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Abstract Type 1 pili are important virulence factors of uropathogenic Escherichia coli that mediate bacterial attachment to epithelial cells in the urinary tract. The pilus rod is comprised of thousands of copies of the main structural subunit FimA and is assembled in vivo by the assembly platform FimD. Although type 1 pilus rods can self-assemble from FimA in vitro, this reaction is slower and produces structures with lower kinetic stability against denaturants compared to in vivo-assembled rods. Our study reveals that FimD-catalysed in vitro-assembled type 1 pilus rods attain a similar stability as pilus rods assembled in vivo. Employing structural, biophysical and biochemical analyses, we show that in vitro assembly reactions lacking FimD produce pilus rods with structural defects, reducing their stability against dissociation. Overall, our results indicate that FimD is not only required for the catalysis of pilus assembly, but also to control the assembly of the most stable quaternary structure.

Nackednaviruses and hepatitis B virus (HBV) have a common non-enveloped viral ancestor. While HBV acquired an envelope during evolution, nackednaviruses remained non-enveloped. Here, Pfister et al. apply CryoEM and NMR to characterize the capsid structure of African cichlid nackednavirus (ACNDV) at pH 5.5 and pH 7.5 and show that the capsid structure is very similar to that of HBV.

Hepatitis B virus (HBV) capsid assembly modulators (CAM) represent a recent class of anti-HBV antivirals. Structural approaches provide limited conformational information on the CAM-induced off-path assemblies. Here, authors use solid-state NMR to establish a structural view on assembly modulation of the HBV capsid.

Digital health technologies can help tackle challenges in global public health. Digital and AI-for-Health Challenges, controlled events whose goal is to generate solutions to a given problem in a defined period of time, are one way of catalysing innovation. This article proposes an expanded investment framework for Global Health AI and digitalhealth Innovation that goes beyond traditional factors such as return on investment. Instead, we propose non monetary and non GDP metrics, such as Disability Adjusted Life Years or achievement of universal health coverage. Furthermore, we suggest a venture building approach around global health, which includes filtering of participants to reduce opportunity cost, close integration of implementation scientists and an incubator for the long-term development of ideas resulting from the challenge. Finally, we emphasize the need to strengthen human capital across a range of areas in local innovation, implementation-science, and in health services.

Here, the authors use solid-state NMR and EPR measurements to characterise the ATP hydrolysis transition state of the oligomeric bacterial DnaB helicase from Helicobacter pylori, which was trapped by using aluminium fluoride as a chemical mimic. They identify protein protons that coordinate to the phosphate groups of ADP and DNA and observe that the aluminium fluoride unit is highly mobile and fast-rotating.

With the growing demand for deploying Deep Learning models to the “edge”, it is paramount to develop techniques that allow to execute state-of-the-art models within very tight and limited resource constraints. In this work we propose a software-hardware optimization paradigm for obtaining a highly efficient execution engine of deep neural networks (DNNs) that are based on fully-connected layers. The work’s approach is centred around compression as a means for reducing the area as well as power requirements of, concretely, multilayer perceptrons (MLPs) with high predictive performances. Firstly, we design a novel hardware architecture named FantastIC4, which (1) supports the efficient on-chip execution of multiple compact representations of fully-connected layers and (2) minimizes the required number of multipliers for inference down to only 4 (thus the name). Moreover, in order to make the models amenable for efficient execution on FantastIC4, we introduce a novel entropy-constrained training method that renders them to be robust to 4bit quantization and highly compressible in size simultaneously. The experimental results show that we can achieve throughputs of 2.45 TOPS with a total power consumption of 3.6W on a Virtual Ultrascale FPGA XCVU440 device implementation, and achieve a total power efficiency of 20.17 TOPS/W on a 22nm process ASIC version. When compared to other state-of-the-art accelerators designed for the Google Speech Command (GSC) dataset, FantastIC4 is better by $51\times $ in terms of throughput and $145\times $ in terms of area efficiency (GOPS/mm2).

