Renal Function and Risk Factors of Moderate to Severe Chronic Kidney Disease in Golestan Province, Northeast of Iran

Introduction: The incidence of end-stage renal disease is increasing worldwide. Earlier studies reported high prevalence rates of obesity and hypertension, two major risk factors of chronic kidney disease (CKD), in Golestan Province, Iran. We aimed to investigate prevalence of moderate to severe CKD and its risk factors in the region. Methods: Questionnaire data and blood samples were collected from 3591 participants (≥18 years old) from the general population. Based on serum creatinine levels, glomerular filtration rate (GFR) was estimated. Results: High body mass index (BMI) was common: 35.0 of participants were overweight (BMI 25-29.9) and 24.5 were obese (BMI ≥30). Prevalence of CKD stages 3 to 5 (CKD-S3-5), i.e., GFR <60 mL/min/1.73 m2, was 4.6. The odds ratio (OR) and 95 confidence interval (95 CI) for the risk of CKD-S3-5 associated with every year increase in age was 1.13 (1.11- 1.15). Men were at lower risk of CKD-S3-5 than women (OR = 0.28; 95 CI 0.18-0.45). Obesity (OR = 1.78; 95 CI 1.04-3.05) and self-reported diabetes (OR = 1.70; 95 CI 1.00-2.86), hypertension (OR = 3.16; 95 CI 2.02-4.95), ischemic heart disease (OR = 2.73; 95 CI 1.55-4.81), and myocardial infarction (OR = 2.69; 95 CI 1.14-6.32) were associated with increased risk of CKD-S3-5 in the models adjusted for age and sex. The association persisted for self-reported hypertension even after adjustments for BMI and history of diabetes (OR = 2.85; 95 CI 1.77-4.59). Conclusion: A considerable proportion of inhabitants in Golestan have CKD-S3-5. Screening of individuals with major risk factors of CKD, in order to early detection and treatment of impaired renal function, may be plausible. Further studies on optimal risk prediction of future end-stage renal disease and effectiveness of any screening program are warranted. © 2010 Najafi et al

Fully automated high-quality NMR structure determination of small 2H-enriched proteins

Determination of high-quality small protein structures by nuclear magnetic resonance (NMR) methods generally requires acquisition and analysis of an extensive set of structural constraints. The process generally demands extensive backbone and sidechain resonance assignments, and weeks or even months of data collection and interpretation. Here we demonstrate rapid and high-quality protein NMR structure generation using CS-Rosetta with a perdeuterated protein sample made at a significantly reduced cost using new bacterial culture condensation methods. Our strategy provides the basis for a high-throughput approach for routine, rapid, high-quality structure determination of small proteins. As an example, we demonstrate the determination of a high-quality 3D structure of a small 8 kDa protein, E. coli cold shock protein A (CspA), using <4 days of data collection and fully automated data analysis methods together with CS-Rosetta. The resulting CspA structure is highly converged and in excellent agreement with the published crystal structure, with a backbone RMSD value of 0.5 Å, an all atom RMSD value of 1.2 Å to the crystal structure for well-defined regions, and RMSD value of 1.1 Å to crystal structure for core, non-solvent exposed sidechain atoms. Cross validation of the structure with 15N- and 13C-edited NOESY data obtained with a perdeuterated 15N, 13C-enriched 13CH3 methyl protonated CspA sample confirms that essentially all of these independently-interpreted NOE-based constraints are already satisfied in each of the 10 CS-Rosetta structures. By these criteria, the CS-Rosetta structure generated by fully automated analysis of data for a perdeuterated sample provides an accurate structure of CspA. This represents a general approach for rapid, automated structure determination of small proteins by NMR

Subliminal stimuli in the near absence of attention influence top-down cognitive control

