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Efficient generation of cardiomyocytes from human-induced pluripotent stem cells (hiPSCs) is important for their application in basic and translational studies. Space microgravity can significantly change cell activities and function. Previously, we reported upregulation of genes associated with cardiac proliferation in cardiac progenitors derived from hiPSCs that were exposed to space microgravity for 3 days. Here we investigated the effect of long-term exposure of hiPSC-cardiac progenitors to space microgravity on global gene expression. Cryopreserved 3D hiPSC-cardiac progenitors were sent to the International Space Station (ISS) and cultured for 3 weeks under ISS microgravity and ISS 1 G conditions. RNA-sequencing analyses revealed upregulation of genes associated with cardiac differentiation, proliferation, and cardiac structure/function and downregulation of genes associated with extracellular matrix regulation in the ISS microgravity cultures compared with the ISS 1 G cultures. Gene ontology analysis and Kyoto Encyclopedia of Genes and Genomes mapping identified the upregulation of biological processes, molecular function, cellular components, and pathways associated with cell cycle, cardiac differentiation, and cardiac function. Taking together, these results suggest that space microgravity has a beneficial effect on the differentiation and growth of cardiac progenitors.

 

Cardiac pathological outcome of metabolic remodeling is difficult to model using cardiomyocytes derived from human-induced pluripotent stem cells (hiPSC-CMs) due to low metabolic maturation.

hiPSC-CM spheres were treated with AMP-activated protein kinase (AMPK) activators and examined for hiPSC-CM maturation features, molecular changes and the response to pathological stimuli.

Treatment of hiPSC-CMs with AMPK activators increased ATP content, mitochondrial membrane potential and content, mitochondrial DNA, mitochondrial function and fatty acid uptake, indicating increased metabolic maturation. Conversely, the knockdown of AMPK inhibited mitochondrial maturation of hiPSC-CMs. In addition, AMPK activator-treated hiPSC-CMs had improved structural development and functional features—including enhanced Ca²⁺transient kinetics and increased contraction. Transcriptomic, proteomic and metabolomic profiling identified differential levels of expression of genes, proteins and metabolites associated with a molecular signature of mature cardiomyocytes in AMPK activator-treated hiPSC-CMs. In response to pathological stimuli, AMPK activator-treated hiPSC-CMs had increased glycolysis, and other pathological outcomes compared to untreated cells.

AMPK activator-treated cardiac spheres could serve as a valuable model to gain novel insights into cardiac diseases.

 

SARS-CoV-2 wastewater surveillance (WWS) at wastewater treatment plants (WWTPs) can reveal sewered community COVID-19 prevalence. For unsewered areas using septic tank systems (STSs) or holding tanks, how to conduct WWS remains unexplored. Here, two large STSs serving Zuma Beach (Malibu, CA) were studied. Supernatant and sludge SARS-CoV-2 concentrations from the directly-sampled STSs parameterized a dynamic solid–liquid separation, a mass balance-based model for estimating the infection rate of users. Pumped septage before hauling and upon WWTP disposal was also sampled and assessed. Most (96%) STS sludge samples contained SARS-CoV-2 N1 and N2 genes, with concentrations exceeding the supernatant and increasing with depth while correlating with total suspended solids (TSS). The trucked septage contained N1 and N2 copies which decayed (coefficients: 0.09–0.29 h−1) but remained detectable. Over approximately 5 months starting in December 2020, modeled COVID-19 prevalence estimations among users ranged from 8 to 18%, mirroring a larger metropolitan area for the first 2 months. The approaches herein can inform public health intervention and augment conventional WWS in that: (1) user infection rates for communal holding tanks are estimable and (2) pumped and hauled septage can be assayed to infer where disease is spreading in unsewered areas.

 

Abstract Transition metal oxides are promising candidates for the next generation of spintronic devices due to their fascinating properties that can be effectively engineered by strain, defects, and microstructure. An excellent example can be found in ferroelastic LaCoO 3 with paramagnetism in bulk. In contrast, unexpected ferromagnetism is observed in tensile-strained LaCoO 3 films, however, its origin remains controversial. Here we simultaneously reveal the formation of ordered oxygen vacancies and previously unreported long-range suppression of CoO 6 octahedral rotations throughout LaCoO 3 films. Supported by density functional theory calculations, we find that the strong modification of Co 3 d -O 2 p hybridization associated with the increase of both Co-O-Co bond angle and Co-O bond length weakens the crystal-field splitting and facilitates an ordered high-spin state of Co ions, inducing an emergent ferromagnetic-insulating state. Our work provides unique insights into underlying mechanisms driving the ferromagnetic-insulating state in tensile-strained ferroelastic LaCoO 3 films while suggesting potential applications toward low-power spintronic devices. 

Since Rendle and Krichene argued that commonly used sampling-based evaluation metrics are “inconsistent” with respect to the global metrics (even in expectation), there have been a few studies on the sampling-based recommender system evaluation. Existing methods try either mapping the sampling-based metrics to their global counterparts or more generally, learning the empirical rank distribution to estimate the top-K metrics. However, despite existing efforts, there is still a lack of rigorous theoretical understanding of the proposed metric estimators, and the basic item sampling also suffers from the “blind spot” issue, i.e., estimation accuracy to recover the top-K metrics when K is small can still be rather substantial. In this paper, we provide an in-depth investigation into these problems and make two innovative contributions. First, we propose a new item-sampling estimator that explicitly optimizes the error with respect to the ground truth, and theoretically highlights its subtle difference against prior work. Second, we propose a new adaptive sampling method that aims to deal with the “blind spot” problem and also demonstrate the expectation-maximization (EM) algorithm can be generalized for such a setting. Our experimental results confirm our statistical analysis and the superiority of the proposed works. This study helps lay the theoretical foundation for adopting item sampling metrics for recommendation evaluation and provides strong evidence for making item sampling a powerful and reliable tool for recommendation evaluation.