Temperature-insensitive silicone composites as ballistic witness materials: the impact of water content on the thermophysical properties.

In this work, different formulations of a room-temperature silicone composite backing material (SCBM) composed of polydimethylsiloxane (PDMS), fumed silica and corn starch were investigated using different characterization techniques, i.e., differential scanning calorimetry, thermogravimetry analysis, X-ray diffraction (XRD) and small-angle X-ray scattering, as a function of controlled relative humidity. At ambient relative humidities in the range of about 20-80%, the equilibrium water content in the SCBM ranges from approximately 4-10%, which is predominantly absorbed by the corn starch. This amount of water content has been shown to have minimal effect on thermal transition temperatures (melting and glass transition) of the SCBMs. The enthalpy of melting increases with increasing relative humidity, which reflects the heterogeneous semicrystalline structure of starch granules and the role of moisture in facilitating the formation of amylopectin double helices mainly in the imperfect crystalline regions. The thermal degradation of SCBM exhibits three major mass loss steps that correspond to dehydration, decomposition of corn starch and decomposition of PDMS. The XRD patterns reveal a characteristic diffuse peak for amorphous PDMS and an A-type crystallinity for the corn starch. The XRD results show no observable changes in the crystal type and crystallinity as a function of moisture content. Results from this work help clarify the fundamental structure-property relationships in SCBMs, which are important for future development of documentary standards, especially the handling and storage specifications of next-generation ballistic witness materials for body armor testing.

A Preclinical Consortium Approach for Assessing the Efficacy of Combined Anti-CD3 Plus IL-1 Blockade in Reversing New-Onset Autoimmune Diabetes in NOD Mice.

There is an ongoing need to develop strategic combinations of therapeutic agents to prevent type 1 diabetes (T1D) or to preserve islet ß-cell mass in new-onset disease. Although clinical trials using candidate therapeutics are commonly based on preclinical studies, concern is growing regarding the reproducibility as well as the potential clinical translation of reported results using animal models of human disorders. In response, the National Institutes of Health Immune Tolerance Network and JDRF established a multicenter consortium of academic institutions designed to assess the efficacy and intergroup reproducibility of clinically applicable immunotherapies for reversing new-onset disease in the NOD mouse model of T1D. Predicated on prior studies, this consortium conducted coordinated, prospective studies, using joint standard operating procedures, fixed criteria for study entry, and common reagents, to optimize combined anti-CD3 treatment plus interleukin-1 (IL-1) blockade to reverse new-onset disease in NOD mice. We did not find that IL-1 blockade with anti-IL-1ß monoclonal antibody or IL-1trap provided additional benefit for reversing new-onset disease compared with anti-CD3 treatment alone. These results demonstrate the value of larger, multicenter preclinical studies for vetting and prioritizing therapeutics for future clinical use.

Transient B-cell depletion with anti-CD20 in combination with proinsulin DNA vaccine or oral insulin: immunologic effects and efficacy in NOD mice.

A recent type 1 diabetes (T1D) clinical trial of rituximab (a B cell-depleting anti-CD20 antibody) achieved some therapeutic benefit in preserving C-peptide for a period of approximately nine months in patients with recently diagnosed diabetes. Our previous data in the NOD mouse demonstrated that co-administration of antigen (insulin) with anti-CD3 antibody (a T cell-directed immunomodulator) offers better protection than either entity alone, indicating that novel combination therapies that include a T1D-related autoantigen are possible. To accelerate the identification and development of novel combination therapies that can be advanced into the clinic, we have evaluated the combination of a mouse anti-CD20 antibody with either oral insulin or a proinsulin-expressing DNA vaccine. Anti-CD20 alone, given once or on 4 consecutive days, produced transient B cell depletion but did not prevent or reverse T1D in the NOD mouse. Oral insulin alone (twice weekly for 6 weeks) was also ineffective, while proinsulin DNA (weekly for up to 12 weeks) showed a trend toward modest efficacy. Combination of anti-CD20 with oral insulin was ineffective in reversing diabetes in NOD mice whose glycemia was controlled with SC insulin pellets; these experiments were performed in three independent labs. Combination of anti-CD20 with proinsulin DNA was also ineffective in diabetes reversal, but did show modest efficacy in diabetes prevention (p = 0.04). In the prevention studies, anti-CD20 plus proinsulin resulted in modest increases in Tregs in pancreatic lymph nodes and elevated levels of proinsulin-specific CD4+ T-cells that produced IL-4. Thus, combination therapy with anti-CD20 and either oral insulin or proinsulin does not protect hyperglycemic NOD mice, but the combination with proinsulin offers limited efficacy in T1D prevention, potentially by augmentation of proinsulin-specific IL-4 production.

Technology and data-intensive science in the beginning of the 21st century.

This article is a summary of the technology issues and challenges of data-intensive science and cloud computing as discussed in the Data-Intensive Science (DIS) workshop in Seattle, September 19-20, 2010.

Comparing two approaches for aligning representations of anatomy.

OBJECTIVE: To analyze the comparison, through their results, of two distinct approaches applied to aligning two representations of anatomy. MATERIALS: Both approaches use a combination of lexical and structural techniques. In addition, the first approach takes advantage of domain knowledge, while the second approach treats alignment as a special case of schema matching. The same versions of FMA and GALEN were aligned by each approach. Two thousand one hundred and ninety-nine concept matches were obtained by both approaches. METHODS AND RESULTS: For matches identified by one approach only (337 and 336, respectively), we analyzed the reasons that caused the other approach to fail. CONCLUSIONS: The first approach could be improved by addressing partial lexical matches and identifying matches based solely on structural similarity. The second approach may be improved by taking into account synonyms in FMA and identifying semantic mismatches. However, only 33% of the possible one-to-one matches among anatomical concepts were identified by the two approaches together. New directions need to be explored in order to handle more complex matches.

Challenges in precisely aligning models of human anatomy using generic schema matching.

This paper describes how we used generic schema matching algorithms to align the Foundational Model of Anatomy (FMA) and the GALEN Common Reference Model (CRM), two large models of human anatomy. We summarize the generic schema matching algorithms we used to identify correspondences. We present sample results that highlight the similarities and differences between the FMA and the CRM. We also identify uses of aggregation, transitivity, and reification, for which generic schema matching fails to produce an accurate mapping and present manually constructed solutions for them.