Biology subjects

Jiang, X.

Publications and source records attributed to Jiang, X..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

Human brains implicitly and rapidly distinguish AI from human voices before decoding prosodic meaning

People encounter AI voices daily. Existing behavioral studies suggest listeners rely on prosodic cues such as intonation and expressiveness to detect audio deepfakes, reporting that AI voices sound prosodically less rich than human voices. To test whether prosodic processing drives deepfake discrimination in the neural time course of voice processing, we recorded electroencephalographic (EEG) data while participants listened to human and AI-generated speakers producing utterances in confident vs. doubtful prosody (tone of voice), with attention directed toward memorizing speaker names. We used voice cloning to control for speaker identity confounds between human and AI voices. Multivariate pattern analysis revealed that neural discrimination of human vs. AI voices emerged rapidly regardless of prosody (confident: 176 ms; doubtful: 134 ms), substantially preceding prosody discrimination (confident vs. doubtful within human voices: 2066 ms; within AI voices: 1366 ms). Acoustic analysis confirmed that prosodic distinctions became classifiable only at utterance offset (90% normalized duration), converging with neural evidence that prosody requires near-complete temporal integration. This temporal dissociation between rapid voice source discrimination and late-emerging prosody decoding suggests that prosody plays a smaller role in audio deepfake detection than listeners retrospectively report. Representational similarity analysis further revealed that spectral envelope features (mel-frequency cepstral coefficients; MFCC), rather than the visually salient high-frequency energy differences, drove neural human-AI discrimination, with MFCCs earliest independent contribution (228 ms) closely following the MVPA decoding onset (134-176 ms). Future studies may manipulate specific acoustic components to establish the causal sources of this rapid and sustained neural discrimination. Significance StatementPeople encounter AI voices daily, in phone calls, navigation apps, supermarket checkouts, and subway announcements. Using electroencephalography, we show that the human brain automatically and rapidly distinguishes everyday AI voices from human speech, even without conscious attention to voice source. Although people may attribute this ability to AI voices sounding monotone or prosodically unnatural, the brain relies on subtler acoustic signatures, enabling discrimination before prosodic information becomes available. Attempts to identify the specific acoustic features driving this neural detection were inconclusive, pointing to the need for future causal investigations. We encourage engineers and policymakers to ensure AI voices remain perceptually detectable, as increasingly humanlike AI voices could cognitively disadvantage the general public if they become indistinguishable from human speech.

neuroscience↗

bioRxiv2026

Gallium induces cytotoxicity through disruption of DNA synthesis rather than ferroptosis

BackgroundGallium (Ga) is a promising anti-tumor agent; however, its precise molecular targets in osteosarcoma remain debated. While current paradigms largely attribute its toxicity to reactive oxygen species (ROS) and ferroptosis, understanding its true mechanism is essential for overcoming therapeutic resistance. This highlights the need for interdisciplinary approaches, such as metabolomics, to unveil novel vulnerabilities in cancer metabolism. MethodsWe employed an interdisciplinary strategy utilizing high-resolution liquid chromatography-mass spectrometry (LC-MS) metabolomics and 13C2-glutamine stable isotope tracing in osteosarcoma cells to elucidate the cytotoxic mechanisms of gallium nitrate. Scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDS) was utilized for elemental mapping, and in silico modeling was applied to evaluated metal binding dynamics. Furthermore, synergistic effects were tested by combining gallium with the DNA-damaging agent cisplatin. ResultsOur metabolic profiling revealed a profound bifurcation characterized by the systemic depletion of glycolysis and pentose phosphate pathway intermediates, coupled with a novel ribonucleotide accumulation bottleneck. The observed distinct signature strongly implicated ribonucleotide reductase (RNR) as the primary enzymatic target. In silico modeling and SEM-EDS visually and thermodynamically confirmedthat gallium acts as a structural decoy for iron within the RNR active site. The co-localization induces functional iron starvation rather than canonical ferroptosis. Furthermore, isotope tracing confirmed that elevated ROS is a consequence of overall metabolic failure, not the primary driver of cell death. Crucially, gallium functioned as a metabolic DNA repair inhibitor, synergizing potently with cisplatin to prevent the repair of platinum-induced DNA lesions. ConclusionsGallium selectively sensitizes highly proliferative sarcoma cells by disrupting RNR-mediated DNA precursor synthesis, while sparing normal osteoblasts. Leveraging metabolomics to uncover this state of functional iron starvation provides a rational, interdisciplinary framework for developing gallium-based combination therapies designed to break platinum resistance in clinical oncology.

