The δ 15N of the body protein pool varied by 4‰ and 46% of the variance was associated with year. Annual variation in δ15N of body protein likely reflected the fall/early winter diet and winter locations, yet 15% of the isotopic variation in amino acid N was due to body proteins. Consistent isotopic differences among blood N pools indicated that animals tolerated fluxes in diet and body stores. Conservation of body protein in caribou is the result of active exchange among diet and body N pools. Adult females were robust to historically severe winter conditions and prioritized body condition and survival over early investment in offspring. For a vagile ungulate residing at low densities in a predator-rich environment, protein restrictions in winter may not be the primary limiting factor for reproduction.Winter severity can influence large herbivore populations through a reduction in maternal proteins available for reproduction. Nitrogen (N) isotopes in blood fractions can be used to track the use of body proteins in northern and montane ungulates. We studied 113 adult female caribou for 13 years throughout a series of severe winters that reduced population size and offspring mass. After these severe winters, offspring mass increased but the size of the population remained low. We devised a conceptual model for routing of isotopic N in blood in the context of the severe environmental conditions experienced by this population. We measured δ Resource availability for large herbivores is primarily dictated by environmental conditions and intraspecific competition Rangifer tarandusOvis canadensisOvibos moschatus) Oreamnos americanus) Ovis canadensis) R. tarandus) use primarily capital and some income to meet nutrient demands throughout a reproductive event Capreolus capreolus) rely exclusively on income to produce offspring Nutrient allocation in reproductive females occurs along a continuum of capital to income investment Availability of maternal proteins for reproduction may provide the mechanistic link between environmental conditions, investment in offspring, and population productivity 15N to light 14N (δ15N) is typically higher in body proteins than in dietary proteins 15N ratios in serum amino acids indicate that an increasing proportion of the associated N is derived from body proteins 15N of serum proteins rises above cellular proteins , so δ15N in serum protein provides an additional indicator of N conservation in wintering ungulates  and relative changes therein (Isotopes of nitrogen (N) can be used to assess the mobilization of body proteins in northern and montane ungulates because the isotope ratio of heavy ngulates . While δ therein , 2 proviSeveral environmental and physiological factors act in concert to shape the isotopic composition of animals −2) population that resides in a multi-predator multi-prey system within Denali National Park and Preserve  of the Denali herd included most of Denali National Park and Preserve, which was roughly bisected by the Alaska Range (Carex spp.)-shrub , tussock tundra, and spruce (Picea spp.) and deciduous (Populus spp. and Betula papyrifera) woodlands, whereas alpine areas contained a mixture of talus, scree, sedge, mountain avens (Dryas spp.), heath (Cassiope spp.), graminoids, lichens, and mosses.The annual range  in the collection tube; whole serum and blood clots were stored at −20°C until processing.During captures, blood (30 mL) was collected from either the saphenous or cephalic veins with a 30 ml syringe and a 20 gauge×1.0 inch needle. Whole blood was immediately transferred into 10 mL serum collection tubes and allowed to clot in the tubes before separating serum. In the field, samples were kept from freezing in the helicopter until processing. Blood samples were centrifuged at 3,000×2WO4) to precipitate serum proteins from whole serum. Whole serum (1.5 mL) was added to a thoroughly mixed solution of 0.66 NH2SO4 (1.5 mL at 3.23 mL·100 ml−1), water (3 mL), and Na2WO4 (1.5 mL at 10% w:v) at room temperature. Denatured serum proteins were precipitated by centrifugation at 10,000×g for 20 minutes at 10°C We used sodium tungstate  against atmospheric N (δ in ‰) 15N of red blood cells (δ15NRBC) largely represented body proteins that were deposited <90 d prior to collection 15N of serum proteins (δ15NProteins) represented the pool of albumins and globulins that interchanged primarily with cellular proteins 15N of serum amino acids represented recent (<4 d) modifications of dietary and (or) endogenous sources of N 15NRBC and δ15NProteins (ΔRBC-Proteins) and the difference between δ15NRBC and δ15NAAs (ΔRBC-AAs). We expected that the ΔRBC-Proteins would increase as maternal protein was mobilized, as recycling of body N results in an increase in δ15N of serum proteins. Secondly, we expected the ΔRBC-AAs would decrease with losses of maternal protein as the pool of amino acids became increasingly derived from endogenous sources of N  by year. We used multiple regression 15NRBC on isotopic parameters  was used to estimate the independent effect of each covariate to each isotopic parameter R2 after the covariate was removed from the full model (ΔAdj. R2i) was used as an index of the relative importance of covariatei, which was interpreted as the percent of variance explained by covariatei within the model. We used coefficients (β), robust estimates of variance We used descriptive statistics to report age, body mass, and isotopic parameters  and 95% confidence intervals were used to evaluate strength and direction (β≠0) of the relationships, respectively. A Shapiro-Wilk’s test was used to evaluate the assumption of normality for all comparisons x-) ± SD.We used linear regression to examine the relationships between snowfall (cm) and each isotopic parameter in the blood. Snowfall  was measn = 65) as independent because these samples were generally collected 3–4 years apart. Some samples of blood fractions were lost during handling, extraction, or counting of isotopes  subsequently reducing sample sizes for ΔRBC-Proteins and ΔRBC-AAs by 25% (We collected 168 blood samples from 113 (pregnancy rate = 95%) caribou during 13 of 15 years during our study . We treas by 25% .15NRBC (n = 155) averaged 2.1±0.90‰ and ranged from 0.18 to 4.72‰. Similarly, the δ15NProteins (n = 140) appeared to track the annual variation in δ15NRBC , while the δ15NAAs (n = 137) was consistently lower than δ15NRBC and δ15NProteins . Indeed, these observations at the population level were consistent with comparisons within individual caribou (RBC-Proteins (n = 127) was similar to zero  while the ΔRBC-AAs (n = 125) was always greater than zero .Isotopic N varied by 4‰ within each fraction of blood across the study period . The δ15 caribou  because 15NRBC, δ15NProteins, and ΔRBC-Proteins) explained ≥62% of the variance (15NAAs and ΔRBC-AAs) accounted for substantially less of the variance (≤31%). Year was the most important covariate in the models describing N isotopes of blood fractions, while the effects of age, body mass, and spatial location were significant but much less important .The performance of the regression models appeared to vary with the primary source of N . Models of body protein parameters  n = 60, 2.6±0.5‰) 15NRBC remains unexplained. We suspect that diet in summer and late fall was strongly influencing δ15NRBC as animals stored body protein before winter for the next annual cycle. Thus, space use and diet in late summer-early winter may be useful in resolving some of this variation in δ15NRBC. Although influential, year remains a covariate that represents a suite of undetermined influences to the isotopic composition of body proteins that integrates N sources over large and varied spatio-temporal scales.The large shifts in δ15NRBC highlighted some interesting influences to this pool of N. Factors that affect isotopic incorporation rates in blood and tissues 15NRBC was higher in larger animals as well as younger and older animals , with most of the additional explained variance (19%) due to the inclusion of δ15NRBC as a predictor. The δ15NProteins increased with δ15NRBC . The δ15NProteins closely tracked that of δ15NRBC  The δovariate  that was δ15NRBC  and cova δ15NRBC , indicat15NRBC was the most important predictor of the isotopic composition of the serum amino acid pool . Yet, this model performed the worst (31% of explained variance) of the model set used to account for variation in δ15N of the blood fractions  n = 137, −2.1±0.99‰). With strong implications for protein status, this again suggested that the pool of serum amino acids in Québec females had larger contributions of endogenous proteins than females in the Denali herd, which is not surprising given the conceptual model of isotopic routing , the pronounced topographical and vegetative gradients in Denali National Park and Preserve offered ample foraging solutions for caribou. Wintering habitats for caribou included large tracts of lichen-rich spruce forests in the northwest, graminoid-dominated tussock flats in the northeast, as well as the windswept mountains of the northern foothills of the Alaska Range (O. moschatus) or Dall sheep , caribou are well adapted to move amongst these foraging patches through areas of variable snow conditions.The prolonged period of severe winters  likely hka Range . Unlike in utero to their offspring. Like other montane ecotypes Rangifer spp. Large body mass usually has a positive effect on reproductive success Due to variable winter conditions and high losses of offspring to predation Isotope signatures for whole blood, serum, and plasma are typically used to reflect different source materials, but herein we provided the first examination of isotopic routing via pools of blood N  in wild animals. Blood represents multiple physiological pathways of N, and, thus assessments of bulk fractions may mask informative isotopic differences due to the dynamic nature of isotopic routing. For instance, there appears to be substantial variance in the isotopic sources within C and N of essential and non-essential amino acids 15N observed in our study could have been the effect of physiological and ecological variations among individuals on the metabolic routing and consequent relative contributions of novel and endogenous resources to N in the non-essential amino acids in caribou red blood cells. Previous studies 15NRBC . Because caribou are a gregarious and generalist species, we would expect variations in δ15NRBC