Biology subjects

Huang, A.

Publications and source records attributed to Huang, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Altered Physiology and Ensemble Recruitment of Dentate Gyrus Semilunar Granule Cells in a Mouse Model of Epilepsy

The dentate gyrus is a major locus for structural and synaptic reorganization in temporal lobe epilepsy. While physiological changes during epileptogensis are well characterized in the principal dentate projection neuron, granule cells (GCs), epilepsy-related changes in semilunar granule cells (SGCs), a distinct subset of dentate projection neurons, remain unknown. Using a mouse pilocarpine model of epilepsy, we show that, unlike GCs, SGCs exhibit an increase in intrinsic excitability 1 week after status epilepticus (SE). GCs, not SGCs. have a lower threshold for action potential firing in mice 1-month post-SE. Both GCs and SGCs display increased frequency of spontaneous excitatory postsynaptic currents (EPSCs) 1-week and 1-month after SE. Uniquely, SGCs received more frequent spontaneous inhibitory postsynaptic currents (sIPSCs) and exhibited smaller afferent-evoked IPSCs early after SE. Additionally, evoked EPSC amplitude in SGCs was reduced 1-month post-SE. Behaviorally, mice 1-month post-SE showed impairments in their ability to use spatial search strategies in a Barnes maze paradigm. Post-SE TRAP2::tdT mice showed reduced activity dependent neuronal ensemble labeling, with fewer tdT-labeled neurons in both task-naive and trained conditions and reduced c-Fos co-expression following task re-acquisition compared to controls. Notably, the proportion of SGCs within labeled ensembles was reduced in task-naive epileptic mice but not in trained animals. Collectively, our findings identify selective changes in SGC intrinsic excitability during epileptogenesis that could contribute to enhanced network excitability. The cell-specific alterations in SGC circuit connectivity during epileptogenesis, alongside the apparent reduction in neuronal recruitment to behavioral ensembles likely contribute to spatial navigation deficits observed in epilepsy.

neuroscience↗

bioRxiv2026

Critical role of cell competition in gliomagenesis

ABSTRACTMalignant glioma is incurable. Using a mouse genetic mosaic system to generate sporadic Trp53,Nf1-null OPCs, we previously identified oligodendrocyte precursor cell (OPC) as a cell-of-origin of glioma. Here, we report that pre-malignant Trp53,Nf1-null OPCs outcompete wildtype counterparts during their expansion. Blocking competition by mutating/strengthening wildtype OPCs impeded both pre-malignant progression and malignant expansion of glioma. "In-tissue" phosphoproteomic profiling revealed an enrichment of phosphopeptides related to RNA splicing and protein translation at the peak of cell competition, suggesting that competitiveness may stem from unique protein species. Among candidates was mTORC1, whose pharmacological inhibition or genetic disruption resulted in a loss of competitiveness in our mouse model. Finally, analysis of patient biopsies and interrogating the role of individual gliomagenic mutations in OPC competition supported its relevance in human gliomas. Together, these findings identified the driving role of competitive interactions among OPCs in gliomagenesis, and suggest unconventional therapeutic strategies to target this process.

cancer biology↗

bioRxiv2026

The Caudate Nucleus Exhibits Distinct Pathology and Cell Type-Specific Responses Across Alzheimer's Disease

A{beta} presence in the caudate nucleus (Ca) partially defines Thal stage III in Alzheimers disease (AD), but little is known about ADs cellular impact on the region. Leveraging a public basal ganglia taxonomy of cellular populations, we generated a cellular resolution atlas of AD-associated pathological changes in Ca. Unlike cortex, we found that Ca AD pathology is dominated by two key features: phosphorylated tau (pTau)-containing neuropil threads enriched near oligodendrocytes in white matter tracts and amyloid-{beta} diffuse plaques enriched in gray matter. Although AD pathology in affected cortical regions results in neuronal loss, we find no AD-driven reductions in neuron proportions in Ca. However, there were observable changes in multiple cellular populations. Protoplasmic astrocytes and FLT1+/IL1B+ microglia increased in abundance with global pTau levels. We also observe gene expression changes in fast-spiking PTHLH-PVALB interneurons indicative of disrupted signaling pathways and altered intrinsic physiological properties. This work provides a cellular-resolution framework for understanding AD pathology in Ca.

