Results 221 to 230 of about 1,547,687 (315)

Beta-Binomial Model for Count Data: An Application in Estimating Model-Based Oral Reading Fluency. [PDF]

Educ Psychol Meas
Qiao X, Kamata A, Kara Y, Potgieter C, Nese JFT.   +4 more
europepmc   +1 more source

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Zero-inflated Poisson mixed model for longitudinal count data with informative dropouts. [PDF]

J Appl Stat
Sinha SK.
europepmc   +1 more source

Exon 7 splicing of ERα predicts poor prognosis and increases phenotypic heterogeneity in luminal a subtype breast cancer

FEBS Open Bio, EarlyView.
ERα splice variant ERα∆7 lacks the C‐terminus, and its expression may change phenotypes of breast cancers. Our results showed that ERα∆7 is found in the luminal A subtype, and elevated ERα∆7 levels are linked to improved cell survival with lower proliferation and migration.
Long Wai Tsui, Taobo Hu, Thomson Christian Husein, Wai Hei Shek, Bingrong Chen, Depeng Wang, Shu Wang, Weichuan Yu, Xiaodan Fan, Mengping Long, Toyotaka Ishibashi   +10 more
wiley   +1 more source

Analyte Importance Analysis in Machine Learning-Based Detection of Wrong-Blood-in-Tube Errors Using Complete Blood Count Data. [PDF]

J Pers Med
Sürmeli BG, Staritzbichler R, Ringel C, Al-Dakkak S, Dörksen H, Kaiser T.   +5 more
europepmc   +1 more source

Development of human monoclonal antibodies against TARM1 by yeast display

FEBS Open Bio, EarlyView.
Human monoclonal antibodies against TARM1 are generated by yeast display‐guided selection. These antibodies bind to soluble and cell‐surface forms of TARM1. Also, these antibodies exhibit agonistic activity in the NFAT‐GFP reporter assay, indicating that TARM1 signaling can be functionally modulated by antibodies and suggesting TARM1 as a potential ...
Rikio Yabe, Mayumi Saeki, Masaaki Hashiguchi, Sayaka Ono, Kazuhisa Aoki, Hidetaka Tanno   +5 more
wiley   +1 more source

Predicting intramammary infections in non-lactating dairy cows using dairy herd improvement somatic cell count data for developing infection control benchmarks. [PDF]

J Vet Med Sci
Yamamoto H, Sentoku Y, Abe H, Sasaka T, Kurumisawa T, Kawai K.   +5 more
europepmc   +1 more source

Establishing an assay to evaluate d‐amino acid oxidase enzyme kinetics and inhibition using WST‐8 redox dye

FEBS Open Bio, EarlyView.
This study investigated a novel WST‐8‐based assay for evaluating d‐Amino acid oxidase (DAO) inhibitors. We confirmed its effectiveness using known inhibitors and found that uremic toxins possess relatively weak inhibitory activity compared to existing drugs.
Kahoko Miyake, Yuki Enoki, Yuka Nakazawa, Kazuaki Taguchi, Kazuaki Matsumoto   +4 more
wiley   +1 more source

Machine Learning-Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones. [PDF]

JCO Clin Cancer Inform
Brouwer CG, Bartelet BM, Douma JAJ, van Doorn L, Kuip EJM, Verheul HMW, Buffart LM.   +6 more
europepmc   +1 more source

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source