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To unlock the full promise of messenger (mRNA) therapies, expanding the toolkit of lipid nanoparticles is paramount. However, a pivotal component of lipid nanoparticle development that remains a bottleneck is identifying new ionizable lipids. Here we describe an accelerated approach to discovering effective ionizable lipids for mRNA delivery that combines machine learning with advanced combinatorial chemistry tools. Starting from a simple four-component reaction platform, we create a chemically diverse library of 584 ionizable lipids. We screen the mRNA transfection potencies of lipid nanoparticles containing those lipids and use the data as a foundational dataset for training various machine learning models. We choose the best-performing model to probe an expansive virtual library of 40,000 lipids, synthesizing and experimentally evaluating the top 16 lipids flagged. We identify lipid 119-23, which outperforms established benchmark lipids in transfecting muscle and immune cells in several tissues. This approach facilitates the creation and evaluation of versatile ionizable lipid libraries, advancing the formulation of lipid nanoparticles for precise mRNA delivery. An approach combining machine learning and combinatorial chemistry enables the creation and evaluation of ionizable lipid libraries for lipid nanoparticle formulation to effectively deliver messenger RNA to several cells and tissues.

The expanding applications of nonviral genomic medicines in the lung remain restricted by delivery challenges. Here, leveraging a high-throughput platform, we synthesize and screen a combinatorial library of biodegradable ionizable lipids to build inhalable delivery vehicles for messenger RNA and CRISPR–Cas9 gene editors. Lead lipid nanoparticles are amenable for repeated intratracheal dosing and could achieve efficient gene editing in lung epithelium, providing avenues for gene therapy of congenital lung diseases. A high-throughput screen improves lipid nanoparticle delivery of gene editors in the lung.

Inhaled delivery of mRNA has the potential to treat a wide variety of diseases. However, nebulized mRNA lipid nanoparticles (LNPs) face several unique challenges including stability during nebulization and penetration through both cellular and extracellular barriers. Here we develop a combinatorial approach addressing these barriers. First, we observe that LNP formulations can be stabilized to resist nebulization-induced aggregation by altering the nebulization buffer to increase the LNP charge during nebulization, and by the addition of a branched polymeric excipient. Next, we synthesize a combinatorial library of ionizable, degradable lipids using reductive amination, and evaluate their delivery potential using fully differentiated air–liquid interface cultured primary lung epithelial cells. The final combination of ionizable lipid, charge-stabilized formulation and stability-enhancing excipient yields a significant improvement in lung mRNA delivery over current state-of-the-art LNPs and polymeric nanoparticles. Nebulized mRNA delivery has broad therapeutic potential but has proven challenging. Here, the authors report on a modified lipid nanoparticle with improved conditions to allow nebulization and demonstrate its application for delivering mRNA to the lungs.

The emergency use authorizations (EUAs) of two mRNA-based severe acute respiratory syndrome coronavirus (SARS-CoV)-2 vaccines approximately 11 months after publication of the viral sequence highlights the transformative potential of this nucleic acid technology. Most clinical applications of mRNA to date have focused on vaccines for infectious disease and cancer for which low doses, low protein expression and local delivery can be effective because of the inherent immunostimulatory properties of some mRNA species and formulations. In addition, work on mRNA-encoded protein or cellular immunotherapies has also begun, for which minimal immune stimulation, high protein expression in target cells and tissues, and the need for repeated administration have led to additional manufacturing and formulation challenges for clinical translation. Building on this momentum, the past year has seen clinical progress with second-generation coronavirus disease 2019 (COVID-19) vaccines, Omicron-specific boosters and vaccines against seasonal influenza, Epstein–Barr virus, human immunodeficiency virus (HIV) and cancer. Here we review the clinical progress of mRNA therapy as well as provide an overview and future outlook of the transformative technology behind these mRNA-based drugs. Anderson and colleagues discuss the progress and challenges of using mRNA for vaccines and immunotherapy.

