Promoter activity analysis and transcriptional profile of Ginkgo biloba 1-Deoxy-D- Xylulose 5-Phosphate reductoisomerase gene (GbDXR) under abiotic stresses

Terpene trilactones (TTL) is a pharmacological ingredient in Ginkgo biloba and its content has become one of the key indices for medicinal value evaluation of ginkgo. 1-Deoxy-D-xylulose 5-phosphate reductoisomerase (DXR) catalyzes the first step specific for isopentenyl diphosphate production in methylerythritol phosphate pathway, which provide the basic structure required for TTLs biosynthesis. To understand the mechanism controlling the GbDXR gene expression, the GbDXR promoter sequence was isolated and subjected to transient expression with the green fluorescent protein (GFP) in tobacco plants. Characteristic analysis revealed various cis-acting elements that related to light-regulated transcription, hormone signaling (auxin, ethylene), adversity stress and defense signaling (heat/dehydration stress) in the GbDXR promoter region. In transient expression assay, deletion of different portions of the upstream GbDXR promoter identified that the promoter region -3230bp to -865bp conserve the positive regulation function, which could promote the expression of GFP in the cytoplasm of tobacco leaf epidermal cells. The regulation function of the promoter region -865bp to -262bp remained to be elucidated. EMSA analysis suggested possible interactions of GbERF10 and GbERF17 with the ERF-binding elements in the upstream of GbDXR promoter. For abiotic stresses treatment, the expression of GbDXR gene could be significantly induced by UV-B and drought stress. In general, the GbDXR gene expressed differently in different ginkgo tissues but exhibited the highest transcriptional level in the root, with the maximum TTLs content simultaneously. The positive relationship between gene expression level and TTLs content indicated that the GbDXR is responsible for TTLs biosynthesis in G. biloba

EEGFuseNet: Hybrid Unsupervised Deep Feature Characterization and Fusion for High-Dimensional EEG With an Application to Emotion Recognition

How to effectively and efficiently extract valid and reliable features from high-dimensional electroencephalography (EEG), particularly how to fuse the spatial and temporal dynamic brain information into a better feature representation, is a critical issue in brain data analysis. Most current EEG studies work in a task driven manner and explore the valid EEG features with a supervised model, which would be limited by the given labels to a great extent. In this paper, we propose a practical hybrid unsupervised deep convolutional recurrent generative adversarial network based EEG feature characterization and fusion model, which is termed as EEGFuseNet. EEGFuseNet is trained in an unsupervised manner, and deep EEG features covering both spatial and temporal dynamics are automatically characterized. Comparing to the existing features, the characterized deep EEG features could be considered to be more generic and independent of any specific EEG task. The performance of the extracted deep and low-dimensional features by EEGFuseNet is carefully evaluated in an unsupervised emotion recognition application based on three public emotion databases. The results demonstrate the proposed EEGFuseNet is a robust and reliable model, which is easy to train and performs efficiently in the representation and fusion of dynamic EEG features. In particular, EEGFuseNet is established as an optimal unsupervised fusion model with promising cross-subject emotion recognition performance. It proves EEGFuseNet is capable of characterizing and fusing deep features that imply comparative cortical dynamic significance corresponding to the changing of different emotion states, and also demonstrates the possibility of realizing EEG based cross-subject emotion recognition in a pure unsupervised manner

High-resolution X-ray microdiffraction analysis of natural teeth

In situ microzone X-ray diffraction analysis of natural teeth is presented. From our experiment, layer orientation and continuous crystal variations in teeth could be conveniently studied using fast online measurements by high-resolution X-ray microdiffraction equipment

Extraction, Isolation and Identification of Antimicrobial Substances from Bacillus amyloliquefaciens CMN1308

