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The majority of schools across Australia rapidly implemented online education during the first wave of COVID-19 restrictions. The school closure disproportionately affected the routines and socialisation of vulnerable students, including those with a refugee background. Refugee-background students have been impacted by COVID-19 as school closures interrupted face-to-face education, including English language and tutorial support and counselling services. School shutdown also impeded refugee-background students' activities outside the home, which could render adverse effects on their physical, mental and social wellbeing. Holistic efforts are urgently needed in Australia to support refugee-background students in order to prevent further learning loss and promote health and wellbeing. [The page range (71-91) on p. 71 of the .pdf is incorrect. The correct page range is p71-76.]

Background: Studies of the association between the apolipoprotein C3 gene (APOC3) rs5128 polymorphism and plasma levels of apolipoprotein C3 (APOC3) and lipids have reported apparently conflicting findings. This meta-analysis aimed to investigate the associations of the rs5128 polymorphism with fasting APOC3 and lipid levels. Methods: The following information was abstracted for each study: ethnicity, age, sex, health condition, sample size, genotyping and lipid assay methods, mean and standard deviation or standard error by genotypes for APOC3 and lipid variables. There were 42 eligible studies with 23846 subjects included in this meta-analysis. A dominant model was used for this meta-analysis. Results: The results showed that the carriers of the variant allele G had higher levels of APOC3 [standardized mean difference (SMD): 0.22, 95% confidence interval (CI): 0.12-0.31, P < 0.00001], triglycerides (TG) (SMD: 0.33, 95% CI: 0.23-0.44, P < 0.00001), total cholesterol (TC) (SMD: 0.15, 95% CI: 0.09-0.22, P < 0.00001), and low-density lipoprotein cholesterol (LDL-C) (SMD: 0.11, 95% CI: 0.04-0.17, P = 0.001) than the non-carriers. No significant association between the APOC3 rs5128 polymorphism and lower levels of high-density lipoprotein cholesterol (HDL-C) was detected under the dominant model (SMD: -0.03, 95% CI: -0.06-0.01, P = 0.156). Conclusions: The results from the present meta-analysis demonstrate a significant association between the APOC3 rs5128 polymorphism and higher levels of APOC3, TG, TC and LDL-C, but further studies are needed to elucidate the underlying mechanisms. [ABSTRACT FROM AUTHOR]

The diversity of agro-environmental conditions among wheat-based farming systems in the mountainous regions of Nepal may favor the development and production of multiple narrowly adapted varieties over a few broadly adapted varieties. Sixteen genotypes were tested using Participatory Varietal Selection (PVS) trials at farmers' fields in three districts in the Kathmandu Valley. Grain yield was the trait most preferred by farmers, followed by tillering, resistance to diseases, drought, and lodging. Farmer selection of optimal genotypes varied over time and location depending on agronomic and climatic pressures, indicating a preference by farmers for growing multiple, narrowly adapted varieties. Production potential of PVS genotypes averaged up to 142% greater than the most widely grown variety, RR21. With farmer participation in the selection process in different agro-ecological micro-niches of Nepal, both yield potential and yield stability of wheat should increase significantly, thereby providing farmers with the economic means to sustain the current small-scale agriculture suited to the mountainous terrain. [ABSTRACT FROM AUTHOR]

Abstract: Improving livelihood of resource poor farmers is an important goal of wheat research in developing countries. Although remarkable success has been achieved to date in developing widely adapted wheat cultivars, many resource poor farmers in marginal areas in developing world have not benefited. Participatory research could greatly enhance identifying cultivars according to the choice of the poor farmers. This study was conducted to examine how farmers’ selection criteria could assist breeders in identifying superior wheat cultivars, and determine if a new statistical analysis tool, GGE biplot, could be effectively used in selection of improved cultivar based on quantitative (grain yield) and qualitative data (farmers’ preference score). The field experiments were conducted in 3 years (2003–2005) in three mid-hill districts in the central Nepal involving resource poor wheat farmers. Sixteen wheat genotypes, including a long-term and a current commercial cultivar, were used in the study. Data were collected on agronomic traits considered important by the participating farmers. These included days to heading and maturity, plant height, effective tiller number, spike length, kernel per spike, 1000-kernel weight and grain yield. Farmers also qualitatively scored each genotype for multiple traits based on their preference. In general, the farmers used the same traits in selecting a superior cultivar that are used by breeders. However, relative importance of different traits differed, not necessarily following in line with the breeder preference. The cultivar superiority based on quantitative agronomic data (breeders’ criteria) and qualitative preference scores (farmers’ criteria) often showed synergies, however, there were differences as well. This indicates farmers’ ability to choose superior cultivars based on qualitative observation compared to tedious quantitative data recording in the on-station testing. In the first year, a greater number of farmers selected improved check as a better choice than recent advanced breeding lines. In the 2nd and 3rd years, the farmers preferred genotypes other than the checks. This underlines the importance of testing of advanced materials in farmers’ fields in multiple years. Principal component analysis using GGE-biplot was useful in identifying superior genotypes based on both quantitative and qualitative data recorded across environments. This approach could be useful in analyzing data from participatory agricultural research conducted under highly diverse farmers’ field conditions where it is easier to record observations on qualitative than quantitative scale. This technique can also be extended to on-farm participatory testing of other technologies. The findings bear implications for a broad range of participatory research and technology evaluation and verification. [Copyright &y& Elsevier]