Cellular therapies are poised to transform the field of medicine.These therapies can potentially impact on cancer, regenerative medicine, and immune disorders.Cellular therapies encompass stem or non-stem cells derived from autologous, allogeneic, or xenogeneic sources.A new generation of innovative immunomodulatory interventions may accelerate translation or maximize the prospects of improving therapeutic outcomes of cellular therapies for long-term clinical success. Cellular therapies are poised to transform the field of medicine by restoring dysfunctional tissues and treating various diseases in a dynamic manner not achievable by conventional pharmaceutics. Spanning various therapeutic areas inclusive of cancer, regenerative medicine, and immune disorders, cellular therapies comprise stem or non-stem cells derived from various sources. Despite numerous clinical approvals or trials underway, the host immune response presents a critical impediment to the widespread adoption and success of cellular therapies. Here, we review current research and clinical advances in immunomodulatory strategies to mitigate immune rejection or promote immune tolerance to cellular therapies. We discuss the potential of these immunomodulatory interventions to accelerate translation or maximize the prospects of improving therapeutic outcomes of cellular therapies for clinical success.

Background Exome sequencing (ES) has been successfully applied in clinical detection of single nucleotide variants (SNVs) and small indels. However, identification of copy number variants (CNVs) using ES data remains challenging. The purpose of this study is to understand the contribution of CNVs and copy neutral runs of homozygosity (ROH) in molecular diagnosis of patients referred for ES. Methods In a cohort of 11,020 consecutive ES patients, an Illumina SNP array analysis interrogating mostly coding SNPs was performed as a quality control (QC) measurement and for CNV/ROH detection. Among these patients, clinical chromosomal microarray analysis (CMA) was performed at Baylor Genetics (BG) on 3229 patients, either before, concurrently, or after ES. We retrospectively analyzed the findings from CMA and the QC array. Results The QC array can detect ~ 70% of pathogenic/likely pathogenic CNVs (PCNVs) detectable by CMA. Out of the 11,020 ES cases, the QC array identified PCNVs in 327 patients and uniparental disomy (UPD) disorder-related ROH in 10 patients. The overall PCNV/UPD detection rate was 5.9% in the 3229 ES patients who also had CMA at BG; PCNV/UPD detection rate was higher in concurrent ES and CMA than in ES with prior CMA (7.2% vs 4.6%). The PCNVs/UPD contributed to the molecular diagnoses in 17.4% (189/1089) of molecularly diagnosed ES cases with CMA and were estimated to contribute in 10.6% of all molecularly diagnosed ES cases. Dual diagnoses with both PCNVs and SNVs were detected in 38 patients. PCNVs affecting single recessive disorder genes in a compound heterozygous state with SNVs were detected in 4 patients, and homozygous deletions (mostly exonic deletions) were detected in 17 patients. A higher PCNV detection rate was observed for patients with syndromic phenotypes and/or cardiovascular abnormalities. Conclusions Our clinical genomics study demonstrates that detection of PCNV/UPD through the QC array or CMA increases ES diagnostic rate, provides more precise molecular diagnosis for dominant as well as recessive traits, and enables more complete genetic diagnoses in patients with dual or multiple molecular diagnoses. Concurrent ES and CMA using an array with exonic coverage for disease genes enables most effective detection of both CNVs and SNVs and therefore is recommended especially in time-sensitive clinical situations.

