Results 131 to 140 of about 113,830 (296)
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
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
The universe, or, The wonders of creation. The infinitely great and the infinitely little
F.-A. Pouchet
openalex +4 more sources
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
The Expanding Universe and the Origin of the Great Nebulæ [PDF]
George Gamow, Edward Teller
openalex +1 more source
CircCCNB1 expression is down‐regulated in nasopharyngeal carcinoma (NPC); thus, less NF90 protein is bound to circCCNB1 and more binds to pri‐miRNAs, blocking their (pri‐miRNAs) binding to DGCR8 and inhibiting the processing and generation of miR‐15b‐5p/miR‐7‐1‐3p. Furthermore, decreased miR‐15b‐5p/miR‐7‐1‐3p promotes the expression of the target genes
Chunmei Fan+6 more
wiley +1 more source
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
On the Relation between the Expansion and the Mean Density of the Universe
A. Einstein, W. de Sitter
openalex +1 more source
Patient engagement involves actively including patients in healthcare decisions and research to ensure care and studies align with their needs. This approach improves outcomes, trust, and communication while fostering collaboration between patients and professionals.
Estela Cepeda+3 more
wiley +1 more source