Results 121 to 130 of about 7,640,907 (324)

On implicit Lagrangian twin support vector regression by Newton method [PDF]

, 2013
S. R. Balasundaram, Deepak Gupta
openalex   +1 more source

Single Image Super-Resolution Algorithm based on Fixed-Point Multi-Model Gaussian Process Regression

, 2022
Ziwei Lu, Hongfei Yu
openalex   +1 more source

Recurrent cancer‐associated ERBB4 mutations are transforming and confer resistance to targeted therapies

Molecular Oncology, EarlyView.
We show that the majority of the 18 analyzed recurrent cancer‐associated ERBB4 mutations are transforming. The most potent mutations are activating, co‐operate with other ERBB receptors, and are sensitive to pan‐ERBB inhibitors. Activating ERBB4 mutations also promote therapy resistance in EGFR‐mutant lung cancer.
Veera K. Ojala, Sini Ahonen, Sara Peltola, Aura Tuohisto‐Kokko, Olaya Esparta, Peppi Suominen, Anne Jokilammi, Iman Farahani, Deepankar Chakroborty, Nikol Dibus, Steffen Boettcher, Tomi T. Airenne, Mark S. Johnson, Lisa D. Eli, Klaus Elenius, Kari J. Kurppa   +15 more
wiley   +1 more source

Estimation of three-dimensional long axes of the maxillary and mandibular first molars with regression analysis [PDF]

, 2019
Kazuto Terada, Takashi Kameda, Ikuo Kageyama, Makoto Sakamoto   +3 more
openalex   +1 more source

Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity

Molecular Oncology, EarlyView.
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung, David Bickel, Lena C. M. Krause, Daria Ezeriņa, Christian Ickes, Julian Wojtachnia, Christine S. Gibhardt, Magdalena Shumanska, Khadija Wahni, Andrea Paluschkiwitz, Julia Malo Pueyo, Ekaterina Baranova, Wim Vranken, Hedwig Stanisz, Ioana Stejerean‐Todoran, Michael P. Schön, Joris Messens, Ivan Bogeski   +17 more
wiley   +1 more source

Application of an Artificial Neural Network for Efficient Computation of Chemical Activities within an EAF Process Model

Metals
The electric arc furnace (EAF) is considered the second most important process for the production of crude steel and is usually used for the melting of scrap.
Alexander Reinicke, Til-Niklas Engbrecht, Lilly Schüttensack, Thomas Echterhof   +3 more
doaj   +1 more source

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

Molecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris, Vasiliki Siozopoulou, Léon C van Kempen, Anne Sieben, Ella Roelant, Stig Hellemans, Elyne Backx, Laure Sorber, Koen De Winne, Senada Koljenović, Karen Zwaenepoel   +10 more
wiley   +1 more source

Combining antibody conjugates with cytotoxic and immune‐stimulating payloads maximizes anti‐cancer activity

Molecular Oncology, EarlyView.
Methods to improve antibody–drug conjugate (ADC) treatment durability in cancer therapy are needed. We utilized ADCs and immune‐stimulating antibody conjugates (ISACs), which are made from two non‐competitive antibodies, to enhance the entry of toxic payloads into cancer cells and deliver immunostimulatory agents into immune cells.
Tiexin Wang, Dong Jun Koo, Peter M. Tessier, Greg M. Thurber   +3 more
wiley   +1 more source

Tumor mutational burden as a determinant of metastatic dissemination patterns

Molecular Oncology, EarlyView.
This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal, Andrea Moreno‐Manuel, Miguel Salvadó‐Pertierra, Cristina Santos‐Vivas, Rebeca Sanz‐Pamplona   +4 more
wiley   +1 more source

The "spurious regression problem" in the classical regression model framework [PDF]

I analyse the "spurious regression problem" from the Classical Regression Model (CRM) point of view. Simulations show that the autocorrelation corrections suggested by the CRM, e.g., feasible generalised least squares, solve the problem.
Gueorgui I. Kolev
core