Platelets are non-nucleated blood effector cells, which plays an important role in coagulation, hemostasis, and thrombosis. However, platelets are extremely susceptible to activation by external stimuli, which in turn damages the platelet’s natural biological activity and affects its biological function. Platelet biological activity has become a hotspot in the field of vascular diseases. In this study, ultrasound parameters (ultrasound intensity and duration time) were used to intervene in the biological activity of platelets. The response of platelets to ultrasound energy was explored from the aspects of platelet morphology, aggregation ability and particle release (the expression of P-selectin and the number of particles). The results showed that the ultrasound intensity of 0.25 W/cm2 (1 MHz, 60 s) had no effect on the morphology, aggregation ability and particle release of platelets. When the ultrasonic intensity was increased to greater than 0.25 W/cm2, the generation of platelet pseudopods, morphological changes, increase of particle release, as well as effect on aggregation were observed. When the ultrasound duration time was 60 s (1 MHz, 0.25 W/cm2), it had no effect on the biological activity of platelets. However, when the ultrasound time was greater than 60 s, the morphology, aggregation ability and microparticles release would been induced with no effect on the secretion of CD62P and total protein components. Therefore, when the ultrasound parameters were 1 MHz and 0.25 W/cm2 with 60 s duration time, the ultrasound energy had no effect on the biological activity of platelets. The results in this study are of great significant for ultrasound energy intervention for the treatment of platelet-related diseases.
ObjectiveExon sequencing and bioinformatics techniques were used to explore the pathogenesis of familial cluster epilepsy at the gene level and search for possible susceptibility genes of familial cluster epilepsy. Methods We selected 20 patients diagnosed with familial cluster epilepsy from the Second Affiliated Hospital of Shandong First Medical University as the research objects, and extracted all potential single nucleotide polymorphism sites and nucleotide insertion or deletion variation in the whole genome, to evaluate the pathogenicity of the mutation site and perform gene ontology pathway analysis of candidate genes. Results The sequencing data of 20 DNA samples were qualified. 28 candidate genes were selected by whole-exon sequencing combined with bioinformatics analysis. Gene ontology of epilepsy risk genes mainly acts on neuroactive ligand-receptor interactions, cholinergic synapses and ion channels. Conclusion A total of 10 genes, TSC 2, NRXN 1, POLG, POLG 2, WDR 45, TBC1D24, CHRNA2,K ANSL1, DEPDC5, and CACNA1A, may be susceptibility genes for familial cluster epilepsy. Candidate genes for familial cluster epilepsy may be involved in biological pathways such as neuroactive ligand-receptor interactions, cholinergic synapses and ion channels.
Recombinant protein SMBPRG4 containing two Somatomedin B domains and a small amount of glycosylation of repetitive sequences of proteoglycan 4 was cloned according to PGR4 gene polymorphism. Mature purification process was established and recombinant protein SMBPRG4, with high-level expression was purified. By using size-exclusion chromatogaraphy and dynamic light scattering, we found that the recombinant protein self-aggregate to dimeric form. Structure prediction and non-reducing electrophoresis revealed that SMBPRG4 was a non-covalently bonded dimer.
