Expansive discovery of chemically diverse structured macrocyclic oligoamides

Small macrocycles with four or fewer amino acids are among the most potent natural products known, but there is currently no way to systematically generate such compounds. We describe a computational method for identifying ordered macrocycles composed of alpha, beta, gamma, and 17 other amino acid backbone chemistries, which we used to predict 14.9 million closed cycles composed of >42,000 monomer combinations. We chemically synthesized 18 macrocycles predicted to adopt single low-energy states and determined their x-ray or nuclear magnetic resonance structures; 15 of these were very close to the design models. We illustrate the therapeutic potential of these macrocycle designs by developing selective inhibitors of three protein targets of current interest. By opening up a vast space of readily synthesizable drug-like macrocycles, our results should considerably enhance structure-based drug design.

New insights into aging in LiNiO2 cathodes from high resolution paramagnetic NMR spectroscopy

Bulk degradation processes are examined in the LiNiO2 cathode using high resolution solid-state NMR, combined with magnetometry and X-ray diffraction. Capacity decay is correlated with bulk heterogeneity, whereby multiple structural domains coexist in the charged state, and the Li content and electrochemical activity of these domains is unraveled for the first time.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. Deep learning methods promise to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here, we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Design of amyloidogenic peptide traps

Segments of proteins with high β-strand propensity can self-associate to form amyloid fibrils implicated in many diseases. We describe a general approach to bind such segments in β-strand and β-hairpin conformations using de novo designed scaffolds that contain deep peptide-binding clefts. The designs bind their cognate peptides in vitro with nanomolar affinities. The crystal structure of a designed protein-peptide complex is close to the design model, and NMR characterization reveals how the peptide-binding cleft is protected in the apo state. We use the approach to design binders to the amyloid-forming proteins transthyretin, tau, serum amyloid A1 and amyloid β1-42 (Aβ42). The Aβ binders block the assembly of Aβ fibrils as effectively as the most potent of the clinically tested antibodies to date and protect cells from toxic Aβ42 species.

Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment

On December 5, 2022, an indirect drive fusion implosion on the National Ignition Facility (NIF) achieved a target gain G_{target} of 1.5. This is the first laboratory demonstration of exceeding "scientific breakeven" (or G_{target}>1) where 2.05 MJ of 351 nm laser light produced 3.1 MJ of total fusion yield, a result which significantly exceeds the Lawson criterion for fusion ignition as reported in a previous NIF implosion [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129, 075001 (2022)PRLTAO0031-900710.1103/PhysRevLett.129.075001]. This achievement is the culmination of more than five decades of research and gives proof that laboratory fusion, based on fundamental physics principles, is possible. This Letter reports on the target, laser, design, and experimental advancements that led to this result.

Precisely patterned nanofibres made from extendable protein multiplexes

Molecular systems with coincident cyclic and superhelical symmetry axes have considerable advantages for materials design as they can be readily lengthened or shortened by changing the length of the constituent monomers. Among proteins, alpha-helical coiled coils have such symmetric, extendable architectures, but are limited by the relatively fixed geometry and flexibility of the helical protomers. Here we describe a systematic approach to generating modular and rigid repeat protein oligomers with coincident C2 to C8 and superhelical symmetry axes that can be readily extended by repeat propagation. From these building blocks, we demonstrate that a wide range of unbounded fibres can be systematically designed by introducing hydrophilic surface patches that force staggering of the monomers; the geometry of such fibres can be precisely tuned by varying the number of repeat units in the monomer and the placement of the hydrophilic patches.

Accurate computational design of three-dimensional protein crystals

Protein crystallization plays a central role in structural biology. Despite this, the process of crystallization remains poorly understood and highly empirical, with crystal contacts, lattice packing arrangements and space group preferences being largely unpredictable. Programming protein crystallization through precisely engineered side-chain-side-chain interactions across protein-protein interfaces is an outstanding challenge. Here we develop a general computational approach for designing three-dimensional protein crystals with prespecified lattice architectures at atomic accuracy that hierarchically constrains the overall number of degrees of freedom of the system. We design three pairs of oligomers that can be individually purified, and upon mixing, spontaneously self-assemble into >100 µm three-dimensional crystals. The structures of these crystals are nearly identical to the computational design models, closely corresponding in both overall architecture and the specific protein-protein interactions. The dimensions of the crystal unit cell can be systematically redesigned while retaining the space group symmetry and overall architecture, and the crystals are extremely porous and highly stable. Our approach enables the computational design of protein crystals with high accuracy, and the designed protein crystals, which have both structural and assembly information encoded in their primary sequences, provide a powerful platform for biological materials engineering.

