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In the U.S., 30–40% of all food produced ends up as waste. By taking advantage of biological processes this waste nutrients can be converted into value-added 2,3-butanediol (2,3-BDO). However, food waste contains live bacteria and fungi which must first be inactivated, a process typically done with autoclaving under high pressure steam. If contaminants are not removed they can out-compete added industrial microbes for nutrients, resulting in lower yields of bio-products. Unfortunately, sterilization methods such as autoclaving greatly increase production time, and increase energy consumption. This creates a demand for novel microorganisms that can out-compete food waste microbiota by natural means without the need for sterilization of food waste. For this study, several Bacillus licheniformis isolates from Yellowstone National Park were investigated for their potential use in the 2,3-BDO industry. B. licheniformis species are a strain of industrial importance as of late, due to the wide metabolic functions and sustainable growth conditions above 45 °C. Whole genomic sequencing data and biochemical classification of B. licheniformis YNP1-TSU, B. licheniformis YNP2-TSU, and B. licheniformis YNP3-TSU were assessed and revealed a wide assortment of anti-microbial peptides and antibodies as well as catabolic genes for assimilation of glucose, fructose, galactose, xylose, arabinose, mannose, starch and sucrose, and linoleic acid. All three B. licheniformis strains had an optimal growth temperature of 50 °C, and were identified as high 2,3-BDO producers. Each strain YNP1-TSU, YNP2-TSU, and YNP3-TSU yielded 0.44 g/g, 0.45 g/g, and 0.43 g/g from mixed sugars found in non-sterilized food waste, respectively.

High-concentration electrolytes (HCEs) can effectively enhance interface stability and cycle performance of Li metal batteries (LMBs). However, HCEs suffer from low ionic conductivity, high viscosity, high cost, and high density. Herein, fluorobenzene (FB) diluted localized high-concentration electrolytes (LHCEs) consisting of lithium bis(fluorosulfonyl)imide (LiFSI)/triethyl phosphate (TEP)/FB are developed. 2.3 M LHCE can reserve concentrated Li

A number of fetal cardiovascular structural defects may alter the hemodynamics of the cardiac chambers resulting in changes in chamber sizes. Quantitative measurements of the sizes of cardiac chambers can augment the diagnostic power of fetal echocardiography.Using a new left atrial volume tracking (LAVT) method, time-left atrial volume curves (TLAVCs) can be automatically obtained. The goal of this study was to examine whether this method can be used to evaluate left atrial volume (LAV) and provide reference values for LAV, and indices of left atrial function in normal human fetuses.204 normal human fetuses were enrolled. Using LAVT, the maximal left atrial volume (LAVmax) and minimal left atrial volume (LAVmin) were measured from TLAVCs. Left atrial ejection fraction (EF) was calculated. The maximal left atrial area (LAAmax) and minimal left atrial area (LAAmin) were measured using manual method tracing.From 21-40 weeks, mean LAVmax increased from 0.27 ml to 4.15 ml and mean LAVmin increased from 0.13ml to 2.26ml, respectively. While the EF remained stable at around 0.43. From 21-40 weeks, mean LAAmax increased from 0.61 cm² to 2.64 cm² and mean LAAmin increased from 0.34 cm² to 1.53 cm².This study establishes reference values for fetal LAV during the second half of gestation. LAVT method has proven to be a feasible method to estimate fetal LAV, suggesting the potential value in assessing left atrial function.

2,3-Butanediol (2,3-BD) is an important platform chemical that can be produced biologically. It is currently fermented below 40 °C using mesophilic strains at acid to neutral pH conditions, but the...

