Microorganisms are essential in the decomposition of corpses and play a significant role in forensic science. However, previous studies have primarily focused on animal remains, specifically the gut, skin, and burial environment. Insufficient research has been conducted on the microbiota of human cadavers, especially in cases of advanced decomposition and additional tissues, resulting in a lack of relevant reference data. In this study, the microbiota of eight cadavers at different stages of decomposition were detected using 16S rRNA, metagenomic sequencing and 2bRAD-M sequencing. Nine different sites, including oral and nasal cavities, heart, liver, spleen, lung, kidney, muscle and gut, were analysed and the efficacy of these methods was evaluated. The results showed that 16S rRNA sequencing was the most cost-effective method for the study of cadavers in the early stages of decomposition, whereas for cadaveric tissues in the late stages of decomposition, 2bRAD-M could overcome host contamination more effectively than metagenomic sequencing. This paves the way for new opportunities in data retrieval and promotes in-depth investigations into the microbiota.

Major depressive disorder (MDD) is a complex psychiatric illness, with synaptic plasticity playing a key role in its pathology. Our study aims to investigate the molecular basis of MDD by analyzing synaptic plasticity-related gene expression at the single-cell level. Utilizing a published snRNA-seq dataset (GSE144136), we identified Excitatory.neurons_1 as the cell cluster most associated with MDD and synaptic plasticity through cell clustering, gene set enrichment analysis (GSEA), and pseudotime analysis. Integrating the bulk RNA-seq data (GSE38206), we identified CASKIN1 and CSTB as hub genes via differential expression analysis and machine learning methods. Further exploration of the relevant mechanisms was performed via cell–cell communication and ligand-receptor interaction analysis, functional enrichment analysis, and the construction of molecular regulatory networks, highlighting miR-21-5p as a key biomarker. We propose that elevated miR-21-5p in MDD downregulates CASKIN1 in Excitatory.neurons_1 cells, resulting in decreased neural connectivity and altered synaptic plasticity. As our analyzed snRNA-seq dataset consists solely of male samples, these findings may be male-specific. Our findings shed light on potential mechanisms underlying synaptic plasticity in MDD, offering novel insights into the disorder’s cellular and molecular dynamics.

DNA mixture analysis poses a significant challenge in forensic genetics, particularly when dealing with degraded and trace amount DNA samples. Multi-SNPs (MNPs) are genetic markers similar to microhaplotypes but with smaller molecular sizes (< 75 bp), making them theoretically more suitable for analyzing degraded and trace amount samples. In this case report, we investigated a cold case involving a campstool stored for over a decade, aiming to detect and locate the suspect’s DNA. We employed both conventional capillary electrophoresis-based short tandem repeat (CE-STR) analysis and next-generation sequencing-based multi-SNP (NGS-MNP) analysis. The typing results and deconvolution of the mixed CE-STR profiles were inconclusive regarding the presence of the suspect’s DNA in the mixed samples. However, through NGS-MNP analysis and presence probability calculations, we determined that the suspect’s DNA was present in the samples from Sect. 4−1 with a probability of 1-8.41 × 10^− 6 (99.999159%). This evidence contradicted the suspect’s statement and aided in resolving the case. Our findings demonstrate the significant potential of MNP analysis for examining degraded and trace amount DNA mixtures in forensic investigations.