Is there an economic case for investing in nursing care – what does the literature tell us?

Aim To determine the cost effectiveness of increasing nurse staffing or changing the nursing skill mix in adult medical and/or surgical patients? Background Research has demonstrated that nurse staffing levels and skill mix are associated with patient outcomes in acute care settings. If increased nurse staffing levels or richer skill mix can be shown to be cost-effective hospitals may be more likely to consider these aspects when making staffing decisions. Design A systematic review of the literature on economic evaluations of nurse staffing and patient outcomes was conducted to see whether there is consensus that increasing nursing hours/skill mix is a cost-effective way of improving patient outcomes. We used the Cochrane Collaboration systematic review method incorporating economic evidence. Data sources The MEDLINE, CINAHL, SPORTDiscus and PsychINFO databases were searched in 2013 for published and unpublished studies in English with no date limits. Review methods The review focused on full economic evaluations where costs of increasing nursing hours or changing the skill mix were included and where consequences included nursing sensitive outcomes. Results Four-cost benefit and five-cost effectiveness analyses were identified. There were no cost-minimization or cost-utility studies identified in the review. A variety of methods to conceptualize and measure costs and consequences were used across the studies making it difficult to compare results. Conclusion This review was unable to determine conclusively whether or not changes in nurse staffing levels and/or skill mix is a cost-effective intervention for improving patient outcomes due to the small number of studies, the mixed results and the inability to compare results across studies

High fat diet rescues disturbances to metabolic homeostasis and survival in the Id2 null mouse in a sex-specific manner

Inhibitor of DNA binding 2 (ID2) is a helix-loop-helix transcriptional repressor rhythmically expressed in many adult tissues. Our previous studies have demonstrated that Id2 null mice have altered expression of circadian genes involved in lipid metabolism, altered circadian feeding behavior, and sex-specific enhancement of insulin sensitivity and elevated glucose uptake in skeletal muscle and brown adipose tissue. Here we further characterized the Id2−/− mouse metabolic phenotype in a sex-specific context and under low and high fat diets, and examined metabolic and endocrine parameters associated with lipid and glucose metabolism. Under the low-fat diet Id2−/− mice showed decreased weight gain, reduced gonadal fat mass, and a lower survival rate. Under the high-fat diet, body weight and gonadal fat gain of Id2−/− male mice was comparable to control mice and survival rate improved markedly. Furthermore, the high-fat diet treated Id2−/− male mice lost the enhanced glucose tolerance feature observed in the other Id2−/− groups, and there was a sex-specific difference in white adipose tissue storage of Id2−/− mice. Additionally, a distinct pattern of hepatic lipid accumulation was observed in Id2−/− males: low lipids on the low-fat diet and steatosis on the high-fat diet. In summary, these data provides valuable insights into the impact of Id2 deficiency on metabolic homeostasis of mice in a sex-specific manner

Dissociation between diurnal cycles in locomotor activity, feeding behavior and hepatic PERIOD2 expression in chronic alcohol-fed mice

Chronic alcohol consumption contributes to fatty liver disease. Our studies revealed that the hepatic circadian clock is disturbed in alcohol-induced hepatic steatosis, and effects of chronic alcohol administration upon the clock itself may contribute to steatosis. We extended these findings to explore the effects of chronic alcohol treatment on daily feeding and locomotor activity patterns. Mice were chronically pair-fed ad libitum for 4 weeks using the Lieber-DeCarli liquid diet, with calorie-controlled liquid and standard chow diets as control groups. Locomotor activity, feeding activity, and real-time bioluminescence recording of PERIOD2::LUCIFERASE expression in tissue explants were measured. Mice on liquid control and chow diets exhibited normal profiles of locomotor activity, with a ratio of 22:78% day/night activity and a peak during early night. This pattern was dramatically altered in alcohol-fed mice, marked by a 49:51% ratio and the absence of a distinct peak. While chow-diet fed mice had a normal 24:76% ratio of feeding activity, with a peak in the early night, this pattern was dramatically altered in both liquid-diet groups: mice had a 43:57% ratio, and an absence of a distinct peak. Temporal differences were also observed between the two liquid-diet groups during late day. Cosinor analysis revealed a ∼4-h and ∼6-h shift in the alcohol-fed group feeding and locomotor activity rhythms, respectively. Analysis of hepatic PER2 expression revealed that the molecular clock in alcohol-fed and control liquid-diet mice was shifted by ∼11 h and ∼6 h, respectively. No differences were observed in suprachiasmatic nucleus explants, suggesting that changes in circadian phase in the liver were generated independently from the central clock. These results suggest that chronic alcohol consumption and a liquid diet can differentially modulate the daily rhythmicity of locomotor and feeding behaviors, aspects that might contribute to disturbances in the circadian timing system and development of hepatic steatosis

