Biology subjects

Yan, B.

Publications and source records attributed to Yan, B..

At least 19 recordsLinked to original sources

bioRxiv2026

FMR1 Perturbations Disrupt Sensory Corticostriatal Circuits and Mitochondrial Energetics in Fragile X Syndrome

Fragile X syndrome (FXS) features sensory, social, and cognitive dysfunction, but how fragile X messenger ribonucleoprotein 1 (FMR1) deficiency disrupts sensory corticostriatal circuitry and whether distinct FMR1 perturbations converge on shared cellular mechanisms remain incompletely defined. We integrated diffusion magnetic resonance imaging (MRI) in individuals with FXS and Fmr1-knockout (KO) mice with projection-defined calcium recording, bidirectional optogenetic manipulation, primary somatosensory cortex (S1)-targeted expression of three patient-associated FMR1 missense variants, regional transcriptomics, and optical manipulation of mitochondrial energetic state. Individuals with FXS exhibited disrupted sensory corticostriatal structural connectivity, with mouse analyses further localizing abnormalities to S1-striatal pathways. Fmr1 deficiency impaired recruitment of the S1-dorsomedial striatum (DMS) pathway during social interaction, and projection-specific manipulation demonstrated that S1-DMS dysfunction contributes to social and cognitive deficits. Three patient-associated FMR1 variants, I234T, E329G, and R586Q, converged on social behavioral deficits, which were improved by S1-DMS activation. Transcriptomic analyses revealed convergent oxidative phosphorylation (OXPHOS)-related mitochondrial remodeling in S1 and DMS across Fmr1 deficiency and variant models. Systemic treatment with the mitochondria-targeted antioxidant MitoQ attenuated novel-location-recognition, social-interaction, and social-novelty deficits in Fmr1-KO mice. Moreover, mt-EcGAPR-based Mitochondrial OptoEnergetic Activation (Mito-OptoEA) enhanced mitochondrial energetic state in S1 and improved novel-location recognition and sociability in both Fmr1-KO and I234T models. Together, these findings define a sensory corticostriatal circuit-metabolic framework for FXS in which S1-DMS circuit dysfunction and convergent mitochondrial energetic abnormalities contribute to FMR1-related social and cognitive phenotypes.

neuroscience↗

bioRxiv2026

ProxiNet transfers spatially learned cellular proximity to dissociated single-cell transcriptomes

Spatial transcriptomics reveals cellular organization within intact tissues, whereas dissociated single-cell RNA sequencing provides broad transcriptomic coverage but loses information about cellular proximity and neighborhood structure. Here, we developed ProxiNet, a spatially supervised framework that learns transcriptomic signatures of pairwise cellular proximity from spatial reference datasets and transfers these relationships to dissociated single-cell transcriptomes. ProxiNet predicted cellular proximity across brain regions and spatial technologies, including zero-shot cross-technology transfer, and gradient-based attribution identified genes and broader transcriptional programs associated with proximity predictions. In spatial datasets with known coordinates, ProxiNet-derived cellular neighborhoods recovered reproducible tissue organization and anatomical structure, providing independent spatial validation of the inferred proximity relationships. Applying the spatially calibrated model to dissociated scRNA-seq revealed heterogeneous cellular neighborhoods with distinct cell-type compositions and candidate communication programs. In an Alzheimer dataset, ProxiNet further identified age-associated remodeling of inferred neighborhoods, including an AD-associated neighborhood at 8 months characterized by distinct astrocyte and neuronal transcriptional states and candidate intercellular communication programs. Together, these results establish pairwise cellular proximity as an interpretable and transferable representation for extending spatially learned tissue organization to dissociated single-cell transcriptomes.

bioinformatics↗

bioRxiv2026

Multi-model biological and sequence information fusion for gene regulatory network inference from single-cell transcriptomics

