Global citrus root microbiota unravels assembly cues and core members.

Introduction: Citrus is one of the most important fruit crops worldwide, and the root-associated microbiota can have a profound impact on tree health and growth. Methods: In a collaborative effort, the International Citrus Microbiome Consortium investigated the global citrus root microbiota with samples collected from nine citrus-producing countries across six continents. We analyzed 16S rDNA and ITS2 amplicon sequencing data to identify predominant prokaryotic and fungal taxa in citrus root samples. Comparative analyses were conducted between root-associated microbial communities and those from the corresponding rhizosphere and bulk soil samples. Additionally, genotype-based group-wise comparisons were performed to assess the impact of citrus genotype on root microbiota composition. Results: Ten predominant prokaryotic phyla, containing nine bacterial phyla including Proteobacteria, Actinobacteria, Acidobacteria, and Bacteroidetes and one archaeal phylum (Thaumarchaeota), and multiple fungal phyla including Ascomycota and Basidiomycota were identified in the citrus root samples. Compared with the microbial communities from the corresponding rhizosphere and bulk soil samples from the same trees, the prokaryotic and fungal communities in the roots exhibited lower diversity and complexity but greater modularity compared to those in the rhizosphere. In total, 30 root-enriched and 150 root-depleted genera in bacterial community were identified, whereas 21 fungal genera were enriched, and 147 fungal genera were depleted in the root niche compared with the rhizosphere. The citrus genotype significantly affected the root prokaryotic and fungal communities. In addition, we have identified the core root prokaryotic genera comprising Acidibacter, Allorhizobium, Bradyrhizobium, Chitinophaga, Cupriavidus, Devosia, Dongia, Niastella, Pseudomonas, Sphingobium, Steroidobacter and Streptomyces, and the core fungal genera including Acrocalymma, Cladosporium, Fusarium, Gibberella, Mortierella, Neocosmospora and Volutella. The potential functions of these core genera of root microbiota were predicted. Conclusion: Overall, this study provides new insights into the assembly of microbial communities and identifies core members of citrus root microbiota across a wide geographic range. The findings offer valuable information for manipulating root microbiota to enhance plant growth and health.

Isolation of anti-tumor monoclonal antibodies targeting on MICA/B α3 domain by single B cell technology for colon cancer therapy.

Colon cancer (CC) is one of the most common gastrointestinal malignancies. Effectiveness of the existing therapies is limited. Immunotherapy is a promising complementary treatment approach for CC. Major histocompatibility complex class I-related protein A and B (MICA/B) are ligands for NK cells. Shedding of MICA/B from the surface of tumor cells by cleavage of MICA/B at the membrane proxial region in MICA/B α3 structural domain is one of immune evasion strategies leading to escape of cancer cells from immunosurveillance. In this study, we generated a panel of MICA/B monoclonal antibodies (mAbs) and identified one of mAbs, mAb RDM028, that had high binding affinity to MICA/B and recognized a site on MICA/B α3 structural domain that is critically important for cleavage of MICA/B. Our study has further demonstrated that RDM028 augmented the surface expression of MICA/B on HCT-116 human CC cells by inhibiting the MICA/B shedding resulting in the enhanced cyotoxicity of NK cells against HCT-116 human CC cells and mediated anti-tumor activity in nude mouse model of colon cancer. These results indicate that mAb RDM028 could be explored for developing as an effective immuno therapy against CC by targeting the MICA/B α3 domain to promot immunosurveillance mediated by MICA/B-NKG2D interaction.

Development and validation of a nomogram for predicting occurrence of severe case in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era.

