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Abstract Cancer immunotherapy using T cell receptor-engineered T cells (TCR-Ts) represents a promising treatment option. However, technologies for pre-clinical safety assessment are incomplete or inaccessible to most laboratories. Here, TCR-T off-target reactivity was assessed in five steps: (1) Mapping target amino acids necessary for TCR-T recognition, followed by (2) a computational search for, and (3) reactivity screening against, candidate cross-reactive peptides in the human proteome. Natural processing and presentation of recognized peptides was evaluated using (4) short mRNAs, and (5) full-length proteins. TCR-Ts were screened for recognition of unintended HLA alleles, and as proxy for off-target reactivity in vivo, a syngeneic, HLA-A*02:01-transgenic mouse model was used. Validation demonstrated importance of studying recognition of full-length candidate off-targets, and that the clinically applied 1G4 TCR has a hitherto unknown reactivity to unintended HLA alleles, relevant for patient selection. This widely applicable strategy should facilitate evaluation of candidate therapeutic TCRs and inform clinical decision-making.

BackgroundSARS-CoV-2 vaccination in rheumatoid arthritis (RA) patients treated with B cell-depleting drugs induced limited seroconversion but robust cellular response. We aimed to document specific T and B cell immunity in response to vaccine booster doses and breakthrough infection (BTI).MethodsWe included 76 RA patients treated with rituximab who received up to four SARS-CoV-2 vaccine doses or three doses plus BTI, in addition to vaccinated healthy donors (HD) and control patients treated with tumor necrosis factor inhibitor (TNFi). We quantified anti-SARS-CoV-2 receptor-binding domain (RBD) Spike IgG, anti-nucleocapsid (NC) IgG, 92 circulating inflammatory proteins, Spike-binding B cells, and Spike-specific T cells along with comprehensive high-dimensional phenotyping and functional assays.FindingsThe time since the last rituximab infusion, persistent inflammation, and age were associated with the anti-SARS-CoV-2 RBD IgG seroconversion. The vaccine-elicited serological response was accompanied by an incomplete induction of peripheral Spike-specific memory B cells but occurred independently of T cell responses. Vaccine- and BTI-elicited cellular immunity was similar between RA and HD ex vivo in terms of frequency or phenotype of Spike-specific cytotoxic T cells and in vitro in terms of the functionality and differentiation profile of Spike-specific T cells.InterpretationSARS-CoV-2 vaccination in RA can induce persistent effector T-cell responses that are reactivated by BTI. Paused rituximab medication allowed serological responses after a booster dose (D4), especially in RA with lower inflammation, enabling efficient humoral and cellular immunity after BTI, and contributed overall to the development of potential durable immunity.

Abstract Diagnostic assays currently used to monitor the efficacy of COVID-19 vaccines measure levels of antibodies to the receptor-binding domain of ancestral SARS-CoV-2 (RBDwt). However, the predictive value for protection against new variants of concern (VOCs) has not been firmly established. Here, we used bead-based arrays and flow cytometry to measure binding of antibodies to spike proteins and receptor-binding domains (RBDs) from VOCs in 12,000 serum samples. Effects of sera on RBD-ACE2 interactions were measured as a proxy for neutralizing antibodies. The samples were obtained from healthy individuals or patients on immunosuppressive therapy who had received two to four doses of COVID-19 vaccines and from COVID-19 convalescents. The results show that anti-RBDwt titers correlate with the levels of binding- and neutralizing antibodies against the Alpha, Beta, Gamma, Delta, Epsilon and Omicron variants. The benefit of multiplexed analysis lies in the ability to measure a wide range of anti-RBD titers using a single dilution of serum for each assay. The reactivity patterns also yield an internal reference for neutralizing activity and binding antibody units per milliliter (BAU/ml). Results obtained with sera from vaccinated healthy individuals and patients confirmed and extended results from previous studies on time-dependent waning of antibody levels and effects of immunosuppressive agents. We conclude that anti-RBDwt titers correlate with levels of neutralizing antibodies against VOCs and propose that our method may be implemented to enhance the precision and throughput of immunomonitoring.

Poor overall survival of hematopoietic stem cell transplantation (HSCT) recipients who developed COVID-19 underlies the importance of SARS-CoV-2 vaccination. Previous studies of vaccine efficacy have reported weak humoral responses but conflicting results on T cell immunity. Here, we have examined the relationship between humoral and T cell response in 48 HSCT recipients who received two doses of Moderna’s mRNA-1273 or Pfizer/BioNTech’s BNT162b2 vaccines. Nearly all HSCT patients had robust T cell immunity regardless of protective humoral responses, with 18/48 (37%, IQR 8.679-5601 BAU/mL) displaying protective IgG anti-receptor binding domain (RBD) levels (>2000 BAU/mL). Flow cytometry analysis of activation induced markers (AIMs) revealed that 90% and 74% of HSCT patients showed reactivity towards immunodominant spike peptides in CD8+ and CD4+ T cells, respectively. The response rate increased to 90% for CD4+ T cells as well when we challenged the cells with a complete set of overlapping peptides spanning the entire spike protein. T cell response was detectable as early as 3 months after transplant, but only CD4+ T cell reactivity correlated with IgG anti-RBD level and time after transplantation. Boosting increased seroconversion rate, while only one patient developed COVID-19 requiring hospitalization. Our data suggest that HSCT recipients with poor serological responses were protected from severe COVID-19 by vaccine-induced T cell responses.

The SARS-CoV-2 Omicron variant possess many mutations within the receptor binding domain of the Spike protein, which confer increased transmissibility and higher antibody escape. Here, the authors carry out analysis of the serological and cellular immune responses of individuals with Omicron breakthrough infection.