cancer biology↗

bioRxiv2026

The structure-interaction model of polymyxin lipopeptides with human oligopeptide transporter 2

Multidrug-resistant (MDR) Gram-negative bacteria pose a critical global health threat, while polymyxins remain a last-line therapy. However, their clinical use is limited by nephrotoxicity. Human oligopeptide transporter 2 (hPepT2) is a membrane transporter mediating the reabsorption of polymyxins in renal cells and contributes to their nephrotoxicity, but the molecular basis of their interaction remains unclear. Here, we investigated the structure-interaction relationship (SIR) of polymyxins with hPepT2 by integrating computational, chemical, and cell biology approaches. Bioinformatic modelling predicted an outward-facing hPepT2 structure and a potential transport pathway, with polymyxins interacting at the lateral opening, particularly E214, D215, D317, D342, and E622. Transporter mutagenesis and molecular analyses confirmed that D215 is critical for polymyxin binding, while other residues influence transporter turnover and/or expression. We subsequently synthesised polymyxin analogues with modifications at Dab1, Dab3, Dab5, and Dab9 of polymyxins, which reduced interactions with hPepT2. Notably, alanine substitution at Dab3 reduced nephrotoxicity in mice while retaining antibacterial activity. Overall, this proof-of-concept study demonstrates that the hPepT2-polymyxin SIR model provides a viable strategy for developing novel, safer lipopeptide antibiotics.

biochemistry↗

bioRxiv2026

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

Designing microbial communities to generate target products is crucial for biotechnology, agriculture, and disease treatment. However, rationally designing such communities from large seed pools has become a major challenge, as the rapidly expanding number of complete microbial genomes greatly expands the search space and sharply increases the required screening time and computational cost. Here, we introduce eBiota, a platform for ab initio design of microbial communities from a pool of 21,514 strains to generate target products. eBiota not only identifies optimal strain combinations but also simulates community behaviors, including microbial interactions and relative abundances. eBiota integrates three modules: CoreBFS, a graph-based search algorithm that rapidly screens for bacteria with complete metabolic pathways related to the target product; ProdFBA, an extended flux balance analysis that identifies microbial consortia with maximal production efficiency; and DeepCooc, a deep learning model trained on 23,323 microbiome samples across various environments to infer co-occurrence patterns. We validated eBiotas capabilities in microbial community design and production efficiency calculation using public microbiome datasets, ranging from single strains to six-member consortia. Further in vitro experiments involving 94 strains confirmed eBiotas ability to identify species that inhibit pathogen growth and to accurately model the relative abundances within complex microbial communities. As an initial digital twin, eBiota provides a powerful platform for the rational design of functional microbial communities, offering new opportunities for metabolic engineering and synthetic biology.

bioengineering↗

bioRxiv2026

KuafuPrimer: Machine learning empowers the design of 16S amplicon sequencing primers toward minimal bias for bacterial communities

Amplicon sequencing protocol targeting the 16S rRNA gene is a widely used and cost-effective method for exploring bacterial communities. However, its performance is often limited by primer bias arising from the arbitrary use of universal primers across diverse microbial communities and habitats. We propose KuafuPrimer to design the optimal 16S rRNA gene primers toward minimal bias for targeted bacterial communities, using few-shot machine learning to guide the primer design procedure based on a small number of samples. Simulations on 809 samples across 26 representative environments and habitats showed that KuafuPrimer-designed primers outperformed the universal primers in taxonomic accuracy, achieving an averaged 16.31% relative reduction in primer bias, with reductions up to 46.08% in plant samples. Notably, KuafuPrimer detected 29 rare and key taxa undetectable by the universal primers. Validation with 317 longitudinal gut microbiota samples demonstrated that KuafuPrimer-designed primers consistently outperformed the universal primers across temporal, individual, and cohort levels, with relative bias reductions of 5.03%, 3.53%, and 3.10%, respectively. Finally, in real PCR experiments on human gut samples from Clostridioides difficile-infected and healthy groups showed that polymerase chain reaction products using KuafuPrimer-designed primers correlated better with metagenomic data compared to the universal primers. More importantly, KuafuPrimer successfully detected Clostridioides difficile, the key pathogen missed by the universal primers, highlighting its potential for improving clinical diagnostics. In summary, KuafuPrimer provides a machine learning-based primer design strategy for targeted bacterial communities, with demonstrated utility in large-scale microbiome initiatives, longitudinal surveys and clinical diagnostics.

