Biology subjects

Chen, D.

Publications and source records attributed to Chen, D..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Dissociable reactivation during NREM and REM sleep supports memory consolidation and emotional dissipation

Sleep is critical for memory consolidation and emotional regulation, yet the respective roles of non-rapid eye movement (NREM) and rapid eye movement (REM) sleep remain unclear. Here, using a within-subject crossover design, we recorded high-density electroencephalography (EEG) across two experimental nights while participants viewed neutral or aversive film clips in a counterbalanced order. Combining with daytime functional localizers establishing neural patterns of aversive vs. neutral emotional processing, multivariate pattern analysis revealed that the reactivation of aversive vs. neutral memory during nocturnal sleep was both stage-dependent and event-specific. In NREM sleep, valence-specific reactivation was time-locked to slow oscillation (SO)-spindle complexes but not to either event alone; in REM sleep, reactivation occurred selectively during phasic REM periods marked by rapid eye movements. Critically, NREM SO-spindle coupling percentage was associated with consolidation of temporal memories; whereas phasic REM reactivation strength was linked to overnight dissipation of negative affect. Our findings provide direct evidence that sleep reprocesses emotional experiences through dissociable stage- and event-specific mechanisms, laying out a framework for future targeted sleep-based interventions.

neuroscience↗

bioRxiv2026

Suppression of RIPK3 by EZH2 contributes to cigarette smoking-induced chemoresistance in lung cancer

Lung cancer remains the leading cause of cancer-related mortality worldwide, with cigarette smoking (CS) representing its primary risk factor. In addition to promoting tumorigenesis, chronic CS exposure contributes to chemotherapy resistance, although the underlying mechanisms remain poorly understood. Here, we established a long-term CS exposure model by repeatedly treating Lewis lung carcinoma (LLC) cells with cigarette smoke extract (CSE). After 4 months of exposure, CSE-treated cells exhibited enhanced proliferation, migration, and resistance to chemotherapy-induced cell death. Mechanistically, chronic CSE exposure suppressed receptor-interacting protein kinase 3 (RIPK3) expression by upregulating the epigenetic regulator enhancer of zeste homolog 2 (EZH2), which promoted repressive histone methylation at the RIPK3 promoter. Loss of RIPK3 impaired chemotherapy-induced cell death primarily by inhibiting ferroptosis rather than necroptosis. Importantly, genetic depletion or pharmacological inhibition of EZH2 restored RIPK3 expression and sensitized lung cancer cells to gemcitabine treatment both in vitro and in vivo. Furthermore, analysis of human lung cancer datasets revealed an inverse correlation between EZH2 and RIPK3 expression, with RIPK3 levels progressively decreasing with smoking history. Collectively, these findings identify the EZH2/RIPK3 axis as a critical mediator of smoking-associated chemoresistance and uncover a previously unrecognized role for RIPK3 in ferroptosis regulation. Targeting EZH2-mediated RIPK3 suppression may represent a promising therapeutic strategy to overcome chemoresistance in lung cancer patients with a history of smoking.

cancer biology↗

bioRxiv2026

Genome-wide association study in Heterogeneous Stock rats identifies genetic loci associated with aversion-based learning and cocaine aversion

Addiction is a complex and heritable trait which progresses through several developmental stages, each of which is presumably influenced by multiple partially overlapping genetic factors. Cocaine initially produces rewarding effects, followed by aversive effects including anxiety, craving, anhedonia, and withdrawal. These aversive effects have been suggested to contribute to the etiology of cocaine use disorders (CUD), as repeated exposure is thought to desensitize the rewarding effects and sensitize the aversive effects through a process involving both aberrant reward-based learning and aberrant avoidance-based learning. We examined the genetic basis of aversion learning using both food-based and cocaine-based behavioral assays in outbred Heterogenous Stock (HS) rats. A total of 1,074 HS rats (35.3% male) underwent runway operant cocaine-seeking, food-based progressive ratio and punishment testing, and locomotion testing. These phenotypes were significantly heritable (with h2 estimates as high as 0.307) and identified significant (p < 0.05) genetic loci related to avoidance-based learning including from the punishment task on Chromosomes 2, 3, 5, and 6, and the cocaine-operant runway latency task on Chromosome X. 172 positional candidate genes were identified from significant and suggestive loci, including Cdh10, Cdh12, Cdh18 which have previously been associated with smoking initiation from human GWAS, Adcy3, Cfap206, and Drc1 which are associated with primary neuronal cilia, as well as SNPs associated with novelty-related and social interaction phenotypes in independent samples of HS rats. Our results suggest that these aversion learning phenotypes are themselves complex heritable traits influenced by multiple genetic loci, which may pleiotropically affect other aspects of addiction biology.

