Critical Connections Research Articles

TMIC-52. DECODING METABOLIC INTERACTIONS IN GLIOBLASTOMA TUMOR MICROENVIRONMENT THROUGH COMPREHENSIVE SPATIAL TRANSCRIPTOMIC AND PROTEOMIC ANALYSIS

Abstract INTRODUCTION Within the GBM microenvironment, distinct micro-niches arise from independent cancer cell lineages with unique metabolic needs, characterized as Fast Cycling Cells (FCCs) and Slow Cycling Cells (SCCs). FCCs preferentially utilize aerobic glycolysis for energy, whereas treatment-resistant SCCs depend on lipid metabolism. Our study decodes the molecular and spatial heterogeneity within the GBM microenvironment, focusing on the dichotomy of immune infiltrates and the metabolic interactions between SCCs and the immune compartment in human GBM patients. METHODS We performed spatial transcriptomics and proteomics combined with geospatially resolved single-cell neighborhood analysis of IHC-stained GBM tissues using CellProfiler and the SNAQ algorithm that we developed to investigate the specific immune microenvironment of SCCs and FCCs. Holotomography and fluorescence-based time-lapse imaging coupled with flow cytometry were used to study lipid transfer between immune cells and GBM cells. Finally, the effects of pharmacological and genetic targeting of lipid transfer were investigated both in vitro and in vivo. RESULTS Our study establishes a connection between spatial metabolic heterogeneity and immune diversity, highlighting how specific tumor cell lineages correlate with characteristic immune micro-niches. In particular, SCCs exploit the metabolic properties of recruited immunosuppressive myeloid-derived cells, which metabolically support tumor cells by facilitating lipid transport and supporting SCC metabolism. Our results show that inhibiting lipid transfer affect SCCs, remodels the immune microenvironment, delays tumor growth and improves disease outcome. Our study also demonstrates a correlation between predicted sensitivity to lipid-modifying drugs, such as statins, and the SCC phenotype. This correlation could enable stratification and selection of patients most likely to benefit from such treatments. CONCLUSIONS This study establishes critical connections between the TME, cellular metabolism, anti-tumor immunity, and treatment vulnerabilities. Our research provides novel insights into how metabolic exchanges contribute to tumor progression and suggests that targeting metabolic interactions could be an effective therapeutic strategy for GBM.

Leadership as a situated practice: Critical connections and liberated networks

Learning Development is founded on multidisciplinary partnerships and collaboration, which can make it difficult for practitioners to recognise leadership in themselves and have it recognised by others, stymieing progression and confidence. This study aims to explore what leadership looks like in a collaborative, community-driven, third space field of practice, and how Learning Development practitioners might recognise leadership in themselves and enact it in practice. Based on based on semi-structured interviews, a phenomenological approach is taken to explore the perceptions and experiences of 20 participants who self-identify as Learning Developers with an interest in leadership. Four key themes emerged from the analysis: Being in the role; Being part of a team; Being part of a community; and Taking a wider view. Each indicates how leadership in Learning Development is values-driven, social, networked, critical, and operates on the three levels of team, community, and field. The interrelationships between these are expressed as a model for strategic influence driven by collaborative connections, and findings suggest that practitioners act as a hub through which knowledge and connections can flow. Given the challenges currently facing the higher education sector, it is vital that institutions are able to harness these crucial roles to remain flexible, responsive, and effective. This study provides a means for recognition and advancement in fields that lack the clear progression routes of academic and professional services colleagues.

Decentralized Privacy Preservation for Critical Connections in Graphs

Decentralized Privacy Preservation for Critical Connections in Graphs

Active Inference Models of AV Takeovers: Relating Model Parameters to Trust, Situation Awareness, and Fatigue.

Our objectives were to assess the efficacy of active inference models for capturing driver takeovers from automated vehicles and to evaluate the links between model parameters and self-reported cognitive fatigue, trust, and situation awareness. Control transitions between human drivers and automation pose a substantial safety and performance risk. Models of driver behavior that predict these transitions from data are a critical tool for designing safer, human-centered, systems but current models do not sufficiently account for human factors. Active inference theory is a promising approach to integrate human factors because of its grounding in cognition and translation to a quantitative modeling framework. We used data from a driving simulation to develop an active inference model of takeover performance. After validating the model's predictions, we used Bayesian regression with a spike and slab prior to assess substantial correlations between model parameters and self-reported trust, situation awareness, fatigue, and demographic factors. The model accurately captured driving takeover times. The regression results showed that increases in cognitive fatigue were associated with increased uncertainty about the need to takeover, attributable to mapping observations to environmental states. Higher situation awareness was correlated with a more precise understanding of the environment and state transitions. Higher trust was associated with increased variance in environmental conditions associated with environmental states. The results align with prior theory on trust and active inference and provide a critical connection between complex driver states and interpretable model parameters. The active inference framework can be used in the testing and validation of automated vehicle technology to calibrate design parameters to ensure safety.

