Miracle-dz/UniFAR-FTUs huggingface dataset:
A shared spatial topography links the functional connectome correlates of cocaine use disorder and dopamine D2/3 receptor densities

Background The biological mechanisms that contribute to cocaine and other substance use disorders involve an array of cortical and subcortical systems. Prior work on the development and maintenance of substance use has largely focused on cortico-striatal circuits, with relatively less attention on alterations within and across large-scale functional brain networks, and associated aspects of the dopamine system. The brain-wide pattern of temporal co-activation between distinct brain regions, referred to as the functional connectome, underpins individual differences in behavior. Critically, the functional connectome correlates of substance use and their specificity to dopamine receptor densities relative to other metabotropic receptors classes remains to be established. Methods We comprehensively characterized brain-wide differences in functional connectivity across multiple scales, including individual connections, regions, and networks in participants with cocaine use disorder (CUD; n=69) and healthy matched controls (n=62), Further, we studied the relationship between the observed functional connectivity signatures of CUD and the spatial distribution of a broad range of normative neurotransmitter receptor and transporter bindings as assessed through 18 different normative positron emission tomography (PET) maps. Results Our analyses identified a widespread profile of functional connectivity differences between individuals with CUD and matched healthy comparison participants (8.8% of total edges; 8,185 edges; pFWE=0.025). We largely find lower connectivity preferentially linking default network and subcortical regions, and higher within-network connectivity in the default network in participants with CUD. Furthermore, we find consistent and replicable associations between signatures of CUD and normative spatial density of dopamine D2/3 receptors. Conclusions Our analyses revealed a widespread profile of altered connectivity in individuals with CUD that extends across the functional connectome and implicates multiple circuits. This profile is robustly coupled with normative dopamine D2/3 receptors densities. Underscoring the translational potential of connectomic approaches for the study of in vivo brain functions, CUD- linked aspects of brain function were spatially coupled to disorder relevant neurotransmitter systems. Key Points Question Are there group differences in whole brain functional connectivity between individuals with and without cocaine use disorder, and to what extent do these connectivity patterns relate to the spatial distribution of dopamine (D2/3) receptor densities? Findings The presence of cocaine use disorder is associated with brain-wide functional connectivity alterations that are spatially coupled to the density of dopamine (D2/3) receptors. Meaning A preferential and replicable link exists between the functional connectome correlates of cocaine use disorder and dopamine receptor densities across the brain.
Spatial chromosome organization and adaptation of the radiation-resistant extremophile Deinococcus radiodurans

Radiation-resistant Deinococcus radiodurans is an extremophilic microorganism capable of withstanding high levels of ionizing radiation and chemical mutagens. It possesses remarkable DNA repair capability and serves as a model organism for studying stress resistance mechanism. However, our understanding on the spatial chromosome organization of this species remains limited. In this study, we employed chromosome conformation capture (3C) technology to determine the 3D genome structure of D. radiodurans and to further investigate the changes of chromosome conformation induced by ultraviolet (UV) irradiation. We observed that UV irradiation reduced short-range chromosome interactions, and smaller chromosomal interaction domains (CIDs) merged to form larger CIDs. Integrating transcriptomic data analysis, we found that the majority of upregulated differentially expressed genes were significantly enriched near specific CID boundaries. Specially, we comprehensively elucidated that the nucleoid-associated protein Dr_ebfC may serve as a global regulator for gene expression by altering chromosome structure, thereby influencing the physiological state of the bacterium. Overall, our study revealed the chromosome conformations of D. radiodurans under different conditions, and offered valuable insights into the molecular responses of this extremophile to environmental stresses.
Noncanonical Activity of Med4 as a Gatekeeper of Metastasis through Epigenetic Control of Integrin Signaling

