Loss of Wnt16 Leads to Skeletal Deformities and Downregulation of Bone Developmental Pathway in Zebrafish.

Wingless-type MMTV integration site family, member 16 (wnt16), is a wnt ligand that participates in the regulation of vertebrate skeletal development. Studies have shown that wnt16 can regulate bone metabolism, but its molecular mechanism remains largely undefined. We obtained the wnt16-/- zebrafish model using the CRISPR-Cas9-mediated gene knockout screen with 11 bp deletion in wnt16, which led to the premature termination of amino acid translation and significantly reduced wnt16 expression, thus obtaining the wnt16-/- zebrafish model. The expression of wnt16 in bone-related parts was detected via in situ hybridization. The head, spine, and tail exhibited significant deformities, and the bone mineral density and trabecular bone decreased in wnt16-/- using light microscopy and micro-CT analysis. RNA sequencing was performed to explore the differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that the down-regulated DEGs are mainly concentrated in mTOR, FoxO, and VEGF pathways. Protein-protein interaction (PPI) network analysis was performed with the detected DEGs. Eight down-regulated DEGs including akt1, bnip4, ptena, vegfaa, twsg1b, prkab1a, prkab1b, and pla2g4f.2 were validated by qRT-PCR and the results were consistent with the RNA-seq data. Overall, our work provides key insights into the influence of wnt16 gene on skeletal development.

3D Fusion Framework for Infarction and Angiogenesis Analysis in a Myocardial Infarct Minipig Model.

The combination of different modality images can provide detailed and comprehensive information for the prognostic assessment and therapeutic strategy of patients with ischemic heart disease. In this study, a 3D fusion framework is designed to integrate coronary computed tomography (CT) angiography (CTA), 2-deoxy-2-[18F]fluoro-D-glucose ([18F]DG) positron emission tomography (PET)/CT, and [68Ga]-1,4,7-triazacyclononane-1,4,7-triacetic acid-(Arg-Gly-Asp)2 ([68Ga]-NOTA-PRGD2) PET/CT images of the myocardial infarction model in minipigs. First, the structural anatomy of the heart in coronary CTA and CT is segmented using a multi-atlas-based method. Then, the hearts are registered using the B-spline-based free form deformation. Finally, the [18F]DG and [68Ga]-NOTA-PRGD2 signals are mapped into the heart in coronary CTA, which produces a single fusion image to delineate both the cardiac structural anatomy and the functional information of myocardial viability and angiogenesis. Heart segmentation demonstrates high accuracy with good agreement between manual delineation and automatic segmentation. The fusion result intuitively reflects the extent of the [18F]DG uptake defect as well as the location where the [68Ga]-NOTA-PRGD2 signal appears. The fusion result verified the occurrence of angiogenesis based on the in vivo noninvasive molecular imaging approach. The presented framework is helpful in facilitating the study of the relationship between infarct territories and blocked coronary arteries as well as angiogenesis.

Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.

Background: The immune microenvironment assumes a significant role in the pathogenesis of osteoarthritis (OA). However, the current biomarkers for the diagnosis and treatment of OA are not satisfactory. Our study aims to identify new OA immune-related biomarkers to direct the prevention and treatment of OA using multi-omics data. Methods: The discovery dataset integrated the GSE89408 and GSE143514 datasets to identify biomarkers that were significantly associated with the OA immune microenvironment through multiple machine learning methods and weighted gene co-expression network analysis (WGCNA). The identified signature genes were confirmed using two independent validation datasets. We also performed a two-sample mendelian randomization (MR) study to generate causal relationships between biomarkers and OA using OA genome-wide association study (GWAS) summary data (cases n = 24,955, controls n = 378,169). Inverse-variance weighting (IVW) method was used as the main method of causal estimates. Sensitivity analyses were performed to assess the robustness and reliability of the IVW results. Results: Three signature genes (FCER1G, HLA-DMB, and HHLA-DPA1) associated with the OA immune microenvironment were identified as having good diagnostic performances, which can be used as biomarkers. MR results showed increased levels of FCER1G (OR = 1.118, 95% CI 1.031-1.212, P = 0.041), HLA-DMB (OR = 1.057, 95% CI 1.045 -1.069, P = 1.11E-21) and HLA-DPA1 (OR = 1.030, 95% CI 1.005-1.056, P = 0.017) were causally and positively associated with the risk of developing OA. Conclusion: The present study identified the 3 potential immune-related biomarkers for OA, providing new perspectives for the prevention and treatment of OA. The MR study provides genetic support for the causal effects of the 3 biomarkers with OA and may provide new insights into the molecular mechanisms leading to the development of OA.

