Research in the field of remote sensing of the environment is valuable and informative. Hyperspectral (HSP) and multispectral (MSP) satellite images have been used for different remote sensing applications. Land Use/Land Cover (LU/LC) change classification has been considered as important research in the field of remote sensing environment. This review aims to identify the various LU/LC applications, remote sensing satellites, geospatial software, pre-processing techniques, LU/LC classification, clustering, spectral unmixing, landscape change models and evaluation metrics. The main objective of this review is to present the more frequently used techniques for analysing LU/LC change with MSP and HSP satellite images. An aim of this review is to motivate future researchers to work efficiently with MSP and HSP satellite images in the field of remote sensing.
{"title":"Comprehensive review on land use/land cover change classification in remote sensing","authors":"M. Sam Navin, L. Agilandeeswari","doi":"10.1255/jsi.2020.a8","DOIUrl":"https://doi.org/10.1255/jsi.2020.a8","url":null,"abstract":"Research in the field of remote sensing of the environment is valuable and informative. Hyperspectral (HSP) and multispectral (MSP) satellite images have been used for different remote sensing applications. Land Use/Land Cover (LU/LC) change classification has been considered as important research in the field of remote sensing environment. This review aims to identify the various LU/LC applications, remote sensing satellites, geospatial software, pre-processing techniques, LU/LC classification, clustering, spectral unmixing, landscape change models and evaluation metrics. The main objective of this review is to present the more frequently used techniques for analysing LU/LC change with MSP and HSP satellite images. An aim of this review is to motivate future researchers to work efficiently with MSP and HSP satellite images in the field of remote sensing.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46520895","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This Letter reviews the application of thermal imaging for food quality control. Thermal imaging uses a single, portable device, which provides a visible image of the invisible infrared radiation, and can be used for real-time monitoring at low cost compared to spectral imaging technology. To monitor the quality parameters of the sample, classification or regression models are constructed using multivariate analysis or chemometrics tools. Few studies have used thermography for the analysis of food to-date, so this Letter will only address thermal mapping, internal defect detection, adulteration detection and the prediction of compound concentration.
{"title":"Thermal imaging as a tool in food analysis","authors":"D. Ferreira","doi":"10.1255/jsi.2020.a7","DOIUrl":"https://doi.org/10.1255/jsi.2020.a7","url":null,"abstract":"This Letter reviews the application of thermal imaging for food quality control. Thermal imaging uses a single, portable device, which provides a visible image of the invisible infrared radiation, and can be used for real-time monitoring at low cost compared to spectral imaging technology. To monitor the quality parameters of the sample, classification or regression models are constructed using multivariate analysis or chemometrics tools. Few studies have used thermography for the analysis of food to-date, so this Letter will only address thermal mapping, internal defect detection, adulteration detection and the prediction of compound concentration.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43760188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Band selection is an effective way to reduce the size of hyperspectral data and to overcome the “curse of dimensionality” in ground object classification. This paper presents a band selection approach based on modified Cuckoo Search (CS) optimisation with correlation-based initialisation. CS is a popular metaheuristic algorithm with efficient optimisation capabilities for band selection. However, it can easily fall into local optimum solutions. To avoid falling into a local optimum, an initialisation strategy based on correlation is adopted instead of random initialisation to initiate the location of nests. Experimental results with Indian Pines, Salinas and Pavia University datasets show that the proposed approach obtains overall accuracy of 82.83 %, 94.83 % and 91.79 %, respectively, which is higher than the original CS algorithm, Genetic Algorithm (GA), Particle Swarm Optimisation (PSO) and Gray Wolf Optimisation (GWO).
