Accurate classification of postmortem decomposition stages is a critical step in estimating the postmortem interval （PMI） and tracing the initial decomposition environment. Research on the decomposition staging methodological system is gradually shifting from empirical observation to the establishment of systems based on multidimensional quantitative indicators. This paper focuses on two key pathways, “macroscopic morphological evolution” and “microscopic molecular succession”, and systema-tically reviews the evolutionary patterns and applicability of the decomposition staging system in three typical environmental media: surface exposure, burial, and aquatic systems. It also summarizes research progress in constructing stage classification models utilizing microbiome and metabolomic features. Furthermore, it highlights the integrated application of decomposition characteristic quantification techniques, multi-omics data integration, and machine learning algorithms in decomposition analysis systems. It analyzes the prospects and challenges of applying these approaches to build a standardized and practical decomposition staging system, aiming to provide theoretical support for establishing a decomposition staging system with high accuracy and strong adaptability to different environments.

Microhaplotypes (MHs) are short, multi-allelic genetic markers that combine high genomic abundance with low mutation rates and the absence of stutter artefacts in PCR. These properties make them promising genetic markers for resolving complex kinships in forensic genetics. In this study, 202 MHs were genotyped in 181 family samples. By integrating empirical genotyping with extensive in-silico simulations, we evaluated the ability of these 202 MHs to identify first-, second-, and third-degree relationships from unrelated pairs. Additionally, four previously selected sets of MHs (190, 301, 337 and 703 MHs) were re-examined to determine their respective effectiveness across these kinship classes. The 202 MHs reliably distinguished first-degree relatives from unrelated individuals and other types of kinships. In addition, these 202 MHs could also discriminate second-degree relatives from unrelated individuals with the accuracy > 0.99. In contrast, the panel's performance declined markedly for third-degree relationships, and obtained accuracy was less than 0.5 when analytical threshold of cumulative likelihood ratio was set as 104 and 10-4. The four alternative panels (190, 301, 337 and 703 MHs) exhibited similarly high effectiveness for first- and second-degree relationships with the accuracy > 0.99. For third-degree relationships, accuracy increased monotonically with the number of microhaplotypes. Specifically, the 337-MH and 703-MH sets correctly assigned the majority of third-degree pairs regardless of the threshold adopted, indicating their suitability for third-degree kinship testing. In summary, the 202-MH panel could serve as a highly efficient tool for first- and second-degree kinship testing in forensic practice. In addition, panels containing 337 or 703 MHs are recommended for third-degree analyses. Future work should further improve performance by integrating MHs with other types of genetic markers to address intricated kinship analysis.

Postmortem microbial communities may provide useful information for forensic microbiology, but species-level and functional profiles across multiple cadaveric anatomical sites remain poorly characterized. Here, shotgun metagenomic sequencing was performed on 144 samples from six anatomical sites, including the oral cavity, nasal cavity, trachea, lung, colon, and anus, collected from 24 human cadavers. A total of 15,301,799,968 raw reads were obtained, and 6565 species were identified, and KEGG pathways were annotated at the L1, L2, and L3 levels. Species-level microbial composition differed significantly among anatomical sites. PERMANOVA with permutations blocked by individual identity showed that anatomical site was the dominant factor explaining microbial community variation (R2 = 0.3778, p = 0.001, q = 0.001), whereas postmortem interval did not show a significant independent effect within the 1-38-day interval. KEGG functional profiles also differed significantly among anatomical sites at the L2 and L3 levels, and 182 of 214 L3 pathways showed significant site-associated differences after false-discovery-rate correction. Pathway-level mixed-effect models further indicated that anatomical site remained significantly associated with most L3 pathways after accounting for postmortem interval, age, sex, cause of death, and repeated sampling from the same individual. Species-pathway correlation analysis identified significant taxon-function associations, but these were interpreted as correlative rather than direct evidence of species-specific functional contribution. Low-biomass sensitivity analyses indicated that respiratory-site results, especially lung and tracheal findings, should be interpreted cautiously because of high host DNA proportions and low non-host read counts. Inter-site shared occurrence and intra-site co-occurrence analyses further described distributional associations across anatomical sites. This study establishes a multi-site postmortem metagenomic reference framework for characterizing anatomical-site-specific microbial and functional patterns, offering insights into forensic microbiology and postmortem microbial ecology.

