Ligand Binding Alters Dimerization and Sequestering of Urokinase Receptors in Raft-Mimicking Lipid Mixtures

Lipid heterogeneities, such as lipid rafts, are widely considered to be important for the sequestering of membrane proteins in plasma membranes, thereby influencing membrane protein functionality. However, the underlying mechanisms of such sequestration processes remain elusive, in part, due to the small size and often transient nature of these functional membrane heterogeneities in cellular membranes. To overcome these challenges, here we report the sequestration behavior of urokinase receptor (uPAR), a glycosylphosphatidylinositol-anchored protein, in a planar model membrane platform with raft-mimicking lipid mixtures of well-defined compositions using a powerful optical imaging platform consisting of confocal spectroscopy XY-scans, photon counting histogram, and fluorescence correlation spectroscopy analyses. This methodology provides parallel information about receptor sequestration, oligomerization state, and lateral mobility with single molecule sensitivity. Most notably, our experiments demonstrate that moderate changes in uPAR sequestration are not only associated with modifications in uPAR dimerization levels, but may also be linked to ligand-mediated allosteric changes of these membrane receptors. Our data show that these modifications in uPAR sequestration can be induced by exposure to specific ligands (urokinase plasminogen activator, vitronectin), but not via adjustment of the cholesterol level in the planar model membrane system. Good agreement of our key findings with published results on cell membranes confirms the validity of our model membrane approach. We hypothesize that the observed mechanism of receptor translocation in the presence of raft-mimicking lipid mixtures is also applicable to other glycosylphosphatidylinositol-anchored proteins.     

Spatial separation of anaerobic ammonium oxidation and nitrite-dependent anaerobic methane oxidation in permeable riverbeds

Anaerobic ammonium oxidation (anammox) and nitrite-dependent anaerobic methane oxidation (n-damo) play important roles in nitrogen and carbon cycling in fresh waters but we do not know how these two processes compete for their common electron acceptor, nitrite. Here, we investigated the spatial distribution of anammox and n-damo across a range of permeable riverbed sediments. Anammox activity and gene abundance were detected in both gravel and sandy riverbeds and showed a simple, common vertical distribution pattern, while the patterns in n-damo were more complex and n-damo activity was confined to the more reduced, sandy riverbeds. Anammox was most active in surficial sediment (0–2 cm), coincident with a peak in hzsA gene abundance and nitrite. In contrast, n-damo activity peaked deeper down (4–8 cm) in the sandy riverbeds, coincident with a peak in n-damo 16S rRNA gene abundance and higher methane concentration. Pore water nitrite, methane and oxygen were key factors influencing the distribution of these two processes in permeable riverbeds. Furthermore, both anammox- and n-damo- activity were positively correlated with denitrification activity, suggesting a role for denitrification in supplying both processes with nitrite. Our data reveal spatial separation between anammox and n-damo in permeable riverbed sediments that potentially avoids them competing for nitrite.     

Robust Volume Assessment of Brain Tissues for 3-Dimensional Fourier Transformation MRI via a Novel Multispectral Technique

A new TRIO algorithm method integrating three different algorithms is proposed to perform brain MRI segmentation in the native coordinate space, with no need of transformation to a standard coordinate space or the probability maps for segmentation. The method is a simple voxel-based algorithm, derived from multispectral remote sensing techniques, and only requires minimal operator input to depict GM, WM, and CSF tissue clusters to complete classification of a 3D high-resolution multislice-multispectral MRI data. Results showed very high accuracy and reproducibility in classification of GM, WM, and CSF in multislice-multispectral synthetic MRI data. The similarity indexes, expressing overlap between classification results and the ground truth, were 0.951, 0.962, and 0.956 for GM, WM, and CSF classifications in the image data with 3% noise level and 0% non-uniformity intensity. The method particularly allows for classification of CSF with 0.994, 0.961 and 0.996 of accuracy, sensitivity and specificity in images data with 3% noise level and 0% non-uniformity intensity, which had seldom performed well in previous studies. As for clinical MRI data, the quantitative data of brain tissue volumes aligned closely with the brain morphometrics in three different study groups of young adults, elderly volunteers, and dementia patients. The results also showed very low rates of the intra- and extra-operator variability in measurements of the absolute volumes and volume fractions of cerebral GM, WM, and CSF in three different study groups. The mean coefficients of variation of GM, WM, and CSF volume measurements were in the range of 0.03% to 0.30% of intra-operator measurements and 0.06% to 0.45% of inter-operator measurements. In conclusion, the TRIO algorithm exhibits a remarkable ability in robust classification of multislice-multispectral brain MR images, which would be potentially applicable for clinical brain volumetric analysis and explicitly promising in cross-sectional and longitudinal studies of different subject groups.     

