Kang, Daehun

Introduction: Understanding mid-term test-retest reliability and within-subject variability is important for interpreting changes observed in longitudinal and intervention studies. The reliability of resting-state functional magnetic resonance imaging (rs-fMRI) is known to vary across measures and brain regions. However, how reliability differs across functional networks and connectivity- and amplitude-based measures, and whether multi-echo acquisition and processing modify these patterns, remain incompletely characterized. Methods: Twenty-two healthy volunteers underwent two rs-fMRI sessions 15.7 ± 4.0 days apart on a Compact 3T scanner. Multi-echo, middle-echo, and independently acquired single-echo datasets were compared, with multi-echo independent component analysis additionally evaluated as a denoising approach. Functional connectivity (FC) and three amplitude-based measures were evaluated using the Schaefer 400 parcellation. Reliability was systematically assessed using intraclass correlation coefficient (ICC), within-subject standard deviation (wSD), and systematic bias at edge or regional, and network levels. Results: Acquisition-dependent differences in reliability were generally modest. Multi-echo acquisition and processing increased functional connectivity strength and the magnitude of amplitude-based measures and improved inferior cortical coverage, but these enhancements did not consistently translate into substantially higher ICC or lower wSD. In contrast, reliability showed clear network-dependent differences. FC reliability varied markedly across network pairs and was not explained by connectivity strength alone; pairs involving the default mode and control networks generally showed more favorable profiles than several somatomotor and visual network pairs. Fractional amplitude of low-frequency fluctuations (fALFF) also showed network-dependent reliability, with the most favorable regional reproducibility observed in the default mode and control networks and lower reproducibility in the somatomotor and visual networks. Conclusion: These findings provide practical mid-term reliability benchmarks for rs-fMRI on a Compact 3T scanner and show that measurement stability varies more clearly across measures and functional networks than across acquisition approaches.

Abstract White matter bundles play a crucial role in cognitive functions by rapidly transmitting information between brain regions. Inter-areal conduction guides the integration of information and conduction velocity is a fundamental parameter in theories and models of brain function. However, distributions of conduction velocity remain difficult to characterize in vivo in humans. In this work, we integrated diffusion magnetic resonance imaging (dMRI) tractography with intracranial electrical stimulation during clinical stereo-electroencephalography (sEEG) monitoring in 17 subjects to measure conduction velocity within four major white matter bundles. Our findings reveal that human brain conduction is characterized by high variability both within and between bundles, reflecting a predominance of slow connections alongside rare high-speed connections. Because conduction velocity in myelinated fibers follows an approximately linear relationship with axon diameter, we derive underlying axon diameter distributions and show that these estimates are comparable to previous post-mortem studies. These findings demonstrate a heavily skewed distribution of human neural conduction velocities and show that structural heterogeneity shapes the timing and integration of information in large-scale networks.

Abstract Hypoxia constrains cerebral oxygen availability and challenges brain function and stability. Although hypoxia-responsive functional connectivity (HR-FC) reorganizes rapidly with declining arterial oxygen partial pressure, its relationship to local neurovascular activity remains unclear. We examined time-resolved amplitude of low-frequency fluctuations (ALFF) in blood-oxygenation-level dependent (BOLD) fMRI during graded acute hypoxia in healthy adults, performing a continuous cognitive test (Go/No-go task) with concurrent physiological monitoring. Dynamic ALFF and functional connectivity were estimated using a sliding-window approach and analyzed across large-scale brain networks defined by Schaefer’s 17-network parcellation. Severe hypoxia elicited temporally dissociated responses across modalities. Functional connectivity increased monotonically, whereas ALFF exhibited pronounced nonlinear modulation, including phase-dependent divergence across networks. During hypoxic decompensation, the default mode network (DefaultA) showed marked ALFF suppression, whereas a ventral secondary somatosensory-dominant network (SomMotB) exhibited preferential preservation despite similar engagement in HR-FC. Together, these findings indicate that network-level ALFF captures a distinct yet complementary layer of functional dynamics, with a temporal profile distinct from functional connectivity. Spontaneous BOLD dynamics during acute hypoxia reflect structured network-level modulation rather than a uniform suppression attributable solely to reduced oxygen availability. These findings support a conceptual framework of cerebral oxygen budgeting , in which metabolic constraints reshape functional dynamics across brain networks.

Women with type 2 diabetes (T2D) have a higher risk of being diagnosed with breast cancer and have worse survival than non-diabetic women if they do develop breast cancer. However, more research is needed to elucidate the biological underpinnings of these relationships. Here, we found that forkhead box A1 (FOXA1), a forkhead family transcription factor, and metformin (1,1-dimethylbiguanide hydrochloride), a medication used to treat T2D, may impact hormone-receptor-positive (HR+) breast cancer (BC) tumor cell growth and metastasis. Indeed, fourteen diabetes-associated genes are highly expressed in only three HR+ breast cancer cell lines but not the other subtypes utilizing a 53,805 gene database obtained from NCBI GEO. Among the diabetes-related genes, FOXA1, MTA3, PAK4, FGFR3, and KIF22 were highly expressed in HR+ breast cancer from 4032 breast cancer patient tissue samples using the Breast Cancer Gene Expression Omnibus. Notably, elevated FOXA1 expression correlated with poorer overall survival in patients with estrogen-receptor-positive/progesterone-receptor-positive (ER+/PR+) breast cancer. Furthermore, experiments demonstrated that loss of the FOXA1 gene inhibited tumor proliferation and invasion in vitro using MCF-7 and T47D HR+ breast cancer cell lines. Metformin, an anti-diabetic medication, significantly suppressed tumor cell growth in MCF-7 cells. Additionally, either metformin treatment or FOXA1 gene deletion enhanced tamoxifen-induced tumor growth inhibition in HR+ breast cancer cell lines within an ex vivo three-dimensional (3D) organoid model. Therefore, the diabetes-related medicine metformin and FOXA1 gene inhibition might be a new treatment for patients with HR+ breast cancer when combined with tamoxifen, an endocrine therapy.