Small-molecule binding and sensing with a designed protein family

Despite transformative advances in protein design with deep learning, the design of small-molecule-binding proteins and sensors for arbitrary ligands remains a grand challenge. Here we combine deep learning and physics-based methods to generate a family of proteins with diverse and designable pocket geometries, which we employ to computationally design binders for six chemically and structurally distinct small-molecule targets. Biophysical characterization of the designed binders revealed nanomolar to low micromolar binding affinities and atomic-level design accuracy. The bound ligands are exposed at one edge of the binding pocket, enabling the de novo design of chemically induced dimerization (CID) systems; we take advantage of this to create a biosensor with nanomolar sensitivity for cortisol. Our approach provides a general method to design proteins that bind and sense small molecules for a wide range of analytical, environmental, and biomedical applications.

De novo design of monomeric helical bundles for pH-controlled membrane lysis

Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0-5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.

Hallucination of closed repeat proteins containing central pockets

In pseudocyclic proteins, such as TIM barrels, β barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.20 ppm

We present a new measurement of the positive muon magnetic anomaly, a_{μ}≡(g_{μ}-2)/2, from the Fermilab Muon g-2 Experiment using data collected in 2019 and 2020. We have analyzed more than 4 times the number of positrons from muon decay than in our previous result from 2018 data. The systematic error is reduced by more than a factor of 2 due to better running conditions, a more stable beam, and improved knowledge of the magnetic field weighted by the muon distribution, ω[over ˜]_{p}^{'}, and of the anomalous precession frequency corrected for beam dynamics effects, ω_{a}. From the ratio ω_{a}/ω[over ˜]_{p}^{'}, together with precisely determined external parameters, we determine a_{μ}=116 592 057(25)×10^{-11} (0.21 ppm). Combining this result with our previous result from the 2018 data, we obtain a_{μ}(FNAL)=116 592 055(24)×10^{-11} (0.20 ppm). The new experimental world average is a_{μ}(exp)=116 592 059(22)×10^{-11} (0.19 ppm), which represents a factor of 2 improvement in precision.

Design of stimulus-responsive two-state hinge proteins

In nature, proteins that switch between two conformations in response to environmental stimuli structurally transduce biochemical information in a manner analogous to how transistors control information flow in computing devices. Designing proteins with two distinct but fully structured conformations is a challenge for protein design as it requires sculpting an energy landscape with two distinct minima. Here we describe the design of "hinge" proteins that populate one designed state in the absence of ligand and a second designed state in the presence of ligand. X-ray crystallography, electron microscopy, double electron-electron resonance spectroscopy, and binding measurements demonstrate that despite the significant structural differences the two states are designed with atomic level accuracy and that the conformational and binding equilibria are closely coupled.

Rapid and automated design of two-component protein nanomaterials using ProteinMPNN

The design of novel protein-protein interfaces using physics-based design methods such as Rosetta requires substantial computational resources and manual refinement by expert structural biologists. A new generation of deep learning methods promises to simplify protein-protein interface design and enable its application to a wide variety of problems by researchers from various scientific disciplines. Here we test the ability of a deep learning method for protein sequence design, ProteinMPNN, to design two-component tetrahedral protein nanomaterials and benchmark its performance against Rosetta. ProteinMPNN had a similar success rate to Rosetta, yielding 13 new experimentally confirmed assemblies, but required orders of magnitude less computation and no manual refinement. The interfaces designed by ProteinMPNN were substantially more polar than those designed by Rosetta, which facilitated in vitro assembly of the designed nanomaterials from independently purified components. Crystal structures of several of the assemblies confirmed the accuracy of the design method at high resolution. Our results showcase the potential of deep learning-based methods to unlock the widespread application of designed protein-protein interfaces and self-assembling protein nanomaterials in biotechnology.

Coordinated Health Care Interventions for Childhood Asthma Gaps in Outcomes (CHICAGO) plan

Background

Evidence-based strategies to improve outcomes in minority children with uncontrolled asthma discharged from the emergency department (ED) are needed.

Objectives

This multicenter pragmatic clinical trial was designed to compare an ED-only intervention (decision support tool), an ED-only intervention and home visits by community health workers for 6 months (ED-plus-home), and enhanced usual care (UC).

Methods

Children aged 5 to 11 years with uncontrolled asthma were enrolled. The change over 6 months in the Patient-Reported Outcomes Measurement Information System Asthma Impact Scale score in children and Satisfaction with Participation in Social Roles score in caregivers were the primary outcomes. The secondary outcomes included guideline-recommended ED discharge care and self-management.

Results

Recruitment was significantly lower than expected (373 vs 640 expected). Of the 373 children (64% Black and 31% Latino children), only 63% completed the 6-month follow-up visit. In multivariable analyses that accounted for missing data, the adjusted odds ratios and 98% CIs for differences in Asthma Impact Scores or caregivers' Satisfaction with Participation in Social Roles scores were not significant. However, guideline-recommended ED discharge care was significantly improved in the intervention groups versus in the UC group, and self-management behaviors were significantly improved in the ED-plus-home group versus in the ED-only and UC groups.

