Immune responses to disease are complex and the only way to understand such a response is to consider the behavior of multiple different cell types across both the innate and adaptive branches of the immune system. We developed Barcode Enabled Antigen Mapping (BEAM) technology to enable easy enrichment of antigen-specific cells. This technology is fully integrated with the 10x Genomics Chromium Single Cell Immune Profiling Solution to allow multimodal evaluation of immune cells including full-length, paired sequences of T and B cell receptor genes while simultaneously screening their specificity for a set of genes. Our antigen-specific TCR workflow (BEAM-T) identifies antigen-specific CD8+T cells. We demonstrate the assay’s performance with spike-in experiments using various percentages of HLA-A*02:01-restricted peptide-stimulated T cells (targeted mixture being 40% T cells with specificity for cytomegalovirus peptide, 10% T cells with specificity for flu peptide and 0–5% anti-SARS-CoV-2 T cells) into a background of human PBMCs. Cells were labeled with a panel of five viral pathogen peptide-loaded multimers, plus a HLA-A*02:01 negative control peptide to assess antigen specificity and were then sorted for CD8+PE+ T cells. We demonstrated that the major VDJ-T clonotypes identified for the SARS-CoV2 cells were retained, albeit with roughly proportionally fewer cells, as the percentage of spiked cells decreased. We further feature the robustness of the protocol with various sample types and models including H2Kb-restricted OT-1 transgenic mouse splenocytes, as well as healthy human donor PBMCs and dissociated tumor cells to demonstrate the utility of an integrated reagent-to-data analysis offering across a range of samples.

The appearance of an incommensurate charge density wave vector $\textbf{Q} = (Q_x,Q_y)$ on multiband intermetallic systems presenting commensurate charge density wave (CDW) and superconductivity (SC) orders is investigated. We consider a two-band model in a square lattice, where the bands have distinct effective masses. The incommensurate CDW (inCDW) and CDW phases arise from an interband Coulomb repulsive interaction, while the SC emerges due to a local intraband attractive interaction. For simplicity, all the interactions, the order parameters and hybridization between bands are considered $\textbf{k}$-independent. The multiband systems that we are interested are intermetallic systems with a $d$-band coexisting with a large $c$-band, for which a mean-field approach has proved suitable. We obtain the eigenvalues and eigenvectors of the Hamiltonian numerically and minimize the free energy density with respect to the diverse parameters of the model by means of the Hellmann-Feynman theorem. We investigate the system in real as well as momentum space and we find an inCDW phase with wave vector $\textbf{Q} = (\pi, Q_y) = (Q_x, \pi)$. Our numerical results show that the arising of an inCDW state depends on parameters, such as the magnitude of the inCDW and CDW interactions, band filling, hybridization and the relative depth of the bands. In general, inCDW tends to emerge at low temperatures, away from half-filling. We also show that, whether the CDW ordering is commensurate or incommensurate, large values of the relative depth between bands may suppress it. We discuss how each parameter of the model affects the emergence of an inCDW phase.

Multi-analyte single cell technologies have potential to greatly accelerate antibody discovery by identifying antigen-specific B cells. Barcode Enabled Antigen Mapping (BEAM) provides a high-throughput, multimodal analysis of antigen-bound B cells (BEAM-Ab) using 10x Genomics Chromium Single Cell Immune Profiling v2 Solution and novel computational approaches to discover B-cell receptor (BCR) sequences for further functional characterization. To demonstrate the antigen sensitivity of BEAM-Ab, we spiked in 5% Hen Egg Lysozyme (HEL) and 5% gp120 transgenic B cells in 90% wild type non-transgenic splenocytes. The cells were screened using a panel of barcoded antigens and then CD19+PE+ (antigen+) B cells were isolated using flow cytometry. Single cell gene expression, BCR, and antigen barcode analysis indicated clonotype specificity to the respective antigens in the sorted cells. Furthermore, we demonstrated BEAM-Ab specificity by analyzing a convalescent COVID patient sample against an antigen panel containing five different COVID antigens and a negative control. Analysis of this COVID sample suggests the clonal expansion of B cells recognizing the ectodomain of the wild type SARS-CoV2 spike protein, receptor binding domain of spike protein, and the ectodomain of the D614G mutant spike protein. We did not observe any clonal expansion to Omicron-specific antigen or the non-specific negative control in our dataset. Our data demonstrates that BEAM-Ab is an effective antibody discovery tool. BEAM-Ab unlocks the ability to rapidly screen large numbers of samples with an accurate single cell resolution and antigen specificity, with the entire workflow generating the candidate sequences just one week after sample processing.

