1 00:00:00,420 --> 00:00:17,430 I think it's just sort of. So Simon studied at Cambridge and then was at Addenbrooke's and qualified, 2 00:00:17,430 --> 00:00:23,280 moved to Nottingham for his basic surgical training and came to Oxford in 2006, 3 00:00:23,280 --> 00:00:35,430 taking up a position with the evidence base in transplantation and completed his thesis and then was appointed as honorary consultant, 4 00:00:35,430 --> 00:00:43,800 transplant surgeon and senior clinical research fellow here in October 2017. 5 00:00:43,800 --> 00:00:54,840 So and I'll introduce James at the same time. James is an academic clinical lecturer in transplantation and has a contract with University Hospital, 6 00:00:54,840 --> 00:01:03,330 Coventry and the University of Oxford looking at this live donor kidney transplant and complex vascular access. 7 00:01:03,330 --> 00:01:09,120 And this is the first appointment to the Coventry Oxford Transplant Network, 8 00:01:09,120 --> 00:01:19,690 which is a UK transplant collaborative which is aimed at improving patient access to transplant by sharing resources to the centres. 9 00:01:19,690 --> 00:01:29,000 I think we're starting with Simon. Thank you very much. Bright morning, everybody, thank you for coming. 10 00:01:29,000 --> 00:01:33,110 So I wrote the title before I'd actually thought about what we're going to talk about this morning, 11 00:01:33,110 --> 00:01:39,680 so actually we're going to focus on kidney preservation, having talked quite a lot in the past about the liver. 12 00:01:39,680 --> 00:01:43,730 And so I'm going to talk about some of the clinical research that we've been doing and part of. 13 00:01:43,730 --> 00:01:48,970 And then James is going to talk a little bit more about some of the translational in lab research. 14 00:01:48,970 --> 00:01:54,340 So for those of you, the work in the chat show, this is a fairly familiar sight outside the theatres, 15 00:01:54,340 --> 00:01:56,830 particularly if Sanjay's been on call for the weekend. 16 00:01:56,830 --> 00:02:05,680 That's a post Sanjay weekend on that on the right hand side there, which is the mainstay of how we store kidneys in the UK at the moment. 17 00:02:05,680 --> 00:02:10,930 So we put them in ice boxes, so cold fluid in ice cooled down to about four degrees. 18 00:02:10,930 --> 00:02:21,700 And this is what we've been doing, probably for about 30, 40, 50 years in the UK since since we started transplanting routinely in the 1960s 1970s. 19 00:02:21,700 --> 00:02:27,190 And there's a very good reason for it. It's very simple. It's very cheap. Logistically, it is straightforward. 20 00:02:27,190 --> 00:02:34,660 It doesn't require power. There are no moving parts to break and nobody has to sit with it and watch and make sure that it's doing what it should do. 21 00:02:34,660 --> 00:02:43,780 But it does have its limitations. So when you store an organ at four degrees, metabolism is slowed, but it's not stopped completely. 22 00:02:43,780 --> 00:02:51,040 And so there's still anaerobic metabolism carrying on in the organ. You get accumulation of metabolites, you get depletion of ATP. 23 00:02:51,040 --> 00:02:56,530 And so when you put the organ in and you reproduce it in your recipient, you get an ischaemia reperfusion injury, 24 00:02:56,530 --> 00:03:05,990 you get inflammation, which then primes the immune system with the risk of of inflammation and damage. 25 00:03:05,990 --> 00:03:10,520 There are lots of reasons why we might want to reconsider this idea of cold storage. 26 00:03:10,520 --> 00:03:18,320 So over the last 10 years or so, as you can see from this graph from an SBT, our donors have been gradually getting older. 27 00:03:18,320 --> 00:03:25,850 Older donors generally have more pre-existing injury from hypertension, diabetes, cardiovascular disease. 28 00:03:25,850 --> 00:03:31,820 And so we're starting off with slightly more marginal kidneys than we would have been perhaps 10 20 years ago. 29 00:03:31,820 --> 00:03:36,440 Equally, the type of donors that we're using has changed as well during that period of time. 30 00:03:36,440 --> 00:03:42,170 So our ideal Dana Oredo deceased donor is a brainstem that donor because there's no period 31 00:03:42,170 --> 00:03:49,310 of warm ischaemia prior to procurement of the organs we're seeing now and using now. 32 00:03:49,310 --> 00:03:57,620 More and more donors after circulatory death, CD donors where there's a mandatory period of five minutes of warm ischaemia before you can start the 33 00:03:57,620 --> 00:04:05,260 retrieval operation so these organs are more injured before we even start this preservation process. 34 00:04:05,260 --> 00:04:08,080 So before we start looking at some of the tools we've got available to us, 35 00:04:08,080 --> 00:04:12,940 it's worth thinking about what the ideal organ preservation method looks like. 36 00:04:12,940 --> 00:04:16,840 So obviously we want to prevent damage during storage, 37 00:04:16,840 --> 00:04:26,260 but we also ideally want to be able to repair some of the damage that's already occurred during that procurement process. 38 00:04:26,260 --> 00:04:29,890 We'd like to be able to prolong the storage time for logistical reasons so we can 39 00:04:29,890 --> 00:04:35,080 transport organs longer distances or we can accept more organs at any one time. 40 00:04:35,080 --> 00:04:41,470 But also, we'd like to be able to assess the viability of organs if we could have some way of trying to work out which organs are going to behave, 41 00:04:41,470 --> 00:04:49,270 work when we transplant them. That would help us to select better and possibly use some of the organs that we don't currently use. 42 00:04:49,270 --> 00:04:56,930 And then moving on to the future would also like to be able to deliver therapeutic interventions to the organs before we transform them. 43 00:04:56,930 --> 00:05:00,370 Second story doesn't stack up to well against all of these criteria. 44 00:05:00,370 --> 00:05:08,260 Probably does help to slow organ damage during storage, although it doesn't stop it completely, but it doesn't really allow any of the others. 45 00:05:08,260 --> 00:05:16,510 It doesn't repair any damage. Storage times are limited, and there's no means of viability assessment. 46 00:05:16,510 --> 00:05:22,090 So even back when we started this in the 1960s, there was an interest in machine preservation of organs. 47 00:05:22,090 --> 00:05:29,230 So this is Belize's hypothermic machine preservation device, so this essentially pumps cold fluid through a kidney. 48 00:05:29,230 --> 00:05:32,350 And as you can see, it's pretty unwieldy and logistically challenging. 49 00:05:32,350 --> 00:05:40,030 It's required a transit van to take it around a forklift truck to move it and say, perhaps unsurprisingly, 50 00:05:40,030 --> 00:05:47,440 as cold storage solutions improve during the 60s and 70s, people move to cold storage for the logistical benefits. 51 00:05:47,440 --> 00:05:49,780 Nowadays, the machines have changed somewhat. 