Interplay between Amaryllidaceae alkaloids, the bacteriome and phytopathogens in Lycoris radiata.

Alkaloids are a large group of plant secondary metabolites with various structures and activities. It is important to understand their functions in the interplay between plants and the beneficial and pathogenic microbiota. Amaryllidaceae alkaloids (AAs) are unique secondary metabolites in Amaryllidaceae plants. Here, we studied the interplay between AAs and the bacteriome in Lycoris radiata, a traditional Chinese medicinal plant containing high amounts of AAs. The relationship between AAs and bacterial composition in different tissues of L. radiata was studied. In vitro experiments revealed that AAs have varying levels of antimicrobial activity against endophytic bacteria and pathogenic fungi, indicating the importance of AA synthesis in maintaining a balance between plants and beneficial/pathogenic microbiota. Using bacterial synthetic communities with different compositions, we observed a positive feedback loop between bacteria insensitive to AAs and their ability to increase accumulation of AAs in L. radiata, especially in leaves. This may allow insensitive bacteria to outcompete sensitive ones for plant resources. Moreover, the accumulation of AAs enhanced by insensitive bacteria could benefit plants when challenged with fungal pathogens. This study highlights the functions of alkaloids in plant-microbe interactions, opening new avenues for designing plant microbiomes that could contribute to sustainable agriculture.

Localisation of the centre of the highest region of muscle spindle abundance of anterior forearm muscles.

The centre of the highest region of muscle spindle abundance (CHRMSA) in the intramuscular nerve-dense region has been suggested as the optimal target location for injecting botulinum toxin A to block muscle spasms. The anterior forearm muscles have a high incidence of spasticity. However, the CHRMSA in the intramuscular nerve-dense region of the forearm anterior muscle group has not been defined. This study aimed to accurately define the body surface position and the depth of CHRMSA in an intramuscular nerve-dense region of the anterior forearm muscles. Twenty-four adult cadavers (57.7 ± 11.5 years) were included in this study. The curved line close to the skin connecting the medial and lateral epicondyles of the humerus was designated as the horizontal reference line (H line), and the line connecting the medial epicondyle of the humerus and the ulnar styloid was defined as the longitudinal reference line (L line). Modified Sihler's staining, haematoxylin-eosin staining and computed tomography scanning were employed to determine the projection points (P and P') of the CHRMSAs on the anterior and posterior surfaces of the forearm. The positions (PH and PL) of point P projected onto the H and L lines, and the depth of each CHRMSA, were determined using the Syngo system. The PH of the CHRMSA of the ulnar head of pronator teres, humeral head of pronator teres, flexor carpi radialis, palmaris longus, flexor carpi ulnaris, ulnar part of flexor digitorum superficialis, radial part of flexor digitorum superficialis, flexor pollicis longus, ulnar part of flexor digitorum profundus, radial portion of flexor digitorum profundus and pronator quadratus muscles were located at 42.48%, 45.52%, 41.20%, 19.70%, 7.77%, 25.65%, 47.42%, 53.47%, 12.28%, 38.41% and 51.68% of the H line, respectively; the PL were located at 18.38%, 12.54%, 28.83%, 13.43%, 17.65%, 32.76%, 57.32%, 64.12%, 20.05%, 45.94% and 88.71% of the L line, respectively; the puncture depths were located at 21.92%, 27.25%, 23.76%, 18.04%, 15.49%, 31.36%, 26.59%, 41.28%, 38.72%, 45.14% and 53.58% of the PP' line, respectively. The percentage values are the means of individual values. We recommend that the body surface puncture position and depth of the CHRMSA are the preferred locations for the intramuscular injection of botulinum toxin A to block anterior forearm muscle spasms.

Root endophyte-mediated alteration in plant H2O2 homeostasis regulates symbiosis outcome and reshapes the rhizosphere microbiota.

