Rapid characterization of adeno-associated virus (AAV) capsid proteins using microchip ZipChip CE-MS.

Adeno-associated viruses (AAVs) are viral vectors used as delivery systems for gene therapies. Intact protein characterization of AAV viral capsid proteins (VPs) and their post-translational modifications is critical to ensuring product quality. In this study, microchip-based ZipChip capillary electrophoresis-mass spectrometry (CE-MS) was applied for the rapid characterization of AAV intact VPs, specifically full and empty viral capsids of serotypes AAV6, AAV8 and AAV9, which was accomplished using 5 min of analysis time. Low levels of dimethyl sulfoxide (4%) in the background electrolyte (BGE) improved MS signal quality and component detection. A sensitivity evaluation revealed consistent detection of VP proteoforms when as little as 2.64 × 106 viral particles (≈26.4 picograms) were injected. Besides the traditional VP proteoforms used for serotype identification, multiple VP3 variants were detected, including truncated VP3 variants most likely generated by leaky scanning as well as unacetylated and un-cleaved VP3 proteoforms. Phosphorylation, known to impact AAV transduction efficiency, was also seen in all serotypes analysed. Additionally, low abundant fragments originating from either N- or C-terminus truncation were detected. As the aforementioned VP components can impact product quality and efficacy, the ZipChip's ability to rapidly characterize them illustrates its strength in monitoring product quality during AAV production.

Development of a Rapid Adeno-Associated Virus (AAV) Identity Testing Platform through Comprehensive Intact Mass Analysis of Full-Length AAV Capsid Proteins.

Adeno-associated viruses (AAVs) are commonly used as vectors for the delivery of gene therapy targets. Characterization of AAV capsid proteins (VPs) and their post-translational modifications (PTMs) have become a critical attribute monitored to evaluate product quality. Liquid chromatography-mass spectrometry (LC-MS) analysis of intact AAV VPs provides both quick and reliable serotype identification as well as proteoform information on each VP. Incorporating these analytical strategies into rapid good manufacturing practice (GMP)-compliant workflows containing robust, but simplified, data processing methods is necessary to ensure effective product quality control (QC) during production. Here, we present a GMP-compliant LC-MS workflow for the rapid identification and in-depth characterization of AAVs. Hydrophilic interaction liquid chromatography (HILIC) MS with difluoroacetic acid as a mobile phase modifier is utilized to achieve the intact separation and identification of AAV VPs and their potential proteoforms. Peptide mapping is performed to confirm PTMs identified during intact VP analysis and for in-depth PTM characterization. The intact separations platform is then incorporated into a data processing workflow developed using GMP-compliant software capable of rapid AAV serotype identification and, if desired, specific serotype PTM monitoring and characterization. Such a platform provides product QC capabilities that are easily accessible in a regulatory setting.

The functional impact of rare variation across the regulatory cascade.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.

SP3-based host cell protein monitoring in AAV-based gene therapy products using LC-MS/MS.

Residual host cell proteins (HCPs) represent a critical quality attribute of biotherapeutic drug products. Workflows enabling reliable HCP detection in monoclonal antibodies and recombinant proteins have been developed, which facilitated process optimization to improve product stability and safety, and allowed setting of acceptance limits for HCP content. However, the detection of HCPs in gene therapy products such as adeno-associated viral (AAV) vectors has been limited. Here, the use of SP3 sample preparation followed by liquid chromatography-mass spectrometry (LC-MS) analysis for HCP profiling in various AAV samples is reported. Suitability of the workflow is demonstrated and provided data constitutes an important reference for future work aiming towards a knowledge-driven improvement of manufacturing conditions and characterization of AAV vector products.

Canonical correlation analysis for multi-omics: Application to cross-cohort analysis.

