Contribution to Antarctic krill acoustic studies — Results of the NO Marion-Dufresne MD25/FIBEX cruise

Summary Antarctic biomass acoustic surveys generally yield biomass estimations expressed in terms of krill biomass, on basis of its being the major component of the Antarctic ecosystem. The influence of other scatterers is often left aside, thus introducing a bias in the estimations. The correlation between krill density distribution, as assessed by trawls, and Mean Volume Backscattering Strength frequency distribution in the range (-80, -60) dB(m^–1·sr^–1), allows to propose a method to reduce the bias. This method could be used to study the influence of each kind of scatterers on the recorded acoustic values, thus leading to better estimations.     

A systematic approach to infer biological relevance and biases of gene network structures

The development of high-throughput technologies has generated the need for bioinformatics approaches to assess the biological relevance of gene networks. Although several tools have been proposed for analysing the enrichment of functional categories in a set of genes, none of them is suitable for evaluating the biological relevance of the gene network. We propose a procedure and develop a web-based resource (BIOREL) to estimate the functional bias (biological relevance) of any given genetic network by integrating different sources of biological information. The weights of the edges in the network may be either binary or continuous. These essential features make our web tool unique among many similar services. BIOREL provides standardized estimations of the network biases extracted from independent data. By the analyses of real data we demonstrate that the potential application of BIOREL ranges from various benchmarking purposes to systematic analysis of the network biology.     

The biosocial female choice theory of social stratification

For decades, the study of social stratification has been dominated by environmental theories. Herein a theory is proposed that contains both biological and sociocultural elements. The theory asserts that most human females, like females of many other mammalian species, have evolved mating preferences biased toward males who are competent in provisioning resources. This female bias is hypothesized to have been naturally selected because females with these biases nearly always have had a reproductive edge over females who lack such a bias. One result of this bias is that human females preferentially mate with males who strive to rise in social status. This, in turn, has favored males who attain or at least strive for high social status, and who advertise and even exaggerate whatever status they already have achieved. At the genetic level, the theory postulates that alleles have accumulated on the human genome that promote social status-striving and achievement to varying degrees. To account for why males are more prone toward status-striving than females, the theory contends that one or more genes on the Y-chromosome interact with genes on the remaining human chromosomes to incline males to gravitate toward social hierarchies and to strive for niches that are relatively high in those hierarchies. Both tested and untested hypotheses are derived from the theory and compared to the empirical evidence currently available.     

Technical bias and the reproducibility crisis: The problem of systemic errors resulting from artefacts of equipment,methods or dataset has been underappreciated

Technical bias can cause lack of reproducibility. While harder to identify than other bias, it can cause consistent systemic errors in experimental data and analysis. Subject Categories: Methods & Resources, S&S: Ethics

The problem of reproducibility of experimental results has been festering for some years and prompted a great deal of research and analysis to explain why so many studies in biomedical research cannot be validated. Among these, the role played by technical bias in yielding erroneous results has been largely underappreciated in contrast to better‐known sources of error, such as inadequate sample sizes, selective reporting or publication pressure. But its significance has come to the fore after recent studies raised questions over earlier findings that were shown to have been warped by technical bias.

Technical bias often occurs alongside other forms of bias and the effects can be additive as well as overlapping.

