Results 121 to 130 of about 10,537,968 (352)

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

open access: yesMolecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima   +6 more
wiley   +1 more source

Maximum number of limit cycles for generalized Li'enard differential equations

open access: yesElectronic Journal of Differential Equations, 2013
Applying the averaging theory of first and second order to a class of generalized polynomial Lienard differential equations, we improve the known lower bounds for the maximum number of limit cycles that this class can exhibit.
Sabrina Badi, Amar Makhlouf
doaj  

Stochastic bifurcation analysis in Brusselator system with white noise

open access: yesAdvances in Difference Equations, 2019
In this paper, we mainly study the stochastic stability and stochastic bifurcation of Brusselator system with multiplicative white noise. Firstly, by a polar coordinate transformation and a stochastic averaging method, the original system is transformed ...
Changzhao Li, Juan Zhang
doaj   +1 more source

Exploring the role of cyclin D1 in the pathogenesis of multiple myeloma beyond cell cycle regulation

open access: yesMolecular Oncology, EarlyView.
Cyclin D1 overexpression altered the cell adhesion pathway, while cyclin D2 upregulation had less impact on pathway enrichment analysis. Multiple myeloma (MM) patients with cyclin D1 overexpression showed reduced CD56 expression and increased circulating tumor cells (CTC) levels, suggesting that cyclin D1 may contribute to MM cell dissemination ...
Ignacio J. Cardona‐Benavides   +13 more
wiley   +1 more source

The critical role of DNA damage‐inducible transcript 4 (DDIT4) in stemness character of leukemia cells and leukemia initiation

open access: yesMolecular Oncology, EarlyView.
Stemness properties, including quiescence, self‐renewal, and chemoresistance, are closely associated with leukemia relapse. Here, we demonstrate that DNA damage‐inducible transcript 4 (DDIT4) is induced in the hypoxic bone marrow niche and is essential for maintaining the stemness of AML1‐ETO9a leukemia cells.
Yishuang Li   +12 more
wiley   +1 more source

Model Averaging for Accelerated Failure Time Models with Missing Censoring Indicators

open access: yesMathematics
Model averaging has become a crucial statistical methodology, especially in situations where numerous models vie to elucidate a phenomenon. Over the past two decades, there has been substantial advancement in the theory of model averaging. However, a gap
Longbiao Liao, Jinghao Liu
doaj   +1 more source

On the Limit Cycles of a Class of Generalized Kukles Polynomial Differential Systems via Averaging Theory

open access: yesInternational Journal of Differential Equations, 2015
We apply the averaging theory of first and second order to a class of generalized Kukles polynomial differential systems to study the maximum number of limit cycles of these systems.
Amar Makhlouf, Amor Menaceur
doaj   +1 more source

Matrigel inhibits elongation and drives endoderm differentiation in aggregates of mouse embryonic stem cells

open access: yesFEBS Open Bio, EarlyView.
Stem cell‐based embryo models (SCBEMs) are valuable to study early developmental milestones. Matrigel, a basement membrane matrix, is a critical substrate used in various SCBEM protocols, but its role in driving stem cell lineage commitment is not clearly defined.
Atoosa Amel   +3 more
wiley   +1 more source

An asymptotic theory for model selection inference in general semiparametric problems. [PDF]

open access: yes
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model averaging and post-model selection/averaging inference using likelihood methods in parametric models, along with associated confidence statements.
Carroll, RJ, Claeskens, Gerda
core  

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