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Abstract We present joint South Pole Telescope and XMM-Newton observations of eight massive galaxy clusters (0.8–2 × 10¹⁵M_⊙) spanning a redshift range of 0.16–0.35. Employing a novel Sunyaev–Zel’dovich + X-ray fitting technique, we effectively constrain the thermodynamic properties of these clusters out to the virial radius. The resulting best-fit electron density, deprojected temperature, and deprojected pressure profiles are in good agreement with previous observations of massive clusters. For the majority of the cluster sample (five out of eight clusters), the entropy profiles exhibit a self-similar behavior near the virial radius. We further derive hydrostatic mass, gas mass, and gas fraction profiles for all clusters up to the virial radius. Comparing the enclosed gas fraction profiles with the universal gas fraction profile, we obtain nonthermal pressure fraction profiles for our cluster sample at  >0.5R₅₀₀, demonstrating a steeper increase betweenR₅₀₀andR₂₀₀that is consistent with the hydrodynamical simulations. Our analysis yields nonthermal pressure fraction ranges of 8%–28% (median: 15% ± 11%) atR₅₀₀and 21%–35% (median: 27% ± 12%) atR₂₀₀. Notably, weak-lensing mass measurements are available for only four clusters in our sample, and our recovered total cluster masses, after accounting for nonthermal pressure, are consistent with these measurements. 

Abstract The metallicity of galaxies, and its variation with galactocentric radius, provides key insights into the formation histories of galaxies and the physical processes driving their evolution. In this work, we analyze the radial metallicity gradients of star-forming galaxies in the EAGLE, Illustris, IllustrisTNG, and SIMBA cosmological simulations across broad mass (10^8.0M_⊙≤M_⋆ ≲ 10^12.0M_⊙) and redshift (0 ≤z≤ 8) ranges. We find that all simulations predict strong negative (i.e., radially decreasing) metallicity gradients at early cosmic times, likely due to their similar treatments of relatively smooth stellar feedback not providing sufficient mixing to quickly flatten gradients. The strongest redshift evolution occurs in galaxies with stellar masses of 10^10.0–10^11.0M_⊙, while galaxies with stellar mass < 10¹⁰M_⊙and >10¹¹M_⊙exhibit weaker redshift evolution. Our result of negative gradients at high redshift contrast with the many positive and flat gradients in the 1 < z < 4 observational literature. Atz > 6, the negative gradients observed with JWST and the Atacama Large Millimeter/submillimeter Array are flatter than those in simulations, albeit with closer agreement than at lower redshift. Overall, we suggest that these smooth stellar feedback galaxy simulations may not sufficiently mix their metal content radially, and that either stronger stellar feedback or additional subgrid turbulent metal diffusion models may be required to better reproduce observed metallicity gradients. 

Abstract We report the detection of the [Oiii] auroral line in 42 galaxies within the redshift range of 3 <z< 10. These galaxies were selected from publicly available JWST data releases, including the JADES and PRIMAL surveys, and observed using both the low-resolution PRISM/CLEAR configuration and medium-resolution gratings. The measured electron temperatures in the high-ionization regions of these galaxies range fromT_e([Oiii]) = 12,000 to 24,000 K, consistent with temperatures observed in local metal-poor galaxies and previous JWST studies. In 10 galaxies, we also detect the [Oii] auroral line, allowing us to determine electron temperatures in the low-ionization regions, which range betweenT_e([Oii]) = 10,830 and 20,000 K. The directT_e-based metallicities of our sample span from 12 + log(O/H) = 7.2 to 8.4, indicating these high-redshift galaxies are relatively metal-poor. By combining our sample with 25 galaxies from the literature, we expand the data set to a total of 67 galaxies within 3 <z< 10, effectively more than doubling the previous sample size for directT_e-based metallicity studies. This larger data set allows us to derive empirical metallicity calibration relations based exclusively on high-redshift galaxies, using six key line ratios: R3, R2, R23, Ne3O2, O32, and O3N2. Notably, we derive a novel metallicity calibration relation for the first time using high-redshiftT_e-based metallicities: $\hat{R}$= 0.18log R2 + 0.98log R3. This new calibration significantly reduces the scatter in high-redshift galaxies compared to the $\hat{R}$relation previously calibrated for low-redshift galaxies. 

We describe the 2023 release of the spectral synthesis code Cloudy. Since the previous major release, migrations of our online services motivated us to adopt git as our version control system. This change alone led us to adopt an annual release scheme, accompanied by a short release paper, the present being the inaugural. Significant changes to our atomic and molecular data have improved the accuracy of Cloudy predictions: we have upgraded our instance of the Chianti database from version 7 to 10; our H- and He-like collisional rates to improved theoretical values; our molecular data to the most recent LAMDA database, and several chemical reaction rates to their most recent UDfA and KiDA values. Finally, we describe our progress on upgrading Cloudy's capabilities to meet the requirements of the X-ray microcalorimeters aboard the upcoming XRISM and Athena missions, and outline future developments that will make Cloudy of use to the X-ray community. 

