Folia Pharmacologica Japonica最新文献

Because of absence of the objective biomarker for major depressive disorder (MDD) or depressive state, psychiatrists depend on subjective examinations in order to properly diagnose their patients. We recently identified the candidates of the objective biomarker of depressive state of late-onset MDD by profiling gene expressions in white blood cells of patients and model mice. We also investigated whether gene expression profiling of white blood cells was useful to elucidate the biological alterations in the brain. Furthermore, we newly developed transgenic mice which will be useful for elucidating the neurological mechanisms of emotional abnormalities in psychiatric disorder. In this review, I introduce our recent research to help for understanding of translational approaches to develop the biomarker of depression.

Antimicrobial resistance is currently recognized as an urgent concern against public health in worldwide. Carbapenem-resistant (CR) Gram-negative bacteria, such as Enterobacterales, Pseudomonas aeruginosa and Acinetobacter baumannii are listed as critical pathogens which are widely spread and can cause severe and often deadly infections in WHO guidance. Cefiderocol (Fetroja^®), a novel and first siderophore cephalosporin, was approved for the infections caused by these problematic CR Gram-negative bacteria in Japan on November 30, 2023. Cefiderocol has unique mechanisms to be incorporated into bacterial cells using bacterial iron transportation system and to be highly stable against most β-lactamases, which lead to promising antibacterial activity against these Gram-negative bacteria including CR strains in vitro. In CREDIBLE-CR Ph3 trial, cefiderocol showed the good efficacy and safety for patients with CR Gram-negative bacteria. In APEKS-cUTI and APEKS-NP trials, cefiderocol showed non-inferiority and suggested superiority to imipenem/cilastatin in complicated urinary tract infection (cUTI) patients, and non-inferiority to high dose of meropemen in pneumonia patients, respectively. Cefiderocol is expected to be an optimal treatment for CR Gram-negative infections with limited treatment options and would be an important drug to combat the threat of CR bacteria.

The advent of a super-aged society poses urgent challenges in overcoming age-related neurological disorders and extending a healthy lifespan. Neurodegenerative diseases such as Alzheimer's disease, dementia with Lewy bodies, and Parkinson's disease are characterized by the accumulation of pathogenic proteins in the brain, leading to the formation of intracellular aggregates known as pathological hallmarks. In the early stages of protein accumulation, before the onset of clinical symptoms such as cognitive impairment or motor dysfunction, brain inflammation begins to occur. Subsequently, neuronal death progresses, and clinical symptoms manifest as dementia or Parkinson's disease. Therefore, there is a need for early prediction of neurodegeneration and the development of disease-modifying drugs for pre-symptomatic prevention. To address this issue, we have focused on enhancing the degradation of amyloid-β protein by targeting Ca²⁺/calmodulin-dependent kinase II (CaMKII)/proteasome system and on suppressing the propagation and uptake mechanisms of α-synuclein by targeting fatty acid-binding proteins (FABPs) coupled with the long isoform of dopamine D2 (D_2L) receptor. Additionally, our analysis of FABP knockout mice has revealed an increased expression of FABPs in the neurodegenerative process, suggesting their involvement in mitochondrial dysfunction and neuronal death. Based on these findings, this article highlights the physiological significance of FABP family proteins in neurodegeneration and discusses the analysis of plasma biomarkers for predicting neurodegenerative disorders and the discriminatory methods for distinguishing between Alzheimer's disease, dementia with Lewy bodies, and Parkinson's disease. Furthermore, we explore the potential of ultra-early prediction of neurodegenerative disorders.

Fluorescent imaging sensors based on genetically-encoded and biocompatible proteins have become important tools in medical and biological research due to their high spatiotemporal resolution and ease of use. Protein engineering has led to the development of imaging sensors that visualize changes in the concentration of various target molecules/ions, such as calcium ions. In addition, the development of chemigenetic sensors based on complexes of proteins and synthetic molecules has been gaining momentum in recent years. In this article, the latest research trends in the development of these imaging sensors are introduced, with focus on the sensors developed by our group.

Biological phenomena are generated by the cooperative and hierarchical relationships between a variety of biomolecules, such as proteins, metabolites, signaling molecules, and ions. In many cases, however, these biomolecules do not have color, and it is difficult to observe them as they are. Therefore, it is necessary to "visualize" each molecule with color or fluorescence, and to analyze the functional relationships between them. The live cell imaging technology using single fluorescent protein (FP)-based indicators has contributed to the visualization of biomolecules. Single FP-based indicators, which change their fluorescence intensity upon binding to the target molecule, have been revolutionized into multicolor indicators by a series of innovative screening methods. On the other hand, we have established an original screening method using semi-rational molecular design and molecular evolution, and have developed many single FP-based indicators for various molecules such as cAMP and glucose. In this article, we focus on single FP-based indicators and introduce their development strategy and the history of screening method.

Knowledge Palette, Inc. is a start-up company that aims to overcome incurable diseases by applying the world's most accurate single-cell level and bulk level transcriptome technology to obtain large-scale data on the state of cells treated with various types of drugs and media, and using this information to highly control cells for improving human health. We are working on new phenotypic drug discovery and higher quality cells for regenerative medicine using big data. As one of its core technologies, the company is utilizing a single-cell-level whole gene expression analysis technology, Quartz-Seq2, which was originally developed in RIKEN. This technology received first place in accuracy of genes detection as well as marker identification, and was ranked No. 1 in overall score in the benchmarking in the international Human Cell Atlas project. By applying this technology to the bulk level analysis of ultra-multiple samples, it has enabled drug screening, analysis of human clinical specimens, and evaluation of numerous culture environments in a high-throughput way. This paper presents an omics-driven drug discovery and cell regulation approach that is combined with large-scale data and artificial intelligence technology.