bioinformatics↗

bioRxiv2026

LAMBDA: A Prophage Detection Benchmark for Genomic Language Models

Transformer-based genomic sequence models represent an emerging frontier in computational biology. Yet, their embeddings have not yet shown the same level of predictive power as natural and protein language models, highlighting a gap between current implementations and theoretical promise. Existing benchmarks for DNA language models primarily focus on classifying regulatory elements in eukaryotic genomes, leaving open the fundamental question of whether these models learn sequence-level features across whole genomes. We introduce LAMBDA, a benchmark designed to rigorously evaluate genome language model embeddings through phage-bacteria sequence discrimination across four categories of increasing complexity: probing tasks, fine-tuning assessments, diagnostic tests, and genome-wide prophage detection. Our comprehensive analysis of current genomic language models provides insight into the importance of training data selection relative to model size, the need for domain-specific training, and the capabilities and limitations of genomic language models for detecting prophage sequences. This benchmark represents a challenging genomic annotation task in the bacterial domain and addresses a key computational problem with direct relevance to microbiology and medicine.

genomics↗

bioRxiv2026

Reliability and Spatiotemporal Autocorrelation of Acoustic Indices: Implications for Biodiversity Monitoring

Passive acoustic monitoring (PAM) is increasingly applied in biodiversity research, yet its reliability as a proxy for biodiversity remains insufficiently evaluated. In particular, the spatiotemporal autocorrelation inherent in acoustic indices of PAM is rarely quantified, despite its importance for the standardized application of acoustic monitoring. We conducted an integrated study to investigate these issues using a complete grid-based monitoring system covering the entire region (100 grids of 1 km x 1 km) in southern subtropical climatic zones. Acoustic data from 58 valid sites were combined with camera-trapping and vegetation surveys to evaluate six commonly used acoustic indices in PAM. We found that these indices were more strongly associated with relative abundance and community diversity metrics of bird and mammal than with species richness. Spatially, autocorrelation ranges of some acoustic indices extended to approximately 4 km (i.e., the Bioacoustic Index (BIO) and Normalized difference soundscape index (NDSI)). Temporally, all indices exhibited significant autocorrelation over 2-5 days, exceeding the typical short-term turnover of bird and mammal activity (1-2 days). Our results indicate that acoustic indices are not direct proxies for species richness but provide complementary information on soundscape dynamics. By explicitly quantifying spatiotemporal autocorrelation, this study offers practical guidance for sampling design and statistical analysis in passive acoustic monitoring, supporting more reliable and efficient biodiversity assessment.

ecology↗

bioRxiv2026

Study of the molecular nature of resistance to bifenazate in a Tetranychus urticae Koch Laboratory Strain

BACKGROUNDThe two-spotted spider mite, Tetranychus urticae Koch, is a major agricultural pest with a rapid propensity for developing acaricide resistance. Bifenazate targets mitochondrial cytochrome b (CYTB). While the G126S mutation is frequently associated with resistance, its independent role remains unclear as it often occurs with other substitutions. This study explores the molecular basis of bifenazate resistance in a Russian laboratory strain derived from a St. Petersburg greenhouse population. RESULTSDisruptive selection with increasing bifenazate concentrations generated resistant and susceptible isofemale lines. AlphaFold2 structural modeling of CYTB indicated that G126S causes a steric clash, leading to conformational destabilization, whereas other reported mutations primarily affect the ligand-binding pocket. Oxford Nanopore sequencing revealed a very low initial frequency of the G126S allele (<1%; 226/35,895 reads) in the unselected population. After one year of stepwise selection (0.00005-0.031% a.i.), the mutant allele frequency surged to 90% (7,272/8,056 reads). No other known resistance-associated mutations were found in the analyzed cytb fragment. CONCLUSIONWe report the first identification of the G126S mutation in a Russian T. urticae population and demonstrate its rapid fixation under bifenazate selection. Within this genetic background, G126S alone appears sufficient to confer high-level resistance, emphasizing the population-specific nature of resistance evolution and the critical need for local monitoring.

