A cost–benefit analysis of the environmental taxation policy in China: A frontier analysis‐based environmentally extended input–output optimization method

China's high‐speed economic development and reliance on overconsumption of natural resources have led to serious environmental pollution. Environmental taxation is seen as an effective economic tool to help mitigate air pollution. In order to assess the effects of different scenarios of environmental taxation policies, we propose a frontier‐based environmentally extended input–output optimization model with explicit emission abatement sectors to reflect the inputs and benefits of abatement. Frontier analysis ensures policy scenarios are assessed under the same technical efficiency benchmark, while input–output analysis depicts the wide range of economic transactions among sectors of an economy. Four scenarios are considered in this study, which are increasing specific tax rates of SO₂, NO_x, and soot and dust separately and increasing all three tax rates simultaneously. Our estimation results show that: raising tax rates of SO₂, NO_x, and soot and dust simultaneously would have the highest emission reduction effects, with the SO₂ tax rate making the greatest contribution to emission reduction. Raising the soot and dust tax rate is the most environmentally friendly strategy due to its highest abatement to welfare through avoided health costs. The combination of frontier analysis and input–output analysis provides policy makers a comprehensive and sectoral approach to assess costs and benefits of environmental taxation.     

Production,optimization, purification,characterization, and anti-cancer application of extracellular L-glutaminase produced from the marine bacterial isolate

Abstract

L-glutaminase from bacterial sources has been proven to be effective and economical agents in cancer therapy, food industry and high-value chemicals like threonine. In the present study, a newly isolated bacterial strain was potentially producing extracellular L-glutaminase, it identified as Bacillus subtilis OHEM11 (MK389501) using the 16S rRNA gene. L-glutaminase production optimized and the optimum factors for production under submerged fermentation were at pH 6.5–7.0 and 35?°C after 28?hr using rhamnose and glutamine as carbon and nitrogen sources, respectively, while bagasse was the best inducer for the production under solid-state fermentation. Ethanol precipitation and ion-exchange chromatography using QFF are the purification steps. L-glutaminase was purified to 2-fold with specific activity 89.78?U/mg and its molecular weight about 54.8?kDa with the alkaline property of the enzyme makes it clear having carcinostatic property; maximum enzyme activity at pH 8.2 and 40?°C and retained about 90% activity for 1?hr. The cytotoxicity effect of L-glutaminase indicated a significant safety on Vero cells with high anticancer activity against NFS-60, HepG-2, and MCF-7 cancer cell lines. The outcomes demonstrated that L-glutaminase could be applied in many biotechnological applications such as pharmaceutical and food processing.     

Optimization of parameters affecting on CHO cell culture producing recombinant erythropoietin

Abstract

Several factors may affect erythropoietin (EPO) sugar structures including designing cell culture procedure, pH, concentration of additives, dissolved oxygen, and other physicochemical parameters. In this study, we investigated the influence of changes in effective parameters and compounds on the growth rate of Chinese hamster ovary cell (CHO) cells producing recombinant EPO. Cell culture was performed at different temperature, buffering conditions, and varied concentrations of additives such as pyruvic acid, insulin, GlutaMAX, and sodium butyrate. Results indicated that the optimal temperature and pH were 37?°C and 7.2, respectively. Also, optimal concentrations for pyruvic acid, butyrate, glutamate, and insulin were obtained to be 20?mM, 1?mM, 2?mM, and 40?μg/mL, respectively. Then, cell culture was performed in microcarrier-coated spinner flasks under the optimized condition. The results showed recombinant human EPO (rhEPO) production with adequate purity. Optimization of physicochemical conditions and culture media are important factors to improve the quantity and quality of protein products. This study showed that cell growth and recombinant EPO protein production significantly increased under the optimized conditions. The results of this research can also be used in scale-up to increase the efficiency of EPO production.

