Metallaphotoredox aryl and alkyl radiomethylation for PET ligand discovery.

Positron emission tomography (PET) radioligands (radioactively labelled tracer compounds) are extremely useful for in vivo characterization of central nervous system drug candidates, neurodegenerative diseases and numerous oncology targets1. Both tritium and carbon-11 radioisotopologues are generally necessary for in vitro and in vivo characterization of radioligands2, yet there exist few radiolabelling protocols for the synthesis of either, inhibiting the development of PET radioligands. The synthesis of such radioligands also needs to be very rapid owing to the short half-life of carbon-11. Here we report a versatile and rapid metallaphotoredox-catalysed method for late-stage installation of both tritium and carbon-11 into the desired compounds via methylation of pharmaceutical precursors bearing aryl and alkyl bromides. Methyl groups are among the most prevalent structural elements found in bioactive molecules, and so this synthetic approach simplifies the discovery of radioligands. To demonstrate the breadth of applicability of this technique, we perform rapid synthesis of 20 tritiated and 10 carbon-11-labelled complex pharmaceuticals and PET radioligands, including a one-step radiosynthesis of the clinically used compounds [11C]UCB-J and [11C]PHNO. We further outline the direct utility of this protocol for preclinical PET imaging and its translation to automated radiosynthesis for routine radiotracer production in human clinical imaging. We also demonstrate this protocol for the installation of other diverse and pharmaceutically useful isotopes, including carbon-14, carbon-13 and deuterium.

Direct observation of ultrafast hydrogen bond strengthening in liquid water.

Water is one of the most important, yet least understood, liquids in nature. Many anomalous properties of liquid water originate from its well-connected hydrogen bond network1, including unusually efficient vibrational energy redistribution and relaxation2. An accurate description of the ultrafast vibrational motion of water molecules is essential for understanding the nature of hydrogen bonds and many solution-phase chemical reactions. Most existing knowledge of vibrational relaxation in water is built upon ultrafast spectroscopy experiments2-7. However, these experiments cannot directly resolve the motion of the atomic positions and require difficult translation of spectral dynamics into hydrogen bond dynamics. Here, we measure the ultrafast structural response to the excitation of the OH stretching vibration in liquid water with femtosecond temporal and atomic spatial resolution using liquid ultrafast electron scattering. We observed a transient hydrogen bond contraction of roughly 0.04 Å on a timescale of 80 femtoseconds, followed by a thermalization on a timescale of approximately 1 picosecond. Molecular dynamics simulations reveal the need to treat the distribution of the shared proton in the hydrogen bond quantum mechanically to capture the structural dynamics on femtosecond timescales. Our experiment and simulations unveil the intermolecular character of the water vibration preceding the relaxation of the OH stretch.

Monitoring the Evolution of Relative Product Populations at Early Times during a Photochemical Reaction.

Identifying multiple rival reaction products and transient species formed during ultrafast photochemical reactions and determining their time-evolving relative populations are key steps toward understanding and predicting photochemical outcomes. Yet, most contemporary ultrafast studies struggle with clearly identifying and quantifying competing molecular structures/species among the emerging reaction products. Here, we show that mega-electronvolt ultrafast electron diffraction in combination with ab initio molecular dynamics calculations offer a powerful route to determining time-resolved populations of the various isomeric products formed after UV (266 nm) excitation of the five-membered heterocyclic molecule 2(5H)-thiophenone. This strategy provides experimental validation of the predicted high (∼50%) yield of an episulfide isomer containing a strained three-membered ring within ∼1 ps of photoexcitation and highlights the rapidity of interconversion between the rival highly vibrationally excited photoproducts in their ground electronic state.

In Situ Single Particle Reconstruction Reveals 3D Evolution of PtNi Nanocatalysts During Heating.

Tailoring nanoparticles' composition and morphology is of particular interest for improving their performance for catalysis. A challenge of this approach is that the nanoparticles' optimized initial structure often changes during use. Visualizing the three dimensional (3D) structural transformation in situ is therefore critical, but often prohibitively difficult experimentally. Although electron tomography provides opportunities for 3D imaging, restrictions in the tilt range of in situ holders together with electron dose considerations limit the possibilities for in situ electron tomography studies. Here, an in situ 3D imaging methodology is presented using single particle reconstruction (SPR) that allows 3D reconstruction of nanoparticles with controlled electron dose and without tilting the microscope stage. This in situ SPR methodology is employed to investigate the restructuring and elemental redistribution within a population of PtNi nanoparticles at elevated temperatures. The atomic structure of PtNi is further examined and a heat-induced transition is found from a disordered to an ordered phase. Changes in structure and elemental distribution are linked to a loss of catalytic activity in the oxygen reduction reaction. The in situ SPR methodology employed here can be extended to a wide range of in situ studies employing not only heating, but gaseous, aqueous, or electrochemical environments to reveal in-operando nanoparticle evolution in 3D.

