96 research outputs found
Correlation between childhood tuberculosis and abundance of T cell gene transcription and impaired T cell function
Purpose: To investigate the relationship amongst childhood tuberculosis, abundance of T cell gene transcription and impairment of T cell function.
Methods: A total of 329 pediatric patients treated for tuberculosis in Central Hospital of Zibo, Zibo, China from 2017 to 2019 were enrolled in the study. Among them, 167 cases of tuberculosis-hospitalized children were assigned to the TB group. Additionally, 162 well- and adequately-treated patients with a previous history of tuberculosis were selected as the control group. The abundance of continuous gene transcripts in the peripheral blood of the children was analyzed. The RNA profiles were analyzed via microarray, while interferon (IFN) level was measured by enzyme linked immunosorbent assay (ELISA). The T cell proliferation was determined by thymidine assay.
Results: Within 6 months of the commencement of treatment, the differentially expressed transcripts returned the expression in children in the control group. The abundance of Talipes equinovarus, atrial septal defect, robin sequence, and the persistence of the left superior vena cava (TARP) gene transcription in the TB group was lower than in the control group on days 30, 120 and 180 (p < 0.05), while IL1R2 gene transcription abundance in the TB group was higher than in the control group on days 30, 120 ,180 (p < 0.05). The proliferation of T cells and IFNÎł in tuberculosis children (TB group) were lower than in healthy controls (p < 0.05). In this study, a total of 129 genes were found to have significant differences in expression, and hence it is speculated that changes in RNA abundance altered the immune pathway.
Conclusion: The reduced abundance of T cell gene transcription and renovated T cell function in children with tuberculosis are related to acquired immunodeficiency. The results of this study provide a theoretical basis for the clinical diagnosis and treatment of tuberculosis in children
ViSNet: an equivariant geometry-enhanced graph neural network with vector-scalar interactive message passing for molecules
Geometric deep learning has been revolutionizing the molecular modeling
field. Despite the state-of-the-art neural network models are approaching ab
initio accuracy for molecular property prediction, their applications, such as
drug discovery and molecular dynamics (MD) simulation, have been hindered by
insufficient utilization of geometric information and high computational costs.
Here we propose an equivariant geometry-enhanced graph neural network called
ViSNet, which elegantly extracts geometric features and efficiently models
molecular structures with low computational costs. Our proposed ViSNet
outperforms state-of-the-art approaches on multiple MD benchmarks, including
MD17, revised MD17 and MD22, and achieves excellent chemical property
prediction on QM9 and Molecule3D datasets. Additionally, ViSNet achieved the
top winners of PCQM4Mv2 track in the OGB-LCS@NeurIPS2022 competition.
Furthermore, through a series of simulations and case studies, ViSNet can
efficiently explore the conformational space and provide reasonable
interpretability to map geometric representations to molecular structures
The correlation of the intestinal with pharyngeal microbiota in early neonates
IntroductionThe gut-lung axis has long been recognized as an important mechanism affecting intestinal and lung immunity. Still, few studies have examined the correlation between the intestinal and pharyngeal microbiota in early neonates, especially when feeding patterns are one of the main drivers of microbiota development.MethodsTo explore the composition and function of intestinal and pharyngeal microbiota and to analyze the effect of limited formula feeding on the initial microbiota colonization in early full-term neonates, we characterized the stool and oropharyngeal microbiota of 20 healthy full-term newborns sampled on days 0 and 5–7 after birth using 16S rRNA gene sequencing. Based on the sequencing results, a comparison was made of the compositions and functions of the intestinal and oropharyngeal microbiota for analysis.Results and discussionAt the phylum level, Firmicutes, Actinobacteria, Proteobacteria, and Bacteroidetes were the most abundant in both niches. At the genus level, the species of pioneer bacteria were rich in the intestine and oropharynx but low in abundance on day 0. On days 5–7, Bifidobacterium (25.40%) and Escherichia-Shigella (22.16%) were dominant in the intestine, while Streptococcus (38.40%) and Staphylococcus (23.13%) were dominant in the oropharynx. There were eight core bacteria genera in the intestine and oropharynx on days 5–7, which were Bifidobacterium, Escherichia-Shigella, Staphylococcus, Streptococcus, Bacteroides, Parabacteroides, Rothia, and Acinetobacter. As indicated by PICRUSt analysis, on days 5–7, the intestinal microbiota was more predictive than the oropharyngeal microbiota in transcription, metabolism, cell motility, cellular processes and signaling, and organismal system function in the KEGG pathway. Compared to exclusive breastfeeding, limited formula feeding (40–60%) had no significant effect on the neonatal intestinal and oropharyngeal microbiota composition during the initial colonization period. Our results suggest that the initial colonization of microbiota is closely related to the ecological niche environment in the intestine and oropharynx, with their core microbiota being closely correlated. We found that early limited formula feeding could not significantly affect the initial colonization of microbiota in the intestine and oropharynx
