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At least 37 records · Page 2Linked to original sources
PubMed1978

When does a response error become a judgmental bias? Commentary on "Judged Frequency of Lethal Events".

The study of Lichtenstein, Slovic, Fischhoff, Layman, and Combs reports several types of errors in subjects' frequency judgments of lethal events. These errors are interpreted as reflecting the operation of two types of judgment biases. In this research, the objective or actual frequency of lethal events served as a standard of comparison; any deviation from this standard was defined as a bias. Thus, the research strategy used is apparently modeled after that of a psychophysicist using illusions to study basic perceptual processes. There is one key difference, however. In the case of illusions, the subject is directly exposed to the physical stimulus object. In the present study, however, subjects were never exposed to actual stimuli. Since subjects were asked to make judgments about things they had not directly experienced, it is not surprising that they would be inaccurate. But unlike the study of illusions, such inaccuracies have not been shown to have any necessary connection to psychological mechanisms. Therefore, it seems somewhat tenuous to offer psychological interpretations of judgmental biases when the origins of those biases have not yet been identified.

Female↗
PubMed2026

Beauty bias in butterfly research and conservation.

Conservation biases have been documented since the first emergence of the concept of biodiversity in the 1980s,1,2,3 showing a systematic disproportion in the allocation of research and conservation efforts among taxa.4,5,6,7,8,9,10,11 One factor underlying this disproportion, gaining prominence in recent literature, is species' perceived beauty, shaped by human visual preferences.12,13,14,15,16,17 Here, we integrate a large-scale survey of the perceived beauty of European butterflies yielding >21,000 survey completions from >100 countries into a time-explicit network linking species' beauty, public attention, research and conservation efforts, and the EU regulatory framework. We found that species beauty is consistently associated with public attention, research, and conservation efforts in a temporally structured pattern compatible with a cumulative beauty bias. Research effort and public attention concentrate on widespread and visually attractive species, whereas species included in the legal conservation framework, particularly the Convention on the Conservation of European Wildlife and Natural Habitats (hereafter, Bern Convention, BC, 1979)18 and the EU Habitats Directive (hereafter, HD, 1992)19 are disproportionately represented by visually appealing and historically protected taxa. Because these frameworks guide funding and management actions, early associations between species beauty and BC/HD inclusion have contributed to long-lasting institutional patterns in butterfly research and conservation. By contrast, European IUCN Red Lists20,21 do not overrepresent beautiful species and identify more inconspicuous taxa as threatened. This mismatch reveals a tension between scientific assessments of extinction risk and historically embedded conservation priorities. Our findings suggest that recognizing beauty bias is vital for aligning conservation with actual ecological urgency. VIDEO ABSTRACT.

Animals↗
PubMed2025

Nonhypermutator Cancers Access Driver Mutations Through Reversals in Germline Mutational Bias.

Cancer is an evolutionary disease driven by mutations in asexually reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Nonhypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and nonhypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and nonhypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

Neoplasms↗
PubMed2025

Navigating Sampling Bias in Discrete Phylogeographic Analysis: Assessing the Performance of an Adjusted Bayes Factor.

Bayesian phylogeographic inference is widely used in molecular epidemiological studies to reconstruct the dispersal history of pathogens. Discrete phylogeographic analysis treats geographic locations as discrete traits and infers lineage transition events among them, and is typically followed by a Bayes factor (BF) test to assess the statistical support. In the standard BF (BFstd) test, the relative abundance of the involved trait states is not considered, which can be problematic in the case of unbalanced sampling. Existing methods to correct sampling bias in discrete phylogeographic analyses using continuous-time Markov chain (CTMC) model, often require additional epidemiological information to balance the sampling effort among locations. As such data is not necessarily available, alternative approaches that rely solely on available genomic data are needed. In this perspective, we assess the performance of a modification of the BFstd, the adjusted Bayes factor (BFadj), which incorporates information on the relative abundance of samples by location when inferring support for transition events and root location inference without requiring additional data. Using a simulation framework, we assess the statistical performance of BFstd and BFadj under varying levels of sampling bias, estimating their type I and type II error rates. Our results show that BFadj complements the BFstd by reducing type I errors at the cost increasing type II errors for inferred transition events, while improving type I and type II errors in root location inference. Our findings provide guidelines for implementing the complementary BFadj to detect and mitigate sampling bias in discrete phylogeographic inference using CTMC modeling.

