The food environment provides an abundance of energy-dense packaged food, some specifically designed to attract children. The appeal of these energy-dense child-targeted foods can have health implications. Some children may be more susceptible to their appeal due to temperamental differences, namely their levels of impulsivity and inhibitory control. This study aimed to determine whether the temperamental dimensions of impulsivity and inhibitory control were associated with children's preferences for packaged food. Five hundred fourteen primary school children (5-12 years) recruited from a science museum participated in a discrete choice experiment to determine their preferred packaging attributes, an implicit association test to assess their attitudes toward packaging, and anthropometric measurements. Primary caregivers completed either the Child Behavior Questionnaire or the Temperament in Middle Childhood Questionnaire to assess impulsivity and inhibitory control in their children. T-tests and multiple regression analyses were utilised for the study. Four key results were found: (a) children preferred the food packaging attributes that reflected healthiness, and (b) they perceived the child-targeted packaging to be healthier compared with plain packaging. However, (c) older children (aged 9-12 years) with higher levels of impulsivity were less discriminating with the packaging design than did children with lower levels, and (d) there was no effect of inhibitory control on children's preferences. Future research should investigate how food manufacturers and policymakers can design food packaging to support children in making healthier choices from packaged foods, particularly those with higher levels of impulsivity.

Using intersectional implicit association measures does not consistently improve the predictive validity of the implicit association test

SES bias in facial trustworthiness judgments: The roles of perceivers' SES and implicit SES stereotypes.

Intracranial aneurysm (IA) is a common neurovascular disorder; rupture causes aneurysmal subarachnoid hemorrhage with high mortality. Despite available interventions, effective preventative therapies are lacking. We aimed to identify novel genetic determinants of IA and aneurysmal subarachnoid hemorrhage to improve risk prediction and nominate hypothesis-generating therapeutic candidates for future evaluation. We conducted a multiancestry genome-wide association study and statistical fine-mapping study across European and East Asian cohorts and applied rigorous multiancestry and multitrait meta-analyses to identify IA-associated loci. Utilizing the Multi-Ancestry Sum of Single Effects model tool for fine mapping, we fine-mapped ancestry-specific and shared signals across loci. To derive a credible set of candidate genes, we integrated data from functional mapping and annotation, polygenic priority score, multivariate set-based association test (combined), transcriptome-wide association study, and summary data-based Mendelian randomization, focusing on genes identified by at least 4 methods. Machine learning algorithms developed diagnostic models, and a polygenic score model was evaluated using the UK Biobank data set. We identified 3 novel IA-associated loci and observed significant genetic correlations between IA and systemic phenotypes. We prioritized a credible set of 40 candidate genes, including GPX1 and NPC1 among the top-ranked candidates, and an expression-based K-nearest neighbor classifier achieved an area under the curve of 0.89 for case-control discrimination between IA cases and controls. We evaluated an IA polygenic score in the UK Biobank evaluation sample, which yielded an area under the curve of 0.83 (95% CI, 0.81-0.84); this performance reflects discrimination in this evaluation setting and warrants further validation in additional independent cohorts before clinical implementation. We observed nominal evidence of interaction between polygenic score and smoking (P=1.09×10-2), suggesting an interplay between genetic susceptibility and a modifiable lifestyle factor. Computational drug repurposing nominated 32 drug classes, including JAK (Janus kinase) inhibitors and dopamine receptor antagonists, as hypothesis-generating candidates for future experimental evaluation. These findings refine IA/aneurysmal subarachnoid hemorrhage-associated loci, prioritize credible candidate genes for functional follow-up, and provide hypothesis-generating translational leads that may inform future studies, pending validation in independent cohorts and experimental models.