molecular biology↗

bioRxiv2026

CESAR: High-Sensitivity Detection of Copy Number Variations in ctDNA Using Segmentation and Anchor Recalibration

BackgroundDetecting copy number variations (CNVs) in circulating tumor DNA (ctDNA) is crucial for the companion diagnosis and resistance monitoring of various solid tumors (e.g., NSCLC, Glioblastoma). However, when tumor-derived DNA fractions are extremely low (often <1%), traditional depth-based methods frequently fail due to non-linear sequencing depth fluctuations and probe-specific capture biases inherent to targeted Next-Generation Sequencing (NGS). MethodsWe developed CESAR (CNV Estimation with Segmentation and Anchor Recalibration), a computational tool for tumor-only CNV detection in targeted NGS panels. CESAR uses Circular Binary Segmentation (CBS) to re-partition target regions according to relative capture efficiency, then applies a data-driven "anchor" selection procedure that, for each target segment, identifies a personalized set of co-varying genomic segments. By selecting the anchor set that minimizes the coefficient of variation (CV) of the anchor-recalibrated depth ratio across a panel of normals, CESAR recalibrates the per-segment baseline and suppresses probe-specific technical noise. Copy-number status is then called from the deviation of the observed ratio against this trained baseline. ResultsUsing standard DNA reference materials, CESAR identified amplifications of MET, ERBB2, and EGFR at low tumor fractions. CESAR resolved focal alterations as subtle as 2.18 copies (a 1.09-fold change relative to the diploid baseline) while reporting no false-positive amplifications in diploid control regions. Applied to a clinical cohort of nine NSCLC ctDNA samples profiled on a 94-gene panel, CESAR successfully separated three MET-amplified samples from six matched negatives, where the standard CNVkit-based pipeline failed to distinguish them. In head-to-head benchmarking on identical data, CESAR reduced technical variance relative to the widely used CNVkit and more reproducibly resolved low-level copy-number gains, particularly in the depth-heterogeneous MET amplicon. ConclusionsCESAR provides a stable and sensitive framework for tumor-only CNV calling in liquid biopsies. On reference standards it outperforms CNVkit in bias and reproducibility, and on a clinical NSCLC cohort it recovered MET CNV abnormalities that a standard CNVkit pipeline missed. Validation on larger and more diverse cohorts is warranted.

bioinformatics↗

bioRxiv2026

Antibody recycling via FcRn drives atherosclerotic plaque vulnerability

Atherosclerotic plaques accumulate low-density lipoprotein (LDL) together with antibodies targeting LDL and its apolipoprotein B (apoB) component. Given the association between IgG and plaque vulnerability, we hypothesized that apoB-specific immune complexes actively promote plaque destabilization. Using immunohistochemistry in carotid endarterectomy specimens, we quantified antibody deposition across morphologically defined plaque regions, and measured apoB reactivity and immune complex levels in matched plaque and plasma samples. IgG deposition was strongly associated with thin fibrous caps, reduced collagen content, and higher overall plaque vulnerability. Symptomatic patients exhibited increased apoB-specific IgG and reduced apoB-IgG immune complexes within plaques, indicating enhanced IgG recycling and heightened inflammatory activity. The neonatal Fc receptor (FcRn) was predominantly expressed by CD163+ macrophages, and mediated antibody recycling, LDL uptake, and production of tumor necrosis factor (TNF) and matrix metalloproteinase-9 (MMP-9) in vitro. Plaque FcRn expression increased with age and correlated with mediators of vulnerability, including collagen-degrading enzymes and pro-inflammatory cytokines. Ex vivo treatment of human plaques with a clinically used FcRn-blocking monoclonal antibody reduced IgG recycling and suppressed TNF and MMP-9 production. These findings identify FcRn-dependent antibody recycling as a contributor to inflammatory plaque vulnerability and highlight FcRn as a potential therapeutic target in atherosclerosis.

