Análisis de autoreactividad de anticuerpos leucémicos soportado por estrategias de Inteligencia Artificial

184 p.Los antígenos son moléculas externas reconocidas por el organismo de variada estructura y naturaleza. El sistema inmune ha desarrollado técnicas de reconocimiento para estos agentes patógenos, representando diferentes mecanismos de defensa contra una posible infección, siendo los anticuerpos los responsables de esta detección. Predecir qué anticuerpo reconocerá a un antígeno, o estimar a nivel cualitativo la intensidad de la interacción que se producirá, es una tarea ardua y compleja, representando un gran desafío en el área inmunológica. Debido a que los antígenos pueden ser distintos tipos de moléculas, y tener procedencia en diferentes patógenos, la forma en la cual un anticuerpo reconoce un conjunto de antígenos con diversas intensidades de interacción, es una pregunta que se ha abordado desde diferentes perspectivas. Por otra parte, el organismo ha desarrollado estrategias para reconocer moléculas externas de aquellas propias. Esto evita que se genere una respuesta inmune sobre tejidos en el organismo. Las moléculas propias del organismo que desencadenan esta respuesta son denominadas auto antígenos, y al proceso de presentar defensas contra estas moléculas se le denomina auto reactividad. El análisis de auto antígenos es de gran relevancia, tanto para el estudio de enfermedades auto inmunes, como para enfermedades relacionadas a células propias del organismo. En el caso de la leucemia, un tipo de cáncer que afecta a células del tejido sanguíneo, el estudio de la auto reactividad y la interacción entre auto antígenos y anticuerpos es de gran relevancia para el diseño y propuestas que permitan diagnosticar y tratar esta enfermedad. Gran parte de los estudios de interacción entre auto antígenos y anticuerpos se han realizado utilizando técnicas experimentales. No obstante, diversos enfoques in-silico han sido desarrollados empleando diferentes herramientas computacionales como docking o simulación molecular para cálculos de energía libre y visualización de interacciones. Pese a su gran utilidad, estas técnicas poseen un alto costo asociados a la necesidad de material experimental, necesidad de poseer estructuras definidas o modelos confiables, elevados tiempos de simulación, entre otros. De esta forma la aplicación de técnicas de machine learning y diversos métodos de codificación representan una alternativa potente al problema de reconocimiento de interacción entre proteína-proteína, particularmente, a secuencias de auto antígenos y anticuerpos de leucemia. A partir de la información de interacciones entre 45 secuencias de cadena pesada de anticuerpos y cerca de 8000 secuencias de auto antígenos, Se diseñó e implemento un sistema predictivo ensamblado cualitativo del nivel de intensidad de la interacción entre auto antígenos y cadenas pesadas de anticuerpos. Como estrategias de entrenamiento de modelos predictivos, se combinaron variados métodos de representación de proteínas, principalmente Natural Language Processing y propiedades fisicoquímicas, con diferentes algoritmos de aprendizaje supervisado logrando un predictor ensamblado con un rendimiento del 81% de accuracy. Se aplicaron diferentes estrategias de validación que permiten demostrar la robustez del sistema predictivo propuesto, incluyendo sistemas de validación cruzada y métodos propios basados en estrategias Leave One Antibody Out. Adicionalmente, se diseñó e implemento un conjunto de colecciones de moléculas inmunológicas integradas en un único sistema de base de datos, al cual acoplado a una estrategia de clasificación filogenética, se diseña e implementa una estrategia de clasificación de secuencias de autoantígenos basado en propiedades descriptivas, funcionales y componentes filogenéticos. La combinación del conjunto de colecciones con el sistema de clasificación, en conjunto con el sistema ensamblado predictivo, facilita el diseño de estrategias de identificación de secuencias autoantígenos y su evaluación contra anticuerpos leucémicos, brindando los soportes iniciales para herramientas de diseño y descubrimiento de antígenos/anticuerpos que cumplan con características relevantes para el problema de la leucemia, denotando la usabilidad de métodos computacionales en problemas complejos de la ingeniería médica. // ABSTRACT: Antigens are external molecules of varied structures and nature recognized by the body. The immune system has developed recognition techniques for these pathogens, representing different defense mechanisms against possible infection, the antibodies responsible for this detection. Predicting which antibody will recognize an antigen or estimating the intensity of the interaction that will occur at a qualitative level is an arduous and complex task, representing a significant challenge in the immunological area. Because antigens can be different types of molecules and have origins in various pathogens, how an antibody recognizes a set of antigens with varying intensities of interaction is a question that has been approached from different perspectives. On the other hand, the organism has developed strategies to recognize external molecules on its own. This prevents an immune response from being generated on tissues in the body. The body’s own molecules that trigger this response are called self-antigens, and the process of presenting defenses against these molecules is called self-reactivity. The analysis of self-antigens is of great relevance, both for studying autoimmune diseases and for diseases related to the body’s own cells. In leukemia, a type of cancer that affects cells of the blood tissue, the study of self-reactivity and the interaction between self-antigens and antibodies is of great relevance for the design of proposals that allow the diagnosis and treatment of this disease. Much of the interaction studies between self-antigens and antibodies have been carried out using experimental techniques. However, various in-silico approaches have been developed using different computational tools such as docking or molecular simulation for free energy calculations and interactive visualization. Despite their great utility, these techniques have a high cost associated with the need for experimental material, the need to have defined structures or reliable models, high simulation times, among others. In this way, the application of machine learning techniques and various coding methods represent a powerful alternative to the problem of protein-protein interaction recognition, particularly to leukemia self-antigen and antibody sequences. From the information of interactions between 45 sequences of antibodies heavy chain and about 8000 sequences of self-antigens, a qualitative assembled predictive system for the level of intensity of the interaction between self-antigens and heavy chains of antibodies was designed and implemented. As predictive model training strategies, various protein representation methods were combined, mainly Natural Language Processing and physicochemical properties, with different supervised learning algorithms, achieving an assembled predictor with a performance of 81% accuracy. Different validation strategies were applied to demonstrate the robustness of the proposed predictive system, including cross-validation systems and proprietary methods based on Leave One Antibody Out strategies. Additionally, a set of collections of immunological molecules integrated into a single database system was designed and implemented. Coupled with a phylogenetic classification strategy, a method for classifying self-antigen sequences based on descriptive properties was designed and implemented. This method uses different functional properties and phylogenetic components to estimate the relation of new sequences with the set of self-antigen sequences. The combination of the group of collections with the classification system, in association with the assembled predictive system, facilitates the design of strategies for the identification of selfantigen sequences and their evaluation against leukemic antibodies, providing the initial supports for tools of creation and discovery of antigens/antibodies that meet relevant characteristics for the leukemia problem, denoting the usability of computational methods in complex issues of medical engineering

