The STAR family of proteins links signaling pathways to various aspects of post-transcriptional regulation and processing of RNAs. Sam68 belongs to this class of heteronuclear ribonucleoprotein particle K (hnRNP K) homology (KH) single domain-cont...
Hepatic glucose production (HGP) is an important component of glucose homeostasis, and deregulated HGP, particularly through gluconeogenesis, contributes to hyperglycemia and pathology of type-2 diabetes (T2D). It has been shown that the gluconeogeni...
The most serious aspect of neoplastic disease is the spread of cancer cells to secondary sites. Skeletal metastases can escape detection long after treatment of the primary tumour and follow-up. Bone tissue is a breeding ground for many types of canc...
Background and objective: Polycystic ovary syndrome (PCOS) is a complex metabolic disorder associated with ovulatory dysfunction, hyperandrogenism, obesity, and insulin resistance, which leads to subfertility. PCOS is the most frequent metabolic diso...
Cancer cells frequently exhibit dysregulation of the DNA damage response (DDR), genomic instability, and altered RNA metabolism. Recent genome-wide studies have strongly suggested an interaction between the pathways involved in the cellular response...
O-GlcNAcylation is a reversible and dynamic post-translational protein modification catalyzed by O-GlcNAc transferase (OGT). Despite the reported association of O-GlcNAcylation with cancer metastasis, the O-GlcNAc proteome profile for cancer aggressi...
Tandem SAM-II/SAM-V riboswitch belongs to a class of riboswitches found in the marine bacterium ‘Candidatus Pelagibacter ubique’. Previous studies have demonstrated that these riboswitches have the potential for digital modulation of gene...
Oncogenic metadherin is a key contributor to tumourigenesis with metadherin expression and cytoplasmic localisation previously linked to poor survival. A number of reports have shown metadherin localises specifically to nuclear speckles known to be r...
Recently, SASH1 has emerged as a novel protein interactor of a few Eph tyrosine kinase receptors like EphA2. These interactions involve the first N-terminal Sam (sterile alpha motif) domain of SASH1 (SASH1-Sam1) and the Sam domain of Eph receptors. C...
Object segmentation, a key type of image segmentation, focuses on detecting and delineating individual objects within an image, essential for applications like robotic vision and augmented reality. Despite advancements in deep learning improving obje...
Among the diverse protein binding modules, Sam (Sterile alpha motif) domains attract attention due to their versatility. They are present in different organisms and play many functions in physiological and pathological processes by binding multiple p...
The Segment Anything Model (SAM), a foundational vision model, struggles with fully automatic segmentation of specific objects. Its “segment everything” mode, reliant on a grid-based prompt strategy, suffers from localization blindness an...
Landslides are common hazardous geological events, and accurate and efficient landslide identification methods are important for hazard assessment and post-disaster response to geological disasters. Deep learning (DL) methods based on remote sensing...
Accurate segmentation of brain vessels is critical for diagnosing cerebral stroke, yet existing AI-based methods struggle with challenges such as small vessel segmentation and class imbalance. To address this, our study proposes a novel 2D segmentati...
S-Adenosyl-L-methionine (SAM) is a central cofactor in cellular methylation, donating methyl groups to a wide range of biological substrates. SAM analogues are promising tools for selective modulation of methyltransferase activity. Here, we investiga...
The complexity of field environments poses significant challenges for the segmentation of cotton top leaves, a critical step for apical bud localization in intelligent topping systems. Conventional segmentation models typically rely on large annotate...
Road extraction from high-resolution remote sensing images (HRSIs) provides critical support for downstream tasks such as autonomous driving path planning and urban planning. Although deep learning-based pixel-level segmentation methods have achieved...
Road object segmentation is crucial for autonomous driving, as it enables vehicles to perceive their surroundings. While deep learning models show promise, their generalization across diverse road conditions, weather variations, and lighting changes...
Recent advances in foundation models have enabled strong zero-shot performance across vision tasks, yet their effectiveness for fine-grained domains such as food image segmentation remains underexplored. This study investigates the zero-shot capabili...
The most devastating abiotic factors worldwide are drought and salinity, causing severe bottlenecks in the agricultural sector. To acclimatize to these harsh ecological conditions, plants have developed complex molecular mechanisms involving diverse...
In eukaryotes, the Dph1•Dph2 dimer is a non-canonical radical SAM enzyme. Using iron-sulfur (FeS) clusters, it cleaves the cosubstrate S-adenosyl-methionine (SAM) to form a 3-amino-3-carboxy-propyl (ACP) radical for the synthesis of diphthamide....
Camouflaged Object Detection (COD) aims to segment objects that are highly integrated with their background, presenting significant challenges such as low contrast, complex textures, and blurred boundaries. Existing deep learning methods often strugg...
Riboswitches regulate gene expression through intricate dynamic conformational transitions, with divalent cation Mg2+ and their ligands playing pivotal roles in this process. The dynamic structural mechanism by which the S-adenosyl-L-methionine (SAM)...
Medical image segmentation, driven by the intrinsic fractal characteristics of biological patterns, plays a crucial role in medical image analysis. Recently, universal image segmentation, which aims to build models that generalize robustly to unseen...
