Structural versatility that serves the function of the HRD motif in the catalytic loop of protein tyrosine kinase, Src

Site‐directed mutagenesis is a traditional approach for structure–function analysis of protein tyrosine kinases, and it requires the generation, expression, purification, and analysis of each mutant enzyme. In this study, we report a versatile high throughput bacterial screening system that can identify functional kinase mutants by immunological detection of tyrosine phosphorylation. Two key features of this screening system are noteworthy. First, instead of blotting bacterial colonies directly from Agar plates to nitrocellulose membrane, the colonies were cultured in 96‐well plates, and then spotted in duplicate onto the membrane with appropriate controls. This made the screening much more reliable compared with direct colony blotting transfer. A second feature is the parallel use of a protein tyrosine phosphatase (PTP)‐expressing host and a non‐PTP‐expressing host. Because high activity Src mutants are toxic to the host, the PTP system allowed the identification of Src mutants with high activity, while the non‐PTP system identified Src mutants with low activity. This approach was applied to Src mutant libraries randomized in the highly conserved HRD motif in the catalytic loop, and revealed that structurally diverse residues can replace the His and Arg residues, while the Asp residue is irreplaceable for catalytic activity

RAPTOR: Routing Attacks on Privacy in Tor

The Tor network is a widely used system for anonymous communication. However, Tor is known to be vulnerable to attackers who can observe traffic at both ends of the communication path. In this paper, we show that prior attacks are just the tip of the iceberg. We present a suite of new attacks, called Raptor, that can be launched by Autonomous Systems (ASes) to compromise user anonymity. First, AS-level adversaries can exploit the asymmetric nature of Internet routing to increase the chance of observing at least one direction of user traffic at both ends of the communication. Second, AS-level adversaries can exploit natural churn in Internet routing to lie on the BGP paths for more users over time. Third, strategic adversaries can manipulate Internet routing via BGP hijacks (to discover the users using specific Tor guard nodes) and interceptions (to perform traffic analysis). We demonstrate the feasibility of Raptor attacks by analyzing historical BGP data and Traceroute data as well as performing real-world attacks on the live Tor network, while ensuring that we do not harm real users. In addition, we outline the design of two monitoring frameworks to counter these attacks: BGP monitoring to detect control-plane attacks, and Traceroute monitoring to detect data-plane anomalies. Overall, our work motivates the design of anonymity systems that are aware of the dynamics of Internet routing

Piloting a Healthy Street Food Venture in Kenya: Lessons Learned

AbstractApproximately 2.5 billion people, majority of them in developing countries, consume street foods on a daily basis. High malnourishment rates in these low-resource settings create a need for healthy street food. The successful introduction of healthy street food could ultimately improve communities’ overall health and wellness without constraining people's budgets and eating habits. Packaging locally available ingredients into aspirational foods like pizza improves consumers’ access to micronutrients without disrupting their consumption of indigenous foods. The Zima Pizza venture was piloted in the town of Nyeri, Kenya to pilot this implementation process. This venture introduced a westernized food option into a local restaurant, and the lessons learned from this venture can inform the introduction of healthier street foods. This article outlines the basis for designing healthier meals for a simple street food business, the challenges that arose in the implementation process, and the lessons learned from this social venture

BadGPT: Exploring Security Vulnerabilities of ChatGPT via Backdoor Attacks to InstructGPT

Recently, ChatGPT has gained significant attention in research due to its ability to interact with humans effectively. The core idea behind this model is reinforcement learning (RL) fine-tuning, a new paradigm that allows language models to align with human preferences, i.e., InstructGPT. In this study, we propose BadGPT, the first backdoor attack against RL fine-tuning in language models. By injecting a backdoor into the reward model, the language model can be compromised during the fine-tuning stage. Our initial experiments on movie reviews, i.e., IMDB, demonstrate that an attacker can manipulate the generated text through BadGPT.Comment: This paper is accepted as a poster in NDSS202

Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!

Large Language Models (LLMs) have made remarkable strides in various tasks. Whether LLMs are competitive few-shot solvers for information extraction (IE) tasks, however, remains an open problem. In this work, we aim to provide a thorough answer to this question. Through extensive experiments on nine datasets across four IE tasks, we demonstrate that current advanced LLMs consistently exhibit inferior performance, higher latency, and increased budget requirements compared to fine-tuned SLMs under most settings. Therefore, we conclude that LLMs are not effective few-shot information extractors in general. Nonetheless, we illustrate that with appropriate prompting strategies, LLMs can effectively complement SLMs and tackle challenging samples that SLMs struggle with. And moreover, we propose an adaptive filter-then-rerank paradigm to combine the strengths of LLMs and SLMs. In this paradigm, SLMs serve as filters and LLMs serve as rerankers. By prompting LLMs to rerank a small portion of difficult samples identified by SLMs, our preliminary system consistently achieves promising improvements (2.4% F1-gain on average) on various IE tasks, with an acceptable time and cost investment.Comment: Accepted by EMNLP 2023 Finding

A Churn for the Better: Localizing Censorship using Network-level Path Churn and Network Tomography

Recent years have seen the Internet become a key vehicle for citizens around the globe to express political opinions and organize protests. This fact has not gone unnoticed, with countries around the world repurposing network management tools (e.g., URL filtering products) and protocols (e.g., BGP, DNS) for censorship. However, repurposing these products can have unintended international impact, which we refer to as "censorship leakage". While there have been anecdotal reports of censorship leakage, there has yet to be a systematic study of censorship leakage at a global scale. In this paper, we combine a global censorship measurement platform (ICLab) with a general-purpose technique -- boolean network tomography -- to identify which AS on a network path is performing censorship. At a high-level, our approach exploits BGP churn to narrow down the set of potential censoring ASes by over 95%. We exactly identify 65 censoring ASes and find that the anomalies introduced by 24 of the 65 censoring ASes have an impact on users located in regions outside the jurisdiction of the censoring AS, resulting in the leaking of regional censorship policies

Evidence for activated Lck protein tyrosine kinase as the driver of proliferation in acute myeloid leukemia cell, CTV-1

Acute myeloid leukemia (AML) is a heterogeneous group of fast growing cancers of myeloid progenitor cells, for which effective treatments are still lacking. Identification of signaling inhibitors that block their proliferation could reveal the proliferative mechanism of a given leukemia cell, and provide small molecule drugs for targeted therapy for AML. In this study, kinase inhibitors that block the majority of cancer signaling pathways are evaluated for their inhibition of two AML cell lines of the M5 subtypes, CTV-1 and THP-1. While THP-1 cells do not respond to any of these inhibitors, CTV-1 cells are potently inhibited by dasatinib, bosutinib, crizotinib, A-770041, and WH-4-23, all potent inhibitors for Lck, a Src family kinase. CTV-1 cells contain a kinase activity that phosphorylates an Lck-specific peptide substrate in an Lck inhibitor-sensitive manner. Furthermore, the Lck gene is over-expressed in CTV-1, and it contains four mutations, two of which are located in regions critical for Lck negative regulation, and are confirmed to activate Lck. Collectively, these results provide strong evidence that mutated and overexpressed Lck is driving CTV-1 proliferation. While Lck activation and overexpression is rare in AML, this study provides a potential therapeutic strategy for treating patients with a similar oncogenic mechanism