Identification of transcription factor target gene interactions and construction of the gene regulatory networks (GRNs) are essential for understanding the molecular mechanisms underlying transcriptional gene regulation. Large scale single cell transcriptomics across different tissues offers unprecedented resolution of cellular diversity and regulatory dynamics by capturing gene expression heterogeneity. However, existing methods often lack effective multimodal integration and fail to fully exploit the hierarchical structure in Gene Ontology (GO) and gene sequence level representations, which limits their ability for predictive performance and biological interpretability. We present scMGFGRN, a multi-model deep learning framework that integrates single-cell transcriptomic profiles with GO hierarchical relationships, gene sequences by leveraging denoising auto encoders, graph attention feature extraction and pertained DNA language model to capture multi-source dependencies within multi-model biological knowledge, while its gated multi head attention module effectively identifies informative regulatory signatures and integrate complementary features from different sources to predict accurate gene regulatory networks. Benchmarking on the seven datasets of human and mouse demonstrates that scMGFGRN outperforms state of the art methods in identifying GRNs. Further analyses reveal that scMGFGRN effectively identifies novel TF gene interactions (TGIs) and reconstructs cell type specific GRNs. Interpretability analysis reveals the contribution patterns of heterogeneous biological sources, demonstrating the ability of scMGFGRN to integrate transcriptomic profiles with multi model structure information.

bioinformatics↗

bioRxiv2026

Targeting cellular senescence alleviates bone marrow aging

Aging of the hematopoietic system impairs hematopoietic stem cell (HSC) function and alters bone marrow niche behavior, increasing susceptibility to anemia, infections, and hematologic malignancies. Here, pharmacologic clearance of senescent cells with the PROTAC compound 753b simultaneously targeting BCL-xL and BCL-2 reverses key secretory, transcriptional, and functional hallmarks of hematopoietic aging with low toxicity, restoring balanced lineage output. Single-cell RNA sequencing further demonstrates that 753b treatment attenuates aging-associated transcriptional signatures in HSCs, while selectively eliminating senescent, pro-survival niche cells without grossly perturbing niche composition. Functionally, 753b suppresses pro-inflammatory cues from both niche and hematopoietic cells including those emanating from neutrophil progenitors, rebalancing global bone marrow secretory ecosystem across stromal and hematopoietic compartments. Collectively, we identify 753b-induced senescent cell clearance as a powerful strategy to rejuvenate aged hematopoiesis and re-establish homeostatic communication between HSCs and their microenvironment, with implications for mitigating age-related hematologic dysfunction and improving hematologic health in older individuals.

cell biology↗

bioRxiv2026

Species-Specific Roles of RIPK1 and TRADD in TNF-Induced Cell Death Reveal a Translational Gap Between Mouse Models and Human Biology

Mouse models have historically been central to studies of TNF-induced cell death and guided pharmaceutical translation into clinic, based on the assumption that TNF signaling is conserved between human and mouse. Here, our work uncovers critical species-specific differences between the two. By systematically dissecting the roles of RIPK1, TRADD, and sensitivity to RIPK1 inhibitors in TNF signaling--including RIPK1 kinase-dependent and-independent apoptosis--we found that both apoptosis modalities diverge between human and mouse cells. In mouse cells, RIPK1 suppresses TRADD-mediated kinase-independent apoptosis, whereas in human cells, RIPK1 and TRADD act redundantly. Moreover, RIPK1 inhibitors block kinase-dependent apoptosis in mouse but not human cells, despite effectively inhibiting RIPK1 S166 phosphorylation. Cross-species complementation revealed that these discrepancies stem not from RIPK1 itself but from cell-context differences. These findings echo the clinical failures of RIPK1 inhibitors despite efficacy in mouse models and underscore the need for humanized models and therapeutics that more faithfully predict clinical outcomes.

