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The mechanisms leading to changes in mesoscale chromatin organization during cellular aging are unknown. Here, we used transcriptional activator-like effectors, RNA-seq and superresolution analysis to determine the effects of genotoxic stress on oocyte chromatin structure. Major satellites are organized into tightly packed globular structures that coalesce into chromocenters and dynamically associate with the nucleolus. Acute irradiation significantly enhanced chromocenter mobility in transcriptionally inactive oocytes. In transcriptionally active oocytes, irradiation induced a striking unfolding of satellite chromatin fibers and enhanced the expression of transcripts required for protection from oxidative stress (Fermt1, Smg1), recovery from DNA damage (Tlk2, Rad54l) and regulation of heterochromatin assembly (Zfp296, Ski-oncogene). Non-irradiated, senescent oocytes exhibit not only high chromocenter mobility and satellite distension but also a high frequency of extra chromosomal satellite DNA. Notably, analysis of biological aging using an oocyte-specific RNA clock revealed cellular communication, posttranslational protein modifications, chromatin and histone dynamics as the top cellular processes that are dysregulated in both senescent and irradiated oocytes. Our results indicate that unfolding of heterochromatin fibers following acute genotoxic stress or cellular aging induced the formation of distended satellites and that abnormal chromatin structure together with increased chromocenter mobility leads to chromosome instability in senescent oocytes.

 

Digital content services provide users with a wide range of content, such as news, articles, or movies, while monetizing their content through various business models and promotional methods. Unfortunately, poorly designed or unpro- tected business logic can be circumvented by malicious users, which is known as business flow tampering. Such flaws can severely harm the businesses of digital content service providers. In this paper, we propose an automated approach that discov- ers business flow tampering flaws. Our technique automatically runs a web service to cover different business flows (e.g., a news website with vs. without a subscription paywall) to collect execution traces. We perform differential analysis on the execution traces to identify divergence points that determine how the business flow begins to differ, and then we test to see if the divergence points can be tampered with. We assess our approach against 352 real-world digital content service providers and discover 315 flaws from 204 websites, including TIME, Fortune, and Forbes. Our evaluation result shows that our technique successfully identifies these flaws with low false-positive and false- negative rates of 0.49% and 1.44%, respectively. 

Smart homes contain diverse sensors and actuators controlled by IoT apps that provide custom automation. Prior works showed that an adversary could exploit physical interaction vulnerabilities among apps and put the users and environment at risk, e.g., to break into a house, an adversary turns on the heater to trigger an app that opens windows when the temperature exceeds a threshold. Currently, the safe behavior of physical interactions relies on either app code analysis or dynamic analysis of device states with manually derived policies by developers. However, existing works fail to achieve sufficient breadth and fidelity to translate the app code into their physical behavior or provide incomplete security policies, causing poor accuracy and false alarms. In this paper, we introduce a new approach, IoTSeer, which efficiently combines app code analysis and dynamic analysis with new security policies to discover physical interaction vulnerabilities. IoTSeer works by first translating sensor events and actuator commands of each app into a physical execution model (PeM) and unifying PeMs to express composite physical execution of apps (CPeM). CPeM allows us to deploy IoTSeer in different smart homes by defining its execution parameters with minimal data collection. IoTSeer supports new security policies with intended/unintended physical channel labels. It then efficiently checks them on the CPeM via falsification, which addresses the undecidability of verification due to the continuous and discrete behavior of IoT devices. We evaluate IoTSeer in an actual house with 14 actuators, six sensors, and 39 apps. IoTSeer discovers 16 unique policy violations, whereas prior works identify only 2 out of 16 with 18 falsely flagged violations. IoTSeer only requires 30 mins of data collection for each actuator to set the CPeM parameters and is adaptive to newly added, removed, and relocated devices. 

Abstract We present the analysis of seven microlensing planetary events with planet/host mass ratios q < 10 −4 : KMT-2017-BLG-1194, KMT-2017-BLG-0428, KMT-2019-BLG-1806, KMT-2017-BLG-1003, KMT-2019-BLG-1367, OGLE-2017-BLG-1806, and KMT-2016-BLG-1105. They were identified by applying the Korea Microlensing Telescope Network (KMTNet) AnomalyFinder algorithm to 2016–2019 KMTNet events. A Bayesian analysis indicates that all the lens systems consist of a cold super-Earth orbiting an M or K dwarf. Together with 17 previously published and three that will be published elsewhere, AnomalyFinder has found a total of 27 planets that have solutions with q < 10 −4 from 2016–2019 KMTNet events, which lays the foundation for the first statistical analysis of the planetary mass-ratio function based on KMTNet data. By reviewing the 27 planets, we find that the missing planetary caustics problem in the KMTNet planetary sample has been solved by AnomalyFinder. We also find a desert of high-magnification planetary signals ( A ≳ 65), and a follow-up project for KMTNet high-magnification events could detect at least two more q < 10 −4 planets per year and form an independent statistical sample.