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Heterogeneous IL-9 production by circulating skin-tropic and extracutaneous memory T cells in atopic dermatitis patients
No full textInterleukin (IL)-9 is present in atopic dermatitis (AD) lesions and is considered to be mainly produced by skin-homing T cells expressing the cutaneous lymphocyte-associated antigen (CLA). However, its induction by AD-associated triggers remains unexplored. Circulating skin-tropic CLA+ and extracutaneous/systemic CLA- memory T cells cocultured with autologous lesional epidermal cells from AD patients were activated with house dust mite (HDM) and staphylococcal enterotoxin B (SEB). Levels of AD-related mediators in response to both stimuli were measured in supernatants, and the cytokine response was associated with different clinical characteristics. Both HDM and SEB triggered heterogeneous IL-9 production by CLA+ and CLA- T cells in a clinically homogenous group of AD patients, which enabled patient stratification into IL-9 producers and non-producers, with the former group exhibiting heightened HDM-specific and total IgE levels. Upon allergen exposure, IL-9 production depended on the contribution of epidermal cells and class II-mediated presentation; it was the greatest cytokine produced and correlated with HDM-specific IgE levels, whereas SEB mildly induced its release. This study demonstrates that both skin-tropic and extracutaneous memory T cells produce IL-9 and suggests that the degree of allergen sensitization reflects the varied IL-9 responses in vitro, which may allow for patient stratification in a clinically homogenous population
Network representations of drum sequences for classification and generation
No full textComplex networks have emerged as a powerful framework for understanding and analyzing musical compositions, revealing underlying structures and dynamics that may not be immediately apparent. This article explores the application of complex network representations to the study of symbolic drum sequences, a topic that has received limited attention in the literature. The proposed methodology involves encoding drum rhythms as directed, weighted complex networks, where nodes represent drum events, and edges capture the temporal succession of these events. This network-based representation allows for the analysis of similarities between different drumming styles, as well as the generation of novel drum patterns. Through a series of experiments, we demonstrate the effectiveness of this approach. First, we show that the complex network representation can accurately classify drum patterns into their respective musical styles, even with a limited number of training samples. Second, we present a generative model based on Markov chains operating on the network structure, which is able to produce new drum patterns that retain the essential features of the training data. Finally, we validate the perceptual relevance of the generated patterns through listening tests, where participants are unable to distinguish the generated patterns from the original ones, suggesting that the network-based representation effectively captures the underlying characteristics of different drumming styles. The findings of this study have significant implications for music research, genre classification, and generative music applications, highlighting the potential of complex networks to provide a transparent and elegant approach to the analysis and synthesis of rhythmic structures in music
La producció de cinema a Catalunya, 2024
No full textAmb la col·laboració de Productors Audiovisuals de Catalunya (PAC) i Acadèmia de Cinema Català (ACC
Democratic Principle and Nationalistic Aspirations in Plurinational States. A Republican Approach
No full textEuropean integration sets up a common acquis beyond state boundaries. Being a political actor in this process involves a commitment to the values on which the EU itself is founded and the rights it safeguards. European integration has paved the way for new ways of political participation that have given a voice to non state actors in this process. From this perspective, this contribution examines the legitimacy of nationalist claims inside EU member states as well as the states facing such claims. I shall argue that as long as both are committed to the common acquis, then both of them are equally legitimate to support their positions. But they are also required to settle these disputes by democratic means in line with that common ground
Multi-turn attacks for automated LLM red teaming
No full textTreball fi de màster de: Erasmus Mundus joint Master in Artificial Intelligence (EMAI)Supervisora: Prof. Lejla Batina
Co-Supervisora: Dra. Maria-Irina NicolaeLarge language models (LLMs) are increasingly used in applications within various domains such as healthcare, research, and education. With the growing use of these models, especially in critical systems (e.g., self-driving cars), the security of these models becomes increasingly crucial. Automated red teaming aims to efficiently and effectively uncover the security vulnerabilities of LLMs and LLM-based applications so that these can be mitigated before being misused by malicious parties. Red teaming often utilizes jailbreak attacks. Most works on jailbreak attacks in the literature focus on single-turn attacks, which are executed as a single input prompt to the target LLM within one conversation turn. Multi-turn attacks, however, better represent manual red teaming, which is also often done over several conversation turns. Additionally, multi-turn attacks have been shown to uncover a greater number and variety of weaknesses and security vulnerabilities compared to single-turn
