Nearest Neighbor Machine Translation is Meta-Optimizer on Output Projection Layer

Nearest Neighbor Machine Translation ($k$NN-MT) has achieved great success in domain adaptation tasks by integrating pre-trained Neural Machine Translation (NMT) models with domain-specific token-level retrieval. However, the reasons underlying its success have not been thoroughly investigated. In this paper, we comprehensively analyze $k$NN-MT through theoretical and empirical studies. Initially, we provide new insights into the working mechanism of $k$NN-MT as an efficient technique to implicitly execute gradient descent on the output projection layer of NMT, indicating that it is a specific case of model fine-tuning. Subsequently, we conduct multi-domain experiments and word-level analysis to examine the differences in performance between $k$NN-MT and entire-model fine-tuning. Our findings suggest that: (1) Incorporating $k$NN-MT with adapters yields comparable translation performance to fine-tuning on in-domain test sets, while achieving better performance on out-of-domain test sets; (2) Fine-tuning significantly outperforms $k$NN-MT on the recall of in-domain low-frequency words, but this gap could be bridged by optimizing the context representations with additional adapter layers.Comment: Accepted by EMNLP202

Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models

The demand for psychological counseling has grown significantly in recent years, particularly with the global outbreak of COVID-19, which has heightened the need for timely and professional mental health support. Online psychological counseling has emerged as the predominant mode of providing services in response to this demand. In this study, we propose the Psy-LLM framework, an AI-based system leveraging Large Language Models (LLMs) for question-answering in online psychological consultation. Our framework combines pre-trained LLMs with real-world professional Q&A from psychologists and extensively crawled psychological articles. The Psy-LLM framework serves as a front-end tool for healthcare professionals, allowing them to provide immediate responses and mindfulness activities to alleviate patient stress. Additionally, it functions as a screening tool to identify urgent cases requiring further assistance. We evaluated the framework using intrinsic metrics, such as perplexity, and extrinsic evaluation metrics, with human participant assessments of response helpfulness, fluency, relevance, and logic. The results demonstrate the effectiveness of the Psy-LLM framework in generating coherent and relevant answers to psychological questions. This article concludes by discussing the potential of large language models to enhance mental health support through AI technologies in online psychological consultation

Survival Motor Neuron (SMN) Protein Insufficiency Exacerbates Renal Ischemia/Reperfusion Injury

The survival of motor neuron (SMN) protein is ubiquitously involved in spliceosome assembly and ribonucleoprotein biogenesis. SMN protein is expressed in kidney and can affect cell death processes. However, the role of SMN in acute kidney injury (AKI) is largely unknown. In the current study, we found that the expression of SMN in the kidney was significantly reduced in both clinical ischemic AKI and a mouse model of renal ischemia-reperfusion injury (IRI). We then used SMN heterozygous knockout (SMN+/-) mice and found that the declines in renal function, tubular injury, and tubular cell apoptosis after experimental IRI were significantly more severe in SMN+/− mice than those in their wild-type littermates. Concomitantly, the canonical transcription factor nuclear factor-κb (NFκb) signaling was enhanced in ischemic SMN+/− mice. In vitro, cobalt dichloride (CoCl2) treatment reduced SMN expression in proximal tubular epithelial cells. In addition, CoCl2-induced apoptosis and activation of NFκb signaling pathway were enhanced by transient transfection of a small-interfering RNA (siRNA) against SMN while attenuated by transient transfection of a full-length SMN plasmid. Taken together, this study for the first time supported the protective role of SMN in ischemic AKI

GEP100/Arf6 Is Required for Epidermal Growth Factor-Induced ERK/Rac1 Signaling and Cell Migration in Human Hepatoma HepG2 Cells

BACKGROUND: Epidermal growth factor (EGF) signaling is implicated in the invasion and metastasis of hepatoma cells. However, the signaling pathways for EGF-induced motility of hepatoma cells remain undefined. METHODOLOGY/PRINCIPAL FINDINGS: We found that EGF dose-dependently stimulated the migration of human hepatoma cells HepG2, with the maximal effect at 10 ng/mL. Additionally, EGF increased Arf6 activity, and ectopic expression of Arf6 T27N, a dominant negative Arf6 mutant, largely abolish EGF-induced cell migration. Blocking GEP100 with GEP100 siRNA or GEP100-△PH, a pleckstrin homology (PH) domain deletion mutant of GEP100, blocked EGF-induced Arf6 activity and cell migration. EGF also increased ERK and Rac1 activity. Ectopic expression GEP100 siRNA, GEP100-△PH, or Arf6-T27N suppressed EGF-induced ERK and Rac1 activity. Furthermore, blocking ERK signaling with its inhibitor U0126 remarkably inhibited both EGF-induced Rac1 activation as well as cell migration, and ectopic expression of inactive mutant form of Rac1 (Rac1-T17N) also largely abolished EGF-induced cell migration. CONCLUSIONS/SIGNIFICANCE: Taken together, this study highlights the function of the PH domain of GEP100 and its regulated Arf6/ERK/Rac1 signaling cascade in EGF-induced hepatoma cell migration. These findings could provide a rationale for designing new therapy based on inhibition of hepatoma metastasis

PI3K and ERK-Induced Rac1 Activation Mediates Hypoxia-Induced HIF-1α Expression in MCF-7 Breast Cancer Cells

