Biology subjects

Kim, H.

Publications and source records attributed to Kim, H..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

Antiphospholipid syndrome (APS) is a platelet factor 4 (PF4)-centric immunothrombotic disorder

Antiphospholipid syndrome (APS) is an immunothrombotic disorder, frequently attributed to autoantibodies that bind {beta}2-glycoprotein I ({beta}2GPI). A study showed that the platelet-specific chemokine, platelet factor 4 (PF4), binds to {beta}2GPI, enhancing recognition of {beta}2GPI by APS antibodies. APS antibodies induce the release of neutrophil extracellular traps (NETs), webs of decondensed chromatin that bind both PF4 and {beta}2GPI. We propose that PF4 bridges {beta}2GPI to NETs (and other PF4-targeted polyanions), leading to the formation of prothrombotic PF4:{beta}2GPI:NET immunotargets in APS. Dynamic light-scattering studies of isolated IgGs from four patients with triple-positive APS show formation of PF4:{beta}2GPI:NET complexes that bind APS antibodies. NETs released in a microfluidic system bound {beta}2GPI, but only in the presence of PF4, forming a multimolecular APS antigenic target. Whole blood infused through a photochemically-injured, endothelium-lined microfluidic channel formed platelet-, fibrin-, and complement-rich thrombi that bound APS antibody only in the presence of PF4. Thrombi were reduced in size if either ADAMTS13 or DNase1 was infused. In a murine APS model, wildtype and transgenic mice expressing platelet human PF4 {+/-} Fc{gamma}RIIA developed more intense neutrophil rolling along veins, and more extensive thrombus formation following laser injury to cremaster arterioles and venules, whereas mice lacking PF4 did not. Three antigenically distinct anti-hPF4 monoclonal antibodies blocked thrombosis in vitro, and neutrophil rolling and thrombosis in vivo. Our studies provide new insights into the basis of APS that has mechanistic parallels to other known PF4 immunothrombotic disorders and offer potential diagnostic and non-anticoagulant therapeutic strategies for clinical management. Key pointsO_LIPF4 enhances {beta}2GPI binding to NETs and these complexes are central to APS immunothrombosis. C_LIO_LIAnti-PF4 monoclonal antibodies block APS immunothrombosis in microfluidic and murine studies. C_LI

cell biology↗

bioRxiv2025

Distinct regulation of AEBP2 isoforms on PRC2 activity

Polycomb Repressive Complex 2 (PRC2) represses gene expression through catalyzing H3K27me3, a histone modification essential for gene repression and maintenance of cellular identity. PRC2 accessory proteins modulate its catalytic activity, chromatin localization, and propagation along the chromatin. AEBP2, one of the PRC2 accessory proteins required for mouse embryogenesis, exists in distinct isoforms. The short isoform enhances PRC2 catalytic activity and promotes H3K27me3 spreading, facilitating robust gene repression while the function of the long isoform has remained unclear. Here, we found that the N-terminal region of AEBP2 long isoform contains a conserved DE-rich motif that inhibits PRC2 activity, both EZH2 automethylation and H3K27 methylation. In addition, re-expression of the AEBP2 long isoform in Mtf2/Jarid2/Aebp2 triple-knockout mESCs failed to restore H3K27me3 and caused defective differentiation, unlike the short isoform. Together, our findings uncover an isoform-specific regulatory mechanism by which AEBP2 controls PRC2 activity and contribute to a broader understanding of how PRC2 is dynamically regulated during development.

molecular biology↗

bioRxiv2025

Neuronal subtype-specific metabolic changes in neurodegenerative and neuropsychiatric diseases predicted via a systems biology-based approach

Understanding how distinct neuronal subtypes contribute to Alzheimers disease (AD) pathology remains a major challenge. Patient-derived induced pluripotent stem cell (iPSC) studies have shown neuronal subtype-specific molecular and pathological signatures, yet the underlying metabolic shifts driving this selective vulnerability are not completely understood. Here we present iNeuron-GEM, the first manually curated, genome-scale metabolic network of human neurons that integrates transcriptomic and metabolic knowledge to resolve subtype-specific metabolic states. By coupling iNeuron-GEM with single nucleus RNA sequencing data from post-mortem human cohort studies, ROSMAP and SEA-AD, we capture neuronal subtype-specific metabolic features and fluxes and identify perturbations in lipid and energy metabolism across excitatory and inhibitory neurons. Integrative analysis with NPS-AD data shows overlapping metabolic disruptions in AD and schizophrenia (SCZ), suggesting shared molecular vulnerabilities between neurodegenerative and neuropsychiatric disorders. We also developed a computational pipeline to infer transcriptional regulation of metabolic pathways and identify NR6A1 and NR3C1 as important regulators of lipid dysregulation in AD neurons. Our study establishes iNeuron-GEM as a framework to identify neuronal subtype-specific metabolic vulnerabilities in complex brain disorders.

