Traditional Testing Strategies Research Articles

Nanothermometry for cellular temperature monitoring and disease diagnostics

AbstractBody temperature variations, including the generation, transfer, and dissipation of heat, play an important role throughout life and participate in all biological events. Cellular temperature information is an indispensable link in the comprehensive understanding of life science processes, but traditional testing strategies cannot provide sufficient information due to their low precision and inefficient cellular‐entrance. In recent years, with the help of luminescent nanomaterials, a variety of new thermometers have been developed to achieve real‐time temperature measurement at the micro/nano scale. In this review, we summarized the latest advances in several nanoparticles for cellular temperature detection and their related applications in revealing cell metabolism and disease diagnosis. Furthermore, this review proposed a few challenges for the nano‐thermometry, expecting to spark novel thought to push forward its preclinical and translational uses.

Unveiling Faulty User Sequences: A Model-Based Approach to Test Three-Tier Software Architectures

Context:When testing three-tiered architectures, strategies often rely on superficial information, e.g., black-box input. However, the correct behavior of software-intensive systems based on such architectural pattern also depends on the logic hidden behind the interface. Verifying the response process is thus often complex and requires ad-hoc strategies. Objective:We propose an approach to identify faults hidden behind the presentation layer. The model-based approach uses an architectural abstraction called managed component Data Flow Graph (mcDFG). The mcDFG is aware of the interactions between all layers of the architecture and guides the generation of tests based on different mcDFG coverage criteria to identify faults in the business logic. Method:To evaluate the approach viability, we consider a three-tiered web application and 32 faults. The fault detection capability is assessed by comparing a set of test suites created by following our method and a set of test suites developed by utilizing traditional testing strategies. Results:The collected data show that the proposed model-based approach is a viable option to identify faults hidden in the logic layer, as it can outperform standard strategies based solely on the presentation layer while keeping the number of test cases and number of interactions per test case low.

Evaluation of 18,911 Individuals with Autism Reveals that Exome Analysis Provides Higher Diagnostic Rates and Reduced Time to Diagnosis than Traditional Testing Strategies (P1-1.Virtual)

Evaluation of 18,911 Individuals with Autism Reveals that Exome Analysis Provides Higher Diagnostic Rates and Reduced Time to Diagnosis than Traditional Testing Strategies (P1-1.Virtual)

Disentangling the Psycholinguistic Loci of Anomia with Cognitive Psychometric Models.

This article reviews advanced statistical techniques for measuring impairments in object naming, particularly in the context of stroke-induced aphasia. Traditional testing strategies can be challenged by the multifaceted nature of impairments that arise due to the complex relationships between localized brain damage and disruption to the cognitive processes required for successful object naming. Cognitive psychometric models can combine response-type analysis with item-response theory to yield accurate estimates of multiple abilities using data collected from a single task. The models also provide insights about how the test items can be challenging in different ways. Although more work is needed to fully optimize their clinical utility in practice, these formal concepts can guide thoughtful selection of stimuli used in treatment or assessment, as well as providing a framework to interpret response-type data.

Super-MSI: CfDNA-based pan-cancer microsatellite instability detection.

e13672 Background: Microsatellite instability (MSI) is a molecular subtype found in many cancers, which is often associated with the benefits of immunotherapy. However, the application of traditional testing strategies (such as PCR or IHC) is largely limited due to their dependencies on sufficient tumor tissues. Here, we introduced Super-MSI, a cfDNA-based pan-cancer MSI detection method using next-generation sequencing (NGS). Methods: 5500 detectable microsatellite loci from 250 white blood cells (WBCs) and 29 PCR-validated MSI-H tissue samples were sequenced and characterized, while the former represented for MSS pattern, and the later, for MSI-H. 91 microsatellite loci with the most variable motif repeat numbers between patterns were filtered and the Super-MSI method was established. Plasma samples were collected from 608 patients with known MSI status assessed by PCR (593 MSS and 15 MSI-H) to validate the method. All samples were sequenced with a 642-gene panel, and initial microsatellite reads count distributions were profiled by MSIsensor. Results: We characterized each microsatellite locus by REF alleles (MSI-H:WBC ratio less than 1) and ALT alleles (MSI-H:WBC ratio more than 20), then defined the sum of ALT alleles frequency in WBC group as the baseline for each candidate locus. For plasma samples with unknown MSI status, hypergeometric distribution and FDR calibration were employed to assess the difference of ALT alleles frequency between the WBC baseline and plasma samples. Locus with FDR adjusted p-value less than 0.05 was defined as an unstable locus based on prior knowledge, and negative log-transformed FDR-p was defined as MSscore for the locus. The plasma sample with both unstable microsatellite proportion larger than 20% and total MSscore larger than 270 was defined as MSI-H, and contrariwise, MSS. For all evaluable samples in the validation cohort, Super-MSI showed high sensitivity and specificity of 60% (9/15) and 100% (593/593) for an overall accuracy of 99.0% (602/608), superior to its kind bMSISEA (83.5%, 106/127) and Guardant360 (98.4%, 934/949). Within LOD of 0.5% maxAF (approximately 1% ctDNA fraction), Super-MSI was able to detect 81.8% (9/11) of MSI-H samples, demonstrating high concordance with tissue-based PCR tests. Conclusions: Super-MSI can genotype pan-cancer patients with blood cfDNA samples and give highly accurate MSI evaluation with 81.8% sensitivity and 100% specificity above 1% ctDNA fraction.

