Research Progress of QuEChERS Pretreatment Technique in the Detection of Multiple Pesticide Residues

The QuEChERS extraction technique is a pretreatment technique that has been rapidly applied in recent years and is widely used in the field of pesticide residues with many advantages. This technique is based on solid phase extraction (SPE), which uses the interaction between adsorbent and impurities in the matrix to achieve the purpose of purification. The method has easier operation and better purification effect than SPE. In this paper, the research progress of the QuEChERS technique in pesticide residue detection in different fields in recent years and its future development were reviewed, hoping to provide reference for further development and utilization of the QuEChERS technique in pesticide residue detection in the future.

Simultaneous Determination of 14 β-Receptor Agonists Residues in Mutton by High Performance Liquid Chromatography-Tandem Mass Spectrometry (HPLC-MS/MS)

[Objectives]A high performance liquid chromatography-tandem mass spectrometry(HPLC-MS/MS)method was established for the determination of 14β-receptor agonist residues in mutton.[Methods]Samples were hydrolyzed byβ-glucuronidase and extracted with 5%acetic acid-acetonitrile(1:99,V/V)solution.An Eclipse plus C 18 column was used for separation,and the MRM mode was used for qualitative analysis,and the external standard method was used for quantitative analysis of matrix standard solutions.[Results]Under the optimal conditions,the retention time of the 14 kinds ofβ-receptor agonists ranged from 1.0 to 9.5 min.When the mass concentration was in the range of 0.05-0.50μg/ml,the linear relationship ofβ-receptor agonists was good,with correlation coefficients(r)≥0.9992.The detection limits of the method were in the range of 0.04-0.87μg/kg,and the quantitative limits were in the range of 0.35-1.86μg/kg.The average recovery values were in the range of 82.8%-108.9%,with RSDs(n=6)in the range of 1.9%-6.7%.[Conclusions]The method is simple,sensitive,reproducible,accurate,and can be used for simultaneous determination of the 14 kinds ofβ-receptor agonist residues in mutton.

Arctic sea ice concentration and thickness data assimilation in the FIO-ESM climate forecast system

To improve the Arctic sea ice forecast skill of the First Institute of Oceanography-Earth System Model(FIO-ESM)climate forecast system,satellite-derived sea ice concentration and sea ice thickness from the Pan-Arctic IceOcean Modeling and Assimilation System(PIOMAS)are assimilated into this system,using the method of localized error subspace transform ensemble Kalman filter(LESTKF).Five-year(2014–2018)Arctic sea ice assimilation experiments and a 2-month near-real-time forecast in August 2018 were conducted to study the roles of ice data assimilation.Assimilation experiment results show that ice concentration assimilation can help to get better modeled ice concentration and ice extent.All the biases of ice concentration,ice cover,ice volume,and ice thickness can be reduced dramatically through ice concentration and thickness assimilation.The near-real-time forecast results indicate that ice data assimilation can improve the forecast skill significantly in the FIO-ESM climate forecast system.The forecasted Arctic integrated ice edge error is reduced by around 1/3 by sea ice data assimilation.Compared with the six near-real-time Arctic sea ice forecast results from the subseasonal-toseasonal(S2 S)Prediction Project,FIO-ESM climate forecast system with LESTKF ice data assimilation has relatively high Arctic sea ice forecast skill in 2018 summer sea ice forecast.Since sea ice thickness in the PIOMAS is updated in time,it is a good choice for data assimilation to improve sea ice prediction skills in the near-realtime Arctic sea ice seasonal prediction.

