Biology subjects

Jeong, J.

Publications and source records attributed to Jeong, J..

At least 19 recordsLinked to original sources

bioRxiv2026

Stabilizing gas in aqueous liquids with metal-organic frameworks for persistent acoustic transduction

Gas is the most efficient mediator of acoustic energy owing to its high compressibility, yet its thermodynamic instability in aqueous environments makes it inherently transient, limiting sustained ultrasound-biological interfacing. Here, we show that gas can be stabilized, confined, and manipulated in the liquid phase to function as a persistent acoustic transducer. By trapping gas within designed microporous metal-organic framework (MOF) nanocrystals, interfacial forces establish a stable ternary-phase equilibrium that suppresses water intrusion and prevents gas collapse, enabling reversible, non-destructive oscillations under ultrasound stimulation and providing design principles for stabilizing gas in liquid environments. By leveraging high-resolution ultra-high-speed digital image correlation (DIC), we unveil the previously inaccessible spatiotemporal dynamics of confined gas oscillations within these nanotransducers under ultrasound stimulation, revealing localized amplification of the surrounding acoustic field and establishing a quantitative structure-function relationship for programmable acoustic transduction. These aqueous-phase gas nanotransducers exhibit sustained acoustic amplification over millions of excitation cycles and remain functional after prolonged storage (>2 years) under physiological conditions. In vitro and in vivo, this platform enables long-term ultrasound imaging and sustained, non-invasive neuromodulation by converting confined gas oscillations into persistent and amplified mechanical actuation. Our findings establish a generalizable design framework for stabilizing gas in liquid environments to achieve persistent and programmable acoustic transduction, thereby enabling sustained ultrasound-biological interfacing and opening opportunities for gas-based therapeutics.

bioengineering↗

bioRxiv2026

Perceived social value is more strongly linked to gossip decisions with age in adolescence

Gossip is central to social exchange, yet how adolescents select what to share and with whom remains unclear. Across two independent samples aged 10-18 years (behavioural, n = 98; fMRI, n = 101 scanned), adolescents read information about absent third parties, chose whether and with whom to share it, and reported their appraisals. Sharing frequency showed no detectable age association. Valuation-to-decision coupling strengthened with age for interest in both samples, with a smaller age interaction for usefulness. Adolescents selected close friends more often with age when sharing. During scenario reading, before participants reported their choices, BOLD responses in a left inferior frontal cluster tracked subsequent interest ratings more strongly with age (n = 92), also within regions engaged by a separate mental-state judgment task. Together, these findings link age in adolescence to stronger valuation-to-decision coupling for interest and a greater proportion of sharing directed to close friends.

neuroscience↗

bioRxiv2026

High-plex protein imaging across thick tissue by synchronized amplification

High-plex protein imaging is essential for decoding complex tissue organization, yet it remains largely confined to thin sections. Current approaches in millimeter-thick samples suffer from poor signal penetration and depth-dependent, uneven signal amplification. Even with specialized instrumentation to facilitate probe diffusion, iterative millimeter-thick tissue workflows can take more than four days per staining round, and reported eleven-marker experiments extend beyond a month. We introduce Amplification by Cyclic Extension (ACE), a DNA-barcoded, synchronized in situ amplification strategy that uses thermally controlled cyclic extension to coordinate DNA concatemer growth across tissue depths. By synchronously activating and coordinating reaction progression throughout the sample, ACE enables controlled, uniform signal amplification across tissue depths. Using ACE, we demonstrate 63-plex protein and RNA imaging in thin sections, 22-plex protein imaging in 200 m mouse brain sections, and 16-plex protein imaging in 1 mm-thick brain tissue encompassing over three million cells. For millimeter-thick tissues, ACE reduces per-round target-switching time from multiple days to less than eight hours, shifting volumetric high-plex protein imaging from months to days. Together, these results establish ACE as a synchronized amplification strategy that enables scalable high-plex protein imaging in thick tissues.

bioengineering↗

bioRxiv2026

Chloroplast expression of Chlamydomonas glycolate dehydrogenase en route to an improved photorespiratory bypass

Successes with photorespiratory bypass pathway engineering have relied on nuclear transformation, requiring subcellular targeting and protein localization in the target organelles for photorespiration. In the current study, mitochondrial Chlamydomonas glycolate dehydrogenase (CrGDH) was directly expressed in chloroplasts of Chlamydomonas and tobacco, as the first enzymatic step for a photorespiratory bypass. Proof-of-concept experiments in Chlamydomonas were followed by transgenic tobacco lines that confirmed the chloroplast accumulation of active CrGDH protein. Photosynthetic rates and biomass were comparable or less than those of wild type plants under the tested conditions, indicating that chloroplast expression of CrGDH alone is insufficient to improve plant performance. These results suggest that additional downstream enzymes within a complete photorespiratory bypass are required to metabolize glyoxylate derived from CrGDH activity and thereby benefit growth. One of the chloroplast transformed lines (APP2882) accumulated CrGDH while maintaining wild type levels of photosynthesis and biomass, providing a best candidate chassis for engineering full photorespiratory bypass pathways.

plant biology↗

bioRxiv2026

Aberrant 3'UTR splicing drives FUS-dependent mRNA condensates and prevents β-catenin from adherens junctions to promote cancer aggressiveness

The protein-coding sequence has long been considered the primary determinant of protein function. Alternative splicing within 3'UTRs (AS-3'UTRs) generates multiple transcript isoforms from a single gene, yet their roles in protein function and disease relevance remain largely unexplored. Through systematic transcriptome-wide identification of cancer-associated AS-3'UTRs, we uncover that AS-3'UTRs of {beta}-catenin mRNA direct distinct subcellular localization of {beta}-catenin mRNA isoforms. Specifically, an aberrantly spliced 3'UTR isoform promotes cytoplasmic mRNA condensate formation through FUS binding to a cancer-associated alternative exon (Exon 16A). Because {beta}-catenin function is exquisitely dependent on its subcellular distribution between adherens junctions and the nucleus, this aberrant 3'UTR isoform reprograms {beta}-catenin localization. By sequestering {beta}-catenin in the cytoplasm, the aberrant 3'UTR isoform prevents its incorporation into E-cadherin-based adherens junctions, thereby inducing epithelial-mesenchymal transition (EMT)-associated transcriptional programs. Notably, the expression signature of the aberrant 3'UTR isoform robustly correlates with poor clinical outcomes in colorectal cancer patients. Together, our findings reveal that AS-3'UTRs operate as a previously unrecognized post-transcriptional regulatory mechanism through which the untranslated region of mRNA, without altering a single amino acid, reprograms protein subcellular fate to drive oncogenic phenotypes.

cell biology↗

bioRxiv2026

TOX enforces the immunosuppressive program of tumor-infiltrating regulatory T cells

Regulatory T (Treg) cells accumulate in the tumor microenvironment (TME) to suppress anti-tumor immunity, but the transcriptional regulators stabilizing their immunosuppressive state remain poorly defined. Here we show that transcriptional factor TOX is selectively upregulated in tumor-infiltrating (TI) Treg cells across human cancers and mouse tumor models, while remaining low in peripheral and naive Treg populations. Treg-specific deletion of TOX reduced tumor burden, impaired TI Treg-mediated immune suppression, and enhanced effector functions of CD8 and CD4 T cells. In mosaic mice, TOX-deficient Tregs were selectively depleted from tumors, accompanied by increased apoptosis. Single-cell RNA sequencing and TCR clonotype analysis linked TOX expression to an effector-like TI Treg state with clonal expansion, whereas TOX loss shifted cells toward a TCF7-associated progenitor-like phenotype. ATAC-seq revealed enrichment of AP-1 motifs in TOX-sufficient TI Tregs. In contrast, TCF7, LEF1, and FOXO1 motifs in TOX-deficient counterparts, uncovering the opposing transcriptional networks downstream of TOX. Furthermore, TOX deficiency augmented CD8 T cell responses to PD-1 blockade. Together, these findings establish TOX as a key regulator of TI Treg fitness and stability, and identify it as a potential therapeutic target to enhance the efficacy of PD-1-based immunotherapy.

immunology↗

bioRxiv2026

Pillbox: A Leakage-Aware Foundation-Model Predictor and Lineage-Ceiling Diagnostic for Cancer Drug Response

We present Pillbox, a predictor whose pipeline is audited against the six Asiaee leakage modes with the one residual pathway shown by per-fold ablation to be non-load-bearing on hard splits. Our model combines CpGPT methylation embeddings, CLAMP drug embeddings, and per-fold-fit gene-expression principal components which are fused by Feature-wise Linear Modulation (FiLM)-conditioned graph attention on the STRING v12 protein-protein interaction graph. Then we -ensemble the model against a histogram-based gradient boosting regressor baseline. On GDSC GSE68379 (987 cell lines, 375 drugs) across seeds 42, 7, and 123, the ensemble reaches test R2 of 0.78, 0.77, and 0.76 on random, histology-blind, and site-blind splits respectively, with cell-aware lifts above the drug-mean floor of +0.054, +0.060, and +0.037. As a quantitative diagnostic for feature-stack saturation we propose the cross-architecture residual correlation, calibrated against a same-architecture-different-initialization control. On histology-blind splits the cross-architecture value of 0.939 falls short of the same-architecture ceiling of 0.974 by approximately 0.03 in residual correlation, a gap we interpret as the headroom available to architecture choice on top of the current foundation-model representation and consistent with the long-established observation that tissue lineage dominates cell-line drug response. We integrated curated mutation, methylation, and drug-target-expression channels, but these do not improve prediction once foundation-model embeddings are in place. Cross-screen validation against PRISM matches the GDSC-to-PRISM measurement reproducibility ceiling within 0.01 Spearman.

bioinformatics↗

bioRxiv2026

Oxidized protein states define metastatic fitness in lung cancer

AbstractReactive oxygen species (ROS) are a pervasive feature of human cancers, yet the protein targets through which ROS-regulated cell states shape tumor biology remains poorly understood. Here, using cysteine chemical proteomics, we define signatures of protein states under distinct cellular ROS environments that capture protein oxidation and conformational changes. Quantifying these signatures in primary lung tumors and brain metastases revealed a surprising enrichment of oxidative states in metastasis. To determine how these states support fitness, we performed genome-wide CRISPR screens and identified the mitochondrial Complex I subunit NDUFA10 as a key oxidation-dependent vulnerability. Oxidation of NDUFA10*Cys253 supports Complex I function through a previously unrecognized nucleotide kinase activity that maintains mitochondrial DNA levels. Enforcing a reduced conformation in NDUFA10 disrupts brain metastatic colonization in vivo. These findings establish ROS regulated protein states as a functional layer of tumor fitness, providing a framework for identifying redox-dependent mechanisms that support cancer progression.

Cancer Biology↗

bioRxiv2026

Modeling environmental surveillance of Dracunculus medinensis in aquatic habitats using a three-dimensional agent-based model

