Search Results (79)

Epidemiological investigations have indicated that females are particularly susceptible to perfluorooctane sulfonate (PFOS)-induced cognitive impairment, yet the mechanisms underlying this sex-specific vulnerability remain obscure. Estrogen and estrogen receptor β (ERβ) signaling are essential for female brain function, but their role in PFOS-induced neurotoxicity has not been explored. We therefore hypothesized that disruption of astrocyte-derived estrogen–ERβ signaling, leading to downregulation of N-myc downstream-regulated gene 2 (NDRG2) and subsequent synaptic dysfunction, contributes to PFOS-induced neurotoxicity in females. Female rats were exposed to PFOS for 30 days, followed by behavioral tests and hippocampal analysis. PC12 cells were treated with astrocyte-conditioned medium (ACM) to assess synaptic injury. Molecular docking was further performed to predict the binding affinity between PFOS and ERβ. In vivo, PFOS exposure impaired cognitive performance and caused hippocampal dysfunction, accompanied by decreased levels of estradiol (E2), aromatase (AROM), ERβ, N-myc downstream regulated gene 2 (NDRG2), and AMPA receptors (AMPARs), together with increased glial fibrillary acidic protein (GFAP) and Ca²⁺/calmodulin-dependent protein kinase II (CaMKII) in the hippocampus. In vitro, PFOS-exposed C6 cells showed reduced E2, AROM, ERβ, and NDRG2, along with elevated GFAP and extracellular glutamate concentration. PC12 cells treated with PFOS-ACM exhibited decreased synaptophysin (SYP), postsynaptic density protein 95 (PSD-95), and AMPARs, as well as increased CaMKII, indicative of synaptic injury. Pretreatment with E2 or the ERβ agonist diarylpropionitrile (DPN) could reverse these molecular alterations and mitigate neuronal dysfunction. Molecular docking revealed a strong binding affinity between PFOS and ERβ. Collectively, these findings support our hypothesis that PFOS impairs cognitive function in female rats by disrupting astrocyte-derived estrogen–ERβ–NDRG2 signaling, with NDRG2 as a potential downstream effector. This provides a mechanistic basis for the heightened female susceptibility to PFOS neurotoxicity and highlighting ERβ as a potential therapeutic target. Full article

This paper presents a computational model of delirium in the Intensive Care Unit (ICU), in which delirium is defined as the endpoint of a self-reinforcing cycle of predictive failure between two bidirectionally coupled agents: the patient and the ICU room environment. Drawing on the active inference framework and the free energy principle, the paper proposes that delirium is not a property of the patient in isolation but a relational phenomenon that emerges when the environment persistently fails to predict the patient’s internal state. This failure triggers a causal feedback mechanism in which desynchronization pressure progressively sharpens the patient’s prior beliefs—implementing precision rigidity in the correct active inference sense: not a brain overwhelmed by noise but a brain locked into a state that incoming observations can no longer update. The model is implemented as a two-agent POMDP in which both agents maintain generative models and continuously attempt to predict each other’s states. The room agent (R)—understood as the environment-side sensing–inference–actuation loop, whether instantiated by clinical staff or by an automated monitoring system—infers the patient (P)’s latent parameters $({\theta }_{\mathrm{cog}},{\theta }_{\mathrm{emo}})$ over time and builds a progressively personalized generative model of the patient. Synchronization is operationalized via two commensurable directional surprisal metrics: $S_{R\to P}=-ln{Q}_R\left(s^{*}\right)$, the room’s surprisal at the patient’s true state, and $S_{P\to R}=-lnP(o_R\mid Q_P)$, the patient’s surprisal at the room’s observations. A systematic ablation study across four model variants shows that room inference is the architectural component necessary to reproduce the synchronization–delirium relationship: when the room infers, the association between synchronization and declared delirium is strong and stable, whereas a non-inferring room collapses to ceiling delirium rates and a weak association. $\theta$ learning and the prior-sharpening feedback do not increase the strength of this association; instead they shape the phenotypic gradient, reducing ceiling effects in vulnerable phenotypes and amplifying the separation between them. The model is presented as a computational hypothesis generator rather than a calibrated clinical predictor, and its implications for ICU design are discussed. Full article

