Identificação de reguladores mestres em adenocarcinoma de pulmão e sua utilização para a prospecção de compostos antitumorais

O câncer de pulmão é uma das neoplasias malignas mais incidentes e letais da oncologia. Ademais, o adenocarcinoma pulmonar compreende o subtipo histológico mais comum e cuja frequência tem aumentado em detrimento de outros tipos nos últimos anos, especialmente em mulheres. Portanto, o entendimento da patofisiologia deste tipo de câncer e a busca por biomarcadores confiáveis, além de novas abordagens terapêuticas e regimes de tratamento, constituem áreas importantes de pesquisa e avanço biomédico. Nas últimas décadas, a Biologia de Sistemas coalesceu e fortaleceu-se com o advento de tecnologias ômicas e da bioinformática, viabilizando e impulsionando o estudo da biologia no contexto de sistemas complexos. Desta forma, este trabalho procura utilizar dados transcriptômicos e estratégias de bioinformática para obter fatores de transcrição candidatos a reguladores mestre do adenocarcinoma pulmonar, utilizado métodos, conceitos e visões oriundas da Biologia de Sistemas. Adicionalmente, desenvolvemos uma metodologia de reposicionamento computacional de drogas e aplicamos esta estratégia para obter drogas candidatas a elaboração de novos regimes terapêuticos. O primeiro passo do estudo foi a reconstrução de redes de co-expressão gênica centradas em fatores de transcrição e seus alvos utilizando informação de tecido não-tumoral, a fim de estabelecer redes de referência. Posteriormente, os grupos de genes constituídos pelos fatores de transcrição e seus alvos, conjuntamente chamados de unidades regulatórias, foram investigados quanto a seus perfis de expressão diferencial utilizando estudos caso-controle. As unidades regulatórias dos fatores de transcrição enriquecidos de genes diferencialmente expressos em mais de 80% dos estudos caso-controle, para ambas as redes de referência, foram consideradas reguladores mestre candidatos da patologia. Esta estratégia resultou em nove fatores de transcrição – ATOH8, DACH1, EPAS1, ETV5, FOXA2, FOXM1, HOXA4, SMAD6 e UHRF1. Em seguida, testamos se os estados de ativação inferidos para estes fatores de transcrição possuíam potencial prognóstico em diferentes coortes de adenocarcinoma, e observamos que três dos nove mostraram associações consistentes com o desfecho de pacientes. Finalmente, utilizamos as unidades regulatórias destes três fatores de transcrição – FOXA2, FOXM1 e UHRF1 – para prospectar drogas candidatas a reposicionamento, o que resultou em seis compostos potencialmente capazes de reverter os perfis transcricionais encontrados no contexto patológico. Estes compostos são: deptropina, promazina, ácido valproico, azaciclonol, metotrexato e composto ChemBridge ID 5109870. Avaliações dos potenciais terapêuticos destes fármacos e seus mecanismos de ação neste câncer podem auxiliar no desenvolvimento de novos tratamentos. Da mesma forma, elucidação dos papéis biológicos específicos dos nove reguladores mestres também tem grande potencial de contribuir para o entendimento da biologia do adenocarcinoma de pulmão.Lung cancer is one of the most common and lethal pathologies of medical oncology. Furthermore, adenocarcinoma comprises the most prevalent lung cancer histological subtype, which frequency increased over other types in recent years, especially among women. For these reasons, further understanding about the pathophysiology of this type of cancer and the search for reliable biomarkers, for new therapeutic drugs and for improved treatment strategies are all important areas of biomedical research and development. In recent decades, the Systems Biology paradigm emerged and strengthened due to novel omic technologies and bioinformatics, enabling and enhancing the study of biological phenomena in the context of complex systems. Thus, this study aims to search for the transcription factors acting as master regulators of lung adenocarcinoma using transcriptomics and employing Systems Biology concepts and views. Additionally, we developed a computational drug repositioning method and implemented it to retrieve candidate molecules for new treatment strategies. The first step in our study involved the reconstruction of co-expression gene networks centered in transcription factors and their targets using non-tumoral data in order to establish reference networks. Afterwards, the groups of genes comprising transcription factors and their targets, collectively called regulatory units, were queried for their differential expression profiles using case-control studies. Regulatory units of the transcription factors enriched with differentially expressed genes in over 80% of case-control studies, for both reference networks, were considered master regulator candidates of the disease. This strategy retrieved nine transcription factors - ATOH8, DACH1, EPAS1, ETV5, FOXA2, FOXM1, HOXA4, SMAD6 and UHRF1. Following that, we tested whether the inferred activities of these master regulators' regulatory units were associated with patient survival using several cohorts datasets, which highlighted three of them consistently associated with patient outcome. Finally, the regulatory units of these three transcription factors - FOXA2, FOXM1 e UHRF1 - were used to query drug candidates for repositioning in lung adenocarcinoma, resulting in six molecules capable to revert disease's the transcriptional profile. These drugs were deptropine, promazine, valproic acid, azacyclonol, methotrexate and ChemBridge ID compound 5109870. The evaluation of their therapeutic potentials and mechanisms of action in lung cancer may assist the development of new treatments. Additionally, further investigations of the retrieved master regulators' roles may lead to improvements in our understanding of adenocarcinoma pathophysiology

