MV-mimicking micelles loaded with PEG-serine-ACP nanoparticles to achieve biomimetic intra/extra fibrillar mineralization of collagen in vitro

Since their discovery, matrix vesicles (MVs) containing minerals have received considerable attention for their role in the mineralization of bone, dentin and calcified cartilage. Additionally, MVs' association with collagen fibrils, which serve as the scaffold for calcification in the organic matrix, has been repeatedly highlighted. The primary purpose of the present study was to establish a MVs–mimicking model (PEG-S-ACP/micelle) in vitro for studying the exact mechanism of MVs-mediated extra/intra fibrillar mineralization of collagen in vivo. In this study, high-concentration serine was used to stabilize the amorphous calcium phosphate (S-ACP), which was subsequently mixed with polyethylene glycol (PEG) to form PEG-S-ACP nanoparticles. The nanoparticles were loaded in the polysorbate 80 micelle through a micelle self-assembly process in an aqueous environment. This MVs–mimicking model is referred to as the PEG-S-ACP/micelle model. By adjusting the pH and surface tension of the PEG-S-ACP/micelle, two forms of minerals (crystalline mineral nodules and ACP nanoparticles) were released to achieve the extrafibrillar and intrafibrillar mineralization, respectively. This in vitro mineralization process reproduced the mineral nodules mediating in vivo extrafibrillar mineralization and provided key insights into a possible mechanism of biomineralization by which in vivo intrafibrillar mineralization could be induced by ACP nanoparticles released from MVs. Also, the PEG-S-ACP/micelle model provides a promising methodology to prepare mineralized collagen scaffolds for repairing bone defects in bone tissue engineering.     

“绿色革命”新进展:赤霉素与氮营养双重调控的表观修饰助力水稻高产高效育种

以半矮秆育种为代表的“绿色革命”极大地提高了作物产量,但也带来氮营养利用效率降低的严重问题。“绿色革命”主要基于调控赤霉素的代谢和信号转导而实现。前期的研究发现,赤霉素信号转导关键因子DELLA蛋白通过调控GRF4而负调控氮素的吸收利用,为半矮秆品系氮利用效率低的问题提供了解决方案。最近的一项研究进一步揭示了GA信号途径与氮响应交叉互作的新机制。该研究发现水稻(Oryza sativa)NGR5是氮素调控分蘖数目的一个关键基因,其表达受氮诱导。通过招募PRC2,NGR5对D14和OsSPL14等分蘖抑制基因所在位点进行H3K27me3甲基化修饰,从而抑制其表达。而在半矮秆背景下超表达NGR5可以提高低氮水平下的水稻产量。NGR5同时也被发现为赤霉素受体GID1的一个新靶标,受到其负调控。该研究发现了调控赤霉素信号通路的新机制,并对高产高效的新一代“绿色革命”育种实践具有重要启示。     

Functional analysis of the C-terminal propeptide of keratinase from Bacillus licheniformis BBE11-1 and its effect on the production of keratinase in Bacillus subtilis

The keratinase from Bacillus licheniformis BBE11-1 is a serine protease and expressed as a pre-pro-precursor. To produce a mature and active keratinase, the propeptide must be cleaved on the C-terminal via cis or trans. In this study, to enhance the production of keratinase in Bacillus subtilis, single amino acid substitutions, single residue deletions and linkers were introduced at the C-terminus of the propeptide. The results showed that optimizing the residue of cleavage site of propeptide will affect the cleavage efficiency of propeptide, and the mature enzyme yield of Leu(P1)Ala mutant increases 50% compared with the wild-type. In addition, inserting linkers and deleting individual residues at the C-terminal of the propeptide decreases the mature keratinase production. Our results indicated that the primary structure of the C-terminus of propeptide is crucial for the mature keratinase production. Propeptide engineering at C-terminus may be an effective approach to increase the yield of keratinase.     

An Efficient Regression Type Estimator in Survey Sampling

For the estimation of population mean in simple random sampling, an efficient regression-type estimator is proposed which is more efficient than the conventional regression estimator and hence than mean per unit estimator, ratio and product estimators and many other estimators proposed by various authors. Some numerical examples are included for illustration.     

Semiparametric Regression in Size-Biased Sampling

Summary .  Size-biased sampling arises when a positive-valued outcome variable is sampled with selection probability proportional to its size. In this article, we propose a semiparametric linear regression model to analyze size-biased outcomes. In our proposed model, the regression parameters of covariates are of major interest, while the distribution of random errors is unspecified. Under the proposed model, we discover that regression parameters are invariant regardless of size-biased sampling. Following this invariance property, we develop a simple estimation procedure for inferences. Our proposed methods are evaluated in simulation studies and applied to two real data analyses.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.     

The Effect of Leaf Age on Gas Exchange and Malate Accumulation in C3-CAM Plant Marrubium Frivaldszkyanum (Lamiaceae)

For the first time the expression of C₃ and CAM in the leaves of different age of Marrubium frivaldszkyanum Boiss, is reported. With increasing leaf age a typical C₃ photosynthesis pattern and high transpiration rate were found. In older leaves a shift to CAM occurred and the 24-h transpiration water loss decreased. A correlation was established between leaf area and accumulation of malate. Water loss at early stages of leaf expansion may be connected with the shift to CAM and the water economy of the whole plant.     

Does Mother Nature really prefer rare species or are log‐left‐skewed SADs a sampling artefact?

Intensively sampled species abundance distributions (SADs) show left‐skew on a log scale. That is, there are too many rare species to fit a lognormal distribution. I propose that this log‐left‐skew might be a sampling artefact. Monte Carlo simulations show that taking progressively larger samples from a log‐unskewed distribution (such as the lognormal) causes log‐skew to decrease asymptotically (move towards ?∞) until it reaches the level of the underlying distribution (zero in this case). In contrast, accumulating certain types of repeated small samples results in a log‐skew that becomes progressively more log‐left‐skewed to a level well beyond the underlying distribution. These repeated samples correspond to samples from the same site over many years or from many sites in 1 year. Data from empirical datasets show that log‐skew generally goes from positive (right‐skewed) to negative (left‐skewed) as the number of temporally or spatially replicated samples increases. This suggests caution when interpreting log‐left‐skew as a pattern that needs biological interpretation.