Body fluids are commonly found biological traces at crime scenes. Differentiating body fluid types-especially saliva (SA) from vaginal secretions (VA)-remains a forensic challenge. Currently, microbes play an increasingly vital role in forensic science. In this study, we analyzed bacterial communities from various samples, including SA, VA, semen (SE) and skin (SK), using Illumina HiSeq sequencing of 16S rRNA gene amplicons. We validated the ability to distinguish SA samples from VA samples using real-time quantitative PCR (qPCR) for specific biomarkers. We obtained 8,211,062 tags and identified 4427 operational taxonomic units (OTUs). Bacteria at the phylum level were similar across the four body fluid types, but their abundances varied. At the genus level, different bacteria dominated. Principal coordinates analysis (PCoA) and cluster analysis revealed significant differences among sample types. Additionally, linear discriminant analysis effect size (LEfSe) identified specific bacterial variations across the four body fluids. qPCR validation of the sequencing-derived markers confirmed that eight specific biomarkers reliably distinguish SA from VA. This work enhances the fundamental understanding of microorganisms in different body fluids and aids in distinguishing SA and VA.

Microbial profiles in dust are closely correlated with geographical locations and provide valuable clues for criminal investigation, demonstrating significant potential in forensic use. However, the feasibility of using microbial profiles from metagenomics datasets to infer the geographical locations remains underexplored. In this study, we collect 170 dust samples from resident communities in four cities across northern, eastern, southwestern, and northwestern China. All samples are subjected to shotgun metagenomic sequencing to reveal variations in microbial composition. In total, 41,029 species are annotated, including 93.39% bacteria, 6.37% eukaryotes, 0.21% viruses, and 0.03% archaea. Clear clustering patterns are observed among the four cities (R2=0.870, P<0.001). Further filtering of species with detection rates below 10% across all samples strengthens city-level clustering (R2=0.948, P<0.001). Additionally, 127 biomarkers are identified using linear discriminant analysis effect size (LEfSe) to distinguish between the cities. Each city harbors a distinct microbial community, with unique species and relatively abundant taxa that contribute to its differentiated microbial profile. All samples are randomly split into training and testing sets in a 7:3 ratio. Five machine learning models including SourceTracker, FEAST, LightGBM, Random Forest and Support Vector Machine are applied to 51 randomly sample data and achieve average accuracies of 88.89%, 92.16%, 98.04%, 99.35% and 69.28%, respectively. These results constitute a microbial genetic map of four cities in China that highlights distinct microbial taxonomic signatures and provides an approach for city-scale source tracking of dust samples.

Objective The proteome of biological evidence contains rich genetic information, namely single amino acid polymorphisms (SAPs) in protein sequences. However, due to the lack of efficient and convenient analysis tools, the application of SAP in public security still faces many challenges. This paper aims to meet the application requirements of SAP analysis for forensic biological evidence's proteome data. Methods The software is divided into three modules. First, based on a built-in database of common non-synonymous single nucleotide polymorphisms (nsSNPs) and SAPs in East Asian populations, the software integrates and annotates newly identified exonic nsSNPs as SAPs, thereby constructing a customized SAP protein sequence database. It then utilizes a pre-installed search engine-either pFind or MaxQuant-to perform analysis and output SAP typing results, identifying both reference and variant types, along with their corresponding imputed nsSNPs. Finally, SAPTyper compares the proteome-based typing results with the individual's exome-derived nsSNP profile and outputs the comparison report. Results SAPTyper accepts proteomic DDA mass spectrometry raw data (DDA acquisition mode) and exome sequencing results of nsSNPs as input and outputs the report of SAPs result. The pFind and Maxquant search engines were used to test the proteome data of 2 hair shafts of 2 individuals, and both obtained SAP results. It was found that the results of the Maxquant search engine were slightly less than those of pFind. This result shows that SAPTyper can achieve SAP fingding function. Moreover, the pFind search engine was used to test the proteome data of 3 hair shafts from 1 European person and 1 African person in the literature. Among the sites fully matched by the literature method, sites detected by SAPTyper are also included; for semi-matching sites, that is, nsSNPs are heterozygous, both literature method and SAPTyper method had the risk of missing detection for one type of the allele. Comparing the analysis results of SAPTyper with the SAP test results reported in the literature, it was found that some imputed nsSNP sites identified by the literature method but not detected by SAPTyper had a MAF of less than 0.1% in East Asian populations, and therefore they were not included in the common nsSNP database of East Asian populations constructed by this software. Since the database construction of this software is based on the genetic variation information of East Asian populations, it is currently unable to effectively identify representative unique common variation sites in European or African populations, but it can still identify SAP sites shared by these populations and East Asian populations. Conclusion An automated SAP analysis algorithm was developed for East Asian populations, and the software named SAPTyper was developed. This software provides a convenient and efficient analysis tool for the research and application of forensic proteomic SAP and has important application prospects in individual identification and phenotypic inference based on SAP.