Test and simulation of high temperature resistant polyamide composite with single lap single bolt connection

The advancement of next-generation aerospace vehicles has presented new requirements and challenges for ensuring the structural integrity of aircraft components in extreme environments. Consequently, the utilization of high temperature resistant polyamide composite materials has become pivotal in the manufacturing of aerospace vehicle parts that operate under high temperatures (250 °C). As a critical connection technology for these materials, the mechanical behavior of bolted connection structures under high temperatures requires further investigation. In this paper, a combination of experimental and numerical simulation is used to investigate the load carrying capacity and failure mechanism of T700/BMP316 composite bolted joints at room temperature and 250 °C. The experimental results show that the ultimate load carrying capacity of the structure at 250 °C is only 13.1 % lower than that of the room temperature environment, indicating that the temperature softening effect of such composites is not significant. Scanning electron microscope (SEM) and computed tomography (CT) results indicate that the structural damage modes were the crushing of the hole edge fibers and matrix due to the extrusion by the bolts, as well as the interlaminar delamination damage. Temperature effects were taken into account for the composite principal structure and finite element modeling was performed using a combination of Pinho criterion and Cohesive model. Numerical simulations allow accurate prediction of the load-displacement response and damage pattern throughout the damage evolution phase. The high temperature test results and the developed finite element model involved in this study can support the design of new-generation aerospace vehicles.

Global health at local level: characterization of tropical diseases in northern Portugal, 2020-2024

Abstract Background The escalating global prevalence and geographic spread of tropical diseases pose significant global health risks worldwide, with local implications. In Portugal, these diseases require mandatory notification. Concerns were raised following the detection of Aedes albopictus mosquitoes in mainland Portugal in 2017, alongside a Dengue outbreak in Madeira in 2012. Despite Portugal being declared malaria-free, the detection of Anopheles mosquitoes also raises concerns. This study aims at characterizing notified cases of tropical diseases in two cities in Northern Portugal since 2020. Methods A retrospective study of Malaria, Dengue, Zika, and Chikungunya cases in the Maia & Valongo’s Public Health Unit included data from the National Epidemiological Surveillance System covering January 2020 to April 2024. Descriptive analysis was conducted using SPSS IBM for iOS® v29. Results are presented as mean ± standard deviation for continuous variables and proportions for categorical ones. Results Five malaria cases were reported, predominantly affecting males (80%), with an average age of 34±16.96 years. Four were Portuguese and one Angolan. All cases were imported, mostly from Angola (80%). Etiological analysis revealed two cases of Plasmodium malariae and three of Plasmodium falciparum. All were hospitalized, no deaths. Four dengue cases were documented, 50% in males, averaged 33±24.73 years. Three were Portuguese and one Mozambican. One was hospitalized with no deaths. All cases were imported from Brazil, Cuba, Indonesia, and islands of Saint Martin/Saint-Barthélemy. No Zika or Chikungunya confirmed cases were identified during this period. Conclusions The increasing incidence of Dengue and Malaria underscores the critical connection between infectious diseases, vector ecology, and global health security. This study highlights the risk of imported Dengue and Malaria cases, emphasizing the imperative for surveillance and preventive actions to protect public health. Key messages • Dengue and Malaria cases in Portugal underline the importance of international collaboration and robust strategies. • Stepped-up surveillance is key to protecting vulnerable groups from imported infections.

