Next-generation IEDB tools: a platform for epitope prediction and analysis.

The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website. The initial release focuses on consolidation of all tools related to HLA class I epitopes (MHC binding, elution, immunogenicity, and processing), making all of these predictions accessible from a single application and allowing for their simultaneous execution with minimal user inputs. Additionally, the PEPMatch tool for identifying highly similar epitopes in a set of curated proteomes, as well as a tool for epitope clustering, are available on the site. The NG Tools site allows users to build data pipelines by sending the output of one tool as input for the next. Over the next several years, all pre-existing IEDB Tools, and any newly developed tools, will be integrated into this new site. Here we describe the philosophy behind the redesign and demonstrate the utility and productivity enhancements that are enabled by the new interface.

Does job control contribute to differences in physician-certified sickness absence across office concepts? A mediation analysis in a nationally representative sample.

OBJECTIVES: Several studies have found higher sickness absence in shared and open workspaces than in private offices, but little is known about why these differences occur. We propose and test job control as a potential mechanism underlying observed differences in the risk of physician-certified sickness absence between private offices and shared and open workspaces. METHODS: We conducted a counterfactual mediation analysis using observational survey data from a nationally representative sample of Norwegian employees merged with prospective data from national registries (N=5512). The registry data included information about whether participants had any physician-certified sickness absence the year following the survey. Models were adjusted for age, sex, education level, occupation group, executive/leadership responsibility, and time spent on office work. RESULTS: We found significantly higher sickness absence risk in conventional [risk ratio (RR) 1.12, 95% confidence interval (CI) 1.01‒1.25] and non-territorial (RR 1.20, 95% 1.04‒1.37) open-plan and non-territorial shared-room offices (RR 1.29, 95% CI 1.13‒1.48) compared to private offices. Natural indirect effects due to job control were statistically significant in all contrasts and accounted for 19-34% of total effects depending on contrast. CONCLUSIONS: Findings were in line with hypothesized relationships and suggest that job control may be a mechanism underlying observed differences in sickness absence across office concepts. Future studies should continue to explore potential mechanisms linking shared and open workspaces to higher sickness absence and other unfavorable outcomes in the workplace, particularly with study designs that provide stronger basis for causal inference.

Simulated quick returns in a laboratory context and effects on sleep and pre-sleep arousal between shifts: a crossover controlled trial.

This trial presents a laboratory model investigating the effect of quick returns (QRs, <11 h time off between shifts) on sleep and pre-sleep arousal. Using a crossover design, 63 participants worked a simulated QR condition (8 h time off between consecutive evening- and day shifts) and a day-day (DD) condition (16 h time off between consecutive day shifts). Participants slept at home and sleep was measured using a sleep diary and sleep radar. Compared to the DD condition, the QR condition reduced subjective and objective total sleep time by approximately one hour (both p < .001), reduced time in light- (p < .001), deep- (p = .004), rapid eye movement (REM, p < .001), percentage of REM sleep (p = .023), and subjective sleep quality (p < .001). Remaining sleep parameters and subjective pre-sleep arousal showed no differences between conditions. Results corroborate previous field studies, validating the QR model and indicating causal effects of short rest between shifts on common sleep parameters and sleep architecture.

This trial proposes a laboratory model to investigate the consequences of quick returns (QRs, <11h time off between shifts) on subjective/objective sleep and pre-sleep arousal. QRs reduced total sleep time, light-, deep-, REM sleep, whereas pre-sleep arousal was unaffected. Results emphasise the importance of ensuring sufficient rest time between shifts.Abbreviation: QR: Quick return; DD: Day-day; NREM: Non-rapid eye movement; REM: Rapid eye movement; PSG: Polysomnography; TIB: Time in bed; SOL: Sleep onset latency; WASO: Wake after sleep onset; TST: Total sleep time; EMA: Early morning awakening; PSAS: Pre-Sleep Arousal Scale; MEQ: Morning-Evening Questionnaire; LMM: Linear mixed model; EMM: Estimated marginal mean; SD: Standard deviation; SE: Standard error; d: Cohens' d; h: hours; m: minutes.

