Wade L. Schulz

Reovirus Uses Multiple Endocytic Pathways for Cell Entry

ABSTRACT Entry of reovirus virions has been well studied in several tissue culture systems. After attachment to junctional adhesion molecule A (JAM-A), virions undergo clathrin-mediated endocytosis followed by proteolytic disassembly of the capsid and penetration to the cytoplasm. However, during in vivo infection of the intestinal tract, and likely in the tumor microenvironment, capsid proteolysis (uncoating) is initiated extracellularly. We used multiple approaches to determine if uncoated reovirus particles, called intermediate subviral particles (ISVPs), enter cells by directly penetrating the limiting membrane or if they take advantage of endocytic pathways to establish productive infection. We found that entry and infection by reovirus ISVPs was inhibited by dynasore, an inhibitor of dynamin-dependent endocytosis, as well as by genistein and dominant-negative caveolin-1, which block caveolar endocytosis. Inhibition of caveolar endocytosis also reduced infection by reovirus virions. Extraction of membrane cholesterol with methyl-β-cyclodextrin inhibited infection by virions but had no effect when infection was initiated with ISVPs. We found this pathway to be independent of both clathrin and caveolin. Together, these data suggest that reovirus virions can use both dynamin-dependent and dynamin-independent endocytic pathways during cell entry, and they reveal that reovirus ISVPs can take advantage of caveolar endocytosis to establish productive infection.

HOS2 and HDA1 encode histone deacetylases with opposing roles in Candida albicans morphogenesis.

Epigenetic mechanisms regulate the expression of virulence traits in diverse pathogens, including protozoan and fungi. In the human fungal pathogen Candida albicans, virulence traits such as antifungal resistance, white-opaque switching, and adhesion to lung cells are regulated by histone deacetylases (HDACs). However, the role of HDACs in the regulation of the yeast-hyphal morphogenetic transitions, a critical virulence attribute of C. albicans, remains poorly explored. In this study, we wished to determine the relevance of other HDACs on C. albicans morphogenesis. We generated mutants in the HDACs HOS1, HOS2, RPD31, and HDA1 and determined their ability to filament in response to different environmental stimuli. We found that while HOS1 and RPD31 have no or a more limited role in morphogenesis, the HDACs HOS2 and HDA1 have opposite roles in the regulation of hyphal formation. Our results demonstrate an important role for HDACs on the regulation of yeast-hyphal transitions in the human pathogen C. albicans.

Blockchain Technology: Applications in Health Care.

Blockchain technology has gained substantial attention in recent years with increased interest in several diverse fields, including the healthcare industry. Blockchain offers a secure, distributed database that can operate without a central authority or administrator. Blockchain uses a distributed, peer-to-peer network to make a continuous, growing list of ordered records called blocks to form a digital ledger. Each transaction, represented in a cryptographically signed block, is then automatically validated by the network itself. Blockchain has also garnered interest as a platform to improve the authenticity and transparency of healthcare data through many use cases, from maintaining permissions in electronic health records (EHR) to streamlining claims processing. In this article, we describe the basics of blockchain and illustrate current and future applications of this technology within the healthcare industry. Bitcoin, a cryptocurrency and payment system first introduced in 2008, is one of the most well-known implementations of blockchain.1 The transfer of digital assets, such as bitcoin, within a blockchain is initiated when a seller or payer submits a transaction (Figure [A]).2 These transactions are broadcasted to every peer connected to the blockchain network where clients, called miners, use a cryptographic algorithm to validate the transaction. This validation solves 2 key problems that previously existed with digital currency exchange: ensuring that the digital asset exists and that it has not already been spent. A transaction is said to be valid if a miner deems it is well formed (the input and output contain only the fields that are defined in the protocol), and the outputs it attempts to transfer exist. Miners are not certified and can be anyone who volunteers to invest their resources. The incentive for miners comes in the form of the bitcoin, which are generated and rewarded to the miners for every block of transactions validated. …

Computational Approach to Annotating Variants of Unknown Significance in Clinical Next Generation Sequencing

Next generation sequencing (NGS) has become a common technology in the clinical laboratory, particularly for the analysis of malignant neoplasms. However, most mutations identified by NGS are variants of unknown clinical significance (VOUS). Although the approach to define these variants differs by institution, software algorithms that predict variant effect on protein function may be used. However, these algorithms commonly generate conflicting results, potentially adding uncertainty to interpretation. In this review, we examine several computational tools used to predict whether a variant has clinical significance. In addition to describing the role of these tools in clinical diagnostics, we assess their efficacy in analyzing known pathogenic and benign variants in hematologic malignancies.