Evaluación del desempeño de organizaciones de usuarios de agua de la región del Maule: un análisis comparativo de organizaciones de regantes terminales autónomas y anidadas

32 p.El sistema de gestión del agua en Chile está en manos de Organizaciones de Usuarios de Agua (OUAs), entidades privadas responsables de la captación, conducción y distribución de las aguas a las que tienen derecho sus titulares. Dentro de estas se encuentran las Juntas de Vigilancia (JVs), encargadas de administrar cauces naturales -como ríos o embalses- y las Asociaciones de Canalistas (ACs) y Comunidades de Agua (CAs), encargadas de administrar cauces artificiales -como canales primarios y secundarios- que distribuyen el agua a usuarios terminales. No obstante, lo anterior, existen casos en que las CAs operan bajo la supervisión de ACs, es decir, se produce una situación de anidamiento (i.e., CAs anidadas) que contrasta con una condición autónoma (CAs autónomas). Esta distinción es relevante al analizar el desempeño de organizaciones de regantes terminales (ORTs) que distribuyen el agua entre los usuarios finales del sistema de distribución, ya que existe evidencia de que las características y aspectos de la gobernanza de estas organizaciones afectan la gestión del agua de riego y el logro de acciones colectivas. El estudio del desempeño de ORTs y sus factores es especialmente relevante frente al escenario actual y proyectado de escasez hídrica. Esta tesis tiene por objetivo explorar diferencias entre ORTs autónomas y anidadas en términos del desempeño en acciones colectivas de estas organizaciones, la prevalencia de sanciones y el liderazgo de sus presidentes. Para ello, se utilizó una muestra de 68 ORTs autónomas y anidadas de la Región del Maule. Mediante análisis de comparación de medias, se analizó el desempeño en acciones colectivas (i.e., tasas de cooperación en diferentes actividades de la organización) y habilidades asociadas al liderazgo de los presidentes. Los resultados muestran que las ORTs autónomas tienen un mejor desempeño, ya que presentan una mayor asistencia a reuniones y menor sobre extracción de agua; además, cuentan en mayor medida con sistemas de sanciones por no limpieza de canales. Por otro lado, los resultados indican que los presidentes de ORTs anidadas tienen mayor vinculación con profesionales y organizaciones externas públicas y privadas. En conclusión, la condición de anidamiento de ORTs tiene incidencia sobre la gestión del agua de riego, lo cual debería considerarse a la hora de diseñar o refinar políticas públicas agrícolas que buscan salvaguardar el estado y la sostenibilidad de los recursos hídricos. // ABSTRACT: The water management system in Chile is in the hands of Water User Organizations (WUOs), private entities responsible for the collection, conduction and distribution of the waters to which their owners are entitled. Among these are the Vigilance Boards (VBs), in charge of managing natural channels -such as rivers or reservoirs- and the Canal Associations (CAs) and Water Communities (WCs), in charge of managing artificial channels -such as primary channels and secondary - that distribute the water to the terminal users. Notwithstanding the above, there are cases in which WCs operate under the supervision of CAs, that is, a nesting situation occurs (i.e., nested WCs) that contrasts with an autonomous condition (autonomous WCs). This distinction is relevant when analyzing the performance of Terminal Irrigation Organizations (TIOs) that distribute water among the final users of the distribution system, since there is evidence that the characteristics and aspects of the governance of these organizations control water management. irrigation and the achievement of collective actions. The study of the performance of TIOs and their factors is especially relevant in the current and projected scenario of water scarcity. This thesis aims to explore differences between autonomous and nested TIOs in terms of the collective action performance of these organizations, the prevalence of sanctions and the leadership of their presidents. For this, a sample of 68 autonomous and nested TIOs from the Maule Region was used. Through means comparison analysis, the performance in collective actions (i.e., rates of cooperation in different activities of the organization) and skills associated with the leadership of the presidents were analyzed. The results show that the autonomous TIOs have a better performance, since they present a greater attendance at meetings and less on water extraction; In addition, to a greater extent, they have sanction systems for not cleaning channels. On the other hand, the results indicate that the presidents of nested TIOs have greater ties with professionals and external public and private organizations. In conclusion, the nesting condition of Terminal Irrigation Organizations has an impact on irrigation water management, which should be considered when designing or refining agricultural public policies that seek to safeguard the status and sustainability of water resources

