Pain associated with COVID-19 vaccination is unrelated to skin biopsy abnormalities

Previous clinical observations raised the possibility that COVID-19 vaccination might trigger a small-fibre neuropathy.Objectives:In this uncontrolled observational study, we aimed to identify small fibre damage in patients complaining of generalized sensory symptoms and pain after COVID-19 vaccination.Methods:We collected clinical data, including a questionnaire for assessing autonomic symptoms (Composite Autonomic Symptom Score-31), and investigated quantitative sensory testing (QST) and skin biopsy in 15 prospectively enrolled patients with generalized sensory symptoms and pain after COVID-19 vaccination. Nine patients complaining of orthostatic intolerance also underwent cardiovascular autonomic tests.Results:We found that all patients experienced widespread pain, and most of them (11 of 15) had a fibromyalgia syndrome. All patients had normal skin biopsy findings, and in the 9 patients with orthostatic intolerance, cardiovascular autonomic tests showed normal findings. Nevertheless, 5 patients had cold and warm detection abnormalities at the QST investigation.Conclusions:In our study, most patients complaining of generalized sensory symptoms and pain after COVID-19 vaccination had clinical and diagnostic test findings compatible with a fibromyalgia syndrome. Although the abnormal QST findings we found in 5 patients might be compatible with a small-fibre neuropathy, they should be cautiously interpreted given the psychophysical characteristics of this diagnostic test. Further larger controlled studies are needed to define precisely the association between small fibre damage and COVID-19 vaccination

Anesthesiology Posters - 2019

Anesthesiology Postershttps://scholarlycommons.libraryinfo.bhs.org/research_education/1000/thumbnail.jp

Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms

Gianluca Tramontana was supported by the GEOCARBON EU FP7 project (GA 283080). Dario Papale, Martin Jung and Markus Reichstein acknowledge funding from the EU FP7 project GEOCARBON (grant agreement no. 283080) and the EU H2020 BACI project (grant agreement no. 640176). Gustau Camps-Valls wants to acknowledge the support by an ERC Consolidator Grant with grant agreement 647423 (SEDAL). Kazuhito Ichii was supported by Environment Research and Technology Development Funds (2-1401) from the Ministry of the Environment of Japan and the JAXA Global Change Observation Mission (GCOM) project (no. 115). Christopher R. Schwalm was supported by National Aeronautics and Space Administration (NASA) grants nos. NNX12AP74G, NNX10AG01A, and NNX11AO08A. M. Altaf Arain thanks the support of Natural Sciences and Engineering Research Council (NSREC) of Canada. Penelope Serrano Ortiz was partially supported by the GEISpain project (CGL2014-52838-C2-1-R) funded by the Spanish Ministry of Economy and Competitiveness and the European Union ERDF funds. Sebastian Wolf acknowledges support from a Marie Curie International Outgoing Fellowship (European Commission, grant 300083). The FLUXCOM initiative is coordinated by Martin Jung, Max Planck Institute for Biogeochemistry (Jena, Germany). This work used eddy-covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, FluxnetCanada (supported by CFCAS, NSERC, BIOCAP, Environment Canada, and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia, USCCC. We acknowledge the financial support to the eddy-covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, the Max Planck Institute for Biogeochemistry, the National Science Foundation, the University of Tuscia and the US Department of Energy, and the databasing and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, the University of California - Berkeley, and the University of Virginia.Spatio-temporal fields of land–atmosphere fluxes derived from data-driven models can complement simulations by process-based land surface models. While a number of strategies for empirical models with eddy-covariance flux data have been applied, a systematic intercomparison of these methods has been missing so far. In this study, we performed a cross-validation experiment for predicting carbon dioxide, latent heat, sensible heat and net radiation fluxes across different ecosystem types with 11 machine learning (ML) methods from four different classes (kernel methods, neural networks, tree methods, and regression splines). We applied two complementary setups: (1) 8-day average fluxes based on remotely sensed data and (2) daily mean fluxes based on meteorological data and a mean seasonal cycle of remotely sensed variables. The patterns of predictions from different ML and experimental setups were highly consistent. There were systematic differences in performance among the fluxes, with the following ascending order: net ecosystem exchange (R2  0.6), gross primary production (R2> 0.7), latent heat (R2 > 0.7), sensible heat (R2 > 0.7), and net radiation (R2 > 0.8). The ML methods predicted the across-site variability and the mean seasonal cycle of the observed fluxes very well (R2 > 0.7), while the 8-day deviations from the mean seasonal cycle were not well predicted (R2 < 0.5). Fluxes were better predicted at forested and temperate climate sites than at sites in extreme climates or less represented by training data (e.g., the tropics). The evaluated large ensemble of ML-based models will be the basis of new global flux products.European Union (EU) GA 283080 283080 640176European Research Council (ERC) 647423Ministry of the Environment, Japan 2-1401JAXA Global Change Observation Mission (GCOM) project 115National Aeronautics & Space Administration (NASA) NNX12AP74G NNX10AG01A NNX11AO08ANatural Sciences and Engineering Research Council of CanadaGEISpain project - Spanish Ministry of Economy and Competitiveness CGL2014-52838-C2-1-REuropean Commission Joint Research Centre 300083United States Department of Energy (DOE) DE-FG02-04ER63917 DE-FG02-04ER63911FAO-GTOS-TCOiLEAPSMax Planck Institute for BiogeochemistryNational Science Foundation (NSF)University of Tusci