The effect of Omicron breakthrough infection and extended BNT162b2 booster dosing on neutralization breadth against SARS-CoV-2 variants of concern.

COVID-19 vaccines are playing a vital role in controlling the COVID-19 pandemic. As SARS-CoV-2 variants encoding mutations in the surface glycoprotein, Spike, continue to emerge, there is increased need to identify immunogens and vaccination regimens that provide the broadest and most durable immune responses. We compared the magnitude and breadth of the neutralizing antibody response, as well as levels of Spike-reactive memory B cells, in individuals receiving a second dose of BNT162b2 at a short (3-4 week) or extended interval (8-12 weeks) and following a third vaccination approximately 6-8 months later. We show that whilst an extended interval between the first two vaccinations can greatly increase the breadth of the immune response and generate a higher proportion of Spike reactive memory B cells, a third vaccination leads to similar levels between the two groups. Furthermore, we show that the third vaccine dose enhances neutralization activity against omicron lineage members BA.1, BA.2 and BA.4/BA.5 and this is further increased following breakthrough infection during the UK omicron wave. These findings are relevant for vaccination strategies in populations where COVID-19 vaccine coverage remains low.

The Ring-Closing Reaction of Cyclopentadiene Probed with Ultrafast X-ray Scattering.

The dynamics of cyclopentadiene (CP) following optical excitation at 243 nm was investigated by time-resolved pump-probe X-ray scattering using 16.2 keV X-rays at the Linac Coherent Light Source (LCLS). We present the first ultrafast structural evidence that the reaction leads directly to the formation of bicyclo[2.1.0]pentene (BP), a strained molecule with three- and four-membered rings. The bicyclic compound decays via a thermal backreaction to the vibrationally hot CP with a time constant of 21 ± 3 ps. A minor channel leads to ring-opened structures on a subpicosecond time scale.

Sphingosine-1-phosphate induces airway smooth muscle hyperresponsiveness and proliferation.

BACKGROUND: The emerging role of sphingosine-1-phosphate (S1P) in regulating smooth muscle functions has led to the exploration of the possibility that this sphingolipid could represent a potential therapeutic target in asthma and other lung diseases. Several studies in animal surrogates have suggested a role for S1P-mediated signaling in the regulation of airway smooth muscle (ASM) contraction, airway hyperresponsiveness, and airway remodeling, but evidence from human studies is lacking. OBJECTIVE: We sought to compare the responsiveness of the airways to S1P in healthy and asthmatic individuals in vivo, in isolated human airways ex vivo, and in murine airways dissected from healthy and house dust mite (HDM)-sensitized animals. METHODS: Airway responsiveness was measured by spirometry during inhalation challenges and by wire myography in airways isolated from human and mouse lungs. Thymidine incorporation and calcium mobilization assays were used to study human ASM cell responses. RESULTS: S1P did not induce contraction of airways isolated from healthy and HDM-exposed mice, nor in human airways. Similarly, there was no airway constriction observed in healthy and asthmatic subjects in response to increasing concentrations of inhaled S1P. However, a 30-minute exposure to S1P induced a significant concentration-dependent enhancement of airway reactivity to methacholine and to histamine in murine and human airways, respectively. HDM-sensitized mice demonstrated a significant increase in methacholine responsiveness, which was not further enhanced by S1P treatment. S1P also concentration-dependently enhanced proliferation of human ASM cells, an effect mediated through S1P receptor type 2, as shown by selective antagonism and S1P receptor type 2 small-interfering RNA knockdown. CONCLUSIONS: Our data suggest that S1P released locally into the airways may be involved in the regulation of ASM hyperresponsiveness and hyperplasia, defining a novel target for future therapies.

Chemical Kinetics of Metal Single Atom and Nanocluster Formation on Surfaces: An Example of Pt on Hexagonal Boron Nitride.

