Exploring the potential of a setup for combined quantification of hydrogen in natural gas - Raman and NMR spectroscopy.

An accurate measurement of the amount fraction of hydrogen in gas mixtures is mandatory for practical applications, requiring methods that are fast, continuous, robust, and cost-effective. This study compares the performance of Raman and benchtop NMR process spectroscopy for determining the hydrogen amount fraction in gas mixtures. A setup was designed to integrate both techniques, enabling measurements of the same sample. Tests were conducted with gravimetrically prepared gas mixtures of reference quality ranging from 1.20 cmol/mol to 85.83 cmol/mol of hydrogen. The results demonstrate that Raman spectroscopy provides superior performance, with a minimal root mean square error (RMSE) of 0.22 cmol/mol and excellent linearity. In contrast, benchtop NMR spectroscopy faced challenges, such as overlapping peaks and longer measurement times, resulting in a higher RMSE of 0.71 cmol/mol. Raman spectroscopy proves to be particularly well-suited for practical applications due to its high accuracy and linearity. Meanwhile, benchtop NMR spectroscopy holds potential for future enhancements through ongoing technological advances, such as higher magnetic field strengths. In summary, the results from our study indicate that Raman spectroscopy is already a serviceable method for precise hydrogen quantification, whereas benchtop NMR spectroscopy can be attributed potential for future applications.

Towards robust fault detection for Takagi-Sugeno nonlinear systems.

This paper addresses robust fault detection observer design for a class of discrete-time Takagi-Sugeno nonlinear systems. A novel design method is presented based on finite-frequency H-/H∞ indices and peak-to-peak analysis. The finite-frequency H- and H∞ indices are utilized to characterize fault sensitivity and disturbance robustness, respectively. The peak-to-peak analysis is used to derive a dynamic threshold. An iterative algorithm is further developed to reduce conservatism. Theoretical proof shows that the performance of the proposed method is not worse than some existing works. Simulation results demonstrate the validity and viability of the proposed method.

PAPerFly: Partial Assembly-based Peak Finder for ab initio binding site reconstruction.

BACKGROUND: The specific recognition of a DNA locus by a given transcription factor is a widely studied issue. It is generally agreed that the recognition can be influenced not only by the binding motif but by the larger context of the binding site. In this work, we present a novel heuristic algorithm that can reconstruct the unique binding sites captured in a sequencing experiment without using the reference genome. RESULTS: We present PAPerFly, the Partial Assembly-based Peak Finder, a tool for the binding site and binding context reconstruction from the sequencing data without any prior knowledge. This tool operates without the need to know the reference genome of the respective organism. We employ algorithmic approaches that are used during genome assembly. The proposed algorithm constructs a de Bruijn graph from the sequencing data. Based on this graph, sequences and their enrichment are reconstructed using a novel heuristic algorithm. The reconstructed sequences are aligned and the peaks in the sequence enrichment are identified. Our approach was tested by processing several ChIP-seq experiments available in the ENCODE database and comparing the results of Paperfly and standard methods. CONCLUSIONS: We show that PAPerFly, an algorithm tailored for experiment analysis without the reference genome, yields better results than an aggregation of ChIP-seq agnostic tools. Our tool is freely available at https://github.com/Caeph/paperfly/ or on Zenodo ( https://doi.org/10.5281/zenodo.7116424 ).

First case of Cutibacterium avidum-infected pelvic lymphocele post-lymphadenectomy for endometrial cancer: A case report.

