Targeting APT2 improves MAVS palmitoylation and antiviral innate immunity.

Innate immunity serves as the primary defense against viral and microbial infections in humans. The precise influence of cellular metabolites, especially fatty acids, on antiviral innate immunity remains largely elusive. Here, through screening a metabolite library, palmitic acid (PA) has been identified as a key modulator of antiviral infections in human cells. Mechanistically, PA induces mitochondrial antiviral signaling protein (MAVS) palmitoylation, aggregation, and subsequent activation, thereby enhancing the innate immune response. The palmitoyl-transferase ZDHHC24 catalyzes MAVS palmitoylation, thereby boosting the TBK1-IRF3-interferon (IFN) pathway, particularly under conditions of PA stimulation or high-fat-diet-fed mouse models, leading to antiviral immune responses. Additionally, APT2 de-palmitoylates MAVS, thus inhibiting antiviral signaling, suggesting that its inhibitors, such as ML349, effectively reverse MAVS activation in response to antiviral infections. These findings underscore the critical role of PA in regulating antiviral innate immunity through MAVS palmitoylation and provide strategies for enhancing PA intake or targeting APT2 for combating viral infections.

S-acylation of p62 promotes p62 droplet recruitment into autophagosomes in mammalian autophagy.

p62 is a well-characterized autophagy receptor that recognizes and sequesters specific cargoes into autophagosomes for degradation. p62 promotes the assembly and removal of ubiquitinated proteins by forming p62-liquid droplets. However, it remains unclear how autophagosomes efficiently sequester p62 droplets. Herein, we report that p62 undergoes reversible S-acylation in multiple human-, rat-, and mouse-derived cell lines, catalyzed by zinc-finger Asp-His-His-Cys S-acyltransferase 19 (ZDHHC19) and deacylated by acyl protein thioesterase 1 (APT1). S-acylation of p62 enhances the affinity of p62 for microtubule-associated protein 1 light chain 3 (LC3)-positive membranes and promotes autophagic membrane localization of p62 droplets, thereby leading to the production of small LC3-positive p62 droplets and efficient autophagic degradation of p62-cargo complexes. Specifically, increasing p62 acylation by upregulating ZDHHC19 or by genetic knockout of APT1 accelerates p62 degradation and p62-mediated autophagic clearance of ubiquitinated proteins. Thus, the protein S-acylation-deacylation cycle regulates p62 droplet recruitment to the autophagic membrane and selective autophagic flux, thereby contributing to the control of selective autophagic clearance of ubiquitinated proteins.

Identification of a novel target of sulforaphane: Sulforaphane binds to acyl-protein thioesterase 2 (APT2) and attenuates its palmitoylation.

Sulforaphane (SFaN) is a food-derived compound with several bioactive properties, including atherosclerosis, diabetes, and obesity treatment. However, the mechanisms by which SFaN exerts its various effects are still unclear. To elucidate the mechanisms of the various effects of SFaN, we explored novel SFaN-binding proteins using SFaN beads and identified acyl protein thioesterase 2 (APT2). We also found that SFaN binds to the APT2 via C56 residue and attenuates the palmitoylation of APT2, thereby reducing plasma membrane localization of APT2. This study reveals a novel bioactivity of SFaN as a regulator of APT2 protein palmitoylation.

Monitoring imatinib decreasing pericyte coverage and HIF-1α level in a colorectal cancer model by an ultrahigh-field multiparametric MRI approach.

