Frontiers in Pharmacology

Population pharmacokinetic (popPK) models are commonly developed using ordinary differential equations (ODEs) to describe deterministic concentration-time profiles, with unexplained variability typically attributed to interindividual variability or residual error. When model misspecification is present, system-level deviations may be absorbed into these conventional variability terms, making the source and magnitude of model inadequacy difficult to assess quantitatively. Stochastic differential equations (SDEs) provide an alternative framework by introducing an explicit system-noise component into the structural model, allowing model-data mismatch to be evaluated more directly. However, historical implementation of SDE-based models in NONMEM has been technically challenging. The availability of the Fortran plug-in subroutine SDE.f90 substantially lowers this barrier and enables more practical implementation of SDE-based models in NONMEM. In this work, SDE-based nonlinear mixed-effects models were evaluated as a quantitative diagnostic framework for probing popPK model misspecification. The SDE.f90 implementation was first verified using simulated one-compartment intravenous bolus datasets with stochastic process noise. Additional simulation-estimation scenarios were then conducted under intentionally misspecified structural or stochastic assumptions, including time-varying elimination, compartmental misspecification, and residual error misspecification. Across these scenarios, the estimated system-noise parameter was generally sensitive to misspecification, with larger values usually associated with greater structural or stochastic mismatch. SDE-based modeling also helped partially separate system-level variability from residual variability and, in selected settings, supported localization of misspecification to specific model components, thereby helping guide model refinement. Overall, SDE-based popPK modeling is a useful addition to the pharmacometric diagnostic toolbox, with system-noise estimates best interpreted together with structural model evaluation, residual diagnostics, parameter behavior, and pharmacologic plausibility.

TRPA1 is a non-selective cation channel that plays a crucial role in several pain and inflammatory conditions. Agents reducing membrane cholesterol decrease TRPA1 activation, but it remains unclear how cholesterol-lowering medications affect TRPA1 function. Given that TRPA1 is activated by a wide variety of chemicals, we explored whether statins have acute effects on this channel. We found that five commonly used statins activate human and mouse TRPA1 in a reversible and concentration-dependent manner. The effective concentrations were above the micromolar range, in the order: simvastatin {approx} lovastatin < fluvastatin < atorvastatin < pravastatin. Statin-induced activation was not correlated to changes in membrane order, nor mediated by N-terminal cysteine residues contributing to electrophilic compound agonism. Molecular docking calculations and the functional characterization of single-point mutants revealed two separate putative binding sites, one situated close to the kink of transmembrane segment 5 (TM5) and the other at the interface between TM4 and TM5. The mTRPA1 inhibitor A-967079 largely abrogated the response to the electrophilic agonist allyl isothiocyanate, but had weaker and varied effects across different statins and menthol. Mutation T877L strongly altered the effect of A-967079, also in an agonist-dependent manner, suggesting competitive binding between this antagonist and the non-electrophilic agonists. The identification of two distinct agonist binding sites may help explaining how TRPA1 is able to respond to a large variety of non-electrophilic compounds, while the finding of competitive interactions at one of these sites may help guide the development of agonist-specific antagonists of therapeutic relevance.

Background and PurposeCardiotoxicity is a major cause for drug failure throughout the drug development process, with particular concern for action potential prolongation and arrhythmia. Hence, such liabilities are heavily considered during the early phases of drug design to pre vent dangerous compounds from progressing. New approach methodologies (NAMs) that efficiently examine this risk early in the discovery pipeline should help streamline drug development programs. We developed a cardiac NAM, a 384-well open bath platform consisting of cardiac tissue derived from human induced pluripotent stem cell (hiPSC)-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. MethodsWe dramatically increased throughput without compromising physiological relevance provided by the 3D micromuscle structure. Our 384-well open bath high-throughput platform allowed evaluation of multiple compounds at a time, enabling us to study the CiPA (comprehensive in vitro proarrhythmia assay) drug panel for proarrhythmia screening. We obtained phenotypic fingerprints of all 28 compounds (9 low, 11 intermediate, and 8 high arrhythmia risk; https://cipaproject.org) in dose-escalation studies around their respective clinical concentrations. The analysis was augmented with an in silico pipeline that used phenotypic biomarkers to invert data into a mathematical model of cellular currents to infer which ion channels were affected upon drug exposure, and then trained a ML model to predict channel block. Results and ConclusionsWe found accurate detection of arrhythmic potential for most of the compounds, and the in silico model inversions were consistent with published values of compound channel block. All the high risk compounds showed action potential duration (APD) prolongation coupled with either action potential abnormalities, early afterdepolarizations (EADs), or beat cessation. For the intermediate risk group, 9 out of 11 compounds caused APD prolongation alone or in combination with EADs while 2 others showed either beat cessation or beat rate change. Augmentation of APD analysis with detailed biophysical modeling and ML tools provided meaningful insight into the mechanisms involved in APD changes. Overall, our cardiac NAM allowed for fast and relevant screening for mechanistic understanding of APD prolongation and proarrhythmic activity, at massively increased throughput compared to other 3D micromuscle models. SummaryCardiotoxicity testing is critical in drug development to prevent arrhythmogenic side effects. Current stringent regulations have greatly reduced market withdrawals; however, these strict evaluations often lead to costly late-stage failures and loss of promising candidates as false positives. We developed a cardiac new approach methodology (NAM), a 384-well open bath cardiac micromuscle platform created from hiPSC-derived cardiomyocytes, enabling high-throughput drug screening while maintaining the structural and functional complexity of 3D cardiac micromuscles. Using the comprehensive in vitro proarrhythmia assay (CiPA) drug panel, we validated the system to accurately detect proarrhythmic potential. Our assay provided phenotypic fingerprints based on mechanical and electrophysiological biomarkers. Integration with computational modeling offered insights into multi-ion channel effects (MICE). Particularly, we identified sodium channel block contributions as a significant factor for poor risk prediction based on traditional parameters. The combined experimental and computational platform can enhance early drug screening, thereby reducing late-stage failures and promoting the progression of low-risk compounds with complex electrophysiological profiles.

