Capillary zone electrophoresis determination of carbohydrate-deficient transferrin using the new CEofix reagents under high-resolution conditions

Capillary zone electrophoresis (CZE) with a dynamic double coating based on the new CEofix reagents is shown to provide high-resolution separations of serum transferrin (Tf) isoforms, a prerequisite for the monitoring of unusual and complex Tf patterns, including those seen with genetic variants and disorders of glycosylation. A 50 microm I.D. fused-silica capillary of 60 cm total length, an applied voltage of 20 kV and a capillary temperature of 30 degrees C results in 15 min CZE runs of high assay precision and thus provides a robust approach for the determination of carbohydrate-deficient transferrin (CDT, sum of asialo-Tf and disialo-Tf in relation to total Tf) in human serum. Except for selected samples of patients with severe liver diseases and sera with high levels of paraproteins, interference-free Tf patterns are detected. Compared with the use of the previous CEofix reagents for CDT under the same instrumental conditions, the resolution between disialo-Tf and trisialo-Tf is significantly higher (1.7 versus 1.4). The CDT levels of reference and patient sera are comparable, suggesting that the new assay can be applied for screening and confirmation analyses. The high-resolution CZE assay represents an attractive alternative to HPLC and can be regarded as a candidate of a reference method for CDT.

Effects of potentised substances on growth kinetics of Saccharomyces cerevisiae and Schizosaccharomyces pombe

BACKGROUND: Homeopathic potencies are used as specific remedies in complementary medicine. Since the mode of action is unknown, the presumed specificity is discussed controversially. OBJECTIVE: This study investigated the effects of potentised substances on two yeast species, Saccharomyces cerevisiae and Schizosaccharomyces pombe, in a stable and reliable test system with systematic negative controls. MATERIALS AND METHODS: Yeast cells were cultivated in either potentised substances or water controls in microplates and their growth kinetics were measured photometrically. Water control runs were performed repeatedly to investigate the stability of the experimental set-up (systematic negative controls). RESULTS: 4 out of 14 screened substances seem to have affected the growth curve parameters slope or yield. Out of these substances, azoxystrobin and phosphorus were chosen for 8 further replication experiments, which partly confirmed the results of the screening. On the average of all experiments, azoxystrobin affected the slope of the growth curve of Saccharomyces cerevisiae (p < 0.05), and phosphorus affected the slope of the growth curve of Schizosaccharomyces pombe (p < 0.05). No effects were seen in the water control runs. In addition, significant interactions between treatment with potentised substances and experiment number were observed in all experiments with potentised substances (p < 0.01), but not in the water control runs. CONCLUSIONS: Both yeast species reacted to certain potentised substances by changing their growth kinetics. However, the interactions found point to additional factors of still unknown nature, that modulate the effects of potentised substances. This stable test system with yeasts may be suitable for further studies regarding the efficacy of homeopathic potencies.

Application and comparison of classification algorithms for recognition of Alzheimer's disease in electrical brain activity (EEG)

The early detection of subjects with probable Alzheimer's disease (AD) is crucial for effective appliance of treatment strategies. Here we explored the ability of a multitude of linear and non-linear classification algorithms to discriminate between the electroencephalograms (EEGs) of patients with varying degree of AD and their age-matched control subjects. Absolute and relative spectral power, distribution of spectral power, and measures of spatial synchronization were calculated from recordings of resting eyes-closed continuous EEGs of 45 healthy controls, 116 patients with mild AD and 81 patients with moderate AD, recruited in two different centers (Stockholm, New York). The applied classification algorithms were: principal component linear discriminant analysis (PC LDA), partial least squares LDA (PLS LDA), principal component logistic regression (PC LR), partial least squares logistic regression (PLS LR), bagging, random forest, support vector machines (SVM) and feed-forward neural network. Based on 10-fold cross-validation runs it could be demonstrated that even tough modern computer-intensive classification algorithms such as random forests, SVM and neural networks show a slight superiority, more classical classification algorithms performed nearly equally well. Using random forests classification a considerable sensitivity of up to 85% and a specificity of 78%, respectively for the test of even only mild AD patients has been reached, whereas for the comparison of moderate AD vs. controls, using SVM and neural networks, values of 89% and 88% for sensitivity and specificity were achieved. Such a remarkable performance proves the value of these classification algorithms for clinical diagnostics.