Conclusions

The ED-based interventions did not significantly improve the primary clinical outcomes, although the study was likely underpowered. Although guideline-recommended ED discharge care and self-management did improve, their effect on clinical outcomes needs further study.

De novo designed ice-binding proteins from twist-constrained helices

Attaining molecular-level control over solidification processes is a crucial aspect of materials science. To control ice formation, organisms have evolved bewildering arrays of ice-binding proteins (IBPs), but these have poorly understood structure-activity relationships. We propose that reverse engineering using de novo computational protein design can shed light on structure-activity relationships of IBPs. We hypothesized that the model alpha-helical winter flounder antifreeze protein uses an unusual undertwisting of its alpha-helix to align its putative ice-binding threonine residues in exactly the same direction. We test this hypothesis by designing a series of straight three-helix bundles with an ice-binding helix projecting threonines and two supporting helices constraining the twist of the ice-binding helix. Our findings show that ice-recrystallization inhibition by the designed proteins increases with the degree of designed undertwisting, thus validating our hypothesis, and opening up avenues for the computational design of IBPs.

Developing virtual and augmented reality applications for science, technology, engineering and math education

The Rhode Island IDeA Network of Biomedical Research Excellence Molecular Informatics Core at the University of Rhode Island Information Technology Services Innovative Learning Technologies developed virtual and augmented reality applications to teach concepts in biomedical science, including pharmacology, medicinal chemistry, cell culture and nanotechnology. The apps were developed as full virtual reality/augmented reality and 3D gaming versions, which do not require virtual reality headsets. Development challenges included creating intuitive user interfaces, text-to-voice functionality, visualization of molecules and implementing complex science concepts. In-app quizzes are used to assess the user's understanding of topics, and user feedback was collected for several apps to improve the experience. The apps were positively reviewed by users and are being implemented into the curriculum at the University of Rhode Island.

Improving the secretion of designed protein assemblies through negative design of cryptic transmembrane domains

Computationally designed protein nanoparticles have recently emerged as a promising platform for the development of new vaccines and biologics. For many applications, secretion of designed nanoparticles from eukaryotic cells would be advantageous, but in practice, they often secrete poorly. Here we show that designed hydrophobic interfaces that drive nanoparticle assembly are often predicted to form cryptic transmembrane domains, suggesting that interaction with the membrane insertion machinery could limit efficient secretion. We develop a general computational protocol, the Degreaser, to design away cryptic transmembrane domains without sacrificing protein stability. The retroactive application of the Degreaser to previously designed nanoparticle components and nanoparticles considerably improves secretion, and modular integration of the Degreaser into design pipelines results in new nanoparticles that secrete as robustly as naturally occurring protein assemblies. Both the Degreaser protocol and the nanoparticles we describe may be broadly useful in biotechnological applications.

De novo design of small beta barrel proteins

Small beta barrel proteins are attractive targets for computational design because of their considerable functional diversity despite their very small size (<70 amino acids). However, there are considerable challenges to designing such structures, and there has been little success thus far. Because of the small size, the hydrophobic core stabilizing the fold is necessarily very small, and the conformational strain of barrel closure can oppose folding; also intermolecular aggregation through free beta strand edges can compete with proper monomer folding. Here, we explore the de novo design of small beta barrel topologies using both Rosetta energy-based methods and deep learning approaches to design four small beta barrel folds: Src homology 3 (SH3) and oligonucleotide/oligosaccharide-binding (OB) topologies found in nature and five and six up-and-down-stranded barrels rarely if ever seen in nature. Both approaches yielded successful designs with high thermal stability and experimentally determined structures with less than 2.4 Å rmsd from the designed models. Using deep learning for backbone generation and Rosetta for sequence design yielded higher design success rates and increased structural diversity than Rosetta alone. The ability to design a large and structurally diverse set of small beta barrel proteins greatly increases the protein shape space available for designing binders to protein targets of interest.