Sub‐assemblage testing and fragility analysis of connections of continuous‐plasterboard suspended ceiling systems

AbstractPast earthquake reconnaissance reports highlighted extensive seismic damages to suspended ceiling components and connections, including instances of complete ceiling failures. The seismic qualification of these nonstructural elements typically requires comprehensive evaluation through full‐scale shake table testing. However, such experimental evaluation is ordinarily not possible for every change made in various components and connections of ceiling systems due to the cost and effort involved. A feasible alternative is to obtain the behavior of components and connections from sub‐assemblage testing and incorporate them in appropriate numerical ceiling models to derive mechanical responses for developing alternative or new installation schemes. This paper considers critical connections of three continuous‐plasterboard suspended ceiling systems that were evaluated using shake table‐generated motions. The connections were classified according to their attachment to typical floors and walls of building structures, and sub‐assemblage testing was conducted using both monotonic and cyclic displacement loading. The observed failure modes in each connection were detailed, and appropriate damage states were assigned as the basis for constructing connection fragility curves. The results of the sub‐assemblage testing were presented in terms of the hysteresis responses, envelope curves, nonlinear backbone curves, and cumulative energy dissipation curves. Additionally, multilinear models of the connections were derived by approximating nonlinear backbone curves’ initial‐ and post‐yield behaviors. These multilinear models were further idealized to derive three equivalent linearized models for simplified yet reasonably accurate results for linear structural analyses. Finally, fragility curves were derived for all connections, considering their cyclic displacement failure capacities.

Mapping individual cortico-basal ganglia-thalamo-cortical circuits integrating structural and functional connectome: implications for upper limb motor impairment poststroke.

This study investigated alterations in functional connectivity (FC) within cortico-basal ganglia-thalamo-cortical (CBTC) circuits and identified critical connections influencing poststroke motor recovery, offering insights into optimizing brain modulation strategies to address the limitations of traditional single-target stimulation. We delineated individual-specific parallel loops of CBTC through probabilistic tracking and voxel connectivity profiles-based segmentation and calculated FC values in poststroke patients and healthy controls, comparing with conventional atlas-based FC calculation. Support vector machine (SVM) analysis distinguished poststroke patients from controls. Connectome-based predictive modeling (CPM) used FC values within CBTC circuits to predict upper limb motor function. Poststroke patients exhibited decreased ipsilesional connectivity within the individual-specific CBTC circuits. SVM analysis achieved 82.8% accuracy, 76.6% sensitivity, and 89.1% specificity using individual-specific parallel loops. Additionally, CPM featuring positive connections/all connections significantly predicted Fugl-Meyer assessment of upper extremity scores. There were no significant differences in the group comparisons of conventional atlas-based FC values, and the FC values resulted in SVM accuracy of 75.0%, sensitivity of 67.2%, and specificity of 82.8%, with no significant CPM capability. Individual-specific parallel loops show superior predictive power for assessing upper limb motor function in poststroke patients. Precise mapping of the disease-related circuits is essential for understanding poststroke brain reorganization.

Link Aggregation for Skip Connection–Mamba: Remote Sensing Image Segmentation Network Based on Link Aggregation Mamba

The semantic segmentation of satellite and UAV remote sensing imagery is pivotal for address exploration, change detection, quantitative analysis and urban planning. Recent advancements have seen an influx of segmentation networks utilizing convolutional neural networks and transformers. However, the intricate geographical features and varied land cover boundary interferences in remote sensing imagery still challenge conventional segmentation networks’ spatial representation and long-range dependency capabilities. This paper introduces a novel U-Net-like network for UAV image segmentation. We developed a link aggregation Mamba at the critical skip connection stage of UNetFormer. This approach maps and aggregates multi-scale features from different stages into a unified linear dimension through four Mamba branches containing state-space models (SSMs), ultimately decoupling and fusing these features to restore the contextual relationships in the mask. Moreover, the Mix-Mamba module is incorporated, leveraging a parallel self-attention mechanism with SSMs to merge the advantages of a global receptive field and reduce modeling complexity. This module facilitates nonlinear modeling across different channels and spaces through multipath activation, catering to international and local long-range dependencies. Evaluations on public remote sensing datasets like LovaDA, UAVid and Vaihingen underscore the state-of-the-art performance of our approach.

Integration of livelihood support with MHPSS in rehabilitation of torture survivors in LMICs: Addressing poverty and mental health dynamics.

