Evolution Pattern in Bruised Tissue of 'Red Delicious' Apple.

The study of apple damage mechanisms is key to improving post-harvest apple treatment techniques, and the evolution pattern of damaged tissue is fundamental to the study of apple damage mechanisms. In the study, 'Red Delicious' apples were used to explore the relationship between damage and time. A cell death zone was found in the pulp of the damaged tissue after the apple had been bruised. The tissue damage was centered in the cell death zone and developed laterally, with the width of the damage increasing with injury time. The extent of tissue damage in the core and pericarpal directions varied. About 60% of the damaged tissue developed in the core direction and 40% in the pericarpal direction, and the damage ratios in both directions remained consistent throughout the injury. The depth of damage and the rate of damage were influenced by the impact force size and the difference in the size of the damaged part of the apple, but the damage development pattern was independent of the impact force size and the difference in the damaged part. The maximum damage rate was reached at about 30 min, and the depth of damage was stabilized at about 72 min. By studying the evolution pattern of the damaged tissue of the bruised 'Red Delicious' apple, it provides the research idea and theoretical basis for enhancing the prediction accuracy and robustness of early stage damage in apples.

Second near-infrared fluorescent Metal-Organic framework sensors for in vivo extracellular adenosine triphosphate monitoring.

Plant nanobionic sensors enable real-time monitoring of signaling molecules in plants by interfacing them with specifically designed nanoprobes, which have been acknowledged as species-independent analytical tools. In this study, we developed a plant nanobionic sensor for in vivo detection of extracellular adenosine triphosphate (eATP) in living plants by designing a novel second near-infrared (NIR-II) fluorescent metal-organic framework (MOF) nanoprobe. The NIR-II fluorescent nanoprobe (IR-1061 micelle@ZIF-90) with a sandwich structure was synthesized by successive encapsulation of the hydrophobic NIR-II dye IR-1061 with the amphipathic polymer DSPE-mPEG 2000 and MOF ZIF-90. Interestingly, coating ZIF-90 around IR-1061 micelles increased the NIR-II fluorescence 16.6-fold. Utilizing the ultrahigh NIR-II fluorescent emission of the designed nanoprobes and specific recognition of ZIF-90 to ATP, the nanoprobes were applied to spatial and temporal monitoring eATP in model and non-model plants under environmental stress.

Molecular Motor-Driven Light-Controlled Logic-Gated K+ Channel for Cancer Cell Apoptosis.

Developing artificial ion transport systems, which process complicated information and step-wise regulate properties, is essential for deeply comprehending the subtle dynamic behaviors of natural channel proteins (NCPs). Here a photo-controlled logic-gated K+ channel based on single-chain random heteropolymers containing molecular motors, exhibiting multi-core processor-like properties to step-wise control ion transport is reported. Designed with oxygen, deoxygenation, and different wavelengths of light as input signals, complicated logical circuits comprising "YES", "AND", "OR" and "NOT" gate components are established. Implementing these logical circuits with K+ transport efficiencies as output signals, multiple state transitions including "ON", "Partially OFF" and "Totally OFF" in liposomes and cancer cells are realized, further causing step-wise anticancer treatments. Dramatic K+ efflux in the "ON" state (decrease by 50% within 7 min) significantly induces cancer cell apoptosis. This integrated logic-gated strategy will be expanded toward understanding the delicate mechanism underlying NCPs and treating cancer or other diseases is expected.

Dynamic Prediction Model for Initial Apple Damage.

Prediction models of damage severity are crucial for the damage expression of fruit. In light of issues such as the mismatch of existing models in actual damage scenarios and the failure of static models to meet research needs, this article proposes a dynamic prediction model for damage severity throughout the entire process of apple damage and studies the relationship between the initial bruise form and impact energy distribution of apple damage. From the experiments, it was found that after impact a "cell death zone" appeared in the internal pulp of the damaged part of Red Delicious apples. The reason for the appearance of the cell death zone was that the impact force propagated in the direction of the fruit kernel in the form of stress waves; the continuous action of which continuously compressed the pulp's cell tissue. When the energy absorbed via elastic deformation reached the limit value, intercellular disadhesion of parenchyma cells at the location of the stress wave peak occurred to form cell rupture. The increase in intercellular space for the parenchyma cells near the rupture site caused a large amount of necrocytosis and, ultimately, formed the cell death zone. The depth of the cell death zone was closely related to the impact energy. The correlation coefficient r between the depth of the cell death zone and the distribution of impact energy was slightly lower at the impact height of 50 mm. As the impact height increased, the correlation coefficient r increased, approaching of value of 1. When the impact height was lower (50 mm), the correlation coefficient r had a large distribution range (from 0.421 to 0.983). As the impact height increased, the distribution range significantly decreased. The width of the cell death zone had a poor correlation with the pressure distribution on the impact surface of the apples that was not related to the impact height. In this article, the corresponding relationship between the form and impact energy distribution of the internal damaged tissues in the initial damage of Red Delicious apples was analyzed. This analysis aimed to provide a research concept and theoretical basis for more reliable research on the morphological changes in the damaged tissues of apples in the future, further improving the prediction accuracy of damage severity.

Supramolecular Strategy to Achieve Distinct Optical Characteristics and Boosted Chiroptical Enhancement Based on the Closed Conformation of Platinum(II) Complexes.

Synthesis of chiral molecules for understanding and revealing the expression, transfer, and amplification of chirality is beneficial to explore effective chiral medicines and high-performance chiroptical materials. Herein, we report a series of square-planar phosphorescent platinum(II) complexes adopting a dominantly closed conformation that exhibit efficient chiroptical transfer and enhancement due to the nonclassical intramolecular C-H···O or C-H···F hydrogen bonds between bipyridyl chelating and alkynyl auxiliary ligands as well as the intermolecular π-π stacking and metal-metal interactions. The spectroscopic and theoretical calculation results demonstrate that the chirality and optic properties are regulated from the molecular level to hierarchical assemblies. Notably, a 154 times larger gabs value of the circular dichroism signals is obtained. This study provides a feasible design principle to achieve large chiropticity and control the expression and transfer of the chirality.

Fast and Accurate Gamma Imaging System Calibration Based on Deep Denoising Networks and Self-Adaptive Data Clustering.

Gamma imagers play a key role in both industrial and medical applications. Modern gamma imagers typically employ iterative reconstruction methods in which the system matrix (SM) is a key component to obtain high-quality images. An accurate SM could be acquired from an experimental calibration step with a point source across the FOV, but at a cost of long calibration time to suppress noise, posing challenges to real-world applications. In this work, we propose a time-efficient SM calibration approach for a 4π-view gamma imager with short-time measured SM and deep-learning-based denoising. The key steps include decomposing the SM into multiple detector response function (DRF) images, categorizing DRFs into multiple groups with a self-adaptive K-means clustering method to address sensitivity discrepancy, and independently training separate denoising deep networks for each DRF group. We investigate two denoising networks and compare them against a conventional Gaussian filtering method. The results demonstrate that the denoised SM with deep networks faithfully yields a comparable imaging performance with the long-time measured SM. The SM calibration time is reduced from 1.4 h to 8 min. We conclude that the proposed SM denoising approach is promising and effective in enhancing the productivity of the 4π-view gamma imager, and it is also generally applicable to other imaging systems that require an experimental calibration step.

A charged nanocomposite membrane via co-deposition of gallic acid and polyethyleneimine-silver for improving separation and antibacterial properties.

Pharmaceuticals have been continuously detected from surface water and groundwater. In order to improve the rejection performance of pharmaceuticals by a nanofiltration membrane (NF), a positively charged membrane was prepared by co-deposition of natural gallic acid and polyethyleneimine on the polyacrylonitrile hydrolysis membrane. Effects of gallic acid concentration, polyethylene imine concentration, reaction time, and the molecular weight of polyethylene imine were documented. The physical and chemical properties of the membrane were also investigated by surface morphology, hydrophilicity, surface charge, and molecular weight cut-off. The optimized membrane had a molecular weight cut-off of about 958 Da and possessed a pure water permeability of 74.21 L·m-2·h-1·MPa-1. The results exhibited salt rejection in the following order: MgCl2 > CaCl2 > MgSO4 > Na2CO3 > NaCl > Na2SO4, while the rejection ability of pharmaceuticals is as follows: amlodipine > atenolol > carbamazepine > ibuprofen, suggesting that the positively charged membrane has enhanced retention to both divalent cations and charged pharmaceuticals. In addition, the antibacterial membrane was obtained by loading silver nanoparticles onto the positively charged membrane, which greatly improved the antibacterial ability of the membrane.

A super-hydrophilic partially reduced graphene oxide membrane with improved stability and antibacterial properties.

In order to improve stability and antibacterial property, a novel super-hydrophilic partially reduced graphene oxide membrane was prepared by interfacial polymerization of piperazine and partially reduced graphene oxide as aqueous solution and trimesoyl chloride as organic solution. Fourier transform infrared spectroscopy, scanning electron microscope, and contact angle measurement were conducted to probe the morphology and properties of the membranes. The modified membrane possessed super-hydrophilicity, improved durability and swelling resistance. The optimized membrane had a molecular weight cut off of about 674 Da and possessed a pure water permeability of 49.86 L·m-2·h-1·MPa-1. The retention order of salts was Na2SO4 > MgSO4 > MgCl2 > Na2CO3 > CaCl2 > NaCl, while the rejection for four kinds of pharmaceuticals followed the order of ibuprofen (92%) > carbamazepine (87%) > amlodipine (80%) > atenolol (76%), indicating that the negatively charged membrane could improve the retention performance by the electrostatic repulsive effect. Moreover, the enhanced antibacterial performance of membrane attributed to the dual effects of the super-hydrophilicity and the tea polyphenols antibacterial material loading, which may alter the charge distribution on and within the membrane, leading to loss of cell viability.

Quantitative Extraction and Evaluation of Tomato Fruit Phenotypes Based on Image Recognition.

Tomato fruit phenotypes are important agronomic traits in tomato breeding as a reference index. The traditional measurement methods based on manual observation, however, limit the high-throughput data collection of tomato fruit morphologies. In this study, fruits of 10 different tomato cultivars with considerable differences in fruit color, size, and other morphological characters were selected as samples. Constant illumination condition was applied to take images of the selected tomato fruit samples. Based on image recognition, automated methods for measuring color and size indicators of tomato fruit phenotypes were proposed. A deep learning model based on Mask Region-Convolutional Neural Network (R-CNN) was trained and tested to analyze the internal structure indicators of tomato fruit. The results revealed that the combined use of these methods can extract various important fruit phenotypes of tomato, including fruit color, horizontal and vertical diameters, top and navel angles, locule number, and pericarp thickness, automatically. Considering several corrections of missing and wrong segmentation cases in practice, the average precision of the deep learning model is more than 0.95 in practice. This suggests a promising locule segmentation and counting performance. Vertical/horizontal ratio (fruit shape index) and locule area proportion were also calculated based on the data collected here. The measurement precision was comparable to manual operation, and the measurement efficiency was highly improved. The results of this study will provide a new option for more accurate and efficient tomato fruit phenotyping, which can effectively avoid artificial error and increase the support efficiency of relevant data in the future breeding work of tomato and other fruit crops.

A high stability GO nanofiltration membrane preparation by co-deposition and crosslinking polydopamine for rejecting dyes.

In order to improve the stability of nanofiltration membrane in separation and purification, a novel polyelectrolyte multilayer nanofiltration membrane was facilely prepared by co-deposition of polydopamine (PDA) and polyethyleneimine (PEI) on the polyethersulfone (PES) ultrafiltration membrane substrate, followed by immersing graphene oxide (GO) solution, and crosslinking PDA. The modified surfaces were characterized using scanning electron microscopy (SEM) and atomic force microscopy (AFM), water contact angle, their saline flux and ability to reject salt and dye were determined. The results also exhibited salt rejection ability as Na2SO4 > K2SO4 > MgSO4 > NaCl > KCl > MgCl2, suggesting the higher rejection of divalent anion. Also, the retention order of the dye by the GO modified membrane is DY86 > DB19 > AG27 > DY142 > DB56 > AR151 > VB5, indicating that the GO modified membrane has better rejection of negatively charged dyes as well as higher molecular weight dyes. Ethanol and hypochlorite resistance tests under different pH conditions showed the membranes coated GO enhanced stability in regard to salt rejection properties. Significantly, the anti-biological test confirmed the growth rate of microalgae on the GO introduced membrane was decreased greatly due to enhanced stability and lower roughness.

Spring onion seed demand forecasting using a hybrid Holt-Winters and support vector machine model.

Demand for spring onion seeds is variable and maintaining its supply is crucial to the success of seed companies. Spring onion seed demand forecasting, which can help reduce the high operational costs increased by long-period propagation and complex logistics, has not previously been investigated yet. This paper provides a novel perspective on spring onion seed demand forecasting and proposes a hybrid Holt-Winters and support vector machine (SVM) forecasting model. The model uses dynamic factors, including historical seed sales, seed inventory, spring onion crop market price and weather data, as inputs to forecast spring onion seed demand. Forecasting error, i.e. the difference between actual and forecasted demand, is assessed. Two advanced machine learning models are trained on the same dataset as benchmark models. Numerical experiments using actual commercial sales data for three spring onion seed varieties show the proposed hybrid model outperformed the statistical-based models for all three forecasting errors. Seed inventory, spring onion crop market price and historical seed sales are the most important dynamic factors, among which seed inventory has short-term influence while other two have mid-term influence on seed demand forecasting. The absolute minimum temperature is the only factor having long-term influence. This study provides a promising spring onion seed demand forecasting model that helps understand the relationships between seed demand and other dynamic factors and the model could potentially be applied to demand forecasting of other crop seeds to reduce total operational costs.

Effects of different fertilizers on methane emissions and methanogenic community structures in paddy rhizosphere soil.

