Current Chinese Science - Volume 1, Issue 1, 2021

Background: Predicting the three-dimensional structure of globular proteins from their amino acid sequence has reached a fair accuracy, but predicting the structure of membrane proteins, especially loop regions, is still a difficult task in structural bioinformatics. The difficulty in predicting membrane loops is due to various factors like length variation, position, flexibility, and they are easily prone to mutation. Objective: In the present work, we address the problem of identifying and ranking near-native loops from a set of decoys generated by Monte-Carlo simulations. Methods: We systematically analyzed native and generated non-native decoys to develop a scoring function. The scoring function uses four important stabilizing energy terms from three popular force fields, such as FOLDX, OPLS, and AMBER, to identify and rank near-native membrane loops. Results: The results reveal better discrimination of native and non-natives and perform poor prediction in binary classifying native and near-native defined based on Root Mean Square Deviation (RMSD), Global Distance Test (GDT), and Template Modeling (TM) score, respectively. Conclusion: From our observations, we conclude that the important energy features described here may help to improve the loop prediction when the membrane protein database size increases.

Two-dimensional (2D) nanomaterials with unique anisotropy and electronic properties are deemed as an ideal platform for establishing clear relationships between structure and catalytic reactivity. Knowledge of their structures is essential for understanding the catalytic behavior, which further facilitates the development of high-performance catalysts. In this review, we focus on the recent progress of synchrotron radiation X-ray absorption spectrum (XAS) techniques in exploring the structure-function relationship of two-dimensional electrocatalysts. Also, we summarize the application of XAS technique in disclosing key factors that affect the catalytic activity, including identification of local atomic structure, electronic structure and defect structure. Through the characterization of the catalytic process with XAS technique, we further highlight the atomic-level correlation between structure and function in the field of oxygen evolution, oxygen reduction, hydrogen evolution and CO2 reduction. Finally, we propose the major challenges and prospects of XAS technique in advancing the development of two-dimensional electrocatalysts. We anticipate that this review provides critical insights into the application of the XAS technique in electrocatalysis, thereby promoting the development of advanced characterization techniques and the design of high-active catalysts.

Background: The use of an amine solution to capture CO2 from flue gases is one of the methods applied commercially to clean up the exhaust gas stream of a power plant. One of the issues in this process is foaming which should be known in order to select a suitable amine for design. Objectives: In this work, all possible types of amines used for CO2 capture, namely, alkanolamines, sterically hindered alkanolamines, multi-alkylamines and cyclic amines, were investigated to elucidate their chemical structure–foaming relationships. Methods: Foam volume produced by each type of 2M amine solution with its equilibrium CO2 loading was measured at 40°C using 94 mL/min of N2 flow. Results: Amines with a higher number or a longer chain of the alkyl group exhibited higher foam volume because of alkyl group’s ability to decrease the surface tension while increasing the viscosity of the solution. An increase in the number of hydroxyl or amino groups in the amine led to the reduction of foam formation due to the increase in surface tension and a decrease in viscosity of the solution. The predictive foam models for non-cyclic and cyclic-amines developed based on the structural variations, surface tension and viscosity of 29 amines predicted the foam volume very well with average absolute deviations (AAD) of 12.7 and 0.001%, respectively. The model accurately predicted the foam volume of BDEA, which was not used in model development with 13.3 %AD. Conclusion: This foam model is, therefore, indispensable in selecting a suitable amine for an amine-based CO2 capture plant design and operation.

Background: Obesity is an emerging pandemic considered to be an outcome of change in lifestyle owing to more processed food and the use of mechanical locomotives. Obesity has not only appeared as a problem in the esthetic appearance of an individual rather is a serious health issue due to its associations with various chronic diseases such as coronary and cardiovascular problems, hypertension, osteoarthritis, type-II diabetes mellitus, hyperlipidemia, and certain cancers. It is estimated that 30 percent of the world’s population, i.e. approximately 2.1 billion people, are victims of obesity. In addition to environmental causes, various genes and a group of genes are reported to be increasing the suceptibility of obesity. Objective: Pakistan is a heterogeneous population, an amalgam of various races, therefore, narrowing down the list of obesity-associated genes and their functional variance could help molecular biologists to select potential SNPs in the Pakistani population for molecular diagnosis and treatment. Method: The extraction of a set of obesity-associated genes has been performed by using Polysearch2. SNPs for each gene are retrieved from dbSNP. RegulomeDB and SNPinfo tools have been used for the functional analysis of SNPs retrieved against the Pakistani population. For the prediction of potential deleterious SNPs, SIFT, Polyphen-2, MUTTASTER, MUTASSESSOR, and LRT (likelihood ratio test) are utilized. Functional analysis of potential deleterious SNPs has been performed by studying protein stability and mapping of identified SNPs to protein structure. For the protein stability analysis, I-Mutant and SNPs3D have been used. Results: Four genes FTO, POMC, LEPR, and MC4R and further analysis revealed 3 deleterious SNPs in FTO, 4 in POMC, 1 in LEPR, and 1 in MC4R. Conclusion: This research was designed to identify obesity-associated genes and the most impactful deleterious SNPs in these genes. These findings will be helpful for the molecular biologists and pharmacists to design better and focused diagnosis and treatment strategies.

Background: CRISPR-Cas9 is a powerful technology that allows us to modify DNA sequences in a specific manner across a variety of organisms. Due to its high efficiency and specificity, and ease of use, it becomes a commonly used method for gene editing. Although many structural and biochemical studies have been carried out to understand the fundamental mechanism of CRISPR/Cas9, our understanding of CRISPR/Cas9 caused off-target effects is still lacking. Methods: The enhanced in vitro cleavage activity of Cas9 protein from Streptococcus pyogenes (SpCas9) was evaluated by both synthetic crRNA-tracrRNA duplexes and in vitro transcribed single guide RNAs. Results: Here, we report an unexpected finding that mismatches between the guide RNA and target DNA significantly enhanced the in vitro cleavage activity of SpCas9 by more than 2 folds. Conclusion: Our observation that mismatches between the guide RNA and target DNA can dramatically increase the in vitro cleavage of Cas9 suggests the potential sequence preference for the CRSIPR/Cas9 system.

Mangroves forests inhabiting the south coast of China are crucial habitats for the functioning of the coastal zone. This role has not been carefully considered in China and compared to their functional role worldwide. China’s mangroves currently occupy 20,303 ha. Average forest biomass is equivalent to the global average, but the mean ratio of below-ground to above-ground biomass is high (46%), reflecting the young age of most forests. Rates of annual litterfall, net primary productivity, and root production are above the global average, indicating that China’s mangrove forests are highly productive within their latitudinal band. High productivity may reflect high rates of organic inputs, young forest ages, and high rates of precipitation. As China’s mangrove forests have short canopies, these data imply that the rates of forest turnover are more rapid than in most other mangroves. Mangrove organic carbon (Corg) stock averaged 190.96 Mg Corg ha^-1, mostly (58%) in soils, less than the global average, reflecting young forest age and frequent soil disturbance. Total Corg stored in China’s mangroves is 3.9 Tg, only 0.03% of the global total, but the total Corg sequestration rate is 139.4 Gg Corg a^-1 while the average Corg sequestration rate is 6.87 Mg Corg ha^-1 a^-1, which is greater than the global average. Corg losses via microbial mineralization are large as total Corg export from mangroves accounts for 44% of the total Corg exported to the South China Sea. Nutrients are efficiently retained suggesting their use and proper management as aquaculture filters. Mangroves have close links to other coastal food webs.

