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Colorectal cancer presents one of the most elevated incidences of cancer worldwide. Colonoscopy relies on histopathology analysis of hematoxylin-eosin (H&E) images of the removed tissue. Novel techniques such as multi-photon microscopy (MPM) show promising results for performing real-time optical biopsies. However, clinicians are not used to this imaging modality and correlation between MPM and H&E information is not clear. The objective of this paper is to describe and make publicly available an extensive dataset of fully co-registered H&E and MPM images that allows the research community to analyze the relationship between MPM and H&E histopathological images and the effect of the semantic gap that prevents clinicians from correctly diagnosing MPM images. The dataset provides a fully scanned tissue images at 10x optical resolution (0.5 m/px) from 50 samples of lesions obtained by colonoscopies and colectomies. Diagnostics capabilities of TPF and H&E images were compared. Additionally, TPF tiles were virtually stained into H&E images by means of a deep-learning model. A panel of 5 expert pathologists evaluated the different modalities into three classes (healthy, adenoma/hyperplastic, and adenocarcinoma). Results showed that the performance of the pathologists over MPM images was 65% of the H&E performance while the virtual staining method achieved 90%. MPM imaging can provide appropriate information for diagnosing colorectal cancer without the need for H&E staining. However, the existing semantic gap among modalities needs to be corrected.

Colorectal cancer presents one of the most elevated incidences of cancer worldwide. Colonoscopy relies on histopathology analysis of hematoxylin-eosin (H&E) images of the removed tissue. Novel techniques such as multi-photon microscopy (MPM) show promising results for performing real-time optical biopsies. However, clinicians are not used to this imaging modality and correlation between MPM and H&E information is not clear. The objective of this paper is to describe and make publicly available an extensive dataset of fully co-registered H&E and MPM images that allows the research community to analyze the relationship between MPM and H&E histopathological images and the effect of the semantic gap that prevents clinicians from correctly diagnosing MPM images. The dataset provides a fully scanned tissue images at 10x optical resolution (0.5 m/px) from 50 samples of lesions obtained by colonoscopies and colectomies. Diagnostics capabilities of TPF and H&E images were compared. Additionally, TPF tiles were virtually stained into H&E images by means of a deep-learning model. A panel of 5 expert pathologists evaluated the different modalities into three classes (healthy, adenoma/hyperplastic, and adenocarcinoma). Results showed that the performance of the pathologists over MPM images was 65% of the H&E performance while the virtual staining method achieved 90%. MPM imaging can provide appropriate information for diagnosing colorectal cancer without the need for H&E staining. However, the existing semantic gap among modalities needs to be corrected.

Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.

Colorectal cancer presents one of the most elevated incidences of cancer worldwide. Colonoscopy relies on histopathology analysis of hematoxylin-eosin (H&E) images of the removed tissue. Novel techniques such as multi-photon microscopy (MPM) show promising results for performing real-time optical biopsies. However, clinicians are not used to this imaging modality and correlation between MPM and H&E information is not clear. The objective of this paper is to describe and make publicly available an extensive dataset of fully co-registered H&E and MPM images that allows the research community to analyze the relationship between MPM and H&E histopathological images and the effect of the semantic gap that prevents clinicians from correctly diagnosing MPM images. The dataset provides a fully scanned tissue images at 10x optical resolution (0.5 m/px) from 50 samples of lesions obtained by colonoscopies and colectomies. Diagnostics capabilities of TPF and H&E images were compared. Additionally, TPF tiles were virtually stained into H&E images by means of a deep-learning model. A panel of 5 expert pathologists evaluated the different modalities into three classes (healthy, adenoma/hyperplastic, and adenocarcinoma). Results showed that the performance of the pathologists over MPM images was 65% of the H&E performance while the virtual staining method achieved 90%. MPM imaging can provide appropriate information for diagnosing colorectal cancer without the need for H&E staining. However, the existing semantic gap among modalities needs to be corrected.

