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Combination treatment with erlotinib plus bevacizumab has the potential to become a standard treatment regimen for patients with epidermal growth factor receptor mutation-positive (Systematic review and meta-analysis.The PubMed, Embase, Web of Science and Cochrane Library databases were searched, from inception to 15 January 2022.We included randomised controlled trials (RCTs), reported in English, assessing the efficacy of erlotinib plus bevacizumab versus erlotinib monotherapy in patients withThe main objective was to assess overall survival (OS), progression-free survival (PFS), objective response rate (ORR) and adverse events (AEs). Two independent reviewers extracted data and assessed the risk of bias. A random-effects model was used where there was evidence for homogeneous effects.Four RCTs (reported across six publications) were included in the meta-analysis, with a total of 775 patients included in the pooled analyses of PFS, OS and ORR (387 in the erlotinib plus bevacizumab intervention group and 388 in the erlotinib group). Compared with the erlotinib alone group, the erlotinib plus bevacizumab group achieved a significantly prolonged PFS (HR: 0.59; 95% CI 0.49 to 0.72; p0.00001; IErlotinib plus bevacizumab for the treatment of patients with

A retrospective review of 9 patients diagnosed with empyema caused by

The promise of strong physical unclonable functions (PUF) is to utilize the manufacturing variations of circuit elements to produce an independent and unpredictable response to any input challenge vector. Attacks on PUFs that predict the responses to input challenge vectors offer an interesting research problem. An attacking approach based on the optimization theory and side-channel information is proposed where we estimate the manufacturing variations of the circuit elements and predict the PUF’s responses to challenge vectors whose actual responses are not known. We apply this attacking approach on some popular PUF designs, including the Arbiter PUFs, the Memristor Crossbar PUFs, and the XOR Arbiter PUFs. Simulations show a substantial reduction in attack complexity compared with previously proposed machine-learning (ML)-based attacks: we achieve an average reduction of 66% in attack time compared with the ML approach. Despite some overhead, our approach is also applicable when the PUF responses are noisy.

To combat security threats to integrated circuit (IC) fabrication outsourcing, 2.5D integration can obfuscate the outsourced design by lifting a portion of the wires into an interposer layer. A security-aware physical design flow for 2.5D IC technology can then help defend against attacks by increasing the layout and functionality obfuscation.

Background: Anti-bacterial drugs are thought to be associated with several malignancies. Objective: We conducted a systematic review and meta-analysis to assess the association between antibacterial drug exposure and the risk of digestive system neoplasms. Methods: Relevant publications reporting a relationship between antibiotic use and the risk of cancer were identified in PubMed, EMBASE, and Cochrane Central Register through June 2018. The random-effects model was selected to pool the risk ratios (RRs) and determine 95% confidence intervals (95% CIs). We performed subgroup analyses by tumor organ site, individual antibacterial drug class, and drug dose accumulation. Results: A total of 17 eligible studies (four randomized trials and 13 observational studies) involving 77,284 cancer patients were included in our analyses. Anti-bacterial drug exposure slightly increased the risk of overall digestive system cancer (RR, 1.12; 95% CI, 1.10-1.14), stomach and small intestine (RR, 1.12; 95% CI, 1.07-1.17), anorectocolonic (RR, 1.08; 95% CI, 1.05-1.12), and hepatobiliary and pancreatic cancers (RR, 1.18; 95% CI, 1.14-1.22). For different anti-bacterial drugs classes, nitroimidazoles (RR, 1.17; 95% CI, 1.09-1.26) and quinolones (RR, 1.18; 95% CI, 1.11-1.26) showed a modest association with the risk of cancers incidence. The risks of digestive system cancers increased with the rise of drug dose accumulation: low (RR, 1.08; 95% CI, 1.05-1.11), intermediate (RR, 1.15; 95% CI, 1.12-1.18), and high (RR, 1.22; 95% CI, 1.18-1.26). Conclusions: Anti-bacterial drug exposure was associated with the risks of digestive system cancer occurrence in our analysis.

Physical limit of transistor miniaturization has driven chip design into the third dimension. 3D integration technology emerges as a viable option to improve chip performance and increase device density in a direction orthogonal to costly device scaling. As 3D integration is becoming a promising technology for next-generation chip design, recent years have seen a huge proliferation of research literature exploiting it from a security perspective. This paper presents a survey on the current state of 3D integration technology from a security perspective and summarizes its security opportunities and challenges. We report current research work on 3D integration based security in three major applications: supply chain attack prevention, side-channel attack mitigation, and trustworthy computing system design. The security advantages and opportunities of 3D integration in these security applications are highlighted. Besides, the paper discusses new vulnerabilities risen by 3D integration that require researchers’ attention. Based on the survey result, we summarize the distinct characteristics of 3D ICs and investigate their impacts on security-aware 3D IC designs.

