Purification and characterization of a novel alginate lyase from the marine bacterium bacillus sp. Alg07

Alginate is the most abundant carbohydrate in brown algae, accounting for up to 10–45% of the dry weight of brown algae. As a linear homopolymer, alginate is composed of (1–4)-linked α-L-guluronic acid (G) and its C5 epimer β-D-mannuronic acid (M), in blocks of poly-α-L-guluronate (polyG), poly-β-D-mannuronate (polyM), and random heteropolymeric sequences(polyMG). Alginate oligosaccharides with various bioactivities can be prepared through the specific degradation of alginate by alginate lyases. Therefore, alginate lyases which can degrade alginate under mild conditions, have drawn great interest. Although many alginate lyases have been discovered and characterized, few can be applied in industrial production of alginate oligosaccharides. In this study, a novel marine strain with efficient degradation ability toward brown algae was isolated and classified to Bacillus sp. A novel alginate lyase, named as AlgA, with high specific activity was purified from the culture medium of this strain. AlgA had a molecular weight of approximately 60 kDa, wtih the optimal temperature and pH of 40◦C and 7.5,respectively. The activity of AlgA was dependent on sodium chloride and could be considerably enhanced by Mg2+ or Ca2+. Under optimal conditions, the activity of AlgA reached up to 8306.7 U/mg, which is the highest activity recorded for alginate lyases. Moreover, the enzyme was stable over a broad pH range (5.0–10.0), and its activity negligibly changed after 24 h of incubation at 40 ◦C. AlgA exhibited high activity and affinity toward poly-β-D-mannuronate (polyM). These characteristics suggested that AlgA is an endolytic polyM-specific alginate lyase (EC 4.2.2.3). The degradation products of alginate and polyM by AlgA were purified and identified through fast protein liquid chromatography and electrospray ionization mass spectrometry, revealing that AlgA mainly produced disaccharides, trisaccharides, and tetrasaccharide from alginate and disaccharides and trisaccharides from polyM. Therefore, the novel alginate lyase AlgA has potential applications in the production of mannuronic oligosaccharides and poly-α-L-guluronate blocks from alginate

Deep Learning with S-shaped Rectified Linear Activation Units

Rectified linear activation units are important components for state-of-the-art deep convolutional networks. In this paper, we propose a novel S-shaped rectified linear activation unit (SReLU) to learn both convex and non-convex functions, imitating the multiple function forms given by the two fundamental laws, namely the Webner-Fechner law and the Stevens law, in psychophysics and neural sciences. Specifically, SReLU consists of three piecewise linear functions, which are formulated by four learnable parameters. The SReLU is learned jointly with the training of the whole deep network through back propagation. During the training phase, to initialize SReLU in different layers, we propose a "freezing" method to degenerate SReLU into a predefined leaky rectified linear unit in the initial several training epochs and then adaptively learn the good initial values. SReLU can be universally used in the existing deep networks with negligible additional parameters and computation cost. Experiments with two popular CNN architectures, Network in Network and GoogLeNet on scale-various benchmarks including CIFAR10, CIFAR100, MNIST and ImageNet demonstrate that SReLU achieves remarkable improvement compared to other activation functions.Comment: Accepted by AAAI-1

Headspace solid-phase microextraction and gas chromatography–mass spectrometry of volatile components of Chrysanthemum morifolium Ramat

Purpose: To extract and analyze the volatile components of Chrysanthemum morifolium Ramat. 'huaiju' by headspace solid-phase microextraction (HS-SPME) and gas chromatography–mass spectrometry (GC–MS).Methods: Volatile components were extracted by HS-SPME and identified by GC–MS. The relative contents of the components were determined by area normalization.Results: The enhanced SPME conditions of C. morifolium involved sample extraction using a 65 μm polydimethylsiloxane/divinylbenzene extraction fiber after balancing for 40 min at 80 °C. A total of 48 components of the essential oil were identified. The major constituents are 2,6,6-trimethylbicyclo[3.1.1]hept-2-en-4-ol, acetate (15.90 %), 4,6,6-trimethyl-bicyclo[3.1.1]hept-3-en-2-one (14.86 %), 2,7,7-trimethyl-bicyclo[3.1.1]hept-2-en-6-one (13.08 %), and cyclohexene,3-(1,5-dimethyl-4-hexenyl)-6- methylene (5.97 %).Conclusion: HS-SPME and GC–MS are convenient, rapid, and reliable approaches for analyzing the volatile components of C. morifolium.Keywords: Chrysanthemum morifolium Ramat., Headspace Solid-phase Microextraction, Gas Chromatography–Mass Spectrometry, Volatile componen

