Wasp venoms possess complex compositions and diverse bioactivities, making them potential pharmacological sources. In this study, venoms from four wasp species (Vespa mandarinia, V. velutina, V. basalis, and Provespa barthelemyi) were collected by electrical stimulation and analyzed using liquid chromatography-tandem mass spectrometry. A total of 681 peptides were identified, nearly 90% of which had not been previously reported. Comparative analyses revealed pronounced species-specific signatures at both peptide and peptide family levels. Sequence-based analyses indicated that peptide release is consistent with targeted proteolytic cleavage patterns, exhibiting features resembling known substrate preferences of metalloproteases and serine proteases, rather than stochastic degradation. Bioinformatic predictions identified 291 peptides with potential bioactive properties spanning multiple functional categories, with angiotensin-converting enzyme (ACE) and dipeptidyl peptidase IV (DPP4) inhibitory activities being the most prominently represented. Among these, eight ACE inhibitory peptides and seventeen DPP4 inhibitory peptides were prioritized as candidates based on predicted safety profiles, and sequence-based analysis further identified ten putative cryptides. Overall, this study establishes the first comparative peptidomic dataset across four wasp venoms, providing insights into peptide diversity, inferred generation patterns, and predicted activities. SIGNIFICANCE: Venoms are rich sources of biologically active molecules and have historically provided templates for clinically used therapeutics. Although major protein toxins have been extensively characterized, the endogenous low-molecular-weight peptide fraction remains comparatively underexplored, particularly in social wasps, and systematic comparative resources remain limited. Venom peptidomic datasets inherently contain multiple layers of biological information, including diversification patterns, peptide origin, and potential bioactivity, yet these aspects are often interpreted independently. By integrating these dimensions, this study establishes a multi-level analytical framework for extracting biological insights and function-related information from venom peptidomes. The identification of consistent cleavage patterns suggests a degree of regulation in peptide generation, shifting the interpretation of venom peptides from degradation by-products toward biologically organized repertoires. Moreover, candidate prioritization illustrates how peptidomic datasets can generate experimentally testable functional hypotheses rather than serving solely as descriptive catalogs. The resulting dataset serves as a reference resource for cumulative comparative analyses. The analytical framework presented here also provides a transferable strategy for functional peptide discovery in other complex secretions.

Anthropogenic stressors represent major threats to marine mammals. Yet, their combined effects on health remain poorly understood. To address this, precision-cut adipose tissue slices (PCATS) from weaned northern elephant seal (NES - Mirounga angustirostris) blubber were exposed to three treatments: (i) epinephrine (acute stress), (ii) cortisol, persistent organic pollutants (Aroclor 1254, BDE-47, BDE-99 and 4,4'-DDE) and variations of hydrostatic pressure mimicking NES diving conditions (chronic stress), and (iii) a combination of acute and chronic stressors. Compared to controls, acute, chronic and combined stressors altered the expression of 4854, 1544, and 8930 genes, respectively. Acute stress upregulated the expression of genes associated with inflammation and hypoxia and downregulated genes involved in lipid and xenobiotic metabolism. Chronic stressors activated inflammation, hypoxia and xenobiotic metabolism genes in exposed PCATS. Combined stress exerted the greatest impact on PCATS transcriptome, uniquely altering 4870 genes and regulating genes involved in lipid metabolism, inflammation and hypoxia. Epinephrine also stimulated PCATS lipolysis, while reducing leptin secretion. This study highlights how multiple stressors disrupt blubber metabolic functions, which are crucial for maintaining homeostasis during energy-demanding periods in marine mammals.

