Functional Roles of H3K4 Methylation in Transcriptional Regulation.

Histone 3 lysine 4 methylation (H3K4me) is a highly evolutionary conserved chromatin modification associated with active transcription, and its three methylation states-mono, di, and trimethylation-mark distinct regulatory elements. However, whether H3K4me plays functional roles in transcriptional regulation or is merely a by-product of histone methyltransferases recruited to actively transcribed loci is still under debate. Here, we outline the studies that have addressed this question in yeast, Drosophila, and mammalian systems. We review evidence from histone residue mutation, histone modifier manipulation, and epigenetic editing, focusing on the relative roles of H3K4me1 and H3K4me3. We conclude that H3K4me1 and H3K4me3 may have convergent functions in establishing open chromatin and promoting transcriptional activation during cell differentiation.

PRMT6 facilitates EZH2 protein stability by inhibiting TRAF6-mediated ubiquitination degradation to promote glioblastoma cell invasion and migration.

Invasion and migration are the key hallmarks of cancer, and aggressive growth is a major factor contributing to treatment failure and poor prognosis in glioblastoma. Protein arginine methyltransferase 6 (PRMT6), as an epigenetic regulator, has been confirmed to promote the malignant proliferation of glioblastoma cells in previous studies. However, the effects of PRMT6 on glioblastoma cell invasion and migration and its underlying mechanisms remain elusive. Here, we report that PRMT6 functions as a driver element for tumor cell invasion and migration in glioblastoma. Bioinformatics analysis and glioma sample detection results demonstrated that PRMT6 is highly expressed in mesenchymal subtype or invasive gliomas, and is significantly negatively correlated with their prognosis. Inhibition of PRMT6 (using PRMT6 shRNA or inhibitor EPZ020411) reduces glioblastoma cell invasion and migration in vitro, whereas overexpression of PRMT6 produces opposite effects. Then, we identified that PRMT6 maintains the protein stability of EZH2 by inhibiting the degradation of EZH2 protein, thereby mediating the invasion and migration of glioblastoma cells. Further mechanistic investigations found that PRMT6 inhibits the transcription of TRAF6 by activating the histone methylation mark (H3R2me2a), and reducing the interaction between TRAF6 and EZH2 to enhance the protein stability of EZH2 in glioblastoma cells. Xenograft tumor assay and HE staining results showed that the expression of PRMT6 could promote the invasion of glioblastoma cells in vivo, the immunohistochemical staining results of mouse brain tissue tumor sections also confirmed the regulatory relationship between PRMT6, TRAF6, and EZH2. Our findings illustrate that PRMT6 suppresses TRAF6 transcription via H3R2me2a to enhance the protein stability of EZH2 to facilitate glioblastoma cell invasion and migration. Blocking the PRMT6-TRAF6-EZH2 axis is a promising strategy for inhibiting glioblastoma cell invasion and migration.

Hydrogen-induced tunable remanent polarization in a perovskite nickelate.

Materials with field-tunable polarization are of broad interest to condensed matter sciences and solid-state device technologies. Here, using hydrogen (H) donor doping, we modify the room temperature metallic phase of a perovskite nickelate NdNiO3 into an insulating phase with both metastable dipolar polarization and space-charge polarization. We then demonstrate transient negative differential capacitance in thin film capacitors. The space-charge polarization caused by long-range movement and trapping of protons dominates when the electric field exceeds the threshold value. First-principles calculations suggest the polarization originates from the polar structure created by H doping. We find that polarization decays within ~1 second which is an interesting temporal regime for neuromorphic computing hardware design, and we implement the transient characteristics in a neural network to demonstrate unsupervised learning. These discoveries open new avenues for designing ferroelectric materials and electrets using light-ion doping.

Uncovering fruit flavor and genetic diversity across diploid wild Fragaria species via comparative metabolomics profiling.

