Publications by authors named "Wenhao Wu"

Rice tillering determines grain yield, yet the molecular regulatory network is still limited. In this study, we demonstrated that the transcription factor OsMADS60 promotes the expression of the auxin transporter OsPIN5b to affect auxin distribution and inhibit rice tillering and grain yield. Natural variation was observed in the promoter region of OsMADS60, with its expression level negatively correlated with tiller number and inducible by auxin.

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Single-cell multiomics clustering integrates multiple omics data to analyze cellular heterogeneity and is crucial for uncovering complex biological processes and disease mechanisms. However, existing matched single-cell multiomics clustering methods often neglect the full utilization of intercellular relationships and the interactions and synergy between features from different omics, leading to suboptimal clustering performance. In this paper, we propose a deep collaborative contrastive learning framework for matched single-cell multiomics data clustering, named scMDCL.

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Graph neural networks (GNNs), as a rising star in machine learning, are widely used in relational data models and have achieved outstanding performance in graph tasks. GNN continuously takes inspiration from mature models in other domains such as computer vision and natural language processing to motivate the development of graph algorithms. However, due to the various data structures from different domains, the cross-domain migration of models has to go through a long period of disassembly and reconstruction, which may not yield the desired results.

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Background And Purpose: Using post-treatment methods to predict functional outcomes of acute ischemic stroke (AIS) patients undergoing endovascular thrombectomy (EVT) is crucial in stroke medicine. The National Institute of Health Stroke Scale (NIHSS) score at 24 h has been widely used; however, there is a paucity of data on using earlier NIHSS scores and their association with outcome. In this study, we aimed to investigate the usage of NIHSS at 1-h time window -ultra-early neurological improvement (UENI)- as a surrogate marker associated with the functional outcomes of AIS patients treated with EVT.

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Mammography is the recommended imaging modality for breast cancer screening. Expressions of human epidermal growth factor receptor 2 (HER2), estrogen receptor (ER), and progesterone receptor (PR) are critical to the development of therapeutic strategies for breast cancer. In this study, a deep learning model (CBAM ResNet-18) was developed to predict the expression of these three receptors on mammography without manual segmentation of masses.

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: With the rapid development of the accumulation of large-scale multiomics data sets, integrating various omics data to provide a thorough study from multiple perspectives can significantly provide stronger support for precise treatment of diseases. However, due to the complexity of multiomics data, issues of feature redundancy and noise often do not receive sufficient attention when processing high-dimensional data. Moreover, simple concatenation strategies may overlook the correlations between different omics data, failing to effectively capture the unique information inherent in multiomics data.

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Background: tNGS and mNGS are valuable tools for diagnosing pathogens in lower respiratory tract infections (LRTIs), which subsequently influence treatment strategies. However, the impact of tNGS and mNGS on antimicrobial stewardship in patients with LRTIs remains unclear.

Methods: Patients diagnosed with LRTIs who underwent tNGS or mNGS between June 2021 and January 2024 were included.

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Background: The young onset Tracheal, Bronchus, and Lung Cancer (TBLC) exhibits distinct gene mutations and clinical characteristics. With worsening air pollution, the incidence of young onset TBLC is increasing, resulting in significant economic burdens. The specific epidemiology of the disease burden remains elusive.

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Aeromonas schubertii infections has caused severe economic losses in aquaculture in China. In this study, we first induced enrofloxacin (ENR) resistance in A. schubertii strains and then analyzed the mechanisms of drug resistance using transcriptomics and metabolomics.

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Article Synopsis
  • The separation of benzene and cyclohexane is vital for getting high-purity cyclohexane and is difficult due to their similar boiling points and sizes.
  • A new covalent organic framework, HFPB-TAB-COF, with a specific pore size is developed to enhance the separation of these two compounds using a technique called pore confinement effect.
  • HFPB-TAB-COF shows high selectivity in separating benzene from cyclohexane, achieving over 99% purity in the produced cyclohexane, thus outperforming existing separation materials.
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  • Hypervirulent Klebsiella pneumoniae (hvKp) is a dangerous pathogen linked to severe infections such as gas gangrene and sepsis, often leading to poor outcomes.
  • A case study highlights the isolation of two carbapenem-susceptible hvKp strains from a patient's samples, which were genetically similar and showed strong resistance to antibiotics in biofilm form.
  • The study underscores the strains' high virulence and the importance of careful antibiotic usage and innovative treatments to tackle infections associated with hvKp.
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Background: Delayed diabetic wound healing is one of the clinical difficulties, the main reason is the limited angiogenesis ability. Deferriamine (DFO) is an iron chelating agent that can induce angiogenesis, but its application is limited due to its short half-life. Increasing the load and slow release performance of desferriamine is beneficial to accelerate diabetic wound healing.