Microplastics (MPs) contaminate terrestrial, freshwater, and marine ecosystems worldwide, yet the mechanisms linking their ingestion, biological effects, and ecological redistribution by organisms remain poorly integrated across taxa and environments. Although many organisms ingest MPs, existing evidence is often fragmented by ecosystem or species group, limiting our ability to identify broader patterns. This review addresses this gap by examining fish and insects, two ecologically distinct and influential groups that collectively span all major ecosystems, to reveal cross-taxon insights in MP exposure and impacts. We synthesize current knowledge on MP sources, environmental distribution, and diversity, and compare the mechanistic pathways through which organisms are exposed to MPs and how such exposure affects physiology, behavior, development, reproduction, and gut microbiota. Despite their contrasting anatomies and life histories, fish and insects exhibit convergent responses to MPs and play key roles in their redistribution through trophic transfer, movement, and cross-ecosystem life cycles. Some species from both groups demonstrated the ability to alter or degrade polymers, likely mediated by their microbiota, with potential implications for MP fate. This cross-taxon perspective clarifies how individual-level effects scale to ecosystem processes and highlights uneven research efforts across taxa, which hinder accurate comparisons. This underscores the need for harmonized, standardized, and ecologically realistic approaches to advance global assessments of MP pollution.

The presence of per- and polyfluoroalkyl substances (PFAS) in the environment raises concerns for food safety, particularly for households producing their own food. This study investigated PFAS bioaccumulation, distribution and depuration in 27 laying chickens, reared near industrially PFAS-contaminated sites in Belgium. Twenty-two chickens were euthanized before depuration to assess PFAS concentrations across nine biological matrices, i.e., serum, breast, fat, gizzard, heart, kidney, liver, skin, and thigh. The remaining five chickens were relocated to a PFAS-free environment to study depuration by periodically collecting eggs. After a period of at least 28 days, the chickens were also euthanized, and the nine biological matrices were analyzed. Thirty-two PFAS, including short- and long-chain carboxylic (PFCA) and sulfonic (PFSA) substances, and emerging PFAS, were quantified using very sensitive validated analytical methods. Biological matrices from chickens before depuration showed PFAS concentrations up to twenty-three times higher and a broader PFAS profile than after the depuration period. Serum, liver, and kidneys were the primary accumulation sites before depuration, with fat containing similar levels before and after depuration. PFAS levels in eggs decreased progressively during the monitoring period, with PFOS dominating the PFSA profile. Both PFSA and PFCA compounds showed consistent declines, illustrating that egg production could be a significant pathway for PFAS elimination. These findings demonstrate how environmental exposure and depuration dynamics influence PFAS contamination in biological matrices. PFAS accumulation in chicken tissues and eggs can enter the human food chain through the consumption of meat and eggs, representing a potential risk to food safety.

The plastic-degrading capacity of some insects has been investigated over the past decade, with the aim of identifying gut microorganisms potentially involved in plastic degradation. However, plastic-only diets impose severe nutritional constraints, potentially driving microbial selection independently of plastic exposure. Here, we examined how nutritional stress influences gut bacterial community and the identification of plastic-associated bacteria in two plastivorous insects, Galleria mellonella and Tenebrio molitor, using polyurethane (PU) as a representative polymer. Bacterial communities were characterized by 16S rRNA gene sequencing under contrasted dietary conditions, including starvation, and complemented by a culture-dependent isolation approach using PU as the sole carbon source. In both species, gut bacterial communities under plastic-only feeding closely resembled those observed under starvation, whereas they differed from nutritionally balanced conditions. Differential abundance analyses reflected this pattern, as taxa enriched under plastic feeding were also enriched under starvation. This convergence was strong and structured in T. molitor, but weaker and more variable in G. mellonella. In addition, bacterial strains were isolated from the gut of T. molitor under both PU-amended and carbon-free conditions. Overall, our results demonstrate that nutritional stress is a driver of gut bacterial community restructuring under plastic-based diets and can bias the identification of candidate plastic-associated bacteria.

Bee venom from Apis mellifera has been traditionally used to treat inflammatory disorders, largely due to its bioactive peptide components. However, comprehensive characterization of these peptides and their interaction with transient receptor potential vanilloid 1 (TRPV1), a key receptor in nociception and inflammation, remains limited. In this study, we systematically profiled the A. mellifera venom peptidome and identified TRPV1-targeting peptides with inflammatory modulatory potential. De novo sequencing-based peptidomics generated an in-house database of 472 peptides (average local confidence, ALC ≥ 50%), including 103 high-confidence peptides (ALC ≥ 80%). Ten novel peptides were identified as candidate TRPV1-targeting peptides through pull-down screening. Among them, three peptides (P1: GNGGGGLGSGGSLGLGHE, P2: MLLAVARSVP, and P3: NQEVEEERLKY) were synthesized and tested for anti-inflammatory activity in LPS-stimulated RAW 264.7 macrophages. All three peptides significantly suppressed TNF-α secretion, with P1 achieving 62.5% inhibition at 10 μM, and modulated IL-6 and IL-1β in a dose-dependent manner. Proteomic profiling and pathway enrichment analyses indicated that these peptides exert anti-inflammatory effects through NF-κB suppression and the modulation of redox and metabolic pathways. This study provides the first evidence that A. mellifera venom contains peptides identified through TRPV1-based affinity screening, including three novel TRPV1-targeting peptides with inflammatory modulatory potential.