FIO-ESM v2.0 CORE2-forced experiment for the CMIP6 Ocean Model Intercomparison Project

We introduced the Coupled Model Intercomparison Project Phase 6(CMIP6)Ocean Model Intercomparison Project CORE2-forced(OMIP-1)experiment by using the First Institute of Oceanography Earth System Model version 2.0(FIO-ESM v2.0),and comprehensively evaluated the simulation results.Unlike other OMIP models,FIO-ESM v2.0 includes a coupled ocean surface wave component model that takes into account non-breaking surface wave-induced vertical mixing in the ocean and effect of surface wave Stokes drift on air-sea momentum and heat fluxes in the climate system.A sub-layer sea surface temperature(SST)diurnal cycle parameterization was also employed to take into account effect of SST diurnal cycle on air-sea heat fluxes to improve simulations of air-sea interactions.Evaluations show that mean values and long-term trends of significant wave height were adequately reproduced in the FIO-ESM v2.0 OMIP-1 simulations,and there is a reasonable fit between the SST diurnal cycle obtained from in situ observations and that parameterized by FIO-ESM v2.0.Evaluations of model drift,temperature,salinity,mixed layer depth,and the Atlantic Meridional Overturning Circulation show that the model performs well in the FIO-ESM v2.0 OMIP-1 simulation.However,the summer sea ice extent of the Arctic and Antarctic is underestimated.

Seasonal prediction skills of FIO-ESM for North Pacific sea surface temperature and precipitation

The seasonal prediction of sea surface temperature(SST) and precipitation in the North Pacific based on the hindcast results of The First Institute of Oceanography Earth System Model(FIO-ESM) is assessed in this study.The Ensemble Adjusted Kalman Filter assimilation scheme is used to generate initial conditions, which are shown to be reliable by comparison with the observations. Based on this comparison, we analyze the FIO-ESM 6-month hindcast results starting from each month of 1993–2013. The model exhibits high SST prediction skills over most of the North Pacific for two seasons in advance. Furthermore, it remains skillful at long lead times for midlatitudes. The reliable prediction of SST can transfer fairly well to precipitation prediction via air-sea interactions.The average skill of the North Pacific variability(NPV) index from 1 to 6 months lead is as high as 0.72(0.55) when El Ni?o-Southern Oscillation and NPV are in phase(out of phase) at initial conditions. The prediction skill of the NPV index of FIO-ESM is improved by 11.6%(23.6%) over the Climate Forecast System, Version 2. For seasonal dependence, the skill of FIO-ESM is higher than the skill of persistence prediction in the later period of prediction.

FIO-ESM v2.0 Outputs for the CMIP6 Global Monsoons Model Intercomparison Project Experiments

Three tiers of experiments in the Global Monsoons Model Intercomparison Project(GMMIP),one of the endorsed model intercomparison projects of phase 6 of the Coupled Model Intercomparison Project(CMIP6),are implemented by the First Institute of Oceanography Earth System Model version 2(FIO-ESM v2.0),following the GMMIP protocols.Evaluation of global mean surface air temperature from 1870 to 2014 and climatological precipitation(1979–2014)in tier-1 shows that the atmosphere model of FIO-ESM v2.0 can reproduce the basic observed atmospheric features.In tier-2,the internal variability is captured by the coupled model,with the SST restoring to the model climatology plus the observed anomalies in the tropical Pacific and North Atlantic.Simulation of the Northern Hemisphere summer monsoon circulation is significantly improved by the SST restoration in the North Atlantic.In tier-3,five orographic perturbation experiments are conducted covering the period 1979–2014 by modifying the surface elevation or vertical heating in the prescribed region.In particular,the strength of the South Asian summer monsoon is reduced by removing the topography or thermal forcing above 500 m over the Asian continent.Monthly and daily simulated outputs of FIO-ESM v2.0 are provided through the Earth System Grid Federation(ESGF)node to contribute to a better understanding of the global monsoon system.

Link between the Barents Oscillation and Recent Boreal Winter Cooling over the Asian Midlatitudes

The link between boreal winter cooling over the midlatitudes of Asia and the Barents Oscillation(BO) since the late 1980s is discussed in this study, based on five datasets. Results indicate that there is a large-scale boreal winter cooling during 1990–2015 over the Asian midlatitudes, and that it is a part of the decadal oscillations of long-term surface air temperature(SAT)anomalies. The SAT anomalies over the Asian midlatitudes are significantly correlated with the BO in boreal winter. When the BO is in its positive phase, anomalously high sea level pressure over the Barents region, with a clockwise wind anomaly,causes cold air from the high latitudes to move over the midlatitudes of Asia, resulting in anomalous cold conditions in that region. Therefore, the recent increasing trend of the BO has contributed to recent winter cooling over the Asian midlatitudes.