systems biology↗

bioRxiv2025

Generative enhancement of non-invasive dataset for motor brain-computer interface by task-relevant neural signals

Despite the increasing adoption of deep neural networks (DNNs) in brain-computer interfaces (BCIs), developing high-degree-of-freedom (DOF) systems capable of decoding continuous movements, such as limb kinematics, remains a significant challenge. This difficulty stems from limited availability of task-specific neural features within individual neural signal datasets. To overcome this, we proposed a generative adversarial network (GAN) framework to enrich training features within neural signal datasets. Specifically, we synthesized artificial neural signal waveforms of the primary motor cortex (M1) from functionally related cortical regions, thereby enhancing neural datasets for improved motor kinematics decoding via DNN. Using magnetoencephalography (MEG) recordings during goal-directed arm-reaching tasks, our results showed that enhancing individual datasets with GAN-synthesized M1 signals significantly improved decoding performance by about 10% (p < 0.05). Such improved performance is sustained even in the absence of real M1 signals. We further generalized the proposed enhancement to the motor imagery BCI competition dataset to improve classification accuracy. Our results highlight the potential of signal-generative networks to improve and augment motor BCIs to achieve freely intended movements.

neuroscience↗

bioRxiv2025

Essential Resources for Curated Immune Markers and Antibody Panels in Cytometry Analysis

The immune system, fundamental to numerous biological research fields, is increasingly investigated at single-cell resolution using high-dimensional flow cytometry and mass cytometry technologies. These approaches require comprehensive immunomarker information and carefully designed antibody panels that address the technical challenges of isotopic and spectral overlap inherent in metal/fluorescent-labeled antibodies. While immune cell markers have been extensively characterized and systematically catalogued, antibody panel information remains fragmented across the literature. To bridge this critical gap, we present ImapDB (Immune cell Marker and Panel Database), a novel Python-based graphical user interface that consolidates curated information on cell markers and antibody panels. ImapDB integrates data from commercial guidebooks, peer-reviewed literature, and validated research sources, currently focusing on normal human immune cell states. The database encompasses 127 distinct immune cell subtypes with over 350 validated markers and includes 45 commercial and 23 custom research antibody panels. Available on GitHub (https://github.com/kimlab-cnu/Cell_Marker_GUI), ImapDB serves as a centralized repository designed to streamline immune profiling assays and enhance research efficiency.

bioinformatics↗

bioRxiv2025

Polyketide Synthase-Like Functionality Acquired by Plant Fatty Acid Elongase

Fatty acid elongation (FAE) typically proceeds through a four-step cycle of condensation, reduction, dehydration, and reduction to yield very long-chain fatty acids. Here, we describe a variation of this pathway in Orychophragmus limprichtianus, whose seed oil was found to contains previously unknown C24-C28 keto-hydroxy fatty acids that account for [~]25% of total fatty acids. Our studies revealed that these compounds are produced through an endoplasmic reticulum-localized discontinuous elongation process in which a 3-keto hydroxy intermediate bypasses full reduction and is extended through a polyketide synthase-like mechanism. Transcriptomic and functional assays identified two divergent enzymes, OlFAE1-2 and the low-activity ketoreductase OlKCR1-1, as central to this process. Protein modeling and mutant analysis suggest that specific amino acid substitutions underlie the altered activity of OlKCR1-1, enabling accumulation of keto intermediates. A portion of these unusual fatty acids accumulated in estolides, complex triacylglycerols that expand the chemical repertoire of seed oils. Together, our findings reveal unexpected flexibility in plant fatty acid elongation and provide new tools for engineering plants and microbes to produce renewable oils with tailored industrial functions.

plant biology↗

bioRxiv2025

Parallel frequency-multiplexed aberration measurement for widefield fluorescence microscopy