Wheat is one of the world’s essential crops, and the presence of foliar diseases significantly affects both the yield and quality of wheat. Accurate identification of wheat leaf diseases is crucial. However, traditional segmentation models face...
The Sam (Sterile alpha motif) domain of the lipid phosphatase Ship2 (Ship2-Sam) is engaged by the Sam domain of the receptor tyrosine kinase EphA2 (EphA2-Sam) and, this interaction is principally linked to procancer effects. Peptides able to hinder t...
SAM domains are crucial mediators of diverse interactions, including those important for tumorigenesis or metastasis of cancers, and thus SAM domains can be attractive targets for developing cancer therapies. This review aims to explore the literatur...
Semantic segmentation of high-resolution remote sensing imagery is a critical technology for the intelligent interpretation of sensor data, supporting automated environmental monitoring and urban sensing systems. However, processing data from dense u...
The lipid phosphatase Ship2 interacts with the EphA2 receptor by forming a heterotypic Sam (sterile alpha motif)–Sam complex. Ship2 works as a negative regulator of receptor endocytosis and consequent degradation, and anti-oncogenic effects in...
The Bifidobacterium bifidum SAM-VI riboswitch undergoes dynamic conformational changes that modulate downstream gene expression. Traditional structural methods such as crystallography capture the bound conformation at high resolution, and additional...
The self-assembled monolayer (SAM) is the most common organic assembly utilized for the formation of the monolayers of alkane-thiolates on gold electrode, resulting in a wide range of applications for the modified SAM on gold in various research area...
Change detection is a pivotal task in remote sensing information extraction, and leveraging the representation capabilities of large models has emerged as a promising direction in recent research. However, existing large-model-based change detection...
The reliable characterization of fabric anisotropy in concrete aggregates is critical for understanding the mechanical behavior and durability of concrete. The accurate segmentation of aggregates is essential for anisotropy assessment. However, conve...
Checking the distance between aircraft fire detection lines is a crucial task in the conformity inspection process of civil aircraft manufacturing. Currently, this task is mainly performed manually, which is inefficient and prone to errors and omissi...
Fluorescent self assembled monolayers (SAMs) on glass were previouslydeveloped in our group as new sensing materials for metal ions. These fluorescent SAMs arecomprised by fluorophores and small molecules sequentially deposited on a monolayer onglass...
Accurate shade matching is essential in restorative and prosthetic dentistry yet remains difficult due to subjectivity in visual assessments. We develop and evaluate a deep learning approach for the simultaneous segmentation of natural teeth and shad...
Background: Medical education represents a complex field of study, influenced by various psychological, demographic, and contextual factors. Academic motivation, essential for educational success, has been linked to critical decisions in medical care...
Computer Vision (CV) has proven to be a powerful tool for automation in agri-food industrial processes, offering high-precision solutions tailored to specific working conditions. Recent advancements in Artificial Neural Networks (ANNs) have revolutio...
Weakly supervised object detection (WSOD) in remote sensing images (RSIs) aims to detect high-value targets by solely utilizing image-level category labels; however, two problems have not been well addressed by existing methods. Firstly, the seed ins...
Plant disease segmentation has achieved significant progress with the help of artificial intelligence. However, deploying high-accuracy segmentation models in resource-limited settings faces three key challenges, as follows: (A) Traditional dense att...
The Segment Anything Model 2 (SAM2) has achieved state-of-the-art performance in pixel-level object segmentation for both static and dynamic visual content. Its streaming memory architecture maintains spatial context across video sequences, yet strug...
Optical coherence tomography (OCT) is a non-invasive imaging technique widely used in ophthalmology for visualizing retinal layers, aiding in the early detection and monitoring of retinal diseases. OCT is useful for detecting diseases such as age-rel...
Food semantic segmentation is of great significance in the field of computer vision and artificial intelligence, especially in the application of food image analysis. Due to the complexity and variety of food, it is difficult to effectively handle th...
The preservation of historical monuments presents a formidable challenge, particularly in monitoring the deterioration of building materials over time. Chateau de Chambord’s facade suffers from common issues such as flaking and spalling, which...
Accurate prediction of landslide susceptibility is a key component of disaster risk reduction and early warning systems. Traditional landslide susceptibility prediction methods often face challenges in capturing complex nonlinear and spatio-temporal...
Dynamic gesture detection is a key topic in computer vision and deep learning, with applications in human–computer interaction and virtual reality. However, traditional methods struggle with long sequences, complex scenes, and multimodal data,...
Unsupervised domain adaptation (UDA) enables training a model on labeled source data to perform well in a target domain without supervision, which is especially valuable in vision-based semantic segmentation. However, existing UDA methods often strug...
Single-image dehazing suffers from severe information loss and the under-constraint problem. The lack of high-quality robust priors leads to limited generalization ability of existing dehazing methods in real-world scenarios. To tackle this challenge...
Currently used elaborate technologies for the detection of bacteria can be improved in regard to their time consumption, labor intensity, accuracy and reproducibility. Well-known electrical measurement methods might connect highly sensitive sensing s...
Recognizing plant leaves in complex agricultural scenes is challenging due to high manual annotation costs and real-time detection demands. Current deep learning methods, such as YOLOv8 and SAM, face trade-offs between annotation efficiency and infer...
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