Heat stress (HS) is a medical emergency defined by abnormally elevated body temperature that causes biochemical, physiological, and hematological changes. The goal of the present research was to detect variations in optical properties (absorption, reduced scattering, and refractive index coefficients) of mouse brain tissue during HS by using near-infrared (NIR) spatial light modulation. NIR spatial patterns with different spatial phases were used to differentiate the effects of tissue scattering from those of absorption. Decoupling optical scattering from absorption enabled the quantification of a tissue's chemical constituents (related to light absorption) and structural properties (related to light scattering). Technically, structured light patterns at low and high spatial frequencies of six wavelengths ranging between 690 and 970 nm were projected onto the mouse scalp surface while diffuse reflected light was recorded by a CCD camera positioned perpendicular to the mouse scalp. Concurrently to pattern projection, brain temperature was measured with a thermal camera positioned slightly off angle from the mouse head while core body temperature was monitored by thermocouple probe. Data analysis demonstrated variations from baseline measurements in a battery of intrinsic brain properties following HS.

Simian virus 40 (SV40) is a small (~45nm), non-enveloped, DNA virus with an icosahedral capsid. Viral DNA associates with histones in the nucleus of infected cells to form a chromatinized, supercoiled, circular minichromosome. The SV40 capsid proteins assemble around this minichromosome to form new virions. The capsid contains 72 pentamers of VP1 protein arrayed on a T=7d icosahedral lattice. Single molecules of VP2/3 protein are associated with the inner surface of all or most VP1 pentamers, potentially linking to the viral chromatin. The icosahedral symmetry of the capsid has allowed its structure to be determined at high resolution by particle averaging and crystallographic methods [1]. However, the organization of the viral chromatin -which is not expected to conform to this symmetry -has not been determined.To study the chromatin structure of individual SV40 particles, we collected single-axis tilt series of plunge-frozen virus particles across an angular range of -70 to +70 degrees on a 120kV Tecnai T12 TEM equipped with an energy filter operating in zero-loss mode. Images were recorded at 2° increments at a dose of 1 e -/Å 2 per image. Three-dimensional reconstructions of these tilt series were computed using IMOD [2]. Reconstructions were denoised by nonlinear anisotropic diffusion filtering. The average in-plane resolution of the reconstructions was calculated by the NLOO method to be 5 nm [3], sufficient to observe nucleosome structures.Individual virions were extracted from tomograms for further analysis. Punctate densities, consistent in size and appearance with nucleosomes, are visible inside the capsids (Fig. 1A). The most prominent viral component was the capsid shell, whose T=7d icosahedral symmetry was clearly visible in individual subtomograms (Fig. 1B) and was further enhanced by particle averaging (Fig. 1C). As expected, averaging revealed no symmetrically distributed internal densities; rather, it produced a low uniform level of internal density. These findings are consistent with earlier data suggesting that viral chromatin is not icosahedrally ordered [4]. Quantifying the nucleosome densities present in individual particles revealed them to be variable in number, with an average of 19 +/-2.5 per particle (Fig. 2). The tomograms also suggest the presence of contacts between some internal chromatin densities and the capsid shell. Ongoing efforts are focused on better defining these putative capsid-chromatin links, as well as the organization of encapsidated minichromasomes.

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Spectral data enabling the derivation of a biological tissue sample's complex refractive index (CRI) can provide a range of valuable information in the clinical and research contexts. Specifically, changes in the CRI reflect alterations in tissue morphology and chemical composition, enabling its use as an optical marker during diagnosis and treatment. In the present work, we report a method for estimating the real and imaginary parts of the CRI of a biological sample using Kramers-Kronig (KK) relations in the spatial frequency domain. In this method, phase-shifted sinusoidal patterns at single high spatial frequency are serially projected onto the sample surface at different near-infrared wavelengths while a camera mounted normal to the sample surface acquires the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial phase maps using KK analysis and are then calibrated against phase-models derived from diffusion approximation. The amplitude of the reflected light, together with phase data, is then introduced into Fresnel equations to resolve both real and imaginary segments of the CRI at each wavelength. The technique was validated in tissue-mimicking phantoms with known optical parameters and in mouse models of ischemic injury and heat stress. Experimental data obtained indicate variations in the CRI among brain tissue suffering from injury. CRI fluctuations correlated with alterations in the scattering and absorption coefficients of the injured tissue are demonstrated. This technique for deriving dynamic changes in the CRI of tissue may be further developed as a clinical diagnostic tool and for biomedical research applications. To the best of our knowledge, this is the first report of the estimation of the spectral CRI of a mouse head following injury obtained in the spatial frequency domain.

A practical algorithm for estimating the wavelength-dependent refractive index (RI) of a turbid sample in the spatial frequency domain with the aid of Kramers-Kronig (KK) relations is presented. In it, phase-shifted sinusoidal patterns (structured illumination) are serially projected at a high spatial frequency onto the sample surface (mouse scalp) at different near-infrared wavelengths while a camera mounted normally to the sample surface captures the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial absorption maps by logarithmic function, and once the absorption coefficient information is obtained, the imaginary part (k) of the complex RI (CRI), based on Maxell's equations, can be calculated. Using the data represented by k, the real part of the CRI (n) is then resolved by KK analysis. The wavelength dependence of n  (  λ  )   is then fitted separately using four standard dispersion models: Cornu, Cauchy, Conrady, and Sellmeier. In addition, three-dimensional surface-profile distribution of n is provided based on phase profilometry principles and a phase-unwrapping-based phase-derivative-variance algorithm. Experimental results demonstrate the capability of the proposed idea for sample's determination of a biological sample's RI value.