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Holy Carnitine! @Altmetric Is On To Something Big!

In our previous article, we talked about a ranking list done by Altmetric of the most popular research articles of 2013. An interesting anecdotal story at the Reference desk just a couple of days after publishing the article, I think, gives strong confirmation of the validity of the Altmetric ranking.

As I was working at the Reference desk, a library patron using a workstation in the reference area [who turned out to be Charles Rebouche, see more below] asked for help with a printing problem he was having. As I approached his station I couldn’t help noticing that the article he was trying to print was on Carnitine, which happened to be a prominent subject of one of the articles that was on the Altmetric ranking. I was especially struck when I noticed this because before I saw the Altmetric ranking list in December, I had never heard of carnitine. As I learned in writing about the Altmetric ranking though, it turns out that carnitine is an ingredient of red meat (and also many energy drinks) that’s implicated in new research as a possible contributor to cardiovascular disease.

After the patron’s printing problem was resolved, I talked to him about his interest in carnitine. Interestingly, I learned that he’s an emeritus faculty member who has spent much of his career on researching carnitine. I told him about my work with the Altmetric list, and about the article that was ranked as being one of the most popular research articles of 2013. He knew all about the surge in popularity of the subject that accompanied the article, he said, because he’s been asked to “come out of retirement” to do a presentation about carnitine, which is why he was in the library catching up on the latest research.

So, on one level, a cute, satisfying story about the rewards of working at the Reference desk. But beyond that, I think this little story shows that the Altmetric ranking is more than an abstract application of “big data,” that Altmetric popularity does indeed have a real effect that’s felt by real researchers!

[Dr. Rebouche has read and approved of this article. He has indeed done voluminous research on carnitine, as attested by his 41 PubMed citations!]

Food, Diet & Nutrition: Popular Subject, Difficult PubMed Search

By Eric Rumsey and Janna Lawrence

In December, Altmetric published a list of the most popular research papers of 2013 <http://www.altmetric.com/top100>. The Altmetric site has developed a method to quantify popularity by using social media and traditional media to measure the “buzz” about particular articles. Of the top 64 articles on the altmetric list, a surprisingly high 19% of them (12 articles) are on food, diet and nutrition (FDN). In comparison, by our count the number of citations in the top 64 for other popular topics are: Brain/Neuro 9, Sleep 5, Heart/Cardio 3, and Cancer 3.

The popularity of FDN strikes us especially because we have recently written on this blog about the difficulty of searching FDN subjects in PubMed. The Altmetric list provides a good opportunity to test our ideas on FDN subjects that are identified by Altmetric data as being especially  popular.

Shown below are the 12 articles in the top 64 articles in the Altmetric ranking that are on FDN, with PubMed links and FDN-related MeSH terms that are used for each of the articles (the asterisk after some headings indicates that the subject is given major emphasis in the article). At the end of the list, we’ll have a few brief comments on MeSH indexing problems.

FDN-related articles on the Altmetric Top 100 Research Articles of 2013

#2 (See comments on this article at bottom)
Primary Prevention of Cardiovascular Disease with a Mediterranean Diet
New England Journal of Medicine
http://www.ncbi.nlm.nih.gov/pubmed/23432189
FDN-related MeSH terms:
Diet, Fat-Restricted
Diet, Mediterranean*
Dietary Supplements
Nuts*
Plant Oils*

#8
Association of Nut Consumption with Total and Cause-Specific Mortality
New England Journal of Medicine
http://www.ncbi.nlm.nih.gov/pubmed/24256379
FDN-related MeSH terms:
Diet*
Diet Surveys
Nuts*

#15 (See comments on this article at bottom)
Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain
Proceedings of the National Academy of Sciences
http://www.ncbi.nlm.nih.gov/pubmed/23479616
FDN-related MeSH terms:
Eating/physiology*
Weight Gain/physiology*

#19
The Autopsy of Chicken Nuggets Reads “Chicken Little”
The American Journal of Medicine
http://www.ncbi.nlm.nih.gov/pubmed/24035124
FDN-related MeSH terms:
Dietary Fats/analysis
Dietary Proteins/analysis
Fast Foods/analysis*
Poultry Products/analysis*

