Application de la factorisation en matrices non-négatives à l'élimination de l'autofluorescence des tissus biologiques

National audienceFluorescent imaging in diffusive media is an emerging modality for medical applications. Here, we use spectrally resolved measurements in order to separate several fluorescence sources. As we want to examine deep (4 cm) fluorophores for human applications, a very weak optical signal is measured and any interference to it may limit the sensitivity of the system. It is thus useful to filter any parasite signal, such as the intrinsic biological tissues fluorescence, called autofluorescence, which mixes with the fluorophore-specific signal. A spectroscopic approach, based on the Non-negative Matrix Factorization (NMF) method, is explored to unmix overlapping spectra and thus isolate the specific fluorescence signals from the autofluorescence signal. This blind source separation method treats specific fluorescence and autofluorescence as different sources to separate; it only needs initial spectra, updated over iterations thanks to regularized multiplicative update rules. Fluorescence contributions of intrinsic fluorescence and specific fluorescence have been satisfactorily isolated on experimental data

Non-negative Matrix Factorization: a blind sources separation method applied to optical fluorescence spectroscopy and multiplexing

International audienceFluorescence optical imaging use one or several (in multiplexing) injected fluorescent markers which specifically bind to targeted compounds. Near infrared light illuminates the region of interest and the emitted fluorescence is analyzed to localize fluorescence sources. A spectroscopic approach and a separation source method (Nonnegative matrix factorization) are explored to separate di fferent fluorescence sources and remove the unwanted biological tissues autofluorescence. We present unmixing results on overlapping spectra of interest, and show that autofluorescence removal improves Fluorescent Diffuse Optical Tomograph

Nonnegative matrix factorization: a blind spectra separation method for in vivo fluorescent optical imaging

International audienceFluorescence imaging in diffusive media is an emerging imaging modality for medical applications that uses injected fluorescent markers that bind to specific targets, e.g., carcinoma. The region of interest is illuminated with near-IR light and the emitted back fluorescence is analyzed to localize the fluorescence sources. To investigate a thick medium, as the fluorescence signal decreases with the light travel distance, any disturbing signal, such as biological tissues intrinsic fluorescence (called autofluorescence) is a limiting factor. Several specific markers may also be simultaneously injected to bind to different molecules, and one may want to isolate each specific fluorescent signal from the others. To remove the unwanted fluorescence contributions or separate different specific markers, a spectroscopic approach is explored. The nonnegative matrix factorization (NMF) is the blind positive source separation method we chose. We run an original regularized NMF algorithm we developed on experimental data, and successfully obtain separated in vivo fluorescence spectra

Application de la Factorisation en Matrices Non-négatives pour l'amélioration de la localisation de tumeurs en tomographie optique diffusive de fluorescence

National audienceL'imagerie optique de fluorescence permet de localiser des marqueurs fluorescents spécifiques injectés au patient qui s'accumulent autour de tumeurs cancéreuses. Une fois les régions dŠintérêt illuminées, un signal de fluorescence est émis par les marqueurs mais également par les tissus sains environnants. Lors de l'analyse de tissus épais, alors que le signal de fluorescence décroit avec le parcours de la lumière, l'autofluorescence des tissus prévient la détection des marqueurs profonds. Un approche spectroscopique basée sur la Factorisation en Matrices Non-négatives (FMN) est proposée pour séparer les spectres de fluorescence et éliminer l'autofluorescence des tissus. Afin de limiter le problème de non-unicité de la décomposition, l'ajout d'a priori à la méthode classique développée par Lee et Seung est proposé; la pertinence de ces contraintes est illustrée sur des exemples d'acquisitions de fluorescence in vivo

In vivo fluorescence spectra unmixing and autofluorescence removal by sparse Non-negative Matrix Factorization

International audienceFluorescence imaging locates fluorescent markers that specifically bind to targets, as tumors: markers are injected to a patient, optimally excited with near infrared light, and located thanks to emitted back fluorescence analysis. To investigate thick and diffusive media, as the fluorescence signal decreases with the light travel distance, the autofluorescence of biological tissues comes to be a limiting factor. To remove autofluorescence and isolate specific fluorescence, a spectroscopic approach, based on Non-negative Matrix Factorization (NMF), is explored. To improve results on spatially sparse markers detection, we suggest a new constrained NMF algorithm which takes sparsity constraints into account. A comparative study between both algorithms is proposed on simulated and in vivo data

Non-negative Matrix Factorization under sparsity constraints to unmix in vivo spectrally resolved acquisitions

International audienceFluorescence imaging in diffusive media is an emerging imaging modality for medical applications which uses injected fluorescent markers (several ones may be simultaneously injected) that bind to specific targets, as tumors. The region of interest is illuminated with near infrared light and the emitted back fluorescence is analyzed to localize the fluorescence sources. To investigate thick medium, as the fluorescence signal decreases with the light travel distance, any disturbing signal, such as biological tissues intrinsic fluorescence - called autofluorescence -, is a limiting factor. To remove autofluorescence and isolate each specific fluorescent signal from the others, a spectroscopic approach, based on Non-negative Matrix Factorization, is explored. We ran an NMF algorithm with sparsity constraints on experimental data, and successfully obtained separated in vivo fluorescence spectra

Regularized non negative matrix factorization for autofluorescence removal in fluorescence optical imaging

International audienceFluorescence imaging in diffusive media locates cancers thanks to injected fluorescent markers specific to the tumors. The region of interest is illuminated with red light and the emitted back fluorescence is analyzed to locate the fluorescence sources. To detect accurately the markers signal and be able to explore thick media (breast, prostate), autofluorescence emitted by biological tissues has to be removed. We propose a spectroscopic approach, based on Non-negative Matrix Factorization (NMF) method, and present interest of regularized NMF algorithms on unmixing results. In vivo autofluorescence removal and tumor detection enhancement results on mice will be presented

Genome analyses of the microalga Picochlorum provide insights into the evolution of thermotolerance in the green lineage

While the molecular events involved in cell responses to heat stress have been extensively studied, our understanding of the genetic basis of basal thermotolerance, and particularly its evolution within the green lineage, remains limited. Here, we present the 13.3-Mb haploid genome and transcriptomes of a halotolerant and thermotolerant unicellular green alga, Picochlorum costavermella (Trebouxiophyceae) to investigate the evolution of the genomic basis of thermotolerance. Differential gene expression at high and standard temperatures revealed that more of the gene families containing up-regulated genes at high temperature were recently evolved, and less originated at the ancestor of green plants. Inversely, there was an excess of ancient gene families containing transcriptionally repressed genes. Interestingly, there is a striking overlap between the thermotolerance and halotolerance transcriptional rewiring, as more than one-third of the gene families up-regulated at 35 degrees C were also up-regulated under variable salt concentrations in Picochlorum SE3. Moreover, phylogenetic analysis of the 9,304 protein coding genes revealed 26 genes of horizontally transferred origin in P. costavermella, of which five were differentially expressed at higher temperature. Altogether, these results provide new insights about how the genomic basis of adaptation to halo- and thermotolerance evolved in the green lineage

Using the multivariate Hawkes process to study interactions between multiple species from camera trap data

DATA AVAILABILITY STATEMENT : Data and code (Nicvert et al., 2023) are available on Figshare at https://doi.org/10.6084/m9.figshare.24552157.v5.Interspecific interactions can influence species' activity and movement patterns. In particular, species may avoid or attract each other through reactive responses in space and/or time. However, data and methods to study such reactive interactions have remained scarce and were generally limited to two interacting species. At this time, the deployment of camera traps opens new opportunities but adapted statistical techniques are still required to analyze interaction patterns with such data. We present the multivariate Hawkes process (MHP) and show how it can be used to analyze interactions between several species using camera trap data. Hawkes processes use flexible pairwise interaction functions, allowing us to consider asymmetries and variations over time when depicting reactive temporal interactions. After describing the theoretical foundations of the MHP, we outline how its framework can be used to study interspecific interactions with camera trap data. We design a simulation study to evaluate the performance of the MHP and of another existing method to infer interactions from camera trap-like data. We also use the MHP to infer reactive interactions from real camera trap data for five species from South African savannas (impala Aepyceros melampus, greater kudu Tragelaphus strepsiceros, lion Panthera leo, blue wildebeest Connochaetes taurinus and Burchell's zebra Equus quagga burchelli). The simulation study shows that the MHP can be used as a tool to benchmark other methods of interspecific interaction inference and that this model can reliably infer interactions when enough data are considered. The analysis of real data highlights evidence of predator avoidance by prey and herbivore–herbivore attraction. Lastly, we present the advantages and limits of the MHP and discuss how it can be improved to infer attraction/avoidance patterns more reliably. As camera traps are increasingly used, the multivariate Hawkes process provides a promising framework to decipher the complexity of interactions structuring ecological communities.The French National Research Agency ANR (project EcoNet).https://onlinelibrary.wiley.com/r/ecyhj2024Mammal Research InstituteZoology and EntomologySDG-15:Life on lan

Improved Survival of HIV-1-Infected Patients with Progressive Multifocal Leukoencephalopathy Receiving Early 5-Drug Combination Antiretroviral Therapy

Progressive multifocal leukoencephalopathy (PML), a rare devastating demyelinating disease caused by the polyomavirus JC (JCV), occurs in severely immunocompromised patients, most of whom have advanced-stage HIV infection. Despite combination antiretroviral therapy (cART), 50% of patients die within 6 months of PML onset. We conducted a multicenter, open-label pilot trial evaluating the survival benefit of a five-drug cART designed to accelerate HIV replication decay and JCV-specific immune recovery.All the patients received an optimized cART with three or more drugs for 12 months, plus the fusion inhibitor enfuvirtide during the first 6 months. The main endpoint was the one-year survival rate. A total of 28 patients were enrolled. At entry, median CD4+ T-cell count was 53 per microliter and 86% of patients had detectable plasma HIV RNA and CSF JCV DNA levels. Seven patients died, all before month 4. The one-year survival estimate was 0.75 (95% confidence interval, 0.61 to 0.93). At month 6, JCV DNA was undetectable in the CSF of 81% of survivors. At month 12, 81% of patients had undetectable plasma HIV RNA, and the median CD4+ T-cell increment was 105 per microliter. In univariate analysis, higher total and naive CD4+ T-cell counts and lower CSF JCV DNA level at baseline were associated with better survival. JCV-specific functional memory CD4+ T-cell responses, based on a proliferation assay, were detected in 4% of patients at baseline and 43% at M12 (P = 0.008).The early use of five-drug cART after PML diagnosis appears to improve survival. This is associated with recovery of anti-JCV T-cell responses and JCV clearance from CSF. A low CD4+ T-cell count (particularly naive subset) and high JCV DNA copies in CSF at PML diagnosis appear to be risk factors for death.ClinicalTrials.gov NCT00120367