IMPROVE: a feature model to predict neoepitope immunogenicity through broad-scale validation of T-cell recognition.

Background: Mutation-derived neoantigens are critical targets for tumor rejection in cancer immunotherapy, and better tools for neoepitope identification and prediction are needed to improve neoepitope targeting strategies. Computational tools have enabled the identification of patient-specific neoantigen candidates from sequencing data, but limited data availability has hindered their capacity to predict which of the many neoepitopes will most likely give rise to T cell recognition. Method: To address this, we make use of experimentally validated T cell recognition towards 17,500 neoepitope candidates, with 467 being T cell recognized, across 70 cancer patients undergoing immunotherapy. Results: We evaluated 27 neoepitope characteristics, and created a random forest model, IMPROVE, to predict neoepitope immunogenicity. The presence of hydrophobic and aromatic residues in the peptide binding core were the most important features for predicting neoepitope immunogenicity. Conclusion: Overall, IMPROVE was found to significantly advance the identification of neoepitopes compared to other current methods.

Leaders as the targets of workplace bullying - prevalence and outcomes.

PURPOSE: Bullying of leaders is an underexplored topic in organizational research. To fill this knowledge gap, the aims of this study were to determine the prevalence of bullying of leaders and to examine whether holding a formal leadership position influences the relationships between exposure to bullying and the outcomes job satisfaction and depression. METHODS: Data from two separate surveys were employed: (1) A cross-sectional occupation specific sample comprising 678 Norwegian child welfare social workers; (2) A nationally representative probability sample of 1,608 Norwegian employees with two time-points (6 months' time-lag). RESULTS: Analyzing multiple indicators of workplace bullying, holding a formal leadership position had no impact on the initial risk of being bullied. Analyses of prospective data showed that leaders report a somewhat stronger increase in levels of bullying over time compared to non-leaders, although the effect size was small. With exception of a small buffering effect on the cross-sectional association between exposure to bullying behaviors and job satisfaction in the second sample, holding a leadership position had no effect on the strength of the association between bullying and outcomes. CONCLUSION: The findings show that leaders have the same risk of being bullied and are influenced by bullying in roughly the same manner as non-leaders. Organizational measures and interventions against bullying should therefore consider leaders as a risk group in line with other employees.

Effects of a work schedule with abated quick returns on insomnia, sleepiness and work-related fatigue: Results from a large-scale cluster randomized controlled trial.

STUDY OBJECTIVES: To investigate the effect of a work schedule with abated quick returns (i.e., >11 hours between two shifts) on insomnia, daytime sleepiness, and work-related fatigue compared to a shift schedule maintaining the usual number of quick returns. METHODS: A two-armed cluster randomized controlled trial including 66 units was conducted at a university hospital in Norway. Units with healthcare workers on rotating shift schedules were randomly assigned to a shift schedule with abated quick returns (intervention) or to continue with a schedule including quick returns as usual (control) for six months. Questionnaires assessed symptoms of insomnia (Bergen Insomnia Scale), daytime sleepiness (Epworth Sleepiness Scale), and work-related fatigue (Revised Swedish Occupational Fatigue Inventory) at baseline and towards the end of the intervention. Data was analyzed using multilevel linear mixed-effects models, and Cohen's d was used to calculate the effect size between groups. RESULTS: Overall, 1314 healthcare workers (85.2% female) completed the baseline questionnaire (response rate 49.1%), and 552 completed the follow-up questionnaire. The intervention reduced quick returns from an average of 13.2 (SD=8.7) to 6.7 (SD=6.0), while the control group's average remained relatively unchanged from 13.2 (SD=8.7) to 12.0 (SD=9.3). Results showed a small improvement in symptoms of insomnia (BIS; d=-0.13, p=0.022) and daytime sleepiness (ESS; d=-0.14, p=0.013) in favor of the intervention. No effects were observed on work-related fatigue. CONCLUSIONS: Reducing the number of quick returns resulted in improvements in insomnia and daytime sleepiness. The findings highlight the importance of sufficient rest time in the work schedule of healthcare workers.

