Dual Recognition DNA Triangular Prism Nanoprobe: Toward the Relationship between K+ and pH in Lysosomes.

Lysosomal acidification is essential for its degradative function, and the flux of H+ correlated with that of K+ in lysosomes. However, there is little research on their correlation due to the lack of probes that can simultaneously image these two ions. To deeply understand the role of K+ in lysosomal acidification, here, we designed and fabricated a nanodevice using a K+-aptamer and two pH-triggered nanoswitches incorporated into a DNA triangular prism (DTP) as a dual signal response platform to simultaneously visualize K+ and pH in lysosomes by a fluorescence method. This strategy could conveniently integrate two signal recognition modules into one probe, so as to achieve the goal of sensitive detection of two kinds of signals in the same time and space, which is suitable for the detection of various signals with the correlation of concentration. By co-imaging both K+ and H+ in lysosomes, we found that the efflux of K+ was accompanied by a decrease of pH, which is of great value in understanding lysosomal acidification. Moreover, this strategy also has broad prospects as a versatile optical sensing platform for multiplexed analysis of other biomolecules in living cells.

Target-Dependent Gating of Nanopores Integrated with H-Cell: Toward A General Platform for Photoelectrochemical Bioanalysis.

Herein we present a proof-of-concept study of target-dependent gating of nanopores for general photoelectrochemical (PEC) bioanalysis in an H-cell. The model system was constructed upon a left chamber containing ascorbic acid (AA), the antibody modified porous anodic alumina (AAO) membrane separator, and a right chamber placed with the three-electrode system. The sandwich immunocomplexation and the associated enzymatic generation of biocatalytic precipitation (BCP) in the AAO nanopores would regulate the diffusion of AA from the left cell to the right cell, leading to a varied photocurrent response of the ZnInS nanoflakes photoelectrode. Exemplified by fatty-acid-banding protein (FABP) as the target, the as-developed protocol achieved good performance in terms of sensitivity, selectivity, reproducibility, as well as efficient reutilization of the working electrode. On the basis of an H-cell, this work features a new protocol of target-dependent gating-based PEC bioanalysis, which can serve as a general PEC analytical platform for various other targets of interest.

Application of recombinase polymerase amplification method for rapid detection of infectious laryngotracheitis virus.

Infectious laryngotracheitis is a significant respiratory disease of chickens that causes huge economic losses due to high morbidity and mortality and reduced egg production. A real-time recombinase polymerase amplification (RPA) assay was developed to accurately detect ILTV. The specific probe and primer sets were carefully designed and screened. The real-time RPA assay was carried out at 39 °C for 30 min, and results were obtained within 15 min. The results of the specificity assay showed no fluorescence signals with other avian-related viruses. The sensitivity of the assay was 1 × 102 copies/µL. The low CV value showed that the assay was reproducible. A total of 115 clinical samples were tested using the real-time RPA assay and the real-time PCR assay in parallel; the coincidence rates of the two detection methods were 100%. The results indicated that the real-time RPA assay is a specific, sensitive, rapid, and useful tool for epidemiological studies and clinical diagnosis, especially in the field and in resource-poor areas.

Cell Type and Nuclear Size Dependence of the Nuclear Deformation of Cells on a Micropillar Array.

While various cellular responses to materials have been published, little concerns the deformation of cell nuclei. Herein we fabricated a polymeric micropillar array of appropriate dimensions to trigger the significant self-deformation of cell nuclei and examined six cell types, which could be classified into cancerous cells (Hela and HepG2) versus healthy cells (HCvEpC, MC3T3-E1, NIH3T3, and hMSC) or epithelial-like cells (Hela, HepG2, and HCvEpC) versus fibroblast-like cells (MC3T3-E1, NIH3T3, and hMSC). While all of the cell types exhibited severe nuclear deformation on the poly(lactide- co-glycolide) (PLGA) micropillar array, the difference between the epithelial-like and fibroblast-like cells was much more significant than that between the cancerous and healthy cells. We also examined the statistics of nuclear shape indexes of cells with an inevitable dispersity of nuclear sizes. It was found that larger nuclei favored more significant deformation on the micropillar array for each cell type. In the same region of nuclear size, the parts of the epithelial-like cells exhibited more significant nuclear deformation than those of the fibroblast-like cells. Hence, this article reports the nuclear size dependence of the self-deformation of cell nuclei on micropillar arrays for the first time and meanwhile strengthens the cell-type dependence.