Breast cancer metastatic relapse after a latency period, known as metastatic dormancy. Through genetic screening in mice, we identified the mediator complex subunit 4 (Med4) as a novel tumor-cell intrinsic gatekeeper in metastatic reactivation. Med4 downregulation effectively awakened dormant breast cancer cells, prompting macroscopic metastatic outgrowth in the lungs. Med4 depletion results in profound changes in nuclear size and three-dimensional chromatin architecture from compacted to relaxed states in contrast to the canonical function of the Mediator complex. These changes rewire the expression of extracellular matrix proteins, integrins, and signaling components resulting in integrin-mediated mechano-transduction and activation of YAP and MRTF. The assembly of stress fibers pulls on the nuclear membrane and contributes to reinforcing the overall chromatin modifications by Med4 depletion. MED4 gene deletions were observed in patients with metastatic breast cancer, and reduced MED4 expression correlates with worse prognosis, highlighting its significance as a potential biomarker for recurrence. Significance This work establishes the first link between Med4 and its role as an epigenetic and transcriptional repressor of ECM programs that reactivates dormant tumor cells in breast cancer metastasis. We highlight the distinct noncanonical role of Med4, in contrast to Med1, as well as the functional implications in vitro and in vivo. We have functionally validated the aberrant signaling pathways activated through both genetic add back and chemical inhibition and correlate our findings with Med4 expression, metastatic potential, and overall outcome in retrospective patient cohorts.
Identification of a novel papillomavirus from a New Zealand fur seal (Arctocephalus forsteri) with oral papilloma-like lesions

Despite being the predominant seal species in the Australian-New Zealand region and serving as a key indicator of marine environmental health, little is known about infectious diseases in New Zealand fur seals (Long-nosed fur seal; Arctocephalus forsteri). Several papillomaviruses have been identified in earless seals and sea lions, with the latter linked to cutaneous plaques and invasive squamous cell carcinoma. To date, no papillomaviruses have been reported in fur seals. We used traditional veterinary diagnostic techniques and metatranscriptomic sequencing of tissue samples to investigate the virome of New Zealand fur seals. We identified a novel papillomavirus, provisionally termed Arctocephalus forsteri papillomavirus 1 (AfPV1) in an animal with clinically and histologically identified oral papilloma-like lesions. RT-PCR confirmed the presence of AfPV1 only in oral papilloma samples from the affected individual. Phylogenetic analysis of the complete 7,926 bp genome of AfPV1 revealed that it clustered with taupapillomaviruses found in related Carnivora species. In addition, we identified the partial genome of a novel Gammaherpesvirus, Arctocephalus forsteri gammaherpesvirus 1 (AfGHV1), in a different individual without pathological evidence of viral infection. These findings highlight the need for further research into the disease associations and impact of undiagnosed and novel viruses on New Zealand fur seals.
Characterizing the monomer-dimer equilibrium of 1 UbcH8/Ube2L6: A combined SAXS and NMR 2 study 3

: Interferon-stimulated gene-15 (ISG15) is an interferon-induced protein with two 17 ubiquitin-like (Ubl) domains linked by a short peptide chain, and the conjugated protein of the 18 ISGylation system. Similar to ubiquitin and other Ubls, ISG15 is ligated to its target proteins with 19 a series of E1, E2, and E3 enzymes known as Uba7, Ube2L6/UbcH8, and HERC5, respectively. 20 Ube2L6/UbcH8 plays a literal central role in ISGylation, underscoring it as an important drug 21 target for boosting innate antiviral immunity. Depending on the type of conjugated protein and the 22 ultimate target protein, E2 enzymes have been shown to function as monomers, dimers, or both. 23 UbcH8 has been crystalized in both monomeric and dimeric forms, but the functional state is 24 unclear. Here, we used a combined approach of small-angle X-ray scattering (SAXS) and nuclear 25 magnetic resonance (NMR) spectroscopy to characterize UbcH8’s oligomeric state in solution. 26 SAXS revealed a dimeric UbcH8 structure that could be dissociated when fused with an N- 27 terminal glutathione S-transferase molecule. NMR spectroscopy validated the presence of a 28 concentration-dependent monomer-dimer equilibrium and suggested a backside dimerization 29 interface. Chemical shift perturbation and peak intensity analysis further suggest dimer-induced 30 conformational dynamics at ISG15 and E3 interfaces - providing hypotheses for the protein's 31 functional mechanisms. Our study highlights the power of combining NMR and SAXS techniques
Engineering orthogonal ribosomes for real-time monitoring using fluorescence

