Screening of Triploid Banana Population Under Natural and Controlled Black Sigatoka Disease for Genomic Selection.

Black sigatoka disease (BSD) is the most important foliar threat in banana production, and breeding efforts against it should take advantage of genomic selection (GS), which has become one of the most explored tools to increase genetic gain, save time, and reduce selection costs. To evaluate the potential of GS in banana for BSD, 210 triploid accessions were obtained from the African Banana and Plantain Research Center to constitute a training population. The variability in the population was assessed at the phenotypic level using BSD- and agronomic-related traits and at the molecular level using single-nucleotide polymorphisms (SNPs). The analysis of variance showed a significant difference between accessions for almost all traits measured, although at the genomic group level, there was no significant difference for BSD-related traits. The index of non-spotted leaves among accessions ranged from 0.11 to 0.8. The accessions screening in controlled conditions confirmed the susceptibility of all genomic groups to BSD. The principal components analysis with phenotypic data revealed no clear diversity partition of the population. However, the structure analysis and the hierarchical clustering analysis with SNPs grouped the population into four clusters and two subpopulations, respectively. The field and laboratory screening of the banana GS training population confirmed that all genomic groups are susceptible to BSD but did not reveal any genetic structure, whereas SNP markers exhibited clear genetic structure and provided useful information in the perspective of applying GS.

Survival and response to pulmonary vasodilator therapies in patients with chronic obstructive pulmonary disease and pulmonary vascular phenotype.

BACKGROUND: The aim of the study was to describe and investigate the effect of pulmonary arterial hypertension (PAH) therapies in a cohort of patients with severe precapillary pulmonary hypertension (PH) associated with chronic obstructive pulmonary disease (COPD; PH-COPD), and to assess factors predictive of treatment response and mortality. MATERIAL AND METHODS: We retrospectively included patients with severe incident PH-COPD who received PAH therapy and underwent RHC at diagnosis and on treatment. RESULTS: From 2015 to 2022, 35 severe PH-COPD patients, with clinical features of pulmonary vascular phenotype, were included. Seventeen (48.5%) patients were treated with combined PAH therapy. PAH therapy led to a significant improvement in hemodynamics (PVR -3.5 Wood Units (-39.3%); p < 0.0001), and in the simplified four-strata risk-assessment score, which improved by at least one category in 21 (60%) patients. This effect was more pronounced in patients on dual therapy. Kaplan-Meier estimated survival rates at 1, 3 and 5 years were 94%, 65% and 42% respectively. Univariate analysis showed a significant reduction in survival in patients with a higher simplified risk score at follow-up (Hazard ratio (HR) 2.88 [1.16-7.15]; p = 0.02). Hypoxemia <50 mmHg was correlated to mortality in multivariate analysis (HR 4.33 [1.08-17.42]; p = 0.04). CONCLUSIONS: Our study confirms the poor prognosis of patients with COPD and a pulmonary vascular phenotype and the potential interest of combined PAH therapy in this population, with good tolerability and greater clinical and hemodynamic improvement than monotherapy. Using the simplified risk score during follow-up could be of interest in this population.

A methodological review of the high-dimensional propensity score in comparative-effectiveness and safety-of-interventions research finds incomplete reporting relative to algorithm development and robustness.

OBJECTIVES: The use of secondary databases has become popular for evaluating the effectiveness and safety of interventions in real-life settings. However, the absence of important confounders in these databases is challenging. To address this issue, the high-dimensional propensity score (hdPS) algorithm was developed in 2009. This algorithm uses proxy variables for mitigating confounding by combining information available across several healthcare dimensions. This study assessed the methodology and reporting of the hdPS in comparative effectiveness and safety research. STUDY DESIGN AND SETTING: In this methodological review, we searched PubMed and Google Scholar from July 2009 to May 2022 for studies that used the hdPS for evaluating the effectiveness or safety of healthcare interventions. Two reviewers independently extracted study characteristics and assessed how the hdPS was applied and reported. Risk of bias was evaluated with the Risk Of Bias In Non-randomised Studies - of Interventions (ROBINS-I) tool. RESULTS: In total, 136 studies met the inclusion criteria; the median publication year was 2018 (Q1-Q3 2016-2020). The studies included 192 datasets, mostly North American databases (n = 132, 69%). The hdPS was used in primary analysis in 120 studies (88%). Dimensions were defined in 101 studies (74%), with a median of 5 (Q1-Q3 4-6) dimensions included. A median of 500 (Q1-Q3 200-500) empirically identified covariates were selected. Regarding hdPS reporting, only 11 studies (8%) reported all recommended items. Most studies (n = 81, 60%) had a moderate overall risk of bias. CONCLUSION: There is room for improvement in the reporting of hdPS studies, especially regarding the transparency of methodological choices that underpin the construction of the hdPS.

Temperature dependence of the mutation rate towards antibiotic resistance.

Objectives: Environmental conditions can influence mutation rates in bacteria. Fever is a common response to infection that alters the growth conditions of infecting bacteria. Here we examine how a temperature change, such as is associated with fever, affects the mutation rate towards antibiotic resistance. Methods: We used a fluctuation test to assess the mutation rate towards antibiotic resistance in Escherichia coli at two different temperatures: 37°C (normal temperature) and 40°C (fever temperature). We performed this measurement for three different antibiotics with different modes of action: ciprofloxacin, rifampicin and ampicillin. Results: In all cases, the mutation rate towards antibiotic resistance turned out to be temperature dependent, but in different ways. Fever temperatures led to a reduced mutation rate towards ampicillin resistance and an elevated mutation rate towards ciprofloxacin and rifampicin resistance. Conclusions: This study shows that the mutation rate towards antibiotic resistance is impacted by a small change in temperature, such as associated with fever. This opens a new avenue to mitigate the emergence of antibiotic resistance by coordinating the choice of an antibiotic with the decision of whether or not to suppress fever when treating a patient. Hence, optimized combinations of antibiotics and fever suppression strategies may be a new weapon in the battle against antibiotic resistance.