The Density of Silicon Tetrafluoride [PDF]
Albert F. O. Germann, H. Booth
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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
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Sex-Biased and Density-Dependent Natal Dispersal in a Highly Mobile but Philopatric Raptor. [PDF]
Zsinka B+6 more
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XXXII. On the relationship between the viscosity, density, and temperature of salt solutions [PDF]
William J. Walker
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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
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Does population density impact maternal and child health? Mediating effects of the Universal Health Coverage Service Coverage Index. [PDF]
Jiang X+11 more
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THE OPTICAL ROTATION AND THE DENSITY OF ALCOHOLIC SOLUTIONS OF GLIADIN. [PDF]
W. E. Mathewson
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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
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Using isolation-by-distance to jointly estimate effective population density and dispersal distance: a practical evaluation using bumble bees. [PDF]
Simpson DT.
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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
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