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Axonal endoplasmic reticulum is the predominantly smooth tubular endoplasmic reticulum network extending through an axon. It connects the organization of a membrane compartment to the long geometry of a neuron. Network amount, tubule diameter, number of tubules per cross-section and continuity along the axon are distinct structural properties.^[ref]

A 2017 study in Drosophila melanogaster combined optical imaging with serial-section electron microscopy. Reconstructions from seventy-five $60\mathrm{nm}$ sections covered $75\times 60=4500\mathrm{nm}=4.5\mu \mathrm{m}$ of axon. Comparing sections revealed tubular branches and continuity that one cross-section alone could not establish.^[ref]

The investigated membrane-shaping-protein mutants showed enlarged tubules and a less extensive network. Measurements of gaps separately considered gap length, number per length and the proportion of axonal length affected.^[ref]

An invented comparison explains why those readouts differ. Two $10\mu \mathrm{m}$ axon segments each contain one detected gap, but their gap lengths are $0.2\mu \mathrm{m}$ and $2\mu \mathrm{m}$. Both gap-count densities are $0.1\mu {\mathrm{m}}^{-1}$, while their affected-length fractions are two percent and twenty percent. Equal counts can conceal a tenfold difference in the extent affected.

The observation criterion matters too. The study's serial-imaging definition required absent tubule signals in at least three successive sections.^[ref] Such an operational criterion connects a structural claim to what the images can resolve; it does not make every dark or faint region in a single image a demonstrated break in a three-dimensional network.

Serial block-face scanning electron microscopy acquires a three-dimensional dataset by repeatedly imaging an exposed specimen face in a scanning electron microscope and removing a thin layer with an ultramicrotome. The removed layer is not the imaged object: each image records the newly exposed block face. This differs from collecting and imaging thin sections in serial-section electron microscopy.^[ref]

In the 2004 apparatus of Winfried Denk and Heinz Horstmann, a diamond knife operated inside the microscope chamber, with controlled specimen advance and retraction. A backscattered electron signal supplied image contrast. Keeping the cutting and imaging operations in the chamber enabled automated image stack acquisition.^[ref]

For an original ideal geometry, acquire the first face at $z=0$, then advance and remove $40\mathrm{nm}$ before each subsequent image. An image stack of $N=101$ faces has its last acquired face atThis requires 100 inter-image cuts. If a data format assigns each face a $40\mathrm{nm}$-deep voxel, its nominal represented thickness is instead $N\Delta z=4.04\mu \mathrm{m}$. State which extent is intended. At lateral pixel pitch $5\mathrm{nm}$, the sampling ratio $\Delta z/p$ is 8.

The resulting image stack needs image registration and a calibrated cutting coordinate. Lateral position jitter, cutting artifacts and the depth range contributing to the electron signal limit the useful reconstruction. Finite voxel spacing is not itself a measurement of spatial resolution. Destructive cutting also means that later imaging cannot recover an exposed face that has already been removed.

Serial-section electron microscopy reconstructs a volume from an ordered image stack of thin physical slices. In the transmission electron microscopy implementation, an ultramicrotome cuts successive slices, which are collected on a support and imaged through the specimen. Image registration aligns corresponding features; image segmentation identifies structures to follow between slices. JEOL's glossary describes sections of 40–100 nm and illustrates the separate registration and segmentation stages.^[ref]

The motivation is geometrical: one isolated slice cannot show whether a feature continues, divides, or ends outside that slice. An ordered image stack provides observations along the third coordinate, although finite section-thickness anisotropy and missing material limit what can be inferred. A change between neighboring images may come from specimen structure, a slice deformation, or imperfect image registration.

For a chosen numerical example, suppose each of $N=200$ consecutive sections has uniform thickness $\Delta z=50\mathrm{nm}$, with lateral pixel pitch $p=4\mathrm{nm}$. Ignoring lost material and thickness variation, the sections coverThe voxel sampling is 12.5 times coarser along the cutting direction. These are chosen dimensions, not measurements from either cited experiment. The first and last section centers are only $(N-1)\Delta z$ apart: center-to-center extent differs from total represented thickness. Neither spacing is automatically the achieved spatial resolution.

Image resampling onto a cubic grid can make an image stack easier to display, but interpolation supplies no additional independent observations. Likewise, smooth image registration cannot resolve missing-section ambiguity in volume reconstruction: a small connecting feature could lie wholly inside lost material. Checking a reconstructed connection therefore needs evidence in the acquired slices, not just a visually smooth rendered surface.

A historically important automation change illustrates the distinction between section and surface imaging. In 2004, Winfried Denk and Heinz Horstmann placed an ultramicrotome with a diamond knife inside a scanning electron microscope. Their serial block-face scanning electron microscopy imaged the exposed block surface between cuts instead of collecting the removed sections. They reported stacks several hundred layers deep, 50–70 nm sectioning, and typically less than 10 nm lateral position jitter. These observations tested an apparatus for acquiring closely aligned serial images; they did not remove the finite spacing between observations.^[ref]

A mechanical detail makes the measurement chain concrete. Their specimen-advance lever reduced the motorized micrometer's motion by 0.11. Thus its stated position measurement uncertainty of 50 nm contributed $0.11\times 50=5.5\mathrm{nm}$ after that reduction; other sources of section-thickness error still required assessment.^[ref]

Ultramicrotomy prepares extremely thin physical sections by advancing a specimen block through a controlled increment and cutting across it with an ultramicrotome. A diamond knife or suitable glass knife removes the section; collected sections can then be examined by transmission electron microscopy. The instrument's feed setting and the geometry of the recovered section are related quantities, but they need not be equal. JEOL explicitly notes dependence on specimen material and temperature.^[ref]

For a materials example, consider a polymer block containing an initially $20.0\mu \mathrm{m}$-long marked interval parallel to the cutting direction. Suppose the recovered section measures $17.0\mu \mathrm{m}$ along that interval, with unchanged transverse width. Its section compression is $1-17/20=15\%$. Under an explicitly ideal volume-conserving model, a nominal $60\mathrm{nm}$ layer would then have recovered thicknessThe altered area and thickness give the same model volume: $0.85\cdot 70.6\simeq 60$. This is an original diagnostic calculation, not a universal correction rule. Material loss, transverse strain or nonuniform deformation would invalidate the model.

A motivating preparation check therefore compares dimensions of recognizable material features before cutting and in the recovered section, while recording cutting direction and specimen conditions. An independent thickness measurement tests whether the feed is a good depth calibration. Image registration can align section images but cannot generally reverse unknown physical deformation. For serial-section electron microscopy, preserve section order and gaps in the image stack as well as the chosen image stack axis calibration.