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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. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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).

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. Multiple Instance Fuzzy Inference

    DTIC Science & Technology

    2015-12-02

    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...or learned from data. In multiple instance problems, the training data is ambiguously labeled. Instances are grouped into bags, labels of bags are

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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…

  16. Vitamin Deficiency Anemia

    MedlinePlus

    Vitamin deficiency anemia Overview By Mayo Clinic Staff Vitamin deficiency anemia is a lack of healthy red blood ... normal amounts of certain vitamins. Vitamins linked to vitamin deficiency anemia include folate, vitamin B-12 and vitamin ...

  17. Alpha-1 Antitrypsin Deficiency

    MedlinePlus

    ... 1 antitrypsin (an-tee-TRIP-sin) deficiency, or AAT deficiency, is a condition that raises your risk ... and other diseases. Some people who have severe AAT deficiency develop emphysema (em-fi-SE-ma)—often ...

  18. 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

  19. 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.

  20. 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

  1. 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.

  2. 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.

  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. 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.

  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. 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.

  8. 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/ ...

  9. Vitamin D Deficiency

    MedlinePlus

    Vitamin D Deficiency A Patient’s Guide Vitamin D helps the body absorb calcium. Along with calcium, it is vital ... for physicians about testing for, treating, and preventing vitamin D deficiency. These guidelines do not apply to people who ...

  10. Folate-deficiency anemia

    MedlinePlus

    ... medlineplus.gov/ency/article/000551.htm Folate-deficiency anemia To use the sharing features on this page, please enable JavaScript. Folate-deficiency anemia is a decrease in red blood cells (anemia) ...

  11. 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.

  12. 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

  13. 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.

  14. 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.…

  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. 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…

  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. 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.

  19. 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.

  20. Autism and Folate Deficiency

    DTIC Science & Technology

    2010-05-01

    W81XWH-09-1-0246 TITLE: Autism and Folate Deficiency PRINCIPAL INVESTIGATOR: Richard H. Finnell, Ph.D...5a. CONTRACT NUMBER W81XWH-09-1-0246 Autism and Folate Deficiency 5b. GRANT NUMBER AR080064-Concept Award 5c. PROGRAM ELEMENT NUMBER...risk factor for autism : alterations in m ethionine metabolism in autistic patients may be due to a functional folate deficiency, and folate receptor

  1. 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.

  2. Statistical Inference in Graphical Models

    DTIC Science & Technology

    2008-06-17

    Probabilistic Network Library ( PNL ). While not fully mature, PNL does provide the most commonly-used algorithms for inference and learning with the efficiency...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...mature and has been used for research purposes for several years, it is written in MATLAB and thus is not suitable to be used in real-time settings. PNL

  3. 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.

  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. Inferring the Why in Images

    DTIC Science & Technology

    2014-01-01

    images. To our knowledge, this challenging problem has not yet been extensively explored in computer vision. We present a novel learning based...automatically infers why people are performing actions in images by learning from visual data and written language. ∗denotes equal contribution 1 Report...explored in computer vision. We present a novel learning based framework that uses high-level visual recognition to infer why people are performing

  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.

  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. Iron induced nickel deficiency

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  10. 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…

  11. 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…

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. Iron deficiency anemia

    MedlinePlus

    ... GM. Disorders of iron homeostasis: iron deficiency and overload. In: Hoffman R, Benz EJ Jr, Silberstein LE, ... to achieve this important distinction for online health information and services. Learn more about A.D.A. ...

  19. [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.

  20. 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.

  1. Factor V deficiency

    MedlinePlus

    ... as many as 20 different proteins in blood plasma. These proteins are called blood coagulation factors. Factor ... You will be given fresh blood plasma or fresh frozen plasma infusions ... These treatments will correct the deficiency temporarily.

  2. 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 ...

  3. 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 ...

  4. 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

  5. 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…

  6. 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…

  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. 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.

  9. 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…

  10. 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.

  11. 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)…

  12. 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…

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. [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.

  7. 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.

  8. 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.

  9. 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.

  10. Fast, Flexible, Rational Inductive Inference

    DTIC Science & Technology

    2013-08-23

    learning phonetic categories – the sounds that make up speech – learning the words that those sounds appear in provides sufficiently strong constraints...first to be able to infer realistic phonetic categories directly from simulated speech data. Objective 2.2: Forming feature-based representations...lexicon in phonetic category acquisition. Psychological Review. Griffiths, T. L., Austerweil, J. L., & Berthiaume, V. G. (2012). Comparing the

  11. 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.

  12. 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.

  13. 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…

  14. 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.

  15. 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.

  16. 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'.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Genetics Home Reference: isolated growth hormone deficiency

    MedlinePlus

    ... Isolated growth hormone deficiency Educational Resources (10 links) Boston Children's Hospital CLIMB: Growth Hormone Deficiency Information Sheet (PDF) Disease InfoSearch: Isolated growth hormone deficiency ...

  2. Genetics Home Reference: proopiomelanocortin deficiency

    MedlinePlus

    ... Open All Close All Description Proopiomelanocortin (POMC) deficiency causes severe obesity that begins at an early age. In addition ... and severe obesity. POMC deficiency is a rare cause of obesity; POMC gene mutations are not frequently associated with ...

  3. 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.

  4. 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 ...

  5. Glucose-6-phosphate dehydrogenase deficiency

    MedlinePlus

    G6PD deficiency; Hemolytic anemia due to G6PD deficiency; Anemia - hemolytic due to G6PD deficiency ... Gallagher PG. Hemolytic anemias. In: Goldman L, Schafer AI, eds. Goldman's Cecil Medicine . 25th ed. Philadelphia, PA: Elsevier Saunders; 2016:chap 161. Janz ...

  6. 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.

  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. 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

  10. 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.

  11. 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.

  12. Iron-Deficiency Anemia (For Parents)

    MedlinePlus

    ... Your 1- to 2-Year-Old Iron-Deficiency Anemia KidsHealth > For Parents > Iron-Deficiency Anemia Print A ... common nutritional deficiency in children. About Iron-Deficiency Anemia Every red blood cell in the body contains ...

  13. How Is Iron-Deficiency Anemia Treated?

    MedlinePlus

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

  14. 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

  15. 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

  16. Inferring echolocation in ancient bats.

    PubMed

    Simmons, Nancy B; Seymour, Kevin L; Habersetzer, Jörg; Gunnell, Gregg F

    2010-08-19

    Laryngeal echolocation, used by most living bats to form images of their surroundings and to detect and capture flying prey, is considered to be a key innovation for the evolutionary success of bats, and palaeontologists have long sought osteological correlates of echolocation that can be used to infer the behaviour of fossil bats. Veselka et al. argued that the most reliable trait indicating echolocation capabilities in bats is an articulation between the stylohyal bone (part of the hyoid apparatus that supports the throat and larynx) and the tympanic bone, which forms the floor of the middle ear. They examined the oldest and most primitive known bat, Onychonycteris finneyi (early Eocene, USA), and argued that it showed evidence of this stylohyal-tympanic articulation, from which they concluded that O. finneyi may have been capable of echolocation. We disagree with their interpretation of key fossil data and instead argue that O. finneyi was probably not an echolocating bat.

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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

  5. Protein inference: A protein quantification perspective.

    PubMed

    He, Zengyou; Huang, Ting; Liu, Xiaoqing; Zhu, Peijun; Teng, Ben; Deng, Shengchun

    2016-08-01

    In mass spectrometry-based shotgun proteomics, protein quantification and protein identification are two major computational problems. To quantify the protein abundance, a list of proteins must be firstly inferred from the raw data. Then the relative or absolute protein abundance is estimated with quantification methods, such as spectral counting. Until now, most researchers have been dealing with these two processes separately. In fact, the protein inference problem can be regarded as a special protein quantification problem in the sense that truly present proteins are those proteins whose abundance values are not zero. Some recent published papers have conceptually discussed this possibility. However, there is still a lack of rigorous experimental studies to test this hypothesis. In this paper, we investigate the feasibility of using protein quantification methods to solve the protein inference problem. Protein inference methods aim to determine whether each candidate protein is present in the sample or not. Protein quantification methods estimate the abundance value of each inferred protein. Naturally, the abundance value of an absent protein should be zero. Thus, we argue that the protein inference problem can be viewed as a special protein quantification problem in which one protein is considered to be present if its abundance is not zero. Based on this idea, our paper tries to use three simple protein quantification methods to solve the protein inference problem effectively. The experimental results on six data sets show that these three methods are competitive with previous protein inference algorithms. This demonstrates that it is plausible to model the protein inference problem as a special protein quantification task, which opens the door of devising more effective protein inference algorithms from a quantification perspective. The source codes of our methods are available at: http://code.google.com/p/protein-inference/.

  6. 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.

  7. 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

  8. 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

  9. 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…

  10. 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

  11. 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.…

  12. 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.…

  13. 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…

  14. 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…

  15. 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.

  16. 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…

  17. 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.

  18. 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…

  19. 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…

  20. 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.…

  1. 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.

  2. 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…

  3. 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

  4. [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.

  5. 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

  6. 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.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  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. 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

  17. 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)

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. Vitamin B12 deficiency anemia

    MedlinePlus

    ... body tissues. There are many types of anemia. Vitamin B12 deficiency anemia is a low red blood cell count ... anemia often do well with treatment. Long-term vitamin B12 deficiency can cause nerve damage. This may be permanent ...

  6. 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…

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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 ...

  16. Genetics Home Reference: glucose phosphate isomerase deficiency

    MedlinePlus

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

  17. Genetics Home Reference: dopamine transporter deficiency syndrome

    MedlinePlus

    ... Genetics Home Health Conditions dopamine transporter deficiency syndrome dopamine transporter deficiency syndrome Enable Javascript to view the ... boxes. Download PDF Open All Close All Description Dopamine transporter deficiency syndrome is a rare movement disorder. ...

  18. Facts about Vitamin K Deficiency Bleeding

    MedlinePlus

    ... Button Information For... Media Policy Makers Facts about Vitamin K Deficiency Bleeding Recommend on Facebook Tweet Share Compartir Vitamins ... serious bleeding problems if not supplemented. What is Vitamin K Deficiency Bleeding or VKDB? Vitamin K deficiency bleeding or ...

  19. What Causes Alpha-1 Antitrypsin Deficiency?

    MedlinePlus

    ... Causes Alpha-1 Antitrypsin Deficiency? Alpha-1 antitrypsin (AAT) deficiency is an inherited disease. "Inherited" means it's ... parents to children through genes. Children who have AAT deficiency inherit two faulty AAT genes, one from ...

  20. How Is Alpha-1 Antitrypsin Deficiency Treated?

    MedlinePlus

    ... Alpha-1 Antitrypsin Deficiency Treated? Alpha-1 antitrypsin (AAT) deficiency has no cure, but its related lung ... pulmonary disease). If you have symptoms related to AAT deficiency, your doctor may recommend: Medicines called inhaled ...

  1. Primary Immune Deficiency Disease Genetics & Inheritance

    MedlinePlus

    ... twitter share with linkedin Primary Immune Deficiency Disease Genetics & Inheritance Primary Immune Deficiency Diseases (PIDDs) Primary Immune Deficiency Diseases (PIDDs) Types of PIDDs Genetics & Inheritance Talking to Your Doctor Featured Research Credit: ...

  2. Genetics Home Reference: lysosomal acid lipase deficiency

    MedlinePlus

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

  3. 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

  4. 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.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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

  10. 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

  11. 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 ...

  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: transcobalamin deficiency

    MedlinePlus

    ... Version: Failure to Thrive Merck Manual Consumer Version: Vitamin Deficiency Anemia Merck Manual Professional Version: Vitamin B12 Orphanet: ... Neutropenia Washington University, St. Louis: Neuromuscular Disease Center: Vitamin B12 (Cobalamin) ... Patient Support and Advocacy Resources (3 links) American ...

  14. Genetics Home Reference: tetrahydrobiopterin deficiency

    MedlinePlus

    ... named? Additional Information & Resources MedlinePlus (3 links) Encyclopedia: Serum Phenylalanine Screening Health Topic: Newborn Screening Health Topic: Phenylketonuria Genetic and Rare Diseases Information Center (1 link) Tetrahydrobiopterin deficiency Educational Resources ( ...

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. 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…

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  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. 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.

  4. Permutation inference for the general linear model

    PubMed Central

    Winkler, Anderson M.; Ridgway, Gerard R.; Webster, Matthew A.; Smith, Stephen M.; Nichols, Thomas E.

    2014-01-01

    Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more flexible with respect to the experimental design and nuisance variables, and conduct detailed simulations to identify the best method for settings that are typical for imaging research scenarios. We present a generic framework for permutation inference for complex general linear models (glms) when the errors are exchangeable and/or have a symmetric distribution, and show that, even in the presence of nuisance effects, these permutation inferences are powerful while providing excellent control of false positives in a wide range of common and relevant imaging research scenarios. We also demonstrate how the inference on glm parameters, originally intended for independent data, can be used in certain special but useful cases in which independence is violated. Detailed examples of common neuroimaging applications are provided, as well as a complete algorithm – the “randomise” algorithm – for permutation inference with the glm. PMID:24530839

  5. 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.

  6. "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…

  7. 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.

  8. 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…

  9. 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…

  10. 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.

  11. 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.

  12. 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…

  13. 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…

  14. 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

  15. 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…

  16. 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…

  17. 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.

  18. 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…

  19. 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.

  20. 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

  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. 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

  3. 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…

  4. 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.

  5. 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.

  6. 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…

  7. 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

  8. 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…

  9. 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.

  10. 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 ...

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. Spectral likelihood expansions for Bayesian inference

    NASA Astrophysics Data System (ADS)

    Nagel, Joseph B.; Sudret, Bruno

    2016-03-01

    A spectral approach to Bayesian inference is presented. It pursues the emulation of the posterior probability density. The starting point is a series expansion of the likelihood function in terms of orthogonal polynomials. From this spectral likelihood expansion all statistical quantities of interest can be calculated semi-analytically. The posterior is formally represented as the product of a reference density and a linear combination of polynomial basis functions. Both the model evidence and the posterior moments are related to the expansion coefficients. This formulation avoids Markov chain Monte Carlo simulation and allows one to make use of linear least squares instead. The pros and cons of spectral Bayesian inference are discussed and demonstrated on the basis of simple applications from classical statistics and inverse modeling.

  20. Unified Theory of Inference for Text Understanding

    DTIC Science & Technology

    1986-11-25

    reataurant script is recognized, script application would lead to inferences such as identifying the waiter as ’ ’the waiter who is employed by the...relations between the objects. Objects have names as a convenience for the system modeler, but the names are not used for purposes other than...intent is that we can consider talking to be a frame with a talker slot which must be filled by a person. This is just a convenient notation; the

  1. 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.

  2. Ambiguity and Uncertainty in Probabilistic Inference.

    DTIC Science & Technology

    1983-09-01

    Bruner , J. S. Going beyond the information given. In J. S. Bruner et al. (Eds.), Contemporary approaches to cognition. Cambridge, MA: Harvard University...82179the non-additivity of complementary probabilities, current psychological theories of risk, and Ellsberg’s original paradox. The model is tested in...most psychological work on inference has been guided by a Bayesian or subjectivist view of probability, increasing concerns have been expressed about

  3. 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

  4. 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.

  5. A Unified Approach to Abductive Inference

    DTIC Science & Technology

    2014-09-30

    performance hacks . Alchemy Lite allows for fast, exact inference for models formulated in terms of TML, as well as the ability to update models with...Kimelfeld (bennyk@gmail.com) Molham Aref (molham.aref@logicblox.com) Charles Rivers Analytics Avi Pfeffer (apfeffer@cra.com) Facebook ...works at Yahoo; now at Facebook ) BAE systems Gregory Sullivan (gregory.sullivan@baesystems.com) Raytheon Kenric P Nelson

  6. 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- ...

  7. Vitamin K deficiency bleeding of the newborn

    MedlinePlus

    Vitamin K deficiency bleeding of the newborn (VKDB) is a bleeding disorder in babies. It most often develops shortly ... Control and Prevention. Notes from the field: late vitamin K deficiency bleeding in infants whose parents declined vitamin K ...

  8. 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 ...

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. 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.

  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. 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.

  18. 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

  19. 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

  20. 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.

  1. 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

  2. Iron-induced nickel deficiency in pecan

    Technology Transfer Automated Retrieval System (TEKTRAN)

    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...

  3. 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…

  4. 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…

  5. 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.

  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. 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…

  8. Iodine deficiency disorders in Europe.

    PubMed Central

    Delange, F.; Bürgi, H.

    1989-01-01

    Recent data on iodine excretion in the urine of adults, adolescents and newborns and on the iodine content of breast milk indicate a high prevalence of iodine deficiency (moderate in many cases and severe in a few) in many European countries. These cases may manifest as subclinical hypothyroidism in neonates and as goitre in adolescents and adults. Lack of iodine causes not only goitre, but also mental deficiency, hearing loss and other neurological impairments, and short stature due to thyroid insufficiency during fetal development and childhood. Although iodinated salt is available theoretically in most countries where it is needed, its quality and share of the market are often unsatisfactory. In many countries where only household salt is iodinated the iodine content has been set too low owing to an overestimation of household salt consumption. Governments are therefore urged to pass legislation and provide means for efficient iodination of salt wherever this is necessary. PMID:2670299

  9. Iron deficiency and brain development.

    PubMed

    Lozoff, Betsy; Georgieff, Michael K

    2006-09-01

    Iron deficiency (ID) is common in pregnant women and infants worldwide. Rodent models show that ID during gestation/lactation alters neurometabolism, neurotransmitters, myelination, and gene/protein profiles before and after iron repletion at weaning. Human infants with iron deficiency anemia test lower in cognitive, motor, social-emotional, and neurophysiologic development than comparison group infants. Iron therapy does not consistently improve developmental outcome, with long-term differences observed. Poorer outcome has also been shown in human and monkey infants with fetal/neonatal ID. Recent randomized trials of infant iron supplementation show benefits, indicating that adverse effects can be prevented and/or reversed with iron earlier in development or before ID becomes severe or chronic. This body of research emphasizes the importance of protecting the developing brain from ID.

  10. Oestrogen deficiency after tubal ligation.

    PubMed

    Cattanach, J

    1985-04-13

    4 of 7 women who had undergone tubal ligation within the past seven years were found to have oestrogen excretion concentrations at ovulation below the tenth percentile. A disturbance in the oestrogen/progesterone ratio as a consequence of localised hypertension at the ovary, when the utero-ovarian arterial loop is occluded at tubal ligation, is proposed as a possible cause of oestrogen deficiency syndrome, dysfunctional uterine bleeding, and menorrhagia after tubal ligation. Similar pathophysiology may occur after hysterectomy with ovarian conservation.