RATIONALE:In this work, the CCS-mass trends equation has been revisited to consider apparent changes in the ion density. METHODS:The ion mobility-derived collision cross section (IM-derived CCS) of negatively, single-charged Fe(II) and Fe (III) metal centers coordinated with three or four halide or linear alkyl carboxylate ligands generated by electrospray operating in the negative ionization mode were obtained using a T-wave mobility cell. RESULTS:The CCS-mass trends were fitted using the equation CCS = A × massPow (where A is an apparent density parameter and Pow is a shape parameter). Iron-halide complexes led to Pow parameters well below the typical limit of 0.5, which could only be explained by refining the fitting equation using a linear combination of these A and Pow parameters. Their physical meaning is described in terms of mass distribution within the volume of the iron-ligand complex ions. CONCLUSIONS:The analysis of the CCS-mass trend of iron-halide and iron-carboxylate complexes allows us to predict the IM-derived CCS and the CCS-mass trends of combinations of iron-halide/carboxylate complexes. The results show no differences in trend between planar trigonal and tetrahedral geometries as described by the valence shell electron pair repulsion (VSEPR) theory.

Based on composite food samples representative of the whole diet, prepared as consumed, total diet studies (TDSs) are amongst the most cost-effective approaches to assess population dietary exposure to chemicals residues and contaminants, and to provide representative data for health risk assessment. The third French TDS was launched in 2018. From the most recent French dietary survey, 276 foods were selected based on consumption and contamination levels, thus covering over 90% of the French diet. Stratification by season (3, 6 or 12-month-periods) and agricultural type (organic vs. conventional) led to collecting 719 composite samples. Each sample was made up of 12 pooled subsamples of the same food, representative of the food supply and habits of the French population and prepared as consumed according to the typical household practices. Food collection took place in 2021-2022 in three French departments. Substitution rules were applied when necessary to increase the likelihood of finding a product or to replace unavailable items (e.g. from supermarket, retailed shop…), that allowed collection of 98% of the expected subsamples. It is intended that the food composite samples will be analyzed for approximately 300 chemicals to update concentration levels, estimate dietary exposure, and support health risk assessment in France.

Room-temperature ionic liquids (RTILs) are a class of solvents with remarkable properties, including specific solvation properties and tuneable acidity levels. The Hammett acidity functions, commonly used to assess the acidity levels of ILs, rely on monitoring the protonation of colour indicators (especially nitroanilines) via UV-visible spectroscopy. However, this method possesses certain limitations, prompting our group to adapt it in Raman spectroscopy in a previous study. Yet the influence of the indicator concentration on the acidity functions has never been thoroughly examined. In this article, we investigated the effect of the 2,4-dichloro-6-nitroaniline concentration (from 7 to 50 mM) on the Hammett acidity functions estimated by Raman spectroscopy in 1-butyl-3-methylimidazolium bistriflimide, [BMIm]NTf2. The acidity measured with this method was higher than the acidity evaluated via UV-visible spectroscopy but lower than the acidity evaluated via Strehlow acidity functions, suggesting specific solvation effects of the nitroaniline in [BMIm]NTf2 and the formation of ion pairs in this solvent, which are discussed in this paper.