Colorectal cancer presents one of the most elevated incidences of cancer worldwide. Colonoscopy relies on histopathology analysis of hematoxylin-eosin (H&E) images of the removed tissue. Novel techniques such as multi-photon microscopy (MPM) show promising results for performing real-time optical biopsies. However, clinicians are not used to this imaging modality and correlation between MPM and H&E information is not clear. The objective of this paper is to describe and make publicly available an extensive dataset of fully co-registered H&E and MPM images that allows the research community to analyze the relationship between MPM and H&E histopathological images and the effect of the semantic gap that prevents clinicians from correctly diagnosing MPM images. The dataset provides a fully scanned tissue images at 10x optical resolution (0.5 m/px) from 50 samples of lesions obtained by colonoscopies and colectomies. Diagnostics capabilities of TPF and H&E images were compared. Additionally, TPF tiles were virtually stained into H&E images by means of a deep-learning model. A panel of 5 expert pathologists evaluated the different modalities into three classes (healthy, adenoma/hyperplastic, and adenocarcinoma). Results showed that the performance of the pathologists over MPM images was 65% of the H&E performance while the virtual staining method achieved 90%. MPM imaging can provide appropriate information for diagnosing colorectal cancer without the need for H&E staining. However, the existing semantic gap among modalities needs to be corrected.

Background: Colorectal cancer has a high incidence rate worldwide, with over 1.8 million new cases and 880,792 deaths in 2018. Fortunately, its early detection significantly increases the survival rate, reaching a cure rate of 90% when diagnosed at a localized stage. Colonoscopy is the gold standard technique for detection and removal of colorectal lesions with potential to evolve into cancer. When polyps are found in a patient, the current procedure is their complete removal. However, in this process, gastroenterologists cannot assure complete resection and clean margins which are given by the histopathology analysis of the removed tissue, which is performed at laboratory. Aims: In this paper, we demonstrate the capabilities of multiphoton microscopy (MPM) technology to provide imaging biomarkers that can be extracted by deep learning techniques to identify malignant neoplastic colon lesions and distinguish them from healthy, hyperplastic, or benign neoplastic tissue, without the need for histopathological staining. Materials and Methods: To this end, we present a novel MPM public dataset containing 14,712 images obtained from 42 patients and grouped into 2 classes. A convolutional neural network is trained on this dataset and a spatially coherent predictions scheme is applied for performance improvement. Results: We obtained a sensitivity of 0.8228 ± 0.1575 and a specificity of 0.9114 ± 0.0814 on detecting malignant neoplastic lesions. We also validated this approach to estimate the self-confidence of the network on its own predictions, obtaining a mean sensitivity of 0.8697 and a mean specificity of 0.9524 with the 18.67% of the images classified as uncertain. Conclusions: This work lays the foundations for performing in vivo optical colon biopsies by combining this novel imaging technology together with deep learning algorithms, hence avoiding unnecessary polyp resection and allowing in situ diagnosis assessment.

Background: Colorectal cancer has a high incidence rate worldwide, with over 1.8 million new cases and 880,792 deaths in 2018. Fortunately, its early detection significantly increases the survival rate, reaching a cure rate of 90% when diagnosed at a localized stage. Colonoscopy is the gold standard technique for detection and removal of colorectal lesions with potential to evolve into cancer. When polyps are found in a patient, the current procedure is their complete removal. However, in this process, gastroenterologists cannot assure complete resection and clean margins which are given by the histopathology analysis of the removed tissue, which is performed at laboratory. Aims: In this paper, we demonstrate the capabilities of multiphoton microscopy (MPM) technology to provide imaging biomarkers that can be extracted by deep learning techniques to identify malignant neoplastic colon lesions and distinguish them from healthy, hyperplastic, or benign neoplastic tissue, without the need for histopathological staining. Materials and Methods: To this end, we present a novel MPM public dataset containing 14,712 images obtained from 42 patients and grouped into 2 classes. A convolutional neural network is trained on this dataset and a spatially coherent predictions scheme is applied for performance improvement. Results: We obtained a sensitivity of 0.8228 ± 0.1575 and a specificity of 0.9114 ± 0.0814 on detecting malignant neoplastic lesions. We also validated this approach to estimate the self-confidence of the network on its own predictions, obtaining a mean sensitivity of 0.8697 and a mean specificity of 0.9524 with the 18.67% of the images classified as uncertain. Conclusions: This work lays the foundations for performing in vivo optical colon biopsies by combining this novel imaging technology together with deep learning algorithms, hence avoiding unnecessary polyp resection and allowing in situ diagnosis assessment.

