Function-specific homeostasis (FSH) has been defined as a negative-feedback response of a biosystem to maintain its interior function-specific conditions so that the function is perfectly performed. There is no photobiomodulation of intranasal low intensity laser therapy (ILILT) on a function in its FSH, but ILILT could modulate a function far from its FSH. This rehabilitation has been found to be mediated by the ratio of intracellular nicotinamide adenine dinucleotide (NAD+) and its reduced form NADH, NAD+/NADH, and then sirtuin 1 (SIRT1). There might be FSH-specific NAD+/NADH (FSN) and SIRT1 activity (FSA). ILILT might enhance NAD+/NADH and SIRT1 activity until they arrive at FSN and FSA, respectively. The NAD+/NADH and SIRT1 activity of related cells of many athletic diseases such as upper respiratory tract infection, asthma, osteoarthritis, exercise-induced muscle damage, wound, traumatic brain injury, and osteoporosis are lower than FSN and FSA, respectively. Therefore, there may be therapeutic effects of ILILT on those athletic diseases. Furthermore, many phenomena and the ILILT mechanism have been integrated to support the prophylaxis effects of ILILT on the swine-origin influenza A (H1N1).

Spectral domain optical coherence tomography (SDOCT) is a noninvasive, cross-sectional imaging technique that measures depth resolved reflectance of tissue by Fourier transforming the spectral interferogram with the scanning of the reference avoided. Interferometric synthetic aperture microscopy (ISAM) is an optical microscopy computed-imaging technique for measuring the optical properties of biological tissues, which can overcome the compromise between depth of focus and transverse resolution. This paper describes the principle of SDOCT and ISAM, which multiplexes raw acquisitions to provide quantitatively meaningful data with reliable spatially invariant resolution at all depths. A mathematical model for a coherent microscope with a planar scanning geometry and spectral detection was described. The two-dimensional fast Fourier transform (FFT) of spectral data in the transverse directions was calculated. Then the nonuniform ISAM resampling and filtering was implemented to yield the scattering potential within the scalar model. Inverse FFT was used to obtain the ISAM reconstruction. One scatterer, multiple scatterers, and noisy simulations were implemented by use of ISAM to catch spatially invariant resolution. ISAM images were compared to those obtained using standard optical coherence tomography (OCT) methods. The high quality of the results validates the rationality of the founded model and that diffraction limited resolution can be achieved outside the focal plane.

Cancer (malignant tumor) is one of the serious threats to human life, causing 13% of all human deaths. A crucial step in the metastasis cascade of cancer is hematogenous spreading of tumor cells from a primary tumor. Thus, isolation and identification of cells that have detached from the primary tumor and circulating in the bloodstream (circulating tumor cells, CTCs) is considered to be a potential alternation to detect, characterize, and monitor cancer. Current methods for isolating CTCs are limited to complex analytic approaches that generate very low yield and purity. Here, we propose a high throughput 3D structured microfluidic chip integrated with surface plasmon resonance (SPR) sensor to isolate and identify CTCs from peripheral whole blood sample. The microfluidic velocity-field within the channel of the chip is mediated by an array of microposts protruding from upper surface of the channel. The height of microposts is shorter than that of the channel, forming a gap between the microposts and the lower surface of the channel. The lower surface of the channel also acts as the SPR sensor which can be used to identify isolated CTCs. Microfluidic velocity-field under different parameters of the arrayed microposts is studied through numerical simulation based on finite element method. Measurement on one of such fabricated microchips is conducted by our established optical Doppler tomography technique benefiting from its noninvasive, noncontact, and high-resolution spatialresolved capabilities. Both simulation and measurement of the microfluidic velocity-field within the structured channel demonstrates that it is feasible to introduce fluidic mixing and causes perpendicular flow component to the lower surface of the channel by the 3D structured microposts. Such mixing and approaching capabilities are especially desirable for isolation and identification of CTCs at the coated SPR sensor.

PUMA (p53 up-regulated modulator of apoptosis, also called Bbc3) was first identified as a BH3-only Bcl-2 family protein that is transcriptionally up-regulated by p53 and activated upon p53-dependent apoptotic stimuli, such as treatment with DNA-damaging drugs or UV irradiation. Recently, studies have shown that PUMA is also up-regulated in response to certain p53-independent apoptotic stimuli, such as growth factor deprivation or treatment with glucocorticoids or STS (staurosporine). However, the molecular mechanisms of PUMA up-regulation and how PUMA functions in response to p53-independent apoptotic stimuli remain poorly understood. In this study, based on real-time single cell analysis, flow cytometry, and western blotting technique, we investigated the function of PUMA in living human lung adenocarcinoma cells (ASTC-a-1) after STS treatment. Our results show that FOXO3a was activated by STS stimulation and then translocated from cytosol to nucleus. The expression of PUMA was up-regulated via a FOXO3a-dependent manner after STS treatment, while p53 had little function in this process. Moreover, cell apoptosis and Bax activation induced by STS were not blocked by Pifithrin- α (p53 inhibitor), which indicated that p53 was not involved in this signaling pathway. Taken together, these results suggest that PUMA promoted Bax activation in a FOXO3a-dependent pathway during STS-induced apoptosis, while p53 was dispensable in this process.

