Using Diffusion MRI to Relate Hippocampal Subfield Microstructure to Delayed Verbal Memory in Cognitively Intact Individuals at Genetic Risk for Developing Alzheimer\u27s Disease

Intervention to delay the onset of Alzheimer\u27s disease (AD) is an important treatment strategy but detecting at-risk individuals before significant disease progression remains challenging. This study evaluates the relationship between hippocampal microstructure and verbal cognition in cognitively intact older adults, focusing on the differences between APOΕ ε4 allele carriers and noncarriers. Participants (n = 41 noncarriers, 33 carriers) over 60 years old (mean ± SD: carriers 71 ± 6.6; noncarriers 71 ± 6.4 years) underwent diffusion-weighted magnetic resonance imaging (dMRI) and volumetric assessments. We assessed hippocampal structure, including microstructure, using Neurite Orientation Dispersion and Density Imaging (NODDI), diffusion tensor imaging (DTI), and volumetric measures. Regression analyses examined the relationship between these hippocampal measures and verbal and visuospatial cognition, as evaluated by the Rey delayed recall tests, i.e., the Auditory Verbal Learning Test (AVLT) and Complex Figure Test (CFT), respectively. Results indicated that while volumetric data showed no significant findings, microstructural measures, particularly orientation dispersion (ODI) in the left subiculum, were positively associated with verbal recall in APOΕ ε4 carriers (p = 0.0011; Bonferroni-corrected alpha = 0.005). These findings suggest that hippocampal microstructure, rather than volume, may provide insights into cognitive decline in individuals at genetic risk for AD

Changes in Land, Ocean, Atmospheric Parameters Associated with the 2025 Myanmar (Mw 7.7) Earthquake

Multiple parameters associated with the land, atmosphere, and ocean were analyzed to study short-term and immediate pre-earthquake changes associated with the 28 March 2025 Myanmar earthquake (Mw 7.7). Anomalous clear-sky outgoing longwave radiation (ClrOLR) and trace gases (CH₄, CO, and O₃) were detected within two months prior to the mainshock. Vertical changes at different pressure levels suggest a possible underground source. High-temporal-resolution observations of the infrared brightness temperature and surface air pressure revealed short-lived fluctuations shortly before the earthquake, which may reflect localized stress adjustments and surface latent heat flux release during the final stage of earthquake preparation. In the oceanic region along the seismogenic fault, vertical variations at depths in chlorophyll-a concentration, sea potential temperature, and salinity indicate possible near-coseismic responses. Furthermore, a comprehensive analysis of sea surface chlorophyll-a, suspended particulate matter, sea surface temperature, precipitation, wind speed, and buoy data was conducted to improve the understanding of earthquake-related changes in oceanic parameters. Our findings reveal notable multigeosphere phenomena associated with major earthquakes and highlight the necessity of further integrated observations to deepen our understanding of strong coupling among Earth systems

Segmentation and Morphometry of Intracranial Internal Carotid Artery Calcification in Relation to Brain Atrophy

Purpose Intracranial internal carotid artery calcification (iICAC) is a form of intracranial arteriosclerosis and is associated with an elevated risk of stroke and dementia. However, iICAC’s relationship with brain atrophy remains poorly understood. We aimed to automatically quantify iICAC morphometric characteristics and evaluate their associations with regional brain volumes (BVs). Methods We developed an automated approach to compute iICAC surface area and thickness from CT brain scans in a sample of physically active South American subsistence farmers (n = 1,232, age range: 40 years to 92 years, 48.1% female, 794 Tsimane and 438 Moseten). Linear regression models were used to assess associations between two iICAC features and regional BVs, adjusted for age, sex, population, and total intracranial volume. Results Significant negative relationships were found between regional BVs and iICAC surface area, but not iICAC thickness. Frontal, parietal, temporal, and subcortical BVs exhibited significant negative associations with iICAC surface area (standardized range: -0.146 to -0.066, p ≤ 0.013), while the occipital BV did not (standardized = -0.035, p = 0.249; = 0.007, p = 0.810). Subcortical BVs demonstrated the strongest negative associations with iICAC surface area (standardized = -0.146, p \u3c 0.001; = -0.139, p \u3c  0.001). Conclusion iICAC surface area—assumed to reflect arterial stiffness—shows a stronger relationship with regional BV loss than iICAC thickness—assumed to indicate arterial stenosis. The findings suggest that brain regions primarily supplied by the anterior circulation are more vulnerable to iICAC-related atrophy. Subcortical BVs showed the strongest negative associations with iICAC surface area, with region-specific analyses identifying significant effects in the putamen, thalamus, hippocampus, amygdala, pallidum, and ventral diencephalon, suggesting heightened vulnerability of deep gray-matter structures to iICAC-related atrophy

