Development of species-specific primers for rapid identification by PCR of the ecologically important pathogen Fusarium keratoplasticum from isolated and environmental samples

The genus Fusarium contains many fungal species known to be pathogenic to animals and plants alike. One species complex within this genus, the Fusarium solani species complex (FSSC), is of particular concern due to its high numbers of pathogenic members. FSSC members are known to contribute significantly to plant, human and other animal fungal disease. One member of the FSSC, Fusarium keratoplasticum, is of particular ecological concern and has been implicated in low hatching success of endangered sea turtle eggs, as well as contribute to human and other animal Fusarium pathogenesis. Species-specific primers for molecular identification of F. keratoplasticum currently do not exist to our knowledge, making rapid identification, tracking and quantitation of this pathogenic fungus difficult. The objective of this study was to develop primers specific to F. keratoplasticum that could be applied to DNA from isolated cultures as well as total (mixed) DNA from environmental samples. RPB2 sequence from 109 Fusarium isolates was aligned and analysed to determine nucleotide polymorphisms specific to F. keratoplasticum useful for primer design. A set of primers were generated and found to be effective for identification of F. keratoplasticum from total DNA extracted from sand surrounding sea turtle nesting sites.     

The Orthocladiinae (Diptera: Chironomidae) of India genus Cricotopus van der Wulp

This is the eleventh part of our series of studies on Orthocladiinae from India. Two new species of the genus Cricotopus, C. albipes and C. tenuisetosus are described in this paper.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.     

Rapid atraumatic sex identification of developmental day 14–16 mice

Abstract

Embryonic mice have been used widely to study organ development. Days 14–16 are critical for sex organ development and differentiation in mice. Current methods for sex identification are limited. Even the simplest polymerase chain reaction method may injure the embryo. We determined that morphologic analysis of embryonic mammary anlagen could be used for rapid atraumatic sex identification of day 14–16 mice. The accuracy of our method was verified by molecular and anatomical approaches.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

An Arabidopsis lipid map reveals differences between tissues and dynamic changes throughout development

Mass spectrometry is the predominant analytical tool used in the field of plant lipidomics. However, there are many challenges associated with the mass spectrometric detection and identification of lipids because of the highly complex nature of plant lipids. Studies into lipid biosynthetic pathways, gene functions in lipid metabolism, lipid changes during plant growth and development, and the holistic examination of the role of plant lipids in environmental stress responses are often hindered. Here, we leveraged a robust pipeline that we previously established to extract and analyze lipid profiles of different tissues and developmental stages from the model plant Arabidopsis thaliana. We analyzed seven tissues at several different developmental stages and identified more than 200 lipids from each tissue analyzed. The data were used to create a web-accessible in silico lipid map that has been integrated into an electronic Fluorescent Pictograph (eFP) browser. This in silico library of Arabidopsis lipids allows the visualization and exploration of the distribution and changes of lipid levels across selected developmental stages. Furthermore, it provides information on the characteristic fragments of lipids and adducts observed in the mass spectrometer and their retention times, which can be used for lipid identification. The Arabidopsis tissue lipid map can be accessed at http://bar.utoronto.ca/efp_arabidopsis_lipid/cgi-bin/efpWeb.cgi .     

Novel methoxy-carotenoids from the burgundy-colored plumage of the Pompadour Cotinga Xipholena punicea

Recent advances in the fields of chromatography, mass spectrometry, and chemical analysis have greatly improved the efficiency with which carotenoids can be extracted and analyzed from avian plumage. Prior to these technological developments, Brush (1968) [1] concluded that the burgundy-colored plumage of the male pompadour Cotinga Xipholena punicea is produced by a combination of blue structural color and red carotenoids, including astaxanthin, canthaxanthin, isozeaxanthin, and a fourth unidentified, polar carotenoid. However, X. punicea does not in fact exhibit any structural coloration. This work aims to elucidate the carotenoid pigments of the burgundy color of X. punicea plumage using advanced analytical methodology. Feathers were collected from two burgundy male specimens and from a third aberrant orange-colored specimen. Pigments were extracted using a previously published technique (McGraw et al. (2005) [2]), separated by high-performance liquid chromatography (HPLC), and analyzed by UV/Vis absorption spectroscopy, chemical analysis, mass spectrometry, nuclear magnetic resonance (NMR), and comparison with direct synthetic products. Our investigation revealed the presence of eight ketocarotenoids, including astaxanthin and canthaxanthin as reported previously by Brush (1968) [1]. Six of the ketocarotenoids contained methoxyl groups, which is rare for naturally-occurring carotenoids and a novel finding in birds. Interestingly, the carotenoid composition was the same in both the burgundy and orange feathers, indicating that feather coloration in X. punicea is determined not only by the presence of carotenoids, but also by interactions between the bound carotenoid pigments and their protein environment in the barb rami and barbules. This paper presents the first evidence of metabolically-derived methoxy-carotenoids in birds.     

县域城镇空间形态与居住建筑能耗关联性的连续尺度研究——以浙江长兴、福建连江为例

居住建筑能耗受建筑周边空间形态的直接影响，确定空间形态低碳效应及其最佳尺度将有助于实现县域城镇低碳转型。以浙江省长兴县、福建省连江县为例，共计选取49个具有代表性的居住建筑样本，采用GIS分析与数理统计相结合的方式，在居住建筑1800m半径范围内，以200m为间隔建立缓冲区，开展全年、最冷月份能耗期及最热月份能耗期建筑能耗与周边空间形态关联性的连续尺度研究。结果表明：(1)道路密度、开发密度、容积率均与建筑能耗呈正相关，但各指标对应的能耗时期、尺度范围有较大差异。(2)水面率、土地利用混合度是与建筑能耗相关的共性指标，但在不同地区的正负效应及尺度范围不同；(3)影响浙闽地区县域城镇最热月份能耗期能耗的关键形态因子为1000m-道路密度、800m-水面率、1600m-开放空间率；影响连江最冷月份能耗期能耗的关键形态因子为800m-水面率。(4)就控碳单元设置而言，长兴县可重点关注1000—1200m半径范围，连江县可重点关注800—1000m、1400m半径范围。(5)浙闽地区县域城镇特性指标为开放空间率，与最热月份能耗期建筑能呈负相关；长兴县特性指标为容积率、水岸密度，分别与全年、最冷...