Graves' disease and the risk of five autoimmune diseases: A Mendelian randomization and colocalization study.

BACKGROUND: Epidemiological studies have consistently demonstrated a high prevalence of concurrent autoimmune diseases in individuals with Graves' disease (GD). OBJECTIVE: The objective of this study is to establish a causal association between GD and autoimmune diseases. METHODS: We employed a two-sample Mendelian randomization (MR) to infer a causal association between GD and five autoimmune diseases, namely rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), Crohn's disease (CD), ulcerative colitis (UC), and amyotrophic lateral sclerosis (ALS), in the East Asian and European population. Genetic correlations were explored through linkage disequilibrium score regression analysis (LDSC). Finally, colocalization analyses were performed to investigate possible genetic foundations. RESULTS: Bidirectional MR analysis indicated that genetically predicted GD increased the risk of RA (Odds Ratio (OR): 1.34, 95 % Confidence Interval (CI): 1.21 to 1.47, P < 0.001) and SLE (OR: 1.21, 95%CI: 1.08 to 1.35, P < 0.001) in the East Asian population. In contrast, we found that genetically predicted RA (OR: 1.14, 95%CI: 1.05 to 1.24, P = 0.002) and SLE (OR: 1.10, 95%CI: 1.03 to 1.17, P = 0.003) were associated with a higher risk of GD. The results have been partially validated in European cohorts. Colocalization analysis suggested the potential existence of shared causal variants between GD and other autoimmune diseases. In particular, gene ARID5B may play an important role in the incidence of autoimmune diseases. CONCLUSION: This study has confirmed that GD was associated with RA and SLE and found a possible key gene ARID5B. It may be necessary to strengthen detection to prevent the occurrence of comorbidities in clinical practice.

A gadoxetic acid-enhanced MRI-based model using LI-RADS v2018 features for preoperatively predicting Ki-67 expression in hepatocellular carcinoma.

PURPOSE: To construct a gadoxetic acid-enhanced MRI (EOB-MRI) -based multivariable model to predict Ki-67 expression levels in hepatocellular carcinoma (HCC) using LI-RADS v2018 imaging features. METHODS: A total of 121 patients with HCC who underwent EOB-MRI were enrolled in this study. The patients were divided into three groups according to Ki-67 cut-offs: Ki-67 ≥ 20% (n = 86) vs. Ki-67 < 20% (n = 35); Ki-67 ≥ 30% (n = 73) vs. Ki-67 < 30% (n = 48); Ki-67 ≥ 50% (n = 45) vs. Ki-67 < 50% (n = 76). MRI features were analyzed to be associated with high Ki-67 expression using logistic regression to construct multivariable models. The performance characteristic of the models for the prediction of high Ki-67 expression was assessed using receiver operating characteristic curves. RESULTS: The presence of mosaic architecture (p = 0.045), the presence of infiltrative appearance (p = 0.039), and the absence of targetoid hepatobiliary phase (HBP, p = 0.035) were independent differential factors for the prediction of high Ki-67 status (≥ 50% vs. < 50%) in HCC patients, while no features could predict high Ki-67 status with thresholds of 20% (≥ 20% vs. < 20%) and 30% (≥ 30% vs. < 30%) (p > 0.05). Four models were constructed including model A (mosaic architecture and infiltrated appearance), model B (mosaic architecture and targetoid HBP), model C (infiltrated appearance and targetoid HBP), and model D (mosaic architecture, infiltrated appearance and targetoid HBP). The model D yielded better diagnostic performance than the model C (0.776 vs. 0.669, p = 0.002), but a comparable AUC than model A (0.776 vs. 0.781, p = 0.855) and model B (0.776 vs. 0.746, p = 0.076). CONCLUSIONS: Mosaic architecture, infiltrated appearance and targetoid HBP were sensitive imaging features for predicting Ki-67 index ≥ 50% and EOB-MRI model based on LI-RADS v2018 features may be an effective imaging approach for the risk stratification of patients with HCC before surgery.

Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma.

BACKGROUND: Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options. PURPOSE: To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC). MATERIAL AND METHODS: A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve. RESULTS: Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; P = 0.008) and MRI (0.946 vs. 0.876; P = 0.003), whereas rim APHE on CT and MRI did not differ significantly (P = 0.809). CONCLUSION: The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

The status and risk factors for anxiety/depression in patients with atrophic chronic gastritis: a cross-sectional study.

BACKGROUND: Atrophic chronic gastritis (ACG) is a preneoplastic condition of gastric carcinoma. Numerous studies have shown anxiety and depression can affect gastrointestinal function, which may promote gastrointestinal disorders development and progression. Thus, we hypothesized that anxiety and depression may enhance the development and progression of ACG. In this study, we aimed to analyse risk factors for anxiety and depression in ACG patients and integrate these risk factors to construct an effective clinical prediction model. METHODS: In total, 118 ACG patients were included from July 2021 to May 2022. Anxiety and depression were assessed utilizing the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire-9 (PHQ-9). Data were collected on demographic characteristics, lifestyle, and dietary habits. Risk factors for anxiety and depression were explored with univariate analysis and multivariate stepwise logistic regression, and risk prediction models were built. RESULTS: Among 118 ACG patients, 36.4% had anxiety, 25.4% had depression, and 21.2% had both anxiety and depression. Poor sleep quality [odd ratio (OR) 4.32, 95% confidence interval (CI): 1.60-11.65, P=0.004] was positively associated with risk of anxiety, while smoking (OR 0.15, 95% CI: 0.03-0.68, P=0.014) and weekly exercise time (OR 0.89, 95% CI: 0.79-0.99, P=0.037) were negatively associated with risk of anxiety. The area under the receiver operating characteristic (ROC) curve was 80.3%, 95% CI: [0.722-0.885]. The sensitivity was 72.1%, and the specificity was 78.7%. Poor sleep quality (P<0.001, OR 23.89, 95% CI: 4.05-141.05), high salt diet (P=0.004, OR 6.94, 95% CI: 1.86-25.96), family history of tumours (P=0.020, OR 6.10, 95% CI: 1.33-27.93), and abdominal pain (P=0.018, OR 4.44, 95% CI: 1.29-15.23) were positively associated with the risk of depression, with an area under the ROC curve of 77.3%, 95% CI: 0.687-0.860. The sensitivity was 83.3%, and the specificity was 62.5%. CONCLUSIONS: Potential anxiety and depression in ACG patients can be identified early by referring to risk factors and protective factors. The prediction model could be used to detect anxiety and depression in ACG patients at their earliest stage and provide meaningful suggestions for ACG patients.

A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma.

PURPOSE: To identify imaging features of macrotrabecular-massive hepatocellular carcinoma (MTM-HCC) using LI-RADS v2018 and other imaging features and to develop a gadoxetic acid-enhanced MRI (EOB-MRI)-based model for pretreatment prediction of MTM-HCC. MATERIALS AND METHODS: A total of 93 patients with pathologically proven HCC (39 MTM-HCC and 54 non-MTM-HCC) were retrospectively evaluated with EOB-MRI at 3 T. Imaging analysis according to LI-RADS v2018 was evaluated by two readers. Univariate and multivariate analyses were performed to determine independent predictors for MTM-HCC. Different logistic regression models were built based on MRI features, including model A (enhancing capsule, blood products in mass and ascites), model B (enhancing capsule and ascites), model C (blood products in mass and ascites), and model D (blood products in mass and enhancing capsule). Diagnostic performance was assessed by receiver operating characteristic (ROC) curves. RESULTS: After multivariate analysis, absence of enhancing capsule (odds ratio = 0.102, p = 0.010), absence of blood products in mass (odds ratio = 0.073, p = 0.030), and with ascites (odds ratio = 55.677, p = 0.028) were identified as independent differential factors for the presence of MTM-HCC. Model A yielded a sensitivity, specificity, and AUC of 35.90% (21.20,52.80), 94.44% (84.60, 98.80), and 0.731 (0.629, 0.818). Model A achieved a comparable AUC than model D (0.731 vs. 0.699, p = 0.333), but a higher AUC than model B (0.731 vs. 0.644, p = 0.048) and model C (0.731 vs. 0.650, p = 0.005). CONCLUSION: The EOB-MRI-based model is promising for noninvasively predicting MTM-HCC and may assist clinicians in pretreatment decisions.