The solute carrier SLC7A1 may act as a protein transporter at the blood-brain barrier.

Despite extensive research, targeted delivery of substances to the brain still poses a great challenge due to the selectivity of the blood-brain barrier (BBB). Most molecules require either carrier- or receptor-mediated transport systems to reach the central nervous system (CNS). These transport systems form attractive routes for the delivery of therapeutics into the CNS, yet the number of known brain endothelium-enriched receptors allowing the transport of large molecules into the brain is scarce. Therefore, to identify novel BBB targets, we combined transcriptomic analysis of human and murine brain endothelium and performed a complex screening of BBB-enriched genes according to established selection criteria. As a result, we propose the high-affinity cationic amino acid transporter 1 (SLC7A1) as a novel candidate for transport of large molecules across the BBB. Using RNA sequencing and in situ hybridization assays, we demonstrated elevated SLC7A1 gene expression in both human and mouse brain endothelium. Moreover, we confirmed SLC7A1 protein expression in brain vasculature of both young and aged mice. To assess the potential of SLC7A1 as a transporter for larger proteins, we performed internalization and transcytosis studies using a radiolabelled or fluorophore-labelled anti-SLC7A1 antibody. Our results showed that SLC7A1 internalised a SLC7A1-specific antibody in human colorectal carcinoma (HCT116) cells. Moreover, transcytosis studies in both immortalised human brain endothelial (hCMEC/D3) cells and primary mouse brain endothelial cells clearly demonstrated that SLC7A1 effectively transported the SLC7A1-specific antibody from luminal to abluminal side. Therefore, here in this study, we present for the first time the SLC7A1 as a novel candidate for transport of larger molecules across the BBB.

Enhancing TCR specificity predictions by combined pan- and peptide-specific training, loss-scaling, and sequence similarity integration.

Predicting the interaction between Major Histocompatibility Complex (MHC) class I-presented peptides and T-cell receptors (TCR) holds significant implications for vaccine development, cancer treatment, and autoimmune disease therapies. However, limited paired-chain TCR data, skewed towards well-studied epitopes, hampers the development of pan-specific machine-learning (ML) models. Leveraging a larger peptide-TCR dataset, we explore various alterations to the ML architectures and training strategies to address data imbalance. This leads to an overall improved performance, particularly for peptides with scant TCR data. However, challenges persist for unseen peptides, especially those distant from training examples. We demonstrate that such ML models can be used to detect potential outliers, which when removed from training, leads to augmented performance. Integrating pan-specific and peptide-specific models alongside with similarity-based predictions, further improves the overall performance, especially when a low false positive rate is desirable. In the context of the IMMREP22 benchmark, this modeling framework attained state-of-the-art performance. Moreover, combining these strategies results in acceptable predictive accuracy for peptides characterized with as little as 15 positive TCRs. This observation places great promise on rapidly expanding the peptide covering of the current models for predicting TCR specificity. The NetTCR 2.2 model incorporating these advances is available on GitHub (https://github.com/mnielLab/NetTCR-2.2) and as a web server at https://services.healthtech.dtu.dk/services/NetTCR-2.2/.

Impact of psychosocial work factors on risk of medically certified sick leave due to common mental disorders: a nationwide prospective cohort study of Norwegian home care workers.

