BTC Human
Description
Gene and mRNA Expression
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mRNA variants: Include glycosylated and truncated forms (lacking 12–30 N-terminal residues) with equivalent activity .
Role in Cell Signaling
BTC activates ErbB-1 (EGFR) and ErbB-4 homodimers and heterodimers, inducing mitogenesis in fibroblasts, vascular smooth muscle cells, and retinal pigment epithelial cells . Its unique ability to activate all ErbB receptor combinations distinguishes it from other EGF family ligands .
Key Biological Activities
Expression and Tissue Distribution
Cancer Research and Drug Development
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Personalized Medicine: Patient-derived BTC organoids (PDOs) enable chemotherapy screening. For example:
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Gene Signature Panels: BTC organoid studies identified expression profiles predicting drug responses, aiding in clinical decision-making .
Recombinant BTC Production
Product Specs
DGNSTRSPET NGLLCGDPEE NCAATTTQSK RKGHFSRCPK QYKHYCIKGR CRFVVAEQTP SCVCDEGYIG ARCERVDLFY
Q&A
Basic Research Questions
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What is the metaphysical characterization of Bitcoin in academic ontology?
Contemporary philosophical research establishes Bitcoin as a socially constructed, non-concrete entity that genuinely exists within established ontological frameworks. According to Oxford Academic publications, Bitcoin represents a unique type of abstract object with distinct properties that challenge traditional metaphysical categories .
Philosophical Approach Characterization of Bitcoin Methodological Implications Social Constructivism Socially constructed entity with genuine existence Examines how social consensus creates and maintains value Abstract Object Theory Type of abstract object with distinct properties Provides framework for analyzing non-physical digital assets Mass/Count Distinction Bitcoin-as-substance vs. portions-of-bitcoin Enables consistent theoretical language for scientific analysis The methodological approach treats linguistic and social conventions as informative (though fallible) guides to Bitcoin's ontology, while recognizing that scientific understanding of Bitcoin's societal roles continually refines this framework . Researchers apply this ontological foundation when investigating Bitcoin's properties, individuation, and categorization across disciplines.
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How is Bis(trichloromethyl)carbonate (BTC) characterized in toxicological research?
Bis(trichloromethyl)carbonate (BTC, triphosgene) is characterized in scientific literature as a versatile solid compound used as a phosgene substitute in research and small-scale production . Despite its solid state offering apparent advantages, research emphasizes the misconception of labeling it as "safe phosgene" .
Property Scientific Characterization Research Methodology Physical State Solid (contrasted with gaseous phosgene) Specialized solid-state handling protocols with recognition of vapor hazards Toxicity Profile Highly toxic with sufficient vapor pressure for dangerous exposure Development of specialized monitoring techniques for laboratory settings Research Applications Small-scale phosgenations in R&D environments Implementation of extended phosgene safety protocols with additional considerations Safety Framework Increasingly regulated due to toxicological concerns Integration of regulatory requirements into experimental design and protocols Research methodologies for BTC involve developing stringent safety protocols that extend beyond those used for phosgene itself, recognizing BTC's unique properties while acknowledging its intrinsic connection to phosgene toxicity . This approach enables researchers to harness BTC's synthetic utility while implementing appropriate safeguards.
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What are the primary environmental impact dimensions of Bitcoin mining in current research?
United Nations research has expanded beyond carbon footprint to include comprehensive environmental impact assessments across multiple dimensions for Bitcoin mining . Scientists have developed methodologies to quantify three primary impact categories:
Environmental Dimension Research Findings Methodological Approach Carbon Footprint Top 10 mining countries responsible for 92-94% of global impact Country-specific energy source analysis mapped to mining activity distribution Water Footprint Significant variations based on electricity generation sources Quantification of water usage in electricity production chains for mining operations Land Footprint Different country rankings compared to carbon metrics Assessment of land use requirements for energy infrastructure supporting mining Research methodology involves country-specific impact assessments that account for different energy sources, revealing that countries like Norway, Sweden, Thailand, and the United Kingdom appear in top contributors for water or land impacts despite not being major carbon contributors . This multi-dimensional approach provides a more comprehensive understanding of Bitcoin's environmental footprint.
Advanced Research Questions
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How are graph neural networks applied to Bitcoin transaction analysis for anti-money laundering research?
Graph neural networks (GNNs) represent the cutting-edge approach to Bitcoin transaction analysis in anti-money laundering (AML) research . The methodology involves constructing and analyzing transaction graphs with temporal properties:
Research Component Technical Specifications Methodological Approach Dataset Scale 252 million nodes, 785 million edges High-performance all-in-memory graph engines for processing massive datasets Temporal Annotation All nodes and edges timestamped for sequential analysis Temporal graph analysis techniques to identify evolving patterns Supervised Learning 34,000 nodes annotated with entity types, 100,000 addresses with entity names/types Multi-class classification models for entity recognition in transaction networks Technical Challenges 200GB blockchain data, heterogeneous neighbor distribution Specialized feature engineering to address graph structure heterogeneity Researchers address two major challenges: managing the massive Bitcoin blockchain size and handling the heterogeneous graph structure where transactions can have varying numbers of neighbors . This research enables identification of patterns associated with illicit activities while accounting for the complexity of legitimate transaction networks , providing valuable tools for regulatory compliance.
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What experimental design methodologies are optimal for testing hypotheses about Bitcoin network interactions?