Lignocellulosic biomass is the earth’s most abundant renewable feedstock alternative that comprises of cellulose, hemi-cellulose and lignin. The synergistic action of cellulolytic/xylanolytic enzymes produced by lignocellulolytic micro-organisms such as bacteria, algae and fungi are capable of robust cellulosic biomass deconstruction. Most of the microorganisms dwelling in extreme environmental habitats such as rumen environment, hot/cold springs, deep ocean trenches, acidic/alkaline pH environment have been considered as an attractive producers of hemi/cellulolytic lignocellulolytic and other biotechnological enzymes with enhanced bio-chemical properties essential for industrial bioconversion processes. However, the potential microbial sources of cellulolytic enzymes and the underlying mechanism to achieve this is not fully elucidated. In this review article, first we detail the composition of lignocellulosic biomass. Next, we describe the structure and functions of divergent hydrolytic enzymes (cellulolytic and xylanolytic enzymes) involved in cellulosic biomass degradation. Third, we analyze, outline and unveil the prospective source of microbes encoding exceptionally diverse set of biotechnologically relevant cellulolytic enzymes which are critical to answer the specific ecological question of by whom, where and how cellulosic biomass is degraded in the environment. Finally, this review article features the snapshot about the future developments and perspectives on microbial enzymes, high-throughput techniques and molecular tools that could be exploited to derive those enzymes from the potential sources.

Aluminum (Al) toxicity primarily targets the root tips, inhibiting root growth and function and leading to crop yield losses on acidic soils. Previously we reported using laser capture microdissection (LCM) proteomics to identify Al-induced proteins in the outer layer cells in the transitional zone of tomato root-tips. This study aims to further characterize Al-induced proteomic dynamics from the outer to interior tissues, thus providing a panoramic view reflecting Al resistance in the root tip as a whole in tomatoes. Three types of cells were isolated via LCM from the basal 350-400 μm (below cell elongation regions) of root tips using tomato (Solanum lycopersicum) 'Micro-Tom' plants. Type I and Type II were from Al-treated plants. Type I included cells of the outer three layers, i.e., the epidermis and cortex initials and the quiescent center (QC) in root apical meristem (RAM), and Type II possessed the interior tissues of the same region. Type III contained cells from the non-Al-treated root tips collected in the same region as Type I. Two tandem mass tag (TMT) proteomics analyses with three biological replicates for each sample type were conducted. The TMTexp1 (comparing Type I and Type II) identified 6575 quantifiable proteins and 178 different abundance proteins (DAPs). The TMTexp2 (comparing Type I and Type III) identified 7197 quantifiable proteins and 162 DAPs. Among all quantified proteins (7685) from the two TMT experiments, 6088 (79%) proteins, including 313 DAPs (92% of the 340 total), were identified in all tissues. A model reflecting the tissue-specific Al-resistance mechanism was proposed, in which the level of the citrate transporter MATE protein, involved in Al exclusion, accumulated to the highest level in the outer-layer cells but decreased toward the interior of root-tips (which concurs with the tissue-specific importance in Al resistance). Proteins for biosynthesis of ethylene and jasmonic acid, proteolytic enzymes, stress-responsive proteins, and cell wall modeling were affected by Al treatment, some in a cell type-specific manner. The KEGG metabolite pathways enriched with these DAPs changed depending on the cell types. This study demonstrated the advantage of using the tissue/cell-specific analysis for identifying proteins and their dynamic changes directly associated with Al resistance in the root-tip region. The proteomics datasets have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (https://www.ebi.ac.uk/pride/) with the dataset identifier as PXD021994 under project title: Proteomics studies of outer and inner cellular layers of tomato root-tips for Al stress, Project DOI: 10.6019/ PXD021994; and PXD018234 under Project title: Al-induced root proteomics changes in stress-acclimated tomato plant, Project DOI: https://doi.org/10.6019/PXD018234. SIGNIFICANCE: This paper presents the method of using laser capture microdissection (LCM) to collect homogenous cell-type specific tissue samples from the outer layers and inner central regions of tomato root-tips. The tandem mass tag-proteomics analysis showed that the outer-layer cells expressed proteomes that were different from the inner tissues of Al-treated root-tips; proteins related to resistance/tolerance to Al toxicity were highly accumulated in the outer-layer cells. Furthermore, the Al-treated outer-layer cells expressed proteomes which were different from the non-Al treated counterpart cells. This study has provided the first dataset of proteins differentiating from the outer to inner layers of cells in Al-treated root-tips. It provided convincing experimental evidences demonstrating the single-cell type proteomics as a powerful analytical approach to identify Al tolerance mechanisms in plants. The analytical procedure of LCM-tandem mass tag-quantitative proteomics analysis has a broad application for proteomics analysis of spatially separated cells in complex tissues.

