Search Results (7,281)

Background: Psychosocial assessment is a core component of lung transplant candidate evaluation, but total scores and broad candidate categories do not necessarily show how individual psychosocial concerns co-occur or which modifiable domains require further clinical attention. This study describes the development and internal evaluation of a clinical decision-support application that reorganizes Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT) data into structured multidomain profiles. Methods: The application was developed using a retrospective single-center dataset of 496 adult lung transplant candidates. It integrates the SIPAT total score and candidate category with seven SIPAT-derived domain indicators, domain burden scores, cohort-referenced z-scores, graphical displays, and a ranked summary of domains for clinical review. All seven indicator targets were prespecified deterministic functions of SIPAT items or domain scores obtained during the same assessment. Random forest algorithms with sigmoid calibration were used to transform these targets into percentage-scaled display values; they were not trained using independently assessed clinical outcomes. Analyses included descriptive statistics, Spearman correlations, exploratory clustering, resampling-based cluster stability assessment, threshold sensitivity analyses, and subgroup analyses by age, sex, and primary pulmonary diagnosis. Results: Upper display-band classifications were identified for depression-related concerns in 32 candidates (6.5%), anxiety-related concerns in 11 (2.2%), nicotine-related concerns in 56 (11.3%), alcohol-related concerns in 22 (4.4%), illicit drug-use concerns in 11 (2.2%), social-support deficits in 40 (8.1%), and non-adherence-related concerns in 7 (1.4%). Exploratory clustering yielded a low-burden majority group (n = 432), a nicotine-dominant group (n = 53), and a small multidomain-elevation group (n = 11). The generated percentage-scaled indicators were positively associated with their conceptually corresponding SIPAT domains (Spearman’s ρ = 0.321–0.774) and with the total SIPAT score (ρ = 0.406–0.802; all p < 0.001). Sensitivity analyses showed that the smaller clusters were less stable under bootstrap resampling. These findings demonstrate internal alignment with the source instrument but do not constitute validation against independent clinical outcomes. Conclusions: The application provides an early-stage framework for organizing and visualizing SIPAT information and identifying domains that may warrant additional clinical assessment. Its outputs should be interpreted as SIPAT-derived decision-support indicators, not as independently validated probabilities of future clinical events. Prospective studies are required to evaluate usability, clinical impact, and associations with longitudinal outcomes. Full article

Background/Objectives: Antimicrobial resistance (AMR) poses a major global health challenge, particularly in opportunistic pathogens such as Pseudomonas aeruginosa. This study aimed to identify metabolic adaptations associated with antibiotic resistance by integrating transcriptomic data from drug-resistant clinical isolates with a genome-scale metabolic model (GEM) of P. aeruginosa under four antibiotic treatments: ceftazidime (CAZ), ciprofloxacin (CIP), meropenem (MEM), and tobramycin (TOB). Methods: Transcriptomic data from 414 clinical isolates were integrated with the iPau21 genome-scale metabolic model (GEM) of P. aeruginosa. Differential gene expression analysis was performed using DESeq2, and differentially expressed genes (DEGs) were identified using a false discovery rate (FDR)-adjusted p-value < 0.05 and a fold-change threshold of ≥2 or ≤0.5. Reporter metabolites (RMs) were identified using the Reporter Metabolite algorithm with an FDR-adjusted p-value < 0.05. Pathway enrichment analysis was performed to characterize condition-specific metabolic alterations, and pathway significance was determined using the Benjamini–Hochberg procedure with an adjusted p-value < 0.05. Results: The analysis revealed predominantly antibiotic-specific transcriptional responses, with limited overlap in DEGs across treatment conditions. Reporter metabolite and pathway enrichment analyses identified distinct metabolic adaptations associated with biofilm formation, virulence, and stress response pathways. Several metabolites, including propionic acid, acetic acid, L-inositol, glutamine, glutarate, fumarate, and melatonin, were computationally prioritized candidate metabolites for future metabolite-based adjuvant strategies aimed at enhancing antibiotic efficacy. Conclusions: This systems biology approach provides a comprehensive framework for identifying metabolic vulnerabilities associated with AMR in P. aeruginosa. The identified metabolites represent candidate antibiotic adjuvant molecules generated through computational prioritization and should be regarded as hypotheses for future experimental validation rather than validated therapeutic interventions. These findings provide a foundation for future studies exploring metabolism-based strategies to improve antibiotic efficacy and combat antimicrobial resistance. Full article

