APPLIED QUANTITATIVE PROTEOMICS ANALYSIS

En esta tesis se ha aplicado el estado del arte en análisis cuantitativo en proteómica. Los datos analizados en este trabajo, provenientes de tres proyectos distintos, fueron obtenidos usando tres de las técnicas más utilizadas en proteómica: cuantificación label-free, marcaje isobárico y SWATH. Los resultados obtenidos en los diferentes proyectos son también interpretados mediante múltiples herramientas bioinformáticas. La cuantificación label-free es utilizada aquí para obtener la combinación óptima de software y parámetros usando un conjunto de datos públicos. El marcaje isobárico, usando TMT, se emplea en el estudio de los diferentes perfiles de expresión proteica, obtenidos con dos modelos de hipoxia de diferente severidad en cerebros de rata. La técnica SWATH se busca en la búsqueda de biomarcadores de síndorme de ovario poliquístico en plasma. Por último, los elementos necesarios para la implantación de una plataforma de análisis proteómica , en términos de software y hardware, se describen en forma detallada. In this thesis, the state of the art in quantitative proteomics analysis has been applied. The data analyzed in this work, coming from three different projects, were acquired using three of the most used techniques in proteomics: label-free, isobaric labeling and SWATH. The results obtained in the different projects are also interpreted using multiple bioinformatics tools. The label-free quantization is used here to asses the optimal combination of software and parameters using a public data set. Isobaric labeling, using TMT, is employed to study the different profiles in protein expression when two hypoxic models, with different severity, are applied in rat brains. The SWATH technique is used in the search of biomarkers for polycystic ovary syndrome in plasma. Finally, the elements required for setting up a platform for proteomics analysis, both in terms of hardware and software, are comprehensively described.Tesis Univ. Jaén. Departamento de Biología Experimenta

Microscale sulfur cycling in the phototrophic pink berry consortia of the Sippewissett Salt Marsh

Microbial metabolism is the engine that drives global biogeochemical cycles, yet many key transformations are carried out by microbial consortia over short spatiotemporal scales that elude detection by traditional analytical approaches. We investigate syntrophic sulfur cycling in the ‘pink berry’ consortia of the Sippewissett Salt Marsh through an integrative study at the microbial scale. The pink berries are macroscopic, photosynthetic microbial aggregates composed primarily of two closely associated species: sulfide-oxidizing purple sulfur bacteria (PB-PSB1) and sulfate-reducing bacteria (PB-SRB1). Using metagenomic sequencing and 34S-enriched sulfate stable isotope probing coupled with nanoSIMS, we demonstrate interspecies transfer of reduced sulfur metabolites from PB-SRB1 to PB-PSB1. The pink berries catalyse net sulfide oxidation and maintain internal sulfide concentrations of 0–500 μm. Sulfide within the berries, captured on silver wires and analysed using secondary ion mass spectrometer, increased in abundance towards the berry interior, while δ34S-sulfide decreased from 6‰ to −31‰ from the exterior to interior of the berry. These values correspond to sulfate–sulfide isotopic fractionations (15–53‰) consistent with either sulfate reduction or a mixture of reductive and oxidative metabolisms. Together this combined metagenomic and high-resolution isotopic analysis demonstrates active sulfur cycling at the microscale within well-structured macroscopic consortia consisting of sulfide-oxidizing anoxygenic phototrophs and sulfate-reducing bacteria

Genetic Insights into the Heterogeneity and Comorbidity of Substance Use Disorders