Technical bias has nothing directly to do with human psychology or deficient analysis, but results from artefacts of equipment, reagents and laboratory methods, as well as lack of standard protocols. As a result, it has contributed to the reproducibility crisis both between (inter) and within (intra) institutions or even individual laboratories. Technical bias often occurs alongside other forms of bias and the effects can be additive as well as overlapping. Some of these apply more to particular fields than others, with sociological research tending to be plagued by different biases than say physics or chemistry. Overall, one could identify six broad categories alongside technical bias.The one most closely related to technical bias is statistical bias, sometimes called sampling error, which arises when the data are not representative of the wider set from which the results are expected. Either the sampling size for an experiment or survey is too small or it is skewed towards a subsector of the whole. The latter can often distort surveys purely because people who agree to take part often differ in some ways from those who decline to do so.Then, there is measurement bias caused by systematic errors in the process of collecting or generating data. A simple example would be measuring height without asking people to take off their shoes. The error would vary between individuals but the apparent average and mean would be too high.Third is confirmation bias, often defined as an unconscious tendency to seek out, recall or notice data that confirms preconceived opinions or hypotheses. This has been cited in the context of the COVID‐19 pandemic where aspects such as hospitalization levels or mutation rates are taken to confirm worst fears when they may be just normal artefacts of a respiratory virus.Fourth is design bias, where misleading results can arise out of the way an experiment or investigation is constructed. This has overlap with some of the other biases since design involves selection of samples, generation of data and the methods used.Fifth is publication bias: the tendency to pursue research and to report results that have a positive outcome, reinforced by journals'' preference for such papers. This is closely related to positive outcome bias and can lead to an overall misleading and rosy picture of research in a field. Egregious examples include the infamous Andrew Wakefield paper falsely connecting the MMR vaccine with autism, which may well not have been published without this tendency towards publicity‐grabbing headlines.Finally, there is hindsight bias, a common human affliction that is the tendency to regard events as having been predictable only after they have occurred. This can lead researchers to subconscious revisionism, for example raising the average prior probability of a given outcome after that has come to pass.

… there is hindsight bias, a common human affliction that is the tendency to regard events as having been predictable only after they have occurred.

     

Accuracy and direction of error in the sexing of the skeleton: implications for paleodemography

Determinations of sex by subjective assessment of the skulls from a skeletal series of known sex were compared to fully independent assessments based on pelves of the same specimens. Within-sex correlations of cranial and pelvic morphologies measured on an android-gynecoid scale were smaller than expected. Subjective assessment by means of the skull compared favorably to that of the linear discriminant functions of Giles and Elliot; however, the direction of error was similar for both procedures. Of course, estimations based on the pelves were generally superior to both in terms of frequency and overall bias of error. The bias of sex estimation for paleodemographic purposes is contingent upon completeness of skeletal remains.     

Are mutagenic non D-loop direct repeat motifs in mitochondrial DNA under a negative selection pressure?

Non D-loop direct repeats (DRs) in mitochondrial DNA (mtDNA) have been commonly implicated in the mutagenesis of mtDNA deletions associated with neuromuscular disease and ageing. Further, these DRs have been hypothesized to put a constraint on the lifespan of mammals and are under a negative selection pressure. Using a compendium of 294 mammalian mtDNA, we re-examined the relationship between species lifespan and the mutagenicity of such DRs. Contradicting the prevailing hypotheses, we found no significant evidence that long-lived mammals possess fewer mutagenic DRs than short-lived mammals. By comparing DR counts in human mtDNA with those in selectively randomized sequences, we also showed that the number of DRs in human mtDNA is primarily determined by global mtDNA properties, such as the bias in synonymous codon usage (SCU) and nucleotide composition. We found that SCU bias in mtDNA positively correlates with DR counts, where repeated usage of a subset of codons leads to more frequent DR occurrences. While bias in SCU and nucleotide composition has been attributed to nucleotide mutational bias, mammalian mtDNA still exhibit higher SCU bias and DR counts than expected from such mutational bias, suggesting a lack of negative selection against non D-loop DRs.     

