Biology subjects

Lim, M.

Publications and source records attributed to Lim, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Blood-brain barrier-traversing multivalent TGFβ trap for anti-cancer immunomodulation of gliomas

Clinical studies have revealed that glioblastoma (GBM) is refractory to immunotherapy, such as immune checkpoint inhibitors (ICIs), due to the immunosuppressive tumor microenvironment (TME) primarily intensified by intratumoral upregulation of transforming growth factor-{beta} (TGF{beta}). Primary GBM tumor bulks are surgically removed in clinic, but invasive tumor cells infiltrated into surrounding normal brain tissue cannot be eradicated by systemic therapy due to the integral blood-brain barrier (BBB), leading to near-inevitable tumor recurrence. To address these translational challenges, we have engineered a TGF{beta}-inhibiting protein nanocage comprising human heavy-chain ferritin protein and TGF{beta} receptor II ectodomain that enables BBB penetration and multivalent TGF{beta} entrapment, respectively. We demonstrate that the nanocage platform, denoted T{beta}R2-HFt, following systemic administration, traverses the BBB, and extensively modulates immunosuppressive TME, both stromal and immune components, thereby potentiating the therapeutic efficacy of a clinically used ICI in multiple mouse glioma models. Notably, a majority of the glioma-bearing animals that received surgical tumor resection, followed by treatment with T{beta}R2-HFt and the ICI, survived the tumor and resisted tumor rechallenge, providing a potential means to control GBM in a durable manner.

bioengineering↗

bioRxiv2026

The MIRO1-BAX Complex Dictates Life and Death at the Mitochondrial Gate

BAX macropores in the outer mitochondrial membrane (OMM) are canonical mediators of apoptosis, but whether the same pore structure can drive distinct cell death pathways remains unclear. Here, we identify the OMM protein MIRO1 as a context-specific modulator of BAX activity. Mechanistically, MIRO1 binds BAX via MIRO1s N-terminal domain to promote macropore formation and the release of mitochondrial DNA (mtDNA) into the cytoplasm, triggering the STING-pIRF3 signaling axis. In glioma cells, this pathway sustains GPX4 expression via pIRF3-mediated transcriptional activation and confers ferroptosis resistance while bypassing inflammation. By contrast, in Parkinsonian neurons, the MIRO1-BAX complex promotes mitochondrial-stress-induced apoptosis. Using structure-guided drug discovery, we developed first-in-class small molecules that allosterically disrupt the MIRO1-BAX complex by engaging MIRO1s distal GTPase pocket. These compounds sensitize glioma cells to ferroptosis and protect neurons from apoptosis. Our findings reveal a disease-specific mitochondrial switch for life-death decisions and illuminate the molecular logic by which cells exploit and interpret OMM permeabilization.

Cell Biology↗

bioRxiv2026

Organoid modeling of tumor-associated macrophages reveals phagocytosis checkpoint blockade-induced conversion to an immunosuppressive SPP1+ phenotype

Tumor-associated macrophages (TAM) exert essential functions during the immune response to cancer. However, investigations of TAM within a native human tumor microenvironment (TME) have been impeded by a lack of appropriate model systems. Here, patient-derived organoids (PDO) from air-liquid interface (ALI)-grown tumor fragments, containing a human TME that encompassed stroma and immune subsets, robustly preserved TAM that were maintained by endogenous CSF-1 and appropriately responded to polarization signals. Antibody blockade of the CD47 regulatory checkpoint in organoids stimulated phagocytosis and remodeled TAM cytokine secretion profiles that were confirmed in anti-CD47 phase I trial patients. Amongst PDO histologies screened, anti-CD47 tumor killing was notable in clear cell renal cell carcinoma (ccRCC) which was associated with increased TAM infiltration. PDO contained diverse previously described TAM subsets; however, anti-CD47 reprogrammed organoid TAM toward an immunosuppressive SPP1+ phenotype, highlighting a negative feedback mechanism. Our findings uncover a resistance circuit engaged by macrophage checkpoint blockade and position ALI PDO as a robust translational platform for dissecting human macrophage biology and informing precision immunotherapy.

