Human In-Vivo Bioassay for the Tissue-Specific Measurement of Nociceptive and Inflammatory Mediators

This in-vivo human bioassay can be used to study human volunteers and patients. Samples are collected from pertinent tissue sites such as the skin via aseptically inserted microdialysis catheters (Dermal Dialysis, Erlangen, Germany). Illustrated in this example is the collection of interstitial fluid from experimentally inflamed skin in human volunteers. Sample collection can be combined with other experimental tests. For example, the simultaneous assessment of locally released biochemicals and subjective sensitivity to painful stimuli in experimentally inflamed skin provides the critical biochemical-behavioral link to identify biomarkers of pain and inflammation. Presented assay in the living human organism allows for mechanistic insight into tissue-specific processes underlying pain and/or inflammation. The method is also well suited to examine the effectiveness of existing or novel interventions - such as new drug candidates - targeting the treatment of painful and/or inflammatory conditions. This article will provide a detailed description on the use of microdialysis techniques for collecting interstitial fluid from experimentally inflamed skin lesion of human study subjects. Interstitial fluid samples are typically processed with aid of multiplex bead array immunoassays allowing assaying up to 100 analytes in samples as small in volume as 50 microliters

Combined cognitive–behavioural and mindfulness programme for people living with dystonia : a proof-of-concept study

Objectives To design and test the delivery of an intervention targeting the non-motor symptoms of dystonia and pilot key health and well-being questionnaires in this population. Design A proof-of-concept study to test the delivery, acceptability, relevance, structure and content for a 3-day group residential programme for the management of dystonia. Setting Participants were recruited from a single botulinum toxin clinic. The intervention was delivered in the community. Participants 14 participants consented to take part (2 withdrew prior to the starting of intervention). The average age was 60 years (range 44–77), 8 of whom were female. After drop-out, 9 participants completed the 3-day programme. Intervention A 3-day group residential programme. Primary and secondary outcome measures Process evaluation and interviews were carried out before and after the intervention to explore participant's views and expectations, as well as experiences of the intervention. Select questionnaires were completed at baseline, 1-month and 3-month follow-up. Results Although participants were not sure what to expect from the programme, they found it informative and for many this together with being in a group with other people with dystonia legitimised their condition. Mindfulness was accepted and adopted as a coping strategy. This was reflected in the 1-month follow-up. Conclusions We successfully delivered a 3-day residential programme to help those living with dystonia manage their condition. Further improvements are suggested. The quantitative outcome measures were acceptable to this group of patients with dystonia

Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.

MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online

The impact of time to death in donors after circulatory death on recipient outcome in simultaneous pancreas-kidney transplantation

Time to arrest in donors after circulatory death is unpredictable and can vary. This leads to variable periods of warm ischaemic damage prior to pancreas transplantation. There is little evidence supporting procurement team stand-down times based on donor time to death (TTD). We examined what impact TTD had on pancreas graft outcomes following DCD SPK transplantation. Data were extracted from the UK transplant registry from 2014 to 2022. Predictors of graft loss were evaluated by a Cox proportional hazards model. Adjusted restricted cubic spline (RCS) models were generated to further delineate the relationship between TTD and outcome. Three-hundred-and-seventy-five DCD simultaneous kidney-pancreas transplant recipients were included. Increasing TTD was not associated with graft survival (aHR 0.98, 95% CI 0.68-1.41, P=0.901). Increasing asystolic time worsened graft survival (aHR 2.51, 95% CI 1.16-5.43, P=0.020). RCS modelling revealed a non-linear relationship was demonstrated between asystolic time and graft survival, and no relationship between TTD and graft survival. We found no evidence that TTD impacts on pancreas graft survival after DCD SPK transplantation, however increasing asystolic time was a significant predictor of graft loss. Procurement teams should attempt to minimise asystolic time to optimize pancreas graft survival rather than focus on the duration of TTD