Background: Brain metastasis is associated with poor prognosis in lung adenocarcinoma (LUAD). Anoikis resistance may contribute to tumor cell survival during metastatic dissemination and brain colonization; however, robust biomarkers for prognostic stratification and brain metastasis-associated classification remain limited. This study aimed to investigate anoikis-related molecular features in LUAD brain metastasis and develop a machine learning-based signature for prognostic assessment and exploratory classification of primary and brain-metastatic LUAD samples. Methods: We integrated single-cell and multi-cohort bulk transcriptomic data. Single-cell analysis was performed to characterize anoikis-related cellular states and intercellular communication in primary and brain-metastatic LUAD samples. In the bulk transcriptomic analysis, TCGA-LUAD was used for prognostic feature selection and risk-model construction, and GSE26939 was used for external prognostic validation. The classification performance of the fixed signature for distinguishing primary LUAD from brain-metastatic LUAD samples was further evaluated in GSE161116 and GSE271259. Immune microenvironment features were assessed, and an LLM-assisted exploratory drug-screening strategy combined with molecular docking was used to prioritize candidate compounds. Results: Single-cell analysis suggested that metastatic epithelial cells exhibited enhanced anoikis-related activity, accompanied by macrophage-associated SPP1-CD44 and MIF-(CD74+CXCR4) communication patterns. Machine learning-based feature selection identified an eight-gene signature consisting of BIRC3, CCL20, CLEC7A, CTSL, GOLM1, ICAM3, MTUS1, and SERPINH1. The signature showed prognostic value in TCGA-LUAD and GSE26939 and demonstrated exploratory classification performance in distinguishing primary LUAD from brain-metastatic LUAD samples. High-risk patients exhibited immune microenvironment alterations and enrichment of tumor progression-related pathways. LLM-assisted compound prioritization and molecular docking highlighted resveratrol and SB431542 as hypothesis-generating candidates with predicted interactions with core targets. Conclusions: This study identified an anoikis-related eight-gene signature for LUAD prognostic stratification and exploratory brain metastasis-associated classification. The findings suggest the potential involvement of anoikis-related tumor–microenvironment interactions in LUAD brain metastasis and provide candidate genes and compounds for further experimental validation. Full article

Introduction: Transcranial photobiomodulation (t-PBM) is a non-invasive metabolic neuromodulation technique intended to enhance cerebral bioenergetics by stimulating mitochondrial activity. To characterize both baseline metabolic vulnerability and real-time metabolic engagement during stimulation, this preliminary study integrated phosphorus magnetic resonance spectroscopy (³¹P-MRS) with resting-state fMRI. Methods: Eleven individuals with mild cognitive impairment (MCI) or early Alzheimer’s disease underwent ³¹P-MRS to quantify baseline cerebral metabolism (PCr/Pi, pH), followed by MRI sessions during which t-PBM was applied over bilateral frontal sites. Fractional amplitude of low-frequency fluctuations (fALFF), a resting-state index strongly associated with cerebral glucose metabolism, was used as a real-time proxy of metabolic change during stimulation. Results: Linear regression analyses indicated that lower baseline PCr/Pi and lower pH, markers of impaired oxidative metabolism, predicted greater increases in fALFF during t-PBM, most prominently in the right frontal pole (FP2) and, to a lesser extent, right dorsolateral prefrontal cortex (F4). While greater dementia severity also predicted larger fALFF responses in select regions, our findings suggest that t-PBM can boost metabolism in some brain regions where it is compromised, but that this may be independent of cognitive function in early AD/MCI. These findings suggest that t-PBM may preferentially engage brain regions with reduced metabolic capacity to exhibit stronger acute responses. Discussion: Overall, these hypothesis-generating results support the combined use of ³¹P-MRS and fALFF as complementary biomarkers to quantify baseline metabolic status and real-time target engagement. A single session of t-PBM produced neural activity changes consistent with partial metabolic normalization in vulnerable cortical regions. As these results are preliminary, ongoing longitudinal work with a larger cohort will determine whether baseline metabolic profiles and acute fALFF responses predict clinical outcomes after repeated t-PBM treatment. Full article