BACKGROUND: The Norwegian home care services experience a high level of sick leave, a large proportion of which is due to common mental disorders. A substantial number of such cases can be attributed to psychosocial factors at work, but more knowledge about occupation-specific risk factors is needed to develop targeted preventive measures to reduce sick leave levels. The aim of this study is to identify the most prominent psychosocial work factors influencing the risk of sick leave spells due to common mental disorders. METHODS: Employees from a random sample of 130 Norwegian home care services (N = 1.819) completed a baseline survey on 15 psychosocial work factors. Participants were subsequently followed up for 26 months using registry data on sick leave. The outcome measure was the number of medically certified sick leave spells due to common mental disorders during follow-up in the Norwegian social insurance database. Incidence risk ratios (IRR) and 95% confidence intervals (CIs) were calculated using negative binomial regression with robust standard errors. RESULTS: Emotional dissonance (IRR 1.30, 95% CI 1.05-1.60) and emotional demands (IRR 1.35, 95% CI 1.14-1.58) were associated with an excess risk of sick leave, while control over work pacing (IRR 0.78, 95% CI 0.62-0.98) was associated with a reduced risk. An estimated 30% (95% CI 8.73-48.82) of sick leave cases were attributable to emotional dissonance and 27% (95% CI 4.80-46.33) were attributable to emotional demands. Control over work pacing was estimated to have prevented 20% (95% CI 1.32-37.78) of the sick leave cases. CONCLUSIONS: This study found that emotional dissonance and emotional demands were robust risk factors for sick leave due to common mental disorders, and that control of work pacing constituted a robust protective factor against sick leave.

DiscoTope-3.0: improved B-cell epitope prediction using inverse folding latent representations.

Accurate computational identification of B-cell epitopes is crucial for the development of vaccines, therapies, and diagnostic tools. However, current structure-based prediction methods face limitations due to the dependency on experimentally solved structures. Here, we introduce DiscoTope-3.0, a markedly improved B-cell epitope prediction tool that innovatively employs inverse folding structure representations and a positive-unlabelled learning strategy, and is adapted for both solved and predicted structures. Our tool demonstrates a considerable improvement in performance over existing methods, accurately predicting linear and conformational epitopes across multiple independent datasets. Most notably, DiscoTope-3.0 maintains high predictive performance across solved, relaxed and predicted structures, alleviating the need for experimental structures and extending the general applicability of accurate B-cell epitope prediction by 3 orders of magnitude. DiscoTope-3.0 is made widely accessible on two web servers, processing over 100 structures per submission, and as a downloadable package. In addition, the servers interface with RCSB and AlphaFoldDB, facilitating large-scale prediction across over 200 million cataloged proteins. DiscoTope-3.0 is available at: https://services.healthtech.dtu.dk/service.php?DiscoTope-3.0.

New light on the HLA-DR immunopeptidomic landscape.

The set of peptides processed and presented by major histocompatibility complex class II molecules defines the immunopeptidome, and its characterization holds keys to understanding essential properties of the immune system. High-throughput mass spectrometry (MS) techniques enable interrogation of the diversity and complexity of the immunopeptidome at an unprecedented scale. Here, we analyzed a large set of MS immunopeptidomics data from 40 donors, 221 samples, covering 30 unique HLA-DR molecules. We identified likely co-immunoprecipitated HLA-DR irrelevant contaminants using state-of-the-art prediction methods and unveiled novel light on the properties of HLA antigen processing and presentation. The ligandome (HLA binders) was enriched in 15-mer peptides, and the contaminome (nonbinders) in longer peptides. Classification of singletons and nested sets showed that the first were enriched in contaminants. Investigating the source protein location of ligands revealed that only contaminants shared a positional bias. Regarding subcellular localization, nested peptides were found to be predominantly of endolysosomal origin, whereas singletons shared an equal distribution between the cytosolic and endolysosomal origin. According to antigen-processing signatures, no significant differences were observed between the cytosolic and endolysosomal ligands. Further, the sensitivity of MS immunopeptidomics was investigated by analyzing overlap and saturation between biological MS replicas, concluding that at least 5 replicas are needed to identify 80% of the immunopeptidome. Moreover, the overlap in immunopeptidome between donors was found to be very low both in terms of peptides and source proteins, the latter indicating a critical HLA bias in the antigen sampling in the HLA antigen presentation. Finally, the complementarity between MS and in silico approaches for comprehensively sampling the immunopeptidome was demonstrated.

