Molecular characterization of Cymbidium kanran cultivars based on extended random amplified polymorphic DNA (ERAPD) markers

Fifty-four Cymbidium kanran cultivars from China, Japan and Korea were examined and analyzed by using the successive screening of 3'-end extended random primer amplified polymorphic DNA (ERAPD) markers to determine their molecular diversity and relationships. In ERAPD analyses, the strandspecific DNA sequence of direct oligonucleotide extension sequencing primers was independently read from each of the RAPD fragments without recourse to cloning or strand separation. Eight primers, identified from 80 original RAPD primers, produced strong repetitive polymorphic bands that were used in 3'-end-extended random primer amplified DNA marker analysis. The products of primers ACTGAACGCCCG + ACTGAACGCCGG and ACTGAACGCCC + ACTGAACGCC, linked to the same locus (2.5 - kb), were developed from the original ACTGAACGC RAPD primer; the products of this marker were more stable and specific than the original RAPD marker. Unweighted pair-group mean analysis (UPGMA) grouped them into two clusters based upon geographical traits. We demonstrated that the ERAPD technique is a powerful tool for cultivar identification and establishment of genetic relationships of cultivars in Cymbidium kanran.Key words: Cymbidium kanran; genetic relationship; Extended random amplified polymorphic DNA (ERAPD

Neural Network-Based Retinal Nerve Fiber Layer Profile Compensation for Glaucoma Diagnosis in Myopia: Model Development and Validation

BACKGROUND: Due to the axial elongation-associated changes in the optic nerve and retina in high myopia, traditional methods like optic disc evaluation and visual field are not able to correctly differentiate glaucomatous lesions. It has been clinically challenging to detect glaucoma in highly myopic eyes. OBJECTIVE: This study aimed to develop a neural network to adjust for the dependence of the peripapillary retinal nerve fiber layer (RNFL) thickness (RNFLT) profile on age, gender, and ocular biometric parameters and to evaluate the network's performance for glaucoma diagnosis, especially in high myopia. METHODS: RNFLT with 768 points on the circumferential 3.4-mm scan was measured using spectral-domain optical coherence tomography. A fully connected network and a radial basis function network were trained for vertical (scaling) and horizontal (shift) transformation of the RNFLT profile with adjustment for age, axial length (AL), disc-fovea angle, and distance in a test group of 2223 nonglaucomatous eyes. The performance of RNFLT compensation was evaluated in an independent group of 254 glaucoma patients and 254 nonglaucomatous participants. RESULTS: By applying the RNFL compensation algorithm, the area under the receiver operating characteristic curve for detecting glaucoma increased from 0.70 to 0.84, from 0.75 to 0.89, from 0.77 to 0.89, and from 0.78 to 0.87 for eyes in the highest 10% percentile subgroup of the AL distribution (mean 26.0, SD 0.9 mm), highest 20% percentile subgroup of the AL distribution (mean 25.3, SD 1.0 mm), highest 30% percentile subgroup of the AL distribution (mean 24.9, SD 1.0 mm), and any AL (mean 23.5, SD 1.2 mm), respectively, in comparison with unadjusted RNFLT. The difference between uncompensated and compensated RNFLT values increased with longer axial length, with enlargement of 19.8%, 18.9%, 16.2%, and 11.3% in the highest 10% percentile subgroup, highest 20% percentile subgroup, highest 30% percentile subgroup, and all eyes, respectively. CONCLUSIONS: In a population-based study sample, an algorithm-based adjustment for age, gender, and ocular biometric parameters improved the diagnostic precision of the RNFLT profile for glaucoma detection particularly in myopic and highly myopic eyes

Rational design of the inlet configuration of flow systems for enhanced mixing

Funder: Chinese Government Scholarship; doi: http://dx.doi.org/10.13039/501100010890Funder: Cambridge Overseas Trust; doi: http://dx.doi.org/10.13039/501100003341AbstractHigh mass transfer rate is a key advantage of microreactors however, under their characteristic laminar flow, it is dominated by slow diffusion rather than fast convection. In this paper, we demonstrate how the configuration of the inlet, i.e. mixers, can promote different flow patterns to greatly enhance mixing efficiency downstream. A systematic evaluation and comparison of different widely adopted mixers as well as advanced designs is presented using a combination of computational fluid dynamics (CFD) and backward particle tracking to accurately calculate diffusion, in the absence of numerical diffusion (false diffusion). In the method, the convection contributed concentration profile is obtained by tracking sampling points from a cross-sectional plane to the inlet point, and diffusion is estimated subsequently. In conventional T- and Y-mixers, the shape of channel, circular or square, is key with only the latter promoting engulfment flow. In cyclone mixers, the resulting average inlet velocity, independent of Reynolds number or geometry, is the dominating design parameter to predict mixing efficiency. This work will serve as a guideline for the design of efficient flow systems with predicted mixing as a way of maximising selectivity and product quality.</jats:p

