Ultrathin In2O3thin-film transistors deposited from trimethylindium and ozone.

Indium oxide (In2O3) is a promising channel material for thin-film transistors (TFTs). In this work, we develop an atomic layer deposition (ALD) process of using trimethylindium and ozone (O3) to deposit In2O3films and fabricate ultrathin In2O3TFTs. The In2O3TFTs with 4 nm channel thickness show generally good switching characteristics with a highIon/Ioffof 108, a high mobility (µFE) of 16.2cm2V-1s-1and a positive threshold voltage (Vth) of 0.48 V. Although the 4 nm In2O3TFTs exhibit short channel effect, it can be improved by adding an ALD Ga2O3capping layer to afford the bilayer In2O3/Ga2O3channel structure. The afforded In2O3/Ga2O3TFTs exhibit improved immunity to the short channel effect, with good TFT characteristics ofIon/Ioffof 107,µFEof 9.3cm2V-1s-1, and positiveVthof 2.23 V. Overall, the thermal budget of the entire process is only 400 °C, which is suitable for the display and CMOS back-end-of-line-compatible applications.

Integrative lncRNA, circRNA, and mRNA analysis reveals expression profiles of six forensic body fluids/tissue.

RNAs have attracted much attention in forensic body fluid/tissue identification (BFID) due to their tissue-specific expression characteristics. Among RNAs, long RNAs (e.g., mRNA) have a higher probability of containing more polymorphic sites that can be used to assign the specific donor of the body fluid/tissue. However, few studies have characterized their overall profiles in forensic science. In this study, we sequenced the transcriptomes of 30 samples from venous blood, menstrual blood, semen, saliva, vaginal secretion, and skin tissue, obtaining a comprehensive picture of mRNA, lncRNA, and circRNA profiles. A total of 90,305 mRNAs, 102,906 lncRNAs (including 19,549 novel lncRNAs), and 40,204 circRNAs were detected. RNA type distribution, length distribution, and expression distribution were presented according to their annotation and expression level, and many novel body fluid/tissue-specific RNA markers were identified. Furthermore, the cognate relations among the three RNAs were analyzed according to gene annotations. Finally, SNPs and InDels from RNA transcripts were genotyped, and 21,611 multi-SNP and 4,471 multi-InDel transcriptomic microhaplotypes (tMHs) were identified. These results provide a comprehensive understanding of transcriptome profiles, which could provide new avenues for tracing the origin of the body fluid/tissue and identifying an individual.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study.

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Comparison of three massively parallel sequencing platforms for single nucleotide polymorphism (SNP) genotyping in forensic genetics.

Three MPS platforms are being used in forensic genetic analysis, i.e., MiSeq FGx, Ion S5 XL, and MGISEQ-2000. However, few studies compared their performance. In this study, we sequenced 83 common SNPs of 71 samples using the ForenSeq™ DNA Signature Prep Kit on MiSeq FGx, the Precision ID Identity Panel on Ion S5 XL, and the MGIEasy Signature Identification Library Prep Kit on MGISEQ-2000 and then the performance was compared. Results showed that the MiSeq FGx had the highest sequence quality but the lowest sequencing depth and allele balance. Discordant genotypes were observed at six SNPs, which may be caused by variants at primer binding regions, indel errors, or misalignments. Besides, two kinds of background noises, allele-specific miscalled reads (ASMR) and allele-nonspecific miscalled reads (ANMR), were characterized. MGISEQ-2000 showed the highest level of ASMR while Ion S5 XL had the highest level of ANMR. Site- and genotype-dependent miscalled patterns were observed at several SNPs on Ion S5 XL and MGISEQ-2000, but few on MiSeq FGx. In conclusion, the three MPS platforms perform differently with respect to sequencing quality, sequencing depth, allele balance, concordance, and background noise. These findings may be useful for data comparison, mixture deconvolution, and heteroplasmy analysis in forensic genetics.