Insulin-like Growth Factor-I (IGF-I) Regulates IGF-binding Protein-5 Synthesis through Transcriptional Activation of the Gene in Aortic Smooth Muscle Cells

Previous studies have shown that porcine aortic smooth muscle cells (SMCs) secrete two insulin-like growth factor-binding proteins (IGFBP), IGFBP-2 and -4, and that these IGFBPs modulate IGF-I-stimulated SMC proliferation and migration. In this study we demonstrate that porcine SMCs express IGFBP-5 mRNA and synthesize and secrete the protein. In this cell type, the biosynthesis of IGFBP-5 is up-regulated by IGF-I. This increase in IGFBP-5 synthesis is accompanied by an increase in the steady-state mRNA levels. The induction of IGFBP-5 mRNA by IGF-I is time- and dose-dependent and requires de novo protein synthesis. IGF-II and insulin also increase IGFBP-5 mRNA levels at high doses. An IGF-I analog with normal affinity for the IGF-I receptor but reduced affinity for IGFBPs evokes a similar increase. Another analog that binds to IGFBPs but not to the receptor has no effect, indicating that this effect of IGF-I is mediated through the IGF-I receptor. The IGF-I-induced IGFBP-5 gene expression is cell type-specific because IGF-I had no such effect in other cell types examined. Nuclear run-on assays revealed that IGF-I increased transcription rate of the IGFBP-5 gene, while IGF-I did not change the IGFBP-5 mRNA stability. Furthermore, the IGFBP-5 promoter was 3.5-fold more active in directing expression of the luciferase reporter gene in IGF-I-treated aortic SMCs as compared to control cells, whereas the luciferase activity remained the same in control- and IGF-I-treated fibroblasts. These results suggest that IGF-I up-regulates IGFBP-5 synthesis by transcriptionally activating the IGFBP-5 gene in aortic SMCs

Normal Values of Circulating IGF-I Bioactivity in the Healthy Population: Comparison with five widely used IGF-I immunoassays

Background: IGF-I immunoassays are primarily used to estimate IGF-I bioactivity. Recently, an IGFI specific Kinase Receptor Activation Assay (KIRA) has been developed as an alternative method. However, no normative values have been established for the IGF-I KIRA. Objective: To establish normative values for the IGF-I KIRA in healthy adults. Design: Cross-sectional study in healthy non-fasting blood donors. Study participants: 426 healthy individuals (310 M, 116 F; age range: 18 – 79 yrs) Main outcome Measures: IGF-I bioactivity determined by the KIRA. Results were compared with total IGF-I, measured by five different IGF-I immunoassays. Results: Mean (± SD) IGF-I bioactivity was 423 (± 131) pmol/L and decreased with age (β = -3.4 pmol/L/yr, p < 0.001). In subjects younger than 55 yrs mean IGF-I bioactivity was significantly higher in women than in men. Above this age this relationship was inverse, suggesting a drop in IGF-I bioactivity after menopause. This drop was not reflected in total IGF-I levels. IGF-I bioactivity was significantly related to total IGF-I (rs varied between 0.46 – 0.52; P-values < 0.001). Conclusions: We established age-specific normative values for the IGF-I KIRA. We observed a significant drop in IGF-I bioactivity in women between 50 and 60 years, which was not perceived by IGF-I immunoassays. The IGF-I KIRA, when compared to IGF-I immunoassays, theoretically has the advantage that it measures net effects of IGF-binding proteins on IGF-I receptor activation. However, it has to be proven whether information obtained by the IGF-I KIRA is clinically more relevant than measurements obtained by IGF-I immunoassays

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

Synergies, Strengths and Challenges: Findings on Community Capability from a Systematic Health Systems Research Literature Review

Background: Community capability is the combined influence of a community’s social systems and collective resources that can address community problems and broaden community opportunities. We frame it as consisting of three domains that together support community empowerment: what communities have; how communities act; and for whom communities act. We sought to further understand these domains through a secondary analysis of a previous systematic review on community participation in health systems interventions in low and middle income countries (LMICs). Methods: We searched for journal articles published between 2000 and 2012 related to the concepts of “community”, “capability/participation”, “health systems research” and “LMIC.” We identified 64 with rich accounts of community participation involving service delivery and governance in health systems research for thematic analysis following the three domains framing community capability. Results: When considering what communities have, articles reported external linkages as the most frequently gained resource, especially when partnerships resulted in more community power over the intervention. In contrast, financial assets were the least mentioned, despite their importance for sustainability. With how communities act, articles discussed challenges of ensuring inclusive participation and detailed strategies to improve inclusiveness. Very little was reported about strengthening community cohesiveness and collective efficacy despite their importance in community initiatives. When reviewing for whom communities act, the importance of strong local leadership was mentioned frequently, while conflict resolution strategies and skills were rarely discussed. Synergies were found across these elements of community capability, with tangible success in one area leading to positive changes in another. Access to information and opportunities to develop skills were crucial to community participation, critical thinking, problem solving and ownership. Although there are many quantitative scales measuring community capability, health systems research engaged with community participation has rarely made use of these tools or the concepts informing them. Overall, the amount of information related to elements of community capability reported by these articles was low and often of poor quality. Conclusions: Strengthening community capability is critical to ensuring that community participation leads to genuine empowerment. Our simpler framework to define community capability may help researchers better recognize, support and assess it

Global patient outcomes after elective surgery: prospective cohort study in 27 low-, middle- and high-income countries.

