Efecto de una cepa de Fusarium oxysporum y de diversas levaduras sobre la nutrición férrica de plantas de pepino y tomate

Trabajo presentado en el XVI Congreso Nacional de Ciencias Hortícolas, celebrado en Córdoba del 17 al 22 de octubre de 2021,El hierro (Fe) es un micronutriente esencial para las plantas. En suelos calizos se encuentra en su forma oxidada (Fe 3+), presentando baja solubilidad y disponibilidad para las plantas. Bajo deficiencia de Fe, las plantas dicotiledóneas inducen diversas respuestas fisiológicas y morfológicas en sus raíces para facilitar así su captación y paliar los efectos que produce su deficiencia. Existen evidencias de que determinados microorganismos rizosféricos, como los que provocan la Respuesta Sistémica Inducida (ISR), pueden facilitar la nutrición férrica de las plantas. El objetivo de este trabajo ha sido, por una parte, estudiar el efecto de la cepa no patogénica de Fusarium oxysporum (FO12), posiblemente inductora de ISR, sobre el crecimiento y clorosis de plantas de tomate (Solanum lycopersicum Mill.), y sobre la colonización de raíces de pepino (Cucumis sativus L.). Por otra parte, estudiar el efecto de determinadas levaduras (Debaryomyces hansenii, Saccharomyces cerevisiae y Hansenula polymorpha) sobre diversas respuestas a la deficiencia de Fe en plantas de pepino. Los experimentos con tomate se han desarrollado en suelo calizo y los de pepino en cultivo hidropónico. Los resultados obtenidos con FO12 han mostrado su capacidad para colonizar endofiticamente las raíces de pepino y su efecto promotor del crecimiento, la concentración de clorofila y de Fe (en hojas) en plantas de tomate. Las diferentes levaduras utilizadas han causado inducción de la capacidad reductora de Fe 3+, de la acidificación de la rizosfera, y de la proliferación de pelos radicales en la zona subapical de las raíces de pepino. Estos resultados sugieren que, tanto FO12 como las diferentes levaduras utilizadas, tienen potencial como biofertilizantes de Fe.Plan Propio de la Universidad de Córdoba y Ministerio de Ciencia e Innovación

Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes

Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson’s disease (PD) and Alzheimer’s disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues

Usefulness of midregional proadrenomedullin to predict poor outcome in patients with community acquired pneumonia.

midregional proadrenomedullin (MR-proADM) is a prognostic biomarker in patients with community-acquired pneumonia (CAP). We sought to confirm whether MR-proADM added to Pneumonia Severity Index (PSI) improves the potential prognostic value of PSI alone, and tested to what extent this combination could be useful in predicting poor outcome of patients with CAP in an Emergency Department (ED).Consecutive patients diagnosed with CAP were enrolled in this prospective, single-centre, observational study. We analyzed the ability of MR-proADM added to PSI to predict poor outcome using receiver operating characteristic (ROC) curves, logistic regression and risk reclassification and comparing it with the ability of PSI alone. The primary outcome was "poor outcome", defined as the incidence of an adverse event (ICU admission, hospital readmission, or mortality at 30 days after CAP diagnosis).226 patients were included; 33 patients (14.6%) reached primary outcome. To predict primary outcome the highest area under curve (AUC) was found for PSI (0.74 [0.64-0.85]), which was not significantly higher than for MR-proADM (AUC 0.72 [0.63-0.81, p > 0.05]). The combination of PSI and MR-proADM failed to improve the predictive potential of PSI alone (AUC 0.75 [0.65-0.85, p=0.56]). Ten patients were appropriately reclassified when the combined PSI and MR-proADM model was used as compared with the model of PSI alone. Net reclassification improvement (NRI) index was statistically significant (7.69%, p = 0.03) with an improvement percentage of 3.03% (p = 0.32) for adverse event, and 4.66% (P = 0.02) for no adverse event.MR-proADM in combination with PSI may be helpful in individual risk stratification for short-term poor outcome of CAP patients, allowing a better reclassification of patients compared with PSI alone

ROC curves for predicting adverse event.

<p>Fig 3a. ROC curves for different biomarkers and PSI. Fig 3b. ROC curves for the PSI & MR-proADM prediction model compared to PSI</p

MR-proADM and CAP severity.

<p>Fig 2a. Relationship between MR-proADM and severity as established by the PSI. Analysis performed with the Jonckheere-Terpstra trend test. Tau b: Kendall’s rank correlation. p: level of statistical significance. Fig 2b. MR-proADM levels according to hospital admission, bacteremia, ICU admission, hospital readmission and 30-day mortality.</p

Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.

<p>Kaplan-Meier survival curves at 90-days mortality according to MR-proADM quartiles.</p

Baseline characteristics of the NACURG cohort.

<p>Differences between patients who died and those who survived were assessed by Cox regression survival analysis for independent continuous variables, and a Kaplan-Meyer survival curve with log-rank tests for independent categorical variables. Differences between patients with or without adverse event were assessed by the Student t test or the non-parametric Mann-Whitney U test for continuous variables and the [χ²] test or the Fisher exact test for dichotomous categorical variables.</p><p>*p: degree of statistical significance.</p><p>**Lactate levels only available for 122 patients (54%) and not therefore included in the multivariate analysis.</p><p>***The percentage of readmissions out of the total number of patients discharged (221; 4 patients died while in hospital and 1 was still inpatient at 30 days).</p><p>Relationship between different independent variables and adverse event and 90-day mortality after consulting the Emergency Department.</p

Patients included in the study.

<p>Patients included in the study.</p