The sensitivity and specificity of one field non-mydriatic digital fundus photography for DR screening

AIM:To evaluate the sensitivity and specificity of one-field non-mydriatic digital fundus photography and direct ophthalmoscopy for diabetic retinopathy(DR)screening, compared with fundus fluorescein angiography( FFA ).<p>METHODS:All 93 patients of type 1 or 2 diabetic who have underwent one-field non-mydriatic digital fundus photography, and direct ophthalmoscopy with dilation of their pupils, and FFA by ophthalmologists. The sensitivity and specificity of one-field non-mydriatic digital fundus photography and direct ophthalmoscopy were calculated respectively, compared with FFA.<p>RESULTS: The sensitivity and specificity of one-field non-mydriatic digital fundus photography for detection of any DR were 80.4% and 94.7%; The sensitivity and specificity of direct ophthalmoscopy for detection of any DR were 64.2% and 84.2%; After the standard for referable DR being lowered down to the moderate non-proliferative diabetic retinopathy(M-NPDR), the sensitivity and specificity of non-mydriatic digital fundus photography for detection were 88.9% and 98.4%, the sensitivity and specificity of direct ophthalmoscopy for detection were 71.5% and 96.7%.<p>CONCLUSION: One-field non-mydriatic digital fundus photography is an effective method for DR screening

A Note on Self-gravitating Radiation in AdS Spacetime

In this paper we investigate the equilibrium self-gravitating radiation in higher dimensional, plane symmetric anti-de Sitter space. We find that there exist essential differences from the spherically symmetric case: In each dimension ($d\geq 4$), there are maximal mass (density), maximal entropy (density) and maximal temperature configurations, they do not appear at the same central energy density; the oscillation behavior appearing in the spherically symmetric case, does not happen in this case; and the mass (density), as a function of the central energy density, increases first and reaches its maximum at a certain central energy density and then decreases monotonically in $4\le d \le 7$, while in $d \geq 8$, besides the maximum, the mass (density) of the equilibrium configuration has a minimum: the mass (density) first increases and reaches its maximum, then decreases to its minimum and then increases to its asymptotic value monotonically. The reason causing the difference is discussed.Comment: Revtex, 13 pages with 8 eps figures, to appear in PRD; v2: typos corrected and the version in PR

MiRFinder: an improved approach and software implementation for genome-wide fast microRNA precursor scans

Background: MicroRNAs (miRNAs) are recognized as one of the most important families of noncoding RNAs that serve as important sequence-specific post-transcriptional regulators of gene expression. Identification of miRNAs is an important requirement for understanding the mechanisms of post-transcriptional regulation. Hundreds of miRNAs have been identified by direct cloning and computational approaches in several species. However, there are still many miRNAs that remain to be identified due to lack of either sequence features or robust algorithms to efficiently identify them. Results: We have evaluated features valuable for pre-miRNA prediction, such as the local secondary structure differences of the stem region of miRNA and non-miRNA hairpins. We have also established correlations between different types of mutations and the secondary structures of pre-miRNAs. Utilizing these features and combining some improvements of the current premiRNA prediction methods, we implemented a computational learning method SVM (support vector machine) to build a high throughput and good performance computational pre-miRNA prediction tool called MiRFinder. The tool was designed for genome-wise, pair-wise sequences from two related species. The method built into the tool consisted of two major steps: 1) genome wide search for hairpin candidates and 2) exclusion of the non-robust structures based on analysis of 18 parameters by the SVM method. Results from applying the tool for chicken/human and D. melanogaster/D. pseudoobscura pair-wise genome alignments showed that the tool can be used for genome wide pre-miRNA predictions. Conclusion: The MiRFinder can be a good alternative to current miRNA discovery software. This tool is available at http://www.bioinformatics.org/mirfinder/

Experimental and numerical simulation studies of the squeezing dynamics of the UBVT system with a hole-plug device

