Loss of Smooth Muscle Tenascin-X Inhibits Vascular Remodeling Through Increased TGF-ß Signaling.

BACKGROUND: Vascular smooth muscle cells (VSMCs) are highly plastic. Vessel injury induces a phenotypic transformation from differentiated to dedifferentiated VSMCs, which involves reduced expression of contractile proteins and increased production of extracellular matrix and inflammatory cytokines. This transition plays an important role in several cardiovascular diseases such as atherosclerosis, hypertension, and aortic aneurysm. TGF-ß (transforming growth factor-ß) is critical for VSMC differentiation and to counterbalance the effect of dedifferentiating factors. However, the mechanisms controlling TGF-ß activity and VSMC phenotypic regulation under in vivo conditions are poorly understood. The extracellular matrix protein TN-X (tenascin-X) has recently been shown to bind TGF-ß and to prevent it from activating its receptor. METHODS: We studied the role of TN-X in VSMCs in various murine disease models using tamoxifen-inducible SMC-specific knockout and adeno-associated virus-mediated knockdown. RESULTS: In hypertensive and high-fat diet-fed mice, after carotid artery ligation as well as in human aneurysmal aortae, expression of Tnxb, the gene encoding TN-X, was increased in VSMCs. Mice with smooth muscle cell-specific loss of TN-X (SMC-Tnxb-KO) showed increased TGF-ß signaling in VSMCs, as well as upregulated expression of VSMC differentiation marker genes during vascular remodeling compared with controls. SMC-specific TN-X deficiency decreased neointima formation after carotid artery ligation and reduced vessel wall thickening during Ang II (angiotensin II)-induced hypertension. SMC-Tnxb-KO mice lacking ApoE showed reduced atherosclerosis and Ang II-induced aneurysm formation under high-fat diet. Adeno-associated virus-mediated SMC-specific expression of short hairpin RNA against Tnxb showed similar beneficial effects. Treatment with an anti-TGF-ß antibody or additional SMC-specific loss of the TGF-ß receptor reverted the effects of SMC-specific TN-X deficiency. CONCLUSIONS: In summary, TN-X critically regulates VSMC plasticity during vascular injury by inhibiting TGF-ß signaling. Our data indicate that inhibition of vascular smooth muscle TN-X may represent a strategy to prevent and treat pathological vascular remodeling.

Nuclear miR-204-3p mitigates metabolic dysfunction-associated steatotic liver disease in mice.

BACKGROUND & AIMS: Accumulating evidence has indicated the presence of mature microRNAs (miR) in the nucleus, but their effects on steatohepatitis remain elusive. We have previously demonstrated that the intranuclear miR-204-3p in macrophages protects against atherosclerosis, which shares multiple risk factors with metabolic dysfunction-associated steatotic liver disease (MASLD). Herein, we aimed to explore the functional significance of miR-204-3p in steatohepatitis. METHODS: miR-204-3p levels and subcellular localization were assessed in the livers and peripheral blood mononuclear cells of patients with MASLD. Wild-type mice fed high-fat or methionine- and choline-deficient diets were injected with an adeno-associated virus system containing miR-204-3p to determine the effect of miR-204-3p on steatohepatitis. Co-culture systems were applied to investigate the crosstalk between macrophages and hepatocytes or hepatic stellate cells (HSCs). Multiple high-throughput epigenomic sequencings were performed to explore miR-204-3p targets. RESULTS: miR-204-3p expression decreased in livers and macrophages in mice and patients with fatty liver. In patients with MASLD, miR-204-3p levels in peripheral blood mononuclear cells were inversely related to the severity of hepatic inflammation and damage. Macrophage-specific miR-204-3p overexpression reduced steatohepatitis in high-fat or methionine- and choline-deficient diet-fed mice. miR-204-3p-overexpressing macrophages inhibited TLR4/JNK signaling and pro-inflammatory cytokine release, thereby limiting fat deposition and inflammation in hepatocytes and fibrogenic activation in HSCs. Epigenomic profiling identified miR-204-3p as a specific regulator of ULK1 expression. ULK1 transcription and VPS34 complex activation by intranuclear miR-204-3p improved autophagic flux, promoting the anti-inflammatory effects of miR-204-3p in macrophages. CONCLUSIONS: miR-204-3p inhibits macrophage inflammation, coordinating macrophage actions on hepatocytes and HSCs to ameliorate steatohepatitis. Macrophage miR-204-3p may be a therapeutic target for MASLD. IMPACT AND IMPLICATIONS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic inflammatory disease ranging from simple steatosis to steatohepatitis. However, the molecular mechanisms underlying the progression of MASLD remain incompletely understood. Here, we demonstrate that miR-204-3p levels in circulating peripheral blood mononuclear cells are negatively correlated with disease severity in patients with MASLD. Nuclear miR-204-3p activates ULK1 transcription and improves autophagic flux, limiting macrophage activation and hepatic steatosis. Our study provides a novel understanding of the mechanism of macrophage autophagy and inflammation in steatohepatitis and suggests that miR-204-3p may act as a potential therapeutic target for MASLD.

Disparate Radiation-Induced Microstructural Injuries in Whole-Brain White Matter of Patients With Nasopharyngeal Carcinoma: A Longitudinal Study Using Multishell Diffusion MRI.

