The story of Westlothiana began in 1984, when the fossil was discovered in Scotland embedded in two slabs of rock. When it was formally described in 1990, researchers could rely only on what was visible at the surface of the crushed specimen. Even so, the skeleton appeared remarkable: a nearly complete body with four limbs, ending in fingers and toes tipped with superficially claw-like structures. At a time when many of its contemporaries retained fin-like limbs better suited to swimming than walking, these features seemed to mark Westlothiana as a pioneer of terrestrial life. Its lizard-like appearance earned it the nickname Lizzie, and its five-toed hands and feet—a configuration familiar from modern mammals and reptiles—reinforced the impression that this was an animal adapted for life on land.

Because of those surface features, Westlothiana was widely treated as the earliest land-adapted amniote, and for nearly 30 years it served as a calibration point in debates about the origin and timing of the amniote lineage. Textbooks, phylogenetic analyses, and popular accounts of early land vertebrates repeatedly leaned on the Scottish fossil as evidence that reptile-like anatomy had emerged by the Early Carboniferous. The fossil, however, was deformed and notoriously difficult to interpret, and its status rested almost entirely on external anatomy that generations of researchers had never been able to examine from the inside.

That changed when a research team led by Xavier Jenkins, a postdoctoral fellow in the American Museum of Natural History’s Division of Paleontology, and Ben Igielman, who began the research during his graduate work at the University of Oxford, turned to high-resolution x-ray imaging. At the European Synchrotron Radiation Facility in Grenoble, France, the team used x-ray scanning to peer through the rock surrounding the specimen and reconstruct anatomical structures that had been invisible from the surface for four decades. The technique allowed the researchers to build a three-dimensional picture of the animal’s internal anatomy without damaging the fragile fossil, exposing features that would ultimately overturn its scientific identity.

What the scans revealed came as a profound shock. Inside the rock, the team found a surprisingly primitive skull, ossified internal gills, and a fish-like mouth lined with thousands of tiny teeth. Each of these features is incompatible with the interpretation of Westlothiana as a reptile or as any kind of amniote ancestor. Internal gills in particular point to an aquatic or amphibious lifestyle, while the primitive skull indicates that the animal belonged to a lineage far more ancient than the amniote stem. As Jenkins put it, Lizzie has been an icon for the early evolution of amniotes for decades, but once the researchers were finally able to see inside the fossil, they found an animal that looked very different from what anyone had expected.

Igielman emphasized just how deceptive the fossil’s outward appearance had been. The surprisingly primitive features of the skull, he noted, show that Lizzie was not only not a reptile but belonged to a much more ancient lineage altogether. In other words, the lizard-like silhouette that captivated paleontologists in 1990 masked an anatomy rooted deep in the tetrapod family tree, and the animal lived a completely different lifestyle than previously believed—one spent in and around water rather than striding across dry ground.

The implications extend well beyond the reclassification of a single specimen. The study concludes that several anatomical traits once assumed to be exclusive to land-adapted amniotes had, in fact, already evolved among earlier, more aquatic members of the stem lineage of tetrapods—the broader group of four-limbed animals that includes amniotes as well as amphibians. Claws and the five-toed foot structure of Westlothiana, long treated as hallmarks of terrestrial adaptation, now appear to have arisen piecemeal in animals that were still amphibious. Roger Benson, the Museum’s Macaulay Curator of Paleontology and a co-author of the study, described the result as a big surprise, noting that although amphibians are commonly thought of as more primitive than reptiles today, some of the traits associated with reptiles were already present in the ancestor of both groups.

The findings also carry weight for one of the most contentious questions in early vertebrate paleontology: the timing of the amniote origin. In recent years, fossil trackways—preserved impressions of animals walking on four limbs with claw-like digits—have been used to argue that amniotes originated during the Devonian Period, more than 359 million years ago. The logic seemed straightforward: clawed, weight-bearing tracks implied a clawed, land-adapted animal, and clawed, land-adapted animals were presumed to be amniotes. The new work breaks that chain of inference. If early tetrapod relatives such as Westlothiana also possessed claws, then the presence of clawed tracks alone can no longer establish that the track-maker was an amniote.

