Name: measuring oral fatty acid thresholds, fat perception, fatty food liking, and papillae density in humans
Uploaded: 2014-06-04T13:00:00
Duration: 10 min 29 s
Description: Watch this Scientific Journal Video about Measuring Oral Fatty Acid Thresholds, Fat Perception, Fatty Food Liking, and Papillae Density in Humans at JoVE.com

The authors would like to acknowledge the support of the Australian National Health and Medical Research Council and Deakin University. The work performed at the Deakin University Sensory laboratory was supported by the National Health and Medical Research Council Grant (1043780)(RSJK) and Horticulture Australia Limited (BS12006)(RSJK).

The following techniques have been approved for use by the Deakin University Human Research Ethics Committee.
1. Demographics and Anthropometry
<ol>
	<li>Record demographic information from participants, including date of birth and gender.</li>
	<li>At baseline (and other study points if temporal study design) take height and weight measurements. Ensure that participants have taken off shoes, heavy jackets or other clothing items, and have removed any heavy items from their pockets.
	<ol>
		<li>Measure participant&#39;s height using a stadiometer. Record measurements to the nearest cm.</li>
		<li>Weigh participants using dedicated scales. Record weight to the nearest g.</li>
		<li>Calculate BMI using the equation:&#160;weight (kg)/height2&#160;(m2). From this, participants are categorized according to standard BMI definition values; healthy 18.5-25 kg/m2, overweight 25-30 kg/m2 or obese &#62;30 kg/m2 27.</li>
	</ol>
	</li>
</ol>
2. Producing Samples for Oral Fatty Acid Threshold Assessment
<ol>
	<li>Use non-fat UHT milk as the base for fatty acid taste threshold assessment. Product can be purchased and stored in bulk if necessary, and will keep unopened for up to 6&#160;months or until the product has reached its expiry. Prepare 2&#160;types of vehicles: vehicle with added fatty acid and a control vehicle. The volume of solutions prepared for testing will depend on participant number. The following protocol provides typical amounts&#160;for&#160;2&#160;participants.</li>
	<li>Prepare a base milk solution to use for both the control and fatty acid vehicle by placing 5% w:v food grade gum arabic (e.g., 100 g per 2 L of milk) into a 3&#160;L glass beaker. If required, hydrate gum prior to use (this will vary depending on gum manufacturer).</li>
	<li>Add 0.01% w:v EDTA to the gum to prevent oxidation (e.g., 200 mg per 2 L of milk).</li>
	<li>Allocate approximately 1 L of non-fat milk per participant (e.g., for 2&#160;participants, use 2 L milk) and pour into beaker.</li>
	<li>Using a laboratory grade mixer with emulsor screen, homogenize the solution at 12,000 rpm for 2 min. Set solution aside.</li>
	<li>Prepare the fatty acid solutions using food grade C18:1. Oxidation can be assessed through gas chromatography if necessary.</li>
	<li>Prepare a series of 13 variants of the fatty acid vehicle (UHT non-fat milk) with increasing concentrations of C18:1 (0.02, 0.06, 1, 1.4, 2, 2.8, 3.8, 5, 6.4, 8, 9.8, 12, and 20 mM/L). To do this, label 250-ml&#160;glass beakers with each concentration.</li>
	<li>Add 5% liquid paraffin to each beaker (e.g., 5 ml&#160;paraffin per 100 ml&#160;of milk solution).</li>
	<li>Based on C18:1 concentration, add the appropriate amount of C18:1 to each beaker (see Table 1).</li>
</ol>
<table border="1" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>C18:1 concentration (mM)</td>
			<td>&#956;l/100 ml</td>
		</tr>
		<tr>
			<td>0.02</td>
			<td>0.56</td>
		</tr>
		<tr>
			<td>0.06</td>
			<td>1.9</td>
		</tr>
		<tr>
			<td>1</td>
			<td>31.5</td>
		</tr>
		<tr>
			<td>1.4</td>
			<td>44.1</td>
		</tr>
		<tr>
			<td>2</td>
			<td>63.1</td>
		</tr>
		<tr>
			<td>2.8</td>
			<td>88.4</td>
		</tr>
		<tr>
			<td>3.8</td>
			<td>119.9</td>
		</tr>
		<tr>
			<td>5</td>
			<td>157.8</td>
		</tr>
		<tr>
			<td>6.4</td>
			<td>202</td>
		</tr>
		<tr>
			<td>8</td>
			<td>250</td>
		</tr>
		<tr>
			<td>9.8</td>
			<td>309</td>
		</tr>
		<tr>
			<td>12</td>
			<td>380</td>
		</tr>
		<tr>
			<td>20</td>
			<td>631.2</td>
		</tr>
	</tbody>
</table>
Table 1.&#160;Example C18:1 concentration per 100 ml&#160;solution. Increasing concentrations (&#181;l/L) of C18:1 are used to prepare the series of 13 emulsions for oral fatty acid threshold testing.
<ol start="10">
	<li>Following use, fill the C18:1 container with N2 to minimize oxidation and store below 4 &#176;C.</li>
	<li>Add the base milk solution to each fatty acid beaker&#160;to a total volume of 100 ml.&#160;Set aside.</li>
	<li>Using the remaining base solution, prepare the control vehicle. In a 2&#160;L glass beaker, add 5% of the remaining volume in liquid paraffin (e.g., 35 ml&#160;liquid paraffin in a final volume of 750 ml) together with the remaining base solution and homogenize for 30 sec per 100 ml&#160;of liquid.</li>
	<li>Homogenize the control vehicle for 30 sec per 100 ml. This step is conducted prior to the fatty acid solutions to prevent contamination with C18:1.</li>
	<li>Homogenize each fatty acid vehicle, beginning with the lowest concentration for 30 sec per 100 ml.</li>
	<li>Sanitize the homogenizer both prior to and following testing.</li>
	<li>As the homogenization process can raise the temperature of the solutions, check temperature of control and C18:1 samples with a thermometer. Serve all samples at RT (20 &#176;C).</li>
	<li>Milk samples must be freshly prepared on the same day as testing. Taste each solution prior to testing to assess freshness and suitability. 
	Note: Depending on volume required, solution preparation will take a minimum of 60 min.</li>
</ol>
3. Oral Fatty Acid Threshold Testing
<ol>
	<li>Ensure that participants have refrained from eating or drinking (including coffee, gum, mouthwash, etc.) for at least 1&#160;hr prior to testing.</li>
	<li>Minimize non-taste cues by conducting testing under red lighting with participants wearing nose clips.</li>
	<li>Use the ascending forced choice triangle procedure to determine oral fatty acid thresholds. Label 30-ml&#160;plastic portion cups with a three-digit identification number. Provide each participant with a set of three 20-ml&#160;solutions in random order; two control vehicles and one fatty acid vehicle with the lowest concentration of C18:1 (0.02 mM).</li>
	<li>To determine a participant&#39;s oral fatty acid threshold, instruct the participant to taste each solution from left to right and expectorate into a sink. Ask participants to not swallow the samples.</li>
	<li>Ask the participant to identify which of the 3&#160;samples is &#39;odd&#39; or &#39;different&#39; and if they are unsure, they must guess (forced choice).</li>
	<li>Have participants rinse their mouth with deionized water after each set of samples.</li>
	<li>If correctly identified, provide the participant with a second set of 3&#160;solutions (2&#160;control and 1&#160;fatty acid solution in random order) with the same fatty acid concentration. If incorrectly identified, provide the participant with a second set of 3&#160;solutions, but with the next highest concentration of C18:1 (0.06 mM).</li>
	<li>Continue this procedure until the participant is able to correctly identify the &#39;odd&#39; sample 3x in a row at the same concentration. The concentration at which they are able to correctly identify the &#39;odd&#39; sample is recorded as the participants C18:1 detection threshold. See Figure 1 for a graphical representation of this process.</li>
	<li>Based on detection threshold, characterize participants as hypersensitive, or hyposensitive to C18:1. In line with previous literature, hypersensitive individuals can detect C18:1 at concentrations &#60;3.8 mM, while hyposensitive individuals require concentrations &#62;3.8 mM. 
	Note: Depending on the number of incorrect answers, the testing procedure can take between 10-30 min to complete.</li>
</ol>
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig1highres.jpg" src="/files/ftp_upload/51236/51236fig1.jpg" /> 