OBJECTIVES:The persistence and infectivity of respiratory viruses in cadavers remain poorly characterized, posing significant biosafety risks for forensic and healthcare professionals. This study systematically evaluates the post-mortem stability and transmission potential of SARS-CoV-2, influenza A virus (IAV), and respiratory syncytial virus (RSV) under varying environmental conditions, providing critical insights into viral kinetics. METHODS:To assess the post-mortem stability of SARS-CoV-2, tissue samples were collected from infected cadavers at 4 ℃, room temperature (RT, 20-22 ℃), and 37 ℃ over a predetermined timeframe. Viral kinetics were analyzed using quantitative assays, while histopathology and immunohistochemistry characterized tissue-specific distribution. Additionally, comparative analyses were conducted both in vitro and in cadaveric tissues to characterize the survival dynamics of IAV and RSV under identical conditions. RESULTS:SARS-CoV-2 exhibited prolonged post-mortem infectivity, persisting for up to 5 days at RT and 37 ℃ and over 7 days at 4 ℃, with the highest risk of transmission occurring within the first 72 h at RT and 24 h at 37 ℃. In contrast, RSV remained viable for 1-2 days, while IAV persisted for only a few hours post-mortem. Viral decay rates were temperature-dependent and varied across tissues, demonstrating distinct post-mortem survival kinetics. CONCLUSIONS:This study presents the first comprehensive analysis of viral persistence in cadavers, revealing prolonged SARS-CoV-2 stability compared to IAV and RSV. These findings underscore the need for enhanced post-mortem biosafety protocols to mitigate occupational exposure risks in forensic and clinical settings. By elucidating viral decay dynamics across environmental conditions, this research establishes a critical foundation for infection control strategies, informing biosafety policies for emerging respiratory pathogens.

Objective Dust has steadily emerged as a frontier research in the field of forensic science because it is a material evidence with significant features and application potential that carries rich environmental DNA information. However, as a crucial foundational step in forensic applications, the collection and DNA extraction research of dust on object surfaces from the perspective of practical applications in forensic science are still in urgent need of development. Methods Dust was collected from object surfaces using a Copan Liquid Amies Elution Swab. DNA was extracted separately from the swab head, sediment, and supernatant within the sample collection tube to evaluate DNA content, thereby determining which components within the tube should be processed and lysed. Dust samples were collected according to five different sampling areas (25-400 cm2) and the DNA concentration was measured to determine the optimal sampling area. The extraction efficiency of three commercial DNA extraction kits for dust samples was compared. The size of the DNA fragments extracted from the dust was analyzed, as well as the presence of human DNA. Additionally, 16S rDNA amplicon sequencing was used to analyze the bacterial information in dust DNA from object surfaces. This process aimed to establish a quality control method for dust DNA extraction. Regarding the critical step of cell lysis in DNA extraction, the quantity of DNA extracted was compared and evaluated under different cell lysis methods and varying vortexing times. This was done to establish an appropriate cell lysis method for dust DNA extraction. Results The sediment and swab head in the dust sampling tube are the primary sources of DNA, and both should be included in subsequent extraction processes. The sampling area of dust is positively correlated with dust DNA concentration, and it is recommended that the sampling area be larger than 5x5 cm2. Using the DNeasy PowerSoil Pro kit can yield a higher amount of DNA. Additionally, there were no significant differences in the sizes of DNA fragments extracted by the three different DNA extraction kits. No human DNA was detected in the DNA extracted from the dust samples, while bacterial DNA was present in the dust from object surfaces. Furthermore, there were differences in microbial species composition between different sampling points. Additionally, using a biological sample homogenizer to grind and lyse for 4 min (2 minx 2 times) resulted in the highest concentration of dust DNA. Conclusion The extraction of dust DNA is influenced by the sampling area, extraction kits, and lysis methods. It is crucial to establish a comprehensive and suitable dust DNA extraction scheme. This not only lays the foundation for researching and extracting environmental DNA data from dust, but also provides a methodological reference for forensic case work involving environmental samples.

