GNN-SubNet: disease subnetwork detection with explainable Graph Neural Networks

The tremendous success of graphical neural networks (GNNs) has already had a major impact on systems biology research. For example, GNNs are currently used for drug target recognition in protein-drug interaction networks as well as cancer gene discovery and more. Important aspects whose practical relevance is often underestimated are comprehensibility, interpretability, and explainability. In this work, we present a graph-based deep learning framework for disease subnetwork detection via explainable GNNs. In our framework, each patient is represented by the topology of a protein-protein network (PPI), and the nodes are enriched by molecular multimodal data, such as gene expression and DNA methylation. Therefore, our novel modification of the GNNexplainer for model-wide explanations can detect potential disease subnetworks, which is of high practical relevance. The proposed methods are implemented in the GNN-SubNet Python program, which we have made freely available on our GitHub for the international research community (https://github.com/pievos101/GNN-SubNet).

T–Cell Engineering for Chimeric Antigen Receptor T–Cell Therapy in Cancer

Through T-cell engineering, researchers at the California South University (CSU) Cancer Research Institute (CRI) have shown that tumor growth can be stopped in a variety of cancers and prevented from spreading to other tissues. Findings from this study are the result of decades of research by Professor Alireza Haidari, a member of the Cancer Biology Research Program at the California South University (CSU), who discovered a protein called AH that can inhibit the growth and spread of cancer cells in several different ways. They become in the tissues of the body. Keywords: Cancer; Cells; Tissues; Tumors; Prevention; Prognosis; Diagnosis; Imaging; Screening, Treatment; Management

First person – Keiichiro Sakai

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Keiichiro Sakai is first author on ‘ Near-infrared imaging in fission yeast using a genetically encoded phycocyanobilin biosynthesis system’, published in JCS. Keiichiro is a PhD student in the lab of Kazuhiro Aoki at the Quantitative Biology Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Aichi, Japan, investigating how phycocyanobilin, a linear tetrapyrrole, brightens near-infrared fluorescent proteins, including iRFP, as a chromophore more efficiently than biliverdin in fission yeast.

Phage display – a tool for detection and prevention against pathogens. A review

In this article are reviewed the promising uses of phage display in the areas such as microbial pathogens detection of and vaccination. Phage display is a molecular technique by which foreign proteins are expressed at the surface of phage particles. Such phages thereby become vehicles for expression that not only carry within them the nucleotide sequence encoding expressed proteins, but have also the capability to replicate. Recent data acquired from genome sequencing and advances in phage biology research have aided the development of phage-derived bacterial detection and treatment strategies.

Novel Approaches in Biomolecule Labeling

The selective functionalization of biomolecules such as proteins, nucleic acids, lipids or carbohydrates is a focus of persistent interest due to their widespread use, ranging from basic chemical biology research to gain insight into biological processes to the most promising biomedical applications, including the development of diagnostics or targeted therapies [...]

Medieval Scientific Policy in Medicine, Measuring Realism in Prophet Medicine

In dark days of Europe, which was a barren science, you saw the world through superstitions of alchemy and methods based on ignorance and speculation. A current of science emerged in medieval world that provided a new definition of science. In modern definition of science, it is knowledge of fixed truths of nature, man and society, which you have acquired with the tools of empirical intellect and by observation and induction, and which have been useful for ensuring the welfare and security of human beings. The background of this scientific current is call to reason, realism and philosophy. The intellect is source of knowledge of world, and the dimensions of the universe are based on principles of philosophy and method of realism. Sarton, leader of historiography of science in middle Ages, introduced Muslims as leaders of science in middle Ages. A collection of health, food, medicine and theoretical treatments is attributed to Muhammad, which has been published under the title of Prophetic Medicine. Ibn Khaldu criticized medicine of Prophet eight hundred years ago. he writes that Prophet was not a physician and a specialist in worldly affairs, and that use of Prophet's medicine does not require observance of status of prophethood The hypothesis of the present study is that despite Ibn Khaldun's criticism, the realism of the Prophet's medical works shows that Prophet's medicine needs new reflection and study, and a special type of medicine is based on trust in divine wisdom in creating an intelligent system between disease and medicine in nature. The present study has analyzed and explained realism in Prophet's medical words about fenugreek and has shown and proved it according to modern medical data. The Prophet issued a general decree regarding fenugreek and said; Hundreds of new laboratory and clinical research in medicine, veterinary medicine, agriculture, biology show general effectiveness of fenugreek in maintaining human health, livestock, nature and environment, and fenugreek is at heart of biology research, which Proves realism of comprehensive speech of Prophet.

Challenges and Perspectives in the Study of Self-Incompatibility in Orchids

Self-incompatibility affects not only the formation of seeds, but also the evolution of species diversity. A robust understanding of the molecular mechanisms of self-incompatibility is essential for breeding efforts, as well as conservation biology research. In recent years, phenotypic and multiple omics studies have revealed that self-incompatibility in Orchidaceae is mainly concentrated in the subfamily Epidendroideae, and the self-incompatibility phenotypes are diverse, even in the same genus, and hormones (auxin and ethylene), and new male and female determinants might be involved in SI response. This work provides a good foundation for future studies of the evolution and molecular mechanisms of self-incompatibility. We review recent research progress on self-incompatibility in orchids at the morphological, physiological, and molecular levels, provide a general overview of self-incompatibility in orchids, and propose future research directions.