Deep Learning Style Transfer for Enhanced Smoke Plume Visibility: A Standardized False Color Composite (SFCC) in GEMS Satellite Imagery

Wildfire smoke visualization using geostationary satellite imagery is essential for real-time monitoring and atmospheric analysis; however, inconsistencies in color tone across Geostationary Environment Monitoring Spectrometer (GEMS) images hinder reliable interpretation and model training. This study proposes a Standardized False Color Composite (SFCC) framework based on deep learning style transfer to enhance the visual consistency and interpretability of wildfire smoke scenes. Four tone-standardization methods were compared: the statistical Empirical Cumulative Distribution Function (ECDF) correction and three neural approaches—ReHistoGAN, StyTr2, and Style Injection Diffusion Model (SI-DM). Each model was evaluated visually and quantitatively using six metrics (SSIM, LPIPS, FID, histogram similarity, ArtFID, and LSCI) and validated on three major wildfire events in Korea (2022–2025). Among the tested models, SI-DM achieved the most balanced performance, preserving structural features while ensuring consistent color-tone alignment (ArtFID = 1.620; LSCI mean = 0.894). Qualitative assessments further confirmed that SI-DM effectively delineated smoke boundaries and maintained natural background tones under complex atmospheric conditions. Additional analysis using GEMS UVAI, VISAI, and CHOCHO demonstrated that the styled composites partially reflect the optical and chemical characteristics distinguishing wildfire smoke from dust aerosols. The proposed SFCC framework establishes a foundation for visually standardized satellite smoke imagery and provides potential for future aerosol-type classification and automated detection applications

Dual-task Effects on Spatiotemporal, Kinematic, and Kinetic Parameters and Their Variability During Running

Background Running in real-world environments often requires using cognitive resources simultaneously with the motor task (dual tasking, DT). Limited existing evidence suggests that DT reduces running speed. Movement variability is essential for a healthy, adaptable motor system. DT has been shown to affect movement variability during walking. Nonetheless, it remains unclear how DT affects spatiotemporal, kinematic, and kinetic parameters and their variability during running. Research question Does DT affect spatiotemporal, kinematic, and kinetic measures and their variability during running? Does running speed influence DT effects? Methods Thirty-one asymptomatic runners participated in this cross-sectional study. Three-dimensional running biomechanics were recorded while participants ran on a treadmill at three speeds (prefer, slow, and fast) with and without performing easy and hard cognitive tasks. Mean and variability of cadence and step length, as well as peak joint angles and moments in the sagittal, frontal, and transverse planes associated with running injuries, were exported for analysis. Results There were significant DT effects on peak knee adduction and pelvis ipsilateral drop angles. Findings also indicated significant DT effects on stride-to-stride variability of peak hip flexion, extension, and adduction, knee flexion and adduction, ankle plantar flexion, and pelvis ipsilateral drop angles, as well as peak knee abductor and ankle plantar flexor moments. Pairwise comparison revealed that runners exhibited lower variability when simultaneously performing a hard cognitive task than running alone. No significant task-by-speed interaction effect was observed, indicating DT effects were not affected by running speeds. Significance Runners demonstrated lower stride-to-stride variability in joint kinematics and kinetics during DT running. This suggests that runners may be less adaptable and thus more susceptible to running injuries under DT conditions. Future evaluation and intervention programs for runners may consider integrating DT condition, which is commonly missing in current practices

