Wide-field intensity fluctuation imaging.

The temporal intensity fluctuations contain important information about the light source and light-medium interaction and are typically characterized by the intensity autocorrelation function, g2(τ). The measurement of g2(τ) is a central topic in many optical sensing applications, ranging from stellar intensity interferometer in astrophysics, to fluorescence correlation spectroscopy in biomedical sciences and blood flow measurement with dynamic light scattering. Currently, g2(τ) at a single point is readily accessible through high-frequency sampling of the intensity signal. However, two-dimensional wide-field imaging of g2(τ) is still limited by the cameras' frame rate. We propose and demonstrate a 2-pulse within-exposure modulation approach to break through the camera frame rate limit and obtain the quasi g2(τ) map in wide field with cameras of only ordinary frame rates.

Wide-field Intensity Fluctuation Imaging.

The temporal intensity fluctuations contain important information about the light source and light-medium interaction and are typically characterized by the intensity autocorrelation function, g2(τ). The measurement of g2(τ) is a central topic in many optical sensing applications, ranging from stellar intensity interferometer in astrophysics, to fluorescence correlation spectroscopy in biomedical sciences and blood flow measurement with dynamic light scattering. Currently, g2(τ) at a single point is readily accessible through high-frequency sampling of the intensity signal. However, two-dimensional wide-field measurement of g2(τ) is still limited by camera frame rates. We propose and demonstrate a 2-pulse within-exposure modulation approach to break through the camera frame rate limit and obtain the quasi g2(τ) map in wide field with cameras of only ordinary frame rates.

A Nuclear Factor Y-B Transcription Factor, GmNFYB17, Regulates Resistance to Drought Stress in Soybean.

Soybean is sensitive to drought stress, and increasing tolerance to drought stresses is an important target for improving the performance of soybean in the field. The genetic mechanisms underlying soybean's drought tolerance remain largely unknown. Via a genome-wide association study (GWAS) combined with linkage analysis, we identified 11 single-nucleotide polymorphisms (SNPs) and 22 quantitative trait locus (QTLs) that are significantly associated with soybean drought tolerance. One of these loci, namely qGI10-1, was co-located by GWAS and linkage mapping. The two intervals of qGI10-1 were differentiated between wild and cultivated soybean. A nuclear factor Y transcription factor, GmNFYB17, was located in one of the differentiated regions of qGI10-1 and thus selected as a candidate gene for further analyses. The analysis of 29 homologous genes of GmNFYB17 in soybean showed that most of the genes from this family were involved in drought stress. The over-expression of GmNFYB17 in soybean enhanced drought resistance and yield accumulation. The transgenic plants grew better than control under limited water conditions and showed a lower degree of leaf damage and MDA content but higher RWC, SOD activity and proline content compared with control. Moreover, the transgenic plants showed a fast-growing root system, especially regarding a higher root-top ratio and more branching roots and lateral roots. The better agronomic traits of yield were also found in GmNFYB17 transgenic plants. Thus, the GmNFYB17 gene was proven to positively regulate drought stress resistance and modulate root growth in soybean. These results provide important insights into the molecular mechanisms underlying drought tolerance in soybean.

GmLecRlk, a Lectin Receptor-like Protein Kinase, Contributes to Salt Stress Tolerance by Regulating Salt-Responsive Genes in Soybean.

