Diagnosis and surgical outcomes of coarctation of the aorta in pediatric patients: a retrospective study

BackgroundCoarctation of the aorta (CoA) is a common congenital cardiovascular malformation, and improvements in the diagnostic process for surgical decision-making are important. We sought to compare the diagnostic accuracy of transthoracic echocardiography (TTE) with computed tomographic angiography (CTA) to diagnose CoA.MethodsWe retrospectively reviewed 197 cases of CoA diagnosed by TTE and CTA and confirmed at surgery from July 2009 to August 2019.ResultsThe surgical findings confirmed that 19 patients (9.6%) had isolated CoA and 178 (90.4%) had CoA combined with other congenital cardiovascular malformations. The diagnostic accuracy of CoA by CTA was significantly higher than that of TTE (χ2 = 6.52, p = 0.01). In contrast, the diagnostic accuracy of TTE for associated cardiovascular malformations of CoA was significantly higher than that of CTA (χ2 = 15.36, p < 0.0001). Infants and young children had more preductal type of CoA, and PDA was the most frequent cardiovascular lesion associated with CoA. The pressure gradient was significantly decreased after the first operation, similar at 6 months, 1 year, and 3 years follow-ups by TTE.ConclusionsCTA is more accurate as a clinical tool for diagnosing CoA; however, TTE with color Doppler can better identify associated congenital cardiovascular malformations. Therefore, combining TTE and CTA would benefit clinical evaluation and management in patients suspected of CoA. TTE was valuable for post-operation follow-up and clinical management

Classification of subtypes and identification of dysregulated genes in sepsis

BackgroundSepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis.MethodsThe datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples.ResultsA total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients.ConclusionThis study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis

Association between estrogen receptor gene polymorphisms and the development and progression of hepatocellular carcinoma

The development and progression of hepatocellular carcinoma (HCC) is associated with estrogen, which exerts its physiological effect by binding to estrogen receptor (ER). The function of ER is regulated by related genes, while the expression and function of these genes are affected by gene polymorphisms, and the genetic susceptibility to tumors is due to the combined effect of different genes and polymorphisms. Therefore, it is believed that ER gene polymorphisms may affect the development, progression, and prognosis of HCC. This article reviews the research advances in ER gene polymorphisms in recent years

A Novel K-Means Clustering Algorithm with a Noise Algorithm for Capturing Urban Hotspots

With the development of cities, urban congestion is nearly an unavoidable problem for almost every large-scale city. Road planning is an effective means to alleviate urban congestion, which is a classical non-deterministic polynomial time (NP) hard problem, and has become an important research hotspot in recent years. A K-means clustering algorithm is an iterative clustering analysis algorithm that has been regarded as an effective means to solve urban road planning problems by scholars for the past several decades; however, it is very difficult to determine the number of clusters and sensitively initialize the center cluster. In order to solve these problems, a novel K-means clustering algorithm based on a noise algorithm is developed to capture urban hotspots in this paper. The noise algorithm is employed to randomly enhance the attribution of data points and output results of clustering by adding noise judgment in order to automatically obtain the number of clusters for the given data and initialize the center cluster. Four unsupervised evaluation indexes, namely, DB, PBM, SC, and SSE, are directly used to evaluate and analyze the clustering results, and a nonparametric Wilcoxon statistical analysis method is employed to verify the distribution states and differences between clustering results. Finally, five taxi GPS datasets from Aracaju (Brazil), San Francisco (USA), Rome (Italy), Chongqing (China), and Beijing (China) are selected to test and verify the effectiveness of the proposed noise K-means clustering algorithm by comparing the algorithm with fuzzy C-means, K-means, and K-means plus approaches. The compared experiment results show that the noise algorithm can reasonably obtain the number of clusters and initialize the center cluster, and the proposed noise K-means clustering algorithm demonstrates better clustering performance and accurately obtains clustering results, as well as effectively capturing urban hotspots

Segmentation technology for character recognition of special note

A new method is proposed..

pH-Responsive Nanoparticles for Delivery of Paclitaxel to the Injury Site for Inhibiting Vascular Restenosis

A high incidence of restenosis has been reported at the site of inflammation following angioplasty and stent implantation. The anti-proliferative drug paclitaxel (PTX) could help to reduce inflammation and restenosis; however, it has poor water solubility and serious adverse side effects at high doses. Given the presence of metabolic acidosis at the site of inflammation, we hypothesized that nanoparticles that are responsive to low pH could precisely release the loaded drug at the target site. We successfully constructed pH-responsive poly(D, L-lactic-co-glycolic acid) (PLGA) nanoparticles loaded with PTX and NaHCO3 as a pH-sensitive therapeutic agent (PTX-NaHCO3-PLGA NPs). The NPs exhibited remarkable pH sensitivity and a good safety profile both in vitro in rat vascular smooth muscle cells and in vivo in Sprague Dawley rats after tail vein injection. In the rat model, the PTX-NaHCO3-PLGA NPs treatment group showed suppressed intimal proliferation following balloon-induced carotid artery injury compared with that of the saline-treated control. Overall, these results demonstrate that our newly developed pH-responsive nanodrug delivery platform has the potential to effectively inhibit restenosis

GSHR, a Web-Based Platform Provides Gene Set-Level Analyses of Hormone Responses in Arabidopsis

Phytohormones regulate diverse aspects of plant growth and environmental responses. Recent high-throughput technologies have promoted a more comprehensive profiling of genes regulated by different hormones. However, these omics data generally result in large gene lists that make it challenging to interpret the data and extract insights into biological significance. With the rapid accumulation of theses large-scale experiments, especially the transcriptomic data available in public databases, a means of using this information to explore the transcriptional networks is needed. Different platforms have different architectures and designs, and even similar studies using the same platform may obtain data with large variances because of the highly dynamic and flexible effects of plant hormones; this makes it difficult to make comparisons across different studies and platforms. Here, we present a web server providing gene set-level analyses of Arabidopsis thaliana hormone responses. GSHR collected 333 RNA-seq and 1,205 microarray datasets from the Gene Expression Omnibus, characterizing transcriptomic changes in Arabidopsis in response to phytohormones including abscisic acid, auxin, brassinosteroids, cytokinins, ethylene, gibberellins, jasmonic acid, salicylic acid, and strigolactones. These data were further processed and organized into 1,368 gene sets regulated by different hormones or hormone-related factors. By comparing input gene lists to these gene sets, GSHR helped to identify gene sets from the input gene list regulated by different phytohormones or related factors. Together, GSHR links prior information regarding transcriptomic changes induced by hormones and related factors to newly generated data and facilities cross-study and cross-platform comparisons; this helps facilitate the mining of biologically significant information from large-scale datasets. The GSHR is freely available at http://bioinfo.sibs.ac.cn/GSHR/

Maternal and infantile gut mycobiome during the weaning period in free ranging Tibetan macaques (Macaca thibetana)

Abstract Gut microbiome is critical to the health of mammals. Many previous studies have revealed the gut bacterial microbiomes of mother and infant changed significantly during the weaning period. However, little is known concerning the gut mycobiome of wild primates. Here, we examined the variations on gut mycobiome between weaning and post‐weaning for both mother and infant in wild‐living Tibetan macaques (Macaca thibetana). Our results showed that the gut mycobiomes of mother and infant were dominated by two phyla Ascomycota and Basidiomycota. For both mother and infant, the ASV richness of gut mycobiome remained relatively steady from weaning to post‐weaning periods, while the Shannon indexes increased significant in weaning compared to post‐weaning periods. However, no significant difference between mother and infant ASV richness and Shannon indexes during weaning and post‐weaning periods respectively. Compared to mothers, we found that much more known taxa of gut fungi were enriched in weaning or post‐weaning periods of infants. In particular, we found that the dominant genus Aspergillus was enriched in infants during weaning period. Furthermore, we found that the relative abundance of plant pathogens were significantly higher in the post‐weaning period than in the weaning period for infants. Our results indicated that weaning events could affect the gut mycobiome significantly for both mothers and infant in Tibetan macaques, which had a stronger effect on the gut mycobiome of infant monkeys than on their mothers

Expression of miR-93-5p as a Potential Predictor of the Severity of Chronic Thromboembolic Pulmonary Hypertension

Background. MicroRNAs (miRNAs) play an important role in the pathogenesis of chronic thromboembolic pulmonary hypertension (CTEPH). However, the potential correlation between miRNA expression and the severity of CTEPH remains unclear. Our previous study indicated that miRNAs hsa-let-7b-3p, hsa-miR-17-5p, hsa-miR-106b-5p, hsa-miR-3202, hsa-miR-665, and hsa-miR-93-5p are closely involved in CTEPH. This study assessed the associations between the expression levels of these miRNAs and clinical parameters in CTEPH patients. Methods. A total of eight CTEPH patients and eight healthy adults as a reference group were included, and clinical data including total protein (TP), albumin (Alb), lactate dehydrogenase (LDH), hydroxybutyrate dehydrogenase (HBDH), uric acid (UA), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels were collected. Right heart catheterization was conducted to obtain hemodynamic data including cardiac index (CI). The expression levels of let-7b-3p, miR-17-5p, miR-106b-5p, miR-3202, miR-665, and miR-93-5p were measured by quantitative real-time PCR (qPCR). Correlation analysis was applied to estimate the associations between miRNA expression levels and clinical parameters in CTEPH patients. Results. Serum TP and Alb levels were decreased, while LDH, HBDH, and UA levels were increased in CTEPH patients compared with the reference group (P<0.05). miR-3202 and miR-665 were upregulated, whereas let-7b-3p, miR-17-5p, miR-106b-5p, and miR-93-5p were downregulated in CTEPH patients relative to the reference group (P<0.05). miR-93-5p expression was positively correlated with NT-proBNP level and negatively correlated with CI (P<0.05). Moreover, let-7b-3p tended to be positively correlated with mean pulmonary arterial pressure. Conclusions. miR-93-5p expression was associated with the severity of CTEPH and could act as a potential predictor of high-risk CTEPH