Hippocampal Long-Term Depression in the Presence of Calcium-Permeable AMPA Receptors

The GluA2 subunit of AMPA glutamate receptors (AMPARs) has been shown to be critical for the expression of NMDA receptor (NMDAR)-dependent long-term depression (LTD). However, in young GluA2 knockout (KO) mice, this form of LTD can still be induced in the hippocampus, suggesting that LTD mechanisms may be modified in the presence of GluA2-lacking, Ca2+ permeable AMPARs. In this study, we examined LTD at the CA1 synapse in GluA2 KO mice by using several well-established inhibitory peptides known to block LTD in wild type (WT) rodents. We showed that while LTD in the KO mice is still blocked by the protein interacting with C kinase 1 (PICK1) peptide pepEVKI, it becomes insensitive to the N-ethylmaleimide-sensitive factor (NSF) peptide pep2m. In addition, the effects of actin and cofilin inhibitory peptides were also altered. These results indicate that in the absence of GluA2, LTD expression mechanisms are different from those in WT animals, suggesting that there are multiple molecular processes enabling LTD expression that are adaptable to physiological and genetic manipulations

Traceability analysis for low-voltage distribution network abnormal line loss using a data-driven power flow model

The abnormal behavior of end-users is one of the main causes of abnormal line loss in distribution networks. The integration of a large amount of distributed renewable energy into a low-voltage distribution network (LVDN) complicates line loss analysis. Traceability analysis for abnormal line loss aims to identify the specific end-user responsible for the anomaly in line loss. This paper proposes, for LVDNs with incomplete topology and line parameters, a practical traceability analysis approach using a data-driven power flow model. A data-driven power flow model based on a neural network is first established to capture the power flow mapping relationship without topology and line parameter information. A backpropagation algorithm is then presented to correct the actual power consumption data according to the measured voltage data. By comparing actual power consumption data with measured power data, users with abnormal behavior can be accurately identified and tracked. Finally, the effectiveness of the proposed approach is verified by actual data

A Case-Control Study between Gene Polymorphisms of Polyunsaturated Fatty Acid Metabolic Rate-Limiting Enzymes and Acute Coronary Syndrome in Chinese Han Population

The purpose of this study is to analyze the relationship between the polymorphisms of fatty acid desaturase 1 (FADS1), fatty acid desaturase 2 (FADS2), and elongation of very long-chain fatty acids-like 2 (ELOVL2) and acute coronary syndrome (ACS) in Chinese Han population. Therefore, we selected three single nucleotide polymorphisms (SNPs) from these candidate genes and genotyped them using PCR-based restriction fragment length polymorphism analysis in 249 ACS patients and 240 non-ACS subjects, as were Han Chinese ancestry. The results showed that rs174556 in the FADS1 gene is found to be in allelic association () and genotypic association () with ACS. The frequencies of rs174556 minor allele (T) in case group were obviously higher than in control group. The trans-phase gene-gene interaction analysis showed that the combined genotype of rs174556 (T/T) and rs3756963 (T/T) was associated with ACS (). And the results suggest that, for rs174556 C>T, the CT/TT genotypes were more likely to lead in ACS in subjects with hypertension after correction of all risk factors (, 95% CI, 2.216–7.126). These findings suggest that the polymorphisms of rs174556 in the FADS1 gene are very likely to be associated with ACS in Chinese Han population, especially in subjects with hypertension

Local and Global Feature Aggregation-Aware Network for Salient Object Detection

With the rise of deep learning technology, salient object detection algorithms based on convolutional neural networks (CNNs) are gradually replacing traditional methods. The majority of existing studies, however, focused on the integration of multi-scale features, thereby ignoring the characteristics of other significant features. To address this problem, we fully utilized the features to alleviate redundancy. In this paper, a novel CNN named local and global feature aggregation-aware network (LGFAN) has been proposed. It is a combination of the visual geometry group backbone for feature extraction, an attention module for high-quality feature filtering, and an aggregation module with a mechanism for rich salient features to ease the dilution process on the top-down pathway. Experimental results on five public datasets demonstrated that the proposed method improves computational efficiency while maintaining favorable performance

Intravenous N-acetylcysteine for prevention of contrast-induced nephropathy: a meta-analysis of randomized, controlled trials.

