Foot-and-mouth disease virus (FMDV) negatively regulates ZFP36 protein expression to alleviate its antiviral activity.

Zinc finger protein 36 (ZFP36) is a key regulator of inflammatory and cytokine production. However, the interplay between swine zinc-finger protein 36 (sZFP36) and foot-and-mouth disease virus (FMDV) has not yet been reported. Here, we demonstrate that overexpression of sZFP36 restricted FMDV replication, while the knockdown of sZFP36 facilitated FMDV replication. To subvert the antagonism of sZFP36, FMDV decreased sZFP36 protein expression through its non-structural protein 3C protease (3Cpro). Our results also suggested that 3Cpro-mediated sZFP36 degradation was dependent on its protease activity. Further investigation revealed that both N-terminal and C-terminal-sZFP36 could be degraded by FMDV and FMDV 3Cpro. In addition, both N-terminal and C-terminal-sZFP36 decreased FMDV replication. Moreover, sZFP36 promotes the degradation of FMDV structural proteins VP3 and VP4 via the CCCH-type zinc finger and NES domains of sZFP36. Together, our results confirm that sZFP36 is a host restriction factor that negatively regulates FMDV replication.IMPORTANCEFoot-and-mouth disease (FMD) is an infectious disease of animals caused by the pathogen foot-and-mouth disease virus (FMDV). FMD is difficult to prevent and control because there is no cross-protection between its serotypes. Thus, we designed this study to investigate virus-host interactions. We first demonstrate that swine zinc-finger protein 36 (sZFP36) impaired FMDV structural proteins VP3 and VP4 to suppress viral replication. To subvert the antagonism of sZFP36, FMDV and FMDV 3Cpro downregulate sZFP36 expression to facilitate FMDV replication. Taken together, the present study reveals a previously unrecognized antiviral mechanism for ZFP36 and elucidates the role of FMDV in counteracting host antiviral activity.

Targeting CCL2-CCR2 signaling pathway alleviates macrophage dysfunction in COPD via PI3K-AKT axis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a leading cause of morbidity and mortality worldwide, characterized by persistent respiratory symptoms and airflow limitation. The involvement of C-C motif chemokine ligand 2 (CCL2) in COPD pathogenesis, particularly in macrophage regulation and activation, is poorly understood despite its recognized role in chronic inflammation. Our study aims to elucidate the regulatory role and molecular mechanisms of CCL2 in the pathogenesis of COPD, providing new insights for therapeutic strategies. METHODS: This study focused on the CCL2-CCR2 signaling pathway, exploring its role in COPD pathogenesis using both Ccl2 knockout (KO) mice and pharmacological inhibitors. To dissect the underlying mechanisms, we employed various in vitro and in vivo methods to analyze the secretion patterns and pathogenic effects of CCL2 and its downstream molecular signaling through the CCL2-CCR2 axis. RESULTS: Elevated Ccl2 expression was confirmed in the lungs of COPD mice and was associated with enhanced recruitment and activation of macrophages. Deletion of Ccl2 in knockout mice, as well as treatment with a Ccr2 inhibitor, resulted in protection against CS- and LPS-induced alveolar injury and airway remodeling. Mechanistically, CCL2 was predominantly secreted by bronchial epithelial cells in a process dependent on STAT1 phosphorylation and acted through the CCR2 receptor on macrophages. This interaction activated the PI3K-AKT signaling pathway, which was pivotal for macrophage activation and the secretion of inflammatory cytokines, further influencing the progression of COPD. CONCLUSIONS: The study highlighted the crucial role of CCL2 in mediating inflammatory responses and remodeling in COPD. It enhanced our understanding of COPD's molecular mechanisms, particularly how CCL2's interaction with the CCR2 activates critical signaling pathways. Targeting the CCL2-CCR2 axis emerged as a promising strategy to alleviate COPD pathology.

An emerging antibacterial nanovaccine for enhanced chemotherapy by selectively eliminating tumor-colonizing bacteria.

