Microrna Expression Profile and Differentially-Expressed Genes in Prolactinomas Following Bromocriptine Treatment

Little is known about the function of microRNAs in prolactinomas treated with bromocriptine. The aim of the study was to explore the microRNAs associated with bromocriptine-treated prolactinomas. Six prolactinoma samples were selected according to whether they received bromocriptine treatment or not before microsurgery, and microRNA expression profiles of bromocriptine-treated and untreated prolactinomas were screened by the miRCURY LNA Array. The differentially expressed microRNAs in microarrays were further validated by stem-loop real-time PCR and subjected to gene ontology analysis and KEGG pathway analysis. In addition, related genes of microRNAs were analyzed by qRT-PCR in 15 prolactinoma samples. The initial analysis by microarrays generated a list of 80 upregulated microRNAs and 71 downregulated microRNAs in treated prolactinomas compared to untreated prolactinomas. miR-206, miR-516b and miR-550 were confirmed to be significantly upregulated, while miR-671-5p was confirmed to be significantly downregulated in treated prolactinomas by qRT-PCR. microRNA-mRNA network analysis integrating GO and KEGG pathway annotation displayed some critical factors. Platelet-derived growth factor α polypeptide (PDGFA) and bone morphogenetic protein 4 (BMP4), were verified to be differentially expressed between the two groups. PDGFA was significantly upregulated in treated prolactinomas, while BMP4 was significantly downregulated in treated prolactinomas. Our study reveals differential expression of microRNAs in prolactinoma after pharmacotherapy. Specific microRNAs may be involved in the inhibition or promotion of prolactinoma tumor growth impacted by bromocriptine pharmacotherapy. PDGFA and BMP4 may be involved in the pharmacotherapy mechanism of prolactinoma

TCM-RF : Hedging the predictions of Random Forest

The output of traditional classifier is point prediction without giving any confidence of it. To the contrary, Transductive Confidence Machine (TCM), which is a novel framework that provides a prediction result coupled with its accurate confidence. This method also can hedge the prediction in which the predicting accuracy will be controlled by predefined confidence level. In the framework of TCM, the efficiency of prediction depends on the strangeness function of samples. This paper incorporates Random forests (RF) into the framework of TCM and proposes new TCM algorithm named TCM-RF, in which the strangeness obtained by RF will be used to implement the confidence prediction. Compared with traditional TCM algorithms, our method benefits from the more precise and robust strangeness measure and takes advantage of random forest. Experiments indicate its effectiveness and robustness. In addition, our study demonstrated that using ensemble strategies to define sample strangeness may be a more principled way than using a single classifier. On the other hand, it also shows that the paradigm of hedging prediction can be applied to an ensemble classifier

Methylprednisolone as Adjunct to Endovascular Thrombectomy for Large-Vessel Occlusion Stroke

Importance It is uncertain whether intravenous methylprednisolone improves outcomes for patients with acute ischemic stroke due to large-vessel occlusion (LVO) undergoing endovascular thrombectomy. Objective To assess the efficacy and adverse events of adjunctive intravenous low-dose methylprednisolone to endovascular thrombectomy for acute ischemic stroke secondary to LVO. Design, Setting, and Participants This investigator-initiated, randomized, double-blind, placebo-controlled trial was implemented at 82 hospitals in China, enrolling 1680 patients with stroke and proximal intracranial LVO presenting within 24 hours of time last known to be well. Recruitment took place between February 9, 2022, and June 30, 2023, with a final follow-up on September 30, 2023.InterventionsEligible patients were randomly assigned to intravenous methylprednisolone (n = 839) at 2 mg/kg/d or placebo (n = 841) for 3 days adjunctive to endovascular thrombectomy. Main Outcomes and Measures The primary efficacy outcome was disability level at 90 days as measured by the overall distribution of the modified Rankin Scale scores (range, 0 [no symptoms] to 6 [death]). The primary safety outcomes included mortality at 90 days and the incidence of symptomatic intracranial hemorrhage within 48 hours. Results Among 1680 patients randomized (median age, 69 years; 727 female [43.3%]), 1673 (99.6%) completed the trial. The median 90-day modified Rankin Scale score was 3 (IQR, 1-5) in the methylprednisolone group vs 3 (IQR, 1-6) in the placebo group (adjusted generalized odds ratio for a lower level of disability, 1.10 [95% CI, 0.96-1.25]; P = .17). In the methylprednisolone group, there was a lower mortality rate (23.2% vs 28.5%; adjusted risk ratio, 0.84 [95% CI, 0.71-0.98]; P = .03) and a lower rate of symptomatic intracranial hemorrhage (8.6% vs 11.7%; adjusted risk ratio, 0.74 [95% CI, 0.55-0.99]; P = .04) compared with placebo. Conclusions and Relevance Among patients with acute ischemic stroke due to LVO undergoing endovascular thrombectomy, adjunctive methylprednisolone added to endovascular thrombectomy did not significantly improve the degree of overall disability.Trial RegistrationChiCTR.org.cn Identifier: ChiCTR210005172

Research on Control Strategy of Free-Piston Stirling Power Generating System

As a clean and fuel adaptive alternative power plant, the Stirling power generating system has drawn attention of experts and scholars in the energy field. In practical application, the instability of free-piston Stirling power generating system caused by abrupt load change is an inevitable problem. Thus, methods to improve the output frequency response and stability of the free-piston Stirling power generating system are necessary. The model of free-piston Stirling power generating system is built by isothermal analysis firstly, and the initial control strategy based on given voltage system is put forward. To further improve the performance of power system, a current feedback decoupling control strategy is proposed, and the mathematical model is established. The influence of full decoupled quadrature-direct (d-q) axis currents is analyzed with respect to the output voltage adjusting time and fluctuation amplitude under the variations of piston displacement and output load. The simulation results show that the system performance is significantly improved, but the dynamic regulation lags caused by the decoupled current control still exist. To solve this problem and improve the performance of decoupled-state feedback current control that relies on parameter accuracy, internal model control based on sliding mode (IMC-SM) current decoupling control strategy is proposed, the system model is established, and then the performance of voltage ripple in generating mode is improved. Finally, the test bench is built, and the steady state and transient voltage control performances are tested. The feasibility and priority of the control strategy is verified by experiment and simulation results

Adaptive association rule mining for web video event classification

Due to the popularity and development of social networks and web video sites, we have witnessed an exponential growth in the volumes of web videos in the last decade. This prompts an urgent demand for efficiently grasping the major events. Nevertheless, the insufficient and noisy text information has made it difficult and challenging to mine the events based on the initial keywords and visual features. In this paper, we propose an adaptive semantic association rule mining method in the NDK (Near-Duplicate Keyframes) level to enrich the keyword information and to remove the words without any semantic relationship. Moreover, both textual and visual information are employed for event classification, targeting for bridging the gap between NDKs and the high-level semantic concepts. Experimental results on large scale web videos from YouTube demonstrate that our proposed method achieves good performance and outperforms the selected baseline methods

Analysis and Experiment of a Novel Brushless Double Rotor Machine for Power-Split Hybrid Electrical Vehicle Applications

A novel brushless double rotor machine (BDRM) is proposed in this paper. The BDRM is an important component in the brushless compound-structure permanent-magnet synchronous machine (CS-PMSM) system, which is a promising technology for power-split hybrid electric vehicle (HEV) applications. Compared with common double rotor machines, the brushes and slip rings required by rotating winding have been omitted in the BDRM, thus there are no such problems as maintenance, friction losses and so forth. Firstly, the torque characteristics of the BDRM are analyzed. As the stator has ring-shaped centralized windings, the size characteristics of the BDRM are different from those of conventional machines. The new sizing and torque equations are analyzed and the theoretical results are applied to determine the main dimensions. Additionally, studies of the analytical magnetic circuit and finite element method (FEM) model show that the BDRM tends to have high leakage flux and low power factor. Although the scope for improving the serious flux leakage of the BDRM is limited by the special magnetic topology, a method to obtain higher power factor is provided. Finally, a 10 kW prototype machine was manufactured, assembly of the prototype is discussed in detail and experimental tests are performed to validate the analytical and simulation results

Performance Analysis and Simulation of a Novel Brushless Double Rotor Machine for Power-Split HEV Applications

A new type of brushless double rotor machine (BDRM) is proposed in this paper. The BDRM is an important component in compound-structure permanent-magnet synchronous machine (CS-PMSM) systems, which are promising for power-split hybrid electric vehicle (HEV) applications. The BDRM can realize the speed adjustment between claw-pole rotor and permanent-magnet rotor without brushes and slip rings. The structural characteristics of the BDRM are described and its magnetic circuit model is built. Reactance parameters of the BDRM are deduced by an analytical method. It is found that the size characteristics of the BDRM are different from those of conventional machines. The new sizing and torque equations are analyzed and the theoretical results are used in the optimization process. Studies of the analytical magnetic circuit and finite element method (FEM) model show that the BDRM tends to have high leakage flux and low power factor, and then the method to obtain high power factor is discussed. Furthermore, a practical methodology of the BDRM design is developed, which includes an analytical tool, 2D field calculation and performance evaluation by 3D field calculation. Finally, different topologies of the BDRM are compared and an optimum prototype is designed

Magnetic Decoupling Design and Experimental Validation of a Radial-Radial Flux Compound-Structure Permanent-Magnet Synchronous Machine for HEVs

The radial-radial flux compound-structure permanent-magnet synchronous machine (CS-PMSM), integrated by two concentrically arranged permanent-magnet electric machines, is an electromagnetic power-splitting device for hybrid electric vehicles (HEVs). As the two electric machines share a rotor as structural and magnetic common part, their magnetic paths are coupled, leading to possible mutual magnetic-field interference and complex control. In this paper, a design method to ensure magnetic decoupling with minimum yoke thickness of the common rotor is investigated. A prototype machine is designed based on the proposed method, and the feasibility of magnetic decoupling and independent control is validated by experimental tests of mutual influence. The CS-PMSM is tested by a designed driving cycle, and functions to act as starter motor, generator and to help the internal combustion engine (ICE) operate at optimum efficiency are validated