Results 211 to 220 of about 478,988 (359)

Diagnostic, prognostic, and immunological roles of FUT8 in lung adenocarcinoma and lung squamous cell carcinoma. [PDF]

open access: yesPLoS One
Li Z   +11 more
europepmc   +1 more source

A case report of lung adenocarcinoma with polyserous effusions as the onset symptom

open access: gold, 2017
Ping Han   +7 more
openalex   +1 more source

Spatial Profiling Reveals Distinct Molecular and Immune Evolution of Mouse Lung Adenocarcinoma Precancers with or Without Carcinogen Exposure

open access: yesAdvanced Science, EarlyView.
Tumor evolution in lung adenocarcinoma is shaped by genetic alterations and spatial immune dynamics. By integrating whole‐exome sequencing, imaging mass cytometry, and spatial transcriptomics across two mouse models, this study reveals how mutational burden, immune infiltration, and cell–state interactions evolve during early and late carcinogenesis ...
Bo Zhu   +34 more
wiley   +1 more source

Discriminating invasive adenocarcinoma among lung pure ground-glass nodules: a multi-parameter prediction model. [PDF]

open access: yesJ Thorac Dis, 2021
Hu F   +14 more
europepmc   +1 more source

TriCON: A Carbon‐Based Triple‐Modal Nanoplatform for Pancreatic Cancer Therapy

open access: yesAdvanced Science, EarlyView.
We developed TriCON, a triple‐modality nanotherapeutic platform, to treat pancreatic ductal adenocarcinoma (PDAC) by synergizing gene editing, chemotherapy, and immunotherapy. TriCON utilizes CRISPR/Cas9 to target the poliovirus receptor (PVR), combined with nano‐encapsulated doxorubicin and checkpoint blockade. This approach achieved significant tumor
Xinyu Peng   +9 more
wiley   +1 more source

Late Recurrence of Mucinous Adenocarcinoma after Lung Transplantation: A Case Report and Literature Review. [PDF]

open access: yesCase Rep Oncol
Claeys E   +12 more
europepmc   +1 more source

CELLama: Foundation Model for Single Cell and Spatial Transcriptomics by Cell Embedding Leveraging Language Model Abilities

open access: yesAdvanced Science, EarlyView.
CELLama is created, a framework that harnesses language models to convert cellular data into “sentences” that represent gene expression and metadata, enabling a universal embedding of cells. Unlike most single‐cell foundation models, CELLama supports scalable analysis and offers flexible applications including spatial transcriptomics.
Jeongbin Park   +7 more
wiley   +1 more source

Home - About - Disclaimer - Privacy