76 research outputs found

    A conserved but plant-specific CDK-mediated regulation of DNA replication protein A2 in the precise control of stomatal terminal division

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    The R2R3-MYB transcription factor FOUR LIPS (FLP) controls the stomatal terminal division through transcriptional repression of the cell cycle genes CYCLIN-DEPENDENT KINASE (CDK) B1s (CDKB1s), CDKA; 1, and CYCLIN A2s (CYCA2s). We mutagenized the weak mutant allele flp-1 seeds with ethylmethane sulfonate and screened out a flp-1 suppressor 1 (fsp1) that suppressed the flp-1 stomatal cluster phenotype. FSP1 encodes RPA2a subunit of Replication Protein A (RPA) complexes that play important roles in DNA replication, recombination, and repair. Here, we show that FSP1/RPA2a functions together with CDKB1s and CYCA2s in restricting stomatal precursor proliferation, ensuring the stomatal terminal division and maintaining a normal guard-cell size and DNA content. Furthermore, we provide direct evidence for the existence of an evolutionarily conserved, but plant-specific, CDK-mediated RPA regulatory pathway. Serine-11 and Serine-21 at the N terminus of RPA2a are CDK phosphorylation target residues. The expression of the phosphorylation-mimic variant RPA2a(S11,21/D) partially complemented the defective cell division and DNA damage hypersensitivity in cdkb1;1 1;2 mutants. Thus, our study provides a mechanistic understanding of the CDK-mediated phosphorylation of RPA in the precise control of cell cycle and DNA repair in plants

    LOWA: Localize Objects in the Wild with Attributes

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    We present LOWA, a novel method for localizing objects with attributes effectively in the wild. It aims to address the insufficiency of current open-vocabulary object detectors, which are limited by the lack of instance-level attribute classification and rare class names. To train LOWA, we propose a hybrid vision-language training strategy to learn object detection and recognition with class names as well as attribute information. With LOWA, users can not only detect objects with class names, but also able to localize objects by attributes. LOWA is built on top of a two-tower vision-language architecture and consists of a standard vision transformer as the image encoder and a similar transformer as the text encoder. To learn the alignment between visual and text inputs at the instance level, we train LOWA with three training steps: object-level training, attribute-aware learning, and free-text joint training of objects and attributes. This hybrid training strategy first ensures correct object detection, then incorporates instance-level attribute information, and finally balances the object class and attribute sensitivity. We evaluate our model performance of attribute classification and attribute localization on the Open-Vocabulary Attribute Detection (OVAD) benchmark and the Visual Attributes in the Wild (VAW) dataset, and experiments indicate strong zero-shot performance. Ablation studies additionally demonstrate the effectiveness of each training step of our approach

    Evaluation and Mitigation of Agnosia in Multimodal Large Language Models

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    While Multimodal Large Language Models (MLLMs) are widely used for a variety of vision-language tasks, one observation is that they sometimes misinterpret visual inputs or fail to follow textual instructions even in straightforward cases, leading to irrelevant responses, mistakes, and ungrounded claims. This observation is analogous to a phenomenon in neuropsychology known as Agnosia, an inability to correctly process sensory modalities and recognize things (e.g., objects, colors, relations). In our study, we adapt this similar concept to define "agnosia in MLLMs", and our goal is to comprehensively evaluate and mitigate such agnosia in MLLMs. Inspired by the diagnosis and treatment process in neuropsychology, we propose a novel framework EMMA (Evaluation and Mitigation of Multimodal Agnosia). In EMMA, we develop an evaluation module that automatically creates fine-grained and diverse visual question answering examples to assess the extent of agnosia in MLLMs comprehensively. We also develop a mitigation module to reduce agnosia in MLLMs through multimodal instruction tuning on fine-grained conversations. To verify the effectiveness of our framework, we evaluate and analyze agnosia in seven state-of-the-art MLLMs using 9K test samples. The results reveal that most of them exhibit agnosia across various aspects and degrees. We further develop a fine-grained instruction set and tune MLLMs to mitigate agnosia, which led to notable improvement in accuracy

    A Brewster route to Cherenkov detectors.