Background: Colorectal cancer has a high incidence rate worldwide, with over 1.8 million new cases and 880,792 deaths in 2018. Fortunately, its early detection significantly increases the survival rate, reaching a cure rate of 90% when diagnosed at a localized stage. Colonoscopy is the gold standard technique for detection and removal of colorectal lesions with potential to evolve into cancer. When polyps are found in a patient, the current procedure is their complete removal. However, in this process, gastroenterologists cannot assure complete resection and clean margins which are given by the histopathology analysis of the removed tissue, which is performed at laboratory. Aims: In this paper, we demonstrate the capabilities of multiphoton microscopy (MPM) technology to provide imaging biomarkers that can be extracted by deep learning techniques to identify malignant neoplastic colon lesions and distinguish them from healthy, hyperplastic, or benign neoplastic tissue, without the need for histopathological staining. Materials and Methods: To this end, we present a novel MPM public dataset containing 14,712 images obtained from 42 patients and grouped into 2 classes. A convolutional neural network is trained on this dataset and a spatially coherent predictions scheme is applied for performance improvement. Results: We obtained a sensitivity of 0.8228 ± 0.1575 and a specificity of 0.9114 ± 0.0814 on detecting malignant neoplastic lesions. We also validated this approach to estimate the self-confidence of the network on its own predictions, obtaining a mean sensitivity of 0.8697 and a mean specificity of 0.9524 with the 18.67% of the images classified as uncertain. Conclusions: This work lays the foundations for performing in vivo optical colon biopsies by combining this novel imaging technology together with deep learning algorithms, hence avoiding unnecessary polyp resection and allowing in situ diagnosis assessment.

Bladder cancer (BC) is the eleventh most diagnosed cancer worldwide. The age-standardized incidence rate (per 100 000 person/years) is 9.0 for men and 2.2 for women [1]. Urothelial carcinoma (UC) represents about 90% of all bladder tumors, thus carrying an enormous social and economic burden [2]. UCs are classified in different stages and grades, depending on their invasiveness and on their degree of cytological abnormalities. The key aspect for a positive prognosis is the early and accurate diagnosis of the lesion stage, in order to identify the most aggressive disease forms and treat them promptly. It is well known that tissue metabolism constitutes a basic mechanism, which is at the base of many pathologies, especially BC. Being able to detect and characterize tissue metabolism and molecular fingerprints at the cellular level could be a key aspect in characterizing the pathology and enabling both early detection and therapy monitoring. The new European Union Horizon 2020 project called AMPLITUDE, the ‘Advanced Multimodal Photonics Laser Imaging Tool for Urothelial Diagnosis in Endoscopy’, starting in January 2020, proposes the development of an advanced multi-modal imaging tool exploiting new laser technologies in an approach combining confocal and non-linear imaging to fulfil unmet clinical needs in terms of the specificity and accuracy of urothelial cancer diagnosis and therapy monitoring. The project is coordinated by Tampere University (Finland) and carried out in cooperation with leading European research organizations including Aston Insitute of Photonic Technologies—AIPT (UK), Consiglio Nazionale delle Ricerche—CNR (Italy), Institute of Photonic Sciences—ICFO (Spain), University of Milan-Bicocca, Modus Research and Innovation Ltd. (UK) and University of Florence (Italy), as well as industrial partners: Ampliconyx Oy (Finland), Femtonics Ltd. (Hungary), HC Photonics (Taiwan), and LEONI Fiber Optics GmbH (Germany).

Bladder cancer (BC) is the eleventh most diagnosed cancer worldwide. The age-standardized incidence rate (per 100 000 person/years) is 9.0 for men and 2.2 for women [1]. Urothelial carcinoma (UC) represents about 90% of all bladder tumors, thus carrying an enormous social and economic burden [2]. UCs are classified in different stages and grades, depending on their invasiveness and on their degree of cytological abnormalities. The key aspect for a positive prognosis is the early and accurate diagnosis of the lesion stage, in order to identify the most aggressive disease forms and treat them promptly. It is well known that tissue metabolism constitutes a basic mechanism, which is at the base of many pathologies, especially BC. Being able to detect and characterize tissue metabolism and molecular fingerprints at the cellular level could be a key aspect in characterizing the pathology and enabling both early detection and therapy monitoring. The new European Union Horizon 2020 project called AMPLITUDE, the ‘Advanced Multimodal Photonics Laser Imaging Tool for Urothelial Diagnosis in Endoscopy’, starting in January 2020, proposes the development of an advanced multi-modal imaging tool exploiting new laser technologies in an approach combining confocal and non-linear imaging to fulfil unmet clinical needs in terms of the specificity and accuracy of urothelial cancer diagnosis and therapy monitoring. The project is coordinated by Tampere University (Finland) and carried out in cooperation with leading European research organizations including Aston Insitute of Photonic Technologies—AIPT (UK), Consiglio Nazionale delle Ricerche—CNR (Italy), Institute of Photonic Sciences—ICFO (Spain), University of Milan-Bicocca, Modus Research and Innovation Ltd. (UK) and University of Florence (Italy), as well as industrial partners: Ampliconyx Oy (Finland), Femtonics Ltd. (Hungary), HC Photonics (Taiwan), and LEONI Fiber Optics GmbH (Germany).