Humans who have recovered from infectious disease possess a memory B cell pool that contains highly-potent antibodies against the cleared pathogenic agent. This pool is a valuable source of therapeutic antibodies but identifying these requires a method that can screen a large number of cells rapidly to identify promising candidates. We used Barcode Enabled Antigen Mapping (BEAM) to screen 100 million peripheral blood mononuclear cells (PBMCs) from a donor who had recovered from COVID-19. This method labels antigens of interest with unique reporter oligonucleotides and uses these labeled antigens to stain lymphocytes according to the binding specificity of their antigen receptors. Individual antigen-bound cells are then captured and analysed using the 10x Genomics Single Cell Immune Profiling Solution. This allows us to identify the antigen-specific cells while also generating transcriptomic profiles and natively paired, heavy and light chain full-length B-cell receptor sequences from each cell. We used BEAM to identify B cells that bound to the spike protein of SARS-CoV-2 and discovered 222 antibodies with high binding affinity confirmed by SPR. The majority of these antibodies bound to multiple variants of concern with some also recognising endemic coronaviruses. We then investigated the potential for these antibodies to neutralize live SARS-CoV-2 and confirmed that 55 exhibited potent neutralization activity. Finally, we performed epitope binning and discovered that the collection of antibodies bound to multiple different epitopes on the spike protein. Compared with hybridoma or other approaches, single cell methods have the potential to discover therapeutic antibodies more rapidly and with a higher diversity of leads.

BackgroundDespite years of studies and effort, the best strategies for treating prostate cancer and minimizing the complications of treatment remain unanswered questions. This gap in knowledge is partially due to the inability to dissect the complex heterogeneous tumor microenvironment (TME) and immune compartment. Spatially resolved molecular profiling of tumor sections will enhance our understanding of these complexities; However, it has been particularly challenging to do spatial molecular profiling in formalin-fixed paraffin-embedded (FFPE) tissues due to RNA degradation associated with this tissue-embedding method, which is routinely used in oncology workflows. The 10x Genomics Visium Spatial Gene Expression Solution for FFPE tissue overcomes these limitations, enabling spatial gene expression analysis of FFPE tissues combined with classical histology staining techniques such as Hematoxylin & Eosin (H&E) staining and immunofluorescence.MethodsWe used the 10x Genomics Visium Spatial Gene Expression Solution for FFPE tissue to analyze and resolve tumorigenic profiles in sections of normal and adenocarcinoma prostate samples. This assay incorporates ~5,000 molecularly barcoded, spatially encoded capture probes in spots over which the tissue is placed, imaged, and permeabilized. Imaging and sequencing data are processed together, resulting in a spatially resolved transcriptional readout.ResultsWe profiled the whole transcriptome in normal, invasive adenocarcinoma, and acinar cell carcinoma FFPE human prostate tissues. Unsupervised clustering of the whole transcriptome data from normal, invasive adenocarcinoma, and acinar cell prostate carcinoma FFPE sections enabled the identification of 2 different regions, which had a well defined spatial distribution within the tissues. Well known prostate gland and prostate-cancer markers were over-expressed in the corresponding healthy and cancerous portions of the tissue, validating the performance of this method. We found that, while in healthy tissues basal cells and luminal cells are spatially organized, this pattern is lost in tumor samples, where luminal cells are greatly expanded in the invasive carcinoma region and do not colocalize with basal cells. Moreover, T lymphocytes are dispersed throughout the whole tissue section in the adenocarcinoma, while plasma B cells are located in the peritumoral region which could impact prognosis.ConclusionsSpatial whole transcriptome analysis opens new opportunities for better understanding the TME which can not only help discover novel predictive tumor biomarkers, but also enable identifying cell type and tumor region specific drug targets.