As voice dialog applications (VDAs, e.g., Siri, 1 1 http://www.apple.com/ios/siri/ . Cortana, 2 2 http://www.microsoft.com/en-us/mobile/campaign-cortana/ . Google Now 3 3 http://www.google.com/landing/now/ . ) are increasing in popularity, inferring emotions from the large-scale internet voice data generated from VDAs can help give a more reasonable and humane response. However, the tremendous amounts of users in large-scale internet voice data lead to a great diversity of users accents and expression patterns. Therefore, the traditional speech emotion recognition methods, which mainly target acted corpora, cannot effectively handle the massive and diverse amount of internet voice data. To address this issue, we carry out a series of observations, find suitable emotion categories for large-scale internet voice data, and verify the indicators of the social attributes (query time, query topic, and users location) and emotion inferring. Based on our observations, two different strategies are employed to solve the problem. First, a deep sparse neural network model that uses acoustic information, textual information, and three indicators (a temporal indicator, descriptive indicator, and geo-social indicator) as the input is proposed. Then, to capture the contextual information, we propose a hybrid emotion inference model that includes long short-term memory to capture the acoustic features and a latent dirichlet allocation to extract text features. Experiments on 93 000 utterances collected from the Sogou Voice Assistant 4 4 http://yy.sogou.com . (Chinese Siri) validate the effectiveness of the proposed methodologies. Furthermore, we compare the two methodologies and give their advantages and disadvantages.

Microbes are ubiquitously distributed in nature and are a critical part of the holobiont fitness. They are perceived as the most potential biochemical reservoir of inordinately diverse and multi-functional enzymes. The robust nature of the microbial enzymes with thermostability, pH stability and multi-functionality make them potential candidates for the efficient biotechnological processes under diverse physio-chemical conditions. The need for sustainable solutions to various environmental challenges has further surged the demand for industrial enzymes. Fueled by the recent advent of recombinant DNA technology, genetic engineering, and high-throughput sequencing and omics techniques, numerous microbial enzymes have been developed and further exploited for various industrial and therapeutic applications. Most of the hydrolytic enzymes (protease being the dominant hydrolytic enzyme) have broad range of industrial uses such as food and feed processing, polymer synthesis, production of pharmaceuticals, manufactures of detergents, paper and textiles, and bio-fuel refinery. In this review article, after a short overview of microbial enzymes, an approach has been made to highlight and discuss their potential relevance in biotechnological applications and industrial bio-processes, significant biochemical characteristics of the microbial enzymes, and various tools that are revitalizing the novel enzymes discovery.

Made available in DSpace on 2021-06-25T10:12:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-02-15 U.S. Department of Agriculture Flavonols are gaining increasing interests due to their diverse health benefits for humans. Broccoli is a main flavonol source in our diet, but the genetic variation of flavonols and their correlation with antioxidant capacity remain to be understood. Here, we examined variations of the two major flavonols kaempferol and quercetin in florets and leaves of 15 diverse broccoli accessions by ultra-performance liquid chromatography. Broccoli accumulated more kaempferol than quercetin in most of the accessions tested, with the ratios varying from 4.4 to 27.9 in leaves and 0.4 to 4.4 in florets. Total flavonoids showed 2.5-fold and 3.3-fold differences in leaves and florets of these accessions, respectively. Principle component analysis revealed that flavonols, along with the key biosynthetic pathway genes, correlated with antioxidant capacity related indicators. This study provides important information for broccoli flavonol genotypic variations and correlation with antioxidant capacity, and will facilitate the development of flavonol enriched cultivars in broccoli. Robert W. Holley Center for Agriculture and Health USDA-ARS Cornell University Anhui Provincial Engineering Laboratory for Efficient Utilization of Featured Resource Plants College of Life Sciences Huaibei Normal University Department of Soil Science Federal University of Lavras, Zip Code 3037 School of Science and Engineering São Paulo State University (UNESP), Zip Code 17602-496 Department of Agriculture Federal University of Lavras, Zip Code 3037 Department of Agricultural and Environmental Sciences Tennessee State University Plant Breeding and Genetics Section School of Integrative Plant Science Cornell University School of Science and Engineering São Paulo State University (UNESP), Zip Code 17602-496