Seeing storms behind the clouds: Biases in the attribution of anger

Anger-prone individuals are volatile and frequently dangerous. Accordingly, inferring the presence of this personality trait in others was important in ancestral human populations. This inference, made under uncertainty, can result in two types of errors: underestimation or overestimation of trait anger. Averaged over evolutionary time, underestimation will have been the more costly error, as the fitness decrements resulting from physical harm or death due to insufficient vigilance are greater than those resulting from lost social opportunities due to excessive caution. We therefore hypothesized that selection has favored an upwards bias in the estimation of others' trait anger relative to estimations of other traits not characterized by such an error asymmetry. Moreover, we hypothesized that additional attributes that i) make the actor more dangerous, or ii) make the observer more vulnerable increase the error asymmetry with regard to inferring anger-proneness, and should therefore correspondingly increase this overestimation bias. In Study 1 (N = 161), a fictitious individual portrayed in a vignette was judged to have higher trait anger than trait disgust, and trait anger ratings were more responsive than trait disgust ratings to behavioral cues of emotionality. In Study 2 (N = 335), participants viewed images of angry or fearful faces. The interaction of factors indicating target's formidability (male sex), target's intent to harm (direct gaze), and perceiver's vulnerability (female sex or high belief in a dangerous world) increased ratings of the target's trait anger but not trait fear.     

A detailed history of intron-rich eukaryotic ancestors inferred from a global survey of 100 complete genomes

Protein-coding genes in eukaryotes are interrupted by introns, but intron densities widely differ between eukaryotic lineages. Vertebrates, some invertebrates and green plants have intron-rich genes, with 6-7 introns per kilobase of coding sequence, whereas most of the other eukaryotes have intron-poor genes. We reconstructed the history of intron gain and loss using a probabilistic Markov model (Markov Chain Monte Carlo, MCMC) on 245 orthologous genes from 99 genomes representing the three of the five supergroups of eukaryotes for which multiple genome sequences are available. Intron-rich ancestors are confidently reconstructed for each major group, with 53 to 74% of the human intron density inferred with 95% confidence for the Last Eukaryotic Common Ancestor (LECA). The results of the MCMC reconstruction are compared with the reconstructions obtained using Maximum Likelihood (ML) and Dollo parsimony methods. An excellent agreement between the MCMC and ML inferences is demonstrated whereas Dollo parsimony introduces a noticeable bias in the estimations, typically yielding lower ancestral intron densities than MCMC and ML. Evolution of eukaryotic genes was dominated by intron loss, with substantial gain only at the bases of several major branches including plants and animals. The highest intron density, 120 to 130% of the human value, is inferred for the last common ancestor of animals. The reconstruction shows that the entire line of descent from LECA to mammals was intron-rich, a state conducive to the evolution of alternative splicing.     

Evaluating the validity and reliability of inertial measurement units for determining knee and trunk kinematics during athletic landing and cutting movements

Inertial Measurement Units (IMUs) are promising alternatives to laboratory-based motion capture methods in biomechanical assessment of athletic movements. The aim of this study was to investigate the validity of an IMU system for determining knee and trunk kinematics during landing and cutting tasks for clinical and research applications in sporting populations. Twenty-seven participants performed five cutting and landing tasks while being recorded using a gold-standard optoelectronic motion capture system and an IMU system. Intra-class coefficients, Pearson’s r, root-mean-square error (RMSE), bias, and Bland-Altman limits of agreements between the motion capture and IMU systems were quantified for knee and trunk sagittal- and frontal-plane range-of-motion (ROM) and peak angles. Our results indicate that IMU validity was task-, joint-, and plane-dependent. Based on good-to-excellent (ICC) correlation, reasonable accuracy (RMSE < 5°), bias within 2°, and limits of agreements within 10°, we recommend the use of this IMU system for knee sagittal-plane ROM estimations during cutting, trunk sagittal-plane peak angle estimation during the double-leg landing task, trunk sagittal-plane ROM estimation for almost all tasks, and trunk frontal-plane peak angle estimation for the right single-leg landing task. Due to poor comparisons with the optoelectronic system, we do not recommend this IMU system for knee frontal-plane kinematic estimations.     

