Femtosecond Laser-Induced Crystallization of Cytosine Monohydrate for Serial Nano Electron Diffraction Analysis
Bibliographic record
Abstract
Determining the atomic structure of materials and molecules is essential for understanding their properties and functions in both materials and life sciences.X-ray crystallography has long been the standard technique, but its reliance on large, well-ordered crystals presents challenges for certain materials, such as membrane proteins [1].Microcrystal electron diffraction (MicroED) has proven effective for solving the structures of biomaterials and small molecules [2].However, its reliance on continuous crystal rotation and high-energy electron exposure limits its applicability to beam-sensitive materials.Recently, serial nano-electron diffraction (SerialNED) has been developed for structure determination of small molecules [3] and proteins [4].Adapted from the snapshot data-collection approach used in serial X-ray crystallography, SerialNED offers key advantages over traditional X-ray diffraction, including lower sample requirements, reduced radiation damage, and comparable resolution [5].A major challenge in SerialNED is the preparation of nanocrystals.Here, we present a novel approach that employs a femtosecond (fs) laser to precisely control the crystallization process [6], enabling the rapid formation of nanocrystals for electron diffraction analysis.This method enhances nucleation efficiency, producing single crystals of organic molecules and proteins with minimal material consumption.By streamlining nanocrystal production, it significantly accelerates the structure determination process compared to conventional batch crystallization techniques.One of our target materials is cytosine, a fundamental DNA base.When cytosine dissolves in water, it forms cytosine monohydrate crystals, which are typically challenging to prepare as nanocrystals suitable for transmission electron microscopy (TEM) analysis due to difficulties in microtoming.Cytosine serves as an excellent testing material not only because it is a DNA base but also because it readily crystallizes [7].After preparing the sample solution, a femtosecond laser (Ti:Sapphire, 800 nm, 35 fs, 1kHz) irradiates it on electron microscopy grids, promoting crystal nucleation.The grids are then dried using a suction unit and prepared for TEM analysis.Using laser-induced crystallization, we successfully generated a relatively large quantity of nanometer-thin cytosine monohydrate crystals.The unit cell parameters and morphology of cytosine monohydrate crystals grown using the femtosecond laser match those grown via conventional methods.These crystals exhibited high-quality diffraction patterns, as illustrated in Fig. 1C.We then applied serial nano-electron diffraction (SerialNED) to these samples, determining the structure with sub-angstrom resolution using a 90 kV electron microscope at room temperature.The experiments were carried out using a Hitachi HT7800 transmission and scanning transmission electron microscope (TEM/STEM), coupled with an X-Spectrum Amber 750K detector, to determine the structure of cytosine monohydrate.Electron diffraction patterns were collected sequentially using the Azorus software package (Hitachi High-Tech Canada Inc.) to map the crystal coordinates.Over 10,000 diffraction patterns were obtained from the sample, enabling the structure to be determined with high resolution (Fig. 2).In summary, femtosecond laser-induced crystallization provides a powerful approach to accelerate and control crystallization processes.This technique enables the production of high-quality single crystals suitable for electron diffraction.By combining this method with SerialNED, it represents a high-throughput solution for structural determination across a wide range of materials [9].
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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 | 0.000 | 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".