neuroscience↗

bioRxiv2025

MOPRs in mouse islets of Langerhans modulate cell signaling and secretion

Article highlightsO_LIMu opioid receptors are expressed on multiple islets of Langerhans cell types C_LIO_LIMu opioid receptors on islets engage canonical Gi signaling cascades in islets C_LIO_LIMu opioid receptors on islets modulate calcium influx and oscillations C_LIO_LIMu opioid receptors on islets modulate insulin and glucagon secretion. C_LI Most clinically and recreationally used opioids drugs act on the endogenous mu opioid receptor (MOPR). While MOPR is typically studied in the context of addiction and analgesia, decades of evidence indicates that they have a strong modulatory role on metabolism and glycemia. However, whether these effects are directly driven by MOPR actions on pancreatic islets remains poorly understood. Here we sought to comprehensively profile MOPRs on islets to assess how their activity shapes cellular physiology and secretion. First, we used RNA-seq, fluorescent in situ hybridization, and immunoblotting approaches to map islet expression. We observed robust expression of MOPR across multiple cell types in islets. Next, using a FRET-based approach, we show that MOPRs recruit canonical inhibitory pathways, reducing cAMP accumulation. Correspondingly, islets from constitutive MOPR knockout mice showed increased calcium influx and oscillations. However, MOPR knockout had no effect on insulin secretion, instead increase glucagon secretion. Surprisingly, while MOPR antagonism increased overall calcium, it reduced calcium oscillations and suppressed insulin secretion. By contrast MOPR agonism suppressed calcium, increased oscillations, and had no effect on overall hormone secretion. Collectively, these results suggest that MOPR can profoundly shape islet activity, with these effects likely driven by their actions on distinct cell types.

pharmacology and toxicology↗

bioRxiv2025

Subspace clustering identifies transcriptome constraints determining cell type identity

With the advent of single-cell RNA-sequencing, researchers now have the ability to define cell types from large amounts of transcriptome information. Currently, most clustering algorithms measure cell-to-cell similarities using distance metrics based on the assumption that each cluster is comprised of "nearby" neighbors. In effect, clusters are a collection of similar cells in the embedded metric. Here, we propose that biological clusters should be comprised of sets of cells that satisfy a set of stochiometric constraints, whose intersections define a cell type. We propose to model each cell population with a single affine subspace, where all cells of the same type share a common set of linear constraints. We present an algorithm that leverages this subspace structure and learns a cell-to-cell affinity matrix based on notions of subspace similarity. We simulate scRNA-seq data according to the subspace model and benchmark our algorithm against pre-existing methods. We further benchmark our algorithm on a C. elegans dataset and show recovery of information on both cell type and developmental time. Lastly, we find the subspaces that our algorithm recovers allow us to find biologically significant genes involved in an organisms development.

cell biology↗

bioRxiv2025

Scalable prediction of symmetric protein complex structures

All life relies on proteins to function, yet accurately modeling protein structures that exceed {approx} 10, 000 amino acids or have higher-order geometries remains difficult. Existing solutions are limited to specific scenarios, require considerable computational resources, or are otherwise unscalable. Consequently, many large, disease-relevant protein complexes in the human proteome, as well as nearly all viruses and numerous other classes, are impractical to model with high fidelity for drug development. To modulate these protein complexes and viruses, structural information is eminently valuable, and often essential. In the last two years, machine learning based-tools that can generate binders to a given target structure with high hit rates have emerged. Combined with high-throughput screening, these technologies can far outpace traditional drug discovery. However, they cannot function well without accurate models of their target structures. Thus, to unlock the full power of AI-driven drug discovery, a scalable method must be developed to predict large protein complex structures. To overcome this bottleneck, we introduce Plica-1, a physics-based method to rapidly and accurately predict the structure of arbitrarily large, symmetric protein complexes. Validated across 4 major symmetry classes (icosahedral, tetrahedral, octahedral, and cyclic), the method consistently achieves near-experimental levels of accuracy, i.e., RMSD < 5[A]. In test cases, the method runs in < 5 minutes on consumer hardware, 103-105 times faster than the closest comparable software. The largest structure currently built, at {approx}40,000 amino acids, is > 8 times the limit of existing machine learning methods. The results demonstrate that protein complexes can be modeled at significantly improved speeds and scales, making Plica-1 a promising tool for protein engineering and drug development.