Cell Biology↗

bioRxiv2026

mTORC1 Directs TNF-Induced Life-or-Death Decisions via Complex I Destabilization

The transition from tumor necrosis factor (TNF)-induced plasma membrane-bound complex I to cytosolic death-inducing complex II switches cells from survival to death. However, the precise regulation of this fatal decision is incompletely understood. Here, we show that mTORC1 promotes this transition by destabilizing later-stage complex I without affecting its initial assembly. Inhibition of mTORC1 unleashes ATG9A and FIP200 activity, thereby promoting the accumulation of CHUK (IKK) in complex I. CHUK scaffolds the kinase-active IKK{beta} to stabilize complex I and prevent complex II formation. Activation of this ATG9A/FIP200-CHUK/IKK{beta} axis protects against TNF-induced fulminant hepatitis while compromises antibacterial defense against Staphylococcus aureus. This mTORC1-governed life-or-death transition provides therapeutic insight into TNF-related pathologies--including cancer, metabolic tissue injury, and microbial infections--where mTORC1 activity is frequently suppressed.

Cell Biology↗

bioRxiv2026

Nature-inspired Nanoparticle Adiposomes Enable Targeted Delivery of Hydrophobic Drug for Anti-Cancer Treatment

The predominance of hydrophobic molecules in drug pipelines poses a fundamental delivery challenge in the aqueous physiological environment. Inspired by the endogenous lipid-transport machinery of lipid droplets and lipoproteins, adiposome was developed as a biocompatible platform for hydrophobic drug delivery. Here, docetaxel (DTX) was selected as a model hydrophobic chemotherapeutic agent to evaluate the therapeutic versatility of adiposome. Non-targeted DTX-loaded adiposomes (DTX-Ad) reduced systemic toxicity by avoiding the allergenic excipients Tween 80 and ethanol used in commercial DTX formulations. The cytotoxic mechanism and intracellular responses of DTX-Ad were comprehensively characterized. To boost antitumor efficacy, three tumor-targeting DTX-Ad formulations were subsequently engineered. Lung-targeting DTX-adiposomes (Lung@DTX-Ad), mediated by AAM-B1-28-CRGDK fusion peptide/NRP1 axis, enhanced antitumor efficacy in a lung metastasis model. BCMA-targeting DTX-adiposomes (BCMA@DTX-Ad), conferred by biotin-avidin-mediated antibody conjugation, achieved sustained suppression in a multiple myeloma model. Liver-targeting DTX-adiposomes (Liver@DTX-Ad), enabled by the ApoE/LDLR axis, outperformed both commercial DTX injection and sorafenib in hepatocellular carcinoma models. Taken together, these results demonstrate adiposome as a promising and broadly applicable drug delivery platform, with considerable potential for clinical translation across diverse malignancies.

cancer biology↗

bioRxiv2026

HMA proteins produce 2',3'-cNMP signaling molecules and activate CNL-mediated immunity in rice

Plants deploy a sensor repertoire, usually NLRs, to perceive pathogen effectors and activate executor NLR-triggered immunity. Here we reveal that rice HMA proteins function as sensors detecting the Magnaporthe oryzae MAX effector AvrPigm to trigger broad-spectrum blast resistance mediated by the CNL PigmR. AvrPigm is conserved with multiple copies in blast genomes and targets HMA proteins, facilitating HMA translocation into the cytoplasm. Cryo-EM structure of the HPP04HMA reveals a filament-like oligomer with ssDNA/RNA bound inside the filament, which display cyclic nucleotide synthase activity to generate 2',3'-cNMP in a CNL-dependent manner. We further discovered that the LRR domains of the executor CNLs perceive 2',3'-cNMP to mount immunity. Our study thus establishes an unrecognized immunity mode with a distinct repertoire of sensor receptors that produce signaling molecules that are perceived by the LRR domains of executor NLRs to mediate immunity, shedding new light on the sensor-executor conception and immune activation in plants. HighlightsO_LIHMA proteins and CNL receptors form a new sensor-executor mode in plant immunity C_LIO_LICryo-EM reveals the filament-like structure of HMA-ssRNA/ssDNA C_LIO_LIHMA proteins are cyclic nucleotide synthetases to generate 2',3'-cNMP C_LIO_LILRR domains of CNLs perceive 2',3'-cNMP to mediate immunity C_LI

plant biology↗

bioRxiv2025

HypoxamicroRNA-210 protects against hepatic steatosis by inhibiting CIDEC expression

