Developing and Evaluating Digital Public Health Interventions Using the Digital Public Health Framework DigiPHrame: A Framework Development Study.

BACKGROUND: Digital public health (DiPH) interventions may help us tackle substantial public health challenges and reach historically underserved populations, in addition to presenting valuable opportunities to improve and complement existing services. However, DiPH interventions are often triggered through technological advancements and opportunities rather than public health needs. To develop and evaluate interventions designed to serve public health needs, a comprehensive framework is needed that systematically covers all aspects with relevance for public health. This includes considering the complexity of the technology, the context in which the technology is supposed to operate, its implementation, and its effects on public health, including ethical, legal, and social aspects. OBJECTIVE: We aimed to develop such a DiPH framework with a comprehensive list of core principles to be considered throughout the development and evaluation process of any DiPH intervention. METHODS: The resulting digital public health framework (DigiPHrame) was based on a scoping review of existing digital health and public health frameworks. After extracting all assessment criteria from these frameworks, we clustered the criteria. During a series of multidisciplinary meetings with experts from the Leibniz ScienceCampus Digital Public Health, we restructured each domain to represent the complexity of DiPH. In this paper, we used a COVID-19 contact-tracing app as a use case to illustrate how DigiPHrame may be applied to assess DiPH interventions. RESULTS: The current version of DigiPHrame consists of 182 questions nested under 12 domains. Domain 1 describes the current status of health needs and existing interventions; domains 2 and 3, the DiPH technology under assessment and aspects related to human-computer interaction, respectively; domains 4 and 5, structural and process aspects, respectively; and domains 6-12, contextual conditions and the outcomes of the DiPH intervention from broad perspectives. In the CWA use case, a number of questions relevant during its development but also important for assessors once the CWA was available were highlighted. CONCLUSIONS: DigiPHrame is a comprehensive framework for the development and assessment of digital technologies designed for public health purposes. It is a living framework and will, therefore, be updated regularly and as new public health needs and technological advancements emerge.

Health economic evaluation of preventive digital public health interventions using decision-analytic modelling: a systematized review.

BACKGROUND: Digital public health (DiPH) provides novel approaches for prevention, potentially leading to long-term health benefits in resource-limited health systems. However, cost-effectiveness of DiPH interventions is unclear. This systematized review investigates the use of decision-analytic modelling in health economic evaluations of DiPH primary prevention and health promotion interventions, focusing on intervention's design, methods used, results, and reporting quality. METHODS: PubMed, CINAHL, and Web of Science were searched for studies of decision-analytic economic evaluations of digital interventions in primary prevention or health promotion, published up to June 2022. Intervention characteristics and selected items were extracted based on the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). Incremental cost-effectiveness ratios (ICERs) were then extracted and price-adjusted to compare the economic evaluation results. Finally, the included studies' reporting quality was assessed by building a score using CHEERS. RESULTS: The database search (including search update) produced 2,273 hits. After removing duplicates, 1,434 titles and abstracts were screened. Of the 89 studies meeting the full-text search criteria, 14 were ultimately reviewed. The most common targets were physical activity (five studies) and weight loss (four). Digital applications include text messages, web-based inventions, app-based interventions, e-learning devices, and the promotion of smartphone apps. The mean ICER of the 12 studies using quality-adjusted life years (QALYs) is €20,955 per QALY (min. - €3,949; max. €114,211). The mean of reported CHEERS items per study is 81% (min. 59%; max. 91%). CONCLUSIONS: This review only includes primary prevention and health promotion, and thus excludes other DiPH fields (e.g. secondary prevention). It also focuses on decision-analytic models, excluding study-based economic evaluations. Standard methods of economic evaluation could be adapted more to the specifics of DiPH by measuring the effectiveness of more current technologies through alternative methods, incorporating a societal perspective, and more clearly defining comparators. Nevertheless, the review demonstrates using common thresholds that the new field of DiPH shows potential for cost-effective preventive interventions.

Molecular basis for asymmetry sensing of siRNAs by the Drosophila Loqs-PD/Dcr-2 complex in RNA interference.

