Biology subjects

Kim, Y.

Publications and source records attributed to Kim, Y..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

Mirror manifolds: partially overlapping neural subspaces for speaking and listening

We utilize internal representations of meaning for two purposes: to understand the words we hear and to generate our own speech. This dual requirement necessitates abstract, modality-agnostic representations. Building on work identifying it as a hub for relational mapping, we hypothesized that the hippocampus supports abstract, cross-person representations, and uses shared semantic geometries to do so. We tested this hypothesis by examining hippocampal activity in a remarkable single-neuron dataset derived from conversational speech. Neurons robustly encoded meanings of both spoken and heard words, and used common geometric embeddings for both, leading to abstract meaning performance. Speaker identity was aligned with meaning via partial subspace alignment, which affords speaker-meaning binding by partitioning meaning by speaker while maintaining cross-speaker generalization. Degrees of subspace rotation varied on a single word level and depended systematically on semantic category. Together, these findings indicate how geometric principles allow for abstract cross-personal meanings while preserving binding to speaker identity.

neuroscience↗

bioRxiv2025

Advancing Wildlife Image Analysis: A Graph Attention Contrastive Learning Approach for Region-Specific Mammal Classification

1. Camera traps have become a cornerstone of wildlife ecological research, yet the manual analysis of the millions of images they generate requires substantial time and resources. Deep learning-based automation has emerged as a promising solution, existing global general-purpose models exhibit limitations in precisely recognizing local endemic species and adapting to unique local ecosystems. 2. This study developed a high-performance classification model optimized for native species. A large-scale "Korean Wildlife Dataset" was constructed from data collected across diverse domestic habitats, and a novel architecture was proposed to overcome limitations of conventional CNNs. The proposed Graph Attention Contrastive Learning (GACL) model is structured as a two-stage pipeline. Stage one employs YOLOv5 and MegaDetector to detect animals, humans, and vehicles, filtering valid images. Stage two performs fine-grained species classification. GACL captures structural relationships among object parts using a Graph Attention Transformer (GAT) and aligns semantic correspondence between images and textual descriptions via Parallel Contrastive Learning, enabling deeper understanding beyond simple visual features. 3. Evaluation on an independent test set demonstrated that the proposed model robust classification performance with an overall accuracy of 96.83% across four classes (Wildboar, Goral, Deers, and Other). Notably, in a comparative analysis against a global general-purpose model, our model showed distinct advantages in the precise recognition of endemic species. Furthermore, it exhibited a lower false positive rate in identifying animals in empty images, confirming its potential to enhance the efficiency of the data cleaning process. 4. Beyond technical accuracy, this study highlights that region-specific AI models that reflect local ecological characteristics can provide substantial practical value for wildlife monitoring and biodiversity conservation. Future work will require continuous efforts in data diversification and model lightweighting to further improve model robustness and practicality.

ecology↗

bioRxiv2025

A predictive framework for stop-loss variants with C-terminal extensions

Stop codons dictate translation termination, and variants occurring at these sites can result in stop-loss variants, leading to C-terminal extensions with potentially significant functional consequences. Despite their clinical relevance, existing prediction tools--primarily developed for missense variants--lack sufficient accuracy for assessing stop-loss variants, mainly due to their insufficiency in accounting for the sequence features of the extended peptide. To address this gap, we developed TAILVAR (Terminal codon Analysis and Improved prediction of Lengthened VARiants), a machine-learning classifier that integrates multi-omics features spanning transcript- and protein-level properties, along with variant effect annotations. Our analyses showed that transcripts lacking downstream stop codons in the 3 untranslated region exhibit lower evolutionary constraints. Additionally, we observed that deleterious variants exhibit greater C-terminal hydrophobicity, which is associated with reduced protein stability and increased degradation, as well as a higher aggregation propensity. TAILVAR outperformed existing benchmarks, demonstrating the highest correlation with functional experiments and establishing thresholds to classify variants as benign or pathogenic. This work offers a systematic framework for interpreting stop-loss variants, providing precise predictions of elongated protein effects that may aid genetic diagnosis and facilitate the discovery of novel disease-associated genes. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/673407v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@1d53baaorg.highwire.dtl.DTLVardef@403289org.highwire.dtl.DTLVardef@b5c8b4org.highwire.dtl.DTLVardef@8bd61a_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2025