genetics↗

bioRxiv2026

Charting the small-molecule universe from mass spectra with neuro-symbolic AI

Mass spectrometry (MS) has revealed millions of small organic molecules across organisms, yet most remain uncharacterized, limiting progress in biology and medicine. Despite computational advances, MS workflows rely heavily on expert input and reference libraries that cover only a fraction of known chemical space. Here, we introduce AIMe (AI Molecule Explorer), a multi-agent neuro-symbolic AI framework that transforms the interpretation of unknown spectra into an omics-scale exploration across the known structural space, providing chemically interpretable annotations. At its core, AIMe combines chemical reasoning with structure- informed learning to predict MS2 spectra by modeling fragmentation as a sequence of actions, outperforming existing methods. AIMe dynamically constructs fragmentation pathways by assigning likelihoods to individual fragmentation actions, linking spectral peaks to explicit fragment molecular formulas and structures. At scale, AIMe predicted MS2 spectra for over 100 million small organic molecules in PubChem and organized them into MS2KOSMOS, a substructure-informed community resource comprising over 800 million predicted spectra that expands the searchable small-molecule universe by roughly three orders of magnitude relative to experimental libraries. Analogous to sequence homology-based searches in genomics and proteomics, AIMe maps unknown spectra to molecular neighborhoods in MS2KOSMOS. Exact- formula indexing enables ranked retrieval of candidates and related structures, with peak-level structural and fragmentation-pathway annotations. Applied to mouse microbiota-dependent metabolites, AIMe enabled putative annotation of knowns and guided structure elucidation of unknowns, revealing previously unreported types of microbiota-dependent polyamines that also occur in humans. At repository scale, AIMe enabled putative annotation of roughly a third of 7 million spectral clusters representing most of the unknowns in the GNPS database. By extending MS2 annotation beyond curated-library matching to interpretable search across the known small-molecule universe, AIMe accelerates discovery and large-scale exploration of small molecules across biomedicine, agriculture, and ecology.

biochemistry↗

bioRxiv2026

Deciphering the Effect of Melittin on Murine Cervical Cancer Cells Based on Transcriptomic Investigation

Melittin, a highly active natural antimicrobial peptide derived from honeybee venom, holds immense pharmacological potential against solid tumors. However, its specific anti-tumor efficacy and transcriptomic dynamics in cervical carcinoma remain to be systematically characterized. This study evaluated the anti-cancer properties of melittin on murine U14 cervical cancer cells following by transcriptomic investigation of the underlying mechanism. Phenotypic evaluations revealed that melittin potently inhibited U14 cell viability, while wound healing assays demonstrated a profound, dose-dependent suppression of cellular migration, culminating in near-complete migratory arrest at high concentrations. Furthermore, flow cytometry quantified a dramatic, dose-dependent surge predominantly in late apoptotic cell populations. These apoptotic events were structurally corroborated by scanning electron microscopy (SEM), which revealed severe plasma membrane perforation and morphological exhaustion. Enrichment analyses indicated that the physical membrane disruption inflicted by melittin translated into a severe metabolic crisis, marked by a global suppression of ribosomal biogenesis and mitochondrial oxidative phosphorylation. Furthermore, melittin profoundly repressed the Tie2-mediated angiogenic pathway (Etv2 down-regulation) while triggering the lethal hyperactivation of the AP-1 transcriptional stress complex (Jun, Fos, Fosb). Collectively, these findings elucidate the pharmacological networks underlying melittins cytotoxicity, providing solid molecular evidence for its development as a natural therapeutic agent against cervical cancer.