Widefield fluorescence microscopy is widely used for imaging at subcellular resolution, but its performance in complex samples is degraded by optical aberrations. Because aberrations can vary spatially across the field of view (FOV), accurate aberration measurement and correction at multiple FOV locations are essential for achieving high-quality imaging over large areas. Here, we introduce parallel frequency-multiplexed aberration measurement (PFAM) to perform massively parallel aberration measurements across an extended FOV. We validated PFAM using fluorescent beads and demonstrated simultaneous measurement and effective correction of spatially varying aberrations at 125 FOV locations. To address the challenges of wavefront sensing in complex samples, we further developed PFAM-SIFT by integrating structured illumination, thereby achieving robust aberration measurement in both brain slices and the mouse brain in vivo. Together, PFAM and PFAM-SIFT provide accurate and scalable wavefront sensing solutions for widefield imaging, enabling simultaneous aberration measurement of spatially varying aberrations in complex biological samples.

biophysics↗

bioRxiv2025

Clonal dynamics of monozygotic twinning in early human embryogenesis

Monozygotic twins are derived from the split of a single zygote early in embryogenesis. Although it was hypothesized that the timing of twining is overall associated with fetal membrane configuration of twins, i.e., chorionicity and amnionicity, our understanding of early embryonic clonal dynamics underlying human twinning is limited. Here we explored the segregations of early embryonic lineages in 7 dichorionic diamniotic (DCDA), 7 monochorionic diamniotic (MCDA), 8 monochorionic monoamniotic (MCMA) monozygotic twins, and 1 dichorionic triamniotic (DCTA) monozygotic triplets, using post-zygotic early embryonic mutations (EEMs) as endogenous lineage barcodes. Patterns of the early lineage distributions among monozygotic twins revealed three apparent clonal categories, referred to as para-identical, sub-identical, and full-identical twins, which largely correlated with the amnionicity of the twins. Rather, despite conventional wisdom, chorionicity was not substantially associated with early clonal compositions, but with blood exchanges in utero. In sub-identical twins, where one co-twin was clonally a part of the other, our data suggested that the foundation of the latter co-twin was established after acquisition of a median of 6 additional post-zygotic mutations (range: 2-13), corresponding to [~]5 early cell divisions. Additional in-depth analysis on the matched placenta from an MCDA twin suggested that separation of two co-twins can precede the separation of the placenta and embryonic proper, and a single chorion can be formed even with multiclonal origin. Our findings provide insights into the clonal dynamics, twinning processes, and cell fate decisions in early human embryogenesis.

genomics↗

bioRxiv2025

A Fully Automated, Data-Driven Approach for Dimensionality Reduction and Clustering in Single-Cell RNA-seq Analysis

Single-cell RNA sequencing (scRNA-seq) provides deep insights into cellular heterogeneity but demands robust dimensionality reduction (DR) and clustering to handle high-dimensional, noisy data. Many DR and clustering approaches rely on user-defined parameters, undermining reliability. Even automated clustering methods like ChooseR and MultiK still employ fixed principal component defaults, limiting their full automation. To overcome this limitation, we propose a fully automated clustering approach by integrating scLENS--a method for optimal PC selection--with these tools. Our fully automated approach improves clustering performance by [~]14% for ChooseR and [~]10% for MultiK and identifies additional cell subtypes, highlighting the advantages of adaptive, data-driven DR. HighlightsO_LIFully automated, data-driven clustering pipeline for scRNA-seq analysis. C_LIO_LIAddresses the limitation of fixed principal component defaults in DR. C_LIO_LIData-driven pipeline improves clustering performance by 10-14%. C_LIO_LIPerformance gains are most pronounced on high-sparsity, high-skewness data. C_LI Author SummaryA fundamental goal in modern biology is to create detailed cellular maps of complex tissues to understand their function in health and disease. Achieving this level of detail is now possible through single-cell sequencing, a technology that generates massive, high-dimensional, and noisy datasets of individual cells genetic profiles. However, accurately identifying cell-types from these datasets remains a major analytical hurdle, as current computational methods rely on subjective parameters that compromise reliability and reproducibility. To address this challenge, we developed a fully automated pipeline that integrates scLENS, an adaptive noise filtering method, with automated cell grouping tools. By providing optimal parameters for noise filtering and cell grouping, our pipeline eliminates their reliance on subjective, fixed parameters, thereby significantly improving accuracy in cell-type classification. This tool, characterized by its high clustering efficiency, can accelerate discoveries in fields like cancer biology and immunology by providing a robust and reproducible analytical platform.

