[Music] thank you how to say for allowing me to present my data today and also for sponsoring this research and as we said the first one is going to be using the plasma sulfur amino acid concentrations to differentiate metabolized methionine contributions of room and protected methionine products the overall take-home message was the plasma dose response method actually differentiates the bioavailabilities of roman protective methionine supplements so for those who are not familiar with the plasma free amino acid dose response technique it's a robust in vivo method for determining how much of an amino acid or analog you can use it for both in the supplement gets absorbed and fed to lactating cows under what we call farm conditions allows for mixing the supplements in the diet and the normal aspects of eating and ruminating this also allows us to be able to feed to allow us to evaluate both liquid and dry encapsulated products because we're mixing it in linearity in response of plasma amino acids or analogs has been confirmed up to 88 percent 84 grams of lysine and 24 grams of methionine and 24 grams of methionine analog and 30 grams of histidine and there's others that have also shown this besides the ones that i've listed here so the overall objective was to investigate if the plasma dose amino plasma amino acid dose response method using total sulfur amino acid concentrations we express these as a percent of total amino acids minus total sulfurs can be statistically differentiated in determining of products the reason we use total sulfur amino acids instead of just looking at methionine is because the other sulfur amino acids do play a role in methionine um with that transparent nation pathway so it's important to look at them all so we had 10 multipliers from acai cows they were mid lactation it was replicated five by five latin square with seven day periods treatments for control where we added no methionine then we had the control diet plus 24 grams of methionine from smartaminem control plus 24 grams of methionine from amino sure xm control plus 24 grams of methionine from meta pearl and control plus 24 grams of methionine from time it um we only use the two levels 0 and 24 because we have shown linearity with the with methionine and so this way we could do this trial and not have a whole lot of cows the basil diet was 182 grams of mp lysine and 52 grams of mp methionine and it was balanced to meet the rdp rup and lysine requirements this is the diet we fed um it's 49 forage unfortunately it was 17.7 percent crude protein because uh our silages came in a whole lot higher in protein than what they were than what we thought along with some of the um proteins being higher this is a typical diet we do feed here at unh with these trials i try to keep the diets very similar among trials so the rumor rheumatoid methionine supplements were mixed into the tmr eight hours before feeding um this is all coming from the work that was done up in um minor institute so that we know if the product is degraded by tmr we're kind of taking that into account cows were fed at eight hour intervals and milked at 12 hour intervals milk yield and dry matter intake were determined daily and average by week milk samples were collected the last three days of covariate week in the last three days of each period and blood samples were collected from the coccyl vein on the last three days of the covariate week in the last three days of each period at two four six and eight hours after the morning feeding those blood samples were composited so we had one sample that was analyzed day and day by treatment were not significant i'd use prop um yeah the repeated procedure of sas to determine that um so then the days were averaged together and this was i tested this for both milk and plasma uh fixed effects for treatment period and square random effects were cal were within square the right procedure sas was used to generate linear regression lines slopes and confidence intervals and we noted significance at p 0.05 so now we're going to get into the important stuff which is the results of the trial so here we have dry matter intake milk yield energy corrected milk fat protein percent lactose percent and and as you can see there's no difference with dry matter intake or milk yield or energy corrected milk but with fat um we did see a decrease in smartimate with smart mean m and metapro and time it and we had no i mean it was a little bit higher in the amino sure xm with protein here we had the smartamine having the highest percent protein compared to control and compared to meta pearl and time it but it was similar compared to the amino sure xm when it came to plasma amino acids this is where things get real fun so we look at total amino acids we have no differences and that's one of the things we want to see but when we look at methionine smartaminem had the highest methionine concentration compared to the other amino acids with the control having the lowest um with amino sure xm being better than the other two cysteine we had no response cystothione alicythione once again we had the highest amount with the smart mean m then came the amino sharam the time at the meta pearl in the control if you look down here for the most part meta pearl and control are very similar they're not significantly different homocysteine no changes taurine this was a little bit of a surprise um usually we do have a significance here if you look numerically the smart mean m is a little bit higher but our standard errors for some reason with taurine were very high total sulfur amino acids once again we see smart amine has the highest total sulfur amino acids with control having the lowest amino sure m is lower than smartamine but it's similar to the timeet and then the metaperl is closer to control than anything else this is the graph um looking at the dose response relationships between the roman protected amino acid treatments and plasma expressed as a percent total sulfurs as a percent total amino acids minus total sulfurs um so when we analyze you're going to wonder okay you said you've had 24 how come these numbers are all over the place well when we analyzed we sent these products off to the university of missouri to be analyzed and what happened is when they came back he found out smart mean only provided actually provided 24.4 percent um the amino shirt m was 25.5 the net a pro was um 28 and the time it was 24.5 so i redid the statistics and then did it so it was how much they were actually supplying but still we're getting smarter means the highest then we get the amino sure then we get the uh time it then we get the meta pearl these are these two are this is significantly different from everything this is significantly different from everything these two are not so when