Virulence profiling, host plant resistance and management of fusarium wilt of pigeonpea

Pigeonpea wilt caused by Fusarium udum is the most important soil borne disease and a main constraint in boosting the yield. The survey conducted in Southern and Central part of India during Kharif 2013-14 and 2014-15 indicated, an incidence ranging from 0.0 to 45.33 per cent during 2013-14 and 0.0 to 70.80 per cent during 2014-15. Disease occurrence was observed irrespective of cropping system, soil types and least wilt incidence was recorded in improved cultivars (TS- 3R, Asha) rather than local cultivars. 111 Fusarium isolates were collected to study the cultural, morphological, molecular and pathogenic variability. The virulence profiling of 72 isolates of F. udum on 11 host differentials, resulted in four groups such as avirulent, least virulent, moderately virulent and highly virulent ones. Based on wilt incidence and reaction of F. udum isolates on four pigeonpea host differentials (ICP 2376, C- 11, ICP 8863 and ICP 9174), 67 virulent isolates were categorised into six variants viz., Variant 0, Variant I, Variant II, Variant III, Variant VI and Variant VII. Variant VI and VII are the new variants identified in present study. Under proteomic study 141 differentially expressed proteins spots were noticed in resistant and susceptible cultivars in F. udum and pigeonpea interaction. Of them, 12 were successfully characterized by using MALDI TOF MS/ MS. The identified proteins belong to seven functional groups viz., metabolism related proteins, biosynthetic process related, defense related, redox homeostasis proteins, signalling protein and a pathogen cell wall protein. This is the first piece of work on pigeonpea wilt proteomics. Out of 52 genotypes screened, 12 were resistant, 14 were moderately resistant, 11 were moderately susceptible and 15 were showed susceptible reaction. The highest vigour index of moderately resistant (BMR-736) and susceptible cultivar (ICP 2376) was recorded in P. fluorescens (RP- 46) + P. putida (RP- 56) treated seeds. The maximum activity of defense related enzymes like, PO, PPO and PAL was recorded in seeds treatment with Pseudomonas fluorescens (RP- 46) and challenged with F. udum (FU- 37). Under glasshouse, condition seed treatment with P. fluorescens (RP- 46) recorded least wilt incidence (8.34 %) in moderately resistant cultivar (BSMR- 736) and 29.17 per centin susceptible cultivar (ICP 2376). Captan among non-systemic fungicides, carbendazim and benomyl among systemic fungicides and Trichoderma harzianum (Th-R) among the bio-agent were effective under in-vitro selected for disease management under field condition. Based on two years performance of treatments, soil drenching with 0.3 per cent carbendazim fungicide recorded significantly lowest mean wilt incidence of 6.18 per cent with highest yield of 1688 kg per ha with the next best treatment by seed treatment @ 4 g per kg seeds + soil application of PGPR consortium @ 25 kg per ha in FYM @ 50 kg per ha, with a wilt incidence of 8.80 per cent and yield of 1567 kg per ha

Nanomaterials to Transform Infection Control with Antimicrobial Solutions

Antimicrobial resistance (AMR) is a major global health problem. The growing number of antibiotic-resistant microbes needs the development of novel antibiotics. Nanotechnology shows potential for overcoming bacterial resistance. Nanoparticles, particularly those around 100 nm, display higher antibacterial activity by using methods that differ from traditional antibiotics. When particle size reduces, materials such as zinc and silver improve their antibacterial action. There are several techniques to evaluate nanoparticle antibacterial activity, each having merits and downsides. This study critically evaluates selected literature, identifies bactericidal mechanisms, and discusses assessment procedures, emphasizing the importance of innovative approaches to bacterial infections

Impact of Gastrostomy Placement on Nutritional Status, Physical Health, and Parental Well-Being of Females with Rett Syndrome: A Longitudinal Study of an Australian Population

© 2018 Elsevier Inc. Objectives: To evaluate how age-related trends in nutritional status, physical health, and parental well-being in females with Rett syndrome may be related to gastrostomy placement and to examine the impact of the procedure on mortality. Study design: We included 323 females from the Australian Rett Syndrome Study and analyzed their demographic, genetic, and child and parental health data collected from over 6 waves of follow-up questionnaire between 2000 and 2011. We used mixed-effects models to estimate the association between repeated measures of outcomes and age, gastrostomy placement and their interaction and Cox proportional hazards regression models to estimate relative risks of mortality for individuals with gastrostomy. Results: Nearly one-third (30.3%) of the cases underwent gastrostomy placement. Nutritional status based on weight, height, and body mass index (BMI) improved over time, and BMI was greater in individuals with gastrostomy placement than in those without (adjusted β = 0.87, 95% CI 0.02-1.73). There was no association between gastrostomy placement and individual's physical health outcomes or parental physical and mental health, nor did the age trend of these outcomes vary by gastrostomy insertion status. Nevertheless, among those at risk of suboptimal weight, the all-cause mortality rate was greater in those who had gastrostomy placement compared with those who had not (hazard ratio 4.07, 95% CI 1.96-8.45). Conclusion: Gastrostomy placement was associated with improvement in BMI in females with Rett syndrome, but its long-term impact on individuals and their families is unclear

