Dynamics of cognitive functions in ageing and their relationship to education level = Динамика когнитивных функций при старении и их связь с уровнем образования

Age-related cognitive changes in the Russian population have not been sufficiently studied. Objective: to assess the time course of changes in cognitive functions (CF) in two serial measurements 9 years apart in the urban population of middle, elder, and senile age and their relationship to education level. Patients and methods. A random male and female sample of 45-69-year-old Novosibirsk residents (n=9360; HAPIEE project) was surveyed. CF was tested by standard methods. Resurvey was conducted in a random subsample (n=1663) included in this analysis. The mean follow-up period was 8.8 years (SD 1.1). Results and discussion. The test for semantic verbal fluency revealed its dynamic decline in all age groups, which was steeper in women than in men (p<0.001). Persons aged 70 years and older showed negative changes in memory, verbal fluency, and attention (p<0.001). Persons with primary (6%) and vocational (26%) education had steeper rates of decline in delayed recall (p=0.011; 0.038) than those with university education (35%). Conclusion. It is established that a dynamic decrease in CF begins at the age of 55–59 years; it is steeper among those aged 70 years and older. An age-related decline in memory function is accelerated in persons with lower educational levels

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

Seasonal and annual fluxes of nutrients and organic matter from large rivers to the Arctic Ocean and surrounding seas

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Estuaries and Coasts 35 (2012): 369-382, doi:10.1007/s12237-011-9386-6.River inputs of nutrients and organic matter impact the biogeochemistry of arctic estuaries and the Arctic Ocean as a whole, yet there is considerable uncertainty about the magnitude of fluvial fluxes at the pan-arctic scale. Samples from the six largest arctic rivers, with a combined watershed area of 11.3 x 106 km2, have revealed strong seasonal variations in constituent concentrations and fluxes within rivers as well as large differences among the rivers. Specifically, we investigate fluxes of dissolved organic carbon, dissolved organic nitrogen, total dissolved phosphorus, dissolved inorganic nitrogen, nitrate, and silica. This is the first time that seasonal and annual constituent fluxes have been determined using consistent sampling and analytical methods at the pan arctic scale, and consequently provide the best available estimates for constituent flux from land to the Arctic Ocean and surrounding seas. Given the large inputs of river water to the relatively small Arctic Ocean, and the dramatic impacts that climate change is having in the Arctic, it is particularly urgent that we establish the contemporary river fluxes so that we will be able to detect future changes and evaluate the impact of the changes on the biogeochemistry of the receiving coastal and ocean systems.This work was supported by the National Science Foundation through grants OPP-0229302, OPP-0519840, OPP-0732522, and OPP-0732944. Additional support was provided by the U. S. Geological Survey (Yukon River) and the Department of Indian and Northern Affairs (Mackenzie River)

Dynamics of trimming the content of face representations for categorization in the brain

To understand visual cognition, it is imperative to determine when, how and with what information the human brain categorizes the visual input. Visual categorization consistently involves at least an early and a late stage: the occipito-temporal N170 event related potential related to stimulus encoding and the parietal P300 involved in perceptual decisions. Here we sought to understand how the brain globally transforms its representations of face categories from their early encoding to the later decision stage over the 400 ms time window encompassing the N170 and P300 brain events. We applied classification image techniques to the behavioral and electroencephalographic data of three observers who categorized seven facial expressions of emotion and report two main findings: (1) Over the 400 ms time course, processing of facial features initially spreads bilaterally across the left and right occipito-temporal regions to dynamically converge onto the centro-parietal region; (2) Concurrently, information processing gradually shifts from encoding common face features across all spatial scales (e.g. the eyes) to representing only the finer scales of the diagnostic features that are richer in useful information for behavior (e.g. the wide opened eyes in 'fear'; the detailed mouth in 'happy'). Our findings suggest that the brain refines its diagnostic representations of visual categories over the first 400 ms of processing by trimming a thorough encoding of features over the N170, to leave only the detailed information important for perceptual decisions over the P300