  11. Congenital deficiency of factor VII.

    PubMed

    Sikka, M; Gomber, S; Madan, N; Rusia, U; Sharma, S

    1996-01-01

    A case of congenital factor VII deficiency in a five-year-old child is reported. The patient, born of a non-consanguineous marriage, presented with repeated bouts of epistaxis since childhood. The prothrombin time (PT) was markedly prolonged with a normal bleeding time (BT), partial thromboplastin time with Kaolin (PTTK) and platelet count. The patient has been on follow up for the last four years and is doing apparently well.

  12. Vitamin D deficiency and diabetes.

    PubMed

    Berridge, Michael J

    2017-03-24

    Vitamin D deficiency has been linked to the onset of diabetes. This review summarizes the role of Vitamin D in maintaining the normal release of insulin by the pancreatic beta cells (β-cells). Diabetes is initiated by the onset of insulin resistance. The β-cells can overcome this resistance by releasing more insulin, thus preventing hyperglycaemia. However, as this hyperactivity increases, the β-cells experience excessive Ca(2+) and reactive oxygen species (ROS) signalling that results in cell death and the onset of diabetes. Vitamin D deficiency contributes to both the initial insulin resistance and the subsequent onset of diabetes caused by β-cell death. Vitamin D acts to reduce inflammation, which is a major process in inducing insulin resistance. Vitamin D maintains the normal resting levels of both Ca(2+) and ROS that are elevated in the β-cells during diabetes. Vitamin D also has a very significant role in maintaining the epigenome. Epigenetic alterations are a feature of diabetes by which many diabetes-related genes are inactivated by hypermethylation. Vitamin D acts to prevent such hypermethylation by increasing the expression of the DNA demethylases that prevent hypermethylation of multiple gene promoter regions of many diabetes-related genes. What is remarkable is just how many cellular processes are maintained by Vitamin D. When Vitamin D is deficient, many of these processes begin to decline and this sets the stage for the onset of diseases such as diabetes.

  13. Current issues in iron deficiency.

    PubMed

    Baynes, R D; Cook, J D

    1996-03-01

    This brief review of developments relating to iron deficiency during the past year covers three main areas: iron supplementation, the regulation of iron absorption, and the use of the serum transferrin receptor for the assessment of iron status. The intermittent administration of iron supplement once or twice weekly rather than daily has been advocated by international health agencies in recent years, but radioiron absorption studies in human subjects have failed to demonstrate any absorptive advantage of the intermittent schedule. The value of prophylactic iron supplementation in elderly blood donors was evaluated and shown to offer limited benefit in maintaining donation frequency. A recent model of the regulation of iron absorption involving erythropoietic and store regulators is discussed and a recent article indicating a potential non-hematopoietic effect of hematopoietic growth factors on iron absorption by the gastrointestinal mucosal cell is reviewed. A new measure of functional iron deficiency, namely the serum transferrin receptor, is discussed, with particular reference to its mechanism of production and its great value in distinguishing iron deficiency anemia from the anemia of chronic disease.

  14. The Meniscus-Deficient Knee

    PubMed Central

    Rao, Allison J.; Erickson, Brandon J.; Cvetanovich, Gregory L.; Yanke, Adam B.; Bach, Bernard R.; Cole, Brian J.

    2015-01-01

    Meniscal tears are the most common knee injury, and partial meniscectomies are the most common orthopaedic surgical procedure. The injured meniscus has an impaired ability to distribute load and resist tibial translation. Partial or complete loss of the meniscus promotes early development of chondromalacia and osteoarthritis. The primary goal of treatment for meniscus-deficient knees is to provide symptomatic relief, ideally to delay advanced joint space narrowing, and ultimately, joint replacement. Surgical treatments, including meniscal allograft transplantation (MAT), high tibial osteotomy (HTO), and distal femoral osteotomy (DFO), are options that attempt to decrease the loads on the articular cartilage of the meniscus-deficient compartment by replacing meniscal tissue or altering joint alignment. Clinical and biomechanical studies have reported promising outcomes for MAT, HTO, and DFO in the postmeniscectomized knee. These procedures can be performed alone or in conjunction with ligament reconstruction or chondral procedures (reparative, restorative, or reconstructive) to optimize stability and longevity of the knee. Complications can include fracture, nonunion, patella baja, compartment syndrome, infection, and deep venous thrombosis. MAT, HTO, and DFO are effective options for young patients suffering from pain and functional limitations secondary to meniscal deficiency. PMID:26779547

  15. Mitochondrial cytochrome c oxidase deficiency.

    PubMed

    Rak, Malgorzata; Bénit, Paule; Chrétien, Dominique; Bouchereau, Juliette; Schiff, Manuel; El-Khoury, Riyad; Tzagoloff, Alexander; Rustin, Pierre

    2016-03-01

    As with other mitochondrial respiratory chain components, marked clinical and genetic heterogeneity is observed in patients with a cytochrome c oxidase deficiency. This constitutes a considerable diagnostic challenge and raises a number of puzzling questions. So far, pathological mutations have been reported in more than 30 genes, in both mitochondrial and nuclear DNA, affecting either structural subunits of the enzyme or proteins involved in its biogenesis. In this review, we discuss the possible causes of the discrepancy between the spectacular advances made in the identification of the molecular bases of cytochrome oxidase deficiency and the lack of any efficient treatment in diseases resulting from such deficiencies. This brings back many unsolved questions related to the frequent delay of clinical manifestation, variable course and severity, and tissue-involvement often associated with these diseases. In this context, we stress the importance of studying different models of these diseases, but also discuss the limitations encountered in most available disease models. In the future, with the possible exception of replacement therapy using genes, cells or organs, a better understanding of underlying mechanism(s) of these mitochondrial diseases is presumably required to develop efficient therapy.

  16. Progesterone Deficiency and Premature Labour

    PubMed Central

    Csapo, A. I.; Pohanka, O.; Kaihola, H. L.

    1974-01-01

    Plasma oestradiol 17β and progesterone levels in 11 patients admitted to hospital for threatened premature labour of unknown aetiology were compared with those of women at similar stages of gestation whose pregnancy was normal. Oestradiol levels in the study group were slightly higher than in the normal controls but their progesterone levels were significantly lower. This progesterone deficiency increased the oestradiol/progesterone ratio in the study group patients, and it increased still more as the progesterone withdrawal continued during premature labour. Since uterine activity during pregnancy is regulated by a balanced action of several factors a deficiency in progesterone, an opponent of uterine activity, creates a regulatory imbalance which, if uncorrected, provokes premature labour. An increase in uterine volume stimulates uterine activity, and the present study reinforced our previous conclusion that the uterine-volume/plasma-progesterone ratio is a more accurate measure of the state of regulatory balance than the progesterone level alone. The cause of the progesterone deficiency in these cases remains unexplained, but we suggest that placental growth and function are contributory factors. We are investigating ways of correcting the resulting imbalance in the regulatory mechanism. PMID:4812406

  17. Nutritional Deficiencies and Phospholipid Metabolism

    PubMed Central

    Gimenez, María S.; Oliveros, Liliana B.; Gomez, Nidia N.

    2011-01-01

    Phospholipids are important components of the cell membranes of all living species. They contribute to the physicochemical properties of the membrane and thus influence the conformation and function of membrane-bound proteins, such as receptors, ion channels, and transporters and also influence cell function by serving as precursors for prostaglandins and other signaling molecules and modulating gene expression through the transcription activation. The components of the diet are determinant for cell functionality. In this review, the effects of macro and micronutrients deficiency on the quality, quantity and metabolism of different phospholipids and their distribution in cells of different organs is presented. Alterations in the amount of both saturated and polyunsaturated fatty acids, vitamins A, E and folate, and other micronutrients, such as zinc and magnesium, are discussed. In all cases we observe alterations in the pattern of phospholipids, the more affected ones being phosphatidylcholine, phosphatidylethanolamine and sphingomyelin. The deficiency of certain nutrients, such as essential fatty acids, fat-soluble vitamins and some metals may contribute to a variety of diseases that can be irreversible even after replacement with normal amount of the nutrients. Usually, the sequelae are more important when the deficiency is present at an early age. PMID:21731449

  18. Mitochondrial Cytochrome c Oxidase Deficiency

    PubMed Central

    Rak, Malgorzata; Bénit, Paule; Chrétien, Dominique; Bouchereau, Juliette; Schiff, Manuel; El-Khoury, Riyad; Tzagoloff, Alexander; Rustin, Pierre

    2016-01-01

    As with other mitochondrial respiratory chain components, marked clinical and genetic heterogeneity is observed in patients with a cytochrome c oxidase deficiency. This constitutes a considerable diagnostic challenge and raises a number of puzzling questions. So far, pathological mutations have been reported in more than 30 genes, in both mitochondrial and nuclear DNA, affecting either structural subunits of the enzyme or proteins involved in its biogenesis. In this review, we discuss the possible causes of the discrepancy between the spectacular advances made in the identification of the molecular bases of cytochrome oxidase deficiency and the lack of any efficient treatment in diseases resulting from such deficiencies. This brings back many unsolved questions related to the frequent delay of clinical manifestation, variable course and severity, and tissue-involvement often associated with these diseases. In this context, we stress the importance to study different models of these diseases, but also discuss the limitations encountered in most available disease models. In the future, with the possible exception of replacement therapy using genes, cells or organs, a better understanding of underlying mechanism(s) of these mitochondrial diseases is presumably required to develop efficient therapy. PMID:26846578

  19. Flu Vaccine Guidance for Patients with Immune Deficiency

    MedlinePlus

    ... Guidance for Patients with Immune Deficiency Share | Flu Vaccine Guidance for Patients with Immune Deficiency This article ... should patients with immune deficiency be given the vaccine? Immune deficient patients have a decreased resistance to ...

  20. Genetics Home Reference: malonyl-CoA decarboxylase deficiency

    MedlinePlus

    ... deficiency of malonyl-CoA decarboxylase malonic aciduria malonyl-coenzyme A decarboxylase deficiency MCD deficiency Related Information How ... molecular characterization of nine new patients with malonyl-coenzyme A decarboxylase deficiency. J Inherit Metab Dis. 2007 ...

  1. Artificial intelligence models for predicting iron deficiency anemia and iron serum level based on accessible laboratory data.

    PubMed

    Azarkhish, Iman; Raoufy, Mohammad Reza; Gharibzadeh, Shahriar

    2012-06-01

    Iron deficiency anemia (IDA) is the most common nutritional deficiency worldwide. Measuring serum iron is time consuming, expensive and not available in most hospitals. In this study, based on four accessible laboratory data (MCV, MCH, MCHC, Hb/RBC), we developed an artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) to diagnose the IDA and to predict serum iron level. Our results represent that the neural network analysis is superior to ANFIS and logistic regression models in diagnosing IDA. Moreover, the results show that the ANN is likely to provide an accurate test for predicting serum iron levels with high accuracy and acceptable precision.

  2. 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

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Inferring cellular networks using probabilistic graphical models.

    PubMed

    Friedman, Nir

    2004-02-06

    High-throughput genome-wide molecular assays, which probe cellular networks from different perspectives, have become central to molecular biology. Probabilistic graphical models are useful for extracting meaningful biological insights from the resulting data sets. These models provide a concise representation of complex cellular networks by composing simpler submodels. Procedures based on well-understood principles for inferring such models from data facilitate a model-based methodology for analysis and discovery. This methodology and its capabilities are illustrated by several recent applications to gene expression data.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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.

  17. Deficiencies in the Management of Iron Deficiency Anemia During Childhood.

    PubMed

    Powers, Jacquelyn M; Daniel, Catherine L; McCavit, Timothy L; Buchanan, George R

    2016-04-01

    Limited high-quality evidence supports the management of iron deficiency anemia (IDA). To assess our institutional performance in this area, we retrospectively reviewed IDA treatment practices in 195 consecutive children referred to our center from 2006 to mid-2010. The majority of children were ≤4 years old (64%) and had nutritional IDA (74%). In 11- to 18-year-old patients (31%), the primary etiology was menorrhagia (42%). Many were referred directly to the emergency department and/or prescribed iron doses outside the recommended range. Poor medication adherence and being lost-to-follow-up were common. Substantial improvements are required in the management of IDA.

  18. 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.

  19. 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.

  20. 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.

  1. 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

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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.

  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. 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

  15. Toward reassessing data-deficient species.

    PubMed

    Bland, Lucie M; Bielby, Jon; Kearney, Stephen; Orme, C David L; Watson, James E M; Collen, Ben

    2016-10-03

    One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data-deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data-deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data-deficient assessments. To develop this, we reviewed 2879 data-deficient assessments in 6 animal groups and identified 8 main justifications for assigning data-deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data-deficient species slipping unnoticed toward extinction.

  16. Alcoholic Myelopathy and Nutritional Deficiency

    PubMed Central

    Koike, Haruki; Nakamura, Tomohiko; Ikeda, Shohei; Takahashi, Mie; Kawagashira, Yuichi; Iijima, Masahiro; Katsuno, Masahisa; Sobue, Gen

    2017-01-01

    A patient with chronic alcoholism presented with myelopathy and low serum folate and cobalamin levels. A 42-year-old alcoholic man had gait disturbance for 4 months. A neurological examination revealed marked spasticity with increased deep tendon reflexes and extensor plantar responses of the lower limbs. His cobalamin level was decreased and his serum folate level was particularly low. His plasma ammonia level was not increased. Abstinence and folic acid and cobalamin supplementation stopped the progression of his neurological deficits. This case indicates that nutritional deficiency should be monitored closely in patients with chronic alcoholism who present with myelopathy. PMID:28049986

  17. Thymic deficiency in Down's syndrome.

    PubMed

    Levin, S; Schlesinger, M; Handzel, Z; Hahn, T; Altman, Y; Czernobilsky, B; Boss, J

    1979-01-01

    Children with Down's syndrome (DS) often have small and abnormal thymuses, with lymphocyte depletion, diminution of the cortex, and loss of corticomedullary demarcation--a picture resembling thymic involution. Besides this, they have markedly enlarged Hassall's corpuscles, some surrounded by a sheath of lymphocytes. Patients with DS are known to have increased numbers of respiratory infections; they also have a higher incidence of lymphatic leukemia than do individuals who do not have DS. Studies of cell-mediated (thymic-dependent) immunity demonstrate that children with DS have both diminished numbers of T cells as well as functional deficiency of these cells.

  18. Practical aspects of gene regulatory inference via conditional inference forests from expression data.

    PubMed

    Bessonov, Kyrylo; Van Steen, Kristel

    2016-12-01

    Gene regulatory network (GRN) inference is an active area of research that facilitates understanding the complex interplays between biological molecules. We propose a novel framework to create such GRNs, based on Conditional Inference Forests (CIFs) as proposed by Strobl et al. Our framework consists of using ensembles of Conditional Inference Trees (CITs) and selecting an appropriate aggregation scheme for variant selection prior to network construction. We show on synthetic microarray data that taking the original implementation of CIFs with conditional permutation scheme (CIFcond ) may lead to improved performance compared to Breiman's implementation of Random Forests (RF). Among all newly introduced CIF-based methods and five network scenarios obtained from the DREAM4 challenge, CIFcond performed best. Networks derived from well-tuned CIFs, obtained by simply averaging P-values over tree ensembles (CIFmean ) are particularly attractive, because they combine adequate performance with computational efficiency. Moreover, thresholds for variable selection are based on significance levels for P-values and, hence, do not need to be tuned. From a practical point of view, our extensive simulations show the potential advantages of CIFmean -based methods. Although more work is needed to improve on speed, especially when fully exploiting the advantages of CITs in the context of heterogeneous and correlated data, we have shown that CIF methodology can be flexibly inserted in a framework to infer biological interactions. Notably, we confirmed biologically relevant interaction between IL2RA and FOXP1, linked to the IL-2 signaling pathway and to type 1 diabetes.

  19. Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference.

    PubMed

    Rahmati, Vahid; Kirmse, Knut; Marković, Dimitrije; Holthoff, Knut; Kiebel, Stefan J

    2016-02-01

    Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits.

  20. Inferring Neuronal Dynamics from Calcium Imaging Data Using Biophysical Models and Bayesian Inference

    PubMed Central

    Rahmati, Vahid; Kirmse, Knut; Marković, Dimitrije; Holthoff, Knut; Kiebel, Stefan J.

    2016-01-01

    Calcium imaging has been used as a promising technique to monitor the dynamic activity of neuronal populations. However, the calcium trace is temporally smeared which restricts the extraction of quantities of interest such as spike trains of individual neurons. To address this issue, spike reconstruction algorithms have been introduced. One limitation of such reconstructions is that the underlying models are not informed about the biophysics of spike and burst generations. Such existing prior knowledge might be useful for constraining the possible solutions of spikes. Here we describe, in a novel Bayesian approach, how principled knowledge about neuronal dynamics can be employed to infer biophysical variables and parameters from fluorescence traces. By using both synthetic and in vitro recorded fluorescence traces, we demonstrate that the new approach is able to reconstruct different repetitive spiking and/or bursting patterns with accurate single spike resolution. Furthermore, we show that the high inference precision of the new approach is preserved even if the fluorescence trace is rather noisy or if the fluorescence transients show slow rise kinetics lasting several hundred milliseconds, and inhomogeneous rise and decay times. In addition, we discuss the use of the new approach for inferring parameter changes, e.g. due to a pharmacological intervention, as well as for inferring complex characteristics of immature neuronal circuits. PMID:26894748

  1. Children's inference generation: The role of vocabulary and working memory.

    PubMed

    Currie, Nicola Kate; Cain, Kate

    2015-09-01

    Inferences are crucial to successful discourse comprehension. We assessed the contributions of vocabulary and working memory to inference making in children aged 5 and 6years (n=44), 7 and 8years (n=43), and 9 and 10years (n=43). Children listened to short narratives and answered questions to assess local and global coherence inferences after each one. Analysis of variance (ANOVA) confirmed developmental improvements on both types of inference. Although standardized measures of both vocabulary and working memory were correlated with inference making, multiple regression analyses determined that vocabulary was the key predictor. For local coherence inferences, only vocabulary predicted unique variance for the 6- and 8-year-olds; in contrast, none of the variables predicted performance for the 10-year-olds. For global coherence inferences, vocabulary was the only unique predictor for each age group. Mediation analysis confirmed that although working memory was associated with the ability to generate local and global coherence inferences in 6- to 10-year-olds, the effect was mediated by vocabulary. We conclude that vocabulary knowledge supports inference making in two ways: through knowledge of word meanings required to generate inferences and through its contribution to memory processes.

