Search

The piezoelectric properties of graphitic carbon nitride with different structures follow the order PTI > melon > PHI, and the melon and PHI showed reverse activities in the photocatalytic and piezoelectric assisted photocatalytic reactions.

As the high-crystalline phase of carbon nitride, poly(heptazine imide) (PHI) has attracted much attention in recent years, considering the more effective light absorption, better charge carrier behavior, and higher surface area of PHI compared with its counterpart with a melon structure that is commonly synthesized through thermal polymerization. Nevertheless, exploring effective strategies to further improve the performance of PHI is still highly desirable. In this work, it is revealed that the photocatalytic as well as piezocatalytic performances of PHI are greatly promoted by coupling with carbon dots (CDots) through a facile ultrasonication process. Detailed structure characterizations indicate that a very low content of CDots (0.05%) decoration can double the light absorbance and achieve the efficient separation and transfer of photogenerated charge carriers. The optimal photocatalytic hydrogen evolution rate of PHI/CDots is about 2.49 and 2.81 times that of PHI, under UV-Visible and visible light irradiation, respectively. Moreover, the piezocatalytic H

An integrated three-in-one ddPCR platform consisting of an easy-to-use chip and a matching control instrument with high user-friendliness and practicability was proposed for nucleic acid detection.

The microbial community within the root system, the rhizosphere closely connected to the root, and their symbiotic relationship with the host are increasingly seen as possible drivers of natural pathogen resistance. Resistant cultivars have the most effective strategy in controlling the Chinese wheat yellow mosaic disease, but the roles of the root and rhizosphere microbial interactions among different taxonomic levels of resistant cultivars are still unknown. Thus, we aimed to investigate whether these microbial community composition and network characteristics are related to disease resistance and to analyze the belowground plant-associated microflora. Relatively high microbial diversity and stable community structure for the resistant cultivars were detected. Comparison analysis showed that some bacterial phyla were significantly enriched in the wheat root or rhizosphere of the resistant wheat cultivar. Furthermore, the root and rhizosphere of the resistant cultivars greatly recruited many known beneficial bacterial and fungal taxa. In contrast, the relative abundance of potential pathogens was higher for the susceptible cultivar than for the resistant cultivar. Network co-occurrence analysis revealed that a much more complex, more mutually beneficial, and a higher number of bacterial keystone taxa in belowground microbial networks were displayed in the resistant cultivar, which may have been responsible for maintaining the stability and ecological balance of the microbial community. Overall, compared with the susceptible cultivar, the resistant cultivar tends to recruit more potential beneficial microbial groups for plant and rhizosphere microbial community interactions. These findings indicate that beneficial rhizosphere microbiomes for cultivars should be targeted and evaluated using community compositional profiles. KEY POINTS: • Different resistance levels in cultivars affect the rhizosphere microbiome.. • Resistant cultivars tend to recruit more potential beneficial microbial groups. • Bacteria occupy a high proportion and core position in the microflora network.

To determine the carrier rate for common recessive genetic diseases in Chenzhou region in order to provide a reference for carrier screening in this region.Targeted capture and high-throughput sequencing were carried out to detect potential variants of 79 genes associated with 88 recessive genetic diseases. Couples at risk were provided with prenatal diagnosis upon their subsequent pregnancies.A total of 1314 individuals were enrolled, among whom 355 (27.02%) were found to be carrier for at least one disease. The carrier rates for 8 diseases have exceeded 1%, with the most common two including thalassemia (11.72%, 154/1314) and autosomal recessive deafness (5.48%, 72/1314). Ten couples were found to be at risk for producing affected offspring. Among these, five females were carriers for X-linked recessive genetic diseases. Following genetic counseling, seven couples had accepted prenatal diagnosis, and 3 affected fetuses were diagnosed.The disease types and pathogenic variants of Chenzhou region have differed from previously reported. Further research is required to validate the above finding with a larger populations.

Zeolitic imidazolate frameworks (ZIFs) can separate olefins from paraffin with very little energy consumption, which is critical for the chemical industry. They can form a large diversity of polymo...

Characterizing the microbial communities associated with soil-borne disease incidence is a key approach in understanding the potential role of microbes in protecting crops from pathogens. In this study, we compared the soil properties and microbial composition of the rhizosphere soil and roots of healthy and bacterial wilt-infected tobacco plants to assess their potential influence on plant health. Our results revealed that the relative abundance of pathogens was higher in diseased plants than in healthy plants. Moreover, compared with healthy plants, there was a significantly higher microbial alpha diversity in the roots and rhizosphere soil of diseased plants. In addition, we detected a lower abundance of certain plant microbiota, including species in the genera Penicillium, Trichoderma, and Burkholderia in the rhizosphere of diseased plants, which were found to be significantly negatively associated with the relative abundance of Ralstonia. Indeed, compared with healthy plants, the co-occurrence networks of diseased plants included a larger number of associations linked to plant health. Furthermore, structural equation modeling revealed that these specific microbes were correlated with disease suppression, thereby implying that they may play important roles in maintaining plant health. In conclusion, our findings provide important insights into the relationships between soil-borne disease incidence and changes in the belowground microbial community. These findings will serve as a basis for further research investigating the use of specific plant-associated genera to inhibit soil-borne diseases.

The intensive use of chemical fertilizer, particularly nitrogen (N) has resulted in not only markedly increased crop yields but also detrimental effects on ecosystems. Plant microbiomes represent an eco-friendly alternative for plant nutrition and productivity, and the effect of N fertilization on plant and soil microbes has been well studied. However, if and how N fertilization modulates seed endophytic microbiomes and grain quality remains largely unknown. Here, we investigated the effect of different N fertilization rates on rice seed endophytic bacterial and fungal communities as well as on grain quality. Higher bacterial and fungal community diversity and richness, but lower grain protein and amino acid contents were found in seeds of rice treated moderate N fertilization than those treated insufficient or excessive N input. There were also more complex co-occurrence networks, and an enrichment of putative beneficial bacterial taxa in seeds under moderate N application, while there was an opposite trend under the excessive N treatment. In addition, the grain amylose and amylopectin contents were positively correlated with the relative abundance of bacterial and fungal dominant genera, while the grain amino acid contents were negatively correlated with the bacterial dominant genera but positively associated with fungal dominant genera. Together, we demonstrate that moderate N fertilization can enhance bacterial and fungal community colonization in seeds and improve grain eating and cooking qualities. This study extends our knowledge regarding the significant role of rational fertilization on seed-microbe interactions in sustainable agriculture.

Dehydratase (DH), a domain in polyketide synthase (PKS) modules, can catalyze the dehydration of β-hydroxy to an α,β-unsaturated acyl intermediate. As the first dual-function (dehydratase/isomerase) DH domain accessible in the PDB database, the gephyronic acid (GphF) DH1 domain from the PKS biosynthetic pathway attracts great attention from researchers. However, the mechanisms of dehydration and isomerization in type I PKS still remain unclear. In this study, MD simulations and QM/MM calculations were combined to elucidate the molecular mechanism of GphF DH1. The results indicated that GphF DH1 had better recognition effect towards the (2R,3R)-substrate and preferred forming the α–β double bond in advance to the β–γ double bond directly. By calculating the binding energy, some key residues near the active pocket were highlighted. Umbrella sampling results showed that non-methylated substrates could form intra-molecular hydrogen bonds more easily than α-methyl substrates. The QM/MM calculations with the M062X/6-311+G**//M062X/6-31G* method and SMD solvation correction supported the one-base dehydration and one-base isomerization mechanism with energy barriers of 27.0 kcal mol−1 and 17.2 kcal mol−1, respectively. These results can encourage future studies for the comprehensive understanding of the catalytic mechanism of PKS DHs and for the rational design of typical DHs.

Bacterial DNA phosphorothioation (PT) physiologically and stereo-specifically replaces a non-bridging oxygen in a phosphate link with a sulfur atom, which can be recognized by a highly conserved sulfur-binding domain (SBD). Here we conducted thermodynamic integration (TI), molecular dynamics simulation, and quantum chemical calculations to decipher the specific molecular interactions between PT-DNA and SBD in

The digital polymerase chain reaction (dPCR) is an irreplaceable variant of PCR techniques due to its capacity for absolute quantification and detection of rare deoxyribonucleic acid (DNA) sequences in clinical samples. Image processing methods, including micro-chamber positioning and fluorescence analysis, determine the reliability of the dPCR results. However, typical methods demand high requirements for the chip structure, chip filling, and light intensity uniformity. This research developed an image-to-answer algorithm with single fluorescence image capture and known image-related error removal. We applied the Hough transform to identify partitions in the images of dPCR chips, the 2D Fourier transform to rotate the image, and the 3D projection transformation to locate and correct the positions of all partitions. We then calculated each partition's average fluorescence amplitudes and generated a 3D fluorescence intensity distribution map of the image. We subsequently corrected the fluorescence non-uniformity between partitions based on the map and achieved statistical results of partition fluorescence intensities. We validated the proposed algorithms using different contents of the target DNA. The proposed algorithm is independent of the dPCR chip structure damage and light intensity non-uniformity. It also provides a reliable alternative to analyze the results of chip-based dPCR systems.

A microfluidic-based digital polymerase chain reaction (dPCR) chip requires precise temperature control as well as uniform temperature distribution to ensure PCR efficiency. However, measuring local temperature and its distribution over thousands of L/nL-volume samples with minimum disturbance is challenging. Here, we present a method of non-contact localized temperature measurement for determination of the non-uniformity of temperature distribution over a dPCR chip. We filled the dPCR chip with a PCR solution containing amplified DNA fragments with a known melting temperature (TM). We then captured fluorescent images of the chip when it was heated from 70 to 99 °C, plotted the fluorescence intensity of each partition as a function of temperature, and calculated measured TM values from each partition. Finally, we created a 3-D map of the dPCR chip with the measured TM as the parameter. Even when the actual TM of the PCR solution was constant, the measured TM value varied between locations due to temperature non-uniformity in the dPCR chip. The method described here thereby characterized the distribution of temperature non-uniformity using a PCR solution with known TM as a temperature sensor. Among the non-contact temperature measurement methods, the proposed TM-based method can determine the temperature distribution within the chip, instead of only at the chip surface. The method also does not suffer from the undesirable photobleaching effect of fluorescein-based temperature measurement method. Temperature determination over the dPCR chip based on TM allowed us to calibrate the temperature sensor and improve the dPCR configuration and precision. This method is also suitable for determining the temperature uniformity of other microarray systems where there is no physical access to the system and thus direct temperature measurement is not possible.

Purpose: Uncovering potential biocontrol agents that suppress soil-borne pathogens is an important step toward developing sustainable management strategies for disease control and to maintain plant health. Plant cultivars influence rhizosphere microorganism-mediated soil-borne disease control. However, the disease-resistance mechanisms and microbial taxa involved in the control of soil-borne mosaic virus are largely unknown. Methods: We designed a field experiment on wheat cultivars for virus-resistance identification and conducted metagenomic analysis to determine the potential mechanisms used by rhizosphere microbial communities that affect the density of the mosaic virus vector-Polymyxa graminis, and to identify potential microbes that inhibit virus transmission. Results: We found high P. graminis abundance and microbial diversity in the susceptible wheat cultivar rhizosphere. The relative abundance of indicative phagotrophs showed a strong negative correlation to P. graminis abundance during disease onset, indicating that predator–prey interactions influenced P. graminis activity. Moreover, we found strong and negative associations between the relative abundance of key ecological cluster, hub phagotrophic species and P. graminis abundance in multitrophic ecological networks. A structural equation model analyses indicated that phagotrophic protists were the main predictors of P. graminis abundance upon disease onset. Conclusion: Our results demonstrate the important role of phagotrophic protists as top-down controllers for plant defense against pathogens. Our findings highlight the complexity of rhizosphere networks, reflecting the co-occurrence patterns of multi-trophic level microbes in virtual networks and strengthening the association between soil microbial diversity and plant health.

The digital polymerase chain reaction (dPCR) technique can quantify specific sequences of deoxyribonucleic acid using either a droplet-based or chip-based system. dPCR duplexing methods in a single fluorescence channel are typically based on the difference in fluorescence amplitude (F) between two targets. The different targets are distinguished from each other by the F-value variation using non-equal probe concentrations or different target lengths. In the present study, we propose a single fluorescence channel-based dPCR duplexing method that combines a specific probe and intercalating dye to increase the difference in F values between the two targets. We selected two sequences, one from chromosome 18 (Chr18) detected only by the intercalating dye EvaGreen and the other from chromosome 21 (Chr21) detected by a combination of a 6-carboxyfluorescein (FAM) probe and EvaGreen. We performed the dPCR protocol and imaged the dPCR chip at room temperature to verify the proposed duplexing method. The result revealed that the difference in F values between Chr18 and Chr21 increased from ≈5% to 20% when using the FAM probe for Chr21 compared with the detection of both amplicons using EvaGreen only. The added FAM probe enabled two-target discrimination using a single-color fluorescent channel. We further determined the difference in F values at different temperatures using artificial dPCR images. This proposed method represents a simple option for single fluorescence channel dPCR duplexing, making it suitable for simplified dPCR systems used for point-of-care applications.

Artificial Neural Network (ANN) models have been extensively applied in the prediction of water resource variables, and Geographical Information System (GIS) includes powerful functions to visualize spatial data. In order to provide an efficient tool for environmental assessment and management that combines the advantages of these two modules, a GIS-based ANN water quality prediction system was developed in the present study. The ANN module and ArcGIS Engine module, along with a dynamic database, were imbedded in the system, which integrates water quality prediction via the ANN model and spatial presentation of the model results. The structure of the ANN model could be modified through the graphical user interface to optimize the model performance. The developed system was applied to a real case study for the prediction of the total phosphorus concentration in the Lake Champlain area. The prediction results were verified with the monitoring data, and the performance of the developed model was further evaluated through graphical techniques and quantitative statistical methods. Overall, the developed system provided satisfactory prediction results, and spatial distribution maps of the predicted results were obtained, which coincided with the monitored values. The developed GIS-based ANN water quality prediction system could serve as an efficient tool for engineers and decision makers.

Understanding the mechanisms that govern microbial community assembly across soil-plant continuum is crucial for predicting the response of ecosystems to environmental changes. However, the impact of the health status of plant on microbial assembly across this continuum still remain poorly understood. Here, we investigated how wheat yellow mosaic (WYM), caused by the wheat mosaic virus transmitted by Polymyxa graminis, affected microbial assembly across soil (bulk soil, rhizosphere soil), and plant (roots and leaves) continuum in a winter wheat (Triticum aestivum L.) system in northern China, using null model analysis. The results showed that deterministic processes dominated the bacterial community assembly, whereas stochastic processes were primarily responsible for the assembly of the fungal communities. With increasing levels of WYM, deterministic processes were greatly enhanced for bacterial community assembly, accompanied by a decrease in community niche breadth. Intensified competition between bacteria and fungi and increased soil total nitrogen (TN) and soil organic carbon (SOC) contents were mainly responsible for the enhanced deterministic processes for bacterial community assembly. Random forest modeling indicated a strong potential of rhizosphere bacterial community assembly for predicting the pathological conditions of wheat. Structural equation modeling showed that disease level was positively correlated with SOC and TN contents, competitions between bacteria and fungi, and the contribution of variable selection processes to the bacterial community assembly in the wheat rhizosphere. Our study revealed the ecological mechanisms underlying the associations between microbial communities and soil-borne disease, and highlighted the significance of microbial community assembly for maintaining soil and plant health.

Currently, the ongoing pandemic has created an unprecedented pressure for the development of various analytical assays and especially their immediate practical applications. A number of tests based on different principles such as immunoassay [1], electrochemistry [2], nucleic acid amplification tests (NAATs) [3] and others have been reported [4]. Immunoassays and NAATs are currently being utilized clinically, while systems based on several other principles did not go further than the acceptance of manuscripts for publication.

The microbial community within the root system, the rhizosphere closely connected to the root, and their symbiotic relationship with the host are increasingly seen as possible drivers of natural pathogen resistance. Resistant cultivars have the most effective strategy in controlling the Chinese wheat yellow mosaic disease, but the roles of the root and rhizosphere microbial interactions among different taxonomic levels of resistant cultivars are still unknown. Thus, we aimed to investigate whether these microbial community composition and network characteristics are related to disease resistance and to analyze the belowground plant-associated microflora. Relatively high microbial diversity and stable community structure for the resistant cultivars were detected. Comparison analysis showed that some bacterial phyla were significantly enriched in the wheat root or rhizosphere of the resistant wheat cultivar. Furthermore, the root and rhizosphere of the resistant cultivars greatly recruited many known beneficial bacterial and fungal taxa. In contrast, the relative abundance of potential pathogens was higher for the susceptible cultivar than for the resistant cultivar. Network co-occurrence analysis revealed that a much more complex, more mutually beneficial, and a higher number of bacterial keystone taxa in belowground microbial networks were displayed in the resistant cultivar, which may have been responsible for maintaining the stability and ecological balance of the microbial community. Overall, compared with the susceptible cultivar, the resistant cultivar tends to recruit more potential beneficial microbial groups for plant and rhizosphere microbial community interactions. These findings indicate that beneficial rhizosphere microbiomes for cultivars should be targeted and evaluated using community compositional profiles. KEY POINTS: • Different resistance levels in cultivars affect the rhizosphere microbiome.. • Resistant cultivars tend to recruit more potential beneficial microbial groups. • Bacteria occupy a high proportion and core position in the microflora network.

We present a family of digital polymerase chain reaction (dPCR) chips made of silicon that are (9 × 9) mm2 in size, have a unique layout design, and have between 26,448 and 1,656,000 reaction wells. The chip layout was split into six fields sized 4200 × 2785 μm2 that contain reaction wells with a gap of a few μm separating the fields from each other. We also developed a universal fluorescence imaging method capable of processing images from those chips. It comprised automatic image acquisition, image stitching, alignment mark registration, rotation correction, determination of reaction wells’ positions, and result processing. The chip design, with fully automated image processing, provided a fast and reliable system for the absolute quantitative analysis of dPCR. Combined with ease-of-use, this family of dPCR chips offers a pathway to enable fast and affordable digital microfluidic diagnostic applications.

Microplastics (MPs) can alter microbial communities and carbon (C) cycling in agricultural soils. However, the mechanism by which MPs affect the decomposition of microbe-driven soil organic matter remains unknown. We investigated the bacterial community succession and temporal turnover during soil organic matter decomposition in MP-amended paddy soils (none, low [0.01% w/w], or high [1% w/w]). We observed that MPs reduced the CO

In this paper, we use the factor analysis model, and get the prediction function of the solvency of insurance companies. In order to verify the feasibility of the model, we have adopted Accumulated Local Effects Plot. It is proved that the solvency of an insurance company is positively correlated with its monetary funds, term deposits and owner's equity, negatively related to its own liabilities, and that the two indicators of monetary capital and insurance company liabilities are factors that have a high marginal contribution to predicting the solvency of insurance companies.

Liu, C.; Zhang, H.Q.; Miao, S.; Li, X.F.; Miao, Q., and Zhou, C.L., 2020. Assessment of status and vulnerability to seawater intrusion in Wendeng District, China. In: Guido Aldana, P.A. and Kantamaneni, K. (eds.), Advances in Water Resources, Coastal Management, and Marine Science Technology. Journal of Coastal Research, Special Issue No. 104, pp. 546–553. Coconut Creek (Florida), ISSN 0749-0208.Assessing the status and risk of seawater intrusion effectively are major problems for coastal groundwater management. This study integrated the groundwater quality index (GQISWI) and the vulnerability model (GALDIT) to establish a modified vulnerability model (GALDITGQI) to seawater intrusion and applied it to Wendeng District. The status of seawater intrusion in the study area was evaluated by GQISWI. In addition, four GALDIT models were applied to the study area, they are standard GALDIT, GALDITW optimized by sensitivity analysis, GALDITR optimized by triangular fuzzy number and GALDITGQI modified by GQISWI. The results of Pearson correlation analysis showed that the correlation between the above four models and TDS reached 0.711, 0.712, 0.740 and 0.762, respectively. The results of GALDITGQI were most relevant to the current status of seawater intrusion, which confirmed the effectiveness of GALDITGQI. This finding has important implications for assessing the vulnerability to seawater intrusion.

PCR has become one of the most valuable techniques currently used in bioscience, diagnostics and forensic science. Here we review the history of PCR development and the technologies that have evolved from the original PCR method. Currently, there are two main areas of PCR utilization in bioscience: high-throughput PCR systems and microfluidics-based PCR devices for point-of-care (POC) applications. We also discuss the commercialization of these techniques and conclude with a look into their modifications and use in innovative areas of biomedicine. For example, real-time reverse transcription PCR is the gold standard for SARS-CoV-2 diagnoses. It could also be used for POC applications, being a key component of the sample-to-answer system.

Nucleic acid amplification for the detection of infectious diseases, food pathogens, or assessment of genetic disorders require a laboratory setting with specialized equipment and technical expertise. Isothermal deoxyribonucleic acid amplification methods, such as loop-mediated isothermal amplification (LAMP), exhibit characteristics ideal for point-of-care (POC) applications, since their instrumentation is simpler in comparison with the standard method of polymerase chain reaction. Other key advantages of LAMP are robustness and the production of pyrophosphate in the presence of the target gene, enabling to detect the reaction products using the naked eye. Polymerase inhibitors, presented in clinical samples, do not affect the amplification process, making LAMP suitable for a simple sample-to-answer diagnostic systems with simplified sample preparation. In this review, we discuss the trends in miniaturized LAMP techniques, such as microfluidic, paper-based, and digital with their advantages and disadvantages, especially for POC applications alongside our opinion of the future development of miniaturized LAMP., Highlights • Introduction of loop mediated isothermal amplification (LAMP) and its principle. • Classical microfluidics-based LAMP for DNA/RNA detection. • Paper-based LAMP. • Microfluidic-based digital LAMP. • Future of microfluidic LAMP development.

The determination of the physical properties of fluids—such as the thermal characteristics, which include heat transfer time (Δt)—is becoming more challenging as system sizes shrink to micro- and nanometer scales. Hence, knowledge of these properties is crucial for the operation of devices requiring precise temperature (T) control, such as polymerase chain reactions, melting curve analysis (MCA), and differential scanning fluorimetry. In this paper, we introduced a flow-through microfluidic system to analyze thermal properties such as Δt among samples and the sidewall of a silicon chip using microscopic image analysis. We performed a spatial MCA with double-stranded deoxyribonucleic acid (dsDNA) and EvaGreen intercalator, using a flow-through microfluidic chip, and achieved a T gradient of ≈ 2.23 K mm−1. We calculated the mean value of Δt as ≈ 33.9 ms from a melting temperature (TM) location shift along the microchannel for a variable flow rate. Our system had a T resolution of ≈ 1.2 mK pixel−1 to distinguish different dsDNA molecules—based on the TM location within the chip—providing an option to use it as a high-throughput device for rapid DNA or protein analysis.