BackgroundResults showing that sera from double vaccinated individuals have minimal neutralizing activity against Omicron have been interpreted as indicating the need for a third vaccine dose for protection. However, there is little information about early immune responses to Omicron infection in double vaccinated individuals.MethodsWe measured inflammatory mediators, antibodies to the SARS-CoV-2 spike and nucleocapsid proteins, and spike peptide-induced release of interferon gamma in whole blood in 51 double-vaccinated individuals infected with Omicron, in 14 infected with Delta, and in 18 healthy controls. The median time points for the first and second samples were 7 and 14 days after symptom onset, respectively.FindingsInfection with Omicron or Delta led to a rapid and similar increase in antibodies to the receptor-binding domain (RBD) of Omicron protein and spike peptide-induced interferon gamma in whole blood. Both the Omicron- and the Delta-infected patients had a mild and transient increase in inflammatory parameters.InterpretationThe results suggest that two vaccine doses are sufficient to mount a rapid and potent immune response upon infection in healthy individuals of with the Omicron variant.FundingThe study was funded by the Oslo University Hospital, and by grants from The Coalition for Epidemic Preparedness Innovations, Research Council of Norway (no 312780, 324272), South-Eastern Norway Regional Health Authority (no 2019067, 2021071, 10357, 2021047, 33612, 2021087, 2017092), EU Horizon 2020 grant no 848099, a philantropic donation from Vivaldi Invest A/S, and The European Virus Archive Global.

Recent progress in additive manufacturing (AM) has transformed how complex bioinspired engineering structures are designed and produced. Nonetheless, these structures present substantial difficulties in mathematical modeling and computational analysis. The main goal of this paper is to develop an effective computational method to predict the dynamic response of graphene platelets (GPLs)-reinforced functionally graded triply periodic minimal surface (FG-TPMS) plates (referred to as GPLR-FG-TPMS plates) supported by PF. To achieve this, we employ TrSDT within the IGA framework for efficiency and accuracy. The study establishes advanced plate models by combining three sheet-based TPMS configurations with three porosity distributions and three GPL distribution variations through the plate thickness. Then, we consider the effects of geometrical parameters, material properties, and BCs on free vibration and the dynamic response of GPLR-FG-TPMS plates supported by PF. The findings greatly improve our understanding of the complex dynamic responses of GPLR-FG-TPMS plates, paving the way for applications in various fields in the future.

Osteoarthritis is a chronic disease primarily characterized by articular cartilage damage. In Vietnam, osteoarthritis accounts for a high percentage of musculoskeletal conditions, especially affecting the knee joints. Recently, slow-acting anti- osteoarthritis drugs, including glucosamine, chondroitin sulfate, and diacerein, have been suggested as key pharmacological options for treating this condition. However, Vietnamese-language resources on these active ingredients remain limited. This article provides a literature review on the efficacy and safety of these drugs to enhance their effective use in clinical practice. Results indicate that glucosamine and chondroitin are both effective and safe for osteoarthritis treatment, as demonstrated by the data analyzed in this study.

ABSTRACT Background Multi‐cancer early detection (MCED) through a single blood test significantly advances cancer diagnosis. However, most MCED tests rely on a single type of biomarkers, leading to limited sensitivity, particularly for early‐stage cancers. We previously developed SPOT‐MAS, a multimodal ctDNA‐based assay analyzing methylation and fragmentomic profiles to detect five common cancers. Despite its potential, SPOT‐MAS exhibited moderate sensitivities for early‐stage cancers. This study investigated whether integrating hotspot mutations into SPOT‐MAS could enhance its detection rates. Method A targeted amplicon sequencing approach was developed to profile 700 hotspot mutations in cell‐free DNA and integrated into the SPOT‐MAS assay, creating a single‐blood draw workflow. This workflow, namely SPOT‐MAS Plus was retrospectively validated in a cohort of 255 non‐metastatic cancer patients (breast, colorectal, gastric, liver, and lung) and 304 healthy individuals. Results Hotspot mutations were detected in 131 of 255 (51.4%) cancer patients, with the highest rates in liver cancer (96.5%), followed by colorectal (59.3%) and lung cancer (53.7%). Lower detection rates were found for cancers with low tumor mutational burden, such as breast (31.3%) and gastric (41.9%) cancers. In contrast, SPOT‐MAS demonstrated higher sensitivities for these cancers (51.6% for breast and 62.9% for gastric). The combination of hotspot mutations with SPOT‐MAS predictions improved early‐stage cancer detection, achieving an overall sensitivity of 78.5% at a specificity of 97.7%. Enhanced sensitivities were observed for colorectal (81.36%) and lung cancer (82.9%). Conclusion The integration of genetic and epigenetic alterations into a multimodal assay significantly enhances the early detection of various cancers. Further validation in larger cohorts is necessary to support broader clinical applications.

In this work, we study the ability to use hand gestures for human-machine interaction from wrist-worn sensors. Towards this goal, we design a wrist-worn prototype to capture RGB video stream of hand gestures. Then we built a new wrist-worn gesture dataset (named WiGes) with various subjects in interaction with home appliances in different environments. To the best of our knowledge, this is the first benchmark released for studying hand gestures from a wrist-worn camera. We then evaluate various CNN models for vision-based recognition. Furthermore, we deeply analyze the models that produce the best trade-off between accuracy, memory requirement, and computational cost. We point out that among studied architectures, MoviNet produces the highest accuracy. Then, we introduce a new MoviNet-based two-stream architecture that takes both RGB and optical flow into account. Our proposed architecture increases the Top-1 accuracy by 1.36% and 3.67% according to two evaluation protocols. Our dataset, baselines, and proposed model analysis give instructive recommendations for human-machine interaction using hand-held devices.