Four separation methods of antimicrobial substances produced by CMN1308 (Bacillus amyloliquefaciens) were evaluated and selected according to number of antimicrobial substances and its activity in vitro. The results showed that extraction by acid precipitation of the fermentation supernatant of CMN1308 was the best with a diameter of inhibition zone of pathogen fungi P. expansum of 12.3 mm in a laboratory bioassay. Applying a silica thin layer chromatography (TLC), SDS-PAGE and other separation technologies we isolate antimicrobial substances, and the separated band were cut off for mass spectrometry analysis. The TLC of crude extract of CMN1308 show a topical band corresponding with the surfactin standard (Rf value =0.75), proved that the strain CMN1308 can produce this surface active compound. The mycoprotein extracted from CMN1308 was separated by Tricine-SDS-PAGE modified with the addition of urea in the separation gel. After mass spectrometric analysis and protein characterization, the isolated mycoprotein showed a maximum ion peak at M/Z of 2679 and molecular weight of 29.5 kDa, matching with protein flagellin. The extracellular antimicrobial protein of strain CMN1308 display four bands after urea-Tricine-SDS-PAGE, but after mass spectrometry analysis only two bands were identified. Band “A” with a maximum ion peak at M/Z of 1926 and molecular weight of 49.8 kDa, aligned with NCBI database, matching with DLDH (dihydrolipoamide dehydrogenase enzyme). Band “D” show the maximum ion peak at M/Z of 2936 and molecular weight of 22.4 kD, matching with a chitin binding protein. Thus, the strain CMN1308 has the potential to be developed as a commercial biological control agent for chestnut common pathogenic fungi

Characteristics of DNA-AuNP networks on cell membranes and real-time movies for viral infection

AbstractThis data article provides complementary data for the article entitled “DNA-AuNP networks on cell membranes as a protective barrier to inhibit viral attachment, entry and budding” Li et al. (2016) [1]. The experimental methods for the preparation and characterization of DNA-conjugated nanoparticle networks on cell membranes were described. Confocal fluorescence images, agarose gel electrophoresis images and hydrodynamic diameter of DNA-conjugated gold nanoparticle (DNA-AuNP) networks were presented. In addition, we have prepared QDs-labeled RSV (QDs-RSV) to real-time monitor the RSV infection on HEp-2 cells in the absence and presence of DNA-AuNP networks. Finally, the cell viability of HEp-2 cells coated by six types of DNA-nanoparticle networks was determined after RSV infection

HA-HI: Synergising fMRI and DTI through Hierarchical Alignments and Hierarchical Interactions for Mild Cognitive Impairment Diagnosis

Early diagnosis of mild cognitive impairment (MCI) and subjective cognitive decline (SCD) utilizing multi-modal magnetic resonance imaging (MRI) is a pivotal area of research. While various regional and connectivity features from functional MRI (fMRI) and diffusion tensor imaging (DTI) have been employed to develop diagnosis models, most studies integrate these features without adequately addressing their alignment and interactions. This limits the potential to fully exploit the synergistic contributions of combined features and modalities. To solve this gap, our study introduces a novel Hierarchical Alignments and Hierarchical Interactions (HA-HI) method for MCI and SCD classification, leveraging the combined strengths of fMRI and DTI. HA-HI efficiently learns significant MCI- or SCD- related regional and connectivity features by aligning various feature types and hierarchically maximizing their interactions. Furthermore, to enhance the interpretability of our approach, we have developed the Synergistic Activation Map (SAM) technique, revealing the critical brain regions and connections that are indicative of MCI/SCD. Comprehensive evaluations on the ADNI dataset and our self-collected data demonstrate that HA-HI outperforms other existing methods in diagnosing MCI and SCD, making it a potentially vital and interpretable tool for early detection. The implementation of this method is publicly accessible at https://github.com/ICI-BCI/Dual-MRI-HA-HI.git

Neural Activation During Tonic Pain and Interaction Between Pain and Emotion in Bipolar Disorder: An fMRI Study

Objective: Pain and affective disorders have clear clinical relevance; however, very few studies have investigated the association between pain and bipolar disorder. This study investigated the brain activity of patients with bipolar disorder (BPs) undergoing tonic pain and assessed the interaction between pain and emotion.Methods: Ten BPs and ten healthy controls (HCs) were exposed to emotional pictures (positive, neutral, or negative), tonic pain only (pain session), and emotional pictures along with tonic pain (combined session). A moderate tonic pain was induced by the infusion of hypertonic saline (5% NaCl) into the right masseter muscle with a computer-controlled system. Whole-brain blood oxygenation level dependent (BOLD) signals were acquired using 3T functional resonance imaging (fMRI).Results: Ten BPs and ten healthy participants were included in the final analysis. During the pain session, BPs accepted more saline, but showed lower pain rating scores than HCs. When experiencing pain, BPs showed a significant decrease in the BOLD signal in the bilateral insula, left inferior frontal gyrus (IFG), and left cerebellum as compared with HCs. In the combined session, the activated regions for positive mood (pain with positive mood > baseline) in BPs were the left cerebellum, right temporal gyrus, and left occipital gyrus; the activated regions for negative mood (pain with negative mood > baseline) were the right occipital gyrus, left insula, left IFG, and bilateral precentral gyrus.Conclusions: This study presents the preliminary finding of the interaction between pain and emotion in BPs. BPs exhibited lower sensitivity to pain, and the activation of insula and IFG may reflect the interaction between emotion and pain stimulus

