New insight into the buckling of growing bilayers

Growth-induced morphological instabilities of film/substrate bilayers are critical for certain (mal)functionalities of biological systems. Understanding the mechanics helps in developing new diagnostics andin designing bio-inspired engineering products, e.g. artificial digital skin.We address gaps in the understanding of the nonlinear mechanics of growing bilayers in the critical and post-critical regimes, particularly when:-the substrate grows much faster than the thin film, and-the film and substrate have comparable stiffnesse

Corpus-Steered Query Expansion with Large Language Models

Recent studies demonstrate that query expansions generated by large language models (LLMs) can considerably enhance information retrieval systems by generating hypothetical documents that answer the queries as expansions. However, challenges arise from misalignments between the expansions and the retrieval corpus, resulting in issues like hallucinations and outdated information due to the limited intrinsic knowledge of LLMs. Inspired by Pseudo Relevance Feedback (PRF), we introduce Corpus-Steered Query Expansion (CSQE) to promote the incorporation of knowledge embedded within the corpus. CSQE utilizes the relevance assessing capability of LLMs to systematically identify pivotal sentences in the initially-retrieved documents. These corpus-originated texts are subsequently used to expand the query together with LLM-knowledge empowered expansions, improving the relevance prediction between the query and the target documents. Extensive experiments reveal that CSQE exhibits strong performance without necessitating any training, especially with queries for which LLMs lack knowledge.Comment: EACL 2024 (Short

Unlikelihood Tuning on Negative Samples Amazingly Improves Zero-Shot Translation

Zero-shot translation (ZST), which is generally based on a multilingual neural machine translation model, aims to translate between unseen language pairs in training data. The common practice to guide the zero-shot language mapping during inference is to deliberately insert the source and target language IDs, e.g., for English and for German. Recent studies have shown that language IDs sometimes fail to navigate the ZST task, making them suffer from the off-target problem (non-target language words exist in the generated translation) and, therefore, difficult to apply the current multilingual translation model to a broad range of zero-shot language scenarios. To understand when and why the navigation capabilities of language IDs are weakened, we compare two extreme decoder input cases in the ZST directions: Off-Target (OFF) and On-Target (ON) cases. By contrastively visualizing the contextual word representations (CWRs) of these cases with teacher forcing, we show that 1) the CWRs of different languages are effectively distributed in separate regions when the sentence and ID are matched (ON setting), and 2) if the sentence and ID are unmatched (OFF setting), the CWRs of different languages are chaotically distributed. Our analyses suggest that although they work well in ideal ON settings, language IDs become fragile and lose their navigation ability when faced with off-target tokens, which commonly exist during inference but are rare in training scenarios. In response, we employ unlikelihood tuning on the negative (OFF) samples to minimize their probability such that the language IDs can discriminate between the on- and off-target tokens during training. Experiments spanning 40 ZST directions show that our method reduces the off-target ratio by -48.0% on average, leading to a +9.1 BLEU improvement with only an extra +0.3% tuning cost

Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction

Promotions are becoming more important and prevalent in e-commerce to attract customers and boost sales, leading to frequent changes of occasions, which drives users to behave differently. In such situations, most existing Click-Through Rate (CTR) models can't generalize well to online serving due to distribution uncertainty of the upcoming occasion. In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions. Firstly, we design a time series that consists of occasion signals generated from the online business scenario. Since occasion signals are more discriminative in the frequency domain, we apply Fourier Transformation to sliding time windows upon the time series, obtaining a sequence of frequency spectrum which is then processed by Occasion Evolution Layer (OEL). In this way, a high-order occasion representation can be learned to handle the online distribution uncertainty. Moreover, we adopt multiple experts to learn feature representations from multiple aspects, which are guided by the occasion representation via an attention mechanism. Accordingly, a mixture of feature representations is obtained adaptively for different occasions to predict the final CTR. Experimental results on real-world datasets validate the superiority of MOEF and online A/B tests also show MOEF outperforms representative CTR models significantly

