Non-invasive health monitoring has recently gained a lot of consideration in the modern healthcare system, because it has the potential to diagnose diseases earlier and can monitor patients in a remote manner. This research presents a hybrid approach in healthcare monitoring by integrating vocal and lung abnormality detection using a multinetwork model. The model utilizes multiple data sources and Mel Frequency Cepstral Coefficients (MFCCs) to capture the frequency spectrum of the signal. A multinetwork model developed for disease identification is made up of hybrid deep learning networks, which consist of Convolutional Neural Networks (CNN) and Bi-directional Recurrent Neural Networks (BiRNN) referred as the Convolutional Bi-directional Recurrent Neural Network (CBiRNN). These CBiRNN models process both the vocal and lung datasets in parallel and feed the predicted results into the ensemble model for comprehensive evaluation. The experimental results show that the proposed CBiRNN model achieves 92% accuracy in voice disorder detection and 98% accuracy in respiratory disorder detection, while the ensemble model attains 98% accuracy for both voice and lung prediction. This innovative multimodal processing technique demonstrates significant potential in advancing health monitoring systems, offering a pathway to more accurate and reliable diagnostic tools.
Vitamin K2 is a fat-soluble vitamin that has been reported to exhibit significant anti-stress activity. Anti-stress properties are considered to be closely associated with lifespan extension. Therefore, we investigated the effects of vitamin K2 on the lifespan and stress resistance of Caenorhabditis elegans, as well as the underlying mechanisms. In the present study, we found that the effects of Vitamin K2 on C. elegans are concentration-dependent. High concentrations (10 μM) of Vitamin K2 are toxic to C. elegans, whereas lower concentrations (5 μM) are beneficial. Treatment with 5 μM Vitamin K2 can extend the lifespan of C. elegans, enhance its physiological functions, protect the intestinal barrier, and reduce the accumulation of lipofuscin associated with aging. Furthermore, Vitamin K2 enhanced the stress resistance of C. elegans by maintaining mitochondrial morphology, alleviating mitochondrial stress, reducing ROS levels, and improving mitochondrial membrane potential and ATP production. Vitamin K2 activates the JNK-1/SIR-2.1/DAF-16 signaling pathway and upregulates the expression of downstream target genes such as ctl-1, ctl-2, sod-1, sod-3, and hsp-16.2. We conclude that appropriate doses of Vitamin K2 protect C. elegans from senescence by activating the JNK-1/SIR-2.1/DAF-16-mediated anti-mitochondrial oxidative stress pathway. These findings suggest that Vitamin K2 may have beneficial effects on lifespan and mitochondrial health in C. elegans, providing a basis for further investigation into its potential relevance for aging and age-related diseases in more complex model systems.
Therapeutic resistance to chemotherapy or radiotherapy is a significant issue in several cancers, including head and neck squamous cell carcinoma (HNSCC). One pathway associated with therapeutic resistance is the NFκB pathway, which promotes survival in response to the cytokine TNFα, a key mediator of chemotherapy and radiotherapy-induced cytotoxicity. However, direct targeting of the NFκB pathway is associated with significant toxicity and thus targeting the regulation of this pathway is a promising therapeutic target. We recently demonstrated that the USP14/UCHL5 inhibitor b-AP15 inhibits NFκB activity, inhibiting proliferation and inducing apoptosis in HNSCC cells. Furthermore, b-AP15 treatment sensitised HNSCC cells to the cytotoxic effects of TNFα, as well as TNF-inducing radiation treatment. Here, we investigated if b-AP15 sensitised HNSCC cells to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL), a cancer selective member of the TNF family. b-AP15 treatment sensitised HNSCC cells to TRAIL treatment. Mechanistically, we show that b-AP15 induced expression of the TRAIL receptor Death Receptor 5 (DR5)/TRAIL Receptor 2 (TRAILR2), which was required for b-AP15-mediated TRAIL sensitisation. b-AP15 induced reactive oxygen species (ROS) and activated the JNK signalling pathway and both ROS and JNK signalling were required for the induction of DR5 expression and TRAIL sensitisation. We further show that b-AP15-mediated reduction of the NFκB-dependent gene XIAP induced DR5 expression and TRAIL sensitisation and that combination between b-AP15 and IAP antagonists was synergistic in HNSCC cells in vitro. Our data further define the mechanism of b-AP15-mediated cytotoxicity and highlight potential combination treatments that warrant further exploration in pre-clinical studies in HNSCC.
