Difference between revisions of "Main Page/Featured article of the week/2021"

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<h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: July 19–25:</h2>
<h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: July 26–August 1:</h2>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab1 Comess FrontArtInt2020 3.jpg|240px]]</div>
'''"[[Journal:Bringing big data to bear in environmental public health: Challenges and recommendations|Bringing big data to bear in environmental public health: Challenges and recommendations]]"'''
 
Understanding the role that the environment plays in influencing [[public health]] often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient [[information]] and confront significant unknowns in the field of [[Environmental health|environmental public health]], yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable [[Journal:The FAIR Guiding Principles for scientific data management and stewardship|(FAIR) data]]. Even when data are readily available, the ability to create, [[Data analysis|analyze]], and draw conclusions from these data using emerging computational tools, such as augmented intelligence, [[artificial intelligence]] (AI), and [[machine learning]], requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. ('''[[Journal:Bringing big data to bear in environmental public health: Challenges and recommendations|Full article...]]''')<br />
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|<br /><h2 style="font-size:105%; font-weight:bold; text-align:left; color:#000; padding:0.2em 0.4em; width:50%;">Featured article of the week: July 19–25:</h2>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 DiNardo Toxins2020 12-4.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 DiNardo Toxins2020 12-4.png|240px]]</div>
'''"[[Journal:Enzyme immunoassay for measuring aflatoxin B1 in legal cannabis|Enzyme immunoassay for measuring aflatoxin B1 in legal cannabis]]"'''
'''"[[Journal:Enzyme immunoassay for measuring aflatoxin B1 in legal cannabis|Enzyme immunoassay for measuring aflatoxin B1 in legal cannabis]]"'''

Revision as of 18:56, 3 August 2021

Featured article of the week archive - 2021

Welcome to the LIMSwiki 2021 archive for the Featured Article of the Week.

Featured article of the week: July 26–August 1:

Tab1 Comess FrontArtInt2020 3.jpg

"Bringing big data to bear in environmental public health: Challenges and recommendations"

Understanding the role that the environment plays in influencing public health often involves collecting and studying large, complex data sets. There have been a number of private and public efforts to gather sufficient information and confront significant unknowns in the field of environmental public health, yet there is a persistent and largely unmet need for findable, accessible, interoperable, and reusable (FAIR) data. Even when data are readily available, the ability to create, analyze, and draw conclusions from these data using emerging computational tools, such as augmented intelligence, artificial intelligence (AI), and machine learning, requires technical skills not currently implemented on a programmatic level across research hubs and academic institutions. (Full article...)


Featured article of the week: July 19–25:

Fig2 DiNardo Toxins2020 12-4.png

"Enzyme immunoassay for measuring aflatoxin B1 in legal cannabis"

The diffusion of the legalization of cannabis for recreational, medicinal, and nutraceutical uses requires the development of adequate analytical methods to assure the safety and security of such products. In particular, aflatoxins are considered to pose a major risk for the health of cannabis consumers. Among analytical methods that allow for adequate monitoring of food safety, immunoassays play a major role thanks to their cost-effectiveness, high-throughput capacity, simplicity, and limited requirement for equipment and skilled operators. Therefore, a rapid and sensitive enzyme immunoassay has been adapted to measure the most hazardous aflatoxin B1 in cannabis products. The assay was acceptably accurate (recovery rate: 78–136%), reproducible (intra- and inter-assay means coefficients of variation 11.8% and 13.8%, respectively), and sensitive (limit of detection and range of quantification: 0.35 ng mL−1 and 0.4–2 ng mL−1 ... (Full article...)


Featured article of the week: July 12–18:

Tab1 Konnick PractLabMed2020 21.png

"The regulatory landscape of precision oncology laboratory medicine in the United States: Perspective on the past five years and considerations for future regulation"

The regulatory landscape for precision oncology in the United States is complicated, with multiple governmental regulatory agencies with different scopes of jurisdiction. Several regulatory proposals have been introduced since the Food and Drug Administration released draft guidance to regulate laboratory developed tests in 2014. Key aspects of the most recent proposals and discussion of central arguments related to the regulation of precision oncology laboratory tests provides insight to stakeholders for future discussions related to regulation of laboratory tests. (Full article...)


Featured article of the week: July 5–11:

Fig6 Argento EMBOReports2020 21-3.jpg

"Institutional ELN-LIMS deployment: Highly customizable ELN-LIMS platform as a cornerstone of digital transformation for life sciences research institutes"

The systematic recording and management of experimental data in academic life science research remains an open problem. École Polytechnique Fédérale de Lausanne (EPFL) engaged in a program of deploying both an electronic laboratory notebook (ELN) and a laboratory information management system (LIMS) six years ago, encountering a host of fundamental questions at the institutional level and within each laboratory. Here, based on our experience, we aim to share with research institute managers, principal investigators (PIs), and any scientists involved in a combined ELN-LIMS deployment helpful tips and tools, with a focus on surrounding yourself with the right people and the right software at the right time. In this article we describe the resources used, the challenges encountered, key success factors, and the results obtained at each phase of our project. Finally, we discuss the current and next challenges we face, as well as how our experience leads us to support the creation of a new position in the research group: the laboratory data manager. (Full article...)


Featured article of the week: June 21–27:

Fig5 Jalali JofMedIntRes2019 21-2.png

"Health care and cybersecurity: Bibliometric analysis of the literature"

Over the past decade, clinical care has become globally dependent on information technology. The cybersecurity of health care information systems is now an essential component of safe, reliable, and effective health care delivery. The objective of this study was to provide an overview of the literature at the intersection of cybersecurity and health care delivery. A comprehensive search was conducted using PubMed and Web of Science for English-language peer-reviewed articles. We carried out chronological analysis, domain clustering analysis, and text analysis of the included articles to generate a high-level concept map composed of specific words and the connections between them. Our final sample included 472 English-language journal articles. Our review results revealed that a majority of the articles were focused on technology. Technology–focused articles made up more than half of all the clusters, whereas managerial articles accounted for only 32 percent of all clusters. (Full article...)


Featured article of the week: June 14–20:

Fig3 Fairchild FrontPubHealth2018 6.jpg

"Epidemiological data challenges: Planning for a more robust future through data standards"

Accessible epidemiological data are of great value for emergency preparedness and response, understanding disease progression through a population, and building statistical and mechanistic disease models that enable forecasting. The status quo, however, renders acquiring and using such data difficult in practice. In many cases, a primary way of obtaining epidemiological data is through the internet, but the methods by which the data are presented to the public often differ drastically among institutions. As a result, there is a strong need for better data sharing practices. This paper identifies, in detail and with examples, the three key challenges one encounters when attempting to acquire and use epidemiological data: (1) interfaces, (2) data formatting, and (3) reporting. (Full article...)


Featured article of the week: June 7–13:

Fig1 Udesky EnviroHealth2019 18.png

"Wrangling environmental exposure data: Guidance for getting the best information from your laboratory measurements"

Environmental health and exposure researchers can improve the quality and interpretation of their chemical measurement data, avoid spurious results, and improve analytical protocols for new chemicals by closely examining lab and field quality control (QC) data. Reporting QC data along with chemical measurements in biological and environmental samples allows readers to evaluate data quality and appropriate uses of the data (e.g., for comparison to other exposure studies, association with health outcomes, use in regulatory decision-making). However many studies do not adequately describe or interpret QC assessments in publications, leaving readers uncertain about the level of confidence in the reported data. One potential barrier to both QC implementation and reporting is that guidance on how to integrate and interpret QC assessments is often fragmented and difficult to find, with no centralized repository or summary. In addition, existing documents are typically written for regulatory scientists rather than environmental health researchers, who may have little or no experience in analytical chemistry. (Full article...)