Figure 1.&#160;Ascending forced choice triangle procedure used for determining fatty acid detection thresholds. Participants are provided with three solutions (two control solutions and one C18:1 solution at a given concentration) and asked to identify the &#39;odd sample&#39;. If correct, participants are given a second set of samples with the same C18:1 concentration. If incorrect, the participant is provided with another set of samples with a higher concentration of C18:1. This procedure continues until three &#39;odd&#39; solutions are correctly identified at a given concentration. This point is deemed the individuals &#39;fatty acid detection threshold&#39;.
4. Fat Ranking Task
This task involves participants tasting four samples of instant custard, each with different fat contents (0, 2, 6, and 10%) and ranking them in order of perceived ascending fat concentration.
<ol>
	<li>Prepare 1&#160;batch of custard using non-fat instant vanilla custard powder according to packet instructions. Mix 2 tablespoons custard powder, 1 tablespoon&#160;sugar, and 2 cups&#160;non-fat milk in a microwave safe bowl. If the suggested product is unavailable, this may be substituted with a similar non-fat instant product (e.g., cook and serve custard).</li>
	<li>Using high power, heat the mixture using a 1,400 W microwave in 30 sec intervals for a total of approximately 5 min, or until thick. This may vary depending on the brand of custard and the wattage of the microwave used. Allow custard to cool.</li>
	<li>Label four 500-ml&#160;kitchen bowls (or similar) with fat percentages.</li>
	<li>Divide the custard into 4&#160;separate 100-g batches.</li>
	<li>Add 0, 2, 6, and 10% vegetable oil to each bowl to achieve the desired fat content (e.g., in a 100 g batch, add 0 ml, 2 ml, 6 ml, and 10 ml vegetable oil to achieve respective fat percentages) and combine. Stir each sample well to ensure all ingredients are completely amalgamated.</li>
	<li>Label four 30-ml plastic portion cups with randomized three-digit numbers. Fill the portion cups with 20 g of each custard (1&#160;type of custard per cup).</li>
	<li>Refrigerate samples prior to testing and serve cold (4 &#176;C).</li>
	<li>Carry testing out under red lights to minimize visual cues.</li>
	<li>Have participants taste, swallow and rank the 4&#160;custards from perceived lowest to highest fat content and receive a score out of 5&#160;depending on their responses.</li>
	<li>Scoring for this task is shown in Table 2. 
	Note: Approximate preparation time for the custard samples is 30 min. The fat ranking task should take no longer than 10 min to complete.</li>
</ol>
<table align="left" border="1" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td>Ranking order</td>
			<td>Score</td>
		</tr>
		<tr>
			<td>0, 2, 6, 10</td>
			<td>5</td>
		</tr>
		<tr>
			<td>2, 0, 6, 10</td>
			<td>4</td>
		</tr>
		<tr>
			<td>0, 2, 10, 6</td>
			<td>3</td>
		</tr>
		<tr>
			<td>0, 6, 2, 10</td>
			<td>2</td>
		</tr>
		<tr>
			<td>1, 6, 10, 2</td>
			<td>1</td>
		</tr>
		<tr>
			<td>6, 0, 2, 10</td>
			<td>1</td>
		</tr>
		<tr>
			<td>2, 10, 6, 0</td>
			<td>1</td>
		</tr>
		<tr>
			<td>2, 6, 0, 10</td>
			<td>0</td>
		</tr>
		<tr>
			<td>6, 2, 10, 0</td>
			<td>0</td>
		</tr>
		<tr>
			<td>0, 10, 2, 6</td>
			<td>0</td>
		</tr>
	</tbody>
</table>
Table 2.&#160;Fat ranking task scoring. Participants are given 4&#160;samples of custard with 0, 2, 6, or 10% fat added. Participants are asked to rank samples from lowest to highest fat content and score 0 to 5 points (5 being the maximum).
5. Fatty Food Liking
<ol>
	<li>Prepare small samples (5-20 g) of both regular and low-fat options of commercially available foods. Foods include regular and low-fat versions of: cream cheese (served on a cracker), chocolate mousse, cheese, dry biscuits, peanut butter dip served on a piece of carrot, mayonnaise, salad dressing (served on a slice of cucumber), and yogurt.</li>
	<li>Label each sample with a random three-digit number for identification.</li>
	<li>Present samples in a random order to prevent order effects.</li>
	<li>Instruct participants to taste each sample individually. Food items are ingested, but participants can eat as much or as little of each sample as they desire.</li>
	<li>Have participants rate how much they like or dislike each sample. Measure liking using a 100-mm hedonic generalized magnitude scale (gLMS; see Figure 2) ranging from strongest imaginable dislike to strongest imaginable like. Record liking by placing a vertical line at the point which represents the participants like or dislike of the food.</li>
</ol>
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig2highres.jpg" src="/files/ftp_upload/51236/51236fig2.jpg" /> 
Figure 2.&#160;Hedonic gLMS. The hedonic gLMS30,31 used to assess liking of both regular and low fat commercially available foods. Participants taste and rate each sample and place a vertical line at the point which best represents their like, or dislike of the sample.
<ol start="6">
	<li>Non-taste inputs are not minimized for this task, so carry this task out under normal light and do not have participants wear nose clips.</li>
</ol>
6. Tongue Photography
<ol>
	<li>Set up a camera and tripod for photography. Regular indoor lighting is sufficient.</li>
	<li>Set the camera to macro mode (or similar) for close up photography.</li>
	<li>Use a hole punch to create a 6-mm diameter circle on a 1.5 cm x 1.5 cm (or similar) square of filter paper. Label the paper with the participant&#39;s identification number.</li>
	<li>In a 50-ml beaker, combine blue food coloring with deionized water at a 1:20 ratio. A small amount is required per participant.</li>
	<li>Pour 30 ml food grade ethanol into a 50-ml&#160;beaker for tweezer sterilization.</li>
	<li>Using masking tape, mark a 20 cm x 30 cm rectangle on the side of the testing table (this should be regular desk height), as shown in Figure 3a.</li>
</ol>
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig3highres.jpg" src="/files/ftp_upload/51236/51236fig3.jpg" /> 
Figure 3.&#160;A) Tongue photography setup. Demonstration of the table setup required prior to tongue photography. B) Tongue photography. Demonstration of the tongue photography method
<ol start="7">
	<li>Have participants place their elbows on the marked corners of the rectangle, rest their chin in their palms and to comfortably protrude their tongue, using the lips to steady this position (Figure 3b). The participant must remain in this position for the duration of the testing.</li>
	<li>Using a rectangular (1.5 cm x 3 cm) strip of filter paper, briefly dry the bottom portion of the tongue.</li>
	<li>Dip a cotton bud into the food coloring/water solution and transfer a small amount of dye onto the anterior dorsal surface of tongue, immediately right of the midline point and close to the tip (see Figure 4). Dry the tongue for a second time with filter paper.</li>
	<li>Dry ethanol sterilized tweezers with paper towel and using tweezers, place the pre-labeled 1.5 cm2 filter paper onto the participant&#39;s tongue, with the 6-mm hole over the blue food coloring (see Figure 4).</li>
	<li>Using flash, take three-digital photographs of the participant&#39;s tongue. For confidentiality, ensure only the participant&#39;s mouth and tongue are visible.</li>
	<li>Remove the 1.5 cm2 filter paper from the participant&#39;s tongue with tweezers that have again been sterilized in food grade ethanol. Upload photographs to a photo editing software and with the zoom function, count all visible fungiform papillae.</li>
	<li>Differentiate fungiform papillae from other papillae as larger mushroom shaped, elevated structures. They do not take on the dye solution as strongly, and as such appear much lighter in color. 
	Note: Tongue photography should take no longer than 10 min to complete.</li>
</ol>
<img alt="Figure 4" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig4highres.jpg" src="/files/ftp_upload/51236/51236fig4.jpg" /> 
Figure 4.&#160;Quantifying fungiform papillae density. Location of the 6-mm area for fungiform papillae assessment. Using photography editing software, numerical figures indicate each fungiform papilla.

