LFA-1 knockout inhibited the tumor growth and is correlated with treg cells.

Cancer immunotherapy has been proven to be clinically effective in multiple types of cancers. Lymphocyte function-associated antigen 1 (LFA-1), a member of the integrin family of adhesion molecules, is expressed mainly on αß T cells. LFA-1 is associated with tumor immune responses, but its exact mechanism remains unknown. Here, two kinds of mice tumor model of LFA-1 knockout (LFA-1-/-) mice bearing subcutaneous tumor and Apc Min/+;LFA-1-/- mice were used to confirm that LFA-1 knockout resulted in inhibition of tumor growth. Furthermore, it also demonstrated that the numbers of regulatory T cells (Treg cells) in the spleen, blood, mesenteric lymph nodes were decreased in LFA-1-/- mice, and the numbers of Treg cells in mesenteric lymph nodes were also decreased in Apc Min/+;LFA-1-/- mice compared with Apc Min/+ mice. LFA-1 inhibitor (BIRT377) was administered to subcutaneous tumor-bearing LFA-1+/+ mice, and the results showed that the tumor growth was inhibited and the number of Treg cells was reduced. The analysis of TIMER tumor database indicated that LFA-1 expression is positively associated with Treg cells and TNM stage. Conclusively, this suggests that LFA-1 knockout would inhibit tumor growth and is correlated with Treg cells. LFA-1 may be one potential target for cancer immunotherapy. Video Abstract.

A novel one-to-multiple unsupervised domain adaptation framework for abdominal organ segmentation.

Abdominal multi-organ segmentation in multi-sequence magnetic resonance images (MRI) is of great significance in many clinical scenarios, e.g., MRI-oriented pre-operative treatment planning. Labeling multiple organs on a single MR sequence is a time-consuming and labor-intensive task, let alone manual labeling on multiple MR sequences. Training a model by one sequence and generalizing it to other domains is one way to reduce the burden of manual annotation, but the existence of domain gap often leads to poor generalization performance of such methods. Image translation-based unsupervised domain adaptation (UDA) is a common way to address this domain gap issue. However, existing methods focus less on keeping anatomical consistency and are limited by one-to-one domain adaptation, leading to low efficiency for adapting a model to multiple target domains. This work proposes a unified framework called OMUDA for one-to-multiple unsupervised domain-adaptive segmentation, where disentanglement between content and style is used to efficiently translate a source domain image into multiple target domains. Moreover, generator refactoring and style constraint are conducted in OMUDA for better maintaining cross-modality structural consistency and reducing domain aliasing. The average Dice Similarity Coefficients (DSCs) of OMUDA for multiple sequences and organs on the in-house test set, the AMOS22 dataset and the CHAOS dataset are 85.51%, 82.66% and 91.38%, respectively, which are slightly lower than those of CycleGAN(85.66% and 83.40%) in the first two data sets and slightly higher than CycleGAN(91.36%) in the last dataset. But compared with CycleGAN, OMUDA reduces floating-point calculations by about 87 percent in the training phase and about 30 percent in the inference stage respectively. The quantitative results in both segmentation performance and training efficiency demonstrate the usability of OMUDA in some practical scenes, such as the initial phase of product development.

Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders.

MicroRNAs (miRNAs) are short RNA molecular fragments that regulate gene expression by targeting and inhibiting the expression of specific RNAs. Due to the fact that microRNAs affect many diseases in microbial ecology, it is necessary to predict microRNAs' association with diseases at the microbial level. To this end, we propose a novel model, termed as GCNA-MDA, where dual-autoencoder and graph convolutional network (GCN) are integrated to predict miRNA-disease association. The proposed method leverages autoencoders to extract robust representations of miRNAs and diseases and meantime exploits GCN to capture the topological information of miRNA-disease networks. To alleviate the impact of insufficient information for the original data, the association similarity and feature similarity data are combined to calculate a more complete initial basic vector of nodes. The experimental results on the benchmark datasets demonstrate that compared with the existing representative methods, the proposed method has achieved the superior performance and its precision reaches up to 0.8982. These results demonstrate that the proposed method can serve as a tool for exploring miRNA-disease associations in microbial environments.

Applicability of multidimensional convolutional neural networks on automated detection of diverse focal liver lesions in multiphase CT images.