Bioactive Constituents of Verbena officinalis Alleviate Inflammation and Enhance Killing Efficiency of Natural Killer Cells
Natural killer (NK) cells play key roles in eliminating pathogen-infected cells. Verbena
officinalis (V. officinalis) has been used as a medical plant in traditional and modern medicine for
its anti-tumor and anti-inflammatory activities, but its effects on immune responses remain largely
elusive. This study aimed to investigate the potential of V. officinalis extract (VO extract) to regulate
inflammation and NK cell functions. We examined the effects of VO extract on lung injury in a mouse
model of influenza virus infection. We also investigated the impact of five bioactive components of
VO extract on NK killing functions using primary human NK cells. Our results showed that oral
administration of VO extract reduced lung injury, promoted the maturation and activation of NK
cells in the lung, and decreased the levels of inflammatory cytokines (IL-6, TNF-α and IL-1β) in the
serum. Among five bioactive components of VO extract, Verbenalin significantly enhanced NK killing
efficiency in vitro, as determined by real-time killing assays based on plate-reader or high-content
live-cell imaging in 3D using primary human NK cells. Further investigation showed that treatment
of Verbenalin accelerated the killing process by reducing the contact time of NK cells with their
target cells without affecting NK cell proliferation, expression of cytotoxic proteins, or lytic granule
degranulation. Together, our findings suggest that VO extract has a satisfactory anti-inflammatory
effect against viral infection in vivo, and regulates the activation, maturation, and killing functions of
NK cells. Verbenalin from V. officinalis enhances NK killing efficiency, suggesting its potential as a
promising therapeutic to fight viral infection
Chitin-based Materials in Tissue Engineering: Applications in Soft Tissue and Epithelial Organ
Chitin-based materials and their derivatives are receiving increased attention in tissue engineering because of their unique and appealing biological properties. In this review, we summarize the biomedical potential of chitin-based materials, specifically focusing on chitosan, in tissue engineering approaches for epithelial and soft tissues. Both types of tissues play an important role in supporting anatomical structures and physiological functions. Because of the attractive features of chitin-based materials, many characteristics beneficial to tissue regeneration including the preservation of cellular phenotype, binding and enhancement of bioactive factors, control of gene expression, and synthesis and deposition of tissue-specific extracellular matrix are well-regulated by chitin-based scaffolds. These scaffolds can be used in repairing body surface linings, reconstructing tissue structures, regenerating connective tissue, and supporting nerve and vascular growth and connection. The novel use of these scaffolds in promoting the regeneration of various tissues originating from the epithelium and soft tissue demonstrates that these chitin-based materials have versatile properties and functionality and serve as promising substrates for a great number of future applications
Microstructure and mechanical properties of Cu joints soldered with a Sn-based composite solder, reinforced by metal foam
In this study, Ni foam, Cu coated Ni foam and Cu-Ni alloy foams were used as strengthening phases for pure Sn solder. Cu-Cu joints were fabricated by soldering with these Sn-based composite solders at 260 °C for different times. The tensile strength of pure Sn solder was improved significantly by the addition of metal foams, and the Cu-Ni alloy/Sn composite solder exhibited the highest tensile strength of 50.32 MPa. The skeleton networks of the foams were gradually dissolved into the soldering seam with increasing soldering time, accompanied by the massive formation of (Cu,Ni)6Sn5 phase in the joint. The dissolution rates of Ni foam, Cu coated Ni foam and Cu-Ni alloy foams into the Sn matrix increased successively during soldering. An increased dissolution rate of the metal foam leads to an increase in the Ni content in the soldering seam, which was found to be beneficial in refining the (Cu,Ni)6Sn5 phase and inhibiting the formation of the Cu3Sn IMC layer on the Cu substrate surface. The average shear strength of the Cu joints was improved with increasing soldering time, and a shear strength of 61.2 MPa was obtained for Cu joints soldered with Cu-Ni alloy/Sn composite solder for 60 min
Comment les professeurs soutiennent-ils la coordination, par les Ă©tudiants, de la perception et du raisonnement ? : Etude de cas en France et en Chine
