Multienzyme cascade biocatalysis is an efficient synthetic process, avoiding the isolation/purification of intermediates and shifting the reaction equilibrium to the product side.. However, multienzyme systems are often limited by their incompatibility and cross-reactivity. Herein, we report a multi-responsive emulsion to proceed multienzyme reactions sequentially for high reactivity. The emulsion is achieved using a CO2 , pH, and thermo-responsive block copolymer as a stabilizer, allowing the on-demand control of emulsion morphology and phase composition. Applying this system to a three-step cascade reaction enables the individual optimal condition for each enzyme, and a high overall conversion (ca. 97 % of the calculated limit) is thereby obtained. Moreover, the multi-responsiveness of the emulsion allows the facile and separate yielding/recycling of products, polymers and active enzymes. Besides, the system could be scaled up with a good yield.

Quantitative MRI (qMRI) of muscles is a promising tool to measure disease progression or to assess therapeutic effects in neuromuscular diseases. Longitudinal imaging studies are needed to show sensitivity of qMRI in detecting disease progression in spinal muscular atrophy (SMA). In this pilot study we therefore studied one-year changes in quantitative MR parameters in relation to clinical scores.

We repeated quantitative 3 T MR analysis of thigh muscles and clinical testing one year after baseline in 10 treatment-naïve patients with SMA, 5 with Type 2 (21.6 ± 7.0 years) and 5 with Type 3 (33.4 ± 11.9 years). this website MR protocol consisted of Dixon, T

mapping and diffusion tensor imaging (DTI). The temporal relation of parameters was examined with a mixed model.

We detected a significant increase in fat fraction (baseline, 38.2% SE 0.6; follow-up, 39.5% SE 0.6; +1.3%, p = 0.001) in all muscles. Muscles with moderate to high fat infiltration at baseline show a larger increase over time (+1.6%, p < 0.001). We did not find any changes in DTI parameters except for low fat-infiltration muscles (m. adductor longus and m. biceps femoris (short head)). The T

of muscles decreased from 28.2 ms to 28.0 ms (p = 0.07). Muscle strength and motor function scores were not significantly different between follow-up and baseline.

Longitudinal imaging data show slow disease progression in skeletal muscle of the thigh of (young-) adult patients with SMA despite stable strength and motor function scores. Quantitative muscle imaging demonstrates potential as a biomarker for disease activity and monitoring of therapy response.

Longitudinal imaging data show slow disease progression in skeletal muscle of the thigh of (young-) adult patients with SMA despite stable strength and motor function scores. Quantitative muscle imaging demonstrates potential as a biomarker for disease activity and monitoring of therapy response.Molecular switches are essential modules in signaling networks and transcriptional reprogramming. Here, we describe a role for small ubiquitin-related modifier SUMO as a molecular switch in epidermal growth factor receptor (EGFR) signaling. Using quantitative mass spectrometry, we compare the endogenous SUMO proteomes of HeLa cells before and after EGF stimulation. Thereby, we identify a small group of transcriptional coregulators including IRF2BP1, IRF2BP2, and IRF2BPL as novel players in EGFR signaling. Comparison of cells expressing wild type or SUMOylation-deficient IRF2BP1 indicates that transient deSUMOylation of IRF2BP proteins is important for appropriate expression of immediate early genes including dual specificity phosphatase 1 (DUSP1, MKP-1) and the transcription factor ATF3. We find that IRF2BP1 is a repressor, whose transient deSUMOylation on the DUSP1 promoter allows-and whose timely reSUMOylation restricts-DUSP1 transcription. Our work thus provides a paradigm how comparative SUMO proteome analyses serve to reveal novel regulators in signal transduction and transcription.Quantitative 23 Na magnetic resonance imaging (MRI) provides tissue sodium concentration (TSC), which is connected to cell viability and vitality. Long acquisition times are one of the most challenging aspects for its clinical establishment. K-space undersampling is an approach for acquisition time reduction, but generates noise and artifacts. The use of convolutional neural networks (CNNs) is increasing in medical imaging and they are a useful tool for MRI postprocessing. The aim of this study is 23 Na MRI acquisition time reduction by k-space undersampling. CNNs were applied to reduce the resulting noise and artifacts. A retrospective analysis from a prospective study was conducted including image datasets from 46 patients (aged 72 ± 13 years; 25 women, 21 men) with ischemic stroke; the 23 Na MRI acquisition time was 10 min. The reconstructions were performed with full dataset (FI) and with a simulated dataset an image that was acquired in 2.5 min (RI). Eight different CNNs with either U-Net-based or ResNet-based architectures were implemented with RI as input and FI as label, using batch normalization and the number of filters as varying parameters. Training was performed with 9500 samples and testing included 400 samples. CNN outputs were evaluated based on signal-to-noise ratio (SNR) and structural similarity (SSIM). After quantification, TSC error was calculated. The image quality was subjectively rated by three neuroradiologists. Statistical significance was evaluated by Student’s t-test. The average SNR was 21.72 ± 2.75 (FI) and 10.16 ± 0.96 (RI). U-Nets increased the SNR of RI to 43.99 and therefore performed better than ResNet. SSIM of RI to FI was improved by three CNNs to 0.91 ± 0.03. CNNs reduced TSC error by up to 15%. The subjective rating of CNN-generated images showed significantly better results than the subjective image rating of RI. The acquisition time of 23 Na MRI can be reduced by 75% due to postprocessing with a CNN on highly undersampled data.

The role of eating habits of pregnant women in the development and treatment of gestational diabetes mellitus (GDM) is well established.

To estimate the contribution of specific nutrients and dietary patterns in the development or privation of GDM in pregnant women.

A systematic review of cohort studies, published between January 2019 and January 2020, of English articles using PubMed, Scopus and Europe PMC databases. Search terms included diabetes, pregnancy, dietary, food, and nutrients.

Only cohort studies about the association between eating habits before and during pregnancy and the risk of GDM in English were included. The studies used dietary patterns, specific nutrients or records of food intake of the participants using a questionnaire.

Two authors independently extracted data from articles-including dietary patterns, food intake, nutrients, number and demographic data of participants, data about pregnancies-using predefined criteria.

In total, 28 cohort studies were organised to examine the correlation between dietary patterns and the prevention of GDM.