Discovery of a Meisoindigo-Derived PROTAC as the ATM Degrader: Revolutionizing Colorectal Cancer Therapy via Synthetic Lethality with ATR Inhibitors.

Meisoindigo (Mei) has long been recognized in chronic myeloid leukemia (CML) treatment. To elucidate its molecular target and mechanisms, we embarked on designing and synthesizing a series of Mei-derived PROTACs. Through this endeavor, VHL-type PROTAC 9b was identified to be highly cytotoxic against SW620, SW480, and K562 cells. Employing DiaPASEF-based quantitative proteomic analysis, in combination with extensive validation assays, we unveiled that 9b potently and selectively degraded ATM across SW620 and SW480 cells in a ubiquitin-proteasome-dependent manner. 9b-induced selective ATM degradation prompted DNA damage response cascades, thereby leading to the cell cycle arrest and cell apoptosis. This pioneering discovery renders the advent of ATM degradation for anti-cancer therapy. Notably, 9b-induced ATM degradation synergistically enhanced the efficacy of ATR inhibitor AZD6738 both in vitro and in vivo. This work establishes the synthetic lethality-inducing properties of ATR inhibitors in the ATM-deficient context, thereby providing new avenues to innovative therapies for colorectal cancer.

Non-destructive detection of defective maize kernels using hyperspectral imaging and convolutional neural network with attention module.

Rapid, effective and non-destructive detection of the defective maize kernels is crucial for their high-quality storage in granary. Hyperspectral imaging (HSI) coupled with convolutional neural network (CNN) based on spectral and spatial attention (Spl-Spal-At) module was proposed for identifying the different types of maize kernels. The HSI data within 380-1000 nm of six classes of sprouted, heat-damaged, insect-damaged, moldy, broken and healthy kernels was collected. The CNN-Spl-At, CNN-Spal-At and CNN-Spl-Spal-At models were established based on the spectra, images and their fusion features as inputs for the recognition of different kernels. Further compared the performances of proposed models and conventional models were built by support vector machine (SVM) and extreme learning machine (ELM). The results indicated that the recognition ability of CNN with attention series models was significantly better than that of SVM and ELM models and fused features were more conducive to expressing the appearance of different kernels than single features. And the CNN-Spl-Spal-At model had an optimal recognition result with high average classification accuracy of 98.04 % and 94.56 % for the training and testing sets, respectively. The recognition results were visually presented on the surface image of kernels with different colors. The CNN-Spl-Spal-At model was built in this study could effectively detect defective maize kernels, and it also had great potential to provide the analysis approaches for the development of non-destructive testing equipment based on HSI technique for maize quality.

Cluster-Aware Grid Layout.

Grid visualizations are widely used in many applications to visually explain a set of data and their proximity relationships. However, existing layout methods face difficulties when dealing with the inherent cluster structures within the data. To address this issue, we propose a cluster-aware grid layout method that aims to better preserve cluster structures by simultaneously considering proximity, compactness, and convexity in the optimization process. Our method utilizes a hybrid optimization strategy that consists of two phases. The global phase aims to balance proximity and compactness within each cluster, while the local phase ensures the convexity of cluster shapes. We evaluate the proposed grid layout method through a series of quantitative experiments and two use cases, demonstrating its effectiveness in preserving cluster structures and facilitating analysis tasks.

Tailoring the optical and mechanical properties of cellulose nanocrystal film by sugar alcohols and its pH/humidity-responsive behavior.

Cellulose nanocrystals (CNC) have gained widespread attention in intelligent food packaging because of their iridescent optical properties. Here, we report a CNC composite film employing CNC, sugar alcohols (e.g., maltol, erythritol, mannitol, sorbitol, and xylitol) and natural pigment anthocyanins, which has a special iridescent color that can be used as a pH and humidity sensor. The effects of five sugar alcohols with different addition ratios on the structural, optical, and mechanical properties of the CNC films were investigated. The results demonstrated that the addition of sugar alcohol made composite films exhibiting a red-shift of λmax, a more uniform color in visual observation, and a larger pitch. Among them, the CNC-mannitol composite film with a ratio of 10:1 exhibited the best mechanical properties, possessing a tensile stress strength of 57 MPa and toughness of 137 J/m3. Subsequently, anthocyanins were incorporated to this composite film, which showed a marked color change along with the pH from 2 to 12 and exhibited a reversible color change from red to transparent upon a relative humidity change from 35 % to 85 %. Overall, such multi-environment-responsive iridescent films with excellent mechanical properties have a great potential for use in intelligent food packaging applications.

