The onset time increased with increasing IGF-1 level and GH and IGF-1 burden. Taken together, a unique NMB status was identified in acromegaly patients with the following characteristics prolonged onset time and shortened DNMBD and CNMBD. Changes in the levels and burdens of GH and IGF-1 and body composition were linearly correlated with intraoperative NMB in acromegaly patients.

Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke.

Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were al treatments used in stroke rehabilitation.

Physical exercise (PE) has been associated with increase neuroplasticity, neurotrophic factors, and improvements in brain function.

To evaluate the effects of different PE protocols on neuroplasticity components and brain function in a human and animal model.

We conducted a systematic review process from November 2019 to January 2020 of the following databases PubMed, ScienceDirect, SciELO, LILACS, and Scopus. A keyword combination referring to PE and neuroplasticity was included as part of a more thorough search process. From an initial number of 20,782 original articles, after reading the titles and abstracts, twenty-one original articles were included. Two investigators evaluated the abstract, the data of the study, the design, the sample size, the participant characteristics, and the PE protocol.

PE increases neuroplasticity via neurotrophic factors (BDNF, GDNF, and NGF) and receptor (TrkB and P75NTR) production providing improvements in neuroplasticity, and cognitive function (learning and memory) in human and animal models.

PE was effective for increasing the production of neurotrophic factors, cell growth, and proliferation, as well as for improving brain functionality.

PE was effective for increasing the production of neurotrophic factors, cell growth, and proliferation, as well as for improving brain functionality.In the era of the rapid development of today’s Internet, people often feel overwhelmed by vast official news streams or unofficial self-media tweets. To help people obtain the news topics they care about, there is a growing need for systems that can extract important events from this amount of data and construct the evolution procedure of events logically into a story. Most existing methods treat event detection and evolution as two independent subtasks under an integrated pipeline setting. However, the interdependence between these two subtasks is often ignored, which leads to a biased propagation. Besides, due to the limitations of news documents’ semantic representation, the performance of event detection and evolution is still limited. To tackle these problems, we propose a Joint Event Detection and Evolution (JEDE) model, to detect events and discover the event evolution relationships from news streams in this paper. Specifically, the proposed JEDE model is built upon the Siamese network, which first introduces the bidirectional GRU attention network to learn the vector-based semantic representation for news documents shared across two subtask networks. Then, two continuous similarity metrics are learned using stacked neural networks to judge whether two news documents are related to the same event or two events are related to the same story. Furthermore, due to the limited available dataset with ground truths, we make efforts to construct a new dataset, named EDENS, which contains valid labels of events and stories. The experimental results on this newly created dataset demonstrate that, thanks to the shared representation and joint training, the proposed model consistently achieves significant improvements over the baseline methods.The traditional label relaxation regression (LRR) algorithm directly fits the original data without considering the local structure information of the data. While the label relaxation regression algorithm of graph regularization takes into account the local geometric information, the performance of the algorithm depends largely on the construction of graph. However, the traditional graph structures have two defects. First of all, it is largely influenced by the parameter values. Second, it relies on the original data when constructing the weight matrix, which usually contains a lot of noise. This makes the constructed graph to be often not optimal, which affects the subsequent work. Therefore, a discriminative label relaxation regression algorithm based on adaptive graph (DLRR_AG) is proposed for feature extraction. DLRR_AG combines manifold learning with label relaxation regression by constructing adaptive weight graph, which can well overcome the problem of label overfitting. Based on a large number of experiments, it can be proved that the proposed method is effective and feasible.In this study, we describe novel gallium(III), germanium(IV), and hafnium(IV) folate complexes, including their synthesis and analyses. The synthesized folate complexes were also subject to thermal analysis (TGA) to better examine their thermal degradation and kinetic properties. The folate complexes had high stability and were nonspontaneous. The Coats-Redfern and Horowitz-Metzger equations were used to determine thermodynamic parameters and describe the kinetic properties. These complexes were synthesized through the chemical interactions in neutralized media between the folic acid drug ligand (FAH2) with GaCl3, GeCl4, and HfCl4 metal salts at 1  2 (metal  ligand) molar ratio. The conductance measurements have low values due to their nonelectrolytic behavior. The X-ray powder diffraction solid powder pattern revealed a semicrystalline nature. In vitro, we screened the synthesized folate chelates for antibacterial and antifungal activities. The inhibition of four bacterial and two fungi pathogens (E. coli, B. subtilis, P. aeruginosa, S. aureus, A. flavus, and Candida albicans) was improved using a folic acid drug relative to the control drug.Inflammation caused by neuropathy contributes to the development of neuropathic pain (NP), but the exact mechanism still needs to be understood. Peroxisome proliferator-activated receptor α (PPARα), an important inflammation regulator, might participate in the inflammation in NP. To explore the role of PPARα in NP, the effects of PPARα agonist WY-14643 on chronic constriction injury (CCI) rats were evaluated. The results showed that WY-14643 stimulation could decrease inflammation and relieve neuropathic pain, which was relative with the activation of PPARα. In addition, we also found that the SIRT1/NF-κB pathway was involved in the WY-14643-induced anti-inflammation in NP, and activation of PPARα increased SIRT1 expression, thus reducing the proinflammatory function of NF-κB. These data suggested that WY-14643 might serve as an inflammation mediator, which may be a potential therapy option for NP.Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic volatile organic compounds (VOCs) play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea-United States Air Quality (KORUS-AQ) experiment in South Korea and the Air Chemistry Research in Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an ensemble adjustment Kalman filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-Chepisode, better simulation of O3, with an average underestimation of 5.5 ppbv, and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.Text analysis can help to identify named entities (NEs) of small molecules, proteins, and genes. Such data are very important for the analysis of molecular mechanisms of disease progression and development of new strategies for the treatment of various diseases and pathological conditions. The texts of publications represent a primary source of information, which is especially important to collect the data of the highest quality due to the immediate obtaining information, in comparison with databases. In our study, we aimed at the development and testing of an approach to the named entity recognition in the abstracts of publications. More specifically, we have developed and tested an algorithm based on the conditional random fields, which provides recognition of NEs of (i) genes and proteins and (ii) chemicals. Careful selection of abstracts strictly related to the subject of interest leads to the possibility of extracting the NEs strongly associated with the subject. To test the applicability of our approacheins that can be responsible for viremic control. Our study demonstrated the applicability of the developed approach for the extraction of useful data on HIV treatment.Delayed repair is a serious public health concern for diabetic populations. Intercellular adhesion molecule 1 (ICAM-1) and Lymphocyte function-associated antigen 1 (LFA-1) play important roles in orchestrating the repair process. However, little is known about their effects on endothelial cell (EC) proliferation and neutrophil activity in subjects with hyperglycemia (HG). We cultured ECs and performed a scratch-closure assay to determine the relationship between ICAM-1 and EC proliferation. Specific internally labeled bacteria were used to clarify the effects of ICAM-1 and LFA-1 on neutrophil phagocytosis. Transwell assay and fluorescence-activated cell sorting analysis evaluated the roles of ICAM-1 and LFA-1 in neutrophil recruitment. ICAM-1+/+ and ICAM-1-/- mice were used to confirm the findings in vivo. The results demonstrated that HG decreased the expression of ICAM-1, which lead to the low proliferation of ECs. HG also attenuated neutrophil recruitment and phagocytosis by reducing the expression of ICAM-1 and LFA-1, which were strongly associated with the delayed repair.