  2. Mevalonate kinase deficiency: current perspectives

    PubMed Central

    Favier, Leslie A; Schulert, Grant S

    2016-01-01

    Mevalonate kinase deficiency (MKD) is a recessively inherited autoinflammatory disorder with a spectrum of manifestations, including the well-defined clinical phenotypes of hyperimmunoglobulinemia D and periodic fever syndrome and mevalonic aciduria. Patients with MKD have recurrent attacks of hyperinflammation associated with fever, abdominal pain, arthralgias, and mucocutaneous lesions, and more severely affected patients also have dysmorphisms and central nervous system anomalies. MKD is caused by mutations in the gene encoding mevalonate kinase, with the degree of residual enzyme activity largely determining disease severity. Mevalonate kinase is essential for the biosynthesis of nonsterol isoprenoids, which mediate protein prenylation. Although the precise pathogenesis of MKD remains unclear, increasing evidence suggests that deficiency in protein prenylation leads to innate immune activation and systemic hyperinflammation. Given the emerging understanding of MKD as an autoinflammatory disorder, recent treatment approaches have largely focused on cytokine-directed biologic therapy. Herein, we review the current genetic and pathologic understanding of MKD, its various clinical phenotypes, and the evolving treatment approach for this multifaceted disorder. PMID:27499643

  3. Management of ornithine transcarbamylase deficiency in pregnancy.

    PubMed

    Mendez-Figueroa, Hector; Lamance, Kerri; Sutton, V Reid; Aagaard-Tillery, Kjersti; Van den Veyver, Ignatia

    2010-11-01

    Ornithine transcarbamylase (OTC) deficiency is the most common enzymatic deficiency in the urea cycle. In catabolic states, such as the intrapartum and immediate postpartum periods, hyperammonemic comas with permanent neurological damage and death can develop. We report six cases of OTC deficiency during pregnancy managed at our institution and review the literature on OTC deficiency during pregnancy. Using the patient database from our Metabolic Clinic, pregnant OTC deficiency carriers were identified. The antenatal, intrapartum, and postpartum periods were analyzed. Corresponding literature was reviewed and an extensive multidisciplinary management plan developed. All six pregnant women had favorable outcomes. No hyperammonemic episodes occurred, and intensive care unit admissions and hemodialysis were not required. Although risk to women with OTC deficiency during the intra- and postpartum period exists, multidisciplinary management and a coherent plan usually result in successful labor, delivery, and postpartum. A comprehensive plan for patients who develop hyperammonemia is recommended.

  4. Human brain lesion-deficit inference remapped.

    PubMed

    Mah, Yee-Haur; Husain, Masud; Rees, Geraint; Nachev, Parashkev

    2014-09-01

    Our knowledge of the anatomical organization of the human brain in health and disease draws heavily on the study of patients with focal brain lesions. Historically the first method of mapping brain function, it is still potentially the most powerful, establishing the necessity of any putative neural substrate for a given function or deficit. Great inferential power, however, carries a crucial vulnerability: without stronger alternatives any consistent error cannot be easily detected. A hitherto unexamined source of such error is the structure of the high-dimensional distribution of patterns of focal damage, especially in ischaemic injury-the commonest aetiology in lesion-deficit studies-where the anatomy is naturally shaped by the architecture of the vascular tree. This distribution is so complex that analysis of lesion data sets of conventional size cannot illuminate its structure, leaving us in the dark about the presence or absence of such error. To examine this crucial question we assembled the largest known set of focal brain lesions (n = 581), derived from unselected patients with acute ischaemic injury (mean age = 62.3 years, standard deviation = 17.8, male:female ratio = 0.547), visualized with diffusion-weighted magnetic resonance imaging, and processed with validated automated lesion segmentation routines. High-dimensional analysis of this data revealed a hidden bias within the multivariate patterns of damage that will consistently distort lesion-deficit maps, displacing inferred critical regions from their true locations, in a manner opaque to replication. Quantifying the size of this mislocalization demonstrates that past lesion-deficit relationships estimated with conventional inferential methodology are likely to be significantly displaced, by a magnitude dependent on the unknown underlying lesion-deficit relationship itself. Past studies therefore cannot be retrospectively corrected, except by new knowledge that would render them redundant

  5. New insights into iron deficiency and iron deficiency anemia.

    PubMed

    Camaschella, Clara

    2017-02-13

    Recent advances in iron metabolism have stimulated new interest in iron deficiency (ID) and its anemia (IDA), common conditions worldwide. Absolute ID/IDA, i.e. the decrease of total body iron, is easily diagnosed based on decreased levels of serum ferritin and transferrin saturation. Relative lack of iron in specific organs/tissues, and IDA in the context of inflammatory disorders, are diagnosed based on arbitrary cut offs of ferritin and transferrin saturation and/or marker combination (as the soluble transferrin receptor/ferritin index) in an appropriate clinical context. Most ID patients are candidate to traditional treatment with oral iron salts, while high hepcidin levels block their absorption in inflammatory disorders. New iron preparations and new treatment modalities are available: high-dose intravenous iron compounds are becoming popular and indications to their use are increasing, although long-term side effects remain to be evaluated.

  6. Active Inference, homeostatic regulation and adaptive behavioural control.

    PubMed

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

    2015-11-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference.

  7. The role of causal models in analogical inference.

    PubMed

    Lee, Hee Seung; Holyoak, Keith J

    2008-09-01

    Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs and in particular on shared higher order relations. In contrast, work in philosophy of science suggests that analogical inference is also guided by causal models of the source and target. In 3 experiments, the authors explored the possibility that people may use causal models to assess the strength of analogical inferences. Experiments 1-2 showed that reducing analogical overlap by eliminating a shared causal relation (a preventive cause present in the source) from the target increased inductive strength even though it decreased similarity of the analogs. These findings were extended in Experiment 3 to cross-domain analogical inferences based on correspondences between higher order causal relations. Analogical inference appears to be mediated by building and then running a causal model. The implications of the present findings for theories of both analogy and causal inference are discussed.

  8. Active Inference, homeostatic regulation and adaptive behavioural control

    PubMed Central

    Pezzulo, Giovanni; Rigoli, Francesco; Friston, Karl

    2015-01-01

    We review a theory of homeostatic regulation and adaptive behavioural control within the Active Inference framework. Our aim is to connect two research streams that are usually considered independently; namely, Active Inference and associative learning theories of animal behaviour. The former uses a probabilistic (Bayesian) formulation of perception and action, while the latter calls on multiple (Pavlovian, habitual, goal-directed) processes for homeostatic and behavioural control. We offer a synthesis these classical processes and cast them as successive hierarchical contextualisations of sensorimotor constructs, using the generative models that underpin Active Inference. This dissolves any apparent mechanistic distinction between the optimization processes that mediate classical control or learning. Furthermore, we generalize the scope of Active Inference by emphasizing interoceptive inference and homeostatic regulation. The ensuing homeostatic (or allostatic) perspective provides an intuitive explanation for how priors act as drives or goals to enslave action, and emphasises the embodied nature of inference. PMID:26365173

  9. Cancer evolution: mathematical models and computational inference.

    PubMed

    Beerenwinkel, Niko; Schwarz, Roland F; Gerstung, Moritz; Markowetz, Florian

    2015-01-01

    Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy.

  10. Bayesian Inference for Nonnegative Matrix Factorisation Models

    PubMed Central

    Cemgil, Ali Taylan

    2009-01-01

    We describe nonnegative matrix factorisation (NMF) with a Kullback-Leibler (KL) error measure in a statistical framework, with a hierarchical generative model consisting of an observation and a prior component. Omitting the prior leads to the standard KL-NMF algorithms as special cases, where maximum likelihood parameter estimation is carried out via the Expectation-Maximisation (EM) algorithm. Starting from this view, we develop full Bayesian inference via variational Bayes or Monte Carlo. Our construction retains conjugacy and enables us to develop more powerful models while retaining attractive features of standard NMF such as monotonic convergence and easy implementation. We illustrate our approach on model order selection and image reconstruction. PMID:19536273

  11. SERIES - Satellite Emission Range Inferred Earth Surveying

    NASA Technical Reports Server (NTRS)

    Macdoran, P. F.; Spitzmesser, D. J.; Buennagel, L. A.

    1983-01-01

    The Satellite Emission Range Inferred Earth Surveying (SERIES) concept is based on the utilization of NAVSTAR Global Positioning System (GPS) radio transmissions without any satellite modifications and in a totally passive mode. The SERIES stations are equipped with lightweight 1.5 m diameter dish antennas mounted on trailers. A series baseline measurement accuracy demonstration is considered, taking into account a 100 meter baseline estimation from approximately one hour of differential Doppler data. It is planned to conduct the next phase of experiments on a 150 m baseline. Attention is given to details regarding future baseline measurement accuracy demonstrations, aspects of ionospheric calibration in connection with subdecimeter baseline accuracy requirements of geodesy, and advantages related to the use of the differential Doppler or pseudoranging mode.

  12. Seasonal constraints on inferred planetary heat content

    NASA Astrophysics Data System (ADS)

    McKinnon, Karen A.; Huybers, Peter

    2016-10-01

    Planetary heating can be quantified using top of the atmosphere energy fluxes or through monitoring the heat content of the Earth system. It has been difficult, however, to compare the two methods with each other because of biases in satellite measurements and incomplete spatial coverage of ocean observations. Here we focus on the the seasonal cycle whose amplitude is large relative to satellite biases and observational errors. The seasonal budget can be closed through inferring contributions from high-latitude oceans and marginal seas using the covariance structure of National Center for Atmospheric Research (NCAR) Community Earth System Model (CESM1). In contrast, if these regions are approximated as the average across well-observed regions, the amplitude of the seasonal cycle is overestimated relative to satellite constraints. Analysis of the same CESM1 simulation indicates that complete measurement of the upper ocean would increase the magnitude and precision of interannual trend estimates in ocean heating more than fully measuring the deep ocean.

  13. Migration of objects and inferences across episodes.

    PubMed

    Hannigan, Sharon L; Reinitz, Mark Tippens

    2003-04-01

    Participants viewed episodes in the form of a series of photographs portraying ordinary routines (e.g., eating at a restaurant) and later received a recognition test. In Experiment 1, it was shown that objects (e.g., a vase of flowers, a pewter lantern) that appeared in a single episode during the study phase migrated between memories of episodes described by the same abstract schema (e.g., from Restaurant Episode A at study to Restaurant Episode B at test), and not between episodes anchored by different schemas. In Experiment 2, it was demonstrated that backward causal inferences from one study episode influenced memories of other episodes described by the same schema, and that high-schema-relevant items viewed in one episode were sometimes remembered as having occurred in another episode of the same schematic type.

  14. A Graphical Approach to Relatedness Inference

    PubMed Central

    Almudevar, Anthony

    2007-01-01

    The estimation of relatedness structure in natural populations using molecular marker data has become an important tool in population biology, resulting in a variety of estimation procedures for specific sampling scenarios. In this article a general approach is proposed, in which the detailed relationship structure, typically a pedigree graph or partition, is considered to be the object of inference. This makes available tools used in complex model selection theory which have demonstrated effectiveness. An important advantage of this approach is that it permits a fully Bayesian approach to the problem, providing a principled and accessible way to measure statistical error. The approach is demonstrated by applying the minimum description length principle. This technique is used in model selection to provide a rational way of comparing models of varying complexity. We show how the resulting score may be interpreted and applied as a Bayesian posterior density. PMID:17169391

  15. Automated adaptive inference of phenomenological dynamical models

    NASA Astrophysics Data System (ADS)

    Daniels, Bryan C.; Nemenman, Ilya

    2015-08-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

  16. Cancer Evolution: Mathematical Models and Computational Inference

    PubMed Central

    Beerenwinkel, Niko; Schwarz, Roland F.; Gerstung, Moritz; Markowetz, Florian

    2015-01-01

    Cancer is a somatic evolutionary process characterized by the accumulation of mutations, which contribute to tumor growth, clinical progression, immune escape, and drug resistance development. Evolutionary theory can be used to analyze the dynamics of tumor cell populations and to make inference about the evolutionary history of a tumor from molecular data. We review recent approaches to modeling the evolution of cancer, including population dynamics models of tumor initiation and progression, phylogenetic methods to model the evolutionary relationship between tumor subclones, and probabilistic graphical models to describe dependencies among mutations. Evolutionary modeling helps to understand how tumors arise and will also play an increasingly important prognostic role in predicting disease progression and the outcome of medical interventions, such as targeted therapy. PMID:25293804

  17. Chloroplast Phylogenomic Inference of Green Algae Relationships.

    PubMed

    Sun, Linhua; Fang, Ling; Zhang, Zhenhua; Chang, Xin; Penny, David; Zhong, Bojian

    2016-02-05

    The green algal phylum Chlorophyta has six diverse classes, but the phylogenetic relationship of the classes within Chlorophyta remains uncertain. In order to better understand the ancient Chlorophyta evolution, we have applied a site pattern sorting method to study compositional heterogeneity and the model fit in the green algal chloroplast genomic data. We show that the fastest-evolving sites are significantly correlated with among-site compositional heterogeneity, and these sites have a much poorer fit to the evolutionary model. Our phylogenomic analyses suggest that the class Chlorophyceae is a monophyletic group, and the classes Ulvophyceae, Trebouxiophyceae and Prasinophyceae are non-monophyletic groups. Our proposed phylogenetic tree of Chlorophyta will offer new insights to investigate ancient green algae evolution, and our analytical framework will provide a useful approach for evaluating and mitigating the potential errors of phylogenomic inferences.

  18. cosmoabc: Likelihood-free inference for cosmology

    NASA Astrophysics Data System (ADS)

    Ishida, Emille E. O.; Vitenti, Sandro D. P.; Penna-Lima, Mariana; Trindade, Arlindo M.; Cisewski, Jessi; M.; de Souza, Rafael; Cameron, Ewan; Busti, Vinicius C.

    2015-05-01

    Approximate Bayesian Computation (ABC) enables parameter inference for complex physical systems in cases where the true likelihood function is unknown, unavailable, or computationally too expensive. It relies on the forward simulation of mock data and comparison between observed and synthetic catalogs. cosmoabc is a Python Approximate Bayesian Computation (ABC) sampler featuring a Population Monte Carlo variation of the original ABC algorithm, which uses an adaptive importance sampling scheme. The code can be coupled to an external simulator to allow incorporation of arbitrary distance and prior functions. When coupled with the numcosmo library, it has been used to estimate posterior probability distributions over cosmological parameters based on measurements of galaxy clusters number counts without computing the likelihood function.

  19. Disabling conditional inferences: an EEG study.

    PubMed

    Bonnefond, Mathilde; Kaliuzhna, Mariia; Van der Henst, Jean-Baptiste; De Neys, Wim

    2014-04-01

    Although the Modus Ponens inference is one of the most basic logical rules, decades of conditional reasoning research show that it is often rejected when people consider stored background knowledge about potential disabling conditions. In the present study we used EEG to identify neural markers of this process. We presented participants with many and few disabler conditionals for which retrieval of disabling conditions was likely or unlikely. As in classic behavioral studies we observed that participants accepted the standard MP conclusion less for conditionals with many disablers. The key finding was that the presentation of the standard MP conclusion also resulted in a more pronounced N2 and less pronounced P3b for the many disabler conditionals. This specific N2/P3b pattern has been linked to the violation and satisfaction of expectations, respectively. Thereby, the present ERP findings support the idea that disabler retrieval lowers reasoners' expectations that the standard MP conclusion can be drawn.

  20. Inferring biological dynamics in heterogeneous cellular environments

    NASA Astrophysics Data System (ADS)

    Pressé, Steve

    In complex environments, it often appears that biomolecules such as proteins do not diffuse normally. That is, their mean square displacement does not scale linearly with time. This anomalous diffusion happens for multiple reasons: proteins can bind to structures and other proteins; fluorophores used to label proteins may flicker or blink making it appear that the labeled protein is diffusing anomalously; and proteins can diffuse in differently crowded environments. Here we describe methods for learning about such processes from imaging data collected inside the heterogeneous environment of the living cell. Refs.: ''Inferring Diffusional Dynamics from FCS in Heterogeneous Nuclear Environments'' Konstantinos Tsekouras, Amanda Siegel, Richard N. Day, Steve Pressé*, Biophys. J. , 109, 7 (2015). ''A data-driven alternative to the fractional Fokker-Planck equation'' Steve Pressé*, J. Stat. Phys.: Th. and Expmt. , P07009 (2015).

  1. Inferring character from faces: a developmental study.

    PubMed

    Cogsdill, Emily J; Todorov, Alexander T; Spelke, Elizabeth S; Banaji, Mahzarin R

    2014-05-01

    Human adults attribute character traits to faces readily and with high consensus. In two experiments investigating the development of face-to-trait inference, adults and children ages 3 through 10 attributed trustworthiness, dominance, and competence to pairs of faces. In Experiment 1, the attributions of 3- to 4-year-olds converged with those of adults, and 5- to 6-year-olds' attributions were at adult levels of consistency. Children ages 3 and above consistently attributed the basic mean/nice evaluation not only to faces varying in trustworthiness (Experiment 1) but also to faces varying in dominance and competence (Experiment 2). This research suggests that the predisposition to judge others using scant facial information appears in adultlike forms early in childhood and does not require prolonged social experience.

  2. Single-Trial Inference on Visual Attention

    NASA Astrophysics Data System (ADS)

    Dyrholm, Mads; Kyllingsbæk, Søren; Vangkilde, Signe; Habekost, Thomas; Bundesen, Claus

    2011-06-01

    In this paper we take a step towards single-trial behavioral modeling within a Theory of Visual Attention (TVA). In selective attention tasks, such as the Partial Report paradigm, the subject is asked to ignore distractors and only report stimuli that belong to the target class. Nothing about a distractor is observed directly in the subject's overt behavior, hence behavioral modeling of such trials involves out-marginalizing the variables that represent the distractors' influence on behavior. In this paper we derive equations for inferring a latent representation of the distractors on a Partial Report trial. This result retrodicts a latent attentional state of the subject using the observed response from that particular trial and thus differs from other predictions made with TVA which are based on expected values of observed variables. We show an example of the result in single-trial analysis of an occipital EEG component.

  3. Causal Inference in Multisensory Heading Estimation

    PubMed Central

    Katliar, Mikhail; Bülthoff, Heinrich H.

