Artificial intelligence improves the diagnosis of human leukocyte antigen (HLA)-B27-negative axial spondyloarthritis based on multi-sequence magnetic resonance imaging and clinical features.

Background: Axial spondyloarthritis (axSpA) is frequently diagnosed late, particularly in human leukocyte antigen (HLA)-B27-negative patients, resulting in a missed opportunity for optimal treatment. This study aimed to develop an artificial intelligence (AI) tool, termed NegSpA-AI, using sacroiliac joint (SIJ) magnetic resonance imaging (MRI) and clinical SpA features to improve the diagnosis of axSpA in HLA-B27-negative patients. Methods: We retrospectively included 454 HLA-B27-negative patients with rheumatologist-diagnosed axSpA or other diseases (non-axSpA) from the Third Affiliated Hospital of Southern Medical University and Nanhai Hospital between January 2010 and August 2021. They were divided into a training set (n=328) for 5-fold cross-validation, an internal test set (n=72), and an independent external test set (n=54). To construct a prospective test set, we further enrolled 87 patients between September 2021 and August 2023 from the Third Affiliated Hospital of Southern Medical University. MRI techniques employed included T1-weighted (T1W), T2-weighted (T2W), and fat-suppressed (FS) sequences. We developed NegSpA-AI using a deep learning (DL) network to differentiate between axSpA and non-axSpA at admission. Furthermore, we conducted a reader study involving 4 radiologists and 2 rheumatologists to evaluate and compare the performance of independent and AI-assisted clinicians. Results: NegSpA-AI demonstrated superior performance compared to the independent junior rheumatologist (≤5 years of experience), achieving areas under the curve (AUCs) of 0.878 [95% confidence interval (CI): 0.786-0.971], 0.870 (95% CI: 0.771-0.970), and 0.815 (95% CI: 0.714-0.915) on the internal, external, and prospective test sets, respectively. The assistance of NegSpA-AI promoted discriminating accuracy, sensitivity, and specificity of independent junior radiologists by 7.4-11.5%, 1.0-13.3%, and 7.4-20.6% across the 3 test sets (all P<0.05). On the prospective test set, AI assistance also improved the diagnostic accuracy, sensitivity, and specificity of independent junior rheumatologists by 7.7%, 7.7%, and 6.9%, respectively (all P<0.01). Conclusions: The proposed NegSpA-AI effectively improves radiologists' interpretations of SIJ MRI and rheumatologists' diagnoses of HLA-B27-negative axSpA.

Mechanism of Lian Hua Qing Wen capsules regulates the inflammatory response caused by M1 macrophage based on cellular experiments and computer simulations.

PURPOSE: The polarization of macrophages with the resulting inflammatory response play a crucial part in tissue and organ damage due to inflammatory. Study has proved Lian Hua Qing Wen capsules (LHQW) can reduce activation of inflammatory response and damage of tissue derived from the inflammatory reactions. However, the mechanism of LHQW regulates the macrophage-induced inflammatory response is unclear. Therefore, we investigated the mechanism of LHQW regulated the inflammatory response of M1 macrophages by cellular experiments and computer simulations. METHODS: This study has analysed the targets and mechanisms of macrophage regulating inflammatory response at gene and protein levels through bioinformatics. The monomeric components of LHQW were analyzed by High Performance Liquid Chromatography (HPLC). We established the in vitro cell model by M1 macrophages (Induction of THP-1 cells into M1 macrophages). RT-qPCR and immunofluorescence were used to detect changes in gene and protein levels of key targets after LHQW treatment. Computer simulations were utilized to verify the binding stability of monomeric components and protein targets. RESULTS: Macrophages had 140,690 gene targets, inflammatory response had 12,192 gene targets, intersection gene targets were 11,772. Key monomeric components (including: Pinocembrin, Fargesone-A, Nodakenin and Bowdichione) of LHQW were screened by HPLC. The results of cellular experiments indicated that LHQW could significantly reduce the mRNA expression of CCR5, CSF2, IFNG and TNF, thereby alleviating the inflammatory response caused by M1 macrophage. The computer simulations further validated the binding stability and conformation of key monomeric components and key protein targets, and IFNG/Nodakenin was able to form the most stable binding conformation for its action. CONCLUSION: In this study, the mechanism of LHQW inhibits the polarization of macrophages and the resulting inflammatory response was investigated by computer simulations and cellular experiments. We found that LHQW may not only reduce cell damage and death by acting on TNF and CCR5, but also inhibit the immune recognition process and inflammatory response by regulating CSF2 and IFNG to prevent polarization of macrophages. Therefore, these results suggested that LHQW may act through multiple targets to inhibit the polarization of macrophages and the resulting inflammatory response.

