Temporal Assessment of Protein Stability in Dried Blood Spots.

The use of protein biomarkers in blood for clinical settings is limited by the cost and accessibility of traditional venipuncture sampling. The dried blood spot (DBS) technique offers a less invasive and more accessible alternative. However, protein stability in DBS has not been well evaluated. Herein, we deployed a quantitative LC-MS/MS system to construct proteomic atlases of whole blood, DBSs, plasma, and blood cells. Approximately 4% of detected proteins' abundance was significantly altered during blood drying into blood spots, with overwhelming disturbances in cytoplasmic fraction. We also reported a novel finding suggesting a decrease in the level of membrane/cytoskeletal proteins (SLC4A1, RHAG, DSC1, DSP, and JUP) and an increase in the level of proteins (ATG3, SEC14L4, and NRBP1) related to intracellular trafficking. Furthermore, we identified 19 temporally dynamic proteins in DBS samples stored at room temperature for up to 6 months. There were three declined cytoskeleton-related proteins (RDX, SH3BGRL3, and MYH9) and four elevated proteins (XPO7, RAN, SLC2A1, and SLC29A1) involved in cytoplasmic transport as representatives. The instability was governed predominantly by hydrophilic proteins and enhanced significantly with an increasing storage time. Our analyses provide comprehensive knowledge of both short- and long-term storage stability of DBS proteins, forming the foundation for the widespread use of DBS in clinical proteomics and other analytical applications.

Technical strategy for monozygotic twin discrimination by single-nucleotide variants.

Monozygotic (MZ) twins are theoretically genetically identical. Although they are revealed to accumulate mutations after the zygote splits, discriminating between twin genomes remains a formidable challenge in the field of forensic genetics. Single-nucleotide variants (SNVs) are responsible for a substantial portion of genetic variation, thus potentially serving as promising biomarkers for the identification of MZ twins. In this study, we sequenced the whole genome of a pair of female MZ twins when they were 27 and 33 years old to approximately 30 × coverage using peripheral blood on an Illumina NovaSeq 6000 Sequencing System. Potentially discordant SNVs supported by whole-genome sequencing were validated extensively by amplicon-based targeted deep sequencing and Sanger sequencing. In total, we found nine bona fide post-twinning SNVs, all of which were identified in the younger genomes and found in the older genomes. None of the SNVs occurred within coding exons, three of which were observed in introns, supported by whole-exome sequencing results. A double-blind test was employed, and the reliability of MZ twin discrimination by discordant SNVs was endorsed. All SNVs were successfully detected when input DNA amounts decreased to 0.25 ng, and reliable detection was limited to seven SNVs below 0.075 ng input. This comprehensive analysis confirms that SNVs could serve as cost-effective biomarkers for MZ twin discrimination.

Epigenetic regulation of human-specific gene expression in the prefrontal cortex.

BACKGROUND: Changes in gene expression levels during brain development are thought to have played an important role in the evolution of human cognition. With the advent of high-throughput sequencing technologies, changes in brain developmental expression patterns, as well as human-specific brain gene expression, have been characterized. However, interpreting the origin of evolutionarily advanced cognition in human brains requires a deeper understanding of the regulation of gene expression, including the epigenomic context, along the primate genome. Here, we used chromatin immunoprecipitation sequencing (ChIP-seq) to measure the genome-wide profiles of histone H3 lysine 4 trimethylation (H3K4me3) and histone H3 lysine 27 acetylation (H3K27ac), both of which are associated with transcriptional activation in the prefrontal cortex of humans, chimpanzees, and rhesus macaques. RESULTS: We found a discrete functional association, in which H3K4me3HP gain was significantly associated with myelination assembly and signaling transmission, while H3K4me3HP loss played a vital role in synaptic activity. Moreover, H3K27acHP gain was enriched in interneuron and oligodendrocyte markers, and H3K27acHP loss was enriched in CA1 pyramidal neuron markers. Using strand-specific RNA sequencing (ssRNA-seq), we first demonstrated that approximately 7 and 2% of human-specific expressed genes were epigenetically marked by H3K4me3HP and H3K27acHP, respectively, providing robust support for causal involvement of histones in gene expression. We also revealed the co-activation role of epigenetic modification and transcription factors in human-specific transcriptome evolution. Mechanistically, histone-modifying enzymes at least partially contribute to an epigenetic disturbance among primates, especially for the H3K27ac epigenomic marker. In line with this, peaks enriched in the macaque lineage were found to be driven by upregulated acetyl enzymes. CONCLUSIONS: Our results comprehensively elucidated a causal species-specific gene-histone-enzyme landscape in the prefrontal cortex and highlighted the regulatory interaction that drove transcriptional activation.