While direct Bitcoin experimental design literature is limited, methodological approaches from complex systems research can be adapted to Bitcoin studies . The experimental design methodology involves:
Design Component Scientific Approach Application to Bitcoin Research Model Selection Non-parametric models avoiding strong assumptions on joint action Models of Bitcoin network interactions without presupposing specific behavioral patterns Design Optimization Minimize variability while maximizing information extraction Efficient allocation of computational resources in Bitcoin network simulations Statistical Testing Robust F-tests to detect departures from expected interaction behaviors Detection of anomalous patterns in Bitcoin transaction networks and market dynamics Sample Size Determination Balance of statistical power and computational feasibility Optimization of data collection in computationally intensive Bitcoin research scenarios These methodological approaches can be applied to study complex interactions within Bitcoin networks, particularly when examining hypotheses about network effects, market behavior, or transaction patterns . The methods prioritize designs that extract maximum information while minimizing resource requirements.
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How do researchers quantify geographical distribution in Bitcoin's environmental impact assessment?
Researchers quantify the geographical distribution of Bitcoin's environmental impact through multi-dimensional assessment frameworks that account for regional differences in energy production . The methodology involves:
Methodological Component Scientific Approach Research Findings Regional Energy Mapping Link Bitcoin mining activity to country-specific energy production profiles Different environmental impact profiles based on regional energy generation sources Multi-dimensional Assessment Separate quantification of carbon, water, and land impacts Country rankings change significantly depending on which impact category is analyzed Impact Concentration Analysis Identification of top contributing countries across metrics Top 10 countries responsible for 92-94% of global environmental footprints Equity Implications Analysis of beneficiaries versus affected populations Transboundary and transgenerational impact assessments reveal justice implications Research findings demonstrate that rankings of countries change significantly depending on which environmental metric is considered . This methodology reveals nuanced environmental impacts that would be missed by carbon-only analyses and provides a foundation for developing evidence-based policy recommendations.
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What methodological approaches are used for entity-centric information extraction from Bitcoin-related video content?
Entity-centric information extraction from Bitcoin-related video content utilizes advanced multimodal analysis techniques that bridge computer vision and natural language processing . The methodology involves:
Methodological Component Technical Approach Research Application Question-worthy Information Identification Deep learning models for content relevance assessment Identifying significant Bitcoin-related information in video sequences Entity Linking Natural language processing and entity recognition systems Connecting extracted information to specific Bitcoin entities and concepts Multimodal Signal Integration Combined processing of visual, audio, and textual information Comprehensive understanding of Bitcoin content across communication modalities Information-seeking Question Generation Neural models trained on question-answer patterns Creation of entity-centric questions about Bitcoin for learning systems and search applications This research has applications in video-based learning about Bitcoin, recommending "People Also Ask" questions as seen in search engines (Fig. 1 in source material), developing video-based chatbots, and enabling fact-checking systems . The approach addresses limitations of previous question generation systems that focused primarily on common objects rather than specific entities.
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What statistical and economic modeling approaches are applied to analyze Bitcoin as a potential economic bubble?
Research analyzing Bitcoin as a potential economic bubble employs various statistical and economic modeling approaches documented in prestigious economic journals . The methodology includes:
Methodological Approach Research Application Key Findings Price Manipulation Analysis Examination of market vulnerabilities in cryptocurrency exchanges Evidence of manipulation during the Mt. Gox bitcoin theft period Correlation Studies Analysis of price movements relative to other cryptocurrencies and market activities Approximately half of Bitcoin's 2017 price increase associated with Tether trading at Bitfinex exchange Economic Bubble Models Application of established economic frameworks to cryptocurrency valuation Multiple Nobel laureates (Stiglitz, Heckman, Krugman) characterize Bitcoin as exhibiting bubble properties Narrative Epidemic Modeling Characterization of price growth dynamics through social transmission Price dynamics described as driven by "contagious narratives" (Shiller) Intrinsic Value Assessment Evaluation of fundamental value proposition in economic terms Characterized as a "pure bubble" with zero intrinsic value (Tirole, 2024) These methodological approaches demonstrate the application of established economic and statistical frameworks to cryptocurrency markets . Research findings indicate vulnerability to manipulation and bubble-like characteristics, though some economists note the possibility of Bitcoin becoming a long-lasting bubble similar to gold or fiat currencies .
Product Science Overview
Human Betacellulin is encoded by the BTC gene located on chromosome 4 . The mature form of BTC is a heparin-binding protein composed of 80 amino acid residues . The recombinant human Betacellulin protein is typically produced in E. coli and has a molecular weight of approximately 9.9 kDa . The protein is highly pure, with a purity greater than 97% as determined by SDS-PAGE .
Betacellulin is known for its ability to bind to and activate the ErbB family of receptor tyrosine kinases, including EGFR/ErbB1, HER2/ErbB2, HER3/ErbB3, and HER4/ErbB4 . This interaction results in the activation of downstream signaling pathways such as the PI3K and Erk pathways, which are crucial for cell proliferation and survival .
Betacellulin has been extensively studied for its role in the proliferation of pancreatic beta cell lines in vitro . Research has shown that BTC can induce beta cell regeneration and increase insulin secretion in rodent models of diabetes . This makes it a promising candidate for therapeutic applications in diabetes treatment.
Recombinant human Betacellulin is produced in a carrier-free form, which means it does not contain Bovine Serum Albumin (BSA) as a carrier protein . This enhances the protein’s stability and shelf-life, making it suitable for various applications, including cell or tissue culture and ELISA standards . The protein is typically lyophilized from a filtered solution in PBS with Trehalose and can be reconstituted at 100-500 μg/mL in PBS . It is stable for up to 12 months when stored at -20 to -70°C .
