Plant-Based Foods – An Inclusive PubMed Search

By Eric Rumsey and Janna Lawrence

In our earlier article on searching for plant-based foods (PBF) in PubMed, we suggested that a quick way to search the subject is to combine the MeSH Plants explosion AND our Food-Diet-Nutrition (FDN) hedge. This works quite well, especially for citations after 2002. In that year the Plants explosion was greatly expanded by the addition of several hundred new MeSH plant names. Before that, articles on specific plants were indexed inconsistently. Sometimes they were put under the plant family name, in which case they were included in the Plants explosion, and in other cases they were indexed under other terms like Vegetables, Fruit, or Plants, Edible, that are not in the Plants explosion.

In order to do the most inclusive search for plant-based foods, including citations before 2002, we have created two hedges, to be used for all the years in PubMed. These hedges include other MeSH terms and text-words, to supplement the plant-name search strategy that works well after 2002. We have done fairly thorough testing of the two hedges, and we recommend the first hedge for most searches. It uses MeSH terms, and it emphasizes “precision,” which means that it gets somewhat fewer citations, but the citations are more likely to be on target. For both of the hedges, we’ve combined them in an OR search with the simple “Plants AND FDN” hedge search mentioned above.

Here’s the first hedge, with the newly added terms in boldface:

(Vegetables [mesh] OR Fruit [mesh] OR Cereals [mesh] OR Plants, Edible [mesh] OR Soybeans [mesh] OR Dietary Fiber [mesh] OR Flour [mesh] OR Bread [mesh] OR Diet, Vegetarian [mesh] OR Nuts [mesh] OR Condiments [mesh] OR Vegetable Proteins [mesh]) OR (Plants [mesh] AND (food OR foods OR beverages OR diet OR dietary OR vitamin OR vitamins OR nutrition OR nutritional OR nutrition disorders OR food industry OR nutritional physiological phenomena OR dietary fats OR dietary proteins OR feeding behavior))

[Number of citations, 8.19.14 - 265,126]

To use this search, click this link. You can also copy the text above and paste it into the PubMed search box. If you have a personal “My NCBI” account in PubMed, the hedge search can be saved for later use, or it can be made into a search filter. For information on setting up and using saved searches, see here; for more information on filters, see here.

Commentary on terms in this hedge (If the “Year introduced” is not given, the term has been in MeSH since its launch in 1966):

  • Vegetables [mesh]
    Citations: 84411
    An explosion that includes about 25 specific vegetables, including Onions, Soybeans, Daucus carota, and Solanum tuberosum. This is a relatively small proportion of all vegetables, which are indexed with their species or family name, in the Plants explosion.
  • Fruit [mesh]
    Citations: 57179
    Notably, this is NOT an explosion. All particular fruit types are indexed with their species or family name, in the Plants explosion.
  • Cereals [mesh]
    Citations: 73516
    An explosion that includes 8 cereals, including Avena sativa, Triticum and Zea mays. This is an important group, since it includes the world’s staple foods–wheat, rice, and corn.
  • Plants, Edible [mesh]
    Citations: 38945
    An explosion that includes several terms elsewhere in this hedge that get more citations when they’re searched separately. The term Plants, Edible by itself gets 5402 citations.
  • Soybeans [mesh]
    Year introduced: 1986
    Citations: 19284
    An explosion that includes Soy Foods, Soy Milk, and Soybean Proteins.
  • Dietary Fiber [mesh]
    Year introduced: 1982(1977)
    Citations: 13468
  • Flour [mesh]
    Citations: 3570
  • Bread [mesh]
    Citations: 3115
  • Diet, Vegetarian [mesh]
    Year introduced: 2003(1963)
    Citations: 2537
  • Nuts [mesh]
    Citations: 2074
  • Condiments [mesh]
    Citations: 1945
    An explosion that includes Spices.
  • Vegetable Proteins [mesh]
    Year introduced: 1975
    Citations: 1515

Here’s the second hedge, with the newly added terms in boldface:

(fruit OR fruits OR vegetable OR vegetables OR cereal OR cereals OR spices OR condiments OR flour OR nut OR nuts OR vegetarian OR soy OR soybean OR soybeans OR bread) OR (Plants [mesh] AND (food OR foods OR beverages OR diet OR dietary OR vitamin OR vitamins OR nutrition OR nutritional OR nutrition disorders OR food industry OR nutritional physiological phenomena OR dietary fats OR dietary proteins OR feeding behavior))

[Number of citations, 8.19.14 - 332,351]

To use this search, click this link, or see instructions above with first hedge.

Most of the words used in this hedge are text-word versions of the MeSH terms used in the first hedge. Since this emphasizes “recall” instead of “precision,” it gets more citations than the first hedge. But the citations are less likely to be relevant. We looked closely at citations using the two hedges, and it was easy to see the lesser relevancy of the citations in the second hedge. Most of these, of course, are retrieved because they mention words that are in the abstract (e.g. fruit, vegetables) but which are not assigned as MeSH terms.

