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Ratiometric fluorescent and electrochemiluminescent dual modal assay for detection of 2,6-pyridinedicarboxylic acid as an<i> anthrax</i> biomarker
No full text2,6-pyridinedicarboxylic acid (DPA) is an excellent biomarker of Bacillus anthracis (B. anthracis). The sensitive detection of DPA, especially through visual point -of -care testing, was significant for accurate and rapid diagnosis of anthrax to timely prevent anthrax disease or biological terrorist attack. Herein, a ratiometric fluorescent (RFL) and electrochemiluminescent (ECL) dual -mode detection platform with a lanthanide ion -based metal -organic framework (Ln-MOF, i.e., M/Y-X: M = Eu, Y = Tb, and X = 4,4 ',4 ''-s-triazine-1,3,5-triyltri-m-aminobenzoic acid) was developed. Eu/Tb-TATAB nanoparticles were constructed to identify DPA. The R -FL detection platform quantitatively detected DPA by monitoring the I545/I617 ratio of the characteristic fluorescence peak intensities of Tb3+ ions and Eu3+ ions. The ECL sensing platform successfully quantified DPA by exploiting the burst effect of DPA on the ECL signal. The above methods had highly sensitive and rapid detection of DPA in water and serum samples. The results showed that this dual -mode detection platform may be projected to be a powerful instrument for preventing related biological warfare and bio-terrorism
Source identification of sedimentary organic carbon in coastal wetlands of the western Bohai Sea
No full textCoastal wetlands play a vital role in mitigating climate change, yet the characteristics of buried organic carbon (OC) and carbon cycling are limited due to difficulties in assessing the composition of OC from different sources (allochthonous vs. autochthonous). In this study, we analyzed the total organic carbon (TOC) to total nitrogen (TN) ratio (C/N), stable carbon isotope (delta 13C) composition, and n-alkane content to distinguish different sources of OC in the surface sediments of the coastal wetlands on the western coast of the Bohai Sea. The coupling of the C/N ratio with delta 13C and n-alkane biomarkers has been proved to be an effective tool for revealing OC sources. The three end-member Bayesian mixing model based on coupling C/N ratios with delta 13C showed that the sedimentary OC was dominated by the contribution of terrestrial particulate organic matter (POM), followed by freshwater algae and marine phytoplankton, with relative contributions of 47 +/- 21 %, 41 +/- 18 % and 12 +/- 17 %, respectively. The relative contributions of terrestrial plants, aquatic macrophytes and marine phytoplankton assessed by n-alkanes were 56 +/- 8 %, 35 +/- 9 % and 9 +/- 5 % in the study area, respectively. The relatively high salinity levels and strong hydrodynamic conditions of the Beidagang Reservoir led to higher terrestrial plants source and lower aquatic macrophytes source than these of Qilihai Reservoir based on the assessment of n-al- kanes. Both methods showed that sedimentary OC was mainly derived from terrestrial sources (plant -domi- nated), suggesting that vegetation plays a crucial role in storing carbon in coastal wetlands, thus, the coastal vegetation management needs to be strengthened in the future. Our findings provide insights into the origins and dynamics of OC in coastal wetlands on the western coast of the Bohai Sea and a significant scientific basis for future monitoring of the blue carbon budget balance in coastal wetlands
Field determination and ecological health risk assessment of trace metals in typical mariculture area of China
No full textField determination of dissolved trace metals (Cu, Pb and Cd) by using automated electrochemical system had been done in three typical mariculture areas of Yellow Sea (YS), East China Sea (ECS) and South China Sea (SCS) in China. Higher concentrations of Cu and Pb were found in ECS while the Cd concentration showed a decreasing trend from north to south of China. The metal distribution and ecological health risk assessments were also conducted. Cu and Pb in the YS and Cu in SCS were moderately contaminated. ECS had considerable Cu contamination and very high Pb contamination. Compared with other coastal areas, mariculture affected the concentration and spatial distribution of trace metals, but it was not a necessarily dominant factor. Overall, the results contribute to the further development of field and on-board metal detection technology and lay a foundation for the realization of field ecological health risk assessments of mariculture waters
Advancements and greenification potential of magnetic molecularly imprinted polymers for chromatographic analysis of veterinary drug residues in milk
No full textMilk, as a widely consumed nutrient-rich food, is crucial for bone health, growth, and overall nutrition. The persistent application of veterinary drugs for controlling diseases and heightening milk yield has imparted substantial repercussions on human health and environmental ecosystems. Due to the high demand, fresh consumption, complex composition of milk, and the potential adverse impacts of drug residues, advanced greener analytical methods are necessitated. Among them, functional materials-based analytical methods attract wide concerns. The magnetic molecularly imprinted polymers (MMIPs), as a kind of typical functional material, possess excellent greenification characteristics and potencies, and they are easily integrated into various detection technologies, which have offered green approaches toward analytes such as veterinary drugs in milk. Despite their increasing applications and great potential, MMIPs' use in dairy matrices remains underexplored, especially regarding ecological sustainability. This work reviews recent advances in MMIPs' synthesis and application as efficient sorbents for veterinary drug extraction in milk followed by chromatographic analysis. The uniqueness and effectiveness of MMIPs in real milk samples are evaluated, current limitations are addressed, and greenification opportunities are proposed. MMIPs show promise in revolutionizing green analytical procedures for veterinary drug detection, aligning with the environmental goals of modern food production systems
Root endodermal suberization induced by nitrate stress regulate apoplastic pathway rather than nitrate uptake in tobacco (Nicotiana tabacum L.)
