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Quantitatively evaluating changes in art critique journals’ use of moral language across time

Chang et al. | Oct 23, 2026

Quantitatively evaluating changes in art critique journals’ use of moral language across time
Image credit: Chang and Mahmoud

The authors use MoralBERT, a BERT-based machine learning model, to analyze the prevalence and evolution of moral language in art critique journals from 1960 to 2015. They draw on Moral Foundations Theory to examine changes in five virtue and five vice foundations over time. They discover slight increases in degradation and care and a decrease in purity among otherwise stable patterns. The study is a novel application of computational moral analysis in a domain not typically associated with such tools. Although the moral signals were relatively faint, the study offers insights into shifting art world discourses and models an exciting method for future inquiry.

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Investigating the effects of PVC microplastics on the growth of Chlorella vulgaris

Beaubien et al. | Oct 13, 2026

Investigating the effects of PVC microplastics on the growth of <i>Chlorella vulgaris</i>

This study examined the effect of varying PVC microplastic concentrations on the growth of Chlorella vulgaris in freshwater, utilizing six PVC levels and identical culture conditions. Cell counts revealed that higher PVC concentrations consistently reduced algal growth, and a Spearman correlation test detected a significant negative monotonic association between PVC concentration and viable cell density. These results support the hypothesis that PVC microplastics impair algal growth, underscoring their ecological risk in freshwater environments.

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Using machine learning to detect outliers of red clump stars

Meng et al. | Oct 10, 2026

Using machine learning to detect outliers of red clump stars

Machine learning offers a powerful way to analyze large astronomical datasets and identify stars with unusual properties. In this study, students used Extreme Gradient Boosting and Isolation Forest models to investigate why some red clump stars deviate from their expected luminosities. Their results show that stellar age plays a much stronger role than metallicity in driving luminosity variation, and the models successfully detected outlier stars that may affect distance measurements in galactic studies.

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Leaky expression of PRMT1 in Escherichia coli and redox regulation of its histone methyltransferase activity

Kim et al. | Oct 07, 2026

Leaky expression of PRMT1 in <i>Escherichia coli</i> and redox regulation of its histone methyltransferase activity

This study characterizes recombinant human Protein arginine methyltransferase 1 (PRMT1) expressed in Escherichia. coli and reveals that the enzyme exhibits leaky expression even without isopropyl β-D-1-thiogalactopyranoside (IPTG) induction. Through in vitro histone methyltransferase assays, we demonstrate that PRMT1 activity toward histone H4R3 is enhanced by dithiothreitol (DTT) in a dose-dependent manner but remains unresponsive to β-mercaptoethanol. These findings highlight the critical role of redox conditions in regulating PRMT1 catalytic function and provide a practical framework for future biochemical and kinetic studies.

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Multi-omic analysis identifies mitochondrial dysfunction as a key feature of hypertrophic cardiomyopathy

Velu et al. | Sep 26, 2026

Multi-omic analysis identifies mitochondrial dysfunction as a key feature of hypertrophic cardiomyopathy

This study used multi-omic analysis to investigate gene expression and DNA methylation patterns associated with hypertrophic cardiomyopathy (HCM). The researchers found significant downregulation of mitochondrial and energy-related pathways, highlighting mitochondrial dysfunction—particularly altered PINK1 expression—as a potential contributor and therapeutic target in HCM.

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In vitro effects of cosmetic products on the growth of skin-resident bacteria

Relia et al. | Sep 20, 2026

<i>In vitro</i> effects of cosmetic products on the growth of skin-resident bacteria

This study investigated how 18 commonly used cosmetic products affect the growth of two skin-resident bacteria, Staphylococcus epidermidis and Micrococcus luteus. At higher concentrations, half of the tested products inhibited at least one bacterial species, suggesting that some cosmetics may disrupt the skin microbiome and its natural balance.

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