To elicit optimal immune responses, messenger RNA vaccines require intracellular delivery of the mRNA and the careful use of adjuvants. Here we report a multiply adjuvanted mRNA vaccine consisting of lipid nanoparticles encapsulating an mRNA-encoded antigen, optimized for efficient mRNA delivery and for the enhanced activation of innate and adaptive responses. We optimized the vaccine by screening a library of 480 biodegradable ionizable lipids with headgroups adjuvanted with cyclic amines and by adjuvanting the mRNA-encoded antigen by fusing it with a natural adjuvant derived from the C3 complement protein. In mice, intramuscular or intranasal administration of nanoparticles with the lead ionizable lipid and with mRNA encoding for the fusion protein (either the spike protein or the receptor-binding domain of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)) increased the titres of antibodies against SARS-CoV-2 tenfold with respect to the vaccine encoding for the unadjuvanted antigen. Multiply adjuvanted mRNA vaccines may improve the efficacy, safety and ease of administration of mRNA-based immunization. Adjuvanting the lipid and the encapsulated messenger RNA-encoded antigen in lipid-nanoparticle mRNA vaccines can enhance the efficiency of mRNA delivery and the activation of the immune responses, as shown for a COVID-19 vaccine in mice.

The impact of digital device use on health and well-being is a pressing question. However, the scientific literature on this topic, to date, is marred by small and unrepresentative samples, poor measurement of core constructs, and a limited ability to address the psychological and behavioral mechanisms that may underlie the relationships between device use and well-being. Recent authoritative reviews have made urgent calls for future research projects to address these limitations. The critical role of research is to identify which patterns of use are associated with benefits versus risks and who is more vulnerable to harmful versus beneficial outcomes, so that we can pursue evidence-based product design, education, and regulation aimed at maximizing benefits and minimizing the risks of smartphones and other digital devices. The objective of this study is to provide normative data on objective patterns of smartphone use. We aim to (1) identify how patterns of smartphone use impact well-being and identify groups of individuals who show similar patterns of covariation between smartphone use and well-being measures across time; (2) examine sociodemographic and personality or mental health predictors and which patterns of smartphone use and well-being are associated with pre-post changes in mental health and functioning; (3) discover which nondevice behavior patterns mediate the association between device use and well-being; (4) identify and explore recruitment strategies to increase and improve the representation of traditionally underrepresented populations; and (5) provide a real-world baseline of observed stress, mood, insomnia, physical activity, and sleep across a representative population. This is a prospective, nonrandomized study to investigate the patterns and relationships among digital device use, sensor-based measures (including both behavioral and physiological signals), and self-reported measures of mental health and well-being. The study duration is 4 weeks per participant and includes passive sensing based on smartphone sensors, and optionally a wearable (Fitbit), for the complete study period. The smartphone device will provide activity, location, phone unlocks and app usage, and battery status information. At the time of submission, the study infrastructure and app have been designed and built, the institutional review board of the University of Oregon has approved the study protocol, and data collection is underway. Data from 4182 enrolled and consented participants have been collected as of March 27, 2023. We have made many efforts to sample a study population that matches the general population, and the demographic breakdown we have been able to achieve, to date, is not a perfect match. The impact of digital devices on mental health and well-being raises important questions. The Digital Well-Being Study is designed to help answer questions about the association between patterns of smartphone use and well-being. DERR1-10.2196/49189.

There is an urgent need for affinity reagents that target phospho-modified sites on individual proteins; however, generating such reagents remains a significant challenge. Here, we describe a genetic selection strategy for routine laboratory isolation of phospho-specific designed ankyrin repeat proteins (DARPins) by linking in vivo affinity capture of a phosphorylated target protein with antibiotic resistance of Escherichia coli cells. The assay is validated using an existing panel of DARPins that selectively bind the nonphosphorylated (inactive) form of extracellular signal-regulated kinase 2 (ERK2) or its doubly phosphorylated (active) form (pERK2). We then use the selection to affinity-mature a phospho-specific DARPin without compromising its selectivity for pERK2 over ERK2 and to reprogram the substrate specificity of the same DARPin towards non-cognate ERK2. Collectively, these results establish our genetic selection as a useful and potentially generalizable protein engineering tool for studying phospho-specific binding proteins and customizing their affinity and selectivity. Protein phosphorylation helps to control many important cellular activities. Here the authors describe a genetic selection strategy to isolate designed ankyrin repeat proteins that bind specifically to phosphomodified targets.