Background and AimsMetabolic dysfunction-associated steatotic liver disease (MASLD) is a major global health burden. Although hypoxia is known to contribute to MASLD pathogenesis, the role of hypoxia signaling remains poorly defined. We investigated whether HypoxamicroRNA-210 (miR-210), a key hypoxia-inducible microRNA, regulates hepatic lipid metabolism and MASLD development. MethodsSerum miR-210 levels were quantified in MASLD patients and matched controls. Human hepatic spheroids and HepG2 cells were exposed to fatty acids to assess miR-210 induction and lipid accumulation. miR-210 knockout mice were fed a Western diet to evaluate hepatic steatosis and transcriptomic changes using RNA sequencing. RNA pull-down and 3UTR-driven luciferase reporter assays were employed to identify miR-210 targets. Functional effects of miR-210 mimic were examined in knockout mice, db/db mice, and in vitro human hepatic spheroid models. ResultsSerum miR-210 levels were significantly reduced in MASLD patients compared with matched controls. Consistently, human hepatic spheroids did not appropriately increase miR-210 expression in response to fatty acid-induced intracellular hypoxia. This blunted miR-210 response contributed to hepatic lipid accumulation, as loss of miR-210 in a mouse model of MASLD led to increased hepatic lipid deposition and activation of lipid metabolic pathways. We identified CIDEC as a direct miR-210 target mediating its inhibitory effects on hepatic lipid accumulation, and restoring miR-210 expression suppressed CIDEC and reduced hepatic lipid content in knockout mice on a Western diet. Moreover, miR-210 attenuated lipid accumulation in both in vitro human hepatic spheroids and in vivo db/db mice models of MASLD. ConclusionsmiR-210 protects against hepatic steatosis by inhibiting CIDEC expression, suggesting miR-210-CIDEC axis as a promising therapeutic target for reducing hepatic lipid accumulation and preventing MASLD progression. Impact and ImplicationsThis study addresses a critical gap in understanding how hypoxia signaling shapes MASLD and uncovers a novel pathogenic mechanism of hepatic steatosis arising from fatty acids-induced dysregulation of miR-210. Impaired hypoxia responses, via blunted miR-210 induction, contribute to hepatic lipid accumulation through upregulation of CIDEC, a newly identified target of miR-210. These findings establish miR-210 as a novel regulator of hepatic lipid homeostasis and underscore its therapeutic potential. Interventions aimed at restoring miR-210 function in the liver may offer a promising strategy to ameliorate hepatic steatosis and prevent MASLD progression.

molecular biology↗

bioRxiv2025

Integrated Multi-Omics Analysis for Molecular Subtyping in NSCLC: A Cohort Study

Lung cancer remains the leading cause of cancer-related morbidity and mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases. Current histopathological classification and driver gene testing provide limited prognostic and therapeutic guidance due to intra-tumoral heterogeneity and incomplete characterization of the tumor microenvironment (TME). Here, we constructed single- and multi-omics molecular classification systems for NSCLC by integrating transcriptomic, genomic, epigenomic, proteomic, and TME data from TCGA LUAD and LUSC cohorts. Single-omics analyses revealed distinct molecular patterns, including DNA methylation subtypes associated with sex and histology. Multi-omics integration identified five consensus subtypes closely corresponding to histology, with three immune-activated (CS2-CS4) and two immunosuppressive (CS1, CS5) subtypes. While overall survival did not differ significantly, progression-free survival analysis highlighted CS4 as a high-risk subtype with KRAS-driven genomic alterations. These findings provide a framework for NSCLC molecular stratification and highlight molecular and immune features that could guide future research on targeted therapies and immunotherapy.

bioinformatics↗

bioRxiv2025

Dyslipidemic SPTLC3 Integrates Bile Acid-FXR Signaling with Sphingolipid Remodeling in MASLD