Catchment sourcing urban pesticide pollution using constructed wetlands in Melbourne, Australia

A survey of 111 urban constructed stormwater wetlands (median watershed area = 86.8 ha) was conducted to identify the major pesticides present and to determine their major catchment sources (residential, industrial, commercial, sporting ovals) and associations with catchment imperviousness. Melbourne, Australia, has separate stormwater and sewerage systems and these wetlands are designed to treat urban stormwater. To maximise the pesticides that could be detected, three types of passive samplers (POCIS, Chemcatcher® SDB-XC and Chemcatcher® C18) were deployed, along with collection of fine sediments. A total of 231 pesticides were screened using these methods. Pesticides that were detected in >5 % of wetlands were checked to determine their registered use in urban areas using an Australian government database (PubCris). Twenty-five pesticides were detected in >5 % of wetlands: 4 pesticides were associated with non-urban land uses (agriculture and forests), another 4 pesticides had no known registered use in urban areas and 17 were associated with urban areas. The pesticides associated with urban areas were the herbicides simazine, diuron, metolachlor, bromacil, propyzamide and paclobutrazol, the fungicides tebuconazole, propiconazole, metalaxyl, trifloxystrobin, iprodione and carbendazim and the insecticides fipronil, bifenthrin, chlorantraniliprole, thiamethoxam and permethrin. Atrazine was also detected in 59 % of wetlands but has not been registered for urban uses in Australia since 2010. It's presence in Melbourne may be due to legacy issues or aerial transportation from rural areas where it's still widely used in crop cultivation. Generally, the major urban catchment source of pesticides is from residential areas (particularly fipronil and simazine), most likely in wood preservatives, paints and from weed or insect control. Many of these widely used pesticides were correlated with increased catchment imperviousness. Some pesticides (bromacil and imidacloprid) were correlated with commercial premises and chlorantraniliprole was correlated with the presence of sporting ovals in the catchment. No pesticides were specifically correlated with industrial areas. The use of passive samplers and fine sediments, in conjunction with detailed land use mapping of stormwater wetland catchments is very effective and efficient in monitoring and sourcing pesticide contamination in urban environments.

A261 SEVERE ACUTE LIVER INJURY SECONDARY TO WILSON’S DISEASE: A CASE REPORT AND REVIEW OF THE LITERATURE

Background

Wilson’s disease is autosomal recessive and rare (prevalence 1/30000-1/50000) caused by mutations in the ATP7B gene involved in copper excretion. Copper deposition drives hepatic injury, along with neuropsychiatric-ophthalmologic, and hematologic symptoms. Leipzig criteria greater than 4 establishes the diagnosis.

Purpose

We report a case of severe liver injury secondary to probable Wilson’s disease.

Method

Literature review of diagnosis, management including emerging therapies was performed using PubMed.

Result(s)

A 29-year-old otherwise healthy male with no family history of liver disease presented with abdominal pain, jaundice, and severe acute liver injury (ALT 1534 U/L ALP 114 U/L bilirubin 113 umol/L) initially misdiagnosed as hepatitis A in community urgent care. He had worsening liver injury (ALT 1809 U/L bilirubin 411 umol/L), with normal INR and no encephalopathy over an additional 3 weeks and was admitted to our tertiary care centre for further work up. History did not reveal viral prodromes, herbals or natural remedies. CBD oil was the only potential exposure, though longstanding use of the same brand argued against this as a cause. Chronic liver disease workup was negative (viral hepatitides, SARS-CoV-2, alpha-1-antitrypsin, acetaminophen level, iron profile, and comprehensive Mitogen autoantibody panel). Patent vasculature on Doppler US. Liver biopsy showed diffuse lobular inflammation, hepatocyte necrosis, 30% parenchymal involvement, primarily lymphocytes with some eosinophils and plasma cells, and no viral inclusions suggesting acute hepatitis with drugs or viral hepatitis as etiologies. The 24-hour urine copper was elevated at 2.19 umol/d (<0.80). Biopsy copper dry weight 60mcg/g (N<50; >250 diagnostic). Normal ceruloplasmin 0.30g/L and serum copper 25.8 umol/L. MRI brain not suggestive of Wilson’s disease, no Kayser-Fleischer rings on Ophthalmology assessment, and no hemolysis. Given a Leipzig score of 3 suggesting possible Wilson’s disease he was started on penicillamine 1500mg daily. Five weeks later he had serologic (ALT 1061 U/L bilirubin 128 umol/L) improvement, yet elevated elastography at 22kPa IQR 5% likely due to inflammation. Given coverage issues, he was switched to compassionate trientine 500mg BID with further improvement (ALT 347 U/L bilirubin 26 umol/L). Sequencing for ATP7B gene mutations are pending (Blueprint Genetics).

Conclusion(s)

Wilson’s disease should be considered in those with hepatic or neuropsychiatric symptoms, transaminases in the 1000s or acute liver failure. Treatment is lifelong with typically good prognosis and is fatal if untreated. Treatment options include chelators D-penicillamine (first line, with side effects including proteinuria and worsened neurological symptoms) and trientine (fewer side effects). Zinc prevents copper absorption and can be used in asymptomatic patients. Transplant in acute liver failure and end-stage liver disease is guided by the King’s score. Several novel therapies including gene therapy are in development.

