Biology subjects

Li, Y.

Publications and source records attributed to Li, Y..

At least 397 records · Page 22Linked to original sources

bioRxiv2026

Differential kin interactions between invasive and native plants: evidence from Alternanthera philoxeroides and its native congener

Reduced competition or facilitation between kin relative to nonkin can improve plant performance, particularly under resource-limited conditions. Understanding whether kin interactions differ between invasive and native species may provide insights into the mechanisms underlying the persistence and spread of invasive species, particularly for species that spread clonally. To explore this, we conducted a greenhouse experiment using the invasive Alternanthera philoxeroides and its native congener A. sessilis in China. For both species, we grew central plants without or with neighbors, and for the latter we had three intraspecific neighbor kinship treatments (kin only, nonkin only, and both kin and nonkin [mixed] neighbors). To test whether kinship effects are affected by resource limitation, we grew the plants under two watering conditions (well-watered and drought-stressed). Our findings revealed that at both the group (i.e., pot-level) and individual levels, invasive plants had a higher biomass production and experienced a less negative relative neighbor effect in kin groups than in nonkin groups, while these patterns were reversed in the native species. Although aboveground architecture of central plants did not differ significantly between kin and nonkin neighbors in either species, neighbor plants of the invasive species produced fewer nodes in kin groups than in nonkin groups, while the reverse was true for the native species. These patterns were not affected by the watering treatment. Together, these results indicate that while the native plants has stronger kin competition, the invasive species has reduced kin competition. Such reduced competition among kin in the invasive Alternanthera philoxeroides may enhance its population dominance and facilitate its spread.

ecology↗

bioRxiv2026

Beyond Student's t: A Systematic Exploration of Heavy-Tailed Residual Densities for Outlier Handling in Population PK Modeling

BackgroundReliable population pharmacokinetic (PopPK) parameter estimation can be compromised by outliers under Gaussian residual error models. A common mitigation strategy is post hoc filtering based on conditional weighted residuals (CWRES); however, this approach can be insensitive due to model "masking" driven by variance inflation. Practical barriers to implementing robust likelihoods in standard software have motivated interest in computationally simpler exponential-tail alternatives such as the Laplace and exponential power distribution (EPD). MethodsWe implemented a one-compartment PopPK model using a custom likelihood workaround in Monolix to benchmark four residual error distributions: Normal, Laplace, Generalized Error Distribution (GED), and Students t. We assessed CWRES sensitivity under extreme contamination and compared estimation performance using theoretical tail-behavior analysis, controlled simulation studies spanning multiple contamination severities, and a real-world caffeine PK case study with influential terminal-phase deviations. ResultsSimulations showed that CWRES-based diagnostics can be unreliable: extreme outliers frequently produced |CWRES| < 6 because the Normal model inflated residual variance, thereby masking contamination. Exponential-tail models (Laplace, GED) improved robustness for mild to moderate outliers but failed under extreme deviations due to insufficiently heavy tails compared to power-law decay. In contrast, the Students t model, via power-law tail behavior, maintained stable and minimally biased structural parameter estimates across contamination scenarios. Consistent patterns were observed in the caffeine case study, where the Students t model provided improved fit and physiologically plausible parameter estimates. ConclusionsCWRES-driven outlier handling is methodologically fragile because influential contamination can be masked by variance inflation and induce biased inference. Among robust residual error models, exponential-tail distributions may be insufficient for extreme outliers, whereas the Students t distribution provides more stable inference across contamination severities. These findings support adopting Students t residual modeling as a default robust option in routine PopPK workflows when outlier contamination is plausible.

pharmacology and toxicology↗

bioRxiv2026

Decoupling CAR-T Expansion, Conversion, and Decay Timing: Physiologically Aligned Semi-Mechanistic Modeling with Smooth Gating and a Cauchy Likelihood Residual Model

