Forensic microbiome research is a field with a wide range of applications and a number of protocols have been developed for its use in this area of research. As individuals host radically different microbiota, the human microbiome is expected to become a new biomarker for forensic identification. To achieve an effective use of this procedure an understanding of factors which can alter the human microbiome and determinations of stable and changing elements will be critical in selecting appropriate targets for investigation. The 16S rRNA gene, which is notable for its conservation and specificity, represents a potentially ideal marker for forensic microbiome identification. Gene sequencing involving 16S rRNA is currently the method of choice for use in investigating microbiomes. While the sequencing involved with microbiome determinations can generate large multi-dimensional datasets that can be difficult to analyze and interpret, machine learning methods can be useful in surmounting this analytical challenge. In this review, we describe the research methods and related sequencing technologies currently available for application of 16S rRNA gene sequencing and machine learning in the field of forensic identification. In addition, we assess the potential value of 16S rRNA and machine learning in forensic microbiome science.
BACKGROUND: Warthin-like papillary renal cell carcinoma (WPRCC) has been described as a rare pathological subtype of papillary renal cell carcinoma in the 2022 World Health Organization Classification of the Urinary and Male Reproductive System. Herein we report a case of WPRCC in the left kidney. CASE SUMMARY: Physical examination of a previously healthy 47-year-old woman revealed a lump in her left kidney, 4.5 cm × 3.5 cm × 3.5 cm in size. Based on the clinical information, imaging data, histmorphological features, and immunohistochemistry results, the pathological diagnosis was WPRCC in left kidney. CONCLUSION: Resection of the mass in the left kidney was performed and her postoperative course was uneventful.