Abstract In this paper, we discuss atomic processes modifying the soft X-ray spectra from optical depth effects like photoelectric absorption and electron scattering suppressing the soft X-ray lines. We also show the enhancement in soft X-ray line intensities in a photoionized environment via continuum pumping. We quantify the suppression/enhancement by introducing a “line modification factor ( f mod ).” If 0 ≤ f mod ≤ 1, the line is suppressed, which could be the case in both collisionally ionized and photoionized systems. If f mod ≥ 1, the line is enhanced, which occurs in photoionized systems. Hybrid astrophysical sources are also very common, where the environment is partly photoionized and partly collisionally ionized. Such a system is V1223 Sgr, an Intermediate Polar binary. We show the application of our theory by fitting the first-order Chandra Medium Energy Grating (MEG) spectrum of V1223 Sgr with a combination of Cloudy -simulated additive cooling-flow and photoionized models. In particular, we account for the excess flux for O vii , O viii , Ne ix , Ne x , and Mg xi lines in the spectrum found in a recent study, which could not be explained with an absorbed cooling-flow model. 

Abstract We present a velocity-resolved reverberation mapping analysis of the hypervariable quasar RM160 (SDSS J141041.25+531849.0) atz= 0.359 with 153 spectroscopic epochs of data representing a 10 yr baseline (2013–2023). We split the baseline into two regimes based on the 3× flux increase in the light curve: a “low state” phase during the years 2013–2019 and a “high state” phase during the years 2022–2023. The velocity-resolved lag profiles (VRLPs) indicate that gas with different kinematics dominates the line emission in different states. The HβVRLP begins with a signature of inflow onto the broad-line region (BLR) in the low state, while in the high state it is flatter with less signature of inflow. The HαVRLP begins consistent with a virialized BLR in the low state, while in the high state shows a signature of inflow. The differences in the kinematics between the Balmer lines and between the low state and the high state suggests complex BLR dynamics. We find that the BLR radius and velocity (both FWHM andσ) do not obey a constant virial product throughout the monitoring period. We find that the BLR lags and continuum luminosity are correlated, consistent with rapid response of the BLR gas to the illuminating continuum. The BLR kinematic profile changes in unpredictable ways that are not related to continuum changes and reverberation lag. Our observations indicate that nonvirial kinematics can significantly contribute to observed line profiles, suggesting caution for black hole mass estimation in luminous and highly varying quasars like RM160. 

The epithelial-mesenchymal transition (EMT) plays a critical role in cancer progression, being responsible in many cases for the onset of the metastatic cascade and being integral in the ability of cells to resist drug treatment. Most studies of EMT focus on its induction via chemical signals such as TGF-β or Notch ligands, but it has become increasingly clear that biomechanical features of the microenvironment such as extracellular matrix (ECM) stiffness can be equally important. Here, we introduce a coupled feedback loop connecting stiffness to the EMT transcription factor ZEB1, which acts via increasing the secretion of LOXL2 that leads to increased cross-linking of collagen fibers in the ECM. This increased cross-linking can effectively increase ECM stiffness and increase ZEB1 levels, thus setting a positive feedback loop between ZEB1 and ECM stiffness. To investigate the impact of this non-cell-autonomous effect, we introduce a computational approach capable of connecting LOXL2 concentration to increased stiffness and thereby to higher ZEB1 levels. Our results indicate that this positive feedback loop, once activated, can effectively lock the cells in a mesenchymal state. The spatial-temporal heterogeneity of the LOXL2 concentration and thus the mechanical stiffness also has direct implications for migrating cells that attempt to escape the primary tumor. 

Epithelial-mesenchymal plasticity (EMP) underlies embryonic development, wound healing, and cancer metastasis and fibrosis. Cancer cells exhibiting EMP often have more aggressive behavior, characterized by drug resistance, and tumor-initiating and immuno-evasive traits. Thus, the EMP status of cancer cells can be a critical indicator of patient prognosis. Here, we compare three distinct transcriptomic-based metrics—each derived using a different gene list and algorithm—that quantify the EMP spectrum. Our results for over 80 cancer-related RNA-seq datasets reveal a high degree of concordance among these metrics in quantifying the extent of EMP. Moreover, each metric, despite being trained on cancer expression profiles, recapitulates the expected changes in EMP scores for non-cancer contexts such as lung fibrosis and cellular reprogramming into induced pluripotent stem cells. Thus, we offer a scoring platform to quantify the extent of EMP in vitro and in vivo for diverse biological applications including cancer.