immunology↗

bioRxiv2026

Global O-GlcNAcome Identifies O-GlcNAcylated Proteins Regulating Oligodendrocyte Precursor Cells Differentiation

Oligodendrocyte precursor cells (OPCs) differentiate into myelinating oligodendrocytes to form the myelin sheaths essential for neural function, a process frequently compromised during aging and in diseases like multiple sclerosis. However, the regulatory landscape of myelination remains incompletely understood. Here, we perform a comprehensive proteomic analysis of the O-GlcNAcome in postnatal day 0 mouse OPCs, identifying 165 O-GlcNAcylation sites across 118 proteins. These proteins are mostly nuclear and characterized by single-site modifications. Comparative analysis identifies 74 novel sites and 22 proteins uniquely O-GlcNAcylated in OPCs. Molecular docking suggestes that O-GlcNAcylation might act as a dynamic regulator of OPC differentiation. Notably, global O-GlcNAcylation levels increase during the OPC-to-oligodendrocyte transition. By integrating our findings with multiple sclerosis-related transcriptomic and proteomic datasets, we identify candidate proteins linking O-GlcNAc dysregulation to demyelination. Among these, Vimentin (Vim) exhibits a pronounced age-dependent discrepancy between decreased protein levels and elevated mRNA expression during differentiation. We validate Threonine 35 and 63 as key O-GlcNAcylation sites on Vimentin. Functional assays confirm that blocking Vimentin O-GlcNAcylation enhance the OPC differentiation. Collectively, our study establishes the first O-GlcNAc landscape for OPCs and suggests O-GlcNAcylation as a pivotal regulator for OPC differentiation.

neuroscience↗

bioRxiv2026

Statins and genetic inhibition of the mevalonate pathway activate an ATF3-STMN2 regenerative program

Loss of neuronal regenerative capacity is a common feature of neurodegenerative disease and axonal injury, yet the transcriptional programs governing this state remain poorly defined. Stathmin-2 (STMN2), a tubulin-binding protein essential for axon maintenance and repair, is profoundly depleted following loss of nuclear TDP-43 in neurodegenerative disease. Here, we identify statins as potent inducers of STMN2 expression. Pharmacological and genetic suppression of the mevalonate pathway, and subsequent prevention of protein geranylgeranylation, restored STMN2 levels in TDP-43 deficient cells and promoted neurite growth. STMN2 induction was abrogated when using a statin analogue unable to interact with HMG-CoA reductase, and through co-administration of mevalonate or geranylgeranyl diphosphate substrates. RNA-seq revealed that statins induce a coordinated pro-regenerative transcriptional response, including activation of the AP-1 transcription factor complex gene, ATF3. Loss of ATF3 attenuated STMN2 induction in vitro, and diminished injury-induced Stmn2 upregulation in spinal motor neurons in vivo. These results demonstrate statins as modulators of ATF3 and STMN2 expression and highlight their therapeutic potential in neurodegenerative disease.

neuroscience↗

bioRxiv2026

Nonanticoagulated Heparin Derivatives Mediate Goblet Cell Differentiation to Restore the Mucosal Barrier for Ulcerative Colitis Therapy