#23
Myths, Presumptions, and Facts about Obesity
New England Journal of Medicine
http://www.ncbi.nlm.nih.gov/pubmed/23363498
FDN-related MeSH terms:
Breast Feeding
Diet, Reducing
Obesity*/physiopathology
Obesity*/prevention & control
Obesity*/therapy
Weight Loss*

#26
Prospective Study of Breakfast Eating and Incident Coronary Heart Disease in a Cohort of Male US Health Professionals
Circulation
http://www.ncbi.nlm.nih.gov/pubmed/23877060
FDN-related MeSH terms:
Breakfast*
Food Habits*

#33
DNA barcoding detects contamination and substitution in North American herbal products
BMC Medicine
http://www.ncbi.nlm.nih.gov/pubmed/24120035
FDN-related MeSH terms:
Not yet indexed

#38
Persistence of Salmonella and E. coli on the surface of restaurant menus
Journal of Environmental Health
http://www.ncbi.nlm.nih.gov/pubmed/23505769
FDN-related MeSH terms:
Food Microbiology*
Foodborne Diseases/microbiology
Foodborne Diseases/prevention & control*

#54
Meat consumption and mortality – results from the European Prospective Investigation into Cancer and Nutrition
http://www.ncbi.nlm.nih.gov/pubmed/23497300
FDN-related MeSH terms:
Diet/adverse effects*
Feeding Behavior*
Meat*
Nutrition Surveys

#58
The Relationship of Sugar to Population-Level Diabetes Prevalence: An Econometric Analysis of Repeated Cross-Sectional Data
PLOS ONE OPEN ACCESS
http://www.ncbi.nlm.nih.gov/pubmed/23460912
FDN-related MeSH terms:
Carbohydrates/analysis*
Obesity/epidemiology

#60
Inverse relationship of food and alcohol intake to sleep measures in obesity
Nutrition & Diabetes
http://www.ncbi.nlm.nih.gov/pubmed/23357877
FDN-related MeSH terms:
This journal is not currently indexed in PubMed/MEDLINE

#64 (See comments on this article at bottom)
Intestinal microbiota metabolism of l-carnitine, a nutrient in red meat, promotes atherosclerosis
Nature Medicine
http://www.ncbi.nlm.nih.gov/pubmed/23563705
FDN-related MeSH terms:
Meat

Our comments on the Altmetric list

The twelve FDN citations in the Altmetric rankings cluster around three subjects – Plant-based foods: #2, #8, # 33; Obesity & Weight Gain: #15, #23, #58, #60; and Meat: #19, #54, #64. In a brief examination of the list, we can see that there are MeSH problems in each of these areas, most notably in these citations, one in each of the three clusters:

  • Plant-Based Foods – #2 (Primary Prevention of Cardiovascular Disease with a Mediterranean Diet) – Olive oil, a major top of this article, is indexed in MeSH as Plant Oils. This is not in the Food explosion, or any other FDN explosion, so it’s not picked up by a comprehensive search for FDN subjects.
  • Obesity and Weight Gain – #15 (Impact of insufficient sleep on … food intake, and weight gain). This is indexed in MeSH as Weight gain, and not as Obesity. The latter term is retrieved by a broad FDN search because it’s in the Nutrition disorders explosion. The seemingly closely-related term Weight gain is not in that explosion, and is therefore not retrieved in a broad FDN search.
  • Meat – #64 (Intestinal microbiota metabolism of … red meat, promotes atherosclerosis) – “Red Meat” is generally considered to be beef, pork and lamb – Because none of these has separate MeSH terms, the article is indexed only as Meat. This is a problem because when that term is searched in PubMed, it is automatically exploded, and the exploded heading includes not just meat, but also fish and poultry. Even searching for Meat as an unexploded MeSH term retrieves some articles for poultry and fish.

We have written previously on the problems of searching in PubMed for Plant-Based Foods. We will write in the future here on the other topics above – Obesity and Meat.

Acknowledgements:

  • Thanks to Colby Vorland (‏@nutsci) who first noted in a tweet the popularity of FDN in the Altmetric ranking.
  • Thanks to Chris Shaffer, for a close reading of our article and useful comments.

ClinicalKey Now Available!