A promising route to tackle the trade-off in cellular resources between synthetic protein production and cellular growth is to use a separate dedicated pool of orthogonal ribosomes to produce synthetic proteins. However, the optimisation of strains containing two ribosomal pools – native for the host cell’s proteome and orthogonal for synthetic proteins – has yet to be thoroughly explored. Here, we address this by creating orthogonal ribosomes that fluoresce by inserting fluorescent RNA aptamers into tethered orthogonal ribosomal RNA (TO-rRNA). To study the tolerance of the engineered ribosomes to aptamer insertion, we assembled and screened a library of candidate insertion sites, identifying several sites in both the 16S and 23S TO-rRNA that enables ribosome labelling with minimal effect on translation activity. Serendipitously, we identify one site in 23S TO-rRNA, where insertion appears to not only be tolerated but to enhance orthogonal ribosome activity, across multiple bacterial strains and RNA insertions. Using bulk and single cell assays, we demonstrate that this variant allows us to label orthogonal ribosomes for dynamic tracking and across populations, making it a promising tool for optimising orthogonal translation in engineered cells. Ribosome engineering offers great potential, both for the development of next-generation microbial cell factories, as well as a tool to expand our understanding of ribosome function in living cells. This work provides a window into the assembly, localisation and function of these molecular machines to meet these aims.
Proteomic Features of Adolescents and Young Adults with Soft Tissue Tumours

Adolescents and young adult (AYA) patients with soft tissue tumours (STT) including sarcomas are an underserved group with disparities in treatment outcomes. To define the molecular features between AYA and older adult (OA) patients, we analysed the proteomic profiles of a large cohort of STT across 10 histological subtypes (AYA n=66, OA n=243). AYA tumours are enriched in proteins involved in mitochondrial metabolism while OA patients have elevated inflammatory and cell cycle signalling. By integrating the patient-level proteomic data with functional genomic profiles from sarcoma cell lines, we show that the mRNA splicing pathway is an intrinsic vulnerability in cell lines from OA patients and that components of the spliceosome complex are independent prognostic factors for metastasis free survival in AYA patients. Our study highlights the importance of performing age-specific molecular profiling studies to identify risk stratification tools and targeted agents tailored for the clinical management of AYA patients.
Is Modeling Access Control Worth It?

Implementing access control policies is an error-prone task that can have severe consequences for the security of software applications. Model-driven approaches have been proposed in the literature and associated tools have been developed with the goal of reducing the complexity of this task and helping developers to produce secure software efficiently. Nevertheless, there is a lack of empirical data supporting the advantages of model-driven security approaches over code-centric approaches, which are the de-facto industry standard for software development. In this work, we compare the result of implementing the same functional and security requirements by multiple developer groups in the context of a security engineering graduate course. We thereby obtain evidence on the security and efficiency of a tool-based model-driven approach to security from the literature compared to a direct implementation in a well-known, modern web-development framework. For example, the projects using model-driven development pass up to 50% more security tests on average with less development effort. Also, we observe that models are twice as concise as manual implementations, which improves system maintainability.
TunneLs for Bootlegging: Fully Reverse-Engineering GPU TLBs for Challenging Isolation Guarantees of NVIDIA MIG