Orthogonal and Robust Analytics Enable Reproducible and Scalable Manufacturing of High Purity Extracellular Vesicles Derived from Mesenchymal Stromal Cells

The development of extracellular vesicle (EV) based therapeutics requires robust analytical assays and scalable downstream processing (DSP) strategies to ensure product quality and reproducibility. In this study, we established an analytical toolbox comprising scattering and fluorescence mode nanoparticle tracking analysis (NTA), fluorescence-based flow cytometry (Fl-FC), and multi-detector analytical size exclusion chromatography. Liposomes, selected for their physicochemical similarity to EVs, were used as reference materials to optimize assay parameters, fluorescence labeling conditions, and dynamic range, minimizing artifacts such as photobleaching and masking effects. Using these optimized analytical tools, we designed a scalable DSP workflow for human bone marrow mesenchymal stromal cell (hBM-MSC) derived EVs, incorporating clarification, tangential flow filtration (TFF), ion exchange chromatography (IEX), buffer exchange, and sterile filtration. IEX chromatography resulted in the elution of two cell-secreted populations, with similar scattering signals while eluate 1 showed approximately 30 times higher absorbance signal compared to eluate 2. Transmission electron microscopy revealed that eluate 1 contained non-vesicular extracellular particles (NVEPs), and eluate 2 was enriched in EVs and showed higher expression of positive markers such as CD81 and CD73 using Simple Western. Additionally, the two IEX eluates showed different proteomic and lipidomic profiles. Then the analytical toolbox was utilized to monitor the DSP process in terms of particle recovery and impurity removal throughout the process determining the high purity level of the final EV preparation. Together, these results demonstrate that orthogonal analytics coupled to a scalable DSP yield reproducible MSC-EV preparations while depleting commonly co-isolated NVEPs. This practical framework advances process analytics of MSC-EV manufacturing and supports reporting of identity, purity, and function aligned with existing guidelines in the field. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/672476v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@142ff8aorg.highwire.dtl.DTLVardef@196c0bforg.highwire.dtl.DTLVardef@485c36org.highwire.dtl.DTLVardef@9dff39_HPS_FORMAT_FIGEXP M_FIG C_FIG Liposomes were used as reference materials to optimize single particle analytics as well as multi detector analytical chromatography to assess particle recovery and impurity removal. This optimized analytical toolbox enabled accurate monitoring of downstream processing steps, establishing a robust workflow for reproducible and scalable mesenchymal stromal derived extracellular vesicles bioprocessing.

bioengineering↗

bioRxiv2025

Endogenous Real Time Imaging Reveals Dynamic Chromosomal Mobility During Ligand-Mediated Transcriptional Burst Events

Enhancers serve as the major genomic elements regulating mammalian signal-dependent transcriptional programs, characterized by alternating periods of target gene "bursting" and "non-busting" that require investigation of induced enhancer condensates and locus motility in real time to provide dynamic insights into signal/ligand-dependent regulatory events. Here, endogenous live cell imaging has revealed the altered chromosomal dynamics/condensate formation occurring during estrogen receptor (ER)-dependent target gene bursting/post-bursting and chronic activation events. Simultaneous DNA/RNA endogenous live imaging reveals that an increased mobility of acutely ER-stimulated loci observed during the bursting phase is, unexpectedly, further increased in the subsequent non-burst phase. Single molecule tracking (SMT) of ER shows that the relatively high-burst, lower-mobility acute state was indeed enriched for high-viscosity, 1,6-hexanediol-sensative ER molecules in a low sub-diffusive confined state with enhanced condensate formation during burst activation. Consistent with this, blocking transcription with flavopiridol shifts DNA tracks into a non-confined state. Differential DNA kinetics during burst vs non-burst has provided a strategy to assess altered condensate formation during gene activation events. (165)

molecular biology↗

bioRxiv2025

Integrating 12 Spatial and Single Cell Technologies to Characterise Tumour Neighbourhoods and Cellular Interactions in three Skin Cancer Types

