Results 81 to 90 of about 5,727,475 (289)

Structure‐forward targeting of claudins with synthetic binders

FEBS Letters, EarlyView.
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley   +1 more source

Engineering peptides into antibodies—opportunities and strategies for therapeutic innovation

FEBS Letters, EarlyView.
Peptides and antibodies occupy complementary therapeutic niches. Peptides recognize difficult targets in a compact format, while antibodies add specificity, long half‐life, and effector functions. This review examines strategies that merge both modalities—peptide grafting into loops, terminal and Fc fusions, and bioconjugation—highlighting how ...
Jinling Wang, Ruslana Romaniuk, Hristo L. Svilenov   +2 more
wiley   +1 more source

AnchorFCI: harnessing genetic anchors for enhanced causal discovery of cardiometabolic disease pathways

Frontiers in Genetics
IntroductionCardiometabolic diseases, a major global health concern, stem from complex interactions of lifestyle, genetics, and biochemical markers. While extensive research has revealed strong associations between various risk factors and these diseases,
Adèle H. Ribeiro, Milena Crnkovic, Jaqueline Lopes Pereira, Regina Mara Fisberg, Flavia Mori Sarti, Marcelo Macedo Rogero, Dominik Heider, Andressa Cerqueira   +7 more
doaj   +1 more source

Liver organoids: modelling complexity in homeostasis and disease

FEBS Letters, EarlyView.
Studying liver in vitro has been challenging because simple 2D cell cultures fail to capture liver's cellular and architectural complexity. To bridge this gap, scientists increasingly use organoids, 3D liver models which better mimic liver composition and function. This review examines recent advances in liver organoid complexity and realism, discusses
Anna M. Dowbaj, Meritxell Huch
wiley   +1 more source

A Structure-Preserving Power-Adaptive Colored-Noise Kalman Filtering Algorithm for Four-Wire Pendulum Velocity Monitoring

Algorithms
Ground testing of space-based gravitational-wave missions requires causal and low-noise horizontal-velocity estimation for vibration-isolation platforms. Fixed sensor fusion becomes suboptimal when sensor noise power varies, especially when complementary
Dehui Meng, Yongkun Chen, Tao Yu, Huadong Li, Qi Li, Zhi Wang   +5 more
doaj   +1 more source

Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry

FEBS Letters, EarlyView.
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri, Ayaka Nagasato‐Ichikawa, Keita Iida, Shuhei Kimura, Akira Imamoto, Mariko Okada   +5 more
wiley   +1 more source

Optimizing wind energy production using explainable AI and causal machine learning

Discover Artificial Intelligence
Wind energy is a key pillar of the global transition toward clean and low-carbon power, and improving wind turbine performance using existing infrastructure has become increasingly important.
Priyadharshini Rengasamy, R. Rajesh
doaj   +1 more source

Value Mining of Power Grid Technology Resource Demand by Integrating Causal-Inference-Spatio- Temporal Graph Neural Network

IEEE Access
The traditional spatio-temporal graph neural networks have challenges such as false correlation interference in the power grid scenarios, insufficient granularity of spatio-temporal dynamic modeling, and lack of causal interpretability.
Fangquan Wu, Chengjia Tang
doaj   +1 more source

Prediction-Powered Causal Inferences

In many scientific experiments, the data annotating cost constraints the pace for testing novel hypotheses. Yet, modern machine learning pipelines offer a promising solution, provided their predictions yield correct conclusions. We focus on Prediction-Powered Causal Inferences (PPCI), i.e., estimating the treatment effect in an unlabeled target ...
Cadei, Riccardo, Demirel, Ilker, De Bartolomeis, Piersilvio, Lindorfer, Lukas, Cremer, Sylvia, Schmid, Cordelia, Locatello, Francesco   +6 more
openaire   +3 more sources

The Causal Power of Social Structures

, 2010
The problem of structure and agency has been the subject of intense debate in the social sciences for over 100 years. This book offers a solution. Using a critical realist version of the theory of emergence, Dave Elder-Vass argues that, instead of ...
Dave Elder-Vass
core   +1 more source