Identification of Stingless Bee Honey Adulteration Using Visible-Near Infrared Spectroscopy Combined with Aquaphotomics

Honey is a natural product that is considered globally one of the most widely important foods. Various studies on authenticity detection of honey have been fulfilled using visible and near-infrared (Vis-NIR) spectroscopy techniques. However, there are limited studies on stingless bee honey (SBH) despite the increase of market demand for this food product. The objective of this work was to present the potential of Vis-NIR absorbance spectroscopy for profiling, classifying, and quantifying the adulterated SBH. The SBH sample was mixed with various percentages (10–90%) of adulterants, including distilled water, apple cider vinegar, and high fructose syrup. The results showed that the region at 400–1100 nm that is related to the color and water properties of the samples was effective to discriminate and quantify the adulterated SBH. By applying the principal component analysis (PCA) on adulterants and honey samples, the PCA score plot revealed the classification of the adulterants and adulterated SBHs. A partial least squares regression (PLSR) model was developed to quantify the contamination level in the SBH samples. The general PLSR model with the highest coefficient of determination and lowest root means square error of cross-validation (RCV2=0.96 and RMSECV=5.88 %) was acquired. The aquaphotomics analysis of adulteration in SBH with the three adulterants utilizing the short-wavelength NIR region (800–1100 nm) was presented. The structural changes of SBH due to adulteration were described in terms of the changes in the water molecular matrix, and the aquagrams were used to visualize the results. It was revealed that the integration of NIR spectroscopy with aquaphotomics could be used to detect the water molecular structures in the adulterated SBH.     

BCA法测定蜜蜂变应原中的蛋白含量

建立了用二喹啉甲酸(BCA)法测定蜜蜂变应原中蛋白含量的方法。经t检验证明,该方法的测定结果与微量凯氏定氮法无显著差异,测定结果的相对标准偏差为3．1％。该方法操作简便,结果准确可靠,可替代微量凯氏定氮法。     

Apis mellifera syriaca Venom: Evaluation of Its Anticoagulant Effect,Proteolytic Activity,and Cytotoxicity along with Its Two Main Compounds—MEL and PLA2—On HeLa Cancer Cells

Bee venom (BV) is one of the most remarkable natural products that has been a subject of studies since ancient times. Recent studies have shown that Apis mellifera syriaca venom possesses antibacterial as well as cytotoxic effects on cancer cell lines. The venom contains a variety of bioactive molecules—mainly melittin (MEL) and phospholipase A2 (PLA2), as well as other compounds that are not well characterized. In this work, we continue the biological characterization of A. mellifera syriaca venom by testing its anticoagulant effect on human plasma using the prothrombin time (PT) test, as well as assessing its proteolytic activity. In addition, the cytotoxicity of the crude venom—and of its two main components, MEL and PLA2—was tested on HeLa cancer cell lines for the first time. The results obtained showed the capacity of A. mellifera syriaca venom to increase clotting time, thereby proving its anticoagulant effect. Moreover, the venom did not demonstrate a significant proteolytic activity unless administrated at concentrations ≥ 5 mg/mL. Finally, we showed that crude A. mellifera syriaca venom, along with MEL, exhibit a strong in vitro cytotoxic effect on HeLa cancer cell lines, even at low concentrations. In summary, our findings could serve as a basis for the development of new natural-based drug candidates in the therapeutic field.     

A discrete artificial bee colony algorithm for the multi-objective flexible job-shop scheduling problem with maintenance activities

This paper presents a novel discrete artificial bee colony (DABC) algorithm for solving the multi-objective flexible job shop scheduling problem with maintenance activities. Performance criteria considered are the maximum completion time so called makespan, the total workload of machines and the workload of the critical machine. Unlike the original ABC algorithm, the proposed DABC algorithm presents a unique solution representation where a food source is represented by two discrete vectors and tabu search (TS) is applied to each food source to generate neighboring food sources for the employed bees, onlooker bees, and scout bees. An efficient initialization scheme is introduced to construct the initial population with a certain level of quality and diversity. A self-adaptive strategy is adopted to enable the DABC algorithm with learning ability for producing neighboring solutions in different promising regions whereas an external Pareto archive set is designed to record the non-dominated solutions found so far. Furthermore, a novel decoding method is also presented to tackle maintenance activities in schedules generated. The proposed DABC algorithm is tested on a set of the well-known benchmark instances from the existing literature. Through a detailed analysis of experimental results, the highly effective and efficient performance of the proposed DABC algorithm is shown against the best performing algorithms from the literature.     