Use of application containers and workflows for genomic data analysis

Background: The rapid acquisition of biological data and development of computationally intensive analyses has led to a need for novel approaches to software deployment. In particular, the complexity of common analytic tools for genomics makes them difficult to deploy and decreases the reproducibility of computational experiments. Methods: Recent technologies that allow for application virtualization, such as Docker, allow developers and bioinformaticians to isolate these applications and deploy secure, scalable platforms that have the potential to dramatically increase the efficiency of big data processing. Results: While limitations exist, this study demonstrates a successful implementation of a pipeline with several discrete software applications for the analysis of next-generation sequencing (NGS) data. Conclusions: With this approach, we significantly reduced the amount of time needed to perform clonal analysis from NGS data in acute myeloid leukemia.

Evaluation of relational and NoSQL database architectures to manage genomic annotations

While the adoption of next generation sequencing has rapidly expanded, the informatics infrastructure used to manage the data generated by this technology has not kept pace. Historically, relational databases have provided much of the framework for data storage and retrieval. Newer technologies based on NoSQL architectures may provide significant advantages in storage and query efficiency, thereby reducing the cost of data management. But their relative advantage when applied to biomedical data sets, such as genetic data, has not been characterized. To this end, we compared the storage, indexing, and query efficiency of a common relational database (MySQL), a document-oriented NoSQL database (MongoDB), and a relational database with NoSQL support (PostgreSQL). When used to store genomic annotations from the dbSNP database, we found the NoSQL architectures to outperform traditional, relational models for speed of data storage, indexing, and query retrieval in nearly every operation. These findings strongly support the use of novel database technologies to improve the efficiency of data management within the biological sciences.

A novel network analysis tool to identify relationships between disease states and risks for red blood cell alloimmunization

We hypothesized that diagnoses may be associated with alloantibody ‘responder’ status and examined associations between disease states and alloimmunization. Patients with ≥1 alloantibody and non‐alloimmunized controls were analysed. Pearsons coefficients were calculated to determine associations between alloimmunization and diseases; significant correlations were selected to construct a network. Inflammatory disorders and diseases requiring chronic transfusion support were associated with responder status. Mitigation steps may be considered in patients with these disorders.

Association of Body Mass Index With Blood Pressure Among 1.7 Million Chinese Adults

Importance Body mass index (BMI) is positively associated with blood pressure (BP); this association has critical implications for countries like China, where hypertension is highly prevalent and obesity is increasing. A greater understanding of the association between BMI and BP is required to determine its effect and develop strategies to mitigate it. Objective To assess the heterogeneity in the association between BMI and BP across a wide variety of subgroups of the Chinese population. Design, Setting, and Participants In this cross-sectional study, data were collected at 1 time point from 1.7 million adults (aged 35-80 years) from 141 primary health care sites (53 urban districts and 88 rural counties) from all 31 provinces in mainland China who were enrolled in the China PEACE (Patient-Centered Evaluative Assessment of Cardiac Events) Million Persons Project, conducted between September 15, 2014, and June 20, 2017. A comprehensive subgroup analysis was performed by defining more than 22 000 subgroups of individuals based on covariates, and within each subgroup, linearly regressing BMI to BP. Main Outcomes and Measures Systolic BP was measured twice with the participant in a seated position, using an electronic BP monitor. Results The study included 1 727 411 participants (1 027 711 women and 699 700 men; mean [SD] age, 55.7 [9.8] years). Among the study sample, the mean (SD) BMI was 24.7 (3.5), the mean (SD) systolic BP was 136.5 (20.4) mm Hg, and the mean (SD) diastolic BP was 81.1 (11.2) mm Hg. The increase of BP per unit BMI ranged from 0.8 to 1.7 mm Hg/(kg/m2) for 95% of the subgroups not taking antihypertensive medication. The association between BMI and BP was substantially weaker in subgroups of patients taking antihypertensive medication compared with those who were untreated. In untreated subgroups, 95% of the coefficients varied by less than 1 mm Hg/(kg/m2). Conclusions and Relevance The association between BMI and BP is positive across tens of thousands of individuals in population subgroups, and, if causal, given its magnitude, would have significant implications for public health.

