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2025
AbstractBackgroundMagnetic resonance imaging (MRI) offers excellent soft tissue contrast essential for diagnosis and treatment, but its long acquisition times can cause patient discomfort and motion artifacts.PurposeTo propose a self‐supervised deep learning‐based compressed sensing MRI method named “Self‐Supervised Adversarial Diffusion for MRI Accelerated Reconstruction (SSAD‐MRI)” to accelerate data acquisition without requiring fully sampled datasets.Materials and MethodsWe used the fastMRI multi‐coil brain axial ‐weighted (‐w) dataset from 1376 cases and single‐coil brain quantitative magnetization prepared 2 rapid acquisition gradient echoes maps from 318 cases to train and test our model. Robustness against domain shift was evaluated using two out‐of‐distribution (OOD) datasets: multi‐coil brain axial postcontrast ‐weighted () dataset from 50 cases and axial T1‐weighted (T1‐w) dataset from 50 patients. Data were retrospectively subsampled at acceleration rates . SSAD‐MRI partitions a random sampling pattern into two disjoint sets, ensuring data consistency during training. We compared our method with ReconFormer Transformer and SS‐MRI, assessing performance using normalized mean squared error (NMSE), peak signal‐to‐noise ratio (PSNR), and structural similarity index (SSIM). Statistical tests included one‐way analysis of variance and multi‐comparison Tukey's honesty significant difference (HSD) tests.ResultsSSAD‐MRI preserved fine structures and brain abnormalities visually better than comparative methods at for both multi‐coil and single‐coil datasets. It achieved the lowest NMSE at , and the highest PSNR and SSIM values at all acceleration rates for the multi‐coil dataset. Similar trends were observed for the single‐coil dataset, though SSIM values were comparable to ReconFormer at . These results were further confirmed by the voxel‐wise correlation scatter plots. OOD results showed significant (p ) improvements in undersampled image quality after reconstruction.ConclusionsSSAD‐MRI successfully reconstructs fully sampled images without utilizing them in the training step, potentially reducing imaging costs and enhancing image quality crucial for diagnosis and treatment.- Book : ()
- Pub. Date : 2025
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2025
As the forefront of inland extension on the Indian plate, the northeastern Tibetan Plateau, marked by low strain rates and high stress levels, is one of the regions with the highest seismic risk. Analyzing seismicity through statistical methods holds significant scientific value for understanding tectonic conditions and assessing earthquake risk. However, seismic monitoring capacity in this region remains limited, and earthquake frequency is low, complicating efforts to improve earthquake catalogs through enhanced identification and localization techniques. Bi-scale empirical probability integral transformation (BEPIT), a statistical method, can address these data gaps by supplementing missing events shortly after moderate to large earthquakes, resulting in a more reliable statistical data set. In this study, we analyzed six earthquake sequences with magnitudes of MS ≥ 6.0 that occurred in northeastern Tibet since 2009, following the upgrade of the regional seismic network. Using BEPIT, we supplemented short-term missing aftershocks in these sequences, creating a more complete earthquake catalog. ETAS model parameters and b values for these sequences were then estimated using maximum likelihood methods to analyze parameter variability across sequences. The findings indicate that the b value is low, reflecting relatively high regional stress. The background seismicity rate is very low, with most mainshocks in these sequences being background events rather than foreshock-driven events. The p-parameter of the ETAS model is high, indicating that aftershocks decay relatively quickly, while the α-parameter is also elevated, suggesting that aftershocks are predominantly induced by the mainshock. These conditions suggest that earthquake prediction in this region is challenging through seismicity analysis alone, and alternative approaches integrating non-seismic data, such as electromagnetic and fluid monitoring, may offer more viable solutions. This study provides valuable insights into earthquake forecasting in the northeastern Tibetan Plateau.- Book : 27(2)
- Pub. Date : 2025
- Page : pp.174-174
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2025
- Book : ()
- Pub. Date : 2025
- Page : pp.1-19
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2025
This article examines the growing influence of Chinese investments in Latin America, focusing on Venezuela and Argentina. It explores how these countries benefit from Chinese capital and how this investment impacts their economies. Venezuela has relied on oil-backed loans to sustain its political system, worsening its economic challenges. In contrast, Argentina has channeled Chinese investment into infrastructure, including hydroelectric dams, nuclear plants, railway modernization, and energy diversification projects. The study highlights that while infrastructure investment can enhance economic stability and reduce reliance on further loans, both countries remain vulnerable due to their dependence on raw material exports. Despite these challenges, the study underscores that with institutional improvements and a shift toward diversification, such investments can contribute to sustainable growth in both nations. A qualitative research approach using secondary sources was employed to analyze the long-term implications of Chinese investments in these two economies.