{"title":"A modified Cuckoo Search algorithm based optimal band subset selection approach for hyperspectral image classification","authors":"S. Sawant, M. Prabukumar, Sathishkumar Samiappan","doi":"10.1255/jsi.2020.a6","DOIUrl":"https://doi.org/10.1255/jsi.2020.a6","url":null,"abstract":"Band selection is an effective way to reduce the size of hyperspectral data and to overcome the “curse of\u0000dimensionality” in ground object classification. This paper presents a band selection approach based on modified Cuckoo\u0000Search (CS) optimisation with correlation-based initialisation. CS is a popular metaheuristic algorithm with efficient\u0000optimisation capabilities for band selection. However, it can easily fall into local optimum solutions. To avoid falling into a\u0000local optimum, an initialisation strategy based on correlation is adopted instead of random initialisation to initiate the location\u0000of nests. Experimental results with Indian Pines, Salinas and Pavia University datasets show that the proposed approach\u0000obtains overall accuracy of 82.83 %, 94.83 % and 91.79 %, respectively, which is higher than the original CS algorithm,\u0000Genetic Algorithm (GA), Particle Swarm Optimisation (PSO) and Gray Wolf Optimisation (GWO).","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43644591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hyperspectral images usually contain hundreds of contiguous spectral bands, which can precisely discriminate the various spectrally similar classes. However, such high-dimensional data also contain highly correlated and irrelevant information, leading to the curse of dimensionality (also called the Hughes phenomenon). It is necessary to reduce these bands before further analysis, such as land cover classification and target detection. Band selection is an effective way to reduce the size of hyperspectral data and to overcome the curse of the dimensionality problem in ground object classification. Focusing on the classification task, this article provides an extensive and comprehensive survey on band selection techniques describing the categorisation of methods, methodology used, different searching approaches and various technical difficulties, as well as their performances. Our purpose is to highlight the progress attained in band selection techniques for hyperspectral image classification and to identify possible avenues for future work, in order to achieve better performance in real-time operation.
{"title":"A survey of band selection techniques for hyperspectral image classification","authors":"S. Sawant, M. Prabukumar","doi":"10.1255/jsi.2020.a5","DOIUrl":"https://doi.org/10.1255/jsi.2020.a5","url":null,"abstract":"Hyperspectral images usually contain hundreds of contiguous spectral bands, which can precisely discriminate the various spectrally similar classes. However, such high-dimensional data also contain highly correlated and irrelevant information, leading to the curse of dimensionality (also called the Hughes phenomenon). It is necessary to reduce these bands before further analysis, such as land cover classification and target detection. Band selection is an effective way to reduce the size of hyperspectral data and to overcome the curse of the dimensionality problem in ground object classification. Focusing on the classification task, this article provides an extensive and comprehensive survey on band selection techniques describing the categorisation of methods, methodology used, different searching approaches and various technical difficulties, as well as their performances. Our purpose is to highlight the progress attained in band selection techniques for hyperspectral image classification and to identify possible avenues for future work, in order to achieve better performance in real-time operation.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43127608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hugues Portier, C. Jaffré, C. Kewish, Christine Chappard, S. Pallu
Bone health depends on the bone mineral density and mechanical strength, characterised quantitatively and inferred through qualitative parameters such as the trabecular and cortical micro-architecture, and other parameters describing the bone cells. Among these cells, the osteocyte has been recognised as the orchestrator of bone remodelling, playing a key role in directing osteoblastic and osteoclastic activities. Conventional optical and electron microscopies have greatly improved our understanding of the cell physiology mechanisms involved in different osteoarticular pathophysiological contexts, especially osteoporosis. More recently, imaging methods exploiting synchrotron radiation, such as X-ray tomography, ptychography, and deep ultraviolet and Fourier transform infrared spectroscopies, have revealed new biochemical, chemical and 3D morphological information about the osteocyte lacuna, the surrounding matrix and the lacuna–canalicular network at spatial length scales spanning microns to tens of nanometres. Here, we review recent results in osteocyte lacuna and lacuna–canalicular network characterisation by synchrotron radiation imaging in human and animal models, contributing to new insights in different physiologic and pathophysiological situations.
