Vascular risk factors can contribute to damage in the brain’s white matter, which contains nerve fibers that connect different brain regions. However, it is unclear how individual risk factors affect specific white matter pathways. This study examined the independent effects of four major vascular risk factors—high blood pressure, heart disease, diabetes, and body mass index (BMI)—using diffusion MRI data from 2,961 participants across five research cohorts. Researchers assessed microscopic changes in 48 white matter pathways using several measures of tissue structure and water movement. High blood pressure and heart disease showed the strongest and most widespread associations with poorer white matter health. Associations with diabetes became weaker in additional analyses, while findings for BMI varied depending on the measure examined. These results suggest that high blood pressure and heart disease may have particularly important relationships with white matter health, highlighting the potential value of managing these conditions to help preserve brain structure.

FIGURE 1

White matter tractography templates. Forty-eight white matter tractography templates were used in this study and can be grouped into TC (A), association (B), projection (C), and limbic tracts (D). IFG, inferior frontal gyrus; IFOF, inferior fronto-occipital fasciculus; ILF, inferior longitudinal fasciculus; IPL, inferior parietal lobe; M1, primary motor cortex; PMd, dorsal premotor cortex; PMv, ventral premotor; S1, primary somatosensory cortex; SLF, superior longitudinal fasciculus; SLF-TP, temporoparietal superior longitudinal fasciculus; SMA, supplementary motor area; SPL, superior parietal lobe; TC, transcallosal; UF, uncinate fasciculus.

]]> /valiant/2026/08/24/lower-cardiac-output-is-a-risk-factor-for-faster-cerebral-atrophy-over-a-11-year-follow-up-period-in-apoe-%ce%b54-carriers/ Mon, 24 Aug 2026 20:10:16 +0000 /valiant/?p=7404 Moore, Elizabeth E.; Zhang, Panpan; Khan, Omair A.; Liu, Dandan; Gupta, Deepak K.; Pechman, Kimberly R.; Gifford, Katherine A.; Landman, Bennett A.; Hohman, Timothy J.; Jefferson, Angela L. (2026). . Alzheimer’s & Dementia, 22(8), e71598.

Cardiac output, the amount of blood the heart pumps each minute, may be related to brain health as people age. This study examined whether lower cardiac output was associated with changes in brain structure over 11 years in middle-aged and older adults. Researchers also investigated whether this relationship differed in people who carry the APOE-ε4 genetic variant, which is associated with an increased risk of Alzheimer’s disease. Among APOE-ε4 carriers, lower cardiac output was associated with smaller brain volumes at the beginning of the study. Over time, lower cardiac output was also associated with greater enlargement of the inferior lateral ventricles, fluid-filled spaces in the brain whose enlargement can indicate loss of surrounding brain tissue. These associations were not observed in people without the APOE-ε4 variant. The findings suggest that subtle reductions in heart function may be associated with greater brain degeneration in APOE-ε4 carriers. However, the results should be interpreted cautiously and confirmed in future studies.

FIGURE 1

Inclusion and exclusion criteria. Missing data categories are mutually exclusive

]]> /valiant/2026/08/24/success-and-failure-with-the-antidyskinetic-effect-of-globus-pallidus-internus-deep-brain-stimulation-a-sweet-spot-and-connectivity-analysis-in-the-csp-468-cohort/ Mon, 24 Aug 2026 20:08:12 +0000 /valiant/?p=7401 D’Souza, Shawn; Shah, Harsh P.; Seshadri, Vikram; Toms, Jamie; D’Haese, Pierre; Dawant, Benoit M.; Li, Rui; Chen, Jeffrey; Opem, Careniena; Koch, Paul; Larson, Paul; Holloway, Kathryn L. (2026). . Neuromodulation.

Deep brain stimulation (DBS) of the globus pallidus internus (GPi), a brain region involved in movement control, can reduce dyskinesias—uncontrolled movements often caused by long-term levodopa treatment in Parkinson disease. However, outcomes can vary depending on where stimulation is delivered. This study analyzed 69 patients with Parkinson disease who received GPi-DBS to identify brain locations and connections associated with improvement or worsening of dyskinesias. Researchers mapped the location and estimated effects of stimulation and examined the structural and functional brain networks connected to these areas. They identified a “sweet spot” associated with greater improvement in the lower back portion of the GPi and just below it, as well as a separate region associated with less favorable outcomes. Nerve fibers passing beneath the GPi, near a pathway called the Ansa Lenticularis, were also linked to reduced dyskinesias. In contrast, stronger functional connections with movement-related regions, including the supplementary motor and premotor areas, were associated with worse outcomes. These findings were confirmed in a separate group of patients, suggesting that both the precise location of stimulation and its connections with wider brain networks may help predict and potentially improve dyskinesia outcomes after GPi-DBS.