cancer biology↗

bioRxiv2026

Sleep reactivation of positive self-evaluation reveals neural-evaluative alignment that varies with depressive symptoms

Positive self-evaluation underpins resilience and mental health, yet how to enhance positive self-evaluation and the underlying neurocognitive mechanisms remain poorly understood. Existing data mostly examined self-evaluative processing of the wakeful minds, with the role of sleep remain unexplored. Here, we demonstrated that reactivation of positive self-evaluation during sleep revealed fine-grained neural-evaluative alignment that varies with depressive symptoms. We found that targeted reactivation of positive personality traits during non-rapid eye movement (NREM) sleep enhanced positive self-evaluation, but this benefit diminished with elevated depressive symptoms. Moreover, cueing positive traits during NREM sleep elicited trait-specific, 11-16 Hz EEG sigma power-based neural representations that aligned with post-sleep positive self-evaluative representational structures, as revealed by representational similarity analyses. Notably, individuals with elevated depressive symptoms exhibited weaker neural-evaluative representational alignments, identifying a maladaptive self-evaluative processing that bridges across sleep and wakefulness states. These findings provide mechanistic insights on how fine-grained neural-evaluative alignment can substantiate positive self-evaluation, and why it was disrupted as depressive symptoms increased. HighlightsO_LIPositive-trait reactivation during NREM sleep enhances positive self-evaluation C_LIO_LIThis behavioral benefit decreases as depressive symptoms increase C_LIO_LISleep cueing evokes trait-specific sigma-band neural representations C_LIO_LINeural-evaluative alignment weakens as depressive symptoms increase C_LI

neuroscience↗

bioRxiv2026

Transcriptomic datasets of melittin- and un-treated murine cervical carcinoma U14 cells

Melittin, a potent amphipathic cationic peptide derived from bee venom, exhibits broad-spectrum antineoplastic efficacy, notably against cervical carcinoma. Despite its established therapeutic potential, the global transcriptional reprogramming orchestrating its acute multi-pathway cytotoxicity remains incompletely understood. To bridge this knowledge gap, we generated the first comprehensive, untargeted RNA-seq dataset profiling the acute phase of melittin-induced cell death in murine cervical carcinoma U14 cells (exposed to 4 g/mL melittin for 20 minutes) alongside untreated controls. Utilizing deep sequencing and rigorous bioinformatics workflows, we quantified genome-wide mRNA abundances and mapped a distinct transcriptomic shift, identifying 254 significantly differentially expressed genes, comprising 158 up- and 96 down-regulated transcripts. Validated by stringent quality control metrics, exceptional genomic mapping rates, and comprehensive functional annotations via the GO and KEGG databases, this high-resolution transcriptomic resource provides a systems-level map of early molecular alterations. All raw and processed sequencing data are publicly available. This transcriptomic resource provides a valuable foundation for elucidating the acute regulatory networks underlying melittin-induced anti-cervical cancer effects. DatasetThe dataset can be accessed through the NGDC website by searching with the BioProject accession number PRJCA068439. Reviewers may use this link for anonymous access during the review process. Direct URL to data: Genome Sequence Archive-CNCB-NGDC

genomics↗

bioRxiv2026

Multicenter self-supervised computational pathology identifies prognostic histomorphological phenotypes in colorectal cancer

H&E whole-slide images capture prognostic information encoded in tumor morphology and the surrounding microenvironment, but these signals remain difficult to extract and interpret at scale. Here, we developed a self-supervised computational pathology framework to predict disease-free survival in colorectal cancer and link model-derived risk to interpretable histomorphology and spatial tumor biology. Using a multicenter developmental cohort spanning colorectal adenomas and invasive colorectal cancer, we trained HPL-PanColon, a self-supervised representation model, to extract tile-level embeddings and identify recurrent histomorphological phenotype clusters across the adenoma-carcinoma spectrum. Compared with general-purpose pathology foundation models, HPL-PanColon yielded representations with reduced institution- and dataset-specific batch effects. We then applied HPL-PanColon to a global survival cohort of 1,024 colorectal cancer patients in a leave-one-institution-out framework, using tile embeddings to train an attention-based survival model and derive the Colon Histomorphology Prognostic Score (CHiPS). CHiPS stratified patients by disease-free survival and provided complementary prognostic information to a UICC TNM-informed clinicopathological model, increasing the c-index from 0.683 to 0.706. Integrating model attention with phenotype assignments traced CHiPS-associated risk to pathologist-recognizable tissue patterns, with high-risk regions enriched for desmoplastic, stromal, and fibroinflammatory morphologies and low-risk regions reflecting tumor-rich epithelial glandular patterns. Spatial transcriptomic analysis further linked high-risk morphologies to fibroblastic, perivascular, myofibroblastic, and immune-reactive tumor microenvironment programs, while low-risk morphologies mapped to epithelial and tumor-enriched regions. These findings establish a scalable framework for interpretable histology-based prognosis and spatial biological discovery in colorectal cancer.

