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We introduce a method to extract the photoacoustic (PA) signal from a contrast reduction of the interference spectrum acquired by spectral domain optical coherence tomography (SDOCT). This all-optical detection is achieved in a noncontact manner directly on the water surface covered on the sample by using its specular reflection. During SDOCT exposure, the phase of the interference spectrum keeps shaking according to the water surface vibration induced by PA excitation. This results in an interference contrast reduction which is quantified by a fast Fourier transform (FFT) for PA imaging. A tungsten filament, asparagus fern leaf, and mouse auricle are imaged to demonstrate the method.

The absence of lymphatic vessels in tumors leads to the retention of interstitial fluid, and the formation of an inverse pressure difference between the tumor and blood vessels hinders drug delivery deep into the tumor, which leads to tumor recurrence and metastasis. Therefore, we designed a novel strategy to downregulate tumor interstitial fluid pressure (TIFP) by water splitting in the tumor interstitium based on piezoelectric catalysis nanomedicine. First, the chemotherapeutic drug doxorubicin (DOX) was loaded on the piezoelectric catalytic material MoS

We propose a high-speed all-optic dual-modal system that integrates spectral-domain optical coherence tomography and photoacoustic microscopy (PAM). A [Formula: see text] coupler-based interferometer is used to remotely detect the surface vibration caused by photoacoustic (PA) waves. Three outputs of the interferometer are acquired simultaneously with a multi-channel data acquisition card. One channel data with the highest PA signal detection sensitivity is selected for sensitivity compensation. Experiment on the phantom demonstrates that the proposed method can successfully compensate for the loss of intensity caused by sensitivity variation. The imaging speed of the PAM is improved compared to our previous system. The total time to image a sample with [Formula: see text] pixels is [Formula: see text][Formula: see text]s. Using the proposed system, the microvasculature in the mouse auricle is visualized and the blood flow state is accessed.

The advancement of anti-tumor nanomedicines is restricted by the delivery efficiency owing to a lack of insight into the intratumoral delivery mechanism, especially traversing the biological barriers. Herein, we explore a new strategy focusing on controlling excessive high tumor interstitial fluid pressure (TIFP) caused by lymphatic lack, which hampers the convective diffusion of nanomedicines to the tumor center. We construct a “nano-lymphatic” system (DOX/g-C3N4/luminol@cytomembrane, DCL@M) based on graphitic carbon nitride (g-C3N4) for photocatalytic water splitting, which can decrease the volume of the tumor interstitial fluid to ameliorate the transfer resistance derived from the high TIFP. In the tumor microenvironment, lactic acid as a sacrificial agent in catalysis greatly promoted the water-splitting efficiency; thus, TIFP in the tumor tissue was reduced to 62.11%, causing an enhancement in blood perfusion to the tumor. The accumulation of the “nano-lymphatic” system (16.73%) in the tumor was 15.9- and 3.31-fold greater than those of free doxorubicin hydrochloride (DOX, 1.05%) and DOX/g-C3N4@cytomembrane (DC@M, 3.03%), respectively. The penetration efficiency of the “nano-lymphatic” system was 8.98% at the tumor center. The “nano-lymphatic” strategy produced reactive oxygen species associated with water splitting to suppress the tumor growth; thus, we define the strategy as hydrodynamic therapy, which provides a new avenue for nanomedicines in traversing biological barriers and achieves a better therapeutic effect.

In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectrums were acquired by Fourier transform (FT) Raman spectroscopy. Spectral data ranging from 800 cm

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

Because of the deficiency of lymphatic reflux in the tumor, the retention of tumor interstitial fluid causes aggravation of the tumor interstitial pressure (TIP), which leads to unsatisfactory tumor penetration of nanomedicine. It is the main inducement of tumor recurrence and metastasis. Herein, we design a pyroelectric catalysis-based "Nano-lymphatic" to decrease the TIP for enhanced tumor penetration and treatments. It realizes photothermal therapy and decomposition of tumor interstitial fluid under NIR-II laser irradiation after reaching the tumor, which reduces the TIP for enhanced tumor penetration. Simultaneously, reactive oxygen species generated during the pyroelectric catalysis can further damage deep tumor stem cells. The results indicate that the "Nano-lymphatic" relieves 52% of TIP, leading to enhanced tumor penetration, which effectively inhibits the tumor proliferation (93.75%) and recurrence. Our finding presents a rational strategy to reduce TIP by pyroelectric catalysis for enhanced tumor penetration and improved treatments, which is of great significance for drug delivery.