Chimeric antigen receptor (CAR) T-cell therapies exhibit complex cellular kinetics characterized by rapid expansion, contraction, and long-term persistence, often with substantial inter-individual variability, frequent below-quantification (BLQ) observations, and occasional influential data points. These features can destabilize inference under Gaussian residual assumptions and motivate robust, likelihood-based approaches that can jointly accommodate outliers and censoring. In prior work, we showed that combining Students t residuals with likelihood-based BLQ handling (M3 censoring) improves robustness in CAR-T cellular kinetics modeling; however, implementing Students t censoring likelihoods is not straightforward in all modeling platforms because the Students t cumulative distribution function (CDF) lacks a simple elementary closed-form. Here, we evaluated the Cauchy residual likelihood as a practical, heavy-tailed alternative to Students t that provides closed-form expressions for both the probability density function (PDF) and CDF. In a two-compartment IV pharmacokinetic simulation with terminal-phase outlier contamination, Cauchy residuals preserved stable parameter recovery comparable to Students t while avoiding the bias and instability observed under Normal residuals. In a real-data integrated CAR-T cellular kinetics application fitted with full Bayesian inference and likelihood-based BLQ handling, replacing Students t with Cauchy yielded highly concordant posterior inference and similar subject-level predictions. We further extended a semi-mechanistic CAR-T cellular kinetics framework by replacing piecewise switching with smooth S-shaped time-varying rate functions and allowing process-specific transition times. Full Bayesian posterior summaries supported asynchronous transition timing, including earlier conversion relative to expansion and later decay-related transitions. Collectively, these results support Cauchy likelihoods as an implementation-friendly robust option and demonstrate that smooth, process-specific transition modeling can enhance physiological plausibility for CAR-T kinetics.

pharmacology and toxicology↗

bioRxiv2026

Delay Differential Equation (DDE) Modeling of CAR-T Cellular Kinetics: Application to BCMA-Targeted (Ide-cel, Orva-cel) and CD19-Targeted (Liso-cel) Therapies

Chimeric antigen receptor (CAR) T-cell therapies undergo rapid in vivo expansion followed by contraction and variable long-term persistence after a single infusion, yielding cellular kinetic (CK) profiles that differ fundamentally from conventional small-molecule and biologic pharmacokinetics. Piecewise, phase-based CK models are widely used, but discontinuous switching and constant expansion assumptions can create numerical instability around the transition window and bias the characterization of early expansion and near-peak behavior. Building on our prior saturable expansion framework (Vmax/Km), we advanced CAR-T CK modeling by introducing (i) smooth S-shaped gating to replace discontinuous phase switching and enable continuous time-varying expansion dynamics, and (ii) delay differential equation (DDE) components to evaluate whether longitudinal data support explicit lags in downstream biological processes. Data were pooled from three CAR-T trials (TRANSCEND, KarMMa-3, and EVOLVE) spanning two BCMA-targeted products (ide-cel, orva-cel) and one CD19-targeted product (liso-cel). Models were estimated in Monolix using SAEM with importance sampling for final likelihood evaluation. Model selection relied on likelihood-based criteria (AIC, BIC, and Monolix BICc) and diagnostic assessments. Relative to a constant-expansion baseline, saturable expansion improved fit and reduced systematic model misspecification at high transgene levels (e.g., qPCR transgene copies/{micro}g). Among multiple DDE placements evaluated, the data most strongly supported a delay on effector-to-memory conversion; delays in effector-like and/or memory-like decay were not favored. Simulations indicated that the conversion delay primarily modulated the timing and magnitude of the memory-like trajectory, with minimal impact on total-cell trajectories during the expansion phase at the evaluated scale. In a shared covariate framework with product as a categorical effect, BCMA-targeted products exhibited higher baseline levels and expansion capacity than liso-cel, with stronger evidence for slower effector-like decay for orva-cel than ide-cel. Overall, smooth-gated saturable expansion with DDE-based delayed conversion provides a parsimonious, biologically motivated framework for CAR-T CK and supports cross-product comparisons under harmonized structural assumptions.

