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Sample records for sp-d deficiency infers

  1. Surfactant protein D (SP-D) deficiency is attenuated in humanised mice expressing the Met(11)Thr short nucleotide polymorphism of SP-D: implications for surfactant metabolism in the lung

    PubMed Central

    Knudsen, Lars; Ochs, Katharina; Boxler, Laura; Tornoe, Ida; Lykke-Sorensen, Grith; Mackay, Rose-Marie; Clark, Howard W; Holmskov, Uffe; Ochs, Matthias; Madsen, Jens

    2013-01-01

    Surfactant protein D (SP-D) is part of the innate immune system involved in lung homeostasis. SP-D knockout mice show accumulations of foamy alveolar macrophages, alveolar lipoproteinosis and pulmonary emphysema. Three single nucleotide polymorphisms (SNPs) have been described in the coding sequence of the human SP-D gene SFTPD. Clinical studies showed that the SNP SFTPD with a nucleotide change from A to C resulting in a Met to Thr substitution at position 11 in the protein (Met(11)Thr), is relevant. This study set out to create a humanised mouse model of the Met(11)Thr SNP. Transgenic mice lines expressing either Met(11) or Thr(11) SP-D under the control of the ubiquitously expressed pROSA26 promoter in C57Bl/6 SP-D deficient mice (DKO) was created. Both Met(11) (142 ± 52 ng mL−1) and Thr(11) (228 ± 76 ng mL−1) mice lines expressed human SP-D at almost similar levels. According to the literature this was within the range of SP-D levels found in wildtype (WT) mice (253 ± 22 ng mL−1). Met(11) or Thr(11) SP-D in serum from transgenic mice bound maltose in a calcium-dependent manner, and binding was inhibited in the presence of EDTA or maltose. Bronchoalveolar lavage showed for both transgenic mice lines complementation of the DKO phenotype by restoring cell counts, phospholipid levels and protein content back to WT levels. Cytospins of BAL pellet cells showed a resemblance to WT but both mice lines showed some foamy alveolar macrophages. The stereological analysis showed for none of the mice lines a complete abrogation of emphysematous alterations. However, both Met(11) and Thr(11) mice lines were partially reverted back to a WT phenotype when compared with DKO mice, indicating important effects on surfactant metabolism in vivo. PMID:24111992

  2. Mice deficient in surfactant protein A (SP-A) and SP-D or in TLR2 manifest delayed parturition and decreased expression of inflammatory and contractile genes.

    PubMed

    Montalbano, Alina P; Hawgood, Samuel; Mendelson, Carole R

    2013-01-01

    Previously we obtained compelling evidence that the fetus provides a critical signal for the initiation of term labor through developmental induction of surfactant protein (SP)-A expression by the fetal lung and secretion into amniotic fluid (AF). We proposed that interactions of AF macrophage (Mϕ) Toll-like receptors (TLRs) with SP-A, at term, or bacterial components, at preterm, result in their activation and migration to the pregnant uterus. Herein the timing of labor in wild-type (WT) C57BL/6 mice was compared with mice homozygous null for TLR2, SP-A, SP-D, or doubly deficient in SP-A and SP-D. Interestingly, TLR2(-/-) females manifested a significant (P < 0.001) delay in timing of labor compared with WT as well as reduced expression of the myometrial contraction-associated protein (CAP) gene, connexin-43, and Mϕ marker, F4/80, at 18.5 d postcoitum (dpc). Whereas in first pregnancies, SP-A(-/-), SP-D(-/-), and SP-A/D(-/-) females delivered at term (∼19.5 dpc), in second pregnancies, parturition was delayed by approximately 12 h in SP-A(-/-) (P = 0.07) and in SP-A/D(-/-) (P <0.001) females. Myometrium of SP-A/D(-/-) females expressed significantly lower levels of IL-1β, IL-6, and CAP genes, connexin-43, and oxytocin receptor at 18.5 dpc compared with WT. F4/80(+) AF Mϕs from TLR2(-/-) and SP-A/D(-/-) mice expressed significantly lower levels of both proinflammatory and antiinflammatory activation markers (e.g. IL-1β, IL-6, ARG1, YM1) compared with gestation-matched WT AF Mϕs. These novel findings suggest that the pulmonary collectins acting via TLR2 serve a modulatory role in the timing of labor; their relative impact may be dependent on parity.

  3. Mice Deficient in Surfactant Protein A (SP-A) and SP-D or in TLR2 Manifest Delayed Parturition and Decreased Expression of Inflammatory and Contractile Genes

    PubMed Central

    Montalbano, Alina P.; Hawgood, Samuel

    2013-01-01

    Previously we obtained compelling evidence that the fetus provides a critical signal for the initiation of term labor through developmental induction of surfactant protein (SP)-A expression by the fetal lung and secretion into amniotic fluid (AF). We proposed that interactions of AF macrophage (Mφ) Toll-like receptors (TLRs) with SP-A, at term, or bacterial components, at preterm, result in their activation and migration to the pregnant uterus. Herein the timing of labor in wild-type (WT) C57BL/6 mice was compared with mice homozygous null for TLR2, SP-A, SP-D, or doubly deficient in SP-A and SP-D. Interestingly, TLR2−/− females manifested a significant (P < 0.001) delay in timing of labor compared with WT as well as reduced expression of the myometrial contraction-associated protein (CAP) gene, connexin-43, and Mφ marker, F4/80, at 18.5 d postcoitum (dpc). Whereas in first pregnancies, SP-A−/−, SP-D−/−, and SP-A/D−/− females delivered at term (∼19.5 dpc), in second pregnancies, parturition was delayed by approximately 12 h in SP-A−/− (P = 0.07) and in SP-A/D−/− (P <0.001) females. Myometrium of SP-A/D−/− females expressed significantly lower levels of IL-1β, IL-6, and CAP genes, connexin-43, and oxytocin receptor at 18.5 dpc compared with WT. F4/80+ AF Mφs from TLR2−/− and SP-A/D−/− mice expressed significantly lower levels of both proinflammatory and antiinflammatory activation markers (e.g. IL-1β, IL-6, ARG1, YM1) compared with gestation-matched WT AF Mφs. These novel findings suggest that the pulmonary collectins acting via TLR2 serve a modulatory role in the timing of labor; their relative impact may be dependent on parity. PMID:23183169

  4. Surfactant protein (SP)-A and SP-D as antimicrobial and immunotherapeutic agents.

    PubMed

    Awasthi, Shanjana

    2010-06-01

    Surfactant protein (SP)-A and SP-D belong to the "Soluble C-type Lectin" family of proteins and are collectively known as "Collectins". Based on their ability to recognize pathogens and to regulate the host defense, SP-A and SP-D have been recently categorized as "Secretory Pathogen Recognition Receptors". SP-A and SP-D were first identified in the lung; the expression of SP-A and SP-D has also been observed at other mucosal surfaces, such as lacrimal glands, gastrointestinal mucosa, genitourinary epithelium and periodontal surfaces. Since the role of these proteins is not fully elucidated at other mucosal surfaces, the focus of this article is on lung-SP-A and SP-D. It has become clear from research studies performed over a number of years that SP-A and SP-D are critical for the maintenance of lung homeostasis and the regulation of host defense and inflammation. However, none of the surfactant preparations available for clinical use have SP-A or SP-D. A review is presented here on SP-A- and SP-D-deficiencies in lung diseases, the importance of the administration of SP-A and SP-D, and recent patents and research directions that may lead to the design of novel SP-A- or SP-D-based therapeutics and surfactants.

  5. Pimarane diterpenes from the Arctic fungus Eutypella sp. D-1.

    PubMed

    Lu, Xiao-Ling; Liu, Jing-Tang; Liu, Xiao-Yu; Gao, Yun; Zhang, Jianpeng; Jiao, Bing-Hua; Zheng, Heng

    2014-02-01

    Two new diterpenes, libertellenone G(1) and libertellenone H(2) were isolated from the fungus Eutypella sp. D-1 isolated from the soil of high latitude of Arctic, together with two known pimarane diterpenes (3-4). The structures of 1 and 2 were elucidated from spectroscopic data (nuclear magnetic resonance, mass spectrometry and infrared). These compounds were evaluated for cytotoxic activity against seven human tumor cell lines. Compound 2 showed a range of cytotoxicity between 3.31 and 44.1 μM. Compound 1 exhibited antibacterial activity against Escherichia coli, Bacillus subtilis and Staphylococcus aureus.

  6. Pesticide tolerance of Paenibacillus sp. D1 and its chitinase.

    PubMed

    Singh, Anil Kumar; Ghodke, Indrajeet; Chhatpar, H S

    2009-01-01

    Excessive use of pesticides in agriculture has led to several problems pertaining to loss of soil fertility and environmental degradation. Biological control agents offer the best alternative to reduce use of toxic pesticides. Paenibacillus sp. D1 isolated from the effluent treatment plant of a seafood processing industry exhibited broad spectrum tolerance towards a number of pesticides at concentrations higher than recommended for field applications. The isolate showed enhanced growth and chitinase production in the presence of some protectant fungicides. None of the tested demethylase inhibitor (DMI) fungicides inhibited growth and chitinase production except triadimefon. The isolate was also tolerant to most commonly used insecticides belonging to the organophosphate, carbamate and cyclodiene organochloride classes. Chitinase of Paenibacillus sp. D1 was found to be more tolerant than the organism itself and was highly stable in the presence of pesticides at the temperature under field conditions in Gujarat, India, i.e. 40 degrees C. This was suggestive of its potential in integrated pest management (IPM) to significantly reduce the use of harmful chemicals. To our knowledge this is the first extensive study on pesticide tolerance of the Paenibacillus species and its chitinase.

  7. Lung surfactant protein D (SP-D) response and regulation during acute and chronic lung injury.

    PubMed

    Gaunsbaek, Maria Quisgaard; Rasmussen, Karina Juhl; Beers, Michael F; Atochina-Vasserman, Elena N; Hansen, Soren

    2013-06-01

    Surfactant protein D (SP-D) is a collection that plays important roles in modulating host defense functions and maintaining phospholipid homeostasis in the lung. The aim of current study was to characterize comparatively the SP-D response in bronchoalveolar lavage (BAL) and serum in three murine models of lung injury, using a validated ELISA technology for estimation of SP-D levels. Mice were exposed to lipopolysaccharide, bleomycin, or Pneumocystis carinii (Pc) and sacrificed at different time points. In lipopolysaccharide-challenged mice, the level of SP-D in BAL increased within 6 h, peaked at 51 h (4,518 ng/ml), and returned to base level at 99 h (612 ng/ml). Serum levels of SP-D increased immediately (8.6 ng/ml), peaked at 51 h (16 ng/ml), and returned to base levels at 99 h (3.8 ng/ml). In a subacute bleomycin inflammation model, SP-D levels were 4,625 and 367 ng/ml in BAL and serum, respectively, 8 days after exposure. In a chronic Pc inflammation model, the highest level of SP-D was observed 6 weeks after inoculation, with BAL and serum levels of 1,868 and 335 ng/ml, respectively. We conclude that serum levels of SP-D increase during lung injury, with a sustained increment during chronic inflammation compared with acute inflammation. A quick upregulation of SP-D in serum in response to acute airway inflammation supports the notion that SP-D translocates from the airways into the vascular system, in favor of being synthesized systemically. The study also confirms the concept of using increased SP-D serum levels as a biomarker of especially chronic airway inflammation.

  8. Influence of sp-d hybridization on the electronic structure of Al-Mn alloys

    NASA Astrophysics Data System (ADS)

    Shukla, A. K.; Biswas, C.; Dhaka, R. S.; Das, S. C.; Krüger, P.; Barman, S. R.

    2008-05-01

    The influence of sp-d hybridization on the electronic structure of different Al-Mn alloys has been studied by photoelectron spectroscopy. Experimental evidence of a pseudogap in a crystalline binary Hume-Rothery alloy is provided. The pseudogap varies systematically with Mn concentration. The sp-d hybridization alone, even in the absence of Hume-Rothery mechanism, can produce the pseudogap. Existence of the pseudogap, suppression of the Mn2p satellite, and decrease in the Doniach-Šunjić asymmetry parameter are the consequences of the sp-d hybridization. An in situ method of preparing these alloys by annealing a Mn adlayer on Al(111) is presented.

  9. Influence of sp-d hybridization on the electronic structure of Al-Mn alloys

    SciTech Connect

    Shukla, A. K.; Biswas, C.; Dhaka, R. S.; Das, S. C.; Barman, S. R.; Krueger, P.

    2008-05-15

    The influence of sp-d hybridization on the electronic structure of different Al-Mn alloys has been studied by photoelectron spectroscopy. Experimental evidence of a pseudogap in a crystalline binary Hume-Rothery alloy is provided. The pseudogap varies systematically with Mn concentration. The sp-d hybridization alone, even in the absence of Hume-Rothery mechanism, can produce the pseudogap. Existence of the pseudogap, suppression of the Mn 2p satellite, and decrease in the Doniach-Sunjic asymmetry parameter are the consequences of the sp-d hybridization. An in situ method of preparing these alloys by annealing a Mn adlayer on Al(111) is presented.

  10. Interplay of Rashba and sp-d exchange couplings in magnetic 2DEGs

    NASA Astrophysics Data System (ADS)

    Mireles, Francisco; Freire, Henrique H. P.; Egues, J. Carlos

    2006-03-01

    In diluted magnetic semiconductor (DMS) quantum wells the sp-d exchange interaction between the itinerant conduction electrons in the well and the localized electrons in the d orbitals of the Mn impurities gives rise to interesting spin-dependent physics [1]. Recently, the interplay of the Rashba spin-orbit and the sp-d exchange interactions in Mn-based wells has been recognized via Shubnikov-de-Haas measurements [2]. While the Rashba spin-orbit has been extensively studied in non-magnetic 2DEGs, its role in DMS systems with a competing sp-d exchange interaction has not yet been addressed theoretically. In this work we present a k.p derivation of an effective Hamiltonian for a Mn-based quantum well with competing Rashba and sp-d interactions, and show numerical results for the magnetoresistance ρxx of typical magnetic 2DEGs using our effective Hamiltonian model. Our results shows interesting beating patterns of the ρxx as a function of the temperature and carrier density which suggests a significant interplay between the spin-orbit and sp-d exchange interactions, as a recent experiment observes [2]. [1] J. C. Egues, PRL 78, 4578 (1998); H. J. P. Freire and J. C. Egues, cond-mat/0412491. [2] Y. S. Gui et al. EPL. 65, 393 (2004).

  11. Surfactant Proteins SP-A and SP-D Modulate Uterine Contractile Events in ULTR Myometrial Cell Line

    PubMed Central

    Sotiriadis, Georgios; Dodagatta-Marri, Eswari; Kouser, Lubna; Alhamlan, Fatimah S.; Kishore, Uday; Karteris, Emmanouil

    2015-01-01

    Pulmonary surfactant proteins SP-A and SP-D are pattern recognition innate immune molecules. However, there is extrapulmonary existence, especially in the amniotic fluid and at the feto-maternal interface. There is sufficient evidence to suggest that SP-A and SP-D are involved in the initiation of labour. This is of great importance given that preterm birth is associated with increased mortality and morbidity. In this study, we investigated the effects of recombinant forms of SP-A and SP-D (rhSP-A and rhSP-D, the comprising of trimeric lectin domain) on contractile events in vitro, using a human myometrial cell line (ULTR) as an experimental model. Treatment with rhSP-A or rhSP-D increased the cell velocity, distance travelled and displacement by ULTR cells. rhSP-A and rhSP-D also affected the contractile response of ULTRs when grown on collagen matrices showing reduced surface area. We investigated this effect further by measuring contractility-associated protein (CAP) genes. Treatment with rhSP-A and rhSP-D induced expression of oxytocin receptor (OXTR) and connexin 43 (CX43). In addition, rhSP-A and rhSP-D were able to induce secretion of GROα and IL-8. rhSP-D also induced the expression of IL-6 and IL-6 Ra. We provide evidence that SP-A and SP-D play a key role in modulating events prior to labour by reconditioning the human myometrium and in inducing CAP genes and pro-inflammatory cytokines thus shifting the uterus from a quiescent state to a contractile one. PMID:26641881

  12. Common genetic variants of surfactant protein-D (SP-D) are associated with type 2 diabetes.

    PubMed

    Pueyo, Neus; Ortega, Francisco J; Mercader, Josep M; Moreno-Navarrete, José M; Sabater, Monica; Bonàs, Sílvia; Botas, Patricia; Delgado, Elías; Ricart, Wifredo; Martinez-Larrad, María T; Serrano-Ríos, Manuel; Torrents, David; Fernández-Real, José M

    2013-01-01

    Surfactant protein-D (SP-D) is a primordial component of the innate immune system intrinsically linked to metabolic pathways. We aimed to study the association of single nucleotide polymorphisms (SNPs) affecting SP-D with insulin resistance and type 2 diabetes (T2D). We evaluated a common genetic variant located in the SP-D coding region (rs721917, Met(31)Thr) in a sample of T2D patients and non-diabetic controls (n = 2,711). In a subset of subjects (n = 1,062), this SNP was analyzed in association with circulating SP-D concentrations, insulin resistance, and T2D. This SNP and others were also screened in the publicly available Genome Wide Association (GWA) database of the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC). We found the significant association of rs721917 with circulating SP-D, parameters of insulin resistance and T2D. Indeed, G carriers showed decreased circulating SP-D (p = 0.004), decreased fasting glucose (p = 0.0002), glycated hemoglobin (p = 0.0005), and 33% (p = 0.002) lower prevalence of T2D, estimated under a dominant model, especially among women. Interestingly, these differences remained significant after controlling for origin, age, gender, and circulating SP-D. Moreover, this SNP and others within the SP-D genomic region (i.e. rs10887344) were significantly associated with quantitative measures of glucose homeostasis, insulin sensitivity, and T2D, according to GWAS datasets from MAGIC. SP-D gene polymorphisms are associated with insulin resistance and T2D. These associations are independent of circulating SP-D concentrations.

  13. Lipopeptide biosurfactant production bacteria Acinetobacter sp. D3-2 and its biodegradation of crude oil.

    PubMed

    Bao, Mutai; Pi, Yongrui; Wang, Lina; Sun, Peiyan; Li, Yiming; Cao, Lixin

    2014-04-01

    In this work, a hydrocarbon-degrading bacterium D3-2 isolated from petroleum contaminated soil samples was investigated for its potential effect in biodegradation of crude oil. The strain was identified as Acinetobacter sp. D3-2 based on morphological, biochemical and phylogenetic analysis. The optimum environmental conditions for growth of the bacteria were determined to be pH 8.0, with a NaCl concentration of 3.0% (w/v) at 30 °C. Acinetobacter sp. D3-2 could utilize various hydrocarbon substrates as the sole carbon and energy source. From this study, we also found that the strain had the ability to produce biosurfactant, with the production of 0.52 g L(-1). The surface tension of the culture broth was decreased from 48.02 to 26.30 mN m(-1). The biosurfactant was determined to contain lipopeptide compounds based on laboratory analyses. By carrying out a crude oil degradation assay in an Erlenmeyer flask experiment and analyzing the hydrocarbon removal rate using gas chromatography, we found that Acinetobacter sp. D3-2 could grow at 30 °C in 3% NaCl solution with a preferable ability to degrade 82% hydrocarbons, showing that bioremediation does occur and plays a profound role during the oil reparation process.

  14. Pulmonary surfactant protein SP-D opsonises carbon nanotubes and augments their phagocytosis and subsequent pro-inflammatory immune response.

    PubMed

    Pondman, Kirsten M; Paudyal, Basudev; Sim, Robert B; Kaur, Anuvinder; Kouser, Lubna; Tsolaki, Anthony G; Jones, Lucy A; Salvador-Morales, Carolina; Khan, Haseeb A; Ten Haken, Bennie; Stenbeck, Gudrun; Kishore, Uday

    2017-01-19

    Carbon nanotubes (CNTs) are increasingly being developed for use in biomedical applications, including drug delivery. One of the most promising applications under evaluation is in treating pulmonary diseases such as tuberculosis. Once inhaled or administered, the nanoparticles are likely to be recognised by innate immune molecules in the lungs such as hydrophilic pulmonary surfactant proteins. Here, we set out to examine the interaction between surfactant protein D (SP-D), a key lung pattern recognition molecule and CNTs, and possible downstream effects on the immune response via macrophages. We show here that a recombinant form of human SP-D (rhSP-D) bound to oxidised and carboxymethyl cellulose (CMC) coated CNTs via its C-type lectin domain and enhanced phagocytosis by U937 and THP-1 macrophages/monocytic cell lines, together with an increased pro-inflammatory response, suggesting that sequestration of SP-D by CNTs in the lungs can trigger an unwanted and damaging immune response. We also observed that functionalised CNTs, opsonised with rhSP-D, continued to activate complement via the classical pathway, suggesting that C1q, which is the recognition sub-component of the classical pathway, and SP-D have distinct pattern recognition sites on the CNTs. Consistent with our earlier reports, complement deposition on the rhSP-D opsonised CNTs led to dampening of the pro-inflammatory immune response by THP-1 macrophages, as evident from qPCR, cytokine array and NF-κB nuclear translocation analyses. This study highlights the importance of understanding the interplay between innate immune humoral factors including complement in devising nanoparticle based drug delivery strategies.

  15. Surfactant proteins, SP-A and SP-D, in respiratory fungal infections: their role in the inflammatory response.

    PubMed

    Carreto-Binaghi, Laura Elena; Aliouat, El Moukhtar; Taylor, Maria Lucia

    2016-06-01

    Pulmonary surfactant is a complex fluid that comprises phospholipids and four proteins (SP-A, SP-B, SP-C, and SP-D) with different biological functions. SP-B, SP-C, and SP-D are essential for the lungs' surface tension function and for the organization, stability and metabolism of lung parenchyma. SP-A and SP-D, which are also known as pulmonary collectins, have an important function in the host's lung immune response; they act as opsonins for different pathogens via a C-terminal carbohydrate recognition domain and enhance the attachment to phagocytic cells or show their own microbicidal activity by increasing the cellular membrane permeability. Interactions between the pulmonary collectins and bacteria or viruses have been extensively studied, but this is not the same for fungal pathogens. SP-A and SP-D bind glucan and mannose residues from fungal cell wall, but there is still a lack of information on their binding to other fungal carbohydrate residues. In addition, both their relation with immune cells for the clearance of these pathogens and the role of surfactant proteins' regulation during respiratory fungal infections remain unknown. Here we highlight the relevant findings associated with SP-A and SP-D in those respiratory mycoses where the fungal infective propagules reach the lungs by the airways.

  16. Structure map including off-stoichiometric and ternary sp-d-valent compounds

    NASA Astrophysics Data System (ADS)

    Hammerschmidt, T.; Bialon, A. F.; Drautz, R.

    2017-10-01

    Structure maps predict the crystal structure of a compound from the knowledge of constituent elements and chemical composition. We recently developed a highly predictive, three-dimensional structure map for stoichiometric binary sp- d-valent compounds. Here we show that the descriptors of this structure map are transferable to off-stoichiometric compounds with similar predictive power. We furthermore demonstrate that the descriptors are suitable for ternary prototypes. In particular, we construct a three-dimensional structure map for 129 prototypical crystal structures for ternary compounds. The crystal structure is predicted correctly with a probability of 78%. With a confidence of 95% the correct crystal structure is among the three most likely crystal structures predicted by the structure map.

  17. DNA vaccine molecular adjuvants SP-D-BAFF and SP-D-APRIL enhance anti-gp120 immune response and increase HIV-1 neutralizing antibody titers.

    PubMed

    Gupta, Sachin; Clark, Emily S; Termini, James M; Boucher, Justin; Kanagavelu, Saravana; LeBranche, Celia C; Abraham, Sakhi; Montefiori, David C; Khan, Wasif N; Stone, Geoffrey W

    2015-04-01

    the gp120 trimer, the inaccessibility of the conserved sequences, highly variable protein sequences, and the loss of HIV-1-specific antibody-producing cells during development. We have shown previously that tumor necrosis factor (TNF) superfamily ligands, including BAFF and APRIL, can be multitrimerized using the lung protein SP-D (surfactant protein D), enhancing immune responses. Here we show that DNA or DNA-protein vaccines encoding BAFF or APRIL multitrimers, IL-12p70, and membrane-bound HIV-1 Env gp140 induced tier 1 and tier 2 neutralizing antibodies in a mouse model. BAFF and APRIL enhanced the immune reaction, improved antibody binding, and increased the numbers of anti-HIV-1 antibody-secreting cells. Adaptation of this vaccine design may prove useful in designing preventive HIV-1 vaccines for humans. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

  18. Stimulatory effect of ethanol on libertellenone H biosynthesis by Arctic fungus Eutypella sp. D-1.

    PubMed

    Shen, Chu; Xu, Ning; Gao, Yanyun; Sun, Xiaoyue; Yin, Ying; Cai, Menghao; Zhou, Xiangshan; Zhang, Yuanxing

    2016-02-01

    Libertellenone H (1) was a promising antitumor diterpenoid isolated from Arctic fungus Eutypella sp. D-1, however, its production was very limited. In this study, we investigated the effects of ethanol on cell growth and libertellenone H production. The mycelium in ethanol-feeding cultures was fragmented and dispersed, and the titer of libertellenone H was remarkably increased to 4.88 mg l(-1) in an optimal feeding manner, which was 16.4-fold higher than the control group. To provide an insight into the cell response to ethanol, genes critical to the libertellenone H biosynthesis were successfully cloned and their transcription levels were determined. The results suggested that the gene transcription levels of 3-hydroxy-3-methyl glutaric acyl coenzyme A reductase and geranylgeranyl diphosphate synthase were up-regulated by ethanol stimulation. The results from this study were helpful for further understanding of the ethanol function on diterpenes biosynthesis as well as developing more effective strategies for over-production of these desired secondary metabolites.

  19. Ecological Inference

    NASA Astrophysics Data System (ADS)

    King, Gary; Rosen, Ori; Tanner, Martin A.

    2004-09-01

    This collection of essays brings together a diverse group of scholars to survey the latest strategies for solving ecological inference problems in various fields. The last half-decade has witnessed an explosion of research in ecological inference--the process of trying to infer individual behavior from aggregate data. Although uncertainties and information lost in aggregation make ecological inference one of the most problematic types of research to rely on, these inferences are required in many academic fields, as well as by legislatures and the Courts in redistricting, by business in marketing research, and by governments in policy analysis.

  20. Humic substances increase survival of freshwater shrimp Caridina sp. D to acid mine drainage.

    PubMed

    Holland, Aleicia; Duivenvoorden, Leo J; Kinnear, Susan H W

    2013-02-01

    Humic substances (HS) are known to decrease the toxicity of heavy metals to aquatic organisms, and it has been suggested that they can provide buffering protection in low pH conditions. Despite this, little is known about the ability for HS to increase survival to acid mine drainage (AMD). In this study, the ability of HS to increase survival of the freshwater shrimp (Caridina sp. D sensu Page et al. in Biol Lett 1:139-142, 2005) to acid mine drainage was investigated using test waters collected from the Mount Morgan open pit in Central Queensland with the addition of Aldrich humic acid (AHA). The AMD water from the Mount Morgan open pit is highly acidic (pH 2.67) as well as contaminated with heavy metals (1780 mg/L aluminum, 101 mg/L copper [Cu], 173 mg/L manganese, 51.8 mg/L zinc [Zn], and 51.8 mg/L iron). Freshwater shrimp were exposed to dilutions in the range of 0.5 % to 5 % AMD water with and without the addition of 10 or 20 mg/L AHA. In the absence of HS, all shrimp died in the 2.5 % AMD treatment. In contrast, addition of HS increased survival in the 2.5 % AMD treatment by ≤66 % as well as significantly decreased the concentration of dissolved Cu, cobalt, cadmium, and Zn. The decreased toxicity of AMD in the presence of HS is likely to be due to complexation and precipitation of heavy metals with the HS; it is also possible that HS caused changes to the physiological condition of the shrimp, thus increasing their survival. These results are valuable in contributing to an improved understanding of potential role of HS in ameliorating the toxicity of AMD environments.

  1. Serum surfactant protein D (SP-D) is a prognostic marker of poor outcome in patients with A/H1N1 virus infection.

    PubMed

    Delgado, Carlos; Krötzsch, Edgar; Jiménez-Alvarez, Luis A; Ramírez-Martínez, Gustavo; Márquez-García, Jose E; Cruz-Lagunas, Alfredo; Morán, Juan; Hernández, Cármen; Sierra-Vargas, Patricia; Avila-Moreno, Federico; Becerril, Carina; Montaño, Martha; Bañales-Méndez, José L; Zúñiga, Joaquín; Buendía-Roldán, Ivette

    2015-02-01

    Surfactant protein D (SP-D) plays an important role in the innate responses against pathogens and its production is altered in lung disorders. We studied the circulating levels of SP-D in 37 patients with acute respiratory distress syndrome due to the A/H1N1 virus infection and in 40 healthy controls. Cox logistic regression models were constructed to explore the association of SP-D levels and risk of death. Mortality rate after a 28-day was 32.42 %. Significant higher levels of SP-D were detected in A/H1N1 patients with fatal outcome (p < 0.05). After adjusting for confounding variables, levels of SP-D ≥250 ng/mL were associated with increased the risk of death (HR = 8.27, 95 % CI 1.1-64.1, p = 0.043). Our results revealed that higher circulating levels of SP-D are associated with higher mortality risk in critically ill A/H1N1 patients. SP-D might be a predictive factor of poor outcomes in viral pneumonia.

  2. Contributions of Phenylalanine 335 to Ligand Recognition by Human Surfactant Protein D: Ring Interactions with SP-D Ligands

    SciTech Connect

    Crouch,E.; McDonald, B.; Smith, K.; Cararella, T.; Seaton, B.; Head, J.

    2006-01-01

    Surfactant Protein D (SP-D) is an innate immune effector that contributes to antimicrobial host defense and immune regulation. Interactions of SP-D with microorganisms and organic antigens involve binding of glycoconjugates to the C-type lectin carbohydrate recognition domain (CRD). A trimeric fusion protein encoding the human neck+CRD (hNCRD) bound to the aromatic glycoside, p-nitrophenyl-alpha-D-maltoside, with nearly a log-fold higher affinity than maltose, the prototypical competitor. Maltotriose, which has the same linkage pattern as the maltoside, bound with intermediate affinity. Site-directed substitution of leucine for phenylalanine 335 (Phe335) decreased affinities for the maltoside and maltotriose without significantly altering the affinity for maltose or glucose, and substitution of tyrosine or tryptophan for leucine restored preferential binding to maltotriose and the maltoside. A mutant with alanine at this position failed to bind to mannan or maltose-substituted solid supports. Crystallographic analysis of the hNCRD complexed with maltotriose or p-nitrophenyl-maltoside showed stacking of the terminal glucose or nitrophenyl ring with the aromatic ring of Phe335. Our studies indicate that Phe335, which is evolutionarily conserved in all known SP-Ds, plays important - if not critical roles - in SP-D function.

  3. Whole genome analysis of halotolerant and alkalotolerant plant growth-promoting rhizobacterium Klebsiella sp. D5A

    PubMed Central

    Liu, Wuxing; Wang, Qingling; Hou, Jinyu; Tu, Chen; Luo, Yongming; Christie, Peter

    2016-01-01

    This research undertook the systematic analysis of the Klebsiella sp. D5A genome and identification of genes that contribute to plant growth-promoting (PGP) traits, especially genes related to salt tolerance and wide pH adaptability. The genome sequence of isolate D5A was obtained using an Illumina HiSeq 2000 sequencing system with average coverages of 174.7× and 200.1× using the paired-end and mate-pair sequencing, respectively. Predicted and annotated gene sequences were analyzed for similarity with the Kyoto Encyclopedia of Genes and Genomes (KEGG) enzyme database followed by assignment of each gene into the KEGG pathway charts. The results show that the Klebsiella sp. D5A genome has a total of 5,540,009 bp with 57.15% G + C content. PGP conferring genes such as indole-3-acetic acid (IAA) biosynthesis, phosphate solubilization, siderophore production, acetoin and 2,3-butanediol synthesis, and N2 fixation were determined. Moreover, genes putatively responsible for resistance to high salinity including glycine-betaine synthesis, trehalose synthesis and a number of osmoregulation receptors and transport systems were also observed in the D5A genome together with numerous genes that contribute to pH homeostasis. These genes reveal the genetic adaptation of D5A to versatile environmental conditions and the effectiveness of the isolate to serve as a plant growth stimulator. PMID:27216548

  4. Whole genome analysis of halotolerant and alkalotolerant plant growth-promoting rhizobacterium Klebsiella sp. D5A

    NASA Astrophysics Data System (ADS)

    Liu, Wuxing; Wang, Qingling; Hou, Jinyu; Tu, Chen; Luo, Yongming; Christie, Peter

    2016-05-01

    This research undertook the systematic analysis of the Klebsiella sp. D5A genome and identification of genes that contribute to plant growth-promoting (PGP) traits, especially genes related to salt tolerance and wide pH adaptability. The genome sequence of isolate D5A was obtained using an Illumina HiSeq 2000 sequencing system with average coverages of 174.7× and 200.1× using the paired-end and mate-pair sequencing, respectively. Predicted and annotated gene sequences were analyzed for similarity with the Kyoto Encyclopedia of Genes and Genomes (KEGG) enzyme database followed by assignment of each gene into the KEGG pathway charts. The results show that the Klebsiella sp. D5A genome has a total of 5,540,009 bp with 57.15% G + C content. PGP conferring genes such as indole-3-acetic acid (IAA) biosynthesis, phosphate solubilization, siderophore production, acetoin and 2,3-butanediol synthesis, and N2 fixation were determined. Moreover, genes putatively responsible for resistance to high salinity including glycine-betaine synthesis, trehalose synthesis and a number of osmoregulation receptors and transport systems were also observed in the D5A genome together with numerous genes that contribute to pH homeostasis. These genes reveal the genetic adaptation of D5A to versatile environmental conditions and the effectiveness of the isolate to serve as a plant growth stimulator.

  5. Perceptual inference.

    PubMed

    Aggelopoulos, Nikolaos C

    2015-08-01

    Perceptual inference refers to the ability to infer sensory stimuli from predictions that result from internal neural representations built through prior experience. Methods of Bayesian statistical inference and decision theory model cognition adequately by using error sensing either in guiding action or in "generative" models that predict the sensory information. In this framework, perception can be seen as a process qualitatively distinct from sensation, a process of information evaluation using previously acquired and stored representations (memories) that is guided by sensory feedback. The stored representations can be utilised as internal models of sensory stimuli enabling long term associations, for example in operant conditioning. Evidence for perceptual inference is contributed by such phenomena as the cortical co-localisation of object perception with object memory, the response invariance in the responses of some neurons to variations in the stimulus, as well as from situations in which perception can be dissociated from sensation. In the context of perceptual inference, sensory areas of the cerebral cortex that have been facilitated by a priming signal may be regarded as comparators in a closed feedback loop, similar to the better known motor reflexes in the sensorimotor system. The adult cerebral cortex can be regarded as similar to a servomechanism, in using sensory feedback to correct internal models, producing predictions of the outside world on the basis of past experience.

  6. Lung remodeling in aging surfactant protein D deficient mice.

    PubMed

    Schneider, Jan Philipp; Arkenau, Martina; Knudsen, Lars; Wedekind, Dirk; Ochs, Matthias

    2017-02-07

    Pulmonary surfactant, a mixture of lipids and proteins at the air-liquid interface of alveoli, prevents the lungs from collapsing due to surface tension. One constituent is surfactant-associated protein-D (SP-D), a protein involved in surfactant homeostasis and innate immunity. Mice deficient in SP-D (SP-D (-/-)) has been described as developing a characteristic phenotype which affects the surfactant system (including changes in the intra-cellular and intra-alveolar surfactant pool, alveolar epithelial type II cells and alveolar macrophages), lung architecture and its inflammatory state (development of an emphysema-like pathology, inflammatory cell infiltration). Furthermore, it has been described that these mice develop sub-pleural fibrosis and a thickening of alveolar septal walls. The aim of the present study was to systematically investigate the long term progression of this phenotype with special focus on parenchymal remodeling, whether there are progressive emphysematous changes and whether there is progressive septal wall thickening which might indicate the development of pulmonary fibrosis. By means of design-based stereology and light microscopy, lungs of wild type (wt) and SP-D (-/-) mice of four age groups (3, 6, 12 and ∼18 months) were investigated. The data do not suggest a relevant spontaneous pro-fibrotic remodeling or a destructive process in the aging SP-D (-/-) mice. We demonstrated neither a significant destructive emphysema nor significant thickening of alveolar septal walls, but the data suggest an increase in the number weighted mean alveolar volume in aging SP-D (-/-) mice without loss of alveoli or alveolar epithelial surface area per lung. This increase may reflect over-distension due to altered mechanical properties of alveoli. In the light of our findings and data from the literature, the question arises as to whether a lack of SP-D promotes structural changes in the lung which have been described as being associated with aging lungs

  7. Statistical Inference

    NASA Astrophysics Data System (ADS)

    Khan, Shahjahan

    Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden "jewels" in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model

  8. Statistical Inference

    NASA Astrophysics Data System (ADS)

    Khan, Shahjahan

    Often scientific information on various data generating processes are presented in the from of numerical and categorical data. Except for some very rare occasions, generally such data represent a small part of the population, or selected outcomes of any data generating process. Although, valuable and useful information is lurking in the array of scientific data, generally, they are unavailable to the users. Appropriate statistical methods are essential to reveal the hidden “jewels” in the mess of the row data. Exploratory data analysis methods are used to uncover such valuable characteristics of the observed data. Statistical inference provides techniques to make valid conclusions about the unknown characteristics or parameters of the population from which scientifically drawn sample data are selected. Usually, statistical inference includes estimation of population parameters as well as performing test of hypotheses on the parameters. However, prediction of future responses and determining the prediction distributions are also part of statistical inference. Both Classical or Frequentists and Bayesian approaches are used in statistical inference. The commonly used Classical approach is based on the sample data alone. In contrast, increasingly popular Beyesian approach uses prior distribution on the parameters along with the sample data to make inferences. The non-parametric and robust methods are also being used in situations where commonly used model assumptions are unsupported. In this chapter,we cover the philosophical andmethodological aspects of both the Classical and Bayesian approaches.Moreover, some aspects of predictive inference are also included. In the absence of any evidence to support assumptions regarding the distribution of the underlying population, or if the variable is measured only in ordinal scale, non-parametric methods are used. Robust methods are employed to avoid any significant changes in the results due to deviations from the model

  9. Attenuated allergic airway hyperresponsiveness in C57BL/6 mice is associated with enhanced surfactant protein (SP)-D production following allergic sensitization

    PubMed Central

    Atochina, Elena N; Beers, Michael F; Tomer, Yaniv; Scanlon, Seth T; Russo, Scott J; Panettieri, Reynold A; Haczku, Angela

    2003-01-01

    Background C57BL/6 mice have attenuated allergic airway hyperresponsiveness (AHR) when compared with Balb/c mice but the underlying mechanisms remain unclear. SP-D, an innate immune molecule with potent immunosuppressive activities may have an important modulatory role in the allergic airway response and the consequent physiological changes. We hypothesized that an elevated SP-D production is associated with the impaired ability of C57BL/6 mice to develop allergic AHR. Methods SP-D mRNA and protein expression was investigated during development of allergic airway changes in a model of Aspergillus fumigatus (Af)-induced allergic inflammation. To study whether strain dependency of allergic AHR is associated with different levels of SP-D in the lung, Balb/c and C57BL/6 mice were compared. Results Sensitization and exposure to Af induced significant airway inflammation in both mouse strains in comparison with naïve controls. AHR to acetylcholine however was significantly attenuated in C57BL/6 mice in spite of increased eosinophilia and serum IgE when compared with Balb/c mice (p < 0.05). Af challenge of sensitized C57BL/6 mice induced a markedly increased SP-D protein expression in the SA surfactant fraction (1,894 ± 170% of naïve controls) that was 1.5 fold greater than the increase in Balb/c mice (1,234 ± 121% p < 0.01). These changes were selective since levels of the hydrophobic SP-B and SP-C and the hydrophilic SP-A were significantly decreased following sensitization and challenge with Af in both strains. Further, sensitized and exposed C57BL/6 mice had significantly lower IL-4 and IL-5 in the BAL fluid than that of Balb/c mice (p < 0.05). Conclusions These results suggest that enhanced SP-D production in the lung of C57BL/6 mice may contribute to an attenuated AHR in response to allergic airway sensitization. SP-D may act by inhibiting synthesis of Th2 cytokines. PMID:14748931

  10. Proteomic studies highlight outer-membrane proteins related to biofilm development in the marine bacterium Pseudoalteromonas sp. D41.

    PubMed

    Ritter, Andrés; Com, Emmanuelle; Bazire, Alexis; Goncalves, Marina Dos Santos; Delage, Ludovic; Le Pennec, Gaël; Pineau, Charles; Dreanno, Catherine; Compère, Chantal; Dufour, Alain

    2012-11-01

    Bacterial biofilm development is conditioned by complex processes involving bacterial attachment to surfaces, growth, mobility, and exoproduct production. The marine bacterium Pseudoalteromonas sp. strain D41 is able to attach strongly onto a wide variety of substrates, which promotes subsequent biofilm development. Study of the outer-membrane and total soluble proteomes showed ten spots with significant intensity variations when this bacterium was grown in biofilm compared to planktonic cultures. MS/MS de novo sequencing analysis allowed the identification of four outer-membrane proteins of particular interest since they were strongly induced in biofilms. These proteins are homologous to a TonB-dependent receptor (TBDR), to the OmpW and OmpA porins, and to a type IV pilus biogenesis protein (PilF). Gene expression assays by quantitative RT-PCR showed that the four corresponding genes were upregulated during biofilm development on hydrophobic and hydrophilic surfaces. The Pseudomonas aeruginosa mutants unable to produce any of the OmpW, OmpA, and PilF homologues yielded biofilms with lower biovolumes and altered architectures, confirming the involvement of these proteins in the biofilm formation process. Our results indicate that Pseudoalteromonas sp. D41 shares biofilm formation mechanisms with human pathogenic bacteria, but also relies on TBDR, which might be more specific to the marine environment. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  11. Humic substances of varying types increase survivorship of the freshwater shrimp Caridina sp. D to acid mine drainage.

    PubMed

    Holland, Aleicia; Duivenvoorden, Leo J; Kinnear, Susan H W

    2014-07-01

    Differences relating to the ability of various types of humic substances (HS) to influence toxicity of pollutants have been reported in the literature, but there still remains a gap in understanding whether various HS will have the same influence on the toxicity of acid mine drainage (AMD). This study investigated differences in the ability of Aldrich humic acid (AHA), Suwannee River humic acid and Suwannee River fulvic acid to decrease toxicity of AMD to the freshwater shrimp (Caridina sp. D). Toxicity tests were conducted over 96 h and used Mount Morgan open pit water as source of AMD and Dee River water as control/diluents. Concentrations of 0-4 % AMD at 0 mg/L HS, 10 mg/L AHA, 10 mg/L Suwannee River humic acid and 10 mg/L Suwannee River fulvic acid were used. Significantly higher survival of shrimp was recorded in the HS treatments compared with the treatment containing no HS. No significant differences were found among HS type. HS considerably increased LC50 values irrespective of type, from 1.29 (0 mg/L HS) to 2.12 % (AHA); 2.19 (Suwannee River humic acid) and 2.22 % (Suwannee River fulvic acid). These results support previous work that HS decrease the toxicity of AMD to freshwater organisms, but with the novel finding that this ability occurs irrespective of HS type. These results increase the stock of knowledge regarding HS and may contribute to a possible remediation option for AMD environments.

  12. Biological wastewater treatment of 1,4-dioxane using polyethylene glycol gel carriers entrapping Afipia sp. D1.

    PubMed

    Isaka, Kazuichi; Udagawa, Makiko; Kimura, Yuya; Sei, Kazunari; Ike, Michihiko

    2016-02-01

    A biological treatment system for 1,4-dioxane-containing wastewater was developed using the bacterium Afipia sp. D1, which can utilize 1,4-dioxane as the sole carbon source. Strain D1 was entrapped in a polyethylene glycol gel carrier to stably maintain it in a bioreactor, and continuous feeding tests were performed to treat model industrial wastewater containing 1,4-dioxane. 1,4-Dioxane removal activity rapidly increased soon after the start of feeding of influent with 400 mg/L 1,4-dioxane, and the volumetric removal rate reached 0.67 kg dioxane/m(3)/d on day 36 by a stepwise increase in loading. The start-up period of the 1,4-dioxane treatment reactor was approximately 1 month, and stable removal performance was subsequently achieved for more than 1 month. The average 1,4-dioxane effluent concentration and 1,4-dioxane removal efficiency were 3.6 mg/L and 99%, respectively, during stable operation. Further 1,4-dioxane degradation activity of the of the gel carrier was characterized in batch experiments with respect to temperature. The optimum temperature for 1,4-dioxane treatment was 31.7°C, and significant removal was observed at a temperature as low as 6.9°C. The apparent activation energy for 1,4-dioxane degradation was estimated to be 47.3 kJ/mol. This is the first report of the development of a 1,4-dioxane biological treatment system using gel entrapment technology.

  13. Comparative Study of Circulating MMP-7, CCL18, KL-6, SP-A, and SP-D as Disease Markers of Idiopathic Pulmonary Fibrosis

    PubMed Central

    Hamai, Kosuke; Iwamoto, Hiroshi; Ishikawa, Nobuhisa; Horimasu, Yasushi; Masuda, Takeshi; Miyamoto, Shintaro; Nakashima, Taku; Ohshimo, Shinichiro; Fujitaka, Kazunori; Hamada, Hironobu; Hattori, Noboru; Kohno, Nobuoki

    2016-01-01

    Background. Recent reports indicate that matrix metalloproteinase-7 (MMP-7) and CC-chemokine ligand 18 (CCL18) are potential disease markers of idiopathic pulmonary fibrosis (IPF). The objective of this study was to perform direct comparisons of these two biomarkers with three well-investigated serum markers of IPF, Krebs von den Lungen-6 (KL-6), surfactant protein-A (SP-A), and SP-D. Methods. The serum levels of MMP-7, CCL18, KL-6, SP-A, and SP-D were evaluated in 65 patients with IPF, 31 patients with bacterial pneumonia, and 101 healthy controls. The prognostic performance of these five biomarkers was evaluated in patients with IPF. Results. The serum levels of MMP-7, KL-6, and SP-D in patients with IPF were significantly elevated compared to those in patients with bacterial pneumonia and in the healthy controls. Multivariate survival analysis showed that serum MMP-7 and KL-6 levels were independent predictors in IPF patients. Moreover, elevated levels of both KL-6 and MMP-7 were associated with poorer survival rates in IPF patients, and the combination of both markers provided the best risk discrimination using the C statistic. Conclusions. The present results indicated that MMP-7 and KL-6 were promising prognostic markers of IPF, and the combination of the two markers might improve survival prediction in patients with IPF. PMID:27293304

  14. Immobilization of Erwinia sp. D12 Cells in Alginate-Gelatin Matrix and Conversion of Sucrose into Isomaltulose Using Response Surface Methodology.

    PubMed

    Kawaguti, Haroldo Yukio; Carvalho, Priscila Hoffmann; Figueira, Joelise Alencar; Sato, Hélia Harumi

    2011-01-01

    Isomaltulose is a noncariogenic reducing disaccharide and also a structural isomer of sucrose and is used by the food industry as a sucrose replacement. It is obtained through enzymatic conversion of microbial sucrose isomerase. An Erwinia sp. D12 strain is capable of converting sucrose into isomaltulose. The experimental design technique was used to study the influence of immobilization parameters on converting sucrose into isomaltulose in a batch process using shaken Erlenmeyer flasks. We assessed the effect of gelatin and transglutaminase addition on increasing the reticulation of granules of Erwinia sp. D12 cells immobilized in alginate. Independent parameters, sodium alginate concentration, cell mass concentration, CaCl(2) concentration, gelatin concentration, and transglutaminase concentration had all a significant effect (P < 0.05) on isomaltulose production. Erwinia sp. D12 cells immobilized in 3.0% (w/v) sodium alginate, 47.0% (w/v) cell mass, 0.3 molL(-1) CaCl(2), 1.7% (w/v) gelatin and 0.15% (w/v) transglutaminase presented sucrose conversion into isomaltulose, of around 50-60% in seven consecutive batches.

  15. Immobilization of Erwinia sp. D12 Cells in Alginate-Gelatin Matrix and Conversion of Sucrose into Isomaltulose Using Response Surface Methodology

    PubMed Central

    Kawaguti, Haroldo Yukio; Carvalho, Priscila Hoffmann; Figueira, Joelise Alencar; Sato, Hélia Harumi

    2011-01-01

    Isomaltulose is a noncariogenic reducing disaccharide and also a structural isomer of sucrose and is used by the food industry as a sucrose replacement. It is obtained through enzymatic conversion of microbial sucrose isomerase. An Erwinia sp. D12 strain is capable of converting sucrose into isomaltulose. The experimental design technique was used to study the influence of immobilization parameters on converting sucrose into isomaltulose in a batch process using shaken Erlenmeyer flasks. We assessed the effect of gelatin and transglutaminase addition on increasing the reticulation of granules of Erwinia sp. D12 cells immobilized in alginate. Independent parameters, sodium alginate concentration, cell mass concentration, CaCl2 concentration, gelatin concentration, and transglutaminase concentration had all a significant effect (P < 0.05) on isomaltulose production. Erwinia sp. D12 cells immobilized in 3.0% (w/v) sodium alginate, 47.0% (w/v) cell mass, 0.3 molL−1 CaCl2, 1.7% (w/v) gelatin and 0.15% (w/v) transglutaminase presented sucrose conversion into isomaltulose, of around 50–60% in seven consecutive batches. PMID:21785708

  16. Genetic Polymorphisms of SP-A, SP-B, and SP-D and Risk of Respiratory Distress Syndrome in Preterm Neonates

    PubMed Central

    Chang, Hong-Yu; Li, Fang; Li, Feng-Sheng; Zheng, Cheng-Zhong; Lei, Yan-Zhe; Wang, Jing

    2016-01-01

    Background We examined selected polymorphisms in 3 pulmonary surfactant-associated proteins (SP) for their influence on serum SP levels and risk of respiratory distress syndrome (RDS) in preterm neonates. Material/Methods Premature infants from a Han population were enrolled, including 100 premature infants with RDS (case group) and 120 premature infants without RDS (control group). SNP genotyping for SP-A (+186A/G and +655C/T), SP-B (−18A/C and 1580C/T), and SP-D (Met11ThrT/C and Ala160ThrG/A) used polymerase chain reaction-restriction fragment length polymorphism. Haplotypes were calculated with Shesis software and serum SP-A/B/D levels were quantified by ELISA. Results Case and control groups exhibited significant differences in genotype and allele frequencies of SP-A (+186A/G, +655C/T) and SP-B (1580C/T). However, no statistically significant differences were observed in the allele and genotype frequencies of SP-B −18A/C, SP-D Met11ThrT/C, and SP-D Ala160ThrG/A. Importantly, serum SP-A and SP-B levels were reduced in RDS patients carrying SP-A (+186A/G, +655C/T) and SP-B (1580C/T) polymorphisms. AA genotype of +186A/G, SP-A level, and CC genotype of 1580C/T were independently correlated with increased RDS risk. Conclusions SP-A (+186A/G) and SP-B (1580C/T) polymorphisms are strongly associated with the risk of RDS in preterm infants. Notably, reduced serum SP-A levels were correlated with a high risk of RDS and may serve as novel biomarkers for RDS detection and monitoring. PMID:28011976

  17. NOS2 Is Critical to the Development of Emphysema in Sftpd Deficient Mice but Does Not Affect Surfactant Homeostasis

    PubMed Central

    Guo, Chang-Jiang; Scott, Pamela A.; Haenni, Beat; Beers, Michael F.; Ochs, Matthias; Gow, Andrew J.

