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Tubulin post-translational modifications (PTMs) occur spatiotemporally throughout cells and are suggested to be involved in a wide range of cellular activities. However, the complexity and dynamic distribution of tubulin PTMs within cells have hindered the understanding of their physiological roles in specific subcellular compartments. Here, we develop a method to rapidly deplete tubulin glutamylation inside the primary cilia, a microtubule-based sensory organelle protruding on the cell surface, by targeting an engineered deglutamylase to the cilia in minutes. This rapid deglutamylation quickly leads to altered ciliary functions such as kinesin-2-mediated anterograde intraflagellar transport and Hedgehog signaling, along with no apparent crosstalk to other PTMs such as acetylation and detyrosination. Our study offers a feasible approach to spatiotemporally manipulate tubulin PTMs in living cells. Future expansion of the repertoire of actuators that regulate PTMs may facilitate a comprehensive understanding of how diverse tubulin PTMs encode ciliary as well as cellular functions. Tubulin post-translational modifications (PTMs) occur spatiotemporally throughout cells, therefore assessing the physiological roles in specific subcellular compartments has been challenging. Here the authors develop a method to rapidly deplete tubulin glutamylation inside the primary cilia by targeting an engineered deglutamylase to the axoneme.

PurposeIn the face of a changing and turbulent environment, an organizational learning culture (OLC) is crucial for the long-term operation of an organization. A learning culture provides the capacity to effectively integrate employees, and it also provides structure so that an organization can move forward via continuous learning and change. Few empirical results are available from Chinese companies enduring an organizational change. To bridge this research gap, this study investigated the relationships among an OLC, job satisfaction, turnover intentions and job performance during organizational change.Design/methodology/approachA quantitative approach with structural equation modeling (SEM) and bootstrapping estimation was used to test hypotheses developed from a sample of 434 employees in a restructured telecommunications company in Taiwan.FindingsEmployees who experienced a higher learning culture had lower levels of turnover intentions and exhibited better job performance. Job satisfaction had a negative impact on employee turnover intentions but a positive impact on job performance. Moreover, job satisfaction fully mediated the relationships between an OLC and employee turnover intentions and job performance. When encountering organizational planned changes, a vibrant learning culture gave employees a higher level of satisfaction in their jobs and workplace. Although unexpected challenges often appeared during the organizational changes, employees with a higher level of job satisfaction tended to fulfill their own job duties and showed fewer turnover intentions.Originality/valueIn investigating issues related to organizational change, this study provides managerial insights and addresses strategies for facilitating the adoption of an OLC into the design and implementation of a better workplace environment.

The interannual variability of the annual maximum ice cover (AMIC) of the Great Lakes is strongly influenced by large-scale atmospheric circulations that drive regional weather patterns. Based on statistical analyses from 1980 to 2020, we identify a reduced number of accumulated freezing degree days across the winter months in recent decades, a step-change decrease of AMIC after the winter of 1997/98, and an increased interannual variability of AMIC since 1993. Our analysis shows that AMIC is significantly correlated with El Ni˜no–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific–North American pattern (PNA) before the winter of 1997/98. After that, the AMIC is significantly correlated with the tropical–Northern Hemisphere pattern (TNH) and eastern Pacific oscillation (EPO). Singular value decomposition of the 500-hPa geopotential height and surface air temperature shows a dipole pattern over the northeast Pacific and North America, demonstrating the ridge–trough system. This dipole pattern shifts northward to the northern Rocky Mountains, placing the Great Lakes region in the trough after 1997/98. This shift coincides with the increased interannual variability of the EPO index, as well as the change in the sea surface temperature (SST) over the northeast Pacific, where the second mode of the empirical orthogonal function (EOF) on SST shows a warm blob-like feature manifested over the Gulf of Alaska. The regression of wave activity flux onto the SST EOF shows that the source of upward and eastward propagation of a stationary Rossby wave shifts to the west coast ofNorthAmerica, likely moving the ridge–trough system eastward after the winter of 1997/98.