Molecular mechanisms driving metabolic disease pathogenesis remain poorly understood. Genetic and functional studies implicate SPTLC3 with dyslipidemia. SPTLC3 synthesizes atypical long-chain bases (LCB) precursors for sphingolipid production. We demonstrate significant SPTLC3 expression in human liver. ORMDL1-3 regulate SPTLC3 post-translationally in hepatic and non-hepatic cells. Independently, farnesoid X receptor (FXR) represses hepatic SPTLC3 transcription via a negative promoter element. In mice, high-fat diet (HFD) induced whereas bile acids normalized hepatic SPTLC3 transcription. SPTLC3 derived LCBs in plasma originate from the liver and are elevated in HFD-fed mice and in patients with metabolic dysfunction-associated steatotic liver disease (MASLD). Cross-species comparison revealed marked differences in LCB composition between mice and humans. Notably, omega-3-methylsphingosine (meC18SO) was significantly associated with MASLD in humans but undetectable in mice. In Huh7 cells, meC18SO enhanced complex II and IV activity, oxygen consumption, and mitochondrial ROS content. FXR-SPTLC3 axis and presented findings have potential implications for future translational research.

biochemistry↗

bioRxiv2025

CerS2 is a druggable target in triple-negative breast cancer

Triple-negative breast cancer (TNBC) remains a significant clinical challenge due to its aggressive nature and lack of effective targeted therapies. The enzyme ceramide synthase 2 (CerS2), which synthesizes pro-apoptotic very long-chain ceramides (VLCCs), represents a promising therapeutic target. Here, we identify and characterize DH20931, a novel, first-in-class small-molecule agonist of CerS2. We demonstrate that DH20931 directly activates CerS2 with nanomolar potency, leading to significant VLCC accumulation in breast cancer cells. This lipotoxic event induces endoplasmic reticulum (ER) stress and triggers apoptosis via the canonical ATF4/CHOP/PUMA signaling pathway. Mechanistically, we uncover a novel interaction between CerS2 and the ER calcium channel, Inositol 1,4,5-trisphosphate receptor 1 (IP3R1). We demonstrate that DH20931 promotes this interaction, enhancing ER-mitochondria proximity and facilitating a CerS2-dependent flux of calcium (Ca{superscript 2}) from the ER into mitochondria. This subsequent mitochondrial Ca{superscript 2} overload serves as a critical trigger for apoptosis. In preclinical evaluations, DH20931 potently inhibited the growth of TNBC cells in 2D and 3D cultures and significantly suppressed tumor progression in orthotopic and patient-derived xenograft (PDX) models, all while exhibiting a favorable safety profile. Our findings validate CerS2 as a druggable target in TNBC and establish a novel therapeutic strategy that leverages a coordinated attack on cancer cells through ER stress and calcium-mediated mitochondrial dysfunction. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/670525v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@2db377org.highwire.dtl.DTLVardef@6175d4org.highwire.dtl.DTLVardef@7edb8corg.highwire.dtl.DTLVardef@80042e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIDH20931 is a first-in-class, potent agonist of Ceramide Synthase 2 (CerS2). C_LIO_LICerS2 activation induces ER stress and engages the ATF4/CHOP/PUMA apoptotic pathway. C_LIO_LIDH20931 promotes a novel CerS2-IP3R1 interaction, causing lethal mitochondrial calcium overload. C_LIO_LITargeting CerS2 shows significant preclinical efficacy against triple-negative breast cancer. C_LI

cancer biology↗

bioRxiv2025

MSF-CPMP: A Novel Multi-Source Feature Fusion Model for Prediction of Cyclic Peptide Membrane Permeability

