GlycomeDB—a unified database for carbohydrate structures

GlycomeDB integrates the structural and taxonomic data of all major public carbohydrate databases, as well as carbohydrates contained in the Protein Data Bank, which renders the database currently the most comprehensive and unified resource for carbohydrate structures worldwide. GlycomeDB retains the links to the original databases and is updated at weekly intervals with the newest structures available from the source databases. The complete database can be downloaded freely or accessed through a Web-interface (www.glycome-db.org) that provides flexible and powerful search functionalities

Comparing the Usefulness of the 1997 and 2009 WHO Dengue Case Classification: A Systematic Literature Review

The 1997 and 2009 WHO dengue case classifications were compared in a systematic review with 12 eligible studies (4 prospective). Ten expert opinion articles were used for discussion. For the 2009 WHO classification studies show: when determining severe dengue sensitivity ranges between 59–98% (88%/98%: prospective studies), specificity between 41–99% (99%: prospective study) - comparing the 1997 WHO classification: sensitivity 24.8–89.9% (24.8%/74%: prospective studies), specificity: 25%/100% (100%: prospective study). The application of the 2009 WHO classification is easy, however for (non-severe) dengue there may be a risk of monitoring increased case numbers. Warning signs validation studies are needed. For epidemiological/pathogenesis research use of the 2009 WHO classification, opinion papers show that ease of application, increased sensitivity (severe dengue) and international comparability are advantageous; 3 severe dengue criteria (severe plasma leakage, severe bleeding, severe organ manifestation) are useful research endpoints. The 2009 WHO classification has clear advantages for clinical use, use in epidemiology is promising and research use may at least not be a disadvantage

Dengue data and surveillance in Tanzania: a systematic literature review

Objective: Although there is evidence that dengue virus is circulating in Tanzania, the country lacks a dengue surveillance system. Consequently, the true estimate of dengue seroprevalence, as well as the incidence in the population, the frequency and magnitude of outbreaks is unknown. This study therefore sought to systematically review available dengue data from Tanzania. Methods: The systematic review was conducted and reported using the PRISMA tool. Five databases (PubMed, Embase, Web of Science, WHOLIS and Google Scholar) were searched for articles using various keywords on the illness, data and geographical location. Identified articles were assessed for inclusion based on predefined eligibility criteria. Data were extracted from included articles, analysed and reported. Results: Based on the 10 seroprevalence studies in defined populations with estimates of acute confirmed infections that were included in the review, the estimated seroprevalence of past dengue infection in Tanzania ranged from 50.6% in a health facility-based study to 11% in a population-based study. Acute confirmed infections of dengue were estimated to be as high as 38.2% of suspected cases. Only one study reported on an outbreak. Conclusions: It is evident that dengue needs to become part of regular disease surveillance in Tanzania. Control measures need to be instituted with a focus on building human resource capacity and integrating dengue control measures in ongoing health programmes, for both preventive and curative interventions. Systematic reviews are valuable in assessing health issues when surveillance data are not available

The minimum information required for a glycomics experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data

MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26:907–910) and mass spectrometry  data (Kolarich et al. 2013, Mol. Cell Proteomics, 12:991–995), here we present the first version of guidelines intended to improve the standards for reporting data from glycan microarray analyses. For each of eight areas in the workflow of a glycan microarray experiment, we provide guidelines for the minimal information that should be provided in reporting results. We hope that the MIRAGE glycan microarray guidelines proposed here will gain broad acceptance by the community, and will facilitate interpretation and reproducibility of the glycan microarray results with implications in comparison of data from different laboratories and eventual deposition of glycan microarray data in international databases

The Minimum Information Required for a Glycomics Experiment (MIRAGE) project: improving the standards for reporting glycan microarray-based data

MIRAGE (Minimum Information Required for A Glycomics Experiment) is an initiative that was created by experts in the fields of glycobiology, glycoanalytics, and glycoinformatics to produce guidelines for reporting results from the diverse types of experiments and analyses used in structural and functional studies of glycans in the scientific literature. As a sequel to the guidelines for sample preparation (Struwe et al. 2016, Glycobiology, 26, 907-910) and mass spectrometry (MS) data (Kolarich et al. 2013, Mol. Cell Proteomics. 12, 991-995), here we present the first version of guidelines intended to improve the standards for reporting data from glycan microarray analyses. For each of eight areas in the workflow of a glycan microarray experiment, we provide guidelines for the minimal information that should be provided in reporting results. We hope that the MIRAGE glycan microarray guidelines proposed here will gain broad acceptance by the community, and will facilitate interpretation and reproducibility of the glycan microarray results with implications in comparison of data from different laboratories and eventual deposition of glycan microarray data in international databases

Prepared to react? Assessing the functional capacity of the primary health care system in rural Orissa, India to respond to the devastating flood of September 2008

Background: Early detection of an impending flood and the availability of countermeasures to deal with it can significantly reduce its health impacts. In developing countries like India, public primary health care facilities are frontline organizations that deal with disasters particularly in rural settings. For developing robust counter reacting systems evaluating preparedness capacities within existing systems becomes necessary. Objective: The objective of the study is to assess the functional capacity of the primary health care system in Jagatsinghpur district of rural Orissa in India to respond to the devastating flood of September 2008. Methods: An onsite survey was conducted in all 29 primary and secondary facilities in five rural blocks (administrative units) of Jagatsinghpur district in Orissa state. A pre-tested structured questionnaire was administered face to face in the facilities. The data was entered, processed and analyzed using STATA® 10. Results: Data from our primary survey clearly shows that the healthcare facilities are ill prepared to handle the flood despite being faced by them annually. Basic utilities like electricity backup and essential medical supplies are lacking during floods. Lack of human resources along with missing standard operating procedures; pre-identified communication and incident command systems; effective leadership; and weak financial structures are the main hindering factors in mounting an adequate response to the floods. Conclusion: The 2008 flood challenged the primary curative and preventive health care services in Jagatsinghpur. Simple steps like developing facility specific preparedness plans which detail out standard operating procedures during floods and identify clear lines of command will go a long way in strengthening the response to future floods. Performance critiques provided by the grass roots workers, like this one, should be used for institutional learning and effective preparedness planning. Additionally each facility should maintain contingency funds for emergency response along with local vendor agreements to ensure stock supplies during floods. The facilities should ensure that baseline public health standards for health care delivery identified by the Government are met in non-flood periods in order to improve the response during floods. Building strong public primary health care systems is a development challenge. The recovery phases of disasters should be seen as an opportunity to expand and improve services and facilities

Dengue contingency planning: from research to policy and practice

Background Dengue is an increasingly incident disease across many parts of the world. In response, an evidence-based handbook to translate research into policy and practice was developed. This handbook facilitates contingency planning as well as the development and use of early warning and response systems for dengue fever epidemics, by identifying decision-making processes that contribute to the success or failure of dengue surveillance, as well as triggers that initiate effective responses to incipient outbreaks. Methodology/Principal findings Available evidence was evaluated using a step-wise process that included systematic literature reviews, policymaker and stakeholder interviews, a study to assess dengue contingency planning and outbreak management in 10 countries, and a retrospective logistic regression analysis to identify alarm signals for an outbreak warning system using datasets from five dengue endemic countries. Best practices for managing a dengue outbreak are provided for key elements of a dengue contingency plan including timely contingency planning, the importance of a detailed, context-specific dengue contingency plan that clearly distinguishes between routine and outbreak interventions, surveillance systems for outbreak preparedness, outbreak definitions, alert algorithms, managerial capacity, vector control capacity, and clinical management of large caseloads. Additionally, a computer-assisted early warning system, which enables countries to identify and respond to context-specific variables that predict forthcoming dengue outbreaks, has been developed. Conclusions/Significance Most countries do not have comprehensive, detailed contingency plans for dengue outbreaks. Countries tend to rely on intensified vector control as their outbreak response, with minimal focus on integrated management of clinical care, epidemiological, laboratory and vector surveillance, and risk communication. The Technical Handbook for Surveillance, Dengue Outbreak Prediction/ Detection and Outbreak Response seeks to provide countries with evidence-based best practices to justify the declaration of an outbreak and the mobilization of the resources required to implement an effective dengue contingency plan

Bioinformatics and molecular modeling in glycobiology

The field of glycobiology is concerned with the study of the structure, properties, and biological functions of the family of biomolecules called carbohydrates. Bioinformatics for glycobiology is a particularly challenging field, because carbohydrates exhibit a high structural diversity and their chains are often branched. Significant improvements in experimental analytical methods over recent years have led to a tremendous increase in the amount of carbohydrate structure data generated. Consequently, the availability of databases and tools to store, retrieve and analyze these data in an efficient way is of fundamental importance to progress in glycobiology. In this review, the various graphical representations and sequence formats of carbohydrates are introduced, and an overview of newly developed databases, the latest developments in sequence alignment and data mining, and tools to support experimental glycan analysis are presented. Finally, the field of structural glycoinformatics and molecular modeling of carbohydrates, glycoproteins, and protein–carbohydrate interaction are reviewed