Bacterial traceability refers to the use of a range of techniques to trace the origins and transmission pathways of bacteria. It is crucial in controlling the spread of diseases, analyzing bioterrorism incidents, and advancing microbial forensics. In recent years, the frequency and scope of bacterial outbreaks have continued to escalate, exerting significant impacts on global biosecurity, public health, and other areas. Consequently, it is required to process traceability of bacteria timely and accurately around the globe. The rapid development of biological and physicochemical traceability techniques provides convenience for tracing bacteria. These techniques not only surpass traditional methods in terms of sensitivity, traceability and throughput, but also find more extensive applications in elucidating bacterial growth mechanisms, transmission routes, and geographical origins. This paper systematically reviews the latest research progress and applications of technologies of bacterial traceability, highlighting key advancements and projecting future trends, with the intent of providing a valuable reference for researchers, facilitating further studies and innovations in this field.

In forensics, it is important to determine the time since deposition (TSD) of bloodstains, one of the most common types of biological evidence in criminal cases. However, no effective TSD inference methods have been established despite extensive attempts in forensic science. Our study investigated the changes in the blood transcriptome over time, and we found that degradation could be divided into four stages (days 0-2, 4-14, 21-56, and 84-168) at 4 °C. A random forest prediction model based on these transcriptional changes was trained on experimental samples and tested in separate test samples. This model was able to successfully predict TSD (area under the curve [AUC] = 0.995, precision = 1, and recall = 1). Thus, this proof-of-concept pilot study has practical significance for assessing physical evidence. Meanwhile, 11 upregulated and 13 downregulated transcripts were identified as potential time-marker transcripts, laying a foundation for further development of TSD analysis methods in forensic science and crime scene investigation.

本文建立了毛干蛋白单氨基酸多态性(single amino acid polymorphism,SAP)的质谱检测方法,以DNA测序验证方法的准确性,并设计多组样本检验SAP鉴定的重现性.对来自6个人的25份毛干样本的SAP鉴定结果进行分析,并与毛干来源人的血液外显子测序结果相比较,对于不一致位点进一步使用Sanger法测序确定SAP对应的SNP分型.共设计四组重复性实验测试,对不同直径/生长部位毛干的分型结果进行了 一致性验证.通过设计的376对引物进行PCR扩增,成功检测了 522个SNP分型,其中32个(6.1％)与前期外显子测序分型不一致,152个(29.1％)为外显子测序中未检测的分型,338个(64.8％)与外显子分型结果一致.四组重复性实验中,组内SAP鉴定准确率平均值为93.6％(95％CI:92.8％～94.5％),鉴定重现率平均值为96.0％(95％CI:94.3％～97.6％).在所有25份样本中,有283个SAP位点在至少两个样本中检出,其中23个位点在全部样本中都被检出.因此,毛干蛋白SAP鉴定方法具有较高的准确性和重现性,得到的23个高检出率SAP位点可作为候选位点构建有效位点组合,呈现出潜在的法医学应用价值.

MicroRNA (miRNA)-based methods for body fluid identification are promising tools in the practice of forensic science. The selection of appropriate endogenous reference genes as normalizers for the relative quantification of miRNA expression levels using quantitative reverse transcription-polymerase chain reaction (RTqPCR) is essential to avoid errors and improve the comparability of miRNA expression level data among different body fluids. In this study, small RNAs were isolated from individual donations of five forensically relevant body fluids (peripheral blood, menstrual blood, saliva, semen and vaginal secretions). Thirty-seven samples were subjected to high-throughput miRNA sequencing. By combining our results with those obtained through a literature investigation, 28 candidate RNAs were identified. Following RTqPCR validation, the candidate RNAs were preliminarily evaluated in 15 samples to exclude miRNAs with low expression and high variation. Then, the expression levels of 10 relatively stable candidate reference RNAs in 100 samples were determined and further analysed using four commonly employed programs (geNorm, NormFinder, BestKeeper and ΔCq). According to the comprehensive stability rankings of the four algorithms, miR-320a-3p was validated as the most stable endogenous reference gene among the five forensically relevant body fluids, followed by miR-484, SNORD43, miR-320c and RNU6b. Moreover, the combined application of miR-320a-3p with RNU6b could increase the normalization effect. In addition, a total of 56 mock samples placed outdoors and indoors for different times were prepared to further evaluate the stability of candidate reference RNAs, and miR-320a-3p remained the preferred reference gene. Furthermore, the relative expression levels of publicly accepted body fluid-specific miRNAs were determined in 30 samples to verify the practicality and effectiveness of the reference genes. Our results revealed a set of alternative reference genes and could promote the development and application of miRNA-based body fluid identification by determining optional reference genes for strict normalization.