caused by contrasts in dietary inputs to operate on the population scale, thus, resulting in intra-annual differences in δ15NRBC. The isotopic model presented herein is conceptual, and by nature, deserves more rigorous evaluations. It is possible that our conceptual model is not sensitive enough to identify small but physiological significant shifts in protein status. Forthcoming work from captive research, however, suggests that this is unlikely and will highlight further insights gained from this model of isotopic routing in northern ungulates. Accordingly, we recommend that future research to examine the sources of inter- and intra-annual variance in the isotopic ecology of large herbivores should consider the conceptual model of isotopic routing presented herein, compound specific assessments, or effects of individual physiology and dietary ecology on metabolic routing.The substantial inter- and intra-annual variation in δ15N within this montane ungulate, while demonstrating little isotopic evidence of reliance on maternal proteins even during severe winters. Caribou continue to demonstrate considerable physiological and behavioral plasticity that undoubtedly contributes to the resilience of this population in the presence of often harsh and varied environmental and ecological conditions that are common of multi-predator multi-prey systems in northern and montane environments.This biochemical evidence supports previous work on this population while continuing to enhance our understanding of some of the environmental, ecological, and physiological mechanisms that affect population dynamics within montane caribou. Year, maternal (age and body mass), and spatial factors (winter location) shaped patterns of variance in δ


The high methane concentrations  that sustain these fluxes are related to the shallow and well-mixed water column that allows an efficient transfer of methane from the seafloor to surface waters. This differs from deeper and stratified seep areas where there is a large decrease of methane between bottom and surface by microbial oxidation or physical transport. Shallow well-mixed continental shelves represent about 33% of the total continental shelf area, so that marine coastal methane emissions are probably under-estimated. Near-shore and shallow seep areas are hot spots of methane emission, and our data also suggest that emissions could increase in response to warming of surface waters.Methane is the second most important greenhouse gas contributing to climate warming. The open ocean is a minor source of methane to the atmosphere. We report intense methane emissions from the near-shore southern region of the North Sea characterized by the presence of extensive areas with gassy sediments. The average flux intensities (~130 μmol m However, the estimates of CH4 “emission” from marine seeps104 release from sediments to bottom waters and not to the actual transfer from surface waters to the atmosphere, which is probably much lower4 concentrations in bottom waters , but removal by microbial CH4 oxidation and lateral dispersion by physical transport leads usually to much lower CH4 concentrations in surface waters (5–20 nmol L−1) even in the shallow areas of continental slopes and shelves131415161718Methane CH is the s4 concentrations in surface waters of the Belgian coastal zone (BCZ) in spring, summer and fall 2010 and 2011  was characterized by CH4 concentrations in surface waters between 3 and 13 times higher than the more off-shore area (>15 km away from the coastline). The overall average CH4 concentration in the BCZ near-shore area (139 nmol L−1) was ~6 times higher than in the off-shore area (24 nmol L−1), and in both areas distinctly above atmospheric equilibrium (~2 nmol L−1). These values are one to two orders of magnitude higher than the CH4 concentrations in surface waters of most of the North Sea with values typically <5 nmol L−1 54 is close to atmospheric equilibrium4 concentrations in surface waters range between 60 and 90 nmol L−1, such as for the Elbe64 data in the Thames river plume were below 25 nmol L−1 (−1) reported4 concentration in the BCZ  was higher than any other previous report in  surface waters of the North Sea, and nearly equals the value reported above an abandoned borehole in the Northern North Sea of 1,453 nmol L−1 4 concentration in the BCZ is comparable to the maximal value in surface waters  in the Santa Barbara Channel , one of the most intense marine seep area in the worldThe CHand 2011  were hige area 13 nmol L−1e area 13 nmol L−1nmol L−1 , distince area 13 nmol L−14 concentrations in near-shore coastal areas have been frequently attributed to estuarine inputs of CH469214 concentrations in the lower salinity region of the Thames river plume  and the outer BCZ , an area of intense shallow submarine gas seepage4 was observed in the lower estuary  compared to the mid estuary    which ha4 between 15 to 300 nmol L−1 have been reported in bottom waters at Tommeliten, a prominent CH4 macro-seep area in the Central North Sea4 concentrations were below 5 nmol L−1. This was attributed to removal by microbial CH4 oxidation and lateral dispersion by physical transport, favored by thermal stratification−1) than bottom waters Concentrations of CH2 values remain close to atmospheric equilibrium , the difference was very small (on average ~14%)  and strong tidal currents, thermal or haline stratification never occurs in the BCZ . Due to ilibrium , with noge ~14%) . Hence, mmeliten .4 concentration in the BCZ showed distinct seasonal variations with higher values in summer than spring and fall. Inter-annual variations were also observed with higher values in summer 2010 than 2011, but conversely lower values in spring and fall 2010 than 2011 in the near-shore area (4 concentrations were associated with lower water temperatures (April 2010) and the highest CH4 concentrations were associated with the higher water temperatures (June 2010) 4 diffusion and ebullition were observed in summer4 production4 solubility4 from sediments to the water column. Hence, increasing temperature could enhance a passive release of CH4 from gassy sediments due to the decrease of gas solubility, but this does not exclude an increase of CH4 production by methanogens also in response to higher temperature, and organic matter availability. Indeed, the maximal CH4 concentrations were observed in summer, when the sediment was enriched in organic matter produced by spring phytoplankton bloom.The dissolved CHore area ; Table 1ne 2010) . The rel4 emissions ranged seasonally between 1 and 160 μmol m−2 d−1 in the off-shore BCZ and between 2 and 426 μmol m−2 d−1 in the near-shore BCZ −2 d−1) 4 emissions in the near-shore BCZ nearly equal the CH4 emission of 180 μmol m−2 d−1 in Santa Barbara Channel , one of the most intense marine seep area in the worldThe air-sea CHhore BCZ . Wind spnd speed . Annual 4 emission budget, it is necessary to evaluate the representativeness of our study site for coastal areas in general. This is not an easy task since there are no global spatial datasets of gassy sediments and of submerged peat deposits. Regions corresponding to drowned coastlines (drowned forests and peatland) have been identified among the coastal environments most likely to have gas-rich sediments, in addition to estuaries, bays, rias and deltas2)4 concentrations in well-mixed and seasonally stratified continental shelves   (Belgica and YSI 6600 on the Luctor), in surface waters (1 m depth) and on some occasions ~3 m above the seafloor. When CTD data were unavailable on the Belgica, we used salinity and temperature measurements from an underway instrument (Sea-bird SBE21) connected to a seawater supply (pumped at 2.5 m). Water samples were collected in borosilicate serum bottles (50 ml) with a tubing, left to overflow, poisoned with a saturated solution of HgCl2 (100 μl), sealed with a butyl stopper, crimped with an aluminum cap, and stored at ambient temperature in the dark until analysis. Dissolved oxygen was measured by titration with the Winkler methodData were collected during 6 cruises in the BCZ on the 09/2011) . Near si09/2011) . Samplin4 was determined with the headspace equilibration technique  and a gas chromatograph4:CO2:N2O:N2 mixtures (Air Liquide Belgium) of 1, 10 and 30 ppm CH4. Each of the three standards was analyzed in triplicate at the start and the end of the daily batch of samples  and the calibration curve was computed by linear regression forced through zero (r2 ≥ 0.999). The slope of the calibration regression line was interpolated linearly from initial and final values for the whole batch of samples, although no statistical difference was ever observed between the start and end calibrations. About 10 ml of the headspace (or standard) was injected through a 6-way valve from which a 2 ml subsample (loop) was injected into a 2 ml column of magnesium perchlorate (water vapor trap), and then into a packed column  kept at 50 °C, using N2 as carrier gas. The 10 ml volume of headspace was sampled with a plastic syringe with a steel needle through the septum, and the retrieved gas volume was replaced by a hyper-saline solution (about 60 g NaCl L−1) injected with another syringe in the bottom of the serum bottle, in order to keep the sampled gas sample at atmospheric pressure. Chromatographic peak areas were integrated and logged using the Peaksimple software (version 4.44 for WindowsTM XP). The in-situ CH4 concentration was computed4 and Henry’s constantThe concentration of CH4 flux (F) was computed according to:The air-sea CHk is the gas transfer velocity and ΔCH4 is the air-sea CH4 concentration gradient computed from the measured dissolved CH4 concentration in seawater and the concentration at equilibrium with an atmospheric CH4 partial pressure value of 1.8 ppm, computed with Henry’s constantwhere k values were computed from the parameterization as a function of wind speed based on dual deliberate tracer (3He/SF6) experiments in the Southern Bight of the North Sea4 in seawater computed from temperaturehttp://www.cdc.noaa.gov/) at 2 grid points covering the sampled region . F was computed using daily wind speed values (average of the 2 grid points) for a time interval of 30 days centered on the date of the middle of the cruises.The How to cite this article: Borges, A. V. et al. Massive marine methane emissions from near-shore shallow coastal areas. Sci. Rep.6, 27908; doi: 10.1038/srep27908 (2016).