we look at the bioavailabilities and for those of you who have not seen any of this kind of work to determine the bioavailability we take the slope of the dose response line so here we'll take the amino sure m and divide it by the the smart amine m we multiply by a hundred and we get thirty five so this bioavailability is relative to smartamine this is the meta pearl this is the timing now from work we've done here we have shown that smartamine is about 80 bioavailable so then we'll take these values and multiply it by that point eight this gives you the bioavailability overall so for amino sure xm it's 28 for meta pearl it's 7.2 and for timeout it's 19.7 and these are the confidence intervals down here um these confidence intervals here are what we normally see the time at confidence interval was very high once again i'm not 100 sure why that happened so in conclusion the plasma amino acid dose response method was sufficiently sensitive detect differences in methionine bioavailability of different commercially available rheumatoid methionine supplements and based on the comparison of the dose response slopes using total sulfur amino acids expresses the percent total amino acids minus total sulfur amino acids amino germ was 35 percent as effective as smart medium metapro is 9.3 and time at was 24 as effective as smart main m in providing methionine so with that i will take any questions well thank you uh nancy for uh for your uh a nice uh presentation uh and describing the methodology that you used uh we have a couple of questions here um the the uh the first one is uh uh did you analyze for the loss of roman protected methionine for each product in the tmr after the eight hours uh pre-incubation no we did not um that's not something we routinely do here um it because i don't really have the methodology that miners has come up with i'm trying to get up to minor to learn that tech technique um but due to covet everything's kind of been screwed up because it is something we would like to start adding to um the technique but until i can learn their procedure it's kind of no right now hopefully in the future yes okay but at least uh so the assumption for this this uh that you took in here is that uh they all were treated similarly and and if there was in fact an effect on each one of those uh could have been picked up by the values that the final values that you've gotten is that that's correct okay well but it would be nice to uh to have those i think we will agree that would be nice to have those values eventually so i know that you're working on that nancy so yeah i i think you are out of the hook for now yeah uh we have some other questions uh why why do you think that some of the sulfur amino acids move up more than others um well this is interesting because in all the trials i've worked i've worked on with methionine usually we do get a response in cystine and taurine i'm not 100 sure why with this trial we did not um in some of it all depends on how deficient the cows are before we start the trial because if they're not as deficient you're going to get some of those other sulfur amino acids you're going to get methionine not you're going to get it going into cysteine down into homocysteine down into taurine because you've got enough methionine for the cows to use these cows are also a little bit later in lactation than what i've used before so it could also be something to do there it's really one of those questions um each trial i've done with smartim with a methionine product usually is a little bit different and i don't not 100 sure why um because the proteins were fairly um consistent the protein percent protein is fairly consistent with what i've seen before the other thing is i also don't know what effect having 17.7 percent crude protein had normally these diets are closer to 16. yeah well i think we had another question what's kind of related to that and i think you answered it uh that it might be the stage of the lactation as well in terms of the uh of the uh the use how how how methane is uh is directed by the cow's metabolism according to uh to her needs at the time so so that might explain that have another question and and then we will move on to the next presentation for lack of time uh and the question is could you please explain why uh liver metabolism and mammary extraction of methane done that do not affect plasma methionine concentrations i mean they might i mean we're not 100 sure because if you look at some of the work elaine lapierre does has done you know they do show differences across the mammary gland in the liver with plasma amino acids but because we're feeding these and we consider them at steady state because we're giving the cows you know product every eight hours we think the body you know the liver and the the mammary gland have kind of it's all in a steady state and everything is being extracted at the same rate you're not getting more at one time versus another time um so therefore whatever is going on in the liver in the mammary gland we're not picking it up when we're taking these plasma amino acids and just one one more i i since since i'm i am the host i have a little of a little bit of a control of this uh uh the the idea also is that the cows are not gaining our body uh losing anybody weight either correct no um as long as the trials are kept short and that's one you know one of the reasons about nice having a seven day trial is they really don't gain body weight or body condition score they might go up from a 3.25 up to a 3.26 and to me that's just the scores it's not like we're going from a 3 up to a 3.75 any change in body weight or body condition score is real small and it all depends on how long the cows are on trial this was a six week trial so we really didn't gain anything okay thank you nancy and uh for uh for in a matter of time respect uh let's go to uh your second presentation so i don't i don't think i need an introduction uh for you you're i've you've already been introduced so please move to the uh to your next presentation if you may thank you nancy okay my next presentation is using the plasma amino acid dose response method to validate the bioavailability of methionine and lysine and smartamine ml this was new to me because we've never evaluated two amino acids at the same time so this was kind of exciting and also where i was hoping it really would work and it did so the bioavailability the take-home message is the bioavailability of lysine and smartment ml we confirmed it to be a minimum of eighty percent and we also confirmed the bioavailability of methionine to be a minimum of eighty percent so uh rumen protected sources of methionine and lysine are needed to be held at the same scrutiny as any other ingredient in their capacity to provide metabolizable lysine