    2014-01-01

    Rationale Surfactant protein D (SP-D) has important immuno-modulatory properties. The absence of SP-D results in an inducible NO synthase (iNOS, coded by NOS2 gene) related chronic inflammation, development of emphysema-like pathophysiology and alterations of surfactant homeostasis. Objective In order to test the hypothesis that SP-D deficiency related abnormalities in pulmonary structure and function are a consequence of iNOS induced inflammation, we generated SP-D and iNOS double knockout mice (DiNOS). Methods Structural data obtained by design-based stereology to quantify the emphysema-like phenotype and disturbances of the intracellular surfactant were correlated to invasive pulmonary function tests and inflammatory markers including activation markers of alveolar macrophages and compared to SP-D (Sftpd−/−) and iNOS single knockout mice (NOS2−/−) as well as wild type (WT) littermates. Measurements and Results DiNOS mice had reduced inflammatory cells in BAL and BAL-derived alveolar macrophages showed an increased expression of markers of an alternative activation as well as reduced inflammation. As evidenced by increased alveolar numbers and surface area, emphysematous changes were attenuated in DiNOS while disturbances of the surfactant system remained virtually unchanged. Sftpd−/− demonstrated alterations of intrinsic mechanical properties of lung parenchyma as shown by reduced stiffness and resistance at its static limits, which could be corrected by additional ablation of NOS2 gene in DiNOS. Conclusion iNOS related inflammation in the absence of SP-D is involved in the emphysematous remodeling leading to a loss of alveoli and associated alterations of elastic properties of lung parenchyma while disturbances of surfactant homeostasis are mediated by different mechanisms. PMID:24465666

  18. Disaccharidase deficiency.

    PubMed

    Bayless, T M; Christopher, N L

    1969-02-01

    This review of the literature and current knowledge concerning a nutritional disorder of disaccharidase deficiency discusses the following topics: 1) a description of disorders of disaccharide digestion; 2) some historical perspective on the laboratory and bedside advances in the past 10 years that have helped define a group of these digestive disorders; 3) a classification of conditions causing disaccharide intolerance; and 4) a discussion of some of the specific clinical syndromes emphasizing nutritional consequences of these syndromes. The syndromes described include congenital lactase deficiency, acquired lactase deficiency in teenagers and adults, acquired generalized disaccharidase deficiency secondary to diffuse mucosal damage, acquired lactose intolerance secondary to alterations in the intestinal transit, sucrase-isomaltase deficiencies, and other disease associations connected with lactase deficiency such as colitis.

  19. Pituitary deficiencies.

    PubMed

    Greco, Deborah S

    2012-02-01

    Diabetes insipidus, arising from damage to or congenital abnormalities of the neurohypophysis, is the most common pituitary deficiency in animals. Hypopituitarism and isolated growth hormone or thyrotropin deficiency may result in growth abnormalities in puppies and kittens. In addition, treatment of associated hormone deficiencies, such as hypothyroidism and hypoadrenocorticism, in patients with panhypopituitarism is vital to restore adequate growth in dwarfed animals. Secondary hypoadrenocorticism is an uncommon clinical entity; however differentiation of primary versus secondary adrenal insufficiency is of utmost importance in determining optimal therapy. This article will focus on the pathogenesis, diagnosis and treatment of hormone deficiencies of the pituitary gland and neurohypophysis. Copyright © 2012. Published by Elsevier Inc.

  20. Identification of the Antibacterial Compound Produced by the Marine Epiphytic Bacterium Pseudovibrio sp. D323 and Related Sponge-Associated Bacteria

    PubMed Central

    Penesyan, Anahit; Tebben, Jan; Lee, Matthew; Thomas, Torsten; Kjelleberg, Staffan; Harder, Tilmann; Egan, Suhelen

    2011-01-01

    Surface-associated marine bacteria often produce secondary metabolites with antagonistic activities. In this study, tropodithietic acid (TDA) was identified to be responsible for the antibacterial activity of the marine epiphytic bacterium Pseudovibrio sp. D323 and related strains. Phenol was also produced by these bacteria but was not directly related to the antibacterial activity. TDA was shown to effectively inhibit a range of marine bacteria from various phylogenetic groups. However TDA-producers themselves were resistant and are likely to possess resistance mechanism preventing autoinhibition. We propose that TDA in isolate D323 and related eukaryote-associated bacteria plays a role in defending the host organism against unwanted microbial colonisation and, possibly, bacterial pathogens. PMID:21892353

  1. Temporal stability of parasite distribution and genetic variability values of Contracaecum osculatum sp. D and C. osculatum sp. E (Nematoda: Anisakidae) from fish of the Ross Sea (Antarctica)

    PubMed Central

    Mattiucci, Simonetta; Cipriani, Paolo; Paoletti, Michela; Nardi, Valentina; Santoro, Mario; Bellisario, Bruno; Nascetti, Giuseppe

    2015-01-01

    The Ross Sea, Eastern Antarctica, is considered a “pristine ecosystem” and a biodiversity “hotspot” scarcely impacted by humans. The sibling species Contracaecum osculatum sp. D and C. osculatum sp. E are anisakid parasites embedded in the natural Antarctic marine ecosystem. Aims of this study were to: identify the larvae of C. osculatum (s.l.) recovered in fish hosts during the XXVII Italian Expedition to Antarctica (2011–2012); perform a comparative analysis of the contemporary parasitic load and genetic variability estimates of C. osculatum sp. D and C. osculatum sp. E with respect to samples collected during the expedition of 1993–1994; to provide ecological data on these parasites. 200 fish specimens (Chionodraco hamatus, Trematomus bernacchii, Trematomus hansoni, Trematomus newnesi) were analysed for Contracaecum sp. larvae, identified at species level by allozyme diagnostic markers and sequences analysis of the mtDNA cox2 gene. Statistically significant differences were found between the occurrence of C. osculatum sp. D and C. osculatum sp. E in different fish species. C. osculatum sp. E was more prevalent in T. bernacchii; while, a higher percentage of C. osculatum sp. D occurred in Ch. hamatus and T. hansoni. The two species also showed differences in the host infection site: C. osculatum sp. D showed higher percentage of infection in the fish liver. High genetic variability values at both nuclear and mitochondrial level were found in the two species in both sampling periods. The parasitic infection levels by C. osculatum sp. D and sp. E and their estimates of genetic variability showed no statistically significant variation over a temporal scale (2012 versus 1994). This suggests that the low habitat disturbance of the Antarctic region permits the maintenance of stable ecosystem trophic webs, which contributes to the maintenance of a large populations of anisakid nematodes with high genetic variability. PMID:26767164

  2. Zinc deficiency.

    PubMed

    Tuerk, Melanie J; Fazel, Nasim

    2009-03-01

    Zinc plays an essential role in numerous biochemical pathways. Zinc deficiency affects many organ systems, including the integumentary, gastrointestinal, central nervous system, immune, skeletal, and reproductive systems. This article aims to discuss zinc metabolism and highlights a few of the diseases associated with zinc deficiency. Zinc deficiency results in dysfunction of both humoral and cell-mediated immunity and increases the susceptibility to infection. Supplementation of zinc has been shown to reduce the incidence of infection as well as cellular damage from increased oxidative stress. Zinc deficiency is also associated with acute and chronic liver disease. Zinc supplementation protects against toxin-induced liver damage and is used as a therapy for hepatic encephalopathy in patients refractory to standard treatment. Zinc deficiency has also been implicated in diarrheal disease, and supplementation has been effective in both prophylaxis and treatment of acute diarrhea. This article is not meant to review all of the disease states associated with zinc deficiency. Rather, it is an introduction to the influence of the many roles of zinc in the body, with an extensive discussion of the influence of zinc deficiency in selected diseases. Zinc supplementation may be beneficial as an adjunct to treatment of many disease states.

  3. Multiple Instance Fuzzy Inference

    DTIC Science & Technology

    2015-12-02

    Zhang, Xin Chen, and Wei-Bang Chen, “An online multiple instance learn - ing system for semantic image retrieval,” in Multimedia Workshops, 2007. ISMW...INFERENCE A novel fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The...fuzzy learning framework that employs fuzzy inference to solve the problem of multiple instance learning (MIL) is presented. The framework introduces a

  4. Inference in `poor` languages

    SciTech Connect

    Petrov, S.

    1996-10-01

    Languages with a solvable implication problem but without complete and consistent systems of inference rules (`poor` languages) are considered. The problem of existence of finite complete and consistent inference rule system for a ``poor`` language is stated independently of the language or rules syntax. Several properties of the problem arc proved. An application of results to the language of join dependencies is given.

  5. Cobalamin deficiency.

    PubMed

    Herrmann, Wolfgang; Obeid, Rima

    2012-01-01

    Cobalamin (Cbl, vitamin B12) consists of a corrinoid structure with cobalt in the centre of the molecule. Neither humans nor animals are able to synthesize this vitamin. Foods of animal source are the only natural source of cobalamin in human diet. There are only two enzymatic reactions in mammalian cells that require cobalamin as cofactor. Methylcobolamin is a cofactor for methionine synthase. The enzyme methylmalonyl-CoA-mutase requires adenosylcobalamin as a cofactor. Therefore, serum concentrations of homocysteine (tHcy) and methylmalonic acid (MMA) will increase in cobalamin deficiency. The cobalamin absorption from diet is a complex process that involves different proteins: haptocorrin, intrinsic factor and transcobalamin (TC). Cobalamin that is bound to TC is called holotranscobalamin (holoTC) which is the metabolically active vitamin B12 fraction. HoloTC consists 6 and 20% of total cobalamin whereas 80% of total serum cobalamin is bound to another binding protein, haptocorrin. Cobalamin deficiency is common worldwide. Cobalamin malabsorption is common in elderly subjects which might explain low vitamin status. Subjects who ingest low amount of cobalamin like vegetarians develop vitamin deficiency. No single parameter can be used to diagnose cobalamin deficiency. Total serum cobalamin is neither sensitive nor it is specific for cobalamin deficiency. This might explain why many deficient subjects would be overlooked by utilizing total cobalamin as status marker. Concentration of holotranscobalamin (holoTC) in serum is an earlier marker that becomes decreased before total serum cobalamin. Concentrations of MMA and tHcy increase in blood of cobalamin deficient subjects. Despite limitations of these markers in patients with renal dysfunction, concentrations of MMA and tHcy are useful functional markers of cobalamin status. The combined use of holoTC and MMA assays may better indicate cobalamin status than either of them. Because Cbl deficiency is a risk factor

  6. [Thyrotropic deficiency].

    PubMed

    Chanson, P

    1998-11-15

    Central hypothyroidism (thyrotropic deficiency) is due to a defect in TSH secretion by thyrotrophs (or alternatively to an altered bioactivity of TSH). Central hypothyroidism is rare and is often associated with other pituitary deficiencies as it is generally encountered in case of hypothalamo-pituitary tumoral process. Clinical symptoms are milder than those of primary thyroid failure. Diagnosis is based on free T4 measurement whose level is decreased while TSH concentration is normal or minimally increased, reflecting an alteration in the bioactivity of TSH. Replacement therapy is monitored by T4 level measurement: the objective is to obtain normal T4 levels. TSH concentration must not be taken into account for the adjustment of the thyroxine doses.

  7. Effects of sp-d exchange on a bound polaron and the g-factor of the exciton in a GaMnAs quantum dot

    NASA Astrophysics Data System (ADS)

    Lalitha, D.; John Peter, A.; Yoo, Chang Kyoo

    2013-08-01

    Magneto bound polaron in a GaMnAs/Ga0.6Al0.4As quantum dot is investigated with the inclusion of exchange interaction effects due to Mn alloy content and the geometrical confinement. The exciton binding energy and the optical transition energy are computed as functions of dot radius and the magnetic field strength for a fixed Mn alloy content (x = 0.02) in a GaMnAs quantum dot. Numerical calculations are performed using variational method within a single band effective mass approximation. The spin polaronic energy of the heavy hole exciton is studied with the spatial confinement using a mean field theory in the presence of magnetic field strength. The magnetization as a function of dot radius is investigated in a GaMnAs/Ga0.6Al0.4As quantum dot. The magnetic field induced size dependence of g-factor is studied. The effective g-factor of conduction (valence) band electron (hole) is obtained in the GaMnAs quantum dot. The results bring out that (i) the geometrical dependence on sp-d exchange interaction in the GaMnAs/Ga0.6Al0.4As quantum dot has great influence with the magnetic field strength, (ii) the Landé factor is more sensitive if the geometrical confinement effect is included and (iii) the value of g-factor increases when the magnetic field strength is enhanced for all the dot radii. Our results are in good agreement with the other investigators.

  8. The Bayes Inference Engine

    SciTech Connect

    Hanson, K.M.; Cunningham, G.S.

    1996-04-01

    The authors are developing a computer application, called the Bayes Inference Engine, to provide the means to make inferences about models of physical reality within a Bayesian framework. The construction of complex nonlinear models is achieved by a fully object-oriented design. The models are represented by a data-flow diagram that may be manipulated by the analyst through a graphical programming environment. Maximum a posteriori solutions are achieved using a general, gradient-based optimization algorithm. The application incorporates a new technique of estimating and visualizing the uncertainties in specific aspects of the model.

  9. Plasminogen deficiency.

    PubMed

    Celkan, Tiraje

    2017-01-01

    Plasminogen plays an important role in fibrinolysis as well as wound healing, cell migration, tissue modeling and angiogenesis. Congenital plasminogen deficiency is a rare autosomal recessive disorder that leads to the development of thick, wood-like pseudomembranes on mucosal surfaces, mostly seen in conjunctivas named as ''ligneous conjunctivitis''. Local conjunctival use of fresh frozen plazma (FFP) in combination with other eye medications such as cyclosporin and artificial tear drops may relieve the symptoms. Topical treatment with plasminogen eye drops is the most promising treatment that is not yet available in Turkey.

  10. Inference as Prediction

    ERIC Educational Resources Information Center

    Watson, Jane

    2007-01-01

    Inference, or decision making, is seen in curriculum documents as the final step in a statistical investigation. For a formal statistical enquiry this may be associated with sophisticated tests involving probability distributions. For young students without the mathematical background to perform such tests, it is still possible to draw informal…

  11. Influence of cystein deficiency on the inhibition of hepatic microsomal detoxication by methyl mercury in two rat strains.

    PubMed

    Beije, B; Arrhenius, E

    1978-06-01

    Two rat strains, Wistar, strain R and Sprague--Dawley, were subjected to cystein deficiency and methyl mercury pretreatment, both separately and in combination, after which the hepatic microsomal N- and C-oxygenation of N,N-dimethylaniline (DMA) was studied. Cystein deficiency caused a reduction in C-oxygenation in strain R microsomes, and this reduction was nearly doubled by methyl mercury pretreatment of the depleted rats. Methyl mercury pretreatment per se of strain R rats on the standard diet gave no effect. By contrast microsomes from cystein deficient SpD rats showed no statistically significant decrease in C-oxygenation, and cystein deficiency did not further enhance the inhibitory effect obtained with methyl mercury pretreatment alone. N-oxygenation was not significantly affected by any treatment of the two strains.

  12. The effects of irradiance levels and spectral composition on mating strategies in the snow alga, Chloromonas sp.-D, from the Tughill Plateau, New York State

    NASA Astrophysics Data System (ADS)

    Hoham, Ronald W.; Schlag, Erin M.; Kang, Jennifer Y.; Hasselwander, Andrew J.; Behrstock, Alissa F.; Blackburn, Ian R.; Johnson, Rurik C.; Roemer, Stephen C.

    1998-07-01

    Studies have related changes in snow albedo to snow crystal structure and to the presence of surface debris (i.e. pine needles), but there has been less attention given to the existence of algae in snow. An increase in the number of snow algae could also decrease albedo and increase snowmelt rates. The primary purpose of this paper is to document how solar irradiance serves to control the developing stages of algae in snow. Snow algae do not appear near the surface until there is meltwater in the snowpack. Low levels of solar irradiance penetrate through the snowpack and germinate snow algal resting stages that lie underneath, and snow algal growth is enhanced by available gases and nutrients. Flagellate cells swim through the snowpack in the meltwater around the snow crystals, and cells are positioned according to irradiance and spectral differences. In this study, Chloromonas sp.-D strains 582C and 582D, isolated from the upper 20 cm of snowpacks in the Tughill Plateau, Whetstone Gulf State Park, NY, were used to investigate mating strategies under different irradiance levels and spectral compositions in the laboratory, and the irradiance levels used in the experiments correlated with those recorded from the upper 20 cm of snow. Using similar irradiance levels, blue light regimes produced more matings than green and red light regimes. There were no trends in mating when comparing green and red light regimes. When red light regimes of higher photon irradiance (85 mol m-2 s-1) were compared with those of blue light regimes of lower irradiance (30 mol m-2 s-1), more mating occurred under red light. A photon irradiance of 95 mol m-2 s-1 [photosynthetically active radiation (PAR) of 400-700 nm] produced the most mating under both wide-spectrum (WS) and cool-white (CW) regimes, but more mating occurred under CW in all irradiances tested. Mating pairs of three types were observed: oblong-oblong (o-o), oblong-sphere (o-s) and sphere-sphere (s-s). Cell packs that produced

  13. Optical Inference Machines

    DTIC Science & Technology

    1988-06-27

    de olf nessse end Id e ;-tl Sb ieeI smleo) ,Optical Artificial Intellegence ; Optical inference engines; Optical logic; Optical informationprocessing...common. They arise in areas such as expert systems and other artificial intelligence systems. In recent years, the computer science language PROLOG has...cal processors should in principle be well suited for : I artificial intelligence applications. In recent years, symbolic logic processing. , the

  14. Inferring Microbial Fitness Landscapes

    DTIC Science & Technology

    2016-02-25

    the foundational work on the mathematical analysis of these diffusion equations , and established the needed connections with stochastic differential ...SECURITY CLASSIFICATION OF: Microbes and viruses evolve. Their evolution is often more rapid and of greater practical importance than our own evolution ...infer from data the determinants of microbial evolution with sufficient resolution that we can quantify 1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND

  15. Active inference and learning.

    PubMed

    Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; O'Doherty, John; Pezzulo, Giovanni

    2016-09-01

    This paper offers an active inference account of choice behaviour and learning. It focuses on the distinction between goal-directed and habitual behaviour and how they contextualise each other. We show that habits emerge naturally (and autodidactically) from sequential policy optimisation when agents are equipped with state-action policies. In active inference, behaviour has explorative (epistemic) and exploitative (pragmatic) aspects that are sensitive to ambiguity and risk respectively, where epistemic (ambiguity-resolving) behaviour enables pragmatic (reward-seeking) behaviour and the subsequent emergence of habits. Although goal-directed and habitual policies are usually associated with model-based and model-free schemes, we find the more important distinction is between belief-free and belief-based schemes. The underlying (variational) belief updating provides a comprehensive (if metaphorical) process theory for several phenomena, including the transfer of dopamine responses, reversal learning, habit formation and devaluation. Finally, we show that active inference reduces to a classical (Bellman) scheme, in the absence of ambiguity.

  16. Towards Context Sensitive Information Inference.

    ERIC Educational Resources Information Center

    Song, D.; Bruza, P. D.

    2003-01-01

    Discusses information inference from a psychologistic stance and proposes an information inference mechanism that makes inferences via computations of information flow through an approximation of a conceptual space. Highlights include cognitive economics of information processing; context sensitivity; and query models for information retrieval.…

  17. Multimodel inference and adaptive management

    USGS Publications Warehouse

    Rehme, S.E.; Powell, L.A.; Allen, C.R.

    2011-01-01

    Ecology is an inherently complex science coping with correlated variables, nonlinear interactions and multiple scales of pattern and process, making it difficult for experiments to result in clear, strong inference. Natural resource managers, policy makers, and stakeholders rely on science to provide timely and accurate management recommendations. However, the time necessary to untangle the complexities of interactions within ecosystems is often far greater than the time available to make management decisions. One method of coping with this problem is multimodel inference. Multimodel inference assesses uncertainty by calculating likelihoods among multiple competing hypotheses, but multimodel inference results are often equivocal. Despite this, there may be pressure for ecologists to provide management recommendations regardless of the strength of their study’s inference. We reviewed papers in the Journal of Wildlife Management (JWM) and the journal Conservation Biology (CB) to quantify the prevalence of multimodel inference approaches, the resulting inference (weak versus strong), and how authors dealt with the uncertainty. Thirty-eight percent and 14%, respectively, of articles in the JWM and CB used multimodel inference approaches. Strong inference was rarely observed, with only 7% of JWM and 20% of CB articles resulting in strong inference. We found the majority of weak inference papers in both journals (59%) gave specific management recommendations. Model selection uncertainty was ignored in most recommendations for management. We suggest that adaptive management is an ideal method to resolve uncertainty when research results in weak inference.

  18. Visual Inference Programming

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter

    2002-01-01

    The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

  19. Visual Inference Programming

    NASA Technical Reports Server (NTRS)

    Wheeler, Kevin; Timucin, Dogan; Rabbette, Maura; Curry, Charles; Allan, Mark; Lvov, Nikolay; Clanton, Sam; Pilewskie, Peter

    2002-01-01

    The goal of visual inference programming is to develop a software framework data analysis and to provide machine learning algorithms for inter-active data exploration and visualization. The topics include: 1) Intelligent Data Understanding (IDU) framework; 2) Challenge problems; 3) What's new here; 4) Framework features; 5) Wiring diagram; 6) Generated script; 7) Results of script; 8) Initial algorithms; 9) Independent Component Analysis for instrument diagnosis; 10) Output sensory mapping virtual joystick; 11) Output sensory mapping typing; 12) Closed-loop feedback mu-rhythm control; 13) Closed-loop training; 14) Data sources; and 15) Algorithms. This paper is in viewgraph form.

  20. Nanotechnology and statistical inference

    NASA Astrophysics Data System (ADS)

    Vesely, Sara; Vesely, Leonardo; Vesely, Alessandro

    2017-08-01

    We discuss some problems that arise when applying statistical inference to data with the aim of disclosing new func-tionalities. A predictive model analyzes the data taken from experiments on a specific material to assess the likelihood that another product, with similar structure and properties, will exhibit the same functionality. It doesn't have much predictive power if vari-ability occurs as a consequence of a specific, non-linear behavior. We exemplify our discussion on some experiments with biased dice.

  1. Inferring Mealy Machines

    NASA Astrophysics Data System (ADS)

    Shahbaz, Muzammil; Groz, Roland

    Automata learning techniques are getting significant importance for their applications in a wide variety of software engineering problems, especially in the analysis and testing of complex systems. In recent studies, a previous learning approach [1] has been extended to synthesize Mealy machine models which are specifically tailored for I/O based systems. In this paper, we discuss the inference of Mealy machines and propose improvements that reduces the worst-time learning complexity of the existing algorithm. The gain over the complexity of the proposed algorithm has also been confirmed by experimentation on a large set of finite state machines.

  2. Moment inference from tomograms

    USGS Publications Warehouse

    Day-Lewis, F. D.; Chen, Y.; Singha, K.

    2007-01-01

    Time-lapse geophysical tomography can provide valuable qualitative insights into hydrologic transport phenomena associated with aquifer dynamics, tracer experiments, and engineered remediation. Increasingly, tomograms are used to infer the spatial and/or temporal moments of solute plumes; these moments provide quantitative information about transport processes (e.g., advection, dispersion, and rate-limited mass transfer) and controlling parameters (e.g., permeability, dispersivity, and rate coefficients). The reliability of moments calculated from tomograms is, however, poorly understood because classic approaches to image appraisal (e.g., the model resolution matrix) are not directly applicable to moment inference. Here, we present a semi-analytical approach to construct a moment resolution matrix based on (1) the classic model resolution matrix and (2) image reconstruction from orthogonal moments. Numerical results for radar and electrical-resistivity imaging of solute plumes demonstrate that moment values calculated from tomograms depend strongly on plume location within the tomogram, survey geometry, regularization criteria, and measurement error. Copyright 2007 by the American Geophysical Union.

  3. Circular inferences in schizophrenia.

    PubMed

    Jardri, Renaud; Denève, Sophie

    2013-11-01

    A considerable number of recent experimental and computational studies suggest that subtle impairments of excitatory to inhibitory balance or regulation are involved in many neurological and psychiatric conditions. The current paper aims to relate, specifically and quantitatively, excitatory to inhibitory imbalance with psychotic symptoms in schizophrenia. Considering that the brain constructs hierarchical causal models of the external world, we show that the failure to maintain the excitatory to inhibitory balance results in hallucinations as well as in the formation and subsequent consolidation of delusional beliefs. Indeed, the consequence of excitatory to inhibitory imbalance in a hierarchical neural network is equated to a pathological form of causal inference called 'circular belief propagation'. In circular belief propagation, bottom-up sensory information and top-down predictions are reverberated, i.e. prior beliefs are misinterpreted as sensory observations and vice versa. As a result, these predictions are counted multiple times. Circular inference explains the emergence of erroneous percepts, the patient's overconfidence when facing probabilistic choices, the learning of 'unshakable' causal relationships between unrelated events and a paradoxical immunity to perceptual illusions, which are all known to be associated with schizophrenia.

  4. Inferring Horizontal Gene Transfer

    PubMed Central

    Lassalle, Florent; Dessimoz, Christophe

    2015-01-01

    Horizontal or Lateral Gene Transfer (HGT or LGT) is the transmission of portions of genomic DNA between organisms through a process decoupled from vertical inheritance. In the presence of HGT events, different fragments of the genome are the result of different evolutionary histories. This can therefore complicate the investigations of evolutionary relatedness of lineages and species. Also, as HGT can bring into genomes radically different genotypes from distant lineages, or even new genes bearing new functions, it is a major source of phenotypic innovation and a mechanism of niche adaptation. For example, of particular relevance to human health is the lateral transfer of antibiotic resistance and pathogenicity determinants, leading to the emergence of pathogenic lineages [1]. Computational identification of HGT events relies upon the investigation of sequence composition or evolutionary history of genes. Sequence composition-based ("parametric") methods search for deviations from the genomic average, whereas evolutionary history-based ("phylogenetic") approaches identify genes whose evolutionary history significantly differs from that of the host species. The evaluation and benchmarking of HGT inference methods typically rely upon simulated genomes, for which the true history is known. On real data, different methods tend to infer different HGT events, and as a result it can be difficult to ascertain all but simple and clear-cut HGT events. PMID:26020646

  5. Bayesian inference in geomagnetism

    NASA Technical Reports Server (NTRS)

    Backus, George E.

    1988-01-01

    The inverse problem in empirical geomagnetic modeling is investigated, with critical examination of recently published studies. Particular attention is given to the use of Bayesian inference (BI) to select the damping parameter lambda in the uniqueness portion of the inverse problem. The mathematical bases of BI and stochastic inversion are explored, with consideration of bound-softening problems and resolution in linear Gaussian BI. The problem of estimating the radial magnetic field B(r) at the earth core-mantle boundary from surface and satellite measurements is then analyzed in detail, with specific attention to the selection of lambda in the studies of Gubbins (1983) and Gubbins and Bloxham (1985). It is argued that the selection method is inappropriate and leads to lambda values much larger than those that would result if a reasonable bound on the heat flow at the CMB were assumed.

  6. BIE: Bayesian Inference Engine

    NASA Astrophysics Data System (ADS)

    Weinberg, Martin D.

    2013-12-01

    The Bayesian Inference Engine (BIE) is an object-oriented library of tools written in C++ designed explicitly to enable Bayesian update and model comparison for astronomical problems. To facilitate "what if" exploration, BIE provides a command line interface (written with Bison and Flex) to run input scripts. The output of the code is a simulation of the Bayesian posterior distribution from which summary statistics e.g. by taking moments, or determine confidence intervals and so forth, can be determined. All of these quantities are fundamentally integrals and the Markov Chain approach produces variates heta distributed according to P( heta|D) so moments are trivially obtained by summing of the ensemble of variates.

  7. Bayes factors and multimodel inference

    USGS Publications Warehouse

    Link, W.A.; Barker, R.J.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

    2009-01-01

    Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

  8. Skin manifestations of primary immune deficiency.

    PubMed

    Lehman, Heather

    2014-04-01

    Cutaneous manifestations are common in primary immune deficiency diseases, affecting between 40 % and 70 % of patients with diagnosed primary immune deficiency. Skin infections characterize many primary immune deficiencies, but there are also frequent noninfectious cutaneous manifestations seen in many of these disorders, including eczematous lesions, erythroderma, cutaneous granulomas, dysplasia of skin, hair, and nails, autoimmune conditions, and frank vasculitis. For the patient with suspected primary immunodeficiency, much can be inferred by evaluating the presenting cutaneous findings, including various infectious susceptibilities, presence of atopy, and evidence of impaired or overactive inflammatory response. The skin manifestations of primary immune deficiency diseases are often early or heralding findings of the underlying immunologic disease. Therefore, awareness of associations between skin findings and immune deficiency may aide in the early detection and treatment of serious or life-threatening immunologic defects. This review summarizes the common skin manifestations of primary immune deficiency diseases and provides the reader with a differential diagnosis of primary immune defects to consider for the most common skin manifestations.

  9. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  10. Improving Inferences from Multiple Methods.

    ERIC Educational Resources Information Center

    Shotland, R. Lance; Mark, Melvin M.

    1987-01-01

    Multiple evaluation methods (MEMs) can cause an inferential challenge, although there are strategies to strengthen inferences. Practical and theoretical issues involved in the use by social scientists of MEMs, three potential problems in drawing inferences from MEMs, and short- and long-term strategies for alleviating these problems are outlined.…

  11. Feature Inference Learning and Eyetracking

    ERIC Educational Resources Information Center

    Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

    2009-01-01

    Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

  12. Learning to Observe "and" Infer

    ERIC Educational Resources Information Center

    Hanuscin, Deborah L.; Park Rogers, Meredith A.

    2008-01-01

    Researchers describe the need for students to have multiple opportunities and social interaction to learn about the differences between observation and inference and their role in developing scientific explanations (Harlen 2001; Simpson 2000). Helping children develop their skills of observation and inference in science while emphasizing the…

  13. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  14. Causal Inference in Retrospective Studies.

    ERIC Educational Resources Information Center

    Holland, Paul W.; Rubin, Donald B.

    1988-01-01

    The problem of drawing causal inferences from retrospective case-controlled studies is considered. A model for causal inference in prospective studies is applied to retrospective studies. Limitations of case-controlled studies are formulated concerning relevant parameters that can be estimated in such studies. A coffee-drinking/myocardial…

  15. Causal Inference and Developmental Psychology

    ERIC Educational Resources Information Center

    Foster, E. Michael

    2010-01-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…

  16. Improving Inferences from Multiple Methods.

    ERIC Educational Resources Information Center

    Shotland, R. Lance; Mark, Melvin M.

    1987-01-01

    Multiple evaluation methods (MEMs) can cause an inferential challenge, although there are strategies to strengthen inferences. Practical and theoretical issues involved in the use by social scientists of MEMs, three potential problems in drawing inferences from MEMs, and short- and long-term strategies for alleviating these problems are outlined.…

  17. Social Inference Through Technology

    NASA Astrophysics Data System (ADS)

    Oulasvirta, Antti

    Awareness cues are computer-mediated, real-time indicators of people’s undertakings, whereabouts, and intentions. Already in the mid-1970 s, UNIX users could use commands such as “finger” and “talk” to find out who was online and to chat. The small icons in instant messaging (IM) applications that indicate coconversants’ presence in the discussion space are the successors of “finger” output. Similar indicators can be found in online communities, media-sharing services, Internet relay chat (IRC), and location-based messaging applications. But presence and availability indicators are only the tip of the iceberg. Technological progress has enabled richer, more accurate, and more intimate indicators. For example, there are mobile services that allow friends to query and follow each other’s locations. Remote monitoring systems developed for health care allow relatives and doctors to assess the wellbeing of homebound patients (see, e.g., Tang and Venables 2000). But users also utilize cues that have not been deliberately designed for this purpose. For example, online gamers pay attention to other characters’ behavior to infer what the other players are like “in real life.” There is a common denominator underlying these examples: shared activities rely on the technology’s representation of the remote person. The other human being is not physically present but present only through a narrow technological channel.

  18. Pyruvate kinase deficiency

    MedlinePlus

    ... the second most common cause, after glucose-6-phosphate dehydrogenase (G6PD) deficiency . PKD is found in people ... Read More Anemia Autosomal recessive Enzyme Glucose-6-phosphate dehydrogenase deficiency Hemolytic anemia Review Date 10/27/ ...

  19. Cobalamin deficiency, hyperhomocysteinemia, and dementia

    PubMed Central

    Werder, Steven F

    2010-01-01

    Introduction Although consensus guidelines recommend checking serum B12 in patients with dementia, clinicians are often faced with various questions: (1) Which patients should be tested? (2) What test should be ordered? (3) How are inferences made from such testing? (4) In addition to serum B12, should other tests be ordered? (5) Is B12 deficiency compatible with dementia of the Alzheimer’s type? (6) What is to be expected from treatment? (7) How is B12 deficiency treated? Methods On January 31st, 2009, a Medline search was performed revealing 1,627 citations related to cobalamin deficiency, hyperhomocysteinemia, and dementia. After limiting the search terms, all abstracts and/or articles and other references were categorized into six major groups (general, biochemistry, manifestations, associations and risks, evaluation, and treatment) and then reviewed in answering the above questions. Results The six major groups above are described in detail. Seventy-five key studies, series, and clinical trials were identified. Evidence-based suggestions for patient management were developed. Discussion Evidence is convincing that hyperhomocysteinemia, with or without hypovitaminosis B12, is a risk factor for dementia. In the absence of hyperhomocysteinemia, evidence is less convincing that hypovitaminosis B12 is a risk factor for dementia. B12 deficiency manifestations are variable and include abnormal psychiatric, neurological, gastrointestinal, and hematological findings. Radiological images of individuals with hyperhomocysteinemia frequently demonstrate leukoaraiosis. Assessing serum B12 and treatment of B12 deficiency is crucial for those cases in which pernicious anemia is suspected and may be useful for mild cognitive impairment and mild to moderate dementia. The serum B12 level is the standard initial test: 200 picograms per milliliter or less is low, and 201 to 350 picograms per milliliter is borderline low. Other tests may be indicated, including plasma

  20. Corneal epithelial stem cells: deficiency and regulation.

    PubMed

    Secker, Genevieve A; Daniels, Julie T

    2008-09-01

    The corneal epithelium is continuously renewed by a population of stem cells that reside in the corneoscleral junction, otherwise known as the limbus. These limbal epithelial stem cells (LESC) are imperative for corneal maintenance with deficiencies leading to in-growth of conjunctival cells, neovascularisation of the corneal stroma and eventual corneal opacity and visual loss. One such disease that has traditionally been thought to be due to LESC deficiency is aniridia, a pan-ocular congenital eye disease due to mutations in the PAX6 gene. Corneal changes or aniridia related keratopathy (ARK) seen in aniridia are typical of LESC deficiency. However, the pathophysiology behind ARK is still ill defined, with current theories suggesting it may be caused by a deficiency in the stem cell niche and adjacent corneal stroma, with altered wound healing responses also playing a role (Ramaesh et al, International Journal of Biochemistry & Cell Biology 37:547-557, 2005) or abnormal epidermal differentiation of LESC (Li et al., The Journal of Pathology 214:9, 2008). PAX6 is considered the master control gene for the eye and is required for normal eye development with expression continuing in the adult cornea, thus inferring a role for corneal repair and regeneration (Sivak et al., Developments in Biologicals 222:41-54, 2000). Studies of models of Pax6 deficiency, such as the small eyed (sey) mouse, should help to reveal the intrinsic and extrinsic mechanisms involved in normal LESC function.

  1. Epidemiology of iodine deficiency.

    PubMed

    Vanderpump, Mark P

    2017-04-01

    Iodine is an essential component of the thyroid hormones thyroxine (T4) and triiodothyronine (T3) produced by the thyroid gland. Iodine deficiency impairs thyroid hormone production and has adverse effects throughout life, particularly early in life as it impairs cognition and growth. Iodine deficiency remains a significant problem despite major national and international efforts to increase iodine intake, primarily through the voluntary or mandatory iodization of salt. Recent epidemiological data suggest that iodine deficiency is an emerging issue in industrialized countries, previously thought of as iodine-sufficient. International efforts to control iodine deficiency are slowing, and reaching the third of the worldwide population that remains deficient poses major challenges.

  2. Inferring handedness from lithic evidence.

    PubMed

    Rugg, G; Mullane, M

    2001-07-01

    Until recently research into the origins of human handedness has been hampered by the lack of valid techniques for inferring handedness in pre-modern populations. A method developed by Toth for inferring handedness from lithic evidence, based on orientation of the cortex on lithic flakes, has produced promising results. However, this method is limited in applicability and has a variable signal to noise ratio. The authors describe a separate method, based on the orientation of the cone of percussion in lithic flakes, for inferring handedness from the lithic evidence. This method complements the cortex method. Some preliminary experimental evidence is presented which indicates that handedness can be inferred from lithic evidence using the cone of percussion method. Suggestions for further research are made.

  3. Bayesian Inference of Galaxy Morphology

    NASA Astrophysics Data System (ADS)

    Yoon, Ilsang; Weinberg, M.; Katz, N.

    2011-01-01

    Reliable inference on galaxy morphology from quantitative analysis of ensemble galaxy images is challenging but essential ingredient in studying galaxy formation and evolution, utilizing current and forthcoming large scale surveys. To put galaxy image decomposition problem in broader context of statistical inference problem and derive a rigorous statistical confidence levels of the inference, I developed a novel galaxy image decomposition tool, GALPHAT (GALaxy PHotometric ATtributes) that exploits recent developments in Bayesian computation to provide full posterior probability distributions and reliable confidence intervals for all parameters. I will highlight the significant improvements in galaxy image decomposition using GALPHAT, over the conventional model fitting algorithms and introduce the GALPHAT potential to infer the statistical distribution of galaxy morphological structures, using ensemble posteriors of galaxy morphological parameters from the entire galaxy population that one studies.

  4. Bayesian Inference: with ecological applications

    USGS Publications Warehouse

    Link, William A.; Barker, Richard J.

    2010-01-01

    This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

  5. Statistical Inference: The Big Picture.

    PubMed

    Kass, Robert E

    2011-02-01

    Statistics has moved beyond the frequentist-Bayesian controversies of the past. Where does this leave our ability to interpret results? I suggest that a philosophy compatible with statistical practice, labelled here statistical pragmatism, serves as a foundation for inference. Statistical pragmatism is inclusive and emphasizes the assumptions that connect statistical models with observed data. I argue that introductory courses often mis-characterize the process of statistical inference and I propose an alternative "big picture" depiction.

  6. Active inference, communication and hermeneutics☆

    PubMed Central

    Friston, Karl J.; Frith, Christopher D.

    2015-01-01

    Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others – during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions – both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then – in principle – they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. PMID:25957007

  7. Active inference, communication and hermeneutics.

    PubMed

    Friston, Karl J; Frith, Christopher D

    2015-07-01

    Hermeneutics refers to interpretation and translation of text (typically ancient scriptures) but also applies to verbal and non-verbal communication. In a psychological setting it nicely frames the problem of inferring the intended content of a communication. In this paper, we offer a solution to the problem of neural hermeneutics based upon active inference. In active inference, action fulfils predictions about how we will behave (e.g., predicting we will speak). Crucially, these predictions can be used to predict both self and others--during speaking and listening respectively. Active inference mandates the suppression of prediction errors by updating an internal model that generates predictions--both at fast timescales (through perceptual inference) and slower timescales (through perceptual learning). If two agents adopt the same model, then--in principle--they can predict each other and minimise their mutual prediction errors. Heuristically, this ensures they are singing from the same hymn sheet. This paper builds upon recent work on active inference and communication to illustrate perceptual learning using simulated birdsongs. Our focus here is the neural hermeneutics implicit in learning, where communication facilitates long-term changes in generative models that are trying to predict each other. In other words, communication induces perceptual learning and enables others to (literally) change our minds and vice versa. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. Causal inference and developmental psychology.

    PubMed

    Foster, E Michael

    2010-11-01

    Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether the risk factor actually causes outcomes. Random assignment is not possible in many instances, and for that reason, psychologists must rely on observational studies. Such studies identify associations, and causal interpretation of such associations requires additional assumptions. Research in developmental psychology generally has relied on various forms of linear regression, but this methodology has limitations for causal inference. Fortunately, methodological developments in various fields are providing new tools for causal inference-tools that rely on more plausible assumptions. This article describes the limitations of regression for causal inference and describes how new tools might offer better causal inference. This discussion highlights the importance of properly identifying covariates to include (and exclude) from the analysis. This discussion considers the directed acyclic graph for use in accomplishing this task. With the proper covariates having been chosen, many of the available methods rely on the assumption of "ignorability." The article discusses the meaning of ignorability and considers alternatives to this assumption, such as instrumental variables estimation. Finally, the article considers the use of the tools discussed in the context of a specific research question, the effect of family structure on child development.

  9. Abductive inference and delusional belief.

    PubMed

    Coltheart, Max; Menzies, Peter; Sutton, John

    2010-01-01

    Delusional beliefs have sometimes been considered as rational inferences from abnormal experiences. We explore this idea in more detail, making the following points. First, the abnormalities of cognition that initially prompt the entertaining of a delusional belief are not always conscious and since we prefer to restrict the term "experience" to consciousness we refer to "abnormal data" rather than "abnormal experience". Second, we argue that in relation to many delusions (we consider seven) one can clearly identify what the abnormal cognitive data are which prompted the delusion and what the neuropsychological impairment is which is responsible for the occurrence of these data; but one can equally clearly point to cases where this impairment is present but delusion is not. So the impairment is not sufficient for delusion to occur: a second cognitive impairment, one that affects the ability to evaluate beliefs, must also be present. Third (and this is the main thrust of our paper), we consider in detail what the nature of the inference is that leads from the abnormal data to the belief. This is not deductive inference and it is not inference by enumerative induction; it is abductive inference. We offer a Bayesian account of abductive inference and apply it to the explanation of delusional belief.

  10. Optimal inference with suboptimal models: Addiction and active Bayesian inference

    PubMed Central

    Schwartenbeck, Philipp; FitzGerald, Thomas H.B.; Mathys, Christoph; Dolan, Ray; Wurst, Friedrich; Kronbichler, Martin; Friston, Karl

    2015-01-01

    When casting behaviour as active (Bayesian) inference, optimal inference is defined with respect to an agent’s beliefs – based on its generative model of the world. This contrasts with normative accounts of choice behaviour, in which optimal actions are considered in relation to the true structure of the environment – as opposed to the agent’s beliefs about worldly states (or the task). This distinction shifts an understanding of suboptimal or pathological behaviour away from aberrant inference as such, to understanding the prior beliefs of a subject that cause them to behave less ‘optimally’ than our prior beliefs suggest they should behave. Put simply, suboptimal or pathological behaviour does not speak against understanding behaviour in terms of (Bayes optimal) inference, but rather calls for a more refined understanding of the subject’s generative model upon which their (optimal) Bayesian inference is based. Here, we discuss this fundamental distinction and its implications for understanding optimality, bounded rationality and pathological (choice) behaviour. We illustrate our argument using addictive choice behaviour in a recently described ‘limited offer’ task. Our simulations of pathological choices and addictive behaviour also generate some clear hypotheses, which we hope to pursue in ongoing empirical work. PMID:25561321

  11. Colour vision deficiency.

    PubMed

    Simunovic, M P

    2010-05-01

    Colour vision deficiency is one of the commonest disorders of vision and can be divided into congenital and acquired forms. Congenital colour vision deficiency affects as many as 8% of males and 0.5% of females--the difference in prevalence reflects the fact that the commonest forms of congenital colour vision deficiency are inherited in an X-linked recessive manner. Until relatively recently, our understanding of the pathophysiological basis of colour vision deficiency largely rested on behavioural data; however, modern molecular genetic techniques have helped to elucidate its mechanisms. The current management of congenital colour vision deficiency lies chiefly in appropriate counselling (including career counselling). Although visual aids may be of benefit to those with colour vision deficiency when performing certain tasks, the evidence suggests that they do not enable wearers to obtain normal colour discrimination. In the future, gene therapy remains a possibility, with animal models demonstrating amelioration following treatment.

  12. Acquired color vision deficiency.

    PubMed

    Simunovic, Matthew P

    2016-01-01

    Acquired color vision deficiency occurs as the result of ocular, neurologic, or systemic disease. A wide array of conditions may affect color vision, ranging from diseases of the ocular media through to pathology of the visual cortex. Traditionally, acquired color vision deficiency is considered a separate entity from congenital color vision deficiency, although emerging clinical and molecular genetic data would suggest a degree of overlap. We review the pathophysiology of acquired color vision deficiency, the data on its prevalence, theories for the preponderance of acquired S-mechanism (or tritan) deficiency, and discuss tests of color vision. We also briefly review the types of color vision deficiencies encountered in ocular disease, with an emphasis placed on larger or more detailed clinical investigations. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Statistical inference and string theory

    NASA Astrophysics Data System (ADS)

    Heckman, Jonathan J.

    2015-09-01

    In this paper, we expose some surprising connections between string theory and statistical inference. We consider a large collective of agents sweeping out a family of nearby statistical models for an M-dimensional manifold of statistical fitting parameters. When the agents making nearby inferences align along a d-dimensional grid, we find that the pooled probability that the collective reaches a correct inference is the partition function of a nonlinear sigma model in d dimensions. Stability under perturbations to the original inference scheme requires the agents of the collective to distribute along two dimensions. Conformal invariance of the sigma model corresponds to the condition of a stable inference scheme, directly leading to the Einstein field equations for classical gravity. By summing over all possible arrangements of the agents in the collective, we reach a string theory. We also use this perspective to quantify how much an observer can hope to learn about the internal geometry of a superstring compactification. Finally, we present some brief speculative remarks on applications to the AdS/CFT correspondence and Lorentzian signature space-times.

  14. Vitamin B12 deficiency.

    PubMed

    Green, Ralph; Allen, Lindsay H; Bjørke-Monsen, Anne-Lise; Brito, Alex; Guéant, Jean-Louis; Miller, Joshua W; Molloy, Anne M; Nexo, Ebba; Stabler, Sally; Toh, Ban-Hock; Ueland, Per Magne; Yajnik, Chittaranjan

    2017-06-29

    Vitamin B12 (B12; also known as cobalamin) is a B vitamin that has an important role in cellular metabolism, especially in DNA synthesis, methylation and mitochondrial metabolism. Clinical B12 deficiency with classic haematological and neurological manifestations is relatively uncommon. However, subclinical deficiency affects between 2.5% and 26% of the general population depending on the definition used, although the clinical relevance is unclear. B12 deficiency can affect individuals at all ages, but most particularly elderly individuals. Infants, children, adolescents and women of reproductive age are also at high risk of deficiency in populations where dietary intake of B12-containing animal-derived foods is restricted. Deficiency is caused by either inadequate intake, inadequate bioavailability or malabsorption. Disruption of B12 transport in the blood, or impaired cellular uptake or metabolism causes an intracellular deficiency. Diagnostic biomarkers for B12 status include decreased levels of circulating total B12 and transcobalamin-bound B12, and abnormally increased levels of homocysteine and methylmalonic acid. However, the exact cut-offs to classify clinical and subclinical deficiency remain debated. Management depends on B12 supplementation, either via high-dose oral routes or via parenteral administration. This Primer describes the current knowledge surrounding B12 deficiency, and highlights improvements in diagnostic methods as well as shifting concepts about the prevalence, causes and manifestations of B12 deficiency.

  15. Locative inferences in medical texts.

    PubMed

    Mayer, P S; Bailey, G H; Mayer, R J; Hillis, A; Dvoracek, J E

    1987-06-01

    Medical research relies on epidemiological studies conducted on a large set of clinical records that have been collected from physicians recording individual patient observations. These clinical records are recorded for the purpose of individual care of the patient with little consideration for their use by a biostatistician interested in studying a disease over a large population. Natural language processing of clinical records for epidemiological studies must deal with temporal, locative, and conceptual issues. This makes text understanding and data extraction of clinical records an excellent area for applied research. While much has been done in making temporal or conceptual inferences in medical texts, parallel work in locative inferences has not been done. This paper examines the locative inferences as well as the integration of temporal, locative, and conceptual issues in the clinical record understanding domain by presenting an application that utilizes two key concepts in its parsing strategy--a knowledge-based parsing strategy and a minimal lexicon.

  16. Perception, illusions and Bayesian inference.

    PubMed

    Nour, Matthew M; Nour, Joseph M

    2015-01-01

    Descriptive psychopathology makes a distinction between veridical perception and illusory perception. In both cases a perception is tied to a sensory stimulus, but in illusions the perception is of a false object. This article re-examines this distinction in light of new work in theoretical and computational neurobiology, which views all perception as a form of Bayesian statistical inference that combines sensory signals with prior expectations. Bayesian perceptual inference can solve the 'inverse optics' problem of veridical perception and provides a biologically plausible account of a number of illusory phenomena, suggesting that veridical and illusory perceptions are generated by precisely the same inferential mechanisms.

  17. MENTAL DEFICIENCY. SECOND EDITION.

    ERIC Educational Resources Information Center

    HILLIARD, L.T.; KIRMAN, BRIAN H.

    REVISED TO INCLUDE LEGISLATIVE AND ADMINISTRATIVE PROCEDURES NEW IN BRITAIN SINCE THE 1957 EDITION, THE TEXT INCLUDES RECENT ADVANCES IN ETIOLOGY, PATHOLOGY, AND TREATMENT OF MENTAL DEFICIENCY. CONSIDERATION OF THE BACKGROUND OF MENTAL DEFICIENCY INCLUDES HISTORICAL AND LEGAL ASPECTS, THE SOCIAL BACKGROUND OF MENTAL DEFECT, PRENATAL CAUSES OF…

  18. Cerebral Folate Deficiency

    ERIC Educational Resources Information Center

    Gordon, Neil

    2009-01-01

    Cerebral folate deficiency (CFD) is associated with low levels of 5-methyltetrahydrofolate in the cerebrospinal fluid (CSF) with normal folate levels in the plasma and red blood cells. The onset of symptoms caused by the deficiency of folates in the brain is at around 4 to 6 months of age. This is followed by delayed development, with deceleration…

  19. Biotinidase deficiency: presymptomatic treatment.

    PubMed Central

    Wallace, S J

    1985-01-01

    Biotinidase deficiency presents with clinical signs of biotin deficiency at the age of 3 months, or soon after. In an infant in whom the diagnosis was made on cord blood, vision and hearing were normal before presymptomatic treatment with biotin. Physical and mental development are good at 14 months. PMID:4015175

  20. Biotinidase deficiency: presymptomatic treatment.

    PubMed

    Wallace, S J

    1985-06-01

    Biotinidase deficiency presents with clinical signs of biotin deficiency at the age of 3 months, or soon after. In an infant in whom the diagnosis was made on cord blood, vision and hearing were normal before presymptomatic treatment with biotin. Physical and mental development are good at 14 months.

  1. Cerebral Folate Deficiency

    ERIC Educational Resources Information Center

    Gordon, Neil

    2009-01-01

    Cerebral folate deficiency (CFD) is associated with low levels of 5-methyltetrahydrofolate in the cerebrospinal fluid (CSF) with normal folate levels in the plasma and red blood cells. The onset of symptoms caused by the deficiency of folates in the brain is at around 4 to 6 months of age. This is followed by delayed development, with deceleration…

  2. Iron induced nickel deficiency

    USDA-ARS?s Scientific Manuscript database

    It is increasingly apparent that economic loss due to nickel (Ni) deficiency likely occurs in horticultural and agronomic crops. While most soils contain sufficient Ni to meet crop requirements, situations of Ni deficiency can arise due to antagonistic interactions with other metals. This study asse...

  3. Vitamin Deficiency Anemia

    MedlinePlus

    ... used to treat cancer can interfere with the metabolism of folate. Vitamin B-12 deficiency anemia risk factors include: Lack of intrinsic factor. Most people with a vitamin B-12 deficiency anemia lack intrinsic factor — a protein secreted by the stomach that is necessary for ...

  4. MENTAL DEFICIENCY. SECOND EDITION.

    ERIC Educational Resources Information Center

    HILLIARD, L.T.; KIRMAN, BRIAN H.

    REVISED TO INCLUDE LEGISLATIVE AND ADMINISTRATIVE PROCEDURES NEW IN BRITAIN SINCE THE 1957 EDITION, THE TEXT INCLUDES RECENT ADVANCES IN ETIOLOGY, PATHOLOGY, AND TREATMENT OF MENTAL DEFICIENCY. CONSIDERATION OF THE BACKGROUND OF MENTAL DEFICIENCY INCLUDES HISTORICAL AND LEGAL ASPECTS, THE SOCIAL BACKGROUND OF MENTAL DEFECT, PRENATAL CAUSES OF…

  5. Improving Explanatory Inferences from Assessments

    ERIC Educational Resources Information Center

    Diakow, Ronli Phyllis

    2013-01-01

    This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

  6. Perceptual Inference and Autistic Traits

    ERIC Educational Resources Information Center

    Skewes, Joshua C; Jegindø, Else-Marie; Gebauer, Line

    2015-01-01

    Autistic people are better at perceiving details. Major theories explain this in terms of bottom-up sensory mechanisms or in terms of top-down cognitive biases. Recently, it has become possible to link these theories within a common framework. This framework assumes that perception is implicit neural inference, combining sensory evidence with…

  7. The mechanisms of temporal inference

    NASA Technical Reports Server (NTRS)

    Fox, B. R.; Green, S. R.

