Influence of forage inclusion in the diet on ileal and total tract digestibility

The present investigation aimed to study the ileal and total tract digestibility of 3 forages (clover-grass, clover-grass silage, and field pea (Pisum sativum)-barley (Hordeum vulgare) silage) supplemented to a basal diet. A total of 24 pigs, adapted to eating forages by supplementing a basal feed with clover-grass silage from weaning, were fitted with a T-cannula at the terminal ileum at approximate 30 kg BW. For each of the 3 types of forage, 2 balance trials with a 4 wk interval were carried out. Two pigs in each test were fed the basal diet and 6 others were fed the basal diet plus forage throughout the whole experiment. The intake of forages was low and quite variable and on average accounted for only 10 to 12% of the DMI. Ileal digestibility of protein estimated by collection from the T-cannula was higher (P = 0.031) than the digestibility estimated by the slaughter technique indicating some separation of the digesta collected from the T-cannula. The forages had, as expected, a lower total tract DM and energy digestibility than the basal diet (P < 0.05). The fresh clover-grass had a higher energy digestibility than the 2 silages (60 vs. 48%; P < 0.05). Inclusion of 10% of GE in the diet as forage reduced (P < 0.05) the energy digestibility of the ration by 2.2% for clover-grass, 3.4% for clover-grass silage, and 5.0% for pea-barley silage. In organic slaughter pig production, the overall energy supply from these forages is limited, but they may play an important role in satiety and rooting behavior.

A translational platform for prototyping closed-loop neuromodulation systems

While modulating neural activity through stimulation is an effective treatment for neurological diseases such as Parkinson's disease and essential tremor, an opportunity for improving neuromodulation therapy remains in automatically adjusting therapy to continuously optimize patient outcomes. Practical issues associated with achieving this include the paucity of human data related to disease states, poorly validated estimators of patient state, and unknown dynamic mappings of optimal stimulation parameters based on estimated states. To overcome these challenges, we present an investigational platform including: an implanted sensing and stimulation device to collect data and run automated closed-loop algorithms; an external tool to prototype classifier and control-policy algorithms; and real-time telemetry to update the implanted device firmware and monitor its state. The prototyping system was demonstrated in a chronic large animal model studying hippocampal dynamics. We used the platform to find biomarkers of the observed states and transfer functions of different stimulation amplitudes. Data showed that moderate levels of stimulation suppress hippocampal beta activity, while high levels of stimulation produce seizure-like after-discharge activity. The biomarker and transfer function observations were mapped into classifier and control-policy algorithms, which were downloaded to the implanted device to continuously titrate stimulation amplitude for the desired network effect. The platform is designed to be a flexible prototyping tool and could be used to develop improved mechanistic models and automated closed-loop systems for a variety of neurological disorders.

Translating standards into practice: experience and lessons learned at the Department of Veterans Affairs

The increased need for interoperable electronic health records in health care organizations underscores the importance of standards. The US Department of Veterans Affairs (VA) has a long history of developing and adopting various types of health care data standards. The authors present in detail their experience in this domain. A formal organization within VA is responsible for helping to develop and implement standards. This group has produced a Standards Life Cycle (SLC) process endorsed by VA key business and information technology (IT) stakeholders. It coordinates the identification, description, and implementation of standards aligned with VA business requirements. In this paper, we review the adoption of four standards in the categories of security and privacy, terminology, health information exchange, and modeling tools; emphasizing the implementation approach used in each. In our experience, adoption is facilitated by internal staff with expertise in standards development and adoption. Use of processes such as an SLC and tools such as an enterprise requirement repository help formally track and ensure that IT development and acquisition incorporate these standards. An organization should adopt standards that are aligned with its business priorities and favor those that are more readily implementable. To assist with this final point, we offer a standard "Likelihood of Adoption Scale," which changes as standards specifications evolve from PDF documents only, to PDF documents with construction and testing tools, to fully functional reference implementations.

Combined SPECT and Multidetector CT for Prostate Cancer Evaluations

(111)In-capromab pendetide is an imaging probe for noninvasive detection of prostate cancer dissemination, and can be difficult to interpret because of low photon statistics resulting in noisy images with limited anatomical precision. We examined if a 16-slice multidetector computed tomography (MDCT) combined with single photon emission computed tomography (SPECT) could increase the impact on the clinical management and improve confidence in SPECT image interpretations in comparison to a relatively low-mA (limited resolution) CT. 17 scans were reviewed from a SPECT combined with low-mA CT scanner; 21 scans were reviewed from a SPECT combined with 16-slice MDCT scanner. Reports of the clinical interpretations from the imaging studies, additional examinations performed by referring physicians as a follow-up to the imaging results, and long-term clinical and laboratory follow-ups were used to define confidence of the SPECT/CT readings and impact of the readings on the patient management. The impact was defined as: the occurrence of the (111)In-capromab pendetide interpretation resulted in additional imaging studies or biopsies. MDCT improved the quality and confidence in the characterization of small lymph nodes with or without uptake of (111)In-capromab pendetide. The increased confidence with MDCT in SPECT/CT readings was evident in all cases reviewed in this study, and the impact on the clinical management was higher (8 out of 21) using SPECT/MDCT than the impact using SPECT combined with low-mA CT (2 out of 17). The dual-modality SPECT/CT provides a quantifiable benefit when MDCT is used instead of low-mA CT, particularly for prostate cancer evaluations using (111)In-capromab pendetide.

