Search

Despite the need for and relevance of leadership skills to the success of medical trainees and healthcare professionals, few medical schools offer formal leadership training during the preclinical years. Where such curricula exist, we have found few schools that intentionally incorporate key principles of lifestyle medicine critical to short- and long-term career development. We describe a novel relationship-centered leadership curriculum, grounded in a conceptual framework of emotional intelligence and incorporating key principles of lifestyle medicine, first piloted in 2019 and now in its fourth year of existence. In comparing pre- and post-course self-evaluations on a 5-point Likert scale, students (n = 19) reported increased competencies in Self (3.12 vs 4.20, P < .001), Teams (3.06 vs 4.00, P < .001), and System (2.55 vs 3.55, P < .001) domains. Qualitative responses demonstrated that a vital strength of the course was its direct relevance and immediate applicability to students’ personal and professional roles and goals. Results provide encouraging support for using a relationship-centered leadership framework that incorporates core elements of lifestyle medicine and emotional intelligence to facilitate medical students’ leadership development, as related to leading oneself and in dynamic relationships with others (e.g., with leaders, colleagues, patients, and within communities, teams, and systems).

Supplemental Figure 1: RT-PCR assay for miR-30a expression in transfected cells by either miR-30a mimic (A) or miR-30a inhibitor (B) and theirand its corresponding controls.

Supplemental Figure 3. Effect of LOX inhibition on metastasis in vivo. Treatment of mice before and after tail vein injection with 8505c cells reduced metastasis in vivo. BAPN treatment was initiated either 24 hours before (upper panel, four mice) or after (lower panel, four mice) tail vein injection. On the left are representative tumor luminescence images of untreated and BAPN-treated mice. B, Representative images of cellular migration and invasion in ATC cell lines transfected with siLOX.

Legends for supplemental figures

Supplemental Figure 2. Images for each cell line shows cells that penetrated the Matrigel (invasion) and those that penetrated the insert's membrane (migration). 72 hours after transfection with miR-30a (A). LOX inhibition reduces cellular migration and invasion in ATC cell lines. Transwell migration and invasion assays were performed after 24 hours of treatment with and without 100 µM BAPN (B).

SUMMARYWe investigate the upper mantle seismic structure beneath southern Madagascar and infer the imprint of geodynamic events since Madagascar’s break-up from Africa and India and earlier rifting episodes. Rayleigh and Love wave phase velocities along a profile across southern Madagascar were determined by application of the two-station method to teleseismic earthquake data. For shorter periods (

Radial seismic anisotropy (RA) designates the difference between the speeds of vertically and horizontally polarized shear waves. RA in the crust can provide information on past tectonic events. Since the amplitude and impact of anisotropic are smaller than the variation of velocity, it is more difficult to distinguish whether radially anisotropic anomalies are driven by the structure or uncertainty. Hence, a lack of considering uncertainty and trade-off here may underestimate radial anisotropy and lead to divergent geodynamical interpretations. The hierarchical transdimensional Bayesian approach is able to provide uncertainty estimates taking fully into account the nonlinearity of the forward problem. Under the Bayesian framework, the mean and the variance of the ensemble containing a large set of models are interpreted as the reference solution and a measure of the model error respectively. In our study, we applied a two-step RA inversion of surface wave dispersion and receiver function based on a hierarchical transdimensional Bayesian Monte Carlo search with coupled uncertainty propagation to a temporary broadband array covering all of Sri Lanka. First, we constructed Rayleigh and Love wave phase velocity and errors maps at periods ranging from 0s to 20s. To remove outliers, data uncertainty distribution was expressed as a mixture of a Gaussian and uniform distribution. Next, we inverted local dispersion curves and receiver functions jointly to obtain 1D shear velocity and RA models. The method effectively quantifies the uncertainty of the final crustal shear wave velocity and RA model and shows robust results. The negative RA (Vsv > Vsh) anomalous with low uncertainty found in the mid-lower crust of Central Sri Lanka may show evidence that the charnockite inclusion is associated with the shear zones confined to the cores of some doubly-plunging synforms. In the east Highland Complex, the positive radial anisotropy (Vsh > Vsv) anomalous with low uncertainty may reveal the evidence for sub-horizontal shear zones along the thrust boundary.

