Topological ranks reveal functional knowledge encoded in biological networks: a comparative analysis.

MOTIVATION: Biological networks topology yields important insights into biological function, occurrence of diseases and drug design. In the last few years, different types of topological measures have been introduced and applied to infer the biological relevance of network components/interactions, according to their position within the network structure. Although comparisons of such measures have been previously proposed, to what extent the topology per se may lead to the extraction of novel biological knowledge has never been critically examined nor formalized in the literature. RESULTS: We present a comparative analysis of nine outstanding topological measures, based on compact views obtained from the rank they induce on a given input biological network. The goal is to understand their ability in correctly positioning nodes/edges in the rank, according to the functional knowledge implicitly encoded in biological networks. To this aim, both internal and external (gold standard) validation criteria are taken into account, and six networks involving three different organisms (yeast, worm and human) are included in the comparison. The results show that a distinct handful of best-performing measures can be identified for each of the considered organisms, independently from the reference gold standard. AVAILABILITY: Input files and code for the computation of the considered topological measures and K-haus distance are available at https://gitlab.com/MaryBonomo/ranking. CONTACT: simona.rombo@unipa.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Briefings in Bioinformatics online.

Protein complex structure prediction powered by multiple sequence alignments of interologs from multiple taxonomic ranks and AlphaFold2.

AlphaFold2 can predict protein complex structures as long as a multiple sequence alignment (MSA) of the interologs of the target protein-protein interaction (PPI) can be provided. In this study, a simplified phylogeny-based approach was applied to generate the MSA of interologs, which was then used as the input to AlphaFold2 for protein complex structure prediction. In this extensively benchmarked protocol on nonredundant PPI dataset, including 107 bacterial PPIs and 442 eukaryotic PPIs, we show complex structures of 79.5% of the bacterial PPIs and 49.8% of the eukaryotic PPIs can be successfully predicted, which yielded significantly better performance than the application of MSA of interologs prepared by two existing approaches. Considering PPIs may not be conserved in species with long evolutionary distances, we further restricted interologs in the MSA to different taxonomic ranks of the species of the target PPI in protein complex structure prediction. We found that the success rates can be increased to 87.9% for the bacterial PPIs and 56.3% for the eukaryotic PPIs if interologs in the MSA are restricted to a specific taxonomic rank of the species of each target PPI. Finally, we show that the optimal taxonomic ranks for protein complex structure prediction can be selected with the application of the predicted template modeling (TM) scores of the output models.

Extending the DeLong algorithm for comparing areas under correlated receiver operating characteristic curves with missing data.

A nonparametric method proposed by DeLong et al in 1988 for comparing areas under correlated receiver operating characteristic curves is used widely in practice. However, the DeLong method as implemented in popular software quietly deletes individuals with any missing values, yielding potentially invalid and/or inefficient results. We simplify the DeLong algorithm using ranks and extend it to accommodate missing data by using a mixed model approach for multivariate data. Simulation results demonstrate the validity and efficiency of our procedure for data missing at random. We illustrate our proposed procedure in SAS, Stata, and R using the original DeLong data.

Body Mass Gain in Wild Brown Capuchins (Sapajus apella) in Relation to Fruit Production and Social Dominance.

In ecological contexts natural selection might favor individuals with a larger body mass to monopolize resources; however, there is wide variation in body mass within populations and potential factors. In this study, we evaluated whether fruit production limits body mass in one group of Sapajus apella, its effects on behavior, and whether there is a relationship between social status and body mass. We recorded activity patterns using focal follows (20 min), body mass (using a modified Ohaus scale), and community wide fruit production estimates (from 60 fruit traps). Body mass remained relatively stable during periods of food scarcity, but in periods of abundance most individuals gained weight, as indicated by their relative growth rates (RGR). Subordinate subadults showed the highest RGR, as expected by their age. In periods of high fruit production activities as traveling, grooming, and playing were more frequent than during fruit scarcity, suggesting energy maximization and potential energetic constraints. We found differences in behavior within the group, as the alpha male was observed feeding more frequently (and for longer periods of time), was more aggressive (e.g., feeding trees), and received more grooming than other individuals. In addition, the alpha male was 60% heavier than the group's average body mass. Our study supports the hypothesis that body weight gain is related to fruit abundance and that body size is associated with social dominance; however, large individuals (both males and females) seem to incur in high metabolic or reproductive costs, as they do not gain much weight as smaller individuals.

