Galectins in the Pathogenesis of Common Retinal Disease

Diseases of the retina are major causes of visual impairment and blindness in developed countries and, due to an ageing population, their prevalence is continually rising. The lack of effective therapies and the limitations of those currently in use highlight the importance of continued research into the pathogenesis of these diseases. Vascular endothelial growth factor (VEGF) plays a major role in driving vascular dysfunction in retinal disease and has therefore become a key therapeutic target. Recent evidence also points to a potentially similarly important role of galectins, a family of β-galactoside-binding proteins. Indeed, they have been implicated in regulating fundamental processes, including vascular hyperpermeability, angiogenesis, neuroinflammation, and oxidative stress, all of which also play a prominent role in retinopathies. Here, we review direct evidence for pathological roles of galectins in retinal disease. In addition, we extrapolate potential roles of galectins in the retina from evidence in cancer, immune and neuro-biology. We conclude that there is value in increasing understanding of galectin function in retinal biology, in particular in the context of the retinal vasculature and microglia. With greater insight, recent clinical developments of galectin-targeting drugs could potentially also be of benefit to the clinical management of many blinding diseases

GC-MS analysis and antibacterial activity of some fractions from Lagochilus ilicifolius Bge. grown in Mongolia

3-methyl-1,2,3,4-tetrahydroquinoline (1), 4-hydroxyisoquinoline (2), 4-(1E)-hydroxy-1-prophenyl)-2-methoxyphenol (3), 4-acetoxycinnamic acid (4), Songoramine (5), and Songorine (6) have been determined by GC-MS analysis from the crude alkaloid mixtures (G1) obtained from the aerial parts of Lagochilus ilicifolius Bge. grown in Mongolia and comparison of the measured data with those from the literature. The compounds 1-6 are described for the first time from L.ilicifolius. From these 3-methyl-1,2,3,4-tetrahydroquinoline (1) was determined for the first time from natural plants.In addition, the antibacterial activity of fractions and total alkaloids were evaluated against Staphylococcus aurous, Bacillus subtilis, Bacillus cereus and Escherichia coli strains, respectively. The growth inhibition zones against gram-positive S.aureus, B.subtilis, B.cereus and gram negative E.coli, strains were observed. Positive results were achieved on 500 μg/disc concentration, but lower results or no active on 100 μg/disc concentration were for the plant extracts, fractions and total alkaloids.Mongolian Journal of Chemistry 16 (42), 2015, 39-4

MODULATORY EFFECT OF CANNABINOID LIGANDS ON THE ANXIETY-LIKE BEHAVIOR OF BULBECTOMIZED RATS

Purpose: The endocannabinoid system is considered a key regulatory system in anxiety behavior. The aim of the present study was to examine the effects of intracerebroventricularly (i.c.v.) injected cannabinoid ligands on the anxiety-like behavior of rats with a model of depression. Material/Methods: The olfactory bulbectomized rat (OBX) is a well-established experimental model of depression. The OBX model exhibits neurochemical changes that are very similar to those seen in patients with depression. CB1 receptor agonist HU-210 and CB1 receptor antagonist SR 141716A were injected i.c.v. in OBX rats, and the anxiety-related behavior of the rats was measured in an elevated plus-maze (EPM) test. Results: OBX rats showed an increased anxiety-like behavior at the EPM test. HU-210 produced an anxiolytic-like effect and alleviated the OBX-induced anxiety, while SR 141716A failed to produce effects on the behavior of OBX rats. Conclusions: The results suggest that CB1 receptors may be involved in the modulation of anxiety-related behavior in OBX rats

STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/

New insights into risk factors for transplant-associated thrombotic microangiopathy in pediatric HSCT

This study aimed to identify a risk profile for development of transplant-associated thrombotic microangiopathy (TA-TMA) in children undergoing hematopoietic stem cell transplantation (HSCT). Between 2013 and 2016, 439 children underwent 474 HSCTs at 2 supraregional United Kingdom centers. At a median of 153 days post-HSCT, TA-TMA occurred among 25 of 441 evaluable cases (5.6%) with no evidence of center variation. Sex, underlying disease, intensity of the conditioning, total body irradiation–based conditioning, the use of calcineurin inhibitors, venoocclusive disease, and viral reactivation did not influence the development of TA-TMA. Donor type: matched sibling donor/matched family donor vs matched unrelated donor vs mismatched unrelated donor/haplo-HSCT, showed a trend toward the development of TA-TMA in 1.8% vs 6.1% vs 8.3%, respectively. Presence of active comorbidity was associated with an increased risk for TA-TMA; 13% vs 3.7% in the absence of comorbidity. The risk of TA-TMA was threefold higher among patients who received >1 transplant. TA-TMA rates were significantly higher among patients with acute graft-versus-host disease (aGVHD) grades III to IV vs aGVHD grade 0 to II. On multivariate analysis, the presence of active comorbidity, >1 transplant, aGVHD grade III to IV were risk factors for TA-TMA (odds ratio [OR]: 5.1, 5.2, and 26.9; respectively), whereas the use of cyclosporine A/tacrolimus-based GVHD prophylaxis was not a risk factor for TA-TMA (OR: 0.3). Active comorbidity, subsequent transplant, and aGVHD grades III to IV were significant risk factors for TA-TMA. TA-TMA might represent a form of a vascular GVHD, and therefore, continuing control of aGVHD is important to prevent worsening of TA-TMA associated with GVHD

Proposed therapeutic range of treosulfan in reduced toxicity pediatric allogeneic hematopoietic stem cell transplant conditioning: results from a prospective trial

Treosulfan is given off‐label in pediatric allogeneic hematopoietic stem cell transplant. This study investigated treosulfan's pharmacokinetics (PKs), efficacy, and safety in a prospective trial. Pediatric patients (n = 87) receiving treosulfan‐fludarabine conditioning were followed for at least 1 year posttransplant. PKs were described with a two‐compartment model. During follow‐up, 11 of 87 patients died and 12 of 87 patients had low engraftment (≤ 20% myeloid chimerism). For each increase in treosulfan area under the curve from zero to infinity (AUC(0‐∞)) of 1,000 mg hour/L the hazard ratio (95% confidence interval) for mortality increase was 1.46 (1.23–1.74), and the hazard ratio for low engraftment was 0.61 (0.36–1.04). A cumulative AUC(0‐∞) of 4,800 mg hour/L maximized the probability of success (> 20% engraftment and no mortality) at 82%. Probability of success with AUC(0‐∞) between 80% and 125% of this target were 78% and 79%. Measuring PK at the first dose and individualizing the third dose may be required in nonmalignant disease

Cross-species high-resolution transcriptome profiling suggests biomarkers and therapeutic targets for ulcerative colitis

Background: Ulcerative colitis (UC) is a disorder with unknown etiology, and animal models play an essential role in studying its molecular pathophysiology. Here, we aim to identify common conserved pathological UC-related gene expression signatures between humans and mice that can be used as treatment targets and/or biomarker candidates.Methods: To identify differentially regulated protein-coding genes and non-coding RNAs, we sequenced total RNA from the colon and blood of the most widely used dextran sodium sulfate Ulcerative colitis mouse. By combining this with public human Ulcerative colitis data, we investigated conserved gene expression signatures and pathways/biological processes through which these genes may contribute to disease development/progression.Results: Cross-species integration of human and mouse Ulcerative colitis data resulted in the identification of 1442 genes that were significantly differentially regulated in the same direction in the colon and 157 in blood. Of these, 51 genes showed consistent differential regulation in the colon and blood. Less known genes with importance in disease pathogenesis, including SPI1, FPR2, TYROBP, CKAP4, MCEMP1, ADGRG3, SLC11A1, and SELPLG, were identified through network centrality ranking and validated in independent human and mouse cohorts.Conclusion: The identified Ulcerative colitis conserved transcriptional signatures aid in the disease phenotyping and future treatment decisions, drug discovery, and clinical trial design

The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets

Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein-protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/

The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest

Much of the complexity within cells arises from functional and regulatory interactions among proteins. The core of these interactions is increasingly known, but novel interactions continue to be discovered, and the information remains scattered across different database resources, experimental modalities and levels of mechanistic detail. The STRING database (https://string-db.org/) systematically collects and integrates protein-protein interactions-both physical interactions as well as functional associations. The data originate from a number of sources: automated text mining of the scientific literature, computational interaction predictions from co-expression, conserved genomic context, databases of interaction experiments and known complexes/pathways from curated sources. All of these interactions are critically assessed, scored, and subsequently automatically transferred to less well-studied organisms using hierarchical orthology information. The data can be accessed via the website, but also programmatically and via bulk downloads. The most recent developments in STRING (version 12.0) are: (i) it is now possible to create, browse and analyze a full interaction network for any novel genome of interest, by submitting its complement of encoded proteins, (ii) the co-expression channel now uses variational auto-encoders to predict interactions, and it covers two new sources, single-cell RNA-seq and experimental proteomics data and (iii) the confidence in each experimentally derived interaction is now estimated based on the detection method used, and communicated to the user in the web-interface. Furthermore, STRING continues to enhance its facilities for functional enrichment analysis, which are now fully available also for user-submitted genomes