A field study on characteristics and diversity of gene expression in the liver of dairy cows during the transition period

Metabolic and endocrine adaptations to support milk production during the transition period vary between individual cows. This variation between cows to adapt to lactation may have a genetic basis. The present field study was carried out to determine hepatic adaptations occurring from late pregnancy through early lactation by measuring mRNA abundance of candidate genes in dairy cows on-farm. Additionally, the objective was to observe the diversity in inter-individual variation for the candidate genes that may give indications where individual adaptations at a molecular level can be found. This study was carried out on-farm including 232 dairy cows (parity >3) from 64 farms in Switzerland. Blood and liver samples were collected on d 20+/-7 before parturition, on d 24+/-2, and on d 89+/-4 after parturition. Blood plasma was assayed for concentrations of glucose, nonesterified fatty acids, beta-hydroxybutyrate, cholesterol, triglycerides, urea, albumin, protein, insulin, insulin-like growth factor-1, leptin, 3,5,3'-triiodothyronine, and thyroxine. Liver samples were obtained at the same time points and were measured for mRNA abundance of 26 candidate genes encoding enzymes and nuclear receptors involved in gluconeogenesis, fatty acid beta-oxidation, fatty acid and triglyceride synthesis, ketogenesis, citric acid cycle, cholesterol synthesis, and the urea cycle. The cows in the present study experienced a marked metabolic load in early lactation, as presented by changes in plasma metabolites and hormones, and responded accordingly with upregulation and downregulation of almost all candidate genes involved in metabolic processes in the liver. The observed inter-individual variation for the candidate genes, which was highest for acetyl-CoA-carboxylase and glycerol-3-phosphate dehydrogenase 2, should be further investigated to unravel the regulation at molecular level for optimal adaptive performance in dairy cows.

Variation in hepatic regulation of metabolism during the dry period and in early lactation in dairy cows

The purpose of this study was to investigate variations in hepatic regulation of metabolism during the dry period, after parturition, and in early lactation in dairy cows. For this evaluation, cows were divided into 2 groups based on the plasma concentration of beta-hydroxybutyric acid (BHBA) in wk 4 postpartum (PP; group HB, BHBA >0.75 mmol/L; group LB, BHBA <0.75 mmol/L, respectively). Liver biopsies were obtained from 28 cows at drying off (mean 59 +/- 8 d antepartum), on d 1, and in wk 4 and 14 PP. Blood samples were collected every 2 wk during this entire period. Liver samples were analyzed for mRNA abundance of genes related to carbohydrate metabolism (pyruvate carboxylase, PC; phosphoenolpyruvate carboxykinase, PEPCK; citrate synthase, CS), fatty acid biosynthesis (ATP citrate lyase, ACLY) and oxidation (acyl-CoA synthetase long-chain, ACSL; carnitine palmitoyltransferase 1A, CPT 1A; carnitine palmitoyltransferase 2, CPT 2; acyl-coenzyme A dehydrogenase very long chain, ACADVL), cholesterol biosynthesis (3-hydroxy-3-methylglutaryl-coenzyme A synthase 1, HMGCS1), ketogenesis (3-hydroxy-3-methylglutaryl-coenzyme A synthase 2, HMGCS2), and of genes encoding the transcription factors peroxisome proliferator-activated receptor alpha (PPARalpha), peroxisome proliferator-activated receptor gamma (PPARgamma), and sterol regulatory element binding factor 1 (SREBF1). Blood plasma was assayed for concentrations of glucose, BHBA, nonesterified fatty acids, cholesterol, triglycerides, insulin, insulin-like growth factor-I, and thyroid hormones. In both groups, plasma parameters followed a pattern usually observed in dairy cows. However, changes were moderate and the energy balance in cows turned positive in wk 7 PP for both groups. Additionally, the energy balance and milk yield were similar for both groups after parturition onwards. Significant group effects were found at drying off, when plasma concentrations of triglycerides were higher in LB than in HB, and in wk 4 PP, when plasma concentrations of glucose and IGF-I were lower in HB than in LB. Similarly, moderate changes in mRNA expression of hepatic genes between the different time points were observed, although HB cows showed more adaptive performance than LB cows based on changes in mRNA expression of PEPCKc, PEPCKm, CS, CPT 1A, CPT 2, and PPARalpha. Part of the variation measured in this study was explained by parity. Significant Spearman rank correlation coefficients between the variables were not similar at each time point and were not similar between the groups at each time point, suggesting that metabolic regulation differs between cows. In conclusion, metabolic regulation in dairy cows is a dynamic system, and differs obviously between cows at different metabolic stages related to parturition.

