Psoriasis

Serum metabolic signatures are associated with anti-drug antibody development in rheumatoid arthritis patients treated with adalimumab

Development of anti-drug antibodies (ADAs) is a barrier to long-term efficacy of biologic therapies in rheumatoid arthritis (RA), but no biomarkers exist to predict ADA formation. This study explored the potential of serum metabolomics to predict development of ADAs to adalimumab in patients with RA. Serum from patients with RA (n=47), treatment naïve for tumour necrosis factor-alpha inhibitor the...

Epigenetic patient stratification reveals a sub-endotype of type 2 asthma with altered B-cell response

Despite biomarker-guided treatment strategies, clinical outcomes among patients with type 2 (T2)-high asthma remain heterogeneous, with some patients responding poorly to T2-targeted biologic therapies. We developed a contrastive machine learning method for patient stratification based on whole-blood DNA methylation (DNAm), applying it to pediatric asthma cohorts of Latino (discovery; n=1,016) and...

Unintended Pregnancy and Preterm Birth in the United States: Causal Inference and Risk Prediction Using National Survey of Family Growth Data

Unintended pregnancy remains common in high income countries and has been linked to poorer maternal and neonatal outcomes. Whether pregnancy intention...

Scaling genetic discovery for organ volumes using machine learning-assisted imputation and bias-corrected GWAS

MRI-derived organ and tissue volumes are powerful endophenotypes for studying complex disease, but their availability is limited by cost and throughpu...

Non-invasive epidermal proteomics and machine learning permits molecular subclassification of psoriasis and eczematous dermatitis

Current approaches to selecting molecularly targeted therapies (biologics and oral small molecules) for immune-mediated skin diseases largely overlook...

Mechanosensitive TRPV4 immunohistochemistry improves deep learning-based grading of ductal carcinoma in situ beyond H&E morphology

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer spanning a biologic continuum from atypical ductal hyperplasia (ADH) to high-grade les...

Identification and validation of shared biomarkers and drug repurposing in psoriasis and Crohn's disease: integrating bioinformatics, machine learning, and experimental approaches.

BACKGROUND: Psoriasis and Crohn's disease (CD) are chronic inflammatory diseases that involve complex immune-mediated mechanisms. Despite clinical ove...

Research on equipment fault diagnosis model based on gan and inverse PINN: Solutions for data imbalance and rare faults.

In the field of medical imaging equipment, fault diagnosis plays a vital role in guaranteeing stable operation and prolonging service life. Traditiona...

Inverse modeling, analysis and control of twin rotor aerodynamic systems with optimized artificial intelligent controllers.

This paper suggests a novel optimal inverse Radial Basis Function (RBF) neural network model for the control of Twin Rotor Aerodynamic Systems (TRAS),...

gRNAde: A Geometric Deep Learning Pipeline for 3D RNA Inverse Design.

Fundamental to the diverse biological functions of RNA are its 3D structure and conformational flexibility, which enable single sequences to adopt a v...

Solving Inverse Problems via Diffusion Optimal Control

Existing approaches to diffusion-based inverse problem solvers frame the signal recovery task as a probabilistic sampling episode, where the solutio...

LEDA: Log-Euclidean Diffeomorphic Autoencoder for Efficient Statistical Analysis of Diffeomorphism

Image registration is a core task in computational anatomy that establishes correspondences between images. Invertible deformable registration, whic...

DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation for High-quality 3D Asset Creation

Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet controlling it to produce desired shapes is difficult and ...

Uni-Renderer: Unifying Rendering and Inverse Rendering Via Dual Stream Diffusion

Rendering and inverse rendering are pivotal tasks in both computer vision and graphics. The rendering equation is the core of the two tasks, as an i...

Diffusion priors for Bayesian 3D reconstruction from incomplete measurements

Many inverse problems are ill-posed and need to be complemented by prior information that restricts the class of admissible models. Bayesian approac...

OTLRM: Orthogonal Learning-based Low-Rank Metric for Multi-Dimensional Inverse Problems

In real-world scenarios, complex data such as multispectral images and multi-frame videos inherently exhibit robust low-rank property. This property...

Stochastic Multiresolution Image Sketching for Inverse Imaging Problems

A challenge in high-dimensional inverse problems is developing iterative solvers to find the accurate solution of regularized optimization problems ...

Diffusion Model with Representation Alignment for Protein Inverse Folding

Protein inverse folding is a fundamental problem in bioinformatics, aiming to recover the amino acid sequences from a given protein backbone structu...

Fair Primal Dual Splitting Method for Image Inverse Problems

Image inverse problems have numerous applications, including image processing, super-resolution, and computer vision, which are important areas in i...

Efficient gradient-based methods for bilevel learning via recycling Krylov subspaces

Many optimization problems require hyperparameters, i.e., parameters that must be pre-specified in advance, such as regularization parameters and pa...