Soybean [Glycine max (L.) Merr.] is an important oil crop that provides valuable resources for human consumption, animal feed, and biofuel. Through the transcriptome analysis in our previous study, GmLecRlk (Glyma.07G005700) was identified as a salt-responsive candidate gene in soybean. In this study, qRT-PCR analysis showed that the GmLecRlk gene expression level was significantly induced by salt stress and highly expressed in soybean roots. The pCAMBIA3300-GmLecRlk construct was generated and introduced into the soybean genome by Agrobacterium rhizogenes. Compared with the wild type (WT), GmLecRlk overexpressing (GmLecRlk-ox) soybean lines had significantly enhanced fresh weight, proline (Pro) content, and catalase (CAT) activity, and reduced malondialdehyde (MDA) and H2O2 content under salt stress. These results show that GmLecRlk gene enhanced ROS scavenging ability in response to salt stress in soybean. Meanwhile, we demonstrated that GmLecRlk gene also conferred soybean salt tolerance when it was overexpressed alone in soybean hairy root. Furthermore, the combination of RNA-seq and qRT-PCR analysis was used to determine that GmLecRlk improves the salt tolerance of soybean by upregulating GmERF3, GmbHLH30, and GmDREB2 and downregulating GmGH3.6, GmPUB8, and GmLAMP1. Our research reveals a new mechanism of salt resistance in soybean, which exposes a novel avenue for the cultivation of salt-resistant varieties.

New monoterpenoids from the stigmas of Crocus sativus.

One new compound, crocusatin M (1), and three new glycosidic compounds, crocusatins N-P (2-4), along with nine known compounds were isolated from the dried stigmas of Crocus sativus. The structures of new compounds were elucidated on the basis of spectroscopic analysis, and the absolute configurations of 1, 2, and 3 were unambiguously assigned by the comparison of experimental and calculated ECD data. This is the first report of the isolation of 4 with the HMG moiety from the genus Crocus. Compounds 1 and 4 exhibited weak anti-inflammatory activities on inhibiting lipopolysaccharide (LPS)-induced NO production.

GmAKT1 is involved in K+ uptake and Na+/K+ homeostasis in Arabidopsis and soybean plants.

Plant roots absorb K+ from soil via K+ channels and transporters, which are important for stress responses. In this research, GmAKT1, an AKT1-type K+ channel, was isolated and characterized. The expression of GmAKT1 was induced by K+-starvation and salinity stresses, and it was preferentially expressed in the soybean roots. And GmAKT1 was located in the plasma membrane. As an inward K+ channel, GmAKT1 participated in K+ uptake, as well as rescued the low-K+-sensitive phenotype of the yeast mutant and Arabidopsis akt1 mutant. Overexpression of GmAKT1 significantly improved the growth of plants and increased K+ concentration, leading to lower Na+/K+ ratios in transgenic Arabidopsis and chimeric soybean plants with transgenic hairy roots. In addition, GmAKT1 overexpression resulted in significant upregulation of these ion uptake-related genes, including GmSKOR, GmsSOS1, GmHKT1, and GmNHX1. Our findings suggested that GmAKT1 plays an important part in K+ uptake under low-K+ condition, and could maintain Na+/K+ homeostasis under salt stress in Arabidopsis and soybean plants.

Identification and functional prediction of soybean CircRNAs involved in low-temperature responses.

Circular RNAs (circRNAs) are a newly characterized type of noncoding RNA and play important roles in microRNA (miRNA) function and transcriptional control. To unravel the mechanism of soybean circRNAs in low-temperature (LT) stress response, genome-wide identification of soybean circRNAs was conducted under LT (4 °C) treatment via deep sequencing. In this study, the existence of backsplicing sites was validated and circRNAs exhibited specific expression patterns in response to LT. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that circRNAs could participate in LT-responsive processes. Our study revealed a new circRNA-miRNA-mRNA network, which is involved in LT responses. Furthermore, soybean circRNAs were predicted to have potential to encode polypeptides or protein. Taken together, our results indicate that soybean circRNAs might encode proteins and be involved in the regulation of LT responses, providing clues regarding the molecular LT-responsive mechanisms in soybean.

Predicting gene regulatory interactions based on spatial gene expression data and deep learning.

