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We are increasingly making use of software in such a way that we should review education in mathematics. The concepts of level curves and gradient field empowered by software images help the understanding of strategies and resolution of optimization problems by the mathematics user in the softage. More than obtaining solutions from straight commands and with the help of the geometric approach the mathematics user can realize the situations when these commands help or how to deal with a problem whenever they are not so helpful.

Extensive in vitro cancer drug screening datasets have enabled scientists to identify biomarkers and develop machine learning models for predicting drug sensitivity. While most advancements have focused on omics profiles, cancer drug sensitivity scores precalculated by the original sources are often used as-is, without consideration for variabilities between studies. It is well-known that significant inconsistencies exist between the drug sensitivity scores across datasets due to differences in experimental setups and preprocessing methods used to obtain the sensitivity scores. As a result, many studies opt to focus only on a single dataset, leading to underutilization of available data and a limited interpretation of cancer pharmacogenomics analysis. To overcome these caveats, we have developed CREAMMIST (https://creammist.mtms.dev), an integrative database that enables users to obtain an integrative dose-response curve, to capture uncertainty (or high certainty when multiple datasets well align) across five widely used cancer cell-line drug–response datasets. We utilized the Bayesian framework to systematically integrate all available dose-response values across datasets (>14 millions dose-response data points). CREAMMIST provides easy-to-use statistics derived from the integrative dose-response curves for various downstream analyses such as identifying biomarkers, selecting drug concentrations for experiments, and training robust machine learning models.

Motivation Large-scale cancer omics studies have highlighted the diversity of patient molecular profiles and the importance of leveraging this information to deliver the right drug to the right patient at the right time. Key challenges in learning predictive models for this include the high-dimensionality of omics data and heterogeneity in biological and clinical factors affecting patient response. The use of multi-task learning techniques has been widely explored to address dataset limitations for in vitro drug response models, while domain adaptation (DA) has been employed to extend them to predict in vivo response. In both of these transfer learning settings, noisy data for some tasks (or domains) can substantially reduce the performance for others compared to single-task (domain) learners, i.e. lead to negative transfer (NT). Results We describe a novel multi-task unsupervised DA method (TUGDA) that addresses these limitations in a unified framework by quantifying uncertainty in predictors and weighting their influence on shared feature representations. TUGDA’s ability to rely more on predictors with low-uncertainty allowed it to notably reduce cases of NT for in vitro models (94% overall) compared to state-of-the-art methods. For DA to in vivo settings, TUGDA improved over previous methods for patient-derived xenografts (9 out of 14 drugs) as well as patient datasets (significant associations in 9 out of 22 drugs). TUGDA’s ability to avoid NT thus provides a key capability as we try to integrate diverse drug-response datasets to build consistent predictive models with in vivo utility. Availabilityand implementation https://github.com/CSB5/TUGDA. Supplementary information Supplementary data are available at Bioinformatics online.

Native Hawaiians and other Pacific Islanders (NHPIs) across the country have experienced significant disparities because of the COVID-19 pandemic. The Pacific Alliance Against COVID-19 used a community-based participatory approach involving academic and community partners to expand sustainable COVID-19 testing capacity and mitigate the severe consequences among NHPI communities in Hawaii. We describe the approach of this one-year study, some of the results, and how the data are being used to inform next steps for the communities. Clinical Trials.gov identifier: NCT04766333. (Am J Public Health. 2022;112(S9):S896–S899. https://doi.org/10.2105/AJPH.2022.306973 )

Software can be employed to solve math problems and we have to cooperate with them not passively but in an active way. In this article, we present situations in which the software user should be careful in order to avoid the use of the straight commands of the software that may put a matrix in its echelon form or give straight its rank. Wrong results appear in Wolfram’s Mathematica software if the matrix has algebraic entries. Using the Gaussian elimination step by step method with the help of elementary matrices is a good strategy for the software user in such cases.

At this moment when we can employ software, mathematics education has to be reviewed. In this article, we point out that ODEs should be taught from a geometric and qualitative point of view together with an introduction to PDEs and vector fields. This would increase the skills of the future mathematics user, not only to obtain explicit solutions from a straight command like DSolve, but also in the situations where this command does not help. The geometric interpretation and the concept of direction fields with images generated by software will give us a good understanding of possible system evolutions.

