Search Results (13)

The common bean (Phaseolus vulgaris L.) is a globally cultivated leguminous crop. Fusarium wilt (FW), caused by Fusarium oxysporum f. sp. phaseoli (Fop), is a significant disease leading to substantial yield loss in common beans. Disease-resistant cultivars are recommended to counteract this. The objective of this investigation was to identify single nucleotide polymorphism (SNP) markers associated with FW resistance and to pinpoint potential resistant common bean accessions within a core collection, utilizing a panel of 157 accessions through the Genome-wide association study (GWAS) approach with TASSEL 5 and GAPIT 3. Phenotypes for Fop race 1 and race 4 were matched with genotypic data from 4740 SNPs of BARCBean6K_3 Infinium Bea Chips. After ranking the 157-accession panel and revealing 21 Fusarium wilt-resistant accessions, the GWAS pinpointed 16 SNPs on chromosomes Pv04, Pv05, Pv07, Pv8, and Pv09 linked to Fop race 1 resistance, 23 SNPs on chromosomes Pv03, Pv04, Pv05, Pv07, Pv09, Pv10, and Pv11 associated with Fop race 4 resistance, and 7 SNPs on chromosomes Pv04 and Pv09 correlated with both Fop race 1 and race 4 resistances. Furthermore, within a 30 kb flanking region of these associated SNPs, a total of 17 candidate genes were identified. Some of these genes were annotated as classical disease resistance protein/enzymes, including NB-ARC domain proteins, Leucine-rich repeat protein kinase family proteins, zinc finger family proteins, P-loopcontaining nucleoside triphosphate hydrolase superfamily, etc. Genomic prediction (GP) accuracy for Fop race resistances ranged from 0.26 to 0.55. This study advanced common bean genetic enhancement through marker-assisted selection (MAS) and genomic selection (GS) strategies, paving the way for improved Fop resistance. Full article

Habitat fragmentation affects flying squirrels despite their ability to cross canopy gaps. If unable to cross gaps, flying squirrels may suffer from limited access to appropriate resources, inbreeding depression, and even extirpation. North American flying squirrels (Glaucomys) have been the focus of limited research on this issue when compared to other areas of the world tackling this problem. However, as all gliding mammals share similar conservation challenges, findings of other species on other continents can be applied to the Glaucomys species in North America. The purpose of this review is to take a metapopulation approach to the problem of gap crossing. This review first discusses necessary habitat conservation strategies for Glaucomys within the patches they reside. The review then discusses patch size and configuration, honing in on maintaining connectivity between habitat patches. Different structures (natural and manmade) used to maintain connectivity are reviewed using gliding mammal literature from around the world. This information is pertinent to North American conservation ecologists and landscape managers, who can use this information to improve habitat connectivity and facilitate crossings of Glaucomys flying squirrels within metapopulations. Full article

Background: Acute kidney injury (AKI) is the second most frequent condition after acute respiratory distress syndrome (ARDS) in critically ill patients with severe COVID-19 and is strongly associated with mortality. The aim of this multicentric study was to assess the impact of the specific treatments of COVID-19 and ARDS on the risk of severe AKI in critically ill COVID-19 patients. Methods: In this cohort study, data from consecutive patients older than 18 years admitted to 6 ICUs for COVID-19-related ARDS requiring invasive mechanical ventilation were included. The incidence and severity of AKI, defined according to the 2012 KDIGO definition, were monitored during the entire ICU stay until day 90. Patients older than 18 years admitted to the ICU for COVID-19-related ARDS requiring invasive mechanical ventilation were included. Results: 164 patients were included in the final analysis; 97 (59.1%) displayed AKI, of which 39 (23.8%) had severe stage 3 AKI, and 21 (12.8%) required renal replacement therapy (RRT). In univariate analysis, severe AKI was associated with angiotensin-converting enzyme inhibitors (ACEI) exposure (p = 0.016), arterial hypertension (p = 0.029), APACHE-II score (p = 0.004) and mortality at D28 (p = 0.008), D60 (p < 0.001) and D90 (p < 0.001). In multivariate analysis, the factors associated with the onset of stage 3 AKI were: exposure to ACEI (OR: 4.238 (1.307–13.736), p = 0.016), APACHE II score (without age) (OR: 1.138 (1.044–1.241), p = 0.003) and iNO (OR: 5.694 (1.953–16.606), p = 0.001). Prone positioning (OR: 0.234 (0.057–0.967), p = 0.045) and dexamethasone (OR: 0.194 (0.053–0.713), p = 0.014) were associated with a decreased risk of severe AKI. Conclusions: Dexamethasone was associated with the prevention of the risk of severe AKI and RRT, and iNO was associated with severe AKI and RRT in critically ill patients with COVID-19. iNO should be used with caution in COVID-19-related ARDS. Full article