Background: The basic principle of genome selection (GS) is to establish a model of genome estimated breeding value (GEBV) by using single-nucleotide polymorphisms (SNPs) covering the entire genome. Despite the decreasing cost of high-throughput genotyping, the GS strategy remains expensive due to the need for phenotyping and genotyping for a large number of samples. Simulation analysis of genome selection is a popular, lower-cost method to determine an optimal breeding program of GS. Objective: To evaluate the utility of simulation data to study the influence of different factors on algorithms. This could be helpful for developing genome selection breeding strategies, especially for stress and resistance traits of fish. Methods: Real data of orange-spotted grouper (Epinephelus coioides) were obtained from a previous genome-wide association study. Ammonia tolerance, different population sizes, SNP density, QTL number, kinship (base mutation rate), and heritability were considered. All of the phenotypes and genotypes were generated by AlphaSimR simulation software. Four genome selection algorithms (gBLUP, rrBLUP, BayesA, and BayesC) were tested to derive GEBV, and their accuracies (area under the curve, AUC) were compared. Results: In different scenarios, the AUC ranges from 0.4237 to 0.6895 for BayesA, 0.4282 to 0.6878 for BayesC, 0.4278 to 0.6798 for gBLUP, and 0.4346 to 0.6834 for rrBLUP. The mean AUC of these four algorithms was not significantly different (0.547–0.548). The accuracies of the four genome selection algorithms were similar but had different predictive performances in specific scenarios. The gBLUP was most stable, and the rrBLUP was slightly better at predicting low heritability traits. When the number of individuals was small, the BayesA and BayesC algorithms were more robust. Conclusion: A practical GS scheme should be optimized in accordance with marker density, heritability, and reference population size. Adequate preliminary research is necessary. The results provide a framework for the design of genomic selection schemes in E. coioides breeding.

Gas sensing materials essentially dominate the performances of the gas sensors which are widely applied in environmental monitoring, industrial production and medical diagnosis. However, most of the traditional gas sensing materials show excellent performances only at high operating temperatures, which are high energy consumptive and have potential issues in terms of reliability and safety of the sensors. Therefore, the development of Room Temperature (RT) gas sensing materials becomes a research hotspot in this field. In recent years, graphene-based materials have been studied as a class of promising RT gas sensing materials because graphene has a unique twodimensional (2D) structure with high electron mobility and superior feasibility of assembling with other “guest components” (mainly small organic molecules, macromolecules and nanoparticles). More interestingly, its electrical properties become even more sensitive toward gas molecules at RT after surface modification. In this review, we have summarized the recently reported graphenebased RT gas sensing materials for the detection of NO2, H2S, NH3, CO2, CO, SO2, Volatile Organic Compounds (VOCs) (i.e. formaldehyde, acetone, toluene, ethanol), as well as Liquefied Petroleum Gas (LPG) and highlighted the latest researches with respect to supramolecular modification of graphene for gas sensing. The corresponding structural features and gas sensing mechanisms of the graphene-based gas sensors have also been generalized.

For decades, the over-exploitation of fossil fuel has made it urgent to develop alternative energy. Photoelectrochemical (PEC) water splitting is a promising approach to generate hydrogen, which is referred to as the fuel of the future due to its high enthalpy of combustion and zero pollution. Though impressive progress has been made over the years, PEC water splitting efficiency is still far from volume production of hydrogen, and more efforts are required to reduce the overpotential, inhibit the yield of hydrogen peroxide by-product, improve the PEC current density, improve light-harvesting capability, and develop low-cost earth-abundant catalysts. Recently, chirality has shown to play a pivotal role in addressing the issues of PEC water splitting via the effect of chiralinduced spin controlling and chiral-enhanced light harvesting. It is high time to pay attention to the art of chirality in promoting water splitting efficiency. Herein, recent progress in this field is reviewed, the approaches to introducing chirality into photo/electronic catalysts for PEC water splitting are summarized, characterization techniques applied in this research field are summed up, the challenges of chirality-enhanced PEC water splitting are discussed, and based on the present achievements, its bright future is anticipated.

