Youth education: maintenance the people in the field

This study aimed to provide new knowledge livestock activities prevalent in family units through the training of students from rural schools. The learning was through a multidisciplinary team, which was part of the educational program of technical training of rural youth, entitled: "Youth Empowerment: Man Maintenance in the field", responsible for disseminating technologies through courses and practical training. This project was carried out in 55 municipal and state schools in Rio Grande do Norte, involving 19 municipalities and 1242 students from rural areas. The educational content of the theoretical segment had the following themes: food, health and reproductive management of cattle, goats, sheep and hens. It was noticed significant absorption of mainly content taught in the following topics: caring for the young (87.76%), importance of castration (91.4%) and handling facilities (96.48%), respectively belonging to the management of cattle, goat, sheep and hens. The higher performance of students among the topics discussed was the management of hens, possibly due to their wider dissemination in the region. The work achieved its goal of imparting knowledge to students, once implemented, will enable a subsequent increase in production by opening new income opportunities for small farmers and improving the economic development of families. Thus, the project has achieved the goals and provided to students from rural areas of the covered municipalities, a working knowledge of increment to be readily adopted in their production systems with real gains in health and management of cattle, goats, sheep and hens.This study aimed to provide new knowledge for livestock activities prevalent in family units through the training of students from rural schools. The learning was through a multidisciplinary team, which was part of the educational program of technical training of rural youth, entitled: "Youth Empowerment: Maintenance the people in the field", responsible for disseminating technologies through courses and practical training. This project was carried out in 55 municipal and state schools in Rio Grande do Norte State, Brazil, involving 19 municipalities and 1242 students from rural areas. The educational content of the theoretical segment had the following themes: food, health and reproductive management of cattle, goats, sheep and hens. It was noticed significant absorption of mainly content taught in the following topics: caring for the foal (87.76%), importance of castration (91.4%) and handling facilities (96.48%), respectively to the management of cattle, goat, sheep and hens. The higher performance of students among the topics discussed was the management of hens, possibly due to their wider dissemination in the region. The work achieved its goal of imparting knowledge to students, once implemented, will enable a subsequent increase in production by opening new income opportunities for small farmers and improving the economic development of families. Thus, the project has achieved the goals and provided to students from rural areas of the covered municipalities, a working knowledge of increment to be readily adopted in their production systems with real gains in health and management of cattle, goats, sheep and hens

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Proteomic Analysis of <i>Trypanosoma cruzi</i> Response to Ionizing Radiation Stress

<div><p><i>Trypanosoma cruzi</i>, the causative agent of Chagas disease, is extremely resistant to ionizing radiation, enduring up to 1.5 kGy of gamma rays. Ionizing radiation can damage the DNA molecule both directly, resulting in double-strand breaks, and indirectly, as a consequence of reactive oxygen species production. After a dose of 500 Gy of gamma rays, the parasite genome is fragmented, but the chromosomal bands are restored within 48 hours. Under such conditions, cell growth arrests for up to 120 hours and the parasites resume normal growth after this period. To better understand the parasite response to ionizing radiation, we analyzed the proteome of irradiated (4, 24, and 96 hours after irradiation) and non-irradiated <i>T. cruzi</i> using two-dimensional differential gel electrophoresis followed by mass spectrometry for protein identification. A total of 543 spots were found to be differentially expressed, from which 215 were identified. These identified protein spots represent different isoforms of only 53 proteins. We observed a tendency for overexpression of proteins with molecular weights below predicted, indicating that these may be processed, yielding shorter polypeptides. The presence of shorter protein isoforms after irradiation suggests the occurrence of post-translational modifications and/or processing in response to gamma radiation stress. Our results also indicate that active translation is essential for the recovery of parasites from ionizing radiation damage. This study therefore reveals the peculiar response of <i>T. cruzi</i> to ionizing radiation, raising questions about how this organism can change its protein expression to survive such a harmful stress.</p></div

Experimental design.

<p>Each two-dimensional gel was loaded with 50 µg of total protein extract per sample, labeled either with Cy3 or Cy5. The internal control (a pool containing 50 µg of all time point proteins: NI, 4, 24, and 96 hours after irradiation) was labeled with Cy2.</p

Distribution of upregulated and downregulated protein spots versus molecular weight, pI, and fold change.

<p>In the scatter plots, upregulated protein spots are shown in red and downregulated protein spots are shown in green. The correlation between molecular weight and pI or fold-change ratio is shown in (A) and (B), respectively. Spots with no significant difference in expression are colored gray. The blue line indicates the negative correlation between molecular weight and fold change.</p

The effect of irradiation and translation inhibition on <i>T. cruzi</i> epimastigotes growth.

<p>Irradiated (500 Gy) or NI parasites were treated with cycloheximide 50 µg/mL (A) or puromycin 25 µg/mL (B), both added 4 hours after irradiation. Each point represents the mean ± standard deviation of three different experiments.</p

2D-DIGE analysis of total protein extracts of irradiated and NI epimastigote cells.

<p>Gel images 1–6 (see the experimental design in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0097526#pone-0097526-t001" target="_blank">Table 1</a>) showing – in triplicate – parasite proteins from each time point, labeled either with Cy3 (green) or Cy5 (red). Proteins were separated in the first dimension along a pH gradient (pH 4–7, 18 cm Immobiline DryStrip (GE Healthcare, USA), and in the second dimension in a 12% polyacrylamide gel. The molecular weight marker (MW) is indicated in kDa.</p