Effects of Nursing Quality Improvement on Thrombolytic Therapy for Acute Ischemic Stroke

Background and purpose: Intravenous thrombolytic therapy significantly improves the outcomes of acute ischemic stroke patients in a time-dependent manner. The aim of this study was to investigate whether continuous nursing quality improvement in stroke nurses has a positive effect on reducing the time to thrombolysis in acute ischemic stroke.Methods: The implementation of nursing quality improvement measures includes establishing full-time stroke nurses, pre-notification by emergency medical services (EMS), stroke team notification protocols, rapid triage, publicity and education, etc. Using a history-controlled approach, we analyzed acute ischemic stroke patients with intravenous thrombolysis during a pre-intervention period (April 1, 2015-July 31, 2016), trial period (August 1, 2016-October 31, 2016), and post-intervention period (November 1, 2016-September 30, 2017). This was done in accordance with the implementation of nursing quality improvement measures, including the general characteristics of the three groups, the time of each step in the process of thrombolysis, and the prognosis.Results: After the implementation of nursing quality improvement measures, the median door-to-needle time (DNT) was shortened from 73 min (interquartile range [IQR] 62–92 min) to 49 min (IQR 40-54 min; p < 0.001) in the post-intervention period. The median onset-to-needle time (ONT) was reduced from 193 min (IQR 155–240 min) to 167 min (IQR 125-227 min; p < 0.001). The proportion of patients with DNT ≤ 60 min increased from 23.94% (51/213) to 86.36% (190/220; p < 0.001) while the proportion of patients with DNT ≤ 40 min increased from 3.29% (7/213) to 25.00% (55/220; p < 0.001). The median time for door-to-laboratory results was decreased from 68 min to 56 min (p < 0.001). There was no significant difference in the fatality rate, 90-day modified Rankin score, length of stay or hospitalization expenses between the three groups of patients (p> 0.05).Conclusions: Implementation of nursing quality improvement measures in stroke nurses is an important factor in shortening the time of medication in patients with thrombolytic therapy, reducing the delay of intravenous thrombolysis in the hospital and helping to expedite presenting patients' arrival to the hospital post-stroke

Temporal Course of Cerebral Autoregulation in Patients With Narcolepsy Type 1: Two Case Reports

Cerebral autoregulation is the mechanism by which constant cerebral blood flow is maintained despite changes in arterial blood pressure. In the two presented cases, cerebral autoregulation was impaired in patients with narcolepsy type 1, and both venlafaxine and fluoxetine may have the potential to improve the impaired cerebral autoregulation. A relationship may exist between impaired cerebral autoregulation and neurological symptoms in patients with narcolepsy type 1

The Herbal Combination of Radix astragali, Radix angelicae sinensis, and Caulis lonicerae Regulates the Functions of Type 2 Innate Lymphocytes and Macrophages Contributing to the Resolution of Collagen-Induced Arthritis

Type 2 innate lymphocytes (ILC2s), promoting inflammation resolution, was a potential target for rheumatoid arthritis (RA) treatment. Our previous studies confirmed that R. astragali and R. angelicae sinensis could intervene in immunologic balance of T lymphocytes. C. lonicerae also have anti-inflammatory therapeutic effects. In this study, the possible molecular mechanisms of the combination of these three herbs for the functions of ILC2s and macrophages contributing to the resolution of collagen-induced arthritis (CIA) were studied. Therefore, we used R. astragali, R. angelicae sinensis, and C. lonicerae as treatment. The synovial inflammation and articular cartilage destruction were alleviated after herbal treatment. The percentages of ILC2s and Tregs increased significantly. The differentiation of Th17 cells and the secretion of IL-17 and IFN-γ significantly decreased. In addition, treatment by the combination of these three herbs could increase the level of anti-inflammatory cytokine IL-4 secreted, active the STAT6 signaling pathway, and then contribute to the transformation of M1 macrophages to M2 phenotype. The combination of the three herbs could promote inflammation resolution of synovial tissue by regulating ILC2s immune response network. The synergistic effects of three drugs were superior to the combination of R. astragali and R. angelicae sinensis or C. lonicerae alone