Deep-learned variational auto-encoders (VAE) have shown remarkable capabilities for lossy image compression. These neural networks typically employ non-linear convolutional layers for finding a compressible representation of the input image. Advanced techniques such as vector quantization, context-adaptive arithmetic coding and variable-rate compression have been implemented in these auto-encoders. Notably, these networks rely on an end-to-end approach, which fundamentally differs from hybrid, block-based video coding systems. Therefore, signal-dependent encoder optimizations have not been thoroughly investigated for VAEs yet. However, rate-distortion optimized encoding heavily determines the compression performance of state-of-the-art video codecs. Designing such optimizations for non-linear, multi-layered networks requires to understand the relationship between the quantization, the bit allocation of the features and the distortion. Therefore, this paper examines the rate-distortion performance of a variable-rate VAE. In particular, one demonstrates that the trained encoder network typically finds features with a near-optimal bit allocation across the channels. Furthermore, one approximates the relationship between distortion and quantization by a higher-order polynomial, whose coefficients can be robustly estimated. Based on these considerations, the authors investigate an encoding algorithm for the Lagrange optimization, which significantly improves the coding efficiency.

Abstract Digital contact tracing approaches based on Bluetooth low energy (BLE) have the potential to efficiently contain and delay outbreaks of infectious diseases such as the ongoing SARS-CoV-2 pandemic. In this work we propose a machine learning based approach to reliably detect subjects that have spent enough time in close proximity to be at risk of being infected. Our study is an important proof of concept that will aid the battery of epidemiological policies aiming to slow down the rapid spread of COVID-19.

DnaB helicases are motor proteins that couple ATP-hydrolysis to the movement of the protein along single-stranded DNA leading to a separation of double-stranded DNA at the replication fork. Here authors use solid-state NMR spectroscopy and reveal DnaB’s conformational responses to ATP hydrolysis and the resulting DNA loading and translocation.

Asparagine and glutamine side-chains can form hydrogen-bonded ladders which contribute significantly to the stability of amyloid fibrils. We show, using the example of HET-s(218–289) fibrils, that the primary amide side-chain proton resonances can be detected in cross-polarization based solid-state NMR spectra at fast magic-angle spinning (MAS). J-coupling based experiments offer the possibility to distinguish them from backbone amide groups if the spin-echo lifetimes are long enough, which turned out to be the case for the glutamine side-chains, but not for the asparagine side-chains forming asparagine ladders. We explore the sensitivity of NMR observables to asparagine ladder formation. One of the two possible asparagine ladders in HET-s(218–289), the one comprising N226 and N262, is assigned by proton-detected 3D experiments at fast MAS and significant de-shielding of one of the NH2 proton resonances indicative of hydrogen-bond formation is observed. Small rotating-frame 15N relaxation-rate constants point to rigidified asparagine side-chains in this ladder. The proton resonances are homogeneously broadened which could indicate chemical exchange, but is presently not fully understood. The second asparagine ladder (N243 and N279) in contrast remains more flexible.

Today, the sedimentation of proteins into a magic-angle spinning (MAS) rotor gives access to fast and reliable sample preparation for solid-state Nuclear Magnetic Resonance (NMR), and this has allowed for the investigation of a variety of non-crystalline protein samples. High protein concentrations on the order of 400 mg/mL can be achieved, meaning that around 50–60% of the NMR rotor content is protein; the rest is a buffer solution, which includes counter ions to compensate for the charge of the protein. We have demonstrated herein the long-term stability of four sedimented proteins and complexes thereof with nucleotides, comprising a bacterial DnaB helicase, an ABC transporter, an archaeal primase, and an RNA polymerase subunit. Solid-state NMR spectra recorded directly after sample filling and up to 5 years later indicated no spectral differences and no loss in signal intensity, allowing us to conclude that protein sediments in the rotor can be stable over many years. We have illustrated, using an example of an ABC transporter, that not only the structure is maintained, but that the protein is still functional after long-term storage in the sedimented state.

1H-detected solid-state NMR experiments feasible at fast magic-angle spinning (MAS) frequencies allow accessing 1H chemical shifts of proteins in solids, which enables their interpretation in terms of secondary structure. Here we present 1H and 13C-detected NMR spectra of the RNA polymerase subunit Rpo7 in complex with unlabeled Rpo4 and use the 13C, 15N, and 1H chemical-shift values deduced from them to study the secondary structure of the protein in comparison to a known crystal structure. We applied the automated resonance assignment approach FLYA including 1H-detected solid-state NMR spectra and show its success in comparison to manual spectral assignment. Our results show that reasonably reliable secondary-structure information can be obtained from 1H secondary chemical shifts (SCS) alone by using the sum of 1Hα and 1HN SCS rather than by TALOS. The confidence, especially at the boundaries of the observed secondary structure elements, is found to increase when evaluating 13C chemical shifts, here either by using TALOS or in terms of 13C SCS.