We report on fabricating plasmonic nanorod crystals using focused ion beam lithography. We first demonstrate manipulating the profiles of nanorods perpendicularly aligned with the substrate. Then we show accurate control of nanorod outlines can be achieved. We also show that it is feasible to manufacture nanorods obliquely aligned with the substrate. Tunable plasmon resonance can be realized with different tilting angles and geometries. Our approach may find important applications in plasmon-assisted sensing and surface enhanced spectroscopy.

Background Ischemic cerebral edema (CE) is a major leading cause of death in patients with ischemic stroke. The CE progression is closely related to the local cerebral blood perfusion (LCBP) level surrounding the edema area. Quantitative studying the interaction between the CE and peripheral LCBP may provide new inspiration for control and even treatment of CE. Methods Photothrombosis ischemia mouse model was established and observed for 9 hours using swept-source optical coherence tomography (SS-OCT). OCT-based angiography and OCT-based attenuation imaging techniques were used to reconstruct the angiograms reflecting the cerebral blood perfusion (CBP) level and optical attenuation coefficient (OAC) maps reflecting the edema state. The influence of edema on LCBP was analyzed by quantifying the blood perfusion in different spatial locations around the edema tissue, and the influence of LCBP on CE progression was revealed by comparing the changes of the edema area and LCBP level over time. Results Preliminary studies show that the effect of edema tissue on LCBP is very significant, which shows a clear spatial dependence. LCBP near the edema tissue is 15-20% lower than that far away from the edema tissue. When the LCBP drops to around 60% of the initial value, the edema area increases sharply. In addition, the level of CBP in the contralateral hemisphere also decreases with time. When the contralateral CBP drops to around 60%, there is a certain probability that contralateral edema will occur. Conclusions CE progression is not only related to the LCBP around the edema tissue but also related to the CBP of non-edematous regions. Controlling the CBP level of non-edematous regions may play a positive role in the treatment of CE. This work provides a new method and inspiration for exploring the mechanism of ischemic CE progression.

Owing to deficiency of lymphatic reflux in the tumor, the retention of tumor interstitial fluid causes the aggravation of tumor interstitial pressure (TIP), which leads to unsatisfactory tumor penetration of nanomedicine. It is the main inducement of tumor recurrence and metastasis. Herein, we design a pyroelectric catalysis-based “Nano-lymphatic” to decrease the TIP for enhanced tumor penetration and treatments. It realizes photothermal therapy and decomposition of tumor interstitial fluid under NIR-II laser irradiation after reaching the tumor, which reduces the TIP for enhanced tumor penetration. Simultaneously, reactive oxygen species generated during the pyroelectric catalysis can further damage deep tumor stem cells. The results indicate that the “Nano-lymphatic” relieves 52% of TIP, leading to enhanced tumor penetration, which effectively inhibits the tumor proliferation (93.75%) and recurrence. Our finding presents a novel strategy to reduce TIP by pyroelectric catalysis for enhanced tumor penetration and improved treatments, which is of great significance for drug delivery.

Segmentation of layers in retinal images obtained by optical coherence tomography (OCT) has become an important clinical tool to diagnose ophthalmic diseases. However, due to the susceptibility to speckle noise and shadow of blood vessels etc., the layer segmentation technology based on a single image still fail to reach a satisfactory level. We propose a combination method of structure interpolation and lateral mean filtering (SI-LMF) to improve the signal-to-noise ratio based on one retinal image. Before performing one-dimensional lateral mean filtering to remove noise, structure interpolation was operated to eliminate thickness fluctuations. Then, we used boundary growth method to identify boundaries. Compared with existing segmentations, the method proposed in this paper requires less data and avoids the influence of microsaccade. The automatic segmentation method was verified on the spectral domain OCT volume images obtained from four normal objects, which successfully identified the boundaries of 10 physiological layers, consistent with the results based on the manual determination.

