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.

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.

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.

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.

Cholesterol esterification inhibition and gemcitabine synergistically suppress pancreatic ductal adenocarcinoma proliferation.

Recent advances have recognized metabolic reprogramming as an underlying mechanism for cancer drug resistance. However, the role of cholesterol metabolism in drug resistance remain elusive. Herein, we report an increased accumulation of cholesteryl ester in gemcitabine-resistant pancreatic ductal adenocarcinoma (PDAC) cells. A potent inhibitor of acyl-CoA cholesterol acyltransferase-1 (ACAT-1), avasimibe, effectively suppressed proliferation of gemcitabine-resistant PDAC cells. Combination of avasimibe and gemcitabine showed strong synergistic effect in suppressing PDAC cell viability in vitro and tumor growth in vivo. Immunoblotting analysis suggests downregulation of Akt by avasimibe is likely to contribute to the synergism. Collectively, our study demonstrates a new combinational therapeutic strategy to overcome gemcitabine resistance for PDAC treatment.

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.

A hybrid registration-based method for whole-body micro-CT mice images.

The widespread use of whole-body small animal in vivo imaging in preclinical research has proposed the new demands on imaging processing and analysis. Micro-CT provides detailed anatomical structural information for continuous detection and different individual comparison, but the body deformation happened during different data acquisition needs sophisticated registration. In this paper, we propose a hybrid method for registering micro-CT mice images, which combines the strengths of point-based and intensity-based registration methods. Point-based non-rigid method using thin-plate spline robust point matching algorithm is utilized to acquire a coarse registration. And then intensity-based non-rigid method using normalized mutual information, Halton sampling and adaptive stochastic gradient descent optimization is used to acquire precise registration. Two accuracy metrics, Dice coefficient and average surface distance are used to do the quantitative evaluation. With the intra- and intersubject micro-CT mice images registration assessment, the hybrid method has been proven capable of excellent performance on micro-CT mice images registration.

In vivo quantitative evaluation of vascular parameters for angiogenesis based on sparse principal component analysis and aggregated boosted trees.

To solve the multicollinearity issue and unequal contribution of vascular parameters for the quantification of angiogenesis, we developed a quantification evaluation method of vascular parameters for angiogenesis based on in vivo micro-CT imaging of hindlimb ischemic model mice. Taking vascular volume as the ground truth parameter, nine vascular parameters were first assembled into sparse principal components (PCs) to reduce the multicolinearity issue. Aggregated boosted trees (ABTs) were then employed to analyze the importance of vascular parameters for the quantification of angiogenesis via the loadings of sparse PCs. The results demonstrated that vascular volume was mainly characterized by vascular area, vascular junction, connectivity density, segment number and vascular length, which indicated they were the key vascular parameters for the quantification of angiogenesis. The proposed quantitative evaluation method was compared with both the ABTs directly using the nine vascular parameters and Pearson correlation, which were consistent. In contrast to the ABTs directly using the vascular parameters, the proposed method can select all the key vascular parameters simultaneously, because all the key vascular parameters were assembled into the sparse PCs with the highest relative importance.

Molecular Optical Simulation Environment (MOSE): a platform for the simulation of light propagation in turbid media.

The study of light propagation in turbid media has attracted extensive attention in the field of biomedical optical molecular imaging. In this paper, we present a software platform for the simulation of light propagation in turbid media named the "Molecular Optical Simulation Environment (MOSE)". Based on the gold standard of the Monte Carlo method, MOSE simulates light propagation both in tissues with complicated structures and through free-space. In particular, MOSE synthesizes realistic data for bioluminescence tomography (BLT), fluorescence molecular tomography (FMT), and diffuse optical tomography (DOT). The user-friendly interface and powerful visualization tools facilitate data analysis and system evaluation. As a major measure for resource sharing and reproducible research, MOSE aims to provide freeware for research and educational institutions, which can be downloaded at http://www.mosetm.net.

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.

Anti-CD30-targeted gold nanoparticles for photothermal therapy of L-428 Hodgkin's cell.

PURPOSE: Due to the efficient bioconjugation and highly photothermal effect, gold nanoparticles can stain receptor-overexpressing cancer cells through specific targeting of ligands to receptors, strongly absorb specific light and efficiently convert it into heat based on the property of surface plasmon resonance, and then induce the localized protein denaturation and cell death. METHODS: Two gold nanoparticle-antibody conjugates, gold-BerH2 antibody (anti-CD30 receptor) and gold-ACT1 antibody (anti-CD25-receptor), were synthesized. Gold-BerH2 conjugates can specifically bind to the surface of L-428 Hodgkin's cells, and gold-ACT1 conjugates were used for the control. The gold nanoparticle-induced L-428 cell-killing experiments were implemented with different experimental parameters. RESULTS: At a relatively low concentration of gold and short incubation time, the influence of cytotoxicity of gold on cell viability can be overlooked. Under laser irradiation at suitable power, the high killing efficiency of gold-targeted L-428 cells was achieved, but little damage was done to nontargeted cancer cells. CONCLUSION: Gold nanoparticle-mediated photothermal therapy provides a relatively safe therapeutic technique for cancer treatment.

Comparative studies of l(p)-regularization-based reconstruction algorithms for bioluminescence tomography.

Inverse source reconstruction is the most challenging aspect of bioluminescence tomography (BLT) because of its ill-posedness. Although many efforts have been devoted to this problem, so far, there is no generally accepted method. Due to the ill-posedness property of the BLT inverse problem, the regularization method plays an important role in the inverse reconstruction. In this paper, six reconstruction algorithms based on l(p) regularization are surveyed. The effects of the permissible source region, measurement noise, optical properties, tissue specificity and source locations on the performance of the reconstruction algorithms are investigated using a series of single source experiments. In order to further inspect the performance of the reconstruction algorithms, we present the double sources and the in vivo mouse experiments to study their resolution ability and potential for a practical heterogeneous mouse experiment. It is hoped to provide useful guidance on algorithm development and application in the related fields.

Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection.

Bioluminescence tomography (BLT) has been successfully applied to the detection and therapeutic evaluation of solid cancers. However, the existing BLT reconstruction algorithms are not accurate enough for cavity cancer detection because of neglecting the void problem. Motivated by the ability of the hybrid radiosity-diffusion model (HRDM) in describing the light propagation in cavity organs, an HRDM-based BLT reconstruction algorithm was provided for the specific problem of cavity cancer detection. HRDM has been applied to optical tomography but is limited to simple and regular geometries because of the complexity in coupling the boundary between the scattering and void region. In the provided algorithm, HRDM was first applied to three-dimensional complicated and irregular geometries and then employed as the forward light transport model to describe the bioluminescent light propagation in tissues. Combining HRDM with the sparse reconstruction strategy, the cavity cancer cells labeled with bioluminescent probes can be more accurately reconstructed. Compared with the diffusion equation based reconstruction algorithm, the essentiality and superiority of the HRDM-based algorithm were demonstrated with simulation, phantom and animal studies. An in vivo gastric cancer-bearing nude mouse experiment was conducted, whose results revealed the ability and feasibility of the HRDM-based algorithm in the biomedical application of gastric cancer detection.

Three-dimensional noninvasive monitoring iodine-131 uptake in the thyroid using a modified Cerenkov luminescence tomography approach.

BACKGROUND: Cerenkov luminescence tomography (CLT) provides the three-dimensional (3D) radiopharmaceutical biodistribution in small living animals, which is vital to biomedical imaging. However, existing single-spectral and multispectral methods are not very efficient and effective at reconstructing the distribution of the radionuclide tracer. In this paper, we present a semi-quantitative Cerenkov radiation spectral characteristic-based source reconstruction method named the hybrid spectral CLT, to efficiently reconstruct the radionuclide tracer with both encouraging reconstruction results and less acquisition and image reconstruction time. METHODOLOGY/PRINCIPAL FINDINGS: We constructed the implantation mouse model implanted with a 400 µCi Na(131)I radioactive source and the physiological mouse model received an intravenous tail injection of 400 µCi radiopharmaceutical Iodine-131 (I-131) to validate the performance of the hybrid spectral CLT and compared the reconstruction results, acquisition, and image reconstruction time with that of single-spectral and multispectral CLT. Furthermore, we performed 3D noninvasive monitoring of I-131 uptake in the thyroid and quantified I-131 uptake in vivo using hybrid spectral CLT. Results showed that the reconstruction based on the hybrid spectral CLT was more accurate in localization and quantification than using single-spectral CLT, and was more efficient in the in vivo experiment compared with multispectral CLT. Additionally, 3D visualization of longitudinal observations suggested that the reconstructed energy of I-131 uptake in the thyroid increased with acquisition time and there was a robust correlation between the reconstructed energy versus the gamma ray counts of I-131 (r(2) = 0.8240). The ex vivo biodistribution experiment further confirmed the I-131 uptake in the thyroid for hybrid spectral CLT. CONCLUSIONS/SIGNIFICANCE: Results indicated that hybrid spectral CLT could be potentially used for thyroid imaging to evaluate its function and monitor its treatment for thyroid cancer.

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.

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.

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.

Automated motion correction for in vivo optical projection tomography.

In in vivo optical projection tomography (OPT), object motion will significantly reduce the quality and resolution of the reconstructed image. Based on the well-known Helgason-Ludwig consistency condition (HLCC), we propose a novel method for motion correction in OPT under parallel beam illumination. The method estimates object motion from projection data directly and does not require any other additional information, which results in a straightforward implementation. We decompose object movement into translation and rotation, and discuss how to correct for both translation and general motion simultaneously. Since finding the center of rotation accurately is critical in OPT, we also point out that the system's geometrical offset can be considered as object translation and therefore also calibrated through the translation estimation method. In order to verify the algorithm effectiveness, both simulated and in vivo OPT experiments are performed. Our results demonstrate that the proposed approach is capable of decreasing movement artifacts significantly thus providing high quality reconstructed images in the presence of object motion.

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.