Using Combination of X-Ray 3D Tomography and FEG-SEM to Perform 3D-FIB Reconstruction in Identified Area to Investigate Effect of Mining Contamination on Scallop Shell Growth
Bibliographic record
Abstract
The shell of the bivalve Pecten maximus, also called Kings Scallop was previously found to be detrimentally affected by the presence of metal contamination, in particular Cu, Pb, and Zn originating from mining activities on the Isle of Man [1]. To shed light on the possible impact of metal contaminations on the 3D morphology and microstructure of the scallop, we used characterization tools at different length scales (from cm to µm) using electron and X-ray probes to determine areas of interest to finally realize localized 3D reconstruction by focused ion beam techniques (FIB). In addition to their thinness, contaminated scallop shells exhibited a pronounced mineralization disruption line within the foliated region. Our data suggest that these disruptions caused reduced fracture strength compared to pollution-free scallops which results in increased mortality due to predation and the process of dredging [2]. We applied 3D X-ray microscopy using micro-computed tomography (microCT) scanning with a ZEISS Xradia 520 Versa X-Ray microscope at different resolutions to locate the disruptive line on contaminated shells and healthy shells. The 3D images (Fig. 1) revealed that this disruptive line is indeed present in healthy shells too, although less marked and thinner than the one observed in the contaminated shells. These lines extend over the entire surface of the shell even if its point of initiation remains a mystery. The same samples were analyzed by scanning electron microscopy (SEM) coupled with elemental analysis by energy dispersive X-ray spectroscopy (EDS) to detect differences of microstructure or orientation on the shell cross section. The equipment used for this purpose was a Hitachi field emission gun (FEG)-SEM SU8230 with low voltage analysis by secondary and backscatter electron (PD-BSE) imaging, Bruker XFlash EDS detector for point analysis, and Bruker Flat Quad detector for EDS mapping analysis. These combined CT-scan and SEM analyses allowed us to determine areas of interest for localized FIB tomography of the different microstructures observed in each type of shell. This FIB tomography was performed using a FIB NX5000 from Hitachi to obtain a stack of images and the Dragonfly software from ORS[3] to build the 3D volume samples from each type. We observed differences in structure of these disruptive lines (Fig. 2) compared to main parts of the shell. Further, we found a higher concentration of sodium, and a detailed analysis of the samples revealed the presence of a main disruption region, which was found to be thicker in the contaminated samples. We also discovered several thinner disruption regions in both types of samples. Overall, our results indicate a significant impact of disruption layers within the scallop shells, which could be causal for the reduced mechanical stability of the shells of scallops from contaminated sites. MicroCT scans of healthy (a, c) and contaminated samples (b, d) at several resolution levels. The disruptive line appearing in the contaminated sample is wider and of higher contrast than the thin line observed in the healthy material. FEG-SEM images of disruptive line observed in (a) healthy shell and (b) contaminated shell. EDS mapping (c) on disruptive line in contaminated sample.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".