We study the crustal structure of Sri Lanka by analyzing data from a temporary seismic network deployed in 2016–2017 to shed light on the amalgamation process from a geophysical perspective. Rayleigh wave phase dispersion curves from ambient noise cross correlation and receiver functions were jointly inverted using a transdimensional Bayesian approach. The Moho depths in Sri Lanka range between 30 and 40 km, with the thickest crust (38–40 km) beneath the central Highland Complex (HC). The thinnest crust (30–35 km) is found along the west coast, which experienced crustal thinning associated with the formation of the Mannar Basin. VP/VS ratios lie within a range of 1.60–1.82 and predominantly favor a felsic to intermediate bulk crustal composition with a significant silica content of the rocks. A major intracrustal (18–27 km), slightly westward dipping (∼4.3°) interface with high VS (∼4 km/s) underneath is prominent in the central HC, continuing into the western Vijayan Complex (VC). The discontinuity might have been part of the respective units prior to the collision and could be an indicator for the proposed tilting of the Wanni Complex/HC crustal sections. It might also be related to the deep crustal HC/VC thrust contact with the VC as an indenting promontory of high VS. A low‐velocity zone in the central HC could have been caused by fluid influx generated by the thrusting process., Key Points: Sri Lanka has mostly isostatically compensated 30–40 km thick crust. VP/VS ratios are between 1.60 and 1.82 and predominantly favor a felsic to intermediate bulk crustal composition. A midcrustal westward dipping interface could be related to the thrust contact between the Highland Complex and the Vijayan Complex.

This study contributes to the development of a new ground‐motion model for Central and Eastern North America (CENA). We evaluate the impact of the seismic‐velocity structure for different crustal regions on ground‐motion measures. We present an overview of the regionalization of the crustal structure of CENA, the physical parameters used for the simulation codes, and the statistical method applied for the comparison of pseudoabsolute response spectral accelerations (PSAs) of four crustal regions defined within CENA. The four crustal regions are (1) the Atlantic Coastal Plain (ACP), (2) the Appalachians (APP), (3) Central North America (CNA), and (4) the Mississippi Embayment/Gulf Coast (MEM). For each region and its statistically representative velocity structure, PSA matrices were computed, covering response oscillator frequencies from 0.5 to 20 Hz and hypocentral distances up to 500 km. PSA matrices for earthquakes at four different focal depths (5, 10, 20, and 30 km) were calculated. The developed method of the normed mean differences gives a meaningful measure for inter‐regional differences of ground motions in comparison with intra‐regional variability. In this study, we compare the ln(PSA) of the APP, ACP, and MEM region with the reference region CNA, respectively. The percentage of ln(PSA) mean difference values that are smaller than the ln(PSA) standard deviation of the reference region CNA lies between 73% and 91% for the APP region, dependent on the focal depth. For the ACP region, it is about 70% for all focal depths, except for the 20 km source depth, which was excluded because a layer boundary at 20.5 km causes unrealistically strong reflections. The percentage for the MEM region is less than 50% for each of the focal depths. This analysis demonstrates that there are two distinct ground‐motion groups for CENA: Group 1: CNA, APP, and ACP Group 2: MEM. Electronic Supplement: Figures of crustal velocity structures, table of Q studies, and Q studies illustrated for one region.

BayHunter is an open source Python tool to perform an McMC transdimensional Bayesian inversion of receiver functions and/ or surface wave dispersion. It is inverting for the velocity-depth structure, the number of layers and noise parameters (noise correlation and amplitude). The forward modeling codes are provided within the package, but are easily replaceable with own codes. It is also possible to add (completely different) data sets. The BayWatch module can be used to live-stream the inversion while it is running: this makes it easy to see how each chain is exploring the parameter space, how the data fits and models change and in which direction the inversion progresses.