Systemic Immunological Consequences of Chronic Periodontitis

Chronic Periodontitis (ChP) is a prevalent inflammatory disease affecting 46% of the US population. ChP produces a profound local inflammatory response to dysbiotic oral microbiota that leads to destruction of alveolar bone and tooth loss. ChP is also associated with systemic illnesses including cardiovascular diseases, malignancies, and adverse pregnancy outcomes. However, the mechanisms underlying these adverse health outcomes are poorly understood. We used a highly multiplex mass cytometry immunoassay to perform an in-depth analysis of the systemic consequences of ChP in patients, before and after periodontal treatment in this prospective cohort study. A high-dimensional analysis of intracellular signaling networks revealed immune system-wide dysfunctions differentiating patients with ChP from healthy controls. Notably, we observed exaggerated pro-inflammatory responses to P. gingivalis-derived lipopolysaccharide in circulating neutrophils and monocytes from patients with ChP. Simultaneously, natural killer cell responses to inflammatory cytokines were attenuated. Importantly, the immune alterations associated with ChP were no longer detectable three weeks after periodontal treatment. Our findings demarcate systemic and cell-specific immune dysfunctions in patients with ChP which can be temporarily reversed by the local treatment of ChP

An immune clock of human pregnancy

The maintenance of pregnancy relies on finely tuned immune adaptations. We demonstrate that these adaptations are precisely timed, reflecting an immune clock of pregnancy in women delivering at term. Using mass cytometry, the abundance and functional responses of all major immune cell subsets were quantified in serial blood samples collected throughout pregnancy. Cell signaling-based Elastic Net, a regularized regression method adapted from the elastic net algorithm, was developed to infer and prospectively validate a predictive model of interrelated immune events that accurately captures the chronology of pregnancy. Model components highlighted existing knowledge and revealed previously unreported biology, including a critical role for the interleukin-2-dependent STAT5ab signaling pathway in modulating T cell function during pregnancy. These findings unravel the precise timing of immunological events occurring during a term pregnancy and provide the analytical framework to identify immunological deviations implicated in pregnancy-related pathologies

Safety and immunogenicity of rVSVΔG-ZEBOV-GP Ebola vaccine in adults and children in Lambaréné, Gabon: A phase I randomised trial.

BACKGROUND: The rVSVΔG-ZEBOV-GP vaccine prevented Ebola virus disease when used at 2 × 107 plaque-forming units (PFU) in a trial in Guinea. This study provides further safety and immunogenicity data. METHODS AND FINDINGS: A randomised, open-label phase I trial in Lambaréné, Gabon, studied 5 single intramuscular vaccine doses of 3 × 103, 3 × 104, 3 × 105, 3 × 106, or 2 × 107 PFU in 115 adults and a dose of 2 × 107 PFU in 20 adolescents and 20 children. The primary objective was safety and tolerability 28 days post-injection. Immunogenicity, viraemia, and shedding post-vaccination were evaluated as secondary objectives. In adults, mild-to-moderate adverse events were frequent, but there were no serious or severe adverse events related to vaccination. Before vaccination, Zaire Ebola virus (ZEBOV)-glycoprotein (GP)-specific and ZEBOV antibodies were detected in 11% and 27% of adults, respectively. In adults, 74%-100% of individuals who received a dose 3 × 104, 3 × 105, 3 × 106, or 2 × 107 PFU had a ≥4.0-fold increase in geometric mean titres (GMTs) of ZEBOV-GP-specific antibodies at day 28, reaching GMTs of 489 (95% CI: 264-908), 556 (95% CI: 280-1,101), 1,245 (95% CI: 899-1,724), and 1,503 (95% CI: 931-2,426), respectively. Twenty-two percent of adults had a ≥4-fold increase of ZEBOV antibodies, with GMTs at day 28 of 1,015 (647-1,591), 1,887 (1,154-3,085), 1,445 (1,013-2,062), and 3,958 (2,249-6,967) for the same doses, respectively. These antibodies persisted up to day 180 for doses ≥3 × 105 PFU. Adults with antibodies before vaccination had higher GMTs throughout. Neutralising antibodies were detected in more than 50% of participants at doses ≥3 × 105 PFU. As in adults, no serious or severe adverse events related to vaccine occurred in adolescents or children. At day 2, vaccine RNA titres were higher for adolescents and children than adults. At day 7, 78% of adolescents and 35% of children had recombinant vesicular stomatitis virus RNA detectable in saliva. The vaccine induced high GMTs of ZEBOV-GP-specific antibodies at day 28 in adolescents, 1,428 (95% CI: 1,025-1,989), and children, 1,620 (95% CI: 806-3,259), and in both groups antibody titres increased up to day 180. The absence of a control group, lack of stratification for baseline antibody status, and imbalances in male/female ratio are the main limitations of this study. CONCLUSIONS: Our data confirm the acceptable safety and immunogenicity profile of the 2 × 107 PFU dose in adults and support consideration of lower doses for paediatric populations and those who request boosting. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR201411000919191