methionine especially in a combined product the plasma free dose technique has been proposed as a method to estimate these two as we've seen from my previous talk and some other talks this is the method we propose and it does seem to be working so this is a repeat of everything i talked about in the other one so i'm not going to go over a whole lot um it's a robust method it's in vivo so um you know we've got everything going on with the cow we can mix the supplements in the diet this allows us to use both liquid and encapsulated and we've shown linearity and other people have shown linearity of plasma amino acids methionine lysine hmtba and histidine in lactating dairy gas the objectives was to determine the bioavailability of lysine and smartamine in smartaml and we had a rp lysine supplement that we were using that i've tested before just to make sure everything was working well um it was like almost like a positive control um and then the same thing with the smartamine we were feeding some smartamine m because i've done work we've done work with that before so it was kind of to also help validate this methodology again with some products we've already tested so in this trial we had eight multiparous women kla cows uh they were 159 days in milk it was a replicated four by four latin square the treatments were a control diet so in this diet we had no methionine and no lysine um and then the control diet plus 60 grams of lysine and 20.5 grams of methionine and that was apple masala infused we had the control diet plus 60 grams of lysine plus 20 grams of methionine from smartamine ml and then the last treatment was 60 grams of lysine from an rp lysine product and 20.5 grams of methionine from smartaminem the basal diet provided 188 grams of mp lysine 68 grams of np methionine and it was balanced to the rdp rup and we met methionine and lysine requirements so unlike the last study here we made sure that the cows were adequate in both lysine and methionine once again this is the typical diet we feed here at unh me um this diet uh was not as high in um crude protein this one came in at 16.7 i was shooting for 16.5 so we were close once again it was a 50 forage diet um just we had good quality forage at the time so we were feeding a little more forage they were also a little bit later in lactation once again we mixed the rp methionine supplements in the tmr eight hours before feeding the cows were fed at eight hour intervals melted twelve hour intervals had milk yield and dry matter intake were determined daily milk samples were collected the last three days of the covariate week in the last three days of each period blood samples were collected from the coxial vein on the last three days of the covariate week in the last three days of each period at two four six and eight hours after the morning feeding those samples were composited together and then so we had one sample per cow per day and that's what was analyzed once again uh day and day by treatment were not significant um so the days were averaged together and this was true for all the um i think all everything i looked at you know dry matter intake milk yield and all the plasma work and all the blood data and milk data then we analyzed using the mixed procedure of sas fixed effects for treatment period and square random effect was cow within square the proc right procedure of sas was used to generate linear regression lines slopes and confidence intervals and what i forgot to tell you in the last one is it was the means that the ls means from this um proc mix that we used in the proc reg significant effects were noted at p less than 0.05 so once again we'll get to the good stuff which is the results um this is your dry matter intake and all your milk data this one we have a little more milk than what we did in the last one in since we were formulating to the diet to be both adequate methionine and lysine the basal diet um we really didn't expect to see anything and that's exactly what we thought um but anyway as you can see dry matter intake milk yield milk fat fat percent protein protein grant yield lactose percent lactose shield mun's four percent fat corrected milk and energy corrected milk were all similar um and this is what we expected if i hadn't seen it then i would have been a little more worried um when it came to the amino acids um this is where we did start to see some stuff um so we're going to start with lysine first our control was the lowest which is to be expected infusion and smartiman ml were very similar and this is what i've seen before when i've infused and used smartaminem with methionine this was the first time i've used smarmy ml so this was encouraging and the rp plus the smart me this is similar to where this product falls when i've tested in the past so that didn't surprise me when it came to methionine once again this was control is the lowest is what we expected with infusion and smart amine ml being similar and then for this this is just looking at smart amine m because there's no methionine in this rp lysine product so this was also encouraging telling us yes things were going nicely here we had no effect in cysteine again we had an effect in cystothione alice with the thione here as long as we fed a methionine as long as methionine was provided we got an increase almost 16 nothing this one i never see an increase in and taurine once again my standard errors for taurine were really high i'm not sure why i have talked to the university of missouri about this and they're not 100 sure why but these the ones that did get methionine are numerically higher than control total sulfurs amino acids as you can see they're all very similar and then the total amino acids were not different which is what we want to see so this is the plasma lysine as a percent total amino acids minus lysine for those of you that um are not familiar with this this is the way we express lysine um in so yeah it's a way of express license sorry um once again we sent these products off to be analyzed um to see what um is actually in the product it's again why these are not all straight at 60 so the analyze content of smart me m was 44.1 which provided 60.5 grams of lysine so the smart amine m is just a little bit beyond the infusion in the rp lyc lysine was 39.4 which provided 49.1 so they were close to what they were saying but they were a little bit lower a little bit higher as you can see for the lysine all three are significantly different with infusion being the highest then we get smarterman m and then we get the rp lysine which is what was expected so to determine the bioavailability of these products we have infusion smartamian ml and the rp lysine these are the slopes that were generated so once again we take the slope of the product and divide it by the slope of infusion multiply by a hundred and we get 80.7 for smartimian ml and 46.7 for the rp lysine this is right around where i usually get this value it was a little bit higher but it was within the range so that made us feel confident that yes this is all working and these are the confidence intervals around those two products for smartamine i mean for methionine once again it's a plasma total sulfur amino acids as part as a percent total amino acids minus total sulfur amino acids so here's the infusion here's the smart amine m and the smart amine ml okay nothing is significantly different here they all kind of overlap except the smart amine ml was was significantly different than the infusion but not by much it was just barely and once again these were tested so the smart amine m provided 20 you know 20.4 grams and the smart mean ml also provided 20.4 so this methionine part of this really was where they where they said it was okay so the bioavailability calculations for smartimian m we get 83.5 and for smartimian ml we get 81.3 here's the confidence intervals very similar this is a little bit higher than what i've gotten for smart mean m in the past but it's still within if you looked at my confidence interview intervals for smart amino ml from what i've done before it falls within that range so it wasn't really that far off and we were very glad so in conclusion the plasma free amino acid dose method can be used to determine the bioavailability of both lysine and methionine and rp amino acid supplementing containing both in the same study it is a little bit difficult but it can be done and the trial confirmed pre previous measurements of bioavailability of lysine and methionine in the rp lysine supplement and the smartaminem so it kind of validates the cleanse that people that they have for both their lysine and methionine in smartening ml these are the references that were cited in the talk and with that i'll take any questions for those who have not been to unh this is what these cows look like when we've got them hooked up and doing these trials great thank you nancy and uh and uh obviously this is a little bit more involved trial involving two amino acids uh i do have a question and i forgot to tell the audience that uh after we are done with the four presenters uh we will have a time to ask questions to any of the presenters so i ask all of the presenters to hang out for a little while after you guys are all done just in case if the audience has some questions that may be related to all the presentations at once uh do you have a couple of questions uh nancy is how does the accuracy of this method compares the to the stable isotope method uh being used by uh virginia tech dr mark hannigan i haven't really looked at it that close daniel if you want to know the truth um so i can't really answer that question um it's something i need to look into especially because i am writing another paper um so we i will be looking into that but as of right now i can't really i really can't comment on that okay uh that's that's that's good maybe we have to have a chat with dr romar hanigan and compare notes at some point yeah yeah i have another question uh um i think this is an interesting one uh uh and it's related to the first trial but it could be related to any uh using these technologies uh and this is specifically smart i mean had higher methanol concentration in plasma but also the cow secreted more methane in milk is the latter accounted in the eval in the availability calculations yeah because if it's in the milk then it's not going to be in the plasma um because like i said once again these cows are what we consider in steady state so if the mammary glands pulling out methionine to put into the milk we're not going to you know if i had not had these cows and stay state then yes the plasmas would be all over the place but i think because they're in steady state we're not seeing the effect so even though they're pulling out more methionine they still have high methionine in their plasma and also that could also explain some of the reasons why cysteine and some of those other total sulfurs are not increasing or decreasing at a at any kind of rate okay um yeah uh that's something that uh uh it's an interesting question to uh to really think about uh nancy but uh but uh uh we maybe we have time to discuss afterwards as well uh well the other thing is we've never we've never taken milk and run it for amino acids so i can't really tell you if we are getting more methionine in the milk yeah yeah yeah just we just have to assume that or really plant the landia the whole amino acid plasma i mean amino acids in in milk protein an observation for this trial uh neither assisting or almost existing uh increasing this trial either so so i mean it's a kind of something that i mean i i know that you keep track of all your trials and as you said in some classes that those do change correct no i never get homocysteine to change okay you gotta remember where homocysteine lies in the whole transplant nation pathway and i don't think you're ever going to get to change because if there's an increase in homocysteine it's automatically going to be going somewhere else so that's one of the few sulfur amino acids i think that stays very constant in the body it's not going to increase or decrease with added methionine or or you know any of the other products that you could you know if you want a dead cysteine so that one never increases and i think it's all gonna be where it is in the cycle cysteine yes i do sometimes see cysteine increase but it's usually in cows are a little bit earlier in lactation okay yeah that this these questions are going to become important after matteo's presentations in terms of the plasma amino acids methodologies used um i have one last question for you nancy uh and i please uh ask you to stay uh just in case there are some more questions to come after all the presenters are done can you disclose what was the roommate protected methionine in gluten-free lysine use in the second trial yes i can because this was an addiso trial so i really you know it's like i have no no i haven't signed any confidentiality with the company it was an agenda it was the edgy pro 3g okay okay uh thank you nancy and uh uh uh for your questions and again uh to all the audience uh nancy will we stay uh with us until the end and i will have some time for uh for uh having uh more questions uh related to her presentations or in general to all of the audience the next presenter is uh is dr lalu balool he is the solution manager for adiseo is based in france uh la luz has been working with us for several years now and he is going to discuss uh the identification of a dietary pla facial and physiological factors a potentially affecting impeding responses of lactating dairy cows to dietary fortification in metabolizable methane and meta-analysis la luis yours so hello everybody and thank you for joining us this year virtual room tables this is a project this project was done in collaboration uh with our colleague crystal long from agropolitec to identify dietary and physiological factors impeding responses or lactating daily curves to dietary fortification and metabolizable methane and to do that we use the meta-analysis approach so our take uh how important here is the the responses of milk protein content and yield to methionine supplementation in lactationary codes vary according to the lactation period some targeted amino acids and chemical parameters okay so several studies shared non-consistent responses to methionine supply on milk production and compositional responses probably due to different uh nutrient content and animal characteristic real can encoders many years ago demonstrated an increase of milk protein content and yield when digestible methionine increased however or high in a high unexplained variation of those responses could be observed at a given level of digestible methane so the objective of this study was to determine the interfering factors impacting milk protein content and yield responses to riemann protected methane a meta-analysis approach was used according to several encoders starting by establishing a database from selected pre-reviewed international publications where the others used agreement protected methylene as metasmart or smartaminem knowing that some diets criteria were reported in the papers we made a homogeneous and complete description of chemical composition and nutritive values of diets according to inner 2007 feeding system validation has been done by comparing the characterized and observed values for crude protein ndf metabolizable protein net energy digestible methionine and digestible lysine as they are the main common parameters supported by the earliers after uh graphical and meta design studies we studied response responses within study responses and a model has been developed and last we studied the interfering factors impacting responses responses according to the slopes and ls means and residuals here are the variation range of the meta design of the database gathering in total 27 publications with 56 treatment which covers a large type of diet used in the practice where we have here dry metal intake ranging from 13 to 28 kilogram percentage of concentrates from 30 to 60 percent starts from 15 to 40 percent nda from uh 25 to 45 percent metabolic protein from 80 to 120 gram per kilogram diameter and not energy of lactation from 1 600 to 1950 kilocal per kilogram july meter a quadratic model has been obtained for milk protein content response to digestible methionine with lower lmse and higher earthquake er square as you can see here in this table which shows how the robustness of the model is so lactation period for milk protein content was not significant and this model predicts 0.14 percent more of milk protein content when digestible methionine increased from unbalanced diets around 1.8 to balance a diet for methionine around 2.5 percent digestible protein a linear model has been obtained for milk protein yield response to digestible methionine with a lower rmse and higher square square which tells also how the robustness of the model is and the lactation period was significant on the slope of the model suggesting higher milk protein yield response at the early lactation period compared to mid lactation and the global model here predicts around 51 gram per day more of milk protein yield one digestible methionine increases from imbalanced diet to balancer diet in terms of digestible methane interfering factor a study figured out two parameters impacting milk protein content response to methionine supplementation for a given level of methionine milk protein content decreases when ether extract content increases and this is something that we observed many times in the practice and firstly for a given level of methionine milk protein content increases when digestible glutamite level increases as well the interfering factor study figured out several parameters impacting milk protein yield responses to methionine supplementation even though within steady slopes figurative negative effects of digestible threonine it seems that this effect is more pronounced when digestible cerealine is higher than five percent of digestible protein which means that the recommendation for uh for um uh theronine digestible theron should be not exceed five percent of digestible protein however as expected for a given level of methionine milk protein yield increases with dry matter intake or starch or decreases with ndf interestingly for a given level of methionine milk protein yield increases when digestible histidine or digestible leucine increased so uh as as a conclusion for this uh work uh each yeah this project shows that it is possible to predict the responses of lactating dairy cows uh as function of human protected methionine and also figure out interference factors uh from animals and diet characteristics that could impact those responses there's results uh also may help targeting further experiment and help in uh uh dietary formulation interference factor study is in going to consider milk yield milk fat content and yield responses diet characterization according to inner 2018 the new you know feeding system and also using considering also other units for digestible methane as a gram per day or a gram per mega cal metabolizable energy the first part here is already done i did it uh yeah we did it uh two or three weeks ago i mean uh by considering milk yield responses milk fat content and yield also responses uh this part was done and now we are validating the models and also the interfering factors parameters then we are going to move to the next step thank you for your attention and please don't hesitate to ask any question you may have i will be pleased to answer them thank you la lu uh it's a lot of data uh and a lot of information to chew uh in uh in such a short time but uh this obviously these methodologies allowed us to really uh look into having a deep in in looking to how the cows metabolized all these amino acids one question is uh why do you use uh uh if i understood you correctly you only use publications that only either metasmart or smartamine were including the treatment is that correct and why if that's correct why yeah exactly danielle for this first step we established the database uh only from international publication uh where the others use it only smart i mean m and meta smart because first we know how the bioavailability uh of this product is we did with uh with the university of new hampshire we determined well