Post-mortem interval (PMI) estimation is a critical task in forensic science. In this study, we used maggots collected from pig carcasses and applied an integrated proteomics and metabolomics approach to determine potential candidate substances for the estimation of PMI. After methanol precipitation, the supernatant containing metabolites and the protein pellet were separated and subjected to metabolomic and proteomic analyses using liquid chromatography-tandem mass spectrometry (LC-MS/MS). MS/MS data were analyzed for identification and quantification using Proteome Discoverer and Compound Discoverer software. A total of 573 metabolites and more than 800 porcine proteins were identified in maggots. This is the first dataset of proteins and metabolites in maggots collected from porcine carcasses. In this study, guanosine monophosphate, xanthine, inosine, adenosine, and guanine were detected with a similar tendency to increase during early days of maggot development and then decreased gradually. We broadly profiled various biomolecules through analysis in the spot of incident. Especially, we confirmed that proteome and metabolome profiling could be performed directly and indirectly.

Pacific abalone (Haliotis discus hannai) is a commercially important mollusk; therefore, improvement of its growth performance and quality has been emphasized. During embryonic development, abalones undergo a series of distinct larval stages, including swimming veliger larvae, juveniles, and mature individuals, and their biomolecular composition varies depending on the developmental stage. Therefore, in the present study, we performed untargeted lipid profiling of abalone tissues at different developmental stages as well as the hemolymph of mature female and male abalones using ultrahigh‐performance liquid chromatography‐tandem mass spectrometry. These profiles can provide meaningful information to understand compositional changes in lipids through abalone metamorphosis and development. A total of 132 lipids belonging to 15 classes were identified from abalone tissues at different developmental stages. Moreover, 21 lipids belonging to 8 classes were identified from the hemolymph of mature abalones. All data were processed following strict criteria to provide accurate information. Triglycerides and phosphatidylcholines were the major lipid components identified in both tissues and hemolymph, accounting for, respectively, 27% and 15% of all lipids in tissues and, respectively, 24% and 38% of all lipids in the hemolymph. Of note, lysophosphatidylcholine was only detected in the tissues of mature abalones, paving the way for further analyses of abalone lipids based on developmental stages. The present findings offer novel insights into the lipidome of abalone tissues and hemolymph at different developmental stages, building a foundation for improving the efficiency and quality of abalone aquaculture.

Gingivitis is a reversible, mild inflammation, whereas periodontitis is a chronic condition with irreversible tissue destruction. Despite the widespread use of clinical indicators, their lack of molecular specificity limits mechanistic diagnosis. Gingival crevicular fluid, a noninvasive medium reflecting localized immune activity, has been insufficiently explored in proteomic studies to distinguish gingivitis from periodontitis. This study revealed quantitative proteomics and network analysis to identify distinct molecular characteristics differentiating the two conditions. We analysed 72 gingival crevicular fluid samples from healthy, gingivitis, and periodontitis groups using liquid chromatography-mass spectrometry and integrated bioinformatic analysis, including differential expression analysis, weighted gene coexpression network analysis, and protein-protein interaction network analysis. Among 649 identified proteins, differential expression analysis revealed significant upregulation of proteins such as RAC2 and S100A12 in periodontitis. Weighted gene coexpression network analysis identified distinct molecular modules associated with each disease stage. Gingivitis showed enrichment of complement-related proteins, while periodontitis was characterized by neutrophil-associated protein modules, demonstrating a complement-to-neutrophil shift with disease progression. Protein-protein interaction network analysis confirmed the central roles of hub proteins such as LCN2 and RAC2, and receiver operating characteristic curve analysis supported their potential as discriminatory markers. These results demonstrate stage-specific proteomic shifts in periodontal disease progression, offering molecular insights for objective diagnosis and therapeutic targeting. The observed complement-to-neutrophil transition enables differentiation between disease stages, which current clinical markers fail to achieve. These proteomic markers provide molecular evidence of progression, potentially enhancing early intervention and guiding treatment beyond conventional clinical assessments. This proteomic profiling reveals complement-to-neutrophil transition from gingivitis to periodontitis, enabling stage-specific diagnosis since current clinical markers cannot distinguish inflammatory mechanisms. The identified protein markers are likely to provide objective molecular evidence for evaluating disease progression, potentially improving early intervention timing and treatment selection compared to traditional clinical measurements alone.

Ensuring the accuracy and reliability of liquid chromatography–mass spectrometry (LC–MS/MS)-based proteomic analysis requires robust quality control (QC) strategies. However, widely used cell line-based QC materials present challenges in reproducibility, scalability, and ethical compliance. In this study, we developed a microalgae-derived QC material based on Synechocystis sp. PCC6803 and evaluated its suitability for LC–MS/MS system performance monitoring. The Synechocystis-based QC samples demonstrated high identification reproducibility, with 76% of the protein groups being consistently detected across five replicates and maintaining a median coefficient of variation (CV) of 6.7% in quantitative precision. Furthermore, QC peptides exhibited excellent linearity (R² ≥ 0.98) and reproducibility (CV ≤ 12.06%) across varying injection amounts. These results indicate that Synechocystis-derived QC materials provide a reproducible and scalable approach that complements conventional QC workflows. They are particularly well suited for routine LC–MS/MS system performance monitoring in proteomics workflows involving non-human or mixed biological samples.