MIA Human

What is Melanoma Inhibitory Activity (MIA) protein and its significance in human research?

Melanoma Inhibitory Activity (MIA) protein serves as a clinically valuable biomarker in malignant melanoma patients, particularly for diagnosing metastatic melanoma stages III and IV. Structurally, MIA adopts an SH3 domain-like fold in solution, characterized by two perpendicular, antiparallel three- and five-stranded β-sheets. Unlike typical SH3 domain structures, MIA is a single-domain protein with an additional antiparallel β-sheet and two disulfide bonds. Notably, MIA was identified as the first extracellular protein to exhibit the SH3 domain-like fold, representing a significant structural discovery .

How does MIA protein function in human cellular contexts?

MIA protein interacts with fibronectin in the extracellular matrix, with peptide ligands identified for MIA displaying sequence similarity to type III human fibronectin repeats. This interaction appears particularly pronounced with FN14, which is located near an integrin α binding site. The invasive potential of melanoma cell lines (such as Mel Im) has been shown to be inhibited by recombinant human MIA (rhMIA) by approximately 45.6% ± 3.1%, demonstrating that the recombinant protein exhibits biological activity comparable to native MIA .

What is the Mixed-Initiative Annotation (Mia) platform in human-AI research?

Mia is a web-based platform designed to facilitate real-time, interactive work experiences between human researchers and machine learning models. The platform enables researchers to engineer human-AI interaction through a REST API and embedded web interface, creating task interfaces that collaborative interface agents can both observe and contribute to simultaneously. This technological approach supports mixed-initiative research, particularly in annotation tasks where humans and AI systems work cooperatively .

What is Maternal Immune Activation (MIA) in human neurodevelopmental research?

Maternal Immune Activation refers to the activation of the maternal immune system during critical gestational windows, which has been correlated with long-term neurodevelopmental deficits in offspring. Research has established associations between MIA and increased risk for neurodevelopmental disorders such as autism spectrum disorder (ASD). Interleukin 6 (IL-6) derived from the gestational parent has been identified as one of the major molecular mediators through which MIA alters developing brain structures and functions .

How is the structure of human MIA protein determined experimentally?

The three-dimensional structure of recombinant human MIA in solution is determined through multi-dimensional NMR spectroscopy. This approach involves collecting and analyzing:

• 1139 approximate inter-residue distance constraints derived from NOESY (nuclear Overhauser and exchange spectroscopy) spectra

• 22 dihedral constraints

• 12 hydrogen bond constraints

• 15N-T₂, 15N{¹H}-NOE and 15N(dipole-CSA) cross-correlation rate experiments to determine dynamic properties

The global fold is uniquely defined due to the large number of non-redundant NOEs, and structures are calculated using simulated annealing protocols implemented in X-PLOR .

How is the Mia platform implemented for facilitating human-AI collaborative research?

The Mia platform is implemented using MeteorJS, MongoDB, and React, providing researchers with three key components:

• API hooks for activity observability: These operate on the Datagram Delivery Protocol (DDP) and allow applications to both listen for activity and contribute to ongoing tasks.

• Annotation interface: This includes an annotation surface where annotations are rendered, an annotation assignment tool that human annotators use to assign labels, and an annotation panel displaying information.

• Experimental task design module: This facilitates designing and deploying mixed-initiative tasks through defining projects with image sets, task designs, and experimental instrumentation .

How are human brain organoid models developed to study Maternal Immune Activation?

Human brain organoid models of MIA utilize induced pluripotent stem cell-derived dorsal forebrain organoids treated with Hyper-IL-6 (a constitutively active form of IL-6). The experimental approach includes:

• Validation that the organoids express the necessary molecular machinery to respond to Hyper-IL-6

• Confirmation of STAT signaling activation upon treatment

• RNA sequencing analysis to identify gene expression changes

• Immunohistochemistry and single-cell RNA-sequencing to analyze cellular composition alterations

• Long-term evaluation of cortical layering as a consequence of Hyper-IL-6 exposure

How are structural data of human MIA analyzed to determine protein dynamics?

