A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.

Postmortem submersion interval (PMSI) estimation and cause-of-death discrimination of corpses in water have long been challenges in forensic practice. Recently, many studies have linked postmortem metabolic changes with PMI extension, providing a potential strategy for estimating PMSI using the metabolome. Additionally, there is a lack of potential indicators with high sensitivity and specificity for drowning identification. In the present study, we profiled the untargeted metabolome of blood samples from drowning and postmortem submersion rats at different PMSIs within 24 h by liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 601 metabolites were detected. Four different machine learning algorithms, including random forest (RF), partial least squares (PLS), support vector machine (SVM), and neural network (NN), were used to compare the efficiency of the machine learning methods. Nineteen metabolites with obvious temporal regularity were selected as candidate biomarkers according to "IncNodePurity." Robust models were built with these biomarkers, which yielded a mean absolute error of 1.067 h. Additionally, 36 other metabolites were identified to build the classifier model for discriminating drowning and postmortem submersion (AUC = 1, accuracy = 95%). Our results demonstrated the potential application of metabolomics combined with machine learning in PMSI estimation and cause-of-death discrimination.

Sudden Death Due to Severe Ovarian Hyperstimulation Syndrome: An Autopsy-Centric Case Report.

ABSTRACT: Ovarian hyperstimulation syndrome (OHSS) is a rare iatrogenic disorder associated with controlled ovarian stimulation during assisted reproductive technology. Severe OHSS may impose serious complications, including pleural effusion, acute renal insufficiency, venous thrombosis, and even death, although lethal outcomes are rare in forensic practice. The reported incidence of severe OHSS ranges from 0.008% to 10%. Herein, we present the case of a 29-year-old woman who diagnosed with polycystic ovary syndrome and infertility chose to undergo assisted reproduction. She received leuprorelin acetate and follicle stimulating hormone prior to egg retrieval. Three days after the retrieval procedure, she developed abdominal pain and distension. Later that same day, she died unexpectedly. The subsequent autopsy revealed turbid effusions of pleural and peritoneal cavities, abnormal ovarian enlargement, and duskiness of multiple organ surfaces. Microscopic examination disclosed edema and hemorrhage in follicles of both ovaries, thrombosis within the myocardial matrix, and massive pulmonary edema. Routine toxicology screening was negative. The death was attributed to severe OHSS. This case provides a morphologic reference for clinical and forensic work. Autopsy findings in instances of severe OHSS provide valuable insight into the mechanisms and pathogenesis of this disease.

miR-26a/30d/152 are reliable reference genes for miRNA quantification in skin wound age estimation.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that exert their biological functions as negative regulators of gene expression. They are involved in the skin wound healing process with a dynamic expression pattern and can therefore potentially serve as biomarkers for skin wound age estimation. However, no reports have described any miRNAs as suitable reference genes (RGs) for miRNA quantification in wounded skin or samples with post-mortem changes. Here, we aimed to identify specific miRNAs as RGs for miRNA quantification to support further studies of skin wound age estimation. Overall, nine miRNAs stably expressed in mouse skin at certain posttraumatic intervals (PTIs) were preselected by next-generation sequencing as candidate RGs. These nine miRNAs and the commonly used reference genes (comRGs: U6, GAPDH, ACTB, 18S, 5S, LC-Ogdh) were quantitatively examined using quantitative real-time reverse-transcription polymerase chain reaction at different PTIs during skin wound healing in mice. The stabilities of these genes were evaluated using four independent algorithms: GeNorm, NormFinder, BestKeeper, and comparative Delta Ct. Stability was further evaluated in mice with different post-mortem intervals (PMIs). Overall, mmu-miR-26a-5p, mmu-miR-30d-5p, and mmu-miR-152-3p were identified as the most stable genes at both different PTIs and PMIs. These three miRNA RGs were additionally validated and compared with the comRGs in human samples. After assessing using one, two, or three miRNAs in combination for stability at different PTIs, PMIs, or in human samples, the set of miR-26a/30d/152 was approved as the best normalizer. In conclusion, our data suggest that the combination of miR-26a/30d/152 is recommended as the normalization strategy for miRNA qRT-PCR quantification in skin wound age estimation. Key points: The small size of miRNAs makes them less susceptible to post-mortem autolysis or putrefaction, leading to their potential use in wound age estimation.Studying miRNAs as biological indicators of skin wound age estimation requires the selection and validation of stable reference genes because commonly used reference genes, such as U6, ACTB, GAPDH, 5S, 18S, and LC-Ogdh, are not stable.miR-26a/30d/152 are stable and reliable as reference genes and their use in combination is a recommended normalization strategy for miRNA quantitative analysis in wounded skin.

Chronic ethanol exposure induced depressive-like behavior in male C57BL/6 N mice by downregulating GluA1.

Chronic ethanol exposure can increase the risk of depression. The α-amino-3­hydroxy-5-methyl-4-isoxazole-propionic acid (AMPA) receptor is a key factor in depression and its treatment. The study was conducted to investigate the depressive-like behavior induced by chronic ethanol exposure in mice and to explore the mechanism in cells. To establish the chronic ethanol exposure mouse model, male C57BL/6 N mice were administered 10% (m/V) and 20% (m/V) ethanol as the only choice for drinking for 60 days, 90 days and 180 days. Depressive-like behavior in mice was confirmed by the forced swimming test (FST). Ethanol-induced changes in the mouse hippocampus were indicated by Western blotting, qPCR and Fluoro-Jade C (FJC) staining. We confirmed that 90- and 180-day ethanol exposure can lead to depressive-like mouse behavior, cell apoptosis, neuronal degeneration, a reduction in GluA1 and brain-derived neurotrophic factor (BDNF) expression, and an increase in IL-6 and IL-1ß in the mouse hippocampus. GluA1 silencing and overexpression models of SH-SY5Y cells were established for further investigation. The cells were treated with 100 mM and 200 mM ethanol for 24 h. Ethanol exposure decreased cell viability and the expression of BDNF and increased the cell apoptosis rate and the expression of BAX, cleaved caspase-3, IL-1ß and IL-6. GluA1 silencing aggravated ethanol-induced changes in cell viability and apoptosis and the expression of BDNF, BAX and cleaved caspase-3, and GluA1 overexpression attenuated these changes. Neither the silencing nor overexpression of GluA1 had an effect on ethanol-induced increases in IL-1ß and IL-6. Our results indicated that chronic ethanol exposure induced depressive-like behavior in male C57BL/6 N mice by downregulating GluA1 expression.