Cross-species single-cell analysis uncovers the immunopathological mechanisms associated with IgA nephropathy progression.

IgA nephropathy (IgAN) represents the main cause of renal failure, while the precise pathogenetic mechanisms have not been fully determined. Herein, we conducted a cross-species single-cell survey on human IgAN and mouse and rat IgAN models to explore the pathogenic programs. Cross-species single-cell RNA sequencing (scRNA-Seq) revealed that the IgAN mesangial cells (MCs) expressed high levels of inflammatory signatures CXCL12, CCL2, CSF1, and IL-34 and specifically interacted with IgAN macrophages via the CXCL12/CXCR4, CSF1/IL-34/CSF1 receptor, and integrin subunit alpha X/integrin subunit alpha M/complement C3 (C3) axes. IgAN macrophages expressed high levels of CXCR4, PDGFB, triggering receptor expressed on myeloid cells 2, TNF, and C3, and the trajectory analysis suggested that these cells derived from the differentiation of infiltrating blood monocytes. Additionally, protein profiling of 21 progression and 28 nonprogression IgAN samples revealed that proteins CXCL12, C3, mannose receptor C-type 1, and CD163 were negatively correlated with estimated glomerular filtration rate (eGFR) value and poor prognosis (30% eGFR as composite end point). Last, a functional experiment revealed that specific blockade of the Cxcl12/Cxcr4 pathway substantially attenuated the glomerulus and tubule inflammatory injury, fibrosis, and renal function decline in the mouse IgAN model. This study provides insights into IgAN progression and may aid in the refinement of IgAN diagnosis and the optimization of treatment strategies.

A radiograph-based deep learning model improves radiologists' performance for classification of histological types of primary bone tumors: A multicenter study.

PURPOSE: To develop a deep learning (DL) model for classifying histological types of primary bone tumors (PBTs) using radiographs and evaluate its clinical utility in assisting radiologists. METHODS: This retrospective study included 878 patients with pathologically confirmed PBTs from two centers (638, 77, 80, and 83 for the training, validation, internal test, and external test sets, respectively). We classified PBTs into five categories by histological types: chondrogenic tumors, osteogenic tumors, osteoclastic giant cell-rich tumors, other mesenchymal tumors of bone, or other histological types of PBTs. A DL model combining radiographs and clinical features based on the EfficientNet-B3 was developed for five-category classification. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity were calculated to evaluate model performance. The clinical utility of the model was evaluated in an observer study with four radiologists. RESULTS: The combined model achieved a macro average AUC of 0.904/0.873, with an accuracy of 67.5 %/68.7 %, a macro average sensitivity of 66.9 %/57.2 %, and a macro average specificity of 92.1 %/91.6 % on the internal/external test set, respectively. Model-assisted analysis improved accuracy, interpretation time, and confidence for junior (50.6 % vs. 72.3 %, 53.07[s] vs. 18.55[s] and 3.10 vs. 3.73 on a 5-point Likert scale [P < 0.05 for each], respectively) and senior radiologists (68.7 % vs. 75.3 %, 32.50[s] vs. 21.42[s] and 4.19 vs. 4.37 [P < 0.05 for each], respectively). CONCLUSION: The combined DL model effectively classified histological types of PBTs and assisted radiologists in achieving better classification results than their independent visual assessment.

Automatic segmentation of fat metaplasia on sacroiliac joint MRI using deep learning.

