Hybridization assay of insect antifreezing protein gene by novel multilayered porous silicon nucleic acid biosensor

A fabrication of a novel simple porous silicon polybasic photonic crystal with symmetrical structure has been reported as a nucleic acid biosensor for detecting antifreeze protein gene in insects (Microdera puntipennis dzhungarica), which would be helpful in the development of some new transgenic plants with tolerance of freezing stress. Compared to various porous silicon-based photonic configurations, porous silicon polytype layered structure is quite easy to prepare and shows more stability; moreover, polybasic photonic crystals with symmetrical structure exhibit interesting optical properties with a sharp resonance in the reflectance spectrum, giving a higher Q factor which causes higher sensitivity for sensing performance. In this experiment, DNA oligonucleotides were immobilized into the porous silicon pores using a standard crosslink chemistry method. The porous silicon polybasic symmetrical structure sensor possesses high specificity in performing controlled experiments with non-complementary DNA. The detection limit was found to be 21.3nM for DNA oligonucleotides. The fabricated multilayered porous silicon-based DNA biosensor has potential commercial applications in clinical chemistry for determination of an antifreeze protein gene or other genes.     

靶向UL27shRNA抑制Ⅱ型单纯疱疹病毒在HEK293细胞中的复制

按照shRNA(small hairpin RNA)设计原则,针对Ⅱ型单纯疱疹病毒(herpes simplex virus type 2, HSV-2)的UL27基因序列保守区域筛选设计、合成4条干扰靶序列并构建表达UL27序列特异性siRNA(short interfering RNA)的质粒载体pGPU6/GFP/Neo．通过脂质体介导重组表达载体转染HEK293细胞 (human embryonic kidney 293 cell)再接种HSV-2．采用实时荧光定量PCR(real-time fluorescent quantitative PCR)技术检测UL27各组的mRNA转录水平,终点滴定法检测细胞上清液中的病毒滴度,四甲基偶氮唑盐(four methyl thiazolyl tetrazolium, MTT)法测定细胞存活率,Western印迹法检测蛋白表达效果．结果显示,UL27shRNA75组对UL27基因mRNA表达抑制效果最佳,同时能显著抑制感染细胞的CPE(cytopathic effect, CPE),降低上清液中的病毒感染滴度,提高细胞的生存率,抑制UL27基因的蛋白表达．提示本研究构建的pGPU6/GFP/Neo-UL27表达载体能在细胞水平上不同程度地干扰HSV-2 UL27基因表达,抑制HSV-2在HEK293细胞中复制．     

Survival prediction in patients with colon adenocarcinoma via multiomics data integration using a deep learning algorithm

The present study proposed a deep learning (DL) algorithm to predict survival in patients with colon adenocarcinoma (COAD) based on multiomics integration. The survival-sensitive model was constructed using an autoencoder for DL implementation based on The Cancer Genome Atlas (TCGA) data of patients with COAD. The autoencoder framework was compared with PCA, NMF, t-SNE, and univariable Cox-PH model for identifying survival-related features. The prognostic robustness of the inferred survival risk groups was validated using three independent confirmation cohorts. Differential expression analysis, Pearson’s correlation analysis, construction of miRNA–target gene network, and function enrichment analysis were performed. Two risk groups with significant survival differences were identified in TCGA set using the autoencoder-based model (log-rank P-value = 5.51e⁻⁰⁷). The autoencoder framework showed superior performance compared with PCA, NMF, t-SNE, and the univariable Cox-PH model based on the C-index, log-rank P-value, and Brier score. The robustness of the classification model was successfully verified in three independent validation sets. There were 1271 differentially expressed genes, 10 differentially expressed miRNAs, and 12 hypermethylated genes between the survival risk groups. Among these, miR-133b and its target genes (GNB4, PTPRZ1, RUNX1T1, EPHA7, GPM6A, BICC1, and ADAMTS5) were used to construct a network. These genes were significantly enriched in ECM–receptor interaction, focal adhesion, PI3K–Akt signaling pathway, and glucose metabolism-related pathways. The risk subgroups obtained through a multiomics data integration pipeline using the DL algorithm had good robustness. miR-133b and its target genes could be potential diagnostic markers. The results would assist in elucidating the possible pathogenesis of COAD.     