BACKGROUND: As global initiatives increase patient access to surgical treatments, there remains a need to understand the adverse effects of surgery and define appropriate levels of perioperative care. METHODS: We designed a prospective international 7-day cohort study of outcomes following elective adult inpatient surgery in 27 countries. The primary outcome was in-hospital complications. Secondary outcomes were death following a complication (failure to rescue) and death in hospital. Process measures were admission to critical care immediately after surgery or to treat a complication and duration of hospital stay. A single definition of critical care was used for all countries. RESULTS: A total of 474 hospitals in 19 high-, 7 middle- and 1 low-income country were included in the primary analysis. Data included 44 814 patients with a median hospital stay of 4 (range 2-7) days. A total of 7508 patients (16.8%) developed one or more postoperative complication and 207 died (0.5%). The overall mortality among patients who developed complications was 2.8%. Mortality following complications ranged from 2.4% for pulmonary embolism to 43.9% for cardiac arrest. A total of 4360 (9.7%) patients were admitted to a critical care unit as routine immediately after surgery, of whom 2198 (50.4%) developed a complication, with 105 (2.4%) deaths. A total of 1233 patients (16.4%) were admitted to a critical care unit to treat complications, with 119 (9.7%) deaths. Despite lower baseline risk, outcomes were similar in low- and middle-income compared with high-income countries. CONCLUSIONS: Poor patient outcomes are common after inpatient surgery. Global initiatives to increase access to surgical treatments should also address the need for safe perioperative care. STUDY REGISTRATION: ISRCTN5181700

An effector Peptide family required for Drosophila toll-mediated immunity.

In Drosophila melanogaster, recognition of an invading pathogen activates the Toll or Imd signaling pathway, triggering robust upregulation of innate immune effectors. Although the mechanisms of pathogen recognition and signaling are now well understood, the functions of the immune-induced transcriptome and proteome remain much less well characterized. Through bioinformatic analysis of effector gene sequences, we have defined a family of twelve genes - the Bomanins (Boms) - that are specifically induced by Toll and that encode small, secreted peptides of unknown biochemical activity. Using targeted genome engineering, we have deleted ten of the twelve Bom genes. Remarkably, inactivating these ten genes decreases survival upon microbial infection to the same extent, and with the same specificity, as does eliminating Toll pathway function. Toll signaling, however, appears unaffected. Assaying bacterial load post-infection in wild-type and mutant flies, we provide evidence that the Boms are required for resistance to, rather than tolerance of, infection. In addition, by generating and assaying a deletion of a smaller subset of the Bom genes, we find that there is overlap in Bom activity toward particular pathogens. Together, these studies deepen our understanding of Toll-mediated immunity and provide a new in vivo model for exploration of the innate immune effector repertoire

Deletion of the 55C <i>Bom</i> genes impairs resistance to <i>E</i>. <i>faecalis</i> infection rather than tolerance.

<p>(A) Points indicate the mean CFU/fly from individual experiments using pools of 5–10 flies per genotype after <i>E</i>. <i>faecalis</i> infection at the indicated time point. Horizontal bars represent the means of the (four or more) independent experiments shown. Significance was measured by two-way ANOVA and is relative to the wild type (<i>w</i>^<i>1118</i>) at the same time point (** p<0.01, *** p<0.001). (B) CFU of individual wild-type (<i>w</i>^<i>1118</i>) flies at 44 hours post-infection. Horizontal bars represent means. “Low” (<3800 CFU/fly) and “high” (>3800 CFU/fly) populations were measured simultaneously during four independent collections of individual flies. Data were binned (indicated by boxes), and means were calculated separately.</p

<i>Bom</i> genes share a conserved 16-aa motif.

<p>(A) Alignment of Bom motifs. Top. Mature Bom peptide sequences of the short-form Boms. Middle. Bom peptide motifs of the tailed Boms. Bottom. Bom peptide motifs from the N- and C-terminal ends of the three bicipital Boms. Shading indicates sequence identity (black) or similarity (gray). (B) Schematic of the three Bom peptide forms. ‘Bom’ represents the conserved 16-aa motif depicted in Fig 1A. Drawings are to scale and arrows indicate sites of cleavage. (C) Schematic of 55C <i>Bom</i> gene cluster on chromosome 2R. Lines beneath schematic demarcate areas deleted in <i>Bom</i>^<i>Δ55C</i> and <i>Bom</i>^{<i>Δleft</i>} chromosomes. The proximal end of the gene cluster is shown to the left.</p