As a result, some ancient trackways previously attributed to early amniotes may instead have been produced by more primitive, amphibious members of the tetrapod lineage—animals that could walk on land but were not yet part of the reptile-mammal branch of the tree. Jenkins summarized the broader lesson: terrestrial-looking traits such as a reptile-like foot, a weight-bearing forelimb, and claw-like phalanges were not unique features of tetrapods but rather accumulated gradually in their close relatives, in animals that were still living in and out of the water. The evolutionary transition from fish to land vertebrate, in this view, was not a single dramatic leap marked by the sudden appearance of reptile-grade anatomy, but a long, mosaic process in which land-ready features appeared one by one in creatures still tied to aquatic environments.

The study, published in Nature, was a collaborative effort that included Jason Head of the University of Cambridge, Vincent Fernandez of the European Synchrotron Radiation Facility, Lucy Roberts of the Natural History Museum in London, and Timothy Smithson of the University Museum of Zoology Cambridge. Support came from the National Science Foundation, the Natural Environment Research Council, and the Biotechnology and Biological Sciences Research Council. For paleontologists, the dethroning of Westlothiana is a reminder of how much remains hidden inside even the most famous fossils—and of how modern imaging technology can rewrite chapters of evolutionary history that seemed settled for generations. Lizzie may no longer be the world’s oldest reptile, but in revealing that claws and five-toed feet evolved before the first amniotes ever walked the Earth, the Scottish fossil may ultimately prove even more valuable to science than it was before.

Subject of Research: Reclassification of the 345-million-year-old Westlothiana lizziae fossil from Scotland as an aquatic stem tetrapod rather than the earliest known reptile, based on synchrotron x-ray imaging

Article Title: Fossil long known as world’s oldest reptile dethroned

Article References: Fossil long known as world’s oldest reptile dethroned. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Westlothiana, paleontology, amniotes, tetrapods, synchrotron imaging, Carboniferous, early reptiles, fossil trackways, evolution, Scotland, Nature study, aquatic adaptation

Holotomography, in its standard form, is a phase-contrast technique. Rather than relying on the absorption of X-rays, which becomes vanishingly small for light elements at the energies needed for nanoscale work, it measures the phase shifts that a wavefront accumulates as it passes through material of varying electron density. By illuminating the sample from many angles and recording holographic interference patterns, an algorithm can recover the refractive-index distribution throughout the object, producing quantitative three-dimensional maps in which contrast reflects electron density rather than mere attenuation. Because it avoids the resolving-power limits of physical X-ray optics, lensless holotomography uses computed diffractive imaging: a coherent, focused beam illuminates the specimen, and the fine structure of the outgoing wave is inferred entirely from measured diffraction and hologram data.

The fundamental obstacle to scaling this approach is computational as much as it is experimental. In the weak-object approximation that underlies most conventional reconstructions, the sample is treated as a thin, gently refracting phase screen: the wave is assumed to pass straight through, accumulating phase but never changing direction more than trivially. This approximation simplifies the mathematics dramatically, allowing fast Fourier-based solvers to run on the angle-by-angle projections independently. It works admirably for isolated cells and thin sections. But as reconstructed field of view and resolution grow together — the two axes along which gigavoxel datasets are defined — the assumption breaks down. Thick or densely structured specimens scatter light more than once, and those higher-order scattering events inject systematic errors that standard algorithms either ignore or mistake for genuine structure, producing artifacts that can be mistaken for biological features.

The new framework confronts this limitation head-on by embedding a multiple-scattering-aware forward model directly into the tomographic reconstruction. Instead of treating each projection as a simple line integral through the refractive-index distribution, the method models wave propagation through the sample using a multi-slice formulation. In this picture, the three-dimensional specimen is conceptually divided into a stack of thin slices along the beam direction. The wave is propagated through one slice, picks up the local phase, then is free-space propagated to the next slice, where it interacts again. Repeated through the full stack, this scheme naturally generates the beam-broadening, inter-slice coupling, and dynamical diffraction effects that single-pass approximations miss. Crucially, the inverse problem — recovering the slice-by-slice refractive index from the measured holograms — is solved iteratively, with the forward model refined at each step until the simulated exit wave agrees with the data.

What makes the achievement notable is not merely the physical fidelity of the model but the sheer scale at which it can be executed. Multi-slice wave propagation, when performed naively, is orders of magnitude more expensive than projection-based tomography, and iterative inversion multiplies that cost. The researchers coupled their scattering-aware solver to a computational architecture that distributes the work across many processing units, exploiting the fact that the propagation between slices is dominated by fast Fourier transforms — operations that parallelize efficiently and that modern graphics processors execute at extraordinary throughput. Combined with strategies for managing the gigantic datasets involved, in which each individual projection can occupy many gigabytes and the final reconstructed volume approaches a billion or more voxels, the pipeline brings what was previously a computationally prohibitive calculation within practical reach.