Background: Pelvic lymphocele (lymphocyst) infection after lymphadenectomy is a rare complication that can cause the spread of inflammation to neighboring organs whose microbiology is not well known. Cutibacterium avidum causes various infections. However, no case reports of C. avidum pelvic lymphocele infection are available; therefore, its clinical characteristics in pelvic lymphocele infections remain unknown. Case presentation: A 38-year-old woman with obesity (body mass index: 38.1 kg/m2) and a history of pelvic lymphadenectomy and chemotherapy for endometrial cancer presented with worsening left lower quadrant (LLQ) pain with fever. Physical examination revealed decreased abdominal bowel sounds and tenderness on LLQ palpation with no signs of peritonitis. Computed tomography (CT) revealed an infected left pelvic lymphocele with inflammation spreading to the adjacent sigmoid colon. Following blood culture, ampicillin/sulbactam (2 g/1 g every 6 h) was administered intravenously. Anaerobic culture bottles revealed gram-positive rods on day 4 of incubation at 37 °C. No other disseminated foci were observed in enhanced whole-body CT and upon transthoracic echocardiography. The isolates grew aerobically and anaerobically on blood agar plates with strong hemolysis. The bacterium was identified as C. avidum using a combination of characteristic peak analysis with matrix-assisted laser desorption ionization (MALDI) and 16S rRNA gene sequencing. The patient was diagnosed with C. avidum pelvic lymphocele infection. Based on penicillin susceptibility, the patient was successfully treated with intravenous ampicillin/sulbactam and de-escalated with intravenous ampicillin (2 g every 6 h) for 10 days, followed by oral amoxicillin (2000 mg/day) for an additional 11 days without drainage. Conclusions: C. avidum should be considered a causative microorganism of pelvic lymphocele infection. Peak analysis using MALDI and distinctive growth on blood agar plates are suitable for identifying C. avidum. Mild pelvic lymphocele caused by C. avidum can be treated with a short course of appropriate antimicrobial treatment without surgical intervention.

Automatic Discrimination of Species within the Enterobacter cloacae Complex Using Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry and Supervised Algorithms.

The Enterobacter cloacae complex (ECC) encompasses heterogeneous clusters of species that have been associated with nosocomial outbreaks. These species may have different acquired antimicrobial resistance and virulence mechanisms, and their identification is challenging. This study aims to develop predictive models based on matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) profiles and machine learning for species-level identification. A total of 219 ECC and 118 Klebsiella aerogenes clinical isolates from three hospitals were included. The capability of the proposed method to differentiate the most common ECC species (Enterobacter asburiae, Enterobacter kobei, Enterobacter hormaechei, Enterobacter roggenkampii, Enterobacter ludwigii, and Enterobacter bugandensis) and K. aerogenes was demonstrated by applying unsupervised hierarchical clustering with principal-component analysis (PCA) preprocessing. We observed a distinctive clustering of E. hormaechei and K. aerogenes and a clear trend for the rest of the ECC species to be differentiated over the development data set. Thus, we developed supervised, nonlinear predictive models (support vector machine with radial basis function and random forest). The external validation of these models with protein spectra from two participating hospitals yielded 100% correct species-level assignment for E. asburiae, E. kobei, and E. roggenkampii and between 91.2% and 98.0% for the remaining ECC species; with data analyzed in the three participating centers, the accuracy was close to 100%. Similar results were obtained with the Mass Spectrometric Identification (MSI) database developed recently (https://msi.happy-dev.fr) except in the case of E. hormaechei, which was more accurately identified with the random forest algorithm. In short, MALDI-TOF MS combined with machine learning was demonstrated to be a rapid and accurate method for the differentiation of ECC species.

ATAC-DEA: A Web-Based ATAC-Seq Data Differential Peak and Annotation Analysis Application.