Surface effects on the crystallization kinetics of amorphous antimony.

Elemental antimony (Sb) is regarded as a promising candidate to improve the programming consistency and cycling endurance of phase-change memory and neuro-inspired computing devices. Although bulk amorphous Sb crystallizes spontaneously, the stability of the amorphous form can be greatly increased by reducing the thickness of thin films down to several nanometers, either with or without capping layers. Computational and experimental studies have explained the depressed crystallization kinetics caused by capping and interfacial confinement; however, it is unclear why amorphous Sb thin films remain stable even in the absence of capping layers. In this work, we carry out thorough ab initio molecular dynamics (AIMD) simulations to investigate the effects of free surfaces on the crystallization kinetics of amorphous Sb. We reveal a stark contrast in the crystallization behavior between bulk and surface models at 450 K, which stems from deviations from the bulk structural features in the regions approaching the surfaces. The presence of free surfaces intrinsically tends to create a sub-nanometer region where crystallization is suppressed, which impedes the incubation process and thus constrains the nucleation in two dimensions, stabilizing the amorphous phase in thin-film Sb-based memory devices.

Structure and Bonding in Amorphous Red Phosphorus.

Amorphous red phosphorus (a-P) is one of the remaining puzzling cases in the structural chemistry of the elements. Here, we elucidate the structure, stability, and chemical bonding in a-P from first principles, combining machine-learning and density-functional theory (DFT) methods. We show that a-P structures exist with a range of energies slightly higher than those of phosphorus nanorods, to which they are closely related, and that the stability of a-P is linked to the degree of structural relaxation and medium-range order. We thus complete the stability range of phosphorus allotropes [Angew. Chem. Int. Ed. 2014, 53, 11629] by now including the previously poorly understood amorphous phase, and we quantify the covalent and van der Waals interactions in all main phases of phosphorus. We also study the electronic densities of states, including those of hydrogenated a-P. Beyond the present study, our structural models are expected to enable wider-ranging first-principles investigations-for example, of a-P-based battery materials.

Detection and Genomic Characterization of Bovine Rhinitis Virus in China.

Bovine rhinitis virus (BRV) is an etiological agent of bovine respiratory disease complex (BRDC) and can be divided into two genotypes-bovine rhinitis A virus (BRAV) and bovine rhinitis B virus (BRBV). However, knowledge about the prevalence and molecular information of BRV in China is still limited. In this study, 163 deep nasal swabs collected from bovines with BRDC syndrome on 16 farms across nine provinces of China were tested for BRAV and BRBV by a duplex real-time RT-PCR assay. The results showed that 28.22% (46/163) of the samples were BRV-positive, and the positive rates were 22.09% (36/163) for BRAV and 9.2% (15/163) for BRBV. The co-circulation of both BRV genotypes was observed on two farms. Furthermore, five near-complete BRV genomes, including three BRAVs and two BRBVs, were obtained. The phylogenetic analysis showed that the three obtained BRAVs were phylogenetically independent, while the two BRBVs exhibited significant genetic heterogeneity. Recombination analysis revealed that three BRAVs and one BRBV strain obtained in this study were recombinants. The present study confirmed the presence and prevalence of BRAV in China, and it found that both types of BRV are circulating in beef cattle, which contributes to a better understanding of the prevalence and molecular characteristics of BRV.

Synthesis and characterization of cellulose nanocrystal-Fe composite nanoparticles and their digestion behavior in simulated gastric fluid.