Hypoxia-inducible factor 1 (HIF-1α) expression induced by hypoxia plays a critical role in promoting tumor angiogenesis and metastasis. However, the molecular mechanisms underlying the induction of HIF-1α in tumor cells remain unknown.In this study, we reported that hypoxia could induce HIF-1α and VEGF expression accompanied by Rac1 activation in MCF-7 breast cancer cells. Blockade of Rac1 activation with ectopic expression of an inactive mutant form of Rac1 (T17N) or Rac1 siRNA downregulated hypoxia-induced HIF-1α and VEGF expression. Furthermore, Hypoxia increased PI3K and ERK signaling activity. Both PI3K inhibitor LY294002 and ERK inhibitor U0126 suppressed hypoxia-induced Rac1 activation as well as HIF-1α expression. Moreover, hypoxia treatment resulted in a remarkable production of reactive oxygen species (ROS). N-acetyl-L-cysteine, a scavenger of ROS, inhibited hypoxia-induced ROS generation, PI3K, ERK and Rac1 activation as well as HIF-1α expression.Taken together, our study demonstrated that hypoxia-induced HIF-1α expression involves a cascade of signaling events including ROS generation, activation of PI3K and ERK signaling, and subsequent activation of Rac1

Dvl2-Dependent Activation of Daam1 and RhoA Regulates Wnt5a-Induced Breast Cancer Cell Migration

The Dishevelled (Dvl) and Dishevelled-associated activator of morphogenesis 1 (Daam1) pathway triggered by Wnt5a regulates cellular polarity during development and tissue homoeostasis. However, Wnt5a signaling in breast cancer progression remains poorly defined.We showed here that Wnt5a activated Dvl2, Daam1 and RhoA, and promoted migration of breast cancer cells, which was, however, abolished by Secreted Frizzled-related protein 2 (sFRP2) pretreatment. Dominant negative Dvl2 mutants or Dvl2 siRNA significantly decreased Wnt5a-induced Daam1/RhoA activation and cell migration. Ectopic expression of N-Daam1, a dominant negative mutant, or Daam1 siRNA remarkably inhibited Wnt5a-induced RhoA activation, stress fiber formation and cell migration. Ectopic expression of dominant negative RhoA (N19) or C3 exoenzyme transferase, a Rho inhibitor, decreased Wnt5a-induced stress fiber formation and cell migration.Taken together, we demonstrated for the first time that Wnt5a promotes breast cancer cell migration via Dvl2/Daam1/RhoA

Lysophosphatidic Acid Induces MDA-MB-231 Breast Cancer Cells Migration through Activation of PI3K/PAK1/ERK Signaling

Enhanced motility of cancer cells is a critical step in promoting tumor metastasis. Lysophosphatidic acid (LPA), representing the major mitogenic activity in serum, stimulates migration in various types of cancer cells. However, the underlying signaling mechanisms for LPA-induced motility of cancer cells remain to be elucidated.In this study, we found that LPA dose-dependently stimulated migration of MDA-MB-231 breast cancer cells, with 10 µM being the most effective. LPA also increased ERK activity and the MEK inhibitor U0126 could block LPA-induced ERK activity and cell migration. In addition, LPA induced PAK1 activation while ERK activation and cell migration were inhibited by ectopic expression of an inactive mutant form of PAK1 in MDA-MB-231 cells. Furthermore, LPA increased PI3K activity, and the PI3K inhibitor LY294002 inhibited both LPA-induced PAK1/ERK activation and cell migration. Moreover, in the breast cancer cell, LPA treatment resulted in remarkable production of reactive oxygen species (ROS), while LPA-induced ROS generation, PI3K/PAK1/ERK activation and cell migration could be inhibited by N-acetyl-L-Cysteine, a scavenger of ROS.Taken together, this study identifies a PI3K/PAK1/ERK signaling pathway for LPA-stimulated breast cancer cell migration. These data also suggest that ROS generation plays an essential role in the activation of LPA-stimulated PI3K/PAK1/ERK signaling and breast cancer cell migration. These findings may provide a basis for designing future therapeutic strategy for blocking breast cancer metastasis

Molecular characterization and clinical relevance of metabolic expression subtypes in human cancers.

Metabolic reprogramming provides critical information for clinical oncology. Using molecular data of 9,125 patient samples from The Cancer Genome Atlas, we identified tumor subtypes in 33 cancer types based on mRNA expression patterns of seven major metabolic processes and assessed their clinical relevance. Our metabolic expression subtypes correlated extensively with clinical outcome: subtypes with upregulated carbohydrate, nucleotide, and vitamin/cofactor metabolism most consistently correlated with worse prognosis, whereas subtypes with upregulated lipid metabolism showed the opposite. Metabolic subtypes correlated with diverse somatic drivers but exhibited effects convergent on cancer hallmark pathways and were modulated by highly recurrent master regulators across cancer types. As a proof-of-concept example, we demonstrated that knockdown of SNAI1 or RUNX1—master regulators of carbohydrate metabolic subtypes-modulates metabolic activity and drug sensitivity. Our study provides a system-level view of metabolic heterogeneity within and across cancer types and identifies pathway cross-talk, suggesting related prognostic, therapeutic, and predictive utility