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Unconventional T cells are a diverse and underappreciated group of relatively rare lymphocytes that are distinct from conventional CD4+ and CD8+ T cells, and that mainly recognize antigens in the absence of classical restriction through the major histocompatibility complex (MHC). These non-MHC-restricted T cells include mucosal-associated invariant T (MAIT) cells, natural killer T (NKT) cells, γδ T cells and other, often poorly defined, subsets. Depending on the physiological context, unconventional T cells may assume either protective or pathogenic roles in a range of inflammatory and autoimmune responses in the kidney. Accordingly, experimental models and clinical studies have revealed that certain unconventional T cells are potential therapeutic targets, as well as prognostic and diagnostic biomarkers. The responsiveness of human Vγ9Vδ2 T cells and MAIT cells to many microbial pathogens, for example, has implications for early diagnosis, risk stratification and targeted treatment of peritoneal dialysis-related peritonitis. The expansion of non-Vγ9Vδ2 γδ T cells during cytomegalovirus infection and their contribution to viral clearance suggest that these cells can be harnessed for immune monitoring and adoptive immunotherapy in kidney transplant recipients. In addition, populations of NKT, MAIT or γδ T cells are involved in the immunopathology of IgA nephropathy and in models of glomerulonephritis, ischaemia–reperfusion injury and kidney transplantation.This Review examines the unique biological characteristics of unconventional T cells, including γδ T cells, mucosal-associated invariant T cells and natural killer T cells, and their roles in kidney injury, glomerulopathies and fibrosis. The authors also discuss the potential clinical applications of these cells, including in patients with kidney failure treated with dialysis or transplantation.

Human γδ T-cells include some of the most common \"antigen-specific\" cell types in peripheral blood and are enriched yet further at mucosal barrier sites where microbial infection and tumors often originate. While the γδ T-cell compartment includes multiple subsets with highly flexible effector functions, human mucosal tissues are dominated by host stress-responsive Vδ1 T-cells and microbe-responsive Vδ2 T-cells. Widely recognized for their potent cytotoxicity, emerging data suggest that γδ T-cells also exert strong influences on downstream adaptive immunity to pathogens and tumors, in particular activation of antigen-presenting cells and/or direct stimulation of other mucosal leukocytes. These unique functional attributes and lack of MHC restriction have prompted considerable interest in therapeutic targeting of γδ T-cells. Indeed, several drugs already in clinical use, including vedolizumab, infliximab, and azathioprine, likely owe their efficacy in part to modulation of γδ T-cell function. Recent clinical trials of Vδ2 T-cell-selective treatments indicate a good safety profile in human patients, and efficacy is set to increase as more potent/targeted drugs continue to be developed. Key advances will include identifying methods of directing γδ T-cell recruitment to specific tissues to enhance host protection against invading pathogens, or alternatively, retaining these cells in the circulation to limit peripheral inflammation and/or improve responses to blood malignancies. Human γδ T-cell control of mucosal immunity is likely exerted multiple mechanisms that induce diverse responses in other types of tissue-resident leukocytes. Understanding the microenvironmental signals that regulate these functions will be critical to the development of new γδ T-cell-based therapies.

Background A substantial proportion of microbiological screening in diagnostic laboratories is due to suspected urinary tract infections (UTIs), yet approximately two thirds of urine samples typically yield negative culture results. By reducing the number of query samples to be cultured and enabling diagnostic services to concentrate on those in which there are true microbial infections, a significant improvement in efficiency of the service is possible. Methodology Screening process for urine samples prior to culture was modelled in a single clinical microbiology laboratory covering three hospitals and community services across Bristol and Bath, UK. Retrospective analysis of all urine microscopy, culture, and sensitivity reports over one year was used to compare two methods of classification: a heuristic model using a combination of white blood cell count and bacterial count, and a machine learning approach testing three algorithms (Random Forest, Neural Network, Extreme Gradient Boosting) whilst factoring in independent variables including demographics, historical urine culture results, and clinical details provided with the specimen. Results A total of 212,554 urine reports were analysed. Initial findings demonstrated the potential for using machine learning algorithms, which outperformed the heuristic model in terms of relative workload reduction achieved at a classification sensitivity > 95%. Upon further analysis of classification sensitivity of subpopulations, we concluded that samples from pregnant patients and children (age 11 or younger) require independent evaluation. First the removal of pregnant patients and children from the classification process was investigated but this diminished the workload reduction achieved. The optimal solution was found to be three Extreme Gradient Boosting algorithms, trained independently for the classification of pregnant patients, children, and then all other patients. When combined, this system granted a relative workload reduction of 41% and a sensitivity of 95% for each of the stratified patient groups. Conclusion Based on the considerable time and cost savings achieved, without compromising the diagnostic performance, the heuristic model was successfully implemented in routine clinical practice in the diagnostic laboratory at Severn Pathology, Bristol. Our work shows the potential application of supervised machine learning models in improving service efficiency at a time when demand often surpasses resources of public healthcare providers.