Barcoding strategies are fundamental to droplet-based single-cell sequencing, and understanding the biases and caveats between approaches is essential. Here, we comprehensively evaluated both short and long reads of the cDNA obtained through the two marketed approaches from 10x Genomics, the “3’ assay” and the “5’ assay”, which attach barcodes at different ends of the mRNA molecule. Although the barcode detection, cell-type identification, and gene expression profile are similar in both assays, the 5’ assay captured more exonic molecules and fewer intronic molecules compared to the 3’ assay. We found that 13.7% of genes sequenced have longer average read lengths and are more complete (spanning both polyA-site and TSS) in the long reads from the 5’ assay compared to the 3’ assay. These genes are characterized by long average transcript length, high intron number, and low expression overall. Despite these differences, cell-type-specific isoform profiles observed from the two assays remain highly correlated. This study provides a benchmark for choosing the single-cell assay for the intended research question, and insights regarding platform-specific biases to be mindful of when analyzing data, particularly across samples and technologies.

A more complete understanding of immune responses to disease requires consideration of multiple different cell types across both the innate and adaptive branches of the immune system along with the detection of many different analytes. We used Barcode Enabled Antigen Mapping (BEAM) and Immune Profiling technology to perform simultaneous multimodal profiling at single cell resolution in hundreds of thousands of peripheral blood mononuclear cells (PBMCs) from a human donor following recovery from COVID-19. In addition to measuring gene and protein expression, we generated full-length, paired sequences of the rearranged T- and B-cell receptors while also screening their specificity for a wide range of antigens from SARS-CoV-2 and other viral pathogens. These data provide insights into the entirety of the immune landscape after recovery from acute viral disease. The scale and throughput of our experiments gave us high-resolution data from all cell types from the innate and adaptive immune systems. We identified antigen-specific clones of both B and T lymphocytes, with the high cellular throughput enabling detection of rare clones. Analysis of all PBMC cell types allowed us to place these antigen-specific clones within the overall transcriptional landscape of the post-viral immune system. Experiments such as these will underpin new systems immunology approaches and will continue to reveal the complex interplay between the components of the immune system. We envisage that these methods will be valuable in the analysis of the immune response to vaccination, infectious disease, cancer, allergy, autoimmune conditions, and ageing that can potentially lead to the development of novel diagnostic and therapeutic approaches.

Half a billion years of evolutionary battle forged the vertebrate adaptive immune system, an astonishingly versatile factory for molecules that can adapt to arbitrary attacks. The history of an individual encounter is chronicled within a clonotype: the descendants of a single fully rearranged adaptive immune cell. For B cells, reading this immune history for an individual remains a fundamental challenge of modern immunology. Identification of such clonotypes is a magnificently challenging problem for three reasons: It is thus impossible to determine clonotypes exactly. All solutions to this problem make a trade-off between sensitivity and specificity; useful solutions must address actual artifacts found in real data. We present enclone [1][1] , a system for computing approximate clonotypes from single cell data, and demonstrate its use and value with the 10x Genomics Immune Profiling Solution. To test it, we generate data for 1.6 million individual B cells, from four humans, including deliberately enriched memory cells, to tax the algorithm and provide a resource for the community. We analytically determine the specificity of enclone ’s clonotyping algorithm, showing that on this dataset the probability of co-clonotyping two unrelated B cells is around 10−9. We prove that using only heavy chains increases the error rate by two orders of magnitude. enclone comprises a comprehensive toolkit for the analysis and display of immune receptor data. It is ultra-fast, easy to install, has public source code, comes with public data, and is documented at [bit.ly/enclone][2]. It has three “flavors” of use: (1) as a command-line tool run from a terminal window, that yields visual output; (2) as a command-line tool that yields parseable output that can be fed to other programs; and (3) as a graphical version (GUI). ### Competing Interest Statement The authors were employees and shareholders of 10x Genomics, Inc at the time of publication. D.B.J. and W.J.M. are inventors on multiple patent applications assigned to 10x Genomics, Inc. related to algorithms and visualization schemas described and displayed in this manuscript. W.J.M., P.S., B.A.A., and D.B.J. are inventors on multiple patent applications assigned to 10x Genomics, Inc. related to technologies for the study of the adaptive immune repertoire. [1]: #fn-3 [2]: http://bit.ly/enclone

