Partial least squares for functional joint models with applications to the Alzheimer's disease neuroimaging initiative study

Many biomedical studies have identified important imaging biomarkers that are associated with both repeated clinical measures and a survival outcome. The functional joint model (FJM) framework, proposed by Li and Luo in 2017, investigates the association between repeated clinical measures and survival data, while adjusting for both high-dimensional images and low-dimensional covariates based on the functional principal component analysis (FPCA). In this paper, we propose a novel algorithm for the estimation of FJM based on the functional partial least squares (FPLS). Our numerical studies demonstrate that, compared to FPCA, the proposed FPLS algorithm can yield more accurate and robust estimation and prediction performance in many important scenarios. We apply the proposed FPLS algorithm to a neuroimaging study. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.     

Reliability of reliability coefficients in the estimation of asymmetry

Although promising to provide insight into the interaction between genotype and environment, investigations into fluctuating asymmetry suffer from a lack of standardization in the reporting of measurement error. In the present paper we show, using both anthropometric and odonto-metric data, that the use of the reliability coefficient calculated for a bilateral measurement provides no indication of the reliability of the corresponding asymmetry estimate, because reliability of asymmetry depends on the relationship between measurement error and the difference between sides. Thus, we suggest that future investigations either provide reliability coefficients for asymmetry estimates specifically, or use methods that account for measurement error. © 1995 Wiley-Liss, Inc.     

From information to understanding: the role of model organism databases in comparative and functional genomics

Data integration is key to functional and comparative genomics because integration allows diverse data types to be evaluated in new contexts. To achieve data integration in a scalable and sensible way, semantic standards are needed, both for naming things (standardized nomenclatures, use of key words) and also for knowledge representation. The Mouse Genome Informatics database and other model organism databases help to close the gap between information and understanding of biological processes because these resources enforce well-defined nomenclature and knowledge representation standards. Model organism databases have a critical role to play in ensuring that diverse kinds of data, especially genome-scale data sets and information, remain useful to the biological community in the long-term. The efforts of model organism database groups ensure not only that organism-specific data are integrated, curated and accessible but also that the information is structured in such a way that comparison of biological knowledge across model organisms is facilitated.     

Incorporation of clustering effects for the Wilcoxon rank sum test: a large-sample approach

The Wilcoxon rank sum test is frequently used in statistical practice for the comparison of measures of location when the underlying distributions are far from normal or not known in advance. An assumption of the ordinary rank sum test is that individual sampling units are independent. In many ophthalmologic clinical trials, the Early Treatment for Diabetic Retinopathy Scale (ETDRS) is a principal endpoint used for measuring the level of diabetic retinopathy. This is an ordinal scale, and it is natural to consider the Wilcoxon rank sum test for the comparison of the level of diabetic retinopathy between treatment groups. However, under this design, unlike the usual Wilcoxon rank sum test, the subject is the unit of randomization, but the eye is the unit of analysis. Furthermore, a person will tend to have different, but correlated, ETDRS scores for fellow eyes. Thus, we propose a correction to the variance of the Wilcoxon rank sum statistic that accounts for clustering effects and that can be used for both balanced (same number of subunits per cluster) or unbalanced (different number of subunits per cluster) data, both in the presence or absence of ties, with p-value adjusted accordingly. In this article, we present large-sample theory and simulation results for this test procedure and apply it to diabetic retinopathy data from type I diabetics in the Sorbinil Retinopathy Trial.     

一种新的生态监测数据质量评估方法——以CERN乔木生长数据为例

将数据可靠性作为有序变量进行分级,在理论上使数据可靠性与主要生态过程、次级生态过程、外部过程等数据源建立关联,构建了一种生态监测数据质量评估方法,提供了一个新的数据质量指数.它通过观察记录的合格率来估计数据集的质量,其检测结果包括了每一条数据的可靠性级别、标记为离群或错误数据的原因,以及完整数据集的质量指数值.将该方法应用于CERN的两个乔木生长数据集,发现该数据质量指数可以定量评估乔木生长数据集的质量.该方法为相关软件的开发提供了基础.     

Copper and the biological evolution

Copper is contained in a number of enzymes and proteins. A remarkable feature is that except for the electron-carrying blue copper proteins (azurin and plastocyanin) and copper-containing cytochrome c oxidase found in some cyanobacteria and some aerobic bacteria, all copper enzymes and proteins are found only in eukaryotes. In the early and middle precambrian period when the stationary oxygen pressure in the atmosphere was quite low, copper existed as either metallic or cuprous sulfides which are very insoluble in aqueous media; thus copper might have been unavailable to organisms. The time when copper became Cu(II) upon rise of the atmospheric oxygen pressure and thus became available to organisms seems to be in the middle of Proteozoic era when first eukaryotic organisms seem to have appeared on earth. Thus copper may be considered to be an indicator element for the atmospheric evolution (switching from anoxygenic to oxygenic) and the evolution of higher organisms (eukaryotes).     

