CNN3 Antibody
- Known as:
- CNN3 Antibody
- Catalog number:
- 36018
- Product Quantity:
- USD
- Category:
- -
- Supplier:
- Signalway
- Gene target:
- CNN3 Antibody
Related genes to: CNN3 Antibody
- Gene:
- CNN3 NIH gene
- Name:
- calponin 3
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 1p21.3
- Locus Type:
- gene with protein product
- Date approved:
- 1996-08-16
- Date modifiied:
- 2016-10-05
Related products to: CNN3 Antibody
Related articles to: CNN3 Antibody
- Trophoblast cell fusion is a vital developmental process that enables the formation of the multinucleated syncytiotrophoblast (STB), which plays a central role in placental function and maternal-fetal exchange. Fusion defects in this lineage are closely associated with pregnancy complications such as preeclampsia (PE) and fetal growth restriction (FGR). Although the fusion of trophoblasts is a highly coordinated event, it involves multiple interdependent steps, including transcriptional programming, membrane remodeling, cytoskeletal rearrangement, metabolic adaptation, and immune regulation. Recent studies have uncovered critical molecular mediators at each of these levels. Transcription factors such as Glial cells missing transcription factor 1(GCM1), Krüppel-like factor 6(KLF6), and Transcription factor EB(TFEB) govern differentiation timing; fusion proteins, including Syncytin-1/2 and Mfn2, facilitate membrane merger; polarity regulators and actin-associated proteins like Par6 and CNN3 organize cytoskeletal architecture; metabolic reprogramming, particularly a shift from oxidative phosphorylation to glycolysis, supplies energy and biosynthetic precursors; and immune modulators such as pregnancy-induced factor 1 and Interleukin-10(IL-10) ensure a permissive environment for fusion at the maternal-fetal interface. Epigenetic mechanisms, including DNA methylation and histone modifications, further fine-tune the expression of fusion-related genes. Alongside mechanistic discoveries, a wide range of experimental models has been developed to investigate trophoblast fusion in vitro. These include traditional monolayer cell lines (e.g., BeWo), primary human trophoblasts, placental explants, trophoblast stem cells, and trophoblast organoids. Each model system provides distinct advantages in recapitulating aspects of syncytialization and placental physiology. Moreover, the integration of multi-omics technologies-such as single-cell and spatial transcriptomics, proteomics, metabolomics, and epigenomics-has expanded our understanding of the spatiotemporal dynamics and molecular complexity underlying trophoblast fusion. Despite these advances, several key challenges remain unresolved, including the lack of models that fully recapitulate the structural and functional features of the human maternal-fetal interface and the limited understanding of posttranslational and spatiotemporal regulatory mechanisms. Addressing these gaps will be essential for translating basic insights into diagnostic and therapeutic innovations for placental diseases. - Source: PubMed
Xiong YanDing Yu-Bin - Atherosclerosis (AS) is a complex pathophysiological process. Evidence has demonstrated that abnormal proliferation and migration of vascular smooth muscle cells (VSMCs) play an essential role in AS. Calponin 3 (CNN3) is implicated in the pathogenesis of various diseases by modulating cell proliferation and migration. However, the roles of CNN3 in VSMCs and AS remains elusive. Experiments were performed in tissues and in vitro to investigate the role of CNN3 in the pathophysiology of AS. The expression of CNN3 in aortic plaques was determined using immunohistochemistry, and the serum CNN3 levels were quantified by enzyme-linked immunosorbent assay (ELISA). The diagnostic potential of CNN3 was evaluated by receiver operating characteristic (ROC) curve analysis. To in vitro functions of CNN3 were analyzed by EdU assays, CCK-8 assays, scratch wound assays, transwell assays, qRT-PCR and western blotting analyses. In this study, we demonstrated CNN3 was significantly upregulated in plaques compared to normal intima tissue. Patients with coronary artery disease were found to have higher CNN3 levels than healthy individuals and was positively correlated with the SYNTAX score of patients. The ROC curve for CNN3 as a diagnostic biomarker reached 0.787. In vitro experiments showed that CNN3 promoted VSMCs proliferation and migration by β-catenin signaling pathway. All the data indicated that CNN3 promoted VSMCs proliferation and migration by modulating the β-catenin signaling to accelerate the AS process. Serum level of CNN3 serves as a promising diagnostic biomarker for AS. - Source: PubMed