pathology↗

bioRxiv2026

De novo design of ligand binding and sensing with a physics based generative approach

The de novo design of ligand-binding proteins has tremendous potential to revolutionize biosensor technology, yet converting these designs into functional sensors remains a major challenge due to the need for ligand-induced conformational changes or modulation of protein-protein interactions. Here, we introduce a physics-based generative approach for the de novo creation of proteins that bind small molecules and metal ions. Our method achieves customizable ligand-binding pocket formation in parallel with simulated protein folding, allowing for precise architectural control of the protein-ligand complex and facilitating the development of biosensors based on either ligand-triggered protein reassociation via split-protein reassembly or ligand-induced protein folding. We demonstrate the versatility of our computational method through successful designs targeting five small molecules, including the very small neurotransmitters serotonin and dopamine, and two metal ions. Biophysical characterization confirmed correct ligand binding, and crystal structures closely matched computational models. We demonstrated the biosensor engineering potential of these designs by constructing serotonin and dopamine sensors using a split protein strategy and explored several approaches to enhance sensor activity. Additionally, we developed a zinc sensor through a zinc-induced protein folding mechanism. Overall, our physics-based generative approach provides a robust framework for the de novo design of ligand-binding proteins, opening new avenues for the development of ligand-responsive biosensors.

bioinformatics↗

bioRxiv2026

IL-21-producing peripheral helper T cells associate with autoimmune bile duct injury in biliary atresia

BackgroundBiliary atresia (BA) is a severe neonatal liver disease characterized by progressive fibrosis and bile duct obliteration. ObjectiveAlthough immune dysregulation is implicated in the pathogenesis of BA, the specific mechanisms driving bile duct injury remain incompletely understood. This study aimed to characterize tertiary lymphoid structures (TLSs) within extrahepatic biliary remnants (EBRs), identify their cellular mediators, and evaluate the therapeutic potential of targeting IL-21 receptor signaling. DesignWe performed integrated bulk RNA sequencing, single-cell RNA sequencing, spatial transcriptomics, multiplex immunohistochemistry, and flow cytometry on clinical samples from BA patients and non-BA cholestatic controls. TLS maturation was assessed by CD23 immunohistochemistry in EBRs from 148 BA patients and correlated with clinical parameters. Anti-IL-21R antibody treatment was evaluated in a rhesus rotavirus-induced BA mouse model, with treatment initiated on day 4 post-infection. ResultsTLSs were identified in BA EBRs with significantly higher prevalence than in matched liver tissues. Mature TLSs containing CD23 germinal centers were associated with elevated serum matrix metalloproteinase-7, more advanced hepatic fibrosis, and localized autoantibody deposition on injured bile ducts. Single-cell profiling revealed expanded CD4+ T peripheral helper (Tph) cells expressing IL-21 and CXCL13 within TLS-containing EBRs. Tph cells were enriched in peripheral blood of BA patients compared to non-BA cholestatic controls (P = 0.0025), and serum IL-21 was significantly elevated (P < 0.0001). Post-infection IL-21R blockade in the mouse model reduced jaundice incidence, improved weight gain, prevented extrahepatic biliary obstruction, and significantly improved long-term survival. ConclusionTLSs in BA extrahepatic biliary remnants harbor expanded Tph cells associated with IL-21-mediated B cell activation and bile duct injury. IL-21R blockade ameliorated disease in a murine BA model, identifying the IL-21/IL-21R axis as a potential therapeutic target warranting further investigation. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSImmune dysregulation contributes to biliary atresia (BA), with documented lymphocyte infiltration and defective B cell tolerance. However, the cellular mechanisms linking local immune activation to bile duct injury are unclear, and the roles of organized lymphoid structures and specific CD4 T cell subsets in orchestrating local humoral responses have not been characterized. What this study addsThis study demonstrates that mature tertiary lymphoid structures in extrahepatic biliary remnants are associated with disease severity markers and localized bile duct injury in BA. We identify T peripheral helper cells as an expanded IL-21-producing CD4 T cell population within these structures, and show that post-infection IL-21 receptor blockade prevents biliary obstruction and improves survival in a murine BA model. How this study might affect research, practice or policyThese findings identify the IL-21/IL-21R signaling axis as a candidate therapeutic target in BA warranting further preclinical and translational investigation. TLS maturation status in biliary remnants and serum autoantibody levels may serve as potential biomarkers of disease severity, meriting prospective evaluation in clinical cohorts.

