Rap1-interacting adapter molecule (RIAM) associates with the plasma membrane via a proximity detector

Adaptive immunity depends on lymphocyte adhesion that is mediated by the integrin lymphocyte functional antigen 1 (LFA-1). The small guanosine triphosphatase Rap1 regulates LFA-1 adhesiveness through one of its effectors, Rap1-interacting adapter molecule (RIAM). We show that RIAM was recruited to the lymphocyte plasma membrane (PM) through its Ras association (RA) and pleckstrin homology (PH) domains, both of which were required for lymphocyte adhesion. The N terminus of RIAM inhibited membrane translocation. In vitro, the RA domain bound both Rap1 and H-Ras with equal but relatively low affinity, whereas in vivo only Rap1 was required for PM association. The PH domain bound phosphoinositol 4,5-bisphosphate (PI(4,5)P2) and was responsible for the spatial distribution of RIAM only at the PM of activated T cells. We determined the crystal structure of the RA and PH domains and found that, despite an intervening linker of 50 aa, the two domains were integrated into a single structural unit, which was critical for proper localization to the PM. Thus, the RA-PH domains of RIAM function as a proximity detector for activated Rap1 and PI(4,5)P2

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis

Background: The propensity of diferent Anopheles mosquitoes to bite humans instead of other vertebrates infuences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Human Blood Index (HBI), currently requires expensive and time-consuming laboratory procedures involving enzyme-linked immunosorbent assays (ELISA) or polymerase chain reactions (PCR). Here, midinfrared (MIR) spectroscopy and supervised machine learning are used to accurately distinguish between vertebrate blood meals in guts of malaria mosquitoes, without any molecular techniques. Methods: Laboratory-reared Anopheles arabiensis females were fed on humans, chickens, goats or bovines, then held for 6 to 8 h, after which they were killed and preserved in silica. The sample size was 2000 mosquitoes (500 per host species). Five individuals of each host species were enrolled to ensure genotype variability, and 100 mosquitoes fed on each. Dried mosquito abdomens were individually scanned using attenuated total refection-Fourier transform infrared (ATR-FTIR) spectrometer to obtain high-resolution MIR spectra (4000 cm−1 to 400 cm−1 ). The spectral data were cleaned to compensate atmospheric water and CO2 interference bands using Bruker-OPUS software, then transferred to Python™ for supervised machine-learning to predict host species. Seven classifcation algorithms were trained using 90% of the spectra through several combinations of 75–25% data splits. The best performing model was used to predict identities of the remaining 10% validation spectra, which had not been used for model training or testing. Results: The logistic regression (LR) model achieved the highest accuracy, correctly predicting true vertebrate blood meal sources with overall accuracy of 98.4%. The model correctly identifed 96% goat blood meals, 97% of bovine blood meals, 100% of chicken blood meals and 100% of human blood meals. Three percent of bovine blood meals were misclassifed as goat, and 2% of goat blood meals misclassifed as human. Conclusion: Mid-infrared spectroscopy coupled with supervised machine learning can accurately identify multiple vertebrate blood meals in malaria vectors, thus potentially enabling rapid assessment of mosquito blood-feeding histories and vectorial capacities. The technique is cost-efective, fast, simple, and requires no reagents other than desiccants. However, scaling it up will require field validation of the findings and boosting relevant technical capacity in affected countries

Single hadron response measurement and calorimeter jet energy scale uncertainty with the ATLAS detector at the LHC

The uncertainty on the calorimeter energy response to jets of particles is derived for the ATLAS experiment at the Large Hadron Collider (LHC). First, the calorimeter response to single isolated charged hadrons is measured and compared to the Monte Carlo simulation using proton-proton collisions at centre-of-mass energies of sqrt(s) = 900 GeV and 7 TeV collected during 2009 and 2010. Then, using the decay of K_s and Lambda particles, the calorimeter response to specific types of particles (positively and negatively charged pions, protons, and anti-protons) is measured and compared to the Monte Carlo predictions. Finally, the jet energy scale uncertainty is determined by propagating the response uncertainty for single charged and neutral particles to jets. The response uncertainty is 2-5% for central isolated hadrons and 1-3% for the final calorimeter jet energy scale.Comment: 24 pages plus author list (36 pages total), 23 figures, 1 table, submitted to European Physical Journal

Beyond the call of duty: Why customers contribute to firm-hosted commercial online communities