Conversion of food waste into 2,3-butanediol (2,3-BDO) via microbial fermentation provides a promising way to reduce waste disposal to landfills and produce sustainable chemicals. However, sterilization of food waste, an energy- and capital-costly process, is generally required before fermentation to avoid any contamination, which reduces the energy net output and economic feasibility of food waste fermentation. In this study, we investigated the non-sterile fermentation of food waste to produce 2,3-BDO using a newly isolated thermophilic and alkaliphilic B. licheniformis YNP5-TSU. Three unitary food waste samples (i.e., pepper, pineapple, cabbage wastes) and one miscellaneous food waste mixture were respectively inoculated with B. licheniformis YNP5-TSU under non-sterile conditions. At 50 °C and an initial pH of 9.0, B. licheniformis YNP5-TSU was able to consume all sugars in food waste and produce 5.2, 5.9, 5.9 and 4.3 g/L of 2,3-BDO within 24 h from pepper, pineapple, cabbage and miscellaneous wastes, respectively, corresponding to a yield of 0.40, 0.38, 0.41 and 0.41 g 2,3-BDO/g sugar. These 2,3-BDO concentrations and yields from the non-sterile fermentations were comparable to those from the traditional sterile fermentations, which produced 4.0–6.8 g/L of 2,3-BDO with yields of 0.31–0.48 g 2,3-BDO/g sugar. Moreover, B. licheniformis was able to ferment various food wastes (pepper, pineapple and miscellaneous wastes) without any external nutrient addition and produce similar 2,3-BDO quantities. The non-sterile fermentation of food waste using novel thermophilic and alkaliphilic B. licheniformis YNP5-TSU provides a robust and energy-efficient approach to convert food waste to high-value chemicals.

Switchgrass plants were grown in a Sandwich tube system to induce gradual drought stress by withholding watering. After 29 days, the leaf photosynthetic rate decreased significantly, compared to the control plants which were watered regularly. The drought-treated plants recovered to the same leaf water content after three days of re-watering. The root tip (1cm basal fragment, designated as RT1 hereafter) and the elongation/maturation zone (the next upper 1 cm tissue, designated as RT2 hereafter) tissues were collected at the 29th day of drought stress treatment, (named SDT for severe drought treated), after one (D1W) and three days (D3W) of re-watering. The tandem mass tags mass spectrometry-based quantitative proteomics analysis was performed to identify the proteomes, and drought-induced differentially accumulated proteins (DAPs). From RT1 tissues, 6156, 7687, and 7699 proteins were quantified, and 296, 535, and 384 DAPs were identified in the SDT, D1W, and D3W samples, respectively. From RT2 tissues, 7382, 7255, and 6883 proteins were quantified, and 393, 587, and 321 proteins DAPs were identified in the SDT, D1W, and D3W samples. Between RT1 and RT2 tissues, very few DAPs overlapped at SDT, but the number of such proteins increased during the recovery phase. A large number of hydrophilic proteins and stress-responsive proteins were induced during SDT and remained at a higher level during the recovery stages. A large number of DAPs in RT1 tissues maintained the same expression pattern throughout drought treatment and the recovery phases. The DAPs in RT1 tissues were classified in cell proliferation, mitotic cell division, and chromatin modification, and those in RT2 were placed in cell wall remodeling and cell expansion processes. This study provided information pertaining to root zone-specific proteome changes during drought and recover phases, which will allow us to select proteins (genes) as better defined targets for developing drought tolerant plants. The mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD017441.