The development of novel therapeutics for infectious diseases remains a global health priority. To accelerate the treatment development, innovative strategies through new approach methodology (NAM) are needed to bridge speed of in vitro with predictive power of in vivo studies, while reducing mammalian experiments. The zebrafish (Danio rerio), particularly the embryo/larva, has been established as a valuable non-mammalian in vivo model in biomedical research. We developed a standardized and streamlined workflow for the zebrafish as NAM, which consisted of 3 steps: drug selection and efficacy evaluation, internal exposure assessment, and PKPD modelling. Compounds with higher tolerated doses than minimum inhibitory concentration were selected. Drug efficacy was quantified through longitudinal individual fluorescence microscopy at baseline and 24 and 48h on treatment. Drug exposure was quantified in larval homogenates and exposure medium from 0-48h on treatment. The PKPD relationship was quantified by non-linear mixed effects modelling. For case study bedaquiline, PKPD was quantified using a one-compartment model with age-depending elimination, and an Emax concentration-response relationship on the delayed logistic bacterial growth function, with an EC50 of 26.6 {micro}g/mL and an Emax of 1.07-1.37. In the case of clarithromycin, in contrast, negligible internal exposure after waterborne treatment were observed, illustrating the risk of false negatives without internal exposure assessments. Bactericidal efficacy was confirmed by intravenous drug injections, showing a clear dose dependent antimycobacterial effect. The standardized zebrafish NAM workflow presented here facilitates the translation of drug efficacy to higher vertebrates, reducing rodent studies to confirmatory or replacing them completely, thus accelerating drug development.

IntroductionImmune checkpoint inhibitors (ICIs) enhance antitumor responses by blocking inhibitory receptors, including PD-1 and CTLA-4. Overactivation can trigger systemic toxicity akin to autoimmune diseases, including kidney manifestations. We sought to 1) profile immune signaling and 2) interrogate potential mechanisms of ICI-related kidney injury in a Human Immune System (HIS) tumor-bearing mouse model treated with nivolumab and ipilimumab. MethodsImmunodeficient BRGS (BALB/c-Rag2nullIl2r{gamma}nullSirpNOD) neonates were engrafted with human CD34+ cells to generate HIS-BRGS mice. Human MDA-MB-231 tumor cells were implanted subcutaneously; once tumors reached [~]150 mm3, mice received weekly intraperitoneal vehicle (PBS) or ICI (nivolumab 20 mg/kg + ipilimumab 10 mg/kg) for 4 weeks (Veh BRGS n=4; ICI BRGS n=6; Veh HIS-BRGS n=7; ICI HIS-BRGS n=7). Kidneys were evaluated by histopathology (H&E, TEM), flow cytometry for human immune phenotypes, multiplex ELISA (80 human proteins; 10 injury biomarkers), bulk RNA sequencing, and targeted qPCR. Pearson correlations identified predictors of histopathological injury. ResultsRenal vasculitis and interstitial nephritis were observed only in ICI-treated HIS-BRGS mice. These kidneys showed a shift toward CD4+ T-cell enrichment with an increased TNF- production capacity compared to CD8+ counterparts. Toxicity was accompanied by increased renal concentrations of human cytokines, chemokines, and soluble receptors. ICI treatment significantly elevated serine proteases (Granzyme A/B) and NGF-{beta}, while decreasing IL-4. Interstitial nephritis correlated with renal PD-1 and MIF. Renal vasculitis correlated with kidney PD-1, CCL1, MIF, Granzyme A, IL-15, and BAFF. Traditional injury biomarkers (KIM-1, NGAL) remained unchanged; however, a trending decrease in EGF was observed. ConclusionsOur study suggests that shifts in human T-cell populations and specific immune proteins could serve as promising biomarkers and mechanistic targets for ICI nephrotoxicity. The tumor-bearing HIS-BRGS mouse model reproducibly recapitulates the histopathological and immunological features of human ICI-induced nephrotoxicity and represents a validated preclinical platform for testing novel therapeutic interventions to preserve kidney function during cancer immunotherapy. Translational StatementImmune checkpoint inhibitor (ICI)-associated nephrotoxicity occurs in up to 25% of treated patients, yet the immunological mechanisms driving renal injury remain poorly characterized due to the scarcity of human biopsy material and the absence of robust preclinical models that recapitulate human immune responses. This study demonstrates that tumor-bearing humanized immune system (HIS) mice treated with combined nivolumab and ipilimumab reproducibly develop renal vasculitis and interstitial nephritis mediated by a human CD4+ T cell-dominant infiltrate, mirroring the clinicopathological features reported in patients with ICI-associated acute kidney injury. By integrating histopathology, flow cytometry, multiplex proteomics, and transcriptomics, we identify a coordinated immune network, including IL-15, CCL1, MIF, GZMA, and BAFF, that correlates with the severity of renal pathology and represents tractable mechanistic targets and candidate biomarkers. These findings provide a validated preclinical platform for dissecting irAE mechanisms and testing novel therapeutic strategies to preserve kidney function during cancer immunotherapy.

