Results 131 to 140 of about 3,321,873 (370)

Unveiling unique protein and phosphorylation signatures in lung adenocarcinomas with and without ALK, EGFR, and KRAS genetic alterations

open access: yesMolecular Oncology, EarlyView.
Proteomic and phosphoproteomic analyses were performed on lung adenocarcinoma (LUAD) tumors with EGFR, KRAS, or EML4–ALK alterations and wild‐type cases. Distinct protein expression and phosphorylation patterns were identified, especially in EGFR‐mutated tumors. Key altered pathways included vesicle transport and RNA splicing.
Fanni Bugyi   +12 more
wiley   +1 more source

Data‐driven performance metrics for neural network learning

open access: yesInternational Journal of Adaptive Control and Signal Processing, EarlyView., 2023
Summary Effectiveness of data‐driven neural learning in terms of both local mimima trapping and convergence rate is addressed. Such issues are investigated in a case study involving the training of one‐hidden‐layer feedforward neural networks with the extended Kalman filter, which reduces the search for the optimal network parameters to a state ...
Angelo Alessandri   +2 more
wiley   +1 more source

Asymptotic analytical methods in fluid mechanics related to drag prediction [PDF]

open access: yes
Some recent theoretical work of a purely analytical nature is described which promises to provide engineering predictions for the important drag-related phenomena of flow in the stall regime. This analytical work deals with rigorous asymptotic studies of
Inger, G. R.
core   +1 more source

Investigating the cell of origin and novel molecular targets in Merkel cell carcinoma: a historic misnomer

open access: yesMolecular Oncology, EarlyView.
This study indicates that Merkel cell carcinoma (MCC) does not originate from Merkel cells, and identifies gene, protein & cellular expression of immune‐linked and neuroendocrine markers in primary and metastatic Merkel cell carcinoma (MCC) tumor samples, linked to Merkel cell polyomavirus (MCPyV) status, with enrichment of B‐cell and other immune cell
Richie Jeremian   +10 more
wiley   +1 more source

Geometric nonlinearities in field theory, condensed matter and analytical mechanics

open access: yesCondensed Matter Physics, 2010
There are two very important subjects in physics: Symmetry of dynamical models and nonlinearity. All really fundamental models are invariant under some particular symmetry groups.
J.J. Sławianowski
doaj   +1 more source

Analytical solution for the Zee mechanism

open access: yes, 2017
We found an analytical solution for the neutrino mass matrix in the most general case of the Zee model. Using the recent data on the neutrino parameters besides generating neutrino masses at 1-loop level we fit also the masses of the charged leptons and the leptonic mixing matrix.
Machado, A. C. B.   +3 more
openaire   +2 more sources

Hypomethylating agents increase L1 retroelement expression without inducing novel insertions in myeloid malignancies

open access: yesMolecular Oncology, EarlyView.
We investigated whether hypomethylating agents (HMAs) used in myeloid malignancies induce somatic retrotransposition. Our findings indicate that HMA treatment increases L1‐encoded protein expression but does not lead to detectable de novo retrotransposition events in either patient samples or cell lines.
Šárka Pavlová   +14 more
wiley   +1 more source

Static Footprint Local Forces, Areas, and Aspect Ratios for Three Type 7 Aircraft Tires [PDF]

open access: yes
The National Tire Modeling Program (NTMP) is a joint NASA/industry effort to improve the understanding of tire mechanics and develop accurate analytical design tools. This effort includes fundamental analytical and experimental research on the structural
Howell, William E.   +2 more
core   +1 more source

Tumor‐agnostic detection of circulating tumor DNA in patients with advanced pancreatic cancer using targeted DNA methylation sequencing and cell‐free DNA fragmentomics

open access: yesMolecular Oncology, EarlyView.
We evaluated circulating tumor DNA (ctDNA) detection in advanced pancreatic cancer using DNA methylation, cell‐free DNA fragment lengths, and 5′ end motifs. Machine learning models were trained to estimate ctDNA levels from each feature and their combination.
Morten Lapin   +10 more
wiley   +1 more source

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