We demonstrated a downward spreading pattern of amyloid, suggesting that amyloid accumulates first in neocortex followed by subcortical structures. Furthermore, our new finding suggested that an amyloid staging scheme based on subcortical involvement might reveal how differential regional accumulation of amyloid affects cognitive decline through functional and structural changes of the brain.
Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are “small world.” There were significant difference between NC and AD group in characteristic path lengths (z = −2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC dataset.
Rationale: Cancer immunotherapy combining immune checkpoint blockade (ICB) with chemotherapeutic drugs has provided significant clinical advances. However, such combination therapeutic regimen has suffered from severe toxicity of both drugs and low response rate of patients. In this study, we propose anti-PD-L1 peptide-conjugated prodrug nanoparticles (PD-NPs) to overcome these obstacles of current cancer immunotherapy. Methods: The functional peptide, consisted of anti-PD-L1 peptide and cathepsin B-specific cleavable peptide, is conjugated to a doxorubicin (DOX), resulting in prodrug nanoparticles of PD-NPs via intermolecular interactions. The antitumor efficacy and immune responses with minimal side effects by PD-NPs combining PD-L1 blockade and ICD are evaluated in breast tumor models. Results : The PD-NPs are taken up by PD-L1 receptor-mediated endocytosis and then induce ICD in cancer cells by DOX release. Concurrently, PD-L1 blockade by PD-NPs disrupt the immune-suppressing pathway of cancer cells, resulting in proliferation and reinvigoration of T lymphocytes. In tumor models, PD-NPs accumulate within tumor tissues via enhanced permeability and retention (EPR) effect and induce immune-responsive tumors by recruiting a large amount of immune cells. Conclusions: Collectively, targeted tumor delivery of anti-PD-L1 peptide and DOX via PD-NPs efficiently inhibit tumor progression with minimal side effects.
The use of iodide as the positive redox-active species in redox flow batteries has been highly anticipated owing to its attractive features of high solubility, excellent reversibility, and low cost. However, the electro-oxidation reaction of iodide (I − ) is very complicated, giving various possible products such as iodine (I 2 ), polyiodides (I 2n+1 − ), and polyiodines (I 2n+2 ) with n ≥ 1. In particular, the electro-oxidation of I − /I 3 − and I 3 − /I 2 occurs in competition depending on the applied potential. Although the former reaction is adopted as the main reaction in most redox flow batteries because I 3 − is highly soluble in an aqueous electrolyte, the latter reaction inevitably occurs together and a thick I 2 -film forms on the electrode, impeding the electro-oxidation of I − . In this study, we investigate the variation of the interface between the electrode and the electrolyte during the development of an I 2 -film and the corresponding change in the charge-transfer resistance (R ct ). Initially, the I 2 -film builds upon the electrode surface in the form of a porous layer and the aqueous I − ions can easily reach the electrode surface through pores inside the film. I − ions are electro-oxidized to I 3 − or I 2 at the interface between the aqueous I − phase and electrode with a small R ct of less than 16.5 ohm•cm 2 . Over time, the I 2 -film is converted into a dense layer and I − ions diffuse through the film in the form of I 3 − , possibly by a Grotthuss-type hopping mechanism. I 3 − can then be electro-oxidized to I 2 at the new interface between the I 2 -film and electrode, resulting in a dramatic 9-fold increase of R ct to 147.4 ohm•cm 2 . This increase of R ct by the dense I 2 -film is also observed in the actual flow battery. At high current densities above 400 mA•cm −2 , the overpotential begins to show an abrupt increase in the amplitude of more than 300 mV after reaching a critical charging capacity at which the dense I 2 -film appears to have begun to form on the felt electrode. Therefore, the I 2 -film exerts a serious negative effect on the performance of the flow battery depending on the current density and electrolyte SoC (state-of-charge).
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