Hyaluronic acid levels are increased in complicated parapneumonic pleural effusions

Background and Aim. Hyaluronic acid (HA) is a component of extracellular matrix and may play a role in the pleural inflammation which is implicated in parapneumonic effusions.The aim of the current study was to investigate HA levels in serum and pleura in patients with parapneumonic effusions. Methods. We prospectively studied pleural and serum levels of HA in 58 patients with pleural effusions due to infection (complicated and uncomplicated parapneumonic effusions), malignant effusions and transudative effusions due to congestive heart failure. In addition to HA, TNF-α and IL-1β levels were determined in pleural fluid and serum by ELISA. Results. The median±SD HA levels (pg/ml) in pleural fluid of patients with complicated effusions (39.058±11.208) were significantly increased (p<0.005), compared to those with uncomplicated parapneumonic effusions (11.230±1.969), malignant effusions (10.837±4.803) or congestive heart failure (5.392±3.133). There was no correlation between pleural fluid and serum HA values. Pleural fluid TNF-α levels (146±127 pg/mL) and IL-1β levels (133.4±156 pg/mL) were significantly higher in patients with complicated parapneumonic effusions compared to patients with other types of effusion (p<0.05). No significant association between HA and TNF-α or IL-1β was found. Conclusions. HA may play a significant role in the inflammatory process which characterises exudative infectious pleuritis. Further investigation might reveal whether HA is a useful marker in the management of parapneumonic effusions

An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics

Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote

Genetic prediction of ICU hospitalization and mortality in COVID-19 patients using artificial neural networks

There is an unmet need of models for early prediction of morbidity and mortality of Coronavirus disease-19 (COVID-19). We aimed to a) identify complement-related genetic variants associated with the clinical outcomes of ICU hospitalization and death, b) develop an artificial neural network (ANN) predicting these outcomes and c) validate whether complement-related variants are associated with an impaired complement phenotype. We prospectively recruited consecutive adult patients of Caucasian origin, hospitalized due to COVID-19. Through targeted next-generation sequencing, we identified variants in complement factor H/CFH, CFB, CFH-related, CFD, CD55, C3, C5, CFI, CD46, thrombomodulin/THBD, and A Disintegrin and Metalloproteinase with Thrombospondin motifs (ADAMTS13). Among 381 variants in 133 patients, we identified 5 critical variants associated with severe COVID-19: rs2547438 (C3), rs2250656 (C3), rs1042580 (THBD), rs800292 (CFH) and rs414628 (CFHR1). Using age, gender and presence or absence of each variant, we developed an ANN predicting morbidity and mortality in 89.47% of the examined population. Furthermore, THBD and C3a levels were significantly increased in severe COVID-19 patients and those harbouring relevant variants. Thus, we reveal for the first time an ANN accurately predicting ICU hospitalization and death in COVID-19 patients, based on genetic variants in complement genes, age and gender. Importantly, we confirm that genetic dysregulation is associated with impaired complement phenotype.- Pfizer Pharmaceuticals(undefined

BLOOD-BRAIN-BARRIER PERMEABILITY IN HEALTHY INFECTED AND STRESSED NEONATES

The assessment of the blood-brain barrier permeability (BBBP) showed that BBBP values were higher in stressed neonates and those with bacterial meningitis than in “healthy” infants or neonates with aseptic meningitis. The BBBP determination may be helpful in differentiating bacterial from aseptic meningitis; the high BBBP should be considered in the management of stressed neonates

Brief Report: Speech and Language Therapy in Children with ASD in an Aquatic Environment: the ASLT (Aquatic Speech and Language Therapy) Program

Although water-based approaches have been shown to be beneficial for children with Autism Spectrum Disorder (ASD), no study thus far has directly investigated the effects of such intervention programs on language skills. The present study aims to evaluate the efficacy of the Aquatic Speech and Language Therapy (ASLT) program, which is a new, exclusively aquatic intervention program designed especially for children with ASD. The effects of ASLT were compared to the outcome of a similar classroom-based intervention, in two groups of children with ASD matched for age, gender, and expressive/receptive vocabulary. Our findings show that ASLT results in significantly greater improvement of vocabulary measures, thus providing direct evidence of water-based intervention’s beneficial effects on language skills in ASD. © 2020, Springer Science+Business Media, LLC, part of Springer Nature

Integrated Design of Centrifugal Compressor and Radial Turbine of a Hybrid \u3bcGT/SOFC Power Train Emulator

Solid Oxide Fuel Cells hold the greatest potential of any other fuel cell technology. Using low cost ceramic materials, they can achieve high electrical efficiencies without relying on CHP. Moreover, SOFCs operate at high temperature (typically above 800\ub0C), which allows fuel flexibility. However, there are still significant technical challenges inhibiting the use of this promising new technology. This paper examines the development of enabling technologies of SOFC/\u3bcGT Hybrid Systems for power generation. The positive characteristics and the drawbacks of solid oxide fuel cells are being introduced. Such an application includes a series of specifications and restrictions. The requirement of maintaining a 7 bar static pressure at the fuel cell inlet leads to the addition of a centrifugal compressor. This additional device is used as a booster with a desired pressure ratio of 1.5. The investigation of two alternative technical approaches for the driving of the booster is presented: an electrically driven compressor and a booster driven by a turbo-expander. The integration procedure carries on with the design of the cycle and its components. The present work is being concluded after the preliminary design of both the compressor and the expander. Results show a 5.79% higher total power output and a wider range of rotational speed for the turbocharger case. Hence, the radial turbine solution is proven to be the most appropriate one for the compressor driving

Fsmpy: A Fuzzy Set Measures Python Library

This paper presents the fsmpy Python library for the implementation of any type of measures and comparisons of different types of fuzzy sets, as well as other important and useful utilities and algorithms. In this paper, we analyze the motivation behind its implementation, the design principles followed, the implemented modules of the library and its capabilities, considering intuitionistic fuzzy sets as the case study. Lastly, some examples of its application to widely used pattern recognition, medical diagnosis and image segmentation are presented