Results 81 to 90 of about 1,398,433 (359)

The Latest Achievements in the Construction of Influenza Virus Detection Aptasensors

Viruses, 2020
Aptamers are short fragments of nucleic acids, DNA or RNA that have the ability to bind selected proteins with high specificity and affinity. These properties allow them to be used as an element of biosensors for the detection of specific proteins ...
Ewelina Wędrowska, Tomasz Wandtke, Elżbieta Piskorska, Piotr Kopiński   +3 more
doaj   +1 more source

Co‐existing monophasic teratoma and uterine adenocarcinoma in a female dog [PDF]

, 2019
Ovarian teratomas are occasionally reported in dogs; the rarest type is the monophasic teratoma,composed of tissues originating from only one germ layer. Canine endometrial adenocarcinomas are also rare in dogs and mainly affect geriatric females.
Catarino, J.C, Faim, S., Freire, A., Neves, T., Orge, L., Payan-Carreira, R., Pires, M.A., Seixas, F., Vilhena, H.   +8 more
core   +2 more sources

Highly multiplexed digital PCR assay for simultaneous quantification of variant allele frequencies and copy number alterations of KRAS and GNAS in pancreatic cancer precursors

Molecular Oncology, EarlyView.
Combining melting curve analysis enhances the multiplexing capability of digital PCR. Here, we developed a 14‐plex assay to simultaneously measure single nucleotide mutations and amplifications of KRAS and GNAS, which are common driver genes in pancreatic cancer precursors. This assay accurately quantified variant allele frequencies in clinical samples
Junko Tanaka, Tatsuo Nakagawa, Yusuke Ono, Yoshio Kamura, Takeshi Ishida, Hidemasa Kawabata, Kenji Takahashi, Hiroki Sato, Andrew S. Liss, Yusuke Mizukami, Takahide Yokoi   +10 more
wiley   +1 more source

Characterization of alternative splicing events and prognostic signatures in gastric cancer

Cancer Cell International
Background Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation.
Nan Zhu, Yupeng Zhao, Wenjing Yan, Lan Wei, Qingqing Sang, Jianfang Li, Bingya Liu, Beiqin Yu   +7 more
doaj   +1 more source

Comparing self‐reported race and genetic ancestry for identifying potential differentially methylated sites in endometrial cancer: insights from African ancestry proportions using machine learning models

Molecular Oncology, EarlyView.
Integrating ancestry, differential methylation analysis, and machine learning, we identified robust epigenetic signature genes (ESGs) and Core‐ESGs in Black and White women with endometrial cancer. Core‐ESGs (namely APOBEC1 and PLEKHG5) methylation levels were significantly associated with survival, with tumors from high African ancestry (THA) showing ...
Huma Asif, J. Julie Kim
wiley   +1 more source

Benefit-risk profile of cytoreductive drugs along with antiplatelet and antithrombotic therapy after transient ischemic attack or ischemic stroke in myeloproliferative neoplasms [PDF]

, 2018
We analyzed 597 patients with myeloproliferative neoplasms (MPN) who presented transient ischemic attacks (TIA, n = 270) or ischemic stroke (IS, n = 327). Treatment included aspirin, oral anticoagulants, and cytoreductive drugs.
Arellano-Rodrigo, Eduardo, Barbui, Tiziano, Beggiato, Eloise, Bellini, Marta, Bertozzi, Irene, Betti, Silvia, Bonifacio, Massimiliano, Cacciola, Emma, Cacciola, Rossella, Carli, Giuseppe, Carobbio, Alessandra, Cattaneo, Daniele, Cazzola, Mario, Censori, Bruno, Cervantes, Francisco, Cortelezzi, Agostino, De Stefano, Valerio, Di Lazzaro, Vincenzo, Elli, Elena Maria, Ellis, Martin H., Finazzi, Guido, Finazzi, Maria Chiara, Gaidano, Gianluca, Gomez, Montse, Griesshammer, Martin, Guglielmelli, Paola, Hernandez-Boluda, Juan-Carlos, Iurlo, Alessandra, Loscocco, Giuseppe Gaetano, Lunghi, Francesca, Miroslava, Palova, Musolino, Caterina, Palandri, Francesca, Randi, Maria Luigia, Rapezzi, Davide, Rossi, Elena, Rumi, Elisa, Sadjadian, Parvis, Scaffidi, Luigi, Tieghi, Alessia, Vannucchi, Alessandro M., Vianelli, Nicola   +41 more
core   +5 more sources

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

P435: ANALYSIS OF MYELOBLAST IMMUNOPHENOTYPE PROFILE IN ACUTE MYELOID LEUKAEMIA AS PREDICTOR FOR CLINICAL OUTCOME

HemaSphere, 2022
M. Sobas, M. Nowak, D. Szymczak, I. Andrasiak, T. Wróbel   +4 more
doaj   +1 more source

DKK1 as a robust predictor for adjuvant platinum chemotherapy benefit in resectable pStage II-III gastric cancer

Translational Oncology, 2023
Background: Adjuvant chemotherapy (ACT) with 5-FU alone or 5-FU plus platinum after curative surgery improves the prognosis of pStage II-III gastric cancer (GC). However, only a subset of patients benefits from adjuvant platinum.
Zhiyuan Fan, Beiqin Yu, Tao Pan, Fangyuan Li, Jianfang Li, Junyi Hou, Wentao Liu, Liping Su, Zhenggang Zhu, Chao Yan, Bingya Liu   +10 more
doaj  

Forecasting Leading Death Causes in Australia using Extended CreditRisk$+$

, 2015
Recently we developed a new framework in Hirz et al (2015) to model stochastic mortality using extended CreditRisk$^+$ methodology which is very different from traditional time series methods used for mortality modelling previously.
Hirz, Jonas, Schmock, Uwe, Shevchenko, Pavel V.   +2 more
core