Soil microbiome of shiro reveals the symbiotic relationship between Tricholoma bakamatsutake and Quercus mongolica.

Tricholoma bakamatsutake is a delicious and nutritious ectomycorrhizal fungus. However, its cultivation is hindered owing to limited studies on its symbiotic relationships. The symbiotic relationship between T. bakamatsutake and its host is closely related to the shiro, a complex network composed of mycelium, mycorrhizal roots, and surrounding soil. To explore the symbiotic relationship between T. bakamatsutake and its host, soil samples were collected from T. bakamatsutake shiro (Tb) and corresponding Q. mongolica rhizosphere (CK) in four cities in Liaoning Province, China. The physicochemical properties of all the soil samples were then analyzed, along with the composition and function of the fungal and bacterial communities. The results revealed a significant increase in total potassium, available nitrogen, and sand in Tb soil compared to those in CK soil, while there was a significant decrease in pH, total nitrogen, total phosphorus, available phosphorus, and silt. The fungal community diversity in shiro was diminished, and T. bakamatsutake altered the community structure of its shiro by suppressing other fungi, such as Russula (ectomycorrhizal fungus) and Penicillium (phytopathogenic fungus). The bacterial community diversity in shiro increased, with the aggregation of mycorrhizal-helper bacteria, such as Paenibacillus and Bacillus, and plant growth-promoting bacteria, such as Solirubrobacter and Streptomyces, facilitated by T. bakamatsutake. Microbial functional predictions revealed a significant increase in pathways associated with sugar and fat catabolism within the fungal and bacterial communities of shiro. The relative genetic abundance of carboxylesterase and gibberellin 2-beta-dioxygenase in the fungal community was significantly increased, which suggested a potential symbiotic relationship between T. bakamatsutake and Q. mongolica. These findings elucidate the microbial community and relevant symbiotic environment to better understand the relationship between T. bakamatsutake and Q. mongolica.

Adaptive Fusion of Deep Learning With Statistical Anatomical Knowledge for Robust Patella Segmentation From CT Images.

Kneeosteoarthritis (KOA), as a leading joint disease, can be decided by examining the shapes of patella to spot potential abnormal variations. To assist doctors in the diagnosis of KOA, a robust automatic patella segmentation method is highly demanded in clinical practice. Deep learning methods, especially convolutional neural networks (CNNs) have been widely applied to medical image segmentation in recent years. Nevertheless, poor image quality and limited data still impose challenges to segmentation via CNNs. On the other hand, statistical shape models (SSMs) can generate shape priors which give anatomically reliable segmentation to varying instances. Thus, in this work, we propose an adaptive fusion framework, explicitly combining deep neural networks and anatomical knowledge from SSM for robust patella segmentation. Our adaptive fusion framework will accordingly adjust the weight of segmentation candidates in fusion based on their segmentation performance. We also propose a voxel-wise refinement strategy to make the segmentation of CNNs more anatomically correct. Extensive experiments and thorough assessment have been conducted on various mainstream CNN backbones for patella segmentation in low-data regimes, which demonstrate that our framework can be flexibly attached to a CNN model, significantly improving its performance when labeled training data are limited and input image data are of poor quality.

An evaluation of Astragali Radix with different growth patterns and years, based on a new multidimensional comparison method.