Background: Essential Balm (EB) is a commonly used medicine with high volatility and short shelf-life during storage. Objective: Slowing down the volatilization rate of EB and exploring the effect of fiber on the volatilization rate of EB. Methods: In this study, electrospinning technology was used to convert the liquid EB into solid EB in order to improve the balm’s storage and longevity. Results: Specifically, core-sheath nanofibers coated with EB were prepared by traditional coaxial electrospinning technology, in which polyvinylpyrrolidone K90 was used as polymer sheath to reduce the volatilization of EB in the core layer. Scanning electron microscopy images showed that the core-sheath flow rate ratio is proportional to the sizes and number of spindles. EB was successfully placed into the fibers and showed good compatibility with the carriers. Infrared spectroscopy indicated the presence of a hydrogen bond between them. Volatility tests showed that all prepared composites could delay the volatility of EB and improve its physical stability. Conclusion: This methodology can be applied toward increasing the shelf-life of liquid drugs by using core-sheath nanofibers. The core-sheath fibers with good morphology are more propitious to delay the volatilization rate of EB.

Background: Noble-metal nanocrystals have been extensively studied over the past decades because of their unique optical properties. The polyol process is considered an effective method for silver (Ag) nanocrystals’ synthesis in solution even though the reproducibility of its shape controlling is still a challenge. Here, Ag nanowires and nanocubes were synthesized by the polyol process, in which the Ag+ ions are directly reduced by ethylene glycol with a certain amount of Cl− ions added. We present the relationship between the final morphology of the Ag nanostructures with the parameters of reaction, including temperature, growth time, injection rate, and the amount of sodium chloride. The as-synthesized nanowires and nanocubes were characterized by scanning electron microscopy, transmission electron microscopy and X-ray diffraction. The uniformly distributed nanocubes with a mean edge length of 140 nm were obtained. The localized surface plasmon resonance of Ag nanocubes was characterized by laser scanning fluorescence confocal microscopy. The photoluminescence enhancement was observed on the perovskite film coupled with Ag nanocubes. Objective: We aimed to synthesize uniform and controllable silver nanocubes and nanowires through the polyol process and explore the interaction between CsPbBr3 perovskite film and Ag nanocubes antennas. Methods: We synthesized silver nanocubes and nanowires through the polyol process where the silver nitrate (AgNO3) was reduced by Ethylene Glycol (EG) in the presence of a blocking agent polyvinylpyrrolidone (PVP). Results: We successfully synthesized Ag nanocubes with an average edge length of 140 nm and Ag nanowires with a uniform distribution in terms of both shape and size through a polyol process with sodium chloride (NaCl) as the additive. In addition, the local photoluminescence (PL) enhancement was observed in a perovskite film by combining Ag nanocubes, which is attributed to the antennas plasmonic effect of the Ag nanocubes. Conclusions: In summary we studied the parameters in the polyol process such as reaction temperature, growth time, injection rate, kind of halide ion and NaCl amount for the synthesis of Ag nanowires and nanocubes. Our results suggest that the concentration of Cl- and the growth time have the main influence on Ag nanowires and nanocubes formation. The optimum growth time was found to be 60 min and 120 min for the formation of Ag nanowires and nanocubes, respectively. In addition, we revealed that the opportune reaction temperature of Ag nanowires was 140 °C. The injection rate of precursors was also found to play an important role in the final morphology of Ag nanowires and nanocubes. In addition, for the generation of Ag nanocubes, the presence of Cl− ion in the reaction is critical, which can eliminate most of the byproducts. We obtained the Ag nanowires with a uniform distribution in terms of both shape and size, and nanocubes with average lengths of 140 nm by the polyol process with the optimal parameters. Plasmon-coupled emission induced by noble-metal nanocrystals has attracted more attention in recent years. In this work, the PL of a perovskite film was enhanced by the coupling of Ag nanocubes due to the surface plasmonic effect.