Publication date: 2026/03/28
Zhang Ru-YiWu Chang-MengChen Juan-JiangLi Liang-XingPang Shu-Yin - Angiogenesis plays a pivotal role in driving tumour progression, including tumour growth, local invasion, and distant metastasis. Calponin 3 (CNN3) belongs to the actin-binding protein family and has been shown to be aberrantly expressed in osteosarcoma specimens, but its exact role in the regulation of angiogenesis remains unknown. This study aimed to investigate the function and underlying mechanism of CNN3 in osteosarcoma angiogenesis. - Source: PubMed
Publication date: 2026/02/13
Sun DongDai FeiXiang BinqingWang HengTao HaiyanZhang ShuaiTao XiaoliangZhu XianjieLuo FeiSong Lei - To address the current challenges of low single-sensor recognition accuracy for coal and rock cutting states, redundant channel feature responses, and poor performance in traditional neural network models, this paper proposes a new multi-sensor coal and rock cutting state recognition model based on a graph neural network (GNN). This model, consisting of a feature encoder, an information exchange module, and a feature decoder, enhances the communication of feature responses between filters within the same layer, thereby improving feature capture and reducing channel redundancy. Comparative, ablation, and noise-resistance experiments on multi-sensor datasets validate the effectiveness, versatility, and robustness of the proposed model. Experimental results show that compared to the baseline models, CNN3, ResNet, and DenseNet achieve improvements of 2.47%, 2.78%, and 1.50%, respectively. With the addition of the ACI block, the ResNet model achieves the best noise-resistance performance, achieving an accuracy of 93.27% even in 6 dB noise, demonstrating excellent robustness. Embedded deployment experiments further confirmed that the proposed model maintains an inference time of less than 216.1 ms/window on the NVIDIA Jetson Nano, meeting the real-time requirements of actual industrial scenarios and demonstrating its broad application prospects in resource-constrained underground working environments. - Source: PubMed
Publication date: 2025/11/07
Jin ZhixinCheng JieCao WenyanWang HongweiZhang JiaxinLiu ZepingWang HaoranLi Jianzhong - Contractile actomyosin bundles, stress fibers, are important for cell migration, adhesion, morphogenesis, and mechanosensing. Calponin (CNN) family proteins are abundant stress fiber components, but their cellular functions and isoform-specific roles remain poorly understood. By depleting the three CNN isoforms (calponin-1 [CNN1], calponin-2 [CNN2], and calponin-3 [CNN3]) individually and collectively from U2OS cells, we show that CNNs are not negative regulators of myosin II, as previously suggested. Instead, we reveal that CNNs are critical regulators of stress fiber organization that control the distribution of actin filament cross-linker, α-actinin, along actomyosin bundles. Consequently, loss of CNNs dramatically reduced stress fiber thickness, increased their fragility, and impaired cell migration. Notably, we also identify isoform-specific roles for CNNs. The non-muscle CNN isoform CNN3 displays rapid turnover in stress fibers, enabling their dynamic remodeling, whereas the smooth-muscle isoform CNN1 exhibits stable association with stress fibers, supporting the formation of "smooth-muscle-like" thick and static actomyosin bundles. Our findings highlight CNNs as key regulators of stress fiber architecture, cell migration, and morphogenesis and provide new insights into the functional diversity of smooth-muscle and non-muscle CNN isoforms. - Source: PubMed
Publication date: 2025/11/25
Kokate Shrikant BOshin Afsana TChua Xiang LeChastney MeganBiswas ParijatKogan KonstantinTomberg TeemuIvaska JohannaLappalainen Pekka