    1987-01-01

    The properties of a temporal language are determined by its constituent elements: the temporal objects which it can represent, the attributes of those objects, the relationships between them, the axioms which define the default relationships, and the rules which define the statements that can be formulated. The methods of inference which can be applied to a temporal language are derived in part from a small number of axioms which define the meaning of equality and order and how those relationships can be propagated. More complex inferences involve detailed analysis of the stated relationships. Perhaps the most challenging area of temporal inference is reasoning over disjunctive temporal constraints. Simple forms of disjunction do not sufficiently increase the expressive power of a language while unrestricted use of disjunction makes the analysis NP-hard. In many cases a set of disjunctive constraints can be converted to disjunctive normal form and familiar methods of inference can be applied to the conjunctive sub-expressions. This process itself is NP-hard but it is made more tractable by careful expansion of a tree-structured search space.

  8. Word Learning as Bayesian Inference

    ERIC Educational Resources Information Center

    Xu, Fei; Tenenbaum, Joshua B.

    2007-01-01

    The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…

  9. Science Shorts: Observation versus Inference

    ERIC Educational Resources Information Center

    Leager, Craig R.

    2008-01-01

    When you observe something, how do you know for sure what you are seeing, feeling, smelling, or hearing? Asking students to think critically about their encounters with the natural world will help to strengthen their understanding and application of the science-process skills of observation and inference. In the following lesson, students make…

  10. Word Learning as Bayesian Inference

    ERIC Educational Resources Information Center

    Xu, Fei; Tenenbaum, Joshua B.

    2007-01-01

    The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with…

  11. Starfish: Robust spectroscopic inference tools

    NASA Astrophysics Data System (ADS)

    Czekala, Ian; Andrews, Sean M.; Mandel, Kaisey S.; Hogg, David W.; Green, Gregory M.

    2015-05-01

    Starfish is a set of tools used for spectroscopic inference. It robustly determines stellar parameters using high resolution spectral models and uses Markov Chain Monte Carlo (MCMC) to explore the full posterior probability distribution of the stellar parameters. Additional potential applications include other types of spectra, such as unresolved stellar clusters or supernovae spectra.

  12. Statistical inference and Aristotle's Rhetoric.

    PubMed

    Macdonald, Ranald R

    2004-11-01

    Formal logic operates in a closed system where all the information relevant to any conclusion is present, whereas this is not the case when one reasons about events and states of the world. Pollard and Richardson drew attention to the fact that the reasoning behind statistical tests does not lead to logically justifiable conclusions. In this paper statistical inferences are defended not by logic but by the standards of everyday reasoning. Aristotle invented formal logic, but argued that people mostly get at the truth with the aid of enthymemes--incomplete syllogisms which include arguing from examples, analogies and signs. It is proposed that statistical tests work in the same way--in that they are based on examples, invoke the analogy of a model and use the size of the effect under test as a sign that the chance hypothesis is unlikely. Of existing theories of statistical inference only a weak version of Fisher's takes this into account. Aristotle anticipated Fisher by producing an argument of the form that there were too many cases in which an outcome went in a particular direction for that direction to be plausibly attributed to chance. We can therefore conclude that Aristotle would have approved of statistical inference and there is a good reason for calling this form of statistical inference classical.

  13. How Forgetting Aids Heuristic Inference

    ERIC Educational Resources Information Center

    Schooler, Lael J.; Hertwig, Ralph

    2005-01-01

    Some theorists, ranging from W. James (1890) to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2…

  14. Science Shorts: Observation versus Inference

    ERIC Educational Resources Information Center

    Leager, Craig R.

    2008-01-01

    When you observe something, how do you know for sure what you are seeing, feeling, smelling, or hearing? Asking students to think critically about their encounters with the natural world will help to strengthen their understanding and application of the science-process skills of observation and inference. In the following lesson, students make…

  15. Perceptual Inference and Autistic Traits

    ERIC Educational Resources Information Center

    Skewes, Joshua C; Jegindø, Else-Marie; Gebauer, Line

    2015-01-01

    Autistic people are better at perceiving details. Major theories explain this in terms of bottom-up sensory mechanisms or in terms of top-down cognitive biases. Recently, it has become possible to link these theories within a common framework. This framework assumes that perception is implicit neural inference, combining sensory evidence with…

  16. Acrodermatitis Enteropathica-like Eruption Associated with Combined Nutritional Deficiency

    PubMed Central

    Kim, You Jeong; Kim, Mi-Yeon; Kim, Hyung Ok; Lee, Myung Duck

    2005-01-01

    We present here a case of acrodermatitis enteropathica-like eruption associated with essential free fatty acid and protein deficiencies as well as borderline zinc deficiency that occurred after Whipple's operation in a 31-yr-old woman. Her eruptions were improved not by zinc supplements alone, but her condition was improved by total parenteral nutrition including amino acids, albumin, lipid and zinc. Although we could not exactly decide which of the nutrients contributed the most to her manifestations, we inferred that all three elements in concert caused her dermatoses. This case shows that even though the patient's skin manifestations and laboratory results are suggestive of acrodermatitis enteropathica, the physicians should keep in mind the possibility that this disease can be associated with other nutritional deficiencies such as free fatty acid or protein deficiency. PMID:16224175

  17. Spontaneous evaluative inferences and their relationship to spontaneous trait inferences.

    PubMed

    Schneid, Erica D; Carlston, Donal E; Skowronski, John J

    2015-05-01

    Three experiments are reported that explore affectively based spontaneous evaluative impressions (SEIs) of stimulus persons. Experiments 1 and 2 used modified versions of the savings in relearning paradigm (Carlston & Skowronski, 1994) to confirm the occurrence of SEIs, indicating that they are equivalent whether participants are instructed to form trait impressions, evaluative impressions, or neither. These experiments also show that SEIs occur independently of explicit recall for the trait implications of the stimuli. Experiment 3 provides a single dissociation test to distinguish SEIs from spontaneous trait inferences (STIs), showing that disrupting cognitive processing interferes with a trait-based prediction task that presumably reflects STIs, but not with an affectively based social approach task that presumably reflects SEIs. Implications of these findings for the potential independence of spontaneous trait and evaluative inferences, as well as limitations and important steps for future study are discussed. (c) 2015 APA, all rights reserved).

  18. Towards General Algorithms for Grammatical Inference

    NASA Astrophysics Data System (ADS)

    Clark, Alexander

    Many algorithms for grammatical inference can be viewed as instances of a more general algorithm which maintains a set of primitive elements, which distributionally define sets of strings, and a set of features or tests that constrain various inference rules. Using this general framework, which we cast as a process of logical inference, we re-analyse Angluin's famous lstar algorithm and several recent algorithms for the inference of context-free grammars and multiple context-free grammars. Finally, to illustrate the advantages of this approach, we extend it to the inference of functional transductions from positive data only, and we present a new algorithm for the inference of finite state transducers.

  19. Drugs producing vitamin deficiencies.

    PubMed

    Montenero, A S

    1980-01-01

    Many drugs produce vitamin deficiencies. They belong to the most important and common therapeutical classes: analgesics, antianemics, antibacterial and antiblastic agents, antibiotics, antidiabetics, antimalarials, antiphlogistics, antipyretics, diuretics, laxatives and purgatives, tranquilizers and anticonvulsives, radiomimetics, hormones and vitamins themselves. The vitamin deprivation processes may be produced by a variety of mechanisms and may involve all vitamins. Recent experiments indicate that there is a competition for binding sites on proteins between vitamin C and salicylate and between dicoumarol and vitamin K. Usually a drug exerts a "devitaminizing" action with respect to only one vitamin. However there are examples of multiple vitamin deficiencies induced by a single drug, like salicylate which deprives the organism of vitamins C, K and pantothenate. These deficiencies may develop either all at the same time or successively. A direct and concomitant vitamin depriving action occurs when an antibiotic blocks the production of vitamins by the enteric flora. A different mode of action occurs in the drug induced folic acid deficiency, which in turn induces a deficiency of vitamin B12. It has been reported that a vitamin deficiency may result from intake of high pharmacological doses of other vitamins. These data need confirmation in patients treated with high doses of nicotinic acid. The drug induced vitamin deficiencies are studied with the same methodology employed for avitaminoses in general; hence they can be diagnosed using the same criteria.

  20. Betaine deficiency in maize

    SciTech Connect

    Lerma, C. ); Rich, P.J.; Ju, G.C.; Yang, Wenju; Rhodes, D. ); Hanson, A.D. )

    1991-04-01

    Maize (Zea mays L.) is a betaine-accumulating species, but certain maize genotypes lack betaine almost completely; a single recessive gene has been implicated as the cause of this deficiency. This study was undertaken to determine whether betaine deficiency in diverse maize germplasm is conditioned by the same genetic locus, and to define the biochemical lesion(s) involved. Complementation tests indicated that all 13 deficient genotypes tested shared a common locus. One maize population (P77) was found to be segregating for betaine deficiency, and true breeding individuals were used to produce related lines with and without betaine. Leaf tissue of both betaine-positive and betaine-deficient lines readily converted supplied betaine aldehyde to betaine, but only the betaine-containing line was able to oxidize supplied choline to betaine. This locates the lesion in betaine-deficient plants at the choline {r arrow} betaine aldehyde step of betaine synthesis. Consistent with this location, betaine-deficient plants were shown to have no detectable endogenous pool of betaine aldehyde.

  1. Iron Deficiency Anemia.

    PubMed

    DeLoughery, Thomas G

    2017-03-01

    Iron deficiency is one of the most common causes of anemia. The 2 main etiologies of iron deficiency are blood loss due to menstrual periods and blood loss due to gastrointestinal bleeding. Beyond anemia, lack of iron has protean manifestations, including fatigue, hair loss, and restless legs. The most efficient test for the diagnosis of iron deficiency is the serum ferritin. Iron replacement can be done orally, or in patients in whom oral iron is not effective or contraindicated, with intravenous iron. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Iodine deficiency: Clinical implications.

    PubMed

    Niwattisaiwong, Soamsiri; Burman, Kenneth D; Li-Ng, Melissa

    2017-03-01

    Iodine is crucial for thyroid hormone synthesis and fetal neurodevelopment. Major dietary sources of iodine in the United States are dairy products and iodized salt. Potential consequences of iodine deficiency are goiter, hypothyroidism, cretinism, and impaired cognitive development. Although iodine status in the United States is considered sufficient at the population level, intake varies widely across the population, and the percentage of women of childbearing age with iodine deficiency is increasing. Physicians should be aware of the risks of iodine deficiency and the indications for iodine supplementation, especially in women who are pregnant or lactating.

  3. Inferring Centrality from Network Snapshots

    NASA Astrophysics Data System (ADS)

    Shao, Haibin; Mesbahi, Mehran; Li, Dewei; Xi, Yugeng

    2017-01-01

    The topology and dynamics of a complex network shape its functionality. However, the topologies of many large-scale networks are either unavailable or incomplete. Without the explicit knowledge of network topology, we show how the data generated from the network dynamics can be utilised to infer the tempo centrality, which is proposed to quantify the influence of nodes in a consensus network. We show that the tempo centrality can be used to construct an accurate estimate of both the propagation rate of influence exerted on consensus networks and the Kirchhoff index of the underlying graph. Moreover, the tempo centrality also encodes the disturbance rejection of nodes in a consensus network. Our findings provide an approach to infer the performance of a consensus network from its temporal data.

  4. System Support for Forensic Inference

    NASA Astrophysics Data System (ADS)

    Gehani, Ashish; Kirchner, Florent; Shankar, Natarajan

    Digital evidence is playing an increasingly important role in prosecuting crimes. The reasons are manifold: financially lucrative targets are now connected online, systems are so complex that vulnerabilities abound and strong digital identities are being adopted, making audit trails more useful. If the discoveries of forensic analysts are to hold up to scrutiny in court, they must meet the standard for scientific evidence. Software systems are currently developed without consideration of this fact. This paper argues for the development of a formal framework for constructing “digital artifacts” that can serve as proxies for physical evidence; a system so imbued would facilitate sound digital forensic inference. A case study involving a filesystem augmentation that provides transparent support for forensic inference is described.

  5. Bayesian Inference on Proportional Elections

    PubMed Central

    Brunello, Gabriel Hideki Vatanabe; Nakano, Eduardo Yoshio

    2015-01-01

    Polls for majoritarian voting systems usually show estimates of the percentage of votes for each candidate. However, proportional vote systems do not necessarily guarantee the candidate with the most percentage of votes will be elected. Thus, traditional methods used in majoritarian elections cannot be applied on proportional elections. In this context, the purpose of this paper was to perform a Bayesian inference on proportional elections considering the Brazilian system of seats distribution. More specifically, a methodology to answer the probability that a given party will have representation on the chamber of deputies was developed. Inferences were made on a Bayesian scenario using the Monte Carlo simulation technique, and the developed methodology was applied on data from the Brazilian elections for Members of the Legislative Assembly and Federal Chamber of Deputies in 2010. A performance rate was also presented to evaluate the efficiency of the methodology. Calculations and simulations were carried out using the free R statistical software. PMID:25786259

  6. Inferring biotic interactions from proxies.

    PubMed

    Morales-Castilla, Ignacio; Matias, Miguel G; Gravel, Dominique; Araújo, Miguel B

    2015-06-01

    Inferring biotic interactions from functional, phylogenetic and geographical proxies remains one great challenge in ecology. We propose a conceptual framework to infer the backbone of biotic interaction networks within regional species pools. First, interacting groups are identified to order links and remove forbidden interactions between species. Second, additional links are removed by examination of the geographical context in which species co-occur. Third, hypotheses are proposed to establish interaction probabilities between species. We illustrate the framework using published food-webs in terrestrial and marine systems. We conclude that preliminary descriptions of the web of life can be made by careful integration of data with theory. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. Statistical learning and selective inference

    PubMed Central

    Taylor, Jonathan; Tibshirani, Robert J.

    2015-01-01

    We describe the problem of “selective inference.” This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have “cherry-picked”—searched for the strongest associations—means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis. PMID:26100887

  8. Inferring Centrality from Network Snapshots

    PubMed Central

    Shao, Haibin; Mesbahi, Mehran; Li, Dewei; Xi, Yugeng

    2017-01-01

    The topology and dynamics of a complex network shape its functionality. However, the topologies of many large-scale networks are either unavailable or incomplete. Without the explicit knowledge of network topology, we show how the data generated from the network dynamics can be utilised to infer the tempo centrality, which is proposed to quantify the influence of nodes in a consensus network. We show that the tempo centrality can be used to construct an accurate estimate of both the propagation rate of influence exerted on consensus networks and the Kirchhoff index of the underlying graph. Moreover, the tempo centrality also encodes the disturbance rejection of nodes in a consensus network. Our findings provide an approach to infer the performance of a consensus network from its temporal data. PMID:28098166

  9. Network Plasticity as Bayesian Inference

    PubMed Central

    Legenstein, Robert; Maass, Wolfgang

    2015-01-01

    General results from statistical learning theory suggest to understand not only brain computations, but also brain plasticity as probabilistic inference. But a model for that has been missing. We propose that inherently stochastic features of synaptic plasticity and spine motility enable cortical networks of neurons to carry out probabilistic inference by sampling from a posterior distribution of network configurations. This model provides a viable alternative to existing models that propose convergence of parameters to maximum likelihood values. It explains how priors on weight distributions and connection probabilities can be merged optimally with learned experience, how cortical networks can generalize learned information so well to novel experiences, and how they can compensate continuously for unforeseen disturbances of the network. The resulting new theory of network plasticity explains from a functional perspective a number of experimental data on stochastic aspects of synaptic plasticity that previously appeared to be quite puzzling. PMID:26545099

  10. Statistical learning and selective inference.

    PubMed

    Taylor, Jonathan; Tibshirani, Robert J

    2015-06-23

    We describe the problem of "selective inference." This addresses the following challenge: Having mined a set of data to find potential associations, how do we properly assess the strength of these associations? The fact that we have "cherry-picked"--searched for the strongest associations--means that we must set a higher bar for declaring significant the associations that we see. This challenge becomes more important in the era of big data and complex statistical modeling. The cherry tree (dataset) can be very large and the tools for cherry picking (statistical learning methods) are now very sophisticated. We describe some recent new developments in selective inference and illustrate their use in forward stepwise regression, the lasso, and principal components analysis.

  11. Causal inference based on counterfactuals

    PubMed Central

    Höfler, M

    2005-01-01

    Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept. PMID:16159397

  12. Bayesian inference for agreement measures.

    PubMed

    Vidal, Ignacio; de Castro, Mário

    2016-08-25

    The agreement of different measurement methods is an important issue in several disciplines like, for example, Medicine, Metrology, and Engineering. In this article, some agreement measures, common in the literature, were analyzed from a Bayesian point of view. Posterior inferences for such agreement measures were obtained based on well-known Bayesian inference procedures for the bivariate normal distribution. As a consequence, a general, simple, and effective method is presented, which does not require Markov Chain Monte Carlo methods and can be applied considering a great variety of prior distributions. Illustratively, the method was exemplified using five objective priors for the bivariate normal distribution. A tool for assessing the adequacy of the model is discussed. Results from a simulation study and an application to a real dataset are also reported.

  13. Inferring the Why in Images

    DTIC Science & Technology

    2014-01-01

    psychophysics as the theory of mind. In this paper, we strive to build a computational model that predicts the motivation behind the actions of people from...other people?s actions, likely due to cognitive skills known in psychophysics as the theory of mind. In this paper, we strive to build a...18 Humans may be able to make such remarkable inferences partially due to cognitive skills known as the theory of mind [34]. Psychophysics researchers

  14. Inference of reversible tree languages.

    PubMed

    López, Damián; Sempere, José M; García, Pedro

    2004-08-01

    In this paper, we study the notion of k-reversibility and k-testability when regular tree languages are involved. We present an inference algorithm for learning a k-testable tree language that runs in polynomial time with respect to the size of the sample used. We also study the tree language classes in relation to other well known ones, and some properties of these languages are proven.

  15. Statistical Inference in Graphical Models

    DTIC Science & Technology

    2008-06-17

    beliefNetwork> </ hercules> Figure 2 1. BNET XML encoding of a Bayesian Network. 28 The most complete package is Kevin Murphy’s Bayes Net Toolbox ( BNT ), an...networks, and dynamic Bayesian networks. Since 2002, researchers at Intel have been converting BNT to an open-source C++ library called the...of C++, and also offers interfaces for calling the library from MATLAB and R 1361. Notably, both BNT and PNL provide learning and inference algorithms

  16. Cortical circuits for perceptual inference.

    PubMed

    Friston, Karl; Kiebel, Stefan

    2009-10-01

    This paper assumes that cortical circuits have evolved to enable inference about the causes of sensory input received by the brain. This provides a principled specification of what neural circuits have to achieve. Here, we attempt to address how the brain makes inferences by casting inference as an optimisation problem. We look at how the ensuing recognition dynamics could be supported by directed connections and message-passing among neuronal populations, given our knowledge of intrinsic and extrinsic neuronal connections. We assume that the brain models the world as a dynamic system, which imposes causal structure on the sensorium. Perception is equated with the optimisation or inversion of this internal model, to explain sensory input. Given a model of how sensory data are generated, we use a generic variational approach to model inversion to furnish equations that prescribe recognition; i.e., the dynamics of neuronal activity that represents the causes of sensory input. Here, we focus on a model whose hierarchical and dynamical structure enables simulated brains to recognise and predict sequences of sensory states. We first review these models and their inversion under a variational free-energy formulation. We then show that the brain has the necessary infrastructure to implement this inversion and present stimulations using synthetic birds that generate and recognise birdsongs.

  17. An introduction to causal inference.

    PubMed

    Pearl, Judea

    2010-02-26

    This paper summarizes recent advances in causal inference and underscores the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underlie all causal inferences, the languages used in formulating those assumptions, the conditional nature of all causal and counterfactual claims, and the methods that have been developed for the assessment of such claims. These advances are illustrated using a general theory of causation based on the Structural Causal Model (SCM) described in Pearl (2000a), which subsumes and unifies other approaches to causation, and provides a coherent mathematical foundation for the analysis of causes and counterfactuals. In particular, the paper surveys the development of mathematical tools for inferring (from a combination of data and assumptions) answers to three types of causal queries: those about (1) the effects of potential interventions, (2) probabilities of counterfactuals, and (3) direct and indirect effects (also known as "mediation"). Finally, the paper defines the formal and conceptual relationships between the structural and potential-outcome frameworks and presents tools for a symbiotic analysis that uses the strong features of both. The tools are demonstrated in the analyses of mediation, causes of effects, and probabilities of causation.

  18. Alpha-1 Antitrypsin Deficiency

    MedlinePlus

    ... much as 20 years. AAT deficiency has no cure, but treatments are available. Treatments often are based on the type of disease you develop. Rate This Content: NEXT >> Updated: October 11, 2011 Twitter Facebook YouTube ...

  19. Factor VII deficiency

    MedlinePlus

    ... if one or more of these factors are missing or are not functioning like they should. Factor VII is one such coagulation factor. Factor VII deficiency runs in families (inherited) and is very rare. Both parents must ...

  20. Factor II deficiency

    MedlinePlus

    ... if one or more of these factors are missing or are not functioning like they should. Factor II is one such coagulation factor. Factor II deficiency runs in families (inherited) and is very rare. Both parents must ...

  1. Growth hormone deficiency - children

    MedlinePlus

    Growth hormone deficiency means the pituitary gland does not make enough growth hormone. ... The pituitary gland is located at the base of the brain. This gland controls the body's balance of hormones. It ...

  2. Alpha-1 antitrypsin deficiency

    MedlinePlus

    ... liver from damage. The condition can lead to emphysema and liver disease ( cirrhosis ). ... descent. Adults with severe A1AT deficiency will develop emphysema, often before 40 years of age. Smoking can ...

  3. Sleep Deprivation and Deficiency

    MedlinePlus

    ... page from the NHLBI on Twitter. What Are Sleep Deprivation and Deficiency? Sleep deprivation (DEP-rih-VA- ... Rate This Content: NEXT >> Updated: June 7, 2017 Sleep Infographic Sleep Disorders & Insufficient Sleep: Improving Health through ...

  4. DOCK8 Deficiency

    MedlinePlus

    ... care at NIAID, visit the NIAID PIDD site . Credit: NIAID Scientist at microscope. Causes DOCK8 deficiency is ... The End of an Era Acknowledgments References Photo Credits Dr. Joseph Kinyoun: Selected Bibliography NIAID 60th Anniversary ...

  5. Adenine phosphoribosyltransferase deficiency.

    PubMed

    Bollée, Guillaume; Harambat, Jérôme; Bensman, Albert; Knebelmann, Bertrand; Daudon, Michel; Ceballos-Picot, Irène

    2012-09-01

    Complete adenine phosphoribosyltransferase (APRT) deficiency is a rare inherited metabolic disorder that leads to the formation and hyperexcretion of 2,8-dihydroxyadenine (DHA) into urine. The low solubility of DHA results in precipitation of this compound and the formation of urinary crystals and stones. The disease can present as recurrent urolithiasis or nephropathy secondary to crystal precipitation into renal parenchyma (DHA nephropathy). The diagnostic tools available-including stone analysis, crystalluria, and APRT activity measurement-make the diagnosis easy to confirm when APRT deficiency is suspected. However, the disease can present at any age, and the variability of symptoms can present a diagnostic challenge to many physicians. The early recognition and treatment of APRT deficiency are of crucial importance for preventing irreversible loss of renal function, which still occurs in a non-negligible proportion of cases. This review summarizes the genetic and metabolic mechanisms underlying stone formation and renal disease, along with the diagnosis and management of APRT deficiency.

  6. [Selenium deficiency in pregnancy?].

    PubMed

    Lechner, W; Jenewein, I; Ritzberger, G; Sölder, E; Waitz-Penz, A; Schirmer, M; Abfalter, E

    1990-07-15

    Selenium content was investigated by atomic absorbtion spectroscopy in 32 normal pregnant women in the 38th-42, week of pregnancy. In congruence with other investigations from middle and northern Europe, selenium deficiency was stated in all of the patients.

  7. Vitamin D deficiency

    PubMed Central

    Gani, Linsey Utami; How, Choon How

    2015-01-01

    Vitamin D deficiency is common and may contribute to osteopenia, osteoporosis and falls risk in the elderly. Screening for vitamin D deficiency is important in high-risk patients, especially for patients who suffered minimal trauma fractures. Vitamin D deficiency should be treated according to the severity of the deficiency. In high-risk adults, follow-up serum 25-hydroxyvitamin D concentration should be measured 3–4 months after initiating maintenance therapy to confirm that the target level has been achieved. All patients should maintain a calcium intake of at least 1,000 mg for women aged ≤ 50 years and men ≤ 70 years, and 1,300 mg for women > 50 years and men > 70 years. PMID:26311908

  8. Children's and adults' evaluation of the certainty of deductive inferences, inductive inferences, and guesses.

    PubMed

    Pillow, Bradford H

    2002-01-01

    Two experiments investigated kindergarten through fourth-grade children's and adults' (N = 128) ability to (1) evaluate the certainty of deductive inferences, inductive inferences, and guesses; and (2) explain the origins of inferential knowledge. When judging their own cognitive state, children in first grade and older rated deductive inferences as more certain than guesses; but when judging another person's knowledge, children did not distinguish valid inferences from invalid inferences and guesses until fourth grade. By third grade, children differentiated their own deductive inferences from inductive inferences and guesses, but only adults both differentiated deductive inferences from inductive inferences and differentiated inductive inferences from guesses. Children's recognition of their own inferences may contribute to the development of knowledge about cognitive processes, scientific reasoning, and a constructivist epistemology.

  9. Vitamin B12 deficiency.

    PubMed

    Oh, Robert; Brown, David L

    2003-03-01

    Vitamin B12 (cobalamin) deficiency is a common cause of macrocytic anemia and has been implicated in a spectrum of neuropsychiatric disorders. The role of B12 deficiency in hyperhomocysteinemia and the promotion of atherosclerosis is only now being explored. Diagnosis of vitamin B12 deficiency is typically based on measurement of serum vitamin B12 levels; however, about 50 percent of patients with subclinical disease have normal B12 levels. A more sensitive method of screening for vitamin B12 deficiency is measurement of serum methylmalonic acid and homocysteine levels, which are increased early in vitamin B12 deficiency. Use of the Schilling test for detection of pernicious anemia has been supplanted for the most part by serologic testing for parietal cell and intrinsic factor antibodies. Contrary to prevailing medical practice, studies show that supplementation with oral vitamin B12 is a safe and effective treatment for the B12 deficiency state. Even when intrinsic factor is not present to aid in the absorption of vitamin B12 (pernicious anemia) or in other diseases that affect the usual absorption sites in the terminal ileum, oral therapy remains effective.

  10. [Iron deficiency and pica].

    PubMed

    Muñoz, J A; Marcos, J; Risueño, C E; de Cos, C; López, R; Capote, F J; Martín, M V; Gil, J L

    1998-02-01

    To study the relationship between pica and iron-lack anaemia in a series of iron-deficiency patients in order to establish the pathogenesis of such relationship. Four-hundred and thirty-three patients were analysed. Pica was studied by introducing certain diet queries into the clinical history. All patients received oral iron and were periodically controlled with the usual clinico-haematological procedures. Pica was present in 23 patients (5.3%). Eight nourishing (namely, coffee grains, almonds, chocolate, ice, lettuce, carrots, sunflower seeds and bread) and 2 non-nourishing (clay and paper) substances were involved. A second episode of pica appeared in 9 cases upon relapsing of iron deficiency. Both anaemia and pica were cured by etiologic and substitutive therapy in all instances. No clear correlation was found with either socio-economic status or pathogenetic causes of iron deficiency and pica, and no haematological differences were seen between patients with pica and those without this alteration. (1) The pathogenesis of pica is unclear, although it appears unrelated to the degree of iron deficiency. (2) According to the findings in this series, pica seems a consequence of iron deficiency rather than its cause. (3) Adequate therapy can cure both conditions, although pica may reappear upon relapse of iron deficiency.

  11. Evidence and Inference in Educational Assessment.

    DTIC Science & Technology

    1995-02-01

    Educational assessment concerns inference about students’ knowledge, skills, and accomplishments. Because data are never so comprehensive and...techniques can be viewed as applications of more general principles for inference in the presence of uncertainty. Issues of evidence and inference in educational assessment are discussed from this perspective. (AN)

  12. Transitive and Pseudo-Transitive Inferences

    ERIC Educational Resources Information Center

    Goodwin, Geoffrey P.; Johnson-Laird, P. N.

    2008-01-01

    Given that A is longer than B, and that B is longer than C, even 5-year-old children can infer that A is longer than C. Theories of reasoning based on formal rules of inference invoke simple axioms ("meaning postulates") to capture such transitive inferences. An alternative theory proposes instead that reasoners construct mental models of the…

  13. Iron deficiency in Europe.

    PubMed

    Hercberg, S; Preziosi, P; Galan, P

    2001-04-01

    In Europe, iron deficiency is considered to be one of the main nutritional deficiency disorders affecting large fractions of the population, particularly such physiological groups as children, menstruating women and pregnant women. Some factors such as type of contraception in women, blood donation or minor pathological blood loss (haemorrhoids, gynaecological bleeding...) considerably increase the difficulty of covering iron needs. Moreover, women, especially adolescents consuming low-energy diets, vegetarians and vegans are at high risk of iron deficiency. Although there is no evidence that an absence of iron stores has any adverse consequences, it does indicate that iron nutrition is borderline, since any further reduction in body iron is associated with a decrease in the level of functional compounds such as haemoglobin. The prevalence of iron-deficient anaemia has slightly decreased in infants and menstruating women. Some positive factors may have contributed to reducing the prevalence of iron-deficiency anaemia in some groups of population: the use of iron-fortified formulas and iron-fortified cereals; the use of oral contraceptives and increased enrichment of iron in several countries; and the use of iron supplements during pregnancy in some European countries. It is possible to prevent and control iron deficiency by counseling individuals and families about sound iron nutrition during infancy and beyond, and about iron supplementation during pregnancy, by screening persons on the basis of their risk for iron deficiency, and by treating and following up persons with presumptive iron deficiency. This may help to reduce manifestations of iron deficiency and thus improve public health. Evidence linking iron status with risk of cardiovascular disease or cancer is unconvincing and does not justify changes in food fortification or medical practice, particularly because the benefits of assuring adequate iron intake during growth and development are well established

  14. Universum Inference and Corpus Homogeneity

    NASA Astrophysics Data System (ADS)

    Vogel, Carl; Lynch, Gerard; Janssen, Jerom

    Universum Inference is re-interpreted for assessment of corpus homogeneity in computational stylometry. Recent stylometric research quantifies strength of characterization within dramatic works by assessing the homogeneity of corpora associated with dramatic personas. A methodological advance is suggested to mitigate the potential for the assessment of homogeneity to be achieved by chance. Baseline comparison analysis is constructed for contributions to debates by nonfictional participants: the corpus analyzed consists of transcripts of US Presidential and Vice-Presidential debates from the 2000 election cycle. The corpus is also analyzed in translation to Italian, Spanish and Portuguese. Adding randomized categories makes assessments of homogeneity more conservative.

  15. Inferring network structure from cascades

    NASA Astrophysics Data System (ADS)

    Ghonge, Sushrut; Vural, Dervis Can

    2017-07-01

    Many physical, biological, and social phenomena can be described by cascades taking place on a network. Often, the activity can be empirically observed, but not the underlying network of interactions. In this paper we offer three topological methods to infer the structure of any directed network given a set of cascade arrival times. Our formulas hold for a very general class of models where the activation probability of a node is a generic function of its degree and the number of its active neighbors. We report high success rates for synthetic and real networks, for several different cascade models.

  16. SICK: THE SPECTROSCOPIC INFERENCE CRANK

    SciTech Connect

    Casey, Andrew R.

    2016-03-15

    There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal

  17. Statistical inference for inverse problems

    NASA Astrophysics Data System (ADS)

    Bissantz, Nicolai; Holzmann, Hajo

    2008-06-01

    In this paper we study statistical inference for certain inverse problems. We go beyond mere estimation purposes and review and develop the construction of confidence intervals and confidence bands in some inverse problems, including deconvolution and the backward heat equation. Further, we discuss the construction of certain hypothesis tests, in particular concerning the number of local maxima of the unknown function. The methods are illustrated in a case study, where we analyze the distribution of heliocentric escape velocities of galaxies in the Centaurus galaxy cluster, and provide statistical evidence for its bimodality.

  18. sick: The Spectroscopic Inference Crank

    NASA Astrophysics Data System (ADS)

    Casey, Andrew R.

    2016-03-01

    There exists an inordinate amount of spectral data in both public and private astronomical archives that remain severely under-utilized. The lack of reliable open-source tools for analyzing large volumes of spectra contributes to this situation, which is poised to worsen as large surveys successively release orders of magnitude more spectra. In this article I introduce sick, the spectroscopic inference crank, a flexible and fast Bayesian tool for inferring astrophysical parameters from spectra. sick is agnostic to the wavelength coverage, resolving power, or general data format, allowing any user to easily construct a generative model for their data, regardless of its source. sick can be used to provide a nearest-neighbor estimate of model parameters, a numerically optimized point estimate, or full Markov Chain Monte Carlo sampling of the posterior probability distributions. This generality empowers any astronomer to capitalize on the plethora of published synthetic and observed spectra, and make precise inferences for a host of astrophysical (and nuisance) quantities. Model intensities can be reliably approximated from existing grids of synthetic or observed spectra using linear multi-dimensional interpolation, or a Cannon-based model. Additional phenomena that transform the data (e.g., redshift, rotational broadening, continuum, spectral resolution) are incorporated as free parameters and can be marginalized away. Outlier pixels (e.g., cosmic rays or poorly modeled regimes) can be treated with a Gaussian mixture model, and a noise model is included to account for systematically underestimated variance. Combining these phenomena into a scalar-justified, quantitative model permits precise inferences with credible uncertainties on noisy data. I describe the common model features, the implementation details, and the default behavior, which is balanced to be suitable for most astronomical applications. Using a forward model on low-resolution, high signal

  19. Iron deficiency anaemia.

    PubMed

    Lopez, Anthony; Cacoub, Patrice; Macdougall, Iain C; Peyrin-Biroulet, Laurent

    2016-02-27

    Anaemia affects roughly a third of the world's population; half the cases are due to iron deficiency. It is a major and global public health problem that affects maternal and child mortality, physical performance, and referral to health-care professionals. Children aged 0-5 years, women of childbearing age, and pregnant women are particularly at risk. Several chronic diseases are frequently associated with iron deficiency anaemia--notably chronic kidney disease, chronic heart failure, cancer, and inflammatory bowel disease. Measurement of serum ferritin, transferrin saturation, serum soluble transferrin receptors, and the serum soluble transferrin receptors-ferritin index are more accurate than classic red cell indices in the diagnosis of iron deficiency anaemia. In addition to the search for and treatment of the cause of iron deficiency, treatment strategies encompass prevention, including food fortification and iron supplementation. Oral iron is usually recommended as first-line therapy, but the most recent intravenous iron formulations, which have been available for nearly a decade, seem to replenish iron stores safely and effectively. Hepcidin has a key role in iron homoeostasis and could be a future diagnostic and therapeutic target. In this Seminar, we discuss the clinical presentation, epidemiology, pathophysiology, diagnosis, and acute management of iron deficiency anaemia, and outstanding research questions for treatment.

  20. Iodine deficiency in children.

    PubMed

    Pearce, Elizabeth N

    2014-01-01

    Iodine is an essential trace mineral, required for the production of thyroid hormone. Iodine deficiency may result in goiter, hypothyroidism, miscarriage, stillbirth, congenital anomalies, infant and neonatal mortality, and impaired growth. Adequate thyroid hormone is critically important for normal growth and neurodevelopment in fetal life, infancy and childhood. The population iodine status is most commonly assessed using median urinary iodine concentration values, but goiter prevalence (determined by palpation or by ultrasound), serum thyroglobulin levels, and neonatal thyroid-stimulating hormone values can also be used. Universal salt iodization programs have been the mainstay of public health efforts to eliminate iodine deficiency worldwide. However, in some regions targeted fortification of foods such as bread has been used to combat iodine deficiency. Iodine supplementation may be required in areas where dietary fortification is not feasible or where it is not sufficient for vulnerable groups such as pregnant women. Although international public health efforts over the past several decades have been highly effective, nearly one third of children worldwide remain at risk for iodine deficiency, and iodine deficiency is considered the leading preventable cause of preventable intellectual deficits.

  1. Congenital prothrombin deficiency.

    PubMed

    Lancellotti, Stefano; De Cristofaro, Raimondo

    2009-06-01

    Prothrombin deficiency is among the rarest inherited coagulation disorders, with a prevalence of approximately 1:2,000,000. Two main phenotypes can be distinguished: (1) hypoprothrombinemia (type I deficiency), characterized by concomitantly low levels of activity and antigen; and (2) dysprothrombinemia (type II deficiency), characterized by the normal or near-normal synthesis of a dysfunctional protein. In some cases, hypoprothrombinemia associated with dysprothrombinemia was also described in compound heterozygous defects. No living patient with undetectable plasma prothrombin has been reported to date. Prothrombin is encoded by a gene of approximately 21 kb located on chromosome 11 and containing 14 exons. Forty different mutations have been identified and characterized in prothrombin deficiency. Many of them surround the catalytic site, whereas another "hot spot" is localized in the recognition domain called anion binding exosite I, also called fibrinogen recognition site. Recently, mutations were identified also in the Na (+)-binding loop and in the light A-chain of thrombin. Most hypoprothrombinemia-associated mutations are missense, but there are also nonsense mutations leading to stop codons and one single nucleotide deletion. Finally, the main aspects of clinical manifestations and therapy of congenital prothrombin deficiency are presented and discussed.

  2. Biotin and biotinidase deficiency

    PubMed Central

    Zempleni, Janos; Hassan, Yousef I; Wijeratne, Subhashinee SK

    2009-01-01

    Biotin is a water-soluble vitamin that serves as an essential coenzyme for five carboxylases in mammals. Biotin-dependent carboxylases catalyze the fixation of bicarbonate in organic acids and play crucial roles in the metabolism of fatty acids, amino acids and glucose. Carboxylase activities decrease substantially in response to biotin deficiency. Biotin is also covalently attached to histones; biotinylated histones are enriched in repeat regions in the human genome and appear to play a role in transcriptional repression of genes and genome stability. Biotin deficiency may be caused by insufficient dietary uptake of biotin, drug–vitamin interactions and, perhaps, by increased biotin catabolism during pregnancy and in smokers. Biotin deficiency can also be precipitated by decreased activities of the following proteins that play critical roles in biotin homeostasis: the vitamin transporters sodium-dependent multivitamin transporter and monocarboxylate transporter 1, which mediate biotin transport in the intestine, liver and peripheral tissues, and renal reabsorption; holocarboxylase synthetase, which mediates the binding of biotin to carboxylases and histones; and biotinidase, which plays a central role in the intestinal absorption of biotin, the transport of biotin in plasma and the regulation of histone biotinylation. Symptoms of biotin deficiency include seizures, hypotonia, ataxia, dermatitis, hair loss, mental retardation, ketolactic acidosis, organic aciduria and also fetal malformations. This review focuses on the deficiencies of both biotin and biotinidase, and the medical management of such cases. PMID:19727438

  3. Biotin and biotinidase deficiency.

    PubMed

    Zempleni, Janos; Hassan, Yousef I; Wijeratne, Subhashinee Sk

    2008-11-01

    Biotin is a water-soluble vitamin that serves as an essential coenzyme for five carboxylases in mammals. Biotin-dependent carboxylases catalyze the fixation of bicarbonate in organic acids and play crucial roles in the metabolism of fatty acids, amino acids and glucose. Carboxylase activities decrease substantially in response to biotin deficiency. Biotin is also covalently attached to histones; biotinylated histones are enriched in repeat regions in the human genome and appear to play a role in transcriptional repression of genes and genome stability. Biotin deficiency may be caused by insufficient dietary uptake of biotin, drug-vitamin interactions and, perhaps, by increased biotin catabolism during pregnancy and in smokers. Biotin deficiency can also be precipitated by decreased activities of the following proteins that play critical roles in biotin homeostasis: the vitamin transporters sodium-dependent multivitamin transporter and monocarboxylate transporter 1, which mediate biotin transport in the intestine, liver and peripheral tissues, and renal reabsorption; holocarboxylase synthetase, which mediates the binding of biotin to carboxylases and histones; and biotinidase, which plays a central role in the intestinal absorption of biotin, the transport of biotin in plasma and the regulation of histone biotinylation. Symptoms of biotin deficiency include seizures, hypotonia, ataxia, dermatitis, hair loss, mental retardation, ketolactic acidosis, organic aciduria and also fetal malformations. This review focuses on the deficiencies of both biotin and biotinidase, and the medical management of such cases.

  4. A Deficiency of Credulousness.

    ERIC Educational Resources Information Center

    Brewer, Richard

    1992-01-01

    Asks the question: how does society assist citizens to stop deluding themselves with ESP, UFOs, astrology, polygraphy, water dowsing, channeling, and all manner of New Age gimcrackery? Supplies an answer: educators should emphasize instruction in probability models and scientific inference, while imparting an appropriate, scientific skepticism to…

  5. A Deficiency of Credulousness.

    ERIC Educational Resources Information Center

    Brewer, Richard

    1992-01-01

    Asks the question: how does society assist citizens to stop deluding themselves with ESP, UFOs, astrology, polygraphy, water dowsing, channeling, and all manner of New Age gimcrackery? Supplies an answer: educators should emphasize instruction in probability models and scientific inference, while imparting an appropriate, scientific skepticism to…

  6. Dopamine, Affordance and Active Inference

    PubMed Central

    Friston, Karl J.; Shiner, Tamara; FitzGerald, Thomas; Galea, Joseph M.; Adams, Rick; Brown, Harriet; Dolan, Raymond J.; Moran, Rosalyn; Stephan, Klaas Enno; Bestmann, Sven

    2012-01-01

    The role of dopamine in behaviour and decision-making is often cast in terms of reinforcement learning and optimal decision theory. Here, we present an alternative view that frames the physiology of dopamine in terms of Bayes-optimal behaviour. In this account, dopamine controls the precision or salience of (external or internal) cues that engender action. In other words, dopamine balances bottom-up sensory information and top-down prior beliefs when making hierarchical inferences (predictions) about cues that have affordance. In this paper, we focus on the consequences of changing tonic levels of dopamine firing using simulations of cued sequential movements. Crucially, the predictions driving movements are based upon a hierarchical generative model that infers the context in which movements are made. This means that we can confuse agents by changing the context (order) in which cues are presented. These simulations provide a (Bayes-optimal) model of contextual uncertainty and set switching that can be quantified in terms of behavioural and electrophysiological responses. Furthermore, one can simulate dopaminergic lesions (by changing the precision of prediction errors) to produce pathological behaviours that are reminiscent of those seen in neurological disorders such as Parkinson's disease. We use these simulations to demonstrate how a single functional role for dopamine at the synaptic level can manifest in different ways at the behavioural level. PMID:22241972

  7. Bayesian inference for radio observations

    NASA Astrophysics Data System (ADS)

    Lochner, Michelle; Natarajan, Iniyan; Zwart, Jonathan T. L.; Smirnov, Oleg; Bassett, Bruce A.; Oozeer, Nadeem; Kunz, Martin

    2015-06-01

    New telescopes like the Square Kilometre Array (SKA) will push into a new sensitivity regime and expose systematics, such as direction-dependent effects, that could previously be ignored. Current methods for handling such systematics rely on alternating best estimates of instrumental calibration and models of the underlying sky, which can lead to inadequate uncertainty estimates and biased results because any correlations between parameters are ignored. These deconvolution algorithms produce a single image that is assumed to be a true representation of the sky, when in fact it is just one realization of an infinite ensemble of images compatible with the noise in the data. In contrast, here we report a Bayesian formalism that simultaneously infers both systematics and science. Our technique, Bayesian Inference for Radio Observations (BIRO), determines all parameters directly from the raw data, bypassing image-making entirely, by sampling from the joint posterior probability distribution. This enables it to derive both correlations and accurate uncertainties, making use of the flexible software MEQTREES to model the sky and telescope simultaneously. We demonstrate BIRO with two simulated sets of Westerbork Synthesis Radio Telescope data sets. In the first, we perform joint estimates of 103 scientific (flux densities of sources) and instrumental (pointing errors, beamwidth and noise) parameters. In the second example, we perform source separation with BIRO. Using the Bayesian evidence, we can accurately select between a single point source, two point sources and an extended Gaussian source, allowing for `super-resolution' on scales much smaller than the synthesized beam.

  8. Quantum Inference on Bayesian Networks

    NASA Astrophysics Data System (ADS)

    Yoder, Theodore; Low, Guang Hao; Chuang, Isaac

    2014-03-01

    Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.

  9. Bayesian inference for OPC modeling

    NASA Astrophysics Data System (ADS)

    Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.

    2016-03-01

    The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.

  10. Symbolic inference of xenobiotic metabolism.

    PubMed

    McShan, D C; Updadhayaya, M; Shah, I

    2004-01-01

    We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds.

  11. SYMBOLIC INFERENCE OF XENOBIOTIC METABOLISM

    PubMed Central

    MCSHAN, D.C.; UPDADHAYAYA, M.; SHAH, I.

    2009-01-01

    We present a new symbolic computational approach to elucidate the biochemical networks of living systems de novo and we apply it to an important biomedical problem: xenobiotic metabolism. A crucial issue in analyzing and modeling a living organism is understanding its biochemical network beyond what is already known. Our objective is to use the available metabolic information in a representational framework that enables the inference of novel biochemical knowledge and whose results can be validated experimentally. We describe a symbolic computational approach consisting of two parts. First, biotransformation rules are inferred from the molecular graphs of compounds in enzyme-catalyzed reactions. Second, these rules are recursively applied to different compounds to generate novel metabolic networks, containing new biotransformations and new metabolites. Using data for 456 generic reactions and 825 generic compounds from KEGG we were able to extract 110 biotransformation rules, which generalize a subset of known biocatalytic functions. We tested our approach by applying these rules to ethanol, a common substance of abuse and to furfuryl alcohol, a xenobiotic organic solvent, which is absent in metabolic databases. In both cases our predictions on the fate of ethanol and furfuryl alcohol are consistent with the literature on the metabolism of these compounds. PMID:14992532

  12. [Vitamin deficiencies and hypervitaminosis].

    PubMed

    Mino, M

    1999-10-01

    There have recently been very few deficiencies with respect to fat soluble and water soluble vitamins in Japan All-trans-retinoic acid as induction or maintenance treatment improves disease free and overall survival against acute promyelocytic leukemia. In the isolated vitamin E deficiencies gene mutation has been cleared for alpha-tocopherol transferprotein. Recently, a relation of nutritional vitamin K intake and senile osteoporosis in women was epidemiologically demonstrated on a prospective study. Thiamin was yet noticed as development of deficiency in alcoholism, while the importance of supplemental folic acid during pregnancy has become especially clear in light of studies showing that folic acid supplements reduce the risk of neural tube defects in the fetus. With respect to hypervitaminosis, the Council for Responsible Nutrition (CRN), USA, has established safe intakes by identifying the NOAEL (No Observed Adverse Effect Level) and LOAEL (Lowest Observed Adverse Effect Level). Summaries of NOAEL and LOAEL for individual vitamins were shown.

  13. Antepartum ornithine transcarbamylase deficiency.

    PubMed

    Nakajima, Hitoshi; Sasaki, Yosuke; Maeda, Tadashi; Takeda, Masako; Hara, Noriko; Nakanishi, Kazushige; Urita, Yoshihisa; Hattori, Risa; Miura, Ken; Taniguchi, Tomoko

    2014-01-01

    Ornithine transcarbamylase deficiency (OTCD) is the most common type urea cycle enzyme deficiencies. This syndrome results from a deficiency of the mitochondrial enzyme ornithine transcarbamylase, which catalyzes the conversion of ornithine and carbamoyl phosphate to citrullin. Our case was a 28-year-old female diagnosed with OTCD following neurocognitive deficit during her first pregnancy. Although hyperammonemia was suspected as the cause of the patient's mental changes, there was no evidence of chronic liver disease. Plasma amino acid and urine organic acid analysis revealed OTCD. After combined modality treatment with arginine, sodium benzoate and hemodialysis, the patient's plasma ammonia level stabilized and her mental status returned to normal. At last she recovered without any damage left.

  14. Thiamine Deficiency and Delirium

    PubMed Central

    Ali, Shahid; Freeman, C.; Barker, Narviar C.; Jabeen, Shagufta; Maitra, Sarbani; Olagbemiro, Yetunde; Richie, William; Bailey, Rahn K.

    2013-01-01

    Thiamine is an essential vitamin that plays an important role in cellular production of energy from ingested food and enhances normal neuronal actives. Deficiency of this vitamin leads to a very serious clinical condition known as delirium. Studies performed in the United States and other parts of the world have established the link between thiamine deficiency and delirium. This literature review examines the physiology, pathophysiology, predisposing factors, clinical manifestations (e.g., Wernicke’s encephalopathy, Wernicke-Korsakoff syndrome, structural and functional brain injuries) and diagnosis of thiamine deficiency and delirium. Current treatment practices are also discussed that may improve patient outcome, which ultimately may result in a reduction in healthcare costs. PMID:23696956

  15. [Prevalence of iron deficiency].

    PubMed

    Dupont, C

    2017-05-01

    Studies of prévalence in iron deficiency separate iron depletion (defined as decreased blood ferritin) and iron deficiency anemia (defined as blood decrease in both ferritin and hemoglobin). In Europe, most studies are outdated. Prevalence of iron depletion varies from 7 to 18 % and 24 to 36% in toddlers and adolescents, respectively. Prevalence of iron deficiency anemia varies from 2 to 8.5% and 7 to 10% in toddlers and adolescents. In French speaking African countries, Demography Health Surveys show that 80% of children aged 0 to 2 years are anemic, severely for 5 to 9% of them. © 2017 Elsevier Masson SAS. Tous droits réservés.

  16. Natural killer cell deficiency.

    PubMed

    Orange, Jordan S

    2013-09-01

    Natural killer (NK) cells are part of the innate immune defense against infection and cancer and are especially useful in combating certain viral pathogens. The utility of NK cells in human health has been underscored by a growing number of persons who are deficient in NK cells and/or their functions. This can be in the context of a broader genetically defined congenital immunodeficiency, of which there are more than 40 presently known to impair NK cells. However, the abnormality of NK cells in certain cases represents the majority immunologic defect. In aggregate, these conditions are termed NK cell deficiency. Recent advances have added clarity to this diagnosis and identified defects in 3 genes that can cause NK cell deficiency, as well as some of the underlying biology. Appropriate consideration of these diagnoses and patients raises the potential for rational therapeutic options and further innovation.

  17. Multiple sulfatase deficiency.

    PubMed

    Soong, B W; Casamassima, A C; Fink, J K; Constantopoulos, G; Horwitz, A L

    1988-08-01

    Multiple sulfatase deficiency is an inherited disorder characterized by a deficiency of several sulfatases and the accumulation of sulfatides, glycosaminoglycans, sphingolipids, and steroid sulfates in tissues and body fluids. The clinical manifestations represent the summation of two diseases: late infantile metachromatic leukodystrophy and mucopolysaccharidosis. We present a 9-year-old girl with a phenotype similar to a mucopolysaccharidosis: short stature, microcephaly, and mild facial dysmorphism, along with dysphagia, retinal degeneration, developmental arrest, and ataxia. We discuss the importance of measuring the sulfatase activities in the leukocytes, and the instability of sulfatases in the cultured skin fibroblasts.

