Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

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

Periodic Host Absence Can Select for Higher or Lower Parasite Transmission Rates

This paper explores the effect of discontinuous periodic host absence on the evolution of pathogen transmission rates by using Ro maximisation techniques. The physiological consequence of an increased transmission rate can be either an increased virulence, i.e. there is a transmission-virulence trade-off or ii) a reduced between season survival, i.e. there is a transmission-survival trade-off. The results reveal that the type of trade-off determines the direction of selection, with relatively longer periods of host absence selecting for higher transmission rates in the presence of a trade-off between transmission and virulence but lower transmission rates in the presence of a trade-of between transmission and between season survival. The fact that for the transmission-virulence trade-off both trade-off parameters operate during host presence whereas for the transmission-survival trade-off one operates during host presence (transmission) and the other (survival) during the period of host absence is the main cause for this difference in selection direction. Moreover, the period of host absence seems to be the key determinant of the pathogens transmission rate. Comparing plant patho-systems with contrasting biological features suggests that airborne plant pathogen respond differently to longer periods of host absence than soil-borne plant pathogens

Two independent proteomic approaches provide a comprehensive analysis of the synovial fluid proteome response to Autologous Chondrocyte Implantation

Background: Autologous chondrocyte implantation (ACI) has a failure rate of approximately 20%, but it is yet to be fully understood why. Biomarkers are needed that can pre-operatively predict in which patients it is likely to fail, so that alternative or individualised therapies can be offered. We previously used label-free quantitation (LF) with a dynamic range compression proteomic approach to assess the synovial fluid (SF) of ACI responders and non-responders. However, we were able to identify only a few differentially abundant proteins at baseline. In the present study, we built upon these previous findings by assessing higher-abundance proteins within this SF, providing a more global proteomic analysis on the basis of which more of the biology underlying ACI success or failure can be understood. Methods: Isobaric tagging for relative and absolute quantitation (iTRAQ) proteomic analysis was used to assess SF from ACI responders (mean Lysholm improvement of 33; n = 14) and non-responders (mean Lysholm decrease of 14; n = 13) at the two stages of surgery (cartilage harvest and chondrocyte implantation). Differentially abundant proteins in iTRAQ and combined iTRAQ and LF datasets were investigated using pathway and network analyses. Results: iTRAQ proteomic analysis confirmed our previous finding that there is a marked proteomic shift in response to cartilage harvest (70 and 54 proteins demonstrating ≥ 2.0-fold change and p < 0.05 between stages I and II in responders and non-responders, respectively). Further, it highlighted 28 proteins that were differentially abundant between responders and non-responders to ACI, which were not found in the LF study, 16 of which were altered at baseline. The differential expression of two proteins (complement C1s subcomponent and matrix metalloproteinase 3) was confirmed biochemically. Combination of the iTRAQ and LF proteomic datasets generated in-depth SF proteome information that was used to generate interactome networks representing ACI success or failure. Functional pathways that are dysregulated in ACI non-responders were identified, including acute-phase response signalling. Conclusions: Several candidate biomarkers for baseline prediction of ACI outcome were identified. A holistic overview of the SF proteome in responders and non-responders to ACI  has been profiled, providing a better understanding of the biological pathways underlying clinical outcome, particularly the differential response to cartilage harvest in non-responders

Método automático de clasificación de color en dientes humanos usando aprendizaje de máquina

Trabajo de InvestigaciónActualmente el proceso de identificación del color de los dientes para la fabricación de prótesis dentales es realizado manualmente por un experto que, utilizando un método de identificación visual, determina el color de las piezas dentales en la boca del paciente, usando guías de color como la VITA®. A pesar de que el método visual es el más utilizado para la identificación del color de dientes, este se ve afectado por distintas variables tales como: el cansancio del experto, la luminosidad en el ambiente, salud visual del especialista, entre otras que influyen en la identificación del color en los dientes. Los errores en la clasificación del color de los dientes pueden generar pérdidas de tiempo lo que implicaría en consecuencia sobrecostos que afectarían directamente al fabricante y la satisfacción final del cliente.1. Planteamiento del problema 2. Pregunta de investigación 3. Objetivos 4. Estado del arte 5. Marco de referencia 6. Alcances y limitaciones 7. Metodología 8. Diseño metodológico 9. Discusión y resultados 10. Conclusiones 11. Trabajos futuros 12. Bibliografía 13. ANEXOSPregradoIngeniero de Sistema

Search for supersymmetry in events with four or more leptons in √s =13 TeV pp collisions with ATLAS