ABSTRACT Background: Self medication with analgesics and non steroidal anti inflammatory drugs (NSAIDs) is common in low- and middle income countries and may expose users to preventable adverse outcomes. Evidence from Guinea remains scarce. This study aimed to estimate the prevalence of self medication with analgesics and NSAIDs among pharmacy clients in urban Conakry, identify associated factors, and describe clinical risk situations. Methods: We conducted a pharmacy based analytical cross sectional study in 30 private pharmacies across Conakry, Guinea. A total of 1,032 participants seeking analgesics or NSAIDs were enrolled between November 3, 2012, and April 5, 2013. Self-medication was defined as acquisition or use without a valid medical prescription. Factors associated with self-medication were analysed using multivariable logistic regression. Results: Among 1,032 participants, 603 reported self medication (prevalence 58.4%). Previous unsupervised use was reported by 78.7%. The most frequently used medicines were paracetamol (56.9%, n=587), diclofenac (21.3%, n=220), ibuprofen (17.9%, n=185), and aspirin (3.9%, n=40). Overall, 68.0% (n=702) reported no knowledge of potential adverse effects. Clinical risk situations were frequent: gastrointestinal disorders (41.3%, n=426), hypertension (9.2%, n=95), and pregnancy exposure among reproductive age women (26.0%). In multivariable analysis, self medication was independently associated with previous analgesic/NSAID use (aOR = 2.8, 95% CI: 2.1 to 3.6), lack of knowledge of adverse effects (aOR = 1.9, 95% CI: 1.4 to 2.5), informal occupation (aOR = 1.6, 95% CI: 1.2 to 2.2), and age 18 to 59 years (aOR = 1.5, 95% CI: 1.1 to 2.1). Conclusions: In this pharmacy based study conducted in urban Conakry, self medication with analgesics and NSAIDs was common and frequently associated with limited awareness of potential adverse effects. These findings support the need for strengthened pharmaceutical regulation, pharmacist-led counselling, health literacy interventions, and improved access to primary care. Keywords: self medication; analgesics; NSAIDs; paracetamol; diclofenac; ibuprofen; pharmacy; Guinea; Conakry; drug safety; public health.

Abstract Introduction The sharing of individual patient data is essential for advancing pharmacometrics but is strictly limited by privacy regulations (e.g., GDPR). While synthetic data generation offers a legally compliant alternative, its structural impact on complex nonlinear mixed-effects (NLME) modelling remains largely unexplored. This study aimed to benchmark five generative artificial intelligence algorithms by evaluating the balance between data privacy and the preservation of structural PK properties and clinical dosing guidance. Material & methods A daptomycin two-compartment PopPK model was used to simulate a reference cohort of 500 patients. Five generative algorithms (Modified AVATAR, Gaussian Copula, Synthpop, TVAE, and CTGAN) produced 100 independent synthetic datasets each. A two-stage evaluation framework was applied: first, a statistical indistinguishability test based on logistic regression (AUC ROC) was used as a macroscopic pre-selection criterion to determine algorithm eligibility for NLME modelling and privacy risk assessment. Privacy risk was independently quantified using the Anonymeter framework (Singling Out and Linkability attacks). Eligible algorithms were further evaluated on PK parameter recovery bias and clinical dosing simulations. Results Deep learning architectures (TVAE, CTGAN) were excluded at the pre-selection stage due to both biologically implausible covariate generation and high macroscopic detectability (mean AUC ROC = 0.837 and 0.986, respectively). Synthpop, AVATAR, and Gaussian Copula all passed the indistinguishability threshold (AUC ROC = 0.475 +- 0.033, 0.490 +- 0.013, and 0.619 +- 0.031, respectively) and proceeded to NLME evaluation. However, attack-based privacy assessment revealed that Synthpop carried an unacceptable singling-out risk (0.035), disqualifying it from privacy-preserving data sharing. AVATAR and Gaussian Copula demonstrated acceptable privacy profiles (singling-out = 0.004 and 0.001; linkability = 0.010 and 0.003, respectively). At the structural level, Gaussian Copula injected stochastic noise inflating residual error (+157.0%) and V1; (+25.9%), blunting predicted Cmax and predisposing to empirical dose escalation and risk of toxicity. AVATAR acted aSs a smoothing filter, deflating V2; (-48.3%) and underestimating CL (-12.9%). Forward clinical simulations confirmed directionally opposed prediction errors: Gaussian Copula consistently underestimated Cmax across standard and renally impaired profiles (-14.5% and -16.0%, respectively), predisposing to empirical dose escalation, whereas AVATAR- and Synthpop-derived models overestimated Cmax and Cmin in the obese infected patient (+14.7% and +8.2%, respectively), compounding the accumulation risk already present in this profile. Conclusion While no generative algorithm currently offers a perfect solution, AVATAR and Gaussian Copula represent the most viable candidates, being the only methods to satisfy both macroscopic indistinguishability and attack-based privacy criteria. These findings highlight the necessity of a structured, two-stage validation framework and suggest that, when coupled with therapeutic drug monitoring, synthetic datasets could significantly enhance multicentre collaboration while maintaining strict regulatory compliance

BackgroundThe discontinuation of Fasiglifam (TAK-875), a GPR40/FFAR1 full agonist, during Phase 3 clinical trials due to hepatotoxicity led to widespread abandonment of GPR40 as a viable therapeutic target for type 2 diabetes mellitus (T2DM). However, mechanistic evidence suggests that Fasiglifams hepatotoxicity arises from mitochondrial liability driven by high lipophilicity (aLogP = 5.31), rather than from on-target GPR40 signaling. We hypothesized that target-level failure was incorrectly inferred from compound-level safety concerns, and that superior candidates exist within publicly available databases. MethodsWe queried ChEMBL Release 36 (28 GB SQLite, 74 tables) for all compounds with documented GPR40/FFAR1 activity (UniProt: O14842). Compounds were filtered by EC50 [&le;] 10 nM in nM units with standard relation "=". Drug-likeness was assessed using Lipinskis Rule of Five (Ro5), aLogP, molecular weight (MW), hydrogen bond donors/acceptors (HBD/HBA), and polar surface area (PSA). A parallel analysis of Therapeutic Target Database (TTD v10.1.01, 4,298 targets) provided clinical context. A real-world evidence (RWE) patient stratification framework was constructed using EMR data from tens of millions of patients with >10 years of longitudinal follow-up. ResultsOf 2,637 GPR40-active compounds in ChEMBL 36, 526 (19.9%) demonstrated EC50 < 100 nM and 102 (3.9%) demonstrated EC50 < 10 nM. Eight compounds met stringent drug-likeness criteria (Ro5 violations = 0, aLogP < 5.0, EC50 [&le;] 1 nM). The lead compound (CHEMBL4859651) exhibited EC50 = 0.04 nM (8.75-fold more potent than Fasiglifam), MW = 297 Da (43% lower), and aLogP = 4.30 (19% lower), with zero Ro5 violations. Mean MW of the eight candidates was 317 {+/-} 28 Da versus 524 Da for Fasiglifam. A parallel GCK analysis identified a protein-protein interaction target (CHEMBL3885579, GCK-GKRP interface) harboring 40 exclusive compounds as an orthogonal strategy for partial GCK activation. ConclusionsSystematic cheminformatic analysis reveals that compounds with substantially superior activity and drug-likeness profiles relative to Fasiglifam exist within ChEMBL 36. Fasiglifams hepatotoxicity is attributable to compound-specific physicochemical properties, not GPR40-mediated toxicity. RWE patient stratification may further mitigate hepatotoxicity risk for next-generation GPR40 agonists. These findings argue for systematic reappraisal of GPR40 as a viable therapeutic target for T2DM.

3:(-)-trans-Cannabidiol ((-)-CBD) is a principal phytocannabinoid from Cannabis sativa. (-)-CBD has complex pharmacology but is a relatively weak inhibitor of CB1 and CB2 receptor signalling. Cannabidiol has two chiral centres and thus four stereoisomers. (+)-trans-CBD ((+)-CBD) has a higher affinity than (-)-CBD at CB1 and CB2, but its pharmacodynamic effects at these receptors are incompletely described. We examined the activity of (+)-CBD at human CB1 and CB2 receptors using a fluorescence-based assay of membrane potential in AtT20 cells stably expressing CB1 or CB2 receptors. (+)-CBD produced a rapid, concentration-dependent hyperpolarization in CB2-expressing cells (pEC50 6.63 {+/-} 0.08) with a maximal effect [~]90% of the response to CP55940. The CB2 response was blocked by pertussis toxin pretreatment and competitively inhibited by the CB2 antagonist AM630 (Schild slope 1.1 {+/-} 0.1). (+)-CBD was a low-efficacy, low-potency CB1 agonist and inhibited somatostatin-receptor effects at high concentrations (10-30 {micro}M). It had no effect on the membrane potential of AtT20 wild-type cells. In silico modelling of ligand interactions with CB2 indicated that (+)-CBD but not (-)-CBD formed an H-bond with Ser285, a residue crucial for agonist activation of CB2. Our data suggests (+)-CBD acted as a CB2 agonist via the orthosteric binding site on the receptor. Synthetic CBD, including (+)-CBD, has previously been administered in clinical trials, presumably without consideration of its potential CB2 agonist activity. Given the relative safety of (-)-CBD in people, (+)-CBD may be a useful drug to explore CB2-sensitive disease states, should it prove similarly safe.