  18. Detection of implausible phylogenetic inferences using posterior predictive assessment of model fit.

    PubMed

    Brown, Jeremy M

    2014-05-01

    Systematic phylogenetic error caused by the simplifying assumptions made in models of molecular evolution may be impossible to avoid entirely when attempting to model evolution across massive, diverse data sets. However, not all deficiencies of inference models result in unreliable phylogenetic estimates. The field of phylogenetics lacks a direct method to identify cases where model specification adversely affects inferences. Posterior predictive simulation is a flexible and intuitive approach for assessing goodness-of-fit of the assumed model and priors in a Bayesian phylogenetic analysis. Here, I propose new test statistics for use in posterior predictive assessment of model fit. These test statistics compare phylogenetic inferences from posterior predictive data sets to inferences from the original data. A simulation study demonstrates the utility of these new statistics. The new tests reject the plausibility of inferred tree lengths or topologies more often when data/model combinations produce biased inferences. I also apply this approach to exemplar empirical data sets, highlighting the value of the novel assessments.

  19. Bayesian Inference of Tumor Hypoxia

    NASA Astrophysics Data System (ADS)

    Gunawan, R.; Tenti, G.; Sivaloganathan, S.

    2009-12-01

    Tumor hypoxia is a state of oxygen deprivation in tumors. It has been associated with aggressive tumor phenotypes and with increased resistance to conventional cancer therapies. In this study, we report on the application of Bayesian sequential analysis in estimating the most probable value of tumor hypoxia quantification based on immunohistochemical assays of a biomarker. The `gold standard' of tumor hypoxia assessment is a direct measurement of pO2 in vivo by the Eppendorf polarographic electrode, which is an invasive technique restricted to accessible sites and living tissues. An attractive alternative is immunohistochemical staining to detect proteins expressed by cells during hypoxia. Carbonic anhydrase IX (CAIX) is an enzyme expressed on the cell membrane during hypoxia to balance the immediate extracellular microenvironment. CAIX is widely regarded as a surrogate marker of chronic hypoxia in various cancers. The study was conducted with two different experimental procedures. The first data set was a group of three patients with invasive cervical carcinomas, from which five biopsies were obtained. Each of the biopsies was fully sectioned and from each section, the proportion of CAIX-positive cells was estimated. Measurements were made by image analysis of multiple deep sections cut through these biopsies, labeled for CAIX using both immunofluorescence and immunohistochemical techniques [1]. The second data set was a group of 24 patients, also with invasive cervical carcinomas, from which two biopsies were obtained. Bayesian parameter estimation was applied to obtain a reliable inference about the proportion of CAIX-positive cells within the carcinomas, based on the available biopsies. From the first data set, two to three biopsies were found to be sufficient to infer the overall CAIX percentage in the simple form: best estimate±uncertainty. The second data-set led to a similar result in 70% of the cases. In the remaining cases Bayes' theorem warned us

  20. Color vision deficiencies

    NASA Astrophysics Data System (ADS)

    Vannorren, D.

    1982-04-01

    Congenital and acquired color vision defects are described in the context of physiological data. Light sources, photometry, color systems and test methods are described. A list of medicines is also presented. The practical social consequences of color vision deficiencies are discussed.

  1. Diagnosing oceanic nutrient deficiency

    NASA Astrophysics Data System (ADS)

    Moore, C. Mark

    2016-11-01

    The supply of a range of nutrient elements to surface waters is an important driver of oceanic production and the subsequent linked cycling of the nutrients and carbon. Relative deficiencies of different nutrients with respect to biological requirements, within both surface and internal water masses, can be both a key indicator and driver of the potential for these nutrients to become limiting for the production of new organic material in the upper ocean. The availability of high-quality, full-depth and global-scale datasets on the concentrations of a wide range of both macro- and micro-nutrients produced through the international GEOTRACES programme provides the potential for estimation of multi-element deficiencies at unprecedented scales. Resultant coherent large-scale patterns in diagnosed deficiency can be linked to the interacting physical-chemical-biological processes which drive upper ocean nutrient biogeochemistry. Calculations of ranked deficiencies across multiple elements further highlight important remaining uncertainties in the stoichiometric plasticity of nutrient ratios within oceanic microbial systems and caveats with regards to linkages to upper ocean nutrient limitation. This article is part of the themed issue 'Biological and climatic impacts of ocean trace element chemistry'.

  2. Vitamin B12 deficiency

    USDA-ARS?s Scientific Manuscript database

    Vitamin B12 (B12; also known as cobalamin) is a B vitamin that has an important role in cellular metabolism, especially in DNA synthesis, methylation and mitochondrial metabolism. Clinical B12 deficiency with classic haematological and neurological manifestations is relatively uncommon. However, sub...

  3. Isolated sulfite oxidase deficiency.

    PubMed

    Rupar, C A; Gillett, J; Gordon, B A; Ramsay, D A; Johnson, J L; Garrett, R M; Rajagopalan, K V; Jung, J H; Bacheyie, G S; Sellers, A R

    1996-12-01

    Isolated sulfite oxidase (SO) deficiency is an autosomal recessively inherited inborn error of sulfur metabolism. In this report of a ninth patient the clinical history, laboratory results, neuropathological findings and a mutation in the sulfite oxidase gene are described. The data from this patient and previously published patients with isolated sulfite oxidase deficiency and molybdenum cofactor deficiency are summarized to characterize this rare disorder. The patient presented neonatally with intractable seizures and did not progress developmentally beyond the neonatal stage. Dislocated lenses were apparent at 2 months. There was increased urine excretion of sulfite and S-sulfocysteine and a decreased concentration of plasma cystine. A lactic acidemia was present for 6 months. Liver sulfite oxidase activity was not detectable but xanthine dehydrogenase activity was normal. The boy died of respiratory failure at 32 months. Neuropathological findings of cortical necrosis and extensive cavitating leukoencephalopathy were reminiscent of those seen in severe perinatal asphyxia suggesting an etiology of energy deficiency. A point mutation that resulted in a truncated protein missing the molybdenum-binding site has been identified.

  4. Spontaneous Trait Inferences on Social Media

    PubMed Central

    Utz, Sonja

    2016-01-01

    The present research investigates whether spontaneous trait inferences occur under conditions characteristic of social media and networking sites: nonextreme, ostensibly self-generated content, simultaneous presentation of multiple cues, and self-paced browsing. We used an established measure of trait inferences (false recognition paradigm) and a direct assessment of impressions. Without being asked to do so, participants spontaneously formed impressions of people whose status updates they saw. Our results suggest that trait inferences occurred from nonextreme self-generated content, which is commonly found in social media updates (Experiment 1) and when nine status updates from different people were presented in parallel (Experiment 2). Although inferences did occur during free browsing, the results suggest that participants did not necessarily associate the traits with the corresponding status update authors (Experiment 3). Overall, the findings suggest that spontaneous trait inferences occur on social media. We discuss implications for online communication and research on spontaneous trait inferences. PMID:28123646

  5. Synaptic Computation Underlying Probabilistic Inference

    PubMed Central

    Soltani, Alireza; Wang, Xiao-Jing

    2010-01-01

    In this paper we propose that synapses may be the workhorse of neuronal computations that underlie probabilistic reasoning. We built a neural circuit model for probabilistic inference when information provided by different sensory cues needs to be integrated, and the predictive powers of individual cues about an outcome are deduced through experience. We found that bounded synapses naturally compute, through reward-dependent plasticity, the posterior probability that a choice alternative is correct given that a cue is presented. Furthermore, a decision circuit endowed with such synapses makes choices based on the summated log posterior odds and performs near-optimal cue combination. The model is validated by reproducing salient observations of, and provide insights into, a monkey experiment using a categorization task. Our model thus suggests a biophysical instantiation of the Bayesian decision rule, while predicting important deviations from it similar to ‘base-rate neglect’ observed in human studies when alternatives have unequal priors. PMID:20010823

  6. Motion Inference During +Gz Acceleration

    DTIC Science & Technology

    2006-09-01

    AFRL-HW-WP-TP-2006-0091 Motion Inference During +Gz Acceleration Lloyd D . Tripp Jr. Richard A. McKinley Robert L. Esken Air Force Research Laboratory...5c. PROGRAM ELEMENT NUMBER 62202F 6. AUTHOR(S) 5d. PROJECT NUMBER Lloyd D . Tripp Jr 7184 Richard A. McKinley 5e. TASK NUMBER Robert L. Esken 03 5f...CD A Cj CL.C2 C 0~ 0. D 0 0~G)C00.E)’ca)4-100 ( 0 Eo12 E a 0 0L0mm 0a0 " C0 U) U) LUr o CLI.,a @ .- . : ) 0 " 0 C CL.. 70 E- 0 M 0.0 toE-C .- 0)c .2 0UL

  7. Word learning as Bayesian inference.

    PubMed

    Xu, Fei; Tenenbaum, Joshua B

    2007-04-01

    The authors present a Bayesian framework for understanding how adults and children learn the meanings of words. The theory explains how learners can generalize meaningfully from just one or a few positive examples of a novel word's referents, by making rational inductive inferences that integrate prior knowledge about plausible word meanings with the statistical structure of the observed examples. The theory addresses shortcomings of the two best known approaches to modeling word learning, based on deductive hypothesis elimination and associative learning. Three experiments with adults and children test the Bayesian account's predictions in the context of learning words for object categories at multiple levels of a taxonomic hierarchy. Results provide strong support for the Bayesian account over competing accounts, in terms of both quantitative model fits and the ability to explain important qualitative phenomena. Several extensions of the basic theory are discussed, illustrating the broader potential for Bayesian models of word learning. (c) 2007 APA, all rights reserved.

  8. Population heterogeneity and causal inference.

    PubMed

    Xie, Yu

    2013-04-16

    Population heterogeneity is ubiquitous in social science. The very objective of social science research is not to discover abstract and universal laws but to understand population heterogeneity. Due to population heterogeneity, causal inference with observational data in social science is impossible without strong assumptions. Researchers have long been concerned with two potential sources of bias. The first is bias in unobserved pretreatment factors affecting the outcome even in the absence of treatment. The second is bias due to heterogeneity in treatment effects. In this article, I show how "composition bias" due to population heterogeneity evolves over time when treatment propensity is systematically associated with heterogeneous treatment effects. A form of selection bias, composition bias, arises dynamically at the aggregate level even when the classic assumption of ignorability holds true at the microlevel.

  9. Population heterogeneity and causal inference

    PubMed Central

    Xie, Yu

    2013-01-01

    Population heterogeneity is ubiquitous in social science. The very objective of social science research is not to discover abstract and universal laws but to understand population heterogeneity. Due to population heterogeneity, causal inference with observational data in social science is impossible without strong assumptions. Researchers have long been concerned with two potential sources of bias. The first is bias in unobserved pretreatment factors affecting the outcome even in the absence of treatment. The second is bias due to heterogeneity in treatment effects. In this article, I show how “composition bias” due to population heterogeneity evolves over time when treatment propensity is systematically associated with heterogeneous treatment effects. A form of selection bias, composition bias, arises dynamically at the aggregate level even when the classic assumption of ignorability holds true at the microlevel. PMID:23530202

  10. Inferred properties of stellar granulation

    SciTech Connect

    Gray, D.F.; Toner, C.G.

    1985-06-01

    Apparent characteristics of stellar granulation in F and G main-sequence stars are inferred directly from observed spectral-line asymmetries and from comparisons of numerical simulations with the observations: (1) the apparent granulation velocity increases with effective temperature, (2) the dispersion of granule velocities about their mean velocity of rise increases with the apparent granulation velocity, (3) the mean velocity of rise of granules must be less than the total line broadening, (4) the apparent velocity difference between granules and dark lanes corresponds to the granulation velocity deduced from stellar line bisectors, (5) the dark lanes show velocities of fall approximately twice as large as the granule rise velocities, (6) the light contributed to the stellar flux by the granules is four to ten times more than the light from the dark lanes. Stellar rotation is predicted to produce distortions in the line bisectors which may give information on the absolute velocity displacements of the line bisectors. 37 references.

  11. Causal inference in public health.

    PubMed

    Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M

    2013-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.

  12. Generic Comparison of Protein Inference Engines*

    PubMed Central

    Claassen, Manfred; Reiter, Lukas; Hengartner, Michael O.; Buhmann, Joachim M.; Aebersold, Ruedi

    2012-01-01

    Protein identifications, instead of peptide-spectrum matches, constitute the biologically relevant result of shotgun proteomics studies. How to appropriately infer and report protein identifications has triggered a still ongoing debate. This debate has so far suffered from the lack of appropriate performance measures that allow us to objectively assess protein inference approaches. This study describes an intuitive, generic and yet formal performance measure and demonstrates how it enables experimentalists to select an optimal protein inference strategy for a given collection of fragment ion spectra. We applied the performance measure to systematically explore the benefit of excluding possibly unreliable protein identifications, such as single-hit wonders. Therefore, we defined a family of protein inference engines by extending a simple inference engine by thousands of pruning variants, each excluding a different specified set of possibly unreliable identifications. We benchmarked these protein inference engines on several data sets representing different proteomes and mass spectrometry platforms. Optimally performing inference engines retained all high confidence spectral evidence, without posterior exclusion of any type of protein identifications. Despite the diversity of studied data sets consistently supporting this rule, other data sets might behave differently. In order to ensure maximal reliable proteome coverage for data sets arising in other studies we advocate abstaining from rigid protein inference rules, such as exclusion of single-hit wonders, and instead consider several protein inference approaches and assess these with respect to the presented performance measure in the specific application context. PMID:22057310

  13. Bayesian Nonparametric Inference – Why and How

    PubMed Central

    Müller, Peter; Mitra, Riten

    2013-01-01

    We review inference under models with nonparametric Bayesian (BNP) priors. The discussion follows a set of examples for some common inference problems. The examples are chosen to highlight problems that are challenging for standard parametric inference. We discuss inference for density estimation, clustering, regression and for mixed effects models with random effects distributions. While we focus on arguing for the need for the flexibility of BNP models, we also review some of the more commonly used BNP models, thus hopefully answering a bit of both questions, why and how to use BNP. PMID:24368932

  14. Generic comparison of protein inference engines.

    PubMed

    Claassen, Manfred; Reiter, Lukas; Hengartner, Michael O; Buhmann, Joachim M; Aebersold, Ruedi

    2012-04-01

    Protein identifications, instead of peptide-spectrum matches, constitute the biologically relevant result of shotgun proteomics studies. How to appropriately infer and report protein identifications has triggered a still ongoing debate. This debate has so far suffered from the lack of appropriate performance measures that allow us to objectively assess protein inference approaches. This study describes an intuitive, generic and yet formal performance measure and demonstrates how it enables experimentalists to select an optimal protein inference strategy for a given collection of fragment ion spectra. We applied the performance measure to systematically explore the benefit of excluding possibly unreliable protein identifications, such as single-hit wonders. Therefore, we defined a family of protein inference engines by extending a simple inference engine by thousands of pruning variants, each excluding a different specified set of possibly unreliable identifications. We benchmarked these protein inference engines on several data sets representing different proteomes and mass spectrometry platforms. Optimally performing inference engines retained all high confidence spectral evidence, without posterior exclusion of any type of protein identifications. Despite the diversity of studied data sets consistently supporting this rule, other data sets might behave differently. In order to ensure maximal reliable proteome coverage for data sets arising in other studies we advocate abstaining from rigid protein inference rules, such as exclusion of single-hit wonders, and instead consider several protein inference approaches and assess these with respect to the presented performance measure in the specific application context.

  15. Online Updating of Statistical Inference in the Big Data Setting.

    PubMed

    Schifano, Elizabeth D; Wu, Jing; Wang, Chun; Yan, Jun; Chen, Ming-Hui

    2016-01-01

    We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models and estimating equations that update as new data arrive. These algorithms are computationally efficient, minimally storage-intensive, and allow for possible rank deficiencies in the subset design matrices due to rare-event covariates. Within the linear model setting, the proposed online-updating framework leads to predictive residual tests that can be used to assess the goodness-of-fit of the hypothesized model. We also propose a new online-updating estimator under the estimating equation setting. Theoretical properties of the goodness-of-fit tests and proposed estimators are examined in detail. In simulation studies and real data applications, our estimator compares favorably with competing approaches under the estimating equation setting.

  16. Sanitary Surveys & Significant Deficiencies Presentation

    EPA Pesticide Factsheets

    The Sanitary Surveys & Significant Deficiencies Presentation highlights some of the things EPA looks for during drinking water system site visits, how to avoid significant deficiencies and what to do if you receive one.

  17. Genetics Home Reference: prothrombin deficiency

    MedlinePlus

    ... II deficiency University of Iowa Health Care: Prothrombin Gene Mutation (PDF) Patient Support and Advocacy Resources (2 links) Canadian Hemophilia Society National Hemophilia Foundation: Factor II Deficiency ClinicalTrials. ...

  18. Genetics Home Reference: biotinidase deficiency

    MedlinePlus

    ... links) Children Living With Inherited Metabolic Diseases (CLIMB) (UK): Biotinidase Deficiency (PDF) Disease InfoSearch: Biotinidase Deficiency Illinois ... Group Children Living with Inherited Metabolic Diseases (CLIMB) (UK) National Organization for Rare Disorders (NORD) GeneReviews (1 ...

  19. Biotinidase deficiency: an atypical presentation.

    PubMed

    Jagadeesh, Sujatha; Suresh, Beena; Seshadri, Suresh; Suzuki, Yoichi

    2013-01-01

    Biotinidase deficiency is a rare metabolic disorder which can cause dermatological manifestations and lead to severe neurological sequelae if untreated. Holocarboxylase synthetase deficiency also has similar manifestations and needs to be differentiated. We present a neonate who had atypical early onset symptoms and was diagnosed to have biotinidase deficiency. Copyright 2012, NMJI.

  20. Isolated sulfite oxidase deficiency.

    PubMed

    Relinque, B; Bardallo, L; Granero, M; Jiménez, P J; Luna, S

    2015-03-10

    Sulfite oxidase deficiency is an uncommon metabolic disease. Only few cases of its isolated form have been reported in the literature. We report a case of severe neonatal onset. A newborn baby of 41 weeks gestational age, weighted at birth of 3240 grams and had an Apgar score of 6-10-10. Fifty-three hours after being born, the baby started with seizures that were refractory to antiepileptic treatment. Brain function was monitored using a-EEG. Laboratory and imaging tests were performed. All of them were consistent with sulfite oxidase deficiency. The diagnosis was confirmed by genetic testing. We highlight the importance of this disease as part of the differential diagnosis of seizures during the neonatal period, as well as the importance of the therapeutic support based on dietary restrictions. It's also remarkable the possibility of prenatal diagnosis by quantifying enzyme activity and it's also possible carrying out DNA mutational analysis.

  1. Biotinidase deficiency in childhood.

    PubMed

    Venkataraman, Viswanathan; Balaji, Padma; Panigrahi, Debasis; Jamal, Rafat

    2013-01-01

    This study reports the clinical, laboratory profile and outcome in seven patients with biotinidase deficiency. The serum biotinidase activity was assayed using spectrophotometric analysis. The age at presentation varied from day 1 of life to the 5 th month. Seizures were the presenting complaint in six patients and clonic seizures were the predominant seizure type. Sparse hair was seen in four patients, while three did not have any cutaneous manifestation. None of the patients had acidosis or hyperammonemia. The clinical response to biotin was dramatic with seizure control in all patients. One patient had neurological deficit at follow-up, while none had optic atrophy or sensorineural hearing loss. Biotinidase deficiency, a potentially treatable condition, should be thought of in any child presenting with neurological symptoms, especially seizures, even in the absence of cutaneous or laboratory manifestations.

  2. [Selective immunoglobulin A deficiency].

    PubMed

    Binek, Alicja; Jarosz-Chobot, Przemysława

    2012-01-01

    Immunoglobulin class A is the main protein of the mucosal immune system. Selective immunoglobulin A deficiency (sIgAD) is the most common primary immunodeficiency in Caucasians. sIGAD is strongly associated with the certain major histocompatibility complex region. Most individuals with sIgAD are asymptomatic and identified coincidentally. However, some patients may present with recurrent infections, allergic disorders and autoimmune manifestations. Several autoimmune diseases, such as systemic lupus erythematosus, diabetes mellitus type 1, Graves disease and celiac disease, are associated with an increased prevalence of sIgAD. Screening for sIgAD in coeliac disease is essential. Patients need treatment of associated diseases. It is also known that IgA deficiency may progress into a common variable immunodeficiency (CVID). Pathogenesis and molecular mechanism involved in sIgAD should be elucidated in the future.

  3. Language deficiency in children.

    PubMed

    Morehead, D M; Morehead, K E; Morehead, W A

    1980-01-01

    Research in cognition and language has provided useful constructs which suggests that specific deficits underlie language deficiencies in children. In addition, this research has provided procedures that the determine what a child knows about language at a particular level of development and has established a sequence of linguistic development that maps the specific content and structure of training programs. Two new areas of research offer additional approaches to assessment and remediation. One approach focuses on the actual principles and strategies that normal children use to learn language, making it possible to determine which methods are most efficient. The second research approach looks at the contextual conditions adults and children provide the first language learner. Preliminary work suggests that the natural conditions found universally in first language learning may be the best indicators of how to proceed with language-deficient children.

  4. Inferring episodic atmospheric iron fluxes in the Western South Atlantic

    NASA Astrophysics Data System (ADS)

    Evangelista, Heitor; Maldonado, Juan; dos Santos, Elaine A.; Godoi, Ricardo H. M.; Garcia, Carlos A. E.; Garcia, Virginia M. T.; Jonhson, Erling; Dias da Cunha, Kenya; Leite, Carlos Barros; Van Grieken, René; Van Meel, Katleen; Makarovska, Yaroslava; Gaiero, Diego M.

    2010-02-01

    Iron (Fe) and other trace elements such as Zn, Mn, Ni and Cu are known as key-factors in marine biogeochemical cycles. It is believed that ocean primary productivity blooms in iron deficient regions can be triggered by iron in aeolian dust. Up to now, scarce aerosol elemental composition, based on measurements over sea at the Western South Atlantic (WSA), exist. An association between the Patagonian semi-desert dust/Fe and chlorophyll-a variability at the Argentinean continental shelf is essentially inferred from models. We present here experimental data of Fe enriched aerosols over the WSA between latitudes 22°S-62°S, during 4 oceanographic campaigns between 2002 and 2005. These data allowed inferring the atmospheric Fe flux onto different latitudinal bands which varied from 30.4 to 1688 nmolFe m -2 day -1 (October 29th-November 15th, 2003); 5.83-1586 nmolFe m -2 day -1 (February 15th-March 6th, 2004) and 4.73-586 nmolFe m -2 day -1(October 21st-November 5th, 2005).

  5. A Comparison of Two Student Instructional Rating Forms Utilizing High-Inference Versus Moderate Inference Items.

    ERIC Educational Resources Information Center

    Wilson, Pamela W.

    Two types of items used in student evaluations of college teaching were compared: high-inference items, which require considerable inferring from what is seen or heard in the classroom to labelling of teacher behavior; and moderate-inference items, such as "teacher listens carefully." Two instruments were administered to random halves of…

  6. Relationship of High-Inference and Low-Inference Observation Measures.

    ERIC Educational Resources Information Center

    Limbacher, Philip C.; Rosenshine, Barak

    The correlation between high-inference measures and low-inference observation measures was studied using two groups of social studies student teachers (25 students per group). The high-inference measure for two video-taped lessons was obtained with the 10-item Teacher Performance Appraisal Scale (TPAS), on which pupils rated the lesson on a scale…

  7. Micronutrient deficiency in children.

    PubMed

    Bhan, M K; Sommerfelt, H; Strand, T

    2001-05-01

    Malnutrition increases morbidity and mortality and affects physical growth and development, some of these effects resulting from specific micronutrient deficiencies. While public health efforts must be targeted to improve dietary intakes in children through breast feeding and appropriate complementary feeding, there is a need for additional measures to increase the intake of certain micronutrients. Food-based approaches are regarded as the long-term strategy for improving nutrition, but for certain micronutrients, supplementation, be it to the general population or to high risk groups or as an adjunct to treatment must also be considered. Our understanding of the prevalence and consequences of iron, vitamin A and iodine deficiency in children and pregnant women has advanced considerably while there is still a need to generate more knowledge pertaining to many other micronutrients, including zinc, selenium and many of the B-vitamins. For iron and vitamin A, the challenge is to improve the delivery to target populations. For disease prevention and growth promotion, the need to deliver safe but effective amounts of micronutrients such as zinc to children and women of fertile age can be determined only after data on deficiency prevalence becomes available and the studies on mortality reduction following supplementation are completed. Individual or multiple micronutrients must be used as an adjunct to treatment of common infectious diseases and malnutrition only if the gains are substantial and the safety window sufficiently wide. The available data for zinc are promising with regard to the prevention of diarrhea and pneumonia. It should be emphasized that there must be no displacement of important treatment such as ORS in acute diarrhea by adjunct therapy such as zinc. Credible policy making requires description of not only the clinical effects but also the underlying biological mechanisms. As findings of experimental studies are not always feasible to extrapolate to

  8. Local and Global Thinking in Statistical Inference

    ERIC Educational Resources Information Center

    Pratt, Dave; Johnston-Wilder, Peter; Ainley, Janet; Mason, John

    2008-01-01

    In this reflective paper, we explore students' local and global thinking about informal statistical inference through our observations of 10- to 11-year-olds, challenged to infer the unknown configuration of a virtual die, but able to use the die to generate as much data as they felt necessary. We report how they tended to focus on local changes…

  9. Symbolic transfer entropy: inferring directionality in biosignals.

    PubMed

    Staniek, Matthäus; Lehnertz, Klaus

    2009-12-01

    Inferring directional interactions from biosignals is of crucial importance to improve understanding of dynamical interdependences underlying various physiological and pathophysiological conditions. We here present symbolic transfer entropy as a robust measure to infer the direction of interactions between multidimensional dynamical systems. We demonstrate its performance in quantifying driver-responder relationships in a network of coupled nonlinear oscillators and in the human epileptic brain.

  10. Inferring extinction from a sighting record.

    PubMed

    Solow, Andrew R

    2005-05-01

    The extinctions of plant and animal species are almost never observed directly, but must be inferred from sighting records. This paper reviews some methods for statistical inference about the extinction of a single species based on a record of its sightings.

  11. Evidence and Inference in Educational Assessment.

    ERIC Educational Resources Information Center

    Mislevy, Robert J.

    1994-01-01

    Educational assessment concerns inference about student knowledge, skills, and accomplishments. Test theory has evolved in part to address questions of weight, coverage, and import of data. Resulting concepts and techniques can be viewed as applications of more general principles for inference in the presence of uncertainty. (SLD)

  12. Forward and backward inference in spatial cognition.

    PubMed

    Penny, Will D; Zeidman, Peter; Burgess, Neil

    2013-01-01

    This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of 'lower-level' computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus.

  13. Scalar Inferences in Autism Spectrum Disorders

    ERIC Educational Resources Information Center

    Chevallier, Coralie; Wilson, Deirdre; Happe, Francesca; Noveck, Ira

    2010-01-01

    On being told "John or Mary will come", one might infer that "not both" of them will come. Yet the semantics of "or" is compatible with a situation where both John and Mary come. Inferences of this type, which enrich the semantics of "or" from an "inclusive" to an "exclusive" interpretation, have been extensively studied in linguistic pragmatics.…

  14. Inferring Learners' Knowledge from Their Actions

    ERIC Educational Resources Information Center

    Rafferty, Anna N.; LaMar, Michelle M.; Griffiths, Thomas L.

    2015-01-01

    Watching another person take actions to complete a goal and making inferences about that person's knowledge is a relatively natural task for people. This ability can be especially important in educational settings, where the inferences can be used for assessment, diagnosing misconceptions, and providing informative feedback. In this paper, we…

  15. Forward and Backward Inference in Spatial Cognition

    PubMed Central

    Penny, Will D.; Zeidman, Peter; Burgess, Neil

    2013-01-01

    This paper shows that the various computations underlying spatial cognition can be implemented using statistical inference in a single probabilistic model. Inference is implemented using a common set of ‘lower-level’ computations involving forward and backward inference over time. For example, to estimate where you are in a known environment, forward inference is used to optimally combine location estimates from path integration with those from sensory input. To decide which way to turn to reach a goal, forward inference is used to compute the likelihood of reaching that goal under each option. To work out which environment you are in, forward inference is used to compute the likelihood of sensory observations under the different hypotheses. For reaching sensory goals that require a chaining together of decisions, forward inference can be used to compute a state trajectory that will lead to that goal, and backward inference to refine the route and estimate control signals that produce the required trajectory. We propose that these computations are reflected in recent findings of pattern replay in the mammalian brain. Specifically, that theta sequences reflect decision making, theta flickering reflects model selection, and remote replay reflects route and motor planning. We also propose a mapping of the above computational processes onto lateral and medial entorhinal cortex and hippocampus. PMID:24348230

  16. Application of Transformations in Parametric Inference

    ERIC Educational Resources Information Center

    Brownstein, Naomi; Pensky, Marianna

    2008-01-01

    The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

  17. The Reasoning behind Informal Statistical Inference

    ERIC Educational Resources Information Center

    Makar, Katie; Bakker, Arthur; Ben-Zvi, Dani

    2011-01-01

    Informal statistical inference (ISI) has been a frequent focus of recent research in statistics education. Considering the role that context plays in developing ISI calls into question the need to be more explicit about the reasoning that underpins ISI. This paper uses educational literature on informal statistical inference and philosophical…

  18. Local and Global Thinking in Statistical Inference

    ERIC Educational Resources Information Center

    Pratt, Dave; Johnston-Wilder, Peter; Ainley, Janet; Mason, John

    2008-01-01

    In this reflective paper, we explore students' local and global thinking about informal statistical inference through our observations of 10- to 11-year-olds, challenged to infer the unknown configuration of a virtual die, but able to use the die to generate as much data as they felt necessary. We report how they tended to focus on local changes…

  19. Inferring Learners' Knowledge from Their Actions

    ERIC Educational Resources Information Center

    Rafferty, Anna N.; LaMar, Michelle M.; Griffiths, Thomas L.

    2015-01-01

    Watching another person take actions to complete a goal and making inferences about that person's knowledge is a relatively natural task for people. This ability can be especially important in educational settings, where the inferences can be used for assessment, diagnosing misconceptions, and providing informative feedback. In this paper, we…

  20. Generative Inferences Based on Learned Relations

    ERIC Educational Resources Information Center

    Chen, Dawn; Lu, Hongjing; Holyoak, Keith J.

    2017-01-01

    A key property of relational representations is their "generativity": From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from…

  1. The Reasoning behind Informal Statistical Inference

    ERIC Educational Resources Information Center

    Makar, Katie; Bakker, Arthur; Ben-Zvi, Dani

    2011-01-01

    Informal statistical inference (ISI) has been a frequent focus of recent research in statistics education. Considering the role that context plays in developing ISI calls into question the need to be more explicit about the reasoning that underpins ISI. This paper uses educational literature on informal statistical inference and philosophical…

  2. Genetic Network Inference Using Hierarchical Structure

    PubMed Central

    Kimura, Shuhei; Tokuhisa, Masato; Okada-Hatakeyama, Mariko

    2016-01-01

    Many methods for inferring genetic networks have been proposed, but the regulations they infer often include false-positives. Several researchers have attempted to reduce these erroneous regulations by proposing the use of a priori knowledge about the properties of genetic networks such as their sparseness, scale-free structure, and so on. This study focuses on another piece of a priori knowledge, namely, that biochemical networks exhibit hierarchical structures. Based on this idea, we propose an inference approach that uses the hierarchical structure in a target genetic network. To obtain a reasonable hierarchical structure, the first step of the proposed approach is to infer multiple genetic networks from the observed gene expression data. We take this step using an existing method that combines a genetic network inference method with a bootstrap method. The next step is to extract a hierarchical structure from the inferred networks that is consistent with most of the networks. Third, we use the hierarchical structure obtained to assign confidence values to all candidate regulations. Numerical experiments are also performed to demonstrate the effectiveness of using the hierarchical structure in the genetic network inference. The improvement accomplished by the use of the hierarchical structure is small. However, the hierarchical structure could be used to improve the performances of many existing inference methods. PMID:26941653

  3. The Impact of Disablers on Predictive Inference

    ERIC Educational Resources Information Center

    Cummins, Denise Dellarosa

    2014-01-01

    People consider alternative causes when deciding whether a cause is responsible for an effect (diagnostic inference) but appear to neglect them when deciding whether an effect will occur (predictive inference). Five experiments were conducted to test a 2-part explanation of this phenomenon: namely, (a) that people interpret standard predictive…

  4. LAIT: a local ancestry inference toolkit.

    PubMed

    Hui, Daniel; Fang, Zhou; Lin, Jerome; Duan, Qing; Li, Yun; Hu, Ming; Chen, Wei

    2017-09-06

    Inferring local ancestry in individuals of mixed ancestry has many applications, most notably in identifying disease-susceptible loci that vary among different ethnic groups. Many software packages are available for inferring local ancestry in admixed individuals. However, most of these existing software packages require specific formatted input files and generate output files in various types, yielding practical inconvenience. We developed a tool set, Local Ancestry Inference Toolkit (LAIT), which can convert standardized files into software-specific input file formats as well as standardize and summarize inference results for four popular local ancestry inference software: HAPMIX, LAMP, LAMP-LD, and ELAI. We tested LAIT using both simulated and real data sets and demonstrated that LAIT provides convenience to run multiple local ancestry inference software. In addition, we evaluated the performance of local ancestry software among different supported software packages, mainly focusing on inference accuracy and computational resources used. We provided a toolkit to facilitate the use of local ancestry inference software, especially for users with limited bioinformatics background.

  5. Predictive Inferences are Represented as Hypothetical Facts

    ERIC Educational Resources Information Center

    Campion, Nicolas

    2004-01-01

    Three experiments examined the processing of predictive and deductive inferences elicited by narrative texts. In Experiment 1, lexical decision responses indicated that these inferences were activated during reading. In Experiment 2, sentences expressing that an event had ''maybe'' taken place were shown to be appropriate in verifying predictive…

  6. Causal Inferences during Text Comprehension and Production.

    ERIC Educational Resources Information Center

    Kemper, Susan

    As comprehension failure results whenever readers are unable to infer missing causal connections, recent comprehension research has focused both on assessing the inferential complexity of texts and on investigating students' developing ability to infer causal relationships. Studies have demonstrated that texts rely on four types of causal…

  7. Measuring the Inference Load of a Text.

    ERIC Educational Resources Information Center

    Kemper, Susan

    1983-01-01

    A new approach to measuring readability is proposed based on the analysis of texts as causally connected chains of actions, physical states, and mental states. Using the inference load formula reflecting the difficulty readers have in inferring causal connections, the difficulty of texts can be adjusted for readers differing in skill or knowledge.…

  8. Causal inference in economics and marketing.

    PubMed

    Varian, Hal R

    2016-07-05

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference.

  9. Application of Transformations in Parametric Inference

    ERIC Educational Resources Information Center

    Brownstein, Naomi; Pensky, Marianna

    2008-01-01

    The objective of the present paper is to provide a simple approach to statistical inference using the method of transformations of variables. We demonstrate performance of this powerful tool on examples of constructions of various estimation procedures, hypothesis testing, Bayes analysis and statistical inference for the stress-strength systems.…

  10. Causal Inference in Public Health

    PubMed Central

    Glass, Thomas A.; Goodman, Steven N.; Hernán, Miguel A.; Samet, Jonathan M.

    2014-01-01

    Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action’s consequences rather than the less precise notion of a risk factor’s causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world. PMID:23297653

  11. Saturn's ionosphere - Inferred electron densities

    NASA Astrophysics Data System (ADS)

    Kaiser, M. L.; Desch, M. D.; Connerney, J. E. P.

    1984-04-01

    During the two Voyager encounters with Saturn, radio bursts were detected which appear to have originated from atmospheric lightning storms. Although these bursts generally extended over frequencies from as low as 100 kHz to the upper detection limit of the instrument, 40 MHz, they often exhibited a sharp but variable low frequency cutoff below which bursts were not detected. We interpret the variable low-frequency extent of these bursts to be due to the reflection of the radio waves as they propagate through an ionosphere which varies with local time. We obtain estimates of electron densities at a variety of latitude and local time locations. These compare well with the dawn and dusk densities measured by the Pioneer 11 Voyager Radio Science investigations, and with model predictions for dayside densities. However, we infer a two-order-of-magnitude diurnal variation of electron density, which had not been anticipated by theoretical models of Saturn's ionosphere, and an equally dramatic extinction of ionospheric electron density by Saturn's rings. Previously announced in STAR as N84-17102

  12. Reinforcement Learning or Active Inference?

    PubMed Central

    Friston, Karl J.; Daunizeau, Jean; Kiebel, Stefan J.

    2009-01-01

    This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain. PMID:19641614

  13. Redshift data and statistical inference

    NASA Technical Reports Server (NTRS)

    Newman, William I.; Haynes, Martha P.; Terzian, Yervant

    1994-01-01

    Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.

  14. Saturn's ionosphere - Inferred electron densities

    NASA Technical Reports Server (NTRS)

    Kaiser, M. L.; Desch, M. D.; Connerney, J. E. P.

    1984-01-01

    During the two Voyager encounters with Saturn, radio bursts were detected which appear to have originated from atmospheric lightning storms. Although these bursts generally extended over frequencies from as low as 100 kHz to the upper detection limit of the instrument, 40 MHz, they often exhibited a sharp but variable low frequency cutoff below which bursts were not detected. We interpret the variable low-frequency extent of these bursts to be due to the reflection of the radio waves as they propagate through an ionosphere which varies with local time. We obtain estimates of electron densities at a variety of latitude and local time locations. These compare well with the dawn and dusk densities measured by the Pioneer 11 Voyager Radio Science investigations, and with model predictions for dayside densities. However, we infer a two-order-of-magnitude diurnal variation of electron density, which had not been anticipated by theoretical models of Saturn's ionosphere, and an equally dramatic extinction of ionospheric electron density by Saturn's rings. Previously announced in STAR as N84-17102

  15. Saturn's ionosphere: Inferred electron densities

    NASA Technical Reports Server (NTRS)

    Kaiser, M. L.; Desch, M. D.; Connerney, J. E. P.

    1983-01-01

    During the two Voyager encounters with Saturn, radio bursts were detected which appear to have originated from atmospheric lightning storms. Although these bursts generally extended over frequencies from as low as 100 kHz to the upper detection limit of the instrument, 40 MHz, they often exhibited a sharp but variable low frequency cutoff below which bursts were not detected. We interpret the variable low-frequency extent of these bursts to be due to the reflection of the radio waves as they propagate through an ionosphere which varies with local time. We obtain estimates of electron densities at a variety of latitude and local time locations. These compare well with the dawn and dusk densitis measured by the Pioneer 11 Voyager Radio Science investigations, and with model predictions for dayside densities. However, we infer a two-order-of-magnitude diurnal variation of electron density, which had not been anticipated by theoretical models of Saturn's ionosphere, and an equally dramatic extinction of ionospheric electron density by Saturn's rings.

  16. Active Inference: A Process Theory.

    PubMed

    Friston, Karl; FitzGerald, Thomas; Rigoli, Francesco; Schwartenbeck, Philipp; Pezzulo, Giovanni

    2017-01-01

    This article describes a process theory based on active inference and belief propagation. Starting from the premise that all neuronal processing (and action selection) can be explained by maximizing Bayesian model evidence-or minimizing variational free energy-we ask whether neuronal responses can be described as a gradient descent on variational free energy. Using a standard (Markov decision process) generative model, we derive the neuronal dynamics implicit in this description and reproduce a remarkable range of well-characterized neuronal phenomena. These include repetition suppression, mismatch negativity, violation responses, place-cell activity, phase precession, theta sequences, theta-gamma coupling, evidence accumulation, race-to-bound dynamics, and transfer of dopamine responses. Furthermore, the (approximately Bayes' optimal) behavior prescribed by these dynamics has a degree of face validity, providing a formal explanation for reward seeking, context learning, and epistemic foraging. Technically, the fact that a gradient descent appears to be a valid description of neuronal activity means that variational free energy is a Lyapunov function for neuronal dynamics, which therefore conform to Hamilton's principle of least action.

  17. Reinforcement learning or active inference?

    PubMed

    Friston, Karl J; Daunizeau, Jean; Kiebel, Stefan J

    2009-07-29

    This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.

  18. Therapeutic inferences for individual patients.

    PubMed

    Flores, Luis

    2015-06-01

    Increased awareness of the gap between controlled research and medical practice has raised concerns over whether the special attention of doctors to probability estimates from clinical trials really improves the care of individuals. Evidence-based medicine has acknowledged that research results are not applicable to all kinds of patients, and consequently, has attempted to overcome this limitation by introducing improvements in the design and analysis of clinical trials. A clinical case is used to highlight the premises required to support reasonable extrapolations from controlled research to individuals. Then, the prospects of two key methodological improvements - pragmatic randomized controlled trials and subgroup analysis - are critically appraised. A principle to guide therapeutic inferences is suggested. According to this principle, the probabilities of interest for purposes of therapeutic decision making are those of the set defined by everything that is relevant to the patient and the outcome of interest at the time of the decision. It is argued that the conditions necessary to authorize automatic extrapolations of research results to specific patients are highly demanding. Furthermore, these requirements are rarely accomplished in real practice, even in the event that probability estimates come from samples generally taken as representative and are derived from specific subsets of patients. Clinicians should generally avoid unreflective extrapolations from research and address, as explicitly as possible, the challenge of estimating probabilities for individual patients. A key element of this task is the integration of data from research and non-research sources. © 2014 John Wiley & Sons, Ltd.

  19. How Is Iron-Deficiency Anemia Treated?

    MedlinePlus

    ... page from the NHLBI on Twitter. How Is Iron-Deficiency Anemia Treated? Treatment for iron-deficiency anemia will ... cases, surgery may be advised. Treatments for Severe Iron-Deficiency Anemia Blood Transfusion If your iron-deficiency anemia ...

  20. Inference-based constraint satisfaction supports explanation

    SciTech Connect

    Sqalli, M.H.; Freuder, E.C.

    1996-12-31

    Constraint satisfaction problems are typically solved using search, augmented by general purpose consistency inference methods. This paper proposes a paradigm shift in which inference is used as the primary problem solving method, and attention is focused on special purpose, domain specific inference methods. While we expect this approach to have computational advantages, we emphasize here the advantages of a solution method that is more congenial to human thought processes. Specifically we use inference-based constraint satisfaction to support explanations of the problem solving behavior that are considerably more meaningful than a trace of a search process would be. Logic puzzles are used as a case study. Inference-based constraint satisfaction proves surprisingly powerful and easily extensible in this domain. Problems drawn from commercial logic puzzle booklets are used for evaluation. Explanations are produced that compare well with the explanations provided by these booklets.

  1. Three Roads Diverged? Routes To Phylogeographic Inference

    PubMed Central

    Bloomquist, Erik W.; Lemey, Philippe

    2010-01-01

    Phylogeographic methods enable inference of the geographical history of genetic lineages. Recent examples successfully explore the patterns of human migration and the origins and spread of viral pandemics. Nevertheless, longstanding disagreement exists over the use and validity of certain phylogeographic inference methodologies. In this paper, we highlight three distinct frameworks for phylogeographic inference to give a taste of this disagreement. Each of the three approaches presents a different viewpoint on phylogeography, most fundamentally how we view the relationship between the inferred history of the sample and the history of the population the sample is embedded in. Satisfactory resolution of this relationship between history of the tree and history of the population remains a challenge for all but the most trivial models of phylogeographic processes. Intriguingly, we believe that some recent methods that entirely side-step inference about the history of the population will eventually help the field toward this goal. PMID:20863591

  2. Phenylalanine hydroxylase deficiency.

    PubMed

    Mitchell, John J; Trakadis, Yannis J; Scriver, Charles R

    2011-08-01

    Phenylalanine hydroxylase deficiency is an autosomal recessive disorder that results in intolerance to the dietary intake of the essential amino acid phenylalanine. It occurs in approximately 1:15,000 individuals. Deficiency of this enzyme produces a spectrum of disorders including classic phenylketonuria, mild phenylketonuria, and mild hyperphenylalaninemia. Classic phenylketonuria is caused by a complete or near-complete deficiency of phenylalanine hydroxylase activity and without dietary restriction of phenylalanine most children will develop profound and irreversible intellectual disability. Mild phenylketonuria and mild hyperphenylalaninemia are associated with lower risk of impaired cognitive development in the absence of treatment. Phenylalanine hydroxylase deficiency can be diagnosed by newborn screening based on detection of the presence of hyperphenylalaninemia using the Guthrie microbial inhibition assay or other assays on a blood spot obtained from a heel prick. Since the introduction of newborn screening, the major neurologic consequences of hyperphenylalaninemia have been largely eradicated. Affected individuals can lead normal lives. However, recent data suggest that homeostasis is not fully restored with current therapy. Treated individuals have a higher incidence of neuropsychological problems. The mainstay of treatment for hyperphenylalaninemia involves a low-protein diet and use of a phenylalanine-free medical formula. This treatment must commence as soon as possible after birth and should continue for life. Regular monitoring of plasma phenylalanine and tyrosine concentrations is necessary. Targets of plasma phenylalanine of 120-360 μmol/L (2-6 mg/dL) in the first decade of life are essential for optimal outcome. Phenylalanine targets in adolescence and adulthood are less clear. A significant proportion of patients with phenylketonuria may benefit from adjuvant therapy with 6R-tetrahydrobiopterin stereoisomer. Special consideration must be

  3. Principal stratification in causal inference.

    PubMed

    Frangakis, Constantine E; Rubin, Donald B

    2002-03-01

    Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority.

  4. Inference for phylogenies under a hybrid parsimony method: evolutionary-symmetric transversion parsimony.

    PubMed

    Sinsheimer, J S; Lake, J A; Little, R J

    1997-03-01

    A new method is proposed for inferring topology for evolutionary trees. Existing methods have complementary strengths and weaknesses. Maximum and transversion parsimony are powerful methods, but they lack statistical consistency, that is, they do not always infer the correct tree as the sequence length becomes very large. Evolutionary parsimony overcomes this deficiency, but it may lack sufficient power when sequence length is small (less than 1000 aligned nucleotides; Sinsheimer, Lake, and Little, 1996, Biometrics 52, 193-210). Our proposed method, evolutionary-symmetric transversion parsimony, is a hybrid that retains the consistency of evolutionary parsimony, while increasing power by incorporating a modified form of transversion parsimony within a statistical model. The method requires choice of a parameter gamma that represents the prior probability that symmetric transversion parsimony yields consistent results. Properties of the method are assessed for a variety of choices of gamma in a large simulation study. In general, inference under the evolutionary-symmetric transversion parsimony has more discriminating power than inference under evolutionary parsimony and is better calibrated than inference under symmetric transversion parsimony. The results are quite robust to the choice of gamma, indicating a value of 0.90 as a reasonable overall choice when the true value of gamma ranges between 0.85 to 1.00. Our method is, like evolutionary parsimony and maximum parsimony, computationally straightforward. The same statistical approach can be applied to combine evolutionary parsimony with other inconsistent methods, such as maximum parsimony, but at the expense of more difficult computations.

  5. Causal inference in obesity research.

    PubMed

    Franks, P W; Atabaki-Pasdar, N

    2017-03-01

    Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis. © 2016 The Association for the Publication of the Journal of Internal Medicine.

  6. Inferring Mantle From Basalt Composition

    NASA Astrophysics Data System (ADS)

    Stracke, A.

    2014-12-01

    Isotope ratios in oceanic basalts, first reported by Gast and co-workers 50 years ago, are unique tracers of mantle composition, because they are expected to mirror the composition of their mantle sources. While the latter is certainly true for homogeneous sources, the plethora of studies over the last 50 years have shown that mantle sources are isotopically heterogeneous on different length scales. Isotopic differences exist between basalts from different ocean basins, volcanoes of individual ocean islands, lava flows of a single volcano, and even in μm sized melt inclusions in a single mineral grain. Diffusion, which acts to homogenize isotopic heterogeneity over Gyr timescales, limits the length scale of isotopic heterogeneity in the mantle to anywhere between several mm to 10s of meters. Melting regions, however, are typically several 100 km wide and up to 100 km deep. The scale of melting is thus generally orders of magnitude larger than the scale of isotopic heterogeneity. How partial melts mix during melting, melt transport, and melt storage then inevitably influences how isotopic heterogeneity is conveyed from source to melt. The isotopic composition of oceanic basalts hence provides an integrated signal of isotopically diverse melts. Recent mixing models and observed isotopic differences between source (abyssal peridotites) and melts (MORB) show that the range of isotopic heterogeneity of erupted melts need NOT directly reflect that of their source(s), nor need observed isotopic endmembers in source and melts be congruent. Many geochemical models, however, implicitly assume equivalence of source and melt composition. Especially when attempting to infer spatial patterns of isotopic heterogeneity in the mantle from those observed in erupted melts, or for linking isotopic diversity to geophysical structures in the mantle requires a more profound understanding to what extent erupted melts represent the isotopic composition of their mantle sources.

  7. Inferring genetic networks from microarray data.

    SciTech Connect

    May, Elebeoba Eni; Davidson, George S.; Martin, Shawn Bryan; Werner-Washburne, Margaret C.; Faulon, Jean-Loup Michel

    2004-06-01

    In theory, it should be possible to infer realistic genetic networks from time series microarray data. In practice, however, network discovery has proved problematic. The three major challenges are: (1) inferring the network; (2) estimating the stability of the inferred network; and (3) making the network visually accessible to the user. Here we describe a method, tested on publicly available time series microarray data, which addresses these concerns. The inference of genetic networks from genome-wide experimental data is an important biological problem which has received much attention. Approaches to this problem have typically included application of clustering algorithms [6]; the use of Boolean networks [12, 1, 10]; the use of Bayesian networks [8, 11]; and the use of continuous models [21, 14, 19]. Overviews of the problem and general approaches to network inference can be found in [4, 3]. Our approach to network inference is similar to earlier methods in that we use both clustering and Boolean network inference. However, we have attempted to extend the process to better serve the end-user, the biologist. In particular, we have incorporated a system to assess the reliability of our network, and we have developed tools which allow interactive visualization of the proposed network.

  8. On Bayesian Inductive Inference & Predictive Estimation

    NASA Technical Reports Server (NTRS)

    Cheeseman, Peter; Stutz, John; Smelyanskiy, Vadim

    2004-01-01

    We investigate Bayesian inference and the Principle of Maximum Entropy (PME) as methods for doing inference under uncertainty. This investigation is primarily through concrete examples that have been previously investigated in the literature. We find that it is possible to do Bayesian inference and PME inference using the same information, despite claims to the contrary, but that the results are not directly comparable. This is because Bayesian inference yields a probability density function (pdf) over the unknown model parameters, whereas PME yields point estimates. If mean estimates are extracted from the Bayesian pdfs, the resulting parameter estimates can differ radically from the PME values and also from the Maximum Likelihood values. We conclude that these differences are due to the Bayesian inference not assuming anything beyond the given prior probabilities and the data, whereas PME implicitly assumes that the given constraints are the only constraints that are operating. Since this assumption can be wrong, PME values may have to be revised when subsequent data shows evidence for more constraints. The entropy concentration previously "proved" by E. T. Jaynes is shown to be in error. Further, we show that PME is a generalized form of independence assumption, and so can be a very powerful method of inference when the variables being investigated are largely independent of each other.

  9. Linguistic Markers of Inference Generation While Reading.

    PubMed

    Clinton, Virginia; Carlson, Sarah E; Seipel, Ben

    2016-06-01

    Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students ([Formula: see text]) reading narrative texts were hand-coded for inferences. These data were also processed with a computer text analysis tool, Linguistic Inquiry and Word Count, for percentages of word use in the following categories: cognitive mechanism words, nonfluencies, and nine types of function words. Findings indicate that cognitive mechanisms were an independent, positive predictor of connections to background knowledge (i.e., elaborative inference generation) and nonfluencies were an independent, negative predictor of connections within the text (i.e., bridging inference generation). Function words did not provide unique variance towards predicting inference generation. These findings are discussed in the context of a cognitive reflection model and the differences between bridging and elaborative inference generation. In addition, potential practical implications for intelligent tutoring systems and computer-based methods of inference identification are presented.

