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W4313138319 abstract "Article Figures and data Abstract Editor's evaluation Introduction Results Discussion Methods Data availability References Decision letter Author response Article and author information Metrics Abstract Electron microscopy of biological tissue has recently seen an unprecedented increase in imaging throughput moving the ultrastructural analysis of large tissue blocks such as whole brains into the realm of the feasible. However, homogeneous, high-quality electron microscopy staining of large biological samples is still a major challenge. To date, assessing the staining quality in electron microscopy requires running a sample through the entire staining protocol end-to-end, which can take weeks or even months for large samples, rendering protocol optimization for such samples to be inefficient. Here, we present an in situ time-lapsed X-ray-assisted staining procedure that opens the ‘black box’ of electron microscopy staining and allows observation of individual staining steps in real time. Using this novel method, we measured the accumulation of heavy metals in large tissue samples immersed in different staining solutions. We show that the measured accumulation of osmium in fixed tissue obeys empirically a quadratic dependence between the incubation time and sample size. We found that potassium ferrocyanide, a classic reducing agent for osmium tetroxide, clears the tissue after osmium staining and that the tissue expands in osmium tetroxide solution, but shrinks in potassium ferrocyanide reduced osmium solution. X-ray-assisted staining gave access to the in situ staining kinetics and allowed us to develop a diffusion-reaction-advection model that accurately simulates the measured accumulation of osmium in tissue. These are first steps towards in silico staining experiments and simulation-guided optimization of staining protocols for large samples. Hence, X-ray-assisted staining will be a useful tool for the development of reliable staining procedures for large samples such as entire brains of mice, monkeys, or humans. Editor's evaluation This important study explores the kinetics of heavy metal staining of tissue using time-lapse imaging with X-ray micro computed tomography (CT). Introducing a compelling approach to investigate staining in situ, this work will be of interest to the wide community of scientists preparing biological samples in particular for large-volume electron microscopy. It will become a reference for the field in establishing a quantitative tool for assessing and developing staining protocols. https://doi.org/10.7554/eLife.72147.sa0 Decision letter Reviews on Sciety eLife's review process Introduction In the past decade the image acquisition rates of biological electron microscopy facilities have been scaled to 107–109 pixels per second through parallelization and automation (Hayworth et al., 2014; Schalek et al., 2011; Ren and Kruit, 2016; Denk and Horstmann, 2004; Hayworth et al., 2020; Eberle et al., 2015; Graham et al., 2019; Xu et al., 2017). The increase in imaging throughput for biological samples has been mainly driven by the emerging Neuroscience field of connectomics which aims to densely reconstruct neuronal circuits with synaptic resolution (Briggman et al., 2011; Helmstaedter et al., 2013; Bock et al., 2011; Zheng et al., 2018; Scheffer et al., 2020; Kornfeld et al., 2017; Wanner and Friedrich, 2020; Lee et al., 2016; Kasthuri et al., 2015; Wilson et al., 2019; Schmidt et al., 2017; Svara et al., 2018; Vishwanathan et al., 2017). Also, the analysis of the terabyte-sized electron microscopy datasets produced by these studies is becoming increasingly automated using machine-learning and computer vision (Januszewski et al., 2018; Dorkenwald et al., 2020; Schubert et al., 2019; Dorkenwald et al., 2017; Berning et al., 2015; Staffler et al., 2017; Jain et al., 2010; Buhmann et al., 2020; Vergara et al., 2020; Turner et al., 2020). Both the image acquisition as well as the image analysis for these types of datasets are being scaled by parallelization to large samples on the order of several cubic millimeters or even entire brains. However, a remaining obstacle is the lack of reliable tissue processing and staining protocols for large samples where the smallest dimension is greater than 1 mm. Existing en bloc electron microscopy staining protocols have been optimized for staining small samples with dimensions of less than 1 mm (Genoud et al., 2018; Hua et al., 2015; Deerinck et al., 2010; Tapia et al., 2012). Using aldehyde-stabilized cryopreservation (McIntyre and Fahy, 2015) the cellular ultrastructure can be preserved even in large tissue blocks with dimensions exceeding 1 mm and entire brains. Despite pioneering work on en bloc staining protocols for whole mouse brains (Mikula and Denk, 