Diffusion Mapping with Diffractive Optical Elements for Periodically Patterned Photobleaching.

Fourier transform-fluorescence recovery after photobleaching (FT-FRAP) using a diffractive optical element (DOE) is shown to support distance-dependent diffusion analysis in biologically relevant media. Integration of DOEs enables patterning of a dot array for parallel acquisition of point-bleach FRAP measurements at multiple locations across the field of view. In homogeneous media, the spatial harmonics of the dot array analyzed in the spatial Fourier transform domain yield diffusion recovery curves evaluated over specific well-defined distances. Relative distances for diffusive recovery in the spatial Fourier transform domain are directly connected to the 2D (h,k) Miller indices of the corresponding lattice lines. The distribution of the photobleach power across the entire field of view using a multidot array pattern greatly increases the overall signal power in the spatial FT-domain for signal-to-noise improvements. Derivations are presented for the mathematical underpinnings of FT-FRAP performed with 2D periodicity in the photobleach patterns. Retrofitting of FT-FRAP into instrumentation for high-throughput FRAP analysis (Formulatrix) supports automated analysis of robotically prepared 96-well plates for precise quantification of molecular mobility. Figures of merit are evaluated for FT-FRAP in analysis for both slow diffusion of fluorescent dyes in glassy polymer matrices spanning several days and model proteins and monoclonal antibodies within aqueous solutions recovering in matters of seconds.

Spectral classification by generative adversarial linear discriminant analysis.

Generative adversarial linear discriminant analysis (GALDA) is formulated as a broadly applicable tool for increasing classification accuracy and reducing overfitting in spectrochemical analysis. Although inspired by the successes of generative adversarial neural networks (GANs) for minimizing overfitting artifacts in artificial neural networks, GALDA was built around an independent linear algebra framework distinct from those in GANs. In contrast to feature extraction and data reduction approaches for minimizing overfitting, GALDA performs data augmentation by identifying and adversarially excluding the regions in spectral space in which genuine data do not reside. Relative to non-adversarial analogs, loading plots for dimension reduction showed significant smoothing and more prominent features aligned with spectral peaks following generative adversarial optimization. Classification accuracy was evaluated for GALDA together with other commonly available supervised and unsupervised methods for dimension reduction in simulated spectra generated using an open-source Raman database (Romanian Database of Raman Spectroscopy, RDRS). Spectral analysis was then performed for microscopy measurements of microsphereroids of the blood thinner clopidogrel bisulfate and in THz Raman imaging of common constituents in aspirin tablets. From these collective results, the potential scope of use for GALDA is critically evaluated relative to alternative established spectral dimension reduction and classification methods.

Periodic Photobleaching with Structured Illumination for Diffusion Imaging.

The use of periodically structured illumination coupled with spatial Fourier-transform fluorescence recovery after photobleaching (FT-FRAP) was shown to support diffusivity mapping within segmented domains of arbitrary shape. Periodic "comb-bleach" patterning of the excitation beam during photobleaching encoded spatial maps of diffusion onto harmonic peaks in the spatial Fourier transform. Diffusion manifests as a simple exponential decay of a given harmonic, improving the signal to noise ratio and simplifying mathematical analysis. Image segmentation prior to Fourier transformation was shown to support pooling for signal to noise enhancement for regions of arbitrary shape expected to exhibit similar diffusivity within a domain. Following proof-of-concept analyses based on simulations with known ground-truth maps, diffusion imaging by FT-FRAP was used to map spatially-resolved diffusion differences within phase-separated domains of model amorphous solid dispersion spin-cast thin films. Notably, multi-harmonic analysis by FT-FRAP was able to definitively discriminate and quantify the roles of internal diffusion and exchange to higher mobility interfacial layers in modeling the recovery kinetics within thin amorphous/amorphous phase-separated domains, with interfacial diffusion playing a critical role in recovery. These results have direct implications for the design of amorphous systems for stable storage and efficacious delivery of therapeutic molecules.

Stochastic Differential Scanning Calorimetry by Nonlinear Optical Microscopy.

Stochastic phase transformations within individual crystalline particles were recorded by integration of second harmonic generation (SHG) imaging with differential scanning calorimetry (DSC). The SHG activity of a crystal is highly sensitive to the specific molecular packing arrangement within a noncentrosymmetric lattice, providing access to information otherwise unavailable by conventional imaging approaches. Consequently, lattice transformations associated with dehydration/desolvation events were readily observed by SHG imaging and directly correlated to the phase transformations detected by the DSC measurements. Following studies of a model system (urea), stochastic differential scanning calorimetry (SDSC) was performed on trehalose dihydrate, which has a more complex phase behavior. From these measurements, SDSC revealed a broad diversity of single-particle thermal trajectories and direct evidence of a "cold phase transformation" process not observable by the DSC measurements alone.