Additional file 4 Figure S1. Multiple sequence alignment of A/B hydrolase superfamily proteins on B. cereus tsu1 genome.

To understand speakers’ attitudes and intentions in real Voice Dialogue Applications (VDAs), effective emphasis inference from users’ queries may play an important role. However, in VDAs, there are tremendous amount of uncertain speakers with a great diversity of users’ dialects, expression preferences, which challenge the traditional emphasis detection methods. In this paper, to better infer emphasis for real voice data, we propose an attentive multimodal neural network. Specifically, first, beside the acoustic features, extensive textual features are applied in modelling. Then, considering the feature in-dependency, we model the multi-modal features utilizing a Multi-path convolutional neural network (MCNN). Furthermore, combining high-level multi-modal features, we train an emphasis classifier by attending on the textual features with an attention-based bidirectional long short-term memory network (ABLSTM), to comprehensively learn discriminative features from diverse users. Our experimental study based on a real-world dataset collected from Sogou Voice Assistant (https://yy.sogou.com/) show that our method outperforms (over 1.0–15.5% in terms of F1 measure) alternative baselines.

A disorder in pears that is known as &lsquo, hard-end&rsquo, fruit affects the appearance, edible quality, and market value of pear fruit. RNA-Seq was carried out on the calyx end of &lsquo, Whangkeumbae&rsquo, pear fruit with and without the hard-end symptom to explore the mechanism underlying the formation of hard-end. The results indicated that the genes in the phenylpropanoid pathway affecting lignification were up-regulated in hard-end fruit. An analysis of differentially expressed genes (DEGs) identified three NAC transcription factors, and RT-qPCR analysis of PpNAC138, PpNAC186, and PpNAC187 confirmed that PpNAC187 gene expression was correlated with the hard-end disorder in pear fruit. A transient increase in PpNAC187 was observed in the calyx end of &lsquo, fruit when they began to exhibit hard-end symptom. Concomitantly, the higher level of PpCCR and PpCOMT transcripts was observed, which are the key genes in lignin biosynthesis. Notably, lignin content in the stem and leaf tissues of transgenic tobacco overexpressing PpNAC187 was significantly higher than in the control plants that were transformed with an empty vector. Furthermore, transgenic tobacco overexpressing PpNAC187 had a larger number of xylem vessel elements. The results of this study confirmed that PpNAC187 functions in inducing lignification in pear fruit during the development of the hard-end disorder.

Teaching style plays an influential role in helping students to achieve academic success. In this paper, we explore a new problem of effectively understanding teachers' teaching styles. Specifically, we study 1) how to quantitatively characterize various teachers' teaching styles for various teachers and 2) how to model the subtle relationship between cross-media teaching related data (speech, facial expressions and body motions, content et al.) and teaching styles. Using the adjectives selected from more than 10,000 feedback questionnaires provided by an educational enterprise, a novel concept called Teaching Style Semantic Space (TSSS) is developed based on the pleasure-arousal dimensional theory to describe teaching styles quantitatively and comprehensively. Then a multi-task deep learning based model, Attention-based Multi-path Multi-task Deep Neural Network (AMMDNN), is proposed to accurately and robustly capture the internal correlations between cross-media features and TSSS. Based on the benchmark dataset, we further develop a comprehensive data set including 4,541 full-annotated cross-modality teaching classes. Our experimental results demonstrate that the proposed AMMDNN outperforms (+0.0842 in terms of the concordance correlation coefficient (CCC) on average) baseline methods. To further demonstrate the advantages of the proposed TSSS and our model, several interesting case studies are carried out, such as teaching styles comparison among different teachers and courses, and leveraging the proposed method for teaching quality analysis., ACM Muitimedia 2019

Switchgrass (Panicum virgatum L.) is a perennial fodder grass and well known as a model renewable bioenergy crop. The plant's high production of biomass for biofuel supply is due to its fast-growing and wide adaptation properties. Very little studies and data are available about microRNAs (miRNAs) in this important biofuel crop. This situation demands to focus and identify new miRNAs and also to study their expressional analysis. In current research, a combination of computational and expressional approaches is applied to profile and characterize miRNAs in switchgrass and analyze some of them under drought stress. A total of 158 new miRNAs belonging to 83 families are identified and characterized from switchgrass expressed sequence tags (ESTs) and genomic survey sequences (GSS). In addition, five pre-miRNA clusters as well as four sense and antisense pre-miRNAs are also predicted from these newly identified miRNAs. Furthermore, 39 miRNAs were randomly selected and subjected to quantitative real-time RT-PCR expressional studies in root, leaf and stem of switchgrass under drought stress. A set of 13, 20 and 25 miRNAs are found as drought responding miRNAs in root, stem and leaf respectively. A total of 894 putative targets are also predicted for 158 switchgrass' miRNAs. These targets play roles in metabolism, transcription factor, signaling pathways, growth & development, stress-related, transport protein and other vital processes. Such findings in switchgrass improved the baseline data of miRNAs and their targets. This data can be utilized to fine-tune this important bioenergy crop under biotic and abiotic stresses. Furthermore, it can also be used for the improvement of biofuel properties of the plant.

Conventional liquid electrolytes applied in lithium-ion batteries suffer from high flammability, lithium dendrites and leakage. Gel polymer electrolytes (GPEs) are promising alternative electrolytes owing to their high ionic conductivities and enhanced safeties. Nevertheless, the flammable plasticizers of GPEs still bring safety hazards for the batteries. To address these issues, nonflammable highly-fluorinated quasi-solid-state polymer electrolytes (ED@PVDF) with ultrahigh ionic conductivities, excellent flame-retardant properties and superior cycling stability are developed. ED@PVDF possesses three-dimensional polymeric network within the framework of electrospun PVDF fibers, which is fabricated by thiol-ene click reaction. Highly-fluorinated carbonates (fluoroethylene carbonate and methyl 2,2,2-trifluoroethyl carbonate) are employed as plasticizers for ED@PVDF to improve flame-retardant property and enhance compatibility with anodes. Nonflammable ED@PVDF exhibits remarkable flame resistance, the highest ionic conductivity (4.41 mS cm−1 at 30 °C) among the nonflammable polymer electrolytes and wide electrochemical windows (5.6 V). ED@PVDF can promote the generation of LiF-rich solid electrolyte interphase and effectively restrain dendrite growth on Li metal anodes. ED@PVDF endows LiFePO4 cells with outstanding rate capability (specific capacity of 123.8 mAh g−1 at 5C rate) and superior cycling stability (capacity retention of 81.4% over 1000 cycles).

In previous work, we reported on the isolation and genome sequence analysis ofBacillus cereusstrain tsu1 NCBI accession number JPYN00000000. The 36 scaffolds in the assembled tsu1 genome were all aligned withB. cereusB4264 genome with variations. Genes encoding for xylanase and cellulase and the cluster of genes in the poly-3-hydroxybutyrate (PHB) biosynthesis pathway were identified in tsu1 genome. The PHB accumulation inB. cereustsu1 was initially identified using Sudan Black staining and then confirmed using high-performance liquid chromatography. Physical properties of these PHB extracts, when analyzed with Raman spectra and Fourier transform infrared spectroscopy, were found to be comparable to the standard compound. The five PHB genes in tsu1(phaA,phaB,phaR,phaC,andphaP)were cloned and expressed with TOPO cloning, and the recombinant proteins were validated using peptide mapping of in-gel trypsin digestion followed by mass spectrometry analysis. The recombinantE. coliBL21 (DE3) (over)expressingphaCwas found to accumulate PHB particles. The cellulolytic activity of tsu1 was detected using carboxymethylcellulose (CMC) plate Congo red assay and the shift towards low-molecular size forms of CMC revealed by gel permeation chromatography in CMC liquid culture and the identification of a cellulase in the secreted proteome.