Cyclic peptides are becoming attractive molecules for drug discovery because of their properties with inherent stability and structural diversity. However, the high potential of cyclic peptide drugs is challenged by the limited membrane permeability cross cell membrane. To predict cyclic peptide membrane permeability (CPMP), an increased number of computational models or tools are designed and used. But these existing algorithms or models do not appropriately capture feature diversity of cyclic peptides. In this study, we introduce a novel multi-source feature fusion model called MSF-CPMP, which aims to increase the accuracy of predicted CPMP. The MSF-CPMP model incorporates three features extracted from SMILES sequences, graph-based molecular structures, and physicochemical properties of cyclic peptides. By benchmarking with other machine learning and deep learning-based methods, MSF-CPMP achieved the highest levels of the evaluation metrics such as accuracy of 0.9062 and AUROC of 0.9546, and further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source fusion. Our result demonstrates that MSF-CPMP outperforms other methods in predicting CPMP, that provides also exemplifies the power of advanced deep learning methods in tackling complex biological challenges, offering contributions to computational biology and clinical treatment. Code is available at https://github.com/wanglabhku/MSF-CPMP Author summaryWe have recognized that cyclic peptides are one type of main macro-molecular drugs useful for treatment of human diseases. However, the structural diversity of cyclic peptides results in limited permeability across cell membranes which is challenging drug research or industrial development. Previously some computational models or tools including machine learning or deep learning ones tried to solve this problem, but they still are not efficient. There are urgent requirement for more effective methodologies. Thus, we introduce a novel multi-source feature fusion model called MSF-CPMP. Our aim is to enhance accuracy and efficiency of predicted CPMP. We carried out evaluation of performance metrics by comparative analysis between MSF-CPMP and other machine learning or deep learning methods. Our result demonstrates that MSF-CPMP outperforms other models in predicting CPMP. We further validated MSF-CPMP robustness in learning capabilities and efficacy of its multi-source feature fusion. In the future we would further improve our methods that can integrate broader biomedicine and biomedical information and provide guide for drug diversity in clinically treating complex human diseases.

bioinformatics↗

bioRxiv2025

Telomerase reverse transcriptase is required for resistance to mycobacterial infection

Age is an important risk factor for infections such as tuberculosis (TB). Telomerase is expressed in immune cells yet leukocyte telomere length declines during ageing suggesting an age-dependent loss of telomerase activity in the immune system. Leukocyte telomere length has been correlated with worse outcomes in TB patients, however the mechanisms linking telomere biology to TB susceptibility and response to therapy are unexplored. Here we use the zebrafish-Mycobacterium marinum model to investigate the role of telomerase in TB resistance. We find depletion and inhibition of Tert, the catalytic subunit of telomerase, increases bacterial burden in zebrafish embryos. The Tert depletion infection susceptibility phenotype could not be rescued by p53 or STING depletion suggesting a non-canonical role for Tert in controlling mycobacterial infection. Consistent with a previously described role for Tert in developmental hematopoiesis, we find Tert is necessary for demand-driven emergency myelopoiesis to support containment of extended mycobacterial infection. Our findings establish a previously undescribed role for host telomerase in supporting infection demand-driven hematopoiesis to control infection.

immunology↗

bioRxiv2025

Clonal hematopoiesis driven by Dnmt3a mutations promotes metabolic disease development

Clonal hematopoiesis (CH) is associated with an increased risk of non-hematologic chronic diseases including metabolic disorders, yet the causality remains poorly defined. DNMT3A is the most frequently altered gene in CH, commonly through monoallelic loss-of-function (LOF) and Arg882His (RH) hotspot mutations. Here we demonstrate in a mouse model that CH driven by Dnmt3a RH and especially LOF promotes obesity, diabetes, and chronic liver disease, further exacerbated by high-fat diet (HFD).

pathology↗

bioRxiv2025

A class of COPI adaptors regulates processing of transmembrane receptors by reinforcing their Golgi retention

