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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.

Papillary adenoma of the lung, a rare and benign tumor, is easily confused with other primary benign or malignant lung tumors and especially with lung adenocarcinoma that has a papillary growth pattern. Enhanced understanding and an accurate diagnosis of papillary adenomas of the lung are crucial for clinical treatment and prognostic assessment. A 61-year-old man who presented with an opportunistic finding in relation to a left lower lobe lung nodule during an examination was admitted to The First Hospital of China Medical University (Shenyang, China) for further treatment. Computed tomography (CT) revealed a well-circumscribed left lower lobe nodule (diameter, ~1 cm), comprising branched papillae with a fibrovascular core and no other structural components. The tumor cells appeared relatively uniform in shape and well arranged with round or oval nuclei. No nucleoli or mitotic figures were observed. Immunohistochemically, the papillary structures of the tumor cells were strongly and diffusely positive for cytokeratin (CK), CK7, Napsin-A and thyroid transcription factor 1. The Ki-67 index was ~1%. A pathological diagnosis of primary papillary adenoma of the lung was made based on these findings. A left lower-lobe wedge resection was performed and the patient's postoperative course was uneventful. Surgical resection is the preferred treatment. Papillary adenoma of the lung is very rare, and its clinical manifestations and CT images are non-specific. It is important to avoid misdiagnosing of papillary adenoma of the lung as another type of lung tumor, especially adenocarcinoma. A clear understanding of the morphological and immunohistochemical features of papillary adenomas is important for the diagnosis of this rare lung tumor. [ABSTRACT FROM AUTHOR]