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Disclosure of Interest

None Declared

Design of Diverse Asymmetric Pockets in De Novo Homo-oligomeric Proteins

A challenge for design of protein-small-molecule recognition is that incorporation of cavities with size, shape, and composition suitable for specific recognition can considerably destabilize protein monomers. This challenge can be overcome through binding pockets formed at homo-oligomeric interfaces between folded monomers. Interfaces surrounding the central homo-oligomer symmetry axes necessarily have the same symmetry and so may not be well suited to binding asymmetric molecules. To enable general recognition of arbitrary asymmetric substrates and small molecules, we developed an approach to designing asymmetric interfaces at off-axis sites on homo-oligomers, analogous to those found in native homo-oligomeric proteins such as glutamine synthetase. We symmetrically dock curved helical repeat proteins such that they form pockets at the asymmetric interface of the oligomer with sizes ranging from several angstroms, appropriate for binding a single ion, to up to more than 20 Å across. Of the 133 proteins tested, 84 had soluble expression in E. coli, 47 had correct oligomeric states in solution, 35 had small-angle X-ray scattering (SAXS) data largely consistent with design models, and 8 had negative-stain electron microscopy (nsEM) 2D class averages showing the structures coming together as designed. Both an X-ray crystal structure and a cryogenic electron microscopy (cryoEM) structure are close to the computational design models. The nature of these proteins as homo-oligomers allows them to be readily built into higher-order structures such as nanocages, and the asymmetric pockets of these structures open rich possibilities for small-molecule binder design free from the constraints associated with monomer destabilization.

Exploration of Structured Symmetric Cyclic Peptides as Ligands for Metal-Organic Frameworks

Despite remarkable advances in the assembly of highly structured coordination polymers and metal-organic frameworks, the rational design of such materials using more conformationally flexible organic ligands such as peptides remains challenging. In an effort to make the design of such materials fully programmable, we first developed a computational design method for generating metal-mediated 3D frameworks using rigid and symmetric peptide macrocycles with metal-coordinating sidechains. We solved the structures of six crystalline networks involving conformationally constrained 6 to 12 residue cyclic peptides with C2, C3, and S2 internal symmetry and three different types of metals (Zn2+, Co2+, or Cu2+) by single-crystal X-ray diffraction, which reveals how the peptide sequences, backbone symmetries, and metal coordination preferences drive the assembly of the resulting structures. In contrast to smaller ligands, these peptides associate through peptide-peptide interactions without full coordination of the metals, contrary to one of the assumptions underlying our computational design method. The cyclic peptides are the largest peptidic ligands reported to form crystalline coordination polymers with transition metals to date, and while more work is required to develop methods for fully programming their crystal structures, the combination of high chemical diversity with synthetic accessibility makes them attractive building blocks for engineering a broader set of new crystalline materials for use in applications such as sensing, asymmetric catalysis, and chiral separation.

Hallucinating symmetric protein assemblies

Deep learning generative approaches provide an opportunity to broadly explore protein structure space beyond the sequences and structures of natural proteins. Here, we use deep network hallucination to generate a wide range of symmetric protein homo-oligomers given only a specification of the number of protomers and the protomer length. Crystal structures of seven designs are very similar to the computational models (median root mean square deviation: 0.6 angstroms), as are three cryo-electron microscopy structures of giant 10-nanometer rings with up to 1550 residues and C33 symmetry; all differ considerably from previously solved structures. Our results highlight the rich diversity of new protein structures that can be generated using deep learning and pave the way for the design of increasingly complex components for nanomachines and biomaterials.

Robust deep learning-based protein sequence design using ProteinMPNN

Although deep learning has revolutionized protein structure prediction, almost all experimentally characterized de novo protein designs have been generated using physically based approaches such as Rosetta. Here, we describe a deep learning-based protein sequence design method, ProteinMPNN, that has outstanding performance in both in silico and experimental tests. On native protein backbones, ProteinMPNN has a sequence recovery of 52.4% compared with 32.9% for Rosetta. The amino acid sequence at different positions can be coupled between single or multiple chains, enabling application to a wide range of current protein design challenges. We demonstrate the broad utility and high accuracy of ProteinMPNN using x-ray crystallography, cryo-electron microscopy, and functional studies by rescuing previously failed designs, which were made using Rosetta or AlphaFold, of protein monomers, cyclic homo-oligomers, tetrahedral nanoparticles, and target-binding proteins.

Lawson Criterion for Ignition Exceeded in an Inertial Fusion Experiment

For more than half a century, researchers around the world have been engaged in attempts to achieve fusion ignition as a proof of principle of various fusion concepts. Following the Lawson criterion, an ignited plasma is one where the fusion heating power is high enough to overcome all the physical processes that cool the fusion plasma, creating a positive thermodynamic feedback loop with rapidly increasing temperature. In inertially confined fusion, ignition is a state where the fusion plasma can begin "burn propagation" into surrounding cold fuel, enabling the possibility of high energy gain. While "scientific breakeven" (i.e., unity target gain) has not yet been achieved (here target gain is 0.72, 1.37 MJ of fusion for 1.92 MJ of laser energy), this Letter reports the first controlled fusion experiment, using laser indirect drive, on the National Ignition Facility to produce capsule gain (here 5.8) and reach ignition by nine different formulations of the Lawson criterion.

