Comparing impact and cost-effectiveness of primary prevention strategies for lipid-lowering.

BACKGROUND: Lipid-lowering therapy is costly but effective at reducing coronary heart disease (CHD) risk. OBJECTIVE: To assess the cost-effectiveness and public health impact of Adult Treatment Panel III (ATP III) guidelines and compare with a range of risk- and age-based alternative strategies. DESIGN: The CHD Policy Model, a Markov-type cost-effectiveness model. DATA SOURCES: National surveys (1999 to 2004), vital statistics (2000), the Framingham Heart Study (1948 to 2000), other published data, and a direct survey of statin costs (2008). TARGET POPULATION: U.S. population age 35 to 85 years. Time Horizon: 2010 to 2040. PERSPECTIVE: Health care system. INTERVENTION: Lowering of low-density lipoprotein cholesterol with HMG-CoA reductase inhibitors (statins). OUTCOME MEASURE: Incremental cost-effectiveness. RESULTS OF BASE-CASE ANALYSIS: Full adherence to ATP III primary prevention guidelines would require starting (9.7 million) or intensifying (1.4 million) statin therapy for 11.1 million adults and would prevent 20,000 myocardial infarctions and 10,000 CHD deaths per year at an annual net cost of $3.6 billion ($42,000/QALY) if low-intensity statins cost $2.11 per pill. The ATP III guidelines would be preferred over alternative strategies if society is willing to pay $50,000/QALY and statins cost $1.54 to $2.21 per pill. At higher statin costs, ATP III is not cost-effective; at lower costs, more liberal statin-prescribing strategies would be preferred; and at costs less than $0.10 per pill, treating all persons with low-density lipoprotein cholesterol levels greater than 3.4 mmol/L (>130 mg/dL) would yield net cost savings. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the assumptions that LDL cholesterol becomes less important as a risk factor with increasing age and that little disutility results from taking a pill every day. LIMITATION: Randomized trial evidence for statin effectiveness is not available for all subgroups. CONCLUSION: The ATP III guidelines are relatively cost-effective and would have a large public health impact if implemented fully in the United States. Alternate strategies may be preferred, however, depending on the cost of statins and how much society is willing to pay for better health outcomes. FUNDING: Flight Attendants' Medical Research Institute and the Swanson Family Fund. The Framingham Heart Study and Framingham Offspring Study are conducted and supported by the National Heart, Lung, and Blood Institute.

Blocking VLDL secretion causes hepatic steatosis but does not affect peripheral lipid stores or insulin sensitivity in mice

The liver secretes triglyceride-rich VLDLs, and the triglycerides in these particles are taken up by peripheral tissues, mainly heart, skeletal muscle, and adipose tissue. Blocking hepatic VLDL secretion interferes with the delivery of liver-derived triglycerides to peripheral tissues and results in an accumulation of triglycerides in the liver. However, it is unclear how interfering with hepatic triglyceride secretion affects adiposity, muscle triglyceride stores, and insulin sensitivity. To explore these issues, we examined mice that cannot secrete VLDL [due to the absence of microsomal triglyceride transfer protein (Mttp) in the liver]. These mice exhibit markedly reduced levels of apolipoprotein B-100 in the plasma, along with reduced levels of triglycerides in the plasma. Despite the low plasma triglyceride levels, triglyceride levels in skeletal muscle were unaffected. Adiposity and adipose tissue triglyceride synthesis rates were also normal, and body weight curves were unaffected. Even though the blockade of VLDL secretion caused hepatic steatosis accompanied by increased ceramides and diacylglycerols in the liver, the mice exhibited normal glucose tolerance and were sensitive to insulin at the whole-body level, as judged by hyperinsulinemic euglycemic clamp studies. Normal hepatic glucose production and insulin signaling were also maintained in the fatty liver induced by Mttp deletion. Thus, blocking VLDL secretion causes hepatic steatosis without insulin resistance, and there is little effect on muscle triglyceride stores or adiposity

Association of the Epstein-Barr virus latent membrane protein 1 with lipid rafts is mediated through its N-terminal region.

The latent membrane protein 1 (LMP1) encoded by the Epstein-Barr virus acts like a constitutively activated receptor of the tumor necrosis factor receptor (TNFR) family and is enriched in lipid rafts. We showed that LMP1 is targeted to lipid rafts in transfected HEK 293 cells, and that the endogenous TNFR-associated factor 3 binds LMP1 and is recruited to lipid rafts upon LMP1 expression. An LMP1 mutant lacking the C-terminal 55 amino acids (Cdelta55) behaves like the wild-type (WT) LMP1 with respect to membrane localization. In contrast, a mutant with a deletion of the 25 N-terminal residues (Ndelta25) does not concentrate in lipid rafts but still binds TRAF3, demonstrating that cell localization of LMP1 was not crucial for TRAF3 localization. Moreover, Ndelta25 inhibited WT LMP1-mediated induction of the transcription factors NF-kappaB and AP-1. Morphological data indicate that Ndelta25 hampers WT LMP1 plasma membrane localization, thus blocking LMP1 function.