BACKGROUND: Contrast-induced nephropathy (CIN) is one of the common causes of acute renal insufficiency after contrast procedures. Whether intravenous N-acetylcysteine (NAC) is beneficial for the prevention of contrast-induced nephropathy is uncertain. In this meta-analysis of randomized controlled trials, we aimed to assess the efficacy of intravenous NAC for preventing CIN after administration of intravenous contrast media. STUDY DESIGN: Relevant studies published up to September 2012 that investigated the efficacy of intravenous N-acetylcysteine for preventing CIN were collected from MEDLINE, OVID, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials, and the conference proceedings from major cardiology and nephrology meetings. The primary outcome was CIN. Secondary outcomes included renal failure requiring dialysis, mortality, and length of hospitalization. Data were combined using random-effects models with the performance of standard tests to assess for heterogeneity and publication bias. Meta-regression analyses were also performed. RESULTS: Ten trials involving 1916 patients met our inclusion criteria. Trials varied in patient demographic characteristics, inclusion criteria, dosing regimens, and trial quality. The summary risk ratio for contrast-induced nephropathy was 0.68 (95% CI, 0.46 to 1.02), a nonsignificant trend towards benefit in patients treated with intravenous NAC. There was evidence of significant heterogeneity in NAC effect across studies (Q = 17.42, P = 0.04; I(2) = 48%). Meta-regression revealed no significant relation between the relative risk of CIN and identified differences in participant or study characteristics. CONCLUSION: This meta-analysis showed that research on intravenous N-acetylcysteine and the incidence of CIN is too inconsistent at present to warrant a conclusion on efficacy. A large, well designed trial that incorporates the evaluation of clinically relevant outcomes in participants with different underlying risks of CIN is required to more adequately assess the role for intravenous NAC in CIN prevention

Dynamic Analysis of Tip Leakage Phenomena in Axial Flow Pumps Using a Square-Cavity Jet Model

In the field of pump impeller studies, tip leakage flow (TLF) and the resultant tip leakage vortex (TLV) significantly influence hydraulic efficiency, cavitation, and noise generation. This paper builds a novel square-cavity jet model combined with Large Eddy Simulation (LES) technology to obtain precise the dynamic properties of the TLV, significantly simplifying the computational resources required for numerical simulations. The novel square-cavity jet model simplifies a single blade channel to a square-cavity, and then adds a longitudinal slit on the top wall of the square-cavity. The analysis of both instantaneous and time-averaged flow fields indicates that the interaction between the main flow and the jet is the primary source of TLV generation. This study successfully captures the formation process of the TLV and accurately reveals its turbulent coherent structures. The evolution of the TLV is divided into three main parts: the first part is the jet slot, predominantly characterized by negative vorticity flow. The second part is the TLV formation, which is mainly composed of significant negative streamwise vortices. The third part is the development of the TLV, where positive and negative vorticities begin to interact, resulting in a more complex overall structure. The entire evolution of the TLV phenomenon starts with a concentrated negative vortex, which, after breakdown, develops at a certain angle to the slot and continuously advances towards the sidewall, ultimately resulting in the formation of a large-scale intermingled group of small-scale positive and negative vortices. This research not only provides a new physical model for investigating the tip leakage phenomenon in axial flow pumps but also offers a powerful tool and methodology for future studies in similar complex flow domains

Design method of PID-type model predictive iterative learning control based on the two-dimensional generalized predictive control scheme

Conference Name:2012 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012. Conference Address: Guangzhou, China. Time:December 5, 2012 - December 7, 2012.For the repetitive, cyclic or batch processes, iterative learning control is essentially a two-dimensional feedback control. By transforming the iterative learning control into a two-dimensional generalized predictive control, a new model predictive iterative leaning control scheme is proposed in this paper for the repetitive, cyclic or batch processes with both time-wise and cycle-wise dynamics. As the proportional, integral and derivative of the prediction errors are considered in the cost function, the proposed ILC scheme can be referred to as a PID-type model predictive iterative learning control (PID-MPILC). Compared with the two-dimensional model predictive iterative learning control (2D-MPILC) proposed in the previous works, the proposed PID-MPILC can provide much better control performances not only along cycle but also along time, which is illustrated by the numerical simulation. 漏 2012 IEEE