Absence of Appl2 sensitizes endotoxin shock through activation of PI3K/Akt pathway

BACKGROUND: The adapter proteins Appl1 (adaptor protein containing pleckstrin homology domain, phosphotyrosine domain, and leucine zipper motif 1) and Appl2 are highly homologous and involved in several signaling pathways. While previous studies have shown that Appl1 plays a pivotal role in adiponectin signaling and insulin secretion, the physiological functions of Appl2 are largely unknown. RESULTS: In the present study, the role of Appl2 in sepsis shock was investigated by using Appl2 knockout (KO) mice. When challenged with lipopolysaccharides (LPS), Appl2 KO mice exhibited more severe symptoms of endotoxin shock, accompanied by increased production of proinflammatory cytokines. In comparison with the wild-type control, deletion of Appl2 led to higher levels of TNF-α and IL-1β in primary macrophages. In addition, phosphorylation of Akt and its downstream effector NF-κB was significantly enhanced. By co-immunoprecipitation, we found that Appl2 and Appl1 interacted with each other and formed a complex with PI3K regulatory subunit p85α, which is an upstream regulator of Akt. Consistent with these results, deletion of Appl1 in macrophages exhibited characteristics of reduced Akt activation and decreased the production of TNFα and IL-1β when challenged by LPS. CONCLUSIONS: Results of the present study demonstrated that Appl2 is a critical negative regulator of innate immune response via inhibition of PI3K/Akt/NF-κB signaling pathway by forming a complex with Appl1 and PI3K.published_or_final_versio

Meta-Learning Based Knowledge Extrapolation for Knowledge Graphs in the Federated Setting

We study the knowledge extrapolation problem to embed new components (i.e., entities and relations) that come with emerging knowledge graphs (KGs) in the federated setting. In this problem, a model trained on an existing KG needs to embed an emerging KG with unseen entities and relations. To solve this problem, we introduce the meta-learning setting, where a set of tasks are sampled on the existing KG to mimic the link prediction task on the emerging KG. Based on sampled tasks, we meta-train a graph neural network framework that can construct features for unseen components based on structural information and output embeddings for them. Experimental results show that our proposed method can effectively embed unseen components and outperforms models that consider inductive settings for KGs and baselines that directly use conventional KG embedding methods.Comment: IJCAI 202

3D bioinspired microstructures for switchable repellency in both air and liquid

In addition to superhydrophobicity/superoleophobicity, surfaces with switchable water/oil repellency have also aroused considerable attention because of their potential values in microreactors, sensors, and microfluidics. Nevertheless, almost all those as-prepared surfaces are only applicable for liquids with higher surface tension (γ > 25.0 mN m-1) in air. In this work, inspired by some natural models, such as lotus leaf, springtail skin, and filefish skin, switchable repellency for liquids (γ = 12.0-72.8 mN m-1) in both air and liquid is realized via employing 3D deformable multiply re-entrant microstructures. Herein, the microstructures are fabricated by a two-photon polymerization based 3D printing technique and the reversible deformation is elaborately tuned by evaporation-induced bending and immersion-induced fast recovery (within 30 s). Based on 3D controlled microstructural architectures, this work offers an insightful explanation of repellency/penetration behavior at any three-phase interface and starts some novel ideas for manipulating opposite repellency by designing/fabricating stimuli-responsive microstructures.Published versionThis work was supported by the National Key Research and Development Program of China (No. 2017YFA0700500), the National Natural Science Foundation of China (Nos. 21327902 and 21902024), the 111 Project (B17011, the Ministry of Education of China), the Natural Science Foundation of Jiangsu Province (No. BK20180408), the China Postdoctoral Science Foundation (BX20180061), and the Fundamental Research Funds for the Central Universities (Nos. 2242019R20007 and 2242019K1G033)

Heterogeneous occurrence of evergreen broad-leaved forests in East Asia:Evidence from plant fossils

Evergreen broad-leaved forests (EBLFs) are widely distributed in East Asia and play a vital role in ecosystem stability. The occurrence of these forests in East Asia has been a subject of debate across various disciplines. In this study, we explored the occurrence of East Asian EBLFs from a palaeobotanical perspective. By collecting plant fossils from four regions in East Asia, we have established the evolutionary history of EBLFs. Through floral similarity analysis and paleoclimatic reconstruction, we have revealed a diverse spatio-temporal pattern for the occurrence of EBLFs in East Asia. The earliest occurrence of EBLFs in southern China can be traced back to the middle Eocene, followed by southwestern China during the late Eocene–early Oligocene. Subsequently, EBLFs emerged in Japan during the early Oligocene and eventually appeared in central-eastern China around the Miocene. Paleoclimate simulation results suggest that the precipitation of wettest quarter (PWetQ, mm) exceeding 600 mm is crucial for the occurrence of EBLFs. Furthermore, the heterogeneous occurrence of EBLFs in East Asia is closely associated with the evolution of the Asian Monsoon. This study provides new insights into the occurrence of EBLFs in East Asia.</p

The early Oligocene establishment of modern topography and plant diversity on the southeastern margin of the Tibetan Plateau

Quantifying the interactions between topography, climate and plant diversity within one of the world's biodiversity hotspots, the southeastern margin of the Tibetan Plateau, remains elusive due to few reliable quantitative paleoelevation reconstructions, precise geological age constraints and well-preserved plant fossils. The Lühe Basin, on the southeastern margin of Tibetan Plateau has yielded abundant plant fossils with a U-Pb age of 33–32 Ma, providing an opportunity to estimate the elevation of this region and plant diversity at that time. Fossil leaf physiognomy was used to reconstruct the paleoclimate and the paleoelevation of the basin was derived from moist enthalpy. The results show that the Lühe Basin, had attained it's present elevation (1.7 ± 0.9 km) by the early Oligocene and, compared to now, experienced a humid subtropical climate with a wetter dry season and lower precipitation seasonality in an overall wetter precipitation regime (1748.5 ± 606 mm). This was accompanied by a greater seasonal range in temperature, although the mean annual temperature (14.9 ± 2.3 °C) was similar to that of today (15.6 °C). Combined with previous studies, we conclude that the appearance of the modern flora across the southeastern margin of the Tibetan Plateau had started by the early Oligocene, corresponding with the establishment of modern topography at that time