Bladder cancer (BC) is the eleventh most diagnosed cancer worldwide. The age-standardized incidence rate (per 100 000 person/years) is 9.0 for men and 2.2 for women [1]. Urothelial carcinoma (UC) represents about 90% of all bladder tumors, thus carrying an enormous social and economic burden [2]. UCs are classified in different stages and grades, depending on their invasiveness and on their degree of cytological abnormalities. The key aspect for a positive prognosis is the early and accurate diagnosis of the lesion stage, in order to identify the most aggressive disease forms and treat them promptly. It is well known that tissue metabolism constitutes a basic mechanism, which is at the base of many pathologies, especially BC. Being able to detect and characterize tissue metabolism and molecular fingerprints at the cellular level could be a key aspect in characterizing the pathology and enabling both early detection and therapy monitoring. The new European Union Horizon 2020 project called AMPLITUDE, the ‘Advanced Multimodal Photonics Laser Imaging Tool for Urothelial Diagnosis in Endoscopy’, starting in January 2020, proposes the development of an advanced multi-modal imaging tool exploiting new laser technologies in an approach combining confocal and non-linear imaging to fulfil unmet clinical needs in terms of the specificity and accuracy of urothelial cancer diagnosis and therapy monitoring. The project is coordinated by Tampere University (Finland) and carried out in cooperation with leading European research organizations including Aston Insitute of Photonic Technologies—AIPT (UK), Consiglio Nazionale delle Ricerche—CNR (Italy), Institute of Photonic Sciences—ICFO (Spain), University of Milan-Bicocca, Modus Research and Innovation Ltd. (UK) and University of Florence (Italy), as well as industrial partners: Ampliconyx Oy (Finland), Femtonics Ltd. (Hungary), HC Photonics (Taiwan), and LEONI Fiber Optics GmbH (Germany).

Bladder cancer (BC) is the eleventh most diagnosed cancer worldwide. The age-standardized incidence rate (per 100 000 person/years) is 9.0 for men and 2.2 for women [1]. Urothelial carcinoma (UC) represents about 90% of all bladder tumors, thus carrying an enormous social and economic burden [2]. UCs are classified in different stages and grades, depending on their invasiveness and on their degree of cytological abnormalities. The key aspect for a positive prognosis is the early and accurate diagnosis of the lesion stage, in order to identify the most aggressive disease forms and treat them promptly. It is well known that tissue metabolism constitutes a basic mechanism, which is at the base of many pathologies, especially BC. Being able to detect and characterize tissue metabolism and molecular fingerprints at the cellular level could be a key aspect in characterizing the pathology and enabling both early detection and therapy monitoring. The new European Union Horizon 2020 project called AMPLITUDE, the ‘Advanced Multimodal Photonics Laser Imaging Tool for Urothelial Diagnosis in Endoscopy’, starting in January 2020, proposes the development of an advanced multi-modal imaging tool exploiting new laser technologies in an approach combining confocal and non-linear imaging to fulfil unmet clinical needs in terms of the specificity and accuracy of urothelial cancer diagnosis and therapy monitoring. The project is coordinated by Tampere University (Finland) and carried out in cooperation with leading European research organizations including Aston Insitute of Photonic Technologies—AIPT (UK), Consiglio Nazionale delle Ricerche—CNR (Italy), Institute of Photonic Sciences—ICFO (Spain), University of Milan-Bicocca, Modus Research and Innovation Ltd. (UK) and University of Florence (Italy), as well as industrial partners: Ampliconyx Oy (Finland), Femtonics Ltd. (Hungary), HC Photonics (Taiwan), and LEONI Fiber Optics GmbH (Germany).