The Thermometer and the Calorimeter,or the Best Choice for Data Acquisition in the Sampling of Biological Rhythms

The comparison between measurements effected by different apparati shows that a given class of instruments provides an integral set of measurements. This characteristic has a certain disadvantage: the modification of the spectral bandwidth is limited to an attenuation of 3 dB. However, it also has certain advantages. The integral measurement (or the counting measurement) makes it possible to satisfy Shannon's sampling criteria by avoiding the necessary anti-aliasing filtering which is commonly impossible to realize on measurements of a biological nature. A second advantage is linked to the reduction of the background noise on the band.     

The Thermometer and the Calorimeter, or the Best Choice for Data Acquisition in the Sampling of Biological Rhythms

The comparison between measurements effected by different apparati shows that a given class of instruments provides an integral set of measurements. This characteristic has a certain disadvantage: the modification of the spectral bandwidth is limited to an attenuation of 3 dB. However, it also has certain advantages. The integral measurement (or the counting measurement) makes it possible to satisfy Shannon's sampling criteria by avoiding the necessary anti-aliasing filtering which is commonly impossible to realize on measurements of a biological nature. A second advantage is linked to the reduction of the background noise on the band.     

The principal airborne and allergenic pollen species in the Netherlands

Summary A list of the principal airborne and allergenic pollen species in the Netherlands was compiled on the basis of the pollen lists of Leiden and Helmond, the Leiden pollen calendar, the hour-square frequencies of the species in question in the Netherlands and the degree of allergenicity of the extent known. Twenty-two trees and shrubs, 9 herbs and 32 grasses were selected.     

Taxonomic assessment of the allopatric gray-cheeked mangabey (Cercocebus albigena) and black mangabey (C. aterrimus): Comparative socioecological data and the species concept

A brief review of past taxonomic assessments of the allopatric gray-cheeked mangabey (Cercocebus albigena) and the black mangabey (Cercocebus aterrimus) is presented. On the basis of pelage, cranial, and biomolecular morphology, aterrimus and albigena have been lumped together in the same species-group, superspecies, subgenus, or species by various systematists over the years. A comparison of the available socioecological data on the two forms supports their close taxonomic association, as they are found to be very similar in socioecological traits. After a brief review of current species concepts, the author, on the basis of the socioecological commonalities, tentatively supports Groves' [1978] conspecific designation of albigena and aterrimus and suggests further tests for this proposal and for the species concept, from the points of view of both taxonomic and evolutionary theory.     

Assessing the power of informative subsets of loci for population assignment: standard methods are upwardly biased

It is well known that statistical classification procedures should be assessed using data that are separate from those used to train the classifier. This principle is commonly overlooked when the classification procedure in question is population assignment using a set of genetic markers that were chosen specifically on the basis of their allele frequencies from amongst a larger number of candidate markers. This oversight leads to a systematic upward bias in the predicted accuracy of the chosen set of markers for population assignment. Three widely used software programs for selecting markers informative for population assignment suffer from this bias. The extent of this bias is documented through a small set of simulations. The relative effect of the bias is largest when screening many candidate loci from poorly differentiated populations. Simple unbiased methods are presented and their use encouraged.     

Phylogenetic relationships in the genus Agathemera (Insecta: Phasmatodea) inferred from the genes 16S,COI and H3

We present a phylogenetic analysis that includes all known species of Agathemera, using as outgroup four species of the genera Heteronemia, Spinonemia, Monticomorpha, and Anisomorpha. Phylogenetic inference was based on three genes, 16S, COI (mitochondrial markers) and H3 (nuclear marker), based on the maximum‐parsimony, maximum‐likelihood and Bayesian inference methods. Our results show that the genus Agathemera is monophyletic; six of its eight species showed phylogenetic support, while the group A. claraziana + A. millepunctata was not resolved. The resulting topology shows two major clades, the first with A. maculafulgens, A. luteola, A. crassa, A. millepunctata, and A. claraziana, and the second including A. grylloidea, A. mesoauriculae, and A. elegans. Species of the first clade have large mesonotal processes and are found mainly east of the Andes, except for A. crassa. Members of the second clade have small or absent mesonotal processes and are distributed mainly to the west of the Andes. © 2012 The Linnean Society of London, Zoological Journal of the Linnean Society, 2012, 165 , 63–72.     