Firm-hosted commercial online communities, in which customers interact to solve each other's service problems, represent a fascinating context to study the motivations of collective action in the form of knowledge contribution to the community. We extend a model of social capital based on Wasko and Faraj (2005) to incorporate and contrast the direct impact of commitment to both the online community and the host firm, as well as reciprocity, on quality and quantity of knowledge contribution. In addition, we examine the moderating influence of three individual attributes that are particularly relevant to the firm-hosted community context: perceived informational value, sportsmanship, and online interaction propensity. We empirically test our framework using self-reported and objective data from 203 members of a firm-hosted technical support community. In addition to several interesting moderating effects, we find that a customer's online interaction propensity, commitment to the community, and the informational value s/he perceives in the community are the strongest drivers of knowledge contribution

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

From 'trading zones' to 'buffer zones': Art and metaphor in the communication of psychiatric genetics to publics

Psychiatric genetics has a difficult relationship with the public given its unshakeable connection to eugenics. Drawing from a five-year public engagement programme that emerged from an internationally renowned psychiatric genetics centre, we propose the concept of the Buffer Zone to consider how an exchange of viewpoints between groups of people – including psychiatric geneticists and lay publics - who are often uneasy in one another’s company can be facilitated through the use of art and metaphor. The artwork at the exhibitions provided the necessary socio-cultural context for scientific endeavours, whilst also enabled public groups to be part of, and remain in, the conversation. Crucial to stress is that this mitigation was not to protect the science; it was to protect the discussion

H-Atlas: The cosmic abundance of dust from the far-infrared background power spectrum

We present a measurement of the angular power spectrum of the cosmic far-infrared background (CFIRB) anisotropies in one of the extragalactic fields of the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) at 250, 350 and 500 μm bands. Consistent with recent measurements of the CFIRB power spectrum in Herschel-SPIRE maps, we confirm the existence of a clear one-halo term of galaxy clustering on arcminute angular scales with large-scale two-halo term of clustering at 30 arcminutes to angular scales of a few degrees. The power spectrum at the largest angular scales, especially at 250 μm, is contaminated by the Galactic cirrus. The angular power spectrum is modeled using a conditional luminosity function approach to describe the spatial distribution of unresolved galaxies that make up the bulk of the CFIRB.Web of Scienc

Towards evidence-based conservation of subterranean ecosystems

Subterranean ecosystems are among the most widespread environments on Earth, yet we still have poor knowledge of their biodiversity. To raise awareness of subterranean ecosystems, the essential services they provide, and their unique conservation challenges, 2021 and 2022 were designated International Years of Caves and Karst. As these ecosystems have traditionally been overlooked in global conservation agendas and multilateral agreements, a quantitative assessment of solution-based approaches to safeguard subterranean biota and associated habitats is timely. This assessment allows researchers and practitioners to understand the progress made and research needs in subterranean ecology and management. We conducted a systematic review of peer-reviewed and grey literature focused on subterranean ecosystems globally (terrestrial, freshwater, and saltwater systems), to quantify the available evidence-base for the effectiveness of conservation interventions. We selected 708 publications from the years 1964 to 2021 that discussed, recommended, or implemented 1,954 conservation interventions in subterranean ecosystems. We noted a steep increase in the number of studies from the 2000s while, surprisingly, the proportion of studies quantifying the impact of conservation interventions has steadily and significantly decreased in recent years. The effectiveness of 31% of conservation interventions has been tested statistically. We further highlight that 64% of the reported research occurred in the Palearctic and Nearctic biogeographic regions. Assessments of the effectiveness of conservation interventions were heavily biased towards indirect measures (monitoring and risk assessment), a limited sample of organisms (mostly arthropods and bats), and more accessible systems (terrestrial caves). Our results indicate that most conservation science in the field of subterranean biology does not apply a rigorous quantitative approach, resulting in sparse evidence for the effectiveness of interventions. This raises the important question of how to make conservation efforts more feasible to implement, cost-effective, and long-lasting. Although there is no single remedy, we propose a suite of potential solutions to focus our efforts better towards increasing statistical testing and stress the importance of standardising study reporting to facilitate meta-analytical exercises. We also provide a database summarising the available literature, which will help to build quantitative knowledge about interventions likely to yield the greatest impacts depending upon the subterranean species and habitats of interest. We view this as a starting point to shift away from the widespread tendency of recommending conservation interventions based on anecdotal and expert-based information rather than scientific evidence, without quantitatively testing their effectiveness.Peer reviewe