Immobilization of urease on copper chelated EC-Tri beads and reversible adsorption

In the present study, Eupergit C® macroporous beads were functionalized with amino triazole and characterized by FTIR-ATR and SEM. Cu2+ ions were chelated on the triazole modified Eupergit C® (EC®), and then the metal chelated beads were used in the adsorption of urease. Maximum reaction rate (Vmax) and Michaelis-Menten constant (km) were determined for the free and immobilized enzymes. Various characteristics of immobilized urease such as the temperature activity curve, thermal stability, operational stability and storage stability were evaluated. The results demonstrated that triazole functionalized Eupergit C® beads can be applied to metal sorption and enzyme immobilization.Key words: Urease, immobilization, Eupergit C®, triazole, chelating beads

Optocoder: computational decoding of spatially indexed bead arrays

Advancing technologies that quantify gene expression in space are transforming contemporary biology research. A class of spatial transcriptomics methods uses barcoded bead arrays that are optically decoded via microscopy and are later matched to sequenced data from the respective libraries. To obtain a detailed representation of the tissue in space, robust and efficient computational pipelines are required to process microscopy images and accurately basecall the bead barcodes. Optocoder is a computational framework that processes microscopy images to decode bead barcodes in space. It efficiently aligns images, detects beads, and corrects for confounding factors of the fluorescence signal, such as crosstalk and phasing. Furthermore, Optocoder employs supervised machine learning to strongly increase the number of matches between optically decoded and sequenced barcodes. We benchmark Optocoder using data from an in-house spatial transcriptomics platform, as well as from Slide-Seq(V2), and we show that it efficiently processes all datasets without modification. Optocoder is publicly available, open-source and provided as a stand-alone Python package on GitHub: https://github.com/rajewsky-lab/optocoder

Profile-encoding reconstruction for multiple-acquisition balanced steady-state free precession imaging

Purpose: The scan-efficiency in multiple-acquisition balanced steady-state free precession imaging can be maintained by accelerating and reconstructing each phase-cycled acquisition individually, but this strategy ignores correlated structural information among acquisitions. Here, an improved acceleration framework is proposed that jointly processes undersampled data across N phase cycles. Methods: Phase-cycled imaging is cast as a profile-encoding problem, modeling each image as an artifact-free image multiplied with a distinct balanced steady-state free precession profile. A profile-encoding reconstruction (PE-SSFP) is employed to recover missing data by enforcing joint sparsity and total-variation penalties across phase cycles. PE-SSFP is compared with individual compressed-sensing and parallel-imaging (ESPIRiT) reconstructions. Results: In the brain and the knee, PE-SSFP yields improved image quality compared to individual compressed-sensing and other tested methods particularly for higher N values. On average, PE-SSFP improves peak SNR by 3.8 ± 3.0 dB (mean ± s.e. across N = 2–8) and structural similarity by 1.4 ± 1.2% over individual compressed-sensing, and peak SNR by 5.6 ± 0.7 dB and structural similarity by 7.1 ± 0.5% over ESPIRiT. Conclusion: PE-SSFP attains improved image quality and preservation of high-spatial-frequency information at high acceleration factors, compared to conventional reconstructions. PE-SSFP is a promising technique for scan-efficient balanced steady-state free precession imaging with improved reliability against field inhomogeneity. Magn Reson Med 78:1316–1329, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicin

Tracking the position and rotational orientation of a catheter using a transmit array system

A new method for detecting the rotational orientation and tracking the position of an inductively coupled radio frequency (ICRF) coil using a transmit array system is proposed. The method employs a conventional body birdcage coil, but the quadrature hybrid is eliminated so that the two excitation channels can be used separately. The transmit array system provides RF excitations such that the body birdcage coil creates linearly polarized and changing RF pulses instead of a conventional rotational forward-polarized excitation. The receive coils and their operations are not modified. Inductively coupled RF coils are constructed on catheters for detecting rotational orientation and for tracking purposes. Signals from the anatomy and from tissue close to the ICRF coil are different due to the new RF excitation scheme: the ICRF coil can be separated from the anatomy in real time, and after doing so, a color-coded image is reconstructed. More importantly, this novel method enables a real-time calculation of the absolute rotational orientation of an ICRF coil constructed on a catheter. © 1982-2012 IEEE

Generation of dissipative solitons in normal-dispersion Raman fiber laser

Dissipative soliton pulses in a synchronously pumped all-normal-dispersion Raman fiber laser is presented theoretically and experimentally. The laser generates 7.1 nJ intra-cavity pulses at 1.12 μm and is compressed to 136 fs. © 2015 IEEE

Particulate impurities in cell-based medicinal products traced by flow imaging microscopy combined with deep learning for image analysis

Cell-based medicinal products (CBMPs) are rapidly gaining importance in the treatment of life-threatening diseases. However, the analytical toolbox for characterization of CBMPs is limited. The aim of our study was to develop a method based on flow imaging microscopy (FIM) for the detection, quantification and characterization of subvisible particulate impurities in CBMPs. Image analysis was performed by using an image classification approach based on a convolutional neural network (CNN). Jurkat cells and Dynabeads were used in our study as a representation of cellular material and non-cellular particulate impurities, respectively. We demonstrate that FIM assisted with CNN is a powerful method for the detection and quantification of Dynabeads and cells with other process related impurities, such as cell agglomerates, cell-bead adducts and debris. By using CNN, we achieved a more than 50-fold lower misclassification rate compared with the use of output parameters from the FIM software. The limit of detection was ~15 000 beads/mL in the presence of ~500 000 cells/mL, making this approach suitable for the detection of these particulate impurities in CBMPs. In conclusion, CNN-assisted FIM is a powerful method for the detection and quantification of cells, Dynabeads and other subvisible process impurities potentially present in CBMPs.Drug Delivery Technolog

Nonlinearity management: From fiber oscillators to amplifiers

While the standard approach to performance scaling in fiber lasers seeks to reduce nonlinear effects through chirping or mode scaling, I will review recent progress in a complementary approach, whereby the governing dynamics are meticulously exploited towards achieving superior performance. © 2015 IEEE

What is the future of targeted therapy in rheumatology: biologics or small molecules?

Background: Until late in the 20th century, the therapy of rheumatic diseases relied on the use of drugs that had been developed through empirical approaches without detailed understanding of the molecular mechanisms involved. That approach changed with the introduction of biologic therapeutics at the end of the 20th century and by the recent development of small-molecule inhibitors of intracellular signal transduction pathways. Here we compare and discuss the advantages and disadvantages of those two groups of targeted anti-inflammatory therapeutics.Discussion: TNF-blocking biologic agents were introduced into the therapy of rheumatoid arthritis and other autoimmune and inflammatory diseases in the late 1990s. Further biologic agents targeting cytokine networks or specific lymphocyte subsets have since been added to the armamentarium of anti-rheumatic therapy. During the last few years, another wave of novel discoveries led to the development of a new class of small molecule anti-inflammatory compounds targeting intracellular signal transduction molecules, such as tyrosine kinases. In all those cases, the specific targets of the drugs are well defined and significant knowledge about their role in the disease pathomechanism is available, qualifying them for being targeted therapeutics for inflammatory rheumatic diseases. While both groups of targeted therapeutics offer significant clinical benefit, they clearly differ in several aspects, such as the localization of their targets, their route of administration and target specificity, as well as technical details such as manufacturing procedures and cost basis. In this debate paper, we compare the advantages and disadvantages of the two different approaches, aiming to shed light on the possible future of targeted therapies.Summary: Biologic therapeutics and small-molecule inhibitors both have significant advantages and disadvantages in the therapy of rheumatic diseases. The future of targeted therapies is one of the most exciting questions of current rheumatology research and therapy. © 2014 Mócsai et al.; licensee BioMed Central Ltd

Pain, depression, and quality of life in neuromyelitis optica spectrum disorder: a cross-sectional study of 166 AQP4 antibody-seropositive patients

OBJECTIVES: To evaluate prevalence, clinical characteristics, and predictors of pain, depression, and their impact on the quality of life (QoL) in a large neuromyelitis optica spectrum disorder (NMOSD) cohort. METHODS: We included 166 patients with aquaporin-4–seropositive NMOSD from 13 tertiary referral centers. Patients received questionnaires on demographic and clinical characteristics, PainDetect, short form of Brief Pain Inventory, Beck Depression Inventory–II, and Short Form 36 Health Survey. RESULTS: One hundred twenty-five (75.3%) patients suffered from chronic NMOSD-associated pain. Of these, 65.9% had neuropathic pain, 68.8% reported spasticity-associated pain and 26.4% painful tonic spasms. Number of previous myelitis attacks (OR = 1.27, p = 0.018) and involved upper thoracic segments (OR = 1.31, p = 0.018) were the only predictive factors for chronic pain. The latter was specifically associated with spasticity-associated pain (OR = 1.36, p = 0.002). More than a third (39.8%) suffered from depression, which was moderate to severe in 51.5%. Pain severity (OR = 1.81, p < 0.001) and especially neuropathic character (OR = 3.44, p < 0.001) were associated with depression. Pain severity and walking impairment explained 53.9% of the physical QoL variability, while depression and walking impairment 39.7% of the mental QoL variability. No specific medication was given to 70.6% of patients with moderate or severe depression and 42.5% of those with neuropathic pain. Two-thirds (64.2%) of patients with symptomatic treatment still reported moderate to severe pain. CONCLUSIONS: Myelitis episodes involving upper thoracic segments are main drivers of pain in NMOSD. Although pain intensity was lower than in previous studies, pain and depression remain undertreated and strongly affect QoL. Interventional studies on targeted treatment strategies for pain are urgently needed in NMOSD