Validation of a Combined In Vivo/In Vitro Ileal Fermentation Assay in the Growing Pig to be Used as a Model for Adult Humans.

BACKGROUND: An in vivo/in vitro ileal fermentation assay using growing pigs has been developed but not yet formally validated. OBJECTIVES: This study aimed to validate the in vivo/in vitro ileal fermentation assay by comparing in vitro fermentation values with those obtained in vivo in growing pigs. The effect of raising pigs under different environmental conditions was also investigated. METHODS: Thirty piglets (1.59 ± 0.31 kg body weight, mean ± standard deviation) were subjected to 1 of 3 treatments: artificially reared (AR) (nonfarm, laboratory housing conditions) from postnatal day (PND) 7 (AR group), inoculated orally with human infant fecal extracts from birth until PND 8 and AR (AR+ group), or conventionally reared on a farm (control group). Starting at PND 7, the AR and AR+ pigs received human infant formula for 3 wk, followed by a human-type diet for 5 wk. Control pigs were weaned on the farm and, on PND 63, relocated to the laboratory animal facility. From PND 63, all pigs received a human-type diet. On PND 78, pigs were killed, after which ileal digesta were collected to perform an in vitro ileal fermentation (in vitro organic matter [OM] fermentability and organic acid production) and to determine digesta microbial composition and dietary OM fermentability in vivo. RESULTS: The rearing regimen resulted in only a few differences in ileal microbial taxonomic composition. The rearing regimen generally did not affect the in vitro production of individual organic acids. The in vivo and in vitro OM fermentability of proximal ileal digesta (19.7 ± 2.04%; mean ± SEM) was similar (P > 0.05) for the AR and control pigs but not for the AR+ pigs. CONCLUSIONS: The control-rearing regimen was preferred over AR or AR+ because of ease of implementation. The in vitro ileal fermentation assay accurately predicted the in vivo OM fermentability.

Toward a social psychology of cynicism.

Cynicism is the attitude that people are primarily motivated by self-interest. It tracks numerous negative outcomes, and yet many people are cynical. To understand this 'cynicism paradox', we review and call for more social psychological work on how cynicism spreads, with implications for how we might slow it down.

A Systematic Review of Acute Irreducible Shoulder Dislocations in the 21st Century.

Background: Rarely, closed reduction cannot be achieved in patients with acute shoulder dislocation, necessitating open management. A paucity of literature exists regarding these cases. Purpose: To perform a systematic review on the mechanism, management, and outcome data of acute irreducible shoulder dislocations. Study Design: Systematic review; Level of evidence, 4. Methods: A systematic review of the literature was performed using the Cochrane Database of Systematic Reviews, the Cochrane Central Register of Controlled Trials, PubMed, and MEDLINE between 2000 and 2020. Inclusion criteria were as follows: human participants, acute irreducible shoulder dislocation requiring open management, English language, and publication within the past 20 years. We excluded basic science articles, technique articles, reviews, editorials, and studies of chronic shoulder dislocations or dislocations with ipsilateral humeral shaft fractures. Results: Twelve articles fit the inclusion criteria and were considered for review. All studies were single case reports (level 4 evidence). Ten of the 12 studies were of male patients. The direction of dislocation included 7 anterior/anteroinferior, 2 posterior, 1 inferior, 1 bilateral inferior, and 1 superolateral. Most dislocations were irreducible owing to a mechanical block to reduction. The most common type of block was an incarcerated long head of the biceps tendon, followed by interposition of 1 of the rotator cuff tendons. The axillary and musculocutaneous nerves, displaced fracture fragments, and Hill-Sachs and bony Bankart lesions were other causes of blocks to reduction. Eleven patients were treated with open surgery, while 1 patient was treated arthroscopically. Procedures performed were dependent on concurrent pathology. Final follow-up ranged from 6 weeks to 2 years, with no repeat dislocation episodes reported. Complications after open reduction included 1 case of brachial plexopathy (posterior cord) and 1 case of musculocutaneous nerve palsy. Conclusion: There is a paucity of literature on the management of irreducible acute shoulder dislocations. The most common irreducible dislocation found in this systematic review was anterior with a mechanical block attributed to interposition of the long head of the biceps tendon. When patients were treated with an open or arthroscopic procedure, recurrence was low, with none reporting recurrent dislocation in limited follow-up.

Exploration of fiber-based cation exchange adsorbents for the removal of monoclonal antibody aggregates.

Cation exchange chromatography (CEX) is a widely used technique for the removal of monoclonal antibody (mAb) aggregates. At present, resins are mainly used for this purpose, as convective types of adsorbents such as membrane adsorbers (MAs) have often not demonstrated overall comparable performance for this particular application. Fiber-based adsorbents can overcome the current limitations of MAs with respect to permeability, binding capacity, and adsorbent cost, and could therefore be a viable alternative to resins for the removal of mAb aggregates. It has not been evaluated, however, whether and under which conditions the use of such adsorbents is feasible for this purpose. In the present study, the use of fiber-based CEX adsorbents for mAb aggregate removal was examined. Two types of fiber-based adsorbents, an uncontrolled grafted and a controlled grafted fiber-based adsorbent, were evaluated with respect to permeability, dynamic mAb binding capacity (DBC), resolution capabilities, and the performance in bind and elute (B/E) and frontal chromatography mode with respect to typical performance indicators. The permeabilities of the fiber-based adsorbents ranged from 200 to 1700 mD, making it possible to use the fiber-based adsorbents at larger bed heights than membrane adsorbers with fast mobile phase velocities. Antibody DBCs ranged from 20 to 41 g/L at 150 cm/h, and at higher mobile phase velocities exceeded the DBC of an existing resin material, Poros 50 HS, which has frequently been used for aggregate removal. Both fiber types showed good resolution capabilities of monomer and aggregates, and provided better resolution per column length than Poros 50 HS. Typical purity and yield constraints were fulfilled for both fiber types in both B/E and frontal chromatography mode for mobile phase velocities ranging up to 480 cm/h and 1060 cm/h. The overall performance of the controlled grafted fibers was found to be superior to the performance of uncontrolled grafted fiber-based adsorbents due to higher productivity and lower buffer consumption. The overall performance of the fiber-based adsorbents was found to be comparable to the performance of Poros 50 HS at typical operating conditions. The results in this study indicate that the use of fiber-based adsorbents for mAb aggregate removal is feasible with a performance that is comparable to the performance of an existing resin material. Depending on the cost of the adsorbents and the use scenario, the usage of such adsorbents could be beneficial.

Prevalence of Antibodies to Crimean-Congo Hemorrhagic Fever Virus in Ruminants, Nigeria, 2015.

Crimean-Congo hemorrhagic fever virus (CCHFV) is a highly transmissible human pathogen. Infection is often misdiagnosed, in part because of poor availability of data in disease-endemic areas. We sampled 150 apparently healthy ruminants throughout Nigeria for virus seropositivity and detected virus-specific IgG in cattle (24%) and goats (2%), highlighting the need for further investigations.

PREDICTING SIGNIFICANCE OF UNKNOWN VARIANTS IN GLIAL TUMORS THROUGH SUB-CLASS ENRICHMENT.

Glial tumors have been heavily studied and sequenced, leading to scores of findings about altered genes. This explosion in knowledge has not been matched with clinical success, but efforts to understand the synergies between drivers of glial tumors may alleviate the situation. We present a novel molecular classification system that captures the combinatorial nature of relationships between alterations in these diseases. We use this classification to mine for enrichment of variants of unknown significance, and demonstrate a method for segregating unknown variants with functional importance from passengers and SNPs.

The BioPAX community standard for pathway data sharing.

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships.

BACKGROUND: Discovering that drug entities already approved for one disease are effective treatments for other distinct diseases can be highly beneficial and cost effective. To do this predictively, our conjecture is that a semantic infrastructure linking mechanistic relationships between pharmacologic entities and multidimensional knowledge of biological systems and disease processes will be highly enabling. RESULTS: To develop a knowledge framework capable of modeling and interconnecting drug actions and disease mechanisms across diverse biological systems contexts, we designed a Disease-Drug Correlation Ontology (DDCO), formalized in OWL, that integrates multiple ontologies, controlled vocabularies, and data schemas and interlinks these with diverse datasets extracted from pharmacological and biological domains. Using the complex disease Systemic Lupus Erythematosus (SLE) as an example, a high-dimensional pharmacome-diseasome graph network was generated as RDF XML, and subjected to graph-theoretic proximity and connectivity analytic approaches to rank drugs versus the compendium of SLE-associated genes, pathways, and clinical features. Tamoxifen, a current candidate therapeutic for SLE, was the highest ranked drug. CONCLUSION: This early stage demonstration highlights critical directions to follow that will enable translational pharmacotherapeutic research. The uniform application of Semantic Web methodology to problems in data integration, knowledge representation, and analysis provides an efficient and potentially powerful means to allow mining of drug action and disease mechanism relationships. Further improvements in semantic representation of mechanistic relationships will provide a fertile basis for accelerated drug repositioning, reasoning, and discovery across the spectrum of human disease.

Safety of a live attenuated Erysipelothrix rhusiopathiae vaccine for swine.