Proliferation of Cells with Severe Nuclear Deformation on a Micropillar Array.

Cellular responses on a topographic surface are fundamental topics about interfaces and biology. Herein, a poly(lactide- co-glycolide) (PLGA) micropillar array was prepared and found to trigger significant self-deformation of cell nuclei. The time-dependent cell viability and thus cell proliferation was investigated. Despite significant nuclear deformation, all of the examined cell types (Hela, HepG2, MC3T3-E1, and NIH3T3) could survive and proliferate on the micropillar array yet exhibited different proliferation abilities. Compared to the corresponding groups on the smooth surface, the cell proliferation abilities on the micropillar array were decreased for Hela and MC3T3-E1 cells and did not change significantly for HepG2 and NIH3T3 cells. We also found that whether the proliferation ability changed was related to whether the nuclear sizes decreased in the micropillar array, and thus the size deformation of cell nuclei should, besides shape deformation, be taken into consideration in studies of cells on topological surfaces.

Development of a real-time loop-mediated isothermal amplification assay for detection of porcine circovirus 3.

BACKGROUND: Porcine circovirus type 3 (PCV3) is an emerging circovirus species, that has been reported in major pig-raising countries including the United States, China, South Korea, Brazil, Spain, and Poland. RESULTS: A real-time loop-mediated isothermal amplification (LAMP) assay was developed for rapid detection of porcine circovirus 3 (PCV3). The method had a detection limit of 1 × 101 copies/µL with no cross-reactions with classical swine fever virus (CSFV) C strain, foot-and-mouth disease virus (FMDV), porcine circovirus 2 (PCV2) LG vaccine strain, porcine epidemic diarrhoea virus (PEDV), porcine respiratory and reproductive syndrome virus (PRRSV), or pseudorabies virus (PRV). The PCV3 positive detection rate of 203 clinical samples for the real-time LAMP assay was 89.66% (182/203). CONCLUSIONS: The real-time LAMP assay is highly sensitive, and specific for use in epidemiological investigations of PCV3.

Remote examination of the seasonal succession of phytoplankton assemblages from time-varying trends.

The seasonal succession of phytoplankton assemblages is important to ascertain the dynamics of an aquatic ecosystem structure, whereas its occurrence in response to hydrodynamic alterations is not clearly understood. In view of the characteristics of annual water level variation formed by the Three Gorges Dam Project (TGDP), our understanding about how these changes affect phytoplankton structure and dynamics is still very limited due to the shortage of long-term observation data. In this study, we used Huan Jing 1 charge-coupled device images over the past decade to examine the phytoplankton succession dates between cyanobacterial and green algal blooms in the backwater area of the Three Gorges Reservoir (TGR). The results indicated continuous wavelet transform-based peak analysis is an efficiency tool that can illustrate the temporal pattern of phytoplankton succession using satellite-derived chlorophyll ɑ and Cyano-Chlorophyta index thresholds. Water level, air temperature, pH and total nitrogen/total phosphorus ratio were four important factors affecting the decline and rise phase of cyanobacterial blooms in the TGR from 2008 to 2018. Given that the upstream dam operation is likely to alter ecological and environmental conditions in the backwater area, this mechanism, so-called "water-level linkage", could alleviate the persistent period of cyanobacterial and green algal blooms. Remote sensing together with time series analysis provided a useful method to examine the seasonal succession of phytoplankton assemblages in the TGR, and these findings provided strategic insight for the water-quality management in the post-TGDP period.