ObjectiveTo develop and evaluate the performance of U-Net for fully automated localization and segmentation of cervical tumors in magnetic resonance (MR) images and the robustness of extracting apparent diffusion coefficient (ADC) radiomics features.MethodsThis retrospective study involved analysis of MR images from 169 patients with cervical cancer stage IB–IVA captured; among them, diffusion-weighted (DW) images from 144 patients were used for training, and another 25 patients were recruited for testing. A U-Net convolutional network was developed to perform automated tumor segmentation. The manually delineated tumor region was used as the ground truth for comparison. Segmentation performance was assessed for various combinations of input sources for training. ADC radiomics were extracted and assessed using Pearson correlation. The reproducibility of the training was also assessed.ResultsCombining b0, b1000, and ADC images as a triple-channel input exhibited the highest learning efficacy in the training phase and had the highest accuracy in the testing dataset, with a dice coefficient of 0.82, sensitivity 0.89, and a positive predicted value 0.92. The first-order ADC radiomics parameters were significantly correlated between the manually contoured and fully automated segmentation methods (p < 0.05). Reproducibility between the first and second training iterations was high for the first-order radiomics parameters (intraclass correlation coefficient = 0.70–0.99).ConclusionU-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images. First-order radiomics features extracted from whole tumor volume demonstrate the potential robustness for longitudinal monitoring of tumor responses in broad clinical settings.SummaryU-Net-based deep learning can perform accurate localization and segmentation of cervical cancer in DW MR images.Key Points• U-Net-based deep learning can perform accurate fully automated localization and segmentation of cervical cancer in diffusion-weighted MR images.• Combining b0, b1000, and apparent diffusion coefficient (ADC) images exhibited the highest accuracy in fully automated localization.• First-order radiomics feature extraction from whole tumor volume was robust and could thus potentially be used for longitudinal monitoring of treatment responses.

Metasurfaces have exhibited exceptional proficiency in precisely modulating light properties within narrow wavelength spectra. However, there is a growing demand for multi-resonant metasurfaces capable of wavefront engineering across broad spectral ranges. In this study, we introduce a microcavity-assisted multi-resonant metasurface platform that integrates subwavelength meta-atoms with a specially designed distributed Bragg reflector (DBR) substrate. This platform enables the simultaneous excitation of various resonant modes within the metasurface, resulting in multiple high- Q resonances spanning from the visible to the near-infrared (NIR) regions. The developed metasurface generates up to 15 high- Q resonant peaks across the visible-NIR spectrum, achieving a maximum efficiency of 81% (70.7%) in simulation (experiment) with an average efficiency of 76.6% (54.5%) and a standard deviation of 4.1% (11.1%). Additionally, we demonstrate the versatility of the multi-resonant metasurface in amplitude, phase, and wavefront modulations at peak wavelengths. By integrating structural color printing and vectorial holographic imaging, our proposed metasurface platform shows potential for applications in optical displays and encryption. This work paves the way for the development of next-generation multi-resonant metasurfaces with broad-ranging applications in photonics and beyond. Previous multi-wavelength metasurfaces are restricted to a few wavelengths or lack wavefront control ability. Here, the authors introduce a microcavity-assisted metasurface that achieves multi-resonant wavefront engineering at 15 high-Q peak wavelengths from 480 nm to 1000 nm.

Aflatoxin B1 (AFB1), a food contaminant derived from Aspergillus fungi, has been reported to cause hepatic immunotoxicity via inflammatory infiltration and cytokines release. As a pro-inflammatory factor, cyclooxygenase-2 (COX-2) is widely involved in liver inflammation induced by xenobiotics. However, the mechanism by which AFB1-induced COX-2 regulates liver inflammatory injury via hepatocytes-Kupffer cells (KCs) crosstalk remains unclear and requires further elucidation. Here, we established a COX-2 upregulated model with AFB1 treatment in vivo (C57BL/6 mice, 1 mg/kg body weight, i.g, 4 weeks) and in vitro (human liver HepaRG cells, 1 μM for 24 h). In vivo, AFB1-treated mice exhibited NLRP3 inflammasome activation, inflammatory infiltration, and increased recruitment of KCs. In vitro, dephosphorylated COX-2 by protein phosphatase 2A (PP2A)-B55δ promoted NLRP3 inflammasome activation, including mitochondrial translocation of NLRP3, caspase 1 cleavage, and IL-1β release. Moreover, phosphorylated COX-2 at serine 601 (p-COX-2Ser601) underwent endoplasmic reticulum (ER) retention for proteasome degradation. Furthermore, pyroptosis and inflammatory response induced by AFB1 were relieved with COX-2 genetic (siPTGS2) intervention or pharmaceutic (celecoxib, 30 mg/kg body weight, i.g, 4 weeks) inhibition of COX-2 via NLRP3 inflammasome suppression in vivo and in vitro. Ex vivo, in a co-culture system with murine primary hepatocytes and KCs, activated KCs induced by damaged signals from pyroptotic hepatocytes, formed a feedback loop to amplify NLRP3-dependent pyroptosis of hepatocytes via pro-inflammatory signaling, leading to liver inflammatory injury. Taken together, our data suggest a novel mechanism that protein quality control of COX-2 determines the intracellular distribution and activation of NLRP3 inflammasome, which promotes liver inflammatory injury via hepatocytes-KCs crosstalk.

