Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 127 records · Page 7Linked to original sources

bioRxiv2026

Field–Flow–Front mapping of breast cancer evolutionary dynamics in situ

Tumour progression reflects not only which clones arise but where, when and in what context they expand--dimensions genotype-centred reconstructions leave unresolved. Here we reconstruct breast cancer evolution in situ across 34 Visium HD, 16 Xenium, 32 MIBI-TOF and 10 CODEX samples, serial-section 3D reconstruction, single-cell and bulk transcriptomes, and genome-wide CRISPR dependency profiles. We partition tumours into 296 cancer microzones--stroma-bounded units within which expansion is reconstructed--and define in each a Cancer Progression Metric(CPM) coupling a transcriptomic clock to expansion geometry. Projected onto tissue, CPM yields a Field-Flow-Front model rendering progression as a continuous physical process and resolving subclonal architecture into spatially coherent domains rather than predefined branches. Unexpectedly, the most advanced fronts were not the most proliferative but low-dependency, slow-cycling populations with directional expansion, driven by an extracellular matrix programme whose evolutionary force exceeded inflammation by nearly an order of magnitude yet whose genes were the least cell-autonomous. Under chemotherapy it persisted while its clonal carriers reshuffled, marking a transferable, stroma-coupled front process--not a fixed clone--as the unit of advance. Distilled into an evolutionary advantage load, this front process predicted recurrence and survival across independent cohorts and improved on conventional staging, establishing a tissue-embedded paradigm for mapping tumour evolutionary dynamics, from local fronts to patient outcome.

Cancer Biology↗

bioRxiv2026

A missense mutation in FBXL3 links circadian regulation to out-of-season estrus in sheep

Seasonal breeding is a remarkable adaptive trait, but it constrains efficient production in the sheep industry. Recent studies have shown that seasonal breeding is associated with endogenous circannual rhythms, which are regulated in part by the circadian clock system. FBXL3, a pivotal component of the SCF (SKP1 - CUL1 - F-box) E3 ubiquitin ligase complex, is a known determinant of the mammalian circadian period. In this study, we identified a missense mutation, T183M, in FBXL3 through selective sweep analysis. The allele frequency of this mutation differed significantly between sheep breeds exhibiting year-round estrus and those showing seasonal breeding patterns. The association between the T183M mutation and seasonal breeding was further validated using an ovariectomized, estradiol-implanted sheep model. We then generated mice carrying the homologous T183M mutation and found that they exhibited significantly lengthened circadian periods, accompanied by reduced CRY1 expression and increased CLOCK expression. Co-immunoprecipitation assays confirmed that the mutation reduced the interaction between FBXL3 and CRY1. These findings demonstrate an evolutionarily conserved role of FBXL3 in the circadian clock system. We propose that the T183M mutation disrupts day-length recognition, thereby influencing seasonal estrus in sheep. Author summarySeasonal breeding limits sheep productivity and is regulated by circadian rhythms, yet the key genetic determinants remain poorly understood. Here, we identified an FBXL3 T183M missense mutation whose allele frequency differed markedly between year-round-estrous and seasonally breeding sheep, and validated its association with seasonal reproduction in a sheep population. Functional analyses in mutant mice showed that this variant lengthened the circadian period, disrupted the expression of core clock genes, and weakened the interaction between FBXL3 and CRY1. These findings suggest that the FBXL3 T183M variant impairs day-length perception, thereby modulating seasonal estrus in sheep. Our study reveals a conserved circadian mechanism underlying seasonal breeding and highlights FBXL3 T183M as a promising genetic target for improving reproductive performance in sheep.