Systolic blood pressure (SBP) increases steadily with age and bears an independent continuous relationship with the incidence of cardiovascular events. Low-grade inflammation is a suspected pathomechanism causing vascular aging and promote coronary artery disease (CAD). Recent animal studies give evidence that Toll-like receptor 4 (TLR4) modulate inflammation and contribute to age-dependent SBP increase. However, there are no data about TLR4 and age-dependent blood pressure increase in human.We therefor investigate a human cohort of 2679 patients with CAD aged between 50–80 years. Genotypes were determined for the TLR4 single nucleotide polymorphism rs4986790 (TLR4 896A/G). Patients were stratified according to tertiles of age and the upper tertile was compared to lower tertiles.P < 0.05) and lower pulse pressure  as compared to TLR4 896A/A allele carrier.In this cohort we show that older patients with the TLR4 896 G allele had significantly lower SBP  contains supplementary material, which is available to authorized users. Systolic blood pressure (SBP) increases steadily with age and bears an independent continuous relationship with the incidence of cardiovascular events . More thChronic low-grade inflammation plays a crucial role in hypertension during aging –9. This The role of TLR4 polymorphism in CAD and myocardial infarktion was inconsistant in the literature , 17. RecP < 0.05). This is also correlated to a reduced number of hypertensive patients in this group (Table p < 0.05). Univariate analysis confirmed age (p < 0.001) and sex (p < 0.001) as commonly known blood pressure modulating risk factors in all tertiles of the cohort. Interestingly TLR4 G polymorphism shows a significant association for SBP (p = 0.017) (Table p < 0.001) and pulse pressure (p = 0.026) only in the upper age tertile (age ≥70 and <80 years) . Multivariate analysis of the upper age tertile confirm TLR4 896 G polymorphism as independent predictor of SBP and hypertension  . Dividinup Table . Pulse p p < 0.00 and sex on Table Table 1CoThis analysis demonstrates in humans that 896G allele carriers older than 70 years reveal lower SBP suggesting an effect of TLR4 signaling on SBP increase with aging.The increasing incidence of hypertension with age is thought to be a physiological process which develops with vascular aging mediated by low-grade inflammation and oxidative stress. Animal studies demonstrated that oxidative stress is acutely induced in the aortic tissue by Toll like receptor 4 (TLR4) ligands. TLR4 are present in different vascular beds and TLR4 ligands have been shown to induce chronic low-grade inflammation and oxidative stress in vascular smooth muscle cells , 23. EveWe investigated the human TLR4 SNP rs4986790  in 2679 patients with history of myocardial infarction . This poVascular aging is accompanied by vascular damage. Pulse pressure is an accepted parameter of vascular damage. Our data confirm that patients without the functional TLR4 SNP have a pulse pressure increase with age corresponding to the general human population , 30. By a-error of 0.05.The probability of a false negative association result because of population stratification is relatively low, because the study participants were consecutively recruited from a defined geographic area of southern Germany with limited recent immigration. The sample size allowed an analysis with 80 % power to detect a six mmHg decrease of SBP among the carriers of the 896G allele at a two-sided In summary, our data indicate for this large cohort of patients with myocardial infarction that carriers of the TLR4 SNP rs4986790 starting from the age of 70 years have a lower SBP and pulse pressure. We propose that TLR4 signaling influences age-dependent SBP increase in CAD patients.We demonstrate an association between the TLR4 SNP rs4986790 genotype and age-dependant blood pressure increase in large cohort of patients with coronary artery disease.Participants were examined at 1. Medizinische Klinik rechts der Isar, Technischen Universität München or Deutsches Herzzentrum München. Between 1993 and 2002, patients with myocardial infarction between the ages of 50 to 80 years were enrolled in a dedicated registry. Written informed consent for genetic analysis was obtained from all individuals. In no case, consent was withdrawn. Out of this cohort, patients with cardiogenic shock and advanced heart insufficiency defined as a SBP < 100 mmHg were excluded, finally reaching a cohort size of 2679 individuals. SBP and DBP were determined under standardized conditions in the laying position . Pulse pressure was calculated from systolic and diastolic blood pressure. Clinical and laboratory data were prospectively collected in an online database. Source data check was done with 20 % of the data. The Institutional Ethics Committee approved the study protocol and the reported investigations were in accordance with the principles of the current version of the Declaration of Helsinki.The diagnosis of myocardial infarction was defined according to the European Society of Cardiology. Briefly, patients presenting with chest pain lasting >20 min combined with ST-segment elevation or pathological Q waves on a surface electrocardiogram. Patients with myocardial infarction had to show either an angiographically occluded infarct-related artery or regional wall motion abnormalities corresponding to the electrocardiographic infarct localization or both. Systemic arterial hypertension was defined as a systolic blood pressure of ≥140 mmHg and/or a diastolic blood pressure of ≥90 mmHg, on at least two separate occasions, or anti-hypertensive treatment. Hypercholesterolemia was defined as a documented total cholesterol value ≥240 mg/dL (≥6.2 mmol/L) or current treatment with cholesterol-lowering medication. Persons reporting regular smoking in the previous 6 months were considered as current smokers. Diabetes mellitus was defined as the presence of a fasting glycaemia ≥126 mg/dL or patients on antidiabetic treatment.TLR4 gene, TLR4A allele) deposited under accession number AF177765 in GenBank (http://www.ncbi.nlm.nih/entrez/). The primers used for amplification of the 896A/G SNP  were 5′ TTGAAGAATTCCGATTAGCATACTTAGAC 3′ and 5′ TCACCAGGGAAAATGAAGAAACAT 3′. Allele-specific signalling was accomplished with the use of the fluorogenic dyes 6-carboxy-fluorescein (FAM) and VIC (proprietary dye of Applied Biosystems) which were attached to the 5′ end of the probe oligonucleotides. Minor groove binder (MGB) groups were conjugated with the 3′ end of the oligonucleotides to facilitate formation of stable duplexes between the probes and their single-stranded DNA targets. The structures of the probes were as follows : FAM-5′ CCTCGATGATATTATTGACT 3′-MGB (for 896A), VIC-5′ CTCGATGGTATTATTG 3′-MGB (for 896G) [BccI  (896A/G SNP). The results obtained with the different methods were fully corresponding, which demonstrated the reliability of the TaqMan systems that were used for genotyping of the 896A/G SNPs in the entire study population. Genotype determination was done by workers who had no knowledge of clinical, laboratory, or angiographic data of the individuals enrolled in the study.A blood sample was drawn from each participant during the regular routing examination for coronary artery angiogram. Genomic DNA was extracted from peripheral blood leukocytes with the QIAamp DNA Blood Kit  or the High Pure PCR Template Preparation Kit . Genotype analysis was performed with allele-specific fluorogenic oligonucleotide probes in an assay combining the polymerase chain reaction (PCR) and the 5′ nuclease reaction . Primers and probes were established with the Primer Express software  after import of a DNA sequence (Homo sapiens or 896G) . Oligonuχ2 test or Fisher's exact test, as appropriate. Continuous variables are expressed as mean ± SD and compared by means of the unpaired, two-sided t test. Genotype frequencies in the case group were compared with values predicted by Hardy–Weinberg equilibrium with the use of the χ2 test. Univariate analysis was performed for the whole cohort, upper age tertile and both lower age tertiles. Multivariate analysis used age, gender and hypercholesterolemia. Level of significance was set at p < 0.05.Patients in the cohort were divided by age into tertiles. In order to investigate the age-related effect, the lower two tertiles were summarized (age ≥50 and <70) and compared with the upper tertile (age ≥70 and <80). The association was examined by the univariate analysis using Spearman’s correlation test. The analysis consisted of comparing separate genotype distributions, between the age tertiles of patients with MI. Association analyses for SBP and DBP were conducted using linear regression, and analyses for dichotomous hypertension using logistic regression Discrete variables are expressed as counts (percentage) and compared with the use of the


This paper investigates the unsteady MHD flow of viscous fluid between two parallel rotating disks. Fluid fills the porous space. Energy equation has been constructed by taking Joule heating, thermal stratification and radiation effects into consideration. We convert system of partial differential equations into system of highly nonlinear ordinary differential equations after employing the suitable transformations. Convergent series solutions are obtained. Behavior of different involved parameters on velocity and temperature profiles is examined graphically. Numerical values of skin friction coefficient and Nusselt number are computed and inspected. It is found that tangential velocity profile is increasing function of rotational parameter. Fluid temperature reduces for increasing values of thermal stratification parameter. At upper disk heat transfer rate enhances for larger values of Eckert and Prandtl numbers. No doubt the fluid flow by rotating disks analyzed extensively because of its many industrial and engineering applications. Such consideration has relevance in medical equipment, food processing technology, air cleaning machine, electric power generating system, aero dynamical engineering, food processing machines and gas turbines. Initial work on rotating disk is presented by Karman . He formImpact of stratification is very important for heat transfer analysis. Stratification phenomena occur due to variation in temperature or fluid with different densities. Thermal stratification has many applications in reservoirs, oceans, estuaries, salinity stratification in rivers, industrial food, heterogeneous mixtures in atmosphere and manufacturing processes. Zhang et al.  examinedStudy of fluid flow with magnetic field has many applications in physics, chemistry, engineering, metallurgy, polymer industry, power generators, pump, droplet filters, electrostatic filters, reactors cooling, the design of heat exchangers, and accelerators. In such examples rate of heat cooling has vital role to improve the desired characteristics of the final product. Intensity and orientation of magnetic field strongly affect the characteristics of the flow. Heat transfer characteristics of the flow strongly changed when magnetic field is applied because it manipulates the suspended particles of fluid and rearranges their concentration in the fluid. Nanofluid flow with convective conditions and MHD effects is inspected by Hayat et al. . Sheikho2O in plants and trees, flow of fluids and solutes in biological tissues and melting and metamorphism of snow. Recently porous medium has gained much interest of researchers because it has many industrial applications like paper pulp drying, gas management in fuel cell, detergent tablets, drying of foods and biological processes such as diffusion, capillarity, dissolution, adsorption, clogging, degradation and shrinkage. Moneim and Hassanin ε we differentiate ξ as follows:To get more simplified form and to remove ξ and taking limit from 0 to ξ we arrive atAlso pressure term can be calculated by integrating τzr and τzθShear stresses at lower rotating disk in radial and tangential directions are Total shear stress is defined asCf1 and Cf2 at the lower and upper disks areqw is given bySkin friction coefficients The Nusselt numbers for lower and upper disks are as follows:f0(ξ), g0(ξ) and θ0(ξ) and auxiliary linear operators Lf, Lg and