Multiomics Characterization of Preterm Birth in Low- and Middle-Income Countries.

Importance: Worldwide, preterm birth (PTB) is the single largest cause of deaths in the perinatal and neonatal period and is associated with increased morbidity in young children. The cause of PTB is multifactorial, and the development of generalizable biological models may enable early detection and guide therapeutic studies. Objective: To investigate the ability of transcriptomics and proteomics profiling of plasma and metabolomics analysis of urine to identify early biological measurements associated with PTB. Design, Setting, and Participants: This diagnostic/prognostic study analyzed plasma and urine samples collected from May 2014 to June 2017 from pregnant women in 5 biorepository cohorts in low- and middle-income countries (LMICs; ie, Matlab, Bangladesh; Lusaka, Zambia; Sylhet, Bangladesh; Karachi, Pakistan; and Pemba, Tanzania). These cohorts were established to study maternal and fetal outcomes and were supported by the Alliance for Maternal and Newborn Health Improvement and the Global Alliance to Prevent Prematurity and Stillbirth biorepositories. Data were analyzed from December 2018 to July 2019. Exposures: Blood and urine specimens that were collected early during pregnancy (median sampling time of 13.6 weeks of gestation, according to ultrasonography) were processed, stored, and shipped to the laboratories under uniform protocols. Plasma samples were assayed for targeted measurement of proteins and untargeted cell-free ribonucleic acid profiling; urine samples were assayed for metabolites. Main Outcomes and Measures: The PTB phenotype was defined as the delivery of a live infant before completing 37 weeks of gestation. Results: Of the 81 pregnant women included in this study, 39 had PTBs (48.1%) and 42 had term pregnancies (51.9%) (mean [SD] age of 24.8 [5.3] years). Univariate analysis demonstrated functional biological differences across the 5 cohorts. A cohort-adjusted machine learning algorithm was applied to each biological data set, and then a higher-level machine learning modeling combined the results into a final integrative model. The integrated model was more accurate, with an area under the receiver operating characteristic curve (AUROC) of 0.83 (95% CI, 0.72-0.91) compared with the models derived for each independent biological modality (transcriptomics AUROC, 0.73 [95% CI, 0.61-0.83]; metabolomics AUROC, 0.59 [95% CI, 0.47-0.72]; and proteomics AUROC, 0.75 [95% CI, 0.64-0.85]). Primary features associated with PTB included an inflammatory module as well as a metabolomic module measured in urine associated with the glutamine and glutamate metabolism and valine, leucine, and isoleucine biosynthesis pathways. Conclusions and Relevance: This study found that, in LMICs and high PTB settings, major biological adaptations during term pregnancy follow a generalizable model and the predictive accuracy for PTB was augmented by combining various omics data sets, suggesting that PTB is a condition that manifests within multiple biological systems. These data sets, with machine learning partnerships, may be a key step in developing valuable predictive tests and intervention candidates for preventing PTB