Impact of bronchiectasis severity on clinical outcomes in patients with allergic bronchopulmonary aspergillosis: a retrospective cohort study.

Background: The impact of bronchiectasis severity on the outcomes of patients with allergic bronchopulmonary aspergillosis (ABPA) remains uncertain.

Objective: To evaluate whether bronchiectasis severity is associated with an increased risk of ABPA exacerbations.

Methods: We retrospectively analyzed ABPA patients between 2007 and 2019.

High Risk of Graft Rejection in Patients with HLA Homozygosity Following Haploidentical Transplant Using Post-Transplant Cyclophosphamide.

Graft rejection is an important concern following haploidentical transplant with a reported incidence of 10-15%. The number of human leukocyte antigen (HLA) mismatches and the vector of mismatch have not been found to be associated with the risk of graft rejection in haploidentical transplants. Patients with HLA homozygosity at all loci (HLA-A, B, C, DRB1, and DQB1) undergoing haploidentical transplant is a rare scenario that results in zero mismatches in the graft-versus-host (GvH) direction and 2-5 mismatches in the host-versus-graft (HvG) direction depending on the donor haplotype.

A review on biomacromolecular ligand-directed nanoparticles: New era in macrophage targeting.

Traditional drug delivery strategies often have side effects due to uneven drug distribution leading to the subtherapeutic impacts. Ligand-modified nanoparticles offer a revolutionary approach to precise drug delivery. These modified nanoparticles can potentially target macrophages, which is crucial for defense and disease progression efficiently.

Haploinsufficiency of ITSN1 is associated with a substantial increased risk of Parkinson's disease.

Despite its significant heritability, the genetic basis of Parkinson's disease (PD) remains incompletely understood. Here, in analyzing whole-genome sequence data from 3,809 PD cases and 247,101 controls in the UK Biobank, we discover that protein-truncating variants in ITSN1 confer a substantially increased risk of PD (p = 6.1 × 10; odds ratio [95% confidence interval] = 10.

Reliability Analysis of Psychological Concept Extraction and Classification in User-penned Text.

The social NLP research community witness a recent surge in the computational advancements of mental health analysis to build responsible AI models for a complex interplay between language use and self-perception. Such responsible AI models aid in quantifying the psychological concepts from user-penned texts on social media. On thinking beyond the low-level () task, we advance the existing binary classification dataset, towards a higher-level task of reliability analysis through the lens of explanations, posing it as one of the safety measures.