{"title":"New insights in osteocyte imaging by synchrotron radiation","authors":"Hugues Portier, C. Jaffré, C. Kewish, Christine Chappard, S. Pallu","doi":"10.1255/jsi.2020.a3","DOIUrl":"https://doi.org/10.1255/jsi.2020.a3","url":null,"abstract":"Bone health depends on the bone mineral density and mechanical strength, characterised quantitatively and\u0000inferred through qualitative parameters such as the trabecular and cortical micro-architecture, and other parameters\u0000describing the bone cells. Among these cells, the osteocyte has been recognised as the orchestrator of bone remodelling,\u0000playing a key role in directing osteoblastic and osteoclastic activities. Conventional optical and electron microscopies have\u0000greatly improved our understanding of the cell physiology mechanisms involved in different osteoarticular\u0000pathophysiological contexts, especially osteoporosis. More recently, imaging methods exploiting synchrotron radiation,\u0000such as X-ray tomography, ptychography, and deep ultraviolet and Fourier transform infrared spectroscopies, have\u0000revealed new biochemical, chemical and 3D morphological information about the osteocyte lacuna, the surrounding matrix\u0000and the lacuna–canalicular network at spatial length scales spanning microns to tens of nanometres. Here, we review\u0000recent results in osteocyte lacuna and lacuna–canalicular network characterisation by synchrotron radiation imaging in\u0000human and animal models, contributing to new insights in different physiologic and pathophysiological situations.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44652733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Wahaia, I. Kašalynas, L. Minkevičius, C. Carvalho Silva, A. Urbanowicz, G. Valušis
Terahertz waves are sensitive to differences in biological tissue hydration, we present promising results regarding the feasibility of applying this with terahertz time-domain spectroscopy and imaging for early detection of cancer through the characterisation of human gastrointestinal tissue with cancer-affected regions. To do that, healthy (normal) and carcinoma-affected gastric tissue samples at different stages were measured using transmission terahertz time-domain spectroscopy in the frequency range of 0.15–2.00 THz. Absorption coefficients and refractive index spectra of both normal and carcinoma-affected tissue were extracted and analysed. The results confirm that the techniques may be powerful tools to perform qualitative, early diagnosis of human cancer.
{"title":"Terahertz spectroscopy and imaging for gastric cancer diagnosis","authors":"F. Wahaia, I. Kašalynas, L. Minkevičius, C. Carvalho Silva, A. Urbanowicz, G. Valušis","doi":"10.1255/jsi.2020.a2","DOIUrl":"https://doi.org/10.1255/jsi.2020.a2","url":null,"abstract":"Terahertz waves are sensitive to differences in biological tissue hydration, we present promising results regarding\u0000 the feasibility of applying this with terahertz time-domain spectroscopy and imaging for early detection of cancer through\u0000the characterisation of human gastrointestinal tissue with cancer-affected regions. To do that, healthy (normal) and\u0000carcinoma-affected gastric tissue samples at different stages were measured using transmission terahertz time-domain\u0000spectroscopy in the frequency range of 0.15–2.00 THz. Absorption coefficients and refractive index spectra of both\u0000normal and carcinoma-affected tissue were extracted and analysed. The results confirm that the techniques may be\u0000powerful tools to perform qualitative, early diagnosis of human cancer.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42861731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marie-Florence A. Yebouet, A. Diby, Kenneth A. Kaduki, J. Zoueu
We report the use of Time Multiplexing Super Resolution (TMSR) to reduce significantly speckle noise in spectral imaging microscopy of unstained thin blood smear samples of malaria-infected blood. The method is based on combining speckle illumination with a moving array serving as an encoding mask. We propose the use of a new encoding mask to improve the performance of the conventional TMSR method. The new mask is a two-dimensional generalisation of the one- dimensional Ipatov code. The mask is projected on the object and 13 low-resolution images captured and subsequently decoded properly using the same array. The low contrast images are added and extracted from the resulting reconstruction, giving a super-resolved, high-contrast image. The Ipatov filter used in this work performs better than the Barker filter.
{"title":"Unstained blood smear contrast enhancement using spectral time multiplexing super resolution","authors":"Marie-Florence A. Yebouet, A. Diby, Kenneth A. Kaduki, J. Zoueu","doi":"10.1255/jsi.2020.a1","DOIUrl":"https://doi.org/10.1255/jsi.2020.a1","url":null,"abstract":"We report the use of Time Multiplexing Super Resolution (TMSR) to reduce significantly speckle noise in spectral\u0000imaging microscopy of unstained thin blood smear samples of malaria-infected blood. The method is based on combining\u0000speckle illumination with a moving array serving as an encoding mask. We propose the use of a new encoding mask to\u0000improve the performance of the conventional TMSR method. The new mask is a two-dimensional generalisation of the one-\u0000dimensional Ipatov code. The mask is projected on the object and 13 low-resolution images captured and subsequently\u0000decoded properly using the same array. The low contrast images are added and extracted from the resulting\u0000reconstruction, giving a super-resolved, high-contrast image. The Ipatov filter used in this work performs better than the\u0000Barker filter.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45154841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Unobe, L. Lau, J. Kalivas, R. Rodriguez, A. Sorensen
Infrared thermal imaging is an evolving approach useful in non-destructive evaluation of materials for industrial and research purposes. This study investigates the use of this method in combination with multivariate data analysis as an alternative to chemical etching; a destructive method currently used to recover defaced serial numbers stamped in metal. This process involves several unique aspects, each of which works to overcome some pertinent challenges associated with the recovery of defaced serial numbers. Infrared thermal imaging of metal surfaces provides thermal images sensitive to local differences in thermal conductivity of regions of plastic strain existing below a stamped number. These strains are created from stamping pressures distorting the atomic crystalline structure of the metal and extend to depths beneath the stamped number. These thermal differences are quite small and thus not readily visible from the raw thermal images of an irregular surface created by removing the stamped numbers. As such, further enhancement is usually needed to identify the subtle variations. The multivariate data analysis method, principal component analysis, is used to enhance these subtle variations and aid the recovery of the serial numbers. Multiple similarity measures are utilised to match recovered numbers to several numerical libraries, followed by application of various fusion rules to achieve consensus identification.