Background: Paranasal sinuses and mastoid air cells have been attributed to multiple functions—such as voice resonance, cranial lightening, and pressure regulation—yet their potential role in local thermal homeostasis remains underappreciated. The thermoregulatory hypothesis, first proposed in the mid-twentieth century, was largely abandoned after the mid-century, when anthropological findings of climate-correlated variation seemed contradictory. Hypothesis: We propose that pneumatized skull regions form a three-component craniofacial biothermal system that maintains thermal stability in the ocular vitreous and vestibular endolymph, two avascular, temperature-sensitive structures that lack intrinsic thermoregulatory capacity. This represents a novel integration that explicitly links paranasal and mastoid pneumatization into a coordinated system that protects sensory organs, distinct from previous brain-cooling hypotheses. Mechanism: The system comprises: (1) passive thermal insulation via air spaces, providing ~15-fold greater thermal resistance than bone; (2) active cold protection via mucosal heat delivery (estimated 2–5 W capacity); and (3) active heat dissipation via evaporative cooling (estimated 0.3–0.5 W capacity). This architecture provides asymmetric protection, with cold buffering exceeding heat dissipation by approximately 5- to 15-fold, consistent with thermodynamic constraints and putative evolutionary priorities. Evidence: Preliminary observations consistent with this hypothesis include the anatomical proximity of pneumatized regions to the vitreous and labyrinth, intranasal selective brain cooling studies, and clinical observations after mastoidectomy showing preserved pressure buffering but reduced vestibular thermal insulation under extreme stimulation. Climate-correlated pneumatization patterns are consistent with bidirectional thermal adaptation. Implications: We present five falsifiable predictions that can be tested with thermographic imaging, pharmacological manipulation, and computational modeling. Validation could inform surgical planning, explain postoperative thermal-sensitivity symptoms, and provide evolutionary insights into craniofacial adaptation. Full article

Explainable Artificial Intelligence (XAI) has become a critical requirement for the responsible deployment of deep learning systems in safety-critical and regulated domains, particularly in medical imaging. In computer vision, gradient-based explanation methods such as Saliency Maps and Gradient-weighted Class Activation Mapping (Grad-CAM) are widely used for interpreting convolutional neural networks (CNNs). However, the increasing adoption of Vision Transformers (ViTs) introduces structural differences in internal representations that challenge the direct transfer of convolutional explainability mechanisms. This study presents a systematic, quantitative, and statistically validated evaluation of gradient-based visual explainability across CNN architectures (VGG16 and ResNet50) and a Vision Transformer (ViT-B/16), using both a domain-specific medical imaging dataset (brain MRI, tumor vs. non-tumor classification). Beyond qualitative heatmap inspection, we conduct deletion-based faithfulness analysis, sensitivity-to-noise evaluation, feature masking validation, and statistical hypothesis testing over 30 independent runs. All models achieve strong predictive performance on the domain dataset (mean accuracy ≈ 0.99), enabling a fair and meaningful comparison of explanation methods across architectures. Results demonstrate that explanation reliability is highly method- and architecture-dependent. Sensitivity differences are consistently statistically significant, whereas deletion-based faithfulness does not always yield equally strong separation under the adopted masking protocol. Masking-based analysis reveals substantial false-positive rates in certain configurations, indicating that visually plausible heatmaps do not necessarily isolate decision-necessary evidence. These findings underscore the importance of coupling visual explanations with behavioral validation metrics, particularly in high-risk domains governed by emerging regulatory frameworks such as the EU AI Act. Overall, the study advocates for empirically validated, architecture-aware, and statistically grounded approaches to medical XAI. Full article

Viral infections of the central nervous system produce memory impairment through mechanisms that extend beyond acute neuronal injury. Herpes simplex virus type 1, human immunodeficiency virus, varicella zoster virus, cytomegalovirus, Epstein–Barr virus, influenza, SARS-CoV-2, West Nile virus, and Zika virus each enter or engage the brain through distinct routes, yet converge on four shared molecular pathways that selectively damage hippocampal circuits: mitochondria-associated membrane (MAM) dysfunction, chronic neuroinflammation, blood–brain barrier (BBB) disruption, and impaired CREB-BDNF signaling. These pathways specifically compromise the dentate gyrus, CA3, and CA1 subfields, producing predictable deficits in pattern separation, associative retrieval, and temporal memory binding. Antiretroviral and antiviral therapies suppress viral replication but fail to reverse organelle-level dysfunction, leaving most hippocampal injury unaddressed. Emerging plasma biomarkers, p-tau217, neurofilament light chain, and GFAP, combined with hippocampal subfield MRI, now enable mechanistic stratification before irreversible circuit loss occurs. This review proposes, as a unifying hypothesis, that virus-associated memory impairment represents a convergent hippocampal syndrome driven by shared downstream pathways, and that combination therapies targeting these pathways simultaneously offer greater therapeutic promise than pathogen-specific approaches alone. The evidentiary basis for this framework varies across pathogens and conditions; direct mechanistic evidence, mechanistic analogy, and preclinical data are distinguished throughout. Full article