Graphical Abstract

Genetic factors and family history can influence a person’s risk of coronary heart disease (CHD), but it is unclear how much they improve risk prediction across different racial and ethnic groups. This study examined two large and diverse U.S. cohorts: 19,348 participants from eMERGE and 239,645 from the All of Us Research Program. Researchers evaluated a polygenic risk score, which estimates genetic risk based on many common genetic variants, genetic variants linked to familial hypercholesterolemia (FH), an inherited condition causing very high cholesterol, and family history of CHD. The polygenic risk score and family history were independently associated with CHD, and their effects were additive and consistent among self-identified White, Black, and Latino participants. In eMERGE, adding these factors to a standard clinical risk calculator improved CHD prediction and reclassified 18.8% of participants at a commonly used 10-year risk threshold. This resulted in about four additional people with CHD being correctly identified per 1,000 people screened. Improvements were observed across all three racial and ethnic groups. These findings suggest that incorporating polygenic risk and family history into clinical risk assessments may improve the identification of people at increased risk of CHD across diverse populations.

Graphical Abstract

The brain and autonomic nervous system, which controls automatic functions such as heart rate, continuously communicate with each other. However, it is often unclear whether specific brain regions are responding to signals from the body or sending signals that influence the body. Using brain imaging and heart rate variability (HRV), a measure of changes in the time between heartbeats, this study examined brain–heart communication in younger and older adults during emotion regulation and rest. During emotion regulation, activity in the insula and cingulate cortex was associated with lower HRV. During rest, several brain regions, including the posterior insula, responded after decreases in HRV, suggesting that they receive information related to changes in the body. In contrast, activity in the anterior insula and cingulate cortex occurred before increases in HRV, suggesting a role in sending signals that influence heart activity. The results support a possible feedback loop in which decreased HRV activates brain regions that receive bodily signals, which then activate regions involved in regulating HRV. This pattern also differed with age, as the brain regions involved in receiving and sending signals were more distinct in younger adults but overlapped more in older adults. These findings provide insight into how the brain and heart coordinate and how this communication may change with aging.

Figure 1

Two types of RMSSD time series paired with whole-brain BOLD signals. Modeling individual BOLD time series at TR with RMSSD time series over two 10-second windows before and after TRs allows us to investigate bidirectional relationships between RMSSD and brain BOLD activity. By correlating at-TR BOLD signals with before-TR RMSSD while accounting for after-TR RMSSD, we can examine how changes in RMSSD influence changes in BOLD activity. Likewise, by correlating at-TR BOLD signals with after-TR RMSSD while accounting for before-TR RMSSD, we can investigate how changes in RMSSD are influenced by changes in BOLD activity.

]]> /valiant/2026/08/24/outcomes-of-72-hour-emergency-department-return-visits-requiring-hospital-admission-in-older-adults-a-nationally-representative-analysis/ Mon, 24 Aug 2026 19:55:37 +0000 /valiant/?p=7391 Steel, Peter A. D.; Hancock, David; Han, Jin H.; Madden, Eli; Stern, Michael; RoyChoudhury, Arindam; Wright, Adam; Ancker, Jessica S.; Zhang, Yiye; Rosen, Anthony. (2026). . BMC Geriatrics, 26(1), 991.

Deciding whether to admit or discharge older adults from the emergency department (ED) can be challenging because both options carry risks. This study examined return visit admissions, defined as hospitalizations within 72 hours after an older adult was initially treated and discharged from the same ED. Researchers analyzed nationally representative U.S. data from 2007 to 2022 for adults aged 65 and older. Of an estimated 3.38 million hospital admissions, 6.1% were return visit admissions. In-hospital death occurred in 4.0% of these admissions compared with 2.3% of admissions during the initial ED visit. After accounting for patient characteristics, illness severity, and other health conditions, return visit admissions were associated with higher odds of in-hospital death. No significant differences were found in hospital stay length or new nursing home placement. The most common diagnoses among return visit admissions were infections, including sepsis, pneumonia, COVID-19, cellulitis, and urinary tract infection. These findings suggest that hospital admission shortly after ED discharge may signal a higher risk of death in older adults, particularly those with infections, although the study does not show that delayed admission causes worse outcomes.

Fig 1 – Cohort Selection Flow Diagram for Older Adult Emergency Department Admissions, NHAMCS 2007–2022

Dementia affects millions of people worldwide and is projected to triple by 2050, making early and accurate diagnosis important for treatment and quality of life. However, artificial intelligence models used to classify dementia from MRI scans may not perform equally well across racial and ethnic groups. This study examined differences in dementia classification among 6,584 Non-Hispanic White, 1,263 Non-Hispanic African American, and 713 Hispanic White individuals. The researchers found significant differences in model performance, particularly when a model trained using data from one group was applied to another. To reduce these differences, they evaluated RegAlign, a machine-learning approach that uses a small amount of data from underrepresented groups to help the model adapt while accounting for differences between groups and dementia categories. RegAlign substantially reduced performance gaps, especially between Non-Hispanic White and Hispanic populations. These findings highlight the importance of using diverse training data and fairness-focused machine-learning methods to improve the accuracy and consistency of MRI-based dementia classification across different racial and ethnic populations.

Fig. 1: Baseline performance on group-balanced subsets for assessing disparities across multi-racial and multi-ethnic populations.