pharmacology and toxicology↗

bioRxiv2026

ALKBH5 Promotes Hepatic Gluconeogenesis via m6A-mediated Stabilization of Ogt mRNA

Excessive hepatic glucose production is a hallmark of fasting hyperglycemia in type 2 diabetes mellitus, yet the epitranscriptomic mechanisms that sustain this dysregulation remain incompletely understood. Here, we show that dexamethasone/forskolin-induced gluconeogenic activation triggers widespread remodeling of RNA m6A methylation in mouse primary hepatocytes. Among the m6A regulators examined, the demethylase ALKBH5 is robustly induced both in vitro and in fasted livers. This induction is mediated by the glucocorticoid receptor, which binds to the Alkbh5 promoter and activates its transcription. Functionally, ALKBH5 overexpression enhances gluconeogenic gene expression and glucose production, whereas both global and hepatocyte-specific Alkbh5 knockout mice exhibit suppressed hepatic gluconeogenesis. Mechanistically, we identify Ogt as a primary downstream target, defining an ALKBH5-OGT epitranscriptomic axis in hepatocytes. ALKBH5 demethylates and stabilizes Ogt mRNA, thereby elevating OGT expression and promoting gluconeogenic gene expression. Consistently, the pro-gluconeogenic effects of ALKBH5 are largely abrogated by OGT knockdown. Finally, pharmacological inhibition of ALKBH5 with 18l effectively improves glucose tolerance and suppresses hepatic gluconeogenesis in both wild-type and db/db mice. Together, these findings reveal a glucocorticoid-responsive epitranscriptomic mechanism whereby ALKBH5 stabilizes Ogt mRNA to drive gluconeogenesis and highlight ALKBH5 as a promising therapeutic target for type 2 diabetes mellitus.

molecular biology↗

bioRxiv2026

Multiscale Symbolic Morpho-Barcoding Reveals Region-Specific and Scale-Dependent Neuronal Organization

Neuronal morphology is a central determinant of circuit organization, yet its multiscale complexity has hindered systematic, brain-wide analysis and integration with anatomical context. Here we introduce Multiscale Morpho-Barcoding (MMB), a framework that encodes whole-brain neuronal morphology into symbolic representations spanning cellular geometry, axonal tract routing, arbor organization, and predicted synaptic distributions. Applying MMB to 1,876 fully reconstructed mouse neurons, comprising 3,776 arbors and 2.63 million predicted presynaptic sites, we identify distinct multiscale morpho-patterns that reveal region-specific and scale-dependent principles of neuronal organization across the brain. MMB robustly discriminates major anatomical divisions and resolves canonical thalamic circuit classes beyond what can be achieved using projection strength alone. By transforming complex neuronal geometry into interpretable multiscale representations, MMB provides a general framework for systematic comparison of neuronal structure and for integrating morphology with connectivity and function at whole-brain scale.

bioinformatics↗

bioRxiv2026

CD8+ T cells are primed by cDC1 and exacerbate tau-mediated neurodegeneration

There are changes in adaptive immunity in Alzheimers disease (AD) and increases in activated CD8+ T cells in brain correlate with tau pathology1-3. However, which cells mediate T cell priming in tau-mediated neurodegeneration remains unclear. In different conditions such as cancer, viral infections, and autoimmune diseases outside the CNS, conventional type-1 dendritic cells (cDC1) perform antigen cross-presentation to prime CD8+ T cells4,5. We demonstrate that tauopathy mice deficient in cDC1 are markedly protected against tau-mediated neurodegeneration and display a selective decrease in brain CD8+ T cell infiltration and glial reactivity. The remaining CD8+ T cells showed an antigen inexperienced status with less clonal expansion, indicating suboptimal T cell priming. We confirm that brain derived antigens are presented in secondary lymphoid tissues to prime CD8+ T cells. Our study identifies cDC1 cells as critical for CD8+ T cell priming outside the CNS. This priming is required for a large increase of activated CD8+ T cells in the brain which promotes tau-mediated neurodegeneration.

