Carbon dots (C-dots) are a kind of fluorescent nanoparticles that are strongly fluorescent, non-blinking, and can be easily synthesized at low cost. Their emission color can be tuned by varying the ...excitation wavelength. Their properties make them strong competitors to semiconductor quantum dots. Synthetic approaches for C-dots can be classified into two categories, viz. top-down and bottom-up methods. Surface passivated and functionalized C-dots can be utilized to sense pH values, metal ions and organic molecules. Owing to their low cytotoxicity, biocompatibility and impressive photostability, long-term observations become possible. C-dots also show promise as labels and for bioimaging. This review (with 142 refs.) is divided into several sections. The first covers commonly used methods for preparation of C-dots including laser ablation, arc discharge, electrochemical methods, pyrolytic processes, template based methods, microwave assisted methods, chemical oxidation methods, reverse micelle based methods, etc. The first section also covers methods for surface functionalization and passivation. We continue by discussing the spectroscopic properties and other physical and chemical properties of C-dots (fluorescence, up-conversion fluorescence, methods for enhancing photoluminescence, effects of pH value, cytotoxicity, etc.). Another section covers the characterization including TEM and XRD. Applications in biology are summarized and subdivided into in vitro imaging, in vivo imaging, chemical probe, quantitation of biomacromolecules, but also in drug delivery, photoacoustic imaging and anticancer therapy. We finally discuss current challenges and perspectives in this promising field.
Graphical Abstract
This review summarizes the commonly used methods for the preparation of C-dots, their surface functionalization, physical and chemical properties, characterization as well as applications and recent advances in the fields of biology and anticancer therapy. We also discuss the challenges and perspectives in this exciting and promising field.
Soil quality evaluation as a decision-making tool to improve understanding of soil quality is essential for grading croplands and adopting proper agricultural practices. Various methods of soil ...quality evaluation have been developed, which have occasionally generated inconsistent evaluation results between differing soil types. The applicability of these techniques is seldom tested before implementing an evaluation method on a specific soil region. Fluvisol is an important soil resource for agriculture in China, especially for irrigation districts along the lower Yellow River. In the present study, the soil quality of two typical agricultural counties (Yucheng and Kenli) along the lower Yellow River was evaluated using four commonly utilized methods. In the two counties, the overall spatial patterns of soil quality derived from the four methods were similar, with differences in details existing among these methods. The soil quality in Yucheng, ranging from moderate to high, is superior to that observed in Kenli, where salinity is the primary limiting factor. In addition, the applicability of soil quality evaluation methods on the Fluvisol was investigated. It was found that the integrated quality indexing-linear scoring (IQI–LS) and the Nemoro indexing-linear scoring (NQI–LS) methods were the most accurate and practical of the four methods studied. These methods, which are based on the total data set of indicators, show better performance for soil quality evaluation on a Fluvisol. Further, different evaluation methods based on the minimum data set of indicators were compared, considering both the accuracy of the evaluation and the economic cost of obtaining the soil data. The results from the present study indicate that the IQI–LS method based on the minimum data set of indictors is recommended for large-scale soil quality evaluations.
•Four soil quality evaluation methods were compared for a Fluvisol.•IQI–LS and NQI–LS methods performed better in soil quality evaluations.•For large-scale studies, the IQI–LS based on a minimum data set is recommended.
This paper describes an analytical technique that can be utilized to predict the short-circuit current in a fault-tolerant permanent-magnet machine under partial-turn short-circuit fault conditions. ...It has been shown that the current in partially short-circuited turns is dependent on their relative position in the slot where the phase winding is accommodated, and the slot-leakage flux associated with these turns has a significant influence on the short-circuit current when a remedial action has been applied. An analytical model that quantifies the variation of the slot-leakage flux as a function of the relative position of partially short-circuited turns has been developed. Both finite-element analysis and experimental results demonstrate the effectiveness of the proposed technique for predicting the short-circuit current.
Abstract
N6-methyl-adenosine(m6A) modification emerges as an abundant and dynamic regulation throughout the Eukaryotic transcriptome. Dysregulation of the m6A regulators has increasingly been found ...in many neoplasms. It is reasonable to believe that m6A changes the fate of cancer cells and subsequently affected all aspects of cancer progression. In view of the context-dependent role of m6A modification, we emphasize a dual effect of m6A in a particular tumor model, that is, m6A plays a promoting role or a suppressing role in different stages of cancer. This novel sight is compared to the older view that a particular m6A regulator acts as a consistent role in cancer progression.
Quantifying global photosynthesis remains a challenge due to a lack of accurate remote sensing proxies. Solar-induced chlorophyll fluorescence (SIF) has been shown to be a good indicator of ...photosynthetic activity across various spatial scales. However, a global and spatially challenging estimate of terrestrial gross primary production (GPP) based on satellite SIF remains unresolved due to the confounding effects of species-specific physical and physiological traits and external factors, such as canopy structure or photosynthetic pathway (C3 or C4). Here we analyze an ensemble of far-red SIF data from OCO-2 satellite and ground observations at multiple sites, using the spectral invariant theory to reduce the effects of canopy structure and to retrieve a structure-corrected total canopy SIF emission (SIFtotal). We find that the relationships between observed canopy-leaving SIF and ecosystem GPP vary significantly among biomes. In contrast, the relationships between SIFtotal and GPP converge around two unique models, one for C3 and one for C4 plants. We show that the two single empirical models can be used to globally scale satellite SIF observations to terrestrial GPP. We obtain an independent estimate of global terrestrial GPP of 129.56 ± 6.54 PgC/year for the 2015–2017 period, which is consistent with the state-of-the-art data- and process-oriented models. The new GPP product shows improved sensitivity to previously undetected ‘hotspots’ of productivity, being able to resolve the double-peak in GPP due to rotational cropping systems. We suggest that the direct scheme to estimate GPP presented here, which is based on satellite SIF, may open up new possibilities to resolve the dynamics of global terrestrial GPP across space and time.
•An ensemble of far-red SIF from ground and OCO-2 was compared with in situ GPP.•BRF data can be used to reduce the effects of canopy structure on SIF.•BRF data is used to derive total canopy SIF emission (SIFtotal) for OCO-2.•SIFtotal and GPP relationships converge two unique models for C3 and C4 plants.•SIFtotal-based model yields an estimate of GPP of 129.56 PgC/year for 2015–2017.
Long non-coding RNA PTENP1, the pseudogene of PTEN tumor suppressor, has been reported to exert its tumor suppressive function via modulation of PTEN expression in many malignancies, including breast ...cancer (BC). However, whether the PTENP1/miR-20a/PTEN axis exists and how it functions in BC progression remains elusive.
The levels of PTENP1, PTEN and miR-20a were measured by qRT-PCR. Furthermore, the breast cancer cells proliferation was further measured by CCK8 assay, colony formation assays, EDU and Ki67 staining. The migratory and invasive ability was determined by transwell assay. Flow cytometry, JC-1 and TUNEL assays were conducted to show the occurrence of apoptosis. Xenograft model was used to show the tumorigenesis of breast cancer cells.
We analyzed PTENP1 and PTEN levels in clinical BC samples and cell lines, and found that PTENP1 and PTEN were confirmed and closely correlated with the malignancy of BC cell lines and poor clinical prognosis. Moreover, alteration of PTENP1 affects BC cell proliferation, invasion, tumorigenesis and chemoresistance to adriamycin (ADR). Bioinformatic analysis and dual-luciferase reporter gene assay predicted that PTENP1 was a direct target of miR-20a, which was clarified an alternative effect on BC aggressiveness phenotype. In addition, PTENP1 functioned as an endogenous sponge of miR-20a to regulate PTEN expression, which mediated BC cells proliferation, invasion and drug resistance via activation the phosphatidylinositol-3 kinase (PI3K)/AKT pathway. PI3K inhibitor LY294002 or siAkt also prevented BC cells progression.
Collectively, these data indicated that PTENP1/miR-20a/PTEN axis involved in the malignant behaviors of BC cells, illuminating the possible mechanism mediated by PTEN via PI3K/Akt pathway. Targeting PTENP1/miR-20a/PTEN may provide a potential diagnosis and treatment strategy for BC.
The Cyclone Global Navigation Satellite System (CYGNSS), a publicly accessible spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) data, provides a new alternative opportunity for ...large-scale soil moisture (SM) retrieval, but with interference from complex environmental conditions (i.e., vegetation cover and ground roughness). This study aims to develop a high-accuracy model for CYGNSS SM retrieval. The normalized surface reflectivity calculated by CYGNSS is fused with variables that are highly related to the SM obtained from optical/microwave remote sensing to solve the problem of the influence of complicated environmental conditions. The Gradient Boost Regression Tree (GBRT) model aided by land-type data is then used to construct a multi-variables SM retrieval model with six different land types of multiple models. The methodology is tested in southeastern China, and the results correlate very well with the existing satellite remote sensing products and in situ SM data (R = 0.765, ubRMSE = 0.054 m3m−3 vs. SMAP; R = 0.653, ubRMSE = 0.057 m3 m−3 vs. ERA5 SM; R = 0.691, ubRMSE = 0.057 m3m−3 vs. in situ SM). This study makes contributions from two aspects: (1) improves the accuracy of the CYGNSS retrieval of SM based on fusion with other auxiliary data; (2) constructs the SM retrieval model with multi-layer multiple models, which is suitable for different land properties.
Unmanned aerial vehicle (UAV)-based multispectral remote sensing effectively monitors agro-ecosystem functioning and predicts crop yield. However, the timing of the remote sensing field campaigns can ...profoundly impact the accuracy of yield predictions. Little is known on the effects of phenological phases on skills of high-frequency sensing observations used to predict maize yield. It is also unclear how much improvement can be gained using multi-temporal compared to mono-temporal data. We used a systematic scheme to address those gaps employing UAV multispectral observations at nine development stages of maize (from second-leaf to maturity). Next, the spectral and texture indices calculated from the mono-temporal and multi-temporal UAV images were fed into the Random Forest model for yield prediction. Our results indicated that multi-temporal UAV data could remarkably enhance the yield prediction accuracy compared with mono-temporal UAV data (R2 increased by 8.1% and RMSE decreased by 27.4%). For single temporal UAV observation, the fourteenth-leaf stage was the earliest suitable time and the milking stage was the optimal observing time to estimate grain yield. For multi-temporal UAV data, the combination of tasseling, silking, milking, and dough stages exhibited the highest yield prediction accuracy (R2 = 0.93, RMSE = 0.77 t·ha−1). Furthermore, we found that the Normalized Difference Red Edge Index (NDRE), Green Normalized Difference Vegetation Index (GNDVI), and dissimilarity of the near-infrared image at milking stage were the most promising feature variables for maize yield prediction.
Monitoring soil salinity is essential for agricultural development and ecological systems in the coastal saline area. The global navigation satellite system (GNSS) interferometry reflectometry ...(GNSS-IR) can provide new opportunities to retrieve long-term soil salinity at the point-scale theoretically, because the utilized L-band of GNSS-IR is sensitive to soil dielectric permittivity, while the soil salinity can affect its imaginary part. However, the method of soil salinity retrieval has not been researched currently. This study, taking the GNSS-IR data from the station located in the coastal saline area, gives the first evaluation of using this data source for soil salinity retrievals. First, the three interferogram metrics (i.e., phase, amplitude, and reflector height) and their corresponding statistics are extended to include the contributions from the environmental conditions. Then, the model for semi-empirically retrieving soil salinity from these parameters is constructed through the gradient boosting regression tree (GBRT) machine learning (ML) technique. The results show that the phase and height and their corresponding statistics have a relatively strong relationship with the soil salinity as independent variables. Meanwhile, the soil salinity retrieved from the global positioning system and BeiDou navigation satellite system (BDS) agree and correlate well with the in-situ measurements derived from the 5TE sensor ( R varies from 0.670 to 0.808, RMSE varies from 1.350 to 1.895 mS/cm, and MAE ranges from 1.049 to 1.749 mS/cm). The work shows the capability of GNSS-IR in retrieving soil salinity and considerably increases the service available from the geodetic-grade GNSS receivers.
Since flood inundation hampers human life and the economy, flood inundation retrieval with high temporal resolution and accuracy is essential for the projection of the environmental impact. In this ...study, a novel cyclone global navigation satellite system (CYGNSS)-based index, named the annual threshold flood inundation index (ATFII) for flood inundation retrieval, is proposed, and the grades of flood inundation are quantified. First, the CYGNSS surface reflectivity with land surface properties (i.e., vegetation and surface roughness) calibration is derived based on the zeroth-order radiative transfer model. Then, an index named ATFII is proposed to achieve inundation retrieval, and the inundation grades are classified. The results are validated with the Visible Infrared Imaging Radiometer Suite (VIIRS) flood product and GPM precipitation data. The validation results between ATFII and GPM precipitation indicate that the ATFII enables flood inundation retrieval at rapid timescales and quantifies the inundation variation grades. Likewise, for monthly results, the R value between the VIIRS flood product and ATFII varies from 0.51 to 0.64, with an acceptable significance level (p < 0.05). The study makes contributions in two aspects: (1) it provides an index-based method for mapping daily flood inundation on a large scale, with the advantages of fast speed and convenience, and (2) it provides a new way to derive inundation grade variations, which can help in studying the behavior of inundation in response to environmental impacts directly.
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