Diffusion-based clock synchronization for molecular communication under inverse Gaussian distribution

Nanonetworks are expected to expand the capabilities of individual nanomachines by allowing them to cooperate and share information by molecular communication. The information molecules are released by the transmitter nanomachine and diffuse across the aqueous channel as a Brownian motion holding the feature of a strong random movement with a large propagation delay. In order to ensure an effective real-time cooperation, it is necessary to keep the clock synchronized among the nanomachines in the nanonetwork. This paper proposes a model on a two-way message exchange mechanism with the molecular propagation delay based on the inverse Gaussian distribution. The clock offset and clock skew are estimated by the maximum likelihood estimation (MLE). Simulation results by MATLAB show that the mean square errors (MSE) of the estimated clock offsets and clock skews can be reduced and converge with a number of rounds of message exchanges. The comparison of the proposed scheme with a clock synchronization method based on symmetrical propagation delay demonstrates that our proposed scheme can achieve a better performance in terms of accuracy

MicroRNA Regulation of Epigenetic Modifiers in Breast Cancer

Epigenetics refers to the heritable changes in gene expression without a change in the DNA sequence itself. Two of these major changes include aberrant DNA methylation as well as changes to histone modification patterns. Alterations to the epigenome can drive expression of oncogenes and suppression of tumor suppressors, resulting in tumorigenesis and cancer progression. In addition to modifications of the epigenome, microRNA (miRNA) dysregulation is also a hallmark for cancer initiation and metastasis. Advances in our understanding of cancer biology demonstrate that alterations in the epigenome are not only a major cause of miRNA dysregulation in cancer, but that miRNAs themselves also indirectly drive these DNA and histone modifications. More explicitly, recent work has shown that miRNAs can regulate chromatin structure and gene expression by directly targeting key enzymes involved in these processes. This review aims to summarize these research findings specifically in the context of breast cancer. This review also discusses miRNAs as epigenetic biomarkers and as therapeutics, and presents a comprehensive summary of currently validated epigenetic targets in breast cancer

Rho GTPases: Big Players in Breast Cancer Initiation, Metastasis and Therapeutic Responses

Rho GTPases, a family of the Ras GTPase superfamily, are key regulators of the actin cytoskeleton. They were originally thought to primarily affect cell migration and invasion; however, recent advances in our understanding of the biology and function of Rho GTPases have demonstrated their diverse roles within the cell, including membrane trafficking, gene transcription, migration, invasion, adhesion, survival and growth. As these processes are critically involved in cancer initiation, metastasis and therapeutic responses, it is not surprising that studies have demonstrated important roles of Rho GTPases in cancer. Although the majority of data indicates an oncogenic role of Rho GTPases, tumor suppressor functions of Rho GTPases have also been revealed, suggesting a context and cell-type specific function for Rho GTPases in cancer. This review aims to summarize recent progresses in our understanding of the regulation and functions of Rho GTPases, specifically in the context of breast cancer. The potential of Rho GTPases as therapeutic targets and prognostic tools for breast cancer patients are also discussed

Nanoparticle-Mediated Therapeutic Agent Delivery for Treating Metastatic Breast Cancer—Challenges and Opportunities

Breast cancer (BC) is the second leading cause of cancer-related death in American women and more than 90% of BC-related death is caused by metastatic BC (MBC). This review stresses the limited success of traditional therapies as well as the use of nanomedicine for treating MBC. Understanding the biological barriers of MBC that nanoparticle in vivo trafficking must overcome could provide valuable new insights for translating nanomedicine from the bench side to the bedside. A view about nanomedicine applied in BC therapy has been summarized with their present status, which is gaining attention in the clinically-applied landscape. The progressions of drug/gene delivery systems, especially the status of their preclinical or clinical trials, are also discussed. Here we highlight that the treatment of metastasis, in addition to the extensively described inhibition of primary tumor growth, is an indispensable requirement for nanomedicine. Along with more innovations in material chemistry and more progressions in biology, nanomedicine will constantly supply more exciting new approaches for targeted drug/gene delivery against MBC

Akt Activation Is Responsible for Enhanced Migratory and Invasive Behavior of Arsenic-Transformed Human Bronchial Epithelial Cells

Background: Arsenic is one of the most common environmental contaminants. Long-term exposure to arsenic causes human bronchial epithelial cell (HBEC) malignant transformation and lung cancer. However, the mechanism of arsenic lung carcinogenesis is not clear, and the migratory and invasive properties of arsenic-transformed cells (As-transformed cells) have rarely been studied

Diversity of archaea and bacteria in a biogas reactor fed with Pennisetum sinese Roxb by 16S rRNA sequence analysis