Supervised machine learning methods have shown impressive performance in interpreting mass signals and automatically segmenting spatially meaningful regions in Mass Spectrometry Imaging (MSI). Such segmentation generates maps that provide researchers with valuable insights into sample composition and serve as a foundation for downstream statistical analyses. However, these models often require data set-specific preprocessing and do not fully exploit the rich mass features available in high-resolution mass spectrometry (HRMS). Unlike low-resolution mass spectrometry, HRMS reveals additional features such as mass defects and repeated mass differences that carry important chemical information. In this work, we propose a novel deep learning architecture based on a Relational Graph Convolutional Network (R-GCN) that captures and leverages those HRMS mass features. Our model explicitly encodes structural features such as mass defects and known mass differences to represent each spectrum as a graph, enabling the learning of associations between chemically related ion families. To the best of our knowledge, no existing deep learning models for MSI classification incorporate this level of chemically informed mass structure. Most existing methods treat spectra as flat vectors or image-like inputs, thereby ignoring the underlying mass relationships. We evaluate our R-GCN approach against several conventional machine learning and deep learning baselines across diverse MSI data sets, demonstrating its robustness to common signal variations (e.g., mass shift, ion loss). Finally, we integrate Class Activation Mapping (CAM) to enhance model interpretability, enabling the identification of ion families that are relevant to specific biological or spatial regions.

Raman spectroscopy is a key technique for planetary exploration, providing mineralogical insights under strict constraints on power, mass and data transmission. This study applies principal component analysis (PCA) to Raman imaging data from the Sericho pallasite meteorite, composed mainly of Mg-rich olivine and Fe-Ni alloy. PCA efficiently reduced the complex dataset to only five principal components, retaining most of the molecular information. Using PCA scores, averaged Raman spectra were calculated to significantly simplify spectral interpretation, highlighting olivine as the dominant mineral and goethite, disordered hematite as well as disordered carbon as minor phases in the sample. In addition, PCA scores associated with the x-y coordinate of the Raman image enable identification of distinct mineralogical domains, revealing the spatial distribution of iron oxyhydroxides primarily at interfaces and fractures of the olivine inclusions. Additionally, PCA-filtered spectra enabled spatially resolved quantification of olivine composition, showing a 5%-10% magnesium enrichment in olivine cores compared to interfaces with iron oxyhydroxides, suggesting weathering origins of the Fe-Ni alloy. These results demonstrate the strong potential of PCA for data reduction, visualization and interpretation of complex Raman datasets, making it a powerful tool for in situ mineralogical analysis during future robotic or human planetary missions where fast real-time data processing is key for informed decision-making.

Per- and polyfluoroalkyl substances (PFAS) are contaminants of increasing concern, with over seven million compounds currently inventoried in the PubChem PFAS Tree. Recently, ion mobility spectrometry has been combined with liquid chromatography and high-resolution mass spectrometry (LC-IMS-HRMS) to assess PFAS. Interestingly, using negative electrospray ionization, perfluoroalkyl carboxylic acids (PFCAs) form homodimers ([2M-H]-), a phenomenon observed with trapped, traveling wave, and drift-tube IMS. In addition to the limited research on their effect on analytical performance, there is little information on the conformations these dimers can adopt. This study aimed to propose most probable conformations for PFCA dimers. Based on qualitative analysis of how collision cross section (CCS) values change with the mass-to-charge ratio (m/z) of PFCA ions, the PFCA dimers were hypothesized to likely adopt a V-shaped structure. To support this assumption, in silico geometry optimizations were performed to generate a set of conformers for each possible dimer. A CCS value was then calculated for each conformer using the trajectory method with Lennard-Jones and ion-quadrupole potentials. Among these conformers, at least one of the ten lowest-energy conformers identified for each dimer exhibited theoretical CCS values within a ±2% error margin compared to the experimental data, qualifying them as plausible structures for the dimers. Our findings revealed that the fluorinated alkyl chains in the dimers are close to each other due to a combination of C-F···O=C and C-F···F-C stabilizing interactions. These findings, together with supplementary investigations involving environmentally relevant cations, may offer valuable insights into the interactions and environmental behavior of PFAS.