AbstractBackgroundThe cardiac and respiratory cycles have been suggested as major drivers of cerebrospinal fluid(CSF) flow. The glymphatic system, one of the mechanisms for the clearance of amyloid‐beta and tau proteins, relies heavily on the movement(flow) of the CSF, and thus, investigating the forces that modulate the CSF flow is essential for understanding the glymphatic flux. Because breathing is trainable through exercise and self‐directed methods, various breathing methods may enhance the CSF flow.MethodReal‐time phase‐contrast MRI(pc‐MRI) was used to measure the CSF flow at the foramen magnum on a 3T. Fast resting‐state fMRI(rsfMRI;TR400ms) was conducted on a compact 3T. Under an IRB‐approved protocol, participants were instructed to breathe slowly and deeply, and subsequently switch to their spontaneous breathing. For rsfMRI data preprocessing, we performed motion correction, skull stripping, spatial smoothing(4mm), temporal filtering(0.01 to 0.1Hz), and linear and quadratic temporal trends removal. fMRI time courses were then normalized to Z‐score at each voxel before being averaged. On the pcMRI, the phase was summed in a CSF region‐of‐interest and plotted vs time. Additionally, we confirmed for possible confounding effects such as head motion or motion‐induced susceptibility changes.ResultrsfMRI findings showed that deep breathing promoted large oscillations in the CSF flow in the ventricles, while spontaneous breathing did not(Figure 1). Additionally, deep breathing resulted in large oscillations in lobar cortical regions. Similar results were observed in the pcMRI, with larger CSF velocity through the foramen magnum during the deep breathing compared to the spontaneous breathing(Figure 2A‐B). The cumulative summation result showed that the volume of CSF flow was increased during deep breathing(Figure 2C).ConclusionThis study provides new evidence that slow and deep breathing promotes CSF flow and global brain BOLD signal, which may be useful in promoting circulation in the brain. The study’s findings also open new avenues for research in the field of neurovascular coupling and mechanisms associated with glymphatic clearance. As hampered CSF flow and/or worsen glymphatic clearance have been shown to associate with pathological aging and dementia, including Alzheimer’s disease and Parkinson’s disease, future research is needed explore the potential of breathing training methods as a non‐pharmacological intervention to support brain health.

In blood-oxygen-level-dependent (BOLD)-based resting-state functional (RS-fMRI) studies, usage of multi-echo echo-planar-imaging (ME-EPI) is limited due to unacceptable late echo times when high spatial resolution is used. Equipped with high-performance gradients, the compact 3T MRI system (C3T) enables a three-echo whole-brain ME-EPI protocol with smaller than 2.5 mm isotropic voxel and shorter than 1 s repetition time, as required in landmark fMRI studies. The performance of the ME-EPI was comprehensively evaluated with signal variance reduction and region-of-interest-, seed- and independent-component-analysis-based functional connectivity analyses and compared with a counterpart of single-echo EPI with the shortest TR possible. Through the multi-echo combination, the thermal noise level is reduced. Functional connectivity, as well as signal intensity, are recovered in the medial orbital sulcus and anterior transverse collateral sulcus in ME-EPI. It is demonstrated that ME-EPI provides superior sensitivity and accuracy for detecting functional connectivity and/or brain networks in comparison with single-echo EPI. In conclusion, the high-performance gradient enabled high-spatial-temporal resolution ME-EPI would be the method of choice for RS-fMRI study on the C3T.

PurposeTo demonstrate the feasibility of pseudo‐continuous arterial‐spin–labeled (pCASL) imaging with 3D fast‐spin‐echo stack‐of‐spirals on a compact 3T scanner (C3T), to perform trajectory correction for eddy‐current–induced deviations in the spiral readout of pCASL imaging, and to assess the correction effect on perfusion‐related images with high‐performance gradients (80 mT/m, 700T/m/s) of the C3T.MethodsTo track eddy‐current–induced artifacts with Archimedean spiral readout, the spiral readout in pCASL imaging was performed with 5 different peak gradient slew rate (Smax) values ranging from 70 to 500 T/m/s. The trajectory for each Smax was measured using a dynamic field camera and applied in a density‐compensated gridding image reconstruction in addition to the nominal trajectory. The effect of the trajectory correction was assessed with perfusion‐weighted (ΔM) images and proton‐density–weighted images as well as cerebral blood flow (CBF) maps, obtained from 10 healthy volunteers.ResultsBlurring artifact on ΔM images was mitigated by the trajectory correction. CBF values on the left and right calcarine cortices showed no significant difference after correction. Also, the signal‐to‐noise ratio of ΔM images improved, on average, by 7.6% after correction (P < .001). The greatest improvement of 12.1% on ΔM images was achieved with a spiral readout using Smax of 300~400 T/m/s.ConclusionEddy currents can cause spiral trajectory deviation, which leads to deformation of the CBF map even in cases of low value Smax. The trajectory correction for spiral‐readout–based pCASL produces more reliable results for perfusion imaging. These results suggest that pCASL is feasible on C3T with high‐performance gradients.