A word about searching for older citations

When we first realized that most of the plant name MeSH terms were only introduced in 2002, it seemed like a serious problem. However, as we’ve looked back retrospectively, we’ve come to see that there really wasn’t much research attention given to the subject in the earlier days of MEDLINE, especially before about 1990.

We’ve done detailed work to study this, but in this article we’ll just give a couple of anecdotal examples of what we’ve found. We looked at the number of citations that contain the word “fruit” since 1968, and found that this stayed flat, at about 400 mentions per year, until about 1990. It’s grown fast since then, and in 2013, the word is in about 8000 citations. In another example, we found that there are 70 articles in all of PubMed that have “sweet potato” in the title, and are on human subjects. All but three of these are after 1992; zero citations from 1980-1992 contain the words in the title. So, if it seems like the hedges in this article aren’t finding many citations before 1990, it’s probably because there just aren’t many to be found.

Things improve in the 1990s. It appears, from our retrospective examination of citations on FDN, that as the volume of research on the subject increased, NLM gradually improved the quality of MeSH indexing to accommodate it. The coverage of more prominent plant families improved, and the application of existing FDN MeSH terms became more consistent. So in the 1990s, even before the mass introduction of new MeSH plant terms in 2002, FDN indexing and retrieval was improving.

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PubMed Food Problem: Red Meat

By Eric Rumsey and Janna Lawrence

As we’ve discussed before, searching for “red meat” in PubMed is difficult because the subject is poorly covered in the MeSH vocabulary. Not only is there not a term for “red meat,” but there are also no MeSH terms for specific kinds of red meat (beef, pork, etc.). There is only the one all-inclusive MeSH term Meat, which includes all kinds of meat, as well as fish and poultry. So this is a rare case in PubMed in which MeSH is essentially useless. The only way to do a thorough search is to use text words that include the phrase “red meat” or that contain specific types of red meat – e.g. “red meat” OR beef OR pork… [etc]

The problem of searching for red meat has returned to our attention recently for two reasons. One is that the subject continues to be in the news. Last winter when we wrote, it was getting attention because red-meat nutrient carnitine was reported to be linked to heart disease. And recently red meat has been back in the news because it’s been reported that tick bites can trigger an allergy to red meats.

The other reason we’ve been thinking about red meat is that, coincidentally, our library has recently gotten a subscription to Embase, which a European-based medical literature database that’s the main alternative to PubMed/MEDLINE. Of course, the first thing we did with new access was to compare the indexing, and especially the explosions, in Embase to PubMed for FDN subjects. We have found several cases in which Embase is better. One case in which it’s clearly better is red meat.

Here’s the explosion in Embase:

Red Meat
… Beef
… Lamb Meat
… Mutton
… Pork
… Rabbit Meat
… Veal
… Venison

This can’t be used directly in PubMed, of course, but at least it gives and idea of specific meats to search in PubMed as text words.

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Twitter Redesigns Profiles, Adds Engagement Features

Twitter has rolled out a new design for users’ profile pages. The important changes are:

  • Graphics are emphasized, with much larger header images
  • Tweets that are getting more “engagement” are in a larger font. The algorithm used to measure a tweet’s engagement is not revealed by Twitter. Engagement appears to be based on the number of retweets, mentions, favorites, and clicks. Apparently large-font tweets only happen on desktop Twitter, not on mobile.
  • You can choose a tweet that you want to emphasize, to be “pinned” to the top of your profile.

More information from Twitter on the new profile:
Coming soon: a whole new you, in your Twitter profile

To see further commentary, search for appropriate terms in Google and Twitter. For instance:

To keep up with what’s happening at Univ Iowa and with Twitter, follow @HardinLib and @EricRumsey.

 

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PubMed Food Problem – Olive Oil

By Eric Rumsey and Janna Lawrence

[Check out additional articles on PubMed & Plant-Based Foods]

Olive oil as a healthy food is a highly popular topic among consumers. It’s also popular among researchers, as shown in a list of the 100 most popular research articles of 2013, by the Altmetric site, in which the number two ranking article is a comparison of olive oil and nuts for prevention of cardiovascular disease, in NEJM. This article shows a major problem with the MeSH indexing of olive oil. Even with its trending popularity, olive oil does not have its own MeSH term. In the NEJM article, and in most articles on olive oil, the only MeSH term that corresponds with olive oil is Plant Oils. This is a problem because Plant Oils is not in any food-diet-nutrition (FDN) explosion, and is therefore not retrieved by broad searches for FDN.

Fortunately, articles on olive oil are often picked up by broad FDN searches because they have other FDN-related MeSH terms. But in many cases, they are not. Here are some examples of articles with olive oil in the title that are not retrieved using our broad FDN hedge because they contain no MeSH terms or text words relating to food, diet or nutrition:

As we’ve discussed previously, most plant-based foods are difficult to search in PubMed because the MeSH terms for them are in the Plants explosion and not in any FDN explosion. Notably, olive oil has a different problem. It’s like other plant-based foods in not having a MeSH term that’s in an FDN explosion. But instead of being in Plants, its MeSH term, Plant Oils, is in the Chemicals and Drugs explosion.