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    Cherenkov detectors enable a valuable tool to identify high-energy particles. However, their sensitivity and momentum coverage are limited by the refractive index of host materials. Especially, identifying particles with energy above multiple gigaelectronvolts requires host materials with a near-unity refractive index, which are limited to bulky gas chambers. Overcoming this fundamental material limit is important for future particle detectors yet remains a long-standing challenge. Here, we propose a different paradigm for Cherenkov detectors that utilizes the broadband angular filter made from stacks of variable one-dimensional photonic crystals. Owing to the Brewster effect, the angular filter is transparent only to Cherenkov photons from a precise incident angle. Particle identification is achieved by mapping each Cherenkov angle to the peak-intensity position of transmitted photons in the detection plane. Such angular filtering effect, although decreases the photon number collected in the detection plane, enables the realization of a non-dispersive pseudo refractive index over the entire visible spectrum. Moreover, the pseudo refractive index can be flexibly designed to different values close to unity. Our angular-selective Brewster paradigm offers a feasible solution to implement compact and highly sensitive Cherenkov detectors especially in beam lines with a small angular divergence using regular dielectrics

    Adjuvant Chemotherapy Versus Adjuvant Concurrent Chemoradiotherapy After Radical Surgery for Early-Stage Cervical Cancer: A Randomized, Non-Inferiority, Multicenter Trial

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    We conducted a prospective study to assess the non-inferiority of adjuvant chemotherapy alone versus adjuvant concurrent chemoradiotherapy (CCRT) as an alternative strategy for patients with early-stage (FIGO 2009 stage IB-IIA) cervical cancer having risk factors after surgery. The condition was assessed in terms of prognosis, adverse effects, and quality of life. This randomized trial involved nine centers across China. Eligible patients were randomized to receive adjuvant chemotherapy or CCRT after surgery. The primary end-point was progression-free survival (PFS). From December 2012 to December 2014, 337 patients were subjected to randomization. Final analysis included 329 patients, including 165 in the adjuvant chemotherapy group and 164 in the adjuvant CCRT group. The median follow-up was 72.1 months. The three-year PFS rates were both 91.9%, and the five-year OS was 90.6% versus 90.0% in adjuvant chemotherapy and CCRT groups, respectively. No significant differences were observed in the PFS or OS between groups. The adjusted HR for PFS was 0.854 (95% confidence interval 0.415-1.757; P = 0.667) favoring adjuvant chemotherapy, excluding the predefined non-inferiority boundary of 1.9. The chemotherapy group showed a tendency toward good quality of life. In comparison with post-operative adjuvant CCRT, adjuvant chemotherapy treatment showed non-inferior efficacy in patients with early-stage cervical cancer having pathological risk factors. Adjuvant chemotherapy alone is a favorable alternative post-operative treatment

    Exploiting tertiary lymphoid structures gene signature to evaluate tumor microenvironment infiltration and immunotherapy response in colorectal cancer

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    BackgroundTertiary lymphoid structures (TLS) is a particular component of tumor microenvironment (TME). However, its biological mechanisms in colorectal cancer (CRC) have not yet been understood. We desired to reveal the TLS gene signature in CRC and evaluate its role in prognosis and immunotherapy response.MethodsThe data was sourced from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Based on TLS-related genes (TRGs), the TLS related subclusters were identified through unsupervised clustering. The TME between subclusters were evaluated by CIBERSORT and xCell. Subsequently, developing a risk model and conducting external validation. Integrating risk score and clinical characteristics to create a comprehensive nomogram. Further analyses were conducted to screen TLS-related hub genes and explore the relationship between hub genes, TME, and biological processes, using random forest analysis, enrichment and variation analysis, and competing endogenous RNA (ceRNA) network analysis. Multiple immunofluorescence (mIF) and immunohistochemistry (IHC) were employed to characterize the existence of TLS and the expression of hub gene.ResultsTwo subclusters that enriched or depleted in TLS were identified. The two subclusters had distinct prognoses, clinical characteristics, and tumor immune infiltration. We established a TLS-related prognostic risk model including 14 genes and validated its predictive power in two external datasets. The model’s AUC values for 1-, 3-, and 5-year overall survival (OS) were 0.704, 0.737, and 0.746. The low-risk group had a superior survival rate, more abundant infiltration of immune cells, lower tumor immune dysfunction and exclusion (TIDE) score, and exhibited better immunotherapy efficacy. In addition, we selected the top important features within the model: VSIG4, SELL and PRRX1. Enrichment analysis showed that the hub genes significantly affected signaling pathways related to TLS and tumor progression. The ceRNA network: PRRX1-miRNA (hsa-miR-20a-5p, hsa-miR-485–5p) -lncRNA has been discovered. Finally, IHC and mIF results confirmed that the expression level of PRRX1 was markedly elevated in the TLS- CRC group.ConclusionWe conducted a study to thoroughly describe TLS gene signature in CRC. The TLS-related risk model was applicable for prognostic prediction and assessment of immunotherapy efficacy. The TLS-hub gene PRRX1, which had the potential to function as an immunomodulatory factor of TLS, could be a therapeutic target for CRC

    Organ-specific effects of brassinosteroids on stomatal production coordinate with the action of TOO MANY MOUTHS