Vocal communication behavior in anurans is energetically expensive and can reveal caller locations, making them vulnerable to predation. Thus, it is likely that calls have been selected to minimize energy and make signals difficult to locate. In earlier work, Jones and Ratnam (2023) suggested that differences in the acoustic receivers of anurans and mammals may be exploited to make anuran calls difficult for mammals to locate, thereby reducing some if not all predation pressure. To test some of these ideas, this study examined sound localization performance in human listeners in response to a synthetic narrowband frog call (pulsed calls of the gray treefrog Dryophytes versicolor, 28% duty-cycle) and its variations, in a dichotic listening task using interaural time differences (ITD) alone. Sounds which were easy to locate (positive control) and difficult to locate (negative control) were also tested. Localization performance in response to synthetic calls (64%) lay between those of positive control (86%) and negative control (32%, chance level). We argue that differences in performance were largely a function of call bandwidth. Among all the variations of calls that were tested (excluding controls), the synthetic call most closely resembling the gray treefrog call had the lowest call energy, the narrowest spectral bandwidth, and was the most difficult to localize. We suggest that calls may have been selected to keep their energy as low as possible by reducing their duty cycle and reducing spectral leakage to maintain narrowband characteristics.
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Parkinson's Disease (PD) is a progressive neurodegenerative disorder that causes motor and cognitive impairments, affecting approximately 1% of individuals over 60 years of age. Speech impairments are among the earliest and most accessible biomarkers, making voice-based assessment a promising avenue for remote PD monitoring. However, existing speech-based PD prediction methods suffer from feature redundancy that degrades model performance, non-Gaussian data distributions that violate model assumptions, and limited systematic feature grouping strategies. This study introduces an adaptive approach to improve PD diagnostic precision by predicting the Motor Unified PD Rating Scale (UPDRS) and Total-UPDRS scores from biomedical voice measurements. The proposed framework addresses these challenges through three integrated components: (1) Box-Cox transformation to stabilize variance, reduce skewness, and normalize features; (2) a clustering-based feature selection method that groups correlated features via K-Means and selects the most informative representative per cluster using mutual information, thereby eliminating redundancy without losing discriminative power; and (3) an Extra Trees Regressor (ETR) whose extreme randomization in node splitting provides computational efficiency and reduced variance. To ensure rigorous evaluation, a subject-independent data splitting strategy is adopted to prevent data leakage, and k-fold cross-validation is employed to assess model stability. The proposed method is compared against multiple feature selection techniques-mutual information, recursive feature elimination, Lasso regression, and autoencoders-paired with nine regression models including Ridge, Lasso, Linear, Decision Tree, k-Nearest Neighbors, Random Forest, Gradient Boosting, AdaBoost, and Extra Trees Regressors. The clustering-based feature selection combined with ETR yielded the best performance, achieving [Formula: see text] scores of 0.999 for Motor-UPDRS and 0.997 for Total-UPDRS on the test set. These results are further supported by cross-validation analysis and feature importance evaluation, demonstrating the effectiveness and robustness of the proposed framework for speech-based PD telemonitoring.
The coevolutionary arms race between plants and herbivores drives the diversification of reciprocal adaptations. However, the transgenerational plasticity of insect behavioral responses to induced plant defenses remains poorly understood. Here, we elucidate a synchronized defense-counterdefense dynamic between tea plants (Camellia sinensis) and the geometrid moth (Ectropis grisescens). We found that larval herbivory rapidly triggers an integrated defense cascade in tea plants, involving Ca2+ signaling, MAPK activation, and jasmonate biosynthesis. This coordinated signaling leads to the accumulation of specific defensive metabolites (luteoloside, galangin, rhofolin, and vitexin), which collectively impair larval growth. Crucially, this herbivore-induced chemical defense creates a selective pressure that drives a reciprocal adaptation in the insect. Gravid E. grisescens females have evolved the ability to detect two characteristic volatiles, (E)-β-ocimene and linalool, emitted by attacked plants. These volatiles serve as reliable oviposition deterrent signals, enabling females to avoid defended hosts and thereby enhance offspring fitness. Our study integrates plant physiological signaling, phytohormone-mediated metabolomic changes, and insect behavioral ecology to reveal a novel paradigm of intergenerational coevolution. It demonstrates how plant induced defenses directly shape insect oviposition strategies, sustaining a dynamic equilibrium in agroecosystems.
