Indian Academy of Pediatrics Guidelines on School Reopening, Remote Learning and Curriculum in and After the COVID-19 Pandemic.

JUSTIFICATION: With the unprecedented COVID-19 pandemic and the resultant school closure, children all over the country are undergoing a lot of educational, psychosocial, and physical problems. There is an urgent and deep felt need to offer scientific and concrete guidance for these concerns and support children in their educational development during these testing times. OBJECTIVE: To review the guidelines and recommendations given by various international agencies and formulate guidelines in the Indian context on (a) how and when to reopen the schools; (b) ways and means of remote learning; and (c) to identify the contents of curriculum that need restructuring in context of the current situation. PROCESS: Indian Academy of Pediatrics (IAP) formed a task force of pediatricians, educationists and technological experts who connected through various video and social platforms. They gathered and exchanged information and thoughts. The writing committee drafted the guidelines and got approval of all the members of the task force. RECOMMENDATIONS: Schools can be reopened only when the local epidemiological parameters are favorable, the administration is equipped with adequate infrastructure and health care facilities, and the stakeholders (teachers, students, parents, and support staff) are prepared for the new normal. In the meanwhile, remote learning (media-based and /or otherwise) should reach to the last student to maintain uninterrupted education. The curriculum needs to be revised, with focus on revision and core contents. Informal learning of psychosocial empowerment and daily living skills should be encouraged rather than stressful formal learning.

Pulmonary delivery of peptide YY for food intake suppression and reduced body weight gain in rats.

AIMS: Peptide YY (PYY) is an endogenous anorectic gut-secreted peptide that has been shown to suppress appetite in animals and humans, when given by injection. This study tested if needle-free pulmonary delivery of PYY enables food intake suppression and reduced body weight gain in rats. The PYY pharmacokinetics and effects on brain neuropeptide levels were also examined. METHODS: Rats received single or once-daily 7-day pulmonary administration of saline or PYYs. Food intake and body weight gain were monitored to study the effects of different doses (0.08-0.90 mg/kg) of PYY3-36, PYY1-36 and PYY13-36. Plasma PYY pharmacokinetics were determined via enzyme-linked immunosorbent assay. Changes in orexigenic neuropeptide Y (NPY) and c-Fos protein levels in the hypothalamus arcuate nucleus (ARC) were measured by immunofluorescence microscopy. RESULTS: PYY3-36 caused dose-dependent and 4- to 6-h food intake suppression following pulmonary delivery. At 0.80 mg/kg, the effect was significant with 35.1 ± 5.7 and 19.7 ± 4.2% suppression at 4 and 6 h, respectively. Repeated administration for 7 days reduced cumulative body weight gain by 39.4 ± 11.0%. PYY1-36, but not PYY13-36, was equipotent to PYY3-36 in food intake suppression. The plasma PYY concentration reached its peak at 10 min following pulmonary delivery with 12-14% of bioavailability. Increased c-Fos and reduced NPY expressions were observed in the hypothalamus ARC, consistent with the magnitude of food intake suppression by each of the PYYs. CONCLUSIONS: Pulmonary delivery of PYY enabled significant 4- to 6-h food intake suppression via 12-14% of lung absorption and hypothalamic ARC interaction, leading to reduced body weight gain in rats.

Obesity and risk of the less commonly diagnosed subtypes of breast cancer.

OBJECTIVES: A set of common epidemiologic risk factors have been associated with the risk of breast cancer despite of its molecular sub-classifications. We implemented a case series study with the primary objective of evaluating if obesity is associated with the diagnostic risk of "ER+ and/or PR+, HER2+", "ER-/PR-, HER2-", or "ER-/PR-, HER2+" relative to the most commonly diagnosed subtype of breast carcinoma, "ER+ and/or PR+, HER2-". METHODS: Demographic, clinical and pathologic data were collected from existing databases. The statuses of HER2/neu biomarker and hormone receptors were dichotomized as either positive or negative. Immunohistochemical staining was used to assess the prevalence of different subtypes. Body mass index was calculated from weight and height data collected at the time of consultation. CONCLUSIONS: Findings from the present study suggest that excess body weight decreases the diagnostic risk of "ER-/PR-, HER2-", or "ER-/PR-, HER2-" relative to "ER+ and/or PR+, HER2-". Obese and overweight women are more likely to be diagnosed with to "ER+ and/or PR+, HER2-", the subtype that has best prognosis and mostly associated with personal lifestyle. Weight gain with the population attributable-risk factor of 21.3% contributes the most to the incidence of invasive post menopausal breast cancer. Younger pre-menopausal women were more likely to be diagnosed with "ER+ and/or PR+, HER2+". In younger women biology of breast cancers with positive expression for hormone receptors and epidermal growth factor is a complex that extends beyond the currently assessed prognostic markers.