The vertebrate adaptive immune system modifies the genome of individual B cells to encode antibodies that bind particular antigens 1 . In most mammals, antibodies are composed of heavy and light chains that are generated sequentially by recombination of V, D (for heavy chains), J and C gene segments. Each chain contains three complementarity-determining regions (CDR1–CDR3), which contribute to antigen specificity. Certain heavy and light chains are preferred for particular antigens 2 – 22 . Here we consider pairs of B cells that share the same heavy chain V gene and CDRH3 amino acid sequence and were isolated from different donors, also known as public clonotypes 23 , 24 . We show that for naive antibodies (those not yet adapted to antigens), the probability that they use the same light chain V gene is around 10%, whereas for memory (functional) antibodies, it is around 80%, even if only one cell per clonotype is used. This property of functional antibodies is a phenomenon that we call light chain coherence. We also observe this phenomenon when similar heavy chains recur within a donor. Thus, although naive antibodies seem to recur by chance, the recurrence of functional antibodies reveals surprising constraint and determinism in the processes of V(D)J recombination and immune selection. For most functional antibodies, the heavy chain determines the light chain.

Background The adaptive immune system identifies foreign antigens based on a series of highly specific interactions involving multiple immune cell types. Identifying the exact mechanisms of said interactions can be difficult to achieve using bulk sequencing methods due to poor resolution. Single cell sequencing offers the ability to match a specific antigen to an immune cell receptor sequence at the cellular level. Methods We used Barcode Enabled Antigen Mapping (BEAM) and Single Cell Immune Profiling technology to profile hundreds of thousands of human peripheral blood mononuclear cells (PBMCs) from a donor following their recovery from COVID-19. These cells were screened for potential binding interactions with multiple antigens from SARS-CoV-2 and other viral pathogens. Sequencing data were also generated for gene expression and paired sequences for both BCRs and TCRs. Results The combination of these two techniques allowed us to identify a number of antigen-specific clonotypes of T cells and B cells. The high throughput of the experiment allowed us to gain understanding on a global scale of the state of the immune system following recovery from a COVID-19 infection, as well as to identify potentially rare clonotypes that may not have been discerned from a smaller sample size. Conclusions This experiment demonstrates the ability of BEAM to both profile the entire immune system at the cellular level at a given point in time as well as distinguish specific antigen-receptor interactions with the same resolution. Insights provided by similar experiments could be invaluable in the creation of precision cell therapies for use in cancer treatment, as well as the development of vaccines and analysis of allergic and autoimmune responses.

Continued advances in single cell gene detection sensitivity and the ability to analyze data quickly with biological context are critical for discoveries in therapeutic research. The second version of the Chromium Single Cell Immune Profiling Solution by 10x Genomics enables highly sensitive detection of gene expression, full-length paired T-cell alpha- and beta-chain and immunoglobulin sequences, T-cell antigen specificity, and cell surface protein expression from the same single cells, allowing a comprehensive view of the immune response at the cellular level. The new workflow provides a 45% increase in the number of genes detected per cell and up to a 25% increase in the cells detected with paired full-length V(D)J receptor sequences in melanoma tumor derived cells. Using a new version of Cell Ranger (v5.0), clonotypes were grouped from >30,000 cells, increasing the power to detect small clonotype expansions with fewer total cells. In addition, the new software enabled comparison of pre- and post-influenza vaccination B-cell receptor sequences from a single donor, identifying post-vaccination specific clonotypes. These technological and informatics advancements enhance a researcher’s ability to perform a broad characterization of immune cell populations at unprecedented throughput and resolution.

Nei Lopes, ∗ Daniel Reyes, † Mucio A. Continentino, and Christopher Thomas ‡ Departamento de F́ısica Teórica, Universidade do Estado do Rio de Janeiro, Rua São Francisco Xavier 524, Maracanã, 20550-013, Rio de Janeiro, RJ, Brazil Instituto Militar de Engenharia Praça General Tibúrcio, 80, 22290-270, Praia Vermelha, Rio de Janeiro, Brazil Centro Brasileiro de Pesquisas F́ısicas, Rua Dr. Xavier Sigaud 150, Urca, 22290-180, Rio de Janeiro , Brazil Departamento de F́ısica, Universidade Federal Rural do Rio de Janeiro, 23897-000, Seropédica, Rio de Janeiro, Brazil (Dated: March 23, 2021)