The Effect of Class Noise on Continuous Test Case Selection: A Controlled Experiment on Industrial Data

Continuous integration and testing produce a large amount of data about defects in code revisions, which can be utilized for training a predictive learner to effectively select a subset of test suites. One challenge in using predictive learners lies in the noise that comes in the training data, which often leads to a decrease in classification performances. This study examines the impact of one type of noise, called class noise, on a learner’s ability for selecting test cases. Understanding the impact of class noise on the performance of a learner for test case selection would assist testers decide on the appropriateness of different noise handling strategies. For this purpose, we design and implement a controlled experiment using an industrial data-set to measure the impact of class noise at six different levels on the predictive performance of a learner. We measure the learning performance using the Precision, Recall, F-score, and Mathew Correlation Coefficient (MCC) metrics. The results show a statistically significant relationship between class noise and the learners performance for test case selection. Particularly, a significant difference between the three performance measures (Precision, F-score, and MCC)under all the six noise levels and at 0% level was found, whereas a similar relationship between recall and class noise was found at a level above30%. We conclude that higher class noise ratios lead to missing out more tests in the predicted subset of test suite and increases the rate of false alarms when the class noise ratio exceeds 30

Comparison of Sentiment Analysis and User Ratings in Venue Recommendation

Venue recommendation aims to provide users with venues to visit, taking into account historical visits to venues. Many venue recommendation approaches make use of the provided users’ ratings to elicit the users’ preferences on the venues when making recommendations. In fact, many also consider the users’ ratings as the ground truth for assessing their recommendation performance. However, users are often reported to exhibit inconsistent rating behaviour, leading to less accurate preferences information being collected for the recommendation task. To alleviate this problem, we consider instead the use of the sentiment information collected from comments posted by the users on the venues as a surrogate to the users’ ratings. We experiment with various sentiment analysis classifiers, including the recent neural networks-based sentiment analysers, to examine the effectiveness of replacing users’ ratings with sentiment information. We integrate the sentiment information into the widely used matrix factorization and GeoSoCa multi feature-based venue recommendation models, thereby replacing the users’ ratings with the obtained sentiment scores. Our results, using three Yelp Challenge-based datasets, show that it is indeed possible to effectively replace users’ ratings with sentiment scores when state-of-the-art sentiment classifiers are used. Our findings show that the sentiment scores can provide accurate user preferences information, thereby increasing the prediction accuracy. In addition, our results suggest that a simple binary rating with ‘like’ and ‘dislike’ is a sufficient substitute of the current used multi-rating scales for venue recommendation in location-based social networks

Alteration of Sequence Specificity of the Type IIS Restriction Endonuclease BtsI

The Type IIS restriction endonuclease BtsI recognizes and digests at GCAGTG(2/0). It comprises two subunits: BtsIA and BtsIB. The BtsIB subunit contains the recognition domain, one catalytic domain for bottom strand nicking and part of the catalytic domain for the top strand nicking. BtsIA has the rest of the catalytic domain that is responsible for the DNA top strand nicking. BtsIA alone has no activity unless it mixes with BtsIB to reconstitute the BtsI activity. During characterization of the enzyme, we identified a BtsIB mutant R119A found to have a different digestion pattern from the wild type BtsI. After characterization, we found that BtsIB(R119A) is a novel restriction enzyme with a previously unreported recognition sequence CAGTG(2/0), which is named as BtsI-1. Compared with wild type BtsI, BtsI-1 showed different relative activities in NEB restriction enzyme reaction buffers NEB1, NEB2, NEB3 and NEB4 and less star activity. Similar to the wild type BtsIB subunit, the BtsI-1 B subunit alone can act as a bottom nicking enzyme recognizing CAGTG(-/0). This is the first successful case of a specificity change among this restriction endonuclease type

Lipidomics Reveals Early Metabolic Changes in Subjects with Schizophrenia: Effects of Atypical Antipsychotics

