ATM: Functions of ATM Kinase and Its Relevance to Hereditary Tumors

Ataxia-telangiectasia mutated (ATM) functions as a key initiator and coordinator of DNA damage and cellular stress responses. ATM signaling pathways contain many downstream targets that regulate multiple important cellular processes, including DNA damage repair, apoptosis, cell cycle arrest, oxidative sensing, and proliferation. Over the past few decades, associations between germline ATM pathogenic variants and cancer risk have been reported, particularly for breast and pancreatic cancers. In addition, given that ATM plays a critical role in repairing double-strand breaks, inhibiting other DNA repair pathways could be a synthetic lethal approach. Based on this rationale, several DNA damage response inhibitors are currently being tested in ATM-deficient cancers. In this review, we discuss the current knowledge related to the structure of the ATM gene, function of ATM kinase, clinical significance of ATM germline pathogenic variants in patients with hereditary cancers, and ongoing efforts to target ATM for the benefit of cancer patients

Small congestion embedding of graphs into hypercubes

金沢大学大学院自然科学研究科知能情報・数理金沢大学工学部We consider the problem of embedding graphs into hypercubes with minimal congestion. Kim and Lai showed that for a given N-vertex graph G and a hypercube it is NP-complete to determine whether G is embeddable in the hypercube with unit congestion, but G can be embedded with unit congestion in a hypercube of dimension 6[log N] if the maximum degree of a vertex in G is no more than 6[log N]. Bhatt et al. showed that every N-vertex binary tree can be embedded in a hypercube of dimension [log N] with O(1) congestion. In this paper, we extend the results above and show the following : (1) Every N-vertex graph G can be embedded with unit congestion in a hypercube of dimension 2[log N] if the maximum degree of a vertex in G is no more than 2[log N], and (2) every N-vertex binary tree can be embedded in a hypercube of dimension [log N] with congestion at most 5. The former answers a question posed by Kim and Lai. The latter is the first result that shows a simple embedding of a binary tree into an optimal-sized hypercube with an explicit small congestion of 5. This partially answers a question posed by Bhatt et al. The embeddings proposed here are quite simple and can be constructed in polynomial time. © 1999 John Wiley & Sons, Inc. Networks 33: 71-77, 1999

Extensive Preferential Pathway Ablation for the Elimination of Premature Ventricular Contractions Arising from the Right Ventricular Outflow Tract

AbstractA 76 y/o women presented with 2 different types of premature ventricular contractions (VPCs 1 and 2) arising from the right ventricular outflow tract (RVOT). Catheter ablation (CA) eliminated PVC1 at the earliest activation site (EAS), but thereafter another PVC morphology (PVC3) appeared. Small potentials preceding the local potential were broadly exhibited from the RVOT’s supero-anterior region to the EAS during PVC3. Point CA targeting such prepotentials failed. Transverse-linear CA with a line connecting sites with such pre-potentials eliminated both PVCs 3 and 2. In cases with broadly spreading preferential pathways, extensive CA might be needed to eliminate the PVCs

距骨壊死に対するアルミナセラミック性人工距骨置換術のSAFE-Qを用いた臨床成績

Background: The purpose of this retrospective review was to evaluate the clinical outcomes of patients who underwent total talar replacement for talar necrosis using the SAFE-Q score, which was hypothesized to improve postoperatively. Methods: The study included 24 ankles of 22 patients who underwent total talar replacement from 2012 to 2018 and were evaluated using SAFE-Q preoperatively and postoperatively. Statistical analysis was performed using the mean values of the SAFE-Q and JSSF scale scores, and the range of ankle motion was compared before and 3 years after the surgery using the Wilcoxon signed-rank test. Results: The SAFE-Q scores improved postoperatively in the all the subcategories. “Pain and Pain-Related” changed from a mean value of 42.2±23.9 points preoperatively to a mean value of 84.6±12.6 points postoperatively (p<.01); “Physical Functioning and Daily Living” changed from 36.3±25.2 points to 73.4±20.5 points (p<.01); “Social Functioning” changed from 34.1±34.8 points to 81.0±25.3 points (p<.01); “Shoe-Related” changed from 41.3±28.9 points to 75.4±22.3 points (p<.01); “General Health and Well-Being” changed from 36.7±32.1 to 76.9±29.3 points (p<.01). Conclusion: Twenty-four osteonecrotic tali of 22 patients treated with alumina ceramic total talar replacement achieved good clinical results, as evaluated using the JSSF ankle/hindfoot score and SAFE-Q. Alumina ceramic total talar replacement is the mainstream treatment for talar osteonecrosis.博士（医学）・甲第856号・令和4年12月22

