A non-policing honey bee colony (Apis mellifera capensis)

In the Cape honey bee Apis mellifera capensis, workers lay female eggs without mating by thelytokous parthenogenesis. As a result, workers are as related to worker-laid eggs as they are to queen-laid eggs and therefore worker policing is expected to be lower, or even absent. This was tested by transferring worker- and queen-laid eggs into three queenright A. m. capensis discriminator colonies and monitoring their removal. Our results show that worker policing is variable in A. m. capensis and that in one colony worker-laid eggs were not removed. This is the first report of a non-policing queenright honey bee colony. DNA microsatellite and morphometric analysis suggests that the racial composition of the three discriminator colonies was different. The variation in policing rates could be explained by differences in degrees of hybridisation between A. m. capensis and A. m. scutellata, although a larger survey is needed to confirm this.     

Improvements in the two-dimensional nuclear magnetic resonance spectroscopy of humic substances

Understanding pollutant sorption, bioremediation of these pollutants, and their interactions with humic substances requires knowledge of molecular-level processes. New developments with nuclear magnetic resonance (NMR) experiments and labeled compounds have improved the overall understanding of these mechanisms. The advancements made with two-dimensional NMR show great promise, as structural information and hydrogen-carbon bond connectivity can be discerned. This communication presents the application of improved two-dimensional NMR methods, the double quantum filtered (DQF) correlation spectroscopy (COSY) and echo/anti-echo heteronuclear single quantum coherence (HSQC) experiments, for use in structural studies of humic substances. Both experiments were found to produce significant improvements over the conventional COSY and heteronuclear multiple quantum coherence (HMQC) experiments that have been previously employed in similar studies. The more sensitive echo/anti-echo HSQC experiment produced more cross-peaks with higher resolution when compared with the HMQC spectra. The DQF-COSY significantly suppressed the diagonal signals and allowed numerous signals previously hidden in the standard COSY experiment to be observed. These improvements will aid current characterization strategies of humic substances from soils, sediments, and water and their subsequent reactions with pollutants and microorganisms.     

Simulating endosulfan transport in runoff from cotton fields in Australia with the GLEAMS model

Endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9methano-2,4,3-benzodioxathiepin 3-oxide), a pesticide that is highly toxic to aquatic organisms, is widely used in the cotton (Gossypium hirsutum L.) industry in Australia and is a risk to the downstream riverine environment. We used the GLEAMS model to evaluate the effectiveness of a range of management scenarios aimed at minimizing endosulfan transport in runoff at the field scale. The field management scenarios simulated were (i) Conventional, bare soil at the beginning of the cotton season and seven irrigations per season; (ii) Improved Irrigation, irrigation amounts reduced and frequency increased to reduce runoff from excess irrigation; (iii) Dryland, no irrigation; (iv) Stubble Retained, increased soil cover created by retaining residue from the previous crop or a specially planted winter cover crop; and (v) Reduced Sprays, a fewer number of sprays. Stubble Retained was the most effective scenario for minimizing endosulfan transport because infiltration was increased and erosion reduced, and the stubble intercepted and neutralized a proportion of the applied endosulfan. Reducing excess irrigation reduced annual export rates by 80 to 90%, but transport in larger storm events was still high. Reducing the number of pesticide applications only reduced transport when three or fewer sprays were applied. We conclude that endosulfan transport from cotton farms can be minimized with a combination of field management practices that reduce excess irrigation and concentration of pesticide on the soil at any point in time; however, discharges, probably with endosulfan concentrations exceeding guideline values, will still occur in storm events.     

Non-invasive fetal genotyping for maternal alleles with droplet digital PCR: A comparative study of analytical approaches

Objectives

To develop a flexible droplet digital PCR (ddPCR) workflow to perform non-invasive prenatal diagnosis via relative mutation dosage (RMD) for maternal pathogenic variants with a range of inheritance patterns, and to compare the accuracy of multiple analytical approaches.