Fusobacterium nucleatum (F. nucleatum), an oral anaerobe, is prevalent in colorectal cancer and is closely related to increased cancer cell growth, metastasis, and poor treatment outcomes. Bacterial vaccines capable of selectively eliminating bacteria present a promising approach to targeting intratumor F. nucleatum, thereby enhancing cancer treatment. Although adjuvants have been employed to enhance the immune response, the vaccine's effectiveness is constrained by inadequate T-cell activation necessary for eradicating intracellular pathogens. In this study, we developed a minimalistic, biomimetic nanovaccine by integrating highly immunostimulatory adjuvant cholesterol-modified CpG oligonucleotides into the autologously derived F. nucleatum membranes. Compared to the traditional vaccines consisting of inactivated bacteria and Alum adjuvant, the nanovaccine coupled with bacterial membranes and adjuvants could remarkably improve multiple antigens and adjuvant co-delivery to dendritic cells, maximizing their ability to achieve effective antigen presentation and strong downstream immune progress. Notably, the nanovaccine exhibits outstanding selective prophylactic and therapeutic effects, eliminating F. nucleatum without affecting intratumoral and gut microbiota. It significantly enhances chemotherapy efficacy and reduces cancer metastasis in F. nucleatum-infected colorectal cancer. Overall, this work represents the rational application of bacterial nanovaccine and provides a blueprint for future development in enhancing the antitumor effect against bacterial-infected cancer.

Exosomal miR-1202 mediates Brodmann Area 44 functional connectivity changes in medication-free patients with major depressive disorder: An fMRI study.

Previous large-sample postmortem study revealed that the expression of miR-1202 in brain tissues from Brodmann area 44 (BA44) was dysregulated in patients with major depressive disorder (MDDs). However, the specific in vivo neuropathological mechanism of miR-1202 as well as its interplay with BA44 circuits in the depressed brain are still unclear. Here, we performed a case-control study with imaging-genetic approach based on resting-state functional magnetic resonance imaging (MRI) data and miR-1202 quantification from 110 medication-free MDDs and 102 healthy controls. Serum-derived circulating exosomes that readily cross the blood-brain barrier were isolated to quantify miR-1202. For validation, repeated MR scans were performed after a six-week follow-up of antidepressant treatment on a cohort of MDDs. Voxelwise factorial analysis revealed two brain areas (including the striatal-thalamic region) in which the effect of depression on the functional connectivity with BA44 was significantly dependent on the expression level of exosomal miR-1202. Moreover, longitudinal change of the BA44 connectivity with the striatal-thalamic region in MDDs after antidepressant treatment was found to be significantly related to the level of miR-1202 expression. These findings revealed that the in vivo neuropathological effect of miR-1202 dysregulation in depression is possibly exerted by mediating neural functional abnormalities in BA44-striatal-thalamic circuits.

MKG-GC: A multi-task learning-based knowledge graph construction framework with personalized application to gastric cancer.

Over the past decade, information for precision disease medicine has accumulated in the form of textual data. To effectively utilize this expanding medical text, we proposed a multi-task learning-based framework based on hard parameter sharing for knowledge graph construction (MKG), and then used it to automatically extract gastric cancer (GC)-related biomedical knowledge from the literature and identify GC drug candidates. In MKG, we designed three separate modules, MT-BGIPN, MT-SGTF and MT-ScBERT, for entity recognition, entity normalization, and relation classification, respectively. To address the challenges posed by the long and irregular naming of medical entities, the MT-BGIPN utilized bidirectional gated recurrent unit and interactive pointer network techniques, significantly improving entity recognition accuracy to an average F1 value of 84.5% across datasets. In MT-SGTF, we employed the term frequency-inverse document frequency and the gated attention unit. These combine both semantic and characteristic features of entities, resulting in an average Hits@ 1 score of 94.5% across five datasets. The MT-ScBERT integrated cross-text, entity, and context features, yielding an average F1 value of 86.9% across 11 relation classification datasets. Based on the MKG, we then developed a specific knowledge graph for GC (MKG-GC), which encompasses a total of 9129 entities and 88,482 triplets. Lastly, the MKG-GC was used to predict potential GC drugs using a pre-trained language model called BioKGE-BERT and a drug-disease discriminant model based on CNN-BiLSTM. Remarkably, nine out of the top ten predicted drugs have been previously reported as effective for gastric cancer treatment. Finally, an online platform was created for exploration and visualization of MKG-GC at https://www.yanglab-mi.org.cn/MKG-GC/.