the bioavailability here many years ago and confirmed that recently uh and uh so uh as the enough uh the in-law feeding system established the recommendation in their database uh where uh where uh they used they used uh in fusion infusion uh publication then uh as we know that we have a good correlation between uh the infusion data and all and smart amine or metasmart product plasma methionine so we first choose to start working with smartamin and metasmart and then we said uh when we determine why sometimes the the responses to methionine from smart amine or metasmart varied in the practice we want to uh to understand which parameters could impact those these responses and then we said the second step will be also move by considering other other products riemann protected uh methane from other products thank you lalu another question is that this responses are obviously based on in-laws and biology in terms of estimating the digestible methionine could you expect different results if other models are used to estimate these values well this is a very good question daniel and i i really i don't know if we are going to to to expect the same uh the same response and also determine also to get the same interference factors but i will be happy to collaborate uh to collaborate on this uh on this way to uh to consider also not only uh in our feeding system the old one or or the new one but also uh using uh the other the other uh feeding system like nrc or or cncps or yeah that would be that would be nice to see if all the all the biologies uh uh meet into the same same conclusion yeah exactly uh and i have another question uh uh is there any do you have any biological reason why threatening a good negative impact the response to methionine so excellent question danielle we started we started interpreting the data because the first step was was the focus on the statistical and meta-analysis and then we say that we have now to uh to see if the biology meets what the statistic says so um the first explanation that i have right now that tyronin is involved in the metabolism in the in the catabolism of methionine isoleucine and um and violin uh in the mitochondria so when we get when we have a higher thyronine so uh the the they stimulate the catabolism uh of those three amino acids through uh alpha ketone butyrate and and properly consume a in the middle country that's my explanation yeah well we'll uh certainly uh uh one of the beauties of this type of analysis is that unearthed questions is not to answer any of them so that's that's a good one to have and i have another one that is also very interesting question for you lalu is in terms of uh well first of all uh two questions uh did you see any negative correlation between the digestible threonine and any other amino acid so that's the only one that you saw the coral the negative correlation with all the negative correlation i saw it is uh for um for for me protein content and make protein yield iso-only therian as negative correlation we have studied positive correlation we have also the glutamate as as positive correlation yeah we need a lot of that for many things exactly and this uh this essentially leads to the second question of the same the same person is uh did you look it uh into dietary starch uh instead of just energy as a whole or did you separate the energy source uh in terms of uh the responses of these these models oh um actually for uh the milk protein uh milk protein yield we have starch uh in the ls means as interfering factor but the correlation is not higher it's not um yeah the the the air the air square is no higher that's more reason why we decide with uh with a global attack team to not consider it for yeah and now but for example as i said for the second step for a milk fat and content and mig fat yield we we finished this this part and what we get is for example net energy of lactation is an interfering factor and also the the digestibility of starch using interference factors for uh for milk uh fat for example i have one more question for you la lu and then i will let you go for now please hang out until the end uh do you remember on top of your heads uh the uh the fat uh content of the diets i mean you have enough white variation in them in terms of uh fat from from the in the diet yeah uh i think uh that's uh you mean the range of variation of fat in the diet correct daniel yeah correct yeah the variation i think is from uh yeah 2.5 percent until uh seven if i remember well oh okay so seven percent yeah yeah then maybe you have enough variation there to look into this uh this fat uh uh impact as well yeah exactly and what we saw the uh when we start uh when we start uh to be higher than 4.5 or five percent then we have a decrease of the responses uh so the fat content in the diet should not be higher according to those results should it should not be higher than five percent okay i have one more question did you how how did you account for differences in the number of cows in the different treatment groups oh sorry say it again daniel how how did you account for the differences in the number of cows in the different treatment groups oh uh the number or the number of cows did not uh did not taken into account in the in the in this meta-analysis maybe something that we should take into account but about a north okay okay uh you uh i would assume that all these were published trials and the number of cows would be between per treatment would be between i don't know 10 and 15 nothing and nothing out of the ordinary um yeah right yeah okay but this is something that we might need that you might need to look at it into okay well thank thank you excellent questions uh for for for all the speakers so far and i will uh i will uh ask mateos uh to join us uh for his last presentations um mateos uh uh he has uh just uh passed his police exam uh on friday uh and he is uh i think he he passed his past uh he hangover uh now um uh so mateo thank you for for staying with us here and uh and i was just uh congratulations for your prelims and i i the floor is yours uh yeah thanks danielle uh good morning everyone uh thanks again for joining the azio virtual round table uh for this last presentation uh we're gonna be discussing uh quantification of covant plasma amino acids uh via lcms uh we're gonna be talking about two different methods one it's a novel method which involves no derivatization at all so let's work with sample preparation and the other method is a more traditional method that involves derivatization i just want to thank all my colleagues in here that were involved with these especially dr sebastian hilla apillo we we have worked a lot on these methods all right just to get us started uh the most commonly used technique for bovine amino acid quantification involves uh a post column mean hydrogen detection h by h plc but this technique is costly and has long runs that may vary from one to two hours and also has many other limitations from a technical standpoint other techniques were developed in the last decades for example gas chromatography or liquid chromatograph coupled to a mass spectrometry and those techniques those techniques have the potential to overcome overcome these limitations there are several methods using derivatization but again they are they can be time consuming with all the pipetting of variations and more recently uh under avatar's methods became available uh you have less labor sample preparation faster analysis uh however these method these methods are not yet validated for for bovine plasma this is just an example of a single quad core lcms that we have on the right you are seeing the the hplc and then on the left the mass spectrometer mass spectrometry and then uh here it's a column that we use for the undivetized method you can get all the amino acids in 10 minutes all right so with that our objective if they were to evaluate and compare a pre-column derivatize method with a novel under vatice method to quantify bovine plasma amino acids by isotope dilutionation via lcms a single quadrupole cms this is how we uh prepare our samples you have your plasma sample here and then we add the internal standard the isotope this is all by weight and then we add your uh acid perichloric acid to eliminate the proteins centrifuge and gather supernatant with filter and then uh we use these methods the pre-colon derivatize method that has a solid phase extraction uh derivatization and then a liquid liquid phase extraction just note that we use one microliter for injection into the lcms and then the other method was under advertisement we use with there's no uh solve the phase extraction no liquid liquid liquid extraction would you just go straight and then injected five microliters into the lcms and then of quantification is based on error under the curve and the ratio of your target amino acid and then your isotope so how we evaluate these methods we look at linearity of mass to charge ratio it's just a molecular weight of amino acid divided by by the charge and then signal sensitivity of the carbon 12 using five to six point standard curves that's the range 1.1 to 500 micromolar we had a full plasma sample from lactating dairy cows and then we had quadruplicates and spiked different amounts of amino acids and look at recovery rates if the method is accurate we expect about 20 percent a hundred percent i'm sorry and then uh lastly here we use 24 plasma samples also from lactating dairy cows to direct compare the two methods a couple things that we use here linear regressions concordance correlation coefficient which involves precision and accuracy and then blend output block test moving on to results i just want to show you chromatogram this is signal sensitivity on the y-axis and then uh the time of amino asks were coming up just as an example we are seeing a tiny here and you can see there are peaks overlapping which is the isotope okay they have different mass charge ratio but they elude at the same time and then we we look at the ratio between them this is a beautiful chromatogram with all peaks very sharp but very defined defined peaks for the under that eyes i just separate them in each amino acid so you can see better uh this is the first segment uh we separate the analysis segments uh the first segment here we're looking at methylene also very good peaks and all the other amino acids for this first first segment were also good the second segment is where the challenge is those amino acids in green they look good but those amino acids in red you can see some they do not have a resolution for the peak and they have some have a lot of background some some noise there okay for the third segment which is the best they are the positive amino acids they easily ionize and you have the histidine lysine arginine here very good peaks very sharp peaks you can see here moving on to some data this is the pre-column derivatize all the essential amino acids we're looking at the linear range for the standard curve for each amino acid and then the signal sensitivity don't worry about those big numbers for now and then the r square for the standard curve a very good r squared for all the essential amino acids here for the non-essential amino acids similarly the linear range the signal sensitivity and then the r square works really well we could get all the amino acids for this pre-column derivatize method for the under advertised method the essential essential amino acids first we're looking at r square they they were also very good all higher than 0.995 but then when we look at uh the ratio of the lower point of the standard curve dividing the derivatized uh to the under advertised method we see a greater signal sensitivity using derivatization some amino acids vary from three times higher some have a hundred times higher look at triion in here uh that's a huge difference in signal sensitivity for the known essential amino acids that's where a little bit of the problem comes up but you're seeing some amino acids they have poor peak resolution or we say a signal to noise ratio less than three and some they do not have linearity and again some have low signal sensitivity with more than 100 times higher for for the derivatization method for plasma recovery and coefficient of variation so if the method is accurate we expect to recover 100 right so that's the uh range that we had for the derivatize method for the essential amino acids and no essential amino acids all of them were equal to a hundred percent when it ran stats the cv range very low of 2.6 to 5 percent and 2.2 to 10 percent however when you look at the under advertise method we also we observe a low coefficient of variation but for the recovered recovery rate range some amino acids we recover a little bit more uh valine here that was 120 percent and then for the non-essential amino acids glutamine that was a little bit below uh a hundred percent this is a direct comparison between the pre-column the derivatives and the androgens you're looking at the essential amino acids here on the left this is the average for the 24 samples that we run and this is some parameters for the linear regression person correlation root mean square error and then we decompose the meaningful error of prediction with mean bias and slope bias you can see some amino acids have really good concordance correlation coefficient which means they were that the two methods were in agreement and very low is look biased for these for these methods some some amino acids for example histidine uh the concordance correlation coefficient was low and you can see there was a problem with slow slow bias for this amino acid for the non-essential amino acids again some we were able to to quantify and then the ones that we were able to quantify in here this is the linear regressions again all the parameters only two amino acids will deserve a high concordance correlation coefficient meaning that the methods were in agreement those were glutamine and asparagine but the other ones they have lower ccc uh this is just a different way to see the data in particular interest here methylene we have a regression plot on the left the derivatize method on the y axis and the under advertised method in the x-axis you can see the the correlation the pearson correlation 0.99 and then the blend output block is another way to see the data if the methods are in agreement we expect the red solid line to be at zero in that case from a timing we have a mean bias of only two micro molar and most of the samples here they lie between of the limit of agreement so we we can conclude that methods were in agreement just as a summary and conclusions overall we evaluated these two methods for a quantification of amino acids in both bovine plasma and then the two methods had linearity precision and accurate recovery rates for most of the essential amino acids despite the lower signal sensitivity obviously for the advertised method the under advertisement had some non-essential amino acids with poor chromatogram peak resolution or no linearity to mass charge ratio and most essential amino acids had a high piercing correlation in the concordance of correlation coefficient and they were in agreement and comparing comparable with a more a traditional method that involves a pre-column derivatization and then no essential amino acid they were a little bit less comparable our conclusion is that sample processing and derivatization are still required for optimization of signal sensitivity but that's specific with the equipment equipment equipment that we have which is a single quadruple mass spectrometry which has just one mass filter with that thank you for your attention and i'll take any questions daniel thank you uh thank you mateo's uh excellent work i know that it gave you a uh lots of headaches and uh and uh i don't know if you have a love or hate relationship with that machine but i know they cost you a lot of headaches uh in the process and i know that sebastian helped you quite a bit as well so both of you did an excellent job um did you uh all the uh the ranges that you use for these amino acids are those within physiological concentrations of the in the plasma of dairy cows yeah that's a good question yeah that's what we try to do for the standard curve to look at what's reporting the literature and have a standard curve that will cover all the physiological range observe uh for all these amino acids have you uh now you compare the the the two uh the two protocols that you've used using these kits have you compare uh let's say now that uh is the derivatize protocol is much better uh or at least more robust did you compare that one with the traditional methodology um we did not compare in-house let's say so i analyze samples that were sent to uh to use that hplc method and our method here they were very comparable for some amino acids some amino acids vary a little bit but to do that kind of lab experiment we we need to know exactly what's going on uh with sample prep so it's best to do at the same location uh that i think that will be more a fair fair comparison for for the methods well at least uh methylene it looks very very comparable with the hplc method yeah my my understanding and forgive for forgive my ignorance but i think uh if if anything uh using the mass spec would be more precise than than using any other methodology is that is that a correct assumption or assessment materials yeah that's correct i mean with hplc we just have peaks coming up and then that's based on rotation time right when the peaks are coming coming out of the column with the h with the lcms mass spectrometer you can increase a lot your sensitivity because the detection is based on the molecular weight the mass charge ratio for that particular amino acid great yeah well considering the time that it takes uh to land these samples and uh and uh and uh particularly uh how how how how many samples you can process uh looks like uh you know we we we might have to uh be need we need to be looking into this process uh i know we are so excellent thank you for your presentation and uh thank you i don't know if there are any other questions uh in these regards uh um are there any any other questions uh for all the uh the speakers i think uh this this last presentation that matches up very nicely with what has been done uh or been presented for you today uh considering that you know in the in the those response uh plasma amino acids is our key uh and then uh and then on on the meta-analysis uh you know we rely on on a lot of this information as well so uh any questions in general for uh all now the presenters one question uh and this is uh for you mateos uh how how close are are we to to having a robust procedure for uh uh and how and for how many amino acids uh with the method that we have right now these commercial kit you can get it to end amino acids pretty easily i think it's very robust especially if you do buy weight and use internal standards uh the isotopes so it works really well you can get all the twin amino acids pretty easily yeah uh can can you get uh besides the amino acids can uh can you use these uh similar are there any kids to detect any other metabolites in the plasma um there are some metabolites that you can get i think the key you can get up to 60 uh compounds but some amino acids you probably need more sample prep or a different equipment for for a better detection and better signal intensity it varies from metabolite to metabolite okay but for now for for the 20 amino acids you feel that uh this uh this the derivative protocol is robust enough to uh to you can catch the 20 amino acids yeah definitely definitely can it's a very nice assay it's just just take a take some time for for example preparation but once you get more familiar with with the essay things things things move faster yeah great excellent okay any other questions uh to to any of the presenters i think we did manage to answer uh the questions as we move along uh so if there are any other questions uh that you can think of afterwards uh send it to me and i will try to uh to uh reach uh the speakers and ask him directly so uh with that uh i am a half an hour uh later than than the time allowed it a lot of time uh i'm looking forward for tomorrow's presentations don't forget 8 am central standard time thank you all for participating and have a good day