Cerebral edema is a severe complication of acute ischemic stroke with high mortality but limited treatment. Although parameters such as brain water content and intracranial pressure may represent the global assessment of edema, optical properties can appear heterogeneously throughout the cerebral tissue relative to the site of injury. In this study, we have monitored the edema formation and progression in both permanent and transient middle cerebral artery occlusion models in rats. Edema was reflected by the decrease of optical attenuation coefficient (OAC) value in OCT system. By utilizing swept-source optical coherence tomography (SS-OCT), we found that in photochemically induced permanent focal stroke model, both the edema size and edema index, steadily developed until the end of monitor (7[Formula: see text]h). Comparatively, when transient ischemia was introduced with endothelin-1 (ET-1), the edema was detected as early as 15[Formula: see text]min, and began to recover after 30[Formula: see text]min until monitor was finished (3[Formula: see text]h). Despite the majority of the edema being recovered to some extent, the condition of a small region within the edema kept deteriorating, presumably due to the reperfusion damage which might result in serious clinical outcomes. Our study has compared the edema characteristics from two different acute ischemic stroke situations. This work not only confirms the capability of OCT to temporal and spatial monitor of edema but is also able to locate focal conditions at some areas that might highly determine the prognosis and treatment decisions.

In this paper, a reagent-free simultaneous and direct detection method of three analytes in human blood based on Fourier-transform Raman (FT-Raman) spectroscopy with 1064 nm laser radiation was proposed for the first time. A total of 161 human blood samples were characterized by FT-Raman spectroscopy under the excitation laser source of 1064 nm. In order to achieve a robust regression model, the Nonlinear Iterative Partial Least Squares (NIPALS) with orthogonal signal correction (OSC) algorithm and sample set partition based on a joint x-y distance (SPXY) is used to establish multivariate calibration models. The root means square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), correlation coefficients ( R 2 ) and ratio of performance to deviation (RPD) were 0.34255 mg/dL, 0.3662 mg/dL, 0.99982 and 56.3524 for glucose, 0.33656 mg/dL, 0.75736 mg/dL, 0.99967 and 34.9169 for total cholesterol (TC), and 0.29956 mg/dL, 0.27469 mg/dL, 0.99998 and 173.5098 for triglycerides (TG), respectively. The analysis results showed that the proposed method could be able to accurately predict the concentration of glucose, TC and TG in blood. This method can instantaneous multi-component detection on whole blood.

With the increasing capacity and transmission distance of the power grid, HVDC technology has been more and more widely used. MTDC is an essential direction for the development of HVDC technology. At this stage, LCC is widely used in the MTDC transmission project, and there is a lot of corresponding design software, but the software development of the hybrid DC transmission is not perfect and mature enough. In this paper, the design method of the parameters of the main loop in the LCC-MMC hybrid HVDC transmission system has been studied. The corresponding design software has been compiled, and this paper presents functional modules to be accomplished in the software package. The correctness of the software calculation is verified by the actual HVDC transmission project data, and the software can be applied to the initial design of the hybrid HVDC transmission project.

Cerebral edema is a serious complication of ischemic cerebrovascular disease and mannitol is a commonly used dehydrating agent for relieving cerebral edema. However, the edema state and surrounding vascular perfusion level during mannitol treatment remains unclear, which affects the clinical application of the medicine. In this paper, we demonstrated the role of swept-source optical coherence tomography (OCT) in the evaluation of mannitol efficacy using mouse models. The OCT-based angiography and attenuation imaging technology were used to obtain the cerebral vascular perfusion level and cerebral edema state at different times. Vascular parameters and edema parameters were quantified and compared. Experimental results show that mannitol can significantly reduce the water content in the central region of edema, effectively inhibiting the rapid growth of the edema area, and restoring cerebral blood flow. On average, the edema area decreased by 33% after 2 h, and the vascular perfusion density increased by 12% after 5 h. This work helps to provide a valuable theoretical basis and research ideas for the clinical treatment of cerebral edema.