MARS an improved de novo peptide candidate selection method for non-canonical antigen target discovery in cancer.

Understanding the nature and extent of non-canonical human leukocyte antigen (HLA) presentation in tumour cells is a priority for target antigen discovery for the development of next generation immunotherapies in cancer. We here employ a de novo mass spectrometric sequencing approach with a refined, MHC-centric analysis strategy to detect non-canonical MHC-associated peptides specific to cancer without any prior knowledge of the target sequence from genomic or RNA sequencing data. Our strategy integrates MHC binding rank, Average local confidence scores, and peptide Retention time prediction for improved de novo candidate Selection; culminating in the machine learning model MARS. We benchmark our model on a large synthetic peptide library dataset and reanalysis of a published dataset of high-quality non-canonical MHC-associated peptide identifications in human cancer. We achieve almost 2-fold improvement for high quality spectral assignments in comparison to de novo sequencing alone with an estimated accuracy of above 85.7% when integrated with a stepwise peptide sequence mapping strategy. Finally, we utilize MARS to detect and validate lncRNA-derived peptides in human cervical tumour resections, demonstrating its suitability to discover novel, immunogenic, non-canonical peptide sequences in primary tumour tissue.

An analysis pipeline for understanding 6-thioguanine effects on a mouse tumour genome.

Mouse tumour models are extensively used as a pre-clinical research tool in the field of oncology, playing an important role in anticancer drugs discovery. Accordingly, in cancer genomics research, the demand for next-generation sequencing (NGS) is increasing, and consequently, the need for data analysis pipelines is likewise growing. Most NGS data analysis solutions to date do not support mouse data or require highly specific configuration for their use. Here, we present a genome analysis pipeline for mouse tumour NGS data including the whole-genome sequence (WGS) data analysis flow for somatic variant discovery, and the RNA-seq data flow for differential expression, functional analysis and neoantigen prediction. The pipeline is based on standards and best practices and integrates mouse genome references and annotations. In a recent study, the pipeline was applied to demonstrate the efficacy of low dose 6-thioguanine (6TG) treatment on low-mutation melanoma in a pre-clinical mouse model. Here, we further this study and describe in detail the pipeline and the results obtained in terms of tumour mutational burden (TMB) and number of predicted neoantigens, and correlate these with 6TG effects on tumour volume. Our pipeline was expanded to include a neoantigen analysis, resulting in neopeptide prediction and MHC class I antigen presentation evaluation. We observed that the number of predicted neoepitopes were more accurate indicators of tumour immune control than TMB. In conclusion, this study demonstrates the usability of the proposed pipeline, and suggests it could be an essential robust genome analysis platform for future mouse genomic analysis.

A large-scale study of peptide features defining immunogenicity of cancer neo-epitopes.

Accurate prediction of immunogenicity for neo-epitopes arising from a cancer associated mutation is a crucial step in many bioinformatics pipelines that predict outcome of checkpoint blockade treatments or that aim to design personalised cancer immunotherapies and vaccines. In this study, we performed a comprehensive analysis of peptide features relevant for prediction of immunogenicity using the Cancer Epitope Database and Analysis Resource (CEDAR), a curated database of cancer epitopes with experimentally validated immunogenicity annotations from peer-reviewed publications. The developed model, ICERFIRE (ICore-based Ensemble Random Forest for neo-epitope Immunogenicity pREdiction), extracts the predicted ICORE from the full neo-epitope as input, i.e. the nested peptide with the highest predicted major histocompatibility complex (MHC) binding potential combined with its predicted likelihood of antigen presentation (%Rank). Key additional features integrated into the model include assessment of the BLOSUM mutation score of the neo-epitope, and antigen expression levels of the wild-type counterpart which is often reflecting a neo-epitope's abundance. We demonstrate improved and robust performance of ICERFIRE over existing immunogenicity and epitope prediction models, both in cross-validation and on external validation datasets.