Integrative approaches that simultaneously model multi-omics data have gained increasing popularity because they provide holistic system biology views of multiple or all components in a biological system of interest. Canonical correlation analysis (CCA) is a correlation-based integrative method designed to extract latent features shared between multiple assays by finding the linear combinations of features-referred to as canonical variables (CVs)-within each assay that achieve maximal across-assay correlation. Although widely acknowledged as a powerful approach for multi-omics data, CCA has not been systematically applied to multi-omics data in large cohort studies, which has only recently become available. Here, we adapted sparse multiple CCA (SMCCA), a widely-used derivative of CCA, to proteomics and methylomics data from the Multi-Ethnic Study of Atherosclerosis (MESA) and Jackson Heart Study (JHS). To tackle challenges encountered when applying SMCCA to MESA and JHS, our adaptations include the incorporation of the Gram-Schmidt (GS) algorithm with SMCCA to improve orthogonality among CVs, and the development of Sparse Supervised Multiple CCA (SSMCCA) to allow supervised integration analysis for more than two assays. Effective application of SMCCA to the two real datasets reveals important findings. Applying our SMCCA-GS to MESA and JHS, we identified strong associations between blood cell counts and protein abundance, suggesting that adjustment of blood cell composition should be considered in protein-based association studies. Importantly, CVs obtained from two independent cohorts also demonstrate transferability across the cohorts. For example, proteomic CVs learned from JHS, when transferred to MESA, explain similar amounts of blood cell count phenotypic variance in MESA, explaining 39.0% ~ 50.0% variation in JHS and 38.9% ~ 49.1% in MESA. Similar transferability was observed for other omics-CV-trait pairs. This suggests that biologically meaningful and cohort-agnostic variation is captured by CVs. We anticipate that applying our SMCCA-GS and SSMCCA on various cohorts would help identify cohort-agnostic biologically meaningful relationships between multi-omics data and phenotypic traits.

An FBN1 deep intronic variant is associated with pseudoexon formation and a variable Marfan phenotype in a five generation family.

Exome sequencing of genes associated with heritable thoracic aortic disease (HTAD) failed to identify a pathogenic variant in a large family with Marfan syndrome (MFS). A genome-wide linkage analysis for thoracic aortic disease identified a peak at 15q21.1, and genome sequencing identified a novel deep intronic FBN1 variant that segregated with thoracic aortic disease in the family (LOD score 2.7) and was predicted to alter splicing. RT-PCR and bulk RNA sequencing of RNA harvested from fibroblasts explanted from the affected proband revealed an insertion of a pseudoexon between exons 13 and 14 of the FBN1 transcript, predicted to lead to nonsense mediated decay (NMD). Treating the fibroblasts with an NMD inhibitor, cycloheximide, greatly improved the detection of the pseudoexon-containing transcript. Family members with the FBN1 variant had later onset aortic events and fewer MFS systemic features than typical for individuals with haploinsufficiency of FBN1. Variable penetrance of the phenotype and negative genetic testing in MFS families should raise the possibility of deep intronic FBN1 variants and the need for additional molecular studies.

Factors affecting adherence to intranasal treatment for allergic rhinitis: A qualitative study.

Objective: To determine the facilitators of and barriers to adherence to use of intranasal pharmacotherapy (daily intranasal corticosteroids and/or antihistamine, and nasal saline irrigation [NSI]), for allergic rhinitis (AR). Methods: Patients were recruited from an academic tertiary care rhinology and allergy clinic. Semi-structured interviews were conducted after the initial visit and/or 4-6 weeks following treatment. Transcribed interviews were analyzed using a grounded theory, inductive approach to elucidate themes regarding patient adherence to AR treatment. Results: A total of 32 patients (12 male, 20 female; age 22-78) participated (seven at initial visit, seven at follow-up visit, and 18 at both). Memory triggers, such as linking nasal routine to existing daily activities or medications, were identified by patients as the most helpful strategy for adherence at initial and follow-up visits. Logistical obstacles related to NSI (messy, takes time, etc.) was the most common concept discussed at follow-up. Patients modified the regimen based on side effects experienced or perceived efficacy. Conclusions: Memory triggers help patients adhere to nasal routines. Logistical obstacles related to NSI can deter from use. Health care providers should address both concepts during patient counseling. Nudge-based interventions that incorporate these concepts may help improve adherence to AR treatment. Level of Evidence: 2.

Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment. METHODS: Blood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples. RESULTS: The discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS). CONCLUSIONS: The identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis.

Molecular examination of the endogenous opioid system in rhesus macaque monkeys with self-injurious behavior.

Self-injurious behavior (SIB) can lead to serious injury and occurs in approximately 1%-4% of the adult population, with higher incidences in adolescent and institutionalized populations, as well as in children with developmental disorders such as Autism. SIB also spontaneously occurs in a low percentage of captive monkeys. Rhesus macaque (Macaca mulatta) monkeys are evolutionarily and physiologically similar to humans, share 93% genetic sequence similarity to humans, and have long been used as testing subjects for vaccine and clinical trials. Previous studies hypothesized that altered endogenous opioid expression occurs in the brains of individuals and animals that self-injure. We examined the regional mRNA expression of opioid signaling genes in sixteen rhesus macaques that exhibited SIB and eight sex- and age- matched controls. The brain regions examined are linked to reward reinforcement and stress adaptation including the hypothalamus, orbital frontal cortex, nucleus accumbens, hippocampus, caudate, and the amygdala. We found decreased µ-opioid receptor (OPRM1) in the amygdala of monkeys with SIB, and reduced prodynorphin (PDYN) in the hypothalamus. Our data suggest dysfunction in the regulation of opioid peptide precursors and calls for further investigation of the endogenous opioid system in SIB.

Analysis of Human Papilloma Virus Content and Integration in Mucoepidermoid Carcinoma.

Mucoepidermoid Carcinomas (MEC) represent the most common malignancies of salivary glands. Approximately 50% of all MEC cases are known to harbor CRTC1/3-MAML2 gene fusions, but the additional molecular drivers remain largely uncharacterized. Here, we sought to resolve controversy around the role of human papillomavirus (HPV) as a potential driver of mucoepidermoid carcinoma. Bioinformatics analysis was performed on 48 MEC transcriptomes. Subsequent targeted capture DNA sequencing was used to annotate HPV content and integration status in the host genome. HPV of any type was only identified in 1/48 (2%) of the MEC transcriptomes analyzed. Importantly, the one HPV16+ tumor expressed high levels of p16, had high expression of HPV16 oncogenes E6 and E7, and displayed a complex integration pattern that included breakpoints into 13 host genes including PIK3AP1, HIPI, OLFM4,SIRT1, ARAP2, TMEM161B-AS1, and EPS15L1 as well as 9 non-genic regions. In this cohort, HPV is a rare driver of MEC but may have a substantial etiologic role in cases that harbor the virus. Genetic mechanisms of host genome integration are similar to those observed in other head and neck cancers.

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits.

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

2-Dimensional ultra-high performance liquid chromatography and DMT-MM derivatization paired with tandem mass spectrometry for comprehensive serum N-glycome characterization.

Glycosylation is a prominent co- and post-translational modification which contributes to a variety of important biological functions. Protein glycosylation characteristics, particularly N-glycosylation, are influenced by changes in one's pathological state, such as through the presence of disease, and as such, there is great interest in N-glycans as potential disease biomarkers. Human serum is an attractive source for N-glycan based biomarker studies as circulatory proteins are representative of one's physiology, with many serum proteins containing N-glycosylation. The difficulty in comprehensively characterizing the serum N-glycome arises from the absence of a biosynthetic template resulting in great structural heterogeneity and complexity. To help overcome these challenges we developed a 2-dimensional liquid chromatography platform which utilizes offline weak anion exchange (WAX) chromatography in the first dimension and hydrophilic interaction liquid chromatography (HILIC) in the second dimension to separate N-glycans by charge, corresponding to degree of sialylation, and size, respectively. Performing these separations offline enables subsequent derivatization with 4-(4,6-Dimethoxy-1,3,5-triazin-2-yl)-4-methylmorpholinium chloride (DMT-MM) for sialic acid linkage determination and the identification of sialic acid linkage isomers. Subsequent tandem mass spectrometry analysis revealed the identification of 212 complete and partial N-glycan structures including low abundant N-glycans containing acetyl and sulphate modifications. The identifications obtained through this platform were then applied to N-glycans released from a set of stage 3 gastric cancer serum samples obtained from patients before (pre-op) and after (post-op) tumour resection to investigate how the serum N-glycome can facilitate differentiation between the two pathological states.

