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The PowerPlex® 35GY System (Promega, USA) is an advanced eight-dye multiplex STR kit, incorporating twenty-three autosomal STR loci, eleven Y chromosome STR loci, one sex determining marker Amelogenin, and two quality indicators. This multiplex system includes 20 CODIS loci and up to 15 mini-STR loci with sizing values less than 250 bases. In this study, validation for PowerPlex® 35GY System was conducted following the guidelines of SWGDAM, encompassing sensitivity, precision, accuracy, concordance, species specificity, stutter, mixture, stability, and degraded DNA. The results from experiments demonstrated that the PowerPlex® 35GY System could effectively amplify DNA samples, with complete allele detection achieved at 125 pg. Moreover, over 90% of alleles from minor contributors were detected at a mixed ratio of 1:4. Additionally, the system was found to yield full profiles even in the presence of hematin, humic acid, and indigo. The PowerPlex® 35GY System demonstrated superior performance in the sensitivity and degraded DNA studies compared to a six-dye STR kit. Hence, it is evident that the PowerPlex® 35GY System is well-suited for forensic practice, whether in casework or for database samples. These findings provide strong support for the efficacy and reliability of the PowerPlex® 35GY System in forensic applications.
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INTRODUCTION: In China, standard smoking cessation practices are rarely used by healthcare service providers (HSPs). WeChat, a popular social media app, has been widely used in China. METHODS: In this single-blind, randomized trial, undertaken in China with 8-week interventions and follow-up to 34 weeks, 1887 HSPs were randomly selected to the intervention (n=942) or control group (n=945) from Oct 2020 to Oct 2021. The intervention group received regular smoking cessation training program messages from the professional team for 8 weeks and followed for 34 weeks. The control group received thanks messages for 8 weeks, and follow-up to 34 weeks. Both groups received a hard copy of the manual after randomization. The primary outcome measure was the utilization rate of behavioral and pharmacotherapy interventions for smoking patients from 9 to 34 weeks. This trial is registered at ClinicalTrials.gov (number NCT03556774). RESULTS: HSPs in the intervention group demonstrated a better overall utilization rate of smoking cessation at 20-week follow-up compared to the control group (35.54% vs 31.41%, p=0.036). Additionally, both groups showed a significant increase in the adoption of various components of the 5A's model - including "Assess", "Assist: set a quit date", "Assist: recommend cessation program", "Assist: provide information", "Assist: recommend medication", and "Arrange" - at the 9-week follow-up relative to baseline. Notably, at the 20-week follow-up, the intervention group reported significantly enhanced utilization rates for all these components, except "Assist: set a quit date". CONCLUSIONS: The "Wechat Wequit" training program effectively enhanced smoking cessation intervention adoption among Chinese HSPs. IMPLICATION: 'WeChat WeQuit' training program was effective in increasing the provision of effective tobacco cessation interventions by Chinese-speaking HSPs to patients with cigarette smoking, which could provide valuable insights into bridging the gap between need and services for smoking cessation in China.
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Background: The expression profiles of differentially expressed genes (DEGs) during pupal development have been demonstrated to be vital in age estimation of forensic entomological study. Here, using forensically important Aldrichina grahami (Diptera: Calliphoridae), we aimed to explore the potential of intrapuparial stage aging and postmortem interval (PMI) estimation based on characterization of successive developmental transcriptomes and gene expression patterns. Methods: We collected A. grahami pupae at 11 successive intrapuparial stages at 20 °C and used the RNA-seq technique to build the transcriptome profiles of their intrapuparial stages. The DEGs were identified during the different intrapuparial stages using comparative transcriptome analysis. The selected marker DEGs were classified and clustered for intrapuparial stage aging and PMI estimation and then further verified for transcriptome data validation. Ultimately, we categorized the overall gene expression levels as the dependent variable and the age of intrapuparial A. grahami as the independent variable to conduct nonlinear regression analysis. Results: We redefined the intrapuparial stages of A. grahami into five key successive substages (I, II, III, IV, and V), based on the overall gene expression patterns during pupal development. We screened 99 specific time-dependent expressed genes (stage-specific DEGs) to determine the different intrapuparial stages based on comparison of the gene expression levels during the 11 developmental intrapuparial stages of A. grahami. We observed that 55 DEGs showed persistent upregulation during the development of intrapuparial A. grahami. We then selected four DEGs (act79b, act88f, up and ninac) which presented consistent upregulation using RT-qPCR (quantitative real-time PCR) analysis, along with consideration of the maximum fold changes during the pupal development. We conducted nonlinear regression analysis to simulate the calculations of the relationships between the expression levels of the four selected DEGs and the developmental time of intrapuparial A. grahami and constructed fitting curves. The curves demonstrated that act79b and ninac showed continuous relatively increasing levels. Conclusions: This study redefined the intrapuparial stages of A. grahami based on expression profiles of developmental transcriptomes for the first time. The stage-specific DEGs and those with consistent tendencies of expression were found to have potential in age estimation of intrapuparial A. grahami and could be supplementary to a more accurate prediction of PMI.
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Blood-containing mixtures are frequently encountered at crime scenes involving violence and murder. However, the presence of blood, and the association of blood with a specific donor within these mixtures present significant challenges in forensic analysis. In light of these challenges, this study sought to address these issues by leveraging blood-specific methylation sites and closely linked microhaplotype sites, proposing a novel composite genetic marker known as "blood-specific methylation-microhaplotype". This marker was designed to the detection of blood and the determination of blood donor within blood-containing mixtures. According to the selection criteria mentioned in the Materials and Methods section, we selected 10 blood-specific methylation-microhaplotype loci for inclusion in this study. Among these loci, eight exhibited blood-specific hypomethylation, while the remaining two displayed blood-specific hypermethylation. Based on data obtained from 124 individual samples in our study, the combined discrimination power (CPD) of these 10 successfully sequenced loci was 0.999999298. The sample allele methylation rate (Ram) was obtained from massive parallel sequencing (MPS), which was defined as the proportion of methylated reads to the total clustered reads that were genotyped to a specific allele. To develop an allele type classification model capable of identifying the presence of blood and the blood donor, we used the Random Forest algorithm. This model was trained and evaluated using the Ram distribution of individual samples and the Ram distribution of simulated shared alleles. Subsequently, we applied the developed allele type classification model to predict alleles within actual mixtures, trying to exclude non-blood-specific alleles, ultimately allowing us to identify the presence of blood and the blood donor in the blood-containing mixtures. Our findings demonstrate that these blood-specific methylation-microhaplotype loci have the capability to not only detect the presence of blood but also accurately associate blood with the true donor in blood-containing mixtures with the mixing ratios of 1:29, 1:19, 1:9, 1:4, 1:2, 2:1, 7:1, 8:1, 31:1 and 36:1 (blood:non-blood) by DNA mixture interpretation methods. In addition, the presence of blood and the true blood donor could be identified in a mixture containing four body fluids (blood:vaginal fluid:semen:saliva = 1:1:1:1). It is important to note that while these loci exhibit great potential, the impact of allele dropouts and alleles misidentification must be considered when interpreting the results. This is a preliminary study utilising blood-specific methylation-microhaplotype as a complementary tool to other well-established genetic markers (STR, SNP, microhaplotype, etc.) for the analysis in blood-containing mixtures.