genetics↗

bioRxiv2026

Embedded transport accelerates interaction-limited biosensing

Phenotypic biosensors that measure bacterial viability and antimicrobial susceptibility are essential for rapid infectious disease diagnostics, yet their speed is fundamentally limited by the rate at which bacteria encounter reporter molecules, a transport bottleneck that has been typically addressed by complex microfluidic solutions. Here we show that this bottleneck can be overcome by engineering transport directly into the sensing material. A multifunctional ionic hydrogel matrix, co-encapsulating bacterial growth medium and the redox reporter resazurin, exploits swelling-driven convective transport to dramatically accelerate bacteria-reporter interactions without any change to assay chemistry. By systematically tailoring the hydrogel crosslinking density and optimizing the encapsulated nutrient-osmotic microenvironment, we maximize metabolic signal generation to achieve a 12-to-48-fold reduction in detection time relative to solution-phase and conventional hydrogel assays. Deployed in a standard 96-well format for urinary tract infection (UTI) diagnosis of 48 clinical samples, the platform rapidly detects infection in 15 minutes to 2 hours, achieving 95% sensitivity and 100% specificity for bacterial detection, and 100% sensitivity and 98% specificity for antimicrobial susceptibility profiling, compared to time-consuming gold-standard urine culture-based methods. Results are readable both quantitatively on a plate reader and visually as a colorimetric assay, enabling point-of-care deployment without additional instrumentation. Thus, embedding transport enhancement within the sensing matrix, represents a general and scalable design principle for accelerating interaction-limited biosensing, which has excellent scope for rapid diagnostic development.

bioengineering↗

bioRxiv2026

Multisensory integration of a host metabolite coordinates bacterial predation of macrophages

The crisis of antimicrobial resistance demands new strategies that circumvent conventional killing. Here, we show that Yersinia pseudotuberculosis intercepts host mesifurane, a mimic of quorum-sensing signal AI-2. Rather than acting through a single receptor, mesifurane is directly and independently sensed by three receptor classes, YcrA, NarX, and CusR, that converge on a "Sense, Arm, Recruit" program. YcrA drives chemotaxis toward host cells; NarX-NarP licenses T6SS-mediated killing; and CusR amplifies AI-2 production to recruit more bacteria. YcrA is conserved across Gram-negative pathogens, creating a therapeutic vulnerability. Suramin sodium, a repurposed drug blocking YcrA, disarms this circuit without inhibiting growth. In murine sepsis, suramin sodium conferred 80-90% survival against WHO critical-priority pathogens, including carbapenem-resistant A. baumannii, E. coli, and P. aeruginosa, even when delayed 8 hours post-infection, without selecting for resistance. These findings establish that disrupting sensory perception, rather than viability, provides an anti-infective strategy bypassing resistance while imposing minimal selective pressure.

microbiology↗

bioRxiv2026

Incorporation of single-neuron projectome-based connectivity motifs enhances the cortex-specific performance of artificial neural networks

The organizational principles of natural neural networks could inspire the new architecture design of artificial neural networks (ANNs). Analysis of single-neuron connectomes of mouse brains revealed distinct profiles of three-node connectivity motifs in various cortical areas and hippocampal formation. A connectome-informed neural network algorithm ("CINA") was developed to incorporate natural connectivity motifs into ANN algorithms represented by recurrent neural network (RNN) and transformer-based large language model (LLM). We found that incorporation of the average profile of cortical motifs improved the RNNs performance in noise-resistant categorization and motor learning benchmark tasks, as compared with RNNs with random connectivity. Notably, incorporating cortex-specific motifs further elevated the RNNs performance in tasks related to the cortical function, and this effect was enhanced by artificially increasing the bias in the motif profile. Similar experimental results were verified on an LLM using Motif-Transformer for natural language question answering and brain-signal decoding tasks. Graph-theoretic analyses showed that incorporating natural motifs drove the emergence of modular and small-world properties in ANNs. Together, we demonstrated not only connectome-inspired optimization of ANN architecture but also functional significance of specific motif profiles in various cortices.

neuroscience↗

bioRxiv2026

Lineage Memory and Convergent Adaptation Dictate the Single-Cell and Spatial Architecture of Brain Malignancies