Perceived Information Revisited

In this study, we present new analytical metrics for evaluating the performance of side-channel attacks (SCAs) by revisiting the perceived information (PI), which is defined using cross-entropy (CE). PI represents the amount of information utilized by a probability distribution that determines a distinguishing rule in SCA. Our analysis partially solves an important open problem in the performance evaluation of deep-learning based SCAs (DL-SCAs) that the relationship between neural network (NN) model evaluation metrics (such as accuracy, loss, and recall) and guessing entropy (GE)/success rate (SR) is unclear. We first theoretically show that the conventional CE/PI is non-calibrated and insufficient for evaluating the SCA performance, as it contains uncertainty in terms of SR. More precisely, we show that an infinite number of probability distributions with different CE/PI can achieve an identical SR. With the above analysis result, we present a modification of CE/PI, named effective CE/PI (ECE/EPI), to eliminate the above uncertainty. The ECE/EPI can be easily calculated for a given probability distribution and dataset, which would be suitable for DL-SCA. Using the ECE/EPI, we can accurately evaluate the SR hrough the validation loss in the training phase, and can measure the generalization of the NN model in terms of SR in the attack phase. We then analyze and discuss the proposed metrics regarding their relationship to SR, conditions of successful attacks for a distinguishing rule with a probability distribution, a statistic/asymptotic aspect, and the order of key ranks in SCA. Finally, we validate the proposed metrics through experimental attacks on masked AES implementations using DL-SCA

On the Success Rate of Side-Channel Attacks on Masked Implementations: Information-Theoretical Bounds and Their Practical Usage

This study derives information-theoretical bounds of the success rate (SR) of side-channel attacks on masked implementations. We first develop a communication channel model representing side-channel attacks on masked implementations. We then derive two SR bounds based on the conditional probability distribution and mutual information of shares. The basic idea is to evaluate the upper-bound of the mutual information between the non-masked secret value and the side-channel trace by the conditional probability distribution of shares given its leakage, with a help of the Walsh–Hadamard transform. With the derived theorems, we also prove the security of masking schemes: the SR decreases exponentially with an increase in the number of masking shares, under a much more relaxed condition than the previous proof. To validate and utilize our theorems in practice, we propose a deep-learning-based profiling method for approximating the conditional probability distribution of shares to estimate the SR bound and the number of traces required for attacking a given device. We experimentally confirm that our bounds are much stronger than the conventional bounds on masked implementations, which validates the relevance of our theorems to practice

Perceived Information Revisited II: Information-Theoretical Analysis of Deep-Learning Based Side-Channel Attacks

In conventional deep-learning-based side-channel attacks (DL-SCAs), an attacker trains a model by updating parameters to minimize the negative log-likelihood (NLL) loss function. Although a decrease in NLL improves DL-SCA performance, the reasons for this improvement remain unclear because of the lack of a formal analysis. To address this open problem, this paper explores the relationship between NLL and the attack success rate (SR) and conducts an information-theoretical analysis of DL-SCAs with an NLL loss function to solve open problems in DL-SCA. To this end, we introduce a communication channel for DL-SCAs and derive an inequality that links model outputs to the SR. Our inequality states that mutual information between the model output and intermediate value, which is named the latent perceived information (LPI), provides an upper bound of the SR of a DL-SCA with a trained neural network. Subsequently, we examine the conjecture by Ito et al. on the relationship between the effective perceived information (EPI) and SR and clarify its valid conditions from the perspective of LPI. Our analysis results reveal that a decrease in NLL correlated with an increase in LPI, which indicates that the model capability to extract intermediate value information from traces is enhanced. In addition, the results indicate that the LPI bounds the SR from above, and a higher upper bound of the SR could directly improve the SR if the selection function satisfies certain conditions, such as bijectivity. Finally, these theoretical insights are validated through attack experiments on neural network models applied to AES software and hardware implementations with masking countermeasures