Recent research has shown that visual stimuli can influence cognitive control functions, even if subjects are unaware of the identity of the stimuli. However, in those previous studies, subjects actively attended to the location of the subliminal stimuli. Here we assessed the role of endogenous spatial attention in such paradigms. We required subjects to quickly prepare for one of two numerical judgment tasks on the basis of the direction of motion in patches of moving dots presented in cued spatial locations. We found that irrelevant motion patches presented in the uncued spatial locations also influenced task performance. Motion in the uncued patches was weak and did not affect the perception of the cued patches. Further analyses suggested that the effect of priming by the uncued stimuli was present even for subjects who could only discriminate such stimuli at chance level. Three additional experiments confirmed that subjects paid minimal attention to the uncued locations, in that the subjects could not perform simple discriminations of conjunctions of features in those locations

Tilt aftereffect following adaptation to translational Glass patterns

Glass patterns (GPs) consist of randomly distributed dot pairs (dipoles) whose orientations are determined by specific geometric transforms. We assessed whether adaptation to stationary oriented translational GPs suppresses the activity of orientation selective detectors producing a tilt aftereffect (TAE). The results showed that adaptation to GPs produces a TAE similar to that reported in previous studies, though reduced in amplitude. This suggests the involvement of orientation selective mechanisms. We also measured the interocular transfer (IOT) of the GP-induced TAE and found an almost complete IOT, indicating the involvement of orientation selective and binocularly driven units. In additional experiments, we assessed the role of attention in TAE from GPs. The results showed that distraction during adaptation similarly modulates the TAE after adapting to both GPs and gratings. Moreover, in the case of GPs, distraction is likely to interfere with the adaptation process rather than with the spatial summation of local dipoles. We conclude that TAE from GPs possibly relies on visual processing levels in which the global orientation of GPs has been encoded by neurons that are mostly binocularly driven, orientation selective and whose adaptation-related neural activity is strongly modulated by attention

Effects of Multimodal Load on Spatial Monitoring as Revealed by ERPs

While the role of selective attention in filtering out irrelevant information has been extensively studied, its characteristics and neural underpinnings when multiple environmental stimuli have to be processed in parallel are much less known. Building upon a dual-task paradigm that induced spatial awareness deficits for contralesional hemispace in right hemisphere-damaged patients, we investigated the electrophysiological correlates of multimodal load during spatial monitoring in healthy participants. The position of appearance of briefly presented, lateralized targets had to be reported either in isolation (single task) or together with a concurrent task, visual or auditory, which recruited additional attentional resources (dual-task). This top-down manipulation of attentional load, without any change of the sensory stimulation, modulated the amplitude of the first positive ERP response (P1) and shifted its neural generators, with a suppression of the signal in the early visual areas during both visual and auditory dual tasks. Furthermore, later N2 contralateral components elicited by left targets were particularly influenced by the concurrent visual task and were related to increased activation of the supramarginal gyrus. These results suggest that the right hemisphere is particularly affected by load manipulations, and confirm its crucial role in subtending automatic orienting of spatial attention and in monitoring both hemispaces

The Flexibility of Nonconsciously Deployed Cognitive Processes: Evidence from Masked Congruence Priming

Background: It is well accepted in the subliminal priming literature that task-level properties modulate nonconscious processes. For example, in tasks with a limited number of targets, subliminal priming effects are limited to primes that are physically similar to the targets. In contrast, when a large number of targets are used, subliminal priming effects are observed for primes that share a semantic (but not necessarily physical) relationship with the target. Findings such as these have led researchers to conclude that task-level properties can direct nonconscious processes to be deployed exclusively over central (semantic) or peripheral (physically specified) representations. Principal Findings: We find distinct patterns of masked priming for "novel" and "repeated" primes within a single task context. Novel primes never appear as targets and thus are not seen consciously in the experiment. Repeated primes do appear as targets, thereby lending themselves to the establishment of peripheral stimulus-response mappings. If the source of the masked priming effect were exclusively central or peripheral, then both novel and repeated primes should yield similar patterns of priming. In contrast, we find that both novel and repeated primes produce robust, yet distinct, patterns of priming. Conclusions: Our findings indicate that nonconsciously elicited cognitive processes can be flexibly deployed over both central and peripheral representations within a single task context. While we agree that task-level properties can influence nonconscious processes, our findings sharply constrain the extent of this influence. Specifically, our findings are inconsistent with extant accounts which hold that the influence of task-level properties is strong enough to restrict the deployment of nonconsciously elicited cognitive processes to a single type of representation (i.e. central or peripheral).13 page(s

