Resolving selfish and spiteful interdependent conflict.

Interdependence occurs when individuals have a stake in the success or failure of others, such that the outcomes experienced by one individual also generate costs or benefits for others. Discussion on this topic has typically focused on positive interdependence (where gains for one individual result in gains for another) and on the consequences for cooperation. However, interdependence can also be negative (where gains for one individual result in losses for another), which can spark conflict. In this article, we explain when negative interdependence is likely to arise and, crucially, the role played by (mis)perception in shaping an individual's understanding of their interdependent relationships. We argue that, owing to the difficulty in accurately perceiving interdependence with others, individuals might often be mistaken about the stake they hold in each other's outcomes, which can spark needless, resolvable forms of conflict. We then discuss when and how reducing misperceptions can help to resolve such conflicts. We argue that a key mechanism for resolving interdependent conflict, along with better sources of exogenous information, is to reduce reliance on heuristics such as stereotypes when assessing the nature of our interdependent relationships.

Thioredoxin is a metabolic rheostat controlling regulatory B cells.

Metabolic programming is important for B cell fate, but the bioenergetic requirement for regulatory B (Breg) cell differentiation and function is unknown. Here we show that Breg cell differentiation, unlike non-Breg cells, relies on mitochondrial electron transport and homeostatic levels of reactive oxygen species (ROS). Single-cell RNA sequencing analysis revealed that TXN, encoding the metabolic redox protein thioredoxin (Trx), is highly expressed by Breg cells, unlike Trx inhibitor TXNIP which was downregulated. Pharmacological inhibition or gene silencing of TXN resulted in mitochondrial membrane depolarization and increased ROS levels, selectively suppressing Breg cell differentiation and function while favoring pro-inflammatory B cell differentiation. Patients with systemic lupus erythematosus (SLE), characterized by Breg cell deficiencies, present with B cell mitochondrial membrane depolarization, elevated ROS and fewer Trx+ B cells. Exogenous Trx stimulation restored Breg cells and mitochondrial membrane polarization in SLE B cells to healthy B cell levels, indicating Trx insufficiency underlies Breg cell impairment in patients with SLE.

The distorting effects of producer strategies: Why engagement does not reveal consumer preferences for misinformation.

A great deal of empirical research has examined who falls for misinformation and why. Here, we introduce a formal game-theoretic model of engagement with news stories that captures the strategic interplay between (mis)information consumers and producers. A key insight from the model is that observed patterns of engagement do not necessarily reflect the preferences of consumers. This is because producers seeking to promote misinformation can use strategies that lead moderately inattentive readers to engage more with false stories than true ones-even when readers prefer more accurate over less accurate information. We then empirically test people's preferences for accuracy in the news. In three studies, we find that people strongly prefer to click and share news they perceive as more accurate-both in a general population sample, and in a sample of users recruited through Twitter who had actually shared links to misinformation sites online. Despite this preference for accurate news-and consistent with the predictions of our model-we find markedly different engagement patterns for articles from misinformation versus mainstream news sites. Using 1,000 headlines from 20 misinformation and 20 mainstream news sites, we compare Facebook engagement data with 20,000 accuracy ratings collected in a survey experiment. Engagement with a headline is negatively correlated with perceived accuracy for misinformation sites, but positively correlated with perceived accuracy for mainstream sites. Taken together, these theoretical and empirical results suggest that consumer preferences cannot be straightforwardly inferred from empirical patterns of engagement.

Management of Newly Diagnosed Multiple Myeloma Today, and in the Future.

Treatment options have expanded rapidly and widely in the past two decades for patients with multiple myeloma. Triplet novel agent-based induction regimens have been accepted as the standard practice wordwide over the last decade both for transplant-eligible and non-eligible patients. The addition of anti-CD38 monoclonal antibodies as part of quadruplet regimens has led to even deeper and longer-lasting responses. The impressive results shown by the quadruplets havebeen practice-changing where accessible in recent years. Chimeric antigen receptor T cell therapy and bispecific antibodies are being tested in the upfront setting and have the potential to once again shift the paradigm of treatment of newly diagnosed MM.

sciCSR infers B cell state transition and predicts class-switch recombination dynamics using single-cell transcriptomic data.