Cutaneous squamous cell carcinoma (cSCC), basal cell carcinoma (BCC), and melanoma - the three major skin cancers - collectively comprise over 70% of all cancer cases. Despite their prevalence, much understanding of cellular interactions in the skin cancer microenvironment is needed, both in the outer skin layer where the cancer originates and at the deeper junctional and dermal layers into which it progresses. To address this gap, we integrated 12 complementary spatial and single-cell technologies to generate orthogonally-validated cell signatures, spatial maps, and interactomes for cSCC, BCC, and melanoma. Through comprehensive comparisons and integrating these spatial methods, we provided practical benchmarking guidelines for experimental design and analysis. By identifying keratinocyte cancer cells and melanomas, we found distinct signatures of these cells compared to non-cancer keratinocytes and melanocytes. Spatial integration of transcriptomics, proteomics and glycomics uncovered cancer niches enriched for cancer initiating cells (melanocytes or keratinocytes) and fibroblast and T-cell (MKFT) clusters, with altered tyrosine and pyrimidine metabolism. Ligand-receptor analysis across >700 cell-type combinations and >1.5 million interactions highlighted key roles for CD44, integrins, and collagens, with CD44-FGF2 emerging as a potential therapeutic target. Consistently, melanoma showed strong MFT interactions, validated by Opal Polaris, RNAScope, Proximal Ligation Assay and two additional single-cell spatial platforms (making a total of 14 technologies). For population-scale generalisation, genetic associations from >500,000 individuals were mapped onto spatial skin tissues, identifying SNPs enriched in domains containing melanocytes and T cells and their ligand-receptor pairs, shedding light on functional mechanisms linking genetic heritability to cells within cancer tissue. We built an interactive multiomics resource for exploring spatially-resolved molecular signatures and cellular crosstalk in skin cancer, available at https://skincanceratlas.com.

cancer biology↗

bioRxiv2025

MEG3 Enhances Survival of Developing Human Neurons with CLCN4-Linked Autophagy Impairment

Genetic variations in CLCN4, encoding the H+/Cl- exchanger CLC-4, are associated with human neurodevelopmental disorders with highly variable phenotypes. A lack of physiologically relevant models has hampered molecular understanding of pathogenic mechanisms. We now establish engineered brain organoid and neuronal cell systems to examine impacts of patient-relevant CLCN4 genetic variations. We find that CLCN4 variants reduced excitatory neuron numbers due to early-stage cell death, accompanied by altered endo-lysosomal dynamics and disrupted autophagic flux. Transcriptomic profiling showed significant downregulation of long non-coding RNA MEG3 in CLCN4-variant neurons. Restoring MEG3 expression is sufficient to rescue cellular defects and improve survival of CLCN4-variant neurons. These findings link CLCN4 dysfunction with impaired autophagy and neuronal cell death, highlighting MEG3 as a potential therapeutic target for neurodevelopmental disorders involving autophagic dysfunction.

neuroscience↗

bioRxiv2025

Flow-sensitive HEG1 controls eNOS activity to prevent endothelial dysfunction, hypertension, and atherosclerosis

Hypertension (HTN), the chronic elevation of blood pressure, accounts for more atherosclerotic cardiovascular disease deaths than any other modifiable risk factor.1 In the arteries, stable blood flow (s-flow) drives healthy, atheroprotective endothelial cell (EC) functions including nitric oxide (NO) production, barrier function, and anti-inflammatory programs via the action of flow-sensitive proteins. We showed that s-flow stimulates Heart-of-Glass 1 (HEG1) protein expression, localization to cell-cell junctions, and secretion from ECs.2 We found that conditional, endothelial cell-specific knockout of (Heg1ECKO) exacerbates atherosclerosis2, however the mechanism was unknown. Here, we report a new role of HEG1 in controlling EC dysfunction, hypertension and atherosclerosis. We discover a novel mechanism: HEG1 regulates NO bioavailability via a flow-dependent HEG1-eNOS interaction (endothelial nitric oxide synthase, NOS3). Heg1ECKO develops spontaneous hypertension and severe atherosclerosis, both of which are effectively treated by Angiotensin-Converting Enzyme inhibition (ACEi). UK BioBank and Swedish cohort studies reveal that plasma HEG1 levels are associated with hypertension and cardiovascular disease risk.3,4 Our findings suggest HEG1 may serve as a biomarker to advance personalized therapies for EC dysfunction, hypertension, and atherosclerosis.

