Development and validation of a method to estimate body weight in critically ill children using length and mid-arm circumference measurements:The PAWPER XL-MAC system

Background. Erroneous weight estimation during the management of emergency presentations in children may contribute to patient harm and poor outcomes. The PAWPER (Paediatric Advanced Weight Prediction in the Emergency Room) XL tape is an accurate length-based, habitus-modified weight estimation device, but is vulnerable to errors if subjective visual assessments of children’s body habitus are incorrect or erratic.Objective. Mid-arm circumference (MAC) has previously been used as a surrogate indicator of habitus, and the objective of this study was to determine whether MAC cut-off values could be used to predict habitus scores (HSs) to create an objective and standardised weight estimation methodology, the PAWPER XL-MAC method.Methods. The PAWPER XL-MAC model was developed by creating MAC ranges for each HS in each weight segment of the tape. This model was validated against two samples, the National Health and Nutrition Examination Survey datasets and data from two previous PAWPER tape studies. The primary outcome measure was to achieve >70% of estimations within 10% of measured weight (PW10 >70%) and >95% within 20% of measured weight (PW20 >95%) for children aged 0 - 18 years.Results. The PAWPER XL-MAC model achieved very high accuracy in the three validation datasets (PW10 79.2%, 79.0% and 81.9%) and a very low critical error rate (PW20 98.5%, 96.0% and 98.0%). This accuracy was maintained across all ages and in all habitus types, except for the severely obese.Conclusions. The PAWPER XL-MAC model proved to be a very accurate, fully objective, standardised system in this study. It has the potential to be accurate across a wide variety of populations, even when used by those not experienced in visual assessment of habitus.Â

Qualities of Restless Legs Syndrome and Periodic Limb Movements

ABSTRACT The two disorders of Restless Legs Syndrome (RLS) and Periodic Limb Movements (PLM) are well recognised as fairly common neurological disorders. The presentation is of a sensory and motor component suggestive of a state of hyperexcitability of the nervous system. The underlying abnormality is believed to involve a dopamine deficiency but many of characteristics of the disorders have not been adequately described or quantified. I investigated, firstly, the possible reasons for the gender bias in the prevalence studies and found that women were more likely to have some associated conditions which may be related to RLS as well as a higher symptom load when compared to men subjects with RLS. I then looked at the problems of analysing the sensations occurring in RLS. Due to the lack of an adequate measuring tool and the possibility of a relationship between the sensations of RLS and those of pain, I used a validated descriptive pain questionnaire (the McGill pain questionnaire) to measure the sensations of RLS. Subjects with RLS were able to describe the sensations with the pain questionnaire and severity indices calculated from the McGill correlated well with measures of RLS severity but not with other intensity measures for pain. In the area of motor events I investigated the possibility of creating a classification system for the muscle activations documented as PLM. I recorded multiple muscle groups in the legs during sleep and devised a classification using sequence of activation and timing of activations from the different muscles. I also used the classification to show subtle changes in the leg activation patterns associated with change in sleep stage

Editorial: Genome wide association studies and genomic selection for crop improvement in the era of Big Data

The exploitation of the genetic diversity of crops is essential for breeding purposes, as the identification of useful/beneficial alleles for target traits within plant genetic resources allows the development of new varieties capable of responding to the challenges of global agriculture (Food and Agriculture Organization of the United Nations, 2010). Whole genome re-sequencing, genome skimming, fractional genome sequencing strategies, and high-density genotyping arrays enable large-scale assessment of genetic diversity for a wide range of species, including major and “orphan” crops (D’Agostino and Tripodi, 2017; Rasheed et al., 2017). This is however of limited value unless associated with adaptation and functional improvement of crops. Recently, several advances in high-throughput phenotyping have overcome the “phenotyping bottleneck” (Walter et al., 2015; Pieruschka and Schurr, 2019; Song et al., 2021), making available robust phenotypic data points acquired following the precise characterization of the agronomic and physiological attributes of crops. More and more studies are taking advantage of these scientific advances and of data science techniques to uncover the genome-to-phenome relationship and unlock the breeding potential of plant genetic resources. Genome-wide association studies (GWAS) and genomic selection (GS) are powerful data science approaches to investigate marker-trait associations (MTAs) for the basic understanding of simple and complex adaptive and functional traits (Liu and Yan, 2019; Voss-Fels et al., 2019; Varshney et al., 2021). Both approaches accelerate the rate of genetic gain in crops and reduce the breeding cycle in a cost-effective manner. For this Research Topic we sought high-quality contributions, covering various aspects of genomics-assisted-breeding: increase in yield, improvement of nutritional content and end-use quality of crops, climate-smart agriculture, cropping systems in agriculture. We did not miss to ask for contributions on technical challenges related to the design of GWAS and GS experiments and data analysis

A verbal descriptor incremental pain scale developed by South African Tswana-speaking patients with low back pain

Background: Measuring pain in patients whose home language is not English can be difficult as there may not be a scale available in their home language. Scales devised in other countries may also not be accurate after translation. Objectives: The aim of this study was to develop and test a new verbal pain descriptor scale in a Tswana-speaking population in South Africa with low back pain. Method: Two separate Tswana-speaking groups (20 males and 20 females) of patients with low back pain were asked to describe each of four categories of pain: mild, moderate, severe and worst. They then voted and descriptions obtaining more than 70% of the vote were taken to the next round of voting with both groups together. A final scale of one description for each category of pain (Tswana Verbal Pain Descriptor Scale – TVPDS) for both males and females was tested on a sample of 250 patients with low back pain and against three other non-verbal pain scales. Results: All items on the final scale were approved by at least 70% of both male and female participants. The scores for the TVPDS correlated well with present pain perception (r = 0.729, p < 0.0001) measured on the numerical visual analogue scale. The TVPDS correlated well with the Wong–Baker FACES Pain Rating Scale (r = 0.695, p < 0.0001) and the Pakistani Coin Pain Scale (r = 0.717, p < 0.0001). Conclusion: The TVPDS has the potential to be a useful clinical scale but more testing in other languages is still required. Clinical implications: This pain scale has the potential to be a useful scale to use for Tswana-speaking persons with low back pain and could also be useful for persons of other languages, if translated

Mapping Agronomic and Quality Traits in Elite Durum Wheat Lines under Differing Water Regimes

Final grain production and quality in durum wheat are affected by biotic and abiotic stresses. The association mapping (AM) approach is useful for dissecting the genetic control of quantitative traits, with the aim of increasing final wheat production under stress conditions. In this study, we used AM analyses to detect quantitative trait loci (QTL) underlying agronomic and quality traits in a collection of 294 elite durum wheat lines from CIMMYT (International Maize and Wheat Improvement Center), grown under different water regimes over four growing seasons. Thirty-seven significant marker-trait associations (MTAs) were detected for sedimentation volume (SV) and thousand kernel weight (TKW), located on chromosomes 1B and 2A, respectively. The QTL loci found were then confirmed with several AM analyses, which revealed 12 sedimentation index (SDS) MTAs and two additional loci for SV (4A) and yellow rust (1B). A candidate gene analysis of the identified genomic regions detected a cluster of 25 genes encoding blue copper proteins in chromosome 1B, with homoeologs in the two durum wheat subgenomes, and an ubiquinone biosynthesis O-methyltransferase gene. On chromosome 2A, several genes related to photosynthetic processes and metabolic pathways were found in proximity to the markers associated with TKW. These results are of potential use for subsequent application in marker-assisted durum wheat-breeding programs

Determining phenological patterns associated with the onset of senescence in a wheat MAGIC mapping population

The appropriate timing of developmental transitions is critical for adapting many crops to their local climatic conditions. Therefore, understanding the genetic basis of different aspects of phenology could be useful in highlighting mechanisms underpinning adaptation, with implications in breeding for climate change. For bread wheat (Triticum aestivum), the transition from vegetative to reproductive growth, the start and rate of leaf senescence and the relative timing of different stages of flowering and grain filling all contribute to plant performance. In this study we screened under Smart house conditions a large, multi-founder “NIAB elite MAGIC” wheat population, to evaluate the genetic elements that influence the timing of developmental stages in European elite varieties. This panel of recombinant inbred lines was derived from eight parents that are or recently have been grown commercially in the UK and Northern Europe. We undertook a detailed temporal phenotypic analysis under Smart house conditions of the population and its parents, to try to identify known or novel Quantitative Trait Loci associated with variation in the timing of key phenological stages in senescence. This analysis resulted in the detection of QTL interactions with novel traits such the time between “half of ear emergence above flag leaf ligule” and the onset of senescence at the flag leaf as well as traits associated with plant morphology such as stem height. In addition, strong correlations between several traits and the onset of senescence of the flag leaf were identified. This work establishes the value of systematically phenotyping genetically unstructured populations to reveal the genetic architecture underlying morphological variation in commercial wheat

Multi-trait ensemble genomic prediction and simulations of recurrent selection highlight importance of complex trait genetic architecture for long-term genetic gains in wheat

Cereal crop breeders have achieved considerable genetic gain in genetically complex traits, such as grain yield, while maintaining genetic diversity. However, focus on selection for yield has negatively impacted other important traits. To better understand multi-trait selection within a breeding context, and how it might be optimized, we analysed genotypic and phenotypic data from a genetically diverse, 16-founder wheat multi-parent advanced generation inter-cross population. Compared to single-trait models, multi-trait ensemble genomic prediction models increased prediction accuracy for almost 90 % of traits, improving grain yield prediction accuracy by 3–52 %. For complex traits, non-parametric models (Random Forest) also outperformed simplified, additive models (LASSO), increasing grain yield prediction accuracy by 10–36 %. Simulations of recurrent genomic selection then showed that sustained greater forward prediction accuracy optimized long-term genetic gains. Simulations of selection on grain yield found indirect responses in related traits, involving optimized antagonistic trait relationships. We found multi-trait selection indices could effectively optimize undesirable relationships, such as the trade-off between grain yield and protein content, or combine traits of interest, such as yield and weed competitive ability. Simulations of phenotypic selection found that including Random Forest rather than LASSO genetic models, and multi-trait rather than single-trait models as the true genetic model accelerated and extended long-term genetic gain whilst maintaining genetic diversity. These results (i) suggest important roles of pleiotropy and epistasis in the wider context of wheat breeding programmes, and (ii) provide insights into mechanisms for continued genetic gain in a limited genepool and optimization of multiple traits for crop improvement