52 00:05:49,780 --> 00:05:56,800 We cannot put it on a tabletop and one person can lift it, and this is the equivalent that we have now in our theatres. 53 00:05:56,800 --> 00:06:05,290 And again, this is this is a hypothermic machine for perfusion kidneys with cold preservation fluid. 54 00:06:05,290 --> 00:06:12,430 Now the benefits of this or the the reported benefits of this is you're flushing cold preservation fluid through the kidney during storage. 55 00:06:12,430 --> 00:06:19,120 So you're removing some of these metabolites that are accumulating and providing substrate at the same time. 56 00:06:19,120 --> 00:06:26,290 So when he was with us, John Callahan undertook a systematic review looking at hypothermic machine preservation, 57 00:06:26,290 --> 00:06:32,890 and there clearly is some clinical benefit to using machine a standard static cold storage. 58 00:06:32,890 --> 00:06:41,410 These are all randomised controlled trials of hypothermic machine preservation versus static cold storage as we see the risk of delayed graft. 59 00:06:41,410 --> 00:06:46,750 Function is reduced by about 20 percent when you use hypothermic machine preservation. 60 00:06:46,750 --> 00:06:51,460 But interestingly, there wasn't much difference in graft survival or graft function. 61 00:06:51,460 --> 00:07:01,330 When you use this technology, so it does seem to prevent the reperfusion injury, but it doesn't have too much of an impact on long term outcomes. 62 00:07:01,330 --> 00:07:04,210 Most of you have had good talk before about the Cape consortium, 63 00:07:04,210 --> 00:07:13,360 so this was an easy funded consortium of transplant centres across Europe who were looking at organ preservation research, 64 00:07:13,360 --> 00:07:20,650 and as part of that, there were three randomised controlled clinical trials and a suite of experimental research as well. 65 00:07:20,650 --> 00:07:26,830 David did. The last grand round presents the results of the liver trial, the normal thymic liver preservation trial. 66 00:07:26,830 --> 00:07:31,540 The next of these trials to report is the third one down there that compare randomised controlled trial, 67 00:07:31,540 --> 00:07:35,770 which was looking at hypothermic kidney preservation. 68 00:07:35,770 --> 00:07:44,320 And the results of this have just come out say the idea behind this trial is to see whether we can improve on hypothalamic machine preservation. 69 00:07:44,320 --> 00:07:51,820 So typically, we flushed the kidneys with code preservation fluid, but there's no oxygenation. 70 00:07:51,820 --> 00:07:55,180 We just literally flushing metabolites out of the kidney. 71 00:07:55,180 --> 00:08:02,440 The group in Poitier, who were part of the Cape consortium, had done some experimental work, which is shown here. 72 00:08:02,440 --> 00:08:08,350 Essentially, they took a DCD pig model, so 60 minutes of warm ischaemia to the kidney, removed the kidney, 73 00:08:08,350 --> 00:08:17,650 placed it on a hypothermic machine preservation device for 22 hours and then transplanted back into the into the pigs again, 74 00:08:17,650 --> 00:08:19,660 and they split the organs into two groups. 75 00:08:19,660 --> 00:08:25,510 One group was standard hypothermic machine preservation, the type that we're used to using in clinical practise. 76 00:08:25,510 --> 00:08:28,690 The second one, they actively oxygenated the profuse age. 77 00:08:28,690 --> 00:08:36,850 So there's no oxygen carrier, but they're just bubbling oxygen through the the profuse that they're using in the device. 78 00:08:36,850 --> 00:08:45,070 And you can see that there's a much lower peak in in creatinine after reperfusion in the transplanted animals. 79 00:08:45,070 --> 00:08:49,720 And the baseline creatinine falls down much more rapidly to a lower level. 80 00:08:49,720 --> 00:08:59,350 And then if you take biopsies three months after transplantation, there's much less in the way of chronic inflammation and fibrosis in the organs. 81 00:08:59,350 --> 00:09:06,640 So oxidation does seem to have some benefit in preventing both short term and long term damage. 82 00:09:06,640 --> 00:09:10,600 And so the purpose of the Kompass study was to test this in a clinical setting. 83 00:09:10,600 --> 00:09:15,940 So this was a multicenter, randomised controlled trial across Europe, looking at oxygenated, 84 00:09:15,940 --> 00:09:21,130 hypothermic machine preservation versus standard, hypothermic machine preservation. 85 00:09:21,130 --> 00:09:26,950 One of the nice things about the kidney is that they come in pairs, so each donor has two. 86 00:09:26,950 --> 00:09:33,910 So it's quite a nice clinical trial designed to actually just take both kidneys from one donor and treat one one way one another way. 87 00:09:33,910 --> 00:09:39,610 And then you can control for that these days. The fact is, so this was a bad kidney design study. 88 00:09:39,610 --> 00:09:47,980 It was blinded. So the way this worked is we had a small army of medical students and other students in the Netherlands and Belgium with vans. 89 00:09:47,980 --> 00:09:53,920 She would take these devices out to the retrieval hospital, switch the oxygen on or off depending on the randomisation, 90 00:09:53,920 --> 00:10:00,610 could put the kidney on the device so that they could adequately blind the surgeons in 91 00:10:00,610 --> 00:10:05,980 both the retrieving and implanting centres as to whether there was oxygenation or not. 92 00:10:05,980 --> 00:10:13,640 And this study was in these more marginal kidneys a DCD donors aged over 50. 93 00:10:13,640 --> 00:10:21,930 The primary endpoint was graft function. OK, so one year after transplant, we looked at estimated GFR in the primary analysis. 94 00:10:21,930 --> 00:10:30,200 You you see there's a slight drop in in EGFR in the standard hypothermic machine preservation group and it's improved in the oxygenated group. 95 00:10:30,200 --> 00:10:37,610 It doesn't quite reach statistical significance. The problem with using graft function as an outcome is, of course, 96 00:10:37,610 --> 00:10:42,260 if a kidney is not functioning one year after transplant, you can't include it in your analysis. 97 00:10:42,260 --> 00:10:44,840 And so as a pre-planned sensitivity analysis, 98 00:10:44,840 --> 00:10:51,260 we imputed all these groups that have failed with EGFR of 10 meals per minute and that Shane on the right hand side. 99 00:10:51,260 --> 00:10:58,970 And that shows that that if you take into account the graft failures, the difference does reach statistical significance. 100 00:10:58,970 --> 00:11:04,760 If you look at measured GFR, so we also measured GFR in these patients at 12 months again, 101 00:11:04,760 --> 00:11:12,020 a statistically significant and probably clinically significant difference of seven men in GFR one year. 102 00:11:12,020 --> 00:11:18,650 Perhaps more interesting is a significant reduction in graft failure in the oxygenated group. 