miRPlant : an integrated tool for identification of plant miRNA from RNA sequencing data

Background Small RNA sequencing is commonly used to identify novel miRNAs and to determine their expression levels in plants. There are several miRNA identification tools for animals such as miRDeep, miRDeep2 and miRDeep*. miRDeep-P was developed to identify plant miRNA using miRDeep’s probabilistic model of miRNA biogenesis, but it depends on several third party tools and lacks a user-friendly interface. The objective of our miRPlant program is to predict novel plant miRNA, while providing a user-friendly interface with improved accuracy of prediction. Result We have developed a user-friendly plant miRNA prediction tool called miRPlant. We show using 16 plant miRNA datasets from four different plant species that miRPlant has at least a 10% improvement in accuracy compared to miRDeep-P, which is the most popular plant miRNA prediction tool. Furthermore, miRPlant uses a Graphical User Interface for data input and output, and identified miRNA are shown with all RNAseq reads in a hairpin diagram. Conclusions We have developed miRPlant which extends miRDeep* to various plant species by adopting suitable strategies to identify hairpin excision regions and hairpin structure filtering for plants. miRPlant does not require any third party tools such as mapping or RNA secondary structure prediction tools. miRPlant is also the first plant miRNA prediction tool that dynamically plots miRNA hairpin structure with small reads for identified novel miRNAs. This feature will enable biologists to visualize novel pre-miRNA structure and the location of small RNA reads relative to the hairpin. Moreover, miRPlant can be easily used by biologists with limited bioinformatics skills

Evaluation of wheat-pigeon pea flour blends for noodle production in Nigeria

Inclusion of legume flours/starches in food formulations such as pastas, noodles, among others, assists in enhancing structure, texture and nutritional quality of the final products. Pigeon pea as a legume is still underutilized in Nigeria and most places in Africa. In this study, the effect of addition of pigeon pea (Cajanus cajan L.) flour (PPF) in various proportions into wheat flour (WF) for noodle production was evaluated with respect to selected chemical, cooking and sensory properties of the formulated products. Pigeon pea grains (1 kg) were cleaned and boiled in 3 L of tap water for 15 min. Boiled seeds were de-hulled and sun-dried for 3 days (average ambient temperature of 33.0 ± 2oC), milled and sieved (mesh size: 300 μm). Flour blends (WF: PPF) for noodle production were 90:10, 80:20, 70:30, 60:40 and 50:50; and 100% WF was used as control. Selected functional properties (Water absorption, swelling, oil absorption capacities and bulk density) of the flours were determined, while the noodles were subjected to chemical, cooking and sensory analyses using standard laboratory methods. Results indicated that more inclusion of the pigeon pea flour (PPF) gave rise to increasing water and oil absorption capacities. The 50:50 noodle had significantly (p<0.05) higher crude protein (15.68%); Magnesium (109.23 mg/100g) and iron (6.88 mg/100g) than the other noodle samples, while all the noodles had low fat contents. This could be an advantage to prevention of rancidity in the food products during storage and availability of noodles suitable for obese and diabetes Miletus Type 2 individuals. The 90:10 noodles had lower values of cooking time and yield but its cooking loss was higher than others. This underscores the benefit of PPF on improvement of texture of the noodles as the amount increased in the mixture. The 90:10 noodle blend was also more acceptable in all the sensory attributes than others. Therefore, utilization of PPF in composite noodle production in Nigeria and other developing countries can be recommended as this could support the effort towards food and nutrition security of households and communities.&nbsp

A role for CaV1 and calcineurin signalling to depolarization-induced changes in neuronal DNA methylation