Endophytic symbioses between plants and fungi are a dominant feature of many terrestrial ecosystems, yet little is known about the signaling that defines these symbiotic associations. Hydrogen peroxide (H2O2) is recognized as a key signal mediating the plant adaptive response to both biotic and abiotic stresses. However, the role of H2O2 in plant-fungal symbiosis remains elusive. Using a combination of physiological analysis, plant and fungal deletion mutants, and comparative transcriptomics, we reported that various environmental conditions differentially affect the interaction between Arabidopsis and the root endophyte Phomopsis liquidambaris, and link this process to alterations in H2O2 levels and H2O2 fluxes across root tips. We found that enhanced H2O2 efflux leading to a moderate increase in H2O2 levels at the plant-fungal interface is required for maintaining plant-fungal symbiosis. Disturbance of plant H2O2 homeostasis compromises the symbiotic ability of plant roots. Moreover, the fungus-regulated H2O2 dynamics modulate the rhizosphere microbiome by selectively enriching for the phylum Cyanobacteria, with strong antioxidant defenses. Our results demonstrated that the regulation of H2O2 dynamics at the plant-fungal interface affects the symbiotic outcome in response to external conditions and highlight the importance of the root endophyte in reshaping the rhizosphere microbiota.

Expression Patterns and Molecular Mechanisms Regulating Drought Tolerance of Soybean [Glycine max (L.) Merr.] Conferred by Transcription Factor Gene GmNAC19.

NAC transcription factors are commonly involved in the plant response to drought stress. A transcriptome analysis of root samples of the soybean variety 'Jiyu47' under drought stress revealed the evidently up-regulated expression of GmNAC19, consistent with the expression pattern revealed by quantitative real-time PCR analysis. The overexpression of GmNAC19 enhanced drought tolerance in Saccharomyces cerevisiae INVSc1. The seed germination percentage and root growth of transgenic Arabidopsis thaliana were improved in comparison with those of the wild type, while the transgenic soybean composite line showed improved chlorophyll content. The altered contents of physiological and biochemical indices (i.e., soluble protein, soluble sugar, proline, and malondialdehyde) related to drought stress and the activities of three antioxidant enzymes (i.e., superoxide dismutase, peroxidase, and catalase) revealed enhanced drought tolerance in both transgenic Arabidopsis and soybean. The expressions of three genes (i.e., P5CS, OAT, and P5CR) involved in proline synthesis were decreased in the transgenic soybean hairy roots, while the expression of ProDH involved in the breakdown of proline was increased. This study revealed the molecular mechanisms underlying drought tolerance enhanced by GmNAC19 via regulation of the contents of soluble protein and soluble sugar and the activities of antioxidant enzymes, providing a candidate gene for the molecular breeding of drought-tolerant crop plants.

The ratio but not individual of fragile to refractory DOM affects greenhouse gases release in different trophic level lakes.

Inland shallow lakes are recognized as an important source of greenhouse gases (GHGs), and their contribution is expected to increase due to global eutrophication. The generation and release of GHGs involved multiple variables, leading to many uncertain potential factors. This study examined the emission characteristics of GHGs at the water-air interface in 12 shallow lakes categorized into four eutrophic levels in the Yangtze River basin. The average emission rates of CH4, CO2 and N2O were 1.55, 3.43, 18.13 and 30.47 mg m-2 h-1, 4.12, 14.64, 25.11 and 69.84 mg m-2 h-1, and 0.2, 0.25, 0.43 and 0.79 mg m-2 day-1 in the oligotrophic, mesotrophic, eutrophic and hypereutrophic lakes, respectively. There were significant correlations between eutrophic levels and the emission rates of CH4 and CO2 (p < 0.05). Redundancy analysis and Mantel test were conducted to further examine the key factors influencing carbon emissions from eutrophic water. It was found that the presence of algae and nutrients in the overlying water played a crucial role in the release of GHGs, indicating the importance of ecosystem productivity in the carbon budget of the lake. In order to assess the bioavailability of organic matter, a new indicator called R(P/H) was proposed. This indicator represents the ratio of protein and humus-like components, which were obtained through EEMs-PARAFAC modeling. The relationship between R(P/H) and CH4 was found to be exponential (R2 = 0.90). Additionally, R(P/H) showed a linear relationship with CO2 and N2O (R2 = 0.68, R2 = 0.75). Therefore, it is crucial to consider R(P/H) as an important factor in accurately estimating global GHG emission fluxes in the future, especially with advancements in the database.

Tumor residue in patients with stage II-IVA nasopharyngeal carcinoma who received intensity-modulated radiation therapy: development and validation of a prediction nomogram integrating postradiotherapy plasma Epstein-Barr virus deoxyribonucleic acid, clinical stage, and radiotherapy dose.