Lθ are taken as follows:ci(i = 1−8) are the constants.Initial guesses q∈ as the embedding parameter and ħf, ħg and ħθ the non-zero auxiliary parameters then the zeroth order deformation problems areDenoting th order deformation problems areThe mfm, gm, θm) comprising the special solutions ci (i = 1−8) are the involved constants.The general solutions  when ħf = −0.5, ħg = 0.7 and ħθ = −0.7.HAM has great feature to control the convergence region by taking appropriate values of nges see . Acceptaf″(0), g′(0) and θ′(0) are convergent up to seven decimal places. We noticed that 11th, 10th and 4th order of approximations are appropriate for convergence of f″(0), g′(0) and θ′(0) respectively.This section describes the impact of various involved parameters on the velocities, temperature, Nusselt number and skin friction coefficient. For this purpose the graphs and tables are constructed.f′(ξ) and axial velocity f(ξ) profiles for Reynolds number Re and scaled stretching parameters γ1 and γ2. Figs γ1 on the radial and axial velocity profiles. It is observed that magnitude of radial velocity increases near the lower disk while opposite behavior is noted near upper disk. However axial velocity increases throughout the system. Radial and axial velocity profiles take negative values near the upper disk because stretching at lower disk is increasing. Figs γ2 on radial and axial velocity of fluid. For larger values of γ2 the radial velocity of fluid enhances near the upper disk and opposite behavior is noticed at lower disk. However the result of axial velocity is reverse.Figs M, porosity parameter β, unsteadiness parameter A1, stretching parameter at upper disk γ2 and rotation parameter Ω on tangential velocity profile g(ξ). g(ξ). For increasing values of Re tangential velocity g(ξ) decreases. M on g(ξ). Tangential velocity decreases as we increase the values of M because magnetic field is a retarding force so when it applies to the fluid it slows down the motion of the fluid particles. Influence of porosity parameter β is portrayed in β increase the permeability constant K0 and thus tangential velocity g(ξ) increases. A1 on tangential velocity. It is observed that for increasing values of A1 the tangential velocity decreases. Impact of stretching parameter of upper disk γ2 on tangential velocity g(ξ) is shown in γ2 the stretching rate enhances. g(ξ). Tangential velocity of fluid is increasing function of Ω.Figs M, unsteadiness parameter A1, stretching parameters γ1 and γ2, rotation parameter Ω, thermal stratification parameter S, Prandtl number Pr, radiation parameter R and Eckert number Ec on temperature profile θ(ξ) shown in the Figs M on temperature profile. Fluid temperature increases with larger values of Hartman number. In fact Lorentz force is also known as a resistive force which slows down the movement of particles. As a result heat is produced and temperature increases. A1 on fluid temperature. For increasing values of unsteadiness parameter the fluid temperature enhances. Figs γ1 and γ2 on temperature profile θ(ξ). Influences of γ1 and γ2 on temperature profile are opposite. Increasing values of stretching parameter at lower disk γ1 reduce the temperature while temperature enhances by increasing stretching parameter of upper disk γ2 Impact of rotation parameter Ω on temperature profile is shown in θ(ξ) for thermal stratification parameter S. Temperature profile and thermal boundary layer thickness are decrease via S. Actually the temperature difference between two disks decreases gradually which shows reduction in fluid temperature. θ(ξ). Temperature profile is decreasing function of Pr because thermal diffusivity decreases by increasing Prandtl number. Hence heat diffuses slowly and so temperature decreases. θ(ξ) for increasing values of radiation parameter R. Temperature profile is increasing function of R. As we increase the values of R mean absorption coefficient decreases. Thus rate of radiative heat transfer to the fluid increases. Ec on fluid temperature. It is noted that the temperature and thermal boundary layer thickness are enhances with increase in Ec. When Ec increases due to friction the heat produced in the fluid and thus temperature enhances.Influences of Hartman number M, porosity parameter β and stretching parameters γ1 and γ2 on skin friction coefficients at the lower and upper disks are depicted in M, γ1 and γ2 while it shows decreasing impact for increasing values of porosity parameter. Increasing values of Re, M, β, γ1 and γ2 enhance skin friction coefficient at upper disk. S, Prandtl number Pr, Reynolds number Re, Eckert number Ec and radiation parameter R on rate of heat transfer at the lower and upper disks. It is observed that impact of Pr, Re and Ec on Nusselt number at both disks is opposite. At lower disk Nusselt number is decreasing function of Pr, Re and Ec while it increases at upper disk. As we increase the values of S the heat transfer rate at both disks decreases. With increasing values of radiation parameter R the heat transfer rate at both disks enhances.Influences of Reynolds number Re, Hartman number Heat transfer and MHD flow analysis between two parallel rotating disks is carried out in presence of thermal radiation, stratification and Joule heating. Main findings of our problem are as follows:Magnitude of radial and axial velocities decreases near the lower disk for increasing values of Re.γ1 and γ2 at lower disk is observed for radial and axial velocities.Opposite behavior of Tangential velocity is decreasing function of Hartman number.Fluid temperature decays with increasing values of thermal stratification parameter and Prandtl number.Temperature profile enhances for larger values of Eckert number and radiation parameter.M and γ1.Surface drag force enhances at both disks for increasing values of Re, Ec heat transfer rate enhances.For larger values of Pr, Re and


However, when RNA polymerase (RNAP) was incubated with Pm DNA in the absence of Mor, a band at promoter position −51 was hypersensitive to DNase I cleavage, demonstrating an interaction of RNAP with the promoter DNA. The hypersensitivity was similar at four different lengths of Pm DNA assayed from −62 to +10, −62 to +46, −96 to +10, and −96 to +46. The hypersensitivity occurred equally well at 5°C, 15°C, and 30°C, indicating that it did not require open complex formation, which only occurred at 30°C. The −51 hypersensitivity at 5°C and 15°C was eliminated by the addition of heparin, consistent with the possibility that it arose by formation of unstable closed complexes of RNAP bound to Pm DNA. Generation of the hypersensitive band required the complete RNAP with its αCTDs, but neither the αCTD nor intact α were sufficient for the interaction and resulting hypersensitivity. There was no correlation between the level of hypersensitivity observed in vitro and the level of Pm activity in vivo, as assayed by the Mor-dependent production of β-galactosidase from a Pm-lacZ fusion. In an “order of addition” experiment, preincubation of Pm DNA with Mor followed by addition of RNAP led to the fastest open complex formation, whereas preincubation of Pm DNA with RNAP gave the slowest. These results support the conclusion that Mor recruits RNAP to Pm rather than reposition a prebound RNAP, as occurs for C-dependent repositioning of RNAP at the Mu late promoter Pmom.The bacteriophage Mu Mor activator protein is absolutely required for transcription from the Mu middle promoter P Escherichia coli K-12 (E. coli) is the key enzyme involved in gene expression. It performs multiple functions in transcrip-tion including promoter recognition, abortive initiation, promoter clearance, elongation, pausing, and termination. Each of these steps can involve conformational changes and serve as a substrate for subsequent steps and thus are targets for regulation . There are multiple σ factors which direct transcription to different sets of genes by recognizing and binding to different specific promoter sequences, allowing the cell to respond to varying environmental conditions and physiological needs  plays an essential role in RNAP assembly by providing the contact surfaces for α dimerization and binding of the β and β′ subunits  plays a regulatory role by binding to AT-rich UP elements located upstream of the −35 region in some promoters and by providing contact surfaces for interaction with trans-acting protein factors called activators  make up the majority of the catalytic site as well as the two sides of the crab claw structure that closes around the template DNA  of Ishihama . The 613Ishihama ; becauseIshihama . The larc) that are in rapid equilibrium with free promoter DNA and free RNAP (McClure c is converted to one or more intermediate complexes (RPi) which exhibit footprints that extend downstream to base +15 to +20   are up-regulated by activator protein binding to the promoter and interacting with RNAP   that is related to the dyad-symmetry element in Pm ; the Ni-NTA column was from Qiagen ; and the Superdex 75 pg was from Amersham Biosciences . Isopropyl-β-D-thiogalactopyranoside (IPTG) and ortho-nitrophenyl-β-galact-opyranoside (ONPG) were from US Biological  and American Biorganics, Inc. , respectively. Radiolabeled [γ-32P] ATP (3000 Ci/mmol) was from Perkin Elmer Life Science , and dNTPs were from Promega . The DNase I (type II from bovine pancreas) was purchased from Sigma Chemical Co. Enzymes EcoRI and BamHI were from New England Biolabs ; T4 polynucleotide kinase was from Promega. The Taq DNA polymerase, T4 DNA ligase and shrimp alkaline phosphatase were from Roche .Standard chemicals for working with DNA and proteins were usually obtained from Sigma Chemical Co.  and BioRad , respectively. Some buffer and media components were obtained from Fisher  or JT Baker . Sources for specific chemicals can be found in previous publications, including those by Artsimovitch and Howe , Kahmeyeβ-galactosidase assays. Standard LB (Miller α subunit and the His-tagged α-CTD. Modified LB (Howe μg/mL and ampicillin (Ap) at 40 μg/mL were added to media when necessary for plasmid maintenance.Minimal medium with casamino acids , a derivative of JM109 carrying an F' plasmid deleted for both lacZ and lacY and expressing higher than normal levels of Lac repressor (Artsimovitch and Howe F+ΔaraD-leu::Mu cts61 zai-737::Tn10 Δlac TetR/pMK100) was used as a source of plasmid pMK100 (Kahmeyer-Gabbe and Howe E.coli B ompT rb− mb− λDE3 pLysS) was freshly transformed with plasmid pKM90 and used for Mor protein overexpression (Artsimovitch and Howe The host strain background for most plasmid constructions and in vivo assays was EcoRI-SmaI-BamHI polylinker upstream of a promoter-less lac operon and five tandem repeats of the rrnB transcription terminator upstream of the polylinker to prevent expression of lacZ by read-through of plasmid transcripts. The lacY gene was deleted to generate pLC1 (Chiang and Howe HindIII linker was cloned just upstream of the polylinker in pLC1 to generate pIA12 (Artsimovitch and Howe m promoter DNA were amplified by PCR using oligonucleotide primers containing EcoRI (upstream primer) and BamHI (downstream primer) sites and cloned into EcoRI-BamHI-digested pIA12 to generate the following Pm-lacZ fusion plasmids: pYM114 contains Pm sequences from −98 to +46, pMM1 has Pm −98 to +10, pYM113 has Pm −62 to +46. Plasmid pIA14 has Pm −62 to +10 cloned into pIA12  that was assayed in the same experiment, setting the wild-type activity to 1000 units. The activities presented were derived by averaging the results obtained in at least three independent assays.The y Miller  with miny Miller . Enzyme y Miller  and normαCTD and thrombin-cleaved untagged αCTD were thoughtfully provided by Muthiah Kumaraswami. Purified His-α protein was gratefully received from Ji Ma. Uncleaved His-αCTD contained 21 extra amino acids at its N-terminus; thrombin-cleaved αCTD has only four extra N-terminal amino acids. The reconstituted wild-type and mutant (ΔαCTD) RNA polymerases were graciously provided by Wilma Ross and Richard Gourse.Mor overexpression and purification was performed as described by Artsimovitch and Howe  except t32P] ATP (3000 Ci/mmol); the enzyme was heat-inactivated, and the mixture was added directly to a PCR reaction containing an