Guinea worm disease eradication efforts may benefit from environmental surveillance methods capable of detecting infected copepod intermediate hosts in aquatic habitats. We developed a three-dimensional, spatially explicit agent-based model to examine how ecological processes influence detection probability for a hypothetical water sampling method. The results show that surveillance sensitivity is shaped by the combined effects of larval diffusion, copepod density, and pond size, with interactions among these factors producing nonlinear relationships. Detection, in our model, was concentrated within a relatively restricted period after larvae matured to the infective stage and before dispersal and mortality reduced presence, indicating a limited spatiotemporal window for effective sampling. Surveillance performance peaked under intermediate dispersal regimes that generated sufficient spatial overlap between larvae and intermediate hosts, while both limited dispersal and excessive diffusion reduced detection by constraining encounters or diluting larval concentrations. Increasing habitat size reduced detection by diluting larval concentrations, but the magnitude of this effect depended on copepod density and dispersal dynamics, producing nonlinear and threshold responses rather than simple scaling with pond volume. Spatial and temporal patterns of detection shifted as larvae dispersed, with the most favorable detection periods occurring when both larval abundance and intermediate host encounters were elevated. These findings indicate that surveillance can be guided by local ecological conditions. When the timing of larval introduction is uncertain, effective surveillance requires repeated sampling over time to capture transient windows of detectability and the sampling will be less effective in very stagnant and highly mixed waterbodies. Overall, this study demonstrates how mechanistic modeling can support the design and interpretation of environmental surveillance strategies for Guinea worm eradication programs. Author summaryGuinea worm disease is close to eradication but confirming that transmission has fully stopped remains difficult because detecting infectious larvae in water is challenging. Transmission depends on freshwater copepods that become infected after ingesting Guinea worm larvae. These copepods are short-lived and unevenly distributed within ponds, and infected individuals may die before larvae reach the infective stage. As a result, environmental detection is inherently uncertain. We developed a three-dimensional agent-based model to simulate larval dispersal, copepod infection, and water sampling in a pond environment. The model shows that detection is constrained to a brief period when mature larvae and copepods overlap in space and time, and that this window depends strongly on local ecological conditions such as larval dispersal, copepod density, and pond size. Because infected copepods can be present outside these narrow detection windows, negative water samples do not necessarily indicate absence of transmission, highlighting the need for repeated, spatially targeted surveillance during the final stages of eradication.

ecology↗

bioRxiv2026

Integrative Clinical-Molecular Modeling Identifies LRRN4CL as a Determinant of Structural and Functional Myocardial Improvement

BackgroundMechanical ventricular unloading and systemic circulatory support with left ventricular assist devices (LVADs) enable myocardial recovery in a subset of advanced heart failure (HF) patients, but predictors and mechanisms of recovery are not well understood. Integrating clinical and molecular data may improve identification of patients most likely to recover and uncover biologically relevant targets in HF. MethodsWe collected and analyzed left ventricular apical myocardial tissue and clinical data from 208 patients undergoing LVAD implantation across five centers. Pre-implant transcriptomic profiles (22,373 mRNA transcripts) were integrated with 59 clinical variables using supervised machine learning with repeated cross-validation to identify and prioritize features associated with myocardial recovery, defined as a binary outcome based on improvement in left ventricular ejection fraction (LVEF [≥]40%) and left ventricular end-diastolic diameter (LVEDD [≤]5.9 cm). We also modeled functional (LVEF) and structural (LVEDD) improvement as a continuous outcome without any predefined LVEF and LVEDD pathological thresholds. Feature prioritization was followed by validation in human myocardial tissue and mechanistic interrogation in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). ResultsIntegrative models achieved modest discrimination for myocardial recovery as a binary categorical outcome (maximum mean cross-validated area under the curve 0.73{+/-}0.15), identifying clinical features such as HF duration, LVEDD, HF pharmacologic therapy, and device configuration. Leucine-rich repeat neuronal 4C-like (LRRN4CL), measured in human myocardium, consistently emerged as a top transcriptomic predictor across both binary and continuous metric models (functional and structural). Higher pre-LVAD LRRN4CL expression was associated with reduced likelihood of myocardial recovery and localized primarily to cardiomyocytes. In iPSC-CMs, LRRN4CL overexpression localized to the sarcoplasmic reticulum, induced transcriptional remodeling characterized by suppression of contractile pathways and activation of stress programs, impaired calcium handling, impaired contraction-relaxation kinetics, and diminished mitochondrial respiratory reserve capacity. ConclusionsIntegration of clinical and myocardial transcriptomic data identifies LRRN4CL as a novel marker associated with impaired myocardial recovery following LVAD-mediated ventricular unloading and systemic circulatory support. These findings move beyond predictive modeling, linking integrative computational discovery to cardiomyocyte dysfunction and providing a translational framework for biologically informed risk stratification and therapeutic targeting for myocardial recovery. CLINICAL PERSPECTIVEO_ST_ABSWhat Is New?C_ST_ABSO_LIIntegrative clinical and myocardial transcriptomic modeling identifies LRRN4CL as a novel molecular determinant of structural and functional changes after LVAD-mediated ventricular unloading and enhanced systemic circulatory support. C_LIO_LIElevated LRRN4CL expression is associated with adverse remodeling signatures, impaired calcium handling, and stress responses in human iPSC-derived cardiomyocytes. C_LIO_LIExperimental overexpression of LRRN4CL directly disrupts calcium cycling, contractile performance, and mitochondrial respiration linking molecular signature to functional phenotype. C_LI What Are the Clinical Implications?O_LIIdentification of LRRN4CL as a marker associated with impaired myocardial recovery supports future efforts toward biologically informed risk stratification for patients undergoing LVAD therapy. C_LIO_LILRRN4CL as a marker of cardiac improvement potential may extend beyond advanced HF to earlier stage disease patients and inform prognosis, risk stratification, and response to medical therapies. C_LIO_LIThese findings highlight LRRN4CL-associated pathways as potential therapeutic targets and demonstrate how integrative clinical-transcriptomic approaches can move beyond clinical prediction toward identification of new biologically precise therapeutic targets in HF following a bedside to bench and back approach. C_LI

