Results 201 to 210 of about 308,264 (290)

Demographic and geographical determinants of human olfactory perception of 909 individuals inhabiting 16 regions. [PDF]

iScience
Drnovsek E, Abraham NM, Abraham JN, Alizadeh R, Aloulou I, Chen L, Berioso Enecilla ML, Fornazieri MA, Frasnelli J, Fuselli JM, Gansatao F, Guducu C, Hernandez AK, Hofer MK, Husain S, Kamel R, Khouri VF, Loy F, Mahmut MK, Marek D, Masala C, Dias Lopes NM, Michaluk É, Miri I, Mirsalehi M, Miteva P, Musa A, Naija H, Nakaachi K, Pieniak M, Pinto JM, Mazal PP, Radwan A, Rafiei F, Rawat D, Reichert A, Scussiatto HO, Sheta HA, Thodupunoori SM, Turner BJ, Wu H, Wylie F, Yoshino A, Zou L, Zyzelewicz B, Bratman GN, Majid A, Hummel T, Oleszkiewicz A.   +48 more
europepmc   +1 more source

Concept Descriptor [PDF]

, 2020
openaire   +1 more source

Feasibility of a ctDNA multigenic panel for non‐small‐cell lung cancer early detection and disease surveillance

Molecular Oncology, EarlyView.
Plasma‐based detection of actionable mutations is a promising approach in lung cancer management. Analysis of ctDNA with a multigene NGS panel identified TP53, KRAS, and EGFR as the most frequently altered, with TP53 and KRAS in treatment‐naïve patients and TP53 and EGFR in previously treated patients.
Giovanna Maria Stanfoca Casagrande, Marcela de Oliveira Silva, Mariana Bisarro dos Reis, Rodrigo de Oliveira Cavagna, Luciane Sussuchi, Icaro Alves Pinto, Natalia Zampieri Pontes, Rodrigo Sampaio Chiarantano, Flavio Augusto Ferreira da Silva, Pedro de Marchi, Letícia Ferro Leal, Rui M. Reis   +11 more
wiley   +1 more source

On machine learning based QSPR analysis of amphetamine derivatives using regression models. [PDF]

Sci Rep
Hanif MF, Hashem AF, Hussain M, Fiidow OA.   +3 more
europepmc   +1 more source

Aggressive prostate cancer is associated with pericyte dysfunction

Molecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero, Ane Martinez‐Larrinaga, Joaquim Grego‐Bessa, Saioa Garcia‐Longarte, Hielke van Splunder, Ianire Astobiza, Amaia Ercilla, Laura Bozal‐Basterra, Isabel Mendizabal, Pilar Villacampa, Arkaitz Carracedo, Mariona Graupera   +11 more
wiley   +1 more source

Accelerated discovery of crystalline materials with record ultralow lattice thermal conductivity via a universal descriptor. [PDF]

Nat Commun
Shen X, Zheng J, Koza MM, Levinsky P, Hejtmanek J, Boullay P, Raveau B, Wang J, Li J, Lemoine P, Candolfi C, Guilmeau E.   +11 more
europepmc   +1 more source

Tumor and germline testing with next generation sequencing in epithelial ovarian cancer: a prospective paired comparison using an 18‐gene panel

Molecular Oncology, EarlyView.
Genetic testing in epithelial ovarian cancer includes both germline and tumor‐testing. This approach often duplicates resources. The current prospective study assessed the feasibility of tumor‐first multigene testing by comparing tumor tissue with germline testing of peripheral blood using an 18‐gene NGS panel in 106 patients.
Elisabeth Spenard, Cristina Mitric, Melanie Care, Tracy L. Stockley, Raymond H. Kim, Jeanna McCuaig, Blaise Clarke, Laura Ranich, Clare Sheen, Sarah E. Ferguson, Liat Hogen, Taymaa May, Marcus Q. Bernardini   +12 more
wiley   +1 more source

Render-Rank-Refine: Accurate 6D Indoor Localization via Circular Rendering. [PDF]

J Imaging
Monawwar H, Fan G.
europepmc   +1 more source

The neural crest‐associated gene ERRFI1 is involved in melanoma progression and resistance toward targeted therapy

Molecular Oncology, EarlyView.
ERRFI1, a neural crest (NC)‐associated gene, was upregulated in melanoma and negatively correlated with the expression of melanocytic differentiation markers and the susceptibility of melanoma cells toward BRAF inhibitors (BRAFi). Knocking down ERRFI1 significantly increased the sensitivity of melanoma cells to BRAFi.
Nina Wang, Qian Sun, Daniel Novak, Lei Zhu, Juliane Poelchen, Tamara Steinfass, Yiman Wang, Viktor Umansky, Jochen Utikal   +8 more
wiley   +1 more source

Machine Learning in Homogeneous Catalysis: Basic Concepts and Best Practices. [PDF]

ACS Catal
Dalmau D, García-Abellán S, Alegre-Requena JV.   +2 more
europepmc   +1 more source