Tratamientos de semillas de Hordeum vulgare con terápicos para el control de Ustilago nuda en el cultivo

PosterLa aplicación de terápicos de semillas constituye una de las herramientas más eficaces al momento de controlar el carbón volador causado por Ustilago nuda. Este patógeno se transmite por semillas por lo cual es importante conocer la cantidad de embriones infectados que tiene cada lote de semillas a sembrarse. El objetivo del trabajo fue evaluar a campo, la eficacia de control de terápicos químicos, en la localidad de Pergamino.EEA PergaminoFil: Couretot, Lucrecia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Fitopatología; ArgentinaFil: Faura, A. Rizobacter; ArgentinaFil: Mina, G. Rizobacter; Argentin

Integument Mycobiota of Wild European Hedgehogs (Erinaceus europaeus) from Catalonia, Spain

There are some reports about the risk of manipulating wild hedgehogs since they can be reservoirs of potential zoonotic agents like dermatophytes. The aim of this study was to describe the integument mycobiota, with special attention to dermatophytes of wild European hedgehogs. Samples from spines and fur were cultured separately in Sabouraud dextrose agar (SDA) with antibiotic and dermatophyte test medium (DTM) plates. Nineteen different fungal genera were isolated from 91 cultures of 102 hedgehogs. The most prevalent genera were Cladosporium (79.1%), Penicillium (74.7%), Alternaria (64.8%), and Rhizopus (63.7%). A lower prevalence of Aspergillus (P = 0,035; χ 2 = 8,633) and Arthrinium (P = 0,043; χ 2 = 8,173) was isolated during the spring time and higher frequencies of Fusarium (P = 0,015; χ 2 = 10,533) during the autumn. The prevalence of Acremonium was significantly higher in young animals (70%, 26/37) than in adults (30%, 11/37) (P = 0,019; χ 2 = 5,915). Moreover, the majority of the saprophytic species that grew at the SDA culture were also detected at the DTM. Finally, no cases of ringworm were diagnosed and no dermatophytes spp. were isolated. Concluding, this study provides the first description of fungal mycobiota of the integument of wild European hedgehogs in Spain, showing a large number of saprophytic species and the absence of dermatophytes

Application of pharmacogenomics and bioinformatics to exemplify the utility of human <i>ex vivo</i> organoculture models in the field of precision medicine

Here we describe a collaboration between industry, the National Health Service (NHS) and academia that sought to demonstrate how early understanding of both pharmacology and genomics can improve strategies for the development of precision medicines. Diseased tissue ethically acquired from patients suffering from chronic obstructive pulmonary disease (COPD), was used to investigate inter-patient variability in drug efficacy using ex vivo organocultures of fresh lung tissue as the test system. The reduction in inflammatory cytokines in the presence of various test drugs was used as the measure of drug efficacy and the individual patient responses were then matched against genotype and microRNA profiles in an attempt to identify unique predictors of drug responsiveness. Our findings suggest that genetic variation in CYP2E1 and SMAD3 genes may partly explain the observed variation in drug response

Blood Biomarker Panels for the Early Prediction of Stroke‐Associated Complications

Background Acute decompensated heart failure (ADHF) and respiratory tract infections (RTIs) are potentially life-threatening complications in patients experiencing stroke during hospitalization. We aimed to test whether blood biomarker panels might predict these complications early after admission. Methods and Results Nine hundred thirty-eight patients experiencing ischemic stroke were prospectively recruited in the Stroke-Chip study. Post-stroke complications during hospitalization were retrospectively evaluated. Blood samples were drawn within 6 hours after stroke onset, and 14 biomarkers were analyzed by immunoassays. Biomarker values were normalized using log-transformation and Z score. PanelomiX algorithm was used to select panels with the best accuracy for predicting ADHF and RTI. Logistic regression models were constructed with the clinical variables and the biomarker panels. The additional predictive value of the panels compared with the clinical model alone was evaluated by receiver operating characteristic curves. An internal validation through a 10-fold cross-validation with 3 repeats was performed. ADHF and RTI occurred in 19 (2%) and 86 (9.1%) cases, respectively. Three-biomarker panels were developed as predictors: vascular adhesion protein-1 >5.67, NT-proBNP (N-terminal pro-B-type natriuretic peptide) >4.98 and d-dimer >5.38 (sensitivity, 89.5%; specificity, 71.7%) for ADHF; and interleukin-6 >3.97, von Willebrand factor >3.67, and d-dimer >4.58 (sensitivity, 82.6%; specificity, 59.8%) for RTI. Both panels independently predicted stroke complications (panel for ADHF: odds ratio [OR] [95% CI], 10.1 [3-52.2]; panel for RTI: OR, 3.73 [1.95-7.14]) after adjustment by clinical confounders. The addition of the panel to clinical predictors significantly improved areas under the curve of the receiver operating characteristic curves in both cases. Conclusions Blood biomarkers could be useful for the early prediction of ADHF and RTI. Future studies should assess the usefulness of these panels in front of patients experiencing stroke with respiratory symptoms such as dyspnea