Understanding diversity of hepatic metabolism and related adaptations in the early lactating dairy cow.

The onset of lactation in dairy cows represents a major metabolic challenge that involves large adaptations in glucose, fatty acid, and mineral metabolism to support lactation and to avoid metabolic dysfunction. The complex system of adaptation can differ considerably between cows, and may have a genetic base. In the present review, the variation in adaptive reactions in dairy cows is discussed. In these studies, the liver being a key metabolic regulator for understanding the variation in adaptive performance of the dairy cow was the main focus of research. Liver function was evaluated through gene expression measurements; to explain the associated phenotypic variability and to identify descriptors for metabolic robustness in dairy cows. Hence, the identified genes involved act as a connecting link between the genotype encoded on the DNA and the phenotypic expression of the target factors at a protein level. The integration of phenotypic data, including gene expression profiles, and genomic data will facilitate a better characterization of the complex interplay between these levels, and will improve the genetic understanding necessary to unravel a certain trait or multi-trait such as metabolic robustness in dairy cows.

Urinary metabolomics in Fxr-null mice reveals activated adaptive metabolic pathways upon bile acid challenge

Farnesoid X receptor (FXR) is a nuclear receptor that regulates genes involved in synthesis, metabolism, and transport of bile acids and thus plays a major role in maintaining bile acid homeostasis. In this study, metabolomic responses were investigated in urine of wild-type and Fxr-null mice fed cholic acid, an FXR ligand, using ultra-performance liquid chromatography (UPLC) coupled with electrospray time-of-flight mass spectrometry (TOFMS). Multivariate data analysis between wild-type and Fxr-null mice on a cholic acid diet revealed that the most increased ions were metabolites of p-cresol (4-methylphenol), corticosterone, and cholic acid in Fxr-null mice. The structural identities of the above metabolites were confirmed by chemical synthesis and by comparing retention time (RT) and/or tandem mass fragmentation patterns of the urinary metabolites with the authentic standards. Tauro-3alpha,6,7alpha,12alpha-tetrol (3alpha,6,7alpha,12alpha-tetrahydroxy-5beta-cholestan-26-oyltaurine), one of the most increased metabolites in Fxr-null mice on a CA diet, is a marker for efficient hydroxylation of toxic bile acids possibly through induction of Cyp3a11. A cholestatic model induced by lithocholic acid revealed that enhanced expression of Cyp3a11 is the major defense mechanism to detoxify cholestatic bile acids in Fxr-null mice. These results will be useful for identification of biomarkers for cholestasis and for determination of adaptive molecular mechanisms in cholestasis.

High-resolution electrophoretic simulations: performance characteristics of one-dimensional simulators

Three comprehensive one-dimensional simulators were used on the same PC to simulate the dynamics of different electrophoretic configurations, including two migrating hybrid boundaries, an isotachophoretic boundary and the zone electrophoretic separation of ten monovalent anions. Two simulators, SIMUL5 and GENTRANS, use a uniform grid, while SPRESSO uses a dynamic adaptive grid. The simulators differ in the way components are handled. SIMUL5 and SPRESSO feature one equation for all components, whereas GENTRANS is based on the use of separate modules for the different types of monovalent components, a module for multivalent components and a module for proteins. The code for multivalent components is executed more slowly compared to those for monovalent components. Furthermore, with SIMUL5, the computational time interval becomes smaller when it is operated with a reduced calculation space that features moving borders, whereas GENTRANS offers the possibility of using data smoothing (removal of negative concentrations), which can avoid numerical oscillations and speed up a simulation. SPRESSO with its adaptive grid could be employed to simulate the same configurations with smaller numbers of grid points and thus is faster in certain but not all cases. The data reveal that simulations featuring a large number of monovalent components distributed such that a high mesh is required throughout a large proportion of the column are fastest executed with GENTRANS.

