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Introduction Traditional open mastoidectomy is performed through a retro-auricular incision to expose the mastoid cortex. Few have addressed the possibility of performing an endoscopic minimally invasive mastoidectomy. Objective Our objective was to test the feasibility of performing an endoscopic mastoidectomy through a 1 cm incision and burr hole. Methods Ten cadaver heads (20 mastoids) were used for this morphometric study. We performed an endoscopic mastoidectomy through a 1 cm burr hole located over the antrum. The goals were to reach predetermined landmarks and maximize the drilling of cancellous mastoid bone. Computed tomography (CT) imaging was acquired at baseline, after endoscopic approach and after traditional open mastoidectomy. The scans were then analyzed with volumetric measurements of each mastoid. Results Endoscopic mastoidectomy facilitated access to most anatomical landmarks. While open mastoidectomy enabled greater extents of mastoidectomy and tegmen exposure, the endoscopic approach exposed 76% of mastoid and 69.9% of the tegmen achievable by the open approach. Additionally, baseline mastoid volume and tegmen surface area positively correlated with the extent of mastoidectomy and tegmen exposure, respectively. Baseline mastoid volume negatively correlated with the percentage of mastoid drilled and tegmen exposed. Conclusion We demonstrated the feasibility of an endoscopic mastoidectomy through a standardized postauricular burr hole. This approach reduces the incision size and the need for soft tissue dissection. Burr hole mastoidectomy is facilitated using angled scopes which are not reliant on 0-degree line-of-sight. Although the endoscopic approach afforded slightly less exposure, the location and burr hole size can be adjusted depending on the clinical indications. [ABSTRACT FROM AUTHOR]

Epilepsy is a prevalent and serious neurological condition which impacts millions of people worldwide. Stereoelectroencephalography (sEEG) is used in cases of drug resistant epilepsy to aid in surgical resection planning due to its high spatial resolution and ability to visualize seizure onset zones. For accurate localization of the seizure focus, sEEG studies combine pre-implantation magnetic resonance imaging, post-implant computed tomography to visualize electrodes, and temporally recorded sEEG electrophysiological data. Many tools exist to assist in merging multimodal spatial information; however, few allow for an integrated spatiotemporal view of the electrical activity. In the current work, we present SEEG4D, an automated tool to merge spatial and temporal data into a complete, four-dimensional virtual reality (VR) object with temporal electrophysiology that enables the simultaneous viewing of anatomy and seizure activity for seizure localization and presurgical planning. We developed an automated, containerized pipeline to segment tissues and electrode contacts. Contacts are aligned with electrical activity and then animated based on relative power. SEEG4D generates models which can be loaded into VR platforms for viewing and planning with the surgical team. Automated contact segmentation locations are within 1 mm of trained raters and models generated show signal propagation along electrodes. Critically, spatial-temporal information communicated through our models in a VR space have potential to enhance sEEG pre-surgical planning. [ABSTRACT FROM AUTHOR]

In nanomedicine, determining the spatial distribution of particles and drugs, together and apart, at high resolution within tissues, remains a major challenge because each must have a different label or detectable feature that can be observed with high sensitivity and resolution. We prepared nanoparticles capable of enzyme-directed assembly of particle therapeutics (EDAPT), containing an analogue of the Pt(II)-containing drug oxaliplatin, an 15N-labeled monomer in the hydrophobic block of the backbone of the polymer, the near-infrared dye Cy5.5, and a peptide that is a substrate for tumor metalloproteinases in the hydrophilic block. When these particles reach an environment rich in tumor associated proteases, the hydrophilic peptide substrate is cleaved, causing the particles to accumulate through a morphology transition, locking them in the tumor extracellular matrix. To evaluate the distribution of drug and EDAPT carrier in vivo, the localization of the isotopically labeled polymer backbone was compared to that of Pt by nanoscale secondary ion mass spectrometry (NanoSIMS). The correlation of NanoSIMS with super-resolution fluorescence microscopy revealed the release of the drug from the nanocarrier and colocalization with cellular DNA within tumor tissue. The results confirmed the dependence of particle accumulation and Pt(II) drug delivery on the presence of a Matrix Metalloproteinase (MMP) substrate and demonstrated antitumor activity. We conclude that these techniques are powerful for the elucidation of the localization of cargo and carrier, and enable a high-resolution assessment of their performance following in vivo delivery.

