Continuum Gauge Fields from Lattice Gauge Fields

On the lattice some of the salient features of pure gauge theories and of gauge theories with fermions in complex representations of the gauge group seem to be lost. These features can be recovered by considering part of the theory in the continuum. The prerequisite for that is the construction of continuum gauge fields from lattice gauge fields. Such a construction, which is gauge covariant and complies with geometrical constructions of the topological charge on the lattice, is given in this paper. The procedure is explicitly carried out in the $U(1)$ theory in two dimensions, where it leads to simple results.Comment: 16 pages, HLRZ 92-3

On the total curvatures of a tame function

Given a definable function f, enough differentiable, we study the continuity of the total curvature function t --> K(t), total curvature of the level {f=t}, and the total absolute curvature function t-->|K| (t), total absolute curvature of the level {f=t}. We show they admits at most finitely many discontinuities

Evaluation of the BD Phoenix™ CPO Detect Test for the detection of carbapenemase producers.

Becton-Dickinson recently developed the Phoenix™ CPO (carbapenemase-producing organism) Detect Test, a growth-based test embedded in Gram-negative (GN) panels for the detection and confirmation of bacteria producing class A, B and D carbapenemases. This study aimed to (a) determine the performance of the CPO test, and (b) assess its added value in routine diagnostic workflows. The performance of the BD Phoenix CPO test was analysed retrospectively on a collection of 185 molecularly characterized strains, including 92 CPOs, and prospectively on 135 and 160 routine isolates with and without CPO suspicion, respectively. In the retrospective study the CPO test exhibited 92.4% accuracy (95%CI 87.6-95.8), 97.8% sensitivity (95%CI 92.4-99.7) and 87.1% specificity (95%CI 78.6-93.2) for carbapenemase detection. The CPO test provided a classification to class A, B, and D for 81.3% of detected carbapenemases with 94.6% accuracy (95%CI 86.7-98.5). In the prospective study the CPO test detection performance showed 77.8% accuracy (95%CI 68.8-84.5), 100% sensitivity (95%CI 91.2-100) and 67.8% specificity (95%CI 57.3-77.1) with 135 CPO-suspicious isolates and 98.8% accuracy and specificity (95%CI 95.6-99.9) with 160 non-CPO-suspicious isolates. Compared to routine testing, the implementation of the CPO test allowed a mean reduction of 21.3 h (95%CI 17.6-25) in turnaround time, 16.8 min (95%CI 13.4-20.2) in hands-on time, and 20.6 CHF (95%CI 16.5-24.8) in costs. The CPO test is reliable for the detection of CPO with a high sensitivity. However, the relatively low detection specificity required the use of additional confirmatory methods. The carbapenemase classification accuracy is robust in providing preliminary results before molecular characterization. Finally, the implementation of the test in routine workflows allowed a significant reduction in turnaround time, hands-on time and cost compared to the conventional approach

Machine Learning Approach for Candida albicans Fluconazole Resistance Detection Using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry.

Candida albicans causes life-threatening systemic infections in immunosuppressed patients. These infections are commonly treated with fluconazole, an antifungal agent targeting the ergosterol biosynthesis pathway. Current Antifungal Susceptibility Testing (AFST) methods are time-consuming and are often subjective. Moreover, they cannot reliably detect the tolerance phenomenon, a breeding ground for the resistance. An alternative to the classical AFST methods could use Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) Mass spectrometry (MS). This tool, already used in clinical microbiology for microbial species identification, has already offered promising results to detect antifungal resistance on non-azole tolerant yeasts. Here, we propose a machine-learning approach, adapted to MALDI-TOF MS data, to qualitatively detect fluconazole resistance in the azole tolerant species C. albicans. MALDI-TOF MS spectra were acquired from 33 C. albicans clinical strains isolated from 15 patients. Those strains were exposed for 3 h to 3 fluconazole concentrations (256, 16, 0 μg/mL) and with (5 μg/mL) or without cyclosporin A, an azole tolerance inhibitor, leading to six different experimental conditions. We then optimized a protein extraction protocol allowing the acquisition of high-quality spectra, which were further filtered through two quality controls. The first one consisted of discarding not identified spectra and the second one selected only the most similar spectra among replicates. Quality-controlled spectra were divided into six sets, following the sample preparation's protocols. Each set was then processed through an R based script using pre-defined housekeeping peaks allowing peak spectra positioning. Finally, 32 machine-learning algorithms applied on the six sets of spectra were compared, leading to 192 different pipelines of analysis. We selected the most robust pipeline with the best accuracy. This LDA model applied to the samples prepared in presence of tolerance inhibitor but in absence of fluconazole reached a specificity of 88.89% and a sensitivity of 83.33%, leading to an overall accuracy of 85.71%. Overall, this work demonstrated that combining MALDI-TOF MS and machine-learning could represent an innovative mycology diagnostic tool

