Vaccination is currently the most effective strategy for the mitigation of the COVID-19 pandemic. mRNA vaccines trigger the immune system to produce neutralizing antibodies (NAbs) against SARS-CoV-2 spike proteins. However, the underlying molecular processes affecting immune response after vaccination remain poorly understood, while there is significant heterogeneity in the immune response among individuals. Metabolomics have often been used to provide a deeper understanding of immune cell responses, but in the context of COVID-19 vaccination such data are scarce. Mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR)-based metabolomics were used to provide insights based on the baseline metabolic profile and metabolic alterations induced after mRNA vaccination in paired blood plasma samples collected and analysed before the first and second vaccination and at 3 months post first dose. Based on the level of NAbs just before the second dose, two groups, “low” and “high” responders, were defined. Distinct plasma metabolic profiles were observed in relation to the level of immune response, highlighting the role of amino acid metabolism and the lipid profile as predictive markers of response to vaccination. Furthermore, levels of plasma ceramides along with certain amino acids could emerge as predictive biomarkers of response and severity of inflammation.

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the most common cause of dementia in the elderly. Among the diverse pathological features of AD, amyloid beta (Aβ) aggregation and neuroinflammation are recognized as central and interlinked mechanisms driving disease progression. This review focuses specifically on these two processes and highlights current pharmacological limitations in modifying disease pathology. Natural products such as curcumin, resveratrol, Ginkgo biloba, epigallocatechin gallate (EGCG), crocin, ashwagandha, and cannabidiol (CBD) have shown promising activity in modulating Aβ aggregation and neuroinflammatory pathways, offering multi-target neuroprotective effects in preclinical studies. However, their therapeutic application remains hindered by poor solubility, instability, rapid metabolism, and limited blood–brain barrier (BBB) permeability. To overcome these barriers, nanotechnology-based drug delivery systems—including polymeric nanoparticles, niosomes, solid lipid nanoparticles, and chitosan-based carriers—have emerged as effective strategies to enhance brain targeting, bioavailability, and pharmacological efficacy. We summarize the mechanistic insights and nanomedicine approaches related to these bioactives and discuss their potential in developing future disease-modifying therapies. By focusing on Aβ aggregation and neuroinflammation, this review provides a targeted perspective on the evolving role of natural compounds and nanocarriers in AD treatment.

The use of e-cigarettes (ECs) has become increasingly popular worldwide, even though scientific results have not established their safety. Diacetyl (DA) and acetylpropionyl (AP), which can be present in ECs, are linked with lung diseases. Ethyl maltol (EM)—the most commonly used flavoring agent—can be present in toxic concentrations. Until now, there is no methodology for the determination of nicotine, propylene glycol (PG), vegetable glycerin (VG), EM, DA, and acetylpropionyl in e-liquids that can be used as a quality control procedure. Herein, gas chromatography coupled with mass spectrometry (GC-MS) was applied for the development of analytical methodologies for these substances. Two GC-MS methodologies were developed and fully validated, fulfilling the standards for the integration in a routine quality control procedure by manufacturers. As proof of applicability, the methodology was applied for the analysis of several e-liquids. Differences were observed between the labeled and the experimental levels of PG, VG, and nicotine. Three samples contained EM at higher concentrations compared to the other samples, while only one contained DA. These validated methodologies can be used for the quality control analysis of EC liquid samples regarding nicotine, PG, and VG amounts, as well as for the measurement of the EM.

Oleuropein (OE) is a secoiridoid glycoside occurring mostly in the Oleaceae family and presenting several pharmacological properties, including hypolipidemic and antioxidant properties. Based on these, several dietary supplements containing olive leaf extracts enriched with OE are commercially available in many countries. The current study aimed to examine the effect of supplementation with such an extract on the serum and urine metabolome of young healthy male athletes. For this purpose, applying a randomized, balanced, double-blind study, nine young, healthy males (physical education students) received either a commercially prepared extract or placebo for one week, followed by a two-week washout period; then, they were subsequently dosed with the alternate scheme (crossover design). Urine and serum samples were analyzed using UHPLC-HRMS, followed by evaluation with several multivariate methods of data analysis. The data were interpreted using a multilevel metabolomic approach (multilevel-sPLSDA) as it was found to be the most efficient approach for the study design. Metabolic pathway analysis of the most affected metabolites revealed that tryptophan and acylcarnitine’s biochemistries were most influenced. Furthermore, several metabolites connected to indole metabolism were detected, which may indicate enhanced serotonin turnover. Phenylethylamine and related metabolites, as well as estrone, were connected to enhanced performance. In addition, possible changes to the lipidemic profile and the blood and urine redox statuses were investigated.

Colistimethate (CMS), the prodrug of polymyxin E (colistin), is an antibiotic widely used as a last-line therapy against multidrug resistant Gram-negative bacteria, but little is known about its pharmacokinetics as its administration has stopped as a result of high neuro- and nephro-toxicity. The measurement of CMS levels in patients’ biological fluids is of great importance in order to find the optimal dose regimen reducing the drug toxicity. Until now, CMS assay methods are based on the indirect determination after its hydrolysis to colistin (CS). Herein, the aim is to find the optimal conditions for the complete hydrolysis of CMS to CS. The reaction was studied at accelerated conditions: 40 °C, 50 °C, and 60 °C, and the results were evaluated by assessing the Arrhenius equation and computation employing the Tenua software. A validated analytical methodology based on ultra-performance liquid chromatography (UPLC) coupled to a hybrid quadrupole time of flight (QToF) instrument is developed for the simultaneous measurement of CMS and CS. The current methodology resulted in complete hydrolysis, in contrast with the previously reported one.

Colistimethate sodium (CMS) is widely administrated for the treatment of life-threatening infections caused by multidrug-resistant Gram-negative bacteria. Until now, the quality control of CMS formulations has been based on microbiological assays. Herein, an ultra-high-performance liquid chromatography coupled to ultraviolet detector methodology was developed for the quantitation of CMS in injectable formulations. The design of experiments was performed for the optimization of the chromatographic parameters. The chromatographic separation was achieved using a Waters Acquity BEH C₈ column employing gradient elution with a mobile phase consisting of (A) 0.001 M aq. ammonium formate and (B) methanol/acetonitrile 79/21 (v/v). CMS compounds were detected at 214 nm. In all, 23 univariate linear-regression models were constructed to measure CMS compounds separately, and one partial least-square regression (PLSr) model constructed to assess the total CMS amount in formulations. The method was validated over the range 100–220 μg mL⁻¹. The developed methodology was employed to analyze several batches of CMS injectable formulations that were also compared against a reference batch employing a Principal Component Analysis, similarity and distance measures, heatmaps and the structural similarity index. The methodology was based on freely available software in order to be readily available for the pharmaceutical industry.