bioengineering↗

bioRxiv2025

Taxonomy-free fecal microbiome profiles enable robust prediction of immunotherapy response and toxicity in melanoma

The gut microbiome has been causally linked to the efficacy of immune-checkpoint inhibitor therapy (ICI), prompting numerous clinical trials of microbiome-targeting strategies. Yet, mechanisms by which gut microbiota shape immune responses remain elusive as taxonomic biomarkers have failed to generalize across multiple cohorts. In this study, we develop a taxonomy-agnostic framework to identify microbial biomarkers of ICI response and immune-related adverse event (irAE) occurrence from metagenomic sequencing. Applying this approach to four independent melanoma cohorts from clinical centers across the United States, we uncover gut microbial proteins produced by diverse bacterial taxa that consistently predict ICI response. Notably, we uncover a previously uncharacterized operon involved in cellular redox homeostasis that is encoded by different bacteria and reliably predicts irAE occurrence. We further validated the predictive power of this operon in a prospectively sequenced melanoma cohort. Our results demonstrate that taxa-agnostic microbial protein biomarkers are robust, generalizable, and provide a path towards pretreatment risk stratification for melanoma patients initiating ICI therapy.

cancer biology↗

bioRxiv2025

TOMM40 suppression promotes neuronal cholesterol imbalance and molecular and behavioral phenotypes of Alzheimer's disease

INTRODUCTIONWhile the APOE4 allele is a major risk factor for Alzheimers disease (AD), the role of TOMM40--an adjacent gene involved in mitochondrial protein import--is not known. METHODSMice, human iPSC-derived neurons (iNeurons), and human brain tissue were used for study of animal cognition, cholesterol metabolism, mitochondrial function, and gene expression. RESULTSTOMM40 knockdown (KD) impaired memory in mice and increased cholesterol and A{beta} 42 in mouse brains and human iNeurons. KD disrupted mitochondria-endoplasmic reticulum contact sites (MERCs), causing mitochondrial dysfunction and promoting reactive oxygen species that led to activation of LXRB (NR1H2), upregulation of APOE and LDLR. and increased cellular cholesterol and A{beta} 42 independent of APOE4. Human brain transcriptomics showed reduced TOMM40 expression that correlated with cholesterol regulatory gene expression, amyloid burden, and clinical AD diagnosis. DISCUSSIONTOMM40 is a novel mediator of AD pathology through dual effects on MERCs that regulate cholesterol homeostasis and mitochondrial function. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=163 SRC="FIGDIR/small/685963v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@e3e3e2org.highwire.dtl.DTLVardef@1861f67org.highwire.dtl.DTLVardef@77a813org.highwire.dtl.DTLVardef@1bb9a83_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2025

Temporal control of sgRNA library activation unlocks large-scale in vivo CRISPR screens

