氨基酸酯化方法的比较及其红外光谱研究

在合成氨基酸酯锗类化合物时,制备了八种氨基酸酯,对文献提供的六种方法进行了实验比较,选出经济简便、产率高的方法。并对氨基酸及其酯的红外光谱的变化特征进行了研究。     

葛胺酮-大豆卵磷脂复合物的制备、表征及体内药代动力学研究

目的:制备葛胺酮(G20)-大豆卵磷脂复合物,提高G20的口服生物利用度。方法:以复合率为评价指标,采用单因素设计和正交试验优化复合物的制备方案,采用X线衍射分析该复合物的物理性质;SD大鼠分别灌胃给予G20及其卵磷脂复合物,RP-HPLC测定G20血药浓度,用药代动力学软件Winnonlin 5.2计算药动学参数。结果:复合物制备最佳条件为G20与卵磷脂的投料摩尔比为1∶1.5、乙醇量40 mL、反应温度50℃、反应时间2h,复合率为100%。在G20-卵磷脂复合物的X线衍射图中,不存在任何G20特征结晶衍射峰。与G20相比,其G20-卵磷脂复合物的口服生物利用度提高了160%。结论:采用磷脂复合物技术可以显著提高G20的口服生物利用度。     

福州市土壤铬含量高光谱预测的GWR模型研究

通过系统分析不同光谱分辨率和光谱变换对土壤铬高光谱预测模型的不确定性影响,筛选出最优的光谱分辨率及光谱变量进行土壤铬含量预测的地理权重回归(GWR)模型构建,利用该模型进行福州市土壤铬含量预测,并将预测结果与普通最小二乘法回归(OLS)结果进行比较分析,探讨GWR模型在土壤铬高光谱预测中的适用性及局限性。结果表明:(1)在10 nm分辨率尺度下,以土壤全铬含量为因变量,反射率的二阶微分和反射率倒数的二阶微分为自变量构建的GWR模型对土壤铬预测的效果最好。GWR模型的R~2和调节R~2分别为0.821和0.716,较OLS模型分别提高了0.529和0.450,而AIC值为720.703,较OLS模型减少了22个单位,残差平方和仅为OLS模型的1/4,说明GWR模型的预测效果较OLS模型有了显著提高。(2)土壤铬预测模型的精度受光谱分辨率影响。对于OLS预测模型来说,3 nm分辨率的模型预测效果最好,而对于GWR预测模型来说,10nm分辨率的模型不仅预测效果最好,其相较于OLS模型的改善作用显著,为土壤铬含量GWR预测的最佳光谱分辨率。(3)光谱的一阶微分变换可以有效增强土壤铬的光谱特征,而其余的光谱变换对土壤铬的光谱特征则未起到增强作用,但可以很好地提高模型的预测效果。(4)研究得出土壤铬GWR模型预测的最佳光谱分辨率为10 nm,为EO-1 Hyperion影像的光谱分辨率,而且随着采样点的增加,GWR模型的预测效果趋于稳定,适合空间异质性大的区域尺度土壤铬预测。故该模型与高光谱影像结合,实现模型从实验室尺度向区域尺度的推广,为格网尺度土壤铬的空间预测提供可能。     

双载体制备青蒿素速释型固体分散体工艺优化研究

对载体类型影响青蒿素固体分散体中药物溶出度进行研究及优化制备工艺。以大豆卵磷脂与PEG 6000或聚乙烯吡咯烷酮为双分散载体,采用溶剂法制备青蒿素速释型固体分散体,以溶出度为考察指标,单因素试验筛选载体类型及最佳制备工艺;并采用红外吸收光谱法(IR)、差示扫描量热法(DSC)进行物相表征,明确载体-药物存在状态。结果表明在50 min内卵磷脂-PVP K30双载体比卵磷脂-PEG 6000药物溶出度更高,制备固体分散体为速释型,50 min内总溶出度87%以上,显著高于原料药和物理混合物,且优化最佳工艺条件为卵磷脂与PVP K30比为1∶7,搅拌时间30 min,无水乙醇用量20 mL。IR及DSC结果显示在固体分散体中药物可能以无定型状态存在。双载体制备青蒿素速释型固体分散体工艺简单可行,可显著提高药物溶出度,为提高青蒿素疗效奠定重要基础。     