Bayes Theorem↗
PubMed2025

Positive selection and relaxed purifying selection contribute to rapid evolution of sex-biased genes in green seaweed Ulva.

BACKGROUND: The evolution of differences in gamete size and number between sexes is a cornerstone of sexual selection theories. The green macroalga Ulva, with incipient anisogamy and parthenogenetic gametes, provides a unique system to investigate theoretical predictions regarding the evolutionary pressures that drive the transition from isogamy to anisogamy, particularly in relation to gamete size differentiation and sexual selection. Its minimal gamete dimorphism and facultative parthenogenesis enable a rare window into early evolutionary steps toward anisogamy. RESULTS: By analyzing the expression profiles of sex-biased genes (SBGs) during gametogenesis, we found that SBGs evolve faster than unbiased genes, driven by higher rates of non-synonymous substitution (dN), indicating that SBGs are under stronger selective pressures. Mating type minus-biased genes (mt-BGs) exhibit higher dN/dS values than mating type plus-biased genes (mt+BGs), suggesting stronger selective pressures on mt-BGs, although this difference was not statistically significant (P = 0.08). Using branch-site and RELAX models, we found positive selection and relaxed purifying selection acting on a significant proportion of SBGs, particularly those associated with flagella function. CONCLUSIONS: This study highlights the selective pressures shaping anisogamy and provides insights into the molecular mechanisms underlying its evolution. The faster evolution of SBGs, particularly mt-BGs, and the positive selection on genes associated with motility, such as those related to flagella function, suggest the importance of enhanced gamete motility in the transition to anisogamy. These findings contribute to our understanding of sexual selection and the evolutionary forces that drive the differentiation of gamete size and number between sexes.

Selection, Genetic↗
PubMed2025

Reference genome bias in light of species-specific chromosomal reorganization and translocations.

BACKGROUND: Whole-genome sequencing efforts, have during the past decade, unveiled the central role of genomic rearrangements-such as chromosomal inversions-in evolutionary processes, including local adaptation in a wide range of taxa. However, employment of reference genomes from distantly or even closely related species for mapping and the subsequent variant calling can lead to errors and/or biases in the datasets generated for downstream analyses. RESULTS: Here, we capitalize on the recently generated chromosome-anchored genome assemblies for Arctic cod (Arctogadus glacialis), polar cod (Boreogadus saida), and Atlantic cod (Gadus morhua) to evaluate the extent and consequences of reference bias on population sequencing datasets (approx. 15-20 × coverage) for both Arctic cod and polar cod. Our findings demonstrate that the choice of reference genome impacts the mapping statistics, including mapping depth and mapping quality, as well as core population genetic estimates, such as heterozygosity levels, nucleotide diversity (π), and cross-species genetic divergence (DXY). Furthermore, using a more distantly related reference genome can lead to inaccurate detection and characterization of chromosomal inversions, i.e., in terms of size (length) and location (position), due to inter-chromosomal reorganizations between species. Additionally, we observe that some of the verified species-specific inversions are split across multiple genomic regions when mapped against a heterospecific reference. CONCLUSIONS: Inaccurate identification of chromosomal rearrangements as well as biased population genetic measures could potentially lead to erroneous interpretation of species-specific genomic diversity, impede the resolution of local adaptation, and thus, impact predictions of their genomic potential to respond to climatic and other environmental perturbations.

Animals↗
PubMed2026

Natural Selection Drives Codon Usage Bias in the Mitochondrial Genome of Ligula intestinalis (Linnaeus, 1758) Gmelin, 1790 (Cestoda: Diphyllobothriidea): Insights from Comparative Genomics and Optimal Codon Identification.