PURPOSE: To investigate the applicability of multidimensional convolutional neural networks (CNNs) together with multiphase contrast-enhanced CT images on automated detection of diverse focal liver lesions (FLLs). METHODS: We trained detection models based on 2.5D and 3D CNN frameworks using 567 patients with 3892 FLLs and validated on a relatively large independent cohort of 1436 patients with 4723 lesions. The detection performance across different phases (arterial, portal venous [PV], and combined phases) was assessed for the 2.5D model. The lesions were divided into two groups with a cutoff size of 20 mm, and further subdivided into four subgroups of <10, 10-20, 20-50, and ≥50 mm, to verify the detection rates for lesions of different sizes for the 2.5D and 3D models. McNemar's test was used to compare the detection sensitivities among different methods. In addition, sensitivity with 95% confidence intervals and free-response receiver operating characteristics (FROC) curves were plotted for visualization of the detectability. RESULTS: In the 2.5D model, the detection rate of PV phase outperformed arterial phase, and a combination of the two phases further improved the performance over a single phase. The detection sensitivities in the arterial, PV, and combined phases were 0.737 versus 0.802 versus 0.832 for all lesions. The 3D model was superior to the 2.5D model for detecting benign lesions (0.896 vs. 0.807, p < 0.001), malignant lesions (0.940 vs. 0.918, p = 0.013), and all lesions (0.902 vs. 0.832, p < 0.001) regardless of size division. Particularly, the 3D model showed higher sensitivity than the 2.5D model in detecting lesions smaller than 20 mm (0.868 vs. 0.759, p < 0.001). For lesions larger than 20 mm, both the 3D and the 2.5D models achieved excellent detection performance. CONCLUSIONS: The proposed CNN detection model was demonstrated to adaptively learn the feature representations of diverse FLLs and generalize well to a large-scale validation dataset. The use of multiphase significantly improved the detectability of FLLs compared to single phase. 3D CNN framework showed an enhanced capability over the 2.5D in the detection of FLLs, particularly small lesions. The promising performance shows that the proposed CNN detection system could be a powerful clinical tool for the early detection of hepatic tumors.

Automatic discrimination of different sequences and phases of liver MRI using a dense feature fusion neural network: a preliminary study.

PURPOSE: To develop and validate a dense feature fusion neural network (DFuNN) to automatically recognize different sequences and phases of liver magnetic resonance imaging (MRI). MATERIALS AND METHODS: In total, 3869 sequences and phases from 384 liver MRI examinations, divided into training/validation (n = 2886 sequences from 287 patients) and test (n = 983 sequences from 97 patients) sets, were used in this retrospective study. Ten unenhanced sequences and enhanced phases were included. Manual sequence recognition, performed by two radiologists (20 and 10 years of experience) in a consensus reading, was used as the reference standard. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of the DFuNN on an identical unseen test set. Finally, we evaluated the factors impacting the model precision. RESULTS: A fusion block improved the performance of the DFuNN. DFuNN with a fusion block achieved good recognition performance for both complete and incomplete sequences and phases in the test set. The average sensitivity of recognition performance for complete sequence and phase inputs ranged from 88.06 to 100%, the average specificity ranged from 99.12 to 99.94%, and the median accuracy ranged from 98.02 to 99.95%. The DFuNN prediction accuracy for patients without cirrhosis were significantly higher than those for patients with cirrhosis (P = 0.0153). No significant difference was found in the accuracy across other factors. CONCLUSION: DFuNN can automatically and accurately identify specific unenhanced MRI sequences and enhanced MRI phases.

Prosaposin mediates inflammation in atherosclerosis.

Macrophages play a central role in the pathogenesis of atherosclerosis. The inflammatory properties of these cells are dictated by their metabolism, of which the mechanistic target of rapamycin (mTOR) signaling pathway is a key regulator. Using myeloid cell-specific nanobiologics in apolipoprotein E-deficient (Apoe -/-) mice, we found that targeting the mTOR and ribosomal protein S6 kinase-1 (S6K1) signaling pathways rapidly diminished plaque macrophages' inflammatory activity. By investigating transcriptome modifications, we identified Psap, a gene encoding the lysosomal protein prosaposin, as closely related with mTOR signaling. Subsequent in vitro experiments revealed that Psap inhibition suppressed both glycolysis and oxidative phosphorylation. Transplantation of Psap -/- bone marrow to low-density lipoprotein receptor knockout (Ldlr -/-) mice led to a reduction in atherosclerosis development and plaque inflammation. Last, we confirmed the relationship between PSAP expression and inflammation in human carotid atherosclerotic plaques. Our findings provide mechanistic insights into the development of atherosclerosis and identify prosaposin as a potential therapeutic target.