The increasing application of time-series analysis in fields like biomedical engineering or telecommunications emphasizes the need for high-quality data to train and evaluate advanced machine learning models. Acquiring temporal data at suitable resolutions is often limited by ethical, economic, or practical constraints. We introduce CoSiBD (Complex Signal Benchmark Dataset for Super-Resolution), a synthetic dataset designed for reproducible time-series super-resolution research. CoSiBD provides 2,500 high-resolution signals (N = 5, 000 samples each over a reference domain τ ∈ [0, 4π]) with aligned low-resolution versions at four levels (150, 250, 500, and 1,000 samples) obtained via uniform decimation. Signals are generated with diverse non-stationary behaviors through piecewise frequency modulation and spline-based amplitude envelopes, and provides both clean and noisy variants. Signals are distributed as NumPy arrays, plain text, and JSON, with comprehensive metadata describing segment structure, generation parameters, and seeds for full reproducibility. Technical validation analyzes spectral properties and reports baseline SR benchmarking and transfer experiments on EEG and speech data.
Soybean stay-green associated virus (SoSGV) is an emerging begomovirus associated with severe disease in soybean crops in East Asia. This study investigated its evolutionary relationships, population structure, recombination history, adaptive signal, and candidate host-interaction features using integrated phylogenetic, population genetic, natural selection, and structural modeling analyses of 54 complete genome sequences. Maximum-likelihood and Bayesian phylogenetic analyses recovered SoSGV as a distinct monophyletic lineage, with strong support in the maximum-likelihood analysis (96% bootstrap support). Population genetic analysis revealed high haplotype diversity (Hd = 0.962), moderate nucleotide diversity (π = 0.022), and a negative Tajima's D value (D = - 1.49, p < 0.05), a pattern consistent with recent demographic expansion but not, by itself, proof of emergence timing. Recombination screening identified two robust coat protein-associated events (best p = 1.95 × 10⁻⁷ and 1.91 × 10⁻¹⁴), and sliding-window similarity analysis independently supported the resulting mosaic structure. Natural selection analyses detected adaptive signal in the V2 gene; MEME identified episodic selection at residues 35 and 36 (p < 0.1), while complementary methods supported additional method-dependent signals. ColabFold predicted a moderate-confidence V2 structure (mean pLDDT = 73.36). Protein docking identified a plausible V2-SKP1-related interface comprising 39 contacting residues, while a short 10 ns molecular dynamics simulation indicated preliminary structural compatibility rather than biological validation. These findings support the hypothesis that recombination contributed to SoSGV diversification and that V2 may interact with SKP1-related host proteins.
Lactate, an energy source and metabolic by-product, has been implicated in cancer progression, but its role in colorectal cancer (CRC) remains incompletely understood. This study investigated the clinical significance, biological effects, and transcriptomic responses of CRC cells to lactate. In human CRC specimens, lactate levels were positively associated with advanced clinical stage and poorer disease-free survival. Functional assays showed that lactate promoted malignant cellular behaviors in both SW480 and HCT116 cells, while pH-control experiments suggested that these effects were not merely due to extracellular acidification alone. RNA sequencing in SW480 cells identified 1,418 differentially expressed genes after lactate treatment. GO and KEGG analyses revealed alterations in multiple metabolic and signaling pathways. qRT-PCR validated the alterations of representative genes, including HK2, VEGFA, JUNB, CCNB1, MAPK4, and COX2. In addition, flow cytometry showed activation of NF-κB and HIF-1α signaling following lactate treatment, and pharmacological inhibition of either pathway significantly attenuated the lactate-induced malignant phenotypes. Together, these findings provide transcriptomic and functional evidence that lactate promotes malignant phenotypes in CRC cells and offer exploratory mechanistic insights into the involvement of NF-κB and HIF-1α signaling.
Reliable detection of bolt loosening in safety-critical infrastructure requires monitoring that captures microsecond-scale transients. However, processing 1 MHz vibration signals at the edge presents a fundamental dilemma: standard downsampling can smear sparse diagnostic impulses, whereas full-bandwidth processing is often computationally prohibitive. Here we propose PGRF-Net, a physics-guided deep learning framework that reconciles transient preservation with extreme compression. PGRF-Net integrates (1) a physics-guided resampling operator for high-rate vibration signals (e.g., 150 : 1 compression); (2) a heterogeneous gradient-spectral tensor representation that augments time-frequency information with morphology-aware channels; and (3) an asymmetric fusion module over two representations derived from the same signal (pseudo-image representation + waveform representation). On a six-class 1 MHz PVDF vibration dataset (109,668 segments; temporal-split test = 16,131), PGRF-Net reaches a best-run clean test accuracy of 95.12% under a block-wise temporal split. A strict file-disjoint split is also reported as a cross-scene hold-out protocol. On an independent Zenodo benchmark (3-fold file-disjoint CV, 9 runs per experiment), we evaluate the proposed pipeline together with three feature-engineering controls (Exp 501-503). These results support a practical compression-learning pipeline for industrial monitoring where both transient fidelity and computational efficiency are required.
