A phytoexclusion strategy for reducing contamination risk of rice based on low-Cd natural variations pyramid of root transporters.

Cadmium pollution in rice is a threat to human health. Phytoexclusion is an effective strategy to reduce the Cd accumulation. Soil-to-root is the first step of Cd entering rice and plays a crucial role in Cd accumulation, so targeting root transporters could be an effective approach for phytoexclusion. This study utilized single-gene & multi-gene joint haplotype analysis to reveal the law of natural variations. The result showed that natural variations of rice root transporters assembled regularly following a certain pattern, rather than randomly. A total of 3 dominant nature variation combinations with 2 high-Cd combinations and 1 low-Cd combination were identified. In addition, indica-japonica differentiation was observed, with indica germplasms harboring high-Cd combinations while japonica germplasms harboring. In Chinese rice landraces, most of the collected indica landraces contained high-Cd combinations, indicating a high Cd contamination risk in indica landraces in terms of both phenotype and genotype. To address this issue, multiple superior low-Cd natural variations were pyramided to create two new low-Cd germplasms. In both pond and farmland trials, the ameliorated rice grain Cd did not exceed safety standards. This research provided a framework for future phytoexclusion, thus to reduce Cd-contamination risk in soil-rice system.

Simulating the infected population and spread trend of 2019-nCov under different policy by EIR model

BackgroundChinese government has taken strong measures in response to the epidemic of new coronavirus (2019-nCoV) from Jan.23, 2020. The number of confirmed infected individuals are still increasing rapidly. Estimating the accurate infected population and the future trend of epidemic spreading under control measures is significant and urgent. There have been reports external icon of spread from an infected patient with no symptoms to a close contact, which means the incubation individuals may has the possibility of infectiousness. However, the traditional transmission model, Susceptible-Exposed-Infectious-Recovered (SEIR) model, assumes that the exposed individual is being infected but without infectiousness. Thus, the estimating infected populations based on SEIR model from the existing literatures seems too far more than the official reported data. MethodsHere, we inferred that the epidemic could be spread by exposed (incubation) individuals. Then, we provide a new Exposed-identified-Recovered (EIR) model, and simulated the epidemic spreading processes from free propagation phase to extremely control phase. Then, we estimate of the size of the epidemic and forecast the future development of the epidemics under strong prevention interventions. According to the spread characters of 2019-nCov, we construct a novel EIR compartment system dynamics model. This model integrates two phases of the epidemic spreading: before intervention and after intervention. We assume that 2019-nCov is firstly spread without intervention then the government started to take strong quarantine measures. Use the latest reported data from National Health Commission of the Peoples Republic of China, we estimate the basic parameters of the model and the basic reproduction number of 2019-nCov. Then, based on this model, we simulate the future spread of the epidemics. Both the infected population and the spreading trend of 2019-nCov under different prevention policy scenarios are estimated. The epidemic spreading trends under different quarantine rate and action starting date of prevention policy are simulated and compared. FindingsIn our baseline scenario, the government has taken strict prevention actions, and the estimate numbers fit the official numbers very well. Simulation results tells that, if the prevention measures are relaxed or the action starting date of prevention measures is later than Jan. 23, 2020, the peak of identified individuals would be greatly increased, and the elimination date also would be delayed. We estimate the reproductive number for 2019-nCoV was 2.7. And simulation of the baseline scenario tells that, the peak infected individuals will be 49093 at Feb.16, 2020 and the epidemic spreading will be eliminated at the end of March 2020. The simulation results also tell that the quarantine rate and the starting date of intervention action policy have great effect on the epidemic spreading. Specifically, if the quarantine rate is reduced from 100% to less than 63%, which is the threshold of the quarantine rate to control the epidemic spreading, the epidemic spreading would never be eliminated out. And, if the starting date of intervention is delayed for 1 day than the date Jan. 23, the peak infected population will increase about 6351 individuals. If the delayed period is 3 days or 7 days, the increasing number would be 21621 or 65929 individuals, thus the peak infected number would up to 70714 and 115022 individuals. InterpretationGiven that 2019-nCoV could be controlled under the strong prevention measures of what China has taken and it will take about three months. The confirmed infected individuals will still keep quick increasing for a generation period (27 days, equal to the sum of exposed period and identified period) after the start time point of control. The strong prevention measures should be insisted until the epidemics is wiped out. Other domestic places and overseas have confirmed infected individuals should take strong interventions immediately. Generally, earlier strong prevention measures could efficiently mitigate the outbreaks in other cities all over the world has confirmed individuals of epidemic of 2019-nCoV.