attacks. While research on multi-turn attacks has increased recently, most works on automatic jailbreaking are still centered on single-turn techniques. This work aims to contribute to the improvement and spreading of multi-turn attacks such that they can be used in automated red teaming to improve the security of LLM applications. The focus of this work lies on the automatic black-box multi-turn attack Generative Offensive Agent Tester (GOAT). Specifically, we extend Generative Offensive Agent Tester (GOAT) with new jailbreak strategies, and both GOAT and these additional strategies are implemented in the Azure Python Risk Identification Tool (PyRIT) red teaming and security evaluation framework. Extensive experiments are conducted to compare the performance of the proposed changes in relation to the original GOAT method in a variety of setups involving a number of tuned attackers and scorer models. A comprehensive analysis of these experimental results reveals that the proposed modifications result in promising improvements in most setups
Emergence and fragmentation of the alpha-band driven by neuronal network dynamics
No full textRhythmic neuronal network activity underlies brain oscillations. To investigate how connected neuronal networks contribute to the emergence of the band and to the regulation of Up and Down states, we study a model based on synaptic short-term depression-facilitation with afterhyperpolarization (AHP). We found that the band is generated by the network behavior near the attractor of the Up-state. Coupling inhibitory and excitatory networks by reciprocal connections leads to the emergence of a stable band during the Up states, as reflected in the spectrogram. To better characterize the emergence and stability of thalamocortical oscillations containing and rhythms during anesthesia, we model the interaction of two excitatory networks with one inhibitory network, showing that this minimal topology underlies the generation of a persistent band in the neuronal voltage characterized by dominant Up over Down states. Finally, we show that the emergence of the band appears when external inputs are suppressed, while fragmentation occurs at small synaptic noise or with increasing inhibitory inputs. To conclude, oscillations could result from the synaptic dynamics of interacting excitatory neuronal networks with and without AHP, a principle that could apply to other rhythms.LZ received salary from the FRM (FDT202012010690). This project received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 882673) and from ANR-NEUC 0001. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Decoding pulmonary embolism: pathophysiology, diagnosis, and treatment
No full textPulmonary Embolism (PE) is a life-threatening condition initiated by the presence of blood clots in the pulmonary arteries, leading to severe morbidity and mortality. Underlying mechanisms involve endothelial dysfunction, including impaired blood flow regulation, a pro-thrombotic state, inflammation, heightened oxidative stress, and altered vascular remodeling. These mechanisms contribute to vascular diseases stemming from PE, such as recurrent thromboembolism, chronic thromboembolic pulmonary hypertension, post-thrombotic syndrome, right heart failure, and cardiogenic shock. Detailing key risk factors and utilizing hemodynamic stability-based categorization, the review aims for precise risk stratification by applying established diagnostic tools and scoring systems. This article explores both conventional and emerging biomarkers as potential diagnostic tools. Additionally, by synthesizing existing knowledge, it provides a comprehensive outlook of the current enhanced PE management and preventive strategies. The conclusion underscores the need for future research to improve diagnostic accuracy and therapeutic effectiveness in PE
Evolutionary dynamics of cancer drug resistance and prediction of tumor modes of growth
No full textCancer remains a significant challenge in healthcare and is a leading concern worldwide. Despite advances in cancer therapy and the identification of numerous actionable events, relapse and drug resistance continue to complicate treatment outcomes. This thesis investigates the evolution of cancer from the perspectives of population genetics, computational simulations, and data analysis .We present a novel method developed to infer patterns of tumor growth in both primary tumors and metastatic sites using approximate Bayesian computation. By considering the sampling noise in DNA sequencing that occurs with the construction of the variant allele frequency distribution, we enable the reconstruction of tumor growth modes in samples with both high and low coverage distributions. Furthermore, we investigate the phenomenon of drug resistance using numerical simulations. We show that using the variant allele frequency distribution of a cancer sample, together with a target of drug resistance genes, informs about the time to relapse.