The payoff is quantitative imaging that remains accurate where conventional methods visibly falter. In single-scattering-based reconstructions of thick, strongly structured specimens, multiple scattering manifests as shadowing, ring-like artifacts, spatially varying resolution loss, and systematic underestimation of electron density in dense regions. These are not cosmetic defects. Quantitative electron density is precisely the measurable that makes holotomography scientifically valuable: it underpins the identification of organelles in cells, the characterization of material phases and porosity in functional materials, and the comparison of healthy and diseased tissue. By modeling the full wave-optical interaction, the new approach recovers electron densities that remain consistent across regions of very different thickness and composition, restoring confidence in the numbers rather than only the pictures.

The gigavoxel scale matters for a practical reason that is easy to overlook in discussions of resolution. Field of view and resolution trade against each other for a fixed detector and beam geometry: to image a large object at high resolution, one must either stitch together many partially overlapping exposures or record enormous detector frames, and in both cases the data volume grows with the cube of the linear resolution improvement. Doubling resolution in all three dimensions yields an eightfold increase in voxels. Datasets at the gigavoxel scale therefore represent the threshold at which whole, intact specimens — an entire cell in three dimensions at nanometre detail, or a sizable volume of battery electrode or bone — can be captured in a single self-consistent reconstruction rather than assembled from fragments, with all the seams and inconsistencies that assembly entails.

Lenslessness is central to reaching this scale. Refractive and diffractive X-ray lenses suffer from limited aperture, efficiency losses, and aberrations, and their use constrains both the achievable field of view and the fidelity of the recovered wavefront. Computed diffractive imaging replaces the lens’s fixed transfer function with an algorithmic reconstruction, letting the detector — which can be made large, efficient, and linear — define the numerical aperture. The cost is computational burden, which is exactly where the new work’s contribution lies: it shows that the computational overhead of a wave-optically accurate model can be absorbed at the very scales where lensless imaging offers its greatest advantages.

The implications extend across the communities that depend on synchrotron and X-ray free-electron laser facilities. For structural biologists, accurate gigavoxel-scale holotomography opens the prospect of imaging whole cryo-preserved cells and small organisms quantitatively, complementing electron tomography’s exquisite resolution with the penetration depth that only X-rays provide. For materials scientists, the technique promises non-destructive, quantitative three-dimensional characterization of energy-storage materials, catalysts, and structural alloys at length scales bridging the gap between electron microscopy and conventional computed tomography. And for the photon-source community, the demonstration establishes that the next generation of brighter, more coherent sources can be exploited fully only if reconstruction algorithms evolve in step — a message that resonates as diffraction-limited storage rings and free-electron lasers come online worldwide.

Challenges remain before such reconstructions become routine. Scattering-aware solvers demand accurate knowledge of experimental parameters — propagation distances, beam profiles, and detector geometry — because errors in these inputs propagate through the multi-slice model in ways that simple approximations tolerate more gracefully. Convergence of the iterative inversion must be monitored carefully for thick, strongly scattering samples, and the data and memory footprints will continue to strain storage and workflow infrastructure at user facilities. Yet the direction is unmistakable. As computational power grows and wave-optical forward models mature, the dividing line between what can be measured and what must be assumed continues to shift toward measurement. Gigavoxel-scale, multiple-scattering-aware lensless holotomography marks a concrete step across that line, bringing quantitative, non-destructive, nanometre-resolution three-dimensional imaging of whole intact specimens closer to everyday practice.

Subject of Research: Gigavoxel-scale multiple-scattering-aware lensless X-ray holotomography

Article Title: Gigavoxel-scale multiple-scattering-aware lensless holotomography

Article References: Rogalski, M., Winnik, J., Dudek, J., Arcab, P., Wdowiak, E., Matryba, P., Stefaniuk, M., Zdańkowski, P., & Trusiak, M. (2026). Gigavoxel-scale multiple-scattering-aware lensless holotomography. Light: Science & Applications, 15(1), Article 381. https://doi.org/10.1038/s41377-026-02416-0

Image Credits: AI Generated

DOI: 10.1038/s41377-026-02416-0

Keywords: holotomography, X-ray phase contrast, lensless imaging, multiple scattering, multi-slice method, computed tomography, synchrotron imaging, electron density, gigavoxel reconstruction, computational imaging, X-ray optics, nanoscale imaging