Development of an xTAG-multiplex PCR array for the detection of four avian respiratory viruses.

Acute respiratory tract infections are of paramount importance in the poultry industry. We developed an xTAG bead assay for the simultaneous detection and discrimination of avian influenza virus (AIV), Newcastle disease virus (NDV), infectious bronchitis virus (IBV) and infectious laryngotracheitis virus (ILTV). The assay lacked nonspecific reactions with other common avian viruses and the limit of detection was 6.75 × 102- 3.52 × 103copies/µL. We examined 60 clinical specimens and found 18 positive for respiratory viruses. Our result demonstrated that xTAG-multiplex PCR method is a high-throughput, rapid, specific and sensitive assay for use in epidemiological studies and clinical detection of avian respiratory pathogens.

A multiplex xTAG assay for the simultaneous detection of five chicken immunosuppressive viruses.

BACKGROUND: Chicken anemia virus (CAV), avian reovirus (ARV), infectious bursal disease virus (IBDV), Marek's disease virus (MDV) and reticuloendotheliosis virus (REV) all cause immunosuppressive disease in birds through vertical or horizontal transmission. Mixed infections with these immunosuppressive pathogens lead to atypical clinical signs and obstruct accurate diagnoses and epidemiological investigations. Therefore, it is essential to develop a high-throughput assay for the simultaneous detection of these immunosuppressive viruses with high specificity and sensitivity. The aim of this study was to establish a novel method using a RT-PCR assay combined with fluorescence labeled polystyrene bead microarray (multiplex xTAG assay) to detect single or mixed viral infections. RESULTS: The results showed that the established xTAG assay had no nonspecific reactions with avian influenza virus (AIV), infectious bronchitis virus (IBV), newcastle disease virus (NDV), infectious laryngotracheitis virus (ILTV), Mycoplasma gallisepticum (MG) and Mycoplasma synoviae (MS). The limit of detection was 1.0 × 103 copies/µL for IBDV and 1.0 × 102copies/µL for the other four viruses. Ninety field samples were tested and the results were confirmed using conventional RT-PCR methods. The detection results of these two methods were 100% consistent. The established multiplex xTAG assay allows a high throughput and simultaneous detection of five chicken immunosuppressive viruses. CONCLUSION: The multiplex xTAG assay has been showed to be an additional tool for molecular epidemiology studies of five chicken immunosuppressive viruses in the poultry industry.

Classification of Rice Heavy Metal Stress Levels Based on Phenological Characteristics Using Remote Sensing Time-Series Images and Data Mining Algorithms.

Heavy metal pollution in crops leads to phenological changes, which can be monitored by remote sensing technology. The present study aims to develop a method for accurately evaluating heavy metal stress in rice based on remote sensing phenology. First, the enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) was applied to blend Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat to generate a time series of fusion images at 30 m resolution, and then the vegetation indices (VIs) related to greenness and moisture content of the rice canopy were calculated to create the time-series of VIs. Second, phenological metrics were extracted from the time-series data of VIs, and a feature selection scheme was designed to acquire an optimal phenological metric subset. Finally, an ensemble model with optimal phenological metrics as classification features was built using random forest (RF) and gradient boosting (GB) classifiers, and the classification of stress levels was implemented. The results demonstrated that the overall accuracy of discrimination for different stress levels is greater than 98%. This study suggests that fusion images can be utilized to detect heavy metal stress in rice, and the proposed method may be applicable to classify stress levels.

Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation.

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000⁻2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

Evaluating Heavy Metal Stress Levels in Rice Based on Remote Sensing Phenology.