  10. Statistical Physics of High Dimensional Inference

    NASA Astrophysics Data System (ADS)

    Advani, Madhu; Ganguli, Surya

    To model modern large-scale datasets, we need efficient algorithms to infer a set of P unknown model parameters from N noisy measurements. What are fundamental limits on the accuracy of parameter inference, given limited measurements, signal-to-noise ratios, prior information, and computational tractability requirements? How can we combine prior information with measurements to achieve these limits? Classical statistics gives incisive answers to these questions as the measurement density α =N/P --> ∞ . However, modern high-dimensional inference problems, in fields ranging from bio-informatics to economics, occur at finite α. We formulate and analyze high-dimensional inference analytically by applying the replica and cavity methods of statistical physics where data serves as quenched disorder and inferred parameters play the role of thermal degrees of freedom. Our analysis reveals that widely cherished Bayesian inference algorithms such as maximum likelihood and maximum a posteriori are suboptimal in the modern setting, and yields new tractable, optimal algorithms to replace them as well as novel bounds on the achievable accuracy of a large class of high-dimensional inference algorithms. Thanks to Stanford Graduate Fellowship and Mind Brain Computation IGERT grant for support.

  11. On Bayesian Inductive Inference & Predictive Estimation

    NASA Technical Reports Server (NTRS)

    Cheeseman, Peter; Stutz, John; Smelyanskiy, Vadim

    2004-01-01

    We investigate Bayesian inference and the Principle of Maximum Entropy (PME) as methods for doing inference under uncertainty. This investigation is primarily through concrete examples that have been previously investigated in the literature. We find that it is possible to do Bayesian inference and PME inference using the same information, despite claims to the contrary, but that the results are not directly comparable. This is because Bayesian inference yields a probability density function (pdf) over the unknown model parameters, whereas PME yields point estimates. If mean estimates are extracted from the Bayesian pdfs, the resulting parameter estimates can differ radically from the PME values and also from the Maximum Likelihood values. We conclude that these differences are due to the Bayesian inference not assuming anything beyond the given prior probabilities and the data, whereas PME implicitly assumes that the given constraints are the only constraints that are operating. Since this assumption can be wrong, PME values may have to be revised when subsequent data shows evidence for more constraints. The entropy concentration previously "proved" by E. T. Jaynes is shown to be in error. Further, we show that PME is a generalized form of independence assumption, and so can be a very powerful method of inference when the variables being investigated are largely independent of each other.

  12. Carnitine palmitoyltransferase II deficiency

    PubMed Central

    Roe, C R.; Yang, B-Z; Brunengraber, H; Roe, D S.; Wallace, M; Garritson, B K.

    2008-01-01

    Background: Carnitine palmitoyltransferase II (CPT II) deficiency is an important cause of recurrent rhabdomyolysis in children and adults. Current treatment includes dietary fat restriction, with increased carbohydrate intake and exercise restriction to avoid muscle pain and rhabdomyolysis. Methods: CPT II enzyme assay, DNA mutation analysis, quantitative analysis of acylcarnitines in blood and cultured fibroblasts, urinary organic acids, the standardized 36-item Short-Form Health Status survey (SF-36) version 2, and bioelectric impedance for body fat composition. Diet treatment with triheptanoin at 30% to 35% of total daily caloric intake was used for all patients. Results: Seven patients with CPT II deficiency were studied from 7 to 61 months on the triheptanoin (anaplerotic) diet. Five had previous episodes of rhabdomyolysis requiring hospitalizations and muscle pain on exertion prior to the diet (two younger patients had not had rhabdomyolysis). While on the diet, only two patients experienced mild muscle pain with exercise. During short periods of noncompliance, two patients experienced rhabdomyolysis with exercise. None experienced rhabdomyolysis or hospitalizations while on the diet. All patients returned to normal physical activities including strenuous sports. Exercise restriction was eliminated. Previously abnormal SF-36 physical composite scores returned to normal levels that persisted for the duration of the therapy in all five symptomatic patients. Conclusions: The triheptanoin diet seems to be an effective therapy for adult-onset carnitine palmitoyltransferase II deficiency. GLOSSARY ALT = alanine aminotransferase; AST = aspartate aminotransferase; ATP = adenosine triphosphate; BHP = β-hydroxypentanoate; BKP = β-ketopentanoate; BKP-CoA = β-ketopentanoyl–coenzyme A; BUN = blood urea nitrogen; CAC = citric acid cycle; CoA = coenzyme A; CPK = creatine phosphokinase; CPT II = carnitine palmitoyltransferase II; LDL = low-density lipoprotein; MCT

  13. Iatrogenic nutritional deficiencies.

    PubMed

    Young, R C; Blass, J P

    1982-01-01

    This article catalogs the nutritional deficiencies inadvertently introduced by certain treatment regimens. Specifically, the iatrogenic effects on nutrition of surgery, hemodialysis, irradiation, and drugs are reviewed. Nutritional problems are particularly frequent consequences of surgery on the gastrointestinal tract. Gastric surgery can lead to deficiencies of vitamin B12, folate, iron, and thiamine, as well as to metabolic bone disease. The benefits of small bowel bypass are limited by the potentially severe nutritional consequences of this procedure. Following bypass surgery, patients should be monitored for signs of possible nutritional probems such as weight loss, neuropathy, cardiac arrhythmias, loss of stamina, or changes in mental status. Minimal laboratory tests should include hematologic evaluation, B12, folate, iron, albumin, calcium, phosphorus, alkaline phosphatase, transaminases, sodium, potassium, chloride, and carbon dioxide levels. Roentgenologic examination of the bone should also be obtained. Loss of bone substance is a major consequence of many forms of treatment, and dietary supplementation with calcium is warranted. Patients undergoing hemodialysis have shown carnitine and choline deficiencies, potassium depletion, and hypovitaminosis, as well as osteomalacia. Chronic drug use may alter intake, synthesis, absorption, transport, storage, metabolism, or excretion of nutrients. Patients vary markedly in the metabolic effects of drugs, and recommendations for nutrition must be related to age, sex, reproductive status, and genetic endowment. Moreover, the illness being treated can itself alter nutritional requirements and the effect of the treatment on nutrient status. The changes in nutritional levels induced by use of estrogen-containing oral contraceptives (OCs) are obscure; however, the effects on folate matabolism appear to be of less clinical import than previously suggested. Reduction in pyridoxine and serum vitamin B12 levels has been

  14. Placental steroid deficiency: association with arylsulfatase A deficiency.

    PubMed Central

    Vidgoff, J; Buxman, M M; Shapiro, L J; Dimond, R L; Wilson, T G; Hepburn, C A; Tabei, T; Heinrichs, W R

    1982-01-01

    A family with an obstetric history consistent with placental sulfatase deficiency has X-linked ichthyosis. Steroid sulfatase deficiency was confirmed in placenta, leukocytes, and cultured skin fibroblasts of affected males; arylsulfatase A diminution was also observed in these tissues of both affected males and 2 generations of related females. No symptoms of metachromatic leukodystrophy are present in any family members. In this family, placental sulfatase deficiency, and arylsulfatase A pseudodeficiency are nonallelic. PMID:6123259

  15. Inference and the introductory statistics course

    NASA Astrophysics Data System (ADS)

    Pfannkuch, Maxine; Regan, Matt; Wild, Chris; Budgett, Stephanie; Forbes, Sharleen; Harraway, John; Parsonage, Ross

    2011-10-01

    This article sets out some of the rationale and arguments for making major changes to the teaching and learning of statistical inference in introductory courses at our universities by changing from a norm-based, mathematical approach to more conceptually accessible computer-based approaches. The core problem of the inferential argument with its hypothetical probabilistic reasoning process is examined in some depth. We argue that the revolution in the teaching of inference must begin. We also discuss some perplexing issues, problematic areas and some new insights into language conundrums associated with introducing the logic of inference through randomization methods.

  16. Degradation monitoring using probabilistic inference

    NASA Astrophysics Data System (ADS)

    Alpay, Bulent

    In order to increase safety and improve economy and performance in a nuclear power plant (NPP), the source and extent of component degradations should be identified before failures and breakdowns occur. It is also crucial for the next generation of NPPs, which are designed to have a long core life and high fuel burnup to have a degradation monitoring system in order to keep the reactor in a safe state, to meet the designed reactor core lifetime and to optimize the scheduled maintenance. Model-based methods are based on determining the inconsistencies between the actual and expected behavior of the plant, and use these inconsistencies for detection and diagnostics of degradations. By defining degradation as a random abrupt change from the nominal to a constant degraded state of a component, we employed nonlinear filtering techniques based on state/parameter estimation. We utilized a Bayesian recursive estimation formulation in the sequential probabilistic inference framework and constructed a hidden Markov model to represent a general physical system. By addressing the problem of a filter's inability to estimate an abrupt change, which is called the oblivious filter problem in nonlinear extensions of Kalman filtering, and the sample impoverishment problem in particle filtering, we developed techniques to modify filtering algorithms by utilizing additional data sources to improve the filter's response to this problem. We utilized a reliability degradation database that can be constructed from plant specific operational experience and test and maintenance reports to generate proposal densities for probable degradation modes. These are used in a multiple hypothesis testing algorithm. We then test samples drawn from these proposal densities with the particle filtering estimates based on the Bayesian recursive estimation formulation with the Metropolis Hastings algorithm, which is a well-known Markov chain Monte Carlo method (MCMC). This multiple hypothesis testing

  17. Familial apolipoprotein E deficiency.

    PubMed Central

    Schaefer, E J; Gregg, R E; Ghiselli, G; Forte, T M; Ordovas, J M; Zech, L A; Brewer, H B

    1986-01-01

    A unique kindred with premature cardiovascular disease, tubo-eruptive xanthomas, and type III hyperlipoproteinemia (HLP) associated with familial apolipoprotein (apo) E deficiency was examined. Homozygotes (n = 4) had marked increases in cholesterol-rich very low density lipoproteins (VLDL) and intermediate density lipoproteins (IDL), which could be effectively lowered with diet and medication (niacin, clofibrate). Homozygotes had only trace amounts of plasma apoE, and accumulations of apoB-48 and apoA-IV in VLDL, IDL, and low density lipoproteins. Radioiodinated VLDL apoB and apoE kinetic studies revealed that the homozygous proband had markedly retarded fractional catabolism of VLDL apoB-100, apoB-48 and plasma apoE, as well as an extremely low apoE synthesis rate as compared to normals. Obligate heterozygotes (n = 10) generally had normal plasma lipids and mean plasma apoE concentrations that were 42% of normal. The data indicate that homozygous familial apoE deficiency is a cause of type III HLP, is associated with markedly decreased apoE production, and that apoE is essential for the normal catabolism of triglyceride-rich lipoprotein constituents. Images PMID:3771793

  18. by Cu Deficiencies

    NASA Astrophysics Data System (ADS)

    Wei, Tian-Ran; Li, Fu; Li, Jing-Feng

    2014-06-01

    This work revealed that the Cu-deficient ternary compounds Cu3- x SbSe4 free of Te and Pb exhibit enhanced thermoelectric performance. Cu3- x SbSe4 ( x = 0, 0.025, 0.050, 0.075) polycrystalline materials with high phase purity were fabricated by a facile method combining mechanical alloying and spark plasma sintering. Effects of Cu deficiencies on crystal structures, microstructures, element chemical states, and thermoelectric properties were systematically studied. High carrier concentration was obtained for the compositions Cu2.95SbSe4 and Cu2.925SbSe4 due to additional Cu vacancies, contributing to a remarkable increase in electrical conductivity. Together with a satisfactorily large Seebeck coefficient above 300 μV/K, a high power factor of about 890 μW/m-K2 at 523 K was achieved for Cu2.95SbSe4 and Cu2.925SbSe4, almost 60% larger than that of the stoichiometric sample with x = 0. The maximum ZT value was increased to 0.50 at 673 K in the Cu2.925SbSe4 sample sintered at a high temperature (703 K); this is the highest value reported so far for the undoped Cu3SbSe4 system.

  19. Subclinical cobalamin deficiency.

    PubMed

    Carmel, Ralph

    2012-03-01

    This review focuses on recent developments and controversies in the diagnosis, consequences, and management of subclinical cobalamin deficiency (SCCD), which affects many elderly persons. Diagnosis of SCCD depends exclusively on biochemical tests whose individual limitations suggest that combinations of tests are needed, especially in epidemiologic research. The causes of SCCD are unknown in more than 60% of cases, which limits prognostic predictions and identification of health consequences. After years of varying, often inconclusive associations, new clinical trials suggest that homocysteine reduction by high doses of folic acid, cobalamin, and pyridoxine may reduce progression of structural brain changes and cognitive impairment, especially in predisposed individuals. The causative or contributory roles, if any, of SCCD itself in cognitive dysfunction require direct study. If the findings are confirmed, high-dose supplementation with three vitamins will probably be more effective than fortification of the diet. The story of SCCD, which is severalfold times more common in the elderly than clinical cobalamin deficiency but also differs from it in arising only infrequently from severe malabsorption and thus being less likely to progress, continues to evolve. Preventive benefits need to be confirmed and expanded, and will require fuller understanding of SCCD pathophysiology, natural history, and health consequences.

  20. Vitamin D Deficiency

    PubMed Central

    Alshishtawy, Moeness Moustafa

    2012-01-01

    Recently, scientists have generated a strong body of evidence providing new information about the preventive effect of vitamin D on a broad range of disorders. This evidence suggests that vitamin D is much more than a nutrient needed for bone health; it is an essential hormone required for regulation of a large number of physiological functions. Sufficient concentration of serum 25-hydroxyvitamin D is essential for optimising human health. This article reviews the present state-of-the-art knowledge about vitamin D’s status worldwide and refers to recent articles discussing some of the general background of vitamin D, including sources, benefits, deficiencies, and dietary requirements, especially in pregnancy. They offer evidence that vitamin D deficiency could be a major public health burden in many parts of the world, mostly because of sun deprivation. The article also discusses the debate about optimal concentration of circulating serum 25-hydroxyvitamin D, and explores different views on the amount of vitamin D supplementation required to achieve and maintain this concentration. PMID:22548132

  1. Iron-deficiency anaemia.

    PubMed

    Cook, J D

    1994-12-01

    Iron-deficiency anaemia (IDA) is a common clinical problem throughout the world and an enormous public health problem in developing countries. The cornerstone of the laboratory identification of IDA is a low haemoglobin and serum ferritin concentration although a normal serum ferritin does exclude IDA. When the serum ferritin is normal in an anaemic patient with iron-deficient erythropoiesis, it is common practise to perform a bone marrow examination to diagnose IDA. The recent introduction of serum transferrin receptor measurements is a useful alternative for distinguishing IDA from the anaemia of chronic disease because the serum receptor concentration is usually elevated in patients with IDA but normal in patients with anaemia due to inflammation or neoplasia. It is helpful for the clinican to be aware of the causes of physiological IDA. The most important are increased rate of body growth, excessive menstrual blood loss, pregnancy, regular blood donation, intensive endurance training, chronic aspirin use and a vegetarian diet. Without these, a careful search for unsuspected gastrointestinal blood loss must be made and even when the suspicion of physiological IDA is high, it is prudent to screen for fecal occult blood. In most patients, IDA responds promptly to oral iron therapy. Patients who experience troublesome side-effects with oral iron might benefit from a gastric delivery system for oral iron which eliminates nausea and vomiting and improves iron absorption when given with food.(ABSTRACT TRUNCATED AT 250 WORDS)

  2. [Iron deficiency and digestive disorders].

    PubMed

    Cozon, G J N

    2014-11-01

    Iron deficiency anemia still remains problematic worldwide. Iron deficiency without anemia is often undiagnosed. We reviewed, in this study, symptoms and syndromes associated with iron deficiency with or without anemia: fatigue, cognitive functions, restless legs syndrome, hair loss, and chronic heart failure. Iron is absorbed through the digestive tract. Hepcidin and ferroportin are the main proteins of iron regulation. Pathogenic micro-organisms or intestinal dysbiosis are suspected to influence iron absorption.

  3. Bayesian Cosmological inference beyond statistical isotropy

    NASA Astrophysics Data System (ADS)

    Souradeep, Tarun; Das, Santanu; Wandelt, Benjamin

    2016-10-01

    With advent of rich data sets, computationally challenge of inference in cosmology has relied on stochastic sampling method. First, I review the widely used MCMC approach used to infer cosmological parameters and present a adaptive improved implementation SCoPE developed by our group. Next, I present a general method for Bayesian inference of the underlying covariance structure of random fields on a sphere. We employ the Bipolar Spherical Harmonic (BipoSH) representation of general covariance structure on the sphere. We illustrate the efficacy of the method with a principled approach to assess violation of statistical isotropy (SI) in the sky maps of Cosmic Microwave Background (CMB) fluctuations. The general, principled, approach to a Bayesian inference of the covariance structure in a random field on a sphere presented here has huge potential for application to other many aspects of cosmology and astronomy, as well as, more distant areas of research like geosciences and climate modelling.

  4. Experimental evidence for circular inference in schizophrenia

    NASA Astrophysics Data System (ADS)

    Jardri, Renaud; Duverne, Sandrine; Litvinova, Alexandra S.; Denève, Sophie

    2017-01-01

    Schizophrenia (SCZ) is a complex mental disorder that may result in some combination of hallucinations, delusions and disorganized thinking. Here SCZ patients and healthy controls (CTLs) report their level of confidence on a forced-choice task that manipulated the strength of sensory evidence and prior information. Neither group's responses can be explained by simple Bayesian inference. Rather, individual responses are best captured by a model with different degrees of circular inference. Circular inference refers to a corruption of sensory data by prior information and vice versa, leading us to `see what we expect' (through descending loops), to `expect what we see' (through ascending loops) or both. Ascending loops are stronger for SCZ than CTLs and correlate with the severity of positive symptoms. Descending loops correlate with the severity of negative symptoms. Both loops correlate with disorganized symptoms. The findings suggest that circular inference might mediate the clinical manifestations of SCZ.

  5. Are Evaluations Inferred Directly From Overt Actions?

    ERIC Educational Resources Information Center

    Brown, Donald; And Others

    1975-01-01

    The operation of a covert information processing mechanism was investigated in two experiments of the self-persuasion phenomena; i. e., making an inference about a stimulus on the basis of one's past behavior. (Editor)

  6. Modelling, inference and big data in biophysics.

    PubMed

    Ho, Joshua W K; Grant, Guy H

    2017-07-30

    In recognition of the increasing importance of big data in biophysics, a new session called 'Modelling, inference, big data' is incorporated into the IUPAB/EBSA Congress on 18 July 2017 at Edinburgh, UK.

  7. Experimental evidence for circular inference in schizophrenia

    PubMed Central

    Jardri, Renaud; Duverne, Sandrine; Litvinova, Alexandra S; Denève, Sophie

    2017-01-01

    Schizophrenia (SCZ) is a complex mental disorder that may result in some combination of hallucinations, delusions and disorganized thinking. Here SCZ patients and healthy controls (CTLs) report their level of confidence on a forced-choice task that manipulated the strength of sensory evidence and prior information. Neither group's responses can be explained by simple Bayesian inference. Rather, individual responses are best captured by a model with different degrees of circular inference. Circular inference refers to a corruption of sensory data by prior information and vice versa, leading us to ‘see what we expect' (through descending loops), to ‘expect what we see' (through ascending loops) or both. Ascending loops are stronger for SCZ than CTLs and correlate with the severity of positive symptoms. Descending loops correlate with the severity of negative symptoms. Both loops correlate with disorganized symptoms. The findings suggest that circular inference might mediate the clinical manifestations of SCZ. PMID:28139642

  8. An inference engine for embedded diagnostic systems

    NASA Technical Reports Server (NTRS)

    Fox, Barry R.; Brewster, Larry T.

    1987-01-01

    The implementation of an inference engine for embedded diagnostic systems is described. The system consists of two distinct parts. The first is an off-line compiler which accepts a propositional logical statement of the relationship between facts and conclusions and produces data structures required by the on-line inference engine. The second part consists of the inference engine and interface routines which accept assertions of fact and return the conclusions which necessarily follow. Given a set of assertions, it will generate exactly the conclusions which logically follow. At the same time, it will detect any inconsistencies which may propagate from an inconsistent set of assertions or a poorly formulated set of rules. The memory requirements are fixed and the worst case execution times are bounded at compile time. The data structures and inference algorithms are very simple and well understood. The data structures and algorithms are described in detail. The system has been implemented on Lisp, Pascal, and Modula-2.

  9. Metamodel-Driven Evolution with Grammar Inference

    NASA Astrophysics Data System (ADS)

    Bryant, Barrett R.; Liu, Qichao; Mernik, Marjan

    2010-10-01

    Domain-specific modeling (DSM) has become one of the most popular techniques for incorporating model-driven engineering (MDE) into software engineering. In DSM, domain experts define metamodels to describe the essential problems in a domain. A model conforms to a schema definition represented by a metamodel in a similar manner to a programming language conforms to a grammar. Metamodel-driven evolution is when a metamodel undergoes evolutions to incorporate new concerns in the domain. However, this results in losing the ability to use existing model instances. Grammar inference is the problem of inferring a grammar from sample strings which the grammar should generate. This paper describes our work in solving the problem of metamodel-driven evolution with grammar inference, by inferring the metamodel from model instances.

  10. Composite likelihood method for inferring local pedigrees

    PubMed Central

    Nielsen, Rasmus

    2017-01-01

    Pedigrees contain information about the genealogical relationships among individuals and are of fundamental importance in many areas of genetic studies. However, pedigrees are often unknown and must be inferred from genetic data. Despite the importance of pedigree inference, existing methods are limited to inferring only close relationships or analyzing a small number of individuals or loci. We present a simulated annealing method for estimating pedigrees in large samples of otherwise seemingly unrelated individuals using genome-wide SNP data. The method supports complex pedigree structures such as polygamous families, multi-generational families, and pedigrees in which many of the member individuals are missing. Computational speed is greatly enhanced by the use of a composite likelihood function which approximates the full likelihood. We validate our method on simulated data and show that it can infer distant relatives more accurately than existing methods. Furthermore, we illustrate the utility of the method on a sample of Greenlandic Inuit. PMID:28827797

  11. Causal inference in economics and marketing

    PubMed Central

    Varian, Hal R.

    2016-01-01

    This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144

  12. Operation of the Bayes Inference Engine

    SciTech Connect

    Hanson, K.M.; Cunningham, G.S.

    1998-07-27

    The authors have developed a computer application, called the Bayes Inference Engine, to enable one to make inferences about models of a physical object from radiographs taken of it. In the BIE calculational models are represented by a data-flow diagram that can be manipulated by the analyst in a graphical-programming environment. The authors demonstrate the operation of the BIE in terms of examples of two-dimensional tomographic reconstruction including uncertainty estimation.

  13. Inferring ethnicity from mitochondrial DNA sequence

    PubMed Central

    2011-01-01

    Background The assignment of DNA samples to coarse population groups can be a useful but difficult task. One such example is the inference of coarse ethnic groupings for forensic applications. Ethnicity plays an important role in forensic investigation and can be inferred with the help of genetic markers. Being maternally inherited, of high copy number, and robust persistence in degraded samples, mitochondrial DNA may be useful for inferring coarse ethnicity. In this study, we compare the performance of methods for inferring ethnicity from the sequence of the hypervariable region of the mitochondrial genome. Results We present the results of comprehensive experiments conducted on datasets extracted from the mtDNA population database, showing that ethnicity inference based on support vector machines (SVM) achieves an overall accuracy of 80-90%, consistently outperforming nearest neighbor and discriminant analysis methods previously proposed in the literature. We also evaluate methods of handling missing data and characterize the most informative segments of the hypervariable region of the mitochondrial genome. Conclusions Support vector machines can be used to infer coarse ethnicity from a small region of mitochondrial DNA sequence with surprisingly high accuracy. In the presence of missing data, utilizing only the regions common to the training sequences and a test sequence proves to be the best strategy. Given these results, SVM algorithms are likely to also be useful in other DNA sequence classification applications. PMID:21554759

  14. [Vitamin deficiencies in breastfed children due to maternal dietary deficiency].

    PubMed

    Kollée, L A A

    2006-03-04

    Dietary deficiencies of vitamin B12 and vitamin D during pregnancy and lactation may result in health problems in exclusively breastfed infants. Vitamin-B12 deficiency in these infants results in irritability, anorexia and failure to thrive during the first 4-8 months of life. Severe and permanent neurodevelopmental disturbances may occur. The most at risk for vitamin-B12 deficiency are breast-fed infants ofveganist and vegetarian mothers. Mothers who cover their skin prevent exposure to the sun and may consequently be at risk for vitamin-D deficiency, as well as putting their offspring at risk. In prenatal and perinatal care, it is important to take the maternal dietary history in order to be able to prevent or treat these disorders. Guidelines for obstetrical and neonatal care should include the topic of vitamin deficiency.

  15. Hereditary galactokinase deficiency

    PubMed Central

    Cook, J. G. H.; Don, N. A.; Mann, Trevor P.

    1971-01-01

    A baby with galactokinase deficiency, a recessive inborn error of galactose metabolism, is described. The case is exceptional in that there was no evidence of gypsy blood in the family concerned. The investigation of neonatal hyperbilirubinaemia led to the discovery of galactosuria. As noted by others, the paucity of presenting features makes early diagnosis difficult, and detection by biochemical screening seems desirable. Cataract formation, of early onset, appears to be the only severe persisting complication and may be due to the biosynthesis and accumulation of galactitol in the lens. Ophthalmic surgeons need to be aware of this enzyme defect, because with early diagnosis and dietary treatment these lens changes should be reversible. PMID:5109408

  16. Iron deficiency and iron deficiency anemia in women.

    PubMed

    Coad, Jane; Pedley, Kevin

    2014-01-01

    Iron deficiency is one of the most common nutritional problems in the world and disproportionately affects women and children. Stages of iron deficiency can be characterized as mild deficiency where iron stores become depleted, marginal deficiency where the production of many iron-dependent proteins is compromised but hemoglobin levels are normal and iron deficiency anemia where synthesis of hemoglobin is decreased and oxygen transport to the tissues is reduced. Iron deficiency anemia is usually assessed by measuring hemoglobin levels but this approach lacks both specificity and sensitivity. Failure to identify and treat earlier stages of iron deficiency is concerning given the neurocognitive implications of iron deficiency without anemia. Most of the daily iron requirement is derived from recycling of senescent erythrocytes by macrophages; only 5-10 % comes from the diet. Iron absorption is affected by inhibitors and enhancers of iron absorption and by the physiological state. Inflammatory conditions, including obesity, can result in iron being retained in the enterocytes and macrophages causing hypoferremia as a strategic defense mechanism to restrict iron availability to pathogens. Premenopausal women usually have low iron status because of iron loss in menstrual blood. Conditions which further increase iron loss, compromise absorption or increase demand, such as frequent blood donation, gastrointestinal lesions, athletic activity and pregnancy, can exceed the capacity of the gastrointestinal tract to upregulate iron absorption. Women of reproductive age are at particularly high risk of iron deficiency and its consequences however there is a controversial argument that evolutionary pressures have resulted in an iron deficient phenotype which protects against infection.

  17. Peroxisomal bifunctional enzyme deficiency.

    PubMed Central

    Watkins, P A; Chen, W W; Harris, C J; Hoefler, G; Hoefler, S; Blake, D C; Balfe, A; Kelley, R I; Moser, A B; Beard, M E

    1989-01-01

    Peroxisomal function was evaluated in a male infant with clinical features of neonatal adrenoleukodystrophy. Very long chain fatty acid levels were elevated in both plasma and fibroblasts, and beta-oxidation of very long chain fatty acids in cultured fibroblasts was significantly impaired. Although the level of the bile acid intermediate trihydroxycoprostanoic acid was slightly elevated in plasma, phytanic acid and L-pipecolic acid levels were normal, as was plasmalogen synthesis in cultured fibroblasts. The latter three parameters distinguish this case from classical neonatal adrenoleukodystrophy. In addition, electron microscopy and catalase subcellular distribution studies revealed that, in contrast to neonatal adrenoleukodystrophy, peroxisomes were present in the patient's tissues. Immunoblot studies of peroxisomal beta-oxidation enzymes revealed that the bifunctional enzyme (enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase) was deficient in postmortem liver samples, whereas acyl-CoA oxidase and the mature form of beta-ketothiolase were present. Density gradient centrifugation of fibroblast homogenates confirmed that intact peroxisomes were present. Immunoblots of fibroblasts peroxisomal fractions showed that they contained acyl-CoA oxidase and beta-ketothiolase, but bifunctional enzyme was not detected. Northern analysis, however, revealed that mRNA coding for the bifunctional enzyme was present in the patient's fibroblasts. These results indicate that the primary biochemical defect in this patient is a deficiency of peroxisomal bifunctional enzyme. It is of interest that the phenotype of this patient resembled neonatal adrenoleukodystrophy and would not have been distinguished from this disorder by clinical study alone. Images PMID:2921319

  18. Iodine deficiency in Europe.

    PubMed

    Delange, F

    1995-01-18

    Iodine is a trace element present in the human body in minute amounts (15-20 mg in adults, i.e. 0.0285 x 10(-3)% of body weight). The only confirmed function of iodine is to constitute an essential substrate for the synthesis of thyroid hormones, tetraiodothyronine, thyroxine or T4 and triiodothyronine, T3 (1). In thyroxine, iodine is 60% by weight. Thyroid hormones, in turn, play a decisive role in the metabolism of all cells of the organism (2) and in the process of early growth and development of most organs, especially of the brain (3). Brain development in humans occurs from fetal life up to the third postnatal year (4). Consequently, a deficit in iodine and/or in thyroid hormones occurring during this critical period of life will result not only in the slowing down of the metabolic activities of all the cells of the organism but also in irreversible alterations in the development of the brain. The clinical consequence will be mental retardation (5). When the physiological requirements of iodine are not met in a given population, a series of functional and developmental abnormalities occur (Table 1), including thyroid function abnormalities and, when iodine deficiency is severe, endemic goiter and cretinism, endemic mental retardation, decreased fertility rate, increased perinatal death, and infant mortality. These complications, which constitute an hindrance to the development of the affected population, are grouped under the general heading of Iodine Deficiency Disorders, IDD (6). Broad geographic areas exist in which the population is affected by IDD.(ABSTRACT TRUNCATED AT 250 WORDS)

  19. Basic Skills: Dealing with Deficiencies.

    ERIC Educational Resources Information Center

    New Mexico State Univ., Las Cruces.

    Research findings on college instruction and basic skills deficiencies are discussed in 12 papers from the first Regional Conference on University Teaching. Titles and authors are as follows: "Basic Skills: Dealing with Deficiencies" (Susanne D. Roueche, with responses by Gary B. Donart, Betty Harris, and James Nordyke); "Is Higher Education an…

  20. The Cardiomyopathy of Iron Deficiency

    PubMed Central

    Hegde, Nikita; Rich, Michael W.; Gayomali, Charina

    2006-01-01

    Iron-deficiency anemia can have deleterious effects on the heart. Herein, we describe the effects of iron deficiency on the heart as corroborated with electrocardiography, radiology, echocardiography, and cardiac catheterization. We review the pathophysiology, clinical features, and management of iron-deficiency–induced cardiomyopathy. PMID:17041692

  1. Basic Skills: Dealing with Deficiencies.

    ERIC Educational Resources Information Center

    New Mexico State Univ., Las Cruces.

    Research findings on college instruction and basic skills deficiencies are discussed in 12 papers from the first Regional Conference on University Teaching. Titles and authors are as follows: "Basic Skills: Dealing with Deficiencies" (Susanne D. Roueche, with responses by Gary B. Donart, Betty Harris, and James Nordyke); "Is Higher Education an…

  2. Congenital deficiency of meibomian glands.

    PubMed Central

    Bron, A J; Mengher, L S

    1987-01-01

    A 16-year-old girl presented with contact lens intolerance. She was found to have a marked deficiency of meibomian glands in the upper lids and almost total absence in the lower lids. Evidence of tear film instability was found and attributed to deficient lid oil production. A daily wear soft contact lens was later fitted and tolerated. PMID:3580344

  3. Inference of Isoforms from Short Sequence Reads

    NASA Astrophysics Data System (ADS)

    Feng, Jianxing; Li, Wei; Jiang, Tao

    Due to alternative splicing events in eukaryotic species, the identification of mRNA isoforms (or splicing variants) is a difficult problem. Traditional experimental methods for this purpose are time consuming and cost ineffective. The emerging RNA-Seq technology provides a possible effective method to address this problem. Although the advantages of RNA-Seq over traditional methods in transcriptome analysis have been confirmed by many studies, the inference of isoforms from millions of short sequence reads (e.g., Illumina/Solexa reads) has remained computationally challenging. In this work, we propose a method to calculate the expression levels of isoforms and infer isoforms from short RNA-Seq reads using exon-intron boundary, transcription start site (TSS) and poly-A site (PAS) information. We first formulate the relationship among exons, isoforms, and single-end reads as a convex quadratic program, and then use an efficient algorithm (called IsoInfer) to search for isoforms. IsoInfer can calculate the expression levels of isoforms accurately if all the isoforms are known and infer novel isoforms from scratch. Our experimental tests on known mouse isoforms with both simulated expression levels and reads demonstrate that IsoInfer is able to calculate the expression levels of isoforms with an accuracy comparable to the state-of-the-art statistical method and a 60 times faster speed. Moreover, our tests on both simulated and real reads show that it achieves a good precision and sensitivity in inferring isoforms when given accurate exon-intron boundary, TSS and PAS information, especially for isoforms whose expression levels are significantly high.

  4. Multisensory oddity detection as bayesian inference.

    PubMed

    Hospedales, Timothy; Vijayakumar, Sethu

    2009-01-01

    A key goal for the perceptual system is to optimally combine information from all the senses that may be available in order to develop the most accurate and unified picture possible of the outside world. The contemporary theoretical framework of ideal observer maximum likelihood integration (MLI) has been highly successful in modelling how the human brain combines information from a variety of different sensory modalities. However, in various recent experiments involving multisensory stimuli of uncertain correspondence, MLI breaks down as a successful model of sensory combination. Within the paradigm of direct stimulus estimation, perceptual models which use Bayesian inference to resolve correspondence have recently been shown to generalize successfully to these cases where MLI fails. This approach has been known variously as model inference, causal inference or structure inference. In this paper, we examine causal uncertainty in another important class of multi-sensory perception paradigm--that of oddity detection and demonstrate how a Bayesian ideal observer also treats oddity detection as a structure inference problem. We validate this approach by showing that it provides an intuitive and quantitative explanation of an important pair of multi-sensory oddity detection experiments--involving cues across and within modalities--for which MLI previously failed dramatically, allowing a novel unifying treatment of within and cross modal multisensory perception. Our successful application of structure inference models to the new 'oddity detection' paradigm, and the resultant unified explanation of across and within modality cases provide further evidence to suggest that structure inference may be a commonly evolved principle for combining perceptual information in the brain.

  5. Iron deficiency anemia in children.

    PubMed

    Subramaniam, Girish; Girish, Meenakshi

    2015-06-01

    Iron deficiency is not just anemia; it can be responsible for a long list of other manifestations. This topic is of great importance, especially in infancy and early childhood, for a variety of reasons. Firstly, iron need is maximum in this period. Secondly, diet in infancy is usually deficient in iron. Thirdly and most importantly, iron deficiency at this age can result in neurodevelopmental and cognitive deficits, which may not be reversible. Hypochromia and microcytosis in a complete blood count (CBC) makes iron deficiency anemia (IDA) most likely diagnosis. Absence of response to iron should make us look for other differential diagnosis like β thalassemia trait and anemia of chronic disease. Celiac disease is the most important cause of true IDA not responding to oral iron therapy. While oral ferrous sulphate is the cheapest and most effective therapy for IDA, simple nonpharmacological and pharmacological measures can go a long way in prevention of iron deficiency.

  6. Iron deficiency: definition and diagnosis.

    PubMed

    Cook, J D; Skikne, B S

    1989-11-01

    There has been a continuous refinement over the past several decades of methods to detect iron deficiency and assess its magnitude. The optimal combination of measurements differs for clinical and epidemiological assessment. Clinically, the major problem is to distinguish true iron deficiency from other causes of iron-deficient erythropoiesis, such as the anaemia of chronic disease. Epidemiologically, techniques that provide quantified estimates of body iron are preferable. For both purposes, the serum ferritin is the focal point of the laboratory detection of iron deficiency. Serum ferritin measurements provide a reliable index of body iron stores in healthy individuals, a cost-effective method of screening for iron deficiency, and a useful alternative to bone marrow examinations in the evaluation of anaemic patients. Preliminary studies indicate that measurement of the serum transferrin receptor may be the most reliable way to assess deficits in tissue iron supply.

  7. Estimating uncertainty of inference for validation

    SciTech Connect

    Booker, Jane M; Langenbrunner, James R; Hemez, Francois M; Ross, Timothy J

    2010-09-30

    We present a validation process based upon the concept that validation is an inference-making activity. This has always been true, but the association has not been as important before as it is now. Previously, theory had been confirmed by more data, and predictions were possible based on data. The process today is to infer from theory to code and from code to prediction, making the role of prediction somewhat automatic, and a machine function. Validation is defined as determining the degree to which a model and code is an accurate representation of experimental test data. Imbedded in validation is the intention to use the computer code to predict. To predict is to accept the conclusion that an observable final state will manifest; therefore, prediction is an inference whose goodness relies on the validity of the code. Quantifying the uncertainty of a prediction amounts to quantifying the uncertainty of validation, and this involves the characterization of uncertainties inherent in theory/models/codes and the corresponding data. An introduction to inference making and its associated uncertainty is provided as a foundation for the validation problem. A mathematical construction for estimating the uncertainty in the validation inference is then presented, including a possibility distribution constructed to represent the inference uncertainty for validation under uncertainty. The estimation of inference uncertainty for validation is illustrated using data and calculations from Inertial Confinement Fusion (ICF). The ICF measurements of neutron yield and ion temperature were obtained for direct-drive inertial fusion capsules at the Omega laser facility. The glass capsules, containing the fusion gas, were systematically selected with the intent of establishing a reproducible baseline of high-yield 10{sup 13}-10{sup 14} neutron output. The deuterium-tritium ratio in these experiments was varied to study its influence upon yield. This paper on validation inference is the

  8. Interactions between copper deficiency, selenium deficiency and adriamycin toxicity

    SciTech Connect

    Fischer, J.; Tackett, R.; Johnson, M.A. )

    1991-03-15

    The objective of this study was to test the hypothesis that there are interactions between copper (Cu) and selenium (Se) status, and adriamycin (ADR) toxicity. Male Sprague Dawley rats were fed Cu,Se adequate; Cu deficient, Se adequate ({minus}Cu); Cu adequate, Se deficient; or Cu,Se deficient diets for 38-41 days. ADR or saline (SAL) were administered weekly for the last 4 weeks of the study. Cu deficiency was confirmed by a 3-fold decrease in liver Cu,Zn-superoxide dismutase and liver Cu, and a 5-fold decrease in RBC Cu,Zn-SOD. Se deficiency was confirmed by a 10-fold decrease in liver glutathione peroxidase (GSH-Px). ADR, Cu deficiency and Se deficiency all caused EKG abnormalities. However, Cu and Se deficiencies did not enhance ADR's influence on EKGs. ADR increased lipid peroxidation in liver by 15% and in heart by 18% (NS). Cu deficiency decreased ADR-induced lipid peroxidation in heart tissue by 25%. ADR influenced Se status by significantly increasing heart GSH-Px, and Cu status by increasing liver Cu, plasma ceruloplasmin and liver Cu, Zn-SOD. These elevations in Cu,Zn-SOD and GSH-Px may be a consequence of the increased lipid peroxidation initiated by ADR. In {minus}Cu rats, ADR caused severe hemolytic anemia characterized by a 19% decrease in hematocrit and a 17-fold increase in splenic Fe. These data suggest that there are numerous interactions between ADR toxicity and Cu and Se status.

  9. Reliability of the Granger causality inference

    NASA Astrophysics Data System (ADS)

    Zhou, Douglas; Zhang, Yaoyu; Xiao, Yanyang; Cai, David

    2014-04-01

    How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result.

  10. Computational inference of neural information flow networks.

    PubMed

    Smith, V Anne; Yu, Jing; Smulders, Tom V; Hartemink, Alexander J; Jarvis, Erich D

    2006-11-24

    Determining how information flows along anatomical brain pathways is a fundamental requirement for understanding how animals perceive their environments, learn, and behave. Attempts to reveal such neural information flow have been made using linear computational methods, but neural interactions are known to be nonlinear. Here, we demonstrate that a dynamic Bayesian network (DBN) inference algorithm we originally developed to infer nonlinear transcriptional regulatory networks from gene expression data collected with microarrays is also successful at inferring nonlinear neural information flow networks from electrophysiology data collected with microelectrode arrays. The inferred networks we recover from the songbird auditory pathway are correctly restricted to a subset of known anatomical paths, are consistent with timing of the system, and reveal both the importance of reciprocal feedback in auditory processing and greater information flow to higher-order auditory areas when birds hear natural as opposed to synthetic sounds. A linear method applied to the same data incorrectly produces networks with information flow to non-neural tissue and over paths known not to exist. To our knowledge, this study represents the first biologically validated demonstration of an algorithm to successfully infer neural information flow networks.

  11. Deep Learning for Population Genetic Inference.

    PubMed

    Sheehan, Sara; Song, Yun S

    2016-03-01

    Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

  12. Scene Construction, Visual Foraging, and Active Inference

    PubMed Central

    Mirza, M. Berk; Adams, Rick A.; Mathys, Christoph D.; Friston, Karl J.

    2016-01-01

    This paper describes an active inference scheme for visual searches and the perceptual synthesis entailed by scene construction. Active inference assumes that perception and action minimize variational free energy, where actions are selected to minimize the free energy expected in the future. This assumption generalizes risk-sensitive control and expected utility theory to include epistemic value; namely, the value (or salience) of information inherent in resolving uncertainty about the causes of ambiguous cues or outcomes. Here, we apply active inference to saccadic searches of a visual scene. We consider the (difficult) problem of categorizing a scene, based on the spatial relationship among visual objects where, crucially, visual cues are sampled myopically through a sequence of saccadic eye movements. This means that evidence for competing hypotheses about the scene has to be accumulated sequentially, calling upon both prediction (planning) and postdiction (memory). Our aim is to highlight some simple but fundamental aspects of the requisite functional anatomy; namely, the link between approximate Bayesian inference under mean field assumptions and functional segregation in the visual cortex. This link rests upon the (neurobiologically plausible) process theory that accompanies the normative formulation of active inference for Markov decision processes. In future work, we hope to use this scheme to model empirical saccadic searches and identify the prior beliefs that underwrite intersubject variability in the way people forage for information in visual scenes (e.g., in schizophrenia). PMID:27378899

  13. Generative Inferences Based on Learned Relations.

    PubMed

    Chen, Dawn; Lu, Hongjing; Holyoak, Keith J

    2016-11-17

    A key property of relational representations is their generativity: From partial descriptions of relations between entities, additional inferences can be drawn about other entities. A major theoretical challenge is to demonstrate how the capacity to make generative inferences could arise as a result of learning relations from non-relational inputs. In the present paper, we show that a bottom-up model of relation learning, initially developed to discriminate between positive and negative examples of comparative relations (e.g., deciding whether a sheep is larger than a rabbit), can be extended to make generative inferences. The model is able to make quasi-deductive transitive inferences (e.g., "If A is larger than B and B is larger than C, then A is larger than C") and to qualitatively account for human responses to generative questions such as "What is an animal that is smaller than a dog?" These results provide evidence that relational models based on bottom-up learning mechanisms are capable of supporting generative inferences.

  14. Deep Learning for Population Genetic Inference

    PubMed Central

    Sheehan, Sara; Song, Yun S.

    2016-01-01

    Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

  15. Maximum likelihood inference of reticulate evolutionary histories

    PubMed Central

    Yu, Yun; Dong, Jianrong; Liu, Kevin J.; Nakhleh, Luay

    2014-01-01

    Hybridization plays an important role in the evolution of certain groups of organisms, adaptation to their environments, and diversification of their genomes. The evolutionary histories of such groups are reticulate, and methods for reconstructing them are still in their infancy and have limited applicability. We present a maximum likelihood method for inferring reticulate evolutionary histories while accounting simultaneously for incomplete lineage sorting. Additionally, we propose methods for assessing confidence in the amount of reticulation and the topology of the inferred evolutionary history. Our method obtains accurate estimates of reticulate evolutionary histories on simulated datasets. Furthermore, our method provides support for a hypothesis of a reticulate evolutionary history inferred from a set of house mouse (Mus musculus) genomes. As evidence of hybridization in eukaryotic groups accumulates, it is essential to have methods that infer reticulate evolutionary histories. The work we present here allows for such inference and provides a significant step toward putting phylogenetic networks on par with phylogenetic trees as a model of capturing evolutionary relationships. PMID:25368173

  16. Maximum likelihood inference of reticulate evolutionary histories.

    PubMed

    Yu, Yun; Dong, Jianrong; Liu, Kevin J; Nakhleh, Luay

    2014-11-18

    Hybridization plays an important role in the evolution of certain groups of organisms, adaptation to their environments, and diversification of their genomes. The evolutionary histories of such groups are reticulate, and methods for reconstructing them are still in their infancy and have limited applicability. We present a maximum likelihood method for inferring reticulate evolutionary histories while accounting simultaneously for incomplete lineage sorting. Additionally, we propose methods for assessing confidence in the amount of reticulation and the topology of the inferred evolutionary history. Our method obtains accurate estimates of reticulate evolutionary histories on simulated datasets. Furthermore, our method provides support for a hypothesis of a reticulate evolutionary history inferred from a set of house mouse (Mus musculus) genomes. As evidence of hybridization in eukaryotic groups accumulates, it is essential to have methods that infer reticulate evolutionary histories. The work we present here allows for such inference and provides a significant step toward putting phylogenetic networks on par with phylogenetic trees as a model of capturing evolutionary relationships.

  17. Inferring learners' knowledge from their actions.

    PubMed

    Rafferty, Anna N; LaMar, Michelle M; Griffiths, Thomas L

    2015-04-01

    Watching another person take actions to complete a goal and making inferences about that person's knowledge is a relatively natural task for people. This ability can be especially important in educational settings, where the inferences can be used for assessment, diagnosing misconceptions, and providing informative feedback. In this paper, we develop a general framework for automatically making such inferences based on observed actions; this framework is particularly relevant for inferring student knowledge in educational games and other interactive virtual environments. Our approach relies on modeling action planning: We formalize the problem as a Markov decision process in which one must choose what actions to take to complete a goal, where choices will be dependent on one's beliefs about how actions affect the environment. We use a variation of inverse reinforcement learning to infer these beliefs. Through two lab experiments, we show that this model can recover people's beliefs in a simple environment, with accuracy comparable to that of human observers. We then demonstrate that the model can be used to provide real-time feedback and to model data from an existing educational game.

  18. Computationally efficient Bayesian inference for inverse problems.

    SciTech Connect

    Marzouk, Youssef M.; Najm, Habib N.; Rahn, Larry A.

    2007-10-01

    Bayesian statistics provides a foundation for inference from noisy and incomplete data, a natural mechanism for regularization in the form of prior information, and a quantitative assessment of uncertainty in the inferred results. Inverse problems - representing indirect estimation of model parameters, inputs, or structural components - can be fruitfully cast in this framework. Complex and computationally intensive forward models arising in physical applications, however, can render a Bayesian approach prohibitive. This difficulty is compounded by high-dimensional model spaces, as when the unknown is a spatiotemporal field. We present new algorithmic developments for Bayesian inference in this context, showing strong connections with the forward propagation of uncertainty. In particular, we introduce a stochastic spectral formulation that dramatically accelerates the Bayesian solution of inverse problems via rapid evaluation of a surrogate posterior. We also explore dimensionality reduction for the inference of spatiotemporal fields, using truncated spectral representations of Gaussian process priors. These new approaches are demonstrated on scalar transport problems arising in contaminant source inversion and in the inference of inhomogeneous material or transport properties. We also present a Bayesian framework for parameter estimation in stochastic models, where intrinsic stochasticity may be intermingled with observational noise. Evaluation of a likelihood function may not be analytically tractable in these cases, and thus several alternative Markov chain Monte Carlo (MCMC) schemes, operating on the product space of the observations and the parameters, are introduced.

  19. Hierarchical cosmic shear power spectrum inference

    NASA Astrophysics Data System (ADS)

    Alsing, Justin; Heavens, Alan; Jaffe, Andrew H.; Kiessling, Alina; Wandelt, Benjamin; Hoffmann, Till

    2016-02-01

    We develop a Bayesian hierarchical modelling approach for cosmic shear power spectrum inference, jointly sampling from the posterior distribution of the cosmic shear field and its (tomographic) power spectra. Inference of the shear power spectrum is a powerful intermediate product for a cosmic shear analysis, since it requires very few model assumptions and can be used to perform inference on a wide range of cosmological models a posteriori without loss of information. We show that joint posterior for the shear map and power spectrum can be sampled effectively by Gibbs sampling, iteratively drawing samples from the map and power spectrum, each conditional on the other. This approach neatly circumvents difficulties associated with complicated survey geometry and masks that plague frequentist power spectrum estimators, since the power spectrum inference provides prior information about the field in masked regions at every sampling step. We demonstrate this approach for inference of tomographic shear E-mode, B-mode and EB-cross power spectra from a simulated galaxy shear catalogue with a number of important features; galaxies distributed on the sky and in redshift with photometric redshift uncertainties, realistic random ellipticity noise for every galaxy and a complicated survey mask. The obtained posterior distributions for the tomographic power spectrum coefficients recover the underlying simulated power spectra for both E- and B-modes.

  20. Children's and Adults' Judgments of the Certainty of Deductive Inferences, Inductive Inferences, and Guesses

    ERIC Educational Resources Information Center

    Pillow, Bradford H.; Pearson, RaeAnne M.; Hecht, Mary; Bremer, Amanda

    2010-01-01

    Children and adults rated their own certainty following inductive inferences, deductive inferences, and guesses. Beginning in kindergarten, participants rated deductions as more certain than weak inductions or guesses. Deductions were rated as more certain than strong inductions beginning in Grade 3, and fourth-grade children and adults…

  1. Children's and Adults' Judgments of the Certainty of Deductive Inferences, Inductive Inferences, and Guesses

    ERIC Educational Resources Information Center

    Pillow, Bradford H.; Pearson, RaeAnne M.; Hecht, Mary; Bremer, Amanda

    2010-01-01

    Children and adults rated their own certainty following inductive inferences, deductive inferences, and guesses. Beginning in kindergarten, participants rated deductions as more certain than weak inductions or guesses. Deductions were rated as more certain than strong inductions beginning in Grade 3, and fourth-grade children and adults…

  2. Using Alien Coins to Test Whether Simple Inference Is Bayesian

    ERIC Educational Resources Information Center

    Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.

    2016-01-01

    Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

  3. Using Alien Coins to Test Whether Simple Inference Is Bayesian

    ERIC Educational Resources Information Center

    Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.

    2016-01-01

    Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

  4. Genetics Home Reference: lysosomal acid lipase deficiency

    MedlinePlus

    ... Home Health Conditions lysosomal acid lipase deficiency lysosomal acid lipase deficiency Printable PDF Open All Close All ... to view the expand/collapse boxes. Description Lysosomal acid lipase deficiency is an inherited condition characterized by ...

  5. Genetics Home Reference: protein C deficiency

    MedlinePlus

    ... Management Genetic Testing (1 link) Genetic Testing Registry: Thrombophilia, hereditary, due to protein C deficiency, autosomal dominant ... my area? Other Names for This Condition hereditary thrombophilia due to protein C deficiency PROC deficiency Related ...

  6. Genetics Home Reference: glucose phosphate isomerase deficiency

    MedlinePlus

    ... Me Understand Genetics Home Health Conditions GPI deficiency glucose phosphate isomerase deficiency Enable Javascript to view the ... boxes. Download PDF Open All Close All Description Glucose phosphate isomerase (GPI) deficiency is an inherited disorder ...

  7. Genetics Home Reference: familial HDL deficiency

    MedlinePlus

    ... Twitter Home Health Conditions familial HDL deficiency familial HDL deficiency Printable PDF Open All Close All Enable ... to view the expand/collapse boxes. Description Familial HDL deficiency is a condition characterized by low levels ...

  8. Genetics Home Reference: isolated growth hormone deficiency

    MedlinePlus

    ... Genetic Testing (4 links) Genetic Testing Registry: Ateleiotic dwarfism Genetic Testing Registry: Autosomal dominant isolated somatotropin deficiency ... in my area? Other Names for This Condition dwarfism, growth hormone deficiency dwarfism, pituitary growth hormone deficiency ...