Paddy soil accounts for 10% of global atmospheric methane (CH4) emissions. Many types of fertilizers may enhance CH4 emissions, especially organic fertilizer. The aim of this study was to explore the effects of different fertilizers on CH4 and methanogen patterns in paddy soil. This experiment involved four treatments: chemical fertilizer (CT), organic fertilizer (OT), mixed with chemical and organic fertilizer (MT), and no fertilizer (ctrl). The three fertilization treatments were applied with total nitrogen at the same rate of 300 kg N ha-1. Paddy CH4, soil physicochemical variables and methanogen communities were quantitatively analyzed. Rhizosphere soil mcrA and pmoA gene copy numbers were determined by qPCR. Methanogenic 16S rRNA genes were identified by MiSeq sequencing. The results indicated CH4 emissions were significantly higher in OT (145.31 kg ha-1) than MT (84.62 kg ha-1), CT (77.88 kg ha-1) or ctrl (32.19 kg ha-1). Soil organic acids were also increased by organic fertilization. CH4 effluxes were significantly and negatively related to mcrA and pmoA gene copy numbers, and positively related to mcrA/pmoA. Above all, hydrogenotrophic Methanocella and acetoclastic Methanosaeta were the predominant methanogenic communities; these communities were strictly associated with soil potassium, oxalate, acetate, and succinate. Application of organic fertilizer promoted the dominant acetoclastic methanogens, but suppressed the dominant hydrogenotrophic methanogens. The transformation in methanogenic community structure and enhanced availability of C substrates may explain the increased CH4 production in OT compared to other treatments. Compared to OT, MT may partially mitigate CH4 emissions while guaranteeing a high rice yield. On this basis, we recommend the local fertilization pattern should change from 300 N kg ha-1 of organic manure to the same level of mixed fertilization. Moreover, we suggest multiple combinations of mixed fertilization merit more investigation in the future.

Genome-wide characterization and evolution analysis of miniature inverted-repeat transposable elements (MITEs) in moso bamboo (Phyllostachys heterocycla).

MAIN CONCLUSION: Moso bamboo MITEs were genome-wide identified first time, and data shows that MITEs contribute to the genomic diversity and differentiation of bamboo. Miniature inverted-repeat transposable elements (MITEs) are widespread in animals and plants. There are a large number of transposable elements in moso bamboo (Phyllostachys heterocycla var. pubescens) genome, but the genome-wide information of moso bamboo MITEs is not known yet. Here we identified 362 MITE families with a total of 489,592 MITE-related sequences, accounting for 4.74 % of the moso bamboo genome. The 362 MITE families are clustered into six known and one unknown super-families. Our analysis indicated that moso bamboo MITEs preferred to reside in or near the genes that might be involved in regulation of host gene expression. Of the seven super-families, three might undergo major expansion event twice, respectively, during 8-11 million years ago (mya) ago and 22-28 mya ago; two might experience a long expansion period from 6 to 13 mya. Almost 1/3 small RNAs might be derived from the MITE sequences. Some MITE families generate small RNAs mainly from the terminals, while others predominantly from the central region. Given the high copy number of MITEs, many siRNAs and miRNAs derived from MITE sequences and the preferential insertion of MITE into gene regions, MITEs may contribute to the genomic diversity and differentiation of bamboo.

Transcriptional profiling by DDRT-PCR analysis reveals gene expression during seed development in Carya cathayensis Sarg.

Hickory (Carya cathayensis Sarg.) seed has one of the highest oil content and is rich in polyunsaturated fatty acids (PUFAs), which kernel is helpful to human health, particularly to human brain function. A better elucidation of lipid accumulation mechanism would help to improve hickory production and seed quality. DDRT-PCR analysis was used to examine gene expression in hickory at thirteen time points during seed development process. A total of 67 unique genes involved in seed development were obtained, and those expression patterns were further confirmed by semi-quantitative RT-PCR and real time RT-PCR analysis. Of them, the genes with known functions were involved in signal transduction, amino acid metabolism, nuclear metabolism, fatty acid metabolism, protein metabolism, carbon metabolism, secondary metabolism, oxidation of fatty acids and stress response, suggesting that hickory underwent a complex metabolism process in seed development. Furthermore, 6 genes related to fatty acid synthesis were explored, and their functions in seed development process were further discussed. The data obtained here would provide the first clues for guiding further functional studies of fatty acid synthesis in hickory.

Identification of liguzinediol metabolites in rats by ultra performance liquid chromatography/quadrupole-time-of-flight mass spectrometry.

Ultra performance liquid chromatography/quadrupole-time-of-flight mass spectrometry (UPLC/QTOF MS) was employed to investigate the in vivo metabolism of liguzinediol. Urine, bile, feces and plasma samples were collected after intravenous administration of 10mg/kg liguzinediol to healthy rats. Altogether seven metabolites were detected and tentatively identified based on the characteristics of their protonated ions. The metabolites were mainly transformed by four main metabolic pathways including oxidation, sulfation, glycine conjugation and glucuronidation.