Fulfilling the Promise of Unique Device Identifiers

In 2013, our capacity to understand the real-world safety and effectiveness of medical devices for surveillance and clinical purposes took a major step forward when the U.S. Food and Drug Administration issued the unique device identifier (UDI) final rule (1). This rule states that any medical device (defined as an instrument, apparatusimplant, in vitro reagent, or other similar or related articleintended to affect the structure or any function of the body of man or other animals, and which does not achieve its primary intended purposes through chemical action [2]) must contain a distinct code on its label and packaging. The UDI consists of a device identifier and production identifier (Figure). It can be linked to the Food and Drug Administrations Global Unique Device Identification Database, which contains standard information about brand, model, description, and other relevant characteristics. Unique device identifiers must be applied to implanted devices, such as pacemakers and artificial hips, and most invasive devices, such as robotic surgical instruments. Figure. Unique device identifier example, with inset. * (Reproduced with permission from the Medicare Payment Advisory Commission [6] and Health Industry Business Communications Council.) Unfortunately, nearly 5 years later, the UDI has had limited effect because it is available in neither electronic health records (EHRs) nor administrative claims data. As such, medical devices cannot be easily identified, tracked, or associated with patients, preventing population-level analyses of their safety and effectiveness. A September 2017 report by the Department of Health and Human Services emphasized the consequences of not having the UDI in claims records: Between 2005 and 2014, delays in identifying 7 devices that were recalled or prematurely failed cost Medicare

Amputation neuroma growing intravascularly into a thrombus.

1.5 billion (3). Recent changes to public policy have provided impetus to improve the accessibility and application of UDIs. The 21st Century Cures Act of 2016 requires the Food and Drug Administration to develop policies to collect real-world evidence using postmarket data to inform regulatory decision making (4). Integration of UDIs into EHRs and claims will be essential to support these and other efforts in device surveillance. In addition, meaningful use stage 3 requirements published in 2015 require EHRs to capture UDIs for implantable medical devices. However, obstacles prevent integration of the UDI. Health systems have not made the necessary investments to alter workflows and capture the UDI in EHRs, often leaving the field blank. In addition, to include it in claims, administrative claims forms would need modification that has been proposed in current draft revisions. If these revisions are not implemented, another opportunity may not arise for more than a decade. Medicare would then have to require UDI adoption through regulation (5), and both provider billing systems and claims processing systems would need updates (6). The Centers for Medicare & Medicaid Services (CMS) and health systems could both benefit from integrating the UDI into claims and EHRs. Beyond the advantage of fewer delays in learning of device failures, CMS could save money. Hospitals receive credits from manufacturers for devices that fail under warranty. Although hospitals are required to report these credits to CMS, allowing CMS to reduce payment for revision surgery, they do not often comply. Integration of UDIs into claims data would improve hospital adherence in reporting these credits and therefore decrease CMS spending (6). Further, requiring the UDI in claims would prompt EHR integration because health systems would likely use EHRs to transmit the UDI for payment. Because of the cost and complexity of changing operating and technical systems to include the UDI in claims, CMS had previously expressed concern about such a requirement. The current proposal shortens the claims requirement to include only the device identifier portion of the UDI, meaning that specific models could be identified but production information (such as lots or serial numbers) would not be available. This decreases the utility of the UDI because important information about a faulty devices production may be missing, and obtaining that information may introduce another source of error. A partial implementation that uses only half of the UDI could also lead to delays and challenges in adding the complete UDI in the future. Health systems may benefit from UDI adoption for several reasons. Inventory management systems could be improved, potentially leading to financial savings (7). The UDI can be captured by barcode scanning, which is ubiquitous in health systems and already widely used for many purposes, such as medication administration. Scanning this single barcode is easier than individually capturing several fields, such as manufacturer, product type, and serial number. Supply chain management could then rely on the UDI to monitor inventory, enable automatic reordering, and ensure that devices are used before their shelf life expires. Inventory management systems could be integrated with EHRs, thus making the UDI available for other uses, such as claims submission. Most important, patients will benefit from UDI adoption into both the EHR and claims data. Knowledge of a patients implanted devices or those used previously can improve clinical care, as well as research to evaluate device safety and effectiveness. Similarly, patients would be able to access information about their devices more readily if these data were made available to them; if issues were identified or the device recalled, they could be notified quickly. To fulfill the promise of UDIs, we must surmount resistance within our health systems to altering status quo workflows and building interfaces for different information systems. These efforts will require organizational commitment, mobilization of relevant stakeholders, and a patient-centered view of this informations value in clinical care improvements and product surveillance (7). In the end, to achieve a learning health care system for medical devices, we need the information in the UDI not only to exist but also to be accessible through our EHRs and claims-based information systems.