Deep Learning of Morphologic Correlations To Accurately Classify CD4+ and CD8+ T Cells by Diffraction Imaging Flow Cytometry.

The two major subtypes of human T cells, CD4+ and CD8+, play important roles in adaptive immune response by their diverse functions. To understand the structure-function relation at the single cell level, we isolated 2483 CD4+ and 2450 CD8+ T cells from fresh human splenocytes by immunofluorescent sorting and investigated their morphologic relations to the surface CD markers by acquisition and analysis of cross-polarized diffraction image (p-DI) pairs. A deep neural network of DINet-R has been built to extract 2560 features across multiple pixel scales of a p-DI pair per imaged cell. We have developed a novel algorithm to form a matrix of Pearson correlation coefficients by these features for selection of a support cell set with strong morphologic correlation in each subtype. The p-DI pairs of support cells exhibit significant pattern differences between the two subtypes defined by CD markers. To explore the relation between p-DI features and CD markers, we divided each subtype into two groups of A and B using the two support cell sets. The A groups comprise 90.2% of the imaged T cells and classification of them by DINet-R yields an accuracy of 97.3 ± 0.40% between the two subtypes. Analysis of depolarization ratios further reveals the significant differences in molecular polarizability between the two subtypes. These results prove the existence of a strong structure-function relation for the two major T cell subtypes and demonstrate the potential of diffraction imaging flow cytometry for accurate and label-free classification of T cell subtypes.

Dura-splitting versus a combined technique for Chiari malformation type I complicated with syringomyelia.

BACKGROUND: Surgical approaches for Chiari malformation type I (CM-I) complicated with syringomyelia (SM) are controversial, so we assessed the efficacy and safety of two widely used procedures. METHODS: We retrospectively analyzed results from posterior fossa decompression (PFD) using bony decompression with dura-splitting or a combined technique (duraplasty with arachnoid dissection and coagulation of the herniated tonsils) for CM-I associated with SM between Jan 2008 and Feb 2016. Patients were followed up for at least one year. General data, primary outcomes (symptom improvement, syrinx reductions, and complications) and secondary outcomes (operating time, blood loss, postoperative hospital stay) for each procedure were compared. RESULTS: Of the 49 patients treated, 17 had dura-splitting decompression and 32 had the combined technique. There were no significant differences in general data. The combined technique was significantly superior to dura-splitting for long-term syrinx reductions (length, 100.03 ± 44.79 vs 72.73 ± 34.79 mm, p = 0.040; diameter, 8.09 ± 3.46 vs 5.73 ± 3.02 mm, p = 0.026) and symptom improvement (75.00% vs 47.06%, p = 0.036). No postoperative complications occurred during dura-splitting cases; however, complications occurred in 9 combined technique cases (31.25%, p = 0.010) and surgical time was longer for the combined technique (248.03 ± 60.12 vs 167.94 ± 60.11 min, p < 0.001). CONCLUSIONS: The combined technique improved long-term symptoms and reduced syringes compared to dura-splitting; however, postoperative complications are more likely.

Resolving power of diffraction imaging with an objective: a numerical study.

Diffraction imaging in the far-field can detect 3D morphological features of an object for its coherent nature. We describe methods for accurate calculation and analysis of diffraction images of scatterers of single and double spheres by an imaging unit based on microscope objective at non-conjugate positions. A quantitative study of the calculated diffraction imaging in spectral domain has been performed to assess the resolving power of diffraction imaging. It has been shown numerically that with coherent illumination of 532 nm in wavelength the imaging unit can resolve single spheres of 2 µm or larger in diameters and double spheres separated by less than 300 nm between their centers.

[Difference of Liver Enzymes in Different Metabolism States of Chronic Hepatitis B].