Raman spectroscopy is an analytical technique of choice for Earth and planetary sciences, which was recently selected as part of robotic exploration missions on Mars. Indeed, several miniaturized Raman spectrometers have been included into the scientific payload of rovers for the remote surface exploration of Mars: SuperCam and Scanning Habitable Environments with Raman and Luminescence for Organics and Chemicals (SHERLOC) for the NASA Mars 2020 mission and the Raman laser spectrometer (RLS) for the European Space Agency's (ESA) ExoMars mission. In preparation for these missions, a number of Mars analogue biogeological samples retrieved on Earth are extensively interrogated using Raman spectrometers, including flight prototype instruments but not only. Some studies also used flight representative portable instruments, as well as benchtop instruments. Commonly, authors reported the excitation laser wavelength and its power but often omitted the laser spot size on the sample which is a key factor for comparing several studies in term of spectrometer capabilities. In this study, we reported an easy, fast and universal experimental approach for determining the effective laser spot size, defined as the diameter of the sample section which is effectively probed by the Raman spectrometer during the analyses. Here, we characterized the effective laser spot size for a benchtop micro-Raman system and two different portable spectrometers, using a standard silicon wafer and gypsum powders with various average grain sizes. The dependence of the laser spot size with the grain size of the samples is discussed with regards to qualitative and quantitative analyses of solid dispersions in the scope of remote planetary missions.

Consumption of peanut-based foods may expose consumers to heat-induced contaminants, including polycyclic aromatic hydrocarbons (PAHs), acrylamide, and furans. This study assessed consumer exposure to heat-induced contaminants in peanut-based foods prepared in Southern Benin. A food consumption survey was conducted in six municipalities of southern Benin, involving 400 adult consumers of kluiklui (fried pressed peanut cake) and/or roasted peanut snacks. Contaminant contents were determined in 27 roasted peanut snack and 42 kluiklui samples using chromatographic and mass spectrometry based-methods. Daily consumption ranged from 0.4 to 346 g for kluiklui and 0.6-284 g for roasted peanut snacks. Benzo[a]pyrene levels were below the limit of quantification in roasted peanut snack samples, while Sigma PAH4 content ranged from 1.0 to 2.8 mu g/kg. The calculated margins of exposure (MOE) for Sigma PAH4 were above 10,000, indicating a low concern of cancer risk. Acrylamide contents varied from 34.4 to 282.5 mu g/kg in kluiklui and from 20.0 to 129 mu g/kg in roasted peanut snacks. Based on median and maximum acrylamide contents, 41-72 % of kluiklui consumers, 38-78 % of roasted peanut snacks consumers, and 80-92 % of consumers of both products had MOEs below 10,000, suggesting a potential carcinogenic health risk. Furan contents ranged from 2.0 to 11.6 mu g/kg in roasted peanut snacks and from 4.0 to 62 mu g/kg in kluiklui. Furans did not raise concern for non-neoplastic effects (MOE > 100), while there was a risk for neoplastic effects, for 2 % of kluiklui consumers. Understanding the impact of specific processing practices (in particular the temperature used during the heat treatment) on contaminant formation is needed for developing risk mitigation strategies related to peanut-based food consumption.

Microplastics (MPs) are increasingly associated with physiological disruptions in aquatic organisms, yet the biological responses to environmentally sourced particles remain underexplored. This study investigated the reproductive toxicity of environmentally derived MPs collected from the Ikopa River (Antananarivo, Madagascar) in Danio rerio. Zebrafish were chronically exposed to cryomilled riverine MPs (1.2-50 mu m) at concentrations of 100 and 1000 mu g/L for 66 days, with daily reproductive assessments conducted over the final 21 days in accordance with OECD Test Guideline 229. Microplastic accumulation in gonadal tissue was assessed, along with subcellular responses via enzymatic assays in gonads and proteomic profiling in liver samples. Reproductive toxicity was evaluated through gonadal histology, fecundity, and fertility rates. MPs accumulated in gonads in a sex-and concentration dependent manner, with the highest levels in males exposed to 1000 mu g/L (177.88 +/- 102.65 particles/mg tissue, mean +/- SD, n = 4). Despite MPs accumulation, no histopathological lesions were observed. However, significant oxidative stress and energy metabolism disruptions were identified in the liver, suggesting hepatic dysfunction as a potential driver of reproductive impairments. Furthermore, six polychlorinated biphenyl (PCB) congeners ranging from dozens to hundreds of ng/g MPs, and seven polybrominated diphenyl ether (PBDE) congeners in the range of a few ng/g MPs were detected on MPs surfaces, which may exacerbate toxicity via apoptosis inhibition. These findings provide novel mechanistic insights into how environmentally relevant MPs impair reproductive function in fish. The results underscore the necessity of incorporating environmental microplastics into toxicity testing frameworks to ensure accurate ecological risk assessment.