Kernel Partial Least Squares Feature Selection Based on Maximum Weight Minimum Redundancy.

Feature selection refers to a vital function in machine learning and data mining. The maximum weight minimum redundancy feature selection method not only considers the importance of features but also reduces the redundancy among features. However, the characteristics of various datasets are not identical, and thus the feature selection method should have different feature evaluation criteria for all datasets. Additionally, high-dimensional data analysis poses a challenge to enhancing the classification performance of the different feature selection methods. This study presents a kernel partial least squares feature selection method on the basis of the enhanced maximum weight minimum redundancy algorithm to simplify the calculation and improve the classification accuracy of high-dimensional datasets. By introducing a weight factor, the correlation between the maximum weight and the minimum redundancy in the evaluation criterion can be adjusted to develop an improved maximum weight minimum redundancy method. In this study, the proposed KPLS feature selection method considers the redundancy between the features and the feature weighting between any feature and a class label in different datasets. Moreover, the feature selection method proposed in this study has been tested regarding its classification accuracy on data containing noise and several datasets. The experimental findings achieved using different datasets explore the feasibility and effectiveness of the proposed method which can select an optimal feature subset and obtain great classification performance based on three different metrics when compared with other feature selection methods.

Age Estimation Based on DNA Methylation and Its Application Prospects in Forensic Medicine.

With the improvement of DNA methylation detection techniques, studies on age-related methylation sites have found more age-specific ones across tissues, which improves the sensitivity and accuracy of age estimation. In addition, the establishment of various statistical models also provides a new direction for the age estimation of tissues from different sources. This review summarizes the related studies of age estimation based on DNA methylation from the aspects of detection technology, age-related cytosine phosphate guanine site and model selection in recent years.

Cross-Platform Application of DNA Methylation Age Estimation Model in Eastern Chinese Han Population.

OBJECTIVES: To evaluate the forensic application value of an age estimation model based on DNA methylation in eastern Chinese Han population, and to provide a theoretical basis for exploring age estimation models suitable for different detection platforms. METHODS: According to the 6 age-related methylation sites in the published blood DNA methylation age estimation models of Chinese Han population, the DNA methylation level of 48 samples was detected by pyrosequencing and next-generation sequencing (NGS). After submitting DNA methylation levels to the age estimation model, the DNA methylation ages were predicted and compared with their real ages. RESULTS: The 6 DNA methylation sites in both detection techniques were age-related, with an R2 of 0.85 and a median absolute deviation (MAD) of 4.81 years when using pyrosequencing；with an R2 of 0.84 and MAD of 4.41 years when using NGS. CONCLUSIONS: The blood DNA methylation age estimation model can be used under pyrosequencing and multi-purpose regional methylation enrichment sequencing technology based on NGS and it can accurately estimate the age.

Proteomic Difference Analysis of Whole Blood and Bloodstains.