To investigate the responses of plant photosynthesis and chlorophyll fluorescence to excessive sulfur fumigation stress (Sulfur) alleviated by pre-treated salt in the soil (Salt), seedlings of a tomato cultivar (Solanum lycopersicum L. ‘Money Maker’) were exposed to the Sulfur with or without the Salt treatment for 15 h. Leaf fresh weight, dry weight, chlorophyll (Chl) content, carotenoid (Car) content, photosynthesis and chlorophyll fluorescence parameters were measured. The results showed that the Sulfur treatment significantly decreased leaf fresh weight, dry weight, Chl and Car contents, net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), maximum quantum efficiency of photosystem II (PSII) photochemistry (Fv/Fm), actual photochemical efficiency of PSII (ФPSII), photochemical quenching coefficient (qP), electron transport rate (ETR), and the effective quantum yield of PSII photochemistry (F′v/F′m). In addition, the Sulfur treatment significantly increased intercellular CO2 concentration (Ci) and non-photochemical quenching coefficients (qN). Plants in soil pre-treated with salt clearly experienced less damage from sulfur toxicity, and these plants were able to retain higher leaf mass per area, greater total Chl and Car contents and photosynthetic activities, and to maintain the integrity of their chlorophyll fluorescence systems than fumigated plants growing in soil that was not pre-treated. Reduced leaf photosynthesis in the Sulfur treatment was due to non-stomatal limitation, and to disturbance of the chlorophyll fluorescence system which needs more energy consumption for thermal dissipation. Our results showed that a cross-tolerance exists between the salt stress and extreme sulfur fumigation stress, and plants pre-treated with salt provided some protection against excessive sulfur toxicity.

Background Bacillus cereus is a bacterial species which grows efficiently on a wide range of carbon sources and accumulates biopolymer poly-hydroxybutyrate (PHB) up to 80% cell dry weight. PHB is an aliphatic polymer produced and stored intracellularly as a reservoir of carbon and energy, its mobilization is a key biological process for sporulation in Bacillus spp. Previously, B. cereus tsu1 was isolated and cultured on rapeseed cake substrate (RCS), with maximum of PHB accumulation reached within 12 h, and depleted after 48 h. Fore-spore and spore structure were observed after 24 h culture. Results Quantitative proteomic analysis of B. cereus tsu1 identified 2952 quantifiable proteins, and 244 significantly changed proteins (SCPs) in the 24 h:12 h pair of samples, and 325 SCPs in the 48 h:12 h pair of samples. Based on gene ontology classification analysis, biological processes enriched only in the 24 h:12 h SCPs include purine nucleotide metabolism, protein folding, metal ion homeostasis, response to stress, carboxylic acid catabolism, and cellular amino acid catabolism. The 48 h:12 h SCPs were enriched into processes including carbohydrate metabolism, protein metabolism, oxidative phosphorylation, and formation of translation ternary structure. A key enzyme for PHB metabolism, poly(R)-hydroxyalkanoic acid synthase (PhaC, KGT44865) accumulated significantly higher in 12 h-culture. Sporulation related proteins SigF and SpoEII were significantly higher in 24 h-samples. Enzymes for nitrate respiration and fermentation accumulated to the highest abundance level in 48 h-culture. Conclusions Changes in proteome of B. cereus tsu1 during PHB intracellular mobilization were characterized in this study. The key enzyme PhaC for PHB synthesis increased significantly after 12 h-culture which supports the highest PHB accumulation at this time point. The protein abundance level of SpoIIE and SigF also increased, correlating with sporulation in 24 h-culture. Enzymes for nitrate respiration and fermentation were significantly induced in 48 h-culture which indicates the depletion of oxygen at this stage and carbon flow towards fermentative growth. Results from this study provide insights into proteome profile changes during PHB accumulation and reuse, which can be applied to achieve a higher PHB yield and to improve bacterial growth performance and stress resistance.

PpCAD2 was originally isolated from the ‘Wangkumbae’ pear (Pyrus pyrifolia Nakai), and it encodes for cinnamyl alcohol dehydrogenase (CAD), which is a key enzyme in the lignin biosynthesis pathway. In order to verify the function of PpCAD2, transgenic tomato (Solanum lycopersicum) ‘Micro-Tom’ plants were generated using over-expression constructs via the agrobacterium-mediated transformation method. The results showed that the PpCAD2 over-expression transgenic tomato plant had a strong growth vigor. Furthermore, these PpCAD2 over-expression transgenic tomato plants contained a higher lignin content and CAD enzymatic activity in the stem, leaf and fruit pericarp tissues, and formed a greater number of vessel elements in the stem and leaf vein, compared to wild type tomato plants. This study clearly indicated that overexpressing PpCAD2 increased the lignin deposition of transgenic tomato plants, and thus validated the function of PpCAD2 in lignin biosynthesis.

Optimization of cellulase activity is vital for synthesizing the end-products of second generation biofuel production. The slightest change in fermentation parameters can reduce the secretion of necessary enzymes to degrade cellulosic biomass. Determining the ecological effects of certain key media components is essential to understand how bacterial species will respond in a fluid environment. For our experiment a cellulosic media was designed to enhance the industrially important thermophile, Bacillus licheniformis YNP5-TSU. After several attempts to simplify the carboxymethylcellulose (CMC) media composition, impaired biofilm maturation and cellulase activity was noticed. This negative artifact occurred only when magnesium sulphate was removed from media. To analyze the shift in gene expression caused by magnesium stress, biofilm associated proteins were extracted from both control (4.0 mM MgSO4) and magnesium depleted (0.0 mM MgSO4) media at 24 hr and 48 hr incubation periods. These proteins were quantified through isobaric labeling and raw data generated from nanoLC-MS/MS identified over 2,000 proteins from the Bacillus licheniformis YNP5-TSU proteome (NCBI accession number MEDD00000000). After statistical normalization and false discovery rate were calculated, a total of 161 proteins from magnesium depleted media and 238 proteins from control media were deemed statistically relevant. A closer look through STRING interconnected webs, data mining, and NCBI annotations revealed several up/down regulated proteins that had linkage to biofilm formation and cellulase secretion. In this study we are able to provide significant evidence that; (1) biofilm maturation and cellulase production are highly correlated and (2), their optimization is dependent on the expression of several key proteins.

Emphasis detection is important for user intention understanding in human-computer interaction scenario. Techniques have been developed to detect the emphatic words in speech, but challenges still exist in Voice Dialogue Applications (VDAs): the tremendous non-specific speakers and their various expressions. In this work, we present a novel approach to automatically detect emphasis in VDAs by using multi-channel convolutional bi -directional long short-term memory neural networks (MC-BLSTM), which can learn various expressions of large amounts of speakers and long span temporal dependencies across speech trajectories. In particular, we first use a multi-channel convolutional component in the proposed approach to extract high-level representation of input acoustic features for emphasis detection. The experimental results on a 3400 real-world dataset collected from Sogou 11http://yy.sogou.com Voice Assistant outper-form current state-of-the-art baseline systems (+6.2% in terms of F1-measure on average).

Gram’s Iodine Assay is currently used to detect endoglucanase, a cellulase enzyme which cleaves β-1,4-glycosidic bonds in carboxymethylcellulose (CMC). When a zone of degradation was observed around non-cellulolytic Escherichia coli JM109 with the use of Gram’s Iodine, the assay was further examined. Additional cellulolytic bacteria were chosen to display these inconsistencies. Bacillus thuringiensis subsp. Kurstaki (Btk) and Cellulomonas persica, known to possess endoglucanase, were incubated at 30 °C for 48 h on several different media; 1.5 % agar only, Davis minimal media, CMC agar, non-CMC agar, and Phytagel CMC. After the incubation period all plates were flooded with Gram’s Iodine for 3–5 min. A clear ring of degradation was identified around colonies in plates containing no cellulose and plates containing agar only. When agar was removed as the solidifying agent and substituted with Phytagel, zones of clearing around cellulolytic organisms were altered. These findings indicate that agar alone can cause additional artifacts and should be replaced by other solidifying agents as well as supplementation of the Congo Red Assay. Taking these precautions can overcome inconsistency problems for future cellulolytic screenings.