Remote Ischemic Conditioning (RIC) has been proposed as a therapeutic intervention to circumvent the ischemia/reperfusion injury (IRI) that is inherent to organ transplantation. Using a porcine kidney transplant model, we aimed to decipher the subclinical molecular effects of a RIC regime, compared to non-RIC controls.

Kidney pairs (n = 8 + 8) were extracted from brain dead donor pigs and transplanted in juvenile recipient pigs following a period of cold ischemia. One of the two kidney recipients in each pair was subjected to RIC prior to kidney graft reperfusion, while the other served as non-RIC control. We designed an integrative Omics strategy combining transcriptomics, proteomics, and phosphoproteomics to deduce molecular signatures in kidney tissue that could be attributed to RIC.

In kidney grafts taken out 10h after transplantation we detected minimal molecular perturbations following RIC compared to non-RIC at the transcriptome level, which was mirrored at the proteome level. In particular, we noted that RIC resulted in suppression of tissue inflammatory profiles. Furthermore, an accumulation of muscle extracellular matrix assembly proteins in kidney tissues was detected at the protein level, which may be in response to muscle tissue damage and/or fibrosis. However, the majority of these protein changes did not reach significance (p < 0.05).

Our data identifies subtle molecular phenotypes in porcine kidneys following RIC, and this knowledge could potentially aid optimization of remote ischemic conditioning protocols in renal transplantation.

Our data identifies subtle molecular phenotypes in porcine kidneys following RIC, and this knowledge could potentially aid optimization of remote ischemic conditioning protocols in renal transplantation.

Emerging wheat stem rust races have become a major threat to global wheat production. Finding additional loci responsible for resistance to these races and incorporating them into currently cultivated varieties is the most economic and environmentally sound strategy to combat this problem. Thus, this study was aimed at characterizing the genetic diversity and identifying the genetic loci conferring resistance to the stem rust of wheat. To accomplish this, 245 elite lines introduced from the International Center for Agricultural Research in the Dry Areas (ICARDA) were evaluated under natural stem rust pressure in the field at the Debre Zeit Agricultural Research Center, Ethiopia. The single nucleotide polymorphisms (SNP) marker data was retrieved from a 15 K SNP wheat array. A mixed linear model was used to investigate the association between SNP markers and the best linear unbiased prediction (BLUP) values of the stem rust coefficient of infection (CI).

Phenotypic analysis revealed that 46% of the lines helection. It is recommended that the resistant wheat genotypes identified in this study be used in the national wheat breeding programs to improve stem rust resistance.Quantitative trait locus (QTL) analysis allows to identify regions responsible for a trait and to associate alleles with their effect on phenotypes. When using biallelic markers to find these QTL regions, two alleles per QTL are modelled. This assumption might be close to reality in specific biparental crosses but is unrealistic in situations where broader genetic diversity is studied. Diversity panels used in genome-wide association studies or multi-parental populations can easily harbour multiple QTL alleles at each locus, more so in the case of polyploids that carry more than two alleles per individual. In such situations a multiallelic model would be closer to reality, allowing for different genetic effects for each potential allele in the population. To obtain such multiallelic markers we propose the usage of haplotypes, concatenations of nearby SNPs. We developed „mpQTL” an R package that can perform a QTL analysis at any ploidy level under biallelic and multiallelic models, depending on the marker type given. We tested the effect of genetic diversity on the power and accuracy difference between bi-allelic and multiallelic models using a set of simulated multiparental autotetraploid, outbreeding populations. Multiallelic models had higher detection power and were more precise than biallelic, SNP-based models, particularly when genetic diversity was higher. This confirms that moving to multi-allelic QTL models can lead to improved detection and characterization of QTLs. KEY MESSAGE QTL detection in populations with more than two functional QTL alleles (which is likely in multiparental and/or polyploid populations) is more powerful when using multiallelic models, rather than biallelic models.

Knowledge of protein motions is significant to understand its functions. While currently available databases for protein motions are mostly focused on overall domain motions, little attention is paid on local residue motions. Albeit with relatively small scale, the local residue motions, especially those residues in binding pockets, may play crucial roles in protein functioning and ligands binding.

A comprehensive protein motion database, namely D3PM, was constructed in this study to facilitate the analysis of protein motions. The protein motions in the D3PM range from overall structural changes of macromolecule to local flip motions of binding pocket residues. Currently, the D3PM has collected 7679 proteins with overall motions and 3513 proteins with pocket residue motions. The motion patterns are classified into 4 types of overall structural changes and 5 types of pocket residue motions. Impressively, we found that less than 15% of protein pairs have obvious overall conformational adaptations induced by ligand binding, while more than 50% of protein pairs have significant structural changes in ligand binding sites, indicating that ligand-induced conformational changes are drastic and mainly confined around ligand binding sites. Based on the residue preference in binding pocket, we classified amino acids into „pocketphilic” and „pocketphobic” residues, which should be helpful for pocket prediction and drug design.

D3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on http://www.d3pharma.com/D3PM/index.php .

D3PM is a comprehensive database about protein motions ranging from residue to domain, which should be useful for exploring diverse protein motions and for understanding protein function and drug design. The D3PM is available on http://www.d3pharma.com/D3PM/index.php .

Gene ontology (GO) enrichment analysis is frequently undertaken during exploration of various -omics data sets. Despite the wide array of tools available to biologists to perform this analysis, meaningful visualisation of the overrepresented GO in a manner which is easy to interpret is still lacking.

Monash Gene Ontology (MonaGO) is a novel web-based visualisation system that provides an intuitive, interactive and responsive interface for performing GO enrichment analysis and visualising the results. MonaGO supports gene lists as well as GO terms as inputs. Visualisation results can be exported as high-resolution images or restored in new sessions, allowing reproducibility of the analysis. An extensive comparison between MonaGO and 11 state-of-the-art GO enrichment visualisation tools based on 9 features revealed that MonaGO is a unique platform that simultaneously allows interactive visualisation within one single output page, directly accessible through a web browser with customisable display options.

MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

MonaGO combines dynamic clustering and interactive visualisation as well as customisation options to assist biologists in obtaining meaningful representation of overrepresented GO terms, producing simplified outputs in an unbiased manner. MonaGO will facilitate the interpretation of GO analysis and will assist the biologists into the representation of the results.

Ecomorphs create the opportunity to investigate ecological adaptation because they encompass organisms that evolved characteristic morphologies under similar ecological demands. For over 50years, scorpions have been empirically assigned to ecomorphs based on the characteristic morphologies that rock, sand, vegetation, underground, and surface dwellers assume. This study aims to independently test the existence of scorpion ecomorphs by quantifying the association between their morphology and ecology across 61 species, representing 14 families of the Scorpiones order.

Without a priori categorization of species into ecomorphs, we identified four groups based on microhabitat descriptors, which reflect how scorpion ecospace is clustered. Moreover, these microhabitat groups, i.e., ecotypes, have significantly divergent morphologies; therefore, they represent ecomorphs. These ecomorphs largely correspond with the ones previously described in the literature. Therefore, we retained the names Lithophilous, Psammophthem on a more solid quantitative footing for future studies of ecological adaptation in scorpions. Our results verify most of the previously defined ecomorphotypes and could be used as a current practice to understand the adaptive significance of ecological morphology.RAB27B is a member of Ras-like small GTPases that plays a role in endocytosis, exocytosis, and vesicle trafficking. We made an attempt to study the impacts of RAB27B on the proliferation and apoptosis of acute myeloid leukemia (AML) cells. The silencing of RAB27B was induced by siRNA for the detection of proliferation, cell cycle, and apoptosis, respectively by Cell Counting Kit-8 (CCK8), flow cytometry, and TUNEL. Related markers were also evaluated by Western blot analysis. The interaction between RAB27B and BDH2 was predicted by bioinformatics analysis and determined by immunoprecipitation. The gain of function of BDH2 was also detected by these functional assays. RAB27B exhibited high levels in AML cells, and RAB27B silencing led to reduced proliferation, increased cell cycle arrest and apoptosis levels. Then, the interaction between RAB27B and BDH2 was confirmed. Moreover, the effects of RAB27B inhibition on the proliferation, cell cycle arrest, and cell apoptosis were abolished after BDH2 overexpression. RAB27B inhibits proliferation and promotes apoptosis of leukemic cells by interacting with BDH2. Targeting RAB27B might be an effective method for the treatment of AML.Osteoarthritis is an inflammatory disease of the musculoskeletal system characterized by damaged articular cartilage. Nintedanib is an oral triple kinase inhibitor with anti-fibrotic and anti-inflammatory properties. Thus, we hypothesized that nintedanib might exert a protective effect in chondrocytes and it could be meaningful to repurpose the drug for osteoarthritis. In this study, we aimed to investigate the potential effects of nintedanib on TNF-α-induced cellular injury in CHON-001 chondrocytes. The results show that nintedanib ameliorated TNF-α-induced reactive oxygen species (ROS) production and reduced glutathione (GSH) decrease. Nintedanib reduced the production of pro-inflammatory cytokines interleukin-6 (IL-6) and interleukin-1β (IL-1β) in TNF-α-induced CHON-001 chondrocytes. Nintedanib restored TNF-α caused decreased expression levels of Col II and sry-type high-mobility-group box-9 (SOX-9) in CHON-001 chondrocytes. Moreover, nintedanib ameliorated the TNF-α-caused impairment of protein kinase A/cAMP-response element-binding protein (PKA/CREB) signaling pathway as revealed by the decreased PKA RI expression and increased p-CREB in CHON-001 cells.