Continuous Evolution of Statistical Estimators for Optimal Decision-Making

In many everyday situations, humans must make precise decisions in the presence of uncertain sensory information. For example, when asked to combine information from multiple sources we often assign greater weight to the more reliable information. It has been proposed that statistical-optimality often observed in human perception and decision-making requires that humans have access to the uncertainty of both their senses and their decisions. However, the mechanisms underlying the processes of uncertainty estimation remain largely unexplored. In this paper we introduce a novel visual tracking experiment that requires subjects to continuously report their evolving perception of the mean and uncertainty of noisy visual cues over time. We show that subjects accumulate sensory information over the course of a trial to form a continuous estimate of the mean, hindered only by natural kinematic constraints (sensorimotor latency etc.). Furthermore, subjects have access to a measure of their continuous objective uncertainty, rapidly acquired from sensory information available within a trial, but limited by natural kinematic constraints and a conservative margin for error. Our results provide the first direct evidence of the continuous mean and uncertainty estimation mechanisms in humans that may underlie optimal decision making

Association Rate Constants of Ras-Effector Interactions Are Evolutionarily Conserved

Evolutionary conservation of protein interaction properties has been shown to be a valuable indication for functional importance. Here we use homology interface modeling of 10 Ras-effector complexes by selecting ortholog proteins from 12 organisms representing the major eukaryotic branches, except plants. We find that with increasing divergence time the sequence similarity decreases with respect to the human protein, but the affinities and association rate constants are conserved as predicted by the protein design algorithm, FoldX. In parallel we have done computer simulations on a minimal network based on Ras-effector interactions, and our results indicate that in the absence of negative feedback, changes in kinetics that result in similar binding constants have strong consequences on network behavior. This, together with the previous results, suggests an important biological role, not only for equilibrium binding constants but also for kinetics in signaling processes involving Ras-effector interactions. Our findings are important to take into consideration in system biology approaches and simulations of biological networks

Clinical chronobiology: a timely consideration in critical care medicine

A fundamental aspect of human physiology is its cyclical nature over a 24-h period, a feature conserved across most life on Earth. Organisms compartmentalise processes with respect to time in order to promote survival, in a manner that mirrors the rotation of the planet and accompanying diurnal cycles of light and darkness. The influence of circadian rhythms can no longer be overlooked in clinical settings; this review provides intensivists with an up-to-date understanding of the burgeoning field of chronobiology, and suggests ways to incorporate these concepts into daily practice to improve patient outcomes. We outline the function of molecular clocks in remote tissues, which adjust cellular and global physiological function according to the time of day, and the potential clinical advantages to keeping in time with them. We highlight the consequences of "chronopathology", when this harmony is lost, and the risk factors for this condition in critically ill patients. We introduce the concept of "chronofitness" as a new target in the treatment of critical illness: preserving the internal synchronisation of clocks in different tissues, as well as external synchronisation with the environment. We describe methods for monitoring circadian rhythms in a clinical setting, and how this technology may be used for identifying optimal time windows for interventions, or to alert the physician to a critical deterioration of circadian rhythmicity. We suggest a chronobiological approach to critical illness, involving multicomponent strategies to promote chronofitness (chronobundles), and further investment in the development of personalised, time-based treatment for critically ill patients

On the Origins of Suboptimality in Human Probabilistic Inference

Humans have been shown to combine noisy sensory information with previous experience (priors), in qualitative and sometimes quantitative agreement with the statistically-optimal predictions of Bayesian integration. However, when the prior distribution becomes more complex than a simple Gaussian, such as skewed or bimodal, training takes much longer and performance appears suboptimal. It is unclear whether such suboptimality arises from an imprecise internal representation of the complex prior, or from additional constraints in performing probabilistic computations on complex distributions, even when accurately represented. Here we probe the sources of suboptimality in probabilistic inference using a novel estimation task in which subjects are exposed to an explicitly provided distribution, thereby removing the need to remember the prior. Subjects had to estimate the location of a target given a noisy cue and a visual representation of the prior probability density over locations, which changed on each trial. Different classes of priors were examined (Gaussian, unimodal, bimodal). Subjects' performance was in qualitative agreement with the predictions of Bayesian Decision Theory although generally suboptimal. The degree of suboptimality was modulated by statistical features of the priors but was largely independent of the class of the prior and level of noise in the cue, suggesting that suboptimality in dealing with complex statistical features, such as bimodality, may be due to a problem of acquiring the priors rather than computing with them. We performed a factorial model comparison across a large set of Bayesian observer models to identify additional sources of noise and suboptimality. Our analysis rejects several models of stochastic behavior, including probability matching and sample-averaging strategies. Instead we show that subjects' response variability was mainly driven by a combination of a noisy estimation of the parameters of the priors, and by variability in the decision process, which we represent as a noisy or stochastic posterior