BACKGROUND: Evidence for prevention strategies of radiotherapy (RT)-related injury in patients with nasopharyngeal carcinoma (NPC) was lacking. Understanding the dynamic alterations in the cerebral white matter (WM) microstructure after RT may be helpful. PURPOSE: To investigate the dynamic alterations in the whole brain WM microstructure in patients with NPC in the 12 months after RT using multishell diffusion MRI (MS-dMRI). STUDY TYPE: Single-center longitudinal study. POPULATION: A total of 28 treatment-naïve patients with pathologically confirmed NPC (age: 39.68 ± 8.93 years, 11 female) and 20 healthy controls (age: 40.65 ± 9.76 years, 7 female). FIELD STRENGTH/SEQUENCES: A 3 T, MS-dMRI using a single-shot echo planar imaging sequence. ASSESSMENT: MS-dMRI was acquired at baseline for the NPC patients and healthy controls, at 0-3 (acute, AC), 6 (early delayed, ED) and 12 months (late delayed, LD) after RT for the NPC patients. The mean and maximum radiation doses to the temporal lobe were acquired. The quality of images was reviewed. MS-dMRI was analyzed using tract-based spatial statistics (TBSS). The presentations of injury were defined by the findings of TBSS. STATISTICAL TESTS: Chi-square, t tests, repeated ANOVA, and Spearman-rank correlation analysis were used. P < 0.05 was considered to be statistically significant. RESULTS: TBSS showed two WM injuries (injuries 1 and 2). Injury 1 emerged in the ED phase in the bilateral temporal poles and persisted throughout the ED and LD phases. Injury 2 developed from the AC to ED phase in the bilateral hemisphere and partially recovered in the LD phase. In the ED and LD phases, the multiple diffusion metrics were well correlated (r > 0.5 or <-0.5) with the RT dose, especially in the WM tracts in the temporal lobes. DATA CONCLUSION: Disparate WM injuries were observed in NPC patients after RT. The injuries may be primarily or secondarily induced by radiation. Injury 1 may be irreversible, while injury 2 seems to partially recover. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 4.

Modulation Effects of the CEP128 Gene on Radiotherapy-Related Brain Injury: A Longitudinal Structural Study Using Multi-Parametric Brain MR Images.

BACKGROUND: The promoter variant rs17111237 in the CEP128 closely relates to radiotherapy (RT)-related brain necrosis in nasopharyngeal carcinoma (NPC) patients. PURPOSE: To explore RT-related dynamic alterations in brain morphology and their potential genetic mechanism, and to explore the modulatory effects of CEP128 genetic variants on RT-related brain morphological alterations in NPC patients. STUDY TYPE: Prospective, longitudinal. POPULATION: One hundred one patients with histopathologic ally-proven NPC (age 41.64 ± 9.63, 46 male), analyzed at baseline (pre-RT), 3-months post-RT and 6 months post-RT, and 19 sex-, age- and education-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3D gradient echo brain volume (3D-BRAVO) and diffusion-weighted single-shot spin-echo echo-planar sequences at 3.0 T. ASSESSMENT: rs17111237 in CEP128 was detected by Sanger sequencing. Structural and diffusion images were processed with FreeSurfer and FSL. Morphometric similarity network (MSN) was constructed with nine cortical indices derived from structural and diffusion images. STATISTICAL TESTS: One-way ANOVA, chi-square test. Pearson's correlation analysis was conducted to measure the relationship between CEP128 gene-expression level in human brain and MSN alterations. Repeated analysis of variance performed to assess group differences in MSN and the modulatory effects of the CEP128 gene within patients. Significance level: P < 0.05, false-discovery rate correction. RESULTS: RT-related significant widespread MSN alterations were observed in the cortices of NPC patients. Notably, regional MSN alterations had a weak but significant negative correlation with the cortical pattern of CEP128 gene expression (r = -0.152). Furthermore, rs17111237 in the CEP128 had significant modulatory effects on the observed MSN alterations in NPC patients, with the modulatory effects being most obvious at 3 months post-RT. CONCLUSIONS: MSN has potential to serve as a sensitive biomarker to detect RT-related brain injury. Inter-brain regional and inter-patient variability of RT-related brain injuries may be attributed to the cortical expression of the CEP128 gene and the modulatory effects of the promoter variant rs17111237 in CEP128. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Vascular smooth muscle-specific LRRC8A knockout ameliorates angiotensin II-induced cerebrovascular remodeling by inhibiting the WNK1/FOXO3a/MMP signaling pathway.

Hypertensive cerebrovascular remodeling involves the enlargement of vascular smooth muscle cells (VSMCs), which activates volume-regulated Cl- channels (VRCCs). The leucine-rich repeat-containing family 8 A (LRRC8A) has been shown to be the molecular identity of VRCCs. However, its role in vascular remodeling during hypertension is unclear. In this study, we used vascular smooth muscle-specific LRRC8A knockout (CKO) mice and an angiotensin II (Ang II)-induced hypertension model. The results showed that cerebrovascular remodeling during hypertension was ameliorated in CKO mice, and extracellular matrix (ECM) deposition was reduced. Based on the RNA-sequencing analysis of aortic tissues, the level of matrix metalloproteinases (MMPs), such as MMP-9 and MMP-14, were reduced in CKO mice with hypertension, which was further verified in vivo by qPCR and immunofluorescence analysis. Knockdown of LRRC8A in VSMCs inhibited the Ang II-induced upregulation of collagen I, fibronectin, and matrix metalloproteinases (MMPs), and overexpression of LRRC8A had the opposite effect. Further experiments revealed an interaction between with-no-lysine (K)-1 (WNK1), which is a "Cl--sensitive kinase", and Forkhead transcription factor O3a (FOXO3a), which is a transcription factor that regulates MMP expression. Ang II induced the phosphorylation of WNK1 and downstream FOXO3a, which then increased the expression of MMP-2 and MMP-9. This process was inhibited or potentiated when LRRC8A was knocked down or overexpressed, respectively. Overall, these results demonstrate that LRRC8A knockout in vascular smooth muscle protects against cerebrovascular remodeling during hypertension by reducing ECM deposition and inhibiting the WNK1/FOXO3a/MMP signaling pathway, demonstrating that LRRC8A is a potential therapeutic target for vascular remodeling-associated diseases such as stroke.

