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Abstract With the growing role of artificial intelligence (AI) in our lives, attention is increasingly turning to the way that humans and AI work together. A key aspect of human–AI collaboration is how people integrate judgements or recommendations from machine agents, when they differ from their own judgements. We investigated trust in human–machine teaming using a perceptual judgement task based on the judge–advisor system. Participants ( $$n=89$$ n = 89 ) estimated a perceptual quantity, then received a recommendation from a machine agent. The participants then made a second response which combined their first estimate and the machine’s recommendation. The degree to which participants shifted their second response in the direction of the recommendations provided a measure of their trust in the machine agent. We analysed the role of advice distance in people’s willingness to change their judgements. When a recommendation falls a long way from their initial judgement, do people come to doubt their own judgement, trusting the recommendation more, or do they doubt the machine agent, trusting the recommendation less? We found that although some participants exhibited these behaviours, the most common response was neither of these tendencies, and a simple model based on averaging accounted best for participants’ trust behaviour. We discuss implications for theories of trust, and human–machine teaming.

Abstract Background Sequence verification is essential for plasmids used as critical reagents or therapeutic products. Typically, high-quality plasmid sequence is achieved through capillary-based Sanger sequencing, requiring customized sets of primers for each plasmid. This process can become expensive, particularly for applications where the validated sequence needs to be produced within a regulated and quality-controlled environment for downstream clinical research applications. Results Here, we describe a cost-effective and accurate plasmid sequencing and consensus generation procedure using the Oxford Nanopore Technologies’ MinION device as an alternative to capillary-based plasmid sequencing options. This procedure can verify the identity of a pure population of plasmid, either confirming it matches the known and expected sequence, or identifying mutations present in the plasmid if any exist. We use a full MinION flow cell per plasmid, maximizing available data and allowing for stringent quality filters. Pseudopairing reads for consensus base calling reduces read error rates from 5.3 to 0.53%, and our pileup consensus approach provides per-base counts and confidence scores, allowing for interpretation of the certainty of the resulting consensus sequences. For pure plasmid samples, we demonstrate 100% accuracy in the resulting consensus sequence, and the sensitivity to detect small mutations such as insertions, deletions, and single nucleotide variants. In test cases where the sequenced pool of plasmids contains subclonal templates, detection sensitivity is similar to that of traditional capillary sequencing. Conclusions Our pipeline can provide significant cost savings compared to outsourcing clinical-grade sequencing of plasmids, making generation of high-quality plasmid sequence for clinical sequence verification more accessible. While other long-read-based methods offer higher-throughput and less cost, our pipeline produces complete and accurate sequence verification for cases where absolute sequence accuracy is required.

Anti-CD19 chimeric antigen receptor (CAR)-T therapy for B cell malignancies has shown clinical success, but a major limitation is the logistical complexity and high cost of manufacturing autologous cell products. If engineered for improved safety, direct infusion of viral gene transfer vectors to initiate in vivo CAR-T transduction, expansion, and anti-tumor activity could provide an alternative, universal approach. To explore this approach we administered approximately 20 million replication-incompetent vesicular stomatitis virus G protein (VSV-G) lentiviral particles carrying an anti-CD19CAR-2A-GFP transgene comprising either an FMC63 (human) or 1D3 (murine) anti-CD19 binding domain, or a GFP-only control transgene, to wild-type C57BL/6 mice by tail vein infusion. The dynamics of immune cell subsets isolated from peripheral blood were monitored at weekly intervals. We saw emergence of a persistent CAR-transduced CD3+ T cell population beginning week 3–4 that reaching a maximum of 13.5% ± 0.58% (mean ± SD) and 7.8% ± 0.76% of the peripheral blood CD3+ T cell population in mice infused with ID3-CAR or FMC63-CAR lentivector, respectively, followed by a rapid decline in each case of the B cell content of peripheral blood. Complete B cell aplasia was apparent by week 5 and was sustained until the end of the protocol (week 8). No significant CAR-positive populations were observed within other immune cell subsets or other tissues. These results indicate that direct intravenous infusion of conventional VSV-G-pseudotyped lentiviral particles carrying a CD19 CAR transgene can transduce T cells that then fully ablate endogenous B cells in wild-type mice.