Class-switch recombination (CSR) is an integral part of B cell maturation. Here we present sciCSR (pronounced 'scissor', single-cell inference of class-switch recombination), a computational pipeline that analyzes CSR events and dynamics of B cells from single-cell RNA sequencing (scRNA-seq) experiments. Validated on both simulated and real data, sciCSR re-analyzes scRNA-seq alignments to differentiate productive heavy-chain immunoglobulin transcripts from germline 'sterile' transcripts. From a snapshot of B cell scRNA-seq data, a Markov state model is built to infer the dynamics and direction of CSR. Applying sciCSR on severe acute respiratory syndrome coronavirus 2 vaccination time-course scRNA-seq data, we observe that sciCSR predicts, using data from an earlier time point in the collected time-course, the isotype distribution of B cell receptor repertoires of subsequent time points with high accuracy (cosine similarity ~0.9). Using processes specific to B cells, sciCSR identifies transitions that are often missed by conventional RNA velocity analyses and can reveal insights into the dynamics of B cell CSR during immune response.

Eco-evolutionary trade-offs in the dynamics of prion strain competition.

Prion and prion-like molecules are a type of self-replicating aggregate protein that have been implicated in a variety of neurodegenerative diseases. Over recent decades, the molecular dynamics of prions have been characterized both empirically and through mathematical models, providing insights into the epidemiology of prion diseases and the impact of prions on the evolution of cellular processes. At the same time, a variety of evidence indicates that prions are themselves capable of a form of evolution, in which changes to their structure that impact their rate of growth or fragmentation are replicated, making such changes subject to natural selection. Here we study the role of such selection in shaping the characteristics of prions under the nucleated polymerization model (NPM). We show that fragmentation rates evolve to an evolutionary stable value which balances rapid reproduction of PrPSc aggregates with the need to produce stable polymers. We further show that this evolved fragmentation rate differs in general from the rate that optimizes transmission between cells. We find that under the NPM, prions that are both evolutionary stable and optimized for transmission have a characteristic length of three times the critical length below which they become unstable. Finally, we study the dynamics of inter-cellular competition between strains, and show that the eco-evolutionary trade-off between intra- and inter-cellular competition favours coexistence.

B cell profiles, antibody repertoire and reactivity reveal dysregulated responses with autoimmune features in melanoma.

B cells are known to contribute to the anti-tumor immune response, especially in immunogenic tumors such as melanoma, yet humoral immunity has not been characterized in these cancers to detail. Here we show comprehensive phenotyping in samples of circulating and tumor-resident B cells as well as serum antibodies in melanoma patients. Memory B cells are enriched in tumors compared to blood in paired samples and feature distinct antibody repertoires, linked to specific isotypes. Tumor-associated B cells undergo clonal expansion, class switch recombination, somatic hypermutation and receptor revision. Compared with blood, tumor-associated B cells produce antibodies with proportionally higher levels of unproductive sequences and distinct complementarity determining region 3 properties. The observed features are signs of affinity maturation and polyreactivity and suggest an active and aberrant autoimmune-like reaction in the tumor microenvironment. Consistent with this, tumor-derived antibodies are polyreactive and characterized by autoantigen recognition. Serum antibodies show reactivity to antigens attributed to autoimmune diseases and cancer, and their levels are higher in patients with active disease compared to post-resection state. Our findings thus reveal B cell lineage dysregulation with distinct antibody repertoire and specificity, alongside clonally-expanded tumor-infiltrating B cells with autoimmune-like features, shaping the humoral immune response in melanoma.

Group reciprocity and the evolution of stereotyping.