OBJECTIVES: To study the changes of protein levels in peripheral blood after it dried. METHODS: The proteins from whole blood and bloodstains were detected by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and normalized by the label-free quantification (LFQ) method. The differential proteins were analyzed by using R 4.2.1 software, limma and edgeR package. The analysis of biological function, signaling pathway and subcellular localization for the differential proteins was then performed. RESULTS: A total of 623 and 596 proteins were detected in whole blood and bloodstains, respectively, of which 31 were statistically significant in the quantitative results, including 10 up-regulated and 21 down-regulated proteins in bloodstains. CONCLUSIONS: The protein abundances in whole blood and bloodstains are highly correlated, and the variation of protein abundances may be related to the changes of endogenous and structural proteins in cells. The application of proteomics technology can assist the screening and identification of protein biomarkers, thereby introducing new biomarkers for forensic research.

Investigation on Rupture Initiation and Propagation of Traffic Tunnel under Seismic Excitation Based on Acoustic Emission Technology.

Traffic tunnels are important engineering structures in transportation, and their stability is critical to traffic safety. In particular, when these tunnels are in an earthquake-prone area, the rupture process under seismic excitation needs to be studied in depth for safer tunnel design. In this paper, based on a construction project on the Nairobi-Malaba railway in East Africa, a laboratory shaking table test with 24 working cases of seismic excitation on a mountain tunnel is designed, and the acoustic emission (AE) technique is employed to investigate the tunnel rupture process. The results show that the high frequency components between 20 and 30 kHz of AE signals are the tunnel rupturing signals under the seismic excitation under such conditions. The tunnel vault and the arch foot are prone to rupture during the seismic excitation, and the initial rupture in the arch foot and vault of the tunnel occur under the horizontal and vertical Kobe wave seismic excitation, respectively, with a maximum acceleration of 0.4 g. After the rupture initiation, the tunnel arch foot continues to rupture in the subsequent working cases regardless of whether the excitation direction is horizontal or vertical, while the tunnel vault does not rupture continuously with the implementation of the subsequent excitations. Moreover, the Kobe seismic wave has a higher degree of damage potential to underground structures than the El seismic wave.

Efficiency Analysis of Uncle-Nephew Relationship Identification by Increasing STR Markers and Adding Reference Samples.

OBJECTIVES: To estimate the system efficiency of uncle-nephew relationship identification by increasing STR markers and adding reference samples based on the test results of simulated data and real samples, so as to provide references for selecting the appropriate number of STRs and reference samples for uncle-nephew relationship identification. METHODS: Five common models of uncle-nephew relationship identification were constructed by adding different reference samples. In each model, the likelihood ratio (LR) for 10 000 pairs of uncle-nephew relationships and 10 000 pairs of unrelated individuals were simulated by detecting 19, 39 or 55 STRs, and the system efficiency at different thresholds was simulated. The samples of the Han population in Zhejiang were collected, and 55 autosomal STRs were obtained by using SiFaSTRTM 23plex kit, Goldeneye® DNA ID 22NC kit and AGCU 21+1 PCR amplification kit. When 19, 39 and 55 STRs were detected, the LR of each model and system efficiency under different thresholds were calculated and compared with the simulation results. RESULTS: Under the same detection system, the calculated results of simulated data and corresponding true samples were basically consistent. In the same model, there was a positive correlation between the system efficiency of uncle-nephew relationship identification and the number of STRs detected. Moreover, the system efficiency of introducing relatives was higher than identifying only two individuals. The order of preference for the introduction of relatives was the full sibling (or mother) of the uncle and the full sibling (or mother) of the nephew. CONCLUSIONS: The system efficiency of uncle-nephew relationship identification could be improved by increasing the number of STRs and introducing known relatives, which would provide the basis for selecting the most appropriate detection system and reference individuals in actual cases.

Effects of Peripheral Blood Different Pretreatment Methods and Preservation Time on RNA Quality.