Functional genomics screens have illuminated genetic dependencies in cancer, but conventional in vitro approaches fail to capture vulnerabilities shaped by the tumor microenvironment. Here, we implement CRISPR-StAR (Stochastic Activation by Recombination), a next-generation inducible CRISPR screening platform for large-scale in vivo applications. The system uses a dual lox-based recombination system to enable guide-level normalization and clonal knockout phenotyping. To analyze the rich (barcode-embedded) sequencing output, we developed UMIBB, a superior Bayesian statistical framework for quantifying gene-level dropout and enrichment compared to conventional software packages. Screening a 30,000-sgRNA library in A549 xenografts, followed by clone representation and dropout correlation analyses, showed high fidelity and reproducibility with dropout phenotypes resolvable using as few as 30 tumors for this size library. Validation across multiple tumor models demonstrated that a single tumor can provide reliable, functional annotation for [~]1,000 genes leveraging intra-tumor library controls for normalization. Comparing in vivo and in vitro screens revealed that a substantial subset of tumor suppressor genes exerts strong phenotypic effects only observable in vivo. For example, single-gene knockout and transcriptomic profiling confirmed that KMT2C and KMT2D have contrasting impacts on tumor growth - an insight that would have been overlooked in standard cell culture. Looking ahead, CRISPR-StAR screening, combined with our user-friendly analysis pipeline available on GitHub (R-package), offer an integrated framework for creating in vivo dependency maps that can complement existing vitro datasets like DepMap and Achilles. Critically, our approach reduces animal use by up to 7-fold compared to conventional in vivo dropout screens. This represents a significant ethical and methodological advancement - achieving genome-scale resolution with far fewer animals and greater reproducibility.

genomics↗

bioRxiv2025

Valve endothelial monolayer fissuring via RhoA activity induces 3D calcific aortic valve lesion emergence as revealed by a longitudinal live-imaging platform

Calcific aortic valve disease (CAVD) is a degenerative disease with wide prevalence in the aging population and a low survival rate after onset of symptoms, yet there are no effective pharmacological treatments. Many patients present to the clinic with symptoms at end-stages of CAVD, when the disease may be irreversible. The ability to identify and live-trace calcific lesion emergence in-vivo would allow for the identification of disease biomarkers and discovery of therapeutic targets at earlier, more treatable stages. In this work, we establish a new multimodal in-vitro CAVD platform consisting of lineage traced-VEC and VIC cells in a 3D model combined with live optical coherence and fluorescence microscopy to unravel VEC, VIC, and matrix transitional events during calcific lesion formation. We discover that fissuring of the endothelial monolayer combined with the formation of dense aggregates in adjacent regions is a key biomarker of the onset of lesion formation. This coincides with the formation of dense VIC and ECM conglomerates under endothelial aggregates, an additional biomarker of pathogenesis. Further, we discover that fibrotic tissue compaction is correlated with but not necessary for lesion formation. Additionally, we identify RhoA activation in disease-treated samples. We demonstrate that RhoA inhibition through ROCK, but not Rac1 inhibition, prevents delamination of the endothelial monolayer, fibrotic remodeling, and emergence of calcific lesions. Together, this work establishes a new longitudinal live-imaging platform that identifies emergent cell and matrix biological signatures of CAVD onset and enables the evaluation of therapeutic interventions. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/660489v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@dc378org.highwire.dtl.DTLVardef@19c37d5org.highwire.dtl.DTLVardef@11581c6org.highwire.dtl.DTLVardef@fb0a6a_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Single-Cell Spatial Mapping of Human Kidney Development Reveals the Critical Role of the Local Microenvironment in Cell Fate Decisions

Cell-cell interactions play a pivotal role in organ development, yet these communications have previously been studied one interaction at a time in model organisms, leaving a gap in our understanding of the cellular interplay in human development. To address this, we investigated human kidney development using single-cell RNA sequencing and spatial transcriptomics, analyzing over 500,000 cells. By mapping gene expression and differentiation trajectories in histologic space, we define the spatial organization of kidney development. Our analysis revealed newfound plasticity, showing that nephron progenitor cells undergo an early fate decision between renal corpuscle and tubular lineages. However, this choice is later reversed with some mature tubule cells transitioning back to a renal corpuscle fate. Further, through a genome-wide, spatially-aware cell-cell interaction analysis, we identified specific ligands and neighboring cell signals that create biologically meaningful cellular neighborhoods and mediate cell fate choices, offering a blueprint to understand the coordination of human development at scale.

