Soft fluorescent nanomaterials have attracted recent attention as imaging agents for biological applications, because they provide the advantages of good biocompatibility, high brightness, and easy ...biofunctionalization. Here, we provide a survey of recent developments in fluorescent soft nano-sized biological imaging agents. Various soft fluorescent nanoparticles (NPs) (including dye-doped polymer NPs, semiconducting polymer NPs, small-molecule organic NPs, nanogels, micelles, vesicles, and biomaterial-based NPs) are summarized from the perspectives of preparation methods, structure, optical properties, and surface functionalization. Based on both optical and functional properties of the nano-sized imaging agents, their applications are then reviewed in terms of
in vitro
imaging,
in vivo
imaging, and cellular-process imaging, by means of specific or nonspecific targeting.
Various soft fluorescent nanomaterials based on organic chromophores are highly competent nano-probes for
in vitro
and
in vivo
imaging.
Functionalized spiropyran-based chemosensors have attracted global attention due to their ability to undergo reversible conversion from a low-fluorescent spiro form to the highly fluorescent ...ring-opened merocyanine form in response to various external stimuli. In this review, systematically summarized and discussed the design and functional groups of spiropyran-based receptors, which possess binding sites for various metal ions and anions for colorimetric and fluorescent sensing applications in aqueous and biological systems.
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•Reversible isomerization can be prompted by numerous stimuli.•Spiropyran-based colorimetric and fluorometric sensors are reviewed.•This review analyzes and summarizes the structure of various organic chelating motifs.•Multifunctional spiropyran is able to detect a broad range of metal ions and anions.
Functionalized spiropyran-based chemosensors have attracted global attention due to their capability to undergo reversible conversion from a low-fluorescent spiro form to the highly fluorescent ring-opened merocyanine form in response to various external stimuli. In recent years, there has been extensive research on spiropyran derivatives basically which are modified with functional chelating agents, emerging as robust colorimetric and fluorescent sensors. These functional spiropyran sensors exhibits broad application prospects in the analysis and detection of trace pollutants, and other relevant research fields. Therefore, this review article outlines various chelating agents mainly amine, carboxylic acid and its derivatives, macrocyclic molecules, heterocyclic molecules, organic dyes, copolymers, and nanoparticles appended spiropyrans and demonstrate their utilization as fluorescent and colorimetric sensors in sensing applications as well as coordination behavior toward various metal ions and anions in aqueous and biological systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study was designed to investigate the in vitro and in vivo antioxidant activities of inulin. The in vitro assays demonstrated that the antioxidant activities of inulin, including the DPPH ...radical scavenging activity, ABTS scavenging activity and ferric reducing power, were weak and significantly lower than those of Vitamin C (P < 0.05). The influence of dietary supplementation with inulin on the antioxidant status of laying hens was evaluated with in vivo antioxidant assays. The results indicated that inulin supplementation quadratically improved the egg production rate of the laying hens (P < 0.01). The antioxidant enzyme activities in the serum, including SOD, CAT, and GSH-Px, and the total antioxidant capacity increased quadratically as inulin levels increased (P < 0.001). The levels of MDA in the serum decreased quadratically as inulin levels increased (P < 0.001). These findings suggest that inulin has the potential to improve the antioxidant status of laying hens.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
•The eight main bioclimatic variables influencing H. riparia Lour distributions were selected.•One positional, 3 topographic and 8 bioclimatic variables were used to model its distribution.•An MAXENT ...model was employed to simulate the habitat suitability distribution.•Habitat suitability for 3 historical periods and 2 climate warming scenarios were calculated.•The habitat suitability of H. riparia Lour is predicted to improve with global warming.
Climate change influences ecosystem by altering the habitat of species in it. We report the quantitative predictions of climate change on riparian species. Homonoia riparia (H. riparia) Lour, a species native to Yunnan Province, China, is a medicinal plant with high ecological and economic value. Its population has declined significantly, and the species has become locally endangered in recent decades. Understanding the habitat requirements of this species, evaluating habitat quality, and predicting its potential habitat are significant for protecting H. riparia Lour. One positional variable, three topographic variables and eight bioclimatic variables were used to model its distribution and potential habitat. The eight main bioclimatic variables influencing species distribution were selected from 19 bioclimatic variables based on correlation analysis and principal component analysis. An MAXENT model, because of the advantages of using presence-only data and performing well with incomplete data, small sample sizes and gaps, was employed to simulate the habitat suitability distribution. The results show that seven variables, namely, annual mean temperature, altitude, precipitation seasonality, precipitation of coldest quarter, the distance to the nearest river, temperature seasonality, and precipitation during the driest month, are significant factors determining H. riparia Lour’s suitable habitat. Habitat suitability for three historical periods and two future climate warming scenarios were calculated. The habitat suitability of H. riparia Lour in Yunnan Province is predicted to improve with global warming.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
In situ weaving an all‐carbon graphdiyne coat on a silicon anode is scalably realized under ultralow temperature (25 °C). This economical strategy not only constructs 3D all‐carbon mechanical and ...conductive networks with reasonable voids for the silicon anode at one time but also simultaneously forms a robust interfacial contact among the electrode components. The intractable problems of the disintegrations in the mechanical and conductive networks and the interfacial contact caused by repeated volume variations during cycling are effectively restrained. The as‐prepared electrode demostrates the advantages of silicon regarding capacity (4122 mA h g−1 at 0.2 A g−1) with robust capacity retention (1503 mA h g−1) after 1450 cycles at 2 A g−1, and a commercial‐level areal capacity up to 4.72 mA h cm−2 can be readily approached. Furthermore, this method shows great promises in solving the key problems in other high‐energy‐density anodes.
The growth of all‐carbon graphdiyne under ultralow temperature is applied to construct in situ the 3D mechanical and conductive networks for a Si anode. Such a strategy well demonstrates the advantages of Si in lithium storage (4122 mA h g−1), and greatly improves the long‐term retention (1503 mA h g−1) after 1450 cycles at 2 A g−1.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The pesticide and veterinary drug residues brought by large-scale agricultural production have become one of the issues in the fields of food safety and environmental ecological security. It is ...necessary to develop the rapid, sensitive, qualitative and quantitative methodology for the detection of pesticide and veterinary drug residues. As one of the achievements of nanoscience, quantum dots (QDs) have been widely used in the detection of pesticide and veterinary drug residues. In these methodology studies, the used QD-signal styles include fluorescence, chemiluminescence, electrochemical luminescence, photoelectrochemistry, etc. QDs can also be assembled into sensors with different materials, such as QD-enzyme, QD-antibody, QD-aptamer, and QD-molecularly imprinted polymer sensors, etc. Plenty of study achievements in the field of detection of pesticide and veterinary drug residues have been obtained from the different combinations among these signals and sensors. They are summarized in this paper to provide a reference for the QD application in the detection of pesticide and veterinary drug residues.
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IJS, KILJ, NUK, PNG, UL, UM, UPUK
Data augmentation plays a crucial role in training a CNN-based detector. Most previous approaches were based on using a combination of general image-processing operations and could only produce ...limited plausible image variations. Recently, GAN (Generative Adversarial Network) based methods have shown compelling visual results. However, they are prone to fail at preserving image-objects and maintaining translation consistency when faced with large and complex domain shifts, such as day-to-night. In this paper, we propose AugGAN, a GAN-based data augmenter which could transform on-road driving images to a desired domain while image-objects would be well-preserved. The contribution of this work is three-fold: (1) we design a structure-aware unpaired image-to-image translation network which learns the latent data transformation across different domains while artifacts in the transformed images are greatly reduced; (2) we quantitatively prove that the domain adaptation capability of a vehicle detector is not limited by its training data; (3) our object-preserving network provides significant performance gain in the difficult day-to-night case in terms of vehicle detection. AugGAN could generate more visually plausible images compared to competing methods on different on-road image translation tasks across domains. In addition, we quantitatively evaluate different methods by training Faster R-CNN and YOLO with datasets generated from the transformed results and demonstrate significant improvement on the object detection accuracies by using the proposed AugGAN model.
Automatic extraction of vertebra regions from a spinal magnetic resonance (MR) image is normally required as the first step to an intelligent spinal MR image diagnosis system. In this work, we ...develop a fully automatic vertebra detection and segmentation system, which consists of three stages; namely, AdaBoost-based vertebra detection, detection refinement via robust curve fitting, and vertebra segmentation by an iterative normalized cut algorithm. In order to produce an efficient and effective vertebra detector, a statistical learning approach based on an improved AdaBoost algorithm is proposed. A robust estimation procedure is applied on the detected vertebra locations to fit a spine curve, thus refining the above vertebra detection results. This refinement process involves removing the false detections and recovering the miss-detected vertebrae. Finally, an iterative normalized-cut segmentation algorithm is proposed to segment the precise vertebra regions from the detected vertebra locations. In our implementation, the proposed AdaBoost-based detector is trained from 22 spinal MR volume images. The experimental results show that the proposed vertebra detection and segmentation system can achieve nearly 98% vertebra detection rate and 96% segmentation accuracy on a variety of testing spinal MR images. Our experiments also show the vertebra detection and segmentation accuracies by using the proposed algorithm are superior to those of the previous representative methods. The proposed vertebra detection and segmentation system is proved to be robust and accurate so that it can be used for advanced research and application on spinal MR images.
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