Infection with Erysipelothrix rhusiopathiae has a significant economic impact on pig production systems worldwide. Both inactivated and attenuated vaccines are available to prevent development of clinical signs of swine erysipelas. The ability of a live attenuated E. rhusiopathiae strain to become persistently established in pigs after intranasal exposure and its potential to cause clinical signs consistent with swine erysipelas after being administered directly into the nasopharynx of healthy pigs was evaluated. Five, E. rhusiopathiae-negative pigs were vaccinated by deep intranasal inoculation then followed for 14 days. Nasal swabs were collected daily for 5 days and clinical observations were made daily for 14 days post-vaccination. Nasal swabs were cultured for E. rhusiopathiae with the intent of back-passaging any recovered organisms into subsequent replicates. No organism was recovered from nasal swabs in the first vaccination replicate. A second replicate including 10 pigs was initiated and followed in an identical manner to that described above. Again, no E. rhusiopathiae was recovered from any pigs. No pigs in either replicate showed any signs of clinical swine erysipelas. The live attenuated E. rhusiopathiae strain evaluated in this study did not appear to become persistently established in pigs post-vaccination, did not cause any local or systemic signs consistent with swine erysipelas, and was therefore unlikely to revert to a virulent state when used in a field setting.

Effect of blood sample handling post-collection on Erysipelothrix rhusiopathiae antibody titres.

A study was conducted to determine the effect of blood sample mishandling on the performance of an enzyme-linked immunosorbent assay for the detection of antibodies against Erysipelothrix rhusiopathiae. Eleven sample maltreatments (storage at -10 degrees C, storage at 4 degrees C, heat treatment of clotted blood, haemolysis, repetitive freeze-thaw cycling, and substitution of plasma in place of serum) were simulated in a laboratory environment and then run concurrently against a gold standard sample (storage at -80 degrees C). The mishandling treatment groups that simulated high levels of haemolysis had significantly lower optical density (OD) readings when compared to the gold standard. However, the magnitude of the effects was relatively small and only samples with OD values close to the cut-off changed state from positive to negative. Heat treatment had a minor, but non-significant, effect on OD values. Findings from this study suggested that immunoglobulin G antibody was stable in the face of most common sample mishandling events.

Identifying disease-causal genes using Semantic Web-based representation of integrated genomic and phenomic knowledge.

Most common chronic diseases are caused by the interactions of multiple factors including the influences and responses of susceptibility and modifier genes that are themselves subject to etiologic events, interactions, and environmental factors. These entities, interactions, mechanisms, and phenotypic consequences can be richly represented using graph networks with semantically definable nodes and edges. To use this form of knowledge representation for inferring causal relationships, it is critical to leverage pertinent prior knowledge so as to facilitate ranking and probabilistic treatment of candidate etiologic factors. For example, genomic studies using linkage analyses detect quantitative trait loci that encompass a large number of disease candidate genes. Similarly, transcriptomic studies using differential gene expression profiling generate hundreds of potential disease candidate genes that themselves may not include genetically variant genes that are responsible for the expression pattern signature. Hypothesizing that the majority of disease-causal genes are linked to biochemical properties that are shared by other genes known to play functionally important roles and whose mutations produce clinical features similar to the disease under study, we reasoned that an integrative genomics-phenomics approach could expedite disease candidate gene identification and prioritization. To approach the problem of inferring likely causality roles, we generated Semantic Web methods-based network data structures and performed centrality analyses to rank genes according to model-driven semantic relationships. Our results indicate that Semantic Web approaches enable systematic leveraging of implicit relations hitherto embedded among large knowledge bases and can greatly facilitate identification of centrality elements that can lead to specific hypotheses and new insights.

Mining human phenome to investigate modularity of complex disorders.

A principal goal for biomedical research is to improve our understanding of factors that control clinical disease phenotypes. Among genetically-determined diseases, identical mutations may exhibit substantial phenotype variance by individual and background strain, suggesting both environmental and genetic mutant allele interactions. Moreover, different diseases can share phenotypic features extensively. To test the hypothesis that phenotypic similarities and differences among diseases and disease subvariants may represent differential activation of correlated feature "disease phenotype modules", we systematically parsed Online Mendelian Inheritance in Man (OMIM) and Syndrome DB databases using the UMLS to construct a disease - clinical phenotypic feature matrix suitable for various clustering algorithms. Using Cardiovascular Syndromes as a model, our results demonstrate a critical role for representing both phenotypic generalization and specificity relationships for the ability to retrieve non-trivial associations among disease entities such as shared protein domains and pathway and ontology functions of associated causal genes.

Advancing translational research with the Semantic Web.

BACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. RESULTS: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. CONCLUSION: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

Knowledge networks in the age of the Semantic Web.