unlabeled opposing primer and plasmid DNA template containing wild-type or mutant Pm. Varying amounts of purified Mor and/or RNAP were incubated with 0.42 nmol/L probe in DNase I footprinting binding buffer  at 30°C for 20 min in a 40-μL reaction volume. Next DNase I (4.5 ng) was added to the binding reactions which were then incubated for 1 min at room temperature and stopped by addition of 50 μL of stop solution . The DNase I treated samples were subjected to phenol:chloroform extraction  to remove the proteins, 60 μL of Quench A solution  and 650 μL of cold absolute ethanol were added to each tube and the mixtures were held on dry ice for 15 min for DNA precipitation. Following centrifugation, each DNA pellet was washed once with cold 70% ethanol and dried in a SpeedVac rotary evaporator. The modified DNAs were cleaved by treatment with 70 μL of a freshly made 10% piperidine solution at 90°C for 30 min. The DNA samples were dried, and the remaining piperidine was removed by SpeedVac drying following sequential resuspension in 30 and 20 μL water. The samples were subjected to electrophoresis on a 6% sequencing gel  were noted, suggesting that RNAP potentially interacted with Pm in the absence of Mor  whether RNAP interaction with Pm in the absence of Mor plays a role in activation of Pm in the presence of Mor. (2) whether or not Mor repositions a prebound RNAP at Pm, and (3) whether evidence for a role of Mor in recruitment of RNAP could be detected by a time difference for open complex formation when two of the three interacting components—RNAP, Mor and Pm—were preincubated together and then the third added last.In previous DNase I footprinting experiments with Pm DNA sequence annotated with the positions of the dyad-symmetry element for Mor binding (−51 to −36). Figurem with the −35 consensus sequence (TTGACA), even when tested with spacings of 17 ± 4 between the −10 and possible −35 sequences, to identify a candidate −35. We note that Pm also lacks the extended −10 sequence, TGn, located immediately upstream of −10 that allows transcription in the absence of a −35 element  between 990 and 1120 units relative to promoter −98 to +46 which was arbitrarily set to 1000 units  Mor and αCTD bound synergistically to Pm without αNTD or any other subunit of RNAP. To ask whether the −51 hypersensitivity would display the same properties, we carried out DNase I footprinting at 5°C with reconstituted RNA polymerases containing and lacking αCTD  was used, there was neither an upstream footprint nor −51 hypersensitivity  bound and produced upstream footprints, but no −51 hypersensitivity  binding of the αCTD and part or all of the remainder of RNAP were required to generate the −51 hypersensitivity, but they did not address the role of the −51 hypersensitivity in Pm activation. If activation of Pm were caused by a Mor-dependent repositioning of a prebound RNAP, one would expect to see a correlation between promoter activity and the degree of hypersensitivity at position −51. We tested this hypothesis by assaying for position −51 hypersensitivity in a pre-existing collection of mutants with base changes upstream of −57. These mutants had essentially wild-type β-galactosidase activities, but a wide range of −51 hypersensitivities. DNase I footprinting was carried out for two mutants with three (JM2-14) or five (JM4-14) base changes in the region from −68 to −57  and greatly decreased for the other . These results demonstrated that there was no correlation between the levels of position −51 hypersensitivity in the absence of Mor and promoter activity in the presence of Mor. This argued against Mor repositioning prebound RNAP.The above experiments demonstrated that both the  three JM-14 or fim activation: (1) Mor might recognize and bind to Pm, then recruit RNAP to bind and initiate transcription; (2) RNAP might be continually bound to Pm with Mor functioning at one or more “post-recruitment” steps, such as isomerization or promoter clearance; or (3) RNAP and Mor might form a complex in solution before binding to Pm DNA. To determine which of these possibilities was most likely, we conducted an “order of addition” experiment, asking whether preincubation of any two of the three components  would lead to faster open complex formation following addition of the third component. All three possible orders of addition were tested. In the first experiment, open complexes were assayed by the generation of an RNAP-dependent DNase I footprint in the region from −23 to +14  Our data make it highly unlikely that Mor repositions a prebound RNAP. First, a higher degree of hypersensitivity, indicative of greater binding of RNAP in the absence of Mor, did not increase promoter activity in the presence of Mor, arguing against a role for Mor repositioning RNAP. Second, the observation in the “order of addition” experiment was that the presence of RNAP bound to Pm actually delayed open complex formation relative to the other orders. (3) In the “order of addition” experiment, the three possible orders showed significant differences in the timing of open complex formation. The order with Mor binding to Pm first produced open complexes the most quickly, supporting the hypothesis that Mor recruits RNAP to the promoter.These results answer three important questions: (1) They demonstrated that −51 hypersensitivity arose from interaction of RNAP and Pm. In addition, they demonstrate the considerable strength of Mor interaction with the αCTD of RNA polymerase, enough to tether the RNAP to the promoter in the absence of open complex formation. Finally, they have demonstrated that an “order of addition” experiment can effectively detect differences in the timing of open complex formation when they are large enough to contribute to investigations of transcriptional activation mechanisms.These results notably increase our knowledge regarding transcription activation by Mor at P


Phantoms are essentially required to generate boundary data for studying the inverse solver performance in electrical impedance tomography (EIT). A MATLAB-based boundary data simulator (BDS) is developed to generate accurate boundary data using neighbouring current pattern for assessing the EIT inverse solvers. Domain diameter, inhomogeneity number, inhomogeneity geometry , background conductivity, and inhomogeneity conductivity are all set as BDS input variables. Different sets of boundary data are generated by changing the input variables of the BDS, and resistivity images are reconstructed using electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS). Results show that the BDS generates accurate boundary data for different types of single or multiple objects which are efficient enough to reconstruct the resistivity images for assessing the inverse solver. It is noticed that for the BDS with 2048 elements, the boundary data for all inhomogeneities with a diameter larger than 13.3% of that of the phantom are accurate enough to reconstruct the resistivity images in EIDORS-2D. By comparing the reconstructed image with an original geometry made in BDS, it would be easier to study the inverse solver performance and the origin of the boundary data error can be identified. Ω) from the surface potentials developed by a constant current injection through the surface electrodes surrounding the domain to be imaged. Before carrying out the practical measurements on patients, it is advised to test an EIT system with a tissue mimicking model of known properties   and the nodal potential matrix [Φ]  through the transformation matrix [K(σ)] is mathematically represented asIn EIT, the FEM technique is used to derive the forward model from the governing equation in the form of a matrix equation establishing the relationship between the injected current and the developed potential within a DUT. The relationship can be assumed as the transfer function of the system which is mathematically represented as a matrix called global stiffness matrix (GSM)  or transC] and [K(σ)] are known, and the nodal potential matrix [Φ] is unknown, the forward model or the mathematical problem is termed as the “forward problem”. The procedure of calculating the [Φ] by solving the forward problem (K(σ)] and known [C] is termed as “forward solution”. In EIT, the forward solver first computes the potential distribution with the assumed initial conductivity distribution (σ0) with a known constant current simulation, and then the inverse solver reconstructs the conductivity distribution from the measured boundary potential data for a same constant current injection through surface electrodes. The EIT reconstruction algorithm tries to mathematically find the elemental conductivity values (conductivity distribution) for which the difference between the estimated nodal potentials (Vc) computed in the FS and the potentials measured (Vm) on the surface electrodes  becomes minimum.Now, in FEM formulation in EIT, when the current matrices [ problem  with knoσ]) is calculated and the boundary data mismatch vector (ΔV  =  Vm − Vc) is minimized by an iteration technique like the modified Newton-Raphson iteration technique (NRIT) [σ] matrix is the desired variation in the elemental conductivity values in [σ] matrix for which the forward solver calculates the boundary potentials more similar to the measured value in next iteration using NRIT. Therefore, the algorithm starts with an initial elemental conductivity vector ([σ0]), and it is then updated to ([σ1] = [σ0] + [Δσ]) in the next iteration. Using this [σ1], FS calculates a new potential distribution in DUT and a new voltage mismatch vector [ΔV1] is thus obtained and compared with the previous voltage mismatch vector [ΔV0]. If the ΔV1 is not found as the minimum, the iteration process is continued till the kth iteration using the conductivity update vector ([Δσk]) developed by GN-MMA. Using, NRIT the [σ] matrix is iteratively updated to [σk+1] = [σk]+[Δσk] and repetitively tries to find out the minimum value of [ΔV].The inverse solver of the EIT reconstruction algorithm is developed with a mathematical minimization algorithm (MMA) –22 such e (NRIT) –22. The σk] for which the voltage mismatch vector is minimized [ΔV]. At a particular iteration in this MMA, the elemental conductivity matrix is calculated when the current matrices [C] and [Φ] or [ΔV = Vm −  Vc] are known. This process is logically an opposite process to the forward problem. Thus, when the current matrices [C] and [Φ] are known, and the elemental conductivity matrix [σ] is unknown, the model or the problem is called the “inverse problem.” The procedure of calculating the [σ] or [Δσ] using with known [ΔV] and the known [C] is termed as “inverse solution.”Hence, in the EIT inverse solver, it is understood that the desired elemental conductivity matrix is obtained by a minimization algorithm (MMA) which is composed of Gauss-Newton method and Newton-Raphson iteration in which the technique iteratively tries to find out an optimum conductivity distribution [σ] for which the voltage mismatch vector [ΔV] becomes minimum. In the image reconstruction process, the minimization algorithm [s) from the computational predicted data [Vc] and the experimental measured data [Vm] and runs iteratively to minimize it. Generally, in the EIT image reconstruction algorithm, the inverse solver searches for a least square solution of the minimized object the function (s) using by a Gauss-Newton method and the NRIT-based iterative approximation techniques. Electrical conductivity imaging is a highly nonlinear and ill-posed inverse problem –22. In Elgorithm , 18 firsf is a function mapping a t-dimensional (t is the number of element in the FEM mesh) impedance distribution into a set of M  available) approximate measured voltages, then the Gauss-Newton-method-based minimization algorithm  is given byBy Gauss-Newton method, the conductivity update vector [ΔH = [f′′] is known as the Hessian matrix  and [Jk] are the voltage mismatch matrix and Jacobian matrix, respectively.In general, using NRIT method, the conductivity update vector expressed as in  can be rf′]Tmatrix in  is called the regularization coefficient [The [atrix in  is alwayatrix in  changes fficient –26(13)sDifferentiating the inject function in  with resσ] is obtained asNow, using Gauss-Newton- (GN-) method-based minimization process, the conductivity update vector [ΔHessian matrix [Neglecting the n matrix  in 15)Hessian f′ by J and GTG by  I (identity matrix) (Replacing  matrix)  reduces J = f′ is the Jacobin as stated earlier.where the matrix σ]) is found asThus, the conductivity update vector ([ΔλIσ) is neglected [σ] is calculated asSometimes, the last term  conductivity matrix [σ0]. The voltage mismatch matrix [ΔV] is estimated, and then it is used to calculate the conductivity update matrix [Δσ] using GN-MMA and is added to the initial conductivity matrix ([σo]) to update it to a new conductivity matrix [σ1 = σo + Δσ] using NRIT. New update matrix [σ1] is used in forward solver to obtain a new calculated boundary data matrix [Vc1] which provides a new voltage mismatch matrix [ΔV1]. Therefore, the NRIT algorithms iteratively calculate the [Δσ] using GN-MMA to find out an optimized [σ] matrix for which the [ΔV] reaches its minimum value. Thus, the EIT reconstruction algorithm is found to work in the following sequences:(1)Vc] for a known current injection matrix [C] and an initial guess (known) conductivity matrix [σ0],forward solver calculates the boundary potential matrix [(2)Vm] is compared with [Vc] to estimate the [ΔV] as [ΔV = Vc − Vm],measured voltage data matrix   is calculated by Gauss-Newton-based minimization algorithm,conductivity update vector [Δ(5)σo] matrix is updated to a new conductivity matrix [σ1 = σo + Δσ] by adding [Δσ] to [σ] using Newton-Raphson iteration technique (NRIT),[(6)σ1] is used in forward solver to calculate the new voltage mismatch matrix [ΔV1],new update matrix [(7)V1] is minimum or not or compare the [ΔV] with a specified error limit (ε) if provided,check whether the  , through the transformation matrix [K(σ)] which is mathematically represented by (K(σ)] in EIT is actually an admittance matrix [K(σ)] inforward model represents the transfer function of the EIT system obtained from the governing equation by FEM formulation . Therefore, the [MEP] is found as a column matrix containing 16 × 16 voltage data all collected with respect to the virtual ground point of the DUT. Hence, in the present study, with neighbouring current injection method, the [MEP] is found as a 256 × 1 matrix containing 256 electrode potentials. In the present study, 1 mA current injection is simulated through the electrodes of the simulated domain containing sixteen nodal electrodes using adjacent or neighboring current injection protocol  [D = 2Rp), inhomogeneity radius (ri), inhomogeneity geometry , inhomogeneity number (Ni), bathing solution conductivity (σb), and inhomogeneity conductivity (σi). 1 mA current injection is simulated to the domain boundary, and corresponding boundary data sets are used for image reconstruction in EIDORS. Data generation in BDS and image reconstruction in EIDORS are studied for different inhomogeneity geometries in DUT. Reconstruction is also studied for different iterations and for multiple inhomogeneity reconstruction to evaluate the BDS. The BDS is designed in such a way that a huge number of voltage data sets can be generated using different types of phantoms with their different design parameters. Boundary potential data [(EIDORS) , 38 for Nmr) as shown in Nmr increases, the number of elements in the FE mesh is increased, and hence the geometric accuracy of the inhomogeneity increases which gives more accurate boundary data and better image reconstruction (Nmr = 4 as per the configuration of the PC (2.4 GHz/1.5 GBRAM/ P-IV) used. It is observed that the FE mesh with Nmr = 4 (containing 2048 elements and 1089 nodes) gives almost an accurate geometry  with a circular inhomogeneity  in the 9th iteration  with the circular inhomogeneities  positioned at different places using the BDS  with proper shape, which gives a boundary data without geometric error and automatically improves the image shape.Voltage data are also generated for a domain  with a circular inhomogeneity (σi = 0.005 S/m) with different diameters (2ri) and all positioned at the phantom center (r = 0). The boundary data are calculated and used for reconstructing the resistivity images. Results show that for the domain discretized with Nmr = 4, the data sets, generated with a diameter larger than 13.3% of the phantom diameter, are accurate enough  containing multiple circular inhomogeneities  placed at different positions inside the domain (r) of 37.5 mm. Similarly, another domain with three circular inhomogeneities (120° apart from each other) placed inside the phantom domain is shown in r) of 37.5 mm. 1 mA current is simulated with the neighbouring current pattern, and the boundary data are collected for resistivity reconstruction. It is noticed that the resistivity images  is developed for studying the resistivity reconstruction in inverse solvers of 2D-EIT. BDS is developed with four parts: imaging domain simulator (IDS), EIT model developer (EMD), current injection simulator (CIS), and boundary data calculator (BDC). Imaging domain simulator (IDS) simulates a domain with single or multiple inhomogeneities of different geometries defined with their corresponding conductivity distributions, whereas the EIT model developer (EMD) derives a forward model using FEM to solve the governing equation of the DUT. Current injection simulator (CIS) simulates a constant current injection through the simulated electrodes positioned at the domain boundary with the neighbouring current injection protocol. The boundary data calculator (BDC) solves the forward model to solve the governing equation and calculates the potentials at all the simulated electrodes. Boundary data are generated with different type of domains simulated in BDS by changing its input parameters. Resistivity images are reconstructed from the boundary data using standard EIT reconstruction software called EIDORS, and the BDS is evaluated. It is observed that the BDS with FE mesh with 2048 elements can simulate an inhomogeneity of desired geometry with suitable accuracy. The BDS with 2048 elements suitably generates the boundary data for simulated domains containing the objects with different geometries which are found efficient for image reconstruction in EIDORS. Results also show that the conductivity or resistivity profiles of the domains simulated in BDS are successfully reconstructed from their corresponding boundary data generated for different type of single and multiple inhomogeneities. By changing the inhomogeneity position, diameter, and number in BDS, boundary data are successfully generated as well as the resistivity images are reconstructed successfully. Multiple inhomogeneity imaging shows that the BDS suitably generates boundary data with the desired accuracy, and the boundary data are found efficient for resistivity reconstruction in EIDORS. Results also show that for the simulated domains discretized with


Post-learning hippocampal sharp wave-ripples (SWRs) generated during slow wave sleep are thought to play a crucial role in memory formation. While in Alzheimer’s disease, abnormal hippocampal oscillations have been reported, the functional contribution of SWRs to the typically observed spatial memory impairments remains unclear. These impairments have been related to degenerative synaptic changes produced by soluble amyloid beta oligomers (Aβos) which, surprisingly, seem to spare the SWR dynamics during routine behavior. To unravel a potential effect of Aβos on SWRs in cognitively-challenged animals, we submitted vehicle- and Aβo-injected mice to spatial recognition memory testing. While capable of forming short-term recognition memory, Aβ mice exhibited faster forgetting, suggesting successful encoding but an inability to adequately stabilize and/or retrieve previously acquired information. Without prior cognitive requirements, similar properties of SWRs were observed in both groups. In contrast, when cognitively challenged, the post-encoding and -recognition peaks in SWR occurrence observed in controls were abolished in Aβ mice, indicating impaired hippocampal processing of spatial information. These results point to a crucial involvement of SWRs in spatial memory formation and identify the Aβ-induced impairment in SWRs dynamics as a disruptive mechanism responsible for the spatial memory deficits associated with Alzheimer’s disease. Information processing and memory formation in rodents have been reported to be accompanied by an array of hippocampal field potential oscillations that are important functionally. For instance, theta oscillations occur during active behavior and rapid eye movement (REM) sleep and have been suggested to provide the temporal frame for the encoding of information4in vitroThe cognitive impairments associated with AD are related to degenerative synaptic changes produced by the presence of soluble amyloid beta proteins (Aβs) in vulnerable brain regions such as the hippocampus considered to be critical for spatial learning and declarative memory16 = 5.85, p < 0.0001), thus confirming the supportive role of the hippocampus in the formation and expression of recognition memory  monomers, dimers, trimers and tetramers under phosphate buffered saline (PBS) conditions  or the test phase . Likewise, there was no preference for a particular arm  = 0.0029, NS) and no effect of treatment on arm preference  = 0.2415, NS) during the encoding phase . Collectively, these findings indicate that Aβo-injected mice were capable of processing visuo-spatial information and forming short-term recognition memory. However, when the retention delay was extended, they exhibited accelerated forgetting, a memory profile also observed in transgenic mouse models of ADWe next sought to unravel the impact of Aβos on memory performance. We used a standardized assay to generate oligomers from synthetic Aβ peptides. As previously reportednditions . Larger nditions . Becausenditions . Followinditions . This de(1–42) peptide in the hippocampus 1 day and 15 days following intracerebroventricular injection. Aβ(1–42) peptides were detectable after 15 days. However, as could be expected, hippocampal Aβ(1–42) peptide concentration was lower after 15 days  compared to 1 day , a decrease likely resulting from cerebral clearance. Altogether, these results indicate that the Aβo-induced behavioral and electrophysiological (see below) changes that we observed are related, at least in part, to the hippocampal amyloid pathology.Aβos were injected intracerebroventrically to avoid hippocampal damage induced by the injection cannula that could have interfered with subsequent electrophysiological recordings in the hippocampus. To verify that Aβos invaded the hippocampus and were still present at the time of behavioral and electrophysiological assessments 15 days post-injection, we conducted experiments in which we measured the concentrations of the AβThe memory profile of Aβo-injected mice points to an inability to form a stable memory over time and is suggestive of impaired consolidation processes during which SWRs are thought to play a privileged roleTo examine the effects of Aβos on SWRs occurrence as a function of the cognitive demand, we recorded the extracellular field potential activity in the CA1 region of the hippocampus over 10 time intervals of 40 minutes distributed as follows: baseline activity prior to memory encoding , encoding-induced activity  and testing-induced activity  . This se6,9 = 16.16, p < 0.0001) which was due to an increase of post-learning  and post-test occurrence of SWRs . These findings reveal that a single learning session is sufficient to produce an increase in the hippocampal SWR occurrence rate, thereby reflecting an important involvement of hippocampal oscillations in memory formation. However, contrasting with memory paradigms involving multiple training sessionsInterestingly, during the course of this experiment, two peaks of hippocampal SWRs occurrence were clearly apparent in PBS-control mice, one triggered upon exploration of the two available arms of the 8-arm radial maze, the other occurring upon the recognition phase of the testing procedure during which mice successfully identified the presence of the new open arm  as well as “time bins” × “treatment” interaction , indicating