Rapid urbanization has become a common occurrence all over the world, particularly in developing countries, and has thus resulted in various eco-environmental problems. In China, urban land has expanded at an unprecedented rate in the past several decades, and sustainable land urbanization has become an important issue in promoting sustainable development. Hence, scholars have proposed ecological carrying capacity (ECC) as a solution to balance socio-economic development and the ecosystems for achieving sustainable development. In the current work, we explored the spatial influence of ECC on land urbanization and its driving mechanism, using the Wuhan agglomeration as a case study. In the first step, we calculated the ECC at the county level using the ecological footprint method. Then, we applied a combination of kernel density and the densi-graph method on the basis of points of interest, in order to identify urbanized areas and to measure land urbanization rates. Finally, we devised spatial models with ECC-based spatial weight matrices to examine the potential spatial interactions or constraints and the influencing factors. Results indicate the following. (1) Land urbanization rates in most counties increased, whereas the average ECC per capita in the Wuhan urban agglomeration decreased from 2010 to 2015; (2) China's land urbanization is primarily driven by socio-economic development, in which fixed asset investments and urban income present positive influences and agricultural outputs show a negative influence; (3) Spatial interaction was formulated through ECC during the land urbanization process. However, this effect was attenuated in 2010-2015. The findings are beneficial for understanding the regional spatial influence of ECC on urban land urbanization. They should also facilitate the formulation of relevant policies for protecting, restoring, and promoting the sustainable use of terrestrial ecosystems to ultimately achieve coordinated and balanced regional development.
Vizcarra, Christina L.
Zhang, Naigong
Marshall, Shannon A.
Wingreen, Ned S.
Zeng, Chen
Mayo, Stephen L.
Our goal is to develop accurate electrostatic models that can be implemented in current computational protein design protocols. To this end, we improve upon a previously reported pairwise decomposable, finite difference Poisson-Boltzmann (FDPB) model for protein design (Marshall et al., Protein Sci 2005, 14, 1293). The improvement involves placing generic sidechains at positions with unknown amino acid identity and explicitly capturing two-body perturbations to the dielectric environment. We compare the original and improved FDPB methods to standard FDPB calculations in which the dielectric environment is completely determined by protein atoms. The generic sidechain approach yields a two to threefold increase in accuracy per residue or residue pair over the original pairwise FDPB implementation, with no additional computational cost. Distance dependent dielectric and solvent-exclusion models were also compared with standard FDPB energies. The accuracy of the new pairwise FDPB method is shown to be superior to these models, even after reparameterization of the solvent-exclusion model.
Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e. g., approximate to 10(30) for the yeast cell cycle process [1]), considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from Boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology Boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.
The anti-CD52 antibody has already been approved for the treatment of patients with resistant chronic lymphocytic leukemia, relapsing-remitting multiple sclerosis, and has demonstrable efficacy against stem cell transplantation rejection. A CHO cell line expressing a humanized anti-CD52 monoclonal antibody (mAb-TH) was cultivated in both fed-batch and perfusion modes, and then purified. The critical quality attributes of these mAb variants were characterized and the pharmacokinetics (PK) properties were investigated. Results showed that the perfusion culture achieved higher productivity, whereas the fed-batch culture produced more aggregates and acid components. Additionally, the perfusion culture produced similar fucose, more galactose and a higher proportion of sialic acid on the anti-CD52 mAb compared to the fed-batch culture. Furthermore, the perfusion process produced anti-CD52 mAb had higher complement-dependent cytotoxicity (CDC) efficacy than that produced by the fed-batch culture, a result probably linked to its higher galactose content. However, antibody produced by fed-batch and perfusion cultures showed similar PK profiles in vivo. In conclusion, perfusion is a more efficient method than fed-batch process in the production of functional anti-CD52 monoclonal antibody. Product quality variants of anti-CD52 mAb were found in different cell culture processes, which demonstrated different physiochemical and biological activities, but comparable PK properties. Whether these observations apply to all mAbs await further investigation.
Miribangul, Amat
Ma, Xiaoli
Zeng, Chen
Zou, Huan
Wu, Yahui
Fan, Tengpeng
Su, Zhi
Semiconductor photocatalysis has the potential for achieving sustainable energy generation and degrading organic contaminants. In TiO2, the addition of carbonaceous nanomaterials has attracted extensive attention as a means to increase its photocatalytic activity. In this study, composites of TiO2 and carbon nanotubes (CNT) in various proportions were synthesized by the hydrothermal method. The crystalline structures, morphologies, and light absorption properties of the TiO2/CNT photocatalysts were characterized by PXRD, TEM and UV-Vis absorption spectra. The photocatalytic efficiency of the composites was evaluated by the degradation of Sudan (I) in UV-Vis light. Introducing 0.1-0.5 wt% CNT was shown to substantially improve the photoactivity of TiO2. The composite with 0.3 wt% CNT showed the best catalytic activity, and its reaction activation energy was calculated as 39.57kJmol(-1) from experimental rates. The degradation products of Sudan (I) with different irradiation durations were characterized by Fourier transform infrared spectroscopy, and a degradation reaction process was proposed.
Hu, Fanghao
Zeng, Chen
Long, Rong
Miao, Yupeng
Wei, Lu
Xu, Qizhi
Min, Wei
Optical multiplexing has a large impact in photonics, the life sciences and biomedicine. However, current technology is limited by a 'multiplexing ceiling' from existing optical materials. Here we engineered a class of polyyne-based materials for optical supermultiplexing. We achieved 20 distinct Raman frequencies, as 'Carbon rainbow', through rational engineering of conjugation length, bond-selective isotope doping and end-capping substitution of polyynes. With further probe functionalization, we demonstrated ten-color organelle imaging in individual living cells with high specificity, sensitivity and photostability. Moreover, we realized optical data storage and identification by combinatorial barcoding, yielding to our knowledge the largest number of distinct spectral barcodes to date. Therefore, these polyynes hold great promise in live-cell imaging and sorting as well as in high-throughput diagnostics and screening.=20