Helder Takashi Imoto Nakaya.

A divulgação de resultados científicos e linhas de pesquisa ao público leigo é um exercício desafiador. Pesquisadores geralmente não estão preparados ou motivados para realizar essa tarefa que é essencial ao progresso da ciência. O objetivo deste projeto é treinar alunos na transmissão do conhecimento científico de uma forma acessível, rápida e divertida. Junto aos pesquisadores, o aluno irá criar vídeos curtos contendo animações que expliquem resultados científicos e linhas de pesquisa usando para isso uma linguagem simples e sem jargões ou termos técnicos. Os vídeos serão disponibilizados em redes sociais ou em websites do departamento ou do laboratório do pesquisador.
Projeto aprovado pelo programa "Bolsa Aprender com Cultura e Extensão".

A disseminação massiva de desinformação científica em saúde, exacerbada durante a pandemia de COVID-19, representa um desafio crítico para a saúde pública. A rápida propagação de fake news, especialmente em plataformas de comunicação digital como o WhatsApp, comprometeu a eficácia das campanhas de saúde e minou a confiança nas instituições científicas. Este projeto visa enfrentar esse problema através do desenvolvimento de um chatbot para WhatsApp que utiliza inteligência artificial multimodal. A ferramenta será capaz de analisar e verificar a veracidade de informações em diferentes formatos de mídia, como textos, áudios, imagens, fotos e vídeos, fornecendo respostas em linguagem natural. O problema central abordado é a necessidade urgente de ferramentas eficazes para combater a desinformação em saúde, que seja acessível e escalável. A hipótese é que a integração de IA multimodal com uma plataforma amplamente utilizada como o WhatsApp pode fornecer uma solução inovadora e eficaz. Evidências sugerem que chatbots equipados com IA são capazes de interagir de forma eficiente com usuários, e a combinação com modelos avançados de linguagem e análise multimodal promete uma verificação de informações mais precisa e contextual. A estratégia metodológica inclui o desenvolvimento de um modelo de Recuperação Aumentada por Geração (RAG), treinamento com dados de fontes confiáveis, personalização de respostas, e implementação de funcionalidades educativas e de análise de sentimento. O projeto será escalável, com potencial para adaptação a diferentes regiões e suportando múltiplos idiomas, garantindo sua aplicabilidade no combate à desinformação em saúde em contextos diversos.

As doenças crônicas não transmissíveis, como diabetes, hipertensão e doenças cardiovasculares, representam desafios significativos para a saúde pública no Brasil, devido à sua alta prevalência e às complicações graves associadas. Este projeto propõe o desenvolvimento de uma plataforma de inteligência artificial (IA) que integre dados clínicos, laboratoriais e demográficos de pacientes do Sistema Único de Saúde (SUS) para identificar padrões preditivos de desfechos clínicos em condições crônicas. O problema a ser abordado é a dificuldade em prever e, consequentemente, prevenir complicações graves em pacientes com doenças crônicas, o que é fundamental para melhorar os desfechos clínicos e otimizar o uso dos recursos de saúde. A hipótese central da proposta é que a aplicação de ferramentas avançadas de IA permitirá a identificação precoce de pacientes em risco elevado, possibilitando intervenções personalizadas e mais eficazes. Enquanto a medicina de precisão tradicionalmente usa dados ômicos?como genômica, proteômica e metabolômica?para adaptar tratamentos às características moleculares de cada paciente, esses métodos são frequentemente caros e inviáveis para implementação em larga escala no Sistema Único de Saúde. Por isso, essa proposta se concentra em uma abordagem de "saúde de precisão", que aproveita dados já coletados de forma rotineira, como informações clínicas, laboratoriais e demográficas, que são amplamente disponíveis e economicamente viáveis no contexto do SUS. A análise integrada desses dados, utilizando IA, pode revelar padrões ocultos que são preditivos de complicações graves, como insuficiência renal em pacientes com diabetes ou eventos cardiovasculares em pacientes hipertensos. Isso não só melhora os desfechos clínicos, mas também promove uma utilização mais eficiente dos recursos de saúde, possibilitando que a saúde de precisão seja uma realidade prática e acessível para a população brasileira.