physiology↗

bioRxiv2025

Gluconeogenesis in Aqueous Microdroplets: Non-Enzymatic Generation of Glucose

Glucose is a central metabolite of living organisms, serving as the primary energy substrate produced predominantly by photosynthetic organisms. Under conditions of limited external glucose supply, organisms activate gluconeogenesis, an endogenous biosynthetic pathway that sustains essential glucose levels. Yet the mechanism of glucose generation, before the advent of photosynthesis and complex enzymatic systems, remains elusive. Recently, microdroplet chemistry has emerged as a novel approach for catalyst-free organic synthesis. Here, we report the non-enzymatic formation of glucose from a simpler organic precursor, pyruvate, in aqueous microdroplets without the aid of organic or inorganic catalysts. Our results show that glucose is generated via a reaction pathway analogous to canonical gluconeogenesis, proceeding through key intermediates including oxaloacetate, glycerate, and glyceraldehyde. Furthermore, thermodynamic analysis indicates that the free energy change associated with glucose formation is overcome in aqueous microdroplets at room temperature, without the need for external energy input or enzymatic catalysis. These findings indicate that aqueous microdroplets can non-enzymatically convert C3 compound, pyruvate, into the C6 sugar glucose, offering a plausible abiotic route for anabolic carbon transformations during abiogenesis.

evolutionary biology↗

bioRxiv2025

Local optogenetic control of genome editing and tumorigenesis in vivo using wireless implantable optoelectronics

Precise spatial regulation of site-specific DNA recombination (SSR) in vivo remains a challenge due to limited tunability of current platforms. Here, we present an optogenetic approach that overcome these limitations by employing engineered light-regulated recombinase E-LightR-Cre and tunable wireless implantable optoelectronic devices. E-LightR-Cre meets the key criteria for spatial regulation of SSR in vivo, showing no detectable activity in the dark, while demonstrating robust activation upon blue-light illumination. To achieve local E-LightR-Cre activation in murine lungs, we developed wireless, fully-implantable optoelectronic devices enabling focal illumination with no discernible organ damage. By modulating illumination intensity and duration, we can control the size of the activated area. Local expression of oncogenic KRas-G12D in a photoactivated subpopulation of cells in vitro revealed rapid reprogramming of the mutant expressing cells and their non-activated neighbors. Light-guided activation of E-LightR-Cre in mouse lungs resulted in focal expression of a reporter gene and allowed us to induce local formation of oncogenic lesions in vivo.

bioengineering↗

bioRxiv2025

Sequential Activation of Senescence and Apoptosis by ONG41008 Eliminated the Human Pancreatic Ductile Adenocarcinoma in nude mice and xenografted human lung cancer

Current therapeutic limitations associated with pancreatic ductal adenocarcinoma (PDAC) are still evident. We have found that ONG41008, the first human synthetic polyphenol, is able to eradicate PDAC in a nude mouse model. ONG41008 is known to potently attenuate human TGF-{beta} production, inducing both anti-fibrotic capacity and anticancer potential through senescence-coupled apoptosis (SCA). These interesting observations closely paralleled ONG41008s ability to inhibit PDACs, and as expected, ONG41008 alone was able to actually ablate engrafted PDACs in nude mice. Interestingly, the anti-PD 1 developed by MSD did not appear to act on immune activation of exhausted Cd8+ T cells in the tumor microenvironment (TME), but primarily on engrafted PDAC blood vessels. These observations support the latest report from MSD. A549 cells known to be a well appreciated human lung adenocarcinoma cell line were treated with ONG41008. Consistent with the prior observations ONG41008 notably induced SCA. and when A549 cells were xenografted into mice daunting tumor formations were noticed. Upon stimulation with ONG41008 via direct intramural injection of these tumors tumor volumes were rapidly regressed. Taken together, we believe that ONG41008 could be a multifaceted anti-cancer agent not only against PDAC but also against other aggressive cancers such as lung cancer.

