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The lithium-ion battery is currently the preferred power source for applications ranging from smart phones to electric vehicles. Imaging the chemical reactions governing its function as they happen, with nanoscale spatial resolution and chemical specificity, is a long-standing open problem. Here, we demonstrate operando spectrum imaging of a Li-ion battery anode over multiple charge-discharge cycles using electron energy-loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM). Using ultrathin Li-ion cells, we acquire reference EELS spectra for the various constituents of the solid-electrolyte interphase (SEI) layer and then apply these “chemical fingerprints” to high-resolution, real-space mapping of the corresponding physical structures. We observe the growth of Li and LiH dendrites in the SEI and fingerprint the SEI itself. High spatial- and spectral-resolution operando imaging of the air-sensitive liquid chemistries of the Li-ion cell opens a direct route to understanding the complex, dynamic mechanisms that affect battery safety, capacity, and lifetime. 

ABSTRACT We employ a sample of 135 873 RR Lyrae stars (RRLs) with precise photometric-metallicity and distance estimates from the newly calibrated P–ϕ31–R21–[Fe/H] and Gaia G band P–R21–[Fe/H] absolute magnitude–metallicity relations of Li et al., combined with available proper motions from Gaia EDR3, and 6955 systemic radial velocities from Gaia DR3 and other sources, in order to explore the chemistry and kinematics of the halo of the Milky Way (MW). This sample is ideally suited for characterization of the inner- and outer-halo populations of the stellar halo, free from the bias associated with spectroscopically selected probes, and for estimation of their relative contributions as a function of Galactocentric distance. The results of a Gaussian mixture model analysis of these contributions are broadly consistent with other observational studies of the halo, and with expectations from recent MW simulation studies. We apply the hdbscan clustering method to the specific energies and cylindrical actions (E, Jr, Jϕ, Jz), identifying 97 dynamically tagged groups (DTGs) of RRLs, and explore their associations with recognized substructures of the MW. The precise photometric-distance determinations (relative distance errors on the order of 5 per cent or better), and the resulting high-quality determination of dynamical parameters, yield highly statistically significant (low) dispersions of [Fe/H] for the stellar members of the DTGs compared to random draws from the full sample, indicating that they share common star-formation and chemical histories, influenced by their birth environments. 

Blind and low-vision (BLV) people watch sports through radio broadcasts that offer a play-by-play description of the game. However, recent trends show a decline in the availability and quality of radio broadcasts due to the rise of video streaming platforms on the internet and the cost of hiring professional announcers. As a result, sports broadcasts have now become even more inaccessible to BLV people. In this work, we present Immersive A/V, a technique for making sports broadcasts —in our case, tennis broadcasts— accessible and immersive to BLV viewers by automatically extracting gameplay information and conveying it through an added layer of spatialized audio cues. Immersive A/V conveys players’ positions and actions as detected by computer vision-based video analysis, allowing BLV viewers to visualize the action. We designed Immersive A/V based on results from a formative study with BLV participants. We conclude by outlining our plans for evaluating Immersive A/V and the future implications of this research. 

Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure–function relationship in the lung. 

ABSTRACT Compared with our extensive understanding of the cell cycle, we have limited knowledge of how the cell quiescence–proliferation decision is regulated. Using a zebrafish epithelial model, we report a novel signaling mechanism governing the cell quiescence–proliferation decision. Zebrafish Ca2+-transporting epithelial cells, or ionocytes, maintain high cytoplasmic Ca2+ concentration ([Ca2+]c) due to the expression of Trpv6. Genetic deletion or pharmacological inhibition of Trpv6, or reduction of external Ca2+ concentration, lowered the [Ca2+]c and reactivated these cells. The ionocyte reactivation was attenuated by chelating intracellular Ca2+ and inhibiting calmodulin (CaM), suggesting involvement of a Ca2+ and CaM-dependent mechanism. Long-term imaging studies showed that after an initial decrease, [Ca2+]c gradually returned to the basal levels. There was a concomitant decease in endoplasmic reticulum (ER) Ca2+ levels. Lowering the ER Ca2+ store content or inhibiting ryanodine receptors impaired ionocyte reactivation. Further analyses suggest that CaM-dependent protein kinase kinase (CaMKK) is a key molecular link between Ca2+ and Akt signaling. Genetic deletion or inhibition of CaMKK abolished cell reactivation, which could be rescued by expression of a constitutively active Akt. These results suggest that the quiescence–proliferation decision in zebrafish ionocytes is regulated by Trpv6-mediated Ca2+ and CaMKK–Akt signaling. 

The molecular mechanisms regulating cell quiescence-proliferation balance are not well defined. Using a zebrafish model, we report that Stc1a, a secreted glycoprotein, plays a key role in regulating the quiescence-proliferation balance of Ca²⁺transporting epithelial cells (ionocytes). Zebrafishstc1a, but not the otherstcgenes, is expressed in a Ca²⁺state-dependent manner. Genetic deletion ofstc1a, but notstc2b, increased ionocyte proliferation, leading to elevated body Ca²⁺levels, cardiac edema, body swelling, and premature death. The increased ionocyte proliferation was accompanied by an increase in the IGF1 receptor-mediated PI3 kinase-Akt-Tor signaling activity in ionocytes. Inhibition of the IGF1 receptor, PI3 kinase, Akt, and Tor signaling reduced ionocyte proliferation and rescued the edema and premature death instc1a^–/–fish, suggesting that Stc1a promotes ionocyte quiescence by suppressing local IGF signaling activity. Mechanistically, Stc1 acts by inhibiting Papp-aa, a zinc metalloproteinase degrading Igfbp5a. Inhibition of Papp-aa proteinase activity restored ionocyte quiescence-proliferation balance. Genetic deletion ofpapp-aaor its substrateigfbp5ain thestc1a^–/–background reduced ionocyte proliferation and rescued the edema and premature death. These findings uncover a novel and Ca²⁺state-dependent pathway regulating cell quiescence. Our findings also provide new insights into the importance of ionocyte quiescent-proliferation balance in organismal Ca²⁺homeostasis and survival.