Fibroblast Growth Factor-10 (FGF-10) Mobilizes Lung-resident Mesenchymal Stem Cells and Protects Against Acute Lung Injury.

FGF-10 can prevent or reduce lung specific inflammation due to traumatic or infectious lung injury. However, the exact mechanisms are poorly characterized. Additionally, the effect of FGF-10 on lung-resident mesenchymal stem cells (LR-MSCs) has not been studied. To better characterize the effect of FGF-10 on LR-MSCs, FGF-10 was intratracheally delivered into the lungs of rats. Three days after instillation, bronchoalveolar lavage was performed and plastic-adherent cells were cultured, characterized and then delivered therapeutically to rats after LPS intratracheal instillation. Immunophenotyping analysis of FGF-10 mobilized and cultured cells revealed expression of the MSC markers CD29, CD73, CD90, and CD105, and the absence of the hematopoietic lineage markers CD34 and CD45. Multipotency of these cells was demonstrated by their capacity to differentiate into osteocytes, adipocytes, and chondrocytes. Delivery of LR-MSCs into the lungs after LPS injury reduced the inflammatory response as evidenced by decreased wet-to-dry ratio, reduced neutrophil and leukocyte recruitment and decreased inflammatory cytokines compared to control rats. Lastly, direct delivery of FGF-10 in the lungs of rats led to an increase of LR-MSCs in the treated lungs, suggesting that the protective effect of FGF-10 might be mediated, in part, by the mobilization of LR-MSCs in lungs

Assessing the Pharmacological and Therapeutic Efficacy of Traditional Chinese Medicine Liangxue Tongyu Prescription for Intracerebral Hemorrhagic Stroke in Neurological Disease Models

Intracerebral hemorrhage is a fatal subtype of stroke, with crucial impact on public health. Surgical removal of the hematoma as an early-stage treatment for ICH can’t improve long-term prognosis remarkably. Liangxue tongyu prescription (LP), a Traditional Chinese Medicine (TCM) formula, includes eight ingredients and has been used to treat ICH in the clinical. In the study, we elucidated the pharmacological efficacy and therapeutic efficacy of LP to dissect the mechanism of LP against ICH via network analysis and experimental validation. First, we discovered 34 potential compounds and 146 corresponding targets in LP based on network prediction. 24 signal pathway were obtained by the Clue Go assay based on potential compounds in LP against ICH. Second, we found that LP can not only decreased the level of high sensitive C reactive protein (HS-CRP), tumor necrosis factor-α (TNF-α), NF-kβ, D-dimmer (D2D), estradiol (E2), S-100B, neuron specific enolase (NSE), and interleukin 1 (IL-1) in plasma on spontaneously hypertensive rats (SHRs), but also promoted cell proliferation and inhibited cell apoptosis on the glutamate-induced PC12 cell. The compounds including Taurine, Paeonol, and Ginsenoside Rb1 in LP can activate PI3K/AKT pathway. Third, from the three-factor two-level factorial design, compound combinations in LP, such as Taurine and Paeonol, Taurine and Geniposide, Ginsenoside Rg1, and Ginsenoside Rb1, had first-level interactions on cell proliferation. Compound combinations including Taurine and Paeonol, Ginsenoside Rg1 and Ginsenoside Rb1 had as significant increase in efficiency on inhibiting the apoptosis of PC12 cells at the low concentration and up-regulating of PI3K and AKT. Overall, our results suggested that LP had integrated therapeutic effect on ICH due to activities of anti-inflammatory, anti-coagulation, blood vessel protection, and protection neuron from excitotoxicity based on the way of “multi-component, multi-target, multi-pathway,” and compound combination in LP can offer protection neuron from excitotoxicity at the low concentration by activation of the PI3K/Akt signal pathway

Anesthetic Propofol Attenuates the Isoflurane-Induced Caspase-3 Activation and Aβ Oligomerization

Accumulation and deposition of β-amyloid protein (Aβ) are the hallmark features of Alzheimer's disease. The inhalation anesthetic isoflurane has been shown to induce caspase activation and increase Aβ accumulation. In addition, recent studies suggest that isoflurane may directly promote the formation of cytotoxic soluble Aβ oligomers, which are thought to be the key pathological species in AD. In contrast, propofol, the most commonly used intravenous anesthetic, has been reported to have neuroprotective effects. We therefore set out to compare the effects of isoflurane and propofol alone and in combination on caspase-3 activation and Aβ oligomerization in vitro and in vivo. Naïve and stably-transfected H4 human neuroglioma cells that express human amyloid precursor protein, the precursor for Aβ; neonatal mice; and conditioned cell culture media containing secreted human Aβ40 or Aβ42 were treated with isoflurane and/or propofol. Here we show for the first time that propofol can attenuate isoflurane-induced caspase-3 activation in cultured cells and in the brain tissues of neonatal mice. Furthermore, propofol-mediated caspase inhibition occurred when there were elevated levels of Aβ. Finally, isoflurane alone induces Aβ42, but not Aβ40, oligomerization, and propofol can inhibit the isoflurane-mediated oligomerization of Aβ42. These data suggest that propofol may mitigate the caspase-3 activation by attenuating the isoflurane-induced Aβ42 oligomerization. Our findings provide novel insights into the possible mechanisms of isoflurane-induced neurotoxicity that may aid in the development of strategies to minimize potential adverse effects associated with the administration of anesthetics to patients

Unit groups of group algebras of some small groups

summary:Let $FG$ be a group algebra of a group $G$ over a field $F$ and ${\mathcal U}(FG)$ the unit group of $FG$. It is a classical question to determine the structure of the unit group of the group algebra of a finite group over a finite field. In this article, the structure of the unit group of the group algebra of the non-abelian group $G$ with order $21$ over any finite field of characteristic $3$ is established. We also characterize the structure of the unit group of $FA_4$ over any finite field of characteristic $3$ and the structure of the unit group of $FQ_{12}$ over any finite field of characteristic $2$, where $Q_{12}=\langle x, y; x^6=1, y^2=x^3, x^y=x^{-1} \rangle$

Identification of Pulmonary Hypertension Using Entropy Measure Analysis of Heart Sound Signal

This study introduced entropy measures to analyze the heart sound signals of people with and without pulmonary hypertension (PH). The lead II Electrocardiography (ECG) signal and heart sound signal were simultaneously collected from 104 subjects aged between 22 and 89. Fifty of them were PH patients and 54 were healthy. Eleven heart sound features were extracted and three entropy measures, namely sample entropy (SampEn), fuzzy entropy (FuzzyEn) and fuzzy measure entropy (FuzzyMEn) of the feature sequences were calculated. The Mann–Whitney U test was used to study the feature significance between the patient and health group. To reduce the age confounding factor, nine entropy measures were selected based on correlation analysis. Further, the probability density function (pdf) of a single selected entropy measure of both groups was constructed by kernel density estimation, as well as the joint pdf of any two and multiple selected entropy measures. Therefore, a patient or a healthy subject can be classified using his/her entropy measure probability based on Bayes’ decision rule. The results showed that the best identification performance by a single selected measure had sensitivity of 0.720 and specificity of 0.648. The identification performance was improved to 0.680, 0.796 by the joint pdf of two measures and 0.740, 0.870 by the joint pdf of multiple measures. This study showed that entropy measures could be a powerful tool for early screening of PH patients

