Determining the relative contribution of retinal disparity and blur cues to ocular accommodation in Down syndrome

Individuals with Down syndrome (DS) often exhibit hypoaccommodation alongside accurate vergence. This study investigates the sensitivity of the two systems to retinal disparity and blur cues, establishing the relationship between the two in terms of accommodative-convergence to accommodation (AC/A) and convergence-accommodation to convergence (CA/C) ratios. An objective photorefraction system measured accommodation and vergence under binocular conditions and when retinal disparity and blur cues were removed. Participants were aged 6–16 years (DS n = 41, controls n = 76). Measures were obtained from 65.9% of participants with DS and 100% of controls. Accommodative and vergence responses were reduced with the removal of one or both cues in controls (p < 0.007). For participants with DS, removal of blur was less detrimental to accommodative responses than removal of disparity; accommodative responses being significantly better when all cues were available or when blur was removed in comparison to when proximity was the only available cue. AC/A ratios were larger and CA/C ratios smaller in participants with DS (p < 0.00001). This study demonstrates that retinal disparity is the main driver to both systems in DS and illustrates the diminished influence of retinal blur. High AC/A and low CA/C ratios in combination with disparity-driven responses suggest prioritisation of vergence over accurate accommodation

Pitfalls of vaccinations with WT1-, Proteinase3- and MUC1-derived peptides in combination with MontanideISA51 and CpG7909

T cells with specificity for antigens derived from Wilms Tumor gene (WT1), Proteinase3 (Pr3), and mucin1 (MUC1) have been demonstrated to lyse acute myeloid leukemia (AML) blasts and multiple-myeloma (MM) cells, and strategies to enhance or induce such tumor-specific T cells by vaccination are currently being explored in multiple clinical trials. To test safety and immunogenicity of a vaccine composed of WT1-, Pr3-, and MUC1-derived Class I-restricted peptides and the pan HLA-DR T helper cell epitope (PADRE) or MUC1-helper epitopes in combination with CpG7909 and MontanideISA51, four patients with AML and five with MM were repetitively vaccinated. No clinical responses were observed. Neither pre-existing nor naive WT1-/Pr3-/MUC1-specific CD8+ T cells expanded in vivo by vaccination. In contrast, a significant decline in vaccine-specific CD8+ T cells was observed. An increase in PADRE-specific CD4+ T helper cells was observed after vaccination but these appeared unable to produce IL2, and CD4+ T cells with a regulatory phenotype increased. Taken into considerations that multiple clinical trials with identical antigens but different adjuvants induced vaccine-specific T cell responses, our data caution that a vaccination with leukemia-associated antigens can be detrimental when combined with MontanideISA51 and CpG7909. Reflecting the time-consuming efforts of clinical trials and the fact that 1/3 of ongoing peptide vaccination trails use CpG and/or Montanide, our data need to be taken into consideration

FlowCT for the analysis of large immunophenotypic datasets and biomarker discovery in cancer immunology

Large-scale immune monitoring is becoming routinely used in clinical trials to identify determinants of treatment responsiveness, particularly to immunotherapies. Flow cytometry remains one of the most versatile and high throughput approaches for single-cell analysis; however, manual interpretation of multidimensional data poses a challenge when attempting to capture full cellular diversity and provide reproducible results. We present FlowCT, a semi-automated workspace empowered to analyze large data sets. It includes pre-processing, normalization, multiple dimensionality reduction techniques, automated clustering, and predictive modeling tools. As a proof of concept, we used FlowCT to compare the T-cell compartment in bone marrow (BM) with peripheral blood (PB) from patients with smoldering multiple myeloma (SMM), identify minimally invasive immune biomarkers of progression from smoldering to active MM, define prognostic T-cell subsets in the BM of patients with active MM after treatment intensification, and assess the longitudinal effect of maintenance therapy in BM T cells. A total of 354 samples were analyzed and immune signatures predictive of malignant transformation were identified in 150 patients with SMM (hazard ratio [HR], 1.7; P < .001). We also determined progression-free survival (HR, 4.09; P < .0001) and overall survival (HR, 3.12; P = .047) in 100 patients with active MM. New data also emerged about stem cell memory T cells, the concordance between immune profiles in BM and PB, and the immunomodulatory effect of maintenance therapy. FlowCT is a new open-source computational approach that can be readily implemented by research laboratories to perform quality control, analyze high-dimensional data, unveil cellular diversity, and objectively identify biomarkers in large immune monitoring studies. These trials were registered at www.clinicaltrials.gov as #NCT01916252 and #NCT02406144.© 2022 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved