Comparison of cold resistance physiological and biochemical features of four Herba Rhodiola seedlings under low temperature

AbstractTo discuss the cold resistance performance of different Herba Rhodiolae and successfully transplant Herba Rhodiolae to the Gansu plateau area for nursing, domestication and planting, this paper systematically studies six physiological and biochemical features of Rhodiola kirilowii, Rhodiola algida, Rhodiola crenulata and Herba Rhodiolae that are closely associated with cold resistance features and concludes with the cold resistance capability of Rhodiola kirilowii. In the selected six main indexes of the Herba Rhodiolae, the POD, SOD and CAT activity and MDA and Pro content in the leaf are the main physiological and biochemical indexes to indicate the cold resistance performance of four Herba Rhodiolae seedlings and can be regarded as the preliminary indexes to assess the winter performance of Herba Rhodiolae. The research work will provide the theoretical basis for the wild variants of Herba Rhodiolae and GAPJ base construction

Terpenoids and other secondary metabolites produced by the Eutypella fungi and their bioactivities

The fungi Eutypella could metabolize a myriad of natural products with unique structures and diverse bioactivities, which were deemed as key sources for lead compounds in drug discovery. Since the first research on the genus Eutypella in 2009, a myriad of secondary metabolites including terpenoids, alkaloids, and polyketides have been discovered in this genus, and most of them exhibited significant pharmacological activities. However, there are no systematic reviews that reported about the structures and bioactivities of Eutypella up to now. In this review, a total of 153 secondary metabolites and 42 references have been systematically summarized, and we found that the terpenoids (68.09%) and alkaloids (19.15%) were the new main components of this fungi, and the primary antiproliferative activity (64.89%) was mainly derived from the terpenoids and alkaloids. Thus, this review about the chemical diversity and biological activities of the metabolites from the fungus Eutypella provided a new perspective for the development of new drugs for pharmacologists

Identification and analysis of the secretome of plant pathogenic fungi reveals lifestyle adaptation

The secretory proteome plays an important role in the pathogenesis of phytopathogenic fungi. However, the relationship between the large-scale secretome of phytopathogenic fungi and their lifestyle is not fully understood. In the present study, the secretomes of 150 plant pathogenic fungi were predicted and the characteristics associated with different lifestyles were investigated. In total, 94,974 secreted proteins (SPs) were predicted from these fungi. The number of the SPs ranged from 64 to 1,662. Among these fungi, hemibiotrophic fungi had the highest number (average of 970) and proportion (7.1%) of SPs. Functional annotation showed that hemibiotrophic and necrotroph fungi, differ from biotrophic and symbiotic fungi, contained much more carbohydrate enzymes, especially polysaccharide lyases and carbohydrate esterases. Furthermore, the core and lifestyle-specific SPs orthogroups were identified. Twenty-seven core orthogroups contained 16% of the total SPs and their motif function annotation was represented by serine carboxypeptidase, carboxylesterase and asparaginase. In contrast, 97 lifestyle-specific orthogroups contained only 1% of the total SPs, with diverse functions such as PAN_AP in hemibiotroph-specific and flavin monooxygenases in necrotroph-specific. Moreover, obligate biotrophic fungi had the largest number of effectors (average of 150), followed by hemibiotrophic fungi (average of 120). Among these effectors, 4,155 had known functional annotation and pectin lyase had the highest proportion in the functionally annotated effectors. In addition, 32 sets of RNA-Seq data on pathogen-host interactions were collected and the expression levels of SPs were higher than that of non-SPs, and the expression level of effector genes was higher in biotrophic and hemibiotrophic fungi than in necrotrophic fungi, while secretase genes were highly expressed in necrotrophic fungi. Finally, the secretory activity of five predicted SPs from Setosphearia turcica was experimentally verified. In conclusion, our results provide a foundation for the study of pathogen-host interaction and help us to understand the fungal lifestyle adaptation

SCULPTOR: Skeleton-Consistent Face Creation Using a Learned Parametric Generator

Recent years have seen growing interest in 3D human faces modelling due to its wide applications in digital human, character generation and animation. Existing approaches overwhelmingly emphasized on modeling the exterior shapes, textures and skin properties of faces, ignoring the inherent correlation between inner skeletal structures and appearance. In this paper, we present SCULPTOR, 3D face creations with Skeleton Consistency Using a Learned Parametric facial generaTOR, aiming to facilitate easy creation of both anatomically correct and visually convincing face models via a hybrid parametric-physical representation. At the core of SCULPTOR is LUCY, the first large-scale shape-skeleton face dataset in collaboration with plastic surgeons. Named after the fossils of one of the oldest known human ancestors, our LUCY dataset contains high-quality Computed Tomography (CT) scans of the complete human head before and after orthognathic surgeries, critical for evaluating surgery results. LUCY consists of 144 scans of 72 subjects (31 male and 41 female) where each subject has two CT scans taken pre- and post-orthognathic operations. Based on our LUCY dataset, we learn a novel skeleton consistent parametric facial generator, SCULPTOR, which can create the unique and nuanced facial features that help define a character and at the same time maintain physiological soundness. Our SCULPTOR jointly models the skull, face geometry and face appearance under a unified data-driven framework, by separating the depiction of a 3D face into shape blend shape, pose blend shape and facial expression blend shape. SCULPTOR preserves both anatomic correctness and visual realism in facial generation tasks compared with existing methods. Finally, we showcase the robustness and effectiveness of SCULPTOR in various fancy applications unseen before.Comment: 16 page, 13 fig

