Biology subjects

Yue, A.

Publications and source records attributed to Yue, A..

4 recordsLinked to original sources

bioRxiv2026

A Multidimensional Arithmetical Ontology for High-Parameter Cytometry: Gaussian Primes and Cryptographic Hashing for Cell Population Standardization

Background. The rapid expansion of high-dimensional single-cell technologies has outpaced the development of standardized metadata infrastructure. Current text-based nomenclature for cell populations and gating strategies lacks computational rigor, hindering cross-study reproducibility and automated machine learning. Our previous mathematical frameworks, the Prime Population System (PPS) and the Unique Gating Identifier (UGI), proposed arithmetical solutions but were limited by biological fragility (no inherent link between a protein and its structural isoforms) and by computational bottlenecks caused by exponential integer growth. Objective. To develop a scalable, multidimensional arithmetical ontology that unambiguously identifies cell populations and hierarchical gating strategies without biological ambiguity or computational overflow. Methods. We transition the base marker dictionary from the one-dimensional real axis to the complex plane of Gaussian integers (a+bi). The reviewed human proteome of the UniProt Knowledgebase is paired with Gaussian primes satisfying a > b > 0, each list being totally ordered by a key intrinsic to it, so that the pairing is determined by position alone. Each protein receives a contiguous reserved block of 64 primes: slot 0 addresses the protein with isoform unresolved, and slot k addresses UniProt isoform k, the slot index being read directly off the accession. A Bipartite Complex Ontology encodes positive (a+bi) and negative (b+ai) expression states through Conjugate Pair Symmetry. To bypass the 64-bit integer limits of Goedel exponentiation, hierarchical gating sequences are held as vectorized arrays of complex numbers and compressed by SHA-256 deterministic hashing. Results. Pairing against the reference release assigns 53,296 identifiers, 20,431 protein-level and 32,865 isoform-level, with no collisions and no manual curation at any step. Every isoform record in the release resolves under a single rule, including the 329 records whose accession prefix differs from the entry that cites them. The geometric symmetry conserves biological state, distinguishing positive, negative and isoform-resolved expression upon factorization over [Z][i]. Localized vectorization with SHA-256 hashing yields immutable 64-character hexadecimal fingerprints for entire gating strategies, resolving the integer explosion problem. Conclusion. By combining complex plane topology with cryptographic hashing, this framework provides a universally scalable, computationally lightweight and biologically accurate registry system. The ontology eliminates nomenclature ambiguity and opens the way to machine learning interoperability and centralized global cytometry databases.

bioinformatics↗

bioRxiv2026

Multispecific nanobody degraders co-deplete membrane receptors and enable targeted delivery of diverse payloads

Targeting membrane receptors underlies the success of antibody-drug conjugates (ADCs), yet single-receptor formats can be limited by heterogeneous expression, compensatory signaling, and variable internalization. Here we developed Multivalent Interchangeable Nanobody Degradation System (MINDS), a modular nanobody-Fc chassis that co-engages multiple membrane receptors, promotes their lysosomal co-depletion, and enables delivery of diverse intracellular payloads. As a proof of concept, we generated Tritazumab, a trispecific nanobody-Fc targeting three oncogenic receptors EGFR, cMET, and TfR1. Tritazumab incorporates a high-affinity, non-transferrin-competing anti-TfR1 nanobody that drives efficient uptake and lysosomal trafficking, enabling coordinated depletion of all three receptors. Across non-small cell lung cancer models, Tritazumab achieved rapid and sustained multi-receptor surface loss with picomolar degradation potency, reaching near-maximal depletion within approximately 1.5 hours. Conjugation of Tritazumab to MMAE preserved receptor binding and produced substantially greater antiproliferative activity and improved tumor selectivity relative to clinical ADCs in matched cell models, along with potent in vivo tumor growth inhibition and acceptable tolerability in a xenograft model. Extending the platform beyond cytotoxic payloads, a BRD4 molecular glue conjugate improved the selectivity window by > 100-fold and showed marked in vivo efficacy, while an EZH2-targeting PROTAC conjugate achieved an approximately 1,000-fold increase in intracellular degradation potency relative to the free PROTAC. These findings establish MINDS as a modular multispecific degrader-payload platform that integrates receptor co-depletion to enhance anticancer selectivity and efficacy.

cancer biology↗

bioRxiv2019

Identifying differential cell populations in flow cytometry data accounting for marker frequency

We introduce a new cell population score called SpecEnr (specific enrichment) and describe a method that discovers robust and accurate candidate biomarkers from flow cytometry data. Our approach identifies a new class of candidate biomarkers we define as driver cell populations, whose abundance is associated with a sample class (e.g. disease), but not as a result of a change in a related population. We show that the driver cell populations we find are also easily interpretable using a lattice-based visualization tool. Our method is implemented in the R package flowGraph, freely available on GitHub (github.com/aya49/flowGraph) and on BioConductor.

bioinformatics↗

bioRxiv2019

High-throughput phenotyping reveals expansive genetic and structural underpinnings of immune variation

By developing a high-density murine immunophenotyping platform compatible with high-throughput genetic screening, we have established profound contributions of genetics and structure to immune variation. Specifically, high-throughput phenotyping of 530 knockout mouse lines identified 140 monogenic \"hits\" (>25%), most of which had never hitherto been implicated in immunology. Furthermore, they were conspicuously enriched in genes for which humans show poor tolerance to loss-of-function. The immunophenotyping platform also exposed dense correlation networks linking immune parameters with one another and with specific physiologic traits. By limiting the freedom of individual immune parameters, such linkages impose genetically regulated \"immunological structures\", whose integrity was found to be associated with immunocompetence. Hence, our findings provide an expanded genetic resource and structural perspective for understanding and monitoring immune variation in health and disease.

immunology↗