- Book : 13(1)
- Pub. Date : 2025
- Page : pp.43-54
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2025
Abstract
We consider the nuclear absorption of dark matter as an alternative to the typical
indirect detection search channels of dark matter decay or annihilation. In this scenario, an
atomic nucleus transitions to an excited state by absorbing a pseudoscalar dark matter particle
and promptly emits a photon as it transitions back to its ground state. The nuclear excitation of
carbon and oxygen in the Galactic Center would produce a discrete photon spectrum in the
𝒪(10) MeV range that could be detected by gamma-ray telescopes. Using the
BIGSTICK large-scale shell-model code, we calculate the excitation energies of carbon and
oxygen. We constrain the dark matter-nucleus coupling for current COMPTEL data, and provide
projections for future experiments AMEGO-X, e-ASTROGAM, and GRAMS for dark matter masses from
∼ 10 to 30 MeV. We find the excitation process to be very sensitive to the dark matter mass
and find that the future experiments considered would improve constraints on the dark
matter-nucleus coupling within an order of magnitude.- Book : 2025(02)
- Pub. Date : 2025
- Page : pp.017-017
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2025
- Book : 1012()
- Pub. Date : 2025
- Page : pp.116821-116821
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2025
Abstract
Extrapolating the observed behavior of helium exhaust in current tokamaks towards future reactors requires the understanding of the underlying physical mechanisms determining helium transport, recycling and pumping. Helium compression is the main physics-based figure of merit characterizing how efficiently helium is transported towards the divertor and recycled at the target plates. Moreover, helium gas transport in the subdivertor region towards the pumps is strongly influenced by vessel geometry and installed pumps.
The SOLPS-ITER code package is used to model H-mode He-seeded deuterium plasmas at the ASDEX Upgrade tokamak, and compared to recent experiments. The simulations generally indicate a poor recycling of helium in the divertor, compared to that of deuterium, in qualitative agreement with the experiment. This is mainly determined by a deeper edge transport barrier and a weaker parallel SOL transport of He ions, with respect to D ions, and by the higher first ionization energy of He atoms, which results in a deeper penetration of recycled atoms into the plasma. The simulated He compression is, however, much smaller than the experimentally measured one, despite the introduction of additional, non-default physics components into the code. Helium gas transport in the subdivertor region towards the pumps is conductance-limited, but moderately enhanced by the entrainment of He atoms into the stronger, viscous deuterium gas flow via friction.
The observed poor helium recycling poses challenges in view of the requirements of helium exhaust in future reactors. Our results emphasize the need to investigate further strategies to optimize helium pumping, to guarantee an efficient removal of helium ash in future burning plasmas. Additionally, the observed difficulty of SOLPS-ITER in reproducing the experimental observations suggests a careful evaluation of the currently available extrapolations of impurity transport towards future devices obtained via edge transport modelling.- Book : ()
- Pub. Date : 2025
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2025
Abstract
Rhenium (186Re) Obisbemeda (186RNL), chelated-186Re encapsulated in nanoliposomes and delivered to brain tumors via convection enhanced delivery (CED), was evaluated in a Phase 1 dose escalation trial (NCT01906385). The primary objective was to determine the maximum tolerated dose (MTD). Secondary objectives included safety and tolerability, dose distribution, the overall response rate (ORR), disease-specific progression-free survival (PFS), and overall survival (OS). 21 patients received up to 22.3 mCi 186RNL over 6 dosing cohorts. Most adverse events (AEs) were unrelated to 186RNL and the MTD was not reached. Although not predefined outcomes, the mOS and mPFS were 11 and 4 months, respectively, and found to correlate with radiation absorbed dose to the tumor and percent tumor treated. When dichotomized by absorbed dose of 100 Gy, the mOS and mPFS were 17 months and 6 months, respectively, for >100 Gy, compared to 6 (mOS) and 2 (mPFS) months, respectively, for <100 Gy. For ORR, 57.1% exhibited stable disease (SD), 4.8% partial response, and 38.1% progressive disease. Overall, patients received radiation absorbed doses without significant toxicity higher than possible with external beam radiation therapy (EBRT) and demonstrated mOS beyond standard of care for recurrent glioblastoma (~8 months).- Book : 16(1)
- Pub. Date : 2025
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2025
- Book : 20(1)
- Pub. Date : 2025
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2025
Glial-origin brain tumors, particularly glioblastomas (GBMs), are known for their devastating prognosis and are characterized by rapid progression and fatal outcomes. Despite advances in surgical resection, complete removal of the tumor remains unattainable, with residual cells driving recurrence that is resistant to conventional therapies. The GBM tumor microenviroment (TME) significantly impacts tumor progression and treatment response. In this review, we explore the emerging role of purinergic signaling, especially the P2X7 receptor (P2X7R). Due to its unique characteristics, it plays a key role in tumor progression and offers a potential therapeutic strategy for GBM through TME modulation. We discuss also the emerging role of the P2X4 receptor (P2X4R) as a promising therapeutic target. Overall, targeting purinergic signaling offers a potential approach to overcoming current GBM treatment limitations.- Book : 18(3)
- Pub. Date : 2025
- Page : pp.385-385
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