The production of atomically dispersed metal catalysts remains a significant challenge in the field of heterogeneous catalysis due to coexistence with continuously packed sites such as nanoclusters and nanoparticles. This work presents a comprehensive guidance on how to increase the degree of atomization through a selection of appropriate experimental conditions and supports. It is based on a rigorous macro-kinetic theory that captures relevant competing processes of nucleation and formation of single atoms stabilized by point defects. The effects of metal-support interactions and deposition parameters on the resulting single atom to nanocluster ratio as well as the role of metal centers formed on point defects in the kinetics of nucleation have been established, thus paving the way to guided synthesis of single atom catalysts. The predictions are supported by experimental results on sputter deposition of Pt on exfoliated hexagonal boron nitride, as imaged by aberration-corrected scanning transmission electron microscopy.

Clinical outcomes of 20 brachycephalic dogs with thoracolumbar spinal deformities causing neurological signs treated with spinal stabilization using 3D-printed patient-specific drill guides.

OBJECTIVE: To describe the clinical outcomes for pugs and French bulldogs with congenital vertebral malformations, undergoing thoracolumbar spinal stabilization surgery using 3D-printed patient-specific drill guides. To evaluate the accuracy of pedicle screw placement in this group of dogs. STUDY DESIGN: Retrospective descriptive study. ANIMALS: Twenty dogs (12 pugs and eight French bulldogs). METHODS: Medical records searched between August 2018 and March 2021 for pugs and French bulldogs diagnosed with congenital vertebral abnormalities via magnetic resonance imaging (MRI) scan and computed tomography (CT) scan causing T3-L3 myelopathy signs that underwent spinal stabilization surgery using 3D-printed patient-specific drill guides followed by a postoperative CT scan. The short-term outcome was based on the neurological grade (modified Frankel score-MFS) on the day after surgery, day of discharge, and at the follow-up examination at 4 to 6 weeks after surgery. The mid-term outcome was obtained via an online questionnaire (or direct examination in one case). RESULTS: Twenty dogs met the inclusion criteria (19/20 grade 2 MFS, 1/20 grade 4 MFS). No complications were reported in the immediate postoperative period and optimal pedicle screw placement was obtained in 169/201 of screws. Twenty-four hours after surgery 16/20 dogs displayed an unchanged neurological grade. Short-term outcomes revealed a static (17/20) or improved (2/20) neurological grade. Ten owners participated in the online questionnaire. All patients were reported to be ambulatory; however, 7/10 dogs displayed abnormal gait. Neurological signs had remained static (6/10) or improved (3/10) in comparison with the dogs' preoperative status at a median of 883.5 days from the surgery. CONCLUSION: Dogs in this study had a favorable short-term outcome and mid-term outcome evaluation revealed a static/improved neurological status. CLINICAL SIGNIFICANCE: Thoracolumbar spinal stabilization surgery using 3D-printed patient-specific drill guides showed a favorable outcome in brachycephalic breeds affected by vertebral deformities.

Ultralow Catalytic Loading for Optimised Electrocatalytic Performance of AuPt Nanoparticles to Produce Hydrogen and Ammonia.

The hydrogen evolution and nitrite reduction reactions are key to producing green hydrogen and ammonia. Antenna-reactor nanoparticles hold promise to improve the performances of these transformations under visible-light excitation, by combining plasmonic and catalytic materials. However, current materials involve compromising either on the catalytic activity or the plasmonic enhancement and also lack control of reaction selectivity. Here, we demonstrate that ultralow loadings and non-uniform surface segregation of the catalytic component optimize catalytic activity and selectivity under visible-light irradiation. Taking Pt-Au as an example we find that fine-tuning the Pt content produces a 6-fold increase in the hydrogen evolution compared to commercial Pt/C as well as a 6.5-fold increase in the nitrite reduction and a 2.5-fold increase in the selectivity for producing ammonia under visible light excitation relative to dark conditions. Density functional theory suggests that the catalytic reactions are accelerated by the intimate contact between nanoscale Pt-rich and Au-rich regions at the surface, which facilitates the formation of electron-rich hot-carrier puddles associated with the Pt-based active sites. The results provide exciting opportunities to design new materials with improved photocatalytic performance for sustainable energy applications.

Compact single-shot soft X-ray photon spectrometer for free-electron laser diagnostics.