Background: The significant rebound of influenza A (H1N1) virus activity, particularly among children, with rapidly growing number of hospitalized cases is of major concern in the post-COVID-19 era. The present study was performed to establish a prediction model of severe case in pediatric patients hospitalized with H1N1 infection during the post-COVID-19 era. Methods: This is a multicenter retrospective study across nine public tertiary hospitals in Yunnan, China, recruiting pediatric H1N1 inpatients hospitalized at five of these centers between February 1 and July 1, 2023, into the development dataset. Screening of 40 variables including demographic information, clinical features, and laboratory parameters were performed utilizing Least Absolute Shrinkage and Selection Operator (LASSO) regression and logistic regression to determine independent risk factors of severe H1N1 infection, thus constructing a prediction nomogram. Receiver operating characteristic (ROC) curve, calibration curve, as well as decision curve analysis (DCA) were employed to evaluate the model's performance. Data from four independent cohorts comprised of pediatric H1N1 inpatients from another four hospitals between July 25 and October 31, 2023, were utilized to externally validate this nomogram. Results: The development dataset included 527 subjects, 122 (23.1 %) of whom developed severe H1N1 infection. The external validation dataset included 352 subjects, 72 (20.5 %) of whom were eventually confirmed as severe H1N1 infection. The LASSO regression identified 19 candidate predictors, with logistic regression further narrowing down to 11 independent risk factors, including underlying conditions, prematurity, fever duration, wheezing, poor appetite, leukocyte count, neutrophil-lymphocyte ratio (NLR), erythrocyte sedimentation rate (ESR), lactate dehydrogenase (LDH), interleukin-10 (IL-10), and tumor necrosis factor-α (TNF-α). By integrating these 11 factors, a predictive nomogram was established. In terms of prediction of severe H1N1 infection, excellent discriminative capacity, favorable accuracy, and satisfactory clinical usefulness of this model were internally and externally validated via ROC curve, calibration curve, and DCA, respectively. Conclusion: Our study successfully established and validated a novel nomogram model integrating underlying conditions, prematurity, fever duration, wheezing, poor appetite, leukocyte count, NLR, ESR, LDH, IL-10, and TNF-α. This nomogram can effectively predict the occurrence of serious case in pediatric H1N1 inpatients during the post-COVID-19 era, facilitating the early recognition and more efficient clinical management of such patients.

A novel combined nomogram for predicting severe acute lower respiratory tract infection in children hospitalized for RSV infection during the post-COVID-19 period.

Introduction: Off-season upsurge of respiratory syncytial virus (RSV) infection with changed characteristics and heightened clinical severity during the post-COVID-19 era are raising serious concerns. This study aimed to develop and validate a nomogram for predicting the risk of severe acute lower respiratory tract infection (SALRTI) in children hospitalized for RSV infection during the post-COVID-19 era using machine learning techniques. Methods: A multicenter retrospective study was performed in nine tertiary hospitals in Yunnan, China, enrolling children hospitalized for RSV infection at seven of the nine participating hospitals during January-December 2023 into the development dataset. Thirty-nine variables covering demographic, clinical, and laboratory characteristics were collected. Primary screening and dimension reduction of data were performed using Least Absolute Shrinkage and Selection Operator (LASSO) regression, followed by identification of independent risk factors for RSV-associated SALRTI using Logistic regression, thus finally establishing a predictive nomogram model. Performance of the nomogram was internally evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) based on the development dataset. External validation of our model was conducted using same methods based on two independent RSV cohorts comprising pediatric RSV inpatients from another two participating hospitals between January-March 2024. Results: The development dataset included 1102 patients, 239 (21.7%) of whom developed SALRTI; while the external validation dataset included 249 patients (142 in Lincang subset and 107 in Dali subset), 58 (23.3%) of whom were diagnosed as SALRTI. Nine variables, including age, preterm birth, underlying condition, seizures, neutrophil-lymphocyte ratio (NLR), interleukin-6 (IL-6), lactate dehydrogenase (LDH), D-dimer, and co-infection, were eventually confirmed as the independent risk factors of RSV-associated SALRTI. A predictive nomogram was established via integrating these nine predictors. In both internal and external validations, ROC curves indicated that the nomogram had satisfactory discrimination ability, calibration curves demonstrated good agreement between the nomogram-predicted and observed probabilities of outcome, and DCA showed that the nomogram possessed favorable clinical application potential. Conclusion: A novel nomogram combining several common clinical and inflammatory indicators was successfully developed to predict RSV-associated SALRTI. Good performance and clinical effectiveness of this model were confirmed by internal and external validations.

