Observing the observer (II): deciding when to decide

In a companion paper [1], we have presented a generic approach for inferring how subjects make optimal decisions under uncertainty. From a Bayesian decision theoretic perspective, uncertain representations correspond to "posterior" beliefs, which result from integrating (sensory) information with subjective "prior" beliefs. Preferences and goals are encoded through a "loss" (or "utility") function, which measures the cost incurred by making any admissible decision for any given (hidden or unknown) state of the world. By assuming that subjects make optimal decisions on the basis of updated (posterior) beliefs and utility (loss) functions, one can evaluate the likelihood of observed behaviour. In this paper, we describe a concrete implementation of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions) and demonstrate its utility by applying it to both simulated and empirical reaction time data from an associative learning task. Here, inter-trial variability in reaction times is modelled as reflecting the dynamics of the subjects' internal recognition process, i.e. the updating of representations (posterior densities) of hidden states over trials while subjects learn probabilistic audio-visual associations. We use this paradigm to demonstrate that our meta-Bayesian framework allows for (i) probabilistic inference on the dynamics of the subject's representation of environmental states, and for (ii) model selection to disambiguate between alternative preferences (loss functions) human subjects could employ when dealing with trade-offs, such as between speed and accuracy. Finally, we illustrate how our approach can be used to quantify subjective beliefs and preferences that underlie inter-individual differences in behaviour.     

Observing the observer (I): meta-bayesian models of learning and decision-making

In this paper, we present a generic approach that can be used to infer how subjects make optimal decisions under uncertainty. This approach induces a distinction between a subject's perceptual model, which underlies the representation of a hidden "state of affairs" and a response model, which predicts the ensuing behavioural (or neurophysiological) responses to those inputs. We start with the premise that subjects continuously update a probabilistic representation of the causes of their sensory inputs to optimise their behaviour. In addition, subjects have preferences or goals that guide decisions about actions given the above uncertain representation of these hidden causes or state of affairs. From a Bayesian decision theoretic perspective, uncertain representations are so-called "posterior" beliefs, which are influenced by subjective "prior" beliefs. Preferences and goals are encoded through a "loss" (or "utility") function, which measures the cost incurred by making any admissible decision for any given (hidden) state of affair. By assuming that subjects make optimal decisions on the basis of updated (posterior) beliefs and utility (loss) functions, one can evaluate the likelihood of observed behaviour. Critically, this enables one to "observe the observer", i.e. identify (context- or subject-dependent) prior beliefs and utility-functions using psychophysical or neurophysiological measures. In this paper, we describe the main theoretical components of this meta-Bayesian approach (i.e. a Bayesian treatment of Bayesian decision theoretic predictions). In a companion paper ('Observing the observer (II): deciding when to decide'), we describe a concrete implementation of it and demonstrate its utility by applying it to simulated and real reaction time data from an associative learning task.     

Evolution of human immunodeficiency virus type 1 in a patient with cross-reactive neutralizing activity in serum

Analysis of longitudinally obtained HIV-1 env sequences from an individual with reported cross-reactive neutralizing activity revealed that the majority of viral variants obtained from serum between 4 and 7 years after seroconversion were unable to persist in peripheral blood. Here we show that these viral variants were more sensitive to autologous serum neutralization, had shorter envelopes with fewer potential N-linked glycosylation sites, and showed lower replication kinetics than successfully evolving HIV-1 variants. These data reflect the host selection pressures on phenotypic characteristics of HIV-1 and illustrate in detail the dynamic interaction between HIV-1 and its host's humoral immune responses.     

Lactobacillus-dominated cervicovaginal microbiota associated with reduced HIV/STI prevalence and genital HIV viral load in African women

Cervicovaginal microbiota not dominated by lactobacilli may facilitate transmission of HIV and other sexually transmitted infections (STIs), as well as miscarriages, preterm births and sepsis in pregnant women. However, little is known about the exact nature of the microbiological changes that cause these adverse outcomes. In this study, cervical samples of 174 Rwandan female sex workers were analyzed cross-sectionally using a phylogenetic microarray. Furthermore, HIV-1 RNA concentrations were measured in cervicovaginal lavages of 58 HIV-positive women among them. We identified six microbiome clusters, representing a gradient from low semi-quantitative abundance and diversity dominated by Lactobacillus crispatus (cluster R-I, with R denoting ‘Rwanda'') and L. iners (R-II) to intermediate (R-V) and high abundance and diversity (R-III, R-IV and R-VI) dominated by a mixture of anaerobes, including Gardnerella, Atopobium and Prevotella species. Women in cluster R-I were less likely to have HIV (P=0.03), herpes simplex virus type 2 (HSV-2; P<0.01), and high-risk human papillomavirus (HPV; P<0.01) and had no bacterial STIs (P=0.15). Statistically significant trends in prevalence of viral STIs were found from low prevalence in cluster R-I, to higher prevalence in clusters R-II and R-V, and highest prevalence in clusters R-III/R-IV/R-VI. Furthermore, only 10% of HIV-positive women in clusters R-I/R-II, compared with 40% in cluster R-V, and 42% in clusters R-III/R-IV/R-VI had detectable cervicovaginal HIV-1 RNA (P_trend=0.03). We conclude that L. crispatus-dominated, and to a lesser extent L. iners-dominated, cervicovaginal microbiota are associated with a lower prevalence of HIV/STIs and a lower likelihood of genital HIV-1 RNA shedding.     