How diverse cancer lineages navigate the draconian central nervous system environment--whether constrained by ancestral ontogeny or driven by convergent adaptation--remains a fundamental biological paradox. To decode this, we integrated extensive in-house and public resources to construct the largest single-cell atlas of primary and secondary brain malignancies (>550,000 cells). We demonstrate that malignant cells balance strict lineage imprinting with shared brain-adaptive programs, powerfully converging upon a dominant pan-cancer mesenchymal (MES)-like state alongside a SYT1+ pioneer subpopulation exploiting neuronal mimicry. Concurrently, the microenvironment undergoes lineage-constrained divergence. The myeloid landscape shifts from a resident-dominated architecture in gliomas to extensive blood-borne infiltration in metastases. Lymphoid responses parallel this, crowning laryngocarcinoma as an ultra-hot subtype and revealing that massive T cell influx in highly infiltrated niches is paradoxically driven into terminal exhaustion, contrasting with severe immune exclusion in cold tumors. Furthermore, stromal-vascular adaptation couples pro-angiogenic tip-endothelial activation with a dynamic opposition between structural extracellular matrix (ECM) deposition and focal proteolytic degradation. Anchored by the pan-cancer MES adaptation, we leveraged subcellular spatial transcriptomics to redefine the microenvironment around four MES-like architectural niches, mapping an evolutionary trajectory from perivascular entry to immunosuppressive stromal remodeling. Finally, projecting these architectures onto independent clinical cohort establishes the MES-S2 proliferative niche as the primary driver of severe clinical deterioration across both transcriptomic and proteomic dimensions.

Cancer Biology↗

bioRxiv2026

ARID4 Modulates Stomatal ABA Signaling and Stress-Responsive Gene Expression to Confer Drought Tolerance in Arabidopsis

To identify novel regulators of plant drought tolerance, we performed a forward genetic screen using thermal infrared imaging to detect alterations in leaf temperature, a proxy for transpiration. This screen identified AT-rich Interacting Domain Protein 4 (ARID4), a protein involved in chromatin remodeling, as a modulator of transpiration. arid4 loss-of-function mutants exhibited cooler leaves, increased water loss from detached leaves, and heightened susceptibility to drought relative to wild-type plants. Stomata of arid4 mutants were hyposensitive to abscisic acid (ABA), displaying reduced ABA-induced reactive oxygen species (ROS) production and impaired stomatal closure. Transcriptome profiling under drought revealed extensive misregulation of genes involved in stress-responses, redox homeostasis, iron acquisition, and photosynthesis. These findings indicate that ARID4 modulates the expression of key regulatory genes to maintain redox homeostasis and photosynthetic efficiency, thereby conferring drought stress tolerance.

Plant Biology↗

bioRxiv2026

The Origin and Evolution of Protein Synthesis: A Co-Adaptation Flexible-Rigid Docking Model Based on First-Principles Reasoning

Although the "RNA world" hypothesis suggests that RNA played a crucial role in the origin of life [7], the functional framework of RNA in prebiotic protein synthesis and the mechanisms of genetic code formation during the prebiotic period remain poorly understood. Here, using the prebiotic "primordial soup" as a model, we reconstructed the detailed steps that would yield a protein with a stable ordered amino-acid sequence in the "primordial soup" at the prebiotic period. In the "primordial soup", a large number of medium- to large-sized biomolecule-like substances--such as RNA-like and protein-like molecules of various sizes and shapes, as well as related polymers like amino-acid-RNA-like etc.--did generate and accumulate. Moreover, protein-like and RNA-like molecules formed even more intricate complexes. These complexes bound free mRNA-like molecules through complementary base pairing. Subsequently, with an extremely low probability, two adjacent amino-acid-RNA-like molecules became bound to this free mRNA-like molecule, and their amino acids underwent a condensation reaction by the complexes, producing peptides and eventually proteins or polypeptides. This free mRNA-like molecule exhibits a certain flexible structure, whereas the super-large complexes formed by protein-like and RNA-like molecules (which possess certain activities) and the amino-acid-RNA molecules exhibit relatively rigid structures. Long-term evolution and mutual selection led to the emergence of proteins with stable amino acid sequences and moderate catalytic activity. In this way, the nucleotide information embedded in such mRNA-like molecules indirectly express through protein synthesis--a process we term the "A Co-Adaptation Flexible-Rigid Docking Model", where flexible mRNA-like molecules dock onto rigid complexes to enable ordered peptide formation. Finally, we show how trinucleotide codons emerge naturally from the flexible-rigid docking constraints.

evolutionary biology↗

bioRxiv2026

Memory stabilizes complex ecological systems but delays full restoration

Memory effects--defined as the capacity of system states to exert long-lasting influence on subsequent dynamics--are widely recognized as central features of complex living systems. In ecological systems, however, their consequences for stability and recovery dynamics remain poorly understood. To fill this gap, we develop a general theoretical framework that incorporates memory into the dynamics of species-rich ecological systems with complex interaction structures. Our analyses reveal that memory effects expand the stability domain, enabling systems that would otherwise be unstable to persist following perturbations, particularly in cases where instability involves oscillatory behavior. At the same time, memory can accelerate short-term recovery, allowing systems to return more rapidly toward equilibrium in the early stages after perturbation. These apparent benefits, however, come at a cost: memory effects markedly slow long-term recovery, thereby delaying full restoration, as memory retains the influence of past perturbations and hinders a full return to equilibrium. We further support these results by integrating empirical data into the framework. Together, these results reveal fundamental trade-offs mediated by memory--enhanced stability and faster short-term recovery at the expense of delayed full restoration--highlighting the dual role of memory in shaping resilience in complex ecological systems and, more broadly, complex living systems.

ecology↗

bioRxiv2026

Scalable in vivo cardiac functional genomics with compressed AAV-Perturb-seq reveals a common mitochondrial response to perturbation

Efficient identification of new targets to treat human disease requires a scalable way to link genotype to phenotype directly in the target organ. Pooled CRISPR screening with single-cell RNA sequencing as a readout (Perturb-seq) has emerged as a method for functional genomics but is typically applied in vitro and is limited in scale. Here, we combine in vivo Perturb-seq via adeno-associated virus (AAV)-mediated delivery with a statistical framework allowing for signal deconvolution after multiple random perturbations per cell (compressed Perturb-seq), to develop in vivo compressed AAV-Perturb-seq, a scalable way to perform high-throughput, cell-autonomous functional genomics in a desired target organ. We apply this approach to study the effect of 585 gene knockouts on the cardiomyocyte transcriptome. We identify that alterations in the mitochondrial transcriptome are a common response to genetic perturbation, a finding independently validated across species and perturbation modalities. We identify very few synergistic perturbations, despite observing frequent combinatorial effects. Broadly, our work establishes a platform to facilitate in vivo functional genomics in a target organ with direct applicability to identifying therapeutic targets for the treatment of human disease.

genomics↗

bioRxiv2026

Rapid Determination of Drug-to-Antibody Ratios in Antibody Drug Conjugates Using Ultrafast Microdroplet Digestion Technology