genomics↗

bioRxiv2025

Efficacy of DNA Methyltransferase Inhibitor Immune Priming Therapy in Combination with PD-1 Inhibitors to Treat High-Risk Pediatric Brain Tumors

BackgroundDespite intensive therapies, outcomes for high-risk pediatric brain tumors (PBTs) remain dismal, prompting the search for novel treatments. DNA methyltransferase inhibitors (DNMTi) have been shown to prime tumors to improve response to checkpoint inhibition. The aim of this study was to investigate the potential of decitabine (DAC), in combination with a PD-1 inhibitor, to improve survival in pediatric high-risk brain tumor models. MethodsAnalysis of human PBT datasets was performed to determine gene expression levels of immune cell associated markers. Tumor response to DAC, with or without a PD-1 inhibitor, was tested in murine models representing H3-wildtype diffuse intrinsic pontine glioma (DIPG), H3K27-mutant diffuse midline glioma (DMG), atypical teratoid rhabdoid tumor (ATRT), and medulloblastoma (MB). CyTOF analysis of allograft tumors was performed to characterize changes within the tumor microenvironment. ResultsAnalysis of PBT subtypes revealed heterogeneous expression of immune cell markers, checkpoint receptors, and MHC molecules. DAC treatment decreased DNA methylation and increased neoantigen expression in human and mouse tumor cells. DAC alone or in combination with a PD-1 inhibitor resulted in prolonged survival in syngeneic mouse models of DIPG and ATRT but not DMG and MB models. CyTOF analysis of mouse tumors revealed changes in local immune cell infiltration upon combination treatment. ConclusionsDAC in combination with a PD-1 inhibitor can alter the immune microenvironment in mouse tumor models. Changes were observed in H3-wildtype DIPG and ATRT models, suggesting that certain tumor subtypes may respond to checkpoint blockade after immune augmentation with DNMTi. Key PointsO_LIPBTs show heterogenous expression of immune cell infiltrates C_LIO_LIDAC or DAC plus a PD-1 inhibitor shows extension of survival in H3-wildtype DIPG and ATRT mouse models C_LIO_LIMyeloid-derived suppressor cell abundance could be a major contributing factor to treatment response C_LI Importance of the StudyChildren with high-risk PBTs face dismal outcomes. Immune checkpoint inhibitor (ICI) successes have been demonstrated in a variety of adult malignancies; however, such beneficial outcomes have not been realized in PBTs. Here we investigate single and combination treatment of DNMTi and PD-1 checkpoint inhibition in syngeneic mouse models of high-risk PBTs. Our results suggest that some H3-wildtype DIPG and ATRT tumor types may be responsive to checkpoint therapy post immunomodulation and warrant further investigation.

immunology↗

bioRxiv2025

H3K79 methylation and H3K36 tri-methylation synergistically regulate gene expression in pluripotent stem cells

In metazoans, nucleosomes harboring H3K79 methylation (H3K79me) deposited by the histone methyltransferase DOT1L decorate actively transcribed genes. Although DOT1L is implicated in transcription regulation and pathogenesis of human diseases such as leukemia and neurological disorders, the role of H3K79me in these biological processes remains elusive. Here, we reveal a novel functional synergism between H3K79me and H3K36 tri-methylation (H3K36me3), another histone modification enriched at active genes, in regulating gene expression and neural cell fate transition. Simultaneous catalytic inactivation of DOT1L and the H3K36 methyltransferase SETD2 via gene editing leads to the global loss of H3K79me and H3K36me3, hyperactive transcription, and failures in neural differentiation. Interestingly, the loss of H3K79me and H3K36me3 causes increased transcription elongation, gained chromatin accessibility at a group of enhancers, and increased binding of TEAD4 transcription factor and its co-activator YAP1 at these enhancers. Furthermore, YAP-TEAD inhibition partially restores the expression levels of hyperactivated genes upon H3K79me/H3K36me3 loss. Taken together, our study demonstrates a synergistic role of H3K79me and H3K36me3 in regulating transcription and cell fate transition, unveils novel mechanisms underlying such synergism, and provides insight into designing therapies that target diseases driven by misregulation or mutations of DOT1L and/or SETD2.

