Oxidatively Responsive Chain Extension to Entangle Engineered Protein Hydrogels

Engineering artificial protein hydrogels for medical applications requires precise control over their mechanical properties, including stiffness, toughness, extensibility, and stability in the physiological environment. Here we demonstrate topological entanglement as an effective strategy to robustly increase the mechanical tunability of a transient hydrogel network based on coiled-coil interactions. Chain extension and entanglement are achieved by coupling the cysteine residues near the N- and C-termini, and the resulting chain distribution is found to agree with the Jacobson–Stockmayer theory. By exploiting the reversible nature of the disulfide bonds, the entanglement effect can be switched on and off by redox stimuli. With the presence of entanglements, hydrogels exhibit a 7.2-fold enhanced creep resistance and a suppressed erosion rate by a factor of 5.8, making the gels more mechanically stable in a physiologically relevant open system. While hardly affecting material stiffness (only resulting in a 1.5-fold increase in the plateau modulus), the entanglements remarkably lead to hydrogels with a toughness of 65 000 J m^(–3) and extensibility to approximately 3000% engineering strain, which enables the preparation of tough yet soft tissue simulants. This improvement in mechanical properties resembles that from double-network hydrogels but is achieved with the use of a single associating network and topological entanglement. Therefore, redox-triggered chain entanglement offers an effective approach for constructing mechanically enhanced and responsive injectable hydrogels

On correlation between canopy vegetation and growth indexes of maize varieties with different nitrogen efficiencies

Studying the canopy spectral reflection characteristics of different N-efficient maize varieties and analyzing the relationship between their growth indicators and spectral vegetation indices can help the breeding and application of N-efficient maize varieties. To achieve the optimal management of N fertilizer resources, developing N-efficient maize varieties is necessary. In this research, maize varieties, i.e., the low-N-efficient (Zhengdan 958, ZD958), the high-N efficient (Xianyu 335, XY335), the double-high varieties (Qiule 368, QL368), and the double inefficient-type varieties (Yudan 606 YD606), were used as materials. Results indicate that nitrogen fertilization significantly increased the vegetation indices NDVI, GNDVI, GOSAVI, and RVI of maize varieties with different nitrogen efficiencies. These findings were consistent with the performance of yield, dry matter mass, and leaf nitrogen content and were also found highest under both medium and high nitrogen conditions in the double-high variety QL368. The correlations of dry matter quality, leaf nitrogen content, yield, and vegetation indices (NDVI, GNDVI, RVI, and GOSAVI) at the filling stage of different N-efficient maize varieties were all highly significant and positive. In this relationship, the best effect was found at the filling stages, with correlation coefficients reaching 0.772–0.942, 0.774–0.970, 0754–0.960, and 0.800–0.960. The results showed that the yield, dry matter weight, and leaf nitrogen content of maize varieties with different nitrogen efficiencies increased first and then stabilized with the increase in the nitrogen application level in different periods, and the highest nitrogen application level of maize yield should be between 270 and 360 kg/hm2. At the filling stage, canopy vegetation index of maize varieties with different nitrogen efficiencies was positively correlated with yield, dry matter weight, and leaf nitrogen content, especially GNDVI and GOSAVI on the leaf nitrogen content. It can be used as a means to predict its growth index

Clinicopathological risk factors for gastric cancer: a retrospective cohort study in China

Objective: To examine the potential clinicopathological factors affecting the prognosis of patients with gastric cancer after surgical treatment in China. Methods: Between 1 January 2001 and 31 December 2012, a total of 716 patients aged 22–84 years with gastric cancer were enrolled in the study. Survival analysis techniques including log rank test and Cox proportional hazard regression model were applied to evaluate the prognostic significance of clinicopathological characteristics in terms of survival time. Results: Of the 24 demographic and pathological variables collected in the data, 16 prognostic factors of gastric cancer were found to have statistically significant influences on survival time from the unadjusted analyses. The adjusted analysis furtherly revealed that age, age square, lymph node metastasis rate group, tumour size group, surgical type II, number of cancer nodules, invasion depth group and the interaction between surgical type II and tumour size group were important prognosis and clinicopathological factors for gastric cancer in Chinese. Conclusion: Our study with relatively large sample size and many potential risk factors enable us to identify independent risk factors associated with the prognosis of gastric cancer. Findings from the current study can be used to assist clinical decision-making, and serve as a benchmark for the planning of future prognosis and therapy for patients with gastric carcinoma

Ultrahigh-throughput screening-assisted in vivo directed evolution for enzyme engineering

Abstract Background Classical directed evolution is a powerful approach for engineering biomolecules with improved or novel functions. However, it traditionally relies on labour- and time-intensive iterative cycles, due in part to the need for multiple molecular biology steps, including DNA transformation, and limited screening throughput. Results In this study, we present an ultrahigh throughput in vivo continuous directed evolution system with thermosensitive inducible tunability, which is based on error-prone DNA polymerase expression modulated by engineered thermal-responsive repressor cI857, and genomic MutS mutant with temperature-sensitive defect for fixation of mutations in Escherichia coli. We demonstrated the success of the in vivo evolution platform with β-lactamase as a model, with an approximately 600-fold increase in the targeted mutation rate. Furthermore, the platform was combined with ultrahigh-throughput screening methods and employed to evolve α-amylase and the resveratrol biosynthetic pathway. After iterative rounds of enrichment, a mutant with a 48.3% improvement in α-amylase activity was identified via microfluidic droplet screening. In addition, when coupled with an in vivo biosensor in the resveratrol biosynthetic pathway, a variant with 1.7-fold higher resveratrol production was selected by fluorescence-activated cell sorting. Conclusions In this study, thermal-responsive targeted mutagenesis coupled with ultrahigh-throughput screening was developed for the rapid evolution of enzymes and biosynthetic pathways

Oxidatively Responsive Chain Extension to Entangle Engineered Protein Hydrogels

Engineering artificial protein hydrogels for medical applications requires precise control over their mechanical properties, including stiffness, toughness, extensibility, and stability in the physiological environment. Here we demonstrate topological entanglement as an effective strategy to robustly increase the mechanical tunability of a transient hydrogel network based on coiled-coil interactions. Chain extension and entanglement are achieved by coupling the cysteine residues near the N- and C-termini, and the resulting chain distribution is found to agree with the Jacobson–Stockmayer theory. By exploiting the reversible nature of the disulfide bonds, the entanglement effect can be switched on and off by redox stimuli. With the presence of entanglements, hydrogels exhibit a 7.2-fold enhanced creep resistance and a suppressed erosion rate by a factor of 5.8, making the gels more mechanically stable in a physiologically relevant open system. While hardly affecting material stiffness (only resulting in a 1.5-fold increase in the plateau modulus), the entanglements remarkably lead to hydrogels with a toughness of 65 000 J m^–3 and extensibility to approximately 3000% engineering strain, which enables the preparation of tough yet soft tissue simulants. This improvement in mechanical properties resembles that from double-network hydrogels but is achieved with the use of a single associating network and topological entanglement. Therefore, redox-triggered chain entanglement offers an effective approach for constructing mechanically enhanced and responsive injectable hydrogels