Establishment of an ELISA to Detect Kaposi＇s Sarcoma-associated Herpesvirus Using Recombinant ORF73

Kaposi's sarcoma-associated herpesvirus (KSHV) is causally related to Kaposi's sarcoma (KS),primary effusion lymphoma (PEL) and a proportion of cases of multicentric Castleman's disease (MCD). The ORF73 protein was cloned into pQE80L-orf73 and expressed in E.coli and purified. The expressed recombinant ORF73 was identified by sodium dodecyl sulfatepolyacrylamide gel electrophoresis (SDS-PAGE). A protein of about 27 kDa was expressed as expected. Western Blotting showed that the purified recombinant ORF73 reacted with KSHV positive serum. The immunogenicity of the recombinant ORF73 was further analysed by ELISA and the optimal conditions were determined. The ORF73 ELISA was used to compare the KSHV seroprevalence between Hubei and Xinjiang Han people. The Hart people in Xinjiang have significantly higher KSHV seroprevalence than their counterparts in Hubei (6.7% vs 2.9%, P = 0.005).     

Comparison of the hydrodynamics and mass transfer characteristics in internal-loop airlift bioreactors utilizing either a novel membrane-tube sparger or perforated plate sparger

Two gas spargers, a novel membrane-tube sparger and a perforated plate sparger, were compared in terms of hydrodynamics and mass transfer (or oxygen transfer) performance in an internal-loop airlift bioreactor. The overall gas holdup ε _T, downcomer liquid velocity V _d, and volumetric mass transfer coefficient K _L a were examined depending on superficial gas velocity U _G increased in Newtonian and non-Newtonian fluids for the both spargers. Compared with the perforated plate sparger, the bioreactor with the membrane-tube sparger increased the values of ε _T by 4.9–48.8 % in air–water system when the U _G was from 0.004 to 0.04 m/s, and by 65.1–512.6 % in air–CMC solution system. The V _d value for the membrane-tube sparger was improved by 40.0–86.3 %. The value of K _L a was increased by 52.8–84.4 % in air–water system, and by 63.3–836.3 % in air–CMC solution system. Empirical correlations of ε _T, V _d, and K _L a were proposed, and well corresponding with the experimental data with the deviation of 10 %.     

The Shenzhen Congress and plant conservation: What have we accomplished in the 6 years since?

At the XIX International Botanical Congress held in Shenzhen, China, in July 2017, the delegates unanimously adopted the Shenzhen Declaration on Plant Sciences in an effort to accelerate the contributions made by plant scientists for the benefit of the world′s changing society. This paper discusses what has been accomplished concerning plant conservation since the Shenzhen Declaration. Beyond the problems we faced in 2017, the global Covid pandemic and the war have presented new challenges. With the massive ecological overshoot, the number of malnourished people globally has increased. Most threats to vascular plants have increased generally over these 6 years, while the responses of the botanical community to them have continued to proceed at a relatively slow pace. Although international cooperation is needed to combat the grave challenges we face, the ease of such collaboration has decreased substantially in recent years. Certainly, rapid deforestation, especially in the tropics, and our ineffective approaches to mitigate climate change will lessen the effectiveness of our strategies to slow extinction. Indeed, our blindness to the reality of ecological overshoot and misperceptions concerning sustainability are accelerating extinction and thus destabilizing social structures and civilization. As an example, conservation in China faces serious challenges with biodiversity loss, but botanical gardens and seed banks there offer hope on ex situ conservation. The botanical and other scientific communities can contribute by drawing the attention of fellow citizens to the gravity of the problems that we face and by being actively engaged in providing solutions and carrying them forward to action.     

Deep learning image analysis models pretrained on daily objects are useful for the preliminary characterization of particulate pharmaceutical samples

Visible and subvisible particles are a quality attribute in sterile pharmaceutical samples. A common method for characterizing and quantifying pharmaceutical samples containing particulates is imaging many individual particles using high-throughput instrumentation and analyzing the populations data. The analysis includes conventional metrics such as the particle size distribution but can be more sophisticated by interpreting other visual/morphological features. To avoid the hurdles of building new image analysis models capable of extracting such relevant features from scratch, we propose using well-established pretrained deep learning image analysis models such as EfficientNet. We demonstrate that such models are useful as a prescreening tool for high-level characterization of biopharmaceutical particle image data. We show that although these models are originally trained for completely different tasks (such as the classification of daily objects in the ImageNet database), the visual feature vectors extracted by such models can be useful for studying different types of subvisible particles. This applicability is illustrated through multiple case studies: (i) particle risk assessment in prefilled syringe formulations containing different particle types such as silicone oil, (ii) method comparability with the example of accelerated forced degradation, and (iii) excipient influence on particle morphology with the example of Polysorbate 80 (PS80). As examples of agnostic applicability of pretrained models, we also elucidate the application to two high-throughput microscopy methods: microflow and background membrane imaging. We show that different particle populations with different morphological and visual features can be identified in different samples by leveraging out-of-the-box pretrained models to analyze images from each sample.     

Growth,ROS Markers,Antioxidant Enzymes,Osmotic Regulators and Metabolic Changes in Tartary Buckwheat Subjected to Short Drought

Tartary buckwheat (Fagopyrum tataricum) is an important pseudocereal feed crop with medicinal and nutritional value. Drought is one of the main causes of reduced growth and yield in these plants. We investigated the growth, physiological, and metabolic responses of the widely promoted Tartary buckwheat variety Chuan Qiao No. 1 to polyethylene glycol (PEG)-mediated drought stress. Drought significantly decreased shoot length, shoot biomass and relative water content. Root length, malondialdehyde content, electrolyte leakage, activities of superoxide dismutase, peroxidase, catalase and amylase, and contents of soluble sugar, soluble protein and proline were increased by PEG-mediated drought. Untargeted metabolomics analysis identified 32 core metabolites in seedlings subjected to PEG-mediated drought, 16 of which increased—including quercetin, isovitexin, cyanidin 3-O-beta-D-glucoside, L-arginine, and glycerophosphocholine, while the other 16 decreased—including 3-methoxytyramine, 2, 6-diaminopimelic acid, citric acid, UDP-alpha-D-glucose, adenosine, keto-D-fructose. The 32 core metabolites were enriched in 29 metabolic pathways, including lysine biosynthesis, citrate (TCA) cycle, anthocyanin biosynthesis, and aminoacyl-tRNA biosynthesis. Among them, taurine and hypotaurine metabolism, flavor and flavor biosynthesis, indole alkaline biosynthesis, and alanine, aspartate and glutamate metabolism were the four main metabolic pathways affected by drought. Our findings provide new insights into the physiological and metabolic response mechanisms of Tartary buckwheat to drought stress.     

Identification and expression profiling of receptor-interacting serine/threonine-protein kinase 2 in Siberian sturgeon (Acipenser baerii)

Receptor-interacting serine/threonine-protein kinase 2 (RIPK2) is an adaptor protein of the pattern recognition receptors NOD1 and NOD2 involved in regulating inflammatory response and resisting pathogenic microbial infection. In this study, Acipenser baerii RIPK2 (AbRIPK2) was identified. The open reading frame of AbRIPK2 was 1815 bp encoding 604 amino acids. AbRIPK2 possessed the typical N-terminal kinase domain (KD) and C-terminal caspase recruitment domain (CARD). The phylogenetic tree analysis revealed that AbRIPK2 shared a relatively high identity with bony fish. Real-time fluorescence quantitative PCR (qRT-PCR) results indicated that AbRIPK2 was highly expressed in the gill, followed by muscle, liver and heart. AbRIPK2 was significantly induced in the spleen and valvular intestine after Streptococcus iniae and Aeromonas hydrophila infection. AbRIPK2 was significantly upregulated after peptidoglycan (PGN) treatment in the splenic leukocytes. This study indicated that AbRIPK2 played a potential role in resisting the pathogenic infection of Siberian sturgeon by responding to bacteria.