The 5-HT3 receptor is a serotonin-gated cation channel of the pentameric ligand-gated ion channel family and plays a key role in fast synaptic transmission within the central, peripheral, and enteric nervous systems. Dysregulation of this receptor has been linked to neurological, psychiatric, and gastrointestinal disorders. While competitive 5-HT3 antagonists, primarily setrons, are clinically used to alleviate gastrointestinal symptoms, there is a growing interest in developing new negative allosteric modulators (NAMs) for this receptor. Here, we applied a drug-repositioning strategy targeting the human 5-HT3A receptor. Using macroscopic current recordings, we identified a previously unrecognized NAM activity of two clinically used drugs, piperazine and its derivative hydroxyzine, on the 5-HT3A receptor. Computational analyses suggested two distinct binding sites at subunit interfaces: one in the lower extracellular domain and another in the upper transmembrane domain. Functional characterization of receptors carrying mutations at key residues within these sites (E75, E208, S248, D293) showed that some mutations abolished drug-induced inhibition, whereas others enhanced the inhibitory effect of hydroxyzine. Altogether, these results validate the proposed allosteric sites and demonstrate that both contribute to the actions of these compounds. This work uncovers a new functional connection between 5-HT3A receptors and piperazine-derived drugs, opening avenues for therapeutic repurposing.

Introduction: Medications with sedative and hypnotic properties, such as benzodiazepines, the so-called 'Z-drugs', and hydroxyzine, are used in primary care. However, data regarding their prescribing patterns, particularly in the context of seasonality, remain limited. Aim: This review aims to assess the current knowledge regarding primary care prescribing patterns for medications with potential sedative and hypnotic effects, with particular emphasis on benzodiazepines, 'Z-drugs', and hydroxyzine. Material and Methods: The systematic review was conducted following the PRISMA guidelines. The PubMed, Web of Science and Scopus databases were searched. Fourteen original English-language publications from 2015 to 2026, which focused on the primary care prescription of selected groups of medications with hypnotic properties, were included. Results: Most of the studies included concerned benzodiazepines, with inconsistent prescribing patterns. Some studies reported a decrease in the rate of their prescription, whilst others indicated an increase, particularly among older people and patients with multimorbidity. Data concerning 'Z-drugs' were less extensive and showed heterogeneous prescribing trends across countries and study periods. Overall, the findings indicate substantial international variability in hypnotic prescribing in primary care. Evidence regarding hydroxyzine prescribing was particularly limited, with only one study specifically examining its prescribing patterns in primary care. Data on the seasonal prescribing patterns for all groups of medications were limited. Conclusions: Prescription of medications with sedative and hypnotic properties remains an important part of primary healthcare practice. Yet, significant research gaps remain regarding hydroxyzine prescribing and the seasonal variation in hypnotic and sedative prescribing.