neuroscience↗

bioRxiv2026

Sex-specific Genetic Regulatory Effects in Chickens

Sexual dimorphism is a defining vertebrate feature, yet its sex-specific molecular architecture remains poorly understood. Here we established a sex-balanced, uniformly reared chicken cohort to map this landscape, integrating individual whole-genome sequencing with 7,969 bulk and 779,380 single nucleus transcriptomes across 32 tissues from 280 birds. We identified 495,098 independent expression quantitative trait loci for 20,194 genes, including 10,937 loci modulated by cell-type composition. Notably, 340 genes were regulated by 449 loci in a sex-dependent manner, significantly enrichment in endocrine tissues like adipose and the adrenal gland. Furthermore, we fine-mapped 1,219 structural variants, demonstrating their unique roles to tissue- and sex-specific expression beyond SNPs. Ultimately, we showed the utility of these regulatory effects in elucidating the molecular basis of metabolism and complex traits in both chickens and humans. This comprehensive atlas of regulatory effects provides profound insights into the genomic and molecular basis of sexual dimorphism in vertebrates.

genomics↗

bioRxiv2026

lncRNA-ISM1 Promotes Hepatocellular Carcinoma Progression through RBM10-Mediated Alternative Splicing of ISM1 and Akt-S6-Dependent Glucose Metabolic Reprogramming

A low-glucose microenvironment can induce metabolic abnormalities in tumour cells, including hepatocellular carcinoma (HCC) cells, and enhance cancer cell stemness. Isthmin-1 (ISM1) is a recently identified adipokine that promotes glucose uptake and enhances cellular metabolism. While the activity of the ISM1 protein is regulated by glycosylases, its transcriptional and posttranscriptional regulation remain poorly understood. A novel alternatively spliced variant of ISM1 (ISM1-AS) was recently identified. Unlike canonical ISM1, ISM1-AS lacks an AMOP domain, a key structural element required for ISM1 function, suggesting the loss of its metabolic regulatory activity. In this study, we found that ISM1 expression was significantly reduced in HCC tissues and correlated with poor prognosis. Functional assays revealed that ISM1 overexpression markedly suppressed HCC cell proliferation and invasion, whereas ISM1-AS overexpression had the opposite effect. Importantly, ISM1 co-overexpression attenuated the oncogenic effects of ISM1-AS. Knockdown of the antisense transcript lncRNA-ISM1 reduced ISM1-AS expression while increasing ISM1 expression, thereby suppressing HCC proliferation and migration. Mechanistically, lncRNA-ISM1 regulated ISM1 alternative splicing by interacting with RBM10, thereby altering the balance between ISM1-AS and ISM1. This shift activated the Akt-S6 signalling pathway, promoting glycolysis and HCC progression. In vivo experiments further confirmed that the lncRNA-ISM1/ISM1-AS/ISM1 axis drives tumour growth via Akt-S6 activation. Our findings demonstrate that lncRNA-ISM1 promotes HCC progression through the RBM10-mediated alternative splicing of ISM1 and activation of the Akt-S6 signalling pathway, highlighting its potential as a therapeutic target for HCC.

molecular biology↗

bioRxiv2026

Macrophage Iron Metabolism in Allografts and Tumors

Macrophages are present at high frequencies in transplanted organs and solid tumors. These infiltrating macrophages are highly tuned by tissue niche signals. However, the underlying mechanisms that orchestrate the activation of distinct macrophage populations remain unclear. Here, using heart transplantation and tumor implantation models, we found that macrophages in cardiac allografts exhibited higher intracellular iron (Fe2+) level and higher expression of the iron transporter SLC11A1 than those in the solid tumors. In mice, the myeloid-specific deletion of Slc11a1 alleviated the proinflammatory state of macrophages and cardiac allografts rejection. Together, our findings identify SLC11A1 as a new player in immune response regulation, implicating SLC11A1 as a therapeutic target for both allograft and tumor rejection. This preprint reports initial findings; additional experiments are ongoing and will be included in a future full manuscript.