A two-microphone noise reduction system for cochlear implant users with nearby microphones. Part II: Performance Evaluation

Users of cochlear implants (auditory aids, which stimulate the auditory nerve electrically at the inner ear) often suffer from poor speech understanding in noise. We evaluate a small (intermicrophone distance 7 mm) and computationally inexpensive adaptive noise reduction system suitable for behind-the-ear cochlear implant speech processors. The system is evaluated in simulated and real, anechoic and reverberant environments. Results from simulations show improvements of 3.4 to 9.3 dB in signal to noise ratio for rooms with realistic reverberation and more than 18 dB under anechoic conditions. Speech understanding in noise is measured in 6 adult cochlear implant users in a reverberant room, showing average improvements of 7.9–9.6 dB, when compared to a single omnidirectional microphone or 1.3–5.6 dB, when compared to a simple directional two-microphone device. Subjective evaluation in a cafeteria at lunchtime shows a preference of the cochlear implant users for the evaluated device in terms of speech understanding and sound quality.

Cardiac c-kit+AT2+ cell population is increased in response to ischemic injury and supports cardiomyocyte performance

The expression pattern of angiotensin AT2 receptors with predominance during fetal life and upregulation under pathological conditions during tissue injury/repair process suggests that AT2 receptors may exert an important action in injury/repair adaptive mechanisms. Less is known about AT2 receptors in acute ischemia-induced cardiac injury. We aimed here to elucidate the role of AT2 receptors after acute myocardial infarction. Double immunofluorescence staining showed that cardiac AT2 receptors were mainly detected in clusters of small c-kit+ cells accumulating in peri-infarct zone and c-kit+AT2+ cells increased in response to acute cardiac injury. Further, we isolated cardiac c-kit+AT2+ cell population by modified magnetic activated cell sorting and fluorescence activated cell sorting. These cardiac c-kit+AT2+ cells, represented approximately 0.19% of total cardiac cells in infarcted heart, were characterized by upregulated transcription factors implicated in cardiogenic differentiation (Gata-4, Notch-2, Nkx-2.5) and genes required for self-renewal (Tbx-3, c-Myc, Akt). When adult cardiomyocytes and cardiac c-kit+AT2+ cells isolated from infarcted rat hearts were cocultured, AT2 receptor stimulation in vitro inhibited apoptosis of these cocultured cardiomyocytes. Moreover, in vivo AT2 receptor stimulation led to an increased c-kit+AT2+ cell population in the infarcted myocardium and reduced apoptosis of cardiomyocytes in rats with acute myocardial infarction. These data suggest that cardiac c-kit+AT2+ cell population exists and increases after acute ischemic injury. AT2 receptor activation supports performance of cardiomyocytes, thus contributing to cardioprotection via cardiac c-kit+AT2+ cell population.

A reliable, traffic-adaptive and energy-efficient link layer for wireless sensor networks

The paper presents a link layer stack for wireless sensor networks, which consists of the Burst-aware Energy-efficient Adaptive Medium access control (BEAM) and the Hop-to-Hop Reliability (H2HR) protocol. BEAM can operate with short beacons to announce data transmissions or include data within the beacons. Duty cycles can be adapted by a traffic prediction mechanism indicating pending packets destined for a node and by estimating its wake-up times. H2HR takes advantage of information provided by BEAM such as neighbour information and transmission information to perform per-hop congestion control. We justify the design decisions by measurements in a real-world wireless sensor network testbed and compare the performance with other link layer protocols.

