Flexible Interface Research Articles

A lightweight convolutional neural network for assessing an EEG risk marker for sudden unexpected death in epilepsy

BackgroundConvolutional neural network (CNN) has achieved state-of-art performance in many electroencephalogram (EEG) related studies. However, the application of CNN in prediction of risk factors for sudden unexpected death in epilepsy (SUDEP) remains as an underexplored area. It is unclear how the trade-off between computation cost and prediction power varies with changes in the complexity and depth of neural nets.MethodsThe purpose of this study was to explore the feasibility of using a lightweight CNN to predict SUDEP. A total of 170 patients were included in the analyses. The CNN model was trained using clips with 10-s signals sampled from the original EEG. We implemented Hann function to smooth the raw EEG signal and evaluated its effect by choosing different strength of denoising filter. In addition, we experimented two variations of the proposed model: (1) converting EEG input into an “RGB” format to address EEG channels underlying spatial correlation and (2) incorporating residual network (ResNet) into the bottle neck position of the proposed structure of baseline CNN.ResultsThe proposed baseline CNN model with lightweight architecture achieved the best AUC of 0.72. A moderate noise removal step facilitated the training of CNN model by ensuring stability of performance. We did not observe further improvement in model’s accuracy by increasing the strength of denoising filter.ConclusionPost-seizure slow activity in EEG is a potential marker for SUDEP, our proposed lightweight architecture of CNN achieved satisfying trade-off between efficiently identifying such biomarker and computational cost. It also has a flexible interface to be integrated with different variations in structure leaving room for further improvement of the model’s performance in automating EEG signal annotation.

Digital Preservation and Reconstruction of Old Cultural Elements in Augmented Reality (AR)

This research aimed to preserve traditional elements and urban fabric with enabled interaction in augmented reality (AR). Cultural elements and fabrics are mutually influential in Lukang, Taiwan. Evolved routes for tourism and religious activities have created characteristic elements and activity-based fabrics and facilities. The sustainable promotion of digital cultural assets started from photogrammetry modeling of alley space and shops. The application of AR enabled situated learning of 68 objects, including decorated façades, jar walls, the Lukang Gate, beggar seats, and other creative cultural elements. The heritages were promoted under a new interactive measure of feasibility that facilitated cultural sustainability in a remote site. A mobile interface with a convenient smartphone configured certain settings that were sufficiently flexible and easy to apply. The study presented an effective and efficient remote and situated learning process that correlated the development or setting of both locations. Correlation was achieved with a high fidelity of appearance and utilizing a flexible transformation interface. An approach, which recreated the background and formerly reconstructed objects during AR simulation, was used to verify the outcome of the situated study with conflicting qualitative and quantitative findings.

GABC: A comprehensive resource and Genome Atlas for Breast Cancer.

We developed the Genome Atlas of Breast Cancer (GABC), a global map of noncoding events in the human genome associated with breast cancer that provides a valuable reference resource for users to investigate the underlying genome abnormalities in breast cancer patients. Although significant progress has been made in breast cancer treatment, its morbidity and recurrence rates in women are still high worldwide. Curation and integration of breast cancer-related dysregulations from multiple aspects is essential for disease prevention and diagnosis. In this study, we developed the GABC, which contains 10 172 aberrant noncoding events occurring at multiomics levels, including the genome (single nucleotide polymorphism and somatic mutation), transcriptome (long noncoding RNA and microRNA) and epigenome (DNA methylation, enhancer and superenhancer). Each event entry provides descriptions of detailed biological mechanisms specific to the region or element. Users can also check the genome locations and relationships of functional regulators. The GABC provides a flexible and user-friendly interface for users to search, browse and download data. In addition, the GABC provides an interface to submit newly discovered noncoding events that can be included in the database. Therefore, the GABC aims to constantly enhance our understanding of noncoding genomic events in breast cancer.

MetaLAFFA: a flexible, end-to-end, distributed computing-compatible metagenomic functional annotation pipeline

BackgroundMicrobial communities have become an important subject of research across multiple disciplines in recent years. These communities are often examined via shotgun metagenomic sequencing, a technology which can offer unique insights into the genomic content of a microbial community. Functional annotation of shotgun metagenomic data has become an increasingly popular method for identifying the aggregate functional capacities encoded by the community’s constituent microbes. Currently available metagenomic functional annotation pipelines, however, suffer from several shortcomings, including limited pipeline customization options, lack of standard raw sequence data pre-processing, and insufficient capabilities for integration with distributed computing systems.ResultsHere we introduce MetaLAFFA, a functional annotation pipeline designed to take unfiltered shotgun metagenomic data as input and generate functional profiles. MetaLAFFA is implemented as a Snakemake pipeline, which enables convenient integration with distributed computing clusters, allowing users to take full advantage of available computing resources. Default pipeline settings allow new users to run MetaLAFFA according to common practices while a Python module-based configuration system provides advanced users with a flexible interface for pipeline customization. MetaLAFFA also generates summary statistics for each step in the pipeline so that users can better understand pre-processing and annotation quality.ConclusionsMetaLAFFA is a new end-to-end metagenomic functional annotation pipeline with distributed computing compatibility and flexible customization options. MetaLAFFA source code is available at https://github.com/borenstein-lab/MetaLAFFA and can be installed via Conda as described in the accompanying documentation.

A molecular dynamics study of the mechanical properties of the graphene/hexagonal boron nitride planar heterojunction for RRAM

Due to their high flexibility and precise interface modulation, resistive random access memory (RRAM) devices composed of graphene/hexagonal boron nitride (Gr/h-BN) planar heterojunctions are regarded as a possible solution and have gained a substantial amount of attention. Molecular dynamics simulations with a modified Tersoff potential are conducted to investigate the mechanical properties of three planar heterojunction RRAM molecular models (Gr/h-BN_V1/V2/V3), which are established according to the interface type and atomic position. Among them, the Gr/h-BN_V1 model exhibits the best mechanical properties, including the fracture strength, fracture strain, and Young's modulus, at all simulation temperatures. The extensive simulations reveal the effects of the temperature, aspect ratio, single-vacancy (SV) and Stone-Wales (SW) defects on the tensile strength of Gr/h-BN RRAM models. As the temperature increases from 10 K to 500 K, the fracture strengths of the Gr/h-BN_V1, Gr/h-BN_V2 and Gr/h-BN_V3 models decrease by 12.6%, 59.6% and 12.0%, respectively. It can be observed that when the aspect ratio is 2.83, the comprehensive mechanical properties of the Gr/ h-BN_V1 model are superior to those of the other models. A 6.7% concentration of single atomic defects in the SV_C, SV_B and SV_N models causes decreases in the fracture strength of 28.0 GPa, 33.9 GPa and 22.6 GPa, respectively, indicating that the mechanical properties are more sensitive to the introduction of boron atomic vacancies than carbon and nitrogen atomic vacancies. At all defect concentrations, the decrease in fracture strength and fracture strain caused by SW defects in the SW_CN model is minimized, while the demarcation point of the relative influence of the defect concentration on the tensile strength is 16% in the SW_CB and SW_CC models. Our present work provides useful insights into the application of highly flexible and stretchable Gr/h-BN planar heterojunctions for RRAM devices.

LiDAR- and AR-Based Monitoring of Evolved Building Façades upon Zoning Conflicts.

Zoning conflicts have transformed Old Street fabrics in terms of architectural style and construction material in Lukang, Taiwan. This transformation should be assessed as a contribution to digital cultural sustainability. The objective of this study was to compare the evolved façades resultant from the changes made by the development of architectural history and urban planning. A combination of 3D scan technology and a smartphone augmented reality (AR) app, Augment®, was applied to the situated comparison with direct interaction on-site. The AR application compared 20 façades in the laboratory and 18 façades in four different sites using a flexible interface. The comparisons identified the correlation of evolved façades in real sites in terms of building volumes and components, pedestrian arcades on store fronts, and previous installations. The situated comparisons were facilitated in a field study with real-time adjustments to 3D models and analyses of correlations across details and components. The application of AR was demonstrated to be effective in reinstalling scenes and differentiating diversified compositions of vocabulary in a remote site.

Versatile Dual-Inlet Sample Introduction System for Multi-Mode Single Particle Inductively Coupled Plasma Mass Spectrometry Analysis and Validation.

