ObjectiveTo observe stage-specific changes in the intestinal microbiota of nude mice after death and to develop a postmortem interval （PMI） estimation model based on “rupture points”, thereby exploring a new model for PMI estimation.MethodsA total of 108 nude mice were sacrificed, and cecal contents were collected at 18 time points （0, 24, 41, 48, 55, 65, 72, 79, 89, 96, 103, 113, 120, 144, 168, 192, 216, and 240 h postmortem）. 16S rRNA gene amplicon sequencing was used to analyze the changes in intestinal microbiota. Based on microbial abundance, a random forest model was employed for cross-validation to identify signature bacterial genera. A segmented regression model was then constructed to estimate PMI and compared with a direct regression model.ResultsBoth α- diversity and β-diversity analyses indicated significant changes in the relative abundance of intestinal microbiota during the periods of 0-103 h and 113-240 h postmortem in nude mice. The segmented regression model built using the random forest algorithm achieved an R2 of 0.96 and a mean absolute error （MAE） of 9.83 h for PMI estimation. In contrast, the direct regression model yielded an R2 of 0.81 and an MAE of 16.91 h.ConclusionMicrobial succession during cadaver decomposition exhibits clear temporal and stage-specific characteristics. A segmented regression model for PMI estimation using “rupture points” can improve the accuracy of PMI estimation in nude mice.

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.

The estimation of postmortem interval (PMI) has long been a focal point in the field of forensic science. Following the death of an organism, microorganisms exhibit a clock-like proliferation pattern during the course of cadaver decomposition, forming the foundation for utilizing microbiology in PMI estimation. The establishment of PMI estimation models based on datasets from different seasons is of great practical significance. In this experiment, we conducted microbiota sequencing and analysis on gravesoil and mouse intestinal contents collected during both the winter and summer seasons and constructed a PMI estimation model using the Random Forest algorithm. The results showed that the MAE of the gut microbiota model in summer was 0.47 ± 0.26 d, R2 = 0.991, and the MAE of the gravesoil model in winter was 1.04 ± 0.22 d, R2 = 0.998. We propose that, in practical applications, it is advantageous to selectively build PMI estimation models based on seasonal variations. Additionally, through a combination of morphological observations, gravesoil microbiota sequencing results, and soil physicochemical data, we identified the time of cadaveric rupture for mouse cadavers, occurring at around days 24–27 in winter and days 6–9 in summer. This study not only confirms previous research findings but also introduces novel insights, contributing to the foundational knowledge necessary to advance the utilization of microbiota for PMI estimation.

Microbial communities can undergo significant successional changes during decay and decomposition, potentially providing valuable insights for determining the postmortem interval (PMI). The microbiota produce various gases that cause cadaver bloating, and rupture releases nutrient-rich bodily fluids into the environment, altering the soil microbiota around the carcasses. In this study, we aimed to investigate the underlying principles governing the succession of microbial communities during the decomposition of pig carcasses and the soil beneath the carcasses. At early decay, the phylum Firmicutes and Bacteroidota were the most abundant in both the winter and summer pig rectum. However, Proteobacteria became the most abundant in the winter pig rectum in late decay. Using genus as a biomarker to estimate the PMI could get the MAE from 1.375 days to 2.478 days based on the RF model. The abundance of bacterial communities showed a decreasing trend with prolonged decomposition time. There were statistically significant differences in microbial diversity in the two periods (pre-rupture and post-rupture) of the four groups (WPG 0–8Dvs. WPG 16–40D, p < 0.0001; WPS 0–16Dvs. WPS 24–40D, p = 0.003; SPG 0D vs. SPG 8–40D, p = 0.0005; and SPS 0D vs. SPS 8–40D, p = 0.0208). Most of the biomarkers in the pre-rupture period belong to obligate anaerobes. In contrast, the biomarkers in the post-rupture period belong to aerobic bacteria. Furthermore, the genus Vagococcus shows a similar increase trend, whether in winter or summer. Together, these results suggest that microbial succession was predictable and can be developed into a forensic tool for estimating the PMI.

目的 研究钝性抵抗伤与命案现场分析相关要素之间的关系,为法医学现场分析提供参考依据.方法对 50 例存在钝性抵抗伤的已破命案进行统计,分析钝性抵抗伤分布、数量、强弱程度等与涉案人的性别、年龄、致死部位、作案工具、作案动机等因素之间的关系.结果(1)手部钝性抵抗伤出现次数最多;(2)前臂与手部钝性抵抗伤存在正相关性,与大腿呈负相关;(3)锤类、棍棒类作案,手部、前臂钝性抵抗伤数量最高;徒手杀人案件,大腿钝性抵抗伤明显增高;(4)案犯为未成年人、老年人时,强抵抗出现的比例增高;(5)大腿钝性抵抗伤多出现在谋性案件;(6)涉案人关系不显著影响钝性抵抗伤的强弱.结论 致伤工具、作案动机能够影响钝性抵抗伤出现的部位及数量;钝性抵抗伤程度强指向案犯可能为未成年、老年人.

在性侵案件中,精阴混合斑检材是常见且具有重要证据价值的物证,如何从中分离出嫌疑人精子细胞并检出其STR分型,是破案的关键,更是法医DNA实验室必须解决的问题.目前,国内实验室主流应用的差异裂解法以及基于此原理的改良方法,都存在难以克服的缺点.微流控技术的不断发展为混合斑中精子细胞的分离带来了新思路,基于不同原理并不断演进的微流控芯片被研制出来以尝试解决此难题.本文从研究和应用进展角度对机械操控法、流体动力和捏流分选融合法、声波差异提取法、介电泳法、SLeX糖芯片法等5种用于精阴混合斑分离的不同类型微流控芯片进行了概述与简要比较.随着相关技术的不断发展和完善,推出具有体积小、速度快、效果稳定等优点,可以广泛适用于各级法医DNA实验室进行案件混合斑分离的芯片将指日可待.

混合STR分型的解释及分析一直是国际上法医物证领域研究的热点和难点.随着DNA检验技术的发展,案件中检出的混合STR分型呈现出模板量降低以及混合组分数增加的趋势,其解释变得愈加复杂,传统的人工分析方法已难以满足现实要求.近几年国外基于统计算法模型的自动化软件解析方法渐趋成为混合STR分型分析的主要方法.本文综述了混合STR分型分析方法的相关研究进展,包括人工为主的定性分析方法以及基于统计模型的基因型概率分析方法;讨论了混合STR分型分析方法的未来发展趋势以及人工智能技术的应用前景.

在我国,鸦片罂粟的违法种植是境内阿片类毒品的主要来源.利用新型、高效的分子标记对鸦片罂粟进行溯源推断可以从源头上对毒品进行铲除,对涉毒案件的侦破具有重要意义.但是,由于地域特异性分子标记的缺乏,我国法庭科学中鸦片罂粟DNA溯源推断方法及体系一直处于空白阶段.基于此,本研究应用RAD简化测序技术对国内3个地区鸦片罂粟植株及1个特殊的蒂巴因品种进行了群体简化测序和组装,并对其SNP位点进行了开发和特异性检测.鸦片罂粟各地域(品种)间的特异性SNP位点结果分别为:甘肃品种(bai)1988个,蒂巴因品种(T)9959个,郑州品种(ZZ)12 080个;武汉品种(WH)3 110个.本研究获得的一系列罂粟地域(品种)特异性SNP位点,为今后罂粟溯源体系的构建提供了充足的分子标记支持.RAD简化测序技术更是为毒品原植物溯源体系的构建提供了一种理想的特异性位点获取方法,对于涉毒案件中及时发现、铲除毒品源头具有十分重要的意义.

