Molecular characterization of the diet of the planktonic community in Málaga Bay (NW Alboran Sea)

The seasonal changes in structure and functioning of the pelagic trophic web in Málaga Bay (NW Alboran Sea) are related to the annual hydrological cycle. However, time series analyses have shown that the relationship between interannual hydrological variability and the plankton community composition is weak. This might be due to different human-induced pressures (nutrient pollution, coastal fisheries) acting on different compartments of the trophic web. The net effect of all these factors would depend on how the ecosystem channels changes in the composition and abundance of each trophic level. Interactions of phytoplankton-ciliates-zooplankton might have a central role in the regulation of the trophic web in Málaga Bay, although the trophic relations of the dominant groups remain still undefined. In order to identify the dominant trophic relationships we aimed to characterise the diet of key ichthyo- and mesozooplankton species in the field. Given that gut content preys (phyto- and microplankton) are fragile and not easy to identify visually, we developed species-specific molecular markers to detect their presence/absence within the predators gut

MAFB shapes human monocyte-derived macrophage response to SARS-CoV-2 and controls severe COVID-19 biomarker expression

22 p.-6 fig.1 graph. abst.Monocyte-derived macrophages, the major source of pathogenic macrophages in COVID-19, are oppositely instructed by macrophage CSF (M-CSF) or granulocyte macrophage CSF (GM-CSF), which promote the generation of antiinflammatory/immunosuppressive MAFB+ (M-MØ) or proinflammatory macrophages (GM-MØ), respectively. The transcriptional profile of prevailing macrophage subsets in severe COVID-19 led us to hypothesize that MAFB shapes the transcriptome of pulmonary macrophages driving severe COVID-19 pathogenesis. We have now assessed the role of MAFB in the response of monocyte-derived macrophages to SARS-CoV-2 through genetic and pharmacological approaches, and we demonstrate that MAFB regulated the expression of the genes that define pulmonary pathogenic macrophages in severe COVID-19. Indeed, SARS-CoV-2 potentiated the expression of MAFB and MAFB-regulated genes in M-MØ and GM-MØ, where MAFB upregulated the expression of profibrotic and neutrophil-attracting factors. Thus, MAFB determines the transcriptome and functions of the monocyte-derived macrophage subsets that underlie pulmonary pathogenesis in severe COVID-19 and controls the expression of potentially useful biomarkers for COVID-19 severity.This work was supported by grant PID2020-114323RB-I00 from Ministerio de Ciencia e Innovación to ALC; “Ayudas FUNDACIÓN BBVA a equipos de investigación científica SARS-CoV-2 y COVID-19” to MAV and ALC; Dirección General de Innovación e Investigación Tecnológica de la Comunidad de Madrid (RETARACOVID, P2022/BMD-7274) to ALC, APK, EFR, and RD; Instituto de Salud Carlos III (grant PI20/00316 to APK, grant PI2100989 to RD, grant PI22/00428 to EFR); Red de Enfermedades Inflamatorias (RICORS RD21/0002/0034) from Instituto de Salud Carlos III and cofinanced by the European Regional Development Fund “A way to achieve Europe” (ERDF) and PRTR to APK; European Commission Horizon 2020 FP (Project VIRUSCAN FETPROACT-2016: ID 731868); Horizon Europe FP (Project EPIC-CROWN-2 ID: 101046084); and Fundación Caixa-Health Research (Project StopEbola HR18-00469) to RD. This research was also funded by the European Commission – NextGenerationEU (Regulation EU 2020/2094), through CSIC’s Global Health Platform (PTI Salud Global). MSF was funded by a Formación de Personal Investigador predoctoral fellowship from Ministerio de Ciencia e Innovación (grant PRE2018-083396). ERV was funded by a Rio-Hortega grant CM19/00149 from the Ministerio de Economía y Competitividad (Instituto de Salud Carlos III) and cofunded by the ERDF. SFDCO was funded by the PREDINMUN-COVID Grant (Fondo Supera COVID-19 from Banco de Santander and CRUE) and PDW by PI19/00096.Peer reviewe