A Bayesian hierarchical model for signal extraction from protein microarrays.

Protein microarrays are a promising technology that measure protein levels in serum or plasma samples. Due to their high technical variability and high variation in protein levels across serum samples in any population, directly answering biological questions of interest using protein microarray measurements is challenging. Analyzing preprocessed data and within-sample ranks of protein levels can mitigate the impact of between-sample variation. As for any analysis, ranks are sensitive to preprocessing, but loss function based ranks that accommodate major structural relations and components of uncertainty are very effective. Bayesian modeling with full posterior distributions for quantities of interest produce the most effective ranks. Such Bayesian models have been developed for other assays, for example, DNA microarrays, but modeling assumptions for these assays are not appropriate for protein microarrays. Consequently, we develop and evaluate a Bayesian model to extract the full posterior distribution of normalized protein levels and associated ranks for protein microarrays, and show that it fits well to data from two studies that use protein microarrays produced by different manufacturing processes. We validate the model via simulation and demonstrate the downstream impact of using estimates from this model to obtain optimal ranks.

External validation of a new predictive model for falls among inpatients using the official Japanese ADL scale, Bedriddenness ranks: a double-centered prospective cohort study.

BACKGROUND: Several reliable predictive models for falls have been reported, but are too complicated and time-consuming to evaluate. We recently developed a new predictive model using just eight easily-available parameters including the official Japanese activities of daily living scale, Bedriddenness ranks, from the Ministry of Health, Labour and Welfare. This model has not yet been prospectively validated. This study aims to prospectively validate our new predictive model for falls among inpatients admitted to two different hospitals. METHODS: A double-centered prospective cohort study was performed from October 1, 2018, to September 30, 2019 in an acute care hospital and a chronic care hospital. We analyzed data from all adult inpatients, for whom all data required by the predictive model were evaluated and recorded. The eight items required by the predictive model were age, gender, emergency admission, department of admission, use of hypnotic medications, previous falls, independence of eating, and Bedriddenness ranks. The main outcome is in-hospital falls among adult inpatients, and the model was assessed by area under the curve. RESULTS: A total of 3,551 adult participants were available, who experienced 125 falls (3.5%). The median age (interquartile range) was 78 (66-87) years, 1,701 (47.9%) were men, and the incidence of falls was 2.25 per 1,000 patient-days and 2.06 per 1,000 occupied bed days. The area under the curve of the model was 0.793 (95% confidence interval: 0.761-0.825). The cutoff value was set as - 2.18, making the specificity 90% with the positive predictive value and negative predictive value at 11.4% and 97%. CONCLUSIONS: This double-centered prospective cohort external validation study showed that the new predictive model had excellent validity for falls among inpatients. This reliable and easy-to-use model is therefore recommended for prediction of falls among inpatients, to improve preventive interventions. TRIAL REGISTRATION: UMIN000040103 (2020/04/08).

Male chimpanzee sexual coercion and mating success at Ngogo.