Heavy metal pollution of croplands is a major environmental problem worldwide. Methods for accurately and quickly monitoring heavy metal stress have important practical significance. Many studies have explored heavy metal stress in rice in relation to physiological function or physiological factors, but few studies have considered phenology, which can be sensitive to heavy metal stress. In this study, we used an integrated Normalized Difference Vegetation Index (NDVI) time-series image set to extract remote sensing phenology. A phenological indicator relatively sensitive to heavy metal stress was chosen from the obtained phenological periods and phenological parameters. The Dry Weight of Roots (WRT), which directly affected by heavy metal stress, was simulated by the World Food Study (WOFOST) model; then, a feature space based on the phenological indicator and WRT was established for monitoring heavy metal stress. The results indicated that the feature space can distinguish the heavy metal stress levels in rice, with accuracy greater than 95% for distinguishing the severe stress level. This finding provides scientific evidence for combining rice phenology and physiological characteristics in time and space, and the method is useful to monitor heavy metal stress in rice.

A New Vegetation Index Based on Multitemporal Sentinel-2 Images for Discriminating Heavy Metal Stress Levels in Rice.

Heavy metal stress in crops is a worldwide problem that requires accurate and timely monitoring. This study aimed to improve the accuracy of monitoring heavy metal stress levels in rice by using multiple Sentinel-2 images. The selected study areas are in Zhuzhou City, Hunan Province, China. Six Sentinel-2 images were acquired in 2017, and heavy metal concentrations in soil were measured. A novel vegetation index called heavy metal stress sensitive index (HMSSI) was proposed. HMSSI is the ratio between two red-edge spectral indices, namely the red-edge chlorophyll index (CIred-edge) and the plant senescence reflectance index (PSRI). To demonstrate the capability of HMSSI, the performances of CIred-edge and PSRI in discriminating heavy metal stress levels were compared with that of HMSSI at different growth stages. Random forest (RF) was used to establish a multitemporal monitoring model to detect heavy metal stress levels in rice based on HMSSI at different growth stages. Results show that HMSSI is more sensitive to heavy metal stress than CIred-edge and PSRI at different growth stages. The performance of a multitemporal monitoring model combining the whole growth stage images was better than any other single growth stage in distinguishing heavy metal stress levels. Therefore, HMSSI can be regarded as an indicator for monitoring heavy metal stress levels with a multitemporal monitoring model.

Finding the Key Periods for Assimilating HJ-1A/B CCD Data and the WOFOST Model to Evaluate Heavy Metal Stress in Rice.

Accurately monitoring heavy metal stress in crops is vital for food security and agricultural production. The assimilation of remote sensing images into the World Food Studies (WOFOST) model provides an efficient way to solve this problem. In this study, we aimed at investigating the key periods of the assimilation framework for continuous monitoring of heavy metal stress in rice. The Harris algorithm was used for the leaf area index (LAI) curves to select the key period for an optimized assimilation. To obtain accurate LAI values, the measured dry weight of rice roots (WRT), which have been proven to be the most stress-sensitive indicator of heavy metal stress, were incorporated into the improved WOFOST model. Finally, the key periods, which contain four dominant time points, were used to select remote sensing images for the RS-WOFOST model for continuous monitoring of heavy metal stress. Compared with the key period which contains all the available remote sensing images, the results showed that the optimal key period can significantly improve the time efficiency of the assimilation framework by shortening the model operation time by more than 50%, while maintaining its accuracy. This result is highly significant when monitoring heavy metals in rice on a large-scale. Furthermore, it can also offer a reference for the timing of field measurements in monitoring heavy metal stress in rice.

Extraction of Rice Phenological Differences under Heavy Metal Stress Using EVI Time-Series from HJ-1A/B Data.