Trapped Alkali-Metal Rydberg Qubit

Rydberg interactions of trapped alkali-metal atoms are used widely to facilitate quantum gate operations in quantum processors and repeaters. In most laboratory realizations using this protocol, the Rydberg states are repelled by the trapping laser fields, requiring that the fields be turned off during gate operations. Here we create a quasi-two-level system in a regime of Rydberg excitation blockade for a mesoscopic Rb ensemble of several hundred atoms confined in a magic-wavelength optical lattice. We observe many-body Rabi oscillations between the ground and collective Rydberg state. In addition we use Ramsey interference techniques to obtain the light shifts of both the lower and upper states of the collective qubit. Whereas the coupling producing the Rabi oscillations is enhanced by a factor of sqrt[N], there is no corresponding enhancement for the light shifts. We derive an effective two-level model which is in good agreement with our observations. Trapped Rydberg qubits and an effective two-level description are expected to have broad applicability for studies of quantum simulation and networking using collective encoding in ensembles of neutral atoms.

Change in self-reported health: A signal for early intervention in a medicare population

BACKGROUND

Health plans and risk-bearing provider organizations seek information sources to inform proactive interventions for patients at risk of adverse health events. Interventions should take into account the strong relationship between social context and health. This retrospective cohort study of a Medicare Advantage population examined whether a change in self-reported health-related quality of life (HRQOL) signals a subsequent change in healthcare needs.

METHODS

A retrospective longitudinal analysis of administrative claims data was conducted for participants in a Medicare Advantage plan with prescription drug coverage (MAPD) who responded to 2 administrations of the Centers for Disease Control and Prevention 4-item Healthy Days survey within 6-18 months during 2015-2018. Changes in HRQOL, as measured by the Healthy Days instrument, were compared with changes in utilization and costs, which were considered to be a reflection of change in healthcare needs.

RESULTS

A total of 48,841 individuals met inclusion criteria. Declining HRQOL was followed by increases in utilization and costs. An adjusted analysis showed that every additional unhealthy day reported one year after baseline was accompanied by an $8 increase in monthly healthcare costs in the subsequent six months for the average patient.

CONCLUSIONS

Declining HRQOL signaled subsequent increases in healthcare needs and utilization.

IMPLICATIONS

Findings suggest that HRQOL assessments in general, and the Healthy Days instrument in particular, could serve as a leading indicator of the need for interventions designed to mitigate poor health outcomes and rising healthcare costs.

LEVEL OF EVIDENCE

III.

Research with Older Asian American Family Caregivers Pre- and During the Pandemic: Challenges and Lessons Learned

Research with hard-to-reach, monolingual adults from ethnic minority communities can present a multitude of challenges throughout the research process. This presentation will highlight challenges and lessons learned from two pilot studies with Vietnamese-, Cambodian-, and Korean-American family caregivers aged 50 and older. The first study (n=9) implemented a one-on-one, telephone-based psychosocial intervention before the COVID-19 pandemic; the second is an ongoing study (n=12) consisting of a group-based intervention via Zoom. Throughout recruitment, the following challenges arose: addressing the lack of familiarity with research among caregivers, earning the trust of caregivers, and identifying creative ways to recruit caregivers to participate. During study implementation, common challenges included: caregivers’ unpredictable daily schedule that made it difficult to participate in the scheduled classes, caregivers feeling apprehensive about technology and Zoom, access to reliable internet, and facilitating participation and engaging the voices of caregivers over the phone or via Zoom. Strategies were identified to address these barriers: engaging the support and collaboration of trusted, bilingual and bicultural community-based providers, building culturally-responsive rapport with caregivers, and seeking continuous feedback from caregivers to improve the appeal of the project implementation. The COVID-19 pandemic added an additional layer of difficulty to the research, requiring creativity and flexibility in implementation that took into consideration caregivers’ heightened anxiety, distress, lack of participation due to around-the-clock care, and loss and grief. The challenges and lessons learned from these studies could guide the development of future research efforts and strategies to effectively engage older hard-to-reach, monolingual Asian American caregivers.

"I Wish I Could Die So I Would Not Be in Pain": A Qualitative Study of Palliative Care Needs Among People With Cancer or HIV/AIDS in Vietnam and Their Caregivers

CONTEXT

Although cancer and HIV/AIDS are common causes of death in Vietnam, limited data exist on their palliative care needs. As palliative care becomes part of Universal Health Coverage, evidence is needed to scale up appropriate care.