Multimorbidity risk identification in elderly health consultation scenarios is challenging because chronic disease history and medication exposure may interact through complex causal pathways. Existing LLM-, RAG-, and graph-based retrieval methods often rely on semantic relevance or graph connectivity, which may be insufficient for identifying user-specific risk mechanisms. This study proposes RACPR, a generative AI-enhanced risk-aware causal path re-ranking framework for interpretable multimorbidity risk identification. RACPR ranks candidate causal paths by integrating user-entity alignment, causal coherence, risk contribution, and path length control and uses generative AI to transform selected paths into readable, path-grounded explanations. To support controlled algorithmic evaluation, we constructed a normalized benchmark of 1002 elderly multimorbidity consultation cases covering diabetes, hypertension, and chronic kidney disease. The benchmark and supporting knowledge graph were derived from publicly available biomedical and health information resources, including PubMed abstracts, guideline and review sources, DrugBank medication-safety evidence, and MedlinePlus-based terminology. Under a leakage-controlled setting, only age, diagnosed diseases, and medication exposures were used as model-accessible inputs, while abnormal indicators, support paths, and rationales were reserved for evaluation. On the test set, RACPR achieved an Accuracy of 0.659, a Precision of 0.602, a Recall of 0.938, an F1-score of 0.733, and an AUC of 0.777. Ablation analysis showed that removing the risk-aware component reduced AUC from 0.777 to 0.428. Benchmark-level explanation evaluation further showed improvements in path consistency, path hit rate, and health-oriented plausibility. These findings indicate that risk-aware causal path re-ranking improved risk ranking and explanation grounding relative to the evaluated baselines under the controlled benchmark setting. Full article

Background/Objectives: Chronic insomnia commonly induces progressive memory decline, severely compromising human daily life and work capability. At present, there are no safe long-term available agents that can concurrently relieve insomnia symptoms and rescue accompanying memory dysfunction. This study aimed to optimize the preparation of deer brain peptides (DBPP) and zinc-chelated DBPP (Zn-DBPP), and explore their protective effects and molecular mechanism against insomnia-caused memory impairment, hoping to develop novel functional candidates for related neurological disorders. Methods: Single-factor experiments combined with response surface methodology were used to optimize the synthesis process of DBPP and Zn-DBPP. A para-chlorophenylalanine-induced insomnia mouse model was established. The structural characteristics, amino acid composition, and antioxidant activity of the products were verified via multiple spectroscopic and biochemical assays. Pentobarbital sodium sleep test and Morris water maze test assessed behavioral changes. Hippocampal neuronal morphology and BDNF-TrkB pathway expression were detected by histological staining, immunofluorescence and Western blotting. Results: The optimized DBPP achieved a hydrolysis rate of 43.89%, and Zn-DBPP possessed a zinc content of 143.37 mg/g. Successful zinc chelation, rich amino acid components, and strong antioxidant capacity were confirmed in Zn-DBPP. In vivo results showed that Zn-DBPP elevated brain zinc levels, improved learning and memory deficits, and restored hippocampal neuronal damage in insomniac mice. Mechanically, Zn-DBPP alleviated memory impairment by upregulating the BDNF-TrkB signaling pathway. Conclusions: The optimized Zn-DBPP exhibits excellent neuroprotective effects against insomnia-induced memory dysfunction. This work provides a reliable theoretical basis for the application of Zn-DBPP as a promising functional food or drug candidate for intervening in insomnia and cognitive decline. Full article

Toad poison (ChanSu), a traditional animal-derived medicine, has long been used in East Asian medical systems for the treatment of inflammatory conditions and tumor-related disorders. While bufadienolides have been extensively investigated as its major bioactive constituents, the contribution of peptide components to its antitumor effects remains largely unexplored. Here, we identified protein-derived candidate antiproliferative peptides from toad poison using an integrated proteomics and bioinformatics-guided strategy. Proteomic analysis identified 135 proteins, from which 2117 peptide sequences were generated via in silico digestion with trypsin and pepsin. Subsequent multi-step screening using PeptideRanker, AntiCP, iACP, and ACPred yielded twelve candidate peptides with predicted anticancer activity. Network pharmacology analysis suggested their potential involvement in cancer-related targets and pathways. ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) evaluation was subsequently used as a complementary assessment of drug-like and safety-related properties, further prioritizing four peptides for experimental validation, while molecular docking supported their interactions with key lung cancer-associated targets. In vitro assays demonstrated that three of the four prioritized peptides (WEAWN, NSQWG, and ACGVIGICQ) exhibited initial antiproliferative activity against human lung cancer A549 cells, though these findings should be interpreted with caution given the absence of a positive control in the MTT assay. This study provides preliminary evidence suggesting that protein-derived peptide candidates from toad poison may possess antiproliferative potential, representing an early systematic exploration of its previously unexplored peptidome as a source of candidate antiproliferative peptides warranting further pharmacological investigation. The integrated strategy presented here offers an efficient approach for the discovery of bioactive peptides from animal-derived traditional medicines. Full article

