Seasonality in elephant dung decay and implications for censusing and population monitoring in south-western Cameroon

Dung decay rates have been used in the past to correct elephant dung counts to estimates of population numbers. These assume that the dung is in a ‘steady state’ where production rates are equal to disappearance rates. The inter‐seasonal variation in decay rates, however, has never been fully investigated for elephant dung. This study, in the Banyang‐Mbo Wildlife Sanctuary in SW Cameroon, investigated whether a single dung decay rate is really appropriate when converting dung counts to population density estimates. A total of 870 fresh elephant dung‐piles were monitored until they had completely decayed, with at least 60 fresh dung piles located each month of the year between July 1994 to June 1995. The elephant dung decay rate obtained was 55.6% to 66.7% lower than those obtained for the rainforests of Gabon. This has implications for using decay rates obtained elsewhere to compute elephant densities from dung counts. Statistically significant differences were found in the mean duration of dung‐piles between different months and different seasons. Environmental variables, with the exception of rainfall, did not aid in predicting the duration of elephant dung‐piles. The model of Plumptre & Harris was used to estimate the standing crop of dung at any particular time of the year. The results show that, if there was no emigration of elephants from the population, then there was only a three‐month period when the dung was in a ‘steady state’. If emigration occurred during the wet season as is thought to occur then there was no period of ‘steady state’.     

Selection and validation of normalization methods for c-DNA microarrays using within-array replications

MOTIVATION: Normalization of microarray data is essential for multiple-array analyses. Several normalization protocols have been proposed based on different biological or statistical assumptions. A fundamental problem arises whether they have effectively normalized arrays. In addition, for a given array, the question arises how to choose a method to most effectively normalize the microarray data. RESULTS: We propose several techniques to compare the effectiveness of different normalization methods. We approach the problem by constructing statistics to test whether there are any systematic biases in the expression profiles among duplicated spots within an array. The test statistics involve estimating the genewise variances. This is accomplished by using several novel methods, including empirical Bayes methods for moderating the genewise variances and the smoothing methods for aggregating variance information. P-values are estimated based on a normal or chi approximation. With estimated P-values, we can choose a most appropriate method to normalize a specific array and assess the extent to which the systematic biases due to the variations of experimental conditions have been removed. The effectiveness and validity of the proposed methods are convincingly illustrated by a carefully designed simulation study. The method is further illustrated by an application to human placenta cDNAs comprising a large number of clones with replications, a customized microarray experiment carrying just a few hundred genes on the study of the molecular roles of Interferons on tumor, and the Agilent microarrays carrying tens of thousands of total RNA samples in the MAQC project on the study of reproducibility, sensitivity and specificity of the data. AVAILABILITY: Code to implement the method in the statistical package R is available from the authors.     

A study of the macro-environment at BenCat in southern Vietnam

Based on the meteorological data over a period of 4 years (1980–3), the macro-environment of BenCat Farm situated in the southern part of Vietnam (27 m above mean sea-level, 11° N and 106° E) was categorized as a “monsoon tropical climate”, due to heavy rainfall (annual mean 2028.96 mm) and about 32% wet days (annual mean 116.52 days) together with high air temperature (annual mean daily temperature 28.58, max. 32.33 and min 24.85° C). April was the hottest (monthly mean >35°C) and January the coldest month (monthly mean <22° C) of the year. The maximum number of wet days were during September and October (mean 18 days.month), whereas the minimum number of wet days were during January and February (mean <1 day/month). The months of December and January at Ben-Cat buffalo farm were categorized as the “comfortable (moderate-Dry) period” as the mean daily temperature was <27° C, while the remaining 10 months of the Calender year (February–November) were categorized as the “hot period” (mean daily temperature >27° C). On the basis of rainfall and the number of wet days, the hot period was further subdivided into a “hot-dry period” (February–April, mean of 1.67 wet days/month and mean rainfall 19.43 mm/month) and a “hot-humid period” (May–November, mean of 15.57 wet days/month and mean rainfall 276.28 mm/month).     