immunology↗

bioRxiv2026

Integrative Multi-Scale Sequence-Structure Modeling for Antimicrobial Peptide Prediction and Design

Antimicrobial resistance (AMR) is accelerating worldwide, undermining frontline antibiotics and making the need for novel agents more urgent than ever. Antimicrobial peptides (AMPs) are promising therapeutics against multidrug-resistant pathogens, as they are less prone to inducing resistance. However, current AMP prediction approaches often treat sequence and structure in isolation and at a single scale, leading to mediocre performance. Here, we propose MultiAMP, a framework that integrates multi-level information for predicting AMPs. The model captures evolutionary and contextual information from sequences alongside global and fine-grained information from structures, synergistically combining these features to enhance predictive power. MultiAMP achieves state-of-the-art performance, outperforming existing methods by over 10% in MCC when identifying distant AMPs sharing less than 40% sequence identity with known AMPs. To discover novel AMPs, we applied MultiAMP to marine organism data, discovering 484 high-confidence peptides with sequences that are highly divergent from known AMPs. Notably, MultiAMP accurately recognizes various structural types of peptides. In addition, our approach reveals functional patterns of AMPs, providing interpretable insights into their mechanisms. Building on these findings, we employed a gradient-based strategy and achieved the design of AMPs with specific motifs. We believe MultiAMP empowers both the rational discovery and mechanistic understanding of AMPs, facilitating future experimental validation and therapeutic design. The codebase is available at https://github.com/jiayili11/multi-amp.

bioinformatics↗

bioRxiv2026

Unified Transcriptome and Mechanics Map of the Intact Mammalian Preimplantation Embryo In Situ

The development and maintenance of multicellular tissues requires that cell states be closely coupled to their local environment, including geometric and mechanical cues. However, studying this coupling in intact tissues has been challenging, because existing measurement technologies cannot simultaneously assess mechanical properties and molecularly defined cell states. To address this gap, we introduce the Unified Transcriptome and Mechanics Map (UTMM), a method for concurrent measurement of the transcriptome and cytoplasmic stiffness (high-frequency elastic modulus) within intact 3D multicellular structures. UTMM relies on two innovations: (1) a targeted in situ RNA sequencing approach for intact 3D embryos (3DISS), and (2) a strategy that leverages high-frequency intracellular organelle fluctuations to infer cell-level stiffness in vivo. We applied UTMM to mouse embryos from the zygote through the morula stage to characterize how RNA expression and cytoplasmic stiffness become coupled during early lineage specification. Our data reveal that, in the early morula, transcriptional and morphological distinctions emerge between trophectoderm and inner cell mass (ICM) lineages, coinciding with a gradual decrease in cytoplasmic stiffness (softening) across all cells from the 2-cell through morula stages. Furthermore, we observe that early lineage biases align with differential mechanical properties, reflecting distinct emerging developmental programs. When we delayed this softening process via mechanical perturbation, embryonic progression was impeded, highlighting the functional importance of coordinated mechanical and transcriptional changes. Together, these results demonstrate UTMMs ability to bridge molecular and mechanical dynamics in multicellular systems, providing a powerful framework for investigating how biomechanical cues shape cell fate decisions in intact tissues. One Sentence SummaryJoint 3D in situ quantification of spatial transcriptome and cytoplasm mechanics in preimplantation mammalian embryos

developmental biology↗

bioRxiv2026

Transplanting ANXA1- CD8+ Naive T cells Delay Aging Through Senolysis

Immunosenescence is a hallmark of aging, yet strategies using defined immune subsets to counteract it are largely unexplored. We performed paired scRNA/TCR-seq on CD45 cells from human bone marrow (15 donors, 3-91 years). T cells were the most altered lineage, with CD8 naive T cell contraction and functional impairment. We identified an expanding ANXA1 CD8 naive subset with senescence signatures and impaired function. ANXA1-deficient CD8 T cells exhibited increased resting stemness and enhanced activation/cytotoxicity upon stimulation. ANXA1- cells showed senolytic activity in vitro and reduced senescence burden in vivo. Monthly transfer of syngeneic ANXA1- CD8 naive T cells into aged mice extended median lifespan by >30 weeks, improving cardiac function, bone density, motor coordination, and marrow immune microenvironment. Our study identifies ANXA1 as critical in CD8 naive T cell aging and establishes ANXA1- cell transfer as a strategy to counter immunosenescence and promote healthy aging.