Next, we analyze genomic patient data to identify genes that, when mutated, may contribute to either drug resistance or promote the development of metastases. This involves comparing cohort-wise selection estimates between primary tumors and their metastatic counterparts. Finally, we analyze the influence of genetic heterogeneity on the level of gene expression counts from single-cell RNA data in patients with acute myeloid leukemia. This work advances the field of cancer evolution by providing a new method to infer tumor modes of growth and helping to understand the measurability of cancer drug resistance in current sequencing methods.El càncer segueix sent un repte significatiu en l'àmbit de la salut i una de les principals preocupacions a nivell mundial. Malgrat els avenços en teràpies i la identificació d’objectius rellevants, les recaigudes i la resistència a fàrmacs segueixen complicant els pronòstics dels tractaments. Aquesta tesi investiga l'evolució del càncer des de les perspectives de la genètica de poblacions, les simulacions computacionals i l'anàlisi de dades.Presentem un mètode nou desenvolupat amb l’objectiu d’inferir patrons de creixement tumoral tant en tumors primaris com en metastàtics utilitzant el càlcul bayesià aproximat. Considerant el soroll de mostreig en la seqüenciació de l'ADN que es produeix en la construcció de la distribució de freqüència de l’al·lel alternatiu, possibilitem la reconstrucció dels modes de creixement del tumor en mostres amb distribucions de cobertura tant altes com baixes.A més, investiguem el fenomen de la resistència a fàrmacs utilitzant simulacions numèriques. Mostrem que utilitzant la distribució de freqüència de l’al·lel alternatiu d'una mostra de càncer juntament amb un conjunt de gens de resistència a fàrmacs obtenim informació sobre el temps fins a la recaiguda.A continuació, analitzem dades genòmiques de pacients per identificar gens que al mutar poden contribuir tant a la resistència a fàrmacs com a promoure el desenvolupament de metàstasis. Això implica comparar estimacions de selecció per cohorts de tumors primaris i els seus equivalents metastàtics.Finalment, analitzem la influència de la heterogeneïtat genètica en el nivell de recomptes d'expressió gènica a partir de dades d'ARN de cèl·lula única en pacients amb leucèmia mieloide aguda.Programa de Doctorat en Biomedicin
Association of environmental noise exposure with cortisol levels in children from eight European birth cohorts
No full textEnvironmental noise is a major environmental risk factor for public health. According to the noise reaction model the release of stress hormones like cortisol in response to noise exposure, plays a key role in the development of noise-induced health effects. We aimed to study the association between environmental noise with both acute (UCC) and cumulative (HCC) cortisol levels in children 5-12 years of age. To do so, we analysed data from the HELIX cohort -with spot UCC data- and from the Generation R and INMA cohorts (Gipuzkoa and Sabadell) -with HCC data. The analytical sample involved: 750 HELIX children (mean age = 7.75), 1326 Generation R children (mean age = 6.06), 111 INMA-Sabadell children (mean age = 8.75) and 288 INMA-Gipuzkoa children (mean age = 7.85). Day-evening-night equivalent (Lden) environmental noise exposure during the year of the follow-up was estimated in the addresses of participants, using existing noise maps. Directed acyclic graphs (DAGs) were used to identify appropriate covariates and reduce the chance for biased estimation. We used mixed-effects modelling and linear modelling to examine the association between Lden and cortisol concentration using complete case analyses. None of the models reached the statistical significance. We observed no correlation between HCC and UCC in INMA-Sabadell participants, for whom both urinary and hair cortisol data were available. Future research should prioritize investigating the effects of environmental noise on HCC, as it may serve as a more reliable indicator for assessing associations with chronic exposures. Additionally, future studies on noise-induced health effects in children should incorporate other biomarkers of stress and chronic inflammation to provide a more comprehensive understanding of these associations.The study was supported