Enhanced functional brain imaging by using adaptive filtering and a depth compensation algorithm in diffuse optical tomography

Reflectance diffuse optical tomography (rDOT) of brain function is limited by its high sensitivity to the superficial tissues (i.e., the scalp and skull) and by its severe decrease in measurement sensitivity with increased depth. Significant interference in rDOT results from spontaneous fluctuations that are embedded in both the superficial tissues and brain, such as arterial pulsation and vasomotion. In this study, first we investigate coherence and phase shift of the spontaneous fluctuations in the resting state, within the superficial tissues and at various depths of the brain, respectively. We demonstrate that the spontaneous fluctuations originating from arterial pulsations ( ～ 1 Hz) are spatially global and temporally coherent, while the fluctuations originating from vasomotion ( ～ 0.1 Hz) tend to have less coherence with increased depth. Second, adaptive cancellation of spontaneous fluctuations with a frequency-specific strategy is utilized and validated in both resting and activation (evoked by a finger-tapping task) states. Third, improved depth localization of motor activation in reconstructed rDOT images is achieved by combining adaptive cancellation with a depth compensation algorithm that we recently reported.     

Multi-platform data integration in microarray analysis

An increasing number of studies have profiled gene expressions in tumor specimens using distinct microarray platforms and analysis techniques. One challenging task is to develop robust statistical models in order to integrate multi-platform findings. We compare some methodologies on the field with respect to estrogen receptor (ER) status, and focus on a unified-among-platforms scale implemented by Shen et al. in 2004, which is based on a Bayesian mixture model. Under this scale, we study the ER intensity similarities between four breast cancer datasets derived from various platforms. We evaluate our results with an independent dataset in terms of ER sample classification, given the derived gene ER signatures of the integrated data. We found that integrated multi-platform gene signatures and fold-change variability similarities between different platform measurements can assist the statistical analysis of independent microarray datasets in terms of ER classification.     

Raman enhancement of rhodamine adsorbed on Ag nanoparticles self-assembled into nanowire-like arrays

ABSTRACT: This work reports on Raman scattering of rhodamine (R6G) molecules absorbed on either randomly distributed or grating-like arrays of approximately 8-nm Ag nanoparticles developed by inert gas aggregation. Optimal growth and surface-enhanced Raman scattering (SERS) parameters have been obtained for the randomly distributed nanoparticles, while effects related to the aging of the silver nanoparticles were studied. Grating-like arrays of nanoparticles have been fabricated using line arrays templates formed either by fracture-induced structuring or by standard lithographic techniques. Grating structures fabricated by both methods exhibit an enhancement of the SERS signal, in comparison to the corresponding signal from randomly distributed Ag nanoparticles, as well as a preferential enhancement in the areas of the sharp features, and a dependence on the polarization direction of the incident exciting laser beam, with respect to the orientation of the gratings structuring. The observed spectroscopic features are consistent with a line-arrangement of hot-spots due to the self- alignment of metallic nanoparticles, induced by the grating-like templates.     

f-Value: measuring an article’s scientific impact

The f-value is a new indicator that measures the importance of a research article by taking into account all citations received, directly and indirectly, up to depth n. The f-value considers all information present in a Citation Graph in order to produce a ranking of the articles. Apart from the mathematical equation that calculates the f-value, we also present the corresponding algorithm with its implementation, plus an experimental comparison of f-value with two known indicators of an article’s scientific importance, namely, the number of citations and the Page Rank for citation analysis. Finally, we discuss the similarities and differences among the indicators.     

A model of carbon ion interactions in water using the classical trajectory Monte Carlo method

In this paper, model calculations for interactions of C(6+) of energies from 1 keV u(-1) to 1 MeV u(-1) in water are presented. The calculations were carried out using the classical trajectory Monte Carlo method, taking into account the dynamic screening of the target core. The total cross sections (TCS) for electron capture and ionisation, and the singly and doubly differential cross sections (SDCS and DDCS) for ionisation were calculated for the five potential energy levels of the water molecule. The peaks in the DDCS for the electron capture to continuum and for the binary-encounter collision were obtained for 500-keV u(-1) carbon ions. The calculated SDCS agree reasonably well with the z(2) scaled proton data for 500 keV u(-1) and 1 MeV u(-1) projectiles, but a large deviation of up to 8-folds was observed for 100-keV u(-1) projectiles. The TCS for ionisation are in agreement with the values calculated from the first born approximation (FBA) at the highest energy region investigated, but become smaller than the values from the FBA at the lower-energy region.     

Localization of adipose tissue embedded biliary tree vessels by use of near-infrared diffuse photon propagation models: a computational feasibility study

Biliary tree structures are embedded in adipose tissue and, therefore, cannot be visualized directly by the surgeon during cholecystectomy operations. This can lead to inadvertent injuries with serious complications for the patient. Computational studies were performed to assess the feasibility of noninvasively localizing these structures from spectrally resolved near-infrared reflectance measurements. Methodologies were developed for vessel localization, both on the adipose tissue surface and depthwise, by use of semi-infinite and two-layer models of diffuse photon propagation in tissues, respectively. The simulation results, along with some preliminary experimental measurements on tissue-simulating phantoms, prove the feasibility of these methods and show promise for their future clinical application.     

