• MeSH
• jazyk (prostředek komunikace) MeSH
• lidé MeSH
• software trendy   MeSH
• studium lékařství * metody   MeSH
• umělá inteligence * trendy   MeSH
• vzdělávací modely MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• novinové články MeSH

BACKGROUND: Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease epidemiology, one can maximise the predictive performance of such forecasts if multiple models are combined into an ensemble. Here, we report on the performance of ensembles in predicting COVID-19 cases and deaths across Europe between 08 March 2021 and 07 March 2022. METHODS: We used open-source tools to develop a public European COVID-19 Forecast Hub. We invited groups globally to contribute weekly forecasts for COVID-19 cases and deaths reported by a standardised source for 32 countries over the next 1-4 weeks. Teams submitted forecasts from March 2021 using standardised quantiles of the predictive distribution. Each week we created an ensemble forecast, where each predictive quantile was calculated as the equally-weighted average (initially the mean and then from 26th July the median) of all individual models' predictive quantiles. We measured the performance of each model using the relative Weighted Interval Score (WIS), comparing models' forecast accuracy relative to all other models. We retrospectively explored alternative methods for ensemble forecasts, including weighted averages based on models' past predictive performance. RESULTS: Over 52 weeks, we collected forecasts from 48 unique models. We evaluated 29 models' forecast scores in comparison to the ensemble model. We found a weekly ensemble had a consistently strong performance across countries over time. Across all horizons and locations, the ensemble performed better on relative WIS than 83% of participating models' forecasts of incident cases (with a total N=886 predictions from 23 unique models), and 91% of participating models' forecasts of deaths (N=763 predictions from 20 models). Across a 1-4 week time horizon, ensemble performance declined with longer forecast periods when forecasting cases, but remained stable over 4 weeks for incident death forecasts. In every forecast across 32 countries, the ensemble outperformed most contributing models when forecasting either cases or deaths, frequently outperforming all of its individual component models. Among several choices of ensemble methods we found that the most influential and best choice was to use a median average of models instead of using the mean, regardless of methods of weighting component forecast models. CONCLUSIONS: Our results support the use of combining forecasts from individual models into an ensemble in order to improve predictive performance across epidemiological targets and populations during infectious disease epidemics. Our findings further suggest that median ensemble methods yield better predictive performance more than ones based on means. Our findings also highlight that forecast consumers should place more weight on incident death forecasts than incident case forecasts at forecast horizons greater than 2 weeks. FUNDING: AA, BH, BL, LWa, MMa, PP, SV funded by National Institutes of Health (NIH) Grant 1R01GM109718, NSF BIG DATA Grant IIS-1633028, NSF Grant No.: OAC-1916805, NSF Expeditions in Computing Grant CCF-1918656, CCF-1917819, NSF RAPID CNS-2028004, NSF RAPID OAC-2027541, US Centers for Disease Control and Prevention 75D30119C05935, a grant from Google, University of Virginia Strategic Investment Fund award number SIF160, Defense Threat Reduction Agency (DTRA) under Contract No. HDTRA1-19-D-0007, and respectively Virginia Dept of Health Grant VDH-21-501-0141, VDH-21-501-0143, VDH-21-501-0147, VDH-21-501-0145, VDH-21-501-0146, VDH-21-501-0142, VDH-21-501-0148. AF, AMa, GL funded by SMIGE - Modelli statistici inferenziali per governare l'epidemia, FISR 2020-Covid-19 I Fase, FISR2020IP-00156, Codice Progetto: PRJ-0695. AM, BK, FD, FR, JK, JN, JZ, KN, MG, MR, MS, RB funded by Ministry of Science and Higher Education of Poland with grant 28/WFSN/2021 to the University of Warsaw. BRe, CPe, JLAz funded by Ministerio de Sanidad/ISCIII. BT, PG funded by PERISCOPE European H2020 project, contract number 101016233. CP, DL, EA, MC, SA funded by European Commission - Directorate-General for Communications Networks, Content and Technology through the contract LC-01485746, and Ministerio de Ciencia, Innovacion y Universidades and FEDER, with the project PGC2018-095456-B-I00. DE., MGu funded by Spanish Ministry of Health / REACT-UE (FEDER). DO, GF, IMi, LC funded by Laboratory Directed Research and Development program of Los Alamos National Laboratory (LANL) under project number 20200700ER. DS, ELR, GG, NGR, NW, YW funded by National Institutes of General Medical Sciences (R35GM119582; the content is solely the responsibility of the authors and does not necessarily represent the official views of NIGMS or the National Institutes of Health). FB, FP funded by InPresa, Lombardy Region, Italy. HG, KS funded by European Centre for Disease Prevention and Control. IV funded by Agencia de Qualitat i Avaluacio Sanitaries de Catalunya (AQuAS) through contract 2021-021OE. JDe, SMo, VP funded by Netzwerk Universitatsmedizin (NUM) project egePan (01KX2021). JPB, SH, TH funded by Federal Ministry of Education and Research (BMBF; grant 05M18SIA). KH, MSc, YKh funded by Project SaxoCOV, funded by the German Free State of Saxony. Presentation of data, model results and simulations also funded by the NFDI4Health Task Force COVID-19 (https://www.nfdi4health.de/task-force-covid-19-2) within the framework of a DFG-project (LO-342/17-1). LP, VE funded by Mathematical and Statistical modelling project (MUNI/A/1615/2020), Online platform for real-time monitoring, analysis and management of epidemic situations (MUNI/11/02202001/2020); VE also supported by RECETOX research infrastructure (Ministry of Education, Youth and Sports of the Czech Republic: LM2018121), the CETOCOEN EXCELLENCE (CZ.02.1.01/0.0/0.0/17-043/0009632), RECETOX RI project (CZ.02.1.01/0.0/0.0/16-013/0001761). NIB funded by Health Protection Research Unit (grant code NIHR200908). SAb, SF funded by Wellcome Trust (210758/Z/18/Z).