Proteomics, essential for understanding gene and cell functions, faces challenges with peptide loss due to adsorption onto vial surfaces, especially in samples with low peptide quantities. Using HeLa tryptic digested standard solutions, we demonstrate preferential adsorption of peptides, particularly hydrophobic ones, onto polypropylene (PP) vials, leading to nonuniform signal loss. This phenomenon can alter protein quantification (e.g., Label-Free Quantification, LFQ) if no appropriate data processing is applied. Our study is based on understanding this adsorption phenomenon to establish recommendations for minimizing peptide loss. To address this issue, we evaluated the nature of surface material and buffer additives to reduce peptide-surface noncovalent binding. Here, we report that using vials made from polymer containing polar monomeric units such as poly(methyl methacrylate) (PMMA) or polyethylene terephthalate (PET) drastically reduces the hydrophobic peptide loss, increasing the global proteomics performance (4-fold increase in identified peptides for the single-cell equivalent peptide content range). Additionally, the incorporation of nonionic detergents like poly(ethylene oxide) (PEO) and n-Dodecyl-Beta-Maltoside (DDM) at optimized concentrations (0.0001% and 0.0075%, respectively) improves the overall proteomic performance and consistency, even across different vial materials. Implementing these recommendations on 0.2 ng/μL HeLa tryptic digest results in a 10-fold increase in terms of peptide signal. Application to True Single-Cell sample preparation without specialized instrumentation dramatically improves the performance, allowing for the identification of approximately 650 proteins, a stark contrast to none detected with classical protocols.

The European Chemicals Agency regulations have recently begun encouraging greener chemistry across all sectors. Armament manufacturers are very interested in moving forward by replacing propellant stabilizers with natural products, which aligns with the green chemistry principle of designing safer chemicals. This article highlights variabilities in the volatiles emitted from propellant powders during aging (from STANAG 4582 [NATO Standardization Agreement]) containing three green stabilizers: alpha-ionone, alpha-tocopherol, and hydroxyl-terminated polybutadiene. Headspace solid-phase microextraction was applied in combination with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC x GC-TOFMS) to analyze the volatile organic compound (VOC) fraction coming from the aging of propellants with three different green stabilizer additives. Principal component analysis (PCA) was used to compare the evolution of VOC profiles over time. The VOC profile from samples less than 5 years aged did not cluster closely on the PCA score plot, indicating variation in their VOC profile based on the number and amount of compounds. Samples greater than 5 years aged demonstrated stable composition with a similar number and amount of compounds present in the VOC profile. The VOC profile demonstrated a shift from fresh to degraded samples, demonstrating that this workflow could be useful to monitor aging progression in the routine quality control of stabilizers.

This study presents a methodical procedure for optimizing laser desorption/ionization mass spectrometry (LDI-MS) supports using porous silicon (PSi) substrates. The approach involves the use of substituted benzyl-pyridinium salts (thermometer ions) to obtain one metric that assesses analyte fragmentation (the effective temperature of vibration). Porous silicon substrates were synthesized via electrochemical etching of p-type silicon wafers (10-20 mΩ·cm), with etching parameters adjusted to vary porosity while maintaining a layer thickness between 700 and 1200 nm. The results revealed that PSi substrates with 40-60% porosity achieved the lowest fragmentation levels. This finding was validated through the analysis of N-acetyl glucosamine, a carbohydrate, which confirmed the effective temperature trend. Further analysis involving peptides, specifically P14R and a peptide mix (Peptide Calibration Standard II, Bruker), demonstrated that the optimized PSi substrates enabled the desorption and ionization of peptides with a maximum mass at m/z 2465, corresponding to ACTH clip 1-17. These results highlight the critical role of substrate porosity in minimizing analyte fragmentation and enhancing LDI-MS performance.