{"title":"Restoration of defaced serial numbers using lock-in infrared thermography (Part I)","authors":"I. Unobe, L. Lau, J. Kalivas, R. Rodriguez, A. Sorensen","doi":"10.1255/jsi.2019.a20","DOIUrl":"https://doi.org/10.1255/jsi.2019.a20","url":null,"abstract":"Infrared thermal imaging is an evolving approach useful in non-destructive evaluation of materials for industrial and\u0000research purposes. This study investigates the use of this method in combination with multivariate data analysis as an\u0000alternative to chemical etching; a destructive method currently used to recover defaced serial numbers stamped in metal.\u0000This process involves several unique aspects, each of which works to overcome some pertinent challenges associated\u0000with the recovery of defaced serial numbers. Infrared thermal imaging of metal surfaces provides thermal images sensitive\u0000 to local differences in thermal conductivity of regions of plastic strain existing below a stamped number. These strains are\u0000 created from stamping pressures distorting the atomic crystalline structure of the metal and extend to depths beneath the\u0000stamped number. These thermal differences are quite small and thus not readily visible from the raw thermal images of an\u0000irregular surface created by removing the stamped numbers. As such, further enhancement is usually needed to identify\u0000the subtle variations. The multivariate data analysis method, principal component analysis, is used to enhance these subtle\u0000variations and aid the recovery of the serial numbers. Multiple similarity measures are utilised to match recovered numbers\u0000to several numerical libraries, followed by application of various fusion rules to achieve consensus identification.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42020422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Rivard, B. Bakan, C. Boulogne, K. Elmorjani, S. Swaraj, R. Belkhou, D. Marion
The main storage components of the maize endosperm are starch, proteins and lipids. Starch and proteins are heterogeneously deposited, leading to the formation of vitreous and floury regions at the periphery and at the centre of the endosperm. The vitreous/floury mass ratio is a key physical parameter of maize end-uses for the food, feed and non-food sectors, as well as for the resistance of seeds to environmental aggressions. To improve maize breeding for vitreousness, one of the main issues is to finely delineate the molecular and physicochemical mechanisms associated with the formation of endosperm texture. In this context, we use scanning transmission X-ray microscopy at the C K-edge on maize endosperm resin-embedded ultrathin sections. The combination of local near edge X-ray absorption fine structure (NEXAFS) spectroscopy and high-resolution images enable us to achieve a quantitative fine description of the spatial distribution of the main components within the endosperm.