Background and PurposeEpilepsy is a neurological condition characterized by recurring seizures and neuronal hyperexcitability. Cell-based high-throughput screening applications have been essential for drug development and discovering novel biological processes. However, cell-based screens do not provide information on how drug-targeted pathways are integrated into a whole animal. Our objective was to develop and evaluate a screening application using zebrafish larvae to identify signalling mechanisms that modulate neural activity. Experimental ApproachWe developed an in vivo automated high-content screening assay using zebrafish larvae expressing the calcium sensor CaMPARI (calcium-modulated photoactivatable ratiometric integrator) in neurons. This assay can quantify neural activity of multiple individual larvae per well in a 96-well format. We quantified neural activity in 8725 individual larvae, in response to 1292 different drugs to identify molecules that protect against convulsant-induced neuronal hyperexcitability. Key ResultsThe assay was effective at identifying drugs that target diverse neurotransmitter signalling systems. While some commonly used anti-convulsants (e.g. phenytoin, carbamazepine, valproic acid) had poor activity in the assay, Kv7 potassium channel activators were consistently effective (ICA-069673, ICA-27243, ICA-110381, retigabine, and ML213). Many compounds approved for treatment of other conditions, including amitriptyline (depression), cyclobenzaprine (muscle spasm), clomipramine (obsessive-compulsive disorder) and ganaxolone (seizures), also strongly suppressed excitability in the assay. Conclusion and ImplicationsNeuronal CaMPARI expression in zebrafish larvae is a powerful tool for plate-based compound library screening to identify drugs that suppress hyperexcitability in vivo. Bullet Point SummaryO_ST_ABSWhat is already knownC_ST_ABSO_LICaMPARI is an integrative Ca2+ sensor that can be used to identify active neurons. C_LIO_LIKv7 activators (retigabine, ML213, and ICA-069673) are effective at reducing convulsant-induced (4-AP) neuronal hyperexcitability. C_LI What this study addsO_LIAn automated in vivo high-content drug screening assay to quantify neural activity. C_LIO_LIA series of drug targets that influence convulsant-induced hyperexcitability. C_LI Clinical significanceO_LIOur new tool will help identify novel compounds and signalling mechanisms that could be pursued as therapeutic targets for diseases involving electrical hyperexcitability. C_LI

ObjectiveTo 1) determine the expression and distribution of all PDE4 isozymes (A-D) along the length of the anterior urethra, 2) culture fibroblasts and epithelial cells from healthy and strictured urethras, 3) investigate an in vitro model of anterior urethral stricture disease (aUSD), and 4) assess the therapeutic potential of phosphodiesterase-4 (PDE4) inhibitors and testosterone compared to paclitaxel. MethodsThe presence and relative abundance of PDE4 isozymes (A-D) was confirmed using immunohistochemistry on 5 male cadaveric urethras. Human urethral fibroblasts (FBs) were cultured from healthy control urethras of patients undergoing vaginoplasty (n=3) and from idiopathic bulbar urethral strictures (L2S1E2) of patients undergoing urethroplasty (n=3). Epithelial cells (ECs) were cultured from a healthy control urethra and two urethral strictures. To investigate a model of aUSD, Control FBs were stimulated with TGF{beta}1 and compared to Stricture FBs on assays of cell proliferation and expression of genes relevant to aUSD pathophysiology. To test therapeutics, Stricture FBs were treated with the PDE4 inhibitor, roflumilast, testosterone (T), or paclitaxel and compared to Control FBs on the previously mentioned assays and cell viability. ResultsPDE4- A, B, and D were detected along the length of the urethra. Expression levels did not differ between urethral regions. TGF{beta}1 altered proliferation and gene expression in a dose-dependent manner. Roflumilast and T preserved cell viability and proliferation and decreased expression of genes positively associated with auSD. ConclusionUrethral FBs and ECs can be cultured from healthy and strictured surgical specimens, enabling in vitro research. PDE4 inhibitors and T may be non-cytotoxic alternatives or additions to paclitaxel for aUSD. HighlightsO_LIPDE4 isozymes A, B, and D are expressed in adult anterior urethras C_LIO_LIPDE4 is expressed equally from proximal bulbar to meatal urethra C_LIO_LIEpithelial cells and fibroblasts can be cultured from healthy and stricture urethra C_LIO_LITGF{beta}1 may not be an optimal method to model aUSD in vitro C_LIO_LIUnlike paclitaxel, roflumilast and testosterone are not toxic to urethral cells C_LI

Background: This study aimed to evaluate real-world adverse event (AE) signals of EV to provide evidence-based guidance for its safe clinical application. Methods: Data from the FDA Adverse Event Reporting System (FAERS) database from the period of 2019 Q1-2025 Q3 were analyzed. Disproportionality analysis algorithms, including the reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and empirical Bayes geometric mean (EBGM), were utilized to mine safety signals.The time to onset (TTO) was evaluated using the Weibull distribution model. Results: Among 11,697,906 reports, 4,177 EV-treated patients experienced 14,511 AEs. The most common System Organ Classes (SOCs) were skin and subcutaneous tissue disorders (18.23%), general disorders and administration site conditions (13.17%).Multi-algorithm consensus identified 179 positive signals. Alongside known toxicities (rash, peripheral neuropathy, hyperglycemia), potential new signals emerged, including dysgeusia, atypical skin lesions, and myelosuppression. Median TTO was 14 days, with the Weibull {beta} of 0.736, confirming an "early failure" profile. Subgroup analysis revealed toxicity heterogeneity: patients aged [&ge;]65 and females exhibited stronger signals for fatal severe cutaneous adverse reactions, while patients aged < 65 and males showed higher susceptibility to neurological and metabolic toxicities. Conclusions: The real-world safety profile of EV confirms known toxicities, reveals new risks (e.g., dysgeusia), and shows toxicity concentrated in the first treatment cycle. Clinical practice requires proactive monitoring during the first two weeks using demographic-specific strategies: vigilance for fatal skin toxicity in elderly and female patients, and close follow-up of neurological and metabolic indicators in younger and male populations.