Accurate determination of drug-to-antibody ratios (DARs) is essential for the development, quality control, and performance evaluation of antibody-drug conjugates (ADCs); yet conventional analytical approaches often require extensive sample preparation, long analysis time, and substantial sample consumption. The peak distribution of intact ADCs is highly complex due to inherent glycosylation heterogeneity and variable drug conjugation. By applying enzymatic digestion, ADC can be converted into smaller subunits or deglycosylated species, thereby significantly simplifying the mass spectral profile. This reduction in structural heterogeneity facilitates clearer peak assignment and enables more accurate and reliable DAR quantification. Herein, we report an ultrafast microdroplet digestion-mass spectrometry strategy for rapid DAR characterization of ADCs. Microdroplet enzymatic digestion of antibodies and ADCs occurs within microsecond-time scales during spray ionization, enabling direct online subunit analysis with minimal sample preparation. The method was validated using NIST monoclonal antibody (mAb) conjugated to ADC mimics spanning low to high DAR (0-14) ranges, Cetuximab-derived ADC mimics (DAR[~]5) with complex glycosylation, and the commercial ADC Kadcyla (DAR[~]3.5). Consistent DAR values were obtained across multiple enzymatic workflows (IdeS, EndoS2, and EndoF3) with good reproducibility (%CV typically <5%). This approach substantially reduces analysis time while maintaining analytical accuracy and structural specificity, providing a rapid, sensitive platform for high-throughput ADC characterization and process monitoring. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/729562v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@23145corg.highwire.dtl.DTLVardef@10ddd88org.highwire.dtl.DTLVardef@14b1370org.highwire.dtl.DTLVardef@1e94ad6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

Transcription factor CCTF1 plays a decisive role in regulating the proteasome activity during archaeal cell division

Archaea of the order Sulfolobales exhibit a highly ordered cell cycle progression similar to that of eukaryotes. It has been demonstrated that degradation of the cell division protein CdvB by the proteasome controls the progression of cell division. However, how the proteasome itself is regulated during the cell cycle is not fully understood. Recently, the cyclically expressed ArsR family transcription factor CCTF1 (cell cycle transcription factor 1) was shown to represses expression of PAN (proteasome-activating nucleotidase) in Sulfolobus acidocaldarius. Here, using biochemical approaches, comparative transcriptomics and proteomics, we provide further insights into the CCTF1 function and show that it regulates PAN expression in Saccharolobus islandicus by binding to an AT-rich palindromic sequence within the pan promoter. We also reassessed the role of the cyclically expressed protein kinase aCcrK in regulation of proteasome activity and conclude that CCTF1, rather than aCcrK, is the primary factor controlling the proteasome activity. These findings advance our understanding of the proteosome-mediated cell cycle regulation in archaea.

microbiology↗

bioRxiv2026

Learning residue-level context for modeling protein-protein interactions

Protein language models (PLMs) enable prediction of protein properties by learning residue-level features from sequence, yet most PLM-based approaches to protein-protein interactions aggregate information across entire proteins, limiting resolution and interpretability. Here we present ReCLIP, a transformer-based framework that learns interaction-specific representations at the level of individual residues by combining intra-protein residue neighborhoods with residue-conditioned representations of interaction partners. We show that residue-centered context provides a general framework for modeling protein interactions across diverse biological settings. ReCLIP accurately predicts mutation-induced perturbations (AUROC = 0.973), generalizes to post-translational modifications that do not alter sequence (AUROC = 0.822), and enables zero-shot prediction of peptide-MHC binding across unseen alleles (AUROC up to 0.972). Analysis of learned residue neighborhoods reveals structurally and functionally coherent patterns aligned with known determinants of binding. Applied to clinically annotated genetic variants, ReCLIP identifies disease-associated interaction perturbations that link pathogenic variants to specific molecular interaction contexts. Our results establish a generalizable and interpretable framework for modeling protein interactions and provide insights into how residue-level context shapes interaction specificity and its perturbation.

bioinformatics↗

bioRxiv2026

Generative design of programmable asymmetric β-barrel nanopores

Protein nanopores are powerful tools for molecular sensing, sequencing, and separation, but designing pores with programmable function remains challenging. Native homo-oligomeric transmembrane {beta} barrels (TMBs) are used for these applications, but their uniform lumens limit spatial resolution and analyte discrimination. Although monomeric TMBs can be designed using energy-based methods, these approaches remain highly manual and limited to structural design rather than function. Here, we present a generative AI framework for TMB design, with backbone and sequence design models trained on a curated distillation set. We characterized 48 designs spanning 0.7-1.5 nm in diameter, diverse lumen chemistries, and hydrophobic thicknesses. Crystal structures closely match the design models. We demonstrate that our method produces customizable nanopores for ion sensing, DNA translocation, and transport across polymer membranes.

