Endothelial nitric oxide synthase gene polymorphism (Glu298Asp) and development of pre-eclampsia: a case-control study and a meta-analysis

BACKGROUND: Pre-eclampsia is thought to have an important genetic component. Recently, pre-eclampsia has been associated in some studies with carriage of a common eNOS gene Glu298Asp polymorphism, a variant that leads to the replacement of glutamic acid by aspartic acid at codon 298. METHOD: Healthy women with singleton pregnancies were recruited from 7 district general hospitals in London, UK. Women at high risk of pre-eclampsia were screened by uterine artery Doppler velocimetry at 22–24 weeks of gestation and maternal blood was obtained to genotype the eNOS Glu298Asp polymorphism. Odds ratios (OR) and 95%CI, using logistic regression methods, were obtained to evaluate the association between the Glu298Asp polymorphism and pre-eclampsia. A meta-analysis was then undertaken of all published studies up to November 2005 examining the association of eNOS Glu298Asp genotype and pre-eclampsia. RESULTS: 89 women with pre-eclampsia and 349 controls were included in the new study. The Glu298Asp polymorphism in a recessive model was not significantly associated with pre-eclampsia (adjusted-OR: 0.83 [95%CI: 0.30–2.25]; p = 0.7). In the meta-analysis, under a recessive genetic model (1129 cases & 2384 controls) women homozygous for the Asp298 allele were not at significantly increased risk of pre-eclampsia (OR: 1.28 [95%CI: 0.76–2.16]; p = 0.34). A dominant model (1334 cases & 2894 controls) was associated with no increase of risk of pre-eclampsia for women carriers of the Asp298 allele (OR: 1.12 [95%CI: 0.84–1.49]; p = 0.42). CONCLUSION: From the data currently available, the eNOS Glu298Asp polymorphism is not associated with a significant increased risk of pre-eclampsia. However, published studies have been underpowered, much larger studies are needed to confirm or refute a realistic genotypic risk of disease, but which might contribute to many cases of pre-eclampsia in the population

Physician perceptions of primary prevention: qualitative base for the conceptual shaping of a practice intervention tool

BACKGROUND: A practice intervention must have its basis in an understanding of the physician and practice to secure its benefit and relevancy. We used a formative process to characterize primary care physician attitudes, needs, and practice obstacles regarding primary prevention. The characterization will provide the conceptual framework for the development of a practice tool to facilitate routine delivery of primary preventive care. METHODS: A focus group of primary care physician Opinion Leaders was audio-taped, transcribed, and qualitatively analyzed to identify emergent themes that described physicians' perceptions of prevention in daily practice. RESULTS: The conceptual worth of primary prevention, including behavioral counseling, was high, but its practice was significantly countered by the predominant clinical emphasis on and rewards for secondary care. In addition, lack of health behavior training, perceived low self-efficacy, and patient resistance to change were key deterrents to primary prevention delivery. Also, the preventive focus in primary care is not on cancer, but on predominant chronic nonmalignant conditions. CONCLUSIONS: The success of the future practice tool will be largely dependent on its ability to "fit" primary prevention into the clinical culture of diagnoses and treatment sustained by physicians, patients, and payers. The tool's message output must be formatted to facilitate physician delivery of patient-tailored behavioral counseling in an accurate, confident, and efficacious manner. Also, the tool's health behavior messages should be behavior-specific, not disease-specific, to draw on shared risk behaviors of numerous diseases and increase the likelihood of perceived salience and utility of the tool in primary care

Use of different RT-QuIC substrates for detecting CWD prions in the brain of Norwegian cervids