• MeSH
• COVID-19 * diagnóza   epidemiologie   MeSH
• epidemie * MeSH
• infekční nemoci * MeSH
• lidé MeSH
• předpověď MeSH
• retrospektivní studie MeSH
• statistické modely MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Research Support, N.I.H., Extramural MeSH
• Research Support, U.S. Gov't, Non-P.H.S. MeSH
• Research Support, U.S. Gov't, P.H.S. MeSH

Metabolic flux investigations of cells and tissue samples are a rapidly advancing tool in diverse research areas. Reliable methods of data normalization are crucial for an adequate interpretation of results and to avoid a misinterpretation of experiments and incorrect conclusions. The most common methods for metabolic flux data normalization are to cell number, DNA and protein. Data normalization may be affected by a variety of factors, such as density, healthy state, adherence efficiency, or proportional seeding of cells. The mussel-derived adhesive Cell-Tak is often used to immobilize poorly adherent cells. Here we demonstrate that this coating strongly affects the fluorescent detection of DNA leading to an incorrect and highly variable normalization of metabolic flux data. Protein assays are much less affected and cell counting can virtually completely remove the effect of the coating. Cell-Tak coating also affects cell shape in a cell line-specific manner and may change cellular metabolism. Based on these observations we recommend cell counting as a gold standard normalization method for Seahorse metabolic flux measurements with protein content as a reasonable alternative.

• MeSH
• DNA * MeSH
• membránové proteiny * MeSH
• Publikační typ
• časopisecké články MeSH

• MeSH
• COVID-19 * patofyziologie   přenos   MeSH
• lidé MeSH
• pandemie MeSH
• SARS-CoV-2 MeSH
• Check Tag
• lidé MeSH

• MeSH
• COVID-19 MeSH
• dějiny 21. století MeSH
• sociologie MeSH
• věda * MeSH
• výzkum MeSH
• Check Tag
• dějiny 21. století MeSH

Granulosa cells (GCs) are somatic cells essential for establishing and maintaining bi-directional communication with the oocytes. This connection has a profound importance for the delivery of energy substrates, structural components and ions to the maturing oocyte through gap junctions. Cumulus cells, group of closely associated GCs, surround the oocyte and can diminished the effect of harmful environmental insults. Both GCs and oocytes prefer different energy substrates in their cellular metabolism: GCs are more glycolytic, whereas oocytes rely more on oxidative phosphorylation pathway. The interconnection of these cells is emphasized by the fact that GCs supply oocytes with intermediates produced in glycolysis. The number of GCs surrounding the oocyte and their age affect the energy status of oocytes. This review summarises available studies collaboration of cellular types in the ovarian follicle from the point of view of energy metabolism, signaling and protection of toxic insults. A deeper knowledge of the underlying mechanisms is crucial for better methods to prevent and treat infertility and to improve the technology of in vitro fertilization.