A Natural Bioactive Peptide from Pinctada fucata Pearls Can Be Used as a Potential Inhibitor of the Interaction between SARS-CoV-2 and ACE2 against COVID-19.

The frequent occurrence of viral infections poses a serious threat to human life. Identifying effective antiviral components is urgent. In China, pearls have been important traditional medicinal ingredients since ancient times, exhibiting various therapeutic properties, including detoxification properties. In this study, a peptide, KKCH, which acts against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was derived from Pinctada fucata pearls. Molecular docking showed that it bound to the same pocket of the SARS-CoV-2 S protein and cell surface target angiotensin-converting enzyme II (ACE2). The function of KKCH was analyzed through surface plasmon resonance (SPR), Enzyme-Linked Immunosorbent Assays, immunofluorescence, and simulation methods using the SARS-CoV-2 pseudovirus and live virus. The results showed that KKCH had a good affinity for ACE2 (KD = 6.24 × 10-7 M) and could inhibit the binding of the S1 protein to ACE2 via competitive binding. As a natural peptide, KKCH inhibited the binding of the SARS-CoV-2 S1 protein to the surface of human BEAS-2B and HEK293T cells. Moreover, viral experiments confirmed the antiviral activity of KKCH against both the SARS-CoV-2 spike pseudovirus and SARS-CoV-2 live virus, with half-maximal inhibitory concentration (IC50) values of 398.1 µM and 462.4 µM, respectively. This study provides new insights and potential avenues for the prevention and treatment of SARS-CoV-2 infections.

Visualization of oxygen vacancies and self-doped ligand holes in La3Ni2O7-δ.

The recent discovery of superconductivity in La3Ni2O7-δ under high pressure with a transition temperature around 80 K (ref. 1) has sparked extensive experimental2-6 and theoretical efforts7-12. Several key questions regarding the pairing mechanism remain to be answered, such as the most relevant atomic orbitals and the role of atomic deficiencies. Here we develop a new, energy-filtered, multislice electron ptychography technique, assisted by electron energy-loss spectroscopy, to address these critical issues. Oxygen vacancies are directly visualized and are found to primarily occupy the inner apical sites, which have been proposed to be crucial to superconductivity13,14. We precisely determine the nanoscale stoichiometry and its correlation to the oxygen K-edge spectra, which reveals a significant inhomogeneity in the oxygen content and electronic structure within the sample. The spectroscopic results also reveal that stoichiometric La3Ni2O7 has strong charge-transfer characteristics, with holes that are self-doped from Ni sites into O sites. The ligand holes mainly reside on the inner apical O and the planar O, whereas the density on the outer apical O is negligible. As the concentration of O vacancies increases, ligand holes on both sites are simultaneously annihilated. These observations will assist in further development and understanding of superconducting nickelate materials. Our imaging technique for quantifying atomic deficiencies can also be widely applied in materials science and condensed-matter physics.

Emergent normal fluid in the superconducting ground state of overdoped cuprates.

The microscopic mechanism for the disappearance of superconductivity in overdoped cuprates is still under heated debate. Here we use scanning tunneling spectroscopy to investigate the evolution of quasiparticle interference phenomenon in Bi2Sr2CuO6+δ over a wide range of hole densities. We find that when the system enters the overdoped regime, a peculiar quasiparticle interference wavevector with arc-like pattern starts to emerge even at zero bias, and its intensity grows with increasing doping level. Its energy dispersion is incompatible with the octet model for d-wave superconductivity, but is highly consistent with the scattering interference of gapless normal carriers. The gapless quasiparticles are mainly located near the antinodes and are independent of temperature, consistent with the disorder scattering mechanism. We propose that a branch of normal fluid emerges from the pair-breaking scattering between flat antinodal bands in the quantum ground state, which is the primary cause for the reduction of superfluid density and suppression of superconductivity in overdoped cuprates.

Visualization Analysis of Small Extracellular Vesicles in the Application of Bone-Related Diseases.