Promising new developments include the introduction of near-infrared-shifted fluorescent molecules that can be used for in vivo labeling of deep tissue functional and molecular processes. Due to versatility and wide availability of optical molecular agents, functional and molecular imaging studies can be done using extrinsic contrast from, e.g. reporter genes or targeted biomarkers that can be genetically expressed or accumulated in a cell- or tissue-specific manner. Despite its great promise, similarly to ultrasonography, optoacoustic imaging possesses several limitations related to imaging through acoustically mismatched areas, such as lungs, skull, and bones. The initial goal of optoacoustic imaging and tomography is retrieval of the absorbed optical energy density inside the object. The highly heterogeneous nature of biological tissues may further lead to the appearance of significant image artifacts and compromise imaging performance and quantification. The true multi-scale imaging capabilities of optoacoustics can be better appreciated when comparing its dynamic imaging performance with other neuroimaging modalities.

The overall aim of this study was verification of the possibility to register the change of NADH fluorescence in live tissue by a portable diagnostical laser system with fibre optical probe output and excitation by compact semiconductor UV light source. The measurements were conducted in fresh brain tissue slices of Wistar rat pups. The fluorescence measurements were conducted simultaneously at intervals of 5 s by the microscopic system with excitation at 360 nm and registering of the emitted fluorescence light at 455 nm and by the tested diagnostical system equipped with the fibre optical probe with excitation at 365 nm and registration of the fluorescence spectrum by the inbuilt spectroscopic subsystem. To modulate the mitochondrial function in the living cells, in the chamber sequentially were added 1 μM FCCP and 1 mM NaCN. The comparisons between the curves registered by the methods allowed us to find well agreement between the microscopic measurements and measurements by the fibre optical probe. The obtained results prove that the tested diagnostic system is capable of sensing the changes in brain metabolic activity associated with the NADH content alterations within the physiological range.

The overall aim of this study was verification of the possibility to register the change of NADH fluorescence in live tissue by a portable diagnostical laser system with fibre optical probe output and excitation by compact semiconductor UV light source. The measurements were conducted in fresh brain tissue slices of Wistar rat pups. The fluorescence measurements were conducted simultaneously at intervals of 5 s by the microscopic system with excitation at 360 nm and registering of the emitted fluorescence light at 455 nm and by the tested diagnostical system equipped with the fibre optical probe with excitation at 365 nm and registration of the fluorescence spectrum by the inbuilt spectroscopic subsystem. To modulate the mitochondrial function in the living cells, in the chamber sequentially were added 1 μM FCCP and 1 mM NaCN. The comparisons between the curves registered by the methods allowed us to find well agreement between the microscopic measurements and measurements by the fibre optical probe. The obtained results prove that the tested diagnostic system is capable of sensing the changes in brain metabolic activity associated with the NADH content alterations within the physiological range.

This studiy was carried out on groups of clinically healthy male Wistar rats. Animals received distilled drinking water ad libitum for 1 month, water containing succinic acid, water containing zinc sulphate and succinate zinc. Using the method of fluorescence spectroscopy, the parameters of brain metabolism in vivo in a model of laboratory rats was investigated. Based on data obtained by fluorescence spectroscopy, we have registered a change in the degree of cellular respiration in different structures of the cerebral cortex with the toxic effect of zinc compounds and succinic acid on the oxygen exchange process.

Laser speckle contrast imaging (LSCI) is a simple and quite powerful method for visualization of flow, microcirculation and perfusion. In current study the speckle contrast variations towards breaking ergodicity conditions are considered with a final aim of envision a practical approach allowing real-time imaging of variations in dynamic properties of complex fluids with an opportunity of quantitative interpretation of the obtained flowing map. As example of systems with static to dynamic transition, melting of Intralipid samples were studied. Also, investigation of influence of static layer thickness above the dynamic sample on the ergodicity condition has been studied.

Laser Doppler flowmetry (LDF) is widely used to study blood microcirculation in the skin. However, during tradition signal processing based on the integral estimations of the power spectrum of detector photocurrent, the significant part of the information about the skin blood ow is lost. In this study, we propose to analyse the distribution of the blood perfusion over the Doppler shift frequencies, which correlate with the RBC velocity. This approach provides localisation of the blood ow oscillations in different subranges of the Doppler shift. The method applied together with the wavelet analysis has been tested in healthy volunteers and patients with psoriasis on the unaffected surface of the skin. It was revealed, that the significant difference in the amplitude of myogenic oscillations is allocated in the region of the low frequency Doppler shift (1-200 Hz). This frequency region can be associated with the signal from slow components of the skin microcirculation, that can point out on a different state of the lymphatic system of the skin in psoriasis.