A gene signature linked to fibroblast differentiation for prognostic prediction of mesothelioma.

BACKGROUND: Malignant mesothelioma is a type of infrequent tumor that is substantially related to asbestos exposure and has a terrible prognosis. We tried to produce a fibroblast differentiation-related gene set for creating a novel classification and prognostic prediction model of MESO. METHOD: Three databases, including NCBI-GEO, TCGA, and MET-500, separately provide single-cell RNA sequencing data, bulk RNA sequencing profiles of MESO, and RNA sequencing information on bone metastatic tumors. Dimensionality reduction and clustering analysis were leveraged to acquire fibroblast subtypes in the MESO microenvironment. The fibroblast differentiation-related genes (FDGs), which were associated with survival and subsequently utilized to generate the MESO categorization and prognostic prediction model, were selected in combination with pseudotime analysis and survival information from the TCGA database. Then, regulatory network was constructed for each MESO subtype, and candidate inhibitors were predicted. Clinical specimens were collected for further validation. RESULT: A total of six fibroblast subtypes, three differentiation states, and 39 FDGs were identified. Based on the expression level of FDGs, three MESO subtypes were distinguished in the fibroblast differentiation-based classification (FDBC). In the multivariate prognostic prediction model, the risk score that was dependent on the expression level of several important FDGs, was verified to be an independently effective prognostic factor and worked well in internal cohorts. Finally, we predicted 24 potential drugs for the treatment of MESO. Moreover, immunohistochemical staining and statistical analysis provided further validation. CONCLUSION: Fibroblast differentiation-related genes (FDGs), especially those in low-differentiation states, might participate in the proliferation and invasion of MESO. Hopefully, the raised clinical subtyping of MESO would provide references for clinical practitioners.

Named entity recognition in aerospace based on multi-feature fusion transformer.

In recent years, along with the rapid development in the domain of artificial intelligence and aerospace, aerospace combined with artificial intelligence is the future trend. As an important basic tool for Natural Language Processing, Named Entity Recognition technology can help obtain key relevant knowledge from a large number of aerospace data. In this paper, we produced an aerospace domain entity recognition dataset containing 30 k sentences in Chinese and developed a named entity recognition model that is Multi-Feature Fusion Transformer (MFT), which combines features such as words and radicals to enhance the semantic information of the sentences. In our model, the double Feed-forward Neural Network is exploited as well to ensure MFT better performance. We use our aerospace dataset to train MFT. The experimental results show that MFT has great entity recognition performance, and the F1 score on aerospace dataset is 86.10%.

Catalytic PMS oxidation universality of CuFe2O4/MnO2 heterojunctions at multiple application scenarios.

The magnetic CuFe2O4/MnO2 heterojunctions were prepared by hydrothermal method, and the effect of different reaction temperature on the physicochemical properties and catalytic activity was investigated. The CuFe2O4/MnO2 heterojunctions prepared at 100 °C can effectively activate peroxymonosulfate (PMS) at multiple application scenarios for degradation and mineralization of tetracycline, o-nitrophenol and ceftriaxone sodium under indoor light, visible light and dark condition. Additionally, the CuFe2O4/MnO2-PMS system showed high catalytic activity and anti-interference ability for degradation of pharmaceutical pollutants in natural water bodies and industrial wastewater. The TC removal efficiency in Qianhu Lake water, Ganjiang River water and tap water was about 88%, 92% and 89%, respectively. The CuFe2O4/MnO2-PMS system is also effective for actual pharmaceutical wastewater treatment with 77.9% of COD removal efficiency. Interestingly, the reactive species of CuFe2O4/MnO2-PMS system under visible light are different from those in dark condition, and the different catalytic mechanisms at multiple application scenarios were proposed. This work provides new insights into mechanism exploration of heterojunction catalyst for PMS activation.

