 Okay, thank you very much. Thank you for the invitation for this webinar. And so I decided to focus this one hour talk on the work we have done in the last let's say 10 years almost on the application of this technique to study pathologic tissues. And so, this is the table of contents of my talk, I will briefly introduce what, why we use this scanning microscopy is, and as all the cases I will describe they contain collagen. I will briefly address what is sub molecular and super molecular structure of collagen, and then I will try to summarize the most of the results we obtained by this technique on these pathologies. So, or scanning microscopy the scanning microscopy okay that's a technique, which is used for x-rays but also with other kind of pros, which basically needs to think we need a source and an optics to have a focus beam. And then we just scan the sample and then we need a 2D detector to collect the signal we are interested to study. And then we have to set up a way to put all together the data and to derive a quantitative analysis. In the final image, what matters is the beam size. So the beam size will give us the final image resolution in that space. So you can use a different type of focusing optics. In this review we recently published, we summarize also the different possibilities you may choose. For the application which I'm going to describe, we basically use the reflective mirrors. And we worked with some beam which had a size of a few tens of micrometers. But of course, especially synchrotrons today, you can decide to work with a very very small beam down to few tens of nanometers. Then the sample is described in this transparency here like an assembly of objects, scattering objects, and in the case these scattering objects are crystalline, it means that the lens scale we need to study can be at an angstrom lens scale or a few angstrom down to one meter, say, the scale. And if you put this simply in the Bragg law, you will see immediately that this lens scale corresponded to a wide angle scattering. So wide angle X-ray scattering can probe this kind of situation. And the typical data that you collect will be either of this type with spots in the 2D image, or with some spots with little wider rings, or very broad rings. So even without knowing too much of crystallography, too much of details of the problem, so you immediately can distinguish these three cases, and micro-crystalline materials and nano-crystalline materials and amorphous. But of course, then in order to extract important and relevant information at atomic scale, you really need to enter a bit more in detail of the pattern and to use the crystallographic knowledge. If the sample, on the contrary, is not crystalline, but is simply made of scattering objects of a certain size, let's say below 100 nanometers, and provided that these objects have an electron density contrast different enough from the matrix where they are embedded. Then it's sufficient that you collect small angle scattering, and the angle of scattering will depend inversely on the size of the object, so the larger the object, the smaller the angle. And then by analyzing the data, you may have a situation where the data contains only amorphological information, and this is the case when these scattering objects are very much dispersed in your matrix. Or in the case, they form a lattice at the nanoscale, you will see the fraction peaks. So let's say, depending on the decreasing on the order in your sample, you may find this situation or this situation. So, as I said, all the cases I have extracted from our work, they all contain collagen, so it's very important that I give you a bit of information on these kind of fibrous protein. I'm talking about type 1 collagen, and if you go in the protein database that is free for everybody of us, and you search for one of the possible structure, atomic structure of type 1 collagen, you can download this one cog type of structure, which is described here. And you see that there are two main directions, the meridional direction, which is along the fiber axis, and the equatorial direction, which is exactly perpendicular to it. And this corresponds to the Vax pattern where you immediately see that there are two major directions, the orthogonal each other, which corresponds to the meridional axis and the equatorial axis of this representation. So if I did the PDF analysis of this structure in order to know where are the major distances which repeats in this structure, and they occur at about 0.29 nanometer and at 1.5 nanometers, and they are clearly recorded in the diffraction pattern. The 0.29 is this little peak here on top of this broad band, and it's one third of the distance, this distance between adiase and amino acid residues, and the 1.5 nanometer distance, which is this much more resolved peak. This corresponds to the distance between laterally spaced molecular triple adiases. So these two periodicity are very important at the molecular scale. If we go to the supramolecular scale, the molecules arranged in these well-ordered, staggered fashion, which is depicted in this image, and they form a real periodicity, even at the nanoscale, around the value, let's say, around the 65 nanometers, bringing origin to these sharp peaks in reciprocal space. As you can see in these measurements, for example, we collected 20 orders of this periodicity, meaning that it's a very well-ordered structure. And if you want in 2D, you can see clearly these rings, these arcs, which