Effect of Micro-strain Stress on in Vitro Proliferation and Functional Expression of Human Osteoarthritic Chondrocytes

Background: This study aimed to analyze the in vitro effect of micro-strain stress on the proliferation and functional marker expression in chondrocytes isolated from human osteoarthritis cartilage samples.Methods: Chondrocytes isolated from human osteoarthritis cartilage samples were subjected to loading with different types of micro-strain stress. The proliferation activity was assessed by flow cytometry, and the functional expression of chondrocyte markers was detected by qRT-PCR and western blot. Results: Flow cytometry results showed stimulation of proliferation of human osteoarthritic chondrocytes when an adequate micro-strain stress was applied. qRT-PCR and western blot results showed that micro-strain stress promotes human osteoarthritic chondrocyte functional marker expression. These features coincide with the upregulation of multiple proteins and genes affecting cell proliferation and functional chondrocyte marker expression, including cyclin D1, collagen II, and Rock.Conclusion: Adequate micro-strain stress could activate the Rho/Rock signaling pathway in osteoarthritic chondrocytes, thus transmitting mechanical signals to the cytoskeleton. This process leads to cytoskeleton reorganization, and transmission of the mechanical signals to the downstream effectors to promote proliferation and functional marker expression of osteoarthritic chondrocytes.

Salinity as a key control on the diazotrophic community composition in the Baltic Sea

Over the next decade, the Baltic Sea is predicted to undergo severe changes including a decrease in salinity due to altering precipitation. This will likely impact the distribution and community composition of Baltic Sea N2 fixing microbes, of which especially heterocystous cyanobacteria are adapted to low salinities and may expand to waters with currently higher salinity, including the Danish Strait and Kattegat, while other high-salinity adapted N2 fixers might decrease in abundance. In order to explore the impact of salinity on the distribution and activity of different diazotrophic clades, we followed the natural salinity gradient from the Eastern Gotland and Bornholm Basins through the Arkona Basin to the Kiel Bight and combined N2 fixation rate measurements with a molecular analysis of the diazotrophic community using the key functional marker gene for N2 fixation nifH, as well as the key functional marker genes anf and vnf, encoding for the two alternative nitrogenases. We detected N2 fixation rates between 0.7 and 6 nmol N L-1 d-1, and the diazotrophic community was dominated by the cyanobacterium Nodularia and the small unicellular, cosmopolitan cyanobacterium UCYN-A. Nodularia was present in abundances between 8.07 x 105 and 1.6 x 107 copies L-1 in waters with salinities of 10 and below, while UCYN-A reached abundances of up to 4.5 x 107 copies L-1 in waters with salinity above 10. Besides those two cyanobacterial diazotrophs, we found several clades of proteobacterial N2 fixers and alternative nitrogenase genes associated with Rhodopseudomonas palustris, a purple non-sulfur bacterium. Based on statistical testing, salinity was identified as the primary parameter describing the diazotrophic distribution, while pH and temperature did not have a similarly significant influence on the diazotrophic distribution. While this statistical analysis will need to be explored in direct experiments, it gives an indication for a future development of diazotrophy in a freshening Baltic Sea with UCYN-A retracting to more saline North Sea waters and heterocystous cyanobacteria expanding as salinity decreases.

Prediction of standard cell types and functional markers from flow cytometry gating definitions using machine learning

BackgroundA key step in clinical flow cytometry data analysis is gating, which involves the identification of cell populations. The process of gating produces a set of reportable results, which are typically described by gating definitions. The non-standardized, non-interpreted nature of gating definitions represents a hurdle for data interpretation and data sharing across and within organizations. Interpreting and standardizing gating definitions for subsequent analysis of gating results requires a curation effort from experts. Machine learning approaches have the potential to help in this process by predicting expert annotations associated with gating definitions.MethodsWe created a gold-standard dataset by manually annotating thousands of gating definitions with cell type and functional marker annotations. We used this dataset to train and test a machine learning pipeline able to predict standard cell types and functional marker genes associated with gating definitions.ResultsThe machine learning pipeline predicted annotations with high accuracy for both cell types and functional marker genes. Accuracy was lower for gating definitions from assays belonging to laboratories from which limited or no prior data was available in the training. Manual error review ensured that resulting predicted annotations could be reused subsequently as additional gold-standard training data.ConclusionsMachine learning methods are able to consistently predict annotations associated with gating definitions from flow cytometry assays. However, a hybrid automatic and manual annotation workflow would be recommended to achieve optimal results.

Natural variations in the non-coding region of ZmNAC080308 contributes maintaining grain yield under drought stress in maize

Background Natural variations derived from both evolutionary selection and genetic recombination, presume to have important functions to respond to various abiotic stresses, which could be used to improve drought tolerance via genomic selection. Results In the present study, the NAC-encoding gene of ZmNAC080308 was cloned and sequenced in 199 inbred lines in maize. Phylogenetic analysis showed that ZmNAC080308 is closely clusteredinto the same group with other well-known NAC genes responding to improve drought tolerance. In total, 86 SNPs and 47 InDels were identified in the generic region of ZmNAC080308, 19 of these variations were associated with GY (grain yield) in different environments. Nine variations in the 5’-UTR region of ZmNAC080308 are closely linked, they might regulate the gene expression and respond to improve GY under drought condition via Sp1-mediated transactivation. Two haplotypes (Hap1 and Hap2) identified in the, 5’-UTR region using the nine variations, and Hap2 containing insertion variants, exhibited 15.47 % higher GY under drought stress condition. Further, a functional marker was developed to predict the drought stress tolerance in a US maize inbred line panel. Lines carrying Hap2 exhibited > 10 % higher GY than those carrying Hap1 under drought stress condition. In Arabidopsis, overexpression ZmNAC080308 enhanced drought tolerance. Conclusions ZmNAC080308 is an important gene responding to drought tolerance, a functional marker is developed for improving maize drought tolerance by selecting this gene.

Ink as a Functional Marker in the Study of the Syriac and Christian Sogdian Manuscript Fragments in the Turfan Collection (Berlin) and in the Krotkov Collection (St. Petersburg)

The Syriac and Christian Sogdian manuscript fragments in the Turfan Collection (Berlin) and in the Krotkov Collection (St. Petersburg) were written in black ink and, much less frequently, in brown ink. The use of red ink is very limited and not yet studied in detail. By linking the analysis of all the elements that are due or related to the scribal discourse in Christian Medieval Central Asia with a well‑established codicological tradition, this contribution is meant to outline the purposes of the use of different ink in the Syriac and Christian Sogdian manuscript fragments discovered in the early 20th century in Xinjiang (China). A broader perspective that takes into account other Eastern Christian manuscript traditions is also included.