cancer biology↗

bioRxiv2025

A 3D Endothelium-on-a-Chip Model Uncovers Cx43-Dependent Glycolytic Shift and Endothelial Barrier Dysfunction in Diabetic Kidney Disease

Endothelial dysfunction is a key pathological feature of diabetic kidney disease (DKD), characterized by increased vascular leakiness and altered metabolic signaling. In this study, we investigated how diabetic conditions affect endothelial barrier integrity and identified the molecular mechanisms contributing to this dysfunction. Using a 3D microfluidic model that recapitulates in vivo vascular architecture and flow, we demonstrated that high glucose (HG) and high fat (HF) conditions significantly impair endothelial barrier function, as demonstrated by increased dextran permeability and loss of VE-cadherin from the cellular membrane site. Metabolomic profiling and functional assays revealed a shift toward glycolysis, marked by elevated lactate levels and upregulation of lactate dehydrogenase A (LDHA), which contributed to barrier disruption. Pharmacological inhibition of LDHA effectively restored barrier function, underscoring the pathogenic role of glycolytic reprogramming. Transcriptomic analyses of mouse and human DKD datasets further identified connexin 43 (Cx43) as a candidate mediator of this dysfunction. Cx43 expression was progressively deregulated in diabetic mouse kidneys and across multiple cell types in human DKD samples. In vitro, Cx43 overexpression in endothelial cells enhanced glycolytic flux, suppressed oxidative metabolism, disrupted VE-cadherin localization, and promoted angiogenic sprouting. Collectively, our findings establish a mechanistic link between Cx43-driven metabolic reprogramming and endothelial barrier dysfunction in DKD, highlighting Cx43 as a potential therapeutic target for preserving vascular integrity in diabetic conditions.

bioengineering↗

bioRxiv2025

Oncolytic HSV-IL27 expression improves CD8 T cell function and therapeutic activity in syngeneic glioma models

BackgroundMalignant gliomas (MG) are the most common primary brain malignancies and are considered universally fatal. Oncolytic HSVs (oHSV) are promising immunotherapeutics capable of selectively lysing cancer cells, eliciting anti-tumor immunity, and providing local delivery of immune-activating transgenes. IL-27 is a pleiotropic cytokine capable of enhancing tumor-reactive cytotoxic T cell (CTL) function while also possessing neuroprotective properties. We hypothesized that IL-27 expression by oHSV would enhance CTL function and improve anti-glioma therapeutic activity. MethodsWe developed an oncolytic herpes simplex virus (oHSV) that expresses IL-27 (C027). The anti-glioma efficacy of C027 was tested in three syngeneic orthotopic glioma models derived from both chemical (CT-2A) and genetic (SB28, KR158) glioma lines. Spectral flow cytometry was used to assess immunophenotypic and functional changes in the tumor infiltrates and systemically. To further investigate the C027-related CTL activity, we employed in vivo cell specific depletion and IL-27 blockade alongside in vitro T cell stimulation assays. Local and systemic antitumor memory was evaluated by both orthotopic and flank tumor rechallenge of C027-treated long-term survivors. ResultsC027 significantly prolonged survival in syngeneic orthotopic glioma models derived from both chemical (CT-2A) and genetic (KR158, SB28) glioma lines. In the CT-2A model, IL-27-expressing oHSV treatment was associated with increased intratumoral multifunctional effector cytotoxic T lymphocytes (CTL) and functional T cell populations systemically. Mechanistically, both CD8 T cells and IL-27 were required for the C027 survival benefit in vivo and IL-27 enhanced CTL function in vitro. C027-treated mice that survived their initial tumors had local and systemic anti-glioma memory rejecting tumors on rechallenge. ConclusionsOur findings demonstrate that IL-27 expression by oHSV significantly improves anti-glioma therapeutic efficacy, enhances CTL effector function, and induces durable immune memory. Thus, IL-27-oHSV may provide a promising therapeutic approach for malignant gliomas. O_LIWhat is already known on this topic - Malignant gliomas are highly aggressive tumors largely resistant to current immunotherapies. Oncolytic herpes simplex viruses (oHSV) are promising immunotherapy agents for malignant gliomas and provide a platform for immunomodulatory gene expression. C_LIO_LIWhat this study adds - In this study, we present a novel IL-27 expressing oHSV (C027) that improves survival in syngeneic glioma-bearing mice through a CD8 T cell and IL-27 dependent mechanism and induces durable immune memory. C_LIO_LIHow this study might affect research, practice or policy - Our study demonstrates that IL-27-expression by oHSV enhances anti-tumor immunity and glioma efficacy suggesting its potential as a novel therapeutic. C_LI

