Evaluation of the Impact of Metabolic Syndrome on Fibrosis in Metabolic Dysfunction-Associated Fatty Liver Disease

Background: Metabolic syndrome (MS) is a condition that consists of several disorders, and the individual impact of these disorders on metabolic dysfunction-associated fatty liver disease (MAFLD) is still not clear in a combined diagnosis of MS. In this study, we aimed to investigate the effect of MS on advanced fibrosis in patients with MAFLD.Methods: We recruited the patients from our gastroenterology out-patient clinic who were being followed up for MAFLD. MAFLD was diagnosed with liver biopsy in all patients. The frequency of MS and other metabolic parameters were also compared between groups with advanced fibrosis and groups in which fibrosis was not as advanced.Results: In total, we enrolled 424 biopsy-proven MAFLD patients to the study. In univariate analysis, individuals with greater age, body mass index (BMI), higher aspartate transaminase (AST), MS, impaired fasting glucose, hypertension, enlarged waist circumference (WC), diabetes mellitus (DM), and women had significantly increased risk for fibrosis. In multivariate analysis, it was found that DM, greater age, higher BMI, and increased AST were seen more commonly in MAFLD patients with advanced fibrosisConclusion: Greater age, a higher BMI, higher AST and a diagnosis of diabetes were more commonly associated with advanced fibrosis. However, DM was found to be the strongest predictive factor of advanced fibrosis in our cohort (OR: 2.495). Multivariate analyses did not indicate a significantly common occurrence of MS in the advanced fibrosis group, despite its important role in MAFLD pathophysiology.     

Rare bioparticle detection via deep metric learning

Recent deep neural networks have shown superb performance in analyzing bioimages for disease diagnosis and bioparticle classification. Conventional deep neural networks use simple classifiers such as SoftMax to obtain highly accurate results. However, they have limitations in many practical applications that require both low false alarm rate and high recovery rate, e.g., rare bioparticle detection, in which the representative image data is hard to collect, the training data is imbalanced, and the input images in inference time could be different from the training images. Deep metric learning offers a better generatability by using distance information to model the similarity of the images and learning function maps from image pixels to a latent space, playing a vital role in rare object detection. In this paper, we propose a robust model based on a deep metric neural network for rare bioparticle (Cryptosporidium or Giardia) detection in drinking water. Experimental results showed that the deep metric neural network achieved a high accuracy of 99.86% in classification, 98.89% in precision rate, 99.16% in recall rate and zero false alarm rate. The reported model empowers imaging flow cytometry with capabilities of biomedical diagnosis, environmental monitoring, and other biosensing applications.

Conventional deep neural networks use simple classifiers to obtain highly accurate results. However, they have limitations in practical applications. This study demonstrates a robust deep metric neural network model for rare bioparticle detection.     

Complication and cost analysis of transbronchial lung cryobiopsy and awake video-assisted thoracic surgery in diagnosis of interstitial lung disease

Aim and introduction:Diagnosing of interstitial lung disease (ILD) is difficult and expensive. The standard diagnostical approaches to ILD are bronchoalveolar lavage, transbronchial lung biopsy, transbronchial lung cryobiopsy (TBLC) and surgical lung biopsy (SLB). SLB is gold standard for the confident diagnosis of ILD but because of the poor performance of the patients it’s use is limited. We conducted a retrospective study to point out that TBLC plays an important role in diagnosis of ILD and has fewer complications and lower cost than awake video-assisted thoracic surgery (AVATS).Material and methods:132 patients who underwent TBLC and AVATS with a pre-diagnosis of ILD in our hospital between 2015 and 2020 were evaluated retrospectively. Diagnosis rates, complications and costs were recorded.Results:There were no non-diagnostic materials in 44 patients in AVATS arm. Prolonged air leak was observed in 11(25.0%) of the patients, and six of them (13.6%) were discharged with Heimlich Valve (HV). Median length of stay in the hospital was 8 days, while average patient cost was $515.9 (415.2-2662.9) in the AVATS arm. Non-diagnostic material was obtained from 10 (11.3%) of 88 patients in TBLC arm. Six (6.8%) of them had pneumothorax, only one of them required a chest tube. No patient was discharged with HV (p=0.001). Median cost for each patient with a median hospital stay of 2.0 (1.0-21.0) (p<0.001) days was $171.9 (80.8-1493.3) (p<0.001).Discussion:Although TBLC is behind AVATS in terms of diagnostic accuracy, it may be an alternative diagnostic tool in the diagnosis of interstitial lung disease due to its acceptable safety profile and cost-effectiveness.     