The GSK3b-MAFB axis controls the pro-fibrotic gene profile of pathogenic monocyte-derived macrophages in severe COVID-19

1 p.-4 fig.MAF and MAFB are members of the “large MAF” transcription factor family that shape the transcriptome of antiinflammatory and pro-tumoral human macrophages. We have now determined the MAF- and MAFB-dependent gene profile of M-CSF-dependent monocyte-derived macrophages (M-MØ), and found that both factors exhibit overlapping transcriptional outcomes during monocyte-to-M-MØ differentiation, but differentially affect macrophage effector functions like production of monocyte-recruiting chemokines, T-cell activation and immunosuppression. Remarkably, MAFB was found to positively regulate the expression of the genesets that define the pathogenic monocyte-derived pulmonary macrophage subsets in COVID-19, as evidenced through siRNA-mediated silencing and analysis of MAFBoverexpressing M-MØ from a Multicentric Carpotarsal Osteolysis (MCTO) patient. MAFB silencing downregulated theexpression of genes coding for biomarkers of COVID-19 severity, and genome-wide mapping of MAFB-binding elements in M-MØ identified biomarkers of COVID-19 severity (CD163, IL10, HGF and CCL2) as direct MAFB targets. Further, and in line with the GSK3b-dependent expression of MAFB, GSK3b inhibition in M-MØ significantly boosted the expression of genes that characterize pathogenic macrophage subsets in severe COVID-19, an effect that was primarily dependent on MAFB. In addition, we have demonstrated that a large number of MAFB-dependent genes, as well as GSK3b-dependent expression of MAFB genes were modulated by SARS-Cov-2 infection on human macrophages. Globally, our results demonstrate that the GSK3b-MAFB axis controls the transcriptome of pathogenic pulmonary macrophages in COVID-19,and positively regulates the expression of biomarkers for COVID-19 severity. Thus, macrophage re-programming through modulation of GSK3 -MAFB axis has potential therapeutic strategy for COVID-19 and other inflammatory diseases.This research work was also funded by the European Commission– NextGenerationEU (Regulation EU 2020/2094), through CSIC's Global Health Platform (PTI Salud Global).Peer reviewe

SARS-CoV-2 viral load in nasopharyngeal swabs is not an independent predictor of unfavorable outcome

The aim was to assess the ability of nasopharyngeal SARS-CoV-2 viral load at first patient’s hospital evaluation to predict unfavorable outcomes. We conducted a prospective cohort study including 321 adult patients with confirmed COVID-19 through RT-PCR in nasopharyngeal swabs. Quantitative Synthetic SARS-CoV-2 RNA cycle threshold values were used to calculate the viral load in log10 copies/mL. Disease severity at the end of follow up was categorized into mild, moderate, and severe. Primary endpoint was a composite of intensive care unit (ICU) admission and/or death (n = 85, 26.4%). Univariable and multivariable logistic regression analyses were performed. Nasopharyngeal SARS-CoV-2 viral load over the second quartile (≥ 7.35 log10 copies/mL, p = 0.003) and second tertile (≥ 8.27 log10 copies/mL, p = 0.01) were associated to unfavorable outcome in the unadjusted logistic regression analysis. However, in the final multivariable analysis, viral load was not independently associated with an unfavorable outcome. Five predictors were independently associated with increased odds of ICU admission and/or death: age ≥ 70 years, SpO2, neutrophils > 7.5 × 103/µL, lactate dehydrogenase ≥ 300 U/L, and C-reactive protein ≥ 100 mg/L. In summary, nasopharyngeal SARS-CoV-2 viral load on admission is generally high in patients with COVID-19, regardless of illness severity, but it cannot be used as an independent predictor of unfavorable clinical outcome

