Experimentally unsupervised deconvolution for light-sheet microscopy with propagation-invariant beams.

Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep-learning method for deconvolution that, in lieu of end-to-end training with ground truths, is trained using known physics of the imaging system. Specifically, we train a generative adversarial network with images generated with the known point-spread function of the system, and combine this with unpaired experimental data that preserve perceptual content. Our method rapidly and robustly deconvolves and super-resolves microscopy images, demonstrating a two-fold improvement in image contrast to conventional deconvolution methods. In contrast to common end-to-end networks that often require 1000-10,000s paired images, our method is experimentally unsupervised and can be trained solely on a few hundred regions of interest. We demonstrate its performance on light-sheet microscopy with propagation-invariant Airy beams in oocytes, preimplantation embryos and excised brain tissue, as well as illustrate its utility for Bessel-beam LSM. This method aims to democratise learned methods for deconvolution, as it does not require data acquisition outwith the conventional imaging protocol.

Optical manipulation: advances for biophotonics in the 21st century.

SIGNIFICANCE: Optical trapping is a technique capable of applying minute forces that has been applied to studies spanning single molecules up to microorganisms. AIM: The goal of this perspective is to highlight some of the main advances in the last decade in this field that are pertinent for a biomedical audience. APPROACH: First, the direct determination of forces in optical tweezers and the combination of optical and acoustic traps, which allows studies across different length scales, are discussed. Then, a review of the progress made in the direct trapping of both single-molecules, and even single-viruses, and single cells with optical forces is outlined. Lastly, future directions for this methodology in biophotonics are discussed. RESULTS: In the 21st century, optical manipulation has expanded its unique capabilities, enabling not only a more detailed study of single molecules and single cells but also of more complex living systems, giving us further insights into important biological activities. CONCLUSIONS: Optical forces have played a large role in the biomedical landscape leading to exceptional new biological breakthroughs. The continuous advances in the world of optical trapping will certainly lead to further exploitation, including exciting in-vivo experiments.

Optical sensory arrays for the detection of urinary bladder cancer-related volatile organic compounds.

Non-invasive detection of urinary bladder cancer remains a significant challenge. Urinary volatile organic compounds (VOCs) are a promising alternative to cell-based biomarkers. Herein, we demonstrate a novel diagnosis system based on an optic fluorescence sensor array for detecting urinary bladder cancer VOCs biomarkers. This study describes a fluorescence-based VOCs sensor array detecting system in detail. The choice of VOCs for the initial part was based on an extensive systematic search of the literature and then followed up using urinary samples from patients with urinary bladder transitional cell carcinoma. Canonical discriminant analysis and partial least squares discriminant analysis (PLS-DA) were employed and correctly detected 31/48 urinary bladder cancer VOC biomarkers and achieved an overall 77.75% sensitivity and 93.25% specificity by PLS-DA modelling. All five urine samples from bladder cancer patients, and five healthy controls were successfully identified with the same sensor arrays. Overall, the experiments in this study describe a real-time platform for non-invasive bladder cancer diagnosis using fluorescence-based gas-sensor arrays. Pure VOCs and urine samples from the patients proved such a system to be promising; however, further research is required using a larger population sample.

Light sheet fluorescence microscopy for neuroscience.

BACKGROUND: The functions of the central nervous system (CNS) rely on the interaction between large populations of neurons across different areas. Therefore, to comprehend CNS functions there is a need for imaging techniques providing access to the neuronal activity of large networks of neurons with very high spatiotemporal resolution. NEW METHOD: Light sheet fluorescence microscopy (LSFM) is a very promising optical sectioning technique that allows volumetric imaging over many length scales while retaining high spatial resolution and minimizing photobleaching and phototoxicity. RESULTS: The application of LSFM in neuroscience opened up the possibility of imaging in-vivo the development of the CNS and acquiring morphological images of whole cleared mammalian brains with sub-cellular resolution. The use of propagation invariant Bessel and Airy beams has shown potential for increasing the penetration depth in turbid neural tissues. COMPARISON WITH EXISTING METHODS: The lack of temporal and/or spatial resolution of traditional neuroscience imaging techniques call attention to a need for a technique capable of providing high spatio temporal resolution. LSFM, which is capable of acquiring high resolution volumetric images is increasingly becoming an interesting imaging technique for neuroscience. CONCLUSIONS: The use of different LSFM geometries has shown the potential of this technique in acquiring in-vivo functional images of the CNS and morphological images of entire cleared mammalian brains. Further development of single objective LSFM implementations and fibre based LSFM combined with the use of propagation invariant beams could allow this technique to be used for in depth in-vivo imaging.