OBJECTIVE: To develop a deep learning (DL) model for segmenting fat metaplasia (FM) on sacroiliac joint (SIJ) MRI and further develop a DL model for classifying axial spondyloarthritis (axSpA) and non-axSpA. MATERIALS AND METHODS: This study retrospectively collected 706 patients with FM who underwent SIJ MRI from center 1 (462 axSpA and 186 non-axSpA) and center 2 (37 axSpA and 21 non-axSpA). Patients from center 1 were divided into the training, validation, and internal test sets (n = 455, 64, and 129). Patients from center 2 were used as the external test set. We developed a UNet-based model to segment FM. Based on segmentation results, a classification model was built to distinguish axSpA and non-axSpA. Dice Similarity Coefficients (DSC) and area under the curve (AUC) were used for model evaluation. Radiologists' performance without and with model assistance was compared to assess the clinical utility of the models. RESULTS: Our segmentation model achieved satisfactory DSC of 81.86% ± 1.55% and 85.44% ± 6.09% on the internal cross-validation and external test sets. The classification model yielded AUCs of 0.876 (95% CI: 0.811-0.942) and 0.799 (95% CI: 0.696-0.902) on the internal and external test sets, respectively. With model assistance, segmentation performance was improved for the radiological resident (DSC, 75.70% vs. 82.87%, p < 0.05) and expert radiologist (DSC, 85.03% vs. 85.74%, p > 0.05). CONCLUSIONS: DL is a novel method for automatic and accurate segmentation of FM on SIJ MRI and can effectively increase radiologist's performance, which might assist in improving diagnosis and progression of axSpA. CRITICAL RELEVANCE STATEMENT: DL models allowed automatic and accurate segmentation of FM on sacroiliac joint MRI, which might facilitate quantitative analysis of FM and have the potential to improve diagnosis and prognosis of axSpA. KEY POINTS: • Deep learning was used for automatic segmentation of fat metaplasia on MRI. • UNet-based models achieved automatic and accurate segmentation of fat metaplasia. • Automatic segmentation facilitates quantitative analysis of fat metaplasia to improve diagnosis and prognosis of axial spondyloarthritis.

Characterization of antigen presentation capability for neoantigen-based products using targeted LC-MS/MS method.

The generation of an immune response in neoantigen-based products relies on antigen presentation, which is closely analyzed by bioassays for T-cell functions such as tetramer or cytokine release. Mass spectrometry (MS) has the potential to directly assess the antigen-presenting capability of antigen-presenting cells (APCs), offering advantages such as speed, multi-target analysis, robustness, and ease of transferability. However, it has not been used for quality control of these products due to challenges in sensitivity, including the number of cells and peptide diversity. In this study, we describe the development and validation of an improved targeted LC-MS/MS method with high sensitivity for characterizing antigen presentation, which could be applied in the quality control of neoantigen-based products. The parameters for the extraction were carefully optimized by different short peptides. Highly sensitive targeted triple quadrupole mass spectrometry combined with ultra-high performance liquid chromatography (UHPLC) was employed using a selective ion monitoring mode (Multiple Reaction Monitoring, MRM). Besides, we successfully implemented robust quality control peptides to ensure the reliability and consistency of this method, which proved invaluable for different APCs. With reference to the guidelines from ICH Q2 (R2), M10, as well as considering the specific attributes of the product itself, we validated the method for selectivity, specificity, sensitivity, limit of detection (LOD), recovery rate, matrix effect, repeatability, and application in dendritic cells (DCs) associated with neoantigen-based products. The validation process yields satisfactory results. Combining this approach with T cell assays will comprehensively assess cell product quality attributes from physicochemical and biological perspectives.

Hantaan virus inhibits type I interferon response by targeting RLR signaling pathways through TRIM25.

Hantaan virus (HTNV) is responsible for hemorrhagic fever with renal syndrome (HFRS), primarily due to its ability to inhibit host innate immune responses, such as type I interferon (IFN-I). In this study, we conducted a transcriptome analysis to identify host factors regulated by HTNV nucleocapsid protein (NP) and glycoprotein. Our findings demonstrate that NP and Gc proteins inhibit host IFN-I production by manipulating the retinoic acid-induced gene I (RIG-I)-like receptor (RLR) pathways. Further analysis reveals that HTNV NP and Gc proteins target upstream molecules of MAVS, such as RIG-I and MDA-5, with Gc exhibiting stronger inhibition of IFN-I responses than NP. Mechanistically, NP and Gc proteins interact with tripartite motif protein 25 (TRIM25) to competitively inhibit its interaction with RIG-I/MDA5, suppressing RLR signaling pathways. Our study unveils a cross-talk between HTNV NP/Gc proteins and host immune response, providing valuable insights into the pathogenic mechanism of HTNV.

Automatic detection, segmentation, and classification of primary bone tumors and bone infections using an ensemble multi-task deep learning framework on multi-parametric MRIs: a multi-center study.

