Notes

Effective and chemoselective hydrogenation of aldehydes catalyzed simply by well-defined PN3-pincer manganese(II) driver precursors: a software within furfural alteration.
a were positively associated with the progression change of pulse rate of patients rate of progression of pulse rate decreases over time. Furthermore, health professionals give more attention to patients who are NYHA class IV, had low LVEF, pneumonic patients to reduce pulse rate during the follow-up time.
A patient's length of hospital stay (LHS) is associated with the severity and outcome of acute exacerbation of chronic obstructive pulmonary disease (AECOPD). Therefore, identification of patients with prolonged LHS at an early stage can potentially reduce the risk of adverse events and treatment costs in patients with AECOPD. Therefore, this study aimed to explore the independent predictors of prolonged LHS in AECOPD patients.

This multicenter cross-sectional study was conducted at two tertiary hospitals between January 2019 and August 2020. Demographic data, underlying diseases, symptoms, and laboratory findings were collected. Univariate analysis was used to identify variables with significant differences. A collinearity diagnostic was applied to the selected variables before the establishment of the regression model. Ordinal logistic regression was performed to explore the independent risk factors for prolonged LHS in patients with AECOPD.

In total, 598 patients with AECOPD were screened. Finally, t/or CCP on admission.
Collectively, our results showed that inflammatory status, hypertension, and CCP were independently associated with LHS in patients with AECOPD. These data indicate that early and appropriate administration of antibiotics and anti-inflammatory drugs is essential for reducing LHS. Hypertension and CCP were independent predictors of worse outcomes in patients with AECOPD. Therefore, advanced management and care should be provided to AECOPD patients with hypertension and/or CCP on admission.Granular porous calcium phosphate scaffolds are used for bone regeneration in dentistry. However, in conventional granules, the macropore interconnectivity is poor and has varying size. Herein, we developed a productive method for fabricating carbonate apatite honeycomb granules with uniformly sized macropores based on extrusion molding. Each honeycomb granule possesses three hexagonal macropores of ∼290 μm along its diagonal. Owing to these macropores, honeycomb granules simultaneously formed new and mature bone and blood vessels in both the interior and exterior of the granules at 4 weeks after implantation. The honeycomb granules are useful for achieving rapid osteogenesis and angiogenesis.
To uncover the neuroprotective effect of
-
compound (Huangqi-Chuanxiong Compound (HCC)) on cerebral infarction (CI) through quantitative proteomics.

CI model was established by the modified Zea Longa intracavitary suture blocking method. After modeling, the rats were given intragastric administration for 7 days, once a day. After the 7-day intervention, the neurological function score was performed, the brain tissue was pathologically observed, and the total serum protein was extracted. Then, these proteins were analyzed by LC-MS/MS to identify the differentially expressed proteins (DEPs) in the HCC/CI group and CI/sham operation group. Finally, bioinformatics analysis was used to analyze DEPs, including gene ontology (GO) analysis, pathway analysis, and protein interaction analysis. ELISA and Western blotting were used to verify the proteomics results.

The neurological function scores of the HCC group were lower than those of the CI group. HE staining showed that the pathological results of the HCCoxia (response to hypoxia, response to decreased oxygen levels), and cellular calcium homeostasis (cellular calcium ion homeostasis). The results of ELISA and Western blot also showed that, compared with model group, the angiotensinogen and catalase in HCC group were decreased (
< 0.05), which is consistent with the findings of proteomics.

The therapeutic mechanism of HCC in the treatment of CI may involve fibrinolysis, cell-matrix adhesion, inflammation, hypoxia, and oxidative stress.
The therapeutic mechanism of HCC in the treatment of CI may involve fibrinolysis, cell-matrix adhesion, inflammation, hypoxia, and oxidative stress.
Tetramethylpyrazine (TMP) is an alkaloid in Chinese herbal medicine, which possesses antiplatelet activity. TMP inhibits platelet activation in many ways. The platelet P2Y
receptor for adenosine 5' diphosphate (ADP) plays a central role in platelet function, hemostasis, and thrombosis. Here, we investigated the inhibitory effect of TMP on P2Y
receptor-related platelet function.

The inhibitory potential of TMP was assessed using agonist-induced platelet aggregation, flow cytometric analysis of CD62p expression, PAC-1 activation, and fibrin clot retraction. After the P2Y12 receptor-related signaling pathway was inhibited using the blocker, platelet activation was studied by platelet aggregation, CD62p expression, and PAC-1 activation. The secretion of cyclic adenosine monophosphate (cAMP) was measured using enzyme-linked immunosorbent assay (ELISA), and the expression of signaling pathway protein, phosphorylation of vasodilator-stimulated phosphoprotein, and phosphorylation of Akt were investigated using western blotting. The release of platelet inflammatory mediators was measured using ELISA.

TMP had an antiplatelet effect by inhibiting ADP-induced aggregation, P-selectin secretion, and glycoprotein (GP) IIb/IIIa expression and reducing the release of atherosclerotic-related inflammatory mediators (sCD40L and IL-1
). TMP decreased the area of clot retraction, reflecting inhibition of GPIIb/IIIa activation. TMP inhibited adenosine diphosphate-induced platelet activation via increased cAMP production, VASP
phosphorylation, and Akt dephosphorylation.