Platelet-Derived MRP-14 Induces Monocyte Activation in Patients With Symptomatic Peripheral Artery Disease

Background

Peripheral artery disease (PAD), a diffuse manifestation of atherothrombosis, is a major cardiovascular threat. Although platelets are primary mediators of atherothrombosis, their role in the pathogenesis of PAD remains unclear.

Effects of current and potential dental etchants on nerve compound action potentials

In this study, a 35% phosphoric acid gel (3M Scotchbond etchant), a nonrinse etchant (NRC), and two EDTA-containing conditioners (RC-Prep and File-Eze) were tested in vitro for blocking nerve conductance evoked in the rat sciatic nerve after local application. The phosphoric acid gel and NRC completely and irreversibly inhibited conductance. On the other hand, RC-Prep reduced the compound action potentials (cAPs) by 50% in 120 min. With File-Eze, the reduction in cAPs was less than 50% after an application time of 160 min (61.8 +/- 1.8%). At 160 min the cAPs in the RC-Prep group had been inhibited by 62.4%. These results indicated strong neurotoxic effects of phosphoric acid and NRC when applied directly on exposed pulp in the total etch procedure.     

Immature dendritic cell transdifferentiation into osteoclasts: a novel pathway sustained by the rheumatoid arthritis microenvironment

Dendritic cells (DCs), the mononuclear cells that initiate immune response, and osteoclasts, the multinucleated bone-resorbing cells, are derived from monocyte/macrophage precursor cells. Granulocyte-macrophage colony-stimulating factor and macrophage colony-stimulating factor (M-CSF) reciprocally regulate the differentiation of both lineages in mice. Using human monocyte-derived DCs generated in vitro, we show that immature DCs transdifferentiate into functional osteoclasts (OCs) in the presence of M-CSF and receptor activator of nuclear factor-kappaB ligand (RANKL). Transdifferentiation operates through fusion of intermediate adherent bipolar fusiform mononuclear cells expressing CD14, CD1a, and RANKL and able to induce RANKL(+) T-cell proliferation. Surprisingly, DC fusion in vitro is faster and more efficient than monocyte fusion to form multinucleated giant cells. The transdifferentiation process reported here supports the existence of a high cellular plasticity within differentiated myeloid phagocytes. Importantly, this process is greatly enhanced by rheumatoid arthritis synovial fluid and involves proinflammatory cytokines such as interleukin 1 or tumor necrosis factor alpha, as well as components of the extracellular matrix such as hyaluronic acid. Our data therefore suggest that DC-derived OCs may be directly involved in the osteolytic lesions observed in human inflammatory bone diseases such as rheumatoid arthritis or in particular forms of Langerhans cell histiocytosis, characterized by accumulation of immature skin DCs and chronic lytic bone lesions.     

Estimation of COVID-19 vaccine effectiveness against hospitalisation in individuals aged ≥ 65 years using electronic health registries; a pilot study in four EU/EEA countries,October 2021 to March 2022

By employing a common protocol and data from electronic health registries in Denmark, Navarre (Spain), Norway and Portugal, we estimated vaccine effectiveness (VE) against hospitalisation due to COVID-19 in individuals aged ≥ 65 years old, without previous documented infection, between October 2021 and March 2022. VE was higher in 65–79-year-olds compared with ≥ 80-year-olds and in those who received a booster compared with those who were primary vaccinated. VE remained high (ca 80%) between ≥ 12 and < 24 weeks after the first booster administration, and after Omicron became dominant.