A story of liver and gut microbes: How does the intestinal flora affect liver disease? A review of the literature

Each individual is endowed with a unique gut microbiota (GM) footprint that mediates numerous host-related physiological functions, such as nutrient metabolism, maintenance of the structural integrity of the gut mucosal barrier, immunomodulation, and protection against microbial pathogens. Because of increased scientific interest in the GM, its central role in the pathophysiology of many intestinal and extraintestinal conditions has been recognized. Given the close relationship between the gastrointestinal tract and the liver, many pathological processes have been investigated in the light of a microbial-centered hypothesis of hepatic damage. In this review we introduce to neophytes the vast world of gut microbes, including prevalent bacterial distribution in healthy individuals, how the microbiota is commonly analyzed, and the current knowledge of the role of GM in liver disease pathophysiology. Also, we highlight the potentials and downsides of GM-based therapy

Potential role of biofeedback visual training in high-speed motorbike drivers

Purpose: In several sports, appropriate training strategies remain a challenge for athletes and coaches, with the goal of improving performance. Extensive research has proposed several technical tools for obtaining parametric evaluations before competition in real 10 life. This study aimed to assess whether some retinal performances might be improved using psychophysical techniques in health professionals involved in motorcycle sports (FIM MotoE). Methods: Two MotoE drivers were screened at baseline using complete ophthalmological examinations and evaluation of retinal reaction times, followed by a biofeedback training program. After 4 months of training, the subjects underwent a control visit using the same protocol as the baseline. 15 Results: Central reaction time was shorter for 75% of drivers, with a consistent reduction (mean value of 20%). The peripheral reaction time showed an increasing trend after visual training. In both drivers, fixation stability improved dramatically (in 30% increments). Conclusion: The potential role of advanced technology was applied to high-speed drivers. Our results may be due to an attentional shift from the peripheral retina to the central retina during training. In our opinion, training potentiates the most useful pathways at the 20 expense of less involved retinal and cortical areas, thus improving driving abilities and safety

On Clinical Agreement on the Visibility and Extent of Anatomical Layers in Digital Gonio Photographs

Purpose: To quantitatively evaluate the inter-annotator variability of clinicians tracing the contours of anatomical layers of the iridocorneal angle on digital gonio photographs, thus providing a baseline for the validation of automated analysis algorithms. Methods: Using a software annotation tool on a common set of 20 images, five experienced ophthalmologists highlighted the contours of five anatomical layers of interest: iris root (IR), ciliary body band (CBB), scleral spur (SS), trabecular meshwork (TM), and cornea (C). Inter-annotator variability was assessed by (1) comparing the number of times ophthalmologists delineated each layer in the dataset; (2) quantifying how the consensus area for each layer (i.e., the intersection area of observers\u2019delineations) varied with the consensus threshold; and (3) calculating agreement among annotators using average per-layer precision, sensitivity, and Dice score. Results: The SS showed the largest difference in annotation frequency (31%) and the minimum overall agreement in terms of consensus size ( 3c28% of the labeled pixels). The average annotator\u2019s per-layer statistics showed consistent patterns, with lower agreement on the CBB and SS (average Dice score ranges of 0.61\u20130.7 and 0.73\u20130.78, respectively) and better agreement on the IR, TM, and C (average Dice score ranges of 0.97\u20130.98, 0.84\u20130.9, and 0.93\u20130.96, respectively). Conclusions: There was considerable inter-annotator variation in identifying contours of some anatomical layers in digital gonio photographs. Our pilot indicates that agreement was best on IR, TM, and C but poorer for CBB and SS. Translational Relevance: This study provides a comprehensive description of interannotator agreement on digital gonio photographs segmentation as a baseline for validating deep learning models for automated gonioscopy

MicroRNAs as Regulators of Neo-Angiogenesis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly vascularized neoplasm. In the tumor niche, abundant angiogenesis is fundamental in providing nutrients for tumor growth and represents the first escape route for metastatic cells. Active angiogenesis, together with metastasis, are responsible for the reduction of recurrence-free survival of HCC. MicroRNAs (miRNAs) are small non-coding RNAs that have recently drawn attention in molecular targeted therapy or as diagnostic and prognostic biomarkers. MiRNA expression in HCC has been widely studied in the last decade. Some miRNAs have been found to be up- or down-regulated, besides association with apoptosis, metastasis progression and drug resistance have been found. This review article aims to summarize the angiogenetic process in tumor diseases and to update on what has been found in the vast world of HCC-related-miRNAs and, eventually, to report the latest finding on several miRNAs involved in HCC angiogenesis. We searched the state of the arts for the 12 miRNAs found to be involved with angiogenesis in HCC (miR-29b, miR-126-3p, miR-144-3p, miR-146a, miR-195, miR-199a-3p, miR-210-3p, miR-338- 3p, mir-491, mir-497, mir-638, mir-1301) and reported their main molecular targets and their overall effect in the sprouting of new vessels

