In Pictures: Modern Chinese Vegetarian Dishes

Sandwich with Sprouted Quinoa, Cheese and Cucumber


2 tbsp light cream cheese
1 tsp chopped fresh dill
4 slices cucumber
2 tbsp sprouted quinoa
1/2 tsp balsamic vinegar
2 rings sliced red onion
1 slice Gouda cheese
2 slices rye or whole wheat bread


  1. Combine the cream cheese and dill and spread on each slice of bread.
  2. Place the cumcumber on one side.
  3. Toss the sprouted quinoa in the vinegar and place on top of the cucumber.
  4. Add the red onion and top with Gouda cheese and the remaining slice of bread.

Makes 1 serving.

Source: Quinoa 365

Food Giants Announce Major New Labeling Initiative

Tamar Haspel wrote . . . . .

Some of the largest food manufacturers and grocers announced today an initiative to provide consumers with “instantaneous access” about detailed information on thousands of products through their smart phones. Shoppers, using their smartphones, will simply scan a code, called a QR code or barcode, according to the initiative by the Grocery Manufacturers Association.

More than 30 food giants, including Pepsi, ConAgra, Hormel, Campbell Soup, Land O’Lakes, Coca-Cola, Nestle, Hershey, and General Foods, have signed on to participate in the SmartLabel Initiative. The SmartLabel will include ingredients, allergens, animal welfare, environmental policies, and, perhaps the most controversial attribute, whether the food contains genetically modified organisms (GMOs).

The information will also be available on the web and, in some cases, at retailers’ customer service desks, so consumers without smartphones also have access to the information. The technology will be available on 30,000 products by the end of 2017. The announcement comes on the heels of the FDA’s approval last month of the first genetically modified animal, a fast-growing salmon, a move that drew many calls for labeling, including from the editorial board of the New York Times.

Proponents of mandatory GMO labeling do not see SmartLabels as a solution. Scott Faber, executive director of Just Label It, believes the QR-code based information is not sufficient to give consumers the information his organization believes they need. “You walk into the market and you see this weird funny box,” he says, describing the situation consumers will find themselves in. “There’s no wording to tell you to scan this for GMO information, and the information will not be easily available to consumers without a smartphone.” According to the Pew Research Center, about one-third of Americans don’t have a smartphone,and that group is older, less educated, and less affluent than those who do.

Faber is also concerned that the information on GMOs will be hidden behind a tab marked “Other,” so it will not be immediately clear to buyers that the information is available.

Faber’s most serious problem with the initiative is that “this is not a proposal about giving consumers information. This is about providing cover to preempt mandatory labeling,” an issue being debated at both the federal and state level.

GMA executive vice president Denzel McGuire points out that the information will be available on the web, which most Americans have access to, and says that putting the GMO issue behind the “Other” tab was a response to congressional concern that genetic engineering not be stigmatized. “If we made it more prominent than the other attributes, that would be stigmatizing.” She also points out that, if GMO labeling groups want this information in the hands of consumers, they could help get the word out on its location.

The GMA’s move shifts the question about GMO labeling from “should we or shouldn’t we” to “mandatory on the box or voluntary in the code.” It essentially takes the no-labeling position off the table. And that same question – box or code – will have to be answered for each new issue that attracts consumer interest.

Greg Jaffe, director of biotechnology for the Center for Science in the Public Interest (CSPI) says that mandatory on-the-box labeling should be reserved for “really important information, most critical for consumers, such as allergens, or food safety, or nutrition.”

Charlie Arnot, CEO of the Center for Food Integrity, an industry group advocating for transparency, agrees: “I appreciate that some want GMO information on the box,” he says, “but there are people just as passionate about workers’ rights, animal care, environmental impact. There isn’t enough real estate on any label to address every concern a consumer might have.”

Source: Time

Read more at GMA

New SmartLabel™ Initiative Gives Consumers Easy Access to Detailed Product Ingredient Information . . . . .

Video: The Future of Fake Meat

In the future, could Tofurkey and other fake or lab-grown meat products give the world more sustainable (and equally delicious) alternatives to beef, chicken and turkey?

In this video, find out how food chemists and other scientists are working to make fake meat taste as good as the real thing.

Watch video of American Chemical Society at You Tube (3:43 minutes) . . . . .

Male and Female Brains

Steven Novella wrote . . . . .

Is it more accurate to say that male and female brains are generally the same or categorically different? This question has been somewhat of a controversy, both scientifically and culturally. A new extensive comparison of male and female brains with fMRI scans hopes to provide a definitive answer.

First for some background, we need to address the basic question of how we even approach or address the issue of categorization. Nature is fuzzy and complex, but humans tend to prefer neat and tidy categories to simplify the task of keeping track of everything, and even to help our understanding. There is therefore frequently a conflict between our desires and reality when it comes to creating categories.

The Pluto controversy is a good example of this, one which was surprisingly heated despite the fact that there are no real social or political issues at stake. There is no objective and definitive line between planets as solar system objects and other planet-like objects. Astronomers had to come up with some rules, rules that are unambiguous to apply. Ideally, such rules of categorization will reflect some underlying phenomenon, in this case, for example, how planets form.

Categorizing life on Earth has been very challenging, and our systems have changed over time as our understanding of biology has changed. The latest system, called cladistics, classifies creatures entirely based on their evolutionary relationships. Some biologist disagree that this is the best system, arguing that morphological similarity should count also. Birds, for example, cladistically may just be one small subgroup of dinosaurs, but some would argue they are different enough to warrant their own category.

When we get to categories that have huge social and political implications, fighting over categories spreads beyond the scientific journals and meetings. The three that most readily come to mind are sex, gender, and race. I often find that such questions are approached in black and white terms – does race exist, for example. I don’t think, however, that phrasing the question that way is helpful.

The problem with trying to argue that men and women are the same, or that race is just a social construct with no biological reality, is that such absolute positions are difficult to rectify with our common experience. This can lead to rejection by some of the underlying point because it sounds like political correctness rather than a scientific conclusion.

A better approach is to ask several more specific questions. The first is, are there objective categorical differences between two or among three or more alleged groups? A categorical difference is a characteristic that is present in all of one group and none of the other, without any overlap. You can also ask, how frequent are exceptions to apparent categorical differences?

For other traits you can ask if there is a statistical difference, is there any overlap, and how likely are members of various alleged groups to have specific traits. This is where everything gets fuzzy, and it essentially becomes impossible to answer the category question with absolutes.

For example, we can look at biological sex in general. Humans mostly are sexually dimorphic, with two distinct categorical sets of genitalia. The genitalia take one of two developmental pathways, with no overlap. There are a minority of people, however, with ambiguous genitalia, usually associated with known hormonal, genetic, or developmental anomalies. Genitalia are not a continuum – there are two distinct groups with some exceptions in the middle.

If we look at a trait like height, however, we see a different picture. Men on average are taller than women, but there are tall women and short men. There is tremendous overlap along a continuum. This is not a categorical difference but a statistical difference.

Another way to look at the difference between categorical and relative difference is to ask this question: If you know someone is male, can you predict their genitalia? Can you predict their height? The answer to the former question is mostly yes, and to the latter mostly no.

The question the researchers of the current study were asking is this – are male and female brains categorically different like genitalia, or perhaps only statistically different like height, or perhaps not different at all?

They looked at four data sets of MRI scans and fMRI scans of brains, including over 1,400 samples. They looked at specific anatomical structures in the brain in which size was measured, and at connections or pathways in the brain for robustness. Lead author Daphne Joel is quoted as saying:

“We show there are differences, but brains do not come in male and female forms. The differences you see are differences between averages. Each one of us is a unique mosaic.”

They found that the differences were statistical, and not categorical. If you look at any one region or pathway in the brain, there were statistical differences between male and female. However, there was a tremendous amount of overlap. Further, as with height, knowing a person’s sex does not allow you to predict any one trait.

Further, individuals rarely had all male or all female traits. Across the four data sets they found that 0-8% had traits consistently of one sex, while 23-53% had a combination of male-end and female-end traits. Individuals are mosaics, with only statistical differences between males and females.

This does not mean that males and females are the same, or that there are no differences. It does mean that individuals are individuals. People are not mentally defined by their sex.

The paper did not address the issue of whether the statistical differences seen were due to inherent or cultural causes. I suspect the answer is both, for various traits. It seems, for example, that testosterone makes males more aggressive. However, a preference for the color pink appears to be a minor and entirely cultural difference.


What are we to make of the results of this study? To summarize my own approach, I think it is counterproductive and not scientifically accurate to deny that there are real differences between identifiable categories of people.

At the same time it is important to recognize when those differences are only statistical with large overlap. What this means is that in such cases it is not scientifically justifiable to treat individuals as members of a group. Membership in a group does not predict what traits the individual will have. It is therefore best to treat people as individuals.

From an ethical point of view this also works. The basic principle of respect for everyone’s individual dignity demands that people be generally treated as individuals. It just so happens that science supports that position also.

I think the medical profession has struck an appropriate balance. For categorical differences, like male-female biological difference, we have no problem treating people generally as members of a category. There is an entire medical specialty dedicated to female medicine (OBGyn). This is not an ethical or scientific problem.

Otherwise we treat people as individuals, but we may use statistical information to inform our decisions. This is because medicine is the practice of taking statistical group data and then applying it to individuals, knowing that group data does not always predict individual response and we have to individualize treatment as we go.

Genetic heritage, for example, is used to predict the probability of certain diseases or even the response to certain treatments. We don’t ignore race or sex in medicine, because these categories have a statistical reality that informs our very important practical decisions. But we recognize that these categories don’t always predict individual traits. Patients – and all people – still need to be treated like individuals.

Source: Neurologica Blog