AltitudeOmics: Red Blood Cell metabolic adaptation to high altitude hypoxia

Red blood cells (RBCs) are key players in systemic oxygen transport. RBCs respond to in vitro hypoxia  through  the so-called  oxygen-dependent  metabolic  regulation,  which  involves  the competitive  binding  of  deoxyhemoglobin  and  glycolytic  enzymes  to  the  N-terminal  cytosolic domain  of  band  3.  This  mechanism  promotes  the  accumulation  of  2,3-DPG,  stabilizing  the deoxygenated state of hemoglobin, and cytosol acidification, triggering oxygen off-loading through the  Bohr  effect.  Despite  in  vitro  studies,  in  vivo adaptations  to  hypoxia  have  not  yet  been completely elucidated. Within  the  framework  of  the AltitudeOmics  study,  erythrocytes  were  collected  from  21 healthy volunteers at sea level, after exposure to high altitude (5260m) for 1, 7 and 16days, and following  reascent  after  7days  at 1525m.  UHPLC-MS  metabolomics  results  were  correlated  to physiological and athletic performance parameters. Immediate  metabolic  adaptations  were  noted as early as a few hours from ascending  to >5000m, and maintained for 16 days at high altitude.  Consistent with the mechanisms elucidated in vitro, hypoxia promoted glycolysis and deregulated the pentose phosphate pathway, as well purine catabolism, glutathione homeostasis, arginine/nitric oxide and sulphur/H2S metabolism. Metabolic adaptations were preserved one week after descent, consistently with improved physical performances in comparison to the first ascendance, suggesting a mechanism of metabolic memory

Factors associated with the clinical outcome of patients with relapsed/refractory CD19+acute lymphoblastic leukemia treated with ARI-0001 CART19-cell therapy

The prognosis of patients with relapsed/refractory (R/R) acute lymphoblastic leukemia (ALL) remains poor, particularly for those relapsing after allogeneic hema-topoietic cell transplantation (alloHCT). Novel agents such as inotuzumab ozogamicin or blinatumomab achieve increased response rates, but these are generally transient unless followed by alloHCT. Chimeric antigen receptors (CAR) targeting CD19 have shown promising results in R/R ALL, and one of these products (tisagenlecleucel) has been approved for the treatment of patients with R/R ALL up to 25 years of age

Why is the Winner the Best?

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work

Multi-Parametric Analysis and Modeling of Relationships between Mitochondrial Morphology and Apoptosis

Mitochondria exist as a network of interconnected organelles undergoing constant fission and fusion. Current approaches to study mitochondrial morphology are limited by low data sampling coupled with manual identification and classification of complex morphological phenotypes. Here we propose an integrated mechanistic and data-driven modeling approach to analyze heterogeneous, quantified datasets and infer relations between mitochondrial morphology and apoptotic events. We initially performed high-content, multi-parametric measurements of mitochondrial morphological, apoptotic, and energetic states by high-resolution imaging of human breast carcinoma MCF-7 cells. Subsequently, decision tree-based analysis was used to automatically classify networked, fragmented, and swollen mitochondrial subpopulations, at the single-cell level and within cell populations. Our results revealed subtle but significant differences in morphology class distributions in response to various apoptotic stimuli. Furthermore, key mitochondrial functional parameters including mitochondrial membrane potential and Bax activation, were measured under matched conditions. Data-driven fuzzy logic modeling was used to explore the non-linear relationships between mitochondrial morphology and apoptotic signaling, combining morphological and functional data as a single model. Modeling results are in accordance with previous studies, where Bax regulates mitochondrial fragmentation, and mitochondrial morphology influences mitochondrial membrane potential. In summary, we established and validated a platform for mitochondrial morphological and functional analysis that can be readily extended with additional datasets. We further discuss the benefits of a flexible systematic approach for elucidating specific and general relationships between mitochondrial morphology and apoptosis