Recent studies have revealed much detailed information about the translation lookaside buffers (TLBs) of modern CPUs, but we find that many properties of such components in modern GPUs still remain unknown or unclear. To fill this knowledge gap, we develop a new GPU TLB reverse-engineering method and apply it to a variety of consumer- and server-grade GPUs in Turing and Ampere generations. Aside from learning significantly more comprehensive and accurate GPU TLB properties, we discover a design flaw of NVIDIA Multi-Instance GPU (MIG) feature. MIG claims full partitioning of the entire GPU memory system for secure GPU sharing in cloud computing. However, we surprisingly find that MIG does not partition the last-level TLB, which is shared by all the compute units in a GPU. Exploiting this design flaw and learned TLB properties, we are able to construct a covert channel for data exfiltration across MIG-enforced isolation. To the best of our knowledge, this is the first attack on MIG. We evaluate the proposed attack on a commercial cloud platform, and we successfully achieve reliable data exfiltration from a victim tenant at a speed of up to 31 kbps with a very high accuracy around 99.8%. Even when the victim is using the GPU for deep neural network training, the transmission can still reach more than 25 kbps with a more than 99.5% accuracy. We propose and implement a mitigation approach that can effectively thwart data exfiltration through this covert channel. Additionally, we present a preliminary study on exploiting the access patterns of the last-level TLB to infer the identity of applications running in other MIG-created GPU instances.
Pakistani Teens and Privacy - How Gender Disparities, Religion and Family Values Impact the Privacy Design Space

The understanding of how teenagers perceive, manage and perform privacy is less well-understood in spaces outside of Western, educated, industrialised, rich and democratic countries. To fill this gap we interviewed 30 teens to investigate the privacy perceptions, practices, and experienced digital harms of young people in Pakistan, a particularly interesting context as privacy in this context is not seen as an individual right or performed within an individualistic framework but instead is influenced by a combination of factors including social norms, family dynamics and religious beliefs. Based on our findings, we developed four personas to systematize the needs and values of this specific population and then conducted focus groups with co-design activities to further explore privacy conflicts. Among other things that confirm and extend existing theories on teen's privacy practices and perceptions, our findings suggest that young women are disproportionately impacted by privacy violations and the harms extend beyond themselves to include their families.
Vulnerability Intelligence Alignment via Masked Graph Attention Networks

Cybersecurity vulnerability information is often sourced from multiple channels, such as government vulnerability repositories, individually maintained vulnerability-gathering platforms, or vulnerability-disclosure email lists and forums. Integrating vulnerability information from different channels enables comprehensive threat assessment and quick deployment to various security mechanisms. However, automatic integration of vulnerability information, especially those lacking decisive information (e.g., CVE-ID), is hindered by the limitations of today's entity alignment techniques. In our study, we annotate and release the first cybersecurity-domain vulnerability alignment dataset, and highlight the unique characteristics of security entities, including the inconsistent vulnerability artifacts of identical vulnerability (e.g., impact and affected version) in different vulnerability repositories. Based on these characteristics, we propose an entity alignment model, CEAM, for integrating vulnerability information from multiple sources. CEAM equips graph neural network-based entity alignment techniques with two application-driven mechanisms: asymmetric masked aggregation and partitioned attention. These techniques selectively aggregate vulnerability artifacts to learn the semantic embeddings for vulnerabilities by an asymmetric mask, while ensuring that the artifacts critical to the vulnerability identification are always taken more consideration. Experimental results on vulnerability alignment datasets demonstrate that CEAM significantly outperforms state-of-the-art entity alignment methods.
FaceReader: Unobtrusively Mining Vital Signs and Vital Sign Embedded Sensitive Info via AR/VR Motion Sensors

