Collagen (COL)−chitosan (CS) composite hydrogels are attracting increasing attention because of their great potential for application as biomaterials. However, conventional COL−CS hydrogels were easily disabled for lack of fully reversible linking in their networks. In this work, we developed a kind of self-healing hydrogel for wound dressing, composed of COL, CS, and dibenzaldehyde-modified PEG 2000 via dynamic imine bonds, and the COL/CS hydrogels showed good thermal stability, injectability, and pH sensitivity, ideally promoting wound-healing performance and hemostatic ability. Furthermore, the hydrogel could monitor multiple human motions, especially the facial expression via strain sensitivity. This work offers a new perspective for the biomass-based hydrogels applied in medical field as wound dressing.

This study investigates the joint effects of business and political ties, cognitive capital, and institutional support on product innovation performance in China and India. The hypotheses are empirically tested using bootstrap and multiple group structural equation modeling methods, and data collected from 300 Chinese and 200 Indian manufacturers. The results reveal that cognitive capital mediates business ties' impacts on product innovation performance in both China and India and that institutional support mediates the effects of business and political ties on product innovation performance only in China. The study also finds that political ties increase institutional support in India and that the effect of cognitive capital on product innovation performance is significantly stronger in India than in China. This study clarifies the mechanisms through which business and political ties enhance product innovation performance and generalizes the results in two emerging markets. The cross-country comparison sheds light on the influences of cultural and institutional environments on such mechanisms and provides insights into how to utilize managers' business and political ties for product innovation in China and India.

No abstract

We developed a classification approach to multiple quantitative trait loci (QTL) mapping built upon a Bayesian framework that incorporates the important prior information that most genotypic markers are not cotransmitted with a QTL or their QTL effects are negligible. The genetic effect of each marker is modeled using a three-component mixture prior with a class for markers having negligible effects and separate classes for markers having positive or negative effects on the trait. The posterior probability of a marker's classification provides a natural statistic for evaluating credibility of identified QTL. This approach performs well, especially with a large number of markers but a relatively small sample size. A heat map to visualize the results is proposed so as to allow investigators to be more or less conservative when identifying QTL. We validated the method using a well-characterized data set for barley heading values from the North American Barley Genome Mapping Project. Application of the method to a new data set revealed sex-specific QTL underlying differences in glucose-6-phosphate dehydrogenase enzyme activity between two Drosophila species. A simulation study demonstrated the power of this approach across levels of trait heritability and when marker data were sparse.T HE fact that we can map variation in complex phetion (Doebley and Stec 1991). As such, QTL mapping is not simply a gene-finding tool. QTL mapping provides notypes to chromosomal regions by exploiting the linkage between random genetic markers and causal critical information regarding quantitative evolutionary genetic processes. genetic variants in related individuals has long been understood. Since the formalization of statistical apTraditional approaches to QTL mapping primarily involve multiple regression models and maximum-likeliproaches to this type of inference by Lander and Botstein (1989) and the advent of high-throughput hood estimation and are powerful for detecting QTL of moderate to large effect. However, detecting multiple methodologies for constructing genetic maps with high marker density, quantitative trait locus (QTL) mapping smaller genetic effects that may modify or interact with larger effects is necessary and remains a challenge. in organisms from crops to mice has provided a rich These smaller effects are important, as they can potenknowledge of genes underlying important socioecotially enhance crop breeding and further our undernomic traits. It also has provided a better understanding standing of genetic background effects on complex disof the genetic architecture of complex traits both within ease. Quantifying the abundance of these types of effects and between species. QTL mapping promises the imfor any given trait also fills a gap in our knowledge provement of crops of international importance, such regarding the distribution of genetic effects. as drought-resistant rice (for review see Price andThe most popular approach for QTL mapping is inCourtois 1999; Price et al. 2002), and the advancement terval...

No abstract