Patients with Down Syndrome (DS) are characterized by dysfunction of several organs, including the liver, brain, heart defects, gastrointestinal anomalies, and lethal immune hypersensitivity. A person with DS is also susceptible to various inflammatory diseases, including hepatic autoimmune diseases. The Cyclic guanosine monophosphate-adenosine monophosphate synthase (cGAS) is known to trigger the stimulator of interferon genes (STING) and downstream proinflammatory factors. In this work, we hypothesized that oxidative stress-associated DNA damage triggers activation of the cGAS-STING signaling pathway and promotes liver inflammation in DS. Here, we investigated the role of reactive oxygen species (ROS) associated DNA damage and the cGAS-STING signaling pathway in the pathogenesis of hepatic inflammation in the DS model. Our results showed that DS cells harbor excessive ROS and DNA damage in DS fibroblasts and DS mouse liver. Further, DS cells accumulate micronuclei that likely serve as a source of cytoplasmic DNA to stimulate cGAS-STING activation. In addition, RNA-seq analysis results showed enhanced expression of key type I interferon factors in cGAS-STING pathways in DS liver and inflammatory responses and elevated liver enzymes such as alanine transaminase (ALT) that indicate a hepatocellular liver injury in DS. The results of this study opened the opportunity to connect endogenous DNA damage triggers innate immune response, which may contribute to the upregulation of the cGAS-STING signaling to exacerbate hepatic inflammation in DS.
Plant cells are connected to their neighbors via plasmodesmata facilitating the exchange of nutrients and signaling molecules. During immune responses, plasmodesmata close, but how this contributes towards a full immune response is unknown. To investigate this, we develop two transgenic lines which allow to induce plasmodesmal closure independently of immune elicitors, using the over-active CALLOSE SYNTHASE3 allele icals3m and the C-terminus of PDLP1 to drive callose deposition at plasmodesmata. Induction of plasmodesmal closure increases the expression of stress responsive genes, salicylic acid accumulation and resistance to Pseudomonas syringae DC3000. More homogeneous plasmodesmal closure using icals3m also leads to the accumulation of starch and sugars, decreases leaf growth, as well as hypersusceptibility to Botrytis cinerea. Based on the profile of responses, we conclude that plasmodesmal closure activates stress signaling, raising questions about the signals mediating this response and whether these responses occur in all circumstances when plasmodesmata close.
The c-Jun N-terminal kinase (JNK) pathway is an evolutionarily conserved signaling cascade that regulates development, stress responses, and pathogenesis. While aberrant JNK activation is linked to cancer and neurodegeneration, its regulatory mechanisms are not fully understood. Here, we identify the RNA-binding protein Ataxin-2 (Atx2) as a novel, essential regulator of JNK-mediated cell death and migration in Drosophila. Atx2 deficiency suppressed JNK-dependent apoptosis, tumor growth and invasion, and thorax closure in normal development, while its overexpression activated JNK signaling, promoting cell death, migration, and tissue remodeling. Mechanistically, Atx2 binds the 3' UTR of hipk mRNA, stabilizing it to enhance the expression of Hipk, a core upstream JNK kinase. Strikingly, this mechanism is conserved: human ATXN2L potently activated Hipk-JNK signaling and cell death in Drosophila and HeLa cells. Our findings reveal a conserved post-transcriptional mechanism for JNK pathway regulation and nominate Atx2 family proteins as potential therapeutic targets in JNK-associated pathologies.
