Dynamic mechanical analysis of the multiple glass transitions of plasticized wheat gluten biopolymer

Glass transition of thermo‐molded biomaterials made from wheat gluten and its main protein classes is studied by dynamic mechanical analysis (DMA). The materials are plasticized with variable contents of glycerol (30–40 wt %) and water (0–20 wt %). For all materials, three successive relaxation phases are systematically detected. Their positions shift to lower temperature as the plasticizer content of materials increases. Composition in gluten, glycerol and water of each relaxation phase is estimated using the Couchman‐Karasz model. Irrespective of the plasticizer content or composition, the relaxation phases shows rather constant plasticizer volume fractions. The low‐, middle‐, and high relaxation phases include respectively around 30, 60 and 80 vol % of gluten protein. These relaxations are assigned to the segmental motion of the surface amino‐acid side groups, to the collective motion of packed gluten proteins, and to the gain in protein conformational mobility as a 2D network of interacting plasticizer molecules forms. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43254.     

Near‐Infrared Intraoperative Chemiluminescence Imaging

Intraoperative imaging technologies recently entered the operating room, and their implementation is revolutionizing how physicians plan, monitor, and perform surgical interventions. In this work, we present a novel surgical imaging reporter system: intraoperative chemiluminescence imaging (ICI). To this end, we have leveraged the ability of a chemiluminescent metal complex to generate near‐infrared light upon exposure to an aqueous solution of Ce⁴⁺ in the presence of reducing tissue or blood components. An optical camera spatially resolves the resulting photon flux. We describe the construction and application of a prototype imaging setup, which achieves a detection limit as low as 6.9 pmol cm^?2 of the transition‐metal‐based ICI agent. As a proof of concept, we use ICI for the in vivo detection of our transition metal tracer following both systemic and subdermal injections. The very high signal‐to‐noise ratios make ICI an interesting candidate for the development of new intraoperative imaging technologies.     

Sanierung eines PCE-Schadens in einem makroskopisch oxischen Grundwasserleiter durch Stimulation anaerober dehalogenierender Bakterien

Grundwasser - Eine erfolgreiche biologische In-situ-Sanierung von PCE-kontaminierten Grundwasserleitern erfordert hinreichend reduzierende Bedingungen sowie die Anwesenheit von molekularem...     

Impact of Grain Boundary Density on Oxide Scaling Revisited

Oxidation of Metals - A straightforward conceptual tool for discriminating between different oxide scaling processes deviating from the parabolic standard model is formulated. Grain boundary...     

Optimized silyl ester diblock methacrylic copolymers: A new class of binders for chemically active antifouling coatings

This work focuses on the assessment of the erosion properties and antifouling (AF) performance of silyl ester copolymer-based coatings through laboratory and field tests. Silyl ester diblock copolymers were synthesized via the reversible addition-fragmentation chain transfer polymerization and were selected as binders for developing copper-free chemically active coatings. AF coatings were subsequently prepared using biocides (Sea-Nine™ 211, Preventol^® A4S, and zinc pyrithione). Laboratory-based bioassays, targeting the growth of selected microorganisms (bacteria and microalgae) and barnacle settlement, highlighted that the silyl ester methacrylic-based binders did not inhibit the growth of microorganisms, are essentially non-toxic to nauplii and reduced the settlement of Amphibalanus amphitrite cyprids. The corresponding biocidal coatings are potent toward bacteria and diatoms but were demonstrated to be toxic against the barnacle larvae. Field test results showed variations with geographical locations: in sub-tropical area, the silyl ester methacrylic-based coatings failed to inhibit the settlement of barnacles; however, field tests performed in Mediterranean Sea for 18 months demonstrated that biocidal silyl ester methacrylic-based coatings were promising candidates.     

Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera

Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are both autoimmune inflammatory and demyelinating diseases of the central nervous system. NMOSD is a highly disabling disease and rapid introduction of the appropriate treatment at the acute phase is crucial to prevent sequelae. Specific criteria were established in 2015 and provide keys to distinguish NMOSD and MS. One of the most reliable criteria for NMOSD diagnosis is detection in patient’s serum of an antibody that attacks the water channel aquaporin-4 (AQP-4). Another target in NMOSD is myelin oligodendrocyte glycoprotein (MOG), delineating a new spectrum of diseases called MOG-associated diseases. Lastly, patients with NMOSD can be negative for both AQP-4 and MOG antibodies. At disease onset, NMOSD symptoms are very similar to MS symptoms from a clinical and radiological perspective. Thus, at first episode, given the urgency of starting the anti-inflammatory treatment, there is an unmet need to differentiate NMOSD subtypes from MS. Here, we used Fourier transform infrared spectroscopy in combination with a machine learning algorithm with the aim of distinguishing the infrared signatures of sera of a first episode of NMOSD from those of a first episode of relapsing-remitting MS, as well as from those of healthy subjects and patients with chronic inflammatory demyelinating polyneuropathy. Our results showed that NMOSD patients were distinguished from MS patients and healthy subjects with a sensitivity of 100% and a specificity of 100%. We also discuss the distinction between the different NMOSD serostatuses. The coupling of infrared spectroscopy of sera to machine learning is a promising cost-effective, rapid and reliable differential diagnosis tool capable of helping to gain valuable time in patients’ treatment.     

Preclinical Evaluation of CAR T Cell Function: In Vitro and In Vivo Models

Immunotherapy using chimeric antigen receptor (CAR) T cells is a rapidly emerging modality that engineers T cells to redirect tumor-specific cytotoxicity. CAR T cells have been well characterized for their efficacy against B cell malignancies, and rigorously studied in other types of tumors. Preclinical evaluation of CAR T cell function, including direct tumor killing, cytokine production, and memory responses, is crucial to the development and optimization of CAR T cell therapies. Such comprehensive examinations are usually performed in different types of models. Model establishment should focus on key challenges in the clinical setting and the capability to generate reliable data to indicate CAR T cell therapeutic potency in the clinic. Further, modeling the interaction between CAR T cells and tumor microenvironment provides additional insight for the future endeavors to enhance efficacy, especially against solid tumors. This review will summarize both in vitro and in vivo models for CAR T cell functional evaluation, including how they have evolved with the needs of CAR T cell research, the information they can provide for preclinical assessment of CAR T cell products, and recent technology advances to test CAR T cells in more clinically relevant models.