Hospital admission for acute pancreatitis in an English population, 1963-98: database study of incidence and mortality

Objectives To investigate trends in the incidence of acute pancreatitis resulting in admission to hospital, and mortality after admission, from 1963 to 1998.Design Analysis of hospital inpatient statistics for acute pancreatitis, linked to data from death certificates.Setting Southern England.Subjects 5312 people admitted to hospital with acute pancreatitis.Main outcome measures Incidence rates for admission to hospital, case fatality rates at 0-29 and 30-364 days after admission, and standardised mortality ratios at monthly intervals up to one year after admission.Results The incidence of acute pancreatitis with admission to hospital increased from 1963-98: age standardised incidence rates were 4.9 per 100 000 population in 1963-74, 7.7 in 1975-86, and 9.8 in 1987-98. Age standardised case fatality rates within 30 days of admission were 14.2% in 1963-74, 7.6% in 1975-86, and 6.7% in 1987-98. From 1975-98, standardised mortality ratios at 30 days were 30 in men and 31 in women (compared with the general population of equivalent age in the same period = 1), and they remained significantly increased until month 5 for men and month 6 for women.Conclusions Incidence rates for acute pancreatitis with admission to hospital rose in both men and women from 1963 to 1998, particularly among younger age groups. This probably reflects, at least in part, an increase in alcoholic pancreatitis. Mortality after admission has not declined since the 1970s. This presumably reflects the fact that no major innovations in the treatment of acute pancreatitis have been introduced. Pancreatitis remains a disease with a poor prognosis during the acute phase.     

Rainfall and the population dynamics of elephant dung‐piles in the forests of southern Ghana

Decaying dung‐piles were observed at three sites in the lowland forests of southern Ghana. Time to disappearance was inversely related to rainfall in the month of deposition. The monthly survival of each age‐class decreased with age and was inversely proportional to rainfall in the month of deposition. A simulation revealed that if elephant numbers and defaecation rates are constant, then dung density in a given month will be governed by rainfall in the two preceding months. Changes in annual rainfall and its monthly distribution in southern Ghana mean that dung‐pile densities will vary from one month to the next, and between the same months in different years, even if elephant numbers are constant. Thus dung counters must take rainfall into account. A new method of censusing elephants in Ghana is presented, and suggestions are made for improving elephant counts in central African forests.     

A comparison of methods for fitting allometric equations to field metabolic rates of animals

We re-examined data for field metabolic rates of varanid lizards and marsupial mammals to illustrate how different procedures for fitting the allometric equation can lead to very different estimates for the allometric coefficient and exponent. A two-parameter power function was obtained in each case by the traditional method of back-transformation from a straight line fitted to logarithms of the data. Another two-parameter power function was then generated for each data-set by non-linear regression on values in the original arithmetic scale. Allometric equations obtained by non-linear regression described the metabolic rates of all animals in the samples. Equations estimated by back-transformation from logarithms, on the other hand, described the metabolic rates of small species but not large ones. Thus, allometric equations estimated in the traditional way for field metabolic rates of varanids and marsupials do not have general importance because they do not characterize rates for species spanning the full range in body size. Logarithmic transformation of predictor and response variables creates new distributions that may enable investigators to perform statistical analyses in compliance with assumptions underlying the tests. However, statistical models fitted to transformations should not be used to estimate parameters of equations in the arithmetic domain because such equations may be seriously biased and misleading. Allometric analyses should be performed on values expressed in the original scale, if possible, because this is the scale of interest.     

Empirical evaluation of data transformations and ranking statistics for microarray analysis

There are many options in handling microarray data that can affect study conclusions, sometimes drastically. Working with a two-color platform, this study uses ten spike-in microarray experiments to evaluate the relative effectiveness of some of these options for the experimental goal of detecting differential expression. We consider two data transformations, background subtraction and intensity normalization, as well as six different statistics for detecting differentially expressed genes. Findings support the use of an intensity-based normalization procedure and also indicate that local background subtraction can be detrimental for effectively detecting differential expression. We also verify that robust statistics outperform t-statistics in identifying differentially expressed genes when there are few replicates. Finally, we find that choice of image analysis software can also substantially influence experimental conclusions.     

