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Tendons are collagen‐rich tissues that are necessary for movement and, as such, are exposed to mechanical forces. Mechanical loading impacts tendon formation, homeostasis and injury. Frequent injury and poor healing of tendon is a major clinical issue. An improved understanding of how tendon cells respond to mechanical forces is needed to advance new therapies to treat tendon injuries and limit degeneration caused by aberrant mechanical loading. In this review, we highlight recent discoveries in how mechanical stimulation impacts tendon and enthesis formation during development, as well as tendon maintenance and degradation during adulthood. We focus on understanding the cell‐level mechanotransduction mechanisms, which include calcium signalling, activation of specific cell receptors and ion channels, and the effect on primary cilia and other downstream cell signalling pathways. These recently identified mechanotransducers in tendon cells show promise as future therapeutic targets, which can be leveraged for tendon healing. 

Abstract Atomic-scale molecular modeling and simulation are powerful tools for computational biology. However, constructing models with large, densely packed molecules, non-water solvents, or with combinations of multiple biomembranes, polymers, and nanomaterials remains challenging and requires significant time and expertise. Furthermore, existing tools do not support such assemblies under the periodic boundary conditions (PBC) necessary for molecular simulation. Here, we describe Multicomponent Assembler in CHARMM-GUI that automates complex molecular assembly and simulation input preparation under the PBC. In this work, we demonstrate its versatility by preparing 6 challenging systems with varying density of large components: (1) solvated proteins, (2) solvated proteins with a pre-equilibrated membrane, (3) solvated proteins with a sheet-like nanomaterial, (4) solvated proteins with a sheet-like polymer, (5) a mixed membrane-nanomaterial system, and (6) a sheet-like polymer with gaseous solvent. Multicomponent Assembler is expected to be a unique cyberinfrastructure to study complex interactions between small molecules, biomacromolecules, polymers, and nanomaterials. 

Abstract Spectroscopic studies of elliptical galaxies show that their stellar population ages, mean metallicity, andαenhancement traced by [Mg/Fe] all increase with galaxy stellar mass or velocity dispersion. We use one-zone galactic chemical evolution (GCE) models with a flexible star formation history (SFH) to model the age, [Mg/H], and [Mg/Fe] inferred from simple stellar population (SSP) fits to observed ellipticals atz∼ 0 andz∼ 0.7. We show that an SSP fit to the spectrum computed from a full GCE model gives ages and abundances close to the light-weighted, logarithmically averaged values of the composite stellar population, 〈age〉, 〈[Mg/H]〉, and 〈[Mg/Fe]〉. With supernova Mg and Fe yields fixed to values motivated by Milky Way stellar populations, we find that predicted 〈[Mg/H]〉–〈age〉 and 〈[Mg/Fe]〉–〈age〉 relations are surprisingly insensitive to SFH parameters: Older galaxies have higher 〈[Mg/Fe]〉, but the detailed form of the SFH has limited impact. The star formation efficiency (SFE) and outflow efficiency affect the early and late evolution of 〈[Mg/H]〉, respectively; explaining observed trends requires higher SFE and lower outflows in more massive galaxies. With core-collapse supernova yields calibrated to the plateau [Mg/Fe]_cc≈ 0.45 observed in many Milky Way studies, our models underpredict the observed 〈[Mg/Fe]〉 ratios of ellipticals by 0.05–0.1 dex. Increasing the core-collapse yield ratio to [Mg/Fe]_cc= 0.55 improves the agreement, though the models remain below the data. We discuss potential resolutions of this discrepancy, including the possibility that many ellipticals terminate their star formation with a self-enriching, terminating burst that reduces the light-weighted age and boosts 〈[Mg/Fe]〉. 