Disruption of Functional Brain Networks Underlies the Handwriting Deficit in Children With Developmental Dyslexia

Developmental dyslexia (DD) is a neurological-based learning disorder that affects 5-17.5% of children. Handwriting difficulty is a prevailing symptom of dyslexia, but its neural mechanisms remain elusive. Using functional magnetic resonance imaging (fMRI), this study examined functional brain networks associated with handwriting in a copying task in Chinese children with DD (n = 17) and age-matched children (n = 36). We found that dyslexics showed reduced network connectivity between the sensory-motor network (SMN) and the visual network (VN), and between the default mode network (DMN) and the ventral attention network (VAN) during handwriting, but not during drawing geometric figures. Moreover, the connectivity strength of the networks showing group differences was correlated with handwriting speed, reading and working memory, suggesting that the handwriting deficit in DD is linked with disruption of a large-scale brain network supporting motoric, linguistic and executive control processes. Taken together, this study demonstrates the alternations of functional brain networks that underly the handwriting deficit in Chinese dyslexia, providing a new clue for the neural basis of DD

T Cells Development Is Different between Thymus from Normal and Intrauterine Growth Restricted Pig Fetus at Different Gestational Stage

This experiment was conducted to evaluate the development of T cells in intrauterine growth retarded (IUGR) piglets at different gestational stages, and tentatively explore the relationship between T cells development and the Notch signaling pathway. A total of 18 crossbred (Landrace×Large white) primiparous sows were mated at similar weights and estruses and euthanized at d 60, 90 and 110 of gestation with six replicates for each time point. One IUGR and one normal fetus were picked from each litter. The T-cell subsets, mRNA expression of Delta-like1, Delta-like4, Jagged1, and Notch2 genes in the thymus were investigated. Compared to normal piglets, CD3+CD4−CD8+ cells in IUGR fetuses at d 90 was 0.13% lower (p<0.05). At d 110 of gestation CD8+ T cells in IUGR fetuses was 0.19% lower (p<0.05). The percentage of CD8+ T cells was 3.14% lower (p<0.05) of the total T cells in IUGR pigs at d 60. The abundance of Notch2 and Delta-like4 mRNA at d 110 was 20.93% higher and 0.77% (p<0.05) lower, and Delta-like1 mRNA at d 90 was 0.19% (p<0.05) higher compared to normal pigs. These results suggested that normal fetuses had a greater proportion of T-cell subsets at earlier gestation periods, and the Notch signaling pathway was likely partially responsible for these differences to some degree

Altered gut microbiota in temporal lobe epilepsy with anxiety disorders

IntroductionPatients with epilepsy are particularly vulnerable to the negative effects of anxiety disorders. In particular, temporal lobe epilepsy with anxiety disorders (TLEA) has attracted more attention in epilepsy research. The link between intestinal dysbiosis and TLEA has not been established yet. To gain deeper insight into the link between gut microbiota dysbiosis and factors affecting TLEA, the composition of the gut microbiome, including bacteria and fungi, has been examined.MethodsThe gut microbiota from 51 temporal lobe epilepsy patients has been subjected to sequencing targeting 16S rDNA (Illumina MiSeq) and from 45 temporal lobe epilepsy patients targeting the ITS-1 region (through pyrosequencing). A differential analysis has been conducted on the gut microbiota from the phylum to the genus level.ResultsTLEA patients' gut bacteria and fungal microbiota exhibited distinct characteristics and diversity as evidenced by high-throughput sequencing (HTS). TLEA patients showed higher abundances of Escherichia-Shigella (genus), Enterobacterales (order), Enterobacteriaceae (family), Proteobacteria (phylum), Gammaproteobacteria (class), and lower abundances of Clostridia (class), Firmicutes, Lachnospiraceae (family), Lachnospirales (order), and Ruminococcus (genus). Among fungi, Saccharomycetales fam. incertae sedis (family), Saccharomycetales (order), Saccharomycetes (class), and Ascomycota (phylum) were significantly more abundant in TLEA patients than in patients with temporal lobe epilepsy but without anxiety. Adoption and perception of seizure control significantly affected TLEA bacterial community structure, while yearly hospitalization frequency affected fungal community structures in TLEA patients.ConclusionHere, our study validated the gut microbiota dysbiosis of TLEA. Moreover, the pioneering study of bacterial and fungal microbiota profiles will help in understanding the course of TLEA and drive us toward preventing TLEA gut microbiota dysbiosis