BACKGROUND: Excessive pericyte coverage promotes tumor growth, and a downregulation may solve this dilemma. Due to the double-edged sword role of vascular pericytes in tumor microenvironment (TME), indiscriminately decreasing pericyte coverage by imatinib causes poor treatment outcomes. Here, we optimized the use of imatinib in a colorectal cancer (CRC) model in high pericyte-coverage status, and revealed the value of multiparametric magnetic resonance imaging (mpMRI) at 9.4T in monitoring treatment-related changes in pericyte coverage and the TME. METHODS: CRC xenograft models were evaluated by histological vascular characterizations and mpMRI. Mice with the highest pericyte coverage were treated with imatinib or saline; then, vascular characterizations, tumor apoptosis and HIF-1α level were analyzed histologically, and alterations in the expression of Bcl-2/bax pathway were assessed through qPCR. The effects of imatinib were monitored by dynamic contrast-enhanced (DCE)-, diffusion-weighted imaging (DWI)- and amide proton transfer chemical exchange saturation transfer (APT CEST)-MRI at 9.4T. RESULTS: The DCE- parameters provided a good histologic match the tumor vascular characterizations. In the high pericyte coverage status, imatinib exhibited significant tumor growth inhibition, necrosis increase and pericyte coverage downregulation, and these changes were accompanied by increased vessel permeability, decreased microvessel density (MVD), increased tumor apoptosis and altered gene expression of apoptosis-related Bcl-2/bax pathway. Strategically, a 4-day imatinib effectively decreased pericyte coverage and HIF-1α level, and continuous treatment led to a less marked decrease in pericyte coverage and re-elevated HIF-1α level. Correlation analysis confirmed the feasibility of using mpMRI parameters to monitor imatinib treatment, with DCE-derived Ve and Ktrans being most correlated with pericyte coverage, Ve with vessel permeability, AUC with microvessel density (MVD), DWI-derived ADC with tumor apoptosis, and APT CEST-derived MTRasym at 1 µT with HIF-1α. CONCLUSIONS: These results provided an optimized imatinib regimen to achieve decreasing pericyte coverage and HIF-1α level in the high pericyte-coverage CRC model, and offered an ultrahigh-field multiparametric MRI approach for monitoring pericyte coverage and dynamics response of the TME to treatment.

CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies.

PURPOSE: To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR. METHODS: A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics. RESULTS: The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 µT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema. CONCLUSION: The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.

Amide proton transfer MRI at 9.4 T for differentiating tissue acidosis in a rodent model of ischemic stroke.

PURPOSE: Differentiating ischemic brain damage is critical for decision making in acute stroke treatment for better outcomes. We examined the sensitivity of amide proton transfer (APT) MRI, a pH-weighted imaging technique, to achieve this differentiation. METHODS: In a rat stroke model, the ischemic core, oligemia, and the infarct-growth region (IGR) were identified by tracking the progression of the lesions. APT MRI signals were measured alongside ADC, T1, and T2 maps to evaluate their sensitivity in distinguishing ischemic tissues. Additionally, stroke under hyperglycemic conditions was studied. RESULTS: The APT signal in the IGR decreased by about 10% shortly after stroke onset, and further decreased to 35% at 5 h, indicating a progression from mild to severe acidosis as the lesion evolved into infarction. Although ADC, T1, and T2 contrasts can only detect significant differences between the IGR and oligemia for a portion of the stroke duration, APT contrast consistently differentiates between them at all time points. However, the contrast to variation ratio at 1 h is only about 20% of the contrast to variation ratio between the core and normal tissues, indicating limited sensitivity. In the ischemic core, the APT signal decreases to about 45% and 33% of normal tissue level at 1 h for the normoglycemic and hyperglycemic groups, respectively, confirming more severe acidosis under hyperglycemia. CONCLUSION: The sensitivity of APT MRI is high in detecting severe acidosis of the ischemic core but is much lower in detecting mild acidosis, which may affect the accuracy of differentiation between the IGR and oligemia.

Unraveling contributions to the Z-spectrum signal at 3.5 ppm of human brain tumors.

PURPOSE: To evaluate the influence of the confounding factors, direct water saturation (DWS), and magnetization transfer contrast (MTC) effects on measured Z-spectra and amide proton transfer (APT) contrast in brain tumors. METHODS: High-grade glioma patients were scanned using an RF saturation-encoded 3D MR fingerprinting (MRF) sequence at 3 T. For MRF reconstruction, a recurrent neural network was designed to learn free water and semisolid macromolecule parameter mappings of the underlying multiple tissue properties from saturation-transfer MRF signals. The DWS spectra and MTC spectra were synthesized by solving Bloch-McConnell equations and evaluated in brain tumors. RESULTS: The dominant contribution to the saturation effect at 3.5 ppm was from DWS and MTC effects, but 25%-33% of the saturated signal in the gadolinium-enhancing tumor (13%-20% for normal tissue) was due to the APT effect. The APT# signal of the gadolinium-enhancing tumor was significantly higher than that of the normal-appearing white matter (10.1% vs. 8.3% at 1 µT and 11.2% vs. 7.8% at 1.5 µT). CONCLUSION: The RF saturation-encoded MRF allowed us to separate contributions to the saturation signal at 3.5 ppm in the Z-spectrum. Although free water and semisolid MTC are the main contributors, significant APT contrast between tumor and normal tissues was observed.

