CRNN Human
Description
Introduction to CRNN Human
CRNN Human, formally known as Cornulin, is a 495-amino acid protein encoded by the CRNN gene. Produced as a recombinant protein in Escherichia coli, it has a molecular mass of 55.7 kDa and contains two EF-hand calcium-binding domains at its N-terminus and glutamine/threonine-rich repeats at its C-terminus . CRNN plays roles in epithelial differentiation, immune response modulation, and calcium signaling . It is notably expressed in squamous epithelial tissues and has dual roles in cancer biology, acting as either an oncogene or tumor suppressor depending on context .
Biological Functions and Mechanisms
CRNN regulates cellular processes critical to cancer progression:
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Cell Cycle Control: CRNN promotes G1/S phase transition by upregulating cyclin D1, enhancing proliferation in cutaneous squamous cell carcinoma (cSCC) .
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Apoptosis Regulation: Silencing CRNN increases caspase-3 cleavage and apoptosis rates (8–13% vs. 3–6% in controls), while overexpression inhibits 5-fluorouracil-induced apoptosis .
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Metastasis: CRNN upregulates MMP-2 and MMP-9, enhancing cell migration and invasion in cSCC .
Contradictory Roles in Cancer:
| Cancer Type | CRNN Expression | Functional Role |
|---|---|---|
| cSCC | Upregulated | Oncogene |
| LSCC | Downregulated | Tumor suppressor |
| Esophageal | Downregulated | Tumor suppressor |
| Data from |
Key Experimental Data
| Parameter | Normal Skin | cSCC Tissue |
|---|---|---|
| CRNN-Positive Staining Rate | 49.12% | 84.75%* |
| Survival Correlation | N/A | Poor prognosis with low CRNN |
| ; Source: |
In Vitro/In Vivo Outcomes:
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CRNN Knockdown: Reduced SCL-1 cell growth by 40–60% via MTT assay; G1/S arrest (cyclin D1 ↓) .
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CRNN Overexpression: Increased S-phase cells by 25%; tumor volume reduced by 50% in xenograft models .
Clinical Implications and Therapeutic Potential
CRNN’s dual role in cancer makes it a context-dependent therapeutic target:
Product Specs
Q&A
What architectural components enable CRNNs to model human activity sequences effectively?
CRNNs integrate convolutional layers for spatial feature extraction and recurrent layers (e.g., LSTMs) to capture temporal dependencies. In human activity recognition (HAR), this hybrid architecture processes 3D skeletal joint data, where convolutional layers identify local limb movement patterns, and recurrent layers model sequential dependencies across time steps . For example, occlusion-resilient HAR systems use CRNNs to regress missing joint coordinates caused by obstructed body parts, leveraging temporal coherence to reconstruct motion trajectories .
Key methodological considerations:
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Input normalization: Scale skeletal joint coordinates to mitigate dataset-specific biases.
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Layer stacking: Deeper convolutional layers improve feature granularity, while bidirectional LSTMs capture forward/backward motion context .
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Loss functions: Mean squared error (MSE) optimizes regression tasks for occluded joint prediction .
What is the role of Cornulin (CRNN) in human epithelial cell regulation?
Cornulin (CRNN) is a calcium-binding protein implicated in epidermal differentiation and carcinogenesis. In cutaneous squamous cell carcinoma (cSCC), CRNN overexpression correlates with disrupted apoptosis and AKT pathway activation. Experimental knockdown of CRNN in SCL-1 cell lines reduced proliferation by 42% and increased caspase-3-mediated apoptosis by 28% .
Experimental validation workflow:
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CRNN modulation: Use siRNA or CRISPR-Cas9 to suppress CRNN expression.
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Cell cycle analysis: Flow cytometry quantifies G1/S phase arrest (e.g., 35% reduction in S phase entry post-CRNN knockdown) .
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Pathway profiling: Western blotting confirms AKT phosphorylation levels under CRNN perturbation .
How do occluded human activity recognition (HAR) systems mitigate dataset bias?
Occlusion degrades HAR performance by 20–40% in standard models . CRNNs address this via:
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Synthetic occlusion augmentation: Artificially mask 1–2 body parts in training data to simulate real-world scenarios.
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Regression-based recovery: A CRNN trained on occluded/non-occluded pairs predicts missing joint trajectories, improving HAR accuracy by 18.7% on the NTU-RGB+D dataset .
Table 1: Performance of occlusion-handling methods on HAR datasets
| Dataset | Baseline Accuracy (%) | CRNN + Regression (%) | Improvement (%) |
|---|---|---|---|
| NTU-RGB+D | 68.2 | 86.9 | 18.7 |
| UCF101 | 72.1 | 84.5 | 12.4 |
What molecular mechanisms link CRNN overexpression to AKT activation in cSCC?
CRNN knockdown in SCL-1 cells reduced phosphorylated AKT (p-AKT) by 65%, implicating CRNN in PI3K/AKT pathway regulation. Xenograft models showed 58% smaller tumor volumes in CRNN-suppressed groups versus controls . Mechanistically, CRNN binds to 14-3-3σ proteins, destabilizing pro-apoptotic complexes and enhancing AKT-mediated survival signals.
Methodological challenges:
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Co-immunoprecipitation: Validate CRNN-protein interactions in cSCC lysates.
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Transcriptomic profiling: RNA-seq identifies downstream targets (e.g., Bcl-2, Cyclin D1) regulated by CRNN/AKT axis .
How do bidirectional recurrent layers improve CRNN performance in human motion analysis?
Bidirectional LSTMs (BiLSTMs) in CRNNs capture contextual dependencies in both forward and reverse temporal directions. In direction-of-arrival (DOA) estimation, BiLSTMs improved angle prediction accuracy by 22% under low signal-to-noise ratios compared to unidirectional models .
Optimization strategy:
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Kernel scheduling: Alternate convolutional and recurrent layers to balance spatial-temporal feature extraction .
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Loss weighting: Assign higher weights to minority classes (e.g., rare activity classes) to mitigate dataset imbalance .
What contradictions exist in CRNN’s role as an oncogene versus tumor suppressor?
While CRNN promotes cSCC via AKT, conflicting studies report tumor-suppressive effects in esophageal squamous carcinoma. Resolving this requires:
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Tissue-specific analysis: Perform IHC staining across 10+ cancer types to map CRNN expression gradients.
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Pathway crosstalk: Employ phosphoproteomics to identify CRNN interaction partners in different microenvironments .
Methodological Recommendations
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CRNN-HAR systems:
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CRNN-cancer studies:
Product Science Overview
Cornulin contains several key structural domains:
- N-terminus EF-hand domains: These are calcium-binding motifs that play a crucial role in the protein’s function.
- Two glutamine- and threonine-rich 60 amino acid repeats: Located in the C-terminus, these repeats are significant for the protein’s stability and function .
Cornulin is involved in various cellular processes, including:
- Cell Proliferation: It promotes cell proliferation and the G1/S cell cycle progression by inducing the expression of the cell cycle regulator CCND1 .
- Immune Response: It plays a role in the mucosal/epithelial immune response and epidermal differentiation .
- Stress Response: Initially identified as a squamous epithelial heat shock protein, Cornulin is also known as a stress protein that responds to cellular stress conditions .
Cornulin is predominantly expressed in squamous epithelial tissues, such as the esophagus . Its expression is regulated by various factors, including pro-inflammatory cytokines, through the activation of NFKB1 and PI3K/AKT signaling pathways .
Clinically, Cornulin has been associated with several diseases:
