[A new cinnamic acid ester derivative from Liquidambaris Resina].

Twelve compounds were isolated from Liquidambaris Resina by silica gel column chromatography and thin layer chromatography. Their structures were identified on the basis of spectral data, electron capture detector data, and physicochemical properties as(2'R, 3'R)-2',3'-dihydroxy-hydrocinnamyl-(E)-cinnamate(1),(E)-cinnamyl-(E)-cinnamate(2), cinnamic acid(3), 28-norlup-20(29)-en-3-one-17ß-hydroperoxide(4), erythrodiol(5), 13ß,28-epoxy-30-hydroxyolean-1-en-3-one(6),(3ß)-olean-12-ene-3,23-diol(7), 2α,3α-dihydroxy-olean-12-en-28-oic acid(8), 28-hydroxyolean-12-en-3-one(9), 3-epi-oleanolic acid(10), 3-oxo-oleanolic acid(11), and hederagenin(12). Compound 1 was a new cinnamic acid ester derivative and compounds 2-4,6-8, and 12 were isolated from Liquidambaris Resina for the first time. Compounds 4, 5, 10, and 12 exerted inhibitory effects on the proliferation of human umbilical vein endothelial cells(HUVEC) with the IC_(50) values of(17.43±2.17),(35.32±0.61),(27.50±0.80), and(46.30±0.30) µmol·L~(-1), respectively.

Imprints of independent allopolyploid formations on patterns of gene expression in two sibling yarrow species (Achillea, Asteraceae).

BACKGROUND: Polyploid species often originate recurrently. While this is well known, there is little information on the extent to which distinct allotetraploid species formed from the same parent species differ in gene expression. The tetraploid yarrow species Achillea alpina and A. wilsoniana arose independently from allopolyploidization between diploid A. acuminata and A. asiatica. The genetics and geography of these origins are clear from previous studies, providing a solid basis for comparing gene expression patterns of sibling allopolyploid species that arose independently. RESULTS: We conducted comparative RNA-sequencing analyses on the two Achillea tetraploid species and their diploid progenitors to evaluate: 1) species-specific gene expression and coexpression across the four species; 2) patterns of inheritance of parental gene expression; 3) parental contributions to gene expression in the allotetraploid species, and homeolog expression bias. Diploid A. asiatica showed a higher contribution than diploid A. acuminata to the transcriptomes of both tetraploids and also greater homeolog bias in these transcriptomes, possibly reflecting a maternal effect. Comparing expressed genes in the two allotetraploids, we found expression of ca. 30% genes were species-specific in each, which were most enriched for GO terms pertaining to "defense response". Despite species-specific and differentially expressed genes between the two allotetraploids, they display similar transcriptome changes in comparison to their diploid progenitors. CONCLUSION: Two independently originated Achillea allotetraploid species exhibited difference in gene expression, some of which must be related to differential adaptation during their post-speciation evolution. On the other hand, they showed similar expression profiles when compared to their progenitors. This similarity might be expected when pairs of merged diploid genomes in tetraploids are similar, as is the case in these two particular allotetraploids.

Phylogenomics Reveals an Ancient Hybrid Origin of the Persian Walnut.

Persian walnut (Juglans regia) is cultivated worldwide for its high-quality wood and nuts, but its origin has remained mysterious because in phylogenies it occupies an unresolved position between American black walnuts and Asian butternuts. Equally unclear is the origin of the only American butternut, J. cinerea. We resequenced the whole genome of 80 individuals from 19 of the 22 species of Juglans and assembled the genome of its relatives Pterocarya stenoptera and Platycarya strobilacea. Using phylogenetic-network analysis of single-copy nuclear genes, genome-wide site pattern probabilities, and Approximate Bayesian Computation, we discovered that J. regia (and its landrace J. sigillata) arose as a hybrid between the American and the Asian lineages and that J. cinerea resulted from massive introgression from an immigrating Asian butternut into the genome of an American black walnut. Approximate Bayesian Computation modeling placed the hybrid origin in the late Pliocene, ∼3.45 My, with both parental lineages since having gone extinct in Europe.