immunology↗

bioRxiv2026

Machine learning-guided discovery of a conserved plasmid proteomic signature enables MALDI-TOF MS detection of pOXA-48-carrying Enterobacterales

OXA-48 carbapenemases are among the most widespread and important resistance mechanisms in Enterobacterales. Yet detecting carbapenemases by conventional workflows necessitates additional testing, thus delaying optimization of therapy and implementation of infection control measures. Here, we present a machine learning approach that identifies the conserved pOXA-48 plasmid directly from routine MALDI-TOF spectra acquired for species identification. The model detects pOXA-48 carriers with an AUROC of 0.96-0.98 across two independent hospital cohorts and instrument platforms, indicating near-perfect discrimination. Using bottom-up proteomics, plasmid conjugation, and plasmid curing, we link the discriminative MALDI-TOF spectral features to proteins encoded on pOXA-48, with DUF1496 domain-containing protein producing the most discriminative spectral feature. Our approach reframes the resistance prediction task from inferring a resistance phenotype to detecting a conserved plasmid through its expressed proteomic signature and has the potential to enable rapid MALDI-TOF MS-based diagnostics for a wide range of plasmid-based resistance determinants.

microbiology↗

bioRxiv2026

Bone Mechanosensing Dictates Hematopoietic Stem Cell Fate and Immune Homeostasis

The vertebrate water-to-land transition was accompanied by a six-fold increase in gravitational force, followed by the migration of hematopoietic stem cells (HSCs) from kidney or liver to the bone marrow, and the acquisition of enhanced immune functions to cope with novel environmental pressures. Bone senses mechanical loading and provides a microenvironment for HSC development, yet whether bone mechanosensation affects immune cell development and immune homeostasis remains unclear. Here, we unveil bone as a mechanosensory organ that translates mechanical force into hematopoietic instructions. Mechanical loading of bone directs HSCs toward lymphoid lineages in mice and non-human primates, whereas unloading favors myeloid commitment. This process requires osteocyte mechanosensor Piezo1, which induces loading-responsive bone-derived factors such as IL1R2, SERPINC1 and INMT, thereby restraining inflammatory signaling and guiding HSC differentiation. Osteocyte Piezo1 deficiency recapitulates the hematopoietic and immune alterations observed during unloading. Functionally, this pathway enhances acute infection resistance and suppresses immunosenescence in mice and in aged long-tailed macaques. Notably, skeletal mechanoregulation of immune homeostasis is conserved across vertebrate species. Our research defines the mechano-bone-immune axis (mechano-osteoimmunology), offering a novel evolutionary perspective on the interconnected development of the skeletal and immune systems and presenting a promising non-pharmacological target to address immune dysfunction.

immunology↗

bioRxiv2026

Radioligand therapy in combination with CAR T cells overcomes the heterogeneous immunosuppressive prostate tumor microenvironment