Abbreviations: EPO: erythropoietin; CHO cell: Chinese hamster ovary cell; rhEPO: recombinant human EPO; DMEM: modified eagle’s medium; FBS: fetal bovine serum; SDS-PAGE: sodium dodecyl sulfate–polyacrylamide gel electrophoresis; IGF-1: insulin-like growth factor 1     

黑老虎叶总黄酮提取工艺及其抗氧化活性研究

为探讨超声波辅助提取黑老虎叶总黄酮的最佳提取工艺条件及其抗氧化活性,该文以黑老虎叶为研究对象,采用超声波提取法提取黑老虎叶总黄酮,通过单因素试验研究提取时间、乙醇浓度、提取温度、料液比对黑老虎叶总黄酮提取率的影响,在单因素试验的基础上,采用正交试验优化其提取工艺条件,测试了最优条件下提取的黑老虎叶总黄酮对DPPH自由基、·OH自由基及超氧阴离子的清除能力。结果表明:黑老虎叶总黄酮超声辅助提取最佳提取条件为提取时间 35 min、乙醇浓度80%、提取温度50 ℃、料液比1:20 g·mL^-1,最佳条件下提取率为4.83%。抗氧化活性测试结果显示,黑老虎叶总黄酮表现出较好的清除DPPH自由基、·OH自由基及超氧阴离子能力,其抗氧化能力为清除DPPH自由基能力>清除超氧阴离子能力>清除·OH自由基能力。在浓度为0.8 mg·mL^-1时,黑老虎叶总黄酮清除DPPH自由基、·OH自由基及超氧阴离子的能力相当于同浓度下Vc的97.6%、82.1%、95.5%,黑老虎叶总黄酮是天然抗氧化剂的良好来源。上述结果为黑老虎叶活性成分的提取及开发利用提供了理论基础。     

Optimization of culture media to enhance the growth of tissue engineered cartilage

Tissue engineering is a promising option for cartilage repair. However, several hurdles still need to be overcome to develop functional tissue constructs suitable for implantation. One of the most common challenges is the general low capacity of chondrocytes to synthesize cartilage-specific extracellular matrix (ECM). While different approaches have been explored to improve the biosynthetic response of chondrocytes, several studies have demonstrated that the nutritional environment (e.g., glucose concentration and media volume) can have a profound effect on ECM synthesis. Thus, the purpose of this study was to optimize the formulation of cell culture media to upregulate the accumulation of cartilaginous ECM constituents (i.e., proteoglycans and collagen) by chondrocytes in 3D culture. Using response surface methodology, four different media factors (basal media, media volume, glucose, and glutamine) were first screened to determine optimal media formulations. Constructs were then cultured under candidate optimal media formulations for 4 weeks and analyzed for their biochemical and structural properties. Interestingly, the maximal accumulation of proteoglycans and collagen appeared to be elicited by different media formulations. Most notably, proteoglycan accumulation was favored by high volume, low glucose-containing DMEM/F12 (1:1) media whereas collagen accumulation was favored by high volume, high glucose-containing F12 media. While high glutamine-containing media elicited increased DNA content, glutamine concentration had no apparent effect on ECM accumulation. Therefore, optimizing the nutritional environment during chondrocyte culture appears to be a promising, straight-forward approach to improve cartilaginous tissue formation. Future work will investigate the combined effects of the nutritional environment and external stimuli.     

利用基因组改组技术提高短杆菌素产量及其培养条件优化*

短杆菌素是一种广谱抗菌肽,对细菌和真菌均有较好的抑制作用,具有潜在的抗生素替代价值。通过对侧孢短芽孢杆菌fmb70进行紫外诱变、亚硝基胍诱变、常压室温等离子体诱变,获得3株短杆菌素产量提高的诱变菌株。随后以诱变菌株为亲本进行两轮基因组改组,获得融合子F₂-24,其短杆菌素产量为(340.5±16.35) μg/mL,是野生菌株fmb70短杆菌素产量的1.92倍。融合子传代5代后,该菌株短杆菌素产量无明显差异,说明菌株稳定性良好。最后对该菌株产短杆菌素的培养基和发酵条件进行优化,优化后的培养基为:4%蔗糖、2%牛肉膏、0.5%氯化镁,发酵温度30℃、培养24 h、培养基初始pH6.0。优化后的短杆菌素产量可达(442.45±9.58)μg/mL,是初始培养条件的2.50倍。     

Prediction of multi-criteria optimization (MCO) parameter efficiency in volumetric modulated arc therapy (VMAT) treatment planning using machine learning (ML)