Metal-containing nanoparticles (NP) can be characterized with inductively coupled plasma mass spectrometers (ICP-MS) in terms of their size and number concentration by using the single-particle mode of the instrument (spICP-MS). The accuracy of measurement depends on the setup, operational conditions of the instrument and specific parameters that are set by the user. The transport efficiency of the ICP-MS is crucial for the quantification of the NP and usually requires a reference material with homogenous size distribution and a known particle number concentration. Currently, NP reference materials are available for only a few metals and in limited sizes. If particles are characterized without a reference standard, the results of both size and particle number may be biased. Therefore, a dual-inlet setup for characterizing nanoparticles with spICP-MS was developed to overcome this problem. This setup is based on a conventional introduction system consisting of a pneumatic nebulizer (PN) for nanoparticle solutions and a microdroplet generator (µDG) for ionic calibration solutions. A new and flexible interface was developed to facilitate the coupling of µDG, PN and the ICP-MS system. The interface consists of available laboratory components and allows for the calibration, nanoparticle (NP) characterization and cleaning of the arrangement, while the ICP-MS instrument is still running. Three independent analysis modes are available for determining particle size and number concentration. Each mode is based on a different calibration principle. While mode I (counting) and mode III (µDG) are known from the literature, mode II (sensitivity), is used to determine the transport efficiency by inorganic ionic standard solutions only. It is independent of NP reference materials. The µDG based inlet system described here guarantees superior analyte sensitivities and, therefore, lower detection limits (LOD). The size dependent LODs achieved are less than 15 nm for all NP (Au, Ag, CeO2) investigated.

Highly Flexible Single-Unit Resolution All Printed Neural Interface on a Bioresorbable Backbone.

Neural interfaces are the parts of the neural prosthesis that are in contact with the target tissue. The mechanical, chemical, and electrical properties of these interfaces can be a major determinant of the life of the implant and the neural tissue for chronic and even acute integrations. In this work, we developed a fully inkjet-printed, flexible neural interface on a bioresorbable backbone capable of recording high-fidelity neural activity. We utilized room temperature fabrication processes that overcome the limitations of semiconductor fabrication techniques for processing low-melting point polymers while maintaining high spatial and single-cell recording resolution. The ∼8 μm-thick devices in this study were fabricated onto two flexible polymers: (a) polyimide (PI), a biocompatible polymer commonly used for neural interfaces, and (b) polycaprolactone (PCL), a bioresorbable polyester with outstanding mechanical properties. Electrodes for neural recording were built at 30, 50, 75, and 100 μm diameter using silver nanoparticles/(3,4-ethylenedioxytiophene)-poly(styrenesulfonate) (AgNPs/PEDOT:PSS), which through our process achieved the lowest impedance reported in the literature reaching ∼200 Ω at 1 kHz for a 50 μm electrode diameter. We further enhanced the electrochemical performance of AgNPs/PEDOT:PSS by an order of magnitude by incorporating exfoliated graphene into the electrodes. The biocompatibility of the fabricated devices and their ability to record single-unit activity were confirmed by in vitro tests on both rat PC12 cells and isolated neural rat retina, respectively.

Ligand binding free-energy calculations with funnel metadynamics.

The accurate resolution of the binding mechanism of a ligand to its molecular target is fundamental to develop a successful drug design campaign. Free-energy calculations, which provide the energy value of the ligand-protein binding complex, are essential for resolving the binding mode of the ligand. The accuracy of free-energy calculation methods is counteracted by their poor user-friendliness, which hampers their broad application. Here we present the Funnel-Metadynamics Advanced Protocol (FMAP), which is a flexible and user-friendly graphical user interface (GUI)-based protocol to perform funnel metadynamics, a binding free-energy method that employs a funnel-shape restraint potential to reveal the ligand binding mode and accurately calculate the absolute ligand-protein binding free energy. FMAP guides the user through all phases of the free-energy calculation process, from preparation of the input files, to production simulation, to analysis of the results. FMAP delivers the ligand binding mode and the absolute protein-ligand binding free energy as outputs. Alternative binding modes and the role of waters are also elucidated, providing a detailed description of the ligand binding mechanism. The entire protocol on the paradigmatic system benzamidine-trypsin, composed of ~105 k atoms, took ~2.8 d using the Cray XC50 piz Daint cluster at the Swiss National Supercomputing Centre.