No full textNitrogen levels and distribution in the rhizosphere strongly regulate the root architecture. Nitrate is an essential nutrient and an important signaling molecule for plant growth and development. Hydroponic experiments were conducted to investigate the differences in endodermal suberization in tobacco (Nicotiana tabacum L.) roots at three nitrate levels. Nitrogen accumulation was detected in the roots, shoots, and xylem sap. Nitrate influx on the root surface was also measured using the non-invasive self-referencing microsensor technique (SRMT). RNA-Seq analysis was performed to identify the genes related to endodermal suberization, nitrate transport, and endogenous abscisic acid (ABA) biosynthesis. The results showed that root length, root-shoot ratio, nitrate influx on the root surface, and NiA and NRT2.4 genes were regulated to maintain the nitrogen nutrient supply in tobacco under low nitrate conditions. Low nitrate levels enhanced root endodermal suberization and hence reduced the apoplastic transport pathway, and genes from the KCS, FAR, PAS2, and CYP86 families were upregulated. The results of exogenous fluridone, an ABA biosynthesis inhibitor, indicated that suberization of the tobacco root endodermis had no relevance to radial nitrate transport and accumulation. However, ABA enhances suberization, relating to ABA biosynthesis genes in the CCD family and degradation gene ABA8ox1
The effects of climate warming and exogenous nitrogen input on soil N2O emissions from mangroves
No full textThe paucity of studies on nitrous oxide (N2O) dynamics with rising temperatures and nitrogen (N)-based eutrophication makes it challenging to evaluate the role of mangroves in mitigating climate change. Here, a 3year mesocosm experiment was conducted to investigate the effects of climate warming (+3 degrees C) and excessive N input (25 mg N L- 1) on soil N2O emissions from two mangroves (Avicennia marina and Bruguiera gymnorrhiza). We found that warming and N input alone significantly increased soil N2O emissions from both mangroves, while the interactive effects of warming and N input on soil N2O emissions were affected by mangrove species. Warming mitigated the positive effect of N input on soil N2O emissions from A. marina; and amplified the effect of N input on soil N2O emissions from B. gymnorrhiza, suggesting that the response of soil N2O emissions to these global change factors is species-dependent. Stable isotopic signature analysis revealed that both warming and N input significantly increased the relative contribution of nitrification to N2O emissions from A. marina; whereas N input, rather than warming, significantly changed the relative contribution of nitrification in B. gymnorrhiza. This could be attributed to the differential changes in soil environmental conditions, plant growth and the microbial structure of the two mangroves. Overall, this study highlights the role of mangrove species in modifying the effects of warming and N input on soil N2O emissions, which should be considered when accurately projecting N2O emissions from mangroves. Furthermore, considering the low N2O emissions from background sediments and the common N limitation across mangroves, our findings suggest that climate warming and exogenous N input may lead to a surge of N2O emissions from mangroves, especially those that are seriously affected by human activities
Research progress and application of chitosan dressings in hemostasis: A review
No full textHemorrhage affects human health, and severe bleeding remains a leading contributor to trauma-related mortality. The speed and effectiveness of the application of hemostatic materials are critical. Conventional hemostatic dressings such as bandages and gauze are gradually being replaced by new types of hemostatic dressings due to their poor hemostatic and antibacterial properties. Chitosan, a biopolymer, is biodegradable and nontoxic and possesses hemostatic and antibacterial properties. Chitosan induces hemostasis through direct contact with red corpuscles and platelets, independent of the coagulation pathways of the host, rendering it an optimal hemostatic dressing. It is widely used in wound care, particularly to stop bleeding, promote wound healing, and provide antimicrobial properties. This article reviews the recent research and development of chitosan-based hemostatic dressings, focusing on trauma hemostasis, burn hemostasis, diabetic skin ulcer hemostasis and other aspects. It also emphasizes the significance of chitosan dressings in wound hemostasis and healing, identifies their research opportunities in hemostasis and wound healing, and explores new research directions