Background: Kidney transplantation (KT) improves survival and quality of life in patients with end-stage kidney disease; however, long-term allograft survival remains a major challenge. Brain natriuretic peptide (BNP), a biomarker of cardiorenal stress and volume status, may be associated with early postoperative physiological changes after KT. This study evaluated the association between early postoperative BNP changes and long-term allograft survival, and explored the potential role of BNP-derived parameters in relation to graft outcomes. Methods: This retrospective cohort study included adult recipients of deceased-donor KT between 2009 and 2018. Patients were categorized according to early graft function. Serum BNP levels were measured preoperatively and within postoperative 24 h, and the percentage increase (dBNP ratio) was calculated. Cox regression and receiver operating characteristic analyses were used to identify risk factors for graft failure and evaluate the discriminatory performance of BNP-derived biomarkers, respectively. Results: Among the 179 recipients, postoperative BNP levels and dBNP ratios differed significantly across graft function groups, with higher values in delayed graft function. After multivariate adjustment, the dBNP ratio remained significantly associated with graft failure (hazard ratio, 1.16; 95% confidence interval, 1.10–1.21; p < 0.001). Additionally, the dBNP ratio demonstrated better discriminatory performance for graft failure compared with postoperative BNP alone (area under the curve, 0.815 vs. 0.596; p < 0.001), with an exploratory cutoff of approximately 18%. Recipients with a dBNP ratio ≥ 18% had poorer early graft function, lower longitudinal estimated glomerular filtration rates, and significantly reduced graft survival. Conclusions: An increased early postoperative dBNP ratio was significantly associated with adverse long-term kidney allograft outcomes. However, given the potential for residual confounding, these findings should be interpreted as associative and hypothesis-generating rather than predictive. Full article

Alzheimer’s disease (AD) is characterized by progressive cognitive decline and the accumulation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles. Beyond genetic and proteostatic mechanisms, infection- and dysbiosis-based models of AD have gained renewed attention, including the antimicrobial protection hypothesis, in which Aβ may participate in innate immune defense. Here, we reanalyzed ribosomal depleted (Ribo-Zero) RNA-seq data from dorsolateral prefrontal cortex (DLPFC) samples from the Mount Sinai Brain Bank cohort (GSE53697) to screen for non-human transcripts. Reads underwent quality control and adapter trimming, taxonomic classification with Kraken2, abundance re-estimation with Bracken, and differential abundance testing with edgeR. Across 17 samples (9 advanced AD and 8 controls), we detected low-biomass microbial signals, with Acinetobacter radioresistens showing enrichment in the AD group (FDR = 0.018). Several additional taxa showed suggestive group differences but did not remain significant after multiple testing correction, including Lactobacillus iners (FDR = 0.051). We also performed an exploratory in silico analysis of an A. radioresistens biofilm-associated protein homolog, identifying predicted amyloidogenic motifs and surface-exposed regions that may be relevant to cross-seeding hypotheses, although no mechanistic inference can be drawn without experimental validation. Given the technical challenges of inferring microbial signals from post-mortem brain RNA-seq data, including contamination risk, low microbial biomass, and overwhelming host background, these findings should be interpreted as hypothesis-generating and warrant orthogonal validation in larger, microbiome-aware cohorts. Full article

Background/Objectives: Neurodegenerative diseases like Alzheimer’s, Parkinson’s, and Amyotrophic lateral sclerosis (ALS) share common molecular pathways, including neuroinflammation and oxidative stress, which complicate the effectiveness of single-target treatments. Garcinia mangostana L. (mangosteen) has shown neuroprotective properties, but previous studies focused on lipophilic xanthones, which have poor bioavailability and uncertain blood–brain barrier permeability. Methods: In the current study, polar metabolites from G. mangostana peel aqueous extract (GMPE) were assessed for potential multi-target interactions via UHPLC-QTOF-MS-based metabolomics, systems pharmacology, and molecular docking analysis. Further, in silico ADMET screening and network-based analyses assessed for overlap between GMPE compounds and genes associated with neurodegeneration (AD, PD, ALS). Results: Analysis of genes linked to AD, PD, and ALS revealed 121 common molecular targets influenced by GMPE metabolites. Network and enrichment analyses indicated that the compounds derived from GMPE may be involved in common pathways related to oxidative stress, neuroinflammation, and neuronal survival. Molecular docking analyses suggest that selected metabolites are likely to exhibit moderate binding affinities to their respective protein targets. Conclusions: The results presented in this study provide evidence that GMPE may possess potential multi-target interactions within common neurodegenerative pathways. However, since the data are based on computational and predictive approaches, these results should be considered hypothesis-generating and warrant further experimental validation. Full article

