An Integrated Study to Analyze Soil Microbial Community Structure and Metabolic Potential in Two Forest Types

Soil microbial metabolic potential and ecosystem function have received little attention owing to difficulties in methodology. In this study, we selected natural mature forest and natural secondary forest and analyzed the soil microbial community and metabolic potential combing the high-throughput sequencing and GeoChip technologies. Phylogenetic analysis based on 16S rRNA sequencing showed that one known archaeal phylum and 15 known bacterial phyla as well as unclassified phylotypes were presented in these forest soils, and Acidobacteria, Protecobacteria, and Actinobacteria were three of most abundant phyla. The detected microbial functional gene groups were related to different biogeochemical processes, including carbon degradation, carbon fixation, methane metabolism, nitrogen cycling, phosphorus utilization, sulfur cycling, etc. The Shannon index for detected functional gene probes was significantly higher (P<0.05) at natural secondary forest site. The regression analysis showed that a strong positive (P<0.05) correlation was existed between the soil microbial functional gene diversity and phylogenetic diversity. Mantel test showed that soil oxidizable organic carbon, soil total nitrogen and cellulose, glucanase, and amylase activities were significantly linked (P<0.05) to the relative abundance of corresponded functional gene groups. Variance partitioning analysis showed that a total of 81.58% of the variation in community structure was explained by soil chemical factors, soil temperature, and plant diversity. Therefore, the positive link of soil microbial structure and composition to functional activity related to ecosystem functioning was existed, and the natural secondary forest soil may occur the high microbial metabolic potential. Although the results can''t directly reflect the actual microbial populations and functional activities, this study provides insight into the potential activity of the microbial community and associated feedback responses of the terrestrial ecosystem to environmental changes.     

MScreen: An Integrated Compound Management and High-Throughput Screening Data Storage and Analysis System

High-throughput screening (HTS) has historically been used by the pharmaceutical industry to rapidly test hundreds of thousands of compounds to identify potential drug candidates. More recently, academic groups have used HTS to identify new chemical probes or small interfering RNA (siRNA) that can serve as experimental tools to examine the biology or physiology of novel proteins, processes, or interactions. HTS presents a significant challenge with the vast and complex nature of data generated. This report describes MScreen, a Web-based, open-source cheminformatics application for chemical library and siRNA plate management, primary HTS and dose-response data handling, structure search, and administrative functions. Each project in MScreen can be secured with passwords or shared in an open-information environment that enables collaborators to easily compare data from many screens, providing a useful means to identify compounds with desired selectivity. Unique features include compound, substance, mixture, and siRNA plate creation and formatting; automated dose-response fitting and quality control (QC); and user, target, and assay method administration. MScreen provides an effective means to facilitate HTS information handling and analysis in the academic setting so that users can efficiently view their screening data and evaluate results for follow-up.     

Application of the GARC Data Logger—a custom-developed data collection device—to capture and monitor mass dog vaccination campaigns in Namibia

Domestic dogs are responsible for 99% of all cases of human rabies and thus, mass dog vaccination has been demonstrated to be the most effective approach towards the elimination of dog-mediated human rabies. Namibia demonstrated the feasibility of this approach by applying government-led strategic rabies vaccination campaigns to reduce both human and dog rabies incidences in the Northern Communal Areas of Namibia since 2016. The lessons learnt using paper-based form for data capturing and management of mass dog vaccination campaign during the pilot and roll out phase of the project (2016–2018) led to the implementation of a simple and accurate data collection tool in the second phase (2019–2022) of the rabies elimination program. In this paper, we describe the implementation of such custom-developed vaccination tracking device, i.e. the Global Alliance for Rabies Control (GARC) Data Logger (GDL), and the integration of the collected data into a website-based rabies surveillance system (Rabies Epidemiological Bulletin—REB) during 2019 and 2020 campaigns. A total of 10,037 dogs and 520 cats were vaccinated during the 2019 campaign and 13,219 dogs and 1,044 cats during the 2020 campaign. The vaccination data were recorded with the GDL and visualized via REB. Subsequent GIS-analysis using gridded population data revealed a suboptimal vaccination coverage in the great majority of grid cells (82%) with a vaccination coverage below 50%. Spatial regression analysis identified the number of schools, estimated human density, and adult dog population were associated with the vaccination performance. However, there was an inverse correlation to human densities. Nonetheless, the use of the GDL improved data capturing and monitoring capacity of the campaign, enabling the Namibian government to improve strategies for the vaccination of at-risk areas towards achieving adequate vaccination coverage which would effectively break the transmission of rabies.     