    2017-01-01

    A large body of research shows that the Central Nervous System (CNS) integrates multisensory information. However, this strategy should only apply to multisensory signals that have a common cause; independent signals should be segregated. Causal Inference (CI) models account for this notion. Surprisingly, previous findings suggested that visual and inertial cues on heading of self-motion are integrated regardless of discrepancy. We hypothesized that CI does occur, but that characteristics of the motion profiles affect multisensory processing. Participants estimated heading of visual-inertial motion stimuli with several different motion profiles and a range of intersensory discrepancies. The results support the hypothesis that judgments of signal causality are included in the heading estimation process. Moreover, the data suggest a decreasing tolerance for discrepancies and an increasing reliance on visual cues for longer duration motions. PMID:28060957

  4. Automated adaptive inference of phenomenological dynamical models

    PubMed Central

    Daniels, Bryan C.; Nemenman, Ilya

    2015-01-01

    Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

  5. Causal Network Inference Via Group Sparse Regularization

    PubMed Central

    Bolstad, Andrew; Van Veen, Barry D.; Nowak, Robert

    2011-01-01

    This paper addresses the problem of inferring sparse causal networks modeled by multivariate autoregressive (MAR) processes. Conditions are derived under which the Group Lasso (gLasso) procedure consistently estimates sparse network structure. The key condition involves a “false connection score” ψ. In particular, we show that consistent recovery is possible even when the number of observations of the network is far less than the number of parameters describing the network, provided that ψ < 1. The false connection score is also demonstrated to be a useful metric of recovery in nonasymptotic regimes. The conditions suggest a modified gLasso procedure which tends to improve the false connection score and reduce the chances of reversing the direction of causal influence. Computational experiments and a real network based electrocorticogram (ECoG) simulation study demonstrate the effectiveness of the approach. PMID:21918591

  6. Inferring Network Connectivity by Delayed Feedback Control

    PubMed Central

    Yu, Dongchuan; Parlitz, Ulrich

    2011-01-01

    We suggest a control based approach to topology estimation of networks with elements. This method first drives the network to steady states by a delayed feedback control; then performs structural perturbations for shifting the steady states times; and finally infers the connection topology from the steady states' shifts by matrix inverse algorithm () or -norm convex optimization strategy applicable to estimate the topology of sparse networks from perturbations. We discuss as well some aspects important for applications, such as the topology reconstruction quality and error sources, advantages and disadvantages of the suggested method, and the influence of (control) perturbations, inhomegenity, sparsity, coupling functions, and measurement noise. Some examples of networks with Chua's oscillators are presented to illustrate the reliability of the suggested technique. PMID:21969856

  7. Monocular Elevation Deficiency - Double Elevator Palsy

    MedlinePlus

    ... sucking thus creating a "wink" when chewing or sucking. Is Monocular Elevation Deficiency associated with other diseases or developmental problems? There is no known association between Monocular Elevation ...

  8. Biotinidase deficiency: novel mutations in Algerian patients.

    PubMed

    Tiar, A; Mekki, A; Nagara, M; Rhouma, F Ben; Messaoud, O; Halim, N Ben; Kefi, R; Hamlaoui, M T; Lebied, A; Abdelhak, S

    2014-02-15

    Biotinidase deficiency is an autosomal recessive disorder of biotin metabolism leading to varying degrees of neurologic and cutaneous symptoms when untreated. In the present study, we report the clinical features and the molecular investigation of biotinidase deficiency in four unrelated consanguineous Algerian families including five patients with profound biotinidase deficiency and one child characterized as partial biotinidase deficiency. Mutation analysis revealed three novel mutations, c.del631C and c.1557T>G within exon 4 and c.324-325insTA in exon 3. Since newborn screening is not available in Algeria, cascade screening in affected families would be very helpful to identify at risk individuals.

  9. Atypical B12 Deficiency with Nonresolving Paraesthesia

    PubMed Central

    Haider, S.; Ahmad, N.; Anaissie, E. J.; Abdel Karim, N.

    2013-01-01

    Vitamin B12 deficiency can present with various hematological, gastrointestinal and neurological manifestations. We report a case of elderly female who presented with neuropathy and vitamin B12 deficiency where the final work-up revealed polyneuropathy, organomegaly, endocrinopathy, monoclonal gammopathy, and skin changes (POEMS). This case suggests that, although POEMS syndrome is a rare entity, it can present with vitamin-B12 deficiency and thus specific work up for early diagnosis of POEMS should be considered in patients with B12 deficiency unresponsive to therapy. PMID:24349810

  10. Cryptosporidiosis in the acquired immune deficiency syndrome.

    PubMed

    Cooper, D A; Wodak, A; Marriot, D J; Harkness, J L; Ralston, M; Hill, A; Penny, R

    1984-10-01

    Cryptosporidiosis was found in a patient with the acquired immune deficiency syndrome. The microbiological and morphological features of this newly recognized opportunistic infection are distinctive and diagnostic.

  11. Iron deficiency anemia in heart failure.

    PubMed

    Arora, Natasha P; Ghali, Jalal K

    2013-07-01

    Anemia and iron deficiency are quite prevalent in patients with heart failure (HF) and may overlap. Both anemia and iron deficiency are associated with worse symptoms and adverse clinical outcomes. In the past few years, there has been an enormous interest in the subject of iron deficiency and its management in patients with HF. In this review, the etiology and relevance of iron deficiency, iron metabolism in the setting of HF, studies on iron supplementation in patients with HF and potential cardiovascular effects of subclinical iron overload are discussed.

  12. Nuclear Forensic Inferences Using Iterative Multidimensional Statistics

    SciTech Connect

    Robel, M; Kristo, M J; Heller, M A

    2009-06-09

    Nuclear forensics involves the analysis of interdicted nuclear material for specific material characteristics (referred to as 'signatures') that imply specific geographical locations, production processes, culprit intentions, etc. Predictive signatures rely on expert knowledge of physics, chemistry, and engineering to develop inferences from these material characteristics. Comparative signatures, on the other hand, rely on comparison of the material characteristics of the interdicted sample (the 'questioned sample' in FBI parlance) with those of a set of known samples. In the ideal case, the set of known samples would be a comprehensive nuclear forensics database, a database which does not currently exist. In fact, our ability to analyze interdicted samples and produce an extensive list of precise materials characteristics far exceeds our ability to interpret the results. Therefore, as we seek to develop the extensive databases necessary for nuclear forensics, we must also develop the methods necessary to produce the necessary inferences from comparison of our analytical results with these large, multidimensional sets of data. In the work reported here, we used a large, multidimensional dataset of results from quality control analyses of uranium ore concentrate (UOC, sometimes called 'yellowcake'). We have found that traditional multidimensional techniques, such as principal components analysis (PCA), are especially useful for understanding such datasets and drawing relevant conclusions. In particular, we have developed an iterative partial least squares-discriminant analysis (PLS-DA) procedure that has proven especially adept at identifying the production location of unknown UOC samples. By removing classes which fell far outside the initial decision boundary, and then rebuilding the PLS-DA model, we have consistently produced better and more definitive attributions than with a single pass classification approach. Performance of the iterative PLS-DA method

  13. Tracing retinal vessel trees by transductive inference

    PubMed Central

    2014-01-01

    Background Structural study of retinal blood vessels provides an early indication of diseases such as diabetic retinopathy, glaucoma, and hypertensive retinopathy. These studies require accurate tracing of retinal vessel tree structure from fundus images in an automated manner. However, the existing work encounters great difficulties when dealing with the crossover issue commonly-seen in vessel networks. Results In this paper, we consider a novel graph-based approach to address this tracing with crossover problem: After initial steps of segmentation and skeleton extraction, its graph representation can be established, where each segment in the skeleton map becomes a node, and a direct contact between two adjacent segments is translated to an undirected edge of the two corresponding nodes. The segments in the skeleton map touching the optical disk area are considered as root nodes. This determines the number of trees to-be-found in the vessel network, which is always equal to the number of root nodes. Based on this undirected graph representation, the tracing problem is further connected to the well-studied transductive inference in machine learning, where the goal becomes that of properly propagating the tree labels from those known root nodes to the rest of the graph, such that the graph is partitioned into disjoint sub-graphs, or equivalently, each of the trees is traced and separated from the rest of the vessel network. This connection enables us to address the tracing problem by exploiting established development in transductive inference. Empirical experiments on public available fundus image datasets demonstrate the applicability of our approach. Conclusions We provide a novel and systematic approach to trace retinal vessel trees with the present of crossovers by solving a transductive learning problem on induced undirected graphs. PMID:24438151

  14. Sympatry inference and network analysis in biogeography.

    PubMed

    Dos Santos, Daniel A; Fernández, Hugo R; Cuezzo, María Gabriela; Domínguez, Eduardo

    2008-06-01

    A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes.

  15. Pathway network inference from gene expression data

    PubMed Central

    2014-01-01

    Background The development of high-throughput omics technologies enabled genome-wide measurements of the activity of cellular elements and provides the analytical resources for the progress of the Systems Biology discipline. Analysis and interpretation of gene expression data has evolved from the gene to the pathway and interaction level, i.e. from the detection of differentially expressed genes, to the establishment of gene interaction networks and the identification of enriched functional categories. Still, the understanding of biological systems requires a further level of analysis that addresses the characterization of the interaction between functional modules. Results We present a novel computational methodology to study the functional interconnections among the molecular elements of a biological system. The PANA approach uses high-throughput genomics measurements and a functional annotation scheme to extract an activity profile from each functional block -or pathway- followed by machine-learning methods to infer the relationships between these functional profiles. The result is a global, interconnected network of pathways that represents the functional cross-talk within the molecular system. We have applied this approach to describe the functional transcriptional connections during the yeast cell cycle and to identify pathways that change their connectivity in a disease condition using an Alzheimer example. Conclusions PANA is a useful tool to deepen in our understanding of the functional interdependences that operate within complex biological systems. We show the approach is algorithmically consistent and the inferred network is well supported by the available functional data. The method allows the dissection of the molecular basis of the functional connections and we describe the different regulatory mechanisms that explain the network's topology obtained for the yeast cell cycle data. PMID:25032889

  16. Synaptic and nonsynaptic plasticity approximating probabilistic inference

    PubMed Central

    Tully, Philip J.; Hennig, Matthias H.; Lansner, Anders

    2014-01-01

    Learning and memory operations in neural circuits are believed to involve molecular cascades of synaptic and nonsynaptic changes that lead to a diverse repertoire of dynamical phenomena at higher levels of processing. Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability all conspire to form and maintain memories. But it is still unclear how these seemingly redundant mechanisms could jointly orchestrate learning in a more unified system. To this end, a Hebbian learning rule for spiking neurons inspired by Bayesian statistics is proposed. In this model, synaptic weights and intrinsic currents are adapted on-line upon arrival of single spikes, which initiate a cascade of temporally interacting memory traces that locally estimate probabilities associated with relative neuronal activation levels. Trace dynamics enable synaptic learning to readily demonstrate a spike-timing dependence, stably return to a set-point over long time scales, and remain competitive despite this stability. Beyond unsupervised learning, linking the traces with an external plasticity-modulating signal enables spike-based reinforcement learning. At the postsynaptic neuron, the traces are represented by an activity-dependent ion channel that is shown to regulate the input received by a postsynaptic cell and generate intrinsic graded persistent firing levels. We show how spike-based Hebbian-Bayesian learning can be performed in a simulated inference task using integrate-and-fire (IAF) neurons that are Poisson-firing and background-driven, similar to the preferred regime of cortical neurons. Our results support the view that neurons can represent information in the form of probability distributions, and that probabilistic inference could be a functional by-product of coupled synaptic and nonsynaptic mechanisms operating over several timescales. The model provides a biophysical realization of Bayesian computation by reconciling several observed neural phenomena whose

  17. Network geometry inference using common neighbors

    NASA Astrophysics Data System (ADS)

    Papadopoulos, Fragkiskos; Aldecoa, Rodrigo; Krioukov, Dmitri

    2015-08-01

    We introduce and explore a method for inferring hidden geometric coordinates of nodes in complex networks based on the number of common neighbors between the nodes. We compare this approach to the HyperMap method, which is based only on the connections (and disconnections) between the nodes, i.e., on the links that the nodes have (or do not have). We find that for high degree nodes, the common-neighbors approach yields a more accurate inference than the link-based method, unless heuristic periodic adjustments (or "correction steps") are used in the latter. The common-neighbors approach is computationally intensive, requiring O (t4) running time to map a network of t nodes, versus O (t3) in the link-based method. But we also develop a hybrid method with O (t3) running time, which combines the common-neighbors and link-based approaches, and we explore a heuristic that reduces its running time further to O (t2) , without significant reduction in the mapping accuracy. We apply this method to the autonomous systems (ASs) Internet, and we reveal how soft communities of ASs evolve over time in the similarity space. We further demonstrate the method's predictive power by forecasting future links between ASs. Taken altogether, our results advance our understanding of how to efficiently and accurately map real networks to their latent geometric spaces, which is an important necessary step toward understanding the laws that govern the dynamics of nodes in these spaces, and the fine-grained dynamics of network connections.

  18. Systematic parameter inference in stochastic mesoscopic modeling

    NASA Astrophysics Data System (ADS)

    Lei, Huan; Yang, Xiu; Li, Zhen; Karniadakis, George Em

    2017-02-01

    We propose a method to efficiently determine the optimal coarse-grained force field in mesoscopic stochastic simulations of Newtonian fluid and polymer melt systems modeled by dissipative particle dynamics (DPD) and energy conserving dissipative particle dynamics (eDPD). The response surfaces of various target properties (viscosity, diffusivity, pressure, etc.) with respect to model parameters are constructed based on the generalized polynomial chaos (gPC) expansion using simulation results on sampling points (e.g., individual parameter sets). To alleviate the computational cost to evaluate the target properties, we employ the compressive sensing method to compute the coefficients of the dominant gPC terms given the prior knowledge that the coefficients are "sparse". The proposed method shows comparable accuracy with the standard probabilistic collocation method (PCM) while it imposes a much weaker restriction on the number of the simulation samples especially for systems with high dimensional parametric space. Fully access to the response surfaces within the confidence range enables us to infer the optimal force parameters given the desirable values of target properties at the macroscopic scale. Moreover, it enables us to investigate the intrinsic relationship between the model parameters, identify possible degeneracies in the parameter space, and optimize the model by eliminating model redundancies. The proposed method provides an efficient alternative approach for constructing mesoscopic models by inferring model parameters to recover target properties of the physics systems (e.g., from experimental measurements), where those force field parameters and formulation cannot be derived from the microscopic level in a straight forward way.

  19. Spurious correlations and inference in landscape genetics.

    PubMed

    Cushman, Samuel A; Landguth, Erin L

    2010-09-01

    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 causal-modelling with partial Mantel tests in individual-based landscape genetic analysis. We used a spatially explicit simulation model to generate genetic data across a spatially distributed population as functions of several alternative gene flow processes. This allowed us to stipulate the actual process that is in action, enabling formal evaluation of the strength of spurious correlations with incorrect models. We evaluated the degree to which naïve correlational approaches can lead to incorrect attribution of the driver of observed genetic structure. Second, we evaluated the power of causal modelling with partial Mantel tests on resistance gradients to correctly identify the explanatory model and reject incorrect alternative models. Third, we evaluated how rapidly after the landscape genetic process is initiated that we are able to reliably detect the effect of the correct model and reject the incorrect models. Our analyses suggest that simple correlational analyses between genetic data and proposed explanatory models produce strong spurious correlations, which lead to incorrect inferences. We found that causal modelling was extremely effective at rejecting incorrect explanations and correctly identifying the true causal process. We propose a generalized framework for landscape genetics based on analysis of the spatial genetic relationships among individual organisms relative to alternative hypotheses that define functional relationships between landscape features and spatial population processes.

  20. Implementation of Fuzzy Inference Systems Using Neural Network Techniques

    DTIC Science & Technology

    1992-03-01

    rules required to implement the system, which are usually supplied by ’experts’. One alternative is to use a neural network -type architecture to implement...the fuzzy inference system, and neural network -type training techniques to ’learn’ the control parameters needed by the fuzzy inference system. By...using a generalized version of a neural network , the rules of the fuzzy inference system can be learned without the assistance of experts.

  1. Interplanetary magnetic sector polarity inferred from polar geomagnetic field observations

    NASA Technical Reports Server (NTRS)

    Friis-Christensen, E.; Lassen, K.; Wilcox, J. M.; Gonzalez, W.; Colburn, D. S.

    1971-01-01

    In order to infer the interplanetary sector polarity from polar geomagnetic field diurnal variations, measurements were carried out at Godhavn and Thule (Denmark) Geomagnetic Observatories. The inferred interplanetary sector polarity was compared with the polarity observed at the same time by Explorer 33 and 35 magnetometers. It is shown that the polarity (toward or away from the sun) of the interplanetary magnetic field can be reliably inferred from observations of the polar cap geomagnetic fields.

  2. Dynamical Logic Driven by Classified Inferences Including Abduction

    NASA Astrophysics Data System (ADS)

    Sawa, Koji; Gunji, Yukio-Pegio

    2010-11-01

    We propose a dynamical model of formal logic which realizes a representation of logical inferences, deduction and induction. In addition, it also represents abduction which is classified by Peirce as the third inference following deduction and induction. The three types of inference are represented as transformations of a directed graph. The state of a relation between objects of the model fluctuates between the collective and the distinctive. In addition, the location of the relation in the sequence of the relation influences its state.

  3. [Iron deficiency in the elderly].

    PubMed

    Helsen, Tuur; Joosten, Etienne

    2016-06-01

    Anemia is a common diagnosis in the geriatric population, especially in institutionalized and hospitalized elderly. Most common etiologies for anemia in elderly people admitted to a geriatric ward are iron-deficiency anemia and anemia associated with chronic disease. Determination of serum ferritin is the most used assay in the differential diagnosis, despite low sensitivity and moderate specificity. New insights into iron homeostasis lead to new diagnostic assays such as serum hepcidin, serum transferrin receptor and reticulocyte hemoglobin equivalent.Importance of proper diagnosis and treatment for this population is large since there is a correlation between anemia and morbidity - mortality. Anemia is usually defined as hemoglobin less than 12 g/dl for women and less than 13 g/dl for men. There is no consensus for which hemoglobinvalue an investigation into underlying pathology is obligatory. This needs to be evaluated depending on functional condition of the patient.

  4. Perspectives on nutritional iron deficiency.

    PubMed

    Hallberg, L

    2001-01-01

    Nutritional iron deficiency (ID) is caused by an intake of dietary iron insufficient to cover physiological iron requirements. Studies on iron absorption from whole diets have examined relationships between dietary iron bioavailability/absorption, iron losses, and amounts of stored iron. New insights have been obtained into regulation of iron absorption and expected rates of changes of iron stores or hemoglobin iron deficits when bioavailability or iron content of the diet has been modified and when losses of iron occur. Negative effects of ID are probably related to age, up to about 20 years, explaining some of earlier controversies. Difficulties in establishing the prevalence of mild ID are outlined. The degree of underestimation of the prevalence of mild ID when using multiple diagnostic criteria is discussed. It is suggested that current low-energy lifestyles are a common denominator for the current high prevalence not only of ID but also of obesity, diabetes, and osteoporosis.

  5. Vitamin A deficiency in quail

    USGS Publications Warehouse

    Nestler, R.B.; Bailey, W.W.