cancer biology↗

bioRxiv2026

SpikeLab: Agentic tools for spike data analysis

Large language models have the potential to transform scientific research and analysis, but without domain-specific structure they produce silent methodological errors, unreported decisions, and irreproducible results. Here we present SpikeLab, a text-to-analysis framework for neural spike data that combines composable data structures with a skill-based agentic system enforcing bounded autonomy: mandatory use of expert-vetted methods, correctness over efficiency, and clarification-seeking on ambiguous requests. In a controlled benchmark on electrophysiology data, Sonnet 4.6 with SpikeLab produced correct and reproducible results across all tasks, outperforming both the unassisted Sonnet and the more capable Opus 4.6, which exhibited deterministic failures including ad hoc method invention, silent data reduction, and inconsistent experimental designs. We demonstrate versatility across in vivo mouse, human, and in vitro brain organoid recordings, and apply the framework to a pharmacological dose-response study spanning single-unit dynamics, pairwise network structure, burst-level temporal sequences, and latent population states, all through natural language prompts without writing analysis code.

neuroscience↗

bioRxiv2025

DINOcell: Learning Generalizable Perturbation Effects through Self-Distillation

AO_SCPLOWBSTRACTC_SCPLOWPredicting cellular responses to therapeutics is a promising approach for novel target discovery. However, state-of-the-art computational models designed to predict perturbation effects struggle to generalize and outperform simple baselines. We present DINOcell, a weakly supervised framework that adapts self-distillation to single-cell transcriptomics for predicting perturbation effects. We demonstrate that DINOcell outperforms baselines in predicting the effects of single gene perturbations. Furthermore, DINOcell accurately predicts non-additive effects of combination perturbations, indicating its capacity to model complex genetic interactions. Finally, we show that DINOcell learns representations that capture biological signals and is a promising, generalizable approach for in silico perturbation modeling, providing a valuable tool for accelerating therapeutic target discovery.

bioinformatics↗

bioRxiv2025

Robotic Handling Preserves Induced Pluripotent Stem Cell Derived Vascular Smooth Muscle Cells Differentiation using a Weekend-free, Automatable, Low-variability, Low-cost (WALL) Protocol

Vascular disease modeling and tissue engineering require scalable, efficient, and reproducible methods for differentiating cells, however no studies have validated whether automation, essential for scale-up, preserves differentiation quality in cells. Here, we developed a differentiation protocol for induced pluripotent stem cell (iPSC)-derived vascular smooth muscle cells (iVSMCs) that is applicable to both manual, and automated robotic culture. iPSC lines generated from male and female donors across various ages were used to optimize the generation of iVSMCs. iVSMCs had consistent morphology and protein expression was largely similar to primary VSMCs, including expression of myosin heavy chain-11 (MYH11), -smooth muscle actin (-SMA), transgelin (TAGLN) and calponin (CNN1). Functionally, these iVSMCs could respond to the vasoconstrictor carbachol. Coupling this protocol with an automated Hamilton liquid-handling robotics system allowed the generation of iVSMCs in large quantities, morphologically similar to manually differentiated iVSMCs. Comparative proteomic analysis confirmed protein expression did not differ between automated and manual differentiation methods. Automation markedly reduced manual labor and facilitated increased production without sacrificing cell quality. This study demonstrates the feasibility of automating iVSMC differentiation, marking a significant step towards scalable VSMC manufacturing for three-dimensional applications, and for the ever-growing demands of organoid and tissue engineering applications. Statement of significanceThe rapidly expanding fields of tissue engineering and high-throughput disease modeling require large quantities of viable cells, making automation essential. Robotic liquid handling systems are increasingly employed for generating large quantities of induced pluripotent stem cell (iPSC)-derived cells, requiring the development of scalable protocols. No studies have yet evaluated whether the use of robotic liquid handling alters the differentiation of cells compared to traditional manual handling. Here, we report a scalable differentiation protocol that robustly generates iPSC-derived VSMCs (iVSMCs) from a cohort of female and male donors of varying age (n=5 lines). We demonstrate for the first time that iVSMCs, differentiated through an automated robotic pipeline, had no significant differences in morphological or proteomic phenotype compared to manual differentiation. The ability to automate this protocol facilitates robust and reproducible differentiation of large quantities of iVSMC, setting a precedent for the application of automation in generating iPSC-derived cells. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=57 SRC="FIGDIR/small/690512v1_ufig1.gif" ALT="Figure 1000"> View larger version (18K): org.highwire.dtl.DTLVardef@673d61org.highwire.dtl.DTLVardef@1eead89org.highwire.dtl.DTLVardef@c3089eorg.highwire.dtl.DTLVardef@6af2cd_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Colorectal cancer relies on an immunosuppressive cellular topography and genomic adaptations for establishing brain metastases