This study investigated the effects of melatonin supplementation on the daily mRNA expression of Bmp-15, Gdf-9, FSH (Fshr) and LH (Lhr) receptor genes and the effect of gonadotropin supplementation on protein expression of melatonin-synthetizing enzymes (ASMT and AANAT) during in vitro maturation (IMV) of rat follicle-enclosed oocytes. We also studied the effects of pinealectomy on the mRNA expression of Bmp-15, Gdf-9, Fshr and Lhr genes in immature oocytes and cumulus cells and on the protein expression and immunolocalization of AANAT and ASMT in immature ovaries. Ovaries were collected from sham-pinealectomized (INTACT) and pinealectomized (PINX) females during the light and dark phases of the 12h:12h light-dark cycle. Melatonin increased the Bmp-15 and Gdf-9 mRNA expression in follicle-enclosed oocytes during dark phase and Lhr mRNA expression during the light phase. The daily mRNA expression of Lhr was negatively correlated with the daily mRNA expression of Bmp-15 and Gdf-9 in follicle-enclosed oocytes supplemented with melatonin. There were no phase differences in oocytes mRNA expression of Bmp-15 and Gdf-9 from PINX females. Pinealectomy did not altered the mRNA expression of Lhr gene in cumulus cells. There were no phase differences in ASMT and AANAT expression in ovaries from INTACT and PINX females and their immunolocalization was seen in most of ovarian cells. AANAT expression in follicle-enclosed oocytes supplemented with LH from INTACT and PINX females was greater during the dark phase. The results suggest that melatonin regulates the daily Bmp-15, Gdf-9 and Lhr mRNA expression during the rat follicle development. There is also an indicative that melatonin plays an important role in the relationship between the daily expression of Lhr and the daily expression of Bmp-15 and Gdf-9 in follicle-enclosed oocytes during oocyte maturation process.

A local renin-angiotensin system (RAS) has been postulated in the pineal gland. In addition to angiotensin II (Ang II), other active metabolites have been described. In this study, we aimed to investigate a role for Ang IV in melatonin synthesis and the presence of its proposed (IRAP)/AT4 receptor (insulin-regulated aminopeptidase) in the pineal gland. The effect of Ang IV on melatonin synthesis was investigated in vitro using isolated pinealocytes. IRAP protein expression and activity were evaluated by Western blot and fluorimetry using Leu-4Me-β-naphthylamide as a substrate. Melatonin was analyzed by HPLC, calcium content by confocal microscopy and cAMP by immunoassay. Ang IV significantly augmented the NE-induced melatonin synthesis to a similar degree as that achieved by Ang II. This Ang IV effect in pinealocytes appears to be mediated by an increase in the intracellular calcium content but not by cAMP. The (IRAP)/AT4 expression and activity were identified in the pineal gland, which were significantly higher in membrane fractions than in soluble fractions. Ang IV significantly reduced IRAP activity in the pineal membrane fractions. The main findings of the present study are as follows: (1) Ang IV potentiates NE-stimulated melatonin production in pinealocytes, (2) the (IRAP)/AT4 receptor is present in the rat pineal gland, and (3) Ang IV inhibits IRAP activity and increases pinealocytes [Ca2+]i. We conclude that Ang IV is an important component of RAS and modulates melatonin synthesis in the rat pineal gland.

Additional file 1: Fig S1. Single-cell RNA-seq statistics for 12 patient-derived cell lines. Fig S2. Impact of dose-response curves from in vitro cell viability assays on IC50 estimates. Fig S3. Training and validation loss. Fig S4. CaDRReS-Sc accurately estimates aggregate IC50 values in the presence of transcriptomic heterogeneity. Fig S5. Survival analysis for clusters based on bulk transcriptomic profiles. Fig S6. Boxplots comparing ITTH scores across clinical response categories for various cancer drugs. Fig S7. Additional performance evaluation per drug. Fig S8. Pairwise comparison of CaDRReS-SC���s performance on unseen cell types. Fig S9. Transcriptomic patterns of cells from HN120 and HN137. Fig S10. Detailed comparison between predicted and observed cell death percentages. Fig S11. Pharmacogenomic space of GDSC cell lines and HNSC patient-derived cell clusters. Fig S12. Comparison of observed and predicted drug response across 5 pooled PDCs and 8 drugs. Fig S13. Predictive performance of ElasticNet and RWEN based on cell clusters. Fig S14. Comparison of drug response between tumor types and pathway activity groups.