Chronic wasting disease (CWD) is a highly contagious prion disease affecting captive and free-ranging cervid populations. CWD has been detected in United States, Canada, South Korea and, most recently, in Europe (Norway, Finland and Sweden). Animals with CWD release infectious prions in the environment through saliva, urine and feces sustaining disease spreading between cervids but also potentially to other non-cervids ruminants (e.g. sheep, goats and cattle). In the light of these considerations and due to CWD unknown zoonotic potential, it is of utmost importance to follow specific surveillance programs useful to minimize disease spreading and transmission. The European community has already in place specific surveillance measures, but the traditional diagnostic tests performed on nervous or lymphoid tissues lack sensitivity. We have optimized a Real-Time Quaking-Induced Conversion (RT-QuIC) assay for detecting CWD prions with high sensitivity and specificity to try to overcome this problem. In this work, we show that bank vole prion protein (PrP) is an excellent substrate for RT-QuIC reactions, enabling the detection of trace-amounts of CWD prions, regardless of prion strain and cervid species. Beside supporting the traditional diagnostic tests, this technology could be exploited for detecting prions in peripheral tissues from live animals, possibly even at preclinical stages of the disease

Assessing Computational Methods of Cis-Regulatory Module Prediction

Computational methods attempting to identify instances of cis-regulatory modules (CRMs) in the genome face a challenging problem of searching for potentially interacting transcription factor binding sites while knowledge of the specific interactions involved remains limited. Without a comprehensive comparison of their performance, the reliability and accuracy of these tools remains unclear. Faced with a large number of different tools that address this problem, we summarized and categorized them based on search strategy and input data requirements. Twelve representative methods were chosen and applied to predict CRMs from the Drosophila CRM database REDfly, and across the human ENCODE regions. Our results show that the optimal choice of method varies depending on species and composition of the sequences in question. When discriminating CRMs from non-coding regions, those methods considering evolutionary conservation have a stronger predictive power than methods designed to be run on a single genome. Different CRM representations and search strategies rely on different CRM properties, and different methods can complement one another. For example, some favour homotypical clusters of binding sites, while others perform best on short CRMs. Furthermore, most methods appear to be sensitive to the composition and structure of the genome to which they are applied. We analyze the principal features that distinguish the methods that performed well, identify weaknesses leading to poor performance, and provide a guide for users. We also propose key considerations for the development and evaluation of future CRM-prediction methods

Chance and necessity in the genome evolution of endosymbiotic bacteria of insects