Steroid sulfatase (STS) plays a crucial role in intratumoral estrogen biosynthesis and represents an attractive therapeutic target in estrogen receptor-positive breast cancer. In this study, a new series of potential STS inhibitors based on the quinone methide oxime scaffold, precisely 2-(4-hydroxyiminocyclohexa-2,5-dien-1-ylidene)-2-phenylacetonitrile framework, were designed and evaluated using an integrated in silico approach. A virtual library comprising 216 compounds (including syn/anti isomers) was screened by molecular docking against the human STS crystal structure (PDB ID: 8EG3). The binding affinities ranged from −7.077 to −9.726 kcal·mol⁻¹; however, only the best-performing compound 45-syn showed values comparable to those of the reference ligands. The top-ranked compound (45-syn) exhibited favorable interactions within the catalytic site, including polar contacts near the FGly–Ca²⁺ region and extensive hydrophobic and π–π interactions in the adjacent pocket. Structure–binding relationship analysis highlighted the importance of electron-withdrawing substituents at R¹ and aromatic moieties at R² for enhanced binding. Molecular dynamics simulations confirmed the stability of ligand–STS complexes and demonstrated reduced flexibility compared to the apo form. Additionally, in silico ADMET predictions indicated generally favorable drug-like profiles for selected candidates. Overall, the results highlight computationally prioritized scaffolds that merit further synthesis and biological evaluation as potential STS inhibitors. Full article

The restoration of mutant p53 stability is a highly sought-after strategy in targeted cancer therapy. This study presents a structure-based virtual screening and molecular dynamics approach to nominate FDA-approved drugs as candidate stabilizers of mutant p53 for downstream experimental validation. A virtual screening library of FDA-approved compounds was docked against three representative p53 mutants (7DHY, 7DHZ, and 7V97) to evaluate their binding potential. The prioritized candidates demonstrated consistent, multi-conformer binding affinities. Protein–ligand interaction profiling revealed that the candidate DB09280 possesses a highly dense interaction network, particularly against the V272M and R249S variants. Residue-level analysis of the G245S structural mutant showed that DB09280 uniquely engages His19, a crucial residue for zinc coordination, and forms stabilizing contacts with adjacent flexible loop residues, including ASN35 and PRO32. Subsequent 500 ns molecular dynamics simulations were consistent with DB09280 acting as a putative conformational clamp on the timescale sampled. The ligand-bound (holo) system exhibited substantially reduced global structural drift (RMSD) and attenuated local residue fluctuation (RMSF) within the core domain compared to the highly unstable apo state. Principal component analysis further indicated that DB09280 restricts the broad conformational sampling of the mutant into a stable, dominant basin within the sampled trajectory. Together, these computational findings nominate DB09280 as a promising candidate structural stabilizer of mutant p53 worthy of experimental follow-up. We emphasize that the in silico stabilization observed here is not equivalent to functional rescue of p53 transcriptional activity; biochemical, biophysical, and cell-based assays will be required to establish whether DB09280 restores wild-type-like DNA binding or tumor-suppressor function in mutant p53 contexts. Full article