BackgroundPer- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA), are persistent organic pollutants ubiquitous in the environment. Epidemiological evidence has closely linked them to an elevated risk of prostate cancer (PCa). However, the precise molecular mechanisms by which combined PFOS/PFOA exposure promotes prostate cancer and their dynamic effects on the tumor microenvironment remain unclear. MethodsThis study constructed a multi-module analytical framework integrating network pharmacology and computational biology: (1) Through ADMET toxicity prediction, multi-database target collection (three-way Venn analysis), panoramic GO/KEGG enrichment, focused androgen receptor (AR) axis analysis, GWAS genetic association validation, protein-protein interaction (PPI) network construction, machine learning-based independent screening, and a relaxed intersection strategy, we systematically identified PFOS/PFOA-prostate cancer core targets. (2) Subsequently, a PFAS-PTS score weighted purely by Cox coefficients was employed to drive gene set variation analysis (GSVA)-based pathway enrichment, tumor microenvironment (TME) deconvolution, ordinary differential equation (ODE)-based kinetic modeling, and drug intervention prediction. ResultsTarget collection identified 100 shared PFOS/PFOA-prostate cancer targets, from which 18 core targets were determined after multi-module screening. These targets were significantly enriched in the AR signaling axis, the PI3K-AKT pathway, and cell cycle regulation. Molecular docking confirmed strong binding affinities of PFOS/PFOA with AR (-9.49/-8.56 kcal/mol), AKT1 (-7.56/-6.93 kcal/mol), and PTEN (-6.36/-6.08 kcal/mol). GSVA revealed that the G2M checkpoint and E2F target gene pathways were significantly upregulated in the high-risk group (padj < 0.001), whereas the androgen response pathway was downregulated (padj = 4.8e-4). TME deconvolution (GSE141445, NNLS) revealed a significantly increased proportion of tumor cells (PCa) (p = 2.4e-4) and markedly reduced CD8+ T cell infiltration (p = 5.7e-4) in the high-risk group, indicating immunosuppressive microenvironment remodeling. ODE-based kinetic modeling confirmed that PFAS promoted tumor cell proliferation and suppressed immune surveillance in a dose-dependent manner. Drug intervention simulation demonstrated that the combination of enzalutamide and Alpelisib achieved optimal tumor cell inhibition (33.9% predicted by the ODE model). ConclusionPFOS/PFOA promote prostate cancer progression primarily through multi-target synergy involving AR axis disruption, PI3K-AKT pathway activation, and cell cycle dysregulation, while reshaping an immunosuppressive tumor microenvironment. The integrative computational framework established in this study provides systematic computational evidence for risk assessment and therapeutic intervention in PFAS-associated prostate cancer.

Background. The intrapulmonary pharmacokinetics of antimicrobial agents used to treat nontuberculous mycobacterial (NTM) pulmonary disease remain poorly characterized, limiting the optimization of dosing regimens. This study characterized the plasma and intrapulmonary pharmacokinetics of azithromycin, ethambutol, rifampicin, clofazimine, and amikacin, as well as their penetration into pulmonary lesion sites. Methods. We prospectively enrolled patients undergoing guideline-based treatment for NTM pulmonary disease who were indicated for surgical resection at a single center in Japan. Drug concentrations were measured in the plasma and lung samples, and analyzed using a population pharmacokinetic model. The lung lesion site, cavity, or nodule/bronchiectatic were evaluated as covariates of the plasma-to-lung partition ratios. Results. Twenty-four patients were enrolled in the study. Antimicrobial agents other than rifampicin and amikacin accumulate in the lungs at concentrations > 40-fold higher than those in the plasma. Notably, the intrapulmonary half-life of ethambutol, which has not been well-characterized to date, is estimated to be approximately 2 months, indicating prolonged retention within the lungs. Evaluation of drug penetration into cavities and nodular/bronchiectatic lesions showed no clearly reduced concentration compared to that of normal lung tissue. However, in the single case where the caseum was obtained, azithromycin, ethambutol, and rifampicin levels exhibited clearly lower concentrations. Conclusions. Ethambutol shows a prolonged intrapulmonary half-life, suggesting sustained lung exposure even with intermittent dosing. The absence of clearly reduced drug penetration into lesion sites suggests that lesion phenotype alone may have limited value in guiding drug selection.

