A Bibliometric and Visual Analysis of the Current Status and Trends of Forensic Mixed Stain Research.

OBJECTIVES: To explore the context and hotspot changes of forensic mixed stain research through bibliometric approach. METHODS: The literature of forensic mixed stain included in the core collection of Web of Science database from 2011 to 2022 were collected as the study object, and the annual publication number, countrie (region), institution, journal, keywords, etc. were bibliometrically and visually analyzed using the R-based Bibliometrix 1.1.6 package and VOSviewer 1.6.18 software. RESULTS: A total of 732 articles on forensic mixed stain were included from 2011 to 2022, with the annual number of articles published and the annual citation frequency showing a steady increase year by year. Among the 59 countries (regions) with the most published articles, the United States ranked first with 246 articles, followed by China with 153 articles. The literature came from 104 journals, and the total number of articles published in the top 10 journals was 633. FORENSIC SCI INT GENET ranked first with 307 articles. Visual analysis using VOSviewer software showed that keywords could be divided into four research clusters, namely the genetic marker development group (blue), the mixed stain typing analysis theory group (red), the sequencing analysis group (yellow), and the case sample research group (green). It can be divided into four development stages in terms of different time periods: early development (2011-2013), middle development (2014-2016), rapid development (2017-2020) and latest development (2021-2022). CONCLUSIONS: The number of publications by domestic and foreign scholars in the study of mixed stain in forensic science is showing a relatively stable trend. Machine learning, next generation sequencing and other research have been the hottest topics that have attracted the most attention in recent years, which is expected to further develop the theory of mixed stain typing and sequencing analysis in forensic mixed stain research.

Analysis of Genetic Polymorphism and Population Genetic Structure of 57 Autosomal InDel Loci in Beichuan Qiang Population.

OBJECTIVES: To investigate the genetic information of 57 autosomal InDel loci (A-InDels) included in AGCU InDel 60 fluorescence detection kit in the Beichuan Qiang population of Sichuan Province and evaluate its application value in forensic medicine. METHODS: A total of 200 unrelated healthy individuals from Beichuan Qiang population of Sichuan Province were typing detected by AGCU InDel 60 fluorescence detection kit. Allele frequencies and population genetic parameters of the 57 A-InDels were statistically analyzed and compared with the available data of 26 populations. RESULTS: After Bonferroni correction, there was no linkage disequilibrium between the 57 A-InDels, and all loci were in Hardy-Weinberg equilibrium. Except for rs66595817 and rs72085595, the minor allele frequencies of 55 A-InDels were above 0.3. PIC ranged from 0.298 3 to 0.375 0, CDP was 1-2.974 8×10-24, CPEduo was 0.999 062 660, and CPEtrio was 0.999 999 999. The calculation of the genetic distance showed that Beichuan Qiang population had the closest genetic distances with Beijing Han and South China Han populations, but far away from African populations. CONCLUSIONS: The 57 A-InDels in AGCU InDel 60 fluorescence detection kit have a good genetic polymorphism in Beichuan Qiang population of Sichuan Province, which can be used as effective supplemental for individual identification and paternity identification in forensic medicine.

Actual mutational research of 19 autosomal STRs based on restricted mutation model and big data.