Colorectal cancer (CRC) brain metastases have a poor prognosis and limited treatment options, including resistance to radiation therapy. Little is known about the molecular and cellular mechanisms that enable CRC tumor cells to adapt to the brain and establish a supportive tumor microenvironment. To address this gap we used spatial transcriptomics to analyze 51 CRC brain metastases. A subset had matched primary colon tumors and longitudinally paired metastatic resections before and after radiation treatment. We identified the critical spatial cellular features of the tumor epithelium and the surrounding tumor microenvironment that support metastatic growth in the brain. CRC brain metastases developed a stromal microenvironment with abundant fibroblasts and tumor-associated macrophages. A fibroblast-macrophage cellular neighborhood promoted angiogenesis, extracellular matrix remodeling, and immune suppression. Tumor cells showed local adaptations. In endothelial-rich regions, they were proliferative whereas in macrophage-rich regions, they were more differentiated and immune evasive. Compared with paired primary tumors, CRC brain metastases showed increased chromosomal instability, with activation of RNA-processing, stress response, and junctional remodeling pathways. After radiation treatment, resistant clones had increased epithelial-mesenchymal transition, while the immunosuppressive stroma remained intact. We identified tumor-derived MIF, GDF15, PRSS3 and SEMA3C ligands and macrophage-derived SPP1 that have the potential to affect multiple cell types in the metastatic niche. These ligand-receptor interactions drive angiogenesis, stromal activation and immune suppression. In a macrophage-tumor-fibroblast co-culture model, knockout of SPP1 in macrophages led to reduced expression of lipid-metabolism related genes and disrupted tumor-promoting interactions. Together, these results indicate that CRC growth in the brain is sustained by a specific cellular organization with immunosuppressive multicellular interactions.

cancer biology↗

bioRxiv2025

Cross-Species Transcriptomic Integration Reveals a Conserved, MIRO1-Mediated Macrophage-to-T Cell Signaling Axis Driving Immunosuppression in Glioma

Mitochondrial regulators are increasingly recognized for their influence on immune signaling within the tumor microenvironment (TME). In glioma, where immunosuppression limits therapeutic efficacy, we investigate how targeting the mitochondrial protein MIRO1 alters the TME. We combine single-nucleus RNA sequencing of murine gliomas treated in vivo with a MIRO1-binding compound and bulk RNA sequencing of human glioma resections treated with the same compound ex vivo. Cross-species transcriptomic integration reveals a MIRO1-responsive program in the TME. Among shared targets, we identify PARP11/Parp11 as a consistently upregulated gene in glioma that is downregulated following MIRO1-binding compound treatment in both human and mouse gliomas. Cell-cell communication analysis shows that a specific cluster of macrophages (MAC1), which exhibits robust Parp11 and Pdl1 (encoding PD-L1) expression, sends immunosuppressive signals to CD8+ cytotoxic T cells, and may receive prostaglandin E{square} signals from another cluster of macrophages (MAC4). Targeting MIRO1 eliminates this cell circuitry and reduces the tumor cell population. Our study provides a transcriptomic framework for understanding mitochondria-immune crosstalk and nominates MIRO1-PARP11 as a potential effector axis of brain immune dysfunction. Summary BlurbTranscriptomic integration of single-nucleus RNA sequencing of murine gliomas and bulk RNA sequencing of human gliomas reveals an immunosuppressive signaling axis in the glioma TME, mediated by MIRO1.