BACKGROUND: To develop and validate a predictive nomogram for tumor residue 3-6 months after treatment based on postradiotherapy plasma Epstein-Barr virus (EBV) deoxyribonucleic acid (DNA), clinical stage, and radiotherapy (RT) dose in patients with stage II-IVA nasopharyngeal carcinoma (NPC) treated with intensity-modulated radiation therapy (IMRT). METHODS: In this retrospective study, 1050 eligible patients with stage II-IVA NPC, who completed curative IMRT and underwent pretreatment and postradiotherapy (-7 to +28 days after IMRT) EBV DNA testing, were enrolled from 2012 to 2017. The prognostic value of the residue was explored using Cox regression analysis in patients (n=1050). A nomogram for predicting tumor residues after 3-6 months was developed using logistic regression analyses in the development cohort (n=736) and validated in an internal cohort (n=314). RESULTS: Tumor residue was an independent inferior prognostic factor for 5-year overall survival, progression-free survival, locoregional recurrence-free survival and distant metastasis-free survival (all P<0.001). A prediction nomogram based on postradiotherapy plasma EBV DNA level (0 vs. 1-499 vs. ≥500 copies/ml), clinical stage (II vs. III vs. IVA), and RT dose (68.00-69.96 vs. 70.00-74.00 Gy) estimated the probability of residue development. The nomogram showed better discrimination (area under the curve (AUC): 0.752) than either the clinical stage (0.659) or postradiotherapy EBV DNA level (0.627) alone in the development and validation cohorts (AUC: 0.728). CONCLUSIONS: We developed and validated a nomogram model integrating clinical characteristics at the end of IMRT for predicting whether tumor will residue or not after 3-6 months. Thus, high-risk NPC patients who might benefit from immediate additional intervention could be identified by the model, and the probability of residue can be reduced in the future.

Widely targeted quantitative lipidomics and prognostic model reveal plasma lipid predictors for nasopharyngeal carcinoma.

BACKGROUND: Dysregulation of lipid metabolism is closely associated with cancer progression. The study aimed to establish a prognostic model to predict distant metastasis-free survival (DMFS) in patients with nasopharyngeal carcinoma (NPC), based on lipidomics. METHODS: The plasma lipid profiles of 179 patients with locoregionally advanced NPC (LANPC) were measured and quantified using widely targeted quantitative lipidomics. Then, patients were randomly split into the training (125 patients, 69.8%) and validation (54 patients, 30.2%) sets. To identify distant metastasis-associated lipids, univariate Cox regression was applied to the training set (P < 0.05). A deep survival method called DeepSurv was employed to develop a proposed model based on significant lipid species (P < 0.01) and clinical biomarkers to predict DMFS. Concordance index and receiver operating curve analyses were performed to assess model effectiveness. The study also explored the potential role of lipid alterations in the prognosis of NPC. RESULTS: Forty lipids were recognized as distant metastasis-associated (P < 0.05) by univariate Cox regression. The concordance indices of the proposed model were 0.764 (95% confidence interval (CI), 0.682-0.846) and 0.760 (95% CI, 0.649-0.871) in the training and validation sets, respectively. High-risk patients had poorer 5-year DMFS compared with low-risk patients (Hazard ratio, 26.18; 95% CI, 3.52-194.80; P < 0.0001). Moreover, the six lipids were significantly correlated with immunity- and inflammation-associated biomarkers and were mainly enriched in metabolic pathways. CONCLUSIONS: Widely targeted quantitative lipidomics reveals plasma lipid predictors for LANPC, the prognostic model based on that demonstrated superior performance in predicting metastasis in LANPC patients.

A method of motion estimation of segmental ventricular wall with tracking of ultrasonic echocardiogram.