    1943-01-01

    Two experiments were conducted to determine the symptoms of avitaminosis A in growing and adolescent bobwhites. Chicks from parents that have received a diet rich in vitamin A may have enough stored to carry them a week or ten days on a growing diet deficient in vitamin A before symptoms of deficiency occur. The first sign is ruffled feathering, with the wing primaries standing out from the body and drooping. Ophthalmia in one or both eyes occurs and may close the eyes completely, but this condition is not severe in all cases and may not even be noticeable. Birds show poor growth, loss of appetite, and weakness before death. Under the conditions of the experiments discussed herein, death may occur in the fourth or fifth week, and mortality is high......Postmortem examination may reveal visceral gout with thick deposits of urates on the kidneys, in the ureters, on the heart, in the proventriculus, and occasionally covering all the viscera. There may also be hemorrhage of the heart and other organs....Adolescent quail reared on a diet rich in vitamin A may be able to live through the winter on a maintenance diet low in this vitamin without showing symptoms of avitaminosis, but some individuals whose storage of vitamin A in the liver is not as great as that of others may succumb to visceral gout.....A growing mash for quail which contains sufficient vitamin A when fresh may, after a period of storage, lose enough of the vitamin to cause the characteristic symptoms of avitaminosis A to appear.

  6. Vitamin D deficiency in adolescents.

    PubMed

    Soliman, Ashraf T; De Sanctis, Vincenzo; Elalaily, Rania; Bedair, Said; Kassem, Islam

    2014-11-01

    The prevalence of severe vitamin D deficiency (VDD) in adolescents is variable but considerably high in many countries, especially in Middle-east and Southeast Asia. Different factors attribute to this deficiency including lack of sunlight exposure due to cultural dress codes and veiling or due to pigmented skin, and less time spent outdoors, because of hot weather, and lower vitamin D intake. A potent adaptation process significantly modifies the clinical presentation and therefore clinical presentations may be subtle and go unnoticed, thus making true prevalence studies difficult. Adolescents with severe VDD may present with vague manifestations including pain in weight-bearing joints, back, thighs and/or calves, difficulty in walking and/or climbing stairs, or running and muscle cramps. Adaptation includes increased parathormone (PTH) and deceased insulin-like growth factor-I (IGF-I) secretion. PTH enhances the tubular reabsorption of Ca and stimulates the kidneys to produce 1, 25-(OH) 2D3 that increases intestinal calcium absorption and dissolves the mineralized collagen matrix in bone, causing osteopenia and osteoporosis to provide enough Ca to prevent hypocalcaemia. Decreased insulin like growth factor-I (IGF-I) delays bone growth to economize calcium consumption. Radiological changes are not uncommon and include osteoporosis/osteopenia affecting long bones as well as vertebrae and ribs, bone cysts, decalcification of the metaphysis of the long bones and pseudo fractures. In severe cases pathological fractures and deformities may occur. Vitamin D treatment of adolescents with VDD differs considerably in different studies and proved to be effective in treating all clinical, biochemical, and radiological manifestations. Different treatment regiments for VDD have been discussed and presented in this mini-review for practical use. Adequate vitamin D replacement after treating VDD, improving calcium intake (milk and dairy products), encouraging adequate exposure

  7. Making inference from wildlife collision data: inferring predator absence from prey strikes.

    PubMed

    Caley, Peter; Hosack, Geoffrey R; Barry, Simon C

    2017-01-01

    Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application.

  8. Making inference from wildlife collision data: inferring predator absence from prey strikes

    PubMed Central

    Hosack, Geoffrey R.; Barry, Simon C.

    2017-01-01

    Wildlife collision data are ubiquitous, though challenging for making ecological inference due to typically irreducible uncertainty relating to the sampling process. We illustrate a new approach that is useful for generating inference from predator data arising from wildlife collisions. By simply conditioning on a second prey species sampled via the same collision process, and by using a biologically realistic numerical response functions, we can produce a coherent numerical response relationship between predator and prey. This relationship can then be used to make inference on the population size of the predator species, including the probability of extinction. The statistical conditioning enables us to account for unmeasured variation in factors influencing the runway strike incidence for individual airports and to enable valid comparisons. A practical application of the approach for testing hypotheses about the distribution and abundance of a predator species is illustrated using the hypothesized red fox incursion into Tasmania, Australia. We estimate that conditional on the numerical response between fox and lagomorph runway strikes on mainland Australia, the predictive probability of observing no runway strikes of foxes in Tasmania after observing 15 lagomorph strikes is 0.001. We conclude there is enough evidence to safely reject the null hypothesis that there is a widespread red fox population in Tasmania at a population density consistent with prey availability. The method is novel and has potential wider application. PMID:28243534

  9. The probabilistic convolution tree: efficient exact Bayesian inference for faster LC-MS/MS protein inference.

    PubMed

    Serang, Oliver

    2014-01-01

    Exact Bayesian inference can sometimes be performed efficiently for special cases where a function has commutative and associative symmetry of its inputs (called "causal independence"). For this reason, it is desirable to exploit such symmetry on big data sets. Here we present a method to exploit a general form of this symmetry on probabilistic adder nodes by transforming those probabilistic adder nodes into a probabilistic convolution tree with which dynamic programming computes exact probabilities. A substantial speedup is demonstrated using an illustration example that can arise when identifying splice forms with bottom-up mass spectrometry-based proteomics. On this example, even state-of-the-art exact inference algorithms require a runtime more than exponential in the number of splice forms considered. By using the probabilistic convolution tree, we reduce the runtime to O(k log(k)2) and the space to O(k log(k)) where k is the number of variables joined by an additive or cardinal operator. This approach, which can also be used with junction tree inference, is applicable to graphs with arbitrary dependency on counting variables or cardinalities and can be used on diverse problems and fields like forward error correcting codes, elemental decomposition, and spectral demixing. The approach also trivially generalizes to multiple dimensions.

  10. Impact of Prematurity and Perinatal Antibiotics on the Developing Intestinal Microbiota: A Functional Inference Study

    PubMed Central

    Arboleya, Silvia; Sánchez, Borja; Solís, Gonzalo; Fernández, Nuria; Suárez, Marta; Hernández-Barranco, Ana M.; Milani, Christian; Margolles, Abelardo; de los Reyes-Gavilán, Clara G.; Ventura, Marco; Gueimonde, Miguel

    2016-01-01

    Background: The microbial colonization of the neonatal gut provides a critical stimulus for normal maturation and development. This process of early microbiota establishment, known to be affected by several factors, constitutes an important determinant for later health. Methods: We studied the establishment of the microbiota in preterm and full-term infants and the impact of perinatal antibiotics upon this process in premature babies. To this end, 16S rRNA gene sequence-based microbiota assessment was performed at phylum level and functional inference analyses were conducted. Moreover, the levels of the main intestinal microbial metabolites, the short-chain fatty acids (SCFA) acetate, propionate and butyrate, were measured by Gas-Chromatography Flame ionization/Mass spectrometry detection. Results: Prematurity affects microbiota composition at phylum level, leading to increases of Proteobacteria and reduction of other intestinal microorganisms. Perinatal antibiotic use further affected the microbiota of the preterm infant. These changes involved a concomitant alteration in the levels of intestinal SCFA. Moreover, functional inference analyses allowed for identifying metabolic pathways potentially affected by prematurity and perinatal antibiotics use. Conclusion: A deficiency or delay in the establishment of normal microbiota function seems to be present in preterm infants. Perinatal antibiotic use, such as intrapartum prophylaxis, affected the early life microbiota establishment in preterm newborns, which may have consequences for later health. PMID:27136545

  11. Micronutrient deficiencies in developing and affluent countries.

    PubMed

    Díaz, J R; de las Cagigas, A; Rodríguez, R

    2003-09-01

    Micronutrient deficiencies, also known as 'hidden hunger', are determining and aggravating factors for health status and quality of life. Three nutritional problems that have serious consequences are deficiencies of iron, vitamin A and iodine. It is estimated that in today's world, iron deficiency anemia affects two billion people, mostly women and children. Blindness due to vitamin A deficiency affects 2.8 million children under 5 years of age. Iodine deficiency disorders affect 740 million people. Cuba is employing various programs to deal with these micronutrient deficiencies. Dietary diversification, fortification of foods and supplementation with pharmaceutical preparations are included in Cuba's response to these deficiencies. Urban agriculture is one strategy to increase dietary diversity. The aim is to increase both the availability and consumption of vegetables and fruits. Food fortification takes many forms in Cuba today and various supplementation programs are carried out. The most common supplemental program in the country is the prenatal program. This program provides four essential nutrients: iron, ascorbic acid, vitamin A and folic acid. At present, iodination covers more than 90% of the total amount of salt used for human consumption. Results of research carried out in Cuba have shown that vitamin A deficiency is nonexistent in children up to 7 y of age. Foods and preparations for these programs are delivered gratuitously or at very low prices.

  12. Fetal anaemia due to pyruvate kinase deficiency.

    PubMed Central

    Gilsanz, F; Vega, M A; Gómez-Castillo, E; Ruiz-Balda, J A; Omeñaca, F

    1993-01-01

    Pyruvate kinase deficiency was diagnosed in an infant by umbilical vessel sampling at 30 weeks' gestation. Although three previous hydropic siblings had been stillborn or died in the neonatal period, this infant survived with transfusion dependent haemolytic anaemia. Prompt fetal diagnosis of pyruvate kinase deficiency is feasible and allows better management of hydrops fetalis due to this disorder. PMID:8285758

  13. Copper deficiency in calves in northcentral Manitoba.

    PubMed

    Smart, M E; Gudmundson, J; Brockman, R P; Cymbaluk, N; Doige, C

    1980-12-01

    Four seven month old Simmental calves were examined because of unthriftiness, a persistent cough, stiffness and lameness. The calves had gastrointestinal and pulmonary parasitism. Analysis of the blood copper levels of these calves and of cows and calves on the farm indicated a generalized deficiency. Only the calves affected with parasitism showed signs of clinical copper deficiency.

  14. [Selenium deficiency and infertility. Andrologic aspects].

    PubMed

    Szöllosi, János; Závaczki, Zoltán; Pál, Attila

    2008-09-14

    Absolute selenium deficiency in human is very rare, although suboptimal daily selenium intake may lead to an unrecognized relative deficiency. Among the many consequences ascribed to decreased selenium level, the effect on male fertility is summarised by the authors. Implications from biochemical, animal experimental and human research are discussed.

  15. Growth Hormone Deficiency, Brain Development, and Intelligence

    ERIC Educational Resources Information Center

    Meyer-Bahlburg, Heino F. L.; And Others

    1978-01-01

    Available from: American Medical Association, 535 N. Dearborn Street, Chicago, Illinois 60610. In order to determine what effect, if any, growth hormone (GH) has on human brain development, 29 patients (mean age 11.7 years) with GH deficiency were selected according to the following criteria: no evidence of reversible GH deficiency, onset of…

  16. Duodenal Amyloidosis Masquerading as Iron Deficiency Anemia

    PubMed Central

    Hurairah, Abu

    2016-01-01

    The present study is a unique illustration of duodenal amyloidosis initially manifesting with iron deficiency anemia. It underscores the importance of clinical suspicion of amyloidosis while performing upper gastrointestinal endoscopy with a biopsy to establish the definite diagnosis in patients with unexplained iron deficiency anemia. PMID:27625911

  17. How common is vitamin B12 deficiency?

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In considering the vitamin B-12 fortification of flour, it is important to know who is at risk of vitamin B-12 deficiency and whether those individuals would benefit from flour fortification.This article reviews current knowledge of the prevalence and causes of vitamin B-12 deficiency and considers ...

  18. MARGINAL IODINE DEFICIENCY EXACERBATES PERCHLORATE THYROID TOXICITY.

    EPA Science Inventory

    The environmental contaminant perchlorate disrupts thyroid homeostasis via inhibition of iodine uptake into the thyroid. This work tested whether iodine deficiency exacerbates the effects of perchlorate. Female 27 day-old LE rats were fed a custom iodine deficient diet with 0, 50...

  19. 30 CFR 57.5015 - Oxygen deficiency.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Oxygen deficiency. 57.5015 Section 57.5015..., Physical Agents, and Diesel Particulate Matter Air Quality-Underground Only § 57.5015 Oxygen deficiency. Air in all active workings shall contain at least 19.5 volume percent oxygen....

  20. 30 CFR 57.5015 - Oxygen deficiency.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Oxygen deficiency. 57.5015 Section 57.5015..., Physical Agents, and Diesel Particulate Matter Air Quality-Underground Only § 57.5015 Oxygen deficiency. Air in all active workings shall contain at least 19.5 volume percent oxygen....

  1. 30 CFR 57.5015 - Oxygen deficiency.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Oxygen deficiency. 57.5015 Section 57.5015..., Physical Agents, and Diesel Particulate Matter Air Quality-Underground Only § 57.5015 Oxygen deficiency. Air in all active workings shall contain at least 19.5 volume percent oxygen....

  2. 30 CFR 57.5015 - Oxygen deficiency.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Oxygen deficiency. 57.5015 Section 57.5015..., Physical Agents, and Diesel Particulate Matter Air Quality-Underground Only § 57.5015 Oxygen deficiency. Air in all active workings shall contain at least 19.5 volume percent oxygen....

  3. 30 CFR 57.5015 - Oxygen deficiency.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Oxygen deficiency. 57.5015 Section 57.5015..., Physical Agents, and Diesel Particulate Matter Air Quality-Underground Only § 57.5015 Oxygen deficiency. Air in all active workings shall contain at least 19.5 volume percent oxygen....

  4. Academic Deficiency: Student Experiences of Institutional Labeling

    ERIC Educational Resources Information Center

    Barouch-Gilbert, Abraham

    2015-01-01

    Limited existing research examines how undergraduate students in the United States experience the process of being identified as deficient due to their academic performance. The purpose of this phenomenological study was to explore the lived experiences of college students on academic probation who were labeled academically deficient. Students…

  5. Ornithine transcarbamylase deficiency presenting as hepatitis.

    PubMed

    Aronson, Paul L; Mistry, Rakesh D

    2011-06-01

    Ornithine transcarbamylase deficiency is an inborn error of metabolism that commonly presents as hyperammonemia in neonates. We present a case of a 2-year-old girl who was referred to a pediatric emergency department for evaluation of hepatitis, an uncommon presentation of ornithine transcarbamylase deficiency. Recognition of late presentations of this disease is important for survival and neurological outcome.

  6. Recurrent pancreatitis in ornithine transcarbamylase deficiency.

    PubMed

    Prada, Carlos E; Kaul, Ajay; Hopkin, Robert J; Page, Kimberley I; Nathan, Jaimie D; Bartholomew, Dennis W; Cohen, Mitchell B; Heubi, James E; Leslie, Nancy D; Burrow, T Andrew

    2012-08-01

    Ornithine transcarbamylase (OTC) deficiency is a urea cycle defect with varying frequency and severity of episodes of hyperammonemia. We report three patients with OTC deficiency with recurrent pancreatitis. The pathogenesis of acute pancreatitis in this patient population requires further elucidation. Pancreatitis significantly affected dietary/metabolic management and increased frequency of hospitalizations.

  7. Inferring gene regression networks with model trees

    PubMed Central

    2010-01-01

    Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database) is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear regressions to separate

  8. Thiamin Deficiency in People with Obesity12

    PubMed Central

    Kerns, Jennifer C; Arundel, Cherinne; Chawla, Lakhmir S

    2015-01-01

    Although obesity has been viewed traditionally as a disease of excess nutrition, evidence suggests that it may also be a disease of malnutrition. Specifically, thiamin deficiency was found in 15.5–29% of obese patients seeking bariatric surgery. It can present with vague signs and symptoms and is often overlooked in patients without alcohol use disorders. This review explores the relatively new discovery of high rates of thiamin deficiency in certain populations of people with obesity, including the effects of thiamin deficiency and potential underlying mechanisms of deficiency in people with obesity. The 2 observational studies that examined the prevalence in preoperative bariatric surgery patients and gaps in our current knowledge (including the prevalence of thiamin deficiency in the general obese population and whether the current RDA for thiamin meets the metabolic needs of overweight or obese adults) are reviewed. Suggestions for future areas of research are included. PMID:25770253

  9. Molecular diagnosis of coenzyme Q10 deficiency.

    PubMed

    Yubero, Delia; Montero, Raquel; Armstrong, Judith; Espinós, Carmen; Palau, Francesc; Santos-Ocaña, Carlos; Salviati, Leonardo; Navas, Placido; Artuch, Rafael

    2015-01-01

    Coenzyme Q10 (CoQ) deficiency syndromes comprise a growing number of neurological and extraneurological disorders. Primary-genetic but also secondary CoQ deficiencies have been reported. The biochemical determination of CoQ is a good tool for the rapid identification of CoQ deficiencies but does not allow the selection of candidate genes for molecular diagnosis. Moreover, the metabolic pathway for CoQ synthesis is an intricate and not well-understood process, where a large number of genes are implicated. Thus, only next-generation sequencing techniques (either genetic panels of whole-exome and -genome sequencing) are at present appropriate for a rapid and realistic molecular diagnosis of these syndromes. The potential treatability of CoQ deficiency strongly supports the necessity of a rapid molecular characterization of patients, since primary CoQ deficiencies may respond well to CoQ treatment.

  10. [Glucose-6-phosphate dehydrogenase deficiency in Japan].

    PubMed

    Kanno, Hitoshi; Ogura, Hiromi

    2015-07-01

    In the past 10 years, we have diagnosed congenital hemolytic anemia in 294 patients, approximately 33% of whom were found to have glucose-6-phosphate dehydrogenase (G6PD) deficiency. It is becoming more common for Japanese to marry people of other ethnic origins, such that G6PD deficiency is becoming more prevalent in Japan. Japanese G6PD deficiency tends to be diagnosed in the neonatal period due to severe jaundice, while G6PD-deficient patients with foreign ancestors tend to be diagnosed at the onset of an acute hemolytic crisis before the age of six. It is difficult to predict the clinical course of each patient by G6PD activity, reduced glutathione content, or the presence/absence of severe neonatal jaundice. We propose that both neonatal G6PD screening and systematic analyses of G6PD gene mutations may be useful for personalized management of patients with G6PD-deficient hemolytic anemia.

  11. Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

    PubMed Central

    Legenstein, Robert; Maass, Wolfgang

    2014-01-01

    It has recently been shown that networks of spiking neurons with noise can emulate simple forms of probabilistic inference through “neural sampling”, i.e., by treating spikes as samples from a probability distribution of network states that is encoded in the network. Deficiencies of the existing model are its reliance on single neurons for sampling from each random variable, and the resulting limitation in representing quickly varying probabilistic information. We show that both deficiencies can be overcome by moving to a biologically more realistic encoding of each salient random variable through the stochastic firing activity of an ensemble of neurons. The resulting model demonstrates that networks of spiking neurons with noise can easily track and carry out basic computational operations on rapidly varying probability distributions, such as the odds of getting rewarded for a specific behavior. We demonstrate the viability of this new approach towards neural coding and computation, which makes use of the inherent parallelism of generic neural circuits, by showing that this model can explain experimentally observed firing activity of cortical neurons for a variety of tasks that require rapid temporal integration of sensory information. PMID:25340749

  12. The Strong-Inference Protocol: Not Just for Grant Proposals

    ERIC Educational Resources Information Center

    Hiebert, Sara M.