In response: Academic perspective.

In response: Academic perspective.

Novel Techniques for High-Sensitivity Hardware Trojan Detection Using Thermal and Power Maps

Hardware Trojans are malicious alterations or injections of unwanted circuitry to integrated circuits (ICs) by untrustworthy factories. They render great threat to the security of modern ICs by various unwanted activities such as bypassing or disabling the security fence of a system, leaking confidential information, deranging, or destroying the entire chip. Traditional testing strategies are becoming ineffective since these techniques suffer from decreased sensitivity toward small Trojans because of oversized chip and large amount of process variation present in nanometer technologies. The production volume along with decreased controllability and observability to complex ICs internals make it difficult to efficiently perform Trojan detection using typical structural tests like path latency and leakage power. In this paper, we propose a completely new post-silicon multimodal approach using runtime thermal and power maps for Trojan detection and localization. Utilizing the novel framework, we propose two different Trojan detection methods involving 2-D principal component analysis. First, supervised thresholding in case training data set is available and second, unsupervised clustering which require no prior characterization data of the chip. We introduce 11 regularization in the thermal to power inversion procedure which improves Trojan detection accuracy. To characterize ICs accurately, we perform our experiments in presence of realistic CMOS process variation. Our experimental evaluations reveal that our proposed methodology can detect very small Trojans with 3-4 orders of magnitude smaller power consumptions than the total power usage of the chip, while it scales very well because of the spatial view to ICs internals by the thermal mapping.

A reusable localized surface plasmon resonance biosensor for quantitative detection of serum squamous cell carcinoma antigen in cervical cancer patients based on silver nanoparticles array

Squamous cell carcinoma antigen (SCCa), as a tumor biomarker, plays an important role in adjuvant diagnosis, treatment evaluation, and prognosis prediction for cervical cancer patients. Localized surface plasmon resonance (LSPR) technique based on noble metal nanoparticles bypasses the disadvantages of traditional testing strategies, in terms of free-labeling, short assay time, good sensitivity, and selectivity. Herein, we develop a novel and reusable LSPR biosensor for the detection of SCCa. First, a triangle-shaped silver nanoparticle array was fabricated using the nanosphere lithography method. Next, we investigated and verified the feasibility of amino coupling method using 11-mercaptoundecanoic acid (MUA) to form a functionalized chip surface with monoclonal anti-SCCa antibodies on the silver nanoparticles for distinct detection of SCCa. Different concentrations of SCCa were successfully tested in both buffer and human serum by the ultrasensitive and specific LSPR system, with a linear quantitative detection range of 0.1–1,000 pM under optimal conditions. With appropriate regeneration solution, for example 50 mM glycine-HCl (pH 2.0), the LSPR biosensor featured effective fabrication reproducibility, which reduced both production cost and testing time. Our study represents the first application of the LSPR biosensor in cervical cancer, and demonstrates that the rapid, simple, and reusable nanochip can serve as a potential alternative for clinical serological diagnosis of SCCa in cervical cancer patients.

A cost effective real-time PCR for the detection of adenovirus from viral swabs

Compared to traditional testing strategies, nucleic acid amplification tests such as real-time PCR offer many advantages for the detection of human adenoviruses. However, commercial assays are expensive and cost prohibitive for many clinical laboratories. To overcome fiscal challenges, a cost effective strategy was developed using a combination of homogenization and heat treatment with an “in-house” real-time PCR. In 196 swabs submitted for adenovirus detection, this crude extraction method showed performance characteristics equivalent to viral DNA obtained from a commercial nucleic acid extraction. In addition, the in-house real-time PCR outperformed traditional testing strategies using virus culture, with sensitivities of 100% and 69.2%, respectively. Overall, the combination of homogenization and heat treatment with a sensitive in-house real-time PCR provides accurate results at a cost comparable to viral culture.