Background: Histological examination of mucosal tissue in inflammatory bowel diseases (IBD) is a sensitive tool to measure disease activity, and histological remission is emerging as a potentially important treatment target. There are several existing histopathological indices, but they often encompass caveats such as not primarily having been designed to measure the degree of inflammation, encompassing subjective components with poor intra- and interindividual reproducibility, and requiring expert pathologists who are scarce, thus resulting in extended response times. Aim: To construct a new computerized, automated index to objectively measure histological disease activity in the ileal and colonic mucosa, applicable to both Crohn's disease (CD) and ulcerative colitis (UC). Materials and methods: Ileocolonic biopsies were collected from control subjects and patients with CD or UC. A group of CD patients was sampled before and after 12 weeks of anti-TNF therapy. Another group of CD and UC patients functioned as a small validation cohort. Epithelial cells, neutrophils, macrophages, and T cells were immunohistochemically stained, followed by digitalization of the color signal and computerized delineation of the epithelial and lamina propria compartments. The various immune cell types within the epithelium and the lamina propria, respectively, were enumerated, and the numbers were compared between control subjects and patients with CD or UC. Results: The numbers of neutrophils and macrophages in the epithelium, and neutrophils in the lamina propria, showed the highest sensitivity and specificity for distinguishing control-subject tissues from CD and UC tissues. These three parameters were thus chosen to construct a new index, named QiC3 1.0, that could separate tissues from control subjects and patients with CD or UC with high precision. It performed equally well in a small validation cohort of patients. The QiC3 index correlated well with previously described histopathological indices, fecal calprotectin, and endoscopic scores in UC, but showed worse correlation with endoscopic scores in CD and symptomatic scores. When applying the new index to tissues from CD patients before and after therapy, it showed good responsiveness, demonstrating a distinct amelioration in the microscopic inflammatory status that corresponded well to improvements in histopathological scores. Conclusion: We describe a new quantitative, computerized, automated, non-subjective, and response-sensitive immunohistological index (QiC3) for measuring disease activity in ileal and colonic mucosal biopsies, suitable for both CD and UC.

Abstract: Objective This study aimed to systematically screen for potential candidate biomarkers and identify therapeutic targets associated with gouty arthritis (GA) through integrated analyses of single-cell and bulk RNA sequencing (RNA-seq) data. Methods The single-cell dataset GSE211783 and the bulk RNA-seq dataset GSE160170 were analyzed using a series of bioinformatic approaches, including cell clustering, differential expression analysis, immune cell infiltration assessment, protein-protein interaction network construction, gene set enrichment analysis, as well as drug sensitivity evaluation. To establish an animal model of GA, monosodium urate crystals were injected intra-articularly into experimental mice. Joint swelling was evaluated, and morphological changes in joint tissues were analyzed through hematoxylin-eosin staining. The presence of TREM1-positive cells was detected by immunohistochemistry and the level of TREM1 protein expression in joint tissues were assessed by Western blotting. Results We identified 102 differentially expressed genes (DEGs) and 14 signaling pathways associated with GA. The PPI network revealed 25 hub genes, of which 17 (including TREM1, TNF, PTGS2, and NLRP3) were highly expressed and 8 (including FCGR3B and CXCR6) showed low expression in the GA samples. These genes correlated significantly with the infiltration levels of macrophages. Among the hub genes, TREM1 was selected for further validation because it correlated significantly with all 14 differential pathways. In animal experiments, GA mice developed marked joint swelling and inflammatory tissue injury, along with a significant increase in TREM1-positive cells and TREM1 protein expression. Conclusion Integrative analysis of single-cell and bulk RNA-seq data identified 102 GA-related DEGs and 14 key pathways, from which 25 hub genes were screened. TREM1 is significantly upregulated in GA and may be linked to macrophage function, providing new insights into biomarker and therapeutic target discovery for GA.

Manufacturers are adopting propellants for use in pressurized metered-dose inhalers (pMDIs) that have lower global warming potentials (GWPs) than the propellants traditionally used in pMDIs. Hydrofluoroalkane (HFA)-134a has been used as the propellant in the pMDI used to deliver the fixed-dose triple combination of budesonide, glycopyrrolate and formoterol fumarate (BGF); following successful clinical evaluation, the BGF pMDI is now being transitioned to the next generation propellant hydrofluoroolefin (HFO)-1234ze(E), which has near-zero GWP. We describe formulation development efforts that led to selection of HFO-1234ze(E) over another propellant, HFA-152a, for reformulation. Propellant-specific studies evaluated active pharmaceutical ingredient (API) stability and aerodynamic particle size distribution (aPSD). Those analyses have been complemented by in silico regional lung deposition modeling conducted after the clinical evaluation of the reformulated BGF pMDI. HFO-1234ze(E) supported favorable stability and aPSD characteristics for BGF pMDI reformulation, compared with HFA-152a, and modeling predicted regional deposition consistent with therapeutic intent. Given that each pMDI is a unique combination of APIs, device, propellant, and excipients, propellant substitution requires product-specific evidence and regulatory approval, and typically takes several years. Targeted analyses, such as those described here, helped to identify the most suitable candidate propellant for successful substitution in the BGF pMDI. HighlightsO_LIFormulation development efforts that led to evaluation of a budesonide-glycopyrrolate-formoterol fumarate pressurized metered-dose inhaler (BGF pMDI) reformulated with the next generation propellant HFO-1234ze(E) in a clinical trial program are described; the suitability of another propellant, HFA-152a, was also assessed C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% relative humidity [RH]), the HFA-152a formulation approached and, in one replicate, fell below the 90% of formulation label claim threshold of evaluation, whereas the original HFA-134a product and the HFO-1234ze(E) formulation remained above that threshold C_LIO_LIOver 6 months under accelerated storage conditions (40{degrees}C/75% RH) and 18 months under long-term stability storage conditions (25{degrees}C/60% RH), the fine particle mass and fine particle fraction for all active pharmaceutical ingredients (APIs) showed that the HFO-1234ze(E) formulation tracked more closely than the HFA-152a formulation to the original HFA-134a product C_LIO_LILater in silico modeling, conducted after clinical testing, predicted a trend for greater deposition of APIs in early airway generations with HFA-152a, whereas HFO-1234ze(E) was predicted to more closely match HFA-134a, indicating a greater likelihood of achieving equivalence to the original HFA-134a product with HFO-1234ze(E) than with HFA-152a C_LIO_LIBased on these analyses and other formulation development efforts, HFO-1234ze(E) was identified as the most suitable propellant for reformulation of the BGF pMDI; for HFA-152a, analyses raised concerns about storage stability, and differences in aerosol characteristics that can impact API deposition in the lungs and, in turn, efficacy C_LI

