| Objective: The deposition time of body fluid stains is an important clue for case detection,and its accurate inference can effectively narrow the scope of police investigation.Most of the current studies have addressed the time elapsed from the time the spot leaves the body to the time it is examined,but it is not possible to control the prediction time error to within one day.How to further reduce the inferential error is a pressing challenge to be solved.Based on circadian biomarkers,it is possible to infer the deposition time of body fluid spots in a day,such as day and night,which can effectively narrow the range of time inference.However,the markers currently studied do not have good anti-degradation properties,so it is crucial to find markers with both circadian and anti-degradation properties.Because of their small molecular weight,miRNAs can exist stably in spots.This study will explore the potential of circadian miRNAs in blood stain deposition time category inference and construct mathematical models of time category inference in conjunction with mRNA.The purpose of this study is to provide a new theoretical basis and technical scheme for the deposition time of body fluid spots.Methods: Fingertip blood was collected from 9 healthy adults based on informed consent,with 9 samples collected at 3-hour intervals per individual.The miRNAs and mRNAs with circadian properties that have been reported in the literature were selected as candidate molecular markers,and specific primers were designed to detect the relative expression of the candidate markers in the above samples for 1 day by RT-q PCR.Independent samples t-test with α=0.05 as the test level was used to test the differential expression of candidate markers between daytime and nighttime.Binary logistic regression models were constructed to infer whether the time of blood deposition was day or night;Fisher discriminant analysis models were constructed to infer three time categories: morning(6:00-11:59),afternoon(12:00-20:59),and evening(21:00-5:59).The blood spots were placed in the chamber and the expression of the candidate markers within the samples was detected on days 0,7,14 and 28,respectively,which was to assess the resistance to degradation of the selected candidate markers and the stability of the constructed assay.Results: Eleven miRNAs with circadian rhythm properties(hsa-miR-150-5p,hsa-miR-375,hsa-miR-192a-5p,hsa-miR-15b-5p,hsa-miR-140-5p,hsa-miR-139-5p,hsa-miR-483-5p,hsa-miR-132-3p,hsa-miR-181a-5p,hsa-miR-27b-5p,hsa-miR-27b-3p)and five mRNAs(TIMELESS,HSPA1 B,PER3,MKNK2,CLOCK)were selected for study.Among them,hsa-miR-150-5p,hsa-miR-140-5p,TIMELESS,and CLOCK showed significant differential daytime and nighttime expression in blood spots.Backward stepwise regression was used to screen the variables,hsa-miR-150-5p,hsa-miR-140-5p,hsa-miR-192a-5p,TIMELESS,PER3 and CLOCK were used to construct a binary logistic regression model with AUC value as the evaluation index,with a training set of 0.905 and a test set of1.000.hsa-miR-150-5p,hsa-miR-140-5p,TIMELESS,HSPA1 B,PER3 and CLOCK were used to construct the Fisher discriminant analysis model with an accuracy of 70.4% for self-validation and 64.2% for cross-validation.The miRNAs had good resistance to degradation and were detectable in all samples;the mRNAs were less stable and degraded rapidly within 7 days,and some loci were no longer detectable in the samples after 14 days.Conclusions:In this study,we found significant daytime and nighttime differential expression of hsa-miR-150-5p,hsa-miR-140-5p,TIMELESS and CLOCK,based on which binary logistic regression model and Fisher discriminant analysis model were successfully constructed for inferring the categories of deposition time of bloodstains.mRNAs are less resistant to degradation,while miRNAs are highly resistant to degradation and are good markers for temporal category inference. |
PDF Full Text Request