Epithelial mucus barrier dysfunction is a pathological hallmark of ulcerative colitis (UC), yet current clinical therapeutic strategies primarily suppress inflammation, lacking reliable approaches for restoration of the mucosal layer. Here, through a systematic screen of our established library of deanticoagulated heparins, we identified NALHP, a non-anticoagulant low-molecular-weight heparin derivative, and its representative fraction S6 as orally active epithelial repair-promoting glycans. NALHP/S6 restored crypt architecture, mucus production and epithelial barrier integrity in experimental colitis. In UC patient-derived colonic organoids, NALHP/S6 reduced aberrant stem/proliferative programs while promoting secretory, absorptive and junctional maturation. Single-cell transcriptomics and temporal validation identified a transient repair-secretory transitional state (RSTS) positioned between classical Wnt-associated stemness and mature barrier-forming epithelial states. Transcriptomic analysis revealed coordinated attenuation of Wnt and Notch signaling, whereas pharmacological reactivation of these pathways opposed NALHP/S6-induced epithelial state progression. These findings define mucosal repair as a regulated epithelial-state transition and identify NALHP/S6 as glycan-based modulators capable of restoring this progression in UC epithelium.

pathology↗

bioRxiv2026

Structural mechanism of Necrocide 1 activation of human TRPM4 that triggers necrosis by sodium overload

The small molecule Necrocide 1 (NC1) constitutively activates human TRPM4, triggering Na influx and leading to necrotic cell death, a process termed Necrosis by Sodium Overload (NECSO). NC1 activation is specific to human TRPM4 and does not affect most of the other mammalian TRPM4 orthologs. Here, we elucidate the molecular mechanism underlying NC1 activation and its species-specific selectivity for human TRPM4 using a combination of single-particle cryo-EM, electrophysiology, and cell death assays. We identify the NC1-binding site and the key molecular determinants responsible for channel activation. In addition, we explain the insensitivity of mouse TRPM4 to NC1 and pinpoint specific residues that define NC1 specificity for human TRPM4. Given the upregulation of TRPM4 in various human cancers, our mechanistic insights into NC1 activation and specificity provide a framework for the potential development of cancer therapeutics targeting TRPM4-mediated necrosis.

biophysics↗

bioRxiv2026

Targeting Circulating FABP4 Ameliorates Obesity-Associated Hepatic Steatosis

Obesity is a major driver of hepatic steatosis, yet the molecular link between excess adiposity and hepatocellular lipid accumulation remains incompletely defined. Here, we identify circulating fatty acid-binding protein 4 (FABP4) as a key mediator of adipocyte-hepatocyte lipid crosstalk in obesity. Analyses of human liver specimens and mouse models reveal aberrant accumulation of FABP4 protein--but not transcript--in hepatocytes during steatosis, indicating an extrinsic source. Genetic deletion of FABP4, specifically in adipocytes, protects against high fat diet-induced hepatic steatosis without altering obesity or systemic lipid levels. Mechanistically, circulating FABP4 directly binds to hepatocytes, facilitating free fatty acid uptake. Furthermore, we developed a high-affinity humanized monoclonal antibody that selectively neutralizes circulating FABP4, blocks hepatocyte binding, suppresses fatty acid uptake, and markedly attenuates hepatic steatosis in multiple obese mouse models. These findings establish circulating FABP4 as a pathogenic lipid chaperone and a promising therapeutic target for obesity-associated hepatic steatosis. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/701451v1_ufig1.gif" ALT="Figure 1"> View larger version (61K): org.highwire.dtl.DTLVardef@5b91d5org.highwire.dtl.DTLVardef@1c34892org.highwire.dtl.DTLVardef@1d17ea9org.highwire.dtl.DTLVardef@d2b43c_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIHepatocytic accumulation of extrinsic FABP4 links adiposity to liver lipid deposition. C_LIO_LISpecific deletion of FABP4 in adipocytes prevents hepatic steatosis without affecting systemic lipid levels or obesity. C_LIO_LICirculating FABP4 derived from adipocytes directly binds hepatocytes to facilitate free fatty acid transfer. C_LIO_LIBlocking circulating FABP4 with a high-affinity anti-FABP4 monoclonal antibody inhibits hepatocyte lipid uptake and attenuates steatosis in multiple obese mouse models. C_LI

pathology↗

bioRxiv2026

Ultrasensitive, Low-Input Detection of Avocado Sunblotch Viroid via RPA-CRISPR and Nanopore-Array Single-Bead Fluorescence Readout

