Targeting the nuclear long noncoding transcript LSP1P5 abrogates extracellular matrix deposition by trans-upregulating CEBPA in keloids.

Keloids are characterized by fibroblast hyperproliferation and excessive accumulation of extracellular matrix (ECM) and are a major global health care burden among cutaneous diseases. However, the function of long noncoding RNA (lncRNA)-mediated ECM remodeling during the pathogenesis of keloids is still unclear. Herein, we identified a long noncoding transcript, namely, lymphocyte-specific protein 1 pseudogene 5 (LSP1P5), that modulates ECM component deposition in keloids. First, high-throughput transcriptome analysis showed that LSP1P5 was selectively upregulated in keloids and correlated with more severe disease in a clinical keloid cohort. Therapeutically, the attenuation of LSP1P5 significantly decreased the expression of ECM markers (COL1, COL3, and FN1) both in vitro and in vivo. Intriguingly, an antifibrotic gene, CCAAT enhancer binding protein alpha (CEBPA), is a functional downstream candidate of LSP1P5. Mechanistically, LSP1P5 represses CEBPA expression by hijacking Suppressor of Zeste 12 to the promoter of CEBPA, thereby enhancing the polycomb repressive complex 2-mediated H3K27me3 and changing the chromosomal opening status of CEBPA. Taken together, these findings indicate that targeting LSP1P5 abrogates fibrosis in keloids through epigenetic regulation of CEBPA, revealing a novel antifibrotic therapeutic strategy that bridges our current understanding of lncRNA regulation, histone modification and ECM remodeling in keloids.

The Effect of Cuproptosis-Related Proteins on Macrophage Polarization in Mesothelioma is Revealed by scRNA-seq.

High invasiveness mesothelioma is a malignant tumor of the peritoneum or pleura. The effect of cuproptosis on mesothelioma (MESO) is still unknown, though. The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets were used to identify differential genes linked to cuproptosis in mesothelioma. Multigene features were then created to assess the course of the disease. Use single-cell data and in vitro validation to uncover crucial gene regulation mechanisms. In MESO, we found nine differentially expressed genes linked to cuproptosis. Using univariate Cox and LASSO regression techniques, a 3-gene feature (P < 0.05) was created, showing a good predictive potential for survival time. According to the risk score, patients in the low-risk subset had a considerably greater survival rate than those in the high-risk subset (P = 0). The similar survival pattern and prediction performance are also seen in the validation queue. The findings of the drug sensitivity research indicate that in high-risk patients, vinblastine, paclitaxel, gefitinib, and erlotinib are sensitive medications (P < 0.05). Classical monocytes were identified as core cells connected to cuproptosis by the CellChat results. SLC31A1 is implicated in the positive regulation of M2 macrophage polarization, according to cell subtype analysis and in vitro confirmation. Genes linked to cuproptosis have a major influence on tumor immunity and can predict how MESO will progress.

An STP-HSI index method for urban built-up area extraction based on multi-source remote sensing data.

A change in an urban built-up area can reflect the process of urbanization and the development of a city. At present, multi-source remote sensing data extraction of built-up areas based on the human settlement index (HSI) has achieved relatively good results but the existence of noise, such as light spillover in the night-time light remote sensing data, seriously affects the accuracy of the HSI. In this paper, a high-precision human settlement index (STP-HSI) method based on spatio-temporal remote sensing and point-of-interest (POI) data is presented to improve the classification accuracy in urban built-up areas extractions. First, to correct light spillover, a new night-time light index the fuzzy c-means spatio-temporal point (FCM-STP) based on fuzzy c-means clustering is proposed, which integrates the spatio-temporal characteristics and uses night light video imaging data from Luojia-1 and POI data. Then, based on the FCM-STP index, the HSI is updated to the STP-HSI index. Finally, a random forest algorithm is used to extract the urban built-up areas, and the random forest feature database is composed of normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and STP-HSI index features and texture features. To develop and evaluate the accuracy of the new method for built-up areas extraction with multi-source data, three test sites located in the cities of China (Guangzhou, Xiamen and Nanjing) are used. The experimental results show that our method outperforms the single-source multi-spectral (Landsat 8) data extraction results, the overall accuracy is improved by up to 7.52%, and the kappa coefficient is improved by up to 14%. Compared with the HSI index, the maximum contribution rates of the STP-HSI increased by 25.74%. These experimental results show that the method in this paper is feasible.

Preparation and cellular protection against oxidation of Konjac oligosaccharides obtained by combination of γ-irradiation and enzymatic hydrolysis.

Konjac glucomannan (KGM) is an important source for preparation of Konjac oligo-glucomannan (KOG), but high molecular weight and viscosity in KGM inhibited its full degradation into KOG. In this study, KOG with a degree of polymerization between 2 and 9 was obtained by combining γ-irradiation and enzymatic hydrolysis in high yield. We investigated the protective effect of KOG against H2O2 - induced oxidative damage in vitro, using human hepatic cell line (LO2) as a cell model. Our results demonstrated that pretreating LO2 with KOG significantly increases cellular survival and antioxidant activities of GSH-Px and CAT enzymes, and reduces levels of LDH, MDA, intracellular accumulation of ROS and Ca2+ concentration within the cell. Marked protective effect against oxidative damage, in addition to obtained high yield of KOG, supports its potential use as an abundant source of antioxidant. To conclude, our study provided a theoretical perspective for future uses of KGM.

Physicochemical properties and cellular protection against oxidation of degraded Konjac glucomannan prepared by γ-irradiation.

Konjac glucomannan (KGM) is an important functional polysaccharide in food research. However, unstable dispersibility of KGM inhibits its in-depth study and wide application. In this study, a degraded KGM (100kGy-KGM), which showed excellent dispersibility and specific physicochemical properties, were obtained by γ-irradiation in a dosage of 100kGy. We investigated the protective effect of 100kGy-KGM against H2O2 induced oxidative damage in LO2 cells. Our results demonstrated that pretreatment of LO2 cells with 100kGy-KGM not only significantly increased cellular survivals and activities of GSH-Px and CAT, but also reduced levels of LDH, MDA and intracellular accumulation of ROS. The marked protective effect against oxidative damage and excellent dispersibility in 100kGy-KGM allowed its possible use as an antioxidant. Our study provided fundamental knowledge to understand the structure-functions relationships of degraded-KGM, which could result in a theoretical guidance for the future application of KGM.