Antibacterial Diphenyl Ether, Benzophenone and Xanthone Derivatives from Aspergillus flavipes.

The extract of the strain Aspergillus flavipes DL-11 exerted antibacterial activities against six Gram-positive bacteria. During the following bioassay-guided separation, ten diphenyl ethers (1-10), two benzophenones (11-12), together with two xanthones (13-14) were isolated. Among them, 4'-chloroasterric acid (1) was a new chlorinated diphenyl ether. Their structures were elucidated by extensive spectroscopic data analysis, including IR, HR-ESI-MS, NMR experiments, and by comparison with the literature data. All compounds showed moderate to strong antibacterial effects on different Gram-positive bacteria with MIC values that ranged from 3.13 to 50 µg/mL, but none of the compounds exhibited activity against Gram-negative bacteria Vibrio parahaemolyticus ATCC17802 (MIC>100 µg/mL). In particular, the MICs of some compounds are at the level of positive control.

Demographically idiosyncratic responses to climate change and rapid Pleistocene diversification of the walnut genus Juglans (Juglandaceae) revealed by whole-genome sequences.

Whether species demography and diversification are driven primarily by extrinsic environmental changes such as climatic oscillations in the Quaternary or by intrinsic biological interactions like coevolution between antagonists is a matter of active debate. In fact, their relative importance can be assessed by tracking past population fluctuations over considerable time periods. We applied the pairwise sequentially Markovian coalescent approach on the genomes of 11 temperate Juglans species to estimate trajectories of changes in effective population size (Ne ) and used a Bayesian-coalescent based approach that simultaneously considers multiple genomes (G-PhoCS) to estimate divergence times between lineages. Ne curves of all study species converged 1.0 million yr ago, probably reflecting the time when the walnut genus last shared a common ancestor. This estimate was confirmed by the G-PhoCS estimates of divergence times. But all species did not react similarly to the dramatic climatic oscillations following early Pleistocene cooling, so the timing and amplitude of changes in Ne differed among species and even among conspecific lineages. The population histories of temperate walnut species were not driven by extrinsic environmental changes alone, and a key role was probably played by species-specific factors such as coevolutionary interactions with specialized pathogens.

A toxicological, metabonomic and transcriptional analysis to investigate the property of mulberry 1-deoxynojirimycin against the growth of Samia cynthia ricini.

1-Deoxynojirimycin (DNJ) is a natural d-glucose analogue from mulberry with promising physiological activity in vivo. Up to the present, the antidiabetic effects of DNJ on lowering blood sugar and accelerating lipid metabolism in mammals were broadly reported, but the specific character of DNJ against insects was vastly ignored. In this study, a toxicological test of DNJ againgst eri-silkworm, Samia cynthia ricini was carried out to investigate the potential of DNJ in insect management. Further, a method of nuclear magnetic resonance (NMR) metabonomics and real-time qPCR (RT-qPCR) were performed to analyze the alteration in midgut of eri-silkworm caused by DNJ. The result of toxicology showed that 5% and 10% DNJ could significantly inhibit the development of third-instar larvae on day 1-5, and mass deaths happened in DNJ groups on day 3-5. The quantitative analysis of 1H NMR in fifth-instar larvae showed that trehalose level increased in midgut of 0, 6 and 12 h DNJ groups, while the concentrations of glucose, lactate, alanine, pyruvate, α-ketoglutarate and fumarate were reduced in varying degrees. Meanwhile, principal component analysis (PCA) indicated that there were significant differences in the metabolic profiles among 12 h DNJ groups and the control group. In addition, RT-qPCR results displayed that four genes coding α-glucosidase, trehalase (THL) and lactate dehydrogenase (LDH) were lowered in expression of 12 h DNJ groups. Simultaneously, THL activity was significantly lowerd in 12 h DNJ groups. These mutually corroborated results indicated that the backbone pathways of energy metabolism, including hydrolysis of trehalose and glycogens, glycolysis and tricarboxylic acid (TCA) cycle were significantly inhibited by DNJ. Thus, the specific mechanism of DNJ efficiently suppressing the growth and energy metabolism of eri-silkworm was explored in this study, providing the potential of DNJ as to the production of botanical insecticide.