Presence-only data and the em algorithm

Summary .  In ecological modeling of the habitat of a species, it can be prohibitively expensive to determine species absence. Presence-only data consist of a sample of locations with observed presences and a separate group of locations sampled from the full landscape, with unknown presences. We propose an expectation–maximization algorithm to estimate the underlying presence–absence logistic model for presence-only data. This algorithm can be used with any off-the-shelf logistic model. For models with stepwise fitting procedures, such as boosted trees, the fitting process can be accelerated by interleaving expectation steps within the procedure. Preliminary analyses based on sampling from presence–absence records of fish in New Zealand rivers illustrate that this new procedure can reduce both deviance and the shrinkage of marginal effect estimates that occur in the naive model often used in practice. Finally, it is shown that the population prevalence of a species is only identifiable when there is some unrealistic constraint on the structure of the logistic model. In practice, it is strongly recommended that an estimate of population prevalence be provided.     

Gauging the effects of sampling failure in biogeographical analysis

Aim Various methods are employed to recover patterns of area relationships in extinct and extant clades. The fidelity of these patterns can be adversely affected by sampling error in the form of missing data. Here we use simulation studies to evaluate the sensitivity of an analytical biogeographical method, namely tree reconciliation analysis (TRA), to this form of sampling failure. Location Simulation study. Methods To approximate varying degrees of taxonomic sampling failure within phylogenies varying in size and in redundancy of biogeographical signal, we applied sequential pruning protocols to artificial taxon–area cladograms displaying congruent patterns of area relationships. Initial trials assumed equal probability of sampling failure among all areas. Additional trials assigned weighted probabilities to each of the areas in order to explore the effects of uneven geographical sampling. Pruned taxon–area cladograms were then analysed with TRA to determine if the optimal area cladograms recovered match the original biogeographical signal, or if they represent false, ambiguous or uninformative signals. Results The results indicate a period of consistently accurate recovery of the true biogeographical signal, followed by a nonlinear decrease in signal recovery as more taxa are pruned. At high levels of sampling failure, false biogeographical signals are more likely to be recovered than the true signal. However, randomization testing for statistical significance greatly decreases the chance of accepting false signals. The primary inflection of the signal recovery curve, and its steepness and slope depend upon taxon–area cladogram size and area redundancy, as well as on the evenness of sampling. Uneven sampling across geographical areas is found to have serious deleterious effects on TRA, with the accuracy of recovery of biogeographical signal varying by an order of magnitude or more across different sampling regimes. Main conclusions These simulations reiterate the importance of taxon sampling in biogeographical analysis, and attest to the importance of considering geographical, as well as overall, sampling failure when interpreting the robustness of biogeographical signals. In addition to randomization testing for significance, we suggest the use of randomized sequential taxon deletions and the construction of signal decay curves as a means to assess the robustness of biogeographical signals for empirical data sets.     

Managing data locally to answer questions globally: The role of collaborative science in ecology

Ecologists are increasingly asking large‐scale and/or broad‐scope questions that require vast datasets. In response, various top‐down efforts and incentives have been implemented to encourage data sharing and integration. However, despite general consensus on the critical need for more open ecological data, several roadblocks still discourage compliance and participation in these projects; as a result, ecological data remain largely unavailable. Grassroots initiatives (i.e. efforts initiated and led by cohesive groups of scientists focused on specific goals) have thus far been overlooked as a powerful means to meet these challenges. These bottom‐up collaborative data integration projects can play a crucial role in making high quality datasets available because they tackle the heterogeneity of ecological data at a scale where it is still manageable, all the while offering the support and structure to do so. These initiatives foster best practices in data management and provide tangible rewards to researchers who choose to invest time in sound data stewardship. By maintaining proximity between data generators and data users, grassroots initiatives improve data interpretation and ensure high‐quality data integration while providing fair acknowledgement to data generators. We encourage researchers to formalize existing collaborations and to engage in local activities that improve the availability and distribution of ecological data. By fostering communication and interaction among scientists, we are convinced that grassroots initiatives can significantly support the development of global‐scale data repositories. In doing so, these projects help address important ecological questions and support policy decisions.     

Human dental reduction: natural selection or the probable mutation effect

Dental reduction has been sufficiently widespread among human populations to render the phenomenon of reduced tooth size worthy of scientific explanation. One of the most controversial models invoked to explain structural reduction in organisms is referred to as the "probable mutation effect" (PME). According to this model, structures no longer functional owing to ecological or cultural changes will experience a relaxation of selection pressure, permitting an accumulation of mutations in the population that inevitably will result in the reduction in size or the loss of the concerned structure. Although the PME continues to be offered as a viable explanation of human dental reduction, it is based upon several premises that modern dental clinical experience fails to support. Known enzyme defects resulting from mutations, factors predisposing to dental infections, and the deleterious effects of teeth that are too large or too small reveal that the PME does not logically account for the reduction of tooth size. Given such information, this paper proposes models of dental reduction based upon natural selection, which, unlike the PME, are testable in both modern and archaeological populations. The integration of clinical and skeletal data permits a more thorough understanding of dental reduction in the hominid fossil record.