Methods

Cell free DNA (cfDNA) was tested from 124 archived maternal plasma samples: 88 cases for sickle cell disease and 36 for rare Mendelian conditions. Three analytical methods were compared: sequential probability ratio testing (SPRT), Bayesian and z-score analyses.

Results

The SPRT, Bayesian and z-score analyses performed similarly well with correct prediction rates of 96%, 97% and 98%, respectively. However, there were high rates of inconclusive results for each cohort, particularly for z-score analysis which was 31% overall. Two samples were incorrectly classified by all three analytical methods; a false negative result predicted for a fetus affected with sickle cell disease and a false positive result predicting the presence of an X-linked IDS variant in an unaffected fetus.

Conclusions

ddPCR can be applied to RMD for diverse conditions and inheritance patterns, but all methods carry a small risk of erroneous results. Further evaluation is required both to reduce the rate of inconclusive results and explore discordant results in more detail.     

Comparing computing formulas for estimating concentration ratios

The purpose of this paper is to provide guidance on the choice of computing formulas (estimators) for estimating average concentration ratios and other ratio-type measures of radionuclides and other environmental contaminant transfers between ecosystem components. Mathematical expressions for the expected value of three commonly used estimators (arithmetic mean of ratios, geometric mean of ratios, and the ratio of means) are obtained when the multivariate lognormal distribution is assumed. These expressions are used to explain why these estimators will not in general give the same estimate of the average concentration ratio. They illustrate that the magnitude of the discrepancies depends on the magnitude of measurement biases, and on the variance and correlations associated with spatial heterogeneity and measurement errors. This paper also reports on a computer simulation study that compares the accuracy of eight computing formulas for estimating a ratio relationship that is constant over time and/or space. Statistical models appropriate for both controlled spiking experiments and observational field studies for either normal or lognormal distributions are considered. Our results indicate that for either type of study the geometric mean is generally preferred if the lognormal distribution applies. However, the geometric mean has the disadvantage that its expected value depends on n, the number of measurements taken. Ricker's estimator, $\text{R}\text{?}{}_{\mathrm{rt}}$, appears to perform worse than the other estimators studied when the observations are lognormal. All eight estimators appear to be equally accurate for the controlled spiking study when data are normally distributed. For observational field studies when data are normally distributed the ratio of means or slight modifications thereof are preferred to other estimators investigated. Before one chooses a computing formula for estimating a concentration ratio, thought should be given to what target value needs to be estimated to satisfy study objectives, and to whether the normal or lognormal distribution is a more realistic model. The geometric mean performs well for lognormal distributions, but comparison of geometric means or of a geometric mean with environmental limits can be misleading if n is small. The arithmetic mean of ratios is a conservative choice in that it will always give a larger estimate than will the geometric mean. It may also be severely biased when data are lognormal and the variances of measurement errors are large. The ratio of the means is a reasonable choice if the distribution is normal. The median of the observed ratios, $\text{R}\text{?}{}_{\mathrm{<mtext>md</mtext>}}$, is useful estimate since it is easily obtained and has an easily understood interpretation as the point above which and below which 50% of the observed ratios lie. Also, it is appropriate no matter what the distribution of the observed ratios may be. Confidence limits on the median are also easily obtained. Finally, while this paper emphasizes applications in radionuclide research, our results should be applicable to a wide range of environmental contaminants since many contaminants have approximately lognormal distributions.     

一种改进的多学习教与学优化算法

针对传统教与学算法在解决复杂多峰函数优化问题时,具有局部最优且搜索开发能力较差的缺点,提出了一种改进的多学习教与学优化算法,新算法为学员的每一维加入不同的教学因子,设计了基于学员均值比较的教师选择策略和向教师及学员学习的多学习策略。基于多个单峰和多峰函数的仿真结果表明,新算法跟传统的、改进的教与学算法相比,在稳定性、寻优精度和收敛速度方面更具优势。