In this paper, a one-dimensional shallow convolutional neural network structure combined with elastic nets (1D-SCNN-EN) was firstly proposed to predict the glucose concentration of blood by Raman spectroscopy. A total of 106 different blood glucose spectra were obtained by Fourier transform (FT) Raman spectroscopy. The one-dimensional shallow convolutional neural network, with elastic nets added to the full connected layer, was presented to capture multiple deep features and reduce the complexity of the model. The 1D-SCNN-EN model has a better performance than conventional approaches (partial least squares and support vector machine). The root mean squared error of calibration (RMSEC), the root mean squared error of prediction (RMSEP), the determination coefficient of prediction ( R P 2 ), and the residual predictive deviation of prediction (RPD) were 0.10262, 0.11210, 0.99403, and 12.94601, respectively. The experiment results showed that the 1D-SCNN-EN model has a higher prediction accuracy and stronger robustness than the other regression models. The overall studies indicated that the 1D-SCNN-EN model looked promising for predict the glucose concentration of blood by Raman spectroscopy when the sample size is small.

The aim of the current research work was to develop sonophoresis-assisted transdermal patches for the treatment of osteoporosis. In the present investigation, we formulated alendronate-chitosan nanoparticles by ionotropic external gelation method. The prepared nanoparticles were found to be smooth and free-flowing. The optimized formulation showed 82.7% of drug release over a period of 12 hours with 99.54% EE, the particle size of 250 nm, PDI 0.22 and zeta potential of 28 mV. The solvent casting evaporation method was used for the development of the patches using HPMC as rate-controlling polymer and dibutyl phthalate as the plasticizer. The optimized patch formulation was found acceptable in terms of physical characteristics (appearance, thickness, folding endurance, weight variation, moisture loss and uptake). The drug content was found to be 99.66±0.9 % with 69.44% of drug permeation through the rat skin. The TP3 formulation had drug content of 99.96% which was the highest among all of the formulations and showed relatively controlled skin permeation of 69.44% over the period of 12 hours. Nearly six-time enhancement of bioavailability was observed when alendronate was used in the nanoparticulate form in transdermal patches used with sonophoresis. Over the period of seven days, the plasma calcium concentration in the rat model was decreased from 16 mg/dl to 4 mg/dl (4 times) in rat groups treated with the transdermal patches containing CS-ALN-NP while the concentration dropped only to 12 mg/dl in case of the transdermal patches containing pure Alendronate. These findings (enhanced skin permeation, enhanced bioavailability and suppression of the plasma calcium level) regarding the transdermal delivery system suggest a promising approach for the treatment of osteoporosis.

The progression of ischemic cerebral edema (CE) is closely related to the level of cerebral blood perfusion (CBP) and affects each other. Simultaneous detection of CBP and CE is helpful in understanding the mechanisms of ischemic CE development. In this article, a wide field of view swept-source optical coherence tomography system was used to detect CE status and CBP levels simultaneously in middle cerebral artery occlusion rats. Images reflecting these two physiological states can be reconstructed with only one C-scan. We quantify these two physiological states into four parameters, which contain two vascular parameters (vascular displacement distance and vascular perfusion density) and two edema parameters (optical attenuation coefficient and edema area). The association between the two vascular parameters and the two edema parameters was analyzed. The results show that there is a strong linear relationship between blood flow parameters and edema parameters. This work provides a new option for CE in vivo detection, and is very likely to play an important role in the development of relevant drugs or in selection of treatment options.

We demonstrate a 3×3 coupler-based fiber-optic interferometric system to detect the local initial photoacoustic pressure. In contrast with the existing interferometric photoacoustic microscopy (PAM) relying on the measurement of the phase change of the probe light caused by the sample surface vibration, the present method measures the intensity change of the probe light caused by the initial photoacoustic pressure. Compared with the conventional interferometric PAMs, this method has the advantages: (1) it is free from the influence of the rough tissue surface, achieving complete noncontact in vivo imaging; (2) the probe light and the excitation light are focused at a same point below the sample surface, and the confocal configuration makes it more convenient for in vivo imaging; and (3) there is no need for phase stabilization, allowing a high imaging speed. These advantages show that the method will be a promising technique for in vivo imaging. This method is verified by imaging of a resolution test target and in vivo imaging of the blood vessels in a mouse ear.

