Prediction of Transcription Factor Binding Sites on Cell-Free DNA Based on Deep Learning.

Transcription factors (TFs) are important regulatory elements for vital cellular activities, and the identification of transcription factor binding sites (TFBS) can help to explore gene regulatory mechanisms. Research studies have proved that cfDNA (cell-free DNA) shows relatively higher coverage at TFBS due to the protection by TF from degradation by nucleases and short fragments of cfDNA are enriched in TFBS. However, there are still great difficulties in the noninvasive identification of TFBSs from experimental techniques.

The Impact of Blood Sample Processing on Ribonucleic Acid (RNA) Sequencing.

In gene quantification and expression analysis, issues with sample selection and processing can be serious, as they can easily introduce irrelevant variables and lead to ambiguous results. This study aims to investigate the extent and mechanism of the impact of sample selection and processing on ribonucleic acid (RNA) sequencing. RNA from PBMCs and blood samples was investigated in this study.

CsPbBr perovskite quantum dots-based Janus membrane with multifunction of luminescence, magnetism and aeolotropic electroconductivity.

Lead halide perovskite quantum dots (QDs) are promising semiconductors for next-generation photoelectric devices. However, the development of perovskite QDs-based multifunctional materials still needs to be addressed in order to further advance the application of perovskite QDs. Herein, a successful synthesis of Janus microfibers array Janus membrane (JMAJM) with up-down structure and multifunction of luminescence, magnetism and electroconductivity is firstly achieved based on CsPbBr QDs through a parallel electrospinning.

Agarose amplification based sequencing characterization cell-free RNA in preimplantation spent embryo medium.

The cell-free RNA (cf-RNA) of spent embryo medium (SEM) has aroused a concern of academic and clinical researchers for its potential use in non-invasive embryo screening. However, comprehensive characterization of cf-RNA from SEM still presents significant technical challenges, primarily due to the limited volume of SEM. Hence, there is urgently need to a small input liquid volume and ultralow amount of cf-RNA library preparation method to unbiased cf-RNA sequencing from SEM.

Wire-in-tube nanofiber as one side to construct specific-shaped Janus nanofiber with improved upconversion luminescence and tunable magnetism.

It is an important strategy to rationally design and construct specific-shaped microscopic nanostructures for developing poly-functional nanomaterials for different advanced applications. In this work, a novel technique combining a parallel electrospinning with a subsequent bi-crucible fluorination is advanced and utilized to facilely synthesize a brand-new peculiar one-dimensional (1D) wire-in-tube nanofiber//nanofiber shaped Janus nanofiber (WJNF) to refrain from usual complicated preparation procedures. Partition of four independent domains in the peculiar-structured Janus nanofiber is microscopically realized.

Spatial Transcriptomic Analysis Reveals Regional Transcript Changes in Early and Late Stages of rd1 Model Mice with Retinitis Pigmentosa.

Retinitis pigmentosa (RP) is the leading cause of inherited blindness with a genetically heterogeneous disorder. Currently, there is no effective treatment that can protect vision for those with RP. In recent decades, the rd1 mouse has been used to study the pathological mechanisms of RP.

iATMEcell: identification of abnormal tumor microenvironment cells to predict the clinical outcomes in cancer based on cell-cell crosstalk network.

Interactions between Tumor microenvironment (TME) cells shape the unique growth environment, sustaining tumor growth and causing the immune escape of tumor cells. Nonetheless, no studies have reported a systematic analysis of cellular interactions in the identification of cancer-related TME cells. Here, we proposed a novel network-based computational method, named as iATMEcell, to identify the abnormal TME cells associated with the biological outcome of interest based on a cell-cell crosstalk network.

Spatial Transcriptome Profiling of Mouse Hippocampal Single Cell Microzone in Parkinson's Disease.

The hippocampus is an important part of the limbic system in the human brain that has essential roles in spatial navigation and cognitive functions. It is still unknown how gene expression changes in single-cell in different spatial locations of the hippocampus of Parkinson's disease. The purpose of this study was to analyze the gene expression features of single cells in different spatial locations of mouse hippocampus, and to explore the effects of gene expression regulation on learning and memory mechanisms.

scRNA-seq data analysis method to improve analysis performance.

