Conformational change of syntaxin linker region induced by Munc13s initiates SNARE complex formation in synaptic exocytosis

The soluble N-ethylmaleimide-sensitive factor attachment protein receptor (SNARE) protein syntaxin-1 adopts a closed conformation when bound to Munc18-1, preventing binding to synaptobrevin-2 and SNAP-25 to form the ternary SNARE complex. Although it is known that the MUN domain of Munc13-1 catalyzes the transition from the Munc18-1/syntaxin-1 complex to the SNARE complex, the molecular mechanism is unclear. Here, we identified two conserved residues (R151, I155) in the syntaxin-1 linker region as key sites for the MUN domain interaction. This interaction is essential for SNARE complex formation in vitro and synaptic vesicle priming in neuronal cultures. Moreover, this interaction is important for a tripartite Munc18-1/syntaxin-1/MUN complex, in which syntaxin-1 still adopts a closed conformation tightly bound to Munc18-1, whereas the syntaxin-1 linker region changes its conformation, similar to that of the LE mutant of syntaxin-1 when bound to Munc18-1. We suggest that the conformational change of the syntaxin-1 linker region induced by Munc13-1 initiates ternary SNARE complex formation in the neuronal system.     

High-level expression,purification and properties of an Endochitinase gene without signal peptide from Lecanicillium lecanii 43H in Pichia pastoris

Molecular Biology Reports - Chitinases play the key role in hydrolysis of chitin, a huge organic carbon reservoir on earth, into monomeric sugars and their eventual conversion into valuable...     

Auto-adaptive Alpha Allocation: A Strategy to Mitigate Risk on Study Assumptions

In some clinical development programs, there are potential biomarkers with promising but uncertain predictive effect, while the probability of success in the overall population cannot be readily dismissed. It is risky to focus only on the overall population, or just the biomarker subpopulation. In 2009, Chen and Beckman proposed a Bayesian decision framework to optimize the type I error rate (alpha) allocation in a Phase III clinical study with possible predictive subset effect. The utilization of internal data in this framework is of particular interest because it provides an opportunity to mitigate the potential risk of misspecified study assumptions using an auto-adaptive strategy. In this paper, we examine this auto-adaptive strategy in detail through extensive numerical case studies and provide guidance on the appropriate use of partial current trial (internal) data in this data-driven optimization framework. We show that internal data can be used to inform the alpha allocation to hypothesis testing in the overall population and the subgroup. The resulting adaptive testing strategy is robust with respect to the uncertainty in the predictive subgroup effect and biomarker prevalence.     

RBM10 inhibits cell proliferation of lung adenocarcinoma via RAP1/AKT/CREB signalling pathway

Initial functional studies have demonstrated that RNA‐binding motif protein 10 (RBM10) can promote apoptosis and suppress cell proliferation; however, the results of several studies suggest a tumour‐promoting role for RBM10. Herein, we assessed the involvement of RBM10 in lung adenocarcinoma cell proliferation and explored the potential molecular mechanism. We found that, both in vitro and in vivo, RBM10 overexpression suppresses lung adenocarcinoma cell proliferation, while its knockdown enhances cell proliferation. Using complementary DNA microarray analysis, we previously found that RBM10 overexpression induces significant down‐regulation of RAP1A expression. In this study, we have confirmed that RBM10 decreases the activation of RAP1 and found that EPAC stimulation and inhibition can abolish the effects of RBM10 knockdown and overexpression, respectively, and regulate cell growth. This effect of RBM10 on proliferation was independent of the MAPK/ERK and P38/MAPK signalling pathways. We found that RBM10 reduces the phosphorylation of CREB via the AKT signalling pathway, suggesting that RBM10 exhibits its effect on lung adenocarcinoma cell proliferation via the RAP1/AKT/CREB signalling pathway.     

Lipid-Based Nanocarriers via Nose-to-Brain Pathway for Central Nervous System Disorders

Neurochemical Research - Neurodegenerative disorders are distinguished by the gradual deterioration of the nervous system’s structure and function due to oxidative stress, mitochondrial...     