L'apprentissage de la géométrie 3D pose des problèmes depuis longtemps. Les environnements de géométrie dynamique 3D (EGD 3D) offrent aux enseignants de nouvelles possibilités pour développer la visualisation des étudiants, mais soulèvent également des problèmes, tels que, pour les étudiants, la tension entre la perception et le raisonnement logique. Cette étude examine un comportement essentiel, mais difficile, pour les enseignants dans les EGD 3D : la conduite de coordination visant à aider les étudiants à coordonner leur propre perception et les différents modes de raisonnement logique, qui comprennent non seulement le raisonnement théorique déductif, mais aussi le raisonnement inductif et abductif. Nous étudions ensuite comment ce comportement peut être lié aux caractéristiques de la situation géométrique (dynamique) et aux connaissances et points de vue des enseignants.Un cadre théorique composite est établi pour répondre à ces questions. L'Approche Documentaire du Didactique (ADD, Trouche et al., 2020) sert d’un cadre structurant qui intègre les régularités dans la conduite de coordination de l’enseignant, et ses connaissances et points de vue, dans une unité cohérente – le schème d'usage (renommé "schème de coordination" dans cette étude). Les règles d'action dans le schème de coordination sont connectées à un sous-cadre, qui est construit à l'aide du diagramme d'argument de Toulmin (1958). Les invariants opératoires dans le schème de coordination sont connectés à un sous-cadre de catégorisation, qui est construit sur le cadre TPACK (Koehler & Mishra, 2009) et d'autres études sur les points de vue des enseignants concernant le contrôle du comportement, les normes sociales et l'économie temporelle (Pierce & Ball, 2009 ; Ruthven, 2014). Les caractéristiques de la situation géométrique (dynamique) sont également décrites selon plusieurs dimensions, lesquelles sont identifiées d'après les travaux de Piaget et al. (1973) et Morgan et al. (2009).Adoptant une méthodologie d’études de cas et se situant dans un projet de cotutelle sino-français, cette étude suit des séries de leçons intégrant des EGD 3D de trois enseignants, dont deux françaises et un chinois, qui ont une grande expérience de l'utilisation des EGD 3D. L'étude aboutit finalement à un cadre renouvelé qui permet de saisir les caractéristiques essentielles des activités de coordination des enseignants, et ouvre de nouvelles perspectives tant pour la formation des enseignants que pour des recherches futures.There have been long-standing challenges in learning 3D geometry. 3D dynamic geometry environments (3D DGEs) offer teachers new opportunities for supporting student visualization but also raise issues, such as the tension between students’ perception and logical reasoning. This study investigates an essential but challenging teacher practice in the learning environments integrated with 3D DGEs: the coordination behavior in support of students’ coordination of their own perception and different modes of logical reasoning which not only include theoretical deductive reasoning but also inductive and abductive reasoning. We further investigate how can this behavior be linked with the characteristics of the (dynamic) geometrical situation and teachers’ knowledge and views.We establish a compound framework to address these questions. The Documentational Approach to Didactics (Trouche et al., 2020) serves as a global framework to integrate the regularities in teachers’ coordination behavior and the underpinning knowledge and views into a coherent unity – usage scheme (renamed “coordination scheme” in this study). The rules of action in the coordination scheme are connected with a sub-framework which is built with the help of Toulmin's (2003) diagram of argument. The operational invariants in the coordination scheme are categorized with a framework, which is built on the TPACK knowledge framework (Koehler & Mishra, 2009) and other studies on teachers’ views about behavior control, social norms and time economy (Pierce & Ball, 2009; Ruthven, 2014). The characteristics of the (dynamic) geometrical situation are also structured from several dimensions which are identified according to the work of Piaget et al. (1973) and Morgan et al. (2009).Adopting a case study methodology and being situated in a Sino-French cooperation project, we use the compound framework to analyze the 3D DGE integrated lessons of experienced teachers in both France and China. The study finally leads to a renewed framework that allows capturing essential features of teachers’ coordination activities and opens new perspectives for both teacher education and further research
A Novel Domain Adaptation-Based Intelligent Fault Diagnosis Model to Handle Sample Class Imbalanced Problem
As the key component to transmit power and torque, the fault diagnosis of rotating machinery is crucial to guarantee the reliable operation of mechanical equipment. Regrettably, sample class imbalance is a common phenomenon in industrial applications, which causes large cross-domain distribution discrepancies for domain adaptation (DA) and results in performance degradation for most of the existing mechanical fault diagnosis approaches. To address this issue, a novel DA approach that simultaneously reduces the cross-domain distribution difference and the geometric difference is proposed, which is defined as MRMI. This work contains three parts to improve the sample class imbalance issue: (1) A novel distance metric method (MVD) is proposed and applied to improve the performance of marginal distribution adaptation. (2) Manifold regularization is combined with instance reweighting to simultaneously explore the intrinsic manifold structure and remove irrelevant source-domain samples adaptively. (3) The â„“2-norm regularization is applied as the data preprocessing tool to improve the model generalization performance. The gear and rolling bearing datasets with class imbalanced samples are applied to validate the reliability of MRMI. According to the fault diagnosis results, MRMI can significantly outperform competitive approaches under the condition of sample class imbalance
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