High-throughput and separating-free phenotyping method for on-panicle rice grains based on deep learning.

Rice is a vital food crop that feeds most of the global population. Cultivating high-yielding and superior-quality rice varieties has always been a critical research direction. Rice grain-related traits can be used as crucial phenotypic evidence to assess yield potential and quality. However, the analysis of rice grain traits is still mainly based on manual counting or various seed evaluation devices, which incur high costs in time and money. This study proposed a high-precision phenotyping method for rice panicles based on visible light scanning imaging and deep learning technology, which can achieve high-throughput extraction of critical traits of rice panicles without separating and threshing rice panicles. The imaging of rice panicles was realized through visible light scanning. The grains were detected and segmented using the Faster R-CNN-based model, and an improved Pix2Pix model cascaded with it was used to compensate for the information loss caused by the natural occlusion between the rice grains. An image processing pipeline was designed to calculate fifteen phenotypic traits of the on-panicle rice grains. Eight varieties of rice were used to verify the reliability of this method. The R2 values between the extraction by the method and manual measurements of the grain number, grain length, grain width, grain length/width ratio and grain perimeter were 0.99, 0.96, 0.83, 0.90 and 0.84, respectively. Their mean absolute percentage error (MAPE) values were 1.65%, 7.15%, 5.76%, 9.13% and 6.51%. The average imaging time of each rice panicle was about 60 seconds, and the total time of data processing and phenotyping traits extraction was less than 10 seconds. By randomly selecting one thousand grains from each of the eight varieties and analyzing traits, it was found that there were certain differences between varieties in the number distribution of thousand-grain length, thousand-grain width, and thousand-grain length/width ratio. The results show that this method is suitable for high-throughput, non-destructive, and high-precision extraction of on-panicle grains traits without separating. Low cost and robust performance make it easy to popularize. The research results will provide new ideas and methods for extracting panicle traits of rice and other crops.

A non-destructive coconut fruit and seed traits extraction method based on Micro-CT and deeplabV3+ model.

With the completion of the coconut gene map and the gradual improvement of related molecular biology tools, molecular marker-assisted breeding of coconut has become the next focus of coconut breeding, and accurate coconut phenotypic traits measurement will provide technical support for screening and identifying the correspondence between genotype and phenotype. A Micro-CT system was developed to measure coconut fruits and seeds automatically and nondestructively to acquire the 3D model and phenotyping traits. A deeplabv3+ model with an Xception backbone was used to segment the sectional image of coconut fruits and seeds automatically. Compared with the structural-light system measurement, the mean absolute percentage error of the fruit volume and surface area measurements by the Micro-CT system was 1.87% and 2.24%, respectively, and the squares of the correlation coefficients were 0.977 and 0.964, respectively. In addition, compared with the manual measurements, the mean absolute percentage error of the automatic copra weight and total biomass measurements was 8.85% and 25.19%, respectively, and the adjusted squares of the correlation coefficients were 0.922 and 0.721, respectively. The Micro-CT system can nondestructively obtain up to 21 agronomic traits and 57 digital traits precisely.

Open-source mobile multispectral imaging system and its applications in biological sample sensing.

Visible-near-infrared spectroscopy data can be utilized as an important quantitative indicator of biomolecular quantitative analysis. When acquiring spectral information, hyperspectral/multispectral imaging systems can obtain the spatial information of the object of interest. This allows the complete spatial-spectral information of the object of interest to be acquired and the spatial distribution of biomolecules to be analyzed. In this study, we present an open-source mobile multispectral imaging system, test the influence of the utilization of LEDs on the multispectral image, and design image-processing algorithms to correct this influence. Todemonstrate the effectivenessofthesystem, the system is applied to meat freshness analysis, small-animal tumor in-vivo imaging, and chlorophyll spatial distribution imaging. The experimental results verify that our system has stable performance and is compatible with a wide range of spectral imaging applications.

Intrinsic specificity of plain ammonium citrate carbon dots for Helicobacter pylori: Interfacial mechanism, diagnostic translation and general revelation.

The exploitation of carbon dots (CDs) is now flourishing; however, more effort is needed to overcome their lack of intrinsic specificity. Herein, instead of synthesizing novel CDs, we reinvestigated three reported CDs and discovered that plain ammonium citrate CDs (AC-CDs) exhibited surprising specificity for Helicobacter pylori. Notably, we showed that the interfacial mechanism behind this specificity was due to the affinity between the high abundant urea/ammonium transporters on H. pylori outer membrane and the surface-coordinated ammonium ions on AC-CDs. Further, we justified that ammonium sulfate-citric acid CDs also possessed H. pylori-specificity owing to their NH4 + doping. Thereby, we suggested that the incorporation of a molecule that could be actively transported by abundant membrane receptors into the precursors of CDs might serve as a basis for developing a plain CD with intrinsic specificity for H. pylori. Moreover, AC-CDs exhibited specificity towards live, dead, and multidrug-resistant H. pylori strains. Based on the specificity, we developed a microfluidics-assisted in vitro sensing approach for H. pylori, achieving a simplified, rapid and ultrasensitive detection with two procedures, shortened time within 45.0 â€‹min and a low actual limit of detection of 10.0 â€‹CFU â€‹mL-1. This work sheds light on the design of more H. pylori-specific or even bacteria-specific CDs and their realistic translation into clinical practice.

Nondestructive 3D phenotyping method of passion fruit based on X-ray micro-computed tomography and deep learning.

Passion fruit is a tropical liana of the Passiflora family that is commonly planted throughout the world due to its abundance of nutrients and industrial value. Researchers are committed to exploring the relationship between phenotype and genotype to promote the improvement of passion fruit varieties. However, the traditional manual phenotyping methods have shortcomings in accuracy, objectivity, and measurement efficiency when obtaining large quantities of personal data on passion fruit, especially internal organization data. This study selected samples of passion fruit from three widely grown cultivars, which differed significantly in fruit shape, size, and other morphological traits. A Micro-CT system was developed to perform fully automated nondestructive imaging of the samples to obtain 3D models of passion fruit. A designed label generation method and segmentation method based on U-Net model were used to distinguish different tissues in the samples. Finally, fourteen traits, including fruit volume, surface area, length and width, sarcocarp volume, pericarp thickness, and traits of fruit type, were automatically calculated. The experimental results show that the segmentation accuracy of the deep learning model reaches more than 0.95. Compared with the manual measurements, the mean absolute percentage error of the fruit width and length measurements by the Micro-CT system was 1.94% and 2.89%, respectively, and the squares of the correlation coefficients were 0.96 and 0.93. It shows that the measurement accuracy of external traits of passion fruit is comparable to manual operations, and the measurement of internal traits is more reliable because of the nondestructive characteristics of our method. According to the statistical data of the whole samples, the Pearson analysis method was used, and the results indicated specific correlations among fourteen phenotypic traits of passion fruit. At the same time, the results of the principal component analysis illustrated that the comprehensive quality of passion fruit could be scored using this method, which will help to screen for high-quality passion fruit samples with large sizes and high sarcocarp content. The results of this study will firstly provide a nondestructive method for more accurate and efficient automatic acquisition of comprehensive phenotypic traits of passion fruit and have the potential to be extended to more fruit crops. The preliminary study of the correlation between the characteristics of passion fruit can also provide a particular reference value for molecular breeding and comprehensive quality evaluation.

PocketMaize: An Android-Smartphone Application for Maize Plant Phenotyping.

A low-cost portable wild phenotyping system is useful for breeders to obtain detailed phenotypic characterization to identify promising wild species. However, compared with the larger, faster, and more advanced in-laboratory phenotyping systems developed in recent years, the progress for smaller phenotyping systems, which provide fast deployment and potential for wide usage in rural and wild areas, is quite limited. In this study, we developed a portable whole-plant on-device phenotyping smartphone application running on Android that can measure up to 45 traits, including 15 plant traits, 25 leaf traits and 5 stem traits, based on images. To avoid the influence of outdoor environments, we trained a DeepLabV3+ model for segmentation. In addition, an angle calibration algorithm was also designed to reduce the error introduced by the different imaging angles. The average execution time for the analysis of a 20-million-pixel image is within 2,500 ms. The application is a portable on-device fast phenotyping platform providing methods for real-time trait measurement, which will facilitate maize phenotyping in field and benefit crop breeding in future.

Affect recognition from facial movements and body gestures by hierarchical deep spatio-temporal features and fusion strategy.

Affect presentation is periodic and multi-modal, such as through facial movements, body gestures, and so on. Studies have shown that temporal selection and multi-modal combinations may benefit affect recognition. In this article, we therefore propose a spatio-temporal fusion model that extracts spatio-temporal hierarchical features based on select expressive components. In addition, a multi-modal hierarchical fusion strategy is presented. Our model learns the spatio-temporal hierarchical features from videos by a proposed deep network, which combines a convolutional neural networks (CNN), bilateral long short-term memory recurrent neural networks (BLSTM-RNN) with principal component analysis (PCA). Our approach handles each video as a "video sentence." It first obtains a skeleton with the temporal selection process and then segments key words with a certain sliding window. Finally, it obtains the features with a deep network comprised of a video-skeleton and video-words. Our model combines the feature level and decision level fusion for fusing the multi-modal information. Experimental results showed that our model improved the multi-modal affect recognition accuracy rate from 95.13% in existing literature to 99.57% on a face and body (FABO) database, our results have been increased by 4.44%, and it obtained a macro average accuracy (MAA) up to 99.71%.

Development of Enteromorpha prolifera polysaccharide-based nanoparticles for delivery of curcumin to cancer cells.

Polyelectrolyte complex nanoparticles were fabricated via electrostatic complexation between Enteromorpha prolifera polysaccharide (EP) and chitosan (CS). The monodisperse EP/CS NPs with negatively charge were prepared at pH4.0 and mixing ratio of 3.0:1.0. Curcumin loaded nanoparticles (CUR-NPs) showed spherical morphology with negatively charge of -16.27±0.97mV and average diameter range of 230 to 330nm. The results of spectroscopic analysis, XRD and DSC confirmed that there were hydrogen-bonding interaction and hydrophobic interaction between curcumin and EP/CS NPs. The CUR-NPs improved storage, thermal and photo stability of curcumin and exhibited sustained release of curcumin in vitro. Moreover, the CUR-NPs showed higher cellular uptake than free CUR with incubation for 3h by CLSM visualization and fluorescence quantitative assay. Furthermore, MTT assay results demonstrated that the CUR-NPs possessed good anticancer activity against B16F10 cells. Therefore, the EP-based nanoparticles are promising candidates for carriers in controllable hydrophobic anti-tumor drug delivery.

Sulfated modification, characterization, and antioxidant and moisture absorption/retention activities of a soluble neutral polysaccharide from Enteromorpha prolifera.

A purified polysaccharide from Enteromorpha prolifera (PEP) with a molecular mass of 147.8kDa, was prepared by hot-water extraction method and purified by anion-exchange chromatography and gel filtration chromatography. Low Mw polysaccharide of E. prolifera (LEP, 44.8kDa) was obtained by enzymatic degradation. Sulfated derivatives of the two different Mw polysaccharides were synthesized by chlorosulfonic acid/pyridine method, and the degrees of substitution of SPEP and SLEP were 0.57 and 0.81, respectively. Physicochemical properties and FT-IR spectra showed that enzymatic degradation and sulfated modification of polysaccharides were successful. 13C NMR analysis showed that the sulfate groups mainly attached to C-6 of rhamnose. Moreover, the study revealed that enzymatic degradation and sulfated modification of polysaccharides improved significantly superoxide, hydroxyl and DPPH radicals scavenging activities in vitro, and enhanced obviously moisture absorption/retention capacities. Therefore, these results demonstrated that molecular weight and sulfate groups had obvious effects on antioxidant activities and moisture absorption/retention abilities of the polysaccharides from E. prolifera.

A high-throughput stereo-imaging system for quantifying rape leaf traits during the seedling stage.

BACKGROUND: The fitness of the rape leaf is closely related to its biomass and photosynthesis. The study of leaf traits is significant for improving rape leaf production and optimizing crop management. Canopy structure and individual leaf traits are the major indicators of quality during the rape seedling stage. Differences in canopy structure reflect the influence of environmental factors such as water, sunlight and nutrient supply. The traits of individual rape leaves traits indicate the growth period of the rape as well as its canopy shape. RESULTS: We established a high-throughput stereo-imaging system for the reconstruction of the three-dimensional canopy structure of rape seedlings from which leaf area and plant height can be extracted. To evaluate the measurement accuracy of leaf area and plant height, 66 rape seedlings were randomly selected for automatic and destructive measurements. Compared with the manual measurements, the mean absolute percentage error of automatic leaf area and plant height measurements was 3.68 and 6.18%, respectively, and the squares of the correlation coefficients (R2) were 0.984 and 0.845, respectively. Compared with the two-dimensional projective imaging method, the leaf area extracted using stereo-imaging was more accurate. In addition, a semi-automatic image analysis pipeline was developed to extract 19 individual leaf shape traits, including 11 scale-invariant traits, 3 inner cavity related traits, and 5 margin-related traits, from the images acquired by the stereo-imaging system. We used these quantified traits to classify rapes according to three different leaf shapes: mosaic-leaf, semi-mosaic-leaf, and round-leaf. Based on testing of 801 seedling rape samples, we found that the leave-one-out cross validation classification accuracy was 94.4, 95.6, and 94.8% for stepwise discriminant analysis, the support vector machine method and the random forest method, respectively. CONCLUSIONS: In this study, a nondestructive and high-throughput stereo-imaging system was developed to quantify canopy three-dimensional structure and individual leaf shape traits with improved accuracy, with implications for rape phenotyping, functional genomics, and breeding.

Isolation, Characterization and Evaluation of Collagen from Jellyfish Rhopilema esculentum Kishinouye for Use in Hemostatic Applications.