bioinformatics↗

bioRxiv2025

SWING domains prime chromatin for nuclear body mediated gene regulation

Nuclear speckles have long been recognized as RNA-rich nuclear bodies, yet their role in genome organization and gene regulation remains incompletely understood. Using a rapid dTAG-mediated degradation system to simultaneously deplete SON and SRRM2--the core structural components of nuclear speckles--we identify a novel class of genomic regions, which we term SWING regions. Upon speckle disruption, SWING regions relocate to the nuclear periphery and acquire repressive histone marks such as H3K9me3, accompanied by gene downregulation, particularly of genes involved in developmental pathways. Consistent with this, depletion of Lamin A reduces lamina association of SWING regions and enhances their association with nuclear speckles, supporting a bidirectional balance between these two nuclear compartments. Notably, human mutations in SON and SRRM2 are associated with neurodevelopmental disorders characterized by intellectual disability and global developmental delay. Patient-derived cells bearing such mutations similarly exhibit SWING-region relocalization and gene repression, underlining a role for speckles in developmental gene regulation. We also report that drug-induced speckle rejuvenation partially rescues aberrant SWING-region localization to the nuclear lamina in patient-derived cells and iPSCs with acute depletion of SON. These findings identify SWING regions as an intermediate chromatin state positioned between nuclear speckles and the lamina, maintained by opposing functions from both structures. Our work reveals a mechanism underlying the contribution of nuclear bodies to 3D genome organization, highlights the importance of nuclear speckles and SWING regions in developmental regulation, and provides a potential therapeutic intervention in speckle dysfunction. Impact StatementIdentification of nuclear speckles as determinants of specific 3D genome organization. Demonstration of functional interactions between opposing nuclear structures (speckle versus lamina) through SWING regions. Establishment of developmental and human disease relevance of speckle-mediated genome organization. Providing potential avenues for therapeutic intervention in speckleopathies.

genetics↗

bioRxiv2025

T-PGI: an engineered STITCHR system for scarless, programmable genome integration

Scarless, programmable insertion of defined DNA remains a central goal for therapeutic genome editing. We introduce T-PGI (Transposon-mediated programmable genomic integration), an engineered implementation of STITCHR that preserves target-primed reverse transcription (TPRT) while substantially improving efficiency, specificity, and modularity. T-PGI uses R2Tocc, a low-background ortholog that we further engineered through defined deletions, rational point mutations, and modular domain insertions to enhance performance. The system employs paired nCas9 nicks flanking homology arms and bicistronic co-expression with dual NLSs, together with optimized RNA donor designs. Using combinatorial guide-template screening, T-PGI achieves robust integration across diverse cargos, including precise cassette insertion following multi-kilobase deletions. Short- and long-read sequencing confirm high-fidelity insertion with minimal local indels or structural variants. Collectively, these advances establish T-PGI as a practical and adaptable platform for accurate, scarless genome integration and provide concise design principles spanning enzyme architecture, donor configuration, and guide pairing for next-generation therapeutic editing.

bioengineering↗

bioRxiv2025

Fragment Screening and Structure-Guided Development of Heparanase Inhibitors Reveals Orthosteric and Allosteric Inhibition

Heparanase is the sole enzyme responsible for breaking down heparan sulfate within the extracellular matrix and its overexpression is linked to human diseases. Despite heparanase being a promising drug target, most efforts have focused on substrate mimetics, which have failed clinical trials, highlighting the need for new inhibitor scaffolds. Here, we employed fragment-based drug design to explore novel chemical space to develop small molecule inhibitors of heparanase. We used a crystallographic and computational approach to identify 31 fragments that bind heparanase; five of these inhibited heparanase in the micromolar range. One of these fragments underwent two cycles of fragment growing, which resulted in a compound with a seven-fold increased potency compared to the initial hit. The results from our fragment screen unveil untapped chemical space for heparanase inhibition, paving the way for the development of potent drug leads with the potential to transform the treatment of heparanase-related diseases. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=56 SRC="FIGDIR/small/679132v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@4a5c9corg.highwire.dtl.DTLVardef@61340org.highwire.dtl.DTLVardef@d9d2ddorg.highwire.dtl.DTLVardef@a2cf82_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

