Utilizando a metodologia PDCA para a melhoria do processo da construção de uma Ponte de Espaguete / Using PDCA methodology to improve the process of building a Spaghetti Bridge

Este trabalho tem o objetivo de mostrar resultados experimentais e a análise dos resultados obtidos no ensaio de uma ponte de espaguete, utilizando o método PDCA como instrumento de melhoria na elaboração e execução do projeto. O projeto ponte de espaguete é realizado no âmbito da disciplina Resistência dos Materiais do Curso de Engenharia Civil da Universidade de Vassouras.  Considerando a metodologia PDCA, foram construídas diversas pontes de espaguete. Durante o processo de construção das pontes, foram identificados diversos problemas tanto nos materiais como no método de execução. Tais problemas juntamente com os ensaios obtidos com os diversos ensaios, geraram feedbacks que foram utilizados para aperfeiçoar o processo construtivo, eliminando possíveis erros até que chegar a um o resultado ótimo. Assim, como resultado do projeto, foi constatado a melhoria ao longo de todo processo, com aumento na capacidade de carga da ponte à medida que elas eram construídas considerando as experiências e problemas identificados na ponte construída na etapa anterior. A ferramenta PDCA foi importante para direcionar na melhoria da elaboração e execução de projetos, visando a diminuição das perdas e buscando uma maior precisão no resultado da carga de ruptura. Do ponto de vista educação, pode-se verificar que projetos como este, os estudantes podem aliar conceitos teóricos com práticos, são interessantes para a construção do conhecimento e desenvolvimento das competências técnicas de engenharia, bem como das competências comportamentais

Fungal and fungal-like diversity in marine sediments from the maritime Antarctic assessed using DNA metabarcoding

We assessed the fungal and fungal-like sequence diversity present in marine sediments obtained in the vicinity of the South Shetland Islands (Southern Ocean) using DNA metabarcoding through high-throughput sequencing (HTS). A total of 193,436 DNA reads were detected in sediment obtained from three locations: Walker Bay (Livingston Island) at 52 m depth (48,112 reads), Whalers Bay (Deception Island) at 151 m (104,704) and English Strait at 404 m (40,620). The DNA sequence reads were assigned to 133 distinct fungal amplicon sequence variants (ASVs) representing the phyla Ascomycota, Basidiomycota, Mortierellomycota, Chytridiomycota, Glomeromycota, Monoblepharomycota, Mucoromycota and Rozellomycota and the fungal-like Straminopila. Thelebolus balaustiformis, Pseudogymnoascus sp., Fungi sp. 1, Ciliophora sp., Agaricomycetes sp. and Chaetoceros sp. were the dominant assigned taxa. Thirty-eight fungal ASVs could only be assigned to higher taxonomic levels, and may represent taxa not currently included in the available databases or represent new taxa and/or new records for Antarctica. The total fungal community displayed high indices of diversity, richness and moderate to low dominance. However, diversity and taxa distribution varied across the three sampling sites. In Walker Bay, unidentified fungi were dominant in the sequence assemblage. Whalers Bay sediment was dominated by Antarctic endemic and cold-adapted taxa. Sediment from English Strait was dominated by Ciliophora sp. and Chaetoceros sp. These fungal assemblages were dominated by saprotrophic, plant and animal pathogenic and symbiotic taxa. The detection of an apparently rich and diverse fungal community in these marine sediments reinforces the need for further studies to characterize their richness, functional ecology and potential biotechnological applications

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

The FlbA-regulated predicted transcription factor Fum21 of <i>Aspergillus niger</i> is involved in fumonisin production

Aspergillus niger secretes proteins throughout the colony except for the zone that forms asexual spores called conidia. Inactivation of flbA that encodes a regulator of G-protein signaling results in colonies that are unable to reproduce asexually and that secrete proteins throughout the mycelium. In addition, the ΔflbA strain shows cell lysis and has thinner cell walls. Expression analysis showed that 38 predicted transcription factor genes are differentially expressed in strain ΔflbA. Here, the most down-regulated predicted transcription factor gene, called fum21, was inactivated. Growth, conidiation, and protein secretion were not affected in strain Δfum21. Whole genome expression analysis revealed that 63 and 11 genes were down- and up-regulated in Δfum21, respectively, when compared to the wild-type strain. Notably, 24 genes predicted to be involved in secondary metabolism were down-regulated in Δfum21, including 10 out of 12 genes of the fumonisin cluster. This was accompanied by absence of fumonisin production in the deletion strain and a 25% reduction in production of pyranonigrin A. Together, these results link FlbA-mediated sporulation-inhibited secretion with mycotoxin production