There’s another baffling quirk in the MeSH indexing of olive oil. Although it doesn’t have its own MeSH term, there are MeSH terms for several other dietary oils in the Dietary Fats explosion (which, of course, is retrieved in broad FDN searches). These other dietary fats are Cod Liver Oil, Corn Oil, Cottonseed Oil, Safflower Oil, Sesame Oil, and Soybean Oil. None of these has close to the number of citations as there are on olive oil. We searched for each of these oils as a phrase in the title, and compared this with olive oil, and found, remarkably, that the total of all of these other oils combined is about the same as the number for olive oil by itself. So why is there not a MeSH term for olive oil?!

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PubMed Food Problem: Cranberry & Cranberries

By Eric Rumsey and Janna Lawrence

[Check out additional articles on PubMed & Plant-Based Foods]

Part of the problem in searching for food in PubMed is that it’s often the case that there’s a fuzzy border between between food and medicine.   A food that is enjoyed for its taste and general nutritional benefits may have properties that make it therapeutic for specific health conditions. A good example of this is cranberries, and cranberry juice, which may have benefits for prevention of urinary tract infections.

As with most plant-based foods, in MeSH indexing, cranberry is in the Plants explosion, and it’s not in any food, diet or nutrition (FDN) explosion. Fortunately, most articles on cranberries and cranberry juice are assigned some FDN indexing terms so that they are retrieved in broad FDN searches. Articles on cranberry juice are often under Beverages, and some articles on cranberries are under Fruit or Dietary supplements.

To show how this works in PubMed, we searched for cranberry or cranberries in the article title, limited to human, and retrieved 322 articles. We then combined this with our broad hedge search to get all articles that contain food, diet or nutrition MeSH terms or text words. This retrieved 255 articles — 79% of the cranberry/cranberries articles, which is a fairly good retrieval. But still, it’s certainly notable that there are 67 articles that are not retrieved, many of which appear to be very much on target, that don’t contain any FDN MeSH terms or text words. Here are some examples:

As we mentioned above, plant-based foods are tricky to search in PubMed because the name of the food plant is usually only in Plants, and not in any FDN explosion. The five articles above are all indexed under Vaccinium macrocarpon, the taxonomic name of cranberry, which is in the Plants explosion. So if you were searching for articles on urinary tract infections and plant-based foods, a strategy that would retrieve these articles would be to combine Urinary Tract Infections AND Plants.

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Is Chocolate A Food? A Problem In PubMed

By Eric Rumsey and Janna Lawrence

[Check out additional articles on PubMed & Plant-Based Foods]

As we’ve written, searching for food-related subjects in PubMed is difficult because of the way the MeSH system is organized. Plant-based foods are especially difficult because in most cases they are treated mainly as plants rather than food.

One result of treating plant-based foods as plants is that the MeSH term is usually the botanical plant name; in the case of chocolate it’s Cacao. This is usually not a serious problem when searching for specific substances because the common food name maps to the botanical MeSH term.

A more serious consequence of treating plant-based foods as plants instead of foods is that they are usually not in any food-related explosion, but only in the Plants explosion. So the only occurrence of chocolate (Cacao) is here:

Plants
   Angiosperms
      Sterculiaceae
         Cacao

The reason this is a problem is because articles on chocolate/Cacao will not be retrieved in a search for Food. So, for example, if you do a general search for food-related causes of migraine, you will not retrieve this article:

Chocolate is a migraine-provoking agent
Journal: Cephalalgia
http://www.ncbi.nlm.nih.gov/pubmed/1860135

This is not retrieved by searching for food because Cacao is not in the Food explosion. More broadly, however, it’s also not retrieved with the comprehensive Food-Diet-Nutrition hedge that we’ve discussed previously, which includes text-words as well MeSH terms and explosions.

Here are several other articles on health and medical aspects of chocolate that are not retrieved by our broad Food-Diet-Nutrition hedge:

If chocolate were the only case of a plant-based food that is not retrieved in a broad PubMed search for food-related topics, it would be a trivial matter. But that’s far from being the case. There are many plant-based foods that have the same problem in PubMed. We will be writing on several of these foods in the next few months, so keep an eye on this space!

 

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Medical & Nursing Journals – A Twitter List

By Sarah Andrews and Eric Rumsey

Many medical and nursing journals now use Twitter. On their Twitter sites, they share links to journal articles and sometimes other news items in the field. We have made a Twitter list with 116 of these journal sites:

https://twitter.com/HardinLib/lists/journals

The base of our list is the National Library of Medicine’s list of Core Clinical journals. There are 119 titles in that list, and we were able to find Twitter feeds for about 75 of them. The other Twitter sites on our list we found in Laika Spoetnik’s Twitter journal list and from Googling likely word combinations.

Not all tweets are for journal articles. The proportion of tweets that are journal articles, as opposed to other news items, varies in different journal feeds.

 

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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!]

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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.
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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.

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