The photon spectrum from free-electron laser (FEL) light sources offers valuable information in time-resolved experiments and machine optimization in the spectral and temporal domains. We have developed a compact single-shot photon spectrometer to diagnose soft X-ray spectra. The spectrometer consists of an array of off-axis Fresnel zone plates (FZP) that act as transmission-imaging gratings, a Ce:YAG scintillator, and a microscope objective to image the scintillation target onto a two-dimensional imaging detector. This spectrometer operates in segmented energy ranges which covers tens of electronvolts for each absorption edge associated with several atomic constituents: carbon, nitrogen, oxygen, and neon. The spectrometer's performance is demonstrated at a repetition rate of 120 Hz, but our detection scheme can be easily extended to 200 kHz spectral collection by employing a fast complementary metal oxide semiconductor (CMOS) line-scan camera to detect the light from the scintillator. This compact photon spectrometer provides an opportunity for monitoring the spectrum downstream of an endstation in a limited space environment with sub-electronvolt energy resolution.

Femtosecond Electronic and Hydrogen Structural Dynamics in Ammonia Imaged with Ultrafast Electron Diffraction.

Directly imaging structural dynamics involving hydrogen atoms by ultrafast diffraction methods is complicated by their low scattering cross sections. Here we demonstrate that megaelectronvolt ultrafast electron diffraction is sufficiently sensitive to follow hydrogen dynamics in isolated molecules. In a study of the photodissociation of gas phase ammonia, we simultaneously observe signatures of the nuclear and corresponding electronic structure changes resulting from the dissociation dynamics in the time-dependent diffraction. Both assignments are confirmed by ab initio simulations of the photochemical dynamics and the resulting diffraction observable. While the temporal resolution of the experiment is insufficient to resolve the dissociation in time, our results represent an important step towards the observation of proton dynamics in real space and time.

Ultrafast Imaging of Molecules with Electron Diffraction.

Photoexcited molecules convert light into chemical and mechanical energy through changes in electronic and nuclear structure that take place on femtosecond timescales. Gas phase ultrafast electron diffraction (GUED) is an ideal tool to probe the nuclear geometry evolution of the molecules and complements spectroscopic methods that are mostly sensitive to the electronic state. GUED is a weak and passive probing tool that does not alter the molecular properties during the probing process and is sensitive to the spatial distribution of charge in the molecule, including both electrons and nuclei. Improvements in temporal resolution have enabled GUED to capture coherent nuclear motions in molecules in the excited and ground electronic states with femtosecond and subangstrom resolution. Here we present the basic theory of GUED and explain what information is encoded in the diffraction signal, review how GUED has been used to observe coherent structural dynamics in recent experiments, and discuss the advantages and limitations of the method.

Bridging imaging users to imaging analysis - A community survey.

The 'Bridging Imaging Users to Imaging Analysis' survey was conducted in 2022 by the Center for Open Bioimage Analysis (COBA), BioImaging North America (BINA) and the Royal Microscopical Society Data Analysis in Imaging Section (RMS DAIM) to understand the needs of the imaging community. Through multichoice and open-ended questions, the survey inquired about demographics, image analysis experiences, future needs and suggestions on the role of tool developers and users. Participants of the survey were from diverse roles and domains of the life and physical sciences. To our knowledge, this is the first attempt to survey cross-community to bridge knowledge gaps between physical and life sciences imaging. Survey results indicate that respondents' overarching needs are documentation, detailed tutorials on the usage of image analysis tools, user-friendly intuitive software, and better solutions for segmentation, ideally in a format tailored to their specific use cases. The tool creators suggested the users familiarise themselves with the fundamentals of image analysis, provide constant feedback and report the issues faced during image analysis while the users would like more documentation and an emphasis on tool friendliness. Regardless of the computational experience, there is a strong preference for 'written tutorials' to acquire knowledge on image analysis. We also observed that the interest in having 'office hours' to get an expert opinion on their image analysis methods has increased over the years. The results also showed less-than-expected usage of online discussion forums in the imaging community for solving image analysis problems. Surprisingly, we also observed a decreased interest among the survey respondents in deep/machine learning despite the increasing adoption of artificial intelligence in biology. In addition, the community suggests the need for a common repository for the available image analysis tools and their applications. The opinions and suggestions of the community, released here in full, will help the image analysis tool creation and education communities to design and deliver the resources accordingly.

