Results 91 to 100 of about 477,715 (269)

CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification—leveraging deep learning models for enhanced diagnostic accuracy

BMC Cancer
Cervical cancer is a significant global health issue affecting women worldwide, necessitating prompt detection and effective management. According to the World Health Organization (WHO), approximately 660,000 new cases of cervical cancer and 350,000 ...
Zahra Taghados, Zohreh Azimifar, Malihezaman Monsefi, Mojgan Akbarzadeh Jahromi   +3 more
doaj   +1 more source

Causal Discovery from Changes

, 2013
Appears in Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI2001)
Tian, Jin, Pearl, Judea
openaire   +2 more sources

Transcriptional network analysis of PTEN‐protein‐deficient prostate tumors reveals robust stromal reprogramming and signs of senescent paracrine communication

Molecular Oncology, EarlyView.
Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice, Jose I. Lopez, Aitziber Ugalde‐Olano, Maite Zufiaurre, Ianire Astobiza, Natalia Martin‐Martin, Laura Bozal‐Basterra, Saioa Garcia‐Longarte, Amaia Zabala‐Letona, Sofia Rey, Aida Santos‐Martin, Miguel Unda, Ana Loizaga‐Iriarte, Mariona Graupera, Paolo Nuciforo, Arkaitz Carracedo, Isabel Mendizabal   +16 more
wiley   +1 more source

Dagma-DCE: Interpretable, Non-Parametric Differentiable Causal Discovery

IEEE Open Journal of Signal Processing
We introduce Dagma-DCE, an interpretable and model-agnostic scheme for differentiable causal discovery. Current non- or over-parametric methods in differentiable causal discovery use opaque proxies of “independence” to justify the inclusion
Daniel Waxman, Kurt Butler, Petar M. Djuric   +2 more
doaj   +1 more source

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

Molecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak, Karolina Pytlak, Sandra Jaworowska, Bogusz Kulawiak, Piotr Bednarczyk   +4 more
wiley   +1 more source

Structural gating and effect-aligned lag-resolved temporal causal discovery framework with application to heat–pollution extremes

Green Technologies and Sustainability
This study proposes Structural Gating and Effect-aligned Discovery for Temporal Causal Discovery (SGED-TCD), a novel and general framework for lag-resolved causal discovery in complex multivariate time series. SGED-TCD combines explicit structural gating,
Rui Chen, Jinsong Wu
doaj   +1 more source

PARP inhibition and pharmacological ascorbate demonstrate synergy in castration‐resistant prostate cancer

Molecular Oncology, EarlyView.
Pharmacologic ascorbate (vitamin C) increases ROS, disrupts cellular metabolism, and induces DNA damage in CRPC cells. These effects sensitize tumors to PARP inhibition, producing synergistic growth suppression with olaparib in vitro and significantly delayed tumor progression in vivo. Pyruvate rescue confirms ROS‐dependent activity.
Nicolas Gordon, Peter T. Gallagher, Orly I. Richter, Neermala Poudel Neupane, Amy C. Mandigo, Jennifer J. McCann, Emanuela Dylgjeri, Irina Vasilevskaya, Christopher McNair, Channing J. Paller, Wm. Kevin Kelly, Karen E. Knudsen, Matthew J. Schiewer, Ayesha A. Shafi   +13 more
wiley   +1 more source

Overcoming Confounding Bias in Causal Discovery Using Minimum Redundancy and Maximum Relevancy Constraint

IEEE Access
Causal discovery is the process of modeling cause and effect relationships among features. Unlike traditional model-based approaches, that rely on fitting data to the models, methods of causal discovery determine the causal structure from data.
Havisha Nadendla, Pujit Pavan Etha, Pradeep Chowriappa   +2 more
doaj   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

TRAIL‐PEG‐Apt‐PLGA nanosystem as an aptamer‐targeted drug delivery system potential for triple‐negative breast cancer therapy using in vivo mouse model

Molecular Oncology, EarlyView.
Aptamers are used both therapeutically and as targeting agents in cancer treatment. We developed an aptamer‐targeted PLGA–TRAIL nanosystem that exhibited superior therapeutic efficacy in NOD/SCID breast cancer models. This nanosystem represents a novel biotechnological drug candidate for suppressing resistance development in breast cancer.
Gulen Melike Demirbolat, Aslihan Kucuk, Omer Erdogan, Samed Ozer, Bensu Kozan, Tugba Cuceli, Erkan Gumus, Evrim Cevik, Ozge Cevik   +8 more
wiley   +1 more source