bioinformatics↗

bioRxiv2026

A functional triangle relationship of topoisomerase IIβ, BARD1, and ERK2 in immediate early gene transcription

Immediate early genes (IEGs) encode master transcription factors, including EGR1, FOS, JUN, and MYC genes that drive robust transcription in the G1 phase of cell cycle. Our previous studies indicate that topoisomerase II{beta} (TOP2B) critically regulates IEG transcription and that the activities of TOP2B are dynamically controlled through post-translational modifications by BRCA1-BARD1 and ERKs. Here, we show that two E2 enzymes, UBCH5b and UBC13/MMS2, differentiate the effects and functions of TOP2B ubiquitination by BRCA1-BARD1. Comprehensive transcriptomics, proteomics, and biochemical and molecular cellular analyses revealed a close relationship between BARD1 and key mitogen-activated protein kinase pathway genes and identified activated ERK2 as a novel kinase that phosphorylates BARD1 at S391, a previously reported mitotic phosphorylation site, whose genetic mutation has been linked to tumorigenesis. Mechanistically, the catalytic activity of ERK2 stimulates TOP2B ubiquitination mediated by BRCA1-BARD1 in complex with UBCH5b and UBC13/MMS2, which controls the binding and function of TOP2B and BARD1 for transcriptional activation at representative IEGs. Taken together, our data propose that there is a functional regulatory circuit involving TOP2B, BARD1, and ERK2, three key transcriptional activators for IEG transcription, in which the gene association and catalytic activity of TOP2B are regulated through E2-differentiated ubiquitination by BRCA1-BARD1 and the phosphorylation of BARD1 by ERK2 for productive transcription.