Background/Objectives: Fibromyalgia is increasingly viewed as a disorder of central sensitization, involving altered nociceptive processing and dysregulated stress and affective neural systems. Evidence supports shared neurobiological mechanisms linking chronic pain, emotional distress, and affect regulation, including corticolimbic and hypothalamic–pituitary–adrenal axis alterations. However, predictive models evaluating psychological distress as markers of these brain-based processes remain scarce. This study aimed to internally validate a preliminary model of fibromyalgia diagnosis using self-reported distress indicators as proxies of central dysregulation. Methods: A case-control design study with 180 participants was performed. Medically diagnosed fibromyalgia cases were recruited via a pain facility or referrals, alongside geographically matched controls from the general population. Psychological variables were conceptualized as neurobehavioral indicators reflecting central sensitization and stress-system dysregulation. Predictors were selected using LASSO penalized regression with 10-fold cross-validation. Retained variables were re-estimated using logistic regression. Model performance was evaluated through Nagelkerke’s pseudo-$R^2$, a likelihood ratio test, and area under the curve (AUC). Internal validation was conducted via 1000-bootstrap resampling with calibration-slope-based shrinkage. Results: The final model included global psychological distress, positive affect, sex, and age ($R^2=0.359$, with good discrimination [AUC = 0.81; optimism-corrected AUC ≈ 0.79]). Higher distress and age were associated with increased odds of fibromyalgia. Conclusions: Self-reported psychological distress, particularly global distress and reduced positive affect, combined with sex and age, showed internal validity in predicting fibromyalgia diagnosis. These findings support the hypothesis that behavioral markers of emotional dysregulation may reflect underlying central sensitization and stress-system alterations implicated in chronic pain. Future research integrating psychological measures with neuroimaging and neuroendocrine markers may further clarify the neural mechanisms linking affective dysregulation and chronic pain vulnerability. Full article

Background/Objectives: Severe acquired brain injury (sABI) disrupts early rehabilitation because arousal fluctuates, trunk control is fragile, and agitation limits therapy tolerance; land-based practice is frequently constrained by fall risk and staffing. We aim to reframe aquatic therapy as a programmable multisensory environment to stabilize arousal and support axial alignment before conventional impairment targets are feasible. Here, programmable denotes the deliberate titration and reporting of water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support as intervention inputs. Methods: This perspective integrates principles from neurobehavioral assessment, motor control, and immersion physiology to propose the Arousal–Alignment–Action loop as a falsifiable model and to define manipulable aquatic inputs (water depth, turbulence or perturbation, temperature, body orientation, and flotation and manual support) as dosing parameters. We outline a pragmatic testing ladder (within-session micro-experiments, feasibility studies, and embedded evaluations) and a minimal outcomes and confounder set to support cumulative evidence. Results: The framework links state regulation to alignment and goal-directed behavior, specifies predictions that can fail, and highlights boundary conditions (sedation, autonomic instability, pain, recent surgery or wounds, and cervical or cardiopulmonary constraints). A minimal outcome package spanning arousal/responsiveness, trunk control, behavioral dysregulation, participation/tolerance, and basic physiology is proposed, with optional objective adjuncts for mechanism-oriented studies. Conclusions: Treating water as a measurable and titratable medium, rather than a generic modality, may reduce early intensity bottlenecks and improve implementability and comparability of aquatic neurorehabilitation research in medically stable sABI; however, the model is intended as hypothesis-generating until supported by stronger direct clinical evidence. Full article