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disease with limited therapies, emphasizing the need for deeper understanding of disease pathogenesis. While more than 40 ALS-associated genes have been identified, their contribution varies significantly across populations and the data from the Indian population remains scarce. We aimed to comprehensively characterize the spectrum of coding DNA variations in ALS-associated genes and identify novel genetic contributors in an Indian cohort. Whole-exome sequencing on 761 ALS patients and 917 in-house healthy controls and repeat-primed PCR for expansions (C9orf72, ATXN2, NOTCH2NLC, NOP56) were performed. Variants were classified using ACMG guidelines, and rare variant association testing was conducted. Overall diagnostic yield was 15.90%, with pathogenic/likely pathogenic variants. Familial ALS showed higher diagnostic yield (36.95%) than sporadic ALS (12.96%). SOD1 dominated familial cases (53.85%), while OPTN, SOD1 and FIG4 were prevalent in sporadic cases. Homozygous SOD1 variants in six patients correlated with juvenile/young onset (< 30 years). C9orf72 expansions (4%) and ATXN2 repeats (1.7%) were identified at frequencies comparable with Asian cohorts. Rare variant analysis identified JAK2 as a novel genome-wide significant signal (FDR = 3.5 × 10-5). This first large-scale genomic survey of Indian ALS patients showed SOD1 being the predominant cause of fALS, while OPTN, FIG4, and other genes drive disease amidst low C9orf72 frequency. The novel JAK2 association suggests a potential neuroinflammatory mechanism, highlighting the importance of studying diverse populations to uncover distinct genetic etiologies.

Despite efforts to increase gender diversity in leadership, women remain undervalued, mainly due to gender stereotypes portraying females as less competent and of lower status. This study employs a novel mixed-gender dyad collaborative task with electroencephalography (EEG) and dipole source localization to investigate the neural mechanisms underpinning gender-biased rejection decisions in a real-time social context. In half of the trials, the male participants were designated as decision-makers, who evaluated their female partners' suggestions and provided the final team answer. EEG data collected from the male low-biased (LB) and high-biased (HB) groups, classified according to the Implicit Association Test (IAT), were analyzed during the decision periods which resulted in the rejection of female answers. The HB group rejected their female partners' choices at 57% in trials with conflict, which was similar in the LB group (55%). However, many rejections by the HB group resulted in wrong decisions (54%) which was significantly lower in the LB group (34%). Although criterion-based bias index from the signal detection theory could not explain this difference, a novel biased-rejection index (BRI), which measured the costly rejection behavior, could significantly separate the two male groups. Dipole source localization based on EEG during the entire decision period revealed significantly lower middle frontal gyrus (MFG), but higher inferior frontal gyrus (IFG) activation in the HB group compared to the LB group. Temporal dynamics analysis (resolution: 0.34s) further showed (but not at a statistically-significant level) less activation in MFG for the HB group during the early stage, and a similar trend in SFG during the middle stage of cognitive processing. On the other hand, the moment magnitudes of IFG dipoles during the entire decision period were significantly correlated with the IAT D-scores, i.e. less IFG activation with lower implicit bias. Given the limitations of the study (lack of EEG from female decision-makers and 10-20 system montage), these findings suggest altered lateral prefrontal cortex (LPFC) activations as part of the neural correlates of gender-biased undervaluation of female contributions during a collaborative task.

This study investigated the long-term clinical effects of multisession gamma transcranial alternating current stimulation (tACS) over the precuneus in early-stage Alzheimer's disease. Forty-six patients from a previous randomized, double-blind, sham-controlled trial with an open-label extension underwent follow-up at 36 and 72 weeks. Participants received either 8 or 16 weeks of gamma tACS. Both treatment durations showed comparable long-term outcomes. Alzheimer's Disease Assessment Scale-Cognitive Subscale did not significantly worsen at 36 weeks, and Face-Name Association Test remained stable at both follow-up time points, whereas Clinical Dementia Rating-Sum of Boxes and Alzheimer's Disease Cooperative Study-Activities of Daily Living worsened over time. These findings suggest relative preservation of selected cognitive measures, despite worsening in broader clinical and functional outcomes.

Health care professionals (HCPs) are known to exhibit explicit and implicit biases toward individuals who use substances. However, it remains unclear whether these biases differ from those of the general population and, if so, when such differences emerge along the training continuum. This study examined whether implicit and explicit biases vary between the general population, health care learners (HCLs), and HCPs, and whether training and experience may modulate the congruence between these bias types. Participants included HCPs, HCLs, and members of the general populations recruited via crowdsourcing. All completed explicit bias instruments and an Implicit Association Test (IAT). Explicit bias scores underwent principal components analysis yielding 2 components: Prejudice (environmental biases) and Stigma Endorsement (personal negative attitudes). Component scores were compared across groups using one-way ANOVA. Fisher's r-to-z transformations compared correlation coefficients between the 3 groups. Hierarchical multiple regression then examined explicit-implicit bias congruence while controlling for key covariates and profession, namely, medicine, nursing, paramedicine (ie, Emergency Medical Technicians, paramedics, and related roles). The sample elicited moderate-to-strong negative biases overall. Groups did not significantly differ in explicit or implicit biases. However, HCPs exhibited significantly stronger correspondence between IAT and Prejudice scores (r = .38, P < .001) than HCLs (r = .10, P = .35) and the general population (r = .08, P = .23); the latter 2 groups did not significantly differ. This difference was maintained in the regression model controlling for key covariates. Although implicit and explicit bias toward individuals who use substances did not differ across HCP, HCL, and the general population, HCPs demonstrated significantly greater alignment of implicit and explicit bias scores. These findings suggest that training and professional experience may not be sufficient to reduce stigma toward this group. In fact, greater experience and environmental biases may be cyclically reinforced.

