2. Controllable experiments combined with numerical simulations revealed that the degradation mechanism changed as the nonionizing radiation energy built up. The trap generation in the gate dielectric, instead of the CNT channel, was identified as the dominating factor for the high-energy-radiation-induced device failure. Therefore, CNT FETs exhibited a >10× higher DD tolerance than that of Si devices, which was limited by the channel damage under irradiation. More importantly, the distinct failure mechanism determined that CNT FETs can maintain a high DD tolerance of 2.8 × 1013MeV/g as the technology node scales down to 45 nm node, suggesting the potential of CNT-based VLSI for high-performance and high-robustness space applications.

Aligned carbon nanotube (ACNT) array was regarded as an excellent channel material to build radio-frequency (RF) field-effect transistors (FETs) with an ultra-high frequency of up to THz regime due to the electrical performance advantages of high carrier mobility and saturation velocity, as well as low intrinsic capacitance. However, ACNT FET with extrinsic current-gain ( ${f}_{\text {T}}$ ) and maximum oscillation ( ${f}_{\text {MAX}}$ ) cut-off frequencies of simultaneously over 300 GHz has not yet been reported. In this letter, we report ACNT based RF FETs with record high dc performance of on-state current about 2.2mA/ $\boldsymbol {\mu } \text{m}$ and peak transconductance about 1.9mS/ $\boldsymbol {\mu } \text{m}$ at a bias of −1V. Especially, the ACNT based FETs show ${f}_{\text {T}}$ and ${f}_{\text {MAX}}$ of up to 376 and 318 GHz by scaling down gate length to 35 nm, indicating the actual RF performance into the THz regime. Radio-frequency amplifiers that exhibit power gain of over 24dB operating in K band is also demonstrated.

To investigate the phytotoxic effects of CeO2nanoparticles (NPs) on crops, soybean plants were cultivated in soil amended with CeO2NPs at 0, 25, 75 and 225 mg kg−1to maturity (96 days after sowing, DAS). A similar treatment with 25 mg kg−1CeCl3was used as an ionic control for comparison. Plant growth, accumulation and distribution of macro and micronutrients, chemical species of Ce, activities of antioxidant enzymes and levels of malondialdehyde (MDA) in the plants were examined at 21 and 96 DAS. CeO2NPs can exert negative effects on the growth and development of soybean plants, but only at the highest concentration tested (225 mg kg−1) and at the latest timepoint, CeO2NPs significantly reduced the biomass by 33.8% compared to the untreated control plants. Biochemical assays show that at 96 DAS, the activities of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) presented a decreasing trend with increased exposure concentrations in both shoots and roots, whereas the accumulation of MDA increased. CeO2NP treatments modified the accumulation of Ca, Fe, Zn, Mn, Cu, and Mo in roots; Ca, Fe and Zn in stems; and P, Mn and Mo in leaves. Ce3+ions and CeO2NPs were found to have very similar but not identical agronomical, physiological and biochemical effects on soybean plants. Synchrotron radiation-based X-ray absorption near edge structure (XANES) analysis shows that in 225 mg kg−1CeO2NP-treated plants, the percentages of Ce(iii) in the roots increased from 4.5% (21 DAS) to 11.8% (96 DAS). The results of this study suggest that CeO2NPs and Ce3+ions may share a common mechanism of toxicity and Ce(iii) species play an important role in the toxic effects of CeO2NPs on soybean plants under experimental conditions.

Open-source cyber threat intelligence (OSCTI) is becoming more influential in obtaining current network security information. Most studies on cyber threat intelligence (CTI) focus on automating the extraction of threat entities from public sources that describe attack events. The cybersecurity knowledge graph aims to change the expression of threat knowledge so that security researchers can accurately and efficiently obtain various types of threat information for preliminary intelligent decisions. The attribution technology can not only assist security analysts in detecting advanced persistent threats, but can also identify the same threat from different attack events. Therefore, it is important to trace the attack threat actor. In this study, we used the knowledge graph technology, considered the latest research on cyber threat attack attribution, and thoroughly examined key related technologies and theories in the process of constructing and applying the advanced persistent threat (APT) knowledge graph from OSCTI. We designed a cybersecurity platform named CSKG4APT based on a knowledge graph. Inspired by the theory of ontology, we constructed CSKG4APT as an APT knowledge graph model based on real APT attack scenarios. We then designed an APT threat knowledge extraction algorithm for completing and updating the knowledge graph using deep learning and expert knowledge. Finally, we proposed a practical APT attack attribution method with attribution and countermeasures. CSKG4APT is not a passive defense method in traditional network confrontation but one that integrates a large amount of fragmented intelligence and can actively adjust its defense strategy. It lays the foundation for further dominance in network attack and defense.