Codon usage bias (CUB) is a useful indicator of evolutionary forces shaping mitochondrial genomes. Codon usage bias in mitochondrial genomes of Diphyllobothriidae and especially in Ligula intestinalis was characterized. The roles of natural selection and mutation pressure in framing this bias were evaluated on the basis of 12 protein-coding genes in Diphyllobothriidae. The complete mitogenome (13,725 bp) of L. intestinalis comprises 12 protein-coding genes (PCGs), 22 tRNAs, and two rRNAs, all positioned on the heavy strand, and contains an overall AT content of 66.15%. The mean CAI (0.176), CBI (-0.105), and ENC (45.33) and an evident preference for U-ending codons observed in all examined genes indicate weak CUB. Neutrality, ENC, and PR2 plots consistently demonstrate that natural selection is the predominant force driving CUB and contributes approximately 56% in L. intestinalis and 83% in other Diphyllobothriidea species, with mutation pressure playing a secondary role. Phylogenetic reconstruction supported the monophyly of Diphyllobothriidea, confirmed the paraphyly of Diphyllobothrium as traditionally defined, and placed Ligula and Digramma as sister taxa. These findings clarify the evolutionary constraints governing codon usage in cestode mitogenomes and provide practical resources for codon optimization in heterologous gene expression and genetic studies of this economically important parasite.

Diphyllobothriidea↗
PubMed2026

Genome-wide characterization of the TGF-β superfamily identifies bmp15, gdf9, and gsdf as sex-biased candidate regulators of gonadal differentiation in the synchronous hermaphrodite Plectropomus leopardus.

The transforming growth factor-β (TGF-β) superfamily plays conserved roles in vertebrate reproduction and gonadal sex differentiation. However, its genomic repertoire and sex-biased expression patterns remain unclear in the leopard coral grouper (Plectropomus leopardus), a species with synchronous hermaphroditism. Here, we performed a genome-wide identification of the TGF-β superfamily, identifying 42 genes from the chromosome-level genome. Phylogenetic and synteny analyses indicated that segmental duplication under purifying selection contributed to family expansion. Expression profiling across multiple tissues and four gonadal developmental stages (undifferentiated, 120 dph; early differentiated, 15 months; mature testis, 3 years; mature ovary, 3 years) identified eight gonad-enriched genes, among which bmp15 and gdf9 exhibited pronounced female-biased expression, with transcripts localized exclusively to the oocyte cytoplasm, particularly in stage II-III oocytes. In contrast, gsdf showed male-biased expression and was localized in spermatogenic cells of the testis. These reciprocal expression patterns indicate that bmp15/gdf9 and gsdf are candidate factors associated with gonadal sex differentiation. Our study provides the first comprehensive characterization of the TGF-β superfamily in P. leopardus and highlights bmp15, gdf9, and gsdf as candidate sex-differentiation factors in this hermaphroditic species.

Animals↗
PubMedDate not supplied

Statistical bias in cross-sequential studies of aging.

In an earlier published study (Botwinick & Arenberg, 1976) it was argued that cross-sequential designs used in studies of aging and intelligence bias results in favor of a larger main effects F ratio for cohort than for time of measurement. As a consequence, purely ontogenetic influences are likely to be misinterpreted as generational. The present paper gives conclusive proof of the statistical bias inherent in these designs. In addition it shows that, for any given number of measurement occasions, the degree of bias increases with the number of different cohorts tested. An explanation of the statistical problem in intuitive terms is also provided.

Aging↗
PubMed1979

Memory loss and response bias in senescence.

Recognition memory was studied in young and elderly women by assessing memory strength and response bias using Signal Detection Theory methodology. Young women (mean age 21 years; n = 8) had better recognition memory (d' and d'e) than did elderly women (mean age 71 years; n = 16) but the groups did not differ significantly on correct recognitions (hit rate) or incorrect recognitions (false affirmative rate). Evaluation of response bias indicated that the elderly women adopted a lax response strategy which resulted in an inflated correct recognition rate. The data indicate that, in aging research, evaluation of memory in terms of correct and incorrect recognitions can lead to erroneous interpretations, due to uncontrolled bias effects. Age does adversely influence recognition memory strength suggesting that acquisition and/or storage processes are not invariant with age.

Adult↗
PubMed2026

Systematic contextual biases in SegmentNT potentially relevant to other nucleotide transformer models.