Wild Fragaria resources exhibit extensive genetic diversity and desirable edible traits, such as high soluble solid content and flavor compounds. However, specific metabolites in different wild strawberry fruits remain unknown. In this study, we characterized 1008 metabolites covering 11 subclasses among 13 wild diploid resources representing eight species, including F. vesca, F. nilgerrensis, F. viridis, F. nubicola, F. pentaphylla, F. mandschurica, F. chinensis, and F. emeiensis. Fifteen potential metabolite biomarkers were identified to distinguish fruit flavors among the 13 diploid wild Fragaria accessions. A total of nine distinct modules were employed to explore key metabolites related to fruit quality through weighted gene co-expression module analysis, with significant enrichment in amino acid biosynthesis pathway. Notably, the identified significantly different key metabolites highlighted the close association of amino acids, sugars, and anthocyanins with flavor formation. These findings offer valuable resources for improving fruit quality through metabolome-assisted breeding.

Toward Durable CO2 Electroreduction with Cu-Based Catalysts via Understanding Their Deactivation Modes.

The technology of CO2 electrochemical reduction (CO2ER) provides a means to convert CO2, a waste greenhouse gas, into value-added chemicals. Copper is the most studied element that is capable of catalyzing CO2ER to obtain multicarbon products, such as ethylene, ethanol, acetate, etc., at an appreciable rate. Under the operating condition of CO2ER, the catalytic performance of Cu decays because of several factors that alters the surface properties of Cu. In this review, these factors that cause the degradation of Cu-based CO2ER catalysts are categorized into generalized deactivation modes, that are applicable to all electrocatalytic systems. The fundamental principles of each deactivation mode and the associated effects of each on Cu-based catalysts are discussed in detail. Structure- and composition-activity relationship developed from recent in situ/operando characterization studies are presented as evidence of related deactivation modes in operation. With the aim to address these deactivation modes, catalyst design and reaction environment engineering rationales are suggested. Finally, perspectives and remarks built upon the recent advances in CO2ER are provided in attempts to improve the durability of CO2ER catalysts.

Biological mitigation of soil nitrous oxide emissions by plant metabolites.

Plant metabolites significantly affect soil nitrogen (N) cycling, but their influence on nitrous oxide (N2O) emissions has not been quantitatively analyzed on a global scale. We conduct a comprehensive meta-analysis of 173 observations from 42 articles to evaluate global patterns of and principal factors controlling N2O emissions in the presence of root exudates and extracts. Overall, plant metabolites promoted soil N2O emissions by about 10%. However, the effects of plant metabolites on N2O emissions from soils varied with experimental conditions and properties of both metabolites and soils. Primary metabolites, such as sugars, amino acids, and organic acids, strongly stimulated soil N2O emissions, by an average of 79%, while secondary metabolites, such as phenolics, terpenoids, and flavonoids, often characterized as both biological nitrification inhibitors (BNIs) and biological denitrification inhibitors (BDIs), reduced soil N2O emissions by an average of 41%. The emission mitigation effects of BNIs/BDIs were closely associated with soil texture and pH, increasing with increasing soil clay content and soil pH on acidic and neutral soils, and with decreasing soil pH on alkaline soils. We furthermore present soil incubation experiments that show that three secondary metabolite types act as BNIs to reduce N2O emissions by 32%-45%, while three primary metabolite classes possess a stimulatory effect of 56%-63%, confirming the results of the meta-analysis. Our results highlight the potential role and application range of specific secondary metabolites in biomitigation of global N2O emissions and provide new biological parameters for N2O emission models that should help improve the accuracy of model predictions.

Neuromorphic one-shot learning utilizing a phase-transition material.

Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient AI and learning machines. An important factor in selection of the hardware building blocks is the identification of candidate materials with physical properties suitable to emulate the large dynamic ranges and varied timescales of neuronal signaling. Previous work has shown that the all-or-none spiking behavior of neurons can be mimicked by threshold switches utilizing material phase transitions. Here, we demonstrate that devices based on a prototypical metal-insulator-transition material, vanadium dioxide (VO2), can be dynamically controlled to access a continuum of intermediate resistance states. Furthermore, the timescale of their intrinsic relaxation can be configured to match a range of biologically relevant timescales from milliseconds to seconds. We exploit these device properties to emulate three aspects of neuronal analog computation: fast (~1 ms) spiking in a neuronal soma compartment, slow (~100 ms) spiking in a dendritic compartment, and ultraslow (~1 s) biochemical signaling involved in temporal credit assignment for a recently discovered biological mechanism of one-shot learning. Simulations show that an artificial neural network using properties of VO2 devices to control an agent navigating a spatial environment can learn an efficient path to a reward in up to fourfold fewer trials than standard methods. The phase relaxations described in our study may be engineered in a variety of materials and can be controlled by thermal, electrical, or optical stimuli, suggesting further opportunities to emulate biological learning in neuromorphic hardware.

Label/immobilization-free Cas12a-based electrochemiluminescence biosensor for sensitive DNA detection.

Electrochemiluminescence (ECL) is one of the most sensitive techniques in the field of diagnostics. However, they typically require luminescent labeling and electrode surface biological modification, which is a time-consuming and laborious process involving multiple steps and may also lead to low reaction efficiency. Fabricating label/modification-free biosensors has become one of the most attractive parts for simplifying the ECL assays. In this work, the ECL luminophores carbon dots (CDs) were encapsulated in DNA hydrogel in situ by a simple rolling circle amplification (RCA) reaction. Upon binding of the target DNA, active Cas12a induces a collateral cleavage of the hydrogel's ssDNA backbone, resulting in a programmable degradation of the hydrogel and the release of CDs. By directly measuring the released CDs ECL, a simple and rapid label/modification-free detection of the target HPV-16 was realized. It is noted that this method allowed for 0.63 pM HPV-16 DNA detection without any amplification step, and it could take only ∼60 min for a fast test of a human serum sample. These results showed that our label/modification-free ECL biosensor has great potential for use in simple, rapid, and sensitive point-of-care (POC) detection.

Subnanometer Scale Mapping of Hydrogen Doping in Vanadium Dioxide.

Hydrogen donor doping of correlated electron systems such as vanadium dioxide (VO2) profoundly modifies the ground state properties. The electrical behavior of HxVO2 is strongly dependent on the hydrogen concentration; hence, atomic scale control of the doping process is necessary. It is however a nontrivial problem to quantitatively probe the hydrogen distribution in a solid matrix. As hydrogen transfers its sole electron to the material, the ionization mechanism is suppressed. In this study, a methodology mapping the doping distribution at subnanometer length scale is demonstrated across a HxVO2 thin film focusing on the oxygen-hydrogen bonds using electron energy loss spectroscopy (EELS) coupled with first-principles EELS calculations. The hydrogen distribution was revealed to be nonuniform along the growth direction and between different VO2 grains, calling for intricate hydrogenation mechanisms. Our study points to a powerful approach to quantitatively map dopant distribution in quantum materials relevant to energy and information sciences.

Modeling denitrification nitrogen losses in China's rice fields based on multiscale field-experiment constraints.

Denitrification plays a critical role in soil nitrogen (N) cycling, affecting N availability in agroecosystems. However, the challenges in direct measurement of denitrification products (NO, N2 O, and N2 ) hinder our understanding of denitrification N losses patterns across the spatial scale. To address this gap, we constructed a data-model fusion method to map the county-scale denitrification N losses from China's rice fields over the past decade. The estimated denitrification N losses as a percentage of N application from 2009 to 2018 were 11.8 ± 4.0% for single rice, 12.4 ± 3.7% for early rice, and 11.6 ± 3.1% for late rice. The model results showed that the spatial heterogeneity of denitrification N losses is primarily driven by edaphic and climatic factors rather than by management practices. In particular, diffusion and production rates emerged as key contributors to the variation of denitrification N losses. These findings humanize a 38.9 ± 4.8 kg N ha-1 N loss by denitrification and challenge the common hypothesis that substrate availability drives the pattern of N losses by denitrification in rice fields.

Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) modified metal-organic frameworks boosting carbon dots electrochemiluminescence emission for sensitive miRNA detection.

Highly efficient luminescent materials play an important role in electrochemiluminescence (ECL) biosensing systems. Herein, the poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) modified carbon dots (CDs)/zeolitic imidazolate framework-8 (ZIF-8) compositing metal-organic frameworks (MOFs) materials with excellent luminescence performance were prepared as the ECL emitters for biosensing application. In this novel ternary composites, CDs were used as emitters, ZIF-8 was used as a carrier, and the luminescent performance was finally improved by introducing PEDOT:PSS to improve the conductivity of the nanomaterials. As a result, CDs/PEDOT:PSS/ZIF-8 exhibited an approximately 8 times ECL intensity compared to CDs alone. By further modifying with AuNPs, the enhancement factor reached ≈10 in reference to the individual CDs. After combining with a DNAzyme-based two-cycle target amplification principle, an ECL biosensor was constructed to achieve high-sensitivity detection of miRNA-21 with a detection limit of 50 aM. The biosensor also demonstrated desirable selectivity, excellent stability, and quantitative ability for human serum target detection. Overall, these findings not only provide a promising pathway for high luminous efficiency ECL emitters synthesis, but also provide a platform for ultrasensitive miRNA sensing.

A MnO2 nanosheet-mediated CRISPR/Cas12a system for the detection of organophosphorus pesticides in environmental water.

Nowadays, easy, convenient, and sensitive sensing strategies are still critical for organophosphorus pesticides in environmental water samples. Herein, a novel organophosphorus pesticide (OP) assay based on acetylcholinesterase (AChE) and a MnO2 nanosheet-mediated CRISPR/Cas12a reaction is reported. The single-strand DNA (ssDNA) activator of CRISPR/Cas12a was simply adsorbed on the MnO2 nanosheets as the nanoswitches of the assay. In the absence of target OPs, AChE hydrolyzed acetylcholine (ATCh) to thiocholine (TCh), which reduced the MnO2 nanosheets to Mn2+, resulting in the release of the activator followed by activation of the CRISPR/Cas12a system. The activated Cas12a thereafter nonspecifically cleaved the FAM/BHQ1-labeled ssDNA (FQ-reporter), producing a fluorescence signal. Upon the addition of target OPs, the hydrolysis of ATCh by AChE was inhibited owing to OPs combining with AChE, and thus effective quantification of OPs could be achieved by measuring the fluorescence changes of the system. As a proof of concept, dichlorvos (DDVP) was chosen as a model OP analyte to address the feasibility of the proposed method. Attributed to the excellent trans-cleavage activity of Cas12a, the fluorescent biosensor exhibits a satisfactory limit of detection (LOD) for DDVP at 0.135 ng mL-1. In addition, the excellent recoveries for the detection of DDVP in environmental water samples demonstrate the applicability of the proposed assay in real sample research.

Spatial Interactions in Hydrogenated Perovskite Nickelate Synaptic Networks.

A key aspect of how the brain learns and enables decision-making processes is through synaptic interactions. Electrical transmission and communication in a network of synapses are modulated by extracellular fields generated by ionic chemical gradients. Emulating such spatial interactions in synthetic networks can be of potential use for neuromorphic learning and the hardware implementation of artificial intelligence. Here, we demonstrate that in a network of hydrogen-doped perovskite nickelate devices, electric bias across a single junction can tune the coupling strength between the neighboring cells. Electrical transport measurements and spatially resolved diffraction and nanoprobe X-ray and scanning microwave impedance spectroscopic studies suggest that graded proton distribution in the inhomogeneous medium of hydrogen-doped nickelate film enables this behavior. We further demonstrate signal integration through the coupling of various junctions.