STAT3 operates as an inflammation-dependent transcriptional switch

Signal transducer and activator of transcription 3 (STAT3) is a key regulator of immune cell function, but its role in lymphocytes remains incompletely understood. Here, we show that STAT3 has a context-dependent function in antiviral natural killer (NK) cells, either promoting or impairing adaptive NK cell responses dependent on the level of inflammation. STAT3 is recruited to distinct genomic sites under homeostatic versus inflammatory environments, where it drives different transcriptional programs. Through this re-localization, STAT3 regulates downstream transcription factors MYB and BLIMP-1 in an inflammation-dependent manner to shape NK cell differentiation under homeostasis and during infection. Thus, STAT3 acts as a transcriptional switch that integrates cytokine signals to control lymphocyte adaptation to different environments. This mechanism highlights how therapeutic interventions targeting STAT3 can result in different outcomes depending on the degree of inflammation. HIGHLIGHTS- STAT3 exerts a context-dependent role on adaptive NK cells during viral infection - STAT3 modulates IL-15 signaling by competing with STAT5 and regulating MYB - Homeostatic versus inflammatory cytokines relocate STAT3 to distinct genomic sites - Downstream transcription factors MYB and BLIMP-1 govern STAT3-dependent differentiation

immunology↗

bioRxiv2025

From Correlation to Causation: Cell-Type-Specific Gene Regulatory Networks in Alzheimer's Disease

INTRODUCTIONAlzheimers disease (AD) involves complex regulatory disruptions across multiple brain cell types, yet a comprehensive understanding of the intracellular causal mechanisms remains unclear. METHODSWe presented an integrative analysis framework using single-nucleus transcriptomic with matched subject-level genotype data from 272 human AD in the Religious Orders Study and the Rush Memory and Aging Project (ROSMAP) study, and constructed causality-based, cell-type-specific gene regulatory networks (GRNs). RESULTSOur method identifies regulatory genes from both transcription factors (TFs) and non-TFs, thereby capturing a complete and accurate causal regulatory map across different brain cell types. This work revealed both established and novel regulations, pathways, and cell-type-unique hub genes in AD. Beyond constructing transcriptome-wide GRNs, we quantitatively assessed hub genes and distinguished those with regulatory or responsive roles. DISCUSSIONOur study provides a comprehensive mapping of cell-type-specific causal GRNs in AD, providing a powerful resource for dynamic pathway exploration, hypothesis generation, and functional interpretation.

neuroscience↗

bioRxiv2025

Gastrointestinal delivery of mRNA lipid nanoparticles selectively targets the pancreas

Lipid nanoparticles (LNPs) administered parenterally often show poor localization to the gastrointestinal (GI) tract and pancreas. In addition, patients typically prefer orally administered drugs to those given intravenously. We therefore investigated whether GI delivery, achievable via device mediated microneedle injections applied to buccal, gastric, small intestinal, colonic, or rectal tissues, could simultaneously enhance LNP delivery to the GI and pancreas while avoiding intravenous administration. Using a combined approach of formulation optimization and GI delivery site screening, we found that cationic SM-102 LNPs delivered gastrically achieved 7-fold higher pancreas delivery in rodents than intravenous neutral SM-102 LNPs. With dose optimization, gastric LNPs achieved 6000-fold greater pancreas to liver targeting ratios than intravenous LNPs. These results suggest GI microneedle administration can reprogram LNP biodistribution, thereby expanding therapeutic opportunities for both local and systemic nucleic acid delivery.

bioengineering↗

bioRxiv2025

LRH-1 is a novel regulator of neutrophil-driven immune responses within the tumor microenvironment.