molecular biology↗

bioRxiv2026

A Deep-Learning Atlas of XPO1-Mediated Nuclear Export at Proteome Scale

Exportin 1 (XPO1/CRM1) is the principal nuclear export receptor for cargos bearing hydrophobic nuclear export sequences (NESs). Dysregulation of XPO1-dependent export is implicated in cancer, neurodegeneration, and other diseases, yet a comprehensive view of XPO1 function remains limited by the poor reliability of sequence-based NES prediction. Existing predictors are largely derived from a small set of XPO1-cargo structures and are therefore biased toward canonical docking geometries, limiting their ability to detect NESs that engage XPO1 through noncanonical pocket-occupancy patterns. We hypothesized that deep learning-based structural modeling could overcome this limitation by directly sampling binding geometries. Using AlphaFold 3, we modeled full-length cargo-XPO1-RanGTP complexes for more than 4,000 human proteins and identified over 3,000 previously uncharacterized, high-confidence NESs. Integration of AlphaFold predictions with unsupervised structural geometry analysis and experimental validation identified both canonical NESs and noncanonical sequence patterns exhibiting atypical anchor-residue usage, expanding the structural language of XPO1-recognized NESs. Groove-resolved contact maps further revealed helix rotation within the export groove as a regulatory feature that can rewire pocket usage without altering the core NES sequence, enabling PTM- and cofactor-sensitive tuning of export strength. This exportome atlas resolves many previously ambiguous or unidentified NESs in disease-associated proteins and across major cellular systems, including centrosome organization, mRNA processing, ubiquitin signaling, kinase networks, ribosome quality control, and macroautophagy. We further identified recurrent NES-NLS tandem motifs encoded in primary sequence, suggesting coordinated regulation of nucleocytoplasmic transport. Together, our deep learning-based exportome atlas, integrated with NLS maps and accessible through a web-searchable resource, defines an expanded and regulatable code of nuclear transport at proteome scale and offers a framework for dissecting nuclear trafficking and its dysregulation in human disease.

cell biology↗

bioRxiv2025

Automated, modular assembly of reconstituted cell-free systems from in vitro-produced components

High-performance cell-free protein synthesis has transformative potential for synthetic biology, yet the prohibitive costs of PURE kits and the labor intensity of in-house preparation have restricted accessibility and scalability. We developed i-POPFLEX (Purified components OPtimized for FLEXible protein expression), a modular cell-free protein synthesis system in which 34 translation factors, individually synthesized in vitro, are assembled using automated liquid handling. This workflow minimizes manual input and supports parallelized production, generating complete, ready-to-use systems within two days. i-POPFLEX achieves up to 5-fold higher protein yields and a 95 % cost reduction (20-fold lower cost) compared with commercial kits. Its flexible architecture also enables selective component inclusion for genetic code reprogramming and site-specific incorporation of non-canonical amino acids. By coupling modular design with automation, i-POPFLEX provides an accessible, customizable, and economically viable platform for next-generation biomanufacturing workflows. Technology readinessi-POPFLEX is a reconstituted cell-free system (CFS) composed of 34 translational components that are individually synthesized in vitro and assembled by automation. This system achieves up to 5-fold higher protein yields with a 95 % cost reduction (20-fold lower; <USD 0.06 {micro}L-1) compared with commercial PURE kits (USD 1.36 {micro}L-1) and reduces preparation time from four days to two. The workflow has been validated across diverse protein and peptide synthesis applications, including genetic code reprogramming and site-specific incorporation of non-canonical amino acids, and integrates seamlessly with benchtop automated liquid-handling platforms. These capabilities place i-POPFLEX at Technology Readiness Level (TRL) 4-5: integrated components validated in a laboratory setting and advancing toward pilot-scale readiness. For full-scale deployment, several key challenges remain. Matching crude lysate costs (USD 0.03 {micro}L-1) will require bulk reagent production, optimized procurement strategies, and specialized equipment for high-throughput component synthesis. Enabling milliliter- and liter-scale production will demand improvements in upstream synthesis, downstream purification, and quality control to ensure consistent performance at industrial throughput. Overcoming these barriers would enable production of thousands to millions of fully assembled i-POPFLEX systems for biofoundry-scale enzyme engineering, metabolic pathway prototyping, and large-scale variant screening, democratizing reconstituted CFS technology, and accelerating adoption in next-generation biomanufacturing pipelines.

synthetic biology↗

bioRxiv2025

Extracellular matrix and cytoskeletal reverse remodeling pathways are key drivers of myocardial recovery following left ventricular assist device therapy