Recent advances in large language models have extended to genomic applications, yet model robustness relative to context is unclear. Here, we demonstrate two intrinsic biases (input sequence length and nucleotide position) affecting SegmentNT results, a model included with the Nucleotide Transformer that provides nucleotide-level predictions of biological features. We demonstrate that nucleotide position within the input sequence (beginning, middle, or end) alters the nature of SegmentNT's raw prediction probabilities, which can be standardized to improve prediction consistency. While longer input sequence length improves model performance, diminishing returns suggest a surprisingly small input length of ∼3072 nucleotides might be sufficient for many applications. We further identify a 24-nucleotide periodic oscillation in SegmentNT's prediction probabilities, revealing an intrinsic bias potentially linked to the model's training tokenization (6-mers) and architecture. We identify potential approaches to account for these biases and provide generalizable insights for utilizing nucleotide-resolution functional prediction models.

Nucleotides↗
PubMed2024

Non-hypermutator cancers access driver mutations through reversals in germline mutational bias.

Cancer is an evolutionary disease driven by mutations in asexually-reproducing somatic cells. In asexual microbes, bias reversals in the mutation spectrum can speed adaptation by increasing access to previously undersampled beneficial mutations. By analyzing tumors from 20 tissues, along with normal tissue and the germline, we demonstrate this effect in cancer. Non-hypermutated tumors reverse the germline mutation bias and have consistent spectra across tissues. These spectra changes carry the signature of hypoxia, and they facilitate positive selection in cancer genes. Hypermutated and non-hypermutated tumors thus acquire driver mutations differently: hypermutated tumors by higher mutation rates and non-hypermutated tumors by changing the mutation spectrum to reverse the germline mutation bias.

Journal Article↗
PubMed1976

Correction of stereological parameters from biased samples on nucleated particle phases. I. Nuclear volume fraction.

Stereologists are aware that the experimental evaluation of component volume fractions and surface-to-volume ratios are subject to systematic errors whenever the requirements for cell identification impose the necessity for component-biased sectioning. Mathematical corrections of biased volume proportion data have recently been published; these corrections assume that the components under analysis are spherical, and that the nucleated particle phase is monodispersed. In this report, general methods for obtaining corrections of biased nuclear volume fraction data are set out for polydispersed phases of nucleated particles, in terms of the relevant shapes and joint size distribution of nucleus and cell; the scope and limitations of these methods are thereby discussed. Explicit corrections of an immediate applicability are obtained, together with their standard errors, for monodispersed phases where nucleus and cell are two dissimilar biaxial ellipsoids (spheroids). When nucleus and cell are two concentric and similar convex bodies of a certain class--to which triaxial ellipsoids belong--the corrections are shown to be very simple. The corrections for the spheroid-spheroid systems are easily accessible with the aid of a small programmable calculator, whereas those for the sphere-spheroid models are directly obtainable from two nomograms.

Cell Nucleus↗
PubMed1976

Correction of stereological parameters from biased samples on nucleated particle phases. II. Specific surface area.

General formulations for correcting component-biased S/V estimates on polydispersed phases of nucleated particles are set out. Direct application of these corrections to monodispersed phases where nucleus and cell are spheroids, yield explicit corrections. As a rule, the corrected specific surface area of the containing bodies equals the product of the nuclear-biased estimate times a correction coefficient, which is bigger than one, and depends upon the shape of the components and the relative volume of nucleus-in-cell. Reference curves which allow a rapid obtention of the correction factor, are provided. Simple formulae for correcting biased surface density and surface-to-volume ratio estimates other than the specific surface area, are also given, together with the standard errors of the corrected parameters.

Anterior Horn Cells↗
PubMed2025

Absolute quantification of the living skin microbiome overcomes relic-DNA bias and reveals specific patterns across volunteers.