PurposeTo predict the impact of optimization parameter changes on dosimetric plan quality criteria in multi-criteria optimized volumetric-modulated-arc therapy (VMAT) planning prior to optimization using machine learning (ML).MethodsA data base comprising a total of 21,266 VMAT treatment plans for 44 cranial and 18 spinal patient geometries was generated. The underlying optimization algorithm is governed by three highly composite parameters which model a combination of important aspects of the solution. Patient geometries were parametrized via volume- and shape properties of the voxel objects and overlap-volume histograms (OVH) of the planning-target-volume (PTV) and a relevant organ-at-risk (OAR). The impact of changes in one of the three optimization parameters on the maximally achievable value range of five dosimetric properties of the resulting dose distributions was studied. To predict the extent of this impact based on patient geometry, treatment site, and current parameter settings prior to optimization, three different ML-models were trained and tested. Precision-recall curves, as well as the area-under-curve (AUC) of the resulting receiver-operator-characteristic (ROC) curves were analyzed for model assessment.ResultsSuccessful identification of parameter regions resulting in a high variability of dosimetric plan properties depended on the choice of geometry features, the treatment indication and the plan property under investigation. AUC values between 0.82 and 0.99 could be achieved. The best average-precision (AP) values obtained from the corresponding precision/recall curves ranged from 0.71 to 0.99.ConclusionsMachine learning models trained on a database of pre-optimized treatment plans can help finding relevant optimization parameter ranges prior to optimization.     

Photon beam energy dependent single-arc volumetric modulated arc optimization

PurposeThe purpose of this work was to present a new single-arc mixed photon (6&18MV) VMAT (SAMP) optimization framework that concurrently optimizes for two photon energies with corresponding partial arc lengths.Methods and materialsOwing to simultaneous optimization of energy dependent intensity maps and corresponding arc locations, the proposed model poses nonlinearity. Unique relaxation constraints based on McCormick approximations were introduced for linearization. Energy dependent intensity maps were then decomposed to generate apertures. Feasibility of the proposed framework was tested on a sample of ten prostate cancer cases with lateral separation ranging from 34 cm (case no.1) to 52 cm (case no.6). The SAMP plans were compared against single energy (6MV) VMAT (SE) plans through dose volume histograms (DVHs) and radiobiological parameters including normal tissue complication probability (NTCP) and equivalent uniform dose (EUD).ResultsThe contribution of higher energy photon beam optimized by the algorithm demonstrated an increase for cases with a lateral separation >40 cm. SAMP–VMAT notably improved bladder and rectum sparing in large size cases. Compared to single energy, SAMP–VMAT plans reduced bladder and rectum NTCP in cases with large lateral separation. With the exception of one case, SAMP–VMAT either improved or maintained femoral heads compared to SE–VMAT. SAMP–VMAT reduced the nontarget tissue integral dose in all ten cases.ConclusionsA single-arc VMAT optimization framework comprising mixed photon energy partial arcs was presented. Overall results underline the feasibility and potential of the proposed approach for improving OAR sparing in large size patients without compromising the target homogeneity and coverage.     

Effects and statistical optimization of fermentation conditions on growth and poly (vinyl alcohol)-degrading enzyme production of Streptomyces venezuelae GY1

The effects of environmental conditions, including temperature, pH and dissolved oxygen, on growth and production of polyvinyl alcohol (PVA)-degrading enzymes of the newly-isolated strain Streptomyces venezuelae GY1 were investigated. The medium composition for strain GY1 was studied first by single factorial design and then optimized using a central composite design. PVA with high saponification is better for growth of, and PVA-degrading enzyme production by S. venezuelae GY1 compared with PVA with low saponification, in contrast with the characteristics of other bacteria producing PVA-degrading enzymes. The optimal temperature and initial pH for production of PVA-degrading enzyme by strain GY1 was 30°C and 7.0, respectively. The optimal medium composition for PVA-degrading enzyme production is: 1.01 g L^?1 of PVA1799, 0.307 g L^?1 of NaNO₃ and 0.512 g L^?1 of MgSO₄?7H₂O.     

Bone Load Estimation for the Proximal Femur Using Single Energy Quantitative CT Data

A density-based load estimation method was applied to determine femoral load patterns. Two-dimensional finite element models were constructed using single energy quantitative computed tomography (QCT) data from two femora. basic load cases included parabolic pressure joint loads and constant tractions on the greater trochanter. An optimization procedure adjusted magnitudes of the basic load cases, such that the applied mechanical stimulus approached the ideal stimulus throughout each model. Dominant estimated load directions were generally consistent with published experimental data for gait. Other estimated loads suggested that loads at extreme joint orientations may be important to maintenance of bone structure. Remodeling simulations with the estimated loads produced density distributions qualitatively similar to the QCT data sets. Average nodal density errors between QCT data and predictions were 0·24 g/cm³ and 0·28 g/cm³. The results indicate that density-based load estimation could improve understanding of loading patterns on bones.