Traffic-Adaptive and Link-Quality-Aware Communication in Wireless Sensor Networks

This paper is a summary of the main contribu- tions of the PhD thesis published in [1]. The main research contributions of the thesis are driven by the research question how to design simple, yet efficient and robust run-time adaptive resource allocation schemes within the commu- nication stack of Wireless Sensor Network (WSN) nodes. The thesis addresses several problem domains with con- tributions on different layers of the WSN communication stack. The main contributions can be summarized as follows: First, a a novel run-time adaptive MAC protocol is intro- duced, which stepwise allocates the power-hungry radio interface in an on-demand manner when the encountered traffic load requires it. Second, the thesis outlines a metho- dology for robust, reliable and accurate software-based energy-estimation, which is calculated at network run- time on the sensor node itself. Third, the thesis evaluates several Forward Error Correction (FEC) strategies to adap- tively allocate the correctional power of Error Correcting Codes (ECCs) to cope with timely and spatially variable bit error rates. Fourth, in the context of TCP-based communi- cations in WSNs, the thesis evaluates distributed caching and local retransmission strategies to overcome the perfor- mance degrading effects of packet corruption and trans- mission failures when transmitting data over multiple hops. The performance of all developed protocols are eval- uated on a self-developed real-world WSN testbed and achieve superior performance over selected existing ap- proaches, especially where traffic load and channel condi- tions are suspect to rapid variations over time.

Coronary artery stents: influence of adaptive statistical iterative reconstruction on image quality using 64-HDCT

OBJECTIVE: The assessment of coronary stents with present-generation 64-detector row computed tomography (HDCT) scanners is limited by image noise and blooming artefacts. We evaluated the performance of adaptive statistical iterative reconstruction (ASIR) for noise reduction in coronary stent imaging with HDCT. METHODS AND RESULTS: In 50 stents of 28 patients (mean age 64 ± 10 years) undergoing coronary CT angiography (CCTA) on an HDCT scanner the mean in-stent luminal diameter, stent length, image quality, in-stent contrast attenuation, and image noise were assessed. Studies were reconstructed using filtered back projection (FBP) and ASIR-FBP composites. ASIR resulted in reduced image noise vs. FBP (P < 0.0001). Two readers graded the CCTA stent image quality on a 4-point Likert scale and determined the proportion of interpretable stent segments. The best image quality for all clinical images was obtained with 40 and 60% ASIR with significantly larger luminal area visualization compared with FBP (+42.1 ± 5.4% with 100% ASIR vs. FBP alone; P < 0.0001) while the stent length was decreased (-4.7 ± 0.9%,

Real-World Evaluation of Sensor Context-aware Adaptive Duty-cycled Opportunistic Routing

Energy is of primary concern in wireless sensor networks (WSNs). Low power transmission makes the wireless links unreliable, which leads to frequent topology changes. Resulting packet retransmissions aggravate the energy consumption. Beaconless routing approaches, such as opportunistic routing (OR) choose packet forwarders after data transmissions, and are promising to support dynamic features of WSNs. This paper proposes SCAD - Sensor Context-aware Adaptive Duty-cycled beaconless OR for WSNs. SCAD is a cross-layer routing solution and it brings the concept of beaconless OR into WSNs. SCAD selects packet forwarders based on multiple types of network contexts. To achieve a balance between performance and energy efficiency, SCAD adapts duty-cycles of sensors based on real-time traffic loads and energy drain rates. We implemented SCAD in TinyOS running on top of Tmote Sky sensor motes. Real-world evaluations show that SCAD outperforms other protocols in terms of both throughput and network lifetime.

Context-Aware Adaptive Opportunistic Routing in Mobile Ad-hoc and Sensor Networks