Transcriptomic changes in heart failure (HF) patients prior to and following left ventricular assist device (LVAD) support have been extensively studied. Recent studies focused on understanding DNA methylation changes in patients with cardiovascular diseases (CVD) and the role of circulating markers of DNA methylation as clinical predictors of the risk of CVD related morbidity and mortality. In this study, we used paired (pre- and post-LVAD) myocardial samples to examine changes in DNA methylation alongside RNA and protein expression. Our data suggests that patients with no improvement in cardiac function after LVAD therapy, despite showing an improvement in energy production (increased {beta}-oxidation of fatty acid) exhibited persistent activation of profibrotic signaling, increased collagen deposition and cytoskeletal disarray evident from abnormal increase in sarcomeric distance following LVAD support. Contrarily, patients with improvement in cardiac function after LVAD therapy showed activation of pro-inflammatory signaling, collagen degradation and myogenesis. Both RNA sequencing and western blot data showed increased COL1A1 and decreased TPPP3 in post-NR thereby suggesting increased fibrosis and disrupted cytoskeletal signaling as potential barriers to myocardial recovery. Additionally, responders to LVAD therapy showed a significant reversal in myocardial interstitial fibrosis with a preserved sarcomeric architecture. Mice model of HF and recovery also confirmed our human findings, with reduced fibrotic signaling and improved cytoskeletal remodeling signaling observed in mice that showed improvement in cardiac function compared to mice with HF. Overall, our data suggests that altering extracellular matrix regulation and cytoskeletal signaling pathways may contribute to myocardial recovery. Further studies targeting these pathways are required to identify new HF therapeutic targets.

genomics↗

bioRxiv2025

Wearable Focused Ultrasound Neuromodulation and Electrophysiological Recording Patch for REM Sleep Enhancement

The rise in sleep disease affecting the general population globally in the past decade has been detrimental to individually and socioeconomically. As of now, approaches often are temporary through medication, permanently using invasive implants with surgical complications or neuromodulation therapy. However, non-invasive, state-dependent neuromodulation during sleep is technically challenging, especially with the lack of flexibility, comfortability and robustness for sleep conditions. Here, we introduce a Non-invasive Electrophysiological Recording and Ultrasound Neuromodulation Sleep Patch (NEUSLeeP) in delivering focused ultrasound stimulation to the subthalamic nucleus (STN) overnight with simultaneous stable polysomnography recording. Our sleep patch integrates a custom eight-channel concentric ring transducer array with real-time electroencephalography (EEG), electrooculography (EOG), electromyography (EMG) recording, and individualized line-of-sight targeting to sonicate deep brain areas while preserving mobility. Our platform operated safely and comfortably across the two-nights sleep study. Stimulation of the left STN was delivered every 90 minutes throughout the night and was associated with a 25% increase in REM (Rapid Eye Movement) sleep duration and a 43 minutes reduction in REM sleep latency compared to a sham night in a study of 26 subjects. Blood Oxygen Level Dependent (BOLD) signal attenuation in functional Magnetic Resonance Imaging (fMRI) was localized primarily to a left ipsilateral basal-ganglia-midbrain-temporal circuit, consistent with selective network modulation rather than global arousal changes. Overall, NEUSLeeP demonstrates feasibility by (i) a light weight and wearable ultrasound neuromodulation and sleep recording during natural sleep; (ii) establishing a potential mechanism relating targeted ultrasound stimulation of STN/sleep networks to REM enhancement.

bioengineering↗

bioRxiv2025

LigifyDB: An interactive platform for predicted small molecule biosensors

Prokaryotic transcription factors (TFs) are used as small molecule biosensors with broad applications in biotechnology, yet only a small fraction from microbial genomes have been characterized. To address this gap, we recently described the bioinformatic method Ligify, which leverages information from genome context and enzyme reaction databases to predict a TFs cognate effector molecule. Here we report Ligify 2.0, a modern web server for Ligify predictions. We systematically evaluate 10,965 small molecules within the Rhea enzyme reaction database for associations to TFs, ultimately generating 13,435 hypothetical interactions between 1,362 small molecules and 3,164 TFs. We then develop an interactive web server (https://ligify.groov.bio) to search and visualize prediction data. Each TF sensor page includes visualizations for chemical ligand structures, interactive TF protein structures, and genome context. Pages also include metadata links, predicted promoter sequences, prediction confidence metrics, and references to relevant literature. A plasmid builder tool enables users to generate custom biosensor circuit designs. Finally, we provide case studies using Ligify 2.0 to identify two TFs from the pathogens Escherichia coli O157:H7 and Mycobacterium abscessus responsive to 4-hydroxybenzoate and Pseudomonas Quinolone Signal, respectively. The Ligify web server aims to facilitate the systematic characterization of biosensors for chemical-control of biological systems. Key pointsO_LILigify 2.0 contains >13,000 predicted transcription factor-small molecule interactions C_LIO_LIA rich web interface provides interactive visualizations and a plasmid design tool C_LIO_LIPredicted ligands for regulators from pathogenic bacteria are experimentally validated C_LI Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=70 SRC="FIGDIR/small/683484v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1afa575org.highwire.dtl.DTLVardef@97c811org.highwire.dtl.DTLVardef@cfdb93org.highwire.dtl.DTLVardef@58977d_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Retrospective attention reveals a decaying theta rhythm in conscious access to a preceeding stimulus

Conscious perception is often presumed to arise immediately upon external stimulation. However, the phenomenon of retroperception-conscious access to a stimulus after it has disappeared-challenges this view by demonstrating that awareness can emerge retrospectively. The fine-grained temporal dynamics governing this process, however, remain unknown. Here, we tested three competing models for the temporal architecture of retroperception: a monotonic decay, a sustained oscillation, and a damped oscillation. We implemented an established retro-cue paradigm and densely sampled behavioral reports. Through spectral analysis and computational modeling, we revealed that both behavioral accuracy and subjective visibility exhibited damped oscillations in the theta-band, superimposed on a time-dependent decay. Furthermore, we demonstrated that these oscillations in accuracy and visibility were temporally aligned, advocating a functional interplay between attention and perception in the post-stimulus period. These results reveal a rhythmically structured and temporally constrained window for conscious reactivation, redefining the limits of when and how the mind can become aware of the past.

neuroscience↗

bioRxiv2025

Postprocessing-Enhanced Machine Learning for Reliable Real-Time Sleep Staging in Closed-Loop Neuromodulation

Real-time sleep stage classification is important for closed-loop neuromodulation at certain stages during sleep, yet current models often yield noisy and unstable outputs that risk false triggers. These fluctuations, especially near stage boundaries, can compromise the safety and reliability of stimulation. Existing methods frequently rely on model-specific architectures or require extensive tuning to maximize precision, which limits their generalizability and hinders deployment in real-time systems. To address this, we propose a lightweight, classifier-independent post-processing pipeline that stabilizes predictions without modifying the underlying classifier. Our method first applies temporal smoothing to predicted sleep-stage probabilities, followed by conservative control logic to enhance stimulation precision. We evaluate four smoothing techniques: Moving Average (MA), Exponential Smoothing (ES), Kalman Filtering (KF), and a novel Weighted Exponential Smoothing (WES), on a 29-subject open-source sleep dataset. To capture the trade-offs between stability and responsiveness, we introduce new real-time evaluation metrics. We identify an optimal smoothing intensity range and assess three control strategies: probability thresholding, naive waiting, and entropy constraint, as well as a hybrid method combining high confidence and low uncertainty. Smoothing improves generalization and robustness: under both low and high synthetic noise ({sigma} > 0.2), smoothed outputs retain 10-15% higher precision and recall across all stages. Control logic further enhances reliability: our hybrid method achieves 80% (Wake), 96% (N2), 98% (N3), and 86% (REM) precision. Finally, we introduce a stage-transition constraint matrix to suppress biologically implausible transitions (e.g., REM[->] N3), to further stabilize outputs during evidence accumulation, with potential applications in objective sleep quality assessment. To our knowledge, this is the first study to systematically characterize real-time trade-offs between smoothing, latency, and control logic in sleep staging. Overall, our generalizable framework is expected to improve safety, interpretability, and deployment feasibility of real-time sleep classification for both clinical and wearable closed-loop neuromodulation systems.

bioengineering↗