Results 241 to 250 of about 141,166 (348)

Single‐Cell Dissection of Tumor‐Infiltrating Lymphocytes Reveals Cellular Architecture Predictive of Therapeutic Efficacy in Acral Melanoma

open access: yesAdvanced Science, EarlyView.
Autologous tumor‐infiltrating lymphocyte (TIL) therapy shows promising efficacy in acral melanoma, yet determinants of durable response remain unclear. By integrating single‐cell transcriptomics and TCR sequencing, this study reveals that TIL products enriched for T follicular helper and intermediate exhausted T cells establish persistent clonal ...
Chao Zhang   +12 more
wiley   +1 more source

Engineered CAR‐NKT Extracellular Vesicles Suppress Tumor Progression and Enhance Antitumor Immunity

open access: yesAdvanced Science, EarlyView.
TM4SF1‐nanobody engineered CAR‐natural killer T–derived extracellular vesicles (CARTM4SF1‐EVs) provide a cell‐free alternative to CAR‐NKT therapy, achieving potent, targeted antitumor activity with reduced toxicity. CARTM4SF1‐EVs induce immunogenic cell death, remodel the tumor microenvironment, and enhance CD8⁺ T‐cell antitumor immunity.
Xiaopei Hao   +14 more
wiley   +1 more source

Engineering Immune Cell to Counteract Aging and Aging‐Associated Diseases

open access: yesAdvanced Science, EarlyView.
This review highlights a paradigm shift in which advanced immune cell therapies, initially developed for cancer, are now being harnessed to combat aging. By engineering immune cells to selectively clear senescent cells and remodel pro‐inflammatory tissue microenvironments, these strategies offer a novel and powerful approach to delay age‐related ...
Jianhua Guo   +5 more
wiley   +1 more source

A Murine Database of Structural Variants Identifies A Candidate Gene for a Spontaneous Murine Lymphoma Model

open access: yesAdvanced Science, EarlyView.
We analyzed long‐read genomic sequencing data obtained from 40 inbred mouse strains to produce a large database of structural variants. This dataset captures the major types of structural variants, which includes deletions, insertions, duplications, and inversions.
Wenlong Ren   +6 more
wiley   +1 more source

Disentangling Coincident Cell Events Using Deep Transfer Learning and Compressive Sensing

open access: yesAdvanced Intelligent Systems, EarlyView.
Overlapping cells during detection distort single‐cell measurements and reduce diagnostic accuracy. A hybrid framework combining a fully convolutional neural network with compressive sensing to disentangle overlapping signals directly from raw time‐series data is presented.
Moritz Leuthner   +2 more
wiley   +1 more source

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