Morphology and Anatomy of Branch–Branch Junctions in Opuntia ficus-indica and Cylindropuntia bigelovii: A Comparative Study Supported by Mechanical Tissue Quantification

The Opuntioideae include iconic cacti whose lateral branch–branch junctions are intriguing objects from a mechanical viewpoint. We have compared Opuntia ficus-indica, which has stable branch connections, with Cylindropuntia bigelovii, whose side branches abscise under slight mechanical stress. To determine the underlying structures and mechanical characteristics of these stable versus shedding cacti junctions, we conducted magnetic resonance imaging, morphometric and anatomical analyses of the branches and tensile tests of individual tissues. The comparison revealed differences in geometry, shape and material properties as follows: (i) a more pronounced tapering of the cross-sectional area towards the junctions supports the abscission of young branches of C. bigelovii. (ii) Older branches of O. ficus-indica form, initially around the branch–branch junctions, collar-shaped periderm tissue. This secondary coverage mechanically stiffens the dermal tissue, giving a threefold increase in strength and a tenfold increase in the elastic modulus compared with the epidermis. (iii) An approximately 200-fold higher elastic modulus of the vascular bundles of O. ficus-indica is a prerequisite for the stable junction of its young branches. Our results provide, for both biological and engineered materials systems, important insights into the geometric characteristics and mechanical properties of branching joints that are either stable or easily detachable.

Assessing the Role of Pericardial Fat as a Biomarker Connected to Coronary Calcification—A Deep Learning Based Approach Using Fully Automated Body Composition Analysis

(1) Background: Epi- and Paracardial Adipose Tissue (EAT, PAT) have been spotlighted as important biomarkers in cardiological assessment in recent years. Since biomarker quantification is an increasingly important method for clinical use, we wanted to examine fully automated EAT and PAT quantification for possible use in cardiovascular risk stratification. (2) Methods: 966 patients with intermediate Framingham risk scores for Coronary Artery Disease referred for coronary calcium scans were included in clinical routine retrospectively. The Coronary Artery Calcium Score (CACS) was extracted and tissue quantification was performed by a deep learning network. (3) Results: The Computed Tomography (CT) segmentations predicted by the network indicated no significant correlation between EAT volume and EAT radiodensity when compared to Agatston score (r = 0.18, r = −0.09). CACS 0 category patients showed significantly lower levels of total EAT and PAT volumes and higher EAT and PAT densities than CACS 1–99 category patients (p < 0.01). Notably, this difference did not reach significance regarding EAT attenuation in male patients. Women older than 50 years, thus more likely to be postmenopausal, were shown to be at higher risk of coronary calcification (p < 0.01, OR = 4.59). CACS 1–99 vs. CACS ≥100 category patients remained below significance level (EAT volume: p = 0.087, EAT attenuation: p = 0.98). (4) Conclusions: Our study proves the feasibility of a fully automated adipose tissue analysis in clinical cardiac CT and confirms in a large clinical cohort that volume and attenuation of EAT and PAT are not correlated with CACS. Broadly available deep learning based rapid and reliable tissue quantification should thus be discussed as a method to assess this biomarker as a supplementary risk predictor in cardiac CT.

Liver fibrosis assessments using FibroScan, virtual-touch tissue quantification, the FIB-4 index, and mac-2 binding protein glycosylation isomer levels compared with pathological findings of liver resection specimens in patients with hepatitis C infection

Background Evaluation of fibrosis stage is important to monitor progression of liver disease and risk of hepatocellular carcinoma (HCC). While liver biopsy is the gold standard, the method is invasive and faces several limitations. The aim of this study was to determine correlations among METAVIR scores and FibroScan, Virtual-Touch tissue quantification (VTQ), fibrosis index based on four factors (FIB-4 index), and Mac-2 binding protein glycosylation isomer (M2BPGi) level, and for examine differences in the reliability of non-invasive methods to evaluate fibrosis. Methods We used liver resection specimens from patients with hepatitis C virus (HCV), correlations were assessed between METAVIR scores and non-invasive method. Receiver operating characteristic (ROC) curves were generated to determine the sensitivity, specificity, and cut off values of the methods. Results All Patients group: In F0–2 vs F3–4, the areas under the ROC curve (AUC) (0.85) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p = 0.002) and that (0.67) of M2BPGi (p = 0.001). The AUC (0.83) of VTQ was significantly higher than that (0.67) of FIB-4 index (p = 0.01) and that (0.67) of M2BPGi (p = 0.002). In F0–3 vs F4, the AUC (0.86) of VTQ was significantly higher than that (0.65) of FIB-4 index (p = 0.04). The AUC (0.89) of FibroScan was significantly higher than that (0.65) of FIB-4 index (p = 0.002) and that (0.76) of M2BPGi (p = 0.02). Non-SVR group: In F0–2 vs F3–4, the AUC (0.85) of FibroScan was significantly higher than that (0.84) of FIB-4 index (p = 0.02) and that (0.73) of M2BPGi (p = 0.003). The AUC (0.84) of VTQ was significantly higher than that (0.74) of FIB-4 index (p = 0.04). In F0–3 vs F4, the AUC (0.91) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p = 0.003) and that (0.78) of M2BPGi (p = 0.02). The AUC (0.88) of VTQ was significantly higher than that of FIB-4 index (0.67) and that of M2BPGi (0.78) (p = 0.04). Conclusions FibroScan and VTQ best reflected the results of hepatic fibrosis diagnosis using liver resection specimens among the four examination methods evaluated.