Application of the Polynomial Chaos Expansion to the Uncertainty Propagation in Fault Transients in Nuclear Fusion Reactors: DTT TF Fast Current Discharge

Nuclear fusion reactors are composed of several complex components whose behavior may be not certain a priori. This uncertainty may have a significant impact on the evolution of fault transients in the machine, causing unexpected damage to its components. For this reason, a suitable method for the uncertainty propagation during those transients is required. The Monte Carlo method would be the reference option, but it is, in most of the cases, not applicable due to the large number of required, repeated simulations. In this context, the Polynomial Chaos Expansion has been considered as a valuable alternative. It allows us to create a surrogate model of the original one in terms of orthogonal polynomials. Then, the uncertainty quantification is performed repeatedly, relying on this much simpler and faster model. Using the fast current discharge in the Divertor Tokamak Test Toroidal Field (DTT TF) coils as a reference scenario, the following method has been applied: the uncertainty on the parameters of the Fast Discharge Unit (FDU) varistor disks is propagated to the simulated electrical and electromagnetic relevant effects. Eventually, two worst-case scenarios are analyzed from a thermal–hydraulic point of view with the 4C code, simulating a fast current discharge as a consequence of a coil quench. It has been demonstrated that the uncertainty on the inputs (varistor parameters) strongly propagates, leading to a wide range of possible scenarios in the case of accidental transients. This result underlines the necessity of taking into account and propagating all possible uncertainties in the design of a fusion reactor according to the Best Estimate Plus Uncertainty approach. The uncertainty propagation from input data to electrical, electromagnetic, and thermal hydraulic results, using surrogate models, is the first of its kind in the field of the modeling of superconducting magnets for nuclear fusion applications

He then said..: Understudied deviations from V2 in Early Germanic

ABSTRACT This paper discusses a V3-pattern in Early Germanic that has so far not been considered independently. In this construction, a clause-initial XP is followed by the adverbial element OHG do/OE þa/OS tho (lit. ‘then’), which is directly followed by the finite verb. Based on a pilot study of the OHG translation of Tatian’s gospel harmony and the OE Blickling Homilies, it is shown that the pattern exhibits slightly different properties in OE and OHG. In OHG, the element preceding do is usually a pronominal shifting topic, while in OE, the clause-initial XP may also be a full DP that is either a shifting topic or a continuing topic. To account for these differences between OE and OHG, we argue that OE þa is first-merged as the head of a clause-medial projection that serves to mark the boundary between the topic and the focus domain. In contrast, OHG do (and OS tho) is a topic marker that is either part of the fronted shifting topic, or base-generated as a head in the left clausal periphery. As to its internal syntax, we propose a grammaticalization path for do/þa/tho in which a demonstrative adverb first turns into an adverbial discourse marker that may also serve expletive functions before it eventually grammaticalizes into the topic particle addressed in this paper

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed sig- nificant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage

Integrated transcriptomics establish macrophage polarization signatures and have potential applications for clinical health and disease

Growing evidence defines macrophages (Mφ) as plastic cells with wide-ranging states of activation and expression of different markers that are time and location dependent. Distinct from the simple M1/M2 dichotomy initially proposed, extensive diversity of macrophage phenotypes have been extensively demonstrated as characteristic features of monocyte-macrophage differentiation, highlighting the difficulty of defining complex profiles by a limited number of genes. Since the description of macrophage activation is currently contentious and confusing, the generation of a simple and reliable framework to categorize major Mφ phenotypes in the context of complex clinical conditions would be extremely relevant to unravel different roles played by these cells in pathophysiological scenarios. In the current study, we integrated transcriptome data using bioinformatics tools to generate two macrophage molecular signatures. We validated our signatures in in vitro experiments and in clinical samples. More importantly, we were able to attribute prognostic and predictive values to components of our signatures. Our study provides a framework to guide the interrogation of macrophage phenotypes in the context of health and disease. The approach described here could be used to propose new biomarkers for diagnosis in diverse clinical settings including dengue infections, asthma and sepsis resolution

Mortality of septic shock patients is associated with impaired mitochondrial oxidative coupling efficiency in lymphocytes : a prospective cohort study

Background: Septic shock is a life-threatening condition that challenges immune cells to reprogram their mitochondrial metabolism towards to increase ATP synthesis for building an appropriate immunity. This could print metabolic signatures in mitochondria whose association with disease progression and clinical outcomes remain elusive. Method: This is a single-center prospective cohort study performed in the ICU of one tertiary referral hospital in Brazil. Between November 2017 and July 2018, 90 consecutive patients, aged 18 years or older, admitted to the ICU with septic shock were enrolled. Seventy-five patients had Simplified Acute Physiology Score (SAPS 3) assessed at admission, and Sequential Organ Failure Assessment (SOFA) assessed on the first (D1) and third (D3) days after admission. Mitochondrial respiration linked to complexes I, II, V, and biochemical coupling efficiency (BCE) were assessed at D1 and D3 and Δ (D3–D1) in isolated lymphocytes. Clinical and mitochondrial endpoints were used to dichotomize the survival and death outcomes. Our primary outcome was 6-month mortality, and secondary outcomes were ICU and hospital ward mortality. Results: The mean SAPS 3 and SOFA scores at septic shock diagnosis were 75.8 (± 12.9) and 8 (± 3) points, respectively. The cumulative ICU, hospital ward, and 6-month mortality were 32 (45%), 43 (57%), and 50 (66%), respectively. At the ICU, non-surviving patients presented elevated arterial lactate (2.8 mmol/L, IQR, 2–4), C-reactive protein (220 mg/L, IQR, 119–284), and capillary refill time (5.5 s, IQR, 3–8). Respiratory rates linked to CII at D1 and D3, and ΔCII were decreased in non-surviving patients. Also, the BCE at D1 and D3 and the ΔBCE discriminated patients who would evolve to death in the ICU, hospital ward, and 6 months after admission. After adjusting for possible confounders, the ΔBCE value but not SOFA scores was independently associated with 6-month mortality (RR 0.38, CI 95% 0.18–0.78; P = 0.009). At a cut-off of − 0.002, ΔBCE displayed 100% sensitivity and 73% specificity for predicting 6-month mortality. Conclusions: The ΔBCE signature in lymphocytes provided an earlier recognition of septic shock patients in the ICU at risk of long-term deterioration of health status

Il fenomeno delle dipendenze nella ASL della Provincia di Lecco. Dati anno 2009

---Il Report analizza il fenomeno delle dipendenze nella ASL della provincia di Lecco. La descrizione del fenomeno si sviluppa intorno all\u27analisi degli indicatori individuati dall\u27Osservatorio Europeo delle Dipendenze di Lisbona (OEDT): 1-uso di sostanze nella popolazione generale (questo indicatore va a rilevare i comportamenti nei confronti di alcol e sostanze psicoattive da parte della popolazione generale); 2-prevalenza d\u27uso problematico delle sostanze psicoattive; 3-domanda di trattamento degli utilizzatori di sostanze; 4-mortalit? degli utilizzatori di sostanze; 5-malattie infettive. Altri due importanti indicatori che si stanno sviluppando, e che vengono qui illustrati, sono l\u27analisi delle Schede di Dimissione Ospedaliera (SDO) e gli indicatori relativi alle conseguenza sociali dell\u27uso di droghe (criminalit? droga correlata). Inoltre sono state applicate diverse metodologie standard di stima sia per quantificare la quota parte sconosciuta di utilizzatori di sostanze che non afferiscono ai servizi, sia per identificarne alcune caratteristiche