OBJECTIVE: To analyze the difference of liver enzymes in different metabolism state groups of chronic hepatitis B (CHB). METHODS: We use prospective cross-sectional study to analyze the difference of liver enzymes in different metabolism state groups in 110 cases of CHB, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) and glutamyl transferase (GGT). RESULTS: Regardless of the presence or absence of fatty liver, the levels of ALP and GGT were increased along with the deterioration of glucose metabolism (P<0.05).The levels of ALP and GGT in the presence of fatty liver group were higher than those in the absence of fatty liver group (P<0.05). The levels of AST, ALP and GGT showed the trend of increasing along with the increase of HOMA-IR and the decrease of HOMA-ß. There was no difference of liver enzymes among the groups with or without other metabolism disorder (P>0.05). CONCLUSION: In CHB, abnormal glucose metabolism and fatty liver can lead to the increase of ALP and GGT. The increase of HOMA-IR and the decrease of HOMA-ß may lead to the increase of AST, ALP and GGT. Other metabolism disorder did not show any effect on the level of liver enzymes.

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus.

Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging.

Spectrophotometric determination of turbid optical parameters without using an integrating sphere.

Spectrophotometric quantification of turbidity by multiple optical parameters has wide-ranging applications in material analysis and life sciences. A robust system design needs to combine hardware for precise measurement of light signals with software to accurately model measurement configuration and rapidly solve a sequence of challenging inverse problems. We have developed and validated a design approach and performed system validation based on radiative transfer theory for determination of absorption coefficient, scattering coefficient, and anisotropy factor without using an integrating sphere. Accurate and rapid determination of parameters and spectra is achieved for microsphere suspension samples by combining photodiode-based measurement of four signals with the Monte Carlo simulation and perturbation-based inverse calculations. The three parameters of microsphere suspension samples have been determined from the measured signals as functions of wavelength from 400 to 800 nm and agree with calculated results based on the Mie theory. It has been shown that the inverse problems in the cases of microsphere suspension samples are well posed with convex cost functions to yield unique solutions, and it takes about 1 min to obtain the three parameters per wavelength.

Acquisition of cross-polarized diffraction images and study of blurring effect by one time-delay-integration camera.

Blurred diffraction images acquired from flowing particles affect the measurement of fringe patterns and subsequent analysis. An imaging unit with one time-delay-integration (TDI) camera has been developed to acquire two cross-polarized diffraction images. It was shown that selected elements of Mueller matrix of single scatters can be imaged with pixel matching precision in this configuration. With the TDI camera, the effect of blurring on imaging of scattered light propagating along the side directions was found to be much more significant for biological cells than microspheres. Despite blurring, classification of MCF-7 and K562 cells is feasible since the effect has similar influence on extracted image parameters. Furthermore, image blurring can be useful for analysis of the correlations among texture parameters for characterization of diffraction images from single cells. The results demonstrate that with one TDI camera the polarization diffraction imaging flow cytometry can be significantly improved and angular distribution of selected Mueller matrix elements can be accurately measured for rapid and morphology-based assay of particles and cells without fluorescent labeling.

Polarization imaging and classification of Jurkat T and Ramos B cells using a flow cytometer.

Label-free and rapid classification of cells can have awide range of applications in biology. We report a robust method of polarization diffraction imaging flow cytometry (p-DIFC) for achieving this goal. Coherently scattered light signals are acquired from single cells excited by a polarized laser beam in the form of two cross-polarized diffraction images. Image texture and intensity parameters are extracted with a gray level co-occurrence matrix (GLCM) algorithm to obtain an optimized set of feature parameters as the morphological "fingerprints" for automated cell classification. We selected the Jurkat T cells and Ramos B cells to test the p-DIFC method's capacity for cell classification. After detailed statistical analysis, we found that the optimized feature vectors yield accuracies of classification between the Jurkat and Ramos ranging from 97.8% to 100% among different cell data sets. Confocal imaging and three-dimensional reconstruction were applied to gain insights on the ability of p-DIFC method for classifying the two cell lines of highly similar morphology. Based on these results we conclude that the p-DIFC method has the capacity to discriminate cells of high similarity in their morphology with "fingerprints" features extracted from the diffraction images, which may be attributed to subtle but statistically significant differences in the nucleus-to-cell volume ratio in the case of Jurkat and Ramos cells.

Analysis of diffraction imaging in non-conjugate configurations.