Stereotypes are generalized beliefs about groups of people, which are used to make decisions and judgements about them. Although such heuristics can be useful when decisions must be made quickly, or when information is lacking, they can also serve as the basis for prejudice and discrimination. In this paper, we study the evolution of stereotypes through group reciprocity. We characterize the warmth of a stereotype as the willingness to cooperate with an individual based solely on the identity of the group they belong to. We show that when stereotype groups are large, such group reciprocity is less likely to evolve, and stereotypes tend to be negative. We also show that, even when stereotypes are broadly positive, individuals are often overly pessimistic about the willingness of those they stereotype to cooperate. We then show that the tendency for stereotyping itself to evolve is driven by the costs of cognition, so that more people are stereotyped with greater coarseness as costs increase. Finally we show that extrinsic 'shocks', in which the benefits of cooperation are suddenly reduced, can cause stereotype warmth and judgement bias to turn sharply negative, consistent with the view that economic and other crises are drivers of out-group animosity.

Diversification of immunoglobulin genes by gene conversion in the domestic chicken (Gallus gallus domesticus).

Sustainable modern poultry production depends on effective protection against infectious diseases and a diverse range of antibodies is key for an effective immune response. In the domestic chicken, somatic gene conversion is the dominant process in which the antibody immunoglobulin genes are diversified. Affinity maturation by somatic hypermutation (SHM) also occurs, but the relative contribution of gene conversion versus somatic hypermutation to immunoglobulin (Ig) gene diversity is poorly understood. In this study, we use high throughput long-read sequencing to study immunoglobulin diversity in multiple immune-associated tissues in Rhode Island Red chickens. To better understand the impact of genetic diversification in the chicken, a novel gene conversion identification software was developed (BrepConvert). In this study, BrepConvert enabled the identification of over 1 million gene conversion events. Mapping the occurrence of putative somatic gene conversion (SGC) events throughout the variable gene region revealed repetitive and highly restricted patterns of genetic insertions in both the antibody heavy and light chains. These patterns coincided with the locations of genetic variability in available pseudogenes and align with antigen binding sites, predominately the complementary determining regions (CDRs). We found biased usage of pseudogenes during gene conversion, as well as immunoglobulin heavy chain diversity gene (IGHD) preferences during V(D)J gene rearrangement, suggesting that antibody diversification in chickens is more focused than the genetic potential for diversity would suggest.

Multi-Omics Reveals Mechanisms of Partial Modulation of COVID-19 Dysregulation by Glucocorticoid Treatment.

Treatments for COVID-19 infections have improved dramatically since the beginning of the pandemic, and glucocorticoids have been a key tool in improving mortality rates. The UK's National Institute for Health and Care Excellence guidance is for treatment to be targeted only at those requiring oxygen supplementation, however, and the interactions between glucocorticoids and COVID-19 are not completely understood. In this work, a multi-omic analysis of 98 inpatient-recruited participants was performed by quantitative metabolomics (using targeted liquid chromatography-mass spectrometry) and data-independent acquisition proteomics. Both 'omics datasets were analysed for statistically significant features and pathways differentiating participants whose treatment regimens did or did not include glucocorticoids. Metabolomic differences in glucocorticoid-treated patients included the modulation of cortisol and bile acid concentrations in serum, but no alleviation of serum dyslipidemia or increased amino acid concentrations (including tyrosine and arginine) in the glucocorticoid-treated cohort relative to the untreated cohort. Proteomic pathway analysis indicated neutrophil and platelet degranulation as influenced by glucocorticoid treatment. These results are in keeping with the key role of platelet-associated pathways and neutrophils in COVID-19 pathogenesis and provide opportunity for further understanding of glucocorticoid action. The findings also, however, highlight that glucocorticoids are not fully effective across the wide range of 'omics dysregulation caused by COVID-19 infections.

Metabolomics Markers of COVID-19 Are Dependent on Collection Wave.