In the pathological cascade of cerebral ischemia, the pyroptosis axis mediated by the NLRP3 inflammasome in activated microglia is a core link driving neuroinflammation and secondary brain injury. Quercetin has been proven to possess multi-target neuroprotective activity, and its anti-inflammatory effect has attracted particular attention. However, direct molecular evidence is lacking regarding how quercetin precisely regulates the NLRP3/Caspase-1/GSDMD core pyroptosis axis in microglia in cerebral ischemia models and whether it can directly target NLRP3 to inhibit this axis, thereby alleviating cerebral ischemic injury. This study aimed to investigate the molecular mechanism by which quercetin alleviates cerebral ischemic injury through inhibiting the pyroptosis axis, combining cellular and animal models with molecular docking and molecular dynamics simulations. The oxygen-glucose deprivation (OGD) model of BV2 microglia and the photothrombotic (PT) model of focal cortical ischemia in male C57BL/6 mice were used to detect the ameliorative effect of quercetin on cerebral ischemia-related injury through cellular and animal experiments. AutoDock Vina 1.5.7 and GROMACS 2025.3 software were employed for molecular docking and molecular dynamics simulations, respectively, to analyze the binding mode and complex stability between quercetin and the NLRP3 protein. The results showed that quercetin could significantly ameliorate OGD-induced injury in BV2 cells and downregulate the expression of pyroptosis and inflammation-related proteins and factors. Meanwhile, it relieved motor dysfunction in PT mice, attenuated cortical neuronal injury, and inhibited the activation of the cerebral pyroptosis axis. At the molecular level, molecular simulation predictions indicated that quercetin might specifically bind to the NACHT domain of the NLRP3 protein, forming a complex with a stable conformation, and van der Waals interactions served as the main driving force for binding. This study confirmed that quercetin can directly bind to the NLRP3 protein and alleviate cerebral ischemia-induced inflammatory injury by inhibiting the activation of the NLRP3/Caspase-1/GSDMD pyroptosis axis and the release of downstream inflammatory factors. Combined with the molecular simulation results, a predictive hypothesis is proposed: direct binding of quercetin to the NLRP3 protein is one of its core mechanisms of action. These findings provide direct experimental evidence for the development of NLRP3-based drugs against ischemic brain injury. Full article

Background/Objectives: Acute ischemic stroke (AIS) is one of the leading causes of mortality worldwide and the primary cause of acquired neurological disability in adults. As part of a stroke magnetic resonance (MR) protocol, fluid-attenuated inversion recovery (FLAIR) plays an important role in the detection and assessment of the degree of leukoaraiosis (LA), while susceptibility-weighted angiography (SWAN) detects cerebral microbleeds (CMBs). The present study sought to examine the association of the degree of LA and CMBs with absolute cerebral blood flow (aCBF) values and functional outcome prediction in patients with AIS. Methods: We conducted a cross-sectional study including a total of 205 male and female patients. All of the patients underwent brain magnetic resonance imaging (MRI) examinations in the first 24 h following suspected AIS, using the stroke protocol. A modified Rankin scale (mRS) was used to evaluate the degree of functional dependence and disability three months after AIS. Results: The incidence of an unfavorable functional outcome evidently increased with more pronounced LA modalities (p < 0.05; χ² test). The Kruskal–Wallis test found a statistically significant difference in aCBF values in relation to a degree of LA (p < 0.05). As there were a small number of multiple CMBs, no statistically significant difference was found based on the detection and degree of CMBs with aCBF and functional outcome; hence, the hypothesis was not entirely confirmed. Conclusions: This study indicates the reliability of MRI application in the initial diagnostic evaluation in order to gain an additional insight into the prediction of AIS outcomes. We demonstrated that LA correlates significantly with an unfavorable functional outcome after AIS, with decreased perfusion values. On the other hand, a higher proportion of unfavorable functional outcomes was observed in patients with CMBs. However, this result was not statistically significant and should be interpreted with caution. Full article

Cancer therapy development increasingly focuses on multi-target approaches to inhibit key proteins involved in tumor growth and angiogenesis. This study explored the potential inhibitory interactions of 110 cannabinoid derivatives using molecular docking simulations against epidermal growth factor receptor (EGFR), vascular endothelial growth factor receptor-1 (VEGFR-1), and VEGFR-2. Blind docking with AutoDock Vina identified eight recurrent hits across all three targets, including polar THC glucuronides and more drug-like cannabinoid scaffolds. Among these, 2′-Hydroxy-Delta (9)-THC and Ajulemic Acid combined favorable multi-target binding with superior predicted pharmacokinetic properties compared with other cannabinoids and reference inhibitors (lapatinib, motesanib, and sorafenib). ADME predictions highlighted Ajulemic Acid as the most promising oral candidate, showing optimal molecular weight, high oral bioavailability, and good gastrointestinal absorption, while 2′-Hydroxy-Delta (9)-THC exhibited potential for central nervous system exposure due to predicted blood–brain barrier permeability. In contrast, glucuronidated THC metabolites and highly lipophilic cannabinol esters displayed strong docking scores but suboptimal drug-likeness, suggesting prodrug- or metabolite-like behavior rather than suitability as primary oral leads. Toxicity predictions classified all compounds as moderately toxic, with Ajulemic Acid showing a comparatively more favorable safety profile. These findings do not demonstrate biological inhibition and should be interpreted strictly as hypothesis-generating computational evidence, providing a rational framework for future in vivo and in vitro validations. Full article