Profiling the complex interactions of immune infiltrate with tumor cells in a tumor microenvironment is critical for advancing our understanding of tumor biology for developing personalized cancer therapies. Using a droplet-based single cell RNA sequencing (scRNA-seq) platform, we profiled the transcriptome and immune repertoire of gastric, kidney, and lung cancer cells that are primarily immune cells from three different donors. scRNA-seq analysis also identified similar fractions of CD45+ immune cells, CD4+ and CD8+ T cells, CD19+ B cells, and myeloid cells compared to flow. Targeted scRNA-seq was also used to identify paired, full length B-cell (BCR) and T-cell (TCR) receptors. In the gastric adenocarcinoma tumor cells, gene expression analysis identified a large population of B cells, but with no clonal expansion. T cells expressing CD8A constituted about 10% of cells with the top clonotype being 1% of all clones. The clear cell RCC sample had a modest fraction of infiltrating T cells with the top clonotype representing 7.4% of all clones, and no B cell infiltrate. The NSCLC cells were mainly T and B cells but limited clonal expansion was observed; the top TCR clonotype was present on 2.2% of all T cells, no expansion was seen in any of the B cell clonotypes. These findings highlight the value of profiling of tumor immune cells holistically and not relying on the presence of B or T cells alone to understand the immune dynamics of the tumor microenvironment. The presence of tumor-infiltrating lymphocytes is associated with favorable clinical outcomes in some cancers, but understanding their cellular subtype and clonality by high resolution profiling is key in the development of immune-based cancer treatments

Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging human pathogen, endemic in areas of China, Japan, and the Korea (KOR). It is primarily transmitted through infected ticks and can cause a severe hemorrhagic fever disease with case fatality rates as high as 30%. Despite its high virulence and increasing prevalence, molecular and functional studies in situ are scarce due to the limited availability of high-titer SFTSV exposure stocks. During the course of field virologic surveillance in 2017, we detected SFTSV in ticks and in a symptomatic soldier in a KOR Army training area. SFTSV was isolated from the ticks producing a high-titer viral exposure stock. Through the use of advanced genomic tools, we present here a complete, in-depth characterization of this viral stock, including a comparison with both the virus in its arthropod source and in the human case, and an in vivo study of its pathogenicity. Thanks to this detailed characterization, this SFTSV viral exposure stock constitutes a quality biological tool for the study of this viral agent and for the development of medical countermeasures, fulfilling the requirements of the main regulatory agencies.

In the present work we study the effect of the aperiodic exchange modulation on the spin gap at finite temperature as well as the specific heat of the Kondo necklace model in two and three dimensions. For this purpose, we use a representation for the localized and conduction electrons in terms of local Kondo singlet and triplet operators. A decoupling scheme on the double time Green's functions is also used to find the dispersion relation for the excitations of the system. The influence of the aperiodic exchange modulation on the spin gap at low temperatures is discussed in the paramagnetic phase. Moreover, we investigate the specific heat as a function of the aperiodic exchange modulation at low temperatures in two cases: above the quantum critical point i.e., along the so-called non-Fermi liquid trajectory and in the Kondo spin liquid state. We have also compared our results with previous bond operator mean-field calculations.

In this paper, we study a two-band model of a superconductor in a square lattice. One band is narrow in energy and includes local Coulomb correlations between its quasiparticles. Pairing occurs in this band due to nearest-neighbor attractive interactions. Extended s-wave as well as d-wave symmetries of the superconducting order parameter are considered. The correlated electrons hybridize with those in another wide conduction band through a k-dependent mixing with even or odd parity depending on the nature of the orbitals. The many-body problem is treated within a slave-boson approach that has proved adequate to deal with the strong electronic correlations that are assumed here. Since applied pressure changes mostly the ratio between hybridization and bandwidths, we can use this ratio as a control parameter to obtain the phase diagrams of the model. We find that, for a wide range of parameters, the critical temperature increases as a function of hybridization (pressure) with a region of first-order transitions. When frustration is introduced, it gives rise to a stable superconducting phase. We find that superconductivity can be suppressed for specific values of band filling due to the Coulomb repulsion. We show how pressure, composition, and strength of correlations affect the superconductivity for different symmetries of the order parameter and the hybridization.