Inhibition kinetics of acetosyringone on xylanase in hydrolysis of hemicellulose

ABSTRACT

Many phenolic compounds, derived from lignin during the pretreatment of lignocellulosic biomass, could obviously inhibit the activity of cellulolytic and hemicellulolytic enzymes. Acetosyringone (AS) is one of the phenolic compounds produced from lignin degradation. In this study, we investigated the inhibitory effects of AS on xylanase activity through kinetic experiments. The results showed that AS could obviously inhibit the activity of xylanase in a reversible and noncompetitive binding manner (up to 50% activity loss). Inhibitory kinetics and constants of xylanase on AS were conducted by the HCH-1 model (β = 0.0090 ± 0.0009 mM^?1). Furthermore, intrinsic and 8-anilino-1-naphthalenesulfonic (ANS)-binding fluorescence results showed that the tertiary structure of AS-mediated xylanase was altered. These findings provide new insights into the role of AS in xylanase activity. Our results also suggest that AS was an inhibitor of xylanase and targeting AS was a potential strategy to increase xylose production.     

Allicin suppresses growth and metastasis of gastric carcinoma: the key role of microRNA-383-5p-mediated inhibition of ERBB4 signaling

ABSTRACT

Allicin is a natural product suppressing the progression of gastric carcinoma (GC). In the current study, the mechanism underlying the anti-GC effect of allicin was explored by focusing on the role of miR-383-5p/ERBB4 signaling. Two GC cell lines were treated with allicin and the effects on viability, apoptosis, migration, invasion, and miR-383-5p/ERBB4 activity in the cells were assessed. The interaction between allicin and miR-383-5p was further explored by inhibiting the miR-383-5p level. Allicin suppressed cell viability and induced apoptosis in both GC cell lines. The compound also inhibited migration and invasion of GC cells, which was associated with the up-regulation miR-383-5p and down-regulation of ERBB4. The inhibition of miR-383-5p by specific inhibitor blocked the anti-GC effect of allicin. Our results demonstrated that allicin contributed to the suppressed growth and metastasis potentials in GC cell lines. The effect was accompanied by an increased level of miR-383-5p and subsequent inhibition of ERBB4.     

Neural spike train reconstruction from calcium imaging via a signal-shape composition model

Science China Life Sciences -     

Effects of Several Environmental Factors on Longevity and Health of the Human Population of Zhongxiang,Hubei, China

Increasing human health and longevity is of global interest. Environmental, genetic, and stochastic factors all affect longevity. Among these factors, the environment is extremely important. To investigate the relationship between the environment and longevity, we studied the environment in Zhongxiang (China), where the inhabitants commonly have long life spans. Air was analyzed for negative oxygen ions, SO₂, and inhalable particles, while drinking water and rice were analyzed for macro- and micro-elements. The air quality in this area was determined to be grade I with high negative oxygen ion content and low SO₂ and inhalable particle contents. Apart from Fe, Mn, and F, all tested elements and the pH were within national standards and World Health Organization guidelines. The percentage of long-lived people in the area was closely related to the macro- and micro-element contents of their staple food, rice. The elements in rice could be classified into three categories according to their effect on longevity: Sr, Ca, Al, Mo, and Se, which were positively correlated with longevity; Fe, Mn, Zn, Cr, P, Mg, and K, which had a weak effect on local longevity, and Cu and Ba, which had a negative effect on longevity.     

Modulating the synthetase activity of penicillin G acylase in organic media by addition of N-methylimidazole: using vinyl acetate as activated acyl donor

This paper reported the modulation of enzyme activity by organic small molecule. The esterification activity of Penicillin G acylase (PGA) was improved more than 70-fold by the addition of 10% N-methylimidazole. Some control experiments have been designed to demonstrate the catalytic specificity of PGA. The structure and the amount of additive were optimized to improve the product yield. The influence of N-methylimidazole on the PGA conformation was investigated by FTIR and autodock simulation. Seven substrates were used to evaluate the effect of structure on the PGA-catalyzed transesterification. A series of products were successfully synthesized with the yield ranged from 56% to 84% and PGA showed specific recognition on the substrate with phenyl group in the presence of 10% N-methylimidazole.