Results 81 to 90 of about 131,864 (294)

Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma

Molecular Oncology, EarlyView.
Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra, Lucca Paolo Hsu Helmich, Daniel Rodrigues de Bastos, Laura Sichero, Patrícia Savio de Araujo‐Souza, Fabio Passetti, Luisa Lina Villa   +6 more
wiley   +1 more source

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

Molecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang, Ayesha Alvero, Yi Qin, Mingjin Wang, Alexandra Fox, Yanfeng Li, Michael Millman, Amy Kemper, Gil Mor, Xian Shuang Liu, Michael Chopp, Zheng Gang Zhang, Yi Zhang   +12 more
wiley   +1 more source

Bellwethers: A Baseline Method For Transfer Learning

, 2018
Software analytics builds quality prediction models for software projects. Experience shows that (a) the more projects studied, the more varied are the conclusions; and (b) project managers lose faith in the results of software analytics if those results
Krishna, Rahul, Menzies, Tim
core   +1 more source

Keratin 19 as a prognostic marker and contributing factor of metastasis and chemoresistance in high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Keratin 19 (KRT19) is overexpressed in high‐grade serous ovarian cancer with high levels of Kallikrein‐related peptidases (KLK) 4–7 and is associated with poor survival. In vivo analyses demonstrate that elevated KRT19 increases peritoneal tumour burden.
Sophia Bielesch, Isabel Vogel, Sina Nokodian, Johanna Moeller, Antonia Blechschmidt, Vicky Hecht, Vanessa Kuentzel, Katharina Thiedig, Melissa Schwab, Oliver Schilling, Holger Bronger, Marion Kiechle, Viktor Magdolen, Tobias Dreyer   +13 more
wiley   +1 more source

Fault Localization Models in Debugging

, 2018
Debugging is considered as a rigorous but important feature of software engineering process. Since more than a decade, the software engineering research community is exploring different techniques for removal of faults from programs but it is quite ...
Alansari, Zainab, Belgaum, Mohammad Riyaz, Miraz, Mahdi H., Soomro, Safeeullah   +3 more
core   +1 more source

Somatic mutational landscape in von Hippel–Lindau familial hemangioblastoma

Molecular Oncology, EarlyView.
The causes of central nervous system (CNS) hemangioblastoma in Von Hippel–Lindau (vHL) disease are unclear. We used Whole Exome Sequencing (WES) on familial hemangioblastoma to investigate events that underlie tumor development. Our findings suggest that VHL loss creates a permissive environment for tumor formation, while additional alterations ...
Maja Dembic, Anne Nørremølle, Lilian Bomme Ousager, Lars van Brakel Andersen, Marie Louise Mølgaard Binderup, Mads Thomassen   +5 more
wiley   +1 more source

DP-CCL: A Supervised Contrastive Learning Approach Using CodeBERT Model in Software Defect Prediction

IEEE Access
Software Defect Prediction (SDP) reduces the overall cost of software development by identifying the code at a higher risk of defects at the initial phase of software development.
Sadia Sahar, Muhammad Younas, Muhammad Murad Khan, Muhammad Umer Sarwar   +3 more
doaj   +1 more source

A Combined-Learning Based Framework for Improved Software Fault Prediction

International Journal of Computational Intelligence Systems, 2017
Software Fault Prediction (SFP) is found to be vital to predict the fault-proneness of software modules, which allows software engineers to focus development activities on fault-prone modules, thereby prioritize and optimize tests, improve software ...
Chubato Wondaferaw Yohannese, Tianrui Li
doaj   +1 more source

Establishment of a humanized patient‐derived xenograft mouse model of high‐grade serous ovarian cancer for preclinical evaluation of combination immunotherapy

Molecular Oncology, EarlyView.
We have established a humanized orthotopic patient‐derived xenograft (Hu‐oPDX) mouse model of high‐grade serous ovarian cancer (HGSOC) that recapitulates human tumor–immune interactions. Using combined anti‐PD‐L1/anti‐CD73 immunotherapy, we demonstrate the model's improved biological relevance and enhanced translational value for preclinical ...
Luka Tandaric, Line Bjørge, Martine Rott Lode, Cecilie Fredvik Torkildsen, Pia Aehnlich, Rammah Elnour, Daniela Elena Costea, Lars Andreas Akslen, Liv Cecilie Vestrheim Thomsen, Emmet McCormack, Katrin Kleinmanns   +10 more
wiley   +1 more source

Semi-Supervised Deep Fuzzy C-Mean Clustering for Software Fault Prediction

IEEE Access, 2018
Software fault prediction is a consequential research area in software quality promise. In this paper, we propose a semi-supervised deep fuzzy C-mean (DFCM) clustering for software fault prediction, which is the cumulation of semi-supervised DFCM ...
Ali Arshad, Saman Riaz, Licheng Jiao, Aparna Murthy   +3 more
doaj   +1 more source