In this paper, a method is proposed to secure an autonomous underwater blasting vibration test (UBVT) system with plugs to deep-water rock, and its specific configuration concept and plugging principle are illustrated. Using the principle of statics, a mathematical model is established for the squeezing force in the process of pressing the hole-plug device (HPD) into holes in rocks. The tension-compression test is conducted on the plugs in round granite holes to obtain the axial pressure-displacement curves of the pressing process with the HPD spring parameter K, friction coefficient μ between the HPD and the rock-wall, and the dynamic contact friction attributes between the metallic HPD and the rock-wall of hole in granite. The axial pressure with such parameters as K, μ, and the squeezing velocity v, among others, and the four steps of the pressing process are numerically simulated. The relations of the characteristic squeezing force with K, μ, and v, as well as the mechanisms of these parameters that influence HPD usage and the sensitivity coefficient, are revealed. The findings of the present study provide references for setting the HPD configuration parameters and for formulating plug-specific construction methods

Species Identification on A Small Sample Size of RNA Sequences by Combined Method of Noise Filtering with L 2 -norm

Abstract. This paper proposed a noise filter with L 2 -norm distance method to design a classification of RNA sequences for the species identification, included of the small sample size of the nucleic acid sequence. This method amended and expanded the study by Hu et al. in 2011 [1]. We verified this method with the biological sample &quot;slipper orchids&quot; and its hybrid for biological species identification test. The result is showed that after applied our method, we can distinguish the paternity of a hybrid among a set of samples of &quot;slipper orchids&quot;

Mechanistic understanding of \u3ci\u3eN\u3c/i\u3e-glycosylation in Ebola virus glycoprotein maturation and function

The Ebola virus (EBOV) trimeric envelope glycoprotein (GP) precursors are cleaved into the receptor-binding GP1 and the fusion-mediating GP2 subunits and incorporated into virions to initiate infection. GP1 and GP2 form heterodimers that have 15 or two N-glycosylation sites (NGSs), respectively. Here we investigated the mechanism of how N-glycosylation contributes to GP expression, maturation, and function. As reported before, we found that, although GP1 NGSs are not critical, the two GP2 NGSs, Asn563 and Asn618, are essential for GP function. Further analysis uncovered that Asn563 and Asn618 regulate GP processing, demannosylation, oligomerization, and conformation. Consequently, these two NGSs are required for GP incorporation into EBOV-like particles and HIV type 1 (HIV-1) pseudovirions and determine viral transduction efficiency. Using CRISPR/Cas9 technology, we knocked out the two classical endoplasmic reticulum chaperones calnexin (CNX) and/or calreticulin (CRT) and found that bothCNXand CRT increase GP expression. Nevertheless, NGSs are not required for the GP interaction with CNX or CRT. Together, we conclude that, although Asn563 and Asn618 are not required for EBOV GP expression, they synergistically regulate its maturation, which determines its functionality

Serum metabolomic alterations in Beagle dogs experimentally infected with Toxocara canis

BackgroundToxocara canis, a globally distributed roundworm, can cause debilitating disease in dogs and humans; however, little is known about the metabolomic response of the hosts to T. canis infection. There is an increasing need to understand the metabolic mechanisms underlying the pathogenesis of T. canis infection in dogs. Here, we examined the metabolomic changes in Beagle dogsʼ serum following T. canis infection using LC-MS/MS.ResultsThe metabolic profiles of Beagle dogsʼ serum were determined at 12 h, 24 h, 10 d and 36 d after oral infection with 300 infectious T. canis eggs by LC-MS/MS. We tested whether the T. canis-associated differentially abundant metabolites could distinguish the serum of infected dogs from controls, as measured by the area under the receiver operating characteristic (ROC) curve (AUC). The differentially expressed metabolites were further evaluated by principal components analysis and pathway enrichment analysis. A total of 5756 and 5299 ions were detected in ESI+ and ESI− mode, respectively. ROC curve analysis revealed nine and five metabolite markers, at 12 hpi and 24 hpi to 36 dpi, respectively, with potential diagnostic value for toxocariasis. The levels of taurocholate, estradiol, prostaglandins and leukotriene were significantly changed. Primary bile acid biosynthesis pathway, steroid hormone biosynthesis pathway and biosynthesis of unsaturated fatty acids pathway were significantly altered by T. canis infection.ConclusionsThese findings show that T. canis infection can induce several changes in the dog serum metabolome and that the metabolic signature associated with T. canis infection in dogs has potential for toxocariasis diagnosis

