Quality of black pepper produced in northeastern Pará.

A pimenta-do-reino (Piper nigrum L.) é a especiaria mais utilizada no mundo. No Brasil, essa cultura tem grande importância econômica, em especial às regiões Norte e Sudeste. Entretanto, a variabilidade na qualidade entre as cultivares é alta. O objetivo deste trabalho foi caracterizar a pimenta preta do nordeste do Pará disponibilizada no mercado, obtendo-se um panorama quanto aos parâmetros de qualidade. Foram avaliadas 23 amostras de pimenta preta de cultivares/clones quanto às impurezas e matérias estranhas, grãos chochos, densidade, umidade e extrato etéreo, conforme estabelecido pela a legislação nacional. Também, foram determinados os teores de cinzas totais, proteínas, fibra bruta e piperina. Dentre as amostras, uma estava fora do padrão para densidade. Os teores de umidade encontravam-se abaixo do limite máximo exigido pela legislação, demonstrando que a secagem e o armazenamento dos grãos foram adequados. Em relação ao extrato etéreo, 52% das amostras não atenderam aos padrões de comercialização. Quanto à piperina, os clones Equador e Panny destacaram-se com teores superiores a 5%. Verificou-se que a composição nutricional da pimenta preta sofre influência do nível tecnológico do sistema de produção. Portanto, a pimenta preta produzida no nordeste do Pará tem qualidade variável

Incidência da podridão radicular da mandioca nos municípios de Bragança, Castanhal e Igarapé-Açu, Pará.

O presente estudo teve como objetivo avaliar a incidência da podridão radicular da mandioca em três municípios no estado do Pará

Association of SNPs in EGR3 and ARC with schizophrenia supports a biological pathway for schizophrenia risk

We have previously hypothesized a biological pathway of activity-dependent synaptic plasticity proteins that addresses the dual genetic and environmental contributions to schizophrenia. Accordingly, variations in the immediate early gene EGR3, and its target ARC, should influence schizophrenia susceptibility. We used a pooled Next-Generation Sequencing approach to identify variants across these genes in U.S. populations of European (EU) and African (AA) descent. Three EGR3 and one ARC SNP were selected and genotyped for validation, and three SNPs were tested for association in a replication cohort. In the EU group of 386 schizophrenia cases and 150 controls EGR3 SNP rs1877670 and ARC SNP rs35900184 showed significant associations (p = 0.0078 and p = 0.0275, respectively). In the AA group of 185 cases and 50 controls, only the ARC SNP revealed significant association (p = 0.0448). The ARC SNP did not show association in the Han Chinese (CH) population. However, combining the EU, AA, and CH groups revealed a highly significant association of ARC SNP rs35900184 (p = 2.353 x 10(-7); OR [95% CI] = 1.54 [1.310-1.820]). These findings support previously reported associations between EGR3 and schizophrenia. Moreover, this is the first report associating an ARC SNP with schizophrenia and supports recent large-scale GWAS findings implicating the ARC complex in schizophrenia risk. These results support the need for further investigation of the proposed pathway of environmentally responsive, synaptic plasticity-related, schizophrenia genes

A comparative evaluation of various invasion assays testing colon carcinoma cell lines

Various colon carcinoma cell lines were tested in different invasion assays, i.e. invasion into Matrigel, into confluent fibroblast layers and into chicken heart tissue. Furthermore, invasive capacity and metastatic potential were determined in nude mice. The colon carcinoma cells used were the human cell lines Caco-2, SW-480, SW-620 and HT-29, and the murine lines Colon-26 and -38. None of the human colon carcinoma cells migrated through porous membranes coated with Matrigel; of the murine lines, only Colon-26 did. When incubated in a mixture of Matrigel and culture medium non-invading cells formed spheroid cultures, whereas invading cells showed a stellate outgrowth. Only the heterogeneously shaped (epithelioid and stellate) cells of SW-480 and SW-620 and the spindle-shaped cells of Colon-26 invaded clearly confluent skin and colon fibroblasts as well as chicken heart tissue. However, when transplanted into the caecum of nude and syngeneic mice, all the lines tested were invasive with the exception of Caco-2 cells. We conclude that the outcome of in vitro tests measuring the invasive capacity of neoplastic cells is largely dependent on the test system used. Invasive capacity in vitro is strongly correlated with cells having a spindle cell shape, vimentin expression and E-cadherin down regulation. In contrast, HT-29 and Colon-38 cells having an epithelioid phenotype were clearly invasive and metastatic in vivo, but not in vitro. © 1999 Cancer Research Campaig