Background: Psychosocial assessment is an important component of lung transplant evaluation. Substance-related concerns may coexist with broader psychosocial vulnerabilities, but this relationship is difficult to evaluate when substance-use indicators and psychosocial scores contain overlapping information. We aimed to characterize psychosocial risk in lung transplant candidates and examine whether alcohol-, nicotine-, and illicit drug-related concerns were associated with psychosocial burden outside the SIPAT substance-use domain. Methods: We retrospectively analyzed 491 adult lung transplant candidates admitted for their first inpatient evaluation at the University Clinical Center in Gdańsk, Poland, between December 2021 and November 2025. All patients underwent routine psychosocial consultation, including the Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT), completed using a locally developed Polish translation. To avoid conceptual and statistical overlap with substance-related indicators derived from Domain D, we calculated a non-substance psychosocial score as the sum of Domains A, B, and C. Three logistic regression models adjusted for age and sex examined associations with alcohol-, nicotine-, and illicit drug-related concerns. Holm correction was applied across the three primary tests. Results: The mean age was 57.2 years (SD = 10.7), and 40.5% of participants were women. Most candidates were classified as excellent or good (89.4%). Alcohol-, nicotine-, and illicit drug-related concerns were documented in 39.5%, 43.8%, and 13.4% of candidates, respectively. In complete-case models (N = 489), each five-point increase in the non-substance psychosocial score was associated with higher odds of alcohol-related concerns (OR = 1.26, 95% CI 1.07–1.48, p = 0.006; Holm-adjusted p = 0.017) and nicotine-related concerns (OR = 1.22, 95% CI 1.04–1.43, p = 0.014; Holm-adjusted p = 0.028). No significant association was observed for illicit drug-related concerns (OR = 0.81, 95% CI 0.62–1.02, p = 0.090). Male sex was associated with alcohol-related concerns (OR = 2.16, 95% CI 1.47–3.19, p < 0.001). Conclusions: Alcohol- and nicotine-related concerns were associated with broader psychosocial burden extending beyond the SIPAT substance-use domain. These findings suggest that substance-related concerns may coexist with difficulties in readiness, social support, or psychological functioning rather than representing isolated behavioral findings. Because this study was cross-sectional and used a non-validated local translation, the results should not be interpreted as evidence of psychometric or predictive validity. Full article

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. Current treatments, including anti-inflammatory drugs and biologics, often have limited efficacy and significant side effects, highlighting the need for novel therapeutic approaches. Phellodendrine (PHE) is a characteristic ingredient of Phellodendri chinensis, yet its effects and mechanisms on IBD remain elusive. The present study evaluated the potential of PHE for preventing dextran sulfate sodium-induced IBD in zebrafish. PHE effectively reduced inflammatory cell infiltration and modulated polarized macrophages. The qPCR results further confirmed the down-regulation of pro-inflammatory genes and up-regulation of anti-inflammatory factors. Consequently, PHE promoted the resolution of IBD inflammation. PHE also restored intestinal barrier integrity by enhancing MUC2 expression, increasing goblet cell counts, and reducing intestinal permeability of both chemical and physical barriers. In addition, PHE was associated with alterations in the gut microbiome, including a reduction in potentially pathogenic microbes and an increase in beneficial microbial populations. PHE also alleviated oxidative stress. Network pharmacology suggested the potential involvement of the IL-17 signaling pathway, the lipid and atherosclerosis pathway, and the TNF signaling pathway in the preventive effects of PHE against intestinal inflammation in the zebrafish model. In vivo gene expression analysis suggested that JUN, PTGS2, IL1B, DRD2, CALM1, and HSP90AA1 may serve as putative targets of PHE. Collectively, our results indicate that PHE demonstrates potential anti-inflammatory and barrier-protective activities in a zebrafish model of intestinal inflammation. The pharmacological mechanisms by which PHE restores intestinal barriers (microbial, chemical, physical, and immune barriers) include resolving inflammation, decreasing ROS production, and enhancing lipid accumulation in the lumen overlying the intestinal mucus barrier. This study provides novel insights into the preventive effects of PHE against intestinal inflammation in a zebrafish model, suggesting its potential as a candidate for further investigation. Full article

