Cyclin D1-mediated microRNA expression signature predicts breast cancer outcome

Background: Genetic classification of breast cancer based on the coding mRNA suggests the evolution of distinct subtypes. Whether the non-coding genome is altered concordantly with the coding genome and the mechanism by which the cell cycle directly controls the non-coding genome is poorly understood. Methods: Herein, the miRNA signature maintained by endogenous cyclin D1 in human breast cancer cells was defined. In order to determine the clinical significance of the cyclin D1-mediated miRNA signature, we defined a miRNA expression superset from 459 breast cancer samples. We compared the coding and non-coding genome of breast cancer subtypes. Results: Hierarchical clustering of human breast cancers defined four distinct miRNA clusters (G1-G4) associated with distinguishable relapse-free survival by Kaplan-Meier analysis. The cyclin D1-regulated miRNA signature included several oncomirs, was conserved in multiple breast cancer cell lines, was associated with the G2 tumor miRNA cluster, ERα+ status, better outcome and activation of the Wnt pathway. The coding and non-coding genome were discordant within breast cancer subtypes. Seed elements for cyclin D1-regulated miRNA were identified in 63 genes of the Wnt signaling pathway including DKK. Cyclin D1 restrained DKK1 via the 3\u27UTR. In vivo studies using inducible transgenics confirmed cyclin D1 induces Wnt-dependent gene expression. Conclusion: The non-coding genome defines breast cancer subtypes that are discordant with their coding genome subtype suggesting distinct evolutionary drivers within the tumors. Cyclin D1 orchestrates expression of a miRNA signature that induces Wnt/β-catenin signaling, therefore cyclin D1 serves both upstream and downstream of Wnt/β-catenin signaling

A trajectory and force dual-incremental robot skill learning and generalization framework using improved dynamical movement primitives and adaptive neural network control

Due to changes in the environment and errors that occurred during skill initialization, the robot's operational skills should be modified to adapt to new tasks. As such, skills learned by the methods with fixed features, such as the classical Dynamical Movement Primitive (DMP), are difficult to use when the using cases are significantly different from the demonstrations. In this work, we propose an incremental robot skill learning and generalization framework including an incremental DMP (IDMP) for robot trajectory learning and an adaptive neural network (NN) control method, which are incrementally updated to enable robots to adapt to new cases. IDMP uses multi-mapping feature vectors to rebuild the forcing function of DMP, which are extended based on the original feature vector. In order to maintain the original skills and represent skill changes in a new task, the new feature vector consists of three parts with different usages. Therefore, the trajectories are gradually changed by expanding the feature and weight vectors, and all transition states are also easily recovered. Then, an adaptive NN controller with performance constraints is proposed to compensate dynamics errors and changed trajectories after using the IDMP. The new controller is also incrementally updated and can accumulate and reuse the learned knowledge to improve the learning efficiency. Compared with other methods, the proposed framework achieves higher tracking accuracy, realizes incremental skill learning and modification, achieves multiple stylistic skills, and is used for obstacle avoidance with different heights, which are verified in three comparative experiments

Comparison of thoracoabdominal versus abdominal-transhiatal surgical approaches in Siewert type II adenocarcinoma at the esophagogastric junction: Protocol for a prospective multicenter randomized controlled trial

BackgroundSiewert type II adenocarcinoma of the esophagogastric junction (Siewert II AEG) can be resected by the right thoracoabdominal surgical approach (RTA) or abdominal-transhiatal surgical approach (TH) under minimally invasive conditions. Although both surgical methods achieve complete tumor resection, there is a debate as to whether the former method is superior to or at least noninferior to the latter in terms of surgical safety. Currently, a small number of retrospective studies have compared the two surgical approaches, with inconclusive results. As such, a prospective multicenter randomized controlled trial is necessary to validate the value of RTA (Ivor-Lewis) compared to TH.MethodsThe planned study is a prospective, multicenter, randomized clinical trial. Patients (n=212) with Siewert II AEG that could be resected by either of the above two surgical approaches will be included in this trial and randomized to the RTA group (n=106) or the TH group (n=106). The primary outcome will be 3-year disease-free survival (DFS). The secondary outcomes will include 5-year overall survival (OS), incidence of postoperative complications, postoperative mortality, local recurrence rate, number and location of removed lymph nodes, quality of life (QOL), surgical Apgar score, and duration of the operation. Follow-ups are scheduled every three months for the first 3 years after the surgery and every six months for the next 2 years.DiscussionAmong Siewert II AEG patients with resectable tumors, this is the first prospective, randomized clinical trial comparing the surgical safety of minimally invasive RTA and TH. RTA is hypothesized to provide better digestive tract reconstruction and dissection of mediastinal lymph nodes while maintaining a high quality of life and good postoperative outcome. Moreover, this trial will provide a high level of evidence for the choice of surgical procedures for Siewert II AEG.Clinical trial registrationChinese Ethics Committee of Registering Clinical Trials, identifier (ChiECRCT20210635); Clinical Trial.gov, identifier (NCT05356520)

Emergence of Xin Demarcates a Key Innovation in Heart Evolution

The mouse Xin repeat-containing proteins (mXinα and mXinβ) localize to the intercalated disc in the heart. mXinα is able to bundle actin filaments and to interact with β-catenin, suggesting a role in linking the actin cytoskeleton to N-cadherin/β-catenin adhesion. mXinα-null mouse hearts display progressively ultrastructural alterations at the intercalated discs, and develop cardiac hypertrophy and cardiomyopathy with conduction defects. The up-regulation of mXinβ in mXinα-deficient mice suggests a partial compensation for the loss of mXinα. To elucidate the evolutionary relationship between these proteins and to identify the origin of Xin, a phylogenetic analysis was done with 40 vertebrate Xins. Our results show that the ancestral Xin originated prior to the emergence of lamprey and subsequently underwent gene duplication early in the vertebrate lineage. A subsequent teleost-specific genome duplication resulted in most teleosts encoding at least three genes. All Xins contain a highly conserved β-catenin-binding domain within the Xin repeat region. Similar to mouse Xins, chicken, frog and zebrafish Xins also co-localized with β-catenin to structures that appear to be the intercalated disc. A putative DNA-binding domain in the N-terminus of all Xins is strongly conserved, whereas the previously characterized Mena/VASP-binding domain is a derived trait found only in Xinαs from placental mammals. In the C-terminus, Xinαs and Xinβs are more divergent relative to each other but each isoform from mammals shows a high degree of within-isoform sequence identity. This suggests different but conserved functions for mammalian Xinα and Xinβ. Interestingly, the origin of Xin ca. 550 million years ago coincides with the genesis of heart chambers with complete endothelial and myocardial layers. We postulate that the emergence of the Xin paralogs and their functional differentiation may have played a key role in the evolutionary development of the heart

A framework for composite layup skill learning and generalizing through teleoperation

In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer. Although there are some works on human-robot skill transfer, it is still difficult to transfer the manipulation skill to robots through teleoperation efficiently and intuitively. In this article, we developed an impedance-based control architecture of telemanipulation in task space for the human-robot skill transfer through teleoperation. This framework not only achieves human-robot skill transfer but also provides a solution to human-robot collaboration through teleoperation. The variable impedance control system enables the compliant interaction between the robot and the environment, smooth transition between different stages. Dynamic movement primitives based learning from demonstration (LfD) is employed to model the human manipulation skills, and the learned skill can be generalized to different tasks and environments, such as the different shapes of components and different orientations of components. The performance of the proposed approach is evaluated on a 7 DoF Franka Panda through the robot-assisted composite layup on different shapes and orientations of the components

Near Real-time Fine-resolution Land Surface Phenological Prediction Using Convolutional Neural Network and Data Fusion

Near real-time fine-resolution land surface phenology (LSP) prediction is essential for understanding surface attributes and ecosystem functions, and solving important ecological processes related to phenology at the landscape scale. In this paper, we applied the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) to fuse image pairs of Landsat 8 and Moderate-resolution Imaging Spectroradiometer (MODIS) as train data, and then applied the first derivative method to retrieve phenophase transition dates from fused time series of satellite data as label data. The convolutional neural network (CNN) model was trained using fusion images as inputs and the label data as targets. The trained model was further used to predict LSP dates from individual Landsat images. As evaluated using the reference data, the predict land surface phenological dates and could match the reference well with the coefficient of determination of 0.77 and root mean squared errors of 3.535, and our study provides an alternative method to predict land surface phenological dates using individual Landsat images

The Application of Discrete Wavelet Transform with Improved Partial Least-Squares Method for the Estimation of Soil Properties with Visible and Near-Infrared Spectral Data

This study evaluated whether wavelet functions (Bior1.3, Bior2.4, Db4, Db8, Haar, Sym4, and Sym8) and decomposition levels (Levels 3–8) can estimate soil properties. The analysis is based on the discrete wavelet transform with partial least-squares (DWT–PLS) method, incorporated into a visible and near-infrared reflectance analysis. The improved DWT–PLS method (called DWT–Stepwise-PLS) enhances the accuracy of the quantitative analysis model with DWT–PLS. The cation exchange capacity (CEC) was best estimated by the DWT–PLS model using the Haar wavelet function. This model yielded the highest coefficient of determination (Rv2 = 0.787, p < 0.001), with the highest relative percentage deviation (RPD = 2.047) and lowest root mean square error (RMSE = 4.16) for the validation data set of the CEC. The RPD of the SOM predictions by DWT–PLS using the Bior1.3 wavelet function was maximized at 1.441 (Rv2 = 0.642, RMSE = 5.96), highlighting the poor overall predictive ability of soil organic matter (SOM) by DWT–PLS. Furthermore, the best performing decomposition levels of the wavelet function were distributed in the fifth, sixth, and seventh levels. For various wavelet functions and decomposition levels, the DWT–Stepwise-PLS method more accurately predicted the quantified soil properties than the DWT–PLS model. DWT–Stepwise-PLS using the Haar wavelet function remained the best choice for quantifying the CEC (Rv2 = 0.92, p < 0.001, RMSE = 4.91, and RPD = 3.57), but the SOM was better predicted by DWT–Stepwise-PLS using the Bior2.4 wavelet function (Rv2 = 0.8, RMSE = 5.34, and RPD = 2.24) instead of the Bior1.3 wavelet function. However, the performance of the DWT–Stepwise-PLS method tended to degrade at high and low decomposition levels of the DWT. These degradations were attributed to a lack of sufficient information and noise, respectively