Improving emerging European NMIs’ capabilities in humidity measurement

The control and measurement of humidity is important for many industrial applications and to ensure the appropriate storage of materials and products. Humidity measurement techniques are diverse and each presents different challenges for use and calibration for a range of pressures and gases. Over the past few years, the development of humidity sensors and apparatus has matured to a level where traceable calibration is beneficial to all industries in which humidity and moisture measurement and control are important. This paper deals with a European project in which the overall objective is to develop or extend the measurement and research capabilities of the participating emerging NMI/DIs’ countries in the field of humidity measurements, where access to these types of facilities is currently limited

Analysis of Flavonoids from<i>Eugenia uniflora</i>Leaves and Its Protective Effect against Murine Sepsis

Eugenia uniflora, referred to as Pitanga cherry shrub, is largely distributed in tropical and subtropical America. This plant is cultivated in many countries and it is suitable for the production of juice, frozen pulp, and tea. Besides, it can be used as treatment for inflammatory diseases. We reported that a flavonoid-rich fraction (HE-Bu) obtained from leaves decreased the lethality induced by cecal ligation and puncture (CLP), a clinically relevant model of sepsis. The oral administration of HE-Bu reduced the late mortality rate by 30%, prevented neutrophil accumulation in lungs, decreased TNF-αand IL-1βserum levels, and markedly decreased iNOS and COX-2 protein expression by ileum cells. Chemical investigation showed myricetin and quercetin rhamnosides as the major components of this fraction. The results showed that HE-Bu protected mice from sepsis and indicated that this edible plant produces compounds that could be considered as potential adjuvants for sepsis treatment.</jats:p

Generator breast datamart\u2014the novel breast cancer data discovery system for research and monitoring: Preliminary results and future perspectives

Background: Artificial Intelligence (AI) is increasingly used for process management in daily life. In the medical field AI is becoming part of computerized systems to manage information and encourage the generation of evidence. Here we present the development of the application of AI to IT systems present in the hospital, for the creation of a DataMart for the management of clinical and research processes in the field of breast cancer. Materials and methods: A multidisciplinary team of radiation oncologists, epidemiologists, medical oncologists, breast surgeons, data scientists, and data management experts worked together to identify relevant data and sources located inside the hospital system. Combinations of open-source data science packages and industry solutions were used to design the target framework. To validate the DataMart directly on real-life cases, the working team defined tumoral pathology and clinical purposes of proof of concepts (PoCs). Results: Data were classified into \u201cNot organized, not \u2018ontologized\u2019 data\u201d, \u201cOrganized, not \u2018ontologized\u2019 data\u201d, and \u201cOrganized and \u2018ontologized\u2019 data\u201d. Archives of real-world data (RWD) identified were platform based on ontology, hospital data warehouse, PDF documents, and electronic reports. Data extraction was performed by direct connection with structured data or text-mining technology. Two PoCs were performed, by which waiting time interval for radiotherapy and performance index of breast unit were tested and resulted available. Conclusions: GENERATOR Breast DataMart was created for supporting breast cancer pathways of care. An AI-based process automatically extracts data from different sources and uses them for generating trend studies and clinical evidence. Further studies and more proof of concepts are needed to exploit all the potentials of this system

Polysaccharides from Agaricus bisporus and Agaricus brasiliensis show similarities in their structures and their immunomodulatory effects on human monocytic THP-1 cells

<p>Abstract</p> <p>Background</p> <p>Mushroom polysaccharides have traditionally been used for the prevention and treatment of a multitude of disorders like infectious illnesses, cancers and various autoimmune diseases. Crude mushroom extracts have been tested without detailed chemical analyses of its polysaccharide content. For the present study we decided to chemically determine the carbohydrate composition of semi-purified extracts from 2 closely related and well known basidiomycete species, i.e. <it>Agaricus bisporus </it>and <it>A. brasiliensis </it>and to study their effects on the innate immune system, in particular on the <it>in vitro </it>induction of pro-inflammatory cytokines, using THP-1 cells.</p> <p>Methods</p> <p>Mushroom polysaccharide extracts were prepared by hot water extraction and precipitation with ethanol. Their composition was analyzed by GC-MS and NMR spectroscopy. PMA activated THP-1 cells were treated with the extracts under different conditions and the production of pro-inflammatory cytokines was evaluated by qPCR.</p> <p>Results</p> <p>Semi-purified polysaccharide extracts of <it>A. bisporus </it>and <it>A. brasiliensis </it>(= <it>blazei</it>) were found to contain (1→6),(1→4)-linked α-glucan, (1→6)-linked β-glucan, and mannogalactan. Their proportions were determined by integration of ¹H-NMR signs, and were considerably different for the two species. <it>A. brasiliensis </it>showed a higher content of β-glucan, while <it>A. bisporus </it>presented mannogalactan as its main polysaccharide. The extracts induced a comparable increase of transcription of the pro-inflammatory cytokine genes IL-1β and TNF-α as well as of COX-2 in PMA differentiated THP-1 cells. Pro-inflammatory effects of bacterial LPS in this assay could be reduced significantly by the simultaneous addition of <it>A. brasiliensis </it>extract.</p> <p>Conclusions</p> <p>The polysaccharide preparations from the closely related species <it>A. bisporus </it>and <it>A. brasiliensis </it>show major differences in composition: <it>A. bisporus </it>shows high mannogalactan content whereas <it>A. brasiliensis </it>has mostly β-glucan. Semi-purified polysaccharide extracts from both <it>Agaricus </it>species stimulated the production of pro-inflammatory cytokines and enzymes, while the polysaccharide extract of <it>A. brasiliensis </it>reduced synthesis of these cytokines induced by LPS, suggesting programmable immunomodulation.</p