珍汕97不育系和保持系水稻花粉发育过程中RNA含量变化的研究

采用组织化学方法，对珍汕９７水稻不育系及保持系的花粉发育过程进行分析，结果表明从幼小的单孢花粉到单核边位出现中央大液泡时期，不育系花粉细胞ＲＮＡ含量与保持系无显著差异，单核末期不育系开始败育，双核期ＲＮＡ含量与保持系双核期花粉细胞相比有显著下降，说明ＲＮＡ含量下降是珍汕９７不育系花粉败育的一个重要生理特征，不育系花粉在单核末期以前发育是正常的．     

An improved artificial bee colony algorithm for directing orbits of chaotic systems

Artificial bee colony algorithm (ABC) is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we propose an improved ABC (IABC) by using a modified search strategy to generate a new food source in order that the exploration and exploitation can be well balanced and satisfactory optimization performances can be achieved. In addition, to enhance the global convergence, when producing the initial population, both opposition-based learning method and chaotic maps are employed. In this paper, the proposed algorithm is applied to control and synchronization of discrete chaotic systems which can be formulated as both multimodal numerical optimization problems with high dimension. Numerical simulation and comparisons with some typical existing algorithms demonstrate the effectiveness and robustness of the proposed approach.     

基于IABC-SVR算法的拉曼光谱定量分析山羊血清蛋白含量

提出了一种基于拉曼光谱和改进人工蜂群算法优化支持向量机回归（IABC-SVR）算法快速定量检测山羊血清蛋白含量的方法。传统人工蜂群算法在数据区域规模较大时,收敛速度逐渐减慢, 出现效率低、精准度下降、局部最优解概率高等问题。所提出的算法解决了这些问题,使算法在进化前期避免陷入局部最优解,在进化中后期能够保持解的全局搜索能力。常规测定血清蛋白总量的方法通常采用凯氏定氮法、双缩脲法等,但存在时效慢、污染样本等缺点。采用拉曼光谱法进行检测,具有快速、无损的优点。以山羊血清为分析对象,按一定体积比配置35组待测样本,用拉曼光谱仪采集拉曼光谱,光谱采集范围为300~1 300 cm-1,采用基线矫正去除荧光背景,使用Savitzky-Golay光谱平滑法对原始光谱进行平滑处理,归一化处理光谱数据,并对拉曼光谱特征峰进行归属。实验结果表明,拉曼光谱能够表征血清中主要化学集团的信息,且由于官能团浓度差异,光谱特征峰强度随浓度变化明显,因此基于特征峰信息可以测定血清蛋白总量。实验中,以购买的山羊血清蛋白含量为基准,通过配置样本的体积比得到各组待测血清样本的蛋白含量,配置的单个液体样本体积为3 mL,随机选取8组实验样本作为模型测试集,剩余27组作为模型训练集。以经过处理的光谱特征峰强度和对应的血清蛋白含量分别作为模型的输入值及输出值,建立IABC-SVR,ABC-SVR和BP三种算法的定量模型,对测试集血清蛋白总量进行预测。最后通过均方差(MSE),相关系数（r）与建模时间分别进行对比,结果表明通过IABC-SVR建立的山羊血清蛋白定量矫正模型效果最佳,模型的相关系数为0.990 27,均方误差为0.244 3,建模时间为1.9 s,预测值方差均小于0.001 g·mL-1,预测准确率为99.8%。实验结果表明,应用激光拉曼光谱技术结合IABC-SVR算法,对快速定量检测山羊血清蛋白含量,具有较高的准确率和稳定性。     

Promising Antimicrobial Properties of Bioactive Compounds from Different Honeybee Products

Bee products have been known for centuries for their versatile healing properties. In recent decades they have become the subject of documented scientific research. This review aims to present and compare the impact of bee products and their components as antimicrobial agents. Honey, propolis, royal jelly and bee venom are bee products that have antibacterial properties. Sensitivity of bacteria to these products varies considerably between products and varieties of the same product depending on their origin. According to the type of bee product, different degrees of activity were observed against Gram-positive and Gram-negative bacteria, yeasts, molds and dermatophytes, as well as biofilm-forming microorganisms. Pseudomonas aeruginosa turned out to be the most resistant to bee products. An analysis of average minimum inhibitory concentration values for bee products showed that bee venom has the strongest bacterial effectiveness, while royal jelly showed the weakest antibacterial activity. The most challenging problems associated with using bee products for medical purposes are dosage and safety. The complexity and variability in composition of these products raise the need for their standardization before safe and predictable clinical uses can be achieved.     

Rutacridone as a Fluorescent Dye for the Study of Pollen

Rutacridone, alkaloid from plant Ruta graveolens was used for the histochemical staining of Hippeastrum hybridum pollen. The rutacridone fluorescence (excited by UV light at 360–380 nm) has been studied with Karnaukhov-constructed microspectrofluorimeters. Nucleus and DNA were stained by this dye in cells and fluoresced by green light with maxima of 530 and 555 nm, respectively. Development of the pollen was analyzed with this dye.     

烟草脱外壁花粉的制备

烟草脱外壁花粉的制备夏惠君，周嫦，杨弘远（武汉大学生命科学学院，武汉，４３００７２）关键词脱外壁花粉，制备，烟草中图法分类号Ｑ９４４．４２花粉粒由外壁、内壁与原生质体３部分组成．有关花粉生物学的研究已有报道［‘·‘ｊ．近年来，花粉原生质体的研究也取得...