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  • Circular RNA (circRNA) plays a key role in gene regulation by interacting with microRNAs (miRNAs), and using accumulated circRNA-miRNA associations can improve prediction models for these interactions.
  • Current prediction models struggle to fully capture complex relationships between circRNAs and miRNAs, necessitating improvements for better accuracy.
  • A new approach called multirelational hypergraph representation learning (MRHRL) enhances predictions by using hypergraphs and a view attention mechanism, and it has shown strong performance in experiments by surpassing existing models.
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Understanding videos, especially aligning them with textual data, presents a significant challenge in computer vision. The advent of vision-language models (VLMs) like CLIP has sparked interest in leveraging their capabilities for enhanced video understanding, showing marked advancements in both performance and efficiency. However, current methods often neglect vital user-generated metadata such as video titles.

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Knowledge of antibiotic desorption from high-temperature biochar is essential for assessing their environmental risks, and for the successful application of biochar to remove antibiotics. In previous studies, irreversible pore deformation, formation of charge-assisted hydrogen bonds or amide bonds were individually proposed to explain the desorption hysteresis of antibiotics on biochars, leading to a debate on hysteresis mechanism. In this study, desorption of sulfamethoxazole (SMX), ciprofloxacin (CFX) and tetracycline (TET) on a wood chip biochar produced at 700 °C (WBC700) and its oxidized product (O-WBC700) was investigated to explore the underlying hysteresis mechanism.

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In this study, the texture formation mechanism of a TA15 titanium alloy under different plane strain compression conditions was investigated by analyzing the slipping, dynamic recrystallization (DRX) and phase transformation behaviors. The results indicated that the basal texture component basically appears under all conditions, since the dominant basal slip makes the C-axis of the α grain rotate to the normal direction (ND, i.e.

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Objectives: KPC-2-producing Pseudomonas aeruginosa high-risk sequence type (ST) 463 is increasingly prevalent in China and poses severe threats to public health. In this study, we aimed to investigate within-host adaptive evolution of this clone during therapy.

Methods: Using nine serial respiratory isolates from a post-lung transplantation patient undergoing multiple antibiotic treatments, we conducted genomic, transcriptomic and phenotypic analyses to uncover the adaptive mechanisms of a KPC-2-producing ST463 P.

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Superhydrophobic porous organic polymers are potential sorbents for volatile organic compounds (VOCs) pollution control by suppressing the competition of water molecules on their surfaces. However, the synthesis of superhydrophobic reagents usually requires large amounts of organic solvents and a long reaction time (≥ 24 h). Herein, a green mechanochemical method was developed to synthesize a superhydrophobic polymer (MSHMP-1) with the advantages of using a small amount of organic solvents (5 mL/g) and a short reaction time (2 h).

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With the advancement of sequencing methodologies, the acquisition of vast amounts of multi-omics data presents a significant opportunity for comprehending the intricate biological mechanisms underlying diseases and achieving precise diagnosis and treatment for complex disorders. However, as diverse omics data are integrated, extracting sample-specific features within each omics modality and exploring potential correlations among different modalities while avoiding mutual interference becomes a critical challenge in multi-omics data integration research. In the context of this study, we proposed a framework that unites specificity-aware GATs and cross-modal attention to integrate different omics data (MOSGAT).

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Article Synopsis
  • The study focuses on a 3D solar evaporator made from balsa wood coated with potassium hydroxide activated carbon (KAC), which enhances water transport height significantly.
  • The KAC-coated evaporator can transport water up to 32 cm and achieves an impressive evaporation rate of 25.3 kg/m²/h under optimal solar conditions.
  • Additionally, the design not only improves water evaporation efficiency but also helps in purifying wastewater by absorbing phenol, indicating its potential for clean water production.
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Background: Breast cancer (BRCA) is one of the most common malignant tumors. The structural maintenance of chromosome (SMC) gene family has been shown to play an important role in human cancers. However, the role of SMC families in BRCA is unclear.

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In the specific use of electromyogram (EMG) driven prosthetics, the user's disability reduces the space available for the electrode array. We propose a framework for EMG decomposition adapted to the condition of a few channels (less than 30 observations), which can elevate the potential of prosthetics in terms of cost and applicability.The new framework contains a peel-off approach, a refining strategy for motor unit (MU) spike train and MU action potential and a re-subtracting strategy to adapt the framework to few channels environments.

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Article Synopsis
  • Recent research has focused on megaplasmids and their role in spreading antimicrobial resistance (AMR), particularly due to advancements in long-read sequencing technologies.
  • Analysis revealed that the majority of identified megaplasmids belong to the IncP-2 type, featuring conserved genetic traits and abundant AMR genes, especially those linked to serious hospital infections.
  • The study proposes that chromids, which can evolve from megaplasmids, might enable quicker genetic adaptations in response to new environments or pressures, highlighting their evolutionary significance.
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Double-walled metal-organic frameworks (MOFs), synthesized using Zn and Co, are potential porous materials for trace benzene adsorption. Aluminum is with low-toxicity and abundance in nature, in comparison with Zn and Co. Therefore, a double-walled Al-based MOF, named as ZJU-520(Al), with large microporous specific surface area of 2235 m g, pore size distribution in the range of 9.

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