Synaptic plasticity is the capacity of neurons to reshape their interactions with each other to rewireneural circuits through the reinforcement, or conversely, weakening of intercellular connections. Thishighly regulated process is essential for during neurodevelopment and in the execution ofneurocognitive functions. Synaptic plasticity is particularly sensitive to exogenous perturbations,including viral infections, but the interplay between viral neuroinfections and synaptic plasticity isstill poorly characterized. Our consortium aims to explore these concepts through the in-depthcharacterization of the major principles governing synaptic plasticity in health and disease. Inparticular, we will use innovative 3D cell models, including cerebral organoids originating frompatients stem cells, coupled with customized machine learning frameworks and bioinformaticnetwork analyses of massive datasets. These investigations will be performed in the context of viralinfections using five of the most relevant emerging viruses with neurotropic potential (Zika virus,West Nile virus, SARS-CoV-2, La Crosse virus, Influenza virus).

This project aims to unravel how the immune system in the skin responds to mosquito-borne virusessuch as Ross River virus (RRV), Dengue, Zika, and Chikungunyaimmediately after transmission via mosquito bite. Despite the enormous global health burden caused by these arboviruses, our understanding of the earliest stages of infection, particularly how viruses escape local control and spread through the body, remains limited. To address this, the research team will use an innovative intradermal infection model that mimics the natural route of viral entry through the skin. Using advanced technologiessuch as intravital imaging, mass cytometry (CyTOF), and single-cell RNA sequencingthe team will track how immune cells respond, move, and in some cases, inadvertently help the virus spread. A unique Tag-and-Track system using transgenic mice will allow them to follow infected immune cells as they migrate from the skin to other tissues. The ultimate goal is to identify immune cells and molecular signals responsible for viral dissemination and develop strategies to block this process. This includes testing topical and systemic treatments that interfere with immune cell migration. The findings could transform our understanding of arbovirus pathogenesis and offer new targets to prevent viral spread and disease progressionnot only for RRV, but potentially for other arboviruses like Zika and Dengue.

O LEVACC é um projeto encomendado pelo Programa Nacional de Imunização que visa informatizar as Cadernetas de Vacinação de milhões de brasileiros. Para ajudar no projeto, não precisamos de seus dados pessoais, apenas de imagens de sua caderneta de vacinação tiradas do seu próprio celular. Todos que contribuírem para nossa pesquisa estarão ajudando a desenvolver um aplicativo que facilitará o trabalho de milhares de agentes de saúde e ajudará o governo a combater epidemias e salvar mais vidas.

To provide a solution for a rapid response of high laboratory diagnostic demand in virus outbreaks in PINA (RIIP).

Classical Swine Fever (CSF) is a contagious, haemorrhagic and often fatal disease of Suidae, such as pigs and wild boar, caused by the classical swine fever virus (CSFV). CSFV is an enveloped, single stranded RNA virus that belongs to the Flaviviridae family (Moennig, 2000), distantly related for example to Zika and Yellow Fever virus. CSFV can be controlled by vaccination particularly using the C strain vaccine. The vaccine provides a rapid and complete protection of pigs against infection and also prevents viral transmission within 5 days of vaccination. The immunological signalling cascades behind the early protection afforded by C Strain are poorly understood, but precede the adaptive response, where IFN+ CD8+ cells arrive before the detection of a virus neutralising antibody response. Interferon is a key component of how the innate immune system responds to challenge with CSFV. System Immunology approaches have been carried out in humans for example on the highly efficacious Yellow Fever vaccine. Deciphering the immune signalling pathways underpinning the effectiveness of the C strain vaccine can shape and optimise the next generation of marker and subunit vaccines well beyond CSFV as access to material including post-mortem tissues where required is not limited. Previous work has indicated a key role of the interferon system if stimulated prior to challenge. The team at UoS has already carried out studies further to the one mentioned above to characterise the action of CSFV C strain vaccine upon vaccination. In particular we have carried out one study sampling tonsils at various time points in the first 90 hours, comparing C-strain and a virulent challenge virus to baseline. Samples have been stored for subsequent analysis by deep sequencing, which will be carried out in 2019. For early 2020 another such study is planned into the design of which the team at USP will provide input. The project is specifically designed to foster the collaboration between Prof Nakaya's team at USP and Prof Steinbach's team in Surrey through collaborative visits in particular. The aim is to generate data in collaboration from which publications and further grant applications will be generated in the course of the project.

