Fine-Grained Visual Text Prompting.

Vision-Language Models (VLMs), such as CLIP, excel in zero-shot image-level visual understanding but struggle with object-based tasks requiring precise localization and recognition. Visual prompts, like colorful boxes or circles, are suggested to enhance local perception. However, these methods often include irrelevant and noisy pixels, leading to suboptimal performance.

Cascade-Activatable Nanoprodrug System Augments Sonochemotherapy of Bladder Cancer.

Sonochemotherapy (SCT) has emerged as a powerful modality for cancer treatment by triggering excessive production of reactive oxygen species (ROS) and controlled release of chemotherapeutic agents under ultrasound. However, achieving spatiotemporally controlled release of chemotherapeutic agents during ROS generation is still an enormous challenge. In this work, we developed a cascade-activated nanoprodrug () system that utilizes a reversible covalent Schiff base mixed with a hypoxia-activatable camptothecin (CPT) prodrug.

Stimuli-Responsive Nanomaterials for Tumor Immunotherapy.

Cancer remains a significant challenge in extending human life expectancy in the 21 century, with staggering numbers projected by the International Agency for Research on Cancer for upcoming years. While conventional cancer therapies exist, their limitations, in terms of efficacy and side effects, demand the development of novel treatments that selectively target cancer cells. Tumor immunotherapy has emerged as a promising approach, but low response rates and immune-related side effects present significant clinical challenges.

TRIM44 Promotes Rabies Virus Replication by Autophagy-Dependent Mechanism.

Tripartite motif (TRIM) proteins are a multifunctional E3 ubiquitin ligase family that participates in various cellular processes. Recent studies have shown that TRIM proteins play important roles in regulating host-virus interactions through specific pathways, but their involvement in response to rabies virus (RABV) infection remains poorly understood. Here, we identified that several TRIM proteins are upregulated in mouse neuroblastoma cells (NA) after infection with the rabies virus using RNA-seq sequencing.

Inducing mitochondriopathy-like damages by transformable nucleopeptide nanoparticles for targeted therapy of bladder cancer.

Mitochondriopathy inspired adenosine triphosphate (ATP) depletions have been recognized as a powerful way for controlling tumor growth. Nevertheless, selective sequestration or exhaustion of ATP under complex biological environments remains a prodigious challenge. Harnessing the advantages of self-assembled nanomaterials, we designed an Intracellular ATP Sequestration (IAS) system to specifically construct nanofibrous nanostructures on the surface of tumor nuclei with exposed ATP binding sites, leading to highly efficient suppression of bladder cancer by induction of mitochondriopathy-like damages.

Single-cell analyses as a marker of the ratio of M1/M2 macrophages is associated with EMT, immune infiltration, and prognosis in bladder cancer.

Background: Bladder cancer is among the most lethal urinary system cancers across the globe. Macrophage 1 and Macrophage 2 play an essential role in the pathogenesis of tumors. Nevertheless, prior studies failed to investigate the implication of the two cells, working in combination, in the development, growth, progression and metastasis of bladder cancer.

Photostable Cascade-Activatable Peptide Self-Assembly on a Cancer Cell Membrane for High-Performance Identification of Human Bladder Cancer.

Missed or residual tumor burden results in high risk for bladder cancer relapse. However, existing fluorescent probes cannot meet the clinical needs because of inevitable photobleaching properties. Performance can be improved by maintaining intensive and sustained fluorescence signals via resistance to intraoperative saline flushing and intrinsic fluorescent decay, providing surgeons with sufficiently clear and high-contrast surgical fields, avoiding residual tumors or missed diagnosis.

DSMENet: Detail and Structure Mutually Enhancing Network for under-sampled MRI reconstruction.

Reconstructing zero-filled MR images (ZF) from partial k-space by convolutional neural networks (CNN) is an important way to accelerate MRI. However, due to the lack of attention to different components in ZF, it is challenging to learn the mapping from ZF to targets effectively. To ameliorate this issue, we propose a Detail and Structure Mutually Enhancing Network (DSMENet), which benefits from the complementary of the Structure Reconstruction UNet (SRUN) and the Detail Feature Refinement Module (DFRM).

HIWDNet: A hybrid image-wavelet domain network for fast magnetic resonance image reconstruction.

The application of Magnetic Resonance Imaging (MRI) is limited due to the long acquisition time of k-space signals. Recently, many deep learning-based MR image reconstruction methods have been proposed to reduce acquisition time and improve MRI image quality by reconstructing images from under-sampled k-space data. However, these methods suffer from two shortcomings.