Introduction: With the depletion of wild Astragali Radix (WA) resources, imitated-wild Astragali Radix (IWA) and cultivated Astragali Radix (CA) have become the main products of Astragali Radix. However, the quality differences of three growth patterns (WA, IWA, CA) and different growth years of Astragali Radix have not been fully characterized, leading to a lack of necessary scientific evidence for their use as substitutes for WA. Methods: We innovatively proposed a multidimensional evaluation method that encompassed traits, microstructure, cell wall components, saccharides, and pharmacodynamic compounds, to comprehensively explain the quality variances among different growth patterns and years of Astragali Radix. Results and discussion: Our study showed that the quality of IWA and WA was comparatively similar, including evaluation indicators such as apparent color, sectional structure and odor, thickness of phellem, diameter and number of vessels, morphology of phloem and xylem, and the levels and ratios of cellulose, hemicellulose, lignin, sucrose, starch, water-soluble polysaccharides, total-saponins. However, the content of sucrose, starch and sorbose in CA was significantly higher than WA, and the diameter and number of vessels, total-flavonoids content were lower than WA, indicating significant quality differences between CA and WA. Hence, we suggest that IWA should be used as a substitute for WA instead of CA. As for the planting years of IWA, our results indicated that IWA aged 1-32 years could be divided into three stages according to their quality change: rapid growth period (1-5 years), stable growth period (6-20 years), and elderly growth period (25-32 years). Among these, 6-20 years old IWA exhibited consistent multidimensional comparative results, showcasing elevated levels of key active components such as water-soluble polysaccharides, flavonoids, and saponins. Considering both the quality and cultivation expenses of IWA, we recommend a cultivation duration of 6-8 years for growers. In conclusion, we established a novel multidimensional evaluation method to systematically characterize the quality of Astragali Radix, and provided a new scientific perspective for the artificial cultivation and quality assurance of Astragali Radix.

Simultaneous identification of DNA and RNA pathogens using metagenomic sequencing in cases of severe acute respiratory infection.

Metagenomic next-generation sequencing (mNGS) is a valuable technique for identifying pathogens. However, conventional mNGS requires the separate processing of DNA and RNA genomes, which can be resource- and time-intensive. To mitigate these impediments, we propose a novel method called DNA/RNA cosequencing that aims to enhance the efficiency of pathogen detection. DNA/RNA cosequencing uses reverse transcription of total nucleic acids extracted from samples by using random primers, without removing DNA, and then employs mNGS. We applied this method to 85 cases of severe acute respiratory infections (SARI). Influenza virus was identified in 13 cases (H1N1: seven cases, H3N2: three cases, unclassified influenza type: three cases) and was not detected in the remaining 72 samples. Bacteria were present in all samples. Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii were detected in four influenza-positive samples, suggesting coinfections. The sensitivity and specificity for detecting influenza A virus were 73.33% and 95.92%, respectively. A κ value of 0.726 indicated a high level of concordance between the results of DNA/RNA cosequencing and SARI influenza virus monitoring. DNA/RNA cosequencing enhanced the efficiency of pathogen detection, providing a novel capability to strengthen surveillance and thereby prevent and control infectious disease outbreaks.

Developing rational scale-down simulators for mimicking substrate heterogeneities based on cell lifelines in industrial-scale bioreactors.

The influence of extracellular variations on the cellular metabolism and thereby the process performance at large-scale can be evaluated using the so-called scale-down simulators. Nevertheless, the major challenge is to design an appropriate scale-down simulator, which can accurately mimic the cell lifelines that record the flow paths and experiences of cells circulating in large-scale bioreactors. To address this, a dedicated SDSA (scale-down simulator application) was purposedly developed on the basis of black box model and process reaction model established for Penicillium chrysogenum strain as well as cell lifelines or trajectories information in an industrial-scale fermentor. Guided by the SDSA, the industrial-relevant metabolic regimes for substrate availability, i.e., excess, limitation and starvation, were successfully reproduced at laboratory-scale three-compartment scale-down (SD) system. In addition, such SDSA can also display individual process dynamics in each compartment, and demonstrate how individual factors influence the entire bioprocess performance, thus serving both educational and research purposes.

Acidithiobacillus species drive the formation of ferric-silica cemented microstructure: Insights into early hardpan development for mine site rehabilitation.