The purpose of this study was to investigate the use of feeding behavior in conjunction with gut microbiome sampled at two growth stages in predicting growth and body composition traits of finishing pigs. Six hundred and fifty-one purebred boars of three breeds: Duroc (DR), Landrace (LR), and Large White (LW), were studied. Feeding activities were recorded individually from 99 to 163 days of age. The 16S rRNA gene sequences were obtained from each pig at 123 ± 4 and 158 ± 4 days of age. When pigs reached market weight, body weight (BW), ultrasound backfat thickness (BF), ultrasound loin depth (LD), and ultrasound intramuscular fat (IMF) content were measured on live animals. Three models including feeding behavior (Model_FB), gut microbiota (Model_M), or both (Model_FB_M) as predictors, were investigated. Prediction accuracies were evaluated through cross-validation across genetic backgrounds using the leave-one-breed-out strategy and across rearing environments using the leave-one-room-out approach. The proportions of phenotypic variance of growth and body composition traits explained by feeding behavior ranged from 0.02 to 0.30, and from 0.20 to 0.52 when using gut microbiota composition. Overall prediction accuracy (averaged over traits and time points) of phenotypes was 0.24 and 0.33 for Model_FB, 0.27 and 0.19 for Model_M, and 0.40 and 0.35 for Model_FB_M for the across-breed and across-room scenarios, respectively. This study shows how feeding behavior and gut microbiota composition provide non-redundant information in predicting growth in swine. Full article

Objectives: To describe clinical characteristics and management of intensive care units (ICU) patients with laboratory-confirmed COVID-19 and to determine 90-day mortality after ICU admission and associated risk factors. Methods: This observational retrospective study was conducted in six intensive care units (ICUs) in three university hospitals in Marseille, France. Between 10 March and 10 May 2020, all adult patients admitted in ICU with laboratory-confirmed SARS-CoV-2 and respiratory failure were eligible for inclusion. The statistical analysis was focused on the mechanically ventilated patients. The primary outcome was the 90-day mortality after ICU admission. Results: Included in the study were 172 patients with COVID-19 related respiratory failure, 117 of whom (67%) received invasive mechanical ventilation. 90-day mortality of the invasively ventilated patients was 27.4%. Median duration of ventilation and median length of stay in ICU for these patients were 20 (9–33) days and 29 (17–46) days. Mortality increased with the severity of ARDS at ICU admission. After multivariable analysis was carried out, risk factors associated with 90-day mortality were age, elevated Charlson comorbidity index, chronic statins intake and occurrence of an arterial thrombosis. Conclusion: In this cohort, age and number of comorbidities were the main predictors of mortality in invasively ventilated patients. The only modifiable factor associated with mortality in multivariate analysis was arterial thrombosis. Full article

Background: Signaling pathways mediated by microRNAs (miRNAs) have been identified as one of the mechanisms that regulate stroke progression and recovery. Recent investigations using stroke patient blood and cerebrospinal fluid (CSF) demonstrated disease-specific alterations in miRNA expression. In this study, for the first time, we investigated miRNA expression signatures in freshly removed human stroke brain tissue. Methods: Human brain samples were obtained during craniectomy and brain tissue resection in severe stroke patients with life-threatening brain swelling. The tissue samples were subjected to histopathological and immunofluorescence microscopy evaluation, next generation miRNA sequencing (NGS), and bioinformatic analysis. Results: miRNA NGS analysis detected 34 miRNAs with significantly aberrant expression in stroke tissue, as compared to non-stroke samples. Of these miRNAs, 19 were previously identified in stroke patient blood and CSF, while dysregulation of 15 miRNAs was newly detected in this study. miRNA direct target gene analysis and bioinformatics approach demonstrated a strong association of the identified miRNAs with stroke-related biological processes and signaling pathways. Conclusions: Dysregulated miRNAs detected in our study could be regarded as potential candidates for biomarkers and/or targets for therapeutic intervention. The results described herein further our understanding of the molecular basis of stroke and provide valuable information for the future functional studies in the experimental models of stroke. Full article