that the dynamic of SWRs during the course of experiment was different in the two groups of animals. Finally, comparison of occurrence of SWRs during all time bins between control and Aβo-injected animals revealed significant difference for the post-encoding period  and a difference close to significance for the post-test period  with all other measurements remaining similar between the two groups (p > 0.2).In sharp contrast, cognitively-challenged Aβ mice exhibited impaired SWR patterns compared to PBS-control mice. Namely, the encoding and recognition-induced peaks in the SWR occurrence rate observed in the control group .When refining our analysis of SWR dynamics by restricting it to shorter time bins of 20 min, we found similar patterns of SWR occurrence in PBS-controls and Aβo-injected mice  and rend12,11 = 22.56, p < 0.0001) a two-way ANOVA showed significant “SWS bins” × “treatment” interaction , indicating a different time course of SWRs occurrence in the two groups. Moreover, a one-way ANOVA showed a significant main effect of repetition in the PBS-control group  and the Aβo-injected group . In the control group the post-hoc analysis revealed a significant increase of post-learning and post-test occurrence of SWRs . By contrast, in Aβ animals no difference between occurrence rate in SWS bins was found . Also direct comparisons of the SWRs occurrence rates in all SWS bins between the two groups showed significant difference for the post-encoding period , a difference approaching significance for the post-test period  and no difference for all remaining bins (p > 0.2).Binning total time and not SWS time might imply that for some animals the rate of SWRs for the first 40 min bin was calculated for instance over the first 5 min of SWS whereas for another time bin, it was calculated over the first 30 min, depending on how much the animal has slept during this time. Therefore we performed additional analysis taking into account time bins corresponding to SWS only . For eacRather than being memory-specific, the testing-induced increase in the occurrence of SWRs could be the consequence of homeostasis maintenance of the neuronal circuits underlying a sustained period of exploration in the Y-maze. To control for this potential confound, we analyzed in detail the profile of exploration of experimental Aβo- and vehicle-injected mice used for hippocampal recordings during both encoding and test phases in the Y-maze. Distance traveled , speed  and percentage of immobility  were similar across the two groups. The fact that vehicle- and Aβo–injected mice underwent the exact same procedure coupled to the observation that these mice explored as well as encoded similarly (as shown by a similar between-group recognition performance at the 10 min delay) enables to exclude a nonspecific contribution of homeostasis maintenance to the observed memory-induced changes in SWR occurrence. We did not observe any correlation between SWR occurrence and recognition memory performance in the Y-maze (data not shown), possibly because exploration time in new arm as the main readout of recognition performance can only be measured over one single trial (innate test with no repeated observations) and does not fully capture the vividness of the memory.Together, these results demonstrate that the deleterious effect of Aβos on the dynamics of SWRs is activity-dependent in nature and only effective in cognitively-demanding situations requiring hippocampal processing.Recognition memory, a subdivision of episodic memory, is of particular interest in the context of AD as this form of memory is typically affected during the early stages of this neurodegenerative diseaseConsistent with previous findings, our study reveals a transitory increase in the occurrence rate of hippocampal SWRs following a spatial learning episode, further strengthening the functional implication of SWRs in the progressive stabilization of spatial information during the course of memory consolidation processes5per seBecause SWRs are triggered in cognitively challenged animals, their dysfunctional patterns are expected to impair memory-related processes. Accordingly, when disrupted experimentally, abnormal SWR signatures leads to impaired spatial learning620We found that the accelerated memory decay of Aβ-treated mice was associated with an abolishment of the two time-limited peaks of SWRs normally seen in controls. The fact that vehicle- and Aβo–injected mice underwent the exact same procedure coupled to the observation that these mice explored as well as encoded similarly (as shown by a similar between-group recognition performance at the 10 min delay) enables to minimize the involvement of nonspecific aspects of our testing procedure. Although we did not record hippocampal activity of mice during testing in the Y-maze, it is likely that mice of both groups maintained a similar theta brain state during exploration of the maze. Thus, the increase in SWR occurrence observed after both encoding and testing phases in vehicle-injected, but not Aβo-injected mice, is likely to be predominantly related to the memory component of the testing procedure and not to a differential requirement of neuronal homeostasis between the two tested groups. Altogether our data suggest that the two time-limited peaks of SWRs likely constitute a prerequisite for the formation and accurate expression of spatial recognition memory.At the mechanistic level, memory reactivation is considered as the core iterative mechanism in contemporary consolidation models. Hippocampal place cells that were co-active during spatial exploration exhibit correlated firing patterns during SWS, revealing a replay mechanism. Importantly, hippocampal replay retains the original temporal order, and occurs preferentially during the occurrence of SWRs79Although many cellular and synaptic mechanisms can explain the Aβ-induced lack of SWRs triggered upon a cognitive challenge, one putative candidate is NMDAR-induced synaptic plasticity. Indeed, it has been demonstrated that high level of Aβos can alter glutamatergic synaptic transmission which in turn can lead to synaptic loss21per se. The failure in expressing long-term recognition memory of Aβ mice was also associated with a lack of a dedicated SWR occurrence peak, possibly indicating that the memory has not been properly stabilized (faster forgetting) or that access to a partially degraded trace was no longer possible. While highlighting the crucial roles played by SWRs dynamics in hippocampal memory processing, our findings also identified the absence of learning-induced SWR occurrence rates as a potentially early marker of AD.In conclusion, our data provide novel insights into the functional involvement of SWRs in the spatial memory impairments observed in AD. While unaffected in basal conditions, the occurrence patterns of hippocampal SWRs associated with either encoding or expression of recognition memory were specifically disrupted in the event of a challenging situation. Because Aβ-treated mice were able to form short-term but not long-term recognition memory, the absence of the SWR occurrence peak following encoding likely impacted predominantly consolidation processes involved in the subsequent stabilization of the hippocampal memory trace and not encoding processes (1–42) peptide was obtained from NeuraTest . Prior to resuspension, each vial was allowed to equilibrate to room temperature for 30 min to avoid condensation upon opening the vial. The first step in the resuspension of the lyophilized peptide was treatment in 1,1,1,3,3,3-hexafluoro-2-propanol . Each vial of peptide was diluted in 100% HFIP to 1 mM. The clear solution containing the dissolved peptide was then aliquoted in microcentrifuge tubes. The HFIP was evaporated using a gentle stream of nitrogen gas under the fume hood. Immediately prior to use, the HFIP-treated aliquots were carefully and completely resuspended to 2 mM in anhydrous dimethyl sulfoxide  by pipette mixing followed by bath sonication for 15 min. Then, the sample was dissolved in 95 μl of ice-cold PBS, immediately vortexed for 30 s, and incubated at 4 °C for 24 h. Final concentration obtained was 100 μM (store at −80 °C). This Aβ preparation has been characterized previously in Stine et al.in vivo in Balducci et al.The AβElectrophoresis was performed on 4–12% NuPAGE Bis-Tris polyacrylamide gels . After size separation within the gel, proteins were transferred to a polyvinylidenedifluoride (PVDF) membrane . Membranes were blocked with a solution containing 0.1% Tween 20 and 200 mM Tris buffered solution (TTBS) complemented with 5% non-fat dry milk during 30 min and incubated with mouse β amyloid 1–16  monoclonal antibody at 4 °C overnight under gentle agitation. Incubation with the secondary fluorescent-conjugated antibody was performed during 1 h at room temperature. After 3 washes with TTBS and one with PBS, the membrane was scanned using a Licor Aerius automated infrared imaging system according to manufacturer’s instructions.et al.After habituation to the vivarium conditions, 83 male C57BL/6J mice (3–4 months) underwent stereotaxic surgery under deep isoflurane anesthesia. As a model of ADThe Y-maze two-trial procedure is routinely used to examine spatial recognition memory and takes advantage of the innate tendency of rodents to explore novel environmentshttp://fmatoolbox.sourceforge.net/API/FMAToolbox/Analyses/FindRipples.html) only during periods classified as SWS. SWRs were identified by thresholding the NSS if its envelope exceeded 2 SD and peak exceeded 5 SD. The time points when the NSS crossed 2 SD were considered as onset and offset of a SWR. Episodes lasting longer than 100 ms were excluded from the analysis whereas episodes separated by less than 30 ms were merged. The occurrence rate was expressed as number of SWRs per sec of SWS (SWS-Rs/sec). Normalized power was calculated as maximum of NSS within a ripple. Time bins containing less than 5 min of a total duration of SWS were excluded from analysis of SWRs dynamics.Daily recordings were performed from 9 am to 4 pm in a closed opaque and dimly illuminated box which could host the animal’s home cage. The mouse head connector was linked to amplifiers by a soft cable allowing free motions of the animal. Behavior was tracked with a video camera. Electroencephalograms and EMG signals were amplified by a differential home-made AC amplifier, digitized at 32 kHz with 16-bit resolution using CED Power 1401 converter and Spike2 software (Cambridge Electronic Design), and stored on a PC for off-line analysis. To obtain local field potential (LFP) signals, raw signals were first processed by NDManager(1–42) oligomers, mice were deeply anesthetized with isoflurane 5% and right hippocampi were carefully harvested and homogenized in lysis buffer containing 20 mM HEPES, 0.15 mM NaCl, 1% triton ×100, 1% deoxycholic acid, 1% SDS, pH 7.5 and supplemented with a protease inhibitor cocktail . Protein amounts of hippocampal homogenates were determined by the Bradford’s protein assay and normalized to 500 μg of protein per sample. Hippocampal concentration of Aβ(1–42) peptide was evaluated by ELISA . This kit specifically detects soluble forms of human Aβ(1–42) peptides with negligible cross-reactivity to human Aβ(1–40) or mouse Aβ(1–42) forms. Aβ concentration in samples was determined by comparison to a standard curve (0–250 pg/ml). The absorbance at 450 nm was read using a microplate reader.Twenty-four hours (n = 4) and 15 days (n = 4) after the intracerebroventricular injection of AβResults were expressed as mean ± SEM. After checking normality of distributions with the Shapiro-Wilk test as well as homogeneity of variance using the Levene’s test, data analyses were performed using analyses of variance (ANOVAs) followed by post-hoc comparisons performed by t-test with Bonferroni correction where appropriate. For ANOVAs with repeated measures, we additionally tested sphericity by means of the Mauchly’s test. Values of p < 0.05 were considered as significant.How to cite this article: Nicole, O. et al. Soluble amyloid beta oligomers block the learning-induced increase in hippocampal sharp wave-ripple rate and impair spatial memory formation. Sci. Rep.6, 22728; doi: 10.1038/srep22728 (2016).