A giant stem-group chaetognath.

Chaetognaths, with their characteristic grasping spines, are the oldest known pelagic predators, found in the lowest Cambrian (Terreneuvian). Here, we describe a large stem chaetognath, Timorebestia koprii gen. et sp. nov., from the lower Cambrian Sirius Passet Lagerstätte, which exhibits lateral and caudal fins, a distinct head region with long antennae and a jaw apparatus similar to Amiskwia sagittiformis. Amiskwia has previously been interpreted as a total-group chaetognathiferan, as either a stem-chaetognath or gnathostomulid. We show that T. koprii shares a ventral ganglion with chaetognaths to the exclusion of other animal groups, firmly placing these fossils on the chaetognath stem. The large size (up to 30 cm) and gut contents in T. koprii suggest that early chaetognaths occupied a higher trophic position in pelagic food chains than today.

Pain, Conflicted Feelings About Work, and Sickness Absence: A Prospective Study of the Effects of Number of Pain Sites and Role Conflicts on Medically Certified Sickness Absence.

We investigated associations between the number of pain sites (NPS) and role conflict with medically certified, pain-related sickness absence (SA) in employees of Norwegian enterprises (N = 5,654). Latent profile analyses identified exposure profiles based on 3 types of role conflict (work-role conflict, work-life conflict, and emotional dissonance). Multinomial logistic regressions estimated effects on absence (short-term absence of less than 56 days, long-term absence of more than 56 days) during 1 year after survey. Effects of the NPS on absence were compared across exposure profiles. Results suggested the NPS and all types of role conflict predicted absences separately. Mutually adjusted regressions revealed unique contributions of the NPS to the short-term and long-term absence (odds ratio [OR] 1.24, 95% confidence interval [CI] 1.18, 1.30 and OR 1.51, 95% CI 1.37, 1.66) and of work-role conflict to the short-term absence (OR 1.18, 95% CI 1.03, 1.35). Latent profile analyses identified 4 exposure profiles ("1 unconflicted," "2 dissonant, otherwise medium," "3 conflicted, medium dissonance," "4 conflicted and dissonant"). Profiles 3 and 4 exhibited elevated risk of SA, with the strongest baseline-adjusted effects for profile 4 (short-term absence OR 1.90, 95% CI 1.40, 2.57, long-term absence OR 1.95, 95% CI 1.15, 3.31). Effects of the NPS on short-term absence were stronger for profile 4 versus profile 1 (OR 1.38 vs 1.24, P < .001). Our findings suggest that addressing role conflicts may prevent pain-related absence, possibly also for individuals already experiencing pain. PERSPECTIVE: This article elucidates the connections between role conflicts associated with work roles, the NPS, and SA due to pain. This should help organizations prevent pain-related absences from work and improve working conditions for workers who remain occupationally active in spite of pain problems.

circHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA.