Predicting risk of cardiovascular disease using retinal OCT imaging

We investigated the potential of optical coherence tomography (OCT) as an additional imaging technique to predict future cardiovascular disease (CVD). We utilised a self-supervised deep learning approach based on Variational Autoencoders (VAE) to learn low-dimensional representations of high-dimensional 3D OCT images and to capture distinct characteristics of different retinal layers within the OCT image. A Random Forest (RF) classifier was subsequently trained using the learned latent features and participant demographic and clinical data, to differentiate between patients at risk of CVD events (MI or stroke) and non-CVD cases. Our predictive model, trained on multimodal data, was assessed based on its ability to correctly identify individuals likely to suffer from a CVD event(MI or stroke), within a 5-year interval after image acquisition. Our self-supervised VAE feature selection and multimodal Random Forest classifier differentiate between patients at risk of future CVD events and the control group with an AUC of 0.75, outperforming the clinically established QRISK3 score (AUC= 0.597). The choroidal layer visible in OCT images was identified as an important predictor of future CVD events using a novel approach to model explanability. Retinal OCT imaging provides a cost-effective and non-invasive alternative to predict the risk of cardiovascular disease and is readily accessible in optometry practices and hospitals.Comment: 18 pages for main manuscript, 7 figures, 2 pages for appendix and preprint for a journa

Epidemiology of gastrostomy insertion for children and adolescents with intellectual disability

The largest group of recipients of pediatric gastrostomy have neurological impairment with intellectual disability (ID). This study investigated trends in first gastrostomy insertion according to markers of disadvantage and ID etiology. Linked administrative and health data collected over a 32-year study period (1983–2014) for children with ID born between 1983 and 2009 in Western Australia were examined. The annual incidence rate change over calendar year was calculated for all children and according to socioeconomic status, geographical remoteness, and Aboriginality. The most likely causes of ID were identified using available diagnosis codes in the linked data set. Of 11,729 children with ID, 325 (2.8%) received a first gastrostomy within the study period. The incidence rate was highest in the 0–2 age group and there was an increasing incidence trend with calendar time for each age group under 6 years of age. This rate change was greatest in children from the lowest socioeconomic status quintile, who lived in regional/remote areas or who were Aboriginal. The two largest identified groups of ID were genetically caused syndromes (15.1%) and neonatal encephalopathy (14.8%). Conclusion: Gastrostomy is increasingly used in multiple neurological conditions associated with ID, with no apparent accessibility barriers in terms of socioeconomic status, remoteness, or Aboriginality.What is Known:• The use of gastrostomy insertion in pediatrics is increasing and the most common recipients during childhood have neurological impairment, most of whom also have intellectual disability (ID).What is New:• Nearly 3% of children with ID had gastrostomy insertion performed, with the highest incidence in children under 3 years of age.• Gastrostomy use across different social groups was equitable in the Australian setting

Predicting risk of cardiovascular disease using retinal OCT imaging

We investigated the potential of optical coherence tomography (OCT) as an additional imaging technique to predict future cardiovascular disease (CVD). We utilised a self-supervised deep learning approach based on Variational Autoencoders (VAE) to learn low-dimensional representations of high-dimensional 3D OCT images and to capture distinct characteristics of different retinal layers within the OCT image. A Random Forest (RF) classifier was subsequently trained using the learned latent features and participant demographic and clinical data, to differentiate between patients at risk of CVD events (MI or stroke) and non-CVD cases. Our predictive model, trained on multimodal data, was assessed based on its ability to correctly identify individuals likely to suffer from a CVD event(MI or stroke), within a 5-year interval after image acquisition. Our self-supervised VAE feature selection and multimodal Random Forest classifier differentiate between patients at risk of future CVD events and the control group with an AUC of 0.75, outperforming the clinically established QRISK3 score (AUC= 0.597). The choroidal layer visible in OCT images was identified as an important predictor of future CVD events using a novel approach to model explanability. Retinal OCT imaging provides a cost-effective and non-invasive alternative to predict the risk of cardiovascular disease and is readily accessible in optometry practices and hospitals