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L., Bagla, R., Morgenson, M., Mirza, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=NaCl+thresholds:+relationship+to+anterior+tongue+locus,+area+of+stimulation,+and+number+of+fungiform+papillae.">NaCl thresholds: relationship to anterior tongue locus, area of stimulation, and number of fungiform papillae.</a> Physiol Behav. 72, 373-378 (2001).</li><li>Hayes, J. E., Duffy, V. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Revisiting+sugar-fat+mixtures:+sweetness+and+creaminess+vary+with+phenotypic+markers+of+oral+sensation.">Revisiting sugar-fat mixtures: sweetness and creaminess vary with phenotypic markers of oral sensation.</a> Chem Senses. 32, 225-236 (2007).</li><li>Tepper, B. J., Nurse, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fat+perception+is+related+to+PROP+taster+status.">Fat perception is related to PROP taster status.</a> Physiol Behav. 61, 949-954 (1997).</li><li>Tepper, B. J., Nurse, R. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PROP+taster+status+is+related+to+fat+perception+and+preference.">PROP taster status is related to fat perception and preference.</a> Ann N Y Acad Sci. 855, 802-804 (1998).</li><li>Shahbake, M., Hutchinson, I., Laing, D. G., Jinks, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rapid+quantitative+assessment+of+fungiform+papillae+density+in+the+human+tongue.">Rapid quantitative assessment of fungiform papillae density in the human tongue.</a> Brain Res. 1052, 196-201 (2005).</li><li>. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+Database+on+Body+Mass+Index.+BMI+classification.">Global Database on Body Mass Index. BMI classification.</a> World Health Organisation. , (2006).</li><li>Astrup, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Obesity+as+an+adaptation+to+a+high+fat+diet:+Evidence+from+a+cross+sectional+study.">Obesity as an adaptation to a high fat diet: Evidence from a cross sectional study.</a> Am J Clin Nutr. 59, 350-355 (1994).</li><li>Mattes, R. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fat+preference+and+adherence+to+a+reduced-fat+diet.">Fat preference and adherence to a reduced-fat diet.</a> Am J Clin Nutr. 57, 373-381 (1993).</li><li>Duffy, V. B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Food+preference+questionnaire+as+a+screening+tool+for+assessing+dietary+risk+of+cardiovascular+disease+within+health+risk+appraisals.">Food preference questionnaire as a screening tool for assessing dietary risk of cardiovascular disease within health risk appraisals.</a> J Am Diet Assoc. 107, 237-245 (2007).</li><li>Duffy, V. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Surveying+food/beverage+liking:+A+tool+for+epidemiological+studies+to+connect+chemosensation+with+health+outcomes.">Surveying food/beverage liking: A tool for epidemiological studies to connect chemosensation with health outcomes.</a> Ann NY Acad Sci. 1170, 558-568 (2009).</li><li>Running, C. A., Mattes, R. D., Tucker, R. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Fat+taste+in+humans:+Sources+of+within-+and+between-subject+variability.">Fat taste in humans: Sources of within- and between-subject variability.</a> Prog Lipid Res. 52, 438-445 (2013).</li><li>Ralston, A. W., Hoerr, C. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+solubilities+of+the+normal+saturated+fatty+acids.">The solubilities of the normal saturated fatty acids.</a> J Org Chem. 7, 546-555 (1942).</li><li>Parodi, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Milk+fat+in+human+nutrition.">Milk fat in human nutrition.</a> Australian Journal of Dairy Technology. 59, 3-59 (2004).</li><li>Pepino, M. Y., Love-Gregory, L., Klein, S., Abumrad, N. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+fatty+acid+translocase+gene+CD36+and+lingual+lipase+influence+oral+sensitivity+to+fat+in+obese+subjects.">The fatty acid translocase gene CD36 and lingual lipase influence oral sensitivity to fat in obese subjects.</a> J Lipid Res. 53, 561-566 (2012).</li><li>Lawless, H. T., Popper, R., Kroll, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+comparison+of+the+labeled+magnitude+(LAM)+scale,+an+11-point+category+scale+and+the+traditional+9-point+hedonic+scale.">A comparison of the labeled magnitude (LAM) scale, an 11-point category scale and the traditional 9-point hedonic scale.</a> Food Qual Prefer. 21, 4-12 (2010).</li><li>Bartoshuk, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hedonic+gLMS:+a+new+scale+that+permits+valid+hedonic+comparisons.">Hedonic gLMS: a new scale that permits valid hedonic comparisons.</a> , (2010).</li></ol>

The authors have nothing to disclose.

