Genomic Promoter Analysis Predicts Functional Transcription Factor Binding

Background. The computational identification of functional transcription factor binding sites (TFBSs) remains a major challenge of computational biology. Results. We have analyzed the conserved promoter sequences for the complete set of human RefSeq genes using our conserved transcription factor binding site (CONFAC) software. CONFAC identified 16296 human-mouse ortholog gene pairs, and of those pairs, 9107 genes contained conserved TFBS in the 3 kb proximal promoter and first intron. To attempt to predict in vivo occupancy of transcription factor binding sites, we developed a novel marginal effect isolator algorithm that builds upon Bayesian methods for multigroup TFBS filtering and predicted the in vivo occupancy of two transcription factors with an overall accuracy of 84%. Conclusion. Our analyses show that integration of chromatin immunoprecipitation data with conserved TFBS analysis can be used to generate accurate predictions of functional TFBS. They also show that TFBS cooccurrence can be used to predict transcription factor binding to promoters in vivo

Meteor radar measurements of MLT winds near the equatorial electro jet region over Thumba (8.5° N, 77° E): comparison with TIDI observations

The All-Sky interferometric meteor (SKYiMET) radar (MR) derived winds in the vicinity of the equatorial electrojet (EEJ) are discussed. As Thumba (8.5° N, 77° E; dip lat. 0.5° N) is under the EEJ belt, there has been some debate on the reliability of the meteor radar derived winds near the EEJ height region. In this regard, the composite diurnal variations of zonal wind profiles in the mesosphere-lower thermosphere (MLT) region derived from TIMED Doppler Interferometer (TIDI) and ground based meteor radar at Thumba are compared. In this study, emphasis is given to verify the meteor radar observations at 98 km height region, especially during the EEJ peaking time (11:00 to 14:00 LT). The composite diurnal cycles of zonal winds over Thumba are constructed during four seasons of the year 2006 using TIDI and meteor radar observations, which showed good agreement especially during the peak EEJ hours, thus assuring the reliability of meteor radar measurements of neutral winds close to the EEJ height region. It is evident from the present study that on seasonal scales, the radar measurements are not biased by the EEJ. The day-time variations of HF radar measured E-region drifts at the EEJ region are also compared with MR measurements to show there are large differences between ionospheric drifts and MR measurements. The significance of the present study lies in validating the meteor radar technique over Thumba located at magnetic equator by comparing with other than the radio technique for the first time

Extending Rapid Image Classification with the Picture Pile Platform for Citizen Science

Picture Pile is a flexible web-based and mobile application for ingesting imagery from satellites, orthophotos, unmanned aerial vehicles and/or geotagged photographs for rapid classification by volunteers. Since 2014, there have been 16 different crowdsourcing campaigns run with Picture Pile, which has involved more than 4000 volunteers who have classified around 11.5 million images. Picture Pile is based on a simple mechanic in which users view an image and then answer a question, e.g., do you see oil palm, with a simple yes, no or maybe answer by swiping the image to the right, left or downwards, respectively. More recently, Picture Pile has been modified to classify data into categories (e.g., crop types) as well as continuous variables (e.g., degree of wealth) so that additional types of data can be collected. The Picture Pile campaigns have covered a range of domains from classification of deforestation to building damage to different types of land cover, with crop type identification as the latest ongoing campaign through the Earth Challenge network. Hence, Picture Pile can be used for many different types of applications that need image classifications, e.g., as reference data for training remote sensing algorithms, validation of remotely sensed products or training data of computer vision algorithms. Picture Pile also has potential for monitoring some of the indicators of the United Nations Sustainable Development Goals (SDGs). The Picture Pile Platform is the next generation of the Picture Pile application, which will allow any user to create their own ‘piles’ of imagery and run their own campaigns using the system. In addition to providing an overview of Picture Pile, including some examples of relevance to SDG monitoring, this presentation will provide an overview of the current status of the Picture Pile Platform along with the data sharing model, the machine learning component and the vision for how the platform will function operationally to aid environmental monitoring

