HECT, UBA and WWE domain containing 1 represses cholesterol efflux during CD4+ T cell activation in Sjögren’s syndrome

Introduction: Sjögren’s syndrome (SS) is a chronic autoimmune disorder characterized by exocrine gland dysfunction, leading to loss of salivary function. Histological analysis of salivary glands from SS patients reveals a high infiltration of immune cells, particularly activated CD4+ T cells. Thus, interventions targeting abnormal activation of CD4+ T cells may provide promising therapeutic strategies for SS. Here, we demonstrate that Hect, uba, and wwe domain containing 1 (HUWE1), a member of the eukaryotic Hect E3 ubiquitin ligase family, plays a critical role in CD4+ T-cell activation and SS pathophysiology.Methods: In the context of HUWE1 inhibition, we investigated the impact of the HUWE1 inhibitor BI8626 and sh-Huwe1 on CD4+ T cells in mice, focusing on the assessment of activation levels, proliferation capacity, and cholesterol abundance. Furthermore, we examined the therapeutic potential of BI8626 in NOD/ShiLtj mice and evaluated its efficacy as a treatment strategy.Results: Inhibition of HUWE1 reduces ABCA1 ubiquitination and promotes cholesterol efflux, decreasing intracellular cholesterol and reducing the expression of phosphorylated ZAP-70, CD25, and other activation markers, culminating in the suppressed proliferation of CD4+ T cells. Moreover, pharmacological inhibition of HUWE1 significantly reduces CD4+ T-cell infiltration in the submandibular glands and improves salivary flow rate in NOD/ShiLtj mice.Conclusion: These findings suggest that HUWE1 may regulate CD4+ T-cell activation and SS development by modulating ABCA1-mediated cholesterol efflux and presents a promising target for SS treatment

Machine Learning Pipelines for Deconvolution of Cellular and Subcellular Heterogeneity from Cell Imaging

Cell-to-cell variations and intracellular processes such as cytoskeletal organization and organelle dynamics exhibit massive heterogeneity. Advances in imaging and optics have enabled researchers to access spatiotemporal information in living cells efficiently. Even though current imaging technologies allow us to acquire an unprecedented amount of cell images, it is challenging to extract valuable information from the massive and complex dataset to interpret heterogeneous biological processes. Machine learning (ML), referring to a set of computational tools to acquire knowledge from data, provides promising solutions to meet this challenge. In this dissertation, we developed ML pipelines for deconvolution of subcellular protrusion heterogeneity from live cell imaging and molecular diagnostic from lens-free digital in-line holography (LDIH) imaging. Cell protrusion is driven by spatiotemporally fluctuating actin assembly processes and is morphodynamically heterogeneous at the subcellular level. Elucidating the underlying molecular dynamics associated with subcellular protrusion heterogeneity is crucial to understanding the biology of cellular movement. Traditional ensemble averaging methods without characterizing the heterogeneity could mask important activities. Therefore, we established an ACF (auto-correlation function) based time series clustering pipeline called HACKS (deconvolution of heterogeneous activities in coordination of cytoskeleton at the subcellular level) to identify distinct subcellular lamellipodial protrusion phenotypes with their underlying actin regulator dynamics from live cell imaging. Using our method, we discover “accelerating protrusion”, which is driven by the temporally ordered coordination of Arp2/3 and VASP activities. Furthermore, deriving the merits of ML, especially Deep Learning (DL) to learn features automatically, we advanced our pipeline to learn fine-grained temporal features by integrating the prior ML analysis results with bi-LSTM (bi-direction long-short term memory) autoencoders to dissect variable-length time series protrusion heterogeneity. By applying it to subcellular protrusion dynamics in pharmacologically and metabolically perturbed epithelial cells, we discovered fine differential response of protrusion dynamics specific to each perturbation. This provides an analytical framework for detailed and quantitative understanding of molecular mechanisms hidden in their heterogeneity. Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microscopy. Numerical reconstruction for hologram images from large-field-of-view LDIH is extremely time-consuming. Until now, there are no effective manual-design features to interpret the lateral and depth information from complex diffraction patterns in hologram images directly, which limits LDIH utility for point-of-care applications. Inherited from advantages of DL to learn generalized features automatically, we proposed a deep transfer learning (DTL)-based approach to process LDIH images without reconstruction in the context of cellular analysis. Specifically, using the raw holograms as input, the features extracted from a well-trained network were able to classify cell categories according to the number of cell-bounded microbeads, which performance was comparable with that of object images as input. Combined with the developed DTL approach, LDIH could be realized as a low-cost, portable tool for point-of-care diagnostics. In summary, this dissertation demonstrate that ML applied to cell imaging can successfully dissect subcellular heterogeneity and perform cell-based diagnosis. We expect that our study will be able to make significant contributions to data-driven cell biological research

A "capacitor" bridge builder based safe path planner for difficult regions identification in changing environments

Finding paths in difficult regions of C-space, such as narrow passages and configuration obstacle boundaries, is a rather challenging problem for path planning in changing environments. When obstacles move in W-space, these regions in C-space will change their edge points from free to collision or on the contrary, for which a "Capacitor" Bridge Builder (CBB) is proposed in this paper to identify their changing characteristics. Specifically, a "Capacitor" bridge is built between positive and negative toggled points in C-Space, which looks like capacitors stuck between narrow passages or boundary regions. Through CBB, the back boundary of an obstacle, which is less likely to be occupied immediately, is marked as a temporary safe region. Furthermore, a Half Bridge Strategy (HBS) is novelly proposed to boost samples inside these regions. Eventually, highly safe paths are revealed by predicting moving directions of obstacles, then replanning times and total planning times will be decreased significantly. Effectiveness of the proposed method has been verified by experiments with two manipulators in difficult changing environments.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000317042703118&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Automation & Control SystemsComputer Science, Artificial IntelligenceRoboticsEICPCI-S(ISTP)

Ethylene Signal Is Involved in the Regulation of Anthocyanin Accumulation in Flesh of Postharvest Plums (<i>Prunus salicina</i> Lindl.)