Design of the ELIMAIA ion collection system

A system of permanent magnet quadrupoles (PMQs) is going to be realized byINFNLNS to be used as a collection system for the injection of laser driven ionbeams up to 60 AMeV in an energy selector based on four resistive dipoles. Thissystem is the first element of the ELIMED (ELI-Beamlines MEDical andMultidisciplinary applications) beam transport, dosimetry and irradiation linethat will be developed by INFN-LNS (It) and installed at the ELI-Beamlinesfacility in Prague (Cz). ELIMED will be the first users open transportbeam-line where a controlled laser-driven ion beam will be used formultidisciplinary researches. The definition of well specified characteristics,both in terms of performances and field quality, of the magnetic lenses iscrucial for the system realization, for the accurate study of the beam dynamicsand for the proper matching with the magnetic selection system which will bedesigned in the next months. Here, we report the design of the collection system and the adopted solutionsin order to realize a robust system form the magnetic point of view. Moreover,the first preliminary transport simulations are also described

Vancomycin exposure and acute kidney injury outcome: A Snapshot From the CAMERA2 Study

Among patients with methicillin-resistant Staphylococcus aureus (MRSA) bacteremia from a prospective randomized clinical trial, acute kidney injury (AKI) rates increased with increasing vancomycin exposure, even within the therapeutic range. AKI was independently more common for the (flu)cloxacillin group. Day 2 vancomycin AUC ≥470 mg·h/L was significantly associated with AKI, independent of (flu)cloxacillin receipt

The new Italian SIDAPA Baseline Series for patch testing (2023): an update according to the new regulatory pathway for contact allergens

Allergic contact dermatitis (ACD) is a common inflammatory skin disease caused by delayed hypersensitivity to chemical and biotic contact allergens. ACD significantly affects the patients' quality of life negatively impacting both occupational and non-occupational settings. Patch testing is the gold standard diagnostic in vivo test to precise the ACD etiology and to correctly perform prevention. According to the Italian Medicines Agency (AIFA) legislative decree no. 178 of 29th May 1991, allergens are defined as medicines and therefore they are subject to strict regulation. In 2017, AIFA (decree no. 2130/2017) started a procedure to regulate contact allergens on the Italian market and actually the contact allergens temporarily authorized are reported in AIFA decree no. 98/2022, valid until November 2023. The availability on the market of contact allergens to diagnose ACD and continuous updating on the basis of new epidemiological trends are mandatory, jointly with the continuous update of the baseline and integrative series for patch testing. For this reason, the scientific community represented in Italy by the Skin Allergies Study Group of SIDeMaST (Italian Society of Dermatology and Venereology) and SIDAPA (Italian Society of Allergological, Occupational and Environmental Dermatology) are constantly working, in close relationship with the European scientific communities with large expertise in this important sector of the modern Dermatology. Herein, we report the setting up of regulatory legislation by AIFA and the new Italian Adult Baseline Series for patch testing

Understanding Streptococcus suis serotype 2 infection in pigs through a transcriptional approach

<p>Abstract</p> <p>Background</p> <p><it>Streptococcus suis </it>serotype 2 (<it>S. suis </it>2) is an important pathogen of pigs. <it>S suis 2 </it>infections have high mortality rates and are characterized by meningitis, septicemia and pneumonia. <it>S. suis </it>2 is also an emerging zoonotic agent and can infect humans that are exposed to pigs or their by-products. To increase our knowledge of the pathogenesis of meningitis, septicemia and pneumonia in pigs caused by <it>S. suis </it>2, we profiled the response of peripheral blood mononuclear cells <b>(</b>PBMC), brain and lung tissues to infection with <it>S. suis </it>2 strain SC19 using the Affymetrix Porcine Genome Array.</p> <p>Results</p> <p>A total of 3,002 differentially expressed transcripts were identified in the three tissues, including 417 unique genes in brain, 210 in lung and 213 in PBMC. These genes showed differential expression (DE) patterns on analysis by visualization and integrated discovery (DAVID). The DE genes involved in the immune response included genes related to the inflammatory response (CD163), the innate immune response (TLR2, TLR4, MYD88, TIRAP), cell adhesion (CD34, SELE, SELL, SELP, ICAM-1, ICAM-2, VCAM-1), antigen processing and presentation (MHC protein complex) and angiogenesis (VEGF), together with genes encoding cytokines (interleukins). Five selected genes were validated by qRT-PCR analysis.</p> <p>Conclusions</p> <p>We studied the response to infection with <it>S. suis </it>2 strain SC19 by microarray analysis. Our findings confirmed some genes identified in previous studies and discovered numerous additional genes that potentially function in <it>S. suis </it>2 infections in vivo. This new information will form the foundation of future investigations into the pathogenesis of <it>S. suis</it>.</p