Determination of Camellia oleifera Abel. Germplasm Resources of Genetic Diversity in China using ISSR Markers

Camellia oleifera is one of the four woody oil plants in the world, which is widely cultivated in South China. To examine the genetic diversity of C. oleifera in China, the diversity and genetic relationships among and within major populations of 109 varieties of C. oleifera were analyzed using ISSR markers. Twenty-three ISSR primers out of 49 primers yielded approximately 487 legible bands. A total of 335 of these bands were polymorphic markers, and the ratio of polymorphism was 68.86%. From the results, Zhejiang province showed the highest populations genetic diversity (H value 0.18), while Guangxi population showed the lowest genetic diversity (H 0.0851). Base on the bands, the genetic similarity coefficient ranged from 0.61 to 0.93 using NTSYS2.10e software. When coefficient was 0.75, 109 cultivars were divided into 11 categories and categories I contain 79 varieties by UPGMA cluster analysis. The test varieties divided into 7 sub-groups when categories were 0.75, which show a close genetic relationship. Results advised that Hunan is the main producing area of C. oleifera, with enriched C. oleifera variety and complex topography, and therefore has a high genetic diversity. Meanwhile, the main varieties of C. oleifera in Hubei are imported from Hunan, which results in fewer varieties and reduces the genetic diversity of C. oleifera. The ISSR profiles can improve C. oleifera germplasm management and provide potential determine correlations between different varieties and its distribution in different province

Influence of Individual Differences in fMRI-Based Pain Prediction Models on Between-Individual Prediction Performance

Decoding subjective pain perception from functional magnetic resonance imaging (fMRI) data using machine learning technique is gaining a growing interest. Despite the well-documented individual differences in pain experience and brain responses, it still remains unclear how and to what extent these individual differences affect the performance of between-individual fMRI-based pain prediction. The present study is aimed to examine the relationship between individual differences in pain prediction models and between-individual prediction error, and, further, to identify brain regions that contribute to between-individual prediction error. To this end, we collected and analyzed fMRI data and pain ratings in a laser-evoked pain experiment. By correlating different types of individual difference metrics with between-individual prediction error, we are able to quantify the influence of these individual differences on prediction performance and reveal a set of brain regions whose activities are related to prediction error. Interestingly, we found that the precuneus, which does not have predictive capability to pain, could also affect the prediction error. This study elucidates the influence of interindividual variability in pain on the between-individual prediction performance, and the results will be useful for the design of more accurate and robust fMRI-based pain prediction models

Protect Effects of Ganoderma lucidum Spore Polysaccharide on Liver Injury Caused by Acetaminophen

Objective: To investigate the protective effects of Ganoderma lucidum spore polysaccharide (GLSP) on liver injury caused by acetaminophen (APAP). Methods: Fifty mice were randomly divided into five groups: Blank group, model group, positive drug group, GLSP low-dose group and GLSP high-dose group, with 10 mice in each group. After each group was pre-administered according to the corresponding dose for 14 consecutive days, the liver index, serum indexes (glutamic oxalacetic transaminase (AST), glutamic-pyruvic transaminase (ALT)) and liver tissue plasma indexes (glutathione (GSH), malonaldehyde (MDA), superoxide dismutase (SOD), Caspase-3, Bax and Bcl-xl) were determined. Results: Compared with the blank group, ALT, AST, MDA and proapoptotic genes Caspase-3 and Bax were very significantly increased in the model group (P<0.01). The contents of SOD and GSH decreased very significantly (P<0.01), and HE staining showed that APAP treated mice showed typical lobular central necrosis of liver. Compared with model group, ALT and AST were very significantly decreased in polysaccharide dose group (P<0.01), SOD and GSH were significantly increased (P<0.05) and MDA was significantly decreased in polysaccharide low-dose group (P<0.05), SOD and GSH were very significantly increased (P<0.01) and MDA was very significantly decreased in polysaccharide high-dose group (P<0.01), and pro-apoptotic genes Caspase-3 and Bax were very significantly decreased in polysaccharide group (P<0.01), and the liver histopathological observation showed that the necrotic area of liver tissue decreased. Conclusion: Ganoderma lucidum spore polysaccharide can preprotect APAP liver injury, and its mechanism may be related to improving the antioxidant capacity of liver and inhibiting the occurrence of apoptosis