are clearly evidenced in the 2D SUCKS data. Okay, so in any data analysis, which I will explain now, is very important three steps of this data, a sort of data reduction. So you collect the 2D image point by point in all the area, which is important to study, and then you reduce from 2D to 1D integrating this along the ring to produce a 1D pattern for each frame. Then for you decide to investigate one or two or three or more peaks of interest for you, the so-called lens scales of your problem, for example, I can decide to monitor point by point the reflection number five of these series of reflections. And then for each one of these 2D image, I take into account a specific ring, and on this ring I study along the azimuth, the variation of the intensity. So to use this multimodal imaging approach, and to get information about the orientation of the fiber, which can be along one of these directions, in this case, for example, is exactly horizontal. So I can follow point by point how the color code, how the orientation of the fiber changes. Of course this is one possible information that I can derive, but I can derive also the abundance of a specific tissue, the abundance of the more tissue across the area which I am exploring and many more information as we will see in the cases. Okay, so let's start with the first application, keratoconus. Keratoconus is a pathology of cornea, and which creates an abnormal curvature of cornea with the strong, strong modification of collagen. And this affects type one collagen, in fact. So in collaboration with the Harvard Medical School in USA, we studied these samples, which were bovine eyes, where we removed in the central part of the eye, the corneal epithelium, and then a cross-linked agent, which is the riboflavine, was used together with exposure to UV lamp. And the question was, what was the effect of this cross-linking? Does it affect, does it give any effect on collagen? And if yes, which effect? So we did the experiment, C-SUX beam line at SLS in Vivigen, putting the sample, as you can see here, in some envelope to keep them wet all the time. And we placed the SUX detector at a distance of seven meters from the sample. And this is the area that we explored, which is roughly 10 by 10 millimeters square. And we decided in this experiment, for example, to work with a beam of 30 by 15 micrometers square. And then this beam was moved across all the area, and point by point, several SUX first SUX, and then VACS data were acquired. Okay, so this is, in this case, most of the information was in the SUX regime. This is already the end of the story, so to say. So in the area that we explored, we recognize that the central part corresponded to a SUX pattern, while the corona around to another SUX pattern. These are the 2D SUX pattern, which are a bit difficult to see in comparison. But if we reduce to the 1D profile, you see immediately that there are some changes. But let's see more in detail. Okay, these are the two same, the same two profiles. And you can see that there are sharp peaks and wide peaks. These sharp peaks corresponds exactly to the periodicity that we expect to find in collagen along the fiber axis, as we previously described, the 65 nanometer periodicity at the nanoscale. And we recognize immediately that there was no big change between the internal part and the external part of the cornea in this specific periodicity. The broad part, on the contrary, corresponds to the equatorial direction, so to the lateral packing of the collagen fibers. So we decided to filter out this periodicity and to work only on the equatorial part. Again, it's a bit difficult to recognize what are the differences between these two curves, at least in reciprocal space. But if you do a PDF analysis, which means you Fourier transform, or so to say, the reciprocal space data into dyke space, the difference appear much clearer in a clear way. And so the problem now is to give an interpretation of this PDF data. The interpretation we discovered was that we could explain all the peaks beside the first one, all the other peaks, due to a simple, hexagonal packing of the fibers, and the first peak to a shell around the collagen fiber. So what's an exotic interpretation, so to say, but then screening across the literature, we recognize that in fact cornea, which have been studied also by TM, has a packing, even at law, a law order packing as an hexagonal. And in fact, so this justified our modeling. But then we went to the data and we tried to reply to the question, which was, I remind you, what happened due to this treatment. And so if you see by our data, the interfibrilla spacing L, the fibrill diameter fee and the shell thickness S, beside the hexagonal packing, our data say that the crosslinking by Riboflavine and UV lamp shrink the area where this was done. So it was real crosslinking agents that put together closer the collagen fibers. And so this was clearly demonstrated by our data. Even if the information was so barred, let's say in the data, we, by combining statistical analysis and crystallography, we could extract it clearly from the data. And now I move to the second case, the epitomellitus, the epitomellitus, maybe we don't know so much, but this is a real pandemic, a global pandemic I should say. We have more than 400 millions people affected by this disease in the world. And if you think that COVID-19 at the moment has 40 millions. So it's really a huge number. It's characterized by these high blood sugar levels