2015; Mikula et al., 2012), large en bloc stained samples still suffer from artifacts such as inhomogeneous staining and membrane or tissue cracks. En bloc sample preparation for electron microscopy generally requires tissue fixation, staining and embedding in resin. First, the macromolecules in the tissue are stabilized via crosslinking by diffusing or perfusing buffered solutions of fixatives such as formaldehyde (Claude and Fullam, 1945; Fox et al., 1985) and glutaraldehyde (Sabatini et al., 1964). Because biological tissue is composed mostly of carbon and other low atomic number elements, the tissue is stained with heavy metals to increase the contrast in electron micrographs (Bahr, 1954; Porter et al., 1945). These heavy metal stains are composed of electron dense atoms such as osmium, lead or uranium. In addition, some of these heavy metals (e.g. osmium) also act as fixatives (Bahr, 1955). Finally, the stained tissue gets dehydrated and embedded in resin. The most commonly used resins are epoxy resins (Maaløe and Andersen, 1956), such as araldite (Glauert et al., 1956) or Epon (Finck, 1960) because of their thermal stability and electron transparency. To inspect the staining quality in an electron microscope, ultrathin sections (<100 nm) are typically collected from the embedded tissue using an ultramicrotome. Many steps in the classic en bloc electron microscopy staining protocols are based on passive diffusion of chemicals into the tissue. Passive diffusion is one of the main bottlenecks for preparing large samples (smallest dimension >1 mm) for electron microscopy (Burkl and Schiechl, 1968; Medawar, 1941). For small samples (smallest dimension <1 mm) a typical en bloc staining protocol takes about 10–15 days including sectioning (Tapia et al., 2012). However, for large samples or whole brains, a diffusion-based staining protocol takes several weeks or even months (Mikula et al., 2012; Mikula and Denk, 2015; Masís et al., 2018). To date, electron microscopy staining is a ‘black box’ and changes to staining protocols can only be assessed using an electron microscope, which in turn requires a sample to be run through the entire staining protocol. Conventional approaches for optimizing the parameters of staining protocols rely on sequential screening of hundreds of samples that have been processed end-to-end. However, sequential screening is very inefficient for months-long protocols. Recently, X-ray based computed micro-tomography (μCT) has been introduced for a relatively fast, macroscopic assessment of staining quality and tissue integrity of resin-embedded whole mouse brains (Mikula and Denk, 2015; Kuan et al., 2020; Dyer et al., 2017). (Mikula and Denk, 2015) showed that the pixel intensities of serial-section EM images and the intensity of the corresponding reslice are similar. Building on this pioneering work, we developed in situ time-lapsed X-ray-assisted staining to observe the staining process while the samples are in the staining solution (Figure 1a). We used X-ray-assisted staining to explore the micro-scale tissue mechanics and the kinetics of the heavy metal diffusion and accumulation in large aldehyde-fixed brain tissue blocks, resulting in new insights on how different staining agents affect the tissue. X-ray-assisted staining opens the ‘black box’ of electron microscopy staining protocols. Each staining step can be monitored and assessed in real time. This enables in silico optimization of electron microscopy staining protocols, which will be particularly useful for the development of staining procedures for large biological samples such as whole brains (Figure 1g). Figure 1 with 3 supplements see all Download asset Open asset X-ray assisted staining. (a) Experimental setup. The sample was glued into a thin layer of Sylgard and sits in staining solution in a sealed glass vial on a motorized stage. X-rays are emitted from an X-ray source, pass through the sample, and the spatial distribution of the transmitted X-rays is detected and used to form a projection image of the X-ray absorption in the sample. Over time, the heavy metals diffuse into the tissue and the accumulation of heavy metals change the X-ray absorption properties of the sample. For the quantitative results presented in this study we used cylindrical tissue samples extracted with a 4 mm diameter biopsy punch from the cortex of mice. (b) Projection images of a 4 mm punch of mouse cortex incubated in 2% buffered osmium tetroxide (OsO4) solution after 10 min, 1 hr, and 10 hr. The osmium diffuses passively from the cortical surface and the brain ventricles into the tissue and forms a staining front of tissue-bound osmium (large arrowhead) that moves towards the center of the sample as time progresses. The accumulation of heavy metals results in an increase in the pixel intensity (a.u.) of the X-ray projection image, which