目的 研究利用鞋印作为寻找生物物证的指引,在作案人行走路线上尤其是鞋印周围提取生物物证的可能性及DNA检出率.方法 通过实验的方法,选择10名不同年龄的男性志愿者分别在室内地面常见的地板、瓷砖和地板革三种客体上正常行走形成鞋印,采用负压吸附和擦拭提取的方法分别提取鞋印上及其周围微量生物物证后进行DNA检测.结果 采用擦拭方法提取,瓷砖上鞋印DNA检出效果最好,检出率为22.5％,地板和地板革的检出率均为7.5％;采用负压吸附方法提取,地板上鞋印DNA的检出率为5％,地板革为2.5％,瓷砖未检出.结论 鞋印周围能够提取到微量生物物证并检出DNA.通过三种客体的比较,擦拭提取的方法较负压吸附法DNA检出率更高.

目的 建立基于微滤技术分离检验人血中脱落上皮细胞的新方法.方法 选用微孔滤膜并构建细胞分离过滤平台,优化过滤参数;制备15组混合细胞悬液,每组包含2个等比例混合的样本,1个进行常规DNA检验,另1个经过滤平台过滤,取滤膜作DNA检验,对比两者的STR分型结果,评判过滤平台的细胞分离效果.结果 当流量为250mL/h、滤膜孔径30μm时,白细胞滤除率可达90％以上,而脱落上皮细胞截留率不低于70％;对15组混合细胞悬液经分离检验,14组获得预期结果.结论 该方法可用于人血中脱落上皮细胞的分离检验,能够改善此类检材中目的细胞的STR分型结果,为刑事案件中血迹浸染的烟蒂等混合生物检材的细胞分离检验提供了一种新思路.

目前,国内刑事技术领域涉及木材DNA种属鉴定的方法尚属空白.在盗砍盗伐、非法走私、假冒仿造木材类案件中,常因木材种类无法判定造成案件无法侦办和诉讼.白木香(Aquilaria sinensis)又称沉香,为桃金娘目(Myrtales)瑞香科(Thymelaeaceae)沉香属(Aquilaria),是木材市场炙手可热的木材种类.近几年,DNA条形码(DNA barcoding)[1-2]技术发展迅速,方法成熟稳定,已广泛应用于动植物的种属鉴定中.本文基于DNA条形码技术,建立识别木材种属的方法,并对1例市售疑似白木香木材进行检验,为将来涉及木材类案件中木材种属的鉴定提供一定的参考.

罂粟作为鸦片及海洛因的毒品原植物,在非法种植与运输案件物证检测中,其物种鉴定一直是案件侦破和定性的关键.本文综合分析了国内外有关罂粟遗传分子标记研究的现状,针对鸦片罂粟SSR及SNP标记缺乏这一难题,阐述了简化基因组测序技术应用于罂粟标记开发的可能和前景.

ABSTRACT:Due to the increase of floating population, the current trans-regional and cross-boundary crimes increase signiifcantly. Human phenotype description studies covering race, age, appearance and other physiological characteristics, are of high interest in genetic association studies. With the extracted genetic information, the biologic evidence could reveal its origin and aid in criminal investigation. Among these is racial inference, which remains an important topic in forensic context. Ancestry informative markers (AIMs) are genetic sites with great different frequency between populations. It can be used to describe the genetic components of a population, to infer the ancestral origin of a DNA sample and then the possible physical characteristics of DNA donor. Of those said above, single nucleotide polymorphism (SNP) is the most commonly used because of its larger number and wider distribution in genome. The panel of SNPs can be designed by calculating the genetic parameters such as Fst, In, and others of the kind. The available techniques for SNP typing include multiple single base extension SNP (SNaPshot), SNPstream and MassArray. Many panels of ancestry informative SNPs have been proposed in recent years. These techniques are playing important roles in practical cases and thus enhance the ability of forensic genetic technology in mining human genetic information. Here we present the development, application and the research on the inference of human race from DNA evidence, aiming to provide a reference for further studies and the application of this technology in a wide range.