Three polymers containing different numbers of thiophene groups were constructed. Degradation experiments on the aqueous solutions of tetracycline and norfloxacin revealed that the polymer with three thiophene groups in the monomer indicated the best degradation efficiency of 73.7% for tetracycline and 56.9% for norfloxacin. Moreover, this polymer had a relatively stronger ability to separate and transport photocharging carriers under visible light. Therefore, the photocatalytic performance of conjugated polymers could be regulated by changing the number of characteristic groups. Background: Antibiotic residues in the environment are considered as one of the most serious sources of environmental pollution. Although catalyst photodegradation is regarded as the most promising strategy to solve environmental pollution-related problems, it still requires new and advanced photocatalysts. Objective: To design new organic conjugated material structures. Materials and Methods: Three polymers (ThME-1, ThME-2, and ThME-3) were prepared by the condensation of melamine with 2, 5-thiophenedicarboxaldehyde, thieno[3, 2-b]thiophene-2, 5-dicarbaldehyde, and dithieno[3, 2-b:2’, 3’-d]thiophene-2, 6-dicarbaldehyde. The photocatalytic performance of these polymers was investigated by testing their diffused light absorption capacity, photocurrent response, AC impedance, specific surface area, fluorescence, and thermal stability. Results: ThME-3, containing three thiophene groups in the monomer, manifested the best degradation efficiency of 73.7% for tetracycline and 56.9% for norfloxacin. Conclusion: The photocatalytic performance of conjugated polymers could be regulated by changing the number of characteristic groups.

Background: As an advanced design technique, topology optimization has received much attention over the past three decades. Topology optimization aims at finding an optimal material distribution in order to maximize the structural performance while satisfying certain constraints. It is a useful tool for the conceptional design. At the same time, additive manufacturing technologies have provided unprecedented opportunities to fabricate intricate shapes generated by topology optimization. Objective: To design a highly efficient structure using topology optimization and to fabricate it using additive manufacturing. Method: The bi-directional evolutionary structural optimization (BESO) technique provides the conceptional design, and the topology-optimized result is post-processed to obtain smooth structural boundaries. Results: We have achieved a highly efficient and elegant structural design which won the first prize in a national competition in China on design optimization and additive manufacturing. Conclusion: In this paper, we present an effective topology optimization approach to maximize the structural load-bearing capacity and establish a procedure to achieve efficient and elegant structural designs. In the loading test of the final competition, our design carried the highest loading and won the first prize in the competition, which demonstrates the capability of BESO in engineering applications.

Background: The corrosion of steel bar leads to the deterioration of structural behaviors, high cost maintenance, shortened service life. The bridge deck structures constructed by Fiber Reinforced Polymer (FRP) bars and High-Volume Fly Ash-Self-Compacting Concrete (HVFA-SCC) can achieve low energy consumption, sustainable construction and high durability. However, the structural behaviors of this bridge deck are still unclear. Objective: The aim of this paper is to study the structural behaviors, including ultimate loads, failure mode, cracking behavior, deflection and strain of one-way HVFA-SCC slabs reinforced with Glass- FRP (GFRP). Experimental: Eleven full-scale HVFA-SCC slabs, varying in reinforcement diameter, reinforcement ratio, shear-span ratio, the type of reinforcing materials and concrete matrix materials, were tested by using a four-point bending load. Methods: The test results of tested specimens were compared with existing theoretical models, such as crack load, ultimate bearing capacity, maximum crack width, maximum crack space and deflection predicted model. Results: The GFRP reinforced HVFA-SCC slab exhibits similar structural behaviors to the GFRP reinforced NC slab. The maximum crack width of HVFA-SCC slab is significantly increased by using GFRP bars with a diameter of 19 mm. Conclusion: It is concluded that it is feasible to use HVFA-SCC instead of NC combined with GFRP bars in bridge deck structures. The stress limit of concrete materials (0.45fc) is the main governing factor for the service limit state (SLS) of GFRP reinforced HVFA-SCC slabs. The maximum crack width of GFRP reinforced HVFA-SCC slabs can be predicted by using EHE-08 and GB 50608-2010 models.