OBJECTIVES: To evaluate the effects of different pretreatment methods and preservation time on RNA quality of peripheral blood samples, and to optimize the preservation method of peripheral blood samples. METHODS: Eight pretreatment methods were used to preprocess the peripheral blood from 3 healthy unrelated individuals and the treated samples were stored at -80 ℃. Total RNA of samples was extracted using Quick-RNATM Miniprep Plus kit. DNA/RNA ShieldTM was added to peripheral blood and total RNA was extracted after preservation at -80 ℃ for 0, 5, 10, 15, 30 and 60 days, respectively. The concentration, purity and integrity of RNA were determined. Statistical analyses were performed by SPSS 22.0 software to compare the differences in RNA yield, purity and integrity among the eight pretreatment methods. RESULTS: In terms of purity, leukocyte pretreated with RNAlaterTM and directly cryopreservation peripheral blood showed the worst purity. The other six methods showed better purity. In terms of yield, blood cells with DNA/RNA ShieldTM came out with the highest yield, followed by peripheral blood with DNA/RNA ShieldTM. In terms of integrity, peripheral blood preserved in PAXgene Blood RNA tube method had the best integrity. Except for peripheral blood pretreated with DNA/RNA ShieldTM and blood cells pretreated with DNA/RNA shieldTM, the other five methods had statistical differences when compared to the method by keeping peripheral blood in PAXgene Blood RNA tube. The purity of RNA stored at six-time gradients ranged from 1.815 to 1.952. With the increase of storage time, RNA yield decreased from 4.516 ng to 1.039 ng, and RNA integrity decreased from 8.533 to 7.150. CONCLUSIONS: According to the results of total RNA's yield, purity and integrity, peripheral blood pretreated with DNA/RNA ShieldTM was the best pretreatment method. After the pretreatment, samples can be preserved for up to 60 days in low temperature.

Disruption of an Evolutionarily Novel Synaptic Expression Pattern in Autism.

Cognitive defects in autism spectrum disorder (ASD) include socialization and communication: key behavioral capacities that separate humans from other species. Here, we analyze gene expression in the prefrontal cortex of 63 autism patients and control individuals, as well as 62 chimpanzees and macaques, from natal to adult age. We show that among all aberrant expression changes seen in ASD brains, a single aberrant expression pattern overrepresented in genes involved synaptic-related pathways is enriched in nucleotide variants linked to autism. Furthermore, only this pattern contains an excess of developmental expression features unique to humans, thus resulting in the disruption of human-specific developmental programs in autism. Several members of the early growth response (EGR) transcription factor family can be implicated in regulation of this aberrant developmental change. Our study draws a connection between the genetic risk architecture of autism and molecular features of cortical development unique to humans.

Modeling Flaw Pulse-Echo Signals in Cylindrical Components Using an Ultrasonic Line-Focused Transducer with Consideration of Wave Mode Conversion.

Investigations on flaw responses can benefit the nondestructive testing of cylinders using line-focused transducers. In this work, the system function, the wave beam model, and a flaw scattering model are combined to develop an ultrasonic measurement model for line-focused transducers to predict flaw responses in cylindrical components. The system function is characterized using reference signals by developing an acoustic transfer function for line-focused transducers, which works at different distances for both planar and curved surfaces. The wave beams in cylindrical components are modeled using a multi-Gaussian beam model, where the effects of wave mode conversion and curvatures of cylinders are considered. Simulation results of wave beams are provided to analyze their propagation behaviors. The proposed ultrasonic measurement model is certified from good agreement between the experimental and predicted signals of side-drilled holes. This work provides guidance for evaluating the detection ability of line-focused transducers in cylindrical component testing applications.

Human brain evolution: transcripts, metabolites and their regulators.

What evolutionary events led to the emergence of human cognition? Although the genetic differences separating modern humans from both non-human primates (for example, chimpanzees) and archaic hominins (Neanderthals and Denisovans) are known, linking human-specific mutations to the cognitive phenotype remains a challenge. One strategy is to focus on human-specific changes at the level of intermediate phenotypes, such as gene expression and metabolism, in conjunction with evolutionary changes in gene regulation involving transcription factors, microRNA and proximal regulatory elements. In this Review we show how this strategy has yielded some of the first hints about the mechanisms of human cognition.