Mesolimbic dopamine (DA) neurons are central to cue-guided reward seeking and action sequence learning. Yet, the mechanisms by which cue-induced DA neural activity drives goal-directed or habitual sequence execution remain unknown. We designed two novel tasks to isolate the effect of sequence-delineating cues on DA-driven behavioral strategies and learning. In the lever insertion fixed-ratio 5 task (LI5), the lever insertion marked sequence initiation. In the lever retraction fixed-ratio 5 task (LR5), the lever retraction served as both sequence termination and reward-predictive cue. We found that sequence initiation and termination cues differentially affect reward expectation during action sequences, with only the termination cue contributing to greater outcome devaluation insensitivity, automaticity and behavioral chunking. Mesolimbic fiber photometry recording revealed that this habit-like behavior was associated with a rapid backpropagation in DA signals from the reward to the immediately preceding cue and with attenuated DA reward prediction error signals, which reflected greater behavioral inflexibility. Finally, in absence of external cues, brief optogenetic stimulation of VTA DA neurons at sequence termination was sufficient to drive automaticity and, to some extent, behavioral chunking. Our results highlight the critical role of cue-evoked DA signals at sequence termination in driving the development of automated, habit-like sequence execution.
Cross-study inconsistencies in autism spectrum disorder (ASD) blood microRNA biomarker studies suggest that methodological heterogeneity may substantially limit reproducibility. We conducted an exploratory meta-analysis of publicly available ASD blood miRNA datasets from the Gene Expression Omnibus, applying rigorous inclusion criteria and standardized analytical protocols. Three datasets were included (GSE89596, GSE67979, GSE222046) comprising 614 miRNAs across 90 participants (45 ASD, 45 controls). Random-effects meta-analysis was performed using Hedges' g effect sizes, with comprehensive heterogeneity assessment and leave-one-dataset-out cross-validation. No miRNAs survived multiple testing correction (Benjamini-Hochberg FDR < 0.05), though seven candidate signals showed consistent evidence with unadjusted p < 0.01 and large effect sizes. These candidates demonstrated near-zero between-study heterogeneity and consistent directionality across validation analyses. Potential age-related and platform-related differences were observed, with near-zero correlation between adult and pediatric effect sizes (Kendall's τ = -0.022); however, these two sources of variability were fully confounded in the available data and could not be separated. Some miRNAs exhibited extreme between-study variability (I² > 80%), indicating substantial methodological differences. Cross-validation revealed that excluding the single adult dataset reduced sign consistency from 89.9% to 68.9%. Our findings suggest that age-related and methodological factors, including technical platform differences, may contribute to limited reproducibility in ASD blood miRNA research, and that blood-derived signals should be interpreted as potentially reflecting peripheral physiological states rather than central disease mechanisms. A supplementary cross-tissue analysis using post-mortem prefrontal cortex data (GSE59286; n = 45) provided direct empirical support for this interpretation: the majority of blood candidate miRNAs showed no corresponding expression in brain tissue, with only hsa-miR-29c-5p demonstrating directional concordance across both tissues. These findings suggest that age stratification, platform harmonization, and cross-tissue validation should be considered essential prerequisites for reliable ASD miRNA biomarker discovery, rather than optional refinements.
Cold preservation is a critical logistical step in liver transplantation but induces ischemia-reperfusion injury (IRI), a key driver of early graft dysfunction. While bulk tissue assays capture global damage, they obscure the cell-type-specific transcriptional programs engaged during hypothermic storage. We utilized a multicellular human liver-on-chip model comprising Patient-Derived Organoids (PDOs), hepatic stellate cells (HSCs), liver sinusoidal endothelial cells (LSECs), and macrophages. Chips were exposed to 24-h static cold storage using either the clinical standard University of Wisconsin (UW) solution or a hyperbranched polyglycerol (HPG)-based formulation, followed by normothermic reperfusion. Single-cell RNA sequencing (scRNA-seq) was performed to map transcriptional trajectories across the preservation-reperfusion axis. We identified candidate solution-dependent transcriptional differences across cell types. PDOs from UW-preserved chips showed comparatively higher mean expression of inflammatory and oxidative stress-associated transcripts (IFI27, SAA1, HMOX1) and mitochondrially-encoded genes (MT-ND5) relative to HPG-preserved samples, which retained comparatively higher expression of homeostatic epithelial markers (EPCAM, KRT18). HSCs and LSECs in the UW group showed comparatively elevated expression of fibrosis-associated (COL1A1, TAGLN) and endothelial adhesion (ICAM1) transcripts. Ligand-receptor interaction modelling identified candidate inflammatory communication axes, including chemokine signaling interactions (CXCL1, CCL20) between macrophages and epithelial compartments, with higher predicted activity under UW preservation. This study provides an exploratory, high-resolution map of cell-type-specific transcriptional patterns associated with hypothermic preservation in a liver-on-chip model. Our findings suggest that preservation solution chemistry is associated with distinct transcriptional signatures spanning stress response, mitochondrial, and intercellular signaling pathways. Transcriptional patterns in HPG-preserved cells were consistent with comparatively attenuated injury responses; however, these observations are hypothesis-generating and require independent biological replication and functional validation, including metabolic flux assays and ROS production measurements before conclusions regarding mitochondrial protection or clinical preservation efficacy can be drawn.
