Results 91 to 100 of about 11,892,944 (395)

La posición de las instituciones de educación superior ante el avance del periodismo digital [PDF]

open access: yes, 2017
Starting from a PhD research paper presented at the Universidad Complutense de Madrid which considers that the education of journalists in Latin America is still at an early stage, the following hypothesis was raised: “Institutions of higher education in
Díaz, Laura   +3 more
core   +1 more source

NanoCMSer: a consensus molecular subtype stratification tool for fresh‐frozen and paraffin‐embedded colorectal cancer samples

open access: yesMolecular Oncology, EarlyView.
Consensus molecular subtypes (CMS1‐4) have been identified to study colorectal cancer heterogeneity and serve as potential biomarkers. In this study, we developed and evaluated NanoCMSer, a NanoString‐based classifier using 55 genes, optimized for FF and FFPE to facilitate the clinical evaluation of CMS subtyping.
Arezo Torang   +10 more
wiley   +1 more source

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

open access: yesMolecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran   +16 more
wiley   +1 more source

Dynamic Efficient Adversarial Training Guided by Gradient Magnitude [PDF]

open access: yesarXiv, 2021
Adversarial training is an effective but time-consuming way to train robust deep neural networks that can withstand strong adversarial attacks. As a response to its inefficiency, we propose Dynamic Efficient Adversarial Training (DEAT), which gradually increases the adversarial iteration during training.
arxiv  

Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer

open access: yesMolecular Oncology, EarlyView.
This study employed targeted metabolomic profiling to identify 302 distinct metabolites present in platelet‐rich plasma (PRP), revealing aberrant metabolic profiles amongst individuals diagnosed with colorectal cancer (CRC). Compared to carcinoembryonic antigen (CEA) and cancer antigen 19‐9 (CA199), our metabolite panel showed improved sensitivity ...
Zuojian Hu   +7 more
wiley   +1 more source

Efficient NLP Model Finetuning via Multistage Data Filtering [PDF]

open access: yesarXiv, 2022
As model finetuning is central to the modern NLP, we set to maximize its efficiency. Motivated by redundancy in training examples and the sheer sizes of pretrained models, we exploit a key opportunity: training only on important data. To this end, we set to filter training examples in a streaming fashion, in tandem with training the target model.
arxiv  

KMT2A degradation is observed in decitabine‐responsive acute lymphoblastic leukemia cells

open access: yesMolecular Oncology, EarlyView.
We demonstrate that decitabine (DEC) not only degrades the DNA methyltransferase DNMT1 but also the leukemic driver lysine methyltransferase KMT2A likely due to structural similarity of the DNA‐binding CXXC domains. DEC influences KMT2A downstream processes and synergizes with menin inhibitor revumenib (REV) to decrease leukemic cell proliferation, and
Luisa Brock   +10 more
wiley   +1 more source

A Novel DNN Training Framework via Data Sampling and Multi-Task Optimization [PDF]

open access: yesarXiv, 2020
Conventional DNN training paradigms typically rely on one training set and one validation set, obtained by partitioning an annotated dataset used for training, namely gross training set, in a certain way. The training set is used for training the model while the validation set is used to estimate the generalization performance of the trained model as ...
arxiv  

CAT:Collaborative Adversarial Training [PDF]

open access: yesarXiv, 2023
Adversarial training can improve the robustness of neural networks. Previous methods focus on a single adversarial training strategy and do not consider the model property trained by different strategies. By revisiting the previous methods, we find different adversarial training methods have distinct robustness for sample instances.
arxiv  

TRPM4 contributes to cell death in prostate cancer tumor spheroids, and to extravasation and metastasis in a zebrafish xenograft model system

open access: yesMolecular Oncology, EarlyView.
Transient receptor potential melastatin‐4 (TRPM4) is overexpressed in prostate cancer (PCa). Knockout of TRPM4 resulted in reduced PCa tumor spheroid size and decreased PCa tumor spheroid outgrowth. In addition, lack of TRPM4 increased cell death in PCa tumor spheroids.
Florian Bochen   +6 more
wiley   +1 more source

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