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.

Postmortem submersion interval estimation of cadavers recovered from freshwater based on gut microbial community succession.

Microbial community succession during decomposition has been proven to be a useful tool for postmortem interval (PMI) estimation. Numerous studies have shown that the intestinal microbial community presented chronological changes after death and was stable in terrestrial corpses with different causes of death. However, the postmortem pattern of intestinal microbial community succession in cadavers retrieved from water remains unclear. For immersed corpses, the postmortem submersion interval (PMSI) is a useful indicator of PMI. To provide reliable estimates of PMSI in forensic investigations, we investigated the gut microbial community succession of corpses submersed in freshwater and explored its potential application in forensic investigation. In this study, the intestinal microbial community of mouse submersed in freshwater that died of drowning or CO2 asphyxia (i.e., postmortem submersion) were characterized by 16S rDNA amplification and high-throughput sequencing, followed by bioinformatic analyses. The results demonstrated that the chronological changes in intestinal bacterial communities were not different between the drowning and postmortem submersion groups. α-diversity decreased significantly within 14 days of decomposition in both groups, and the ß-diversity bacterial community structure ordinated chronologically, inferring the functional pathway and phenotype. To estimate PMSI, a regression model was established by random forest (RF) algorithm based on the succession of postmortem microbiota. Furthermore, 15 genera, including Proteus, Enterococcus, and others, were selected as candidate biomarkers to set up a concise predicted model, which provided a prediction of PMSI [MAE (± SE) = 0.818 (± 0.165) d]. Overall, our present study provides evidence that intestinal microbial community succession would be a valuable marker to estimate the PMSI of corpses submerged in an aquatic habitat.

Inferring Postmortem Submersion Interval in Rats Found in Water Based on Vitreous Humor Metabolites.

OBJECTIVES: The metabolomics technique of LC-MS/MS combined with data analysis was used to detect changes and differences in metabolic profiles in the vitreous humor of early rat carcasses found in water, and to explore the feasibility of its use for early postmortem submersion interval (PMSI) estimation and the cause of death determination. METHODS: The experimental model was established in natural lake water with 100 SD rats were randomly divided into a drowning group (n=50) and a postmortem (CO2 suffocation) immediately submersion group (n=50). Vitreous humor was extracted from 10 rats in each group at 0, 6, 12, 18 and 24 h postmortem for metabolomics analyses, of which 8 were used as the training set to build the model, and 2 were used as test set. PCA and PLS multivariate statistical analysis were performed to explore the differences in metabolic profiles among PMSI and causes of death in the training set samples. Then random forest (RF) algorithm was used to screen several biomarkers to establish a model. RESULTS: PCA and PLS analysis showed that the metabolic profiles had time regularity, but no differences were found among different causes of death. Thirteen small molecule biomarkers with good temporal correlation were selected by RF algorithm. A simple PMSI estimation model was constructed based on this indicator set, and the data of the test samples showed the mean absolute error (MAE) of the model was 0.847 h. CONCLUSIONS: The 13 metabolic markers screened in the vitreous humor of rat corpses in water had good correlations with the early PMSI. The simplified PMSI estimation model constructed by RF can be used to estimate the PMSI. Additionally, the metabolic profiles of vitreous humor cannot be used for early identification of cause of death in water carcasses.

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.

Film-Stabilizing Attributes of Polymeric Core-Shell Nanoparticles.

Self-organization of nanoparticles into stable, molecularly thin films provides an insightful paradigm for manipulating the manner in which materials interact at nanoscale dimensions to generate unique material assemblies at macroscopic length scales. While prior studies in this vein have focused largely on examining the performance of inorganic or organic/inorganic hybrid nanoparticles (NPs), the present work examines the stabilizing attributes of fully organic core-shell microgel (CSMG) NPs composed of a cross-linked poly(ethylene glycol dimethacrylate) (PEGDMA) core and a shell of densely grafted, but relatively short-chain, polystyrene (PS) arms. Although PS homopolymer thin films measuring from a few to many nanometers in thickness, depending on the molecular weight, typically dewet rapidly from silica supports at elevated temperatures, spin-coated CSMG NP films measuring as thin as 10 nm remain stable under identical conditions for at least 72 h. Through the use of self-assembled monolayers (SAMs) to alter the surface of a flat silica-based support, we demonstrate that such stabilization is not attributable to hydrogen bonding between the acrylic core and silica. We also document that thin NP films consisting of three or less layers (10 nm) and deposited onto SAMs can be fully dissolved even after extensive thermal treatment, whereas slightly thicker films (40 nm) on Si wafer become only partially soluble during solvent rinsing with and without sonication. Taken together, these observations indicate that the present CSMG NP films are stabilized primarily by multidirectional penetration of relatively short, unentangled NP arms caused by NP layering, rather than by chain entanglement as in linear homopolymer thin films. This nanoscale "velcro"-like mechanism permits such NP films, unlike their homopolymer counterparts of comparable chain length and thickness, to remain intact as stable, free-floating sheets on water, and thus provides a viable alternative to ultrathin organic coating strategies.

Preparation of N2/CO2 triggered reversibly coagulatable and redispersible latexes by emulsion polymerization of styrene with a reactive switchable surfactant.

This work reports the development of a reversibly coagulatable and redispersible polystyrene latex system that can be triggered by N(2)/CO(2). The coagulatability and redispersibility of the latexes were achieved by employing 0.9-5.6 wt % (N-amidino)dodecyl acrylamide (DAm), a reactive switchable surfactant, in an emulsion polymerization of styrene under CO(2) atmosphere. The resulted latex particles were readily coagulated by N(2) bubbling at 60 °C and redispersed by CO(2) bubbling and ultrasonication, which switched amidine moieties between neutral and ionic states. The coagulation/redispersion processes were repeatable. The prepared latexes showed good stabilities against electrolytes, especially with higher charges.