Small extracellular vesicles were shown to have similar functional roles to their parent cells without the defect of potential tumorigenicity, which made them a great candidate for regenerative medicine. The last twenty years have witnessed the rapid development of research on small extracellular vesicles. In this paper, we employed a scientometric synthesis method to conduct a retrospective analysis of small extracellular vesicles in the field of bone-related diseases. The overall background analysis consisted the visualization of the countries, institutions, journals, and authors involved in research. The current status of the research direction and future trends were presented through the analysis of references and keywords, which showed that engineering strategies, mesenchymal stem cell derived exosomes, and cartilage damage were the most concerning topics, and scaffold, osteoarthritis, platelet-rich plasma, and senescence were the future trends. We also discussed the current problems and challenges in practical applications, including the in-sight mechanisms, the building of relevant animal models, and the problems in clinical trials. By using CiteSpace, VOSviewer, and Bibliometrix, the presented data avoided subjective selectivity and tendency well, which made the conclusion more reliable and comprehensive. We hope that the findings can provide new perspectives for researchers to understand the evolution of this field over time and to search for novel research directions.

An integrated multi-omics approach reveals polymethoxylated flavonoid biosynthesis in Citrus reticulata cv. Chachiensis.

Citrus reticulata cv. Chachiensis (CRC) is an important medicinal plant, its dried mature peels named "Guangchenpi", has been used as a traditional Chinese medicine to treat cough, indigestion, and lung diseases for several hundred years. However, the biosynthesis of the crucial natural products polymethoxylated flavonoids (PMFs) in CRC remains unclear. Here, we report a chromosome-scale genome assembly of CRC with the size of 314.96 Mb and a contig N50 of 16.22 Mb. Using multi-omics resources, we discover a putative caffeic acid O-methyltransferase (CcOMT1) that can transfer a methyl group to the 3-hydroxyl of natsudaidain to form 3,5,6,7,8,3',4'-heptamethoxyflavone (HPMF). Based on transient overexpression and virus-induced gene silencing experiments, we propose that CcOMT1 is a candidate enzyme in HPMF biosynthesis. In addition, a potential gene regulatory network associated with PMF biosynthesis is identified. This study provides insights into PMF biosynthesis and may assist future research on mining genes for the biosynthesis of plant-based medicines.

Laryngopharyngeal reflux disease: Updated examination of mechanisms, pathophysiology, treatment, and association with gastroesophageal reflux disease.

Laryngopharyngeal reflux disease (LPRD) is an inflammatory condition in the laryngopharynx and upper aerodigestive tract mucosa caused by reflux of stomach contents beyond the esophagus. LPRD commonly presents with sym-ptoms such as hoarseness, cough, sore throat, a feeling of throat obstruction, excessive throat mucus. This complex condition is thought to involve both reflux and reflex mechanisms, but a clear understanding of its molecular mechanisms is still lacking. Currently, there is no standardized diagnosis or treatment protocol. Therapeutic strategies for LPRD mainly include lifestyle modifications, proton pump inhibitors and endoscopic surgery. This paper seeks to provide a comprehensive overview of the existing literature regarding the mechanisms, patho-physiology and treatment of LPRD. We also provide an in-depth exploration of the association between LPRD and gastroesophageal reflux disease.

Fabrication-induced even-odd discrepancy of magnetotransport in few-layer MnBi2Te4.

The van der Waals antiferromagnetic topological insulator MnBi2Te4 represents a promising platform for exploring the layer-dependent magnetism and topological states of matter. Recently observed discrepancies between magnetic and transport properties have aroused controversies concerning the topological nature of MnBi2Te4 in the ground state. In this article, we demonstrate that fabrication can induce mismatched even-odd layer dependent magnetotransport in few-layer MnBi2Te4. We perform a comprehensive study of the magnetotransport properties in 6- and 7-septuple-layer MnBi2Te4, and reveal that both even- and odd-number-layer device can show zero Hall plateau phenomena in zero magnetic field. Importantly, a statistical survey of the optical contrast in more than 200 MnBi2Te4 flakes reveals that the zero Hall plateau in odd-number-layer devices arises from the reduction of the effective thickness during the fabrication, a factor that was rarely noticed in previous studies of 2D materials. Our finding not only provides an explanation to the controversies regarding the discrepancy of the even-odd layer dependent magnetotransport in MnBi2Te4, but also highlights the critical issues concerning the fabrication and characterization of 2D material devices.

