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The objective of this study was to develop an accessible and accurate analysis method for microplastics that have been unintentionally added to cream cosmetic products. An experiment was performed on three cleansing creams in rich and viscous formulations. A spiked sample was prepared by adding polyethylene (PE) microspheres to the cleansing creams. After removing cosmetic ingredients from the creams using chemical digestion, damage to the PE microspheres was identified using Fourier transform infrared (FT-IR) spectroscopy. Field emission scanning electron microscopy (FE-SEM) images were obtained before and after digestion and used to characterize the morphology of the PE microspheres. The highest digestion efficiency was obtained using a chemical digestion method consisting of heating and stirring a sample in a 10 wt% KOH solution at 55 °C and 300 rpm for 5 days and did not damage the PE microspheres. The Nile red (9-diethylamino-5H-benzo[α]phenoxazine-5-one) staining method was effective in identifying small microplastics (< 106 μm). The optimal staining conditions are 5 μg/ml Nile red in n -hexane for green wavelengths.

We present HiGlass, an open source visualization tool built on web technologies that provides a rich interface for rapid, multiplex, and multiscale navigation of 2D genomic maps alongside 1D genomic tracks, allowing users to combine various data types, synchronize multiple visualization modalities, and share fully customizable views with others. We demonstrate its utility in exploring different experimental conditions, comparing the results of analyses, and creating interactive snapshots to share with collaborators and the broader public. HiGlass is accessible online at http://higlass.io and is also available as a containerized application that can be run on any platform.

Understanding translational control in gene expression relies on precise and comprehensive determination of translation initiation sites (TIS) across the entire transcriptome. The recently developed ribosome-profiling technique enables global translation analysis, providing a wealth of information about both the position and the density of ribosomes on mRNAs. Here we present an approach, global translation initiation sequencing, applying in parallel the ribosome E-site translation inhibitors lactimidomycin and cycloheximide to achieve simultaneous detection of both initiation and elongation events on a genome-wide scale. This approach provides a view of alternative translation initiation in mammalian cells with single-nucleotide resolution. Systemic analysis of TIS positions supports the ribosome linear-scanning mechanism in TIS selection. The alternative TIS positions and the associated ORFs identified by global translation initiation sequencing are conserved between human and mouse cells, implying physiological significance of alternative translation. Our study establishes a practical platform for uncovering the hidden coding potential of the transcriptome and offers a greater understanding of the complexity of translation initiation.

Three-dimensional (3D) nanoframe structures are very appealing because their inner voids and ridges interact efficiently with light and analytes, allowing for effective optical-based sensing. However, the realization of complex nanoframe architecture with high yield is challenging because the systematic design of such a complicated nanostructure lacks an appropriate synthesis protocol. Here, we show the synthesis method for complex 3D nanoframes wherein two-dimensional (2D) dual-rim nanostructures are engraved on each facet of octahedral nanoframes. The synthetic scheme proceeds through multiple executable on-demand steps. With Au octahedral nanoparticles as a sacrificial template, sequential processes of edge-selective Pt deposition and inner Au etching lead to Pt octahedral mono-rim nanoframes. Then, adlayers of Au are grown on Pt skeletons via the Frank-van der Merwe mode, forming sharp and well-developed edges. Next, Pt selective deposition on both the inner and outer boundaries leads to tunable geometric patterning on Au. Finally, after the selective etching of Au, Pt octahedral dual-rim nanoframes with highly homogeneous size and shape are achieved. In order to endow plasmonic features, Au is coated around Pt frames while retaining their geometric shape. The resultant plasmonic dual-rim engraved nanoframes possess strong light entrapping capability verified by single-particle surface-enhanced Raman scattering (SERS) and show the potential of nanoprobes for biosensing through SERS-based immunoassay. Most SERS-active nanostructures suffer from low robustness against misalignment to field polarization. Here, the authors demonstrate three-dimensional nanoframes of octahedral geometry, with two rims engraved on each facet, as polarization-independent SERS nanoprobes.

Data analysis often entails a multitude of heterogeneous steps, from the application of various command line tools to the usage of scripting languages like R or Python for the generation of plots and tables. It is widely recognized that data analyses should ideally be conducted in a reproducible way. Reproducibility enables technical validation and regeneration of results on the original or even new data. However, reproducibility alone is by no means sufficient to deliver an analysis that is of lasting impact (i.e., sustainable) for the field, or even just one research group. We postulate that it is equally important to ensure adaptability and transparency. The former describes the ability to modify the analysis to answer extended or slightly different research questions. The latter describes the ability to understand the analysis in order to judge whether it is not only technically, but methodologically valid. Here, we analyze the properties needed for a data analysis to become reproducible, adaptable, and transparent. We show how the popular workflow management system Snakemake can be used to guarantee this, and how it enables an ergonomic, combined, unified representation of all steps involved in data analysis, ranging from raw data processing, to quality control and fine-grained, interactive exploration and plotting of final results.

Neurons live for decades in a postmitotic state, their genomes susceptible to DNA damage. Here we survey the landscape of somatic single-nucleotide variants (SNVs) in the human brain. We identified thousands of somatic SNVs by single-cell sequencing of 36 neurons from the cerebral cortex of three normal individuals. Unlike germline and cancer SNVs, which are often caused by errors in DNA replication, neuronal mutations appear to reflect damage during active transcription. Somatic mutations create nested lineage trees, allowing them to be dated relative to developmental landmarks and revealing a polyclonal architecture of the human cerebral cortex. Thus, somatic mutations in the brain represent a durable and ongoing record of neuronal life history, from development through postmitotic function.

Transposable elements (TEs) help shape the structure and function of the human genome. When inserted into some locations, TEs may disrupt gene regulation and cause diseases. Here, we present xTea (x-Transposable element analyzer), a tool for identifying TE insertions in whole-genome sequencing data. Whereas existing methods are mostly designed for short-read data, xTea can be applied to both short-read and long-read data. Our analysis shows that xTea outperforms other short read-based methods for both germline and somatic TE insertion discovery. With long-read data, we created a catalogue of polymorphic insertions with full assembly and annotation of insertional sequences for various types of retroelements, including pseudogenes and endogenous retroviruses. Notably, we find that individual genomes have an average of nine groups of full-length L1s in centromeres, suggesting that centromeres and other highly repetitive regions such as telomeres are a significant yet unexplored source of active L1s. xTea is available at https://github.com/parklab/xTea . Identification of transposable element (TE) insertions from whole genome sequencing data remains challenging. Here the authors developed a comprehensive TE insertion detection algorithm xTea that can be applied to both short-read and long-read sequencing data.

Higher-order sensory thalamic nuclei are densely connected with multiple cortical and subcortical areas, yet the role of these nuclei remains elusive. The posteromedial thalamic nucleus (POm), the higher-order thalamic nucleus in the rodent somatosensory system, is an anatomical hub broadly connected with multiple sensory and motor brain areas yet weakly responds to passive sensory stimulation and whisker movements. To understand the role of POm in sensory perception, we developed a self-initiated, two-alternative forced-choice task in freely moving mice during active sensing. Using optogenetic and chemogenetic manipulation, we show that POm plays a significant role in sensory perception and the projection from the primary somatosensory cortex to POm is critical for the contribution of POm in sensory perception during active sensing.

Cross-ancestry genetic correlation is an important parameter to understand the genetic relationship between two ancestry groups. However, existing methods cannot properly account for ancestry-specific genetic architecture, which is diverse across ancestries, producing biased estimates of cross-ancestry genetic correlation. Here, we present a method to construct a genomic relationship matrix (GRM) that can correctly account for the relationship between ancestry-specific allele frequencies and ancestry-specific allelic effects. Through comprehensive simulations, we show that the proposed method outperforms existing methods in the estimations of SNP-based heritability and cross-ancestry genetic correlation. The proposed method is further applied to anthropometric and other complex traits from the UK Biobank data across ancestry groups. For obesity, the estimated genetic correlation between African and European ancestry cohorts is significantly different from unity, suggesting that obesity is genetically heterogenous between these two ancestries. Cross-ancestry genetic correlation can reveal differences in the genetic basis of traits between populations, but methods can be biased by ancestry-specific genetic architecture. Here, the authors present a method to for estimating cross-ancestry genetic correlations, accounting for ancestry-specific genetic architecture.

Human induced pluripotent stem cells show no consistent differences from human embryonic stem cells in a study that controls for several sources of variability. The equivalence of human induced pluripotent stem cells (hiPSCs) and human embryonic stem cells (hESCs) remains controversial. Here we use genetically matched hESC and hiPSC lines to assess the contribution of cellular origin (hESC vs. hiPSC), the Sendai virus (SeV) reprogramming method and genetic background to transcriptional and DNA methylation patterns while controlling for cell line clonality and sex. We find that transcriptional and epigenetic variation originating from genetic background dominates over variation due to cellular origin or SeV infection. Moreover, the 49 differentially expressed genes we detect between genetically matched hESCs and hiPSCs neither predict functional outcome nor distinguish an independently derived, larger set of unmatched hESC and hiPSC lines. We conclude that hESCs and hiPSCs are molecularly and functionally equivalent and cannot be distinguished by a consistent gene expression signature. Our data further imply that genetic background variation is a major confounding factor for transcriptional and epigenetic comparisons of pluripotent cell lines, explaining some of the previously observed differences between genetically unmatched hESCs and hiPSCs.