For spectroscopic measurements, representative samples are needed in the course of building a calibration model to guarantee accurate predictions. The most widely used selection method is the Kennard-Stone method, which can be used before a reference measurement is done. In this paper, a method termed semi-supervised selection is presented to determine whether a sample should be added to the calibration set. The selection procedure has two steps. First, part of the population of samples is selected using the Kennard-Stone method, and their concentrations are measured. Second, another part of the population of samples is selected based on the scalar value distribution of the net analyte signal. If the net analyte signal of a sample is distinctive compared to the existing net analyte signal values, then the sample is added to the calibration set. The analyte of interest in the sample is then measured so that the sample can be used as a calibration sample. By a validation test, it is shown that the presented method is more efficient than random selection and Kennard-Stone selection. As a result, both the time and the money spent on reference measurements are saved.

A multi-pass cell with ellipsoid structure used dual optical source of opposite side was proposed firstly in this paper. The EMPC was composed of double concave spherical mirrors and an ellipsoidal resonator. The radius of curvature of the two symmetric concave spherical mirrors was 200 mm and the length of the cavity was 120 mm. The size of the resonator of the photoacoustic (PA) cell in the experiment is Φ 28 m m × 100 m m and the size of the buffer cell at both ends of the PA cell is Φ 70 m m × 10 m m . The two laser beams were injected from the two sides of the concave spherical mirrors by the optical fiber. The absorption spectrum line with the acetylene wavelength of 1531.58 nm was selected. The simulation results show that the light beam can be reflected 37 times in EMPC and the optical path length can reach 8.64 m. In the experiment, the 2 f signal peak value fitting curve obtained at different concentrations with good linearity. Allan deviation analysis of experimental results shows the detection limit of EMPC was 60 ppb when the average time was 2 s. When the average time was 2 s, the normalized noise equivalent absorption (NNEA) coefficient of the system was 9.84 × 10 - 8 c m - 1 · W · H z - 1 / 2 . The whole system has high detection sensitivity and stability.

We demonstrate a Fourier-transform-based method for extensive-dynamic-range and high-resolution surface profiling using phase-sensitive spectral-domain white-light interferometry. By combining the frequency and phase of interference fringes, this method is capable of displacement measurement with nanometer-scale resolution and a dynamic range up to several millimeters. The performance of the method is demonstrated by surface profiling of a coin, gauge blocks, and a cell-phone circuit board.

The normal specification for multivariate calibration is the root mean square error (RMSE), which is computed from the error of all the samples in one set. As a result, condensed samples will inherently have less error than sparse samples. However, this phenomenon is undesirable in monitoring processes where marginal samples should be measured more accurately. Improving the accuracy of a calibration model over a particular interval would have a practical impact. By selecting uniformly distributed samples and including all the focused interval samples to decrease the cluster effect and include more matrix information, the accuracy of the target interval can be improved over that of an unselected calibration set. The selection method is based on a net analyte signal norm value computation and selection. Simulated spectral data and real sample sets are used to test the capability of the presented sample selection method. The experimental results show the method can improve interval accuracy for minor analyte and get almost equal interval accuracy for major analyte.

This study investigates Ophiopogon japonicas, a traditional Chinese medicine, by establishing the process model of polysaccharide precipitation based on a neural network algorithm. First, the principle of the BP neural network and the selection method of the model parameters are discussed, and the improved BP neural network algorithm is proposed. Then, the BP neural network model based on the population genetic algorithm (PGA) is established by analyzing the precipitation process of Ophiopogon japonicus polysaccharide. The weights and thresholds are trained and optimized to improve the precision of the polysaccharide precipitation model. Finally, the effect of the algorithm is illustrated by numerical simulation, and the simulation results are analyzed. This work lays the foundation for the future control system design.

