ワカメ資化性イムノバイオティクスのイムノシンバイオティクスとしての利用性に関する基礎研究

Tohoku University課

An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms

Stochastic variance reduced methods have shown strong performance in solving finite-sum problems. However, these methods usually require the users to manually tune the step-size, which is time-consuming or even infeasible for some large-scale optimization tasks. To overcome the problem, we propose and analyze several novel adaptive variants of the popular SAGA algorithm. Eventually, we design a variant of Barzilai-Borwein step-size which is tailored for the incremental gradient method to ensure memory efficiency and fast convergence. We establish its convergence guarantees under general settings that allow non-Euclidean norms in the definition of smoothness and the composite objectives, which cover a broad range of applications in machine learning. We improve the analysis of SAGA to support non-Euclidean norms, which fills the void of existing work. Numerical experiments on standard datasets demonstrate a competitive performance of the proposed algorithm compared with existing variance-reduced methods and their adaptive variants

Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes

In-context learning (ICL) refers to the ability of a model to condition on a few in-context demonstrations (input-output examples of the underlying task) to generate the answer for a new query input, without updating parameters. Despite the impressive ICL ability of LLMs, it has also been found that ICL in LLMs is sensitive to input demonstrations and limited to short context lengths. To understand the limitations and principles for successful ICL, we conduct an investigation with ICL linear regression of transformers. We characterize several Out-of-Distribution (OOD) cases for ICL inspired by realistic LLM ICL failures and compare transformers with DeepSet, a simple yet powerful architecture for ICL. Surprisingly, DeepSet outperforms transformers across a variety of distribution shifts, implying that preserving permutation invariance symmetry to input demonstrations is crucial for OOD ICL. The phenomenon specifies a fundamental requirement by ICL, which we termed as ICL invariance. Nevertheless, the positional encodings in LLMs will break ICL invariance. To this end, we further evaluate transformers with identical positional encodings and find preserving ICL invariance in transformers achieves state-of-the-art performance across various ICL distribution shiftsComment: Ongoing work; preliminary versio

Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Invariant graph representation learning aims to learn the invariance among data from different environments for out-of-distribution generalization on graphs. As the graph environment partitions are usually expensive to obtain, augmenting the environment information has become the de facto approach. However, the usefulness of the augmented environment information has never been verified. In this work, we find that it is fundamentally impossible to learn invariant graph representations via environment augmentation without additional assumptions. Therefore, we develop a set of minimal assumptions, including variation sufficiency and variation consistency, for feasible invariant graph learning. We then propose a new framework Graph invAriant Learning Assistant (GALA). GALA incorporates an assistant model that needs to be sensitive to graph environment changes or distribution shifts. The correctness of the proxy predictions by the assistant model hence can differentiate the variations in spurious subgraphs. We show that extracting the maximally invariant subgraph to the proxy predictions provably identifies the underlying invariant subgraph for successful OOD generalization under the established minimal assumptions. Extensive experiments on datasets including DrugOOD with various graph distribution shifts confirm the effectiveness of GALA.Comment: NeurIPS 2023, 34 pages, 35 figure

Isolation and immunocharacterization of lactobacillus salivarius from the intestine of wakame-fed pigs to develop novel "Immunosynbiotics"

Emerging threats of antimicrobial resistance necessitate the exploration of effective alternatives for healthy livestock growth strategies. ?Immunosynbiotics?, a combination of immunoregulatory probiotics and prebiotics with synergistic effects when used together in feed, would be one of the most promising candidates. Lactobacilli are normal residents of the gastrointestinal tract of pigs, and many of them are able to exert beneficial immunoregulatory properties. On the other hand, wakame (Undaria pinnafida), an edible seaweed, has the potential to be used as an immunoregulatory prebiotic when added to livestock feed. Therefore, in order to develop a novel immunosynbiotic, we isolated and characterized immunoregulatory lactobacilli with the ability to utilize wakame. Following a month-long in vivo wakame feeding trial in 8-week-old Landrace pigs (n = 6), sections of intestinal mucous membrane were processed for bacteriological culture and followed by identification of pure colonies by 16S rRNA sequence. Each isolate was characterized in vitro in terms of their ability to assimilate to the wakame and to differentially modulate the expression of interleukin-6 (IL-6) and interferon beta (IFN-β) in the porcine intestinal epithelial (PIE) cells triggered by Toll-like receptor (TLR)-4 and TLR-3 activation, respectively. We demonstrated that feeding wakame to pigs significantly increased the lactobacilli population in the small intestine. We established a wakame-component adjusted culture media that allowed the isolation and characterization of a total of 128 Lactobacilli salivarius colonies from the gut of wakame-fed pigs. Interestingly, several L. salivarius isolates showed both high wakame assimilation ability and immunomodulatory capacities. Among the wakame assimilating isolates, L. salivarius FFIG71 showed a significantly higher capacity to upregulate the IL-6 expression, and L. salivarius FFIG131 showed significantly higher capacity to upregulate the IFN-β expression; these could be used as immunobiotic strains in combination with wakame for the development of novel immunologically active feeds for pigs.Fil: Masumizu, Yuki. Tohoku University; JapónFil: Zhou, Binghui. Tohoku University; JapónFil: Humayun Kober, AKM. Tohoku University; Japón. Chittagong Veterinary and Animal Sciences University; BangladeshFil: Islam, M. Aminul. Agricultural University; Bangladesh. Tohoku University; JapónFil: Iida, Hikaru. Tohoku University; JapónFil: Ikeda-Ohtsubo, Wakako. Tohoku University; JapónFil: Suda, Yoshihito. Department Of Food Agriculture, Miyagi University; JapónFil: Albarracín, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; Argentina. Tohoku University; Japón. Universidad Nacional de Tucumán; ArgentinaFil: Nochi, Tomonori. Tohoku University; JapónFil: Aso, Hisashi. Tohoku University; JapónFil: Suzuki, Keiichi. Tohoku University; JapónFil: Villena, Julio Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Centro de Referencia para Lactobacilos; Argentina. Tohoku University; JapónFil: Kitazawa, Haruki. Tohoku University; Japó

ITCH Nuclear Translocation and H1.2 Polyubiquitination Negatively Regulate the DNA Damage Response

The downregulation of the DNA damage response (DDR) enables aggressive tumors to achieve uncontrolled proliferation against replication stress, but the mechanisms underlying this process in tumors are relatively complex. Here, we demonstrate a mechanism through which a distinct E3 ubiquitin ligase, ITCH, modulates DDR machinery in triple-negative breast cancer (TNBC). We found that expression of a nuclear form of ITCH was significantly increased in human TNBC cell lines and tumor specimens. Phosphorylation of ITCH at Ser257 by AKT led to the nuclear localization of ITCH and ubiquitination of H1.2. The ITCH-mediated polyubiquitination of H1.2 suppressed RNF8/RNF168-dependent formation of 53BP1 foci, which plays important roles in DDR. Consistent with these findings, impaired ITCH nuclear translocation and H1.2 polyubiquitination sensitized cells to replication stress and limited cell growth and migration. AKT activation of ITCH-H1.2 axis may confer TNBC cells with a DDR repression to counteract the replication stress and increase cancer cell survivorship and growth potential