Diagnostic strategies for SARS-CoV-2 infection and interpretation of microbiological results.

To face the current COVID-19 pandemic, diagnostic tools are essential. It is recommended to use real-time RT-PCR for RNA viruses in order (a) to perform a rapid and accurate diagnostic, (b) to guide patient care and management and (c) to guide epidemiological strategies. Further studies are warranted to define the role of serological diagnosis and a possible correlation between serological response and prognosis. The aim was to guide clinical microbiologists in the use of these diagnostic tests and clinicians in the interpretation of their results. A search of literature was performed through PubMed and Google Scholar using the keywords SARS-CoV-2, SARS-CoV-2 molecular diagnosis, SARS-CoV-2 immune response, SARS-CoV-2 serology/antibody testing, coronavirus diagnosis. The present review discusses performances, limitations and use of current and future diagnostic tests for SARS-CoV-2. Real-time RT-PCR remains the reference method for diagnosis of SARS-CoV-2 infection. On the other hand, notwithstanding its varying sensitivity according to the time of infection, serology represents a valid asset (a) to try to solve possible discrepancies between a highly suggestive clinical and radiological presentation and negative RT-PCR, (b) to solve discrepancies between different PCR assays and (c) for epidemiological purposes

Single Strand Annealing Plays a Major Role in RecA-Independent Recombination between Repeated Sequences in the Radioresistant Deinococcus radiodurans Bacterium

© 2015 Ithurbide et al. The bacterium Deinococcus radiodurans is one of the most radioresistant organisms known. It is able to reconstruct a functional genome from hundreds of radiation-induced chromosomal fragments. Our work aims to highlight the genes involved in recombination between 438 bp direct repeats separated by intervening sequences of various lengths ranging from 1,479 bp to 10,500 bp to restore a functional tetA gene in the presence or absence of radiation-induced DNA double strand breaks. The frequency of spontaneous deletion events between the chromosomal direct repeats were the same in recA+ and in ΔrecA, ΔrecF, and ΔrecO bacteria, whereas recombination between chromosomal and plasmid DNA was shown to be strictly dependent on the RecA and RecF proteins. The presence of mutations in one of the repeated sequence reduced, in a MutS-dependent manner, the frequency of the deletion events. The distance between the repeats did not influence the frequencies of deletion events in recA+as well in ΔrecA bacteria. The absence of the UvrD protein stimulated the recombination between the direct repeats whereas the absence of the DdrB protein, previously shown to be involved in DNA double strand break repair through a single strand annealing (SSA) pathway, strongly reduces the frequency of RecA- (and RecO-) independent deletions events. The absence of the DdrB protein also increased the lethal sectoring of cells devoid of RecA or RecO protein. γ-irradiation of recA+cells increased about 10-fold the frequencies of the deletion events, but at a lesser extend in cells devoid of the DdrB protein. Altogether, our results suggest a major role of single strand annealing in DNA repeat deletion events in bacteria devoid of the RecA protein, and also in recA+bacteria exposed to ionizing radiation