RNA interference defends against RNA viruses and retro-elements within an organism's genome. It is triggered by duplex siRNAs, of which one strand is selected to confer sequence-specificity to the RNA induced silencing complex (RISC). In Drosophila, Dicer-2 (Dcr-2) and the double-stranded RNA binding domain (dsRBD) protein R2D2 form the RISC loading complex (RLC) and select one strand of exogenous siRNAs according to the relative thermodynamic stability of base-pairing at either end. Through genome editing we demonstrate that Loqs-PD, the Drosophila homolog of human TAR RNA binding protein (TRBP) and a paralog of R2D2, forms an alternative RLC with Dcr-2 that is required for strand choice of endogenous siRNAs in S2 cells. Two canonical dsRBDs in Loqs-PD bind to siRNAs with enhanced affinity compared to miRNA/miRNA* duplexes. Structural analysis, NMR and biophysical experiments indicate that the Loqs-PD dsRBDs can slide along the RNA duplex to the ends of the siRNA. A moderate but notable binding preference for the thermodynamically more stable siRNA end by Loqs-PD alone is greatly amplified in complex with Dcr-2 to initiate strand discrimination by asymmetry sensing in the RLC.

Limits for Resolving Isobaric Tandem Mass Tag Reporter Ions Using Phase-Constrained Spectrum Deconvolution.

A popular method for peptide quantification relies on isobaric labeling such as tandem mass tags (TMT), which enables multiplexed proteome analyses. Quantification is achieved by reporter ions generated by fragmentation in a tandem mass spectrometer. However, with higher degrees of multiplexing, the smaller mass differences between the reporter ions increase the mass resolving power requirements. This contrasts with faster peptide sequencing capabilities enabled by lowered mass resolution on Orbitrap instruments. It is therefore important to determine the mass resolution limits for highly multiplexed quantification when maximizing proteome depth. Here, we defined the lower boundaries for resolving TMT reporter ions with 0.0063 Da mass differences using an ultra-high-field Orbitrap mass spectrometer. We found the optimal method depends on the relative ratio between closely spaced reporter ions and that 64 ms transient acquisition time provided sufficient resolving power for separating TMT reporter ions with absolute ratio changes up to 16-fold. Furthermore, a 32 ms transient processed with phase-constrained spectrum deconvolution provides >50% more identifications with >99% quantified but with a slight loss in quantification precision and accuracy. These findings should guide decisions on what Orbitrap resolution settings to use in future proteomics experiments, relying on isobaric TMT reporter ion quantification.

Systematic evaluation of CS-Rosetta for membrane protein structure prediction with sparse NOE restraints.

We critically test and validate the CS-Rosetta methodology for de novo structure prediction of α-helical membrane proteins (MPs) from NMR data, such as chemical shifts and NOE distance restraints. By systematically reducing the number and types of NOE restraints, we focus on determining the regime in which MP structures can be reliably predicted and pinpoint the boundaries of the approach. Five MPs of known structure were used as test systems, phototaxis sensory rhodopsin II (pSRII), a subdomain of pSRII, disulfide binding protein B (DsbB), microsomal prostaglandin E2 synthase-1 (mPGES-1), and translocator protein (TSPO). For pSRII and DsbB, where NMR and X-ray structures are available, resolution-adapted structural recombination (RASREC) CS-Rosetta yields structures that are as close to the X-ray structure as the published NMR structures if all available NMR data are used to guide structure prediction. For mPGES-1 and Bacillus cereus TSPO, where only X-ray crystal structures are available, highly accurate structures are obtained using simulated NMR data. One main advantage of RASREC CS-Rosetta is its robustness with respect to even a drastic reduction of the number of NOEs. Close-to-native structures were obtained with one randomly picked long-range NOEs for every 14, 31, 38, and 8 residues for full-length pSRII, the pSRII subdomain, TSPO, and DsbB, respectively, in addition to using chemical shifts. For mPGES-1, atomically accurate structures could be predicted even from chemical shifts alone. Our results show that atomic level accuracy for helical membrane proteins is achievable with CS-Rosetta using very sparse NOE restraint sets to guide structure prediction. Proteins 2017; 85:812-826. © 2016 Wiley Periodicals, Inc.