Nucleoside triphosphates (NTPs) are used as chemical energy source in a variety of cell systems. Structural snapshots along the NTP hydrolysis reaction coordinate are typically obtained by adding stable, nonhydrolyzable adenosine triphosphate (ATP) -analogues to the proteins, with the goal to arrest a state that mimics as closely as possible a physiologically relevant state, e.g., the pre-hydrolytic, transition and post-hydrolytic states. We here present the lessons learned on two distinct ATPases on the best use and unexpected pitfalls observed for different analogues. The proteins investigated are the bacterial DnaB helicase from Helicobacter pylori and the multidrug ATP binding cassette (ABC) transporter BmrA from Bacillus subtilis, both belonging to the same division of P-loop fold NTPases. We review the magnetic-resonance strategies which can be of use to probe the binding of the ATP-mimics, and present carbon-13, phosphorus-31, and vanadium-51 solid-state nuclear magnetic resonance (NMR) spectra of the proteins or the bound molecules to unravel conformational and dynamic changes upon binding of the ATP-mimics. Electron paramagnetic resonance (EPR), and in particular W-band electron-electron double resonance (ELDOR)-detected NMR, is of complementary use to assess binding of vanadate. We discuss which analogues best mimic the different hydrolysis states for the DnaB helicase and the ABC transporter BmrA. These might be relevant also to structural and functional studies of other NTPases.

Modern solid-state NMR techniques offer a wide range of opportunities for the structural characterization of frustrated Lewis pairs (FLPs), their aggregates, and the products of cooperative addition reactions at their two Lewis centers. This information is extremely valuable for materials that elude structural characterization by X-ray diffraction because of their nanocrystalline or amorphous character, (pseudo-)polymorphism, or other types of disordering phenomena inherent in the solid state. Aside from simple chemical shift measurements using single-pulse or cross-polarization/magic-angle spinning NMR detection techniques, the availability of advanced multidimensional and double-resonance NMR methods greatly deepened the informational content of these experiments. In particular, methods quantifying the magnetic dipole−dipole interaction strengths and indirect spin−spin interactions prove useful for the measurement of intermolecular association, connectivity, assessment of FLP−ligand distributions, and the stereochemistry of adducts. The present review illustrates several important solid-state NMR methods with some insightful applications to open questions in FLP chemistry, with a particular focus on supramolecular associates.

The substitution of Mg2+ by Mn2+ in the bacterial DnaB helicase from Helicobacter pylori, an ATP:Mg2+-fuelled protein engine, allows electron paramagnetic resonance (EPR) spectroscopy to be performed on this system. EPR experiments make it possible to monitor nucleotide binding and to estimate the fraction of bound Mn2+ through relaxation measurements. Furthermore, by measuring spin–spin distances we probe the geometry within such multimeric assemblies using ultra-wideband double electron-electron resonance (DEER) and relaxation induced dipolar modulation enhancement (RIDME). The extraction of distance distributions from RIDME experiments on high-spin paramagnetic centres is influenced by the presence of dipolar frequency overtones. We show herein that we can correct for these overtones by using a modified kernel function in Tikhonov regularization analysis routines, and that the overtone coefficients for Mn2+ in the DnaB helicase are practically the same as in the previously studied Mn2+–Mn2+ model compounds.

These days, there is an increasing interest in Mobile TV broadcast services shown by customers as well as service providers. One general problem of Mobile TV broadcast services is to maximize the coverage of users receiving an acceptable service quality, which is mainly influenced by the user's position and mobility within the cell. In this paper, graceful degradation is considered as an approach for improved service availability and coverage. We present a layered transmission approach for 3GPP's Release 6 Multimedia and Broadcast Service (MBMS) based on temporal scalability using H.264/AVC Baseline Profile. A differentiation in robustness between temporal quality layers is achieved by unequal error protection approach based on either application layer Forward Error Correction (FEC) or unequal transmit power for the layers or even a combination of both. We discuss the corresponding MBMS service as well as network settings and define measures allowing for evaluating the amount of users reached with a certain mobile terminal play-out quality while considering the network cell capacity usage. Using simulated 3GPP Rel. 6 network conditions, we show that if the service and network settings are chosen carefully, a noticeable extension of the coverage of the MBMS service can be achieved.