The techniques described for determination of oral fatty acid thresholds, fatty food liking, and tongue papillae density have been validated and used in a number of published works in recent years and we suggest oral fatty acid threshold assessment, the fat ranking task and fatty food liking be performed in duplicate at each relevant time point in a study. There has been some discussion regarding the optimum method for assessing detection thresholds32. In particular, the composition of solutions used varies between laboratories, as does the methodology itself. Specifically, the fatty acid used in this protocol, C18:1, we believe is a generally representative and easy to use fatty acid, as opposed to other fatty acids, including linoleic acid (C18:2) and lauric acid (C12:0), which have been used previously9. C18:1 is commonly found in the food supply and unlike C12:0 is liquid at RT, and is more resistant to oxidation than C18:29. C18:1 has also been shown to provide reliable data across multiple testing sessions, and is highly correlated with C18:2 and C12:010. Furthermore, C18:1 has been examined extensively throughout relevant literature, and is thus more helpful for comparisons.
A major point of difference between the protocol outlined within the present paper and other procedures used in other laboratories are the vehicles used for presenting fatty acid stimuli and the systematic approach by which detection thresholds are determined. Two major fatty acid vehicles used within the literature are non-fat milk10,17 and water emulsions6. While both have demonstrated efficacy for fatty acid threshold determination, participants may be more likely to identify the taste of fat within milk, that is, it is unusual to taste fatty acids in water, which may result in lower levels of external validity for studies utilizing a water base. Non-fat milk provides a vehicle for fatty acid chemoreception, without compromising validity. Although these two methods are yet to be directly compared in the literature, it is known that fatty acids are poorly soluble in water33. As a result of fatty acid solubility in milk-based solutions, this emulsion could both be kept longer and be more homogenous than water-based solutions, though this is yet to be confirmed. When implementing this methodology, it is important to note free fatty acids may be naturally present in milk34 and consequently, the product should be used well within its expiry to prevent the increase of free fatty acids (which develop with age) and potential interference with taste threshold performance. Successful preparation of the solutions depends on numerous factors. Firstly, the order in which the &#39;ingredients&#39; are added is imperative. Vehicle preparation steps should carefully follow those outlined earlier to ensure proper vehicle composition and a stable emulsion. Secondly, temperature must be controlled for. Each sample must be presented to participants at RT to ensure participants do not detect the &#39;odd sample&#39; due to factors other than &#39;taste&#39;. Finally, all samples must be correctly homogenized for the suggested period of time. While the emulsion of fatty acids and no-fat milk is more effective than if water were to be used, there is still a chance of emulsion separation within the sample.
The specific testing method used in oral fatty acid threshold determination must also be considered. Two sensory-based methods have been commonly described in the literature; one being the ascending forced choice triangle procedure and the alternate, the staircase method35. The ascending forced choice triangle methodology is an established method for taste threshold determination and can be considered useful for several reasons, including the fact that, unlike the staircase method, the ascending method begins with the lowest concentration of C18:1 (0.02 mM) and increases until the participant is able to detect the presence of fatty acid in solution9. Conversely, the staircase method involves increasing or decreasing the fatty acid concentration from a predetermined midpoint11. However, starting a threshold determination at a point above threshold may cause a desensitization of response impairing ones tasting ability. Further, the ascending method has a lower probability of random chance influencing results (3.7%) compared with the staircase method (11.1%)11. As such, we suggest the ascending forced choice triangle method, combined with non-fat milk as a vehicle for taste testing appears to be an effective means of accurately determining oral thresholds.
Food acceptance or liking testing is one of the more straightforward assessments performed within sensory research and as such there are few problems that tend to arise. However, the type of liking scale used is an important focus. In this case, a hedonic gLMS is the most effective, as it has good discriminatory power and is easy for participants to use36. The end points of the hedonic gLMS are labeled with the descriptors &#39;strongest imaginable dislike&#39; and &#39;strongest imaginable like&#39; and participants evaluate liking against all hedonic experiences, not solely foods30,31. This is effective in controlling for ceiling effects produced by standard 9-point scales, as all experiences are considered and compared. Further, the hedonic gLMS is more able to demonstrate greater individual variance, as the scale is broader36. Food acceptance testing itself may be limited by the foods presented, in that we only present two options per food type. Further research may include several more brands or types of each food, each with differing fat contents, or perhaps specifically made products where fat content can be controlled and is the only variable. It is important to note that the interpretation of all data must be done with caution. While a potential link between liking, preference and intake is plausible and intriguing, results are generated within a laboratory environment and there may be limits to the applicability of these findings to real-world situations.
Assessing papillae density through tongue photography is a more difficult process, with specific steps that must be taken in order to produce appropriate and applicable results. In particular, it is important to identify the correct papillae type. Three types of taste papillae are visible on the human tongue; fungiform, foliate and circumvallate4. Fungiform papillae can however be easily distinguished as mushroom-shaped structures26, and are generally the papillae that are recorded during sensitivity assessments. Fungiform papillae tend to range in concentration from 5-60 per 6-mm area37 (depending on sensitivity), though there have been studies indicating that some individuals may have upwards of 230 papillae the same area21. The type of camera used is fundamental to obtaining appropriate results and may account for this variability. Prior to the use of digital photography in this area, videomicroscopy was the gold standard for identifying and recording papillae density. However, it has been determined that the same level of identification is possible using an appropriate digital camera26. Further, digital photography takes only several minutes, where videomicroscopy may take up to an hour26. Not only this, but digital photography has the potential to be far less costly, and more portable, which may be helpful for use with various participant groups26. Finally, while we aim to measure fungiform papillae density for associations with oral fatty acid detection, we also suggest taste thresholds for the five prototypical tastes also be performed in parallel. Given previous linkage with papillae density and taste function, this could serve as an additional &#39;checking measure&#39; which may add integrity to the data, especially given this is a new area of research.
The area of oral chemoreception research, particularly regarding fatty acids, is an emerging one, and as such it is important for all research to be performed to a high standard, preferably with the use of consistent protocols to allow for direct comparisons.

Excessive dietary fat consumption is a potential contributor to weight gain1-3 and obesity has become a modern day global epidemic. Research suggests higher levels of fat intake, particularly as part of an ad libitum diet, may be associated with a higher BMI2,3, however the factors influencing dietary fat consumption and preference are far from clear. Searching for the mechanisms which underlie fat consumption is therefore an obvious goal and of particular interest is an oral mechanism responsible for fat detection, commonly termed &#39;fatty acid taste&#39;2.
From an evolutionary standpoint, the taste system presumably served as a gatekeeper of the digestive system, guiding the consumption of energy dense nutrients and expulsion of potentially toxic compounds4. The sense of taste is elicited through specialized taste receptor cells which are distributed within three types of tongue papillae; fungiform, foliate, and circumvallate papillae, which can each contain up to several hundred taste buds5. In addition to the widely accepted five prototypical tastes (sweet, salty, sour, bitter, and umami), it is not entirely surprising that there has been suggestion of an oral mechanism for detecting fat, or more likely their breakdown products fatty acids6.
Previous research has consistently shown fatty acids can be detected in the oral cavity over a range of concentrations7-11, despite the fact that it is not a &#39;taste&#39; in the traditional sense, as it has no single discernible perceptual quality associated with it (i.e. sweet)12. Work from our laboratory has highlighted functional implications of impaired fatty acid chemoreception, namely on body weight and dietary fat consumption. Those who are less able to detect fatty acids (hyposensitive) appear to have a higher body mass index (BMI) and consume more energy9, while a relationship between oral fatty acid sensitivity and dietary fat consumption has also been observed; that is, fatty acid hyposensitive individuals have been shown to consume more animal fats, including, meat, high fat dairy, and fatty spreads&#160;all of which are been implicated as contributors to weight gain13. Additionally, individuals who are more sensitive to fatty acids appear to be better equipped at differentiating between samples with varying fat contents9. While other research groups have failed to find similar associations10,14,15, this growing area of research remains intriguing.
These individual differences in fatty acid chemoreception appear to be somewhat modulated by environmental factors, including diet. Habitual fat intake has been associated with impaired oral fatty acid chemoreception and consequently, a heightened preference for, and increased consumption of dietary fat16. In addition to gustatory adaptation, the gastrointestinal tract (GI) also appears responsive to such changes in fat intake17 and impaired GI fatty acid sensitivity may be implicated in the inability to generate appropriate satiety signaling responses which discourage excess energy consumption18.
In addition to environmental factors, fatty acid chemoreception may also be dictated by genetic or physiological differences between individuals, including the concentration of fungiform papillae density (and presumably taste receptors) on an individual&#39;s tongue19. Higher density of fungiform tongue papillae has been linked to heightened oral sensitivity for numerous orally detected compounds including 6-n-propylthiouracil (PROP)20, sugar21, and salt22, while others have also noted an association with creamy perception23. PROP supertasters (who presumably have a higher number of fungiform papillae) are able to distinguish high fat from low fat salad dressings24 and are able to discriminate the fat content and creaminess of dairy foods more accurately than non-tasters23,25. At this stage however, the relationship between fungiform papillae density and oral fatty acid &#39;taste&#39; detection is unknown.
At the basis of human oral fatty acid chemoreception research is the application of various sensory techniques. Identifying individual variability in oral fatty acid detection is a major focus and largely depends on the determination of fatty acid detection thresholds, that is, the lowest point at which fatty acid is able to be detected in solution9. While the specific testing method and stimulus vehicle used varies across the literature and between research groups, the typical procedure involves presenting a participant with a set of emulsified fatty acid and control (no fatty acid) solutions and identifying which is the &#39;odd&#39; sample. Here we present an established, reliable and reproducible method for threshold determination10 using emulsified milk solutions and an ascending forced choice triangle procedure.
The extent to which oral fatty acid sensitivity influences diet, namely consumption of fatty foods, and the ability to perceive fat in foods is also of interest and here we also report on two additional established techniques to further extend our understanding of fatty acid chemoreception. Fatty food liking can be identified by providing individuals with samples of commercially available foods, with both a regular and a low-fat option who are asked to indicate liking of each16. In regards to fat perception, a fat ranking task has been developed by our laboratory, designed to evaluate an individual&#39;s ability to detect fat in custard, a typical food matrix16. To evaluate genetic or physiological differences between individuals, a commonly used tongue photography method involves staining, photographing and quantifying fungiform papillae26. While using this technique in fatty acid research is in its infancy, increasing application, especially in both lean and overweight/obese population groups may help to identify inherent causes of excess fat consumption.

