Rapamycin Attenuated Zinc-Induced Tau Phosphorylation and Oxidative Stress in Rats: Involvement of Dual mTOR/p70S6K and Nrf2/HO-1 Pathways

Alzheimer's disease is pathologically characterized by abnormal accumulation of amyloid-beta plaques, neurofibrillary tangles, oxidative stress, neuroinflammation, and neurodegeneration. Metal dysregulation, including excessive zinc released by presynaptic neurons, plays an important role in tau pathology and oxidase activation. The activities of mammalian target of rapamycin (mTOR)/ribosomal S6 protein kinase (p70S6K) are elevated in the brains of patients with Alzheimer's disease. Zinc induces tau hyperphosphorylation via mTOR/P70S6K activation in vitro. However, the involvement of the mTOR/P70S6K pathway in zinc-induced oxidative stress, tau degeneration, and synaptic and cognitive impairment has not been fully elucidated in vivo. Here, we assessed the effect of pathological zinc concentrations in SH-SY5Y cells by using biochemical assays and immunofluorescence staining. Rats (n = 18, male) were laterally ventricularly injected with zinc, treated with rapamycin (intraperitoneal injection) for 1 week, and assessed using the Morris water maze. Evaluation of oxidative stress, tau phosphorylation, and synaptic impairment was performed using the hippocampal tissue of the rats by biochemical assays and immunofluorescence staining. The results from the Morris water maze showed that the capacity of spatial memory was impaired in zinc-treated rats. Zinc sulfate significantly increased the levels of P-mTOR Ser2448, P-p70S6K Thr389, and P-tau Ser356 and decreased the levels of nuclear factor erythroid 2-related factor-2 (Nrf2) and heme oxygenase-1 (HO-1) in SH-SY5Y cells and in zinc-treated rats compared with the control groups. Increased expression of reactive oxygen species was observed in zinc sulfate-induced SH-SY5Y cells and in the hippocampus of zinc-injected rats. Rapamycin, an inhibitor of mTOR, rescued zinc-induced increases in mTOR/p70S6K activation, tau phosphorylation, and oxidative stress, and Nrf2/HO-1 inactivation, cognitive impairment, and synaptic impairment reduced the expression of synapse-related proteins in zinc-injected rats. In conclusion, our findings imply that rapamycin prevents zinc-induced cognitive impairment and protects neurons from tau pathology, oxidative stress, and synaptic impairment by decreasing mTOR/p70S6K hyperactivity and increasing Nrf2/HO-1 activity

Towards Collaborative Intelligence: Routability Estimation based on Decentralized Private Data

Applying machine learning (ML) in design flow is a popular trend in EDA with various applications from design quality predictions to optimizations. Despite its promise, which has been demonstrated in both academic researches and industrial tools, its effectiveness largely hinges on the availability of a large amount of high-quality training data. In reality, EDA developers have very limited access to the latest design data, which is owned by design companies and mostly confidential. Although one can commission ML model training to a design company, the data of a single company might be still inadequate or biased, especially for small companies. Such data availability problem is becoming the limiting constraint on future growth of ML for chip design. In this work, we propose an Federated-Learning based approach for well-studied ML applications in EDA. Our approach allows an ML model to be collaboratively trained with data from multiple clients but without explicit access to the data for respecting their data privacy. To further strengthen the results, we co-design a customized ML model FLNet and its personalization under the decentralized training scenario. Experiments on a comprehensive dataset show that collaborative training improves accuracy by 11% compared with individual local models, and our customized model FLNet significantly outperforms the best of previous routability estimators in this collaborative training flow.Comment: 6 pages, 2 figures, 5 tables, accepted by DAC'2

Legume Shrubs Are More Nitrogen-Homeostatic than Non-legume Shrubs

Legumes are characterized as keeping stable nutrient supply under nutrient-limited conditions. However, few studies examined the legumes' stoichiometric advantages over other plants across various taxa in natural ecosystems. We explored differences in nitrogen (N) and phosphorus (P) stoichiometry of different tissue types (leaf, stem, and root) between N2-fixing legume shrubs and non-N2-fixing shrubs from 299 broadleaved deciduous shrubland sites in northern China. After excluding effects of taxonomy and environmental variables, these two functional groups differed considerably in nutrient regulation. N concentrations and N:P ratios were higher in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated between the plants and soil for non-N2-fixing shrubs, but not for legume shrubs, indicating a stronger stoichiometric homeostasis in legume shrubs than in non-N2-fixing shrubs. N concentrations were positively correlated among three tissue types for non-N2-fixing shrubs, but not between leaves and non-leaf tissues for legume shrubs, demonstrating that N concentrations were more dependent among tissues for non-N2-fixing shrubs than for legume shrubs. N and P concentrations were correlated within all tissues for both functional groups, but the regression slopes were flatter for legume shrubs than non-N2-fixing shrubs, implying that legume shrubs were more P limited than non-N2-fixing shrubs. These results address significant differences in stoichiometry between legume shrubs and non-N2-fixing shrubs, and indicate the influence of symbiotic nitrogen fixation (SNF) on plant stoichiometry. Overall, N2-fixing legume shrubs are higher and more stoichiometrically homeostatic in N concentrations. However, due to excess uptake of N, legumes may suffer from potential P limitation. With their N advantage, legume shrubs could be good nurse plants in restoration sites with degraded soil, but their P supply should be taken care of during management according to our results