Fast and motion-robust saturation transfer MRI with inherent B0 correction using rosette trajectories and compressed sensing.

PURPOSE: To implement rosette readout trajectories with compressed sensing reconstruction for fast and motion-robust CEST and magnetization transfer contrast imaging with inherent correction of B0 inhomogeneity. METHODS: A pulse sequence was developed for fast saturation transfer imaging using a stack of rosette trajectories with a higher sampling density near the k-space center. Each rosette lobe was segmented into two halves to generate dual-echo images. B0 inhomogeneities were estimated using the phase difference between the images and corrected subsequently. The rosette-based imaging was evaluated in comparison to a fully sampled Cartesian trajectory and demonstrated on CEST phantoms (creatine solutions and egg white) and healthy volunteers at 3 T. RESULTS: Compared with the conventional Cartesian acquisition, compressed sensing reconstructed rosette images provided image quality with overall higher contrast-to-noise ratio and significantly faster readout time. Accurate B0 map estimation was achieved from the rosette acquisition with a negligible bias of 0.01 Hz between the rosette and dual-echo Cartesian gradient echo B0 maps, using the latter as ground truth. The water-saturation spectra (Z-spectra) and amide proton transfer weighted signals obtained from the rosette-based sequence were well preserved compared with the fully sampled data, both in the phantom and human studies. CONCLUSIONS: Fast, motion-robust, and inherent B0-corrected CEST and magnetization transfer contrast imaging using rosette trajectories could improve subject comfort and compliance, contrast-to-noise ratio, and provide inherent B0 homogeneity information. This work is expected to significantly accelerate the translation of CEST-MRI into a robust, clinically viable approach.

Evaluation of the molecular origin of amide proton transfer-weighted imaging.

PURPOSE: To evaluate the assumption in amide proton transfer weighted (APTw) imaging that the APT dominates over the relayed nuclear Overhauser enhancement (rNOE) and other CEST effects such as those from amines/guanidines, thereby providing imaging of mobile proteins/peptides. METHODS: We introduced two auxiliary asymmetric analysis metrics that can vary the relative contributions from amine/guanidinium CEST and other effects. By comparing these metrics with the conventional asymmetric analysis metric on healthy rat brains, we can approximately assess the contribution from amines/guanidines to APTw and determine whether the APT dominates over the rNOE effect. To further investigate the molecular origin of APTw, we used samples of dialyzed tissue homogenates to eliminate small metabolites and supernatants of homogenates to separate lipids from other components. RESULTS: When the APTw signal is positive using high saturation amplitudes (e.g., 2-3 µT), the contributions from amines/guanidines are significant and cannot be ignored. The APTw signal from the dialyzed homogenates and the controls has negligible changes, indicating that it primarily originates from macromolecules rather than small metabolites. Additionally, the APTw signals with low saturation amplitudes (e.g., 1 µT) were negative in tissue homogenates but positive in their supernatants, suggesting that proteins contribute positively to APTw signals, whereas lipids contribute negatively to it. CONCLUSION: The positive APTw signal using high saturation amplitudes could have significant contributions from soluble proteins through CEST, including amide/amine/guanidine proton transfer effects. In contrast, the negative APTw signal using low saturation amplitudes has significant contribution from lipids through rNOE.

Enhancing SNR in CEST imaging: A deep learning approach with a denoising convolutional autoencoder.

PURPOSE: To develop a SNR enhancement method for CEST imaging using a denoising convolutional autoencoder (DCAE) and compare its performance with state-of-the-art denoising methods. METHOD: The DCAE-CEST model encompasses an encoder and a decoder network. The encoder learns features from the input CEST Z-spectrum via a series of one-dimensional convolutions, nonlinearity applications, and pooling. Subsequently, the decoder reconstructs an output denoised Z-spectrum using a series of up-sampling and convolution layers. The DCAE-CEST model underwent multistage training in an environment constrained by Kullback-Leibler divergence, while ensuring data adaptability through context learning using Principal Component Analysis-processed Z-spectrum as a reference. The model was trained using simulated Z-spectra, and its performance was evaluated using both simulated data and in vivo data from an animal tumor model. Maps of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects were quantified using the multiple-pool Lorentzian fit, along with an apparent exchange-dependent relaxation metric. RESULTS: In digital phantom experiments, the DCAE-CEST method exhibited superior performance, surpassing existing denoising techniques, as indicated by the peak SNR and Structural Similarity Index. Additionally, in vivo data further confirm the effectiveness of the DCAE-CEST in denoising the APT and NOE maps when compared with other methods. Although no significant difference was observed in APT between tumors and normal tissues, there was a significant difference in NOE, consistent with previous findings. CONCLUSION: The DCAE-CEST can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution compared with other methods.

