Results 141 to 150 of about 2,520,715 (284)

Simplex C++ Syntax for Solving Chemical Engineering Cost Optimization Problems

, 2021
Abdulhalim Musa Abubakar, Okoh Chibuike Francis, Zakiyyu Muhammad Sarkinbaka, Muhammad Sabo Yahaya   +3 more
openalex   +2 more sources

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

Molecular 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, Sriraam Sivachandran, Melissa Galati, Brandon Ramchatesingh, Hibo Rijal, Johnny Hanna, Elena Netchiporouk, May Chergui, Margaret Redpath, Samy Abou Setah, Ivan V. Litvinov   +10 more
wiley   +1 more source

Shape differentiation of steady-state reaction-diffusion problems arising in chemical engineering with non-smooth kinetics with dead core

Electronic Journal of Differential Equations, 2017
In this paper we consider an extension of the results in shape differentiation of semilinear equations with smooth nonlinearity presented by Diaz and Gomez-Castro [8] to the case in which the nonlinearities might be less smooth.
David Gomez-Castro
doaj  

BIBLIOMETRIC ANALYSIS OF THE WORLD SCIENTIFIC PRODUCTION IN CHEMICAL ENGINEERING DURING 2000-2011. PART 3: ANALYSIS OF RESEARCH TRENDS AND HOT TOPICS

Journal of Amasya University the Institute of Sciences and Technology, 2020
A comprehensive bibliometric analysis of the scientific production of Chemical Engineering area has been carried out using the Web of Science database for the period 2000-2011 through three complementary studies.
Esther García-carpintero, Ruben Miranda
doaj  

Editorial for the Special Issue: Energy Security and Chemical Engineering Congress (ESChE) 2019, Penang, Malaysia [PDF]

, 2020
Dai‐Viet N. Vo, Doan Pham Minh, Sonil Nanda, Trinh Duy Nguyen   +3 more
openalex   +1 more source

YAP1::TFE3 mediates endothelial‐to‐mesenchymal plasticity in epithelioid hemangioendothelioma

Molecular Oncology, EarlyView.
The YAP1::TFE3 fusion protein drives endothelial‐to‐mesenchymal transition (EndMT) plasticity, resulting in the loss of endothelial characteristics and gain of mesenchymal‐like properties, including resistance to anoikis, increased migratory capacity, and loss of contact growth inhibition in endothelial cells.
Ant Murphy, Samuel Hartzler, Paula A. Vargas Carranza, Shyaman Jayasundara, Madison E. Yates, Nimod D. Janson, Bozhi Liu, Annaleigh Benton, Majid Kazemian, Jason A. Hanna   +9 more
wiley   +1 more source

Emerging role of ARHGAP29 in melanoma cell phenotype switching

Molecular Oncology, EarlyView.
This study gives first insights into the role of ARHGAP29 in malignant melanoma. ARHGAP29 was revealed to be connected to tumor cell plasticity, promoting a mesenchymal‐like, invasive phenotype and driving tumor progression. Further, it modulates cell spreading by influencing RhoA/ROCK signaling and affects SMAD2 activity. Rho GTPase‐activating protein
Beatrice Charlotte Tröster, Melanie Kappelmann‐Fenzl, Anja Katrin Bosserhoff, Nicole Rachinger   +3 more
wiley   +1 more source

Data Ecosystems for Scientific Experiments: Managing Combustion Experiments and Simulation Analyses in Chemical Engineering. [PDF]

Front Big Data, 2021
Ramalli E, Scalia G, Pernici B, Stagni A, Cuoci A, Faravelli T.   +5 more
europepmc   +1 more source

Separation processes and technologies as the mainstay in chemical, biochemical, petroleum and environmental engineering: A special issue

, 2016
Mahesh Ganesapillai, Arun Kumar Singh, Prithvi Simha   +2 more
openalex   +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

Molecular 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, Kjersti Tjensvoll, Karin Hestnes Edland, Satu Oltedal, Herish Garresori, Bjørnar Gilje, Saga Ekedal, Trygve Eftestøl, Jan Terje Kvaløy, Filip Janku, Oddmund Nordgård   +10 more
wiley   +1 more source