Small effective population size and the disproportionately large use of few genetically superior bulls in artificial insemination lead to extensive runs of homozygosity and an increased risk of homozygosity for deleterious alleles in domestic cattle, which may cause inbreeding depression. The adverse effects of inbreeding on phenotypic performance are well established, but the genetic variants contributing to inbreeding depression remain largely unknown. This study aimed to analyse the impacts of inbreeding on stature (measured as height at the sacral bone) in a cohort of 15,306 Brown Swiss (BS) cows that have imputed genotypes at 20 million sequence variants and stature measurements as height at the sacral bone. The average genomic inbreeding coefficient of the 15,306 BS cows estimated from runs of homozygosity (ROH) was 0.369 (± 0.022). We found a loss in stature, with height at the sacral bone decreasing by 0.076cm per 1% increase in inbreeding (p = 1.94e-09). Contributions to inbreeding depression were significant for long (> 2Mb), medium (> 0.1-≤ 2Mb), and short (≥ 50kb-≤ 0.1Mb) ROH (p = 1.29e-12, p = 3.20e-04 and p = 1.77e-06, respectively), suggesting that both ancient and recent inbreeding have negative effects on stature. Non-additive association testing identified a novel recessive quantitative trait locus (QTL) for stature on chromosome 25, with the most significantly associated SNP (p = 2.35e-21) residing at 14,535,327bp. Cows homozygous for the alternate allele of the top-associated SNP were 2cm shorter than heterozygous and reference allele homozygotes. Fine mapping of the QTL identified a splice donor variant (rs447836030 at 25:14,515,474) of the gene ABCC6 encoding ATP-binding cassette subfamily C member 6 which causes exon skipping as both a positional and functional candidate causal variant. Our study reveals evidence for inbreeding depression on stature in a large cohort of BS cattle. We also uncover a recessive QTL that decreases stature through non-additive association testing. This QTL harbors a high-impact variant affecting a splice donor site of ABCC6 which leads to exon skipping, thereby possibly contributing to inbreeding depression. Accumulating non-lethal deleterious alleles in ROH may reduce the overall fitness of the BS cattle population.

