Quantitative dissection of T cell negative selection mechanisms in the thymus

While many factors can influence the fate of developing T cells in the thymus, among the most influential are the strength and timing of signals transmitted by the T cell antigen receptor (TCR). Weak TCR binding to peptide/major histocompatibility complex (MHC) ligands induces thymocytes to develop into naïve T cells, a process called positive selection. Mechanisms that prevent naive T cell development are termed “negative selection” and include apoptotic deletion and agonist selection into non-naive T cell lineages. Strong TCR binding to pMHC ligands induces negative selection of thymocytes. Thymocytes interact with two broad types of antigen-presenting cells (APCs): bone marrow (BM)-derived APCs and thymic epithelial cells (TECs). The traditional view of thymic selection is that positive selection occurs in the thymic cortex via interaction with TECs, followed by negative selection in the thymic medulla via interaction with BM-APCs. However, recent studies reveal that thymocytes can undergo either cortical or medullary negative selection, which differ in terms of the phenotypes of the thymocytes involved and their timing during T cell development. It remains unclear which APC types are required to mediate these two negative selection processes, which are called “Wave 1” and “Wave 2” of negative selection. In addition, the contributions of MHC class I (MHCI) and MHC class II (MHCII) to the two waves are unclear. To dissect thymic selection, two assays were used in this study. First, the transcription factor, Helios, was used in a flow cytometry assay as a marker of negatively selected cells, in conjunction with chemokine receptor-7 (CCR7) to distinguish thymocyte maturation stages. Apoptosis-defective mice were used to inhibit death of negatively selected cells, allowing direct quantification of negative selection. Genetic ablation of MHCII expression within BM-APCs or autoimmune regulator (Aire–/–) within TECs was used to examine the roles of APC types in thymic selection. Mice lacking expression of MHCI and/or MHCII were also examined. Second, a TCR sequencing assay was used to examine the characteristics of positively and negatively selected TCR repertoires in mice lacking expression of MHCI and/or MHCII. In TCR transgenic and polyclonal models, MHCII+ BM-APCs were required to induce wave 1 negative selection. Ablation of MHCII+ BM-APCs either abrogated negative selection completely or delayed negative selection from wave 1 to wave 2. Although MHCI and MHCII were found to induce similar frequencies of TCR-signalled thymocytes, MHCII was found to make a greater contribution to negative selection than MHCI. Sequencing data revealed that TCRs that provoke negative selection at wave 1 are enriched with hydrophobic amino acids in the region expected to interact with the peptide component of pMHC ligands. Interestingly, hydrophobic amino acids are also enriched in the same region of TCRs that transmit a signal in mice lacking MHC expression. These results provide new insight into the determinants of thymic negative selection

Embarrassingly Parallel Acceleration of Global Tractography via Dynamic Domain Partitioning

Global tractography estimates brain connectivity by organizing signal-generating fiber segments in an optimal configuration that best describes the measured diffusion-weighted data, promising better stability than local greedy methods with respect to imaging noise. However, global tractography is computationally very demanding and requires computation times that are often prohibitive for clinical applications. We present here a reformulation of the global tractography algorithm for fast parallel implementation amendable to acceleration using multi-core CPUs and general-purpose GPUs. Our method is motivated by the key observation that each fiber segment is affected by a limited spatial neighborhood. In other words, a fiber segment is influenced only by the fiber segments that are (or can potentially be) connected to its two ends and also by the diffusion-weighted signal in its proximity. This observation makes it possible to parallelize the Markov chain Monte Carlo (MCMC) algorithm used in the global tractography algorithm so that concurrent updating of independent fiber segments can be carried out. Experiments show that the proposed algorithm can significantly speed up global tractography, while at the same time maintain or even improve tractography performance

Colorectal cancer screening using immunochemical fecal occult blood test

Fecal occult blood test (FOBT) screening has been shown to decrease the incidence and mortality of colorectal cancer (CRC). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the immunochemical fecal occult blood test (i-FOBT) in diagnosing CRC were assessed among the patients in a tertiary referral hospital in Malaysia. A total sample of 814 patients aged 16 to 85 years old who performed i-FOBT and endoscopic screenings was obtained. The patients were recruited for a retrospective investigation. Sensitivity, specificity, PPV, and NPV were derived for the CRC screenees. Out of the 814 patients screened using i-FOBT, half of them were above 59 years old (49.6%), and 36% had positive i-FOBT. Gender distribution was almost equal, where 53.4% of the patients were female, and 46.6% were male. Majority of the patients were Malays (56.6%), followed by Chinese (24.0%), Indians (16.5%), and others (2.9%). Among the 71 patients referred for colonoscopy, 57.7% and 42.3% corresponded to positive and negative i-FOBT cases, respectively. Polyps were found to be most common among the patients (25.6%), 7.0% were found positive for invasive CRC, and 35.2% had normal colonoscopic findings. There was a significant association between colonoscopic finding and positive i-FOBT (p=0.001). The sensitivity, specificity, PPV, and NPV for CRC detection were 66.7%, 43.0%, 9.8%, and 93.3%, respectively. The results indicate that i-FOBT is a useful tool in the detection of abnormalities in the lower gastrointestinal tract and therefore serves as a cornerstone for potential large-scale screening programmes

