Stem Cell Research & Therapy•2025•DOI: 10.1186/s13287-025-04214-8
The authors wish to note the following correction: The images in Fig. 2D of our paper, which were intended to show Annexin V staining for apoptosis of human dental pulp stem cells (hDPSCs) and HGF-transfected hDPSCs (HGF-hDPSCs) under hypoxic conditions or serum-free media, were incorrect. The original results demonstrated that more apoptotic cells were observed in the hDPSCs group compared to the HGF-hDPSCs group. However, we inadvertently used images of Annexin V staining for apoptosis in human bone marrow mesenchymal stem cells (hBMSCs) and HGF-transfected hBMSCs (HGF-hBMSCs). Upon reviewing the original experimental records, we discovered that the incorrect images were included during the manuscript preparation process due to insufficient verification. We have now provided the correct images for hDPSCs and HGF-hDPSCs in Fig. 2D (see attachment). We sincerely apologize for this oversight. This error occurred because our research group has been extensively engaged in studying the biological characteristics of HGF gene-transfected mesenchymal stem cells. Unfortunately, due to carelessness, we mistakenly selected the wrong images. Nevertheless, our research consistently demonstrates that the anti-apoptotic ability of mesenchymal stem cells (including rBMSCs, hBMSCs, and hDPSCs) is enhanced under hypoxic conditions or serum-free media following HGF gene transfection. The methodology and results remain consistent with our previous studies. After thoroughly reviewing all data and experimental records, we confirm that this correction does not affect the validity of the original study’s results or conclusions.
Acta Biochimica et Biophysica Sinica•2025•DOI: 10.3724/abbs.2024226
Glutaminolysis and glycolysis promote the malignant progression of colorectal cancer. The role of activating transcription factor 4 (ATF4) in solute carrier family 1 member 5 (SLC1A5)-mediated glutaminolysis and glycolysis remains to be elucidated. SLC1A5 and ATF4 expression levels are detected in colorectal cancer tissues. ATF4 is knocked down or overexpressed to assess its role in cell viability, migration and invasion. SLC1A5 is knocked down to evaluate its role in cell viability, migration, invasion, and metastasis and the metabolism of glutamine and glucose. The regulatory effect of the transcription factor ATF4 on SLC1A5 transcription and expression is determined using a luciferase reporter assay and chromatin immunoprecipitation (ChIP) techniques. Upregulated ATF4 and SLC1A5 expressions are observed in tumor tissue, which is positively correlated with the tumor, node, and metastasis (TNM) stages. ATF4-overexpressing SW480 cells show the increased cell viability, migration and invasion. Conversely, ATF4 knockdown decreases the viability, migration and invasion of HCT-116 cells. SLC1A5 knockdown inhibits viability, migration, invasion, and metastasis and the metabolism of glutamine and glucose in HT-29 cells, as well as the expressions of two key glycolytic enzymes, hexokinase 2 (HK2) and pyruvate kinase M2 (PKM2). The luciferase activity of the SLC1A5 promoter is increased by ATF4 overexpression. SLC1A5 promoter enrichment is increased by anti-ATF4 antibody immunoprecipitation in ATF4-overexpressing colorectal cells, indicating that ATF4 targets SLC1A5 to promote glutamine and glucose metabolism in these cells. In summary, the ATF4/SLC1A5 axis plays a significant role in the progression of colorectal cancer by regulating glutamine metabolism and glycolysis.
Acta Biochimica et Biophysica Sinica•2025•DOI: 10.3724/abbs.2024185
Circular RNAs play a pivotal role in the progression of various cancers. In our previous study, we observed high expression of the circRNA MALAT1 (cMALAT1) in intrahepatic cholangiocarcinoma (ICC) cells co-incubated with activated hepatic stellate cells. This study is designed to explore the roles of cMALAT1 and the underlying mechanisms in ICC. We find that cMALAT1 significantly facilitates the progression of ICC both in vitro and in vivo. The binding between cMALAT1 and miR-512-5p is subsequently confirmed through RNA pull-down experiments. As anticipated, the application of miR-512-5p mimics noticeably reverses the cMALAT1 overexpression-induced malignant phenotypes of ICC cells. Furthermore, VCAM1 is identified as a downstream gene of the cMALAT1/miR-512-5p axis. Importantly, silencing of VCAM1 not only effectively suppresses the malignant phenotypes of ICC cells but also significantly impairs the functions of cMALAT1. Our study reveals that cMALAT1 promotes the progression of ICC by competitively binding to VCAM1 mRNA with miR-512-5p, leading to the upregulation of VCAM1 expression and the activation of the PI3K/AKT signaling pathway.
Chinese Traditional and Herbal Drugs•2026•DOI: 10.7501/j.issn.0253-2670.2026.16.20261625
Sterol biosynthesis in Stellaria dichotoma var. lanceolata remains poorly characterized despite the medicinal value of its sterol constituents. This study integrated high-performance liquid chromatography (HPLC) quantification of sterols across root, stem, leaf, and flower tissues with full-length transcriptome sequencing and comparative transcriptomics. A total of 372,483 high-quality full-length transcripts were assembled, of which 128,646 were annotated. Differential expression analysis revealed 43,354 genes shared across all four tissues (50.02% of total genes), with 9,647 differentially expressed genes (DEGs) between root and flower, 12,143 between root and leaf, and only 388 between leaf and stem. Weighted gene coexpression network analysis (WGCNA) identified 43 coexpression modules, and the MEblue module contained six key enzyme genes: NP_NY_transcript_168676 (FPPS), NP_NY_transcript_335811 (SQS), NP_NY_transcript_44001 (SQS), NP_NY_transcript_246835 (CAS), NP_NY_transcript_328932 (CAS), and NP_NY_transcript_183565 (GPPS). RT-qPCR validation confirmed expression trends consistent with transcriptome data. These findings provide a foundation for elucidating the biosynthetic pathway and molecular regulation of sterols in S. dichotoma var. lanceolata.
Chinese Journal of Tissue Engineering Research•2026•DOI: 10.12307/2026.21692
BACKGROUND: Deep learning methods have made breakthrough progress in the field of bone imaging diagnosis. They have overcome the problems of easy misdiagnosis and low efficiency in traditional bone imaging diagnosis methods, and are conducive to the popularization of intelligent diagnosis methods in orthopedics. OBJECTIVE: To review the application, advantages and disadvantages of deep learning in the diagnosis of common bone diseases. METHODS: Literature published from January 2021 to June 2025 on deep learning-assisted skeletal image diagnosis was retrieved from CNKI, WanFang, PubMed, and Web of Science databases. Chinese and English search terms included “artificial intelligence, deep learning, machine learning, computer-aided diagnosis, skeletal imaging, fracture, bone tumor, osteoporosis, osteoarthritis, synovitis, spinal, cartilage, classification, detection, segmentation.” According to the inclusion criteria, 76 articles were finally included in this review. RESULTS AND CONCLUSION: Deep learning models have become powerful tools for bone imaging diagnosis and are gradually gaining recognition from clinicians, improving the efficiency of bone imaging diagnosis. Deep learning technology uses its image feature capture ability to help improve the clinical diagnosis of fractures, bone tumors, osteoporosis, osteoarthritis, synovitis, and spinal lesions, providing a reference for clinical decision-making. Although deep learning diagnostic applications have great potential, they are prone to insufficient model generalization and rely heavily on large amounts of annotated data, which reduces model credibility and hinders clinical translation. Future research should focus on improving the robustness and generalization of deep learning models. In summary, deep learning has certain reference value in clinical bone imaging diagnosis.