Results from a search for supersymmetry in events with four or more charged leptons (electrons, muons and taus) are presented. The analysis uses a data sample corresponding to 36.1 fb −1 of proton-proton collisions delivered by the Large Hadron Collider at s √ =13 TeV and recorded by the ATLAS detector. Four-lepton signal regions with up to two hadronically decaying taus are designed to target a range of supersymmetric scenarios that can be either enriched in or depleted of events involving the production and decay of a Z boson. Data yields are consistent with Standard Model expectations and results are used to set upper limits on the event yields from processes beyond the Standard Model. Exclusion limits are set at the 95% confidence level in simplified models of General Gauge Mediated supersymmetry, where higgsino masses are excluded up to 295 GeV. In R -parity-violating simplified models with decays of the lightest supersymmetric particle to charged leptons, lower limits of 1.46 TeV, 1.06 TeV, and 2.25 TeV are placed on wino, slepton and gluino masses, respectively

Search for High-Mass Resonances Decaying to τν in pp Collisions at √s=13 TeV with the ATLAS Detector

A search for high-mass resonances decaying to τν using proton-proton collisions at √s=13 TeV produced by the Large Hadron Collider is presented. Only τ-lepton decays with hadrons in the final state are considered. The data were recorded with the ATLAS detector and correspond to an integrated luminosity of 36.1 fb−1. No statistically significant excess above the standard model expectation is observed; model-independent upper limits are set on the visible τν production cross section. Heavy W′ bosons with masses less than 3.7 TeV in the sequential standard model and masses less than 2.2–3.8 TeV depending on the coupling in the nonuniversal G(221) model are excluded at the 95% credibility level

Search for the direct production of charginos and neutralinos in final states with tau leptons in √s=13 TeV collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with at least two hadronically decaying tau leptons is presented. The analysis uses a dataset of pp collisions corresponding to an integrated luminosity of 36.1 fb−1, recorded with the ATLAS detector at the Large Hadron Collider at a centre-of-mass energy of 13TeV.Nosignificant deviation from the expected Standard Model background is observed. Limits are derived in scenarios of ˜χ+1 ˜χ−1 pair production and of ˜χ±1 ˜χ02 and ˜χ+1 ˜χ−1 production in simplified models where the neutralinos and charginos decay solely via intermediate left-handed staus and tau sneutrinos, and the mass of the ˜ τL state is set to be halfway between the masses of the ˜χ±1 and the ˜χ01. Chargino masses up to 630 GeV are excluded at 95% confidence level in the scenario of direct production of ˜χ+1 ˜χ−1 for a massless ˜χ01. Common ˜χ±1 and ˜χ02 masses up to 760 GeV are excluded in the case of production of ˜χ±1 ˜χ02 and ˜χ+1 ˜χ−1 assuming a massless ˜χ01. Exclusion limits for additional benchmark scenarios with large and small mass-splitting between the ˜χ±1 and the ˜χ01 are also studied by varying the ˜ τL mass between the masses of the ˜χ±1 and the ˜χ01

Measurement of the cross section for inclusive isolated-photon production in pp collisions at √s=13TeV using the ATLAS detector

Inclusive isolated-photon production in pp collisions at a centre-of-mass energy of 13TeVis studied with the ATLAS detector at the LHC using a data set with an integrated luminosity of 3.2fb−1. The cross section is measured as a function of the photon transverse energy above 125GeVin different regions of photon pseudorapidity. Next-to-leading-order perturbative QCD and Monte Carlo event-generator predictions are compared to the cross-section measurements and provide an adequate description of the data

Performance of missing transverse momentum reconstruction with the ATLAS detector using proton–proton collisions at √s = 13 TeV

The performance of the missing transverse momentum (EmissT) reconstruction with the ATLAS detector is evaluated using data collected in proton–proton collisions at the LHC at a centre-of-mass energy of 13 TeV in 2015. To reconstruct EmissT, fully calibrated electrons, muons, photons, hadronically decaying τ -leptons, and jets reconstructed from calorimeter energy deposits and charged-particle tracks are used. These are combined with the soft hadronic activity measured by reconstructed charged-particle tracks not associated with the hard objects. Possible double counting of contributions from reconstructed charged-particle tracks from the inner detector, energy deposits in the calorimeter, and reconstructed muons from the muon spectrometer is avoided by applying a signal ambiguity resolution procedure which rejects already used signals when combining the various EmissT contributions. The individual terms as well as the overall reconstructed EmissT are evaluated with various performance metrics for scale (linearity), resolution, and sensitivity to the data-taking conditions. The method developed to determine the systematic uncertainties of the EmissT scale and resolution is discussed. Results are shown based on the full 2015 data sample corresponding to an integrated luminosity of 3.2 fb−1