Identification of Coalmine Water Inrush Source with PCA-BP Model Based on Laser-Induced Fluorescence Technology.

The water inrush should been rapidly and accurately identified during preventing coalmine water inrush. The laser induced fluorescent (LIF) spectrum technology provides a new method to identify water inrush with the characteristics of high sensitivity, quick and accurate monitoring. In order to identify water inrush, this paper introduces the spectrum technology of LIF to obtain water inrush fluorescence spectra data. The spectral preprocessing methods of Savitzky-Golay(SG) and Multiplicative Scatter Correction (MSC) have been used to eliminate noise spectra in collecting process. Principal component analysis (PCA) extracts feature information, for SG reprocessing data, when the number of principal component is 3, the cumulative contribution rate can reach 99.76 percent. This method has largely retained the information of original data. This paper chooses the classification model with 3 layers BP neural network, constructing by different training and testing sets. The classification model with SG preprocessing has achieved accurate identification, however, appeared few false identification for MSC and original data. The result shows that SG preprocessing is better than MSC. Research results show that the classification model with PCA and BP neural network can effectively identify coalmine water inrush, and have the strong self-organizing, self-learning ability.

[Application of the Identification of Mine Water Inrush with LIF Spectrometry and KNN Algorithm Combined with PCA].

Rapid identification and classification of mine water inrush is important for flood prevention work underground. This paper proposed a method of KNN combined with PCA identification of water inrush in mine with the laser induced fluorescence spectrum with an immersion probe laser into water samples. The fluorescence spectra of 4 kinds of water samples were obtained. For each set of data preprocessing, the processed data in each sample from 15 sets of data as the training setwith a total of 60 groups. The other 20 groups were used as the prediction set. The data were processed by principal component analysis (PCA), and then the KNN algorithm was used to classify and identify the principal component analysis. During the experiment, the pretreatment method in the principal component number is 2 while the correct rate has reached 100% by KNN classification algorithm.

[Research on the Source Identification of Mine Water Inrush Based on LIF Technology and PLS-DA Algorithm].

Rapid source identification of mine water inrush has great significance for early warning and rescuing after the mine water inrush. Conventional method taking the concentration of ions as the discriminant factor takes such a long time that a method of rapid source identification of mine water inrush is in urgent need. This method is combined with Laser induced fluorescence (LIF) technology and Partial Least Squares-Discriminant Analysis (PLS-DA) algorithm. In the experiment, 405 nm laser was used to excite the water and 100 groups of fluorescence spectrum from 5 different aquifer of the mine were obtained. According to the spectra curve features, the data was compressed to obtain proper spectral data. 15 groups of spectrum of each water inrush samples were applied, with a total of 75 groups of spectrum as the prediction set while the rest of 25 groups of spectrum as the test set. To verify the experimental result, an experimental model was built with soft independent modeling of class analogy (SIMCA) to compare with PLS-DA. The result shows that the fluorescence spectra of different aquifer water samples is of great difference, without any pre-treatment, the PLS-DA algorithm based on the PLS model has higher modeling accuracy compared with SIMCA algorithm, which reaches to 100%, the validation results and the correlation of separation of variables are both more than 0.951, the RMSECV and RMSEP are both less than 0.123, using the model to identify the 5 water samples of test set, the accuracy are up to 100%.

[Research on the Source Identification of Mine Water Inrush Based on LIF Technology and SIMCA Algorithm].