Let's get fat: emergence of S-acylation as a therapeutic target in Huntington disease.

Protein mislocalization is a key initial step in neurodegeneration, regardless of etiology, and has been linked to changes in the dynamic addition of saturated fatty acids to proteins, a process known as S-acylation. With the advent of new techniques to study S-acylation and the recent discovery of new enzymes that facilitate protein deacylation, novel small molecules are emerging as potential new therapeutic treatments. Huntington disease (HD) is a devastating, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric deficits caused by a CAG repeat expansion in the HTT gene. The protein that is mutated in HD, huntingtin, is less S-acylated which is associated with mutant HTT aggregation and cytotoxicity. Recent exciting findings indicate that restoring S-acylation in HD models using small molecule inhibitors of the deacylation enzymes is protective. Herein, we set out to describe the known roles of S-acylation in HD and how it can be targeted for therapeutic design.

Amide Proton Transfer-Weighted MRI, Associations with Clinical Severity and Prognosis in Ischemic Strokes.

BACKGROUND: The National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin scale (mRS) scores have important shortcomings. Amide proton transfer-weighted (APTw) imaging might offer more valuable information in ischemic strokes assessment. PURPOSE: To utilize APTw, apparent diffusion coefficient (ADC), and computed tomography perfusion (CTP) for the assessment of clinical symptom severity and 90-day prognosis in patients diagnosed with ischemic stroke. STUDY TYPE: Prospective. SUBJECTS: 61 patients (mean age 63.2 ± 9.7 years; 46 males, 15 females) with ischemic strokes were included in the study. FIELD STRENGTH/SEQUENCE: 3T/turbo spin echo (TSE) T1 -weighted imaging, T2 -weighted imaging, T2 -fluid attenuated inversion recovery (T2 -FLAIR), diffusion-weighted imaging (DWI), and single-shot TSE APTw imaging. ASSESSMENT: APTw, ADC, and CTP were used to compare patient subgroups and construct a prognostic nomogram model. STATISTICAL TESTS: Kolmogorov-Smirnov test, t-test, Mann-Whitney U test, chi-square test, Pearson correlation analysis, multivariate logistic regression analysis, decision curve analysis (DCA), receiver operating characteristic curves (ROCs). The significance threshold was set at P < 0.05. RESULTS: Correlation analysis revealed that APTw and NIHSS exhibit the highest correlation (r = -0.634, 95% confidence interval [CI] -0.418 to -0.782), surpassing that of ADC and lesion size. Multivariable analysis revealed APTw (odds ratio [OR] 0.905, 95% CI 0.845-0.970), ADC (OR 0.745, 95% CI 0.609-0.911), and infarct core-cerebral blood volume (IC-CBV) (OR 0.547, 95% CI 0.310-0.964) as potential risk factors associated with a poor prognosis. The nomogram model demonstrated the highest predictive efficacy, with an area under the curve (AUC) of 0.960 (95% CI 0.911-0.988), exceeding that of APTw, ADC, and IC-CBV individually. DATA CONCLUSION: The APTw technique holds potential value in categorizing and managing patients with ischemic stroke, offering guidance for the implementation of clinical treatment strategies. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Characterization of carotid plaques using chemical exchange saturation transfer imaging.