    2007-01-01

    The strong-inference protocol puts into action the important concepts in Platt's often-assigned, classic paper on the strong-inference method (10). Yet, perhaps because students are frequently performing experiments with known outcomes, the protocols they write as undergraduates are usually little more than step-by-step instructions for performing…

  13. Causal Inference and Language Comprehension: Event-Related Potential Investigations

    ERIC Educational Resources Information Center

    Davenport, Tristan S.

    2014-01-01

    The most important information conveyed by language is often contained not in the utterance itself, but in the interaction between the utterance and the comprehender's knowledge of the world and the current situation. This dissertation uses psycholinguistic methods to explore the effects of a common type of inference--causal inference--on language…

  14. Statistical Inference and Patterns of Inequality in the Global North

    ERIC Educational Resources Information Center

    Moran, Timothy Patrick

    2006-01-01

    Cross-national inequality trends have historically been a crucial field of inquiry across the social sciences, and new methodological techniques of statistical inference have recently improved the ability to analyze these trends over time. This paper applies Monte Carlo, bootstrap inference methods to the income surveys of the Luxembourg Income…

  15. Investigation of Statistical Inference Methodologies Through Scale Model Propagation Experiments

    DTIC Science & Technology

    2015-09-30

    Investigation of Statistical Inference Methodologies Through Scale Model Propagation Experiments Jason D. Sagers Applied Research Laboratories...statistical inference methodologies for ocean-acoustic problems by investigating and applying statistical methods to data collected from scale -model...experiments over a translationally invariant wedge, (2) to plan and conduct 3D propagation experiments over the Hudson Canyon scale -model bathymetry, and (3

  16. Bayesian Statistical Inference for Coefficient Alpha. ACT Research Report Series.

    ERIC Educational Resources Information Center

    Li, Jun Corser; Woodruff, David J.

    Coefficient alpha is a simple and very useful index of test reliability that is widely used in educational and psychological measurement. Classical statistical inference for coefficient alpha is well developed. This paper presents two methods for Bayesian statistical inference for a single sample alpha coefficient. An approximate analytic method…

  17. The Role of Causal Models in Analogical Inference

    ERIC Educational Resources Information Center

    Lee, Hee Seung; Holyoak, Keith J.

    2008-01-01

    Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs and in particular on shared higher order relations. In contrast, work in philosophy of science suggests that analogical inference is also guided by causal models of the source and target. In 3…

  18. Strategic Processing and Predictive Inference Generation in L2 Reading

    ERIC Educational Resources Information Center

    Nahatame, Shingo

    2014-01-01

    Predictive inference is the anticipation of the likely consequences of events described in a text. This study investigated predictive inference generation during second language (L2) reading, with a focus on the effects of strategy instructions. In this experiment, Japanese university students read several short narrative passages designed to…

  19. Contemporary Quantitative Methods and "Slow" Causal Inference: Response to Palinkas

    ERIC Educational Resources Information Center

    Stone, Susan

    2014-01-01

    This response considers together simultaneously occurring discussions about causal inference in social work and allied health and social science disciplines. It places emphasis on scholarship that integrates the potential outcomes model with directed acyclic graphing techniques to extract core steps in causal inference. Although this scholarship…

  20. Hemispheric inference priming during comprehension of conversations and narratives.

    PubMed

    Powers, Chivon; Bencic, Rachel; Horton, William S; Beeman, Mark

    2012-09-01

    In this study we examined asymmetric semantic activation patterns as people listened to conversations and narratives that promoted causal inferences. Based on the hypothesis that understanding the unique features of conversational input may benefit from or require a modified pattern of conceptual activation during conversation, we compared semantic priming in both hemispheres for inferences embedded in conversations and in narratives. Participants named inference-related target words or unrelated words presented to the left visual field-right hemisphere (lvf-RH) or to the right visual field-left hemisphere (rvf-LH) at critical coherence points that required an inference in order to correctly understand an utterance in the context of the conversation or narrative. Fifty-seven undergraduates listened to 36 conversations or narratives and were tested at 100 target inference points. During narrative comprehension, inference-related priming was reliable and equally strong in both hemispheres. In contrast, during conversation comprehension, inference-related priming was only reliable for target words presented to lvf-RH. This work demonstrates that priming for inference-related concepts can be measured with input in conversational form and suggests the language processing style of the RH is advantageous for comprehending conversation.

  1. Deduced Inference in the Analysis of Experimental Data

    ERIC Educational Resources Information Center

    Bird, Kevin D.

    2011-01-01

    Any set of confidence interval inferences on J - 1 linearly independent contrasts on J means, such as the two comparisons [mu][subscript 1] - [mu][subscript 2] and [mu][subscript 2] - [mu][subscript 3] on 3 means, provides a basis for the deduction of interval inferences on all other contrasts, such as the redundant comparison [mu][subscript 1] -…

  2. Aging and Predicting Inferences: A Diffusion Model Analysis

    ERIC Educational Resources Information Center

    McKoon, Gail; Ratcliff, Roger

    2013-01-01

    In the domain of discourse processing, it has been claimed that older adults (60-0-year-olds) are less likely to encode and remember some kinds of information from texts than young adults. The experiment described here shows that they do make a particular kind of inference to the same extent that college-age adults do. The inferences examined were…

  3. A Probability Index of the Robustness of a Causal Inference

    ERIC Educational Resources Information Center

    Pan, Wei; Frank, Kenneth A.

    2003-01-01

    Causal inference is an important, controversial topic in the social sciences, where it is difficult to conduct experiments or measure and control for all confounding variables. To address this concern, the present study presents a probability index to assess the robustness of a causal inference to the impact of a confounding variable. The…

  4. Exploring Beginning Inference with Novice Grade 7 Students

    ERIC Educational Resources Information Center

    Watson, Jane M.

    2008-01-01

    This study documented efforts to facilitate ideas of beginning inference in novice grade 7 students. A design experiment allowed modified teaching opportunities in light of observation of components of a framework adapted from that developed by Pfannkuch for teaching informal inference with box plots. Box plots were replaced by hat plots, a…

  5. Developing Young Students' Informal Inference Skills in Data Analysis

    ERIC Educational Resources Information Center

    Paparistodemou, Efi; Meletiou-Mavrotheris, Maria

    2008-01-01

    This paper focuses on developing students' informal inference skills, reporting on how a group of third grade students formulated and evaluated data-based inferences using the dynamic statistics data-visualization environment TinkerPlots[TM] (Konold & Miller, 2005), software specifically designed to meet the learning needs of students in the…

  6. Deontic Introduction: A Theory of Inference from Is to Ought

    ERIC Educational Resources Information Center

    Elqayam, Shira; Thompson, Valerie A.; Wilkinson, Meredith R.; Evans, Jonathan St. B. T.; Over, David E.

    2015-01-01

    Humans have a unique ability to generate novel norms. Faced with the knowledge that there are hungry children in Somalia, we easily and naturally infer that we ought to donate to famine relief charities. Although a contentious and lively issue in metaethics, such inference from "is" to "ought" has not been systematically…

  7. Jumping to the Right Conclusions, Inferences, and Predictions

    ERIC Educational Resources Information Center

    Giannattasio, Jack; Bazler, Judith

    2005-01-01

    Writing meaningful conclusions, drawing accurate inferences, and making relevant predictions are essential skills that many adolescents lack. The differences among conclusions, inferences, and predictions, although subtle, must be recognized to accurately analyze and interpret lab data. During one of the authors' 14 years as a physics and…

  8. Mast cell deficiency exacerbates inflammatory bowel symptoms in interleukin-10-deficient mice

    PubMed Central

    Zhang, Hanying; Xue, Yansong; Wang, Hui; Huang, Yan; Du, Min; Yang, Qiyuan; Zhu, Mei-Jun

    2014-01-01

    AIM: To test the role of mast cells in gut inflammation and colitis using interleukin (IL)-10-deficient mice as an experimental model. METHODS: Mast cell-deficient (KitW-sh/W-sh) mice were crossbred with IL-10-deficient mice to obtain double knockout (DKO) mice. The growth, mucosal damage and colitis status of DKO mice were compared with their IL-10-deficient littermates. RESULTS: DKO mice exhibited exacerbated colitis compared with their IL-10-deficient littermates, as shown by increased pathological score, higher myeloperoxidase content, enhanced Th1 type pro-inflammatory cytokines and inflammatory signaling, elevated oxidative stress, as well as pronounced goblet cell loss. In addition, deficiency in mast cells resulted in enhanced mucosal damage, increased gut permeability, and impaired epithelial tight junctions. Mast cell deficiency was also linked to systemic inflammation, as demonstrated by higher serum levels of tumor necrosis factor α and interferon γ in DKO mice than that in IL-10-deficient mice. CONCLUSION: Mast cell deficiency in IL-10-deficient mice resulted in systematic and gut inflammation, impaired gut barrier function, and severer Th1-mediated colitis when compared to mice with only IL-10-deficiency. Inflammation and impaired gut epithelial barrier function likely form a vicious cycle to worsen colitis in the DKO mice. PMID:25083083

  9. Virtual reality and consciousness inference in dreaming

    PubMed Central

    Hobson, J. Allan; Hong, Charles C.-H.; Friston, Karl J.

    2014-01-01

    This article explores the notion that the brain is genetically endowed with an innate virtual reality generator that – through experience-dependent plasticity – becomes a generative or predictive model of the world. This model, which is most clearly revealed in rapid eye movement (REM) sleep dreaming, may provide the theater for conscious experience. Functional neuroimaging evidence for brain activations that are time-locked to rapid eye movements (REMs) endorses the view that waking consciousness emerges from REM sleep – and dreaming lays the foundations for waking perception. In this view, the brain is equipped with a virtual model of the world that generates predictions of its sensations. This model is continually updated and entrained by sensory prediction errors in wakefulness to ensure veridical perception, but not in dreaming. In contrast, dreaming plays an essential role in maintaining and enhancing the capacity to model the world by minimizing model complexity and thereby maximizing both statistical and thermodynamic efficiency. This perspective suggests that consciousness corresponds to the embodied process of inference, realized through the generation of virtual realities (in both sleep and wakefulness). In short, our premise or hypothesis is that the waking brain engages with the world to predict the causes of sensations, while in sleep the brain’s generative model is actively refined so that it generates more efficient predictions during waking. We review the evidence in support of this hypothesis – evidence that grounds consciousness in biophysical computations whose neuronal and neurochemical infrastructure has been disclosed by sleep research. PMID:25346710

  10. Attention as a Bayesian inference process

    NASA Astrophysics Data System (ADS)

    Chikkerur, Sharat; Serre, Thomas; Tan, Cheston; Poggio, Tomaso

    2011-03-01

    David Marr famously defined vision as "knowing what is where by seeing". In the framework described here, attention is the inference process that solves the visual recognition problem of what is where. The theory proposes a computational role for attention and leads to a model that performs well in recognition tasks and that predicts some of the main properties of attention at the level of psychophysics and physiology. We propose an algorithmic implementation a Bayesian network that can be mapped into the basic functional anatomy of attention involving the ventral stream and the dorsal stream. This description integrates bottom-up, feature-based as well as spatial (context based) attentional mechanisms. We show that the Bayesian model predicts well human eye fixations (considered as a proxy for shifts of attention) in natural scenes, and can improve accuracy in object recognition tasks involving cluttered real world images. In both cases, we found that the proposed model can predict human performance better than existing bottom-up and top-down computational models.

  11. Global atmospheric black carbon inferred from AERONET

    PubMed Central

    Sato, Makiko; Hansen, James; Koch, Dorothy; Lacis, Andrew; Ruedy, Reto; Dubovik, Oleg; Holben, Brent; Chin, Mian; Novakov, Tica

    2003-01-01

    AERONET, a network of well calibrated sunphotometers, provides data on aerosol optical depth and absorption optical depth at >250 sites around the world. The spectral range of AERONET allows discrimination between constituents that absorb most strongly in the UV region, such as soil dust and organic carbon, and the more ubiquitously absorbing black carbon (BC). AERONET locations, primarily continental, are not representative of the global mean, but they can be used to calibrate global aerosol climatologies produced by tracer transport models. We find that the amount of BC in current climatologies must be increased by a factor of 2–4 to yield best agreement with AERONET, in the approximation in which BC is externally mixed with other aerosols. The inferred climate forcing by BC, regardless of whether it is internally or externally mixed, is ≈1 W/m2, most of which is probably anthropogenic. This positive forcing (warming) by BC must substantially counterbalance cooling by anthropogenic reflective aerosols. Thus, especially if reflective aerosols such as sulfates are reduced, it is important to reduce BC to minimize global warming. PMID:12746494

  12. How prescriptive norms influence causal inferences.

    PubMed

    Samland, Jana; Waldmann, Michael R

    2016-11-01

    Recent experimental findings suggest that prescriptive norms influence causal inferences. The cognitive mechanism underlying this finding is still under debate. We compare three competing theories: The culpable control model of blame argues that reasoners tend to exaggerate the causal influence of norm-violating agents, which should lead to relatively higher causal strength estimates for these agents. By contrast, the counterfactual reasoning account of causal selection assumes that norms do not alter the representation of the causal model, but rather later causal selection stages. According to this view, reasoners tend to preferentially consider counterfactual states of abnormal rather than normal factors, which leads to the choice of the abnormal factor in a causal selection task. A third view, the accountability hypothesis, claims that the effects of prescriptive norms are generated by the ambiguity of the causal test question. Asking whether an agent is a cause can be understood as a request to assess her causal contribution but also her moral accountability. According to this theory norm effects on causal selection are mediated by accountability judgments that are not only sensitive to the abnormality of behavior but also to mitigating factors, such as intentionality and knowledge of norms. Five experiments are presented that favor the accountability account over the two alternative theories.

  13. Functional network inference of the suprachiasmatic nucleus

    PubMed Central

    Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, Francis J.; Herzog, Erik D.; Petzold, Linda R.

    2016-01-01

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure. PMID:27044085

  14. Functional network inference of the suprachiasmatic nucleus

    SciTech Connect

    Abel, John H.; Meeker, Kirsten; Granados-Fuentes, Daniel; St. John, Peter C.; Wang, Thomas J.; Bales, Benjamin B.; Doyle, Francis J.; Herzog, Erik D.; Petzold, Linda R.

    2016-04-04

    In the mammalian suprachiasmatic nucleus (SCN), noisy cellular oscillators communicate within a neuronal network to generate precise system-wide circadian rhythms. Although the intracellular genetic oscillator and intercellular biochemical coupling mechanisms have been examined previously, the network topology driving synchronization of the SCN has not been elucidated. This network has been particularly challenging to probe, due to its oscillatory components and slow coupling timescale. In this work, we investigated the SCN network at a single-cell resolution through a chemically induced desynchronization. We then inferred functional connections in the SCN by applying the maximal information coefficient statistic to bioluminescence reporter data from individual neurons while they resynchronized their circadian cycling. Our results demonstrate that the functional network of circadian cells associated with resynchronization has small-world characteristics, with a node degree distribution that is exponential. We show that hubs of this small-world network are preferentially located in the central SCN, with sparsely connected shells surrounding these cores. Finally, we used two computational models of circadian neurons to validate our predictions of network structure.

  15. Causal inference with a quantitative exposure.

    PubMed

    Zhang, Zhiwei; Zhou, Jie; Cao, Weihua; Zhang, Jun

    2016-02-01

    The current statistical literature on causal inference is mostly concerned with binary or categorical exposures, even though exposures of a quantitative nature are frequently encountered in epidemiologic research. In this article, we review the available methods for estimating the dose-response curve for a quantitative exposure, which include ordinary regression based on an outcome regression model, inverse propensity weighting and stratification based on a propensity function model, and an augmented inverse propensity weighting method that is doubly robust with respect to the two models. We note that an outcome regression model often imposes an implicit constraint on the dose-response curve, and propose a flexible modeling strategy that avoids constraining the dose-response curve. We also propose two new methods: a weighted regression method that combines ordinary regression with inverse propensity weighting and a stratified regression method that combines ordinary regression with stratification. The proposed methods are similar to the augmented inverse propensity weighting method in the sense of double robustness, but easier to implement and more generally applicable. The methods are illustrated with an obstetric example and compared in simulation studies.

  16. Inferences of Ice Processes From Properties

    NASA Astrophysics Data System (ADS)

    Alley, R. B.; Wilen, L. A.; Spencer, M. K.; Hansen, D. P.; Fitzpatrick, J. J.

    2001-12-01

    Barclay Kamb's pioneering work on the physics and mineralogy of laboratory and natural ices has guided glaciological research spanning 40 years. Much of that research required extremely tedious use of optical universal stages to study thin sections of ice. Recent advances in digital systems have revolutionized data collection and offer great opportunities to use ice properties to infer processes that operate too slowly for proper laboratory investigation, leading toward a greatly improved understanding of the history of ice and its softness for further deformation (Wilen, 1999; Hansen and Wilen, in review; Wilen et al., this meeting). Patterns of nearest-neighbor c-axis orientations reveal the influence of nucleation-and-growth recrystallization (typically indicative of steady-state deformation) or polygonization. Combining these results with correlations between grain sizes and dust and chemical loadings reveals impurity effects on active processes. The relations between mean grain size and c-axis-fabric strength may show the importance of grain-boundary processes in deformation. Bubble sizes reveal climate conditions during firnification, and bubble shapes can provide information on in situ strain rates. These and many other possibilities should enhance our understanding of ice flow and of the paleoclimatic records archived in ice.

  17. Inferring interaction partners from protein sequences

    PubMed Central

    Bitbol, Anne-Florence; Dwyer, Robert S.; Colwell, Lucy J.; Wingreen, Ned S.

    2016-01-01

    Specific protein−protein interactions are crucial in the cell, both to ensure the formation and stability of multiprotein complexes and to enable signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interaction partners, causing their sequences to be correlated. Here we exploit these correlations to accurately identify, from sequence data alone, which proteins are specific interaction partners. Our general approach, which employs a pairwise maximum entropy model to infer couplings between residues, has been successfully used to predict the 3D structures of proteins from sequences. Thus inspired, we introduce an iterative algorithm to predict specific interaction partners from two protein families whose members are known to interact. We first assess the algorithm’s performance on histidine kinases and response regulators from bacterial two-component signaling systems. We obtain a striking 0.93 true positive fraction on our complete dataset without any a priori knowledge of interaction partners, and we uncover the origin of this success. We then apply the algorithm to proteins from ATP-binding cassette (ABC) transporter complexes, and obtain accurate predictions in these systems as well. Finally, we present two metrics that accurately distinguish interacting protein families from noninteracting ones, using only sequence data. PMID:27663738

  18. Inferring unstable equilibrium configurations from experimental data

    NASA Astrophysics Data System (ADS)

    Virgin, L. N.; Wiebe, R.; Spottswood, S. M.; Beberniss, T.