Cellulose nanocrystals (CNC) exhibit great potential as a food emulsifier or functional material template. Herein, CNC-Fe nanoparticles were successfully prepared via an in situ chemical reduction approach. Zeta potential measurements, low-field nuclear magnetic resonance spectroscopy, and atomic force microscopy showed that Fe(III) ions were adsorbed onto CNC when FeCl3 was added to a CNC dispersion. Micromorphological analysis revealed small (diameter = 10.0 ± 2.4 nm) spherical nanoparticles synthesized on the surface of aggregated CNC after the reduction of the Fe(III) ions. Fourier transform infrared spectroscopy revealed an intense peak at 779 cm-1 in the CNC-Fe nanoparticles, which was attributed to FeO stretching vibrations. X-ray photoelectron spectroscopy indicated that the valence state of Fe in CNC-Fe nanoparticles was predominantly ferrous. The synthesized CNC-Fe nanoparticles demonstrated excellent colloidal stability in a dispersion for 21 d and complete, rapid, and spontaneous dissolution in vitro simulated gastric fluid. Our results highlight the potential use of CNC as a template for loading Fe into nanoparticles for Fe fortification in food.

Negative Dielectric Constant of Water at a Metal Interface.

Water polarizability at a metal interface plays an essential role in electrochemistry. We devise a classical molecular dynamics approach with an efficient description of metal polarization and a novel ac field method to measure the local dielectric response of interfacial water. Water adlayers next to the metal surface exhibit higher-than-bulk in-plane and negative out-of-plane dielectric constants, the latter corresponding physically to overscreening of the applied field. If we account for the gap region at the interface, the average out-of-plane dielectric constant is quite low (ε_{⊥}≈2), in agreement with reported measurements on confined thin films.

Z-scheme CuO/Fe3O4/GO heterojunction photocatalyst: Enhanced photocatalytic performance for elimination of tetracycline.

CuO/Fe3O4/GO, as a Z-scheme heterojunction catalyst, was successfully synthesized and used as a photocatalyst for removing tetracycline from aqueous solution. The CuO/Fe3O4/GO heterogeneous catalyst combines the narrow bandgap semiconductor CuO, oxygen vacancies of Fe3O4, and oxygen-containing reaction sites of GO. Without the addition of activators (persulfate or H2O2), the photocatalytic performance on decomposing tetracycline is very excellent. Compared with GO, Fe3O4, and CuO, CuO/Fe3O4/GO exhibits superior photocatalytic performance. Under visible light radiation, CuO/Fe3O4/GO generates h+ and ⋅O2-, which are the mainly responsible active groups for TC degradation. The effects of various pH, catalysts, and reuse on the degradation performance are evaluated, and the optimal conditions for CuO/Fe3O4/GO removal of tetracycline are obtained at pH 7, catalyst dosage 20 mg⋅L-1, TC at a concentration of 30 mg/L, nearly 97.3% of tetracycline is decomposed. This study has great potential in the treatment of wastewater containing various antibiotics.

Circulation of heterogeneous Carnivore protoparvovirus 1 in diarrheal cats and prevalence of an A91S feline panleukopenia virus variant in China.

Cats are susceptible to panleukopenia virus (FPV) and canine parvovirus type 2 (CPV-2) infection. FPV has been recognized as relatively conservative in genetic evolution compared to CPV-2, but information regarding FPV variations in cats is still limited. The aim of this study was to investigate the molecular prevalence of FPV and CPV-2 variants among cats in China. From April 2019 to December 2021, 193 diarrheal faecal samples of cats were collected from Southwest China and 127 (65.80%) samples tested positive to Carnivore protoparvovirus 1. FPV, CPV-2 and some their genomic variants were identified from positive samples, indicating a heterogeneous Carnivore protoparvovirus 1 circulation in the cat population in China. Among FPV strains, an A91S FPV mutant reached the detection rate of 39.37%, which showed that this FPV genomic variant has been prevalent in the tested cats. Moreover, 7 strains of A91S FPV variants were isolated and purified successfully using F81 cells, and the genomes were sequenced. Phylogenetic trees based on the nearly complete genomic sequences, VP2 and NS1 nucleotide sequences showed that the A91S FPV variants were located in the FPV clade, but all clustered into a separate branch. Structural prediction showed that A91S mutation in VP2 protein extended the random coil of aa residues from 92-95 to 91-95. Moreover, the analysis of all complete VP2 sequences of FPV and CPV-2 available in the GenBank database revealed that the A91S FPV variant has been prevalent in China since 2017 and has reported in four other countries in cats. Thus, our study revealed that heterogeneous Carnivore protoparvovirus 1 are circulating in the cat population in China, and first reported the prevalence and genomic characteristics of the A91S FPV variant, which contributed to a better understanding of the molecular prevalence and genetic evolution of FPV in cats.