Evaluation of three techniques for the study of harvester ant (Pogonomyrmex spp.) diet

The estimation of an ant's diet is crucial in many ecological studies. Different techniques, which involve different assumptions and field procedures, have been used to estimate the composition of harvester ant diet. In this study, three techniques are compared for the estimation of the diet of Pogonomyrmex rastratus (Mayr), Pogonomyrmex pronotalis (Santschi), and Pogonomyrmex inermis (Forel) in the central Monte desert, Argentina: (1) hand collection of items brought back to the nest by foragers, (2) collection of items with a semiautomated device with pitfall traps, and (3) collection of the discarded material accumulated in middens. The hand collection technique and the collection of middens provided the lowest and the highest number of items, respectively. Midden samples and pitfall traps contained a higher proportion of nonseed items, probably coming from sources other than ants, than hand-collected items. The three techniques provided similar estimations of species richness but a bias against small seeds was detected for P. pronotalis and P. inermis with the hand collection technique, possibly because of the difficulty of collecting small items by hand. The percentage of seed species in the diet obtained with different techniques was positively correlated in the great majority of colonies. Overall, despite their intrinsic differences, the three techniques proved consistent, which constitutes a robustness test for the estimations obtained. In comparative ecological studies, the awareness that results depend on the techniques and their assumptions is particularly important.     

The Impact of Outliers on Net-Benefit Regression Model in Cost-Effectiveness Analysis

Ordinary least square (OLS) in regression has been widely used to analyze patient-level data in cost-effectiveness analysis (CEA). However, the estimates, inference and decision making in the economic evaluation based on OLS estimation may be biased by the presence of outliers. Instead, robust estimation can remain unaffected and provide result which is resistant to outliers. The objective of this study is to explore the impact of outliers on net-benefit regression (NBR) in CEA using OLS and to propose a potential solution by using robust estimations, i.e. Huber M-estimation, Hampel M-estimation, Tukey''s bisquare M-estimation, MM-estimation and least trimming square estimation. Simulations under different outlier-generating scenarios and an empirical example were used to obtain the regression estimates of NBR by OLS and five robust estimations. Empirical size and empirical power of both OLS and robust estimations were then compared in the context of hypothesis testing.Simulations showed that the five robust approaches compared with OLS estimation led to lower empirical sizes and achieved higher empirical powers in testing cost-effectiveness. Using real example of antiplatelet therapy, the estimated incremental net-benefit by OLS estimation was lower than those by robust approaches because of outliers in cost data. Robust estimations demonstrated higher probability of cost-effectiveness compared to OLS estimation. The presence of outliers can bias the results of NBR and its interpretations. It is recommended that the use of robust estimation in NBR can be an appropriate method to avoid such biased decision making.     

REML estimation of variance parameters in nonlinear mixed effects models using the SAEM algorithm

Nonlinear mixed effects models are now widely used in biometrical studies, especially in pharmacokinetic research or for the analysis of growth traits for agricultural and laboratory species. Most of these studies, however, are often based on ML estimation procedures, which are known to be biased downwards. A few REML extensions have been proposed, but only for approximated methods. The aim of this paper is to present a REML implementation for nonlinear mixed effects models within an exact estimation scheme, based on an integration of the fixed effects and a stochastic estimation procedure. This method was implemented via a stochastic EM, namely the SAEM algorithm. The simulation study showed that the proposed REML estimation procedure considerably reduced the bias observed with the ML estimation, as well as the residual mean squared error of the variance parameter estimations, especially in the unbalanced cases. ML and REML based estimators of fixed effects were also compared via simulation. Although the two kinds of estimates were very close in terms of bias and mean square error, predictions of individual profiles were clearly improved when using REML vs. ML. An application of this estimation procedure is presented for the modelling of growth in lines of chicken.     