A conceptual framework for managing very diverse data for complex, interdisciplinary science

Much attention has been given to the challenges of handling massive data volumes in modern data-intensive science. This paper examines an equally daunting challenge – the diversity of interdisciplinary data, notably research data, and the need to interrelate these data to understand complex systemic problems such as environmental change and its impact. We use the experience of the International Polar Year 2007–8 (IPY) as a case study to examine data management approaches seeking to address issues around complex interdisciplinary science. We find that, while technology is a critical factor in addressing the interdisciplinary dimension of the data intensive science, the technologies developing for exa-scale data volumes differ from those that are needed for extremely distributed and heterogeneous data. Research data will continue to be highly heterogeneous and distributed and will require technologies to be much simpler and more flexible. More importantly, there is a need for both technical and cultural adaptation. We describe a vision of discoverable, open, linked, useful, and safe collections of data, organized and curated using the best principles and practices of information and library science. This vision provides a framework for our discussion and leads us to suggest several short- and long-term strategies to facilitate a socio-technical evolution in the overall science data ecosystem.

Technological Development for Commercialization of Amorphous Silicon Based Multijunction Modules

Some of the significant steps in technological development for large-scale commercialization of amorphous silicon (a-Si:H) based multijunction photovoltaic modules are presented. These developments are establishing a high quality baseline process for manufacturing large-area ( ˜ 8 ft2) a-Si:H/a-SiGe:H tandem junction modules with improved stabilized conversion efficiency, throughput, yield, and reduced materials usage.

Efficiency Limitations of Multicrystalline Silicon Solar Cells Due to Defect Clusters

Multicrystalline Si wafers used in commercial solar cell fabrication exhibit a tendency to form large “clusters” of defects, which remain laterally separated from each other. Defect clusters are also sites of impurity precipitation. Because precipitated impurities cannot be gettered by the conventional processes used in Si solar cell fabrication, defect clusters constitute low-performing regions in the cell. They shunt the device and constitute the primary efficiency limiting mechanism in current solar cells. We show that the efficiency loss caused by defect clusters can exceed 3–4 absolute points.

Detection of viruses via statistical gene expression analysis

We develop a new bayesian construction of the elastic net (ENet), with variational bayesian analysis. This modeling framework is motivated by analysis of gene expression data for viruses, with a focus on H3N2 and H1N1 influenza, as well as Rhino virus and RSV (respiratory syncytial virus). Our objective is to understand the biological pathways responsible for the host response to such viruses, with the ultimate objective of developing a clinical test to distinguish subjects infected by such viruses from subjects with other symptom causes (e.g., bacteria). In addition to analyzing these new datasets, we provide a detailed analysis of the bayesian ENet and compare it to related models.

The European and American use of exploratory approaches for first-in-human studies

Exploratory approaches for first-in-human clinical studies have evolved over the last few years and have stimulated the issuance of national regulatory guidances in some European countries as well as the United States. With the increasing implementation of these approaches and the recent preparation of a multiregional regulatory guidance (ICH M3 rev2), an exchange of experiences on the opportunities and challenges of exploratory clinical trials was desirable; thus, a workshop focusing on the use of this clinical approach was planned and conducted in Lisbon, Portugal, March 18-19, 2009 sponsored by the Portuguese Health Authority (INFARMED) and DIA. The structure of the workshop focused in three main areas. Regulatory representatives from Portugal, Belgium, Germany, the United Kingdom and the United States formally reviewed their experiences. This was followed by a discussion on issues from an ethics review perspective as well as an insight to the opportunities in the area of biologics. The industry perspective was presented by representatives from Merck, Pfizer, J&J, Novartis, Speedel, AstraZeneca, GSK, and Roche. Finally, through break out sessions, issues were identified to be addressed moving forward. It is the purpose of this paper to report on the outcome of this workshop.

A model-driven approach for biomedical data integration

A core challenge in biomedical data integration is to enable semantic interoperability between its various stakeholders as well as other interested parties. Promoting the adoption of worldwide accepted information standards along with common controlled terminologies is the right path to achieve this. Our paper describes a solution to this fundamental problem by proposing an approach to semantic data integration based on information models serving as a common language to represent health data coupled with technology that is able to represent the data semantics. We used the HL7 v3 Reference Information Model (RIM) [1] to derive a specific data model for the integrated data, the Web Ontology Language (OWL) [2] to build an ontology that harmonizes the metadata from the disparate data sources, the Unified Modeling Language (UML) [3] to model the data representation, and the Object Constraint Language (OCL) [4] to specify UML model constraints. To illustrate the approach, we use the Essential Hypertension Summary CDA document and related models from Hypergenes, a European Commission funded project [5] exploring the Essential Hypertension disease model.