[EN] An open question in evolutionary biology is how does the selection¿drift balance determine the fates of biological interactions. We searched for signatures of selection and drift in genomes of five endosymbiotic bacterial groups known to evolve under strong genetic drift. Although most genes in endosymbiotic bacteria showed evidence of relaxed purifying selection, many genes in these bacteria exhibited stronger selective constraints than their orthologs in free-living bacterial relatives. Remarkably, most of these highly constrained genes had no role in the host¿symbiont interactions but were involved in either buffering the deleterious consequences of drift or other host-unrelated functions, suggesting that they have either acquired new roles or their role became more central in endosymbiotic bacteria. Experimental evolution of Escherichia coli under strong genetic drift revealed remarkable similarities in the mutational spectrum, genome reduction patterns and gene losses to endosymbiotic bacteria of insects. Interestingly, the transcriptome of the experimentally evolved lines showed a generalized deregulation of the genome that affected genes encoding proteins involved in mutational buffering, regulation and amino acid biosynthesis, patterns identical to those found in endosymbiotic bacteria. Our results indicate that drift has shaped endosymbiotic associations through a change in the functional landscape of bacterial genes and that the host had only a small role in such a shiftThis work was supported by Science Foundation Ireland (12/IP/1637) and grants from the Spanish Ministerio de Economia y Competitividad (MINECO-FEDER; BFU2012-36346 and BFU2015-66073-P) to MAF. DAP and CT were supported by Juan de la Cierva fellowships from MINECO (references: JCI-2011-11089 and JCA-2012-14056, respectively). DAP is supported by funds from the University of Nevada, Reno, NV, USA.Sabater-Muñoz, B.; Toft, C.; Alvarez-Ponce, D.; Fares Riaño, MA. (2017). Chance and necessity in the genome evolution of endosymbiotic bacteria of insects. The ISME Journal. 11(6):1291-1304. https://doi.org/10.1038/ismej.2017.18S12911304116Aguilar-Rodriguez J, Sabater-Munoz B, Montagud-Martinez R, Berlanga V, Alvarez-Ponce D, Wagner A et al. (2016). The molecular chaperone DnaK is a source of mutational robustness. Genome Biol Evol 8: 2979–2991.Alvarez-Ponce D, Sabater-Munoz B, Toft C, Ruiz-Gonzalez MX, Fares MA . (2016). Essentiality is a strong determinant of protein rates of evolution during mutation accumulation experiments in Escherichia coli. Genome Biol Evol 8: 2914–2927.Anders S, Huber W . (2010). Differential expression analysis for sequence count data. Genome Biol 11: R106.Archibald J . (2014) One Plus One Equals One: Symbiosis and the Evolution of Complex Life. Oxford University Press: Oxford, UK.Aussel L, Loiseau L, Hajj Chehade M, Pocachard B, Fontecave M, Pierrel F et al. (2014). ubiJ, a new gene required for aerobic growth and proliferation in macrophage, is involved in coenzyme Q biosynthesis in Escherichia coli and Salmonella enterica serovar Typhimurium. J Bacteriol 196: 70–79.Baumann P, Baumann L, Clark MA . (1996). Levels of Buchnera aphidicola chaperonin groEL during growth of the aphid Schizaphis graminum. Curr Microbiol 32: 7.Benjamini Y, Yekutieli Y . (2005). False discovery rate controlling confidence intervals for selected parameters. J Am Stat Assoc 100: 10.Bennett GM, Moran NA . (2015). Heritable symbiosis: the advantages and perils of an evolutionary rabbit hole. Proc Natl Acad Sci USA 112: 10169–10176.Bermingham J, Rabatel A, Calevro F, Vinuelas J, Febvay G, Charles H et al. (2009). Impact of host developmental age on the transcriptome of the symbiotic bacterium Buchnera aphidicola in the pea aphid (Acyrthosiphon pisum. Appl Environ Microbiol 75: 7294–7297.Bogumil D, Dagan T . (2010). Chaperonin-dependent accelerated substitution rates in prokaryotes. Genome Biol Evol 2: 602–608.Carbon S, Ireland A, Mungall CJ, Shu S, Marshall B, Lewis S et al. (2009). AmiGO: online access to ontology and annotation data. Bioinformatics 25: 288–289.Chen Z, Wang Y, Li Y, Li Y, Fu N, Ye J et al. (2012). Esre: a novel essential non-coding RNA in Escherichia coli. FEBS Lett 586: 1195–1200.Clark JW, Hossain S, Burnside CA, Kambhampati S . (2001). Coevolution between a cockroach and its bacterial endosymbiont: a biogeographical perspective. Proc Biol Sci 268: 393–398.Dale C, Wang B, Moran N, Ochman H . (2003). Loss of DNA recombinational repair enzymes in the initial stages of genome degeneration. Mol Biol Evol 20: 1188–1194.Deatherage DE, Barrick JE . (2014). Identification of mutations in laboratory-evolved microbes from next-generation sequencing data using breseq. Methods Mol Biol 1151: 165–188.Douglas AE . (2003). The nutritional physiology of aphids. Adv Insect Physiol 31: 68.Fares MA, Barrio E, Sabater-Munoz B, Moya A . (2002a). The evolution of the heat-shock protein GroEL from Buchnera, the primary endosymbiont of aphids, is governed by positive selection. Mol Biol Evol 19: 1162–1170.Fares MA, Ruiz-Gonzalez MX, Moya A, Elena SF, Barrio E . (2002b). Endosymbiotic bacteria: groEL buffers against deleterious mutations. Nature 417: 398.Gancedo C, Flores CL, Gancedo JM . (2016). The expanding landscape of moonlighting proteins in yeasts. Microbiol Mol Biol Rev 80: 765–777.Gerardo NM, Altincicek B, Anselme C, Atamian H, Barribeau SM, de Vos M et al. (2010). Immunity and other defenses in pea aphids, Acyrthosiphon pisum. Genome Biol 11: R21.Gomez-Valero L, Latorre A, Silva FJ . (2004). The evolutionary fate of nonfunctional DNA in the bacterial endosymbiont Buchnera aphidicola. Mol Biol Evol 21: 2172–2181.Gomez-Valero L, Silva FJ, Christophe Simon J, Latorre A . (2007). Genome reduction of the aphid endosymbiont Buchnera aphidicola in a recent evolutionary time scale. Gene 389: 87–95.Gonzalez-Domenech CM, Belda E, Patino-Navarrete R, Moya A, Pereto J, Latorre A . (2012). Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches. BMC Microbiol 12 (Suppl 1): S5.Hansen AK, Moran NA . (2011). Aphid genome expression reveals host-symbiont cooperation in the production of amino acids. Proc Natl Acad Sci USA 108: 2849–2854.Hansen AK, Moran NA . (2014). The impact of microbial symbionts on host plant utilization by herbivorous insects. Mol Ecol 23: 1473–1496.Henderson B, Fares MA, Lund PA . (2013). Chaperonin 60: a paradoxical, evolutionarily conserved protein family with multiple moonlighting functions. Biol Rev Camb Philos Soc 88: 955–987.Humphreys NJ, Douglas AE . (1997). Partitioning of symbiotic bacteria between generations of an insect: a quantitative study of a Buchnera sp. in the pea aphid (Acyrthosiphon pisum reared at different temperatures. Appl Environ Microbiol 63: 3294–3296.International Aphid Genomics Consortium. (2010). Genome sequence of the pea aphid Acyrthosiphon pisum. PLoS Biol 8: e1000313.Kadibalban AS, Bogumil D, Landan G, Dagan T . (2016). DnaK-dependent accelerated evolutionary rate in prokaryotes. Genome Biol Evol 8: 1590–1599.Katoh K, Standley DM . (2013). MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol 30: 772–780.Kelkar YD, Ochman H . (2013). Genome reduction promotes increase in protein functional complexity in bacteria. Genetics 193: 303–307.Koga R, Meng XY, Tsuchida T, Fukatsu T . (2012). Cellular mechanism for selective vertical transmission of an obligate insect symbiont at the bacteriocyte-embryo interface. Proc Natl Acad Sci USA 109: E1230–E1237.Kuo CH, Moran NA, Ochman H . (2009). The consequences of genetic drift for bacterial genome complexity. Genome Res 19: 1450–1454.Kuo CH, Ochman H . (2009). Deletional bias across the three domains of life. Genome Biol Evol 1: 145–152.Law R, Lewis DH . (1983). Biotic environments and the maintenance of sex-some evidence from mutualistic symbioses. Biol J Linnean Soc 20: 28.Liu XD, Xie L, Wei Y, Zhou X, Jia B, Liu J et al. (2014). Abiotic stress resistance, a novel moonlighting function of ribosomal protein RPL44 in the halophilic fungus Aspergillus glaucus. Appl Environ Microbiol 80: 4294–4300.Lohse M, Bolger AM, Nagel A, Fernie AR, Lunn JE, Stitt M et al. (2012). RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Res 40: W622–W627.Macdonald SJ, Lin GG, Russell CW, Thomas GH, Douglas AE . (2012). The central role of the host cell in symbiotic nitrogen metabolism. Proc Biol Sci 279: 2965–2973.McClure R, Balasubramanian D, Sun Y, Bobrovskyy M, Sumby P, Genco CA et al. (2013). Computational analysis of bacterial RNA-Seq data. Nucleic Acids Res 41: e140.McCutcheon JP, Moran NA . (2012). Extreme genome reduction in symbiotic bacteria. Nat Rev Microbiol 10: 13–26.McFall-Ngai M, Hadfield MG, Bosch TC, Carey HV, Domazet-Loso T, Douglas AE et al. (2013). Animals in a bacterial world, a new imperative for the life sciences. Proc Natl Acad Sci USA 110: 3229–3236.Mira A, Ochman H, Moran NA . (2001). Deletional bias and the evolution of bacterial genomes. Trends Genet 17: 589–596.Moran NA . (1996). Accelerated evolution and Muller's rachet in endosymbiotic bacteria. Proc Natl Acad Sci USA 93: 2873–2878.Moran NA, Dunbar HE, Wilcox JL . (2005). Regulation of transcription in a reduced bacterial genome: nutrient-provisioning genes of the obligate symbiont Buchnera aphidicola. J Bacteriol 187: 4229–4237.Moran NA, McCutcheon JP, Nakabachi A . (2008). Genomics and evolution of heritable bacterial symbionts. Annu Rev Genet 42: 165–190.Moran NA, McLaughlin HJ, Sorek R . (2009). The dynamics and time scale of ongoing genomic erosion in symbiotic bacteria. Science 323: 379–382.Nakabachi A, Ishida K, Hongoh Y, Ohkuma M, Miyagishima SY . (2014). Aphid gene of bacterial origin encodes a protein transported to an obligate endosymbiont. Curr Biol 24: R640–R641.Nilsson AI, Koskiniemi S, Eriksson S, Kugelberg E, Hinton JC, Andersson DI . (2005). Bacterial genome size reduction by experimental evolution. Proc Natl Acad Sci USA 102: 12112–12116.Patino-Navarrete R, Moya A, Latorre A, Pereto J . (2013). Comparative genomics of Blattabacterium cuenoti: the frozen legacy of an ancient endosymbiont genome. Genome Biol Evol 5: 351–361.Pettersson ME, Berg OG . (2007). Muller's ratchet in symbiont populations. Genetica 130: 199–211.Price DR, Feng H, Baker JD, Bavan S, Luetje CW, Wilson AC . (2014). Aphid amino acid transporter regulates glutamine supply to intracellular bacterial symbionts. Proc Natl Acad Sci USA 111: 320–325.Reyes-Prieto M, Vargas-Chavez C, Latorre A, Moya A . (2015). SymbioGenomesDB: a database for the integration and access to knowledge on host-symbiont relationships. Database 2015: bav109 (1–8).Robinson MD, McCarthy DJ, Smyth GK . (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26: 139–140.Sabater-Muñoz B, Prats-Escriche M, Montagud-Martinez R, Lopez-Cerdan A, Toft C, Aguilar-Rodriguez J et al. (2015). Fitness trade-offs determine the role of the molecular chaperonin groel in buffering mutations. Mol Biol Evol 32: 2681–2693.Schlicker A, Domingues FS, Rahnenfuhrer J, Lengauer T . (2006). A new measure for functional similarity of gene products based on Gene Ontology. BMC Bioinformatics 7: 302.Shigenobu S, Watanabe H, Hattori M, Sakaki Y, Ishikawa H . (2000). Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp. APS. Nature 407: 81–86.Supek F, Bosnjak M, Skunca N, Smuc T . (2011). REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE 6: e21800.Tamas I, Klasson L, Canback B, Naslund AK, Eriksson AS, Wernegreen JJ et al. (2002). 50 million years of genomic stasis in endosymbiotic bacteria. Science 296: 2376–2379.Toft C, Fares MA . (2008). The evolution of the flagellar assembly pathway in endosymbiotic bacterial genomes. Mol Biol Evol 25: 2069–2076.van Ham RC, Kamerbeek J, Palacios C, Rausell C, Abascal F, Bastolla U et al. (2003). Reductive genome evolution in Buchnera aphidicola. Proc Natl Acad Sci USA 100: 581–586.Wernegreen JJ . (2002). Genome evolution in bacterial endosymbionts of insects. Nat Rev Genet 3: 850–861.Wernegreen JJ . (2011). Reduced selective constraint in endosymbionts: elevation in radical amino acid replacements occurs genome-wide. PLoS One 6: e28905.Williams TA, Fares MA . (2010). The effect of chaperonin buffering on protein evolution. Genome Biol Evol 2: 609–619.Yang Z . (2007). PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24: 1586–1591