Effect of the silica-rubber interface on the mechanical, viscoelastic, and tribological behaviors of filled styrene-butadiene rubber vulcanizates

In this research, the effects of the surface modification of silica by low-molecular-weight hydroxyl-terminated polybutadiene (HTPB) are compared with those of bis(3-triethoxysilylpropyl)tetrasulfide (TESPT) on the mechanical, viscoelastic, and tribological properties of styrene-butadiene rubber (SBR) vulcanizates. Both modifiers have the ability to make covalent bonds with the rubber matrix, but with different interfacial characteristics controlling the final properties. The results displayed improvements in the tribological behavior of both modified silica-filled vulcanizates over pristine silica- and carbon black-filled vulcanizates. However, the HTPB modification method, despite providing a finer dispersion of the silica in the rubber, did not result in better tribological properties for the vulcanizates compared with those of the TESPT modification method. It was discussed that the HTPB modifier did not enhance tribological properties, especially abrasion resistance, as much as the TESPT modifier did because of the soft and flexible interface that was created in the presence of the HTPB modifier, in contrast to the rigid interface in the presence of TESPT. Molecular structure of silica surface modifiers greatly controls the performance of silica-filled styrene-butadiene rubber (SBR) through interfacial characteristics of the composites. Soft nature of low molecular-weight hydroxyl terminated polybutadiene (HTPB) and small number of its covalent bounds to the rubber matrix was compared with large number of rigid covalent bounds made between bis(3-triethoxysilylpropyl)tetrasulfide (TESPT) and rubber. Despite the better dispersion of silica modified with the former, the latter ensures higher transfer of stress to particles at large strains, inducing improved strength and abrasion resistance to composites.

Ctf18-RFC and DNA Pol ϵ form a stable leading strand polymerase/clamp loader complex required for normal and perturbed DNA replication.

The eukaryotic replisome must faithfully replicate DNA and cope with replication fork blocks and stalling, while simultaneously promoting sister chromatid cohesion. Ctf18-RFC is an alternative PCNA loader that links all these processes together by an unknown mechanism. Here, we use integrative structural biology combined with yeast genetics and biochemistry to highlight the specific functions that Ctf18-RFC plays within the leading strand machinery via an interaction with the catalytic domain of DNA Pol ϵ. We show that a large and unusually flexible interface enables this interaction to occur constitutively throughout the cell cycle and regardless of whether forks are replicating or stalled. We reveal that, by being anchored to the leading strand polymerase, Ctf18-RFC can rapidly signal fork stalling to activate the S phase checkpoint. Moreover, we demonstrate that, independently of checkpoint signaling or chromosome cohesion, Ctf18-RFC functions in parallel to Chl1 and Mrc1 to protect replication forks and cell viability.

Versatile Triboiontronic Transistor via Proton Conductor.

Iontronics are effective in modulating electrical properties through the electric double layers (EDLs) assisted with ionic migration/arrangement, which are highly promising for unconventional electronics, ionic sensory devices, and flexible interactive interface. Proton conductors with the smallest and most abundant protons (H+) can realize a faster migration/polarization under electric field to form the EDL with higher capacitance. Here, a versatile triboiontronic MoS2 transistor via proton conductor by sophisticated combination of triboelectric modulation and protons migration has been demonstrated. This device utilizes triboelectric potential originated from mechanical displacement to modulate the electrical properties of transistors via protons migration/accumulation. It shows superior electrical properties, including high current on/off ratio over 106, low cutoff current (∼0.04 pA), and steep switching properties (89 μm/dec). Pioneering noise tests are conducted to the tribotronic devices to exclude the possible noise interference introduced by mechanical displacement. The versatile triboiontronic MoS2 transistor via proton conductor has been utilized for mechanical behavior derived logic devices and an artificial sensory neuron system. This work represents the reliable and effective triboelectric potential modulation on electronic transportation through protonic dielectrics, which is highly desired for theoretical study of tribotronic gating, active mechanosensation, self-powered electronic skin, artificial intelligence, etc.

Enabling Cellular Communication for Aerial Vehicles: Providing Reliability for Future Applications

Due to safety concerns, a reliable radio communication link is a key component in the future application of unmanned aerial vehicles (UAVs), as it will enable beyond visual line-of-sight (BVLOS) operations. In terms of cost and deployment time, radio communication for aerial vehicles will greatly benefit from the ready-to-market infrastructure and ubiquitous coverage of cellular networks. However, these are optimized for terrestrial users, and the different propagation environment experienced by aerial vehicles poses some interference challenges. In this article, field measurements and system-level simulations are used to assess interferencemitigation solutions that can improve aerial-link reliability. We then discuss how 5 G New Radio (NR) favors the integration of UAVs into cellular networks, as its flexible air interface and beamforming-suited frequencies facilitate the deployment of interference-management solutions.

