History of clinical transplantation

How transplantation came to be a clinical discipline can be pieced together by perusing two volumes of reminiscences collected by Paul I. Terasaki in 1991-1992 from many of the persons who were directly involved. One volume was devoted to the discovery of the major histocompatibility complex (MHC), with particular reference to the human leukocyte antigens (HLAs) that are widely used today for tissue matching.1 The other focused on milestones in the development of clinical transplantation.2 All the contributions described in both volumes can be traced back in one way or other to the demonstration in the mid-1940s by Peter Brian Medawar that the rejection of allografts is an immunological phenomenon.3,4 © 2008 Springer New York

Health Impairments in Children and Adolescents After Hospitalization for Acute COVID-19 or MIS-C

OBJECTIVES: To evaluate risk factors for postdischarge sequelae in children and adolescents hospitalized for acute coronavirus disease 2019 (COVID-19) or multisystem inflammatory syndrome in children (MIS-C). METHODS: Multicenter prospective cohort study conducted in 25 United States pediatric hospitals. Patients <21-years-old, hospitalized May 2020 to May 2021 for acute COVID-19 or MIS-C with follow-up 2 to 4 months after admission. We assessed readmissions, persistent symptoms or activity impairment, and new morbidities. Multivariable regression was used to calculate adjusted risk ratios (aRR) and 95% confidence intervals (CI). RESULTS: Of 358 eligible patients, 2 to 4 month survey data were available for 119 of 155 (76.8%) with acute COVID-19 and 160 of 203 (78.8%) with MIS-C. Thirteen (11%) patients with acute COVID-19 and 12 (8%) with MIS-C had a readmission. Thirty-two (26.9%) patients with acute COVID-19 had persistent symptoms (22.7%) or activity impairment (14.3%) and 48 (30.0%) with MIS-C had persistent symptoms (20.0%) or activity impairment (21.3%). For patients with acute COVID-19, persistent symptoms (aRR, 1.29 [95% CI, 1.04-1.59]) and activity impairment (aRR, 1.37 [95% CI, 1.06-1.78]) were associated with more organ systems involved. Patients with MIS-C and pre-existing respiratory conditions more frequently had persistent symptoms (aRR, 3.09 [95% CI, 1.55-6.14]) and those with obesity more frequently had activity impairment (aRR, 2.52 [95% CI, 1.35-4.69]). New morbidities were infrequent (9% COVID-19, 1% MIS-C). CONCLUSIONS: Over 1 in 4 children hospitalized with acute COVID-19 or MIS-C experienced persistent symptoms or activity impairment for at least 2 months. Patients with MIS-C and respiratory conditions or obesity are at higher risk of prolonged recovery

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

Mobilise-D insights to estimate real-world walking speed in multiple conditions with a wearable device

This study aimed to validate a wearable device’s walking speed estimation pipeline, considering complexity, speed, and walking bout duration. The goal was to provide recommendations on the use of wearable devices for real-world mobility analysis. Participants with Parkinson’s Disease, Multiple Sclerosis, Proximal Femoral Fracture, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, and healthy older adults (n = 97) were monitored in the laboratory and the real-world (2.5 h), using a lower back wearable device. Two walking speed estimation pipelines were validated across 4408/1298 (2.5 h/laboratory) detected walking bouts, compared to 4620/1365 bouts detected by a multi-sensor reference system. In the laboratory, the mean absolute error (MAE) and mean relative error (MRE) for walking speed estimation ranged from 0.06 to 0.12 m/s and − 2.1 to 14.4%, with ICCs (Intraclass correlation coefficients) between good (0.79) and excellent (0.91). Real-world MAE ranged from 0.09 to 0.13, MARE from 1.3 to 22.7%, with ICCs indicating moderate (0.57) to good (0.88) agreement. Lower errors were observed for cohorts without major gait impairments, less complex tasks, and longer walking bouts. The analytical pipelines demonstrated moderate to good accuracy in estimating walking speed. Accuracy depended on confounding factors, emphasizing the need for robust technical validation before clinical application. Trial registration: ISRCTN – 12246987

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism

Fragmentation of tissue-resident macrophages during isolation confounds analysis of single-cell preparations from mouse hematopoietic tissues

Mouse hematopoietic tissues contain abundant tissue-resident macrophages that support immunity, hematopoiesis, and bone homeostasis. A systematic strategy to characterize macrophage subsets in mouse bone marrow (BM), spleen, and lymph node unexpectedly reveals that macrophage surface marker staining emanates from membrane-bound subcellular remnants associated with unrelated cells. Intact macrophages are not present within these cell preparations. The macrophage remnant binding profile reflects interactions between macrophages and other cell types in vivo. Depletion of CD169+ macrophages in vivo eliminates F4/80+ remnant attachment. Remnant-restricted macrophage-specific membrane markers, cytoplasmic fluorescent reporters, and mRNA are all detected in non-macrophage cells including isolated stem and progenitor cells. Analysis of RNA sequencing (RNA-seq) data, including publicly available datasets, indicates that macrophage fragmentation is a general phenomenon that confounds bulk and single-cell analysis of disaggregated hematopoietic tissues. Hematopoietic tissue macrophage fragmentation undermines the accuracy of macrophage ex vivo molecular profiling and creates opportunity for misattribution of macrophage-expressed genes to non-macrophage cells.Susan M. Millard, Ostyn Heng, Khatora S. Opperman, Anuj Sehgal, Katharine M. Irvine, Simranpreet Kaur, Cheyenne J. Sandrock, Andy C. Wu, Graham W. Magor, Lena Batoon, Andrew C. Perkins, Jacqueline E. Noll, Andrew C.W. Zannettino, David P. Sester, Jean-Pierre Levesque, David A. Hume, Liza J. Raggatt, Kim M. Summers, and Allison R. Petti