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Background Spermatogenesis is an intricate biological event wherein an undifferentiated spermatogonium develops into mature sperms. MicroRNAs are a type of single strand small non-coding RNA molecule and are implicated in the regulation of many crucial pathways during cell proliferation, apoptosis, and differentiation.Method Here, we present a comprehensive comparison of miRNA expression profiling in three main stages during porcine spermatogenesis using high-throughput sequencing. Results We built three small RNA libraries for the testis, the epididymis and the ejaculated sperm from a Landrace boar, and in total obtained 3821 precursor hairpins encoding for 4761 mature miRNAs, of which 23 are miRNA*. Notably, Zonggang Luo and Yingkai Liu contributed equally to this work.Capsule ZGL carried out the molecular genetic studies, participated in the sequence alignment, and revised themanuscript. YKL participated in the study design and drafted the manuscript. LC carried out the RT-PCR and data analysis. ME participated in the experiment. Assist Reprod Genet (2015) 32:451-460 DOI 10.1007 940 precursor miRNAs produced both the 5'-and 3'-strands as sister pairs, indicating the distinctive expression patterns of germ cell miRNAs. Additionally, 418 out of 710 co-expressed miRNAs were identified as being differentially expressed between libraries (P<0.001). Apart from the sexual specific X chromosome, many miRNAs were found to be located on chromosome 12, which may play potential roles in spermatogenesis according to the result of synteny analysis with human and mouse. The Gene Ontology and KEGG pathway analysis revealed that the target genes of co-expressed miRNAs were highly involved in the cell cycle process, metal ion binding, modification of plasma membrane, and the p53 signal pathway.

Dental caries is a multifactorial disease that can be caused by interactions between genetic and environmental risk factors. Despite the availability of caries risk assessment tools, caries risk prediction models incorporating new factors, such as human genetic markers, have not yet been reported. The aim of this study was to construct a new model for caries risk prediction in teenagers, based on environmental and genetic factors, using a machine learning algorithm. We performed a prospective longitudinal study of 1,055 teenagers (710 teenagers for cohort 1 and 345 teenagers for cohort 2) aged 13 years, of whom 953 (633 teenagers for cohort 1 and 320 teenagers for cohort 2) were followed for 21 months. All participants completed an oral health questionnaire, an oral examination, biological (salivary and cariostate) tests, and single nucleotide polymorphism sequencing analysis. We constructed a caries risk prediction model based on these data using a random forest with an AUC of 0.78 in cohort 1 (training cohort). We further verified the discrimination and calibration abilities of this caries risk prediction model using cohort 2. The AUC of the caries risk prediction model in cohort 2 (testing cohort) was 0.73, indicating high discrimination ability. Risk stratification revealed that our caries risk prediction model could accurately identify individuals at high and very high caries risk but underestimated risks for individuals at low and very low caries risk. Thus, our caries risk prediction model has the potential for use as a powerful community-level tool to identify individuals at high caries risk.

The objective of this study was to identify risk factors for enamel and dentin caries in adolescents. Method: This 1-year longitudinal study was conducted in 2018 and 2019; 13-to 14-year-old adolescents were recruited. The merged International Caries Detection and Assessment System (ICDAS) was used to identify caries. The relationships between the caries increment and variables were analyzed with a zero-inflated negative binomial (ZINB) regression model. Results: A total of 1,016 participants completed the assessment. The ZINB analysis found that individuals with caries at baseline were more likely to develop new dentin caries. Females, or individuals who had a high cariostat score had an increased likelihood of having a high D4-6MFT score. Among the caries-free adolescents at baseline, females, or individuals who consumed snacks once or more than once a day were more likely to develop caries. Individuals from one-child families, who used fluoride toothpaste, and who had a high saliva buffering capability (pH≥4.25) had an increased likelihood of a low D1-6MFT score. Conclusion: The results suggest that there are some specific risk factors of initiating of enamel caries in adolescents, including the frequency of snack consumption, sex, saliva buffering capability, fluoride toothpaste usage and belonging to a one-child family. In all adolescents, most of whom have enamel caries, the dentin caries risk factors were past caries experience, cariostat score and sex.