The dark matter particle explorer (DAMPE) has been in operation stably for nearly seven years. The key sub-detector of DAMPE is the bismuth germanium oxide (BGO) electromagnetic (EM) calorimeter, which consists of 308 BGO crystal bars. As a long-term apparatus in space, the BGO calorimeter faces continuous radiation bombardment, and therefore, the radiation resistance of the BGO is crucial for the performance of energy measurement. To understand the aging of BGO crystals caused by radiation in space, the stability including attenuation length and absolute energy scale has been examined with on-orbit data over 6.5 years. The aging effects are found in the BGO crystals of the inner and outer parts of the BGO calorimeter. Due to real-time calibration, the BGO calorimeter is still in a stable operation status.

The dissemination of digital disinformation in online social networks (OSNs) has been the subject of extensive research, although many challenges remain, including the analysis and control of disinformation dissemination across different platforms (i.e., cross-platform). In this article, we investigate and analyze the spreading patterns and regularities of disinformation both within a single platform and across platforms. To explore the complex relationship between user propagation desire and behaviour within the same group, a user propagation desire inference model based on propagation characteristics (behaviour characteristics and time characteristics) and a bidirectional backpropagation (B-BP) deep neural network are constructed. Then, to avoid overfitting due to the interaction of users’ propagation behaviour and the correlation among propagation characteristics, a novel adaptive weighted particle swarm optimization evolutionary algorithm is utilized to further optimize the B-BP deep neural network. We design and conduct a series of evaluation experiments on the current global hot topics including but not limited to novel coronavirus-19 pandemic (COVID-19), food safety, medical and health, and environmental protection. By using a real-world social platform and its social situation metadata analysis, the experimental results show that the proposed method not only accurately predicts the level of user propagation desire under multiple behaviour interactions but also facilitates social platform managers in handling disinformation disseminators. Our findings reveal that the intensity of social users’ desires to spread disinformation is related to the topics and groups that users are interested in, while the propagation motivation of social users is not strong under topics that users are not interested in. Our studies also demonstrate that social users with propagation desires tend to utilize their familiar social platforms and local circles for communication, and the behaviour and desire to spread disinformation to the cross-platform are not strong. We posit that these findings can help inform online and, fine-grained governance and mitigation strategies other than “one size fits all” approaches (e.g., “account prohibition and deletion”), and hopefully minimize disinformation dissemination.

Industrial internet security incidents occur frequently, and it is very important to accurately and effectively detect industrial internet attacks. In this paper, a novel CNN-LSTM fusion model-based method is proposed to detect malicious behavior under industrial internet security. Firstly, the data distribution is analyzed with the help of kernel density estimation, and the Pearson correlation coefficient is used to select the strong correlation feature as the model input. The one-dimensional convolutional neural network and the long short-term memory network respectively extract the spatial sequence features of the data and then use the softmax function to complete the classification task. In order to verify the effectiveness of the model, it is evaluated on the NSL-KDD dataset and the GAS dataset, and experiments show that the model has a significant performance improvement over a single model. In the detection of industrial network traffic data, the accuracy rate of 97.09% and the recall rate of 90.84% are achieved.

Severe acute respiratory syndrome-coronavirus-1/2 (SARS-CoV-1/2) macrodomain 3 (Mac3) is critical for replication and transcription of the viral genome and is therefore a potential therapeutic target. Here, we solved the crystal structure of SARS-CoV-2 Mac3, which reveals a small-molecule binding pocket. Two low-molecular-weight drugs, oxaprozin and meclomen, induced different patterns of nuclear magnetic resonance (NMR) chemical shift perturbations (CSPs). Meclomen binds to site I of SARS-CoV-2 Mac3 with binding pose determined by NMR CSP and transferred paramagnetic relaxation enhancement, while oxaprozin binds to site II as revealed by the crystal structure. Interestingly, oxaprozin and meclomen both perturb residues in site I of SARS-CoV Mac3. Fluorescence polarization experiments further demonstrated that oxaprozin and meclomen inhibited the binding of DNA-G4s to SARS-CoV-2 Mac3. Our work identified two adjacent ligand-binding sites of SARS-CoV-2 Mac3 that shall facilitate structure-guided fragment linking of these compounds for more potent inhibitors.