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data

Motivation Single-cell multimodal assays allow us to simultaneously measure two different molecular features of the same cell, enabling new insights into cellular heterogeneity, cell development and diseases. However, most existing methods suffer from inaccurate dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare cell subpopulations. Results Here, we present VIMCCA, a computational framework based on variational-assisted multi-view canonical correlation analysis to integrate paired multimodal single-cell data. Our statistical model uses a common latent variable to interpret the common source of variances in two different data modalities. Our approach jointly learns an inference model and two modality-specific non-linear models by leveraging variational inference and deep learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA facilitates integrating various types of joint-modality data, thus leading to more reliable and accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage based on joint-modality profiles

Analysis and Radiometric Calibration for Backscatter Intensity of Hyperspectral LiDAR Caused by Incident Angle Effect

Hyperspectral LiDAR (HSL) is a new remote sensing detection method with high spatial and spectral information detection ability. In the process of laser scanning, the laser echo intensity is affected by many factors. Therefore, it is necessary to calibrate the backscatter intensity data of HSL. Laser incidence angle is one of the important factors that affect the backscatter intensity of the target. This paper studied the radiometric calibration method of incidence angle effect for HSL. The reflectance of natural surfaces can be simulated as a combination of specular reflection and diffuse reflection. The linear combination of the Lambertian model and Beckmann model provides a comprehensive theory that can be applied to various surface conditions, from glossy to rough surfaces. Therefore, an adaptive threshold radiometric calibration method (Lambertian-Beckmann model) is proposed to solve the problem caused by the incident angle effect. The relationship between backscatter intensity and incident angle of HSL is studied by combining theory with experiments, and the model successfully quantifies the difference between diffuse and specular reflectance coefficients. Compared with the Lambertian model, the proposed model has higher calibration accuracy, and the average improvement rate to the samples in this study was 22.67%. Compared with the results before calibration with the incidence angle of less than 70 degrees, the average improvement rate of the Lambertian-Beckmann model was 62.26%. Moreover, we also found that the green leaves have an obvious specular reflection effect near 650-720 nm, which might be related to the inner microstructure of chlorophyll. The Lambertian-Beckmann model was more helpful to the calibration of leaves in the visible wavelength range. This is a meaningful and a breakthrough exploration for HSL.Peer reviewe

Impact of a Fermented High-Fiber Rye Diet on Helicobacter pylori and Cardio-Metabolic Risk Factors: A Randomized Controlled Trial Among Helicobacter pylori-Positive Chinese Adults

Background: High dietary fiber intake has been associated with reduced risk of Helicobacter pylori infection and co-morbidities such as gastric cancer but also with reduced risk of cardiovascular disease. It has been suggested that fermented rye could affect Helicobacter pylori bacterial load and that high- fiber rye may be superior to wheat for improvement of several cardiometabolic risk factors, but few long-term interventions with high fiber rye foods have been conducted.Objective: To examine the effect of high-fiber wholegrain rye foods with added fermented rye bran vs. refined wheat on Helicobacter pylori infection and cardiometabolic risk markers in a Chinese population with a low habitual consumption of high fiber cereal foods.Design: A parallel dietary intervention was set up and 182 normal- or overweight men and women were randomized to consume wholegrain rye products containing fermented rye bran (FRB) or refined wheat (RW) for 12 weeks. Anthropometric measurements, fasting blood sample collection and C-13-urea breath test (C-13-UBT) were performed at baseline and after 6 and 12 weeks of intervention as well as 12 weeks after the end of the intervention.Results: No difference between diets on Helicobacter pylori bacterial load measured by C-13-UBT breath test or in virulence factors of Helicobacter pylori in blood samples were found. Low density lipoprotein cholesterol (LDL-C) and high sensitivity C-reactive protein (hs-CRP) were significantly lower in the FRB group, compared to the RW group after 12 weeks of intervention. The intervention diets did not affect markers of glucose metabolism or insulin sensitivity.Conclusions: While the results of the present study did not support any effect of FRB on Helicobacter pylori bacterial load, beneficial effects on LDL-C and hs-CRP were clearly shown. This suggest that consumption of high fiber rye foods instead of refined wheat could be one strategy for primary prevention of cardiovascular disease