Circadian Programs of Transcriptional Activation, Signaling, and Protein Turnover Revealed by Microarray Analysis of Mammalian Cells

Many aspects of physiology and behavior are temporally organized into daily 24 hr rhythms, driven by an endogenous circadian clock. Studies in eukaryotes have identified a network of interacting genes forming interlocked autoregulatory feedback loops which underlie overt circadian organization in single cells [1, 2]. While in mammals the master oscillator resides in the suprachiasmatic nuclei of the hypothalamus [2], semiautonomous circadian oscillators also exist in peripheral tissues [3–5] and in immortalized fibroblasts, where rhythmicity is induced following a serum shock [6, 7]. We used this model system in combination with high-density cDNA microarrays to examine the magnitude and quality of clock control of gene expression in mammalian cells. Supported by application of novel bioinformatics tools, we find ∼2% of genes, including expected canonical clock genes, to show consistent rhythmic circadian expression across five independent experiments. Rhythmicity in most of these genes is novel, and they fall into diverse functional groups, highlighted by a predominance of transcription factors, ubiquitin-associated factors, proteasome components, and Ras/MAPK signaling pathway components. When grouped according to phase, 68% of the genes were found to peak during estimated subjective day, 32% during estimated subjective night, with a tendency to peak at a phase corresponding to anticipation of dawn or dusk

Conserved Expression of the Glutamate NMDA Receptor 1 Subunit Splice Variants during the Development of the Siberian Hamster Suprachiasmatic Nucleus

Glutamate neurotransmission and the N-methyl-D-aspartate receptor (NMDAR) are central to photic signaling to the master circadian pacemaker located in the hypothalamic suprachiasmatic nucleus (SCN). NMDARs also play important roles in brain development including visual input circuits. The functional NMDAR is comprised of multiple subunits, but each requiring the NR1 subunit for normal activity. The NR1 can be alternatively spliced to produce isoforms that confer different functional properties on the NMDAR. The SCN undergoes extensive developmental changes during postnatal life, including synaptogenesis and acquisition of photic signaling. These changes are especially important in the highly photoperiodic Siberian hamster, in which development of sensitivity to photic cues within the SCN could impact early physiological programming. In this study we examined the expression of NR1 isoforms in the hamster at different developmental ages. Gene expression in the forebrain was quantified by in situ hybridization using oligonucleotide probes specific to alternatively spliced regions of the NR1 heteronuclear mRNA, including examination of anterior hypothalamus, piriform cortex, caudate-putamen, thalamus and hippocampus. Gene expression analysis within the SCN revealed the absence of the N1 cassette, the presence of the C2 cassette alone and the combined absence of C1 and C2 cassettes, indicating that the dominant splice variants are NR1-2a and NR1-4a. Whilst we observe changes at different developmental ages in levels of NR1 isoform probe hybridization in various forebrain structures, we find no significant changes within the SCN. This suggests that a switch in NR1 isoform does not underlie or is not produced by developmental changes within the hamster SCN. Consistency of the NR1 isoforms would ensure that the response of the SCN cells to photic signals remains stable throughout life, an important aspect of the function of the SCN as a responder to environmental changes in quality/quantity of light over the circadian day and annual cycle

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them

Changing glucocorticoid action:11β-hydroxysteroid dehydrogenase type 1 in acute and chronic inflammation

AbstractSince the discovery of cortisone in the 1940s and its early success in treatment of rheumatoid arthritis, glucocorticoids have remained the mainstay of anti-inflammatory therapies. However, cortisone itself is intrinsically inert. To be effective, it requires conversion to cortisol, the active glucocorticoid, by the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1). Despite the identification of 11β-HSD in liver in 1953 (which we now know to be 11β-HSD1), its physiological role has been little explored until recently. Over the past decade, however, it has become apparent that 11β-HSD1 plays an important role in shaping endogenous glucocorticoid action. Acute inflammation is more severe with 11β-HSD1-deficiency or inhibition, yet in some inflammatory settings such as obesity or diabetes, 11β-HSD1-deficiency/inhibition is beneficial, reducing inflammation. Current evidence suggests both beneficial and detrimental effects may result from 11β-HSD1 inhibition in chronic inflammatory disease. Here we review recent evidence pertaining to the role of 11β-HSD1 in inflammation.This article is part of a Special Issue entitled ‘CSR 2013’

Guidelines for Genome-Scale Analysis of Biological Rhythms

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding ‘big data’ that is conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them