LettuceDB: an integrated multi-omics database for cultivated lettuce.

Crop genomics has advanced rapidly during the past decade, which generated a great abundance of omics data from multi-omics studies. How to utilize the accumulating data becomes a critical and urgent demand in crop science. As an attempt to integrate multi-omics data, we developed a database, LettuceDB (https://db.cngb.org/lettuce/), aiming to assemble multidimensional data for cultivated and wild lettuce germplasm. The database includes genome, variome, phenome, microbiome and spatial transcriptome. By integrating user-friendly bioinformatics tools, LettuceDB will serve as a one-stop platform for lettuce research and breeding in the future. Database URL: https://db.cngb.org/lettuce/.

The first bioactive (angiotensin-converting enzyme-inhibitory) peptide isolated from pearl matrix protein.

In this research, we unveil the medical potential of pearls by identifying a novel bioactive peptide within them for the first time. The peptide, termed KKCHFWPFPW, emerges as a pioneering angiotensin I-converting enzyme (ACE) inhibitor, originating from the pearl matrix of Pinctada fucata. Employing quadrupole time-of-flight mass spectrometry, this peptide was meticulously selected and pinpointed. With a molecular weight of 1417.5 Da and a theoretical isoelectric point of 9.31, its inhibitory potency was demonstrated through a half-maximal inhibitory concentration (IC50) of 4.17 µM, established via high-performance liquid chromatography. The inhibition of ACE by this peptide was found to be competitive, as revealed by Lineweaver-Burk plot analysis, where an increase in peptide concentration correlated with an enhanced rate of ACE inhibition. To delve into the interaction between KKCHFWPFPW and ACE, molecular docking simulations were conducted using the Maestro 2022-1 Glide software, shedding light on the inhibitory mechanism. This investigation suggests that peptides derived from the P. martensii pearl matrix hold promise as a novel source for antihypertensive agents.

Evaluation of disease severity and prediction of severe cases in children hospitalized with influenza A (H1N1) infection during the post-COVID-19 era: a multicenter retrospective study.

BACKGROUND: The rebound of influenza A (H1N1) infection in post-COVID-19 era recently attracted enormous attention due the rapidly increased number of pediatric hospitalizations and the changed characteristics compared to classical H1N1 infection in pre-COVID-19 era. This study aimed to evaluate the clinical characteristics and severity of children hospitalized with H1N1 infection during post-COVID-19 period, and to construct a novel prediction model for severe H1N1 infection. METHODS: A total of 757 pediatric H1N1 inpatients from nine tertiary public hospitals in Yunnan and Shanghai, China, were retrospectively included, of which 431 patients diagnosed between February 2023 and July 2023 were divided into post-COVID-19 group, while the remaining 326 patients diagnosed between November 2018 and April 2019 were divided into pre-COVID-19 group. A 1:1 propensity-score matching (PSM) was adopted to balance demographic differences between pre- and post-COVID-19 groups, and then compared the severity across these two groups based on clinical and laboratory indicators. Additionally, a subgroup analysis in the original post-COVID-19 group (without PSM) was performed to investigate the independent risk factors for severe H1N1 infection in post-COIVD-19 era. Specifically, Least Absolute Shrinkage and Selection Operator (LASSO) regression was applied to select candidate predictors, and logistic regression was used to further identify independent risk factors, thus establishing a prediction model. Receiver operating characteristic (ROC) curve and calibration curve were utilized to assess discriminative capability and accuracy of the model, while decision curve analysis (DCA) was used to determine the clinical usefulness of the model. RESULTS: After PSM, the post-COVID-19 group showed longer fever duration, higher fever peak, more frequent cough and seizures, as well as higher levels of C-reactive protein (CRP), interleukin 6 (IL-6), IL-10, creatine kinase-MB (CK-MB) and fibrinogen, higher mechanical ventilation rate, longer length of hospital stay (LOS), as well as higher proportion of severe H1N1 infection (all P < 0.05), compared to the pre-COVID-19 group. Moreover, age, BMI, fever duration, leucocyte count, lymphocyte proportion, proportion of CD3+ T cells, tumor necrosis factor α (TNF-α), and IL-10 were confirmed to be independently associated with severe H1N1 infection in post-COVID-19 era. A prediction model integrating these above eight variables was established, and this model had good discrimination, accuracy, and clinical practicability. CONCLUSIONS: Pediatric H1N1 infection during post-COVID-19 era showed a higher overall disease severity than the classical H1N1 infection in pre-COVID-19 period. Meanwhile, cough and seizures were more prominent in children with H1N1 infection during post-COVID-19 era. Clinicians should be aware of these changes in such patients in clinical work. Furthermore, a simple and practical prediction model was constructed and internally validated here, which showed a good performance for predicting severe H1N1 infection in post-COVID-19 era.