BACKGROUND: Ultrasonic echocardiography is commonly used for monitoring myocardial dysfunction. However, it has limitations such as poor quality of echocardiography images and subjective judgment of doctors. METHODS: In this paper, a calculation model based on optical flow tracking of echocardiogram is proposed for the quantitative estimation motion of the segmental wall. To improve the accuracy of optical flow estimation, a method based on confidence-optimized multiresolution(COM) optical flow model is proposed to reduce the estimation errors caused by the large amplitude of myocardial motion and the presence of "shadows" and other image quality problems. In addition, motion vector decomposition and dynamic tracking of the ventricular region of interest are used to extract information regarding the myocardial segmental motion. The proposed method was validated using simulation images and 50 clinical cases (25 patients and 25 healthy volunteers) for myocardial motion analysis. RESULTS: The results demonstrated that the proposed method could track the motion information of myocardial segments well and reduce the estimation errors of optical flow caused due to the use of low-quality echocardiogram images. CONCLUSIONS: The proposed method improves the accuracy of motion estimation for the cardiac ventricular wall.

Correlations Among Clinical Phenotypes, Radiological Examination Indexes, and Hearing Status in Congenital Microtia.

Microtia is a congenital malformation of the external ear that often presents with other anatomical abnormalities and ipsilateral hearing loss (HL). The aim of this study was to present the correlation among important phenotypic abnormalities in microtia and their relationship with HL in a clinical population in China. In this study, a retrospective analysis was conducted on 307 patients diagnosed with microtia who visited the Department of Auricular Reconstruction of the Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, for surgical auricle reconstruction from April 2021 to April 2022. Standardized classification of ear malformations, craniofacial CT scans, and pure tone audiometric data were collected, and statistical analyses were performed using the rank sum test, Kruskal-Wallis test, and Spearman's rank correlation coefficient. The results showed that group differences between ear malformation and variations in the development of mandible, external auditory canal (EAC), and mastoid pneumatization were statistically significant and each had a positive correlation. Among them, the correlation between development of ear and EAC was the most significant (Ρ=0.72). Besides, the severity of HL (97% were conductive) was positively correlated with ear and EAC dysplasia with or without mandibular hypoplasia. Based on the statistical analysis of the correlation between ear malformation and HL, the authors strongly recommend that facial phenotype reconstruction and hearing improvement of microtia should be considered comprehensively, regardless of whether children with microtia show HL or not, early diagnosis of audiology evaluation and appropriate intervention measures should be implemented.

Integrated strategies for chemotherapy cycles in nasopharyngeal carcinoma patients: Real-world data from two epidemic centers guiding decision-making.

Objective: Two cycles of induction chemotherapy (IC) followed by 2 cycles of platinum-based concurrent chemoradiotherapy (CCRT) (2IC+2CCRT) for locoregionally advanced nasopharyngeal carcinoma (LA-NPC) is widely adopted but not evidence-confirmed. This study aimed to determine the clinical value of 2IC+2CCRT regarding efficacy, toxicity and cost-effectiveness. Methods: This real-world study from two epidemic centers used propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. The enrolled patients were divided into three groups based on treatment modality: Group A (2IC+2CCRT), Group B (3IC+2CCRT or 2IC+3CCRT) and Group C (3IC+3CCRT). Long-term survival, acute toxicities and cost-effectiveness were compared among the groups. We developed a prognostic model dividing the population into high- and low-risk cohorts, and survivals including overall survival (OS), progression-free survival (PFS), distant metastasis-free survival (DMFS) and locoregional relapse-free survival (LRRFS) were compared among the three groups according to certain risk stratifications. Results: Of 4,042 patients, 1,175 were enrolled, with 660, 419, and 96 included in Groups A, B and C, respectively. Five-year survivals were similar among the three groups after PSM and confirmed by IPTW. Grade 3-4 neutropenia and leukocytopenia were significantly higher in Groups C and B than in Group A (52.1% vs. 41.5% vs. 25.2%; 41.7% vs. 32.7% vs. 25.0%) as were grade 3-4 nausea/vomiting and oral mucositis (29.2% vs. 15.0% vs. 6.1%; 32.3% vs. 25.3% vs. 18.0%). Cost-effective analysis suggested that 2IC+2CCRT was the least expensive, while the health benefits were similar to those of the other groups. Further exploration showed that 2IC+2CCRT tended to be associated with a shorter PFS in high-risk patients, while 3IC+3CCRT potentially contributed to poor PFS in low-risk individuals, mainly reflected by LRRFS. Conclusions: In LA-NPC patients, 2IC+2CCRT was the optimal choice regarding efficacy, toxicity and cost-effectiveness; however, 2IC+2CCRT and 3IC+3CCRT probably shortened LRRFS in high- and low-risk populations, respectively.