To evaluate finerenone-associated adverse events (AEs) and to investigate the association between finerenone use and renal injury via data mining of the Food and Drug Administration Adverse Event Reporting System (FAERS). To minimize statistical bias, the data extraction period was set from database inception (2004) to provide a stable background for disproportionality analysis. Four disproportionality algorithms (ROR, PRR, BCPNN, and MGPS) and stricter case-screening methods were employed to improve analytical precision. Additionally, a clinical priority evaluation was conducted to rank clinical risks and surveillance levels for these AEs. Supplementary analysis was performed to assess the relationship between finerenone and renal injury, as well as associated risk factors. A total of 1316 finerenone-related reports were identified. 30 AEs were detected as significantly positive signals, with most being related to renal function (15 PTs, 50%), blood pressure (5 PTs, 16.67%), and blood potassium (4 PTs, 13.33%). Among them, blood glucose increased, blood creatine increased, and flank pain were new potential AEs. Acute kidney injury, hyperkalemia, renal impairment, glomerular filtration rate decreased, blood creatinineincreased, blood potassium increased, and hyponatremia exhibited moderate clinical priority levels and warrant further study. Signals reflecting renal injury were detected in patients regardless of baseline nephropathy. Male sex, taking more than 3 drugs, and using amlodipine may be risk factors for finerenone-related nephrotoxicity. These results highlight new finerenone-related AEs, provide ranked guidance for pharmacovigilance through clinical priority evaluation, and clarify factors that influence renal injury, providing guidance for individualized treatment and improved drug safety.
Glutaminase 1 (GLS1) drives glutaminolysis to support tumor growth and survival, yet its role in the tumor microenvironment remains poorly understood. Here, we demonstrate that GLS1 promotes angiogenesis in head and neck squamous cell carcinoma (HNSCC) via an exosome-dependent mechanism. In HNSCC xenograft models, genetic silencing of GLS1 or treatment with CB-839 markedly reduces intratumoral angiogenesis. Exosomes from GLS1-deficient cells impair endothelial cell migration and tube formation compared with control exosomes. Proteomic analysis reveals a loss of the pro-angiogenic protein Tenascin C (TNC) in GLS1-deficient exosomes. Mechanistically, loss of GLS1 interferes with USP1-mediated deubiquitination of Caveolin-1 (CAV1), resulting in CAV1 degradation and impaired recruitment of TNC into exosomes. Exosomes deficient in CAV1-TNC complexes subsequently disrupt integrin-dependent FAK-SRC signaling in endothelial cells, inhibiting their angiogenic activity. Collectively, these findings uncover a non-metabolic role of GLS1 in promoting tumor angiogenesis through exosome-mediated CAV1-TNC signaling, suggesting that targeting GLS1 may simultaneously inhibit tumor metabolism and angiogenesis in HNSCC.
Brain arteriovenous malformations (BAVMs) are increasingly recognized as dynamic vascular diseases driven by endothelial genetic alterations and dysregulated signaling pathways, rather than as static structural anomalies. Accumulating evidence from both hereditary and sporadic forms of BAVMs has established endothelial signaling dysfunction as a central pathogenic mechanism underlying aberrant angiogenesis, progressive lesion remodeling, and vascular instability that predisposes to hemorrhage. These insights have fundamentally shifted the conceptual framework of BAVMs toward a pathway-driven disease model. Despite this progress, direct access to biologically informative molecular material from living AVM lesions remains limited, posing a major barrier to detailed mechanistic interrogation and the translation of molecular insights into clinical decision-making. Historically, molecular characterization of AVMs has relied almost exclusively on surgically resected tissue, restricting analyses to selected patient populations and frequently reflecting late-stage disease biology. Such approaches provide limited insight into disease initiation, temporal evolution, or treatment-induced molecular changes. Recent advances in minimally invasive biopsy strategies, particularly those leveraging endovascular access, have begun to overcome these limitations by enabling molecular interrogation of AVMs in vivo. In this mini review, we summarize emerging approaches for molecular profiling of AVMs, with a primary focus on BAVMs, while also drawing on relevant studies in extracranial and other arteriovenous malformations that share common endovascular access routes, technical principles, and translational implications.