• MeSH
• antioxidancia metabolismus   MeSH
• energetický metabolismus MeSH
• folikulární buňky účinky léků   metabolismus   MeSH
• lidé MeSH
• metabolismus lipidů MeSH
• metabolismus sacharidů MeSH
• nebezpečné látky toxicita   MeSH
• oocyty růst a vývoj   metabolismus   MeSH
• reaktivní formy kyslíku metabolismus   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• ženské pohlaví MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

BACKGROUND/OBJECTIVES: Branched chain amino acids (BCAA) are among nutrients strongly linked with insulin sensitivity (IS) measures. We investigated the effects of a chronic increase of BCAA intake on IS in two groups of healthy subjects differing in their basal consumption of BCAA, that is, vegans and omnivores. SUBJECTS/METHODS: Eight vegans and eight matched omnivores (five men and three women in each group) received 15 g (women) or 20 g (men) of BCAA daily for 3 months. Anthropometry, blood analyses, glucose clamp, arginine test, subcutaneous abdominal adipose tissue (AT) and skeletal muscle (SM) biopsies (mRNA levels of selected metabolic markers, respiratory chain (RC) activity) were performed at baseline, after the intervention and after a 6 month wash-out period. RESULTS: Compared with omnivores, vegans had higher IS at baseline (GIR, glucose infusion rate: 9.6±2.4 vs 7.1±2.4 mg/kg/min, 95% CI for difference: 0.55 to 5.82) that declined after the intervention and returned to baseline values after the wash-out period (changes in GIR with 95% CI, 3-0 months: -1.64 [-2.5; -0.75] and 9-3 months: 1.65 [0.75; 2.54] mg/kg/min). No such change was observed in omnivores. In omnivores the intervention led to an increased expression of lipogenic genes (DGAT2, FASN, PPARγ, SCD1) in AT. SM RC activity increased in both groups. CONCLUSIONS: Negative impact of increased BCAA intake on IS was only detected in vegans, that is, subjects with low basal amino acids/BCAA intake, which appear to be unable to induce sufficient compensatory changes within AT and SM on a BCAA challenge.

• MeSH
• antropometrie MeSH
• cvičení MeSH
• dieta veganská MeSH
• dieta MeSH
• dietární expozice škodlivé účinky   MeSH
• dietní proteiny aplikace a dávkování   MeSH
• dospělí MeSH
• glykemický clamp MeSH
• inzulin krev   MeSH
• inzulinová rezistence MeSH
• kosterní svaly účinky léků   metabolismus   MeSH
• krevní glukóza metabolismus   MeSH
• lidé MeSH
• mladý dospělý MeSH
• prospektivní studie MeSH
• průzkumy a dotazníky MeSH
• vegani * MeSH
• větvené aminokyseliny aplikace a dávkování   krev   MeSH
• vztah mezi dávkou a účinkem léčiva MeSH
• Check Tag
• dospělí MeSH
• lidé MeSH
• mladý dospělý MeSH
• mužské pohlaví MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

Obesity is often associated with metabolic impairments in peripheral tissues. Evidence suggests an excess of free fatty acids (FFA) as one factor linking obesity and related pathological conditions and the impact of FFA overload on skeletal muscle metabolism is described herein. Obesity is associated with dysfunctional adipose tissue unable to buffer the flux of dietary lipids. Resulting increased levels and fluxes of plasma FFA lead to ectopic lipid deposition and lipotoxicity. FFA accumulated in skeletal muscle are associated with insulin resistance and overall cellular dysfunction. Mechanisms supposed to be involved in these conditions include the Randle cycle, intracellular accumulation of lipid metabolites, inflammation and mitochondrial dysfunction or mitochondrial stress. These mechanisms are described and discussed in the view of current experimental evidence with an emphasis on conflicting theories of decreased vs. increased mitochondrial fat oxidation associated with lipid overload. Since different types of FFA may induce diverse metabolic responses in skeletal muscle cells, this review also focuses on cellular mechanisms underlying the different action of saturated and unsaturated FFA.

• MeSH
• energetický metabolismus fyziologie   MeSH
• kosterní svaly metabolismus   patologie   MeSH
• kyseliny mastné neesterifikované metabolismus   MeSH
• lidé MeSH
• obezita metabolismus   patologie   MeSH
• tuková tkáň metabolismus   patologie   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

• Publikační typ
• abstrakt z konference MeSH