Many transmembrane (TM) receptors undergo essential post-translational modification in the Golgi prior to their delivery to the plasma membrane. Whether and how the passage and accompanied modification of these receptors across the Golgi is controlled remains unclear. Here, we show that leptin receptor overlapping transcript (LEPROT) and LEPROT-like 1 (LEPROTL1) regulate receptor activation by securing their sufficient Golgi retention. LEPROTs localize to cis and medial Golgi in a COPI-dependent manner. Deletion of LEPROTs in cells causes expedited release of receptors transiting through the Golgi, and leakage of some Golgi-enriched proteins into the endomembrane compartments. LEPROTs interact directly with COPI coats and simultaneously engage a variety of integral membrane proteins with relatively long TM domains at acidic pH. Loss of LEPROTs dysregulates receptor activity, including that of EGFR and TFRC, due to defective modification. Collectively, LEPROTs serve as a class of COPI adaptors for TM receptors, ensuring adequate preparation, which is vital for subsequent action on the plasma membrane.

cell biology↗

bioRxiv2025

Autoantibody hotspots reveal origin and impact of immunogenic XIST ribonucleoprotein complex

Four out of five patients with autoimmune diseases are women. The XIST ribonucleoprotein (RNP) complex, comprising the female-specific long noncoding RNA XIST and over 100 associated proteins, may drive several autoimmune diseases that disproportionately affect women, who have elevated levels of autoantibodies against the XIST RNP. However, the structural distribution, potential origin, and clinical significance of XIST RNP autoantibodies remained unexplored. Here, we find that XIST RNP is associated with autoantigens associated with six female-biased autoimmune conditions. Mapping autoantibody targets to their occupancy sites on XIST shows that these autoantigens are concentrated at discrete "hotspots" along the XIST lncRNA, notably the A-repeat. Cell type-specific protein expression data nominated neutrophils as a predominant source of hotspot antigens, and we confirmed the presence of both XIST and hotspot antigens in neutrophil extracellular traps during NETosis, an immunogenic programmed cell death pathway triggered by neutrophil activation upon which neutrophils extrude their nuclear content. Furthermore, we found that levels of autoantibodies against a top hotspot antigen, SPEN, that binds the A-repeat, correlate with severe digital ischemia in systemic sclerosis in two independent cohorts. Together, these data show a plausible mechanism for the origin of AXA, guided by RNA structure and RNA-protein interactions, and show that antibodies to XIST RNP holds promise for disease endotyping and prognostication in female-biased autoimmune conditions. One Sentence SummaryNovel autoantibodies target hotspots on XIST ribonucleoprotein complex in female-biased autoimmune diseases.

immunology↗

bioRxiv2024

Deep Ensemble Model for Quantitative Optical Property and Chromophore Concentration Images of Biological Tissues

The ability to quantify widefield tissue optical properties (OPs, i.e., absorption and scattering) has major implications on the characterization of various physiological and disease processes. However, conventional image processing methods for tissue optical properties are either limited to qualitative analysis, or have tradeoffs in speed and accuracy. The key to quantification of optical properties is the extraction of amplitude maps from reflectance images under sinusoidal illumination of different spatial frequencies. Conventional three-phase demodulation (TPD) method has been demonstrated for the mapping of OPs, but it requires as many as 14 measurement images for accurate OP extraction, which leads to limited throughput and hinders practical translation. Although single-phase demodulation (SPD) method has been proposed to map OPs with a single measurement image, it is typically subject to image artifacts and decreased measurement accuracy. To tackle those challenges, here we develop a deep ensemble model (DEM) that can map tissue optical properties with high accuracy in a single snapshot, increasing the measurement speed by 14x compared to conventional TPD method. The proposed method was validated with measurements on an array of optical phantoms, ex vivo tissues, and in vivo tissues. The errors for OP extraction were 0.83 {+/-} 5.0% for absorption and 0.40 {+/-} 1.9% for reduced scattering, dramatically lower than that of the state-of-the-art SPD method (2.5 {+/-} 15% for absorption and -1.2 {+/-} 11% for reduced scattering). It was further demonstrated that while trained with data from a single wavelength, the DEM can be directly applied to other wavelengths and effectively obtain optical property and chromophore concentration images of biological tissues. Together, these results highlight the potential of DEM to enable new capabilities for quantitative monitoring of tissue physiological and disease processes.

biophysics↗