Silencing long noncoding RNA LINC01133 suppresses pancreatic cancer through regulation of microRNA-1299-dependent IGF2BP3.

The deregulation of long noncoding RNAs (lncRNAs) holds great potential in the treatment of multiple cancers, including pancreatic cancer (PC). However, the specific molecular mechanisms by which LINC01133 contributes to pancreatic cancer remain unknown. Subsequent to bioinformatics analysis, we predicted and analyzed differentially expressed lncRNAs, microRNAs, and genes in pancreatic cancer. We determined the expression patterns of LINC01133, miR-1299, and insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3) in pancreatic cancer cells, and validated their interactions through luciferase reporter and RNA immunoprecipitation assays. We implemented loss-of-function and gain-of-function experiments for LINC01133, miR-1299, and IGF2BP3 to assay their potential effects on pancreatic cancer cell functions. We observed high expression of LINC01133 and IGF2BP3, but low expression of miR-1299, in pancreatic cancer cells. Furthermore, we found that LINC01133 enhances IGF2BP3 through binding with miR-1299. Silencing LINC01133 or IGF2BP3 and/or overexpressing miR-1299 limited pancreatic cancer cell proliferation, invasion, epithelial-mesenchymal transition, and suppressed tumorigenic abilities in mice lacking T cells (nude mice). Overall, our findings identified that silencing LINC01133 downregulates IGF2BP3 by upregulating miR-1299 expression, ultimately leading to the prevention of pancreatic cancer.

Radiative Decay Width of J/ψ→γη_{(2)} from N_{f}=2 Lattice QCD.

The large radiative production rate for pseudoscalar mesons in the J/ψ radiative decay remains elusive. We present the first lattice QCD calculation of partial decay width of J/ψ radiatively decaying into η_{(2)}, the SU(2) flavor singlet pseudoscalar meson, which confirms QCD U_{A}(1) anomaly enhancement to the coupling of gluons with flavor singlet pseudoscalar mesons. The lattice simulation is carried out using N_{f}=2 lattice QCD gauge configurations at the pion mass m_{π}≈350 MeV. In particular, the distillation method has been utilized to calculate light quark loops. The results are reported here with the mass m_{η_{(2)}}=718(8) MeV and the decay width Γ(J/ψ→γη_{(2)})=0.385(45) keV. By assuming the dominance of U_{A}(1) anomaly and flavor singlet-octet mixing angle θ=-24.5°, the production rates for the physical η and η^{'} in J/ψ radiative decay are predicted to be 1.15(14)×10^{-3} and 4.49(53)×10^{-3}, respectively, which agree well with the experimental measurement data. Our study manifests the potential of lattice QCD studies on the light hadron production in J/ψ radiative decays.

A numerical tool for assessing human thermal safety and thermal comfort in cold-weather activities.

This paper describes a newly developed software tool to evaluate human thermal safety and thermal comfort in cold-weather activities aimed at guiding users to arrange activity plans and select appropriate clothing ensembles. The software inputs include conditions of activity, environment, human body, and clothing ensemble. It outputs physiological temperatures, cold injury risks, thermal sensations, and thermal comforts in intuitive ways like cloud maps and curves. The software tool is characterized by (1) integration of a thermoregulatory model that predicts human thermophysiological responses under exercise conditions in cold environments, (2) the functions of clothing ensemble database and individual parameter database, (3) the human centric outputs that directly reflect human physiological and mental status, and (4) the user-friendly operation interface and output interface, as well as a wide applicability. The software is validated with human test studies covering ambient temperatures from - 30.6 to 5 °C, clothing ensembles from 1.34 to 3.20 clo, and activity intensities from 2 to 9 Mets. The average prediction RMSEs of core temperature, mean skin temperature, thermal sensation, and thermal comfort are 0.16 °C, 0.45 °C, 0.58, and 1.41, respectively. The software is an advanced expansion to current standards and guidance of cold exposure assessment and a meaningful tool for the fields of occupational health care, cold protection, and environmental ergonomics.

Rotating Lorentz Force Magnetic Bearings' Dynamics Modeling and Adaptive Controller Design.

To address the issues of our agile satellites' poor attitude maneuverability, low pointing stability, and pointing inaccuracy, this paper proposes a new type of stabilized platform based on seven-degree-of-freedom Lorentz force magnetic levitation. Furthermore, in this study, we designed an adaptive controller based on the RBF neural network for the rotating magnetic bearing, which can improve the pointing accuracy of satellite loads. To begin, the advanced features of the new platform are described in comparison with the traditional electromechanical platform, and the structural characteristics and working principle of the platform are clarified. The significance of rotating magnetic bearings in improving load pointing accuracy is also clarified, and its rotor dynamics model is established to provide the input and output equations. The adaptive controller based on the RBF neural network is designed for the needs of high accuracy of the load pointing, high stability, and strong robustness of the system, and the current feedback inner loop is added to improve the system stiffness and rapidity. The final simulation results show that, when compared to the PID controller and robust sliding mode controller, the controller's pointing accuracy and anti-interference ability are greatly improved, and the system robustness is strong, which can effectively improve the pointing accuracy and pointing stability of the satellite/payload, as well as provide a powerful means of solving related problems in the fields of laser communication, high score detection, and so on.

Immunomodulatory potential of natural products from herbal medicines as immune checkpoints inhibitors: Helping to fight against cancer via multiple targets.

Immunotherapy sheds new light to cancer treatment and is satisfied by cancer patients. However, immunotoxicity, single-source antibodies, and single-targeting stratege are potential challenges to the success of cancer immunotherapy. A huge number of promising lead compounds for cancer treatment are of natural origin from herbal medicines. The application of natural products from herbal medicines that have immunomodulatory properties could alter the landscape of immunotherapy drastically. The present study summarizes current medication for cancer immunotherapy and discusses the potential chemicals from herbal medicines as immune checkpoint inhibitors that have a broad range of immunomodulatory effects. Therefore, this review provides valuable insights into the efficacy and mechanism of actions of cancer immunotherapies, including natural products and combined treatment with immune checkpoint inhibitors, which could confer an improved clinical outcome for cancer treatment.

Effect of m6A methyltransferase METTL3 -mediated MALAT1/E2F1/AGR2 axis on adriamycin resistance in breast cancer.

N6-methyladenosine (m6A) methyltransferase METTL3 has been implicated in carcinogenesis, which may be associated the overexpression of MALAT1. However, the downstream mechanics actions remain largely unknown. This study intends to probe the downstream mechanism of the N6-methyladenosine (m6 A) methyltransferase METTL3 and MALAT1 in adriamycin resistance in breast cancer. Through Bioinformatics databases lncMAP, TCGA and GTEx, we predicted the downstream transcription factors E2F1 and AGR2 of MALAT1 in breast cancer. The Cancer Genome Atlas and Genotype-Tissue Expression (GTEx) databases were used to screen the downstream target genes of MALAT1. MeRIP-qPCR was used to detect the m6 A level of MALAT1 in cells. RIP was used to detect the binding between MALAT1 and E2F1, and chromatin immunoprecipitation (ChIP) for the binding of E2F1 to AGR2 promoter. Cell Counting Kit-8 and colony formation assays were used to detect cell viability. Transwell was used to detect cell invasion. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) and western blot were used to detect the expression of related genes and proteins. A nude mouse xenograft tumor model was established to observe the effect of METTL3 on adriamycin resistance of breast cancer. The total survival of mice after exogenous gene silencing was analyzed by the Kaplan-Meier method. METTL3 was highly expressed in adriamycin-resistant breast cancer cells. METTL3 promotes adriamycin resistance in breast cancer cells. METTL3 mediates the expression of MALAT1 in adriamycin-resistant breast cancer through m6 A. MALAT1 increases adriamycin resistance in breast cancer cells by recruiting E2F1 to activate AGR2 transcription. METTL3 can regulate the expression of MALAT1 through m6 A, mediate the E2F1/AGR2 axis, and promote the adriamycin resistance of breast cancer. METTL3 may modify MALAT1 protein through m6 A, recruit E2F1 and activate downstream AGR2 expression, thus promoting adriamycin resistance in breast cancer.

Modelling and experimental study of thermo-physiological responses of human exercising in cold environments.

A numerical human thermo-physiological model is developed with the consideration of characteristics of exercising people in cold environments. The developed model is characterized by: 1) the concept of net exercise efficiency which is used to correct the calculation of metabolic heat production by excluding mechanical energy; 2) the effects of low temperature on basal metabolic rate and basal blood flow rate; 3) the integration with a multi-layer clothing model to calculate the heat and moisture transfer through the clothing system, which takes into account the air gaps between the clothing layers to reflect the ventilation and air penetration effect from the ambient wind. Human subject experiment is conducted in a climate chamber to validate the proposed model. The human subject experiment is also carried out in a cold environment (-5 °C) combined with different air velocity conditions (still air, 2 m/s), taking into account the activities of different intensities (standing statically, 2 km/h walking and 7 km/h running). Thermo-physiological parameters including the core temperature, 8-point local skin temperatures and the clothing layer temperatures, are measured during the experiment. Comparison between the predicted and experimental results gives the root mean squared error (RMSE) of core temperature and mean skin temperature of 0.06-0.10 °C and 0.17-0.27 °C, respectively. RMSE values for local skin and clothing layer temperatures are no higher than 1.5 °C and most within 0.8 °C. The model is also validated with published data under various ambient temperature and activity intensity conditions. The proposed model is shown to be capable of predict the thermo-physiological responses of people exposed and exercising in cold environments.

Potential Focal Adhesion Kinase Inhibitors in Management of Cancer: Therapeutic Opportunities from Herbal Medicine.

Focal adhesion kinase (FAK) is a multifunctional protein involved in cellular communication, integrating and transducing extracellular signals from cell-surface membrane receptors. It plays a central role intracellularly and extracellularly within the tumor microenvironment. Perturbations in FAK signaling promote tumor occurrence and development, and studies have revealed its biological behavior in tumor cell proliferation, migration, and adhesion. Herein we provide an overview of the complex biology of the FAK family members and their context-dependent nature. Next, with a focus on cancer, we highlight the activities of FAK signaling in different types of cancer and how knowledge of them is being used for screening natural compounds used in herbal medicine to fight tumor development.

Research on the variations in individual waste separation behavior due to different information strategies-Mediating effects of psychological distance.

Although information intervention can guide individual behavior, there are variations in information interpretation and processing results caused by different psychological distances. This study explored the explanation mechanism underlying individual psychological distances and their effects on different information intervention strategies that aim to improve waste separation behavior. The survey sample data obtained from large-scale field intervention experiments were analyzed using regression analysis, a difference-in-difference test, and T-tests. The results showed that (1) psychological distance has a significant mediating effect on the interaction between the cognition of separation and waste separation behavior; (2) modeling is a form of information intervention effectively promotes individual waste separation behavior and the waste separation behavior relationship; (3) among groups with different cognitions of separation, modeling can significantly promote the waste separation behavior of the group with low-level concerns as it improves their habit and citizen dimensions. The publicity and education strategies can positively promote the habit dimension of the group with low-level concerns, but it has a negative effect on the waste separation behavior of the high-level concerns group; (4) among groups with different psychological distances towards waste separation, modeling can significantly promote the waste separation behavior of the group with a closer expected distance. The research results provide effective theoretical support and practical significance for promoting individual waste separation behavior and realizing waste recycling and reduction.

Antibacterial Activity of Aureonuclemycin Produced by Streptomyces aureus Strain SPRI-371.

Actinomycetes play a vital role as one of the most important natural resources for both pharmaceutical and agricultural applications. The actinomycete strain SPRI-371, isolated from soil collected in Jiangsu province, China, was classified as Streptomyces aureus based on its morphological, physiological, biochemical and molecular biological characteristics. Its bacterial activity metabolites were identified as aureonuclemycin (ANM), belonging to adenosine derivatives with the molecular formula C16H19N5O9 for ANM A and C10H13N5O3 for ANM B. Simultaneously, the industrial fermentation process of a mutated S. aureus strain SPRI-371 was optimized in a 20 m3 fermentation tank, featuring a rotation speed of 170 rpm, a pressure of 0.05 MPa, an inoculum age of 36−40 h and a dissolved oxygen level maintained at 1−30% within 40−80 h and at >60% in the later period, resulting in an ANM yield of >3700 mg/L. In the industrial separation of fermentation broth, the sulfuric acid solution was selected to adjust pH and 4# resin was used for adsorption. Then, it was resolved with 20% ethanol solution and concentrated in a vacuum (60−65 °C), with excellent results. Antibacterial experiments showed that ANM was less active or inactive against Xanthomonas oryzae pv. oryzae, Xanthomonas citri subsp. citri and Xanthomonas oryzae pv. oryzicola and most bacteria, yeast and fungi in vitro. However, in vivo experiments showed that ANM exhibited extremely significant protective and therapeutic activity against diseases caused by X. oryzae pv. oryzae and X. oryzae pv. oryzicola in rice and X. citri in oranges and lemons. In field trials, ANM A 150 gai/ha + ANM B 75 gai/ha exhibited excellent therapeutic activity against rice bacterial leaf blight, citrus canker and rice bacterial leaf streak. Furthermore, as the dosage and production cost of ANM are lower than those of commercial drugs, it has good application prospects.

RUN-UP: Accelerated multishot diffusion-weighted MRI reconstruction using an unrolled network with U-Net as priors.

PURPOSE: To accelerate and improve multishot diffusion-weighted MRI reconstruction using deep learning. METHODS: An unrolled pipeline containing recurrences of model-based gradient updates and neural networks was introduced for accelerating multishot DWI reconstruction with shot-to-shot phase correction. The network was trained to predict results of jointly reconstructed multidirection data using single-direction data as input. In vivo brain and breast experiments were performed for evaluation. RESULTS: The proposed method achieves a reconstruction time of 0.1 second per image, over 100-fold faster than a shot locally low-rank reconstruction. The resultant image quality is comparable to the target from the joint reconstruction with a peak signal-to-noise ratio of 35.3 dB, a normalized root-mean-square error of 0.0177, and a structural similarity index of 0.944. The proposed method also improves upon the locally low-rank reconstruction (2.9 dB higher peak signal-to-noise ratio, 29% lower normalized root-mean-square error, and 0.037 higher structural similarity index). With training data from the brain, this method also generalizes well to breast diffusion-weighted imaging, and fine-tuning further reduces aliasing artifacts. CONCLUSION: A proposed data-driven approach enables almost real-time reconstruction with improved image quality, which improves the feasibility of multishot DWI in a wide range of clinical and neuroscientific studies.

Long non-coding RNA MIR100HG promotes the migration, invasion and proliferation of triple-negative breast cancer cells by targeting the miR-5590-3p/OTX1 axis.

BACKGROUND: As an aggressive subtype of breast cancer with a high risk of recurrence, triple-negative breast cancer (TNBC) lacks available treatment targets. LncRNA MIR100HG promotes cell proliferation in TNBC. However, few studies have investigated the molecular mechanism of MIR100HG in TNBC. Thus, additional in-depth investigations are needed to unravel its associated regulatory mechanism. METHODS: MIR100HG and miR-5590-3p expression in TNBC tissue samples and cell lines was detected by RT-qPCR. Flow cytometry, transwell, wound-healing, CCK8 and colony formation assays were performed to analyse cell apoptosis, cell cycle, invasion, migration and proliferation. The protein expression of orthodenticle homeobox 1 (OTX1) and proteins in the ERK/MAPK signalling pathway were assessed by western blot analysis. Bioinformatics and luciferase assay were performed to predict and validate the interaction between MIR100HG and miR-5590-3p as well as OTX1 and miR-5590-3p. RNA immunoprecipitation (RIP) was used to detect the interaction between MIR100HG and miR-5590-3p. Subcutaneous tumour growth was observed in nude mice. Immunohistochemistry (IHC) analysis was used to assess OTX1 expression in tumour tissues. RESULTS: MIR100HG expression was upregulated, whereas that of miR-5590-3p was downregulated in TNBC. MIR100HG was shown to directly interact with miR-5590-3p. Furthermore, MIR100HG knockdown could promote TNBC cell apoptosis and cell cycle arrest in G0/G1 phase while inhibiting migration, invasion and proliferation. Furthermore, miR-5590-3p inhibition showed the opposite results and could reverse the effect of MIR100HG knockdown in TNBC cells. MiR-5590-3p downregulated the ERK/MAPK signalling pathway, suppressed the migration, invasion and proliferation of TNBC cells and promoted their apoptosis and cell cycle arrest in G0/G1 phase by targeting OTX1. In addition, MIR100HG knockdown inhibited OTX1 expression by upregulating miR-5590-3p in vivo, thereby inhibiting tumour growth. CONCLUSIONS: MIR100HG promotes the progression of TNBC by sponging miR-5590-3p, thereby upregulating OTX1, suggesting a new potential treatment target for TNBC.

Data-driven self-calibration and reconstruction for non-cartesian wave-encoded single-shot fast spin echo using deep learning.

BACKGROUND: Current self-calibration and reconstruction methods for wave-encoded single-shot fast spin echo imaging (SSFSE) requires long computational time, especially when high accuracy is needed. PURPOSE: To develop and investigate the clinical feasibility of data-driven self-calibration and reconstruction of wave-encoded SSFSE imaging for computation time reduction and quality improvement. STUDY TYPE: Prospective controlled clinical trial. SUBJECTS: With Institutional Review Board approval, the proposed method was assessed on 29 consecutive adult patients (18 males, 11 females, range, 24-77 years). FIELD STRENGTH/SEQUENCE: A wave-encoded variable-density SSFSE sequence was developed for clinical 3.0T abdominal scans to enable 3.5× acceleration with full-Fourier acquisitions. Data-driven calibration of wave-encoding point-spread function (PSF) was developed using a trained deep neural network. Data-driven reconstruction was developed with another set of neural networks based on the calibrated wave-encoding PSF. Training of the calibration and reconstruction networks was performed on 15,783 2D wave-encoded SSFSE abdominal images. ASSESSMENT: Image quality of the proposed data-driven approach was compared independently and blindly with a conventional approach using iterative self-calibration and reconstruction with parallel imaging and compressed sensing by three radiologists on a scale from -2 to 2 for noise, contrast, sharpness, artifacts, and confidence. Computation time of these two approaches was also compared. STATISTICAL TESTS: Wilcoxon signed-rank tests were used to compare image quality and two-tailed t-tests were used to compare computation time with P values of under 0.05 considered statistically significant. RESULTS: An average 2.1-fold speedup in computation was achieved using the proposed method. The proposed data-driven self-calibration and reconstruction approach significantly reduced the perceived noise level (mean scores 0.82, P < 0.0001). DATA CONCLUSION: The proposed data-driven calibration and reconstruction achieved twice faster computation with reduced perceived noise, providing a fast and robust self-calibration and reconstruction for clinical abdominal SSFSE imaging. LEVEL OF EVIDENCE: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:841-853.

Compressed Sensing: From Research to Clinical Practice with Deep Neural Networks.

Compressed sensing (CS) reconstruction methods leverage sparse structure in underlying signals to recover high-resolution images from highly undersampled measurements. When applied to magnetic resonance imaging (MRI), CS has the potential to dramatically shorten MRI scan times, increase diagnostic value, and improve overall patient experience. However, CS has several shortcomings which limit its clinical translation such as: 1) artifacts arising from inaccurate sparse modelling assumptions, 2) extensive parameter tuning required for each clinical application, and 3) clinically infeasible reconstruction times. Recently, CS has been extended to incorporate deep neural networks as a way of learning complex image priors from historical exam data. Commonly referred to as unrolled neural networks, these techniques have proven to be a compelling and practical approach to address the challenges of sparse CS. In this tutorial, we will review the classical compressed sensing formulation and outline steps needed to transform this formulation into a deep learning-based reconstruction framework. Supplementary open source code in Python will be used to demonstrate this approach with open databases. Further, we will discuss considerations in applying unrolled neural networks in the clinical setting.

Stereoselective Assembly of Multifunctional Spirocyclohexene Pyrazolones That Induce Autophagy-Dependent Apoptosis in Colorectal Cancer Cells.

Enantio- and diastereoselective synthesis of multifunctional spiropyrazolone scaffolds has been achieved using secondary amine-catalyzed [4 + 2] annulations of α,ß,γ,δ-unsaturated pyrazolones with aldehydes. The pyrazolone substrates serve as C4 synthons to produce 6-membered, carbocycle-based, chiral spiropyrazolone derivatives. The synthesized chiral compounds showed potent toxicity against a panel of cancer cell lines. The most potent compound 3h-induced cell cycle arrest and macroautophagy in HCT116 colorectal cancer cells, triggering autophagy-dependent apoptotic cell death.

A novel very simple laparoscopic hepatic inflow occlusion apparatus for laparoscopic liver surgery.

BACKGROUND: Control of bleeding is extremely important for laparoscopic liver resection. We introduce a new and operationally simple laparoscopic hepatic inflow occlusion apparatus (LHIOA) and its successful application in laparoscopic surgery for patients with cirrhosis. METHODS: The self-designed LHIOA was constructed using a tracheal catheter (7.5#) and infusion set. The tracheal catheter and infusion set were trimmed to 30 and 70 cm, to serve as an occlusion tube and occlusion tape, respectively. After establishment of pneumoperitoneum, the occlusion tape was inserted to encircle the hepatoduodenal ligament. The occlusion tube was then introduced and the ends of the occlusion tape were pulled out of it to occlude the hepatic inflow. Under intermittent vascular occlusion with the LHIOA, the liver parenchyma was transected using an ultrasonic scalpel and monopolar electrocoagulation. Outcomes of the application of the LHIOA in hepatocellular carcinoma patients with cirrhosis (LHIOA group, n = 46) were compared with patients undergoing laparoscopic hepatectomy without LHIOA (non-LHIOA group, n = 46), using one-to-one propensity case-matched analysis. RESULTS: The LHIOA effectively occluded the hepatic inflow while showing no damage to the hepatoduodenal ligament. The time required for presetting the LHIOA is 6.8 ± 0.6 min. The conversion rate in the non-LHIOA group was 13.0% while there was no conversion in the occlusion group (P < 0.001). The median blood loss of patients in the LHIOA group (60 ml, range 50-200 ml) was significantly less than that of patients in the non-LHIOA group (250 ml, range 100-800) (P < 0.001). Transfusion was required in 8 patients in the non-LHIOA group while no transfusion was required in the LHIOA group. The median operative time in the LHIOA group (157 min, range 80-217 min) was significantly shorter than that in the non-LHIOA group (204 min, range 105-278 min) (P < 0.001). CONCLUSIONS: The new LHIOA is effective, safe, and simple. It can significantly reduce conversion rate, blood loss, and operative time. It facilitates laparoscopic liver resection and is recommended for use.

The application of aptamer 5TR1 in triple negative breast cancer target therapy.

Chemotherapy is one of the standard strategies for treatment of breast cancer. Adriamycin (Dox) is a first-line chemotherapy agent for breast cancer. However, the gastrointestinal reactions, myocardial toxicity and other side effects caused by Dox due to its un-specific cytotoxicity limit the clinical treatment effect. To address this need, aptamer has been regarded as an ideal target molecular carrier. In the present study, we selected an aptamer 5TR1 that can specifically bind to the MUC1 protein which has been regarded as an important tumor biomarker, as well as a potential target in anticancer therapies. Dox was loaded on the modified 5TR1-GC, which specifically targets breast cancer cell MDA-MB-231. Cell viability and apoptosis assays demonstrated that the 5TR1-GC-Dox exhibited target specificity of cytotoxicity in MDA-MB-231. Moreover, in vivo xenograft study also confirmed that 5TR1-GC-Dox had a more effective effect on tumor growth inhibition and induced the apoptosis of malignant tumor cells compared to Dox. We provided a novel experimental and theoretical basis for developing an aptamer targeted drug system, thus to promote the killing effect of drugs on breast cells and to reduce the damage to normal cells and tissues for breast cancer.

MiR-137 Suppresses Triple-Negative Breast Cancer Stemness and Tumorigenesis by Perturbing BCL11A-DNMT1 Interaction.

BACKGROUND/AIMS: Triple negative breast cancer (TNBC) is resistant to conventional chemotherapy due to high proportions of cancer stem cells (CSCs). The aim of this study is to unravel the miR-137-mediated regulatory mechanism of B-cell lymphoma/leukemia 11A (BCL11A) in TNBC. METHODS: A corhort of 34 TNBC tumor tissues and paired adjacent normal tissues, as well as 25 non-TNBC tumor tissues and paired adjacent normal tissues were collected post-operatively from patients with breast cancer. Q-PCR was performed to determine the mRNA levels of miR-137 and BCL11A in breast tissues and cell lines. Bioinformatics analysis and dual luciferase reporter assay were used to verify the direct interaction between miR-137 and BCL11A. After up-/down-regulation of BCL11A, miR-137, or DNMT1 via lentiviral transduction in TNBC cell lines SUM149 and MDA-MB-231 cells, Q-PCR and Western blot assays were used to detect the expression levels of BCL11A, DNA methyltransferases 1 (DNMT1), and Islet-1 (ISL1). Mammosphere assay was conducted to assess tumorosphere formation ability of cells, coupled with flow cytometry to determine the percentage of breast cancer stem cells. Co-immunoprecipitation assay was used to determine the interaction between BCL11A and DNMT1. Xenograft tumorigenesis assay was performed to monitor tumor formation in vivo. RESULTS: BCL11A was highly expressed in TNBC, whereas miR-137 was significantly lower in both TNBC tissues and cell lines. miR-137 suppressed BCL11A expression at both mRNA and protein levels by directly targeting its 3'UTR. In both SUM149 and MDA-MB-231 cells, overexpression of miR-137 or knockdown of BCL11A reduced the number of tumoroshperes and the percentage of cancer stem cells in vitro, and inhibited tumor development in vivo. Furthermore, BCL11A interacted with DNMT1 in TNBC cells. Silencing of either BCL11A or DNMT1 impaired cancer stemness and tumorigenesis of TNBC via suppressing ISL1 expression both in vitro, and in vivo. CONCLUSIONS: By perturbing BCL11A-DNMT1 interaction, miR-137 impairs cancer stemness and suppresses tumor development in TNBC.

Variable-Density Single-Shot Fast Spin-Echo MRI with Deep Learning Reconstruction by Using Variational Networks.

Purpose To develop a deep learning reconstruction approach to improve the reconstruction speed and quality of highly undersampled variable-density single-shot fast spin-echo imaging by using a variational network (VN), and to clinically evaluate the feasibility of this approach. Materials and Methods Imaging was performed with a 3.0-T imager with a coronal variable-density single-shot fast spin-echo sequence at 3.25 times acceleration in 157 patients referred for abdominal imaging (mean age, 11 years; range, 1-34 years; 72 males [mean age, 10 years; range, 1-26 years] and 85 females [mean age, 12 years; range, 1-34 years]) between March 2016 and April 2017. A VN was trained based on the parallel imaging and compressed sensing (PICS) reconstruction of 130 patients. The remaining 27 patients were used for evaluation. Image quality was evaluated in an independent blinded fashion by three radiologists in terms of overall image quality, perceived signal-to-noise ratio, image contrast, sharpness, and residual artifacts with scores ranging from 1 (nondiagnostic) to 5 (excellent). Wilcoxon tests were performed to test the hypothesis that there was no significant difference between VN and PICS. Results VN achieved improved perceived signal-to-noise ratio (P = .01) and improved sharpness (P < .001), with no difference in image contrast (P = .24) and residual artifacts (P = .07). In terms of overall image quality, VN performed better than did PICS (P = .02). Average reconstruction time ± standard deviation was 5.60 seconds ± 1.30 per section for PICS and 0.19 second ± 0.04 per section for VN. Conclusion Compared with the conventional parallel imaging and compressed sensing reconstruction (PICS), the variational network (VN) approach accelerates the reconstruction of variable-density single-shot fast spin-echo sequences and achieves improved overall image quality with higher perceived signal-to-noise ratio and sharpness. © RSNA, 2018 Online supplemental material is available for this article.