Abstract Poorly differentiated chordoma (PDC) is a recently recognized subtype of chordoma characterized by expression of the embryonic transcription factor, brachyury, and loss of INI1. PDC primarily affects children and is associated with a poor prognosis and limited treatment options. Here we describe the molecular and immune tumour microenvironment profiles of two paediatric PDCs produced using whole-genome, transcriptome and whole-genome bisulfite sequencing (WGBS) and multiplex immunohistochemistry. Our analyses revealed the presence of tumour-associated immune cells, including CD8+ T cells, and expression of the immune checkpoint protein, PD-L1, in both patient samples. Molecular profiling provided the rationale for immune checkpoint inhibitor (ICI) therapy, which resulted in a clinical and radiographic response. A dominant T cell receptor (TCR) clone specific for a brachyury peptide–MHC complex was identified from bulk RNA sequencing, suggesting that targeting of the brachyury tumour antigen by tumour-associated T cells may underlie this clinical response to ICI. Correlative analysis with rhabdoid tumours, another INI1-deficient paediatric malignancy, suggests that a subset of tumours may share common immune phenotypes, indicating the potential for a therapeutically targetable subgroup of challenging paediatric cancers.

Access to commercial CD19 CAR-T cells remains limited even in wealthy countries like Canada due to clinical, logistical, and financial barriers related to centrally manufactured products. We created a non-commercial academic platform for end-to-end manufacturing of CAR-T cells within Canada’s publicly funded healthcare system. We report initial results from a single-arm, open-label study to determine the safety and efficacy of in-house manufactured CD19 CAR-T cells (entitled CLIC-1901) in participants with relapsed/refractory CD19 positive hematologic malignancies. Using a GMP compliant semi-automated, closed process on the Miltenyi Prodigy, T cells were transduced with lentiviral vector bearing a 4-1BB anti-CD19 CAR transgene and expanded. Participants underwent lymphodepletion with fludarabine and cyclophosphamide, followed by infusion of non-cryopreserved CAR-T cells. Thirty participants with non-Hodgkin’s lymphoma (n=25) or acute lymphoblastic leukemia (n=5) were infused with CLIC-1901: 21 males (70%), median age 66 (range 18-75). Time from enrollment to CLIC-1901 infusion was a median of 20 days (range 15-48). The median CLIC-1901 dose infused was 2.3 × 106 CAR-T cells/kg (range 0.13-3.6 × 106/kg). Toxicity included ≥ grade 3 cytokine release syndrome (n=2) and neurotoxicity (n=1). Median follow-up was 6.5 months. Overall response rate at day 28 was 76.7%. Median progression-free and overall survival was 6 months (95%CI 3-not estimable) and 11 months (95% 6.6-not estimable), respectively. This is the first trial of in-house manufactured CAR-T cells in Canada and demonstrates that administering fresh CLIC-1901 product is fast, safe, and efficacious. Our experience may provide helpful guidance for other jurisdictions seeking to create feasible and sustainable CAR-T cell programs in research-oriented yet resource-constrained settings.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03765177, identifier NCT03765177.

Background: The positive impact of parenting programs for youth mental health is undermined by difficulties engaging parents. Low engagement disproportionately impacts parents of lower-socioeconomic positions (SEPs). Internet- and mobile-based interventions hold potential for overcoming barriers to enrolment, but additional research is needed to understand how programs can appropriately meet the needs of parents across SEPs. Consumer preference methods such as discrete choice experiments may be valuable in this endeavour. Method: A discrete choice experiment was used to determine the relative influence of modifiable program features on parents' intent to enrol. 329 Australian parents of children aged 0–18 repeatedly selected their preferred program from randomized sets of hypothetical programs in an online survey. Each hypothetical program was unique, varying across four program features: module duration, program platform, user control, and program cost. Cumulative link models were used to predict choices, with education, household income, and community advantage used as indicators of SEP. Results: Overall, parents preferred cheaper programs and briefer modules. Parents' preferences differed based on their socioeconomic challenges. Lower-income parents preferred briefer modules, cheaper programs and application-based programs compared to higher-income parents. Parents with less education preferred briefer modules and a predefined module order. Parents living in areas of less advantage preferred website-based programs, user choice of module order, and more expensive programs. Conclusions: This study offers program developers evidence-based strategies for tailoring internet- and mobile-based parenting interventions to increase lower-SEP parent enrolment. Findings also highlight the importance of considering parents' socioeconomic challenges to ensure programs do not perpetuate existing mental health inequalities, as “one-size-fits-all” approaches are likely insufficient for reaching lower-SEP parents.