103 00:11:18,650 --> 00:11:21,110 And if you look at the mechanism for that, 104 00:11:21,110 --> 00:11:29,120 you see there's a halving in the risk of acute rejection during the first year transplant with oxygenated machine preservation. 105 00:11:29,120 --> 00:11:33,320 So there does seem to be something in this the clinical data to support that animal data 106 00:11:33,320 --> 00:11:38,840 from prior to the one year after transplantation with oxygenated machine preservation, 107 00:11:38,840 --> 00:11:44,720 we're seeing improved function, less graft failure and a reduction in the risk of acute rejection. 108 00:11:44,720 --> 00:11:54,540 And it seems to be that reduction in the risk of acute rejection that seems to mediate the differences in function and graft failure. 109 00:11:54,540 --> 00:12:00,660 In terms of the mechanisms, well, if you're oxygenating, you will reduce the risk of ischaemic damage, 110 00:12:00,660 --> 00:12:04,980 build up of metabolites during preservation, and so you get less human ischaemia, 111 00:12:04,980 --> 00:12:11,790 reperfusion injury and if you reduce the ischaemia reperfusion injury, there'll be less inflammation pastes reperfusion, 112 00:12:11,790 --> 00:12:18,270 which will result in less priming of the innate immune response and the subsequent adaptive immune response. 113 00:12:18,270 --> 00:12:27,470 And we seem to be seeing less in the way of acute rejection, but also less in the way of chronic inflammation and fibrosis later on. 114 00:12:27,470 --> 00:12:30,860 So hypothermic machine preservation, then if we add oxygen to it, 115 00:12:30,860 --> 00:12:35,450 does seem to do a little better than cold storage, we can prevent damage during storage. 116 00:12:35,450 --> 00:12:43,430 We can repair damage to a degree that's occurring during preservation, which might allow us to store kidneys for a little bit longer. 117 00:12:43,430 --> 00:12:52,280 But we still don't have a means of assessing viability of organs during preservation to see which ones we think are going to work or not. 118 00:12:52,280 --> 00:12:53,240 Nor do we have to do that. 119 00:12:53,240 --> 00:13:00,920 We've really got to be able to store our organs in a functioning state, and that's where normal thermic preservation comes in. 120 00:13:00,920 --> 00:13:09,410 So we're now producing the kidneys with oxygenated blood at body temperature, providing nutrients so that they can metabolise as normal, 121 00:13:09,410 --> 00:13:16,760 which has the potential to allow us to assess viability and deliver therapeutics on the circuit. 122 00:13:16,760 --> 00:13:22,700 David Nasrallah in our last round round present the results of the liver study using normal smoke machine preservation 123 00:13:22,700 --> 00:13:30,740 and certainly in the liver that does appear to be a reduction in the reperfusion injury following transplantation. 124 00:13:30,740 --> 00:13:37,280 But perhaps more interestingly, there was also a difference in discard rate between the two arms in that study, 125 00:13:37,280 --> 00:13:45,080 which suggests that the surgeons were able to use information from the device to make a decision as to whether they could transplant a liberal or not, 126 00:13:45,080 --> 00:13:51,130 and potentially improve utilisation of livers that would otherwise be discarded. 127 00:13:51,130 --> 00:13:53,140 So what about the kidney? 128 00:13:53,140 --> 00:14:00,740 Well, you can't really talk about normal thermic preservation of the kidney without talking about the work of Mike Nicholson and Sarah HostGator, 129 00:14:00,740 --> 00:14:10,550 now in Cambridge. He really does most of the initial clinical research in this area, so they have a a slightly less developed circuit. 130 00:14:10,550 --> 00:14:19,120 You can see on the right hand side that consisting of a bunch of pumps and an oxygenated and derived from a paediatric anaesthetic machine, I think. 131 00:14:19,120 --> 00:14:25,150 And they took 18 kidneys that they accepted otherwise for transplant, 132 00:14:25,150 --> 00:14:32,290 and they placed them on this circuit for an hour just after cold storage prior to transplantation and then transplanted the kidneys. 133 00:14:32,290 --> 00:14:36,760 And you can see that they get quite impressive delayed graft function rates when they do this. 134 00:14:36,760 --> 00:14:44,650 So we would expect and kidneys like this to see a delayed graft function rate of perhaps 30 percent to 40 to 50 percent. 135 00:14:44,650 --> 00:14:49,000 And they saw in their 18 kidneys a delayed graft function rate of just over five percent. 136 00:14:49,000 --> 00:14:56,110 So this does seem to be having some some effect in repairing the organs prior to reperfusion. 137 00:14:56,110 --> 00:15:02,800 What about viability assessment? So they took this one step further, and they took a whole bunch of discarded kidneys, 138 00:15:02,800 --> 00:15:06,490 the kidneys that were not accepted for transplant anywhere in the UK. 139 00:15:06,490 --> 00:15:10,450 They took these kidneys, they refused them and they developed what they call the QC school, 140 00:15:10,450 --> 00:15:18,940 which is a sort of clinical score for assessing organ viability based upon macroscopic perfusion, blood flow, urine output. 141 00:15:18,940 --> 00:15:25,750 They then applied this score prospectively to a further group of discarded kidneys and demonstrated that they were able 142 00:15:25,750 --> 00:15:32,530 to transplant some of these kidneys that were declined by all UK centres and actually improved the transplant rate. 143 00:15:32,530 --> 00:15:40,180 And so the five kidneys that they transplanted for had immediate function, and they all did OK after a year. 144 00:15:40,180 --> 00:15:46,940 So. The challenge with their method is they're only producing for a very short period of time, 145 00:15:46,940 --> 00:15:53,540 so they're only producing for an hour immediately prior to the transplantation. 146 00:15:53,540 --> 00:15:56,510 So you're not preventing any of the damage to the cause during storage, 147 00:15:56,510 --> 00:16:01,670 but they do seem to be able to reverse some of that damage prior to transplantation. 148 00:16:01,670 --> 00:16:10,930 It's clearly doesn't have any logistical benefits because you're not prolonging preservation time, but it does seem to allow viability assessments. 149 00:16:10,930 --> 00:16:13,030 So off the back of this in the liver research, 150 00:16:13,030 --> 00:16:21,200 Emory wasn't back when she was here as a defo student along with Peter and Constantine developed a prototype. 151 00:16:21,200 --> 00:16:27,860 Normally, semi kidney preservation device based upon the liver circuit that we've used previously, 152 00:16:27,860 --> 00:16:33,890 and Emery used first a series of Pekinese and then discarded human kidneys, 153 00:16:33,890 --> 00:16:37,700 and was able to demonstrate that she could refuse them under stable conditions 154 00:16:37,700 --> 00:16:43,010 for up to 24 hours a far longer than anybody else has managed to this point. 155 00:16:43,010 --> 00:16:46,430 So this shows the development of a device is constantly mammary on the right hand side there. 