The effect of COVID-19 infection on the human metabolome has been widely reported, but to date all such studies have focused on a single wave of infection. COVID-19 has generated numerous waves of disease with different clinical presentations, and therefore it is pertinent to explore whether metabolic disturbance changes accordingly, to gain a better understanding of its impact on host metabolism and enable better treatments. This work used a targeted metabolomics platform (Biocrates Life Sciences) to analyze the serum of 164 hospitalized patients, 123 with confirmed positive COVID-19 RT-PCR tests and 41 providing negative tests, across two waves of infection. Seven COVID-19-positive patients also provided longitudinal samples 2-7 months after infection. Changes to metabolites and lipids between positive and negative patients were found to be dependent on collection wave. A machine learning model identified six metabolites that were robust in diagnosing positive patients across both waves of infection: TG (22:1_32:5), TG (18:0_36:3), glutamic acid (Glu), glycolithocholic acid (GLCA), aspartic acid (Asp) and methionine sulfoxide (Met-SO), with an accuracy of 91%. Although some metabolites (TG (18:0_36:3) and Asp) returned to normal after infection, glutamic acid was still dysregulated in the longitudinal samples. This work demonstrates, for the first time, that metabolic dysregulation has partially changed over the course of the pandemic, reflecting changes in variants, clinical presentation and treatment regimes. It also shows that some metabolic changes are robust across waves, and these can differentiate COVID-19-positive individuals from controls in a hospital setting. This research also supports the hypothesis that some metabolic pathways are disrupted several months after COVID-19 infection.

An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics.

The majority of metabolomics studies to date have utilised blood serum or plasma, biofluids that do not necessarily address the full range of patient pathologies. Here, correlations between serum metabolites, salivary metabolites and sebum lipids are studied for the first time. 83 COVID-19 positive and negative hospitalised participants provided blood serum alongside saliva and sebum samples for analysis by liquid chromatography mass spectrometry. Widespread alterations to serum-sebum lipid relationships were observed in COVID-19 positive participants versus negative controls. There was also a marked correlation between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate in the COVID-19 positive cohort. The biofluids analysed herein were also compared in terms of their ability to differentiate COVID-19 positive participants from controls; serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum performed well (sensitivity 0.92; specificity 0.84), with saliva performing worst (sensitivity 0.78; specificity 0.83). These findings show that alterations to skin lipid profiles coincide with dyslipidaemia in serum. The work also signposts the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions.

Pandemic, Epidemic, Endemic: B Cell Repertoire Analysis Reveals Unique Anti-Viral Responses to SARS-CoV-2, Ebola and Respiratory Syncytial Virus.

Immunoglobulin gene heterogeneity reflects the diversity and focus of the humoral immune response towards different infections, enabling inference of B cell development processes. Detailed compositional and lineage analysis of long read IGH repertoire sequencing, combining examples of pandemic, epidemic and endemic viral infections with control and vaccination samples, demonstrates general responses including increased use of IGHV4-39 in both Zaire Ebolavirus (EBOV) and COVID-19 patient cohorts. We also show unique characteristics absent in Respiratory Syncytial Virus or yellow fever vaccine samples: EBOV survivors show unprecedented high levels of class switching events while COVID-19 repertoires from acute disease appear underdeveloped. Despite the high levels of clonal expansion in COVID-19 IgG1 repertoires there is a striking lack of evidence of germinal centre mutation and selection. Given the differences in COVID-19 morbidity and mortality with age, it is also pertinent that we find significant differences in repertoire characteristics between young and old patients. Our data supports the hypothesis that a primary viral challenge can result in a strong but immature humoral response where failures in selection of the repertoire risk off-target effects.

Inequality, identity, and partisanship: How redistribution can stem the tide of mass polarization.

The form of political polarization where citizens develop strongly negative attitudes toward out-party members and policies has become increasingly prominent across many democracies. Economic hardship and social inequality, as well as intergroup and racial conflict, have been identified as important contributing factors to this phenomenon known as "affective polarization." Research shows that partisan animosities are exacerbated when these interests and identities become aligned with existing party cleavages. In this paper, we use a model of cultural evolution to study how these forces combine to generate and maintain affective political polarization. We show that economic events can drive both affective polarization and the sorting of group identities along party lines, which, in turn, can magnify the effects of underlying inequality between those groups. But, on a more optimistic note, we show that sufficiently high levels of wealth redistribution through the provision of public goods can counteract this feedback and limit the rise of polarization. We test some of our key theoretical predictions using survey data on intergroup polarization, sorting of racial groups, and affective polarization in the United States over the past 50 y.

