Sarcophaga peregrina (Robineau-Desvoidy, 1830) is a species of medical and forensic importance. In order to investigate the molecular mechanism during postembryonic development and identify specific genes that may serve as potential targets, transcriptome analysis was used to investigate its gene expression dynamics from the larval to pupal stages, based on our previous de novo-assembled genome of S. peregrina. Totals of 2457, 3656, 3764, and 2554 differentially expressed genes were identified. The specific genes encoding the structural constituent of cuticle were significantly differentially expressed, suggesting that degradation and synthesis of cuticle-related proteins might actively occur during metamorphosis. Molting (20-hydroxyecdysone, 20E) and juvenile (JH) hormone pathways were significantly enriched, and gene expression levels changed in a dynamic pattern during the developmental stages. In addition, the genes in the oxidative phosphorylation pathway were significantly expressed at a high level during the larval stage, and down-regulated from the wandering to pupal stages. Weighted gene co-expression correlation network analysis (WGCNA) further demonstrated the potential regulation mechanism of tyrosine metabolism in the process of puparium tanning. Moreover, 10 consistently up-regulated genes were further validated by qRT-PCR. The utility of the models was then examined in a blind study, indicating the ability to predict larval development. The developmental, stage-specific gene profiles suggest novel molecular markers for age prediction of forensically important flies.

Forensic entomology offers unique advantages for the minimum postmortem interval (PMImin) estimation of decomposed corpses in forensic investigations. Accurate species identification and up-to-date locality information are essential. Hainan Island has a tropical rainforest climate and a vast territory. In this study, the community structure of necrophagous flies on Hainan Island was investigated in detail according to geographical environment. The results showed that the dominant species included C. megacephala, S. peregrina, C. rufifacies, S. misera, H. ligurriens, S. sericea, S. cinerea, S. dux, C. pinguis, and M. domestica. Furthermore, C. rufifacies and C. villeneuvi were found only in the high-altitude areas of Wuzhi Mountain, while S. cinerea was distributed only in coastal areas; the latter is a representative species of Hainan Island and has not been reported before. Furthermore, a GenBank database of forensically important flies was established, whilst a high-resolution melt (HRM) curve analysis was applied to identify the common species of Hainan Island for the first time. This study enriches the database of forensically important flies in tropical rainforest regions.

Accurate postmortem interval estimation is an important issue in forensic investigations. Entomological evidence is widely used to estimate the minimum postmortem interval (PMI_min), primarily based on insect development and succession on decomposing remains. However, once adult emergence has occurred and only empty puparia remain, the applicability of conventional development-based methods becomes limited. Empty puparia, which can persist at crime scenes for extended periods, may provide time-related information based on their weathering after adult emergence. Nevertheless, for Aldrichina grahami (Aldrich, 1930) (Diptera: Calliphoridae), a forensically important necrophagous species, systematic models for empty puparia weathering remain limited. In this study, a 13-month indoor exposure experiment was conducted to characterize weathering-associated changes in empty puparia of A. grahami using metabolomic and bacterial community analyses. The results showed that lipid metabolites, particularly long-chain fatty acids such as stearic and palmitic acids, decreased consistently with weathering time. In contrast, bacterial communities showed variation over time but exhibited weaker associations with weathering time. In internal cross-validation, the metabolomics model showed lower prediction error than the bacterial community model, while decision-level integration yielded the lowest error within this dataset. These results suggest that empty puparia undergo measurable molecular changes during indoor weathering, which may assist in estimating the post-eclosion interval (PEI) and thereby provide supplementary information for PMI_min assessment in long-interval cases.

Hyperspectral imaging (HSI) has potential for forensic entomology, but its practical use is limited by manual region-of-interest (ROI) delineation before spectral extraction. This step is time-consuming, operator-dependent, and difficult to standardize across insect species and developmental stages. Here, we developed an automated individual-level ROI-to-spectrum workflow for HSI analysis of forensically important insects. The dataset included 63 hyperspectral images and 1868 manually annotated insect individuals, covering larvae, pupae, and adults. The proposed Hyperspectral Imaging Fully Convolutional Network (HSI-FCN) segmented insect body regions from three-band pseudo-RGB images, back-projected the predicted masks to the original HSI data cubes, generated individual-level ROIs, and extracted full-band mean spectra. On an independent test set containing 204 insect individuals, HSI-FCN achieved mean Dice and intersection over union (IoU) values of 0.9079 and 0.8328, respectively, and showed the best overall performance among representative segmentation models. All test individuals were successfully matched with their corresponding manual ROIs. Spectra extracted from automated ROIs were highly consistent with manual ROI spectra, with a mean spectral angle mapper of 3.06° and a Pearson correlation coefficient of 0.9956. These results show that the proposed workflow can replace manual ROI delineation with a reproducible preprocessing step for insect HSI analysis, supporting standardized spectral extraction and future applications in forensic entomology.