The ER luminal binding protein (BiP) mediates an increase in drought tolerance in soybean and delays drought-induced leaf senescence in soybean and tobacco

The ER-resident molecular chaperone BiP (binding protein) was overexpressed in soybean. When plants growing in soil were exposed to drought (by reducing or completely withholding watering) the wild-type lines showed a large decrease in leaf water potential and leaf wilting, but the leaves in the transgenic lines did not wilt and exhibited only a small decrease in water potential. During exposure to drought the stomata of the transgenic lines did not close as much as in the wild type, and the rates of photosynthesis and transpiration became less inhibited than in the wild type. These parameters of drought resistance in the BiP overexpressing lines were not associated with a higher level of the osmolytes proline, sucrose, and glucose. It was also not associated with the typical drought-induced increase in root dry weight. Rather, at the end of the drought period, the BiP overexpressing lines had a lower level of the osmolytes and root weight than the wild type. The mRNA abundance of several typical drought-induced genes [NAC2, a seed maturation protein (SMP), a glutathione-S-transferase (GST), antiquitin, and protein disulphide isomerase 3 (PDI-3)] increased in the drought-stressed wild-type plants. Compared with the wild type, the increase in mRNA abundance of these genes was less (in some genes much less) in the BiP overexpressing lines that were exposed to drought. The effect of drought on leaf senescence was investigated in soybean and tobacco. It had previously been reported that tobacco BiP overexpression or repression reduced or accentuated the effects of drought. BiP overexpressing tobacco and soybean showed delayed leaf senescence during drought. BiP antisense tobacco plants, conversely, showed advanced leaf senescence. It is concluded that BiP overexpression confers resistance to drought, through an as yet unknown mechanism that is related to ER functioning. The delay in leaf senescence by BiP overexpression might relate to the absence of the response to drought

Addressing climate change with behavioral science:A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p

Addressing climate change with behavioral science: a global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions’ effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior—several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people’s initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors

Addressing climate change with behavioral science:A global intervention tournament in 63 countries

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.</p

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

<i>Schistosoma mansoni Sm</i>KI-1 serine protease inhibitor binds to elastase and impairs neutrophil function and inflammation

<div><p>Protease inhibitors have important function during homeostasis, inflammation and tissue injury. In this study, we described the role of <i>Schistosoma mansoni Sm</i>KI-1 serine protease inhibitor in parasite development and as a molecule capable of regulating different models of inflammatory diseases. First, we determine that recombinant (r) <i>Sm</i>KI-1 and its Kunitz domain but not the C-terminal region possess inhibitory activity against trypsin and neutrophil elastase (NE). To better understand the molecular basis of NE inhibition by S<i>m</i>KI-1, molecular docking studies were also conducted. Docking results suggest a complete blockage of NE active site by <i>Sm</i>KI-1 Kunitz domain. Additionally, r<i>Sm</i>KI-1 markedly inhibited the capacity of NE to kill schistosomes. In order to further investigate the role of <i>Sm</i>KI-1 in the parasite, we designed specific siRNA to knockdown <i>Sm</i>KI-1 in <i>S</i>. <i>mansoni</i>. <i>SmKI-1</i> gene suppression in larval stage of <i>S</i>. <i>mansoni</i> robustly impact in parasite development <i>in vitro</i> and <i>in vivo</i>. To determine the ability of <i>Sm</i>KI-1 to interfere with neutrophil migration and function, we tested <i>Sm</i>KI-1 anti-inflammatory potential in different murine models of inflammatory diseases. Treatment with <i>Sm</i>KI-1 rescued acetaminophen (APAP)-mediated liver damage, with a significant reduction in both neutrophil recruitment and elastase activity. In the model of gout arthritis, this protein reduced neutrophil accumulation, IL-1β secretion, hypernociception, and overall pathological score. Finally, we demonstrated the ability of <i>Sm</i>KI-1 to inhibit early events that trigger neutrophil recruitment in pleural cavities of mice in response to carrageenan. In conclusion, <i>Sm</i>KI-1 is a key protein in <i>S</i>. <i>mansoni</i> survival and it has the ability to inhibit neutrophil function as a promising therapeutic molecule against inflammatory diseases.</p></div