Cervical cancer (CC) affects women worldwide, and more than 95% of cases are caused by persistent infection with high-risk human papillomavirus (HR-HPV), such as type 16, which promotes the progression of precancerous lesions to cancer. This study aimed to identify differentially expressed proteins (DEPs) in biopsies from patients with HPV16+ low-grade squamous intraepithelial lesions (LSILs) and from patients with HPV16+ squamous cell carcinoma (SCC) compared with those from HPV-negative normal cervical tissue (NCT HPV−) controls. The samples were analyzed by high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) using a data-independent acquisition (DIA) approach. Data processing and differential protein expression analysis were performed with the DIA-NN software (Data-Independent Acquisition Neural Networks), followed by bioinformatics analyses, including Venn diagrams, pathway enrichment, functional interactome, The Cancer Genome Atlas (TCGA)-SCC data integration, and Western blot detection. In total, 1607 DEPs associated with cell adhesion and extracellular matrix proteins were identified in LSILs, whereas 1516 DEPs associated with catalytic and transport activities were identified in SCC; the proteins overexpressed in LSILs (332) were enriched in processes such as metabolism, immune response activation, and stress and cell death responses. In contrast, proteins overexpressed in SCC (205) were associated with the cell cycle, DNA damage, drug metabolism, proteasome degradation, methylation, and immune response. Interaction analyses highlighted proteins related to early proteins 1,5,6 and 7 (E1, E5, E6, and E7). In terms of the two DEPs, S100 calcium binding protein A10 (S100A10/p11) and thymidine phosphorylase (TYMP) were detected in patients with LSIL, HSIL, and SCC at the protein level, consistent with their higher transcript levels in public datasets. Given the small, exploratory cohort, these findings are hypothesis-generating, and validation in a larger, balanced, independent cohort is required. In conclusion, this study identified DEPs associated with the progression of premalignant lesions to SCC that may represent candidate biomarkers and therapeutic targets warranting further investigation. Full article

Background: The C-X-C chemokine receptor type 7 (CXCR7), also known as atypical chemokine receptor 3 (ACKR3), primarily signals through β-arrestin and plays a pivotal role in tumor progression, inflammation, and neurodegenerative diseases. CXCR7 antagonists block chemokine binding and dampen β-arrestin signaling. Accordingly, identification of such antagonists is highly desirable for therapeutic development against CXCR7 driven pathologies. Methods: Through microscale thermophoresis (MST) screening of a Food and Drug Administration (FDA)-approved drug library, entacapone was identified as a CXCR7 binder. The NanoBit complementation assay was employed to evaluate the effect of entacapone on CXCR7 mediated β-arrestin 1/2 recruitment. Molecular docking was performed to predict the binding pocket and binding sites. Results: Entacapone specifically bound to CXCR7 with a Kd value of 6.04 µM. Although entacapone did not directly activate CXCR7, it selectively inhibited CXCL12 and VUF11207 induced β-arrestin 1 recruitment with no significant effect on β-arrestin 2 recruitment. Molecular docking suggested that entacapone interacted with key residues via hydrophobic contacts, including Trp100, Phe124, Gln301, and Leu305, and formed hydrogen bonds with Ser103, Asn108, and Tyr51 in the transmembrane core, collectively suggesting a possible binding mode compatible with stabilizing the receptor in an inactive conformation. Conclusions: Entacapone, a clinically well established COMT inhibitor, is reported for the first time as a novel biased antagonist of CXCR7, providing a new candidate molecule for drug repurposing. Full article

Background/Objectives: Substance use behaviors share a complex, overlapping polygenic architecture, yet translating genome-wide association study (GWAS) findings into actionable biological mechanisms remains challenging. This study aimed to characterize the genetic architecture of five substance use traits (alcohol consumption, alcohol dependence, nicotine use, illicit drug use, and behavioral disinhibition) and identify shared and distinct gene expression signatures within the neural circuits governing addiction. Methods: We reanalyzed 7188 individuals from the Minnesota Center for Twin and Family Research (MCTFR) cohort utilizing longitudinal composite phenotypes spanning five substance-use domains and general behavioral disinhibition. Post-QC, 6874 individuals were retained for downstream analysis. Following genomic imputation and linear mixed model GWAS (GEMMA), we utilized the SNipar framework to partition polygenic risk scores (PRS) into direct and indirect genetic effects, investigating intergenerational shifts in genetic penetrance and effects of assortative mating. Finally, we integrated our summary statistics with brain tissue reference panels to perform a transcriptome-wide association study (TWAS) modeling genetically regulated gene expression within neural circuits relevant to addiction. Results: Partitioning of polygenic risk revealed that while surface-level parental DNA correlations were modest (r = 0.08), underlying latent genetic correlations approached unity (R_δ ≈ 0.99), indicating that addiction risk clustering in families is driven by intense assortive mating and concentrated biological inheritance. Multi-phenotype TWAS identified several significant gene–phenotype associations—notably ADAM32 and SLC9A3, which demonstrated pleiotropic effects across multiple substance use categories. Crucially, these significant TWAS signals were enriched in striatal structures (caudate, putamen, substantia nigra) and frontal cortical regions. Conclusions: Our findings support a model of shared genetic liability across diverse substance use behaviors, mediated by specific gene expression patterns in the mesolimbic dopamine system and frontal cortex. By integrating multi-phenotype GWAS and TWAS, this study highlights pleiotropic candidate genes and provides critical insights into the tissue-specific neurobiological pathways underlying addiction vulnerability. Full article