Engineered Cancer Cells as Signal Probes for Fluorescence-Assisted Digital Counting Analysis.

Fluorescence-assisted digital counting analysis allowed sensitive quantification of targets by measuring individual fluorescent labels. However, traditional fluorescent labels suffered from low brightness, small size, and sophisticated preparation procedures. Herein, engineering fluorescent dye-stained cancer cells with magnetic nanoparticles were proposed to construct single-cell probes for fluorescence-assisted digital counting analysis by quantifying the target-dependent binding or cleaving events. Various engineering strategies of cancer cells including biological recognition and chemical modification were developed for rationally designing single-cell probes. Introduction of suitable recognition elements into single-cell probes allowed digital quantification of each target-dependent event via counting the colored single-cell probes in the representative image taken using a confocal microscope. The reliability of the proposed digital counting strategy was corroborated by traditional optical microscopy- and flow cytometry-dependent counting technologies. The advantages of single-cell probes, including high brightness, big size, ease of preparation, and magnetic separation, contributed to the sensitive and selective analysis of targets of interest. As proof-to-concept assays, indirect analysis of exonuclease III (Exo III) activity, as well as direct quantitation of cancer cells, were investigated, and the potential in biological sample analysis was also assessed. This sensing strategy will open a new avenue for the development of biosensors.

Head and neck MRI-based T stage and [18F]FDG PET/CT-based N/M stage improved prognostic stratification in primary nasopharyngeal carcinoma.

OBJECTIVES: To evaluate whether MRI-based T stage (TMRI), [18F]FDG PET/CT-based N (NPET/CT), and M stage (MPET/CT) are superior in NPC patients' prognostic stratification based on long-term survival evidences, and whether TNM staging method involving TMRI + NPET/CT + MPET/CT could improve NPC patients' prognostic stratification. METHODS: From April 2007 to December 2013, 1013 consecutive untreated NPC patients with complete imaging data were enrolled. All patients' initial stages were repeated based on (1) the NCCN guideline recommended "TMRI + NMRI + MPET/CT" ("MMP") staging method; (2) the traditional "TMRI + NMRI + Mconventional work-up (CWU)" ("MMC") staging method; (3) the single-step "TPET/CT + NPET/CT + MPET/CT" ("PPP") staging method; or (4) the "TMRI + NPET/CT + MPET/CT" ("MPP") staging method recommended in present research. Survival curve, ROC curve, and net reclassification improvement (NRI) analysis were used to evaluate the prognosis predicting ability of different staging methods. RESULTS: [18F]FDG PET/CT performed worse on T stage (NRI = - 0.174, p < 0.001) but better on N (NRI = 0.135, p = 0.004) and M stage (NRI = 0.126, p = 0.001). The patients whose N stage upgraded by [18F]FDG PET/CT had worse survival (p = 0.011). The "TMRI + NPET/CT + MPET/CT" ("MPP") method performed better on survival prediction when compared with "MMP" (NRI = 0.079, p = 0.007), "MMC" (NRI = 0.190, p < 0.001), or "PPP" method (NRI = 0.107, p < 0.001). The "TMRI + NPET/CT + MPET/CT" ("MPP") method could reclassify patients' TNM stage to a more appropriate stage. The improvement is significant in patients with more than 2.5-years follow-up according to the time-dependent NRI values. CONCLUSIONS: The MRI is superior to [18F]FDG PET/CT in T stage, and [18F]FDG PET/CT is superior to CWU in N/M stage. The "TMRI + NPET/CT + MPET/CT" ("MPP") staging method could significantly improve NPC patients' long-term prognostic stratification. CLINICAL RELEVANCE STATEMENT: The present research provided long-term follow-up evidence for benefits of MRI and [18F]FDG PET/CT in TNM staging for nasopharyngeal carcinoma, and proposes a new imaging procedure for TNM staging incorporating MRI-based T stage and [18F]FDG PET/CT-based N and M stage, which significantly improves long-term prognostic stratification for patients with NPC. KEY POINTS: • The long-term follow-up evidence of a large-scale cohort was provided to evaluate the advantages of MRI, [18F]FDG PET/CT, and CWU in the TNM staging of nasopharyngeal carcinoma. • A new imaging procedure for TNM stage of nasopharyngeal carcinoma was proposed.

Divergent white matter changes in patients with nasopharyngeal carcinoma post-radiotherapy with different outcomes: a potential biomarker for prediction of radiation necrosis.

