Label-free concurrent 5-modal microscopy (Co5M) resolves unknown spatio-temporal processes in wound healing

Non-invasive assessment of hair regeneration in androgenetic alopecia mice in vivo using two-photon and second harmonic generation imaging

The identification of crucial targets for hair regrowth in androgenetic alopecia (AGA) involves determining important characteristics and different stages during the process of hair follicle regeneration. Traditional methods for assessing key features and different stages of hair follicle primarily involve taking skin tissue samples and determining them through various staining or other methods. However, non-invasive assessment methods have been long sought. Therefore, in this study, endogenous fluorescence signals from skin keratin and second harmonic signals from skin collagen fibers were utilized as probes, two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) imaging techniques were employed to non-invasively assess hair shafts and collagen fibers in AGA mice in vivo. The TPEF imaging technique revealed that the alternation of new and old hair shafts and the different stages of the growth period in AGA mice were delayed. In addition, SHG imaging found testosterone reduced hair follicle area and miniaturized hair follicles. The non-invasive TPEF and SHG imaging techniques provided important methodologies for determining significant characteristics and different stages of the growth cycle in AGA mice, which will facilitate future non-invasive assessments on human scalps in vivo and reduce the use of animal testing.

Spiking neural networks for predictive and explainable modelling of multimodal streaming data with a case study on financial time series and online news

In a first study, this paper argues and demonstrates that spiking neural networks (SNN) can be successfully used for predictive and explainable modelling of multimodal streaming data. The paper proposes a new method, where both time series and on-line news are integrated as numerical streaming data in the same time domain and then used to train incrementally a SNN model. The connectivity and the spiking activity of the SNN are then analyzed through clustering and dynamic graph extraction to reveal on-line interaction between all input variables in regard to the predicted one. The paper answers the main research question of how to understand the dynamic interaction of time series and on-line news through their integrative modelling. It offers a new method to evaluate the efficiency of using on-line news on the predictive modelling of time series. Results on financial stock time series and online news are presented. In contrast to traditional machine learning techniques, the method reveals the dynamic interaction between stock variables and news and their dynamic impact on model accuracy when compared to models that do not use news information. Along with the used financial data, the method is applicable to a wide range of other multimodal time series and news data, such as economic, medical, environmental and social. The proposed method, being based on SNN, promotes the use of massively parallel and low energy neuromorphic hardware for multivariate on-line data modelling.

High-speed optical resolution photoacoustic microscopy with MEMS scanner using a novel and simple distortion correction method

Optical resolution photoacoustic microscopy (OR-PAM) is a remarkable biomedical imaging technique that can selectively visualize microtissues with optical-dependent high resolution. However, traditional OR-PAM using mechanical stages provides slow imaging speed, making it difficult to biologically interpret in vivo tissue. In this study, we developed a high-speed OR-PAM using a recently commercialized MEMS mirror. This system (MEMS-OR-PAM) consists of a 1-axis MEMS mirror and a mechanical stage. Furthermore, this study proposes a novel calibration method that quickly removes the spatial distortion caused by fast MEMS scanning. The proposed calibration method can easily correct distortions caused by both the scan geometry of the MEMS mirror and its nonlinear motion by running an image sequence only once using a ruler target. The combination of MEMS-OR-PAM and distortion correction method was verified using three experiments: (1) leaf skeleton phantom imaging to test the distortion correction efficacy; (2) spatial resolution and depth of field (DOF) measurement for system performance; (3) in-vivo finger capillary imaging to verify their biomedical use. The results showed that the combination could achieve a high-speed (32 s in 2 × 4 mm) and high lateral resolution (~ 6 µm) imaging capability and precisely visualize the circulating structure of the finger capillaries.

Correlative imaging of the spatio-angular dynamics of biological systems with multimodal instant polarization microscope

The spatial and angular organization of biological macromolecules is a key determinant, as well as informative readout, of their function. Correlative imaging of the dynamic spatio-angular architecture of cells and organelles is valuable, but remains challenging with current methods. Correlative imaging of spatio-angular dynamics requires fast polarization-, depth-, and wavelength-diverse measurement of intrinsic optical properties and fluorescent labels. We report a multimodal instant polarization microscope (miPolScope) that combines a broadband polarization-resolved detector, automation, and reconstruction algorithms to enable label-free imaging of phase, retardance, and orientation, multiplexed with fluorescence imaging of concentration, anisotropy, and orientation of molecules at diffraction-limited resolution and high speed. miPolScope enabled multimodal imaging of myofibril architecture and contractile activity of beating cardiomyocytes, cell and organelle architecture of live HEK293T and U2OS cells, and density and anisotropy of white and grey matter of mouse brain tissue across the visible spectrum. We anticipate these developments in joint quantitative imaging of density and anisotropy to enable new studies in tissue pathology, mechanobiology, and imaging-based screens.

Nanosecond SRS fiber amplifier for label-free near-infrared photoacoustic microscopy of lipids

Near-infrared photoacoustics receives increasing interest as an intravital modality to sense key biomolecules. One of the most central types of biomolecules of interest are lipids as they constitute essential bio-hallmarks of cardiovascular and metabolic diseases and their in-vivo detection holds insightful information about disease progression and treatment monitoring. However, the full potential of near-infrared photoacoustic for high-resolution and high-sensitivity biomedical studies of lipids has so far not been exploited due a lack of appropriate excitation sources delivering short-pulses at high-repetition-rate, high-pulse-energy, and wavelength around 1200 nm. Here, we demonstrate a custom-built SRS fiber amplifier that provides optical excitations at 1192.8 nm, repetition rates of 200 kHz, pulse durations below 2 ns, and pulse energies beyond 5 μJ. We capitalize on the performance of our excitation source and show near-infrared photoacoustics resolving intrinsic lipid contrast in biomedically relevant specimens ranging from single cells to lipid-rich tissue with subcellular resolution.