    2016-09-01

    This research considers the structural behavior of slender, mechanically buckled beams and panels of the type commonly found in aerospace structures. The specimens were deflected and then clamped in a rigid frame in order to exhibit snap-through. That is, the initial equilibrium and the buckled (snapped-through) equilibrium configurations both co-existed for the given clamped conditions. In order to transit between these two stable equilibrium configurations (for example, under the action of an externally applied load), it is necessary for the structural component to pass through an intermediate unstable equilibrium configuration. A sequence of sudden impacts was imparted to the system, of various strengths and at various locations. The goal of this impact force was to induce relatively intermediate-sized transients that effectively slowed-down in the vicinity of the unstable equilibrium configuration. Thus, monitoring the velocity of the motion, and specifically its slowing down, should give an indication of the presence of an equilibrium configuration, even though it is unstable and not amenable to direct experimental observation. A digital image correlation (DIC) system was used in conjunction with an instrumented impact hammer to track trajectories and statistical methods used to infer the presence of unstable equilibria in both a beam and a panel.

  19. Bayesian inference in physics: case studies

    NASA Astrophysics Data System (ADS)

    Dose, V.

    2003-09-01

    This report describes the Bayesian approach to probability theory with emphasis on the application to the evaluation of experimental data. A brief summary of Bayesian principles is given, with a discussion of concepts, terminology and pitfalls. The step from Bayesian principles to data processing involves major numerical efforts. We address the presently employed procedures of numerical integration, which are mainly based on the Monte Carlo method. The case studies include examples from electron spectroscopies, plasma physics, ion beam analysis and mass spectrometry. Bayesian solutions to the ubiquitous problem of spectrum restoration are presented and advantages and limitations are discussed. Parameter estimation within the Bayesian framework is shown to allow for the incorporation of expert knowledge which in turn allows the treatment of under-determined problems which are inaccessible by the traditional maximum likelihood method. A unique and extremely valuable feature of Bayesian theory is the model comparison option. Bayesian model comparison rests on Ockham's razor which limits the complexity of a model to the amount necessary to explain the data without fitting noise. Finally we deal with the treatment of inconsistent data. They arise frequently in experimental work either from incorrect estimation of the errors associated with a measurement or alternatively from distortions of the measurement signal by some unrecognized spurious source. Bayesian data analysis sometimes meets with spectacular success. However, the approach cannot do wonders, but it does result in optimal robust inferences on the basis of all available and explicitly declared information.

  20. Mathematical inference in one point microrheology

    NASA Astrophysics Data System (ADS)

    Hohenegger, Christel; McKinley, Scott

    2016-11-01

    Pioneered by the work of Mason and Weitz, one point passive microrheology has been successfully applied to obtaining estimates of the loss and storage modulus of viscoelastic fluids when the mean-square displacement obeys a local power law. Using numerical simulations of a fluctuating viscoelastic fluid model, we study the problem of recovering the mechanical parameters of the fluid's memory kernel using statistical inference like mean-square displacements and increment auto-correlation functions. Seeking a better understanding of the influence of the assumptions made in the inversion process, we mathematically quantify the uncertainty in traditional one point microrheology for simulated data and demonstrate that a large family of memory kernels yields the same statistical signature. We consider both simulated data obtained from a full viscoelastic fluid simulation of the unsteady Stokes equations with fluctuations and from a Generalized Langevin Equation of the particle's motion described by the same memory kernel. From the theory of inverse problems, we propose an alternative method that can be used to recover information about the loss and storage modulus and discuss its limitations and uncertainties. NSF-DMS 1412998.

  1. BAYESIAN INFERENCE OF CMB GRAVITATIONAL LENSING

    SciTech Connect

    Anderes, Ethan; Wandelt, Benjamin D.; Lavaux, Guilhem

    2015-08-01

    The Planck satellite, along with several ground-based telescopes, has mapped the cosmic microwave background (CMB) at sufficient resolution and signal-to-noise so as to allow a detection of the subtle distortions due to the gravitational influence of the intervening matter distribution. A natural modeling approach is to write a Bayesian hierarchical model for the lensed CMB in terms of the unlensed CMB and the lensing potential. So far there has been no feasible algorithm for inferring the posterior distribution of the lensing potential from the lensed CMB map. We propose a solution that allows efficient Markov Chain Monte Carlo sampling from the joint posterior of the lensing potential and the unlensed CMB map using the Hamiltonian Monte Carlo technique. The main conceptual step in the solution is a re-parameterization of CMB lensing in terms of the lensed CMB and the “inverse lensing” potential. We demonstrate a fast implementation on simulated data, including noise and a sky cut, that uses a further acceleration based on a very mild approximation of the inverse lensing potential. We find that the resulting Markov Chain has short correlation lengths and excellent convergence properties, making it promising for applications to high-resolution CMB data sets in the future.

  2. Bell's theorem, inference, and quantum transactions

    NASA Astrophysics Data System (ADS)

    Garrett, A. J. M.

    1990-04-01

    Bell's theorem is expounded as an analysis in Bayesian inference. Assuming the result of a spin measurement on a particle is governed by a causal variable internal (hidden, “local”) to the particle, one learns about it by making a spin measurement; thence about the internal variable of a second particle correlated with the first; and from there predicts the probabilistic result of spin measurements on the second particle. Such predictions are violated by experiment: locality/causality fails. The statistical nature of the observations rules out signalling; acausal, superluminal, or otherwise. Quantum mechanics is irrelevant to this reasoning, although its correct predictions of experiment imply that it has a nonlocal/acausal interpretation. Cramer's new transactional interpretation, which incorporates this feature by adapting the Wheeler-Feynman idea of advanced and retarded processes to the quantum laws, is advocated. It leads to an invaluable way of envisaging quantum processes. The usual paradoxes melt before this, and one, the “delayed choice” experiment, is chosen for detailed inspection. Nonlocality implies practical difficulties in influencing hidden variables, which provides a very plausible explanation for why they have not yet been found; from this standpoint, Bell's theorem reinforces arguments in favor of hidden variables.

  3. Probabilistic learning and inference in schizophrenia

    PubMed Central

    Averbeck, Bruno B.; Evans, Simon; Chouhan, Viraj; Bristow, Eleanor; Shergill, Sukhwinder S.

    2010-01-01

    Patients with schizophrenia make decisions on the basis of less evidence when required to collect information to make an inference, a behavior often called jumping to conclusions. The underlying basis for this behaviour remains controversial. We examined the cognitive processes underpinning this finding by testing subjects on the beads task, which has been used previously to elicit jumping to conclusions behaviour, and a stochastic sequence learning task, with a similar decision theoretic structure. During the sequence learning task, subjects had to learn a sequence of button presses, while receiving noisy feedback on their choices. We fit a Bayesian decision making model to the sequence task and compared model parameters to the choice behavior in the beads task in both patients and healthy subjects. We found that patients did show a jumping to conclusions style; and those who picked early in the beads task tended to learn less from positive feedback in the sequence task. This favours the likelihood of patients selecting early because they have a low threshold for making decisions, and that they make choices on the basis of relatively little evidence. PMID:20810252

  4. Impact of nonignorable coarsening on Bayesian inference.

    PubMed

    Zhang, Jiameng; Heitjan, Daniel F

    2007-10-01

    The coarse data model of Heitjan and Rubin (1991) generalizes the missing data model of Rubin (1976) to cover other forms of incompleteness such as censoring and grouping. The model has 2 components: an ideal data model describing the distribution of the quantity of interest and a coarsening mechanism that describes a distribution over degrees of coarsening given the ideal data. The coarsening mechanism is said to be nonignorable when the degree of coarsening depends on an incompletely observed ideal outcome, in which case failure to properly account for it can spoil inferences. A theme in recent research is to measure sensitivity to nonignorability by evaluating the effect of a small departure from ignorability on the maximum likelihood estimate (MLE) of a parameter of the ideal data model. One such construct is the "index of local sensitivity to nonignorability" (ISNI) (Troxel and others, 2004), which is the derivative of the MLE with respect to a nonignorability parameter evaluated at the ignorable model. In this paper, we adapt ISNI to Bayesian modeling by instead defining it as the derivative of the posterior expectation. We propose the application of ISNI as a first step in judging the robustness of a Bayesian analysis to nonignorable coarsening. We derive formulas for a range of models and apply the method to evaluate sensitivity to nonignorable coarsening in 2 real data examples, one involving missing CD4 counts in an HIV trial and the other involving potentially informatively censored relapse times in a leukemia trial.

  5. Atomic Inference from Weak Gravitational Lensing Data

    SciTech Connect

    Marshall, Phil; /KIPAC, Menlo Park

    2005-12-14

    We present a novel approach to reconstructing the projected mass distribution from the sparse and noisy weak gravitational lensing shear data. The reconstructions are regularized via the knowledge gained from numerical simulations of clusters, with trial mass distributions constructed from n NFW profile ellipsoidal components. The parameters of these ''atoms'' are distributed a priori as in the simulated clusters. Sampling the mass distributions from the atom parameter probability density function allows estimates of the properties of the mass distribution to be generated, with error bars. The appropriate number of atoms is inferred from the data itself via the Bayesian evidence, and is typically found to be small, reecting the quality of the data. Ensemble average mass maps are found to be robust to the details of the noise realization, and succeed in recovering the demonstration input mass distribution (from a realistic simulated cluster) over a wide range of scales. As an application of such a reliable mapping algorithm, we comment on the residuals of the reconstruction and the implications for predicting convergence and shear at specific points on the sky.

  6. Inference by replication in densely connected systems

    SciTech Connect

    Neirotti, Juan P.; Saad, David

    2007-10-15

    An efficient Bayesian inference method for problems that can be mapped onto dense graphs is presented. The approach is based on message passing where messages are averaged over a large number of replicated variable systems exposed to the same evidential nodes. An assumption about the symmetry of the solutions is required for carrying out the averages; here we extend the previous derivation based on a replica-symmetric- (RS)-like structure to include a more complex one-step replica-symmetry-breaking-like (1RSB-like) ansatz. To demonstrate the potential of the approach it is employed for studying critical properties of the Ising linear perceptron and for multiuser detection in code division multiple access (CDMA) under different noise models. Results obtained under the RS assumption in the noncritical regime give rise to a highly efficient signal detection algorithm in the context of CDMA; while in the critical regime one observes a first-order transition line that ends in a continuous phase transition point. Finite size effects are also observed. While the 1RSB ansatz is not required for the original problems, it was applied to the CDMA signal detection problem with a more complex noise model that exhibits RSB behavior, resulting in an improvement in performance.

  7. Inferring human mobility using communication patterns.

    PubMed

    Palchykov, Vasyl; Mitrović, Marija; Jo, Hang-Hyun; Saramäki, Jari; Pan, Raj Kumar

    2014-08-22

    Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.

  8. Inferring human mobility using communication patterns

    NASA Astrophysics Data System (ADS)

    Palchykov, Vasyl; Mitrović, Marija; Jo, Hang-Hyun; Saramäki, Jari; Pan, Raj Kumar

    2014-08-01

    Understanding the patterns of mobility of individuals is crucial for a number of reasons, from city planning to disaster management. There are two common ways of quantifying the amount of travel between locations: by direct observations that often involve privacy issues, e.g., tracking mobile phone locations, or by estimations from models. Typically, such models build on accurate knowledge of the population size at each location. However, when this information is not readily available, their applicability is rather limited. As mobile phones are ubiquitous, our aim is to investigate if mobility patterns can be inferred from aggregated mobile phone call data alone. Using data released by Orange for Ivory Coast, we show that human mobility is well predicted by a simple model based on the frequency of mobile phone calls between two locations and their geographical distance. We argue that the strength of the model comes from directly incorporating the social dimension of mobility. Furthermore, as only aggregated call data is required, the model helps to avoid potential privacy problems.

  9. Human Inferences about Sequences: A Minimal Transition Probability Model

    PubMed Central

    2016-01-01

    The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or surprise signals recorded in electrophysiology and functional MRI. Here, we explore the hypothesis that the brain acts as a near-optimal inference device that constantly attempts to infer the time-varying matrix of transition probabilities between the stimuli it receives, even when those stimuli are in fact fully unpredictable. This parsimonious Bayesian model, with a single free parameter, accounts for a broad range of findings on surprise signals, sequential effects and the perception of randomness. Notably, it explains the pervasive asymmetry between repetitions and alternations encountered in those studies. Our analysis suggests that a neural machinery for inferring transition probabilities lies at the core of human sequence knowledge. PMID:28030543

  10. Toddlers infer higher-order relational principles in causal learning.

    PubMed

    Walker, Caren M; Gopnik, Alison

    2014-01-01

    Children make inductive inferences about the causal properties of individual objects from a very young age. When can they infer higher-order relational properties? In three experiments, we examined 18- to 30-month-olds' relational inferences in a causal task. Results suggest that at this age, children are able to infer a higher-order relational causal principle from just a few observations and use this inference to guide their own subsequent actions and bring about a novel causal outcome. Moreover, the children passed a revised version of the relational match-to-sample task that has proven very difficult for nonhuman primates. The findings are considered in light of their implications for understanding the nature of relational and causal reasoning, and their evolutionary origins.

  11. Wisdom of crowds for robust gene network inference

    PubMed Central

    Marbach, Daniel; Costello, James C.; Küffner, Robert; Vega, Nicci; Prill, Robert J.; Camacho, Diogo M.; Allison, Kyle R.; Kellis, Manolis; Collins, James J.; Stolovitzky, Gustavo

    2012-01-01

    Reconstructing gene regulatory networks from high-throughput data is a long-standing problem. Through the DREAM project (Dialogue on Reverse Engineering Assessment and Methods), we performed a comprehensive blind assessment of over thirty network inference methods on Escherichia coli, Staphylococcus aureus, Saccharomyces cerevisiae, and in silico microarray data. We characterize performance, data requirements, and inherent biases of different inference approaches offering guidelines for both algorithm application and development. We observe that no single inference method performs optimally across all datasets. In contrast, integration of predictions from multiple inference methods shows robust and high performance across diverse datasets. Thereby, we construct high-confidence networks for E. coli and S. aureus, each comprising ~1700 transcriptional interactions at an estimated precision of 50%. We experimentally test 53 novel interactions in E. coli, of which 23 were supported (43%). Our results establish community-based methods as a powerful and robust tool for the inference of transcriptional gene regulatory networks. PMID:22796662

  12. Quantum-Like Representation of Non-Bayesian Inference

    NASA Astrophysics Data System (ADS)

    Asano, M.; Basieva, I.; Khrennikov, A.; Ohya, M.; Tanaka, Y.

    2013-01-01

    This research is related to the problem of "irrational decision making or inference" that have been discussed in cognitive psychology. There are some experimental studies, and these statistical data cannot be described by classical probability theory. The process of decision making generating these data cannot be reduced to the classical Bayesian inference. For this problem, a number of quantum-like coginitive models of decision making was proposed. Our previous work represented in a natural way the classical Bayesian inference in the frame work of quantum mechanics. By using this representation, in this paper, we try to discuss the non-Bayesian (irrational) inference that is biased by effects like the quantum interference. Further, we describe "psychological factor" disturbing "rationality" as an "environment" correlating with the "main system" of usual Bayesian inference.

  13. Infections Revealing Complement Deficiency in Adults

    PubMed Central

    Audemard-Verger, A.; Descloux, E.; Ponard, D.; Deroux, A.; Fantin, B.; Fieschi, C.; John, M.; Bouldouyre, A.; Karkowsi, L.; Moulis, G.; Auvinet, H.; Valla, F.; Lechiche, C.; Davido, B.; Martinot, M.; Biron, C.; Lucht, F.; Asseray, N.; Froissart, A.; Buzelé, R.; Perlat, A.; Boutboul, D.; Fremeaux-Bacchi, V.; Isnard, S.; Bienvenu, B.

    2016-01-01

    Abstract Complement system is a part of innate immunity, its main function is to protect human from bacterial infection. As genetic disorders, complement deficiencies are often diagnosed in pediatric population. However, complement deficiencies can also be revealed in adults but have been poorly investigated. Herein, we describe a case series of infections revealing complement deficiency in adults to study clinical spectrum and management of complement deficiencies. A nationwide retrospective study was conducted in French university and general hospitals in departments of internal medicine, infectious diseases enrolling patients older than 15 years old who had presented at least one infection leading to a complement deficiency diagnosis. Forty-one patients included between 2002 and 2015 in 19 different departments were enrolled in this study. The male-to-female ratio was 1.3 and the mean age at diagnosis was 28 ± 14 (15–67) years. The main clinical feature was Neisseria meningitidis meningitis 75% (n = 31/41) often involving rare serotype: Y (n = 9) and W 135 (n = 7). The main complement deficiency observed was the common final pathway deficiency 83% (n = 34/41). Half of the cohort displayed severe sepsis or septic shock at diagnosis (n = 22/41) but no patient died. No patient had family history of complement deficiency. The mean follow-up was 1.15 ± 1.95 (0.1–10) years. Half of the patients had already suffered from at least one infection before diagnosis of complement deficiency: meningitis (n = 13), pneumonia (n = 4), fulminans purpura (n = 1), or recurrent otitis (n = 1). Near one-third (n = 10/39) had received prophylactic antibiotics (cotrimoxazole or penicillin) after diagnosis of complement deficiency. The vaccination coverage rate, at the end of the follow-up, for N meningitidis, Streptococcus pneumonia, and Haemophilius influenzae were, respectively, 90% (n = 33/37), 47% (n = 17/36), and 35

  14. Genetics Home Reference: dopamine beta-hydroxylase deficiency

    MedlinePlus

    ... Genetics Home Health Conditions dopamine beta-hydroxylase deficiency dopamine beta-hydroxylase deficiency Enable Javascript to view the ... boxes. Download PDF Open All Close All Description Dopamine beta (β)-hydroxylase deficiency is a condition that ...

  15. G6PD Deficiency (Glucose-6-Phosphate Dehydrogenase) (For Parents)

    MedlinePlus

    ... trigger, is removed. In rare cases, G6PD deficiency leads to chronic anemia . With the right precautions, a child with G6PD deficiency can lead a healthy and active life. About G6PD Deficiency ...

  16. Genetics Home Reference: ataxia with vitamin E deficiency

    MedlinePlus

    ... Conditions ataxia with vitamin E deficiency ataxia with vitamin E deficiency Enable Javascript to view the expand/collapse boxes. ... PDF Open All Close All Description Ataxia with vitamin E deficiency is a disorder that impairs the body's ability ...

  17. Who Is at Risk for Alpha-1 Antitrypsin Deficiency?

    MedlinePlus

    ... for Alpha-1 Antitrypsin Deficiency? Alpha-1 antitrypsin (AAT) deficiency occurs in all ethnic groups. However, the ... most often in White people of European descent. AAT deficiency is an inherited condition. "Inherited" means the ...