Structured RNAs in the ENCODE selected regions of the human genome.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Skeletal Muscle Mitochondrial and Lipid Droplet Volume Density: Validity of Electron Microscopy Point-counting Measurements

Mitochondrial (M) and lipid droplet (L) volume density (vd) are often used in exercise research. Vd is the volume of muscle occupied by M and L. The means of calculating these percents are accomplished by applying a grid to a 2D image taken with transmission electron microscopy; however, it is not known which grid best predicts these values. PURPOSE: To determine the grid with the least variability of Mvd and Lvd in human skeletal muscle. METHODS: Muscle biopsies were taken from vastus lateralis of 10 healthy adults, trained (N=6) and untrained (N=4). Samples of 5-10mg were fixed in 2.5% glutaraldehyde and embedded in EPON. Longitudinal sections of 60 nm were cut and 20 images were taken at random at 33,000x magnification. Vd was calculated as the number of times M or L touched two intersecting grid lines (called a point) divided by the total number of points using 3 different sizes of grids with squares of 1000x1000nm sides (corresponding to 1µm2), 500x500nm (0.25µm2) and 250x250nm (0.0625µm2). Statistics included coefficient of variation (CV), 1 way-BS ANOVA and spearman correlations. RESULTS: Mean age was 67 ± 4 yo, mean VO2peak 2.29 ± 0.70 L/min and mean BMI 25.1 ± 3.7 kg/m2. Mean Mvd was 6.39% ± 0.71 for the 1000nm squares, 6.01% ± 0.70 for the 500nm and 6.37% ± 0.80 for the 250nm. Lvd was 1.28% ± 0.03 for the 1000nm, 1.41% ± 0.02 for the 500nm and 1.38% ± 0.02 for the 250nm. The mean CV of the three grids was 6.65% ±1.15 for Mvd with no significant differences between grids (P>0.05). Mean CV for Lvd was 13.83% ± 3.51, with a significant difference between the 1000nm squares and the two other grids (P<0.05). The 500nm squares grid showed the least variability between subjects. Mvd showed a positive correlation with VO2peak (r = 0.89, p < 0.05) but not with weight, height, or age. No correlations were found with Lvd. CONCLUSION: Different size grids have different variability in assessing skeletal muscle Mvd and Lvd. The grid size of 500x500nm (240 points) was more reliable than 1000x1000nm (56 points). 250x250nm (1023 points) did not show better reliability compared with the 500x500nm, but was more time consuming. Thus, choosing a grid with square size of 500x500nm seems the best option. This is particularly relevant as most grids used in the literature are either 100 points or 400 points without clear information on their square size.

Stochastic demography and the neutral substitution rate in class-structured populations.

The neutral rate of allelic substitution is analyzed for a class-structured population subject to a stationary stochastic demographic process. The substitution rate is shown to be generally equal to the effective mutation rate, and under overlapping generations it can be expressed as the effective mutation rate in newborns when measured in units of average generation time. With uniform mutation rate across classes the substitution rate reduces to the mutation rate.

Caspase-8 and c-FLIPL associate in lipid rafts with NF-kappaB adaptors during T cell activation.

Humans and mice lacking functional caspase-8 in T cells manifest a profound immunodeficiency syndrome due to defective T cell antigen receptor (TCR)-induced NF-kappaB signaling and proliferation. It is unknown how caspase-8 is activated following T cell stimulation, and what is the caspase-8 substrate(s) that is necessary to initiate T cell cycling. We observe that following TCR ligation, a small portion of total cellular caspase-8 and c-FLIP(L) rapidly migrate to lipid rafts where they associate in an active caspase complex. Activation of caspase-8 in lipid rafts is followed by rapid cleavage of c-FLIP(L) at a known caspase-8 cleavage site. The active caspase.c-FLIP complex forms in the absence of Fas (CD95/APO1) and associates with the NF-kappaB signaling molecules RIP1, TRAF2, and TRAF6, as well as upstream NF-kappaB regulators PKC theta, CARMA1, Bcl-10, and MALT1, which connect to the TCR. The lack of caspase-8 results in the absence of MALT1 and Bcl-10 in the active caspase complex. Consistent with this observation, inhibition of caspase activity attenuates NF-kappaB activation. The current findings define a link among TCR, caspases, and the NF-kappaB pathway that occurs in a sequestered lipid raft environment in T cells.

