Global existence of weak solutions of the nematic liquid crystal flow in dimensions three

For any bounded smooth domain $\Omega\subset\mathbb R^3$, we establish the global existence of a weak solution $u:\Omega\times (0,+\infty)\to\mathbb R^3\times\mathbb S^2$ of the initial-boundary value (or the Cauchy) problem of the simplified Ericksen-Leslie system (1.1) modeling the hydrodynamic flow of nematic liquid crystals for any initial and boundary (or Cauchy) data $(u_0. d_0)\in {\bf H}\times H^1(\Omega,\mathbb S^2$), with $d_0(\Omega)\subset\mathbb S^2_+$ (the upper hemisphere). Furthermore, ($u,d$) satisfies the global energy inequality (1.4).Comment: 24 page

Interaction Between Cytolethal Distending Toxin Produced By Campylobacter Jejuni And Helicobacter Hepaticus And Host Innate Immune Defense

Cytolethal distending toxin (CDT) of C. jejuni, a leading cause of intestinal illness worldwide, and H. hepaticus, a laboratory mice pathogen causes cell cycle arrest and induces apoptosis in eukaryotic cells. In the present studies, the interactions of CDT with host innate defense mechanisms were investigated within the context of intestinal infection. The acute stage of intestinal infection by C. jejuni is characterized by massive transepithelial migration of activated PMNs into the intestinal lumen. Recently, neutrophil extracellular traps (NETs) have emerged as an important innate host defense mechanism against bacterial pathogens. We hypothesize that CDT nuclease mediates resistance against extracellular killing in NETs. First, NETs were discovered to capture C. jejuni in non-human primates with acute campylobacteriosis. The lack of direct induction of NETs formation in vitro by C. jejuni indicates NETs formation in C. jejuni infection might be indirectly mediated by components present within the intestinal microenvironment. Although C. jejuni were efficiently captured within NETs, they themselves did not induce NET fromation. However, once captured, C. jejuni survived within NETs, and CDT did not play a role in escape of C. jejuni from NETs. Taken together, the data suggest that within the context of the intestinal tract, NETs likely provide innate defense by a mechanism of bacterial exclusion and disposal by intestinal peristalsis. Given that CDT-induced intoxication of epithelial cells leads to a DDR, we hypothesized that CDT-intoxicated intestinal epithelial cells display a senescenceassociated secretory phenotype (SASP). Following treatment of human intestinal epithelial cells with sub-lethal doses of CDT from either C. jejuni or H. hepaticus or C. jejuni whole cell lysates, we observed persistent DDR including cell growth arrest and upregulation of [gamma]-H2AX, accumulation of intracytoplasmic beta-galactosidase, and expression of pro-inflammatory cytokines IL-6 and IL-24 and CXCL-8 chemokine characteristic of SASP. In sum, the data reveal that activation of senescence pathways is a novel and potentially important downstream mechanism of CDT-induced genotoxicity that might contribute to host innate defense during intestinal infection by bacterial pathogens

Prompt Tuning based Adapter for Vision-Language Model Adaption

Large pre-trained vision-language (VL) models have shown significant promise in adapting to various downstream tasks. However, fine-tuning the entire network is challenging due to the massive number of model parameters. To address this issue, efficient adaptation methods such as prompt tuning have been proposed. We explore the idea of prompt tuning with multi-task pre-trained initialization and find it can significantly improve model performance. Based on our findings, we introduce a new model, termed Prompt-Adapter, that combines pre-trained prompt tunning with an efficient adaptation network. Our approach beat the state-of-the-art methods in few-shot image classification on the public 11 datasets, especially in settings with limited data instances such as 1 shot, 2 shots, 4 shots, and 8 shots images. Our proposed method demonstrates the promise of combining prompt tuning and parameter-efficient networks for efficient vision-language model adaptation. The code is publicly available at: https://github.com/Jingchensun/prompt_adapter