The Impact of Variational Primary Collaterals on Cerebral Autoregulation

The influence of the anterior and posterior communicating artery (ACoA and PCoA) on dynamic cerebral autoregulation (dCA) is largely unknown. In this study, we aimed to test whether substantial differences in collateral anatomy were associated with differences in dCA in two common types of stenosis according to digital subtraction angiography (DSA): either isolated basal artery and/or bilateral vertebral arteries severe stenosis/occlusion (group 1; group 1A: with bilateral PCoAs; and group 1B: without bilateral PCoAs), or isolated unilateral internal carotid artery severe stenosis/occlusion (group 2; group 2A: without ACoA and with PCoA; group 2B: with ACoA and without PCoAs; and group 2C: without both ACoA and PCoA). The dCA was calculated by transfer function analysis (a mathematical model), and was evaluated in middle cerebral artery (MCA) and/or posterior cerebral artery (PCA). Of a total of 231 non-acute phase ischemic stroke patients who received both dCA assessment and DSA in our lab between 2014 and 2017, 51 patients met inclusion criteria based on the presence or absence of ACoA or PCoA, including 21 patients in the group 1, and 30 patients in the group 2. There were no significant differences in gender, age, and mean blood pressure between group 1A and group 1B, and among group 2A, group 2B, and group 2C. In group 1, the PCA phase difference values (autoregulatory parameter) were significantly higher in the subgroup with patent PCoAs, compared to those without. In group 2, the MCA phase difference values were higher in the subgroup with patent ACoA, compared to those without. This pilot study found that the cross-flow of the ACoA/PCoA to the affected area compensates for compromised dCA in the affected area, which suggests an important role of the ACoA/PCoA in stabilizing cerebral blood flow

Heterologous Expression of Alteromonas macleodii and Thiocapsa roseopersicina [NiFe] Hydrogenases in Synechococcus elongatus

Oxygen-tolerant [NiFe] hydrogenases may be used in future photobiological hydrogen production systems once the enzymes can be heterologously expressed in host organisms of interest. To achieve heterologous expression of [NiFe] hydrogenases in cyanobacteria, the two hydrogenase structural genes from Alteromonas macleodii Deep ecotype (AltDE), hynS and hynL, along with the surrounding genes in the gene operon of HynSL were cloned in a vector with an IPTG-inducible promoter and introduced into Synechococcus elongatus PCC7942. The hydrogenase protein was expressed at the correct size upon induction with IPTG. The heterologously-expressed HynSL hydrogenase was active when tested by in vitro H2 evolution assay, indicating the correct assembly of the catalytic center in the cyanobacterial host. Using a similar expression system, the hydrogenase structural genes from Thiocapsa roseopersicina (hynSL) and the entire set of known accessory genes were transferred to S. elongatus. A protein of the correct size was expressed but had no activity. However, when the 11 accessory genes from AltDE were co-expressed with hynSL, the T. roseopersicina hydrogenase was found to be active by in vitro assay. This is the first report of active, heterologously-expressed [NiFe] hydrogenases in cyanobacteria

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

A high speed inference architecture for multimodal emotion recognition based on sparse cross modal encoder

In recent years, multimodal emotion recognition models are using pre-trained networks and attention mechanisms to pursue higher accuracy, which increases the training burden and slows down the training and inference speed. In order to strike a balance between speed and accuracy, this paper proposes a speed-optimized multimodal emotion recognition architecture for speech and text emotion recognition. In the feature extraction part, a lightweight residual graph convolutional network (ResGCN) is selected as the speech feature extractor, and an efficient RoBERTa pre-trained network is used as the text feature extractor. Then, an algorithm complexity-optimized sparse cross-modal encoder (SCME) is proposed and used to fuse these two types of features. Finally, a new gated fusion module (GF) is used to weight multiple results and input them into a fully connected layer (FC) for classification. The proposed method is tested on the IEMOCAP dataset and the MELD dataset, achieving weighted accuracies (WA) of 82.4% and 65.0%, respectively. This method achieves higher accuracy than the listed methods while having an acceptable training and inference speed