Graph convolutional networks for computational drug development and discovery.

Despite the fact that deep learning has achieved remarkable success in various domains over the past decade, its application in molecular informatics and drug discovery is still limited. Recent advances in adapting deep architectures to structured data have opened a new paradigm for pharmaceutical research. In this survey, we provide a systematic review on the emerging field of graph convolutional networks and their applications in drug discovery and molecular informatics. Typically we are interested in why and how graph convolution networks can help in drug-related tasks. We elaborate the existing applications through four perspectives: molecular property and activity prediction, interaction prediction, synthesis prediction and de novo drug design. We briefly introduce the theoretical foundations behind graph convolutional networks and illustrate various architectures based on different formulations. Then we summarize the representative applications in drug-related problems. We also discuss the current challenges and future possibilities of applying graph convolutional networks to drug discovery.

Root endophyte differentially regulates plant response to NO3- and NH4+ nutrition by modulating N fluxes at the plant-fungal interface.

In the soil, plant roots associated with fungi often encounter uneven distribution of nitrate (NO3- )/ammonium (NH4+ ) patches, but the mechanism underlying N form-influenced plant-fungal interactions remains limited. We inoculated Arabidopsis with a root endophyte Phomopsis liquidambaris, and evaluated the effects of P. liquidambaris on plant performance under NO3- or NH4+ nutrition. Under NO3- nutrition, P. liquidambaris inoculation promoted seedling growth, whereas under NH4+ nutrition, P. liquidambaris suppressed seedling growth. Under high NH4+ conditions, fungus-colonized roots displayed increased NH4+ accumulation and NH4+ efflux, similar to the effect of ammonium stress caused by elevated NH4+ levels. Notably, this fungus excluded NH4+ during interactions with host roots, thereby leading to increased NH4+ levels at the plant-fungal interface under high NH4+ conditions. A nitrite reductase-deficient strain that excludes NO3- but absorbs NH4+ , decreased NH4+ levels in Arabidopsis shoots and rescued plant growth and nitrogen metabolism under high NH4+ levels. Transcriptomic analysis highlighted that P. liquidambaris had altered transcriptional responses associated with plant response to inorganic N forms. Our results demonstrate that fungus-regulated NO3- /NH4+ dynamics at the plant-fungal interface alters plant response to NO3- /NH4+ nutrition. This study highlights the essential functions of root endophytes in plant adaptation to soil nitrogen nutrients.

Synthesis of Well-Ordered Mesoporous Aluminosilicates with High Aluminum Contents: The Challenge and the Promise.

SBA-15 has recently emerged as a potential material for the catalytic conversion of large molecules. Usually, SBA-15 has a low content of aluminum due to the conventional acidic synthesis medium. Although a few approaches have been adopted to prepare Al-SBA-15 with a high alumina content, it is still challenging to prepare well-ordered Al-SBA-15 with a high alumina content. Here, we demonstrate a facile synthesis process in neutral mediums for the grafting of Al into the framework of SBA-15. This approach relies mainly on the dissociation of Si-O-Si bonds and the polymerization of Si-O-Si/Al bonds promoted by sodium persulfate (SPS) in neutral mediums. In this way, well-ordered Al-SBA-15 with a high aluminum content and enhanced acidity was obtained. Results of X-ray fluorescence spectroscopy (XRF) showed an n(SiO2)/n(Al2O3) ratio of 13.7, much lower than that of the conventional sample (21.7) obtained in acidic medium. The characterization results indicated the presence of a well-ordered Al-containing mesophase with high hydrothermal stability. Notably, the Al content and the acidity of Al-SBA-15 can be tuned by changing the SPS amount.

Development of a colloidal gold immunochromatographic strip for the rapid detection of pefloxacin in grass carp with a novel pretreatment method.

