Circular RNAs (circRNAs) are an abundant class of endogenous non-coding RNAs and are associated with numerous diseases, including cancer, cardiovascular diseases, and type 2 diabetes mellitus (T2DM). However, the association between circRNAs and inflammation or inflammatory cytokines in patients with T2DM remains to be fully elucidated. The purpose of the present study was to investigate the expression profiles of circRNAs in peripheral leucocytes of patients with T2DM and their association with inflammatory cytokines. Peripheral blood from patients with T2DM (n=43) and healthy individuals (n=45) were collected for RNA sequencing and later verification. Reverse transcription-polymerase chain reaction (RT-PCR) and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) analyses were used to detect the expression levels of circRNAs. The expression of inflammatory factors, including interleukin (IL)-1, (IL)-6, and tumor necrosis factor (TNF)-α were measured via enzyme-linked immunosorbent assay. Furthermore, the mRNA expression level of ankyrin repeat domain 36 (ANKRD36), a protein located at 2q11.2 that interacts with the GAPDH gene, was measured using RT-qPCR analysis. The circRNA/microRNA (miRNA) interaction was predicted using RegRNA and mirPath software. In total, 220 circRNAs were found to be differentially expressed between patients with T2DM and healthy individuals, of which 107 were upregulated and 113 were downregulated. Among the nine selected circRNAs, circANKRD36 was significantly upregulated in patients with T2DM compared with control subjects (P=0.02). The expression level of circANKRD36 was positively correlated with glucose and glycosylated hemoglobin (r=0.3250, P=0.0047 and r=0.3171, P=0.0056, respectively). The expression level of IL-6 was significantly different between the T2DM group and control group (P=0.028) and was positively correlated with circANKRD36. The difference of circANKRD36 host gene expression between patients with T2DM and healthy controls was significant (P=0.04). Taken together, circANKRD36 may be involved in T2DM and inflammation-associated pathways via interaction with miRNAs, including hsa-miR-3614-3p, hsa-miR-498, and hsa-miR-501-5p. The expression of circANKRD36 was up regulated in peripheral blood leucocytes and was correlated with chronic inflammation in T2DM. Therefore, circANKRD36 can be used as a potential biomarker for screening chronic inflammation in patients with T2DM.

Invasive fungal infections acquired in the hospital have progressively emerged as an important cause of life-threatening infection. In particular, airborne fungi in hospitals are considered critical pathogens of hospital-associated infections. To identify the causative airborne microorganisms, high-volume air samplers were utilized for collection, and species identification was performed using a culture-based method and DNA sequencing analysis with the Illumina MiSeq and HiSeq 2000 sequencing systems. Few bacteria were grown after cultivation in blood agar. However, using microbiome sequencing, the relative abundance of fungi, Archaea species, bacteria and viruses was determined. The distribution characteristics of fungi were investigated using heat map analysis of four departments, including the Respiratory Intensive Care Unit, Intensive Care Unit, Emergency Room and Outpatient Department. The prevalence of Aspergillus among fungi was the highest at the species level, approximately 17% to 61%, and the prevalence of Aspergillus fumigatus among Aspergillus species was from 34% to 50% in the four departments. Draft genomes of microorganisms isolated from the hospital environment were obtained by sequence analysis, indicating that investigation into the diversity of airborne fungi may provide reliable results for hospital infection control and surveillance.

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Highlights CEST MRI under non-equilibrium conditions is prone to measurement variabilities. The QUASS algorithm reconstructs the equilibrium CEST effect from measurements. The QUASS CEST algorithm enables fast and equilibrium tumor imaging at 3 T.

Corners in images represent a lot of important information. Extracting corners accurately is significant to image processing, which can reduce much of the calculations. In this paper, two widely used corner detection algorithms, SUSAN and Harris corner detection algorithms which are both based on intensity, were compared in stability, noise immunity and complexity quantificationally via stability factor η, anti-noise factor ρ and the runtime of each algorithm. It concluded that Harris corner detection algorithm was superior to SUSAN corner detection algorithm on the whole. Moreover, SUSAN and Harris detection algorithms were improved by selecting an adaptive gray difference threshold and by changing directional differentials, respectively, and compared using these three criterions. In addition, SUSAN and Harris corner detectors were applied to an image matching experiment. It was verified that the quantitative evaluations of the corner detection algorithms were valid through calculating match efficiency, defined as correct matching corner pairs dividing by matching time, which can reflect the performances of a corner detection algorithm comprehensively. Furthermore, the better corner detector was used into image mosaic experiment, and the result was satisfied. The work of this paper can provide a direction to the improvement and the utilization of these two corner detection algorithms

Lung microbiome ecosystem homeostasis in idiopathic pulmonary fibrosis (IPF) remains uncharacterized. The aims of this study were to identify unique microbial signatures of the lung microbiome and analyze microbial gene function in IPF patients. DNA isolated from BALF samples was obtained for high-throughput gene sequencing. Microbial metagenomic data were used for principal component analysis (PCA) and analyzed at different taxonomic levels. Shotgun metagenomic data were annotated using the KEGG database and were analyzed for functional and metabolic pathways. In this study, 17 IPF patients and 38 healthy subjects (smokers and non-smokers) were recruited. For the PCA, the first and the second principal component explained 16.3 and 13.4% of the overall variability, respectively. The β diversity of microbiome was reduced in the IPF group. Signature of IPF's microbes was enriched of Streptococcus, Pseudobutyrivibrio, and Anaerorhabdus . The translocation of lung microbiome was shown that 32.84% of them were from oral. After analysis of gene function, ABC transporter systems, biofilm formation, and two-component regulatory system were enriched in IPF patients' microbiome. Here we shown the microbiology characteristics in IPF patients. The microbiome may participate in altering internal conditions and involving in generating antibiotic resistance in IPF patients.

Abstract-Malaria is one of the most serious parasitic infections of human. The accurate and timely diagnosis of malaria infection is essential to control and cure the disease. Some image processing algorithms to automate the diagnosis of malaria on thin blood smears are developed, but the percentage of parasitaemia is often not as precise as manual count. One reason resulting in this error is ignoring the cells at the borders of images. In order to solve this problem, a kind of diagnosis scheme within large field of view (FOV) is proposed. It includes three steps. The first step is image mosaicing to obtain large FOV based on space-time manifolds. The second step is the segmentation of erythrocytes where an improved Hough Transform is used. The third step is the detection of nucleated components. At last, it is concluded that the counting accuracy of malaria infection within large FOV is finer than several regular FOVs.

Circulating tumor cells (CTCs) quantification may be helpful for evaluating cancer dissemination, predicting prognosis and assessing therapeutic effectiveness and safety. In the present study, CTCs from blood samples of 72 patients with hepatocellular carcinoma (HCC) were enriched with anti-EpCAM nanoparticles. AFP mRNA level was detected by nested polymerase chain reaction (PCR) after enrichment of CTCs from HCC blood samples at 0, 3, 6, 9 and 12 months after hepatectomy, respectively. AFP mRNA expression in CTCs was positive in 43 patients (59.7%) and negative in 29 patients (40.3%) before hepatectomy. Among 43 patients with positive AFP mRNA expression in CTCs before hepatectomy, 10 and 11 were diagnosed as intrahepatic/extrahepatic metastasis before and after hepatectomy, respectively. In addition, these 21 patients with metastasis had persisting positive AFP mRNA of CTCs during the whole tested year. Specifically, 3 patients with AFP mRNA negative in CTCs before hepatectomy changed to be positive at 6 and 9 months, and 2 of them were diagnosed as metastasis 12 months after hepatectomy. We conclude that the positive AFP mRNA of CTCs can be a pivotal predictor for HCC metastasis before and after hepatectomy. The release of AFP expression from hepatocellular carcinoma cells into circulation must be a major source of HCC metastasis.