Radical and Ionic Mechanisms in Rearrangements of o-Tolyl Aryl Ethers and Amines Initiated by the Grubbs-Stoltz Reagent, Et3SiH/KOtBu.

Rearrangements of o-tolyl aryl ethers, amines, and sulfides with the Grubbs-Stoltz reagent (Et3SiH + KOtBu) were recently announced, in which the ethers were converted to o-hydroxydiarylmethanes, while the (o-tol)(Ar)NH amines were transformed into dihydroacridines. Radical mechanisms were proposed, based on prior evidence for triethylsilyl radicals in this reagent system. A detailed computational investigation of the rearrangements of the aryl tolyl ethers now instead supports an anionic Truce-Smiles rearrangement, where the initial benzyl anion can be formed by either of two pathways: (i) direct deprotonation of the tolyl methyl group under basic conditions or (ii) electron transfer to an initially formed benzyl radical. By contrast, the rearrangements of o-tolyl aryl amines depend on the nature of the amine. Secondary amines undergo deprotonation of the N-H followed by a radical rearrangement, to form dihydroacridines, while tertiary amines form both dihydroacridines and diarylmethanes through radical and/or anionic pathways. Overall, this study highlights the competition between the reactive intermediates formed by the Et3SiH/KOtBu system.

Tissue and regional expression patterns of dicistronic tRNA-mRNA transcripts in grapevine (Vitis vinifera) and their evolutionary co-appearance with vasculature in land plants.

Transfer RNAs (tRNA) are crucial adaptor molecules between messenger RNA (mRNA) and amino acids. Recent evidence in plants suggests that dicistronic tRNA-like structures also act as mobile signals for mRNA transcripts to move between distant tissues. Co-transcription is not a common feature in the plant nuclear genome and, in the few cases where polycistronic transcripts have been found, they include non-coding RNA species, such as small nucleolar RNAs and microRNAs. It is not known, however, the extent to which dicistronic transcripts of tRNA and mRNAs are expressed in field-grown plants, or the factors contributing to their expression. We analysed tRNA-mRNA dicistronic transcripts in the major horticultural crop grapevine (Vitis vinifera) using a novel pipeline developed to identify dicistronic transcripts from high-throughput RNA-sequencing data. We identified dicistronic tRNA-mRNA in leaf and berry samples from 22 commercial vineyards. Of the 124 tRNA genes that were expressed in both tissues, 18 tRNA were expressed forming part of 19 dicistronic tRNA-mRNAs. The presence and abundance of dicistronic molecules was tissue and geographic sub-region specific. In leaves, the expression patterns of dicistronic tRNA-mRNAs significantly correlated with tRNA expression, suggesting that their transcriptional regulation might be linked. We also found evidence of syntenic genomic arrangements of tRNAs and protein-coding genes between grapevine and Arabidopsis thaliana, and widespread prevalence of dicistronic tRNA-mRNA transcripts among vascular land plants but no evidence of these transcripts in non-vascular lineages. This suggests that the appearance of plant vasculature and tRNA-mRNA occurred concurrently during the evolution of land plants.

The natural selection of good science.

Scientists in some fields are concerned that many published results are false. Recent models predict selection for false positives as the inevitable result of pressure to publish, even when scientists are penalized for publications that fail to replicate. We model the cultural evolution of research practices when laboratories are allowed to expend effort on theory, enabling them, at a cost, to identify hypotheses that are more likely to be true, before empirical testing. Theory can restore high effort in research practice and suppress false positives to a technical minimum, even without replication. The mere ability to choose between two sets of hypotheses, one with greater prior chance of being correct, promotes better science than can be achieved with effortless access to the set of stronger hypotheses. Combining theory and replication can have synergistic effects. On the basis of our analysis, we propose four simple recommendations to promote good science.

