RNAi-directed downregulation of OsBADH2 results in aroma (2-acetyl-1-pyrroline) production in rice (Oryza sativa L.)

<p>Abstract</p> <p>Background</p> <p>Aromatic rice is popular worldwide because of its characteristic fragrance. Genetic studies and physical fine mapping reveal that a candidate gene (<it>fgr</it>/<it>OsBADH2</it>) homologous to <it>betaine aldehyde dehydrogenase </it>is responsible for aroma metabolism in fragrant rice varieties, but the direct evidence demonstrating the functions of <it>OsBADH2 </it>is lacking. To elucidate the physiological roles of <it>OsBADH2</it>, sequencing approach and RNA interference (RNAi) technique were employed to analyze allelic variation and functions of <it>OsBADH2 </it>gene in aroma production. Semi-quantitative, real-time reverse transcription-polymerase chain reaction (RT-PCR), as well as gas chromatography-mass spectrometry (GC-MS) were conducted to determine the expression levels of <it>OsBADH2 </it>and the fragrant compound in wild type and transgenic <it>OsBADH2</it>-RNAi repression lines, respectively.</p> <p>Results</p> <p>The results showed that multiple mutations identical to <it>fgr </it>allele occur in the 13 fragrant rice accessions across China; <it>OsBADH2 </it>is expressed constitutively, with less expression abundance in mature roots; the disrupted <it>OsBADH2 </it>by RNA interference leads to significantly increased 2-acetyl-1-pyrroline production.</p> <p>Conclusion</p> <p>We have found that the altered expression levels of <it>OsBADH2 </it>gene influence aroma accumulation, and the prevalent aromatic allele probably has a single evolutionary origin.</p

Compressive sensing based secret signals recovery for effective image steganalysis in secure communications

Conventional image steganalysis mainly focus on presence detection rather than the recovery of the original secret messages that were embedded in the host image. To address this issue, we propose an image steganalysis method featured in the compressive sensing (CS) domain, where block CS measurement matrix senses the transform coefficients of stego-image to reflect the statistical differences between the cover and stego- images. With multi-hypothesis prediction in the CS domain, the reconstruction of hidden signals is achieved efficiently. Extensive experiments have been carried out on five diverse image databases and benchmarked with four typical stegographic algorithms. The comprehensive results have demonstrated the efficacy of the proposed approach as a universal scheme for effective detection of stegography in secure communications whilst it has greatly reduced the numbers of features requested for secret signal reconstruction

Acupuncture Modulates the Functional Connectivity of the Default Mode Network in Stroke Patients

Abundant evidence from previous fMRI studies on acupuncture has revealed significant modulatory effects at widespread brain regions. However, few reports on the modulation to the default mode network (DMN) of stroke patients have been investigated in the field of acupuncture. To study the modulatory effects of acupuncture on the DMN of stroke patients, eight right hemispheric infarction and stable ischemic stroke patients and ten healthy subjects were recruited to undergo resting state fMRI scanning before and after acupuncture stimulation. Functional connectivity analysis was applied with the bilateral posterior cingulate cortices chosen as the seed regions. The main finding demonstrated that the interregional interactions between the ACC and PCC especially enhanced after acupuncture at GB34 in stroke patients, compared with healthy controls. The results indicated that the possible mechanisms of the modulatory effects of acupuncture on the DMN of stroke patients could be interpreted in terms of cognitive ability and motor function recovery

Association mapping of stigma and spikelet characteristics in rice (Oryza sativa L.)

Stigma and spikelet characteristics play an essential role in hybrid seed production. A mini-core of 90 accessions developed from USDA rice core collection was phenotyped in field grown for nine traits of stigma and spikelet and genotyped with 109 DNA markers, 108 SSRs plus an indel. Three major clusters were built upon Rogers’ genetic distance, indicative of indicas, and temperate and tropical japonicas. A mixed linear model combining PC-matrix and K-matrix was adapted for mapping marker-trait associations. Resulting associations were adjusted using false discovery rate technique. We identified 34 marker-trait associations involving 22 SSR markers for eight traits. Four markers were associated with single stigma exsertion (SStgE), six with dual exsertion (DStgE) and five with total exsertion. RM5_Chr1 played major role indicative of high regression with not only DStgE but also SStgE. Four markers were associated with spikelet length, three with width and seven with L/W ratio. Numerous markers were co-associated with multiple traits that were phenotypically correlated, i.e. RM12521_Chr2 associated with all three correlated spikelet traits. The co-association should improve breeding efficiency because single marker could be used to assist breeding for multiple traits. Indica entry 1032 (cultivar 50638) and japonica entry 671 (cultivar Linia 84 Icar) with 80.65 and 75.17% of TStgE, respectively are recommended to breeder for improving stigma exsertion

Extraction and Purification of Nicotine from Tobacco Rhizomes by Supercritical CO₂

Currently, in the ongoing development of the tobacco industry, a large amount of tobacco rhizomes is discarded as waste. These wastes are usually disposed of through incineration or burial. However, these tobacco wastes still have some economic value. High-purity nicotine has a promising market outlook as the primary raw material for electronic cigarette liquid. Nicotine is not only found in tobacco leaves but also in the rhizomes of tobacco plants. This study presents a method for treating tobacco waste and extracting high-purity nicotine from it. After mixing the raw material powder and entrainer in specific ratios, as much of the nicotine in tobacco roots can be extracted as possible using supercritical carbon dioxide extraction. The effects of temperature, the ratio of the entrainer, and the volume fraction of ethanol in the entrainer on the nicotine yield in supercritical fluid extraction (SFE) at 25 MPa for 120 min were discussed. By using 90% ethanol (a raw material mass-to-volume ratio of 1:5) as the entrainer, we obtained the highest nicotine yield of 0.49% at 65 °C. Meanwhile, the purity of the crude extract was 61.71%, and after purification, it increased to 97.57%. In this way, we can not only obtain nicotine with market value but also further reduce the harm to the environment caused by tobacco waste disposal

A Zeroth-Order Adaptive Learning Rate Method to Reduce Cost of Hyperparameter Tuning for Deep Learning

Due to powerful data representation ability, deep learning has dramatically improved the state-of-the-art in many practical applications. However, the utility highly depends on fine-tuning of hyper-parameters, including learning rate, batch size, and network initialization. Although many first-order adaptive methods (e.g., Adam, Adagrad) have been proposed to adjust learning rate based on gradients, they are susceptible to the initial learning rate and network architecture. Therefore, the main challenge of using deep learning in practice is how to reduce the cost of tuning hyper-parameters. To address this, we propose a heuristic zeroth-order learning rate method, Adacomp, which adaptively adjusts the learning rate based only on values of the loss function. The main idea is that Adacomp penalizes large learning rates to ensure the convergence and compensates small learning rates to accelerate the training process. Therefore, Adacomp is robust to the initial learning rate. Extensive experiments, including comparison to six typically adaptive methods (Momentum, Adagrad, RMSprop, Adadelta, Adam, and Adamax) on several benchmark datasets for image classification tasks (MNIST, KMNIST, Fashion-MNIST, CIFAR-10, and CIFAR-100), were conducted. Experimental results show that Adacomp is not only robust to the initial learning rate but also to the network architecture, network initialization, and batch size

A Novel AP2/ERF Transcription Factor CR1 Regulates the Accumulation of Vindoline and Serpentine in Catharanthus roseus

As one type of the most important alkaloids in the world, terpenoid indole alkaloids (TIAs) show a wide range of pharmaceutical activities that are beneficial for clinical treatments. Catharanthus roseus produces approximately 130 identified TIAs and is considered to be a model plant to study TIA biosynthesis. In order to increase the production of high medical value metabolites whose yields are extremely low in C. roseus, genetic engineering combined with transcriptional regulation has been applied in recent years. By using bioinformatics which is based on RNA sequencing (RNA-seq) data from methyl jasmonate (MeJA)-treated C. roseus as well as phylogenetic analysis, the present work aims to screen candidate genes that may be involved in the regulation of TIA biosynthesis, resulting in a novel AP2/ERF transcription factor, CR1 (Catharanthus roseus 1). Subsequently, virus-induced gene silencing (VIGS) of CR1 was carried out to identify the involvement of CR1 in the accumulations of several TIAs and quantitative real-time PCR (qRT-PCR) was then applied to detect the expression levels of 7 genes in the related biosynthetic pathway in silenced plants. The results show that all the 7 genes were upregulated in CR1-silenced plants. Furthermore, metabolite analyses indicate that silencing CR1 could increase the accumulations of vindoline and serpentine in C. roseus. These results suggest a novel negative regulator which may be involved in the TIAs biosynthetic pathway