A naive Bayesian classifier (NBC) combined with principal component analysis (PCA) effectively differentiates the dose-dependent effects of certain groups of psychoactive drugs based on their impact on the amplitude-spectral characteristics of electrocorticograms (ECoG) in rats. This approach has been shown to be useful for pharmacological screening of agents with unknown or poorly understood activity. Despite previously obtained optimistic results, classification determination for some drugs was inaccurate, necessitating the search for possible ways to improve the predictive effectiveness of the proposed algorithm. One possible approach would be to use as input quantitative data not only the impact of the psychoactive drugs studied on the amplitude-spectral characteristics of ECoG but also connectivity changes, including the average coherence power of different pairs of leads. The aim of this study was to compare the accuracy of NBC in classifying the pharmacological mechanism of action of agents with well-known mechanisms (test set) using pharmaco-EEG data on changes in the amplitude-spectral characteristics of ECoG, coherence, and the combined use of two data sets. Materials and methods. Experiments were performed on Wistar rats with chronically implanted ECoG electrodes. The training set, relative to which the effects of the pharmacological agents from the test set were classified, were the matrices of effects of 12 pharmacological agents: the NMDA antagonist dizocilpine, the D2/D3 antagonists haloperidol and sulpiride, the M-anticholinergic tropicamide, the H1/5HT2A receptor blocker hydroxyzine, the acetylcholinesterase inhibitor galantamine, the alpha-2 adrenergic agonist dexmedetomidine, the alpha-2 adrenergic antagonist atipamezole, the adenosine receptor blocker caffeine and the GABA-mimetics aminophenylbutyric acid (phenibut), bromdihydrochlorophenylbenzodiazepine (phenazepam) and 5-ethyl-5-phenyl-2,4,6(1H,3H,5H)-pyrimidinetrione. The test set included various drugs with tropism for the targets of the training set drugs: dopamine receptor antagonists chlorpromazine, droperidol, tiapride and raclopride, H1-histamine blockers diphenhydramine and promethazine, 5-HT2-receptor blockers ritanserin and glemenserin, acetylcholinesterase inhibitor ipidacrine, alpha2-adrenergic receptor antagonist yohimbine, alpha2-adrenergic agonists medetomidine and xylazine, GABA-mimetics 5-ethyl-5-(1-methylbutyl)-2,4,6(1H,3H,5H)-pyrimidinetrione and chloral hydrate. The analysis of the ECoG signal included the calculation of 132 amplitude-spectral characteristics and 75 coherence indicators, which, using the PCA, led to new integrative indicators used for further classification of the NBC. Results and discussion. For each drug in the test set, the median similarity probability with a particular group from the training set was calculated, which was used to assess the classification quality. It was found that, when using the amplitude-spectral characteristics of ECoG, the proposed methodological approach allows for the identification of the ECoG effects of several groups of psychoactive drugs, including D2/D3-dopamine, M-cholinergic, H1-histamine, and 5-HT2-serotonin receptor blockers, AChE inhibitors, GABA-mimetics, and alpha-2-adrenergic receptor agonists and antagonists. This approach enabled the correct classification of 18 of 24 groups in the test set. When using changes in coherence indices as the initial data, the classification accuracy also amounted to 18 of 24 groups. When combining the two data sets, the number of correctly identified NBC groups was 20 of 24 groups. When comparing the classification during training (confusion matrix), it was found that coherence data or adding coherence data to the data based on changes in amplitude-spectral characteristics leads to a statistically significant (p < 0.01 in both cases) increase in accuracy. Conclusions. The obtained data demonstrated high accuracy in classifying the pharmacological activity of the test sample drugs using any of the three compared approaches. Despite the lack of statistically significant differences between them, classification based on the combined dataset demonstrated a higher number of "correct" similarities. This allows us to recommend the approach based on combined data of drug effects on amplitude-spectral characteristics and coherence as the most promising for further studies using pharmaco-EEG screening.

Sick sinus syndrome (SSS) presents significant challenges in psychiatric medication management because of the potential for worsening cardiac conduction and interactions with antiarrhythmic therapy. A 35-year-old woman with generalized anxiety disorder (GAD) and insomnia was treated with bupropion, hydroxyzine, melatonin, and intermittent quetiapine, alongside comorbid SSS and supraventricular tachycardia managed post-ablation with metoprolol. A review of her regimen identified several cardiac safety concerns: quetiapine's potential interference with flecainide, hydroxyzine-associated QT prolongation, and bupropion's CYP2D6 inhibition that could increase flecainide levels. Management prioritized minimizing arrhythmogenic risk by discontinuing quetiapine, restricting hydroxyzine to low doses, and continuing melatonin, supplemented by stress testing and reassessment of psychotropic options. This case highlights the importance of careful psychotropic selection in patients with SSS, favoring lower-risk agents, such as mirtazapine, which is one of the safest among several possible alternatives, while maintaining close ECG monitoring and coordinated cardiology and psychiatry collaboration to reduce drug-drug interactions and optimize safety.