Hardpan-based profiles naturally formed under semi-arid climatic conditions have substantial potential in rehabilitating sulfidic tailings, resulting from their aggregation microstructure regulated by Fe-Si cements. Nevertheless, eco-engineered approaches for accelerating the formation of complex cementation structure remain unclear. The present study aims to investigate the microbial functions of extremophiles on mineral dissolution, oxidation, and aggregation (cementation) through a microcosm experiment containing pyrites and polysilicates, of which are dominant components in typical sulfidic tailings. Microspectroscopic analysis revealed that pyrite was rapidly dissolved and massive microbial corrosion pits were displayed on pyrite surfaces. Synchrotron-based X-ray absorption spectroscopy demonstrated that approximately 30 % pyrites were oxidized to jarosite-like (ca. 14 %) and ferrihydrite-like minerals (ca. 16 %) in talc group, leading to the formation of secondary Fe precipitates. The Si ions co-dissolved from polysilicates may be embedded into secondary Fe precipitates, while these clustered Fe-Si precipitates displayed distinct morphology (e.g., "circular" shaped in the talc group, "fine-grained" shaped in the chlorite group, and "donut" shaped in the muscovite group). Moreover, the precipitates could join together and act as cementing agents aggregating mineral particles together, forming macroaggregates in talc and chlorite groups. The present findings revealed critical microbial functions on accelerating mineral dissolution, oxidation, and aggregation of pyrite and various silicates, which provided the eco-engineered feasibility of hardpan-based technology for mine site rehabilitation.

[Nature-effect transformation mechanism of mulberry leaves and silkworm droppings based on chemical composition analysis].

Starting with the relationship between mulberry leaves and silkworm droppings as food and metabolites, this study systematically compared the chemical components, screened out differential components, and quantitatively analyzed the main differential components based on ultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS) and UPLC-Q-TRAP-MS combined with principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA). Moreover, the in vitro enzymatic transformation of the representative differential components was studied. The results showed that(1) 95 components were identified from mulberry leaves and silkworm droppings, among which 27 components only exist in mulberry leaves and 8 components in silkworm droppings. The main differential components were flavonoid glycosides and chlorogenic acids.(2) Nineteen components with significant difference were quantitatively analyzed, and the components with significant differences and high content were neochlorogenic acid, chlorogenic acid, and rutin.(3) The crude protease in the mid-gut of silkworm significantly metabolized neochlorogenic acid and chlorogenic acid, which may be an important reason for the efficacy change in mulberry leaves and silkworm droppings. This study lays a scientific foundation for the development, utilization, and quality control of mulberry leaves and silkworm droppings. It provides references for clarifying the possible material basis and mechanism of the pungent-cool and dispersing nature of mulberry leaves transforming into the pungent-warm and dampness-resolving nature of silkworm droppings, and offers a new idea for the study of nature-effect transformation mechanism of traditional Chinese medicine.

A Rational Design of Metal-Organic Framework Nanozyme with High-Performance Copper Active Centers for Alleviating Chemical Corneal Burns.

Metal-organic frameworks (MOFs) have attracted significant research interest in biomimetic catalysis. However, the modulation of the activity of MOFs by precisely tuning the coordination of metal nodes is still a significant challenge. Inspired by metalloenzymes with well-defined coordination structures, a series of MOFs containing halogen-coordinated copper nodes (Cu-X MOFs, X = Cl, Br, I) are employed to elucidate their structure-activity relationship. Intriguingly, experimental and theoretical results strongly support that precisely tuning the coordination of halogen atoms directly regulates the enzyme-like activities of Cu-X MOFs by influencing the spatial configuration and electronic structure of the Cu active center. The optimal Cu-Cl MOF exhibits excellent superoxide dismutase-like activity with a specific activity one order of magnitude higher than the reported Cu-based nanozymes. More importantly, by performing enzyme-mimicking catalysis, the Cu-Cl MOF nanozyme can significantly scavenge reactive oxygen species and alleviate oxidative stress, thus effectively relieving ocular chemical burns. Mechanistically, the antioxidant and antiapoptotic properties of Cu-Cl MOF are achieved by regulating the NRF2 and JNK or P38 MAPK pathways. Our work provides a novel way to refine MOF nanozymes by directly engineering the coordination microenvironment and, more significantly, demonstrating their potential therapeutic effect in ophthalmic disease.