177Lu-PSMA-617 (PluvictoTM, Lu-177 RLT) is an FDA-approved targeted radioligand therapy (RLT) for metastatic castration-resistant prostate cancer (mCRPC), but its durability of response to this singular approach poses a challenge to the field. Chimeric antigen receptor (CAR) T cell therapy has revolutionized clinical practice for hematological malignancies, but its clinical development for solid tumors, including mCRPC, has been encumbered by antigen heterogeneity and the immunosuppressive tumor microenvironment (TME). Here, we evaluate the therapeutic combination of Lu-177 RLT and PSCA-CAR T cells to overcome these barriers. In human xenograft and mouse syngeneic prostate cancer models with homogeneous or heterogeneous antigen expression, the sequential administration of Lu-177 RLT, cyclophosphamide (Cy), and PSCA-CAR T cells improves tumor control and prolongs survival compared to monotherapies. Mechanistically, Lu-177 RLT alone or with Cy remodels the TME by promoting pro-inflammatory myeloid responses and activating endogenous T cells, while enhancing CAR T cell activation and effector function. We additionally evaluated 225Ac-PSMA-617 RLT as an emerging approach in combination with CAR T cells and observed anti-tumor responses, supporting its potential as an alternative RLT partner. These findings support RLT as an immune priming strategy to enhance CAR T cell therapy and provide a rationale for clinical translation of this combination in mCRPC. One Sentence SummaryCombining 177Lu-PSMA-617 radioligand therapy with PSCA-CAR T cells improves tumor control and survival in prostate cancer models by overcoming the antigen heterogeneity and reshaping the immunosuppressive tumor microenvironment.

cancer biology↗

bioRxiv2026

Evolutionary Origins of Molecular Programs Underlying Brain Circuitry

The vertebrate pallium harbors independently evolved structures that, nevertheless, support strikingly similar sensory and cognitive circuit architectures. The mechanisms and evolutionary timing driving the emergence of these parallel pallial circuits remain unelucidated. Here, we integrated spatial transcriptomic and single-nucleus RNA-seq datasets from eight representative vertebrate species spanning approximately 500 million years of evolution to reconstruct the evolutionary assembly of the primary sensory-allocortical (Pr-Al) molecular axis, a conserved cortical hierarchical axis defined in our prior work. We uncovered that Pr- and Al-like neuronal identities are deeply conserved across sarcopterygians, encompassing all tetrapods and lobe-finned fishes. Intriguingly, this ancestral neuronal homology is uncoupled from spatially partitioned patterning: only tetrapods further compartmentalized these Pr- and Al- neurons into distinct pallium regions. Functional enrichment of Pr- and Al- gene programs uncovered a conserved tetrapod genetic core suite including MAPK signaling and axon guidance pathways. This core toolkit underwent sequential functional refinement from amphibians through mammals. Notably, mammals and birds convergently evolved association-cortical molecular profiles enriched for synaptic regulatory genes to support advanced cognitive functions. Collectively, this work delineates a stepwise vertebrate pallium evolutionary paradigm that explains how conserved molecular modules shape spatially organized brain circuitry across deep evolutionary time.

evolutionary biology↗

bioRxiv2026

Comprehensive transcriptome data of melittin- and un-treated murine hepatoma Hepa 1-6 cells

Melittin, the principal bioactive peptide of bee venom, exerts potent antitumor activity against hepatocellular carcinoma (HCC). However, the comprehensive transcriptomic alterations it elicits in hepatoma cells remain poorly characterized. Here, we present an integrated transcriptome dataset from melittin- and un-treated murine Hepa 1-6 hepatoma cells, encompassing messenger RNA (mRNA) and microRNA (miRNA) expression profiles. Cells were exposed to 4 g/mL melittin in serum-free DMEM for 20 min, and total RNA was subjected to ribosomal RNA-depleted strand-specific RNA sequencing on an Illumina NovaSeq6000 platform (paired-end 150 bp) and small RNA sequencing on an Illumina HiSeq2500 platform (single-end 50 bp). Raw data were processed using Cutadapt to remove adapters and low-quality reads, yielding clean datasets with Q20 [≥] 99.85%, Q30 [≥] 98.48%, and valid data ratios exceeding 85%. All raw and processed sequencing data are publicly available. This transcriptomic resource provides a valuable resource and basis for elucidating the regulatory networks underlying melittin-induced anti-hepatoma effects. DatasetThe dataset can be accessed through the National Genomics Data Center, China National Center website by searching with the BioProject accession number PRJCA065485 Reviewers may use this link for anonymous access during the review process. Direct URL to data: Genome Sequence Archive-CNCB-NGDC. Dataset LicenseCC BY 4.0