  18. Genetics Home Reference: iron-refractory iron deficiency anemia

    MedlinePlus

    ... refractory iron deficiency anemia iron-refractory iron deficiency anemia Enable Javascript to view the expand/collapse boxes. ... All Close All Description Iron-refractory iron deficiency anemia is one of many types of anemia , which ...

  19. Genetics Home Reference: aromatic l-amino acid decarboxylase deficiency

    MedlinePlus

    ... l-amino acid decarboxylase deficiency aromatic l-amino acid decarboxylase deficiency Enable Javascript to view the expand/ ... Open All Close All Description Aromatic l-amino acid decarboxylase (AADC) deficiency is an inherited disorder that ...

  20. Leptin deficiency in maltreated children.

    PubMed

    Danese, A; Dove, R; Belsky, D W; Henchy, J; Williams, B; Ambler, A; Arseneault, L

    2014-09-23

    Consistent with findings from experimental research in nonhuman primates exposed to early-life stress, children exposed to maltreatment are at high risk of detrimental physical health conditions, such as obesity and systemic inflammation. Because leptin is a key molecule involved in the regulation of both energy balance and immunity, we investigated abnormalities in leptin physiology among maltreated children. We measured leptin, body mass index and C-reactive protein in 170 12-year-old children members of the Environmental-Risk Longitudinal Twin Study, for whom we had prospectively-collected information on maltreatment exposure. We found that maltreated children exhibited blunted elevation in leptin levels in relation to increasing levels of physiological stimuli, adiposity and inflammation, compared with a group of non-maltreated children matched for gender, zygosity and socioeconomic status. These findings were also independent of key potential artifacts and confounders, such as time of day at sample collection, history of food insecurity, pubertal maturation and depressive symptoms. Furthermore, using birth weight as a proxy measure for leptin, we found that physiological abnormalities were presumably not present at birth in children who went on to be maltreated but only emerged over the course of childhood, after maltreatment exposure. Leptin deficiency may contribute to onset, persistence and progression of physical health problems in maltreated children.

  1. How I treat ADA deficiency.

    PubMed

    Gaspar, H Bobby; Aiuti, Alessandro; Porta, Fulvio; Candotti, Fabio; Hershfield, Michael S; Notarangelo, Luigi D

    2009-10-22

    Adenosine deaminase deficiency is a disorder of purine metabolism leading to severe combined immunodeficiency (ADA-SCID). Without treatment, the condition is fatal and requires early intervention. Haematopoietic stem cell transplantation is the major treatment for ADA-SCID, although survival following different donor sources varies considerably. Unlike other SCID forms, 2 other options are available for ADA-SCID: enzyme replacement therapy (ERT) with pegylated bovine ADA, and autologous haematopoietic stem cell gene therapy (GT). Due to the rarity of the condition, the lack of large scale outcome studies, and availability of different treatments, guidance on treatment strategies is limited. We have reviewed the currently available evidence and together with our experience of managing this condition propose a consensus management strategy. Matched sibling donor transplants represent a successful treatment option with high survival rates and excellent immune recovery. Mismatched parental donor transplants have a poor survival outcome and should be avoided unless other treatments are unavailable. ERT and GT both show excellent survival, and therefore the choice between ERT, MUD transplant, or GT is difficult and dependent on several factors, including accessibility to the different modalities, response of patients to long-term ERT, and the attitudes of physicians and parents to the short- and potential long-term risks associated with different treatments.

  2. Deficient approaches to human neuroimaging

    PubMed Central

    Stelzer, Johannes; Lohmann, Gabriele; Mueller, Karsten; Buschmann, Tilo; Turner, Robert

    2014-01-01

    Functional magnetic resonance imaging (fMRI) is the workhorse of imaging-based human cognitive neuroscience. The use of fMRI is ever-increasing; within the last 4 years more fMRI studies have been published than in the previous 17 years. This large body of research has mainly focused on the functional localization of condition- or stimulus-dependent changes in the blood-oxygenation-level dependent signal. In recent years, however, many aspects of the commonly practiced analysis frameworks and methodologies have been critically reassessed. Here we summarize these critiques, providing an overview of the major conceptual and practical deficiencies in widely used brain-mapping approaches, and exemplify some of these issues by the use of imaging data and simulations. In particular, we discuss the inherent pitfalls and shortcomings of methodologies for statistical parametric mapping. Our critique emphasizes recent reports of excessively high numbers of both false positive and false negative findings in fMRI brain mapping. We outline our view regarding the broader scientific implications of these methodological considerations and briefly discuss possible solutions. PMID:25071503

  3. Perinatal iron deficiency and neurocognitive development

    PubMed Central

    Radlowski, Emily C.; Johnson, Rodney W.

    2013-01-01

    Iron deficiency is the most common form of nutrient deficiency worldwide. It is highly prevalent due to the limited availability of high quality food in developing countries and poor dietary habits in industrialized countries. According to the World Health Organization, it affects nearly 2 billion people and up to 50% of women who are pregnant. Maternal anemia during pregnancy is especially burdensome to healthy neurodevelopment in the fetus because iron is needed for proper neurogenesis, development, and myelination. Maternal anemia also increases the risk of low birth weight, either due to premature birth or fetal growth restriction, which is associated with delayed neurocognitive development and even psychiatric illness. As rapid neurodevelopment continues after birth infants that received sufficient iron in utero, but that receive a low iron diet after 6 months of age, also show deficits in neurocognitive development, including impairments in learning and memory. Unfortunately, the neurocognitive complications of iron deficiency during critical pre- and postnatal periods of brain development are difficult to remedy, persisting into adulthood. Thus, preventing iron deficiency in the pre- and postnatal periods is critical as is devising new means to recapture cognitive function in individuals who experienced early iron deficiency. This review will discuss the prevalence of pre- and postnatal iron deficiency, the mechanism, and effects of iron deficiency on brain and cognitive development. PMID:24065908

  4. Fetal polyol metabolism in copper deficiency

    SciTech Connect

    Fields, M.; Lewis, C.G.; Beal, T. )

    1989-02-09

    Since pregnant rats consuming fructose, copper deficient diets fail to give birth, the relationship between maternal copper deficiency, polyol metabolism and fetal mortality was investigated. Forty Sprague-Dawley rats were fed from conception one of the following diets: fructose, copper deficient; fructose, copper adequate; starch, copper deficient or starch, copper adequate. The deficient diets contained 0.6 ug Cu and the adequate 6.0 ug Cu/g diet. Pregnancy was terminated at day 19 of gestation. Glucose, sorbitol and fructose were measured in maternal blood, placenta and fetal liver. Fructose consumption during pregnancy resulted in higher levels of fructose and sorbitol in maternal blood when compared to starch. In the fructose dietary groups, the placenta and fetal liver contained extremely high levels of glucose, fructose and sorbitol compared to the corresponding metabolites from the starch dietary groups. Copper deficiency further elevated fructose and sorbitol concentrations in the placenta and fetal liver respectively. Since high tissue levels of glucose, fructose and sorbitol have been shown to have deleterious effects on cellular metabolism, these data suggest that when fructose was fed during pregnancy the combination of an aberration of carbohydrate metabolism with copper deficiency could be responsible for the pathology and mortality of the developing fetus.

  5. Iodine deficiency, more than cretinism and goiter.

    PubMed

    Verheesen, R H; Schweitzer, C M

    2008-11-01

    Recent reports of the World Health Organization show iodine deficiency to be a worldwide occurring health problem. As iodine status is based on median urinary iodine excretion, even in countries regarded as iodine sufficient, a considerable part of the population may be iodine deficient. Iodine is a key element in the synthesis of thyroid hormones and as a consequence, severe iodine deficiency results in hypothyroidism, goiter, and cretinism with the well known biochemical alterations. However, it is also known that iodine deficiency may give rise to clinical symptoms of hypothyroidism without abnormality of thyroid hormone values. This led us to the hypothesis that iodine deficiency may give rise to subtle impairment of thyroid function leading to clinical syndromes resembling hypothyroidism or diseases that have been associated with the occurrence of hypothyroidism. We describe several clinical conditions possibly linked to iodine deficiency, a connection that has not been made thus far. In this paper we will focus on the relationship between iodine deficiency and obesity, attention deficit hyperactivity disorder (ADHD), psychiatric disorders, fibromyalgia, and malignancies.

  6. Inferring climate variability from skewed proxy records

    NASA Astrophysics Data System (ADS)

    Emile-Geay, J.; Tingley, M.

    2013-12-01

    Many paleoclimate analyses assume a linear relationship between the proxy and the target climate variable, and that both the climate quantity and the errors follow normal distributions. An ever-increasing number of proxy records, however, are better modeled using distributions that are heavy-tailed, skewed, or otherwise non-normal, on account of the proxies reflecting non-normally distributed climate variables, or having non-linear relationships with a normally distributed climate variable. The analysis of such proxies requires a different set of tools, and this work serves as a cautionary tale on the danger of making conclusions about the underlying climate from applications of classic statistical procedures to heavily skewed proxy records. Inspired by runoff proxies, we consider an idealized proxy characterized by a nonlinear, thresholded relationship with climate, and describe three approaches to using such a record to infer past climate: (i) applying standard methods commonly used in the paleoclimate literature, without considering the non-linearities inherent to the proxy record; (ii) applying a power transform prior to using these standard methods; (iii) constructing a Bayesian model to invert the mechanistic relationship between the climate and the proxy. We find that neglecting the skewness in the proxy leads to erroneous conclusions and often exaggerates changes in climate variability between different time intervals. In contrast, an explicit treatment of the skewness, using either power transforms or a Bayesian inversion of the mechanistic model for the proxy, yields significantly better estimates of past climate variations. We apply these insights in two paleoclimate settings: (1) a classical sedimentary record from Laguna Pallcacocha, Ecuador (Moy et al., 2002). Our results agree with the qualitative aspects of previous analyses of this record, but quantitative departures are evident and hold implications for how such records are interpreted, and

  7. Inferring mental states from neuroimaging data: From reverse inference to large-scale decoding

    PubMed Central

    Poldrack, Russell A.

    2011-01-01

    A common goal of neuroimaging research is to use imaging data to identify the mental processes that are engaged when a subject performs a mental task. The use of reasoning from activation to mental functions, known as “reverse inference”, has been previously criticized on the basis that it does not take into account how selectively the area is activated by the mental process in question. In this Perspective, I outline the critique of informal reverse inference, and describe a number of new developments that provide the ability to more formally test the predictive power of neuroimaging data. PMID:22153367

  8. Statistical Inference for Data Adaptive Target Parameters.

    PubMed

    Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

    2016-05-01

    Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

  9. Steroid 21 hydroxylase deficiency congenital adrenal hyperplasia.

    PubMed

    Nimkarn, Saroj; Lin-Su, Karen; New, Maria I

    2011-10-01

    Steroid 21 hydroxylase deficiency is the most common form of congenital adrenal hyperplasia (CAH). The severity of this disorder depends on the extent of impaired enzymatic activity, which is caused by various mutations of the 21 hydroxylase gene. This article reviews adrenal steroidogenesis and the pathophysiology of 21 hydroxylase deficiency. The three forms of CAH are then discussed in terms of clinical presentation, diagnosis and treatment, and genetic basis. Prenatal diagnosis and treatment are also reviewed. The goal of therapy is to correct the deficiency in cortisol secretion and suppress androgen overproduction. Glucocorticoid replacement has been the mainstay of treatment for CAH, but new treatment strategies continue to be developed and studied.

  10. Iron-refractory iron deficiency anemia (IRIDA).

    PubMed

    Heeney, Matthew M; Finberg, Karin E

    2014-08-01

    Iron deficiency anemia is a common global problem whose etiology is typically attributed to acquired inadequate dietary intake and/or chronic blood loss. However, in several kindreds multiple family members are affected with iron deficiency anemia that is unresponsive to oral iron supplementation and only partially responsive to parenteral iron therapy. The discovery that many of these cases harbor mutations in the TMPRSS6 gene led to the recognition that they represent a single clinical entity: iron-refractory iron deficiency anemia (IRIDA). This article reviews clinical features of IRIDA, recent genetic studies, and insights this disorder provides into the regulation of systemic iron homeostasis.

  11. Molecular genetics of human lactase deficiencies.

    PubMed

    Järvelä, Irma; Torniainen, Suvi; Kolho, Kaija-Leena

    2009-01-01

    Lactase non-persistence (adult-type hypolactasia) is present in more than half of the human population and is caused by the down-regulation of lactase enzyme activity during childhood. Congenital lactase deficiency (CLD) is a rare severe gastrointestinal disorder of new-borns enriched in the Finnish population. Both lactase deficiencies are autosomal recessive traits and characterized by diminished expression of lactase activity in the intestine. Genetic variants underlying both forms have been identified. Here we review the current understanding of the molecular defects of human lactase deficiencies and their phenotype-genotype correlation, the implications on clinical practice, and the understanding of their function and role in human evolution.

  12. Unilateral Isolated Proximal Femoral Focal Deficiency

    PubMed Central

    Doğer, Emek; Köpük, Şule Y.; Çakıroğlu, Yiğit; Çakır, Özgür; Yücesoy, Gülseren

    2013-01-01

    Objective. To discuss a patient with a prenatal diagnosis of unilateral isolated femoral focal deficiency. Case. Antenatal diagnosis of unilateral isolated femoral focal deficiency was made at 20 weeks of gestation. The length of left femur was shorter than the right, and fetal femur length was below the fifth percentile. Proximal femoral focal deficiency was diagnosed. After delivery, the diagnosis was confirmed with skeletal radiographs and magnetic resonance imaging. In prenatal ultrasonographic examination, the early recognition and exclusion of skeletal dysplasias is important; moreover, treatment plans should be initiated, and valuable information should be provided to the family. PMID:23984135

  13. Nutrition and hair: deficiencies and supplements.

    PubMed

    Finner, Andreas M

    2013-01-01

    Hair follicle cells have a high turnover. A caloric deprivation or deficiency of several components, such as proteins, minerals, essential fatty acids, and vitamins, caused by inborn errors or reduced uptake, can lead to structural abnormalities, pigmentation changes, or hair loss, although exact data are often lacking. The diagnosis is established through a careful history, clinical examination of hair loss activity, and hair quality and confirmed through targeted laboratory tests. Examples of genetic hair disorders caused by reduced nutritional components are zinc deficiency in acrodermatitis enteropathica and copper deficiency in Menkes kinky hair syndrome.

  14. Severe Vitamin D Deficiency Causing Kyphoscoliosis.

    PubMed

    Singhai, Abhishek; Banzal, Subodh

    2013-01-01

    Vitamin D deficiency is common among Indian population. Women are especially at risk for severe vitamin D deficiency. The risk is higher for those who are multiparous and postmenopausal. Poor exposure to sunlight, higher latitude, winter season, inadequate diet, older age, obesity and malabsorption are also important risk factors. Symptoms of hypovitaminosis D, including diffuse or migratory pain affecting several sites (especially the shoulder, pelvis, ribcage and lower back) have also been misdiagnosed as musculoskeletal disorders, including fibromyalgia, polymyalgia rheumatica and ankylosing spondylitis. Here, we report two cases presented with kyphoscoliosis, diagnosed to have severe vitamin D deficiency.

  15. Severe Vitamin D Deficiency Causing Kyphoscoliosis

    PubMed Central

    Singhai, Abhishek; Banzal, Subodh

    2013-01-01

    Vitamin D deficiency is common among Indian population. Women are especially at risk for severe vitamin D deficiency. The risk is higher for those who are multiparous and postmenopausal. Poor exposure to sunlight, higher latitude, winter season, inadequate diet, older age, obesity and malabsorption are also important risk factors. Symptoms of hypovitaminosis D, including diffuse or migratory pain affecting several sites (especially the shoulder, pelvis, ribcage and lower back) have also been misdiagnosed as musculoskeletal disorders, including fibromyalgia, polymyalgia rheumatica and ankylosing spondylitis. Here, we report two cases presented with kyphoscoliosis, diagnosed to have severe vitamin D deficiency. PMID:26664847

  16. Hypopituitarism: growth hormone and corticotropin deficiency.

    PubMed

    Capatina, Cristina; Wass, John A H

    2015-03-01

    This article presents an overview of adult growth hormone deficiency (AGHD) and corticotropin deficiency (central adrenal failure, CAI). Both conditions can result from various ailments affecting the hypothalamus or pituitary gland (most frequently a tumor in the area or its treatment). Clinical manifestations are subtle in AGHD but potentially life-threatening in CAI. The diagnosis needs dynamic testing in most cases. Treatment of AGHD is recommended in patients with documented severe deficiency, and treatment of CAI is mandatory in all cases. Despite significant progress in replacement hormonal therapy, more physiologic treatments and more reliable indicators of treatment adequacy are still needed.

  17. Causal inference in biology networks with integrated belief propagation.

    PubMed

    Chang, Rui; Karr, Jonathan R; Schadt, Eric E

    2015-01-01

    Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

  18. Active inference and robot control: a case study.

    PubMed

    Pio-Lopez, Léo; Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

    2016-09-01

    Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours.

  19. Disjunctive illusory inferences and how to eliminate them.

    PubMed

    Khemlani, Sangeet; Johnson-Laird, P N

    2009-07-01

    The mental model theory of reasoning postulates that individuals construct mental models of the possibilities in which the premises of an inference hold and that these models represent what is true but not what is false. An unexpected consequence of this assumption is that certain premises should yield systematically invalid inferences. This prediction is unique among current theories of reasoning, because no alternative theory, whether based on formal rules of inference or on probabilistic considerations, predicts these illusory inferences. We report three studies of novel illusory inferences that depend on embedded disjunctions-for example, premises of this sort: A or else (B or else C). The theory distinguishes between those embedded disjunctions that should yield illusions and those that should not. In Experiment 1, we corroborated this distinction. In Experiment 2, we extended the illusory inferences to a more stringently controlled set of problems. In Experiment 3, we established a novel method for reducing illusions by calling for participants to make auxiliary inferences.

  20. Active inference and robot control: a case study

    PubMed Central

    Nizard, Ange; Friston, Karl; Pezzulo, Giovanni

    2016-01-01

    Active inference is a general framework for perception and action that is gaining prominence in computational and systems neuroscience but is less known outside these fields. Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. By manipulating visual and proprioceptive noise levels, we show under which conditions robot control under the active inference scheme is accurate. Besides accurate control, our analysis of the internal system dynamics (e.g. the dynamics of the hidden states that are inferred during the inference) sheds light on key aspects of the framework such as the quintessentially multimodal nature of control and the differential roles of proprioception and vision. In the discussion, we consider the potential importance of being able to implement active inference in robots. In particular, we briefly review the opportunities for modelling psychophysiological phenomena such as sensory attenuation and related failures of gain control, of the sort seen in Parkinson's disease. We also consider the fundamental difference between active inference and optimal control formulations, showing that in the former the heavy lifting shifts from solving a dynamical inverse problem to creating deep forward or generative models with dynamics, whose attracting sets prescribe desired behaviours. PMID:27683002