Solution structure of a minor and transiently formed state of a T4 lysozyme mutant.

Proteins are inherently plastic molecules, whose function often critically depends on excursions between different molecular conformations (conformers). However, a rigorous understanding of the relation between a protein's structure, dynamics and function remains elusive. This is because many of the conformers on its energy landscape are only transiently formed and marginally populated (less than a few per cent of the total number of molecules), so that they cannot be individually characterized by most biophysical tools. Here we study a lysozyme mutant from phage T4 that binds hydrophobic molecules and populates an excited state transiently (about 1 ms) to about 3% at 25 °C (ref. 5). We show that such binding occurs only via the ground state, and present the atomic-level model of the 'invisible', excited state obtained using a combined strategy of relaxation-dispersion NMR (ref. 6) and CS-Rosetta model building that rationalizes this observation. The model was tested using structure-based design calculations identifying point mutants predicted to stabilize the excited state relative to the ground state. In this way a pair of mutations were introduced, inverting the relative populations of the ground and excited states and altering function. Our results suggest a mechanism for the evolution of a protein's function by changing the delicate balance between the states on its energy landscape. More generally, they show that our approach can generate and validate models of excited protein states.

Differential global structural changes in the core particle of yeast and mouse proteasome induced by ligand binding.

Two clusters of configurations of the main proteolytic subunit ß5 were identified by principal component analysis of crystal structures of the yeast proteasome core particle (yCP). The apo-cluster encompasses unliganded species and complexes with nonpeptidic ligands, and the pep-cluster comprises complexes with peptidic ligands. The murine constitutive CP structures conform to the yeast system, with the apo-form settled in the apo-cluster and the PR-957 (a peptidic ligand) complex in the pep-cluster. In striking contrast, the murine immune CP classifies into the pep-cluster in both the apo and the PR-957-liganded species. The two clusters differ essentially by multiple small structural changes and a domain motion enabling enclosure of the peptidic ligand and formation of specific hydrogen bonds in the pep-cluster. The immune CP species is in optimal peptide binding configuration also in its apo form. This favors productive ligand binding and may help to explain the generally increased functional activity of the immunoproteasome. Molecular dynamics simulations of the representative murine species are consistent with the experimentally observed configurations. A comparison of all 28 subunits of the unliganded species with the peptidic liganded forms demonstrates a greatly enhanced plasticity of ß5 and suggests specific signaling pathways to other subunits.

Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

Recent work has shown that the accuracy of ab initio structure prediction can be significantly improved by integrating evolutionary information in form of intra-protein residue-residue contacts. Following this seminal result, much effort is put into the improvement of contact predictions. However, there is also a substantial need to develop structure prediction protocols tailored to the type of restraints gained by contact predictions. Here, we present a structure prediction protocol that combines evolutionary information with the resolution-adapted structural recombination approach of Rosetta, called RASREC. Compared to the classic Rosetta ab initio protocol, RASREC achieves improved sampling, better convergence and higher robustness against incorrect distance restraints, making it the ideal sampling strategy for the stated problem. To demonstrate the accuracy of our protocol, we tested the approach on a diverse set of 28 globular proteins. Our method is able to converge for 26 out of the 28 targets and improves the average TM-score of the entire benchmark set from 0.55 to 0.72 when compared to the top ranked models obtained by the EVFold web server using identical contact predictions. Using a smaller benchmark, we furthermore show that the prediction accuracy of our method is only slightly reduced when the contact prediction accuracy is comparatively low. This observation is of special interest for protein sequences that only have a limited number of homologs.

The Q Exactive HF, a Benchtop mass spectrometer with a pre-filter, high-performance quadrupole and an ultra-high-field Orbitrap analyzer.