The integration of livelihood support with mental health and psycho-social support (MHPSS) seems crucial for the rehabilitation of torture survivors in low- and middle-income countries (LMICs). This study aimed to explore the intersec-tionality of poverty and mental health, and the integration of livelihood support with-in MHPSS frameworks related to the rehabilitation of torture survivors in LMICs. A cross-sectional study was conducted using a semi-structured questionnaire distributed to members of the International Rehabilitation Council for Torture Victims (IRCT) in LMICs (n=25). The questionnaire explored the perception of IRCT centres in LMIC countries regard-ing the extent to which poverty contributes to poor mental health outcomes among torture sur-vivors and the effectiveness of integrating livelihood support into MHPSS interventions. The study highlighted the significant economic challenges faced by torture survivors, indicating a high prevalence of extreme poverty among this group. The study found that 92% of respondents believed that poverty and mental health outcomes of torture survivors are strongly linked. Eco-nomic and social inequalities were identified as key determinants of mental health, emphasizing the need to address these inequalities in rehabilitation programs for torture survivors. The study underscores the critical connection between poverty, mental health, and the experience of torture. In the view of most IRCT centres, the integration of livelihood support with MHPSS is essential for addressing economic disparities and promoting long-term resilience among survivors. The results highlight the need to conduct long-term longitudinal studies that provide support to this perception. The study recommends enhancing coordination among stakeholders, addressing cultural and social barriers, securing sustainable funding, and developing strategies to integrate livelihood support with MHPSS for torture survivors. According to participants, rehabilitation programmes should include economic empowerment, mental health support, and social integration, to contribute to a holistic recovery, long-term resilience, and overall well-being.

A graph network-based learnable simulator for spatial-temporal prediction of rigid projectile penetration

Predicting plate penetration by rigid projectiles (PPRP) is crucial in terminal ballistics, with broad applications in civil and military engineering. Empirical and analytical methods face challenges in predicting field variables like displacement and stress in target plates. Although numerical methods offer high accuracy, they suffer from low computational efficiency. Herein, we introduce an efficient data-driven machine learning (ML) method based on graph neural networks (GNNs), named PGN, specifically tailored to address the PPRP problem. Unlike traditional ML methods that establish direct input-output mappings, PGN predicts comprehensive spatial-temporal information pertaining to the projectile-target interaction process. A thorough analysis of PGN's performance in terms of accuracy, computational efficiency and generalization ability was performed. Compared to validated results of numerical simulations, PGN maintained high precision with RMSE for displacement, stress, and strain predictions below 0.5 %, 9.5 %, and 2.1 %, respectively. It also achieved R2 values exceeding 0.92 for the time history of projectile velocity and acceleration, while requiring only 9.8 % of the computation time compared to LS-DYNA. In generalization tests, PGN exhibited remarkable adaptability in tackling challenging scenarios that extend far beyond the training data distribution, with overall RMSE between 11 % and 13 %. Furthermore, we find that the maximum information propagation capacity of a simulated physical system must meet or exceed the information propagation need of the real-world physical phenomenon it aims to replicate. Consequently, an approach was proposed to determine the critical connectivity radius of the massage passing method directly from the wave speed in the target medium, which greatly improved the accuracy and efficiency of PGN.

Edwin Chadwick: A Pioneer of Public Health Reform and His Role in Sanitary Awakening.

Edwin Chadwick (1800-1890) was a central figure in the 19th-century public health reform movement in Britain. His work was instrumental in the sanitary awakening, a movement that revolutionized public health through the systematic improvement of urban sanitation and hygiene. As a lawyer by training, Chadwick was deeply influenced by Jeremy Bentham's welfare maximization theory, which emphasized the greatest good for the greatest number. His most significant contribution was his 1842 publication, "The Report on the Sanitary Condition of the Labouring Population," in which he documented the deplorable conditions faced by the working class and the link between poor sanitation and disease. Chadwick's advocacy led to the passage of the Public Health Act of 1848, which established local health boards and marked the beginning of modern public health systems. His focus on clean water, efficient sewage systems, and waste management not only reduced the spread of diseases like cholera and typhoid but also set the stage for future public health initiatives globally. The sanitary awakening, largely driven by Chadwick's efforts, highlighted the critical connection between environment and health, a principle that continues to underpin public health practices today. Chadwick's legacy lives on in the ongoing efforts to improve urban living conditions and prevent disease through public health infrastructure.

Effect of faying surface treatments and bolt tightened levels on fretting fatigue performance of slip critical connections with high strength bolts

The experimental investigation focuses on the fretting fatigue performance of M24 high-strength bolt slip critical connections (SCC) under shear load, taking into account the influence factors of faying surface treatments and bolt tightened levels. A novel extensometer supporting device for measuring micro-displacement between connection plates is proposed. The μ-N curves are obtained. Three-dimensional surface morphology scanning and fracture morphology analysis are conducted on the specimens. The results showed that the SCC contact area can be divided into stick, partial slip, and gross slip, with distribution ranges determined for each zone. Meanwhile the fretting fatigue life decreases with the increase of μ and pre-tension. Finally, a prediction of fretting fatigue life is made based on a multiaxial fatigue critical plane model.

