Results 81 to 90 of about 139,695 (308)

Dual PI3K/AKT and CDK4/6 inhibition reveals selective sensitivity in an SHH medulloblastoma stem cell model

Molecular Oncology, EarlyView.
Targeted therapy was evaluated in SHH medulloblastoma using neuroepithelial stem cell (NES) and tumor‐derived NES‐like (tNES) models in 2D monolayers and 3D spheroids. PI3K, AKT, and CDK4/6 inhibitors had minimal effects in NES but markedly reduced viability and growth and induced apoptosis in tNES cells, revealing distinct therapeutic vulnerabilities.
Monika Lukoseviciute, Madeleine Birgersson, Paolo Ceriani, Margareta Wilhelm, Ourania N Kostopoulou   +4 more
wiley   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

Molecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova, Michele Montrone, Uday Rangaswamy, Francesco Diversi, Irene Schiavo, Denise Ferrarini, Roberta Di Florio, Irene Longo, Michele Coscia, Nicola Zamboni, Giorgia Demontis, Lisa Veghini, Vincenzo Corbo, Remo Sanges, Paul Heppenstall   +14 more
wiley   +1 more source

Hijacking emergency granulopoiesis: Neutrophil ontogeny and reprogramming in cancer

Molecular Oncology, EarlyView.
Neutrophils are highly plastic innate immune cells; their functions in cancer extend beyond the tumour microenvironment. This Review summarises current understanding of neutrophil maturation and heterogeneity and highlights tumour‐induced granulopoiesis as a systemic programme that expands immature, immunosuppressive neutrophils via tumour‐derived ...
Gabriela Marinescu, Yi Feng
wiley   +1 more source

Using Dimensionality Reduction to Analyze Protein Trajectories

Frontiers in Molecular Biosciences, 2019
In recent years the analysis of molecular dynamics trajectories using dimensionality reduction algorithms has become commonplace. These algorithms seek to find a low-dimensional representation of a trajectory that is, according to a well-defined ...
Gareth A. Tribello, Piero Gasparotto
doaj   +1 more source

Interpreting the effects of DNA polymerase variants at the structural level

Molecular Oncology, EarlyView.
Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi, Karolina Krzesińska, Ludovica Beltrame, Pablo Sánchez‐Izquierdo Besora, Matteo Tiberti, Mef Nilbert, Anna Rohlin, Elena Papaleo   +7 more
wiley   +1 more source

Two-Stage Dimensionality Reduction for Social Media Engagement Classification

Applied Sciences
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira, Alisson Assis Cardoso   +2 more
doaj   +1 more source

Dimensionality Reduction Data Sets

, 2021
Benchmark data sets from various sources that can be used to test and compare dimensionality reduction ...
Igor Matheus Souza Moreira, Caio Marcos Flexa Rodrigues   +1 more
core   +1 more source

Proteasome inhibitor, ixazomib prevents topoisomerase‐I degradation and reverses irinotecan resistance in colorectal cancer

Molecular Oncology, EarlyView.
Ixazomib inhibits proteasome‐mediated degradation of topoisomerase I induced by irinotecan, thereby restoring drug sensitivity and promoting tumor cell death in colorectal cancer. Irinotecan, a topoisomerase I (topoI) inhibitor, is widely used for colorectal cancer, but resistance remains a major clinical challenge.
Yuho Ebata, Koji Ando, Hirofumi Hasuda, Koshi Mimori, Elizabeth C. Unan, Siddhartha Pulukuri, Aahana Tiku, Allison Berger, Eiji Oki, Ajit Bharti, Tomoharu Yoshizumi   +10 more
wiley   +1 more source

Dimensionality Reduction Algorithms on High Dimensional Datasets

Emitter: International Journal of Engineering Technology, 2014
Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible ...
Iwan Syarif
doaj   +3 more sources

Dimensionality Reduction and Feature Selection using a Mixed-norm Penalty Function

, 2006
Dimensionality reduction, which is the process of mapping high-dimension patterns to lower dimension subspaces, is a key issues in enhancing the processing efficiency of high dimensional data such as hyperspectral images.
Zeng, Huiwen
core