Probabilistic Interaction Network of Evidence Algorithm and its Application to Complete Labeling of Peak Lists from Protein NMR Spectroscopy

The process of assigning a finite set of tags or labels to a collection of observations, subject to side conditions, is notable for its computational complexity. This labeling paradigm is of theoretical and practical relevance to a wide range of biological applications, including the analysis of data from DNA microarrays, metabolomics experiments, and biomolecular nuclear magnetic resonance (NMR) spectroscopy. We present a novel algorithm, called Probabilistic Interaction Network of Evidence (PINE), that achieves robust, unsupervised probabilistic labeling of data. The computational core of PINE uses estimates of evidence derived from empirical distributions of previously observed data, along with consistency measures, to drive a fictitious system M with Hamiltonian H to a quasi-stationary state that produces probabilistic label assignments for relevant subsets of the data. We demonstrate the successful application of PINE to a key task in protein NMR spectroscopy: that of converting peak lists extracted from various NMR experiments into assignments associated with probabilities for their correctness. This application, called PINE-NMR, is available from a freely accessible computer server (http://pine.nmrfam.wisc.edu). The PINE-NMR server accepts as input the sequence of the protein plus user-specified combinations of data corresponding to an extensive list of NMR experiments; it provides as output a probabilistic assignment of NMR signals (chemical shifts) to sequence-specific backbone and aliphatic side chain atoms plus a probabilistic determination of the protein secondary structure. PINE-NMR can accommodate prior information about assignments or stable isotope labeling schemes. As part of the analysis, PINE-NMR identifies, verifies, and rectifies problems related to chemical shift referencing or erroneous input data. PINE-NMR achieves robust and consistent results that have been shown to be effective in subsequent steps of NMR structure determination

Chemicals released by male sea cucumber mediate aggregation and spawning behaviours

The importance of chemical communication in reproduction has been demonstrated in many marine broadcast spawners. However, little is known about the use of chemical communication by echinoderms, the nature of the compounds involved and their mechanism(s) of action. Here, the hypothesis that the sea cucumber Holothuria arguinensis uses chemical communication for aggregation and spawning was tested. Water conditioned by males, but not females, attracted both males and females; gonad homogenates and coelomic fluid had no effect on attraction. Male spawning water, but not female spawning water, stimulated males and females to release their gametes; the spermatozoa alone did not induce spawning. H. arguinensis male spawning water also induced spawning in the phylogenetically related H. mammata. This indicates that males release pheromones together with their gametes that induce spawning in conspecifics and possibly sympatric species. Finally, the male pheromone seems to be a mixture with at least one labile compound (biological activity is lost after four hours at ambient temperature) possibly including phosphatidylcholines. The identification of pheromones in sea cucumbers offers a new ecological perspective and may have practical applications for their aquaculture.FCT - Foundation for Science and Technology [UID/Multi/04326/2013, SFRH/BD/90761/2012]info:eu-repo/semantics/publishedVersio

Hierarchical decision-making produces persistent differences in learning performance

Human organizations are commonly characterized by a hierarchical chain of command that facilitates division of labor and integration of effort. Higher-level employees set the strategic frame that constrains lower-level employees who carry out the detailed operations serving to implement the strategy. Typically, strategy and operational decisions are carried out by different individuals that act over different timescales and rely on different kinds of information. We hypothesize that when such decision processes are hierarchically distributed among different individuals, they produce highly heterogeneous and strongly path-dependent joint learning dynamics. To investigate this, we design laboratory experiments of human dyads facing repeated joint tasks, in which one individual is assigned the role of carrying out strategy decisions and the other operational ones. The experimental behavior generates a puzzling bimodal performance distribution-some pairs learn, some fail to learn after a few periods. We also develop a computational model that mirrors the experimental settings and predicts the heterogeneity of performance by human dyads. Comparison of experimental and simulation data suggests that self-reinforcing dynamics arising from initial choices are sufficient to explain the performance heterogeneity observed experimentally