Evolocumab for early reduction of LDL-C levels in patients with acute ischemic stroke: a randomized controlled trial.

Background: Low-density lipoprotein cholesterol (LDL-C) has been determined as an established risk factor for acute ischemic stroke (AIS). Despite the recommendation for in-hospital initiation of high-intensity statin therapy in AIS patients, achieving the desired target LDL-C levels remains challenging. Evolocumab, a highly effective and quickly acting agent for reducing LDL-C levels, has yet to undergo extensively exploration in the acute phase of AIS.

Computed tomography image quality in patients with primary hepatocellular carcinoma: intraindividual comparison of contrast agent concentrations.

Objective: This study aimed to assess the impact of the different concentrations of iodine contrast agents used on the quality of computed tomography (CT) images obtained intraindividually in hepatocellular carcinoma patients.

Methods: In this retrospective study, data from a cohort of 29 patients diagnosed with primary hepatocellular carcinoma who had undergone two preoperative CT-enhanced examinations within a 3-month timeframe were analyzed. Each patient was randomly assigned to receive either a low-concentration contrast agent (300 mg I/mL iohexol) or a high-concentration contrast agent (350 mg I/mL iohexol) for the first scan and the alternative contrast agent for the second scan.

Effect of skinfold thickness on arm venous access port in cancer patients.

Background: Currently, skinfold thickness in studies on arm venous access ports and the effect of venous access port application are unknown.

Materials And Methods: A total of 256 cancer patients who underwent primary venous access port placement in the Fourth Hospital of Hebei Medical University from September 2022 to March 2023 were selected as the study subjects. Two hundred fifty-six patients were divided into normal skinfold thickness group and high skinfold thickness group according to skinfold thickness.

Clinical Application Value of Multimedia Education and Nursing Intervention in a Coronary Computed Tomography Angiography.

To explore the application value of multimedia education and nursing intervention in a coronary computed tomography angiography (CCTA). A total of 120 patients who underwent a 256-slice spiral CCTA examination in our hospital from April 2019 to April 2020 were selected. Patients were divided into two groups of 60 patients each, that is, the control group and the observation group, using a random number table method.

Evaluation of an Access-Risk-Knowledge (ARK) Platform for Governance of Risk and Change in Complex Socio-Technical Systems.

Three key challenges to a whole-system approach to process improvement in health systems are the complexity of socio-technical activity, the capacity to change purposefully, and the consequent capacity to proactively manage and govern the system. The literature on healthcare improvement demonstrates the persistence of these problems. In this project, the Access-Risk-Knowledge (ARK) Platform, which supports the implementation of improvement projects, was deployed across three healthcare organisations to address risk management for the prevention and control of healthcare-associated infections (HCAIs).

The effects of the renin inhibitor aliskiren on neuronal toxic damage.

The neurotoxicity of amyloid-β (Aβ) and its deposition in neurons plays a critical role in the occurrence and development of Alzheimer's disease (AD). Several preclinical experiments have found that the renin inhibitor aliskiren has a wide range of physiological effects, including hindering the progression of atherosclerosis and anti-inflammatory. This study is aimed to explore the effect of aliskiren on neuronal toxic damage and the underlying mechanism.

Robust Ellipse Fitting With Laplacian Kernel Based Maximum Correntropy Criterion.

The performance of ellipse fitting may significantly degrade in the presence of outliers, which can be caused by occlusion of the object, mirror reflection or other objects in the process of edge detection. In this paper, we propose an ellipse fitting method that is robust against the outliers, and thus maintaining stable performance when outliers can be present. We formulate an optimization problem for ellipse fitting based on the maximum entropy criterion (MCC), having the Laplacian as the kernel function from the well-known fact that the l -norm error measure is robust to outliers.

Decentralized Dimensionality Reduction for Distributed Tensor Data Across Sensor Networks.

This paper develops a novel decentralized dimensionality reduction algorithm for the distributed tensor data across sensor networks. The main contributions of this paper are as follows. First, conventional centralized methods, which utilize entire data to simultaneously determine all the vectors of the projection matrix along each tensor mode, are not suitable for the network environment.

[Increased expressions of programmed death 1 (PD-1) and its ligands in peripheral CD3(+) T cells and CD19(+) B cells in patients with hepatocellular carcinoma].

Objective To investigate the changes of programmed death 1 (PD-1) and ligands, as well as interferon-γ (IFN-γ) in peripheral blood mononuclear cells (PBMCs) of patients with hepatocellular carcinoma (HCC). Methods The peripheral blood was collected from 15 early HCC patients, 13 progressive HCC patients and 12 healthy volunteers. PBMCs was isolated from the peripheral blood.

Robust Ellipse Fitting via Half-Quadratic and Semidefinite Relaxation Optimization.

Ellipse fitting is widely applied in the fields of computer vision and automatic manufacture. However, the introduced edge point errors (especially outliers) from image edge detection will cause severe performance degradation of the subsequent ellipse fitting procedure. To alleviate the influence of outliers, we develop a robust ellipse fitting method in this paper.

Salvage radiotherapy in patients with local recurrent esophageal cancer after radical radiochemotherapy.

Purpose: The aim of this study was to evaluate the salvage radiotherapy outcome in patients with local recurrent esophageal cancer after radical radiochemotherapy (RCT).

Methods: A total of 114 patients with local recurrent esophageal squamous cell carcinoma after initial radical RCT were retrospectively analyzed. Fifty-five (55) patients belonged to the salvage radiotherapy group (SR group) and 59 patients to the non-salvage radiotherapy group (NSR group).

Effects of broth composition and light condition on antimicrobial susceptibility testing of ionic silver.

In this study, the minimum inhibitory concentrations (MICs) of AgNO3 against bacteria were investigated in a variety of microorganism culture broths. Broth- and light-dependent MIC values were observed and correlated negatively with nano-Ag speciation development. We advocate here the importance of broth and light standardization in Ag antimicrobial test.

Asymmetric double-image encryption based on cascaded discrete fractional random transform and logistic maps.

A double-image encryption is proposed based on the discrete fractional random transform and logistic maps. First, an enlarged image is composited from two original images and scrambled in the confusion process which consists of a number of rounds. In each round, the pixel positions of the enlarged image are relocated by using cat maps which are generated based on two logistic maps.

Distributed dictionary learning for sparse representation in sensor networks.

This paper develops a distributed dictionary learning algorithm for sparse representation of the data distributed across nodes of sensor networks, where the sensitive or private data are stored or there is no fusion center or there exists a big data application. The main contributions of this paper are: 1) we decouple the combined dictionary atom update and nonzero coefficient revision procedure into two-stage operations to facilitate distributed computations, first updating the dictionary atom in terms of the eigenvalue decomposition of the sum of the residual (correlation) matrices across the nodes then implementing a local projection operation to obtain the related representation coefficients for each node; 2) we cast the aforementioned atom update problem as a set of decentralized optimization subproblems with consensus constraints. Then, we simplify the multiplier update for the symmetry undirected graphs in sensor networks and minimize the separable subproblems to attain the consistent estimates iteratively; and 3) dictionary atoms are typically constrained to be of unit norm in order to avoid the scaling ambiguity.

Enhanced multistatic active sonar signal processing.

Multistatic active sonar systems involve the transmission and reception of multiple probing sequences and can achieve significantly enhanced performance of target detection and localization through exploiting spatial diversity. This paper mainly focuses on two signal processing aspects of such systems, namely, enhanced range-Doppler imaging and improved target parameter estimation. The main contributions of this paper are (1) a hybrid dense-sparse method is proposed to generate range-Doppler images with both low sidelobe levels and high accuracy; (2) a generalized K-Means clustering (GKC) method for target association is developed to associate the range measurements from different transmitter-receiver pairs, which is actually a range fitting procedure; (3) the extended invariance principle-based weighted least-squares method is developed for accurate target position and velocity estimation.

Image fusion using higher order singular value decomposition.

A novel higher order singular value decomposition (HOSVD)-based image fusion algorithm is proposed. The key points are given as follows: 1) Since image fusion depends on local information of source images, the proposed algorithm picks out informative image patches of source images to constitute the fused image by processing the divided subtensors rather than the whole tensor; 2) the sum of absolute values of the coefficients (SAVC) from HOSVD of subtensors is employed for activity-level measurement to evaluate the quality of the related image patch; and 3) a novel sigmoid-function-like coefficient-combining scheme is applied to construct the fused result. Experimental results show that the proposed algorithm is an alternative image fusion approach.