  9. A Learning Algorithm for Multimodal Grammar Inference.

    PubMed

    D'Ulizia, A; Ferri, F; Grifoni, P

    2011-12-01

    The high costs of development and maintenance of multimodal grammars in integrating and understanding input in multimodal interfaces lead to the investigation of novel algorithmic solutions in automating grammar generation and in updating processes. Many algorithms for context-free grammar inference have been developed in the natural language processing literature. An extension of these algorithms toward the inference of multimodal grammars is necessary for multimodal input processing. In this paper, we propose a novel grammar inference mechanism that allows us to learn a multimodal grammar from its positive samples of multimodal sentences. The algorithm first generates the multimodal grammar that is able to parse the positive samples of sentences and, afterward, makes use of two learning operators and the minimum description length metrics in improving the grammar description and in avoiding the over-generalization problem. The experimental results highlight the acceptable performances of the algorithm proposed in this paper since it has a very high probability of parsing valid sentences.

  10. Single board system for fuzzy inference

    NASA Technical Reports Server (NTRS)

    Symon, James R.; Watanabe, Hiroyuki

    1991-01-01

    The very large scale integration (VLSI) implementation of a fuzzy logic inference mechanism allows the use of rule-based control and decision making in demanding real-time applications. Researchers designed a full custom VLSI inference engine. The chip was fabricated using CMOS technology. The chip consists of 688,000 transistors of which 476,000 are used for RAM memory. The fuzzy logic inference engine board system incorporates the custom designed integrated circuit into a standard VMEbus environment. The Fuzzy Logic system uses Transistor-Transistor Logic (TTL) parts to provide the interface between the Fuzzy chip and a standard, double height VMEbus backplane, allowing the chip to perform application process control through the VMEbus host. High level C language functions hide details of the hardware system interface from the applications level programmer. The first version of the board was installed on a robot at Oak Ridge National Laboratory in January of 1990.

  11. Automatic transformations in the inference process

    SciTech Connect

    Veroff, R. L.

    1980-07-01

    A technique for incorporating automatic transformations into processes such as the application of inference rules, subsumption, and demodulation provides a mechanism for improving search strategies for theorem proving problems arising from the field of program verification. The incorporation of automatic transformations into the inference process can alter the search space for a given problem, and is particularly useful for problems having broad rather than deep proofs. The technique can also be used to permit the generation of inferences that might otherwise be blocked and to build some commutativity or associativity into the unification process. Appropriate choice of transformations, and new literal clashing and unification algorithms for applying them, showed significant improvement on several real problems according to several distinct criteria. 22 references, 1 figure.

  12. Scalar inferences in Autism Spectrum Disorders.

    PubMed

    Chevallier, Coralie; Wilson, Deirdre; Happé, Francesca; Noveck, Ira

    2010-09-01

    On being told "John or Mary will come", one might infer that not both of them will come. Yet the semantics of "or" is compatible with a situation where both John and Mary come. Inferences of this type, which enrich the semantics of "or" from an 'inclusive' to an 'exclusive' interpretation, have been extensively studied in linguistic pragmatics. However, the phenomenon has not been much explored in Autism Spectrum Disorders (ASDs), where pragmatic deficits are commonly reported. Here, we present an experiment investigating these inferences. We predicted that, as a result of the reported pragmatic deficits, participants with ASD would produce fewer inferential enrichments of "or" than matched controls. However, contrary to expectations, but in line with recent findings by Pijnacker et al. (Journal of Autism and Developmental Disorders, 39, 607-618, 2009), performances did not differ across groups. This unexpected finding is discussed in light of the literature on pragmatic abilities in autism.

  13. Identification and Inference for Econometric Models

    NASA Astrophysics Data System (ADS)

    Andrews, Donald W. K.; Stock, James H.

    2005-07-01

    This volume contains the papers presented in honor of the lifelong achievements of Thomas J. Rothenberg on the occasion of his retirement. The authors of the chapters include many of the leading econometricians of our day, and the chapters address topics of current research significance in econometric theory. The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference. Several of the chapters provide overviews and treatments of basic conceptual issues, while others advance our understanding of the properties of existing econometric procedures and/or propose new ones. Specific topics include identification in nonlinear models, inference with weak instruments, tests for nonstationary in time series and panel data, generalized empirical likelihood estimation, and the bootstrap.

  14. Causal Inference in Latent Class Analysis

    PubMed Central

    Lanza, Stephanie T.; Coffman, Donna L.; Xu, Shu

    2014-01-01

    The integration of modern methods for causal inference with latent class analysis (LCA) allows social, behavioral, and health researchers to address important questions about the determinants of latent class membership. In the present article, two propensity score techniques, matching and inverse propensity weighting, are demonstrated for conducting causal inference in LCA. The different causal questions that can be addressed with these techniques are carefully delineated. An empirical analysis based on data from the National Longitudinal Survey of Youth 1979 is presented, where college enrollment is examined as the exposure (i.e., treatment) variable and its causal effect on adult substance use latent class membership is estimated. A step-by-step procedure for conducting causal inference in LCA, including multiple imputation of missing data on the confounders, exposure variable, and multivariate outcome, is included. Sample syntax for carrying out the analysis using SAS and R is given in an appendix. PMID:25419097

  15. Network inference in the nonequilibrium steady state

    NASA Astrophysics Data System (ADS)

    Dettmer, Simon L.; Nguyen, H. Chau; Berg, Johannes

    2016-11-01

    Nonequilibrium systems lack an explicit characterization of their steady state like the Boltzmann distribution for equilibrium systems. This has drastic consequences for the inference of the parameters of a model when its dynamics lacks detailed balance. Such nonequilibrium systems occur naturally in applications like neural networks and gene regulatory networks. Here, we focus on the paradigmatic asymmetric Ising model and show that we can learn its parameters from independent samples of the nonequilibrium steady state. We present both an exact inference algorithm and a computationally more efficient, approximate algorithm for weak interactions based on a systematic expansion around mean-field theory. Obtaining expressions for magnetizations and two- and three-point spin correlations, we establish that these observables are sufficient to infer the model parameters. Further, we discuss the symmetries characterizing the different orders of the expansion around the mean field and show how different types of dynamics can be distinguished on the basis of samples from the nonequilibrium steady state.

  16. Spontaneous inferences, implicit impressions, and implicit theories.

    PubMed

    Uleman, James S; Adil Saribay, S; Gonzalez, Celia M

    2008-01-01

    People make social inferences without intentions, awareness, or effort, i.e., spontaneously. We review recent findings on spontaneous social inferences (especially traits, goals, and causes) and closely related phenomena. We then describe current thinking on some of the most relevant processes, implicit knowledge, and theories. These include automatic and controlled processes and their interplay; embodied cognition, including mimicry; and associative versus rule-based processes. Implicit knowledge includes adult folk theories, conditions of personhood, self-knowledge to simulate others, and cultural and social class differences. Implicit theories concern Bayesian networks, recent attribution research, and questions about the utility of the disposition-situation dichotomy. Developmental research provides new insights. Spontaneous social inferences include a growing array of phenomena, but they have been insufficiently linked to other phenomena and theories. We hope the links suggested in this review begin to remedy this.

  17. Quality of computationally inferred gene ontology annotations.

    PubMed

    Skunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-05-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon-an important outcome given that >98% of all annotations are inferred without direct curation.

  18. Prevention of iron deficiency.

    PubMed

    Hallberg, L

    1994-12-01

    This chapter discusses different methods to prevent iron deficiency--to reduce iron losses (e.g. reducing menstrual iron losses by using a contraceptive pill or combating of hookworm infestation) or to increase iron absorption. Iron absorption can be increased (1) by modifying the composition of meals--increasing the content of dietary factors enhancing iron absorption (e.g. meat and ascorbic acid) or reducing the content of factors inhibiting iron absorption such as phytate and iron-binding phenolic compounds, (2) by increasing the iron content of the diet by fortification with iron, or by (3) supplementation with iron tablets. Several factors to consider in the choice of strategy are discussed such as the importance of the bioavailability of the diet for the efficacy of iron fortification, the choice of vehicle for iron fortification that is compatible with the iron compound used, the feasibility to increase the bioavailability of the dietary iron by modification of the composition of the diet and the short time available in pregnancy to ensure a sufficient supply of the extra iron needed limiting the effective measures available to supplementation with iron tablets.

  19. Iron deficiency and thrombocytosis.

    PubMed

    Holbro, A; Volken, T; Buser, A; Sigle, J P; Halter, J P; Passweg, J R; Tichelli, A; Infanti, L

    2017-01-01

    According to many textbooks, iron deficiency (ID) is associated with reactive thrombocytosis. In this study, we aimed to investigate the correlation between serum ferritin levels and platelet counts in a large cohort of healthy blood donors. We included all whole blood and apheresis donors aged 18 years or older with at least one ferritin measurement and one platelet count performed at the same visit between 1996 and 2014. A total of 130 345 blood counts and ferritin measurements obtained from 22 046 healthy donors were analysed. Overall, no correlation between serum ferritin and platelet count was observed (r = -0.03, ρ = 0.04 for males, and r = 0.01, ρ = -0.02 for females, respectively). Associations remained clinically negligible after adjusting for age, time since previous blood donation, number of donations and restricting the analysis to ferritin deciles. In this large, retrospective single-centre study, correlations between low ferritin and platelet count in a large and homogeneous cohort of healthy donors were negligible. Further studies in patients with more severe anaemia and patients with inflammation are warranted.

  20. Lymphopoiesis in Protein Deficiency

    PubMed Central

    Bhuyan, U. N.; Ramalingaswami, V.

    1974-01-01

    In view of the depressed immunity in protein malnutrition, an assessment of the lymphoproliferative activity of the constantly stimulated mesenteric lymph node of the guinea pig was undertaken. A significant reduction of this activity was observed in protein deficiency. a) The germinal centers were reduced in number and size; new formation in the medulla was rarely seen. Lymphoid cells showed lowering of mitotic index and mitotic rate and prolongation of mitotic duration and turnover time. Nuclear labeling with 3H-thymidine was focal and localized to the peripheral zone. b) Mitotic activity and nuclear labeling were less pronounced in the outer cortex and medulla and least in the paracortical area. Specific uptake of 3H-thymidine paralleled the low labeling index. c) No appreciable reduction in the number of plasma cells in the medulla was observed. Serum γ-globulin levels were not significantly altered, but albumin levels were consistently reduced. This was suggestive of preferential preservation of plasma cell activity in the malnourished host. d) There were significant lymphopenia and neutropenia with relative increase of neutrophils in the peripheral blood. This might indicate more severe involvement of lymphopoiesis than myelopoiesis in protein malnutrition. ImagesFig 5Fig 6Fig 7Fig 8Fig 1Fig 2Fig 3Fig 4 PMID:4132687

  1. Iron Deficiency Anemia in Pregnancy.

    PubMed

    Breymann, Christian

    2015-10-01

    Anemia is a common problem in obstetrics and perinatal care. Any hemoglobin below 10.5 g/dL can be regarded as true anemia regardless of gestational age. Reasons for anemia in pregnancy are mainly nutritional deficiencies, parasitic and bacterial diseases, and inborn red blood cell disorders such as thalassemias. The main cause of anemia in obstetrics is iron deficiency, which has a worldwide prevalence between estimated 20%-80% and consists of a primarily female population. Stages of iron deficiency are depletion of iron stores, iron-deficient erythropoiesis without anemia, and iron deficiency anemia, the most pronounced form of iron deficiency. Pregnancy anemia can be aggravated by various conditions such as uterine or placental bleedings, gastrointestinal bleedings, and peripartum blood loss. In addition to the general consequences of anemia, there are specific risks during pregnancy for the mother and the fetus such as intrauterine growth retardation, prematurity, feto-placental miss ratio, and higher risk for peripartum blood transfusion. Besides the importance of prophylaxis of iron deficiency, the main therapy options for the treatment of pregnancy anemia are oral iron and intravenous iron preparations.

  2. Betaine Deficiency in Maize 1

    PubMed Central

    Lerma, Claudia; Rich, Patrick J.; Ju, Grace C.; Yang, Wen-Ju; Hanson, Andrew D.; Rhodes, David

    1991-01-01

    Maize (Zea mays L.) is a betaine-accumulating species, but certain maize genotypes lack betaine almost completely; a single recessive gene has been implicated as the cause of this deficiency (D Rhodes, PJ Rich [1988] Plant Physiol 88: 102-108). This study was undertaken to determine whether betaine deficiency in diverse maize germplasm is conditioned by the same genetic locus, and to define the biochemical lesion(s) involved. Complementation tests indicated that all 13 deficient genotypes tested shared a common locus. One maize population (P77) was found to be segregating for betaine deficiency, and true breeding individuals were used to produce related lines with and without betaine. Leaf tissue of both betaine-positive and betaine-deficient lines readily converted supplied betaine aldehyde to betaine, but only the betaine-containing line was able to oxidize supplied choline to betaine. This locates the lesion in betaine-deficient plants at the choline → betaine aldehyde step of betaine synthesis. Consistent with this location, betaine-deficient plants were shown to have no detectable endogenous pool of betaine aldehyde. PMID:16668098

  3. Declarative Memory, Awareness, and Transitive Inference

    PubMed Central

    Smith, Christine; Squire, Larry R.

    2006-01-01

    A characteristic usually attributed to declarative memory is that what is learned is accessible to awareness. Recently, the relationship between awareness and declarative (hippocampus-dependent) memory has been questioned on the basis of findings from transitive inference tasks. In transitive inference, participants are first trained on overlapping pairs of items (e.g., A+B−, B+C−, C+D−, and D+E−, where + and − indicate correct and incorrect choices). Later, participants who choose B over D when presented with the novel pair BD are said to demonstrate transitive inference. The ability to exhibit transitive inference is thought to depend on the fact that participants have represented the stimulus elements hierarchically (i.e., A>B>C>D>E). We found that performance on five-item and six-item transitive inference tasks was closely related to awareness of the hierarchical relationship among the elements of the training pairs. Participants who were aware of the hierarchy performed near 100% correct on all tests of transitivity, but participants who were unaware of the hierarchy performed poorly (e.g., on transitive pair BD in the five-item problem; on transitive pairs BD, BE, and CE in the six-item problem). When the five-item task was administered to memory-impaired patients with damage thought to be limited to the hippocampal region, the patients were impaired at learning the training pairs. All patients were unaware of the hierarchy and, like unaware controls, performed poorly on the BD pair. The findings indicate that awareness is critical for robust performance on tests of transitive inference and support the view that awareness of what is learned is a fundamental characteristic of declarative memory. PMID:16267221

  4. A formal model of interpersonal inference

    PubMed Central

    Moutoussis, Michael; Trujillo-Barreto, Nelson J.; El-Deredy, Wael; Dolan, Raymond J.; Friston, Karl J.

    2014-01-01

    Introduction: We propose that active Bayesian inference—a general framework for decision-making—can equally be applied to interpersonal exchanges. Social cognition, however, entails special challenges. We address these challenges through a novel formulation of a formal model and demonstrate its psychological significance. Method: We review relevant literature, especially with regards to interpersonal representations, formulate a mathematical model and present a simulation study. The model accommodates normative models from utility theory and places them within the broader setting of Bayesian inference. Crucially, we endow people's prior beliefs, into which utilities are absorbed, with preferences of self and others. The simulation illustrates the model's dynamics and furnishes elementary predictions of the theory. Results: (1) Because beliefs about self and others inform both the desirability and plausibility of outcomes, in this framework interpersonal representations become beliefs that have to be actively inferred. This inference, akin to “mentalizing” in the psychological literature, is based upon the outcomes of interpersonal exchanges. (2) We show how some well-known social-psychological phenomena (e.g., self-serving biases) can be explained in terms of active interpersonal inference. (3) Mentalizing naturally entails Bayesian updating of how people value social outcomes. Crucially this includes inference about one's own qualities and preferences. Conclusion: We inaugurate a Bayes optimal framework for modeling intersubject variability in mentalizing during interpersonal exchanges. Here, interpersonal representations are endowed with explicit functional and affective properties. We suggest the active inference framework lends itself to the study of psychiatric conditions where mentalizing is distorted. PMID:24723872

  5. Iatrogenic limbal stem cell deficiency.

    PubMed Central

    Holland, E J; Schwartz, G S

    1997-01-01

    PURPOSE: To describe a group of patients with limbal stem cell (SC) deficiency without prior diagnosis of a specific disease entity known to be causative of SC deficiency. METHODS: We performed a retrospective review of the records of all patients with ocular surface disease presenting to the University of Minnesota between 1987 and 1996. Patients were categorized according to etiology of limbal deficiency. Patients who did not have a specific diagnosis previously described as being causative for limbal deficiency were analyzed. Risk factors, clinical findings and sequelae were evaluated. RESULTS: Eight eyes of six patients with stem cell deficiency not secondary to a known diagnosis were described. All eyes had prior ocular surgery involving the corneoscleral limbus. Six eyes had been on chronic topical medications and all eyes had concurrent external disease such as pterygium, keratoconjunctivitis sicca, rosacea or herpes simplex virus keratitis. All eyes had superior quadrants affected corresponding to areas of prior limbal surgery. Sequelae of disease included corneal scarring and neo-vascularization, and five eyes had with visual acuity of 20/200 or worse. CONCLUSIONS: Because the epitheliopathy started peripherally and extended centrally in all patients, we feel it represents a stem cell deficiency. The fact that all patients were affected superiorly, at sites of a prior limbal surgical incision, points to surgical trauma to the SC as the likely major etiologic factor for the deficiency. The surgical trauma to the limbal SC probably made these cells more susceptible to damage from other external disease influences and toxicity from chronic topical medications. Because the stem cell deficiency is secondary to prior ocular surgery and chronic topical medications, we propose the term "iatrogenic limbal stem cell deficiency". Images FIGURE 1 FIGURE 2A FIGURE 2B FIGURE 3A FIGURE 3B PMID:9440165

  6. Matrix Factorization for Transcriptional Regulatory Network Inference

    PubMed Central

    Ochs, Michael F.; Fertig, Elana J.

    2013-01-01

    Inference of Transcriptional Regulatory Networks (TRNs) provides insight into the mechanisms driving biological systems, especially mammalian development and disease. Many techniques have been developed for TRN estimation from indirect biochemical measurements. Although successful when initially tested in model organisms, these regulatory models often fail when applied to data from multicellular organisms where multiple regulation and gene reuse increase dramatically. Non-negative matrix factorization techniques were initially introduced to find non-orthogonal patterns in data, making them ideal techniques for inference in cases of multiple regulation. We review these techniques and their application to TRN analysis. PMID:25364782

  7. Gene-network inference by message passing

    NASA Astrophysics Data System (ADS)

    Braunstein, A.; Pagnani, A.; Weigt, M.; Zecchina, R.

    2008-01-01

    The inference of gene-regulatory processes from gene-expression data belongs to the major challenges of computational systems biology. Here we address the problem from a statistical-physics perspective and develop a message-passing algorithm which is able to infer sparse, directed and combinatorial regulatory mechanisms. Using the replica technique, the algorithmic performance can be characterized analytically for artificially generated data. The algorithm is applied to genome-wide expression data of baker's yeast under various environmental conditions. We find clear cases of combinatorial control, and enrichment in common functional annotations of regulated genes and their regulators.

  8. Inference System Integration Via Logic Morphisms

    NASA Technical Reports Server (NTRS)

    Bjorner, Nikolaj S.; Espinosa, David

    2000-01-01

    This is a final report on the accomplishments during the period of the NASA grant. The work on inference servers accomplished the integration of the SLANG logic (Specware's default specification logic) with a number of inference servers in order to make their complementary strengths available. These inverence servers are (1) SNARK. (2) Gandalf, Setheo, and Spass, (3) the Prototype Verification System (PVS) from SRI. (4) HOL98. We designed and implemented MetaSlang, an ML-like language, which we are using to specify and implement all our logic morphisms.

  9. Organophosphates and monocyte esterase deficiency.

    PubMed Central

    McClean, E; Mackey, H; Markey, G M; Morris, T C

    1995-01-01

    AIMS--To examine the possibility that monocyte esterase deficiency (MED) could be caused by exposure to organophosphates. METHODS--Pseudocholinesterase, paraoxonase and arylesterase activities were measured in the serum and acetylcholinesterase activity was measured in the red cells of a group of monocyte esterase deficient subjects and compared with the enzyme activities of a control group of monocyte esterase positive subjects. RESULTS--No significant difference was found between the enzyme activities of the monocyte esterase deficient group and the control group for any of the esterases investigated. CONCLUSION--Current or recent exposure to organophosphorus is not the cause of MED. PMID:7560207

  10. Genetics Home Reference: hereditary antithrombin deficiency

    MedlinePlus

    ... Merck Manual Home Edition for Patients and Caregivers: Thrombophilia National Blood Clot Alliance: Antithrombin Deficiency Orphanet: Hereditary thrombophilia due to congenital antithrombin deficiency Patient Support and ...

  11. Binding of inferred germline precursors of broadly neutralizing HIV-1 antibodies to native-like envelope trimers.

    PubMed

    Sliepen, Kwinten; Medina-Ramírez, Max; Yasmeen, Anila; Moore, John P; Klasse, Per Johan; Sanders, Rogier W

    2015-12-01

    HIV-1 envelope glycoproteins (Env) and Env-based immunogens usually do not interact efficiently with the inferred germline precursors of known broadly neutralizing antibodies (bNAbs). This deficiency may be one reason why Env and Env-based immunogens are not efficient at inducing bNAbs. We evaluated the binding of 15 inferred germline precursors of bNAbs directed to different epitope clusters to three soluble native-like SOSIP.664 Env trimers. We found that native-like SOSIP.664 trimers bind to some inferred germline precursors of bNAbs, particularly ones involving the V1/V2 loops at the apex of the trimer. The data imply that native-like SOSIP.664 trimers will be an appropriate platform for structure-guided design improvements intended to create immunogens able to target the germline precursors of bNAbs.

  12. [Niacin deficiency and cutaneous immunity].

    PubMed

    Ikenouchi-Sugita, Atsuko; Sugita, Kazunari

    2015-01-01

    Niacin, also known as vitamin B3, is required for the synthesis of coenzymes, nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP). Niacin binds with G protein-coupled receptor (GPR) 109A on cutaneous Langerhans cells and causes vasodilation with flushing in head and neck area. Niacin deficiency due to excessive alcohol consumption, certain drugs or inadequate uptake in diet causes pellagra, a photosensitivity dermatitis. Recently several studies have revealed the mechanism of photosensitivity in niacin deficiency, which may pave a way for new therapeutic approaches. The expression level of prostaglandin E synthase (PTGES) is up-regulated in the skin of both pellagra patients and niacin deficient pellagra mouse models. In addition, pellagra is mediated through prostaglandin E₂-EP4 (PGE₂-EP4) signaling via reactive oxygen species (ROS) production in keratinocytes. In this article, we have reviewed the role of niacin in immunity and the mechanism of niacin deficiency-induced photosensitivity.

  13. Genetics Home Reference: tetrahydrobiopterin deficiency

    MedlinePlus

    ... Epub 2007 Dec 3. Citation on PubMed Liu TT, Chiang SH, Wu SJ, Hsiao KJ. Tetrahydrobiopterin-deficient ... Shen M, Zhou Z, Zhang Z, Shen S, Liu TT, Hsiao KJ. Long-term outcome and neuroradiological findings ...

  14. Reconstructive surgery for fibular deficiency.

    PubMed

    Shatilov, O E; Rozkov, A V; Cheminova, T V

    1991-08-01

    Three types of fibular deficiency are described which determine the nature of the surgery and prosthesis required. The surgical management of 50 patients who had a total of 103 operations is described.

  15. Spurious correlations and inference in landscape genetics

    Treesearch

    Samuel A. Cushman; Erin L. Landguth

    2010-01-01

    Reliable interpretation of landscape genetic analyses depends on statistical methods that have high power to identify the correct process driving gene flow while rejecting incorrect alternative hypotheses. Little is known about statistical power and inference in individual-based landscape genetics. Our objective was to evaluate the power of causalmodelling with partial...

  16. Directions of strong winds on Mars inferred

    NASA Technical Reports Server (NTRS)

    Howard, A. D.

    1972-01-01

    Asymmetrical crater shadings and diffuse light and dark streaks visible on the photography returned by the 1969 Mars flyby of Mariners 6 and 7 are probably eolian in origin. Wind directions inferred from mapping of these features parallel motions of observed global dust storms or relate to expected patterns of topographic funneling of winds.

  17. Making statistical inferences about software reliability

    NASA Technical Reports Server (NTRS)

    Miller, Douglas R.

    1986-01-01

    Failure times of software undergoing random debugging can be modeled as order statistics of independent but nonidentically distributed exponential random variables. Using this model inferences can be made about current reliability and, if debugging continues, future reliability. This model also shows the difficulty inherent in statistical verification of very highly reliable software such as that used by digital avionics in commercial aircraft.

  18. Decision generation tools and Bayesian inference

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Wang, Wenjian; Forrester, Thomas; Kostrzewski, Andrew; Veeris, Christian; Nielsen, Thomas

    2014-05-01

    Digital Decision Generation (DDG) tools are important software sub-systems of Command and Control (C2) systems and technologies. In this paper, we present a special type of DDGs based on Bayesian Inference, related to adverse (hostile) networks, including such important applications as terrorism-related networks and organized crime ones.

  19. What Children Infer from Social Categories

    ERIC Educational Resources Information Center

    Diesendruck, Gil; Eldror, Ehud

    2011-01-01

    Children hold the belief that social categories have essences. We investigated what kinds of properties children feel licensed to infer about a person based on social category membership. Seventy-two 4-6-year-olds were introduced to novel social categories defined as having one internal--psychological or biological--and one external--behavioral or…

  20. Campbell's and Rubin's Perspectives on Causal Inference

    ERIC Educational Resources Information Center

    West, Stephen G.; Thoemmes, Felix

    2010-01-01

    Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

  1. Causal Inferences in the Campbellian Validity System

    ERIC Educational Resources Information Center

    Lund, Thorleif

    2010-01-01

    The purpose of the present paper is to critically examine causal inferences and internal validity as defined by Campbell and co-workers. Several arguments are given against their counterfactual effect definition, and this effect definition should be considered inadequate for causal research in general. Moreover, their defined independence between…

  2. Effects of Media on Children's Inference Justifications.

    ERIC Educational Resources Information Center

    Rodriguez, Stephen R.; And Others

    This study examined whether the sources of information children use to substantiate story-based inferences are influenced by the medium of delivery. The 48 third grade students who acted as subjects were stratified by sex and randomly assigned to one of two media conditions; i.e., each child was presented an African folktale either (1) as a…

  3. Variations on Bayesian Prediction and Inference

    DTIC Science & Technology

    2016-05-09

    SECURITY CLASSIFICATION OF: A Bayesian approach, based on updating prior information in light of new observations, via Bayes’s formula, has both nice...Prediction and Inference Report Title A Bayesian approach, based on updating prior information in light of new observations, via Bayes’s formula, has both

  4. HIERARCHICAL PROBABILISTIC INFERENCE OF COSMIC SHEAR

    SciTech Connect

    Schneider, Michael D.; Dawson, William A.; Hogg, David W.; Marshall, Philip J.; Bard, Deborah J.; Meyers, Joshua; Lang, Dustin

    2015-07-01

    Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.

  5. Unconscious relational inference recruits the hippocampus.

    PubMed

    Reber, Thomas P; Luechinger, Roger; Boesiger, Peter; Henke, Katharina

    2012-05-02

    Relational inference denotes the capacity to encode, flexibly retrieve, and integrate multiple memories to combine past experiences to update knowledge and improve decision-making in new situations. Although relational inference is thought to depend on the hippocampus and consciousness, we now show in young, healthy men that it may occur outside consciousness but still recruits the hippocampus. In temporally distinct and unique subliminal episodes, we presented word pairs that either overlapped ("winter-red", "red-computer") or not. Effects of unconscious relational inference emerged in reaction times recorded during unconscious encoding and in the outcome of decisions made 1 min later at test, when participants judged the semantic relatedness of two supraliminal words. These words were either episodically related through a common word ("winter-computer" related through "red") or unrelated. Hippocampal activity increased during the unconscious encoding of overlapping versus nonoverlapping word pairs and during the unconscious retrieval of episodically related versus unrelated words. Furthermore, hippocampal activity during unconscious encoding predicted the outcome of decisions made at test. Hence, unconscious inference may influence decision-making in new situations.

  6. Making statistical inferences about software reliability

    NASA Technical Reports Server (NTRS)

    Miller, Douglas R.

    1988-01-01

    Failure times of software undergoing random debugging can be modelled as order statistics of independent but nonidentically distributed exponential random variables. Using this model inferences can be made about current reliability and, if debugging continues, future reliability. This model also shows the difficulty inherent in statistical verification of very highly reliable software such as that used by digital avionics in commercial aircraft.

  7. John Updike and Norman Mailer: Sport Inferences.

    ERIC Educational Resources Information Center

    Upshaw, Kathryn Jane

    The phenomenon of writer use of sport inferences in the literary genre of the novel is examined in the works of Updike and Mailer. Novels of both authors were reviewed in order to study the pattern of usage in each novel. From these patterns, concepts which illustrated the sport philosophies of each author were used for general comparisons of the…

  8. Bayesian structural inference for hidden processes.

    PubMed

    Strelioff, Christopher C; Crutchfield, James P

    2014-04-01

    We introduce a Bayesian approach to discovering patterns in structurally complex processes. The proposed method of Bayesian structural inference (BSI) relies on a set of candidate unifilar hidden Markov model (uHMM) topologies for inference of process structure from a data series. We employ a recently developed exact enumeration of topological ε-machines. (A sequel then removes the topological restriction.) This subset of the uHMM topologies has the added benefit that inferred models are guaranteed to be ε-machines, irrespective of estimated transition probabilities. Properties of ε-machines and uHMMs allow for the derivation of analytic expressions for estimating transition probabilities, inferring start states, and comparing the posterior probability of candidate model topologies, despite process internal structure being only indirectly present in data. We demonstrate BSI's effectiveness in estimating a process's randomness, as reflected by the Shannon entropy rate, and its structure, as quantified by the statistical complexity. We also compare using the posterior distribution over candidate models and the single, maximum a posteriori model for point estimation and show that the former more accurately reflects uncertainty in estimated values. We apply BSI to in-class examples of finite- and infinite-order Markov processes, as well to an out-of-class, infinite-state hidden process.

  9. Linguistic Markers of Inference Generation While Reading

    ERIC Educational Resources Information Center

    Clinton, Virginia; Carlson, Sarah E.; Seipel, Ben

    2016-01-01

    Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students (N = 218) reading narrative…

  10. Inference and the Introductory Statistics Course

    ERIC Educational Resources Information Center

    Pfannkuch, Maxine; Regan, Matt; Wild, Chris; Budgett, Stephanie; Forbes, Sharleen; Harraway, John; Parsonage, Ross

    2011-01-01

    This article sets out some of the rationale and arguments for making major changes to the teaching and learning of statistical inference in introductory courses at our universities by changing from a norm-based, mathematical approach to more conceptually accessible computer-based approaches. The core problem of the inferential argument with its…

  11. Statistical Inference and Stochastic Simulation for Microrheology

    DTIC Science & Technology

    2013-12-18

    inference and stochastic simulation to analyze time series data from passive microrheology experiments of biofluids, especially mucus . During the time...analyze time series data from passive microrheology experiments of biofluids, especially mucus . During the time of the grant, progress was made on both

  12. Double jeopardy in inferring cognitive processes.

    PubMed

    Fific, Mario

    2014-01-01

    Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes from the construction of inadequate research designs possessing a low diagnostic accuracy of cognitive processes. For that reason we introduced the systems factorial technology (SFT), which has primarily been designed to make inferences about underlying processing order (serial, parallel, coactive), stopping rule (terminating, exhaustive), and process dependency. SFT proposes that the minimal research design complexity to learn about n number of cognitive processes should be equal to 2 (n) . In addition, SFT proposes that (a) each cognitive process should be controlled by a separate experimental factor, and (b) The saliency levels of all factors should be combined in a full factorial design. In the current study, the author cross combined the levels of jeopardies in a 2 × 2 analysis, leading to four different analysis conditions. The results indicate a decline in the diagnostic accuracy of inferences made about cognitive processes due to the presence of each jeopardy in isolation and when combined. The results warrant the development of more individual subject analyses and the utilization of full-factorial (SFT) experimental designs.

  13. Reliability vs. Diagnosticity in Hierarchical Inference.

    DTIC Science & Technology

    1981-06-01

    of cascaded inference in jurisprudence: methodological considerations (Report #80-01). Houston: Rice University, Department of Psychology , Research Report...Report #79-04). Houston: Rice University, Deparlment of Psychology , Research Report Series, 1979. p f I! I, ’ I: CONTRACT DISTRIBUTION LIST (Unclassified

  14. Making valid causal inferences from observational data.

    PubMed

    Martin, Wayne

    2014-02-15

    The ability to make strong causal inferences, based on data derived from outside of the laboratory, is largely restricted to data arising from well-designed randomized control trials. Nonetheless, a number of methods have been developed to improve our ability to make valid causal inferences from data arising from observational studies. In this paper, I review concepts of causation as a background to counterfactual causal ideas; the latter ideas are central to much of current causal theory. Confounding greatly constrains causal inferences in all observational studies. Confounding is a biased measure of effect that results when one or more variables, that are both antecedent to the exposure and associated with the outcome, are differentially distributed between the exposed and non-exposed groups. Historically, the most common approach to control confounding has been multivariable modeling; however, the limitations of this approach are discussed. My suggestions for improving causal inferences include asking better questions (relates to counterfactual ideas and "thought" trials); improving study design through the use of forward projection; and using propensity scores to identify potential confounders and enhance exchangeability, prior to seeing the outcome data. If time-dependent confounders are present (as they are in many longitudinal studies), more-advanced methods such as marginal structural models need to be implemented. Tutorials and examples are cited where possible. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Evolutionary inference via the Poisson Indel Process.

    PubMed

    Bouchard-Côté, Alexandre; Jordan, Michael I

    2013-01-22

    We address the problem of the joint statistical inference of phylogenetic trees and multiple sequence alignments from unaligned molecular sequences. This problem is generally formulated in terms of string-valued evolutionary processes along the branches of a phylogenetic tree. The classic evolutionary process, the TKF91 model [Thorne JL, Kishino H, Felsenstein J (1991) J Mol Evol 33(2):114-124] is a continuous-time Markov chain model composed of insertion, deletion, and substitution events. Unfortunately, this model gives rise to an intractable computational problem: The computation of the marginal likelihood under the TKF91 model is exponential in the number of taxa. In this work, we present a stochastic process, the Poisson Indel Process (PIP), in which the complexity of this computation is reduced to linear. The Poisson Indel Process is closely related to the TKF91 model, differing only in its treatment of insertions, but it has a global characterization as a Poisson process on the phylogeny. Standard results for Poisson processes allow key computations to be decoupled, which yields the favorable computational profile of inference under the PIP model. We present illustrative experiments in which Bayesian inference under the PIP model is compared with separate inference of phylogenies and alignments.

  16. Efficient Bayesian inference for ARFIMA processes

    NASA Astrophysics Data System (ADS)

    Graves, T.; Gramacy, R. B.; Franzke, C. L. E.; Watkins, N. W.

    2015-03-01

    Many geophysical quantities, like atmospheric temperature, water levels in rivers, and wind speeds, have shown evidence of long-range dependence (LRD). LRD means that these quantities experience non-trivial temporal memory, which potentially enhances their predictability, but also hampers the detection of externally forced trends. Thus, it is important to reliably identify whether or not a system exhibits LRD. In this paper we present a modern and systematic approach to the inference of LRD. Rather than Mandelbrot's fractional Gaussian noise, we use the more flexible Autoregressive Fractional Integrated Moving Average (ARFIMA) model which is widely used in time series analysis, and of increasing interest in climate science. Unlike most previous work on the inference of LRD, which is frequentist in nature, we provide a systematic treatment of Bayesian inference. In particular, we provide a new approximate likelihood for efficient parameter inference, and show how nuisance parameters (e.g. short memory effects) can be integrated over in order to focus on long memory parameters, and hypothesis testing more directly. We illustrate our new methodology on the Nile water level data, with favorable comparison to the standard estimators.

  17. GAMBIT: Global And Modular BSM Inference Tool

    NASA Astrophysics Data System (ADS)

    GAMBIT Collaboration; Athron, Peter; Balazs, Csaba; Bringmann, Torsten; Buckley, Andy; Chrzä Szcz, Marcin; Conrad, Jan; Cornell, Jonathan M.; Dal, Lars A.; Dickinson, Hugh; Edsjö, Joakim; Farmer, Ben; Jackson, Paul; Krislock, Abram; Kvellestad, Anders; Lundberg, Johan; McKay, James; Mahmoudi, Farvah; Martinez, Gregory D.; Putze, Antje Raklev, Are; Ripken, Joachim; Rogan, Christopher; Saavedra, Aldo; Savage, Christopher; Scott, Pat; Seo, Seon-Hee; Serra, Nicola; Weniger, Christoph; White, Martin; Wild, Sebastian

    2017-08-01

    GAMBIT (Global And Modular BSM Inference Tool) performs statistical global fits of generic physics models using a wide range of particle physics and astrophysics data. Modules provide native simulations of collider and astrophysics experiments, a flexible system for interfacing external codes (the backend system), a fully featured statistical and parameter scanning framework, and additional tools for implementing and using hierarchical models.

  18. "Comments on Slavin": Synthesizing Causal Inferences

    ERIC Educational Resources Information Center

    Briggs, Derek C.

    2008-01-01

    When causal inferences are to be synthesized across multiple studies, efforts to establish the magnitude of a causal effect should be balanced by an effort to evaluate the generalizability of the effect. The evaluation of generalizability depends on two factors that are given little attention in current syntheses: construct validity and external…

  19. The Role of Inference in Effective Communication.

    ERIC Educational Resources Information Center

    Brown, Paula M.; Dell, Gary S.

    A study was conducted to determine whether speakers vary the explicitness of a message in accordance with a listener's likelihood of inferring the intended information. Thirty-six hearing and hearing-impaired college students were asked to read a series of 20 paragraphs. After each one, they were to re-tell the story in their own words to the…

  20. Inverse Ising inference with correlated samples

    NASA Astrophysics Data System (ADS)

    Obermayer, Benedikt; Levine, Erel

    2014-12-01

    Correlations between two variables of a high-dimensional system can be indicative of an underlying interaction, but can also result from indirect effects. Inverse Ising inference is a method to distinguish one from the other. Essentially, the parameters of the least constrained statistical model are learned from the observed correlations such that direct interactions can be separated from indirect correlations. Among many other applications, this approach has been helpful for protein structure prediction, because residues which interact in the 3D structure often show correlated substitutions in a multiple sequence alignment. In this context, samples used for inference are not independent but share an evolutionary history on a phylogenetic tree. Here, we discuss the effects of correlations between samples on global inference. Such correlations could arise due to phylogeny but also via other slow dynamical processes. We present a simple analytical model to address the resulting inference biases, and develop an exact method accounting for background correlations in alignment data by combining phylogenetic modeling with an adaptive cluster expansion algorithm. We find that popular reweighting schemes are only marginally effective at removing phylogenetic bias, suggest a rescaling strategy that yields better results, and provide evidence that our conclusions carry over to the frequently used mean-field approach to the inverse Ising problem.

  1. Active interoceptive inference and the emotional brain

    PubMed Central

    Friston, Karl J.

    2016-01-01

    We review a recent shift in conceptions of interoception and its relationship to hierarchical inference in the brain. The notion of interoceptive inference means that bodily states are regulated by autonomic reflexes that are enslaved by descending predictions from deep generative models of our internal and external milieu. This re-conceptualization illuminates several issues in cognitive and clinical neuroscience with implications for experiences of selfhood and emotion. We first contextualize interoception in terms of active (Bayesian) inference in the brain, highlighting its enactivist (embodied) aspects. We then consider the key role of uncertainty or precision and how this might translate into neuromodulation. We next examine the implications for understanding the functional anatomy of the emotional brain, surveying recent observations on agranular cortex. Finally, we turn to theoretical issues, namely, the role of interoception in shaping a sense of embodied self and feelings. We will draw links between physiological homoeostasis and allostasis, early cybernetic ideas of predictive control and hierarchical generative models in predictive processing. The explanatory scope of interoceptive inference ranges from explanations for autism and depression, through to consciousness. We offer a brief survey of these exciting developments. This article is part of the themed issue ‘Interoception beyond homeostasis: affect, cognition and mental health’. PMID:28080966

  2. Statistical inference for serial dilution assay data.

    PubMed

    Lee, M L; Whitmore, G A

    1999-12-01

    Serial dilution assays are widely employed for estimating substance concentrations and minimum inhibitory concentrations. The Poisson-Bernoulli model for such assays is appropriate for count data but not for continuous measurements that are encountered in applications involving substance concentrations. This paper presents practical inference methods based on a log-normal model and illustrates these methods using a case application involving bacterial toxins.

  3. Metacognitive inferences from other people's memory performance.

    PubMed

    Smith, Robert W; Schwarz, Norbert

    2016-09-01

    Three studies show that people draw metacognitive inferences about events from how well others remember the event. Given that memory fades over time, detailed accounts of distant events suggest that the event must have been particularly memorable, for example, because it was extreme. Accordingly, participants inferred that a physical assault (Study 1) or a poor restaurant experience (Studies 2-3) were more extreme when they were well remembered one year rather than one week later. These inferences influence behavioral intentions. For example, participants recommended a more severe punishment for a well-remembered distant rather than recent assault (Study 1). These metacognitive inferences are eliminated when people attribute the reporter's good memory to an irrelevant cause (e.g., photographic memory), thus undermining the informational value of memory performance (Study 3). These studies illuminate how people use lay theories of memory to learn from others' memory performance about characteristics of the world. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  4. Campbell's and Rubin's Perspectives on Causal Inference

    ERIC Educational Resources Information Center

    West, Stephen G.; Thoemmes, Felix

    2010-01-01

    Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…

  5. Rates inferred from the space debris catalog

    SciTech Connect

    Canavan, G.H.

    1996-08-01

    Collision and fragmentation rates are inferred from the AFSPC space debris catalog and compare with estimates from other treatments. The collision rate is evaluated without approximation. The fragmentation rate requires additional empirical assessments. The number of fragments per collision is low compared to analytic and numerical treatments, is peaked low, and falls rapidly with altitude.

  6. Phylogeny and the inference of evolutionary trajectories

    PubMed Central

    Hancock, Lillian; Edwards, Erika J.

    2014-01-01

    Most important organismal adaptations are not actually single traits, but complex trait syndromes that are evolutionarily integrated into a single emergent phenotype. Two alternative photosynthetic pathways, C4 photosynthesis and crassulacean acid metabolism (CAM), are primary plant adaptations of this sort, each requiring multiple biochemical and anatomical modifications. Phylogenetic methods are a promising approach for teasing apart the order of character acquisition during the evolution of complex traits, and the phylogenetic placement of intermediate phenotypes as sister taxa to fully optimized syndromes has been taken as good evidence of an ‘ordered’ evolutionary trajectory. But how much power does the phylogenetic approach have to detect ordered evolution? This study simulated ordered and unordered character evolution across a diverse set of phylogenetic trees to understand how tree size, models of evolution, and sampling efforts influence the ability to detect an evolutionary trajectory. The simulations show that small trees (15 taxa) do not contain enough information to correctly infer either an ordered or unordered trajectory, although inference improves as tree size and sampling increases. However, even when working with a 1000-taxon tree, the possibility of inferring the incorrect evolutionary model (type I/type II error) remains. Caution is needed when interpreting the phylogenetic placement of intermediate phenotypes, especially in small lineages. Such phylogenetic patterns can provide a line of evidence for the existence of a particular evolutionary trajectory, but they should be coupled with other types of data to infer the stepwise evolution of a complex character trait. PMID:24755279

  7. Quasi-Experimental Designs for Causal Inference

    ERIC Educational Resources Information Center

    Kim, Yongnam; Steiner, Peter

    2016-01-01

    When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…

  8. Linguistic Markers of Inference Generation While Reading

    ERIC Educational Resources Information Center

    Clinton, Virginia; Carlson, Sarah E.; Seipel, Ben

    2016-01-01

    Words can be informative linguistic markers of psychological constructs. The purpose of this study is to examine associations between word use and the process of making meaningful connections to a text while reading (i.e., inference generation). To achieve this purpose, think-aloud data from third-fifth grade students (N = 218) reading narrative…

  9. Investigating Mathematics Teachers' Thoughts of Statistical Inference

    ERIC Educational Resources Information Center

    Yang, Kai-Lin

    2012-01-01

    Research on statistical cognition and application suggests that statistical inference concepts are commonly misunderstood by students and even misinterpreted by researchers. Although some research has been done on students' misunderstanding or misconceptions of confidence intervals (CIs), few studies explore either students' or mathematics…

  10. What Children Infer from Social Categories

    ERIC Educational Resources Information Center

    Diesendruck, Gil; Eldror, Ehud

    2011-01-01

    Children hold the belief that social categories have essences. We investigated what kinds of properties children feel licensed to infer about a person based on social category membership. Seventy-two 4-6-year-olds were introduced to novel social categories defined as having one internal--psychological or biological--and one external--behavioral or…

  11. Tactile length contraction as Bayesian inference

    PubMed Central

    Tong, Jonathan; Ngo, Vy

    2016-01-01

    To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. PMID:27121574

  12. Quasi-Experimental Designs for Causal Inference

    ERIC Educational Resources Information Center

    Kim, Yongnam; Steiner, Peter

    2016-01-01

    When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…

  13. Perceptual inferences about indeterminate arrangements of figures.

    PubMed

    Moreno-Ríos, Sergio; Rojas-Barahona, Cristian A; García-Madruga, Juan A

    2014-05-01

    Previous studies in spatial propositional reasoning showed that adults use a particular strategy for making representations and inferences from indeterminate descriptions (those consistent with different alternatives). They do not initially represent all the alternatives, but construct a unified mental representation that includes a kind of mental footnote. Only when the task requires access to alternatives is the unified representation re-inspected. The degree of generalisation of this proposal to other perceptual situations was evaluated in three experiments with children, adolescents and adults, using a perceptual inference task with diagrammatic premises that gave information about the location of one of three possible objects. Results obtained with this very quick perceptual task support the kind of representation proposed from propositional spatial reasoning studies. However, children and adults differed in accuracy, with the results gradually changing with age: indeterminacy leads adults to require extra time for understanding and inferring alternatives, whereas children commit errors. These results could help inform us of how people can make inferences from diagrammatic information and make wrong interpretations.

  14. Pediatric Pain, Predictive Inference, and Sensitivity Analysis.

    ERIC Educational Resources Information Center

    Weiss, Robert

    1994-01-01

    Coping style and effects of counseling intervention on pain tolerance was studied for 61 elementary school students through immersion of hands in cold water. Bayesian predictive inference tools are able to distinguish between subject characteristics and manipulable treatments. Sensitivity analysis strengthens the certainty of conclusions about…

  15. Causal Inferences with Group Based Trajectory Models

    ERIC Educational Resources Information Center

    Haviland, Amelia M.; Nagin, Daniel S.

    2005-01-01

    A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This paper lays out and applies a method for using observational longitudinal data to make more confident causal inferences about the…

  16. Causal Inferences in the Campbellian Validity System

    ERIC Educational Resources Information Center

    Lund, Thorleif

    2010-01-01

    The purpose of the present paper is to critically examine causal inferences and internal validity as defined by Campbell and co-workers. Several arguments are given against their counterfactual effect definition, and this effect definition should be considered inadequate for causal research in general. Moreover, their defined independence between…

  17. Double jeopardy in inferring cognitive processes

    PubMed Central

    Fific, Mario

    2014-01-01

    Inferences we make about underlying cognitive processes can be jeopardized in two ways due to problematic forms of aggregation. First, averaging across individuals is typically considered a very useful tool for removing random variability. The threat is that averaging across subjects leads to averaging across different cognitive strategies, thus harming our inferences. The second threat comes from the construction of inadequate research designs possessing a low diagnostic accuracy of cognitive processes. For that reason we introduced the systems factorial technology (SFT), which has primarily been designed to make inferences about underlying processing order (serial, parallel, coactive), stopping rule (terminating, exhaustive), and process dependency. SFT proposes that the minimal research design complexity to learn about n number of cognitive processes should be equal to 2n. In addition, SFT proposes that (a) each cognitive process should be controlled by a separate experimental factor, and (b) The saliency levels of all factors should be combined in a full factorial design. In the current study, the author cross combined the levels of jeopardies in a 2 × 2 analysis, leading to four different analysis conditions. The results indicate a decline in the diagnostic accuracy of inferences made about cognitive processes due to the presence of each jeopardy in isolation and when combined. The results warrant the development of more individual subject analyses and the utilization of full-factorial (SFT) experimental designs. PMID:25374545

  18. Knowledge-Based Inferences Are Not General

    ERIC Educational Resources Information Center

    Shears, Connie; Chiarello, Christine

    2004-01-01

    Although knowledge-based inferences (Graesser, Singer, & Trabasso, 1994) depend on general knowledge, there may be differences across knowledge areas in how they support these processes. This study explored processing differences between 2 areas of knowledge (physical cause?effect vs. goals and planning) to establish (a) that each would support…

  19. Investigating Mathematics Teachers' Thoughts of Statistical Inference

    ERIC Educational Resources Information Center

    Yang, Kai-Lin

    2012-01-01

    Research on statistical cognition and application suggests that statistical inference concepts are commonly misunderstood by students and even misinterpreted by researchers. Although some research has been done on students' misunderstanding or misconceptions of confidence intervals (CIs), few studies explore either students' or mathematics…

  20. Inferring Internet Denial-of-Service Activity

    DTIC Science & Technology

    2007-11-02

    Inferring Internet Denial-of-Service Activity David Moore CAIDA San Diego Supercomputer Center University of California, San Diego dmoore@caida.org...the local network topology. kc claffy and Colleen Shannon at CAIDA provided support and valuable feed- back throughout the project. David Wetherall

  1. Nutritional deficiency in oral candidosis.

    PubMed

    Jenkins, W M; Macfarlane, T W; Ferguson, M M; Mason, D K

    1977-08-01

    A retrospective study of 108 patients was carried out to investigate the possible relationship between infection of the mouth with Candida albicans and blood levels of iron, folic acid and vitamin B12. The patients were separated into two groups--those with hyperplastic and those with atrophic candidal lesions--and compared with separate control groups. Twenty-one patients had chronic hyperplastic candidosis and seven were iron deficient. Comparison with an age- and sex-matched control group showed the differences to be significant only at the p less than 0.1 level. Seven of the patients with hyperplastic lesions had folic acid deficiency and the difference between patients and controls was statistically significant (less than 0.05). However, no significant differences in iron or folic acid deficiency were noted between 87 patients with atrophic candidosis and 65 conttrols, and vitamin B12 deficiency was not statistically significant for either the hyperplastic or the atrophic group. It is concluded that deficiency of iron, folic acid or vitamin B12 alone does not promote growth of Candida albicans on the oral mucous membrane but that in some susceptible individuals, iron or folic deficiency may facilitate epithelial invasion by hyphae of Candida albicans.

  2. The neurology of biotinidase deficiency.

    PubMed

    Wolf, Barry

    2011-01-01

    Biotinidase deficiency is an autosomal recessively inherited metabolic disorder in which the enzyme, biotinidase, is defective and the vitamin, biotin, is not recycled. Individuals with biotinidase deficiency, if not treated with biotin, usually exhibit neurological and cutaneous abnormalities. Biotin treatment can ameliorate or prevent symptoms. Biotinidase deficiency meets the major criteria for inclusion in newborn screening programs. With the advent of universal newborn screening for the disorder, the "window-of-opportunity" to characterize the consequences of the untreated disease is essentially gone. To understand the neurology of biotinidase deficiency, we must depend on what is already known about symptomatic individuals with the disorder. Therefore, in this review, the neurological findings of symptomatic individuals with profound biotinidase deficiency have been compiled to catalog the characteristic features of the disorder and the consequences of biotin treatment on these findings. In addition, based on the available evidence, I have speculated on the cause of neurological problems associated with the disorder. Future studies in biotinidase-deficient animals should allow us to demonstrate more definitively if these speculations are correct. Copyright © 2011 Elsevier Inc. All rights reserved.