Over the last decade, large-scale cancer omics studies have highlighted the diversity of patient molecular profiles and the importance of leveraging this information to deliver the right drug to the right patient at the right time. Key challenges in learning predictive models for this include the high-dimensionality of omics data, limitations in the number of data points available, and heterogeneity in biological and clinical factors affecting patient response. The use of multi-task learning (MTL) techniques has been widely explored to address dataset limitations forin vitrodrug response models, while domain adaptation (DA) has been employed to extend them to predict in vivo response. In both of these transfer learning settings, noisy data for some tasks (or domains) can substantially reduce the performance for others compared to single-task (domain) learners, i.e. lead to negative transfer (NT). We describe a novel multi-task unsupervised domain adaptation method (TUGDA) that addresses these limitations in a unified framework by quantifying uncertainty in predictors and weighting their influence on shared domain/task feature representations. TUGDA’s ability to rely more on predictors with low-uncertainty allowed it to notably reduce cases of negative transfer forin vitromodels (63% for drugs with limited data and 94% overall) compared to state-of-the-art methods. For domain adaptation toin vivosettings, TUGDA improved performance for 6 out of 12 drugs in patient-derived xenografts, and 7 out of 22 drugs in TCGA patient datasets, despite being trained in an unsupervised fashion. TUGDA’s ability to avoid negative transfer thus provides a key capability as we try to integrate diverse drug-response datasets to build consistent predictive models within vivoutility.Availabilityhttps://github.com/CSB5/TUGDA

Background Accumulating evidence suggests that plasminogen activator inhibitor-1 (PAI-1) plays an important role in bladder tumorigenesis by regulating cell cycle. However, it remains unclear whether and how inhibition of PAI-1 suppresses bladder tumorigenesis. Methods To elucidate the therapeutic effect of PAI-1 inhibition, we tested its tumorigenicity in PAI-1 knockout (KO) mice exposed to a known bladder carcinogen. Results PAI-1 deficiency did not inhibit carcinogen-induced bladder cancer in mice although carcinogen-exposed wild type mice significantly increased PAI-1 levels in bladder tissue, plasma and urine. We found that PAI-1 KO mice exposed to carcinogen tended to upregulate protein C inhibitor (PAI-3), urokinase-type plasminogen activator (uPA) and tissue-type PA (tPA), and significantly increased PAI-2, suggesting a potential compensatory function of these molecules when PAI-1 is abrogated. Subsequent studies employing gene expression microarray using mouse bladder tissues followed by post hoc bioinformatics analysis and validation experiments by qPCR and IHC demonstrated that SERPING1 is further downregulated in PAI-1 KO mice exposed to BBN, suggesting that SERPING1 as a potential missing factor that regulate PAI-2 overexpression (compensation pathway). Conclusions These results indicate that serpin compensation pathway, specifically PAI-2 overexpression in this model, supports bladder cancer development when oncoprotein PAI-1 is deleted. Further investigations into PAI-1 are necessary in order to identify true potential targets for bladder cancer therapy.

People with obesity are often dyslipidemic and prescribed statins to prevent cardiovascular events. A common side effect of statin use is myopathy. This could potentially be caused by the reduction of selenoproteins that curb oxidative stress, in turn, affecting creatine metabolism. We determined if statins regulate hepatic and muscular selenoprotein expression, oxidative stress and creatine metabolism. Mice lacking selenocysteine lyase (Scly KO), a selenium-provider enzyme for selenoprotein synthesis, were fed a high-fat, Se-supplemented diet and treated with simvastatin. Statin improved creatine metabolism in females and oxidative responses in both sexes. Male Scly KO mice were heavier than females after statin treatment. Hepatic selenoproteins were unaffected by statin and genotype in females. Statin upregulated muscular Gpx1 in females but not males, while Scly loss downregulated muscular Gpx1 in males and Selenon in females. Osgin1 was reduced in statin-treated Scly KO males after AmpliSeq analysis. These results refine our understanding of the sex-dependent role of selenium in statin responses.

