LncRNA Recognition-Associated CpG Island Detection and Methylation Analysis.

CpG islands (CGIs) are rare, interspersed DNA sequences, which possess a significant deviation from background genomic distribution by exhibiting patterns of GC-rich and CpG-rich sequence, the density of which provides a good classification feature for long noncoding RNA (lncRNA) promoters. By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CGIs, their methylation states, CpG spacing, and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be elucidated at individual gene and gene family levels, together with consideration of species and lineage specificity.

Superhydrophobic Electrospun PI/PTFE Membranes with Ultralow Dielectric Constants for High-Frequency Telecommunication.

High-frequency, high-power, and high-speed telecommunication in a complex environment promotes the development of dielectric materials toward a low dielectric constant, low dielectric loss, good thermal properties, and long-term reliability. Here, polyimide/polytetrafluoroethylene (PI/PTFE) nanofiber membranes with an inherent super hydrophobicity, excellent dielectric properties, good thermal stability, and enhanced tensile strength were prepared via a simple electrospinning strategy and an imidization reaction. The obtained PI/PTFE membranes demonstrate a superlow average dielectric constant of 1.

Sanggenol L induces ferroptosis in non-small cell lung cancer cells via regulating the miR-26a-1-3p/MDM2/p53 signaling pathway.

Ferroptosis is a regulated cell death marked by iron-dependent lipid peroxidation. Tumor cells that survive by evading chemotherapy-induced apoptosis are vulnerable to ferroptosis. Therefore, it is particularly urgent to explore active ingredients that can selectively induce ferroptosis in cancer cells.

Intranasal immunisation with recombinant Toxoplasma gondii uridine phosphorylase confers resistance against acute toxoplasmosis in mice.

Toxoplasmosis is caused by Toxoplasma gondii, which infects all warm-blooded animals, including humans. Currently, control measures for T. gondii infection are insufficient due to the lack of effective medications or vaccines.

Discovering hematoma-stimulated circuits for secondary brain injury after intraventricular hemorrhage by spatial transcriptome analysis.

Introduction: Central nervous system (CNS) diseases, such as neurodegenerative disorders and brain diseases caused by acute injuries, are important, yet challenging to study due to disease lesion locations and other complexities.

Methods: Utilizing the powerful method of spatial transcriptome analysis together with novel algorithms we developed for the study, we report here for the first time a 3D trajectory map of gene expression changes in the brain following acute neural injury using a mouse model of intraventricular hemorrhage (IVH). IVH is a common and representative complication after various acute brain injuries with severe mortality and mobility implications.

Spatiotemporal Transformer Neural Network for Time-Series Forecasting.

Predicting high-dimensional short-term time-series is a difficult task due to the lack of sufficient information and the curse of dimensionality. To overcome these problems, this study proposes a novel spatiotemporal transformer neural network (STNN) for efficient prediction of short-term time-series with three major features. Firstly, the STNN can accurately and robustly predict a high-dimensional short-term time-series in a multi-step-ahead manner by exploiting high-dimensional/spatial information based on the spatiotemporal information (STI) transformation equation.

ANKRD49 promotes the invasion and metastasis of lung adenocarcinoma via a P38/ATF-2 signalling pathway.

Lung adenocarcinoma (LUAD) is the most challenging neoplasm to treat in clinical practice. Ankyrin repeat domain 49 protein (ANKRD49) is highly expressed in several carcinomas; however, its pattern of expression and role in LUAD are not known. Tissue microarrays, immunohistochemistry, χ test, Spearman correlation analysis, Kaplan-Meier, log-rank test, and Cox's proportional hazard model were used to analyse the clinical cases.

Artificial intelligence in cancer target identification and drug discovery.

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations.

Green synthesis of manganese-cobalt-tungsten composite oxides for degradation of doxycycline via efficient activation of peroxymonosulfate.

The advanced oxidation process of peroxymonosulfate activated by solid catalyst is one of the main technologies to solve the pollution of antibiotics in water environment.In this work, a series of composites (MCW) containing Mn, Co, and W were synthesized using green ball milling, which does not produce the three wastes (waste gas, waste water and industrial residue). It shows a unique and high catalytic activity for peroxymonosulfate-based degradation of doxycycline (DC) under the pH condition between 4 and 9, and it can be reused five times.

Developing an Embedding, Koopman and Autoencoder Technologies-Based Multi-Omics Time Series Predictive Model (EKATP) for Systems Biology research.

It is very important for systems biologists to predict the state of the multi-omics time series for disease occurrence and health detection. However, it is difficult to make the prediction due to the high-dimensional, nonlinear and noisy characteristics of the multi-omics time series data. For this reason, this study innovatively proposes an Embedding, Koopman and Autoencoder technologies-based multi-omics time series predictive model (EKATP) to predict the future state of a high-dimensional nonlinear multi-omics time series.

Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme.

Background: Glioblastoma multiforme (GBM) is one of the most common malignant brain tumors and its average survival time is less than 1 year after diagnosis.

Results: Firstly, this study aims to develop the novel survival analysis algorithms to explore the key genes and proteins related to GBM. Then, we explore the significant correlation between AEBP1 upregulation and increased EGFR expression in primary glioma, and employ a glioma cell line LN229 to identify relevant proteins and molecular pathways through protein network analysis.

Effects of forest regeneration practices on the flux of soil CO after clear-cutting in subtropical China.

Reforestation after clear-cutting is used to facilitate rapid establishment of new stands. However, reforestation may cause additional soil disturbance by affecting soil temperature and moisture, thus potentially influencing soil respiration. Our aim was to compare the effects of different reforestation methods on soil CO flux after clear-cutting in a Chinese fir plantation in subtropical China: uncut (UC), clear-cut followed by coppicing regeneration without soil preparation (CC), clear-cut followed by coppicing regeneration and reforestation with soil preparation, tending in pits and replanting (CCR), and clear-cut followed by coppicing regeneration and reforestation with overall soil preparation, tending and replanting (CCR).