Chimpanzees (Pan troglodytes) have a complex mating system in which both sexes use multiple tactics. Most copulations occur in group contexts, and high-ranking males can gain high mating and reproductive success, but females typically mate with multiple males and the potential for sperm competition is high. Also, male-female dyads sometimes form temporary exclusive mating associations (consortships). Male aggression to receptive females is common. Several studies have supported the hypothesis that this is sexual coercion, but debate exists regarding the importance of coercion relative to that of female choice. The number of adult males in a community can influence the balance between these processes. In the large Ngogo community, male dominance ranks and rates of aggression to fully-swollen females were positively related to mating success as estimated by copulation rates and by proportions of copulations achieved. Aggression rates were higher than at other sites, overall and per male, especially during periovulatory periods, and increased with the number of males associating with a female. Aggression impaired female foraging efficiency. Males initiated most copulations and females rarely refused mating attempts. Male-to-female grooming was positively associated with male mating success and with the proportion of copulations that females initiated, but the amount of grooming was typically small and whether grooming-for-mating trading occurs is uncertain. These results are consistent with the hypothesis that sexual coercion is an important component of male chimpanzee mating strategies in many sociodemographic circumstances, but also show that male tactics vary both in response to and independently of those circumstances.

High inter-rater reliability of Japanese bedriddenness ranks and cognitive function scores: a hospital-based prospective observational study.

BACKGROUND: The statistical validities of the official Japanese classifications of activities of daily living (ADLs), including bedriddenness ranks (BR) and cognitive function scores (CFS), have yet to be assessed. To this aim, we evaluated the ability of BR and CFS to assess ADLs using inter-rater reliability and criterion-related validity. METHODS: New inpatients aged ≥75 years were enrolled in this hospital-based prospective observational study. BR and CFS were assessed once by an attending nurse, and then by a social worker/medical clerk. We evaluated inter-rater reliability between different professions by calculating the concordance rate, kappa coefficient, Cronbach's α, and intraclass correlation coefficient. We also estimated the relationship of the Barthel Index and Katz Index with the BR and CFS using Spearman's correlation coefficients. RESULTS: For the 271 patients enrolled, BR at the first assessment revealed 66 normal, 10 of J1, 15 of J2, 18 of A1, 31 of A2, 37 of B1, 35 of B2, 22 of C1, and 32 of C2. The concordance rate between the two BR assessments was 68.6%, with a kappa coefficient of 0.61, Cronbach's α of 0.91, and an intraclass correlation coefficient of 0.83, thus showing good inter-rater reliability. BR was negatively correlated with the Barthel Index (r = - 0.848, p < 0.001) and Katz Index (r = - 0.820, p < 0.001), showing justifiable criterion-related validity. Meanwhile, CFS at the first assessment revealed 92 normal, 47 of 1, 19 of 2a, 30 of 2b, 60 of 3a, 8 of 3b, 8 of 4, and 0 of M. The concordance rate between the two CFS assessments was 70.1%, with a kappa coefficient of 0.62, Cronbach's α of 0.87, and an intraclass correlation coefficient 0.78, thus also showing good inter-rater reliability. CFS was negatively correlated with the Barthel Index (r = - 0.667, p < 0.001) and Katz Index (r = - 0.661, p < 0.001), showing justifiable criterion-related validity. CONCLUSIONS: BR and CFS could be reliable and easy-to-use grading scales of ADLs in acute clinical practice or large-scale screening, with high inter-rater reliabilities among different professions and significant correlations with well-established, though complicated to use, instruments to assess ADLs. TRIAL REGISTRATION: UMIN000041051 (2020/7/10).

The nonparametric Behrens-Fisher problem with dependent replicates.

Purely nonparametric methods are developed for general two-sample problems in which each experimental unit may have an individual number of possibly correlated replicates. In particular, equality of the variances, or higher moments, of the distributions of the data is not assumed, even under the null hypothesis of no treatment effect. Thus, a solution for the so-called nonparametric Behrens-Fisher problem is proposed for such models. The methods are valid for metric, count, ordered categorical, and even dichotomous data in a unified way. Point estimators of the treatment effects as well as their asymptotic distributions will be studied in detail. For small sample sizes, the distributions of the proposed test statistics are approximated using Satterthwaite-Welch-type t-approximations. Extensive simulation studies show favorable performance of the new methods, in particular, in small sample size situations. A real data set illustrates the application of the proposed methods.