The Web has become the major medium for various communities to share their knowledge. To this end, it provides an optimal environment for knowledge networks. The web offers global connectivity that is virtually instantaneous, and whose resources and documents can easily be indexed for easy searching. In the coupled realms of biomedical research and healthcare, this has become especially important where today many thousands of communities already exist that connect across academia, hospitals and industry. These communities also rely on several forms of knowledge assets, including publications, experimental data, domain-specific vocabularies and policies. Web-based communities will be one of the earlier beneficiaries of the emerging Semantic Web. With the new standards and technologies of the Semantic Web, effective utilization of knowledge networks will expand profoundly, fostering new levels of innovation and knowledge.

BioDash: a Semantic Web dashboard for drug development.

A researcher's current scientific understanding is assembled from multiple sources of facts and knowledge, along with beliefs and hypotheses of their interpretations. A comprehensive and structured aggregation of all the relevant components is to-date not possible using standard database technologies, nor is it obvious how to include beliefs, such as models and hypotheses into such a bundle. When such information is required as the basis for important decision-making (e.g., in drug discovery), scientists often resort to using commercial presentation applications. This is sub-optimal for the effective use of knowledge, and alternatives that support the inclusion of meaning are urgently needed. This paper describes a prototype Semantic Web application, BioDash, which attempts to aggregate heterogeneous yet related facts and statements (using an RDF model) into an intuitive, visually descriptive and interactive display.

Assessment of the economic impact of porcine reproductive and respiratory syndrome on swine production in the United States.

OBJECTIVE: To estimate the annual cost of infections attributable to porcine reproductive and respiratory syndrome (PRRS) virus to US swine producers. DESIGN: Economic analysis. SAMPLE POPULATION: Data on the health and productivity of PRRS-affected and PRRS-unaffected breeding herds and growing-pig populations were collected from a convenience sample of swine farms in the midwestern United States. PROCEDURE: Health and productivity variables of PRRS-affected and PRRS-unaffected swine farms were analyzed to estimate the impact of PRRS on specific farms. National estimates of PRRS incidence were then used to determine the annual economic impact of PRRS on US swine producers. RESULTS: PRRS affected breeding herds and growing-pig populations as measured by a decrease in reproductive health, an increase in deaths, and reductions in the rate and efficiency of growth. Total annual economic impact of these effects on US swine producers was estimated at dollar 66.75 million in breeding herds and dollar 493.57 million in growing-pig populations. CONCLUSIONS AND CLINICAL RELEVANCE: PRRS imposes a substantial financial burden on US swine producers and causes approximately dollar 560.32 million in losses each year. By comparison, prior to eradication, annual losses attributable to classical swine fever (hog cholera) and pseudorabies were estimated at dollar 364.09 million and dollar 36.27 million, respectively (adjusted on the basis of year 2004 dollars). Current PRRS control strategies are not predictably successful; thus, PRRS-associated losses will continue into the future. Research to improve our understanding of ecologic and epidemiologic characteristics of the PRRS virus and technologic advances (vaccines and diagnostic tests) to prevent clinical effects are warranted.

A life science Semantic Web: are we there yet?

More than ever, life science researchers depend on information from multiple sources. The Semantic Web offers a powerful new strategy for consolidating both text and structured data into a comprehensive collections and views. In addition, these aggregates are readable by both humans and machines and could be the basis of information management and knowledge exchange.

Integrative biological analysis of the APOE*3-leiden transgenic mouse.

Integrative (or systems biology) is a new approach to analyzing biological entities as integrated systems of genetic, genomic, protein, metabolite, cellular, and pathway events that are in flux and interdependent. Here, we demonstrate the application of intregrative biological analysis to a mammalian disease model, the apolipoprotein E3-Leiden (APO*E3) transgenic mouse. Mice selected for the study were fed a normal chow diet and sacrificed at 9 weeks of age-conditions under which they develop only mild type I and II atherosclerotic lesions. Hepatic mRNA expression analysis showed a 25% decrease in APO A1 and a 43% increase in liver fatty acid binding protein expression between transgenic and wild type control mice, while there was no change in PPAR-alpha expression. On-line high performance liquid chromatography-mass spectrometry quantitative profiling of tryptic digests of soluble liver proteins and liver lipids, coupled with principle component analysis, enabled rapid identification of early protein and metabolite markers of disease pathology. These included a 44% increase in L-FABP in transgenic animals compared to controls, as well as an increase in triglycerides and select bioactive lysophosphatidylcholine species. A correlation analysis of identified genes, proteins, and lipids was used to construct an interaction network. Taken together, these results indicate that integrative biology is a powerful tool for rapid identification of early markers and key components of pathophysiologic processes, and constitute the first application of this approach to a mammalian system.