ZIF-8, as an important photoresponsive metal–organic framework (MOF), holds great promise in the field of cancer theranostics owing to its versatile physiochemical properties. However, its photocatalytic anticancer application is still restricted because of the wide bandgap and specific response to ultraviolet light. Herein, we developed lanthanide-doped nanoparticles (LDNPs) coated with Fe/Mn bimetal-doped ZIF-8 (LDNPs@Fe/Mn-ZIF-8) for second near-infrared (NIR-II) imaging-guided synergistic photodynamic/chemodynamic therapy (PDT/CDT). The LDNPs were synthesized by encapsulating an optimal Yb3+/Ce3+-doped active shell on the NaErF4:Tm core to achieve dual-mode red upconversion (UC) and NIR-II downconversion (DC) emission upon NIR laser irradiation. At the optimal doping concentration, the UC and DC NIR-II emission intensities of LDNPs were increased 30.2- and 13.2-fold above those of core nanoparticles, which endowed LDNPs@Fe/Mn-ZIF-8 with an outstanding capability to carry out UC-mediated PDT and NIR-II optical imaging. In addition, the dual doping of Fe2+/Mn2+markedly decreased the bandgap of the ZIF-8 photosensitizer from 5.1 to 1.7 eV, expanding the excitation threshold of ZIF-8 to the visible light region (∼650 nm), which enabled Fe/Mn-ZIF-8 to be efficiently excited by UC photons to achieve photocatalytic-driven PDT. Furthermore, Fe2+/Mn2+ions could be responsively released in the tumor microenvironment through degradation of Fe/Mn-ZIF-8, thereby producing hydroxyl radicals (·OH) by Fenton/Fenton-like reactions to realize CDT. Meanwhile, the degradation of Fe/Mn-ZIF-8 endowed the nanosystems with tumor self-enhanced NIR-II imaging function, providing precise guidance for CDT/PDT.

ABSTRACTLong non-coding RNAs (lncRNAs) are relevant to the development of human cancers. Here, we aimed to investigate the role and mechanism of Linc00883 in the proliferation, invasion, and migration of colorectal cancer (CRC) cells. CRC cell lines SW480 and LoVo were applied as in vitromodels in this study. Quantitative real-time PCR was applied to measure Linc00883, miR-577, and FKBP14 expressions. Cell Counting Kit-8, transwell, and wound-healing assays were carried out to confirm the function of Linc00883. Western blot was applied to detect the protein levels of the epithelial–mesenchymal transition-related proteins E-cadherin, vimentin, fibronectin, and α-SMA. RNA immunoprecipitation (RIP) and RNA pull-down experiments were performed to confirm the relationship between Linc00883 and miR-577. Linc00883 expression was elevated in CRC tissues and cells, and the patients with high expression of Linc00883 were related to a low survival rate and prone to distant metastasis. Moreover, we corroborated that Linc00883 and miR-577, miR-577 and FKBP14 are bound to each other. Linc00883 was negatively correlated with miR-577, and miR-577 was also negatively correlated with FKBP14. Furthermore, interference with Linc00883 restrained the proliferation, invasion, and migration of CRC cells through the miR-577/FKBP14 axis. In vivostudies also clarified that Linc00883 facilitated the growth of CRC tumors and the epithelial–mesenchymal transition (EMT) of CRC. Our results demonstrated that Linc00883 facilitated the proliferation, invasion, and migration of CRC cells by regulating the miR-577/FKBP14 axis.