DOT1L bridges transcription and heterochromatin formation at mammalian pericentromeres.

Repetitive DNA elements are packaged in heterochromatin, but many require bursts of transcription to initiate and maintain long-term silencing. The mechanisms by which these heterochromatic genome features are transcribed remain largely unknown. Here, we show that DOT1L, a conserved histone methyltransferase that modifies lysine 79 of histone H3 (H3K79), has a specialized role in transcription of major satellite repeats to maintain pericentromeric heterochromatin and genome stability. We find that H3K79me3 is selectively enriched relative to H3K79me2 at repetitive elements in mouse embryonic stem cells (mESCs), that DOT1L loss compromises pericentromeric satellite transcription, and that this activity involves possible coordination between DOT1L and the chromatin remodeler SMARCA5. Stimulation of transcript production from pericentromeric repeats by DOT1L participates in stabilization of heterochromatin structures in mESCs and cleavage-stage embryos and is required for preimplantation viability. Our findings uncover an important role for DOT1L as a bridge between transcriptional activation of repeat elements and heterochromatin stability, advancing our understanding of how genome integrity is maintained and how chromatin state is set up during early development.

Oxide-Derived Bismuth as an Efficient Catalyst for Electrochemical Reduction of Flue Gas.

Post-combustion flue gas (mainly containing 5-40% CO2 balanced by N2 ) accounts for about 60% global CO2 emission. Rational conversion of flue gas into value-added chemicals is still a formidable challenge. Herein, this work reports a ß-Bi2 O3 -derived bismuth (OD-Bi) catalyst with surface coordinated oxygen for efficient electroreduction of pure CO2 , N2, and flue gas. During pure CO2 electroreduction, the maximum Faradaic efficiency (FE) of formate reaches 98.0% and stays above 90% in a broad potential of 600 mV with a long-term stability of 50 h. Additionally, OD-Bi achieves an ammonia (NH3 ) FE of 18.53% and yield rate of 11.5 µg h-1 mgcat -1 in pure N2 atmosphere. Noticeably, in simulated flue gas (15% CO2 balanced by N2 with trace impurities), a maximum formate FE of 97.3% is delivered within a flow cell, meanwhile above 90% formate FEs are obtained in a wide potential range of 700 mV. In-situ Raman combined with theory calculations reveals that the surface coordinated oxygen species in OD-Bi can drastically activate CO2 and N2 molecules by selectively favors the adsorption of *OCHO and *NNH intermediates, respectively. This work provides a surface oxygen modulation strategy to develop efficient bismuth-based electrocatalysts for directly reducing commercially relevant flue gas into valuable chemicals.

Selective area doping for Mott neuromorphic electronics.

The cointegration of artificial neuronal and synaptic devices with homotypic materials and structures can greatly simplify the fabrication of neuromorphic hardware. We demonstrate experimental realization of vanadium dioxide (VO2) artificial neurons and synapses on the same substrate through selective area carrier doping. By locally configuring pairs of catalytic and inert electrodes that enable nanoscale control over carrier density, volatility or nonvolatility can be appropriately assigned to each two-terminal Mott memory device per lithographic design, and both neuron- and synapse-like devices are successfully integrated on a single chip. Feedforward excitation and inhibition neural motifs are demonstrated at hardware level, followed by simulation of network-level handwritten digit and fashion product recognition tasks with experimental characteristics. Spatially selective electron doping opens up previously unidentified avenues for integration of emerging correlated semiconductors in electronic device technologies.

Metallic bismuth nanoclusters confined in micropores for efficient electrocatalytic reduction of carbon dioxide with long-term stability.