Increasing water availability and facilitation weaken biodiversity-biomass relationships in shrublands

Positive biodiversity–ecosystem‐functioning (BEF) relationships are commonly found in experimental and observational studies, but how they vary in different environmental contexts and under the influence of coexisting life forms is still controversial. Investigating these variations is important for making predictions regarding the dynamics of plant communities and carbon pools under global change. We conducted this study across 433 shrubland sites in northern China. We fitted structural equation models (SEMs) to analyze the variation in the species‐richness–biomass relationships of shrubs and herbs along a wetness gradient and general liner models (GLMs) to analyze how shrub or herb biomass affected the species‐richness–biomass relationship of the other life form. We found that the positive species‐richness–biomass relationships for both shrubs and herbs became weaker or even negative with higher water availability, likely indicating stronger interspecific competition within life forms under more benign conditions. After accounting for variation in environmental contexts using residual regression, we found that the benign effect of greater facilitation by a larger shrub biomass reduced the positive species‐richness–biomass relationships of herbs, causing them to become nonsignificant. Different levels of herb biomass, however, did not change the species‐richness–biomass relationship of shrubs, possibly because greater herb biomass did not alter the stress level for shrubs. We conclude that biodiversity in the studied plant communities is particularly important for plant biomass production under arid conditions and that it might be possible to use shrubs as nurse plants to facilitate understory herb establishment in ecological restoration

Carbon–biodiversity relationships in a highly diverse subtropical forest

Carbon‐focused climate mitigation strategies are becoming increasingly important in forests. However, with ongoing biodiversity declines we require better knowledge of how much such strategies account for biodiversity. We particularly lack information across multiple trophic levels and on established forests, where the interplay between carbon stocks, stand age, and tree diversity might influence carbon–biodiversity relationships. Using a large dataset (>4600 heterotrophic species of 23 taxonomic groups) from secondary, subtropical forests, we tested how multitrophic diversity and diversity within trophic groups relate to aboveground, belowground, and total carbon stocks at different levels of tree species richness and stand age. Our study revealed that aboveground carbon, the key component of climate‐based management, was largely unrelated to multitrophic diversity. By contrast, total carbon stocks—that is, including belowground carbon—emerged as a significant predictor of multitrophic diversity. Relationships were nonlinear and strongest for lower trophic levels, but nonsignificant for higher trophic level diversity. Tree species richness and stand age moderated these relationships, suggesting long‐term regeneration of forests may be particularly effective in reconciling carbon and biodiversity targets. Our findings highlight that biodiversity benefits of climate‐oriented management need to be evaluated carefully, and only maximizing aboveground carbon may fail to account for biodiversity conservation requirements

Leaf size of woody dicots predicts ecosystem primary productivity

A key challenge in ecology is to understand the relationships between organismal traits and ecosystem processes. Here, with a novel dataset of leaf length and width for 10 480 woody dicots in China and 2374 in North America, we show that the variation in community mean leaf size is highly correlated with the variation in climate and ecosystem primary productivity, independent of plant life form. These relationships likely reflect how natural selection modifies leaf size across varying climates in conjunction with how climate influences canopy total leaf area. We find that the leaf size–primary productivity functions based on the Chinese dataset can predict productivity in North America and vice-versa. In addition to advancing understanding of the relationship between a climate-driven trait and ecosystem functioning, our findings suggest that leaf size can also be a promising tool in palaeoecology for scaling from fossil leaves to palaeo-primary productivity of woody ecosystems

Species richness stabilizes productivity via asynchrony and drought-tolerance diversity in a large-scale tree biodiversity experiment

Extreme climatic events threaten forests and their climate mitigation potential globally. Understanding the drivers promoting ecosystem stability is therefore considered crucial for mitigating adverse climate change effects on forests. Here, we use structural equation models to explain how tree species richness, asynchronous species dynamics, species-level population stability, and drought-tolerance traits relate to the stability of forest productivity along an experimentally manipulated species richness gradient ranging from 1 to 24 tree species. Tree species richness improved community stability by increasing asynchrony. That is, at higher species richness, interannual variation in productivity among tree species buffered the community against stress-related productivity declines. This effect was positively related to variation in stomatal control and resistance-acquisition strategies among species, but not to the community-weighted means of these trait syndromes. The identified mechanisms by which tree species richness stabilizes forest productivity emphasize the importance of diverse, mixed-species forests to adapt to climate change

Species richness stabilizes productivity via asynchrony and drought-tolerance diversity in a large-scale tree biodiversity experiment

Extreme climatic events threaten forests and their climate mitigation potential globally. Understanding the drivers promoting ecosystem stability is therefore considered crucial for mitigating adverse climate change effects on forests. Here, we use structural equation models to explain how tree species richness, asynchronous species dynamics, species-level population stability, and drought-tolerance traits relate to the stability of forest productivity along an experimentally manipulated species richness gradient ranging from 1 to 24 tree species. Tree species richness improved community stability by increasing asynchrony. That is, at higher species richness, interannual variation in productivity among tree species buffered the community against stress-related productivity declines. This effect was positively related to variation in stomatal control and resistance-acquisition strategies among species, but not to the community-weighted means of these trait syndromes. The identified mechanisms by which tree species richness stabilizes forest productivity emphasize the importance of diverse, mixed-species forests to adapt to climate change