Copyright © 2015 The Authors Published by Elsevier Inc.Direct manipulations of neuronal activity have been shown to induce changes in DNA methylation (DNAm), although little is known about the cellular signaling pathways involved. Using reduced representation bisulfite sequencing, we identify DNAm changes associated with moderate chronic depolarization in dissociated rat hippocampal cultures. Consistent with previous findings, these changes occurred primarily in the vicinity of loci implicated in neuronal function, being enriched in intergenic regions and underrepresented in CpG-rich promoter regulatory regions. We subsequently used 2 pharmacological interventions (nifedipine and FK-506) to test whether the identified changes depended on 2 interrelated signaling pathways known to mediate multiple forms of neuronal plasticity. Both pharmacological manipulations had notable effects on the extent and magnitude of depolarization-induced DNAm changes indicating that a high proportion of activity-induced changes are likely to be mediated by calcium entry through L-type CaV1 channels and/or downstream signaling via the calcium-dependent phosphatase calcineurin.Wellcome TrustMRC 4-year PhD studentshipKCL CDN-SGDP collaborative seed fundin

Exceptional Evolutionary Expansion of Prefrontal Cortex in Great Apes and Humans

One of the enduring questions that has driven neuroscientific enquiry in the last century has been the nature of differences in the prefrontal cortex of humans versus other animals [1]. The prefrontal cortex has drawn particular interest due to its role in a range of evolutionarily specialized cognitive capacities such as language [2], imagination [3], and complex decision making [4]. Both cytoarchitectonic [5] and comparative neuroimaging [6] studies have converged on the conclusion that the proportion of prefrontal cortex in the human brain is greatly increased relative to that of other primates. However, considering the tremendous overall expansion of the neocortex in human evolution, it has proven difficult to ascertain whether this extent of prefrontal enlargement follows general allometric growth patterns, or whether it is exceptional [1]. Species’ adherence to a common allometric relationship suggests conservation through phenotypic integration, while species’ deviations point toward the occurrence of shifts in genetic and/or developmental mechanisms. Here we investigate prefrontal cortex scaling across anthropoid primates and find that great ape and human prefrontal cortex expansion are non-allometrically derived features of cortical organization. This result aligns with evidence for a developmental heterochronic shift in human prefrontal growth [7, 8], suggesting an association between neurodevelopmental changes and cortical organization on a macroevolutionary scale. The evolutionary origin of non-allometric prefrontal enlargement is estimated to lie at the root of great apes (∼19–15 mya), indicating that selection for changes in executive cognitive functions characterized both great ape and human cortical organization

Feature extraction for the analysis of colon status from the endoscopic images

BACKGROUND: Extracting features from the colonoscopic images is essential for getting the features, which characterizes the properties of the colon. The features are employed in the computer-assisted diagnosis of colonoscopic images to assist the physician in detecting the colon status. METHODS: Endoscopic images contain rich texture and color information. Novel schemes are developed to extract new texture features from the texture spectra in the chromatic and achromatic domains, and color features for a selected region of interest from each color component histogram of the colonoscopic images. These features are reduced in size using Principal Component Analysis (PCA) and are evaluated using Backpropagation Neural Network (BPNN). RESULTS: Features extracted from endoscopic images were tested to classify the colon status as either normal or abnormal. The classification results obtained show the features' capability for classifying the colon's status. The average classification accuracy, which is using hybrid of the texture and color features with PCA (τ = 1%), is 97.72%. It is higher than the average classification accuracy using only texture (96.96%, τ = 1%) or color (90.52%, τ = 1%) features. CONCLUSION: In conclusion, novel methods for extracting new texture- and color-based features from the colonoscopic images to classify the colon status have been proposed. A new approach using PCA in conjunction with BPNN for evaluating the features has also been proposed. The preliminary test results support the feasibility of the proposed method

Evaluation of qPCR-Based Assays for Leprosy Diagnosis Directly in Clinical Specimens