With the development of single-cell RNA sequencing technology (scRNA-seq), we have the ability to study biological questions at the level of the individual cell transcriptome. Nowadays, many analysis tools, specifically suitable for single-cell RNA sequencing data, have been developed. In this review, the currently commonly used scRNA-seq protocols are discussed.

A comprehensive characterization of cell-free RNA in spent blastocyst medium and quality prediction for blastocyst.

The rate of pregnancy can be affected by many factors in assisted reproductive technology (ART), and one of which is the quality of embryos. Therefore, selecting the embryos with high potential is crucial for the outcome. Fifteen spent blastocyst medium (SBM) samples were collected from 14 patients who received in vitro fertilization (IVF) or intracytoplasmic sperm injection (ICSI), seven from high-grade embryos and eight from low-grade embryos.

Extracellular cell-free RNA profile in human large follicles and small follicles.

Previous studies have shown that a large number of valuable and functional cell-free RNAs (cfRNAs) were found in follicular fluid. However, the species and characteristics of follicular fluid cfRNAs have not been reported. Furthermore, their implications are still barely understood in the evaluation of follicular fluid from follicles of different sizes, which warrants further studies.

Prediction of Time-Series Transcriptomic Gene Expression Based on Long Short-Term Memory with Empirical Mode Decomposition.

RNA degradation can significantly affect the results of gene expression profiling, with subsequent analysis failing to faithfully represent the initial gene expression level. It is urgent to have an artificial intelligence approach to better utilize the limited data to obtain meaningful and reliable analysis results in the case of data with missing destination time. In this study, we propose a method based on the signal decomposition technique and deep learning, named Multi-LSTM.

Sensitive and Low-Bias Transcriptome Sequencing Using Agarose PCR.

Transcriptome sequencing has emerged as an important research tool for exploring the mysteries of life at the single-cell level. However, its wide application is limited by the bias associated with the amplification reactions which is essential for library building of trace RNA. In this study, low-melting-point agarose was added to the amplification reactions to take advantage of its molecular crowding effect and polymer cross-linked structure to improve the sensitivity of the reactions and reduce bias.

Pan-cancer analysis reveals sex-specific signatures in the tumor microenvironment.

The processes of cancer initiation, progression, and response to therapy are affected by the sex of cancer patients. Immunotherapy responses largely depend on the tumor microenvironment (TME), but how sex may shape some TME features, remains unknown. Here, we analyzed immune infiltration signatures across 19 cancer types from 1771 male and 1137 female patients in The Cancer Genome Atlas to evaluate how sex may affect the tumor mutational burden (TMB), immune scores, stromal scores, tumor purity, immune cells, immune checkpoint genes, and functional pathways in the TME.

CNA2Subpathway: identification of dysregulated subpathway driven by copy number alterations in cancer.

Biological pathways reflect the key cellular mechanisms that dictate disease states, drug response and altered cellular function. The local areas of pathways are defined as subpathways (SPs), whose dysfunction has been reported to be associated with the occurrence and development of cancer. With the development of high-throughput sequencing technology, identifying dysfunctional SPs by using multi-omics data has become possible.

Prioritization of candidate cancer drugs based on a drug functional similarity network constructed by integrating pathway activities and drug activities.

Due to the speed, efficiency, relative risk, and lower costs compared to traditional drug discovery, the prioritization of candidate drugs for repurposing against cancers of interest has attracted the attention of experts in recent years. Herein, we present a powerful computational approach, termed prioritization of candidate drugs (PriorCD), for the prioritization of candidate cancer drugs based on a global network propagation algorithm and a drug-drug functional similarity network constructed by integrating pathway activity profiles and drug activity profiles. This provides a new approach to drug repurposing by first considering the drug functional similarities at the pathway level.

Identification of Cancer Dysfunctional Subpathways by Integrating DNA Methylation, Copy Number Variation, and Gene-Expression Data.

A subpathway is defined as the local region of a biological pathway with specific biological functions. With the generation of large-scale sequencing data, there are more opportunities to study the molecular mechanisms of cancer development. It is necessary to investigate the potential impact of DNA methylation, copy number variation (CNV), and gene-expression changes in the molecular states of oncogenic dysfunctional subpathways.