Aberrant sphingolipid metabolism has been reported to promote breast cancer progression. Sphingosine kinase 1 (SphK1) is a key metabolic enzyme for the formation of pro-survival S1P from pro-apoptotic ceramide. The role of SphK1 in breast cancer has been well studied in estrogen receptor (ER)-positive breast cancer; however, its role in human epidermal growth factor 2 (HER2)-positive breast cancer remains unclear. Here, we show that genetic deletion of SphK1 significantly reduced mammary tumor development with reduced tumor incidence and multiplicity in the MMTV-neu transgenic mouse model. Gene expression analysis revealed significant reduction of claudin-2 (CLDN2) expression in tumors from SphK1 deficient mice, suggesting that CLDN2 may mediate SphK1's function. It is remarkable that SphK1 deficiency in HER2-positive breast cancer model inhibited tumor formation by the different mechanism from ER-positive breast cancer. In vitro experiments demonstrated that overexpression of SphK1 in ER-/PR-/HER2+ human breast cancer cells enhanced cell proliferation, colony formation, migration and invasion. Furthermore, immunostaining of SphK1 and CLDN2 in HER2-positive human breast tumors revealed a correlation in high-grade disease. Taken together, these findings suggest that SphK1 may play a pivotal role in HER2-positive breast carcinogenesis. Targeting SphK1 may represent a novel approach for HER2-positive breast cancer chemoprevention and/or treatment.

Anhydroecgonine methyl ester (AEME), also called methylecgonidine, is a pyrolysis product of crack cocaine that is neurotoxic and potentiates cocaine-induced sensitization. The sensitization induced by drugs of abuse can be influenced by melatonin, a neuroprotective pineal hormone. In the same way, drugs of abuse like alcohol and methamphetamine can modify melatonin synthesis. The aim of the present work was to investigate the AEME effects on melatonin synthesis in the rat pineal gland. Neurotransmitter systems involved in its effects, antioxidant enzyme activities and the melatonin protective role in AEME-induced toxicity were also evaluated. The animals were injected with AEME i.p. (1.12 mg per kg of body weight per day) or vehicle for 10 consecutive days and the nocturnal pineal melatonin synthesis profile and SOD, GPx and GR activities in the cerebral cortex and hippocampus were assessed. Cultured pineal glands were incubated with AEME for 30 min or 48 h before norepinephrine stimulation and melatonin synthesis, arylalkylamine N-acetyltransferase activity, cAMP and [Ca2+]i were determined. The involvement of cholinergic and glutamatergic systems was analyzed using different antagonists. The protective role of melatonin in AEME toxicity on hippocampal neurons was evaluated by a viability assay. AEME impaired melatonin synthesis both in vivo and in vitro and this effect seems to be mediated by muscarinic receptors and [Ca2+]i elevation. AEME reduced neuronal viability and melatonin was able to protected hippocampal neurons against AEME toxicity. The melatonin synthesis impairment observed could lead to the worsening of the direct AEME neurotoxicity and to the exacerbation of the crack cocaine addiction and sensitization.