Circular RNAs (circRNAs) represent a class of widespread endogenous RNAs that regulate gene expression and thereby influence cell biological decisions with implications for the pathogenesis of several diseases. Here, we disclose a novel gene-regulatory role of circHIPK3 by combining analyses of large genomics datasets and mechanistic cell biological follow-up experiments. Specifically, we use temporal depletion of circHIPK3 or specific RNA binding proteins (RBPs) and identify several perturbed genes by RNA sequencing analyses. Using expression-coupled motif analyses of mRNA expression data from various knockdown experiments, we identify an 11-mer motif within circHIPK3, which is also enriched in genes that become downregulated upon circHIPK3 depletion. By mining eCLIP datasets, we find that the 11-mer motif constitutes a strong binding site for IGF2BP2 and validate this circHIPK3-IGF2BP2 interaction experimentally using RNA-immunoprecipitation and competition assays in bladder cancer cell lines. Our results suggest that circHIPK3 and IGF2BP2 mRNA targets compete for binding. Since the identified 11-mer motif found in circHIPK3 is enriched in upregulated genes following IGF2BP2 knockdown, and since IGF2BP2 depletion conversely globally antagonizes the effect of circHIPK3 knockdown on target genes, our results suggest that circHIPK3 can sequester IGF2BP2 as a competing endogenous RNA (ceRNA), leading to target mRNA stabilization. As an example of a circHIPK3-regulated gene, we focus on the STAT3 mRNA as a specific substrate of IGF2BP2 and validate that manipulation of circHIPK3 regulates IGF2BP2-STAT3 mRNA binding and thereby STAT3 mRNA levels. However, absolute copy number quantifications demonstrate that IGF2BP2 outnumbers circHIPK3 by orders of magnitude, which is inconsistent with a simple 1:1 ceRNA hypothesis. Instead, we show that circHIPK3 can nucleate multiple copies of IGF2BP2, potentially via phase separation, to produce IGF2BP2 condensates. Finally, we show that circHIPK3 expression correlates with overall survival of patients with bladder cancer. Our results are consistent with a model where relatively few cellular circHIPK3 molecules function as inducers of IGF2BP2 condensation thereby regulating STAT3 and other key factors for cell proliferation and potentially cancer progression.

LTX-315 and adoptive cell therapy using tumor-infiltrating lymphocytes generate tumor specific T cells in patients with metastatic soft tissue sarcoma.

LTX-315 is an oncolytic peptide that elicits both local and systemic immune responses upon intratumoral injection. In the present pilot trial, we treated patients with metastatic soft tissue sarcoma with the combination of LTX-315 and adoptive T-cell therapy using in vitro expanded tumor-infiltrating lymphocytes. Six heavily pretreated patients were included in the trial and treated with LTX-315 of which four patients proceeded to adoptive T-cell therapy. Overall, the treatment was considered safe with only expected and manageable toxicity. The best overall clinical response was stable disease for 208 days, and in this patient, we detected tumor-reactive T cells in the blood that lasted until disease progression. In three patients T-cell reactivity against in silico predicted neoantigens was demonstrated. Additionally, de novo T-cell clones were generated and expanded in the blood following LTX-315 injections. In conclusion, this pilot study provides proof that it is feasible to combine LTX-315 and adoptive T-cell therapy, and that this treatment can induce systemic immune responses that resulted in stabilization of the disease in sarcoma patients with otherwise progressive disease. Further optimization of the treatment protocol is warranted to increase clinical activity. ClinicalTrials.gov Identifier: NCT03725605.

Daily interpersonal conflicts and daily negative and positive affect: exploring the moderating role of neuroticism.

BACKGROUND AND OBJECTIVES: Drawing on affective events theory, the present study investigates relationships between daily interpersonal conflicts and negative and positive affective reactions, and tested whether trait neuroticism moderates immediate (same day) and persisting (next-day) affective reactions. DESIGN AND METHODS: A sample of 53 Norwegian naval cadets completed a diary questionnaire for 30 consecutive days (total N = 1590). RESULTS: As predicted, the findings showed that cadets reported more negative affect (but not less positive affect) on days they were confronted with affective events that were of a conflicting nature. In addition, the proposed interaction effects between daily conflict and neuroticism were significant for both negative and positive affect. Specifically, the immediate and persistent effects of daily conflicts on negative affect were strongest for individuals high (vs. low) in neuroticism. Moreover, individuals high in neuroticism reported less positive affect on days with conflicts, whereas individuals low in neuroticism reported more positive affect the two days following interpersonal conflicts. CONCLUSIONS: The findings contribute to affective events theory with important knowledge about the role of trait neuroticism in dealing with interpersonal conflicts in a natural work setting.