Multimodal imaging of bacterial-host interface in mice and piglets with Staphylococcus aureus endocarditis.

Acute bacterial endocarditis is a rapid, difficult to manage, and frequently lethal disease. Potent antibiotics often cannot efficiently kill Staphylococcus aureus that colonizes the heart's valves. S. aureus relies on virulence factors to evade therapeutics and the host's immune response, usurping the host's clotting system by activating circulating prothrombin with staphylocoagulase and von Willebrand factor-binding protein. An insoluble fibrin barrier then forms around the bacterial colony, shielding the pathogen from immune cell clearance. Targeting virulence factors may provide previously unidentified avenues to better diagnose and treat endocarditis. To tap into this unused therapeutic opportunity, we codeveloped therapeutics and multimodal molecular imaging to probe the host-pathogen interface. We introduced and validated a family of small-molecule optical and positron emission tomography (PET) reporters targeting active thrombin in the fibrin-rich environment of bacterial colonies. The imaging agents, based on the clinical thrombin inhibitor dabigatran, are bound to heart valve vegetations in mice. Using optical imaging, we monitored therapy with antibodies neutralizing staphylocoagulase and von Willebrand factor-binding protein in mice with S. aureus endocarditis. This treatment deactivated bacterial defenses against innate immune cells, decreased in vivo imaging signal, and improved survival. Aortic or tricuspid S. aureus endocarditis in piglets was also successfully imaged with clinical PET/magnetic resonance imaging. Our data map a route toward adjuvant immunotherapy for endocarditis and provide efficient tools to monitor this drug class for infectious diseases.

Author Correction: Phosphoinositide 3-Kinase (PI3K) Subunit p110δ Is Essential for Trophoblast Cell Differentiation and Placental Development in Mouse.

A correction has been published and is appended to both the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Convolution kernel and iterative reconstruction affect the diagnostic performance of radiomics and deep learning in lung adenocarcinoma pathological subtypes.

BACKGROUND: The aim of this study was to investigate the influence of convolution kernel and iterative reconstruction on the diagnostic performance of radiomics and deep learning (DL) in lung adenocarcinomas. METHODS: A total of 183 patients with 215 lung adenocarcinomas were included in this study. All CT imaging data was reconstructed with three reconstruction algorithms (ASiR at 0%, 30%, 60% strength), each with two convolution kernels (bone and standard). A total of 171 nodules were selected as the training-validation set, whereas 44 nodules were selected as the testing set. Logistic regression and a DL framework-DenseNets were selected to tackle the task. Three logical experiments were implemented to fully explore the influence of the studied parameters on the diagnostic performance. The receiver operating characteristic curve (ROC) was used to evaluate the performance of constructed models. RESULTS: In Experiments A and B, no statistically significant results were found in the radiomic method, whereas two and six pairs were statistically significant (P < 0.05) in the DL method. In Experiment_C, significant differences in one and four models were found in the radiomics and DL methods, respectively. Moreover, models constructed with standard convolution kernel data outperformed that constructed with bone convolution kernel data in all studied ASiR levels in the DL method. In the DL method, B0 and S60 performed best in bone and standard convolution kernel, respectively. CONCLUSION: The results demonstrated that DL was more susceptible to CT parameter variability than radiomics. Standard convolution kernel images seem to be more appropriate for imaging analysis. Further investigation with a larger sample size is needed.

Myeloid-derived suppressor cells accumulate among myeloid cells contributing to tumor growth in matrix metalloproteinase 12 knockout mice.