An effective method to monitor heavy metal stress in crops is of critical importance to assure agricultural production and food security. Phenology, as a sensitive indicator of environmental change, can respond to heavy metal stress in crops and remote sensing is an effective method to detect plant phenological changes. This study focused on identifying the rice phenological differences under varied heavy metal stress using EVI (enhanced vegetation index) time-series, which was obtained from HJ-1A/B CCD images and fitted with asymmetric Gaussian model functions. We extracted three phenological periods using first derivative analysis: the tillering period, heading period, and maturation period; and constructed two kinds of metrics with phenological characteristics: date-intervals and time-integrated EVI, to explore the rice phenological differences under mild and severe stress levels. Results indicated that under severe stress the values of the metrics for presenting rice phenological differences in the experimental areas of heavy metal stress were smaller than the ones under mild stress. This finding represents a new method for monitoring heavy metal contamination through rice phenology.

Deriving the Characteristic Scale for Effectively Monitoring Heavy Metal Stress in Rice by Assimilation of GF-1 Data with the WOFOST Model.

Accurate monitoring of heavy metal stress in crops is of great importance to assure agricultural productivity and food security, and remote sensing is an effective tool to address this problem. However, given that Earth observation instruments provide data at multiple scales, the choice of scale for use in such monitoring is challenging. This study focused on identifying the characteristic scale for effectively monitoring heavy metal stress in rice using the dry weight of roots (WRT) as the representative characteristic, which was obtained by assimilation of GF-1 data with the World Food Studies (WOFOST) model. We explored and quantified the effect of the important state variable LAI (leaf area index) at various spatial scales on the simulated rice WRT to find the critical scale for heavy metal stress monitoring using the statistical characteristics. Furthermore, a ratio analysis based on the varied heavy metal stress levels was conducted to identify the characteristic scale. Results indicated that the critical threshold for investigating the rice WRT in monitoring studies of heavy metal stress was larger than 64 m but smaller than 256 m. This finding represents a useful guideline for choosing the most appropriate imagery.

Population structure and diversification of Gymnospermium kiangnanense, a plant species with extremely small populations endemic to eastern China.

Background: Gymnospermium kiangnanense is the only species distributed in the subtropical region within the spring ephemeral genus Gymnospermium. Extensive human exploitation and habitat destruction have resulted in a rapid shrink of G. kiangnanense populations. This study utilizes microsatellite markers to analyze the genetic diversity and structure and to deduce historical population events of extant populations of G. kiangnanense. Methods: A total of 143 individuals from eight extant populations of G. kiangnanense, including two populations from Anhui Province and six populations from Zhejiang Province, were analyzed with using 21 pairs of microsatellite markers. Genetic diversity indices were calculated using Cervus, GENEPOP, GenALEX. Population structure was assessed using genetic distance (UPGMA), principal coordinate analysis (PCoA), Bayesian clustering method (STRUCTURE), and molecular variation analysis of variance (AMOVA). Population history events were inferred using DIYABC. Results: The studied populations of G. kiangnanense exhibited a low level of genetic diversity (He = 0.179, I = 0.286), but a high degree of genetic differentiation (FST = 0.521). The mean value of gene flow (Nm ) among populations was 1.082, indicating prevalent gene exchange via pollen dispersal. Phylogeographic analyses suggested that the populations of G. kiangnanense were divided into two lineages, Zhejiang (ZJ) and Anhui (AH). These two lineages were separated by the Huangshan-Tianmu Mountain Range. AMOVA analysis revealed that 36.59% of total genetic variation occurred between the two groups. The ZJ lineage was further divided into the Hangzhou (ZJH) and Zhuji (ZJZ) lineages, separated by the Longmen Mountain and Fuchun River. DIYABC analyses suggested that the ZJ and AH lineages were separated at 5.592 ka, likely due to the impact of Holocene climate change and human activities. Subsequently, the ZJZ lineage diverged from the ZJH lineage around 2.112 ka. Given the limited distribution of G. kiangnanense and the significant genetic differentiation among its lineages, both in-situ and ex-situ conservation strategies should be implemented to protect the germplasm resources of G. kiangnanense.

Exosomes Derived from Astragaloside IV-pretreated Endothelial Progenitor Cells (AS-IV-Exos) Alleviated Endothelial Oxidative Stress and Dysfunction Via the miR-210/ Nox2/ROS Pathway.