PCG Classification Using Multidomain Features and SVM Classifier

This paper proposes a method using multidomain features and support vector machine (SVM) for classifying normal and abnormal heart sound recordings. The database was provided by the PhysioNet/CinC Challenge 2016. A total of 515 features are extracted from nine feature domains, i.e., time interval, frequency spectrum of states, state amplitude, energy, frequency spectrum of records, cepstrum, cyclostationarity, high-order statistics, and entropy. Correlation analysis is conducted to quantify the feature discrimination abilities, and the results show that “frequency spectrum of state”, “energy”, and “entropy” are top domains to contribute effective features. A SVM with radial basis kernel function was trained for signal quality estimation and classification. The SVM classifier is independently trained and tested by many groups of top features. It shows the average of sensitivity, specificity, and overall score are high up to 0.88, 0.87, and 0.88, respectively, when top 400 features are used. This score is competitive to the best previous scores. The classifier has very good performance with even small number of top features for training and it has stable output regardless of randomly selected features for training. These simulations demonstrate that the proposed features and SVM classifier are jointly powerful for classifying heart sound recordings

Full-reference image quality assessment by combining features in spatial and frequency domains

Objective image quality assessment employs mathematical and computational theory to objectively assess the quality of output images based on the human visual system (HVS). In this paper, a novel approach based on multifeature extraction in the spatial and frequency domains is proposed. We combine the gradient magnitude and phase congruency maps to generate a local structure (LS) map, which can perceive local structural distortions. The LS matches well with HVS and highlights differences with details. For complex visual information, such as texture and contrast sensitivity, we deploy the log-Gabor filter, and spatial frequency, respectively, to effectively capture their variations. Moreover, we employ the random forest (RF) to overcome the limitations of existing pooling methods. Compared with support vector regression, RF can obtain better prediction results. Extensive experimental results on the five benchmark databases indicate that the proposed method precedes all the state-of-the-art image quality assessment metrics in terms of prediction accuracy. In addition, the proposed method is in compliance with the subjective evaluations

Formation and Properties of 1-D Alumina Nanostructures Prepared via a Template-free Thermal Reaction

AbstractA facile template-free thermal reaction was applied to prepare one dimensional (1-D) alumina nanostructures. Through utilizing the anisotropic modules existing in layered structures, the 1-D alumina nanostructures could be controlled to form nanotubes or nanorods with various configuration. The characters were then carefully studied and discussed based on the observation of TEM, XRD and photoluminescence

A two-stage mutual information based Bayesian lasso algorithm for multi-locus genome-wide association studies

Genome-wide association study (GWAS) has turned out to be an essential technology for exploring the genetic mechanism of complex traits. To reduce the complexity of computation, it is well accepted to remove unrelated single nucleotide polymorphisms (SNPs) before GWAS, e.g., by using iterative sure independence screening expectation-maximization Bayesian Lasso (ISIS EM-BLASSO) method. In this work, a modi?ed version of ISIS EM-BLASSO is proposed, which reduces the number of SNPs by a screening methodology based on Pearson correlation and mutual information, then estimates the effects via EM-Bayesian Lasso (EM-BLASSO), and finally detects the true quantitative trait nucleotides (QTNs) through likelihood ratio test. We call our method a two-stage mutual information based Bayesian Lasso (MBLASSO). Under three simulation scenarios, MBLASSO improves the statistical power and retains the higher effect estimation accuracy when comparing with three other algorithms. Moreover, MBLASSO performs best on model fitting, the accuracy of detected associations is the highest, and 21 genes can only be detected by MBLASSO in Arabidopsis thaliana datasets.</p

Phylogenetic analysis of HIV-1 genomes based on the position-weighted K-mers method

HIV-1 viruses, which are predominant in the family of HIV viruses, have strong pathogenicity and infectivity. They can evolve into many different variants in a very short time. In this study, we propose a new and effective alignment-free method for the phylogenetic analysis of HIV-1 viruses using complete genome sequences. Our method combines the position distribution information and the counts of the k-mers together. We also propose a metric to determine the optimal k value. We name our method the Position-Weighted k-mers (PWkmer) method. Validation and comparison with the Robinson-Foulds distance method and the modified bootstrap method on a benchmark dataset show that our method is reliable for the phylogenetic analysis of HIV-1 viruses. PWkmer can resolve within-group variations for different known subtypes of Group M of HIV-1 viruses. This method is simple and computationally fast for whole genome phylogenetic analysis.</p