Myeloid-derived suppressor cells (MDSCs) are found frequently in patients and mice bearing tumors, which derived from immature myeloid cells. In healthy individuals, immature myeloid cells formed in the bone marrow differentiating to dendritic cells, macrophages and neutrophils. However, it is unclear whether some gene deficiency will lead to MDSCs accumulation in mice without bearing tumor. Here, we observed that MDSCs accumulated in the bone marrow of matrix metalloproteinase 12 knockout mice (MMP12-/- mice) compared with wild type mice (MMP12+/+ mice). And the number of CD4+ cells dramatically decreased, regulatory T cells was up-regulation and MDSCs function were determined. The results suggested that immune surveillance have been impaired in MMP12-/- transgenic mice. After intravenous administration of B16 murine melanoma cells, MMP12-/- mice developed more metastatic pulmonary nodules than MMP12+/+ mice. Meanwhile, more MDSCs appeared in the tumors of MMP12-/- mice compared with those of MMP12+/+ mice. Mechanistically, we performed a MDSC blocking assay, finding that blockade of MDSCs resulted in reducing growth of tumors in MMP12-/- mice. Furthermore, we ascertained that macrophages in MMP12-/- mice abundantly secrete IL-1ß in bone marrow which induce the accumulation of MDSCs in the bone marrow. Together, these results demonstrated that the macrophages in MMP12-/- mice could crosstalk with myeloid cells through IL-1ß, inducing MDSCs accumulation, then contributing to tumor growth. It has revealed that the critical roles of macrophage in myeloid cells differentiation.

Efficacy and safety assessment of a TRAF6-targeted nanoimmunotherapy in atherosclerotic mice and non-human primates.

Macrophage accumulation in atherosclerosis is directly linked to the destabilization and rupture of plaque, causing acute atherothrombotic events. Circulating monocytes enter the plaque and differentiate into macrophages, where they are activated by CD4+ T lymphocytes through CD40-CD40 ligand signalling. Here, we report the development and multiparametric evaluation of a nanoimmunotherapy that moderates CD40-CD40 ligand signalling in monocytes and macrophages by blocking the interaction between CD40 and tumour necrosis factor receptor-associated factor 6 (TRAF6). We evaluated the biodistribution characteristics of the nanoimmunotherapy in apolipoprotein E-deficient (Apoe-/-) mice and in non-human primates by in vivo positron-emission tomography imaging. In Apoe-/- mice, a 1-week nanoimmunotherapy treatment regimen achieved significant anti-inflammatory effects, which was due to the impaired migration capacity of monocytes, as established by a transcriptome analysis. The rapid reduction of plaque inflammation by the TRAF6-targeted nanoimmunotherapy and its favourable toxicity profiles in both mice and non-human primates highlights the translational potential of this strategy for the treatment of atherosclerosis.

Author Correction: Efficacy and safety assessment of a TRAF6-targeted nanoimmunotherapy in atherosclerotic mice and non-human primates.

In the version of this Article originally published, the surname of the author Edward A. Fisher was spelt incorrectly as 'Fischer'. This has now been corrected.

IRF3 and type I interferons fuel a fatal response to myocardial infarction.

Interferon regulatory factor 3 (IRF3) and type I interferons (IFNs) protect against infections and cancer, but excessive IRF3 activation and type I IFN production cause autoinflammatory conditions such as Aicardi-Goutières syndrome and STING-associated vasculopathy of infancy (SAVI). Myocardial infarction (MI) elicits inflammation, but the dominant molecular drivers of MI-associated inflammation remain unclear. Here we show that ischemic cell death and uptake of cell debris by macrophages in the heart fuel a fatal response to MI by activating IRF3 and type I IFN production. In mice, single-cell RNA-seq analysis of 4,215 leukocytes isolated from infarcted and non-infarcted hearts showed that MI provokes activation of an IRF3-interferon axis in a distinct population of interferon-inducible cells (IFNICs) that were classified as cardiac macrophages. Mice genetically deficient in cyclic GMP-AMP synthase (cGAS), its adaptor STING, IRF3, or the type I IFN receptor IFNAR exhibited impaired interferon-stimulated gene (ISG) expression and, in the case of mice deficient in IRF3 or IFNAR, improved survival after MI as compared to controls. Interruption of IRF3-dependent signaling resulted in decreased cardiac expression of inflammatory cytokines and chemokines and decreased inflammatory cell infiltration of the heart, as well as in attenuated ventricular dilation and improved cardiac function. Similarly, treatment of mice with an IFNAR-neutralizing antibody after MI ablated the interferon response and improved left ventricular dysfunction and survival. These results identify IRF3 and the type I IFN response as a potential therapeutic target for post-MI cardioprotection.