Influence of Ageing on Flexible Pavement Interface Bond under Repeated Shear Stresses

The durability of interface bond was not sufficiently taken into consideration, and the research work in this field is scares and scattered. The interface bond usually practices dynamic shear stresses throughout its service life while ageing due to volatilization provide stiffness at the interface. In this investigation, an attempt has been made to assess the durability of the interface bond in terms of resistance to ageing under repeated shear stresses. Two types of tack coat (Rapid Curing cutback RC-70 and Cationic Medium setting emulsion CMS) and three application rates have been implemented in the preparation of two layers slab samples (base overlaid by binder, and binder overlaid by wearing) courses using roller compactor. Asphalt concrete core specimens were obtained from the roller compacted slab samples and subjected to long term ageing, then the specimens were subjected to 1200 repeated shear stress cycles. The accumulation of permanent deformation was monitored. Afterwards, the specimens were tested for interface shear strength at 20 °C. Control specimens were also tested for comparison. It was concluded that ageing reduces the total microstrain for RC-70 tack coat by (43.6, 25.6, and 29.5) % and (50, 51.3, and 30.2) % for (binder-base) and (wearing-binder) interfaces for the application rate of (0.15, 0.33, 0.5) l/m2 respectively. However, ageing reduces the total microstrain for CMS tack coat by (37, 35.5, and 40.3) % and (45.2 , 49, and 46.8) % for (binder-base) and (wearing-binder) interfaces for the application rate of (0.1, 0.23, 0.35) l/m2 respectively. Ageing increases the interface bond shear strength by a range of (8-27)% for various interfaces, tack coat type and application rates.

Abstract A40: The SIAMCAT R package enables statistical and machine learning analyses for case-control microbiome datasets

Abstract Alterations in microbiome composition have been linked to many human diseases, including colorectal cancer or precancerous liver diseases. Findings from microbiome-association studies are increasingly explored as promising avenues for clinical applications due to their diagnostic or therapeutic potential. However, microbiome data complexity and the lack of integrated computational tools make it difficult to arrive at robust associations and predictive disease models. Here, we present the SIAMCAT R package as a modular and user-friendly toolbox for machine learning workflows, statistical analysis, and confounder detection for case-control microbiome datasets. Previously, we conducted a machine learning meta-analysis of colorectal cancer metagenomics studies (Wirbel, Pyl et al., Nat Med 2019) using the functionalities of SIAMCAT, which is now available to the wider community via Bioconductor. We showcase how SIAMCAT is a versatile tool by applying it to a large set of metagenomic datasets that have been processed with a wide variety of taxonomic and functional profiling tools. We furthermore demonstrate how SIAMCAT can help to detect confounding factors in microbiome association studies. By making stringent machine learning workflows and analysis pipelines available through a user-friendly and flexible interface, SIAMCAT will facilitate microbiome data analyses, biomarker discovery, and thus the translation of microbiome research to clinical applications, while simultaneously improving statistical rigor and safeguarding against common machine learning pitfalls. Citation Format: Jakob Wirbel, Konrad Zych, Morgan Essex, Nicolai Karcher, Ece Kartal, Guillem Salazar, Peer Bork, Shinichi Sunagawa, Georg Zeller. The SIAMCAT R package enables statistical and machine learning analyses for case-control microbiome datasets [abstract]. In: Proceedings of the AACR Special Conference on the Microbiome, Viruses, and Cancer; 2020 Feb 21-24; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2020;80(8 Suppl):Abstract nr A40.

The open EEGLAB portal Interface: High-Performance computing with EEGLAB

EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently (Delorme et al., 2019) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscience community to build and run MATLAB pipelines using the EEGLAB tool environment. We are now releasing an EEGLAB plug-in, nsgportal, that interfaces EEGLAB with NSG directly from within EEGLAB running on MATLAB on any personal lab computer. The plug-in features a flexible MATLAB graphical user interface (GUI) that allows users to easily submit, interact with, and manage NSG jobs, and to retrieve and examine their results. Command line nsgportal tools supporting these GUI functionalities allow EEGLAB users and plug-in tool developers to build largely automated functions and workflows that include optional NSG job submission and processing. Here we present details on nsgportal implementation and documentation, provide user tutorials on example applications, and show sample test results comparing computation times using HPC versus laptop processing.