PURPOSE: The preoperative assessment of carotid plaques is necessary to render revascularization safe and effective. The aim of this study is to evaluate the usefulness of chemical exchange saturation transfer (CEST)-MRI, particularly amide proton transfer (APT) imaging as a preoperative carotid plaque diagnostic tool. METHODS: We recorded the APT signal intensity on concentration maps of 34 patients scheduled for carotid endarterectomy. Plaques were categorized into group A (APT signal intensity ≥ 1.90 E-04; n = 12) and group B (APT signal intensity < 1.90 E-04; n = 22). Excised plaques were subjected to histopathological assessment and, using the classification promulgated by the American Heart Association, they were classified as intraplaque hemorrhage-positive [type VI-positive (tVI+)] and -negative [no intraplaque hemorrhage (tVI-)]. RESULTS: Of the 34 patients, 22 (64.7%) harbored tVI+- and 12 (35.3%) had tVI- plaques. The median APT signals were significantly higher in tVI+- than tIVI- patients (2.43 E-04 (IQR = 0.98-4.00 E-04) vs 0.54 E-04 (IQR = 0.14-1.09 E-04), p < .001). Histopathologically, the number of patients with tVI+ plaques was significantly greater in group A (100%, n = 12) than group B (45%, n = 22) (p < .01). The number of symptomatic patients or asymptomatic patients with worsening stenosis was also significantly greater in group A than group B (75% vs 36%, p < .01). CONCLUSION: In unstable plaques with intraplaque hemorrhage and in patients with symptoms or progressive stenosis, the ATP signals were significantly elevated. CEST-MRI studies has the potential for the preoperative assessment of the plaques' characteristics.

Prenylation of aromatic amino acids and plant phenolics by an aromatic prenyltransferase from Rasamsonia emersonii.

Dimethylallyl tryptophan synthases (DMATSs) are aromatic prenyltransferases that catalyze the transfer of a prenyl moiety from a donor to an aromatic acceptor during the biosynthesis of microbial secondary metabolites. Due to their broad substrate scope, DMATSs are anticipated as biotechnological tools for producing bioactive prenylated aromatic compounds. Our study explored the substrate scope and product profile of a recombinant RePT, a novel DMATS from the thermophilic fungus Rasamsonia emersonii. Among a variety of aromatic substrates, RePT showed the highest substrate conversion for L-tryptophan and L-tyrosine (> 90%), yielding two mono-prenylated products in both cases. Nine phenolics from diverse phenolic subclasses were notably converted (> 10%), of which the stilbenes oxyresveratrol, piceatannol, pinostilbene, and resveratrol were the best acceptors (37-55% conversion). The position of prenylation was determined using NMR spectroscopy or annotated using MS2 fragmentation patterns, demonstrating that RePT mainly catalyzed mono-O-prenylation on the hydroxylated aromatic substrates. On L-tryptophan, a non-hydroxylated substrate, it preferentially catalyzed C7 prenylation with reverse N1 prenylation as a secondary reaction. Moreover, RePT also possessed substrate-dependent organic solvent tolerance in the presence of 20% (v/v) methanol or DMSO, where a significant conversion (> 90%) was maintained. Our study demonstrates the potential of RePT as a biocatalyst for the production of bioactive prenylated aromatic amino acids, stilbenes, and various phenolic compounds. KEY POINTS: • RePT catalyzes prenylation of diverse aromatic substrates. • RePT enables O-prenylation of phenolics, especially stilbenes. • The novel RePT remains active in 20% methanol or DMSO.

Compensating Image Distortions in a Commercial Reflectron-Type Atom Probe.

In atom probe tomography, the spatial resolution and accuracy of the data critically depend on the 3D reconstruction of the 2D detector data. Atom probes with a reflectron have an improved mass resolving power and must include a model of the imaging properties of the reflectron. However, for modern wide-angle reflectron instruments, these imaging properties are not trivial and need to be determined for the reflectron used. This is typically done by the instrument manufacturer, and due to the proprietary nature of the instrument design, the imaging properties are opaque to the user. In this paper, we provide a method to determine the imaging properties of a reflectron that can easily be carried out on commercial instrumentation. This method is used to provide the user with a transformation function from the provided detector data, which can already contain some corrections applied, to a virtual detector placed before the reflectron. From there on, 3D reconstructions can be carried out analogous to straight flight path instruments. Correction algorithms and reference data for Imago/CAMECA LEAP 3000, 4000, 5000, and 6000 series instruments are also provided.

An Automated Site-Specific Tip Preparation Method for Atom Probe Tomography Using Script-Controlled Focused Ion Beam/Scanning Electron Microscopy.

