Retrospective Analysis of Death Cases of Oral Diphenidol Hydrochloride Poisoning.

OBJECTIVES: To explore the characteristics of postmortem examination, chemical examination and scene investigation of deaths caused by oral diphenidol hydrochloride poisoning, and so as to provide a reference for proper settlement and prevention of such deaths. METHODS: The data of 22 deaths caused by oral diphenidol hydrochloride poisoning in a city from January 2018 to August 2020 were collected, including case details, scene investigations, autopsies, chemical examinations and digital evidence. Thirty-one cases of deaths caused by oral diphenidol hydrochloride poisoning reported in previous literature were also collected. RESULTS: In the 53 oral diphenidol hydrochloride poisoning death cases, 50 cases were suicide, 2 cases were accidental, while 1 case was undetermined. Fifty-two cases were found in the medical records or crime scene investigation reports with doses ranging from 775 mg to 12 500 mg, and 23 deceased were detected with postmortem blood concentrations ranging from 2.71 mg/L to 83.1 mg/L. Clinical symptoms were recorded in 6 patients, including conscious disturbance and convulsion. Among the 45 cases which were performed with external examination, 23 cases autopsied. CONCLUSIONS: Most of the deceased of oral diphenidol hydrochloride poisoning were suicide. No significant correlation was found between dose and blood concentration through the retrospective analysis of cases.

New Advances, Challenges and Opportunities in Forensic Applications of Microbiomics.

The succession of microbiota is closely associated with several essential factors, including race, sex, health condition, lifestyle, postmortem interval, etc., and it has great potential application value in forensic medicine. This paper summarizes recent studies on the forensic applications of the microbiome, including individual identification, geographical feature identification, origin identification of the tissue or body fluid, and postmortem interval estimation, and introduces the current machine learning algorithms for microbiology research based on next-generation sequencing data. In addition, the current problems facing forensic microbiomics such as the extraction and preservation of samples, construction of standardization and database, ethical review and practical applicability are discussed. Future multi-omics studies are expected to explore micro ecosystems from a comprehensive and dynamic perspective, to promote the development of forensic microbiomics application.