Graph Out-of-Distribution Generalization with Controllable Data Augmentation

Graph Neural Network (GNN) has demonstrated extraordinary performance in classifying graph properties. However, due to the selection bias of training and testing data (e.g., training on small graphs and testing on large graphs, or training on dense graphs and testing on sparse graphs), distribution deviation is widespread. More importantly, we often observe \emph{hybrid structure distribution shift} of both scale and density, despite of one-sided biased data partition. The spurious correlations over hybrid distribution deviation degrade the performance of previous GNN methods and show large instability among different datasets. To alleviate this problem, we propose \texttt{OOD-GMixup} to jointly manipulate the training distribution with \emph{controllable data augmentation} in metric space. Specifically, we first extract the graph rationales to eliminate the spurious correlations due to irrelevant information. Secondly, we generate virtual samples with perturbation on graph rationale representation domain to obtain potential OOD training samples. Finally, we propose OOD calibration to measure the distribution deviation of virtual samples by leveraging Extreme Value Theory, and further actively control the training distribution by emphasizing the impact of virtual OOD samples. Extensive studies on several real-world datasets on graph classification demonstrate the superiority of our proposed method over state-of-the-art baselines.Comment: Under revie

TNFAIP1 contributes to the neurotoxicity induced by Aβ25–35 in Neuro2a cells

Background: Amyloid-beta (Aβ) accumulation is a hallmark of Alzheimer’s disease (AD) that can lead to neuronal dysfunction and apoptosis. Tumor necrosis factor, alpha-induced protein 1 (TNFAIP1) is an apoptotic protein that was robustly induced in the transgenic C. elegans AD brains. However, the roles of TNFAIP1 in AD have not been investigated. Results: We found TNFAIP1 protein and mRNA levels were dramatically elevated in primary mouse cortical neurons and Neuro2a (N2a) cells exposed to Aβ25–35. Knockdown and overexpression of TNFAIP1 significantly attenuated and exacerbated Aβ25–35-induced neurotoxicity in N2a cells, respectively. Further studies showed that TNFAIP1 knockdown significantly blocked Aβ25–35-induced cleaved caspase 3, whereas TNFAIP1 overexpression enhanced Aβ25–35-induced cleaved caspase 3, suggesting that TNFAIP1 plays an important role in Aβ25–35-induced neuronal apoptosis. Moreover, we observed that TNFAIP1 was capable of inhibiting the levels of phosphorylated Akt and CREB, and also anti-apoptotic protein Bcl-2. TNFAIP1 overexpression enhanced the inhibitory effect of Aβ25–35 on the levels of p-CREB and Bcl-2, while TNFAIP1 knockdown reversed Aβ25–35-induced attenuation in the levels of p-CREB and Bcl-2. Conclusion: These results suggested that TNFAIP1 contributes to Aβ25–35-induced neurotoxicity by attenuating Akt/CREB signaling pathway, and Bcl-2 expression

A complex regulatory network underlies de novo root regeneration in red maple (Acer rubrum)

Red maple (Acer rubrum L.) is ornamentally and medicinally valuable. However, its wide application is restricted by the difficulty of rooting in cuttings. We analyzed paraffin sections of roots regenerating using RNA-Seq to decipher the mechanisms underlying de novo root regeneration (DNRR) in red maple cuttings. This work contributes to improving the rooting rate and shortening the rooting time. We identified four stages during DNRR: 0 day after induction (DAI), no new cell formation; 30 DAI, root meristem organization; 36 DAI, root primordium formation; and 45 DAI, root elongation growth. We identified 37,959 unigenes by de novo assembly, with 25,477(67.12%) functionally annotated. Furthermore, we identified 1,285 differentially expressed genes (DEGs) between adjacent stages. From GO and KEGG enrichment networks, we found evidence that plant hormones are significant in DNRR of red maple cuttings. Specifically, 149 DEGs functioned in hormone signal transduction pathways, particularly those involving ethylene, auxin, and jasmonic acid (JA). We propose a complex regulatory network model of DNRR in red maple, where wounding induces root regeneration through pathways of JA and auxin signaling. The transcription factors ERF109 and ERF115 integrate JA signal and participate in DNRR directly by regulating SCR activation and indirectly, by promoting auxin biosynthesis.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Targeting Mcl-1 Degradation by Bergenin Inhibits Tumorigenesis of Colorectal Cancer Cells

Myeloid leukemia 1 (Mcl-1) is frequently overexpressed in human malignancies and emerged as a promising drug target. In this study, we verified the inhibitory effect of bergenin on colorectal cancer cells both in vivo and in vitro. In an in vitro setting, bergenin significantly reduced the viability and colony formation and promoted apoptosis of CRC cells dose-dependently. Bergenin decreased the activity of Akt/GSK3β signaling and enhanced the interaction between FBW7 and Mcl-1, which eventually induced Mcl-1 ubiquitination and degradation. Using the HA-Ub K48R mutant, we demonstrated that bergenin promotes Mcl-1 K48-linked polyubiquitination and degradation. In vivo studies showed that bergenin significantly reduced tumor size and weight without toxicity to vital organs in mice. Overall, our results support the role of bergenin in inhibiting CRC cells via inducing Mcl-1 destruction, suggesting that targeting Mcl-1 ubiquitination could be an alternative strategy for antitumor therapy