[eng] Substance use disorders (SUDs) are psychiatric disorders characterized by a recurring desire to continue taking a substance regardless of its destructive consequences. The etiology of SUDs is complex and multifactorial, where both genetic and environmental factors have an impact on the disease development. In addition, SUDs often co-occur at high prevalence with other psychiatric conditions, significantly impacting life expectancy, disease severity and societal burden. Over the past decade, genome-wide association studies (GWASs) have identified various risk loci for substance-specific SUD, as well as a shared genetic vulnerability for addiction. In addition, post-GWAS analyses have helped unravel the complex genetic architecture of SUDs, which can also involve an interplay of gene-environment interactions, and its relationship with comorbid mental health conditions. Current research in this field is making collective efforts to provide deeper and clearer knowledge into the genetic and environmental factors involved into the co-occurrence of SUDs and psychiatric disorders, which may be partially driving the high heterogeneity observed in SUDs, and the biological mechanisms driving these relationships. The present thesis comprises two studies that leverage in-house clinical cohorts, with both phenotypical and genetic data available, and state-of-the-art genomic techniques to investigate the shared genetic liability between SUDs and co-occurring traits, and to shed light into the genetic underpinnings of SUDs heterogeneity. The first study particularly focused on the relationship between SUDs and attention-deficit and hyperactivity disorder (ADHD). In this study, we tested whether the genetic liability to five SUD-related phenotypes share a common genetic background in both the general population and clinically diagnosed ADHD individuals, using an in-house sample of 989 subjects and polygenic scores (PGSs) analyses. We further explored the genetic overlap and the causal relationship between ADHD and SUDs using genetic correlation and Mendelian randomization analyses. Our results confirmed a significant genetic correlation between ADHD and SUDs and supported the current literature on the causal effect of the genetic liability to ADHD on the risk for SUDs. We provided novel findings on the effect of the genetic liability to lifetime cannabis use on an increased risk for ADHD and found evidence of a shared genetic background underlying SUDs between general population and ADHD, at least for lifetime cannabis use, alcohol dependence and smoking initiation. The second study aimed to disentangle SUDs heterogeneity using multidimensional data from a deeply phenotyped SUDs cohort of 1,427 individuals and PGSs for comorbid psychiatric disorders, behavioral and other related traits. We systematically explored the associations between the PGSs and 39 SUD-related phenotypes, and performed PGSs-environment interaction analyses using information on lifetime emotional, physical and/or sexual abuse. Our results revealed different patterns of associations between the genetic liability for mental health-related traits and SUD-related phenotypes, which may help explain part of the heterogeneity observed in SUDs. We also found evidence of a PGS-environment interaction showing that genetic liability for suicide attempt worsened the psychiatric status in SUDs individuals with a history of emotional physical and/or sexual abuse. Overall, the results of the present thesis provide new insights into the genetic overlap and causal relationships between SUDs and ADHD and contribute to a better understanding of the role of the genetic liability for psychiatric disorders and related traits, as well as its interaction with adverse life experiences, in the complexity of SUD heterogeneity. Lastly, this thesis provides a general discussion of the findings, which offers an extensive interpretation of the results in the context of existing literature, discusses the main methodological implications and outlines prospective directions for advancing in this line of research.[cat] Els trastorns per l'ús de substàncies (TUS) són trastorns psiquiàtrics caracteritzats per un desig recurrent de continuar prenent una o diverses substàncies, independentment de les seves conseqüències destructives. L'etiologia dels TUS és complexa i multifactorial, on tant factors genètics com ambientals tenen un impacte en el desenvolupament de la malaltia. A més, els TUS sovint es presenten simultàniament amb altres trastorns psiquiàtrics, afectant significativament la severitat de la malaltia, l’esperança de vida i la càrrega en la societat. Durant l'última dècada, els estudis d'associació del genoma complet (GWASs) han identificat diverses variants genètiques de risc per a TUS de substàncies específiques, així com una vulnerabilitat genètica compartida per a l'addicció. A més, les anàlisis post-GWAS han ajudat a desxifrar l'arquitectura genètica complexa dels TUS, que també pot implicar la interacció entre gens i ambient, i la seva relació amb trastorns de salut mental comòrbids. La recerca actual en aquest camp està focalitzada en profunditzar en el coneixement sobre els factors genètics i ambientals involucrats en la coexistència del TUS i trastorns psiquiàtrics, el qual pot ser parcialment responsable de l’alta heterogeneïtat observada en el TUS, i els mecanismes biològics implicats. La present tesi està composta per dos estudis que utilitzen cohorts clíniques, amb dades fenotípiques i genètiques disponibles, i tècniques genòmiques actuals per explorar la carga genètica compartida entre els TUS i els trets comòrbids, i per investigar la heterogeneïtat dels TUS des del punt de vista genètic. El primer estudi es centra particularment en la relació entre els TUS i el trastorn per dèficit d’atenció i hiperactivitat (TDAH). En aquest estudi, vam testar si la càrrega genètica per a cinc fenotips de TUS comparteixen una base genètica comuna en la població general i en individus amb TDAH, fent servir un mostra interna de 989 individus i anàlisis de puntuacions poligèniques (PGSs). Seguidament, vam explorar el solapament genètic i la relació causal entre el TDAH i els TUS utilitzant anàlisis de correlació genètica i de randomització mendeliana. Els nostres resultats confirmen una base genètic comuna entre el TDAH i els TUS i donen suport a la literatura actual sobre l'efecte causal de la càrrega genètica pel TDAH en el risc de TUS. A més, descrivim per primera vegada l'efecte causal de la càrrega genètica per a l'ús de cànnabis en el risc de TDAH i trobem evidències d'un component genètic compartit subjacent als TUS en la població general i en els individus amb TDAH, almenys per a l'ús de cànnabis, la dependència a l'alcohol i l'inici del consum de tabac. El segon estudi té com a objectiu desxifrar la heterogeneïtat dels TUS utilitzant dades multidimensionals d'una cohort de TUS de 1,427 individus dels quals es disposa una àmplia informació fenotípica, i PGSs per a trastorns psiquiàtrics comòrbids, trets del comportament i altres trets relacionats. Vam explorar les associacions entre els PGSs i 39 fenotips de TUS, i vam portar a terme anàlisis d’interacció PGS-ambient utilitzant informació sobre abús emocional, físic i/o sexual al llarg de la vida. Els nostres resultats revelen diferents patrons d'associacions entre la càrrega genètica per a trets relacionats amb la salut mental i fenotips de TUS, el que pot ajudar a explicar part de la heterogeneïtat observada en els TUS. També trobem evidència d'una interacció PGS-ambient que mostra que la càrrega genètica per a intents de suïcidi empitjora l'estat psiquiàtric en individus amb TUS que han patit abús emocional, físic i/o sexual. En conjunt, els resultats de la present tesi aporten noves perspectives sobre el solapament genètic i les relacions causals entre els TUS i el TDAH i contribueixen a una millor comprensió del paper de la càrrega genètica pels trastorns psiquiàtrics i trets relacionats, així com la seva interacció amb experiències adverses al llarg de la vida, en la complexitat de la heterogeneïtat dels TUS. Finalment, aquesta tesi ofereix una discussió general, la qual proporciona una extensa interpretació dels resultats en el context de la literatura existent, discuteix les principals implicacions metodològiques i detalla les futures direccions per avançar en aquesta línia de investigació