OBJECTIVES: To investigate the effects of standard radiotherapy on temporal white matter (WM) and its relationship with radiation necrosis (RN) in patients with nasopharyngeal carcinoma (NPC), and to determine the predictive value of WM volume alterations at the early stage for RN occurrence at the late-delay stage. METHODS: Seventy-four treatment-naive NPC patients treated with standard radiotherapy were longitudinally followed up for 36 months. Structural MRIs were collected at multiple time points during the first year post-radiotherapy. Longitudinal structural images were processed using FreeSurfer. Linear mixed models were used to delineate divergent trajectories of temporal WM changes between patients who developed RN and who did not. Four machine learning methods were used to construct predictive models for RN with temporal WM volume alterations at early-stage. RESULTS: The superior temporal gyrus (STG) had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy. Patients with RN showed more rapid atrophy than those with NRN. A predictive model constructed with temporal WM volume alterations at early-stage post-radiotherapy had good performance for RN; the areas under the curve (AUC) were 0.879 and 0.806 at 1-3 months and 6 months post-radiotherapy, respectively. Moreover, the predictive model constructed with absolute temporal volume at 1-3 months post-radiotherapy also presented good performance; the AUC was 0.842, which was verified by another independent dataset (AUC = 0.773). CONCLUSIONS: NPC patients with RN had more sharp atrophy in the STG than those with NRN. Temporal WM volume at early-stage post-radiotherapy may serve as an in vivo biomarker to identify and predict RN occurrence. KEY POINTS: • The STG had divergent atrophy trajectories in NPC patients with different outcomes (RN vs. NRN) post-radiotherapy. • Although both groups exhibited time-dependent atrophy in the STG, the patients with RN showed a more rapid volume decrease than those with NRN. • Temporal WM volume alteration (or absolute volume) at the early stage could predict RN occurrence at the late-delay stage after radiotherapy.

Glioma survival prediction from whole-brain MRI without tumor segmentation using deep attention network: a multicenter study.

OBJECTIVES: To develop and validate a deep learning model for predicting overall survival from whole-brain MRI without tumor segmentation in patients with diffuse gliomas. METHODS: In this multicenter retrospective study, two deep learning models were built for survival prediction from MRI, including a DeepRisk model built from whole-brain MRI, and an original ResNet model built from expert-segmented tumor images. Both models were developed using a training dataset (n = 935) and an internal tuning dataset (n = 156) and tested on two external test datasets (n = 194 and 150) and a TCIA dataset (n = 121). C-index, integrated Brier score (IBS), prediction error curves, and calibration curves were used to assess the model performance. RESULTS: In total, 1556 patients were enrolled (age, 49.0 ± 13.1 years; 830 male). The DeepRisk score was an independent predictor and can stratify patients in each test dataset into three risk subgroups. The IBS and C-index for DeepRisk were 0.14 and 0.83 in external test dataset 1, 0.15 and 0.80 in external dataset 2, and 0.16 and 0.77 in TCIA dataset, respectively, which were comparable with those for original ResNet. The AUCs at 6, 12, 24, 26, and 48 months for DeepRisk ranged between 0.77 and 0.94. Combining DeepRisk score with clinicomolecular factors resulted in a nomogram with a better calibration and classification accuracy (net reclassification improvement 0.69, p < 0.001) than the clinical nomogram. CONCLUSIONS: DeepRisk that obviated the need of tumor segmentation can predict glioma survival from whole-brain MRI and offers incremental prognostic value. KEY POINTS: • DeepRisk can predict overall survival directly from whole-brain MRI without tumor segmentation. • DeepRisk achieves comparable accuracy in survival prediction with deep learning model built using expert-segmented tumor images. • DeepRisk has independent and incremental prognostic value over existing clinical parameters and IDH mutation status.

Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.

OBJECTIVES: Develop and evaluate a deep learning-based automatic meningioma segmentation method for preoperative meningioma differentiation using radiomic features. METHODS: A retrospective multicentre inclusion of MR examinations (T1/T2-weighted and contrast-enhanced T1-weighted imaging) was conducted. Data from centre 1 were allocated to training (n = 307, age = 50.94 ± 11.51) and internal testing (n = 238, age = 50.70 ± 12.72) cohorts, and data from centre 2 external testing cohort (n = 64, age = 48.45 ± 13.59). A modified attention U-Net was trained for meningioma segmentation. Segmentation accuracy was evaluated by five quantitative metrics. The agreement between radiomic features from manual and automatic segmentations was assessed using intra class correlation coefficient (ICC). After univariate and minimum-redundancy-maximum-relevance feature selection, L1-regularized logistic regression models for differentiating between low-grade (I) and high-grade (II and III) meningiomas were separately constructed using manual and automatic segmentations; their performances were evaluated using ROC analysis. RESULTS: Dice of meningioma segmentation for the internal testing cohort were 0.94 ± 0.04 and 0.91 ± 0.05 for tumour volumes in contrast-enhanced T1-weighted and T2-weighted images, respectively; those for the external testing cohort were 0.90 ± 0.07 and 0.88 ± 0.07. Features extracted using manual and automatic segmentations agreed well, for both the internal (ICC = 0.94, interquartile range: 0.88-0.97) and external (ICC = 0.90, interquartile range: 0.78-70.96) testing cohorts. AUC of radiomic model with automatic segmentation was comparable with that of the model with manual segmentation for both the internal (0.95 vs. 0.93, p = 0.176) and external (0.88 vs. 0.91, p = 0.419) testing cohorts. CONCLUSIONS: The developed deep learning-based segmentation method enables automatic and accurate extraction of meningioma from multiparametric MR images and can help deploy radiomics for preoperative meningioma differentiation in clinical practice. KEY POINTS: • A deep learning-based method was developed for automatic segmentation of meningioma from multiparametric MR images. • The automatic segmentation method enabled accurate extraction of meningiomas and yielded radiomic features that were highly consistent with those that were obtained using manual segmentation. • High-grade meningiomas were preoperatively differentiated from low-grade meningiomas using a radiomic model constructed on features from automatic segmentation.

Multi-parametric Z-spectral MRI may have a good performance for glioma stratification in clinical patients.

OBJECTIVES: To comprehensively and noninvasively risk-stratify glioma grade, isocitrate dehydrogenase (IDH) genotype, and 1p/19q codeletion status using multi-contrast Z-spectral magnetic resonance imaging (MRI). METHODS: One hundred and thirteen patients with glioma were retrospectively included. Multiple contrasts contributing to Z-spectra, including direct saturation of water (DSW), semi-solid magnetization transfer contrast (MTC), amide proton transfer (APT) effect, aliphatic nuclear Overhauser effect, and the 2-ppm chemical exchange saturation transfer peak (CEST@2ppm), were fitted with five individual Lorentzian functions. Z-spectral contrasts were compared according to the three most important risk stratifications: tumor grade, IDH genotype, and 1p/19q codeletion status. We further investigated the differentiation of 1p/19q codeletion status within IDH mutant gliomas. The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic (ROC) analyses. RESULTS: DSW was significantly different within grade, IDH genotypes, and 1p/19q codeletion status. APT was significantly different with grade and IDH mutation, but not with 1p/19q subtypes. CEST@2ppm was only significantly different with 1p/19q codeletion subtypes. DSW and CEST@2ppm were the two Z-spectral contrasts able to differentiate 1p/19q codeletion subtypes within IDH mutant gliomas. For differentiating glioma grades using ROC analyses, DSW achieved the largest AUC. For differentiating IDH genotypes, DSW and APT achieved comparable AUCs. DSW was the best metric for differentiating 1p/19q codeletion status within all patients and within the IDH mutant patients. Combining all Z-spectral contrasts improved sensitivity and specificity for all risk stratifications. CONCLUSIONS: Multi-parametric Z-spectral MRI serves as a useful, comprehensive, and noninvasive imaging technique for glioma stratification in clinical patients. KEY POINTS: • Multiple contrasts contributing to Z-spectra were separately fitted with Lorentzian functions. • Z-spectral contrasts were compared within the three most important and common tumor risk stratifications for gliomas: tumor grade, IDH genotype, and 1p/19q codeletion status. • The stratification performance of individual Z-spectral contrasts and their combination was quantified using receiver operating characteristic analyses, which found Z-spectral MRI to be a useful and comprehensive imaging biomarker for glioma stratification.

Platelet CFTR inhibition enhances arterial thrombosis via increasing intracellular Cl- concentration and activation of SGK1 signaling pathway.

Platelet hyperactivity is essential for thrombus formation in coronary artery diseases (CAD). Dysfunction of the cystic fibrosis transmembrane conductance regulator (CFTR) in patients with cystic fibrosis elevates intracellular Cl- levels ([Cl-]i) and enhanced platelet hyperactivity. In this study, we explored whether alteration of [Cl-]i has a pathological role in regulating platelet hyperactivity and arterial thrombosis formation. CFTR expression was significantly decreased, while [Cl-]i was increased in platelets from CAD patients. In a FeCl3-induced mouse mesenteric arteriole thrombosis model, platelet-specific Cftr-knockout and/or pre-administration of ion channel inhibitor CFTRinh-172 increased platelet [Cl-]i, which accelerated thrombus formation, enhanced platelet aggregation and ATP release, and increased P2Y12 and PAR4 expression in platelets. Conversely, Cftr-overexpressing platelets resulted in subnormal [Cl-]i, thereby decreasing thrombosis formation. Our results showed that clamping [Cl-]i at high levels or Cftr deficiency-induced [Cl-]i increasement dramatically augmented phosphorylation (Ser422) of serum and glucocorticoid-regulated kinase (SGK1), subsequently upregulated P2Y12 and PAR4 expression via NF-κB signaling. Constitutively active mutant S422D SGK1 markedly increased P2Y12 and PAR4 expression. The specific SGK1 inhibitor GSK-650394 decreased platelet aggregation in wildtype and platelet-specific Cftr knockout mice, and platelet SGK1 phosphorylation was observed in line with increased [Cl-]i and decreased CFTR expression in CAD patients. Co-transfection of S422D SGK1 and adenovirus-induced CFTR overexpression in MEG-01 cells restored platelet activation signaling cascade. Our results suggest that [Cl-]i is a novel positive regulator of platelet activation and arterial thrombus formation via the activation of a [Cl-]i-sensitive SGK1 signaling pathway. Therefore, [Cl-]i in platelets is a novel potential biomarker for platelet hyperactivity, and CFTR may be a potential therapeutic target for platelet activation in CAD.

Macrophage NFATc3 prevents foam cell formation and atherosclerosis: evidence and mechanisms.

AIMS: Our previous study demonstrated that Ca2+ influx through the Orai1 store-operated Ca2+ channel in macrophages contributes to foam cell formation and atherosclerosis via the calcineurin-ASK1 pathway, not the classical calcineurin-nuclear factor of activated T-cell (NFAT) pathway. Moreover, up-regulation of NFATc3 in macrophages inhibits foam cell formation, suggesting that macrophage NFATc3 is a negative regulator of atherogenesis. Hence, this study investigated the precise role of macrophage NFATc3 in atherogenesis. METHODS AND RESULTS: Macrophage-specific NFATc3 knockout mice were generated to determine the effect of NFATc3 on atherosclerosis in a mouse model of adeno-associated virus-mutant PCSK9-induced atherosclerosis. NFATc3 expression was decreased in macrophages within human and mouse atherosclerotic lesions. Moreover, NFATc3 levels in peripheral blood mononuclear cells from atherosclerotic patients were negatively associated with plaque instability. Furthermore, macrophage-specific ablation of NFATc3 in mice led to the atherosclerotic plaque formation, whereas macrophage-specific NFATc3 transgenic mice exhibited the opposite phenotype. NFATc3 deficiency in macrophages promoted foam cell formation by potentiating SR-A- and CD36-meditated lipid uptake. NFATc3 directly targeted and transcriptionally up-regulated miR-204 levels. Mature miR-204-5p suppressed SR-A expression via canonical regulation. Unexpectedly, miR-204-3p localized in the nucleus and inhibited CD36 transcription. Restoration of miR-204 abolished the proatherogenic phenotype observed in the macrophage-specific NFATc3 knockout mice, and blockade of miR-204 function reversed the beneficial effects of NFATc3 in macrophages. CONCLUSION: Macrophage NFATc3 up-regulates miR-204 to reduce SR-A and CD36 levels, thereby preventing foam cell formation and atherosclerosis, indicating that the NFATc3/miR-204 axis may be a potential therapeutic target against atherosclerosis.

Biologic Pathways Underlying Prognostic Radiomics Phenotypes from Paired MRI and RNA Sequencing in Glioblastoma.

Background The biologic meaning of prognostic radiomics phenotypes remains poorly understood, hampered in part by lack of multicenter reproducible evidence. Purpose To uncover the biologic meaning of individual prognostic radiomics phenotypes in glioblastomas using paired MRI and RNA sequencing data and to validate the reproducibility of the identified radiogenomics linkages externally. Materials and Methods This retrospective multicenter study included four data sets gathered between January 2015 and December 2016. From a radiomics analysis set, a 13-feature radiomics signature was built using preoperative MRI for overall survival prediction. Using a radiogenomics training set with both MRI and RNA sequencing, biologic pathways were enriched and correlated with each of the 13 radiomics phenotypes. Radiomics-correlated key genes were identified to derive a prognostic radiomics gene expression (RadGene) score. The reproducibility of identified pathways and genes was validated with an external test set and a public data set (The Cancer Genome Atlas [TCGA]). A log-rank test was performed to assess prognostic significance. Results A total of 435 patients (mean age, 55 years ± 15 [standard deviation]; 263 men) were enrolled. The radiomics signature was associated with overall survival (hazard ratio [HR], 3.68; 95% CI: 2.08, 6.52; P < .001) in the radiomics validation subset. Four types of prognostic radiomics phenotypes were correlated with distinct pathways: immune, proliferative, treatment responsive, and cellular functions (false-discovery rate < 0.10). Thirty radiomics-correlated genes were identified. The prognostic significance of the RadGene score was confirmed in an external test set (HR, 2.02; 95% CI: 1.19, 3.41; P = .01) and a TCGA test set (HR, 1.43; 95% CI: 1.001, 2.04; P = .048). The radiomics-associated pathways and key genes can be replicated in an external test set. Conclusion Individual radiomics phenotypes on MRI scans predictive of overall survival were driven by distinct key pathways involved in immune regulation, tumor proliferation, treatment responses, and cellular functions in glioblastoma, which could be reproduced externally. © RSNA, 2021 Online supplemental material is available for this article.

Nomogram for the prediction of primary distant metastasis of nasopharyngeal carcinoma to guide individualized application of FDG PET/CT.

PURPOSE: This study aimed to establish an effective nomogram to predict primary distant metastasis (DM) in patients with nasopharyngeal carcinoma (NPC) to guide the application of PET/CT. METHODS: In total, 3591 patients with pathologically confirmed NPC were consecutively enrolled. The nomogram was constructed based on 1922 patients treated between 2007 and 2014. Multivariate logistical regression was applied to identify the independent risk factors of DM. The predictive value of the nomogram was evaluated using the concordance index (C-index), calibration curve, probability density functions (PDFs), and clinical utility curve (CUC). The results were validated in 1669 patients enrolled from 2015 to 2016. Net reclassification improvement (NRI) was applied to compare performances of the nomogram with other clinical factors. The best cut-off value of the nomogram chosen for clinical application was analyzed. RESULTS: A total of 355 patients showed primary DM among 3591 patients, yielding an incidence rate of 9.9%. Sex, N stage, EBV DNA level, lactate dehydrogenase level, and hemoglobin level were independent predictive factors for primary DM. C-indices in the training and validation cohort were 0.796 (95% CI, 0.76-0.83) and 0.779 (95% CI, 0.74-0.81), respectively. The NRI indices demonstrated that this model had better predictive performance than plasma EBV DNA level and N stage. We advocate for a threshold probability of 3.5% for guiding the application of PET/CT depending on the clinical utility analyses. CONCLUSION: This nomogram is a useful tool to predict primary DM of NPC and guide the clinical application of PET/CT individually at the initial staging.

Deep Learning With 3D Convolutional Neural Network for Noninvasive Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

BACKGROUND: Microvascular invasion (MVI) is a critical prognostic factor of hepatocellular carcinoma (HCC). However, it could only be obtained by postoperative histological examination. PURPOSE: To develop an end-to-end deep-learning models based on MRI images for preoperative prediction of MVI in HCC patients who underwent surgical resection. STUDY TYPE: Retrospective. POPULATION: Two hundred and thirty-seven patients with histologically confirmed HCC. FIELD STRENGTH: 1.5 T and 3.0 T. SEQUENCE: Axial T2 -weighted (T2 -w) with turbo spin echo sequence, T2 -Spectral Presaturation with Inversion Recovery (T2 -SPIR), and dynamic contrast-enhanced (DCE) imaging with fat suppressed enhanced T1 high-resolution isotropic volume examination. ASSESSMENT: The patients were randomly divided into training (N = 158) and validation (N = 79) sets. Data augmentation by random rotation was performed on the training set and the sample size increased to 1940 for each MR sequence. A three-dimensional convolutional neural network (3D CNN) was used to develop four deep-learning models, including three single-layer models based on single-sequence, and fusion model combining three sequences. MVI status was obtained from the postoperative pathology reports. STATISTICAL TESTS: The dice similarity coefficient (DSC) and Hausdorff distance (HD) were applied to assess the similarity and reproducibility between the manual segmentations of tumor from two radiologists. Receiver operating characteristic curve analysis was used to evaluate model performance. MVI was identified in 92 (38.8%) patients. Good reproducibility with interobserver DSCs of 0.90, 0.89, and 0.89 and HDs of 4.09, 3.67, and 3.60 was observed for PVP, T2 WI, and T2 -SPIR, respectively. The fusion model achieved an area under the curve (AUC) of 0.81, sensitivity of 69%, and specificity of 79% in the training set and 0.72, sensitivity of 55%, and specificity of 81% in the validation set. DATA CONCLUSION: 3D CNN model may serve as a noninvasive tool to predict MVI in HCC, whereas its accuracy needs to be enhanced with larger cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Low value of whole-body dual-modality [18f]fluorodeoxyglucose positron emission tomography/computed tomography in primary staging of stage I-II nasopharyngeal carcinoma: a nest case-control study.

OBJECTIVES: The value of using PET/CT for staging of stage I-II NPC remains unclear. Hence, we aimed to investigate the survival benefit of PET/CT for staging of early-stage NPC before radical therapy. METHODS: A total of 1003 patients with pathologically confirmed NPC of stages I-II were consecutively enrolled. Among them, 218 patients underwent both PET/CT and conventional workup ([CWU], head-and-neck MRI, chest radiograph, liver ultrasound, bone scintigraphy) before treatment. The remaining 785 patients only underwent CWU. The standard of truth (SOT) for lymph node metastasis was defined by the change of size according to follow-up MRI. The diagnostic efficacies were compared in 218 patients who underwent both PET/CT and CWU. After covariate adjustment using propensity scoring, a cohort of 872 patients (218 with and 654 without pre-treatment PET/CT) was included. The primary outcome was overall survival based on intention to treat. RESULTS: Retropharyngeal lymph nodes were metastatic based on follow-up MRI in 79 cases. PET/CT was significantly less sensitive than MRI in detecting retropharyngeal lymph node lesions (72.2% [62.3-82.1] vs. 91.1% [84.8-97.4], p = 0.004). Neck lymph nodes were metastatic in 89 cases and PET/CT was more sensitive than MRI (96.6% [92.8-100.0] vs. 76.4% [67.6-85.2], p < 0.001). In the survival analyses, there was no association between pre-treatment PET/CT use and improved overall survival, progression-free survival, local relapse-free survival, regional relapse-free survival, and distant metastasis-free survival. CONCLUSIONS: This study showed PET/CT is of little value for staging of stage I-II NPC patients at initial imaging. KEY POINTS: • PET/CT was more sensitive than MRI in detecting neck lymph node lesions whereas it was significantly less sensitive than MRI in detecting retropharyngeal lymph node lesions. • No association existed between pre-treatment PET/CT use and improved survival in stage I-II NPC patients.

Reduced intracellular chloride concentration impairs angiogenesis by inhibiting oxidative stress-mediated VEGFR2 activation.