(We originally announced that ClinicalKey was available yesterday, but discovered some issues with it.  It seems to be running fine now, both on-campus and off, but if you have any problems, do not hesitate to contact us at 319-335-9151.)

Elsevier’s ClinicalKey is now available through the Health Sciences Resources A-Z list, as well as through the All Databases A-Z list.  ClinicalKey will replace MDConsult in mid-January 2014, and includes most of the content currently in that resource, plus more.  All content can be searched through a single search box, or specific types of information can be selected from the top of the screen.

Clinical Key includes:

  • Over 1100 Elsevier biomedical books*
  • More than 500 journal titles*
  • Clinical monographs from First Consult
  • Procedures Consult content and videos
  • Practice guidelines
  • Clinical Pharmacology drug monographs
  • Patient education information

Although ClinicalKey can be used without individual registration, creating an account allows users to use special features, such as accessing PDFs of most book chapters (all books have HTML chapters), saving searches, and creating presentations using ClinicalKey content.

A ClinicalKey user guide is available at http://www.elsevier-data.de/ClinicalKey/ClinicalKey_user_guide.pdf.  ClinicalKey is available off-campus to UI students, faculty, and staff by logging in with your HawkID and password.  Questions?  Contact your liaison or the Hardin Library reference staff at 319-335-9151 or lib-hardin@uiowa.edu.

*Records for books and journals will be available soon in the InfoHawk catalog and the Electronic Journals list.

 

Exam Master added a new mode – Learning

Exam Master now includes a new learning mode.  You can view the correct answer choice and question explanation immediately without generating a score report.

4 modes are available in Exam Master

1. Test Mode: Submit an answer choice for each question and click score to complete the session.  If score report access is allowed, go to My Stats to evaluate your strengths and weaknesses by topical area.

2. Review Mode: Available after an exam is scored in test mode.  Compares answer choice previously selected in test mode in correct answer choice and allows access to question explanations.

3. Study Mode: Review question feedback and access to an explanation upon submitting an answer choice for each question.  A score report is generated using the first answer choice submitted.  Click score to complete the study session.

4. New Learning Mode: View correct answer choice and question explanation immediately and learn the question content without generating a score report.

Exam Master includes material on:

Anatomy
Biochemistry
Cytology and Histology
Internal and Clinical Medicine
Medical Microbiology
Pathology
Physiology
Psychiatry
Clinical Modules for Physician Assistants
Medical Subject Review for Physician Assistants
PANCE/PANRE Certification Review – Updated July 2013
Dental Subject Review for NBDE Part I
Family Medicine Certification Review
General Pediatrics Certification Review
General Surgery Certification Review
Internal Medicine Certification Review
SPEX (Special Purpose EXamination)
Pharmacy Review (NAPLEX)
Supplemental Medical Sciences for Pharmacy
USMLE Step 1 Board Preparation
USMLE Step 1 Medical Subject Review
USMLE Step 2 CK Board Preparation
USMLE Step 2 CK Medical Subject Review
USMLE Step 3 Board Preparation
USMLE Step 3 Medical Subject Review

PubMed’s Secret Ingredient: Explosions

By Eric Rumsey, Janna Lawrence, and guest author Chris Shaffer, former Hardin librarian, now University Librarian, Oregon Health & Science Univ

Explosions are a powerful, built-in feature of PubMed that make it easy to search for clusters of related subjects. Because they’re so seamlessly incorporated into PubMed, it’s possible to search the database without having any knowledge of explosions. But to get the best results, it helps to understand how they work.

CardiovasDis67

The clip from the MeSH database to the left gives an idea of the hierarchical “tree structure” of explosions. When you search in PubMed for a MeSH term that’s at the top of a category, the search automatically includes all of the terms indented under it. So for instance, if you search in PubMed for Cardiovascular Abnormalities, the two terms indented under it are also included. The “+” sign after these terms indicate that they are explosions that have other terms under them, which are also included.

To see details of specific exploded terms, search the MeSH Database. (To see the page for Cardiovascular Diseases, in the example at left, click the graphic, or click here)

Much of the elegance of explosions is the ability to search large categories, and to move up and down “the tree” to try out more or less specific terms. For example, let’s say you’re interested in the subject of exercise and heart diseases. Combining those concepts in PubMed, you find there are more than 7000 citations. So, how many citations are there about the broader concept of cardiovascular diseases and exercise? With the power of PubMed’s automatic explosions, it’s easy to see that there are about double the number. And, of course, it’s easy to move the other direction in the tree, to do the search with specific terms and explosions anywhere in the hierarchy.

Another key reason explosions are so valuable is that articles are indexed only to the most specific MeSH term. An article on Cardiac Tamponade, for example, will only be assigned that term, and not the broader term Heart Diseases. Without explosions, it would not be found by searching for Heart Diseases. But because it’s in the Heart Diseases explosion, it is found.

Why “Secret Ingredient”?

We call explosions PubMed’s “Secret Ingredient” because they are very powerful but little-known and/or taken for granted. It wasn’t always this way – When the Medline database (which is what you’re searching in PubMed) was in its early days, in the 1980’s, explosions certainly were acknowledged to be a “big deal” – With the relatively low-powered computers of the time, explosions took big chunks of computer time, and were used with caution. With today’s computers, of course, this is only a distant memory, and, fortunately, no one needs to worry about using explosions.

A further reason that explosions have receded into the background is that, with the advent of Google-style simple search interfaces, PubMed has adopted the same sort of simple interface. This has had the effect of making people less aware of what PubMed is doing “under the hood.” With the simple, Google-like interface of PubMed, it’s natural to think that it works “just like Google.” But in fact it’s quite different – With only a bit of oversimplifying, the basic difference is that Google searching is purely computer-based and PubMed is based on human indexing. Humans actually read every article in PubMed, and assign 10-15 MeSH terms, which is what makes explosions possible.

How to search without an explosion

When you search for a subject in PubMed, the default is for it to explode the MeSH term that’s associated with the subject, and this is almost always what you want, since articles are indexed with the most specific term available. For example, an article about cardiac arrhythmias will be indexed as Arrythmias, Cardiac, and not to its broader heading, Heart Diseases. There may be occasions, however, when you only want the MeSH term at the top of the category, without subsidiary terms. The way to do that search, using the example discussed here, is to search for: Heart Diseases [mh:noexp]. Another way to do this is to click the box that says “Do not include MeSH terms found below this term in the MeSH hierarchy” on the MeSH Database display for Heart Diseases.

Anatomy.tv now available online from Hardin Library

AnatomyTV Launch PageHardin Library for the Health Sciences is excited to announce that Anatomy.tv is now available for our patrons!

Anatomy.tv is an internet-based anatomy tool provided by Stat!Ref which includes a complete set of 3D human models.

Anatomy.tv allows for manipulation and 360-degree rotation of virtual models, as well as filtering different layers of anatomical structure. Additionally, Anatomy.tv links to relevant text, clinical images, diagrams, scans, and videos. Supplementary information such as quizzes, MCQs, and patient information are all available for download.

To begin using Anatomy.tv, simply go to the Hardin Library website and select the tool from the Health Sciences Resources A-Z list.  Direct access is also available at http://purl.lib.uiowa.edu/AnatomyTV.

Please note that access to Anatomy.tv is limited to a set number of users, so if you encounter problems using this resource please feel free to contact Hardin Reference staff at 319-335-9151 or lib-hardin@uiowa.edu and we will provide assistance.

Plant-Based Foods – A Tricky PubMed Search

This article has been superseded by the following:
Plant-Based Foods – A Tricky PubMed Search – Revised 2016

**********************

By Eric Rumsey and Janna Lawrence

As discussed in an earlier article, searching for Food-Diet-Nutrition in PubMed is difficult because the subject is spread around in several different places in the MeSH classification system. In another article, we provide a way around this, which provides a broad set of search terms that can be used to search for the subject. An aspect of the subject, however, that cannot be put in a “package” that makes it possible to search together as a group is plant-based foods.

The Food cluster-explosion contains many specific foods, as MeSH headings, including some plant-based foods. A large proportion of all plant-based foods, however, are not in the Food cluster-explosion, but are only in Plants, and not in Food. These, of course, will not be retrieved by searching for “Food.” Adding to the confusion, some vegetables (but no fruits) are in both categories. Here are some examples:

Sweet potato is put under the MeSH term Ipomoea batatas. Its only place in the MeSH tree is in the Plants explosion:

Plants
   Angiosperms
      Convulvulaceae
         Ipomoea
            Ipomoea batatas

As noted above, this will not be retrieved by searching for “food.”

Kale (MeSH term Brassica), on the other hand, is included in both Plants and Food and so it will be retrieved by searching for “food”:

Plants
   Angiosperms
      Brassicaceae
         Brassica
Food
   Vegetables
      Brassica

The examples for sweet potato and kale bring to light another point of confusion, which is that terms in the Plants explosion are usually botanical names that are not recognizable to most people. A few examples (all of which are only in the Plants explosion but not in the Food explosion):

Grapes is Vitis
Strawberry is Fragaria
Okra is Abelmoschus
Kidney Beans is Phaseolus
Chocolate is Cacao
Turmeric is Curcuma

This is usually not a problem when searching for specific food plants, because when searching for a common name, it’s mapped to the botanical MeSH term (e.g. if you search for Grapes, it maps to Vitis). The problem comes if you want to browse the Plants cluster to pick out the edible plants from the many plants that are not edible, because only the botanical names are listed. The Rose family (Rosaceae) of plants, for example, has several edible species within it. There are 19 genera listed in MeSH in the family, and 6 of them have edible species. But to find them, you have to be able to pick out the genera with edible species (e.g. Malus, Prunus) from the others (e.g. Agrimonia, Alchemilla).

A caveat: There is an exploded MeSH term Plants, Edible, which might seem to be a good place to search for plant-based foods. Unfortunately, however, it’s of limited usefulness – The explosion contains only grain plants and a relatively small number of vegetables, and the term Plants, Edible itself is mostly used to index articles that are on the general concept rather than articles on specific types of edible plants.

A qualification: What we say here about the difficulty of doing comprehensive PubMed searches that include all specific plant-based foods applies to a lesser degree to other types of foods also. Looking, for example, at Meat in the MeSH classification of Food, there are no headings for specific types of meat (e.g. beef, pork), so they’re all indexed under the broader term Meat. The reason the problem is so much more complicated for plant-based foods is because there are so many of them, and also because the line between plant-based foods and plant-based medicines is often fuzzy.

Advice on searching for plant-based foods

[9.4.14. For comprehensive searches on plant-based foods, see the hedge in our newly published article]

Consider combining Plants with your subject – The Plants explosion in MeSH is very large, containing hundreds of plant species. It’s organized by taxonomic relationships, which makes it hard for a non-botanist to browse. But it’s useful to combine with other subjects in searching, because it’s so comprehensive. The main drawback in searching it is that in addition to plant-based foods, it also has many plant-based drugs, which you’ll have to sift out from the food articles.

If you want to restrict your search to plant-based foods, instead of foods in general, you can combine the Plants explosion AND the Food-Diet-Nutrition hedge search discussed in a previous article.

If you combine your subject with the hedge in the previous article and it misses articles on particular plant-based foods, search specifically for those. If you do a search for food and migraine, for example, and your search doesn’t pick up specific foods that you know have been associated with migraine (e.g. chocolate), combine those foods specifically with migraine.


The Plant-Based Foods category has links to additional articles we’ve written on searching plant-based foods in PubMed.

Keep up with your favorite journals using BrowZine!

The UI Libraries now subscribes to BrowZine, an app that makes it easier to read your favorite journals on your iPad or Android tablet.  Because BrowZine knows which journals the UI Libraries subscribe to, it’s easy to find your favorite journals by title or subject and even to create a personal bookshelf of your favorite journals.  Individual articles can also be saved for reading later. Articles found in BrowZine can also be synced with Zotero, Dropbox, or other services.

Download BrowZine onto your device from the Apple App Store, Google Play, or the Amazon store.  Launch BrowZine, and select University of Iowa from the dropdown list.  You will then be asked to log in with your HawkID and password.  (You should only have to do this once.)  From there, BrowZine will know what journals the library has.  Almost all of the library’s online journals are available; if you find one that is not, please contact us.

You can watch a 2-minute video about BrowZine at http://vimeo.com/52663192.  If you have questions, please feel free to contact Hardin Reference staff at 319-335-9151 or lib-hardin@uiowa.edu.