Standing Air Bubble-Based Micro-Hydraulic Capacitors for Flow Stabilization in Syringe Pump-Driven Systems.

Unstable liquid flow in syringe pump-driven systems due to the low-speed vibration of the step motor is commonly observed as an unfavorable phenomenon, especially when the flow rate is relatively small. Upon the design of a convenient and cost-efficient microfluidic standing air bubble system, this paper studies the physical principles behind the flow stabilization phenomenon of the bubble-based hydraulic capacitors. A bubble-based hydraulic capacitor consists of three parts: tunable microfluidic standing air bubbles in specially designed crevices on the fluidic channel wall, a proximal pneumatic channel, and porous barriers between them. Micro-bubbles formed in the crevices during liquid flow and the volume of the bubble can be actively controlled by the pneumatic pressure changing in the proximal channel. When there is a flowrate fluctuation from the upstream, the flexible air-liquid interface would deform under the pressure variation, which is analogous to the capacitive charging/discharging process. The theoretical model based on Euler law and the microfluidic equivalent circuit was developed to understand the multiphysical phenomenon. Experimental data characterize the liquid flow stabilization performance of the flow stabilizer with multiple key parameters, such as the number and the size of microbubbles. The developed bubble-based hydraulic capacitor could minimize the flow pulses from syringe pumping by 75.3%. Furthermore, a portable system is demonstrated and compared with a commercial pressure-driven flow system. This study can enhance the understanding of the bubble-based hydraulic capacitors that would be beneficial in microfluidic systems where the precise and stable liquid flow is required.

On attaining user-friendly hand gesture interfaces to control existing GUIs

BackgroundHand gesture interfaces are dedicated programs that principally perform hand tracking and hand gesture prediction to provide alternative controls and interaction methods. They take advantage of one of the most natural ways of interaction and communication, proposing novel input and showing great potential in the field of the human-computer interaction. Developing a flexible and rich hand gesture interface is known to be a time-consuming and arduous task. Previously published studies have demonstrated the significance of the finite-state-machine (FSM) approach when mapping detected gestures to GUI actions. MethodsIn our hand gesture interface, we broadened the FSM approach by utilizing gesture-specific attributes, such as distance between hands, distance from the camera, and time of occurrences, to enable users to perform unique GUI actions. These attributes are obtained from hand gestures detected by the RealSense SDK employed in our hand gesture interface. By means of these gesture-specific attributes, users can activate static gestures and perform them as dynamic gestures. We also provided supplementary features to enhance the efficiency, convenience, and user-friendliness of our hand gesture interface. Moreover, we developed a complementary application for recording hand gestures by capturing hand keypoints in depth and color images to facilitate the generation of hand gesture datasets. ResultsWe conducted a small-scale user survey with fifteen subjects to test and evaluate our hand gesture interface. Anonymous feedback obtained from the users indicates that our hand gesture interface is adequately facile and self-explanatory to use. In addition, we received constructive feedback about minor flaws regarding the responsiveness of the interface. ConclusionsWe proposed a hand gesture interface along with key concepts to attain user-friendliness and effectiveness in the control of existing GUIs.

Silicon Anodes: Flexible Interface Design for Stress Regulation of a Silicon Anode toward Highly Stable Dual‐Ion Batteries (Adv. Mater. 17/2020)

The “Flexible Interface Design” of a silicon anode is represented as a shield made of wicker by Zijian Zheng, Yongbing Tang, and co-workers, as reported in article number 1908470. The spear is broken when striking the shield, suggesting the significant effectiveness of the flexible interface design which is helpful to relieve interface stress.

Retro Is Cool: Structure of the Versatile Retromer Complex

In this issue of Structure, Kendall etal. (2020) reveal the cryo-EM structure of the mammalian retromer complex, which is essential in sorting membrane proteins in endosomes. The retromer heterotrimer can oligomerize in multiple conformations; this versatility is promoted by a flexible interface of electrostatic residues on the VPS35 subunit.