Growth and development of infant giant pandas (Ailuropoda melanoleuca) at the Wolong Reserve,China

From 1991 to 1993 inclusive, seven infant giant pandas (Ailuropoda melanoleuca) were born at the China Conservation and Research Center for the Giant Panda. Average daily weight gain in the first 6 months for mother-reared infants (n = 5) was 71.3 g/day; for one partially mother-reared and partially hand-reared infant, 41.5 g/day; and for one completely hand-reared infant, 50.3 g/day. There was a significant difference in growth rates across the first 6 months in all methods of rearing. In addition, a comparison of growth rates across the three rearing methods showed significant differences in the first, second, third, fifth, and sixth months. Average daily body length increase for mother-reared infants was 4.1 mm/day; for partially mother-reared/partially hand-reared infants, 4.0 mm/day; and for the completely hand-reared infant, 2.8 mm/day. In mother-reared infants, body length increase during the first month was significantly greater than during the following months, and was slowest during the sixth month. At birth, infants were all pink in color with a light white coat of lanugo. Black pigmentation was first noted at 7–10 days of age, which was also the time that initial hair coat growth was seen. Eyes opened at 35–48 days of age. Ears opened at 31–50 days of age. Deciduous dentition was first seen at 82–121 days of age, while permanent dentition began to erupt at 350 days of age. © 1996 Wiley-Liss, Inc.     

Evaluation of specific gravity as normalization strategy for cattle urinary metabolome analysis

Urine is an ideal biofluid for metabolomics studies since it is obtained noninvasively, and its composition is affected by genetic and environmental factors reflecting the physiology of multiple organs. However, urine dilution effects and instrumental variation from the analytical method play a significant confounding role when one attempts to characterize biological and physiological factors through NMR and MS measurements of small molecule concentrations. Several normalization approaches have been used for urinary metabolomics studies and normalization to osmolality or to total useful MS signal have been proposed. When dealing with urinary metabolome analysis in cattle, freeze-drying (FD) is the method commonly used for normalization purposes. Herein, normalization to specific gravity, which provides a fair estimation of urine osmolality, was compared to the time consuming FD step and to the normalization to total useful MS signal in order to assess if this approach could be used as normalization strategy to differentiate control from anabolic treated animals. The results revealed that ~80 % of the metabolites detected as constituting the acquired MS fingerprints for the freeze-dried samples and for the samples normalized to both specific gravity (SG) and total useful MS signal were in common. In addition, similar information from the multivariate statistical analysis was obtained by both normalization approaches. We demonstrate, therefore, that SG can be used as normalization approach for urinary metabolome analysis in cattle resulting in a high sample throughput procedure when compared with the FD step.     

SynteBase/SynteView: a tool to visualize gene order conservation in prokaryotic genomes

Background

Most microarray studies are made using labelling with one or two dyes which allows the hybridization of one or two samples on the same slide. In such experiments, the most frequently used dyes areCy3 andCy5. Recent improvements in the technology (dye-labelling, scanner and, image analysis) allow hybridization up to four samples simultaneously. The two additional dyes areAlexa488 andAlexa494. The triple-target or four-target technology is very promising, since it allows more flexibility in the design of experiments, an increase in the statistical power when comparing gene expressions induced by different conditions and a scaled down number of slides. However, there have been few methods proposed for statistical analysis of such data. Moreover the lowess correction of the global dye effect is available for only two-color experiments, and even if its application can be derived, it does not allow simultaneous correction of the raw data.

Results

We propose a two-step normalization procedure for triple-target experiments. First the dye bleeding is evaluated and corrected if necessary. Then the signal in each channel is normalized using a generalized lowess procedure to correct a global dye bias. The normalization procedure is validated using triple-self experiments and by comparing the results of triple-target and two-color experiments. Although the focus is on triple-target microarrays, the proposed method can be used to normalizepdifferently labelled targets co-hybridized on a same array, for any value ofpgreater than 2.

Conclusion

The proposed normalization procedure is effective: the technical biases are reduced, the number of false positives is under control in the analysis of differentially expressed genes, and the triple-target experiments are more powerful than the corresponding two-color experiments. There is room for improving the microarray experiments by simultaneously hybridizing more than two samples.     