The quadrupole Orbitrap mass spectrometer (Q Exactive) made a powerful proteomics instrument available in a benchtop format. It significantly boosted the number of proteins analyzable per hour and has now evolved into a proteomics analysis workhorse for many laboratories. Here we describe the Q Exactive Plus and Q Exactive HF mass spectrometers, which feature several innovations in comparison to the original Q Exactive instrument. A low-resolution pre-filter has been implemented within the injection flatapole, preventing unwanted ions from entering deep into the system, and thereby increasing its robustness. A new segmented quadrupole, with higher fidelity of isolation efficiency over a wide range of isolation windows, provides an almost 2-fold improvement of transmission at narrow isolation widths. Additionally, the Q Exactive HF has a compact Orbitrap analyzer, leading to higher field strength and almost doubling the resolution at the same transient times. With its very fast isolation and fragmentation capabilities, the instrument achieves overall cycle times of 1 s for a top 15 to 20 higher energy collisional dissociation method. We demonstrate the identification of 5000 proteins in standard 90-min gradients of tryptic digests of mammalian cell lysate, an increase of over 40% for detected peptides and over 20% for detected proteins. Additionally, we tested the instrument on peptide phosphorylation enriched samples, for which an improvement of up to 60% class I sites was observed.

A mechanism for the auto-inhibition of hyperpolarization-activated cyclic nucleotide-gated (HCN) channel opening and its relief by cAMP.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) ion channels control neuronal and cardiac electrical rhythmicity. There are four homologous isoforms (HCN1-4) sharing a common multidomain architecture that includes an N-terminal transmembrane tetrameric ion channel followed by a cytoplasmic "C-linker," which connects a more distal cAMP-binding domain (CBD) to the inner pore. Channel opening is primarily stimulated by transmembrane elements that sense membrane hyperpolarization, although cAMP reduces the voltage required for HCN activation by promoting tetramerization of the intracellular C-linker, which in turn relieves auto-inhibition of the inner pore gate. Although binding of cAMP has been proposed to relieve auto-inhibition by affecting the structure of the C-linker and CBD, the nature and extent of these cAMP-dependent changes remain limitedly explored. Here, we used NMR to probe the changes caused by the binding of cAMP and of cCMP, a partial agonist, to the apo-CBD of HCN4. Our data indicate that the CBD exists in a dynamic two-state equilibrium, whose position as gauged by NMR chemical shifts correlates with the V½ voltage measured through electrophysiology. In the absence of cAMP, the most populated CBD state leads to steric clashes with the activated or "tetrameric" C-linker, which becomes energetically unfavored. The steric clashes of the apo tetramer are eliminated either by cAMP binding, which selects for a CBD state devoid of steric clashes with the tetrameric C-linker and facilitates channel opening, or by a transition of apo-HCN to monomers or dimer of dimers, in which the C-linker becomes less structured, and channel opening is not facilitated.

A hybrid NMR/SAXS-based approach for discriminating oligomeric protein interfaces using Rosetta.

Oligomeric proteins are important targets for structure determination in solution. While in most cases the fold of individual subunits can be determined experimentally, or predicted by homology-based methods, protein-protein interfaces are challenging to determine de novo using conventional NMR structure determination protocols. Here we focus on a member of the bet-V1 superfamily, Aha1 from Colwellia psychrerythraea. This family displays a broad range of crystallographic interfaces none of which can be reconciled with the NMR and SAXS data collected for Aha1. Unlike conventional methods relying on a dense network of experimental restraints, the sparse data are used to limit conformational search during optimization of a physically realistic energy function. This work highlights a new approach for studying minor conformational changes due to structural plasticity within a single dimeric interface in solution.

Access to Cα backbone dynamics of biological solids by 13C T1 relaxation and molecular dynamics simulation.

We introduce a labeling scheme for magic angle spinning (MAS) solid-state NMR that is based on deuteration in combination with dilution of the carbon spin system. The labeling strategy achieves spectral editing by simplification of the HαCα and aliphatic side chain spectral region. A reduction in both proton and carbon spin density in combination with fast spinning (≥50 kHz) is essential to retrieve artifact-free (13)C-R1 relaxation data for aliphatic carbons. We obtain good agreement between the NMR experimental data and order parameters extracted from a molecular dynamics (MD) trajectory, which indicates that carbon based relaxation parameters can yield complementary information on protein backbone as well as side chain dynamics.