Analyzing the Long Time-Scale Dynamics of Uremic Toxins Bound to Sudlow Site II in Human Serum Albumin.

Protein bound uremic toxins (PBUTs), a series of chemicals that remain a challenge for removal strategies used on patients suffering with chronic kidney disease, could be strong candidates for MD study in order to better understand the interactions and time scales associated with binding mode transitions. Currently, traditional dialysis methods cannot satisfactorily remove PBUTs from the bloodstream. This is at least partly due to these toxin's high level of affinity for protein binding sites, particularly the prominent human serum albumin (HSA) and two of its drug binding sites (Sudlow site I and II). We investigate the dynamics of binding site transitions and interactions by MD simulations targeting four well-known toxins: indoxyl sulfate (IS), p-cresyl sulfate (PCS), indole-3-acetic acid (IAA), and hippurate acid (HIP). Long-time scale dynamics are obtained by the use of time-structure independent component analysis (tICA) for dimensionality reduction followed by spectral analysis of a Markov state model (MSM) scored using the generalized matrix Rayleigh quotient (GMRQ). Our results add new insights to prior findings related to the key role of charge-pairing in governing toxin-protein interactions. We find that IAA, the bulkiest hydrophobic toxin studied, observes the slowest process of at least 3 times slower than the smaller, less hydrophobic toxins. In general, we find that the processes slower than 15 ns are correlated with a transition from dominantly hydrophobic interactions deep in the binding pocket to a gain in hydrogen bonding partners near the mouth of the pocket. Our results indicate that aromatic residues such as PHE play a part in a type of toxin stabilization akin to π-stacking. In conclusion, this work presents mechanistic descriptions of interactions/transitions for a set of important PBUTs that bind Sudlow site II on time scales relevant to the underlying binding kinetics of most interest.

Does the BioBLU 0.3f single-use scale to the BioFlo® 320 reuseable bioreactor on a matched volumetric oxygen mass transfer coefficient?

The volumetric oxygen mass transfer coefficient ([Formula: see text]) is an essential parameter in aerobic high-cell density fermentation where the availability of oxygen to growing microorganisms is a limiting factor. Bioprocess teams looking to scale-up/down between the Eppendorf BioBLU 0.3f single-use vessel and the BioFlo® 320 reusable vessel bioreactors may find it challenging using a matched [Formula: see text]. The maximum [Formula: see text] of the BioFlo® 320 reusable bioreactor was 109 h-1, which was approximately twice that of the BioBLU 0.3f single-use vessel. The results here show no overlap in [Formula: see text] values when both bioreactors were compared and thus conclude that scalability based on [Formula: see text] is not viable. The maximum [Formula: see text] of the Eppendorf BioBLU 0.3f single-use reported here was 47 h-1 compared to that of the manufacturer's value of 2500 h-1, indicating a 53-fold difference. This discrepancy was attributed to the incompatible sulfite addition method used by the manufacturer for estimation.

Endothelial Nitric Oxide Suppresses Action-Potential-Like Transient Spikes and Vasospasm in Small Resistance Arteries.

Endothelial dysfunction in small arteries is a ubiquitous, early feature of cardiovascular disease, including hypertension. Dysfunction reflects reduced bioavailability of endothelium-derived nitric oxide (NO) and depressed endothelium-dependent hyperpolarization that enhances vasoreactivity. We measured smooth muscle membrane potential and tension, smooth muscle calcium, and used real-time quantitative polymerase chain reaction in small arteries and isolated tubes of endothelium to investigate how dysfunction enhances vasoreactivity. Rat nonmyogenic mesenteric resistance arteries developed vasomotion to micromolar phenylephrine (α1-adrenoceptor agonist); symmetrical vasoconstrictor oscillations mediated by L-type voltage-gated Ca2+ channels (VGCCs). Inhibiting NO synthesis abolished vasomotion so nanomolar phenylephrine now stimulated rapid, transient depolarizing spikes in the smooth muscle associated with chaotic vasomotion/vasospasm. Endothelium-dependent hyperpolarization block also enabled phenylephrine-vasospasm but without spikes or chaotic vasomotion. Depolarizing spikes were Ca2+-based and abolished by either T-type or L-type VGCCs blockers with depressed vasoconstriction. Removing NO also enabled transient spikes/vasoconstriction to Bay K-8644 (L-type VGCC activator). However, these were abolished by the L-type VGCC blocker nifedipine but not T-type VGCC block. Phenylephrine also initiated T-type VGCC-transient spikes and enhanced vasoconstriction after NO loss in nonmyogenic arteries from spontaneously hypertensive rats. In contrast to mesenteric arteries, myogenic coronary arteries displayed transient spikes and further vasoconstriction spontaneously on loss of NO. T-type VGCC block abolished these spikes and additional vasoconstriction but not myogenic tone. Therefore, in myogenic and nonmyogenic small arteries, reduced NO bioavailability engages T-type VGCCs, triggering transient depolarizing spikes in normally quiescent vascular smooth muscle to cause vasospasm. T-type block may offer a means to suppress vasospasm without inhibiting myogenic tone mediated by L-type VGCCs.

Elucidating the Molecular Interactions between Uremic Toxins and the Sudlow II Binding Site of Human Serum Albumin.

Protein bound uremic toxins (PBUTs) have been correlated to poor clinical outcomes for patients with chronic kidney disease (CKD) and are not susceptible to the traditional dialysis techniques. Several PBUTs are known to bind strongly with the primary drug carrying sites of human serum albumin (HSA): Sudlow site I and Sudlow site II. A detailed energetic and structural description of PBUT interactions with these binding sites would provide useful insight into the design of materials that specifically displace and capture PBUTs. In this work, we used molecular dynamics (MD) simulations to study in atomistic detail four PBUTs bound in Sudlow site II. Specifically, we used the experimentally resolved X-ray structure of simulated indoxyl sulfate (IS) bound to Sudlow site II (PDB ID: 2BXH) to generate initial binding poses for p-cresyl sulfate (pCS), indole-3-acetic acid (IAA), and hippuric acid (HA). We calculated the interaction energy between toxin and protein in MD simulations and performed mean shift clustering on the collection of molecular structures from MD to identify the primary binding modes of each toxin. We find that all four toxins are primarily stabilized by electrostatic interactions between their anionic moiety and the hydrophilic residues in Sudlow site II. We observed transience in the strongest toxin-protein interaction, a charge-pairing with the positively charged R410 residue. We confirm the finding that the primary binding pose of IS in Sudlow site II is stabilized by a hydrogen bond with the carbonyl oxygen of L430 and find that this is also true for IAA. We provide insight into the chemical functional groups that might be incorporated to improve the specificity of synthetic materials for PBUT capture. This work represents a next step toward the de novo design of solutions to the problem of PBUT management in CKD patients.

Elucidating Molecular Design Principles for Charge-Alternating Peptides.

The therapeutic potential of protein drugs has been hindered by difficulties with long-term stability and rapid clearance from the body. Recombinant fusion proteins provide a scalable platform for engineered biologics, whereby a polypeptide domain is appended to alter the physical characteristics of a therapeutic protein and enhance its pharmaceutical viability. Two simple design principles for recombinant fusion proteins, based on the physical properties of the polypeptide domain, have been separately applied to address issues with the stability and delivery of biologics. "Conformationally disordered" peptides, exemplified by the homo amino acid peptide polyG, have been shown to increase the circulation half-life and bioactivity of protein therapeutics in vivo. Superhydrophilic peptides, exemplified by the alternating-charge peptide poly(EK), have been shown to increase the thermostability of proteins in vitro. The combination of superhydrophilicity and conformational disorder in a single fusion peptide could simultaneously address concerns regarding the stability and therapeutic lifetime of biologics. In the current work, we use enhanced sampling molecular dynamics (MD) simulations to investigate the conformational ensemble of poly(EK) and glycine-substituted poly(EK) variants and validate our structural predictions with circular dichroism (CD). We find the (EK)15 peptide exhibits a high propensity for forming antiparallel ß-strand secondary structures, which are stabilized by extensive salt bridging of the positive and negative side chains. MD simulations predict that limited glycine substitutions effectively disrupt the secondary structure and promote disordered conformations at physiologically relevant temperatures. We conclude that the conformational disorder of alternating-charge peptides should be taken into account to improve their suitability for drug delivery applications. We also contribute a computational approach to quantify conformational disorder in polypeptides, which should facilitate the de novo design of effective fusion proteins.