The leading-edge (LE) of hepatocellular carcinoma (HCC) is a critical region driving malignant progression and is closely associated with high patient mortality and marked intratumoral heterogeneity. Multi-omics integration identified elevated expression of SPARC and IGFBP7 in the LE region, which was associated with stromal remodeling-related transcriptional programs and an immune-depleted microenvironment. Cell-cell communication and pathway analyses further suggested potential links between LE-associated stromal states and pro-invasive signaling programs. Furthermore, we developed SpaPred, which demonstrated favorable performance in inferring the spatiotemporal heterogeneity of HCC at the spatial resolution. This model overcomes the limitations of existing algorithms in analyzing the composition of tissue spatial structures. Finally, integration of in silico trajectory-perturbation and pharmacogenomic drug-response analyses prioritized Oxaliplatin, Belinostat, and Temsirolimus as candidate compounds associated with LE-related transcriptional programs. These drug predictions are computational and require experimental validation. Collectively, SpaPred provides a hypothesis-generating framework for investigating spatial heterogeneity and candidate therapeutic vulnerabilities in HCC. Full article

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited effective therapies. In this study, a series of 2-(arylamino)thiazol-4(5H)-one derivatives was synthesized using an efficient microwave-assisted protocol, and evaluated for neuroprotective effects against 6-hydroxydopamine (6-OHDA)-induced oxidative stress (OS) in SH-SY5Y neuronal cells and an Aβ42-expressing Drosophila melanogaster model of AD. Among the synthesized compounds, 3n, 3i, and 3b exhibited low cytotoxicity and significant neuroprotection, as evidenced by increased cell viability, reduced reactive oxygen species (ROS) production, and preserved mitochondrial membrane potential. Notably, compound 3n demonstrated the highest activity and effectively ameliorated Aβ42-induced behavioral deficits in vivo. Molecular docking studies predicted favorable binding affinity within the acetylcholinesterase (AChE) active site, with the thiazol scaffold and aryl substituents stabilizing ligand binding through π–π stacking and hydrophobic interactions; compound 3n also formed additional hydrogen bonds enhancing its affinity. Consistent with the docking predictions, in vitro AChE inhibition studies demonstrated that compounds 3n, 3i, and 3b inhibited AChE in a concentration-dependent manner. Network pharmacology predicted seven potential core targets implicated in AD pathogenesis and related pathways, including OS, neuroinflammation, and synaptic dysfunction. Furthermore, in silico pharmacokinetic analysis indicated compliance with Lipinski’s and Veber’s rules, supporting favorable drug-like properties. While further experimental validation is essential, these findings highlight 2-(arylamino)thiazol-4(5H)-one derivatives, particularly compound 3n, as promising multifunctional candidates for further preclinical development against AD. Full article

The mechanisms underlying neurodegenerative diseases (NDDs) involve multiple pathological processes, such as abnormal protein aggregation, oxidative stress, neuroinflammation, mitochondrial dysfunction, and the disruption of neurovascular unit homeostasis. The blood–brain barrier (BBB) restricts drug exposure in the brain, posing a significant challenge for central nervous system delivery and for improving therapeutic efficacy. In recent years, carbon dots derived from natural products (CDs) have emerged as candidate materials for brain delivery and theranostic applications due to their small size, modifiable surfaces, fluorescence-tracking capability, and potential neuroprotective activity. This narrative review summarizes their sources, physicochemical characteristics, biological basis, interactions with the BBB, delivery strategies, neuroprotective effects, and imaging applications. Current evidence suggests that these CDs can alleviate oxidative stress and inflammatory responses, influence abnormal protein aggregation, and support drug delivery and fluorescence tracking in certain cellular and animal models. However, BBB permeability, brain fluorescence signals, brain parenchymal exposure, and therapeutic efficacy represent distinct levels of evidence and should not be considered interchangeable. Future studies should focus on strengthening material standardization, ensuring batch-to-batch consistency, characterizing absorption, distribution, metabolism, and excretion (ADME), conducting long-term safety assessments, and validating using humanized BBB models. Full article