Comments on: fold change rank ordering statistics: a new method for detecting differentially expressed genes.

We published a new method (BMC Bioinformatics 2014, 15:14) for searching for differentially expressed genes from two biological conditions datasets. The presentation of theorem 1 in this paper was incomplete. We received an anonymous comment about our publication that motivates the present work. Here, we present a complementary result which is necessary from the theoretical point of view to demonstrate our theorem. We also show that this result has no negative impact on our conclusions obtained with synthetic and experimental microarrays datasets.

Data construction for phosphorylation site prediction.

Protein phosphorylation is one of the most pervasive post-translational modifications, regulating diverse cellular processes in various organisms. As mass spectrometry-based experimental approaches for identifying phosphorylation events are resource-intensive, many computational methods have been proposed, in which phosphorylation site prediction is formulated as a classification problem. They differ in several ways, and one crucial issue is the construction of training data and test data for unbiased performance evaluation. In this article, we categorize the existing data construction methods and try to answer three questions: (i) Is it equivalent to use different data construction methods in the assessment of phosphorylation site prediction algorithms? (ii) What kind of test data set is unbiased for assessing the prediction performance of a trained algorithm in different real world scenarios? (iii) Among the summarized training data construction methods, which one(s) has better generalization performance for most scenarios? To answer these questions, we conduct comprehensive experimental studies for both non-kinase-specific and kinase-specific prediction tasks. The experimental results show that: (i) different data construction methods can lead to significantly different prediction performance; (ii) there can be different test data construction methods that are unbiased with respect to different real world scenarios; and (iii) different data construction methods have different generalization performance in different real world scenarios. Therefore, when developing new algorithms in future research, people should concentrate on what kind of scenario their algorithm will work for, what the corresponding unbiased test data are and which training data construction method can generate best generalization performance.

Changes in the dominance hierarchy of captive female Japanese macaques as a consequence of merging two previously established groups.

Dominance hierarchies play an important role in reducing competition and aggression in social animals. In zoos, changes in group composition are often required due to management protocols, but these changes may have long lasting effects on dominance hierarchies, and, consequently, the wellbeing of the animals. We studied the changes in the female dominance hierarchy that occurred both during and after the formation of a group of 10 adult Japanese macaques at the Zoo de Granby by combining members from two previously established groups. There was no significant correlation between individual ranks in the old groups (groups A and B) and their ranks in the new group (group AB), indicating a significant change in the hierarchy. Alliances between kin appeared to be important in determining rank; when the sister of the dominant female was removed from group AB, the hierarchy changed significantly a second time. The average standardized rank of individuals added later in the formation process of group AB was not different from those added earlier. Ranks in the group AB did correlate with age of individual at the beginning of the field season, but not at the end, after the shift in hierarchy occurred. Zoo management must be aware of the consequences small changes in a social group can have when removing and transferring individuals in both primates and in other social species. Zoo Biol. 35:505-512, 2016. © 2016 Wiley Periodicals, Inc.

Towards an integrated phylogenetic classification of the Tremellomycetes.

Families and genera assigned to Tremellomycetes have been mainly circumscribed by morphology and for the yeasts also by biochemical and physiological characteristics. This phenotype-based classification is largely in conflict with molecular phylogenetic analyses. Here a phylogenetic classification framework for the Tremellomycetes is proposed based on the results of phylogenetic analyses from a seven-genes dataset covering the majority of tremellomycetous yeasts and closely related filamentous taxa. Circumscriptions of the taxonomic units at the order, family and genus levels recognised were quantitatively assessed using the phylogenetic rank boundary optimisation (PRBO) and modified general mixed Yule coalescent (GMYC) tests. In addition, a comprehensive phylogenetic analysis on an expanded LSU rRNA (D1/D2 domains) gene sequence dataset covering as many as available teleomorphic and filamentous taxa within Tremellomycetes was performed to investigate the relationships between yeasts and filamentous taxa and to examine the stability of undersampled clades. Based on the results inferred from molecular data and morphological and physiochemical features, we propose an updated classification for the Tremellomycetes. We accept five orders, 17 families and 54 genera, including seven new families and 18 new genera. In addition, seven families and 17 genera are emended and one new species name and 185 new combinations are proposed. We propose to use the term pro tempore or pro tem. in abbreviation to indicate the species names that are temporarily maintained.