A robust method to quantify low molecular weight contaminants in heparin: detection of tris(2-n-butoxyethyl) phosphate

Recently, oversulfated chondroitin sulfate (OSCS) was identified in contaminated heparin preparations, which were linked to several adverse clinical events and deaths. Orthogonal analytical techniques, namely nuclear magnetic resonance (NMR) and capillary electrophoresis (CE), have since been applied by several authors for the evaluation of heparin purity and safety. NMR identification and quantification of residual solvents and non-volatile low molecular contaminants with USP acceptance levels of toxicity was achieved 40-fold faster than the traditional GC-headspace technique, which takes similar to 120 min against similar to 3 min to obtain a (1)H NMR spectrum with a signal/noise ratio of at least 1000/1. the procedure allowed detection of Class 1 residual solvents at 2 ppm and quantification was possible above 10 ppm. 2D NMR techniques (edited-HSQC (1)H/(13)C) permitted visualization of otherwise masked EDTA signals at 3.68/59.7 ppm and 3.34/53.5 ppm, which may be overlapping mononuclear heparin signals, or those of ethanol and methanol. Detailed NMR and ESI-MS/MS studies revealed a hitherto unknown contaminant, tris(2-n-butoxyethyl) phosphate (TBEP), which has potential health risks.Brazilian agency Fundacao AraucariaBrazilian agency FINEP (PRONEX-CARBOIDRATOS, PADCT II/SBIO)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Univ Fed Parana, Dept Bioquim & Biol Mol, BR-81531980 Curitiba, PR, BrazilIst Ric Chim & Biochim G Ronzoni, I-20133 Milan, ItalyUniversidade Federal de São Paulo, Dept Bioquim & Biol Mol, BR-04044020 São Paulo, SP, BrazilUniv Liverpool, Sch Biol Sci, Liverpool L69 7ZB, Merseyside, EnglandUniversidade Federal de São Paulo, Dept Bioquim & Biol Mol, BR-04044020 São Paulo, SP, BrazilWeb of Scienc

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented in daily practice. The objective of the study was to validate a machine-learning risk prediction model using easy-to-obtain parameters to help to identify patients with COVID-19 who are at higher risk of death. The training cohort included all patients admitted to Fondazione Policlinico Gemelli with COVID-19 from March 5, 2020, to November 5, 2020. Afterward, the model was tested on all patients admitted to the same hospital with COVID-19 from November 6, 2020, to February 5, 2021. The primary outcome was in-hospital case-fatality risk. The out-of-sample performance of the model was estimated from the training set in terms of Area under the Receiving Operator Curve (AUROC) and classification matrix statistics by averaging the results of fivefold cross validation repeated 3-times and comparing the results with those obtained on the test set. An explanation analysis of the model, based on the SHapley Additive exPlanations (SHAP), is also presented. To assess the subsequent time evolution, the change in paO2/FiO2 (P/F) at 48&nbsp;h after the baseline measurement was plotted against its baseline value. Among the 921 patients included in the training cohort, 120 died (13%). Variables selected for the model were age, platelet count, SpO2, blood urea nitrogen (BUN), hemoglobin, C-reactive protein, neutrophil count, and sodium. The results of the fivefold cross-validation repeated 3-times gave AUROC of 0.87, and statistics of the classification matrix to the Youden index as follows: sensitivity 0.840, specificity 0.774, negative predictive value 0.971. Then, the model was tested on a new population (n = 1463) in which the case-fatality rate was 22.6%. The test model showed AUROC 0.818, sensitivity 0.813, specificity 0.650, negative predictive value 0.922. Considering the first quartile of the predicted risk score (low-risk score group), the case-fatality rate was 1.6%, 17.8% in the second and third quartile (high-risk score group) and 53.5% in the fourth quartile (very high-risk score group). The three risk score groups showed good discrimination for the P/F value at admission, and a positive correlation was found for the low-risk class to P/F at 48&nbsp;h after admission (adjusted R-squared = 0.48). We developed a predictive model of death for people with SARS-CoV-2 infection by including only easy-to-obtain variables (abnormal blood count, BUN, C-reactive protein, sodium and lower SpO2). It demonstrated good accuracy and high power of discrimination. The simplicity of the model makes the risk prediction applicable for patients in the Emergency Department, or during hospitalization. Although it is reasonable to assume that the model is also applicable in not-hospitalized persons, only appropriate studies can assess the accuracy of the model also for persons at home

Cooperativas de catadores de materiais recicláveis como alternativa à exclusão social e sua relação com a população de rua

A informalidade no trabalho, que marca a realidade da maioria das relações de trabalho brasileiras, somada às características encontradas na população de rua, constituem o pano de fundo social propenso à geração de formas alternativas de organização do trabalho. A informalidade no trabalho, assim como a população de rua, tem composição e origem acentuadamente heterogênea; assim, torna-se fundamental que qualquer política pública destinada a estes aspectos considere suas especificidades. Neste contexto, surgem as cooperativas de catadores de resíduos sólidos, formadas por antigos catadores de lixo e ex-moradores de rua, como alternativa à informalidade no trabalho e busca pela cidadania, dentro da perspectiva da autogestão. Por meio de uma análise atual e de uma caracterização histórica sobre experiências de cooperativas de catadores brasileiras, buscou-se mostrar a capacidade inclusiva do modelo cooperativista e da relevância das parcerias destas com o poder público e com outros atores sociais. Neste escopo, é fundamental a abordagem de experiências bem sucedidas de catadores que, unidos sob a égide do cooperativismo, com a participação do poder público e/ou independentemente dele – puderam lograr a inclusão social. A autogestão desponta, assim, como alternativa real de trabalho àqueles que se encontram marginalizados pelo sistema formal de trabalho