Exceptional evolutionary divergence of human muscle and brain metabolomes parallels human cognitive and physical uniqueness.

Metabolite concentrations reflect the physiological states of tissues and cells. However, the role of metabolic changes in species evolution is currently unknown. Here, we present a study of metabolome evolution conducted in three brain regions and two non-neural tissues from humans, chimpanzees, macaque monkeys, and mice based on over 10,000 hydrophilic compounds. While chimpanzee, macaque, and mouse metabolomes diverge following the genetic distances among species, we detect remarkable acceleration of metabolome evolution in human prefrontal cortex and skeletal muscle affecting neural and energy metabolism pathways. These metabolic changes could not be attributed to environmental conditions and were confirmed against the expression of their corresponding enzymes. We further conducted muscle strength tests in humans, chimpanzees, and macaques. The results suggest that, while humans are characterized by superior cognition, their muscular performance might be markedly inferior to that of chimpanzees and macaque monkeys.

Fluorescence-Enhanced Sensing of Hypochlorous Acid Based on 2-Pyridylthiazole Unit.

Hypochlorous acid, being one of reactive oxygen species (ROS), is essential to protect the body against invasion of pathogens. Excess of hypochlorous acid (HOCl) is believed to be in tight connection with various inflammation-related diseases. It remains a challenge to detect the ROS in physiological conditions (aqueous buffer and neutral pH) with selectivity. In the presented paper, we have synthesized a ferrocence-modified pyridylthiazole derivatives, 1,4-di{5-[(4'-ferrocenyl-2'-(4"-pyridyl)]thiazinyl}benzene (DFPT). Only HOCl could turn-on the fluorescence of DFPT with enhanced emission at 465 nm. Compared to the other reported HOCl sensors, DFPT could selectively detect HOCl with rapid response (< 60 s) in the aqueous buffer (pH = 7.0). The detection limit at pH = 7.0 was 0.7 µM according to the titration experiment.

Extension of cortical synaptic development distinguishes humans from chimpanzees and macaques.

Over the course of ontogenesis, the human brain and human cognitive abilities develop in parallel, resulting in a phenotype strikingly distinct from that of other primates. Here, we used microarrays and RNA-sequencing to examine human-specific gene expression changes taking place during postnatal brain development in the prefrontal cortex and cerebellum of humans, chimpanzees, and rhesus macaques. We show that the most prominent human-specific expression change affects genes associated with synaptic functions and represents an extreme shift in the timing of synaptic development in the prefrontal cortex, but not the cerebellum. Consequently, peak expression of synaptic genes in the prefrontal cortex is shifted from <1 yr in chimpanzees and macaques to 5 yr in humans. This result was supported by protein expression profiles of synaptic density markers and by direct observation of synaptic density by electron microscopy. Mechanistically, the human-specific change in timing of synaptic development involves the MEF2A-mediated activity-dependent regulatory pathway. Evolutionarily, this change may have taken place after the split of the human and the Neanderthal lineages.

Widespread splicing changes in human brain development and aging.

While splicing differences between tissues, sexes and species are well documented, little is known about the extent and the nature of splicing changes that take place during human or mammalian development and aging. Here, using high-throughput transcriptome sequencing, we have characterized splicing changes that take place during whole human lifespan in two brain regions: prefrontal cortex and cerebellum. Identified changes were confirmed using independent human and rhesus macaque RNA-seq data sets, exon arrays and PCR, and were detected at the protein level using mass spectrometry. Splicing changes across lifespan were abundant in both of the brain regions studied, affecting more than a third of the genes expressed in the human brain. Approximately 15% of these changes differed between the two brain regions. Across lifespan, splicing changes followed discrete patterns that could be linked to neural functions, and associated with the expression profiles of the corresponding splicing factors. More than 60% of all splicing changes represented a single splicing pattern reflecting preferential inclusion of gene segments potentially targeting transcripts for nonsense-mediated decay in infants and elderly.

MicroRNA-driven developmental remodeling in the brain distinguishes humans from other primates.