Development of a rapid neutralizing antibody test for SARS-CoV-2 and its application for neutralizing antibody screening and vaccinated serum testing.

Background: Since the outbreak of coronavirus disease (COVID-19), the high infection rate and mutation frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent, have contributed to the ongoing global pandemic. Vaccination has become the most effective means of controlling COVID-19. Traditional neutralizing tests of sera are complex and labor-intensive, therefore, a rapid test for detecting neutralizing antibodies and antibody status post-immunization is needed. Methods: Based on the fact that antibodies exhibit neutralizing activity by blocking the binding of the S protein receptor-binding domain (S-RBD) to ACE2, we developed a rapid neutralizing antibody test, ACE2-Block-ELISA. To evaluate the sensitivity and specificity, we used 54 positive and 84 negative serum samples. We also tested the neutralizing activities of monoclonal antibodies (mAbs) and 214 sera samples from healthy individuals immunized with the inactivated SARS-CoV-2 vaccine. Results: The sensitivity and specificity of the ACE2-Block ELISA were 96.3% and 100%, respectively. For neutralizing mAb screening, ch-2C5 was selected for its ability to block the ACE2-S-RBD interaction. A plaque assay confirmed that ch-2C5 neutralized SARS-CoV-2, with NT50 values of 4.19, 10.63, and 1.074 µg/mL against the SARS-CoV-2 original strain, and the Beta and Delta variants, respectively. For the immunized sera samples, the neutralizing positive rate dropped from 82.14% to 32.16% within 4 months post-vaccination. Conclusions: This study developed and validated an ACE2-Block-ELISA to test the neutralizing activities of antibodies. As a rapid, inexpensive and easy-to-perform method, this ACE2-Block-ELISA has potential applications in rapid neutralizing mAb screening and SARS-CoV-2 vaccine evaluation.

Identification and Validation of the Signatures of Infiltrating Immune Cells in the Eutopic Endometrium Endometria of Women With Endometriosis.

Endometriosis is an oestrogen-dependent chronic inflammatory process with primary symptoms including dysmenorrhea, chronic pelvic pain, and infertility. The immune environment of the endometrium is essential for successful embryo implantation and ongoing pregnancy. In this study, we assessed the composition, density, and distribution of infiltrating immune cells in the endometria of women with endometriosis. Gene expression profiles of endometrial samples were downloaded from the Gene Expression Omnibus (GEO) database. We found that the TNF signalling pathway, the IL-17 signalling pathway, and the MAPK signalling pathway were significantly enriched in the eutopic endometria of women with endometriosis. The fractions and proportion of infiltrating immune cells were estimated by the CIBERSORT, MCP-counter, and ImmuCellAI methods. We found that the proportions of CD8+ T cells, activated NK cells, and follicular helper T cells were significantly higher in the endometria of women with endometriosis than in the endometria of normal controls, while the proportions of M2 macrophages and resting mast cells were significantly lower in the eutopic endometria. In GSE120103 (n = 36), we found that elevated CD8+ T cells in endometriosis increased the risk of infertility (P = 0.0019). The area under the receiver operating characteristic (ROC) curve (AUC) of CD8+ T cells to distinguish fertile and infertile endometriosis was 0.914. In clinical samples (n = 40), we found that the proportions of CD8+ T cells and CD56+ NK cells were significantly higher in the eutopic endometria of women with endometriosis than in the endometria of normal controls, while the proportion of CD163+ macrophages were lower in the eutopic endometria. The AUCs of CD8+ T cells and CD163+ macrophages were 0.727 and 0.833, respectively, which indicated that CD8 and CD163 were potential diagnostic markers for endometriosis. In conclusion, our results demonstrated that increased CD8+ T cells and CD56+ NK cells and decreased CD163+ macrophages within the eutopic endometria of women with endometriosis reveal a proinflammatory feature in the endometrial immune environment and that elevated CD8+ T cells increase the risk of infertility in women with the disease.

Novel MRI technique for the quantification of biochemical deterioration in steroid-induced osteonecrosis of femoral head: a prospective diagnostic trial.

To explore the novel magnetic resonance imaging techniques, IVIM-DWI and IDEAL-IQ in detecting bone marrow fat and microcirculation in steroid-induced osteonecrosis of the femoral head (SIONFH). In this prospective study, 49 patients (80 hips) with SIONFH taking glucocorticoids and 24 healthy volunteers (48 hips) were recruited and assessed by T1WI, T2WI/fs, IDEAL-IQ and IVIM-DWI. The affected hips, contralateral asymptomatic hips and normal hips, as well as normal, penumbra and necrotic areas in the affected hips, were classified and evaluated. Imaging results were compared with histologic bone sections obtained from SIONFH patients undergoing surgery. The fat fraction (FF) and perfusion fraction (f) differences between groups were analyzed using analysis of variance, the LSD t-test, Pearson correlation analysis and ROC curve analysis. Our results demonstrate that IDEAL-IQ (FF) and IVIM-DWI (f) enable the classification of SIONFH at different ARCO stages. The FF was positively associated with the progression of the disease (r = 0.72), in contrast to f (r = -0.17). The FF and f were significantly different among the necrotic, penumbra and normal areas, and they were negatively correlated with each other (r = -0.37). The diagnostic sensitivity and specificity of IDEAL-IQ were 96.9% and 86.7%, and those of IVIM-DWI were 72.34% and 58.33%, respectively. The FF in contralateral asymptomatic hips was significantly higher than in normal hips, but no difference was found for f. IDEAL-IQ, and not IVIM-DWI, was identified to successfully detect bone marrow fat, which is beneficial to the diagnosis of the severity of SIONFH.

Cancer-Associated Fibroblast Heterogeneity: A Factor That Cannot Be Ignored in Immune Microenvironment Remodeling.

Cancer-associated fibroblasts (CAFs) are important, highly heterogeneous components of the tumor extracellular matrix that have different origins and express a diverse set of biomarkers. Different subtypes of CAFs participate in the immune regulation of the tumor microenvironment (TME). In addition to their role in supporting stromal cells, CAFs have multiple immunosuppressive functions, via membrane and secretory patterns, against anti-tumor immunity. The inhibition of CAFs function and anti-TME therapy targeting CAFs provides new adjuvant means for immunotherapy. In this review, we outline the emerging understanding of CAFs with a particular emphasis on their origin and heterogeneity, different mechanisms of their regulation, as well as their direct or indirect effect on immune cells that leads to immunosuppression.

Prediction of Microvascular Invasion in Hepatocellular Carcinoma With a Multi-Disciplinary Team-Like Radiomics Fusion Model on Dynamic Contrast-Enhanced Computed Tomography.

OBJECTIVE: To investigate microvascular invasion (MVI) of HCC through a noninvasive multi-disciplinary team (MDT)-like radiomics fusion model on dynamic contrast enhanced (DCE) computed tomography (CT). METHODS: This retrospective study included 111 patients with pathologically proven hepatocellular carcinoma, which comprised 57 MVI-positive and 54 MVI-negative patients. Target volume of interest (VOI) was delineated on four DCE CT phases. The volume of tumor core (V tc ) and seven peripheral tumor regions (V pt , with varying distances of 2, 4, 6, 8, 10, 12, and 14 mm to tumor margin) were obtained. Radiomics features extracted from different combinations of phase(s) and VOI(s) were cross-validated by 150 classification models. The best phase and VOI (or combinations) were determined. The top predictive models were ranked and screened by cross-validation on the training/validation set. The model fusion, a procedure analogous to multidisciplinary consultation, was performed on the top-3 models to generate a final model, which was validated on an independent testing set. RESULTS: Image features extracted from V tc +V pt(12mm) in the portal venous phase (PVP) showed dominant predictive performances. The top ranked features from V tc +V pt(12mm) in PVP included one gray level size zone matrix (GLSZM)-based feature and four first-order based features. Model fusion outperformed a single model in MVI prediction. The weighted fusion method achieved the best predictive performance with an AUC of 0.81, accuracy of 78.3%, sensitivity of 81.8%, and specificity of 75% on the independent testing set. CONCLUSION: Image features extracted from the PVP with V tc +V pt(12mm) are the most reliable features indicative of MVI. The MDT-like radiomics fusion model is a promising tool to generate accurate and reproducible results in MVI status prediction in HCC.

A Computed Tomography Nomogram for Assessing the Malignancy Risk of Focal Liver Lesions in Patients With Cirrhosis: A Preliminary Study.

PURPOSE: The detection and characterization of focal liver lesions (FLLs) in patients with cirrhosis is challenging. Accurate information about FLLs is key to their management, which can range from conservative methods to surgical excision. We sought to develop a nomogram that incorporates clinical risk factors, blood indicators, and enhanced computed tomography (CT) imaging findings to predict the nature of FLLs in cirrhotic livers. METHOD: A total of 348 surgically confirmed FLLs were included. CT findings and clinical data were assessed. All factors with P < 0.05 in univariate analysis were included in multivariate analysis. ROC analysis was performed, and a nomogram was constructed based on the multivariate logistic regression analysis results. RESULTS: The FLLs were either benign (n = 79) or malignant (n = 269). Logistic regression evaluated independent factors that positively affected malignancy. AFP (OR = 10.547), arterial phase hyperenhancement (APHE) (OR = 740.876), washout (OR = 0.028), satellite lesions (OR = 15.164), ascites (OR = 156.241), and nodule-in-nodule architecture (OR =27.401) were independent predictors of malignancy. The combined predictors had excellent performance in differentiating benign and malignant lesions, with an AUC of 0.959, a sensitivity of 95.24%, and a specificity of 87.5% in the training cohort and AUC of 0.981, sensitivity of 94.74%, and specificity of 93.33% in the test cohort. The C-index was 96.80%, and calibration curves showed good agreement between the nomogram predictions and the actual data. CONCLUSIONS: The nomogram showed excellent discrimination and calibration for malignancy risk prediction, and it may aid in making FLLs treatment decisions.

Diagnostic performance of LI-RADS for MRI and CT detection of HCC: A systematic review and diagnostic meta-analysis.