There is a critical need for mapping early metabolic changes in schizophrenia to capture failures in regulation of biochemical pathways and networks. This information could provide valuable insights about disease mechanisms, trajectory of disease progression, and diagnostic biomarkers. We used a lipidomics platform to measure individual lipid species in 20 drug-naïve patients with a first episode of schizophrenia (FE group), 20 patients with chronic schizophrenia that had not adhered to prescribed medications (RE group), and 29 race-matched control subjects without schizophrenia. Lipid metabolic profiles were evaluated and compared between study groups and within groups before and after treatment with atypical antipsychotics, risperidone and aripiprazole. Finally, we mapped lipid profiles to n3 and n6 fatty acid synthesis pathways to elucidate which enzymes might be affected by disease and treatment. Compared to controls, the FE group showed significant down-regulation of several n3 polyunsaturated fatty acids (PUFAs), including 20:5n3, 22:5n3, and 22:6n3 within the phosphatidylcholine and phosphatidylethanolamine lipid classes. Differences between FE and controls were only observed in the n3 class PUFAs; no differences where noted in n6 class PUFAs. The RE group was not significantly different from controls, although some compositional differences within PUFAs were noted. Drug treatment was able to correct the aberrant PUFA levels noted in FE patients, but changes in re patients were not corrective. Treatment caused increases in both n3 and n6 class lipids. These results supported the hypothesis that phospholipid n3 fatty acid deficits are present early in the course of schizophrenia and tend not to persist throughout its course. These changes in lipid metabolism could indicate a metabolic vulnerability in patients with schizophrenia that occurs early in development of the disease. © 2013 McEvoy et al

Platelet-derived growth factor-B gene delivery sustains gingival fibroblast signal transduction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65871/1/j.1600-0765.2008.01089.x.pd

Early Gnathostome Phylogeny Revisited: Multiple Method Consensus

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.A series of recent studies recovered consistent phylogenetic scenarios of jawed vertebrates, such as the paraphyly of placoderms with respect to crown gnathostomes, and antiarchs as the sister group of all other jawed vertebrates. However, some of the hylogenetic relationships within the group have remained controversial, such as the positions of Entelognathus, ptyctodontids, and the Guiyu-lineage that comprises Guiyu, Psarolepis and Achoania. The revision of the dataset in a recent study reveals a modified phylogenetic hypothesis, which shows that some of these phylogenetic conflicts were sourced from a few inadvertent miscodings. The interrelationships of early gnathostomes are addressed based on a combined new dataset with 103 taxa and 335 characters, which is the most comprehensive morphological dataset constructed to date. This dataset is investigated in a phylogenetic context using maximum parsimony (MP), Bayesian inference (BI) and maximum likelihood (ML) approaches in an attempt to explore the consensus and incongruence between the hypotheses of early gnathostome interrelationships recovered from different methods. Our findings consistently corroborate the paraphyly of placoderms, all `acanthodians' as a paraphyletic stem group of chondrichthyans, Entelognathus as a stem gnathostome, and the Guiyu-lineage as stem sarcopterygians. The incongruence using different methods is less significant than the consensus, and mainly relates to the positions of the placoderm Wuttagoonaspis, the stem chondrichthyan Ramirosuarezia, and the stem osteichthyan LophosteusÐthe taxa that are either poorly known or highly specialized in character complement. Given that the different performances of each phylogenetic approach, our study provides an empirical case that the multiple phylogenetic analyses of morphological data are mutually complementary rather than redundant

What is normal nasal airflow? A computational study of 22 healthy adults.

BACKGROUND: Nasal airflow is essential for the functioning of the human nose. Given individual variation in nasal anatomy, there is yet no consensus what constitutes normal nasal airflow patterns. We attempt to obtain such information that is essential to differentiate disease-related conditions. METHODS: Computational fluid dynamics (CFD) simulated nasal airflow in 22 healthy subjects during resting breathing. Streamline patterns, airflow distributions, velocity profiles, pressure, wall stress, turbulence, and vortical flow characteristics under quasi-steady state were analyzed. Patency ratings, acoustically measured minimum cross-sectional area (MCA), and rhinomanometric nasal resistance (NR) were examined for potential correlations with morphological and airflow-related variables. RESULTS: Common features across subjects included: \u3e50% total pressure drop reached near the inferior turbinate head; wall shear stress, NR, turbulence energy, and vorticity were lower in the turbinate than in the nasal valve region. However, location of the major flow path and coronal velocity distributions varied greatly across individuals. Surprisingly, on average, more flow passed through the middle than the inferior meatus and correlated with better patency ratings (r = -0.65, p \u3c 0.01). This middle flow percentage combined with peak postvestibule nasal heat loss and MCA accounted for \u3e70% of the variance in subjective patency ratings and predicted patency categories with 86% success. Nasal index correlated with forming of the anterior dorsal vortex. Expected for resting breathing, the functional impact for local and total turbulence, vorticity, and helicity was limited. As validation, rhinomanometric NR significantly correlated with CFD simulations (r = 0.53, p \u3c 0.01). CONCLUSION: Significant variations of nasal airflow found among healthy subjects; Key features may have clinically relevant applications