In vivo T2* weighted MRI visualizes cardiac lesions in murine models of acute and chronic viral myocarditis.

OBJECTIVE: Acute and chronic forms of myocarditis are mainly induced by virus infections. As a consequence of myocardial damage and inflammation dilated cardiomyopathy and chronic heart failure may develop. The gold standard for the diagnosis of myocarditis is endomyocardial biopsies which are required to determine the etiopathogenesis of cardiac inflammatory processes. However, new non-invasive MRI techniques hold great potential in visualizing cardiac non-ischemic inflammatory lesions at high spatial resolution, which could improve the investigation of the pathophysiology of viral myocarditis. RESULTS: Here we present the discovery of a novel endogenous T2* MRI contrast of myocardial lesions in murine models of acute and chronic CVB3 myocarditis. The evaluation of infected hearts ex vivo and in vivo by 3D T2w and T2*w MRI allowed direct localization of virus-induced myocardial lesions without any MRI tracer or contrast agent. T2*w weighted MRI is able to detect both small cardiac lesions of acute myocarditis and larger necrotic areas at later stages of chronic myocarditis, which was confirmed by spatial correlation of MRI hypointensity in myocardium with myocardial lesions histologically. Additional in vivo and ex vivo MRI analysis proved that the contrast mechanism was due to a strong paramagnetic tissue alteration in the vicinity of myocardial lesions, effectively pointing towards iron deposits as the primary contributor of contrast. The evaluation of the biological origin of the MR contrast by specific histological staining and transmission electron microscopy revealed that impaired iron metabolism primarily in mitochondria caused iron deposits within necrotic myocytes, which induces strong magnetic susceptibility in myocardial lesions and results in strong T2* contrast. CONCLUSION: This T2*w MRI technique provides a fast and sensitive diagnostic tool to determine the patterns and the severity of acute and chronic enteroviral myocarditis and the precise localization of tissue damage free of MR contrast agents.

Polyglucose nanoparticles with renal elimination and macrophage avidity facilitate PET imaging in ischaemic heart disease.

Tissue macrophage numbers vary during health versus disease. Abundant inflammatory macrophages destruct tissues, leading to atherosclerosis, myocardial infarction and heart failure. Emerging therapeutic options create interest in monitoring macrophages in patients. Here we describe positron emission tomography (PET) imaging with 18F-Macroflor, a modified polyglucose nanoparticle with high avidity for macrophages. Due to its small size, Macroflor is excreted renally, a prerequisite for imaging with the isotope flourine-18. The particle's short blood half-life, measured in three species, including a primate, enables macrophage imaging in inflamed cardiovascular tissues. Macroflor enriches in cardiac and plaque macrophages, thereby increasing PET signal in murine infarcts and both mouse and rabbit atherosclerotic plaques. In PET/magnetic resonance imaging (MRI) experiments, Macroflor PET imaging detects changes in macrophage population size while molecular MRI reports on increasing or resolving inflammation. These data suggest that Macroflor PET/MRI could be a clinical tool to non-invasively monitor macrophage biology.

Inflammatory Molecule, PSGL-1, Deficiency Activates Macrophages to Promote Colorectal Cancer Growth through NFκB Signaling.