目的 准确估算血迹离体时间能为刑事案件调查提供信息或线索.本文利用qPCR技术检测血迹中RNA的降解情况,进而筛选并评估适用于血迹离体时间推断的内参基因(reference genes).方法 本研究制备 10 名志愿者 0～90 d区间范围内 7 个时间节点共 70 份样本的总RNA为实验材料,基于其中 6 名志愿者的样本的qPCR数据,使用geNorm和NormFinder算法对14个候选内参基因(let-7g-5p,let-7i-5p,miR-191-5p,miR-484,miR-103a-5p,miR-423-5p,PPIA,ACTB,5SrRNA,18SrRNA,miR-93-5p,U6b,SNORD24,SNORD38B)进行稳定性评估,筛选内参基因及其使用方案.选取全部10 名志愿者70 份样本,验证内参基因及其使用方案的校正效果.结果 qPCR检测显示miRNA在血迹离体后 90 d范围内表现出的稳定性较强.综合使用geNorm和NormFinder两种算法获得的内参基因使用方案为:以let-7g-5p为单基因内参,或以let-7g-5p、U6b和miR-191-5p组合为三内参基因.70 个样本对两个内参基因使用方案的校正能力验证显示,多基因组合内参方案的三次方程模型能更准确推断血液斑迹的离体时间.结论 本研究首先推荐以ACTB为标记,以let-7g-5p、U6b、miR-191-5p组合的三内参基因三次方程校正模型用于血迹离体时间推断检验鉴定技术研发;在考虑提高检验效率、简化实验流程等需求而需要选择单基因作为内参基因时,可以选择ACTB为标记,使用let-7g-5p为内参基因的三次方校正模型.

Background Non-recombining regions of the Y-chromosome recorded the evolutionary traces of male human populations and are inherited haplotype-dependently and male-specifically. Recent whole Y-chromosome sequencing studies have identified previously unrecognized population divergence, expansion and admixture processes, which promotes a better understanding and application of the observed patterns of Y-chromosome genetic diversity. Results Here, we developed one highest-resolution Y-chromosome single nucleotide polymorphism (Y-SNP) panel targeted for uniparental genealogy reconstruction and paternal biogeographical ancestry inference, which included 639 phylogenetically informative SNPs. We genotyped these loci in 1033 Chinese male individuals from 33 ethnolinguistically diverse populations and identified 256 terminal Y-chromosomal lineages with frequency ranging from 0.0010 (singleton) to 0.0687. We identified six dominant common founding lineages associated with different ethnolinguistic backgrounds, which included O2a2b1a1a1a1a1a1a1-M6539, O2a1b1a1a1a1a1a1-F17, O2a2b1a1a1a1a1b1a1b-MF15397, O2a2b2a1b1-A16609, O1b1a1a1a1b2a1a1-F2517, and O2a2b1a1a1a1a1a1-F155. The AMOVA and nucleotide diversity estimates revealed considerable differences and high genetic diversity among ethnolinguistically different populations. We constructed one representative phylogenetic tree among 33 studied populations based on the haplogroup frequency spectrum and sequence variations. Clustering patterns in principal component analysis and multidimensional scaling results showed a genetic differentiation between Tai-Kadai-speaking Li, Mongolic-speaking Mongolian, and other Sinitic-speaking Han Chinese populations. Phylogenetic topology inferred from the BEAST and Network relationships reconstructed from the popART further showed the founding lineages from culturally/linguistically diverse populations, such as C2a/C2b was dominant in Mongolian people and O1a/O1b was dominant in island Li people. We also identified many lineages shared by more than two ethnolinguistically different populations with a high proportion, suggesting their extensive admixture and migration history. Conclusions Our findings indicated that our developed high-resolution Y-SNP panel included major dominant Y-lineages of Chinese populations from different ethnic groups and geographical regions, which can be used as the primary and powerful tool for forensic practice. We should emphasize the necessity and importance of whole sequencing of more ethnolinguistically different populations, which can help identify more unrecognized population-specific variations for the promotion of Y-chromosome-based forensic applications.