Estimation of coancestry in Iberian pigs using molecular markers

Genetic markers provide a useful tool toestimate pairwise coancestry betweenindividuals in the absence of a known pedigree. Inthe present work 62 pigs from two relatedstrains of Iberian breed, Guadyerbas andTorbiscal, belonging to a conservationprogramme with completely known pedigrees since1945, have been genotyped for 49microsatellites. Four coefficients thatsummarise molecular resemblance betweenindividuals together with eightestimators of coancestry have been calculatedfrom this information. Their values werecompared with the genealogical coancestry,calculated from the complete or partialpedigree. The eight estimations obtained usingmolecular information substantiallyunderestimate the coancestry calculated usingthe genealogical analysis. The correlationbetween the estimates and the genealogicalvalues was also calculated. This correlationwas high, between 0.78 and 0.93 for differentestimators, when all pairwise comparisons amongthe 62 animals were considered. However, thecorrelation decreases remarkably to 0.49–0.69and 0.37–0.47 for the Guadyerbas and Torbiscalpopulations respectively, when they wereanalysed separately. All the correlations weresimilar to those obtained when using simplecoefficients of molecular resemblance such asmolecular coancestry or similarity indexes.Finally, simulations were carried out tofurther explore the results obtained. It isconcluded that lack of information on theallele frequencies in the base population mayexplain the bias of these estimators inpopulations with complex pedigrees.     

大肠杆菌mRNA编码区长度、形成二级结构倾向与密码子偏好性的关系

从GenBank获得大肠杆菌K-12MG1655株的全基因组序列,计算了与基因密码子偏好性相关的多个参数(Nc、CAI、GC、GC3s),对其mRNA编码区长度、形成二级结构倾向与密码子偏好性之间的关系进行了统计学分析,发现虽然翻译效率(包括翻译速度和翻译精度)是制约大肠杆菌高表达基因的密码子偏好性的主要因素,同时,mRNA编码区长度及其形成二级结构的倾向也是形成这种偏好性的不可忽略的原因,而且对偏好性有一定程度的削弱。另外对mRNA编码区形成二级结构倾向的生物学意义进行了讨论分析。     

Real-time estimation of plasma insulin concentration from continuous glucose monitor measurements

Continuous glucose monitors can measure interstitial glucose concentration in real time for closed-loop glucose control systems, known as artificial pancreas. These control systems use an insulin feedback to maintain plasma glucose concentration within a narrow and safe range, and thus to avoid health complications. As it is not possible to measure plasma insulin concentration in real time, insulin models have been used in literature to estimate them. Nevertheless, the significant inter- and intra-patient variability of insulin absorption jeopardizes the accuracy of these estimations. In order to reduce these limitations, our objective is to perform a real-time estimation of plasma insulin concentration from continuous glucose monitoring (CGM). Hovorka’s glucose–insulin model has been incorporated in an extended Kalman filter in which different selected time-variant model parameters have been considered as extended states. The observability of the original Hovorka’s model and of several extended models has been evaluated by their Lie derivatives. We have evaluated this methodology with an in-silico study with 100 patients with Type 1 diabetes during 25 h. Furthermore, it has been also validated using clinical data from 12 insulin pump patients with Type 1 diabetes who underwent four mixed meal studies. Real-time insulin estimations have been compared to plasma insulin measurements to assess performance showing the validity of the methodology here used in comparison with that formerly used for insulin models. Hence, real-time estimations for plasma insulin concentration based on subcutaneous glucose monitoring can be beneficial for increasing the efficiency of control algorithms for the artificial pancreas.     

Body mass prediction from stature and bi-iliac breadth in two high latitude populations, with application to earlier higher latitude humans

Previous studies have indicated that body mass can be estimated from stature and bi-iliac (maximum pelvic) breadth with reasonable accuracy in modern humans, supporting the use of this method to estimate body mass in earlier human skeletal samples. However, to date the method has not been tested specifically on high latitude individuals, whose body form in some ways more closely approximates that of earlier higher latitude humans (i.e., large and broad-bodied). In this study, anthropometric data for 67 Alaskan Inupiat and 54 Finnish adults were used to test the stature/bi-iliac body mass estimation method. Both samples are very broad-bodied, and the Finnish sample is very tall as well. The method generally works well in these individuals, with average directional biases in body mass estimates of 3% or less, except in male Finns, whose body masses are systematically underestimated by an average of almost 9%. A majority of individuals in the total pooled sample have estimates to within +/-10% of their true body masses, and more than three-quarters have estimates to within +/-15%. The major factor found to affect directional bias is shoulder to hip breadth (biacromial/bi-iliac breadth). Male Finns have particularly wide shoulders, which may in part explain their systematic underestimation. New body mass estimation equations are developed that include the new data from this study. When applied to a sample of earlier (late middle Pleistocene to early Upper Paleolithic) higher latitude skeletal specimens, differences between previous and new body estimates are small (less than 2%). However, because the Finns significantly extend the range of morphological variation beyond that represented in the original world-wide reference sample used in developing the method, thereby increasing its generality, it is recommended that these new formulas be used in subsequent body mass estimations.     