Protein dynamics of human MIA are analyzed through multiple parameters:

These measurements revealed that residues Met1–Leu7 lack a compact fold, while residues Tyr69–Ala75 exhibit increased flexibility with 15N{¹H}-NOE values <0.6 and elevated 15N-T₂ values. Additionally, decreased η × T₂ values for residues D68–A75 suggest slow motions in this region .

What approaches are used to analyze human-AI interaction data in Mia-based studies?

Human-AI interaction data analysis in Mia studies involves multiple analytical approaches:

• Correlation analysis between participant characteristics (e.g., altruism scores) and behavioral measures (e.g., frequency of providing help to AI)

• Statistical significance testing to identify differences in performance metrics across experimental conditions

• Analysis of self-reported measures in relation to observed behaviors

A feasibility study revealed several insights, including:

• Participants' altruism scores did not correlate with how frequently they provided help to the AI agent (p = .88)

• Altruism scores positively correlated with agreement levels to feeling good when providing help (p = .03)

• Participants working alongside AI with bidirectional help were significantly more accurate when self-reporting higher productivity (p = .03)

• Participants who could only observe but not interact with AI annotated significantly faster than other participants (p = .04)

How are transcriptomic data analyzed in human brain organoid models of MIA?

Transcriptomic analysis of human brain organoids exposed to Hyper-IL-6 involves several analytical approaches:

Single-cell RNA-sequencing also revealed a small increase in the proportion of radial glia cells after Hyper-IL-6 treatment, with these cells exhibiting the most pronounced transcriptional changes .

How do the structural features of MIA protein relate to its biological function?

The SH3 domain-like fold of MIA has significant implications for its biological activities. Unlike typical SH3 domains, which are commonly found in intracellular signaling proteins, MIA represents the first extracellular protein identified with this structural fold. The structural analysis reveals two disulfide bonds (Cys13-Cys18 and Cys36-Cys107) that contribute to MIA's stability in the extracellular environment.

Phage display screening identified a high percentage of clones carrying heptapeptides with multiple prolines - out of 40 isolated and sequenced clones, 11 (27.5%) contained two or more prolines. This is significant because:

• SH3 domains typically bind proline-rich sequences

• The peptide ligands identified show sequence similarity to type III human fibronectin repeats

• This structural relationship suggests MIA may function by interfering with fibronectin-integrin interactions

What methodological challenges exist in evaluating human-AI collaborations through the Mia platform?

Research using the Mia platform reveals several methodological challenges in human-AI collaboration studies:

• Discrepancies between self-reported traits and observed behaviors: Although participants' altruism scores did not correlate with how frequently they actually provided help to the AI agent, these scores did correlate with self-reported positive feelings about providing help.

• Complex interaction between perceived productivity and actual performance: Participants who could work alongside and interact bidirectionally with the AI were significantly more accurate when they felt more productive.

• Observational effects without direct interaction: Participants who could only observe but not interact with the AI annotated significantly faster, suggesting complex dynamics in human-AI observational learning.

These findings indicate that designing effective human-AI collaborative systems requires sophisticated methodological approaches that account for both behavioral and psychological dimensions of human-AI interaction .

What are the molecular consequences of Maternal Immune Activation in human brain organoid models?

Human brain organoid models reveal complex molecular consequences of MIA:

• Upregulation of major histocompatibility complex class I (MHCI) genes after Hyper-IL-6 exposure, which have been implicated in autism spectrum disorder development.

• Cell-type specific effects with radial glia cells showing the most pronounced transcriptional changes, including downregulation of genes related to protein translation, consistent with findings from mouse models of MIA.

• Identification of differentially expressed genes not found in mouse models, suggesting species-specific responses to MIA that may be unique to human neurodevelopment.

• Long-term consequences including abnormal cortical layering, providing insight into how early immune activation might lead to neurodevelopmental alterations associated with conditions like ASD .

