Etiologic Diagnosis of Infective Endocarditis by Broad-Range Polymerase Chain Reaction: A 3-Year Experience

We analyzed surgically resected endocardial specimens from 49 patients by broad-range PCR. PCR results were compared with (1) results of previous blood cultures, (2) results of culture and Gram staining of resected specimens, and (3) clinical data (Duke criteria). Molecular analyses of resected specimens and previous blood cultures showed good overall agreement. However, in 18% of patients with sterile blood cultures, bacterial DNA was found in the resected materials. When data from patients with definite or rejected cases of infective endocarditis (IE) were included, the sensitivity, specificity, and positive and negative predictive values of broad-range PCR were 82.6%, 100%, 100%, and 76.5%, respectively, overall, and 94.1%, 100%, 100%, and 90%, for cases of native valve endocarditis. The sensitivity, specificity, and positive and negative predictive values of culture of resected specimens from patients with native valve endocarditis were 17.6%, 88.9%, 75%, and 36.4%. We recommend broad-range PCR of surgically resected endocardial material in cases of possible IE, in cases of suspected IE in which blood cultures are sterile, and in cases in which organisms grow in blood cultures but only Duke minor criteria are met. We propose to add molecular techniques to the pathologic criteria of the Duke classification schem

Machine Learning-based Test Selection for Simulation-based Testing of Self-driving Cars Software

Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS) like self-driving cars (SDC) because they are more efficient and less dangerous than field operational test cases. Despite this, thoroughly testing SDCs in simulated environments remains challenging because SDCs must be tested in a sheer amount of long-running test cases. Past results on software testing optimization have shown that not all the test cases contribute equally to establishing confidence in test subjects' quality and reliability, and the execution of "safe and uninformative" test cases can be skipped to reduce testing effort. However, this problem is only partially addressed in the context of SDC simulation platforms. In this paper, we investigate test selection strategies to increase the cost-effectiveness of simulation-based testing in the context of SDCs. We propose an approach called SDC-Scissor (SDC coSt-effeCtIve teSt SelectOR) that leverages Machine Learning (ML) strategies to identify and skip test cases that are unlikely to detect faults in SDCs before executing them. Our evaluation shows that SDC-Scissor outperforms the baselines. With the Logistic model, we achieve an accuracy of 70%, a precision of 65%, and a recall of 80% in selecting tests leading to a fault and improved testing cost-effectiveness. Specifically, SDC-Scissor avoided the execution of 50% of unnecessary tests as well as outperformed two baseline strategies. Complementary to existing work, we also integrated SDC-Scissor into the context of an industrial organization in the automotive domain to demonstrate how it can be used in industrial settings.Comment: arXiv admin note: substantial text overlap with arXiv:2111.0466

Synovial tissues concentrate secreted APRIL

INTRODUCTION: A proliferation-inducing ligand (APRIL) from the TNF family, owing to its role in the generation and survival of plasma cells (PCs), is currently targeted for rheumatoid arthritis (RA) treatment. However, little is known about APRIL expression in RA lesions, hampering our understanding of the way APRIL may modulate this autoimmune disease. METHODS: We performed immunological staining of human normal, non-RA and RA synovial tissues with a pair of antibodies specifically recognizing APRIL-producing cells and secreted APRIL. RESULTS: We detected significant amounts of secreted APRIL in normal synovium mostly concentrated around blood vessels and at the lining layer, but no cells producing APRIL. Meanwhile, we observed that blood neutrophils constitutively secrete APRIL, indicating that blood APRIL may diffuse into the synovium via its fenestrated vessels. Synovium from non-RA and RA patients retained similarly secreted APRIL, but in this case APRIL-producing cells, including neutrophils and macrophages, were present in the tissue. Notably, PCs--when present in RA synovium--accumulated in areas of APRIL retention, spreading from blood vessels towards the lining layer. CONCLUSIONS: PCs accumulate in synovial zones rich in secreted APRIL, consistent with a pro-survival role of APRIL for PCs in RA. The concentration of APRIL by normal synovium indicates that this tissue may constitute a proper environment for PCs even before RA onset

Familial X-linked cardiomyopathy (Danon disease): diagnostic confirmation by mutation analysis of the LAMP2 gene

A boy presented at age 2.5 years with mild left ventricular hypertrophy and mild myopathy. Hypertrophic cardiomyopathy progressed relentlessly, leading to death at age 16 years shortly before planned heart transplantation. During the course of the disease, his mother developed severe dilated cardiomyopathy and died of its complications at 46 years of age. The combination of myopathy and cardiomyopathy, the biochemical and electron microscopy findings in a muscle biopsy, and the pedigree suggested Danon disease (MIM 300257), an X-linked lysosomal storage disorder caused by deficiency of lysosome-associated membrane protein-2 (LAMP2). The diagnosis was confirmed by the identification of a novel mutation, G138A, in the LAMP2gene, leading to the premature stop codon W46X. Conclusion:Early diagnosis of Danon disease is important for genetic counselling and timely cardiac transplantation, the only effective therapeutic optio

Machine learning-based test selection for simulation-based testing of self-driving cars software

Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS) like self-driving cars (SDC) because they are more efficient and less dangerous than eld operational test cases. Despite this, thoroughly testing SDCs in simulated environments remains challenging because SDCs must be tested in a sheer amount of long-running test cases. Past results on software testing optimization have shown that not all the test cases contribute equally to establishing con dence in test subjects' quality and reliability, and the execution of \safe and uninformative" test cases can be skipped to reduce testing effort. However, this problem is only partially addressed in the context of SDC simulation platforms. In this paper, we investigate test selection strategies to increase the cost-effectiveness of simulation-based testing in the context of SDCs. We propose an approach called SDC-Scissor (SDC coSt-effeCtIve teSt SelectOR) that leverages Machine Learning (ML) strategies to identify and skip test cases that are unlikely to detect faults in SDCs before executing them

Co-amplification of the HER2 gene and chromosome 17 centromere: a potential diagnostic pitfall in HER2 testing in breast cancer

Co-amplification of the centromere on chromosome 17 (CEP17) and HER2 can occur in breast cancer. Such aberrant patterns (clusters) on CEP17 can be misleading to calculate the HER2/CEP17 ratio, and thus underreporting of HER2 amplification. We identified 14 breast cancers retrospectively with HER2/CEP17 co-amplification and performed FISH (fluorescence in situ hybridization) with additional chromosome 17 probes (17p11.1-q11.1, 17p11.2-p12, TP53 on 17p13.1, RARA on 17q21.1-3 and TOP2 on 17q21.3-22) to characterize the spanning of the amplicon in these cases. Furthermore, the HER2 status was analyzed by means of HER2 silver in situ hybridization (SISH) and immunohistochemistry (IHC). The co-amplification of HER2/CEP17 was compared between the three institutions. TP53 was eusomic in all cases, 17p11.2-p12 in 79% (11/14), whereas 17p11.1-q11.1 showed chromosomal gain in all cases. RARA was amplified in 10/14 cases (71%) and TOP2 in 3/14 cases (21%). HER2 was amplified with FISH/SISH in all 14 cases. 9/14 tumors were 3+ IHC positive (64%) and 3 cases were 2+ IHC positive. In our cohort the CEP17 amplicon almost always involves the HER2 but not the TOP2 locus. Overall agreement on HER2/CEP17 ratio (when applying ASCO/CAP guidelines) was only 64% (9/14 cases) between the institutions. Discrepant ratios varied from 1.1 to 14.3. The HER2/CEP17 co-amplification is not defined in the ASCO/CAP guidelines, and may result in inaccurate HER2-FISH/SISH status, particularly if only the calculated HER2/CEP17 ratio is reported. It is recommended to report separate CEP17 and HER2 signals in complex HER2/CEP17 pattern

High-performance Implementations and Large-scale Validation of the Link-wise Artificial Compressibility Method

The link-wise artificial compressibility method (LW-ACM) is a recent formulation of the artificial compressibility method for solving the incompressible Navier-Stokes equations. Two implementations of the LW-ACM in three dimensions on CUDA enabled GPUs are described. The first one is a modified version of a stateof-the-art CUDA implementation of the lattice Boltzmann method (LBM), showing that an existing GPU LBM solver might easily be adapted to LW-ACM. The second one follows a novel approach, which leads to a performance increase of up to 1.8 compared to the LBM implementation considered here, while reducing the memory requirements by a factor of 5.25. Large-scale simulations of the lid-driven cubic cavity at Reynolds number Re = 2000 were performed for both LW-ACM and LBM. Comparison of the simulation results against spectral elements reference data shows that LW-ACM performs almost as well as multiple-relaxation-time LBM in terms of accurac

Fatigue safety of riveted bridges - Part 2: Verification based on the monitoring data of the project "Railway Bridge at Eglisau"

Fatigue safety of riveted bridges Part 2: Verification based on the monitoring data of the project "Railway Bridge at Eglisau". Long term monitoring over one year has been conducted on the riveted Railway Bridge over the Rhine at Eglisau. Measured values were exploited by rainflow analysis and served as the basis for the verification of fatigue safety. As the locations of measurements are generally not identical with the cross sections of verification, measured strains respectively stresses, were extrapolated to the relevant verification cross section by means of factors that were obtained by structural analysis. Using these values, all fatigue relevant structural details were first verified with respect to the fatigue limit. Then, damage accumulation calculation according to the Palmgren-Miner rule and based on Wohler curves for riveted details was performed for those structural details where the fatigue limit check was not fulfilled. Sufficient fatigue safety could finally be verified for the whole riveted structure and an additional service life of at least 50 years for the most fatigue relevant structural element

Fatigue safety examination of a riveted railway bridge using data from long term monitoring

Long term monitoring of structural elements of a 115 years old riveted railway bridge structure of high value as cultural heritage has been conducted. Monitored values were exploited by Rainflow analysis and served as the basis for the fatigue safety verification. As the locations of measurements are generally not identical with the cross sections of verification, measured strains were translated to the relevant verification cross section by means of factors that were determined by structural analysis. Using these values, all fatigue relevant structural details were first verified with respect to the fatigue limit. Then, damage accumulation calculation according to the Palmgren-Miner Rule was performed for those elements where the fatigue limit check was not fulfilled. Sufficient fatigue safety could finally be verified for the entire riveted structure and additional service duration of at least 50 years for this riveted structure could be validated