TMP selectively inhibits ADP-induced platelet activation via P2Y
receptor-related signaling pathways.
TMP selectively inhibits ADP-induced platelet activation via P2Y12 receptor-related signaling pathways.This study was to investigate the effects of Biyeom-go (BYG, an herbal formula) on immune biomarkers present in the nasal mucosa of patients with allergic rhinitis under exposure to particulate matter 2.5 (PM2.5), and on changes in goblet cells and immune biomarkers in mice under exposure to Korea diesel particulate matter (KDP20). Thirty patients showing characteristic allergic rhinitis symptoms were enrolled in Jeonju-si, Korea, and treated with BYG thrice a day for four weeks. Changes in the expression of immune biomarkers (interleukin 4 (IL-4), IL-5, IL-8, IL-13, IL-33, and thymic stromal lymphopoietin (TSLP) mRNA), total nasal symptom scores (TNSS), mini-rhinitis-specific quality of life questionnaire (RQLQ) results, and visual analog scale scores were evaluated after 4 weeks of treatment. Additionally, the difference in PM2.5 concentrations in the air in Jeonju-si, Korea (November, 2019 ∼ March, 2020), was analyzed to determine the change in TNSS. KDP20 (100 μg/mL) was exposed to C57BL/6 mice for 10 days; 0.05% Nasonex (a positive control, mometasone furoate), or BYG was administrated for 5 days twice a day. The expression of inflammatory factors was detected via qRT-PCR using nasopharynx tissue samples of mice. BYG treatment was found to be associated with significant improvement in total nasal symptoms, especially itching and sneezing (p less then 0.0001), and mini-RQLQ after 4 weeks. IL-8 (p less then 0.01), IL-33 (p less then 0.01), and TSLP (p less then 0.001) expression levels decreased after BYG treatment. In mice, administration of BYG reduced the number of goblet cells increased through KDP20 treatment. KDP20-induced immune biomarkers (IL-33, TSLP, tumor necrosis factor alpha, and IL-8) were also significantly downregulated in the nasopharynx tissue after BYG treatment. Therefore, BYG may show therapeutic effects against allergic rhinitis in humans, and it was confirmed that the expression of PM-induced inflammatory factors in mice was decreased via BYG treatment.Smartwatches are wearable devices intended to be smartphone companions that capture health data and ease access to notifications. They have also become personalisable standing as a fashion statement. This combination resulted in staggering adoption rates recently leading to question whether smartwatch users' choice and use satisfaction emerge from utility features or from its fashion characteristics. This paper proposes and validates a fit theory to investigate the antecedents of adopters' satisfaction. Besides evaluating fit with identity, the model assesses both perceived and actual task-technology fit of smartwatches. A questionnaire-based quantitative approach is used to collect data from about 300 smartwatch users in Qatar. To test the proposed model, data is analysed using structural equation modeling (SEM) and artificial neural networks (ANN). Furthermore, ANN sensitivity analysis ranks the importance of the fit factors affecting users' choice during pre- and post-adoption stages. see more Both task-technology and technology-identity fit factors are quasi-equally important in explaining 62% of satisfaction variance. ANN analysis revealed that post-adoption satisfaction is primarily attributed to smartwatches' ability to fit with users' identity and secondarily to its perceived fit with tasks. Nevertheless, pre-adoption choice of smartwatches is mainly guided by their functionality. This paper is the first to propose and validate an integrated task-technology-identity fit model to explain smartwatch utilization and users' satisfaction. The originality also lies in assessing actual task-technology fit and as perceived by users. Employing two modes of analysis revealed extra insights too.Radiological methodologies, such as chest x-rays and CT, are widely employed to help diagnose and monitor COVID-19 disease. COVID-19 displays certain radiological patterns easily detectable by X-rays of the chest. Therefore, radiologists can investigate these patterns for detecting coronavirus disease. However, this task is time-consuming and needs lots of trial and error. One of the main solutions to resolve this issue is to apply intelligent techniques such as deep learning (DL) models to automatically analyze the chest X-rays. Nevertheless, fine-tuning of architecture and hyperparameters of DL models is a complex and time-consuming procedure. In this paper, we propose an effective method to detect COVID-19 disease by applying convolutional neural network (CNN) to the chest X-ray images. To improve the accuracy of the proposed method, the last Softmax CNN layer is replaced with a K -nearest neighbors (KNN) classifier which takes into account the agreement of the neighborhood labeling. Moreover, we develop a novel evolutionary algorithm by improving the basic version of competitive swarm optimizer. To this end, three powerful evolutionary operators Cauchy Mutation (CM), Evolutionary Boundary Constraint Handling (EBCH), and tent chaotic map are incorporated into the search process of the proposed evolutionary algorithm to speed up its convergence and make an excellent balance between exploration and exploitation phases. Then, the proposed evolutionary algorithm is used to automatically achieve the optimal values of CNN's hyperparameters leading to a significant improvement in the classification accuracy of the proposed method. Comprehensive comparative results reveal that compared with current models in the literature, the proposed method performs significantly more efficient.
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