Unveiling the Sleep-Immunity Nexus: Plant Bioresources for Ameliorating Consequences of Sleep Deprivation

Sleep is a fundamental physiological process that not only supports immune function but also contributes significantly to overall well-being. Because of the established decline in the average amount of sleep due to lifestyle and rise in shift work over the past few decades, exploring the relationship between sleep and immunity has become crucial. Moreover, infections trigger increased sleep as a result of the host's immunological response, particularly the release of proinflammatory cytokines, such as tumour necrosis factor and interleukin-1. Understanding the mechanisms governing the human immune response against different pathogens during sleep, as well as the neuroimmune interconnections, immune regulatory effects of sleep, and the impact of cytokines in sleep deprivation, is crucial. Traditional medicine has employed plant derived preparations for treating various sleep disorders and promoting better sleep. While some plant derived products have shown positive effects on sleep, it is essential to acknowledge the limited scientific research in this area, and altered individual responses to these. In conclusion, recognizing the critical connection between sleep and immunity underscores the importance of prioritizing sufficient and restorative sleep to bolster overall health and well-being. While certain products may offer potential benefits for better sleep, further scientific investigation is necessary to fully understand their effectiveness and applicability on an individual basis.

AaMYC3 bridges the regulation of glandular trichome density and artemisinin biosynthesis in Artemisia annua.

Artemisinin, the well-known natural product for treating malaria, is biosynthesised and stored in the glandular-secreting trichomes (GSTs) of Artemisia annua. While numerous efforts have clarified artemisinin metabolism and regulation, the molecular association between artemisinin biosynthesis and GST development remains elusive. Here, we identified AaMYC3, a bHLH transcription factor of A. annua, induced by jasmonic acid (JA), which simultaneously regulates GST density and artemisinin biosynthesis. Overexpressing AaMYC3 led to a substantial increase in GST density and artemisinin accumulation. Conversely, in the RNAi-AaMYC3 lines, both GST density and artemisinin content were markedly reduced. Through RNA-seq and analyses conducted both in vivo and in vitro, AaMYC3 not only directly activates AaHD1 transcription, initiating GST development, but also up-regulates the expression of artemisinin biosynthetic genes, including CYP71AV1 and ALDH1, thereby promoting artemisinin production. Furthermore, AaMYC3 acts as a co-activator, interacting with AabHLH1 and AabHLH113, to trigger the transcription of two crucial enzymes in the artemisinin biosynthesis pathway, ADS and DBR2, ultimately boosting yield. Our findings highlight a critical connection between GST initiation and artemisinin biosynthesis in A. annua, providing a new target for molecular design breeding of traditional Chinese medicine.

Revisiting One of the Oldest Orphanages, Asylums, and Indigenous Residential Boarding Schools: The Thomas Indian School at Seneca Nation.

For Indigenous populations, one of the most recognized acts of historical trauma has come from boarding schools. These institutions were established by federal and state governments to forcibly assimilate Indigenous children into foreign cultures through spiritual, physical, and sexual abuse and through the destruction of critical connections to land, family, and tribal community. This literature review focuses on the impact of one of the oldest orphanages, asylums, and Indigenous residential boarding schools in the United States. The paper shares perspectives on national and international parallels of residential schools, land, truth and reconciliation, social justice, and the reconnection of resiliency-based Indigenous Knowledge towards ancestral strength, reclamation, survivorship, and cultural continuance.

Feature attention graph neural network for estimating brain age and identifying important neural connections in mouse models of genetic risk for Alzheimer’s disease