Autophagy, a crucial process in cancer, is closely intertwined with both tumor progression and drug resistance development. However, existing methods used to assess autophagy activity often pose invasiveness and time-related constraints, limiting their applicability in preclinical drug investigations. In this study, we developed a non-invasive autophagy detection system (NIADS-autophagy, also called G-cleave LC3B biosensor) by integrating a split-luciferase-based biosensor with an LC3B cleavage sequence, which swiftly identified classic autophagic triggers, such as Earle's Balanced Salt Solution and serum deprivation, through protease-mediated degradation pathways. The specificity of G-cleave LC3B biosensor was confirmed via CRISPR gene editing of pivotal autophagy regulator ATG4B, yielding diminished luciferase activity in MDA-MB-231 breast cancer cells. Notably, the G-cleave LC3B biosensor exhibited strong concordance with established autophagy metrics, encompassing LC3B lipidation, SQSTM1 degradation, and puncta accumulation analysis. To underscore the usage potential of the G-cleave LC3B biosensor, we discovered that resveratrol acts as a synergistic enhancer by significantly potentiating apoptosis in MDA-MB-231 cells when combined with doxorubicin treatment. Overall, the luminescence-based G-cleave LC3B biosensor presents a rapid and dependable avenue for determining autophagy activity, thereby facilitating high-throughput assessment of promising autophagy-associated anti-cancer therapies across diverse malignancies.

Alterations in membrane proteins (MPs) and their regulated pathways have been established as cancer hallmarks and extensively targeted in clinical applications. However, the analysis of MP-interacting proteins and downstream pathways across human malignancies remains challenging. Here, we present a systematically integrated method to generate a resource of cancer membrane protein-regulated networks (CaMPNets), containing 63,746 high-confidence protein–protein interactions (PPIs) for 1962 MPs, using expression profiles from 5922 tumors with overall survival outcomes across 15 human cancers. Comprehensive analysis of CaMPNets links MP partner communities and regulated pathways to provide MP-based gene sets for identifying prognostic biomarkers and druggable targets. For example, we identify CHRNA9 with 12 PPIs (e.g., ERBB2) can be a therapeutic target and find its anti-metastasis agent, bupropion, for treatment in nicotine-induced breast cancer. This resource is a study to systematically integrate MP interactions, genomics, and clinical outcomes for helping illuminate cancer-wide atlas and prognostic landscapes in tumor homo/heterogeneity. Membrane proteins have been implicated in cancers, but studying the downstream effects of their perturbation remains challenging. Here, the authors map the membrane protein-regulated network of 15 cancers, a resource for prognostic biomarker development and druggable target identification.

As a type of immunogenic cell death, ferroptosis participates in the creation of immunoactive tumor microenvironments. However, knowledge of spatial location of tumor cells with ferroptosis signature in tumor environments and the role of ferroptotic stress in inducing the expression of immune‐related molecules in cancer cells is limited. Here the spatial association of the transcriptomic signatures is demonstrated for ferroptosis and inflammation/immune activation located in the invasive front of head and neck squamous cell carcinoma (HNSCC). The association between ferroptosis signature and inflammation/immune activation is more prominent in HPV‐negative HNSCC compared to HPV‐positive ones. Ferroptotic stress induces PD‐L1 expression through reactive oxygen species (ROS)‐elicited NF‐κB signaling pathway and calcium influx. Priming murine HNSCC with the ferroptosis inducer sensitizes tumors to anti‐PD‐L1 antibody treatment. A positive correlation between the ferroptosis signature and the active immune cell profile is shown in the HNSCC samples. This study reveals a subgroup of ferroptotic HNSCC with immune‐active signatures and indicates the potential of priming HNSCC with ferroptosis inducers to increase the antitumor efficacy of immune checkpoint inhibitors. Ferroptosis stress elicits PD‐L1 expression in head and neck cancer cells and modulates tumor microenvironments to an immune‐active state, highlighting the potential of priming tumors with ferroptosis inducers to potentiate the antitumor efficacy of immunotherapy.

Herpes simplex virus （HSV）, a member of the Herpesviridae family, is a significant human pathogen that results in mucocutaneous lesions in the oral cavity or genital infections. Acyclovir （ACV） and related nucleoside analogues can successfully treat HSV infections, but the emergence of drug resistance to ACV has created a barrier for the treatment of HSV infections, especially in immunocompromised patients. There is an urgent need to explore new and effective tactics to circumvent drug resistance to HSV. This review summarises the current strategies in the development of new targets （the DNA helicase/primase （H/P） complex）, new types of molecules （nature products） and new antiviral mechanisms （lethal mutagenesis of Janus-type nucleosides） to fight the drug resistance of HSV.