Drug repurposing based on a quantum-inspired method versus classical fingerprinting uncovers potential antivirals against SARS-CoV-2.

The COVID-19 pandemic has accelerated the need to identify new antiviral therapeutics at pace, including through drug repurposing. We employed a Quadratic Unbounded Binary Optimization (QUBO) model, to search for compounds similar to Remdesivir, the first antiviral against SARS-CoV-2 approved for human use, using a quantum-inspired device. We modelled Remdesivir and compounds present in the DrugBank database as graphs, established the optimal parameters in our algorithm and resolved the Maximum Weighted Independent Set problem within the conflict graph generated. We also employed a traditional Tanimoto fingerprint model. The two methods yielded different lists of lead compounds, with some overlap. While GS-6620 was the top compound predicted by both models, the QUBO model predicted BMS-986094 as second best. The Tanimoto model predicted different forms of cobalamin, also known as vitamin B12. We then determined the half maximal inhibitory concentration (IC50) values in cell culture models of SARS-CoV-2 infection and assessed cytotoxicity. We also demonstrated efficacy against several variants including SARS-CoV-2 Strain England 2 (England 02/2020/407073), B.1.1.7 (Alpha), B.1.351 (Beta) and B.1.617.2 (Delta). Lastly, we employed an in vitro polymerization assay to demonstrate that these compounds directly inhibit the RNA-dependent RNA polymerase (RdRP) of SARS-CoV-2. Together, our data reveal that our QUBO model performs accurate comparisons (BMS-986094) that differed from those predicted by Tanimoto (different forms of vitamin B12); all compounds inhibited replication of SARS-CoV-2 via direct action on RdRP, with both models being useful. While Tanimoto may be employed when performing relatively small comparisons, QUBO is also accurate and may be well suited for very complex problems where computational resources may limit the number and/or complexity of possible combinations to evaluate. Our quantum-inspired screening method can therefore be employed in future searches for novel pharmacologic inhibitors, thus providing an approach for accelerating drug deployment.

Methanol synthesis from CO2 and H2 using supported Pd alloy catalysts.

A number of Pd based materials have been synthesised and evaluated as catalysts for the conversion of carbon dioxide and hydrogen to methanol, a useful platform chemical and hydrogen storage molecule. Monometallic Pd catalysts show poor methanol selectivity, but this is improved through the formation of Pd alloys, with both PdZn and PdGa alloys showing greatly enhanced methanol productivity compared with monometallic Pd/Al2O3 and Pd/TiO2 catalysts. Catalyst characterisation shows that the 1 : 1 ß-PdZn alloy is present in all Zn containing post-reaction samples, including PdZn/Ga2O3, with the Pd2Ga alloy formed for the Pd/Ga2O3 sample. The heat of mixing was calculated for a variety of alloy compositions with high values determined for both PdZn and Pd2Ga alloys, at ca. -0.6 eV per atom and ca. -0.8 eV per atom, respectively. However, ZnO is more readily reduced than Ga2O3, providing a possible explanation for the preferential formation of the PdZn alloy, rather than PdGa, when in the presence of Ga2O3.

Maleic acid is a biomarker for maleylacetoacetate isomerase deficiency; implications for newborn screening of tyrosinemia type 1.

Dried blood spot succinylacetone (SA) is often used as a biomarker for newborn screening (NBS) for tyrosinemia type 1 (TT1). However, false-positive SA results are often observed. Elevated SA may also be due to maleylacetoacetate isomerase deficiency (MAAI-D), which appears to be clinically insignificant. This study investigated whether urine organic acid (uOA) and quantitative urine maleic acid (Q-uMA) analyses can distinguish between TT1 and MAAI-D. We reevaluated/measured uOA (GC-MS) and/or Q-uMA (LC-MS/MS) in available urine samples of nine referred newborns (2 TT1, 7 false-positive), eight genetically confirmed MAAI-D children, and 66 controls. Maleic acid was elevated in uOA of 5/7 false-positive newborns and in the three available samples of confirmed MAAI-D children, but not in TT1 patients. Q-uMA ranged from not detectable to 1.16 mmol/mol creatinine in controls (n = 66) and from 0.95 to 192.06 mmol/mol creatinine in false-positive newborns and MAAI-D children (n = 10). MAAI-D was genetically confirmed in 4/7 false-positive newborns, all with elevated Q-uMA, and rejected in the two newborns with normal Q-uMA. No sample was available for genetic analysis of the last false-positive infant with elevated Q-uMA. Our study shows that MAAI-D is a recognizable cause of false-positive TT1 NBS results. Elevated urine maleic acid excretion seems highly effective in discriminating MAAI-D from TT1.