Circannual Variation in the Incidence of Uterine Cervix Cancer

The impact of uterine cervix cancer (UCC) can be greatly reduced by regular vaginal examination and other preventive measures. With this aim, UCC screening programs had been developed and applied for several years in Mexico and elsewhere. One point still to be considered in such preventive programs is the possible circannual pattern in the morbidity or mortality of UCC. With the aim of identifying a possible circannual pattern of variation in the incidence of UCC, we analyzed the monthly totals of positive detected cases of UCC in the state of Nuevo León (Mexico) between 1978 and 1987. For eliminating bias due to the seasonal variation in the number of preventive check-ups, data were first expressed in percentage of tests done in the same month. The least-squares fit of a 1 -year cosine curve to the data reveals a statistically significant circannual pattern (p = 0.013), with a maximum of relative incidence detected in February. Results indicate UCC incidence higher than the yearly average during the winter, with secondary peaks in August and November. This pattern of variation is similar if one considers separately for analysis the relative incidence of type III, IV, or V UCC (relating to cases suggesting, highly suggesting, or concluding a malignant alteration, respectively). For evaluating the cost-effectiveness of the UCC screening campaign providing these data, the monthly totals of screening check-ups done over the same period were also analyzed. Results reveal a statistically significant circannual rhythm (p > 0.001), with a maximum detected in June. This timing seems to be related to the incidence of most common diseases in Mexico, such as giardiasis and salmonellosis, but not to the UCC morbidity rates. Health educational and screening campaigns for prevention of UCC and other major conditions should be timed during the year according to morbidity and mortality statistics, for which a circannual pattern of variation is documented herein.     

Physiological Daily Inhalation Rates for Free-Living Individuals Aged 2.6 Months to 96 Years Based on Doubly Labeled Water Measurements: Comparison with Time-Activity-Ventilation and Metabolic Energy Conversion Estimates

In the first part of this article, a critical review of traditional approaches used to estimate daily inhalation rates as a function of age for health risk assessment purposes shows that such rates are not totally reliable due to various biases introduced by both quantitative and qualitative deficiencies regarding certain input parameters. In the second part, the magnitude of under- and overestimations of published inhalation rates derived from each approach is described by a comparison with new sets of physiological daily inhalation rates and distribution percentile values based on total daily energy expenditures (TDEEs) measured by the doubly labeled water (DLW) method. TDEEs are derived from the analysis of deuterium (²H) and heavy oxygen-18 (¹⁸O) in urine samples by gas-isotope-ratio mass spectrometry during an aggregate period of over 20,000 days for unrestrained free-living normal-weight individuals aged 2.6 months to 96 years (n = 1252). Regarding physiological values based on DLW measurements, opposite tendencies have been observed between two sets of estimates using time-activity patterns both biased by conservative input data assumptions during sleep and light activities: most estimates based on the time-activity-ventilation approach are overestimated, whereas most of those using metabolic equivalent approach are underestimated. Erroneous food intakes have clearly lead to underestimated rates when used in daily food-energy intake (EFD) and Parameter A approaches. With the latter approach, overestimated basal metabolic rates (BMRs) used in EFD/BMR ratios contribute to the underestimation of inhalation values. Few mean daily inhalation rates and Monte Carlo simulation percentiles based on traditional approaches (57 out of 253) are close to physiological values within a gap of ± 5% or less. Aggregate errors in all estimates (in m³/day and m³/kg-day) vary from -52 to +126%. The most accurate daily inhalation rates are those based on DLW measurements with an error of about ± 5%, as calculated in previous studies for free-living males and females aged 1 month to 96 years and pregnant and lactating adolescents and women aged 11 to 55 years during real-life situations in their normal surroundings.     

How should we normalize electromyograms obtained from healthy participants? What we have learned from over 25 years of research

Electromyograms (EMGs) need to be normalized if comparisons are sought between trials when electrodes are reapplied, as well as between different muscles and individuals. The methods used to normalize EMGs recorded from healthy individuals have been appraised for more than a quarter of a century. Eight methods were identified and reviewed based on criteria relating to their ability to facilitate the comparison of EMGs. Such criteria included the magnitude and pattern of the normalized EMG, reliability, and inter-individual variability. If the aim is to reduce inter-individual variability, then the peak or mean EMG from the task under investigation should be used as the normalization reference value. However, the ability of such normalization methods to facilitate comparisons of EMGs is questionable. EMGs from MVCs can be as reliable as those from submaximal contractions, and do not appear to be affected by contraction mode or joint kinematics, particularly for the elbow flexors. Thus, the EMG from an isometric MVC is endorsed as a normalization reference value. Alternatively the EMG from a dynamic MVC can be used, although it is recognized that neither method is guaranteed to be able to reveal how active a muscle is in relation to its maximal activation capacity.     