Surface Blocking-Based Potentiometric Biosensor for Detection of E. coli ATCC 15597 Using Phage MS2 as a Receptor
No full textNowadays, using a potentiometric ion sensor to achieve detection of biological analytes is still a big challenge, since these analytes usually do not yield a measurable ion signal. To address this challenge, a simple and robust potentiometric sensing protocol based on a delayed Nernstian response is proposed for the label-free detection of biological analytes. The proposed sensor platform is composed of two layers: the surface recognition layer and the indicator-ion-selective electrode (ISE) membrane layer. It is based on a surface blocking mechanism in which the surface recognition interactions between the surface recognition element and the target can impede the diffusion of the indicator ion from the aqueous phase to the sensing membrane phase to reach the final Nernstian-response equilibrium, thus resulting in a delayed potential change. Such a potential change could be used to measure the concentration of a biological target in the sample. Thus, a sensing system was designed by using phage MS2, its host bacterium Escherichia coli ATCC 15597(abbreviated as E. coli H), and a solid-contact butyrylcholine ISE as a surface recognition element, a target, and an indicator electrode, respectively. This new concept offers a simple, sensitive, and extremely selective potentiometric method for detection of E. coli H with a detection limit of 100 CFU mL-1. It can be expected that the present approach may pave the way to using ISEs to detect various important nonionic biological targets in clinical and environmental applications
Polymeric membrane ion-selective electrode based on potential-modulated ion transfer: ultrasensitive measurement of oceanic pH
No full textThe application of a potentiometric pH electrode in ocean acidification observation is still a challenge due to its poor sensitivity to small pH changes. Herein, a simple approach to remarkably improve the detection precision of a polymeric membrane ion-selective electrode is proposed based on the potential-modulated ion transfer mechanism. The present sensing strategy displays highly sensitive responses to small pH changes for seawater analysis with a precision of 5 mu pH, which is 2 orders of magnitude lower than that of the conventional pH electrode
UAV multispectral remote sensing for the estimation of SPAD values at various growth stages of maize under different irrigation levels
No full textChlorophyll is crucial for photosynthesis in plants and the readings by a SPAD meter (Soil and Plant Analyzer Development) can be used to represent leaf chlorophyll content for monitoring crop growth status and predicting grain yield. Remote sensing technology has shown potential in non-destructive monitoring of SPAD values over large areas, but current SPAD inversion models are limited in their ability to incorporate multiple principal components besides spectral parameters, adapt to other variables such as water stress, and predict SPAD only throughout the entire growth period. This two-year study used crop parameters (plant height and leaf area index) and vegetation indices (VI) derived from unmanned aerial vehicle (UAV) multispectral images to develop SPAD prediction models for maize under different irrigation levels in the 2018 and 2019 growing seasons in Inner Mongolia, China. Two nonlinear machine learning models, random forest (RF) and support vector regression (SVR), and a multiple statistical regression method (partial least squares regression (PLSR)) were used to modeling SPAD. The results showed that the VIs with a high correlation with SPAD varied at each growth stage and the accuracy of SPAD estimation model can be improved significantly by dividing different growth stages (R2 increased by more than 104 %). PLSR performed better than RF and SVR for each growth period, especially at the reproductive R stage (R2 = 0.79, RMSE = 2.25). LAI and PH did not always improve prediction accuracy, but adding crop parameters did increase the correlation coefficient between predicted values and biomass by 8.3 %. This study provides valuable insights into the estimation of SPAD at different growth stages of maize under varying water stress levels using UAV data and crop parameters, offering guidance for farmland management and yield prediction