Thermal conductivity sensors face an omnipresent cross-influence through varying humidity levels in real-life applications. We present the results of investigations on the influence of humidity on a hydrogen thermal conductivity sensor and approaches for predicting the behavior of thermal conductivity towards humidity. A literature search and comparison of different mixing equations for binary gas mixtures were carried out. The theoretical results were compared with experimental results from three different thermal conductivity sensors with mixtures of water vapor in nitrogen. The mixing equations show a large discrepancy between each other. Some of the models predict a continuously decreasing thermal conductivity and some predict an increasing thermal conductivity for increasing levels of humidity. Our measurements indicate an increase in thermal conductivity followed by a decrease after reaching a peak value. It is shown that the measured behavior is reproducible with different sensors. Depending on the sensor, this corresponds to an error up to 2 vol.% in the measured hydrogen value. The measured behavior is consistent with only one of the three models. Compared to this model, our own sensor shows a maximum deviation of 1.4%. Mixing equations for gas mixtures must be chosen carefully, taking into consideration whether mixing partners include polar or non-polar molecules. Some simplified mixing equations cannot be used to calculate the thermal conductivity of water vapor in air or nitrogen.

Cytometry analysis has seen a considerable expansion in recent years in the maximum number of parameters that can be acquired in a single experiment. In response to this technological advance there has been an increased effort to develop new computational methodologies for handling high-dimensional single cell data acquired by flow or mass cytometry. Despite the success of numerous algorithms and published packages to replicate and outperform traditional manual analysis, widespread adoption of these techniques has yet to be realised in the field of immunology. Here we present CytoPy, a Python framework for automated analysis of cytometry data that integrates a document-based database for a data-centric and iterative analytical environment. In addition, our algorithm-agnostic design provides a platform for open-source cytometry bioinformatics in the Python ecosystem. We demonstrate the ability of CytoPy to phenotype T cell subsets in whole blood samples even in the presence of significant batch effects due to technical and user variation. The complete analytical pipeline was then used to immunophenotype the local inflammatory infiltrate in individuals with and without acute bacterial infection. CytoPy is open-source and licensed under the MIT license. CytoPy is available at https://github.com/burtonrj/CytoPy , with notebooks accompanying this manuscript ( https://github.com/burtonrj/CytoPyManuscript ) and software documentation at https://cytopy.readthedocs.io/ .

Human blood Vγ9Vδ2 T cells respond to signals from microbes and tumors and subsequently differentiate into professional antigen-presenting cells (γδ T-APCs) for induction of CD4⁺ and CD8⁺ T cell responses. γδ T-APCs readily take up and degrade exogenous soluble protein for peptide loading on MHC I, in a process termed antigen cross-presentation. The mechanisms underlying antigen cross-presentation are ill-defined, most notably in human dendritic cells (DCs), and no study has addressed this process in γδ T-APCs. Here we show that intracellular protein degradation and endosomal acidification were significantly delayed in γδ T-APCs compared with human monocyte-derived DCs (moDCs). Such conditions are known to favor antigen cross-presentation. In both γδ T-APCs and moDCs, internalized antigen was transported across insulin-regulated aminopeptidase (IRAP)-positive early and late endosomes; however, and in contrast to various human DC subsets, γδ T-APCs efficiently translocated soluble antigen into the cytosol for processing via the cytosolic proteasome-dependent cross-presentation pathway. Of note, γδ T-APCs cross-presented influenza antigen derived from virus-infected cells and from free virus particles. The robust cross-presentation capability appears to be a hallmark of γδ T-APCs and underscores their potential application in cellular immunotherapy.

Background Involving and engaging the public in scientific research and higher education is slowly becoming the norm for academic institutions in the United Kingdom and elsewhere. Driven by a wide range of stakeholders including regulators, funders, research policymakers and charities public involvement and public engagement are increasingly seen as essential in delivering open and transparent activity that is relevant and positively impacts on our society. It is obvious that any activities involving and engaging members of the public should be conducted safely and ethically. However, it is not clear whether conducting activities ethically means they require ethical approval from a research ethics committee. Main body Although there is some guidance available from government organisations (e.g. the UK Health Research Authority) to suggest ethical approval is not required for such activities, requests from funders and publishers to have ethical approval in place is commonplace in the authors’ experience. We explore this using case studies from our own institution. Conclusion We conclude that any public-facing activity with the purpose to systemically investigate knowledge, attitudes and experiences of members of the public as research and as human participants requires prior approval from an ethics committee. In contrast, engaging and involving members of the public and drawing on lived experience to inform aspects of research and teaching does not. However, lack of clarity around this distinction often results in the academic community seeking ethical approval ‘just in case’, leading to wasted time and resources and erecting unnecessary barriers for public involvement and public engagement. Instead, ethical issues and risks should be appropriately considered and mitigated by the relevant staff within their professional roles, be it academic or a professional service. Often this can involve following published guidelines and conducting an activity risk assessment, or similar. Moving forward, it is critical that academic funders and publishers acknowledge the distinction and agree on an accepted approach to avoid further exacerbating the problem. Plain English summary Involving and engaging members of the public is recognised best practice in university research and teaching. Involvement and engagement activities (for instance, working with the public to design a research study) continue to increase in priority and are an important part of an academic’s role. However, there is often confusion amongst researchers and educators around whether involving the public in these activities requires prior ethical approval, similar to what would be the case when inviting members of the public to participate in a clinical research study, or to donate samples such as blood for experiments. As an example, sometimes researchers are asked for ethical approval by scientific journals when trying to publish the findings from their public involvement and engagement work, when in fact this is not needed. The ongoing uncertainty about the difference between actual research on one hand and public involvement and engagement on the other hand wastes precious time and resources, and is a barrier for scientists to working with the public. We have developed guidance for academic staff on when ethical approval is and is not required, using examples from our own experience. We wrote this article to bring awareness to this problem; share our views with the wider academic community; encourage discussion around the problem and possible solutions; and ultimately contribute to educating on when research ethics approval is needed, and when not.

The outcome of infection is dependent on the ability of viruses to manipulate the infected cell to evade immunity, and the ability of the immune response to overcome this evasion. Understanding this process is key to understanding pathogenesis, genetic risk factors, and both natural and vaccine-induced immunity. SARS-CoV-2 antagonises the innate interferon response, but whether it manipulates innate cellular immunity is unclear. An unbiased proteomic analysis determined how cell surface protein expression is altered on SARS-CoV-2-infected lung epithelial cells, showing downregulation of activating NK ligands B7-H6, MICA, ULBP2, and Nectin1, with minimal effects on MHC-I. This occurred at the level of protein synthesis, could be mediated by Nsp1 and Nsp14, and correlated with a reduction in NK cell activation. This identifies a novel mechanism by which SARS-CoV-2 host-shutoff antagonises innate immunity. Later in the disease process, strong antibody-dependent NK cell activation (ADNKA) developed. These responses were sustained for at least 6 months in most patients, and led to high levels of pro-inflammatory cytokine production. Depletion of spike-specific antibodies confirmed their dominant role in neutralisation, but these antibodies played only a minor role in ADNKA compared to antibodies to other proteins, including ORF3a, Membrane, and Nucleocapsid. In contrast, ADNKA induced following vaccination was focussed solely on spike, was weaker than ADNKA following natural infection, and was not boosted by the second dose. These insights have important implications for understanding disease progression, vaccine efficacy, and vaccine design.

γδ T cells are implicated in host defense against microbes and tumors but their mode of function remains largely unresolved. Here, we have investigated the ability of activated human Vγ9Vδ2⁺ T cells (termed γδ T-APCs) to cross-present microbial and tumor antigens to CD8⁺ αβ T cells. Although this process is thought to be mediated best by DCs, adoptive transfer of ex vivo antigen-loaded, human DCs during immunotherapy of cancer patients has shown limited success. We report that γδ T-APCs take up and process soluble proteins and induce proliferation, target cell killing and cytokine production responses in antigen-experienced and naïve CD8⁺ αβ T cells. Induction of APC functions in Vγ9Vδ2⁺ T cells was accompanied by the up-regulation of costimulatory and MHC class I molecules. In contrast, the functional predominance of the immunoproteasome was a characteristic of γδ T cells irrespective of their state of activation. γδ T-APCs were more efficient in antigen cross-presentation than monocyte-derived DCs, which is in contrast to the strong induction of CD4⁺ αβ T cell responses by both types of APCs. Our study reveals unexpected properties of human γδ T-APCs in the induction of CD8⁺ αβ T effector cells, and justifies their further exploration in immunotherapy research.

We present a concept for a wafer-level manufactured photoacoustic transducer, suitable to be used in consumer-grade gas sensors. The transducer consists of an anodically bonded two-layer stack of a blank silicon wafer and an 11 µm membrane, which was wet-etched from a borosilicate wafer. The membrane separates two cavities; one of which was hermetically sealed and filled with CO2 during the anodic bonding and acts as an infrared absorber. The second cavity was designed to be connected to a standard MEMS microphone on PCB-level forming an infrared-sensitive photoacoustic detector. CO2 sensors consisting of the detector and a MEMS infrared emitter were built up and characterized towards their sensitivity and noise levels at six different component distance ranging from 3.0 mm to 15.5 mm. The signal response for the sample with the longest absorption path ranged from a decrease of 8.3% at a CO2 concentration of 9400 ppm to a decrease of 0.8% at a concentration of 560 ppm. A standard deviation of the measured values of 18 ppm was determined when the sensor was exposed to 1000 ppm CO2.