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2025
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2025
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2025
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2025
The abundance and blue color of the super-early (redshift z>10) luminous galaxies discovered by the James Webb Space Telescope (JWST) can be explained if radiation-driven outflows have ejected their dust on kiloparsec-scales. To test this hypothesis, we predict the Atacama Large Millimeter Array (ALMA) detectability of this extended dust component. Based on the observed properties of the galaxy, its observed continuum flux at 88 μm, F_88, depends on the dust-to-stellar mass ratio, ξ_d, and on the extent of the dust distribution, r_d. When this is applied to the most distant known galaxy, GS-z14-0 at z=14.32, the fiducial model (ξ_d = 1/529) predicts F_ fid = 14.9, μJy and a dust extent r_d=1.4 kpc. If the galaxy is very dust rich (ξ_d =1/40) max = 40.1, μJy. These values are lower fid = 9.5, μJy) if the dust is predominantly made of large grains such as those that form in supernova ejecta. Forthcoming ALMA observations might come very close to constraining the fiducial predictions of the outflow-based attenuation-free model. Other super-early galaxies are predicted to be fainter at 88 μm, mostly because their star formation rate is lower than that of GS-z14-0, with fiducial fluxes in the range $2-5.2 μ$Jy.- Book : ()
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2025
Disrupted nuclear shape is associated with multiple pathological processes including premature aging disorders, cancer-relevant chromosomal rearrangements, and DNA damage. Nuclear blebs (i.e., herniations of the nuclear envelope) have been induced by (1) nuclear compression, (2) nuclear migration (e.g., cancer metastasis), (3) actin contraction, (4) lamin mutation or depletion, and (5) heterochromatin enzyme inhibition. Recent work has shown that chromatin transformation is a hallmark of bleb formation, but the transformation of higher-order structures in blebs is not well understood. As higher-order chromatin has been shown to assemble into nanoscopic packing domains, we investigated if (1) packing domain organization is altered within nuclear blebs and (2) if alteration in packing domain structure contributed to bleb formation. Using Dual-Partial Wave Spectroscopic microscopy, we show that chromatin packing domains within blebs are transformed both by B-type lamin depletion and the inhibition of heterochromatin enzymes compared to the nuclear body. Pairing these results with single-molecule localization microscopy of constitutive heterochromatin, we show fragmentation of nanoscopic heterochromatin domains within bleb domains. Overall, these findings indicate that chromatin within blebs is associated with a fragmented higher-order chromatin structure.- Book : ()
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2025
Sea fog significantly impacts marine activities, ecosystems, and radiation balance. We analyzed the decadal variation characteristics of sea fog frequency (SFF) over the northwestern Pacific and investigated the roles of the Pacific decadal oscillation (PDO) and sea surface temperature (SST) warming in driving these changes. The results show that SFF experienced a significant and sudden decadal increase around 1978 (up by 12.9%) and a prominent decadal decrease around 1999 (down by 7.8%). The sudden increase in SFF around 1978 was closely related to the PDO. A positive PDO phase induced unusual anticyclonic circulation and southerly winds over the northwestern Pacific, enhancing low-level atmospheric stability and moisture supply, thus facilitating sea fog formation. Nevertheless, the decrease in SFF around 1999 was related to SST warming in the north Pacific. The rise in sea temperatures weakened the SST front south of the foggy region, reducing the cooling and condensation of warm air necessary for sea fog formation. This study enhances the understanding of the decadal variability mechanism of SFF over the northwestern Pacific regulated by large-scale circulation systems and provides a reference for future sea fog forecasting work.- Book : 16(2)
- Pub. Date : 2025
- Page : pp.130-130
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2025
AbstractCytoplasmic TDP43 mislocalization and aggregation are pathological hallmarks of amyotrophic lateral sclerosis (ALS). However, the initial cellular insults that lead to TDP43 mislocalization remain unclear. In this study, we demonstrate that Nemo-like kinase (NLK)—a proline-directed serine/threonine kinase—promotes the mislocalization of TDP43 and other RNA-binding proteins by disrupting nuclear import. NLK levels are selectively elevated in neurons exhibiting TDP43 mislocalization in ALS patient tissues, while genetic reduction ofNLKreduces toxicity in human neuron models of ALS. Our findings suggest that NLK is a promising therapeutic target for neurodegenerative diseases.- Book : ()
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2025
- Book : 111(2)
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2025
The increasing importance of waste materials utilization with the necessary modification to remove various pollutants from industrial wastewater has been a research focus over the past few decades. Using waste material from one industry to solve pollution problems in another ultimately leads toward sustainable and circular approaches in environmental engineering, solving waste management and wastewater treatment issues simultaneously. In contemporary research and industry, there is a notable trend toward utilizing industrial wastes as precursors for adsorbent formation with a wide application range. In line with this trend, red mud, a byproduct generated during alumina production, is increasingly viewed as a material with the potential for beneficial reuse rather than strictly a waste. One of the potential uses of red mud, due to its specific composition, is in the removal of heavy metal and radionuclide ions. This study summarizes red mud’s potential as an adsorbent for wastewater treatment, emphasizing techno-economic analysis and sorption capacities. An overview of the existing research includes a critical evaluation of the adsorption performance, factors influencing efficiency rather than efficacy, and the potential for specific pollutant adsorption from aqueous solutions. This review provides a new approach to a circular economy implementation in wastewater treatment while guiding future research directions for sustainable and cost-effective solutions.- Book : 13(2)
- Pub. Date : 2025
- Page : pp.107-107
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2025
Abstract
A new glass system with the composition 60B2O3 + 30PbF2 + (10−x)K2O + x Er2O3 (x = 0 to 3 mol%) were synthesized using the melt-quenching technique and comprehensively analyzed to evaluate their structural, optical, mechanical, and radiation shielding properties. Increasing Er2O3 concentration enhanced the density (from 4.260 to 4.89 g/cm3) and reduced the molar volume (from 29.28 to 28.98 cm3/mol), indicating a denser and more compact glass matrix. Optical studies revealed increased UV absorbance, a red shift in the cutoff wavelength, and a reduction in the optical energy gap from 3.487 to 3.335 eV (direct transitions). Urbach energy values increased from 0.722 to 1.083 eV, signifying heightened structural disorder. Enhanced refractive index and extinction coefficients further underscored the glasses’ potential for optical applications. Mechanical analyses demonstrated a significant increase in all elastic moduli, including Young’s, bulk, and shear moduli, with Er2O3 incorporation, indicating improved rigidity and mechanical stability. The radiation shielding performance of the glasses was assessed across photon energies of 0.015–15 MeV, incorporating both experimental data and machine learning (ML)-based predictions of mass attenuation coefficients (MAC). The ML model, developed using a neural network architecture, successfully predicted MAC values with high accuracy, demonstrating excellent agreement with XCOM-calculated results. Key shielding parameters, including half-value layer (HVL), effective atomic number (Zeff), and buildup factors (EABF and EBF), improved significantly with higher Er2O3 content. BPKE3 glass, with the highest Er2O3 concentration, exhibited the best shielding efficiency, outperforming conventional shielding materials in terms of lower HVL and buildup factors, coupled with higher MAC and Zeff values. This study highlights the dual role of Er2O3-doped lead borate glasses as efficient optical and radiation shielding materials. Machine learning effectively predicts shielding parameters, aiding material optimization for applications in nuclear, medical, and industrial fields.- Book : ()
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