Patients receiving maintenance hemodialysis (MHD) have a markedly increased incidence of urinary tract infection (UTI) because of impaired immune function, reduced urine output, and complications related to medical procedures. Post-void residual urine volume (PVR) is a key indicator of bladder emptying function. Elevated PVR is associated with urinary retention and bacterial colonization and is considered an indicator related to higher UTI risk. However, previous studies have mainly examined the cross-sectional association between a single PVR measurement and UTI risk. In patients receiving MHD, PVR often changes dynamically because of autonomic neuropathy, diabetic cystopathy, and fluctuations in volume status; therefore, a single assessment may not fully capture longitudinal changes. Group-based trajectory modeling (GBTM) can identify distinct longitudinal patterns, but evidence regarding its use to characterize PVR trajectories in the MHD population and assess their association with UTI risk remains limited. Clinical data were retrospectively collected from 302 patients who received regular MHD treatment at our hospital from January 2021 to December 2024. PVR was measured by ultrasonography every 3-6 months. GBTM was applied to repeated PVR measurements to identify trajectory classes. The optimal model was selected according to the Bayesian information criterion (BIC), average posterior probability (APP), odds of correct classification (OCC), and clinical interpretability. Baseline characteristics and UTI occurrence were compared among trajectory groups, and baseline characteristics of included and excluded patients were compared. Kaplan-Meier analysis and the log-rank test were used to compare cumulative UTI incidence. Posterior-probability-weighted Cox proportional hazards regression and Fine-Gray competing-risk models with death as a competing event were used to assess the association between PVR trajectories and UTI risk. In an exploratory analysis, death and nonfatal study-exit events were also combined as competing events. Restricted cubic spline (RCS) regression was used to explore the dose-response association between baseline PVR and first UTI risk. Robustness was evaluated using a clinically parsimonious Cox model, Firth penalized partial-likelihood Cox regression, and other sensitivity analyses. GBTM identified three PVR trajectories: low-level stable (138 patients, 45.7%), moderate-level increasing (103 patients, 34.1%), and persistently elevated (61 patients, 20.2%). During a median follow-up of 26.8 months, 60 patients (19.9%) developed a first UTI. The proportions of UTI in the low-level stable, moderate-level increasing, and persistently elevated groups were 10.1%, 22.3%, and 37.7%, respectively (χ²=20.78, P < 0.001). In the fully adjusted Cox model, the moderate-level increasing group showed a borderline association with higher first UTI risk (hazard ratio [HR] = 1.96, 95% confidence interval (CI): 1.01-3.82, P = 0.047), but this association did not reach statistical significance in the Fine-Gray competing-risk model (subdistribution hazard ratio [SHR] = 1.85, 95% CI: 0.94-3.64, P = 0.073). The persistently elevated group was independently associated with higher first UTI risk in both the Cox model (HR = 3.35, 95% CI: 1.68-6.68, P = 0.001) and the Fine-Gray model (SHR = 3.12, 95% CI: 1.53-6.36, P = 0.002). RCS exploratory analysis suggested a nonlinear association between baseline PVR and first UTI risk (overall association test P < 0.001; nonlinearity test P = 0.012); the slope of the HR curve tended to increase around approximately 80 mL, and this value was used to describe an exploratory curve feature in this study sample. Among MHD patients with measurable urine output who were able to complete serial PVR assessment, a persistently elevated PVR trajectory was independently associated with higher first UTI risk, and baseline PVR showed a nonlinear dose-response association with first UTI risk. Serial PVR assessment may provide supplementary risk-stratification information for MHD patients with measurable urine output. Not applicable.

Previous research has shown that people tend to associate higher vertical spatial positions with male and lower positions with female. In this study, we document an understudied vertical representation of gender within Azhaliism, a Vajrayana Buddhist lineage practiced by the Bai people in southwestern China. In Study 1, we found that while Bai Taoists exhibited the conventional "men is up" metaphor in an explicit gender-verticality association test, Bai Azhaliists responded with "female is up." In Study 2, Bai Taoists implicitly encoded male faces faster when presented in a high (vs. low) vertical position, whereas Bai Azhaliists showed the opposite pattern, with the "female is up" metaphorical congruency effect standing in stark contrast to many other metaphorical mappings documented to date. These findings are consistent with the view in Azhaliism that sky beings are often female and earth beings are male. We also ruled out an alternative explanation based on power or valence differences between men and women; ratings of power and valence did not differ significantly as a function of target gender among Bai Azhaliists. Taken together, these results suggest that religious practice shapes cultural variation in the metaphorical representation of gender.

Workplace inclusion has gained prominence in autism-employment research, but it remains unclear whether it represents an extension of outcome-focused scholarship or a structurally distinct subdomain. We examined whether the two traditions can be consistently distinguished across bibliometric dimensions, and whether inclusion-oriented growth exceeds overall expansion of autism research output. A comparative bibliometric study used two curated corpora retrieved from Scopus and Web of Science (February 23, 2026): inclusion-oriented (INCL; n = 514) and outcome-oriented (OUT; n = 310), totaling 824 unique publications after deduplication. Structural differentiation was examined using document-level bibliographic coupling with Louvain community detection, complemented by modularity and cluster-corpus association tests. Author, journal, and keyword overlap were quantified using Jaccard indices. Annual counts were normalized against total ASD publication output in Scopus. The coupling network yielded 22 clusters (Q = 0.426). Cluster membership was strongly associated with corpus affiliation, χ²(21) = 105.87, p < .001, Cramér's V = 0.556. Author overlap was low (J = 0.057), journal overlap modest (J = 0.179), and keyword overlap moderate (J = 0.26). The inclusion-oriented share of ASD output grew approximately 4.1-fold from 2011 to 2015 to 2021-2025, against 1.6-fold for outcome-oriented research and 2.4-fold for the broader field. Multiple bibliometric indicators consistently differentiate outcome-oriented and inclusion-oriented corpora, indicating distinct but conceptually adjacent strands of scholarship. Inclusion-oriented research has grown at a rate substantially exceeding overall field expansion. Findings provide hypothesis-generating evidence consistent with disciplinary diversification and highlight the need for integrative frameworks linking vocational rehabilitation and organizational inclusion research.