Deep Learning for Differentiating Benign From Malignant Parotid Lesions on MR Images

Purpose/Objectives(s)Salivary gland tumors are a rare, histologically heterogeneous group of tumors. The distinction between malignant and benign tumors of the parotid gland is clinically important. This study aims to develop and evaluate a deep-learning network for diagnosing parotid gland tumors via the deep learning of MR images.Materials/MethodsTwo hundred thirty-three patients with parotid gland tumors were enrolled in this study. Histology results were available for all tumors. All patients underwent MRI scans, including T1-weighted, CE-T1-weighted and T2-weighted imaging series. The parotid glands and tumors were segmented on all three MR image series by a radiologist with 10 years of clinical experience. A total of 3791 parotid gland region images were cropped from the MR images. A label (pleomorphic adenoma and Warthin tumor, malignant tumor or free of tumor), which was based on histology results, was assigned to each image. To train the deep-learning model, these data were randomly divided into a training dataset (90%, comprising 3035 MR images from 212 patients: 714 pleomorphic adenoma images, 558 Warthin tumor images, 861 malignant tumor images, and 902 images free of tumor) and a validation dataset (10%, comprising 275 images from 21 patients: 57 pleomorphic adenoma images, 36 Warthin tumor images, 93 malignant tumor images, and 89 images free of tumor). A modified ResNet model was developed to classify these images. The input images were resized to 224x224 pixels, including four channels (T1-weighted tumor images only, T2-weighted tumor images only, CE-T1-weighted tumor images only and parotid gland images). Random image flipping and contrast adjustment were used for data enhancement. The model was trained for 1200 epochs with a learning rate of 1e-6, and the Adam optimizer was implemented. It took approximately 2 hours to complete the whole training procedure. The whole program was developed with PyTorch (version 1.2).ResultsThe model accuracy with the training dataset was 92.94% (95% CI [0.91, 0.93]). The micro-AUC was 0.98. The experimental results showed that the accuracy of the final algorithm in the diagnosis and staging of parotid cancer was 82.18% (95% CI [0.77, 0.86]). The micro-AUC was 0.93.ConclusionThe proposed model may be used to assist clinicians in the diagnosis of parotid tumors. However, future larger-scale multicenter studies are required for full validation

MicroRNA Patterns Associated with Clinical Prognostic Parameters and CNS Relapse Prediction in Pediatric Acute Leukemia

BACKGROUND: Recent reports have indicated that microRNAs (miRNAs) play a critical role in malignancies, and regulations in the progress of adult leukemia. The role of miRNAs in pediatric leukemia still needs to be established. The purpose of this study was to investigate the aberrantly expressed miRNAs in pediatric acute leukemia and demonstrate miRNA patterns that are pediatric-specific and prognostic parameter-associated. METHODOLOGY/PRINCIPAL FINDINGS: A total of 111 pediatric bone marrow samples, including 99 patients and 12 normal donors, were enrolled in this study. Of those samples, 36 patients and 7 normal samples were used as a test cohort for the evaluation of miRNA profiling; 63 pediatric patients and 5 normal donors were used as a validation cohort to confirm the miRNA differential expression. Pediatric ALL- and AML-specific microRNA expression patterns were identified in this study. The most highly expressed miRNAs in pediatric ALL were miR-34a, miR-128a, miR-128b, and miR-146a, while the highly expressed miRNAs in pediatric AML were miR-100, miR-125b, miR-335, miR-146a, and miR-99a, which are significantly different from those reported for adult CLL and AML. miR-125b and miR-126 may serve as favorable prognosticators for M3 and M2 patients, respectively. Importantly, we identified a "miRNA cascade" associated with central nervous system (CNS) relapse in ALL. Additionally, miRNA patterns associated with prednisone response, specific risk group, and relapse of ALL were also identified. CONCLUSIONS/SIGNIFICANCE: There are existing pediatric-associated and prognostic parameter-associated miRNAs that are independent of cell lineage and could provide therapeutic direction for individual risk-adapted therapy for pediatric leukemia patients