Laser Doppler flowmetry (LDF) is widely used to study blood microcirculation in the skin. However, during tradition signal processing based on the integral estimations of the power spectrum of detector photocurrent, the significant part of the information about the skin blood ow is lost. In this study, we propose to analyse the distribution of the blood perfusion over the Doppler shift frequencies, which correlate with the RBC velocity. This approach provides localisation of the blood ow oscillations in different subranges of the Doppler shift. The method applied together with the wavelet analysis has been tested in healthy volunteers and patients with psoriasis on the unaffected surface of the skin. It was revealed, that the significant difference in the amplitude of myogenic oscillations is allocated in the region of the low frequency Doppler shift (1-200 Hz). This frequency region can be associated with the signal from slow components of the skin microcirculation, that can point out on a different state of the lymphatic system of the skin in psoriasis.

Laser speckle contrast imaging (LSCI) is a simple and quite powerful method for visualization of flow, microcirculation and perfusion. In current study the speckle contrast variations towards breaking ergodicity conditions are considered with a final aim of envision a practical approach allowing real-time imaging of variations in dynamic properties of complex fluids with an opportunity of quantitative interpretation of the obtained flowing map. As example of systems with static to dynamic transition, melting of Intralipid samples were studied. Also, investigation of influence of static layer thickness above the dynamic sample on the ergodicity condition has been studied.

This studiy was carried out on groups of clinically healthy male Wistar rats. Animals received distilled drinking water ad libitum for 1 month, water containing succinic acid, water containing zinc sulphate and succinate zinc. Using the method of fluorescence spectroscopy, the parameters of brain metabolism in vivo in a model of laboratory rats was investigated. Based on data obtained by fluorescence spectroscopy, we have registered a change in the degree of cellular respiration in different structures of the cerebral cortex with the toxic effect of zinc compounds and succinic acid on the oxygen exchange process.

Time traces obtained from a variety of biophysical experiments contain valuable information on underlying processes occurring at the molecular level. Accurate quantification of these data can help explain the details of the complex dynamics of biological systems. Here, we describe PLANT (Piecewise Linear Approximation of Noisy Trajectories), a segmentation algorithm that allows the reconstruction of time-trace data with constant noise as consecutive straight lines, from which changes of slopes and their respective durations can be extracted. We present a general description of the algorithm and perform extensive simulations to characterize its strengths and limitations, providing a rationale for the performance of the algorithm in the different conditions tested. We further apply the algorithm to experimental data obtained from tracking the centroid position of lymphocytes migrating under the effect of a laminar flow and from single myosin molecules interacting with actin in a dual-trap force-clamp configuration., The authors gratefully acknowledge financial support fromthe European Commission (FP7-ICT-2011-7, grant number 288263), Erasmus Mundus Doctorate Program Europhoton-ics (grant number 159224-1-2009-1-FR-ERA MUNDUS-EMJD), Spanish Ministry of Economy and Competi-tiveness (“Severo Ochoa” Programme for Centres of Excellence in Research & Development SEV-2015-0522,and FIS2014-56107-R grants), Generalitat de Catalunyathrough the CERCA program, Italian Ministry of Uni-versity and Research (FIRB “Futuro in Ricerca” 2013grant n. RBFR13V4M2 and Flagship Project NANOMAX),Fundaci ́o Privada CELLEX (Barcelona), Ente Cassa diRisparmio di Firenze, Human Frontier Science Program (GARGP0027/2012) and LaserLab Europe 4 (GA 654148). C.M.acknowledges funding from the Spanish Ministry of Econ-omy and Competitiveness (MINECO) and the EuropeanSocial Fund (ESF) through the Ram ́on y Cajal program 2015(RYC-2015-17896)., Peer Reviewed, Postprint (author's final draft)

This studiy was carried out on groups of clinically healthy male Wistar rats. Animals received distilled drinking water ad libitum for 1 month, water containing succinic acid, water containing zinc sulphate and succinate zinc. Using the method of fluorescence spectroscopy, the parameters of brain metabolism in vivo in a model of laboratory rats was investigated. Based on data obtained by fluorescence spectroscopy, we have registered a change in the degree of cellular respiration in different structures of the cerebral cortex with the toxic effect of zinc compounds and succinic acid on the oxygen exchange process.