Single-Cell Transcriptomic Analyses Define Distinct Peripheral B Cell Subsets and Discrete Development Pathways.

Separation of B cells into different subsets has been useful to understand their different functions in various immune scenarios. In some instances, the subsets defined by phenotypic FACS separation are relatively homogeneous and so establishing the functions associated with them is straightforward. Other subsets, such as the "Double negative" (DN, CD19+CD27-IgD-) population, are more complex with reports of differing functionality which could indicate a heterogeneous population. Recent advances in single-cell techniques enable an alternative route to characterize cells based on their transcriptome. To maximize immunological insight, we need to match prior data from phenotype-based studies with the finer granularity of the single-cell transcriptomic signatures. We also need to be able to define meaningful B cell subsets from single cell analyses performed on PBMCs, where the relative paucity of a B cell signature means that defining B cell subsets within the whole is challenging. Here we provide a reference single-cell dataset based on phenotypically sorted B cells and an unbiased procedure to better classify functional B cell subsets in the peripheral blood, particularly useful in establishing a baseline cellular landscape and in extracting significant changes with respect to this baseline from single-cell datasets. We find 10 different clusters of B cells and applied a novel, geometry-inspired, method to RNA velocity estimates in order to evaluate the dynamic transitions between B cell clusters. This indicated the presence of two main developmental branches of memory B cells. A T-independent branch that involves IgM memory cells and two DN subpopulations, culminating in a population thought to be associated with Age related B cells and the extrafollicular response. The other, T-dependent, branch involves a third DN cluster which appears to be a precursor of classical memory cells. In addition, we identify a novel DN4 population, which is IgE rich and closely linked to the classical/precursor memory branch suggesting an IgE specific T-dependent cell population.

CSF1R defines the mononuclear phagocyte system lineage in human blood in health and COVID-19.

Mononuclear phagocytes defend tissues, present antigens, and mediate recovery and healing. To date, we lack a marker to unify mononuclear phagocytes in humans or that informs us about their origin. Here, we reassess mononuclear phagocyte ontogeny in human blood through the lineage receptor CSF1R, in the steady state and in COVID-19. We define CSF1R as the first sensitive and reproducible pan-phagocyte lineage marker, to identify and enumerate all conventional monocytes, and the myeloid dendritic cells. In the steady state, CSF1R is sufficient for sorting and immuno-magnetic isolation. In pathology, changes in CSF1R are more sensitive than CD14 and CD16. In COVID-19, a significant drop in membrane CSF1R is useful for stratifying patients, beyond the power of cell categories published thus far, which fail to capture COVID-19 specific events. Importantly, CSF1R defines cells which are neither conventional monocytes nor DCs, which are missed in published analysis. CSF1R decrease can be linked ex vivo to high CSF1 levels. Blood assessment of CSF1R+ cells opens a developmental window to the Mononuclear Phagocyte System in transit from bone marrow to tissues, supports isolation and phenotypic characterisation, identifies novel cell types, and singles out CSF1R inhibition as therapeutic target in COVID-19 and other diseases.

Polarization under rising inequality and economic decline.

Social and political polarization is an important source of conflict in many societies. Understanding its causes has become a priority of scholars across disciplines. We demonstrate that shifts in socialization strategies analogous to political polarization can arise as a locally beneficial response to both rising wealth inequality and economic decline. In many contexts, interaction with diverse out-groups confers benefits from innovation and exploration greater than those that arise from interacting exclusively with a homogeneous in-group. However, when the economic environment favors risk aversion, a strategy of seeking lower-risk in-group interactions can be important to maintaining individual solvency. Our model shows that under conditions of economic decline or increasing inequality, some members of the population benefit from adopting a risk-averse, in-group favoring strategy. Moreover, we show that such in-group polarization can spread rapidly to the whole population and persist even when the conditions that produced it have reversed.