Efgartigimod is a human IgG1 antibody Fc fragment that reduces IgG levels through neonatal Fc receptor blockade. This study evaluated whether efgartigimod affects the generation of T-cell-dependent antibodies and cellular immune responses to keyhole limpet hemocyanin (KLH) immunization in non-human primates. Cynomolgus monkeys received efgartigimod or vehicle control intravenously for 11 wk, followed by a recovery phase. KLH challenges occurred during both the dosing phase and the recovery phase. No statistically significant differences emerged in anti-KLH IgM levels between the efgartigimod and control groups. Likewise, comparable KLH-specific T cell responses were observed between groups. Anti-KLH IgG titers were lower in efgartigimod-treated animals compared with controls only after the first boost of KLH, coinciding with decreases in total IgG titers in efgartigimod-treated animals, and returned to baseline levels by the end of the recovery phase. Taken together, these results indicate that efgartigimod does not suppress T-cell-dependent antibody responses or antibody class-switching. The findings of this study are consistent with efgartigimod's pharmacological mechanism of action and suggest that efgartigimod does not impair the generation of effective immune responses.

Glioma is characterized by high heterogeneity and poor prognosis. Attempts have been made to understand its diversity in both genetic expressions and radiomic characteristics, while few integrated the two omics in predicting survival of glioma. This study was intended to investigate the connection between glioma imaging and genome, and examine its predictive value in glioma mortality risk and tumor immune microenvironment (TIME). Clinical, transcriptomics and radiomics data were obtained from public datasets and patients in our center. Correlation analysis between gene expression and radiomic feature (RF) was performed, followed by survival analysis to select RF-related genes (RFRGs) and gene expression-related RFs (GRRFs). After that, RFRGs and GRRFs were used to construct mortality risk prediction model of all glioma and isocitrate dehydrogenase (IDH) wild type (WT) glioma. The association between RFRGs and TIME was explored. Six cohorts composed of 1,754 glioma patients were included. Thirty-five genes and eighty-two RFs demonstrated high correlation with each other. Gene score based on RFRGs was independent predictor of both glioma (P < 0.05) and IDH-WT glioma (P < 0.05). Same score based on GRRFs was also able to stratify risk of both glioma (P < 0.0001) and IDH-WT glioma (P < 0.0001), with nomograms constructed separately. The TIME of gliomas predicted with RFRGs' score found mismatched risk of death with immune response. RFRGs and GRRFs were able to predict glioma mortality risk and TIME. Further studies could validate our results and explore this genome-imaging interactions.

Recent technological advances have introduced novel methods for measuring body composition, each with unique benefits and limitations. The choice of method often depends on the trade-offs between accuracy, cost, participant burden, and the ability to measure specific body composition compartments.

PI4KA-related disorder is a highly clinically variable condition characterized by neurological (limb spasticity, developmental delay, intellectual disability, seizures, ataxia, nystagmus) and gastrointestinal (inflammatory bowel disease and multiple intestinal atresia) manifestations. Although features consistent with immunodeficiency (autoimmunity/autoinflammation and recurrent infections) have been reported in a subset of patients, the burden of B-cell deficiency and hypogammaglobulinemia has not been extensively investigated. We sought to describe the clinical presentation and manifestations of patients with PI4KA-related disorder and to investigate the metabolic consequences of biallelic PI4KA variants in B cells.