The use of genome-scale sequencing allows for identification of genetic findings beyond the original indication for testing (secondary findings). The ClinGen Actionability Working Groups (AWG) protocol for evidence synthesis and semi-quantitative metric scoring evaluates four domains of clinical actionability for potential secondary findings: severity and likelihood of the outcome, and effectiveness and nature of the intervention. As of February 2018, the AWG has scored 127 genes associated with 78 disorders (up-to-date topics/scores are available at www.clinicalgenome.org). Scores across these disorders were assessed to compare genes/disorders recommended for return as secondary findings by the American College of Medical Genetics and Genomics (ACMG) with those not currently recommended. Disorders recommended by the ACMG scored higher on outcome-related domains (severity and likelihood), but not on intervention-related domains (effectiveness and nature of the intervention). Current practices indicate that return of secondary findings will expand beyond those currently recommended by the ACMG. The ClinGen AWG evidence reports and summary scores are not intended as classifications of actionability, rather they provide a resource to aid decision makers as they determine best practices regarding secondary findings. The ClinGen AWG is working with the ACMG Secondary Findings Committee to update future iterations of their secondary findings list.

Identifying fundamental drivers of science and developing predictive models to capture its evolution are instrumental for the design of policies that can improve the scientific enterprise-for example, through enhanced career paths for scientists, better performance evaluation for organizations hosting research, discovery of novel effective funding vehicles, and even identification of promising regions along the scientific frontier. The science of science uses large-scale data on the production of science to search for universal and domain-specific patterns. Here, we review recent developments in this transdisciplinary field.

The atomic structure of the infectious, protease-resistant, β-sheet-rich and fibrillar mammalian prion remains unknown. Through the cryo-EM method MicroED, we reveal the sub-ångström-resolution structure of a protofibril formed by a wild-type segment from the β2-α2 loop of the bank vole prion protein. The structure of this protofibril reveals a stabilizing network of hydrogen bonds that link polar zippers within a sheet, producing motifs we have named 'polar clasps'.

One of the biggest bottlenecks for structural analysis of proteins remains the creation of high-yield and high-purity samples of the target protein. Cell-free protein synthesis technologies are powerful and customizable platforms for obtaining functional proteins of interest in short timeframes, while avoiding potential toxicity issues and permitting high-throughput screening. These methods have benefited many areas of genomic and proteomics research, therapeutics, vaccine development and protein chip constructions. In this work, we demonstrate a versatile and multiscale eukaryotic wheat germ cell-free protein expression pipeline to generate functional proteins of different sizes from multiple host organism and DNA source origins. We also report on a robust purification procedure, which can produce highly pure (> 98%) proteins with no specialized equipment required and minimal time invested. This pipeline successfully produced and analyzed proteins in all three major geometry formats used for structural biology including single particle analysis with electron microscopy, and both two-dimensional and three-dimensional protein crystallography. The flexibility of the wheat germ system in combination with the multiscale pipeline described here provides a new workflow for rapid production and purification of samples that may not be amenable to other recombinant approaches for structural characterization.

Previous proof-of-concept measurements on single-layer two-dimensional membrane-protein crystals performed at X-ray free-electron lasers (FELs) have demonstrated that the collection of meaningful diffraction patterns, which is not possible at synchrotrons because of radiation-damage issues, is feasible. Here, the results obtained from the analysis of a thousand single-shot, room-temperature X-ray FEL diffraction images from two-dimensional crystals of a bacteriorhodopsin mutant are reported in detail. The high redundancy in the measurements boosts the intensity signal-to-noise ratio, so that the values of the diffracted intensities can be reliably determined down to the detector-edge resolution of 4 Å. The results show that two-dimensional serial crystallography at X-ray FELs is a suitable method to study membrane proteins to near-atomic length scales at ambient temperature. The method presented here can be extended to pump-probe studies of optically triggered structural changes on submillisecond timescales in two-dimensional crystals, which allow functionally relevant large-scale motions that may be quenched in three-dimensional crystals.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

Supported metallic nanoparticles play a central role in catalysis. However, predictive modeling is particularly challenging due to the structural and dynamic complexity of the nanoparticle and its interface with the support, given that the sizes of interest are often well beyond those accessible via traditional ab initio methods. With recent advances in machine learning, it is now feasible to perform MD simulations with potentials retaining near-density-functional theory (DFT) accuracy, which can elucidate the growth and relaxation of supported metal nanoparticles, as well as reactions on those catalysts, at temperatures and time scales approaching those relevant to experiments. Furthermore, the surfaces of the support materials can also be modeled realistically through simulated annealing to include effects such as defects and amorphous structures. We study the adsorption of fluorine atoms on ceria and silica supported palladium nanoparticles using machine learning potential trained by DFT data using the DeePMD framework. We show defects on ceria and Pd/ceria interfaces are crucial for the initial adsorption of fluorine, while the interplay between Pd and ceria and the reverse oxygen migration from ceria to Pd control spillover of fluorine from Pd to ceria at later stages. In contrast, silica supports do not induce fluorine spillover from Pd particles. [ABSTRACT FROM AUTHOR]