immunology↗

bioRxiv2026

Dynamic, single-cell monitoring of CAR T cell identity and activation with Raman spectroscopy

Chimeric antigen receptor (CAR) T cell therapies have reshaped treatment for cancers and immune-mediated diseases, yet their safety and efficacy depend on both the proliferation of engineered cells and their dynamic functional state -- features that remain challenging to monitor in real-time clinical settings. Current methods require targeted labels, extensive processing, and provide only static snapshots of cell identity and activation. Here, we introduce a surface-enhanced Raman spectroscopy (SERS) and machine learning (ML) approach that enables single-cell identification of engineered CAR T cells without molecularly-targeted labels and time-resolved, semi-continuous monitoring of their functional activation state through a single physical readout spanning donor-derived cells and patient blood. From intrinsic vibrational signatures of live cells, we detect spectral differences resulting from engineered receptor expression in donor-derived CD19- and GD2-targeted CAR T cells (nine and five donors, respectively) with 81-85% donor-level accuracy, and resolve dynamic antigen-specific activation trajectories with temporal precision. Applying this same SERS-ML method to longitudinal samples from a four-patient CD19-CAR T therapy cohort, we classify patient peripheral blood mononuclear cells across pre-and post-infusion timepoints with a mean patient-level accuracy of 84%, and show that isolated CAR-positive T cells are distinguishable from both CAR-negative T cells and background populations with average 86-88% accuracies. These capabilities stem from biochemical signatures consistent with processes such as receptor expression, tonic signalling, and immune synapse formation, demonstrating a single method that reports both cellular identity and activation state with biochemical specificity across cell engineering and clinical monitoring contexts. Our results extend CAR T cell monitoring beyond static phenotyping and support the potential of SERS-ML analysis for rapid, point-of-care assessment of engineered immune cells across the therapeutic lifecycle.

bioengineering↗

bioRxiv2026

NRF2 pathway activation and SPP1⁺TREM2⁺ macrophages drive chemoradiotherapy resistance in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is among the most aggressive cancers, with low rates of durable response to chemoradiotherapy and limited therapeutic options for relapsed disease. To uncover mechanisms of treatment resistance and relapse, we performed comprehensive multi-omics profiling of >100 pre-treatment and post-relapse ESCC tumors from a prospective clinical trial (NCT04694391), integrating whole-exome/genome sequencing, bulk RNA-sequencing, single-cell RNA sequencing, and spatial transcriptomics. We identify somatic alterations in NFE2L2/KEAP1 in nearly 40% of relapsed patients, which are associated with upregulation of NRF2 signaling targets in resistant tumors and cell line models. At single-cell and spatial resolution, relapsed tumors are enriched for NRF2-activated epithelial cells that physically co-localize with immunosuppressive SPP1TREM2 macrophages. This co-localization suggests a synergistic interaction between NRF2-driven tumor programs and macrophage-mediated immune suppression that promotes relapse after chemoradiotherapy. Our findings nominate NFE2L2/KEAP1 mutations as predictive biomarkers for patient stratification and highlight therapeutic targeting of NRF2 signaling and SPP1TREM2 macrophages as rational strategies to overcome resistance in ESCC.

cancer biology↗

bioRxiv2026

TRU-PE: A Universal, Trackable Prime Editor Toolkit for Robust Single- and Multi-Locus Genome Engineering

