Currently the determination of cyanidin 3-rutinoside content in plant petals usually requires chemical assays or high performance liquid chromatography (HPLC), which are time-consuming and laborious. ...In this study, we aimed to develop a low-cost, high-throughput method to predict cyanidin 3-rutinoside content, and developed a cyanidin 3-rutinoside prediction model using near-infrared (NIR) spectroscopy combined with partial least squares regression (PLSR). We collected spectral data from
(Magnoliaceae) tepals and used five different preprocessing methods and four variable selection algorithms to calibrate the PLSR model to determine the best prediction model. The results showed that (1) the PLSR model built by combining the blockScale (BS) preprocessing method and the Significance multivariate correlation (sMC) algorithm performed the best; (2) The model has a reliable prediction ability, with a coefficient of determination (R
) of 0.72, a root mean square error (RMSE) of 1.04%, and a residual prediction deviation (RPD) of 2.06. The model can be effectively used to predict the cyanidin 3-rutinoside content of the perianth slices of
, providing an efficient method for the rapid determination of cyanidin 3-rutinoside content.
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•A QDs-based “turn-off-on” biosensor was developed to detect HSA.•Resveratrol quenched the fluorescence of QDs.•HSA can restore the quenched fluorescence of QDs-resveratrol ...system.•The limit of detection was 6.898 ng·mL−1.
We described a highly sensitive and selective strategy for sensing of human serum albumin (HSA) by constructing a reversible fluorescent “turn-off-on” sensor. Monodispersed cadmium telluride quantum dots (CdTe QDs) were synthesized by using a simple aqueous phase synthesis method, which exhibited strong green fluorescence. The CdTe QDs fluorescence was first quenched using resveratrol through dynamic quenching type, that is to say, excited states CdTe QDs collided with resveratrol. HSA can cooperate with resveratrol to dissociate CdTe QDs/resveratrol, leading to the recovered fluorescence of CdTe QDs. Therefore, a facile reversible fluorescent “turn-off-on” sensor can be developed for HSA detection. In a wide concentration range of HSA (0.0237–100 μg mL−1), the detection limit could reach 6.898 ng mL−1, which was much lower than previously reported values, indicating high sensitivity. Meanwhile, this strategy was successfully applied to the synthetic samples and demonstrated ideal selectivity. Moreover, the mechanisms of the interactions among QDs, resveratrol, and HSA were also investigated. The proposed strategy for HSA determination based on the constructed reversible fluorescent “turn-off-on” sensor suggests great promising in fluorescent sensing.
Rapid and accurate plant growth and biomass estimation is essential for formulating and implementing targeted forest cultivation measures. In this study, RGB-D imaging technology was used to obtain ...the RGB and depth imaging data for a Toona sinensis seedling canopy to estimate plant growth and aboveground biomass (AGB). Three hundred T. sinensis seedlings from 20 varieties were planted under five different drought stress treatments. The U-Net model was applied first to achieve highly accurate segmentation of plants from complex backgrounds. Simple linear regression (SLR) was used for plant height prediction, and the other three models, including multivariate linear (ML), random forest (RF) and multilayer perceptron (MLP) regression, were applied to predict the AGB and compared for optimal model selection. The results showed that the SLR model yields promising and reliable results for the prediction of plant height, with R2 and RMSE values of 0.72 and 1.89 cm, respectively. All three regression methods perform well in the prediction of AGB estimation. MLP yields the highest accuracy in predicting dry and fresh aboveground biomass compared to the other two regression models, with R2 values of 0.77 and 0.83, respectively. The combination of Gray, Green minus red (GMR) and Excess green index (ExG) was identified as the key predictor by RReliefF for predicting dry AGB. GMR was the most important in predicting fresh AGB. This study demonstrated that the merits of RGB-D and machine learning models are effective phenotyping techniques for plant height and AGB prediction, and can be used to assist dynamic responses to drought stress for breeding selection.
Vitamin E, also known as tocochromanol, is a lipid-soluble antioxidant that can only be produced by photosynthetic organisms in nature. Vitamin E is not only essential in human diets, but also ...required for plant environment adaptions. To synthesize vitamin E, specific prenyl groups needs to be incorporated with homogentisate as the first step of reaction. After decades of studies, an almost complete roadmap has been revealed for tocochromanol biosynthesis pathway. However, chlorophyll-derived prenyl precursors for synthesizing tocochromanols are still a mystery. In recent years, by employing forward genetic screening and genome-wide-association approaches, significant achievements were acquired in studying vitamin E. In this review, by summarizing the recent progresses in vitamin E, we provide to date the most updated whole view of vitamin E biosynthesis pathway. Also, we discussed about the role of vitamin E in plants stress response and its potential as signaling molecules.
Dark septate endophytes (DSEs) fungi are beneficial to host plants with regard to abiotic stress. Here, we examined the capability of SWIR spectroscopy to classify fungus types and detected the ...growth stages of DSEs fungi in a timely, non-destructive and time-saving manner. The SWIR spectral data of five DSEs fungi in six growth stages were collected, and three pre-processing methods and sensitivity analysis (SA) variable selection methods were performed using a machine learning model. The results showed that the De-trending + first Derivative (DET_FST) processing spectra combined with the support vector machine (SVM) model yielded the best classification accuracy for fungi classification at different growth stages and growth stage detection on different fungus types. The mean accuracy of generic model for fungi classification and growth stage detection are 0.92 and 0.99 on the calibration set, respectively. Seven important bands, 1164, 1456, 2081, 2272, 2278, 2448 and 2481 nm, were found to be related to the SVM fungi classification. This study provides a rapid and efficient method for the classification of fungi in different growth stages and the detection of fungi growth stage of various types of fungi and could serve as a tool for fungi study.
To evaluate ultrasound characteristics in the prediction of malignant and benign phyllodes tumor of the breast (PTB) by using Logistic regression analysis.
79 lesions diagnosed as PTB by pathology ...were analyzed retrospectively. The ultrasound features of PTB were recorded and compared between benign and malignant tumors by using single factor and multiple stepwise Logistic regression analysis. Moreover, the Logistic regression model for malignancy prediction was also established.
There were 79 patients with PTB, including 39 benign PTBs and 40 malignant PTBs (33 borderline PTBs and 7 malignant PTBs by pathologic classification). The area under the ROC curve (AUC) of lesion size and age were 0.737 and 0.850 respectively. There were significant differences in age, lesion size, shape, internal echo, liquefaction, and blood flow between malignant and benign PTBs by using single-factor analysis (P<0.05). Age, internal echo, and liquefaction were significant features by using Logistic regression analysis. The corresponding regression equation In (p/(1 - p) = -3.676+2.919 internal echo +3.029 liquefaction +4.346 age).
Internal echo, age, and liquefaction are independent ultrasound characteristics in predicting the malignancy of PTBs.
•1. Water extraction and alcohol precipitation yielded Phellinus igniarius extracts.•2. Dual probing of compound activity by UF-LC combined with molecular docking.•3. Aqueous extraction was optimized ...using the response surface methodology.•4. Target compounds were isolated using HSCCC combined with semi-preparative LC.•5. Purity of all three target compounds exceeded 98%.
We developed an efficient combination method for extraction, biological activity screening, and preparation of 5-lipoxygenase inhibitors from Phellinus igniarius. 5-Lipoxygenase inhibitors were rapidly screened using ultrafiltration-liquid chromatography based on the receptor-ligand affinity. Parameters such as extraction time, extraction times, and temperature as well as liquid–solid ratio were optimized using response surface methodology to maximize the total yield of the three target compounds. Next, bioactive ingredients were isolated using high-speed countercurrent chromatography and semi-preparative liquid chromatography. Three active ingredients, phellibaumin E, protocatechuic aldehyde, and osmundacetone, were obtained via ultrafiltration-liquid chromatography. Subsequently, the potential anti-dementia effects of the obtained bioactive compounds were verified using molecular docking assays. The above-mentioned target compounds, with purities of 98.82%, 98.89%, and 99.51%, respectively, were separated using a two-phase solvent system consisting of n-hexane–ethyl acetate-ethanol–water (2.5:2:0.75:3, v/v/v/v) coupled with semi-preparative liquid chromatography.
Biocatalysis is increasingly replacing traditional methods of manufacturing fine chemicals due to its green, mild, and highly selective nature, but biocatalysts, such as enzymes, are generally ...costly, fragile, and difficult to recycle. Immobilization provides protection for the enzyme and enables its convenient reuse, which makes immobilized enzymes promising heterogeneous biocatalysts; however, their industrial applications are limited by the low specific activity and poor stability. Herein, we report a feasible strategy utilizing the synergistic bridging of triazoles and metal ions to induce the formation of porous enzyme-assembled hydrogels with increased activity. The catalytic efficiency of the prepared enzyme-assembled hydrogels toward acetophenone reduction is 6.3 times higher than that of the free enzyme, and the reusability is confirmed by the high residual catalytic activity after 12 cycles of use. A near-atomic resolution (2.1 Å) structure of the hydrogel enzyme is successfully analyzed via cryogenic electron microscopy, which indicates a structure-property relationship for the enhanced performance. In addition, the possible mechanism of gel formation is elucidated, revealing the indispensability of triazoles and metal ions, which guides the use of two other enzymes to prepare enzyme-assembled hydrogels capable of good reusability. The described strategy can pave the way for the development of practical catalytic biomaterials and immobilized biocatalysts.
Drought is a climatic event that considerably impacts plant growth, reproduction and productivity.
is a tree species with high economic, edible and medicinal value, and has drought resistance. Thus, ...the objective of this study was to dynamically monitor the physiological indicators of
in real time to ensure the selection of drought-resistant varieties of
. In this study, we used near-infrared spectroscopy as a high-throughput method along with five preprocessing methods combined with four variable selection approaches to establish a cross-validated partial least squares regression model to establish the relationship between the near infrared reflectance spectroscopy (NIRS) spectrum and physiological characteristics (i.e., chlorophyll content and nitrogen content) of
leaves. We also tested optimal model prediction for the dynamic changes in
chlorophyll and nitrogen content under five separate watering regimes to mimic non-destructive and dynamic detection of plant leaf physiological changes. Among them, the accuracy of the chlorophyll content prediction model was as high as 72%, with root mean square error (RMSE) of 0.25, and the RPD index above 2.26. Ideal nitrogen content prediction model should have
of 0.63, with RMSE of 0.87, and the RPD index of 1.12. The results showed that the PLSR model has a good prediction effect. Overall, under diverse drought stress treatments, the chlorophyll content of
leaves showed a decreasing trend over time. Furthermore, the chlorophyll content was the most stable under the 75% field capacity treatment. However, the nitrogen content of the plant leaves was found to have a different and variable trend, with the greatest drop in content under the 10% field capacity treatment. This study showed that NIRS has great potential for analyzing chlorophyll nitrogen and other elements in plant leaf tissues in non-destructive dynamic monitoring.
In this study, a brass or glass spherical impactor vertically penetrating into a granular bed composed of mono-sized spherical or elongated particles was simulated with three-dimensional (3D) ...discrete element method (DEM). Good agreement of the particle masses in the cup before and after penetration can be found in the simulations and experiments. The effects of particle length (
), friction coefficient, and particle configuration on the penetration depth of the impactor, ejecta mass, and solid volume fraction describing the response of the granular bed are discussed. The penetration depth is negatively correlated with
as the corresponding solid volume fraction of the granular bed decreases. A smaller friction coefficient leads to a larger penetration depth of the impactor and more ejection of particles. When the impactor is penetrating the
= 10 mm elongated particles, the penetration depth is negatively correlated to the order parameter and solid volume fraction.
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