The market size of augmented reality and virtual reality (AR/VR) has been expanding rapidly in recent years, with the use of face-mounted headsets extending beyond gaming to various application sectors, such as education, healthcare, and the military. Despite the rapid growth, the understanding of information leakage through sensor-rich headsets remains in its infancy. Some of the headset's built-in sensors do not require users' permission to access, and any apps and websites can acquire their readings. While theseunrestricted sensors are generally considered free of privacy risks, we find that an adversary could uncover private information by scrutinizing sensor readings, making existing AR/VR apps and websites potential eavesdroppers. In this work, we investigate a novel, unobtrusive privacy attack called FaceReader, which reconstructs high-quality vital sign signals (breathing and heartbeat patterns) based on unrestricted AR/VR motion sensors. FaceReader is built on the key insight that the headset is closely mounted on the user's face, allowing the motion sensors to detect subtle facial vibrations produced by users' breathing and heartbeats. Based on the reconstructed vital signs, we further investigate three more advanced attacks, including gender recognition, user re-identification, and body fat ratio estimation. Such attacks pose severe privacy concerns, as an adversary may obtain users' sensitive demographic/physiological traits and potentially uncover their real-world identities. Compared to prior privacy attacks relying on speeches and activities, FaceReader targets spontaneous breathing and heartbeat activities that are naturally produced by the human body and are unobtrusive to victims. In particular, we design an adaptive filter to dynamically mitigate the impacts of body motions. We further employ advanced deep-learning techniques to reconstruct vital sign signals, achieving signal qualities comparable to those of dedicated medical instruments, as well as deriving sensitive gender, identity, and body fat information. We conduct extensive experiments involving 35 users on three types of mainstream AR/VR headsets across 3 months. The results reveal that FaceReader can reconstruct vital signs with low mean errors and accurately detect gender (over 93.33%). The attack can also link/re-identify users across different apps, websites, and longitudinal sessions with over 97.83% accuracy. Furthermore, we present the first successful attempt at revealing body fat information from motion sensor data, achieving a remarkably low estimation error of 4.43%.
WiCop: Engineering WiFi Temporal White-Spaces for Safe Operations of Wireless Personal Area Networks in Medical Applications

ZigBee and other wireless technologies operating in the (2.4GHz) ISM band are being applied in Wireless Personal Area Networks (WPAN) for many medical applications. However, these low duty cycle, low power, and low data rate medical WPANs suffer from WiFi co-channel interferences. WiFi interference can lead to longer latency and higher packet losses in WPANs, which can be particularly harmful to safety-critical applications with stringent temporal requirements, such as ElectroCardioGraphy (ECG). This paper exploits the Clear Channel Assessment (CCA) mechanism in WiFi devices and proposes a novel policing framework, WiCop, that can effectively control the temporal white-spaces between WiFi transmissions. Such temporal white-spaces can be utilized for delivering low duty cycle WPAN traffic. We have implemented and validated WiCop on SORA, a software-defined radio platform. Experimental results show that with the assistance of the proposed WiCop policing schemes, the packet reception rate of a ZigBee-based WPAN can increase by up to 116% in the presence of a heavy WiFi interferer. A case study on the medical application of WPAN ECG monitoring demonstrates that WiCop can bound ECG signal distortion within 2% even under heavy WiFi interference. An analytical framework is devised to model the CCA behavior of WiFi interferers and the performance of WPANs under WiFi interference with or without WiCop protection. The analytical results are corroborated by experiments.
Are duplicates really harmful? An empirical study on bug report summarization techniques

Recent research works have proven that duplicate bug reports can provide helpful information to assist developers in software tasks such as fault localization and program fixing, while thoroughly reading duplicate bug reports is time‐consuming and inefficient. Summarization is a possible solution for gaining essential information quickly. However, there are many challenges when applying existing summarizing techniques on duplicate bug reports. Duplicate bug reports describe the same problem from different views and vary in quality, content, and writing style. Moreover, the code snippet understanding and the semantic gap between natural and programming languages make the summary generation even more difficult. Thus, in this paper, we want to investigate whether the state‐of‐the‐art summarization approaches can overcome the resistance and generate an effective summary for duplicate bug reports. We collected more than 8,000 groups of duplicate reports from GitHub and labeled 60 groups with 149 reports manually for the evaluation. Results showed that although the existing summarization approaches can work on duplicate bug reports, there are significant differences between them when it comes to code snippet summarization. Moreover, several methods can be very sluggish for summarizing long bug reports. Our study provides insights and guidelines for choosing proper summarization approaches in different scenarios.