Sub-basal Corneal Nerve Plexus Analysis Using a New Software Technology

PURPOSE:To study sub-basal corneal nerve plexus (SCNP) parameters by in vivo corneal confocal microscopy using a new software technology and examine the effect of demographics and diabetes mellitus (DM) on corneal nerves morphology. METHODS:A Confoscan 4 (Nidek Technologies) was used in this cross-sectional study to image the SCNP in 84 right eyes at the Miami Veterans Affairs eye clinic. Images were analyzed using a new semiautomated nerve analysis software program (The Corneal Nerve Analysis tool) which evaluated 9 parameters including nerve fibers length (NFL) and nerve fibers length density (NFLD). The main outcome measure was the examination of SCNP morphology by demographics, comorbidities, and HbA1c level. RESULTS:Interoperator and intraoperator reproducibility were good for the 9 parameters studied (Intraclass Correlations [ICCs] 0.73–0.97). Image variability between two images within the same scan was good for all parameters (ICC 0.66–0.80). Older individuals had lower SCNP parameters with NFL and NFLD negatively correlating with age (r=−0.471, and −0.461, respectively, P<0.01 for all). Patients with diabetes had lower mean NFLD 10987.6 μm/mm (±3,284.6) and NFL 1,289.5 μm/frame (±387.2) compared with patients without diabetes (mean NFLD 15077.1 μm/mm [±4,261.3] and NFL 1750.0 μm/frame [±540.7]) (P<0.05 for all). HbA1c levels in patients with diabetes were inversely correlated with NFL and NFLD (r= −0.568, and −0.569, respectively, P<0.05 for all). CONCLUSIONS:The Corneal Nerve Analysis tool is a reproducible diagnostic software technique for the analysis of the SCNP with confocal microscopy. Older age, DM, and higher level of HbA1c were associated with a significant reduction in SCNP parameters

The Role of Liver and Spleen Elastography in the Screening of Esophageal Varices in Patients with Liver Cirrhosis: Do We Really Need Endoscopy?

Background: recently, the Baveno VI guidelines have suggested that esophagogastroduodenoscopy (EGD) to stage esophageal varices can be avoided in patients with advanced liver disease who have a liver stiffness (LS) 150x103/\u3bcL. Our study aims to analyze spleen stiffness (SS) as a non\u2010invasive method of diagnosis for clinically significant portal hypertension in order to avoid EGD in low\u2010risk patients for esophageal varices. We also want to compare the SS to other non\u2010invasive techniques and analyze their reproducibility and inter\u2010observer concordance. Patients and Methods: in this prospective study, we detected the SS and LS in 150 patients diagnosed with liver cirrhosis to be submitted for endoscopic screening for esophageal varices. In addition, we enrolled 70 healthy control individuals, who for other reasons, had undergone an endoscopic examination of the upper digestive tracts and who were negative for hepatic and lymphoproliferative disease. The discriminatory capacity for the presence of esophageal varices of the SS has been compared with that deriving from other non\u2010invasive procedures (LS, splenic diameter, splenic surface, platelet count, and combined scores deriving from these parameters). Optimal SS cut\u2010offs were sought to exclude the presence of varices. Particular emphasis was placed on the search for possible correlations of the with ultrasound parameters of portal hypertension and platelet count. Finally, we studied in a double\u2010blind fashion inter\u2010operator concordance with 50 measurements for LS, and 25 for SS. Results: cirrhotic patients have significantly higher SS and LS values than controls. The SS values were higher in cirrhotic patients with varices (n = 62) compared to patients without esophageal varices (n = 88) and to healthy controls (p <0.001). SS showed an AUROC of 0.93 (95% C.I., 0.89\u20100.97), statistically different from the other predictors (p <0.001). The cut\u2010off, chosen according to Youden\u2019s Index and equal to 38.55 kPa, showed sensitivity of 87%, specificity of 89%, NPV of 91%, and PPV of 84%. Instead, the cut\u2010off of 30.79 kPa has 100% sensitivity and 100% NPV. The cut\u2010off of 69.73 kPa demonstrated specificity and PPV of 100%. The SS demonstrated weak linear correlation with the splenic dimensions (bipolar diameter and surface measured at the organ\u2019s hilum). Moreover, it has a linear correlation with the platelet count, which was greater than that present with LS (r = 0.5 vs r = 0.32). The test revealed an excellent intraclass correlation coefficient (ICC) equal to 0.96 for SS and 0.97 for LS. Conclusion: the results of this study show how the SS can play an important role in the daily clinical management of cirrhotic patients. The SS (alone or combined with other indicators) may play an important role as a non\u2010invasive screening test for predicting the risk of varices

Semantic segmentation of gonio-photographs via adaptive ROI localisation and uncertainty estimation

To develop and test a deep learning (DL) model for semantic segmentation of anatomical layers of the anterior chamber angle (ACA) in digital gonio-photographs. We used a pilot dataset of 274 ACA sector images, annotated by expert ophthalmologists to delineate five anatomical layers: iris root, ciliary body band, scleral spur, trabecular meshwork and cornea. Narrow depth-of-field and peripheral vignetting prevented clinicians from annotating part of each image with sufficient confidence, introducing a degree of subjectivity and features correlation in the ground truth. To overcome these limitations, we present a DL model, designed and trained to perform two tasks simultaneously: (1) maximise the segmentation accuracy within the annotated region of each frame and (2) identify a region of interest (ROI) based on local image informativeness. Moreover, our calibrated model provides results interpretability returning pixel-wise classification uncertainty through Monte Carlo dropout. The model was trained and validated in a 5-fold cross-validation experiment on ~90% of available data, achieving ~91% average segmentation accuracy within the annotated part of each ground truth image of the hold-out test set. An appropriate ROI was successfully identified in all test frames. The uncertainty estimation module located correctly inaccuracies and errors of segmentation outputs. The proposed model improves the only previously published work on gonio-photographs segmentation and may be a valid support for the automatic processing of these images to evaluate local tissue morphology. Uncertainty estimation is expected to facilitate acceptance of this system in clinical settings