PURPOSE: To perform a meta-analysis evaluating the diagnostic accuracy of the Liver Imaging Reporting and Data System (LI-RADS) category ≥ 3 (LI-RADS 3-5v) for detecting hepatocellular carcinoma (HCC). METHOD: A systematic PubMed, Embase, and Web of Science electronic database search was performed for original diagnostic studies published through July 31, 2018. Statistical analysis included data pooling, forest plot construction, heterogeneity testing, meta-regression, and subgroup analyses. RESULTS: Eighteen studies (v2011, v2014 and v2017) involving 3386 patients were included in the meta-analysis. The pooled sensitivity and specificity of LI-RADS ≥ 3 for diagnosing HCC were 0.86 (95 % confidence interval (CI): 0.78-0.91) and 0.85 (95 % CI: 0.78-0.90), respectively. The area under the curve (AUC) was 0.92 (95 % CI: 0.89-0.94). Meta-regression analysis showed that the publication year, blinding to the reference standard and the number of readers were significant factors affecting heterogeneity. In subgroup analyses, magnetic resonance imaging (MRI) demonstrated higher sensitivity (0.82 vs. 0.73) and comparable specificity (0.79 vs. 0.78) than computed tomography (CT). For HCCs ≤30 mm, LI-RADS showed lower sensitivity of 0.72 and specificity of 0.80 compared with HCC of all sizes. LR-5 showed higher sensitivity and specificity than LR-3 (sensitivity: 0.67 vs. 0.07, P = 0.02; specificity: 0.93 vs. 0.75, p < 0.001) and higher sensitivity than LR-4 (sensitivity: 0.67 vs. 0.29, P = 0.02; specificity: 0.93 vs. 0.80, p = 0.75). LR ≥ 5 had higher specificity at the cost of decreased sensitivity than LR ≥ 3 (specificity: 0.94 vs. 0.68, p < 0.001; sensitivity: 0.66 vs. 0.74, P = 0.70) and LR ≥ 4 (specificity: 0.94 vs. 0.84, p < 0.001; sensitivity: 0.66 vs. 0.74, P = 0.77). CONCLUSIONS: LI-RADS ≥ 3 shows high diagnostic accuracy for HCCs, with a pooled sensitivity of 0.86 and specificity of 0.85. The specificity is higher for LR-5 and LR ≥ 5. However, further prospective studies on LI-RADS ≥ 3 are needed to elucidate its value for diagnosing small HCCs (≤20 mm).

Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features.

The noninvasive detection of tumor proliferation is of great value and the Ki-67 is a biomarker of tumor proliferation. We hypothesized that radiomics characteristics may be related to tumor proliferation. To evaluate whether computed tomography (CT) radiomics feature analyses could aid in assessing the Ki-67 marker index in hepatocellular carcinoma (HCC), we retrospectively analyzed preoperative CT findings of 74 patients with HCC. The texture feature calculations were computed from MaZda 4.6 software, and the sequential forward selection algorithm was used as the selection method. The correlation between radiomics features and the Ki-67 marker index, as well as the difference between low Ki-67 (<10%) and high Ki-67 (≥10%) groups were evaluated. A simple logistic regression model was used to evaluate the associations between texture features and high Ki-67, and receiver operating characteristic analysis was performed on important parameters to assess the ability of radiomics characteristics to distinguish the high Ki-67 group from the low Ki-67 group. Contrast, correlation, and inverse difference moment (IDM) were significantly different (P < 0.001) between the low and high Ki-67 groups. Contrast (odds ratio [OR] = 0.957; 95% confidence interval [CI]: 0.926-0.990, P = 0.01) and correlation (OR = 2.5☆105; 95% CI: 7.560-8.9☆109; P = 0.019) were considered independent risk factors for combined model building with logistic regression. Angular second moment (r = -0.285, P = 0.014), contrast (r = -0.449, P < 0.001), correlation (r = 0.552, P < 0.001), IDM (r = 0.458, P < 0.001), and entropy (r = 0.285, P = 0.014) strongly correlated with the Ki-67 scores. Contrast, correlation, and the combined predictor were predictive of Ki-67 status (P < 0.001), with areas under the curve ranging from 0.777 to 0.836. The radiomics characteristics of CT have potential as biomarkers for predicting Ki-67 status in patients with HCC. These findings suggest that the radiomics features of CT might be used as a noninvasive measure of cellular proliferation in HCC.

Clinical value of texture analysis in differentiation of urothelial carcinoma based on multiphase computed tomography images.

Identification of histologic grading of urothelial carcinoma still depends on histopathologic examination. As an emerging and promising imaging technology, radiomic texture analysis is a noninvasive technique and has been studied to differentiate various tumors. This study explored the value of computed tomography (CT) texture analysis for the differentiation of low-grade urothelial carcinoma (LGUC), high-grade urothelial carcinoma (HGUC), and their invasive properties.Radiologic data were analyzed retrospectively for 94 patients with pathologically proven urothelial carcinomas from November 2016 to April 2019. Pathologic examination demonstrated that tumors were: high grade in 43 cases, and low grade in 51 cases; and nonmuscle invasive (NMI) in 37 cases, and muscle invasive (MI) in 37 cases. Maximum tumor diameters on CT scan were manually outlined as regions of interest and 78 texture features were extracted automatically. Three-phasic CT images were used to measure texture parameters, which were compared with postoperative pathologic grading and invasive results. The independent sample t test or Mann-Whitney U test was used to compare differences in parameters. Receiver-operating characteristic curves for statistically significant parameters were used to confirm efficacy.Of the 78 features extracted from each phase of CT images, 26 (33%), 20 (26%), and 22 (28%) texture parameters were significant (P < .05) for differentiating LGUC from HGUC, while 19 (24%), 16 (21%), and 30 (38%) were significant (P < .05) for differentiating NMI from MI urothelial carcinoma. Highest areas the under curve for differentiating grading and invasive properties were obtained by variance (0.761, P < .001) and correlation (0.798, P < .001) on venous-phase CT images.Texture analysis has the potential to distinguish LGUC and HGUC, or NMI from MI urothelial carcinoma, before surgery.

Correlations between P53 Mutation Status and Texture Features of CT Images for Hepatocellular Carcinoma.

OBJECTIVES: To investigate the performance of texture analysis in characterizing P53 mutations of hepatocellular carcinomas (HCCs) based on computed tomography (CT). METHODS: A total of 63 HCC patients underwent CT scans and were tested for P53 mutations. Patients were divided into two groups of P53(-) and P53(+) according to the P53 scores. First- and second-order texture features were computed from the CT images and compared between groups using independent Student's t-test. A Spearman's correlation coefficient was used for correlations to assess the relationship between the different P53 sores and CT data. The performance of texture features in differentiating the P53 mutations of HCC was assessed using receiver operating characteristic analysis. RESULTS: The mean values of angular second moment (ASM; mean = 0.001) and contrast (mean = 194.727) for P53(-) were higher than those of P53(+). Meanwhile the mean values of correlation (mean = 0.735), sum variance (mean = 1,111.052), inverse difference moment (IDM; mean = 0.090), and entropy (mean = 3.016) for P53(-) were lower than those of P53(+). Significant correlations were found between P53 scores and ASM (r = - 0.439), contrast (r = - 0.263), correlation (r = 0.551), sum of squares (r = 0.282), sum variance (r = 0.417), IDM (r = 0.308), and entropy (r = 0.569). Five texture parameters (ASM, contrast, correlation, IDM, and entropy) were predictive of P53 mutation status, with areas under the curve ranging from 0.621 to 0.792. CONCLUSIONS: There was a direct relationship between P53 mutations and gray-level co-occurrence matrix, but not with histograms for HCC patients. Correlation and entropy seemed to be the most promising in differentiating P53 (-) from P53(+).

Meta-analysis of intravoxel incoherent motion magnetic resonance imaging in differentiating focal lesions of the liver.

INTRODUCTION: Accurate detection and characterization of focal liver lesions, including differentiation between malignant and benign lesions, are particularly important. The objective of this meta-analysis was to evaluate the parameters of intravoxel incoherent motion (IVIM), including apparent diffusion coefficient (ADC), pure molecular diffusion coefficient (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (f) in differentiating focal liver lesions. METHODS: IVIM method employed for focal liver lesion and the quality assessment of diagnostic studies were evaluated. Standardized mean differences and 95% confidence intervals were calculated. The heterogeneity was quantified with the I statistic. RESULTS: The difference between groups was analyzed according to the I values from 6 different studies using fixed effects or random effects models. Significant differences in ADC (P < .001) and D (P < .001) were observed between benign and malignant lesions. Moreover, significant differences in ADC (P < .001), D (P < .001), and f (P = .01) were found between hemangioma and hepatocellular carcinoma (HCC). In addition, no significant difference was observed between the metastases and HCC. CONCLUSIONS: D and ADC values were useful for the differentiation between benignity and malignancy; higher values of ADC, D, and f were observed in hemangioma compared to HCC. Nevertheless, IVIM did not result as the optimal approach for differentiation between the metastases and HCC.

Larsenimonas suaedae sp. nov., a moderately halophilic, endophytic bacterium isolated from the halophyte Suaeda salsa.

A moderately halophilic, Gram-stain-negative, non-endospore-forming endophytic bacterium designated strain ST307T was isolated from the euhalophyte Suaeda salsa in Dongying, China. Strain ST307T was aerobic, rod-shaped, motile and orange-yellow-pigmented. The organism grew at NaCl concentrations of 0.6-20 % (w/v) (optimum 5-6 %, w/v), at temperatures of 5-45 °C (optimum 35 °C) and at pH 5-9 (optimum pH 7-8). It accumulated poly-ß-hydroxybutyric acid and produced exopolysaccharides. The major fatty acids were C18 : 1ω7c/C18 : 1ω6c, C16 : 0 and C16 : 1ω7c/C16 : 1ω6c. The predominant lipoquinone was ubiquinone Q-9. The polar lipids consisted of phosphatidylethanolamine, phosphatidylglycerol, diphosphatidylglycerol, a glycoaminolipid and a phosphoglycoaminolipid. The DNA G+C content was 60.5 mol%. Phylogenetic analyses of 16S rRNA gene sequences and concatenated atpA, rpoD and secA gene sequences revealed that the strain represents a member of the genus Larsenimonas. The closest related type strain was Larsenimonas salina M1-18T. Mean DNA-DNA relatedness values between strain ST307T and the related species L. salina M1-18T, Chromohalobacter beijerinckii DSM 7218T, C. canadensis DSM 6769T, C. israelensis DSM 6768T, C. marismortui CGMCC 1.2321T, C. nigrandesensis DSM 14323T, C. salexigens DSM 3043T and C. sarecensis DSM 15547T were 15±2-45±1 %. On the basis of phenotypic, chemotaxonomic and molecular features, strain ST307T clearly represents a novel species of the genus Larsenimonas. The name Larsenimonassuaedae sp. nov. is proposed, with ST307T (=CGMCC 1.8902T=DSM 22428T) as the type strain.

Alteration of spontaneous neuronal activity in young adults with non-clinical depressive symptoms.

Non-clinical depressive symptoms (nCDSs) are highly prevalent in young adults and may be associated with the risk of developing full-fledged depressive disorders. However, the neural basis underlying nCDSs remains unknown. To explore the alteration of spontaneous brain activity in individuals with nCDSs compared with healthy controls (HCs), we investigated resting-state brain activity using the amplitude of low-frequency fluctuations (ALFF) in subjects with nCDSs (n=17) and HCs (n=20). All subjects were drawn from a sample of 1105 college students participating in a survey assessing depressive symptoms. We determined that nCDSs can lead to reduced ALFF in the right ventral lateral prefrontal cortex (VLPFC) and right dorsolateral prefrontal cortex (DLPFC) and to increased ALFF in the left fusiform, left posterior cerebellum, right cuneus, left inferior parietal lobule, right supramarginal gyrus and bilateral precuneus. In addition, with respect to Beck Depression Inventory (BDI) scores and ALFF values in subjects with nCDSs, a positive correlation was discovered in the right DLPFC, while a negative correlation was identified in left posterior cerebellum and bilateral precuneus after correction. These results indicate that nCDSs are characterized by altered spontaneous activity in several important functional regions. We suggest that altered ALFFs in the right DLPFC, left posterior cerebellum and bilateral precuneus may be biomarkers that are related to the pathophysiology of nCDSs in young adults.