We determined radial anisotropy in the crust of southern Madagascar from the differences between the speeds of vertically and horizontally polarized shear waves (VSV and VSH), which we derived from Rayleigh and Love wave dispersion determined from seismic ambient noise correlations. The amalgamated Precambrian units in the east and the Phanerozoic Morondava basin in the west of southern Madagascar were shaped by different geodynamic processes. The crystalline basement was strongly deformed and metamorphosed to varying degrees during the assembly of Gondwana in the Pan‐African Orogeny, whereas the Morondava basin was completed with the separation of Africa and Madagascar. The different developments are reflected in first‐order differences in the radial anisotropy patterns. In the Precambrian domains, positive anisotropy (VSVVSH) sandwiched in between. The upper crustal anisotropy may reflect shallowly dipping layering within the Archean and adjacent imbricated nappe stacks, whereas the lower crustal anisotropy likely represents fossilized crustal flow during the postorogenic or synorogenic collapse of the Pan‐African Orogen. The negative anisotropy layer may have preserved vertically oriented large shear zones of late Pan‐African age. Within the Morondava basin, negative anisotropy in the uppermost ∼5 km could have been generated by steep normal faults, jointing, and magmatic dike intrusions. The deeper sediments and underlying crustal basement are characterized by positive anisotropy. This is consistent with horizontal bedding in the sediments and with fabric alignment in the basement created by extension during the basin formation.

The Klyuchevskoy Volcanic Group is a cluster of the world's most active subduction volcanoes, situated on the Kamchatka Peninsula, Russia. The volcanoes lie in an unusual off‐arc position within the Central Kamchatka Depression (CKD), a large sedimentary basin whose origin is not fully understood. Many gaps also remain in the knowledge of the crustal magmatic plumbing system of these volcanoes. We conducted an ambient noise surface wave tomography, to image the 3‐D shear wave velocity structure of the Klyuchevskoy Volcanic Group and CKD within the surrounding region. Vertical component cross correlations of the continuous seismic noise are used to measure interstation Rayleigh wave group and phase traveltimes. We perform a two‐step surface wave tomography to model the 3‐D Vsv velocity structure. For each inversion stage we use a transdimensional Bayesian Monte Carlo approach, with coupled uncertainty propagation. This ensures that our model provides a reliable 3‐D velocity image of the upper 15 km of the crust, as well as a robust assessment of the uncertainty in the observed structure. Beneath the active volcanoes, we image small slow velocity anomalies at depths of 2–5 km but find no evidence for magma storage regions deeper than 5 km—noting the 15 km depth limit of the model. We also map two clearly defined sedimentary layers within the CKD, revealing an extensive 8 km deep sedimentary accumulation. This volume of sediments is consistent with the possibility that the CKD was formed as an Eocene‐Pliocene fore‐arc regime, rather than by recent (, Plain Language Summary: The Klyuchevskoy Volcanic Group is a cluster of 13 volcanoes on the Kamchatkan corner of the Pacific ring of fire. The volcanoes regularly produce large eruptions, but good knowledge of the magma plumbing system beneath the surface is still lacking. Why the Klyuchevskoy Volcanic Group volcanoes lie in the location they do, in a large low‐lying depression, is also unexplained. We undertook a seismic experiment and used the data to produce a 3‐D velocity image of the subsurface beneath the volcanoes and the depression. We found that small regions of slow seismic velocity are located beneath the active volcanoes, at 2–5 km depth below sea level. This slower velocity is probably caused by magma lying within the porous fracture spaces in this rock. The seismic velocities are much faster beneath the dormant volcanoes, suggesting they have no magma beneath them. With our velocity image, we also find that the Central Kamchatka Depression is very deep, filled with over 8 km of sediments. This supports an idea that the sediments accumulated as a fore‐arc basin over many millions of years, since 40 Ma, when the active line of volcanoes was found 100 km to the west., Key Points: Three‐dimensional shear velocity structure of the Klyuchevskoy area was determined using coupled transdimensional Monte Carlo inversions. Slow velocity anomalies suggest magma storage beneath active volcanoes at 2–5 km depth (below sea level) but not in the midcrust. Sediments filling the Central Kamchatka Depression are 8 km deep, consistent with an origin of the depression as a fore‐arc basin., European Union Horizon 2020 Research and Innovation Programme http://dx.doi.org/10.13039/501100007601, Russian Ministry of Education and Science http://dx.doi.org/10.13039/501100003443, Alexander von Humboldt Foundation http://dx.doi.org/10.13039/100005156