OBJECTIVES: To develop an ensemble multi-task deep learning (DL) framework for automatic and simultaneous detection, segmentation, and classification of primary bone tumors (PBTs) and bone infections based on multi-parametric MRI from multi-center. METHODS: This retrospective study divided 749 patients with PBTs or bone infections from two hospitals into a training set (N = 557), an internal validation set (N = 139), and an external validation set (N = 53). The ensemble framework was constructed using T1-weighted image (T1WI), T2-weighted image (T2WI), and clinical characteristics for binary (PBTs/bone infections) and three-category (benign/intermediate/malignant PBTs) classification. The detection and segmentation performances were evaluated using Intersection over Union (IoU) and Dice score. The classification performance was evaluated using the receiver operating characteristic (ROC) curve and compared with radiologist interpretations. RESULT: On the external validation set, the single T1WI-based and T2WI-based multi-task models obtained IoUs of 0.71 ± 0.25/0.65 ± 0.30 for detection and Dice scores of 0.75 ± 0.26/0.70 ± 0.33 for segmentation. The framework achieved AUCs of 0.959 (95%CI, 0.955-1.000)/0.900 (95%CI, 0.773-0.100) and accuracies of 90.6% (95%CI, 79.7-95.9%)/78.3% (95%CI, 58.1-90.3%) for the binary/three-category classification. Meanwhile, for the three-category classification, the performance of the framework was superior to that of three junior radiologists (accuracy: 65.2%, 69.6%, and 69.6%, respectively) and comparable to that of two senior radiologists (accuracy: 78.3% and 78.3%). CONCLUSION: The MRI-based ensemble multi-task framework shows promising performance in automatically and simultaneously detecting, segmenting, and classifying PBTs and bone infections, which was preferable to junior radiologists. CLINICAL RELEVANCE STATEMENT: Compared with junior radiologists, the ensemble multi-task deep learning framework effectively improves differential diagnosis for patients with primary bone tumors or bone infections. This finding may help physicians make treatment decisions and enable timely treatment of patients. KEY POINTS: • The ensemble framework fusing multi-parametric MRI and clinical characteristics effectively improves the classification ability of single-modality models. • The ensemble multi-task deep learning framework performed well in detecting, segmenting, and classifying primary bone tumors and bone infections. • The ensemble framework achieves an optimal classification performance superior to junior radiologists' interpretations, assisting the clinical differential diagnosis of primary bone tumors and bone infections.

SOCS1 Peptidomimetic Alleviates Glomerular Inflammation in MsPGN by Inhibiting Macrophage M1 Polarization.

Mesangial proliferative glomerulonephritis (MsPGN), the most common pathological change in primary glomerulonephritis, is characterized by increased macrophage infiltration into glomeruli, which results in proinflammatory cytokine release. Macrophage infiltration and differentiation are induced by the Janus kinase 2 and signal transducer and activator of the transcription 1 (JAK2/STAT1) pathway. As a suppressor of cytokine signaling 1 (SOCS1) downregulates the immune response by inhibiting the JAK2/STAT1 pathway, we investigated whether a peptide mimicking the SOCS1 kinase inhibitor region, namely, SOCS1 peptidomimetic, protects against nephropathy. Glomerular JAK2/STAT1 pathway activation was synchronized with kidney injury in an MsPGN rat model. Rats treated with the SOCS1 peptidomimetic exhibited reduced pathological glomerular changes and lessened macrophage recruitment. Moreover, in vivo, the phosphorylation of the JAK2/STAT1 pathway was downregulated in infiltrated macrophages of glomeruli. In vitro, the SOCS1 peptidomimetic inhibited macrophage M1 polarization by suppressing JAK2/STAT1 activation. In conclusion, our study demonstrated that the SOCS1 peptidomimetic plays a protective role against pathologic glomerular changes in MsPGN by reducing macrophage infiltration and inhibiting macrophage polarizing to the M1 phenotype. SOCS1 peptidomimetic, therefore, presents a feasible therapeutic strategy to alleviate renal inflammation in MsPGN.

Mn3 O4 Nanoshell Coated Metal-Organic Frameworks with Microenvironment-Driven O2 Production and GSH Exhaustion Ability for Enhanced Chemodynamic and Photodynamic Cancer Therapies.