The Common Data Elements for cancer research: remarks on functions and structure.

OBJECTIVES: The National Cancer Institute (NCI) has developed the Common Data Elements (CDE) to serve as a controlled vocabulary of data descriptors for cancer research, to facilitate data interchange and inter-operability between cancer research centers. We evaluated CDE's structure to see whether it could represent the elements necessary to support its intended purpose, and whether it could prevent errors and inconsistencies from being accidentally introduced. We also performed automated checks for certain types of content errors that provided a rough measure of curation quality. METHODS: Evaluation was performed on CDE content downloaded via the NCI's CDE Browser, and transformed into relational database form. Evaluation was performed under three categories: 1) compatibility with the ISO/IEC 11179 metadata model, on which CDE structure is based, 2) features necessary for controlled vocabulary support, and 3) support for a stated NCI goal, set up of data collection forms for cancer research. RESULTS: Various limitations were identified both with respect to content (inconsistency, insufficient definition of elements, redundancy) as well as structure--particularly the need for term and relationship support, as well as the need for metadata supporting the explicit representation of electronic forms that utilize sets of common data elements. CONCLUSIONS: While there are numerous positive aspects to the CDE effort, there is considerable opportunity for improvement. Our recommendations include review of existing content by diverse experts in the cancer community; integration with the NCI thesaurus to take advantage of the latter's links to nationally used controlled vocabularies, and various schema enhancements required for electronic form support.

Informatics tools to improve clinical research.

During the conduct of complex clinical trials, there are numerous sources and types of data collection and project coordination problems. Methods and approaches to address the conduct of a trial vary in both the cost and time to perform and the potential benefit. Informatics tools can help trial coordinators and investigators ensure the collection of high quality research data during all phases of a clinical trial.

Automating identification of adverse events related to abnormal lab results using standard vocabularies.

Laboratory data need to be imported automatically into central Clinical Study Data Management Systems (CSDMSs), and abnormal laboratory data need to be linked to clinically related adverse events. This import of laboratory data can be automated through mapping to standard vocabularies with HL7/LOINC mapping to the metadata within a CSDMS. We have designed a system that uses the UMLS metathesaurus as a common source to map or link abnormal laboratory values to adverse event CTCAE coded terms and grades in the metadata of TrialDB, a generic CSDMS.

Metadata driven generation of reports for clinical studies.

We have developed a reporting engine to dynamically create Web-based reports for multiple types of clinical studies in a large-scale clinical study data management system (CSDMS), TrialDB. The engine, currently in production use, generates reports based on metadata that is defined through a GUI, thus eliminating the need to write code for every report.

Integration of Web-based and PC-based clinical research databases.

UNLABELLED: We have created a Web-based repository or data library of information about measurement instruments used in studies of multi-factorial geriatric health conditions (the Geriatrics Research Instrument Library - GRIL) based upon existing features of two separate clinical study data management systems. GRIL allows browsing, searching, and selecting measurement instruments based upon criteria such as keywords and areas of applicability. Measurement instruments selected can be printed and/or included in an automatically generated standalone microcomputer database application, which can be downloaded by investigators for use in data collection and data management. METHODS: Integration of database applications requires the creation of a common semantic model, and mapping from each system to this model. Various database schema conflicts at the table and attribute level must be identified and resolved prior to integration. Using a conflict taxonomy and a mapping schema facilitates this process. RESULTS: Critical conflicts at the table level that required resolution included name and relationship differences. CONCLUSIONS: A major benefit of integration efforts is the sharing of features and cross-fertilization of applications created for similar purposes in different operating environments. Integration of applications mandates some degree of metadata model unification.

Approaches and informatics tools to assist in the integration of similar clinical research questionnaires.

OBJECTIVE: The integration of similar clinical research questionnaires is a complex process that can benefit from informatics approaches and tools that provide a systematic structure for performing mapping and integration. This systematic approach is necessary to address complex issues in integration such as data heterogeneity, differing levels of granularity of questions and responses, and other issues involving semantic differences. Informatics tools and approaches have been successfully applied to various standard clinical vocabulary integration processes but not for questionnaire integration or mapping. METHODS: A systematic approach to questionnaire integration was developed in the context of a collaboration of researchers using Trial/DB, a database designed to support clinical research. This approach was applied to the integration of questionnaires involving breast cancer risk factors from each of three research sites. RESULTS: From 375 questions on the three original questionnaires, we identified 65 concepts that were measured by two or three of the sites. An algorithm was developed and used to formalize the process of mapping questions and answers across the questionnaires. The approach was applied to previously collected data and prospective data in disparate data-base systems to import and merge the data from these three sites into Trial/DB. CONCLUSION: Informatics tools that support a systematic approach to mapping questionnaires can be used throughout the research process from questionnaire integration and creation, legacy data integration to data library maintenance and curation.