Survival of Lactobacillus plantarum in model solutions and fruit juices

The aim of the work was to study the survival of Lactobacillus plantarum NCIMB 8826 in model solutions and develop a mathematical model describing its dependence on pH, citric acid and ascorbic acid. A Central Composite Design (CCD) was developed studying each of the three factors at five levels within the following ranges, i.e., pH (3.0-4.2), citric acid (6-40 g/L), and ascorbic acid (100-1000 mg/L). In total, 17 experimental runs were carried out. The initial cell concentration in the model solutions was approximately 1 × 10⁸ CFU/mL; the solutions were stored at 4 °C for 6 weeks. Analysis of variance (ANOVA) of the stepwise regression demonstrated that a second order polynomial model fits well the data. The results demonstrated that high pH and citric acid concentration enhanced cell survival; one the other hand, ascorbic acid did not have an effect. Cell survival during storage was also investigated in various types of juices, including orange, grapefruit, blackcurrant, pineapple, pomegranate, cranberry and lemon juice. The model predicted well the cell survival in orange, blackcurrant and pineapple, however it failed to predict cell survival in grapefruit and pomegranate, indicating the influence of additional factors, besides pH and citric acid, on cell survival. Very good cell survival (less than 0.4 log decrease) was observed after 6 weeks of storage in orange, blackcurrant and pineapple juice, all of which had a pH of about 3.8. Cell survival in cranberry and pomegranate decreased very quickly, whereas in the case of lemon juice, the cell concentration decreased approximately 1.1 logs after 6 weeks of storage, albeit the fact that lemon juice had the lowest pH (pH ~ 2.5) among all the juices tested. Taking into account the results from the compositional analysis of the juices and the model, it was deduced that in certain juices, other compounds seemed to protect the cells during storage; these were likely to be proteins and dietary fibre In contrast, in certain juices, such as pomegranate, cell survival was much lower than expected; this could be due to the presence of antimicrobial compounds, such as phenolic compounds.     

Glycosylation Modulates Plasma Membrane Trafficking of CD24 in Breast Cancer Cells

In breast cancer, expression of Cluster of Differentiation 24 (CD24), a small GPI-anchored glycoprotein at the cell periphery, is associated with metastasis and immune escape, while its absence is associated with tumor-initiating capacity. Since the mechanism of CD24 sorting is unknown, we investigated the role of glycosylation in the subcellular localization of CD24. Expression and localization of wild type N36- and/or N52-mutated CD24 were analyzed using immunofluorescence in luminal (MCF-7) and basal B (MDA-MB-231 and Hs578T) breast cancer cells lines, as well as HEK293T cells. Endogenous and exogenously expressed wild type and mutated CD24 were found localized at the plasma membrane and the cytoplasm, but not the nucleoplasm. The cell lines showed different kinetics for the sorting of CD24 through the secretory/endocytic pathway. N-glycosylation, especially at N52, and its processing in the Golgi were critical for the sorting and expression of CD24 at the plasma membrane of HEK293T and basal B type cells, but not of MCF-7 cells. In conclusion, our study highlights the contribution of N-glycosylation for the subcellular localization of CD24. Aberrant N-glycosylation at N52 of CD24 could account for the lack of CD24 expression at the cell surface of basal B breast cancer cells.     

Rapid Non-destructive Detection of Spoilage of Intact Chicken Breast Muscle Using Near-infrared and Fourier Transform Mid-infrared Spectroscopy and Multivariate Statistics

Near-infrared (NIR) transflectance and Fourier transform-infrared (FT-IR) attenuated total reflectance spectra of intact chicken breast muscle packed under aerobic conditions and stored at 4° for 14 days were collected and investigated for their potential use in rapid non-destructive detection of spoilage. Multiplicative scatter correction-transformed NIR and standard normal variate-transformed FT-IR spectra were analysed using principal component analysis (PCA), partial least-squares discriminant analysis (PLS2-DA) and outer product analysis (OPA). PCA and PLS2-DA regression failed to completely discriminate between days 0 and 4 samples (total viable count (TVC) days 0 and 4 = 5.23 and 6.75 log₁₀ cfu g⁻¹) which had bacterial loads smaller than the accepted levels (8 log₁₀ cfu g⁻¹) of sensory spoilage detection but classified correctly days 8 and 14 samples (TVC days 8 and 14 = 9.61 and 10.37 log₁₀ cfu g⁻¹). OPA performed on both NIR and FT-IR datasets revealed several correlations that highlight the effect of proteolysis in influencing the spectra. These correlations indicate that increase in free amino acids and peptides could be the main factor in the discrimination of intact chicken breast muscle. This investigation suggests that NIR and FT-IR spectroscopy can become useful, rapid, non-destructive tools for spoilage detection.