Background An alarming rise in reported Lassa fever cases continues in west Africa. Liberia has the largest reported per capita incidence of Lassa fever cases in the region, but genomic information on the circulating strains is scarce. The aim of this study was to substantially increase the available pool of data to help foster the generation of targeted diagnostics and therapeutics. Methods Clinical serum samples collected from 17 positive Lassa fever cases originating from Liberia (16 cases) and Guinea (one case) within the past decade were processed at the Liberian Institute for Biomedical Research using a targeted-enrichment sequencing approach, producing 17 near-complete genomes. An additional 17 Lassa virus sequences (two from Guinea, seven from Liberia, four from Nigeria, and four from Sierra Leone) were generated from viral stocks at the US Centers for Disease Control and Prevention (Atlanta, GA) from samples originating from the Mano River Union (Guinea, Liberia, and Sierra Leone) region and Nigeria. Sequences were compared with existing Lassa virus genomes and published Lassa virus assays. Findings The 23 new Liberian Lassa virus genomes grouped within two clades (IV.A and IV.B) and were genetically divergent from those circulating elsewhere in west Africa. A time-calibrated phylogeographic analysis incorporating the new genomes suggests Liberia was the entry point of Lassa virus into the Mano River Union region and estimates the introduction to have occurred between 300-350 years ago. A high level of diversity exists between the Liberian Lassa virus genomes. Nucleotide percent difference between Liberian Lassa virus genomes ranged up to 27% in the L segment and 18% in the S segment. The commonly used Lassa Josiah-MGB assay was up to 25% divergent across the target sites when aligned to the Liberian Lassa virus genomes. Interpretation The large amount of novel genomic diversity of Lassa virus observed in the Liberian cases emphasises the need to match deployed diagnostic capabilities with locally circulating strains and underscores the importance of evaluating cross-lineage protection in the development of vaccines and therapeutics.

Superconductivity in strongly correlated systems is a remarkable phenomenon that attracts huge interest. The study of this problem is relevant for materials such as the high T c oxides, pnictides and heavy fermions. These systems also have in common the existence of electrons of several orbitals that coexist at a common Fermi surface. In this paper we study the effect of pressure, chemical or applied on multi-band superconductivity. Pressure varies the atomic distances and consequently the overlap of the wave-functions in the crystal. This rearranges the electronic structure that we model including a pressure dependent hybridization between the bands. We consider the case of two-dimensional systems in a square lattice with inverted bands. We study the conditions for obtaining a pressure induced superconductor quantum critical point and show that hybridization, i.e. pressure can induce a Bardeen-Cooper-Schrieffer-Bose-Einstein condensation crossover in multi-band systems even for moderate interactions. We found a tail-like superconductor regime and briefly discuss the influence of the symmetry of the order parameter in the results.

Development of an effective vaccine became a worldwide priority after the devastating 2013-2016 Ebola disease outbreak. To qualitatively profile the humoral response against advanced filovirus vaccine candidates, we developed Domain Programmable Arrays (DPA), a systems serology platform to identify epitopes targeted after vaccination or filovirus infection. We optimized the assay using a panel of well-characterized monoclonal antibodies. After optimization, we utilized the system to longitudinally characterize the immunoglobulin (Ig) isotype-specific responses in non-human primates vaccinated with rVSV-ΔG-EBOV-glycoprotein (GP). Strikingly, we observed that, although the IgM response was directed against epitopes over the whole GP, the IgG and IgA responses were almost exclusively directed against the mucin-like domain (MLD) of the glycan cap. Further research will be needed to characterize this possible biased IgG and IgA response toward the MLD, but the results corroborate that DPA is a valuable tool to qualitatively measure the humoral response after vaccination.

Superconductivity in strongly correlated systems is a remarkable phenomenon that attracts a huge interest. The study of this problem is relevant for materials as the high $T_c$ oxides, pnictides and heavy fermions. These systems also have in common the existence of electrons of several orbitals that coexist at a common Fermi-surface. In this paper we study the effect of pressure, chemical or applied on multi-band superconductivity. Pressure varies the atomic distances and consequently the overlap of the wave-functions in the crystal. This rearranges the electronic structure that we model including a pressure dependent hybridization between the bands. We consider the case of two-dimensional systems in a square lattice with inverted bands. We study the conditions for obtaining a pressure induced superconductor quantum critical point and show that hybridization, i.e., pressure can induce a BCS-BEC crossover in multi-band systems even for moderate interactions. We briefly discuss the influence of the symmetry of the order parameter in the results.