Abstract Alzheimer’s disease (AD), a widely studied neurodegenerative disorder, poses significant research challenges due to its high prevalence and complex etiology. Age, a critical risk factor for AD, is typically assessed by comparing physiological and estimated brain ages. This study utilizes mouse models expressing human alleles of APOE and human nitric oxide synthase 2 (hNOS2), replicating genetic risks for AD alongside a human-like immune response. We developed a multivariate model that incorporates brain structural connectomes, APOE genotypes, demographic traits (age and sex), environmental factors such as diet, and behavioral data to estimate brain age. Our methodology employs a Feature Attention Graph Neural Network (FAGNN) to integrate these diverse datasets. Behavioral data are processed using a 2D convolutional neural network (CNN), demographic traits via a 1D CNN, and brain connectomes through a graph neural network equipped with a quadrant attention module that accentuates critical neural connections. The FAGNN model demonstrated a mean absolute error in age prediction of 31.85 days and a root mean squared error of 41.84 days, significantly outperforming simpler models. Our analysis further focused on the brain age delta, which assesses accelerated or delayed aging by comparing brain age, predicted by FAGNN, to the chronological age. A high-fat diet and the presence of the human NOS2 gene were identified as significant accelerators of brain aging in the old age group. Key neural connections identified by FAGNN, such as those between the cingulum, corpus callosum, striatum, hippocampus, thalamus, hypothalamus, cerebellum, and piriform cortex, were found to be significant in the aging process. Validation using diffusion MRI-based metrics, including fractional anisotropy and return-to-origin probability measures across these connections, revealed significant age-related differences. These findings suggest that white matter degradation in the connections highlighted by FAGNN plays a key role in aging. Our findings suggest that the complex interplay of APOE genotype with sex, immunity, and environmental factors modulates brain aging and enhance our understanding of AD risk in mouse models of aging.

FROM PRISON TO A MODEL OF BELARUSIAN SOCIETY

This analytical essay is a fragment of the research devoted to the analysis of the organization and way of life and social relations in modern Belarusian penitentiaries after August 2020. The study proposes to consider the world of the Belarusian prison as a social model, which the Belarusian authorities are actively unfolding in modern Belarus. This model manifests itself especially in the situation when a large number of political prisoners appear in prisons, which creates situations of confrontation between two worlds. The author consecutively examines several lines of tension in the lifestyles and actions of two colliding worlds: identity and self-image, critical thinking, minority (Unmündigkeit), community connections and relations, the private and the public. The conclusion gives a general characterization of this social model and examines the phenomenon of communal sociality as a basic element for the formation of this kind of systems in the modern world. The research is based on the reflection of the author’s personal experience.

SGT: Aging-related bug prediction via semantic feature learning based on graph-transformer

Software aging, characterized by an increasing failure rate or performance decline in long-running software systems, poses significant risks including financial losses and potential harm to human life. This is primarily attributed to the accumulation of runtime errors, commonly referred to as aging-related bugs (ARBs). ARBP aims to detect and address ARBs before software release, optimizing testing resource allocation. However, ARBP’s effectiveness relies heavily on dataset quality. Prior research often relied on manually designed metrics that lack semantic features, resulting in low prediction accuracy. Some studies construct models to learn semantic features from source code, but typically focus on token-level features from abstract Syntax Trees, neglecting critical topological and functional connections. In this paper, we introduce the SGT model, an ARBP method based on Graph-Transformer. This model efficiently extracts semantic information and logical structures from source code, capturing data dependencies and program dependencies. We also propose sub-graph sampling based on node degree to reduce structural complexity and apply random oversampling to address class imbalance. Experiments on three projects demonstrate notable improvements. For instance, SGT achieved F1 scores of 0.726 and 0.706 on Linux and MySQL, respectively. Compared to ALW, SGT shows a 12.3% and 6.8% improvement on Linux and MySQL.

A morphometric comparison of the ductus reuniens in humans and guinea pigs, with a note on its evolutionary importance.

The mammalian inner ear contains the sensory organs responsible for balance (semicircular canals, utricle, and saccule) and hearing (cochlea). While these organs are functionally distinct, there exists a critical structural connection between the two: the ductus reuniens (DR). Despite its functional importance, comparative descriptions of DR morphology are limited, hindering our understanding of the evolutionary diversification of hearing and balance systems among mammals. Using virtual 3D models derived from micro-CT, we examine the morphology of the DR and its relationship to the bony labyrinth in humans compared to that in a commonly used animal model, the guinea pig. Anatomical reconstructions and univariate measurements were carried out in the software 3D Slicer. Data indicate similarities in DR morphology between humans and guinea pigs in terms of overall shape. However, there are considerable differences in relative DR length and width between humans and guinea pigs. Humans possess a relatively shorter and narrower DR but with wider openings to the saccule and cochlear duct. This results in a relatively more constricted DR lumen in humans which may differentially limit fluid transfer between the saccule and cochlea. Our results reveal previously hidden morphological diversity in the communication between the hearing and balance systems of the mammalian inner ear which may indicate alternative strategies for isolating the Organ of Corti from the peripheral vestibular system throughout mammalian evolution.