Elevated plasma cholesterol levels have been linked to worse outcomes in breast and ovarian cancer. Prior work including our own has demonstrated that myeloid immune cells are highly responsive to cholesterol fluctuations and to proteins involved in cholesterol regulation. However, the specific roles of Liver Receptor Homolog-1 (LRH-1, or NR5A2), a key transcriptional regulator of cholesterol homeostasis, within myeloid cells remains largely undefined. Interestingly, LRH-1 mRNA levels are reduced in both breast and ovarian tumors compared to normal tissue. Its elevated expression within tumors is associated with increased survival time. These clinical correlations prompted us to explore the role of LRH-1 in myeloid cells particularly in the context of breast and ovarian cancer progression. Initial analyses confirmed LRH-1 expression in various myeloid cell types, with particularly high levels in neutrophils. We therefore focused on how LRH-1 influences neutrophil behaviors relevant to cancer, including migration, NETosis, phagocytosis, and interactions with T cells. Small molecule ligands for LRH-1 regulated neutrophil migration towards cancer cells. Phagocytosis was also regulated by LRH-1 small molecule ligands, the extent being dependent on type of bait (e. coli vs. cancer cells). In T cell co-cultures, neutrophils pretreated with an LRH-1 agonist promoted greater T cell expansion - particularly in CD4 cells - while LRH-1 inhibition suppressed this response. Moreover, LRH-1 activation reduced NETosis, while treatment with an antagonist or inverse agonist enhanced NETosis. Treatment of mice with an inverse agonist of LRH-1 increased the growth of 4T1 and E0771 mammary tumors. Given prior evidence that neutrophils contribute to the recurrence of dormant lesions, we further examined the role of LRH-1 in this context. Mice harboring dormant D2.0R mammary cancer lesions treated with an LRH-1 inverse agonist exhibited earlier tumor recurrence and enhanced metastatic progression compared to vehicle-treated controls. In contrast, treatment with BL001, a small chemical LRH-1 agonist, delayed recurrence in D2.0R-grafted mice. Collectively, these findings reveal that LRH-1 is a novel regulator of neutrophil-driven immune responses within the tumor microenvironment. LRH-1 thus remerges as a promising therapeutic target to suppress metastasis or prevent recurrence in breast cancer.

cancer biology↗

bioRxiv2025

Determination of α-Synuclein Protein Interactions by μMap Photo-proximity Labeling

Fibrillar aggregates of the natively disordered protein -synuclein (S) are hallmarks of Parkinsons disease and related neurodegenerative disorders termed synucleinopathies. Here, we used micromap ({micro}Map) photo-proximity labeling to determine the interactomes of S monomers and fibrils in mouse brain lysate to better understand both the loss of healthy function and gain of toxic function aspects of synucleinopathies. Several S variants were synthesized and characterized, showing that the small size (1 kDa) of the Ir catalyst attached through a Cys-maleimide linkage makes it minimally-perturbing to S, with a narrow labeling radius that allows one to identify interactome differences between different regions of S. Monomer and fibril interactomes were compared to each other and to previous proximity labeling data sets for validation and several examples of further investigations are demonstrated, including Western blotting, super-resolution microscopy, and {micro}Map in primary neurons.

biochemistry↗

bioRxiv2025

Dynamic Brain Network Changes Associated with Successful Smoking Cessation

BackgroundTobacco smoking continues to be a leading cause of preventable morbidity and mortality globally, with the success rate of unaided cessation remaining consistently low. Understanding the neurobiological mechanisms of smoking cessation is crucial for improving quit rates. However, there has been a lack of studies examining brain network changes associated with smoking cessation over time. In this study, we aimed to investigate longitudinal changes in the functional connectivity (FC) of large-scale brain networks underlying smoking cessation outcomes using resting-state functional magnetic resonance imaging (fMRI). MethodsA total of 98 treatment-seeking smokers participated in a 6-week cessation program and underwent resting-state fMRI scans before and after the intervention. Independent component analysis identified the salience network (SN), executive control network (ECN), and default mode network (DMN) components, and region of interest (ROI)-to-ROI FC was compared between successful and unsuccessful quitters using a group x time mixed-effects model. Correlations with smoking-related measures were explored. ResultsSignificant group-by-time interaction effects were found in FC, particularly involving connections between SN and ECN, as well as between the SN and DMN. Specifically, successful quitters exhibited greater baseline FC in the SN-ECN and SN-DMN circuits, which tended to normalize during the cessation process. Exploratory correlational analyses revealed trends suggesting that stronger pre-quit connectivity between the SN and ECN was associated with greater withdrawal severity and longer smoking history in successful quitters. ConclusionsTaken together, the normalization of initially elevated pre-quit FC in SN-ECN and SN-DMN circuits may reflect an adaptive neural process that supports successful withdrawal management and attentional reallocation during cessation. The identification of these neural substrates not only enhances our mechanistic understanding of smoking cessation over time but also underscores the need for targeted interventions that focus on these neural circuits to enhance quit outcomes.

neuroscience↗