Lineage delimitation and description of nine new species of bush frogs (Anura: Raorchestes, Rhacophoridae) from the Western Ghats Escarpment

Bush frogs of the genus Raorchestes are distributed mainly in the Western Ghats Escarpment of Peninsular India. The inventory of species in this genus is incomplete and there is ambiguity in the systematic status of species recognized by morphological criteria. To address the dual problem of taxon sampling and systematic uncertainty in bush frogs, we used a large-scale spatial sampling design, explicitly incorporating the geographic and ecological heterogeneity of the Western Ghats. We then used a hierarchical multi-criteria approach by combining mitochondrial phylogeny, genetic distance, geographic range, morphology and advertisement call to delimit bush frog lineages. Our analyses revealed the existence of a large number of new lineages with varying levels of genetic divergence. Here, we provide diagnoses and descriptions for nine lineages that exhibit divergence across multiple axes. The discovery of new lineages that exhibit high divergence across wide ranges of elevation and across the major massifs highlights the large gaps in historical sampling. These discoveries underscore the significance of addressing inadequate knowledge of species distribution, namely the ``Wallacean shortfall'', in addressing the problem of taxon sampling and unknown diversity in tropical hotspots. A biogeographically informed sampling and analytical approach was critical in detecting and delineating lineages in a consistent manner across the genus. Through increased taxon sampling, we were also able to discern a number of well-supported sub-clades that were either unresolved or absent in earlier phylogenetic reconstructions and identify a number of shallow divergent lineages which require further examination for assessment of their taxonomic status

Regulated acid-base transport in the collecting duct

The renal collecting system serves the fine-tuning of renal acid-base secretion. Acid-secretory type-A intercalated cells secrete protons via a luminally expressed V-type H(+)-ATPase and generate new bicarbonate released by basolateral chloride/bicarbonate exchangers including the AE1 anion exchanger. Efficient proton secretion depends both on the presence of titratable acids (mainly phosphate) and the concomitant secretion of ammonia being titrated to ammonium. Collecting duct ammonium excretion requires the Rhesus protein RhCG as indicated by recent KO studies. Urinary acid secretion by type-A intercalated cells is strongly regulated by various factors among them acid-base status, angiotensin II and aldosterone, and the Calcium-sensing receptor. Moreover, urinary acidification by H(+)-ATPases is modulated indirectly by the activity of the epithelial sodium channel ENaC. Bicarbonate secretion is achieved by non-type-A intercalated cells characterized by the luminal expression of the chloride/bicarbonate exchanger pendrin. Pendrin activity is driven by H(+)-ATPases and may serve both bicarbonate excretion and chloride reabsorption. The activity and expression of pendrin is regulated by different factors including acid-base status, chloride delivery, and angiotensin II and may play a role in NaCl retention and blood pressure regulation. Finally, the relative abundance of type-A and non-type-A intercalated cells may be tightly regulated. Dysregulation of intercalated cell function or abundance causes various syndromes of distal renal tubular acidosis underlining the importance of these processes for acid-base homeostasis

Preprocedural Prognostic Factors in Acute Decompensated Aortic Stenosis

Acute decompensated aortic stenosis (ADAS) is common and associated with poor outcomes. Myocardial remodeling and function, including a novel echo staging classification (0 to 4, representing increasing degrees of cardiac damage/dysfunction), impact outcomes in stable aortic stenosis. However, this has not been assessed in patients with ADAS. This study aims to evaluate the impact of the myocardium, echo staging classification, and clinical parameters on mortality in ADAS. ADAS was defined as an acute deterioration in symptoms (New York Heart Association 4, Canadian Cardiovascular Society 3/4, or syncope) that warranted admission to the hospital and urgent aortic valve replacement. Using a retrospective observational study design, 292 consecutive patients with ADAS who underwent transcatheter aortic valve implantation (TAVI) were identified and included in this study. Echocardiographic and clinical characteristics were evaluated using regression analysis. The outcome was all-cause mortality after TAVI. At 1 year after TAVI, advanced echo staging (>2) independently predicted mortality (hazards ratio: 1.85, 95% confidence interval: 1.01 to 3.39; p = 0.045). At a follow-up of 2.4 ± 1.4 years, myocardial, valvular, and clinical parameters did not predict mortality, except for frailty (hazards ratio: 2.31, 95% confidence interval: 1.38 to 3.85; p = 0.001). In patients with ADAS, short-term mortality after TAVI is influenced by more advanced cardiac damage/dysfunction based on the echo staging classification, whereas mid-term mortality is driven by frailty rather than echo staging classification