156 00:16:46,430 --> 00:16:54,220 So it started off as a bunch of lab equipment and turned into a quite nice looking prototype, which has been developed further since then. 157 00:16:54,220 --> 00:16:59,110 One of the challenges with the kidney is that, unlike the liver, the kidney produces urine, 158 00:16:59,110 --> 00:17:04,090 and so if you leave it on a circuit for too long, then it will obviously produce. You're in the second volume will decrease. 159 00:17:04,090 --> 00:17:09,640 And so if somehow you have to replace that volume, see some of the early experiments that Anne-Marie did, 160 00:17:09,640 --> 00:17:13,480 she added in Ringer's Lactate to try and maintain the circulating volume. 161 00:17:13,480 --> 00:17:18,340 But you find that very quickly during preservation, you get electrolyte imbalances, 162 00:17:18,340 --> 00:17:23,410 imbalances, and it's very difficult to maintain perfusion for long periods of time. 163 00:17:23,410 --> 00:17:27,820 And so one of the things that she tested during her experiments with this idea of urinary circulation, 164 00:17:27,820 --> 00:17:33,490 so you simply take the urine that the kidneys excreted made it back into the circuit to maintain homeostasis. 165 00:17:33,490 --> 00:17:36,250 And that actually seems to work quite well. 166 00:17:36,250 --> 00:17:43,870 So the graphs here, the black dots, the the kidneys without urinary circulation and then the red ones are the ones with urinary circulation, 167 00:17:43,870 --> 00:17:50,170 and you can see that you can preserve a kidney without recirculation, just using me as lactate for perhaps up to six hours or so. 168 00:17:50,170 --> 00:17:55,330 But then you start to get electrolyte imbalances and eventually the resistance increases. 169 00:17:55,330 --> 00:18:00,310 The perfusion pressures decrease in the unable to maintain perfusion for longer periods of time. 170 00:18:00,310 --> 00:18:07,370 With urine recirculation, you can get a nice, stable preservation for 24 hours or even longer. 171 00:18:07,370 --> 00:18:13,430 So no Muslim fusion seems to take most of our boxes, we can prevent damage, we can repair damage. 172 00:18:13,430 --> 00:18:17,720 We can potentially store for long periods of time up to and beyond 24 hours, 173 00:18:17,720 --> 00:18:26,690 and we potentially have a means of viability assessment and enough time on the circuit to be able to deliver therapeutic interventions. 174 00:18:26,690 --> 00:18:34,760 So where are we taking this next? Well, we've got funding from the NIH are free for a phase one clinical trial of this prototype device and the aims 175 00:18:34,760 --> 00:18:42,410 of that to assess safety and feasibility of an MP for the first time in human kidneys for up to 24 hours. 176 00:18:42,410 --> 00:18:49,520 At the same time, we'll collect samples to look for biomarkers for perfusion and predicting viability of dying of kidneys 177 00:18:49,520 --> 00:18:56,300 and to look at the post-transplant outcomes of these kidneys will compare them to to historical controls. 178 00:18:56,300 --> 00:19:05,810 So we're going to take 36 kidneys. We're going to perfused them in gradually increasing durations from six to 12 to 24 hours, 179 00:19:05,810 --> 00:19:13,100 and there'll be a safety stop after each phase of the trial to look at the results and make sure that things are working as we expect. 180 00:19:13,100 --> 00:19:22,400 And then each patient will be matched to historical controls from our from our own cohort to see whether there's any impact on clinical outcomes. 181 00:19:22,400 --> 00:19:25,580 Primary outcomes, purely a safety outcome. 30 day graft survival. 182 00:19:25,580 --> 00:19:31,850 And then we'll also look at graft function, long term graft survival and the incidence of delayed in primary function. 183 00:19:31,850 --> 00:19:42,180 And then we'll also be taking samples looking at perfusion parameters and biomarkers as potential predictors of organ viability. 184 00:19:42,180 --> 00:19:51,120 So I'm going to hand over to James now, he's going to talk about some of the more sort of lab and translational research. 185 00:19:51,120 --> 00:19:56,230 Evan, thanks very much, Simon. So. 186 00:19:56,230 --> 00:20:02,470 I'm going to talk a bit about the science side of what we've been doing in the department, and it seems like this might be a little bit back to front, 187 00:20:02,470 --> 00:20:07,540 but they they kind of run in parallel and I'm going to go back over a little bit of background as well, 188 00:20:07,540 --> 00:20:16,270 just so it fits in with with the science as well as the clinical. And so, I mean, as transplant surgeons, our objective is to transplant more organs. 189 00:20:16,270 --> 00:20:24,220 We don't want to compromise patient's outcome and we want better graft survival, the EU on fewer kidneys that don't work. 190 00:20:24,220 --> 00:20:28,780 And I've shown a graph on the left side which which, if you ignore the Green Line at the bottom, 191 00:20:28,780 --> 00:20:33,520 shows the outcomes over five years of all deceased and the transplants. 192 00:20:33,520 --> 00:20:41,400 And actually, if you look at the one year numbers, if you look here, you've got a round about 90 95 percent survival at one year. 193 00:20:41,400 --> 00:20:45,700 So the survival rates are very good. They're not good enough. We want them better, but they're very good. 194 00:20:45,700 --> 00:20:50,050 And in fact, they're so good that drug companies have almost stopped doing clinical trials 195 00:20:50,050 --> 00:20:55,150 into immunosuppression because you can't really power a trial to go from 95, 196 00:20:55,150 --> 00:20:58,540 96, 97 percent without, without many, many, many patients. 197 00:20:58,540 --> 00:21:10,750 So we need to try and find better ways of improving these outcomes and say the way we've been doing this is. 198 00:21:10,750 --> 00:21:20,310 So. Simon showed this graph and apologised for the repetition, but but the question is, is there a need to do this? 199 00:21:20,310 --> 00:21:25,740 Well, as he explained, the donors are getting older and there's not much we can do about that. 200 00:21:25,740 --> 00:21:31,860 And if you look about 280 patients last year died whilst waiting for either a kidney or a pancreas. 201 00:21:31,860 --> 00:21:36,360 So this certainly is a need to do this. And where can we find the resource for this? 202 00:21:36,360 --> 00:21:41,160 We're transplanting what we think is as many kidneys as we're offered, but actually we're not. 203 00:21:41,160 --> 00:21:49,110 So this is consistent over 10 years, about 10 or 12 percent off of kidneys that are retrieved are not transplanted. 204 00:21:49,110 --> 00:21:54,450 So of those we we think about, half of them are probably transplants. 