Nanomedicine exhibits emerging potentials to deliver advanced therapeutic strategies in the fight against triple-negative breast cancer (TNBC). Nevertheless, it is still difficult to develop a precise codelivery system that integrates highly effective photosensitizers, low toxicity, and hydrophobicity. In this study, PCN-224 is selected as the carrier to enable effective cancer therapy through light-activated reactive oxygen species (ROS) formation, and the PCN-224@Mn3 O4 @HA is created in a simple one-step process by coating Mn3 O4 nanoshells on the PCN-224 template, which can then be used as an "ROS activator" to exert catalase- and glutathione peroxidase-like activities to alleviate tumor hypoxia while reducing tumor reducibility, leading to improved photodynamic therapeutic (PDT) effect of PCN-224. Meanwhile, Mn2+ produced cytotoxic hydroxyl radicals (∙OH) via the Fenton-like reaction, thus producing a promising spontaneous chemodynamic therapeutic (CDT) effect. Importantly, by remodeling the tumor microenvironment (TME), Mn3 O4 nanoshells downregulated hypoxia-inducible factor 1α expression, inhibiting tumor growth and preventing tumor revival. Thus, the developed nanoshells, via light-controlled ROS formation and multimodality imaging abilities, can effectively inhibit tumor proliferation through synergistic PDT/CDT, and prevent tumor resurgence by remodeling TME.

Hibifolin, a Natural Sortase A Inhibitor, Attenuates the Pathogenicity of Staphylococcus aureus and Enhances the Antibacterial Activity of Cefotaxime.

This study aimed to identify hibifolin as a sortase A (SrtA) inhibitor and to determine whether it could attenuate the virulence of methicillin-resistant Staphylococcus aureus (MRSA). We employed a fluorescence resonance energy transfer (FRET) assay to screen a library of natural molecules to identify compounds that inhibit SrtA activity. Fluorescence quenching assay and molecular docking were performed to verify the direct binding interaction between SrtA and hibifolin. The pneumonia model was established using C57BL/6J mice by MRAS nasal administration for evaluating the effect of hibifolin on the pathogenicity of MRSA. Herein, we found that hibifolin was able to inhibit SrtA activity with an IC50 of 31.20 µg/mL. Further assays showed that the capacity of adhesion of bacteria to the host cells and biofilm formation was decreased in hibifolin-treated USA300. Results obtained from fluorescence quenching assay and molecular docking indicated that hibifolin was capable of targeting SrtA protein directly. This interaction was further confirmed by the finding that the inhibition activities of hibifolin on mutant SrtA were substantially reduced after mutating the binding sites (TRP-194, ALA-104, THR-180, ARG-197, ASN-114). The in vivo study showed that hibifolin in combination with cefotaxime protected mice from USA300 infection-induced pneumonia, which was more potent than cefotaxime alone, and no significant cytotoxicity of hibifolin was observed. Taken together, we identified that hibifolin attenuated the pathogenicity of S. aureus by directly targeting SrtA, which may be utilized in the future as adjuvant therapy for S. aureus infections. IMPORTANCE We identified hibifolin as a sortase A (SrtA) inhibitor by screening the natural compounds library, which effectively inhibited the activity of SrtA with an IC50 value of 31.20 µg/mL. Hibifolin attenuated the pathogenic behavior of Staphylococcus aureus, including adhesion, invasion, and biofilm formation. Binding assays showed that hibifolin bound to SrtA protein directly. Hibifolin improved the survival of pneumonia induced by S. aureus USA300 in mice and alleviated the pathological damage. Moreover, hibifolin showed a synergistic antibacterial effect with cefotaxime in USA300-infected mice.

Single Cell Dissection of Epithelial-Immune Cellular Interplay in Acute Kidney Injury Microenvironment.