While multiple studies have reported the accelerated evolution of brain gene expression in the human lineage, the mechanisms underlying such changes are unknown. Here, we address this issue from a developmental perspective, by analyzing mRNA and microRNA (miRNA) expression in two brain regions within macaques, chimpanzees, and humans throughout their lifespan. We find that constitutive gene expression divergence (species differences independent of age) is comparable between humans and chimpanzees. However, humans display a 3-5 times faster evolutionary rate in divergence of developmental patterns, compared to chimpanzees. Such accelerated evolution of human brain developmental patterns (i) cannot be explained by life-history changes among species, (ii) is twice as pronounced in the prefrontal cortex than the cerebellum, (iii) preferentially affects neuron-related genes, and (iv) unlike constitutive divergence does not depend on cis-regulatory changes, but might be driven by human-specific changes in expression of trans-acting regulators. We show that developmental profiles of miRNAs, as well as their target genes, show the fastest rates of human-specific evolutionary change, and using a combination of computational and experimental methods, we identify miR-92a, miR-454, and miR-320b as possible regulators of human-specific neural development. Our results suggest that different mechanisms underlie adaptive and neutral transcriptome divergence, and that changes in the expression of a few key regulators may have been a major driving force behind rapid evolution of the human brain.

Rapid metabolic evolution in human prefrontal cortex.

Human evolution is characterized by the rapid expansion of brain size and drastic increase in cognitive capabilities. It has long been suggested that these changes were accompanied by modifications of brain metabolism. Indeed, human-specific changes on gene expression or amino acid sequence were reported for a number of metabolic genes, but actual metabolite measurements in humans and apes have remained scarce. Here, we investigate concentrations of more than 100 metabolites in the prefrontal and cerebellar cortex in 49 humans, 11 chimpanzees, and 45 rhesus macaques of different ages using gas chromatography-mass spectrometry (GC-MS). We show that the brain metabolome undergoes substantial changes, both ontogenetically and evolutionarily: 88% of detected metabolites show significant concentration changes with age, whereas 77% of these metabolic changes differ significantly among species. Although overall metabolic divergence reflects phylogenetic relationships among species, we found a fourfold acceleration of metabolic changes in prefrontal cortex compared with cerebellum in the human lineage. These human-specific metabolic changes are paralleled by changes in expression patterns of the corresponding enzymes, and affect pathways involved in synaptic transmission, memory, and learning.

Elucidating hepatocellular carcinoma progression: a novel prognostic miRNA-mRNA network and signature analysis.

There is increasing evidence that miRNAs play an important role in the prognosis of HCC. There is currently a lack of acknowledged models that accurately predict patient prognosis. The aim of this study is to create a miRNA-based model to precisely forecast a patient's prognosis and a miRNA-mRNA network to investigate the function of a targeted mRNA. TCGA miRNA dataset and survival data of HCC patients were downloaded for differential analysis. The outcomes of variance analysis were subjected to univariate and multivariate Cox regression analyses and LASSO analysis. We constructed and visualized prognosis-related models and subsequently used violin plots to probe the function of miRNAs in tumor cells. We predicted the target mRNAs added those to the String database, built PPI protein interaction networks, and screened those mRNA using Cytoscape. The hub mRNA was subjected to GO and KEGG analysis to determine its biological role. Six of them were associated with prognosis: hsa-miR-139-3p, hsa-miR-139-5p, hsa-miR-101-3p, hsa-miR-30d-5p, hsa-miR-5003-3p, and hsa-miR-6844. The prognostic model was highly predictive and consistently performs, with the C index exceeding 0.7 after 1, 3, and 5 years. The model estimated significant differences in the Kaplan-Meier plotter and the model could predict patient prognosis independently of clinical indicators. A relatively stable miRNA prognostic model for HCC patients was constructed, and the model was highly accurate in predicting patients with good stability over 5 years. The miRNA-mRNA network was constructed to explore the function of mRNA.