杨梅苷脂质体的制备研究

目的：制备杨梅苷脂质体。方法：采用逆相蒸发法制备杨梅苷脂质体。用冷冻离心法分离脂质体和游离药物,用高效液相色谱法测定药物含量并计算包封率。采用激光粒度仪测定平均粒径。结果：杨梅苷脂质体制备的最佳处方和工艺为：卵磷脂：杨梅6：1,卵磷脂：胆固醇2：1,有机相：水相4：1,磷酸盐缓冲溶液的pH值为6.86,浓度为0.005 mol.L-1;超声时间为5分钟。结论：最佳条件下制备的杨梅苷脂质体包封率较高,粒径分布好,质量稳定。     

基于光谱指数的喀斯特植物叶片叶绿素含量定量估算

为了探讨适合于喀斯特植物叶片叶绿素含量估算的光谱指数,在总结以往基于光谱指数的植物生化参数估算研究基础上发现,常用光谱指数通常采用差值、比值、归一化以及倒数差值方式来构建。因此,我们通过上述4种光谱指数构建方式对所采集的4种典型喀斯特植物——黄荆(Vitex negundo)、盐麸木(Rhus chinensis)、朴树(Celtis sinensis)和红背山麻杆(Alchornea trewioides)叶片原始光谱反射率及其一阶导数值与同步测定的叶片叶绿素含量进行遍历分析,以期获得最优光谱指数并将其应用于喀斯特植物叶片叶绿素含量定量估算研究。结果表明:(1)常用光谱指数中,改良红边归一化指数(modified red-edge normalized difference vegetation index, mND705)对喀斯特植物叶片叶绿素含量估算效果较好(决定系数为0.45,均方根误差为0.26 mg·g^-1)。(2)虽然荧光比值(fluorescence ratio index, FRI1)和叶绿素吸收面积光谱指数(chlorophyll absorption area index, CAAI)在估算喀斯特与非喀斯特植物叶片叶绿素含量能力相当,但是其估算精度相对较低(决定系数小于0.45)。(3)通过差值、比值、归一化以及倒数差值方式构建的光谱指数无论是基于植物叶片原始光谱反射率,还是其一阶导数值,相比常用光谱指数都能更好地估算喀斯特植物叶片叶绿素含量(决定系数大于0.60)。其中,基于植物叶片原始光谱反射率一阶导数值的差值光谱指数 [dD(760, 769)]对喀斯特植物叶片叶绿素含量的估算精度最好,其决定系数为0.71,均方根误差为0.19 mg·g^-1。综上可知,结合高光谱遥感技术的光谱指数模型可快速定量估算喀斯特植物叶片叶绿素含量,为典型喀斯特地区植物生长诊断及其对环境胁迫适应性评价提供重要科学依据和技术支持。     

木鳖子种仁油中特殊脂肪酸成分的研究

<正> 葫芦科植物木鳖子Momordica cochinchinensis (Lour.) Spr.的种子入药,功能消肿、散结、祛毒。它分布于我国四川、湖北、河南、安徽,浙江、福建、广东、广西、贵州和云南等地。该种子富含油脂,种仁含油率高达41.2％。其化学组成,经气相色谱法鉴定其混合脂肪酸甲酯,紫外光谱和红外光谱测试其混合脂肪酸,同时制备其顺丁烯二酸酐的衍生物,通过熔点,红外光谱及质谱法鉴定此衍生物,证实该种子油中含有29.02％的α-桐酸组分。     

免标记光学纳米生物传感器的研究

利用发光稳定的多孔硅,当蛋白质溶液固定到多孔硅表面时,其发光强度和反射光谱的峰位会随着被测物质量浓度的变化而发生变化的特性。制备免标记光学纳米生物传感器来检测牛血清白蛋白（BSA）,把不同质量浓度的BSA溶液固定到多孔硅上测量反射光谱的峰位和荧光强度的变化。实验结果表明：反射光谱的峰位与牛血清白蛋白的浓度呈线性关系：y=1．4189x＋366．31,R^2=0．9898;荧光强度的降低量与BSA溶液的浓度呈线性关系,检测限为8×10^-9 mol／L。     