cancer biology↗

bioRxiv2025

Dual checkpoint blockade of glioblastoma with Anti-PD-1 and Anti-LAG-3 promotes expansion of tumor-reactive T cell clones along a unique pathway of differentiation

IDH-wildtype grade IV glioblastoma is the most aggressive adult primary brain tumor and remains refractory to anti-PD-1 monotherapy despite evidence of limited tumor-specific T cell induction. To determine the impact of immune checkpoint inhibitors (ICIs) on glioblastoma T cell transcriptional landscape and repertoire, we conducted paired single-cell RNA sequencing (scRNA-seq) and T cell receptor sequencing (TCR-seq) of tumor-infiltrating lymphocytes (TILs) from patients with untreated, newly diagnosed glioblastoma and from recurrent glioblastoma treated with dual checkpoint blockade targeting PD-1 and LAG-3. Using a validated transcriptional signature, we found that predicted tumor-reactive T cells (TRC) in untreated glioblastomas reside almost exclusively in a clonally expanded GZMKhi population with developmental plasticity, affording them the potential to differentiate into both tissue-resident and terminal effector T cells. Dual ICI therapy induced substantial clonal remodeling, characterized by the recruitment of new TRC from the periphery into the tumor microenvironment (TME) and differentiation into transitional effectors and ultimately terminal effectors along a gradient characterized by simultaneous acquisition of cytotoxic and exhaustion genes, regulated by specific transcriptional, metabolic, and epigenetic programs. Longitudinal clonal tracking in peripheral blood confirmed that with ICI treatment, most TRC expand transiently in circulation prior to tumor infiltration, with peripherally derived clones becoming the major contributor to the GZMKhi TRC that further expand in the tumor. Our study provides the first comprehensive map of T cell clonal dynamics and differentiation in glioblastoma following dual ICIs and highlights a potential mechanism of immune activation and peripheral recruitment of TRC in glioblastoma not previously described. Our results suggest that therapeutic strategies to sustain these GZMKhi early effector and transitional effector T cells may further enhance ICI therapeutic efficacy in glioblastoma.

immunology↗

bioRxiv2025

Transcriptome sequencing of Hodgkin lymphoma Hodgkin and Reed-Stenberg cells reveals escape from NK cell recognition and an unfolded protein response

The mutational profile of classic Hodgkin lymphoma (cHL) overlaps with that of related B cell lymphomas, including primary mediastinal B cell lymphoma (PMBL), and yet these are different histologically and clinically. To discover the molecular features that distinguish cHL, we deployed flow cytometric cell sorting and low-input RNA sequencing to generate full transcriptome data from viable, isolated Hodgkin and Red-Sternberg (HRS) cells from eighteen primary tumors, alongside matched intra-tumoral non-neoplastic B cells and four cell lines. Comparison of HRS cells to normal cellular subsets revealed evidence of abortive plasma cell differentiation, with an unfolded protein response signature, shared with plasma cell neoplasms, but not other B-cell lymphoma types. Comparison of cHL to PMBL revealed similarities but also key differences in B cell differentiation programs accompanied by upregulation of genes involved in microtubule cytoskeleton organization in cHL, which may be related to the unique multinucleated nature of HRS cells. In HRS cells, we also observed a downregulation of SLAM family receptors, which are crucial for NK cell activation, providing a potential mechanism for immune evasion from NK-mediated killing. STATEMENT OF SIGNIFICANCEThis study defines a unique transcriptional program in classic Hodgkin Lymphoma (cHL) marked by oncogenic signaling, chromatin integrity, DNA repair, and immune escape including loss of NK-activating receptors. HRS cells resemble plasma cells and have an unfolded protein response signature, which distinguishes them from diffuse large and primary mediastinal B cell lymphomas.