AbstractObjective:This study aimed to assess the effects of Apolipoprotein E (APOE) gene polymorphisms, dietary nutrient intake, and their interactions on the prevalence of dyslipidemia in a Yao minority area, China.Methods:rs429358, rs7412, rs7259620, and rs405509 of the APOEgene were genotyped in 1014 adults aged ≥30 years by using the MassArray system. Dietary nutrients intake data were ascertained from a 109-item food frequency questionnaire (FFQ).Results:Multifactorial logistics regression analysis showed that dyslipidemia was associated with rs7412-CT/TT genotype (OR: 0.540, Bonferroni correction confidence interval: 0.336–0.869), high fat intake (OR: 1.644, 95% CI: 1.128–2.395), high saturated fatty acid (SFA) intake (OR: 1.668, 95% CI: 1.146–2.428), medium carbohydrate intake (OR: 0.634, 95% CI: 0.461–0.873) and high carbohydrate intake (OR: 0.591, 95% CI: 0.406–0.858). The results of logistics regression multiplication model showed that medium carbohydrate intake in the carriers of the rs7412 minor alleles was associated with a low risk of dyslipidemia (OR: 0.433, Bonferroni correction confidence interval: 0.199–0.941).Conclusions:Genetic variations at the rs7412, dietary fat, SFA, and carbohydrate intake and the interaction between APOEgene polymorphisms and carbohydrate intake are associated with dyslipidemia in Yao nationality people.

The purpose of this study is to enhance the economic applicability, reliability, and flexibility of energy supply by developing a novel Hybrid Energy System (HES). We establish a hybrid power generation model that integrates wind power generation (PW), photovoltaic power generation (PV), concentrated solar power (CSP), thermal power generation (TP), and wind and solar power curtailment (WSC) energy storage to enable flexible energy utilization and improve overall energy efficiency. To address the challenges of integrated regulation across multiple energy sources, we introduced an event-triggered multi-agent consensus algorithm with a PID controller (PEMCA) and applied it to the HES. PEMCA is employed to regulate the power output of each energy source to maximize the economic benefits of HES operation. The event-triggered mechanism within PEMCA significantly reduces the communication frequency, while the PID controller effectively mitigates the communication interference fluctuations, eliminates errors, and ensure smooth operation of the system. Verification results indicate that, compared to the traditional multi-agent incremental consensus algorithm (MCA), PEMCA substantially decreases the number of communications within the hybrid energy system, resulting in a 93.6 % reduction in communication space utilization. To evaluate the impact of communication interference within the HES, we simulated three different levels of interference. The results demonstrate that PEMCA outperforms the MCA algorithm in terms of stability and anti-interference capability, effectively suppressing error fluctuations and exhibiting greater robustness and reliability. When the HES system is combined with the PEMCA strategy, the total system cost is reduced by 1.4 % and 4.2 %, respectively, compared to using the Gurobi mathematical solver and the consideration of secondary energy. These findings validate the effectiveness of the algorithm.

Mallotus philippensis, a novel and mostly unexplored feedstock with a significantly greater oil content of 50%, serves as the foundation of a prospective and sustainable supply for biodiesel synthesis. The most notable aspect of this research is the development and application of a bio-based green nanocatalyst with ingenuity and environmental safety viaa method employing an autoclave reactor from raw conventional materials such as rotten fungus fruits infused with a nano-WO3catalyst. The obtained catalyst was then subjected to several analyses, including scanning electron microscopy, energy-dispersive X-ray analysis, X-ray diffraction, and Fourier transform infrared spectroscopy. This research focused on the potential of this unique feedstock within the limits of an industrial setting. The synthesized nanocatalyst showed promising long-term performance and great catalytic efficiency. The biodiesel production reached its peak under optimal conditions, which included a methanol-to-oil ratio of 11:1, a reaction period of 120 min at 110°C, and a catalyst concentration of 0.15% by weight. Under precisely optimized conditions, this investigation rigorously examined the effectiveness, environmental stability, reusability, and economic feasibility of this green catalyst. The findings of this study demonstrate the stability and consistency of nanocatalyst performance, particularly throughout reusability cycles.