Seasonal,unimodal lunar‐day oscillations in potato O2‐consumption

Abstract

O₂‐consumption of sprouting potato plugs in constant conditions was monitored hourly over ten years. The data for each month was reorganized to obtain the mean rate for each hour of the lunar day. All the data revealed a very low amplitude residual lunar‐day pattern, range less than 1%, with a lesser minimum at upper transit of the moon and major maximum at lower transit. Hourly variances disclosed a significantly greater range from upper transit to lower than for the rest of the day. To discover possible inverting tendencies for the lunar cycles, the mean monthly days were divided into quarters with each quarter expressed as its deviation from the daily mean. Greater negative correlation than random (—0.333) would indicate an inverting semidiurnal cycle if found between adjacent quarters, and a diurnal if between alternate ones. A diurnal cycle was demonstrated (P<.001) using all data when the quarters included centering on upper transit but not when the quarter terminated at this time. Using the upper‐transit‐centered quarterly series an annual modulation was found, with a highly significant diurnal cycle (P<.000001) for the months September‐February and only randomness for March‐August. The results during fall and winter indicate a family of inverting diurnal lunar‐day cycles with maxima at upper transit, lower transit, moonrise, or moonset. Neither diurnal nor semidiurnal lunar cycles occurred the remainder of the year.     

毛乌素沙地海流兔河流域植被净初级生产力估算

采用CASA(Carnegie-Ames-Stanford Approach)模型,结合TERRA MODIS卫星数据和气象数据,对毛乌素沙地海流兔河流域2015年各月的植被净初级生产力(NPP)进行估算,并对植被NPP月平均值的时空分布规律及其与气象因子和地下水位埋深的关系进行了分析.结果表明:毛乌素沙地海流兔河流域2015年植被NPP总量为2.88×1011 g,生长季(4月份至10月份)的植被NPP总量达2.81×1011 g,占全年植被NPP总量的97.57%.随着时间推移,植被NPP月平均值和归一化差分植被指数(NDVI)月平均值呈"缓慢增加—急剧增加—急剧下降"的变化趋势.植被NPP月平均值季节变化明显,春季、夏季、秋季和冬季植被NPP月平均值之和分别为20.55、69.39、20.46和0.48 g·m-2.从空间分布上看,中部河谷和滩地的植被NPP月平均值总体上高于东南部、西部和西北部等沙丘荒漠区.月平均气温对植被NPP月平均值变化的影响最大,其次为平均实际日蒸散发量和地表月太阳辐射.植被NPP月平均值随着地下水位埋深的增加而减小,最大值出现在地下水位埋深1~2 m之间.上述研究结果显示:采用CASA模型可以较好地估算毛乌素沙地海流兔河流域植被NPP值,月平均气温和地下水位埋深对该流域植被NPP值的影响较大.     

Time trends and demography of mortality after fractured neck of femur in an English population, 1968-98: database study

Objectives To investigate time trends in mortality after admission to hospital for fractured neck of femur from 1968 to 1998, and to report on the effects of demographic factors on mortality.Design Analysis of hospital inpatient statistics for fractured neck of femur, incorporating linkage to death certificates.Setting Four counties in southern England.Subjects 32 590 people aged 65 years or over admitted to hospital with fractured neck of femur between 1968 and 1998.Main outcome measures Case fatality rates at 30, 90, and 365 days after admission, and standardised mortality ratios at monthly intervals up to one year after admission.Results Case fatality rates declined between the 1960s and the early 1980s, but there was no appreciable fall thereafter. They increased sharply with increasing age: for example, fatality rates at 30 days in 1984-98 increased from 4% in men aged 64-69 years to 31% in those aged ≥ 90. They were higher in men than women, and in social classes IV and V than in classes I and II. In the first month after fracture, standardised mortality ratios in women were 16 times higher, and those in men 12 times higher, than mortality in the same age group in the general population.Conclusions The high mortality rates, and the fact that they have not fallen over the past 20 years, reinforce the need for measures to prevent osteoporosis and falls and their consequences in elderly people. Whether post-fracture mortality has fallen to an irreducible minimum, or whether further decline is possible, is unclear.     

Recommended strategies for spectral processing and post-processing of 1D <Superscript>1</Superscript>H-NMR data of biofluids with a particular focus on urine

¹H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.     

Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images

Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.