Ronapreve, a combination of two neutralising monoclonal antibodies, casirivimab and imdevimab, was amongst the authorised treatments against SARS-CoV-2 early in the COVID-19 pandemic. Ronapreve has lost some of its efficiency with the rise of new virus variants, however, it remains a valuable tool for experimental studies to gain insights into the mechanisms and effects of anti-viral drugs. In this study we combined morphological, pharmacokinetic and molecular approaches (including multiomics) to investigate the biodistribution of Ronapreve in the K18-hACE2 murine model of SARS-CoV-2 neuroinvasion, as well as possible consequences for the brain. We also investigated the effect of the treatment on the infection status. Our results showed that after intraperitoneal injection, Ronapreve accumulates in the serum and is unable to cross the blood-brain barrier, thus not reaching the brain parenchyma; treatment has only a minimal effect on the brain transcriptome, with no significant changes in the brain lipidome or metabolome. Nonetheless, post-exposure Ronapreve treatment resulted in reduced viral loads in the lung and, in particular, the brain, with markedly reduced tissue response in the brain, as shown by the transcriptomic analysis. The results suggest a peripheral mode of action of Ronapreve to block brain infection, possibly by lowering viral replication in the nasal epithelium, reducing a subsequent spread to the brain.

Background and PurposeWhile inflammation has been generally considered to exacerbate symptoms of schizophrenia, some clinical observations suggest that acute inflammation may alleviate positive symptoms. However, animal models often use excessive inflammatory stimuli, and the effects of acute inflammation--comparable to levels observed in patients--remain unknown. Experimental ApproachTo address this, we examined whether acute inflammation induced under relatively mild, clinically relevant conditions suppresses behavioural sensitization in methamphetamine (METH)-sensitized mice, a model of psychostimulant-induced psychosis with relevance to certain aspects of positive symptoms of schizophrenia. We used a repeated METH (1 mg/kg) sensitized model to evaluate the effects of acute inflammation on behavioural sensitization. Acute inflammation was induced via two methods using either lipopolysaccharides (LPS; 1 g/kg) to mimic peripheral immune activation or restraint stress (RS; single 2-h exposure) to model the neuroinflammation induced by psychological stress. LPS doses were adjusted with reference to the magnitude of peripheral cytokine elevation reported in patients, and RS was applied in short single sessions to avoid excessive inflammation. Key ResultsBoth LPS and RS significantly suppressed behavioural sensitization, without inducing other behavioural abnormalities. This suppression was dependent on toll-like receptor-4 activation. LPS-mediated suppression involved cyclooxygenase-2, whereas RS-mediated suppression was linked to the microglia-derived tumour necrosis factor-. LPS did not alter, whereas RS significantly reduced the striatal extracellular dopamine levels. Conclusion and ImplicationsThese findings suggest that acute inflammation suppresses behavioural sensitization through distinct mechanisms depending on the inflammatory trigger, providing a framework for understanding how inflammation may influence psychosis-related processes, with potential relevance to schizophrenia.

The Na+/K+-ATPase (NKA) regulates ion balance in the kidney and influences cellular processes like proliferation and apoptosis through its signal transduction. The endogenous ligand 20-Hydroxyeicosatetraenoic acid (20-HETE) contributes to inflammation and fibrosis in chronic kidney disease (CKD) and inhibits NKA activity in renal tubules. However, the molecular mechanism of this interaction remains unclear. In this study, we used in-silico approach to investigate the potential interaction between 20-HETE and NKA. Various ligands, including known NKA ligands such as cardiotonic steroids (CTS), 20-HETE, and negative controls, were docked using rigid and Induced Fit Docking to predict the affinity of the ligands toward NKA. Binding free energy calculations with the Prime Molecular mechanics with generalized Born and surface area (Prime MM/GBSA) tools were used to confirm the involvement of key amino acids in ligand-receptor interactions. The docking analyses revealed that 20-HETE exhibited a binding affinity comparable to negative control, with some differences between rigid and induced fit docking. Binding free energy data highlighted key amino acids in the 20-HETE and NKA interaction. Interaction fingerprint and mutations such as Ala330Gly and Val329Ala significantly reduced binding free energy, while Thr804Ala showed a notable decrease, underscoring the potential importance of these amino acids in ligand stabilization. These findings provide computational evidence supporting potential direct interaction between 20-HETE and NKA and identify candidate residues for future experimental validation.