Flexibility in crosstalk between H2B ubiquitination and H3 methylation in vivo

Histone H2B ubiquitination is a dynamic modification that promotes methylation of histone H3K79 and H3K4. This crosstalk is important for the DNA damage response and has been implicated in cancer. Here, we show that in engineered yeast strains, ubiquitins tethered to every nucleosome promote H3K79 and H3K4 methylation from a proximal as well as a more distal site, but only if in a correct orientation. This plasticity indicates that the exact location of the attachment site, the native ubiquitin-lysine linkage and ubiquitination cycles are not critical for trans-histone crosstalk in vivo. The flexibility in crosstalk also indicates that other ubiquitination events may promote H3 methylation.     

The Vaginal Microbiota: What Have We Learned after a Decade of Molecular Characterization?

We conducted a systematic review of the Medline database (U.S. National Library of Medicine, National Institutes of Health, Bethesda, MD, U.S.A) to determine if consistent molecular vaginal microbiota (VMB) composition patterns can be discerned after a decade of molecular testing, and to evaluate demographic, behavioral and clinical determinants of VMB compositions. Studies were eligible when published between 1 January 2008 and 15 November 2013, and if at least one molecular technique (sequencing, PCR, DNA fingerprinting, or DNA hybridization) was used to characterize the VMB. Sixty three eligible studies were identified. These studies have now conclusively shown that lactobacilli-dominated VMB are associated with a healthy vaginal micro-environment and that bacterial vaginosis (BV) is best described as a polybacterial dysbiosis. The extent of dysbiosis correlates well with Nugent score and vaginal pH but not with the other Amsel criteria. Lactobacillus crispatus is more beneficial than L. iners. Longitudinal studies have shown that a L. crispatus-dominated VMB is more likely to shift to a L. iners-dominated or mixed lactobacilli VMB than to full dysbiosis. Data on VMB determinants are scarce and inconsistent, but dysbiosis is consistently associated with HIV, human papillomavirus (HPV), and Trichomonas vaginalis infection. In contrast, vaginal colonization with Candida spp. is more common in women with a lactobacilli-dominated VMB than in women with dysbiosis. Cervicovaginal mucosal immune responses to molecular VMB compositions have not yet been properly characterized. Molecular techniques have now become more affordable, and we make a case for incorporating them into larger epidemiological studies to address knowledge gaps in etiology and pathogenesis of dysbiosis, associations of different dysbiotic states with clinical outcomes, and to evaluate interventions aimed at restoring and maintaining a lactobacilli-dominated VMB.     

FcgammaR expression on macrophages is related to severity and chronicity of synovial inflammation and cartilage destruction during experimental immune-complex-mediated arthritis (ICA)

We investigated the role of Fcγ receptors (FcγRs) on synovial macrophages in immune-complex-mediated arthritis (ICA). ICA elicited in knee joints of C57BL/6 mice caused a short-lasting, florid inflammation and reversible loss of proteoglycans (PGs), moderate chondrocyte death, and minor erosion of the cartilage. In contrast, when ICA was induced in knee joints of Fc receptor (FcR) γ-chain^-/- C57BL/6 mice, which lack functional FcγRI and RIII, inflammation and cartilage destruction were prevented. When ICA was elicited in DBA/1 mice, a very severe, chronic inflammation was observed, and significantly more chondrocyte death and cartilage erosion than in arthritic C57BL/6 mice. The synovial lining and peritoneal macrophages of na?ve DBA/1 mice expressed a significantly higher level of FcγRs than was seen in C57BL/6 mice. Moreover, elevated and prolonged expression of IL-1 was found after stimulation of these cells with immune complexes. Zymosan or streptococcal cell walls caused comparable inflammation and only mild cartilage destruction in all strains. We conclude that FcγR expression on synovial macrophages may be related to the severity of synovial inflammation and cartilage destruction during ICA.     

Development of highly polymorphic SNP markers from the complexity reduced portion of maize [Zea mays L.] genome for use in marker-assisted breeding

The duplicated and the highly repetitive nature of the maize genome has historically impeded the development of true single nucleotide polymorphism (SNP) markers in this crop. Recent advances in genome complexity reduction methods coupled with sequencing-by-synthesis technologies permit the implementation of efficient genome-wide SNP discovery in maize. In this study, we have applied Complexity Reduction of Polymorphic Sequences technology (Keygene N.V., Wageningen, The Netherlands) for the identification of informative SNPs between two genetically distinct maize inbred lines of North and South American origins. This approach resulted in the discovery of 1,123 putative SNPs representing low and single copy loci. In silico and experimental (Illumina GoldenGate (GG) assay) validation of putative SNPs resulted in mapping of 604 markers, out of which 188 SNPs represented 43 haplotype blocks distributed across all ten chromosomes. We have determined and clearly stated a specific combination of stringent criteria (>0.3 minor allele frequency, >0.8 GenTrainScore and >0.5 Chi_test100 score) necessary for the identification of highly polymorphic and genetically stable SNP markers. Due to these criteria, we identified a subset of 120 high-quality SNP markers to leverage in GG assay-based marker-assisted selection projects. A total of 32 high-quality SNPs represented 21 haplotypes out of 43 identified in this study. The information on the selection criteria of highly polymorphic SNPs in a complex genome such as maize and the public availability of these SNP assays will be of great value for the maize molecular genetics and breeding community.