A Novel Role for MAPKAPK2 in Morphogenesis during Zebrafish Development

One of the earliest morphogenetic processes in the development of many animals is epiboly. In the zebrafish, epiboly ensues when the animally localized blastoderm cells spread, thin over, and enclose the vegetally localized yolk. Only a few factors are known to function in this fundamental process. We identified a maternal-effect mutant, betty boop (bbp), which displays a novel defect in epiboly, wherein the blastoderm margin constricts dramatically, precisely when half of the yolk cell is covered by the blastoderm, causing the yolk cell to burst. Whole-blastoderm transplants and mRNA microinjection rescue demonstrate that Bbp functions in the yolk cell to regulate epiboly. We positionally cloned the maternal-effect bbp mutant gene and identified it as the zebrafish homolog of the serine-threonine kinase Mitogen Activated Protein Kinase Activated Protein Kinase 2, or MAPKAPK2, which was not previously known to function in embryonic development. We show that the regulation of MAPKAPK2 is conserved and p38 MAP kinase functions upstream of MAPKAPK2 in regulating epiboly in the zebrafish embryo. Dramatic alterations in calcium dynamics, together with the massive marginal constrictive force observed in bbp mutants, indicate precocious constriction of an F-actin network within the yolk cell, which first forms at 50% epiboly and regulates epiboly progression. We show that MAPKAPK2 activity and its regulator p38 MAPK function in the yolk cell to regulate the process of epiboly, identifying a new pathway regulating this cell movement process. We postulate that a p38 MAPKAPK2 kinase cascade modulates the activity of F-actin at the yolk cell margin circumference allowing the gradual closure of the blastopore as epiboly progresses

Tracing the Origin of the Fungal α1 Domain Places Its Ancestor in the HMG-Box Superfamily: Implication for Fungal Mating-Type Evolution

BACKGROUND: Fungal mating types in self-incompatible Pezizomycotina are specified by one of two alternate sequences occupying the same locus on corresponding chromosomes. One sequence is characterized by a gene encoding an HMG protein, while the hallmark of the other is a gene encoding a protein with an α1 domain showing similarity to the Matα1p protein of Saccharomyces cerevisiae. DNA-binding HMG proteins are ubiquitous and well characterized. In contrast, α1 domain proteins have limited distribution and their evolutionary origin is obscure, precluding a complete understanding of mating-type evolution in Ascomycota. Although much work has focused on the role of the S. cerevisiae Matα1p protein as a transcription factor, it has not yet been placed in any of the large families of sequence-specific DNA-binding proteins. METHODOLOGY/PRINCIPAL FINDINGS: We present sequence comparisons, phylogenetic analyses, and in silico predictions of secondary and tertiary structures, which support our hypothesis that the α1 domain is related to the HMG domain. We have also characterized a new conserved motif in α1 proteins of Pezizomycotina. This motif is immediately adjacent to and downstream of the α1 domain and consists of a core sequence Y-[LMIF]-x(3)-G-[WL] embedded in a larger conserved motif. CONCLUSIONS/SIGNIFICANCE: Our data suggest that extant α1-box genes originated from an ancestral HMG gene, which confirms the current model of mating-type evolution within the fungal kingdom. We propose to incorporate α1 proteins in a new subclass of HMG proteins termed MATα_HMG

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis