Dysfunction of neurovascular coupling in patients with cerebral small vessel disease: A combined resting-state fMRI and arterial spin labeling study.

BACKGROUND: Cerebral small vessel disease (CSVD) closely correlates to cognitive impairment, but its pathophysiology and the neurovascular mechanisms of cognitive deficits were unclear. We aimed to explore the dysfunctional patterns of neurovascular coupling (NVC) in patients with CSVD and further investigate the neurovascular mechanisms of CSVD-related cognitive impairment. METHODS: Forty-three patients with CSVD and twenty-four healthy controls were recruited. We adopted resting-state functional magnetic resonance imaging combined with arterial spin labeling to investigate the NVC dysfunctional patterns in patients with CSVD. The Human Brain Atlas with 246 brain regions was applied to extract the NVC coefficients for each brain region. Partial correlation analysis and mediation analysis were used to explore the relationship between CSVD pathological features, NVC dysfunctional patterns, and cognitive decline. RESULTS: 8 brain regions with NVC dysfunction were found in patients with CSVD (p < 0.025, Bonferroni correction). The NVC dysfunctional patterns in regions of the default mode network and subcortical nuclei were negatively associated with lacunes, white matter hyperintensities burden, and the severity of CSVD (FDR correction, q < 0.05). The NVC decoupling in regions located in the default mode network positively correlated with delayed recall deficits (FDR correction, q < 0.05). Mediation analysis suggested that the decreased NVC pattern of the left superior frontal gyrus partially mediated the impact of white matter hyperintensities on delayed recall (Mediation effect: -0.119; 95%CI: -11.604,-0.458; p < 0.05). CONCLUSION: The findings of this study reveal the NVC dysfunctional pattern in patients with CSVD and illustrate the neurovascular mechanism of CSVD-related cognitive impairment. The NVC function in the left superior frontal gyrus may serve as a promising biomarker and therapeutic target for memory deficits in patients with CSVD.

Development and validation of a clinical-radiomics nomogram for predicting a poor outcome and 30-day mortality after a spontaneous intracerebral hemorrhage.

Background: Noncontrast computed tomography (NCCT) is often performed for patients with a suspected spontaneous intracerebral hemorrhage (ICH) at the time of admission. Both clinical and radiomic features on the initial NCCT can predict the outcomes of those with ICH, but satisfactory model performance remains challenging. Methods: A total of 258 acute ICH patients from the Central Hospital of Wuhan (CHW) between January 2018 and December 2020 were retrospectively assigned to training and internal validation cohorts at a ratio of 7:3. An independent external testing cohort of 87 patients from January 2021 to July 2021 from the Fifth Affiliated Hospital of Nanchang University (FAHNU) was also used. Based on the least absolute shrinkage and selection operator (LASSO) algorithm, radiomics (rad)-scores were generated from 9 quantitative features on the initial NCCT images. Three models (radiomics, clinical, and hybrid) were established using stepwise logistic regression analysis. The Akaike information criterion and the likelihood ratio test were used to compare the goodness of fit of the three models. Receiver operating characteristic (ROC) curve analysis was performed and bar charts were constructed to evaluate the discrimination of constructed model for predicting a poor outcome following ICH. Results: The three cohorts had similar baseline clinical characteristics, including demographic features and outcomes. In the clinical model, hematoma expansion [2.457 (0.297, 2.633); P=0.014], intracerebral ventricular hemorrhage [2.374 (0.180, 1.882); P=0.018], and location [-2.268 (-2.578, -0.188); P=0.023] were independently associated with a poor clinical outcome. In the hybrid model, location [-2.291 (-2.925, -0.228); P=0.022], and rad-score [5.255 (0.680, 11.460); P<0.001] were independently associated with a poor outcome. The hybrid model achieved satisfactory discriminability, with areas under curve (AUCs) of 0.892 [95% confidence interval (CI): 0.847 to 0.937], 0.893 (95% CI: 0.820 to 0.966), and 0.838 (95% CI: 0.755 to 0.920) in the training, internal validation, and external testing cohorts, respectively. The hybrid model also achieved good discriminability in the prediction of 30-day mortality, with AUCs of 0.840, 0.823, and 0.883 in the training, internal validation, and external testing cohorts, respectively. The rad-score [2.861 (1.940, 4.220); P<0.001] was the predominant risk factor associated with 30-day mortality. Conclusions: Radiomic analysis based on initial NCCT scans showed added value in predicting a poor outcome after ICH. A clinical-radiomics model yielded improved accuracy in predicting a poor outcome and 30-day death following ICH compared with radiomics alone.

Clinical features and risk factors of COVID-19-associated liver injury and function: A retrospective analysis of 830 cases.

INTRODUCTION AND OBJECTIVES: The incidence of liver injury (LI) in hospitalized COVID-19 patients ranged from 14% to 53% based on sole or multiple elevated indexes for LI. The aims of our study were to investigate the changes of parameters (ALT, AST) in LI and determine the risk factors for LI in a cohort of 830 COVID-19 patients. METHODS: Demographic information, clinical features, and laboratory testing outcomes on admission were compared between patients with and without liver biochemistry abnormality (LBA). The same comparisons were performed between the LBA and LI groups. The updated RUCAM was used to determine the causality between drugs application and LI. Univariable and multivariable logistic regression analyses were used to explore the potential risk factors associated with LBA and LI. RESULTS: A total of 227 (27.3%) patients exhibited LBA and 32 (3.9%) patients were categorized as having LI based on the diagnostic criteria. 32.6% (74/227) of the LBA patients had RUCAM score >3, whereas the non-LBA patients had a slight lower at rate of 24.2% (146/603) (P?=?0.047). Multivariable regression showed that a higher incidence of LBA was associated with hepatic hypoattenuation on computed tomography (CT) (odds ratio: 2.243, 95% confidence interval: 1.410-3.592, p?=?0.001), lymphocyte proportion <20% (2.088, 1.476-2.954, p?1?mg/dL (2.650, 1.845-3.806, p?1 (2.558, 1.820-3.596, p?1.0?mg/dL, lymphocyte proportion <20%, AST/ALT ratio <1, and triglyceride levels >1.7?mol/L are potential risk factors for LI.

Risk assessment of first upper gastrointestinal bleeding using computerized tomoscanning in esophageal varices patients with cirrhosis and portal hypertension.

To evaluate the risk of first upper gastrointestinal bleeding by computerized tomoscanning (CT) for esophageal varices patients with cirrhotic portal hypertension.One hundred thirty two esophageal varices patients with cirrhotic portal hypertension who are also complicated with gastrointestinal bleeding were recruited as bleeding group, while another 132 patients without bleeding as non-bleeding group. The diameter of esophageal varices, number of vascular sections, and total area of blood vessels were measured by CT scanning. The sensitivity and specificity of these indicators were calculated, and Youden index was adjusted with the critical point.The diameter of esophageal varices was 7.83 ±â€Š2.76 mm in bleeding group, and 6.57 ±â€Š3.42 mm in non-bleeding group. The Youden index was 0.32 with the critical point 5.55 mm. The area under the receiver operating characteristics (AUROC) was 0.72. The number of venous vessels was 4.5 ±â€Š2 in bleeding group, whereas being 4 ±â€Š2 in non-bleeding group. The Youden index was 0.35 with a critical point 4, and the area under the curve (AUC) was 0.68. The blood vessel area was 1.73 ±â€Š1.15 cm in bleeding group, and 1.12 ±â€Š0.89 cm in non-bleeding group. The Youden index was 0.48 with the critical point being 1.03 cm, and corresponding AUC was 0.82.Among all 3 indicators of the total area, diameter, and number of sections of the esophageal varices, the total area of esophageal varices showed more accuracy as a potential and novel indicator for bleeding prediction.

Radiomics features on non-contrast computed tomography predict early enlargement of spontaneous intracerebral hemorrhage.

