Free-standing homochiral 2D monolayers by exfoliation of molecular crystals.

Two-dimensional materials with monolayer thickness and extreme aspect ratios are sought for their high surface areas and unusual physicochemical properties1. Liquid exfoliation is a straightforward and scalable means of accessing such materials2, but has been restricted to sheets maintained by strong covalent, coordination or ionic interactions3-10. The exfoliation of molecular crystals, in which repeat units are held together by weak non-covalent bonding, could generate a greatly expanded range of two-dimensional crystalline materials with diverse surfaces and structural features. However, at first sight, these weak forces would seem incapable of supporting such intrinsically fragile morphologies. Against this expectation, we show here that crystals composed of discrete supramolecular coordination complexes can be exfoliated by sonication to give free-standing monolayers approximately 2.3 nanometres thick with aspect ratios up to approximately 2,500:1, sustained purely by apolar intermolecular interactions. These nanosheets are characterized by atomic force microscopy and high-resolution transmission electron microscopy, confirming their crystallinity. The monolayers possess complex chiral surfaces derived partly from individual supramolecular coordination complex components but also from interactions with neighbours. In this respect, they represent a distinct type of material in which molecular components are all equally exposed to their environment, as if in solution, yet with properties arising from cooperation between molecules, because of crystallinity. This unusual nature is reflected in the molecular recognition properties of the materials, which bind carbohydrates with strongly enhanced enantiodiscrimination relative to individual molecules or bulk three-dimensional crystals.

A dense and U-shaped transformer with dual-domain multi-loss function for sparse-view CT reconstruction.

OBJECTIVE: CT image reconstruction from sparse-view projections is an important imaging configuration for low-dose CT, as it can reduce radiation dose. However, the CT images reconstructed from sparse-view projections by traditional analytic algorithms suffer from severe sparse artifacts. Therefore, it is of great value to develop advanced methods to suppress these artifacts. In this work, we aim to use a deep learning (DL)-based method to suppress sparse artifacts. METHODS: Inspired by the good performance of DenseNet and Transformer architecture in computer vision tasks, we propose a Dense U-shaped Transformer (D-U-Transformer) to suppress sparse artifacts. This architecture exploits the advantages of densely connected convolutions in capturing local context and Transformer in modelling long-range dependencies, and applies channel attention to fusion features. Moreover, we design a dual-domain multi-loss function with learned weights for the optimization of the model to further improve image quality. RESULTS: Experimental results of our proposed D-U-Transformer yield performance improvements on the well-known Mayo Clinic LDCT dataset over several representative DL-based models in terms of artifact suppression and image feature preservation. Extensive internal ablation experiments demonstrate the effectiveness of the components in the proposed model for sparse-view computed tomography (SVCT) reconstruction. SIGNIFICANCE: The proposed method can effectively suppress sparse artifacts and achieve high-precision SVCT reconstruction, thus promoting clinical CT scanning towards low-dose radiation and high-quality imaging. The findings of this work can be applied to denoising and artifact removal tasks in CT and other medical images.

CGP-Uformer: A low-dose CT image denoising Uformer based on channel graph perception.

BACKGROUND: An effective method for achieving low-dose CT is to keep the number of projection angles constant while reducing radiation dose at each angle. However, this leads to high-intensity noise in the reconstructed image, adversely affecting subsequent image processing, analysis, and diagnosis. OBJECTIVE: This paper proposes a novel Channel Graph Perception based U-shaped Transformer (CGP-Uformer) network, aiming to achieve high-performance denoising of low-dose CT images. METHODS: The network consists of convolutional feed-forward Transformer (ConvF-Transformer) blocks, a channel graph perception block (CGPB), and spatial cross-attention (SC-Attention) blocks. The ConvF-Transformer blocks enhance the ability of feature representation and information transmission through the CNN-based feed-forward network. The CGPB introduces Graph Convolutional Network (GCN) for Channel-to-Channel feature extraction, promoting the propagation of information across distinct channels and enabling inter-channel information interchange. The SC-Attention blocks reduce the semantic difference in feature fusion between the encoder and decoder by computing spatial cross-attention. RESULTS: By applying CGP-Uformer to process the 2016 NIH AAPM-Mayo LDCT challenge dataset, experiments show that the peak signal-to-noise ratio value is 35.56 and the structural similarity value is 0.9221. CONCLUSIONS: Compared to the other four representative denoising networks currently, this new network demonstrates superior denoising performance and better preservation of image details.

An Imidazole-Based Triangular Macrocycle for Visual Detection of Formaldehyde.

Highly selective detection of formaldehyde utilizing supramolecules has promising applications in both environmental monitoring and biomonitoring areas. Herein we present a new class of imidazole-based, coordination-driven, self-assembled triangular macrocycles with specific recognition of formaldehyde. The visible fluorescence change to the naked eye from yellow to green-yellow occurs via an unusual reversible hydroxymethylation reaction of imidazole, whereas the corresponding imidazole ligands show no fluorescence change. This study provides a new method for efficient formaldehyde detection by utilizing imidazole-based coordination supramolecules.

RAD-UNet: a Residual, Attention-Based, Dense UNet for CT Sparse Reconstruction.

To suppress the streak artifacts in images reconstructed from sparse-view projections in computed tomography (CT), a residual, attention-based, dense UNet (RAD-UNet) deep network is proposed to achieve accurate sparse reconstruction. The filtered back projection (FBP) algorithm is used to reconstruct the CT image with streak artifacts from sparse-view projections. Then, the image is processed by the RAD-UNet to suppress streak artifacts and obtain high-quality CT image. Those images with streak artifacts are used as the input of the RAD-UNet, and the output-label images are the corresponding high-quality images. Through training via the large-scale training data, the RAD-UNet can obtain the capability of suppressing streak artifacts. This network combines residual connection, attention mechanism, dense connection and perceptual loss. This network can improve the nonlinear fitting capability and the performance of suppressing streak artifacts. The experimental results show that the RAD-UNet can improve the reconstruction accuracy compared with three existing representative deep networks. It may not only suppress streak artifacts but also better preserve image details. The proposed networks may be readily applied to other image processing tasks including image denoising, image deblurring, and image super-resolution.

Non-convex optimization based optimal bone correction for various beam-hardening artifacts in CT imaging.

Tube of X-ray computed tomography (CT) system emitting a polychromatic spectrum of photons leads to beam hardening artifacts such as cupping and streaks, while the metal implants in the imaged object results in metal artifacts in the reconstructed images. The simultaneous emergence of various beam-hardening artifacts degrades the diagnostic accuracy of CT images in clinics. Thus, it should be deeply investigated for suppressing such artifacts. In this study, data consistency condition is exploited to construct an objective function. Non-convex optimization algorithm is employed to solve the optimal scaling factors. Finally, an optimal bone correction is acquired to simultaneously correct for cupping, streaks and metal artifacts. Experimental result acquired by a realistic computer simulation demonstrates that the proposed method can adaptively determine the optimal scaling factors, and then correct for various beam-hardening artifacts in the reconstructed CT images. Especially, as compared to the nonlinear least squares before variable substitution, the running time of the new CT image reconstruction algorithm decreases 82.36% and residual error reduces 55.95%. As compared to the nonlinear least squares after variable substitution, the running time of the new algorithm decreases 67.54% with the same residual error.

LINC00958 promotes endometrial cancer cell proliferation and metastasis by regulating the miR-145-3p/TCF4 axis.

BACKGROUND: Long noncoding RNAs (lncRNAs) exert an essential regulatory role in cancer progression. This work focuses on the role of LINC00958 in endometrial cancer (EC). METHODS: LINC00958 expression in EC tissues was examined by GEPIA database and TCGA-UCEC dataset. LINC00958, miR-145-3p, and TCF4 mRNA expression levels in EC tissues and cells were examined by qRT-PCR. Western blot was employed to determine TCF4, E-cadherin, and N-cadherin protein expression levels. After LINC00958 was overexpressed or silenced, cell proliferation was determined using Cell Counting Kit 8 (CCK-8) and bromodeoxyuridine (BrdU) incorporation experiments. Cell migration and invasion were examined by Transwell experiment. Dual-luciferase reporter gene or RNA immunoprecipitation (RIP) experiments were executed to validate the targeting relationships among LINC00958 and miR-145-3p and TCF4. The effects of LINC00958 on EC cell proliferation and metastasis were investigated in vivo using a nude mouse subcutaneous graft model and a caudal vein injection model. RESULTS: LINC00958 was remarkably upmodulated in EC. Moreover, its overexpression was strongly linked to unfavorable overall survival of the patients. Functional experiments confirmed that in vitro knockdown of LINC00958 suppressed EC cell proliferation and metastasis. LINC00958 was validated to decoy miR-145-3p and repressed its expression, and TCF4 was uncovered to be a target gene of miR-145-3p and negatively modulated by miR-145-3p. Furthermore, the function of LINC00958 was dependent on its regulation of miR-145-3p and TCF4. CONCLUSIONS: LINC00958 acts as an oncogenic lncRNA to regulate EC progression by modulating the miR-145-3p/TCF4 axis. Knockdown of LINC00958 impedes tumor growth and metastasis in vitro and in vivo, opening a new avenue for therapeutic intervention.

LINC00852 promotes the proliferation and invasion of ovarian cancer cells by competitively binding with miR-140-3p to regulate AGTR1 expression.

BACKGROUND: Dysregulation of long non-coding RNAs (lncRNAs) has been identified in ovarian cancer. However, the expression and biological functions of LINC00852 in ovarian cancer are not understood. METHODS: The expressions of LINC00852, miR-140-3p and AGTR1 mRNA in ovarian cancer tissues and cells were detected by quantitative reverse transcription polymerase chain reaction (qRT-PCR) assay. Gain- and loss-of-function assays were performed to explore the biological functions of LINC00852 and miR-140-3p in the progression of ovarian cancer in vitro. The bindings between LINC00852 and miR-140-3p were confirmed by luciferase reporter gene assay, RNA immunoprecipitation (RIP) assay and RNA pull-down assay. RESULTS: We found that LINC00852 expression was significantly up-regulated in ovarian cancer tissues and cells, whereas miR-140-3p expression was significantly down-regulated in ovarian cancer tissues. Functionally, LINC00852 knockdown inhibited the viability, proliferation and invasion of ovarian cancer cells, and promoted the apoptosis of ovarian cancer cells. Further investigation showed that LINC00852 interacted with miR-140-3p, and miR-140-3p overexpression suppressed the viability, proliferation and invasion of ovarian cancer cells. In addition, miR-140-3p interacted with AGTR1 and negatively regulated its level in ovarian cancer cells. Mechanistically, we found that LINC00852 acted as a ceRNA of miR-140-3p to promote AGTR1 expression and activate MEK/ERK/STAT3 pathway. Finally, LINC00852 knockdown inhibited the growth and invasion ovarian cancer in vivo. CONCLUSION: LINC00852/miR-140-3p/AGTR1 is an important pathway to promote the proliferation and invasion of ovarian cancer.

A simple and fast ASD-POCS algorithm for image reconstruction.

PURPOSE: The adaptive steepest descent projection onto convex set (ASD-POCS) algorithm is a promising algorithm for constrained total variation (TV) type norm minimization models in computed tomography (CT) image reconstruction using sparse and/or noisy data. However, in ASD-POCS algorithm, the existing gradient expression of the TV-type norm appears too complicated in the implementation code and reduces image reconstruction speed. To address this issue, this work aims to develop and test a simple and fast ASD-POCS algorithm. METHODS: Since the original algorithm is not derived thoroughly, we first obtain a simple matrix-form expression by thorough derivation via matrix representations. Next, we derive the simple matrix expressions of the gradients of TV, adaptive weighted TV (awTV), total p-variation (TpV), high order TV (HOTV) norms by term combinations and matrix representations. The deep analysis is then performed to identify the hidden relations of these terms. RESULTS: The TV reconstruction experiments by use of sparse-view projections via the Shepp-Logan, FORBILD and a real CT image phantoms show that the simplified ASD-POCS (S-ASD-POCS) using the simple matrix-form expression of TV gradient achieve the same reconstruction accuracy relative to ASD-POCS, whereas it enables to speed up the whole ASD process 1.8-2.7 time fast. CONCLUSIONS: The derived simple matrix expressions of the gradients of these TV-type norms may simplify the implementation of the ASD-POCS algorithm and speed up the ASD process. Additionally, a general gradient expression suitable to all the sparse transform-based optimization models is demonstrated so that the ASD-POCS algorithm may be tailored to extended image reconstruction fields with accelerated computational speed.

A TV-minimization image-reconstruction algorithm without system matrix.

PURPOSE: Total Variation (TV) minimization algorithm is a classical compressed sensing (CS) based iterative image reconstruction algorithm that can accurately reconstruct images from sparse-view projections in computed tomography (CT). However, the system matrix used in the algorithm is often too large to be stored in computer memory. The purpose of this study is to investigate a new TV algorithm based on image rotation and without system matrix to avoid the memory requirement of system matrix. METHODS: Without loss of generality, a rotation-based adaptive steepest descent-projection onto convex sets (R-ASD-POCS) algorithm is proposed and tested to solve the TV model in parallel beam CT. Specifically, simulation experiments are performed via the Shepp-Logan, FORBILD and real CT image phantoms are used to verify the inverse-crime capability of the algorithm and evaluate the sparse reconstruction capability and the noise suppression performance of the algorithm. RESULTS: Experimental results show that the algorithm can achieve inverse-crime, accurate sparse reconstruction and thus accurately reconstruct images from noisy projections. Compared with the classical ASD-POCS algorithm, the new algorithm may yield the similar image reconstruction accuracy without use of the huge system matrix, which saves the computational memory space significantly. Additionally, the results also show that R-ASD-POCS algorithm is faster than ASD-POCS. CONCLUSIONS: The proposed new algorithm can effectively solve the problem of using huge memory in large scale and iterative image reconstruction. Integrating with ASD-POCS frame, this no-system-matrix based scheme may be readily extended and applied to any iterative image reconstructions.

The lncRNA SNHG15/miR-18a-5p axis promotes cell proliferation in ovarian cancer through activating Akt/mTOR signaling pathway.

Here, we report the expression pattern, function and regulatory mechanism of SNHG15 together with miR-18a-5p micro RNA in ovarian cancer (OC) for the first time. We recruited 20 patients and took normal ovarian tissues and ovarian tumor tissues from them. We used cell culture, transfection, in vivo tumor xenograft assay, and multiple types of detection assays to investigate the expression and regulation of long noncoding RNA (lncRNA) SNHG15/miR-18a-5p in ovarian tissues and cells. Results: We found that the messenger RNA expression level of SNHG15 was significantly higher and miR-18 was decreased in ovarian cancer tissues and in OC cells. Functional experiments showed that SNHG15 overexpression potentiated the migration and invasion of OC cells, while SNHG15 inhibition reduced the tumor proliferation, which was restored via overexpression of miR-18a. SNHG15 was found to directly target and suppress the expression of miR-18a. Our results illustrate the possible molecular mechanism of lncRNA SNHG15/miR-18a-5p functions in cell proliferation in OC. SNHG15/miR-18a promoted the progression of OC cells via the protein kinase B/mammalian target of rapamycin signaling pathway.

Establishment and characterization of patient-derived cancer models of malignant peripheral nerve sheath tumors.

BACKGROUND: Malignant peripheral nerve sheath tumors (MPNSTs) are a rare subtype of soft-tissue sarcoma, derived from a peripheral branch or the sheath of the sciatic nerve, brachial plexus, or sacral plexus. The clinical outcomes for MPNST patients with unresectable or metastatic tumors are dismal, and novel therapeutic strategies are required. Although patient-derived cancer cell lines are vital for basic research and preclinical studies, few MPNST cell lines are available from public cell banks. Therefore, the aim of this study was to establish cancer cell lines derived from MPNST patients. METHODS: We used tumor tissues from five patients with MPNSTs, including one derived from a rare bone tissue MPNST. The tumor tissues were obtained at the time of surgery and were immediately processed to establish cell lines. A patient-derived xenograft was also established when a sufficient amount of tumor tissue was available. The characterization of established cells was performed with respect to cell proliferation, spheroid formation, and invasion. The mutation status of actionable genes was monitored by NCC Oncopanel, by which the mutation of 114 genes was assessed by next-generation sequencing. The response to anti-cancer agents, including anti-cancer drugs approved for the treatment of other malignancies was investigated in the established cell lines. RESULTS: We established five cell lines (NCC-MPNST1-C1, NCC-MPNST2-C1, NCC-MPNST3-C1, NCC-MPNST4-C1, and NCC-MPNST5-C1) from the original tumors, and also established patient-derived xenografts (PDXs) from which one cell line (NCC-MPNST3-X2-C1) was produced. The established MPNST cell lines proliferated continuously and formed spheroids while exhibiting distinct invasion abilities. The cell lines had typical mutations in the actionable genes, and the mutation profiles differed among the cell lines. The responsiveness to examined anti-cancer agents differed among cell lines; while the presence of an actionable gene mutation did not correspond with the response to the anticipated anti-cancer agents. CONCLUSION: The established cell lines exhibit various characteristics, including proliferation and invasion potential. In addition, they had different mutation profiles and response to the anti-cancer agents. These observations suggest that the established cell lines will be useful for future research on MPNSTs.

Self-Assembly of Highly Stable Zirconium(IV) Coordination Cages with Aggregation Induced Emission Molecular Rotors for Live-Cell Imaging.

The self-assembly of highly stable zirconium(IV)-based coordination cages with aggregation induced emission (AIE) molecular rotors for in vitro bio-imaging is reported. The two coordination cages, NUS-100 and NUS-101, are assembled from the highly stable trinuclear zirconium vertices and two flexible carboxyl-decorated tetraphenylethylene (TPE) spacers. Extensive experimental and theoretical results show that the emissive intensity of the coordination cages can be controlled by restricting the dynamics of AIE-active molecular rotors though multiple external stimuli. Because the two coordination cages have excellent chemical stability in aqueous solutions (pH stability: 2-10) and impressive AIE characteristics contributed by the molecular rotors, they can be employed as novel biological fluorescent probes for in vitro live-cell imaging.

Hydrophobic Shielding of Outer Surface: Enhancing the Chemical Stability of Metal-Organic Polyhedra.

Metal-organic polyhedra (MOP) are a promising class of crystalline porous materials with multifarious potential applications. Although MOPs and metal-organic frameworks (MOFs) have similar potential in terms of their intrinsic porosities and physicochemical properties, the exploitation of carboxylate MOPs is still rudimentary because of the lack of systematic development addressing their chemical stability. Herein we describe the fabrication of chemically robust carboxylate MOPs via outer-surface functionalization as an a priori methodology, to stabilize those MOPs system where metal-ligand bond is not so strong. Fine-tuning of hydrophobic shielding is key to attaining chemical inertness with retention of the framework integrity over a wide range of pH values, in strong acidic conditions, and in oxidizing and reducing media. These results are further corroborated by molecular modelling studies. Owing to the unprecedented transition from instability to a chemically ultra-stable regime using a rapid ambient-temperature gram-scale synthesis (within seconds), a prototype strategy towards chemically stable MOPs is reported.

Recovery of miR-139-5p in Ovarian Cancer Reverses Cisplatin Resistance by Targeting C-Jun.

BACKGROUND/AIMS: In platinum-based chemotherapy for ovarian cancer, acquired drug resistance is a frequent occurrence. Because recent studies have demonstrated that dysregulation of microRNAs (miRNAs) is partly responsible for the induction of acquired drug resistance in cancers, we hypothesized that correcting the dysregulation of key miRNAs would reverse the acquired resistance to platinum-based drugs in ovarian cancer. METHODS: Cisplatin-resistant SKOV3 and A2780 ovarian cancer cell lines (SKOV3-R and A2780-R, respectively) were established by long-term exposure to cisplatin. MTT assays were performed to evaluate the viability of SKOV3, SKOV3-R, A2780, and A2780-R cells. Quantitative PCR was used to examine the expression of miR-139-5p in these cell lines. The regulatory mechanism was confirmed by western blot analysis and luciferase reporter assays. After treatment with miR-139-5p and cisplatin, mitochondrial membrane potential and apoptosis were measured by using flow cytometry. Interaction with c-Jun and activating transcription factor 2 (ATF2) was evaluated by co-immunoprecipitation. Expression of B-cell lymphoma-extra large (Bcl-xl) and activation of caspase-9 and caspase-3 were detected by western blotting. RESULTS: Expression of miR-139-5p was decreased in SKOV3-R and A2780-R cells. Recovery of miR-139-5p increased the sensitivity of SKOV3-R and A2780-R cells to cisplatin treatment, inhibited the interaction of c-Jun and ATF2, and decreased Bcl-xl expression in SKOV3-R and A2780-R cells. Expression of miR-139-5p promoted cisplatin-induced mitochondrial apoptosis through binding the 3' untranslated region of c-Jun mRNA. CONCLUSION: Recovery of miR-139-5p suppressed the expression of c-Jun and thus reversed cisplatin-resistance in ovarian cancer.

Pazopanib-induced changes in protein expression signatures of extracellular vesicles in synovial sarcoma.

Secreted proteins enclosed in extracellular vesicles can act as intercellular messengers. The objective of this study was to elucidate the role of proteins secreted from synovial sarcoma cells in the regulatory network underlying pazopanib response. We performed a comprehensive analysis of expression of proteins secreted from four synovial sarcoma cell lines (SYO-1, HS-SYII, 1273/99, and YaFuSS) using mass spectroscopy. Comparison of up-regulated proteins in cells, extracellular vesicles-free conditioned media, and extracellular vesicles revealed significantly up-regulated Wnt in synovial sarcoma vesicles. Furthermore, we compared protein signatures of cells, conditioned media, and extracellular vesicles before and after pazopanib treatment. Interestingly, protein signatures of extracellular vesicles showed robust changes in Wnt signaling pathways in response to pazopanib. Our findings provide insight into the potential role of Wnt, a protein secreted from the extracellular vesicles of synovial sarcoma cells, making it a potential candidate for use in sarcoma diagnosis.

Investigation of the preconditioner-parameter in the preconditioned Chambolle-Pock algorithm applied to optimization-based image reconstruction.

The optimization-based image reconstruction methods have been thoroughly investigated in the field of medical imaging. The Chambolle-Pock (CP) algorithm may be employed to solve these convex optimization image reconstruction programs. The preconditioned CP (PCP) algorithm has been shown to have much higher convergence rate than the ordinary CP (OCP) algorithm. This algorithm utilizes a preconditioner-parameter to tune the implementation of the algorithm to the specific application, which ranges from 0 and 2, but is often set to 1. In this work, we investigated the impact of the preconditioner-parameter on the convergence rate of the PCP algorithm when it is applied to the TV constrained, data-divergence minimization (TVDM) optimization based image reconstruction. We performed the investigations in the context of 2D computed tomography (CT) and 3D electron paramagnetic resonance imaging (EPRI). For 2D CT, we used the Shepp-Logan and two FORBILD phantoms. For 3D EPRI, we used a simulated 6-spheres phantom and a physical phantom. Study results showed that the optimal preconditioner-parameter depends on the specific imaging conditions. Simply setting the parameter equal to 1 cannot guarantee a fast convergence rate. Thus, this study suggests that one should adaptively tune the preconditioner-parameter to obtain the optimal convergence rate of the PCP algorithm.

Three novel accurate pixel-driven projection methods for 2D CT and 3D EPR imaging.

OBJECTIVES: This work aims to explore more accurate pixel-driven projection methods for iterative image reconstructions in order to reduce high-frequency artifacts in the generated projection image. METHODS: Three new pixel-driven projection methods namely, small-pixel-large-detector (SPLD), linear interpolation based (LIB) and distance anterpolation based (DAB), were proposed and applied to reconstruct images. The performance of these methods was evaluated in both two-dimensional (2D) computed tomography (CT) images via the modified FORBILD phantom and three-dimensional (3D) electron paramagnetic resonance (EPR) images via the 6-spheres phantom. Specifically, two evaluations based on projection generation and image reconstruction were performed. For projection generation, evaluation was using a 2D disc phantom, the modified FORBILD phantom and the 6-spheres phantom. For image reconstruction, evaluations were performed using the FORBILD and 6-spheres phantom. During evaluation, 2 quantitative indices of root-mean-square-error (RMSE) and contrast-to-noise-ratio (CNR) were used. RESULTS: Comparing to the use of ordinary pixel-driven projection method, RMSE of the SPLD based least-square algorithm was reduced from 0.0701 to 0.0384 and CNR was increased from 5.6 to 19.47 for 2D FORBILD phantom reconstruction. For 3D EPRI, RMSE of SPLD was also reduced from 0.0594 to 0.0498 and CNR was increased from 3.88 to 11.58. In addition, visual evaluation showed that images reconstructed in both 2D and 3D images suffered from high-frequency line-shape artifacts when using the ordinary pixel-driven projection method. However, using 3 new methods all suppressed the artifacts significantly and yielded more accurate reconstructions. CONCLUSIONS: Three proposed pixel-driven projection methods achieved more accurate iterative image reconstruction results. These new and more accurate methods can also be easily extended to other imaging modalities. Among them, SPLD method should be recommended to 3D and four dimensional (4D) EPR imaging.

Proteomic study of hepatocellular carcinoma using a novel modified aptamer-based array (SOMAscan™) platform.

Vascular invasion is a pathological hallmark of hepatocellular carcinoma (HCC), associated with poor prognosis; it is strongly related to the early recurrence and poor survival after curative resection. In order to determine the proteomic backgrounds of HCC carcinogenesis and vascular invasion, we employed a novel modified aptamer-based array (SOMAscan) platform. SOMAscan is based on the Slow Off-rate Modified Aptamers (SOMAmers), which rely on the natural 3D folding of single-stranded DNA-based protein affinity reagents. Currently, the expression level of 1129 proteins can be assessed quantitatively. Correlation matrix analysis showed that the overall proteomic features captured by SOMAscan differ between tumor and non-tumor tissues. Non-tumor tissues were shown to have more homogeneous proteome backgrounds than tumor tissues. A comparative study identified 68 proteins with differential expression between tumor and non-tumor tissues, together with eight proteins associated with vascular invasion. Gene Ontology analysis showed that the extracellular space and extracellular region proteins were predominantly detected. Network analysis revealed the linkage of seven proteins, AKT1, MDM2, PTEN, FGF1, MAPK8, PRKCB, and FN1, which were categorized as the components of "Pathways in cancer" in pathway analysis. The results of SOMAscan analysis were not concordant with those obtained by western blotting; only the determined FN1 levels were concordant between the two platforms. We demonstrated that the proteome captured by SOMAscan includes the proteins relevant to carcinogenesis and vascular invasion in HCC. The identified proteins may serve as candidates for the future studies of disease mechanisms and clinical applications.

Discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2) is a novel biomarker of myxofibrosarcoma invasion identified by global protein expression profiling.

Myxofibrosarcoma (MFS) is a mesenchymal malignancy characterized by frequent recurrence even after radical wide resection. To optimize therapy for MFS patients, we aimed to identify candidate tissue biomarkers of MFS invasion potential. Invasion characteristics of MFS were evaluated by magnetic resonance imaging and protein expression profiling of primary tumor tissues performed using two-dimensional difference gel electrophoresis (2D-DIGE). Protein expression profiles were compared between invasive and non-invasive tumors surgically resected from 11 patients. Among the 3453 protein spots observed, 59 demonstrated statistically significant difference in intensity (≥2-fold) between invasive and non-invasive tumors (p<0.01 by Wilkoxon test), and were identified by mass spectrometry as 47 individual proteins. Among them, we further focused on discoidin, CUB and LCCL domain-containing protein 2 (DCBLD2), a receptor tyrosine kinase with aberrant expression in malignant tumors. Immunohistochemistry analysis of 21 additional MFS cases revealed that higher DCBLD2 expression was significantly associated with invasive properties of tumor cells. DCBLD2 sensitivity and specificity, and positive and negative predictive values for MFS invasion were 69.2%, 87.5%, 90%, and 63.6%, respectively. The expression level of DCBLD2 was consistent in different portions of tumor tissues. Thus, DCBLD2 expression can be a useful biomarker to evaluate invasive properties of MFS. Further validation studies based on multi-institutional collaboration and comprehensive analysis of DCBLD2 biological functions in MFS are required to confirm its prognostic utility for clinical application.