biochemistry↗

bioRxiv2026

Spatiotemporal Cascade of AP1/CCA1-TOC1 Module Gates Stem Development

Stem development is crucial in plant vertical architecture and overall crop improvement. The molecular mechanisms underlying the initiation and circadian growth of stem remain still enigmatic. Here, we demonstrate that APETALA1 (AP1) spatially initiates circadian stem growth through a noncell-autonomous role of TIMING OF CAB EXPRESSION1 (TOC1) emanating from the floral meristem to inflorescence meristem in Arabidopsis thaliana. Mechanistically, AP1 interacts with and recruits CIRCADIAN CLOCK-ASSOCIATED1 (CCA1) to associate TOC1. Dynamic formation of the AP1-CCA1 complex is crucial for maintaining the circadian rhythmicity and expression of TOC1. Tissue-specific expression of TOC1 in floral meristems rescues the developmental defects of toc1 mutants at both functional and transcriptional levels. Furthermore, TOC1 directly activates the circadian expression of pectin methylesterase gene family, which is critical for its role in stem development. AP1 homologs regulate circadian stem elongation and plant height in wheat and rice, underscoring the conserved mechanism across flowering plants. Our findings uncovered a spatiotemporal regulatory cascade gating stem development and identified candidate genes for crop improvement.

plant biology↗

bioRxiv2026

Alginate-Coated Collagen Hydrogel Tubes for Scalable Cell and Biotherapeutic Particle Manufacturing

Efficient, scalable, and cost-effective production of mammalian cells and biotherapeutic particles remains a major challenge for both research and clinical applications. Conventional 2D and 3D culture systems suffer from low volumetric yields, poor scalability, and high costs. Previously, we developed collagen hydrogel tube microbioreactors (ColTubes) that support high-density, high-viability cell culture by preventing excessive cell aggregation and minimizing hydrodynamic stress. However, ColTubes exhibit adhesion to culture vessels and to each other, and leaked cells frequently attach to outer tube surfaces -- behaviors that would limit scalability. Here we introduce AlgColTubes: collagen hydrogel tubes coated with a thin, ionically crosslinked alginate layer to overcome these limitations. Scanning electron microscopy confirms that alginate penetrates the collagen wall and forms a stable interpenetrating hydrogel network, whose depth can be tuned by coating concentration and duration. The alginate coating remains structurally intact under static and dynamic culture conditions without impairing nutrient transport or cell growth. AlgColTubes eliminate tube-tube and tube-vessel adhesion, and prevent exogenous cell attachment to the outer surface, while maintaining cell viability and proliferation comparable to uncoated ColTubes. Their unique architecture -- an adhesive collagen interior and non-adhesive alginate exterior -- further enables a truncated-tube format for continuous release of biotherapeutic particles through open tube ends. We demonstrate that lentivirus is released from truncated AlgColTubes in a segment length-dependent manner, reaching ~100% release efficiency at 1-mm segment lengths. AlgColTubes provide a scalable, cost-effective platform for high-yield cell and particle manufacturing, with broad potential across basic research, translational studies, and industrial bioprocessing.

bioengineering↗

bioRxiv2026

Proton FLASH preserves neurocognition across delivery techniques: implications for clinical translation in pediatric brain tumors