N6 - Methyladenosine defines a new checkpoint in γδ T cell development.

T cells, which are derived from hematopoietic stem cells (HSCs), are the most important components of adaptive immune system. Based on the expression of αß and γδ receptors, T cells are mainly divided into αß and γδ T cells. In the thymus, they share common progenitor cells, while undergoing a series of well-characterized and different developmental processes. N6 -Methyladenosine (m6 A), one of the most abundant modifications in mRNAs, plays critical roles in cell development and maintenance of function. Recently, we have demonstrated that the depletion of m6 A demethylase ALKBH5 in lymphocytes specifically induces an expansion of γδ T cells through the regulation of Jag1/Notch2 signaling, but not αß T cells, indicating a checkpoint role of ALKBH5 and m6 A modification in the early development of γδ T cells. Based on previous studies, many key pathway molecules, which exert dominant roles in γδ T cell fate determination, have been identified as the targets regulated by m6 A modification. In this review, we mainly summarize the potential regulation between m6 A modification and these key signaling molecules in the γδ T cell lineage commitment, to provide new perspectives in the checkpoint of γδ T cell development.

Levocarnitine regulates the growth of angiotensin II-induced myocardial fibrosis cells via TIMP-1.

This study aimed to explore the effects of tissue inhibitor of metalloproteinases-1 (TIMP-1) on levocarnitine (LC)-mediated regulation of angiotensin II (AngII)-induced myocardial fibrosis (MF) and its underlying mechanisms. H9C2 cells were treated with AngII for 24 h to induce fibrosis. The cells were then treated with LC or transfected with TIMP-1-OE plasmid/si­TIMP-1. Cell apoptosis, viability, migration, and related gene expression were analyzed. AngII treatment significantly upregulated Axl, α-SMA, and MMP3 expression (P < 0.05) and downregulated STAT4 and TIMP1 expression (P < 0.05) relative to the control levels. After transfection, cells with TIMP-1 overexpression/knockdown were successfully established. Compared with that of the control, AngII significantly inhibited cell viability and cell migration while promoting cell apoptosis (P < 0.05). LC and TIMP-1-OE transfection further suppressed cell viability and migration induced by Ang II and upregulated apoptosis, whereas si-TIMP-1 had the opposite effect. Furthermore, LC and TIMP-1-OE transfection downregulated Axl, AT1R, α-SMA, collagen III, Bcl-2, and MMP3 expression caused by AngII and upregulated caspase 3, p53, and STAT4 expression, whereas si-TIMP-1 had the opposite effect. TIMP-1 is therefore a potential therapeutic target for delaying MF progression.

Screening and Analysis of Serum Protein Biomarkers Infected by Coronavirus Disease 2019 (COVID-19).

Coronavirus disease 2019 (COVID-19) has spread widely around the world, and in-depth research on COVID-19 is necessary for biomarkers and target drug discovery. This analysis collected serum from six COVID-19-infected patients and six healthy people. The protein changes in the infected and healthy control serum samples were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The differential protein signature in both groups was retrieved and analyzed by the Kyoto Encyclopedia of Gene and Genomes (KEGG), Gene ontology, COG/KOG, protein-protein interaction, and protein domain interactions tools. We shortlisted 24 differentially expressed proteins between both groups. Ten genes were significantly up-regulated in the infection group, and fourteen genes were significantly down-regulated. The GO and KEGG pathway enrichment analysis suggested that the chromosomal part and chromosome were the most enriched items. The oxytocin signaling pathway was the most enriched item of KEGG analysis. The netrin module (non-TIMP type) was the most enriched protein domain in this study. Functional analysis of S100A9, PIGR, C4B, IL-6R, IGLV3-19, IGLV3-1, and IGLV5-45 revealed that SARS-CoV-2 was closely related to immune response.

Detection by environmental surveillance and genomic characterization of H5N8 highly pathogenic avian influenza virus from a poultry meat market in Beijing, China, 2021-22.