Hemostat has been a crucial focus since human body is unable to control massive blood loss, and collagen proves to be an effective hemostat in previous studies. In this study, collagen was isolated from the mesoglea of jellyfish Rhopilema esculentum Kishinouye and its hemostatic property was studied. The yields of acid-soluble collagen (ASC) and pepsin-soluble (PSC) were 0.12% and 0.28% respectively. The SDS-PAGE patterns indicated that the collagen extracted from jellyfish mesoglea was type I collagen. The lyophilized jellyfish collagen sponges were cross-linked with EDC and interconnected networks in the sponges were revealed by scanning electron microscope (SEM). Collagen sponges exhibited higher water absorption rates than medical gauze and EDC/NHS cross-linking method could improve the stability of the collagen sponges. Compared with medical gauze groups, the blood clotting indexes (BCIs) of collagen sponges were significantly decreased (P < 0.05) and the concentration of collagen also had an influence on the hemostatic property (P < 0.05). Collagen sponges had an improved hemostatic ability compared to the gauze control in tail amputation rat models. Hemostatic mechanism studies showed that hemocytes and platelets could adhere and aggregate on the surface of collagen sponge. All properties make jellyfish collagen sponge to be a suitable candidate used as hemostatic material and for wound healing applications.

Nanoparticles based on phenylalanine ethyl ester-alginate conjugate as vitamin B2 delivery system.

Phenylalanine ethyl ester (PAE)-alginate (Alg) conjugate (PAE-Alg, PEA) was synthesized and formation of an amide bond between PAE and Alg was confirmed by Fourier transformed-infrared and (1)H nuclear magnetic resonance spectroscopy. The degree of PAE substitution was 3.5-4.7 (PAE group per hundred sugar residues of Alg) which was determined by elemental analysis. The critical aggregation concentration values determined for PEA conjugates PEA1, PEA2, and PEA3 were 0.20, 0.12, and 0.10 mg/ml, respectively. The particle size of PEA nanoparticles (PEA-NPs) decreased from 425 nm to 226 nm with the increasing degree of PAE substitution. Vitamin B2 (VB2), as a model nutrient, was encapsulated into the nanoparticles. The drug-loading content increased with increasing degree of PAE substitution. The maximum VB2 loading capacity and loading efficiency of PEA3 nanoparticles were 3.53 ± 0.03% and 91.48 ± 0.80%, respectively. The in vitro release behavior of VB2 from the PEA-NPs showed a biphasic release profile with an initial burst release of about 40-50% of VB2 in the first 10 h followed by a steady and continuous release phase for the following 50 h in PBS, pH 7.4. The human colorectal carcinoma cell line was used to investigate the cytotoxicity of PEA-NPs. Our results showed that various concentrations of nanoparticles did not cause significant cytotoxicity against cell lines at normal concentrations.

[Low-grade fibromyxoid sarcoma: a clinicopathological analysis of 9 cases].

OBJECTIVE: To study the clinicopathological features, immnophenotype and differential diagnosis of low-grade fibromyxoid sarcoma (LGFMS). METHODS: The clinical, radiological and pathological features of 9 cases of LGFMS were reviewed. RESULTS: The patients consisted of six males and three females with ages ranging from 11 to 65 years (mean 31.4 years). Clinically, most cases presented as slowly growing painless masses located in the extremities, trunk and neck. Two cases had a history of a rapid recent enlargement. Three cases presented with recurrent diseases after incomplete resection. Ultrasound showed heterogeneous signal. Precontrast CT and T1-weighted MRI showed a nodular mass of low to isodensity, while contrast-enhanced CT and T2-weighted MRI demonstrated contrasting zonal areas of hypo/hyperintensity. The tumors measured 3 to 16 cm (mean 7.7 cm), with a fibrous to myxoid appearance on cut surface. Histologically, they were composed of alternating collagenous and myxoid areas. A transition between the two areas could be identified. Giant rosette-like structures were observed in 3 cases. The center of the giant rosettes was composed of eosinophilic collagen, which showed centrifugal in arrangement. There was also gradual transition between the giant rosettes and the fibromyxoid component. On high magnification, the tumor was composed of ovoid to spindle-shaped cells with hyperchromatic nuclei. Nuclear atypia was inconspicuous. The tumor cells were arranged mostly in interlacing fascicles or whorls. Vessels were not prominent and necrosis was absent. Immunohistochemically, the tumor cells showed unique staining for vimentin, consistent with a fibroblastic differentiation. CONCLUSIONS: LGFMS is a distinctive low grade fibroblastic sarcoma of young adults. Recognizing the characteristics of the rare entity may help to avoid misdiagnosis. Wide local excision is recommended to avoid local recurrences.