Branching Random Walks with Two Types of Particles on Multidimensional Lattices

We consider a continuous-time branching random walk on a multidimensional lattice with two types of particles and an infinite number of initial particles. The main results are devoted to the study of the generating function and the limiting behavior of the moments of subpopulations generated by a single particle of each type. We assume that particle types differ from each other not only by the laws of branching, as in multi-type branching processes, but also by the laws of walking. For a critical branching process at each lattice point and recurrent random walk of particles, the effect of limit spatial clustering of particles over the lattice is studied. A model illustrating epidemic propagation is also considered. In this model, we consider two types of particles: infected and immunity generated. Initially, there is an infected particle that can infect others. Here, for the local number of particles of each type at a lattice point, we study the moments and their limiting behavior. Additionally, the effect of intermittency of the infected particles is studied for a supercritical branching process at each lattice point. Simulations are presented to demonstrate the effect of limit clustering for the epidemiological model

Systematic evaluation of B-cell clonal family inference approaches

Abstract The reconstruction of clonal families (CFs) in B-cell receptor (BCR) repertoire analysis is a crucial step to understand the adaptive immune system and how it responds to antigens. The BCR repertoire of an individual is formed throughout life and is diverse due to several factors such as gene recombination and somatic hypermutation. The use of Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) using next generation sequencing enabled the generation of full BCR repertoires that also include rare CFs. The reconstruction of CFs from AIRR-seq data is challenging and several approaches have been developed to solve this problem. Currently, most methods use the heavy chain (HC) only, as it is more variable than the light chain (LC). CF reconstruction options include the definition of appropriate sequence similarity measures, the use of shared mutations among sequences, and the possibility of reconstruction without preliminary clustering based on V- and J-gene annotation. In this study, we aimed to systematically evaluate different approaches for CF reconstruction and to determine their impact on various outcome measures such as the number of CFs derived, the size of the CFs, and the accuracy of the reconstruction. The methods were compared to each other and to a method that groups sequences based on identical junction sequences and another method that only determines subclones. We found that after accounting for data set variability, in particular sequencing depth and mutation load, the reconstruction approach has an impact on part of the outcome measures, including the number of CFs. Simulations indicate that unique junctions and subclones should not be used as substitutes for CF and that more complex methods do not outperform simpler methods. Also, we conclude that different approaches differ in their ability to correctly reconstruct CFs when not considering the LC and to identify shared CFs. The results showed the effect of different approaches on the reconstruction of CFs and highlighted the importance of choosing an appropriate method

Flow cytometry for pediatric platelets

The ability of platelets to carry out their hemostatic function can be impaired in a wide range of inherited and acquired conditions: trauma, surgery, inflammation, pre-term birth, sepsis, hematological malignancies, solid tumors, chemotherapy, autoimmune disorders, and many others. Evaluation of this impairment is vitally important for research and clinical purposes. This problem is particularly pronounced in pediatric patients, where these conditions occur frequently, while blood volume and the choice of blood collection methods could be limited. Here we describe a simple flow cytometry-based screening method of comprehensive whole blood platelet function testing that was validated for a range of pediatric and adult samples (n = 31) in the hematology hospital setting including but not limited to: classic inherited platelet function disorders (Glanzmann’s thrombasthenia; Bernard-Soulier, Wiscott-Aldrich, and Hermasky-Pudlak syndromes, MYH9-dependent thrombocytopenia), healthy and pre-term newborns, acute and chronic immune thrombocytopenia, chronic lympholeukemia, effects of therapy on platelet function, etc. The method output includes levels of forward and side scatter, levels of major adhesion and aggregation glycoproteins Ib and IIb-IIIa, active integrins’ level based on PAC-1 binding, major alpha-granule component P-selectin, dense granule function based on mepacrine uptake and release, and procoagulant activity quantified as a percentage of annexin V-positive platelets. This analysis is performed for both resting and dual-agonist-stimulated platelets. Preanalytical and analytical variables are provided and discussed. Parameter distribution within the healthy donor population for adults (n = 72) and children (n = 17) is analyzed

Additional file 1 of Systematic evaluation of B-cell clonal family inference approaches

Additional file 1: Supplementary Figure 1. Data simulation pipeline. Simulation approach is an integration of ImmuneSim, Alakazam and SHazaM tools and equally use the data of CF groupings obtained from each of the 10 CF inference approaches. Supplementary Figure 2. Determination of the number of TP, TN, FP, and FN. Three simulated CFs (2 singletons) and two inferred CFs are shown. Supplementary Figure 3. Overall correlation between the log10(number of CFs) and the standardized sequence depth for all combinations of approach (except SCOPer; A7, A8) and dataset. Supplementary Figure 4. Overall trend between the log10(number of CFs) and the standardized mutation load for all combinations of approach (except SCOPer; A7, A8) and dataset. Supplementary Figure 5. Summary of significant pairwise comparisons between Approaches. Supplementary Figure 6. Number of TP, TN, FP, and FN cases produced by the ten approaches when applied to six samples from three simulated datasets (D10, D11, D12). Supplementary Figure 7. Normalized number of TP, TN, FP, and FN cases produced by the ten approaches when applied to six samples from three simulated datasets (D10, D11, D12)

Understanding repertoire sequencing data through a multiscale computational model of the germinal center

Sequencing of B-cell and T-cell immune receptor repertoires helps us to understand the adaptive immune response, although it only provides information about the clonotypes (lineages) and their frequencies and not about, for example, their affinity or antigen (Ag) specificity. To further characterize the identified clones, usually with special attention to the particularly abundant ones (dominant), additional time-consuming or expensive experiments are generally required. Here, we present an extension of a multiscale model of the germinal center (GC) that we previously developed to gain more insight in B-cell repertoires. We compare the extent that these simulated repertoires deviate from experimental repertoires established from single GCs, blood, or tissue. Our simulations show that there is a limited correlation between clonal abundance and affinity and that there is large affinity variability among same-ancestor (same-clone) subclones. Our simulations suggest that low-abundance clones and subclones, might also be of interest since they may have high affinity for the Ag. We show that the fraction of plasma cells (PCs) with high B-cell receptor (BcR) mRNA content in the GC does not significantly affect the number of dominant clones derived from single GCs by sequencing BcR mRNAs. Results from these simulations guide data interpretation and the design of follow-up experiments