A rapid colloidal gold immunochromatography assay (GICA) for the detection of pefloxacin (PEF) was established and optimized. The anti-PEF monoclonal antibody (mAb) was used to target PEF as a colloidal gold-mAb conjugate. The mAb belonged to the IgG2b subtype, lambda light chain, the affinity constant (Ka) was 5.21 × 109 L·mol-1, and its half maximal inhibitory concentration (IC50) was 0.23 ng·mL-1. No obvious cross-reactivity (CR) was observed with other common fluoroquinolone antibiotics, including ciprofloxacin (CIP), norfloxacin (NOR), lomefloxacin (LOM) and ofloxacin (OFL). The visual limit of detection (vLOD) of the optimized GICA was 2 ng·g-1 under the conventional pretreatment method, and the assay was completed in 15 min. Liquid chromatography tandem-mass spectrometry (LC-MS/MS) was employed to confirm the performance of the strip. In addition, a novel pretreatment was established and compared with conventional pretreatment. Without the removal of organic solvents, the novel pretreatment method reduced the sample pretreatment time (more than 10 min). The vLOD of the optimized GICA was also 2 ng·g-1 when applying the novel pretreatment method. In conclusion, the proposed PEF-GICA could detect samples containing PEF rapidly and accurately, and the novel pretreatment method saved the time of sample pretreatment and improved the efficiency of detection.

Kernel principal components based cascade forest towards disease identification with human microbiota.

BACKGROUND: Numerous pieces of clinical evidence have shown that many phenotypic traits of human disease are related to their gut microbiome, i.e., inflammation, obesity, HIV, and diabetes. Through supervised classification, it is feasible to determine the human disease states by revealing the intestinal microbiota compositional information. However, the abundance matrix of microbiome data is so sparse, an interpretable deep model is crucial to further represent and mine the data for expansion, such as the deep forest model. What's more, overfitting can still exist in the original deep forest model when dealing with such "large p, small n" biology data. Feature reduction is considered to improve the ensemble forest model especially towards the disease identification in the human microbiota. METHODS: In this work, we propose the kernel principal components based cascade forest method, so-called KPCCF, to classify the disease states of patients by using taxonomic profiles of the microbiome at the family level. In detail, the kernel principal components analysis method is first used to reduce the original dimension of human microbiota datasets. Besides, the processed data is fed into the cascade forest to preliminarily discriminate against the disease state of the samples. RESULTS: The proposed KPCCF algorithm can represent the small-scale and high-dimension human microbiota datasets with the sparse feature matrix. Systematic comparison experiments demonstrate that our method consistently outperforms the state-of-the-art methods with the comparative study on 4 datasets. CONCLUSION: Despite sharing some common characteristics, a one-size-fits-all solution does not exist in any space. The traditional depth model has limitations in the biological application of the unbalanced scale between small samples and high dimensions. KPCCF distinguishes from the standard deep forest model for its excellent performance in the microbiota field. Additionally, compared to other dimensionality reduction methods, the kernel principal components analysis method is more suitable for microbiota datasets.

An ATP-Binding Cassette Transporter, LaABCB11, Contributes to Alkaloid Transport in Lycoris aurea.

As a kind of Amaryllidaceae alkaloid which is accumulated in the species of Lycoris plants, lycorine has a range of physiological effects. The biosynthesis pathway of lycorine has been partly revealed, but the transport and accumulation mechanisms of lycorine have rarely been studied. In this study, an ATP-binding cassette (ABC) transporter from Lycoris aurea (L'Hér) Herb., namely LaABCB11, was cloned and functionally characterized. Heterologous expression showed that LaABCB11 transported lycorine in an outward direction, increased the tolerance of yeast cells to lycorine, and caused a lower lycorine accumulation in transformants than control or mutant in yeast. LaABCB11 is associated with the plasma membrane, and in situ hybridization indicated that LaABCB11 was mainly expressed in the phloem of leaves and bulbs, as well as in the cortical cells of roots. These findings suggest that LaABCB11 functions as a lycorine transport and it might be related to the translocation and accumulation of lycorine from the leaves and bulbs to the roots.

[Research progress in original species identification in industry chain of Rhei Radix et Rhizoma].

Rhei Radix et Rhizoma is a kind of commonly used Chinese medicinal materials. Due to the overharvesting, the wild resource is endangering. Large market demand caused severely adulterant of commercial Rhei Radix et Rhizoma medicinal materials and decoction pieces. This manuscript reviewed the advances of the original species authentication in the industrial chain of Rhei Radix et Rhizoma during the latest decade, including characteristics and microscopic features, phytochemical analysis on anthraquinones, and molecular authentication based on DNA barcoding. Accordingly, an original species authentication route for the industrial chain of Rhei Radix et Rhizoma was summarized:(1)the identification of seeds and seedlings by DNA barcoding;(2) the selection of high variable sites based on the chloroplast genome;(3)biomonitoring of the Rhei Radix et Rhizoma medicinal materials and decoction pieces by two-dimensional DNA barcode;(4)traceability of Chinese patent medicines by third-generation sequencing. In conclusion, the combination of molecular identification and traditional identification methods provides a new idea for the identification of the original species of Rhei Radix et Rhizoma in the industrial chain and a essential guidance for the research of drug safety and efficacy of Rhei Radix et Rhizoma.