Rapid and sensitive detection of plant pathogens, such as the Avocado Sunblotch Viroid (ASBVd), is essential for early disease management and agricultural biosecurity. Yet, most current diagnostic methods not only require relatively large sample inputs but also often lack the ultrasensitivity required for reliable detection with scarce or minimally collected plant material. Here, we report a novel low-input but ultrasensitive diagnostic platform that integrates isothermal recombinase polymerase amplification (RPA), CRISPR-Cas12a detection, and a solid-state nanopore array for the detection of ASBVd. The system leverages CRISPR-Cas12a collateral cleavage activity to generate single-bead fluorescent signals, which are captured by a nanopore array through pressure-driven blockage. Our platform achieves a detection limit down to 1.68 copies/L while using only 40 nL of bead-fluorophore mixture per readout, which is over 100-fold less than conventional assays based on fluorescent readout using an imaging reader, enabling detection from minimal avocado sample collection. We demonstrate robust binary classification of ASBVd-positive and -negative samples from multiple avocado tissue types and orchards in California. The assay requires just 60 minutes and operates entirely under isothermal conditions, avoiding the need for bulky PCR instruments and supporting on-site deployment with minimal equipment. This method provides a promising platform for field-deployable, ultrasensitive, and low-input diagnostics of viroids and other low-titer pathogens in plant or clinical settings.

bioengineering↗

bioRxiv2026

Iron Deficiency Drives Sarcopenia in the Elderly: HIF-1α-Mediated Fibro-Adipogenic Progenitor Differentiation Induces Fat Infiltration and Impairs Muscle Function

Abnormal iron metabolism is closely linked to sarcopenia; however, the specific iron metabolism features of fat-infiltrating sarcopenia remain poorly understood. Proteomic sequencing revealed that in skeletal muscle with severe fat infiltration, the expression of iron utilization-related proteins was significantly downregulated, whereas that of iron uptake and storage proteins was markedly upregulated, thereby presenting an abnormal iron deficiency (ID) phenotype. Nevertheless, the mechanism by which ID drives intramuscular fat infiltration has not been fully elucidated. Using clinical samples, aged murine ID models, and in vitro cell assays, this study is the first to demonstrate that ID stabilizes hypoxia-inducible factor-1 (HIF-1), promoting aberrant adipogenic differentiation of fibro-adipogenic progenitors (FAPs), disrupting the homeostatic balance between satellite cells (SCs) and FAPs, exacerbating skeletal muscle fat infiltration, and impairing muscle repair capacity. Notably, treatment with the HIF-1 inhibitor PX478 reversed these pathological alterations and improved muscle function. Collectively, our findings identify the ID-HIF-1-FAPs axis as a key driver of intramuscular fat infiltration, offering a novel therapeutic target for the clinical management of fat-infiltrating sarcopenia.

cell biology↗

bioRxiv2026

Joint Segmental Duplication Co-option Drives Human-specific Transcriptional Readthrough and Expression Fine-tuning of NPEPPS-TBC1D3

Segmental duplication (SD) is a major driver of functional changes in evolution and disease. Many genes embedded within SDs, such as NPEPPS and TBC1D3, display substantial copy number variation (CNV) across individuals. Yet, the precise identification of the functional copies and their transcriptional outputs remains largely unstudied. Focusing on NPEPPS and TBC1D3, we illustrate human-specific expression fine-tuning mechanisms associated with readthrough transcripts. We identified a human-specific NPEPPS-TBC1D3 digenic genomic structure that originated from a joint SD pair and became fixed across populations. Experiments demonstrate that this structure generates NPEPPS-TBC1D3 readthrough transcripts, which are the predominant isoforms of TBC1D3 expression in various cell types, fine-tuning its protein level. Furthermore, a human-specific hypomethylation signal within an upstream CpG island of NPEPPS precisely pinpoints the expressed TBC1D3 paralog. Moreover, we reveal transcriptional readthrough events are [~]3-fold enriched for joint-SD-associated transcriptional readthrough (JSDTR) and identify 109 JSDTR gene pairs, including neurodevelopmentally important pairs and clinically interesting SERF1A/B-SMN1/2. Taken together, our findings comprehensively describe an example of how a joint SD event shaped evolution and suggest that JSDTR is a broad mechanism for the emergence of new functions.

genetics↗