Cerenkov luminescence tomography of aminopeptidase N (APN/CD13) expression in mice bearing HT1080 tumors.

In vivo imaging of aminopeptidase N (APN/CD13) expression is crucial for the early detection of cancer. This study attempted to show that APN/CD13 expression can be imaged and quantified with novel Cerenkov luminescence tomography (CLT). Na131I with various activities was placed at different depths in a tissue-mimicking phantom, and various porcine tissues and luminescent images were acquired. The binding of 131I-NGR with human fibrosarcoma HT1080 and human colon cancer HT-29 cells was detected with Cerenkov luminescence imaging (CLI). Nude mice bearing HT-1080 tumors were imaged after injection with 131I-NGR using both planar and tomographic CLI methods. The penetration depth increased with ascending activity of Na131I. There was a robust linear correlation between the optical signal intensity and the HT1080 cell numbers (r2 = .9691), as well as the activity (r2 = .9860). The three-dimensional visualization CLT results clearly showed that 131I-NGR uptake in tumor tissues represented a high expression of the APN/CD13 receptor. CLT also allowed quantifying 131I-NGR uptake in tumor tissues showing an average activity of 0.1388 ± 4.6788E-6 MBq in tumor tissues. Our study indicated that 131I-NGR combined with CLT allowed us to image and quantify tumor-associated APN/CD13 expression noninvasively. The promising CLT technique could be potentially used for sensitively evaluating tumor angiogenesis in vivo.

Influence investigation of a void region on modeling light propagation in a heterogeneous medium.

A void region exists in some biological tissues, and previous studies have shown that inaccurate images would be obtained if it were not processed. A hybrid radiosity-diffusion method (HRDM) that couples the radiosity theory and the diffusion equation has been proposed to deal with the void problem and has been well demonstrated in two-dimensional and three-dimensional (3D) simple models. However, the extent of the impact of the void region on the accuracy of modeling light propagation has not been investigated. In this paper, we first implemented and verified the HRDM in 3D models, including both the regular geometries and a digital mouse model, and then investigated the influences of the void region on modeling light propagation in a heterogeneous medium. Our investigation results show that the influence of the region can be neglected when the size of the void is less than a certain range, and other cases must be taken into account.

Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis.

Background: Both obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. This study aims to investigate the common gene signatures and biological pathways in OB and PD through bioinformatics analysis of publicly available transcriptome datasets. Methods: The RNA expression profile datasets of OB (GSE104815) and PD (GSE106090) were used as training data, and GSE152991 and GSE16134 as validation data. After screening for differentially expressed genes (DEGs) shared by OB and PD, gene enrichment analysis, protein-protein interaction (PPI) network construction, GeneMANIA analysis, immune infiltration analysis and gene set enrichment analysis (GSEA) were performed. In addition, receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the hub gene. Finally, we constructed the hub gene-associated TF-miRNA-mRNA regulatory network. Results: We identified a total of 147 DEGs shared by OB and PD (38 down-regulated and 109 up-regulated). Functional analysis showed that these genes were mainly enriched in immune-related pathways such as B cell receptor signalling, leukocyte migration and cellular defence responses. 14 hub genes (FGR, MNDA, NCF2, FYB1, EVI2B, LY86, IGSF6, CTSS, CXCR4, LCK, FCN1, CXCL2, P2RY13, MMP7) showed high sensitivity and specificity in the ROC curve analysis. The results of immune infiltration analysis showed that immune cells such as macrophages, activated CD4 T cells and immune B cells were present at high infiltration levels in both OB and PD samples.The results of GeneMANIA analysis and GSEA analysis suggested that five key genes (FGR, LCK, FYB1, LY86 and P2RY13) may be strongly associated with macrophages. Finally, we constructed a TF-miRNA-mRNA regulatory network consisting of 233 transcription factors (TFs), 8 miRNAs and 14 mRNAs based on the validated information obtained from the database. Conclusions: Five key genes (FGR, LCK, FYB1, LY86, P2RY13) may be important biomarkers of OB and PD. These genes may play an important role in the pathogenesis of OB and PD by affecting macrophage activity and participating in immune regulation and inflammatory responses.

Solving inverse problems for optical scanning holography using an adaptively iterative shrinkage-thresholding algorithm.