Despite the high prevalence of prostate cancer in older men, the predictive value of a polygenic risk score (PRS) remains uncertain in men aged ≥70 years. We used a 6.6 million-variant PRS to predict the risk of incident prostate cancer in a prospective study of 5701 men of European descent aged ≥70 years (mean age 75 years) enrolled in the ASPirin in Reducing Events in the Elderly (ASPREE) clinical trial. The study endpoint was prostate cancer, including metastatic or non-metastatic disease, confirmed by an expert panel. After excluding participants with a history of prostate cancer at enrolment, we used a multivariable Cox proportional hazards model to assess the association between the PRS and incident prostate cancer risk, adjusting for covariates. Additionally, we examined the distribution of Gleason grade groups by PRS group to determine if a higher PRS was associated with higher grade disease. We tested for interaction between the PRS and aspirin treatment. Logistic regression was used to independently assess the association of the PRS with prevalent (pre-trial) prostate cancer, reported in medical histories. During a median follow-up time of 4.6 years, 218 of the 5701 participants (3.8%) were diagnosed with prostate cancer. The PRS predicted incident risk with a hazard ratio (HR) of 1.52 per standard deviation (SD) (95% confidence interval (CI) 1.33–1.74, p < 0.001). Men in the top quintile of the PRS distribution had an almost three times higher risk of prostate cancer than men in the lowest quintile (HR = 2.99 (95% CI 1.90–4.27), p < 0.001). However, a higher PRS was not associated with a higher Gleason grade groups. We found no interaction between aspirin treatment and the PRS for prostate cancer risk. The PRS was also associated with prevalent prostate cancer (odds ratio = 1.80 per SD (95% CI 1.65–1.96), p < 0.001).While a PRS for prostate cancer is strongly associated with incident risk in men aged ≥70 years, the clinical utility of the PRS as a biomarker is currently limited by its inability to select for clinically significant disease. Full article

fastai is a deep learning library which provides practitioners with high-level components that can quickly and easily provide state-of-the-art results in standard deep learning domains, and provides researchers with low-level components that can be mixed and matched to build new approaches. It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying patterns of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai includes: a new type dispatch system for Python along with a semantic type hierarchy for tensors; a GPU-optimized computer vision library which can be extended in pure Python; an optimizer which refactors out the common functionality of modern optimizers into two basic pieces, allowing optimization algorithms to be implemented in 4–5 lines of code; a novel 2-way callback system that can access any part of the data, model, or optimizer and change it at any point during training; a new data block API; and much more. We used this library to successfully create a complete deep learning course, which we were able to write more quickly than using previous approaches, and the code was more clear. The library is already in wide use in research, industry, and teaching. Full article

In the United States, extensive investments have been made to restore the ecological function and services of coastal marine habitats. Despite a growing body of science supporting coastal restoration, few studies have addressed the suite of societally enabling conditions that helped facilitate successful restoration and recovery efforts that occurred at meaningful ecological (i.e., ecosystem) scales, and where restoration efforts were sustained for longer (i.e., several years to decades) periods. Here, we examined three case studies involving large-scale and long-term restoration efforts including the seagrass restoration effort in Tampa Bay, Florida, the oyster restoration effort in the Chesapeake Bay in Maryland and Virginia, and the tidal marsh restoration effort in San Francisco Bay, California. The ecological systems and the specifics of the ecological restoration were not the focus of our study. Rather, we focused on the underlying social and political contexts of each case study and found common themes of the factors of restoration which appear to be important for maintaining support for large-scale restoration efforts. Four critical elements for sustaining public and/or political support for large-scale restoration include: (1) resources should be invested in building public support prior to significant investments into ecological restoration; (2) building political support provides a level of significance to the recovery planning efforts and creates motivation to set and achieve meaningful recovery goals; (3) recovery plans need to be science-based with clear, measurable goals that resonate with the public; and (4) the accountability of progress toward reaching goals needs to be communicated frequently and in a way that the general public comprehends. These conclusions may help other communities move away from repetitive, single, and seemingly unconnected restoration projects towards more large-scale, bigger impact, and coordinated restoration efforts. Full article