The most evident symptom of AD is a severe decline in cognition. Cognitive processes, as any other brain function, arise from the activity of specific cell assemblies of interconnected neurons that generate neural network dynamics based on their intrinsic and synaptic properties. Thus, the origin of Aβ-induced cognitive dysfunction, and possibly AD-related cognitive decline, must be found in specific alterations in properties of these cells and their consequences in neural network dynamics. The well-known relationship between AD and alterations in the activity of several neural networks is reflected in the slowing of the electroencephalographic (EEG) activity. Some features of the EEG slowing observed in AD, such as the diminished generation of different network oscillations, can be induced in vivo and in vitro upon Aβ application or by Aβ overproduction in transgenic models. This experimental approach offers the possibility to study the mechanisms involved in cognitive dysfunction produced by Aβ. This type of research may yield not only basic knowledge of neural network dysfunction associated with AD, but also novel options to treat this modern epidemic.Understanding the neural mechanisms underlying brain dysfunction induced by amyloid beta-protein (A Postmortem studies of brains from long-term AD patients have revealed the presence of senile plaques that contain the amyloid beta-peptide (Aβ) [β aggregates  is a progressive neurodegenerative disorder characterized by severe cognitive impairments , 2. Postide (Aβ) , 4. Mostews, see , 6). Sucews, see ). By looews, see , 2, 8–10ews, see ). One ofews, see , 13, whiews, see . Thus, lews, see  , a higher theta/delta ratio was found during the non-REM period of the sleep-wake cycle [swe and mutated presenilin 1 (A246E) show enhanced theta rhythm during wakefulness and REM sleep [swe and presenilin 1 (G384A) mutations showed an age-dependent decrease in theta hippocampal activity elicited by brainstem stimulation [β induces alterations in theta rhythm generation in rodents was reported by Sun and Alkon [β induces cognitive decline without affecting synaptic transmission or long-term potentiation. However, they observed that the hippocampus of Aβ-treated animals cannot generate carbachol-induced theta oscillations ex vivo [swe mice [As mentioned, theta rhythm oscillations have been closely related to different cognitive processes both in rodents  and humaneration , 34–36, neration –22. Morea rhythm , 56, 57.neration –50, 58. EM sleep , an obseEM sleep . In contmulation . To my knd Alkon , who fou ex vivo . Similar ex vivo . An idenswe mice .swe mice express a reduction in the generation of kainate-induced gamma rhythm ex vivo [in vivo [swe transgenic mice show no alterations in either the fast oscillations (ripples) or in the sharp waves where they are superimposed [β presence, a close correlation between reduced gamma activity and a functional behavioral deficit was recently detected in the olfactory network of the APPswe transgenic mouse [β reduces the power of beta-gamma bursts produced by the entorhinal cortex in vitro [As mentioned before, gamma rhythms have also been associated with several cognitive processes, and their disruption is associated with several neurological disorders, including AD . Beside ex vivo , other a[in vivo . Howeverrimposed ; indeed,rimposed . Interesic mouse . The samic mouse . Finallyin vitro .β exerts on them can be explained by the fact that such oscillations are not homogeneous; instead, they represent a broad variety of network functional configurations that rely on complex mixtures of intrinsic and synaptic properties [β have on the diverse oscillatory patterns, along with a thorough characterization of such relationships, would reveal key network properties affected by Aβ that would be potential therapeutic targets [The complex changes observed in different oscillatory activities in AD pathology as well as the complex effects that Aoperties , 55, 64. targets .β application [β production by transfecting the cultures with the human APP gene [β to the culture medium drastically reduced the synchronized neuronal calcium oscillations [in vivo to evaluate neural activity, either in the hippocampal CA1 region or in the cortex of the double transgenic mice expressing APPswe and mutated presenilin 1 (G384A) [β induced an increase in neuronal calcium transients that lasted for few seconds [β to hippocampal slices induced a reduction in the number of cells that exhibited calcium transients within a few minutes. The neurons that remained active in the presence of Aβ showed a frequency of calcium transients similar to that in control conditions [Besides electrophysiological means, neural network activity can also be analyzed through functional multi-neuron calcium imaging, which allows the evaluation of neural network dynamics with single-cell resolution , 65. Usilication . This eflication –70, showAPP gene  or by dillations , 68, 70. (G384A) , 31. The (G384A) , 31. Intnditions .β disrupts synchronized synaptic activity in the prefrontal cortex depending on the concentration of the peptide and the duration of application [β (1 nM) inhibits synchronized activity, whereas application of a higher concentration of Aβ (500 nM) induced a biphasic effect that consisted of an initial decrease in network activity followed by an overexcitation [β application can produce an acute and transient reduction in neural network activity. However, if Aβ exposure is maintained for several hours (24 h) the Aβ-induced inhibition of neural network activity is reversed, and the activity becomes indistinguishable from the control [β on neuronal network activity can be time and concentration dependent. It is possible that during prolonged Aβ exposure the peptide loses its ability to inhibit neural network activity through enzymatic degradation or sequestration into plaques. On the other hand, Aβ could lead to differential changes in neural network activity (even overexcitation) by forming aggregates with different sizes that produce differential effects on network activity [β by changing their properties to compensate for the inhibitory effects produced by Aβ. In fact, in some cases, deregulation of such compensatory changes could lead to the generation of aberrant hyperexcitable states, such as those observed in several AD transgenic mice. Patch clamp recordings have demonstrated that Alication . Applicacitation . An oppo control . All theactivity . Alternaswe and presenilin 1 with deleted exon 9 correlates with increased fast oscillatory activity in the thalamocortical network [Some reports that characterized the EEG activity throughout the sleep-wake transitions in certain strains of AD transgenic mice found no evidence for epileptiform activity , 49, 58; network . β may indeed reduce epileptiform activity. For example, it has been found that slices taken from APPswe transgenic mice have a reduced frequency of epileptiform synchronous events induced by 4-aminopyridine [in vivo and in vitro [β was shown to reduce epileptiform activity induced in vitro by chronic blockade of GABAergic inhibition [β on distinct neural network activities can be found in the diversity of epileptiform states that networks can evolve into or in the various compensatory changes induced by the presence of Aβ.In contrast to the evidence just reviewed, there is other evidence indicating that, instead of having a proepileptic effect, Apyridine , which iin vitro –79. Morehibition . Again, β-induced cognitive decline is the alteration of diverse neural network activity patterns. The experimental findings described here clearly indicate that the EEG slowing observed in AD patients can be reproduced both in vivo and in vitro in animal models of AD, which represent an excellent opportunity to study the cellular mechanisms involved in cognitive decline as a way to reveal therapeutic targets for AD. Of course, the evidence shows that the effects of Aβ on neural network activity are rather complex and depend on its concentration and conformation, as well as the duration of its application. However, such complexity, if well characterized, would provide evidence of specific cellular mechanisms affected by Aβ that would be essential for most, if not all, of the disturbances of neural network activity produced by this peptide. It is likely that several of the seemingly contradictory Aβ-dependent effects represent different elements of the same causal chain or, alternatively, that they represent independent branches of a more complex pathogenic process. Since Aβ produces a strong deleterious effect on neural networks, it is likely that several strategies would develop to compensate for the inhibition produced by Aβ and that, in some cases, the failure of such adaptive changes would lead some networks to more disruptive states (hyperexcitation). Of course, it would be essential to determine which of the diverse effects of Aβ on neural network activity account for the cognitive dysfunction observed both in animal models and in AD patients.The data summarized in this paper support the notion that a major component of Aβ-induced neural network dysfunction offers an important, alternative view for the understanding of AD pathology. This pathological process, which does not necessarily involve neurodegeneration in its early stages, would provide an experimental model to test pharmacological or nonpharmacological means to prevent such network disruption. For instance, it has been shown that reestablishing gamma oscillation by overexpression of the Nav1.1 channel reduces the aberrant epileptiform activity and the cognitive decline in the transgenic mouse expressing the APP with the Swedish and Indiana mutations [swe transgenic mouse, by passive Aβ immunization, correlates with a reduction in the circadian rhythm alterations observed in these mice [β on neural network activity and prevented Aβ-dependent cognitive deficits in transgenic AD mice that expresses the APP with the Swedish and Indiana mutations [β on the generation of beta-gamma activity in the entorhinal cortex. This and other observations support the use of lithium in the treatment of AD [β. Whether or not these studies will render therapeutic approaches to treat AD, remains to be determined.Finally, the study of Autations . Similarese mice . Moreoveese mice , 81. It utations . Finallyutations , abolishnt of AD . These a