Electrochemical reduction of CO2 to formate via renewable electricity is a cost-effective route. However, the existing bismuth-based electrocatalysts are in oxide form and involve in-situ reduction to metallic bismuth during CO2 reduction. In this work, we demonstrate a nanocomposite electrocatalyst by confining Bi nanoclusters into porous carbons (Bi NCs@PC). In particular, the Bi NCs show excellent stability that can maintain zero valences during long-term electrocatalysis or after months of storage in the air. The as-synthesized Bi NCs@PC catalyst achieves up to 96 % formate Faradaic efficiency (FE) at -1.15 V versus reversible hydrogen electrode. Notably, the FE only attenuates by 7.3 % after 30 days of storage under ambient conditions. In-situ Raman spectrum identify the key intermediates during formate formation. Moreover, Bi NCs encapsulated in carbon micropores could significantly reduce the formation energy of the intermediate *OCHO by density functional theory.

Complex Oxides for Brain-Inspired Computing: A Review.

The fields of brain-inspired computing, robotics, and, more broadly, artificial intelligence (AI) seek to implement knowledge gleaned from the natural world into human-designed electronics and machines. In this review, the opportunities presented by complex oxides, a class of electronic ceramic materials whose properties can be elegantly tuned by doping, electron interactions, and a variety of external stimuli near room temperature, are discussed. The review begins with a discussion of natural intelligence at the elementary level in the nervous system, followed by collective intelligence and learning at the animal colony level mediated by social interactions. An important aspect highlighted is the vast spatial and temporal scales involved in learning and memory. The focus then turns to collective phenomena, such as metal-to-insulator transitions (MITs), ferroelectricity, and related examples, to highlight recent demonstrations of artificial neurons, synapses, and circuits and their learning. First-principles theoretical treatments of the electronic structure, and in situ synchrotron spectroscopy of operating devices are then discussed. The implementation of the experimental characteristics into neural networks and algorithm design is then revewed. Finally, outstanding materials challenges that require a microscopic understanding of the physical mechanisms, which will be essential for advancing the frontiers of neuromorphic computing, are highlighted.

Efficient Probabilistic Computing with Stochastic Perovskite Nickelates.

Probabilistic computing has emerged as a viable approach to solve hard optimization problems. Devices with inherent stochasticity can greatly simplify their implementation in electronic hardware. Here, we demonstrate intrinsic stochastic resistance switching controlled via electric fields in perovskite nickelates doped with hydrogen. The ability of hydrogen ions to reside in various metastable configurations in the lattice leads to a distribution of transport gaps. With experimentally characterized p-bits, a shared-synapse p-bit architecture demonstrates highly parallelized and energy-efficient solutions to optimization problems such as integer factorization and Boolean satisfiability. The results introduce perovskite nickelates as scalable potential candidates for probabilistic computing and showcase the potential of light-element dopants in next-generation correlated semiconductors.

Negative Differential Resistance in Oxygen-ion Conductor Yttria-stabilized Zirconia for Extreme Environment Electronics.

Oxygen-ion conductors have traditionally been studied in the context of high temperature (≈ 873 to 1773 K) energy conversion and sensor technologies. However, there is growing interest in exploring ion-based electronics for harsh environments (400 to 573 K) that represents an emerging field. Here, we utilize a blocking electrode to modify the interface properties of oxygen-ion conducting yttria-stabilized zirconia (YSZ) thin film electrochemical cells. The modified YSZ cell exhibits negative differential resistance (NDR) in the current-voltage curves at 543 K in the air. A double-sweep method and analysis of the scan-rate dependence of the j-V characteristics clearly suggest that the NDR behavior is formed by the reduction reaction of adsorbed oxygen or platinum oxide at the YSZ/Pt interface. A stable and switchable YSZ NDR device is realized with a high peak-to-valley current ratio of 5.8 at 543 K. Utilizing the NDR effect, we demonstrate a proof-of-concept switchable ternary inverter by interfacing with a silicon transistor. Oxygen-ion conductors and their interfaces offer new directions to design electronics for extreme environments.