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The thermal distillation of crude oil mixtures is an energy-intensive process, accounting for nearly 1% of global energy consumption. Membrane-based separations are an appealing alternative or tandem process to distillation due to intrinsic energy efficiency advantages. We developed a family of spirocyclic polytriazoles from structurally diverse monomers for membrane applications. The resulting polymers were prepared by a convenient step-growth method using copper-catalysed azide–alkyne cycloaddition, providing very fast reaction rates, high molecular weights and solubilities in common organic solvents and non-interconnected microporosity. Fractionation of whole Arabian light crude oil and atmospheric tower bottom feeds using these materials enriched the low-boiling-point components and removed trace heteroatom and metal impurities (comparable performance with the lighter feed as the commercial polyimide, Matrimid), demonstrating opportunities to reduce the energy cost of crude oil distillation with tandem membrane processes. Membrane-based molecular separation under these demanding conditions is made possible by high thermal stability and a moderate level of dynamic chain mobility, leading to transient interconnections between micropores, as revealed by the calculations of static and swollen pore structures.Thermal fractionation of petroleum consumes large amounts of energy. Here stable microporous polymers are synthesized using click chemistry, which have similar performance to commercial polyimides for the fractionation of light crude oils and successful application to heavy feeds under realistic conditions.

Cas13a has been used to target RNA viruses in cell culture, but efficacy has not been demonstrated in animal models. In this study, we used messenger RNA (mRNA)-encoded Cas13a for mitigating influenza virus A and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mice and hamsters, respectively. We designed CRISPR RNAs (crRNAs) specific for PB1 and highly conserved regions of PB2 of influenza virus, and against the replicase and nucleocapsid genes of SARS-CoV-2, and selected the crRNAs that reduced viral RNA levels most efficiently in cell culture. We delivered polymer-formulated Cas13a mRNA and the validated guides to the respiratory tract using a nebulizer. In mice, Cas13a degraded influenza RNA in lung tissue efficiently when delivered after infection, whereas in hamsters, Cas13a delivery reduced SARS-CoV-2 replication and reduced symptoms. Our findings suggest that Cas13a-mediated targeting of pathogenic viruses can mitigate respiratory infections. Cas13a delivered to the lung of mice and hamsters inhibits replication of influenza virus and SARS-CoV-2.

Messenger RNA has now been used to vaccinate millions of people. However, the diversity of pulmonary pathologies, including infections, genetic disorders, asthma and others, reveals the lung as an important organ to directly target for future RNA therapeutics and preventatives. Here we report the screening of 166 polymeric nanoparticle formulations for functional delivery to the lungs, obtained from a combinatorial synthesis approach combined with a low-dead-volume nose-only inhalation system for mice. We identify P76, a poly-β-amino-thio-ester polymer, that exhibits increased expression over formulations lacking the thiol component, delivery to different animal species with varying RNA cargos and low toxicity. P76 allows for dose sparing when delivering an mRNA-expressed Cas13a-mediated treatment in a SARS-CoV-2 challenge model, resulting in similar efficacy to a 20-fold higher dose of a neutralizing antibody. Overall, the combinatorial synthesis approach allowed for the discovery of promising polymeric formulations for future RNA pharmaceutical development for the lungs.Screening of hundreds of nanoparticle polymers identifies an effective and low-toxicity formulation for the functional delivery of RNA to the lungs of distinct animal species.