Prime editing (PE) holds immense promise for precise genome editing, but its wider adoption is constrained by large payloads and inefficient delivery in recalcitrant cell types. Here, we present TRU-PE (Trackable, Robust, and Universal Prime Editor), a toolkit that overcomes these barriers via a split-vector architecture coupled with fluorescence-guided enrichment. This design ensures stoichiometric component expression, yielding marked improvements in editing efficiency and accelerated workflows compatible with both plasmid and viral delivery. By integrating a polycistronic hCtRNA-sgRNA/pegRNA array, the derivative TRU-MPE system enables simultaneous editing of up to ten genomic loci. Furthermore, it enhances the performance of evolved PE editors, allows flexible vector stoichiometry and inspires novel editing reporters. Leveraging these capabilities, we successfully generated a combinatorial human iPSC-based platform for GATA2 deficiency, which accurately recapitulates genotype-specific hematopoietic defects. TRU-PE thus provides a user-friendly, scalable framework for robust single- and multi-locus genome engineering, accelerating functional genomics and therapeutic development.

genetics↗

bioRxiv2026

Cardiac PIEZO 1 Channels Modulate Anxiety

Increases in conscious cardiac interoception explain the ability of some individuals with anxiety to "feel" their heartbeat without taking their pulse. Subconscious cardiac interoception is the detection of heart signals from baroreceptors without subjective awareness. We tested our hypothesis that contrasting sensitivity of PIEZO 1 stretch channels mediates both forms of cardiac interoception and feelings of anxiety. In healthy volunteers, we found conscious cardiac interoception assessed by measuring heartbeat detection accuracy was increased with lower heart rates and greater stroke volumes and cardiac stretch but not associated with anxiety. Disruption of Piezo 1 in cardiac sensory neurons enhanced anxiety in rodents. Accordingly, we used an ex vivo assay of PIEZO 1 sensitivity to correlate subconscious cardiac interoception with anxiety in men and women. When compared to healthy individuals with lower PIEZO 1 sensitivity, men and women with higher PIEZO 1 activity had marked diminution in state anxiety. Those with lower anxiety also had enhanced variability in their instantaneous baroreceptor sensitivity at rest and reduced cardiac rate pressure products following stress. We propose that a reduction in PIEZO 1 sensitivity causes errors in "predictive coding;" the imbalance between expected and actual heart rate responses to changes in blood pressure leads to anxiety and increased cardiac workloads. We also report testosterone, which is anxiolytic, enhanced, whereas the stress hormone corticosterone, decreased Piezo 1 gene transcription. Selectively enhancing subconscious interoception by increasing PIEZO 1 sensitivity may improve predictive coding, cardiovascular outcomes, and ameliorate the subjective manifestations of anxiety.

physiology↗

bioRxiv2026

Cell Type Architecture and Positional Gene Gradients in an Adult Animal at Subcellular Resolution

The spatial organization of cell types and gene expression underlies tissue architecture and organismal physiology. However, resolving complete cellular and molecular landscapes within a three-dimensional context remains challenging, particularly in organisms with high cellular heterogeneity and complex geometry. Here, we developed a semi-supervised workflow to reconstruct high-resolution three-dimensional spatial transcriptomic models of the planarian Schmidtea mediterranea at single-cell resolution. Planarians are basal bilaterians capable of regenerating body structures after injury. Our reconstruction maps the distribution of cell types and spatially patterned gene expression across the intact organism and identifies 119 candidate positional control genes (PCGs). These genes are expressed across muscle, neural, and epidermal populations. Functional perturbation of selected candidates, including pitx3, ptpn11, pi4ka, upf3b, and cul1, revealed roles in regeneration following injury. In addition, we identify intestinal cells as prominent components of the microenvironment surrounding adult tgs1 pluripotent stem cells (neoblasts). Together, these results demonstrate the utility of three-dimensional spatial transcriptomic reconstruction for mapping cellular architecture and positional gene regulation in complex adult organisms.

developmental biology↗