PKD1 Phosphorylation-Dependent Degradation of SNAIL by SCF-FBXO11 Regulates Epithelial-Mesenchymal Transition and Metastasis

SummaryMetastatic dissemination is often initiated by the reactivation of an embryonic development program referred to as epithelial-mesenchymal transition (EMT). The transcription factor SNAIL promotes EMT and elicits associated pathological characteristics such as invasion, metastasis, and stemness. To better understand the posttranslational regulation of SNAIL, we performed a luciferase-based, genome-wide E3 ligase siRNA library screen and identified SCF-FBXO11 as an important E3 that targets SNAIL for ubiquitylation and degradation. Furthermore, we discovered that SNAIL degradation by FBXO11 is dependent on Ser-11 phosphorylation of SNAIL by protein kinase D1 (PKD1). FBXO11 blocks SNAIL-induced EMT, tumor initiation, and metastasis in multiple breast cancer models. These findings establish the PKD1-FBXO11-SNAIL axis as a mechanism of posttranslational regulation of EMT and cancer metastasis

Transcriptome and metabolome for identifying key metabolites impacting the Vibrio parahaemolyticus in Litopenaeus vannamei

IntroductionShrimp is an important aquaculture species worldwide. Vibrio parahaemolyticus (VP) is an opportunistic pathogen of Litopenaeus vannamei that can cause diseases such as acute hepatopancreatic necrotic disease (AHPND), resulting in significant losses to the shrimp farming industry.MethodsIn this study, We analyzed two shrimp populations by transcriptomics and non-targeted metabolomics, which exhibited significant differences in resistance to VP. Through integrated analysis, we identified genes and metabolites linked to the development of shrimp's resistance to VP.Results and discussionThe analysis revealed that the differential metabolism of flavonoid compounds, especially quercetin, significantly influences the expression of shrimp's resistance to VP. Supplementing feed with an appropriate quantity of quercetin has the potential to increase the expression of crucial genes in the NF-κB pathway, including TLR and AP1, along with the expression of the antibacterial peptide crustin, resulting in a decreased mortality rate. Together, these results indicate that an appropriate amount of quercetin can strengthen the immune response of shrimp to VP, thereby reducing the incidence of AHPND

Unraveling the pathogenic potential of the Pentatrichomonas hominis PHGD strain: impact on IPEC-J2 cell growth, adhesion, and gene expression

Pentatrichomonas hominis, a flagellated parasitic protozoan, predominantly infects the mammalian digestive tract, often causing symptoms such as abdominal pain and diarrhea. However, studies investigating its pathogenicity are limited, and the mechanisms underlying P. hominis-induced diarrhea remain unclear. Establishing an in vitro cell model for P. hominis infection is imperative. This study investigated the interaction between P. hominis and IPEC-J2 cells and its impact on parasite growth, adhesion, morphology, and cell viability. Co-cultivation of P. hominis with IPEC-J2 cells resulted in exponential growth of the parasite, with peak densities reaching approximately 4.8 × 105 cells/mL and 1.2 × 106 cells/mL at 48 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. The adhesion rate of P. hominis to IPEC-J2 cells reached a maximum of 93.82% and 86.57% at 24 h for initial inoculation concentrations of 104 cells/mL and 105 cells/mL, respectively. Morphological changes in IPEC-J2 cells co-cultivated with P. hominis were observed, manifesting as elongated and irregular shapes. The viability of IPEC-J2 cells exhibited a decreasing trend with increasing P. hominis concentration and co-cultivation time. Additionally, the mRNA expression levels of IL-6, IL-8, and TNF-α were upregulated, whereas those of CAT and CuZn-SOD were downregulated. These findings provide quantitative evidence that P. hominis can promote its growth by adhering to IPEC-J2 cells, inducing morphological changes, reducing cell viability, and triggering inflammatory responses. Further in vivo studies are warranted to confirm these results and enhance our understanding of P. hominis infection