cancer biology↗

bioRxiv2025

Emotional and Linguistic Features Predict Prefrontal Functional Connectivity during Ongoing Dialogues: An fNIRS Investigation

Identifying the neural bases of language has been a central focus in neuro-science since the pioneering case studies by Broca and Wernicke. Contemporary research has moved beyond classical modular models to conceptualize language as supported by a distributed network of anatomically and functionally interconnected brain regions. Yet, few studies have explored how these networks operate during spontaneous, real-life speech, limiting our understanding of language in natural contexts. In this study, we collected data from 84 individuals engaged in live conversations. Participants prefrontal brain activity was recorded using functional near-infrared spectroscopy hyperscanning, and functional connectivity was quantified via wavelet transform coherence. Dialogues were manually transcribed, and computational methods were applied to extract emotional and semantic/syntactic features from the speech data. Using linear mixed-effects models, we found that emotional content significantly predicted prefrontal functional connectivity [Formula] Among all emotional predictors, expressed anger was the most robust: higher anger levels were associated with reduced connectivity between the left middle frontal gyrus and the right inferior frontal gyrus [Formula]. While other semantic and syntactic features did not predict overall connectivity, degree assortativity--an index of linguistic structure--was negatively associated with connectivity between the superior frontal gyri and the left inferior frontal gyrus [Formula]. These findings highlight how both affective and structural properties of speech modulate prefrontal connectivity during real-life interaction. More broadly, this work demonstrates the potential of integrating computational linguistics with social neuroscience to uncover the neural mechanisms of real-life social interactions.

neuroscience↗

bioRxiv2025

DCAF16-Based Covalent Degradative Handles for the Modular Design of Degraders

Targeted protein degradation (TPD) is a powerful strategy for targeting and eliminating disease-causing proteins. While heterobifunctional Proteolysis-Targeting Chimeras (PROTACs) are more modular, the rational design of monovalent or molecular glue degraders remains challenging. In this study, we generated a small library of BET-domain inhibitor JQ1 analogs bearing elaborated electrophilic handles to identify permissive covalent degradative handles and E3 ligase pairs. We identified an elaborated fumaramide handle that, when appended onto JQ1, led to the proteasome-dependent degradation of BRD4. Further characterization revealed that the E3 ubiquitin ligase CUL4DCAF16--a common E3 ligase target of electrophilic degraders--was responsible for BRD4 loss by covalently targeting C173 on DCAF16. While this original fumaramide handle, when appended onto other protein-targeting ligands, did not accommodate the degradation of other neo-substrates, a truncated version of this handle attached to JQ1 was still capable of degrading BRD4, now through targeting both C173 and C178. This truncated fumaramide handle, when appended on various protein targeting ligands, and was also more permissive in degrading other neo-substrates, including CDK4/6, SMARCA2/4, and the androgen receptor (AR). We further demonstrated that this optimized truncated fumaramide handle, when transplanted onto an AR DNA binding domain-targeting ligand, could degrade both AR and the undruggable truncation variant of AR, AR-V7, in androgen-independent prostate cancer cells in a DCAF16-dependent manner. Overall, we have identified a unique DCAF16-targeting covalent degradative handle that can be transplanted across several protein-targeting ligands to induce the degradation of their respective targets for the modular design of monovalent or bifunctional degraders.

biochemistry↗

bioRxiv2025

Centella asiatica improves sleep quality and quantity in aged mice

Age-related sleep disruption is common in older adults. Not only does the total amount of time spent in sleep decline, but the number of arousals during sleep increases with age. As sleep is important for both memory consolidation and to prevent neurodegenerative pathology, this decline in sleep and/or sleep consolidation may underlie age-related cognitive decline and dementias. Furthermore, treatment of sleep disruption can improve quality of life. However, few interventions have successfully reversed age-related sleep decline. Extracts from the plant Centella asiatica have demonstrated neuroprotective effects in human, rodent, and fly models of aging and neurodegenerative diseases, and is a promising intervention for dementias, yet little is known about how these extracts affect sleep patterns. Here, we administered Centella asiatica water extract (CAW) dosed or control chow to male and female C57BL6/J mice aged 18 months. Effects on sleep composition were determined using electrodes that recorded EEG and EMG signals. We found that CAW dosed chow (1000 mg/kg/day) increased REM sleep time in aged male mice and decreased the number of arousals during sleep observed in aged females, compared to age- and sex-matched controls. We conclude that CAW administered in food has a moderate, sex-dependent effect on sleep quantity and quality. Statement of SignificanceSleep declines with age and may underline age-related cognitive changes. However, few interventions have successfully reversed age-related sleep and cognitive decline. This study found that botanical extract from the plant Centella asiatica increased total REM sleep time in aged male mice, and decreased sleep fragmentation in aged female mice, compared to age- and sex-matched controls. Whether these moderate, sex-dependent effect sizes on sleep in aged mice are impactful enough to affect cognition, quality of life, and/or neurodegenerative pathology could be explored in future studies.

neuroscience↗

bioRxiv2024

Negative regulation of Activation-Induced Cytidine Deaminase gene transcription in developing B cells by a PU.1-interacting intronic region

Activation-induced cytidine deaminase (AID, encoded by Aicda) plays a key role in somatic hypermutation and class switch recombination in germinal center B cells. However, off-target effects of AID are implicated in human leukemia and lymphoma. A mouse model of precursor B cell acute lymphoblastic leukemia driven by deletion of the related transcription factors PU.1 and Spi-B revealed C->T transition mutations compatible with being induced by AID. Therefore, we hypothesized that PU.1 negatively regulates Aicda during B cell development. Aicda mRNA transcript levels were increased in leukemia cells and preleukemic bone marrow pre-B cells lacking PU.1 and/or Spi-B, relative to wild type cells. Using chromatin immunoprecipitation, PU.1 was found to interact with a negative regulatory region (R2-1) within the first intron of Aicda. CRISPR-Cas9-induced mutagenesis of R2-1 in cultured pre-B cells resulted in upregulation of Aicda in response to lipopolysaccharide stimulation. Mutation of the PU.1 interaction site and neighboring sequences resulted in reduced repressive ability of R2-1 in transient transfection analysis followed by luciferase assays. These results show that a PU.1-interacting intronic region negatively regulates Aicda transcription in developing B cells.

immunology↗

bioRxiv2024

Spatial Transcriptomics Reveals Spatially Diverse Cancer-Associated Fibroblast in Lung Squamous Cell Carcinoma Linked to Tumor Progression

While cancer-associated fibroblasts (CAFs) are crucial in influencing tumor growth and immune responses in lung cancer, we still lack a comprehensive understanding of their spatial organization associated with tumor progression and clinical outcomes. This gap highlights the need to elucidate how the intricate spatial arrangement of CAFs affects their interactions within the tumor microenvironment, ultimately shaping cancer progression and patient prognosis. Here, we unveil the spatial diversity of CAFs in lung squamous cell carcinoma (LUSC), a prevalent and aggressive lung cancer type, elucidating their impact on tumor progression and patient outcomes using spatial transcriptomics (ST). Image-based ST data from 33 LUSC patients demonstrated a significant association of spatial interactions of tumor epithelium and CAFs with tumor size and metabolic activity measured by [18F]fluorodeoxyglucose PET. Furthermore, the proximity of fibroblasts to tumor epithelial cells was linked to recurrence-free survival in LUSC patients. By characterizing CAFs based on their spatial relationship, we identified distinct molecular signatures related to spatially distinct fibroblast subpopulations. In addition, barcode-based ST data from 8 LUSC patients revealed spatially overlapping fibroblast regions characterized by upregulated glycolysis pathways. Our study underscores the importance of the complex spatial dynamics of the tumor microenvironment revealed by ST and its implications for patient outcomes in LUSC.