  3. Phenotypic variation in biotinidase deficiency.

    PubMed

    Wolf, B; Grier, R E; Allen, R J; Goodman, S I; Kien, C L; Parker, W D; Howell, D M; Hurst, D L

    1983-08-01

    Biotinidase deficiency is the usual biochemical defect in biotin-responsive late-onset multiple carboxylase deficiency. We reviewed the clinical features of six patients with the enzyme deficiency and compared them with features described in the literature in children with late-onset MCD. In all of the reported probands, MCD was diagnosed because they had metabolic ketoacidosis and organic aciduria in addition to various neurologic and cutaneous symptoms, such as seizures, ataxia, skin rash, and alopecia. Although in several of our patients biotinidase deficiency was also diagnosed because they manifested a similar spectrum of findings, others never had ketoacidosis or organic aciduria. Thus the initial features of biotinidase deficiency usually include neurologic or cutaneous symptoms, whereas organic aciduria and MCD are delayed, secondary manifestations of the disease. These findings suggest that biotinidase deficiency should be considered in any infant or child with any of these neurologic or cutaneous findings, with or without ketoacidosis or organic aciduria. If the diagnosis cannot be excluded, such individuals should be given a therapeutic trial of pharmacologic doses of biotin.

  4. Iron-Deficiency Anemia (For Parents)

    MedlinePlus

    ... Habits for TV, Video Games, and the Internet Iron-Deficiency Anemia KidsHealth > For Parents > Iron-Deficiency Anemia Print ... anemia, a common nutritional deficiency in children. About Iron-Deficiency Anemia Every red blood cell in the body ...

  5. [Iron deficiency and iron deficiency anemia are global health problems].

    PubMed

    Dahlerup, Jens; Lindgren, Stefan; Moum, Björn

    2015-03-10

    Iron deficiency and iron deficiency anemia are global health problems leading to deterioration in patients' quality of life and more serious prognosis in patients with chronic diseases. The cause of iron deficiency and anemia is usually a combination of increased loss and decreased intestinal absorption and delivery from iron stores due to inflammation. Oral iron is first line treatment, but often hampered by intolerance. Intravenous iron is safe, and the preferred treatment in patients with chronic inflammation and bowel diseases. The goal of treatment is normalisation of hemoglobin concentration and recovery of iron stores. It is important to follow up treatment to ensure that these objectives are met and also long-term in patients with chronic iron loss and/or inflammation to avoid recurrence of anemia.

  6. Leaf Senescence by Magnesium Deficiency

    PubMed Central

    Tanoi, Keitaro; Kobayashi, Natsuko I.

    2015-01-01

    Magnesium ions (Mg2+) are the second most abundant cations in living plant cells, and they are involved in various functions, including photosynthesis, enzyme catalysis, and nucleic acid synthesis. Low availability of Mg2+ in an agricultural field leads to a decrease in yield, which follows the appearance of Mg-deficient symptoms such as chlorosis, necrotic spots on the leaves, and droop. During the last decade, a variety of physiological and molecular responses to Mg2+ deficiency that potentially link to leaf senescence have been recognized, allowing us to reconsider the mechanisms of Mg2+ deficiency. This review focuses on the current knowledge about the physiological responses to Mg2+ deficiency including a decline in transpiration, accumulation of sugars and starch in source leaves, change in redox states, increased oxidative stress, metabolite alterations, and a decline in photosynthetic activity. In addition, we refer to the molecular responses that are thought to be related to leaf senescence. With these current data, we give an overview of leaf senescence induced by Mg deficiency. PMID:27135350

  7. Iodine deficiency and thyroid disorders.

    PubMed

    Zimmermann, Michael B; Boelaert, Kristien

    2015-04-01

    Iodine deficiency early in life impairs cognition and growth, but iodine status is also a key determinant of thyroid disorders in adults. Severe iodine deficiency causes goitre and hypothyroidism because, despite an increase in thyroid activity to maximise iodine uptake and recycling in this setting, iodine concentrations are still too low to enable production of thyroid hormone. In mild-to-moderate iodine deficiency, increased thyroid activity can compensate for low iodine intake and maintain euthyroidism in most individuals, but at a price: chronic thyroid stimulation results in an increase in the prevalence of toxic nodular goitre and hyperthyroidism in populations. This high prevalence of nodular autonomy usually results in a further increase in the prevalence of hyperthyroidism if iodine intake is subsequently increased by salt iodisation. However, this increase is transient because iodine sufficiency normalises thyroid activity which, in the long term, reduces nodular autonomy. Increased iodine intake in an iodine-deficient population is associated with a small increase in the prevalence of subclinical hypothyroidism and thyroid autoimmunity; whether these increases are also transient is unclear. Variations in population iodine intake do not affect risk for Graves' disease or thyroid cancer, but correction of iodine deficiency might shift thyroid cancer subtypes toward less malignant forms. Thus, optimisation of population iodine intake is an important component of preventive health care to reduce the prevalence of thyroid disorders. Copyright © 2015 Elsevier Ltd. All rights reserved.

  8. Iron Deficiency and Bariatric Surgery

    PubMed Central

    Jáuregui-Lobera, Ignacio

    2013-01-01

    It is estimated that the prevalence of anaemia in patients scheduled for bariatric surgery is higher than in the general population and the prevalence of iron deficiencies (with or without anaemia) may be higher as well. After surgery, iron deficiencies and anaemia may occur in a higher percentage of patients, mainly as a consequence of nutrient deficiencies. In addition, perioperative anaemia has been related with increased postoperative morbidity and mortality and poorer quality of life after bariatric surgery. The treatment of perioperative anaemia and nutrient deficiencies has been shown to improve patients’ outcomes and quality of life. All patients should undergo an appropriate nutritional evaluation, including selective micronutrient measurements (e.g., iron), before any bariatric surgical procedure. In comparison with purely restrictive procedures, more extensive perioperative nutritional evaluations are required for malabsorptive procedures due to their nutritional consequences. The aim of this study was to review the current knowledge of nutritional deficits in obese patients and those that commonly appear after bariatric surgery, specifically iron deficiencies and their consequences. As a result, some recommendations for screening and supplementation are presented. PMID:23676549

  9. An Intuitive Dashboard for Bayesian Network Inference

    NASA Astrophysics Data System (ADS)

    Reddy, Vikas; Charisse Farr, Anna; Wu, Paul; Mengersen, Kerrie; Yarlagadda, Prasad K. D. V.

    2014-03-01

    Current Bayesian network software packages provide good graphical interface for users who design and develop Bayesian networks for various applications. However, the intended end-users of these networks may not necessarily find such an interface appealing and at times it could be overwhelming, particularly when the number of nodes in the network is large. To circumvent this problem, this paper presents an intuitive dashboard, which provides an additional layer of abstraction, enabling the end-users to easily perform inferences over the Bayesian networks. Unlike most software packages, which display the nodes and arcs of the network, the developed tool organises the nodes based on the cause-and-effect relationship, making the user-interaction more intuitive and friendly. In addition to performing various types of inferences, the users can conveniently use the tool to verify the behaviour of the developed Bayesian network. The tool has been developed using QT and SMILE libraries in C++.

  10. Inferring network topology via the propagation process

    NASA Astrophysics Data System (ADS)

    Zeng, An

    2013-11-01

    Inferring the network topology from the dynamics is a fundamental problem, with wide applications in geology, biology, and even counter-terrorism. Based on the propagation process, we present a simple method to uncover the network topology. A numerical simulation on artificial networks shows that our method enjoys a high accuracy in inferring the network topology. We find that the infection rate in the propagation process significantly influences the accuracy, and that each network corresponds to an optimal infection rate. Moreover, the method generally works better in large networks. These finding are confirmed in both real social and nonsocial networks. Finally, the method is extended to directed networks, and a similarity measure specific for directed networks is designed.

  11. Interoceptive inference, emotion, and the embodied self.

    PubMed

    Seth, Anil K

    2013-11-01

    The concept of the brain as a prediction machine has enjoyed a resurgence in the context of the Bayesian brain and predictive coding approaches within cognitive science. To date, this perspective has been applied primarily to exteroceptive perception (e.g., vision, audition), and action. Here, I describe a predictive, inferential perspective on interoception: 'interoceptive inference' conceives of subjective feeling states (emotions) as arising from actively-inferred generative (predictive) models of the causes of interoceptive afferents. The model generalizes 'appraisal' theories that view emotions as emerging from cognitive evaluations of physiological changes, and it sheds new light on the neurocognitive mechanisms that underlie the experience of body ownership and conscious selfhood in health and in neuropsychiatric illness.

  12. Pointwise probability reinforcements for robust statistical inference.

    PubMed

    Frénay, Benoît; Verleysen, Michel

    2014-02-01

    Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation.

  13. Neural Circuit Inference from Function to Structure.

    PubMed

    Real, Esteban; Asari, Hiroki; Gollisch, Tim; Meister, Markus

    2017-01-23

    Advances in technology are opening new windows on the structural connectivity and functional dynamics of brain circuits. Quantitative frameworks are needed that integrate these data from anatomy and physiology. Here, we present a modeling approach that creates such a link. The goal is to infer the structure of a neural circuit from sparse neural recordings, using partial knowledge of its anatomy as a regularizing constraint. We recorded visual responses from the output neurons of the retina, the ganglion cells. We then generated a systematic sequence of circuit models that represents retinal neurons and connections and fitted them to the experimental data. The optimal models faithfully recapitulated the ganglion cell outputs. More importantly, they made predictions about dynamics and connectivity among unobserved neurons internal to the circuit, and these were subsequently confirmed by experiment. This circuit inference framework promises to facilitate the integration and understanding of big data in neuroscience.

  14. Dopamine, reward learning, and active inference

    PubMed Central

    FitzGerald, Thomas H. B.; Dolan, Raymond J.; Friston, Karl

    2015-01-01

    Temporal difference learning models propose phasic dopamine signaling encodes reward prediction errors that drive learning. This is supported by studies where optogenetic stimulation of dopamine neurons can stand in lieu of actual reward. Nevertheless, a large body of data also shows that dopamine is not necessary for learning, and that dopamine depletion primarily affects task performance. We offer a resolution to this paradox based on an hypothesis that dopamine encodes the precision of beliefs about alternative actions, and thus controls the outcome-sensitivity of behavior. We extend an active inference scheme for solving Markov decision processes to include learning, and show that simulated dopamine dynamics strongly resemble those actually observed during instrumental conditioning. Furthermore, simulated dopamine depletion impairs performance but spares learning, while simulated excitation of dopamine neurons drives reward learning, through aberrant inference about outcome states. Our formal approach provides a novel and parsimonious reconciliation of apparently divergent experimental findings. PMID:26581305

  15. The NIFTY way of Bayesian signal inference

    SciTech Connect

    Selig, Marco

    2014-12-05

    We introduce NIFTY, 'Numerical Information Field Theory', a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTY can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTY as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D{sup 3}PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.

  16. The empirical accuracy of uncertain inference models

    NASA Technical Reports Server (NTRS)

    Vaughan, David S.; Yadrick, Robert M.; Perrin, Bruce M.; Wise, Ben P.

    1987-01-01

    Uncertainty is a pervasive feature of the domains in which expert systems are designed to function. Research design to test uncertain inference methods for accuracy and robustness, in accordance with standard engineering practice is reviewed. Several studies were conducted to assess how well various methods perform on problems constructed so that correct answers are known, and to find out what underlying features of a problem cause strong or weak performance. For each method studied, situations were identified in which performance deteriorates dramatically. Over a broad range of problems, some well known methods do only about as well as a simple linear regression model, and often much worse than a simple independence probability model. The results indicate that some commercially available expert system shells should be used with caution, because the uncertain inference models that they implement can yield rather inaccurate results.

  17. The NIFTy way of Bayesian signal inference

    NASA Astrophysics Data System (ADS)

    Selig, Marco

    2014-12-01

    We introduce NIFTy, "Numerical Information Field Theory", a software package for the development of Bayesian signal inference algorithms that operate independently from any underlying spatial grid and its resolution. A large number of Bayesian and Maximum Entropy methods for 1D signal reconstruction, 2D imaging, as well as 3D tomography, appear formally similar, but one often finds individualized implementations that are neither flexible nor easily transferable. Signal inference in the framework of NIFTy can be done in an abstract way, such that algorithms, prototyped in 1D, can be applied to real world problems in higher-dimensional settings. NIFTy as a versatile library is applicable and already has been applied in 1D, 2D, 3D and spherical settings. A recent application is the D3PO algorithm targeting the non-trivial task of denoising, deconvolving, and decomposing photon observations in high energy astronomy.

  18. FUNCTIONAL SIGNIFICANCE OF EARLY-LIFE IRON DEFICIENCY: OUTCOMES AT 25 YEARS

    PubMed Central

    Lozoff, Betsy; Smith, Julia B.; Kaciroti, Niko; Clark, Katy M.; Guevara, Silvia; Jimenez, Elias

    2013-01-01

    Objective To determine adulthood functioning following chronic iron deficiency in infancy. Study design At 25 years, we compared 33 participants with chronic iron deficiency in infancy to 89 who were iron-sufficient before and/or after iron therapy. Outcomes included education, employment, marital status, physical and mental health. Results Adjusting for sex and SES, a higher proportion of the chronic iron-deficient group did not complete secondary school (58.1% vs.19.8% in iron-sufficient group, Wald-value = 8.74, p = .003), were not pursuing further education/training (76.1% vs. 31.5%, Wald-value = 3.01, p = .08; suggestive trend), and were single (83.9% vs. 23.7%, Wald-value = 4.49, p = .03). They reported poorer emotional health and more negative emotions and feelings of dissociation/detachment. Results were similar in secondary analyses comparing the chronic iron-deficient group to participants in the iron-sufficient group who had been iron-deficient before treatment in infancy. Path analysis showed direct paths for chronic iron deficiency in infancy and being single and more detachment/dissociation at 25 years. There were indirect paths for chronic iron deficiency and not completing secondary school via poorer cognitive functioning in early adolescence and more negative emotions via behavior problems in adolescence, indicating a cascade of adverse outcomes. Conclusion The observational nature of the study limits causal inference, despite control for background factors. Nonetheless, the results indicate substantial loss of human potential. There may be broader societal implications, because many adults worldwide had chronic iron deficiency in infancy. Iron deficiency can be prevented or treated before it becomes chronic or severe. PMID:23827739

  19. Functional significance of early-life iron deficiency: outcomes at 25 years.

    PubMed

    Lozoff, Betsy; Smith, Julia B; Kaciroti, Niko; Clark, Katy M; Guevara, Silvia; Jimenez, Elias

    2013-11-01

    To evaluate adulthood function following chronic iron deficiency in infancy. At 25 years, we compared 33 subjects with chronic iron deficiency in infancy to 89 who were iron-sufficient before and/or after iron therapy. Outcomes included education, employment, marital status, and physical and mental health. Adjusting for sex and socioeconomic status, a higher proportion of the group with chronic iron deficiency did not complete secondary school (58.1% vs 19.8% in iron-sufficient group; Wald value = 8.74; P = .003), were not pursuing further education/training (76.1% vs 31.5%; Wald value = 3.01; P = .08; suggestive trend), and were single (83.9% vs 23.7%, Wald value = 4.49; P = .03). They reported poorer emotional health and more negative emotions and feelings of dissociation/detachment. Results were similar in secondary analyses comparing the chronic iron-deficient group with subjects in the iron-sufficient group who had been iron-deficient before treatment in infancy. Path analysis showed direct paths for chronic iron deficiency in infancy and being single and more detachment/dissociation at 25 years. There were indirect paths for chronic iron deficiency and not completing secondary school via poorer cognitive functioning in early adolescence and more negative emotions via behavior problems in adolescence, indicating a cascade of adverse outcomes. The observational nature of this study limits our ability to draw causal inference, even when controlling for background factors. Nonetheless, our results indicate substantial loss of human potential. There may be broader societal implications, considering that many adults worldwide had chronic iron deficiency in infancy. Iron deficiency can be prevented or treated before it becomes chronic or severe. Copyright © 2013 Mosby, Inc. All rights reserved.

  20. Context recognition for a hyperintensional inference machine

    NASA Astrophysics Data System (ADS)

    Duží, Marie; Fait, Michal; Menšík, Marek

    2017-07-01

    The goal of this paper is to introduce the algorithm of context recognition in the functional programming language TIL-Script, which is a necessary condition for the implementation of the TIL-Script inference machine. The TIL-Script language is an operationally isomorphic syntactic variant of Tichý's Transparent Intensional Logic (TIL). From the formal point of view, TIL is a hyperintensional, partial, typed λ-calculus with procedural semantics. Hyperintensional, because TIL λ-terms denote procedures (defined as TIL constructions) producing set-theoretic functions rather than the functions themselves; partial, because TIL is a logic of partial functions; and typed, because all the entities of TIL ontology, including constructions, receive a type within a ramified hierarchy of types. These features make it possible to distinguish three levels of abstraction at which TIL constructions operate. At the highest hyperintensional level the object to operate on is a construction (though a higher-order construction is needed to present this lower-order construction as an object of predication). At the middle intensional level the object to operate on is the function presented, or constructed, by a construction, while at the lowest extensional level the object to operate on is the value (if any) of the presented function. Thus a necessary condition for the development of an inference machine for the TIL-Script language is recognizing a context in which a construction occurs, namely extensional, intensional and hyperintensional context, in order to determine the type of an argument at which a given inference rule can be properly applied. As a result, our logic does not flout logical rules of extensional logic, which makes it possible to develop a hyperintensional inference machine for the TIL-Script language.

  1. A Theory of Diagnostic Inference: Judging Causality.

    DTIC Science & Technology

    1983-08-01

    Lepper, 1981) and the lack of search for disconfirming hypotheses (e.g., Mynatt , et al. 1977, 1978; Tweney, et al., 1980), we stress that a...perception de la causalite. Paris: Vrin, 1946. Mynatt , C. R., Doherty, M. Z., a Tweney, R. D. Confirmation bias in a simulated research environment: An...experimental study of scientific inference. Quarterly Journal of Experimental Psychology, 1977, 29, 85-95. =4 57 Mynatt , C. R., Doherty, M. E., & Tweney, R

  2. Inferring Trust Based on Similarity with TILLIT

    NASA Astrophysics Data System (ADS)

    Tavakolifard, Mozhgan; Herrmann, Peter; Knapskog, Svein J.

    A network of people having established trust relations and a model for propagation of related trust scores are fundamental building blocks in many of today’s most successful e-commerce and recommendation systems. However, the web of trust is often too sparse to predict trust values between non-familiar people with high accuracy. Trust inferences are transitive associations among users in the context of an underlying social network and may provide additional information to alleviate the consequences of the sparsity and possible cold-start problems. Such approaches are helpful, provided that a complete trust path exists between the two users. An alternative approach to the problem is advocated in this paper. Based on collaborative filtering one can exploit the like-mindedness resp. similarity of individuals to infer trust to yet unknown parties which increases the trust relations in the web. For instance, if one knows that with respect to a specific property, two parties are trusted alike by a large number of different trusters, one can assume that they are similar. Thus, if one has a certain degree of trust to the one party, one can safely assume a very similar trustworthiness of the other one. In an attempt to provide high quality recommendations and proper initial trust values even when no complete trust propagation path or user profile exists, we propose TILLIT — a model based on combination of trust inferences and user similarity. The similarity is derived from the structure of the trust graph and users’ trust behavior as opposed to other collaborative-filtering based approaches which use ratings of items or user’s profile. We describe an algorithm realizing the approach based on a combination of trust inferences and user similarity, and validate the algorithm using a real large-scale data-set.

  3. Thermodynamics of statistical inference by cells.

    PubMed

    Lang, Alex H; Fisher, Charles K; Mora, Thierry; Mehta, Pankaj

    2014-10-03

    The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on statistical estimation and learning. To do so, we investigate the constraints placed by (nonequilibrium) thermodynamics on the ability of biochemical signaling networks to estimate the concentration of an external signal. We show that accuracy is limited by energy consumption, suggesting that there are fundamental thermodynamic constraints on statistical inference.

  4. Tactile length contraction as Bayesian inference.

    PubMed

    Tong, Jonathan; Ngo, Vy; Goldreich, Daniel

    2016-08-01

    To perceive, the brain must interpret stimulus-evoked neural activity. This is challenging: The stochastic nature of the neural response renders its interpretation inherently uncertain. Perception would be optimized if the brain used Bayesian inference to interpret inputs in light of expectations derived from experience. Bayesian inference would improve perception on average but cause illusions when stimuli violate expectation. Intriguingly, tactile, auditory, and visual perception are all prone to length contraction illusions, characterized by the dramatic underestimation of the distance between punctate stimuli delivered in rapid succession; the origin of these illusions has been mysterious. We previously proposed that length contraction illusions occur because the brain interprets punctate stimulus sequences using Bayesian inference with a low-velocity expectation. A novel prediction of our Bayesian observer model is that length contraction should intensify if stimuli are made more difficult to localize. Here we report a tactile psychophysical study that tested this prediction. Twenty humans compared two distances on the forearm: a fixed reference distance defined by two taps with 1-s temporal separation and an adjustable comparison distance defined by two taps with temporal separation t ≤ 1 s. We observed significant length contraction: As t was decreased, participants perceived the two distances as equal only when the comparison distance was made progressively greater than the reference distance. Furthermore, the use of weaker taps significantly enhanced participants' length contraction. These findings confirm the model's predictions, supporting the view that the spatiotemporal percept is a best estimate resulting from a Bayesian inference process. Copyright © 2016 the American Physiological Society.

  5. Phylogeny and the inference of evolutionary trajectories.

    PubMed

    Hancock, Lillian; Edwards, Erika J

    2014-07-01

    Most important organismal adaptations are not actually single traits, but complex trait syndromes that are evolutionarily integrated into a single emergent phenotype. Two alternative photosynthetic pathways, C4 photosynthesis and crassulacean acid metabolism (CAM), are primary plant adaptations of this sort, each requiring multiple biochemical and anatomical modifications. Phylogenetic methods are a promising approach for teasing apart the order of character acquisition during the evolution of complex traits, and the phylogenetic placement of intermediate phenotypes as sister taxa to fully optimized syndromes has been taken as good evidence of an 'ordered' evolutionary trajectory. But how much power does the phylogenetic approach have to detect ordered evolution? This study simulated ordered and unordered character evolution across a diverse set of phylogenetic trees to understand how tree size, models of evolution, and sampling efforts influence the ability to detect an evolutionary trajectory. The simulations show that small trees (15 taxa) do not contain enough information to correctly infer either an ordered or unordered trajectory, although inference improves as tree size and sampling increases. However, even when working with a 1000-taxon tree, the possibility of inferring the incorrect evolutionary model (type I/type II error) remains. Caution is needed when interpreting the phylogenetic placement of intermediate phenotypes, especially in small lineages. Such phylogenetic patterns can provide a line of evidence for the existence of a particular evolutionary trajectory, but they should be coupled with other types of data to infer the stepwise evolution of a complex character trait. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

  6. To link, to infer, to understand.

    PubMed

    Kock, H

    1989-01-01

    A model of linkage in text processing is proposed: An external proposition and an inference belonging to one frame are superimposed to constitute understanding. A text containing four academic subjects was presented orally to students who recalled it in writing. After transforming the recalls into propositions they are entered into a nonmetric multidimensional scaling to yield a text space. The subjects' interest choices among items of the four aspects are scaled to render an interest space. The decomposition ob both as subspaces of a common space yields an angle as their overall similarity and indicates the degree of predictability from interests. As the aggregate of inferences shows directedness, correlated with volitional-motivational orientation, and inference base is assumed to intervene. It is concluded that recipients try to superimpose and thereby construct a primary stage of processing. This allows for a very general algorithm of parallel information processing (holographic thesis), perhaps constructing the properties we are used to. Motivated perception, knowledge influence, schema-directedness and contribution to coherence are rivalled out as an explanation of this process.

  7. Functional neuroanatomy of intuitive physical inference

    PubMed Central

    Mikhael, John G.; Tenenbaum, Joshua B.; Kanwisher, Nancy

    2016-01-01

    To engage with the world—to understand the scene in front of us, plan actions, and predict what will happen next—we must have an intuitive grasp of the world’s physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events—a “physics engine” in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general “multiple demand” system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action. PMID:27503892

  8. Inferring sparse networks for noisy transient processes

    NASA Astrophysics Data System (ADS)

    Tran, Hoang M.; Bukkapatnam, Satish T. S.

    2016-02-01

    Inferring causal structures of real world complex networks from measured time series signals remains an open issue. The current approaches are inadequate to discern between direct versus indirect influences (i.e., the presence or absence of a directed arc connecting two nodes) in the presence of noise, sparse interactions, as well as nonlinear and transient dynamics of real world processes. We report a sparse regression (referred to as the -min) approach with theoretical bounds on the constraints on the allowable perturbation to recover the network structure that guarantees sparsity and robustness to noise. We also introduce averaging and perturbation procedures to further enhance prediction scores (i.e., reduce inference errors), and the numerical stability of -min approach. Extensive investigations have been conducted with multiple benchmark simulated genetic regulatory network and Michaelis-Menten dynamics, as well as real world data sets from DREAM5 challenge. These investigations suggest that our approach can significantly improve, oftentimes by 5 orders of magnitude over the methods reported previously for inferring the structure of dynamic networks, such as Bayesian network, network deconvolution, silencing and modular response analysis methods based on optimizing for sparsity, transients, noise and high dimensionality issues.

  9. Bayesian Inference for Skewed Stable Distributions

    NASA Astrophysics Data System (ADS)

    Shokripour, Mona; Nassiri, Vahid; Mohammadpour, Adel

    2011-03-01

    Stable distributions are a class of distributions which allow skewness and heavy tail. Non-Gaussian stable random variables play the role of normal distribution in the central limit theorem, for normalized sums of random variables with infinite variance. The lack of analytic formula for density and distribution functions of stable random variables has been a major drawback to the use of stable distributions, also in the case of inference in Bayesian framework. Buckle introduced priors for the parameters of stable random variables to obtain an analytic form of posterior distribution. However, many researchers tried to solve the problem, through the Markov chain Monte Carlo methods, e.g. [8] and their references. In this paper a new class of heavy-tailed distribution is introduced, called skewed stable. This class has two main advantages: It has many inferential advantages, since it is a member of exponential family, so the Bayesian inference can be drawn similar to the exponential family of distributions and modelling skew data with stable distributions is dominated by this family. Finally, Bayesian inference for skewed stable arc compared to the stable distributions through a few simulations study.

  10. Inference of magnetic fields in inhomogeneous prominences

    NASA Astrophysics Data System (ADS)

    Milić, I.; Faurobert, M.; Atanacković, O.

    2017-01-01

    Context. Most of the quantitative information about the magnetic field vector in solar prominences comes from the analysis of the Hanle effect acting on lines formed by scattering. As these lines can be of non-negligible optical thickness, it is of interest to study the line formation process further. Aims: We investigate the multidimensional effects on the interpretation of spectropolarimetric observations, particularly on the inference of the magnetic field vector. We do this by analyzing the differences between multidimensional models, which involve fully self-consistent radiative transfer computations in the presence of spatial inhomogeneities and velocity fields, and those which rely on simple one-dimensional geometry. Methods: We study the formation of a prototype line in ad hoc inhomogeneous, isothermal 2D prominence models. We solve the NLTE polarized line formation problem in the presence of a large-scale oriented magnetic field. The resulting polarized line profiles are then interpreted (i.e. inverted) assuming a simple 1D slab model. Results: We find that differences between input and the inferred magnetic field vector are non-negligible. Namely, we almost universally find that the inferred field is weaker and more horizontal than the input field. Conclusions: Spatial inhomogeneities and radiative transfer have a strong effect on scattering line polarization in the optically thick lines. In real-life situations, ignoring these effects could lead to a serious misinterpretation of spectropolarimetric observations of chromospheric objects such as prominences.

  11. Inferring Genetic Ancestry: Opportunities, Challenges, and Implications

    PubMed Central

    Royal, Charmaine D.; Novembre, John; Fullerton, Stephanie M.; Goldstein, David B.; Long, Jeffrey C.; Bamshad, Michael J.; Clark, Andrew G.

    2010-01-01

    Increasing public interest in direct-to-consumer (DTC) genetic ancestry testing has been accompanied by growing concern about issues ranging from the personal and societal implications of the testing to the scientific validity of ancestry inference. The very concept of “ancestry” is subject to misunderstanding in both the general and scientific communities. What do we mean by ancestry? How exactly is ancestry measured? How far back can such ancestry be defined and by which genetic tools? How do we validate inferences about ancestry in genetic research? What are the data that demonstrate our ability to do this correctly? What can we say and what can we not say from our research findings and the test results that we generate? This white paper from the American Society of Human Genetics (ASHG) Ancestry and Ancestry Testing Task Force builds upon the 2008 ASHG Ancestry Testing Summary Statement in providing a more in-depth analysis of key scientific and non-scientific aspects of genetic ancestry inference in academia and industry. It culminates with recommendations for advancing the current debate and facilitating the development of scientifically based, ethically sound, and socially attentive guidelines concerning the use of these continually evolving technologies. PMID:20466090

  12. Combinatorics of distance-based tree inference

    PubMed Central

    Pardi, Fabio; Gascuel, Olivier

    2012-01-01

    Several popular methods for phylogenetic inference (or hierarchical clustering) are based on a matrix of pairwise distances between taxa (or any kind of objects): The objective is to construct a tree with branch lengths so that the distances between the leaves in that tree are as close as possible to the input distances. If we hold the structure (topology) of the tree fixed, in some relevant cases (e.g., ordinary least squares) the optimal values for the branch lengths can be expressed using simple combinatorial formulae. Here we define a general form for these formulae and show that they all have two desirable properties: First, the common tree reconstruction approaches (least squares, minimum evolution), when used in combination with these formulae, are guaranteed to infer the correct tree when given enough data (consistency); second, the branch lengths of all the simple (nearest neighbor interchange) rearrangements of a tree can be calculated, optimally, in quadratic time in the size of the tree, thus allowing the efficient application of hill climbing heuristics. The study presented here is a continuation of that by Mihaescu and Pachter on branch length estimation [Mihaescu R, Pachter L (2008) Proc Natl Acad Sci USA 105:13206–13211]. The focus here is on the inference of the tree itself and on providing a basis for novel algorithms to reconstruct trees from distances. PMID:23012403

  13. Combinatorics of distance-based tree inference.

    PubMed

    Pardi, Fabio; Gascuel, Olivier

    2012-10-09

    Several popular methods for phylogenetic inference (or hierarchical clustering) are based on a matrix of pairwise distances between taxa (or any kind of objects): The objective is to construct a tree with branch lengths so that the distances between the leaves in that tree are as close as possible to the input distances. If we hold the structure (topology) of the tree fixed, in some relevant cases (e.g., ordinary least squares) the optimal values for the branch lengths can be expressed using simple combinatorial formulae. Here we define a general form for these formulae and show that they all have two desirable properties: First, the common tree reconstruction approaches (least squares, minimum evolution), when used in combination with these formulae, are guaranteed to infer the correct tree when given enough data (consistency); second, the branch lengths of all the simple (nearest neighbor interchange) rearrangements of a tree can be calculated, optimally, in quadratic time in the size of the tree, thus allowing the efficient application of hill climbing heuristics. The study presented here is a continuation of that by Mihaescu and Pachter on branch length estimation [Mihaescu R, Pachter L (2008) Proc Natl Acad Sci USA 105:13206-13211]. The focus here is on the inference of the tree itself and on providing a basis for novel algorithms to reconstruct trees from distances.

  14. Orthologous repeats and mammalian phylogenetic inference

    PubMed Central

    Bashir, Ali; Ye, Chun; Price, Alkes L.; Bafna, Vineet

    2005-01-01

    Determining phylogenetic relationships between species is a difficult problem, and many phylogenetic relationships remain unresolved, even among eutherian mammals. Repetitive elements provide excellent markers for phylogenetic analysis, because their mode of evolution is predominantly homoplasy-free and unidirectional. Historically, phylogenetic studies using repetitive elements have relied on biological methods such as PCR analysis, and computational inference is limited to a few isolated repeats. Here, we present a novel computational method for inferring phylogenetic relationships from partial sequence data using orthologous repeats. We apply our method to reconstructing the phylogeny of 28 mammals, using more than 1000 orthologous repeats obtained from sequence data available from the NISC Comparative Sequencing Program. The resulting phylogeny has robust bootstrap numbers, and broadly matches results from previous studies which were obtained using entirely different data and methods. In addition, we shed light on some of the debatable aspects of the phylogeny. With rapid expansion of available partial sequence data, computational analysis of repetitive elements holds great promise for the future of phylogenetic inference. PMID:15998912

  15. Can orangutans (Pongo abelii) infer tool functionality?

    PubMed

    Mulcahy, Nicholas J; Schubiger, Michèle N

    2014-05-01

    It is debatable whether apes can reason about the unobservable properties of tools. We tested orangutans for this ability with a range of tool tasks that they could solve by using observational cues to infer tool functionality. In experiment 1, subjects successfully chose an unbroken tool over a broken one when each tool's middle section was hidden. This prevented seeing which tool was functional but it could be inferred by noting the tools' visible ends that were either disjointed (broken tool) or aligned (unbroken tool). We investigated whether success in experiment 1 was best explained by inferential reasoning or by having a preference per se for a hidden tool with an aligned configuration. We conducted a similar task to experiment 1 and included a functional bent tool that could be arranged to have the same disjointed configuration as the broken tool. The results suggested that subjects had a preference per se for the aligned tool by choosing it regardless of whether it was paired with the broken tool or the functional bent tool. However, further experiments with the bent tool task suggested this preference was a result of additional demands of having to attend to and remember the properties of the tools from the beginning of the task. In our last experiment, we removed these task demands and found evidence that subjects could infer the functionality of a broken tool and an unbroken tool that both looked identical at the time of choice.

  16. Functional neuroanatomy of intuitive physical inference.

    PubMed

    Fischer, Jason; Mikhael, John G; Tenenbaum, Joshua B; Kanwisher, Nancy

    2016-08-23

    To engage with the world-to understand the scene in front of us, plan actions, and predict what will happen next-we must have an intuitive grasp of the world's physical structure and dynamics. How do the objects in front of us rest on and support each other, how much force would be required to move them, and how will they behave when they fall, roll, or collide? Despite the centrality of physical inferences in daily life, little is known about the brain mechanisms recruited to interpret the physical structure of a scene and predict how physical events will unfold. Here, in a series of fMRI experiments, we identified a set of cortical regions that are selectively engaged when people watch and predict the unfolding of physical events-a "physics engine" in the brain. These brain regions are selective to physical inferences relative to nonphysical but otherwise highly similar scenes and tasks. However, these regions are not exclusively engaged in physical inferences per se or, indeed, even in scene understanding; they overlap with the domain-general "multiple demand" system, especially the parts of that system involved in action planning and tool use, pointing to a close relationship between the cognitive and neural mechanisms involved in parsing the physical content of a scene and preparing an appropriate action.

  17. Cortical information flow during inferences of agency

    PubMed Central

    Dogge, Myrthel; Hofman, Dennis; Boersma, Maria; Dijkerman, H. Chris; Aarts, Henk

    2014-01-01

    Building on the recent finding that agency experiences do not merely rely on sensorimotor information but also on cognitive cues, this exploratory study uses electroencephalographic recordings to examine functional connectivity during agency inference processing in a setting where action and outcome are independent. Participants completed a computerized task in which they pressed a button followed by one of two color words (red or blue) and rated their experienced agency over producing the color. Before executing the action, a matching or mismatching color word was pre-activated by explicitly instructing participants to produce the color (goal condition) or by briefly presenting the color word (prime condition). In both conditions, experienced agency was higher in matching vs. mismatching trials. Furthermore, increased electroencephalography (EEG)-based connectivity strength was observed between parietal and frontal nodes and within the (pre)frontal cortex when color-outcomes matched with goals and participants reported high agency. This pattern of increased connectivity was not identified in trials where outcomes were pre-activated through primes. These results suggest that different connections are involved in the experience and in the loss of agency, as well as in inferences of agency resulting from different types of pre-activation. Moreover, the findings provide novel support for the involvement of a fronto-parietal network in agency inferences. PMID:25177282

  18. Evolutionary inferences from the analysis of exchangeability

    PubMed Central

    Hendry, Andrew P.; Kaeuffer, Renaud; Crispo, Erika; Peichel, Catherine L.; Bolnick, Daniel I.

    2013-01-01

    Evolutionary inferences are usually based on statistical models that compare mean genotypes and phenotypes (or their frequencies) among populations. An alternative is to use the actual distribution of genotypes and phenotypes to infer the “exchangeability” of individuals among populations. We illustrate this approach by using discriminant functions on principal components to classify individuals among paired lake and stream populations of threespine stickleback in each of six independent watersheds. Classification based on neutral and non-neutral microsatellite markers was highest to the population of origin and next-highest to populations in the same watershed. These patterns are consistent with the influence of historical contingency (separate colonization of each watershed) and subsequent gene flow (within but not between watersheds). In comparison to this low genetic exchangeability, ecological (diet) and morphological (trophic and armor traits) exchangeability was relatively high – particularly among populations from similar habitats. These patterns reflect the role of natural selection in driving parallel changes adaptive changes when independent populations colonize similar habitats. Importantly, however, substantial non-parallelism was also evident. Our results show that analyses based on exchangeability can confirm inferences based on statistical analyses of means or frequencies, while also refining insights into the drivers of – and constraints on – evolutionary diversification. PMID:24299398

  19. Inferring Pedigree Graphs from Genetic Distances

    NASA Astrophysics Data System (ADS)

    Tamura, Takeyuki; Ito, Hiro

    In this paper, we study a problem of inferring blood relationships which satisfy a given matrix of genetic distances between all pairs of n nodes. Blood relationships are represented by our proposed graph class, which is called a pedigree graph. A pedigree graph is a directed acyclic graph in which the maximum indegree is at most two. We show that the number of pedigree graphs which satisfy the condition of given genetic distances may be exponential, but they can be represented by one directed acyclic graph with n nodes. Moreover, an O(n3) time algorithm which solves the problem is also given. Although phylogenetic trees and phylogenetic networks are similar data structures to pedigree graphs, it seems that inferring methods for phylogenetic trees and networks cannot be applied to infer pedigree graphs since nodes of phylogenetic trees and networks represent species whereas nodes of pedigree graphs represent individuals. We also show an O(n2) time algorithm which detects a contradiction between a given pedigreee graph and distance matrix of genetic distances.

  20. Quality of Computationally Inferred Gene Ontology Annotations

    PubMed Central

    Škunca, Nives; Altenhoff, Adrian; Dessimoz, Christophe

    2012-01-01

    Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation. PMID:22693439

  1. Glucose-6-Phosphate Dehydrogenase Deficiency.

    PubMed

    Luzzatto, Lucio; Nannelli, Caterina; Notaro, Rosario

    2016-04-01

    G6PD is a housekeeping gene expressed in all cells. Glucose-6-phosphate dehydrogenase (G6PD) is part of the pentose phosphate pathway, and its main physiologic role is to provide NADPH. G6PD deficiency, one of the commonest inherited enzyme abnormalities in humans, arises through one of many possible mutations, most of which reduce the stability of the enzyme and its level as red cells age. G6PD-deficient persons are mostly asymptomatic, but they can develop severe jaundice during the neonatal period and acute hemolytic anemia when they ingest fava beans or when they are exposed to certain infections or drugs. G6PD deficiency is a global health issue.

  2. [Vitamin A deficiency and xerophtalmia

    PubMed

    Diniz, A da S; Santos, L M

    2000-11-01

    OBJECTIVE: To review cases of vitamin A deficiency and the effects of vitamin A supplementation on child morbidity and mortality. METHODS: Articles published in scientific journals, technical and scientific books, and also publications by international organizations were used as source of information. RESULTS: Clinical manifestations of xerophthalmia affect the retina (night blindness), the conjunctiva (conjunctival xerosis, with or without Bitot spots), and the cornea (corneal xerosis). Corneal xerosis may lead to corneal ulceration and liquefactive necrosis (keratomalacia). A priori, these signs and symptoms are the best indicators of vitamin A deficiency; they are, however, extremely rare. Laboratory indicators include Conjunctival Impression Cytology and serum retinol concentrations. The World Health Organization (WHO) recommends the use of two biological markers in order to characterize vitamin A deficiency in a given population. If only one biological marker is used, this marker has to be backed up by a set of at least four additional risk factors. Corneal xerophthalmia should be treated as a medical emergency; In the event of suspected vitamin A deficiency, a 200,000 IU vitamin A dose should be administered orally, repeating the dose after 24 hours (half the dose for infants younger than one year). Vitamin A supplementation in endemic areas may cause a 23 to 30% reduction in the mortality rate of children aged between 6 months and five years, and attenuate the severity of diarrhea. The methods for the control of vitamin A deficiency are available in the short (supplementation with megadoses), medium (food fortification), and long run (diet diversification). CONCLUSION: There is evidence of vitamin A deficiency among Brazilian children. Pediatricians must be aware of the signs and symptoms of this disease, however sporadic they might be. It is of paramount importance that vitamin A be included in public policy plans so that we can ensure the survival of

  3. About recent star formation rates inferences

    NASA Astrophysics Data System (ADS)

    Cerviño, M.; Bongiovanni, A.; Hidalgo, S.

    2017-03-01

    Star Formation Rate (SFR) inferences are based in the so-called constant SFR approximation, where synthesis models are require to provide a calibration; we aims to study the key points of such approximation to produce accurate SFR inferences. We use the intrinsic algebra used in synthesis models, and we explore how SFR can be inferred from the integrated light without any assumption about the underling Star Formation history (SFH). We show that the constant SFR approximation is actually a simplified expression of more deeper characteristics of synthesis models: It is a characterization of the evolution of single stellar populations (SSPs), acting the SSPs as sensitivity curve over different measures of the SFH can be obtained. As results, we find that (1) the best age to calibrate SFR indices is the age of the observed system (i.e. about 13 Gyr for z = 0 systems); (2) constant SFR and steady-state luminosities are not requirements to calibrate the SFR ; (3) it is not possible to define a SFR single time scale over which the recent SFH is averaged, and we suggest to use typical SFR indices (ionizing flux, UV fluxes) together with no typical ones (optical/IR fluxes) to correct the SFR from the contribution of the old component of the SFH, we show how to use galaxy colors to quote age ranges where the recent component of the SFH is stronger/softer than the older component. Particular values of SFR calibrations are (almost) not affect by this work, but the meaning of what is obtained by SFR inferences does. In our framework, results as the correlation of SFR time scales with galaxy colors, or the sensitivity of different SFR indices to sort and long scale variations in the SFH, fit naturally. In addition, the present framework provides a theoretical guideline to optimize the available information from data/numerical experiments to improve the accuracy of SFR inferences. More info en Cerviño, Bongiovanni & Hidalgo A&A 588, 108C (2016)

  4. Iron deficiency in the tropics.

    PubMed

    Fleming, A F

    1982-06-01

    Iron in food is classified as belonging to the haem pool, the nonhaem pool, and extraneous sources. Haem iron is derived from vegetable and animal sources with varying bioavailability. Hookworm infestation of the intestinal tract affects 450 million people in the tropics. Schistosoma mansoni caused blood loss in 7 Egyptian patients of 7.5- 25.9 ml/day which is equivalent to a daily loss of iron of .6-7.3 mg daily urinary loss of iron in 9 Egyptian patients. Trichuris trichiura infestation by whipworm is widespread in children with blood loss of 5 ml/day/worm. The etiology of anemia in children besides iron deficiency includes malaria, bacterial or viral infections, folate deficiency and sickle-cell disease. Severe infections cause profound iron-deficiency anemia in children in central American and Malaysia. Plasmodium falciparum malaria-induced anaemia in tropical Africa lowers the mean haemoglobin concentration in the population by 2 g/dI, causing profound anaemia in some. The increased risk of premature delivery, low birthweight, fetal abnormalities, and fetal death is directly related to the degree of maternal anemia. Perinatal mortality was reduced from 38 to 4% in treated anemic mothers. Mental performance was significantly lower in anemic school children and improved after they received iron. Supplements of iron, soy-protein, calcium, and vitamins given to villagers with widespread malnutrition, iron deficiency, and hookworm infestation in Colombia reduced enteric infections in children. Severe iron-deficiency anemia was treated in adults in northern Nigeria by daily in Ferastral 10 ml, which is equivalent to 500 mg of iron per day. Choloroquine, folic acid, rephenium hydroxynaphthoate, and tetrachlorethylene treat adults with severe iron deficiency from hookworm infestation in rural tropical Africa. Blood transfusion is indicated if the patient is dying of anaemia or is pregnant with a haemoglobin concentration 6 gm/dl. In South East Asia, mg per day

  5. Respiratory chain complex I deficiency caused by mitochondrial DNA mutations

    PubMed Central

    Swalwell, Helen; Kirby, Denise M; Blakely, Emma L; Mitchell, Anna; Salemi, Renato; Sugiana, Canny; Compton, Alison G; Tucker, Elena J; Ke, Bi-Xia; Lamont, Phillipa J; Turnbull, Douglass M; McFarland, Robert; Taylor, Robert W; Thorburn, David R

    2011-01-01

    Defects of the mitochondrial respiratory chain are associated with a diverse spectrum of clinical phenotypes, and may be caused by mutations in either the nuclear or the mitochondrial genome (mitochondrial DNA (mtDNA)). Isolated complex I deficiency is the most common enzyme defect in mitochondrial disorders, particularly in children in whom family history is often consistent with sporadic or autosomal recessive inheritance, implicating a nuclear genetic cause. In contrast, although a number of recurrent, pathogenic mtDNA mutations have been described, historically, these have been perceived as rare causes of paediatric complex I deficiency. We reviewed the clinical and genetic findings in a large cohort of 109 paediatric patients with isolated complex I deficiency from 101 families. Pathogenic mtDNA mutations were found in 29 of 101 probands (29%), 21 in MTND subunit genes and 8 in mtDNA tRNA genes. Nuclear gene defects were inferred in 38 of 101 (38%) probands based on cell hybrid studies, mtDNA sequencing or mutation analysis (nuclear gene mutations were identified in 22 probands). Leigh or Leigh-like disease was the most common clinical presentation in both mtDNA and nuclear genetic defects. The median age at onset was higher in mtDNA patients (12 months) than in patients with a nuclear gene defect (3 months). However, considerable overlap existed, with onset varying from 0 to >60 months in both groups. Our findings confirm that pathogenic mtDNA mutations are a significant cause of complex I deficiency in children. In the absence of parental consanguinity, we recommend whole mitochondrial genome sequencing as a key approach to elucidate the underlying molecular genetic abnormality. PMID:21364701

  6. Statistical Inference at Work: Statistical Process Control as an Example

    ERIC Educational Resources Information Center

    Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia

    2008-01-01

    To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…

  7. Development of L2 Word-Meaning Inference while Reading

    ERIC Educational Resources Information Center

    Hamada, Megumi

    2009-01-01

    Ability to infer the meaning of unknown words encountered while reading plays an important role in learners' L2 word-knowledge development. Despite numerous findings reported on word-meaning inference, how learners develop this ability is still unclear. In order to provide a developmental inquiry into L2 word-meaning inference while reading, this…

  8. Statistical Inference at Work: Statistical Process Control as an Example

    ERIC Educational Resources Information Center

    Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia

    2008-01-01

    To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…

  9. Reasoning about Informal Statistical Inference: One Statistician's View

    ERIC Educational Resources Information Center

    Rossman, Allan J.

    2008-01-01

    This paper identifies key concepts and issues associated with the reasoning of informal statistical inference. I focus on key ideas of inference that I think all students should learn, including at secondary level as well as tertiary. I argue that a fundamental component of inference is to go beyond the data at hand, and I propose that statistical…

  10. Mediational Inferences in the Process of Counselor Judgment.

    ERIC Educational Resources Information Center

    Haase, Richard F.; And Others

    1983-01-01

    Replicates research on the process of moving from observations to clinical judgments. Counselors (N=20) made status inferences, attributional inferences, and diagnostic classification of clients based on case folders. Results suggest the clinical judgment process was stagewise mediated, and attributional inferences had little direct impact on…

  11. Development of L2 Word-Meaning Inference while Reading

    ERIC Educational Resources Information Center

    Hamada, Megumi

    2009-01-01

    Ability to infer the meaning of unknown words encountered while reading plays an important role in learners' L2 word-knowledge development. Despite numerous findings reported on word-meaning inference, how learners develop this ability is still unclear. In order to provide a developmental inquiry into L2 word-meaning inference while reading, this…

  12. Towards a neural implementation of causal inference in cue combination.

    PubMed

    Ma, Wei Ji; Rahmati, Masih

    2013-01-01

    Causal inference in sensory cue combination is the process of determining whether multiple sensory cues have the same cause or different causes. Psychophysical evidence indicates that humans closely follow the predictions of a Bayesian causal inference model. Here, we explore how Bayesian causal inference could be implemented using probabilistic population coding and plausible neural operations, but conclude that the resulting architecture is unrealistic.

  13. Inferring Epidemiological Dynamics with Bayesian Coalescent Inference: The Merits of Deterministic and Stochastic Models

    PubMed Central

    Popinga, Alex; Vaughan, Tim; Stadler, Tanja; Drummond, Alexei J.

    2015-01-01

    Estimation of epidemiological and population parameters from molecular sequence data has become central to the understanding of infectious disease dynamics. Various models have been proposed to infer details of the dynamics that describe epidemic progression. These include inference approaches derived from Kingman’s coalescent theory. Here, we use recently described coalescent theory for epidemic dynamics to develop stochastic and deterministic coalescent susceptible–infected–removed (SIR) tree priors. We implement these in a Bayesian phylogenetic inference framework to permit joint estimation of SIR epidemic parameters and the sample genealogy. We assess the performance of the two coalescent models and also juxtapose results obtained with a recently published birth–death-sampling model for epidemic inference. Comparisons are made by analyzing sets of genealogies simulated under precisely known epidemiological parameters. Additionally, we analyze influenza A (H1N1) sequence data sampled in the Canterbury region of New Zealand and HIV-1 sequence data obtained from known United Kingdom infection clusters. We show that both coalescent SIR models are effective at estimating epidemiological parameters from data with large fundamental reproductive number R0 and large population size S0. Furthermore, we find that the stochastic variant generally outperforms its deterministic counterpart in terms of error, bias, and highest posterior density coverage, particularly for smaller R0 and S0. However, each of these inference models is shown to have undesirable properties in certain circumstances, especially for epidemic outbreaks with R0 close to one or with small effective susceptible populations. PMID:25527289

  14. Impact of micronutrient deficiencies on obesity.

    PubMed

    García, Olga P; Long, Kurt Z; Rosado, Jorge L

    2009-10-01

    Micronutrient deficiencies have been found in obese individuals across age groups worldwide. While the effects of micronutrient deficiencies on human functions have been studied widely in different populations, there is limited information on how these micronutrient deficiencies affect obese populations. An examination of the available literature suggests associations exist between micronutrient deficiencies and obesity in different populations. These associations and possible mechanisms of the deficiencies' metabolic effects, such as their influence on leptin and insulin metabolism, are discussed here. Further studies are needed to clarify the roles of the different micronutrient deficiencies with respect to obesity and its comorbid conditions.

  15. Management of Iron Deficiency Anemia

    PubMed Central

    Jimenez, Kristine; Kulnigg-Dabsch, Stefanie

    2015-01-01

    Anemia affects one-fourth of the world’s population, and iron deficiency is the predominant cause. Anemia is associated with chronic fatigue, impaired cognitive function, and diminished well-being. Patients with iron deficiency anemia of unknown etiology are frequently referred to a gastroenterologist because in the majority of cases the condition has a gastrointestinal origin. Proper management improves quality of life, alleviates the symptoms of iron deficiency, and reduces the need for blood transfusions. Treatment options include oral and intravenous iron therapy; however, the efficacy of oral iron is limited in certain gastrointestinal conditions, such as inflammatory bowel disease, celiac disease, and autoimmune gastritis. This article provides a critical summary of the diagnosis and treatment of iron deficiency anemia. In addition, it includes a management algorithm that can help the clinician determine which patients are in need of further gastrointestinal evaluation. This facilitates the identification and treatment of the underlying condition and avoids the unnecessary use of invasive methods and their associated risks. PMID:27099596

  16. VISUAL DEFICIENCIES AND READING DISABILITY.

    ERIC Educational Resources Information Center

    ROSEN, CARL L.