Determination of solution structures of proteins up to 40 kDa using CS-Rosetta with sparse NMR data from deuterated samples.

We have developed an approach for determining NMR structures of proteins over 20 kDa that utilizes sparse distance restraints obtained using transverse relaxation optimized spectroscopy experiments on perdeuterated samples to guide RASREC Rosetta NMR structure calculations. The method was tested on 11 proteins ranging from 15 to 40 kDa, seven of which were previously unsolved. The RASREC Rosetta models were in good agreement with models obtained using traditional NMR methods with larger restraint sets. In five cases X-ray structures were determined or were available, allowing comparison of the accuracy of the Rosetta models and conventional NMR models. In all five cases, the Rosetta models were more similar to the X-ray structures over both the backbone and side-chain conformations than the "best effort" structures determined by conventional methods. The incorporation of sparse distance restraints into RASREC Rosetta allows routine determination of high-quality solution NMR structures for proteins up to 40 kDa, and should be broadly useful in structural biology.

Automatic NOESY assignment in CS-RASREC-Rosetta.

We have developed an approach for simultaneous structure calculation and automatic Nuclear Overhauser Effect (NOE) assignment to solve nuclear magnetic resonance (NMR) structures from unassigned NOESY data. The approach, autoNOE-Rosetta, integrates Resolution Adapted Structural RECombination (RASREC) Rosetta NMR calculations with algorithms for automatic NOE assignment. The method was applied to two proteins in the 15-20 kDa size range for which both, NMR and X-ray data, is available. The autoNOE-Rosetta calculations converge for both proteins and yield accurate structures with an RMSD of 1.9 Å to the X-ray reference structures. The method greatly expands the radius of convergence for automatic NOE assignment, and should be broadly useful for NMR structure determination.

Robust and highly accurate automatic NOESY assignment and structure determination with Rosetta.

We have developed a novel and robust approach for automatic and unsupervised simultaneous nuclear Overhauser effect (NOE) assignment and structure determination within the CS-Rosetta framework. Starting from unassigned peak lists and chemical shift assignments, autoNOE-Rosetta determines NOE cross-peak assignments and generates structural models. The approach tolerates incomplete and raw NOE peak lists as well as incomplete or partially incorrect chemical shift assignments, and its performance has been tested on 50 protein targets ranging from 50 to 200 residues in size. We find a significantly improved performance compared to established programs, particularly for larger proteins and for NOE data obtained on perdeuterated protein samples. X-ray crystallographic structures allowed comparison of Rosetta and conventional, PDB-deposited, NMR models in 20 of 50 test cases. The unsupervised autoNOE-Rosetta models were often of significantly higher accuracy than the corresponding expert-supervised NMR models deposited in the PDB. We also tested the method with unrefined peak lists and found that performance was nearly as good as for refined peak lists. Finally, demonstrating our method's remarkable robustness against problematic input data, we provided correct models for an incorrect PDB-deposited NMR solution structure.

Site-specific analysis of heteronuclear Overhauser effects in microcrystalline proteins.

Relaxation parameters such as longitudinal relaxation are susceptible to artifacts such as spin diffusion, and can be affected by paramagnetic impurities as e.g. oxygen, which make a quantitative interpretation difficult. We present here the site-specific measurement of [(1)H](13)C and [(1)H](15)N heteronuclear rates in an immobilized protein. For methyls, a strong effect is expected due to the three-fold rotation of the methyl group. Quantification of the [(1)H](13)C heteronuclear NOE in combination with (13)C-R 1 can yield a more accurate analysis of side chain motional parameters. The observation of significant [(1)H](15)N heteronuclear NOEs for certain backbone amides, as well as for specific asparagine/glutamine sidechain amides is consistent with MD simulations. The measurement of site-specific heteronuclear NOEs is enabled by the use of highly deuterated microcrystalline protein samples in which spin diffusion is reduced in comparison to protonated samples.