In collaboration with Dr Helder Nakaya (Scientific Platform Pasteur USP, Brazil) an expert insystems vaccinology and single-#8208;cell immunoprofiling25,26, we intend to use Cellular Indexing ofTranscriptomes and Epitopes by Sequencing (CITE-#8208;Seq)29 to single-#8208;cell sequence CTLs using barcodeddextramers harboring the epitopes discovered by immunopeptidomics. This method will allow us tomaximize the use of the small numbers of specific T cells from the humanized mice to retrieve thesequences of epitope-#8208;specific variable regions of T cell receptors (TCRs). TCRs will be expressed onreporter cells which will become fluorescent after TCR activation by the complex peptide-#8208;MHC class Imolecule30. Thus, to validate Pf ATCs instead of focusing on the elimination of infected hepatocytes,which can depend on non-#8208;specific factors, such as secreted cytokines in vitro, or yet on the highamounts of CTLs that will be determined by the immunization method/model in vivo, we propose torely on the specific-#8208;TCR activation of reporter cells by epitopes presented on the surface of Pf infectedhepatocytes.

Data related to human health, from clinical and epidemiological information to medical images and omics data, are being generated and accumulated in an unprecedented amount in history. The analysis and integration of such information is critical to improve our understanding of the pathophysiology of diseases, their transmission, as well as their diagnosis and treatment. This project proposes innovative approaches for: analyzing large epidemiological databases; mapping hotspots of disease transmission; integrating transcriptome data with clinical and immunological data; and using machine learning for interpretation and analysis of microscopic images. State-of-the-art techniques or systems analyses and machine learning will be used and even developed for each approach, taking into account the foundations of integrative biology. We hope that the results of the project can clarify several problems related to human health, from the automatic analysis of microscopic slides to the molecular mechanisms of infectious and inflammatory diseases

A Peste Suína Clássica (PSC) é uma doença contagiosa, hemorrágica e muitas vezes fatal de Suidae, como porcos e javalis, causada pelo vírus da peste suína clássica (CSFV). O CSFV é um vírus de RNA de fita simples, envelopado, que pertence à família Flaviviridae (Moennig, 2000), relacionado, por exemplo, ao vírus da Zika e da Febre Amarela. O CSFV pode ser controlado por vacinação, particularmente utilizando a vacina da cepa C. A vacina fornece uma proteção rápida e completa dos porcos contra a infecção e também previne a transmissão viral dentro de 5 dias da vacinação.As cascatas de sinalização imunológica por trás da proteção precoce proporcionada pela cepa C são mal compreendidas, mas precedem a resposta adaptativa, em que as células CD8+ IFNg+ chegam antes da detecção de uma resposta de anticorpos neutralizadores de vírus. O interferon é um componente chave de como o sistema imune inato responde ao desafio com o CSFV. As abordagens de imunologia do sistema foram realizadas em humanos, por exemplo, na vacina altamente eficaz da Febre Amarela. Decifrar as vias de sinalização imune que sustentam a eficácia da vacina da cepa C pode moldar e otimizar a próxima geração de vacinas marcadoras e de subunidades bem além do CSFV, pois o acesso ao material, incluindo os tecidos post-mortem, quando necessário, não é limitado. Trabalhos anteriores indicaram um papel fundamental do sistema interferon se estimulado antes do desafio. A equipe da UoS já realizou estudos adicionais ao mencionado acima para caracterizar a ação da vacina contra a cepa C do CSFV após a vacinação. Em particular, realizamos um estudo amostrando amígdalas em vários momentos nas primeiras 90 horas, comparando a linhagem C e um vírus de desafio virulento à linha de base. As amostras foram armazenadas para posterior análise por sequenciamento profundo, que será realizado em 2019. Para o início de 2020, outro projeto desse tipo está planejado para o projeto, do qual a equipe da USP fornecerá dados.O projeto é especificamente projetado para promover a colaboração entre a equipe do Prof Nakaya na USP e a equipe do Prof Steinbach em Surrey, através de visitas colaborativas em particular. O objetivo é gerar dados em colaboração a partir dos quais as publicações e outras solicitações de subsídios serão geradas no decorrer do projeto.