How should bioassays be designed to validate recombinant human MIA activity?

Effective validation of recombinant human MIA requires multiple complementary approaches:

• Boyden Chamber assays to test biological activity by measuring the inhibition of invasive potential in melanoma cell lines (e.g., Mel Im).

• Phage display screening to identify peptide interactions, with special attention to proline-rich sequences that typically interact with SH3 domains.

• Comparative analysis between recombinant and native MIA to ensure functional equivalence.

• Structural validation through NMR spectroscopy to confirm proper folding and formation of disulfide bonds (Cys13-Cys18 and Cys36-Cys107) .

What design elements are critical for effective mixed-initiative annotation experiments?

Successful mixed-initiative annotation experiments using the Mia platform require careful consideration of:

• Task definition and division: Clearly defining how workload will be distributed between human and AI annotators, including interface design elements that facilitate this division.

• Experimental conditions design: Creating appropriate comparative conditions to evaluate different interaction modalities (e.g., observation-only vs. help-giving vs. help-seeking).

• Comprehensive data collection: Integrating questionnaires at various stages (before, during, and after tasks) alongside time-stamped telemetry information to track user interface activity.

• Balanced task complexity: Designing tasks that are sufficiently challenging to benefit from collaboration while remaining accessible to human annotators .

What validation steps are necessary for human brain organoid models of MIA?

Robust validation of human brain organoid models of MIA requires several critical steps:

• Verification that organoids express the molecular machinery necessary for responding to Hyper-IL-6, the experimental activator.

• Confirmation of downstream signaling activation (e.g., STAT signaling) upon Hyper-IL-6 treatment to ensure the model recapitulates expected molecular responses.

• Characterization of cellular composition through multiple methodologies (immunohistochemistry and single-cell RNA-sequencing) to identify cell type-specific effects.

• Assessment of long-term developmental consequences, particularly cortical layering abnormalities, to establish the model's relevance to neurodevelopmental disorders.

• Comparative analysis with existing MIA models (e.g., mouse models) to identify both conserved and species-specific responses .

How can structural insights into human MIA inform therapeutic development?

The structural characterization of human MIA protein opens several avenues for therapeutic development:

• Target identification based on MIA-fibronectin interactions, potentially leading to new approaches for inhibiting melanoma progression.

• Design of peptide-based inhibitors leveraging the identified binding preferences of MIA, particularly those with proline-rich motifs identified through phage display.

• Structure-based drug design targeting the unique features of MIA's SH3 domain-like fold, including its additional antiparallel β-sheet and two disulfide bonds.

• Development of diagnostic applications based on MIA's role as a biomarker for metastatic melanoma stages III and IV .

How might the Mia platform evolve to support broader human-AI research applications?

The Mia platform shows potential for expansion in several directions:

• Integration with diverse machine learning models beyond image annotation tasks, supporting a wider range of collaborative scenarios.

• Extension to additional annotation tasks, such as video annotation with bounding boxes and other complex data types.

• Development of more sophisticated help mechanisms to study different modes of human-AI interaction beyond the current observational and direct assistance modalities.

• Support for more complex team configurations, including human teams and hybrid intelligence teams where humans and AI systems complement each other's capabilities .

What are the translational potentials of human brain organoid MIA models?

Human brain organoid models of MIA offer several translational opportunities:

• Mechanistic understanding of how maternal immune activation contributes to neurodevelopmental disorders, potentially identifying intervention targets.

• Screening platform for therapeutics that might mitigate the effects of maternal immune activation on fetal brain development.

• Identification of biomarkers associated with MIA-induced developmental alterations that could inform clinical diagnostics.

• Comparative studies with other models to understand species-specific responses, potentially explaining why some findings in animal models don't translate to humans.

• Investigation of the role of major histocompatibility complex class I (MHCI) genes in neurodevelopmental disorders like ASD, building on the observation of their upregulation following Hyper-IL-6 exposure .