Bioorthogonal chemistry represents a class of high-yielding chemical reactions that proceed rapidly and selectively in biological environments without side reactions towards endogenous functional groups. Rooted in the principles of physical organic chemistry, bioorthogonal reactions are intrinsically selective transformations not commonly found in biology. Key reactions include native chemical ligation and the Staudinger ligation, copper-catalysed azide–alkyne cycloaddition, strain-promoted [3 + 2] reactions, tetrazine ligation, metal-catalysed coupling reactions, oxime and hydrazone ligations as well as photoinducible bioorthogonal reactions. Bioorthogonal chemistry has significant overlap with the broader field of ‘click chemistry’ — high-yielding reactions that are wide in scope and simple to perform, as recently exemplified by sulfuryl fluoride exchange chemistry. The underlying mechanisms of these transformations and their optimal conditions are described in this Primer, followed by discussion of how bioorthogonal chemistry has become essential to the fields of biomedical imaging, medicinal chemistry, protein synthesis, polymer science, materials science and surface science. The applications of bioorthogonal chemistry are diverse and include genetic code expansion and metabolic engineering, drug target identification, antibody–drug conjugation and drug delivery. This Primer describes standards for reproducibility and data deposition, outlines how current limitations are driving new research directions and discusses new opportunities for applying bioorthogonal chemistry to emerging problems in biology and biomedicine.The underlying mechanisms and optimal conditions that drive biorthogonal reactions and the utility of these for applications in medicinal chemistry and protein synthesis to polymers and materials science are described in this Primer. Current reproducibility standards and how current reaction limitations are driving new research efforts are also discussed.

Membrane-based organic solvent separations are rapidly emerging as a promising class of technologies for enhancing the energy efficiency of existing separation and purification systems. Polymeric membranes have shown promise in the fractionation or splitting of complex mixtures of organic molecules such as crude oil. Determining the separation performance of a polymer membrane when challenged with a complex mixture has thus far occurred in an ad hoc manner, and methods to predict the performance based on mixture composition and polymer chemistry are unavailable. Here, we combine physics-informed machine learning algorithms (ML) and mass transport simulations to create an integrated predictive model for the separation of complex mixtures containing up to 400 components via any arbitrary linear polymer membrane. We experimentally demonstrate the effectiveness of the model by predicting the separation of two crude oils within 6-7% of the measurements. Integration of ML predictors of diffusion and sorption properties of molecules with transport simulators enables for the rapid screening of polymer membranes prior to physical experimentation for the separation of complex liquid mixtures. Membranes can be used for energy efficient organic liquid mixture separations. Here the authors use machine learning and transport simulations to predict the separation of complex mixtures such as crude oils by any linear polymer membrane.

Polymers of intrinsic microporosity (PIMs) have been used as precursors for the fabrication of porous carbon molecular sieve (CMS) membranes. PIM-1, a prototypical PIM material, uses a fused-ring structure to increase chain rigidity between spirobisindane repeat units. These two factors inhibit effective chain packing, thus resulting in high free volume within the membrane. However, a decrease of pore size and porosity was observed after pyrolytic conversion of PIM-1 to CMS membranes, attributed to the destruction of the spirocenter, which results in the “flattening” of the polymer backbone and graphite-like stacking of carbonaceous strands. Here, a spirobifluorene-based polymer of intrinsic microporosity (PIM-SBF) was synthesized and used to fabricate CMS membranes that showed significant increases in p-xylene permeability (approximately four times), with little loss in p-xylene/o-xylene selectivity (13.4 versus 14.7) for equimolar xylene vapor separations when compared to PIM-1–derived CMS membranes. This work suggests that it is feasible to fabricate such highly microporous CMS membranes with performances that exceed current state-of-the-art zeolites at high xylene loadings.

RNA interference (RNAi) holds unique potential as a clinically viable modality to pharmacologically regulate oncogenes in sequence-specific manner. However, systemic delivery of RNAi to tumors encounters myriad obstructions, and strategies to overcome such barriers have largely consisted of academic demonstrations with few approaches reaching patients. Here we report the development of a self-agglomerating nanohydrogel (SANGs) platform that selectively localizes to tumor tissue, is efficiently internalized by cancer cells, is agnostic to RNAi payload, and achieves functional suppression of multiple oncogene targets. After intravenous injection, SANGs preferentially accumulate and are retained in primary and metastatic loci in four aggressive cancer models in rodents. SANGs deliver multiple RNAi payloads that significantly suppress oncogene expression and sensitize previously resistant tumors while being safe and well tolerated in simulated clinical applications across three species. We propose, and provide the first direct evidence in support of, a mechanism featuring emergent material properties by which SANGs achieve durable solid-tumor delivery without attachment of cell- or tumor-targeting ligands. Overall, the SANGs platform is an enabling technology for RNAi-based cancer therapeutics and is poised for advanced pharmaceutical development with multiple solid-tumor indications. RNAi therapy has huge potential but effective delivery to target location is a major issue. Here, the authors report on the delivery of RNAi to tumors using self-agglomerating nanohydrogels that can overcome the different delivery barriers and supply multiple RNAi payloads.