The importance of statistics in natural sciences is unquestionable. Statistics is essential to analyze data appropriately and to reach reliable conclusions. However, little is known about formal statistical methods on graphs and their theoretical properties even with an increasing number of reports on the analysis of real world networks (e.g. functional brain networks, protein-protein interaction networks, and social interaction networks). Networks are usually analyzed using computational algorithms based on graph theory, such as calculation of centrality measures (relative importance of vertices and edges) or identification of structural patterns (motifs). The main drawback of this approach is the fact that real world networks present intrinsic fluctuations (random noise) that are not taken into account by these "classical" algorithms. Therefore, methods with statistical perspective may aid and complement these analyses. The main goals of this proposal is the development of both theory and computational statistics methods and apply them to real world data, such as networks from molecular biology, neuroimaging, and cardiac data. The development of this project will be essential to obtain novel insights, solidify the cooperation among PIs, and improve the research quality of all involved groups. In the long term, we will consolidate the field of Network Statistics, form groups of highly qualified researchers, and ultimately build a Center for Network Statistics in Brazil. This center will develop novel theoretical frameworks, methodological tools and also apply the latter to solve health sciences problems.

To apply systems biology methods to integrate nasopharyngeal microbiome, mucosal and blood transcriptome, immunological and clinical data following intranasal live attenuated influenza vaccine in children, and to identify and investigate the putative role of long noncoding RNAs (lncRNAs) in vaccine-induced mucosal immunity.

We will apply cutting-edge systems biology approaches to decipher cattle response to BRD. Through network analyses, our goal is to combine in depth cattle immune, transcriptomic and metabolomics profiling to identify key targets for disease intervention or therapeutics.

GRAND CHALLENGES EXPLORATIONS da Bill Melinda Gates FoundationHelder Nakaya of the University of Sao Paulo in Brazil will identify hotspots of malaria transmission using the GPS data from mobile phones of infected individuals in order to find asymptomatic cases and help elimination efforts. Malaria is a major public health concern in many countries including Brazil. Eliminating the disease is difficult due in part to the existence of asymptomatic individuals who can still spread the disease but are difficult to detect. Relying on a patient remembering where they have been to identify asymptomatic individuals has not been adequate. Instead, they will test their online tool, which can extract the location history of an individual that has been recorded on their mobile phone, using patients with malaria in a reference hospital in Manaus, Brazil. The tool will be used to identify potential hotspots of transmission, which will be verified by taking blood samples from residents to identify those elusive asymptomatic patients. They will also develop an application for health care workers that displays the hotspots on a map.

The VSV-EBOPLUS collaborative research project is aimed to decipher the immune and molecular signatures of adult and pediatric responses elicited by the rVSVrG-ZEBOV-GP vaccine, the only Ebola vaccine with demonstrated 100 protective efficacy in humans.VSV-EBOPLUS will apply advanced cutting-edge technologies and systems vaccinology approaches to characterize the signatures of the responses to rVSVrG-ZEBOV-GP vaccination in clinical studies conducted in three different continents (Europe, Africa, US), in almost 1000 adults, adolescents and children.VSV-EBOPLUS is a public-private consortium of 11 partners from 8 different countries involving experts from academic and research institutions, clinical sites (Switzerland, Gabon, USA) and the rVSVrG-ZEBOV-GP vaccine manufacturer. The project, of the duration of 5 years, has a total budget of more than 15 million, and it is funded by the Innovative Medicines Initiative 2 (IMI 2) Joint Undertaking.

Systems biology of typhoid fever: Unravelling regulation of human host-responses to infection with Salmonella Typhi and live oral vaccination

It is estimated that thousands of long non-coding RNAs (lncRNAs) are transcribed in the genome of several organisms. Dr. Kouzarides? group at Cambridge University re-analyzed a vast amount of RNA-sequencing data, and identified ~600 lncRNAs that were ?positionally conserved? (pcRNAs) in human and mouse genomes. Among the genes associated with these pcRNAs, a striking enrichment was observed for loci related to embryonic and tissue development. They also demonstrated that pcRNA expression is highly tissue-specific and directly correlates with the associated coding genes, supporting the idea that pcRNAs are context-specific regulators of developmental genes. Our group at University of São Paulo is utilizing publicly available high-throughput data to investigate the expression of lncRNAs under hundreds of different perturbations and conditions, and studying the implication of lncRNAs in the regulation of candidate target genes. We compared the genomic regions of these ~600 pcRNAs with the genomic regions of probes from different microarray platforms and found that most of these pcRNAs are represented by one or more probes. Here we propose to analyse the expression patterns of these pcRNAs, and how their expression correlates with the expression of coding genes, in a large panel of human cancer cell lines, primary tumours and disease conditions. The functions of a number of selected pcRNAs will be validated by Dr. Kouzarides' group. By assessing the transcription of pcRNAs and their associated coding genes in thousands of microarray studies, we expect to identify the biological conditions that affect the most the expression of pcRNAs and to reveal interesting mechanisms of gene regulation.