immunology↗

bioRxiv2025

Longitudinal deep phenotyping in a mouse model of West syndrome reveals temporal dynamics of synapse remodeling, gliosis, and proteomic and lipidomic changes during seizure evolution

Neurodevelopmental disorders can have long-lasting effects, causing not only early pediatric symptoms but also a range of neurological issues throughout adulthood. West syndrome is a severe neurodevelopmental disorder marked by infantile spasms, an early symptom that typically subsides with age. However, many patients progress to other seizure forms, known as seizure evolution, which is closely linked to poor long-term outcomes. Despite its clinical significance, the neurobiological mechanisms behind seizure evolution in West syndrome remain poorly understood. Recent genetic studies have consistently identified the CYFIP2 p.Arg87Cys variant in West syndrome patients, and the Cyfip2+/R87C mouse model carrying this mutation has been shown to recapitulate key symptoms of the disorder, including infantile spasms. In this study, we aimed to gain deeper insight into seizure evolution by conducting longitudinal deep phenotyping of the Cyfip2+/R87C mouse model from the neonatal stage to seven months of age. We tracked seizure activity through behavioral and EEG recordings and employed multi-omic analyses, including tissue and single-cell level transcriptomics, ultrastructural analysis, proteomics, and lipidomics, to capture a comprehensive view of molecular and cellular changes. Our results showed that after an initial period of neonatal spasms, Cyfip2+/R87C mice entered a seizure-free phase, followed by spontaneous recurrent seizures in adulthood, ultimately leading to premature death. This progression was associated with synaptic remodeling, sequential activation of different glial cell types, lipid droplet accumulation in astrocytes, and significant proteomic and lipidomic changes in the brain. These findings suggest that seizure evolution in West syndrome involves complex, time-dependent interactions between neurons and glial cells, along with alterations in lipid metabolism. Our study highlights the potential of longitudinal multi-omic approaches to uncover underlying mechanisms of seizure evolution and suggests that targeting these changes could offer novel therapeutic strategies. Additionally, the dataset generated here may provide valuable insights for other epilepsy and neurodevelopmental disorder models.

neuroscience↗

bioRxiv2025

Chromatix: a differentiable, GPU-accelerated wave-optics library

Modern microscopy methods incorporate computational modeling as an integral part of the imaging process, either to solve inverse problems or optimize the optical system design itself. These methods often depend on differentiable optics simulations, yet no standardized framework exists--forcing computational optics researchers to repeatedly and independently implement simulations with limited reusability and performance. These common problems limit the potential impact of computational optics as a field. Here we present Chromatix: an open-source, GPU-accelerated, differentiable wave optics simulation library. Chromatix builds on JAX to democratize fast, parallelized simulation of diverse optical systems and expand the design space in computational optics. Chromatix standardizes a growing collection of optical elements and propagation methods allowing a broad range of applications, which we demonstrate here for snapshot microscopy, holography, and phase retrieval. We demonstrate speed improvements of 2-6x on a single GPU and up to 22x on 8 GPUs.

