No abstract

Identifying gene regulatory networks (GRNs) at the resolution of single cells has long been a great challenge, and the advent of single-cell multi-omics data provides unprecedented opportunities to construct GRNs. Here, we propose a novel strategy to integrate omics datasets of single-cell ribonucleic acid sequencing and single-cell Assay for Transposase-Accessible Chromatin using sequencing, and using an unsupervised learning neural network to divide the samples with high copy number variation scores, which are used to infer the GRN in each gene block. Accuracy validation of proposed strategy shows that approximately 80% of transcription factors are directly associated with cancer, colorectal cancer, malignancy and disease by TRRUST; and most transcription factors are prone to produce multiple transcript variants and lead to tumorigenesis by RegNetwork database, respectively. The source code access are available at: https://github.com/Cuily-v/Colorectal_cancer.

Alzheimer's disease (AD) is a progressive, neurodegenerative disease. Accumulating evidence suggests that inflammatory response, oxidative stress and autophagy are involved in amyloid β (Aβ)-induced memory deficits. Silibinin (silybin), a flavonoid derived from the herb milk thistle, is well known for its hepatoprotective activities. In this study, we investigated the neuroprotective effect of silibinin on Aβ-injected rats. Results demonstrated that silibinin significantly attenuated Aβ-induced memory deficits in Morris water maze and novel object-recognition tests. Silibinin exerted anxiolytic effect in Aβ-injected rats as determined in elevated plus maze test. Silibinin attenuated the inflammatory responses, increased glutathione (GSH) levels and decreased malondialdehyde (MDA) levels, and upregulated autophagy levels in the Aβ-injected rats. In conclusion, silibinin is a potential candidate for AD treatment because of its anti-inflammatory, antioxidant and autophagy regulating activities.

No abstract

With the rapid growth of the aging population, exploring the biological basis of aging and related molecular mechanisms has become an important topic in modern scientific research. Aging can cause multiple organ function attenuations, leading to the occurrence and development of various age-related metabolic, nervous system, and cardiovascular diseases. In addition, aging is closely related to the occurrence and development of tumors. Although a number of studies have used various mouse models to study aging, further research is needed to associate mouse and human aging at the molecular level. In this paper, we systematically assessed the relationship between human and mouse aging by comparing multi-tissue age-related gene expression sets. We compared 18 human and mouse tissues, and found 9 significantly correlated tissue pairs. Functional analysis also revealed some terms related to aging in human and mouse. And we performed a crosswise comparison of homologous age-related genes with 18 tissues in human and mouse respectively, and found that human Brain_Cortex was significantly correlated with Brain_Hippocampus, which was also found in mouse. In addition, we focused on comparing four brain-related tissues in human and mouse, and found a gene– GFAP –related to aging in both human and mouse.