Structural Basis for the Subtype-Selectivity of K\u3csub\u3eCa\u3c/sub\u3e2.2 Channel Activators

Small-conductance (KCa2.2) and intermediate-conductance (KCa3.1) Ca2+-activated K+ channels are gated by a Ca2+-calmodulin dependent mechanism. NS309 potentiates the activity of both KCa2.2 and KCa3.1, while rimtuzalcap selectively activates KCa2.2. Rimtuzalcap has been used in clinical trials for the treatment of spinocerebellar ataxia and essential tremor. We report cryo-electron microscopy structures of NS309-bound KCa2.2 and KCa3.1, in addition to structures of rimtuzalcap-bound KCa2.2 and mutant KCa3.1_R355K. The different conformations of calmodulin and the cytoplasmic HC helices in the two channels underlie the subtype-selectivity of rimtuzalcap for KCa2.2. NS309 binds to pre-existing pockets in both channels, while the bulkier rimtuzalcap binds in an induced-fit pocket in KCa2.2 requiring conformational changes. In KCa2.2, calmodulin’s N-lobes are sufficiently far apart to enable conformational changes to accommodate either NS309 or rimtuzalcap. In KCa3.1, calmodulin’s N-lobes are closer to each other and constrained by KCa3.1’s HC helices, which allows binding of NS309 but not rimtuzalcap. Replacement of arginine-355 in KCa3.1’s HB helix with lysine (KCa3.1_R355K) allows the binding of rimtuzalcap and renders the mutant channel sensitive to rimtuzalcap. These structures provide a framework for structure-based drug design targeting KCa2.2 channels

Avoiding Unintended Consequences: Science of Reading Policies May Harm Deaf Children

Many U.S. policies inspired by the Science of Reading rest on two assumptions: (1) skilled reading always involves automatic mapping between written words and speech sounds, and (2) all children benefit from systematic instruction of phonological awareness and phonics. These assumptions are not wholly accurate, that they do not consider scientific evidence from deaf readers, and that policies based on these assumptions may be harmful to deaf children. First, skilled reading does not always rely on phonology. Evidence shows that deaf readers can read effectively without using spoken language phonology and that phonological processing can be unrelated to reading skill in this group. Second, a fundamental issue in deaf education is prioritizing speech and hearing over language development, academics, cognition, and socio-emotional well-being. This unhealthy imbalance persists despite the mounting evidence that we cannot ensure deaf children acquire spoken language. Policies mandating speech-based reading instruction for all children overlook how deaf readers develop literacy, and reinforce the overemphasis on speech, which creates the conditions for language deprivation. We caution against a one-size-fits-all approach to reading instruction and emphasize the need for differentiated instruction that respects the diverse ways beginning readers, including deaf learners, acquire literacy

2025 2nd Place Winner: Robin Gomes, Connor Bogenreif, and Mir Aminy, “The Role of Repertoire Selection and Teacher Collaboration in Culturally Responsive Music Education”

(From left to right) Pictured are Assistant Dean for Library AI Literacy and Instructional Services, Taylor Greene; 2025 Graduate Research Prize Second Place Winners, Connor Bogenreif, Mir Aminy, and Robin Gomes; and the prize’s benefactor, Eric M. Scandrett.https://digitalcommons.chapman.edu/graduate_research_prize_photos/1006/thumbnail.jp

Multi-modal Tensor Fusion for Alzheimer’s Disease Recognition

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual imagery, demographics, and longitudinal time-series data, to enhance AD recognition. Our approach leverages tensor representations to model intricate cross-modal interactions while preserving structural dependencies within each modality. Experimental results on publicly available AD datasets demonstrate that the proposed method outperforms the accuracy of the state-of-the-art deep learning classification. This work highlights the potential of tensor-based multimodal learning to advance precision medicine for neurodegenerative diseases