Background: Understanding the acute kidney injury (AKI) microenvironment changes and the complex cellular interaction is essential to elucidate the mechanisms and develop new targeted therapies for AKI. Methods: We employed unbiased single-cell RNA sequencing to systematically resolve the cellular atlas of kidney tissue samples from mice at 1, 2 and 3 days after ischemia-reperfusion AKI and healthy control. The single-cell transcriptome findings were validated using multiplex immunostaining, western blotting, and functional experiments. Results: We constructed a systematic single-cell transcriptome atlas covering different AKI timepoints with immune cell infiltration increasing with AKI progression. Three new proximal tubule cells (PTCs) subtypes (PTC-S1-new/PTC-S2-new/PTC-S3-new) were identified, with upregulation of injury and repair-regulated signatures such as Sox9, Vcam1, Egr1, and Klf6 while with downregulation of metabolism. PTC-S1-new exhibited pro-inflammatory and pro-fibrotic signature compared to normal PTC, and trajectory analysis revealed that proliferating PTCs were the precursor cell of PTC-S1-new, and part of PTC-S1-new cells may turn into PTC-injured and then become fibrotic. Cellular interaction analysis revealed that PTC-S1-new and PTC-injured interacted closely with infiltrating immune cells through CXCL and TNF signaling pathways. Immunostaining validated that injured PTCs expressed a high level of TNFRSF1A and Kim-1, and functional experiments revealed that the exogenous addition of TNF-α promoted kidney inflammation, dramatic injury, and specific depletion of TNFRSF1A would abrogate the injury. Conclusions: The single-cell profiling of AKI microenvironment provides new insight for the deep understanding of molecular changes of AKI, and elucidates the mechanisms and developing new targeted therapies for AKI.

Hypoxic mesenchymal stem cell-derived extracellular vesicles ameliorate renal fibrosis after ischemia-reperfusion injure by restoring CPT1A mediated fatty acid oxidation.

BACKGROUND: Renal fibrosis is a common pathological process of chronic kidney diseases induced by multiple factors. Hypoxic pretreatment of mesenchymal stem cells can enhance the efficacy of secreted extracellular vesicles (MSC-EVs) on various diseases, but it is not clear whether they can better improve renal fibrosis. The latest research showed that recovery of fatty acid oxidation (FAO) can reduce renal fibrosis. In this study, we aimed to examine whether hypoxic pretreatment with MSC extracellular vesicles (Hypo-EVs) can improve FAO to restore renal fibrosis and to investigate the underlying mechanism. METHODS: Hypo-EVs were isolated from hypoxia-pretreated human placenta-derived MSC (hP-MSC), and Norm-EVs were isolated from hP-MSC cultured under normal conditions. We used ischemia-reperfusion (I/R)-induced renal fibrosis model in vivo. The mice were injected with PBS, Hypo-EVs, or Norm-EVs immediately after the surgery and day 1 postsurgery. Renal function, kidney pathology, and renal fibrosis were assessed for kidney damage evaluation. For mechanistic exploration, fatty acid oxidation (FAO), mitochondrial morphological alterations, ATP production and mitochondrial mass proteins were detected in vivo. Mitochondrial membrane potential and reactive oxygen species (ROS) production were investigated in vitro. RESULTS: We found that Hypo-EVs confer a superior therapeutic effect on recovery of renal structure damage, restoration of renal function and reduction in renal fibrosis. Meanwhile, Hypo-EVs enhanced mitochondrial FAO in kidney by restoring the expression of a FAO key rate-limiting enzyme carnitine palmitoyl-transferase 1A (CPT1A). Mechanistically, the improvement of mitochondrial homeostasis, characterized by repaired mitochondrial structure, restoration of mitochondrial mass and ATP production, inhibition of oxidative stress, and increased mitochondrial membrane potential, partially explains the effect of Hypo-EVs on improving mitochondrial FAO and thus attenuating I/R damage. CONCLUSIONS: Hypo-EVs suppress the renal fibrosis by restoring CPT1A-mediated mitochondrial FAO, which effects may be achieved through regulation of mitochondrial homeostasis. Our findings provide further mechanism support for development cell-free therapy of renal fibrosis.

Synergistic photothermal-photodynamic-chemotherapy toward breast cancer based on a liposome-coated core-shell AuNS@NMOFs nanocomposite encapsulated with gambogic acid.

A multifunctional nanoplatform with core-shell structure was constructed in one-pot for the synergistic photothermal, photodynamic, and chemotherapy against breast cancer. In the presence of gambogic acid (GA) as the heat-shock protein 90 (HSP90) inhibitor and the gold nanostars (AuNS) as the photothermal reagent, the assembly of Zr4+ with tetrakis (4-carboxyphenyl) porphyrin (TCPP) gave rise to the nanocomposite AuNS@ZrTCPP-GA (AZG), which in turn, further coated with PEGylated liposome (LP) to enhance the stability and biocompatibility, and consequently the antitumor effect of the particle. Upon cellular uptake, the nanoscale metal - organic framework (NMOF) of ZrTCPP in the resulted AuNS@ZrTCPP-GA@LP (AZGL) could be slowly degraded in the weak acidic tumor microenvironment to release AuNS, Zr4+, TCPP, and GA to exert the synergistic treatment of tumors via the combination of AuNS-mediated mild photothermal therapy (PTT) and TCPP-mediated photodynamic therapy (PDT). The introduction of GA serves to reduce the thermal resistance of the cell to re-sensitize PTT and the constructed nanoplatform demonstrated remarkable anti-tumor activity in vitro and in vivo. Our work highlights a facile strategy to prepare a pH-dissociable nanoplatform for the effective synergistic treatment of breast cancer.

DDTNet: A dense dual-task network for tumor-infiltrating lymphocyte detection and segmentation in histopathological images of breast cancer.

The morphological evaluation of tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H& E)-stained histopathological images is the key to breast cancer (BCa) diagnosis, prognosis, and therapeutic response prediction. For now, the qualitative assessment of TILs is carried out by pathologists, and computer-aided automatic lymphocyte measurement is still a great challenge because of the small size and complex distribution of lymphocytes. In this paper, we propose a novel dense dual-task network (DDTNet) to simultaneously achieve automatic TIL detection and segmentation in histopathological images. DDTNet consists of a backbone network (i.e., feature pyramid network) for extracting multi-scale morphological characteristics of TILs, a detection module for the localization of TIL centers, and a segmentation module for the delineation of TIL boundaries, where a boundary-aware branch is further used to provide a shape prior to segmentation. An effective feature fusion strategy is utilized to introduce multi-scale features with lymphocyte location information from highly correlated branches for precise segmentation. Experiments on three independent lymphocyte datasets of BCa demonstrate that DDTNet outperforms other advanced methods in detection and segmentation metrics. As part of this work, we also propose a semi-automatic method (TILAnno) to generate high-quality boundary annotations for TILs in H& E-stained histopathological images. TILAnno is used to produce a new lymphocyte dataset that contains 5029 annotated lymphocyte boundaries, which have been released to facilitate computational histopathology in the future.

A dual-role of SARS-CoV-2 nucleocapsid protein in regulating innate immune response.

The recently emerged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of ongoing global pandemic of COVID-19, may trigger immunosuppression in the early stage and overactive immune response in the late stage of infection; However, the underlying mechanisms are not well understood. Here we demonstrated that the SARS-CoV-2 nucleocapsid (N) protein dually regulated innate immune responses, i.e., the low-dose N protein suppressed type I interferon (IFN-I) signaling and inflammatory cytokines, whereas high-dose N protein promoted IFN-I signaling and inflammatory cytokines. Mechanistically, the SARS-CoV-2 N protein dually regulated the phosphorylation and nuclear translocation of IRF3, STAT1, and STAT2. Additionally, low-dose N protein combined with TRIM25 could suppress the ubiquitination and activation of retinoic acid-inducible gene I (RIG-I). Our findings revealed a regulatory mechanism of innate immune responses by the SARS-CoV-2 N protein, which would contribute to understanding the pathogenesis of SARS-CoV-2 and other SARS-like coronaviruses, and development of more effective strategies for controlling COVID-19.

SARS-CoV-2 Membrane Protein Inhibits Type I Interferon Production Through Ubiquitin-Mediated Degradation of TBK1.

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative pathogen of current COVID-19 pandemic, and insufficient production of type I interferon (IFN-I) is associated with the severe forms of the disease. Membrane (M) protein of SARS-CoV-2 has been reported to suppress host IFN-I production, but the underlying mechanism is not completely understood. In this study, SARS-CoV-2 M protein was confirmed to suppress the expression of IFNß and interferon-stimulated genes induced by RIG-I, MDA5, IKKϵ, and TBK1, and to inhibit IRF3 phosphorylation and dimerization caused by TBK1. SARS-CoV-2 M could interact with MDA5, TRAF3, IKKϵ, and TBK1, and induce TBK1 degradation via K48-linked ubiquitination. The reduced TBK1 further impaired the formation of TRAF3-TANK-TBK1-IKKε complex that leads to inhibition of IFN-I production. Our study revealed a novel mechanism of SARS-CoV-2 M for negative regulation of IFN-I production, which would provide deeper insight into the innate immunosuppression and pathogenicity of SARS-CoV-2.

A new nairo-like virus associated with human febrile illness in China.