The objective of this study is to establish a novel method for continuously monitoring thrombus progression with various outcome measures and to assess the efficacy of antithrombotic drugs in murine thrombosis model in mice. In the study, thrombus was induced in the femoral vein of mice by FeCl3 and monitored over time by spectral-domain optical coherence tomography (OCT). Three-dimensional images of thrombi with or without heparin as an antithrombotic agent were obtained from OCT angiography. In addition, several parameters of thrombi were analyzed and compared between control and anticoagulant groups. By using OCT, we were able to trace thrombus generation in the same mouse in real time. We found that in our model heparin reduced thrombus size by ~60% and thrombus cross-sectional area by 50%. OCT results also show that both time to thrombus size (>0.02mm3 ) and time to occlusion (>30%) were significantly reduced after heparin addition. This study demonstrates that OCT reliably monitors thrombus generation and progression from various aspects including thrombus size. This enables us to measure the kinetic of thrombosis more accurately, and effectively evaluate the efficacy and activities of antithrombotic drugs. This model may represent a useful tool in antithrombotic drug discoveries in preclinical studies.

Doppler optical coherence tomography (OCT) offers additional flow velocity information, which extends the application of OCT. Phase wrapping is the inherent problem that limits measureable range of Doppler OCT. We propose a phase unwrapping method which is suitable for correcting phase in Doppler OCT images. Points (pixels) in flow region are divided into groups according to the radial distance. Points in the same group are supposed to have close velocity. Phase unwrapping algorithm begins at the boundary layer group and is performed sequentially toward the center. Using the proposed criterion, points in a group are separated into two categories, signal points and noise points. Wrapping rounds are determined for signal points phase unwrapping. Mean value of the corrected signal points replaces the noise points for noise reduction. The method is validated with capillary tube flow phantom and in vivo blood flow.

The occurrence and development of ischemic stroke are closely related to cerebral blood flow. Real-time monitoring of cerebral perfusion level is very useful for understanding the mechanisms of the disease. A wide field of view (FOV) is conducive to capturing lesions and observing the progression of the disease. In this paper, we attempt to monitor the whole-brain microcirculation in middle cerebral artery occlusion (MCAO) rats over time using a wide FOV swept-source OCT (SS-OCT) system. A constrained image registration algorithm is used to remove motion artifacts that are prone to occur in a wide FOV angiography. During ischemia, cerebral perfusion levels in the left and right hemispheres, as well as in the whole brain were quantified and compared. Changes in the shape and location of blood vessels were also recorded. The results showed that the trend in cerebral perfusion levels of both hemispheres was highly consistent during MCAO, and the position of the blood vessels varied over time. This work will provide new insights of ischemic stroke and is helpful to assess the effectiveness of potential treatment strategies.

Optical coherence tomography (OCT) angiography is a noninvasive imaging modality that produces volumetric views of blood flow perfusion in vivo with resolution at capillary level, which has been widely adopted to monitor cerebral perfusion status after stroke in experimental settings. Accurate quantification of cerebral perfusion from OCT angiograms is important for understanding the cerebral vascular pathophysiology and assessing the treatment of ischemic stroke. Quantification of blood vessels from OCT angiography faces some problems; one is uneven backscatter (which causes some blood vessels to be very bright, some very dark), and the other is that the brightness in the same blood vessel also changes due to the difference in diameter or depth. In this paper, we proposed a locally adaptive region growing algorithm to solve this problem. The algorithm, which confines the region growing process to a local region, is used to segment blood vessels in different images to cope well with the intensity changes in blood vessels. During segmentation, the initial seed pixels were selected with the aid of the Otsu algorithm, the growth criterion considered both global and local information, and the thresholds were also adjusted adaptively as local regions varied. After these processes are completed, we can calculate the percentage of segmented blood vessels across field of view of the images, named cerebral vascular perfusion density, and use it as an indicator to evaluate the cerebral blood perfusion of middle cerebral artery occlusion in mice. This paper demonstrates that the algorithm can produce satisfactory vascular segmentation results, and CVPD can be used as an effective indicator for evaluating post-ischemic injury.

Constructing an excellent calibration set is crucial to ensuring accurate multivariate calibration of spectra data. The purpose of this paper is to present an improved Kennard–Stone (KS) calibration set construction strategy based on different derivative spectra information spaces, termed Consensus Kennard–Stone (CKS). The core idea is to make full use of different derivative spectra information spaces when constructing the calibration set using a consensus selection method as well as to improve the prediction performance of the multivariate regression model. The experimental results from two public spectra datasets indicate that the proposed CKS strategy can use a more appropriate subset of samples for constructing the calibration set in the multivariate regression model and has superior predictive performance compared with the existing classic sample-selection KS strategies.

A calibration set comprises the multidimensional space that represents the samples for prediction. The representative ability of a calibration set is a major factor that affects the predictive performance of a multivariate regression. A new reference value (YR)-based sample-selection algorithm that assembles a dependent value (y-value) uniform distribution is presented to assure the representation. The existing typical sample-selection algorithm is used for comparison. A set of soy sauce data is used as a set of typical samples that have a complex solution. Comparing the prediction results, it is shown that YR sample-selection has similar prediction performance to that of sample set partitioning based on joint x–y distances (SPXY), but with a simpler algorithm. The calibration models of the y-reference-included sample sets (SPXY and YR) are more accurate than those of y-reference-excluded sample sets (RS and KS). After modeling with the selected representative samples, the performances of YR and SPXY are comparable to that of full sample modeling with fewer samples.

Magnetomotive optical coherence tomography (MMOCT) is a promising imaging method for noninvasive three-dimensional tracking of magnetic nanoparticle (MNP) motions in target tissues or organs. The external B -field is the driving force that provides MMOCT contrast. However, B -field modulation also introduces modulation noise, thereby decreasing the quality of the MMOCT image. In this paper, a common-path–based device is designed for modulation noise reduction. The device is capable of adjusting interference distance, reference light intensity, and imaging position ( X − Y translation). The sensitivity of the MMOCT is increased by ∼ 20 times with the new device. Using the proposed device, the distribution of MNPs injected in zebrafish was imaged.

Cerebral edema is a severe complication of ischemic cerebrovascular disease, which can lead to microcirculation compression resulting in additional ischemic damage. Real-time and continuous in vivo imaging techniques for edema detection are of great significance to basic research on cerebral edema. We attempted to monitor the cerebral edema status in rats with middle cerebral artery occlusion (MCAO) over time, using a wide field-of-view swept-source optical coherence tomography (SS-OCT) system. Optical attenuation coefficients (OACs) were calculated by an optimized depth-resolved estimation method, and en face OAC maps covering the whole cortex were obtained. Then, the tissue affected by edema was segmented from the OAC maps, and the cortical area affected by edema was estimated. Both magnetic resonance image (MRI) and brain water content measurements were used to verify the presence of cerebral edema. The results showed that the average OAC of the ischemic area gradually decreased as cerebral edema progressed, and the edema area detected by SS-OCT had high similarity in position and shape to that obtained by MRI. This work extends the application of OCT and provides an option for detecting cerebral edema in vivo after ischemic stroke.

To guarantee accurate predictions, representative samples are needed when building a calibration model for spectroscopic measurements. However, in general, it is not known whether a sample is representative prior to measuring its concentration, which is both time-consuming and expensive. In this paper, a method to determine whether a sample should be selected into a calibration set is presented. The selection is based on the difference of Euclidean norm of net analyte signal (NAS) vector between the candidate and existing samples. First, the concentrations and spectra of a group of samples are used to compute the projection matrix, NAS vector, and scalar values. Next, the NAS vectors of candidate samples are computed by multiplying projection matrix with spectra of samples. Scalar value of NAS is obtained by norm computation. The distance between the candidate set and the selected set is computed, and samples with the largest distance are added to selected set sequentially. Last, the concentration of the analyte is measured such that the sample can be used as a calibration sample. Using a validation test, it is shown that the presented method is more efficient than random selection. As a result, the amount of time and money spent on reference measurements is greatly reduced.

Plasmonic nanostructures with ultrasmall gaps have found extensive applications such as molecule detection, chemical/bio-sensing, and surface enhanced Raman scattering due to the considerably enhanced electric field at the plasmon resonance. Here, we demonstrate the series of geometries of plasmonic crystals with different designs and ultrasmall gaps fabricated by a single-step focused ion beam patterning process. These designs include diversiform nanoantennae and compact nanoclusters. We show smallest features down to sub-10 nm. Our approach may find special applications in plasmon-assisted sensing, imaging and waveguiding.

In this paper, the novel technique for monitoring time-related changes that occur during wine fermentation, associated with auto-calibration Fourier transform Raman spectroscopy (FT-RS) and chemometric data analysis, was investigated. The auto-calibration system, which is composed of a reference optical path and measurement optical path, is first presented in this paper. The reference optical path was used to eliminate the frequency shift and intensity shift of the Raman spectra induced by the ambient temperature. The micro-fermentation trials conducted in our laboratory during 2013 were monitored by the auto-calibration FT-RS and by high-performance liquid chromatography (HPLC). Principal component analysis (PCA) and Partial least square (PLS) were applied to the Raman spectra to determine the relationship between the spectra and the concentration of sugar or alcohol during the fermentation process. The results from the PLS-PCA and HPLC showed good correlations and were obtained between predicted and actual sample values for sugar (0.995), ethanol (0.9999), and glycerol (0.98). The experimental results showed that the auto-calibration FT-RS is useful to identify crucial information about the quality of the final product in agreement with the chemical analyses during wine fermentation.

The optical attenuation coefficient (OAC) reflects the optical properties of various tissues or tissues of the same type under different physiological conditions. Quantitative measurement of OAC from optical coherence tomography (OCT) signals can provide additional information and can increase the potential for OCT applications. We present an optimized depth-resolved estimation (ODRE) method that derives a precise mapping between the measured OCT signal and the OAC. In contrast to previous depth-resolved estimation (DRE) methods, the optimized method can estimate the OAC in any depth range and ignore whether the light is completely attenuated. Numerical simulations and phantom experiments are used to verify its validity, and this method is applied to detect cerebral damage. In combination with OCT angiography, real-time observation of the change of blood perfusion and the degree of cerebral damage in mice with focal cerebral ischemia provides important information to help us understand the temporal relationship between brain damage and ischemia.

We demonstrated a method for measurement of central corneal thickness (CCT) with a sub-micrometer sensitivity using a spectral domain optical coherence tomography system without needing a super broad bandwidth light source. By combining the frequency and phase components of Fourier transform, the method is capable of measurement of a large dynamic range with a high sensitivity. Absolute phases are retrieved by comparing the correlations between the detected and simulated interference fringes. The phase unwrapping ability of the present method was quantitatively tested by measuring the displacement of a piezo linear stage. The human CCTs of six volunteers were measured to verify its clinical application. It provides a potential tool for clinical diagnosis and research applications in ophthalmology.

Filtering and estimation of derivatives in a single step from noisy signals is an important and challenging task in signal processing. The aim of this paper is to propose a new tracking differentiator based on only one parameter; this differentiator is able to synchronously filter noise and estimate the derivative of the input signal. The new tracking differentiator design is based on an inverse Taylor series approach. Both error and stability analyses of the tracking differentiator design are provided. Theoretical analysis and computer simulation results show that this tracking differentiator cannot only obtain better filtering results than previous approaches but can also estimate the derivatives with high accuracy.

This paper discusses a new stabilization technique used to measure acoustic signals over a large range of operating temperatures. The new stabilization technique is based on a diaphragm-based extrinsic Fabry–Perot interferometer (EFPI) acoustic sensor and feedback stabilization using a tunable fiber laser. The feedback stabilization technique is used to control the output wavelength of the tunable fiber laser to operate in the linear range of the diaphragm-based EFPI acoustic sensor. This method has no signal detection bandwidth limit, a high tuning speed, and a large tunable range. To verify the performance of the stabilization technique, we measured the output of the sensor by changing the environmental temperature, and the experimental results demonstrate that this system can stabilize the operating point of the sensor very well. An acoustic signal was successfully detected using a photoacoustic spectrometer system, and the fade-out problem was solved.

We demonstrate a method for quantitative phase (QP) imaging without 2π ambiguity using a spectral domain phase microscopy system. The method is capable of QP measurement of a large dynamic range with a high sensitivity. We determine an integer multiple of 2π to correct wrapped phases by calculating the phase shift difference between the detected interference fringe and simulated fringes. The presented method is quantitatively verified by measuring the vibration generated by a piezo linear stage and mapping the surface topography of a slanted mirror. QP imaging of red blood cells is also performed to demonstrate the method's capacity and application in biological imaging.