Could CMIP6 climate models reproduce the early-2000s global warming slowdown?

The unexpected global warming slowdown during 1998–2013 challenges the existing scientific understanding of global temperature change mechanisms,and thus the simulation and prediction ability of state-of-the-art climate models since most models participating in phase 5 of the Coupled Model Intercomparison Project(CMIP5)cannot simulate it.Here,we examine whether the new-generation climate models in CMIP6 can reproduce the recent global warming slowdown,and further evaluate their capacities for simulating key-scale natural variabilities which are the most likely causes of the slowdown.The results show that although the CMIP6 models present some encouraging improvements when compared with CMIP5,most of them still fail to reproduce the warming slowdown.They considerably overestimate the warming rate observed in 1998–2013,exhibiting an obvious warming acceleration rather than the observed deceleration.This is probably associated with their deficiencies in simulating the distinct temperature change signals from the human-induced long-term warming trend and/or the three crucial natural variabilities at interannual,interdecadal,and multidecadal scales.In contrast,the 4 models that can successfully reproduce the slowdown show relatively high skills in simulating the long-term warming trend and the three keyscale natural variabilities.Our work may provide important insight for the simulation and prediction of near-term climate changes.

S100 calcium-binding protein A9 promotes skin regeneration through toll-like receptor 4 during tissue expansion

Background:In plastic surgery,tissue expansion is widely used for repairing skin defects.However,low expansion efficiency and skin rupture caused by thin,expanded skin remain significant challenges in promoting skin regeneration during expansion.S100 calcium-binding protein A9(S100A9)is essential in promoting wound healing;however,its effects on skin regeneration during tissue expansion remain unclear.The aim of the present study was to explore the role of S100A9 in skin regeneration,particularly collagen production to investigate its importance in skin regeneration during tissue expansion.Methods:The expression and distribution of S100A9 and its receptors-toll-like receptor 4(TLR-4)and receptor for advanced glycation end products were studied in expanded skin.These character-istics were investigated in skin samples of rats and patients.Moreover,the expression of S100A9 was investigated in stretched keratinocytes in vitro.The effects of S100A9 on the proliferation and migration of skin fibroblasts were also observed.TAK-242 was used to inhibit the binding of S100A9 to TLR-4;the levels of collagen I(COL I),transforming growth factor beta(TGF-β),TLR-4 and phospho-extracellular signal-related kinase 1/2(p-ERK1/2)in fibroblasts were determined.Furthermore,fibroblasts were co-cultured with stretched S100A9-knockout keratinocytes by siRNA transfection and the levels of COL I,TGF-β,TLR-4 and p-ERK1/2 in fibroblasts were investigated.Additionally,the area of expanded skin,thickness of the dermis,and synthesis of COL I,TGF-β,TLR-4 and p-ERK1/2 were analysed to determine the effects of S100A9 on expanded skin.Results:Increased expression of S100A9 and TLR-4 was associated with decreased extracellular matrix(ECM)in the expanded dermis.Furthermore,S100A9 facilitated the proliferation and migration of human skin fibroblasts as well as the expression of COL I and TGF-βin fibroblasts via the TLR-4/ERK1/2 pathway.We found that mechanical stretch-induced S100A9 expression and secretion of keratinocytes stimulated COL I,TGF-β,TLR-4 and p-ERK1/2 expression in skin fibroblasts.Recombined S100A9 protein aided expanded skin regeneration and rescued dermal thinning in rats in vivo as well as increasing ECM deposition during expansion.Conclusions:These findings demonstrate that mechanical stretch promoted expanded skin regeneration by upregulating S100A9 expression.Our study laid the foundation for clinically improving tissue expansion using S100A9.