P-selectin glycoprotein ligand 1 (SELPLG/PSGL-1) is an inflammatory molecule that is functionally related to immune cell differentiation and leukocyte mobilization. However, the role of PSGL-1 in tumor development remains unknown. Therefore, this study investigates the mechanistic role of PSGL-1 in the development of intestinal tumors in colorectal cancer. ApcMin/+ mice are highly susceptible to spontaneous intestinal adenoma formation, and were crossbred with PSGL1-null mice to generate compound transgenic mice with a ApcMin/+;PSGL-1-/- genotype. The incidence and pathologic features of the intestinal tumors were compared between the ApcMin/+ mice and ApcMin/+;PSGL-1-/- mice. Importantly, PSGL-1-deficient mice showed increased susceptibility to develop intestinal tumors and accelerated tumor growth. Mechanistically, increased production of the mouse chemokine ligand 9 (CCL9/MIP-1γ) was found in the PSGL-1-deficient mice, and the macrophages are likely the major source of macrophage inflammatory protein-1 gamma (MIP-1γ). Studies in vitro demonstrated that macrophage-derived MIP-1γ promoted colorectal cancer tumor cell growth through activating NFκB signaling. Conversely, restoration of the PSGL-1 signaling via bone marrow transplantation reduced MIP-1γ production and attenuated the ability of ApcMin/+;PSGL-1-/- mice to generate intestinal tumors. In human colorectal cancer clinical specimens, the presence of PSGL-1-positive cells was associated with a favorable tumor-node-metastasis staging and decreased lymph node metastasis.Implications:PSGL-1 deficiency and inflammation render intestinal tissue more vulnerable to develop colorectal tumors through a MIP-1γ/NFκB signaling axis. Mol Cancer Res; 15(4); 467-77. ©2017 AACR.

Phosphoinositide 3-Kinase (PI3K) Subunit p110δ Is Essential for Trophoblast Cell Differentiation and Placental Development in Mouse.

Maternal PI3K p110δ has been implicated in smaller litter sizes in mice, but its underlying mechanism remains unclear. The placenta is an indispensable chimeric organ that supports mammalian embryonic development. Using a mouse model of genetic inactivation of PI3K p110δ (p110δ(D910A/D910A)), we show that fetuses carried by p110δ(D910A/D910A) females were growth retarded and showed increased mortality in utero mainly during placentation. The placentas in p110δ(D910A/D910A) females were anomalously anemic, exhibited thinner spongiotrophoblast layer and looser labyrinth zone, which indicate defective placental vasculogenesis. In addition, p110δ was detected in primary trophoblast giant cells (P-TGC) at early placentation. Maternal PI3K p110δ inactivation affected normal TGCs generation and expansion, impeded the branching of chorioallantoic placenta but enhanced the expression of matrix metalloproteinases (MMP-2, MMP-12). Poor vasculature support for the developing fetoplacental unit resulted in fetal death or gross growth retardation. These data, taken together, provide the first in vivo evidence that p110δ may play an important role in placental vascularization through manipulating trophoblast giant cell.

Imaging Macrophage and Hematopoietic Progenitor Proliferation in Atherosclerosis.

RATIONALE: Local plaque macrophage proliferation and monocyte production in hematopoietic organs promote progression of atherosclerosis. Therefore, noninvasive imaging of proliferation could serve as a biomarker and monitor therapeutic intervention. OBJECTIVE: To explore (18)F-FLT positron emission tomography-computed tomography imaging of cell proliferation in atherosclerosis. METHODS AND RESULTS: (18)F-FLT positron emission tomography-computed tomography was performed in mice, rabbits, and humans with atherosclerosis. In apolipoprotein E knock out mice, increased (18)F-FLT signal was observed in atherosclerotic lesions, spleen, and bone marrow (standardized uptake values wild-type versus apolipoprotein E knock out mice, 0.05 ± 0.01 versus 0.17 ± 0.01, P<0.05 in aorta; 0.13 ± 0.01 versus 0.28 ± 0.02, P<0.05 in bone marrow; 0.06 ± 0.01 versus 0.22 ± 0.01, P<0.05 in spleen), corroborated by ex vivo scintillation counting and autoradiography. Flow cytometry confirmed significantly higher proliferation of macrophages in aortic lesions and hematopoietic stem and progenitor cells in the spleen and bone marrow in these mice. In addition, (18)F-FLT plaque signal correlated with the duration of high cholesterol diet (r(2)=0.33, P<0.05). Aortic (18)F-FLT uptake was reduced when cell proliferation was suppressed with fluorouracil in apolipoprotein E knock out mice (P<0.05). In rabbits, inflamed atherosclerotic vasculature with the highest (18)F-fluorodeoxyglucose uptake enriched (18)F-FLT. In patients with atherosclerosis, (18)F-FLT signal significantly increased in the inflamed carotid artery and in the aorta. CONCLUSIONS: (18)F-FLT positron emission tomography imaging may serve as an imaging biomarker for cell proliferation in plaque and hematopoietic activity in individuals with atherosclerosis.