Since 2010 the year when it was first reported in domestic ducks in China, highly pathogenic avian influenza (HPAI) H5N8 has caused several outbreaks in different countries. The first outbreak wave was documented in South Korea and Japan in 2014 and the second wave was reported in Asian and European countries in 2016. More importantly, zoonotic infection was first reported in poultry workers in Russia in 2021. Therefore, active surveillance on H5N8 is highly needed. Surveillance on live birds instead of environmental samples is commonly reported. In the present study, we reported detection and genomic characterization of an environmental H5N8 strain in environmental samples of Tongzhou poultry meat markets in Beijing on a monthly basis from March 2021 to February 2022. Among 600 samples screened, a total of 27 samples were positive for influenza A virus with 4 typed as H5N8, 10 H7N9, and 13 H9N2. Whole genome sequencing and analysis of one duck neck with a higher virus load showed that A/Environment sample/Beijing/TZ001/20 21 (H5N8) clade 2.3.4.4b had the highest identities (over 99%) in all eight segments with H5N8 isolates from wild birds swan and tern in Hubei and had polybasic cleavage site PLREKRRKR/G, characteristic of a HPAI virus. Overall, our data indicate that HPAI H5N8 virus is still circulating in domestic ducks in China in the study period and continued surveillance in domestic and wild birds is needed to control H5N8.

An Updated Review on SARS-CoV-2 Infection in Animals.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has lasted for two years and caused millions of infections and deaths in humans. Although the origin of SARS-CoV-2 infection in humans remains unknown, infection in animals has been frequently reported in varieties of animals all over the world. Both experimental and natural infections of SARS-CoV-2 in different animal species provide useful information on viral host range and pathogenicity. As the pandemic continues to evolve, SARS-CoV-2 infection in animals will be expanding. In this review, we summarized SARS-CoV-2 testing and infection in animals as well as SARS-CoV-2 strains and transmission in animals. Current data showed that at least 18 different animal species tested positive for SARS-CoV-2. These 18 animal species belong to pet, captive, farmed, and wild animals. Fifteen of the eighteen animal species were known to be positive for the Delta variant and ten animal species were infected with two different types of variants. Human-to-animal, animal-to-animal, and animal-to-human transmission events were suggested in different outbreaks involved in animal infection with SARS-CoV-2. Continued testing, immunization, and surveillance are warranted.

Using Wool Keratin Derived Metallo-Nanozymes as a Robust Antioxidant Catalyst to Scavenge Reactive Oxygen Species Generated by Smoking.

Self-assembled nanostructures based on biomolecules (e.g., proteins and amino acids) and metal ions have promising applications in mimicking the nanostructure, properties, and functions of natural enzymes. Herein, a metal ion-mediated self-assembly method for constructing catalytically active Cu-wool-keratin (CuWK) two-dimensional nanozymes is presented. Specifically, by introducing copper ions as abiological cofactors, WK can serve as a protein scaffold to design and create Cu catalytic sites. The optimized hybrids with Cu-WK coordination framework exhibit significant superoxide dismutases-like activity, catalase-like activity, and hydroxyl radical scavenging ability. These combined antioxidant activities make CuWK a robust nanozyme to effectively remove various reactive oxygen species (ROS). In this work, the as-prepared CuWK as a new additive can be integrated into a cigarette filter system to effectively remove the produced ROS from the burning of tobacco. More importantly, the CuWK nanozymes as a critical element can be further utilized to construct a recycling cigarette holder. Therefore, the present work shows that nanozymes with advanced catalytic capabilities can be constructed by self-assembly of metal ions and proteins, thus facilitating the rational design and discovery of this kind of artificial metalloenzymes.

Phytochromes A and B Mediate Light Stabilization of BIN2 to Regulate Brassinosteroid Signaling and Photomorphogenesis in Arabidopsis.