Cancer Biology↗

bioRxiv2026

The optical origin of the human skin color 'banana' in CIELAB space

Human skin colors occupy a characteristic banana-shaped region in CIE L*a*b* space, but why skin color coordinates are restricted to this region and how they relate to melanin and blood remain incompletely understood. We developed a physics-based framework linking skin chromophore content to colorimeter-derived skin color coordinates using two complementary three-layer light transport models. Across physiologic ranges of epidermal melanosome volume fraction and dermal blood volume fraction, simulated reflectance spectra were converted to CIE L*a*b* coordinates and compared with human skin color measurements from the International Skin Spectra Archive. Physiologic variation in melanin and blood reproduced the observed banana-shaped locus and revealed distinct chromophore-specific trajectories. Iso-melanin trajectories became progressively more linear as melanin increased, whereas iso-blood trajectories retained the curvature of the skin color locus. As melanin increased, perceptible color differences from blood volume changes were reduced, providing a mechanistic explanation for reduced erythema visibility in highly pigmented skin. These relationships were stable across plausible variations in layer thickness and tissue oxygenation and agreed with external validation data. The framework also identified when the Individual Typology Angle is confounded by blood or distorted by dermal melanin. Together, these findings establish a mechanistic optical basis for interpreting colorimeter-derived skin color coordinates.

bioengineering↗

bioRxiv2026

GEOAgent: An AI-driven Autonomous Framework for Intelligent GEO Data Retrieval and Standardized Preprocessing

Datasets in the Gene Expression Omnibus (GEO) remain difficult to reuse at scale because sample annotations are heterogeneous and raw sequencing data require assay-specific preprocessing. We present GEOAgent, an AI-driven autonomous framework designed for intelligent dataset retrieval and standardized preprocessing by coupling autonomous semantic governance with an automated Nextflow pipeline named bioStream. Metadata from 181,760 sequencing series and 84,756 associated PubMed records were organized in a relational database and semantic index to support natural-language dataset retrieval. The framework automatically determines assay modalities, resolves experimental design pairings, and standardizes sample naming to minimize manual curation overhead. Based on these parsed attributes, the framework generates deployment-ready manifests to automatically execute containerized workflows across bulk and single-cell omics modalities. In expert-curated benchmarks, the workflow achieved 96% retrieval precision alongside 100% accuracy in assay classification and sample relationship resolution. The web platform is publicly accessible, while the source code and associated databases are openly available via GitHub and Zenodo.

bioinformatics↗

bioRxiv2026

Developing engineering strategies to enhance the genetic stability of fatty alcohol-producing strains for production scale-up

Robust strain stability is essential for industrial-scale fatty alcohol production, as metabolic burden and toxicity not only constrain productivity but also create selective pressure for low-producing or non-producing subpopulations. This genetic instability leads to genetic heterogeneity and compromises strain performance during large-scale fermentation. In this study, we investigated the production stability of fatty alcohol-producing Yarrowia lipolytica strains and developed systematic strategies to improve the genetic stability of engineered strains for scale-up production. In a mock fermentation scale-up, a fatty acyl-CoA reductase (FAR)-expressing strain lost fatty alcohol production after five consecutive passages. To address this, we fused FAR to phosphoglycerate kinase I (PGK1), a gene essential to cell growth, to promote the stability of FAR expression and prevent production loss. This strategy extended fatty alcohol production by one passage. Additionally, FAR was fused to GFP and extended production stability by four additional passages. In parallel, competitive co-culture experiments, in which producing strains were cultured alongside non-producing mutants, revealed that when non-producers emerged with a frequency of 10-5, they dominated the fermentation population within six passages; at 10%, they took only two passages. Furthermore, deep sequencing of strains that demonstrate different levels of stability and fatty alcohol productivity identified mutation patterns that contribute to strain instability. These findings provide insights into engineering Y. lipolytica with enhanced genetic stability for scale-up fatty alcohol production.

synthetic biology↗