Fixed drug eruptions (FDE) are drug-induced skin reactions that repeatedly occur at the same anatomical site. The skin lesions are usually clear hyperpigmented patches that may develop into blisters. The skin response involves type IV delayed hypersensitivity reactions and is caused by drug-specific memory CD8 T-cells located at the affected skin site. Levocetirizine, an H1-selective second-generation piperazine antihistamine, has a good safety profile and is used to treat the skin reactions. Its nonprescription availability leads to self-medication and unrecognised adverse drug reactions (ADR). FDE due to levocetirizine, as well as with cetirizine, is less common in the literature. This case was reported to our ADR Monitoring Center and causality was assessed as probable and preventable. This case shows that antihistamines such as levocetirizine can trigger FDE in susceptible individuals. Improving clinical awareness through robust Pharmacovigilance activities, educating patients about triggers, and discouraging self-medication are crucial for preventing recurrence.

Schizophrenia (SCZ) involves immune dysregulation and synaptic deficits, yet the molecular link between peripheral inflammation and central synaptic pathology remains unclear. We integrated blood transcriptomes from four SCZ cohorts (478 samples: 245 patients, 233 controls) and validated findings in single-cell brain data and an ELNI mouse model. After batch correction, 272 genes were differentially expressed, with S100A8 as the top upregulated immune gene. WGCNA identified a disease-associated module (blue, 133 genes, r = 0.16, p = 7 × 10[-4]) containing S100A8; its intersection with differentially expressed genes yielded 44 key genes enriched for cytoplasmic translation, mitochondrial electron transport, and innate immunity. Machine learning ranked S100A8 as the top discriminative feature, and its upregulation was robust across four independent analytic pipelines. CIBERSORTx revealed increased neutrophils and decreased regulatory T and resting NK cells in patients, with S100A8 correlating positively with neutrophils. Single-cell analysis showed that S100A8-expressing cells were specifically expanded in microglia (2.98% → 3.94%, OR = 1.34), and S100A8[+] microglia displayed an activated state with coordinated upregulation of complement (C1QA/B/C) and phagocytic genes and downregulation of homeostatic markers (P2RY12, CX3CR1). In ELNI mice exhibiting SCZ-like behaviors, S100A8/S100A9 were upregulated in hippocampus and frontal cortex, accompanied by CD68 induction and reduced synaptophysin, with S100A8 correlating positively with CD68 and negatively with synaptophysin. Molecular docking identified hydroxyzine as a candidate S100A8 ligand. These convergent findings establish S100A8 as a hub linking peripheral immune dysregulation to microglial activation and synaptic pathology in SCZ, highlighting it as a candidate biomarker and therapeutic target.

First-generation H1 antihistamines have central nervous system penetration and anticholinergic activity, with potential side effects including sedation, cognitive impairment, and anterograde amnesia. First-generation antihistamines pose risks in driving under the influence of drugs (DUID) and drug-facilitated crimes (DFC) forensic casework. A liquid chromatography-tandem mass spectrometry method was developed and validated for five first-generation H1 antihistamines: chlorpheniramine, diphenhydramine, doxylamine, hydroxyzine, and promethazine. The calibration range was 1-200 ng/mL with a 1/x linear calibration model for quantitative compounds, and the limit of detection was determined to be 0.5 ng/mL for all compounds. Bias and precision were acceptable, with minor but acceptable suppression observed at low and high concentrations. No exogenous or endogenous interferences were observed. Carryover was not detected after a 400 ng/mL sample. Processed samples were determined to be stable 24 h after initial injection when stored in the refrigerated multi-sampler. Authentic forensic specimens from DUID and DFC investigations showed a wide range of concentrations for diphenhydramine. Selected case reports are presented to demonstrate the applicability of the method. The high percentage of polysubstance cases, range of concentrations, and delayed sample collection in DFC cases underscore the importance of a sensitive and reproducible method for these first-generation antihistamines, especially in human-performance casework.