Drosophila TMEM63 and mouse TMEM63A are lysosomal mechanosensory ion channels.

Cells sense physical forces and convert them into electrical or chemical signals, a process known as mechanotransduction. Whereas extensive studies focus on mechanotransduction at the plasma membrane, little is known about whether and how intracellular organelles sense mechanical force and the physiological functions of organellar mechanosensing. Here we identify the Drosophila TMEM63 (DmTMEM63) ion channel as an intrinsic mechanosensor of the lysosome, a major degradative organelle. Endogenous DmTMEM63 proteins localize to lysosomes, mediate lysosomal mechanosensitivity and modulate lysosomal morphology and function. Tmem63 mutant flies exhibit impaired lysosomal degradation, synaptic loss, progressive motor deficits and early death, with some of these mutant phenotypes recapitulating symptoms of TMEM63-associated human diseases. Importantly, mouse TMEM63A mediates lysosomal mechanosensitivity in Neuro-2a cells, indicative of functional conservation in mammals. Our findings reveal DmTMEM63 channel function in lysosomes and its physiological roles in vivo and provide a molecular basis to explore the mechanosensitive process in subcellular organelles.

Dynamic root microbiome sustains soybean productivity under unbalanced fertilization.

Root-associated microbiomes contribute to plant growth and health, and are dynamically affected by plant development and changes in the soil environment. However, how different fertilizer regimes affect quantitative changes in microbial assembly to effect plant growth remains obscure. Here, we explore the temporal dynamics of the root-associated bacteria of soybean using quantitative microbiome profiling (QMP) to examine its response to unbalanced fertilizer treatments (i.e., lacking either N, P or K) and its role in sustaining plant growth after four decades of unbalanced fertilization. We show that the root-associated bacteria exhibit strong succession during plant development, and bacterial loads largely increase at later stages, particularly for Bacteroidetes. Unbalanced fertilization has a significant effect on the assembly of the soybean rhizosphere bacteria, and in the absence of N fertilizer the bacterial community diverges from that of fertilized plants, while lacking P fertilizer impedes the total load and turnover of rhizosphere bacteria. Importantly, a SynCom derived from the low-nitrogen-enriched cluster is capable of stimulating plant growth, corresponding with the stabilized soybean productivity in the absence of N fertilizer. These findings provide new insights in the quantitative dynamics of the root-associated microbiome and highlight a key ecological cluster with prospects for sustainable agricultural management.

Quantized anomalous Hall resistivity achieved in molecular beam epitaxy-grown MnBi2Te4 thin films.

The intrinsic magnetic topological insulator MnBi2Te4 provides a feasible pathway to the high-temperature quantum anomalous Hall (QAH) effect as well as various novel topological quantum phases. Although quantized transport properties have been observed in exfoliated MnBi2Te4 thin flakes, it remains a big challenge to achieve molecular beam epitaxy (MBE)-grown MnBi2Te4 thin films even close to the quantized regime. In this work, we report the realization of quantized anomalous Hall resistivity in MBE-grown MnBi2Te4 thin films with the chemical potential tuned by both controlled in situ oxygen exposure and top gating. We find that elongated post-annealing obviously elevates the temperature to achieve quantization of the Hall resistivity, but also increases the residual longitudinal resistivity, indicating a picture of high-quality QAH puddles weakly coupled by tunnel barriers. These results help to clarify the puzzles in previous experimental studies on MnBi2Te4 and to find a way out of the big difficulty in obtaining MnBi2Te4 samples showing quantized transport properties.

