Nonsteroidal anti-inflammatory drugs compose one of the most widely used classes of medications, but the risks for early development remain controversial, especially in the nervous system. Here, we utilized zebrafish larvae to assess the potentially toxic effects of nonsteroidal anti-inflammatory drugs and found that sulindac can selectively induce apoptosis of GABAergic neurons in the brains of zebrafish larvae brains. Zebrafish larvae exhibit hyperactive behaviour after sulindac exposure. We also found that akt1 is selectively expressed in GABAergic neurons and that SC97 (an Akt1 activator) and exogenous akt1 mRNA can reverse the apoptosis caused by sulindac. Further studies showed that sulindac binds to retinoid X receptor alpha (RXRα) and induces autophagy in GABAergic neurons, leading to activation of the mitochondrial apoptotic pathway. Finally, we verified that sulindac can lead to hyperactivity and selectively induce GABAergic neuron apoptosis in mice. These findings suggest that excessive use of sulindac may lead to early neurodevelopmental toxicity and increase the risk of hyperactivity, which could be associated with damage to GABAergic neurons.

The multi-level spatial chromatin organization in the nucleus is closely related to chromatin activity. The mechanism of chromatin organization and remodeling attract much attention. Phase separation describes the biomolecular condensation which is the basis for membraneless compartments in cells. Recent research shows that phase separation is a key aspect to drive high-order chromatin structure and remodeling. In addition, chromatin functional compartmentalization in the nucleus which is formed by phase separation also plays an important role in overall chromatin structure. In this review, we summarized the latest work about the role of phase separation in spatial chromatin organization, focusing on direct and indirect effects of phase separation on 3D chromatin organization and its impact on transcription regulation.

Formaldehyde (FA) is a chemical that facilitates crosslinking between DNA and proteins. It is widely used in various biochemical assays, such as chromosome conformation capture (3C) and Chromatin Immunoprecipitation (ChIP). While the concentration and temperature of FA treatment are recognized as crucial factors in crosslinking, their quantitative effects have largely remained unexplored. In this study, we employed 3C as a model system to systematically assess the impacts of these two factors on crosslinking. Our findings indicate that the strength of crosslinking significantly influences chromatin conformation detection at nearly all known structural levels. Specifically, a delicate balance between sensitivity and reliability is required when detecting higher-level structures, such as chromosome compartments. Conversely, intense crosslinking is preferred when targeting lower-level structures, such as topologically associated domains (TADs) or chromatin loops. Based on our data, we propose a conceptual molecular thermal motion model to elucidate the roles of these two factors in restricting FA crosslinking. Our results not only shed light on the previously overlooked confounding factor in FA crosslinking but also highlight the need for caution in new technology developments that rely on FA crosslinking.

Heat shock is a common environmental stress, although the response of the nucleus to it remains controversial in mammalian cells. Acute reaction and chronic adaptation to environmental stress may have distinct internal rewiring in the gene regulation networks. However, this difference remains largely unexplored. Here, we report that chromatin conformation and chromatin accessibility respond differently in short- and long-term heat shock in human K562 cells. We found that chromatin conformation in K562 cells was largely stable in response to short-term heat shock, whereas it showed clear and characteristic changes after long-term heat treatment with little alteration in chromatin accessibility during the whole process. We further show in silico and experimental evidence strongly suggesting that changes in chromatin conformation may largely stem from an accumulation of cells in the M stage of the cell cycle in response to heat shock. Our results represent a paradigm shift away from the controversial view of chromatin response to heat shock and emphasize the necessity of cell cycle analysis when interpreting bulk Hi-C data.

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

Osteoporosis is a known risk factor for rotator cuff tears (RCTs), but the causal correlation and underlying mechanisms remain unclear. This study aims to evaluate the impact of osteoporosis on RCT risk and investigate their genetic associations. Using data from the UK Biobank (n = 457 871), cross-sectional analyses demonstrated that osteoporosis was significantly associated with an increased risk of RCTs (adjusted OR [95% CI] = 1.38 [1.25–1.52]). A longitudinal analysis of a subset of patients (n = 268 117) over 11 years revealed that osteoporosis increased the risk of RCTs (adjusted HR [95% CI] = 1.56 [1.29–1.87]), which is notably varied between sexes in sex-stratified analysis. Causal inference methods, including propensity score matching, inverse probability weighting, causal random forest and survival random forest models further confirmed the causal effect, both from cross-sectional and longitudinal perspectives. A colocalization analysis across multiple datasets identified six candidate loci, including the successfully replicated PKDCC rs12996954 variant, which may help explain the shared genetic basis between osteoporosis and RCTs. In conclusion, osteoporosis significantly increases the risk of RCTs, emphasizing the importance of osteoporosis management in preventing RCTs. The identification of shared genetic loci provides new insights into their potential pathogenic mechanisms.