Short tandem repeat (STR) markers have been widely used in forensic paternity testing and individual identification, but the STR mutation might impact on the forensic result interpretation. Importantly, the STR mutation rate was underestimated due to ignoring the "hidden" mutation phenomenon in most similar studies. Considering this, we use Slooten and Ricciardi's restricted mutation model based on big data to obtain more accurate mutation rates for each marker. In this paper, the mutations of 20 autosomal STRs loci (D3S1358, D1S1656, D13S317, Penta E, D16S539, D18S51, D2S1338, CSF1PO, Penta D, TH01, vWA, D21S11, D6S1043, D7S820, D5S818, TPOX, D8S1179, D12S391, D19S433, and FGA; The restricted model does not include the correction factor of D6S1043, this paper calculates remaining 19 STR loci mutation rates) were investigated in 28,313 (Total: 78,739 individuals) confirmed parentage-testing cases in Chinese Han population. As a result, total 1665 mutations were found in all loci, including 1614 one-steps, 34 two-steps, 8 three-steps, and 9 nonintegral mutations. The loci-specific average mutation rates ranged from 0.00007700 (TPOX) to 0.00459050 (FGA) in trio's and 0.00000000 (TPOX) to 0.00344850 (FGA) in duo's. We analyzed the relationship between mutation rates of the apparent and actual, the trio's and duo's, the paternal and maternal, respectively. The results demonstrated that the actual mutation rates are more than the apparent mostly, and the values of µ1"/µ2"(apparent) are also greater than µ1/µ2 (actual) commonly (µ1", µ1; µ2", µ2 are the mutation rates of one-step and two-step). Therefore, the "hidden" mutations are identified. In addition, the mutations rates of trio's and duo's, the paternal and maternal, exhibit significant difference. Next, those mutation data are used to do a comparison with the studies of other Han populations in China, which present the temporal and regional disparities. Due to the large sample size, some rare mutation events, such as monozygotic (MZ) mutation and "fake four-step mutation", are also reported in this study. In conclusion, the estimation values of actual mutations are obtained based on big data, they can not only provide basic data for the Chinese forensic DNA and population genetics databases, but also have important significance for the development of forensic individual identification, paternity testing and genetics research.

Beating of grafted chains induced by active Brownian particles.

We study the interplay between active Brownian particles (ABPs) and a "hairy" surface in two-dimensional geometry. We find that the increase of propelling force leads to and enhances inhomogeneous accumulation of ABPs inside the brush region. Oscillation of chain bundles (beating like cilia) is found in company with the formation and disassembly of a dynamic cluster of ABPs at large propelling forces. Meanwhile chains are stretched and pushed down due to the effective shear force by ABPs. The decrease of the average brush thickness with propelling force reflects the growth of the beating amplitude of chain bundles. Furthermore, the beating phenomenon is investigated in a simple single-chain system. We find that the chain swings regularly with a major oscillatory period, which increases with chain length and decreases with the increase of propelling force. We build a theory to describe the phenomenon and the predictions on the relationship between the period and amplitude for various chain lengths, and propelling forces agree very well with simulation data.

Enhancing testing efficacy of high-density SNP microarrays to distinguish pedigrees belonging to the same kinship class.

Kinship testing, which involves genotyping genetic markers and comparing their profiles between individuals, holds significant applications in forensic science. However, the prevalent use of independent markers often lacks the discriminatory power to distinguish pedigrees belong to the same kinship class. While numerous studies have attempted to address this challenge through diverse approaches, the testing efficacy of high-density SNP microarrays in combination with the likelihood approach remains unclear. In this study, we further explored the utilization of linked autosomal SNPs derived from microarrays with the likelihood approach. Several SNP panels with differing numbers of loci were developed and putative pedigrees were constructed to evaluated to test their efficacy in distinguishing second-degree relationships, including grandparent-grandchild, half-siblings, and avuncular. Our findings indicate that the use of high-density SNP microarrays is theoretically feasible for discriminating second-degree relationships, with balanced classification rates ranging from 0.444 to 0.853. Moreover, to optimize the practical effectiveness of discriminating pedigrees belonging to the same kinship class, several other aspects such as adding additional SNPs or an additional relative and examining the effects of genotype errors and population selection were discussed. Our results revealed that the employment of denser marker sets with more accurate genotyping methods may be beneficial. Additionally, the inclusion of additional relatives and the selection of an appropriate reference population also appear to be crucial factors for enhancing the accuracy of kinship testing. In conclusion, our study provides insights into the potential of high-density SNPs in kinship testing and highlights the need for further optimization and examination into various factors that may contribute to enhancing testing efficacy.