Ecological Causal Assessment

Edited by experts at the leading edge of the development of causal assessment methods for more than two decades, Ecological Causal Assessment gives insight and expert guidance on how to identify cause-effect relationships in environmental systems. The book discusses the importance of asking the fundamental question "Why did this effect happen?" be

Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods

We test the adequacies of several proposed and two new statistical methods for recovering the causal structure of systems with feedback from synthetic BOLD time series. We compare an adaptation of the first correct method for recovering cyclic linear systems; Granger causal regression; a multivariate autoregressive model with a permutation test; the Group Iterative Multiple Model Estimation (GIMME) algorithm; the Ramsey et al. non-Gaussian methods; two non-Gaussian methods by Hyvärinen and Smith; a method due to Patel et al.; and the GlobalMIT algorithm. We introduce and also compare two new methods, Fast Adjacency Skewness (FASK) and Two-Step, both of which exploit non-Gaussian features of the BOLD signal. We give theoretical justifications for the latter two algorithms. Our test models include feedback structures with and without direct feedback (2-cycles), excitatory and inhibitory feedback, models using experimentally determined structural connectivities of macaques, and empirical human resting-state and task data. We find that averaged over all of our simulations, including those with 2-cycles, several of these methods have a better than 80% orientation precision (i.e., the probability of a directed edge is in the true structure given that a procedure estimates it to be so) and the two new methods also have better than 80% recall (probability of recovering an orientation in the true structure)

Mechanisms Governing Mesothelial Clearance by Ovarian Cancer Spheroids

Metastatic dissemination of ovarian tumors involves the invasion of multi-cellular tumor cell clusters into the mesothelial cell lining of organs in the peritoneal cavity. We developed an in vitro assay that models this initial step of ovarian cancer metastasis to investigate the mechanisms of invasion. Pre-clustered ovarian cancer multicellular spheroids are incubated with GFP-expressing mesothelial monolayers and the extent of mesothelial invasion is monitored by time-lapse video microscopy

EVALUATING ARTIFICIAL INTELLIGENCE FOR OPERATIONS IN THE INFORMATION ENVIRONMENT

Recent advances in artificial intelligence (AI) portend a future of accelerated information cycles and intensified technology diffusion. As AI applications become increasingly prevalent and complex, Special Operations Forces (SOF) face the challenge of discerning which tools most effectively address operational needs and generate an advantage in the information environment. Yet, SOF currently lack an end user–focused evaluation framework that could assist information practitioners in determining the operational value of an AI tool. This thesis proposes a practitioner’s evaluation framework (PEF) to address the question of how SOF should evaluate AI technologies to conduct operations in the information environment (OIE). The PEF evaluates AI technologies through the perspective of the information practitioner who is familiar with the mission, the operational requirements, and OIE processes but has limited to no technical knowledge of AI. The PEF consists of a four-phased approach—prepare, design, conduct, recommend—that assesses nine evaluation domains: mission/task alignment; data; system/model performance; user experience; sustainability; scalability; affordability; ethical, legal, and policy considerations; and vendor assessment. By evaluating AI through a more structured, methodical approach, the PEF enables SOF to identify, assess, and prioritize AI-enabled tools for OIE.Outstanding ThesisMajor, United States ArmyApproved for public release. Distribution is unlimited

2016 International Land Model Benchmarking (ILAMB) Workshop Report

As earth system models (ESMs) become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of terrestrial biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistryclimate feedbacks and ecosystem processes in these models are essential for reducing the acknowledged substantial uncertainties in 21st century climate change projections