TrialDB: A web-based Clinical Study Data Management System.

Clinical Study Data Management Systems (CSDMSs) are a class of software that support centralized management of data generated during the conduct of clinical studies. Commercial CSDMSs include Oracle Clinical, ClinTrial and MetaTrial. Such systems, which are typically deployed at an institutional or organizational level, must accommodate diverse types of data from different clinical domains that is generated by different groups of clinical investigators. Large-scale CSDMSs typically employ a high-end database engine that is usually accessed over an intranet or the Internet using Web-based technologies. CSDMSs in institution-wide use for a variety of clinical domains are best served by entity-attribute-value (EAV) modeling for the clinical data: all the commercial CSDMSs that we are aware of use EAV design. However, de novo development of EAV databases for data management is a challenging task. A large body of generic metadata-driven code must be developed before a basic EAV application can be written. Clearly, the availability of pre-existing software with the requisite functionality would be very valuable. We will discuss the benefits of such software being in open-source form.

An introduction to information retrieval: applications in genomics.

Information retrieval (IR) is the field of computer science that deals with the processing of documents containing free text, so that they can be rapidly retrieved based on keywords specified in a user's query. IR technology is the basis of Web-based search engines, and plays a vital role in biomedical research, because it is the foundation of software that supports literature search. Documents can be indexed by both the words they contain, as well as the concepts that can be matched to domain-specific thesauri; concept matching, however, poses several practical difficulties that make it unsuitable for use by itself. This article provides an introduction to IR and summarizes various applications of IR and related technologies to genomics.

Use of general-purpose negation detection to augment concept indexing of medical documents: a quantitative study using the UMLS.

OBJECTIVES: To test the hypothesis that most instances of negated concepts in dictated medical documents can be detected by a strategy that relies on tools developed for the parsing of formal (computer) languages-specifically, a lexical scanner ("lexer") that uses regular expressions to generate a finite state machine, and a parser that relies on a restricted subset of context-free grammars, known as LALR(1) grammars. METHODS: A diverse training set of 40 medical documents from a variety of specialties was manually inspected and used to develop a program (Negfinder) that contained rules to recognize a large set of negated patterns occurring in the text. Negfinder's lexer and parser were developed using tools normally used to generate programming language compilers. The input to Negfinder consisted of medical narrative that was preprocessed to recognize UMLS concepts: the text of a recognized concept had been replaced with a coded representation that included its UMLS concept ID. The program generated an index with one entry per instance of a concept in the document, where the presence or absence of negation of that concept was recorded. This information was used to mark up the text of each document by color-coding it to make it easier to inspect. The parser was then evaluated in two ways: 1) a test set of 60 documents (30 discharge summaries, 30 surgical notes) marked-up by Negfinder was inspected visually to quantify false-positive and false-negative results; and 2) a different test set of 10 documents was independently examined for negatives by a human observer and by Negfinder, and the results were compared. RESULTS: In the first evaluation using marked-up documents, 8,358 instances of UMLS concepts were detected in the 60 documents, of which 544 were negations detected by the program and verified by human observation (true-positive results, or TPs). Thirteen instances were wrongly flagged as negated (false-positive results, or FPs), and the program missed 27 instances of negation (false-negative results, or FNs), yielding a sensitivity of 95.3 percent and a specificity of 97.7 percent. In the second evaluation using independent negation detection, 1,869 concepts were detected in 10 documents, with 135 TPs, 12 FPs, and 6 FNs, yielding a sensitivity of 95.7 percent and a specificity of 91.8 percent. One of the words "no," "denies/denied," "not," or "without" was present in 92.5 percent of all negations. CONCLUSIONS: Negation of most concepts in medical narrative can be reliably detected by a simple strategy. The reliability of detection depends on several factors, the most important being the accuracy of concept matching.

Integration of multidisciplinary sensory data: a pilot model of the human brain project approach.

The paper provides an overview of neuroinformatics research at Yale University being performed as part of the national Human Brain Project. This research is exploring the integration of multidisciplinary sensory data, using the olfactory system as a model domain. The neuroinformatics activities fall into three main areas: 1) building databases and related tools that support experimental olfactory research at Yale and can also serve as resources for the field as a whole, 2) using computer models (molecular models and neuronal models) to help understand data being collected experimentally and to help guide further laboratory experiments, 3) performing basic neuroinformatics research to develop new informatics technologies, including a flexible data model (EAV/CR, entity-attribute-value with classes and relationships) designed to facilitate the integration of diverse heterogeneous data within a single unifying framework.

UMLS concept indexing for production databases: a feasibility study.

OBJECTIVES: To explore the feasibility of using the National Library of Medicine's Unified Medical Language System (UMLS) Metathesaurus as the basis for a computational strategy to identify concepts in medical narrative text preparatory to indexing. To quantitatively evaluate this strategy in terms of true positives, false positives (spuriously identified concepts) and false negatives (concepts missed by the identification process). METHODS: Using the 1999 UMLS Metathesaurus, the authors processed a training set of 100 documents (50 discharge summaries, 50 surgical notes) with a concept-identification program, whose output was manually analyzed. They flagged concepts that were erroneously identified and added new concepts that were not identified by the program, recording the reason for failure in such cases. After several refinements to both their algorithm and the UMLS subset on which it operated, they deployed the program on a test set of 24 documents (12 of each kind). RESULTS: Of 8,745 matches in the training set, 7,227 (82.6 percent ) were true positives, whereas of 1,701 matches in the test set, 1, 298 (76.3 percent) were true positives. Matches other than true positive indicated potential problems in production-mode concept indexing. Examples of causes of problems were redundant concepts in the UMLS, homonyms, acronyms, abbreviations and elisions, concepts that were missing from the UMLS, proper names, and spelling errors. CONCLUSIONS: The error rate was too high for concept indexing to be the only production-mode means of preprocessing medical narrative. Considerable curation needs to be performed to define a UMLS subset that is suitable for concept matching.

Web-based UMLS concept retrieval by automatic text scanning: a comparison of two methods.

The Web is increasingly the medium of choice for multi-user application program delivery. Yet selection of an appropriate programming environment for rapid prototyping, code portability, and maintainability remain issues. We summarize our experience on the conversion of a LISP Web application, Search/SR to a new, functionally identical application, Search/SR-ASP using a relational database and active server pages (ASP) technology. Our results indicate that provision of easy access to database engines and external objects is almost essential for a development environment to be considered viable for rapid and robust application delivery. While LISP itself is a robust language, its use in Web applications may be hard to justify given that current vendor implementations do not provide such functionality. Alternative, currently available scripting environments for Web development appear to have most of LISP's advantages and few of its disadvantages.

Generation of pedigree diagrams for web display using scalable vector graphics from a clinical trials database.

The standard method of studying inherited disease is to observe its pattern of distribution in families, that is, its pattern in a pedigree. For clinical studies focused on inherited disease, a pedigree diagram is a valuable visual tool for the display of inheritance patterns. We describe the creation of a web-based pedigree display module for Trial/DB, a Web accessible database developed at the Yale Center for Medical Informatics (YCMI) to support clinical research studies. The pedigree diagram is generated dynamically from the database. The icons representing each subject in the pedigree are selectable hyperlinks that will display detailed clinical data collected on the subject. Microsoft Active Server Page and Scalable Vector Graphics (SVG) are used to create the interactive pedigree diagrams.

Easing the transition between attribute-value databases and conventional databases for scientific data.

We have previously developed and described a modeling and development framework called EAV/CR, which is appropriate for designing databases containing highly heterogeneous and evolving data, as in the case of scientific databases for rapidly advancing domains. The use of EAV/CR has been hampered by the lack of generic tools for non-procedurally transferring data into or out of legacy systems or analytical packages: the transfer task is complicated by the different representation of EAV vs. conventional data, which is not addressed by commercial data-transfer programs. We have therefore created such a tool, which works with a wide variety of data sources that are accessible via Microsoft OLE DB technology. The data transfer tool requires minimal programmer intervention to set up, and no programming to use on a regular basis. Current limitations of the tool are also noted.

Reengineering a database for clinical trials management: lessons for system architects.

This paper describes the process of enhancing Trial/DB, a database system for clinical studies management. The system's enhancements have been driven by the need to maximize the effectiveness of developer personnel in supporting numerous and diverse users, of study designers in setting up new studies, and of administrators in managing ongoing studies. Trial/DB was originally designed to work over a local area network within a single institution, and basic architectural changes were necessary to make it work over the Internet efficiently as well as securely. Further, as its use spread to diverse communities of users, changes were made to let the processes of study design and project management adapt to the working styles of the principal investigators and administrators for each study. The lessons learned in the process should prove instructive for system architects as well as managers of electronic patient record systems.