Search

The mass ($M_\mathrm{BH}$) of a supermassive black hole (SMBH) can be measured using spatially-resolved kinematics of the region where the SMBH dominates gravitationally. The most reliable measurements are those that resolve the smallest physical scales around the SMBHs. We consider here three metrics to compare the physical scales probed by kinematic tracers dominated by rotation: the radius of the innermost detected kinematic tracer $R_\mathrm{min}$ normalised by respectively the SMBH's Schwarzschild radius ($R_\mathrm{Schw}\equiv 2GM_\mathrm{BH}/c^2$, where $G$ is the gravitational constant and $c$ the speed of light), sphere-of-influence (SOI) radius ($R_\mathrm{SOI}\equiv GM_\mathrm{BH}/\sigma_\mathrm{e}^2$, where $\sigma_\mathrm{e}$ is the stellar velocity dispersion within the galaxy's effective radius) and equality radius [the radius $R_\mathrm{eq}$ at which the SMBH mass equals the enclosed stellar mass, $M_\mathrm{BH}=M_*(R_\mathrm{eq})$, where $M_*(R)$ is the stellar mass enclosed within the radius $R$]. All metrics lead to analogous simple relations between $R_\mathrm{min}$ and the highest circular velocity probed $V_\mathrm{c}$. Adopting these metrics to compare the SMBH mass measurements using molecular gas kinematics to those using megamaser kinematics, we demonstrate that the best molecular gas measurements resolve material that is physically closer to the SMBHs in terms of $R_\mathrm{Schw}$ but is slightly farther in terms of $R_\mathrm{SOI}$ and $R_\mathrm{eq}$. However, molecular gas observations of nearby galaxies using the most extended configurations of the Atacama Large Millimeter/sub-millimeter Array can resolve the SOI comparably well and thus enable SMBH mass measurements as precise as the best megamaser measurements., Comment: 13 pages, 9 figures. Accepted by MNRAS

Breast cancer invasion into adipose tissue strongly influences disease progression and metastasis. The degree of cancer cell invasion into adipose tissue depends on numerous biochemical and physical properties of cancer cells, adipocytes, and other key components of adipose tissue. We model breast cancer invasion into adipose tissue as a physical process by carrying out simulations of active, cohesive spherical particles (cancer cells) invading into confluent packings of deformable polyhedra (adipocytes). We quantify the degree of invasion by calculating the interfacial area $A_t$ between cancer cells and adipocytes. We determine the long-time value of $A_t$ versus the activity and strength of the cohesion between cancer cells, as well as mechanical properties of the adipocytes and extracellular matrix (ECM) in which the adipocytes are embedded. We show that the degree of invasion collapses onto a master curve by plotting it versus a dimensionless energy scale $E_c$, which grows linearly with mean-square fluctuations and persistence time of the cancer cell velocities, is inversely proportional to the pressure of the system, and has an offset that increases with the cancer cell cohesive energy. The condition, $E_c \gg 1$, indicates that cancer cells will invade the adipose tissue, whereas for $E_c \ll 1$, the cancer cells and adipocytes remain demixed. We also show that constraints on adipocyte positions by the ECM decrease $A_t$ relative to that obtained for unconstrained adipocytes. Finally, spatial heterogeneity in structural and mechanical properties of the adipocytes in the presence of ECM impedes invasion relative to adipose tissue with uniform properties.

Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix where each element represents the average contact probability or number of contacts between two chromatin loci. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in Hi-C maps within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that KerTAD consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states., Comment: 23 pages, 10 figures

The ATLAS and CMS collaborations have recently presented results of searches for compressed electroweakinos in final states including soft leptons. These searches are sensitive to mass splittings ranging from quite small values of about 5 GeV to O(10) GeV, which are endemic to scenarios with wino-like and higgsino-like lightest supersymmetric particles (LSPs). While all experimental results exhibit apparently compatible mild excesses, these soft-lepton analyses, taken together with disappearing-track searches targeting much smaller splittings, notably leave unconstrained a sizeable region of parameter space with modest splittings of 1-5 GeV. We point out that this gap can be closed, for scenarios with a higgsino-like LSP, by monojet searches. On the other hand, we find at the same time that current monojet searches show excesses in a region partially overlapping that favoured by the soft-lepton analyses. We provide an up-to-date map of these results and show, among others, a best-fit point with an excess greater than $2\sigma$ that is consistent with a higgsino-like LSP mass around 177 GeV. We finally comment on how such a point can be realised in the MSSM., Comment: 7 pages, 2 figures. Updated to resemble Phys. Lett. B Version of Record