Combing the time-correlated single photon counting (TCSPC) with fluorescence lifetime imaging microscopy (FLIM) provides promising opportunities in revealing important information on the microenvironment of cells and tissues, but the applications are thus far mainly limited by the accuracy and precision of the TCSPC-FLIM technique. Here we present a comprehensive investigation on the performance of two data analysis methods, the first moment (M1) method and the conventional least squares (Fitting) method, in quantifying fluorescence lifetime. We found that the M1 method is more superior than the Fitting method when the lifetime is short (70 ~ 400 ps) or the signal intensity is weak (<103 photons).

Near-infrared spectroscopy (NIRS) is generally accepted as a functional brain imaging technology for brain activation study. With multichannel highly sensitive NIRS instruments, it has become possible to assess functional connectivity of different brain regions by NIRS. However, the feasibility needs to be validated in complex cognitive activities. In this study, we recorded the hemodynamic activity of the bilateral prefrontal cortex (PFC) during a color-word matching Stroop task. Wavelet transform coherence (WTC) analysis was applied to assess the functional connectivity of all homologous channel pairs within the left/right PFC. Both the behavioral and brain activation results showed significant Stroop effects. The results of WTC analysis revealed that, bilateral functional connectivity was significantly stronger during both the incongruent stimuli and neutral stimuli compared to that of the rest period. It also showed significant Stroop effect. Our findings demonstrate that, NIRS becomes a valuable tool to elucidate the functional connectivity of brain cortex in complex cognitive activities.

A device, that is used for biomedical operation or safety-critical applications like point-of-care health assessment, massive parallel DNA analysis, automated drug discovery, air-quality monitoring and food-safety testing, must have the attributes like reliability, dependability and correctness. As the biochips are used for these purposes; therefore, these devices must be fault free all the time. Naturally before using these chips, they must be well tested. We are proposing a novel technique that can detect multiple faults, locate the fault positions within the biochip, as well as calculate the traversal time if the biochip is fault free. The proposed technique also highlights a new idea how to select the appropriate base node or pseudo source (start electrode). The main idea of the proposed technique is to form multiple loops with the neighboring electrode arrays and then test each loop by traversing test droplet to check whether there is any fault. If a fault is detected then the proposed technique also locates it by backtracking the test droplet. In case, no fault is detected, the biochip is fault free then the proposed technique also calculates the time to traverse the chip. The result suggests that the proposed technique is efficient and shows significant improvement to calculate fault-free biochip traversal time over existing method.

In this paper, a novel photoacoustic viscoelasticity imaging (PAVEI) technique that provides viscoelastic information of biological tissues is presented. We deduced the process of photoacoustic (PA) effect on the basis of thermal viscoelasticity theory and established the relationship between the PA phase delay and the viscoelasticity for soft solids. By detecting the phase delay of PA signal, the viscoelasticity distribution of absorbers can be mapped. Gelatin phantoms with different densities and different absorption coefficients were used to verify the dependence of PAVEI measurements. Moreover, tissue mimicking phantoms mixed with fat and collagen at different concentrations were used to testify the feasibility of this technique with reliable contrast. Finally, the PAVEI was successfully applied to discrimination between biological tissue constituents. Our experimental results demonstrate that this novel technique has the potential for visualizing the anatomical and biomechanical properties of biological tissues.

Functional near infrared spectroscopy (fNIRS) is a technique that is used for noninvasive measurement of the oxyhemoglobin (HbO2) and deoxyhemoglobin (HHb) concentrations in the brain tissue. Since the ratio of the concentration of these two agents is correlated with the neuronal activity, fNIRS can be used for the monitoring and quantifying the cortical activity. The portability of fNIRS makes it a good candidate for studies involving subject's movement. The fNIRS measurements, however, are sensitive to artifacts generated by subject's head motion. This makes fNIRS signals less effective in such applications. In this paper, the autoregressive moving average (ARMA) modeling of the fNIRS signal is proposed for state-space representation of the signal which is then fed to the Kalman filter for estimating the motionless signal from motion corrupted signal. Results are compared to the autoregressive model (AR) based approach, which has been done previously, and show that the ARMA models outperform AR models. We attribute it to the richer structure, containing more terms indeed, of ARMA than AR. We show that the signal to noise ratio (SNR) is about 2 dB higher for ARMA based method.

Advanced glycation end products (AGEs) are a complex and heterogeneous group of compounds that have been implicated in diabetes related complifications. Skin autofluorescence was recently introduced as an alternative tool for skin AGEs accumulation assessment in diabetes. Successful optical diagnosis of diabetes requires a rapid and accurate classification algorithm. In order to improve the performance of noninvasive and optical diagnosis of type 2 diabetes, support vector machines (SVM) algorithm was implemented for the classification of skin autofluorescence from diabetics and control subjects. Cross-validation and grid-optimization methods were employed to calculate the optimal parameters that maximize classification accuracy. Classification model was set up according to the training set and then verified by the testing set. The results show that radical basis function is the best choice in the four common kernels in SVM. Moreover, a diagnostic accuracy of 82.61%, a sensitivity of 69.57%, and a specificity of 95.65% for discriminating diabetics from control subjects were achieved using a mixed kernel function, which is based on liner kernel function and radical basis function. In comparison with fasting plasma glucose and HbA1c test, the classification method of skin autofluorescence spectrum based on SVM shows great potential in screening of diabetes.