The automation of the atom probe tomography (APT) tip preparation using a focused ion beam (FIB) with a scanning electron microscopy (SEM) dual-beam system will certainly contribute to systematic APT research with higher throughput and reliability. While our previous work established a method to prepare tips with a specified tip curvature and taper angle automatically, by using script-controlled FIB/SEM, the technique has been expanded to automated "site-specific" tip preparation in the current work. The improved procedure can automatically detect not only the tip shape but also the interface position in the tip; thus, the new function allows for control of the tip apex position. In other words, automated "site-specific" tip preparations are possible. The details of the automation procedure and some experimental demonstrations, that is, a Pt cap on Si, InGaN-based MQWs, and a p-n junction of GaAs, are presented.

Parameter Optimization in Cluster Identification Algorithms for Characterizing Nanoclusters in Al-Mg-Si-Cu Alloys.

Optimization of user-defined parameters (Dmax, Nmin, order (K)) in the Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, used to characterize nanoclusters in Al-0.9% Mg-1.0% Si-0.3% Cu (mass %), was conducted. Ten combinations of parameters with a given K were considered for samples naturally aged (NA) and preaged (PA) at 100°C. We confirmed four types of unphysical clusters, artificially formed, by analyzing composition with size, atomic density, and atomic arrangement inside clusters. The optimum combinations minimizing those unphysical clusters were obtained for both NA and PA samples. Meanwhile, to evaluate the reliability of the optimum combination, volume rendering and isosurfacing were performed. As a result, regions of high solute concentration were confirmed, and those regions are in good agreement with the position of the clusters obtained by applying the optimum combination in DBSCAN. Furthermore, by comparing the optimum combinations with the fixed parameters widely used until now, we showed that for each dataset, considering independent parameters obtained in the same method is desirable rather than using fixed parameters. Consequently, an idea of determining the algorithm parameters for characterizing the nanoclusters in Al-Mg-Si(-Cu) alloys was introduced.

A MATLAB Toolbox for Findable, Accessible, Interoperable, and Reusable Atom Probe Data Science.

Atom probe tomography (APT) data analytics have traditionally been based on manual analytics by researchers. As newer atom probes together with focused ion beam-based specimen preparation have opened APT to many more materials, yielding much more complex mass spectra, building up a systematic understanding of the pathway from raw data to final interpretation has increasingly become important. This demands a system in which the data and treatment can be traced, ideally by any interested party. Such an approach of findable, accessible, interoperable, and reusable (FAIR) data and analysis policies is becoming increasingly important, not just in APT. In this paper, we present a toolbox, written in MATLAB, which allows the user to store the raw and processed data in a standardized FAIR format (hierarchical data format 5) and process the data in a largely scriptable environment to minimize manual user input. This allows for the experiment data to be interchanged without owner explanations and the analysis to be reproduced. We have devised a metadata scheme that is extensible to other experiments in the materials science domain. With this toolbox, collective knowledge can be built up, and a large number of data sets can be analyzed in a fully automated fashion.

On the Use of a Cluster Identification Method and a Statistical Approach for Analyzing Atom Probe Tomography Data for GP Zones in Al-Zn-Mg(-Cu) Alloys.

Early-stage clustering in two Al-Mg-Zn(-Cu) alloys has been investigated using atom probe tomography and transmission electron microscopy. Cluster identification by the isoposition method and a statistical approach based on the pair correlation function have both been applied to estimate the cluster size, composition, and volume fraction from atom probe data sets. To assess the accuracy of the quantification of clusters of different mean sizes, synthesized virtual data sets were used, accounting for a simulated degraded spatial resolution. The quality of the predictions made by the two complementary methods is discussed, considering the experimental and simulated data sets.

A Versatile Broadband Attached Proton Test Experiment for Routine 13C Nuclear Magnetic Resonance Spectroscopy.

The proposed broadband attached proton test sequence allows the user to easily record 13C nuclear magnetic resonance multiplicity-edited and quaternary-carbon-only spectra. Compared to earlier attached proton test experiments, it preserves both a tolerance for wide ranges of one-bond-coupling constant values and the effective suppression of residual CHn signals in the quaternary-carbon-only spectra. The recording of edited spectra or quaternary-carbon-only spectra is made easy by a single, user-controllable constant. These attributes make the broadband attached proton test experiment attractive for the 13C analysis of small molecules, including spectral editing, particularly in high-throughput analysis laboratories.