Laser Doppler flowmetry (LDF) is widely used to study blood microcirculation in the skin. However, during tradition signal processing based on the integral estimations of the power spectrum of detector photocurrent, the significant part of the information about the skin blood ow is lost. In this study, we propose to analyse the distribution of the blood perfusion over the Doppler shift frequencies, which correlate with the RBC velocity. This approach provides localisation of the blood ow oscillations in different subranges of the Doppler shift. The method applied together with the wavelet analysis has been tested in healthy volunteers and patients with psoriasis on the unaffected surface of the skin. It was revealed, that the significant difference in the amplitude of myogenic oscillations is allocated in the region of the low frequency Doppler shift (1-200 Hz). This frequency region can be associated with the signal from slow components of the skin microcirculation, that can point out on a different state of the lymphatic system of the skin in psoriasis.

Laser speckle contrast imaging (LSCI) is a simple and quite powerful method for visualization of flow, microcirculation and perfusion. In current study the speckle contrast variations towards breaking ergodicity conditions are considered with a final aim of envision a practical approach allowing real-time imaging of variations in dynamic properties of complex fluids with an opportunity of quantitative interpretation of the obtained flowing map. As example of systems with static to dynamic transition, melting of Intralipid samples were studied. Also, investigation of influence of static layer thickness above the dynamic sample on the ergodicity condition has been studied.

Laser Doppler flowmetry (LDF) is widely used to study blood microcirculation in the skin. However, during tradition signal processing based on the integral estimations of the power spectrum of detector photocurrent, the significant part of the information about the skin blood ow is lost. In this study, we propose to analyse the distribution of the blood perfusion over the Doppler shift frequencies, which correlate with the RBC velocity. This approach provides localisation of the blood ow oscillations in different subranges of the Doppler shift. The method applied together with the wavelet analysis has been tested in healthy volunteers and patients with psoriasis on the unaffected surface of the skin. It was revealed, that the significant difference in the amplitude of myogenic oscillations is allocated in the region of the low frequency Doppler shift (1-200 Hz). This frequency region can be associated with the signal from slow components of the skin microcirculation, that can point out on a different state of the lymphatic system of the skin in psoriasis.

This studiy was carried out on groups of clinically healthy male Wistar rats. Animals received distilled drinking water ad libitum for 1 month, water containing succinic acid, water containing zinc sulphate and succinate zinc. Using the method of fluorescence spectroscopy, the parameters of brain metabolism in vivo in a model of laboratory rats was investigated. Based on data obtained by fluorescence spectroscopy, we have registered a change in the degree of cellular respiration in different structures of the cerebral cortex with the toxic effect of zinc compounds and succinic acid on the oxygen exchange process.