205 00:21:54,450 --> 00:22:03,070 So how do we go about assessing this and when we get this, what we think the problem here is what's in the box? 206 00:22:03,070 --> 00:22:09,180 Okay, well, that's in the box. It's a kidney. And for those non transplant surgeons, it looks okay. 207 00:22:09,180 --> 00:22:12,720 You see that kidney thing. That's great. It looks fine. 208 00:22:12,720 --> 00:22:18,180 It's well flushed. Someone's very kindly bunched it for us. But what we don't know? 209 00:22:18,180 --> 00:22:22,620 Once they transplant it, is it going to be this or is it going to be this? 210 00:22:22,620 --> 00:22:30,990 Because you can't tell from just looking the kidney? And so that's where the normal foamy perfusion ideally comes into play. 211 00:22:30,990 --> 00:22:38,070 I think Simon talks about Mike Nicholson's work, which has got some, which is. 212 00:22:38,070 --> 00:22:44,550 Fine, if you just take some very simple measures. But there's nothing else in there that tells us about what's inside. 213 00:22:44,550 --> 00:22:48,750 And so our aims in the department were both clinical and scientific. 214 00:22:48,750 --> 00:22:55,740 The clinical the funding for the phase one trial has been achieved thereafter funding for a larger, 215 00:22:55,740 --> 00:22:59,820 randomised trial to see whether this technology can be used and then a conditioning unit. 216 00:22:59,820 --> 00:23:04,590 That's the goal. We have kidneys that come from around the country or from wherever they've not be 217 00:23:04,590 --> 00:23:08,430 transplanted and we assess them and then we decide with their transplants well. 218 00:23:08,430 --> 00:23:12,990 And if they are, we either transplant themselves or we send them elsewhere to be transplanted. 219 00:23:12,990 --> 00:23:16,220 And in parallel with that, we will have got some scientific goals. 220 00:23:16,220 --> 00:23:24,270 So using discarded human kidneys for research is challenging because they're a very heterogeneous group. 221 00:23:24,270 --> 00:23:28,440 There's a huge variation in what you get an Anne-Marie's data, a fantastic. 222 00:23:28,440 --> 00:23:33,600 Some of these kidneys are going round the houses and had very, very long periods of cold ischaemia. 223 00:23:33,600 --> 00:23:41,130 And so we needed a better model to assess the science than discarding human kidneys because we wanted to look at things like mechanisms of action. 224 00:23:41,130 --> 00:23:44,610 And we wanted to add novel therapies to see why that would take us. 225 00:23:44,610 --> 00:23:50,700 And so if you think Mike's machine looks a bit Heath Robinson, then you can just take a look at ours. 226 00:23:50,700 --> 00:23:56,190 And I've put this up because this was very much in the early days where we we've 227 00:23:56,190 --> 00:24:00,990 got a sophisticated pump and and the technology that you can't see there, 228 00:24:00,990 --> 00:24:02,820 that actually does the work. 229 00:24:02,820 --> 00:24:12,210 But this is a device where you pump hot pump from centrifugal pump blood into the oxygen data up into the renal artery here. 230 00:24:12,210 --> 00:24:16,200 And then it drains down the renal vein and then back around the circuit. 231 00:24:16,200 --> 00:24:20,790 And we've modified that because if you just buy these disposables, they're two thousand euros each. 232 00:24:20,790 --> 00:24:24,540 So if you imagine we go to our abattoir, we get a pig kidney, we get some pig blood, 233 00:24:24,540 --> 00:24:28,740 which is essentially free, and then we need two thousand euros to do the experiment. 234 00:24:28,740 --> 00:24:35,340 So that's completely unrealistic in any walk of research. And so by doing it this way, we can reuse components. 235 00:24:35,340 --> 00:24:36,420 We can buy them separately. 236 00:24:36,420 --> 00:24:42,570 We can do it in a way that we can actually get some information by pumping large numbers of kidneys without spending lots of money. 237 00:24:42,570 --> 00:24:46,470 And the classic is the one that we started with. 238 00:24:46,470 --> 00:24:51,600 And then this is what's the the open circuit because the vein is not granulated. 239 00:24:51,600 --> 00:24:59,610 So the renal vein is draining directly into the chamber Philip blood rather than having it suspended in a as you saw on the previous. 240 00:24:59,610 --> 00:25:05,940 And so one of our early questions which one's better does it matter what we use because the open circuit is much, 241 00:25:05,940 --> 00:25:12,960 much easier to use in the cloud, so it's much less. And so we had a medical student who came in. 242 00:25:12,960 --> 00:25:18,000 It's an experiment with us and and we just compare the two. 243 00:25:18,000 --> 00:25:23,550 This was right at the bottom of our learning curve three four years ago when we first started. 244 00:25:23,550 --> 00:25:27,510 And so it's not perfect, perfect experiments. 245 00:25:27,510 --> 00:25:34,710 But what it sort of showed initially was there wasn't much difference in terms of perfusion characteristics on she. 246 00:25:34,710 --> 00:25:37,440 The closed circuit seemed to produce more urine. 247 00:25:37,440 --> 00:25:43,410 Now there's a theory that if you've got a candidate in the vein, it's a bit like having it attached to the IVC. 248 00:25:43,410 --> 00:25:49,560 You've got some venous pressure, whereas if you've got the renal vein draining into it into a canister, there's no venous pressure at all. 249 00:25:49,560 --> 00:25:56,520 So maybe you increase the pressure across the glomerulus and and you and you help, but that's possible. 250 00:25:56,520 --> 00:26:01,530 But actually, when we looked at the kind of markers of injury in the other parameters, it wasn't consistent. 251 00:26:01,530 --> 00:26:05,400 So the lactate was higher in the closed circuit, the HGH was in the open. 252 00:26:05,400 --> 00:26:09,600 And so in the end, for the sake of ease, we went to the open circuit. 253 00:26:09,600 --> 00:26:15,450 OK. But with these pig kidneys, we could not perfusion and beyond about eight hours. 254 00:26:15,450 --> 00:26:19,950 The human kidneys seem to work. OK. Kidneys are much more sensitive. 255 00:26:19,950 --> 00:26:25,380 They're much more visa spastic. And so we couldn't control the CO2 levels. 256 00:26:25,380 --> 00:26:30,030 And in parallel with what we were doing, there was a Canadian group who just did this beautiful pig, 257 00:26:30,030 --> 00:26:35,670 also transplant model where the kidneys were pumped for 16 hours transplanted and the results were fantastic. 258 00:26:35,670 --> 00:26:39,390 So we thought, Oh, goodness me, what are they doing that we're not? Why can they do it? 259 00:26:39,390 --> 00:26:43,020 And we can't. And so we just it made some small changes. 260 00:26:43,020 --> 00:26:46,710 We change things like the vasodilator, OK. 261 00:26:46,710 --> 00:26:53,280 And so this is three groups. It's we used to you say, do not to proceed because that's what my next news. 262 00:26:53,280 --> 00:26:56,490 That's what others it used and it seemed to work. 263 00:26:56,490 --> 00:27:02,640 Our colleagues in Groningen, I'm glad Brooke is not here because he would tell me, I'm not pronouncing it right. 264 00:27:02,640 --> 00:27:08,510 Groningen in the Netherlands, they don't use any vasodilator. 265 00:27:08,510 --> 00:27:14,330 And the Katz Group, they use Verapamil, so we compared the three, and what we found is there wasn't much difference. 266 00:27:14,330 --> 00:27:18,260 Interestingly, even if you didn't use a visa to later at all. 267 00:27:18,260 --> 00:27:21,920 The sodium nitric oxide kidneys look like they produce more urine. 268 00:27:21,920 --> 00:27:29,240 But if you look at the error bars, it's essentially one kidney will just be an outlier there and produce lots of urea. 269 00:27:29,240 --> 00:27:38,270 But what we found was striking. Because. The sodium nitrate precede kidneys, which is the ventilator we've been using all along, 270 00:27:38,270 --> 00:27:43,370 got a profound lactic acid process and the price drops dramatically. 271 00:27:43,370 --> 00:27:46,190 OK. And so you do a little bit more digging a bit more research, 272 00:27:46,190 --> 00:27:52,850 and you find that one of the metabolic by-products of sodium patricide is a cyanide type compound, 273 00:27:52,850 --> 00:27:57,530 which interferes with oxidative respiration and effectively stops the kidneys respiratory. 274 00:27:57,530 --> 00:28:07,120 So we stop using that and we started using verapamil. And then we had a fantastic Italian nephrologist who came over and spent a year with us. 275 00:28:07,120 --> 00:28:14,500 So this is the Italian influence, and we wanted to tinker a bit with the preservation solution we were using because as you heard, 276 00:28:14,500 --> 00:28:25,060 Simon said, the Nixon Group used Ringer's lactate. Anne-Marie used albumin, human albumin and in the liver trial gel fusion was used. 277 00:28:25,060 --> 00:28:30,760 And so it's there's so many questions that need answering, which is the best one, which is the right one to use. 278 00:28:30,760 --> 00:28:34,240 And so what we did here is we we took the pig blood. 279 00:28:34,240 --> 00:28:38,980 It came from the abattoir with the kidney and we split it into its component fractions. 280 00:28:38,980 --> 00:28:47,330 And then we resuspended the red cells with a known amount of plasma, took out all the noise, get all the immune cells. 281 00:28:47,330 --> 00:28:51,070 And and we're a little bit more meticulous about some of the sterility. 282 00:28:51,070 --> 00:28:55,030 And if we filtered the blood and it was still white cells in it, we felt it again. 283 00:28:55,030 --> 00:29:02,950 What we found is the perfusion got better and say, suddenly we got abattoir pig kidneys and we could perfused them for 18 hours, 284 00:29:02,950 --> 00:29:11,200 which is what we've been wanting to achieve as a sort of model of what we wanted to compare with the human setting. 285 00:29:11,200 --> 00:29:14,950 They produce urine. The perfusion was reasonably stable, they acknowledge. 286 00:29:14,950 --> 00:29:22,090 At the end, if you look at the lactate does start increasing, but that's one or two kidneys. And so. 287 00:29:22,090 --> 00:29:26,650 If you don't believe me, I thought I show you some of those pictures. So this is a kidney on the machine. 288 00:29:26,650 --> 00:29:34,900 It looks shiny because it's covered in cling film, which again is a very cost effective way of keeping the kidney warm and moist. 289 00:29:34,900 --> 00:29:40,060 And so at one hour, it's reasonably pink and perfused in 18 hours the same. 290 00:29:40,060 --> 00:29:45,340 So you can pretty much tell when the kidneys dying because it starts looking black and blockchain horrible. 291 00:29:45,340 --> 00:29:54,070 And that kidney looks okay. So it starts to achieve this objective of a research model of kidneys that was a cost effective way of doing. 292 00:29:54,070 --> 00:29:58,750 And so we wanted to look a bit more into some of the mechanisms of action. 293 00:29:58,750 --> 00:30:01,780 We know that mitochondria are crucial parties, 294 00:30:01,780 --> 00:30:08,230 so we know there's hundreds of factors that are important in in all of this clotting cascade, et cetera. 295 00:30:08,230 --> 00:30:13,480 But we wanted to look at the mitochondrial function in kidneys undergoing Nelson Fusion. 296 00:30:13,480 --> 00:30:23,200 And so this is funded by Academy Medical Sciences grants, and we used Animal House pigs, not slaughterhouse pigs for this model. 297 00:30:23,200 --> 00:30:32,650 Okay. And so pigs were anaesthetised at the laparotomy, and then they had one kidney removed and flushed, completely healthy. 298 00:30:32,650 --> 00:30:39,730 It's a beautiful living donor kidney. This is the gold standard kidneys and uninjured kidney, and it's just flushed and put a nice temporarily. 299 00:30:39,730 --> 00:30:46,240 The contralateral kidney is then clamped for 60 Minutes to give it a 60 minute warm ischaemic. 300 00:30:46,240 --> 00:30:53,170 So it's pretty injured. You can see how injured it is. You compare that picture to the one before where the kidney look nice and pink and healthy. 301 00:30:53,170 --> 00:31:00,880 So this is a pretty skinny kidney. And then on top of that, we want to put it on ice or on the pump for 24 hours. 302 00:31:00,880 --> 00:31:05,680 So it has a period of warm ischaemic injury where it's got the oxygenated blood in it and it's got 303 00:31:05,680 --> 00:31:10,840 a bit of cold ischaemic injury where it's sitting in a box of ice and then we fuse both of them. 304 00:31:10,840 --> 00:31:17,110 Excuse me, for eight hours on the machine. OK, so what we found initially? 305 00:31:17,110 --> 00:31:22,510 Well, if you compare the two groups and interestingly, that doesn't appear to be much difference. 306 00:31:22,510 --> 00:31:27,220 So the Nicholson score tells you fellows important and we looked at this. 307 00:31:27,220 --> 00:31:33,870 And so but it doesn't seem to matter, but all of this injured group. 308 00:31:33,870 --> 00:31:40,290 Two kidneys didn't make it for eight hours. They made it to four or five hours and they were essentially dying. 309 00:31:40,290 --> 00:31:47,160 It was a terminal model. The kidneys looked the purple holy perfused, and so the graft doesn't really give the game away. 310 00:31:47,160 --> 00:31:56,100 So. So we split the grooves and we split them into injured kidneys that that appeared to recover healthy kidneys, which is the blue line. 311 00:31:56,100 --> 00:32:04,920 And then the grey line at the bottom is those kidneys that didn't, did not profuse and did not survive and were not viable. 312 00:32:04,920 --> 00:32:08,040 And the line starts to split. 313 00:32:08,040 --> 00:32:18,930 So perhaps flow is important, but more crucially, when we start looking at measures that aren't just perfusion parameters like oxygen consumption, 314 00:32:18,930 --> 00:32:24,750 you might think it's logical and obvious, but actually we haven't seen this before. 315 00:32:24,750 --> 00:32:31,110 The oxygen consumption drops dramatically. They stop consuming oxygen in these kidneys and start dying and their lactate levels go up. 316 00:32:31,110 --> 00:32:39,410 So we start to find objective measures of viability during an MP other than just blood flow. 317 00:32:39,410 --> 00:32:47,990 And the other interesting thing is, despite the urine output of these injured kidneys, they're not functioning OK, so they're not clearing creatinine. 318 00:32:47,990 --> 00:32:56,630 If you look at the orange line, no ground clearance to the healthy kidneys as you would expect pretty consistent creatinine clearance. 319 00:32:56,630 --> 00:33:06,020 Same with the urine album creatinine ratio. So what that shows is is leaky glomerular due to injury, just like albumin into the urine. 320 00:33:06,020 --> 00:33:13,190 So the healthy kidneys don't do that and the injured ones do. So measuring function is not very helpful because they're not functioning. 321 00:33:13,190 --> 00:33:20,130 It doesn't tell you whether they're viable or not. It just tells you that they're not working. It doesn't tell you whether they'll recover. 322 00:33:20,130 --> 00:33:26,160 So we looked at the mitochondria. And say the healthy kidneys, the graph on the left, 323 00:33:26,160 --> 00:33:33,750 the mitochondrial respiration is pretty stable and the way you do this just out of interest is if anyone is particularly interested in this, 324 00:33:33,750 --> 00:33:40,980 you take the kidney biopsies at different time points, you homogenised the tissue and then you extract the mitochondria fresh. 325 00:33:40,980 --> 00:33:46,440 So you have to do this at the time of the experiment. You can't just sort of put it in the freezer and say, maybe we'll do this next month. 326 00:33:46,440 --> 00:33:51,240 So it's quite time and resource intensive. And once you've got these mitochondria extracted, 327 00:33:51,240 --> 00:33:56,220 you put them in a chamber clerk's electrode and you pass oxygen into it and then you measure 328 00:33:56,220 --> 00:34:02,850 the current across the chamber and it tells you how much oxygen they are using at that time. 329 00:34:02,850 --> 00:34:07,140 And so it's a measure of mitochondrial respiration and measure of mitochondrial function. 330 00:34:07,140 --> 00:34:15,170 So it's probably the most accurate way of assessing how these mitochondria function. And so the healthy ones just sort of keep functioning. 331 00:34:15,170 --> 00:34:19,010 The injured ones, although it's only small numbers, 332 00:34:19,010 --> 00:34:25,340 there is a suggestion in these mitochondria that managed to get eight hours that they start recovering. 333 00:34:25,340 --> 00:34:30,890 So the graphs, you have to believe me with you, I have faith starts going up, 334 00:34:30,890 --> 00:34:36,200 but we acknowledge this is small numbers and we acknowledge it's a suggestion rather than any significance. 335 00:34:36,200 --> 00:34:40,190 So the other thing you notice is that the levels are a bit lower. 336 00:34:40,190 --> 00:34:49,140 So if you look at the the y axis, we've got two just below 20 and you've got around about 50 here, which sort of fits with an injured kidney. 337 00:34:49,140 --> 00:34:52,700 And then we we split the grass again. 338 00:34:52,700 --> 00:35:02,360 To see whether the injured kidneys that didn't perform as well were different to those that did, and apart from perhaps this anomalous reading here, 339 00:35:02,360 --> 00:35:08,900 the injured kidneys that don't make it sort of the mitochondria appear not to function, 340 00:35:08,900 --> 00:35:14,330 as well as the ones that either healthy or the skinny ones that recover. 341 00:35:14,330 --> 00:35:20,270 So we had some suggestion that mitochondria function is important during this, which again, it makes sense, doesn't it? 342 00:35:20,270 --> 00:35:24,950 You need mitochondria, but this this was work that hadn't been done before. 343 00:35:24,950 --> 00:35:30,110 And so then I'll just touch briefly on some of the science that Anne-Marie did. 344 00:35:30,110 --> 00:35:33,770 So this is one of the human kidneys that was discarded on the left. 345 00:35:33,770 --> 00:35:41,450 And you can see the picture doesn't come out well, but it's quite patchy here, and this kidney would have been turned down for the characteristics. 346 00:35:41,450 --> 00:35:43,820 So a transplant surgeon somewhere would have looked in Sydney, 347 00:35:43,820 --> 00:35:48,110 and that's not well fused or transplanted, actually when you put it on the machine and it's OK. 348 00:35:48,110 --> 00:35:58,070 Sorry about the mug thing. And so we wanted to look at whether you can demonstrate any regeneration or repair during perfusion. 349 00:35:58,070 --> 00:36:04,430 Hepatocyte growth factor is a mark of this. That's produced is a protein produced by many different cells, not just the liver, 350 00:36:04,430 --> 00:36:09,260 which is involved in tissue regeneration, tissue repair and so across perfusion. 351 00:36:09,260 --> 00:36:14,810 You can see the levels increase. So the kidney appears to be producing levels of hepatocyte growth factor. 352 00:36:14,810 --> 00:36:21,440 It pays to be able to produce proteins, which demonstrates its functioning to some degree. 353 00:36:21,440 --> 00:36:24,860 And this is a clever scatterplot. This is work that others did. 354 00:36:24,860 --> 00:36:33,860 It's on kidney tissue from Anne-Marie's experiments, and it essentially shows the change in protein expression across the perfusion. 355 00:36:33,860 --> 00:36:42,920 So the left lt1 one is a scatterplot, and it shows the difference in upregulated proteins and downregulated proteins throughout the perfusion. 356 00:36:42,920 --> 00:36:49,150 Each dots the different protein. The heat map on the left is just a different way of demonstrating this. 357 00:36:49,150 --> 00:36:54,400 So it goes from zero, 14, 24 hours and each line is a protein. 358 00:36:54,400 --> 00:36:58,270 And red doesn't mean good in green, so red doesn't mean bad in green means good. 359 00:36:58,270 --> 00:37:03,640 It just tells you whether it's been upregulated or downregulated. And again, that doesn't mean it's good or bad. 360 00:37:03,640 --> 00:37:07,480 It might be a heat shock protein. It might be a marker of inflammation. 361 00:37:07,480 --> 00:37:10,930 It may be a repair protein. It just tells you that there's a change. 362 00:37:10,930 --> 00:37:18,910 And so what we see during perfusion is we see a change in the protein profile of the kidney, which again, that's fascinating to know. 363 00:37:18,910 --> 00:37:24,740 This helps you with determining pathway analysis, and it helps you with hypothesis generation. 364 00:37:24,740 --> 00:37:28,240 You look at these proteins think, where do we look next? How can we find out what's going on? 365 00:37:28,240 --> 00:37:34,080 So this is crucial. What? And then we decided to have a bit of fun and add some therapies to it. 366 00:37:34,080 --> 00:37:37,470 He got a kidney in a machine. You can do what you like, you can add whatever you like to. 367 00:37:37,470 --> 00:37:47,270 It's a fantastic model for testing things on. So I'm not going to steal and Caitlin Rosenberg's thunder because she did a lot of this work for her, 368 00:37:47,270 --> 00:37:54,410 her defence and hasn't presented that work yet, but that we've got a collaboration with her. 369 00:37:54,410 --> 00:38:00,260 The MEAP collaboration, which is between a group in our house in Denmark and Rotterdam in the Netherlands, 370 00:38:00,260 --> 00:38:05,060 where we produce pig derived ADP's drive pig stem cells. 371 00:38:05,060 --> 00:38:09,510 And we've been doing the normal thermic perfusion side of that. 372 00:38:09,510 --> 00:38:12,830 So the initial bit was a dose testing. 373 00:38:12,830 --> 00:38:20,530 So you take two million, 10 million and 50 million stem cells and you give them to a kidney during machine perfusion. 374 00:38:20,530 --> 00:38:25,210 And the questions were very simple. Where do they go? Can we find them? 375 00:38:25,210 --> 00:38:29,110 These questions are relatively unanswered. Do they have any effect? 376 00:38:29,110 --> 00:38:35,920 If so, what effect? So we weren't trying to be too clever. We just wanted to see if we could answer some simple questions. 377 00:38:35,920 --> 00:38:41,740 As part of this, there's a big auto transplant model. The results are currently being analysed. 378 00:38:41,740 --> 00:38:47,920 I'm not going to talk about that today, but that's a part of the sort of bigger picture with this project. 379 00:38:47,920 --> 00:38:55,570 And so these graphs just show the the groups of control two million, 10 million and 50 million stem cells. 380 00:38:55,570 --> 00:39:01,900 And so essentially what it showed was it didn't really matter how many stem cells you you give them. 381 00:39:01,900 --> 00:39:07,180 It doesn't seem to change what happens during perfusion. So the perfusion characteristics were the same. 382 00:39:07,180 --> 00:39:12,590 The injury markers were the same. The haemolysis, the likes it, they were all essentially the same. 383 00:39:12,590 --> 00:39:16,820 There wasn't any difference in anything that you measured. OK? 384 00:39:16,820 --> 00:39:21,320 The perfusion tended to dip a bit when you gave lots and lots of stem cells, but it seemed to recover. 385 00:39:21,320 --> 00:39:25,520 And so you could. Is that positive or negative? Well, it means you can give lots of stem cells. 386 00:39:25,520 --> 00:39:30,710 It doesn't appear to clog up the capillary system. It doesn't appear to have an effect on perfusion. 387 00:39:30,710 --> 00:39:38,300 So that may be positive because it means you can give lots of stem cells if they work or also means you don't have to give lots of stem cell. 388 00:39:38,300 --> 00:39:46,730 But we don't really know what they do. And so we have done some work looking at whether it improves cytokine release and growth factors. 389 00:39:46,730 --> 00:39:52,400 Haven't got time to go into all of that because I want to show you some pretty pictures because that's more interesting. 390 00:39:52,400 --> 00:39:56,840 So we've we took some biopsies from these kidneys to see if we could find the stem cells. 391 00:39:56,840 --> 00:40:02,700 And these are labelled these stem cells with something called Q dots. 392 00:40:02,700 --> 00:40:07,440 And the slightly perverse side of this is if you and what you do is you take this big population of stem cells, 393 00:40:07,440 --> 00:40:11,580 which have been expanded in a very clever way and you add kudos to them. 394 00:40:11,580 --> 00:40:18,630 And then that affects their viability and they probably don't work. But if you don't add kudos, you can't find that you've got no idea why they go. 395 00:40:18,630 --> 00:40:22,620 So for this experiment, we added these because we wanted to see where they go. 396 00:40:22,620 --> 00:40:29,730 So it's probably not fair assessing how well they work and trying to find where they go in the same experiment. 397 00:40:29,730 --> 00:40:38,370 But this is a slide of a kidney, and this was the two million stem cells group, and you can see one can see one get. 398 00:40:38,370 --> 00:40:43,710 So we found one, which was which was I mean, that was fantastic. We found stem cells could well then us. 399 00:40:43,710 --> 00:40:50,910 Now, one kudo doesn't mean one stem cell because some of the stem cells take up lots and lots and lots of kudos. 400 00:40:50,910 --> 00:40:57,540 And then if the stem cell dies, it releases the kudos. So actually, it tells you that there's probably a stem cell there, 401 00:40:57,540 --> 00:41:01,290 but there's definitely acute, OK, they're on the stem cell has been there or something. 402 00:41:01,290 --> 00:41:06,700 But then if you go on and look at the 10 million, there's more some hair. 403 00:41:06,700 --> 00:41:14,370 Some air. Down there and there in the climate, realists, interestingly, that's where they all appear to be. 404 00:41:14,370 --> 00:41:21,570 And then you look at the 50 million and there's more still. So it's not quantified, but there appears to be a dose response. 405 00:41:21,570 --> 00:41:25,830 So the more stem cells you give, the more you can find. And again, that's interesting. 406 00:41:25,830 --> 00:41:30,420 That's useful. That wasn't this has not been been done before. 407 00:41:30,420 --> 00:41:34,830 Again, they appear to be in the climate. That's probably because they get stuck in the capillaries. 408 00:41:34,830 --> 00:41:36,060 We don't know for sure, 409 00:41:36,060 --> 00:41:45,630 but they go into the blood supply and then they probably get stuck in the end of the because they're bigger than the calibre of the capillary. 410 00:41:45,630 --> 00:41:51,510 Makes sense. And so said, this work will lead on to more, there's lots more facets to this, 411 00:41:51,510 --> 00:42:00,190 but this is just to give you an idea of some of the things we're doing and where we're taking the preservation. 412 00:42:00,190 --> 00:42:08,170 And so, so overall, in our kind of progression towards both these clinical and scientific goals, 413 00:42:08,170 --> 00:42:13,270 Simons told you the trials have been completed, the hope them coach native fusion. 414 00:42:13,270 --> 00:42:18,820 The funding for the phase one trial has been complete and we started to work on and produce a rapid, 415 00:42:18,820 --> 00:42:28,270 reproducible model of kidney perfusion using abattoir pig kidneys, which is cost effective and can be used reused consumables. 416 00:42:28,270 --> 00:42:31,120 We've got some promising data on mitochondrial recovery. 417 00:42:31,120 --> 00:42:39,400 We've got lots to do on M.S. therapy and we got plenty of work ongoing and we've we've just got a little grant to do to look at a fusion solution. 418 00:42:39,400 --> 00:42:43,540 We've got some work on MRI imaging and giving those to the kidney. 419 00:42:43,540 --> 00:42:48,310 So there's lots and lots of work to be done here. So thank you very much for listening. 420 00:42:48,310 --> 00:42:52,870 I hope that's been interesting. We've got lots of collaborators, lots of people to thank. 421 00:42:52,870 --> 00:42:58,070 I hope I haven't missed anybody. If I have, I'm sure they're not here. 422 00:42:58,070 --> 00:43:03,777 Happy to take any questions.