Results 51 to 60 of about 477,456 (237)
Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung +17 more
wiley +1 more source
RIPK4 function interferes with melanoma cell adhesion and metastasis
RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski +9 more
wiley +1 more source
Watch and Learn: Semi-Supervised Learning of Object Detectors from Videos
We present a semi-supervised approach that localizes multiple unknown object instances in long videos. We start with a handful of labeled boxes and iteratively learn and label hundreds of thousands of object instances.
Hebert, Martial +2 more
core +1 more source
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +1 more source
Multiple Object Tracking via Feature Pyramid Siamese Networks
When multiple object tracking (MOT) based on the tracking-by-detection paradigm is implemented, the similarity metric between the current detections and existing tracks plays an essential role. Most of the MOT schemes based on a deep neural network learn
Sangyun Lee, Euntai Kim
doaj +1 more source
SANet: Structure-Aware Network for Visual Tracking
Convolutional neural network (CNN) has drawn increasing interest in visual tracking owing to its powerfulness in feature extraction. Most existing CNN-based trackers treat tracking as a classification problem.
Fan, Heng, Ling, Haibin
core +1 more source
Hippo pathway at the crossroads of stemness and therapeutic resistance in breast cancer
Dysregulation of the Hippo pathway drives nuclear accumulation of YAP/TAZ, activating stemness‐related transcriptional programs that sustain breast cancer stemness and fuel therapeutic resistance across subtypes, underscoring Hippo signaling as a targetable vulnerability. Figure created and edited with BioRender.com.
Giulia Schiavoni +11 more
wiley +1 more source
CoMaL Tracking: Tracking Points at the Object Boundaries
Traditional point tracking algorithms such as the KLT use local 2D information aggregation for feature detection and tracking, due to which their performance degrades at the object boundaries that separate multiple objects.
Mittal, Anurag +2 more
core +1 more source
Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley +1 more source
Learning Background-Aware Correlation Filters for Visual Tracking
Correlation Filters (CFs) have recently demonstrated excellent performance in terms of rapidly tracking objects under challenging photometric and geometric variations. The strength of the approach comes from its ability to efficiently learn - "on the fly"
Fagg, Ashton +2 more
core +1 more source