Microbial Reduction of Cr (VI)-loaded Schwertmannite by Shewanella oneidensis MR-1

Microbial transformation of sulfate minerals plays an important role in controlling the behavior of heavy metals in mining areas. Here, the anaerobic reduction of Cr (VI)-loaded schwertmannite by Shewanella oneidensis MR-1 (S. oneidensis MR-1) was investigated. The release of ferrous iron (Fe(II)) to the solution demonstrated the microbial reduction of structural Fe(III) from the schwertmannite to Fe(II). The concentration of Cr in solution decreased in all treatments, indicating that no Cr was released to the solution during this bio-reduction process of schwertmannite. The incorporation of chromate into the mineral structure of schwertmannite increased the microbial stability of the mineral, retarding the formation of secondary phases during bio-reduction process. Analysis of the XRD, SEM and fourier transform infrared spectroscopy (FT-IR) results further showed that goethite formed after 3 or 7 days with a lower content (0.22% or 0.37%) of Cr in schwertmannite, while no secondary mineral was observed with a higher concentration of Cr (0.6 wt%) incorporated in schwertmannite until 22 days. These results imply that microbial reduction of Cr(VI)-loaded schwertmannite does not lead to the release of Cr to the solution, and the microbial stability of schwertmannite will be increased by the incorporation of chromate.     

Nonlinear responses of productivity and diversity of alpine meadow communities to degradation北大核心CSCD

Aims The alpine meadow degradation could have profound effects on the grassland productivity. The aim of our study is to clarify the dynamic response of community productivity and species diversity in the process of alpine meadow degradation. Methods In the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Northern Tibetan Grassland Ecosystem Research Station (Nagqu station), we conducted stages experiments with multiple degradation levels: control, mild degraded meadow, moderate degraded meadow, severe degraded meadow and serious sandy meadow. Important findings The response of aboveground biomass to alpine meadow degradation showed a linear or nonlinear increased response patterns, but the belowground biomass and total biomass decreased nonlinearly. As observed in measurement of aboveground biomass, Margalef index, Simpson index, Shannon-Wiener index and Pielou evenness index also exhibit a nonlinear increased response to degradation. The results of structural equation models showed that belowground biomass has a positive relationship with soil carbon content (p < 0.05) and volume water content (p < 0.1). However, soil nutrient and soil physical properties had no significant impact on aboveground biomass (p < 0.1). Compared with soil physical properties, soil nutrition is an important factor influencing the diversity index. In our study, the nonlinear responses of productivity and diversity of alpine meadow were described by using the multiple levels of degradation in space. The results suggested that aboveground productivity cannot interpret the degree of degradation of alpine meadow, and by contrast, alpine meadow degradation should be measured by the change of plant functional groups, such as edible grasses and poisonous forbs. © 2018 Editorial Office of Chinese Journal of Plant Ecology. All rights reserved.     

Generation of “Virtual” Control Groups for Single Arm Prostate Cancer Adjuvant Trials

It is difficult to construct a control group for trials of adjuvant therapy (Rx) of prostate cancer after radical prostatectomy (RP) due to ethical issues and patient acceptance. We utilized 8 curve-fitting models to estimate the time to 60%, 65%, … 95% chance of progression free survival (PFS) based on the data derived from Kattan post-RP nomogram. The 8 models were systematically applied to a training set of 153 post-RP cases without adjuvant Rx to develop 8 subsets of cases (reference case sets) whose observed PFS times were most accurately predicted by each model. To prepare a virtual control group for a single-arm adjuvant Rx trial, we first select the optimal model for the trial cases based on the minimum weighted Euclidean distance between the trial case set and the reference case set in terms of clinical features, and then compare the virtual PFS times calculated by the optimum model with the observed PFSs of the trial cases by the logrank test. The method was validated using an independent dataset of 155 post-RP patients without adjuvant Rx. We then applied the method to patients on a Phase II trial of adjuvant chemo-hormonal Rx post RP, which indicated that the adjuvant Rx is highly effective in prolonging PFS after RP in patients at high risk for prostate cancer recurrence. The method can accurately generate control groups for single-arm, post-RP adjuvant Rx trials for prostate cancer, facilitating development of new therapeutic strategies.