    THE ROLE OF VISUAL SENSORY DEFICIENCIES IN THE CAUSATION READING DISABILITY IS DISCUSSED. PREVIOUS AND CURRENT RESEARCH STUDIES DEALING WITH SPECIFIC VISUAL PROBLEMS WHICH HAVE BEEN FOUND TO BE NEGATIVELY RELATED TO SUCCESSFUL READING ACHIEVEMENT ARE LISTED--(1) FARSIGHTEDNESS, (2) ASTIGMATISM, (3) BINOCULAR INCOORDINATIONS, AND (4) FUSIONAL…

  17. Growth hormone deficiency: an update.

    PubMed

    Audí, L; Fernández-Cancio, M; Camats, N; Carrascosa, A

    2013-03-01

    Growth hormone (GH) deficiency (GHD) in humans manifests differently according to the individual developmental stage (early after birth, during childhood, at puberty or in adulthood), the cause or mechanism (genetic, acquired or idiopathic), deficiency intensity and whether it is the only pituitary-affected hormone or is combined with that of other pituitary hormones or forms part of a complex syndrome. Growing knowledge of the genetic basis of GH deficiency continues to provide us with useful information to further characterise mutation types and mechanisms for previously described and new candidate genes. Despite these advances, a high proportion of GH deficiencies with no recognisable acquired basis continue to be labelled as idiopathic, although less frequently when they are congenital and/or familial. The clinical and biochemical diagnoses continue to be a conundrum despite efforts to harmonise biochemical assays for GH and IGF-1 analysis, probably because the diagnosis based on the so-called GH secretion stimulation tests will prove to be of limited usefulness for predicting therapy indications.

  18. Genetics Home Reference: arginase deficiency

    MedlinePlus

    ... of reactions that occurs in liver cells. This cycle processes excess nitrogen, generated when protein is used by the body, ... enzyme controls the final step of the urea cycle, which produces urea by removing nitrogen from arginine. In people with arginase deficiency , arginase ...

  19. Psychological Problems in Mental Deficiency.

    ERIC Educational Resources Information Center

    Sarason, Seymour B.; Doris, John

    A statement of goals and the rationale for organization precede a historical discussion of mental deficiency and society. The problem of labels like IQ and brain injured and the consequences of the diagnostic process are illustrated by case histories; case studies are also used to examine the criteria used to decide who is retarded and to discuss…

  20. Nutritional deficiencies after bariatric surgery.

    PubMed

    Davies, D J; Baxter, J M; Baxter, J N

    2007-09-01

    A current review of nutritional complications following bariatric procedures is presented, focusing on the most common and clinically important deficiencies. A brief outline of nutritional supplementation protocol is presented, highlighting the need for a standardized, national or international set of guidelines for pre- and postoperative nutritional screening and appropriate supplementation.

  1. Genetics Home Reference: transcobalamin deficiency

    MedlinePlus

    ... Epub 2008 Oct 29. Citation on PubMed Ratschmann R, Minkov M, Kis A, Hung C, Rupar T, Mühl A, Fowler B, Nexo E, Bodamer OA. Transcobalamin II deficiency at birth. Mol Genet Metab. 2009 Nov;98(3):285-8. doi: 10.1016/j.ymgme.2009.06.003. Epub 2009 Jun 6. ...

  2. Psychological Problems in Mental Deficiency.

    ERIC Educational Resources Information Center

    Sarason, Seymour B.; Doris, John

    A statement of goals and the rationale for organization precede a historical discussion of mental deficiency and society. The problem of labels like IQ and brain injured and the consequences of the diagnostic process are illustrated by case histories; case studies are also used to examine the criteria used to decide who is retarded and to discuss…

  3. Do diuretics cause magnesium deficiency?

    PubMed Central

    Davies, D L; Fraser, R

    1993-01-01

    1. Controlled trials, of which there are few, do not substantiate claims that diuretics play a role in causing magnesium deficiency. Consequently, the vast majority of patients taking conventional doses of thiazide diuretics (i.e. bendrofluazide 2.5 mg day-1 or equivalent) do not need magnesium supplements. On balance, potassium-sparing diuretics tend to increase serum and intracellular magnesium content; this should not be taken as evidence of prior magnesium deficiency. It remains theoretically possible that large doses of loop diuretics given more than once daily for long periods could induce negative magnesium balance and magnesium deficiency. However, it has been difficult to run appropriately controlled trials in conditions where such therapy is needed (i.e. heart failure) and until more reliable information becomes available no absolute recommendation can be made. 2. Methods for the measurement of intracellular free magnesium levels are now available and are more relevant to the assessment of magnesium deficiency than total intracellular magnesium content; the complex relationship between intracellular free and total magnesium content remains to be defined. Future work involving the effect of diuretics on intracellular free magnesium measurements should make every attempt to avoid the errors of trial design and multiple publication that litter current and past literature. PMID:8373706

  4. Case report: pyruvate kinase deficiency.

    PubMed

    Rothman, J M

    1995-09-01

    Pyruvate kinase deficiency is a rare cause of congenital hemolytic anemia. Despite a paucity of reports, splenectomy resulted in successful outcomes for two siblings with this disorder. The sisters were diagnosed at birth with profound jaundice and congenital nonspherocytic hemolytic anemia.

  5. Iron deficiency: the global perspective.

    PubMed

    Cook, J D; Skikne, B S; Baynes, R D

    1994-01-01

    The prevelance of IDA in industrialized countries has declined in recent decades, but there has been little change in the worldwide prevalence. IDA is currently estimated to affect more than 500 million people. Recent studies have indicated that anemia per se, the most common manifestation of iron deficiency, is less important from a public health standpoint than liabilities associated with tissue iron deficiency. The most important of the latter are an impairment in psychomotor development and cognitive function in infants and preschoolers, a deficit in work performance in adults, and an increase in the frequency of low birth weight, prematurity, and perinatal mortality in pregnancy. There have been several recent advances in combatting nutritional iron deficiency. One of the major problems has been in distinguishing iron deficiency from other causes of anemia seen epidemiologically such as malaria, HIV infection, chronic inflammation, hemoglobinopathies, and protein energy malnutrition. When combined with serum ferritin and hemoglobin determinations, the serum transferrin receptor assay is a valuable addition in epidemiologic surveys because it provides a quantitative measure of functional iron deficiency and it distinguishes true IDA from the anemia of chronic disease. The most difficult challenge is to develop effective methods of supplying iron to large segments of a population. Supplementation with iron tablets is suitable for only brief periods of need such as during pregnancy. The poor compliance with existing supplementation programs is believed to be due mainly to the gastrointestinal side effects of oral iron which can be eliminated by the use of a gastric delivery system. The most effective long-term strategy is to increase the intake of bioavailable iron in the diet. The customary approach has been to fortify a food staple such as wheat, rice, sugar, or salt, and thereby increase the iron intake of the entire population. However, because of concerns

  6. Iron refractory iron deficiency anemia

    PubMed Central

    De Falco, Luigia; Sanchez, Mayka; Silvestri, Laura; Kannengiesser, Caroline; Muckenthaler, Martina U.; Iolascon, Achille; Gouya, Laurent; Camaschella, Clara; Beaumont, Carole

    2013-01-01

    Iron refractory iron deficiency anemia is a hereditary recessive anemia due to a defect in the TMPRSS6 gene encoding Matriptase-2. This protein is a transmembrane serine protease that plays an essential role in down-regulating hepcidin, the key regulator of iron homeostasis. Hallmarks of this disease are microcytic hypochromic anemia, low transferrin saturation and normal/high serum hepcidin values. The anemia appears in the post-natal period, although in some cases it is only diagnosed in adulthood. The disease is refractory to oral iron treatment but shows a slow response to intravenous iron injections and partial correction of the anemia. To date, 40 different Matriptase-2 mutations have been reported, affecting all the functional domains of the large ectodomain of the protein. In vitro experiments on transfected cells suggest that Matriptase-2 cleaves Hemojuvelin, a major regulator of hepcidin expression and that this function is altered in this genetic form of anemia. In contrast to the low/undetectable hepcidin levels observed in acquired iron deficiency, in patients with Matriptase-2 deficiency, serum hepcidin is inappropriately high for the low iron status and accounts for the absent/delayed response to oral iron treatment. A challenge for the clinicians and pediatricians is the recognition of the disorder among iron deficiency and other microcytic anemias commonly found in pediatric patients. The current treatment of iron refractory iron deficiency anemia is based on parenteral iron administration; in the future, manipulation of the hepcidin pathway with the aim of suppressing it might become an alternative therapeutic approach. PMID:23729726

  7. Bayesian Estimation and Inference Using Stochastic Electronics.

    PubMed

    Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M; Hamilton, Tara J; Tapson, Jonathan; van Schaik, André

    2016-01-01

    In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream.

  8. Nonparametric inference of network structure and dynamics

    NASA Astrophysics Data System (ADS)

    Peixoto, Tiago P.

    The network structure of complex systems determine their function and serve as evidence for the evolutionary mechanisms that lie behind them. Despite considerable effort in recent years, it remains an open challenge to formulate general descriptions of the large-scale structure of network systems, and how to reliably extract such information from data. Although many approaches have been proposed, few methods attempt to gauge the statistical significance of the uncovered structures, and hence the majority cannot reliably separate actual structure from stochastic fluctuations. Due to the sheer size and high-dimensionality of many networks, this represents a major limitation that prevents meaningful interpretations of the results obtained with such nonstatistical methods. In this talk, I will show how these issues can be tackled in a principled and efficient fashion by formulating appropriate generative models of network structure that can have their parameters inferred from data. By employing a Bayesian description of such models, the inference can be performed in a nonparametric fashion, that does not require any a priori knowledge or ad hoc assumptions about the data. I will show how this approach can be used to perform model comparison, and how hierarchical models yield the most appropriate trade-off between model complexity and quality of fit based on the statistical evidence present in the data. I will also show how this general approach can be elegantly extended to networks with edge attributes, that are embedded in latent spaces, and that change in time. The latter is obtained via a fully dynamic generative network model, based on arbitrary-order Markov chains, that can also be inferred in a nonparametric fashion. Throughout the talk I will illustrate the application of the methods with many empirical networks such as the internet at the autonomous systems level, the global airport network, the network of actors and films, social networks, citations among

  9. Dynamical Inference in the Milky Way

    NASA Astrophysics Data System (ADS)

    Bovy, Jo

    Current and future surveys of the Galaxy contain a wealth of information about the structure and evolution of the Galactic disk and halo. Teasing out this information is complicated by measurement uncertainties, missing data, and sparse sampling. I develop and describe several applications of generative modeling--creating an approximate description of the probability of the data given the physical parameters of the system--to deal with these issues. I develop a method for inferring the Galactic potential from individual observations of stellar kinematics such as will be furnished by the upcoming Gaia space astrometry mission. This method takes uncertainties in our knowledge of the distribution function of stellar tracers into account through marginalization. I demonstrate the method by inferring the force law in the Solar System from observations of the positions and velocities of the eight planets at a single epoch. I apply a similar method to derive the Milky Way's circular velocity from observations of maser kinematics. I infer the velocity distribution of nearby stars from Hipparcos data, which only consist of tangential velocities, by forward modeling the underlying distribution with a flexible multi-Gaussian model. I characterize the contribution of several "moving groups"---overdensities of co-moving stars---to the full distribution. By studying the properties of stars in these moving groups, I show that they do not form a single-burst population and that they are most likely due to transient non-axisymmetric features of the disk, such as transient spiral structure. By forward modeling one such scenario, I show how the Hercules moving group can be traced around the Galaxy by future surveys, which would confirm that the Milky Way bar's outer Lindblad resonance lies near the Solar radius.

  10. Bayesian Estimation and Inference Using Stochastic Electronics

    PubMed Central

    Thakur, Chetan Singh; Afshar, Saeed; Wang, Runchun M.; Hamilton, Tara J.; Tapson, Jonathan; van Schaik, André

    2016-01-01

    In this paper, we present the implementation of two types of Bayesian inference problems to demonstrate the potential of building probabilistic algorithms in hardware using single set of building blocks with the ability to perform these computations in real time. The first implementation, referred to as the BEAST (Bayesian Estimation and Stochastic Tracker), demonstrates a simple problem where an observer uses an underlying Hidden Markov Model (HMM) to track a target in one dimension. In this implementation, sensors make noisy observations of the target position at discrete time steps. The tracker learns the transition model for target movement, and the observation model for the noisy sensors, and uses these to estimate the target position by solving the Bayesian recursive equation online. We show the tracking performance of the system and demonstrate how it can learn the observation model, the transition model, and the external distractor (noise) probability interfering with the observations. In the second implementation, referred to as the Bayesian INference in DAG (BIND), we show how inference can be performed in a Directed Acyclic Graph (DAG) using stochastic circuits. We show how these building blocks can be easily implemented using simple digital logic gates. An advantage of the stochastic electronic implementation is that it is robust to certain types of noise, which may become an issue in integrated circuit (IC) technology with feature sizes in the order of tens of nanometers due to their low noise margin, the effect of high-energy cosmic rays and the low supply voltage. In our framework, the flipping of random individual bits would not affect the system performance because information is encoded in a bit stream. PMID:27047326

  11. Temporal causal inference with stochastic audiovisual sequences.

    PubMed

    Locke, Shannon M; Landy, Michael S

    2017-01-01

    Integration of sensory information across multiple senses is most likely to occur when signals are spatiotemporally coupled. Yet, recent research on audiovisual rate discrimination indicates that random sequences of light flashes and auditory clicks are integrated optimally regardless of temporal correlation. This may be due to 1) temporal averaging rendering temporal cues less effective; 2) difficulty extracting causal-inference cues from rapidly presented stimuli; or 3) task demands prompting integration without concern for the spatiotemporal relationship between the signals. We conducted a rate-discrimination task (Exp 1), using slower, more random sequences than previous studies, and a separate causal-judgement task (Exp 2). Unisensory and multisensory rate-discrimination thresholds were measured in Exp 1 to assess the effects of temporal correlation and spatial congruence on integration. The performance of most subjects was indistinguishable from optimal for spatiotemporally coupled stimuli, and generally sub-optimal in other conditions, suggesting observers used a multisensory mechanism that is sensitive to both temporal and spatial causal-inference cues. In Exp 2, subjects reported whether temporally uncorrelated (but spatially co-located) sequences were perceived as sharing a common source. A unified percept was affected by click-flash pattern similarity and the maximum temporal offset between individual clicks and flashes, but not on the proportion of synchronous click-flash pairs. A simulation analysis revealed that the stimulus-generation algorithms of previous studies is likely responsible for the observed integration of temporally independent sequences. By combining results from Exps 1 and 2, we found better rate-discrimination performance for sequences that are more likely to be integrated than those that are not. Our results support the principle that multisensory stimuli are optimally integrated when spatiotemporally coupled, and provide insight

  12. Using alien coins to test whether simple inference is Bayesian.

    PubMed

    Cassey, Peter; Hawkins, Guy E; Donkin, Chris; Brown, Scott D

    2016-03-01

    Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we asked people for prior and posterior inferences about the probability that 1 of 2 coins would generate certain outcomes. Most participants' inferences were inconsistent with Bayes' rule. Only in the simplest version of the task did the majority of participants adhere to Bayes' rule, but even in that case, there was a significant proportion that failed to do so. The current results highlight the importance of close quantitative comparisons between Bayesian inference and human data at the individual-subject level when evaluating models of cognition.

  13. The boundaries of language and thought in deductive inference.

    PubMed

    Monti, Martin M; Parsons, Lawrence M; Osherson, Daniel N

    2009-07-28

    Is human thought fully embedded in language, or do some forms of thought operate independently? To directly address this issue, we focus on inference-making, a central feature of human cognition. In a 3T fMRI study we compare logical inferences relying on sentential connectives (e.g., not, or, if ... then) to linguistic inferences based on syntactic transformation of sentences involving ditransitive verbs (e.g., give, say, take). When contrasted with matched grammaticality judgments, logic inference alone recruited "core" regions of deduction [Brodmann area (BA) 10p and 8m], whereas linguistic inference alone recruited perisylvian regions of linguistic competence, among others (BA 21, 22, 37, 39, 44, and 45 and caudate). In addition, the two inferences commonly recruited a set of general "support" areas in frontoparietal cortex (BA 6, 7, 8, 40, and 47). The results indicate that logical inference is not embedded in natural language and confirm the relative modularity of linguistic processes.

  14. AIMS: Asteroseismic Inference on a Massive Scale

    NASA Astrophysics Data System (ADS)

    Reese, Daniel R.

    2016-11-01

    AIMS (Asteroseismic Inference on a Massive Scale) estimates stellar parameters and credible intervals/error bars in a Bayesian manner from a set of seismic frequency data and so-called classic constraints. To achieve reliable parameter estimates and computational efficiency it searches through a grid of pre-computed models using an MCMC algorithm; interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modeling consists of individual frequencies from peak-bagging, which can be complemented with classic spectroscopic constraints.

  15. Bayesian inference and the parametric bootstrap

    PubMed Central

    Efron, Bradley

    2013-01-01

    The parametric bootstrap can be used for the efficient computation of Bayes posterior distributions. Importance sampling formulas take on an easy form relating to the deviance in exponential families, and are particularly simple starting from Jeffreys invariant prior. Because of the i.i.d. nature of bootstrap sampling, familiar formulas describe the computational accuracy of the Bayes estimates. Besides computational methods, the theory provides a connection between Bayesian and frequentist analysis. Efficient algorithms for the frequentist accuracy of Bayesian inferences are developed and demonstrated in a model selection example. PMID:23843930

  16. Conditional statistical inference with multistage testing designs.

    PubMed

    Zwitser, Robert J; Maris, Gunter

    2015-03-01

    In this paper it is demonstrated how statistical inference from multistage test designs can be made based on the conditional likelihood. Special attention is given to parameter estimation, as well as the evaluation of model fit. Two reasons are provided why the fit of simple measurement models is expected to be better in adaptive designs, compared to linear designs: more parameters are available for the same number of observations; and undesirable response behavior, like slipping and guessing, might be avoided owing to a better match between item difficulty and examinee proficiency. The results are illustrated with simulated data, as well as with real data.

  17. Data free inference with processed data products

    SciTech Connect

    Chowdhary, K.; Najm, H. N.

    2014-07-12

    Here, we consider the context of probabilistic inference of model parameters given error bars or confidence intervals on model output values, when the data is unavailable. We introduce a class of algorithms in a Bayesian framework, relying on maximum entropy arguments and approximate Bayesian computation methods, to generate consistent data with the given summary statistics. Once we obtain consistent data sets, we pool the respective posteriors, to arrive at a single, averaged density on the parameters. This approach allows us to perform accurate forward uncertainty propagation consistent with the reported statistics.

  18. Identifying inference attacks against healthcare data repositories

    PubMed Central

    Vaidya, Jaideep; Shafiq, Basit; Jiang, Xiaoqian; Ohno-Machado, Lucila

    Health care data repositories play an important role in driving progress in medical research. Finding new pathways to discovery requires having adequate data and relevant analysis. However, it is critical to ensure the privacy and security of the stored data. In this paper, we identify a dangerous inference attack against naive suppression based approaches that are used to protect sensitive information. We base our attack on the querying system provided by the Healthcare Cost and Utilization Project, though it applies in general to any medical database providing a query capability. We also discuss potential solutions to this problem. PMID:24303279

  19. Inverse Ising Inference Using All the Data

    NASA Astrophysics Data System (ADS)

    Aurell, Erik; Ekeberg, Magnus

    2012-03-01

    We show that a method based on logistic regression, using all the data, solves the inverse Ising problem far better than mean-field calculations relying only on sample pairwise correlation functions, while still computationally feasible for hundreds of nodes. The largest improvement in reconstruction occurs for strong interactions. Using two examples, a diluted Sherrington-Kirkpatrick model and a two-dimensional lattice, we also show that interaction topologies can be recovered from few samples with good accuracy and that the use of l1 regularization is beneficial in this process, pushing inference abilities further into low-temperature regimes.

  20. Bayesian Inference in Satellite Gravity Inversion

    NASA Technical Reports Server (NTRS)

    Kis, K. I.; Taylor, Patrick T.; Wittmann, G.; Kim, Hyung Rae; Torony, B.; Mayer-Guerr, T.

    2005-01-01

    To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

  1. Bayesian Inference in Satellite Gravity Inversion

    NASA Technical Reports Server (NTRS)

    Kis, K. I.; Taylor, Patrick T.; Wittmann, G.; Kim, Hyung Rae; Torony, B.; Mayer-Guerr, T.

    2005-01-01

    To solve a geophysical inverse problem means applying measurements to determine the parameters of the selected model. The inverse problem is formulated as the Bayesian inference. The Gaussian probability density functions are applied in the Bayes's equation. The CHAMP satellite gravity data are determined at the altitude of 400 kilometer altitude over the South part of the Pannonian basin. The model of interpretation is the right vertical cylinder. The parameters of the model are obtained from the minimum problem solved by the Simplex method.

  2. Inferring Evolutionary Scenarios for Protein Domain Compositions

    NASA Astrophysics Data System (ADS)

    Wiedenhoeft, John; Krause, Roland; Eulenstein, Oliver

    Essential cellular processes are controlled by functional interactions of protein domains, which can be inferred from their evolutionary histories. Methods to reconstruct these histories are challenged by the complexity of reconstructing macroevolutionary events. In this work we model these events using a novel network-like structure that represents the evolution of domain combinations, called plexus. We describe an algorithm to find a plexus that represents the evolution of a given collection of domain histories as phylogenetic trees with the minimum number of macroevolutionary events, and demonstrate its effectiveness in practice.

  3. Inferring Boolean network states from partial information

    PubMed Central

    2013-01-01

    Networks of molecular interactions regulate key processes in living cells. Therefore, understanding their functionality is a high priority in advancing biological knowledge. Boolean networks are often used to describe cellular networks mathematically and are fitted to experimental datasets. The fitting often results in ambiguities since the interpretation of the measurements is not straightforward and since the data contain noise. In order to facilitate a more reliable mapping between datasets and Boolean networks, we develop an algorithm that infers network trajectories from a dataset distorted by noise. We analyze our algorithm theoretically and demonstrate its accuracy using simulation and microarray expression data. PMID:24006954

  4. Genetics Home Reference: familial glucocorticoid deficiency

    MedlinePlus

    ... familial glucocorticoid deficiency type 1 lead to defective trafficking of the receptor to the cell surface. J ... short stature, and natural killer cell deficiency in humans. J Clin Invest. 2012 Mar;122(3):814- ...

  5. Genetics Home Reference: beta-ureidopropionase deficiency

    MedlinePlus

    ... down N-carbamyl-beta-alanine to beta-alanine, ammonia, and carbon dioxide. Both beta-aminoisobutyric acid and ... beta-ureidopropionase deficiency Merck Manual Professional Version: Pyrimidine Metabolism Disorders Orphanet: Beta-ureidopropionase deficiency Patient Support and ...

  6. What Causes Alpha-1 Antitrypsin Deficiency?

    MedlinePlus

    ... this page from the NHLBI on Twitter. What Causes Alpha-1 Antitrypsin Deficiency? Alpha-1 antitrypsin (AAT) ... develop. The most common faulty gene that can cause AAT deficiency is called PiZ. If you inherit ...

  7. Iron deficiency--facts and fallacies.

    PubMed

    Oski, F A

    1985-04-01

    Iron deficiency occurs in all strata of society, is primarily a result of postnatal feeding practices and not due to congenital deficiencies of iron, can be prevented by appropriate dietary guidance, and, when present, produces important nonhematologic manifestations.

  8. Multiple Carboxylase Deficiency (Late Onset) Due to Deficiency of Biotinidase

    PubMed Central

    Mukhopadhyay, Debadatta; Das, Manoj Kumar; Dhar, Sandipan; Mukhopadhyay, Maya

    2014-01-01

    Biotinidase is a ubiquitous mammalian cell enzyme occurring in liver, serum and kidney. It cleaves biotin from biocytin, which is a cofactor for biotin dependent enzymes, namely the human carboxylases. Biotinidase deficiency is associated with a wide spectrum of neurological, dermatological, immunological and ophthalmological abnormalities. This is a case of a 3-year-old boy presenting with delayed developmental milestones, tachypnea, progressively increasing ataxia, alopecia and dermatitis, all which dramatically responded to high doses of biotin. PMID:25284861

  9. Iron deficiency and iron deficiency anaemia in women.

    PubMed

    Percy, Laura; Mansour, Diana; Fraser, Ian

    2017-04-01

    Iron deficiency (ID) is the most common micronutrient deficiency worldwide with >20% of women experiencing it during their reproductive lives. Hepcidin, a peptide hormone mostly produced by the liver, controls the absorption and regulation of iron. Understanding iron metabolism is pivotal in the successful management of ID and iron deficiency anaemia (IDA) using oral preparations, parenteral iron or blood transfusion. Oral preparations vary in their iron content and can result in gastrointestinal side effects. Parenteral iron is indicated when there are compliance/tolerance issues with oral iron, comorbidities which may affect absorption or ongoing iron losses that exceed absorptive capacity. It may also be the preferred option when rapid iron repletion is required to prevent physiological decompensation or given preoperatively for non-deferrable surgery. As gynaecologists, we focus on managing women's heavy menstrual bleeding (HMB) and assume that primary care clinicians are treating the associated ID/IDA. We now need to take the lead in diagnosing, managing and initiating treatment for ID/IDA and treating HMB simultaneously. This dual management will significantly improve their quality of life. In this chapter we will summarise the importance of iron in cellular functioning, describe how to diagnose ID/IDA and help clinicians choose between the available treatment options. Copyright © 2016. Published by Elsevier Ltd.

  10. Deficiency of Adenosine Deaminase 2 Causes Antibody Deficiency.

    PubMed

    Schepp, Johanna; Bulashevska, Alla; Mannhardt-Laakmann, Wilma; Cao, Hongzhi; Yang, Fang; Seidl, Maximilian; Kelly, Susan; Hershfield, Michael; Grimbacher, Bodo

    2016-04-01

    Determining the monogenic cause of antibody deficiency and immune dysregulation in a non-consanguineous family with healthy parents, two affected children, and one unaffected child. Whole Exome Sequencing (WES) was performed in the index family. WES results were confirmed by Sanger Sequencing. Dried plasma spots of the male patient and his mother were analyzed for ADA2 enzymatic activity. Following data analysis of WES, we found a compound heterozygous mutation in CECR1 (encoding adenosine deaminase 2, ADA2) that segregated in the two affected children. Enzyme activity measurement confirmed a severely diminished ADA2 activity in our patient. The 32 year old index patient was suffering from recurrent respiratory infections and was previously diagnosed with common variable immunodeficiency (CVID), showing no signs of vasculitis. His sister had a systemic lupus erythematosus (SLE)-like phenotype and died at age 17. Deficiency of ADA2 (DADA2) has been reported to cause vasculopathy and early-onset stroke. Our case suggests that it should also be considered when evaluating patients with antibody deficiencies and immune dysregulation syndromes.

  11. Quantum Enhanced Inference in Markov Logic Networks

    NASA Astrophysics Data System (ADS)

    Wittek, Peter; Gogolin, Christian

    2017-04-01

    Markov logic networks (MLNs) reconcile two opposing schools in machine learning and artificial intelligence: causal networks, which account for uncertainty extremely well, and first-order logic, which allows for formal deduction. An MLN is essentially a first-order logic template to generate Markov networks. Inference in MLNs is probabilistic and it is often performed by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling. An MLN has many regular, symmetric structures that can be exploited at both first-order level and in the generated Markov network. We analyze the graph structures that are produced by various lifting methods and investigate the extent to which quantum protocols can be used to speed up Gibbs sampling with state preparation and measurement schemes. We review different such approaches, discuss their advantages, theoretical limitations, and their appeal to implementations. We find that a straightforward application of a recent result yields exponential speedup compared to classical heuristics in approximate probabilistic inference, thereby demonstrating another example where advanced quantum resources can potentially prove useful in machine learning.

  12. Brain Connectivity Inference under Network Spatial Subsampling

    NASA Astrophysics Data System (ADS)

    da Rocha Amaral, Selene; Vieira, Gilson; Baccala, Luiz

    2013-03-01

    Neurophysiological time series analysis using functional Magnetic Resonance Magnetic Imaging (fMRI) data can be seen as tool to investigate how the complex networks of neuronal populations interact naturally leading to brain connectivity description issues where it is desirable to process as many simultaneous structures as possible to avoid misleading interaction inferences. Here we systematically use simulations to gauge how connectivity inference is affected when only subsets of network structures are considered through exploratory tools like Partial Directed Coherence (PDC) and confirmatory methods like Dynamic Causal Modeling (DCM). PDC is based on Granger causality and uses autoregressive models to expose the direction of information flow whereas DCM was proposed to characterize neural fMRI connectivity using prior knowlegde of possible connectivity structures. SPM software was used to simulate the full network fMRI data which was subject to realistic noise levels prior to analysis of network structure subsets. This work has been financially supported by FAPESP/CINAPCE 2011/0150-4

  13. Inferring epigenetic dynamics from kin correlations.

    PubMed

    Hormoz, Sahand; Desprat, Nicolas; Shraiman, Boris I

    2015-05-05

    Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal--a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available.

  14. Information Theory, Inference and Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Mackay, David J. C.

    2003-10-01

    Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. This textbook introduces theory in tandem with applications. Information theory is taught alongside practical communication systems, such as arithmetic coding for data compression and sparse-graph codes for error-correction. A toolbox of inference techniques, including message-passing algorithms, Monte Carlo methods, and variational approximations, are developed alongside applications of these tools to clustering, convolutional codes, independent component analysis, and neural networks. The final part of the book describes the state of the art in error-correcting codes, including low-density parity-check codes, turbo codes, and digital fountain codes -- the twenty-first century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, David MacKay's groundbreaking book is ideal for self-learning and for undergraduate or graduate courses. Interludes on crosswords, evolution, and sex provide entertainment along the way. In sum, this is a textbook on information, communication, and coding for a new generation of students, and an unparalleled entry point into these subjects for professionals in areas as diverse as computational biology, financial engineering, and machine learning.

  15. Inferring seizure frequency from brief EEG recordings.

    PubMed

    Westover, M Brandon; Bianchi, Matt T; Shafi, Mouhsin; Hoch, Daniel B; Cole, Andrew J; Chiappa, Keith; Cash, Sydney S

    2013-04-01

    Routine EEGs remain a cornerstone test in caring for people with epilepsy. Although rare, a self-limited seizure (clinical or electrographic only) may be observed during such brief EEGs. The implications of observing a seizure in this situation, especially with respect to inferring the underlying seizure frequency, are unclear. The issue is complicated by the inaccuracy of patient-reported estimations of seizure frequency. The treating clinician is often left to wonder whether the single seizure indicates very frequent seizures, or if it is of lesser significance. We applied standard concepts of probabilistic inference to a simple model of seizure incidence to provide some guidance for clinicians facing this situation. Our analysis establishes upper and lower bounds on the seizure rate implied by observing a single seizure during routine EEG. Not surprisingly, with additional information regarding the expected seizure rate, these bounds can be further constrained. This framework should aid the clinician in applying a more principled approach toward decision making in the setting of a single seizure on a routine EEG.

  16. PREMER: a Tool to Infer Biological Networks.

    PubMed

    Villaverde, Alejandro F; Becker, Kolja; Banga, Julio R

    2017-10-04

    Inferring the structure of unknown cellular networks is a main challenge in computational biology. Data-driven approaches based on information theory can determine the existence of interactions among network nodes automatically. However, the elucidation of certain features - such as distinguishing between direct and indirect interactions or determining the direction of a causal link - requires estimating information-theoretic quantities in a multidimensional space. This can be a computationally demanding task, which acts as a bottleneck for the application of elaborate algorithms to large-scale network inference problems. The computational cost of such calculations can be alleviated by the use of compiled programs and parallelization. To this end we have developed PREMER (Parallel Reverse Engineering with Mutual information & Entropy Reduction), a software toolbox that can run in parallel and sequential environments. It uses information theoretic criteria to recover network topology and determine the strength and causality of interactions, and allows incorporating prior knowledge, imputing missing data, and correcting outliers. PREMER is a free, open source software tool that does not require any commercial software. Its core algorithms are programmed in FORTRAN 90 and implement OpenMP directives. It has user interfaces in Python and MATLAB/Octave, and runs on Windows, Linux and OSX (https://sites.google.com/site/premertoolbox/).

  17. An Ada inference engine for expert systems

    NASA Technical Reports Server (NTRS)

    Lavallee, David B.

    1986-01-01

    The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.

  18. Graphical models for inferring single molecule dynamics

    PubMed Central

    2010-01-01

    Background The recent explosion of experimental techniques in single molecule biophysics has generated a variety of novel time series data requiring equally novel computational tools for analysis and inference. This article describes in general terms how graphical modeling may be used to learn from biophysical time series data using the variational Bayesian expectation maximization algorithm (VBEM). The discussion is illustrated by the example of single-molecule fluorescence resonance energy transfer (smFRET) versus time data, where the smFRET time series is modeled as a hidden Markov model (HMM) with Gaussian observables. A detailed description of smFRET is provided as well. Results The VBEM algorithm returns the model’s evidence and an approximating posterior parameter distribution given the data. The former provides a metric for model selection via maximum evidence (ME), and the latter a description of the model’s parameters learned from the data. ME/VBEM provide several advantages over the more commonly used approach of maximum likelihood (ML) optimized by the expectation maximization (EM) algorithm, the most important being a natural form of model selection and a well-posed (non-divergent) optimization problem. Conclusions The results demonstrate the utility of graphical modeling for inference of dynamic processes in single molecule biophysics. PMID:21034427

  19. Inferring social ties from geographic coincidences

    PubMed Central

    Crandall, David J.; Backstrom, Lars; Cosley, Dan; Suri, Siddharth; Huttenlocher, Daniel; Kleinberg, Jon

    2010-01-01

    We investigate the extent to which social ties between people can be inferred from co-occurrence in time and space: Given that two people have been in approximately the same geographic locale at approximately the same time, on multiple occasions, how likely are they to know each other? Furthermore, how does this likelihood depend on the spatial and temporal proximity of the co-occurrences? Such issues arise in data originating in both online and offline domains as well as settings that capture interfaces between online and offline behavior. Here we develop a framework for quantifying the answers to such questions, and we apply this framework to publicly available data from a social media site, finding that even a very small number of co-occurrences can result in a high empirical likelihood of a social tie. We then present probabilistic models showing how such large probabilities can arise from a natural model of proximity and co-occurrence in the presence of social ties. In addition to providing a method for establishing some of the first quantifiable estimates of these measures, our findings have potential privacy implications, particularly for the ways in which social structures can be inferred from public online records that capture individuals’ physical locations over time. PMID:21148099

  20. Inferring causal structure: a quantum advantage

    NASA Astrophysics Data System (ADS)

    Ried, Katja; Spekkens, Robert

    2014-03-01

    The problem of inferring causal relations from observed correlations is central to science, and extensive study has yielded both important conceptual insights and widely used practical applications. Yet some of the simplest questions are impossible to answer classically: for instance, if one observes correlations between two variables (such as taking a new medical treatment and the subject's recovery), does this show a direct causal influence, or is it due to some hidden common cause? We develop a framework for quantum causal inference, and show how quantum theory provides a unique advantage in this decision problem. The key insight is that certain quantum correlations can only arise from specific causal structures, whereas pairs of classical variables can exhibit any pattern of correlation regardless of whether they have a common cause or a direct-cause relation. For example, suppose one measures the same Pauli observable on two qubits. If they share a common cause, such as being prepared in an entangled state, then one never finds perfect (positive) correlations in every basis, whereas perfect anticorrelations are possible (if one prepares the singlet state). Conversely, if a channel connects the qubits, hence a direct causal influence, perfect anticorrelations are impossible.

  1. Causal inference, probability theory, and graphical insights.

    PubMed

    Baker, Stuart G

    2013-11-10

    Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design.

  2. Phylogenetic Inference From Conserved sites Alignments

    SciTech Connect

    grundy, W.N.; Naylor, G.J.P.

    1999-08-15

    Molecular sequences provide a rich source of data for inferring the phylogenetic relationships among species. However, recent work indicates that even an accurate multiple alignment of a large sequence set may yield an incorrect phylogeny and that the quality of the phylogenetic tree improves when the input consists only of the highly conserved, motif regions of the alignment. This work introduces two methods of producing multiple alignments that include only the conserved regions of the initial alignment. The first method retains conserved motifs, whereas the second retains individual conserved sites in the initial alignment. Using parsimony analysis on a mitochondrial data set containing 19 species among which the phylogenetic relationships are widely accepted, both conserved alignment methods produce better phylogenetic trees than the complete alignment. Unlike any of the 19 inference methods used before to analyze this data, both methods produce trees that are completely consistent with the known phylogeny. The motif-based method employs far fewer alignment sites for comparable error rates. For a larger data set containing mitochondrial sequences from 39 species, the site-based method produces a phylogenetic tree that is largely consistent with known phylogenetic relationships and suggests several novel placements.

  3. Inferring epigenetic dynamics from kin correlations

    PubMed Central

    Hormoz, Sahand; Desprat, Nicolas; Shraiman, Boris I.

    2015-01-01

    Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal—a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available. PMID:25902540

  4. Natural frequencies facilitate diagnostic inferences of managers

    PubMed Central

    Hoffrage, Ulrich; Hafenbrädl, Sebastian; Bouquet, Cyril

    2015-01-01

    In Bayesian inference tasks, information about base rates as well as hit rate and false-alarm rate needs to be integrated according to Bayes’ rule after the result of a diagnostic test became known. Numerous studies have found that presenting information in a Bayesian inference task in terms of natural frequencies leads to better performance compared to variants with information presented in terms of probabilities or percentages. Natural frequencies are the tallies in a natural sample in which hit rate and false-alarm rate are not normalized with respect to base rates. The present research replicates the beneficial effect of natural frequencies with four tasks from the domain of management, and with management students as well as experienced executives as participants. The percentage of Bayesian responses was almost twice as high when information was presented in natural frequencies compared to a presentation in terms of percentages. In contrast to most tasks previously studied, the majority of numerical responses were lower than the Bayesian solutions. Having heard of Bayes’ rule prior to the study did not affect Bayesian performance. An implication of our work is that textbooks explaining Bayes’ rule should teach how to represent information in terms of natural frequencies instead of how to plug probabilities or percentages into a formula. PMID:26157397

  5. Causal Inference for Spatial Constancy across Saccades

    PubMed Central

    Atsma, Jeroen; Maij, Femke; Koppen, Mathieu; Irwin, David E.; Medendorp, W. Pieter

    2016-01-01

    Our ability to interact with the environment hinges on creating a stable visual world despite the continuous changes in retinal input. To achieve visual stability, the brain must distinguish the retinal image shifts caused by eye movements and shifts due to movements of the visual scene. This process appears not to be flawless: during saccades, we often fail to detect whether visual objects remain stable or move, which is called saccadic suppression of displacement (SSD). How does the brain evaluate the memorized information of the presaccadic scene and the actual visual feedback of the postsaccadic visual scene in the computations for visual stability? Using a SSD task, we test how participants localize the presaccadic position of the fixation target, the saccade target or a peripheral non-foveated target that was displaced parallel or orthogonal during a horizontal saccade, and subsequently viewed for three different durations. Results showed different localization errors of the three targets, depending on the viewing time of the postsaccadic stimulus and its spatial separation from the presaccadic location. We modeled the data through a Bayesian causal inference mechanism, in which at the trial level an optimal mixing of two possible strategies, integration vs. separation of the presaccadic memory and the postsaccadic sensory signals, is applied. Fits of this model generally outperformed other plausible decision strategies for producing SSD. Our findings suggest that humans exploit a Bayesian inference process with two causal structures to mediate visual stability. PMID:26967730

  6. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, Robert M.; Kery, Marc; Royle, J. Andrew; Plattner, Matthias

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species- and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity.

  7. Models for inference in dynamic metacommunity systems

    USGS Publications Warehouse

    Dorazio, R.M.; Kery, M.; Royle, J. Andrew; Plattner, M.

    2010-01-01

    A variety of processes are thought to be involved in the formation and dynamics of species assemblages. For example, various metacommunity theories are based on differences in the relative contributions of dispersal of species among local communities and interactions of species within local communities. Interestingly, metacommunity theories continue to be advanced without much empirical validation. Part of the problem is that statistical models used to analyze typical survey data either fail to specify ecological processes with sufficient complexity or they fail to account for errors in detection of species during sampling. In this paper, we describe a statistical modeling framework for the analysis of metacommunity dynamics that is based on the idea of adopting a unified approach, multispecies occupancy modeling, for computing inferences about individual species, local communities of species, or the entire metacommunity of species. This approach accounts for errors in detection of species during sampling and also allows different metacommunity paradigms to be specified in terms of species-and location-specific probabilities of occurrence, extinction, and colonization: all of which are estimable. In addition, this approach can be used to address inference problems that arise in conservation ecology, such as predicting temporal and spatial changes in biodiversity for use in making conservation decisions. To illustrate, we estimate changes in species composition associated with the species-specific phenologies of flight patterns of butterflies in Switzerland for the purpose of estimating regional differences in biodiversity. ?? 2010 by the Ecological Society of America.

  8. On uncertain sightings and inference about extinction.

    PubMed

    Solow, Andrew R; Beet, Andrew R

    2014-08-01

    The extinction of many species can only be inferred from the record of sightings of individuals. Solow et al. (2012, Uncertain sightings and the extinction of the Ivory-billed Woodpecker. Conservation Biology 26:180-184) describe a Bayesian approach to such inference and apply it to a sighting record of the Ivory-billed Woodpecker (Campephilus principalis). A feature of this sighting record is that all uncertain sightings occurred after the most recent certain sighting. However, this appears to be an artifact. We extended this earlier work in 2 ways. First, we allowed for overlap in time between certain and uncertain sightings. Second, we considered 2 plausible statistical models of a sighting record. In one of these models, certain and uncertain sightings that are valid arise from the same process whereas in the other they arise from independent processes. We applied both models to the case of the Ivory-billed Woodpecker. The result from the first model did not favor extinction, whereas the result for the second model did. This underscores the importance, in applying tests for extinction, of understanding what could be called the natural history of the sighting record. © 2014 Society for Conservation Biology.

  9. Receptive Field Inference with Localized Priors

    PubMed Central

    Park, Mijung; Pillow, Jonathan W.

    2011-01-01

    The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets. PMID:22046110

  10. Efficient inference for hybrid dynamic Bayesian networks

    NASA Astrophysics Data System (ADS)

    Chang, Kuo Chu; Chen, Hongda

    2005-07-01

    This paper is a revision of a paper presented at the SPIE conference on Signal Processing, Senior Fusion, and Target Recognition XII, Aug. 2004, Orlando, Florida. The paper presented there appears (unrefereed) in SPIE Proceedings Vol. 5429. Bayesian networks for static as well as for dynamic cases have been the subject of a great deal of theoretical analysis and practical inference-algorithm development in the research community of artificial intelligence, machine learning, and pattern recognition. After summarizing the well-known theory of discrete and continuous Bayesian networks, we introduce an efficient reasoning scheme into hybrid Bayesian networks. In addition to illustrating the similarities between the dynamic Bayesian networks and the Kalman filter, we present a computationally efficient approach for the inference problem of hybrid dynamic Bayesian networks (HDBNs). The proposed method is based on the separation of the dynamic and static nodes, and subsequent hypercubic partitions via the decision tree algorithm. Experiments show that with high statistical confidence the novel algorithm used in the HDBN performs favorably in the trade-offs of computational complexity and accuracy performance, compared to other exact and approximate methods for applications with uncertainty in a dynamic system.

  11. Inferring Seizure Frequency From Brief EEG Recordings

    PubMed Central

    Westover, M. Brandon; Bianchi, Matt T.; Shafi, Mouhsin; Hoch, Daniel B.; Cole, Andrew J.; Chiappa, Keith; Cash, Sydney S.

    2012-01-01

    Routine EEGs remain a cornerstone test in caring for people with epilepsy. Although rare, a self-limited seizure (clinical or electrographic only) may be observed during such brief EEGs. The implications of observing a seizure in this situation, especially with respect to inferring the underlying seizure frequency, are unclear. The issue is complicated by the inaccuracy of patient-reported estimations of seizure frequency. The treating clinician is often left to wonder whether the single seizure indicates very frequent seizures, or if it is of lesser significance. We applied standard concepts of probabilistic inference to a simple model of seizure incidence to provide some guidance for clinicians facing this situation. Our analysis establishes upper and lower bounds on the seizure rate implied by observing a single seizure during routine EEG. Not surprisingly, with additional information regarding the expected seizure rate, these bounds can be further constrained. This framework should aid the clinician in applying a more principled approach toward decision making in the setting of a single seizure on a routine EEG. PMID:23545768

  12. Issues with inferring Internet topological attributes

    NASA Astrophysics Data System (ADS)

    Amini, Lisa D.; Shaikh, Anees; Schulzrinne, Henning G.

    2002-07-01

    A number of recent studies are based on data collected from routing tables of inter-domain routers utilizing Border Gateway Protocol (BGP) and tools, such as traceroute, to probe end-to-end paths. The goal is to infer Internet topological properties. However, as more data is collected, it becomes obvious that data intended to represent the same properties, if gathered at different points within the network, can depict significantly different characteristics. While systematic data collection from a number of network vantage points can reduce certain ambiguities, thus far, no methods have been reported for fully resolving these issues. The goal of our study was to quantify the effect these anomalies have on key Internet structural attributes. We report on our analysis of over 290,000 measurements from globally distributed sites. We contrast results obtained from router-level measurements with those obtained from BGP routing tables, and offer insights as to why certain inferred properties differ. We demonstrate that the effect on some attributes, such as the average path length and the AS degree distribution can be minimized through careful data collection techniques. We also illustrate how using this same data to model other attributes, such as the actual forwarding path between a pair of nodes, or the level of AS path asymmetry, can produce substantially misleading results.

  13. Cooperative inference: Features, objects, and collections.

    PubMed

    Searcy, Sophia Ray; Shafto, Patrick

    2016-10-01

    Cooperation plays a central role in theories of development, learning, cultural evolution, and education. We argue that existing models of learning from cooperative informants have fundamental limitations that prevent them from explaining how cooperation benefits learning. First, existing models are shown to be computationally intractable, suggesting that they cannot apply to realistic learning problems. Second, existing models assume a priori agreement about which concepts are favored in learning, which leads to a conundrum: Learning fails without precise agreement on bias yet there is no single rational choice. We introduce cooperative inference, a novel framework for cooperation in concept learning, which resolves these limitations. Cooperative inference generalizes the notion of cooperation used in previous models from omission of labeled objects to the omission values of features, labels for objects, and labels for collections of objects. The result is an approach that is computationally tractable, does not require a priori agreement about biases, applies to both Boolean and first-order concepts, and begins to approximate the richness of real-world concept learning problems. We conclude by discussing relations to and implications for existing theories of cognition, cognitive development, and cultural evolution. (PsycINFO Database Record

  14. Spatial Inference for Distributed Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Braverman, A. J.; Katzfuss, M.; Nguyen, H.

    2014-12-01

    Remote sensing data are inherently spatial, and a substantial portion of their value for scientific analyses derives from the information they can provide about spatially dependent processes. Geophysical variables such as atmopsheric temperature, cloud properties, humidity, aerosols and carbon dioxide all exhibit spatial patterns, and satellite observations can help us learn about the physical mechanisms driving them. However, remote sensing observations are often noisy and incomplete, so inferring properties of true geophysical fields from them requires some care. These data can also be massive, which is both a blessing and a curse: using more data drives uncertainties down, but also drives costs up, particularly when data are stored on different computers or in different physical locations. In this talk I will discuss a methodology for spatial inference on massive, distributed data sets that does not require moving large volumes of data. The idea is based on a combination of ideas including modeling spatial covariance structures with low-rank covariance matrices, and distributed estimation in sensor or wireless networks.

  15. Hierarchical Bayesian inference in the visual cortex

    NASA Astrophysics Data System (ADS)

    Lee, Tai Sing; Mumford, David

    2003-07-01

    Traditional views of visual processing suggest that early visual neurons in areas V1 and V2 are static spatiotemporal filters that extract local features from a visual scene. The extracted information is then channeled through a feedforward chain of modules in successively higher visual areas for further analysis. Recent electrophysiological recordings from early visual neurons in awake behaving monkeys reveal that there are many levels of complexity in the information processing of the early visual cortex, as seen in the long-latency responses of its neurons. These new findings suggest that activity in the early visual cortex is tightly coupled and highly interactive with the rest of the visual system. They lead us to propose a new theoretical setting based on the mathematical framework of hierarchical Bayesian inference for reasoning about the visual system. In this framework, the recurrent feedforward/feedback loops in the cortex serve to integrate top-down contextual priors and bottom-up observations so as to implement concurrent probabilistic inference along the visual hierarchy. We suggest that the algorithms of particle filtering and Bayesian-belief propagation might model these interactive cortical computations. We review some recent neurophysiological evidences that support the plausibility of these ideas. 2003 Optical Society of America

  16. Representing Documents via Latent Keyphrase Inference

    PubMed Central

    Liu, Jialu; Ren, Xiang; Shang, Jingbo; Cassidy, Taylor; Voss, Clare R.; Han, Jiawei

    2017-01-01

    Many text mining approaches adopt bag-of-words or n-grams models to represent documents. Looking beyond just the words, i.e., the explicit surface forms, in a document can improve a computer’s understanding of text. Being aware of this, researchers have proposed concept-based models that rely on a human-curated knowledge base to incorporate other related concepts in the document representation. But these methods are not desirable when applied to vertical domains (e.g., literature, enterprise, etc.) due to low coverage of in-domain concepts in the general knowledge base and interference from out-of-domain concepts. In this paper, we propose a data-driven model named Latent Keyphrase Inference (LAKI) that represents documents with a vector of closely related domain keyphrases instead of single words or existing concepts in the knowledge base. We show that given a corpus of in-domain documents, topical content units can be learned for each domain keyphrase, which enables a computer to do smart inference to discover latent document keyphrases, going beyond just explicit mentions. Compared with the state-of-art document representation approaches, LAKI fills the gap between bag-of-words and concept-based models by using domain keyphrases as the basic representation unit. It removes dependency on a knowledge base while providing, with keyphrases, readily interpretable representations. When evaluated against 8 other methods on two text mining tasks over two corpora, LAKI outperformed all. PMID:28229132

  17. Iron Deficiency in Autism and Asperger Syndrome.

    ERIC Educational Resources Information Center

    Latif, A.; Heinz, P.; Cook, R.

    2002-01-01

    Retrospective analysis of the full blood count and, when available, serum ferritin measurements of 96 children (52 with autism and 44 with Asperger syndrome) found six autistic children had iron deficiency and 12 of the 23 autistic children with serum ferritin measures were iron deficient. Far fewer Asperger children were iron deficient. Results…

  18. Iron Deficiency in Autism and Asperger Syndrome.

    ERIC Educational Resources Information Center

    Latif, A.; Heinz, P.; Cook, R.

    2002-01-01

    Retrospective analysis of the full blood count and, when available, serum ferritin measurements of 96 children (52 with autism and 44 with Asperger syndrome) found six autistic children had iron deficiency and 12 of the 23 autistic children with serum ferritin measures were iron deficient. Far fewer Asperger children were iron deficient. Results…

  19. [Clinical symptoms in IgA deficiency].

    PubMed

    De Oliveira-Serra, Flavio Augusto; Mosca, Tainá; Santos de Menezes, Maria da Conceição; Carvalho-Neves Forte, Wilma

    2017-01-01

    IgA deficiency is the most common primary immunodeficiency. Early diagnosis and clinical follow-up may improve the quality of life of patients with IgA deficiency. To this end, IgA deficiency should be further studied and better understood on its clinical manifestations. To determine IgA deficiency clinical manifestations. Cross-sectional, retrospective, exploratory study, where the medical records of 39 patients with IgA deficiency were analyzed. Among the analyzed cases, 10 patients were diagnosed with total IgA deficiency and 29 patients with partial IgA deficiency. Partial and total IgA deficiency main clinical manifestations were allergic rhinoconjunctivitis and allergic asthma. In total IgA deficiency, in addition to allergic diseases, a statistically significant number (p < 0.05) of cases of infection-related rhinosinusitis, tonsillitis and conjunctivitis were also observed. This study showed that the main clinical manifestations in IgA deficiency were allergic rhinoconjunctivitis and allergic asthma. In addition, patients with total IgA deficiency showed a significant increase in infection-related rhinosinusitis, tonsillitis and conjunctivitis, when compared with patients with partial IgA deficiency.

  20. Iron-induced nickel deficiency in pecan

    USDA-ARS?s Scientific Manuscript database

    Economic loss due to nickel (Ni) deficiency can occur in horticultural and agronomic crops. This study assesses impact of excessive iron (Fe) on expression of Ni deficiency in pecan [Carya illinoinensis (Wangenh.) K. Koch]. Field and greenhouse experiments found Ni deficiency to be inducible by ei...