was measured along the radial axis of cortical depth from the cortical surface towards the white matter. The small arrowhead indicates the upper edge of the 2 mm thin layer of Sylgard. (c) Measured pixel intensities of the X-ray projection images for different concentrations of buffered OsO4 solutions. The higher/darker the intensity, the more X-rays are absorbed. The pixel intensity/X-ray absorption scales linearly with the concentration/density of osmium (black line, Pearson correlation coefficient r=0.99, <10–6; n=3 for each concentration). (d) Propagation of the staining front in 4 mm brain punches immersed in 2% buffered OsO4 solution (n=13) measured along the radial axis of cortical depth (mean ±s.d.). The propagation can be fitted by a quadratic model (dashed black lines) in which the penetration depth x of the staining front is proportional to the square root of the incubation time t (residual standard error: SEres = 14.68 μm). (e) Intensity profiles of the spatial heavy metal accumulation after t=20 hr of incubation in 2% buffered OsO4 (blue, n=13), Ferro-redOs (green, n=6). Ferro-redOs with 5.56% (orange, n=4) and 11.25% formamide (red, n=4) solutions (mean ±s.d.). In Ferro-redOs the heavy metal staining is not homogenous and there is a more densely stained tissue band at a depth of 300–800 μm. (f) Tissue expansion quantified as change in sample height of aldehyde-fixed brain punches immersed in OsO4 (blue, n=13), Ferro-redOs (green, n=6), Ferro-redOs with 5.56% (orange, n=4) and 11.25% formamide (red, n=4), respectively, as a function of the immersion duration (mean ±s.d.). All solutions were buffered by cacodylate. A monomolecular growth model was fitted to the average tissue expansion in OsO4 solution (black dashed line, residual standard error SEres = 0.06%). (g) In situ X-ray-assisted staining of large tissue samples. The images show projections of a whole mouse brain incubated in 2% buffered OsO4 at different points in time across 2.5 days. The arrowheads indicate the location of the staining front of accumulated osmium. Scale bar 2 mm. Figure 1—source data 1 Experimentally measured accumulation of heavy metals (blue traces) in buffered 2% OsO4 solution in n=13 different samples. The corresponding simulated model was fitted individually to the experimental data of each sample (black traces). The first row of every sample shows the temporal profile of osmium accumulation at different cortical depths, while the second row shows the spatial profile of osmium accumulation at different times after staining onset. The black circles indicate the location of axon tracts that tended to accumulate osmium faster and stronger. The third row shows the measured spatial-temporal accumulation of osmium (left), the corresponding fitted model simulations (middle) and the distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig1-data1-v2.pdf Download elife-72147-fig1-data1-v2.pdf Figure 1—source data 2 Experimentally measured accumulation of heavy metals in a buffered solution of 2% OsO4 reduced with 2.5% potassium ferrocyanide K4[Fe(CN)6] (Ferro-redOs) in n=6 different samples. The first row shows the temporal profile of osmium accumulation at different cortical depths, while the second row shows the spatial profile of osmium accumulation at different times after staining onset. The black circles indicate the location of axon tracts that tended to accumulate osmium faster and stronger. The third row shows the measured spatial-temporal accumulation of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hoursr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig1-data2-v2.pdf Download elife-72147-fig1-data2-v2.pdf Figure 1—source data 3 Experimentally measured accumulation of heavy metals in buffered 2% Ferro-redOs solution with 5.56% formamide in n=4 different samples. The first row of every sample shows the temporal profile of osmium accumulation at different cortical depths, while the second row shows the spatial profile of osmium accumulation at different times after staining onset. The black circles indicate the location of axon tracts that tended to accumulate osmium faster and stronger. The third row shows the measured spatial-temporal accumulation of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hoursr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig1-data3-v2.pdf Download elife-72147-fig1-data3-v2.pdf Figure 1—source data 4 Experimentally measured accumulation of heavy metals in buffered 2% Ferro-redOs solution with 11.25% formamide in n=4 different samples. The first row of every sample shows the temporal profile of osmium accumulation at different cortical depths, while the second row shows the spatial profile of osmium accumulation at different times after staining onset. The black circles indicate the location of axon tracts that tended to accumulate osmium