Effects of secukinumab on enthesiophyte and erosion progression in psoriatic arthritis -a one-year double-blind, randomized, placebo-controlled trial utilizing high-resolution peripheral quantitative computed tomography.

Objectives: This study aimed to ascertain the effect of secukinumab on erosion and enthesiophyte progression in psoriatic arthritis (PsA) by high-resolution peripheral quantitative computed tomography (HR-pQCT).

Methods: This was a phase 4, double-blind, randomized, placebo-controlled trial. Patients with active PsA and ≥ 1 erosion in the metacarpophalangeal joints (MCPJ) 2-4 were randomised in a 1:1 ratio to subcutaneous secukinumab or placebo.

OsCBL1 Modulates the Nitrate-Induced Phosphate Response by Altering OsNLP4 Cytoplasmic-Nucleus Shuttling.

Nitrate can directly activate phosphate (Pi) starvation signaling, ultimately promoting plant growth by enhancing phosphorus absorption and utilization and optimizing the balance of nitrogen and phosphorus nutrients. However, the complex mechanisms by which plants integrate complex nutrient signals from nitrogen to phosphorus are not well understood. This study highlights the importance of Calcineurin B-like protein-1 (OsCBL1), a calcium sensor, in coordinating nitrogen and phosphorus signaling in rice.

Decoding the ontogeny of myeloid lineage diversity by cross-species and developmental analyses of hematopoietic progenitor atlases.

Myeloid cells play vital roles in homeostasis and immune responses in vertebrates, but the developmental pathway underlying their lineage diversity remains elusive. Here, we construct a single-cell transcriptional map of myeloid progenitors from mouse bone marrow and conduct cross-species and developmental analyses across human, monkey, mouse, and zebrafish. We uncover a conserved specification program separating the eosinophil-basophil-mast cell (EBM) lineage and neutrophil-monocyte (NM) lineage, reclassifying myeloid cells beyond the conventional granulocytic and monocytic framework.

Mode Hypergraph Neural Network.

The hypergraph neural network (HGNN) is an emerging powerful tool for modeling and learning complex, high-order correlations among entities upon hypergraph structures. While existing HGNN-based approaches excel in modeling high-order correlations among data using hyperedges, they often have difficulties in distinguishing diverse semantics ( e.g.

Cellular blueprint of healthy and diseased human epiglottis and subglottis-a study of the Canadian Airways Research (CARE) group.

Background: The larynx consists of the supraglottis, glottis, and subglottis and each differ in tissue composition, lymphatic drainage, ability to counter infections, and response to injuries. However, the cellular mechanisms driving laryngeal homoeostasis remain largely unexplored. As a result, understanding disease pathogenesis within the larynx including idiopathic subglottic stenosis (iSGS) and intubation-related traumatic stenosis has been challenging.