ObjectiveTo investigate the impact of clopidogrel resistance on the long-term prognosis in the elderly with acute coronary syndrome (ACS), as clopidogrel is widely used for secondary prevention in the patients with ACS, while studies on the relationship between clopidogrel resistance and long-term outcome in the elderly with ACS are limited. MethodsThree hundred elderly patients with ACS, aged from 70 to 95, with on average age of (81.3±6.4) years old, receiving clopidogrel (75 mg, once a day) over one month between January 2009 and December 2010 were followed up for major adverse cardiac events (MACE, including cardiac death, non-fatal re-myocardial infarction, angina, ischemia stroke/TIA, acute thrombosis and hemorrhage). Platelet aggregation was measured by light transmission aggregometry using adenosine diphosphate as a stimulus. According to the variation of platelet aggregation, the patients were divided into clopidogrel resistance group (<10%) and non-lopidogrel resistance group (≥10%). The median follow-up was 2 years. A Cox hazard proportional model was used to estimate time to outcome associated with clopidogrel resistance and MACE. ResultsThe incidence of clopidogrel resistance was 24.0% in our study population. Patients with diabetes, renal insufficiency, or a higher body mass index tended to have clopidogrel resistance. Compared with those patients without clopidogrel resistance, there was significantly increased MACE in patients with clopidogrel resistance (37.5%, 22.8%; P=0.032). Additionally, Cox hazard proportional model analysis demonstrated that clopidogrel resistance was an independently risk factor for MACE[HR=2.34, 95% CI (1.07, 4.57), P=0.016]. ConclusionDiabetes, renal insufficiency and high body max index are associated with clopidogrel resistance, which can predict the increased risk of MACE in elderly patients with ACS.
Objective To screen the prognostic related genes specific to idiopathic pulmonary fibrosis (IPF), understand the pathogenesis of IPF and provide potential therapeutic targets, as well as provide a data basis for the related research focusing on the functional verification and clinical transformation potential of prognostic gene targets. Methods Transcriptome datasets of multiple disease groups diagnosed in accordance with the IPF diagnostic criteria from the Gene Expression Omnibus (GEO) were included. Difference analyses were conducted between disease groups and control groups for datasets of different data types respectively. The difference analysis results of the up-regulated genes and down-regulated genes were respectively summarized and analyzed using the robust rank aggregation (RRA) algorithm. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and survival analyses were performed on the top 30 up-regulated genes in the ranking. Results Among the GO analysis results of the top 30 upregulated genes in the ranking, the key biological processes and mechanisms of IPF were mainly extracellular matrix (ECM) remodeling and abnormal differentiation and repair of epithelial cells. In the KEGG analysis results, the IPF-related signaling pathways include the relaxin signaling pathway, ECM-receptor interaction, and transforming growth factor-β (TGF-β) signaling pathway. Among them, the seven genes with positive significance in survival analysis were as follows: complement factor H (CFH), collagen type I alpha 1 chain (COL1A1), keratin 14 (KRT14), lymphocyte antigen 6 family member D (LY6D), matrix metallopeptidase1 (MMP1), matrix metallopeptidase 7 (MMP7), Versican (VCAN). ConclusionsCFH, COL1A1, KRT14, LY6D, MMP1, MMP7, and VCAN are potential prognostic genes related to IPF. Among them, MMP7 has the greatest potential.
Early screening of skin cancer is crucial to the survival rate of patients. Although deep learning has made significant progress in dermoscopic image analysis, the blurred edge of the lesion, the vulnerability to noise interference, and the limited computing resources at the time of model deployment are still the main bottlenecks. To this end, this paper proposes a frequency-space collaborative enhancement network (FSC-Net) based on lightweight classification. Aiming at the problem of blurred lesion edge and noise interference, the network first constructs a learning frequency enhancement module. Through the dynamic selective enhancement of frequency domain features, the lesion edge is finely characterized while suppressing high-frequency artifacts. Secondly, aiming at the scale heterogeneity of lesion morphology, this paper proposes a multi-scale aggregation module, which uses multi-branch pooling to reduce the loss of deep semantic features in the lightweight network. Finally, in order to solve the problem of difficult localization of complex lesion areas, this paper introduces a directional spatial calibration mechanism, which realizes accurate localization of lesion features through orthogonal decoupling coding and asymmetry factors. The experimental results on the 2019 international skin image collaboration challenge (ISIC2019) and the human against machine with 10000 training images (HAM10000) dataset show that FSC-Net achieves 93.41% eight-classification accuracy and 95.84% seven-classification accuracy with a lower number of parameters. Compared with the existing advanced models, the proposed method achieves a better balance between computational overhead and diagnostic performance, and provides a robust and efficient solution for auxiliary diagnosis in resource-constrained environments.