OBJECTIVE: To explore the value of radiomics features on non-contrast computed tomography (NCCT) in predicting early enlargement of spontaneous intracerebral hemorrhage (SICH). PATIENTS AND METHODS: 167 patients with SICH were divided into enlarged hematoma and non-enlarged hematoma groups based on the volume of hematoma on 24-h follow-up CT images > 30% and/or 6 ml of the baseline NCCT. The baseline NCCT images of all cases were imported into radiomics software to extract the radiomics features of the initial hematoma. For each case, the features with good predictability were retained after the feature-selected process; the remaining features were used to construct model with 23 algorithms one-by-one. A 5-fold method was used to cross-validate the model and repeated 5 times. The algorithm model with the highest accuracy was selected as predictive model for hematoma enlargement (HE) in SICH, its average parameters including AUC, accuracy, sensitivity, specificity, F1 score, positive predictive value (PPV), negative predictive value (NPV), false positive rate (FPR), false negative rate (FNR),and false discovery rate (FDR) were taken as evaluating indicators. RESULTS: A total of 1227 texture features of each cerebral hematoma were obtained. After the feature-selected process, 4 features (wavelet-LHL mean, wavelet-LLL _ Idm, wavelet-LLL _run length non-uniformity normalized, and wavelet-LLL _contrast) remained to construct the predictive models. Among 23 model algorithms, Linear Support Vector Classifier showed the highest accuracy (72.6%), and eventually was selected as the predictive model, its AUC, accuracy, sensitivity, specificity, F1 score, PPV, NPV, FPR, FNR, and FDR were 0.729, 0.726,0.717,0.736,0.714, 0.736, 0.741, 0.264, 0.283 and 0.264, respectively. CONCLUSION: Radiomics features of cerebral hematoma on baseline NCCT images showed good performance in predicting HE of SICH.

LncRNA DGCR5 represses the development of hepatocellular carcinoma by targeting the miR-346/KLF14 axis.

Long non-coding RNAs (lncRNAs) are a class of regulatory noncoding RNAs. Emerging evidence highlights the critical roles of lncRNAs in the progression of hepatocellular carcinoma (HCC). Although many lncRNAs have been identified in the development of HCC, the association between DiGeorge syndrome critical region gene 5 (DGCR5) and HCC remains unclear. In the current study, we focused on the biological role of DGCR5 in HCC. We observed that DGCR5 was decreased in HCC cells, including SMCC7721, Hep3B, HepG2, MHCC-97L, MHCC-97H, and SNU449 hepatocellular carcinoma cells, compared with the normal human liver cell line THLE-3 normal human liver cells. In addition, DGCR5 overexpression could repress HCC cell growth, migration, and invasion considerably. Increasing studies have indicated the interactions between lncRNAs and microRNAs. MicroRNAs are endogenous small noncoding RNAs and they can play important roles in tumorigenesis. MicroRNA 346 (miR-346) has been demonstrated in various human cancer types, including HCC. MiR-346 was found to be increased in HCC cells and DGCR5 can act as a sponge of miR-346 to modulate the progression of HCC. The binding correlation between DGCR5 and miR-346 was validated in our research. Subsequently, Krüppel-like factor 14 (KLF14) was predicted as a downstream target of miR-346 and miR-346 can induce the development of HCC by inhibiting KLF14. Finally, we proved that DGCR5 can rescue the inhibited levels of KLF14 repressed by miR-346 mimics in MHCC-97H and Hep3B cells. Taken together, it was indicated in our study that DGCR5 can restrain the progression of HCC through sponging miR-346 and modulating KLF14 in vitro.

Contrast opacification difference of mural artery and the transluminal attenuation gradient on coronary computed tomography angiography for detection of systolic compression of myocardial bridge.

PURPOSE: Myocardial bridges (MB) have traditionally been considered a benign condition, but recent studies have demonstrated that the clinical complications can be dangerous. The transluminal attenuation gradient (TAG) obtained from coronary computed tomography angiography (CCTA) data (Retrospective ECG-triggered method) has been used in detecting significant stenosis in coronary artery caused by atherosclerosis. Contrast opacification difference (COD) was the parameters calculated as the change between attenuation of mural artery and the median attenuation of presumptive vessel segment; it was evaluated along with TAGstandardized (TAGs) and MB length for predicting MB with systolic compression (MB-SC) in patients diagnosed as MB in left anterior descending coronary artery (LAD) by CCTA or invasive coronary angiograph (ICA). METHODS: A total of 107 MB patients were divided into three groups based on systolic compression (SC), including: Group 1 (MB without SC); Group 2 (MB with mild SC); and Group 3 (MB with significant SC). ANOVA and Kruskal-Wallis analysis indicated TAGs showed the most significant differences for MB identification. RESULTS: This study revealed that TAGs decreasing and COD increasing were dominated in MB with significant SC. CONCLUSIONS: COD had a higher sensitivity and a higher negative predictive value for detecting MB with significant SC than TAGs.