ABSTRACTSeveral nairo-like viruses have been discovered in ticks in recent years, but their relevance to public health remains unknown. Here, we found a patient who had a history of tick bite and suffered from a febrile illness was infected with a previously discovered RNA virus, Beiji nairovirus (BJNV), in the nairo-like virus group of the order Bunyavirales. We isolated the virus by cell culture assay. BJNV could induce cytopathic effects in the baby hamster kidney and human hepatocellular carcinoma cells. Negative-stain electron microscopy revealed enveloped and spherical viral particles, morphologically similar to those of nairoviruses. We identified 67 patients as BJNV infection in 2017-2018. The median age of patients was 48 years (interquartile range 41-53 years); the median incubation period was 7 days (interquartile range 3-12 days). Most patients were men (70%), and a few (10%) had underlying diseases. Common symptoms of infected patients included fever (100%), headache (99%), depression (63%), coma (63%), and fatigue (54%), myalgia or arthralgia (45%); two (3%) patients became critically ill and one died. BJNV could cause growth retardation, viremia and histopathological changes in infected suckling mice. BJNV was also detected in sheep, cattle, and multiple tick species. These findings demonstrated that the newly discovered nairo-like virus may be associated with a febrile illness, with the potential vectors of ticks and reservoirs of sheep and cattle, highlighting its public health significance and necessity of further investigation in the tick-endemic areas worldwide.

Role of the IL-33/ST2 receptor axis in ovarian cancer progression.

Ovarian cancer remains a significant health problem for women in the world due to its diagnosis at advanced stages of disease and the high mortality rate of patients. To date, ovarian cancer is frequently treated with tumor reduction surgery followed by platinum/paclitaxel-based chemotherapy; however, most patients eventually develop relapsed disease. The mRNA expression levels of interleukin-33 (IL-33) and the suppressor of tumorigenicity 2 (ST2) receptor are significantly upregulated in ovarian cancer tissues and metastatic tumor lesions. In addition, IL-33 and ST2 expression has been associated with a poor overall survival in patients with epithelial ovarian cancer. The IL-33 receptor ST2 is expressed as both a membrane-anchored receptor (ST2L) activated by IL-33, and as a soluble variant that exhibits anti-inflammatory properties. In the present review, the functions of the IL-33/ST2L axis in cells and their aberrant expression levels in ovarian cancer were discussed. In addition, targeting their expression as a novel strategy for the control of ovarian cancer progression was emphasized.

Activated mesangial cells induce glomerular endothelial cells proliferation in rat anti-Thy-1 nephritis through VEGFA/VEGFR2 and Angpt2/Tie2 pathway.

OBJECTIVES: We aimed to investigate the underlying mechanism of endothelial cells (ECs) proliferation in anti-Thy-1 nephritis. MATERIALS AND METHODS: We established anti-Thy-1 nephritis and co-culture system to explore the underlying mechanism of ECs proliferation in vivo and in vitro. EdU assay kit was used for measuring cell proliferation. Immunohistochemical staining and immunofluorescence staining were used to detect protein expression. ELISA was used to measure the concentration of protein in serum and medium. RT-qPCR and Western blot were used to qualify the mRNA and protein expression. siRNA was used to knock down specific protein expression. RESULTS: In anti-Thy-1 nephritis, ECs proliferation was associated with mesangial cells (MCs)-derived vascular endothelial growth factor A (VEGFA) and ECs-derived angiopoietin2 (Angpt2). In vitro co-culture system activated MCs-expressed VEGFA to promote vascular endothelial growth factor receptor2 (VEGFR2) activation, Angpt2 expression and ECs proliferation, but inhibit TEK tyrosine kinase (Tie2) phosphorylation. MCs-derived VEGFA stimulated Angpt2 expression in ECs, which inhibited Tie2 phosphorylation and promoted ECs proliferation. And decline of Tie2 phosphorylation induced ECs proliferation. In anti-Thy-1 nephritis, promoting Tie2 phosphorylation could alleviate ECs proliferation. CONCLUSIONS: Our study showed that activated MCs promoted ECs proliferation through VEGFA/VEGFR2 and Angpt2/Tie2 pathway in experimental mesangial proliferative glomerulonephritis (MPGN) and in vitro co-culture system. And enhancing Tie2 phosphorylation could alleviate ECs proliferation, which will provide a new idea for MPGN treatment.