OBJECTIVES

To elicit from people with cancer or HIV/AIDS in Vietnam, and their caregivers, the specific multidimensional symptoms and concerns that cause serious health-related suffering.

METHODS

Semistructured, qualitative, in-depth interviews were conducted with stage III or IV cancer patients, people with HIV/AIDS, and their caregivers at three cancer treatment centers and two HIV/AIDS treatment centers in northern, central, and southern Vietnam. Interviews were analyzed using thematic analysis.

RESULTS

Sixty people were interviewed (21 cancer patients, 20 people with HIV/AIDS, 19 caregivers). Pain and other physical symptoms severely impacted their daily lives. Psychological distress-including sadness, depression, worry, and a feeling of having no future-was mentioned frequently, and it was exacerbated by disease progression and by social problems such as financial difficulties and, among people with HIV/AIDS, stigma. Caregivers also suffered physically and psychosocially. Spirituality emerged as a source of strength for patients. Findings highlighted patients' and family caregivers' desire for more information about diagnosis, prognosis, and treatment, a shift toward individual decision-making.

CONCLUSION

The findings demonstrate common, multidimensional, and severe suffering among people living with cancer or HIV/AIDS and their caregivers in Vietnam. These qualitative data should guide development of optimum clinical assessment tools and palliative care services for these populations.

Interpersonal Psychotherapy-Adolescent Skills Training With Youth From Asian American and Immigrant Families: Cultural Considerations and Intervention Process

Although research has identified effective evidence-based depression prevention interventions for diverse youth, little is known about how the intervention process unfolds with immigrant family youth. This study utilized a qualitative approach to explore cultural and clinical differences in the implementation of Interpersonal Psychotherapy-Adolescent Skills Training (IPT-AST) in two schools, one serving youth from primarily immigrant, Asian American families and the second, youth from mostly nonimmigrant, non-Hispanic White families. A total of 131 IPT-AST sessions were audio recorded, transcribed, and coded for presence and patterns of cultural and clinical constructs. Results revealed that sessions with immigrant family youth were more likely to contain discussions of interpersonal problems characterized by estrangement, goals of spending time together with important others, mentions of emotion suppression and academic achievement expectations, conversations about acculturation, differences in value orientation, and discomfort with implementing new intervention skills. Dialogue from interventionist and youth exchanges is presented to illustrate how these themes emerged and were addressed by interventionists in a culturally responsive manner. The study highlights how IPT-AST with immigrant family and Asian American youth may unfold differently compared to youth from nonimmigrant families. Implications of findings for providers are discussed.

Measurement of the Positive Muon Anomalous Magnetic Moment to 0.46 ppm

We present the first results of the Fermilab National Accelerator Laboratory (FNAL) Muon g-2 Experiment for the positive muon magnetic anomaly a_{μ}≡(g_{μ}-2)/2. The anomaly is determined from the precision measurements of two angular frequencies. Intensity variation of high-energy positrons from muon decays directly encodes the difference frequency ω_{a} between the spin-precession and cyclotron frequencies for polarized muons in a magnetic storage ring. The storage ring magnetic field is measured using nuclear magnetic resonance probes calibrated in terms of the equivalent proton spin precession frequency ω[over ˜]_{p}^{'} in a spherical water sample at 34.7 °C. The ratio ω_{a}/ω[over ˜]_{p}^{'}, together with known fundamental constants, determines a_{μ}(FNAL)=116 592 040(54)×10^{-11} (0.46 ppm). The result is 3.3 standard deviations greater than the standard model prediction and is in excellent agreement with the previous Brookhaven National Laboratory (BNL) E821 measurement. After combination with previous measurements of both μ^{+} and μ^{-}, the new experimental average of a_{μ}(Exp)=116 592 061(41)×10^{-11} (0.35 ppm) increases the tension between experiment and theory to 4.2 standard deviations.

Production of renewable oleo-furan surfactants by cross-ketonization of biomass-derived furoic acid and fatty acids

Production of an oleo-furan surfactant precursor from biomass-derived furoic acid and fatty acid via cross-ketonization.

Using longitudinally sampled viral nucleotide sequences to characterize the drivers of HIV-1 transmission

OBJECTIVES

Understanding the drivers of HIV-1 transmission is of importance for curbing the ongoing epidemic. Phylogenetic methods based on single viral sequences allow us to assess whether two individuals are part of the same viral outbreak, but cannot on their own assess who potentially transmitted the virus. We developed and assessed a molecular epidemiology method with the main aim to screen cohort studies for and to characterize individuals who are 'potential HIV-1 transmitters', in order to understand the drivers of HIV-1 transmission.

METHODS

We developed and validated a molecular epidemiology approach using longitudinally sampled viral Sanger sequences to characterize potential HIV-1 transmitters in the Swiss HIV Cohort Study.