Ethylene is positively correlated with the anthocyanin accumulation in postharvest plum fruit, but the regulation mechanism has not been fully clarified. In this work, the ‘Friar’ plum fruit under different storage temperatures (0, 10 and 25 °C) and treatments (100.0 μL L−1 ethylene and 1.0 μL L−1 1-MCP) were applied to study the relationship between anthocyanin accumulation and ethylene signal pathway. The fruits stored at 10 °C had higher ethylene production rate and more anthocyanin in flesh than those stored at 0 °C and 25 °C. Ten ethylene biosynthesis associated genes and forty-one ethylene signal transduction related genes were obtained from the previous transcriptome data. Among them, the expression levels of ethylene biosynthesis associated genes (PsACS1, PsACS4 and PsACO1), and ethylene signal transduction related genes (PsERS1s, PsETR2, PsERF1a, and PsERF12) were markedly higher in the fruits stored at 10 °C than those at 0 °C and 25 °C. Exogenous ethylene treatment enhanced while 1-MCP treatment inhibited the anthocyanin accumulation in the flesh under storage at 10 °C. In addition, exogenous ethylene treatment markedly increased the expression levels of PsACS1, PsACS4, PsACO1, PsETR2, PsERF1a, and PsERF12 in the flesh once it turning red, as well as the anthocyanin biosynthesis related genes (PsPAL, PsCHS, PsF3H, PsDRF, PsANS, PsUFGT and PsMYB10), whereas 1-MCP treatment manifested the contrary effects. Correlation analysis indicated that there was a significant positive correlation between genes expression related to ethylene signal pathway and anthocyanin biosynthesis, except for PsERF11. In conclusion, ethylene signal pathway is involved in the flesh reddening by up-regulating the anthocyanin biosynthesis related genes

The Prognostic Value of Lymph Nodes Dissection Number on Survival of Patients with Lymph Node-Negative Gastric Cancer

Objective. The study was designed to explore the prognostic value of examined lymph node (LN) number on survival of gastric cancer patients without LN metastasis. Methods. Between August 1995 and January 2011, 300 patients who underwent gastrectomy with D2 lymphadenectomy for LN-negative gastric cancer were reviewed. Patients were assigned to various groups according to LN dissection number or tumor invasion depth. Some clinical outcomes, such as overall survival, operation time, length of stay, and postoperative complications, were compared among all groups. Results. The overall survival time of LN-negative GC patients was 50.2±30.5 months. Multivariate analysis indicated that LN dissection number (P<0.001) and tumor invasion depth (P<0.001) were independent prognostic factors of survival. The number of examined LNs was positively correlated with survival time (P<0.05) in patients with same tumor invasion depth but not correlated with T1 stage or examined LNs >30. Besides, it was not correlated with operation time, transfusion volume, length of postoperative stay, or postoperative complication incidence (P>0.05). Conclusions. The number of examined lymph nodes is an independent prognostic factor of survival for patients with lymph node-negative gastric cancer. Sufficient dissection of lymph nodes is recommended during surgery for such population

Deconvolution of subcellular protrusion heterogeneity and the underlying actin regulator dynamics from live cell imaging

Cell protrusion dynamics are heterogeneous at the subcellular level, but current analyses operate at the cellular or ensemble level. Here the authors develop a computational framework to quantify subcellular protrusion phenotypes and reveal the underlying actin regulator dynamics at the leading edge

Computational Interspecies Translation Between Alzheimer’s Disease Mouse Models and Human Subjects Identifies Innate Immune Complement, TYROBP, and TAM Receptor Agonist Signatures, Distinct From Influences of Aging

Mouse models are vital for preclinical research on Alzheimer’s disease (AD) pathobiology. Many traditional models are driven by autosomal dominant mutations identified from early onset AD genetics whereas late onset and sporadic forms of the disease are predominant among human patients. Alongside ongoing experimental efforts to improve fidelity of mouse model representation of late onset AD, a computational framework termed Translatable Components Regression (TransComp-R) offers a complementary approach to leverage human and mouse datasets concurrently to enhance translation capabilities. We employ TransComp-R to integratively analyze transcriptomic data from human postmortem and traditional amyloid mouse model hippocampi to identify pathway-level signatures present in human patient samples yet predictive of mouse model disease status. This method allows concomitant evaluation of datasets across different species beyond observational seeking of direct commonalities between the species. Additional linear modeling focuses on decoupling disease signatures from effects of aging. Our results elucidated mouse-to-human translatable signatures associated with disease: excitatory synapses, inflammatory cytokine signaling, and complement cascade- and TYROBP-based innate immune activity; these signatures all find validation in previous literature. Additionally, we identified agonists of the Tyro3 / Axl / MerTK (TAM) receptor family as significant contributors to the cross-species innate immune signature; the mechanistic roles of the TAM receptor family in AD merit further dedicated study. We have demonstrated that TransComp-R can enhance translational understanding of relationships between AD mouse model data and human data, thus aiding generation of biological hypotheses concerning AD progression and holding promise for improved preclinical evaluation of therapies.</jats:p