The DIRAC framework: Geometric structure underlies roles of diversity and accuracy in combining classifiers.

Combining classification systems potentially improves predictive accuracy, but outcomes have proven impossible to predict. Similar to improving binary classification with fusion, fusing ranking systems most commonly increases Pearson or Spearman correlations with a target when the input classifiers are "sufficiently good" (generalized as "accuracy") and "sufficiently different" (generalized as "diversity"), but the individual and joint quantitative influence of these factors on the final outcome remains unknown. We resolve these issues. Building on our previous empirical work establishing the DIRAC (DIversity of Ranks and ACcuracy) framework, which accurately predicts the outcome of fusing binary classifiers, we demonstrate that the DIRAC framework similarly explains the outcome of fusing ranking systems. Specifically, precise geometric representation of diversity and accuracy as angle-based distances within rank-based combinatorial structures (permutahedra) fully captures their synergistic roles in rank approximation, uncouples them from the specific metrics of a given problem, and represents them as generally as possible.

Rank-based principal stratum sensitivity analyses.

We describe rank-based approaches to assess principal stratification treatment effects in studies where the outcome of interest is only well-defined in a subgroup selected after randomization. Our methods are sensitivity analyses, in that estimands are identified by fixing a parameter and then we investigate the sensitivity of results by varying this parameter over a range of plausible values. We present three rank-based test statistics and compare their performance through simulations, and provide recommendations. We also study three different bootstrap approaches for determining levels of significance. Finally, we apply our methods to two studies: an HIV vaccine trial and a prostate cancer prevention trial.

Consistency of dominance rank order: a comparison of David's Scores with I&SI and Bayesian methods in macaques.

In nonhuman primate social groups, dominance ranks are usually assigned to individuals based on outcomes of dyadic agonistic encounters. Multiple approaches have been used, but currently there is no consensus. One approach, David's Scores (DS), offers dual advantages of yielding cardinal scores that may in turn be used to compute hierarchical steepness. Here we correlate rank orders yielded by DS with those yielded by both the traditionally used I&SI approach and the recently proposed parametric Bayesian approach. We use six datasets for female macaques (three despotic and three tolerant groups), and 90 artificially generated datasets modeling macaque groups. We also use the artificial datasets to determine the impact of three characteristics (group size, interaction frequency, and directional asymmetry of aggression) on the magnitude of correlation coefficients, and assess the relative utility of two indices used to compute DS: Dij versus Pij. DS-based rank orders were strongly positively correlated with those yielded by the other two approaches for five out of the six macaque datasets, and for the majority of artificial datasets. Magnitudes of correlation coefficients were unrelated to group size or interaction frequency, but increased with directional asymmetry, suggesting methodological inconsistencies were more likely when dyads had more frequent reversals in directions of aggression. Finally, rank orders calculated using the Dij and Pij indices were similarly consistent with orders from other methods. We conclude that DS offers consistent estimates of rank orders, except perhaps in groups with very low levels of aggression asymmetry. In such "tolerant" groups, we suggest that the relatively greater methodological variability in rank orders may reflect behavioral characteristics of tolerant groups rather than computational inconsistencies between methods. We hypothesize that this quality may be quantified using posterior probability scores of Bayesian rank orders and may also index macaque social styles.

Tukey's Depth for Object Data.