The increased reliability and efficiency of the quantitative polymerase chain reaction (qPCR) makes it a promising tool for performing large-scale screening for infectious disease among high-risk individuals. To date, no study has evaluated the specificity and sensitivity of different qPCR assays for leprosy diagnosis using a range of clinical samples that could bias molecular results such as difficult-to-diagnose cases. In this study, qPCR assays amplifying different M. leprae gene targets, sodA, 16S rRNA, RLEP and Ag 85B were compared for leprosy differential diagnosis. qPCR assays were performed on frozen skin biopsy samples from a total of 62 patients: 21 untreated multibacillary (MB), 26 untreated paucibacillary (PB) leprosy patients, as well as 10 patients suffering from other dermatological diseases and 5 healthy donors. To develop standardized protocols and to overcome the bias resulted from using chromosome count cutoffs arbitrarily defined for different assays, decision tree classifiers were used to estimate optimum cutoffs and to evaluate the assays. As a result, we found a decreasing sensitivity for Ag 85B (66.1%), 16S rRNA (62.9%), and sodA (59.7%) optimized assay classifiers, but with similar maximum specificity for leprosy diagnosis. Conversely, the RLEP assay showed to be the most sensitive (87.1%). Moreover, RLEP assay was positive for 3 samples of patients originally not diagnosed as having leprosy, but these patients developed leprosy 5–10 years after the collection of the biopsy. In addition, 4 other samples of patients clinically classified as non-leprosy presented detectable chromosome counts in their samples by the RLEP assay suggesting that those patients either had leprosy that was misdiagnosed or a subclinical state of leprosy. Overall, these results are encouraging and suggest that RLEP assay could be useful as a sensitive diagnostic test to detect M. leprae infection before major clinical manifestations

TRASER - Total Reflection Amplification of Spontaneous Emission of Radiation

Background and Objective: Light and lasers in medical therapy have made dramatic strides since their invention five decades ago. However, the manufacture of lasers can be complex and expensive which often makes treatments limited and costly. Further, no single laser will provide the correct parameters to treat all things. Hence, laser specialists often need multiple devices to practice their specialty. A new concept is described herein that has the potential to replace many lasers and light sources with a single ‘tunable ’ device. Study Design/Material and Methods: This device amplifies spontaneous emission of radiation by capturing and retaining photons through total internal reflection, hence the acronym Total Reflection Amplification of Spontaneous Emission of Radiation, or TRASER. Results: Specific peaks of light can be produced in a reproducible manner with high peak powers of variable pulse durations, a large spot size, and high repetition rate. Conclusion: Considering the characteristics and parameters of Traser technology, it is possible that this one device woul

A microsatellite repeat in PCA3 long non-coding RNA is associated with prostate cancer risk and aggressiveness.

Short tandem repeats (STRs) are repetitive sequences of a polymorphic stretch of two to six nucleotides. We hypothesized that STRs are associated with prostate cancer development and/or progression. We undertook RNA sequencing analysis of prostate tumors and adjacent non-malignant cells to identify polymorphic STRs that are readily expressed in these cells. Most of the expressed STRs in the clinical samples mapped to intronic and intergenic DNA. Our analysis indicated that three of these STRs (TAAA-ACTG2, TTTTG-TRIB1, and TG-PCA3) are polymorphic and differentially expressed in prostate tumors compared to adjacent non-malignant cells. TG-PCA3 STR expression was repressed by the anti-androgen drug enzalutamide in prostate cancer cells. Genetic analysis of prostate cancer patients and healthy controls (N > 2,000) showed a significant association of the most common 11 repeat allele of TG-PCA3 STR with prostate cancer risk (OR = 1.49; 95% CI 1.11-1.99; P = 0.008). A significant association was also observed with aggressive disease (OR = 2.00; 95% CI 1.06-3.76; P = 0.031) and high mortality rates (HR = 3.0; 95% CI 1.03-8.77; P = 0.045). We propose that TG-PCA3 STR has both diagnostic and prognostic potential for prostate cancer. We provided a proof of concept to be applied to other RNA sequencing datasets to identify disease-associated STRs for future clinical exploratory studies