Cotutela Universitat Politècnica de Catalunya i Università degli Studi di Firenze, The migration of leukocytes from the blood stream to sites of injury and infection in the extravascular tissues is fundamental for the immune response. Two of the main receptors mediating this process are the integrins aLß2 and a4ß1, both expressed on the leukocyte cell membrane, which bind to their respective ligands ICAM-1 and VCAM-1, expressed on endothelial cell (EC) membrane. The dynamic and lateral organization of integrins on the cell membrane has been shown to be crucial in the regulation of cell adhesion. Likewise, organization of ligands in small domains (clusters) would probably reinforce the bonds formed with the integrins, thus increasing leukocyte adhesion. However, how the spatiotemporal behavior of integrins and their ligands is affected by the influence of external factors, such as mechanical and/or biochemical stimuli, has not been extensively studied. In addition, the impact of such spatiotemporal changes in the process of leukocyte adhesion and migration has not been addressed yet. The main aim of this thesis has been to address these questions using a combination of state-of-art biophysical tools, including advanced cell imaging, single molecule dynamic approaches, cell mechanical stimulation, and custom-designed algorithms for data quantification. From the technical side, our general approach involved the use of single particle tracking (SPT) approaches to monitor the dynamics of individual molecules implicated in the process of the cell adhesion, in combination with different super-resolution microscopy techniques, such as STED and STORM, to visualize changes in their nanoscale organization upon the influence of biochemical and/or mechanical stimuli. To mechanically stimulate cells we developed two different approaches; namely, a mechanical stretching device and a parallel-plate flow chamber (PPFC). We integrated these devices into our single molecule set-up and succeeded in recording the diffusion of integrins on cells plated on the mechanica, La migración de leucocitos desde el torrente sanguíneo a sitios de lesión e infección es fundamental en la respuesta inmune. Dos de los principales receptores que median este proceso son las integrinas aLß2 y a4ß1, que se expresan en la membrana celular de los leucocitos y se unen a sus respectivos ligandos ICAM-1 y VCAM-1, ambos localizados sobre la membrana de células endoteliales (CE). Se ha demostrado que la dinámica y la organización lateral de las integrinas sobre la membrana celular son cruciales en la regulación de la adhesión celular. Asimismo, es muy probable que la organización de los ligandos en pequeños dominios refuerce los enlaces formados con las integrinas, fortaleciendo así la adhesión celular. Sin embargo, cómo el comportamiento espacio-temporal de las integrinas y sus ligandos es afectado por factores externos, tales como estímulos mecánicos y/o bioquímicos, no ha sido ampliamente estudiado. Además, el impacto de estos cambios espacio-temporales en el proceso de adhesión y migración leucocitaria aún no ha sido abordado. El objetivo principal de esta tesis ha sido abordar estas interrogantes usando una combinación de herramientas biofísicas de última generación que incluyen avanzadas técnicas de visualización, dinámica de moléculas individuales, estimulación mecánica de células y desarrollo de algoritmos para la cuantificación de datos. Con este fin hemos utilizado métodos de seguimiento de partículas individuales para monitorizar la dinámica de moléculas individuales, en combinación con técnicas de microscopía de super-resolución, como STED y STORM, para visualizar cambios en su organización a nano-escala tras la estimulación bioquímica y/o mecánica. Para estimular las células mecánicamente hemos desarrollado dos métodos: un dispositivo de estiramiento y una cámara de flujo de placa paralela. Ambos dispositivos fueron integrados a nuestro montaje experimental de detección de moléculas individuales y el primero fue exitosamente utilizado en la car, Postprint (published version)

Mechanistic understanding of how the brain gives rise to complex behavioral and cognitive functions is one of science's grand challenges. The technical challenges that we face as we attempt to gain a systems-level understanding of the brain are manifold. The brain's structural complexity requires us to push the limit of imaging resolution and depth, while being able to cover large areas, resulting in enormous data acquisition and processing needs. Furthermore, it is necessary to detect functional activities and 'map' them onto the structural features. The functional activity occurs at multiple levels, using electrical and chemical signals. Certain electrical signals are only decipherable with sub-millisecond timescale resolution, while other modes of signals occur in minutes to hours. For these reasons, there is a wide consensus that new tools are necessary to undertake this daunting task. Optical techniques, due to their versatile and scalable nature, have great potentials to answer these challenges. Optical microscopy can now image beyond the diffraction limit, record multiple types of brain activity, and trace structural features across large areas of tissue. Genetically encoded molecular tools opened doors to controlling and detecting neural activity using light in specific cell types within the intact brain. Novel sample preparation methods that reduce light scattering have been developed, allowing whole brain imaging in rodent models. Adaptive optical methods have the potential to resolve images from deep brain regions. In this roadmap article, we showcase a few major advances in this area, survey the current challenges, and identify potential future needs that may be used as a guideline for the next steps to be taken.

A tilted fiber Bragg grating (TFBG) was integrated as the dispersive element in a high performance biomedical imaging system. The spectrum emitted by the 23 mm long active region of the fiber is projected through custom designed optics consisting of a cylindrical lens for vertical beam collimation and successively by an achromatic doublet onto a linear detector array. High resolution tomograms of biomedical samples were successfully acquired by the frequency domain OCT-system. Tomograms of ophthalmic and dermal samples obtained by the frequency domain OCT-system were obtained achieving 2.84 μm axial and 10.2 μm lateral resolution. The miniaturization reduces costs and has the potential to further extend the field of application for OCT-systems in biology, medicine and technology.

A tilted fiber Bragg grating (TFBG) was integrated as the dispersive element in a high performance biomedical imaging system. The spectrum emitted by the 23 mm long active region of the fiber is projected through custom designed optics consisting of a cylindrical lens for vertical beam collimation and successively by an achromatic doublet onto a linear detector array. High resolution tomograms of biomedical samples were successfully acquired by the frequency domain OCT-system. Tomograms of ophthalmic and dermal samples obtained by the frequency domain OCT-system were obtained achieving 2.84 μm axial and 10.2 μm lateral resolution. The miniaturization reduces costs and has the potential to further extend the field of application for OCT-systems in biology, medicine and technology.