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			<td height="42" style="height:42px;width:216px;">Name of Material/ Equipment</td>
			<td style="width:104px;">Company</td>
			<td style="width:119px;">Catalog Number</td>
			<td style="width:471px;">Comments/Description</td>
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			<td height="63" style="height:63px;width:216px;">Gum Arabic TIC Pretested PRE-HYDRATED FT Powder</td>
			<td style="width:104px;">Alchemy Agencies Ltd. NZ</td>
			<td style="width:119px;">CFR# 21 CFR 184.1330</td>
			<td>Food grade agrigum</td>
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			<td height="63" style="height:63px;width:216px;">EDTA (Ethylenediaminetetraacetic acid)</td>
			<td style="width:104px;">Merck</td>
			<td style="width:119px;">1.08418 0250</td>
			<td>Disodium salt dehydrate</td>
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			<td height="63" style="height:63px;width:216px;">L4RT Homogenizer</td>
			<td style="width:104px;">Silverson Longmedow, MA</td>
			<td style="width:119px;">L4RT</td>
			<td></td>
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			<td height="21" style="height:21px;width:216px;">Liquid Paraffin</td>
			<td style="width:104px;">Fauldings</td>
			<td style="width:119px;"></td>
			<td>No catalog number as liquid paraffin is a regular consumable product</td>
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			<td height="63" style="height:63px;width:216px;">Nikon AF-S VR Micro Nikkor 105mm f/2.8G IF-ED camera lens</td>
			<td style="width:104px;">Nikon</td>
			<td align="right" style="width:119px;">2160</td>
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			<td height="42" style="height:42px;width:216px;">SLIK Sprint Pro II tripod</td>
			<td style="width:104px;">Slik Corporation</td>
			<td>611-849</td>
			<td></td>
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			<td height="42" style="height:42px;width:216px;">Nikon D90 Digital Camera with LCD Protector</td>
			<td style="width:104px;">Nikon</td>
			<td style="width:119px;">BM-10</td>
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			<td height="21" style="height:21px;width:216px;">Nitrogen</td>
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			<td height="63" style="height:63px;width:216px;">Tanita Body Scan Composition Monitor Scales</td>
			<td style="width:104px;">Tanita, Cloverdale, WA, Australia</td>
			<td style="width:119px;">BC-551</td>
			<td></td>
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			<td height="84" style="height:84px;width:216px;">Seca Stadiometer</td>
			<td style="width:104px;">Medshop Australia, Fairfield, VIC, Australia</td>
			<td style="width:119px;">MED435</td>
			<td></td>
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measuring oral fatty acid thresholds, fat perception, fatty food liking, and papillae density in humans

Emerging evidence from a number of laboratories indicates that humans have the ability to identify fatty acids in the oral cavity, presumably via fatty acid receptors housed on taste cells. Previous research has shown that an individual&#39;s oral sensitivity to fatty acid, specifically oleic acid (C18:1) is associated with body mass index (BMI), dietary fat consumption, and the ability to identify fat in foods. We have developed a reliable and reproducible method to assess oral chemoreception of fatty acids, using a milk and C18:1 emulsion, together with an ascending forced choice triangle procedure. In parallel, a food matrix has been developed to assess an individual&#39;s ability to perceive fat, in addition to a simple method to assess fatty food liking. As an added measure tongue photography is used to assess papillae density, with higher density often being associated with increased taste sensitivity.

The methods detailed above are important as some emerging evidence has indicated that impaired fatty acid chemoreception in the oral cavity and GI tract may be associated with increases in BMI and the development of obesity17. Several studies have used the described protocols to investigate oral fatty acid detection and our recent publication has shown the method is both reliable and reproducible10. Studies using this methodology have been able to reliably determine individual&#39;s oral fatty acid detection thresholds by identifying the point at which participants are able to detect a difference between milk samples9. After three testing sessions utilizing this protocol, Stewart et al.9 found that the mean detection threshold for C18:1 was 2.2 &#177; 0.1, with detection thresholds ranging from 1-6.4 mM (see Figure 5). More recently, we have established a C18:1 detection threshold range from 0.26-12 mM, (mean: 2.64 &#177; 0.7 mM)10. These results support the notion that fatty acids can be detected in the oral cavity, and that marked individual differences in sensitivity to C18:1 exist. Based on these results, we are able to classify individuals as hypersensitive or hyposensitive to C18:1. Hypersensitive individuals are able to correctly identify C18:1 &#60;3.8 mM, while hyposensitive subjects require concentrations &#62;3.8 mM. Research from our laboratory has found oral sensitivity to C18:1 is associated with dietary fat consumption and BMI (Figure 6), where C18:1 hyposensitive individuals consume more saturated and animal fats and have a higher BMI13. Interestingly, in a study conducted by Stewart and Keast16, it was found that consuming a low fat diet resulted in increased sensitivity to C18:1 for both lean and overweight participants (Figure 7). However, this study also found that when participants consumed a high fat diet, lean individuals had reduced sensitivity to C18:1, while overweight individuals had no change in taste sensitivity (Figure 8). This suggests that habitually consuming a high fat diet, which is more likely for overweight individuals, may result in attenuated fatty acid chemoreception28. However, as there were no differences in baseline sensitivity between lean and overweight participants, these results may indicate that lean individuals are simply more susceptible to dietary changes regarding fat intake. This may also suggest that it was the presence of the specific intervention (high- vs low-fat) that may have influenced outcomes, rather than habitual diets, which may or may not have been different to the intervention diet. Despite this, this study indicates that there are some fundamental differences between lean and overweight individuals regarding fatty acid taste sensitivity, which requires further investigation.
<img alt="Figure 5" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig5highres.jpg" src="/files/ftp_upload/51236/51236fig5.jpg" /> 
Figure 5.&#160;C18:1 taste detection thresholds. Marked variability has been shown in sensitivity to C18:1 with participants able to detect C18:1 across a range of concentrations (1 mM-6.4 mM).
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig6highres.jpg" src="/files/ftp_upload/51236/51236fig6.jpg" /> 
Figure 6.&#160;C18:1 taste detection thresholds and association with BMI. An association between the ability to detect C18:1 and body composition has been shown, whereby those with higher detection thresholds (hyposensitive individuals) have significantly higher BMI values (P = 0.002, r2= 0.467).
<img alt="Figure 7" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig7highres.jpg" src="/files/ftp_upload/51236/51236fig7.jpg" /> 
Figure 7.&#160;C18:1 detection thresholds following a low fat diet. Following 4 week consumption of a low fat diet, C18:1 detection thresholds increased for both lean and obese individuals.
<img alt="Figure 8" fo:content-width="5in" fo:src="/files/ftp_upload/51236/51236fig8highres.jpg" src="/files/ftp_upload/51236/51236fig8.jpg" /> 
Figure 8.&#160;C18:1 detection thresholds following a high fat diet. Following 4 week consumption of a high fat diet, lean individuals displayed reduced sensitivity to C18:1 (P = 0.006), while overweight individuals demonstrated no change (P= 0.609).
Similarly to the impact of diet on detection thresholds for fatty acids, there is research to suggest that food liking may be plastic and altered by exposure. For example, it appears that a high fat diet increases preference for a higher fat product, with the opposite occurring following consumption of a low fat diet16. However, these changes have not been consistent in the literature. It appears that changes to preferences are mediated by the length of time the individual has been adhering to a high or low-fat diet. Specifically, Mattes29 found significant changes in participant food preferences after 12 weeks on a reduced fat diet, while Stewart and Keast16 found only sporadic and marginal changes after four weeks on a similar diet. Consuming a high fat diet altered participant preferences for yogurt, with preferences for low-fat yogurt increasing, converse to expected results (Baseline (BL): 19.44 &#177; 5.73, Week 4 (WK4): 21.94 &#177; 5.21, P = 0.046). Further, after four weeks on a low-fat diet, preferences for low-fat butter increased in all participants (BL: 6.23 &#177; 4.26, WK4: 7.32 &#177; 3.04, P = 0.046). Preferences for low-fat yogurt increased for lean participants only (BL: 2.51 &#177; 3.26, WK4: 3.68 &#177; 4.94, P = 0.07) while preferences for low-fat mousse decreased for all participants (P = 0.01).
The ability to detect fat in foods is assessed by asking participants to taste and rank a series of custards with differing fat contents. Fat perception is identified based on how well participants were able to rank the samples. Fat perception has been known to change with diet, for example, following a low fat diet has resulted in improvements to participant&#39;s performance in correctly identifying and ranking the degree of fat in each custard sample11. Furthermore, it appears that there is an association between sensitivity to C18:1 and identification and ranking of fat content4. Indeed, individuals who were hypersensitive to C18:1 performed significantly better on the fat ranking task (4.3 &#177; 0.6) compared to hyposensitive individuals (2.3 &#177; 0.1, P = 0.02) (scores are out of a maximum of five)9. This indicates that individuals who are more sensitive to fatty acids were also better at differentiating between the four varying fat concentrations in custard. While there was a trend for performance to improve after consuming the low-fat diet for four weeks, this was not a significant change (BL: 1.3 &#177; 0.3, WK4: 2 &#177; 0.3, P = 0.077)16.
Papillae density i.e. the number of papillae (and hence taste buds) present on the tongue varies between individuals and is indicative of taste function. Higher fungiform papillae density has been linked to heightened taste sensitivity, for compounds including sucrose21 and the bitter substance PROP20. Tongue papillae density, as determined by tongue photography, varies considerably between subjects. For example, Zhang et al.21 found that there were significant individual differences between participants, ranging from a concentration of 7.07 &#177; 0.35/cm2 to 233.43 &#177; 0.00/cm2 (data was for a single participant), whereas others26 have found a mean fungiform papillae concentration to be 156.00 &#177; 5.86/cm2. Further, it has been found that papillae can appear significantly differently in structure between individuals, with variation in height, width, and shape,21 though limited evidence regarding the possible implications of these differences. Given previous findings linking papillae number with taste sensitivity, it is plausible that a similar relationship may also exist for oral fatty acid sensitivity, whereby those who are more orally sensitive to fatty acids may have a higher density of taste papillae and therefore a higher number of oral fatty acid receptors. While this association is yet to be established, it presents a novel area of research may help implicate the underlying mechanisms guiding the over consumption of fat.

Watch this Scientific Journal Video about Measuring Oral Fatty Acid Thresholds, Fat Perception, Fatty Food Liking, and Papillae Density in Humans at JoVE.com

Measuring Oral Fatty Acid Thresholds, Fat Perception, Fatty Food Liking, and Papillae Density in Humans

Oral chemoreception of fatty acids and the association with diet and fatty food preferences may enable the identification of mechanisms involved with the development of obesity and why dietary changes may be difficult for many individuals.

Emerging evidence from a number of laboratories indicates that humans have the ability to identify fatty acids in the oral cavity, presumably via fatty ...

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object categories with precisely definable, preferably naturalistic, properties1. Furthermore, for studies on perceptual learning, it is useful to create novel objects and object categories (or object classes) with such properties2.
Many innovative and useful methods currently exist for creating novel objects and object categories3-6 (also see refs. 7,8). However, generally speaking, the existing methods have three broad types of shortcomings.
First, shape variations are generally imposed by the experimenter5,9,10, and may therefore be different from the variability in natural categories, and optimized for a particular recognition algorithm. It would be desirable to have the variations arise independently of the externally imposed constraints.
Second, the existing methods have difficulty capturing the shape complexity of natural objects11-13. If the goal is to study natural object perception, it is desirable for objects and object categories to be naturalistic, so as to avoid possible confounds and special cases.
Third, it is generally hard to quantitatively measure the available information in the stimuli created by conventional methods. It would be desirable to create objects and object categories where the available information can be precisely measured and, where necessary, systematically manipulated (or 'tuned'). This allows one to formulate the underlying object recognition tasks in quantitative terms.
Here we describe a set of algorithms, or methods, that meet all three of the above criteria. Virtual morphogenesis (VM) creates novel, naturalistic virtual 3-D objects called 'digital embryos' by simulating the biological process of embryogenesis14. Virtual phylogenesis (VP) creates novel, naturalistic object categories by simulating the evolutionary process of natural selection9,12,13. Objects and object categories created by these simulations can be further manipulated by various morphing methods to generate systematic variations of shape characteristics15,16. The VP and morphing methods can also be applied, in principle, to novel virtual objects other than digital embryos, or to virtual versions of real-world objects9,13. Virtual objects created in this fashion can be rendered as visual images using a conventional graphical toolkit, with desired manipulations of surface texture, illumination, size, viewpoint and background. The virtual objects can also be 'printed' as haptic objects using a conventional 3-D prototyper.
We also describe some implementations of these computational algorithms to help illustrate the potential utility of the algorithms. It is important to distinguish the algorithms from their implementations. The implementations are demonstrations offered solely as a 'proof of principle' of the underlying algorithms. It is important to note that, in general, an implementation of a computational algorithm often has limitations that the algorithm itself does not have.
Together, these methods represent a set of powerful and flexible tools for studying object recognition and perceptual learning by biological and computational systems alike. With appropriate extensions, these methods may also prove useful in the study of morphogenesis and phylogenesis.

We describe a novel methodology for creating naturalistic 3-D objects and object categories with precisely defined feature variations. We use simulations of the biological processes of morphogenesis and phylogenesis to create novel, naturalistic virtual 3-D objects and object categories that can then be rendered as visual images or haptic objects.

In order to quantitatively study object perception, be it perception by biological systems or by machines, one needs to create objects and object ...

Using Affordable LED Arrays for Photo-Stimulation of Neurons

Standard slice electrophysiology has allowed researchers to probe individual components of neural circuitry by recording electrical responses of single cells in response to electrical or pharmacological manipulations1,2. With the invention of methods to optically control genetically targeted neurons (optogenetics), researchers now have an unprecedented level of control over specific groups of neurons in the standard slice preparation. In particular, photosensitive channelrhodopsin-2 (ChR2) allows researchers to activate neurons with light3,4. By combining careful calibration of LED-based photostimulation of ChR2 with standard slice electrophysiology, we are able to probe with greater detail the role of adult-born interneurons in the olfactory bulb, the first central relay of the olfactory system. Using viral expression of ChR2-YFP specifically in adult-born neurons, we can selectively control young adult-born neurons in a milieu of older and mature neurons. Our optical control uses a simple and inexpensive LED system, and we show how this system can be calibrated to understand how much light is needed to evoke spiking activity in single neurons. Hence, brief flashes of blue light can remotely control the firing pattern of ChR2-transduced newborn cells.

Adult-born neurons expressing ChR2 can be manipulated in slice electrophysiological preparations in order to examine their contribution towards the function of olfactory neural circuits.

Standard slice electrophysiology has allowed researchers to probe individual components of neural circuitry by recording electrical responses of single ...

Selective Viral Transduction of Adult-born Olfactory Neurons for Chronic in vivo Optogenetic Stimulation

Local interneurons are continuously regenerated in the olfactory bulb of adult rodents1-3. In this process, called adult neurogenesis, neural stem cells in the walls of the lateral ventricle give rise to neuroblasts that migrate for several millimeters along the rostral migratory stream (RMS) to reach and incorporate into the olfactory bulb. To study the different steps and the impact of adult-born neuron integration into preexisting olfactory circuits, it is necessary to selectively label and manipulate the activity of this specific population of neurons. The recent development of optogenetic technologies offers the opportunity to use light to precisely activate this specific cohort of neurons without affecting surrounding neurons4,5. Here, we present a series of procedures to virally express Channelrhodopsin2(ChR2)-YFP in a temporally restricted cohort of neuroblasts in the RMS before they reach the olfactory bulb and become adult-born neurons. In addition, we show how to implant and calibrate a miniature LED for chronic in vivo stimulation of ChR2-expressing neurons.

Selective Viral Transduction of Adult-born Olfactory Neurons for Chronic in vivo Optogenetic Stimulation

Adult-born neurons of the olfactory bulb can be optogenetically controlled using Channelrhodopsin2-expressing lentiviral injection in the rostral migratory stream and chronic photostimulation with an implanted miniature LED.

Local interneurons are continuously regenerated in the olfactory bulb of adult rodents1-3. In this process, called adult neurogenesis, neural stem cells ...

MPI CyberMotion Simulator: Implementation of a Novel Motion Simulator to Investigate Multisensory Path Integration in Three Dimensions

Path integration is a process in which self-motion is integrated over time to obtain an estimate of one's current position relative to a starting point 1. Humans can do path integration based exclusively on visual 2-3, auditory 4, or inertial cues 5. However, with multiple cues present, inertial cues - particularly kinaesthetic - seem to dominate 6-7. In the absence of vision, humans tend to overestimate short distances (&lt;5 m) and turning angles (&lt;30&deg;), but underestimate longer ones 5. Movement through physical space therefore does not seem to be accurately represented by the brain.
Extensive work has been done on evaluating path integration in the horizontal plane, but little is known about vertical movement (see 3 for virtual movement from vision alone). One reason for this is that traditional motion simulators have a small range of motion restricted mainly to the horizontal plane. Here we take advantage of a motion simulator 8-9 with a large range of motion to assess whether path integration is similar between horizontal and vertical planes. The relative contributions of inertial and visual cues for path navigation were also assessed.
16 observers sat upright in a seat mounted to the flange of a modified KUKA anthropomorphic robot arm. Sensory information was manipulated by providing visual (optic flow, limited lifetime star field), vestibular-kinaesthetic (passive self motion with eyes closed), or visual and vestibular-kinaesthetic motion cues. Movement trajectories in the horizontal, sagittal and frontal planes consisted of two segment lengths (1st: 0.4 m, 2nd: 1 m; &plusmn;0.24 m/s2 peak acceleration). The angle of the two segments was either 45&deg; or 90&deg;. Observers pointed back to their origin by moving an arrow that was superimposed on an avatar presented on the screen.
Observers were more likely to underestimate angle size for movement in the horizontal plane compared to the vertical planes. In the frontal plane observers were more likely to overestimate angle size while there was no such bias in the sagittal plane. Finally, observers responded slower when answering based on vestibular-kinaesthetic information alone. Human path integration based on vestibular-kinaesthetic information alone thus takes longer than when visual information is present. That pointing is consistent with underestimating and overestimating the angle one has moved through in the horizontal and vertical planes respectively, suggests that the neural representation of self-motion through space is non-symmetrical which may relate to the fact that humans experience movement mostly within the horizontal plane.

An efficient way to gain insight into how humans navigate themselves in three dimensions is described. The method takes advantage of a motion simulator capable of moving observers in ways unattainable by traditional simulators. Results confirm that movement in the horizontal plane is underestimated, while vertical movement is overestimated.

Path integration is a process in which self-motion is integrated over time to obtain an estimate of one's current position relative to a starting point 1. ...

Isolation and Culture of Human Fungiform Taste Papillae Cells

Taste cells are highly specialized, with unique histological, molecular and physiological characteristics that permit detection of a wide range of simple stimuli and complex chemical molecules contained in foods. In human, individual fungiform papillae contain from zero to as many as 20 taste buds. There is no established protocol for culturing human taste cells, although the ability to maintain taste papillae cells in culture for multiple cell cycles would be of considerable utility for characterizing the molecular, regenerative, and functional properties of these unique sensory cells. Earlier studies of taste cells have been done using freshly isolated cells in primary culture, explant cultures from rodents, or semi-intact taste buds in tissue slices1,2,3,4. Although each of these preparations has advantages, the development of long-term cultures would have provided significant benefits, particularly for studies of taste cell proliferation and differentiation. Several groups, including ours, have been interested in the development and establishment of taste cell culture models. Most attempts to culture taste cells have reported limited viability, with cells typically not lasting beyond 3-5 d5,6,7,8. We recently reported on a successful method for the extended culture of rodent taste cells9. We here report for the first time the establishment of an in vitro culture system for isolated human fungiform taste papillae cells. Cells from human fungiform papillae obtained by biopsy were successfully maintained in culture for more than eight passages (12 months) without loss of viability. Cells displayed many molecular and physiological features characteristic of mature taste cells. Gustducin and phospholipase C &beta;2, (PLC-&beta;2) mRNA were detected in many cells by reverse transcriptase-polymerase chain reaction and confirmed by sequencing. Immunocytochemistry analysis demonstrated the presence of gustducin and PLC-&beta;2 expression in cultured taste cells. Cultured human fungiform cells also exhibited increases in intracellular calcium in response to appropriate concentrations of several taste stimuli indicating that taste receptors and at least some of the signalling pathways were present. These results sufficient indicate that taste cells from adult humans can be generated and maintained for at least eight passages. Many of the cells retain physiological and biochemical characteristics of acutely isolated cells from the adult taste epithelium to support their use as a model taste system. This system will enable further studies of the processes involved in proliferation, differentiation and function of mammalian taste receptor cells in an in vitro preparation.
Human fungiform taste papillae used for establishing human fungiform cell culture were donated for research following proper informed consent under research protocols that were reviewed and approved by the IRB committee. The protocol (#0934) was approved by Schulman Associates Institutional Review Board Inc., Cincinnati, OH. Written protocol below is based on published parameters reported by Ozdener et al. 201110.

We aimed to develop a reproducible protocol for isolating and maintaining long-term cultures of human fungiform taste papillae cells. Cells from human fungiform papillae obtained by biopsy were successfully maintained in culture for more than eight passages (12 months) without loss of viability.

Taste cells are highly specialized, with unique histological, molecular and physiological characteristics that permit detection of a wide range of simple ...

Progressive-ratio Responding for Palatable High-fat and High-sugar Food in Mice

Foods that are rich in fat and sugar significantly contribute to over-eating and escalating rates of obesity. The consumption of palatable foods can produce a rewarding effect that strengthens action-outcome associations and reinforces future behavior directed at obtaining these foods. Increasing evidence that the rewarding effects of energy-dense foods play a profound role in overeating and the development of obesity has heightened interest in studying the genes, molecules and neural circuitry that modulate food reward1,2. The rewarding impact of different stimuli can be studied by measuring the willingness to work to obtain them, such as in operant conditioning tasks3. Operant models of food reward measure acquired and voluntary behavioral responses that are directed at obtaining food. A commonly used measure of reward strength is an operant procedure known as the progressive ratio (PR) schedule of reinforcement.4,5 In the PR task, the subject is required to make an increasing number of operant responses for each successive reward. The pioneering study of Hodos (1961) demonstrated that the number of responses made to obtain the last reward, termed the breakpoint, serves as an index of reward strength4. While operant procedures that measure changes in response rate alone cannot separate changes in reward strength from alterations in performance capacity, the breakpoint derived from the PR schedule is a well-validated measure of the rewarding effects of food. The PR task has been used extensively to assess the rewarding impact of drugs of abuse and food in rats (e.g.,6-8), but to a lesser extent in mice9. The increased use of genetically engineered mice and diet-induced obese mouse models has heightened demands for behavioral measures of food reward in mice. In the present article we detail the materials and procedures used to train mice to respond (lever-press) for a high-fat and high-sugar food pellets on a PR schedule of reinforcement. We show that breakpoint response thresholds increase following acute food deprivation and decrease with peripheral administration of the anorectic hormone leptin and thereby validate the use of this food-operant paradigm in mice.

The present report details the protocol employed to measure the rewarding effects of high-fat food in mice using a progressive ratio operant conditioning task.

Foods that are rich in fat and sugar significantly contribute to over-eating and escalating rates of obesity. The consumption of palatable foods can ...

RNAi-mediated Double Gene Knockdown and Gustatory Perception Measurement in Honey Bees (Apis mellifera)

This video demonstrates novel techniques of RNA interference (RNAi) which downregulate two genes simultaneously in honey bees using double-stranded RNA (dsRNA) injections. It also presents a protocol of proboscis extension response (PER) assay for measuring gustatory perception.	
	RNAi-mediated gene knockdown is an effective technique downregulating target gene expression. This technique is usually used for single gene manipulation, but it has limitations to detect interactions and joint effects between genes. In the first part of this video, we present two strategies to simultaneously knock down two genes (called double gene knockdown). We show both strategies are able to effectively suppress two genes, vitellogenin (vg) and ultraspiracle (usp), which are in a regulatory feedback loop. This double gene knockdown approach can be used to dissect interrelationships between genes and can be readily applied in different insect species.	
	The second part of this video is a demonstration of proboscis extension response (PER) assay in honey bees after the treatment of double gene knockdown. The PER assay is a standard test for measuring gustatory perception in honey bees, which is a key predictor for how fast a honey bee's behavioral maturation is. Greater gustatory perception of nest bees indicates increased behavioral development which is often associated with an earlier age at onset of foraging and foraging specialization in pollen. In addition, PER assay can be applied to identify metabolic states of satiation or hunger in honey bees. Finally, PER assay combined with pairing different odor stimuli for conditioning the bees is also widely used for learning and memory studies in honey bees.

RNAi-mediated Double Gene Knockdown and Gustatory Perception Measurement in Honey Bees Apis mellifera

In this protocol, we describe two strategies that simultaneously suppress two genes (double gene knockdown) in honey bees. Then we present how to use the proboscis extension response (PER) assay to study the effect of double gene knockdown on honey bee gustatory perception.

This video demonstrates novel techniques of RNA  interference (RNAi) which downregulate two genes simultaneously in honey bees  using double-stranded RNA ...

Whole Mount Immunolabeling of Olfactory Receptor Neurons in the Drosophila Antenna

Odorant molecules bind to their target receptors in a precise and coordinated manner. Each receptor recognizes a specific signal and relays this information to the brain. As such, determining how olfactory information is transferred to the brain, modifying both perception and behavior, merits investigation. Interestingly, there is emerging evidence that cellular transduction and transcriptional factors are involved in the diversification of olfactory receptor neuron. Here we provide a robust whole mount immunological labeling method to assay in vivo olfactory receptor neuron organization. Using this method, we identified all olfactory receptor neurons with anti-ELAV antibody, a known pan-neural marker and Or49a-mCD8::GFP, an olfactory receptor neuron specifically expressed in Nba neuron using anti-GFP antibody.

Whole Mount Immunolabeling of Olfactory Receptor Neurons in the Drosophila Antenna

Herein we describe the process of whole mount immunostaining of Drosophila antennae, which enables us to better understand the molecular mechanisms involved in the diversification of olfactory receptor neurons (ORN)s.

Odorant molecules bind to their target receptors in a precise and coordinated manner. Each receptor recognizes a specific signal and relays this ...

The Neuromuscular Junction: Measuring Synapse Size, Fragmentation and Changes in Synaptic Protein Density Using Confocal Fluorescence Microscopy

The neuromuscular junction (NMJ) is the large, cholinergic relay synapse through which mammalian motor neurons control voluntary muscle contraction. Structural changes at the NMJ can result in neurotransmission failure, resulting in weakness, atrophy and even death of the muscle fiber. Many studies have investigated how genetic modifications or disease can alter the structure of the mouse NMJ. Unfortunately, it can be difficult to directly compare findings from these studies because they often employed different parameters and analytical methods. Three protocols are described here. The first uses maximum intensity projection confocal images to measure the area of acetylcholine receptor (AChR)-rich postsynaptic membrane domains at the endplate and the area of synaptic vesicle staining in the overlying presynaptic nerve terminal. The second protocol compares the relative intensities of immunostaining for synaptic proteins in the postsynaptic membrane. The third protocol uses Fluorescence Resonance Energy Transfer (FRET) to detect changes in the packing of postsynaptic AChRs at the endplate. The protocols have been developed and refined over a series of studies. Factors that influence the quality and consistency of results are discussed and normative data are provided for NMJs in healthy young adult mice.

The neuromuscular junction (NMJ) is altered in a variety of conditions that can sometimes culminate in synaptic failure. This report describes fluorescence microscope-based methods to quantify such structural changes.

The neuromuscular junction (NMJ) is the large, cholinergic relay synapse through which mammalian motor neurons control voluntary muscle contraction. ...

Non-invasive Assessment of Changes in Corticomotoneuronal Transmission in Humans

The corticospinal pathway is the major pathway connecting the brain with the muscles and is therefore highly relevant for movement control and motor learning. There exists a number of noninvasive electrophysiological methods investigating the excitability and plasticity of this pathway. However, most methods are based on quantification of compound potentials and neglect that the corticospinal pathway consists of many different connections that are more or less direct. Here, we present a method that allows testing excitability of different fractions of the corticospinal transmission. This so called H-reflex conditioning technique allows one to assess excitability of the fastest (monosynaptic) and also polysynaptic corticospinal pathways. Furthermore, by using two different stimulation sites, the motor cortex and the cervicomedullary junction, it allows not only differentiation between cortical and spinal effects but also assessment of transmission at the corticomotoneural synapse. In this manuscript, we describe how this method can be used to assess corticomotoneural transmission after low-frequency repetitive transcranial magnetic stimulation, a method that was previously shown to reduce excitability of cortical cells. Here we demonstrate that not only cortical cells are affected by this repetitive stimulation but also transmission at the corticomotoneuronal synapse at the spinal level. This finding is important for the understanding of basic mechanisms and sites of neuroplasticity. Besides investigation of basic mechanisms, the H-reflex conditioning technique may be applied to test changes in corticospinal transmission following behavioral (e.g., training) or therapeutic interventions, pathology or aging and therefore allows a better understanding of neural processes that underlie movement control and motor learning.

The aim of the present study was to assess changes in transmission at the corticomotoneuronal synapses in humans after repetitive transcranial magnetic stimulation. For this purpose, an electrophysiological method is introduced that allows assessment of pathway specific corticospinal transmission, i.e. differentiation of fast, direct corticospinal pathways from polysynaptic connections.

The corticospinal pathway is the major pathway connecting the brain with the muscles and is therefore highly relevant for movement control and motor ...