Benzene (BENZ) is classified as a Class 1 residual solvent according to ICH Q3C guidelines due to its established classification as a Group 1 human carcinogen. During the chemical production of Cetirizine Dihydrochloride (CTZ) API, Cetirizine Dihydrochloride tablet (CTZT), Levocetirizine Dihydrochloride (LCTZ) API, and Levocetirizine Dihydrochloride tablet (LCTZT), BENZ can appear as a residual process impurity with carcinogenic risk; development of a highly sensitive quantification method is a critical requirement for pharmaceutical quality control. This study focused on developing and validating a method for detecting trace-level BENZ in CTZ and LCTZ drug substance and drug product. The method demonstrated exceptional sensitivity, with a least detectable concentration of 0.04 ppm and a quantifiable concentration of 0.12 ppm, significantly lower than the ICH-mandated safety limit of 2 ppm. Linearity and accuracy studies yielded an outstanding percentage of samples spiked BEN in the drug substance and drug product of CTZ and LCTZ and found within acceptance limit, approving the method's validity in presence of the drug atmosphere. Conventional headspace GC-FID/GC-MS are established techniques for benzene analysis; the proposed HPLC method offers a simpler, cost-effective, and validated method, making it well suited for routine quality control laboratories where GC facilities may not be readily available.

The majority of chemical signals detected in public metabolomics repositories remain structurally undefined. Large language models (LLMs) are probabilistic systems whose capacity to generate outputs beyond their training data, which can cause hallucinations, makes them also potentially suited to hypothesize structures for molecules that have never been described. We aimed to build a system that could harness this LLM generative capacity combined with domain specific tools/framework to constrain hallucination and produce validated discoveries. We developed a GNPS2 agentic AI system that interprets LC-MS/MS data by integrating spectral alignment, molecular formula inference, rule-based structural enumeration, machine learning-based spectrum prediction, and translates natural language hypotheses from domain experts into dynamically generated analytical workflows. We demonstrate the annotation of unknown drug metabolites from public data guided by chemical hypotheses. The agent predicted, and we experimentally confirmed, a phosphorylated hydroxyzine, an acetaminophen-p-coumaric acid ester, and identified two new oxidative ibuprofen-carnitine conjugates from public repositories. These results demonstrate that LLM-driven agentic reasoning, when combined with domain expertise, can indeed generate experimentally testable structural hypotheses for previously uncharacterized metabolites leveraging pan repository data.

Staphylococcus (S.) pseudintermedius, as a commensal of the skin and mucosa, leads to a variety of diseases in dogs, most commonly skin and ear infections. The development of methicillin-resistant S. pseudintermedius (MRSP) is an emerging risk for animals and humans. The aim of this study was to test cetirizine and N-acetylcysteine as synergistic substances with cephalexin for treating S. pseudintermedius infections. Each of the five methicillin-sensitive S. pseudintermedius (MSSP) isolates and five MRSP isolates, and one control strain were tested. The minimal inhibitory concentration (MIC) of the substances was tested by broth microdilution assay. In a checkerboard assay, the MIC of cefalexin alone was compared to the MIC of the substances combined. The determined dose reduction index (DRI) shows the influence each substance had on the efficacy of cefalexin. Furthermore, the minimal bactericide concentration (MBC) of N-acetylcysteine (NAC) was identified, and a time kill assay was performed to determine its time-related efficacy on selected isolates. Cetirizine showed no inhibition on bacterial growth or influence on antibiotic efficacy. NAC inhibited bacterial growth at 2 mg/mL. A significant synergistic influence was shown against the MRSP (p < 0.001) and MSSP isolates (p < 0.01). The MBC of the MSSP isolates and control strain was 12.8 and 25.6 mg/mL for the MRSP isolates. The time kill assay showed that NAC is bactericidal within 120 s at the prior determined MBC concentrations. NAC showed an antibacterial effect alone and a synergistic influence on cefalexin's antibacterial properties. Thus, NAC shows promising efficacy in treating infections with S. pseudintermedius; according to the preliminary study conducted here, this effect may be independent of the resistance profile.