Diffraction imaging of scattered light allows extraction of information on scatterer's morphology. We present a method for accurate simulation of diffraction imaging of single particles by combining rigorous light scattering model with ray-tracing software. The new method has been validated by comparison to measured images of single microspheres. Dependence of fringe patterns on translation of an objective based imager to off-focus positions has been analyzed to clearly understand diffraction imaging with multiple optical elements. The calculated and measured results establish unambiguously that diffraction imaging should be pursued in non-conjugate configurations to ensure accurate sampling of coherent light distribution from the scatterer.

Rapid inverse radiative transfer solver for multiparameter spectrophotometry without integrating sphere.

Significance: Multiparameter spectrophotometry (MPS) provides a powerful tool for accurate characterization of turbid materials in applications such as analysis of material compositions, assay of biological tissues for clinical diagnosis and food safety monitoring. Aim: This work is aimed at development and validation of a rapid inverse solver based on a particle swarm optimization (PSO) algorithm to retrieve the radiative transfer (RT) parameters of absorption coefficient, scattering coefficient and anisotropy factor of a turbid sample. Approach: Monte Carlo (MC) simulations were performed to obtain calculated signals for comparison to the measured ones of diffuse reflectance, diffuse transmittance and forward transmittance. An objective function has been derived and combined with the PSO algorithm to iterate MC simulations for MPS. Results: We have shown that the objective function can significantly reduce the variance in calculated signals by local averaging of an inverse squared error sum function between measured and calculated signals in RT parameter space. For validation of the new objective function for PSO based inverse solver, the RT parameters of 20% Intralipid solutions have been determined from 520 to 1000 nm which took about 2.7 minutes on average to complete signal measurement and inverse calculation per wavelength. Conclusion: The rapid solver enables MPS to be translated into easy-to-use and cost-effective instruments without integrating sphere for material characterization by separating and revealing compositional profiles at the molecular and particulate scales.

Study of low speed flow cytometry for diffraction imaging with different chamber and nozzle designs.

Achieving effective hydrodynamic focusing and flow stability at low speed presents a challenging design task in flow cytometry for studying phenomena such as cell adhesion and diffraction imaging of cells with low-cost cameras. We have developed different designs of flow chamber and sheath nozzle to accomplish the above goal. A 3D computational model of the chambers has been established to simulate the fluid dynamics in different chamber designs and measurements have been performed to determine the velocity and size distributions of the core fluid from the nozzle. Comparison of the simulation data with experimental results shows good agreement. With the computational model significant insights were gained for optimization of the chamber design and improvement of the cell positioning accuracy for study of slow moving cells. The benefit of low flow speed has been demonstrated also by reduced blurring in the diffraction images of single cells. Based on these results, we concluded that the new designs of chamber and sheath nozzle produce stable hydrodynamic focusing of the core fluid at low speed and allow detailed study of cellular morphology under various rheological conditions using the diffraction imaging method.

Analysis of cellular objects through diffraction images acquired by flow cytometry.

It was found that the diffraction images acquired along the side scattering directions with objects in a cell sample contain pattern variations at both the global and local scales. We show here that the global pattern variation is associated with the categorical size and morphological heterogeneity of the imaged objects. An automated image processing method has been developed to separate the acquired diffraction images into three types of global patterns. Combined with previously developed method for quantifying local texture pattern variations, the new method allows fully automated analysis of diffraction images for rapid and label-free classification of cells according to their 3D morphology.

Fast method for inverse determination of optical parameters from two measured signals.

Solving inverse problems requires multiple forward calculations of measured signals. We present a fast method combining graphic processing unit-accelerated Monte Carlo simulations of individual photons and a new perturbation scheme for a 300-fold speedup in comparison to conventional CPU-based approaches. The method allows rapid calculations of the diffuse reflectance and transmittance signals from a turbid sample of absorption coefficient µ(a), scattering coefficient µ(s), and anisotropy factor g based on the principle of correlated sampling. To demonstrate its strong utility, we have applied the method for determining the optical parameters of diluted intralipid samples with satisfactory results.

A novel method of diffraction imaging flow cytometry for sizing microspheres.

We report a novel method of diffraction imaging flow cytometry to measure and analyze size distribution of microspheres. An automated and robust image processing software based on the short-time-Fourier-transform algorithm has been developed to analyze the characteristic and spatially varying oscillations of side scatters recorded as a diffraction image. Our results demonstrate that the new method allows accurate and rapid determination of single microspheres' diameters ranging from 1 to 100 µm. The capacity for analysis of light scattering by two-sphere aggregates has been demonstrated but analytical tools for characterization of aggregates by multiple microspheres remain to be developed.

Photoplethysmographic imaging and analysis of pulsatile pressure wave in palmar artery at 10 wavelengths.

Significance: As a noncontact method, imaging photoplethysmography (iPPG) may provide a powerful tool to measure pulsatile pressure wave (PPW) in superficial arteries and extract biomarkers for monitoring of artery wall stiffness. Aim: We intend to develop a approach for extraction of the very weak cardiac component from iPPG data by identifying locations of strong PPW signals with optimized illumination wavelength and determining pulse wave velocity (PWV). Approach: Monochromatic in vivo iPPG datasets have been acquired from left hands to investigate various algorithms for retrieval of PPW signals, distribution maps and waveforms, and their dependence on arterial location and wavelength. Results: A robust algorithm of pixelated independent component analysis (pICA) has been developed and combined with spatiotemporal filtering to retrieve PPW signals. Spatial distributions of PPW signals have been mapped in 10 wavelength bands from 445 to 940 nm and waveforms were analyzed at multiple locations near the palmar artery tree. At the wavelength of 850 nm selected for timing analysis, we determined PWV values from 12 healthy volunteers in a range of 0.5 to 5.8 m/s across the hand region from wrist to midpalm and fingertip. Conclusions: These results demonstrate the potentials of the iPPG method based on pICA algorithm for translation into a monitoring tool to characterize wall stiffness of superficial artery by rapid and noncontact measurement of PWV and other biomarkers within 10 s.

Analysis of polarized diffraction images of human red blood cells: a numerical study.

We carried out a systematic study on cross-polarized diffraction image (p-DI) pairs of 3098 mature red blood cells (RBCs) using optical cell models with varied morphology, refractive index (RI), and orientation. The influence of cell rotation on texture features of p-DI pairs characterized by the gray-level co-occurrence matrix (GLCM) algorithm was quantitatively analyzed. Correlations between the transverse diameters of RBCs with different RI values and scattering efficiency ratios of s- and p-polarized light were also investigated. The correlations remain strong even for RBCs with significant orientation variations. In addition, we applied a minimum redundancy maximum relevance (mRMR) algorithm to improve the performance of support vector machine (SVM) classifiers. It was demonstrated that a set of selected GLCM parameters allowed for an efficient solution of classification problems of RBCs based on morphology. For 1598 RBCs with varied shapes corresponding to normal or pathological cases, the accuracy of the SVM based classifications increased from 83.8% to 96.8% with the aid of mRMR. These results indicate the strong potential of p-DI data for rapid and accurate screening examinations of RGC shapes in routine clinical tests.

[Expression of proto-oncogene Wip1 in breast cancer and its clinical significance].

OBJECTIVE: To investigate the expression of proto-oncogene Wip1 in breast cancer tissue and its clinical significance. METHODS: Through the uses of semi-RT-PCR, immunohistochemical technique and Western blot, the specimens from 70 patients of breast cancer and 20 normal controls were detected for Wip1 mRNA and protein expression. At the same time, the authors analyzed the relations between the expression of Wip1 in human breast cancer and different clinical pathologic parameters. RESULTS: RT-PCR: The values of gene expression of Wip1 mRNA in breast cancer tissue, pericancerous tissue and normal breast tissue were 0.715 +/- 0.087, 0.175 +/- 0.021 and 0.154 +/- 0.022 respectively. Thus the value of gene expression in breast cancer tissue was significantly higher than that in pericancerous tissue or normal breast tissue (P < 0.01). Immunohistochemistry: The high expression rates of Wip1 protein in breast cancer tissue, pericancerous tissue and normal breast tissue were 62.9% (44/70), 2.9% (2/70) and 0 (0/20) respectively and there was a significant difference among these three different tissues (P < 0.01). Western blot: The relative contents of Wip1 protein in breast cancer tissue, pericancerous tissue and normal breast tissue were 0.688 +/- 0.151, 0.251 +/- 0.043 and 0.234 +/- 0.044 respectively. The relative content of Wip1 protein in breast cancer tissue was significantly higher than that in pericancerous tissue or normal breast tissue (P < 0.01). The high expression of Wip1 protein was negatively correlated with the expression of p53, but it had nothing to do with tumor size, age, tumor staging, axillary lymph node metastasis and expressions of ER and PR. CONCLUSION: The high expression of Wip1 mRNA and its protein in breast cancer tissue may promote the growth of breast cancer. Wip1 may become a new target for therapy of breast cancer.

[The study of different operative style for abdominal aortic aneurysm during surrounding operation].

OBJECTIVE: To compare the the similarities and differences during the surrounding operation of endovascular repair (EVAR) and open surgical repair (OSR) for abdominal aortic aneurysm. METHODS: 112 patients with abdominal aortic aneurysms (AAA) were selected from 2004 to 2009: among them, 66 patients were treated with EVAR, 46 patients with OSR. Data of two groups were collected and analyzed during surrounding operation. RESULTS: Compared to OSR group, the mean blood lost, blood transfusion and intra-operative fluid in EVAR group were significantly less than OSR group (P < 0.05). The mean time of operation, observation period in ICU and being in hospital in EVAR group were shorter than OSR group (P < 0.05). But the cost of hospitalization in EVAR was far higher than that of OSR group (P < 0.05). In short term postoperative complications the OSR group was higher than the EVAR (P < 0.05), however, there was no statistically significant difference in death rate of the two groups during surrounding operation (P > 0.05). CONCLUSION: EVAR has the advantages of mild trauma, less blood loss, quicker recovery after operation, and less disturbance to internal environment. Especially, it is suitable for the patients who can not undergo open surgery repair, but its cost is still higher.

[Analysis of death-related factors of type B aortic dissection treated medically during the acute phase].

OBJECTIVE: To analyze the death-related risk factors of type B aortic dissection treated medically during the acute phase (symptoms presenting within 14 d), and to determine the predictors of surgical indications for acute type B aortic dissection. METHODS: Clinical data of 42 patients with acute type B aortic dissection admitted from January 2007 to May 2009 was retrospectively reviewed. There were 33 male and 9 female with a mean age of (50 +/- 12) years old. Therapy included analgesia, controlled hypotension and beta-receptor blocker, the mortality in acute phase was 33.3% (14/42). Univariate and multivariate logistic regression analyses were performed to identify the predictors of the death in acute phase. RESULTS: In univariate logistic regression analysis, the malperfusion of aortic branches (P = 0.018) and maximum aortic diameter (P = 0.002) were significant predictors of death. In the multivariate logistic regression model, the malperfusion of aortic branches (P = 0.041) and maximum aortic diameter (P = 0.005) were also considered as the significant death-related factors.Risk of death augmented significantly (P = 0.000) when the maximum aortic diameter over 40 mm. CONCLUSION: Malperfusion of aortic branches and the large maximum aortic diameter (> 40 mm) are the indications of surgery or endovascular therapy for acute type B aortic dissection.

Deep learning of diffraction image patterns for accurate classification of five cell types.

Development of label-free methods for accurate classification of cells with high throughput can yield powerful tools for biological research and clinical applications. We have developed a deep neural network of DINet for extracting features from cross-polarized diffraction image (p-DI) pairs on multiple pixel scales to accurately classify cells in five types. A total of 6185 cells were measured by a polarization diffraction imaging flow cytometry (p-DIFC) method followed by cell classification with DINet on p-DI data. The averaged value and SD of classification accuracy were found to be 98.9% ± 1.00% on test data sets for 5-fold training and test. The invariance of DINet to image translation, rotation, and blurring has been verified with an expanded p-DI data set. To study feature-based classification by DINet, two sets of correctly and incorrectly classified cells were selected and compared for each of two prostate cell types. It has been found that the signature features of large dissimilarities between p-DI data of correctly and incorrectly classified cell sets increase markedly from convolutional layers 1 and 2 to layers 3 and 4. These results clearly demonstrate the importance of high-order correlations extracted at the deep layers for accurate cell classification.