Reverse engineering of gene regulatory networks (GRNs) is a central task in systems biology. Most of the existing methods for GRN inference rely on gene co-expression analysis or TF-target binding information, where the determination of co-expression is often unreliable merely based on gene expression levels, and the TF-target binding data from high-throughput experiments may be noisy, leading to a high ratio of false links and missed links, especially for large-scale networks. In recent years, the microscopy images recording spatial gene expression have become a new resource in GRN reconstruction, as the spatial and temporal expression patterns contain much abundant gene interaction information. Till now, the spatial expression resources have been largely underexploited, and only a few traditional image processing methods have been employed in the image-based GRN reconstruction. Moreover, co-expression analysis using conventional measurements based on image similarity may be inaccurate, because it is the local-pattern consistency rather than global-image-similarity that determines gene-gene interactions. Here we present GripDL (Gene regulatory interaction prediction via Deep Learning), which incorporates high-confidence TF-gene regulation knowledge from previous studies, and constructs GRNs for Drosophila eye development based on Drosophila embryonic gene expression images. Benefitting from the powerful representation ability of deep neural networks and the supervision information of known interactions, the new method outperforms traditional methods with a large margin and reveals new intriguing knowledge about Drosophila eye development.

AnnoFly: annotating Drosophila embryonic images based on an attention-enhanced RNN model.

MOTIVATION: In the post-genomic era, image-based transcriptomics have received huge attention, because the visualization of gene expression distribution is able to reveal spatial and temporal expression pattern, which is significantly important for understanding biological mechanisms. The Berkeley Drosophila Genome Project has collected a large-scale spatial gene expression database for studying Drosophila embryogenesis. Given the expression images, how to annotate them for the study of Drosophila embryonic development is the next urgent task. In order to speed up the labor-intensive labeling work, automatic tools are highly desired. However, conventional image annotation tools are not applicable here, because the labeling is at the gene-level rather than the image-level, where each gene is represented by a bag of multiple related images, showing a multi-instance phenomenon, and the image quality varies by image orientations and experiment batches. Moreover, different local regions of an image correspond to different CV annotation terms, i.e. an image has multiple labels. Designing an accurate annotation tool in such a multi-instance multi-label scenario is a very challenging task. RESULTS: To address these challenges, we develop a new annotator for the fruit fly embryonic images, called AnnoFly. Driven by an attention-enhanced RNN model, it can weight images of different qualities, so as to focus on the most informative image patterns. We assess the new model on three standard datasets. The experimental results reveal that the attention-based model provides a transparent approach for identifying the important images for labeling, and it substantially enhances the accuracy compared with the existing annotation methods, including both single-instance and multi-instance learning methods. AVAILABILITY AND IMPLEMENTATION: http://www.csbio.sjtu.edu.cn/bioinf/annofly/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

[Efficacy and safety evaluation of systemic red light therapy for burn wound repair].

OBJECTIVE: To investigate effects of systemic red light therapy on wound repair of burned patients and discuss its possible mechanisms of wound healing promotion. METHODS: 138 burned patients were randomly divided into systemic red light treatment group (n = 69) and control group (n = 69). Patients in control group received routine therapy, while those in test group were given systemic red light therapy once a day, 30 minutes at a time until the wounds were recovered. The clinical findings and variables indicating wound repair were assessed on the 7th, 10th, 14th day, 21st day post-burn and the day when the wounds were healed. RESULTS: Mean time of wound recovery were 19.86 +/- 2.43 days and 21.02 +/- 2.97 days respectively of those deep-thickness wounds in test group and control group, with statistically significance (P < 0.05). For the severity of the pain, VAS during time of dressing change on the 10th, 14th day post burn was lower in test group than that in control group which indicated less painful in test group (P < 0.05), suggesting pain relief effect of systemic red light therapy. CONCLUSION: Systemic red light therapy was effective to promote wound healing of deep-thickness burn wounds and other similar acute wounds. Simultaneously, it is efficacious in pain relief and safe for those patients.

[Effect of isoflavone on human breast cancer cell line MCF-7 and its probable mechanism].

The effects of isoflavone on human breast cancer cell line MCF-7 growth and apoptosis and its probable mechanisms were studied in vitro. The results showed that isoflavone could significantly inhibit the growth and induce the apoptosis of MCF-7 cells. Western Blotting showed that isoflavone increased iNOS protein expression. These results suggested that isoflavone significantly inhibited the MCF-7 growth and induced cell apoptosis by regulating iNOS gene expression.