As an effective supplement to the current forensic DNA typing and one of the research hotpots in forensic science, the in-depth mining and characterization of biological evidence can provide rich and reliable clues for case investigation. In this study, the time-dependent variations of transcriptome were confirmed in in vitro blood samples within 0-168 days and a random forest model was established to realize the classification of blood samples with different TSD (time since deposition). Meanwhile, significant differences were observed in the transcripts of blood samples with different smoking habits and genders within a certain time period. HLA-DRB1, HLA-DQB1 and HLA-DQA2 were identified as markers for smoking habit identification, while the transcripts for RPS4Y1 and EIF1AY from the non-recombining region of the Y chromosome (NRY) were identified as markers for male sex identification. Thus, this study provides a theoretical foundation and experimental strategy for establishing a transcriptome-based method for characterizing blood sample retention time and donor characteristics in the field of forensic investigation.

构建一套包含39个常染色体基因座及Amelogenin性别基因的9色荧光STR复合扩增体系,并验证其在微量与降解检材中的应用效果.根据中国人群核心基因座推荐标准及实际办案需要,筛选出合适的候选基因座,设计引物并以9种荧光染料对其进行标记,构建复合扩增体系并优化;对该体系进行灵敏度、种属特异性、稳定性等确证实验,并通过检验案件样本做进一步评估.结果表明:一套包含39个常染色体STR基因座及Amelogenin性别基因座(其中28个基因座＜300 bp)的9色荧光复合扩增体系构建成功.各基因座均衡性良好,灵敏度达0.125 ng,对常见PCR抑制剂具备一定的耐受能力.两性混合样本最低检测比例为1:4;适用于不同类型案件样本检测,且与市场上其他同类试剂盒比对分型结果一致,种属特异性较好.所构建体系首次采用9色荧光标记技术制成复合扩增试剂,一次性检出基因座数量多,系统效能高;该体系构成以miniSTR为主,对于微量降解检材具有较高的实际应用价值.

研究表明人体不同的身体部位有独特的微生物群落,且在身体各部位发现的微生物总量比人体自身细胞更多,因此基于人体微生物群落组成的时空分布特点和变化规律来进行体液组织来源推断是一个重要的应用方向.本文综述了人体微生物多样性分析应用于法医学体液组织来源鉴定的背景、研究技术、近年来的研究进展及应用挑战,以期为相关研究和实践提供参考.

目的 筛选血痕中与其形成时间(time since deposition,TSD)具有相关性的RNA生物标志物并构建血痕形成时间推断模型.方法 从文献筛选 12 个候选RNA生物标志物(ALAS2、B2M、HBA、HBB、PPIA、ACTB、GAPDH、SPTB、SNORD24、SNORD38B、5S rRNA、18S rRNA),以let-7g-5p为内参基因,利用实时荧光定量PCR(Quantitative Real-time PCR,RT-qRCR)技术检测 10 名健康无关个体在 7 个时间节点的 70 份血痕样本,候选RNA生物标志物在 0～180 d范围内的相对表达丰度,筛选与形成时间相关性高的RNA生物标志物,以此构建用于血痕形成时间推断的多元线性回归模型并验证.结果 通过GraphPad Prism和SPSS Statistic 22 软件对候选RNA生物标志物的∆Cq值(∆Cq = Cq 生物标志物-Cq let-7g-5p)进行正态分布分析和相关性分析,确认PPIA、ACTB、GAPDH、ALAS2、B2M、HBA、18S rRNA和HBB这 8 个RNA生物标志物与血痕形成时间具有相关性.根据模型构建需要,选择向后回归法分别基于8个、4 个、2个RNA生物标志物构建血痕形成时间推断多元线性回归模型,通过留一法对模型进行验证,选取实验样本和案件样本对模型推断效果进行测试,确定模型平均绝对偏差(Mean absolute deviation,MAD).结论 本研究构建和验证了用于血痕形成时间推断的基于多个RNA生物标志物的多元线性回归模型,并使用案件样本进行了测试,评估了模型的实战应用潜力.