Anti-tumor immunological response induced by local intervention is ideal for treatment of metastatic tumors. Laser immunotherapy was developed to synergize photothermal interaction with immunological stimulation for cancer treatment. Using an infrared laser, indocyanine green (ICG, as a light absorbing agent), and glycated chitosan (GC, as an immunostimulant), laser immunotherapy has resulted in tumor suppression and anti-tumor responses in pre-clinical as well as clinical studies. To further understand the mechanism of laser immunotherapy, the effects of laser and GC treatment without specific enhancement of laser absorption were studied. Passive adoptive immunity transfer was performed using splenocytes as immune cells. Spleen cells harvested from tumor-bearing mice treated by laser + GC provided 60% immunity in naive recipients. Furthermore, cytotoxicity and TNF-α secretion by splenocytes from treated mice also indicated that laser + GC induced immunity was tumor-specific. The high level of infiltrating T cells in tumors after laser +GC treatment further confirmed a specific anti-tumor immune response. Therefore, laser + GC could prove to be a promising selective local treatment modality that induces a systemic anti-tumor response, with appropriate laser parameters and GC doses.

The aim of this ex vivo study was to explore the potential of using the fluorescence lifetime of intracellular reduced nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) as a label-free indicator to characterize the differences between human leukemic myeloid cells and normal mononuclear cells (MNC). The steady-state and time-resolved autofluorescence of two human leukemic myeloid cell lines (K562, HL60) and MNC were measured by a spectrofluorimeter. According to excitation–emission matrix (EEM) analysis, the optimal emission of NAD(P)H in these cells suspensions occurred at 445 nm. Furthermore, the fluorescence lifetimes of NAD(P)H in leukemic myeloid cells and MNC were determined by fitting the time-resolved autofluorescence data. The mean fluorescence lifetimes of NAD(P)H in K562, HL60, and MNC cells were 5.57± 1.19, 4.45 ± 0.71, and 7.31 ± 0.60 ns, respectively. There was a significant difference in the mean lifetime of NAD(P)H between leukemic myeloid cells and MNC (p < 0:05). The difference was essentially caused by the change in relative concentration of free and protein-bound NAD(P)H. This study suggests that the mean fluorescence lifetime of NAD(P)H might be a potential labelfree indicator for differentiating leukemic myeloid cells from MNC.

The use of an electrical probe is formed by whispering gallery modes (WGMs) of light within the coated microring circuits, in which the electrical signal is generated by trapped electron tunneling along the circular path of the coated microring circuit. The collection of electrons is formed within the WGMs, where in this study, a modified nonlinear microring resonator known as a PANDA ring resonator is coated by gold material and forms the mirroring circuit. The induced current (magnetic field) within the circuit occurs by the coupling effects between trapped electrons and coated ring, which can penetrate into the brain cells and transform to the required signals via the terahertz carrier for psychiatric investigations. The use of WGMs for 3D image construction using a PANDA conjugate mirror is also discussed, which is useful for thermal and imaging sensors.

Recently, we found that high concentration of taxol (70 μM) induced cell death with cytoplasm vacuolization, the typical characteristic of both paraptosis and oncosis, in human lung carcinoma (ASTC-a-1) cells. This report was designed to further determine the form of taxol-induced cell death with cytoplasm vacuolization. It is generally considered that the cytoplasm vacuolization in oncosis due to the swelling of endoplasmic reticulum (ER), mitochondria, lysosomes and nuclei occurs after the loss of mitochondrial membrane potential (ΔΨm). However, flow cytometry (FCM) analysis showed that taxol-induced cytoplasm vacuolization preceded the loss of ΔΨm. Moreover, taxol treatment did not induce the collapse of microtubule, the typical characteristic of oncosis. These data demonstrated that taxol-induced cell death with cytoplasm vacuolization is not oncosis. FCM analysis by Annexin V-FITC/PI apoptosis detection kit further demonstrated that taxol-induced cell death with cytoplasm vacuolization is not apoptosis. In conclusion, in combination with our recent in vitro and in vivo data, this report further demonstrates that high concentration of taxol induces cell death with cytoplasm vacuolization in paraptosis-like but not oncosis fashion.

T-rays is sensitive to covalently cross-linked proteins and can be used to probe unique dynamic properties of water surrounding a protein. In this paper, we demonstrate the unique absorption properties of the dynamic hydration shells determined by hemagglutinin (HA) protein in terahertz frequency. We study the changes arising from different concentrations in detail and show that nonlinear absorption coefficient is induced by the dynamic hydration water. The binary and ternary component model were used to interpret the nonlinearity absorption behaviors and predict the thickness of the hydration shells around the HA protein in aqueous phase.

Fourier transform infrared imaging (FTIRI) was used to examine the depth-dependent content variations of macromolecular components, collagen and proteoglycan (PG), in osteoarthritic and healthy cartilages. Dried 6 μm thick sections of canine knee cartilages were imaged at 6.25 μm pixel-size in FTIRI. By analyzing the infrared (IR) images and spectra, the depth dependence of characteristic band (sugar) intensity of PG show obvious difference between the cartilage sections of (OA) and health. The result confirms that PG content decreases in the osteoarthritic cartilage. However, no clear change occurs to collagen, suggesting that the OA influences little on the collagen content at early stage of OA. This observation will be helpful to further understand PG loss associated with pathological conditions in OA, and demonstrates that FTIRI has the potential to become an important analytical tool to identify early clinical signs of tissue degradation, such as PG loss even collagen disruption.