Raman spectroscopy for accurately characterizing biomolecular changes in androgen-independent prostate cancer cells.

Metastatic prostate cancer resistant to hormonal manipulation is considered the advanced stage of the disease and leads to most cancer-related mortality. With new research focusing on modulating cancer growth, it is essential to understand the biochemical changes in cells that can then be exploited for drug discovery and for improving responsiveness to treatment. Raman spectroscopy has a high chemical specificity and can be used to detect and quantify molecular changes at the cellular level. Collection of large data sets generated from biological samples can be employed to form discriminatory algorithms for detection of subtle and early changes in cancer cells. The present study describes Raman finger printing of normal and metastatic hormone-resistant prostate cancer cells including analyses with principal component analysis and linear discrimination. Amino acid-specific signals were identified, especially loss of arginine band. Androgen-resistant prostate cancer cells presented a higher content of phenylalanine, tyrosine, DNA and Amide III in comparison to PNT2 cells, which possessed greater amounts of L-arginine and had a B conformation of DNA. The analysis utilized in this study could reliably differentiate the 2 cell lines (sensitivity 95%; specificity 88%).

Single nanoparticles magnetization curves by controlled tip magnetization magnetic force microscopy.

The development of high spatial resolution and element sensitive magnetic characterization techniques to quantitatively measure magnetic parameters of individual nanoparticles (NPs) and deeply understand and tune their magnetic properties is a hot topic in nanomagnetism. Magnetic force microscopy (MFM), thanks to its high lateral resolution, appears as a promising technique for the magnetic characterization of single nano-sized materials although it is still limited by some drawbacks, especially by the presence of electrostatic artifacts. Recently, these limitations have been overcome by the development of a particular MFM based technique called controlled magnetization - MFM (CM-MFM) allowing, in principle, a quantifiable correlation between the measured magnetic signal and the magnetization of the object under investigation. Here we propose an experimental procedure, based on the use of CM-MFM technique, to measure the magnetization curve of single magnetic NPs individuating their saturation magnetization, magnetic field, and coercivity. We measured, for the first time, the magnetization curves of individual Fe3O4 nanoparticles with diameters in the range of 18-32 nm by using a MFM instrument. Results are in very good agreement with the quantitative data obtained by SQUID analysis on a macroscopic sample, showing the high potential of the technique in the field of nanomagnetometry.

Intermediate phases during solid to liquid transitions in long-chain n-alkanes.

The solid to liquid phase transition of n-alkanes with more than ten carbon atoms is an interesting phenomenon relevant to many fields, from cosmetics to automotive. Here we report Raman spectroscopy of tetradecane, pentadecane and hexadecane as a function of temperature. In order to gain information on the structural changes that the hydrocarbons undergo during melting, and to determine the temperature and the speed at which the phase change occurs, their temperature-dependent Raman spectra are acquired. The spectra are analysed not only with respect to frequency shifts, band widths, and intensity ratio of certain bands, but also using a principal component analysis. The spectroscopic data suggest that the solid to liquid phase transition in hexadecane, differently from tetradecane and pentadecane, is almost instantaneous. Tetradecane shows a slightly faster transition than pentadecane. In addition, a rotator phase as an intermediate state between the liquid and crystalline solid phases is identified in pentadecane. Different characteristic features in the solid spectra of the hydrocarbons relate tetradecane and hexadecane to a tryclinic crystalline structure, and pentadecane to an orthorhombic structure.

Probing the Evaporation Dynamics of Ethanol/Gasoline Biofuel Blends Using Single Droplet Manipulation Techniques.

Using blends of bioethanol and gasoline as automotive fuel leads to a net decrease in the production of harmful emission compared to the use of pure fossil fuel. However, fuel droplet evaporation dynamics change depending on the mixing ratio. Here we use single particle manipulation techniques to study the evaporation dynamics of ethanol/gasoline blend microdroplets. The use of an electrodynamic balance enables measurements of the evaporation of individual droplets in a controlled environment, while optical tweezers facilitate studies of the behavior of droplets inside a spray. Hence, the combination of both methods is perfectly suited to obtain a complete picture of the evaporation process. The influence of adding varied amounts of ethanol to gasoline is investigated, and we observe that droplets with a greater fraction of ethanol take longer to evaporate. Furthermore, we find that our methods are sensitive enough to observe the presence of trace amounts of water in the droplets. A theoretical model, predicting the evaporation of ethanol and gasoline droplets in dry nitrogen gas, is used to explain the experimental results. Also a theoretical estimation of the saturation of the environment, with other aerosols, in the tweezers is carried out.