Cenozoic uplift in the Tianshan played an important role in driving Proto‐Paratethys Sea retreat and Asian aridification. However, most paleoclimate studies have focused on the Pamir‐Tianshan corridor, and frequently overlook the role of the entire Tianshan range in modifying the Central Asian climate during Cenozoic uplift. When and how Cenozoic deformation of Tianshan was initiated and propagated are intensively debated which makes its role in contributing to climate change in Central Asia more ambiguous. To address this issue, this study presents new detrital zircon U‐Pb and detrital apatite U‐Pb and fission track age data from Cenozoic sedimentary successions (54–0 Ma) in the northern margin of the Tarim Basin and integrates these data with published provenance data from adjacent regions. Our results show that deformation/uplift of the Baicheng‐Kuqa Depression and the South Tianshan occurred at ∼41–37 Ma and ∼24 Ma, when topographic growth of South Tianshan began to block the flow of sediment from the north. Continued uplift of the South Tianshan completely blocked fluvial transport from the Central Tianshan‐Yili Block by ∼10 Ma, as shown by the paucity of 380–310 Ma detrital zircons/apatites. Far‐field, north‐directed compressive stress resulting from the India‐Asia collision began to propagate toward the South Tianshan and its foreland during the Late Eocene, and continued to propagate into the South Tianshan and northward at the ∼24 Ma and 10 Ma. Finally, we suggest a two‐stage of aridification in the Tarim Basin which can be linked to two stages (∼24 and 10 Ma) of growth of the Tianshan. The Tarim Basin and the Taklimakan Desert are located in Central Asia, between the Tibetan Plateau to the south and the Tianshan orogenic belt to the north. This region is a crucial area for exploring the primary drivers of Cenozoic desertification. We performed a systematic zircon and apatite provenance study (including detrital apatite and zircon U‐Pb dating, and detrital apatite fission track analysis) in Cenozoic strata from the northern margin of the Tarim Basin. Our results reveal pulsed deformation of the South Tianshan that initiated at ∼41–37 Ma with two subsequent pulses at ∼24 Ma and ∼10 Ma, the timing of which suggests a close link to the two‐step aridification (∼24 and 10 Ma) of the Tarim Basin. We suggest that the pulsed Cenozoic rise and growth of the South Tianshan played a crucial role in blocking westerly winds, restricting moisture from reaching the Tarim Basin, and driving Cenozoic aridification of the Tarim Basin. Initiation of the Cenozoic uplift of the South Tianshan occurred in the Late EoceneFurther uplift of the South Tianshan completely blocked fluvial transport from the north by ∼10 MaPulsed growth of Tianshan play a dominant role in the two‐step aridification of the Tarim Basin Initiation of the Cenozoic uplift of the South Tianshan occurred in the Late Eocene Further uplift of the South Tianshan completely blocked fluvial transport from the north by ∼10 Ma Pulsed growth of Tianshan play a dominant role in the two‐step aridification of the Tarim Basin

Natural silks are renewable proteins with impressive mechanical properties and biocompatibility that are useful in various fields. However, the cellular and spatial organization of silk-secreting organs remains unclear. Here, we combined single-nucleus and spatially resolved transcriptomics to systematically map the cellular and spatial composition of the silk glands (SGs) of mulberry silkworms late in larval development. This approach allowed us to profile SG cell types and cell state dynamics and identify regulatory networks and cell-cell communication related to efficient silk protein synthesis; key markers were validated via transgenic approaches. Notably, we demonstrated the indispensable role of the ecdysone receptor (ultraspiracle) in regulating endoreplication in SG cells. Our atlas presents the results of spatiotemporal analysis of silk-secreting organ architecture late in larval development; this atlas provides a valuable reference for elucidating the mechanism of efficient silk protein synthesis and developing sustainable products made from natural silk.

Biomimetic nanozyme with natural enzyme-like activities has drawn extensive attention in cancer therapy, while its application was hindered by the limited catalytic efficacy in the complicated tumor microenvironment (TME). Herein, a hybrid biomimetic nanozyme combines polydopamine-decorated CuO with a natural enzyme of glucose oxidase (GOD), among which CuO is endowed with a high loading rate (47.1%) of GOD due to the elaborately designed hollow mesoporous structure that is constructed to maximize the cascade catalytic efficacy. In the TME, CuO could catalyze endogenous H2O2into O2for relieving tumor hypoxia and improving the catalytic efficacy of GOD. Whereafter, the amplified glucose oxidation induces starvation therapy, and the generated H2O2and H+enhance the catalytic activity of CuO. Significantly, the tumor-specific chemodynamic therapy (CDT) could be realized when CuO degraded into Cu2+in acidic and reductive TME. Furthermore, the photothermal therapy with high photothermal conversion efficiency (30.2%) is achieved under NIR-II laser (1064 nm) excitation, which could reinforce the generation of reactive oxygen species (•OH and •O2–). The TME initiates the biochemical reaction cycle of CuO, O2, and GOD, which couples with an NIR-II-induced thermal effect to realize O2-promoted starvation and photothermal–chemodynamic combined therapy. This hybrid biomimetic nanozyme enlightens the further development of nanozymes in multimodal cancer therapy.