BackgroundRadiation therapy is integral to the curative treatment of childhood brain tumors but contributes to late neurocognitive impairment in survivors. FLASH (ultra-high dose rate, >40Gy/s) reduces normal-tissue toxicity in preclinical models, and proton-FLASH is currently the only modality capable of delivering ultra-high dose rates to the deep targets, such as pediatric brain tumors. However, two questions remain unresolved before clinical translation: (1) whether the FLASH effect can be achieved on synchrotron-based proton systems, which deliver protons in discrete spills that may be insufficient to cover a clinical target within a single delivery, and (2) which dose-rate metric, among the multiple definitions currently used in the field, best predicts the biological FLASH effect. MethodsC57BL/6 mice (7-8 weeks) received 10 Gy whole-brain RT via a clinical Hitachi ProBEAT synchrotron with CBCT-guided delivery, using three transmission-beam techniques: single-spill pencil beam scanning (SS PBS), multi-spill PBS with [~]2-second inter-spot delay (MS PBS), and passive scatter (PS), compared to conventional (CONV) delivery and unirradiated controls (n=24-28/group, equal sex distribution). Dose rate was quantified using three frameworks: field dose rate (FDR), PBS dose rate (PBSDR), and dose-averaged dose rate (DADR). Recognition memory was assessed by novel object recognition (NOR) at 6 weeks post-RT, and cognitive flexibility was assessed via touchscreen visual discrimination and reversal learning at 14 weeks. Hippocampal neuroinflammation was evaluated by immunofluorescence and immunohistochemistry for Iba1, NeuN, and GFAP. ResultsFLASH conditions were met by SS PBS and PS under all three dose-rate definitions, but MS PBS qualified as FLASH only by DADR. Despite this, neuroprotection was preserved across all three FLASH techniques: discrimination index was significantly higher for SS PBS (P=0.021), MS PBS (P=0.008), and PS (P<0.001) versus CONV, with no significant difference between FLASH techniques. On touchscreen testing, FLASH-treated females demonstrated preserved cognitive flexibility (P=0.047 vs. CONV on reversal learning correct trials). Iba1+ microglia were reduced in FLASH compared to CONV mice, with morphology suggestive of preserved homeostatic state. ConclusionsSynchrotron-based proton FLASH preserves neurocognitive function across all delivery techniques, including under multi-spill delivery essential for treating clinical-scale pediatric brain tumors. Critically, this neuroprotection was observed even for deliveries that qualified as FLASH only by DADR, identifying DADR as the dose-rate metric most relevant to the biological FLASH effect with direct implications for clinical trial design and dose-rate reporting standards.

cancer biology↗

bioRxiv2026

Levodopa increases substantia nigra iron: implications for Parkinson's disease

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSExcessive or unregulated iron in the brain can lead to toxicity via ferroptosis and related mechanisms. Iron accumulation in the substantia nigra (SN) occurs with Parkinsons disease (PD) progression and has been hypothesized to be an etiological mechanism. ObjectiveBased on emerging clinical observations, we tested the hypothesis that iron accumulation in the SN is a consequence of levodopa administration and is treatment-related rather than an intrinsic etiological mechanism. MethodsWe used both unilaterally lesioned 6-OHDA and unlesioned rats. We administered levodopa to rats at doses that were allometrically calculated to be similar to those used in mid-stages of PD. Iron-sensitive MRI (R2*) was used to quantify iron in the brain. Both group and intra-subject analyses were done using paired t-tests and linear mixed models. ResultsExperiment 1 used the unilateral 6-OHDA model to take advantage of the almost complete lack of dopamine neurons on the lesioned side. This permitted testing if levodopa-induced iron accumulation occurred in and/or depended on dopamine neurons. Fifteen days of levodopa treatment caused a marked increase in Fe in both the lesioned (p = 0.042) and unlesioned sides (p = 0.005), showing that iron accumulation does not depend on the presence of dopamine neurons. Based on these data, in experiment 2 unlesioned rats were administered levodopa daily for four months, and iron (R2*) values were assessed at baseline, 1, 2, and 4 months. In these normal rats, the levodopa-treated group had significantly increased Fe (R2*) in the substantia nigra compared to the vehicle group (p = 0.013). Interestingly, these effects were limited to the striatum, with no increases seen in the striatum, ventral tegmental area, or frontal cortex ConclusionLevodopa triggers processes that increase iron deposition in the substantia nigra, but this process may not depend on dopamine neurons. The underlying mechanisms and the effect on PD progression are important to elucidate and may transform how we understand PD and related neurodegenerative disorders

neuroscience↗