genetics↗

bioRxiv2025

A multi-modal cell-free RNA language model for liquid biopsy applications

Cell-free RNA (cfRNA) profiling has emerged as a powerful tool for non-invasive disease detection, but its application is limited by data sparsity and complexity, especially in settings with constrained sample availability. We introduce Exai-1, a multi-modal, transformer-based generative foundation model that integrates RNA sequence embeddings with cfRNA abundance data to capture biologically meaningful representations of circulating RNAs. By leveraging both sequence and expression modalities, Exai-1 captures a biologically meaningful latent structure of cfRNA profiles. Pre-trained on over 306 billion tokens from 8,339 samples, Exai-1 enhances signal fidelity, reduces technical noise, and improves disease detection by generating synthetic cfRNA profiles. We show that self-attention and variational inference are particularly important for preservation of biological signals and contextual relationships. Additionally, Exai-1 facilitates cross-biofluid translation and assay compatibility through disentangling biological signals from confounders. By uniting sequence-informed embeddings with cfRNA expression patterns, Exai-1 establishes a transfer learning foundation for liquid biopsy, offering a scalable and adaptable framework for next-generation cfRNA-based diagnostics.

bioinformatics↗

bioRxiv2025

Defined cellular reprogramming of androgen receptor-active prostate cancer to neuroendocrine prostate cancer

Neuroendocrine prostate cancer (NEPC) arises primarily through neuroendocrine transdifferentiation (NEtD) as an adaptive mechanism of therapeutic resistance. Models to define the functional effects of putative drivers of this process on androgen receptor (AR) signaling and NE cancer lineage programs are lacking. We adapted a genetically defined strategy from the field of cellular reprogramming to directly convert AR-active prostate cancer (ARPC) to AR-independent NEPC using candidate factors. We delineated critical roles of the pioneer factors ASCL1 and NeuroD1 in NEtD and uncovered their abilities to silence AR expression and signaling by remodeling chromatin at the somatically acquired AR enhancer and global AR binding sites with enhancer activity. We also elucidated the dynamic temporal changes in the transcriptomic and epigenomic landscapes of cells undergoing acute lineage conversion from ARPC to NEPC which should inform future therapeutic development. Further, we distinguished the activities of ASCL1 and NeuroD1 from the inactivation of RE-1 silencing transcription factor (REST), a master suppressor of a major neuronal gene program, in establishing a NEPC lineage state and in modulating the expression of genes associated with major histocompatibility complex class I (MHC I) antigen processing and presentation. These findings provide important, clinically relevant insights into the biological processes driving NEtD of prostate cancer.

cancer biology↗

bioRxiv2025

Tumor suppressor collateral damage screens reveal mRNA homeostasis protein HBS1L as a novel vulnerability in ch9p21 driven FOCAD deleted cancer

Chromosomal deletion of tumor suppressor genes often occurs in an imprecise manner, leading to co-deletion of neighboring genes. This collateral damage can create novel dependencies specific to the co-deleted context. One notable example is the dependency on PRMT5 activity in tumors with MTAP deletion, which co-occurs with CDKN2A/B loss, leading to the development of MTA-cooperative PRMT5 inhibitors. To identify additional collateral damage context/target pairs for chromosome 9p and other common loci of chromosomal deletions, we conducted a combinatorial CRISPR screen knocking out frequently co-deleted genes in combination with a focused target library. We identified the gene encoding the ribosome rescue factor PELO as synthetic lethal with loss of gene encoding the SKI complex interacting protein FOCAD, which is frequently co-deleted alongside MTAP and CDKN2A/B on chromosome 9p. A genome-wide screen in FOCAD isogenic cells further identified the ribosome rescue GTPase and PELO binding partner HBS1L as the top synthetic lethal target for FOCAD loss. Analysis of publicly available data and genetic manipulation of HBS1L using orthogonal modalities validated this interaction. HBS1L dependency in FOCAD-deleted cells was rescued by FOCAD re-expression, and FOCAD intact cells could be rendered HBS1L-dependent by FOCAD knockout, demonstrating the context specificity of this interaction. Mechanistically, HBS1L loss led to translational arrest and activated the unfolded protein response in FOCAD-deleted cells. In vivo, HBS1L deletion eliminated growth of FOCAD-deleted tumors. Here we propose a model where the FOCAD/SKI complex and HBS1L/PELO work together to resolve aberrant mRNA-induced ribosomal stalling, making the HBS1L/PELO complex an intriguing novel target for treating FOCAD-deleted tumors.