Lipid composition of fingermark residue and donor classification using GC/MS

Lipids available in fingermark residue represent important targets for enhancement and dating techniques. While it is well known that lipid composition varies among fingermarks of the same donor (intra-variability) and between fingermarks of different donors (inter-variability), the extent of this variability remains uncharacterised. Thus, this worked aimed at studying qualitatively and quantitatively the initial lipid composition of fingermark residue of 25 different donors. Among the 104 detected lipids, 43 were reported for the first time in the literature. Furthermore, palmitic acid, squalene, cholesterol, myristyl myristate and myristyl myristoleate were quantified and their correlation within fingermark residue was highlighted. Ten compounds were then selected and further studied as potential targets for dating or enhancement techniques. It was shown that their relative standard deviation was significantly lower for the intra-variability than for the inter-variability. Moreover, the use of data pretreatments could significantly reduce this variability. Based on these observations, an objective donor classification model was proposed. Hierarchical cluster analysis was conducted on the pre-treated data and the fingermarks of the 25 donors were classified into two main groups, corresponding to "poor" and "rich" lipid donors. The robustness of this classification was tested using fingermark replicates of selected donors. 86% of these replicates were correctly classified, showing the potential of such a donor classification model for research purposes in order to select representative donors based on compounds of interest.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Aging of myelinating glial cells predominantly affects lipid metabolism and immune response pathways.

Both the central and the peripheral nervous systems are prone to multiple age-dependent neurological deficits, often attributed to still unknown alterations in the function of myelinating glia. To uncover the biological processes affected in glial cells by aging, we analyzed gene expression of the Schwann cell-rich mouse sciatic nerve at 17 time points throughout life, from day of birth until senescence. By combining these data with the gene expression data of myelin mouse mutants carrying deletions of either Pmp22, SCAP, or Lpin1, we found that the majority of age-related transcripts were also affected in myelin mutants (54.4%) and were regulated during PNS development (59.5%), indicating a high level of overlap in implicated molecular pathways. The expression profiles in aging copied the direction of transcriptional changes observed in neuropathy models; however, they had the opposite direction when compared with PNS development. The most significantly altered biological processes in aging involved the inflammatory/immune response and lipid metabolism. Interestingly, both these pathways were comparably changed in the aging optic nerve, suggesting that similar biological processes are affected in aging of glia-rich parts of the central and peripheral nervous systems. Our comprehensive comparison of gene expression in three distinct biological conditions including development, aging, and myelin disease thus revealed a previously unanticipated relationship among themselves and identified lipid metabolism and inflammatory/immune response pathways as potential therapeutical targets to prevent or delay so far incurable age-related and inherited forms of neuropathies.

An infrared reflection-absorption spectroscopic (IRRAS) study of the interaction of lipid A and lipopolysaccharide Re with endotoxin-binding proteins.

Lipopolysaccharides (LPS, endotoxins) are main constituents of the outer membranes of Gram-negative bacteria, with the 'endotoxic principle' lipid A anchoring LPS into the membrane. When LPS is removed from the bacteria by the action of the immune system or simply by cell dividing, it may interact strongly with immunocompetent cells such as mononuclear cells. This interaction may lead, depending on the LPS concentration, to beneficial (at low) or pathophysiological (at high concentrations) reactions, the latter frequently causing the septic shock syndrome. There is a variety of endogenous LPS-binding proteins. To this class belong lactoferrin (LF) and hemoglobin (Hb), which have been shown to suppress and enhance the LPS-induced cytokine secretion in mononuclear cells, respectively. To elucidate the interaction mechanisms of endotoxins with these proteins, we have investigated in an infrared reflection-absorption spectroscopy (IRRAS) study the interaction of LPS or lipid A monolayers at the air/water interface with LF and Hb proteins, injected into the aqueous subphase. The data are clearly indicative of completely different interaction mechanisms of the endotoxins with the proteins, with the LF acting only at the LPS backbone, whereas Hb incorporates into the lipid monolayer. These data allow an understanding of the different reactivities in the biomedicinal systems.

CARMA1 is a critical lipid raft-associated regulator of TCR-induced NF-kappa B activation.

CARMA1 is a lymphocyte-specific member of the membrane-associated guanylate kinase (MAGUK) family of scaffolding proteins, which coordinate signaling pathways emanating from the plasma membrane. CARMA1 interacts with Bcl10 via its caspase-recruitment domain (CARD). Here we investigated the role of CARMA1 in T cell activation and found that T cell receptor (TCR) stimulation induced a physical association of CARMA1 with the TCR and Bcl10. We found that CARMA1 was constitutively associated with lipid rafts, whereas cytoplasmic Bcl10 translocated into lipid rafts upon TCR engagement. A CARMA1 mutant, defective for Bcl10 binding, had a dominant-negative (DN) effect on TCR-induced NF-kappa B activation and IL-2 production and on the c-Jun NH(2)-terminal kinase (Jnk) pathway when the TCR was coengaged with CD28. Together, our data show that CARMA1 is a critical lipid raft-associated regulator of TCR-induced NF-kappa B activation and CD28 costimulation-dependent Jnk activation.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.