Development of a GC/Quadrupole-Orbitrap mass spectrometer, part I: design and characterization.

Identification of unknown compounds is of critical importance in GC/MS applications (metabolomics, environmental toxin identification, sports doping, petroleomics, and biofuel analysis, among many others) and remains a technological challenge. Derivation of elemental composition is the first step to determining the identity of an unknown compound by MS, for which high accuracy mass and isotopomer distribution measurements are critical. Here, we report on the development of a dedicated, applications-grade GC/MS employing an Orbitrap mass analyzer, the GC/Quadrupole-Orbitrap. Built from the basis of the benchtop Orbitrap LC/MS, the GC/Quadrupole-Orbitrap maintains the performance characteristics of the Orbitrap, enables quadrupole-based isolation for sensitive analyte detection, and includes numerous analysis modalities to facilitate structural elucidation. We detail the design and construction of the instrument, discuss its key figures-of-merit, and demonstrate its performance for the characterization of unknown compounds and environmental toxins.

Improvement of virtual screening results by docking data feature analysis.

In this study, we propose a novel approach to evaluate virtual screening (VS) experiments based on the analysis of docking output data. This approach, which we refer to as docking data feature analysis (DDFA), consists of two steps. First, a set of features derived from the docking output data is computed and assigned to each molecule in the virtually screened library. Second, an artificial neural network (ANN) analyzes the molecule's docking features and estimates its activity. Given the simple architecture of the ANN, DDFA can be easily adapted to deal with information from several docking programs simultaneously. We tested our approach on the Directory of Useful Decoys (DUD), a well-established and highly accepted VS benchmark. Outstanding results were obtained by DDFA not only in comparison with the conventional rankings of the docking programs used in this work but also with respect to other methods found in the literature. Our approach performs with similar good results as the best available methods, which, however, also require substantially more computing time, economic resources, and/or expert intervention. Taken together, DDFA represents an automatic and highly attractive methodology for VS.

Ultra high resolution linear ion trap Orbitrap mass spectrometer (Orbitrap Elite) facilitates top down LC MS/MS and versatile peptide fragmentation modes.

Although only a few years old, the combination of a linear ion trap with an Orbitrap analyzer has become one of the standard mass spectrometers to characterize proteins and proteomes. Here we describe a novel version of this instrument family, the Orbitrap Elite, which is improved in three main areas. The ion transfer optics has an ion path that blocks the line of sight to achieve more robust operation. The tandem MS acquisition speed of the dual cell linear ion trap now exceeds 12 Hz. Most importantly, the resolving power of the Orbitrap analyzer has been increased twofold for the same transient length by employing a compact, high-field Orbitrap analyzer that almost doubles the observed frequencies. An enhanced Fourier Transform algorithm-incorporating phase information-further doubles the resolving power to 240,000 at m/z 400 for a 768 ms transient. For top-down experiments, we combine a survey scan with a selected ion monitoring scan of the charge state of the protein to be fragmented and with several HCD microscans. Despite the 120,000 resolving power for SIM and HCD scans, the total cycle time is within several seconds and therefore suitable for liquid chromatography tandem MS. For bottom-up proteomics, we combined survey scans at 240,000 resolving power with data-dependent collision-induced dissociation of the 20 most abundant precursors in a total cycle time of 2.5 s-increasing protein identifications in complex mixtures by about 30%. The speed of the Orbitrap Elite furthermore allows scan modes in which complementary dissociation mechanisms are routinely obtained of all fragmented peptides.

Sb(V) dihalide corroles: efficient singlet oxygen photosensitisers.

Sb(V) dihalide corrole complexes, in particular difluoro-5,15-di(4-cyanophenyl)-10-(2,4,5-trimethoxyphenyl)corrolatoantimony(V) (complex 1), show distinct emission properties and efficient intersystem crossing rates. Furthermore, complex 1 is characterised by its extended triplet excited state lifetime and an impressive singlet oxygen quantum yield exceeding 95%. This emphasises its potential for effective photooxidation reactions, positioning it as a leader in Sb(V) complex applications.