Computation of continuous relative phase and modulation of frequency of human movement

Continuous relative phase measures have been used to quantify the coordination between different body segments in several activities. Our aim in this study was to investigate how the methods traditionally used to compute the continuous phase of human rhythmic movement are affected by modulations of frequency. We compared the continuous phase computed method with the traditional method derived from the position-velocity phase plane and with the Hilbert Transform. The methods were tested using sinusoidal signals with a modulation of frequency between or within cycles. Our results showed that the continuous phase computed with the first method results in oscillations in the phase time-series not expected for a sinusoidal signal and that the continuous phase is overestimated with the Hilbert Transform. We proposed a new method that produces a correct estimation of continuous phase by using half-cycle estimations of frequency to normalize the phase planes prior to calculating phase angles. The findings of the current study have important implications for computing continuous relative phase when investigating human movement coordination.     

Estimates of the average strength of natural selection are not inflated by sampling error or publication bias

Kingsolver et al.'s review of phenotypic selection gradients from natural populations provided a glimpse of the form and strength of selection in nature and how selection on different organisms and traits varies. Because this review's underlying database could be a key tool for answering fundamental questions concerning natural selection, it has spawned discussion of potential biases inherent in the review process. Here, we explicitly test for two commonly discussed sources of bias: sampling error and publication bias. We model the relationship between variance among selection gradients and sample size that sampling error produces by subsampling large empirical data sets containing measurements of traits and fitness. We find that this relationship was not mimicked by the review data set and therefore conclude that sampling error does not bias estimations of the average strength of selection. Using graphical tests, we find evidence for bias against publishing weak estimates of selection only among very small studies (N<38). However, this evidence is counteracted by excess weak estimates in larger studies. Thus, estimates of average strength of selection from the review are less biased than is often assumed. Devising and conducting straightforward tests for different biases allows concern to be focused on the most troublesome factors.     

Compositional evolution of noncoding DNA in the human and chimpanzee genomes

We have examined the compositional evolution of noncoding DNA in the primate genome by comparison of lineage-specific substitutions observed in 1.8 Mb of genomic alignments of human, chimpanzee, and baboon with 6542 human single-nucleotide polymorphisms (SNPs) rooted using chimpanzee sequence. The pattern of compositional evolution, measured in terms of the numbers of GC-->AT and AT-->GC changes, differs significantly between fixed and polymorphic sites, and indicates that there is a bias toward fixation of AT-->GC mutations, which could result from weak directional selection or biased gene conversion in favor of high GC content. Comparison of the frequency distributions of a subset of the SNPs revealed no significant difference between GC-->AT and AT-->GC polymorphisms, although AT-->GC polymorphisms in regions of high GC segregate at slightly higher frequencies on average than GC-->AT polymorphisms, which is consistent with a fixation bias favoring high GC in these regions. However, the substitution data suggest that this fixation bias is relatively weak, because the compositional structure of the human and chimpanzee genomes is becoming homogenized, with regions of high GC decreasing in GC content and regions of low GC increasing in GC content. The rate and pattern of nucleotide substitution in 333 Alu repeats within the human-chimpanzee-baboon alignments are not significantly affected by the GC content of the region in which they are inserted, providing further evidence that, since the time of the human-chimpanzee ancestor, there has been little or no regional variation in mutation bias.