Epoxy paint failure in B-52 fuel tanks: Part II. Influence of DIEGME concentration in the fuel on the failure process

A model has been proposed to explain the failure of the original BMS10-39 epoxy paint on upper vertical surfaces in B-52 fuel tanks. The model involves interaction of the paint with DIEGME, a fuel system ice inhibitor (FSII) in jet fuel, that is distilled from the liquid fuel. In this communication, distillation experiments used to support the model are refined to better match the mass transfer of vapor from fuel in a B-52 fuel tank at close to room temperature. The interaction of these lower temperature distillates with the paint affirms the earlier model. On the basis of these experiments it is proposed that paint failure may be controlled or eliminated by reducing the level of DIEGME in the fuel. Proposed changes in military jet fuel composition are detailed.     

Advancing controlled release packaging through smart blending

Researchers from Rutgers University and Clemson University have collaborated to develop a concept of using smart blending to generate functional packaging films for the controlled release of active compounds such as antimicrobials, antioxidants and flavour compounds to extend the shelf‐life of food. In this paper, literature results are reviewed to justify the significance of controlled release packaging (CRP) and the research gaps for further development are identified. A major research gap is the lack of packaging materials that can provide the release of active compounds at rates suitable for a wide range of food packaging applications. Smart blending is a promising technology for bridging this research gap. To fully realize the potentials of smart blending, a systematic approach for developing CRP using smart blending is also presented. Copyright © 2005 John Wiley & Sons, Ltd.     

Inside this month

This issue contains a preview of the CFA’s annual trade show, which this year takes place in Anaheim, California. Those of you who also attend the JEC Composites Show in Paris will see a vast difference between these two events, not only in cultural terms but also in focus. CFA is an association for US manufacturers and its show places a high emphasis on education and networking. JEC’s slant is to the end-user and it strives to be a showcase for composites technology. Both of these approaches are to the ultimate benefit of the composites industry, but as companies continue to look at ways of spending their money more effectively, show attendance is one area coming under increasing scrutiny. Many have been saying that it is too expensive to attend JEC every year and now a group of major resin suppliers, including DSM, Reichhold, Ashland and Cray Valley, have taken the step of staying away from next year’s show (see page 64). This will surely dent the show’s profits and it will be interesting to see how the organisers, as well as other exhibitors, will respond to this development.     

Establishing In-House Cutoffs of CSF Alzheimer’s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer’s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST^® ELISA and Lumipulse G^® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer’s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing–Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland–Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan–Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815⁻²⁷). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects.     

TLR/WNT: A Novel Relationship in Immunomodulation of Lung Cancer

The most frequent cause of death by cancer worldwide is lung cancer, and the 5-year survival rate is still very poor for patients with advanced stage. Understanding the crosstalk between the signaling pathways that are involved in disease, especially in metastasis, is crucial to developing new targeted therapies. Toll-like receptors (TLRs) are master regulators of the immune responses, and their dysregulation in lung cancer is linked to immune escape and promotes tumor malignancy by facilitating angiogenesis and proliferation. On the other hand, over-activation of the WNT signaling pathway has been reported in lung cancer and is also associated with tumor metastasis via induction of Epithelial-to-mesenchymal-transition (EMT)-like processes. An interaction between both TLRs and the WNT pathway was discovered recently as it was found that the TLR pathway can be activated by WNT ligands in the tumor microenvironment; however, the implications of such interactions in the context of lung cancer have not been discussed yet. Here, we offer an overview of the interaction of TLR-WNT in the lung and its potential implications and role in the oncogenic process.     

Identification of Structural and Molecular Signatures Mediating Adaptive Changes in the Mouse Kidney in Response to Pregnancy

Pregnancy is characterized by adaptations in the function of several maternal body systems that ensure the development of the fetus whilst maintaining health of the mother. The renal system is responsible for water and electrolyte balance, as well as waste removal. Thus, it is imperative that structural and functional changes occur in the kidney during pregnancy. However, our knowledge of the precise morphological and molecular mechanisms occurring in the kidney during pregnancy is still very limited. Here, we investigated the changes occurring in the mouse kidney during pregnancy by performing an integrated analysis involving histology, gene and protein expression assays, mass spectrometry profiling and bioinformatics. Data from non-pregnant and pregnant mice were used to identify critical signalling pathways mediating changes in the maternal kidneys. We observed an expansion of renal medulla due to proliferation and infiltration of interstitial cellular constituents, as well as alterations in the activity of key cellular signalling pathways (e.g., AKT, AMPK and MAPKs) and genes involved in cell growth/metabolism (e.g., Cdc6, Foxm1 and Rb1) in the kidneys during pregnancy. We also generated plasma and urine proteomic profiles, identifying unique proteins in pregnancy. These proteins could be used to monitor and study potential mechanisms of renal adaptations during pregnancy and disease.     

Ranking the efficacies of selected red wine phenolic anti-oxidants using reversed-phase HPLC

Several studies have assessed total anti-oxidant activity of wine or individual components in isolation using chemical-based assays. In this study, a quantitative approach was developed to assess the relative anti-oxidant efficacies of selected red wine phenolics via peak reduction, using reversed-phase HPLC. Both intact red wine and phenolic standard solutions were challenged with five oxidant model systems as follows: (1) hydrogen peroxide (H₂O₂); redox-active metal ions (2) Fe³⁺ and (3) Cu²⁺; and the Fenton reagents (4) H₂O₂ + Fe²⁺; and (5) H₂O₂ + Cu⁺. Treatment with oxidants (1–3) resulted in loss of 47–60% of phenolic standards, which increased to 66–89% for treatment with the Fenton systems, with quercetin exhibiting the optimal anti-oxidant activity. For intact red wine, treatment with oxidants (1–3) led to all phenolic compounds being oxidised (27–77% loss), with caffeic acid and quercetin as the most effective anti-oxidants. For both Fenton systems (4–5), activities in red wine were considerably enhanced for caffeic acid and quercetin, which exhibited the highest anti-oxidant efficacies with 100% peak reduction, while p-coumaric acid and gallic acid were less effective anti-oxidants with peak reductions of 60–68%. The ranking, facilitated by this new quantitative approach, allows comparison of the individual efficacies of the anti-oxidants in a complex matrix.     

Hydration-Induced Void-Containing Hydrogels for Encapsulation and Sustained Release of Small Hydrophilic Molecules

Efficient encapsulation and sustained release of small hydrophilic molecules from traditional hydrogel systems are challenging due to the large mesh size of 3D networks and high water content. Furthermore, the encapsulated molecules are prone to early release from the hydrogel prior to use, resulting in a short shelf life of the formulation. Here, a hydration-induced void-containing hydrogel (HVH) based on hyperbranched polyglycerol-poly(propylene oxide)-hyperbranched polyglycerol (HPG-PPG-HPG) as a robust and efficient delivery system is presented for small hydrophilic molecules. Specifically, after the HPG-PPG-HPG is incubated overnight at 4 °C in the drug solution, it is hydrated into a hydrogel containing micron-sized voids, which can encapsulate hydrophilic drugs and achieve 100% drug encapsulation efficiency. In addition, the voids are surrounded by a densely packed polymer matrix, which restricts drug transport to achieve sustained drug release. The hydrogel/drug formulation can be stored for several months without changing the drug encapsulation and release properties. HVH hydrogels are injectable due to shear thinning properties. In rats, a single injection of the HPG-PPG-HPG hydrogel containing 8 µg of tetrodotoxin (TTX) produces sciatic nerve block lasting up to 10 h without any TTX-related systemic toxicity nor local toxicity to nerves and muscles.     

Regularized field map estimation in MRI

In fast magnetic resonance (MR) imaging with long readout times, such as echo-planar imaging (EPI) and spiral scans, it is important to correct for the effects of field inhomogeneity to reduce image distortion and blurring. Such corrections require an accurate field map, a map of the off-resonance frequency at each voxel. Standard field map estimation methods yield noisy field maps, particularly in image regions with low spin density. This paper describes regularized methods for field map estimation from two or more MR scans having different echo times. These methods exploit the fact that field maps are generally smooth functions. The methods use algorithms that decrease monotonically a regularized least-squares cost function, even though the problem is highly nonlinear. Results show that the proposed regularized methods significantly improve the quality of field map estimates relative to conventional unregularized methods.