bioinformatics↗

bioRxiv2025

Stochastic LASSO for extremely high-dimensional genomic data

Accurate identification of significant features in high-dimensional data is indispensable in high-throughput genomic analysis and association studies. Least Absolute Shrinkage and Selection Operator (LASSO) and its derivatives have been widely adapted to discover potential biomarkers as a feature selection scheme in various biological systems. Recently, bootstrap-based LASSO models, such as Random LASSO and Hi-LASSO, have been effective solutions for extremely high-dimensional but low sample size (EHDLSS) genomic data. However, the bootstrap-based LASSO models still have several drawbacks, such as multicollinearity within bootstrap samples, missing predictors in draw, and randomness in predictor sampling. To tackle the limitations, we propose a new bootstrap-based LASSO, named Stochastic LASSO, that effectively reduces multicollinearity in bootstrap samples and mitigates randomness in predictor sampling, resulting in remarkably outperforming benchmarks in feature selection and coefficient estimation. Furthermore, Stochastic LASSO provides a two-stage t-test strategy for selecting statistically significant features. The performance of Stochastic LASSO was assessed by comparing the existing benchmark models in extensive simulation experiments. In the simulation experiments, Stochastic LASSO consistently showed significant improvements in performance compared to the state-of-the-art LASSO models for feature selection, coefficient estimation, and robustness. We also applied Stochastic LASSO for the gene expression data of publicly available TCGA cancer datasets and identified statistically significant genes associated with survival month prediction. The source code is publicly available at: https://github.com/datax-lab/StochasticLASSO.

bioinformatics↗

bioRxiv2025

Exploration of Novel Biomarkers through a Precision Medicine Approach Using Multi-omics and Brain Organoids in Patients with Atypical Depression and Psychotic Symptoms

Major depressive disorder (MDD) with atypical features accompanied by psychotic symptoms represents a severe and under-researched subtype of depression and severe mental illness, characterized by significant personal and social impact. This study aims to explore novel biomarkers through a precision medicine approach by integrating clinical data, white blood cell (WBC) single-cell RNA sequencing (scRNA-seq), plasma proteomics, and brain organoid models to uncover immunological and neurological alterations in patients with this condition. Patients exhibited elevated stress, anxiety, and depression levels, with increased WBC counts. Plasma proteomic profiling identified an upregulation of proteins implicated in synaptic formation, including Doublecortin-Like Kinase 3 (DCLK3) and Calcyon (CALY), as well as immune-related proteins such as Complement Component 5 (C5). WBC scRNA-seq revealed significant neutrophil and monocyte transcriptomic alterations, suggesting increased inflammation and immune dysregulation. Patient-derived brain organoids display reduced growth and distinct gene expression patterns compared to controls, particularly under dexamethasone-induced stress conditions. Integrating multi-omics data and brain organoid models offers a novel framework for understanding the pathophysiology of psychiatric disorder, which is one of the most complex disorders.

neuroscience↗

bioRxiv2025

Mechanical environment afforded by engineered polymer hydrogel critically regulates survival of neural stem cells transplanted in the injured spinal cord via Piezo1-mediated mechanotransduction

Neural stem cell (NSC) transplantation is a promising therapeutic approach for spinal cord repair, but poor graft survival remains a critical challenge. Here, we demonstrate that the mechanical properties of the transplantation microenvironment play a crucial role in NSC survival in the injured spinal cord. While our previously engineered imidazole-poly(organophosphazene) (I-5) hydrogel effectively prevented cavity formation by promoting extracellular matrix remodeling, NSCs transplanted with 10% hydrogel exhibited poor survival. Remarkably, increasing the hydrogel concentration to 16%, which created a 5-fold stiffer matrix, significantly enhanced NSC graft survival and synaptic integration. Using in vitro models with controlled substrate stiffness, we found that NSCs on stiffer substrates displayed enhanced adhesion, complex morphology, and increased viability. Importantly, we identified the mechanosensitive ion channel Piezo1 as the key molecular mediator of these stiffness-dependent behaviors. CRISPR/Cas9-mediated Piezo1 gene editing in NSCs significantly reduced graft survival in vivo when transplanted with 16% hydrogel, confirming that Piezo1-mediated mechanotransduction is essential for NSC survival in the injured spinal cord. Our findings reveal a previously unrecognized mechanism governing graft survival in the injured spinal cord and suggest that optimizing the mechanical properties of biomaterial scaffolds or targeting Piezo1-dependent mechanotransduction could substantially improve outcomes of cell-based therapies for neurological disorders.

neuroscience↗