Chloride (Cl-) homeostasis is of great significance in cardiovascular system. Serum Cl- level is inversely associated with the mortality of patients with heart failure. Considering the importance of angiogenesis in the progress of heart failure, this study aims to investigate whether and how reduced intracellular Cl- concentration ([Cl-]i) affects angiogenesis. Human umbilical endothelial cells (HUVECs) were treated with normal Cl- medium or low Cl- medium. We showed that reduction of [Cl-]i (from 33.2 to 16.18 mM) inhibited HUVEC proliferation, migration, cytoskeleton reorganization, tube formation, and subsequently suppressed angiogenesis under basal condition, and VEGF stimulation or hypoxia treatment. Moreover, VEGF-induced NADPH-mediated reactive oxygen species (ROS) generation and VEGFR2 axis activation were markedly attenuated in low Cl- medium. We revealed that lowering [Cl-]i inhibited the expression of the membrane-bound catalytic subunits of NADPH, i.e., p22phox and Nox2, and blunted the translocation of cytosolic regulatory subunits p47phox and p67phox, thereby restricting NADPH oxidase complex formation and activation. Furthermore, reduced [Cl-]i enhanced ROS-associated protein tyrosine phosphatase 1B (PTP1B) activity and increased the interaction of VEGFR2 and PTP1B. Pharmacological inhibition of PTP1B reversed the effect of lowering [Cl-]i on VEGFR2 phosphorylation and angiogenesis. In mouse hind limb ischemia model, blockade of Cl- efflux using Cl- channel inhibitors DIDS or DCPIB (10 mg/kg, i.m., every other day for 2 weeks) significantly enhanced blood flow recovery and new capillaries formation. In conclusion, decrease of [Cl-]i suppresses angiogenesis via inhibiting oxidase stress-mediated VEGFR2 signaling activation by preventing NADPH oxidase complex formation and promoting VEGFR2/PTP1B association, suggesting that modulation of [Cl-]i may be a novel therapeutic avenue for the treatment of angiogenic dysfunction-associated diseases.

Diagnostic performance of multiparametric MRI in the evaluation of treatment response in glioma patients at 3T.

BACKGROUND: MRI is one of the most important techniques to assess the treatment response of gliomas. However, differentiating tumor recurrence (TuR) from treatment effects (TrE) remains challenging. PURPOSE: To compare the diagnostic performance of MR diffusion-weighted imaging (DWI), arterial spin labeling (ASL), proton MR spectroscopy (MRS), and amide proton transfer (APT) imaging in differentiating between TuR and TrE in posttreatment glioma patients. STUDY TYPE: Prospective. POPULATION: Thirty patients with suspected tumor progression. FIELD STRENGTH/SEQUENCE: DWI, ASL, proton MRS, and APT imaging were performed at 3T MR. ASSESSMENT: MR indices, including ADC, relative cerebral blood flow (rCBF), ratios of Cho/Cr, Cho/NAA, and NAA/Cr and APT-weighted (APTw) effect were obtained from DWI, ASL, proton MRS, and APT imaging, respectively. Indices were measured in the contralateral normal-appearing white matter and lesions defined on the Gd-enhanced T1 w image. TuR or TrE was either determined histologically or clinically from longitudinal MRI follow-up for at least 6 months. STATISTICAL TESTS: The diagnostic performance of the indices was evaluated using Student's t-test, receiver operating characteristic (ROC) curve, and multivariate logistic regression analyses. RESULTS: Among the 30 patients, 16 were diagnosed as having TuR and the rest having TrE. The recurrent tumors showed a significantly higher APTw effect (1.56 ± 1.14%) and rCBF (1.44 ± 0.61) compared with lesions representing treatment effects (-0.44 ± 1.34% and 0.72 ± 0.25, respectively, with P < 0.001). The areas under the curve (AUCs) were 0.87 and 0.90 for APTw and rCBF, respectively, in differentiating between TuR and TrE. Combining APTw and rCBF achieved a higher AUC of 0.93. MRS index ratios of Cho/Cr (P = 0.25), Cho/NAA (P = 0.16), and NAA/Cr (P = 0.86) and ADC (P = 0.37) showed no significant differences between TuR and TrE lesions, with AUCs lower than 0.70. DATA CONCLUSION: Compared with DWI and MRS, ASL and APT imaging techniques showed better diagnostic capability in distinguishing TuR from TrE. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2020;51:1154-1161.

Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI.

BACKGROUND: It is difficult to prospectively differentiate between benign (World Health Organization [WHO] I) and nonbenign (WHO II and III) meningiomas. PURPOSE: To evaluate the feasibility of preoperative differentiation between benign and nonbenign meningiomas by using texture analysis from multiparametric MR data. STUDY TYPE: Retrospective. SUBJECTS: In all, 184 patients with meningioma (139 benign and 45 nonbenign) were included as the training cohort and 79 patients with meningioma (60 benign and 19 nonbenign) were included as the external validation cohort. FIELD STRENGTH/SEQUENCE: T1 -weighted, T2 -weighted, and contrast-enhanced T1 -weighted imaging were performed on 1.5 or 3.0T MR systems from two centers. ASSESSMENT: Tumor segmentation and radiological characteristic (RC) evaluation were performed by experienced radiologists. The texture features were extracted from preprocessed images and combined with RCs, and then the combined features were reduced by using a two-step feature selection. Three single-sequence models and a multiparametric MRI (the combination of single sequences) model were constructed and then evaluated with the external validation cohort. STATISTICAL TESTS: Area under receiver operating characteristic curve (AUC), accuracy (Acc), f1-score (F1), sensitivity (Sen), and specificity (Spec), were calculated to quantify the performance of the models. RESULTS: Among the four texture models, the multiparametric MRI model demonstrated the best performance for differentiating between benign and nonbenign meningiomas in both the training and external validation cohorts (AUC 0.91, Acc 89%, F1 0.88, Sen 0.93, and Spec 0.87 in the training cohort; AUC 0.83, Acc 80%, F1 0.77, Sen 0.84, and Spec 0.78 in the validation cohort). DATA CONCLUSION: Nonbenign meningiomas might be preoperatively differentiated from benign meningiomas by using texture analysis from multiparametric MR data. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;51:1810-1820.