Abstract BackgroundEcological barriers can shape the movement strategies of migratory animals that navigate around or across them, creating migratory divides. Wind plays a large role in facilitating aerial migrations and can temporally or spatially change the challenge posed by an ecological barrier, with beneficial winds potentially converting a barrier into a corridor. Here, we explore the role wind plays in shaping initial southbound migration strategy among individuals breeding at two sites along an ecological barrier. MethodsUsing GPS satellite transmitters, we tracked the southbound migrations of Short-billed Dowitchers(Limnodromus griseus caurinus)from two breeding sites in Alaska to nonbreeding sites in coastal Mexico. The breeding sites were positioned in distinct regions along an ecological barrier – the Gulf of Alaska. We investigated potential differences in migratory timing, wind availability, and tailwind supportenroute across the Gulf of Alaska between individuals breeding at the two sites. ResultsRoute choice and arrival timing to wintering sites differed markedly between the two breeding sites: individuals departing from the more westerly site left at the same time as those from further east but crossed the Gulf of Alaska farther west and arrived along the Pacific coast of Mexico an average of 19 days earlier than their counterparts. Dowitchers from both sites departed with slight tailwinds, but once aloft over the Gulf of Alaska, birds from the more westerly site had up to twelve times more tailwind assistance than birds from the more easterly one. ConclusionsThe distinct migration strategies and degree of wind assistance experienced by birds at these two breeding sites demonstrates how differences in wind availability along migratory routes can form the basis for intraspecific variation in migration strategies with potential carryover effects. Future changes in wind regimes may therefore interact with changes in habitat availability to influence migration patterns and migratory bird conservation. 

This paper investigates methods for training parameterized functions for guiding state-space search algorithms. Existing work commonly generates data for training such guiding functions by solving problem instances while leveraging the current version of the guiding function. As a result, as training progresses, the guided search algorithm can solve more difficult instances that are, in turn, used to further train the guiding function. These methods assume that a set of problem instances of varied difficulty is provided. Since previous work was not designed to distinguish the instances that the search algorithm can solve from those that cannot be solved with the current guiding function, the algorithm commonly wastes time attempting and failing to solve many of these instances. In this paper, we improve upon these training methods by generating a curriculum for learning the guiding function that directly addresses this issue. Namely, we propose and evaluate a Teacher-Student Curriculum (TSC) approach where the teacher is an evolutionary strategy that attempts to generate problem instances of ``correct difficulty'' and the student is a guided search algorithm utilizing the current guiding function. The student attempts to solve the problem instances generated by the teacher. We conclude with experiments demonstrating that TSC outperforms the current state-of-the-art Bootstrap Learning method in three representative benchmark domains and three guided search algorithms, with respect to the time required to solve all instances of the test set. 

The development of efficient quantum communication technologies depends on the innovation in multiple layers of its implementation, a challenge we address from the fundamental properties of the physical system at the nano-scale to the instrumentation level at the macro-scale. We select a promising near infrared quantum emitter, the nitrogen-vacancy (NV) center in 4H-SiC, and integrate it, at an ensemble level, with nanopillar structures that enhance photon collection efficiency into an objective lens. Moreover, changes in collection efficiency in pillars compared to bulk can serve as indicators of color center orientation in the lattice. To characterize NV center properties at the unprecedented sub-2 Kelvin temperatures, we incorporate compatible superconducting nanowire single photon detectors inside the chamber of an optical cryostat and create the ICECAP, the Integrated Cryogenic system for Emission, Collection And Photon-detection. ICECAP measurements show no significant linewidth broadening of NV ensemble emission and up to 14-fold enhancement in collected emission. With additional filtering, we measure emitter lifetimes of NV centers in a basal (hk) and an axial (kk) orientation unveiling their cryogenic values of 2.2 ns and 2.8 ns. 

Abstract Lithium niobate is a promising material for developing quantum acoustic technologies due to its strong piezoelectric effect and availability in the form of crystalline thin films of high quality. However, at radio frequencies and cryogenic temperatures, these resonators are limited by the presence of decoherence and dephasing due to two-level systems. To mitigate these losses and increase device performance, a more detailed picture of the microscopic nature of these loss channels is needed. In this study, we fabricate several lithium niobate acoustic wave resonators and apply different processing steps that modify their surfaces. These treatments include argon ion sputtering, annealing, and acid cleans. We characterize the effects of these treatments using three surface-sensitive measurements: cryogenic microwave spectroscopy measuring density and coupling of TLS to mechanics, X-ray photoelectron spectroscopy and atomic force microscopy. We learn from these studies that, surprisingly, increases of TLS density may accompany apparent improvements in the surface quality as probed by the latter two approaches. Our work outlines the importance that surfaces and fabrication techniques play in altering acoustic resonator coherence, and suggests gaps in our understanding as well as approaches to address them.