Submitted by Aline Batista (alinehb.ufpel@gmail.com) on 2020-08-25T00:44:29Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Rafael_Peres_Machado.pdf: 1827028 bytes, checksum: c71be13ce287642560bfb09d61279565 (MD5) Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2020-08-25T01:29:24Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Rafael_Peres_Machado.pdf: 1827028 bytes, checksum: c71be13ce287642560bfb09d61279565 (MD5) Made available in DSpace on 2020-08-25T01:29:24Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_Rafael_Peres_Machado.pdf: 1827028 bytes, checksum: c71be13ce287642560bfb09d61279565 (MD5) Previous issue date: 2019-10-30 Sem bolsa Nas últimas décadas, a crise fiscal tem se agravado em vários Estados brasileiros. Muitos deles apresentam dívidas de bilhões de reais, tornando premente que este problema fiscal seja enfrentado e combatido em várias frentes. Nesse contexto, é importante que se entenda que as variáveis macroeconômicas interagem com as variáveis relativas à execução orçamentária em relações de causa e efeito possibilitando o desenvolvimento econômico ou até mesmo degradação das condições de vida da população. Nesse sentido, este trabalho visa contribuir no enfrentamento dessa crise e na obtenção do equilíbrio fiscal com esclarecimentos de como se dão essas relações e propondo um modelo econométrico que possibilite a realização de previsões das Receitas Correntes para os Estados analisados. Estabeleceu-se como objetivo geral desta pesquisa analisar as causalidades existentes entre as variáveis macroeconômicas PIB, inflação e desemprego e as variáveis de execução orçamentária dos Estados brasileiros. Para isso, foram identificados para o período de 2008-2 a 2015-2 os valores referentes às receitas e às despesas de quatro Estados brasileiros (Minas Gerais, Pernambuco, Rio Grande do Sul e São Paulo), bem como os valores referentes às variáveis PIB, inflação e desemprego relativas aos territórios desses entes políticos. Utilizou-se o teste de causalidade de Granger a fim de descobrir as relações de causalidade existentes. Entre os principais resultados, descobriu-se que, segundo esse teste, a Variação Percentual do PIB tem uma relação unidirecional de causalidade com as variáveis utilizadas para representar a execução orçamentária. Identificou-se que ela causa as Receitas Total e Corrente, a Despesa Total e os Quocientes de Execução Orçamentária e de Execução Orçamentária Corrente. Constatou-se que a Variação Percentual do PIB apresenta uma relação positiva com as Receitas Total e Corrente e com a Despesa Total, isto é, havendo elevação ou redução daquela estas também variam na mesma direção. Quanto à inflação, representada pelo Índice de Preços ao Consumidor Ampliado (IPCA), descobriu-se que, de acordo com o teste de causalidade de Granger, ela causa a Receita de Capital e o Quociente de Execução Orçamentária, também em uma relação positiva e unidirecional. Analisou-se, ainda, as causalidades existentes entre as receitas e as despesas tendo ficado evidente a existência de uma relação de causalidade bidirecional em quase todas as relações. Por fim, desenvolveu-se o modelo econométrico utilizando o modelo de vetores autoregressivos (VAR). Para a escolha do modelo foram utilizadas somente as variáveis que no teste de causalidade de Granger se demonstraram como causadoras da Receita Corrente. A escolha do modelo foi realizada utilizando-se critérios de escolha de modelos como o R2, R2 ajustado, critérios de informação de Akaike, de Schwarz e Hannan-Quinn. Todos os testes foram realizados utilizando-se os dados em painel. Os testes para a construção do modelo foram realizados no software Gretl. Os demais testes foram realizados com o software Eviews. In recent decades, the fiscal crisis has worsened in several Brazilian states. Many of them have a debt of billions of reais, making it urgent that this fiscal problem is tackled on many fronts. In this context, it is important to understand that the macroeconomic variables interact with the variables related to budget execution in cause and effect relations, enabling the economic development or even degradation of the population's living conditions. In this sense, this paper aims to contribute to the confrontation of this crisis and to obtain the fiscal balance by clarifying how these relations occur and proposing an econometric model that makes it possible to make current revenue forecasts for the states analyzed. The general objective of this research was to analyze the causalities between the macroeconomic variables GDP, inflation and unemployment and the budget execution variables of the Brazilian states. For this, for the period 2008-2 to 2015-2 were identified the amounts referring to the revenues and expenses of four Brazilian states (Minas Gerais, Pernambuco, Rio Grande do Sul and São Paulo), as well axs the values referring to the variables GDP, inflation and unemployment relative to the territories of these political entities. Granger's causality test was used to discover existing causal relationships. Among the main results, it was found that, according to this test, the Percentage Change of GDP has a unidirectional causal relationship with the variables used to represent budget execution. It has been found to cause Total and Current Revenue, Total Expense, and Budget Execution and Current Budget Execution Quotients. It was found that the Percentage Change of GDP has a positive relationship with Total and Current Revenue and Total Expenditure, that is, whether there is an increase or reduction of that also vary in the same direction. Regarding inflation, represented by the Extended Consumer Price