As redes gênicas que coordenam os diferentes processos inflamatórios são extremamente complexas e podem envolver centenas de genes. Entender precisamente quais componentes e as interações entre eles relevantes em uma determinada condição inflamatória pode fornecer importantes candidatos a alvos de fármacos, mais específicos e com menos efeitos adversos.

The ability to predict vaccine immunity offers a solution to a major challenge in vaccinology: to prospectively determine vaccine efficacy. This ability is of considerable public health importance in identifying ?non-responders? in special populations in which a vaccine may induce suboptimal immunity. In addition, it would be great value in clinical trials of novel vaccines, to provide a rapid means to assess vaccine efficacy, without the need to identify the incidence of the target disease in vaccinated versus unvaccinated populations. In this context, this ?systems vaccinology? approach is beginning to be used to define signatures of vaccine efficacy in clinical trials. Importantly, this approach is yielding new insights about the fundamental mechanisms of immunity

Chikungunya virus (CHIKV) and Ross River virus (RRV) cause (occasionally very large) outbreaks of polyarthritis/polyarthralgia, which is often debilitating, lasts from weeks to months (occasionally longer), and is generally poorly managed with current treatments. 
Aim: To use RNA-Seq analysis to characterise the inflammatory signatures and viral genomes associated with chronic arthritis.

Estima-se que milhares de longos RNAs não-codificadores (lncRNAs) sejam gerados à partir da transcrição do genoma de diversos organismos. No entanto, apenas uma fração muito pequena destes foi caracterizada funcionalmente. Um dos maiores motivos para isso está em nossa falta de conhecimento sobre os tecidos e condições biológicas nos quais esses lncRNAs são transcritos e como eles interagem com o DNA ou outros RNAs. A maioria dos estudos que utilizam técnicas de larga-escala como microarrays e sequenciamento de nova geração (RNA-seq) tem como objetivo principal monitorar a expressão dos genes codificadores de proteína. Porém, muitos destes dados, não explorados nas publicações originais, são provenientes de lncRNAs. Neste projeto, nós propomos utilizar os milhares de estudos de microarrays disponíveis em um banco de dados público para estudar a biologia de sistema dos lncRNAs frente a diferentes perturbações e suas possíveis implicações na regulação de genes alvos. Uma re-anotação que fizemos da plataforma da Affymetrix mais usada, na qual mais de 2.300 estudos foram publicados, revelou a existência de 10.248 sondas que medem a expressão de possíveis lncRNAs. Estudar o perfil de expressão de lncRNAs e como estes se correlacionam com os perfis de genes codificadores de proteína em tantos tecidos e condições irá revelar mecanismos de regulação interessantes. Estas análises irão envolver a identificação de módulos de co-expressão, a predição dos fatores de transcrição envolvidos e a associação de lncRNAs com doenças e infecções. Propomos também validar o papel regulatório de lncRNAs em alguns desses achados.

Inflammatory diseases are a complex and heterogeneous group of diseases that affect more than 10 of the word population. The current options for the treatment of these diseases are still limited and in some cases, inefficient due to limited understanding of the mechanisms underlying these diseases. The development of translational research by a center that can generate scientific knowledge and also identify new therapeutic targets of inflammatory diseases is imperative. The Center for research in inflammatory diseases (CPDI) will be created with this goal. The general objective of the CPDI will be to perform integrative and translational research to identify, validate and target known and novel biological pathways involved with the induction and resolution of inflammation. As a result, we expect the development of innovative therapeutic strategies and drugs that effectively target inflammatory diseases. The project will involve high-throughput genetic screenings, in vivo and in vitro models of diseases, modeling and chemical synthesis, as well as the discovery of new natural molecules from plants and saliva from arthropods. After selecting the potential drugs and bio-drugs, CPDI will protect the intellectual property and, after partnerships with private companies, coordinate pre-clinical toxicological studies and early clinical trials. The CPDI will also dedicate intense efforts to disseminate knowledge to the general public, in order to fulfill the societal objective of spreading education and generating an enthusiasm for science.