faster and stronger. The third row shows the measured spatial-temporal accumulation of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hoursr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig1-data4-v2.pdf Download elife-72147-fig1-data4-v2.pdf Figure 1—source data 5 Experimentally measured accumulation of heavy metals in a buffered solution of 2% OsO4 reduced with 2.5% potassium ferricyanide K3[Fe(CN)6] (Ferri-redOs) in n=2 different samples. The first row shows the temporal profile of osmium accumulation at different cortical depths, while the second row shows the spatial profile of osmium accumulation at different times after staining onset. The black circles indicate the location of axon tracts that tended to accumulate osmium faster and stronger. The third row shows the measured spatial-temporal accumulation of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hoursr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig1-data5-v2.pdf Download elife-72147-fig1-data5-v2.pdf Results We developed in situ time-lapsed X-ray-assisted staining with the goal of facilitating and accelerating the optimization of staining protocols for large biological samples such as whole mouse brains (Abbott et al., 2020). 4mm-brain punches of transcardially perfused mice were immersed in aldehyde fixatives for 36 hr. After washing the sample blocks with cacodylate buffer, the samples were immersed in staining solution and immediately placed in the acquisition chamber of a Zeiss Xradia 520 Versa 3D for X-ray microscopy (Figure 1a). The Xradia can be operated in two different modes: In the μCT mode, projections of the sample are acquired at different rotation angles in order to reconstruct a 3D computed tomograph of the sample. Depending on the required signal to noise and resolution, this mode allowed us to acquire approximately 1–2 computed tomographs per hour. In single-projection mode, a projection of the sample is acquired in a fixed position every few seconds without rotating the sample. The advantage of the μCT mode is that arbitrary virtual reslices can be extracted to assess the staining progression in various parts of the sample. However, with our X-ray microscope, the temporal resolution in μCT mode was limited to 30–60 min per tomograph. Therefore we performed all quantitative experiments in single-projection mode where the temporal resolution for monitoring of the heavy metal diffusion and accumulation was on the order of a few seconds. Note, in this mode, the pixel intensities of the resulting X-ray projection images are accumulated through the entire sample and therefore the correspondence to the pixel intensities in thin serial-section EM images is less accurate than in μCT mode (Figure 1—figure supplement 1). As soon as the samples got placed in the staining solutions, the heavy metals started accumulating in the immersed tissue. The stained tissue absorbs more X-rays than the unstained tissue, resulting in a noticeable intensity difference that can be used to track the diffusion and accumulation of the heavy metals in the tissue (Figure 1b). Quadratic scaling of incubation times with sample size Osmium tetroxide (OsO4) is one of the most commonly used contrast agents for lipid staining in electron microscopy due to its large atomic number and its ability to integrate into cellular membranes (Porter et al., 1945; Palade, 1952; Watson, 1958). The immersion times for OsO4 vary between a few minutes to several days, depending on the sample size and tissue type, and are usually determined empirically (Genoud et al., 2018; Hua et al., 2015; Tapia et al., 2012; Mikula and Denk, 2015). However, the kinetics of OsO4 staining of biological tissue are not well understood and so far had to be determined experimentally by trial and error. We therefore set out to measure the diffusion and accumulation of OsO4 by placing 4 mm punches of aldehyde-fixed mouse brains in 2% buffered OsO4 solution. The osmium diffused into the tissue and accumulated in the sample during the staining process (Figure 1b). The intensity of X-ray absorption in the projection images scales linearly with the local concentration/density of osmium (Figure 1c). The density of OsO4 in the tissue increased beyond the density in the surrounding staining solution, indicating that the density of binding sites for OsO4 in the tissue is higher than the concentration of the OsO4 in the staining solution (Figure 1b). The diffusion and spatio-temporal accumulation of OsO4 results in a staining front that propagates towards the center of the sample (Figure 1b). As expected for diffusive processes (Carnevale et al., 1979), the propagation of the OsO4 staining front can be approximated by a quadratic model (Figure 1d). As in the case of other fixatives (Medawar, 1941), the osmium staining penetration in aldehyde fixed tissue obeys a quadratic scaling law, or rather a “rule of thumb”, for how the necessary incubation time t depends on the staining depth or sample size x: (1) t ∝ x2 This means, for example, that if one would adapt an established OsO4 staining protocol for 3 X larger samples, one would have to prolong the incubation time by 9 X in order to produce comparable staining results. Similarly, the time it takes for any point in the sample to reach a given concentration is proportional to the square of its distance to the sample surface (Carnevale et al., 1979). Monitoring staining kinetics and tissue deformation After 20 hr of incubation the staining density of osmium is homogeneous across the first 1000 μm of cortical depth (Figure 1e). In addition, the ultrastructure is well preserved (Figure 1—figure supplement 2). Reduced osmium is another commonly used staining agent that is known to result in higher contrast for electron microscopy images than non-reduced OsO4. Typically, a buffered 2% OsO4 solution is reduced with 2.5% potassium ferrocyanide (K4[Fe(CN)6]) (Hua et al., 2015; Willingham and Rutherford, 1984; Mikula and Denk, 2015), which we will call Ferro-redOs throughout this manuscript. Consistent with previous reports on Ferro-redOs staining in large samples (Hua et al., 2015; Mikula and Denk, 2015) we found that for Ferro-redOs the accumulation of heavy metals peaks at a depth between 300 and 800 μm (Figure 1e), whereas the tissue above or below that depth is stained less. Traditionally, this band of more heavily stained tissue has been associated with precipitated osmium that hinders the diffusion and prevents homogenous staining (Genoud et al., 2018; Hua et al., 2015; Mikula and Denk, 2015), in particular deeper in the tissue. No such band is present in tissue immersed in non-reduced OsO4. (Mikula and Denk, 2015) reported that homogeneous staining of large samples with Ferro-redOs was achieved by adding formamide to the Ferro-redOs solution. However, the underlying mechanisms by which formamide acts are not known (Mikula and Denk, 2015; Genoud et al., 2018). (Mikula and Denk, 2015) hypothesized that formamide might prevent precipitation by generally solubilizing compounds or that it might allow highly charged molecules to cross membranes more easily. Adding formamide to the Ferro-redOs solution indeed resulted in more homogeneous staining (Figure 1e, ), but the heavy metal density was lower than in osmium only. (Mikula and Denk, 2015) reported that the tissue tends to expand at high concentrations of formamide (>50%). But we found that the tissue expands even at lower formamide concentrations, while the amount of expansion depends on both the formamide concentration and the incubation duration (Figure 1f). For a concentration of 11.25% formamide, the sample height increased by about 15% within 20 hr of incubation, whereas for a formamide concentration of 5.56%, the tissue height expanded only by approximately 10% (Figure 1f). Note, in the first 3 hr of incubation in Ferro-redOs with 5.56% formamide the tissue actually shrank, suggesting that there are opposite forces acting on the tissue. Indeed, in Ferro-redOs solution without any formamide, the tissue shrank by about 5% in height (Figure 1f). In contrast, we found that in 2% buffered OsO4 solution the sample height expands by about 5% (Figure 1f). However, we found no sample expansion if the reduced osmium solution was prepared with 2.5% potassium ferricyanide K3[Fe(CN)6]+ 8 a,b), another commonly used reducing agent for OsO4. Hua et al., 2015 suggested an alternative approach to achieve homogeneous staining in 1 mm brain punches with Ferro-redOs without formamide, in which osmium and the reducing agent are applied separately. First, the samples are immersed in buffered 2% OsO4 solution for 90 min. Subsequently, the samples are placed for 90 min in buffered 2.5% K4[Fe(CN)6] without any washing step in-between. We repeated this procedure for 4 mm brain punches: First, the samples were incubated in 2% buffered OsO4 for 22 hours resulting in homogeneous staining throughout the sample. Next, we placed the sample directly without any washing step in 2.5% buffered K4[Fe(CN)6] solution. (Hua et al., 2015) hypothesized that the main effect of reducing agents such as K4[Fe(CN)6] is to convert VIII-oxidized water-soluble osmium into an VI-oxidized water-soluble form which is thought to generate additional, non-polar OsO2 to be deposited in the membrane increasing the heavy metal content and the contrast in electron microscopy. However, we found that the heavy metal density in the K4[Fe(CN)6] immersed samples did not increase, but rather decrease from the sample surface towards the center as time progressed (Figure 2a). This suggests that K4[Fe(CN)6] removes or “washes out” osmium from the sample (Litman and Barrnett, 1972) resulting in an inverse staining gradient. This “washing effect” is stronger for longer incubation times as well as close to the sample surface and around blood vessels (anecdotal observation in electron microscopy images, data not shown). For incubation times longer than 12 hr, K4[Fe(CN)6] readily dissolves and disintegrates the tissue (Figure 2—figure supplement 1). Interestingly, no ‘washing effect’ was observed if the same procedure was repeated with 2.5% potassium ferricyanide K3[Fe(CN)6], but the sample height shrank by about 2% (Figure 1—figure supplement 3,f, ). Similarly, only a small reduction in heavy metal density could be observed when the sample was washed with double-distilled H2O for 20 hr (Figure 2—figure supplements 2 and 3). Figure 2 with 5 supplements see all Download asset Open asset Kinetics and tissue mechanics of electron microscopy staining. (a) Spatio-temporal washout of osmium in samples incubated in 2.5% potassium ferrocyanide K4[Fe(CN)6] (n=6). The samples have been stained with 2% OsO4 for 22 hrs prior to placing them in K4[Fe(CN)6]. The osmium gets washed out from the sample surface towards the center as the incubation time increases. (b) Average experimentally measured spatio-temporal osmium density (nmol/mm3) accumulation in samples (n=13) immersed in 2% buffered OsO4 solution. Because of the surface curvature of the cortical samples, the tissue thickness decreases towards the surface (x=0) and results in a lower intensity in the projection images (see tissue geometry model in f). (c) Simulated spatio-temporal osmium density (nmol/mm3) accumulation fitted to the average experimental data in b. (d) Density profiles (nmol/mm3) of the spatial accumulation of osmium (n=13, mean ±s.d.) after 1 hr (orange), 2 hrs (red), and 10 hr (blue) of incubation in 2% buffered OsO4 overlaid with the simulation of the diffusion-reaction-advection model (dashed lines). (e) Density profiles (nmol/mm3) of the temporal accumulation of osmium (n=13, mean ±s.d.) at a depth of 200 μm (blue), 600 μm (red), and 1000 μm (orange) during incubation in 2% buffered OsO4, overlaid with the simulation of the diffusion-reaction-advection model (dashed lines). (f) The geometry of the 4 mm brain punches was modeled as a cylinder with a curved surface. The curvature of the sample surface is approximated by a circle with radius 12H⋅H2+14R2 , where R is diameter of the cylinder and H is the height of the curved surface. The projected tissue thickness as a function of the depth x from the sample surface is then given by d(x): d(x)=2⋅xH⋅H2+14R2-x2 , for 0≤x≤H and d(x)=R, for x>H (g) Diffusion-reaction-advection model for osmium staining. The model combines four coupled processes: (1) Free OsO4 diffuses passively into the tissue and (2) binds to the available binding sites. (3) In the presence of freely diffusing OsO4 previously masked binding sites are slowly turned into additional binding sites for OsO4. (4) The sample expands by about 5% in sample height within 20 hr of incubation (see Figure 1f). Figure 2—source data 1 Experimentally measured washout of heavy metals in buffered 2.5% potassium ferrocyanide K4[Fe(CN)6] solution in n=6 different samples that have previously been stained with buffered OsO4 for 22 hr. The first row of every sample shows the temporal profile of osmium washout at different cortical depths, while the second row shows the spatial profile of osmium washout at different times after staining onset. The black circles indicate the location of axon tracts. The third row shows the measured spatial-temporal washout of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig2-data1-v2.pdf Download elife-72147-fig2-data1-v2.pdf Figure 2—source data 2 Experimentally measured washout of heavy metals in buffered 2.5% potassium ferricyanide K3[Fe(CN)6] solution in n=4 different samples that have previously been stained with buffered OsO4 for 22 hrs. The first row of every sample shows the temporal profile of osmium washout at different cortical depths, while the second row shows the spatial profile of osmium washout at different times after staining onset. The black circles indicate the location of axon tracts. The third row shows the measured spatial-temporal washout of osmium (left) and the corresponding distribution of osmium in projection images of the sample at the beginning of the experiment and after about 22 hoursr of incubation (right). https://cdn.elifesciences.org/articles/72147/elife-72147-fig2-data2-v2.pdf Download elife-72147-fig2-data2-v2.pdf The kinetics of osmium tetroxide staining The chemistry and diffusion-reaction-advection kinetics of OsO4 staining in aldehyde-fixed tissue are" @default.
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W4313138319 title "Decision letter: In situ X-ray-assisted electron microscopy staining for large biological samples" @default.
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