dbSWEET: An Integrated Resource for SWEET Superfamily to Understand,Analyze and Predict the Function of Sugar Transporters in Prokaryotes and Eukaryotes

SWEET (Sweet Will Eventually be Exported Transporter) proteins have been recently discovered and form one of the three major families of sugar transporters. Homologs of SWEET are found in both prokaryotes and eukaryotes. Bacterial SWEET homologs have three transmembrane segments forming a triple-helical bundle and the functional form is dimers. Eukaryotic SWEETs have seven transmembrane helical segments forming two triple-helical bundles with a linker helix. Members of SWEET homologs have been shown to be involved in several important physiological processes in plants. However, not much is known regarding the biological significance of SWEET homologs in prokaryotes and in mammals. We have collected more than 2000 SWEET homologs from both prokaryotes and eukaryotes. For each homolog, we have modeled three different conformational states representing outward open, inward open and occluded states. We have provided details regarding substrate-interacting residues and residues forming the selectivity filter for each SWEET homolog. Several search and analysis options are available. The users can generate a phylogenetic tree and structure-based sequence alignment for selected set of sequences. With no metazoan SWEETs functionally characterized, the features observed in the selectivity filter residues can be used to predict the potential substrates that are likely to be transported across the metazoan SWEETs. We believe that this database will help the researchers to design mutational experiments and simulation studies that will aid to advance our understanding of the physiological role of SWEET homologs. This database is freely available to the scientific community at http://bioinfo.iitk.ac.in/bioinfo/dbSWEET/Home.     

Unified Materials Information System (UMIS): An Integrated Material Stocks and Flows Data Structure

Modern society depends on the use of many diverse materials. Effectively managing these materials is becoming increasingly important and complex, from the analysis of supply chains, to quantifying their environmental impacts, to understanding future resource availability. Material stocks and flows data enable such analyses, but currently exist mainly as discrete packages, with highly varied type, scope, and structure. These factors constitute a powerful barrier to holistic integration and thus universal analysis of existing and yet to be published material stocks and flows data. We present the Unified Materials Information System (UMIS) to overcome this barrier by enabling material stocks and flows data to be comprehensively integrated across space, time, materials, and data type independent of their disaggregation, without loss of information, and avoiding double counting. UMIS can therefore be applied to structure diverse material stocks and flows data and their metadata across material systems analysis methods such as material flow analysis (MFA), input‐output analysis, and life cycle assessment. UMIS uniquely labels and visualizes processes and flows in UMIS diagrams; therefore, material stocks and flows data visualized in UMIS diagrams can be individually referenced in databases and computational models. Applications of UMIS to restructure existing material stocks and flows data represented by block flow diagrams, system dynamics diagrams, Sankey diagrams, matrices, and derived using the economy‐wide MFA classification system are presented to exemplify use. UMIS advances the capabilities with which complex quantitative material systems analysis, archiving, and computation of material stocks and flows data can be performed.     

An Integrated Approach to Three-Dimensional Data Collection at Dinosaur Tracksites in the Rocky Mountain West

Public lands in the Rocky Mountain West are home to an abundance of vertebrate paleontological resources. These fossils typically are found in badlands terrain and at some distance from convenient transportation. These and other factors often make conventional surveying and mapping techniques time-consuming and problematic. Even obtaining quality images, at useful scales with limited distortions, can be difficult. In order to preserve the value of these unique paleontological resources, an integrated approach to close-range photogrammetry and high-accuracy ground-control surveying was developed in northern Wyoming for the documentation of tracks at the Red Gulch Dinosaur Tracksite. At this site, several methods for taking high-resolution, low-distortion photographs of localities were investigated. These methods included using tripods of various heights, remote-controlled airplanes, and an Aerial Camera Blimp System. In addition, the use of a variety of ground-control collection methods, including high accuracy GPS and Light Detection and Ranging, have also been investigated. These various field data collection methods were successfully integrated using soft copy photogrammetry to produce digital terrain models, which can represent the surface to a precision of 1 cm or less. The three-dimensional data were brought into GIS software where they are displayed, combined with photographs, and rotated for viewing from different perspectives. As a result of the success of these technologies in Wyoming, studies of other dinosaur tracksites in Colorado, Utah, and Wyoming (as well as bonebeds) have utilized these methods. The information gained from these sites is aiding in our understanding of community dynamics and preservational history of dinosaur populations in the Rocky Mountain West.     