Thermodynamic analysis of the Quantum Critical behavior of Ce-lattice compounds

A systematic analysis of low temperature magnetic phase diagrams of Ce compounds is performed in order to recognize the thermodynamic conditions to be fulfilled by those systems to reach a quantum critical regime and, alternatively, to identify other kinds of low temperature behaviors. Based on specific heat ($C_m$) and entropy ($S_m$) results, three different types of phase diagrams are recognized: i) with the entropy involved into the ordered phase ($S_{MO}$) decreasing proportionally to the ordering temperature ($T_{MO}$), ii) those showing a transference of degrees of freedom from the ordered phase to a non-magnetic component, with their $C_m(T_{MO})$ jump ($\Delta C_m$) vanishing at finite temperature, and iii) those ending in a critical point at finite temperature because their $\Delta C_m$ do not decrease with $T_{MO}$ producing an entropy accumulation at low temperature. Only those systems belonging to the first case, i.e. with $S_{MO}\to 0$ as $T_{MO}\to 0$, can be regarded as candidates for quantum critical behavior. Their magnetic phase boundaries deviate from the classical negative curvature below $T\approx 2.5$\,K, denouncing frequent misleading extrapolations down to T=0. Different characteristic concentrations are recognized and analyzed for Ce-ligand alloyed systems. Particularly, a pre-critical region is identified, where the nature of the magnetic transition undergoes significant modifications, with its $\partial C_m/\partial T$ discontinuity strongly affected by magnetic field and showing an increasing remnant entropy at $T\to 0$. Physical constraints arising from the third law at $T\to 0$ are discussed and recognized from experimental results

Efficient pairwise RNA structure prediction and alignment using sequence alignment constraints

BACKGROUND: We are interested in the problem of predicting secondary structure for small sets of homologous RNAs, by incorporating limited comparative sequence information into an RNA folding model. The Sankoff algorithm for simultaneous RNA folding and alignment is a basis for approaches to this problem. There are two open problems in applying a Sankoff algorithm: development of a good unified scoring system for alignment and folding and development of practical heuristics for dealing with the computational complexity of the algorithm. RESULTS: We use probabilistic models (pair stochastic context-free grammars, pairSCFGs) as a unifying framework for scoring pairwise alignment and folding. A constrained version of the pairSCFG structural alignment algorithm was developed which assumes knowledge of a few confidently aligned positions (pins). These pins are selected based on the posterior probabilities of a probabilistic pairwise sequence alignment. CONCLUSION: Pairwise RNA structural alignment improves on structure prediction accuracy relative to single sequence folding. Constraining on alignment is a straightforward method of reducing the runtime and memory requirements of the algorithm. Five practical implementations of the pairwise Sankoff algorithm – this work (Consan), David Mathews' Dynalign, Ian Holmes' Stemloc, Ivo Hofacker's PMcomp, and Jan Gorodkin's FOLDALIGN – have comparable overall performance with different strengths and weaknesses

Shortcomings of Vitamin D-Based Model Simulations of Seasonal Influenza

Seasonal variation in serum concentration of the vitamin D metabolite 25(OH) vitamin D [25(OH)D], which contributes to host immune function, has been hypothesized to be the underlying source of observed influenza seasonality in temperate regions. The objective of this study was to determine whether observed 25(OH)D levels could be used to simulate observed influenza infection rates. Data of mean and variance in 25(OH)D serum levels by month were obtained from the Health Professionals Follow-up Study and used to parameterize an individual-based model of influenza transmission dynamics in two regions of the United States. Simulations were compared with observed daily influenza excess mortality data. Best-fitting simulations could reproduce the observed seasonal cycle of influenza; however, these best-fit simulations were shown to be highly sensitive to stochastic processes within the model and were unable consistently to reproduce observed seasonal patterns. In this respect the simulations with the vitamin D forced model were inferior to similar modeling efforts using absolute humidity and the school calendar as seasonal forcing variables. These model results indicate it is unlikely that seasonal variations in vitamin D levels principally determine the seasonality of influenza in temperate regions

Evolutionary Determinants of Genetic Variation in Susceptibility to Infectious Diseases in Humans

Although genetic variation among humans in their susceptibility to infectious diseases has long been appreciated, little focus has been devoted to identifying patterns in levels of variation in susceptibility to different diseases. Levels of genetic variation in susceptibility associated with 40 human infectious diseases were assessed by a survey of studies on both pedigree-based quantitative variation, as well as studies on different classes of marker alleles. These estimates were correlated with pathogen traits, epidemiological characteristics, and effectiveness of the human immune response. The strongest predictors of levels of genetic variation in susceptibility were disease characteristics negatively associated with immune effectiveness. High levels of genetic variation were associated with diseases with long infectious periods and for which vaccine development attempts have been unsuccessful. These findings are consistent with predictions based on theoretical models incorporating fitness costs associated with the different types of resistance mechanisms. An appreciation of these observed patterns will be a valuable tool in directing future research given that genetic variation in disease susceptibility has large implications for vaccine development and epidemiology