Due to design and fabrication outsourcing to foundries, the problem of malicious modifications to integrated circuits (ICs), also known as hardware Trojans (HTs), has attracted attention in academia as well as industry. To reduce the risks associated with Trojans, researchers have proposed different approaches to detect them. Among these approaches, test-time detection approaches have drawn the greatest attention. Many test-time approaches assume the existence of a Trojan-free (TF) chip/model also known as “golden model.” Prior works suggest using reverse engineering (RE) to identify such TF ICs for the golden model. However, they did not state how to do this efficiently. In fact, RE is a very costly process which consumes lots of time and intensive manual effort. It is also very error prone. In this paper, we propose an innovative and robust RE scheme to identify the TF ICs. We reformulate the Trojan-detection problem as clustering problem. We then adapt a widely used machine learning method, ${K}$ -means clustering, to solve our problem. Simulation results using state-of-the-art tools on several publicly available circuits show that the proposed approach can detect HTs with high accuracy rate. A comparison of this approach with our previously proposed approach [1] is also conducted. Both the limitations and application scenarios of the two methods are discussed in detail.

The hardware Trojan threat has motivated development of Trojan detection schemes at all stages of the integrated circuit (IC) lifecycle. While the majority of existing schemes focus on ICs at test-time, there are many unique advantages offered by post-deployment/run-time Trojan detection. However, run-time approaches have been underutilized with prior work highlighting the challenges of implementing them with limited hardware resources. In this paper, we propose three innovative low-overhead approaches for run-time Trojan detection which exploit the thermal sensors already available in many modern systems to detect deviations in power/thermal profiles caused by Trojan activation. The first one is a local sensor-based approach that uses information from thermal sensors together with hypothesis testing to make a decision. The second one is a global approach that exploits correlation between sensors and maintains track of the ICs thermal profile using a Kalman filter (KF). The third approach incorporates leakage power into the system dynamic model and apply extended KF (EKF) to track ICs thermal profile. Simulation results using state-of-the-art tools on ten publicly available Trojan benchmarks verify that all three proposed approaches can detect active Trojans quickly and with few false positives. Among three approaches, EKF is flawless in terms of the ten benchmarks tested but would require the most overhead.

Physical unclonable functions (PUFs) utilize manufacturing variations of circuit elements to produce unpredictable response to any challenge vector. The attack on PUF aims to predict the PUF response to all challenge vectors while only a small number of challenge-response pairs (CRPs) are known. The target PUFs in this paper include the Arbiter PUF (ArbPUF) and the Memristor Crossbar PUF (MXbarPUF). The manufacturing variations of the circuit elements in the targeted PUF can be characterized by a weight vector. An optimization-theoretic attack on the target PUFs is proposed. The feasible space for a PUF's weight vector is described by a convex polytope confined by the known CRPs. The centroid of the polytope is chosen as the estimate of the actual weight vector, while new CRPs are adaptively added into the original set of known CRPs. The linear behavior of both ArbPUF and MXbarPUF is proven which ensures that the feasible space for their weight vectors is convex. Simulation shows that our approach needs 71.4% fewer known CRPs and 86.5% less time than the state-of-the-art machine learning based approach.

Background Cyclin-dependent kinase 5 (CDK5) is an atypical CDK which plays a vital role in several cancers via regulating migration and motility of cancer cells. However, the clinicopathological impact and function of CDK5 in lung cancer remain poorly understood. The present study was aimed at exploring expression and clinicopathological significance of CDK5 in lung cancer. Methods There were 395 samples of lung tissue including 365 lung tumors (339 non-small cell lung cancers and 26 small cell lung cancers) and 30 samples of normal lung. CDK5 expression was detected by immunohistochemistry on lung tissue microarrays. Results Over expression was detected in lung cancer compared with normal lung tissues (P = 0.001). Furthermore, area under curve (AUC) of receiver operating characteristic (ROC) of CDK5 was 0.685 (95 % CI 0.564~0.751, P = 0.004). In lung cancer, we also discovered close correlations between CDK5 and pathological grading (r = 0.310, P