The Ebola virus (EBOV) envelope glycoprotein (GP) mediates the fusion of the virion membrane with the membrane of susceptible target cells during infection. While proteolytic cleavage of GP by endosomal cathepsins and binding of the cellular receptor Niemann-Pick C1 protein (NPC1) are essential steps for virus entry, the detailed mechanisms by which these events promote membrane fusion remain unknown. Here, we applied single-molecule Förster resonance energy transfer (smFRET) imaging to investigate the structural dynamics of the EBOV GP trimeric ectodomain, and the functional transmembrane protein on the surface of pseudovirions. We show that in both contexts, pre-fusion GP is dynamic and samples multiple conformations. Removal of the glycan cap and NPC1 binding shift the conformational equilibrium, suggesting stabilization of conformations relevant to viral fusion. Furthermore, several neutralizing antibodies enrich alternative conformational states. This suggests that these antibodies neutralize EBOV by restricting access to GP conformations relevant to fusion. This work demonstrates previously unobserved dynamics of pre-fusion EBOV GP and presents a platform with heightened sensitivity to conformational changes for the study of GP function and antibody-mediated neutralization. Full article

This paper presents a summary of the key findings of the special issue of Atmosphere on Air Quality in New South Wales and discusses the implications of the work for policy makers and individuals. This special edition presents new air quality research in Australia undertaken by (or in association with) the Clean Air and Urban Landscapes hub, which is funded by the National Environmental Science Program on behalf of the Australian Government’s Department of the Environment and Energy. Air pollution in Australian cities is generally low, with typical concentrations of key pollutants at much lower levels than experienced in comparable cities in many other parts of the world. Australian cities do experience occasional exceedances in ozone and PM_2.5 (above air pollution guidelines), as well as extreme pollution events, often as a result of bushfires, dust storms, or heatwaves. Even in the absence of extreme events, natural emissions play a significant role in influencing the Australian urban environment, due to the remoteness from large regional anthropogenic emission sources. By studying air quality in Australia, we can gain a greater understanding of the underlying atmospheric chemistry and health risks in less polluted atmospheric environments, and the health benefits of continued reduction in air pollution. These conditions may be representative of future air quality scenarios for parts of the Northern Hemisphere, as legislation and cleaner technologies reduce anthropogenic air pollution in European, American, and Asian cities. However, in many instances, current legislation regarding emissions in Australia is significantly more lax than in other developed countries, making Australia vulnerable to worsening air pollution in association with future population growth. The need to avoid complacency is highlighted by recent epidemiological research, reporting associations between air pollution and adverse health outcomes even at air pollutant concentrations that are lower than Australia’s national air quality standards. Improving air quality is expected to improve health outcomes at any pollution level, with specific benefits projected for reductions in long-term exposure to average PM_2.5 concentrations. Full article

Climate change poses a range of current and future health risks that health professionals need to understand, track, and manage. However, conventional monitoring and evaluation (M&E) as practiced in the health sector, including the use of indicators, does not adequately serve this purpose. Improved indicators are needed in three broad categories: (1) vulnerability and exposure to climate-related hazards; (2) current impacts and projected risks; and (3) adaptation processes and health system resilience. These indicators are needed at the population level and at the health systems level (including clinical care and public health). Selected indicators must be sensitive, valid, and useful. And they must account for uncertainties about the magnitude and pattern of climate change; the broad range of upstream drivers of climate-sensitive health outcomes; and the complexities of adaptation itself, including institutional learning and knowledge management to inform iterative risk management. Barriers and constraints to implementing such indicators must be addressed, and lessons learned need to be added to the evidence base. This paper describes an approach to climate and health indicators, including characteristics of the indicators, implementation, and research needs. Full article

Radio frequency identification (RFID) technology has already been applied in a number of areas to facilitate the tracking process. However, the insufficient tracking accuracy of RFID is one of the problems that impedes its wider application. Previous studies focus on examining the accuracy of discrete points RFID, thereby leaving the tracking accuracy of the areas between the observed points unpredictable. In this study, spatial and temporal analysis is applied to interpolate the continuous distribution of RFID tracking accuracy based on the Kriging method. An implementation trial has been conducted in the loading and docking area in front of a warehouse to validate this approach. The results show that the weak signal area can be easily identified by the approach developed in the study. The optimum distance between two RFID readers and the effect of the sudden removal of readers are also presented by analysing the spatial and temporal variation of RFID tracking accuracy. This study reveals the correlation between the testing time and the stability of RFID tracking accuracy. Experimental results show that the proposed approach can be used to assist the RFID system setup process to increase tracking accuracy. Full article