Liver fibrosis assessments using FibroScan, Virtual-Touch tissue quantification, the FIB-4 index, and Mac-2 binding protein glycosylation isomer levels compared with pathological findings of liver resection specimens in patients with hepatitis C infection

BackgroundEvaluation of fibrosis stage is important to monitor progression of liver disease and risk of hepatocellular carcinoma (HCC). While liver biopsy is the gold standard, the method is invasive and faces several limitations. The aim of this study was to determine correlations among METAVIR scores and FibroScan, Virtual-Touch tissue quantification (VTQ), fibrosis index based on four factors (FIB-4 index), and Mac-2 binding protein glycosylation isomer (M2BPGi) level , and for examine differences in the reliability of non-invasive methods to evaluate fibrosis.MethodsWe used liver resection specimens from patients with hepatitis C virus (HCV), correlations were assessed between METAVIR scores and non-invasive method. Receiver operating characteristic (ROC) curves were generated to determine the sensitivity, specificity, and cut off values of the methods.ResultsAll Patients group: In F0-2 vs F3-4, the areas under the ROC curve (AUC) (0.85) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p=0.002) and that (0.67) of M2BPGi (p=0.001). The AUC (0.83) of VTQ was significantly higher than that (0.67) of FIB-4 index (p=0.01) and that (0.67) of M2BPGi (p=0.002). In F0-3 vs F4, the AUC (0.86) of VTQ was significantly higher than that (0.65) of FIB-4 index (p=0.04). The AUC (0.89) of FibroScan was significantly higher than that (0.65) of FIB-4 index (p=0.002) and that (0.76) of M2BPGi (p=0.02).Non-SVR group: In F0-2 vs F3-4, the AUC (0.85) of FibroScan was significantly higher than that (0.84) of FIB-4 index (p=0.02) and that (0.73) of M2BPGi (p=0.003). The AUC (0.84) of VTQ was significantly higher than that (0.74) of FIB-4 index (p=0.04). In F0-3 vs F4, the AUC (0.91) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p=0.003) and that (0.78) of M2BPGi (p=0.02). The AUC (0.88) of VTQ was significantly higher than that of FIB-4 index (0.67) and that of M2BPGi (0.78) (p=0.04).ConclusionsFibroScan and VTQ best reflected the results of hepatic fibrosis diagnosis using liver resection specimens among the four examination methods evaluated.

Liver fibrosis assessments using FibroScan, Virtual-Touch tissue quantification, the FIB-4 index, and Mac-2 binding protein glycosylation isomer levels compared with pathological findings of liver resection specimens in patients with hepatitis C infection

BackgroundEvaluation of fibrosis stage is important to monitor progression of liver disease and risk of hepatocellular carcinoma (HCC). While liver biopsy is the gold standard, the method is invasive and faces several limitations. The aim of this study was to determine correlations among METAVIR scores and FibroScan, Virtual-Touch tissue quantification (VTQ), fibrosis index based on four factors (FIB-4 index), and Mac-2 binding protein glycosylation isomer (M2BPGi) level , and for examine differences in the reliability of non-invasive methods to evaluate fibrosis.MethodsWe used liver resection specimens from patients with hepatitis C virus (HCV), correlations were assessed between METAVIR scores and non-invasive method. Receiver operating characteristic (ROC) curves were generated to determine the sensitivity, specificity, and cut off values of the methods.ResultsAll Patients group: In F0-2 vs F3-4, the areas under the ROC curve (AUC) (0.85) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p=0.002) and that (0.67) of M2BPGi (p=0.001). The AUC (0.83) of VTQ was significantly higher than that (0.67) of FIB-4 index (p=0.01) and that (0.67) of M2BPGi (p=0.002). In F0-3 vs F4, the AUC (0.86) of VTQ was significantly higher than that (0.65) of FIB-4 index (p=0.04). The AUC (0.89) of FibroScan was significantly higher than that (0.65) of FIB-4 index (p=0.002) and that (0.76) of M2BPGi (p=0.02).Non-SVR group: In F0-2 vs F3-4, the AUC (0.85) of FibroScan was significantly higher than that (0.84) of FIB-4 index (p=0.02) and that (0.73) of M2BPGi (p=0.003). The AUC (0.84) of VTQ was significantly higher than that (0.74) of FIB-4 index (p=0.04). In F0-3 vs F4, the AUC (0.91) of FibroScan was significantly higher than that (0.67) of FIB-4 index (p=0.003) and that (0.78) of M2BPGi (p=0.02). The AUC (0.88) of VTQ was significantly higher than that of FIB-4 index (0.67) and that of M2BPGi (0.78) (p=0.04).ConclusionsFibroScan and VTQ best reflected the results of hepatic fibrosis diagnosis using liver resection specimens among the four examination methods evaluated.