Fusobacterium nucleatumF. nucleatum

Neoantigens present unique and specific targets for personalized cancer immunotherapy strategies. Given the low mutational burden yet immunotherapy responsiveness of malignant mesothelioma (MM) when compared to other carcinogen-induced malignancies, identifying candidate neoantigens and T cells that recognize them has been a challenge. We used pleural effusions to gain access to MM tumor cells as well as immune cells in order to characterize the tumor-immune interface in MM. We characterized the landscape of potential neoantigens from SNVs identified in 27 MM patients and performed whole transcriptome sequencing of cell populations from 18 patient-matched pleural effusions. IFNγ ELISpot was performed to detect a CD8+ T cell responses to predicted neoantigens in one patient. We detected a median of 68 (range 7–258) predicted neoantigens across the samples. Wild-type non-binding to mutant binding predicted neoantigens increased risk of death in a model adjusting for age, sex, smoking status, histology and treatment (HR: 33.22, CI: 2.55–433.02, p = .007). Gene expression analysis indicated a dynamic immune environment within the pleural effusions. TCR clonotypes increased with predicted neoantigen burden. A strong activated CD8+ T-cell response was identified for a predicted neoantigen produced by a spontaneous mutation in the ROBO3 gene. Despite the challenges associated with the identification of bonafide neoantigens, there is growing evidence that these molecular changes can provide an actionable target for personalized therapeutics in difficult to treat cancers. Our findings support the existence of candidate neoantigens in MM despite the low mutation burden of the tumor, and may present improved treatment opportunities for patients.

The self-immunopeptidome is the repertoire of all self-peptides that can be presented by the combination of MHC variants carried by an individual, defined by their HLA genotype. Each MHC variant presents a distinct set of self-peptides, and the number of peptides in a set is variable. Subjects carrying MHC variants that present fewer self-peptides should also present fewer mutated peptides, resulting in decreased immune pressure on tumor cells. To explore this, we predicted peptide-MHC binding values using all unique 8-11mer human peptides in the human proteome and all available HLA class I allelic variants, for a total of 134 billion unique peptide--MHC binding predictions. From these predictions, we observe that most peptides are able to be presented by relatively few (< 250) MHC, while some can be presented by upwards of 1,500 different MHC. There is substantial overlap among the repertoires of peptides presented by different MHC and no relationship between the number of peptides presented and HLA population frequency. Nearly 30% of self-peptides are presentable by at least one MHC, leaving 70% of the human peptidome unsurveyed by T cells. We observed similar distributions of predicted self-immunopeptidome sizes in cancer subjects compared to controls, and within the pan-cancer population, predicted self-immunopeptidome size combined with mutational load to predict survival. Self-immunopeptidome analysis revealed evidence for tumor immunoediting and identified specific peptide positions that most influence immunogenicity. Because self-immunopeptidome size is defined by HLA genotypes and approximates neoantigen load, HLA genotyping could offer a rapid predictive biomarker for response to immunotherapy.

The digital imaging and remote sensing image generation model is a physics-based image and data simulation model that is primarily used to generate synthetic imagery across the visible to thermal infrared regions using engineering-driven descriptions of remote sensing systems. The model recently went through a major redesign and reimplementation effort to address changes in user requirements and numerical computation trends that have emerged in the 15 years since the last major development effort. The new model architecture adopts some of the latest light transport algorithms matured by the computer graphics community and features a framework that is easily parallelized at the microscale (multithreading) and macroscale (cluster-based computing). A detailed description of the framework is provided, including a novel method for efficiently storing, evaluating, integrating, and sampling spherical and hemispherical datasets appropriate for the representation of modeled or measured bidirectional scattering, reflectance, and transmission distribution functions. The capabilities of the model are then briefly demonstrated and cross-verified with scenarios of interest to the remote sensing community.

Establishing linkages between light detection and ranging (lidar) data, produced from interrogating forest canopies, to the highly complex forest structures, composition, and traits that such forests contain, remains an extremely difficult problem. Radiative transfer models have been developed to help solve this problem and test new sensor platforms in a virtual environment. Many forest canopy studies include the major assumption of isotropic (Lambertian) reflecting and transmitting leaves or non-transmitting leaves. Here, we study when these assumptions may be valid and evaluate their associated impacts/effects on the lidar waveform, as well as its dependence on wavelength, lidar footprint, view angle, and leaf angle distribution (LAD), by using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) remote sensing radiative transfer simulation model. The largest effects of Lambertian assumptions on the waveform are observed at visible wavelengths, small footprints, and oblique interrogation angles relative to the mean leaf angle. For example, a 77% increase in return signal was observed with a configuration of a 550 nm wavelength, 10 cm footprint, and 45° interrogation angle to planophile leaves. These effects are attributed to (i) the bidirectional scattering distribution function (BSDF) becoming almost purely specular in the visible, (ii) small footprints having fewer leaf angles to integrate over, and (iii) oblique angles causing diminished backscatter due to forward scattering. Non-transmitting leaf assumptions have the greatest error for large footprints at near-infrared (NIR) wavelengths. Regardless of leaf angle distribution, all simulations with non-transmitting leaves with a 5 m footprint and 1064 nm wavelength saw around a 15% reduction in return signal. We attribute the signal reduction to the increased multiscatter contribution for larger fields of view, and increased transmission at NIR wavelengths. Armed with the knowledge from this study, researchers will be able to select appropriate sensor configurations to account for or limit BSDF effects in forest lidar data.