cancer biology↗

bioRxiv2025

Neutrophil KLF2 regulates inflammasome-dependent neonatal mortality from endotoxemia

Preterm neonates die at a significantly higher rate from sepsis than full-term neonates, attributable to their dysregulated immune response. In addition to tissue destruction caused directly by bacterial invasion, an overwhelming cytokine response by the immune cells to bacterial antigens also results in collateral damage. Sepsis leads to decreased gene expression of a critical transcription factor, Kruppel-like factor-2 (KLF2), a tonic repressor of myeloid cell activation. Using a murine model of myeloid-Klf2 deletion, we show that loss of KLF2 is associated with decreased survival after endotoxemia in a developmentally dependent manner, with increased mortality at postnatal day 4 (P4) compared to P12 pups. This survival is significantly increased by neutrophil depletion. P4 knockout pups have increased pro-inflammatory cytokine levels after endotoxemia compared to P4 controls or P12 pups, with significantly increased levels of IL-1{beta}, a product of the activation of the NLRP3 inflammasome complex. Loss of myeloid-KLF2 at an earlier postnatal age leads to a greater increase in NLRP3 priming and activation and greater IL-1{beta} release by BMNs. Inhibition of NLRP3 inflammasome activation by MCC950 significantly increased survival after endotoxemia in P4 pups. Transcriptomic analysis of bone marrow neutrophils showed that loss of myeloid-KLF2 is associated with gene enrichment of pro-inflammatory pathways in a developmentally dependent manner. These data suggest that targeting KLF2 could be a novel strategy to decrease the pro-inflammatory cytokine storm in neonatal sepsis and improve survival in neonates with sepsis. Summary sentenceKLF2 regulates the developmental response to endotoxin in neonatal mice through the NLRP3 inflammasome signaling pathway.

immunology↗

bioRxiv2025

Semiparametric Confidence Sets for Arbitrary Effect Sizes in Longitudinal Neuroimaging

The majority of neuroimaging inference focuses on hypothesis testing rather than effect estimation. With concerns about replicability, there is growing interest in reporting standardized effect sizes from neuroimaging group-level analyses. Confidence sets are a recently developed approach to perform inference for effect sizes in neuroimaging but are restricted to univariate effect sizes and cross-sectional data. Thus, existing methods exclude increasingly common multigroup or nonlinear longitudinal associations of biological brain measurements with inter- and intra-individual variations in diagnosis, development, or symptoms. We broadly generalize the confidence set approach by developing a method for arbitrary effect sizes in longitudinal studies. Our method involves robust estimation of the effect size image and spatial and temporal covariance function based on generalized estimating equations. We obtain more efficient effect size estimates by concurrently estimating the exchangeable working covariance and using a nonparametric bootstrap to determine the joint distribution of effect size across voxels used to construct confidence sets. These confidence sets identify regions of the image where the lower or upper simultaneous confidence interval is above or below a given threshold with high probability. We evaluate the coverage and simultaneous confidence interval width of the proposed procedures using realistic simulations and perform longitudinal analyses of aging and diagnostic differences of cortical thickness in Alzheimers disease and diagnostic differences of resting-state hippocampal activity in psychosis. This comprehensive approach along with the visualization functions integrated into the pbj R package offers a robust tool for analyzing repeated neuroimaging measurements.

neuroscience↗