by the European Community's Seventh Framework Programme [FP7/2007–2013] under grant agreement no. 308333 [the HELIX project], and from the European Union's Horizon 2020 research and innovation programme (LIFECYCLE, grant agreement No 733206, 2016; EUCAN-Connect grant agreement No 824989; ATHLETE, grant agreement No 874583; LongITools, grant agreement No 874739). Cortisol and related Glucocorticosteroids were measured within the HELIX cohorts as part of the UK Research and Innovation METAGE project (Grant ref: MR/S03532X/1). We further acknowledge funding from Instituto de Salud Carlos III (FIS-PI06/0867, FIS-PI09/00090, FIS464,445PI13/02187, FIS-PI18/01142 include FEDER funds, Red INMA G03/176; CB06/02/0041; PI041436; PI081151 incl. FEDER funds; PI12/01890 incl. FEDER funds; CP13/00054 incl. FEDER funds, CPII18/00018), CIBERESP, Department of Health of the BasqueGovernment (2005111093, 2009111069, 2013111089 and 2015111065), and the Provincial Government of Gipuzkoa (DFG06/002, DFG08/001, DFG15/221 and DFG89/17), Generalitat de Catalunya-CIRIT 1999SGR 00241, Generalitat de Catalunya-AGAUR (2009 SGR 501, 2014 SGR 822), Fundació La marató de TV3 (090430), Spanish Ministry of Economy and Competitiveness (SAF2012-32991 incl. FEDER funds), Agence Nationale de Securite Sanitaire de l’Alimentation de l’Environnement et du Travail (1262C0010), EU Commission (261357, 308333, 603794 and 634453). We acknowledge support from the grant CEX2023-0001290-S funded by MCIN/AEI/10.13039/501100011033, and support from the Generalitat de Catalunya through the CERCA Program. The general design of the Generation R Study is made possible by financial support from the Erasmus MC, University Medical Center, Rotterdam, Erasmus University Rotterdam, Netherlands Organization for Health Research and Development (ZonMw), Netherlands Organisation for Scientific Research (NWO), Ministry of Health, Welfare and Sport and Ministry of Youth and Families. VJ received funding from a Consolidator Grant from the European Research Council (ERC-2014-CoG-648916). The study sponsors had no role in the study design, data analysis, interpretation of data, or writing of this report.
BiB receives funding from the UK Medical Research Council (MRC) and UK Economic and Social Science Research Council (ESRC) (MR/N024391/1); the British Heart Foundation (CS/16/4/32482); a Wellcome Infrastructure Grant (WT101597MA); the National Institute for Health Research under its Applied Research Collaboration for Yorkshire and Humber (NIHR200166). The National Institute for Health Research Clinical Research Network provided research delivery support for this study. The views expressed in this publication are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. The EDEN study was supported by Foundation for medical research (FRM), National Agency for Research (ANR), National Institute for Research in Public health (IRESP: TGIR cohorte santé 2008 program), French Ministry of Health (DRG), French Ministry of Research, INSERM Bone and Joint Diseases National Research (PRO-A), and Human Nutrition National Research Programs, Paris-Sud University, Nestlé, French National Institute for Population Health Surveillance (InVS), French National Institute for Health Education (INPES), the European Union FP7 programmes (FP7/2007–2013, HELIX, ESCAPE, ENRIECO, Medall projects), Diabetes National Research Program (through a collaboration with the French Association of Diabetic Patients (AFD)), French Agency for Environmental Health Safety (now ANSES), Mutuelle Générale de l’Education Nationale a complementary health insurance (MGEN), French national agency for food security, French-speaking association for the study of diabetes and metabolism (ALFEDIAM). The “Rhea” project was financially supported by European projects (EU FP6–2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7–2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009-single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU-FP7-HEALTH-2012 Proposal No 308333 HELIX, ATHLETE) and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011–2014; “Rhea Plus”: Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012–2015). The funding bodies have not affected in any way the study and the presented results. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research