Hearing in Sickle Cell Disease: Cochlear and Subcortical Dysfunction without Cortical Impairment.

Childhood-onset systemic lupus erythematosus (cSLE) is associated with significant morbidity and mortality. While numerous variants have been associated with adult-onset SLE, limited data exist on genetic variation within cSLE. We aimed to investigate genetic factors of early-onset cSLE, defined as onset of cSLE prior to age 10. Employing a case-only design, we performed whole genome sequencing analysis on 37 subjects with early onset cSLE. We hypothesised that rare, functional variants with large effects in genes associated with SLE contribute to the risk of early-onset cSLE and that the polygenic risk score (PRS) would be inversely associated with age of onset and presence of nephritis. A total of 153 linkage disequilibrium-independent variants were analysed and compared with previously reported SLE single-nucleotide polymorphisms. Rare (minor allele frequency (MAF) ≤1%), damaging protein-altering (Combined Annotation Dependent Depletion; CADD≥20) variants, including variants isolated to previously reported monogenic SLE genes (n=49), were prioritised for secondary analysis. 37.8% of our cSLE cohort carried at least one rare, pathogenic variant in monogenic SLE genes. We identified 31, 012 rare, damaging, pathogenic variants in our cSLE cohort, including two genes implicated in mitochondrial protein degradation (AFG3L2, SPG7) and several genes in the interferon pathway (IFIH1, IFNGR1). We found that higher PRS scores were associated with increased nephritis odds (p=0.0092) but not age of onset (p>0.05). Burden testing using the optimal sequence kernel association test (SKAT-O) revealed nominal enrichment of rare variants (MAF≤ 5%) in immune-related genes, including ISG15, PSMB9 and RNASEH2A, several of which are involved in type I interferon and antigen presentation pathways. These results have the potential to enhance our understanding of cSLE. Further studies must be conducted to expand our findings.

ObjectiveThis study investigated if an empathy-evoking vignette could reduce facial differences bias, while considering gender.DesignParticipants (N = 124) were randomly assigned to read either an empathy-evoking vignette or nothing, after which they completed indirect and direct bias measures.SettingThe study was conducted entirely online.ParticipantsThose completing the study were members of the general public, none of which had a facial difference.InterventionsParticipants either read a short, empathy-evoking vignette or nothing before then completing the tasks.Main Outcome MeasuresThe indirect measure of bias was an implicit association task. Explicit measures of bias were questions about preferences and attitudes toward people with facial differences.ResultsReading the vignette led to lower bias on indirect and direct measures in females, whereas in the small sample of males, vignette males tended toward greater bias than no-vignette males. Although we tried to expand insights into bias in different genders, we did not have enough non-binary participants.ConclusionThis study showed that empathy-evoking vignettes can attenuate facial differences bias in females but may inadvertently heighten bias in males, underscoring the moderating role of gender in narrative-based interventions. Future work should explore diverse narrative types and perspectives, using a wider range of stimuli (varied facial differences, genders, ethnicities) and participant genders, and should incorporate gender into analyses of bias.

NERINE reveals rare variant associations in gene networks across phenotypes and implicates an SNCA-PRL-LRRK2 subnetwork in Parkinson's disease.

The cognitive abilities of many non-human animals have been investigated in recent years; however, outside of laboratory rodent strains, it is largely unknown how direct and indirect genetic factors influence the development of cognition. In a previous study, we found no impact of maternal genetic or non-genetic effects on problem solving in the fawn-footed mosaic-tailed rat Melomys cervinipes. However, cognition is multifaceted, and different forms of cognition may not all be influenced by the same factors. Therefore, we investigated whether maternal genetic and non-genetic effects affected the development of multiple, different measures of cognition in the fawn-footed mosaic-tailed rat. We first measured the amount of maternal care mothers provided to their offspring and then tested mothers and offspring as adults in three tests: an associative memory test, a novel object recognition test, and a food extraction task (to assess learning). We assessed whether the maternal care provided by mothers influenced cognition and used parent-offspring regressions to determine whether the cognitive abilities of individuals had a heritable component. Offspring that received more indirect care were significantly more likely to learn the lever task than offspring that received less indirect care, possibly because this task required more neurological processing for successful completion than the other tests. No other measure of maternal care significantly influenced offspring cognition, and offspring cognition did not appear to have a heritable component. This suggests that cognitive development in this species is likely quite flexible, and that maternal direct and indirect genetic effects may not play a significant role in the development of cognition.

Conceptual metaphor theory supposes that metaphor underlies much of human understanding. The implicit association test (IAT) has recently been used to quantify metaphoric alignments, like black and white, that may also be associated with racial bias. Here, in six experiments, we studied the extent to which performance on the controversial race IAT might be attributed to metaphoric alignments of white and black, such as with good and evil. Experiment 1 replicates a prior report that IAT scores for black-white color alone are as strong as those associated with race. Experiment 2 shows that, for White participants, measured biases are just as strongly correlated between race and color IATs as between two different instances of the race IAT. Experiment 3 shows that metaphor-based color biases measured by IATs are just as strong among people who identify as Black as those who identify as White. Experiments 4 and 6 show that correlations between race and color IAT scores extend to Black participants. Experiment 5 shows that white-positive bias on a variety of color IATs is related to the figurative affective meanings of colors, not to literal color preferences or to explicit racial bias. Experiment 6 showed that variations in the figurative affective meanings of colors predicts within-group variation in scores on the race IAT. Across all experiments that tested both color and race IATs, variation in performance on a black-white color IAT (but not a blue-gray color IAT) was the strongest predictor of variation in performance on the Black-White race IAT.

Recent advances in Bayesian modeling and deep learning have enabled scalable estimation of cognitive process models. In this article, we present a fully Bayesian workflow that leverages amortized inference with neural networks to rapidly estimate individual parameters and compare models from big behavioral data. Using data from a large online implicit association test sample (N > 5,000,000), we investigate how latent parameters, such as drift rate, boundary separation, nondecision times, and their variabilities, relate to key socioeconomic variables. Our exploratory findings reveal small but consistent associations of cognitive model parameters with socioeconomic covariates. Notably, trial-by-trial variability in drift rate, often ignored in prior work, emerged as the strongest predictor across all socioeconomic covariates. Our primary contribution lies in illustrating how deep learning-based Bayesian estimation and model comparison can be applied to mine robust insights from large and noisy behavioral data sets. We discuss limitations and implications for modeling individual differences in large-scale data sets and provide an open pipeline for future use. This work exemplifies how the emerging field of behavioral data science can extend cognitive modeling to new domains and support data-driven hypothesis generation targeting the cognitive underpinnings of individual differences. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

High-throughput genomic and proteomic technologies are used to study biological systems by performing differential expression analysis across various experimental conditions. Geneset Ordinal Association Test (GOAT) is an analytic method recently introduced to statistically evaluate the differential expression of a defined set of genes or proteins. Despite the availability of numerous enrichment tools, many lack accessibility for users without programming expertise, provide limited continuation beyond listing top enriched terms, and offer little support for interactive visual exploration or hypothesis generation. Moreover, existing web-based platforms rarely support multi-contrast comparisons and generally omit gene-level or network-based context for pathway analysis. To address these limitations, we present Geneset Ordinal Association Test Enrichment Analysis (GOATEA), an R/Shiny application that implements and extends the GOAT algorithm with interactive visualization, multi-contrast comparison, and integrated gene- and network-based context for bottom-up pathway analysis, enabling comprehensive enrichment analysis. GOATEA supports independent analysis of transcriptomic and proteomic data. To demonstrate its capability to integrate matched modalities, we applied it to the Colameo dataset containing paired mass spectrometry and RNA sequencing data. This proof-of-concept example highlights the tool's strength in enabling multi-omics analyses and simultaneous comparison of multiple contrasts. An interactive overlap analysis identified 458 shared genes for focused enrichment and network exploration. By integrating these results in a gene- and network-based context for bottom-up pathway analysis, GOATEA applies a stringent interaction confidence threshold to emphasize qualitative protein-protein interactions, highlighting topic-relevant associations for further hypothesis generation. GOATEA streamlines enrichment analysis workflows by combining the GOAT algorithm with interactive visualizations in a user-friendly graphical interface. It facilitates exploratory analysis and hypothesis generation for researchers with or without programming expertise. GOATEA is available as an open-source tool, with full documentation, including usage vignettes (https://mauritsunkel.github.io/goatea/).