Assay for transposase-accessible chromatin sequencing (ATAC-seq) has become one of the most widely used sequencing methods in studies of gene regulation, aiming to identify open chromatin sites and decipher how chromatin accessibility regulates gene expression. However, due to a lack of programming experience or minimal bioinformatics training, it is difficult for biologists to fully explore and interpret ATAC-seq results. Despite several available programs or websites that allow researchers to analyze and visualize ATAC-seq data, several limitations exist. ATAC-seq data differential expression analysis (ATAC-DEA), a web application that facilitates the exploration and visualization of differential peak analysis and annotation from ATAC-seq data, was developed (www.atac-dea.xyz:3838/ATAC-DEA). ATAC-DEA uses DiffBind and ChIPpeakAnno to process differential peak and annotation analysis results. ATAC-DEA has five features: (1) runs on a web server; (2) processes three files into one small file, which is used as the input for ATAC-DEA; (3) availability of various downloadable plots; (4) multifactor analysis and customized contrast model; and (5) annotates individual, overlapped, and differential peaks. It provides an easy-to-use user interface (UI) design for users to explore the data and modify the parameters interactively based on experimental purposes. ATAC-DEA allows biologists to generate user-friendly visual results from ATAC-seq downstream analysis.

Studies of defect states and kinetic parameters of car windscreen for thermoluminescence retrospective dosimetry.

In case of any natural disasters or technical failures of nuclear facilities, the surrounding media including human beings may receive unexpected radiation exposures. In such a situation, there is no viable way to know how much radiation dose is received by human beings. Realizing that motorized vehicles are parked at fixed but increasing distances within the nuclear installation and industrial environment, this study investigates the kinetic parameters of readily available car windscreens which form the basis to be employed in post-accident dose reconstruction or for retrospective dosimetry. To understand the luminescence features of this crystalline media, a convenient thermoluminescence (TL) technique has been employed. Several well-defined theoretical models and methods were employed to calculate the kinetic parameters including the order of kinetics (b), activation energy (E) or trap depth, frequency factor (s) or escape probability and trap lifetime (τ), by analyzing the glow curves of the irradiated samples. The analysed trapping parameters indicate that the Toyota (E = 0.75-1.31 eV, s = 3.0E+6 - 3.7E+9 (s-1), τ = 6.9E+5 - 1.3E+14 s) and Honda (E = 0.95-1.68 eV, s = 2.1E+10 - 4.1E+13 (s-1), τ = 2.2E+9 - 3.1E+20 s) windscreen offer promising features for conventional TL dosimetry applications, while the obtained longer lifetime (τ = 6.8E+10 - 8.6E+29 s) or higher activation energy (E = 1.23-2.15 eV) for Proton brand windscreen indicates better stability or slow fading of the material, thus suitable for retrospective TL dosimetry. In addition, by assessing the area of deconvoluted micro-Raman spectra of windshield glasses in high-frequency regions, it has been observed the phenomenon of dose-dependent structural alterations and internal annealing of defects. This pattern is also consistent with those cyclical pattern observed in the intensity ratio of defect and graphite modes in the studies of carbon-rich media. Such common phenomena indicate the possibility of using the Raman microspectroscopy as a probe of radiation damage in silica-based media.

Rapid and Reproducible MALDI-TOF-Based Method for the Detection of Vancomycin-Resistant Enterococcus faecium Using Classifying Algorithms.

Vancomycin-resistant Enterococcus faecium represents a health threat due to its ability to spread and cause outbreaks. MALDI-TOF MS has demonstrated its usefulness for E. faecium identification, but its implementation for antimicrobial resistance detection is still under evaluation. This study assesses the repeatability of MALDI-TOF MS for peak analysis and its performance in the discrimination of vancomycin-susceptible (VSE) from vancomycin-resistant isolates (VRE). The study was carried out on protein spectra from 178 E. faecium unique clinical isolates-92 VSE, 31 VanA VRE, 55 VanB VRE-, processed with Clover MS Data Analysis software. Technical and biological repeatability were assayed. Unsupervised (principal component analysis, (PCA)) and supervised algorithms (support vector machine (SVM), random forest (RF) and partial least squares-discriminant analysis (PLS-DA)) were applied. The repeatability assay was performed with 18 peaks common to VSE and VRE with intensities above 1.0% of the maximum peak intensity. It showed lower variability for normalized data and for the peaks within the 3000-9000 m/z range. It was found that 80.9%, 79.2% and 77.5% VSE vs. VRE discrimination was achieved by applying SVM, RF and PLS-DA, respectively. Correct internal differentiation of VanA from VanB VRE isolates was obtained by SVM in 86.6% cases. The implementation of MALDI-TOF MS and peak analysis could represent a rapid and effective tool for VRE screening. However, further improvements are needed to increase the accuracy of this approach.

Comparing the electrophysiological effects of traumatic noise exposure between rodents.

Noise-induced hearing deficits are important health problems in the industrialized world. As the underlying physiological dysfunctions are not well understood, research in suitable animal models is urgently needed. Three rodent species (Mongolian gerbil, rat, and mouse) were studied to compare the temporal dynamics of noise-induced hearing loss after identical procedures of noise exposure. Auditory brainstem responses (ABRs) were measured before, during, and up to 8 wk after noise exposure for threshold determination and ABR waveform analysis. Trauma induction with stepwise increasing sound pressure level was interrupted by five interspersed ABR measurements. Comparing short- and long-term dynamics underlying the following noise-induced hearing loss revealed diverging time courses between the three species. Hearing loss occurred early on during noise exposure in all three rodent species at or above trauma frequency. Initial noise level (105 dB SPL) was most effective in rats whereas the delayed level increase to 115 dB SPL affected mice much stronger. Induced temporary threshold shifts in rats and mice were larger in animals with lower pretrauma ABR thresholds. The increase in activity (gain) along the auditory pathway was derived by comparing the amplitudes of short- and long-latency ABR waveform components. Directly after trauma, significant effects were found for rats (decreasing gain) and mice (increasing gain) whereas gerbils revealed high individual variability in gain changes. Taken together, our comparative study revealed pronounced species-specific differences in the development of noise-induced hearing loss and the related processing along the auditory pathway.NEW & NOTEWORTHY We compared deficits after noise trauma in different rodents that are typically used in hearing research (Mongolian gerbil, rat, and mouse). We observed noise-induced threshold changes and alterations in the activity of processing auditory information along the ascending auditory pathway. Our results reveal pronounced differences in the characteristics of trauma-induced damage in these different rodent groups.

Detection of azole resistance in Aspergillus fumigatus complex isolates using MALDI-TOF mass spectrometry.

OBJECTIVES: The main goal of this study was to accurately detect azole resistance in species of the Aspergillus fumigatus complex by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). METHODS: Identification of isolates (n = 868) was done with MALDI-TOF MS using both commercial and in-house libraries. To determine azole susceptibility, the EUCAST E.Def. 9.3.2 method was applied as the reference standard. Identification of resistant isolates was confirmed by DNA sequence analysis. Protein spectra obtained by MALDI-TOF MS were analysed to differentiate species within the A. fumigatus complex and to detect azole-resistant A. fumigatus sensu stricto isolates. RESULTS: Correct discrimination of A. fumigatus sensu stricto from cryptic species was accomplished in 100% of the cases applying principal component analysis (PCA) to protein spectra generated by MALDI-TOF MS. Furthermore, a specific peak (4586 m/z) was found to be present only in cryptic species. The application of partial least squares (PLS) discriminant analysis allowed 98.43% (±0.038) discrimination between susceptible and azole-resistant A. fumigatus sensu stricto isolates. Finally, based on PLS and SVM, A. fumigatus sensu stricto isolates with different cyp51A gene mutations were correctly clustered in 91.5% of the cases. CONCLUSIONS: MALDI-TOF MS combined with peak analysis is a novel tool that allows the differentiation of A. fumigatus sensu stricto from other species within the A. fumigatus complex, as well as the detection of azole-resistant A. fumigatus sensu stricto. Although further studies are still needed, the results reported here show the great potential of MALDI-TOF and machine learning for the rapid detection of azole-resistant Aspergillus fumigatus isolates from clinical origins.