Rapid source identification of mine water inrush is of great significance for early warning and prevention in mine water hazard. According to the problem that traditional chemical methods to identify source takes a long time, put forward a method for rapid source identification of mine water inrush with laser induced fluorescence (LIF) technology and soft independent modeling of class analogy (SIMCA) algorithm. Laser induced fluorescence technology has the characteristics of fast analysis, high sensitivity and so on. With the laser assisted, fluorescence spectrums can be collected real-time by the fluorescence spectrometer. According to the fluorescence spectrums, the type of water samples can be identified. If the database is completed, it takes a few seconds for coal mine water source identification, so it is of great significance for early warning and post-disaster relief in coal mine water disaster. The experiment uses 405 nm laser emission laser into the 5 kinds of water inrush samples and get 100 groups of fluorescence spectrum, and then put all fluorescence spectrums into preprocessing. Use 15 group spectrums of each water inrush samples, a total of 75 group spectrums, as the prediction set, the rest of 25 groups spectrums as the test set. Using principal component analysis (PCA) to modeling the 5 kinds of water samples respectively, and then classify the water samples with SIMCA on the basis of the PCA model. It was found that the fluorescence spectrum are obvious different of different water inrush samples. The fluorescence spectrums after preprocessing of Gaussian-Filter, under the condition of the principal component number is 2 and the significant level α = 5%, the accuracy of prediction set and testing set are all 100% with the SIMCA to classify the water inrush samples.

Flowering time and transcriptome variation in Capsella bursa-pastoris (Brassicaceae).

• Flowering is a major developmental transition and its timing in relation to environmental conditions is of crucial importance to plant fitness. Understanding the genetic basis of flowering time variation is important to determining how plants adapt locally. • Here, we investigated flowering time variation of Capsella bursa-pastoris collected from different latitudes in China. We also used a digital gene expression (DGE) system to generate partial gene expression profiles for 12 selected samples. • We found that flowering time was highly variable and most strongly correlated with day length and winter temperature. Significant differences in gene expression between early- and late-flowering samples were detected for 72 candidate genes for flowering time. Genes related to circadian rhythms were significantly overrepresented among the differentially expressed genes. • Our data suggest that circadian rhythms and circadian clock genes play an important role in the evolution of flowering time, and C. bursa-pastoris plants exhibit expression differences for candidate genes likely to affect flowering time across the broad range of environments they face in China.

Assembly of an early-matured japonica (Geng) rice genome, Suijing18, based on PacBio and Illumina sequencing.

The early-matured japonica (Geng) rice variety, Suijing18 (SJ18), carries multiple elite traits including durable blast resistance, good grain quality, and high yield. Using PacBio SMRT technology, we produced over 25 Gb of long-read sequencing raw data from SJ18 with a coverage of 62×. Using Illumina paired-end whole-genome shotgun sequencing technology, we generated 59 Gb of short-read sequencing data from SJ18 (23.6 Gb from a 200 bp library with a coverage of 59× and 35.4 Gb from an 800 bp library with a coverage of 88×). With these data, we assembled a single SJ18 genome and then generated a set of annotation data. These data sets can be used to test new programs for variation deep mining, and will provide new insights into the genome structure, function, and evolution of SJ18, and will provide essential support for biological research in general.

Sesquiterpenoids from Curcuma wenyujin with anti-influenza viral activities.

Five sesquiterpenoids, 1α,8α-epidioxy-4α-hydroxy- 5αH-guai-7(11),9-dien- 12,8-olide. (1), 8,9-seco-4ß-hydroxy-1α,5ßH-7(11)-guaen-8,10-olide (2), 8α-hydroxy-1α, 4ß,7ßH-guai-10(15)-en- 5ß,8ß-endoxide(3), 7ß,8α-dihydroxy-1α,4αH-guai-10(15)-en-5ß,8ß-endoxide(4) and 7-hydroxy-5(10),6,8-cadinatriene-4-one(5), together with seven known analogs were isolated from the rhizomes of Curcuma wenyujin. Their structures and relative configurations were determined on the basis of spectroscopic methods including 2D NMR techniques, and the structures of 1 and 2 were confirmed by single-crystal X-ray diffraction experiment. Compounds 1-10 and 12 showed significant in vitro antiviral activity against the influenza virus A with IC50 values ranged from 6.80 to 39.97 µM, and SI values ranged from 6.35 to 37.25.