Fungal endophytes promote the accumulation of Amaryllidaceae alkaloids in Lycoris radiata.

Lycoris radiata is a main source of Amaryllidaceae alkaloids; however, the low content of these alkaloids in planta remains a limit to their pharmaceutical development and utilization. The accumulation of secondary metabolites can be enhanced in plants inoculated with fungal endophytes. In this study, we analysed the diversity of culturable fungal endophytes in different organs of L. radiata. Then, by analysing the correlation between the detectable rate of each fungal species and the content of each tested alkaloid, we proposed several fungal candidates implicated in the increase of alkaloid accumulation. This was verified by inoculating these candidates to L. radiata plants. Based on the results of two independent experiments conducted in May 2018 and October 2019, the individual inoculation of nine fungal endophytes significantly increased the total content of the tested alkaloids in the entire L. radiata plants. This is the first study in L. radiata to show that fungal endophytes are able to improve the accumulation of various alkaloids. Therefore, our results provide insights into a better understanding of interactions between plants and fungal endophytes and suggest an effective strategy for enhancing the alkaloid content in the cultivation of L. radiata.

Characterization, validation, and cross-species transferability of EST-SSR markers developed from Lycoris aurea and their application in genetic evaluation of Lycoris species.

BACKGROUND: The Lycoris genus includes many ornamentally and medicinally important species. Polyploidization and hybridization are considered modes of speciation in this genus, implying great genetic diversity. However, the lack of effective molecular markers has limited the genetic analysis of this genus. RESULTS: In this study, mining of EST-SSR markers was performed using transcriptome sequences of L. aurea, and 839 primer pairs for non-redundant EST-SSRs were successfully designed. A subset of 60 pairs was randomly selected for validation, of which 44 pairs could amplify products of the expected size. Cross-species transferability of the 60 primer pairs among Lycoris species were assessed in L. radiata Hreb, L. sprengeri Comes ex Baker, L. chinensis Traub and L. anhuiensis, of which between 38 to 77% of the primers were able to amplify products in these Lycoris species. Furthermore, 20 and 10 amplification products were selected for sequencing verification in L. aurea and L. radiata respectively. All products were validated as expected SSRs. In addition, 15 SSRs, including 10 sequence-verified and 5 unverified SSRs were selected and used to evaluate the genetic diversity of seven L. radiata lines. Among these, there were three sterile lines, three fertile lines and one line represented by the offspring of one fertile line. Unweighted pair group method with arithmetic mean analysis (UPGMA) demonstrated that the outgroup, L. aurea was separated from L. radiata lines and that the seven L. radiata lines were clustered into two groups, consistent with their fertility. Interestingly, even a dendrogram with 34 individuals representing the seven L. radiata lines was almost consistent with fertility. CONCLUSIONS: This study supplies a pool of potential 839 non-redundant SSR markers for genetic analysis of Lycoris genus, that present high amplification rate, transferability and efficiency, which will facilitate genetic analysis and breeding program in Lycoris.

RMTL: an R library for multi-task learning.

MOTIVATION: Multi-task learning (MTL) is a machine learning technique for simultaneous learning of multiple related classification or regression tasks. Despite its increasing popularity, MTL algorithms are currently not available in the widely used software environment R, creating a bottleneck for their application in biomedical research. RESULTS: We developed an efficient, easy-to-use R library for MTL (www.r-project.org) comprising 10 algorithms applicable for regression, classification, joint predictor selection, task clustering, low-rank learning and incorporation of biological networks. We demonstrate the utility of the algorithms using simulated data. AVAILABILITY AND IMPLEMENTATION: The RMTL package is an open source R package and is freely available at https://github.com/transbioZI/RMTL. RMTL will also be available on cran.r-project.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.