Results 151 to 160 of about 169,948 (309)

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

open access: yesAdvanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu   +4 more
wiley   +1 more source

Nuclear Mechanotransduction Across the Metastatic Cascade: Decoding Spatiotemporal Heterogeneity in Cancer Dissemination

open access: yesAdvanced Science, EarlyView.
Tumor metastasis results from complex interactions between cancer cells and mechanical microenvironments. We propose a “nucleus‐centered, cross‐stage mechanical signal decoding” model, highlighting how nuclear mechanosensors interpret forces at different stages.
Linqi Song   +4 more
wiley   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

open access: yesAdvanced Science, EarlyView.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng   +17 more
wiley   +1 more source

Deciphering the Impact of RAC1‐SPTAN1 in ARPKD Cystogenesis Using Multifaceted Models

open access: yesAdvanced Science, EarlyView.
Distal/connecting tubules expressing SLC8A1 have been suggested as a potential origin of ARPKD cysts. SPTAN1 has been identified as a key molecule in ARPKD cyst formation. Restoring SPTAN1 in PKHD1−/− organoids reduced cyst formation, normalized calcium levels, and decreased RAC1/c‐FOS expression, highlighting SPTAN1's role in ARPKD and the potential ...
Shohei Kuraoka   +9 more
wiley   +1 more source

Cells Dynamically Adapt Their Nuclear Volumes and Proliferation Rates During Single to Multicellular Transitions

open access: yesAdvanced Science, EarlyView.
It is currently not well understood how cells regulate basic properties, e.g., volume and mechanics within dense multicellular environments like tumors. Here, we show that different cell types of cancer and also normal cells largely decrease their nuclear and cellular volumes in emerging cell clusters and that this is partly driven by cell cycle shifts.
Vaibhav Mahajan   +13 more
wiley   +1 more source

Tumor‐Induced Splenic Remodeling: Mechanisms of Systemic Immunosuppression and Emerging Therapeutic Opportunities

open access: yesAdvanced Science, EarlyView.
ABSTRACT Despite the transformative impact of cancer immunotherapies such as immune checkpoint blockade, durable clinical responses remain limited. Increasing evidence indicates that antitumor immunity is governed not only by the tumor microenvironment, but also by systemic immune regulation mediated by peripheral immune organs. Among these, the spleen
Yuehua Liu, Xiaoqian Nie, Xiaofei Gao
wiley   +1 more source

From Cell‐Free Transcriptomes to Single‐Cell Landscapes: Biomarker Discovery and Originating Cell Alteration Analysis via Graph Matrix Factorization

open access: yesAdvanced Science, EarlyView.
CellFreeGMF traces plasma cfRNA to likely originating cell types by integrating single‐cell atlases with graph‐regularized matrix factorization. The method decomposes cfRNA profiles into sample–cell contributions to reconstruct pseudo single‐cell expression.
Wenxiang Zhang   +9 more
wiley   +1 more source

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