Yeasts associated with the production of distilled alcoholic beverages

Distilled alcoholic beverages are produced firstly by fermenting sugars emanating from cereal starches (in the case of whiskies), sucrose-rich plants (in the case of rums), fructooligosaccharide-rich plants (in the case of tequila) or from fruits (in the case of brandies). Traditionally, such fermentations were conducted in a spontaneous fashion, relying on indigenous microbiota, including wild yeasts. In modern practices, selected strains of Saccharomyces cerevisiae are employed to produce high levels of ethanol together with numerous secondary metabolites (eg. higher alcohols, esters, carbonyls etc.) which greatly influence the final flavour and aroma characteristics of spirits following distillation of the fermented wash. Therefore, distillers, like winemakers, must carefully choose their yeast strain which will be very important in providing the alcohol content and the sensory profiles of spirit beverages. This Chapter discusses yeast and fermentation aspects associated with the production of selected distilled spirits and highlights similarities and differences with the production of wine

Dendritic cell deficiencies persist seven months after SARS-CoV-2 infection

Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV)-2 infection induces an exacerbated inflammation driven by innate immunity components. Dendritic cells (DCs) play a key role in the defense against viral infections, for instance plasmacytoid DCs (pDCs), have the capacity to produce vast amounts of interferon-alpha (IFN-α). In COVID-19 there is a deficit in DC numbers and IFN-α production, which has been associated with disease severity. In this work, we described that in addition to the DC deficiency, several DC activation and homing markers were altered in acute COVID-19 patients, which were associated with multiple inflammatory markers. Remarkably, previously hospitalized and nonhospitalized patients remained with decreased numbers of CD1c+ myeloid DCs and pDCs seven months after SARS-CoV-2 infection. Moreover, the expression of DC markers such as CD86 and CD4 were only restored in previously nonhospitalized patients, while no restoration of integrin β7 and indoleamine 2,3-dyoxigenase (IDO) levels were observed. These findings contribute to a better understanding of the immunological sequelae of COVID-19

Key Factors Associated With Pulmonary Sequelae in the Follow-Up of Critically Ill COVID-19 Patients

Introduction: Critical COVID-19 survivors have a high risk of respiratory sequelae. Therefore, we aimed to identify key factors associated with altered lung function and CT scan abnormalities at a follow-up visit in a cohort of critical COVID-19 survivors. Methods: Multicenter ambispective observational study in 52 Spanish intensive care units. Up to 1327 PCR-confirmed critical COVID-19 patients had sociodemographic, anthropometric, comorbidity and lifestyle characteristics collected at hospital admission; clinical and biological parameters throughout hospital stay; and, lung function and CT scan at a follow-up visit. Results: The median [p25–p75] time from discharge to follow-up was 3.57 [2.77–4.92] months. Median age was 60 [53–67] years, 27.8% women. The mean (SD) percentage of predicted diffusing lung capacity for carbon monoxide (DLCO) at follow-up was 72.02 (18.33)% predicted, with 66% of patients having DLCO < 80% and 24% having DLCO < 60%. CT scan showed persistent pulmonary infiltrates, fibrotic lesions, and emphysema in 33%, 25% and 6% of patients, respectively. Key variables associated with DLCO < 60% were chronic lung disease (CLD) (OR: 1.86 (1.18–2.92)), duration of invasive mechanical ventilation (IMV) (OR: 1.56 (1.37–1.77)), age (OR [per-1-SD] (95%CI): 1.39 (1.18–1.63)), urea (OR: 1.16 (0.97–1.39)) and estimated glomerular filtration rate at ICU admission (OR: 0.88 (0.73–1.06)). Bacterial pneumonia (1.62 (1.11–2.35)) and duration of ventilation (NIMV (1.23 (1.06–1.42), IMV (1.21 (1.01–1.45)) and prone positioning (1.17 (0.98–1.39)) were associated with fibrotic lesions. Conclusion: Age and CLD, reflecting patients’ baseline vulnerability, and markers of COVID-19 severity, such as duration of IMV and renal failure, were key factors associated with impaired DLCO and CT abnormalities

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort

Background Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster.Methods Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3.Results Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3.Conclusions During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis