34 research outputs found
Identification of transcription factors regulating senescence in wheat through gene regulatory network modelling
Rural Climathon Playbook
This guide is based on lessons learned from organising two rural Climathons in spring 2022, as part of a British Academy-funded project about net zero futures. This document is intended for Local Organisers of rural Climathons, to provide inspiration and suggested principles to ensure a successful event
Towards local solutions for net zero: Using Climathons to vision food and farming futures
In this policy brief we discuss the need to embed the net zero agenda in small-scale regions, to allow citizens to co-create solutions that are locally relevant. We demonstrate this with evidence from a British Academy-funded project that used adapted âClimathonsâ as a method to debate food and farming solutions in two UK rural farming regions. This approach was effective in convening rural land use stakeholders, providing space for constructive dialogue, strengthening existing networks and partnerships, and generating locally relevant net zero solutions that are being progressed beyond the event
Paediatric PARV4 infection in South Africa: relationship to age, maternal PARV4 status, and HIV infection
ROBIS: A new tool to assess risk of bias in systematic reviews was developed
AbstractObjectiveTo develop ROBIS, a new tool for assessing the risk of bias in systematic reviews (rather than in primary studies).Study Design and SettingWe used four-stage approach to develop ROBIS: define the scope, review the evidence base, hold a face-to-face meeting, and refine the tool through piloting.ResultsROBIS is currently aimed at four broad categories of reviews mainly within health care settings: interventions, diagnosis, prognosis, and etiology. The target audience of ROBIS is primarily guideline developers, authors of overviews of systematic reviews (âreviews of reviewsâ), and review authors who might want to assess or avoid risk of bias in their reviews. The tool is completed in three phases: (1) assess relevance (optional), (2) identify concerns with the review process, and (3) judge risk of bias. Phase 2 covers four domains through which bias may be introduced into a systematic review: study eligibility criteria; identification and selection of studies; data collection and study appraisal; and synthesis and findings. Phase 3 assesses the overall risk of bias in the interpretation of review findings and whether this considered limitations identified in any of the phase 2 domains. Signaling questions are included to help judge concerns with the review process (phase 2) and the overall risk of bias in the review (phase 3); these questions flag aspects of review design related to the potential for bias and aim to help assessors judge risk of bias in the review process, results, and conclusions.ConclusionsROBIS is the first rigorously developed tool designed specifically to assess the risk of bias in systematic reviews
Potential for diagnosis of infectious disease from the 100,000 Genomes Project Metagenomic Dataset: Recommendations for reporting results
The identification of microbiological infection is usually a diagnostic investigation, a complex process that is firstly initiated by clinical suspicion. With the emergence of high-throughput sequencing (HTS) technologies, metagenomic analysis has unveiled the power to identify microbial DNA/RNA from a diverse range of clinical samples (1). Metagenomic analysis of whole human genomes at the clinical/research interface bypasses the steps of clinical scrutiny and targeted testing and has the potential to generate unexpected findings relating to infectious and sometimes transmissible disease. There is no doubt that microbial findings that may have a significant impact on a patientâs treatment and their close contacts should be reported to those with clinical responsibility for the sample-donating patient. There are no clear recommendations on how such findings that are incidental, or outside the original investigation, should be handled. Here we aim to provide an informed protocol for the management of incidental microbial findings as part of the 100,000 Genomes Projectwhich may have broader application in this emerging field. As with any other clinical information, we aim to prioritise the reporting of data that are most likely to be of benefit to the patient and their close contacts. We also set out to minimize risks, costs and potential anxiety associated with the reporting of results that are unlikely to be of clinical significance. Our recommendations aim to support the practice of microbial metagenomics by providing a simplified pathway that can be applied to reporting the identification of potential pathogens from metagenomic datasets. Given that the ambition for UK sequenced human genomes over the next 5 years has been set to reach 5 million and the field of metagenomics is rapidly evolving, the guidance will be regularly reviewed and will likely adapt over time as experience develops
Uncovering hidden variation in polyploid wheat
Comprehensive reverse genetic resources, which have been key to understanding gene function in diploid model organisms, are missing in many polyploid crops. Young polyploid species such as wheat, which was domesticated less than 10,000 y ago, have high levels of sequence identity among subgenomes that mask the effects of recessive alleles. Such redundancy reduces the probability of selection of favorable mutations during natural or human selection, but also allows wheat to tolerate high densities of induced mutations. Here we exploited this property to sequence and catalog more than 10 million mutations in the protein-coding regions of 2,735 mutant lines of tetraploid and hexaploid wheat. We detected, on average, 2,705 and 5,351 mutations per tetraploid and hexaploid line, respectively, which resulted in 35â40 mutations per kb in each population. With these mutation densities, we identified an average of 23â24 missense and truncation alleles per gene, with at least one truncation or deleterious missense mutation in more than 90% of the captured wheat genes per population. This public collection of mutant seed stocks and sequence data enables rapid identification of mutations in the different copies of the wheat genes, which can be combined to uncover previously hidden variation. Polyploidy is a central phenomenon in plant evolution, and many crop species have undergone recent genome duplication events. Therefore, the general strategy and methods developed herein can benefit other polyploid crops
Socioeconomic inequalities in overweight and obesity among 6â to 9âyearâold children in 24 countries from the World Health Organization European region
Childhood overweight and obesity have significant short- and long-term negative impacts on children's health and well-being. These challenges are unequally distributed according to socioeconomic status (SES); however, previous studies have often lacked standardized and objectively measured data across national contexts to assess these differences. This study provides a cross-sectional picture of the association between SES and childhood overweight and obesity, based on data from 123,487 children aged 6â9 years in 24 countries in the World Health Organization (WHO) European region. Overall, associations were found between overweight/obesity and the three SES indicators used (parental education, parental employment status, and family-perceived wealth). Our results showed an inverse relationship between the prevalence of childhood overweight/obesity and parental education in high-income countries, whereas the opposite relationship was observed in most of the middle-income countries. The same applied to family-perceived wealth, although parental employment status appeared to be less associated with overweight and obesity or not associated at all. This paper highlights the need for close attention to context when designing interventions, as the association between SES and childhood overweight and obesity varies by country economic development. Population-based interventions have an important role to play, but policies that target specific SES groups are also needed to address inequalities.The authors gratefully acknowledge support through a grant from the
Russian Government in the context of the WHO European Office for
the Prevention and Control of NCDs. The Ministries of health of Austria, Croatia, Greece, Italy, Malta, Norway, and the Russian Federation
provided financial support for the meetings at which the protocol,
data collection procedures, and analyses were discussed. Data collection in the countries was made possible through funding from: Albania: World Health Organization (WHO) Country Office Albania and
the WHO Regional Office for Europe. Bulgaria: WHO Regional Office
for Europe. Croatia: Ministry of Health, Croatian Institute of Public
Health and WHO Regional Office for Europe. Czechia: Ministry of
Health of the Czech Republic, grant nr. 17-31670A and MZCRâRVO
EU 00023761. Denmark: The Danish Ministry of Health. France: Santé
publique France, the French Agency for Public Health. Georgia: WHO.
Ireland: Health Service Executive. Italy: Italian Ministry of Health; Italian National Institute of Health (Istituto Superiore di SanitĂ ). Kazakhstan: the Ministry of Health of the Republic of Kazakhstan within the
scientific and technical program. Kyrgyzstan: World Health Organization.
Latvia: Centre for Disease Prevention and Control, Ministry of Health,
Latvia. Lithuania: Science Foundation of Lithuanian University of Health
Sciences and Lithuanian Science Council and WHO. Malta: Ministry of
Health; Montenegro: WHO and Institute of Public Health of Montenegro. Poland, National Health Program, Ministry of Health. Portugal: Ministry of Health Institutions, the National Institute of Health, Directorate
General of Health, Regional Health Directorates and the kind technical
support from the Center for Studies and Research on Social Dynamics
and Health (CEIDSS). Romania: Ministry of Health; Russian Federation:
WHO. San Marino: Health Ministry, Educational Ministry, Social Security
Institute and Health Authority. Spain: the Spanish Agency for Food
Safety & Nutrition. Tajikistan: WHO Country Office in Tajikistan and
Ministry of Health and Social Protection. Turkmenistan: WHO Country
Office in Turkmenistan and Ministry of Health. Turkey: Turkish Ministry
of Health and World Bank.info:eu-repo/semantics/publishedVersio