Economic evaluation of sediments as a source of plant nutrients

Sediment deposition as a result of soil erosion is a significant problem in the village water tanks. In order to increase the rainwater storage capacity, removal of sediments from water tanks was taken up under the State Government Water Conservation Programme in Medak District, Andhra Pradesh, India. The feasibility of desilting operations and returning such huge amounts of sediments to agricultural fields was assessed by determining the sediment quality in terms of nutrients, organic carbon (C), biological properties and their economic value as a source of plant nutrients. Analysis of sediment samples showed an average of 720 mg nitrogen (N), 320 mg phosphorus (P), 310 mg potassium (K) and 9.1 g of organic C per kg of sediment. Higher microbial populations were found in the sediments that recorded high nutrient and organic C contents. The microbial biomass C in the sediments recorded an average value of 308 mg kg–1 sediment and the average proportion of microbial biomass C to organic C was 3.8%. Application of 48,777 t of sediment from 21 tanks returned 34 t of N, 15 t of P, 15 t of K and 433 t of organic C to agricultural lands. The benefit– cost ratio of desilting operation and application of sediments to agricultural lands in 21 tanks varied from 0.65 to 5.38, with an average ratio of 1.88. Further, extrapolation of the results for the N, P, K and organic C nutrient values to 78 water tanks in Medak district indicated that 177 t of N, 82 t of P, 76 t of K and 2016 t of organic C could be returned to the agricultural fields. The study suggests economic feasibility for the application of tank sediments to the agricultural fields for crop production, in addition to increased water storage capacity, groundwater recharge and availability of more irrigation water and environmental benefits

Capsomer Vaccines Protect Mice from Vaginal Challenge with Human Papillomavirus

Capsomers were produced in bacteria as glutathione-S-transferase (GST) fusion proteins with human papillomavirus type 16 L1 lacking the first nine and final 29 residues (GST-HPV16L1Δ) alone or linked with residues 13–47 of HPV18, HPV31 and HPV45 L2 in tandem (GST-HPV16L1Δ-L2x3). Subcutaneous immunization of mice with GST-HPV16L1Δ or GST-HPV16L1Δ-L2x3 in alum and monophosphoryl lipid A induced similarly high titers of HPV16 neutralizing antibodies. GST-HPV16L1Δ-L2x3 also elicited moderate L2-specific antibody titers. Intravaginal challenge studies showed that immunization of mice with GST-HPV16 L1Δ or GST-HPV16L1Δ-L2x3 capsomers, like Cervarix®, provided complete protection against HPV16. Conversely, vaccination with GST-HPV16 L1Δ capsomers failed to protect against HPV18 challenge, whereas mice immunized with either GST-HPV16L1Δ-L2x3 capsomers or Cervarix® were each completely protected. Thus, while the L2-specific response was moderate, it did not interfere with immunity to L1 in the context of GST-HPV16L1Δ-L2x3 and is sufficient to mediate L2-dependent protection against an experimental vaginal challenge with HPV18

Building a community-based open harmonised reference data repository for global crop mapping

Reference data is key to produce reliable crop type and cropland maps. Although research projects, national and international programs as well as local initiatives constantly gather crop related reference data, finding, collecting, and harmonizing data from different sources is a challenging task. Furthermore, ethical, legal, and consent-related restrictions associated with data sharing represent a common dilemma faced by international research projects. We address these dilemmas by building a community-based, open, harmonised reference data repository at global extent, ready for model training or product validation. Our repository contains data from different sources such as the Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM) Joint Experiment for Crop Assessment and Monitoring (JECAM) sites, the Radiant MLHub, the Future Harvest (CGIAR) centers, the National Aeronautics and Space Administration Food Security and Agriculture Program (NASA Harvest), the International Institute for Applied Systems Analysis (IIASA) citizen science platforms (LACO-Wiki and Geo-Wiki), as well as from individual project contributions. Data of 2016 onwards were collected, harmonised, and annotated. The data sets spatial, temporal, and thematic quality were assessed applying rules developed in this research. Currently, the repository holds around 75 million harmonised observations with standardized metadata of which a large share is available to the public. The repository, funded by ESA through the WorldCereal project, can be used for either the calibration of image classification deep learning algorithms or the validation of Earth Observation generated products, such as global cropland extent and maize and wheat maps. We recommend continuing and institutionalizing this reference data initiative e.g. through GEOGLAM, and encouraging the community to publish land cover and crop type data following the open science and open data principles