Progress on the antiferromagnetic topological insulator MnBi2Te4.

Topological materials, which feature robust surface and/or edge states, have now been a research focus in condensed matter physics. They represent a new class of materials exhibiting nontrivial topological phases, and provide a platform for exploring exotic transport phenomena, such as the quantum anomalous Hall effect and the quantum spin Hall effect. Recently, magnetic topological materials have attracted considerable interests due to the possibility to study the interplay between topological and magnetic orders. In particular, the quantum anomalous Hall and axion insulator phases can be realized in topological insulators with magnetic order. MnBi2Te4, as the first intrinsic antiferromagnetic topological insulator discovered, allows the examination of existing theoretical predictions; it has been extensively studied, and many new discoveries have been made. Here we review the progress made on MnBi2Te4 from both experimental and theoretical aspects. The bulk crystal and magnetic structures are surveyed first, followed by a review of theoretical calculations and experimental probes on the band structure and surface states, and a discussion of various exotic phases that can be realized in MnBi2Te4. The properties of MnBi2Te4 thin films and the corresponding transport studies are then reviewed, with an emphasis on the edge state transport. Possible future research directions in this field are also discussed.

Gate-Controlled Neuromorphic Functional Transition in an Electrochemical Graphene Transistor.

Neuromorphic devices have attracted significant attention as potential building blocks for the next generation of computing technologies owing to their ability to emulate the functionalities of biological nervous systems. The essential components in artificial neural networks such as synapses and neurons are predominantly implemented by dedicated devices with specific functionalities. In this work, we present a gate-controlled transition of neuromorphic functions between artificial neurons and synapses in monolayer graphene transistors that can be employed as memtransistors or synaptic transistors as required. By harnessing the reliability of reversible electrochemical reactions between carbon atoms and hydrogen ions, we can effectively manipulate the electric conductivity of graphene transistors, resulting in a high on/off resistance ratio, a well-defined set/reset voltage, and a prolonged retention time. Overall, the on-demand switching of neuromorphic functions in a single graphene transistor provides a promising opportunity for developing adaptive neural networks for the upcoming era of artificial intelligence and machine learning.

Dynamics of rhizosphere microbial structure and function associated with the biennial bearing of moso bamboo.

Moso bamboo (Phyllostachys edulis) is a valuable nontimber forestry product with a biennial cycle, producing abundant bamboo shoots within one year (on-year) and few shoots within the following year (off-year). Moso bamboo plants undergo clonal reproduction, resulting in similar genetic backgrounds. However, the number of moso bamboo shoots produced each year varies. Despite this variation, the impact of soil nutrients and the root microbiome on the biennial bearing of moso bamboo is poorly understood. We collected 139 soil samples and determined 14 major physicochemical properties of the rhizosphere, rhizoplane, and bulk soil in different seasons (i.e., the growing and deciduous seasons) and different years (i.e., on- and off-years). Based on 16S rRNA and metagenomic sequencing, major variations were found in the rhizospheric microbial composition during different seasons and years in the moso bamboo forest. Environmental driver analysis revealed that essential nutrients (i.e., SOC, TOC, TN, P, and NH4+) were the main drivers of the soil microbial community composition and were correlated with the on- and off-year cycles. Moreover, 19 MAGs were identified as important biomarkers that could distinguish on- and off-years. We found that both season and year influenced both the microbial community structure and functional pathways through the biosynthesis of nutrients that potentially interact with the moso bamboo growth rhythm, especially the on-year root-associated microbiome, which had a greater abundance of specific nutrients such as gibberellins and vitamin B6. This work provides a dynamic perspective of the differential responses of various on- and off-year microbial communities and enhances our understanding of bamboo soil microbiome biodiversity and stability.