Index (IPCA), it was found that, according to Granger's causality test, it causes the Capital Revenue and the Budget Execution Quotient, also in a positive relationship. one way. The causalities between income and expenditure were also analyzed and a two-way causal relationship was evident in almost all relationships. Finally, the econometric model was developed using the vector autoregressive model (VAR). For the choice of the model, only the variables that in the Granger causality test were shown to cause current revenue were used. The choice of model was made using model selection criteria such as R2, adjusted R2, Akaike, Schwarz and Hannan-Quinn information criteria. All tests were performed using panel data. Tests for the construction of the model were performed using Gretl software. The other tests were performed with Eviews software.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior In the last decades, collaboration in architecture design has been object of study due to being part of the designers’ routine. These investigations have intensified nowadays, with the advent of technological tools that enable high-speed data transmission and distance communication. In parallel, there is a consolidated theoretical consensus that points to the fact that conflicts are inevitably inserted within the context of human relations. Therefore, it becomes evident that there is a need to discuss strategies for a better understanding of collaboration and conflict management in architecture design teamwork, which would allow us to identify means that would facilitate collective performance in design. On the other hand, the domain of design cognition has revealed, especially since the 1990s, that the role of cognitive actions performed during design contributed to the understanding of processes related to the elaboration of ideas and acquisition of knowledge. Furthermore, this thesis questions the way in which designers interact socio-cognitively, from hypothesis on the impact caused by recognition of problem, individual or collective, in design teams. Through methodological procedures made up mainly of protocol analysis, it was possible to reflect on interactions between individuals, ways of dealing with conflicts and ideas conceived in the team’s design process. For this purpose, there were carried out observational studies with eighteen students of the last year of bachelor’s course in Architecture and Urban Design, forming six teams composed of three members each. These teams designed architecture designs according to pre-established constraints. The teams were arranged in two scenarios: first, there was an individual stage and then the participants were rearranged as a team; secondly, students designed only as a team. The design processes were monitored in laboratory through audio and video recordings and the results obtained reveal evidence of five interfering factors in the team design process: i. design problem; ii. social-cognitive interaction; iii. procedure adopted; iv. conflict management; v. ideas and thoughts. Based on this scientific investigation, the research contributes to contemporary debate about the teaching and practice of design teams on the Architecture field. Nas últimas décadas, a colaboração em projeto de arquitetura tem sido objeto de estudo por fazer parte da rotina dos projetistas. Esse estudo se intensificou na atualidade, com o advento de ferramentas tecnológicas, que possibilitam transmissão de dados em alta velocidade e comunicação à distância. Em paralelo, há um corpo teórico consolidado que aponta para o fato de conflitos estarem inevitavelmente inseridos dentro do contexto das relações humanas. Diante disso, coloca-se em evidência a necessidade de discutir um melhor entendimento sobre colaboração e gestão de conflitos no projeto de Arquitetura em equipe, o que consequentemente permitiria identificar meios que facilitariam a atuação projetual coletiva. Por outro lado, o domínio da cognição em projeto tem revelado, sobretudo a partir da década de 1990, o papel de ações cognitivas realizadas durante o ato de projetar e, como consequência, contribuído para a compreensão de processos relativos à elaboração de ideias e aquisição de conhecimentos. Com esses preceitos, coloca-se em discussão a maneira como projetistas interagem sóciocognitivamente, a partir da hipótese sobre o impacto causado pelo reconhecimento do problema, individual ou coletivo, em equipes de projeto. Por meio de procedimentos metodológicos constituídos, sobretudo, por protocolos de análise, foi possível refletir sobre interações entre indivíduos, modos de lidar com conflitos e ideias concebidas no processo de projetar em equipe. Para tanto, foram realizados estudos observacionais com dezoito estudantes do último ano de graduação em Arquitetura e Urbanismo, configurando seis equipes compostas por três integrantes. Essas equipes conceberam projetos de Arquitetura de acordo com condicionantes estabelecidas. As equipes foram dispostas em dois cenários: no primeiro, houve uma etapa individual e depois os participantes foram reunidos em equipe; no segundo, os estudantes projetaram apenas em equipe. Os processos de projeto foram monitorados em laboratório por meio de registros em áudio e vídeo. Resultados obtidos revelam evidências de cinco fatores interferentes no processo de projetar em equipe: i. problema de projeto; ii. interação sóciocognitiva; iii. procedimento adotado; iv. gerenciamento de conflitos; v. ideias e pensamentos. Baseado nessa investigação científica, a presente pesquisa contribui para o debate contemporâneo sobre ensino e prática projetual em equipe na área de Arquitetura.