The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m^3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb--Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.Comment: 55 pages, 82 figure

Ecosystem-atmosphere interactions in the Arctic: using data-model approaches to understand carbon cycle feedbacks

The terrestrial CO2 exchange in the Arctic plays an important role in the global carbon (C) cycle. The Arctic ecosystems, containing a large amount of organic carbon (C), are experiencing ongoing warming in recent decades, which is affecting the C cycling and the feedback interactions between its different components. To improve our understanding of the atmosphere-ecosystem interactions, the Greenland Ecosystem Monitoring (GEM) program measures ecosystem CO2 exchange and links it to biogeochemical processes. However, this task remains challenging in northern latitudes due to an insufficient number of measurement sites, particularly covering full annual cycles, but also the frequent gaps in data affected by extreme conditions and remoteness. Combining ecosystem models and field observations we are able to study the underlying processes of Arctic CO2 exchange in changing environments. The overall aim of the research is to use data-model approaches to analyse the patterns of C exchange and their links to biological processes in Arctic ecosystems, studied in detail both from a measurement and a modelling perspective, but also from a local to a pan-arctic scale. In Paper I we found a compensatory response of photosynthesis (GPP) and ecosystem respiration (Reco), both highly sensitive to the meteorological drivers (i.e. temperatures and radiation) in Kobbefjord, West Greenland tundra. This tight relationship led to a relatively insensitive net ecosystem exchange (NEE) to the meteorology, despite the large variability in temperature and precipitations across growing seasons. This tundra ecosystem acted as a consistent sink of C (-30 g C m-2), except in 2011 (41 g C m-2), which was associated with a major pest outbreak. In Paper II we estimated this decrease of C sink strength of 118-144 g C m-2 in the anomalous year (2011), corresponding to 1210-1470 tonnes C at the Kobbefjord catchment scale. We concluded that the meteorological sensitivity of photosynthesis and respiration were similar, and hence compensatory, but we could not explain the causes. Therefore, in Paper III we used a calibrated and validated version of the Soil-Plant-Atmosphere model to explore full annual C cycles and detail the coupling between GPP and Reco. From this study we found two key results. First, similar metrological buffering to growing season reduced the full annual C sink strength by 60%. Second, plant traits control the compensatory effect observed (and estimated) between gross primary production and ecosystem respiration. Because a site-specific location is not representative of the entire Arctic, we further evaluated the pan-Arctic terrestrial C cycling using the CARDAMOM data assimilation system in Paper IV. Our estimates of C fluxes, pools and transit times are in good agreement with different sources of assimilated and independent data, both at pan-Arctic and local scale. Our benchmarking analysis with extensively used Global Vegetation Models (GVM) highlights that GVM modellers need to focus on the vegetation C dynamics, but also the respiratory losses, to improve our understanding of internal C cycle dynamics in the Arctic. Data-model approaches generate novel outputs, allowing us to explore C cycling mechanisms and controls that otherwise would not have been possible to address individually. Also, discrepancies between data and models can provide information about knowledge gaps and ecological indicators not previously detected from field observations, emphasizing the unique synergy that models and data are capable of bringing together

Deficit of homozygosity among 1.52 million individuals and genetic causes of recessive lethality

Genotypes causing pregnancy loss and perinatal mortality are depleted among living individuals and are therefore difficult to find. To explore genetic causes of recessive lethality, we searched for sequence variants with deficit of homozygosity among 1.52 million individuals from six European populations. In this study, we identified 25 genes harboring protein-altering sequence variants with a strong deficit of homozygosity (10% or less of predicted homozygotes). Sequence variants in 12 of the genes cause Mendelian disease under a recessive mode of inheritance, two under a dominant mode, but variants in the remaining 11 have not been reported to cause disease. Sequence variants with a strong deficit of homozygosity are over-represented among genes essential for growth of human cell lines and genes orthologous to mouse genes known to affect viability. The function of these genes gives insight into the genetics of intrauterine lethality. We also identified 1077 genes with homozygous predicted loss-of-function genotypes not previously described, bringing the total set of genes completely knocked out in humans to 4785.publishedVersio

Fine-Tuning Roles of Endogenous Brain-Derived Neurotrophic Factor, TrkB and Sortilin in Colorectal Cancer Cell Survival

International audienceBACKGROUND: Neurotrophin receptors were initially identified in neural cells. They were recently detected in some cancers in association with invasiveness, but the function of these tyrosine kinase receptors was not previously investigated in colorectal cancer (CRC) cells. METHODS AND FINDINGS: We report herein that human CRC cell lines synthesize the neural growth factor Brain-derived neurotrophic factor (BDNF) under stress conditions (serum starvation). In parallel, CRC cells expressed high- (TrkB) and low-affinity (p75(NTR)) receptors at the plasma membrane, whereas TrkA and TrkC, two other high affinity receptors for NGF and NT-3, respectively, were undetectable. We demonstrate that BDNF induced cell proliferation and had an anti-apoptotic effect mediated through TrkB, as assessed by K252a, a Trk pharmacologic inhibitor. It suppressed both cell proliferation and survival of CRC cells that do not express TrkA nor TrkC. In parallel to the increase of BDNF secretion, sortilin, a protein acting as a neurotrophin transporter as well as a co-receptor for p75(NTR), was increased in the cytoplasm of primary and metastatic CRC cells, which suggests that sortilin could regulate neurotrophin transport in these cells. However, pro-BDNF, also detected in CRC cells, was co-expressed with p75(NTR) at the cell membrane and co-localized with sortilin. In contrast to BDNF, exogenous pro-BDNF induced CRC apoptosis, which suggests that a counterbalance mechanism is involved in the control of CRC cell survival, through sortilin as the co-receptor for p75(NTR), the high affinity receptor for pro-neurotrophins. Likewise, we show that BDNF and TrkB transcripts (and not p75(NTR)) are overexpressed in the patients' tumors by comparison with their adjacent normal tissues, notably in advanced stages of CRC. CONCLUSION: Taken together, these results highlight that BDNF and TrkB are essential for CRC cell growth and survival in vitro and in tumors. This autocrine loop could be of major importance to define new targeted therapies