Prevalence and characteristics of a feline parvovirus-like virus in dogs in China.

In this study, 192 diarrheal fecal samples were collected from 2019 to 2021 for monitoring the molecular prevalence of canine parvovirus 2 (CPV-2) among dogs in Southwest China, and 113 samples were detected as Carnivore protoparvovirus 1-positive. Surprisingly, 28/113 (24.8%) strains were identified as feline parvovirus (FPV)-like viruses based on the key amino acid (aa) residues in VP2. Further, 6 FPV-like strains were successfully isolated and genome sequenced, and phylogenetic trees based on the genome, VP2 and NS1 sequences showed that the 6 FPV-like strains were most genetically related with FPV instead of CPV-2. Interestingly, the VP2 proteins of the FPV-like virus contained all key aa residues typical for FPV and can be 100% identical to that of FPV, but the VP1 intron and NS1 aa sequences exhibited some unique molecular characteristics. The FPV-like isolate could hemagglutinate swine erythrocyte at pH values between 6 and 8, and replicated efficiently in MDCK cell line; moreover, the virus could cause canine systemic infection via oral administration. Further analysis based on VP2 sequences of FPV and CPV-2 in GenBank revealed that the FPV-like virus had already existed among dogs in 4 Asian countries, and have circulated widely in China. This study first confirmed that the FPV-like isolates could efficiently infect dogs, and has been prevalent among dogs in China. Moreover, this study first reported the genome characteristics of the FPV-like virus in dogs, which may represent a novel evolution pattern involving in the cross-species transmission of the virus from cats to dogs.

Theory for the Elementary Time Scale of Stress Relaxation in Polymer Nanocomposites.

We construct a microscopic theory for the elementary time scale of stress relaxation in dense polymer nanocomposites. The key dynamical event is proposed to involve the rearrangement of cohesive segment-nanoparticle (NP) tight bridging complexes via an activated small NP dilational motion, which allows the confined segments to relax. The corresponding activation energy is determined by the NP bridge coordination number and potential of mean force barrier. The activation energy varies nonlinearly with interfacial cohesion strength and NP concentration, and a universal master curve is predicted. The theory is in very good agreement with experiments. The underlying ideas are relevant to a variety of other hybrid macromolecular materials involving hard particles and soft macromolecules.

Activated relaxation in supercooled monodisperse atomic and polymeric WCA fluids: Simulation and ECNLE theory.

We combine simulation and Elastically Collective Nonlinear Langevin Equation (ECNLE) theory to study the activated relaxation in monodisperse atomic and polymeric Weeks-Chandler-Andersen (WCA) liquids over a wide range of temperatures and densities in the supercooled regime under isochoric conditions. By employing novel crystal-avoiding simulations, metastable equilibrium dynamics is probed in the absence of complications associated with size polydispersity. Based on a highly accurate structural input from integral equation theory, ECNLE theory is found to describe well the simulated density and temperature dependences of the alpha relaxation time of atomic fluids using a single system-specific parameter, ac, that reflects the nonuniversal relative importance of local cage and collective elastic barriers. For polymer fluids, the explicit dynamical effect of local chain connectivity is modeled at the fundamental dynamic free energy trajectory level based on a different parameter, Nc, that quantifies the degree of intramolecular correlation of bonded segment activated barrier hopping. For the flexible chain model studied, a physically intuitive value of Nc ≈ 2 results in good agreement between simulation and theory. A direct comparison between atomic and polymeric systems reveals that chain connectivity can speed up activated segmental relaxation due to weakening of equilibrium packing correlations but can slow down relaxation due to local bonding constraints. The empirical thermodynamic scaling idea for the alpha time is found to work well at high densities or temperatures but fails when both density and temperature are low. The rich and subtle behaviors revealed from simulation for atomic and polymeric WCA fluids are all well captured by ECNLE theory.

