Results 201 to 210 of about 29,604,152 (395)
Mutational analysis of the R64 oriT region: requirement for precise location of the NikA-binding sequence [PDF]
Nobuhisa Furuya, Teruya Komano
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Cancer stem cells are associated with aggressive disease, but a deep characterization of such markers is lacking in endometrial cancer. This study uses imaging mass cytometry to explore putative cancer stem cell markers in endometrial tumors and corresponding organoid models.
Hilde E. Lien+7 more
wiley +1 more source
Capture, integration, and analysis of digital system requirements with conceptual graphs [PDF]
Walling R. Cyre
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Peripheral blood proteome biomarkers distinguish immunosuppressive features of cancer progression
Immune status significantly influences cancer progression. This study used plasma proteomics to analyze benign 67NR and malignant 4T1 breast tumor models at early and late tumor stages. Immune‐related proteins–osteopontin (Spp1), lactotransferrin (Ltf), calreticulin (Calr) and peroxiredoxin 2 (Prdx2)–were associated with systemic myeloid‐derived ...
Yeon Ji Park+6 more
wiley +1 more source
An analysis of industry responses to federal regulations in safety requirements for new automobiles [PDF]
Howard M. Bunch
openalex
Stochastic variation in the FOXM1 transcription program mediates replication stress tolerance
Cellular heterogeneity is a major cause of drug resistance in cancer. Segeren et al. used single‐cell transcriptomics to investigate gene expression events that correlate with sensitivity to the DNA‐damaging drugs gemcitabine and prexasertib. They show that dampened expression of transcription factor FOXM1 and its target genes protected cells against ...
Hendrika A. Segeren+4 more
wiley +1 more source
Genetic analysis of dorsoventral pattern formation in the zebrafish: requirement of a BMP-like ventralizing activity and its dorsal repressor. [PDF]
M. Hammerschmidt+2 more
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Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song+13 more
wiley +1 more source