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    In Arabidopsis, stomatal development initiates after protodermal cells acquire stomatal lineage cell fate. Stomata or their precursors communicate with their neighbor epidermal cells to ensure the one cell spacing rule. The signals from EPF/EPFL peptide ligands received by TOO MANY MOUTHS (TMM) and ERECTA-family receptors are supposed to be transduced by YODA MAPK cascade. A basic helix-loop-helix transcription factor SPEECHLESS (SPCH) is another key regulator of stomatal cell fate determination and asymmetric entry divisions, and SPCH activity is regulated by YODA MAPK cascade. Brassinosteroid (BR) signaling, one of the most well characterized signal transduction pathways in plants, contributes to the control of stomatal production. But opposite organ-specific effects of BR on stomatal production were reported. Here we confirm that stomatal production in hypocotyls is controlled by BR levels. YODA and CYCD4 are not essential for BR stomata-promoting function. Furthermore, we found that BR could confer tmm hypocotyls clustered stomatal phenotype, indicating that the BR organ-specific effects on stomatal production might coordinate with the TMM organ-specific actions

    The Effect of Ultraviolet Aging Duration on the Rheological Properties of Sasobit/SBS/Nano-TiO2-Modified Asphalt Binder

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    In recent years, nanoparticles have been introduced into warm-mix-modified asphalt to improve asphalt performance after sustaining ultraviolet (UV) aging, yet the evaluation of aging performance is often a descriptive characterization of rheological properties. This study extends rheological characterization with viscoelastic mechanical modeling to evaluate resistance to UV aging using Sasobit and SBS compound-modified binder blended with nano-titanium dioxide (TiO2). The extended method comprises characterizations using several rheological properties and a viscoelastic mechanical model, named the 2S2P1D model, on modified asphalt after 3 days, 6 days and 9 days of ultraviolet (UV) aging. The rheological properties of the UV-aged binders were tested at high and medium temperatures in terms of viscosity, complex modulus, phase angle and fatigue factor. Rheological test results showed that nanoparticles generally had no apparent effect on the complex modulus of aged binders regardless of UV aging times. However, the aged binder with nanoparticles showed better fatigue resistance than aged binders without nanoparticles after 3 days of UV aging. As an extension, the black space diagram and 2S2P1D model were used to investigate the viscoelastic properties of these aged binders. The k and h values, as important model parameters, were almost the same and less than one for all UV-aged binders. All investigated aged asphalt binders showed characteristics of a viscoelastic solid in terms of the master curves of the complex modulus and phase angle, and the master curves of the phase angle for all UV-aged binders did not meet the time–temperature equivalence. Moreover, these observations from the 2S2P1D model revealed that aging durations did not affect the viscoelastic mechanical characteristics of warm mix asphalt in this study. The method adopted in this study may promote a comprehensive evaluation of asphalt properties after UV aging, especially considering the viscoelastic mechanical performance

    Organ-specific effects of brassinosteroids on stomatal production coordinate with the action of TOO MANY MOUTHS

    No full text
    In Arabidopsis, stomatal development initiates after protodermal cells acquire stomatal lineage cell fate. Stomata or their precursors communicate with their neighbor epidermal cells to ensure the one cell spacing rule. The signals from EPF/EPFL peptide ligands received by TOO MANY MOUTHS (TMM) and ERECTA-family receptors are supposed to be transduced by YODA MAPK cascade. A basic helix-loop-helix transcription factor SPEECHLESS (SPCH) is another key regulator of stomatal cell fate determination and asymmetric entry divisions, and SPCH activity is regulated by YODA MAPK cascade. Brassinosteroid (BR) signaling, one of the most well characterized signal transduction pathways in plants, contributes to the control of stomatal production. But opposite organ-specific effects of BR on stomatal production were reported. Here we confirm that stomatal production in hypocotyls is controlled by BR levels. YODA and CYCD4 are not essential for BR stomata-promoting function. Furthermore, we found that BR could confer tmm hypocotyls clustered stomatal phenotype, indicating that the BR organ-specific effects on stomatal production might coordinate with the TMM organ-specific actions

    Fault Detection in Active Magnetic Bearings Using Digital Twin Technology

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    Active magnetic bearings (AMBs) are widely used in different industries to offer non-contact and high-velocity rotational support. The AMB is prone to failures, which may result in system instability and decreased performance. The efficacy and reliability of magnetic bearings can be significantly affected by failures in the sensor and control systems, leading to system imbalance and possible damage. A digital twin is an advanced technology that has been increasingly used in different industrial fields. It allows for the creation and real-time monitoring of virtual replicas of physical systems. This paper proposes a novel method for fault detection of Active Magnetic Bearings (AMBs) using digital twin technology and a neural network. The digital twin model serves as a virtual representation that accurately replicates the actual AMB system’s efficiency and features, allowing continuous real-time monitoring and detection of faults. The conventional neural network (CNN) is used as the primary tool for identifying faults in the Active Magnetic Bearing (AMB) within a digital twin model. Experiments proved the effectiveness and robustness of the suggested approach method to fault detection in the AMB
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