We develop a novel exploratory tool for non-Euclidean object data based on data depth, extending celebrated Tukey's depth for Euclidean data. The proposed metric halfspace depth, applicable to data objects in a general metric space, assigns to data points depth values that characterize the centrality of these points with respect to the distribution and provides an interpretable center-outward ranking. Desirable theoretical properties that generalize standard depth properties postulated for Euclidean data are established for the metric halfspace depth. The depth median, defined as the deepest point, is shown to have high robustness as a location descriptor both in theory and in simulation. We propose an efficient algorithm to approximate the metric halfspace depth and illustrate its ability to adapt to the intrinsic data geometry. The metric halfspace depth was applied to an Alzheimer's disease study, revealing group differences in the brain connectivity, modeled as covariance matrices, for subjects in different stages of dementia. Based on phylogenetic trees of 7 pathogenic parasites, our proposed metric halfspace depth was also used to construct a meaningful consensus estimate of the evolutionary history and to identify potential outlier trees.

Clinical Evaluation of Stainless Steel Crown versus Zirconia Crown in Primary Molars: An In Vivo Study.

Aim: The objective of this clinical trial was to evaluate and compare two full-coronal restoration [stainless steel crowns (SSCs) and zirconia crown] in carious primary posterior teeth. Materials and methods: Forty endodontically treated primary teeth in children within the age-group of 3-9 years were selected and divided into two equal groups (20 SSCs and 20 zirconia crown). The two crowns were evaluated for retentivity of crown, temporomandibular joint (TMJ) problem, gingival response, plaque accumulation, and tooth wear in opposing teeth after 1st and 3rd month follow-up. Results: Both the crowns showed 100% results regarding TMJ problems, but SSCs performed better in terms of retention of crown, gingival response, plaque accumulation, and tooth wear in opposing teeth. The statistics showed significant result by using Mann-Whitney U test and Wilcoxon signed-rank test. Conclusion: Stainless steel crowns performed better among both the full-coronal restoration for posterior primary teeth. Clinical significance: Stainless steel crowns remain "Gold Standard", for posterior full coverage restorations in primary molars as compared to zirconia crowns. How to cite this article: Agrawal R, Khanduja R, Singhal M, et al. Clinical Evaluation of Stainless Steel Crown versus Zirconia Crown in Primary Molars: An In Vivo Study. Int J Clin Pediatr Dent 2022;15(1):15-19.

Could a Focus on the "Why" of Taxonomy Help Taxonomy Better Respond to the Needs of Science and Society?

Genomics has put prokaryotic rank-based taxonomy on a solid phylogenetic foundation. However, most taxonomic ranks were set long before the advent of DNA sequencing and genomics. In this concept paper, we thus ask the following question: should prokaryotic classification schemes besides the current phylum-to-species ranks be explored, developed, and incorporated into scientific discourse? Could such alternative schemes provide better solutions to the basic need of science and society for which taxonomy was developed, namely, precise and meaningful identification? A neutral genome-similarity based framework is then described that could allow alternative classification schemes to be explored, compared, and translated into each other without having to choose only one as the gold standard. Classification schemes could thus continue to evolve and be selected according to their benefits and based on how well they fulfill the need for prokaryotic identification.

Innovation and efficiency in financial institutions.

This paper proposes a new methodology that combines standard production theory with Multiple-Criteria Decision Analysis (MCDA) methods to rank banks based on their capability of using investment in new technologies to reduce the other inputs' usage, for a given level of output. Banks are first ranked based on their investment in innovation (innovation rank); afterwards, we calculate the overall rank by combining two factors of production, viz. labor and assets, using the PROMETHEE II approach that belongs to the family of the outranking methods. We then use directional efficiency measures to measure the banks' efficiency by means of relation between two ranks, for a given level of the outputs. We apply the methodology to a sample of US and EU banks sourced from Orbis BankFocus. The key findings suggest there are four types of banks in our sample: (a) banks whose innovation rank is positively correlated with the overall rank; (b) banks exhibiting a negative correlation between two ranks: their overall ranks are low while still exhibiting high innovation ranks; (c) banks with high overall rank but low innovation rank and (d) banks with the worst ranks both for the innovation rank and the overall rank. The least efficient banks belong to this group.