Chemoreceptor responsiveness at sea level does not predict the pulmonary pressure response to high altitude

The hypoxic ventilatory response (HVR) at sea level (SL) is moderately predictive of the change in pulmonary artery systolic pressure (PASP) to acute normobaric hypoxia. However, because of progressive changes in the chemoreflex control of breathing and acid-base balance at high altitude (HA), HVR at SL may not predict PASP at HA. We hypothesized that resting peripheral oxyhemoglobin saturation (SpO2) at HA would correlate better than HVR at SL to PASP at HA. In 20 participants at SL, we measured normobaric, isocapnic HVR (L/min·-%SpO2 -1) and resting PASP using echocardiography. Both resting SpO2 and PASP measures were repeated on day 2 (n=10), days 4-8 (n=12), and 2-3 weeks (n=8) after arrival at 5050m. These data were also collected at 5050m on life-long HA residents (Sherpa; n=21). Compared to SL, SpO2 decreased from 98.6 to 80.5% (P<0.001), while PASP increased from 21.7 to 34.0mmHg (P<0.001) after 2-3 weeks at 5050m. Isocapnic HVR at SL was not related to SpO2 or PASP at any time point at 5050m (all P>0.05). Sherpa had lower PASP (P<0.01) than lowlanders on days 4-8 despite similar SpO2. Upon correction for hematocrit, Sherpa PASP was not different from lowlanders at SL, but lower than lowlanders at all HA time points. At 5050m, whilst SpO2 was not related to PASP in lowlanders at any point (all R2=0.50), there was a weak relationship in the Sherpa (R2=0.16; P=0.07). We conclude that neither HVR at SL nor resting SpO2 at HA correlates with elevations in PASP at HA

Cyclophosphamide-Induced Cystitis Increases Bladder CXCR4 Expression and CXCR4-Macrophage Migration Inhibitory Factor Association

BACKGROUND: Macrophage migration inhibitory factor (MIF) is a pro-inflammatory cytokine involved in cystitis and a non-cognate ligand of the chemokine receptor CXCR4 in vitro. We studied whether CXCR4-MIF associations occur in rat bladder and the effect of experimental cystitis. METHODS AND FINDINGS: Twenty male rats received saline or cyclophosphamide (40 mg/kg; i.p.; every 3(rd) day) to induce persistent cystitis. After eight days, urine was collected and bladders excised under anesthesia. Bladder CXCR4 and CXCR4-MIF co-localization were examined with immunhistochemistry. ELISA determined MIF and stromal derived factor-1 (SDF-1; cognate ligand for CXCR4) levels. Bladder CXCR4 expression (real-time RTC-PCR) and protein levels (Western blotting) were examined. Co-immunoprecipitations studied MIF-CXCR4 associations.Urothelial basal and intermediate (but not superficial) cells in saline-treated rats contained CXCR4, co-localized with MIF. Cyclophosphamide treatment caused: 1) significant redistribution of CXCR4 immunostaining to all urothelial layers (especially apical surface of superficial cells) and increased bladder CXCR4 expression; 2) increased urine MIF with decreased bladder MIF; 3) increased bladder SDF-1; 4) increased CXCR4-MIF associations. CONCLUSIONS: These data demonstrate CXCR4-MIF associations occur in vivo in rat bladder and increase in experimental cystitis. Thus, CXCR4 represents an alternative pathway for MIF-mediated signal transduction during bladder inflammation. In the bladder, MIF may compete with SDF-1 (cognate ligand) to activate signal transduction mediated by CXCR4

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

Lysozyme transgenic goats’ milk positively impacts intestinal cytokine expression and morphology

In addition to its well-recognized antimicrobial properties, lysozyme can also modulate the inflammatory response. This ability may be particularly important in the gastrointestinal tract where inappropriate inflammatory reactions can damage the intestinal epithelium, leading to significant health problems. The consumption of milk from transgenic goats producing human lysozyme (hLZ) in their milk therefore has the potential to positively impact intestinal health. In order to investigate the effect of hLZ-containing milk on the inflammatory response, young pigs were fed pasteurized milk from hLZ or non-transgenic control goats and quantitative real-time PCR was performed to assess local expression of TNF-α, IL-8, and TGF-β1 in the small intestine. Histological changes were also investigated, specifically looking at villi width, length, crypt depth, and lamina propria thickness along with cell counts for intraepithelial lymphocytes and goblet cells. Significantly higher expression of anti-inflammatory cytokine TGF-β1 was seen in the ileum of pigs fed pasteurized milk containing hLZ (P = 0.0478), along with an increase in intraepithelial lymphocytes (P = 0.0255), and decrease in lamina propria thickness in the duodenum (P = 0.0001). Based on these results we conclude that consuming pasteurized milk containing hLZ does not induce an inflammatory response and improves the health of the small intestine in pigs

Gene Ontology annotations and resources.

The Gene Ontology (GO) Consortium (GOC, http://www.geneontology.org) is a community-based bioinformatics resource that classifies gene product function through the use of structured, controlled vocabularies. Over the past year, the GOC has implemented several processes to increase the quantity, quality and specificity of GO annotations. First, the number of manual, literature-based annotations has grown at an increasing rate. Second, as a result of a new 'phylogenetic annotation' process, manually reviewed, homology-based annotations are becoming available for a broad range of species. Third, the quality of GO annotations has been improved through a streamlined process for, and automated quality checks of, GO annotations deposited by different annotation groups. Fourth, the consistency and correctness of the ontology itself has increased by using automated reasoning tools. Finally, the GO has been expanded not only to cover new areas of biology through focused interaction with experts, but also to capture greater specificity in all areas of the ontology using tools for adding new combinatorial terms. The GOC works closely with other ontology developers to support integrated use of terminologies. The GOC supports its user community through the use of e-mail lists, social media and web-based resources

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology: enhancements for 2011

The Gene Ontology (GO) (http://www.geneontology.org) is a community bioinformatics resource that represents gene product function through the use of structured, controlled vocabularies. The number of GO annotations of gene products has increased due to curation efforts among GO Consortium (GOC) groups, including focused literature-based annotation and ortholog-based functional inference. The GO ontologies continue to expand and improve as a result of targeted ontology development, including the introduction of computable logical definitions and development of new tools for the streamlined addition of terms to the ontology. The GOC continues to support its user community through the use of e-mail lists, social media and web-based resources