Phytochromes A and B (phyA and phyB) are the far-red and red lights photoreceptors mediating many light responses in Arabidopsis thaliana. Brassinosteroid (BR) is a pivotal phytohormone regulating a variety of plant developmental processes including photomorphogenesis. It is known that phyB interacts with BES1 to inhibit its DNA-binding activity and repress BR signaling. Here, we show that far-red and red lights modulate BR signaling through phyA and phyB regulation of the stability of BIN2, a glycogen synthase kinase 3 (GSK3)-like kinase that phosphorylates BES1/BZR1 to inhibit BR signaling. The BIN2 gain-of-function mutant bin2-1 displays an enhanced photomorphogenic phenotype in both far-red and red lights. phyA-enhanced accumulation of BIN2 promotes the phosphorylation of BES1 in far-red light. BIN2 acts genetically downstream from PHYA to regulate photomorphogenesis under far-red light. Both phyA and phyB interact directly with BIN2, which may promote the interaction of BIN2 with BES1 and induce the phosphorylation of BES1. Our results suggest that far-red and red lights inhibit BR signaling through phyA and phyB stabilization of BIN2 and promotion of BES1 phosphorylation, which defines a new layer of the regulatory mechanism that allows plants to coordinate light and BR signaling pathways to optimize photomorphogenesis.

Changes in Oxygen Availability during Glucose-Limited Chemostat Cultivations of Penicillium chrysogenum Lead to Rapid Metabolite, Flux and Productivity Responses.

Bioreactor scale-up from the laboratory scale to the industrial scale has always been a pivotal step in bioprocess development. However, the transition of a bioeconomy from innovation to commercialization is often hampered by performance loss in titer, rate and yield. These are often ascribed to temporal variations of substrate and dissolved oxygen (for instance) in the environment, experienced by microorganisms at the industrial scale. Oscillations in dissolved oxygen (DO) concentration are not uncommon. Furthermore, these fluctuations can be exacerbated with poor mixing and mass transfer limitations, especially in fermentations with filamentous fungus as the microbial cell factory. In this work, the response of glucose-limited chemostat cultures of an industrial Penicillium chrysogenum strain to different dissolved oxygen levels was assessed under both DO shift-down (60% → 20%, 10% and 5%) and DO ramp-down (60% → 0% in 24 h) conditions. Collectively, the results revealed that the penicillin productivity decreased as the DO level dropped down below 20%, while the byproducts, e.g., 6-oxopiperidine-2-carboxylic acid (OPC) and 6-aminopenicillanic acid (6APA), accumulated. Following DO ramp-down, penicillin productivity under DO shift-up experiments returned to its maximum value in 60 h when the DO was reset to 60%. The result showed that a higher cytosolic redox status, indicated by NADH/NAD+, was observed in the presence of insufficient oxygen supply. Consistent with this, flux balance analysis indicated that the flux through the glyoxylate shunt was increased by a factor of 50 at a DO value of 5% compared to the reference control, favoring the maintenance of redox status. Interestingly, it was observed that, in comparison with the reference control, the penicillin productivity was reduced by 25% at a DO value of 5% under steady state conditions. Only a 14% reduction in penicillin productivity was observed as the DO level was ramped down to 0. Furthermore, intracellular levels of amino acids were less sensitive to DO levels at DO shift-down relative to DO ramp-down conditions; this difference could be caused by different timescales between turnover rates of amino acid pools (tens of seconds to minutes) and DO switches (hours to days at steady state and minutes to hours at ramp-down). In summary, this study showed that changes in oxygen availability can lead to rapid metabolite, flux and productivity responses, and dynamic DO perturbations could provide insight into understanding of metabolic responses in large-scale bioreactors.

Discriminant Geometrical and Statistical Alignment With Density Peaks for Domain Adaptation.