RESULTS

Our method was able to identify 279 potential HIV-1 transmitters and allowed us to determine the main epidemiological and virological drivers of transmission. We found that the directionality of transmission was consistent with infection times for 72.9% of 85 potential HIV-1 transmissions with accurate infection date estimates. Being a potential HIV-1 transmitter was associated with risk factors including viral load [adjusted odds ratio_{multivariable} (95% confidence interval): 1.86 (1.49-2.32)], syphilis coinfection [1.52 (1.06-2.19)], and recreational drug use [1.45 (1.06-1.98)]. By contrast for the potential HIV-1 recipients, this association was weaker or even absent [1.18 (0.82-1.72), 0.89 (0.52-1.55) and 1.53 (0.98-2.39), respectively], indicating that inferred directionality of transmission is useful at the population level.

CONCLUSIONS

Our results indicate that longitudinally sampled Sanger sequences do not provide sufficient information to identify transmitters with high certainty at the individual level, but that they allow the drivers of transmission at the population level to be characterized.

Validation of a fuel particle dissolution model with samples from the Red Forest within the Chernobyl exclusion zone

The contamination in the near exclusion zone of the Chernobyl nuclear power plant (ChNPP) with ⁹⁰Sr, ^238-240Pu and ²⁴¹Am is associated with irradiated nuclear fuel particles. Fit for purpose models enabling long term prediction of mobility and bioavailability of particle-associated radionuclides are crucial for radiation protection of humans and the environment, as well as for planning of remediation measures and future land use. In the present work, a dynamic fuel particle dissolution model developed in 1999-2002 is described and validated using data based on sampling in 2015. The model is based on the characterization of the radionuclide source term of the waste in a shallow sub-surface radioactive waste storage, trench #22, in the Chernobyl Pilot Site (CPS) located in the Red Forest, 2.5 km west of the ChNPP, as well as the description of physical and chemical properties of the fuel particles and subsequent radionuclide leaching into the soil solution. Transformation rate constants of the fuel particle dissolution model related to topsoil, radioactive waste trench and submerged materials, and drained cooling pond sediments, should largely control the mobility and bioavailability of radionuclides (e.g., solubility in the soil, migration to groundwater and transfer to plants). The predicting power of the Chernobyl fuel particle dissolution model with respect to radionuclide leaching dynamics was validated using samples from the same experimental site, showing that predicted particle leaching and subsequent mobility and bioavailability were within 46 ± 3% of the observed data. Therefore, linking source- and release-scenario dependent characteristics of radioactive particles to their potential weathering can provide information that can be implemented in impact assessments models for existing contaminated areas as well as for future events.

Quality Improvement Project Demonstrate that Prolonged Pre-Analytical Time Does Not Lead to False Negative Blood Cultures

Introduction/Objective

Bacterial infection is a significant cause of morbidity and mortality. Prompt identification of microorganisms and their susceptibilities to antimicrobial therapies is critical in the management of patients with bloodstream infections. Blood cultures are collected in paired aerobic and anaerobic bottles. However, transport delays might allow some organisms to grow extensively prior to incubation in the blood culture instruments, leading to false-negative culture results. The Detroit Medical Center utilizes the BD Bactec™ instruments for blood culture incubation and the Verigene DNA-based molecular assay for the identification of bacteria and major resistance genes. It has a core microbiology lab that serves 6 hospitals, however, 2 of the hospitals are remotely located.

The aim of this project was to determine if transportation delays led to significant false-negative culture results. If significant false negativity occurred, additional Bactec™ instruments would need to be purchased.

Methods

For one month, we tracked the collection of blood cultures to incubation time at one of the remote hospitals. All blood cultures that remain negative after 164 hours of incubation are routinely discarded. However, in this case, they were subcultured to a Petri plate containing chocolate agar for 30 days. Any organisms that grew were identified by standard lab techniques.

Results

Of the 547 negative culture bottles that were subcultured for possible false-negative results, only 3 (0.5%) bottles grew bacteria. All three were isolated from different patients. The mean time from blood collection to incubation in the instrument was 4-8 hours. The isolates either met criteria for contaminated cultures, or they grew the same pathogen that had previously been identified in the paired bottle from the same culture. The organisms isolated include coagulase negative Staphylococcus species, Staphylococcus pettenkoferi, and Pseudomonas aeruginosa. No unexpected pathogenic organisms were detected.

Conclusion

Our results demonstrate that prolonged pre-analytical time does not lead to false-negative blood culture results. The patients’ diagnoses were not changed, therefore, the purchase of additional blood culture instruments was not necessary. However, transportation time from the patient floors to the main microbiology lab needs to be improved to meet the recommended 2 hours pre-analytical time.