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NF90–NF45 functions as a negative regulator of methyltransferase‐like 3/14 (METTL3/14)‐mediated N6‐methyladenosine (m6A) modification on primary microRNAs (pri‐miRNAs). NF90–NF45 binds to anti‐oncogenic pri‐miRNAs and inhibits their m6A modification, thereby suppressing the biogenesis of anti‐oncogenic miRNAs.
Takuma Higuchi +6 more
wiley +1 more source
Aged human bmMSCs are seeded in the scaffold. Osteoblastic induction can slightly increase cell's bone‐forming activity to produce bone‐like tissues, shown as the sporadic xylenol orange‐stained spots (the lower left image). Notably, pioglitazone plus EGCG co‐treatment dramatically increases cell's bone‐forming activity and bone‐like tissue production (
Ching‐Yun Chen +6 more
wiley +1 more source
dUTPases are involved in balancing the appropriate nucleotide pools. We showed that dUTPase is essential for normal development in zebrafish. The different zebrafish genomes contain several single‐nucleotide variations (SNPs) of the dut gene. One of the dUTPase variants displayed drastically lower protein stability and catalytic efficiency as compared ...
Viktória Perey‐Simon +6 more
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Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley +1 more source
Chemoresistance in bladder cancer: Macrophage recruitment associated with CXCL1, CXCL5 and CXCL8 expression is characteristic of Gemcitabine/Cisplatin (Gem/Cis) Non‐Responder tumors (right side) while Responder tumors did not show substantial tumor‐stromal crosstalk (left side). All biological icons are attributed to Bioicons: carcinoma, cancerous‐cell‐
Sophie Leypold +11 more
wiley +1 more source
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Methods in molecular biology, 2012
Principal components analysis (PCA) is a standard tool in multivariate data analysis to reduce the number of dimensions, while retaining as much as possible of the data's variation. Instead of investigating thousands of original variables, the first few components containing the majority of the data's variation are explored.
Detlef, Groth +3 more
openaire +3 more sources
Principal components analysis (PCA) is a standard tool in multivariate data analysis to reduce the number of dimensions, while retaining as much as possible of the data's variation. Instead of investigating thousands of original variables, the first few components containing the majority of the data's variation are explored.
Detlef, Groth +3 more
openaire +3 more sources
Coupled Principal Component Analysis
IEEE Transactions on Neural Networks, 2004A framework for a class of coupled principal component learning rules is presented. In coupled rules, eigenvectors and eigenvalues of a covariance matrix are simultaneously estimated in coupled equations. Coupled rules can mitigate the stability-speed problem affecting noncoupled learning rules, since the convergence speed in all eigendirections of the
Möller, Ralf, Könies, Axel
openaire +3 more sources

