<i>In Vivo</i> Near-Infrared Fluorescence Imaging Selective for Soluble Amyloid β Aggregates Using y‑Shaped BODIPY Derivative

Soluble amyloid β (Aβ) aggregates, suggested to be the most toxic forms of Aβ, draw attention as therapeutic targets and biomarkers of Alzheimer’s disease (AD). As soluble Aβ aggregates are transient and diverse, imaging their diverse forms in vivo is expected to have a marked impact on research and diagnosis of AD. Herein, we report a near-infrared fluorescent (NIRF) probe, BAOP-16, targeting diverse soluble Aβ aggregates. BAOP-16, whose molecular shape resembles “y”, showed a marked selective increase in fluorescence intensity upon binding to soluble Aβ aggregates in the near-infrared region and a high binding affinity for them. Additionally, BAOP-16 could detect Aβ oligomers in the brains of Aβ-inoculated model mice. In an in vivo fluorescence imaging study of BAOP-16, brains of AD model mice displayed significantly higher fluorescence signals than those of wild-type mice. These results indicate that BAOP-16 could be useful for the in vivo NIRF imaging of diverse soluble Aβ aggregates

<i>In Vivo</i> Near-Infrared Fluorescence Imaging Selective for Soluble Amyloid β Aggregates Using y‑Shaped BODIPY Derivative

Soluble amyloid β (Aβ) aggregates, suggested to be the most toxic forms of Aβ, draw attention as therapeutic targets and biomarkers of Alzheimer’s disease (AD). As soluble Aβ aggregates are transient and diverse, imaging their diverse forms in vivo is expected to have a marked impact on research and diagnosis of AD. Herein, we report a near-infrared fluorescent (NIRF) probe, BAOP-16, targeting diverse soluble Aβ aggregates. BAOP-16, whose molecular shape resembles “y”, showed a marked selective increase in fluorescence intensity upon binding to soluble Aβ aggregates in the near-infrared region and a high binding affinity for them. Additionally, BAOP-16 could detect Aβ oligomers in the brains of Aβ-inoculated model mice. In an in vivo fluorescence imaging study of BAOP-16, brains of AD model mice displayed significantly higher fluorescence signals than those of wild-type mice. These results indicate that BAOP-16 could be useful for the in vivo NIRF imaging of diverse soluble Aβ aggregates

image_1_Elucidating T Cell Activation-Dependent Mechanisms for Bifurcation of Regulatory and Effector T Cell Differentiation by Multidimensional and Single-Cell Analysis.PDF

<p>In T cells, T cell receptor (TCR) signaling initiates downstream transcriptional mechanisms for T cell activation and differentiation. Foxp3-expressing regulatory T cells (Treg) require TCR signals for their suppressive function and maintenance in the periphery. It is, however, unclear how TCR signaling controls the transcriptional program of Treg. Since most of studies identified the transcriptional features of Treg in comparison to naïve T cells, the relationship between Treg and non-naïve T cells including memory-phenotype T cells (Tmem) and effector T cells (Teff) is not well understood. Here, we dissect the transcriptomes of various T cell subsets from independent datasets using the multidimensional analysis method canonical correspondence analysis (CCA). We show that at the cell population level, resting Treg share gene modules for activation with Tmem and Teff. Importantly, Tmem activate the distinct transcriptional modules for T cell activation, which are uniquely repressed in Treg. The activation signature of Treg is dependent on TCR signals and is more actively operating in activated Treg. Furthermore, by using a new CCA-based method, single-cell combinatorial CCA, we analyzed unannotated single-cell RNA-seq data from tumor-infiltrating T cells, and revealed that FOXP3 expression occurs predominantly in activated T cells. Moreover, we identified FOXP3-driven and T follicular helper-like differentiation pathways in tumor microenvironments, and their bifurcation point, which is enriched with recently activated T cells. Collectively, our study reveals the activation mechanisms downstream of TCR signals for the bifurcation of Treg and Teff differentiation and their maturation processes.</p

BODIPY-Based Molecular Probe for Imaging of Cerebral β-Amyloid Plaques

We designed and synthesized a BODIPY-based probe (BAP-1) for the imaging of β-amyloid plaques in the brain. In binding experiments in vitro, BAP-1 showed excellent affinity for synthetic Aβ aggregates. β-Amyloid plaques in Tg2576 mouse brain were clearly visualized with BAP-1. In addition, the labeling of β-amyloid plaques was demonstrated in vivo in Tg2576 mice. These results suggest BAP-1 to be a useful fluorescent probe for the optical imaging of cerebral β-amyloid plaques in patients with Alzheimer’s disease

Preparation of Asymmetric Urea Derivatives that Target Prostate-Specific Membrane Antigen for SPECT Imaging

Prostate-specific membrane antigen (PSMA) has been identified as a diagnostic and therapeutic target for prostate cancer. (<i>S</i>)-2-[3-[(<i>R</i>)-1-Carboxy-2-mercaptoethyl]­ureido-pentanedioic acid (Cys-CO-Glu) were used to design novel PSMA targeting probes by nucleophilic conjugate addition between cysteine and maleimide based reagents. <b>3</b> ([¹²³I]­IGLCE) was synthesized by this strategy and showed high affinity for PSMA. Results of binding inhibition assays of these derivatives suggested the importance of an aromatic group and succinimide moiety for high affinity. [¹²³I]<b>3</b> was evaluated in vivo with PSMA positive LNCaP and PSMA negative PC-3 human prostate cancer xenograft bearing mice. [¹²⁵I]<b>3</b> accumulated in LNCaP tumors but not in PC-3 tumors, and the accumulation was inhibited by 2-(phosphonomethyl)­pentanedioic acid (2-PMPA). Use of [¹²³I]<b>3</b> provided positive images of LNCaP tumors in single photon emission tomography scans. These results warrant further evaluation of [¹²³I]<b>3</b> and its derivatives as radiolabeled probes for the diagnosis of prostate cancer

Kaplan-Meier curves for overall survival for MDS patients according to the HSC-CMP score(a, b), which was made by CCAM, and the well-established classifications (c–g).

<p>Patients were stratified into 2 to 6 groups by the followings: (a) HSC-CMP score, two groups (1: and 2: ). (b) HSC-CMP score, three groups (1: , 2: , and 3: ). (c) Cytopenia score. (d) Blast score. (e) Karyotype score. (f) IPSS score. (g) Disease classification. P values are by log-rank test.</p

Kaplan-Meier curves for time to AML transformation for MDS patients according to the HSC-CMP score(a, b), which was made by CCAM, and the well-established classifications (c–g).

<p>Patients were stratified into 2 to 6 groups by the followings: (a) HSC-CMP score, two groups (1: and 2: ). (b) HSC-CMP score, three groups (1: , 2: , and 3: ). (c) Cytopenia score. (d) Blast score. (e) Karyotype score. (f) IPSS score. (g) Disease classification. P values are by log-rank test.</p

The features of CCAM and other univariate and multivariate/multidimensional methods for microarray analysis.

<p>The features of CCAM and other univariate and multivariate/multidimensional methods for microarray analysis.</p

Schematic representation of CCAM and instructions for its practical usage.

<p>(a) Overview of CCAM. See Methods for the full instructions. (b) Schematic representation of the decomposition of variation (<i>inertia</i>). (1) Total inertia is divided into constrained and unconstrained inertias by regression of main data on explanatory variables. (2) Constrained inertia is distributed to different axes by singular value decomposition.</p

Summary of microarray datasets used in this study.

<p>Summary of microarray datasets used in this study.</p