Insights from proteome to phosphorylated proteome: deciphering different regulatory mechanisms in goat muscles with high- and low-meat quality

To investigate the inner mechanisms of meat quality differences between high-quality (HQ) and low-quality (LQ), a comparative quantitative study between longissimus thoracis and external intercostals of goat muscle was performed from proteome to phosphorylated proteome using RP-HPLC in combination with the ‘isobaric tag’ for relative and absolute quantitation (iTRAQ) labelling strategy. Altogether, 1441 proteins were identified in our study, of which 673 were phosphoproteins, and a total of twenty were common differentially expressed proteins. Myosin, carbonic anhydrase, and phosphoglucomutase could be used as proteins marker for HQ and LQ meat. Bioinformatics analysis showed that these proteins exhibited different rates for glycolysis and oxidative phosphorylation reaction, thus causing the different pH and NADH change rates, and resulting in better colour, tenderness, and water retention in HQ meat. The release of Ca²⁺ and adenosine triphosphate changed the meat quality through calcium signalling. Our finding provides a comprehensive view of proteome changes and their phosphorylation levels in goat muscle, involved in producing meats of different muscle parts. It also gives a better understanding of the regulation of protein on various biological processes that determine the final meat quality attributes.     

Double emulsion (W/O/W) gel stabilised by polyglycerol polyricinoleate and calcium caseinate as mangiferin carrier: insights on formulation and stability properties

Mangiferin (MGF) is a phenolic compound isolated from mango, but its poor solubility significantly limits its use. In this study, MGF was embedded into the inner aqueous phase of W₁/O/W₂ emulsions. Firstly, the dissolution method of MGF was determined. MGF remained stable in solution with pH 13 at 30 min, and its solubility reached 10 mg mL⁻¹. When the pH of MGF solutions was adjusted from pH 13 to pH 6, MGF did not immediately crystallise, providing sufficient time to construct the MGF-loaded W₁/O/W₂ emulsions. Subsequently, the MGF-loaded W₁/O/W₂ emulsions were constructed using polyglycerol polyricinoleate (PGPR) and calcium caseinate (CAS). The formation and stability of the W₁/O/W₂ emulsions were investigated. The MGF-loaded W₁/O/W₂ emulsions stabilised with 1% PGPR and 1% – 3% CAS exhibited a low viscosity, limited loading capacity, and poor stability. Conversely, the MGF-loaded W₁/O/W₂ emulsions stabilised by 3%PGPR–3%CAS exhibited optimal loading capacity (encapsulation efficiency = 95.31% and loading efficiency = 0.91%) and stability, which was attributed to the fact that high viscosity and gel state retarded the migration of inner aqueous phase. These results indicated that the W₁/O/W₂ emulsions stabilised by PGPR and CAS may be a potential alternative for encapsulating mangiferin.     

天然黏土矿物在靛蓝染色废水电絮凝中的应用

为提高靛蓝染色废水电絮凝处理效率,以天然黏土矿物为协同吸附剂,采用电絮凝-吸附联合工艺处理靛蓝染色废水。探究黏土类型对絮体沉降速率和Zeta电位的影响,通过废水色度、浊度、脱色率和化学需氧量(COD)去除率评价絮凝处理效果。确定最佳黏土矿物种类并结合絮体显微观察,进一步分析黏土矿物与电絮凝的协同作用机制。结果表明:黏土矿物加入可降低Zeta电位绝对值;硅藻土与电絮凝协同的主要絮凝机制为网捕卷扫,同时兼具一定的电荷中和与吸附架桥作用;电絮凝反应结束后,仅需加入1 g/L硅藻土反应3 min,Zeta电位绝对值可达到最低,为15.585 mV,废水脱色率提升至94.08%。     

新媒体环境下智慧化阅读推广研究——以重庆第二师范学院为例

开展智慧化阅读推广,紧跟时代步伐,有效提升读者多重阅读体验和满意度,增强智慧化阅读推广的价值,促进智慧化阅读推广服务的有效化、规范化、科学化、常态化、长期化发展,已成为当前阅读推广研究中一个重要的切入点。文章基于智慧化阅读研究,结合"新媒体"高新技术环境,提出智慧化阅读推广的内容分析、具体实施、环境构建、推广评估与效果、推广改进等几个方面组成的以读者为中心的核心服务体系。本文分析了智慧化阅读基本方面,以我校图书馆实际运用推广效果,智慧化阅读存在的优、劣势及相应的对策。     

Detection of crowdedness in bus compartments based on ResNet algorithm and video images

Multimedia Tools and Applications - The crowding in bus is an important factor affecting passenger satisfaction and bus dispatching level. However, how to use video images to detect crowding...     

Failure Prediction of Municipal Water Pipes Using Machine Learning Algorithms

Pipe failure prediction has become a crucial demand of operators in daily operation and asset management due to the increase in operation risks of water distribution networks. In this paper, two machine learning algorithms, namely, random forest (RF) and logistic regression (LR) algorithms are employed for pipe failure prediction. RF algorithm consists of a group of decision trees that predicts pipe failure independently and makes the final decision by voting together. For the LR algorithm, the mapping relationship between existing data and decision variables is expressed by the logistic function. Then, the prediction is made by comparing the conditional probability with the fixed threshold value. The proposed algorithms are illustrated using an actual water distribution network in China. Results indicate that the RF algorithm performs better than the LR algorithm in terms of accuracy, recall, and area under the receiver operating characteristic curve. The effects of seven characteristics on pipe failures are analyzed, and diameter and length are identified as the top two influential factors.

Graphical Abstract

     

Augmented reality instructions for construction toys enabled by accurate model registration and realistic object/hand occlusions

Virtual Reality - BRICKxAR is a novel augmented reality (AR) instruction method for construction toys such as LEGO®. With BRICKxAR, physical LEGO construction is guided by virtual bricks....     

面向智慧小镇建设的机房电气管线多目标优化布置方法

常规的管线布置优化方法难以在优化过程中得到全局搜索的最优解,导致安全性能无法得到保障,因此面向智慧小镇建设设计一个新的机房电气管线多目标优化布置方法。设置电气管线约束条件,将电压均值、单位时间内电流量、电气管线损耗恢复能力作为目标函数。优化管线布置全局搜索,使用交叉操作的方式不断得到更优解。建立多目标优化电气管线模型,得到电气管线多目标优化的数学模型。通过实验数据可知,该管线布置方法在算法测试中优于常规的3种算法,且在安全性能的检测中只与标准最优值相差6.22×10⁴,3个常规方法与标准最优值的差距为6.813×10⁴、7.6×10⁴、8.32×10⁴,因此可知该多目标优化的管线布置方法可以得到更优解。