BACKGROUND: Chronic hyperglycemia in diabetes induces oxidative stress, leading to damage to the vascular system. In this study, we aimed to evaluate the effects and mechanisms of AS-IV-Exos in alleviating endothelial oxidative stress and dysfunction caused by high glucose (HG). METHODS: Histopathological changes were observed using HE staining, and CD31 expression was assessed through immunohistochemistry (IHC). Cell proliferation was evaluated through CCK8 and EDU assays. The levels of ROS, SOD, and GSH-Px in the skin tissues of each group were measured using ELISA. Cell adhesion, migration, and tube formation abilities were assessed using adhesion, Transwell, and tube formation experiments. ROS levels in HUVEC cells were measured using flow cytometry. The levels of miR-210 and Nox2 were determined through quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The expression of Nox2, SOD, GSH-Px, CD63, and CD81 was confirmed using WB. RESULTS: The level of miR-210 was reduced in diabetes-induced skin damage, while the levels of Nox2 and ROS increased. Treatment with AS-IV increased the level of miR-210 in EPC-Exos. Compared to Exos, AS-IV-Exos significantly reduced the proliferation rate, adhesion number, migration speed, and tube-forming ability of HGdamaged HUVEC cells. AS-IV-Exos also significantly decreased the levels of SOD and GSH-Px in HG-treated HUVEC cells and reduced the levels of Nox2 and GSH-Px. However, ROS levels and Nox2 could reverse this effect. CONCLUSION: AS-IV-Exos effectively alleviated endothelial oxidative stress and dysfunction induced by HG through the miR-210/Nox2/ROS pathway.

Rapid lateral flow immunoassay for fluorescence detection of canine distemper virus (CDV).

Canine distemper virus (CDV) is a highly contagious and potentially lethal virus that affects dogs and other members of the Canidae family, including wolves, foxes, and coyotes. Here, we present a fluorescent lateral flow immunoassay (FLFA) platform for the detection of CDV, which utilizes fluorescent microspheres - fusion protein monoclonal antibody (mAb)-labeled monoclonal antibody. The assay detected CDV within 5 min, with a detection limit threshold of 3 × 102 TCID50/mL. Notably, the assay demonstrated no cross-reactivity with canine parvovirus, canine coronavirus, canine adenovirus, feline calicivirus, feline herpesvirus, or feline parvovirus. Field and clinical applicability of the assay was evaluated using 63 field samples, including 30 canine fecal samples, 18 swab samples, and 15 blood samples. The coincidence rate between the detection results of clinical samples obtained through FLFA and reverse transcription polymerase chain reaction (RT-PCR) was 96.83%. Thus, this assay offers a significant advancement for the rapid diagnosis of CDV at the point of care.

Calcium-based MOFs as scaffolds for shielding immobilized lipase and enhancing its stability.

The enzyme immobilization technology has become a key tool in the field of enzyme applications; however, improving the activity recovery and stability of the immobilized enzymes is still challenging. Herein, we employed a magnetic carboxymethyl cellulose (MCMC) nanocomposite modified with ionic liquids (ILs) for covalent immobilization of lipase, and used Ca-based metal-organic frameworks (MOFs) as the support skeleton and protective layer for immobilized enzymes. The ILs contained long side chains (eight CH2 units), which not only enhanced the hydrophobicity of the carrier and its hydrophobic interaction with the enzymes, but also provided a certain buffering effect when the enzyme molecules were subjected to compression. Compared to free lipase, the obtained CaBPDC@PPL-IL-MCMC exhibited higher specific activity and enhanced stability. In addition, the biocatalyst could be easily separated using a magnetic field, which is beneficial for its reusability. After 10 cycles, the residual activity of CaBPDC@PPL-IL-MCMC could reach up to 86.9%. These features highlight the good application prospects of the present immobilization method.