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Trees are characterized with selective absorption of different forms of nitrogen. Ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3--N) are the main forms of nitrogen for plant absorption. We examined the differences of absorption between NH4+-N and NO3--N for 1-year-old Machilus pauhoi seedlings planted in local hilly red soil in a pot experiment. A controlled experiment with 7 different NH4+-N/NO3--N treatments was conducted, to study the effects of nitrogen forms and different NH4+-N/NO3--N ratios on the growth and leaf traits of M. pauhoi seedlings. The results showed that there were no significant differences in the relative growth rate of ground diameter (GD), plant height (TH), and biomass (RGR) of M. pauhoi seedlings with different NH4+-N/NO3--N ratios for four months, but these parameters were relatively high under the treatment of NH4+-N:NO3--N=5:5. The seedlings of M. pauhoi didn't show obvious preference for NH4+-N and NO3--N in short term. The extremely low NH4+-N/NO3--N ratio application was unsuitable for their growth. Different NH4+-N/NO3--N application had significant effects on leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf relative water content (LRWC), net photosynthetic rate (Pn), intercellular CO2 concentration (Ci), water use efficiency (WUE), and photosynthetic nitrogen use efficiency (PNUE). M. pauhoi seedlings under the treatment of NH4+-N:NO3--N=1:9 had the highest LA, SLA, Pn, WUE and PNUE. However, the seedlings under the treatment of NH4+-N:NO3--N=9:1 had the lowest LDMC, leaf tissue density (LTD), LRWC and Ci. Different NH4+-N/NO3--N combined application did not affect leaf nitrogen content (LN) and leaf phosphorus content (LP), which were highest under the treatment of NH4+-N:NO3--N=5:5. Across different NH4+-N/NO3--N combined treatments, GD, TH, and RGR were significantly negatively correlated with SLA, while both GD and RGR were significantly negatively correlated with PNUE. Our results could provide theoretical basis for precise nutrient management and high-efficiency cultivation techniques during the seedling stage of the M. pauhoi.

Unraveling Crystallization Mechanisms and Electronic Structure of Phase-Change Materials by Large-Scale Ab Initio Simulations.

Ge-Sb-Te ("GST") alloys are leading phase-change materials for digital memories and neuro-inspired computing. Upon fast crystallization, these materials form rocksalt-like phases with large structural and vacancy disorder, leading to an insulating phase at low temperature. Here, a comprehensive description of crystallization, structural disorder, and electronic properties of GeSb2 Te4 based on realistic, quantum-mechanically based ("ab initio") computer simulations with system sizes of more than 1000 atoms is provided. It is shown how an analysis of the crystallization mechanism based on the smooth overlap of atomic positions kernel reveals the evolution of both geometrical and chemical order. The connection between structural and electronic properties of the disordered, as-crystallized models, which are relevant to the transport properties of GST, is then studied. Furthermore, it is shown how antisite defects and extended Sb-rich motifs can lead to Anderson localization in the conduction band. Beyond memory applications, these findings are therefore more generally relevant to disordered rocksalt-like chalcogenides that exhibit self-doping, since they can explain the origin of Anderson insulating behavior in both p- and n-doped chalcogenide materials.

Cluster Fragments in Amorphous Phosphorus and their Evolution under Pressure.

Amorphous phosphorus (a-P) has long attracted interest because of its complex atomic structure, and more recently as an anode material for batteries. However, accurately describing and understanding a-P at the atomistic level remains a challenge. Here, it is shown that large-scale molecular-dynamics simulations, enabled by a machine-learning (ML)-based interatomic potential for phosphorus, can give new insights into the atomic structure of a-P and how this structure changes under pressure. The structural model so obtained contains abundant five-membered rings, as well as more complex seven- and eight-atom clusters. Changes in the simulated first sharp diffraction peak during compression and decompression indicate a hysteresis in the recovery of medium-range order. An analysis of cluster fragments, large rings, and voids suggests that moderate pressure (up to about 5 GPa) does not break the connectivity of clusters, but higher pressure does. The work provides a starting point for further computational studies of the structure and properties of a-P, and more generally it exemplifies how ML-driven modeling can accelerate the understanding of disordered functional materials.

Long Wavelength Thermal Density Fluctuations in Molecular and Polymer Glass-Forming Liquids: Experimental and Theoretical Analysis under Isobaric Conditions.

We establish via an in-depth analysis of experimental data that the dimensionless compressibility (proportional to the dimensionless amplitude of long wavelength thermal density fluctuations) of one-component normal and supercooled liquids of chemically complex nonpolar and weakly polar molecules and polymers follows extremely well a surprisingly simple and general temperature dependence over an exceptionally wide range of pressures and temperatures. A theoretical basis for this behavior is shown to exist in the venerable van der Waals model and its more modern interpretations. Although associated hydrogen-bonding (and to a lesser degree strongly polar) liquids display modestly more complex behavior, rather simple temperature and pressure dependences are also discovered. A new approach to collapse the temperature- and pressure-dependent dimensionless compressibility data onto a master curve is formulated that differs from the empirical thermodynamic scaling approach. As a practical matter, we also find that the dimensionless compressibility scales well as an inverse power law with temperature with an exponent that is system dependent and decreases with pressure. At very high pressures and low temperatures, the thermal liquid behavior appears to approach (but not reach) a repulsion-dominated random close packing limit. All these findings are relevant to our recent theoretical work on the problem of activated relaxation and vitrification of supercooled molecular and polymeric liquids.

Collective Nanoparticle Dynamics Associated with Bridging Network Formation in Model Polymer Nanocomposites.

The addition of nanoparticles (NPs) to polymers is a powerful method to improve the mechanical and other properties of macromolecular materials. Such hybrid polymer-particle systems are also rich in fundamental soft matter physics. Among several factors contributing to mechanical reinforcement, a polymer-mediated NP network is considered to be the most important in polymer nanocomposites (PNCs). Here, we present an integrated experimental-theoretical study of the collective NP dynamics in model PNCs using X-ray photon correlation spectroscopy and microscopic statistical mechanics theory. Silica NPs dispersed in unentangled or entangled poly(2-vinylpyridine) matrices over a range of NP loadings are used. Static collective structure factors of the NP subsystems at temperatures above the bulk glass transition temperature reveal the formation of a network-like microstructure via polymer-mediated bridges at high NP loadings above the percolation threshold. The NP collective relaxation times are up to 3 orders of magnitude longer than the self-diffusion limit of isolated NPs and display a rich dependence with observation wavevector and NP loading. A mode-coupling theory dynamical analysis that incorporates the static polymer-mediated bridging structure and collective motions of NPs is performed. It captures well both the observed scattering wavevector and NP loading dependences of the collective NP dynamics in the unentangled polymer matrix, with modest quantitative deviations emerging for the entangled PNC samples. Additionally, we identify an unusual and weak temperature dependence of collective NP dynamics, in qualitative contrast with the mechanical response. Hence, the present study has revealed key aspects of the collective motions of NPs connected by polymer bridges in contact with a viscous adsorbing polymer medium and identifies some outstanding remaining challenges for the theoretical understanding of these complex soft materials.

Ectopic targeting of CG DNA methylation in Arabidopsis with the bacterial SssI methyltransferase.

The ability to target epigenetic marks like DNA methylation to specific loci is important in both basic research and in crop plant engineering. However, heritability of targeted DNA methylation, how it impacts gene expression, and which epigenetic features are required for proper establishment are mostly unknown. Here, we show that targeting the CG-specific methyltransferase M.SssI with an artificial zinc finger protein can establish heritable CG methylation and silencing of a targeted locus in Arabidopsis. In addition, we observe highly heritable widespread ectopic CG methylation mainly over euchromatic regions. This hypermethylation shows little effect on transcription while it triggers a mild but significant reduction in the accumulation of H2A.Z and H3K27me3. Moreover, ectopic methylation occurs preferentially at less open chromatin that lacks positive histone marks. These results outline general principles of the heritability and interaction of CG methylation with other epigenomic features that should help guide future efforts to engineer epigenomes.