Mobile ad-hoc networks (MANETs) and wireless sensor networks (WSNs) have been attracting increasing attention for decades due to their broad civilian and military applications. Basically, a MANET or WSN is a network of nodes connected by wireless communication links. Due to the limited transmission range of the radio, many pairs of nodes in MANETs or WSNs may not be able to communicate directly, hence they need other intermediate nodes to forward packets for them. Routing in such types of networks is an important issue and it poses great challenges due to the dynamic nature of MANETs or WSNs. On the one hand, the open-air nature of wireless environments brings many difficulties when an efficient routing solution is required. The wireless channel is unreliable due to fading and interferences, which makes it impossible to maintain a quality path from a source node to a destination node. Additionally, node mobility aggravates network dynamics, which causes frequent topology changes and brings significant overheads for maintaining and recalculating paths. Furthermore, mobile devices and sensors are usually constrained by battery capacity, computing and communication resources, which impose limitations on the functionalities of routing protocols. On the other hand, the wireless medium possesses inherent unique characteristics, which can be exploited to enhance transmission reliability and routing performance. Opportunistic routing (OR) is one promising technique that takes advantage of the spatial diversity and broadcast nature of the wireless medium to improve packet forwarding reliability in multihop wireless communication. OR combats the unreliable wireless links by involving multiple neighboring nodes (forwarding candidates) to choose packet forwarders. In opportunistic routing, a source node does not require an end-to-end path to transmit packets. The packet forwarding decision is made hop-by-hop in a fully distributed fashion. Motivated by the deficiencies of existing opportunistic routing protocols in dynamic environments such as mobile ad-hoc networks or wireless sensor networks, this thesis proposes a novel context-aware adaptive opportunistic routing scheme. Our proposal selects packet forwarders by simultaneously exploiting multiple types of cross-layer context information of nodes and environments. Our approach significantly outperforms other routing protocols that rely solely on a single metric. The adaptivity feature of our proposal enables network nodes to adjust their behaviors at run-time according to network conditions. To accommodate the strict energy constraints in WSNs, this thesis integrates adaptive duty-cycling mechanism to opportunistic routing for wireless sensor nodes. Our approach dynamically adjusts the sleeping intervals of sensor nodes according to the monitored traffic load and the estimated energy consumption rate. Through the integration of duty cycling of sensor nodes and opportunistic routing, our protocol is able to provide a satisfactory balance between good routing performance and energy efficiency for WSNs.

Performance on auditory and visual temporal informationprocessing is related to psychometric intelligence

The present study investigated the relationship between psychometric intelligence and temporal resolution power (TRP) as simultaneously assessed by auditory and visual psychophysical timing tasks. In addition, three different theoretical models of the functional relationship between TRP and psychometric intelligence as assessed by means of the Adaptive Matrices Test (AMT) were developed. To test the validity of these models, structural equation modeling was applied. Empirical data supported a hierarchical model that assumed auditory and visual modality-specific temporal processing at a first level and amodal temporal processing at a second level. This second-order latent variable was substantially correlated with psychometric intelligence. Therefore, the relationship between psychometric intelligence and psychophysical timing performance can be explained best by a hierarchical model of temporal information processing.

An adaptive Newton-method based on a dynamical systems approach

The traditional Newton method for solving nonlinear operator equations in Banach spaces is discussed within the context of the continuous Newton method. This setting makes it possible to interpret the Newton method as a discrete dynamical system and thereby to cast it in the framework of an adaptive step size control procedure. In so doing, our goal is to reduce the chaotic behavior of the original method without losing its quadratic convergence property close to the roots. The performance of the modified scheme is illustrated with various examples from algebraic and differential equations.

Herbaceous plant species invading natural areas tend to have stronger adaptive root foraging than other naturalized species

Although plastic root-foraging responses are thought to be adaptive, as they may optimize nutrient capture of plants, this has rarely been tested. We investigated whether nutrient-foraging responses are adaptive, and whether they pre-adapt alien species to become natural-area invaders. We grew 12 pairs of congeneric species (i.e., 24 species) native to Europe in heterogeneous and homogeneous nutrient environments, and compared their foraging responses and performance. One species in each pair is a USA natural-area invader, and the other one is not. Within species, individuals with strong foraging responses, measured as plasticity in root diameter and specific root length, had a higher biomass. Among species, the ones with strong foraging responses, measured as plasticity in root length and root biomass, had a higher biomass. Our results therefore suggest that root foraging is an adaptive trait. Invasive species showed significantly stronger root-foraging responses than non-invasive species when measured as root diameter. Biomass accumulation was decreased in the heterogeneous vs. the homogeneous environment. In aboveground, but not belowground and total biomass, this decrease was smaller in invasive than in non-invasive species. Our results show that strong plastic root-foraging responses are adaptive, and suggest that it might aid in pre-adapting species to becoming natural-area invaders.