{"title":"Spatial distribution of starch, proteins and lipids in maize endosperm probed by scanning transmission X-ray microscopy","authors":"C. Rivard, B. Bakan, C. Boulogne, K. Elmorjani, S. Swaraj, R. Belkhou, D. Marion","doi":"10.1255/jsi.2019.a21","DOIUrl":"https://doi.org/10.1255/jsi.2019.a21","url":null,"abstract":"The main storage components of the maize endosperm are starch, proteins and lipids. Starch and proteins are\u0000heterogeneously deposited, leading to the formation of vitreous and floury regions at the periphery and at the centre of the\u0000 endosperm. The vitreous/floury mass ratio is a key physical parameter of maize end-uses for the food, feed and non-food\u0000 sectors, as well as for the resistance of seeds to environmental aggressions. To improve maize breeding for\u0000vitreousness, one of the main issues is to finely delineate the molecular and physicochemical mechanisms associated with\u0000 the formation of endosperm texture. In this context, we use scanning transmission X-ray microscopy at the C K-edge on\u0000maize endosperm resin-embedded ultrathin sections. The combination of local near edge X-ray absorption fine structure\u0000(NEXAFS) spectroscopy and high-resolution images enable us to achieve a quantitative fine description of the spatial\u0000distribution of the main components within the endosperm.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43058086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
PB1-F2 is a non-structural protein of influenza A viruses (IAV) that modulates viral pathogenesis in a host-specific manner. In mammals, this protein has been shown to increase IAV virulence by delaying the early immune response and, eventually, exacerbating lung inflammation at the late stage of infection. PB1-F2 is a small protein, but displays very high sequence polymorphism and sequence length disparity depending on viral strain. These features result in strong variations in the cellular activity of PB1-F2. Studies have also reported that the effect of PB1-F2 is cell-type dependent. It has notably been shown that PB1-F2 can promote apoptosis in immune cells, but not in epithelial cells. This phenomenon appears to be partly related to the higher order structure of the protein, given that the presence of PB1-F2 β-aggregated structures in infected immune cells correlates with cell death induction. In this work, we evaluated, by synchrotron Fourier transform infrared spectromicroscopy, the impact of the transient expression of PB1-F2 on the biochemical composition of the human epithelial cell line HEK293T. Two PB1-F2 variants that are closely related to each other but derived from a strain with high [A/BrevigMission/1/1918 (H1N1)] or a low [A/WSN/1933 (H1N1)] virulence were studied here. Infrared spectra analysis revealed no specific enrichment of β-aggregated structures in PB1-F2-expressing cells. Nevertheless, this analysis suggested that there is a higher content of β-sheet secondary structures in the PB1-F2 from A/WSN/1933 than that from A/BrevigMission/1/1918. Our data also showed no change in membrane composition in the presence of PB1-F2, implying that PB1-F2 does not promote apoptosis in HEK293T cells. Finally, we found that the PB1-F2 from A/WSN/1933 interferes with adenosine triphosphate production, suggesting that this PB1-F2 variant may disturb the mitochondrial activity.
{"title":"Impact of the influenza protein PB1-F2 on the biochemical composition of human epithelial cells revealed by synchrotron Fourier transform infrared spectromicroscopy","authors":"O. Leymarie, R. Le Goffic, F. Jamme, C. Chevalier","doi":"10.1255/jsi.2019.a18","DOIUrl":"https://doi.org/10.1255/jsi.2019.a18","url":null,"abstract":"PB1-F2 is a non-structural protein of influenza A viruses (IAV) that modulates viral pathogenesis in a host-specific\u0000manner. In mammals, this protein has been shown to increase IAV virulence by delaying the early immune response and,\u0000eventually, exacerbating lung inflammation at the late stage of infection. PB1-F2 is a small protein, but displays very high\u0000sequence polymorphism and sequence length disparity depending on viral strain. These features result in strong variations\u0000 in the cellular activity of PB1-F2. Studies have also reported that the effect of PB1-F2 is cell-type dependent. It has notably\u0000 been shown that PB1-F2 can promote apoptosis in immune cells, but not in epithelial cells. This phenomenon appears to be\u0000 partly related to the higher order structure of the protein, given that the presence of PB1-F2 β-aggregated structures in\u0000infected immune cells correlates with cell death induction. In this work, we evaluated, by synchrotron Fourier transform\u0000infrared spectromicroscopy, the impact of the transient expression of PB1-F2 on the biochemical composition of the human\u0000 epithelial cell line HEK293T. Two PB1-F2 variants that are closely related to each other but derived from a strain with high\u0000[A/BrevigMission/1/1918 (H1N1)] or a low [A/WSN/1933 (H1N1)] virulence were studied here. Infrared spectra analysis\u0000revealed no specific enrichment of β-aggregated structures in PB1-F2-expressing cells. Nevertheless, this analysis\u0000suggested that there is a higher content of β-sheet secondary structures in the PB1-F2 from A/WSN/1933 than that from\u0000A/BrevigMission/1/1918. Our data also showed no change in membrane composition in the presence of PB1-F2, implying\u0000that PB1-F2 does not promote apoptosis in HEK293T cells. Finally, we found that the PB1-F2 from A/WSN/1933 interferes\u0000with adenosine triphosphate production, suggesting that this PB1-F2 variant may disturb the mitochondrial activity.","PeriodicalId":37385,"journal":{"name":"Journal of Spectral Imaging","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42190749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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