Antibacterial Fusobacterium nucleatum-Mimicking Nanomedicine to Selectively Eliminate Tumor-Colonized Bacteria and Enhance Immunotherapy Against Colorectal Cancer.

Clinical evidence indicates that tumor-colonizing bacteria can be closely related to the tumor development and therapeutic responses. Selectively eliminating bacteria within tumors may be an attractive approach to enhance cancer treatment without additional side effects. Herein, it is found that, owing to the high affinity between the membrane protein Fap-2 on Fusobacterium nucleatum and d-galactose-ß (1-3)-N-acetyl-d-galactosamine (Gal-GalNAc) overexpressed on colorectal tumor cells, F. nucleatum can colonize in colorectal tumors, as evidenced by both clinical samples and animal tumor models. Notably, F. nucleatum colonized in colorectal tumors can lead to an immunosuppressive tumor microenvironment, greatly reducing their responses to immune checkpoint blockade (ICB) therapy. Inspired by this finding, an F. nucleatum-mimetic nanomedicine is designed by fusing F. nucleatum cytoplasmic membrane (FM) with Colistin-loaded liposomes to achieve selective killing of tumor-colonizing F. nucleatum without affecting gut microbes. As a result, the therapeutic responses of F. nucleatum-colonized tumors to ICB therapies can be successfully restored, as demonstrated in an F. nucleatum-infected subcutaneous CT-26 tumor model, chemically induced spontaneous colorectal cancer models, and MC-38 tumor model. In summary, this work presents an F. nucleatum-mimicking nanomedicine that can selectively eliminate tumor-colonized bacteria, which is promising for enhancing the responses of cancer immunotherapy against F. nucleatum-colonized colorectal cancer.

Developmental toxicity in Daphnia magna induced by environmentally relevant concentrations of carbon black: From the perspective of metabolomics and symbiotic bacteria composition.

The level of carbon black (CB) pollution in the environment is rapidly increasing, owing to the increase in natural and industrial emissions. The water environment has become an important sink for CB. However, studies on CB mainly focused on its impact on air pollution and phytoremediation applications, and the toxicity mechanism of CB in aquatic organisms is relatively limited. Thus, Daphnia magna was used as a model organism to explore the developmental toxicity of environmentally relevant concentrations of CB under a full life-cycle exposure. The toxicity mechanism of CB in aquatic organisms was investigated based on metabolomic and symbiotic microbial analyses. It was found that compared with the control group, the body length of exposed D. magna decreased, while the mortality and intestinal inflammation increased with increasing concentration of CB. The normal reproductive regularity of D. magna was disturbed, and the deformity and body length of the offspring increased and decreased, respectively, after CB exposure. Metabolomic analysis showed that the urea cycle metabolic pathway of exposed D. magna was increased significantly, suggesting a perturbation of N metabolism. In addition, two eicosanoids were increased, suggesting possible inflammation in D. magna. The levels of seven phospholipid metabolites decreased that might be responsible for offspring malformations. Microbiological analysis showed that the composition of the symbiotic microbial community of D. magna was disturbed, including microorganisms involved in carbon cycling, nitrogen cycling, and biodegradation of pollutants, as well as pathogenic microorganisms. Overall, this study found that the inflammatory related metabolites and symbiotic bacterial, as well as reproductive related metabolites, were disrupted after D. magna exposed to different concentrations of CB, which revealed a possible developmental toxicity mechanism of CB in D. magna. These findings provide a scientific basis for analyzing the risks of CB in aquatic environments.