in the four prolonged times, well beyond this number, which is the threshold. This creates some covalent bonding of glucose protein with the creation of these products, which are called the agile, which are irreversible products so they cannot be dissolved anymore. And one of the principal targets is collagen type one. And so we did on purpose some bio tissues of pericardium tissue from bovine. And so to say we doped with collagen, with glucose at this collagen. So we left for three days in glucose with the extra dose, very, very big doses at the pathological, just at the border pathologic and well beyond the pathologic level. So to see what was the effect of these glucose inside the tissue. And once again, we went through the analysis of our well known Bucks and Sucks peak. So first of all, we analyze the effect on the meridional Bucks peak, the one at 0.29 nanometers. We followed the orientation and how this orientation was changing in the area. And we follow also how the peak was moving across the area analyze per sample and among the samples so that means at increasing glucose dose. And we realized that the pair in the area that we explore the peak was moving according to an histogram and by monitoring the position of the peak and the width of this peak. We follow a certain trend, we could derive a certain trend of the variation of this peak. And we analyze also the equatorial peak, exactly in the same way. So taking the point by point how the orientation of this specific lattice periodicity was changing and how the periodicity number was varying point by point. And we derive the trend for this periodicity and we so we have seen that it is similar to the between the regional and equatorial the same trend. And finally, we repeated the same also at the nano scale. We decided to work on the number nine of this series of samples and to monitor again how this was changing. And once again, by the histogram across the entire area, we could derive the variation and the trend of this periodicity at the nano scale. Together, the conclusion we could derive the web, first of all, by looking at this color map was giving us an internal source sort of internal check, which means that the meridional vax was parallel point by point to the meridional vax as it is expected because there are two periodicity along the same fiber axis. And also the meridional vax is exactly perpendicular to the equatorial vax as it is expected for these two reflections. You may say, but that's a useful I mean, why do you have to derive this information. And this is a sort of internal check because when you have to screen across so many data, like in this case, each map contains 10,000 20,000 80,000 data is very important to put internal check that confirm either by statistical by crystallographic ratios that your black box is working properly. On the contrary, the periodicity changing with the glucose that was a very important and quantitative analysis. And the reason that we ascribe for this dilatation that we have monitor at certain up to a certain concentration of glucose was the following. And we know that collagen is hydrophobic molecule sugar is made by hydrophobic and hydrophilic part, the hydrophilic part attracts water and the water inside collagen initiate as well in process and this well in process explain the dilatation that we see in the first step of when we add that we start to add glucose. But then after a certain amount, this stops and reverse becomes a contraction. And the reason for the contraction according to us was that due to the creation of this agile. The agile means cross links, very strong cross links inside between the collagen molecules and the cross links create stiffening, as we know, and the stiffening means contraction, and this explained the results of analysis. As a third now case and from this on, I will move a still to some tissue containing collagen but mineralized collagen. And that means that this is contains all what we have seen up to now, plus an additional tissue. And the rotation is an inorganic tissue, which is hydroxyapatite hydroxyapatite is made by calcium potassium and other elements and organized according to a crystallographic symmetry which is the exogenous as this forms a nano crystals, this is the way our bonds are forms, and this the relationship between hydroxyapatite and collagen is very precise in space is expected that this nano crystals filled the gaps left open by collagen. Okay, so we wanted to study austerities, which is a chronic degenerative disorder of the hip joint. We studied the supramolecular changes and subtle molecular changes eventually of this disease. Monetary by wax and socks, this disorder, and relating to the age of the patients. We studied the different patients from an age between 62 to 87 affected by the same disease, and this bone was as planted during surgery. They were prepared the cutting embedding some polymers. And this is the composite image, for example, in socks mode, and you can see that there are immediately clear regions where you see differences very clear. The yellow one is the region where the bone is the blue one is the region where the polymer embedding the biopsies. And all this region contains in this specific case, for example, 80,000 frames. So once again, we did the same procedure we did the fall the folding, which means transforming each to the frame socks and bucks in one day profile, either for bucks and for socks. And then we rely also in this case on statistical analysis