On R\'{e}nyi Differential Privacy in Statistics-Based Synthetic Data Generation

Privacy protection with synthetic data generation often uses differentially private statistics and model parameters to quantitatively express theoretical security. However, these methods do not take into account privacy protection due to the randomness of data generation. In this paper, we theoretically evaluate R\'{e}nyi differential privacy of the randomness in data generation of a synthetic data generation method that uses the mean vector and the covariance matrix of an original dataset. Specifically, for a fixed $\alpha > 1$, we show the condition of $\varepsilon$ such that the synthetic data generation satisfies $(\alpha, \varepsilon)$-R\'{e}nyi differential privacy under a bounded neighboring condition and an unbounded neighboring condition, respectively. In particular, under the unbounded condition, when the size of the original dataset and synthetic datase is 10 million, the mechanism satisfies $(4, 0.576)$-R\'{e}nyi differential privacy. We also show that when we translate it into the traditional $(\varepsilon, \delta)$-differential privacy, the mechanism satisfies $(4.00, 10^{-10})$-differential privacy.Comment: 18 pages, 3 figure

Long-term results of a randomized controlled trial comparing neoadjuvant Adriamycin, cisplatin, and 5-fluorouracil vs docetaxel, cisplatin, and 5-fluorouracil followed by surgery for esophageal cancer (OGSG1003)

Sugimura, K, Yamasaki, M, Yasuda, T, et al. Long‐term results of a randomized controlled trial comparing neoadjuvant Adriamycin, cisplatin, and 5‐fluorouracil vs docetaxel, cisplatin, and 5‐fluorouracil followed by surgery for esophageal cancer (OGSG1003). Ann. Gastroenterol. Surg. 2020; 00: 1– 8. https://doi.org/10.1002/ags3.12388

Alzheimer Aβ Assemblies Accumulate in Excitatory Neurons upon Proteasome Inhibition and Kill Nearby NAKα3 Neurons by Secretion

アルツハイマー病の神経毒性物質の形成と伝搬機構を解明 --発症に繋がる新たなメカニズムを提案--. 京都大学プレスリリース. 2019-03-01.We identified ∼30-mer amyloid-β protein (Aβ) assemblies, termed amylospheroids, from brains of patients with Alzheimer disease (AD) as toxic entities responsible for neurodegeneration and showed that Na+, K+-ATPase α3 (NAKα3) is the sole target of amylospheroid-mediated neurodegeneration. However, it remains unclear where in neurons amylospheroids form and how they reach their targets to induce neurodegeneration. Here, we present an in vitro culture system designed to chronologically follow amylospheroid formation in mature neurons expressing amyloid precursor protein bearing early-onset AD mutations. Amylospheroids were found to accumulate mainly in the trans-Golgi network of excitatory neurons and were initially transported in axons. Proteasome inhibition dramatically increased amylospheroid amounts in trans-Golgi by increasing Aβ levels and induced dendritic transport. Amylospheroids were secreted and caused the degeneration of adjacent NAKα3-expressing neurons. Interestingly, the ASPD-producing neurons later died non-apoptotically. Our findings demonstrate a link between ASPD levels and proteasome function, which may have important implications for AD pathophysiology

Automated algorithm development to assess survival of human neurons using longitudinal single-cell tracking: Application to synucleinopathy

The development of phenotypic assays with appropriate analyses is an important step in the drug discovery process. Assays using induced pluripotent stem cell (iPSC)-derived human neurons are emerging as powerful tools for drug discovery in neurological disease. We have previously shown that longitudinal single cell tracking enabled the quantification of survival and death of neurons after overexpression of α-synuclein with a familial Parkinson's disease mutation (A53T). The reliance of this method on manual counting, however, rendered the process labor intensive, time consuming and error prone. To overcome these hurdles, we have developed automated detection algorithms for neurons using the BioStation CT live imaging system and CL-Quant software. In the current study, we use these algorithms to successfully measure the risk of neuronal death caused by overexpression of α-synuclein (A53T) with similar accuracy and improved consistency as compared to manual counting. This novel method also provides additional key readouts of neuronal fitness including total neurite length and the number of neurite nodes projecting from the cell body. Finally, the algorithm reveals the neuroprotective effects of brain-derived neurotrophic factor (BDNF) treatment in neurons overexpressing α-synuclein (A53T). These data show that an automated algorithm improves the consistency and considerably shortens the analysis time of assessing neuronal health, making this method advantageous for small molecule screening for inhibitors of synucleinopathy and other neurodegenerative diseases