Cd/Pt Precursor Solution for Solar H2 Production and in situ Photochemical Synthesis of Pt Single-atom Decorated CdS Nanoparticles.

Despite extensive efforts to develop high-performance H2 evolution catalysts, this remains a major challenge. Here, we demonstrate the use of Cd/Pt precursor solutions for significant photocatalytic H2 production (154.7 mmol g-1 h-1 ), removing the need for a pre-synthesized photocatalyst. In addition, we also report simultaneous in situ synthesis of Pt single-atoms anchored CdS nanoparticles (PtSA -CdSIS ) during photoirradiation. The highly dispersed in situ incorporation of extensive Pt single atoms on CdSIS enables the enhancement of active sites and suppresses charge recombination, which results in exceptionally high solar-to-hydrogen conversion efficiency of ≈1 % and an apparent quantum yield of over 91 % (365 nm) for H2 production. Our work not only provides a promising strategy for maximising H2 production efficiency but also provides a green process for H2 production and the synthesis of highly photoactive PtSA -CdSIS nanoparticles.

The time-resolved atomic, molecular and optical science instrument at the Linac Coherent Light Source.

The newly constructed time-resolved atomic, molecular and optical science instrument (TMO) is configured to take full advantage of both linear accelerators at SLAC National Accelerator Laboratory, the copper accelerator operating at a repetition rate of 120 Hz providing high per-pulse energy as well as the superconducting accelerator operating at a repetition rate of about 1 MHz providing high average intensity. Both accelerators power a soft X-ray free-electron laser with the new variable-gap undulator section. With this flexible light source, TMO supports many experimental techniques not previously available at LCLS and will have two X-ray beam focus spots in line. Thereby, TMO supports atomic, molecular and optical, strong-field and nonlinear science and will also host a designated new dynamic reaction microscope with a sub-micrometer X-ray focus spot. The flexible instrument design is optimized for studying ultrafast electronic and molecular phenomena and can take full advantage of the sub-femtosecond soft X-ray pulse generation program.

Trainable segmentation for transmission electron microscope images of inorganic nanoparticles.

We present a trainable segmentation method implemented within the python package ParticleSpy. The method takes user labelled pixels, which are used to train a classifier and segment images of inorganic nanoparticles from transmission electron microscope images. This implementation is based on the trainable Waikato Environment for Knowledge Analysis (WEKA) segmentation, but is written in python, allowing a large degree of flexibility and meaning it can be easily expanded using other python packages. We find that trainable segmentation offers better accuracy than global or local thresholding methods and requires as few as 100 user-labelled pixels to produce an accurate segmentation. Trainable segmentation presents a balance of accuracy and training time between global/local thresholding and neural networks, when used on transmission electron microscope images of nanoparticles. We also quantitatively investigate the effectiveness of the components of trainable segmentation, its filter kernels and classifiers, in order to demonstrate the use cases for the different filter kernels in ParticleSpy and the most accurate classifiers for different data types. A set of filter kernels is identified that are effective in distinguishing particles from background but that retain dissimilar features. In terms of classifiers, we find that different classifiers perform optimally for different image contrast; specifically, a random forest classifier performs best for high-contrast ADF images, but that QDA and Gaussian Naïve Bayes classifiers perform better for low-contrast TEM images.

Measurement of the size, shape and composition of nanoparticles is routinely performed using transmission electron microscopy and related techniques. Typically, distinguishing particles from the background in an image is performed using the intensity of each pixel, creating two sets of pixels to separate particles from background. However, this separation of intensity can be difficult if the contrast in an image is low, or if the intensity of the background varies significantly. In this study, an approach that takes into account additional image features (such as boundaries and texture) was investigated to study electron microscope images of metallic nanoparticles. In this 'trainable segmentation' approach, the user labels examples of particle and background pixels in order to train a machine learning algorithm to distinguish between particles and background. The performance of different machine learning algorithms was investigated, in addition to the effect of using different features to aid the segmentation. Overall, a trainable segmentation approach was found to perform better than use of an intensity threshold to distinguish between particles and background in electron microscope images.