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Personalized recommender systems play a crucial role in modern society, especially in e-commerce, news, and ads areas. Correctly evaluating and comparing candidate recommendation models is as essential as constructing ones. The common offline evaluation strategy is holding out some user-interacted items from training data and evaluating the performance of recommendation models based on how many items they can retrieve. Specifically, for any hold-out item or so-called target item for a user, the recommendation models try to predict the probability that the user would interact with the item and rank it among overall items, which is calledglobal evaluation. Intuitively, a good recommendation model would assign high probabilities to such hold-out/target items. Based on the specific ranks, some metrics likeRecall@KandNDCG@Kcan be calculated to further quantify the quality of the recommender model. Instead of ranking the target items among all items, Koren first proposed to rank them among a smallsampled set of items, then quantified the performance of the models, which is calledsampling evaluation. Ever since then, there has been a large amount of work adopting sampling evaluation due to its efficiency and frugality. In recent work, Rendle and Krichene argued that the sampling evaluation is “inconsistent” with respect to a global evaluation in terms of offline top-Kmetrics.

In this work, we first investigate the “inconsistent” phenomenon by taking a glance at the connections between sampling evaluation and global evaluation. We reveal the approximately linear relationship between sampling with respect to its global counterpart in terms of the top-KRecall metric. Second, we propose a new statistical perspective of the sampling evaluation—to estimate the global rank distribution of the entire population. After the estimated rank distribution is obtained, the approximation of the global metric can be further derived. Third, we extend the work of Krichene and Rendle, directly optimizing the error with ground truth, providing not only a comprehensive empirical study but also a rigorous theoretical understanding of the proposed metric estimators. To address the “blind spot” issue, where accurately estimating metrics for small top-Kvalues in sampling evaluation is challenging, we propose a novel adaptive sampling method that generalizes the expectation-maximization algorithm to this setting. Last but not least, we also study the user sampling evaluation effect. This series of works outlines a clear roadmap for sampling evaluation and establishes a foundational theoretical framework. Extensive empirical studies validate the reliability of the sampling methods presented.

 

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.