Identification of infants at high-risk for autism spectrum disorder using multiparameter multiscale white matter connectivity networks: Identification of Infants at High-Risk for ASD

Autism spectrum disorder (ASD) is a wide range of disabilities that cause life-long cognitive impairment and social, communication, and behavioral challenges. Early diagnosis and medical intervention are important for improving the life quality of autistic patients. However, in the current practice, diagnosis often has to be delayed until the behavioral symptoms become evident during childhood. In this study, we demonstrate the feasibility of using machine learning techniques for identifying high-risk ASD infants at as early as six months after birth. This is based on the observation that ASD-induced abnormalities in white matter (WM) tracts and whole-brain connectivity have already started to appear within 24 months after birth. In particular, we propose a novel multikernel support vector machine classification framework by using the connectivity features gathered from WM connectivity networks, which are generated via multiscale regions of interest (ROIs) and multiple diffusion statistics such as fractional anisotropy, mean diffusivity, and average fiber length. Our proposed framework achieves an accuracy of 76% and an area of 0.80 under the receiver operating characteristic curve (AUC), in comparison to the accuracy of 70% and the AUC of 70% provided by the best single-parameter single-scale network. The improvement in accuracy is mainly due to the complementary information provided by multiparameter multiscale networks. In addition, our framework also provides the potential imaging connectomic markers and an objective means for early ASD diagnosis

Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

This paper presents measurements of the $W^+ \rightarrow \mu^+\nu$ and $W^- \rightarrow \mu^-\nu$ cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Search for chargino-neutralino production with mass splittings near the electroweak scale in three-lepton final states in √s=13 TeV pp collisions with the ATLAS detector

A search for supersymmetry through the pair production of electroweakinos with mass splittings near the electroweak scale and decaying via on-shell W and Z bosons is presented for a three-lepton final state. The analyzed proton-proton collision data taken at a center-of-mass energy of √s=13  TeV were collected between 2015 and 2018 by the ATLAS experiment at the Large Hadron Collider, corresponding to an integrated luminosity of 139  fb−1. A search, emulating the recursive jigsaw reconstruction technique with easily reproducible laboratory-frame variables, is performed. The two excesses observed in the 2015–2016 data recursive jigsaw analysis in the low-mass three-lepton phase space are reproduced. Results with the full data set are in agreement with the Standard Model expectations. They are interpreted to set exclusion limits at the 95% confidence level on simplified models of chargino-neutralino pair production for masses up to 345 GeV

Targets for cancer therapy in childhood sarcomas

Development of chemotherapeutic treatment modalities resulted in a dramatic increase in the survival of children with many types of cancer. Still, in case of some pediatric cancer entities including rhabdomyosarcoma, osteosarcoma and Ewing's sarcoma, survival of patients remains dismal and novel treatment approaches are urgently needed. Therefore, based on the concept of targeted therapy, numerous potential targets for the treatment of these cancers have been evaluated pre-clinically or in some cases even clinically during the last decade. This review gives an overview over many different potential therapeutic targets for treatment of these childhood sarcomas, including receptor tyrosine kinases, intracellular signaling molecules, cell cycle and apoptosis regulators, proteasome, hsp90, histone deacetylases, angiogenesis regulators and sarcoma specific fusion proteins. The large number of potential therapeutic targets suggests that improved comparability of pre-clinical models might be necessary to prioritize the most effective ones for future clinical trials

Nfkb2 variants reveal a p100-degradation threshold that defines autoimmune susceptibility

NF-κB2/p100 (p100) is an inhibitor of κB (IκB) protein that is partially degraded to produce the NF-κB2/p52 (p52) transcription factor. Heterozygous NFKB2 mutations cause a human syndrome of immunodeficiency and autoimmunity, but whether autoimmunity arises from insufficiency of p52 or IκB function of mutated p100 is unclear. Here, we studied mice bearing mutations in the p100 degron, a domain that harbors most of the clinically recognized mutations and is required for signal-dependent p100 degradation. Distinct mutations caused graded increases in p100-degradation resistance. Severe p100-degradation resistance, due to inheritance of one highly degradation-resistant allele or two subclinical alleles, caused thymic medullary hypoplasia and autoimmune disease, whereas the absence of p100 and p52 did not. We inferred a similar mechanism occurs in humans, as the T cell receptor repertoires of affected humans and mice contained a hydrophobic signature of increased self-reactivity. Autoimmunity in autosomal dominant NFKB2 syndrome arises largely from defects in nonhematopoietic cells caused by the IκB function of degradation-resistant p100