With millions of apps that can be downloaded from official or third-party market, Android has become one of the most popular mobile platforms today. These apps help people in all kinds of ways and thus have access to lots of user's data that in general fall into three categories: sensitive data, data to be shared with other apps, and non-sensitive data not to be shared with others. For the first and second type of data, Android has provided very good storage models: an app's private sensitive data are saved to its private folder that can only be access by the app itself, and the data to be shared are saved to public storage (either the external SD card or the emulated SD card area on internal FLASH memory). But for the last type, i.e., an app's non-sensitive and non-shared data, there is a big problem in Android's current storage model which essentially encourages an app to save its non-sensitive data to shared public storage that can be accessed by other apps. At first glance, it seems no problem to do so, as those data are non-sensitive after all, but it implicitly assumes that app developers could correctly identify all sensitive data and prevent all possible information leakage from private-but-non-sensitive data. In this paper, we will demonstrate that this is an invalid assumption with a thorough survey on information leaks of those apps that had followed Android's recommended storage model for non-sensitive data. Our studies showed that highly sensitive information from billions of users can be easily hacked by exploiting the mentioned problematic storage model. Although our empirical studies are based on a limited set of apps, the identified problems are never isolated or accidental bugs of those apps being investigated. On the contrary, the problem is rooted from the vulnerable storage model recommended by Android. To mitigate the threat, we also propose a defense framework.

Abstract According to previous reports, information could be leaked from GPU memory; however, the security implications of such a threat were mostly over-looked, because only limited information could be indirectly extracted through side-channel attacks. In this paper, we propose a novel algorithm for recovering raw data directly from the GPU memory residues of many popular applications such as Google Chrome and Adobe PDF reader. Our algorithm enables harvesting highly sensitive information including credit card numbers and email contents from GPU memory residues. Evaluation results also indicate that nearly all GPU-accelerated applications are vulnerable to such attacks, and adversaries can launch attacks without requiring any special privileges both on traditional multi-user operating systems, and emerging cloud computing scenarios.

Higher-order visual thalamus plays a fundamental but poorly understood role in attention-demanding tasks. To investigate how neuronal dynamics in higher-order visual thalamus are modulated by sustained attention, we performed multichannel electrophysiological recordings in the lateral posterior-pulvinar complex (LP/pulvinar) in the ferret (Mustela putorius furo). We recorded single unit activity and local field potential (LFP) during the performance of the five-choice serial reaction time task (5-CSRTT), which is used in both humans and animals as an assay of sustained attention. We found that half of the units exhibited an increasing firing rate during the delay period before stimulus onset (attention-modulated units). In contrast, the non-attention-modulated units responded to the stimulus, but not during the delay period. Spike-field coherence (SFC) of only the attention-modulated neurons significantly increased from the start of the delay period until screen touch, predominantly in the θ frequency band. In addition, θ power and θ/γ phase amplitude coupling (PAC) were elevated throughout the delay period. Our findings suggest that the θ oscillation plays a central role in orchestrating thalamic signaling during sustained attention.

Sustained attention requires the coordination of neural activity across multiple cortical areas in the frontoparietal network, in particular the prefrontal cortex (PFC) and posterior parietal cortex (PPC). Previous work has demonstrated that activity in these brain regions is coordinated by neuronal oscillations of the local field potential (LFP). However, the underlying coordination of activity in terms of organization of single unit (SU) spiking activity has remained poorly understood, particularly in the freely moving animal. We found that long-range functional connectivity between anatomically connected PFC and PPC was mediated by oscillations in the theta frequency band. SU activity in PFC was phase locked to theta oscillations in PPC, and spiking activity in PFC and PPC was locked to local high-gamma activity. Together, our results support a model in which frequency-specific synchronization mediates functional connectivity between and within PFC and PPC of the frontoparietal attention network in the freely moving animal.

Although oscillations during development have been characterized in a wide range of neural systems, little is known about the interaction between these network oscillations and neuronal spiking, and the interactions among different oscillation frequencies. Here we recorded the spontaneous and visual-elicited local field potential (LFP) and multi-unit activity (MUA) in the visual cortex of freely-moving juvenile ferrets before and after eye-opening. We found that both the spontaneous and visually-elicited LFP power was increased after eye-opening, especially in higher frequency bands (>30 Hz). Spike LFP phase coupling was decreased for lower frequency bands (theta and alpha) but slightly increased for higher frequencies (high-gamma band). A similar shift towards faster frequencies also occurred for phase-amplitude coupling; with maturation, the coupling of the theta/alpha/beta band amplitude to the delta phase was decreased and the high-gamma amplitude coupling to theta/alpha phase was increased. This shift towards higher frequencies was also reflected in the visual responses; the LFP oscillation became more entrained by visual stimulation with higher frequencies (>10 Hz). Taken together, these results suggest gamma oscillation as a signature of the maturation of cortical circuitry.

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function.

Background

The neurotrophic factor Artemin (ARTN) is involved in tumor proliferation and metastasis. Nonetheless, ARTN's significance in cervical cancer (CC) has not been studied. In our study, we propose to investigate the biological function of ARTN in CC as well as its particular regulatory mechanism.

Methods

Immunohistochemistry (IHC) was used to examine the degree of ARTN protein expression in CC patient tissue. Real-time PCR and Western blotting were performed to reveal related genes' levels in CC cells. The CCK-8 test, the colony formation assay, the wound-healing assay, and the transwell assay were utilized to determine the proliferation, migration, and invasion capabilities, respectively. To generate lung metastasis models, stable ARTN-expressing SiHa cells were injected into the caudal tail vein of mice. IHC was used to examine the protein levels in CC mice model tissues.

Results

ARTN was overexpressed in CC tissues relative to normal cervical tissues and linked positively with lymph node metastases (P=0.012) and recurrence (P=0.015) in CC patients. In vitro, ARTN overexpression promoted the proliferation, invasion, and migration of CC cells. In contrast, the consequences of depleting endogenous ARTN were the opposite. Moreover, overexpression of ARTN increased lung metastasis of CC cells in vivo and shortened the lifespan of mice models. In addition, ARTN overexpression significantly enhanced AKT phosphorylation on Ser473 and mTOR phosphorylation on Ser2448 and promoted the epithelial-mesenchymal transition (EMT) cascade. In addition, rapamycin, a selective inhibitor of mTORC1, might rescue the EMT phenotype caused by ARTN.

Conclusion

Our findings suggested that ARTN may enhance CC metastasis through the AKT/mTORC1 pathway. ARTN is anticipated to be a novel potential therapeutic target for the treatment of CC metastases.

The growth of the Tibetan Plateau throughout the past 66 million years has profoundly affected the Asian climate, but how this unparalleled orogenesis might have driven vegetation and plant diversity changes in eastern Asia is poorly understood. We approach this question by integrating modeling results and fossil data. We show that growth of north and northeastern Tibet affects vegetation and, crucially, plant diversity in eastern Asia by altering the monsoon system. This northern Tibetan orographic change induces a precipitation increase, especially in the dry (winter) season, resulting in a transition from deciduous broadleaf vegetation to evergreen broadleaf vegetation and plant diversity increases across southeastern Asia. Further quantifying the complexity of Tibetan orographic change is critical for understanding the finer details of Asian vegetation and plant diversity evolution.