Purpose: To investigate the structure and function of the complex rumen microbial community in a biogas reactor by 16S rRNA gene analysis, which was fed with Pennisetum sinese Roxb as the monosubstrate.Methods: Two 16S ribosomal RNA (rRNA) clone libraries of bacteria and archaea were established by polymerase chain reaction. Community structure was determined by phylogenetic analyses of 119 and 100 16S rRNA gene clones from the bacterial and archaeal libraries, respectively.Results: In the bacterial library, 13.4 % of clones were affiliated with Treponema porcinum, 5.9 % with Eubacterium limosum, 5 % with Clostridium, 5 % with Bacteroidetes, 4.2 % with Firmicutes, 2.5 % with Anaerofilum and a total of 64 % clones belonged to unclassified or uncultured bacteria. In the archaeal library, Methanobacterium curvum made up 12 % of known clones, Methanosarcina barkeri represented 8 %, Methanobacterium bryantii represented 4 % and Methanofollis ethanolicus represented 2 %, respectively; the remaining 74 % of the clones were unclassified archaebacteria.Conclusion: T. porcinum and M. curvum are the most predominant bacteria and archaea in a biogas reactor fed with P. sinese as the sole substrate.Keywords: Pennisetum sinese Roxb, Archaea, Bacteria, Biogas reactor, 16S rDNA sequencin

Cardiovascular disease prediction model based on patient behavior patterns in the context of deep learning: a time-series data analysis perspective

To address the limitations of traditional cardiovascular disease prediction models in capturing dynamic changes and personalized differences in patients, we propose a novel LGAP model based on time-series data analysis. This model integrates Long Short-Term Memory (LSTM) networks, Graph Neural Networks (GNN), and Multi-Head Attention mechanisms. By combining patients' time-series data (such as medical records, physical parameters, and activity data) with relationship graph data, the model effectively identifies patient behavior patterns and their interrelationships, thereby improving the accuracy and generalization of cardiovascular disease risk prediction. Experimental results show that LGAP outperforms traditional models on datasets such as PhysioNet and NHANES, particularly in prediction accuracy and personalized health management. The introduction of LGAP offers a new approach to enhancing the precision of cardiovascular disease prediction and the development of customized patient care plans

Distribution of different plant life forms on tropical islands: patterns and underlying mechanisms

IntroductionIsland biogeography theory posits that both island area and isolation significantly influence species distribution patterns and community structure. This study investigates the effects of island area and isolation on plant community structure, specifically focusing on the variation in species richness and abundance among different plant life forms (i.e., trees and shrubs) on tropical islands in the South China Sea.MethodsWe surveyed woody plants and collected soil samples from 20 tropical islands in the South China Sea, analyzing how island area, isolation, climate and soil factors influence plant communities across different life forms (trees vs. shrubs).ResultsThe results indicate that species richness increases with island area and decreases with isolation, which aligns with the classic predictions of island biogeography. However, plant abundance exhibits a more complex pattern: tree abundance is positively correlated with island area and negatively correlated with isolation, while shrub abundance shows the opposite trend. Furthermore, the relative tree richness and abundance are predominant on larger, less isolated islands, whereas shrubs are more prevalent on smaller, more remote islands. These contrasting patterns suggest that different life forms adopt distinct ecological strategies within island ecosystems. The structural equation model (SEM) revealed that island area, isolation, and climatic factors directly affect the richness and abundance of trees but not shrubs. Additionally, the indirect effect of soil pH has proven to be a crucial environmental factor in shaping plant community structure.DiscussionOverall, this study highlights the multifaceted roles of geographic, climatic, and soil factors in determining the composition of island plant communities across different life forms. The findings have important implications for island conservation, as they provide a deeper understanding of how plant communities respond to spatial and environmental factors, aiding in the management of biodiversity on tropical islands

Circular RNA circNOL10 Inhibits Lung Cancer Development by Promoting SCLM1-Mediated Transcriptional Regulation of the Humanin Polypeptide Family

circNOL10 is a circular RNA expressed at low levels in lung cancer, though its functions in lung cancer remain unknown. Here, the function and molecular mechanism of circNOL10 in lung cancer development are investigated using in vitro and in vivo studies, and it is shown that circNOL10 significantly inhibits the development of lung cancer and that circNOL10 expression is co‐regulated by methylation of its parental gene Pre‐NOL10 and by splicing factor epithelial splicing regulatory protein 1 (ESRP1). circNOL10 promotes the expression of transcription factor sex comb on midleg‐like 1 (SCML1) by inhibiting transcription factor ubiquitination and thus also affects regulation of the humanin (HN) polypeptide family by SCML1. circNOL10 also affects mitochondrial function through regulating the humanin polypeptide family and affecting multiple signaling pathways, ultimately inhibiting cell proliferation and cell cycle progression, and promoting the apoptosis of lung cancer cells, thereby inhibiting lung cancer development. This study investigates the functions and molecular mechanisms of circNOL10 in the development of lung cancer and reveals its involvement in the transcriptional regulation of the HN polypeptide family by SCML1. The results also demonstrate the inhibitory effect of HN on lung cancer cells growth. These findings may identify novel targets for the molecular therapy of lung cancer