CIBBIM-Nanomedicine

Psychedelics have garnered significant interest for their therapeutic potential in mental health conditions such as depression, anxiety, and post-traumatic stress disorder. While research has primarily focused on well-studied psychedelics, phenethylamine derivatives have also gathered interest for their potential therapeutic applications. Thus, this study aims to investigate the pharmacological profile, safety and therapeutic potential of novel N-(2-fluorobenzyl) phenethylamine analogs (NBFs) of the 2C-X series-25C-NBF, 25B-NBF, and 25I-NBF. NBFs displayed high affinity and selectivity for the 5-HT2A receptor and demonstrated bias factors (defined in our study as the preference for Gq over β-arrestin pathways at 5-HT2A receptor) similar to that of 5-HT. Acute administration induced moderate head-twitch responses without affecting locomotion or pre-pulse inhibition. Our studies revealed no rewarding effects in mice nor reinforcing effects or changes in accumbal dopamine levels in rats after NBFs administration. Further characterization of 25C-NBF revealed psychoplastogenic effects (dendritogenesis, spinogenesis and increased Bdnf mRNA levels) both in vitro and in vivo. In addition, 25C-NBF reduced despair-like behavior in response to acute stress and exerted rapid antidepressant effects in a model of anhedonia-like behavior induced by chronic corticosterone administration. Taken together, these findings suggest that 25C-NBF, and further analogs, may hold potential as novel antidepressants with a rapid onset of action and a favorable safety profile in terms of no abuse potential or sensorimotor gating deficits.

Pancreatic DuctalAdenocarcinoma (PDAC) is one of the most lethalmalignancies, with limited treatment options. Altered lipid metabolism,including dysregulated eicosanoid pathways, plays a role in PDAC progressionand therapy resistance. In this study, we investigated the impactof a treatment with polymeric hydroxychloroquine (PCQ), a novel macromolecularderivative of hydroxychloroquine (HCQ), on tumor lipid metabolismin a syngeneic mouse model of PDAC. Using a validated LC-MS/MS method,we quantified 72 eicosanoids in tumors to assess the metabolic changesinduced by PCQ and HCQ treatment. Our findings revealed significantPCQ-mediated downregulation of multiple protumorigenic eicosanoids,including PGD2, PGJ2, LTE4, LTB4, and HETEs, and upregulation of antitumorresolvins. This was further confirmed by Partial Least Squares DiscriminantAnalysis (PLS-DA) and heatmap analysis. The parent compound HCQ showedminimal impact on eicosanoid concentrations in the tumors, with nosignificant alterations at 24-h and modulation of only six eicosanoidsdownregulated at 72-h post treatment. Overall, our data highlighta novel role of PCQ in modulating tumor lipid metabolism, suggestinga unique mechanism of action and its potential as an adjuvant agentin the therapy of PDAC.

Current first-line antidepressants, such as selective serotonin reuptake inhibitors (SSRI), often present a delayed onset of action and fail to effectively treat a large proportion of patients, leaving a gap in the treatment of mood disorders. Psychedelics have recently emerged as promising alternatives due to their ability to produce fast-acting antidepressant effects through neuroplastic adaptations, but their hallucinogenic properties remain a major obstacle to their widespread therapeutic use. In this study, we characterized a novel class of halogenated DMT derivatives-5-F-DMT, 5-Cl-DMT, and 5-Br-DMT-for their pharmacological activity, behavioral effects, and therapeutic potential. Using a combination of in vitro assays, in silico modeling, and in vivo behavioral and gene expression studies, we found that halogen substitution at the 5-position modulates receptor affinity and selectivity across key serotonin (5-HT) receptors (5-HT1A/2 A/2B/2CR) and transporter (SERT). Notably, 5-Br-DMT was found to activate 5-HT2AR but did not induce the head twitch response (HTR) in mice, suggesting non-hallucinogenic activity. Furthermore, 5-Br-DMT upregulated immediate early genes (IEGs) associated with neuroplasticity in the mouse prefrontal cortex and hippocampus (Arc, Egr-1, -2 and -3) and promoted dendritic growth in cortical neurons. In a mouse model of stress-induced depression, a single administration (10 mg/kg, i.p.) of 5-Br-DMT resulted in a significant reduction in depressive-like behavior, reflecting rapid antidepressant effects. Collectively, our results highlight 5-Br-DMT as a non-hallucinogenic psychoplastogen with antidepressant properties, supporting its potential as a prototypical candidate for further study. Moreover, the evaluation and biological characterization of the halogenated DMT derivatives offers valuable information on structure-activity relationships that may guide the design of future therapeutic compounds.

ObjectiveThe presence of pancreaticobiliary maljunction (PBM) in pediatric patients with congenital choledochal malformation significantly impacts clinical management and surgical decision-making. Current preoperative evaluation of PBM coexistence remains challenging in children, while intraoperative cholangiography does not consistently provide diagnostic-quality imaging. This study aims to develop machine learning-based algorithm models for detecting pancreaticobiliary maljunction (PBM) in children with congenital choledochal malformation.MethodsWe conducted a retrospective study utilizing data from patients with congenital choledochal malformation treated at our center between January 2019 and January 2024. Demographic characteristics, clinical features, and preoperative laboratory parameters were processed through rigorous data curation and feature engineering pipelines. Cases were allocated via random sampling into training (80%) and hold-out test (20%) cohorts, maintaining strict separation between training and test cohorts. Seven machine learning algorithms - Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), Adaptive Boosting (AdaBoost), Light Gradient Boosting Machine (LightGBM), and K-Nearest Neighbors (KNN) - were implemented with five-fold cross-validation. An ensemble voting classifier was specifically constructed using these models. Model performance was quantified through comprehensive metrics including area under the ROC curve (AUC), sensitivity, specificity, positive/negative predictive values, accuracy, precision, recall, and F1-score. This study employed the nonparametric bootstrap method to estimate the confidence interval for the area under the receiver operating characteristic curve (AUC). SHapley Additive exPlanations (SHAP) was employed for model interpretability, with feature importance rankings determined by absolute SHAP value magnitudes.ResultsIn a cohort of 803 pediatric patients with congenital choledochal malformation, 628 (78.2%) demonstrated concurrent pancreaticobiliary maljunction. We developed a detection model incorporating 43 clinical features, with Random Forest showing optimal performance. An ensemble voting classifier integrating seven machine learning algorithms achieved enhanced discriminative performance (AUC: 0.87 (0.81, 0.92); Recall: 0.91 (0.85, 0.95); F1-score: 0.91 (0.87, 0.94)). Key features contributing to PBM detection included: laboratory markers and clinical parameters.ConclusionBy integrating preoperative clinical symptoms and laboratory parameters, machine learning algorithms demonstrated significant detection capability in identifying PBM among pediatric congenital choledochal malformation patients, with the RF model achieving superior performance metrics among all base models. The developed ensemble voting classifier provides valuable preoperative guidance for surgical planning and clinical management, enabling detection of PBM comorbidity before surgery in congenital choledochal malformation cases.