BACKGROUND: As the first line of defense against external pathogens, the skin and its resident microbiota are responsible for protection and eubiosis. Innovations in DNA sequencing have significantly increased our knowledge of the skin microbiome. However, current characterizations do not discriminate between DNA from live cells and remnant DNA from dead organisms (relic DNA), resulting in a combined readout of all microorganisms that were and are currently present on the skin rather than the actual living population of the microbiome. Additionally, most methods lack the capability for absolute quantification of the microbial load on the skin, complicating the extrapolation of clinically relevant information. RESULTS: Here, we integrated relic-DNA depletion with shotgun metagenomics and bacterial load determination to quantify live bacterial cell abundances across different skin sites. Though we discovered up to 90% of microbial DNA from the skin to be relic DNA, we saw no significant effect of this on the relative abundances of taxa determined by shotgun sequencing. Relic-DNA depletion prior to sequencing strengthened underlying patterns between microbiomes across volunteers and reduced intraindividual similarity. We determined the absolute abundance and the fraction of population alive for several common skin taxa across body sites and found taxa-specific differential abundance of live bacteria across regions to be different from estimates generated by total DNA (live + dead) sequencing. CONCLUSIONS: Our results reveal the significant bias relic DNA has on the quantification of low biomass samples like the skin. The reduced intraindividual similarity across samples following relic-DNA depletion highlights the bias introduced by traditional (total DNA) sequencing in diversity comparisons across samples. The divergent levels of cell viability measured across different skin sites, along with the inconsistencies in taxa differential abundance determined by total vs live cell DNA sequencing, suggest an important hypothesis for certain sites being susceptible to pathogen infection. Overall, our study demonstrates a characterization of the skin microbiome that overcomes relic-DNA bias to provide a baseline for live microbiota that will further improve mechanistic studies of infection, disease progression, and the design of therapies for the skin. Video Abstract.

Humans↗
PubMed1977

Orientation bias in the Rod-and-Frame Test.

Rod-and-frame data for a sample of 21 males and 25 females showed marked asymmetries in the magnitudes of the frame effects for left and right frame-tilt. These asymmetries are interpreted as an underlying tendency for individuals to set the rod systematically clockwise or counterclockwise of true vertical, independently of the influence of the visible frame, and the term "orientation bias" is used to describe this tendency. 14 males and 14 females demonstrated orientation biases significantly different from zero. In group comparisons males differed significantly from females, the mean bias for males as a group lying significantly left (counterclockwise) of vertical while the mean for females as a group did not differ from zero. Implications for conventional measures of field dependence are discussed. Possible diagnostic significance of orientation performance for brain injury is also considered, and an unusual individual performance is described.

Adult↗
PubMed1979

Bias in drug abuse survey research.

An analysis of the drug abuse literature indicated that significant biases may affect the existing data. First, the lack of standardization in survey research leads to problems of reliability, validity, and objectivity in drug abuse measurement. Second, the "demand characteristics" of the survey situation may cause the subject to bias his responses in a particular direction, depending on his interaction with and his interpretations of the survey conditions. Third, both overt and covert biases of the researcher may significantly affect the outcome of the survey. Fourth, limitations of the survey method itself (e.g., the source of the survey data, difficulties in obtaining random samples, conclusions overemphasizing student drug use, limitations of the sample survey as a measurement device) seriously restrict our understanding of drug abuse phenomena.

Humans↗
PubMed2026

A doubly robust framework for addressing outcome-dependent selection bias in multi-cohort EHR studies.

Selection bias can hinder accurate estimation of association parameters in binary disease risk models using non-probability samples like electronic health records (EHRs). The issue is compounded when participants are recruited from multiple clinics/centers with varying selection mechanisms that may depend on the disease/outcome of interest. Traditional inverse-probability-weighted (IPW) methods, based on constructed parametric selection models, often struggle with misspecifications when selection mechanisms vary across cohorts. This paper introduces a new Joint Augmented Inverse Probability Weighted (JAIPW) method, which integrates individual-level data from multiple cohorts collected under potentially outcome-dependent selection mechanisms, with data from an external probability sample. JAIPW offers double robustness by incorporating a flexible auxiliary score model to address potential misspecifications in the selection models. We outline the asymptotic properties of the JAIPW estimator, and our simulations reveal that JAIPW achieves up to 6 times lower relative bias and 5 times lower root mean square error (RMSE) compared to the best performing joint IPW methods under scenarios with misspecified selection models. Applying JAIPW to the Michigan Genomics Initiative (MGI), a multi-clinic EHR-linked biobank, combined with external national probability samples, resulted in cancer-sex association estimates closely aligned with national benchmark estimates. We also analyzed the association between cancer and polygenic risk scores (PRS) in MGI to illustrate a situation where the exposure variable is not measured in the external probability sample.

Selection Bias↗