The impacts of environmental warming on Odonata: a review

Climate change brings with it unprecedented rates of increase in environmental temperature, which will have major consequences for the earth's flora and fauna. The Odonata represent a taxon that has many strong links to this abiotic factor due to its tropical evolutionary history and adaptations to temperate climates. Temperature is known to affect odonate physiology including life-history traits such as developmental rate, phenology and seasonal regulation as well as immune function and the production of pigment for thermoregulation. A range of behaviours are likely to be affected which will, in turn, influence other parts of the aquatic ecosystem, primarily through trophic interactions. Temperature may influence changes in geographical distributions, through a shifting of species' fundamental niches, changes in the distribution of suitable habitat and variation in the dispersal ability of species. Finally, such a rapid change in the environment results in a strong selective pressure towards adaptation to cope and the inevitable loss of some populations and, potentially, species. Where data are lacking for odonates, studies on other invertebrate groups will be considered. Finally, directions for research are suggested, particularly laboratory studies that investigate underlying causes of climate-driven macroecological patterns

Enhancing Network Slicing Architectures with Machine Learning, Security, Sustainability and Experimental Networks Integration

Network Slicing (NS) is an essential technique extensively used in 5G networks computing strategies, mobile edge computing, mobile cloud computing, and verticals like the Internet of Vehicles and industrial IoT, among others. NS is foreseen as one of the leading enablers for 6G futuristic and highly demanding applications since it allows the optimization and customization of scarce and disputed resources among dynamic, demanding clients with highly distinct application requirements. Various standardization organizations, like 3GPP's proposal for new generation networks and state-of-the-art 5G/6G research projects, are proposing new NS architectures. However, new NS architectures have to deal with an extensive range of requirements that inherently result in having NS architecture proposals typically fulfilling the needs of specific sets of domains with commonalities. The Slicing Future Internet Infrastructures (SFI2) architecture proposal explores the gap resulting from the diversity of NS architectures target domains by proposing a new NS reference architecture with a defined focus on integrating experimental networks and enhancing the NS architecture with Machine Learning (ML) native optimizations, energy-efficient slicing, and slicing-tailored security functionalities. The SFI2 architectural main contribution includes the utilization of the slice-as-a-service paradigm for end-to-end orchestration of resources across multi-domains and multi-technology experimental networks. In addition, the SFI2 reference architecture instantiations will enhance the multi-domain and multi-technology integrated experimental network deployment with native ML optimization, energy-efficient aware slicing, and slicing-tailored security functionalities for the practical domain.Comment: 10 pages, 11 figure

A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM): a multi-cohort machine learning study

Background: Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. Methods: In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. Findings: 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS-B dataset. Differential abundance analysis, and the first round of feature selection using FS-PLS identified 35 protein biomarker candidates, of which 13 had commercial ELISA or Luminex tests available. 16 proteins with ELISA or Luminex tests available were identified by literature review. Further evaluation via Luminex and ELISA and the second round of feature selection using FS-PLS revealed a six-protein signature: three of the included proteins are elevated in bacterial infections (SELE, NGAL, and IFN-γ), and three are elevated in viral infections (IL18, NCAM1, and LG3BP). Performance testing of the signature using Luminex assays revealed area under the receiver operating characteristic curve values between 89·4% and 93·6%. Interpretation: This study has led to the identification of a protein signature that could be ultimately developed into a blood-based point-of-care diagnostic test for rapidly diagnosing bacterial and viral infections in febrile children. Such a test has the potential to greatly improve care of children who are febrile, ensuring that the correct individuals receive antibiotics