Optical scanning holography (OSH) records a three-dimensional object into a two-dimensional hologram through two-dimensional optical scanning. The recovery of sectional images from the hologram, termed as an inverse problem, has been previously implemented by conventional methods as well as the use of l2 norm. However, conventional methods require time consuming processing of section by section without eliminating the defocus noise and the l2 norm method often suffers from the drawback of over-smoothing. Moreover, these methods require the whole hologram data (real and imaginary parts) to eliminate the twin image noise, whose computation complexity and the sophisticated post-processing are far from desirable. To handle these difficulties, an adaptively iterative shrinkage-thresholding (AIST) algorithm, characterized by fast computation and adaptive iteration, is proposed in this paper. Using only a half hologram data, the proposed method obtained satisfied on-axis reconstruction free of twin image noise. The experiments of multi-planar reconstruction and improvement of depth of focus further validate the feasibility and flexibility of our proposed AIST algorithm.

Multilevel, hybrid regularization method for reconstruction of fluorescent molecular tomography.

In this paper, a multilevel, hybrid regularization method is presented for fluorescent molecular tomography (FMT) based on the hp-finite element method (hp-FEM) with a continuous wave. The hybrid regularization method combines sparsity regularization and Landweber iterative regularization to improve the stability of the solution of the ill-posed inverse problem. In the first coarse mesh level, considering the fact that the fluorescent probes are sparsely distributed in the entire reconstruction region in most FMT applications, the sparse regularization method is employed to take full advantage of this sparsity. In the subsequent refined mesh levels, since the reconstruction region is reduced and the initial value of the unknown parameters is provided from the previous mesh, these mesh levels seem to be different from the first level. As a result, the Landweber iterative regularization method is applied for reconstruction. Simulation experiments on a 3D digital mouse atlas and physical experiments on a phantom are conducted to evaluate the performance of our method. The reconstructed results show the potential and feasibility of the proposed approach.

Mapping of bioluminescent images onto CT volume surface for dual-modality BLT and CT imaging.

We present a method for mapping the two-dimensional (2D) bioluminescent images (BLIs) onto a three-dimensional (3D) body surface derived from the computed tomography (CT) volume data. This mapping includes two closely-related steps, the spatial registration of the 2D BLIs into the coordinate system of the CT volume data and the light flux recovering on the body surface from BLIs. By labeling markers on the body surface, we proposed an effective registration method to achieve the spatial position alignment. The subsequent light flux recovering is presented based on the inverse process of the free-space light transport model and taking the influence of the camera lens diaphragm into account. Incorporating the mapping procedure into the bioluminescence tomography (BLT) reconstruction, we developed a dual-modality BLT and CT imaging framework to provide both optical and anatomical information. The accuracy of the registration and the light flux recovering methods were evaluated via physical phantom experiments. The registration method was found to have a mean error of 0.41 mm and 0.35 mm in horizontal and vertical direction, and the accuracy of the light flux recovering method was below 5%. Furthermore, we evaluated the performance of the dual-modality BLT/CT imaging framework using a mouse phantom. Preliminary results revealed the potential and feasibility of the dual-modality imaging framework.

Graphics processing unit parallel accelerated solution of the discrete ordinates for photon transport in biological tissues.

As a widely used numerical solution for the radiation transport equation (RTE), the discrete ordinates can predict the propagation of photons through biological tissues more accurately relative to the diffusion equation. The discrete ordinates reduce the RTE to a serial of differential equations that can be solved by source iteration (SI). However, the tremendous time consumption of SI, which is partly caused by the expensive computation of each SI step, limits its applications. In this paper, we present a graphics processing unit (GPU) parallel accelerated SI method for discrete ordinates. Utilizing the calculation independence on the levels of the discrete ordinate equation and spatial element, the proposed method reduces the time cost of each SI step by parallel calculation. The photon reflection at the boundary was calculated based on the results of the last SI step to ensure the calculation independence on the level of the discrete ordinate equation. An element sweeping strategy was proposed to detect the calculation independence on the level of the spatial element. A GPU parallel frame called the compute unified device architecture was employed to carry out the parallel computation. The simulation experiments, which were carried out with a cylindrical phantom and numerical mouse, indicated that the time cost of each SI step can be reduced up to a factor of 228 by the proposed method with a GTX 260 graphics card.

GPU-based Monte Carlo simulation for light propagation in complex heterogeneous tissues.

As the most accurate model for simulating light propagation in heterogeneous tissues, Monte Carlo (MC) method has been widely used in the field of optical molecular imaging. However, MC method is time-consuming due to the calculations of a large number of photons propagation in tissues. The structural complexity of the heterogeneous tissues further increases the computational time. In this paper we present a parallel implementation for MC simulation of light propagation in heterogeneous tissues whose surfaces are constructed by different number of triangle meshes. On the basis of graphics processing units (GPU), the code is implemented with compute unified device architecture (CUDA) platform and optimized to reduce the access latency as much as possible by making full use of the constant memory and texture memory on GPU. We test the implementation in the homogeneous and heterogeneous mouse models with a NVIDIA GTX 260 card and a 2.40GHz Intel Xeon CPU. The experimental results demonstrate the feasibility and efficiency of the parallel MC simulation on GPU.

Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method.

In this paper, we present an incomplete variables truncated conjugate gradient (IVTCG) method for bioluminescence tomography (BLT). Considering the sparse characteristic of the light source and insufficient surface measurement in the BLT scenarios, we combine a sparseness-inducing (ℓ1 norm) regularization term with a quadratic error term in the IVTCG-based framework for solving the inverse problem. By limiting the number of variables updated at each iterative and combining a variable splitting strategy to find the search direction more efficiently, it obtains fast and stable source reconstruction, even without a priori information of the permissible source region and multispectral measurements. Numerical experiments on a mouse atlas validate the effectiveness of the method. In vivo mouse experimental results further indicate its potential for a practical BLT system.

Experimental Cerenkov luminescence tomography of the mouse model with SPECT imaging validation.

Optical molecular imaging resulting from Cerenkov radiation has become a motivating topic recently and will potentially open new avenues for the study of small animal imaging. Cerenkov-based optical imaging taken from living animals in vivo has been studied with two-dimensional (2D) planar geometry and three-dimensional (3D) homogeneous mouse model. In this study, we performed 3D Cerenkov-based luminescence tomography (CLT) using a heterogeneous mouse model with an implanted Na(131)I radioactive source, which provided the accurate location for the reconstructed source. Furthermore, single photon emission computed tomography (SPECT) was utilized to verify the results of 3D CLT. We reconstructed the localization and intensity of an embedded radioactive source with various concentrations, and established a quantitative relationship between the radiotracer activity and the reconstructed intensity. The results showed the ability of in vivo CLT to recover the radioactive probe distribution in the heterogeneous mouse model and the potential of a SPECT imaging validation strategy to verify the results of optical molecular tomography.

In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models.

Bioluminescence tomography (BLT) is a new optical molecular imaging modality, which can monitor both physiological and pathological processes by using bioluminescent light-emitting probes in small living animal. Especially, this technology possesses great potential in drug development, early detection, and therapy monitoring in preclinical settings. In the present study, we developed a dual modality BLT prototype system with Micro-computed tomography (MicroCT) registration approach, and improved the quantitative reconstruction algorithm based on adaptive hp finite element method (hp-FEM). Detailed comparisons of source reconstruction between the heterogeneous and homogeneous mouse models were performed. The models include mice with implanted luminescence source and tumor-bearing mice with firefly luciferase report gene. Our data suggest that the reconstruction based on heterogeneous mouse model is more accurate in localization and quantification than the homogeneous mouse model with appropriate optical parameters and that BLT allows super-early tumor detection in vivo based on tomographic reconstruction of heterogeneous mouse model signal.

3D reconstruction of light flux distribution on arbitrary surfaces from 2D multi-photographic images.

Optical tomography can demonstrate accurate three-dimensional (3D) imaging that recovers the 3D spatial distribution and concentration of the luminescent probes in biological tissues, compared with planar imaging. However, the tomographic approach is extremely difficult to implement due to the complexity in the reconstruction of 3D surface flux distribution from multi-view two dimensional (2D) measurements on the subject surface. To handle this problem, a novel and effective method is proposed in this paper to determine the surface flux distribution from multi-view 2D photographic images acquired by a set of non-contact detectors. The method is validated with comparison experiments involving both regular and irregular surfaces. Reconstruction of the inside probes based on the reconstructed surface flux distribution further demonstrates the potential of the proposed method in its application in optical tomography.

Generalized free-space diffuse photon transport model based on the influence analysis of a camera lens diaphragm.