Machine Learning Diagnosis of Peritonsillar Abscess.

Peritonsillar abscess (PTA) is a difficult diagnosis to make clinically, with clinical examination of even otolaryngologists showing poor sensitivity and specificity. Machine learning is a form of artificial intelligence that "learns" from data to make predictions. We developed a machine learning classifier to predict the diagnosis of PTA based on patient symptoms. We retrospectively collected clinical data and symptomatology from 916 patients who underwent attempted needle aspiration for PTA. Machine learning classifiers were trained on a subset of the data to predict the presence or absence of purulence on attempted aspiration. The performance of the model was evaluated on a holdout set. The accuracy of the top-performing algorithm, the artificial neural network, was 72.3%. Artificial neural networks can use patient symptoms to exceed human ability to predict PTA in patients with clinical suspicion for PTA. Similar models can assist medical decision making for clinicians who have suspicion of PTA.

Trimethylamine N-oxide-derived zwitterionic polymers: A new class of ultralow fouling bioinspired materials.

Materials that resist nonspecific protein adsorption are needed for many applications. However, few are able to achieve ultralow fouling in complex biological milieu. Zwitterionic polymers emerge as a class of highly effective ultralow fouling materials due to their superhydrophilicity, outperforming other hydrophilic materials such as poly(ethylene glycol). Unfortunately, there are only three major classes of zwitterionic materials based on poly(phosphorylcholine), poly(sulfobetaine), and poly(carboxybetaine) currently available. Inspired by trimethylamine N-oxide (TMAO), a zwitterionic osmolyte and the most effective protein stabilizer, we here report TMAO-derived zwitterionic polymers (PTMAO) as a new class of ultralow fouling biomaterials. The nonfouling properties of PTMAO were demonstrated under highly challenging conditions. The mechanism accounting for the extraordinary hydration of PTMAO was elucidated by molecular dynamics simulations. The discovery of PTMAO polymers demonstrates the power of molecular understanding in the design of new biomimetic materials and provides the biomaterials community with another class of nonfouling zwitterionic materials.

The Prevalence of Traumatic Brain Injury and On-Campus Service Utilization Among Undergraduate Students.

OBJECTIVE: (1) To examine the prevalence of college-aged students on campus who had a history of concussion(s) or traumatic brain injury (TBI) and associated symptoms and (2) to evaluate the rate of campus service utilization among students who had a TBI. SETTING: A representative sampling, randomly selected campus-wide e-mail was sent out with a Qualtrics online survey. PARTICIPANTS: College-aged students (N = 466, n = 429) at a northeastern US university responded and consented to participate in the online survey. DESIGN: Descriptive study using an online survey to evaluate the prevalence of TBI and subsequent utility of campus services. MAIN OUTCOME MEASURES: The survey assessed concussion history and the diagnosing clinician, activity in which it occurred, level of consciousness, associated symptoms, and utilization of campus services for academic accommodation. RESULTS: Prevalence of concussion/TBI in the study population (51.7%) is notably higher than previous reporting in adult and college populations (∼10%-25%). Campus disability and accommodative services were underutilized (10%-13%) and were accessed more readily by the female population. In addition, there were reportable increases in symptom prevalence and service utilization with a greater number of previous concussions. CONCLUSIONS: Awareness and utilization of accommodative services, especially with a history of concussions, need to be improved in order to ensure academic and occupational success of students.