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Background A large number of biological studies have shown that miRNAs are inextricably linked to many complex diseases. Studying the miRNA-disease associations could provide us a root cause understanding of the underlying pathogenesis in which promotes the progress of drug development. However, traditional biological experiments are very time-consuming and costly. Therefore, we come up with an efficient models to solve this challenge. Results In this work, we propose a deep learning model called EOESGC to predict potential miRNA-disease associations based on embedding of embedding and simplified convolutional network. Firstly, integrated disease similarity, integrated miRNA similarity, and miRNA-disease association network are used to construct a coupled heterogeneous graph, and the edges with low similarity are removed to simplify the graph structure and ensure the effectiveness of edges. Secondly, the Embedding of embedding model (EOE) is used to learn edge information in the coupled heterogeneous graph. The training rule of the model is that the associated nodes are close to each other and the unassociated nodes are far away from each other. Based on this rule, edge information learned is added into node embedding as supplementary information to enrich node information. Then, node embedding of EOE model training as a new feature of miRNA and disease, and information aggregation is performed by simplified graph convolution model, in which each level of convolution can aggregate multi-hop neighbor information. In this step, we only use the miRNA-disease association network to further simplify the graph structure, thus reducing the computational complexity. Finally, feature embeddings of both miRNA and disease are spliced into the MLP for prediction. On the EOESGC evaluation part, the AUC, AUPR, and F1-score of our model are 0.9658, 0.8543 and 0.8644 by 5-fold cross-validation respectively. Compared with the latest published models, our model shows better results. In addition, we predict the top 20 potential miRNAs for breast cancer and lung cancer, most of which are validated in the dbDEMC and HMDD3.2 databases. Conclusion The comprehensive experimental results show that EOESGC can effectively identify the potential miRNA-disease associations.

miRNAs significantly affect multifarious biological processes involving human disease. Biological experiments always need enormous financial support and time cost. Taking expense and difficulty into consideration, to predict the potential miRNA-disease associations, a lot of high-efficiency computational methods by computer have been developed, based on a network generated by miRNA-disease association dataset. However, there exist many challenges. Firstly, the association between miRNAs and diseases is intricate. These methods should consider the influence of the neighborhoods of each node from the network. Secondly, how to measure whether there is an association between two nodes of the network is also an important problem. In our study, we innovatively integrate graph node embedding with a multilayer perceptron and propose a method DEMLP. To begin with, we construct a miRNA-disease network by miRNA-disease adjacency matrix (MDA). Then, low-dimensional embedding representation vectors of nodes are learned from the miRNA-disease network by DeepWalk. Finally, we use these low-dimensional embedding representation vectors as input to train the multilayer perceptron. Experiments show that our proposed method that only utilized the miRNA–disease association information can effectively predict miRNA-disease associations. To evaluate the effectiveness of DEMLP in a miRNA-disease network from HMDD v3.2, we apply fivefold crossvalidation in our study. The ROC-AUC computed result value of DEMLP is 0.943, and the PR-AUC value of DEMLP is 0.937. Compared with other state-of-the-art methods, our method shows good performance using only the miRNA-disease interaction network.

Human interleukin 2 (IL-2) has shown impressive results as a therapeutic agent for cancer. However, IL-2-based cancer therapy is limited by strong Treg amplification owing to its high binding affinity to IL-2 receptor α (IL-2Rα) and its short half-life owing to its small molecular size. In this study, we solved these problems using a covalent modification strategy of the IL-2 variant, i.e., substituting cysteine (C) for lysine (K) at position 35, using octadecanedicarboxylic acid through maleimide chemistry, creating IL-2K35C-moFA. IL-2K35C-moFA was equipotent to human IL-2 wild type (IL-2WT) in activating tumor-killing CD8+ memory effector T cells (CD8+ T) and NK cells bearing the intermediate affinity IL-2 receptors, and less potent than IL-2WT on CTLL-2 cells bearing the high-affinity IL-2 receptors. Moreover, it was shown to support the preferential activation of IL-2 receptor β (IL-2Rβ) over IL-2Rα because of the mutation and fatty acid conjugation. In a B16F10 murine tumor model, IL-2K35C-moFA showed efficacy as a single dose and provided durable immunity for 1 week. Our results support the further evaluation of IL-2K35C-moFA as a novel cancer immunotherapy.