cancer biology↗

bioRxiv2024

RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies

With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms{+/-}1.5ms (mean{+/-}STD) after the waveform trough while the recording remains ongoing. RT-Sorts true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sorts performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sorts functionality on different types of recording hardware and electrode configurations.

neuroscience↗

bioRxiv2024

DCAF16-Based Covalent Handle for the Rational Design of Monovalent Degraders

Targeted protein degradation with monovalent molecular glue degraders is a powerful therapeutic modality for eliminating disease causing proteins. However, rational design of molecular glue degraders remains challenging. In this study, we sought to identify a transplantable and linker-less covalent handle that could be appended onto the exit vector of various protein-targeting ligands to induce the degradation of their respective targets. Using the BET family inhibitor JQ1 as a testbed, we synthesized and screened a series of covalent JQ1 analogs and identified a vinylsulfonyl piperazine handle that led to the potent and selective degradation of BRD4 in cells. Through chemoproteomic profiling, we identified DCAF16 as the E3 ligase responsible for BRD4 degradation--an E3 ligase substrate receptor that has been previously covalently targeted for molecular glue-based degradation of BRD4. Interestingly, we demonstrated that this covalent handle can be transplanted across a diverse array of protein-targeting ligands spanning many different protein classes to induce the degradation of CDK4, the androgen receptor, BTK, SMARCA2/4, and BCR-ABL/c-ABL. Our study reveals a DCAF16-based covalent degradative and linker-less chemical handle that can be attached to protein-targeting ligands to induce the degradation of several different classes of protein targets.

biochemistry↗

bioRxiv2024

Emotional Content and Semantic Structure of Dialogues Predict Interpersonal Neural Synchrony in the Prefrontal Cortex: a Hyperscanning Studywith Functional Near-Infrared Spectroscopy

A fundamental characteristic of social exchanges is the synchronization of individuals behaviors, physiological responses, and neural activity. However, the association between how individuals communicate in terms of emotional content and expressed associative knowledge and interpersonal synchrony has been scarcely investigated so far. This study addresses this research gap by bridging recent advances in cognitive neuroscience data, affective computing, and cognitive data science frameworks. Using functional near-infrared spectroscopy (fNIRS) hyperscanning, prefrontal neural data were collected during social interactions involving 84 participants (i.e., 42 dyads) aged 18-35 years. Wavelet transform coherence was used to assess interpersonal neural synchrony between participants. We used manual transcription of dialogues and automated methods to codify transcriptions as emotional levels and syntactic/semantic networks. Our quantitative findings reveal higher than random expectations levels of interpersonal neural synchrony in the superior frontal gyrus (q = .038) and the bilateral middle frontal gyri (q < .001, q < .001). Linear mixed models based on dialogues emotional content only significantly predicted interpersonal neural synchrony across the prefrontal cortex[Formula] . Conversely, models relying on syntactic/semantic features were more effective at the local level, for predicting brain synchrony in the right middle frontal gyrus [Formula] Generally, models based on the emotional content of dialogues were not effective when limited to data from one region of interest at a time, whereas models based on syntactic/semantic features show the opposite trend, losing predictive power when incorporating data from all regions of interest. Moreover, we found an interplay between emotions and associative knowledge in predicting brain synchrony, providing quantitative support to the major role played by these linguistic components in social interactions and in prefrontal processes. Our study identifies a mind-brain duality in emotions and associative knowledge reflecting neural synchrony levels, opening new ways for investigating human interactions.

neuroscience↗