细菌光谱检测方法与分子机制的研究进展

细菌是人类最常见的致病源之一,不仅严重危害人类健康和公共卫生安全,还带来了巨额的医疗支出。快速而准确的细菌检测对细菌感染的治疗具有重要的意义。光谱检测方法不但可以快速实时地获得细菌的分类、含量以及功能状态等信息,而且具有操作简单、非侵入性的优势,在细菌检测领域具有巨大的潜力。本文介绍了拉曼光谱、太赫兹光谱、可见光和近红外光光谱、荧光光谱在细菌检测方面的研究与应用,并对可见光和近红外光光谱的分子机制——光靶点,包括含有视网膜发色团的细菌视紫红质(CBCRs)、带有四吡咯发色团的拟菌植物色素、带有对香豆酸发色团的光活性黄蛋白(PYP)、带有黄素单核苷酸(FMN)的光氧压力(LOV)结构域、带有黄素腺嘌呤二核苷酸(FAD)发色团的隐色剂和含有FAD的蓝光感应域等进行了阐述。最后,针对现有细菌光谱检测技术的优缺点提出了细菌检测技术的优化策略,希望对细菌的光谱检测研究提供帮助。     

拉曼光谱技术在微生物学中的应用

拉曼光谱具有快速、灵敏、无损、实时监测等显著特点,在微生物学领域得到广泛应用。分别介绍共焦显微拉曼光谱、共振拉曼光谱、表面增强拉曼光谱、拉曼成像、相干反斯托克斯拉曼光谱、激光镊子拉曼光谱和Raman-FISH的原理和特点,并重点总结和分析不同拉曼光谱技术在微生物的结构、化学组成,以及代谢过程等相关研究中的应用优势。合理利用这些技术在基础微生物、发酵微生物和微生物诊断等方面具有潜在的应用价值。     

Differences between vocalization evoked by social stimuli in feral cats and house cats

To investigate how socialization can affect the types and characteristics of vocalization produced by cats, feral cats (n = 25) and house cats (n = 13) were used as subjects, allowing a comparison between cats socialized to people and non-socialized cats. To record vocalization and assess the cats’ responses to behavioural stimuli, five test situations were used: approach by a familiar caretaker, by a threatening stranger, by a large doll, by a stranger with a dog and by a stranger with a cat.Feral cats showed extremely aggressive and defensive behaviour in most test situations, and produced higher call rates than those of house cats in the test situations, which could be attributed to less socialization to other animals and to more sensitivity to fearful situations. Differences were observed in the acoustic parameters of feral cats in comparison to those of house cats. The feral cat produced significantly higher frequency in fundamental frequency, peak frequency, 1st quartile frequency, 3rd quartile frequency of growls and hisses in agonistic test situations. In contrast to the growls and hisses, in meow, all acoustic parameters like fundamental frequency, first formant, peak frequency, 1st quartile frequency, and 3rd quartile frequency of house cats were of significantly higher frequency than those of feral cats. Also, house cats produced calls of significantly shorter in duration than feral cats in agonistic test situations.These results support the conclusion that a lack of socialization may affect usage of types of vocalizations, and the vocal characteristics, so that the proper socialization of cat may be essential to be a suitable companion house cat.     

Variability in the performance of the spectrogram correlation detector for North-east Pacific blue whale calls

Spectrogram correlation has been used successfully for automatic detection of baleen whale calls. However, applying this method consistently to long time series can be challenging. To illustrate the potential challenges of the automatic detection process, recordings collected in the Southern California Bight between 2007 and 2012 were used for detection of North-east Pacific blue whale (Balaenoptera musculus) B calls. The effects of the following factors were investigated: blue whale B call frequency shift and appropriate kernel modification, seasonal variability in call abundance, analyst variability and noise. Due to intra- and inter-annual changes in the call frequency of blue whale B calls, seasonal and annual adjustments to the call detection kernel were needed. To account for seasonal variability in call production, evaluation of the detector against ground truth data was performed at multiple times during the year. Analyst variability did not affect overall long-term trends in detection, but it had an impact on the total number of detections, as well as call rate estimation. Noise, particularly from shipping, was negatively correlated with detections at hourly time scales. A detailed analysis of variability in the performance of spectrogram correlation detectors should be performed when applying this method to long-term acoustic data-sets.     