Fused deposition modeling (FDM), a common form of 3D printing, offers a low-cost and accessible way to produce medical devices and tissue scaffolds directly at the point of care. However, reliable clinical use requires consistent printing under different environmental conditions. This study examined how temperature and humidity affect porous scaffolds made from polylactic acid (PLA), a widely used biocompatible material. Scaffolds were printed at temperatures ranging from 25–40 °C and relative humidity levels of 30–70%, then evaluated for pore structure, water-holding capacity, mechanical strength, and compatibility with cells. Temperature and humidity had little effect on the overall shape and visible pore structure of the printed scaffolds. However, higher printing temperatures increased scaffold stiffness and were associated with increased reactive oxygen species (ROS), molecules that can indicate cellular stress. Changes in humidity had little effect on mechanical properties but influenced cell survival and ROS production. Overall, moderate temperatures of 25–35 °C and low-to-moderate humidity of 30–50% provided the best balance between mechanical stability and biological compatibility. These findings may help improve the consistency and reliability of FDM-printed medical scaffolds for affordable point-of-care applications.

Fig 1 – Advantages, applications, and manufacturing techniques of porous scaffolds (image regenerated using BioRender).

]]> /valiant/2026/08/24/a-comparative-evaluation-of-multiple-enlarged-perivascular-space-segmentation-tools/ Mon, 24 Aug 2026 19:28:42 +0000 /valiant/?p=7380 LeFevre, James D.; Robb, W. Hudson; Liu, Dandan; Jackson, T. Bryan; Pechman, Kimberly R.; Shashikumar, Niranjana; Vyas, Yukti; Landman, Bennett A.; Davis, L. Taylor; Hohman, Timothy J.; Jefferson, Angela L. (2026). . Magnetic Resonance Imaging, 134, 110749.

Enlarged perivascular spaces (ePVS) are fluid-filled spaces around small blood vessels in the brain that can become more visible with aging and small vessel disease and may reflect reduced clearance of waste from the brain. Measuring ePVS manually on MRI scans is time-consuming and impractical for large studies. To address this, researchers developed DORES, a deep learning tool that automatically identifies and measures ePVS using two types of brain MRI images. The model was developed using data from the ĚŔÍ·Ěő Memory and Aging Project and evaluated against expert manual measurements and three other automated tools. DORES showed good performance in identifying ePVS in both white matter and the basal ganglia, a group of structures deep within the brain, and its estimates of ePVS number and volume agreed well with expert measurements. Testing on an independent Alzheimer’s disease imaging dataset showed somewhat lower performance, as was also observed with the other automated methods. Results also varied depending on the type of MRI scanner used, suggesting that scanner differences can affect measurement consistency. Overall, DORES provides a promising automated approach for measuring ePVS in older adults, although scanner-related differences should be considered when applying the method across multiple research sites.

Fig. 1. Representative White Matter ePVS Segmentations of DORES Performance in VMAP.

T₁-weighted axial scans were selected to illustrate DORES performance at the 25th (top row; Dice = 0.55), 50th (middle row; Dice = 0.63), and 75th (bottom row; Dice = 0.73) percentiles of white matter regional Dice scores. The first column displays the raw, skull-stripped images in the white matter. The second column displays the corresponding segmentation overlays. Manual segmentations are shown in blue, whereas DORES predictions are shown in red. Voxels where manual and DORES segmentations overlap appear purple. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

]]> /valiant/2026/08/24/heavy-ion-induced-single-event-effects-in-6-5-kv-and-10-kv-sic-power-mosfets-and-correlation-to-the-selc-and-seb-depletion-capacitance-energy-models/ Mon, 24 Aug 2026 19:26:16 +0000 /valiant/?p=7377 Islam, S.; Sengupta, A.; Ball, D. R.; Osheroff, J. M.; Sternberg, A. L.; Galloway, K. F.; Witulski, A. F.; Kosier, S. L.; Schrimpf, R. D. (2026). . IEEE Transactions on Nuclear Science.

This study tests a model designed to predict when silicon carbide (SiC) power devices will experience single event burnout (SEB), a sudden and permanent failure caused by energetic particles such as heavy ions. The critical depletion energy model predicts the voltage at which SEB occurs based mainly on the doping level of the device’s semiconductor layer, rather than other design features such as layer thickness. Researchers tested the model using 6.5 and 10 kV SiC metal-oxide-semiconductor field-effect transistors (MOSFETs), extending experiments to higher voltages than previously studied. The devices were exposed to several types of heavy ions with different energy-deposition characteristics, and voltage ranges associated with increased leakage current and permanent failure were identified. Results from ions with high energy deposition agreed with the model’s predictions. Overall, the findings extend experimental support for the critical depletion energy model from previously tested voltages of up to 4.5 kV to devices rated as high as 10 kV.

Fig. 1. 

SEB voltage versus epi doping for experimental SiC power MOSFETs, extended up to 10 kV using the critical energy model from [28]. All data points correspond to high-LET Pr ions.