Unsupervised domain adaptation (DA) aims to perform classification tasks on the target domain by leveraging rich labeled data in the existing source domain. The key insight of DA is to reduce domain divergence by learning domain-invariant features or transferable instances. Despite its rapid development, there still exist several challenges to explore. At the feature level, aligning both domains only in a single way (i.e., geometrical or statistical) has limited ability to reduce the domain divergence. At the instance level, interfering instances often obstruct learning a discriminant subspace when performing the geometrical alignment. At the classifier level, only minimizing the empirical risk on the source domain may result in a negative transfer. To tackle these challenges, this article proposes a novel DA method, called discriminant geometrical and statistical alignment (DGSA). DGSA first aligns the geometrical structure of both domains by projecting original space into a Grassmann manifold, then matches the statistical distributions of both domains by minimizing their maximum mean discrepancy on the manifold. In the former step, DGSA only selects the density peaks to learn the Grassmann manifold and so to reduce the influences of interfering instances. In addition, DGSA exploits the high-confidence soft labels of target landmarks to learn a more discriminant manifold. In the latter step, a structural risk minimization (SRM) classifier is learned to match the distributions (both marginal and conditional) and predict the target labels at the same time. Extensive experiments on objection recognition and human activity recognition tasks demonstrate that DGSA can achieve better performance than the comparison methods.

Attract-Repel Encoder: Learning Anomaly Representation Away From Landmarks.

Anomaly detection (AD) has attracted great interest in the data mining community. With the development of deep learning, various deep autoencoders have been used and modified to solve AD problems due to their efficient data coding and reconstruction mechanisms. However, such methods still suffer challenges when solving some practical AD tasks. On the one hand, an AD dataset may contain diverse normal patterns rather than a universal pattern. Specifically, the normal data usually distribute in multiple clusters; meanwhile, the exact number of clusters is hard to know in practice. On the other hand, most existing autoencoder-based methods focus on encoding normal features but have not considered exploring the characteristics of abnormal data. To tackle these challenges, this article proposes a novel autoencoder-based AD model, the attract-repel encoder (ARE). ARE selects some landmarks in the encoding space to represent the diverse normal patterns. Besides, ARE can adaptively update the landmarks and their quantity during training. Then this article proposes the attract-repel loss (AR loss) function to train ARE. AR loss attracts normal samples to landmarks and repels anomalies away from landmarks so that it can learn both normal and abnormal features. Finally, ARE computes a sample's anomaly score by summing up its reconstruction error and its distance to the landmarks. Moreover, ARE can be trained either semisupervised or unsupervised. This article presents comprehensive experiments to evaluate the effectiveness of our approach.

Arabidopsis cryptochrome 1 undergoes COP1 and LRBs-dependent degradation in response to high blue light.

Arabidopsis cryptochrome 1 (CRY1) is an important blue light photoreceptor that promotes photomorphogenesis under blue light. The blue light photoreceptors CRY2 and phototropin 1, and the red/far-red light photoreceptors phytochromes B and A undergo degradation in response to blue and red light, respectively. This study investigated whether and how CRY1 might undergo degradation in response to high-intensity blue light (HBL). We demonstrated that CRY1 is ubiquitinated and degraded through the 26S proteasome pathway in response to HBL. We found that the E3 ubiquitin ligase constitutive photomorphogenic 1 (COP1) is involved in mediating HBL-induced ubiquitination and degradation of CRY1. We also found that the E3 ubiquitin ligases LRBs physically interact with CRY1 and are also involved in mediating CRY1 ubiquitination and degradation in response to HBL. We further demonstrated that blue-light inhibitor of cryptochromes 1 interacts with CRY1 in a blue-light-dependent manner to inhibit CRY1 dimerization/oligomerization, leading to the repression of HBL-induced degradation of CRY1. Our findings indicate that the regulation of CRY1 stability in HBL is coordinated by COP1 and LRBs, which provides a mechanism by which CRY1 attenuates its own signaling and optimizes photomorphogenesis under HBL.

Corrigendum: Phytochromes A and B mediate light stabilization of BIN2 to regulate brassinosteroid signaling and photomorphogenesis in Arabidopsis.

[This corrects the article DOI: 10.3389/fpls.2022.865019.].