白腹管鼻蝠成体交流声波多样性

小蝙蝠亚目即通常所说的蝙蝠,是哺乳动物中群居程度最高的类群之一,主要依靠声学信号在黑暗环境中进行交流并维持社群结构,很多蝙蝠种类的交流声波具有极高的多样性,但是目前关于特定种类蝙蝠交流声波的研究还比较缺乏。我们通过录制白腹管鼻蝠(Murina leucogaster)成体的声波,深入研究其交流声波声谱特征,根据交流声波在声谱图上的形状对声波类型进行初步划分,并利用主成分分析(PCA)和判别分析(DFAs)进行验证。结果表明,其交流声波在声谱结构上具有较高多样性,分为16种不同的音节类型,其中包括13种简单音节和3种组合音节,大多数音节都具有多谐波结构。简单音节可分为9种调频音节、2种准恒频音节和2种噪音,组合音节由简单音节无间隔地组合而成。第一谐波最大频率、第一谐波带宽、持续时间为与调频音节类型相关的主要参数。本研究结果为今后进一步开展研究蝙蝠发声行为的行为学意义和声波交流的神经生理学机制方面的研究奠定了基础。     

An audio–visual nest monitoring system for the study and manipulation of siblicide in bearded vultures <Emphasis Type="Italic">Gypaetus barbatus</Emphasis> on the island of Crete (Greece)

We describe here an automated surveillance system that was installed in a bearded vulture (Gypaetus barbatus) nest in Crete during 2003–2006 with the aim of studying siblicide in this species. The system caused only minimal levels of disturbance to the birds and was capable of operating autonomously for more than 1 week. It comprised (1) a nest monitoring subsystem (camera, microphone, battery with a charge controller and a transmitter together with an antenna), which was supported by a solar panel, and (2) a recording subsystem (antenna receiver, video signal controller and a remote controlled PC through a GSM modem) that compressed the audio–video signal and provided real time monitoring. Two-egg clutches with a 7-day laying and hatching interval were recorded while hatching asynchrony was also determined through an analysis of the bioacoustic data. Food delivery rate and number of feeds to the first chick increased after the hatching of its sibling although not significantly so. Of the aggressive interactions recorded, 98% were initiated by the dominant chick and resulted in an average of 246 ± 157 peckings per day. Supplementary feeding did not produce any significant correlation between feeding rate and sibling aggression. The second chick survived 5 days and died as a result of starvation accelerated by sibling aggression. Intervention measures aimed at increasing the survival chance of the second chick should be undertaken when the latter is 1–2 days old.     

Multivariate classification of animal communication signals: A simulation-based comparison of alternative signal processing procedures using electric fishes

Evolutionary studies of communication can benefit from classification procedures that allow individual animals to be assigned to groups (e.g. species) on the basis of high-dimension data representing their signals. Prior to classification, signals are usually transformed by a signal processing procedure into structural features. Applications of these signal processing procedures to animal communication have been largely restricted to the manual or semi-automated identification of landmark features from graphical representations of signals. Nonetheless, theory predicts that automated time-frequency-based digital signal processing (DSP) procedures can represent signals more efficiently (using fewer features) than can landmark procedures or frequency-based DSP – allowing more accurate classification. Moreover, DSP procedures are objective in that they require little previous knowledge of signal diversity, and are relatively free from potentially ungrounded assumptions of cross-taxon homology. Using a model data set of electric organ discharge waveforms from five sympatric species of the electric fish Gymnotus, we adopted an exhaustive simulation approach to investigate the classificatory performance of different signal processing procedures. We considered a landmark procedure, a frequency-based DSP procedure (the fast Fourier transform), and two kinds of time-frequency-based DSP procedures (a short-time Fourier transform, and several implementations of the discrete wavelet transform -DWT). The features derived from each of these signal processing procedures were then subjected to dimension reduction procedures to separate those features which permit the most effective discrimination among groups of signalers. We considered four alternative dimension reduction methods. Finally, each combination of reduced data was submitted to classification by linear discriminant analysis. Our results support theoretical predictions that time-frequency DSP procedures (especially DWT) permit more efficient discrimination of groups. The performance of signal processing was found to depend largely upon the dimension reduction procedure employed, and upon the number of resulting features. Because the best combinations of procedures are dataset-dependent and difficult to predict, we conclude that simulations of the kind described here, or at least simplified versions of them, should be routinely executed before classification of animal signals - especially unfamiliar ones.     