of so many frames. We used here the principal component analysis to reduce this such a huge number of data to reduce number with the lowest correlated data. For example, we extracted this four to the box. And here the corresponding one day box. And then for each point, it's also corresponds to the two desks and the one desks. So clearly there are some area which are simply background the panel on the first column. There's one area where there are some polymers, not very relevant for the study that we want to do. Another area where we see very clearly on the contrary, the diffraction from hydroxyapatite, which is here in 2D and 1D. The diffraction also in socks from collagen because I remind you this is a composite material made of soft tissue which is collagen visualized by socks and art tissue which is hydroxyapatite visualized by box. Okay, then we wanted to proceed and what we did was exactly the same way. We studied some precise landscape. So for college and we decided to study the third, the first and the third meridional reflection. And for box from box data, we decided to study the 002 reflection of hydroxyapatite and the 210 reflection of hydroxyapatite. And the reason for this choice is that the 002 reflection should be nominally parallel to the collagen fiber direction and the 210 reflection is exactly orthogonal to the 002. Okay, once the landscape are defined, we proceed with our multimodal analysis, which means once again that per ring that we have to analyze, we follow the variation along the azimuth of the ring of the intensity. And we can reconstruct a microscopy which point by point contains an orientation along the map, which is in this case, for example, the orientation of the collagen fiber. We repeated the same also for the hydroxyapatite and point by point, we gain the information of the 002 reflection of the 210 reflection and we could internally check once again that whenever there is a color here in the complementary reflection, there is the orthogonal color because these two reflection are known to be orthogonal by crystallographic rules and must be orthogonal also by this microscopy. So this was an internal check that we did also this time and was fine. We cross-analyzed the data, which means here a collagen, here it is the hydroxyapatite, and we recognize that wherever there is a color here, it is the same color here, which means that the two components are exactly aligned parallel to each other, which is not absolutely straightforward because this is the model how it should be. This is our dimension, how it is in the sample, in the tissue. So the pathology did not destroy this order. On the contrary, the mineralization, the interfibrillar mineralization, which is supposed to be exactly in this way that mineral forms where the collagen is the gaps and forms in these bands is completely verified by our data. But then we wanted to go back to the problem. What was the problem here? The problem was to try to link morphological crystallographic structural information with the pathology and with the age. So we went back on collagen. On collagen for each of these raw data, we decided to extract three profiles per biopsy, apart from the background, the profile along the meridional direction, the profile along the equatorial direction, and point by point to make a canonical correlation analysis, which is again another statistical approach. So to quantitatively recognize how much collagen is in each biopsy to be quantitative of this point, we repeated that for all frames, the 80,000 frames per sample, for all the sample, and we arrived to this final graphic that clearly says that there is an increase of the collagen diffraction with the age. There is an linearity, perfect linearity in this pathology of the collagen fingerprint and with the age, and this is explained again by an increased level of cross link. So the fragility of bones in this pathology is due to the increased level of cross link, which is clearly here analyzed, and each point is the results of the statistical analysis of 80 frames. So although these are only six patients, each point is a very high content of information. Okay, so let's complicate a little bit more the problem. Let's go to another pathology, which is aneurysm. This condition, pathologic conditions, which can occur in aorta or in the artery of the leg, creates a weakening of the wall of the artery with really a disruption of the wall integrity. So, but what do we expect to find from the Saxon-Vax point of view? We studied some tissue extracted during surgery once again, affected by this pathology. And what is known is that this kind of wall contains collagen, type 1 again, but contains also some myofibril in the myocardium, for example. The Saxon analysis, which is now, you know perfectly what I mean, when I do, I show these maps, okay, we once again we did all the procedure, which means folding, data reduction, statistical analysis, all what I explained in the previous cases. But then we have to decide the lens scale of the problem also here. The lens scale are, in this case, clearly we see the peaks of collagen. So we decided to work selecting the fifth order of this spacing. Then we see the myofilament first order of this periodicity with this broad bump here. And then we search for a certain shallow, and it's not very big, this information, but can be deduced, due to the diameter of the elastin. And point by point we remapped these microscopes with a strong information content, because each point contains a tissue relevant microscopy. So for example, wherever we see here that does not contain collagen, on the contrary, contains elastin and myofilament. And then this fulfills our request for the soft part of soft tissues contained in these microscopes. But then we went across the Vax microscopes. Either the microscopy simply in transmission, so the absorption microscopy, which tells already a lot of things, because you see here is dark, wherever it's dark, it means that they absorb a lot. But if we keep the information content at this level is not enough, because we don't know what is the reason for this absorption. On the contrary, if we collect also the Vax pattern, and we do the same analysis, we recognize that there are three signals that by which we can explain the Vax data. And amorphous like this blue one, a nano-crystalline like this green one, and a micro-crystalline like this magenta one. So for example, this very highly absorbing part corresponds to the nano-crystal diffraction pattern. This area, which is violet, is a mixture of amorphous and micro-crystalline material. And this white is the mixture of the three. Okay, but what is exactly this? Now we need the crystallography information. And by searching across our database and by refitting our data, we could explain that the nano-crystal is hydroxyapatite, and we could derive all the relevant crystallography information about this profile, while the micro-crystalline diffraction pattern is cholesterol. By this second part of the data, we could extract all the information relative to the hard matter part of the tissue. And by combining everything together, we could cross correlate the hard matter and the soft matter, which means, for example, wherever there is hydroxyapatite, it does not exist collagen, but exists elastin and myofilament. And so this co-localization, cross-correlation of the soft matter part and the hard part is made, made, combining SACS microscopy and BACS microscopy with this quite important data analysis. Okay, last example, breast cancer. Breast cancer is another pathology, which is unfortunately well known by women, and it can be recognized because whenever you do my mammography, which is a real time in vivo analysis, you immediately suspect something when you see micro-facification in the tissue. My classification does not mean that you have the cancer. It may, it can be a sign of malignancy, but also not. So typically, you do a core biopsy, and then by histology and immunochemistry, you have to decide what is the status of the tissue and of the pathology and take a decision. So now, with the Institute of the breast unit of Mojiri in Pavia, we had them in this precise analysis, which is from the tissue blocks, they cut a five micron tissue for ramen, and very close to it, the 50 micron thick slice for X-ray diffraction. And to study in combination with one after the other. So they prepare the sample in a specific way, and they have analyzed 52 slices, making a very large classification of them, and so deriving five blocks of tissues, Benign, the green here, up to extreme malign, which means invasive calcium. So classifying per degree of malignancy. And they have done first a large analysis of these materials, already analyzing that when you have a benign sample, they are more heterogeneous than malign one, and different content of also phosphate, carbonase proteins, and they ask us to corroborate their analysis and also to validate them on specific tissues. So the same tissue that were analyzed by Rama, by Raman, were analyzed also by a Saxon-Vax microscopy. And for example, you see here what we already have seen in the previous cases, we have seen the absorption microscopy, which tells us immediately, okay, here we have some micro-pensification. Then we have done the Vax microscopy and the Vax microscopy. Clearly, say that in this micro-pensification, the major, the most, the largest part is where the white is indicated here. Contemporary, we have also the Sax analysis, which tells us the collagen, and you can see clearly that the green Sax color corresponds to the white Vax color, and the green Sax color correspond to a spacing of 63 nanometer, while the red one around the micro-pensification is smaller. So that means that the collagen is mineralized by this micro-pensification, and then by getting into the microscopy and analyzing in detail the Vax signals for this micro-pensification by Ritville analysis from by crystallography, we could address what was the crystallographic structure which explained the data, which was hydroxyapatite also in this case, but also we could follow how this peak shrinked by the malignancy, so by increasing the malignancy of the tissue, the main size increase, double, and by increasing the malignancy also the C axis of these crystalline unicell increases. So the malignancy leaves a clear sign in the Vax diffraction, which can be extracted, decoded, and quantitatively. That's the reason for that. There can be two reasons. One reason could be the altered metabolism of the magnesium ions, which are known to be involved inside this cancer, and magnesium ions substituted to carbon ions, so induce some variation in the lattice. And the other second cause can be a carbonate substitution in the hydroxyapatite. Both cases are open, and now we have done a second experiment in September, collecting other data on the same biopsy by fluorescence and absorption spectroscopy. So to really understand which of the two, if not both, are involved in this explanation. So, hi, I'm concluding. We have seen how these microscopes can be very helpful and very quantitative for many different pathologies that we have explored. In other cases, there is a strong combination of statistical approaches and crystallographic methods. They have to be safely combined in a synergic way in order to extract so many information. So we have developed our own program for this analysis, which is free for download for academics that you can find on our website, where most of the knowledge that we have acquired in so many years of work has been inserted in this software for all the other people who you may need. So thank you and thanking the group of people I have the honor to work with, which are here pictured. And I want to thank also Oliver Bunk, because he was present with me in all the paper which I have explained in these 10 years. And I want to thank all of you for listening. Thank you very much. I want to invite the audience to join us to virtually thank Chince for a great talk, really. Thank you again. So now it's time for the questions. We remind you that the video is recorded and it will be uploaded on YouTube. The participants today allow us to have a diet discussion with the speaker. So if you feel like you want to turn on your video and audio, feel free to do it, so that we can have a better interactive discussion together. Otherwise, I think some of you turn on the video before we have to turn them off. It's time for the questions. But if you don't have or you feel too shy right now to ask questions to the speaker, we can maybe ask you a couple of questions. Yeah, so for example, I'm always amazed to see how like from one instrument, you can actually get information about different pathologies and so I think some of the people in the audience might not be experts. And I think somewhat my wonder, if I want to have access to this technique, and I'm not from the University of Vali, how can I have access to it? Yeah, actually it was a good point because I should say that this work, which I explained, they have been either entirely studied in our lab or doubled. So we prepare the experiment in our lab, collecting some preliminary data, for example, in order to be very focused at the synchrotron and to have a screen across the biopsies so to carry the most important ones. Actually, in the last experiment we have done, we mounted 100 samples. Yes, 76 for the second part of the diabetes projects and 25 for another project that we are running on the glioblastoma now. But what I wanted to say that in our lab, where we have a tabletop machine, there is access, free access for whatever wants to come in collaboration for a specific experiment, which I really advise because it's very important to go very well prepared to a synchrotron experiment, not only to waste time, which is the time of everybody. So it's not my time or your time, common time. And, but also for another reason that today we know that open access publications are very much encouraged. And if you really want to publish a good paper, it's fundamental that you prepare in a very good way to experiment. So all the time you spend the time at home to really get into the problem is a well good time. Yeah, definitely help you to get such a great final results that you show us today. On this, on the sample thing what you said, I'm just curious to know how do you, what is your control sample when you have the 76 different samples or subjects or 26 different samples or subjects. How do you choose your control sample or what is your control measurement depends on the on the problem you have, for example, on glucose tissue, let's say, we have several controls without glucose or we repeat more than once the same sample, we cut more, we repeat, or we explore a larger area. So remember that the area that we explore can be several millimeters square, such as small beam, you have really 80,000 frames already in one microscopy, you will have an abundant information, very large. So you may have the opposite problem that the quantity of information is so called high throughput analysis. So you have really to deal with big machines, also for the computing. Yes, that's interesting. Another question I have is, so my background is in solid state materials. So, from your first case, where you show that if we have a different packing, or different stacking things, you can image them so if I have like a mesopotamia to where we have this ABC ABC kind of stacking. Can I image it through the cross section? Because I mean, I did TM, so I know that there is this different packing mostly on the surface is hexagonal, but on the cross section we want to see, is it possible? We haven't done, but I presume, depending on you cut your sample, you know, so the way we proceed was to create a, I mean, look at the, where is it, this one, okay. This is the cornea. So the curvature is exactly in this plane. We place it as it is. We haven't, in that case, we haven't really, we didn't want more than we haven't. We took the decision to put it like it is even wet. Because the purpose was that not artificially modified in any way the cornea itself by cutting and preparing it. But we could have done cutting along the other direction and mounting different slices of the cornea. This was possible. So yeah, so the cross section is possible to see. Thank you. There's also a good point, I mean, that it's possible to investigate the sample as they are without artificially induced order.