Three-dimensional image reconstruction with Feldkamp, Davis, and Kress (FDK) algorithm is the most time consuming part in Micro-CT. The parallel algorithm based on the computer cluster is capable of accelerating image reconstruction speed; however, the hardware is very expensive. In this paper, using the most current graphics processing units (GPU), we present a method based on common unified device architecture (CUDA) for speeding up the Micro-CT image reconstruction process. The most time consuming filtering and back-projection parts of the FDK algorithm are parallelized for the CUDA architecture. The CUDA-based reconstruction speed and image qualities are compared with CPU results for the projecting data of the Micro-CT system. The results show that the 3D image reconstruction speed based on CUDA is ten times faster than the speed with CPU. In conclusion the FDK algorithm based on CUDA for Micro-CT can reconstruct the 3D image right after the end of data acquisition.

Limitations of cancer margin delineation and surgical guidance by means of autofluorescence imaging under conditions of laser ablation were investigated and preliminary results are presented. PinPointTM (Novadaq Technologies Inc., Canada) was used to capture digital images and Er:YAG laser (2.94μm, Glissando, WaveLightTM, Germany) was exploited to cause laser ablation on both normal and cancer sites of the specimen. It was shown that changes of the autofluorescence image after ablation extend beyond the actual sizes of the ablation loci. The tumor tissue after the laser ablation starts to emit fluorescent light within the green wavelength band (490–550nm) similar to normal tissue stating that the current technology of in-process tissue classification fails. However, when the autofluorescence was collected in the red range (600–750nm), then the abnormal/normal contrast was reduced, but still present even after the laser ablation. The present study highlights the importance of finding a proper technology for surgical navigation of cancer removal under conditions of high power effects in biological tissues.

This paper proposes a method for predicting the reduced scattering coefficients of tissuesimulating phantoms or the desired amount of scatters for producing phantoms according to Mie scattering theory without measurements with other instruments. The concentration of the scatters TiO₂ particles is determined according to Mie theory calculation and added to transparent host epoxy resin to produce phantoms with different reduced scattering coefficients. Black India Ink is added to alter the absorption coefficients of the phantoms. The reduced scattering coefficients of phantoms are measured with single integrating sphere system. The results show that the measurements are in direct proportion to the concentration of TiO₂ and have identical with Mie theory calculation at multiple wavelengths. The method proposed can accurately determine the concentration of scatters in the phantoms to ensure the phantoms are qualified with desired reduced scattering coefficients at specified wavelength. This investigation should be possible to manufacture the phantom simply in reasonably accurate for evaluation of biomedical optical imaging systems.

In this paper, a model-based reconstruction technique is proposed to simultaneously measure the relative deoxyhemoglobin concentration and the relative blood flow velocity in cerebral cortex. With the help of this model-based reconstruction technique, artifacts due to nonuniform laser illumination and curvature of cortex are efficiently corrected. The results of relative deoxyhemoglobin concentration and relative blood flow velocity are then used to detect and distinguish cerebral arteries and veins. In an experimental study on rat, cerebral blood vessels are segmented from the reconstructed blood flow image by Otsu multiple threshold method. Afterwards, arteries and veins are distinguished by a simple fuzzy criterion based on the information of relative deoxyhemoglobin concentration.

Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technology which is suitable for psychiatric patients. Several fNIRS studies have found abnormal brain activations during cognitive tasks in elderly depression. In this paper, we proposed a discriminative model of multivariate pattern classification based on fNIRS signals to distinguish elderly depressed patients from healthy controls. This model used the brain activation patterns during a verbal fluency task as features of classification. Then Pseudo-Fisher Linear Discriminant Analysis was performed on the feature space to generate discriminative model. Using leave-one-out (LOO) cross-validation, our results showed a correct classification rate of 88%. The discriminative model showed its ability to identify people with elderly depression and suggested that fNIRS may be an efficient clinical tool for diagnosis of depression. This study may provide the first step for the development of neuroimaging biomarkers based on fNIRS in psychiatric disorders.

Cortical spreading depression (CSD), which is a significant pathological phenomenon that correlates with migraines and cerebral ischemia, has been characterized by a wave of depolarization among neuronal cells and propagates across the cortex at a rate of 2–5mm/min. Although the propagation pattern of CSD was well-investigated using high-resolution optical imaging technique, the variation of propagation speed of CSD across different regions of cortex was not well-concerned, partially because of the lack of ideal approach to visualize two-dimensional distribution of propagation speed of CSD over the whole imaged cortex. Here, we have presented a method to compute automatically the propagation speed of CSD throughout every spots in the imaged cortex. In this method, temporal clustering analysis (TCA) and least square estimation (LSE) were first used to detect origin site where CSD was induced. Taking the origin site of CSD as the origin of coordinates, the data matrix of each image was transformed into the corresponding points based on the polar-coordinate representation. Then, two fixed-distance regions of interest (ROIs) are sliding along with the radial coordinate at each polar angle within the image for calculating the time lag with correlating algorithm. Finally, we could draw a twodimensional image, in which the value of each pixel represented the velocity of CSD when it spread through the corresponding area of the imaged cortex. The results demonstrated that the method can reveal the heterogeneity of propagation speed of CSD in the imaged cortex with high fidelity and intuition.