Accounting for variability in sample size estimation with applications to nonadherence and estimation of variance and effect size

We consider sample size calculations for testing differences in means between two samples and allowing for different variances in the two groups. Typically, the power functions depend on the sample size and a set of parameters assumed known, and the sample size needed to obtain a prespecified power is calculated. Here, we account for two sources of variability: we allow the sample size in the power function to be a stochastic variable, and we consider estimating the parameters from preliminary data. An example of the first source of variability is nonadherence (noncompliance). We assume that the proportion of subjects who will adhere to their treatment regimen is not known before the study, but that the proportion is a stochastic variable with a known distribution. Under this assumption, we develop simple closed form sample size calculations based on asymptotic normality. The second source of variability is in parameter estimates that are estimated from prior data. For example, we account for variability in estimating the variance of the normal response from existing data which are assumed to have the same variance as the study for which we are calculating the sample size. We show that we can account for the variability of the variance estimate by simply using a slightly larger nominal power in the usual sample size calculation, which we call the calibrated power. We show that the calculation of the calibrated power depends only on the sample size of the existing data, and we give a table of calibrated power by sample size. Further, we consider the calculation of the sample size in the rarer situation where we account for the variability in estimating the standardized effect size from some existing data. This latter situation, as well as several of the previous ones, is motivated by sample size calculations for a Phase II trial of a malaria vaccine candidate.     

Technologies and methods for sample pretreatment in efficient proteome and peptidome analysis

Although great progresses have been made in proteomics during the last decade, proteomics is still in its infancy. Extreme complexity of proteome sample and large dynamic range of protein abundance overwhelm the capability of all currently available analytical platforms. Sample pretreatment is a good approach to reduce the complexity of proteome sample and decrease the dynamic range. In this article, we present an overview of different technologies and methods for sample pretreatment in efficient proteome and peptidome analysis. Methods for isolation of rare amino acid-containing peptides, terminal peptides, PTM peptides and endogenous peptides are reviewed. In addition, two automated sample pretreatment technologies, i.e. automated sample injection and on-line digestion, are also covered.     

Combining counts and incidence data: an efficient approach for estimating the log-normal species abundance distribution and diversity indices

Obtaining accurate estimates of diversity indices is difficult because the number of species encountered in a sample increases with sampling intensity. We introduce a novel method that requires that the presence of species in a sample to be assessed while the counts of the number of individuals per species are only required for just a small part of the sample. To account for species included as incidence data in the species abundance distribution, we modify the likelihood function of the classical Poisson log-normal distribution. Using simulated community assemblages, we contrast diversity estimates based on a community sample, a subsample randomly extracted from the community sample, and a mixture sample where incidence data are added to a subsample. We show that the mixture sampling approach provides more accurate estimates than the subsample and at little extra cost. Diversity indices estimated from a freshwater zooplankton community sampled using the mixture approach show the same pattern of results as the simulation study. Our method efficiently increases the accuracy of diversity estimates and comprehension of the left tail of the species abundance distribution. We show how to choose the scale of sample size needed for a compromise between information gained, accuracy of the estimates and cost expended when assessing biological diversity. The sample size estimates are obtained from key community characteristics, such as the expected number of species in the community, the expected number of individuals in a sample and the evenness of the community.     

Satellite Telemetry in Avian Research and Management: Sample Size Considerations

Abstract: Satellite tracking is currently used to make inferences to avian populations. Cost of transmitters and logistical challenges of working with some species can limit sample size and strength of inferences. Therefore, careful study design including consideration of sample size is important. We used simulations to examine how sample size, population size, and population variance affected probability of making reliable inferences from a sample and the precision of estimates of population parameters. For populations of >100 individuals, a sample >20 birds was needed to make reliable inferences about questions with simple outcomes (i.e., 2 possible outcomes). Sample size demands increased rapidly for more complex problems. For example, in a problem with 3 outcomes, a sample of >75 individuals will be needed for proper inference to the population. Combining data from satellite telemetry studies with data from surveys or other types of sampling may improve inference strength.