DYRK1A inhibition suppresses STAT3/EGFR/Met signalling and sensitizes EGFR wild‐type NSCLC cells to AZD9291

DYRK1A is considered a potential cancer therapeutic target, but the role of DYRK1A in NSCLC oncogenesis and treatment requires further investigation. In our study, high DYRK1A expression was observed in tumour samples from patients with lung cancer compared with normal lung tissues, and the high levels of DYRK1A were related to a reduced survival time in patients with lung cancer. Meanwhile, the DYRK1A inhibitor harmine could suppress the proliferation of NSCLC cells compared to that of the control. As DYRK1A suppression might be effective in treating NSCLC, we next explored the possible specific molecular mechanisms that were involved. We showed that DYRK1A suppression by siRNA could suppress the levels of EGFR and Met in NSCLC cells. Furthermore, DYRK1A siRNA could inhibit the expression and nuclear translocation of STAT3. Meanwhile, harmine could also regulate the STAT3/EGFR/Met signalling pathway in human NSCLC cells. AZD9291 is effective to treat NSCLC patients with EGFR‐sensitivity mutation and T790 M resistance mutation, but the clinical efficacy in patients with wild‐type EGFR remains modest. We showed that DYRK1A repression could enhance the anti‐cancer effect of AZD9291 by inducing apoptosis and suppressing cell proliferation in EGFR wild‐type NSCLC cells. In addition, harmine could enhance the anti‐NSCLC activity of AZD9291 by modulating STAT3 pathway. Finally, harmine could enhance the anti‐cancer activity of AZD9291 in primary NSCLC cells. Collectively, targeting DYRK1A might be an attractive target for AZD9291 sensitization in EGFR wild‐type NSCLC patients.     

Artificial cationic peptides that increase nuclease resistance of siRNA without disturbing RNAi activity

Properties of cationic peptides bearing amino or guanidino groups with various side chain lengths that bind to double stranded RNAs (dsRNAs) were investigated. Peptides with shorter side chain lengths effectively bound to dsRNAs (12mers) increasing their thermal stability. NMR measurements suggested that the cationic peptide binds to the inner side of the major groove of dsRNA. These peptides also increased the thermal stability of siRNA and effectively protected from RNase A digestion. On the other hand, both peptides containing amino groups and guanidine groups did not disturb RNAi activity.     

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes

The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the following step. Yet, this strategy does not consider potential interactions between a priori distant process steps and therefore cannot guarantee for optimal overall process performance. To overcome these limitations, we established a smart approach to develop and utilize integrated process models using machine learning techniques and genetic algorithms. We evaluated the application of the data-driven models to explore potential efficiency increases and compared them to a conventional development approach for one of our development products. First, we developed a data-driven integrated process model using gradient boosting machines and Gaussian processes as machine learning techniques and a genetic algorithm as recommendation engine for two downstream unit operations, namely solubilization and refolding. Through projection of the results into our large-scale facility, we predicted a twofold increase in productivity. Second, we extended the model to a three-step model by including the capture chromatography. Here, depending on the selected baseline-process chosen for comparison, we obtained between 50% and 100% increase in productivity. These data show the successful application of machine learning techniques and optimization algorithms for downstream process development. Finally, our results highlight the importance of considering integrated process models for the whole process chain, including all unit operations.     

Effect of lactulose on growth performance and intestinal morphology of pre-ruminant calves using a milk replacer containing Enterococcus faecium

The synthetic disaccharide lactulose is known to improve the intestinal microflora by stimulating the growth of selected probiotic bacteria in the gut. In our experiment the effects of lactulose in combination with the probiotic bacteria Enterococcus faecium on growth performance and morphology of the bovine intestine were examined. Calves aged 39 ± 2 days were randomised to three feeding groups (no. = 14 each group): control (L0), fed milk replacer (MR) containing E. faecium; a lactulose group (L1) containing additional 1% lactulose and a second lactulose group (L3) containing 3% lactulose dry matter. The calves were weighed weekly. After 19 weeks the calves were slaughtered and tissues were collected for histological studies. The average daily live weight gain tended to be higher (P < 0.1) for L3 (1350 g/day) than L0 (1288 g/day). Compared with L0, a reduction (P < 0.001) of ileal villus height due to lactulose treatment of approximately 14% in group L1 and 20% in L3 was determined. A significant decrease in the depth of the crypts about 12% in L1 and 8% in L3 was detected in the caecum. The surface area of lymph follicles from Peyer's patches was decreased by lactulose treatment. Results show that lactulose has an effect on the morphology of intestine. A significant effect on growth performance can not be confirmed. However, results permit the conclusion that lactulose feeding has the tendency to increase growth performance.     

Spatiotemporal modeling of first and second wave outbreak dynamics of COVID-19 in Germany

The COVID-19 pandemic has kept the world in suspense for the past year. In most federal countries such as Germany, locally varying conditions demand for state- or county-level decisions to adapt to the disease dynamics. However, this requires a deep understanding of the mesoscale outbreak dynamics between microscale agent models and macroscale global models. Here, we use a reparameterized SIQRD network model that accounts for local political decisions to predict the spatiotemporal evolution of the pandemic in Germany at county resolution. Our optimized model reproduces state-wise cumulative infections and deaths as reported by the Robert Koch Institute and predicts the development for individual counties at convincing accuracy during both waves in spring and fall of 2020. We demonstrate the dominating effect of local infection seeds and identify effective measures to attenuate the rapid spread. Our model has great potential to support decision makers on a state and community politics level to individually strategize their best way forward during the months to come.

     

The pearl necklace model in protein A chromatography: Molecular mechanisms at the resin interface

Staphylococcal protein A chromatography is an established core technology for monoclonal antibody purification and capture in the downstream processing. MabSelect SuRe involves a tetrameric chain of a recombinant form of the B domain of staphylococcal protein A, called the Z-domain. Little is known about the stoichiometry, binding orientation, or preferred binding. We analyzed small-angle X-ray scattering data of the antibody–protein A complex immobilized in an industrial highly relevant chromatographic resin at different antibody concentrations. From scattering data, we computed the normalized radial density distributions. We designed three-dimensional (3D) models with protein data bank crystallographic structures of an IgG1 (the isoform of trastuzumab, used here; Protein Data Bank: 1HZH) and the staphylococcal protein A B domain (the native form of the recombinant structure contained in MabSelect SuRe resin; Protein Data Bank: 1BDD). We computed different binding conformations for different antibody to protein A stoichiometries (1:1, 2:1, and 3:1) and compared the normalized radial density distributions computed from 3D models with those obtained from the experimental data. In the linear range of the isotherm we favor a 1:1 ratio, with the antibody binding to the outer domains in the protein A chain at very low and high concentrations. In the saturation region, a 2:1 ratio is more likely to occur. A 3:1 stoichiometry is excluded because of steric effects.     

Application of the salt stress to the protoplast cultures of the carrot (Daucus carota L.) and evaluation of the response of regenerants to soil salinity

This is the first study to generate carrot plants for enhanced salinity tolerance using a single-cell in vitro system. Protoplasts of three carrot accessions were exposed to treatment by seven different concentrations of NaCl (10–400 mM). Salt concentrations higher than 50 mM decreased plating efficiency and those of 200–400 mM of NaCl completely arrested mitotic divisions of cultured cells. The protoplast-derived plants from the control and 50–100 mM NaCl treatment were subjected to an 8-week salt stress in greenhouse conditions induced by salinized soil (EC 3 and 6 mS cm^?1). 50 mM NaCl stress applied in vitro induced polyploidy among regenerated plants. The regenerants obtained from the 50 and 100 mM NaCl-treated protoplast cultures grown in saline soil had a higher survival rate compared to the regenerants from the control cultures. The salt-stressed plants accumulated anthocyanins in petioles and produced denser hairs on leaves and petioles in comparison to the control plants. Salt stress influenced pollen viability and seed setting of obtained regenerants. The results suggest that salt stress applied in vitro in protoplast cultures creates variation which allows alleviating the negative effects of salt stress on the development and reproduction of the carrot.

     

The fetal circadian rhythm in pregnancies complicated by pregestational diabetes is altered by maternal glycemic control and the morning cortisol concentration

Circadian rhythmicity is fundamental to human physiology, and is present even during fetal life in normal pregnancies. The impact of maternal endocrine disease on the fetal circadian rhythm is not well understood. The present study aimed to determine the fetal circadian rhythm in pregnancies complicated by pregestational diabetes mellitus (PGDM), compare it with a low-risk reference population, and identify the effects of maternal glycemic control and morning cortisol concentrations. Long-term fetal electrocardiogram recordings were made in 40 women with PGDM at 28 and 36 weeks of gestation. Two recordings were made in 18 of the women (45.0%) and one recording was made in 22 (55.0%). The mean fetal heart rate (fHR) and the fHR variation (root mean square of squared differences) were extracted in 1-min epochs, and circadian rhythmicity was detected by cosinor analysis. The study cohort was divided based on HbA1c levels and morning cortisol concentrations. Statistically, significant circadian rhythms in the fHR and the fHR variation were found in 45 (100%) and 44 (95.7%) of the 45 acceptable PGDM recordings, respectively. The rhythms were similar to those of the reference population. However, there was no statistically significant population-mean rhythm in the fHR among PGDM pregnancies at 36 weeks, indicating an increased interindividual variation. The group with higher HbA1c levels (>6.0%) had no significant population-mean fHR rhythm at 28 or 36 weeks, and no significant fHR-variation rhythm at 36 weeks. Similarly, the group with a lower morning cortisol concentration (≤8.8 µg/dl) had no significant population-mean fHR-variation rhythm at 28 and 36 weeks. These findings indicate that individual fetal rhythmicity is present in pregnancies complicated by PGDM. However, suboptimal maternal glycemic control and a lower maternal morning cortisol concentration are associated with a less-well-synchronized circadian system of the fetus.