Identification of Tetranectin as a Potential Biomarker for Metastatic Oral Cancer

Lymph node involvement is the most important predictor of survival rates in patients with oral squamous cell carcinoma (OSCC). A biomarker that can indicate lymph node metastasis would be valuable to classify patients with OSCC for optimal treatment. In this study, we have performed a serum proteomic analysis of OSCC using 2-D gel electrophoresis and liquid chromatography/tandem mass spectrometry. One of the down-regulated proteins in OSCC was identified as tetranectin, which is a protein encoded by the CLEC3B gene (C-type lectin domain family 3, member B). We further tested the protein level in serum and saliva from patients with lymph-node metastatic and primary OSCC. Tetranectin was found significantly under-expressed in both serum and saliva of metastatic OSCC compared to primary OSCC. Our results suggest that serum or saliva tetranectin may serve as a potential biomarker for metastatic OSCC. Other candidate serum biomarkers for OSCC included superoxide dismutase, ficolin 2, CD-5 antigen-like protein, RalA binding protein 1, plasma retinol-binding protein and transthyretin. Their clinical utility for OSCC detection remains to be further tested in cancer patients

Genome-wide association study of febrile seizures implicates fever response and neuronal excitability genes

Febrile seizures represent the most common type of pathological brain activity in young children and are influenced by genetic, environmental and developmental factors. In a minority of cases, febrile seizures precede later development of epilepsy. We conducted a genome-wide association study of febrile seizures in 7635 cases and 83 966 controls identifying and replicating seven new loci, all with P < 5 x 10(-10). Variants at two loci were functionally related to altered expression of the fever response genes PTGER3 and IL10, and four other loci harboured genes (BSN, ERC2, GABRG2, HERC1) influencing neuronal excitability by regulating neurotransmitter release and binding, vesicular transport or membrane trafficking at the synapse. Four previously reported loci (SCN1A, SCN2A, ANO3 and 12q21.33) were all confirmed. Collectively, the seven novel and four previously reported loci explained 2.8% of the variance in liability to febrile seizures, and the single nucleotide polymorphism heritability based on all common autosomal single nucleotide polymorphisms was 10.8%. GABRG2, SCN1A and SCN2A are well-established epilepsy genes and, overall, we found positive genetic correlations with epilepsies (r(g) = 0.39, P = 1.68 x 10(-4)). Further, we found that higher polygenic risk scores for febrile seizures were associated with epilepsy and with history of hospital admission for febrile seizures. Finally, we found that polygenic risk of febrile seizures was lower in febrile seizure patients with neuropsychiatric disease compared to febrile seizure patients in a general population sample. In conclusion, this largest genetic investigation of febrile seizures to date implicates central fever response genes as well as genes affecting neuronal excitability, including several known epilepsy genes. Further functional and genetic studies based on these findings will provide important insights into the complex pathophysiological processes of seizures with and without fever.Peer reviewe

The ALICE TPC, a large 3-dimensional tracking device with fast readout for ultra-high multiplicity events

The design, construction, and commissioning of the ALICE Time-Projection Chamber (TPC) is described. It is the main device for pattern recognition, tracking, and identification of charged particles in the ALICE experiment at the CERN LHC. The TPC is cylindrical in shape with a volume close to 90 m3 and is operated in a 0.5 T solenoidal magnetic field parallel to its axis. In this paper we describe in detail the design considerations for this detector for operation in the extreme multiplicity environment of central Pb–Pb collisions at LHC energy. The implementation of the resulting requirements into hardware (field cage, read-out chambers, electronics), infrastructure (gas and cooling system, laser-calibration system), and software led to many technical innovations which are described along with a presentation of all the major components of the detector, as currently realized. We also report on the performance achieved after completion of the first round of stand-alone calibration runs and demonstrate results close to those specified in the TPC Technical Design Report.publishedVersio

Rapid De Novo Evolution of X Chromosome Dosage Compensation in Silene latifolia, a Plant with Young Sex Chromosomes

Evidence for dosage compensation in Silene latifolia, a plant with 10-million-year-old sex chromosomes, reveals that dosage compensation can evolve rapidly in young XY systems and is not an animal-specific phenomenon

Spadin, a Sortilin-Derived Peptide, Targeting Rodent TREK-1 Channels: A New Concept in the Antidepressant Drug Design

We found that spadin, a natural peptide derived from sortilin, blocks the mouse TREK-1 channel and might be an efficient and fast-acting antidepressant

Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth

A well-functioning placenta is essential for fetal and maternal health throughout pregnancy. Using placental weight as a proxy for placental growth, we report genome-wide association analyses in the fetal (n = 65,405), maternal (n = 61,228) and paternal (n = 52,392) genomes, yielding 40 independent association signals. Twenty-six signals are classified as fetal, four maternal and three fetal and maternal. A maternal parent-of-origin effect is seen near KCNQ1. Genetic correlation and colocalization analyses reveal overlap with birth weight genetics, but 12 loci are classified as predominantly or only affecting placental weight, with connections to placental development and morphology, and transport of antibodies and amino acids. Mendelian randomization analyses indicate that fetal genetically mediated higher placental weight is causally associated with preeclampsia risk and shorter gestational duration. Moreover, these analyses support the role of fetal insulin in regulating placental weight, providing a key link between fetal and placental growth