The camera lens diaphragm is an important component in a noncontact optical imaging system and has a crucial influence on the images registered on the CCD camera. However, this influence has not been taken into account in the existing free-space photon transport models. To model the photon transport process more accurately, a generalized free-space photon transport model is proposed. It combines Lambertian source theory with analysis of the influence of the camera lens diaphragm to simulate photon transport process in free space. In addition, the radiance theorem is also adopted to establish the energy relationship between the virtual detector and the CCD camera. The accuracy and feasibility of the proposed model is validated with a Monte-Carlo-based free-space photon transport model and physical phantom experiment. A comparison study with our previous hybrid radiosity-radiance theorem based model demonstrates the improvement performance and potential of the proposed model for simulating photon transport process in free space.

Advancing Image Understanding in Poor Visibility Environments: A Collective Benchmark Study.

Existing enhancement methods are empirically expected to help the high-level end computer vision task: however, that is observed to not always be the case in practice. We focus on object or face detection in poor visibility enhancements caused by bad weathers (haze, rain) and low light conditions. To provide a more thorough examination and fair comparison, we introduce three benchmark sets collected in real-world hazy, rainy, and low-light conditions, respectively, with annotated objects/faces. We launched the UG2+ challenge Track 2 competition in IEEE CVPR 2019, aiming to evoke a comprehensive discussion and exploration about whether and how low-level vision techniques can benefit the high-level automatic visual recognition in various scenarios. To our best knowledge, this is the first and currently largest effort of its kind. Baseline results by cascading existing enhancement and detection models are reported, indicating the highly challenging nature of our new data as well as the large room for further technical innovations. Thanks to a large participation from the research community, we are able to analyze representative team solutions, striving to better identify the strengths and limitations of existing mindsets as well as the future directions.

A source reconstruction algorithm based on adaptive hp-FEM for bioluminescence tomography.

As a novel modality of molecular imaging, bioluminescence tomography (BLT) is used to in vivo observe and measure the biological process at cellular and molecular level in small animals. The core issue of BLT is to determine the distribution of internal bioluminescent sources from optical measurements on external surface. In this paper, a new algorithm is presented for BLT source reconstruction based on adaptive hp-finite element method. Using adaptive mesh refinement strategy and intelligent permissible source region, we can obtain more accurate information about the location and density of sources, with the robustness, stability and efficiency improved. Numerical simulations and physical experiment were both conducted to verify the performance of the proposed algorithm, where the optical data on phantom surface were obtained via Monte Carlo simulation and CCD camera detection, respectively. The results represent the merits and potential of our algorithm for BLT source reconstruction.

A study of photon propagation in free-space based on hybrid radiosity-radiance theorem.

Noncontact optical imaging has attracted increasing attention in recent years due to its significant advantages on detection sensitivity, spatial resolution, image quality and system simplicity compared with contact measurement. However, photon transport simulation in free-space is still an extremely challenging topic for the complexity of the optical system. For this purpose, this paper proposes an analytical model for photon propagation in free-space based on hybrid radiosity-radiance theorem (HRRT). It combines Lambert's cosine law and the radiance theorem to handle the influence of the complicated lens and to simplify the photon transport process in the optical system. The performance of the proposed model is evaluated and validated with numerical simulations and physical experiments. Qualitative comparison results of flux distribution at the detector are presented. In particular, error analysis demonstrates the feasibility and potential of the proposed model for simulating photon propagation in free-space.

Imaging of cancer cells by multiphoton microscopy using gold nanoparticles and fluorescent dyes.

Due to their unique optical properties, optical probes, including metal nanoparticles (NPs) and fluorescent dyes, are increasingly used as labeling tools in biological imaging. Using multiphoton microscopy and fluorescence lifetime imaging (FLIM) at 750-nm excitation, we recorded intensity and FLIM images from gold NPs (30 nm) and the fluorescent dye Alexa 488 (A488) conjugated with monoclonal ACT-1 antibodies as well as Hoechst 33258 (H258) after incubation with the lymphoma cell line (Karpas-299). From the FLIM images, we can easily discriminate the imaging difference between cells and optical probes according to their distinct fluorescence lifetimes (cellular autofluorescence: 1 to 2 ns; gold NPs: <0.02 ns; A488: 3.5 ns; H258: 2.5 ns). The NP-ACT-1 and A488-ACT-1 conjugates were bound homogeneously on the surface of cells, whereas H258 stained the cell nucleus. We demonstrate that the emission intensity of gold NPs is about ten times stronger than that of the autofluorescence of Karpas-299 cells at the same excitation power. Compared with fluorescent dyes, stronger emission is also observed from gold NPs. Together with their high photostability, these observations suggest that gold NPs are a viable alternative to fluorescent dyes for cellular imaging and cancer diagnosis.