Purpose To develop a true single shot turbo spin echo (SShTSE) acquisition with Dixon for robust T2 -weighted abdominal imaging with uniform fat and water separation at 3T. Methods The in-phase (IP) and out-of-phase (OP) echoes for Dixon processing were acquired in the same repetition time of a SShTSE using partial echoes. A phase-preserved bi-directional homodyne reconstruction was developed to compensate the partial echo and the partial phase encoding of SShTSE. With IRB approval, the SShTSE-Dixon was compared against standard SShTSE, without and with fat suppression using spectral adiabatic inversion recovery (SPAIR) in 5 healthy volunteers and 5 patients. The SNR and contrast ratio (CR) of spleen to liver were compared among different acquisitions. Results The bi-directional homodyne reconstruction successfully minimized ringing artifacts because of partial acquisitions. SShTSE-Dixon achieved uniform fat suppression compared to SShTSE-SPAIR with fat suppression failures of 1/10 versus 10/10 in the axial plane and 0/5 versus 5/5 in the coronal plane, respectively. The SNRs of the liver (12.2 ± 4.9 vs. 11.7 ± 5.2; P = .76) and spleen (25.9 ± 11.6 vs. 23.7 ± 9.7; P = .14) were equivalent between fat-suppressed images (SShTSE-Dixon water-only and SShTSE-SPAIR). The SNRs of liver (14.4 ± 5.7 vs. 13.4 ± 5.0; P = .60) and spleen (26.5 ± 10.1 vs. 25.7 ± 8.5; P = .56) were equivalent between non-fat-suppressed images (SShTSE-Dixon IP and SShTSE). The CRs of spleen to liver were also similar between fat-suppressed images (2.6 ± 0.4 vs. 2.5 ± 0.5; P =.92) and non-fat-suppressed images (2.3 ± 0.6 vs. 2.2 ± 0.4; P =.84). Conclusion SShTSE-Dixon generates robust abdominal T2 -weighted images at 3T with and without uniform fat suppression, along with perfectly co-registered fat-only images in a single acquisition.

Introduction CEST MRI permits quantitation of macromolecules such as amide proteins that are of interest in cancer metabolism. However, optimal CEST acquisition and analysis methods remain undetermined. In this study, we investigated CEST MRI as an imaging biomarker for early treatment response in 51 TNBC patients receiving NAST and compared the performance with two different CEST saturation power levels and two analysis methods. Methods A total of 51 stage I-III TNBC patients enrolled in the prospective ARTEMIS trial (NCT02276443) had CEST imaging performed on a 3T MRI scanner at baseline before NAST (BL, N = 51), after 2 cycles (C2, N = 37), and 4 cycles (C4, N = 44) of NAST. 33 of the 51 patients had imaging at all 3 time points. 29 of the 33 patients had pathological findings, with N = 16 with pathological complete response (pCR) and N = 13 with non-pCR. Two sets of CEST images using 0.9 and 2.0 µT saturation power levels were acquired and analyzed using the magnetization transfer ratio asymmetry (MTRasym) and the Lorentzian line fitting (Mag3.5) methods, for a total of 4 acquisition/analysis combinations. The group averaged CEST signals, MTRasym at 0.9 and 2.0 µT and Mag3.5 at 0.9 and 2.0 µT, at BL, C2 and C4 were determined and evaluated using unpaired (51 patients) and paired (33 patients) Kruskal-Wallis tests. The Mag3.5 at 0.9 µT and the MTRasym at 2.0 µT were further compared between pCR and non-pCR. The group averaged CEST signals at BL, C2, and C4 were evaluated using the Friedman test for the pCR and the non-PCR groups. Separately, the change in the CEST signal from BL to C2 and C4 was determined for each patient and evaluated using the Mann-Whitney test for both groups. P < 0.05 was considered statistically significant. Results The MTRasym at BL was higher at 2.0 µT than at 0.9 µT. In contrast, the Mag3.5 at BL was higher at 0.9 µT than at 2.0 µT. The MTRasym at 2.0 µT and the Mag3.5 at 0.9 µT decreased during treatment while the MTRasym at 0.9 µT and the Mag3.5 at 2.0 µT were similar. Both the unpaired and the paired Mag3.5 at 0.9 µT showed a significant decrease at C2 and C4 vs. BL (p < 0.01). The unpaired and paired MTRasym at 2.0 µT showed a decrease, although the change was not significant except for the unpaired data at C4. The decrease in the group averaged Mag3.5 at 0.9 µT was significant at C2 vs. BL for the pCR group (p = 0.04), while it was not significant for the pCR group at C4 vs. BL and for the non-pCR group at either C2 or C4 vs. BL. The group averaged MTRasym at 2.0 µT changes were not significant for either the pCR or the non-pCR groups. None of the CEST signal changes on a per patient basis at C2-BL, C4-BL and C4-C2 were significantly different between the pCR and the non-pCR groups. Further, none of the group averaged CEST signals at BL, C2 and C4 were significantly different between the pCR and the non-pCR groups. Conclusion Our study demonstrates that the CEST quantitation in TNBC patients undergoing NAST depends on acquisition and analysis. For a maximum change in the CEST effect, Lorentzian line fitting is better paired with acquisition at a low saturation power (0.9 µT) and MTRasym is better paired with acquisition at a high saturation power (2.0 µT). Further, a significant CEST signal decrease was observed in TNBC patients with pCR after NAST when a 0.9 µT saturation power and the Lorentzian line fitting were used. In comparison, the decrease was not significant in non-pCR patients using the same saturation power and analysis method. The results suggest that the CEST signal acquired at 0.9 µT saturation power and analyzed using Lorentzian line fitting may be able to differentiate between pCR and non-pCR among TNBC patients undergoing NAST. Additional studies with a larger patient population are ongoing to further validate our findings and their potential for determining pCR. Citation Format: Shu Zhang, Gaiane M Rauch, Beatriz E Adrada, Medine Boge, Rania MM Mohamed, Abeer H Abdelhafez, Jong Bum Son, Jia Sun, Nabil A Elshafeey, Jason B White, Deanna L Lane, Jessica WT Leung, Marion E Scoggins, David A Spak, Elsa Arribas, Elizabeth Ravenberg, Lumarie Santiago, Tanya W Moseley, Gary J Whitman, Huong Le-Petross, Benjamin C Musall, Mitsuharu Miyoshi, Xinzeng Wang, Brandy Willis, Stacy Hash, Aikaterini Kotrotsou, Peng Wei, Ken-Pin Hwang, Alastair Thompson, Stacy L Moulder, Rosalind P Candelaria, Wei Yang, Jingfei Ma, Mark D Pagel. Assessment of early response to neoadjuvant systemic therapy (NAST) of triple-negative breast cancer (TNBC) using chemical exchange saturation transfer (CEST) MRI: A pilot study [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS3-08.

Introduction Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have been applied to medical imaging, leading to improvements in image quality. Our goal is to evaluate the performance of a new deep learning-based reconstruction method, “DLR” in improving image quality and mitigating artifacts, which is now commercially available as AIRTM Recon DL (GE Healthcare, Waukesha, WI). We hypothesize that applying DLR to the T2WI images of the prostate provides improved image quality and reduced artifacts. Methods This study included 31 patients with a history of prostate cancer that had a multiparametric MRI of the prostate with an endorectal coil (ERC) at 1.5 T or 3.0 T. Four series of T2-weighted images were generated in total: one set with the ERC signal turned on (ERC) and another set with the ERC signal turned off (Non-ERC). Each of these sets then reconstructed using two different reconstruction methods: conventional reconstruction (Conv) and DL Recon (DLR): ERCDLR, ERCConv, Non-ERCDLR, and Non-ERCConv. Three radiologists independently reviewed and scored the four sets of images for (i) image quality, (ii) artifacts, and (iii) visualization of anatomical landmarks and tumor. Results The Non-ERCDLR scored as the best series for (i) overall image quality (p p Conclusion Prostate imaging without the use of an endorectal coil could benefit from deep learning reconstruction as demonstrated with T2-weighted imaging MRI evaluations of the prostate.

Genome-wide association studies (GWAS) are powerful tools for identifying pathogenic genes of complex diseases and revealing genetic structure of diseases. However, due to gene-to-gene interactions, only a part of the hereditary factors can be revealed. The meta-analysis based on GWAS can integrate gene expression data at multiple levels and reveal the complex relationship between genes. Therefore, we used meta-analysis to integrate GWAS data of sarcoma to establish complex networks and discuss their significant genes. Firstly, we established gene interaction networks based on the data of different subtypes of sarcoma to analyze the node centralities of genes. Secondly, we calculated the significant score of each gene according to the Staged Significant Gene Network Algorithm (SSGNA). Then, we obtained the critical gene set HYC of sarcoma by ranking the scores, and then combined Gene Ontology enrichment analysis and protein network analysis to further screen it. Finally, the critical core gene set Hcore containing 47 genes was obtained and validated by GEPIA analysis. Our method has certain generalization performance to the study of complex diseases with prior knowledge and it is a useful supplement to genome-wide association studies.

PURPOSE: To determine if amide proton transfer–weighted chemical exchange saturation transfer (APT(W) CEST) MRI is useful in the early assessment of treatment response in persons with triple-negative breast cancer (TNBC). MATERIALS AND METHODS: In this prospective study, a total of 51 participants (mean age, 51 years [range, 26–79 years]) with TNBC were included who underwent APT(W) CEST MRI with 0.9- and 2.0-µT saturation power performed at baseline, after two cycles (C2), and after four cycles (C4) of neoadjuvant systemic therapy (NAST). Imaging was performed between January 31, 2019, and November 11, 2019, and was a part of a clinical trial (registry number NCT02744053). CEST MR images were analyzed using two methods—magnetic transfer ratio asymmetry (MTR(asym)) and Lorentzian line shape fitting. The APT(W) CEST signals at baseline, C2, and C4 were compared for 51 participants to evaluate the saturation power levels and analysis methods. The APT(W) CEST signals and their changes during NAST were then compared for the 26 participants with pathology reports for treatment response assessment. RESULTS: A significant APT(W) CEST signal decrease was observed during NAST when acquisition at 0.9-µT saturation power was paired with Lorentzian line shape fitting analysis and when the acquisition at 2.0 µT was paired with MTR(asym) analysis. Using 0.9-µT saturation power and Lorentzian line shape fitting, the APT(W) CEST signal at C2 was significantly different from baseline in participants with pathologic complete response (pCR) (3.19% vs 2.43%; P = .03) but not with non-pCR (2.76% vs 2.50%; P > .05). The APT(W) CEST signal change was not significant between pCR and non-pCR at all time points. CONCLUSION: Quantitative APT(W) CEST MRI depended on optimizing acquisition saturation powers and analysis methods. APT(W) CEST MRI monitored treatment effects but did not differentiate participants with TNBC who had pCR from those with non-pCR. © RSNA, 2021 Clinical trial registration no. NCT02744053 Supplemental material is available for this article. Keywords Molecular Imaging-Cancer, Molecular Imaging-Clinical Translation, MR-Imaging, Breast, Technical Aspects, Tumor Response, Technology Assessment

PURPOSE To improve the robustness of arterial spin-labeled measured perfusion using a novel Cartesian acquisition with spiral profile reordering (CASPR) 3D turbo spin echo (TSE) in the brain and kidneys. METHODS The CASPR view ordering followed a pseudo-spiral trajectory on a Cartesian grid, by sampling the center of k-space at the beginning of each echo train of a segmented 3D TSE acquisition. With institutional review board approval and written informed consent, 14 normal subjects (9 brain and 5 kidneys) were scanned with pCASL perfusion imaging using 3D CASPR and compared against 3D linear TSE (brain and kidneys), the established 2D EPI and 3D gradient and spin echo perfusion (brain), and 2D single-shot turbo spin-echo perfusion (kidneys). The SNR and the quantitative perfusion values were compared among different acquisitions. RESULTS 3D CASPR TSE achieved robust perfusion across all slices compared to 3D linear TSE in the brain and kidneys. Compared to 2D EPI, 3D CASPR TSE showed higher SNR across the brain (P < 0.01), and exhibited good agreement (36.4 ± 4.7 and 36.9 ± 5.3 mL/100 g/min with 2D EPI and 3D CASPR, respectively), and with 3D gradient and spin echo (27.9 ± 7.2 mL/100 g/min). Compared to a single slice 2D single-shot turbo spin-echo acquisition, 3D CASPR TSE achieved robust perfusion across the entire kidneys in similar scan time with comparable quantified perfusion values (154.1 ± 74.6 and 151.7 ± 70.6 mL/100 g/min with 2D single-shot turbo spin-echo and 3D CASPR, respectively). CONCLUSION The CASPR view ordering with 3D TSE achieves robust arterial spin-labeled perfusion in the brain and kidneys because of the sampling of the center of k-space at the beginning of each echo train.

Purpose The recently introduced inhomogeneous magnetization transfer (ihMT) method has predominantly been applied for imaging the central nervous system. Future applications of ihMT, such as in peripheral nerves and muscles, will involve imaging in the vicinity of adipose tissues. This work aims to systematically investigate the partial volume effect of fat on the ihMT signal and to propose an efficient fat-separation method that does not interfere with ihMT measurements. Methods First, the influence of fat on ihMT signal was studied using simulations. Next, the ihMT sequence was combined with a multi-echo Dixon acquisition for fat separation. The sequence was tested in 9 healthy volunteers using a 3T human scanner. The ihMT ratio (ihMTR) values were calculated in regions of interest in the brain and the spinal cord using standard acquisition (no fat saturation), water-only, in-phase, and out-of-phase reconstructions. The values obtained were compared with a standard fat suppression method, spectral presaturation with inversion recovery. Results Simulations showed variations in the ihMTR values in the presence of fat, depending on the TEs used. The IhMTR values in the brain and spinal cord derived from the water-only ihMT multi-echo Dixon images were in good agreement with values from the unsuppressed sequence. The ihMT-spectral presaturation with inversion recovery combination resulted in 24%-35% lower ihMTR values compared with the standard non-fat-suppressed acquisition. Conclusion The presence of fat within a voxel affects the ihMTR calculations. The IhMT multi-echo Dixon method does not compromise the observable ihMT effect and can potentially be used to remove fat influence in ihMT.

Background. DNA methylation is essential for regulating gene expression, and the changes of DNA methylation status are commonly discovered in disease. Therefore, identification of differentially methylation patterns, especially differentially methylated regions (DMRs), in two different groups is important for understanding the mechanism of complex diseases. Few tools exist for DMR identification through considering features of methylation data, but there is no comprehensive integration of the characteristics of DNA methylation data in current methods. Results. Accounting for the characteristics of methylation data, such as the correlation characteristics of neighboring CpG sites and the high heterogeneity of DNA methylation data, we propose a data-driven approach for DMR identification through evaluating the energy of single site using modified 1D Ising model. Applied to both simulated and publicly available datasets, our approach is compared with other popular methods in terms of performance. Simulated results show that our method is more sensitive than competing methods. Applied to the real data, our method can identify more common DMRs than DMRcate, ProbeLasso, and Wang’s methods with a high overlapping ratio. Also, the necessity of integrating the heterogeneity and correlation characteristics in identifying DMR is shown through comparing results with only considering mean or variance signals and without considering relationship of neighboring CpG sites, respectively. Through analyzing the number of DMRs identified in real data located in different genomic regions, we find that about 90% DMRs are located in CGI which always regulates the expression of genes. It may help us understand the functional effect of DNA methylation on disease.

Background The 3D short tau inversion recovery (STIR) sequence is routinely used in clinical MRI to achieve robust fat suppression. However, the performance of the commonly used adiabatic inversion pulse, hyperbolic secant (HS), is compromised in challenging areas with increased B0 and B1 inhomogeneities, such as brachial plexus at 3T. Purpose To demonstrate the frequency offset corrected inversion (FOCI) pulse as an efficient fat suppression STIR pulse with increased robustness to B0 and B1 inhomogeneities at 3T, compared to the HS pulse. Study type Prospective. Subjects/phantom Initial evaluation was performed in phantoms and one healthy volunteer by varying the B1 field, while subsequent comparison was performed in three healthy volunteers and five patients without varying the B1 . Field strength/sequence 3T; 3D TSE-STIR with HS and FOCI pulses. Assessment Brachial plexus images were qualitatively evaluated by two musculoskeletal radiologists independently using a four-point grading scale for fat suppression, shading artifacts, and nerve visualization. Statistical test The Wilcoxon signed-rank test with P Results Simulations and phantom experiments demonstrated broader bandwidth (2.5 kHz vs. 0.83 kHz, increased B0 robustness) at the same adiabatic threshold and lower adiabatic threshold (5 μT vs. 7 μT at 3.5 ppm, increased B1 robustness) at the same bandwidth with the FOCI pulse compared to the HS pulse With increased bandwidth, the FOCI pulse achieved robust fat suppression even at 50% of maximum B1 strength, while the HS pulse required >75% of maximum B1 strength. Compared to the standard 3D TSE-STIR with HS pulse, the FOCI pulse achieved uniform fat suppression (P Data conclusion The FOCI pulse has increased robustness to B0 and B1 inhomogeneities, compared to the HS pulse, and enables uniform fat suppression in brachial plexus at 3T. Level of evidence 1 Techinical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1104-1111.

This paper investigates a new impulsive stochastic chemostat model with nonlinear perturbation in a polluted environment. We present the analysis and the criteria of the extinction of the microorganisms, and establish sufficient conditions for the existence of a unique ergodic stationary distribution of the model via Lyapunov functions method. The results show that both stochastic noise and impulsive toxicant input have great effects on the survival and extinction of the microorganisms. Moreover, we provide a series of numerical simulations to illustrate the analytical results.

PURPOSE: To develop a whole-body MRI technique at 3T with improved lesion conspicuity for metastatic cancer detection using fast, high-resolution and high signal-to-noise ratio T2-weighted (T2W) imaging with simultaneous fat and fluid suppression. THEORY AND METHODS: The proposed Dual-Echo T2-weighted acquisition for Enhanced Conspicuity of Tumors (DETECT) acquires four images, in-phase (IP) and out-of-phase (OP) at a short and a long echo time (TE) using single-shot turbo spin echo. The IP/OP images at the short and long TEs are reconstructed using the standard Dixon and shared-field-map Dixon reconstruction respectively, for robust fat/water separation. An adaptive complex subtraction between the two TE water-only images achieves fluid attenuation. DETECT imaging was optimized and evaluated in whole-body imaging of five healthy volunteers, and compared against diffusion-weighted imaging with background suppression (DWIBS) in five patients with known metastatic renal cell carcinoma. RESULTS: Robust fat/water separation and fluid attenuation were achieved using the shared-field-map Dixon reconstruction and adaptive complex subtraction, respectively. DETECT imaging technique generated co-registered T2W images with and without fat suppression, heavily T2W, and fat and fluid suppressed T2W whole-body images in less than 7 minutes. Compared to DWIBS acquired in 17 minutes, the DETECT imaging achieved better detection and localization of lesions in patients with metastatic cancer. CONCLUSION: DETECT imaging technique generates T2W images with high resolution, high SNR, minimal geometric distortions, and provides good lesion conspicuity with robust fat and fluid suppression in less than 7 minutes for whole-body imaging, demonstrating efficient and reliable metastatic cancer detection at 3T.

In this paper, we propose a new nonlinear stochastic SIRS epidemic model with standard incidence rate and saturated treatment function. The main purpose of this paper is to investigate the threshold dynamics of the nonlinear stochastic SIRS epidemic model by making use of stochastic inequality techniques. By using Lyapunov methods and Itô’s formula, we first prove the existence and uniqueness of a global positive solution for the corresponding limiting system. Furthermore, we obtain sufficient conditions for the extinction and persistence in mean of the nonlinear stochastic SIRS epidemic model by using the techniques of a series of stochastic inequalities. Finally, we provide some numerical simulations to illustrate the performance of our theoretical findings.

Purpose CEST MRI for breast lesion characterization is promising. However, artifacts are prone to develop in breast CEST imaging due to strong lipid signals. The aims of the study are: 1) to develop and validate the CEST-Dixon imaging sequence for simultaneous water-fat separation and B0 mapping; 2) use the CEST-Dixon method to characterize suspicious lesions in patients undergoing percutaneous biopsy. Methods The gradient-echo multi-echo Dixon acquisition is used to create fat-free CEST and B0 maps. The sequence has been validated in phantoms and in vivo. Five healthy volunteers and ten patients were scanned to compare the CEST contrast in three frequency ranges centered at 1, 2 and 3.5 ppm. The correlation between the CEST contrast and pathology markers (tumor type, ER status, Ki-67) was also investigated by stratifying the patients into ER-negative invasive ductal carcinoma (IDC) (more aggressive), ER-positive IDC (less aggressive) and benign groups. Results The CEST-Dixon sequence shows homogenous fat removal in the water-only images. The ER-negative IDC tissues display a trend to higher CEST contrast in all three frequencies ranges, while the ER-positive IDC, benign and normal tissues have lower CEST contrast. No significant differences were observed between the ER-positive IDC, benign and normal tissues. Of the three frequencies ranges, the CEST contrasts at 1 ppm are high in the ER-negative IDC group, have the largest difference between the ER-negative IDC and the other groups and have the highest correlation with Ki-67. Conclusions Breast CEST-Dixon imaging shows potential to differentiate more aggressive from less aggressive cancers.

This paper considers a high-dimensional stochastic SEIQR (susceptible-exposed-infected-quarantined-recovered) epidemic model with quarantine-adjusted incidence and the imperfect vaccination. The main aim of this study is to investigate stochastic effects on the SEIQR epidemic model and obtain its thresholds. We first obtain the sufficient condition for extinction of the disease of the stochastic system. Then, by using the theory of Hasminskii and the Lyapunov analysis methods, we show there is a unique stationary distribution of the stochastic system and it has an ergodic property, which means the infectious disease is prevalent. This implies that the stochastic disturbance is conducive to epidemic diseases control. At last, computer numerical simulations are carried out to illustrate our theoretical results.

Purpose Chemical exchange saturation transfer (CEST) MRI is increasingly evolving from brain to body applications. One of the known problems in the body imaging is the presence of strong lipid signals. Although their influence on the CEST effect is acknowledged, there was no study that focuses on the interplay among echo time, fat fraction, and Z-spectrum. This study strives to address these points, with the emphasis on the application in the breast. Methods Z-spectra were simulated in phase and out of phase of the main fat peak at -3.4 ppm, with the fat fraction varying from 0 to 100%. The magnetization transfer ratio asymmetry in two ranges, centering at the exchanging pool and at 3.5 ppm approximately opposite the nonexchanging fat pool, were calculated and were plotted against fat fraction. The results were verified in phantoms and in vivo. Results The results demonstrate the combined influence of fat fraction and echo time on the Z-spectrum for gradient echo based CEST acquisitions. The influence is straightforward in the in-phase images, but it is more complicated in the out-of-phase images, potentially leading to erroneous CEST contrast. Conclusions This study provides a basis for understanding the origin and appearance of lipid artifacts in CEST imaging, and lays the foundation for their efficient removal. Magn Reson Med 79:2731-2737, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

In this paper, considering the impact of stochastic environment noise on infection rate, a stochastic SIS epidemic model with nonlinear incidence rate is proposed and analyzed. Firstly, for the corresponding deterministic system, the threshold which determines the extinction or permanence of the disease is obtained by analyzing the stability of the equilibria. Then, for the stochastic system, the global dynamics is investigated by using the theory of stochastic differential equations; especially the threshold dynamics is explored when the stochastic environment noise is small. The results show that the condition for the epidemic disease to go to extinction in the stochastic system is weaker than that of the deterministic system, which implies that stochastic noise has a significant impact on the spread of infectious diseases and the larger stochastic noise is conducive to controlling the epidemic diseases. To illustrate this phenomenon, we give some computer simulations with different intensities of the stochastic noise.

Additional file 1. Supplementary figures, results and information.

Background: Tumor purity is of great significance for the study of tumor genotyping and the prediction of recurrence, which is significantly affected by tumor heterogeneity. Tumor heterogeneity is the basis of drug resistance in various cancer treatments, and DNA methylation plays a core role in the generation of tumor heterogeneity. Almost all types of cancer cells are associated with abnormal DNA methylation in certain regions of the genome. The selection of tumor-related differential methylation sites, which can be used as an indicator of tumor purity, has important implications for purity assessment. At present, the selection of information sites mostly focuses on inter-tumor heterogeneity and ignores the heterogeneity of tumor growth space that is sample specificity. Results: Considering the specificity of tumor samples and the information gain of individual tumor sample relative to the normal samples, we present an approach, PESM, to evaluate the tumor purity through the specificity difference methylation sites of tumor samples. Applied to more than 200 tumor samples of Prostate adenocarcinoma (PRAD) and Kidney renal clear cell carcinoma (KIRC), it shows that the tumor purity estimated by PESM is highly consistent with other existing methods. In addition, PESM performs better than the method that uses the integrated signal of methylation sites to estimate purity. Therefore, different information sites selection methods have an important impact on the estimation of tumor purity, and the selection of sample specific information sites has a certain significance for accurate identification of tumor purity of samples.

We define several novel centrality metrics: the high-order degree and combined degree of undirected network, the high-order out-degree and in-degree and combined out out-degree and in-degree of directed network. Those are the measurement of node importance with respect to the number of the node neighbors. We also explore those centrality metrics in the context of several best-known networks. We prove that both the degree centrality and eigenvector centrality are the special cases of the high-order degree of undirected network, and both the in-degree and PageRank algorithm without damping factor are the special cases of the high-order in-degree of directed network. Finally, we also discuss the significance of high-order out-degree of directed network. Our centrality metrics work better in distinguishing nodes than degree and reduce the computation load compared with either eigenvector centrality or PageRank algorithm.

The 3D short tau inversion recovery (STIR) sequence is routinely used in clinical MRI to achieve robust fat suppression. However, the performance of the commonly used adiabatic inversion pulse, hyperbolic secant (HS), is compromised in challenging areas with increased BTo demonstrate the frequency offset corrected inversion (FOCI) pulse as an efficient fat suppression STIR pulse with increased robustness to BProspective.Initial evaluation was performed in phantoms and one healthy volunteer by varying the B3T; 3D TSE-STIR with HS and FOCI pulses.Brachial plexus images were qualitatively evaluated by two musculoskeletal radiologists independently using a four-point grading scale for fat suppression, shading artifacts, and nerve visualization.The Wilcoxon signed-rank test with P 0.05 was considered statistically significant.Simulations and phantom experiments demonstrated broader bandwidth (2.5 kHz vs. 0.83 kHz, increased BThe FOCI pulse has increased robustness to B1 Techinical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1104-1111.

PURPOSE: CEST MRI for breast lesion characterization is promising. However, artifacts are prone to develop in breast CEST imaging due to strong lipid signals. The aims of the study are: 1) to develop and validate the CEST-Dixon imaging sequence for simultaneous water-fat separation and B(0) mapping; 2) use the CEST-Dixon method to characterize suspicious lesions in patients undergoing percutaneous biopsy. METHODS: The gradient-echo multi-echo Dixon acquisition is used to create fat-free CEST and B(0) maps. The sequence has been validated in phantoms and in vivo. Five healthy volunteers and ten patients were scanned to compare the CEST contrast in three frequency ranges centered at 1, 2 and 3.5 ppm. The correlation between the CEST contrast and pathology markers (tumor type, ER status, Ki-67) was also investigated by stratifying the patients into ER-negative invasive ductal carcinoma (IDC) (more aggressive), ER-positive IDC (less aggressive) and benign groups. RESULTS: The CEST-Dixon sequence shows homogenous fat removal in the water-only images. The ER-negative IDC tissues display a trend to higher CEST contrast in all three frequencies ranges, while the ER-positive IDC, benign and normal tissues have lower CEST contrast. No significant differences were observed between the ER-positive IDC, benign and normal tissues. Of the three frequencies ranges, the CEST contrasts at 1 ppm are high in the ER-negative IDC group, have the largest difference between the ER-negative IDC and the other groups and have the highest correlation with Ki-67. CONCLUSIONS: Breast CEST-Dixon imaging shows potential to differentiate more aggressive from less aggressive cancers.

The Loess Plateau is located in the semi-arid part of China and is regarded as one of the most eroded areas in the world. Based on a review of relevant researches and results, we give a comprehensive summary of the status quo of the Loess Plateau, including its natural environment (e.g., geomorphology and geology, soils, water, climate, vegetation, land use), socioeconomic conditions, and ecological problems and risks. In order to achieve a more sustainable regional development, constraints and challenges are discussed that can be used as a basis for improving implemented management practices. Moreover, ecological problems and risks resulting from control of soil and water loss are raised, which provide implications for ecological and economic development, as well as land-use changes in the region. At the end, we provide some insights and recommendations for the agricultural and economic development of the Loess Plateau.

Purpose To develop and evaluate magnetic resonance (MR) neurography of the brachial plexus with robust fat and blood suppression for increased conspicuity of nerves at 3.0 T in clinically feasible acquisition times. Materials and Methods This prospective study was HIPAA compliant, with institutional review board approval and written informed consent. A low-refocusing-flip-angle three-dimensional (3D) turbo spin-echo (TSE) sequence was modified to acquire both in-phase and out-of-phase echoes, required for chemical shift (Dixon) reconstruction, in the same repetition by using partial echoes combined with modified homodyne reconstruction with phase preservation. This multiecho TSE modified Dixon (mDixon) sequence was optimized by using simulations and phantom studies and in three healthy volunteers. The sequence was tested in five healthy volunteers and was evaluated in 10 patients who had been referred for brachial plexopathy at 3.0 T. The images were evaluated against the current standard of care, images acquired with a 3D TSE short inversion time inversion recovery (STIR) sequence, qualitatively by using the Wilcoxon signed-rank test and quantitatively by using the Friedman two-way analysis of variance, with P.05 considered to indicate a statistically significant difference. Results Multiecho TSE-mDixon involving partial-echo and homodyne reconstruction with phase preservation achieved uniform fat suppression in half the imaging time compared with multiacquisition TSE-mDixon. Compared with 3D TSE STIR, fat suppression, venous suppression, and nerve visualization were significantly improved (P.05), while arterial suppression was better but not significantly so (P = .06), with increased apparent signal-to-noise ratio in the dorsal nerve root ganglion and C6 nerve (P.001) with the multiecho TSE-mDixon sequence. Conclusion The multiecho 3D TSE-mDixon sequence provides robust fat and blood suppression, resulting in increased conspicuity of the nerves, in clinically feasible imaging times and can be used for MR neurography of the brachial plexus at 3.0 T.

Genome-wide association studies (GWAS) are used to identify diseases associated with single nucleotide polymorphisms (SNPs). But many existing methods did not consider the interactions among SNPs while SNPs form a network in complex interrelated ways. In our research, we attempted to establish case and control mutual information networks based on simulation data of breast cancer associated gene BRCA2. By constructing the network and comparing the network statistics, the average degree of network is found to clearly distinguish the case and control groups. Starting from the network structure, we put forward a method to find “structural key SNPs”, and got four structural key SNPs. Two out of these four SNPs are pre-assigned causal SNPs in BRCA2. A large number of simulative experiments and results illustrate the feasibility of our proposed method.

Single nucleotide polymorphism (SNP)-set analysis in genome-wide association studies (GWASs) has become a hot topic. Most existing SNP-set analystic methods are designed and work well according to the different natures of common or rare variants and associated diseases. But the information that the disease associated variants are common or rare cannot be gained in advance. Therefore, in this research, we proposed a new and powerful weighted function method without distinguishing common or rare variants to select tagging SNP-set. We applied our selection method to sequence kernel association test (SKAT) and compared the power with some existing methods. The simulation results showed that our method has higher power not only than SKAT in un-weighted case, but also than SKAT in other weighted functions. Moreover, the power is improved significantly when the minor allele frequency (MAF) of causal SNP is relatively small.

In Positron Emission Tomography (PET), crystal look-up tables (CLUT) are used to map the positions of incident annihilation photons to individual crystals in a typical 2D scintillator detector. To obtain the CLUT, a flood image of the detector is first acquired by irradiating the detector with a flood source. The flood image is then segmented into regions, each corresponding to a specific crystal in the detector. In this paper, a simple and robust method is proposed for fast crystal identification. First, morphology methods and a Gaussian kernel are applied to enhance the contrast of the image. Local maxima is then searched and identified as peaks. A fast method is developed to sort the peaks and the borders of the crystal are calculated using the coordinates of adjacent peaks. CLUT is then generated based on the borders of the crystals. A MATLAB graphical user interface (GUI) tool incorporating the proposed method is also developed to facilitate optional interactive operations. The method was tested using (1) a flood image of an Inveon detector; (2) four flood images of PET insert detectors; (3) a flood image of a clinical PET scanner detector; (4) a flood image of a prototype PETbox detector and (5) four flood images of MicroPET R4 detectors. For all the flood images tested, 3 edge crystals in one of the MicroPET R4 detectors and 8 edge crystals in the prototype PETbox detector were failed to be identified. Besides that, all the crystals were automatically segmented and the resulting CLUT were reasonably satisfactory. The computational time for segmentation in the MATLAB environment was less than 2 sec for each flood image on a standard Pc. Results show that the proposed method exhibits reasonably good performance as well as robustness dealing with different flood images and we believe it could be used in the daily basis where thousands of crystals need to be accurately identified.

[Purpose]Soil moisture is a main limiting factor to influence vegetation restoration in loess plateau. Studying the impact of environmental factors on spatial distribution of soil water resource from regional scale can make it easier to understand the relationship between vegetation restoration and eco-environment construction, which can provide theoretical basis about soil water resource effective utilization and management. [Method]Taken Yanhe river basin as a study area, methods of variance analysis and multiple comparison was used to analyze the influence of climate, topography and land use type on soil moisture. [Result] The results are as follows: annual average temperature rainfall has significant influence on soil moisture with soil of 0∼40cm and 40∼140 cm depth, and annual average temperature has significant influence on soil moisture with soil of 40∼140cm and 40∼200 cm depth with their interaction having significant on all study layers; only slope aspect in topographic factors has significant influence on soil moisture with soil of 0∼40cm and 40∼140 cm depth; land use types have significant on all study layers. [Conclusions] Reasonable land use pattern is the key for high efficiency utilization of soil moisture and vegetation restoration.

A new segmentation method for segmenting the scalp, skull, cerebrospinal fluid (CSF) layer, grey matter and white matter in MRI of mouse brain was proposed. The method is based on the threshold, K-means Clustering and Narrow Band Level Set methods. Firstly, the threshold for skull segmentation is obtained by simple interaction. Secondly, skull segmentation using threshold methods combined with dilation and erosion and the skull upper surface is extracted. Thirdly, brain is extracted using narrow band level set method and scalp is obtained by minus other tissues. In the next step, brain is segmented by fuzzy c-means clustering. Finally, the 3D segmentation result is reconstructed.

Two novel durene-containing molecules, 1,4-bis-[4-(9-carbazolyl)-phenyl]-durene (CPD) and 1,4-bis-{4-[9-(3,6-(di-tert-butyl)carbazoyl)]-phenyl}-durene (t-BuCPD), which are derived from 4,4′-bis(9-carbazolyl)biphenyl (CBP) by inserting durene in its biphenyl core, are designed and synthesized for use as host materials for blue phosphors in organic light-emitting diodes (OLEDs). Inserting durene in biphenyl causes a right-angle torsion between the durene and the adjacent phenyl groups due to the strong steric hindrance effect of the durene group, confining the effective π-conjugation on only one carbazole and one phenyl and increasing the triplet energies of CPD and t-BuCPD to over 3.0 eV. These durene-decorated molecules show higher thermal stabilities than many other CBP derivatives. Blue phosphorescent OLEDs were fabricated using CPD and t-BuCPD as triplet hosts and traditional iridium(III)bis(4,6-(difluorophenyl)pyridinato-N,C2′)picolinate (Firpic) as a dopant and excellent performances were achieved. In particular, peak efficiencies of 26.2 cd A−1 and 14.8 lm W−1 were realized when CPD was used as both a host and exciton-blocking material. This is the first report using durene to tune the triplet energy levels of phosphorescent host materials.

Homoleptic tris-cyclometalated iridium(III) complexes containing 2-phenylbenzothiazole derivatives as ligands have been successfully synthesized and characterized for the first time. Electron-donating (CH3, OCH3) and -withdrawing groups (F) were introduced into the 6-position of the benzothiazole moiety in the ligands to verify their influence on the optical and electronic properties of the complexes. Organic light-emitting diodes using these iridium complexes as doped emitters exhibited orange electrophosphorescence with excellent performances. An extremely high brightness of 95 800 cd m−2 and a maximum luminance efficiency of 87.9 cd A−1 (46.0 lm W−1) were achieved for the pristine complex without any substituent in the ligand. These performances represent a significant improvement for vacuum-deposited orange OLEDs and the new record of the efficiencies for orange OLEDs reported so far. The substituents in the ligand were observed to be rather unimportant to influence the performance of this series of iridium complexes.