Current cartilage tissue engineering strategies cannot as yet fabricate new tissue that is indistinguishable from native cartilage with respect to zonal organization, extracellular matrix composition, and mechanical properties. Integration of implants with surrounding native tissues is crucial for long-term stability and enhanced functionality. In this study, we developed a bioprinting system with simultaneous photopolymerization capable for three-dimensional (3D) cartilage tissue engineering. Poly(ethylene glycol) dimethacrylate (PEGDMA) with human chondrocytes were printed to repair defects in osteochondral plugs (3D biopaper) in layer-by-layer assembly. Compressive modulus of printed PEGDMA was 395.73±80.40 kPa, which was close to the range of the properties of native human articular cartilage. Printed human chondrocytes maintained the initially deposited positions due to simultaneous photopolymerization of surrounded biomaterial scaffold, which is ideal in precise cell distribution for anatomic cartilage engineering. Viability of printed human chondrocytes increased 26% in simultaneous polymerization than polymerized after printing. Printed cartilage implant attached firmly with surrounding tissue and greater proteoglycan deposition was observed at the interface of implant and native cartilage in Safranin-O staining. This is consistent with the enhanced interface failure strength during the culture assessed by push-out testing. Printed cartilage in 3D biopaper had elevated glycosaminoglycan (GAG) content comparing to that without biopaper when normalized to DNA. These observations were consistent with gene expression results. This study indicates the importance of direct cartilage repair and promising anatomic cartilage engineering using 3D bioprinting technology.

SARS-CoV-2 emerged in late 2019 and has since spread around the world, causing a pandemic of the respiratory disease COVID-19. Detecting antibodies against the virus is an essential tool for tracking infections and developing vaccines. Such tests, primarily utilizing the enzyme-linked immunosorbent assay (ELISA) principle, can be either qualitative (reporting positive/negative results) or quantitative (reporting a value representing the quantity of specific antibodies). Quantitation is vital for determining stability or decline of antibody titers in convalescence, efficacy of different vaccination regimens, and detection of asymptomatic infections. Quantitation typically requires two-step ELISA testing, in which samples are first screened in a qualitative assay and positive samples are subsequently analyzed as a dilution series. To overcome the throughput limitations of this approach, we developed a simpler and faster system that is highly automatable and achieves quantitation in a single-dilution screening format with sensitivity and specificity comparable to those of ELISA.

N-glycosylation plays an important role in the structure and function of membrane and secreted proteins. The spike protein on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, is heavily glycosylated and the major target for developing vaccines, therapeutic drugs and diagnostic tests. The first major SARS-CoV-2 variant carries a D614G substitution in the spike (S-D614G) that has been associated with altered conformation, enhanced ACE2 binding, and increased infectivity and transmission. In this report, we used mass spectrometry techniques to characterize and compare the N-glycosylation of the wild type (S-614D) or variant (S-614G) SARS-CoV-2 spike glycoproteins prepared under identical conditions. The data showed that half of the N-glycosylation sequons changed their distribution of glycans in the S-614G variant. The S-614G variant showed a decrease in the relative abundance of complex-type glycans (up to 45%) and an increase in oligomannose glycans (up to 33%) on all altered sequons. These changes led to a reduction in the overall complexity of the total N-glycosylation profile. All the glycosylation sites with altered patterns were in the spike head while the glycosylation of three sites in the stalk remained unchanged between S-614G and S-614D proteins.