Gene flow from Clearfield® rice to weedy rice under field conditions

Imidazolinone-herbicide-resistant Clearfield® (CL) rice permits the selective chemical control of weedy rice (Oryza sativa), a major weed problem in South-East Asian rice growing countries. However, there is major concern involving resistant individuals resulting from gene flow as the cultivated and weedy rice live side by side in the fields. An experiment was conducted in the rice fields of Kuala Rompin, Pahang, Malaysia to determine which Clearfield® rice cultivars and weedy rice cultivars are more prone to hybridization, and the effect on distance between the pollen donor and receptor plants. The experiment was piloted in a split plot design with four replications. Encircled population technique was used to determine the distance between the Clearfield® rice and detection of hybrids (F1). Resistance of progeny was determined after spraying with OnDuty™ and the confirmation of hybrids was done using the SSR primer RM251. Higher survival rate was recorded with cv. CL2 which was significantly different from cv. CL1. Weedy rice cultivar V1 and V2 in CL1 plots differed significantly from the same cultivar from CL2 plots. However, no significant difference was observed between weedy rice cultivars of V3 and V4, either in CL1 or CL2 plots. No survivors were found after second spraying. Suspected hybrids were found up to 5 m however the rate was much lower compared to only 1 m from the CL plots

Impact of the COVID-19 pandemic on patients with paediatric cancer in low-income, middle-income and high-income countries: a multicentre, international, observational cohort study

OBJECTIVES: Paediatric cancer is a leading cause of death for children. Children in low-income and middle-income countries (LMICs) were four times more likely to die than children in high-income countries (HICs). This study aimed to test the hypothesis that the COVID-19 pandemic had affected the delivery of healthcare services worldwide, and exacerbated the disparity in paediatric cancer outcomes between LMICs and HICs. DESIGN: A multicentre, international, collaborative cohort study. SETTING: 91 hospitals and cancer centres in 39 countries providing cancer treatment to paediatric patients between March and December 2020. PARTICIPANTS: Patients were included if they were under the age of 18 years, and newly diagnosed with or undergoing active cancer treatment for Acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, Wilms' tumour, sarcoma, retinoblastoma, gliomas, medulloblastomas or neuroblastomas, in keeping with the WHO Global Initiative for Childhood Cancer. MAIN OUTCOME MEASURE: All-cause mortality at 30 days and 90 days. RESULTS: 1660 patients were recruited. 219 children had changes to their treatment due to the pandemic. Patients in LMICs were primarily affected (n=182/219, 83.1%). Relative to patients with paediatric cancer in HICs, patients with paediatric cancer in LMICs had 12.1 (95% CI 2.93 to 50.3) and 7.9 (95% CI 3.2 to 19.7) times the odds of death at 30 days and 90 days, respectively, after presentation during the COVID-19 pandemic (p<0.001). After adjusting for confounders, patients with paediatric cancer in LMICs had 15.6 (95% CI 3.7 to 65.8) times the odds of death at 30 days (p<0.001). CONCLUSIONS: The COVID-19 pandemic has affected paediatric oncology service provision. It has disproportionately affected patients in LMICs, highlighting and compounding existing disparities in healthcare systems globally that need addressing urgently. However, many patients with paediatric cancer continued to receive their normal standard of care. This speaks to the adaptability and resilience of healthcare systems and healthcare workers globally

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality