Detection and Automated Scoring of Dicentric Chromosomes in Nonstimulated Lymphocyte Prematurely Condensed Chromosomes After Telomere and Centromere Staining

PurposeTo combine telomere and centromere (TC) staining of premature chromosome condensation (PCC) fusions to identify dicentrics, centric rings, and acentric chromosomes, making possible the realization of a dose–response curve and automation of the process.Methods and MaterialsBlood samples from healthy donors were exposed to 60Co irradiation at varying doses up to 8 Gy, followed by a repair period of 8 hours. Premature chromosome condensation fusions were carried out, and TC staining using peptide nucleic acid probes was performed. Chromosomal aberration (CA) scoring was carried out manually and automatically using PCC-TCScore software, developed in our laboratory.ResultsWe successfully optimized the hybridization conditions and image capture parameters, to increase the sensitivity and effectiveness of CA scoring. Dicentrics, centric rings, and acentric chromosomes were rapidly and accurately detected, leading to a linear-quadratic dose–response curve by manual scoring at up to 8 Gy. Using PCC-TCScore software for automatic scoring, we were able to detect 95% of dicentrics and centric rings.ConclusionThe introduction of TC staining to the PCC fusion technique has made possible the rapid scoring of unstable CAs, including dicentrics, with a level of accuracy and ease not previously possible. This new approach can be used for biological dosimetry in radiation emergency medicine, where the rapid and accurate detection of dicentrics is a high priority using automated scoring. Because there is no culture time, this new approach can also be used for the follow-up of patients treated by genotoxic therapy, creating the possibility to perform the estimation of induced chromosomal aberrations immediately after the blood draw

Validation of image processing tools for 3-D fluorescence microscopy

International audience3-D optical fluorescent microscopy becomes nowadays an efficient tool for volumic investigation of living biological samples. Using optical sectioning technique, a stack of 2-D images is obtained. However, due to the nature of the system optical transfer function and non-optimal experimental conditions, acquired raw data usually suffer from some distortions. In order to carry out biological analysis, raw data have to be restored by deconvolution. The system identification by the point-spread function is useful to obtain the knowledge of the actual system and experimental parameters, which is necessary to restore raw data. It is furthermore helpful to precise the experimental protocol. In order to facilitate the use of image processing techniques, a multi-platform-compatible software package called VIEW3D has been developed. It integrates a set of tools for the analysis of fluorescence images from 3-D wide-field or confocal microscopy. A number of regularisation parameters for data restoration are determined automatically. Common geometrical measurements and morphological descriptors of fluorescent sites are also implemented to facilitate the characterisation of biological samples. An example of this method concerning cytogenetics is presented

The Transition between Telomerase and ALT Mechanisms in Hodgkin Lymphoma and Its Predictive Value in Clinical Outcomes

International audienceBackground: We analyzed telomere maintenance mechanisms (TMMs) in lymph node samples from HL patients treated with standard therapy. The TMMs correlated with clinical outcomes of patients. Materials and Methods: Lymph node biopsies obtained from 38 HL patients and 24 patients with lymphadenitis were included in this study. Seven HL cell lines were used as in vitro models. Telomerase activity (TA) was assessed by TRAP assay and verified through hTERT immunofluorescence expression; alternative telomere lengthening (ALT) was also assessed, along with EBV status. Results: Both TA and ALT mechanisms were present in HL lymph nodes. Our findings were reproduced in HL cell lines. The highest levels of TA were expressed in CD30−/CD15− cells. Small cells were identified with ALT and TA. Hodgkin and Reed Sternberg cells contained high levels of PML bodies, but had very low hTERT expression. There was a significant correlation between overall survival (p < 10−3), event-free survival (p < 10−4), and freedom from progression (p < 10−3) and the presence of an ALT profile in lymph nodes of EBV+ patients. Conclusion: The presence of both types of TMMs in HL lymph nodes and in HL cell lines has not previously been reported. TMMs correlate with the treatment outcome of EBV+ HL patients

Long-term kidney function recovery and mortality after COVID-19-associated acute kidney injury: An international multi-centre observational cohort study

Background: While acute kidney injury (AKI) is a common complication in COVID-19, data on post-AKI kidney function recovery and the clinical factors associated with poor kidney function recovery is lacking. Methods: A retrospective multi-centre observational cohort study comprising 12,891 hospitalized patients aged 18 years or older with a diagnosis of SARS-CoV-2 infection confirmed by polymerase chain reaction from 1 January 2020 to 10 September 2020, and with at least one serum creatinine value 1–365 days prior to admission. Mortality and serum creatinine values were obtained up to 10 September 2021. Findings: Advanced age (HR 2.77, 95%CI 2.53–3.04, p < 0.0001), severe COVID-19 (HR 2.91, 95%CI 2.03–4.17, p < 0.0001), severe AKI (KDIGO stage 3: HR 4.22, 95%CI 3.55–5.00, p < 0.0001), and ischemic heart disease (HR 1.26, 95%CI 1.14–1.39, p < 0.0001) were associated with worse mortality outcomes. AKI severity (KDIGO stage 3: HR 0.41, 95%CI 0.37–0.46, p < 0.0001) was associated with worse kidney function recovery, whereas remdesivir use (HR 1.34, 95%CI 1.17–1.54, p < 0.0001) was associated with better kidney function recovery. In a subset of patients without chronic kidney disease, advanced age (HR 1.38, 95%CI 1.20–1.58, p < 0.0001), male sex (HR 1.67, 95%CI 1.45–1.93, p < 0.0001), severe AKI (KDIGO stage 3: HR 11.68, 95%CI 9.80–13.91, p < 0.0001), and hypertension (HR 1.22, 95%CI 1.10–1.36, p = 0.0002) were associated with post-AKI kidney function impairment. Furthermore, patients with COVID-19-associated AKI had significant and persistent elevations of baseline serum creatinine 125% or more at 180 days (RR 1.49, 95%CI 1.32–1.67) and 365 days (RR 1.54, 95%CI 1.21–1.96) compared to COVID-19 patients with no AKI. Interpretation: COVID-19-associated AKI was associated with higher mortality, and severe COVID-19-associated AKI was associated with worse long-term post-AKI kidney function recovery. Funding: Authors are supported by various funders, with full details stated in the acknowledgement section

Déconvolution adaptative en microscopie tridimensionnelle de fluorescence

Le microscope de fluorescence a pris une place importante pour l étude du fonctionnement des cellules vivantes. Cependant, les données acquises ne sont pas directement exploitables en vu de mesures quantitatives car ces données subissent des distorsions. Une déconvolution est une solution au probleme. Des méthodes ont été proposées, mais requierent des connaissances de l utilisateur pour le réglage de parametres qui sont critiques, car ce probleme inverse est mal posé et une étape de régularisation est nécessaire. La premiere partie propose une automatisation du choix des parametres de régularisation des méthodes directes. L objectif est de permettre une utilisation de routine pour des non-spécialistes, permettant une constance des résultats ainsi qu une stabilité accrue. Les méthodes directes automatisées ont été appliquées a des images de cytologie et de cytogénétique moléculaire. Cependant, les déconvolutions nécessitent une bonne caractérisation du systeme, et une étude sur les parametres susceptibles de varier entre plusieurs acquisitions est présentée. La seconde partie de cette these propose un algorithme permettant la prise en compte de la non invariance du systeme, basé sur le processus de formation d image. Par une approche Monte-Carlo, la solution est calculée par essais successifs aléatoires, en suivant une distribution de probabilité qui est fonction de l erreur de biais entre l estimation dans le plan image et l image observée. La solution est obtenue en minimisant, par un algorithme de recuit simulé, une fonction d erreur dans l espace image , avec contraintes sur le voisinage dans l espace objet .The 3D fluorescence microscope has become the method of choice in biological sciences for living cells study. However, the data acquired with conventional 3D fluorescence microscope are not quantitatively significant for spatial distribution or volume evaluation of fluorescent areas in reason of distortions. Deconvolution is a solution. Direct methods have been proposed, but knowledge of users for the tuning of critical parameters are required, because of the regularization needs due to the ill posed nature of the problem. The first part of this work present the automated tuning of direct methods regularization parameter. The aim is to permit the use of deconvolution by non specialists, giving constant results. The automated direct methods were applied on cytology and cytogenetic 3D data. The presented methods require a sharp characterization of the instrument, so an analysis of the influence of variation of the optical setup on the deconvolution result is presented. The last part of the work present concern the second tendency of deconvolution algorithms, by taking into account the space-variant response case. The solution is computed by a Monte-Carlo process, random guesses following a probability distribution function linked to the bias error of the estimation of the observed image and the raw observed image. The solution is obtained by the minimization of an error criterion in image space with neighborhood constraints in object space.MULHOUSE-SCD Sciences (682242102) / SudocSudocFranceF

Contribution à la microscopie de fluorescence, Deconvolution des échantillons épais avec PSF variables en profondeur

La reconstruction 3D par coupes sériées en microscopie optique est un moyen efficace pour étudier des spécimens biologiques fluorescents. Dans un tel système, la formation d'une image peut être représentée comme une convolution linéaire d'un objet avec une réponse impulsionnelle optique de l'instrument (PSF). Pour une étude quantitative, une estimation de l'objet doit être calculée en utilisant la déconvolution qui est le phénomène inverse de la convolution. Plusieurs algorithmes de déconvolution ont été développés en se basant sur des modèles statistiques ou par inversion directe, mais ces algorithmes se basent sur la supposition de l'invariance spatiale de la PSF pour simplifier et accélérer le processus. Dans certaines configurations optiques la PSF 3D change significativement en profondeur et ignorer ces changements implique des erreurs quantitatives dans l'estimation. Nous proposons un algorithme (EMMA) qui se base sur une hypothèse où l'erreur minimale sur l'estimation par un algorithme ne tenant pas compte de la non-invariance, se situe aux alentours de la position (profondeur) de la PSF utilisée. EMMA utilise des PSF à différentes positions et fusionne les différentes estimations en utilisant des masques d'interpolation linéaires adaptatifs aux positions des PSF utilisées. Pour obtenir des PSF à différentes profondeurs, un algorithme d'interpolation de PSF a également été développé. La méthode consiste à décomposer les PSF mesurées en utilisant les moments de Zernike pseudo-3D, puis les variations de chaque moment sont approximés par une fonction polynomiale. Ces fonctions polynomiales sont utilisées pour interpoler des PSF aux profondeurs voulues.The 3-D fluorescence microscope has become the method of choice in biological sciences for living cells study. However, the data acquired with conventional3-D fluorescence microscopy are not quantitatively significant because of distortions induced by the optical acquisition process. Reliable measurements need the correction of theses distortions. Knowing the instrument impulse response, also known as the PSF, one can consider the backward process of convolution induced by the microscope, known as "deconvolution". However, when the system response is not invariant in the observation field, the classical algorithms can introduce large errors in the results. In this thesis we propose a new approach, which can be easily adapted to any classical deconvolution algorithm, direct or iterative, for bypassing the non-invariance PSF problem, without any modification to the later. Based on the hypothesis that the minimal error in a restored image using non-invariance assumption is located near the used PSF position, the EMMA (Evolutive Merging Masks Algorithm) blends multiple deconvolutions in the invariance assumption using a specific merging mask set. In order to obtain sufficient number of measured PSF at various depths for a better restoration using EMMA (or any other depth-variant deconvolution algorithm) we propose a 3D PSF interpolation algorithm based on the image moments theory using Zernike polynomials as decomposition base. The known PSF are decomposed into Zernike moments set and each moment's variation is fitted into a polynomial function, the resulting functions are then used to interpolate the needed PSF's Zernike moments set to reconstruct the interpolated PSF.MULHOUSE-SCD Sciences (682242102) / SudocSudocFranceF

Microgrid Cyber-Security: Review and Challenges toward Resilience

The importance of looking into microgrid security is getting more crucial due to the cyber vulnerabilities introduced by digitalization and the increasing dependency on information and communication technology (ICT) systems. Especially with a current academic unanimity on the incremental significance of the microgrid&rsquo;s role in building the future smart grid, this article addresses the existing approaches attending to cyber-physical security in power systems from a microgrid-oriented perspective. First, we start with a brief descriptive review of the most commonly used terms in the latest relevant literature, followed by a comprehensive presentation of the recent efforts explored in a manner that helps the reader to choose the appropriate future research direction among several fields

New Time-Frequency Transient Features for Nonintrusive Load Monitoring

A crucial step in nonintrusive load monitoring (NILM) is feature extraction, which consists of signal processing techniques to extract features from voltage and current signals. This paper presents a new time-frequency feature based on Stockwell transform. The extracted features aim to describe the shape of the current transient signal by applying an energy measure on the fundamental and the harmonic frequency voices. In order to validate the proposed methodology, classical machine learning tools are applied (k-NN and decision tree classifiers) on two existing datasets (Controlled On/Off Loads Library (COOLL) and Home Equipment Laboratory Dataset (HELD1)). The classification rates achieved are clearly higher than that for other related studies in the literature, with 99.52% and 96.92% classification rates for the COOLL and HELD1 datasets, respectively