62 research outputs found
A qualitative study of how self-harm starts and continues among Chinese adolescents
Background
It is essential to investigate the experiences behind why adolescents start and continue to self-harm in order to develop targeted treatment and prevent future self-harming behaviours.
Aims
The aims of this study are to understand the motivations for initiating and repeating nonfatal self-harm, the different methods used between first-time and repeated self-harm and the reasons that adolescents do not seek help from health services.
Methods
Adolescents with repeated nonfatal self-harm experiences were recruited to participate in individual, semi-structured qualitative interviews. The interviews were analysed with interpretative phenomenological analysis.
Results
We found that nonfatal self-harm among adolescents occurred comparatively early and was often triggered by specific reasons. However, the subsequent nonfatal self-harm could be causeless, with repeated self-harm becoming a maladaptive coping strategy to handle daily pressure and negative emotions. The choice of tools used was related to the ease of accessibility, the life-threatening risk and the size of the scars. Adolescents often concealed their scars on purpose, which made early identification insufficient. Peer influence, such as online chat groups encouraging self-harm by discussing and sharing self-harm pictures, could also lead to increased self-harm. The results also included participants’ opinions on how to stop nonfatal self-harm and their dissatisfaction with the current healthcare services.
Conclusions
The current study provides important implications both for early identification and interventions for adolescents who engage in repeated nonfatal self-harm, and for individualising treatment planning that benefits them. It is also worthwhile to further investigate how peer influence and social media may affect self-harm in adolescents
MicroRNAs Up-Regulated by CagA of Helicobacter pylori Induce Intestinal Metaplasia of Gastric Epithelial Cells
CagA of Helicobacter pylori is a bacterium-derived oncogenic protein closely associated with the development of gastric cancers. MicroRNAs (miRNAs) are a class of widespread non-coding RNAs, many of which are involved in cell growth, cell differentiation and tumorigenesis. The relationship between CagA protein and miRNAs is unclear. Using mammalian miRNA profile microarrays, we found that miRNA-584 and miRNA-1290 expression was up-regulated in CagA-transformed cells, miRNA-1290 was up-regulated in an Erk1/2-dependent manner, and miRNA-584 was activated by NF-κB. miRNA-584 sustained Erk1/2 activities through inhibition of PPP2a activities, and miRNA-1290 activated NF-κB by knockdown of NKRF. Foxa1 was revealed to be an important target of miRNA-584 and miRNA-1290. Knockdown of Foxa1 promoted the epithelial-mesenchymal transition significantly. Overexpression of miRNA-584 and miRNA-1290 induced intestinal metaplasia of gastric epithelial cells in knock-in mice. These results indicate that miRNA-584 and miRNA-1290 interfere with cell differentiation and remodel the tissues. Thus, the miRNA pathway is a new pathogenic mechanism of CagA
A novel PCR-based method for high throughput prokaryotic expression of antimicrobial peptide genes
<p>Abstract</p> <p>Background</p> <p>To facilitate the screening of large quantities of new antimicrobial peptides (AMPs), we describe a cost-effective method for high throughput prokaryotic expression of AMPs. EDDIE, an autoproteolytic mutant of the N-terminal autoprotease, Npro, from classical swine fever virus, was selected as a fusion protein partner. The expression system was used for high-level expression of six antimicrobial peptides with different sizes: Bombinin-like peptide 7, Temporin G, hexapeptide, Combi-1, human Histatin 9, and human Histatin 6. These expressed AMPs were purified and evaluated for antimicrobial activity.</p> <p>Results</p> <p>Two or four primers were used to synthesize each AMP gene in a single step PCR. Each synthetic gene was then cloned into the pET30a/His-EDDIE-GFP vector via an <it>in vivo </it>recombination strategy. Each AMP was then expressed as an Npro fusion protein in <it>Escherichia coli</it>. The expressed fusion proteins existed as inclusion bodies in the cytoplasm and the expression levels of the six AMPs reached up to 40% of the total cell protein content. On <it>in vitro </it>refolding, the fusion AMPs was released from the C-terminal end of the autoprotease by self-cleavage, leaving AMPs with an authentic N terminus. The released fusion partner was easily purified by Ni-NTA chromatography. All recombinant AMPs displayed expected antimicrobial activity against <it>E. coli</it>, <it>Micrococcus </it>luteus and <it>S. cerevisia</it>.</p> <p>Conclusions</p> <p>The method described in this report allows the fast synthesis of genes that are optimized for over-expression in <it>E. coli </it>and for the production of sufficiently large amounts of peptides for functional and structural characterization. The Npro partner system, without the need for chemical or enzymatic removal of the fusion tag, is a low-cost, efficient way of producing AMPs for characterization. The cloning method, combined with bioinformatic analyses from genome and EST sequence data, will also be useful for screening new AMPs. Plasmid pET30a/His-EDDIE-GFP also provides green/white colony selection for high-throughput recombinant AMP cloning.</p
Prediction Method for Hydraulic Conductivity considering the Effect of Sizes of Ellipsoid Soil Particles from the Microscopic Perspective
Study on the Isolation of Two Atrazine-Degrading Bacteria and the Development of a Microbial Agent
Two bacteria capable of efficiently degrading atrazine were isolated from soil, and named ATLJ-5 and ATLJ-11. ATLJ-5 and ATLJ-11 were identified as Bacillus licheniformis and Bacillus megaterium, respectively. The degradation efficiency of atrazine (50 mg/L) by strain ATLJ-5 can reach about 98.6% after 7 days, and strain ATLJ-11 can reach 99.6% under the same conditions. The degradation of atrazine is faster when two strains are used in combination. Adding the proper amount of fresh soil during the degradation of atrazine by these two strains can also increase the degradation efficiency. The strains ATLJ-5 and ATLJ-11 have high tolerance to atrazine, and can tolerate at least 1000 mg/L of atrazine. In addition, the strains ATLJ-5 and ATLJ-11 have been successfully made into a microbial agent that can be used to treat atrazine residues in soil. The degradation efficiency of atrazine (50 mg/kg) could reach 99.0% by this microbial agent after 7 days. These results suggest that the strains ATLJ-5 and ATLJ-11 can be used for the treatment of atrazine pollution
Nonlinear Behavior of Marine Soil on the Dynamic Stability of Upper Wharf Structures: A Numerical Simulation Approach
Fault Detection for Wind Turbine Blade Bolts Based on GSG Combined with CS-LightGBM
Aiming at the problem of class imbalance in the wind turbine blade bolts operation-monitoring dataset, a fault detection method for wind turbine blade bolts based on Gaussian Mixture Model–Synthetic Minority Oversampling Technique–Gaussian Mixture Model (GSG) combined with Cost-Sensitive LightGBM (CS-LightGBM) was proposed. Since it is difficult to obtain the fault samples of blade bolts, the GSG oversampling method was constructed to increase the fault samples in the blade bolt dataset. The method obtains the optimal number of clusters through the BIC criterion, and uses the GMM based on the optimal number of clusters to optimally cluster the fault samples in the blade bolt dataset. According to the density distribution of fault samples in inter-clusters, we synthesized new fault samples using SMOTE in an intra-cluster. This retains the distribution characteristics of the original fault class samples. Then, we used the GMM with the same initial cluster center to cluster the fault class samples that were added to new samples, and removed the synthetic fault class samples that were not clustered into the corresponding clusters. Finally, the synthetic data training set was used to train the CS-LightGBM fault detection model. Additionally, the hyperparameters of CS-LightGBM were optimized by the Bayesian optimization algorithm to obtain the optimal CS-LightGBM fault detection model. The experimental results show that compared with six models including SMOTE-LightGBM, CS-LightGBM, K-means-SMOTE-LightGBM, etc., the proposed fault detection model is superior to the other comparison methods in the false alarm rate, missing alarm rate and F1-score index. The method can well realize the fault detection of large wind turbine blade bolts
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