An Integrated Flow Cytometry-Based System for Real-Time,High Sensitivity Bacterial Detection and Identification

Foodborne illnesses occur in both industrialized and developing countries, and may be increasing due to rapidly evolving food production practices. Yet some primary tools used to assess food safety are decades, if not centuries, old. To improve the time to result for food safety assessment a sensitive flow cytometer based system to detect microbial contamination was developed. By eliminating background fluorescence and improving signal to noise the assays accurately measure bacterial load or specifically identify pathogens. These assays provide results in minutes or, if sensitivity to one cell in a complex matrix is required, after several hours enrichment. Conventional assessments of food safety require 48 to 56 hours. The assays described within are linear over 5 orders of magnitude with results identical to culture plates, and report live and dead microorganisms. This system offers a powerful approach to real-time assessment of food safety, useful for industry self-monitoring and regulatory inspection.     

Henipaviruses—A constant threat to livestock and humans

In this review, we highlight the risk to livestock and humans from infections with henipaviruses, which belong to the virus family Paramyxoviridae. We provide a comprehensive overview of documented outbreaks of Nipah and Hendra virus infections affecting livestock and humans and assess the burden on the economy and health systems. In an increasingly globalized and interconnected world, attention must be paid to emerging viruses and infectious diseases, as transmission routes can be rapid and worldwide.     

Multivariate Data Analysis Methodology to Solve Data Challenges Related to Scale‐Up Model Validation and Missing Data on a Micro‐Bioreactor System

Multivariate data analysis (MVDA) is a highly valuable and significantly underutilized resource in biomanufacturing. It offers the opportunity to enhance understanding and leverage useful information from complex high‐dimensional data sets, recorded throughout all stages of therapeutic drug manufacture. To help standardize the application and promote this resource within the biopharmaceutical industry, this paper outlines a novel MVDA methodology describing the necessary steps for efficient and effective data analysis. The MVDA methodology is followed to solve two case studies: a “small data” and a “big data” challenge. In the “small data” example, a large‐scale data set is compared to data from a scale‐down model. This methodology enables a new quantitative metric for equivalence to be established by combining a two one‐sided test with principal component analysis. In the “big data” example, this methodology enables accurate predictions of critical missing data essential to a cloning study performed in the ambr15 system. These predictions are generated by exploiting the underlying relationship between the off‐line missing values and the on‐line measurements through the generation of a partial least squares model. In summary, the proposed MVDA methodology highlights the importance of data pre‐processing, restructuring, and visualization during data analytics to solve complex biopharmaceutical challenges.     

Responses in allometric growth of two dominant species of subalpine meadow—Arundinella anomala and Miscanthus sinensis—to climate warming in Wugongshan Mountains,China

AimsArundinella anomala and Miscanthus sinensis are dominant species in the subalpine meadow of Wugongshan Mountains. Here we studied the effects of climate warming on allometric relationships among different growth components in the two species through simulated warming in natural habitat.
Methods The warming experiments were conducted with open-top chambers (OTCs) in natural habitat in a subalpine meadow community of Wugongshan Mountains. The two main Gramineae species, Arundinella anomala and Miscanthus sinensis, were selected as the study materials. Two sizes of OTCs were set up to create contrasting levels of warming (i.e. TD for low warming and TG for high warming). The morphological variables, such as the plant height and the basal diameter of shoots, were measured. Allometric analysis was conducted with the Smart Package in R software.
Important findings Significant or highly significant correlations and significant allometric relationships were found between and among growth components in both species. The allometry of the growth in most morphological features was strengthened and modified by simulated warming. Stem diameter and plant height, and spike length in A. anomala and M. sinensis changed from isometric to allometric following warming. The relationship The synchronized growth between stem diameter and spikelet in A. anomala was weakened, but their allometry was enhanced with increased warming. The allometric relationship between plant height and leaf length in A. anomala transformed into isometric growth, but it was in reversed pattern in M. sinensis. Warming promoted the plant height and leaf sheath length in A. anomala, whilst higher warming changed the growth relationship between plant height and leaf sheath length in M. sinensis. Similar allometric relationships among the leaf traits were observed, but warming did not significantly impact their allometric exponents. The results suggested that climate warming could have varied effects on different plants, and the differences are often related to the adaptability of plants.     

武功山亚高山草甸群落优势植物野古草和芒异速生长对气候变暖的响应

气候变暖正持续影响着陆地生态系统的结构和功能, 一直是备受关注的热点问题。异速生长关系被认为是生物界中的一种普遍规律, 但我们对于气候变暖如何影响植物异速生长特征所知甚少。该文采用开顶式增温小室对野外自然生境进行模拟增温的方法, 研究了气候变暖对江西武功山亚高山草甸植物群落优势种野古草(Arundinella anomala)和芒(Miscanthus sinensis)异速生长特征的影响。结果表明: 野古草和芒的大多数形态指标之间均具有显著或极显著相关生长关系和异速生长关系, 气候变暖强化了两种禾本科植物大多数形态特征之间的异速生长, 或改变了其原有的生长关系。气候变暖还导致野古草和芒的基部茎粗与其高度、穗长间由原有的等速生长关系转变为异速生长关系; 野古草基部茎粗与小穗数间的异速生长随着温度升高而趋于增强。气候变暖导致野古草个体高度与其叶片长度的异速生长关系转变为等速生长关系, 而芒有相反表现。同时, 增温促进了野古草株高及叶鞘长的生长, 较强增温则改变了芒株高和叶鞘长之间的生长关系; 野古草和芒的叶片形态特征之间几乎都表现为类似的异速生长关系, 增温对其异速生长指数无显著影响。研究表明气候变暖对不同植物和植物构件具有差异性影响, 这种差异性往往与植物的适应性有关。     

Multi-scale Data Used to Analyze the Spatial Distribution of French Grunts, Haemulon Flavolineatum, Relative to Hard and Soft Bottom in a Benthic Landscape

We evaluated the day-time distribution of juvenile and adult French grunts, Haemulon flavolineatum, relative to the spatial configuration of hard and soft bottom areas in a benthic landscape. Probability of juvenile presence on hard bottom sites was inversely correlated with distance to soft bottom. Adults presence at hard bottom sites showed no significant relationship with distance to soft bottom. A significant and positive relationship was found between presence of juveniles on hard bottom sites and area of soft bottom within 100m, but no significant relationship was found for area of soft bottom within 500m. Adults exhibited no significant relationship with area of soft bottom for either distance tested. These distributions are suspected to be the result of the combined influence of larval settlement patterns and foraging behaviors associated with hard and soft bottom. This study indicates that data collected at very fine scales can be analyzed in the context of the broad-scale mosaic of habitats in the benthic landscape to predict patterns of fish distribution. Such spatially explicit conclusions are not possible through analysis of fine-scale or broad-scale data alone.     

A Statewide Approach to Health Care Personnel Maldistribution—The California Area Health Education Center System

An Area Health Education Center (AHEC) system has been established in California to address the maldistribution of physicians and other health care professionals. The AHEC program uses educational incentives to recruit and retain health care personnel in underserved areas by linking the academic resources of university health science centers with local educational and clinical facilities. The medical schools, working in partnership with urban or rural AHECs throughout the state, are implementing educational programs to attract trainees and licensed professionals to work in underserved communities. The California AHEC project entered its fifth year in October of 1983 with the participation of all eight medical schools and the Charles Drew Postgraduate School of Medicine, 35 other health professions schools, 17 independent AHECs and more than 400 clinical training sites. Educational programs are reaching more than 22,000 students and practicing health professionals throughout California. We review the current status of the California AHEC system and use the AHEC programs at Loma Linda University to illustrate the effect this intervention is having.     

Raising the Barriers to Access to Medicines in the Developing World – The Relentless Push for Data Exclusivity

Since the adoption of the WTO‐TRIPS Agreement in 1994, there has been significant controversy over the impact of pharmaceutical patent protection on the access to medicines in the developing world. In addition to the market exclusivity provided by patents, the pharmaceutical industry has also sought to further extend their monopolies by advocating the need for additional ‘regulatory’ protection for new medicines, known as data exclusivity. Data exclusivity limits the use of clinical trial data that need to be submitted to the regulatory authorities before a new drug can enter the market. For a specified period, generic competitors cannot apply for regulatory approval for equivalent drugs relying on the originator's data. As a consequence, data exclusivity lengthens the monopoly for the original drug, impairing the availability of generic drugs. This article illustrates how the pharmaceutical industry has convinced the US and the EU to impose data exclusivity on their trade partners, many of them developing countries. The key arguments formulated by the pharmaceutical industry in favor of adopting data exclusivity and their underlying ethical assumptions are described in this article, analyzed, and found to be unconvincing. Contrary to industry's arguments, it is unlikely that data exclusivity will promote innovation, especially in developing countries. Moreover, the industry's appeal to a property rights claim over clinical test data and the idea that data exclusivity can prevent the generic competitors from ‘free‐riding’ encounters some important problems: Neither legitimize excluding all others.     

Globalization, Health, and the Environment: An Integrated Perspective

Globalization, Health, and the Environment: An Integrated Perspective . Greg Guest, ed. Lanham, MD: Rowman and Littlefield, 2006. 274 pp.