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

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

Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}$and correspond to an integrated luminosity of$4.6\;{\rm f}{{{\rm b}}^{-1}}$. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum${{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}$and pseudorapidity$|\eta |\lt 1.9$, is measured to be${{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

Search for direct pair production of the top squark in all-hadronic final states in proton-proton collisions at s√=8 TeV with the ATLAS detector

The results of a search for direct pair production of the scalar partner to the top quark using an integrated luminosity of 20.1fb−1 of proton–proton collision data at √s = 8 TeV recorded with the ATLAS detector at the LHC are reported. The top squark is assumed to decay via t˜→tχ˜01 or t˜→ bχ˜±1 →bW(∗)χ˜01 , where χ˜01 (χ˜±1 ) denotes the lightest neutralino (chargino) in supersymmetric models. The search targets a fully-hadronic final state in events with four or more jets and large missing transverse momentum. No significant excess over the Standard Model background prediction is observed, and exclusion limits are reported in terms of the top squark and neutralino masses and as a function of the branching fraction of t˜ → tχ˜01 . For a branching fraction of 100%, top squark masses in the range 270–645 GeV are excluded for χ˜01 masses below 30 GeV. For a branching fraction of 50% to either t˜ → tχ˜01 or t˜ → bχ˜±1 , and assuming the χ˜±1 mass to be twice the χ˜01 mass, top squark masses in the range 250–550 GeV are excluded for χ˜01 masses below 60 GeV

Search for pair-produced long-lived neutral particles decaying to jets in the ATLAS hadronic calorimeter in ppcollisions at √s=8TeV

The ATLAS detector at the Large Hadron Collider at CERN is used to search for the decay of a scalar boson to a pair of long-lived particles, neutral under the Standard Model gauge group, in 20.3fb−1of data collected in proton–proton collisions at √s=8TeV. This search is sensitive to long-lived particles that decay to Standard Model particles producing jets at the outer edge of the ATLAS electromagnetic calorimeter or inside the hadronic calorimeter. No significant excess of events is observed. Limits are reported on the product of the scalar boson production cross section times branching ratio into long-lived neutral particles as a function of the proper lifetime of the particles. Limits are reported for boson masses from 100 GeVto 900 GeV, and a long-lived neutral particle mass from 10 GeVto 150 GeV

Search for R-parity-violating supersymmetry in events with four or more leptons in sqrt(s) =7 TeV pp collisions with the ATLAS detector

A search for new phenomena in final states with four or more leptons (electrons or muons) is presented. The analysis is based on 4.7 fb−1 of $\sqrt{s}=7\;\mathrm{TeV}$ proton-proton collisions delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in two signal regions: one that requires moderate values of missing transverse momentum and another that requires large effective mass. The results are interpreted in a simplified model of R-parity-violating supersymmetry in which a 95% CL exclusion region is set for charged wino masses up to 540 GeV. In an R-parity-violating MSUGRA/CMSSM model, values of m 1/2 up to 820 GeV are excluded for 10 < tan β < 40

Search for high-mass resonances decaying to dilepton final states in pp collisions at s√=7 TeV with the ATLAS detector

The ATLAS detector at the Large Hadron Collider is used to search for high-mass resonances decaying to an electron-positron pair or a muon-antimuon pair. The search is sensitive to heavy neutral Z′ gauge bosons, Randall-Sundrum gravitons, Z * bosons, techni-mesons, Kaluza-Klein Z/γ bosons, and bosons predicted by Torsion models. Results are presented based on an analysis of pp collisions at a center-of-mass energy of 7 TeV corresponding to an integrated luminosity of 4.9 fb−1 in the e + e − channel and 5.0 fb−1 in the μ + μ −channel. A Z ′ boson with Standard Model-like couplings is excluded at 95 % confidence level for masses below 2.22 TeV. A Randall-Sundrum graviton with coupling k/MPl=0.1 is excluded at 95 % confidence level for masses below 2.16 TeV. Limits on the other models are also presented, including Technicolor and Minimal Z′ Models