Application of headspace solid phase microextraction to qualitative and quantitative analysis of tobacco additives in cigarettes

Cigarettes may contain up to 10% by weight additives which are intended to make them more attractive. A fast and rugged method for a cigarette-screening for additives with medium volatility was developed using automatic headspace solid phase microextraction (HS-SPME) with a 65 microm carbowax-divinylbenzene fiber and gas chromatography-mass spectrometry (GC-MS) with standard electron impact ionisation. In three runs, each cigarette sample was extracted in closed headspace vials using basic, acidic and neutral medium containing 0.5 g NaCl or Na2SO4. Furthermore, the method was optimized for quantitative determination of 17 frequently occurring additives. The practical applicability of the method was demonstrated for cigarettes from 32 brands.

Floral scents affect the distribution of hive bees around dancers

Floral scents are important information cues used to organize foraging-related tasks in honeybees. The waggle dance, apart from encoding spatial information about food sources, might facilitate the transfer of olfactory information by increasing the dissipation of volatiles brought back by successful foragers. By assuming that food scents are more intensive on specific body parts of returning foragers, i.e., the posterior legs of pollen foragers and mouthparts of nectar foragers, we quantified the interactions between hive mates and foragers during dances advertising different types of food sources. For natural sources, a higher proportion of hive mates contacted the hind legs of pollen dancers (where the pollen loads were located) with their heads compared to non-pollen dancers. On the other hand, the proportion of head-to-head contacts was higher for non-pollen foragers during the waggle runs. When the food scent was manipulated, dancers collecting scented sugar solution had a higher proportion of head-to-head contacts and a lower proportion around their hind legs compared to dancers collecting unscented solution. The presence of food odors did not affect in-hive behaviors of dancers, but it increased the number of trophallaxes in-between waggle runs (i.e., during circle phases). These results suggest that the honeybee dance facilitates the olfactory information transfer between incoming foragers and hive mates, and we propose that excitatory displays in other social insect species serve the same purpose. While recent empirical and theoretical findings suggested that the colony level foraging benefits of the spatial information encoded in the waggle dance vary seasonally and with habitats, the role of the dance as a compound signal not only indicating the presence of a profitable resource but also amplifying the information transfer regarding floral odors may be important under any ecological circumstances.

Better Memory and Neural Efficiency in Young Apolipoprotein E 4 Carriers

The apolipoprotein E (APOE) epsilon4 allele is the major genetic risk factor for Alzheimer's disease, but an APOE effect on memory performance and memory-related neurophysiology in young, healthy subjects is unknown. We found an association of APOE epsilon4 with better episodic memory compared with APOE epsilon2 and epsilon3 in 340 young, healthy persons. Neuroimaging was performed in a subset of 34 memory-matched individuals to study genetic effects on memory-related brain activity independently of differential performance. E4 carriers decreased brain activity over 3 learning runs, whereas epsilon2 and epsilon3 carriers increased activity. This smaller neural investment of epsilon4 carriers into learning reappeared during retrieval: epsilon4 carriers exhibited reduced retrieval-related activity with equal retrieval performance. APOE isoforms had no differential effects on cognitive measures other than memory, brain volumes, and brain activity related to working memory. We suggest that APOE epsilon4 is associated with good episodic memory and an economic use of memory-related neural resources in young, healthy humans.

Analysis and performance of a UPC implementation of a parallel longest common subsequence algorithm

An important problem in computational biology is finding the longest common subsequence (LCS) of two nucleotide sequences. This paper examines the correctness and performance of a recently proposed parallel LCS algorithm that uses successor tables and pruning rules to construct a list of sets from which an LCS can be easily reconstructed. Counterexamples are given for two pruning rules that were given with the original algorithm. Because of these errors, performance measurements originally reported cannot be validated. The work presented here shows that speedup can be reliably achieved by an implementation in Unified Parallel C that runs on an Infiniband cluster. This performance is partly facilitated by exploiting the software cache of the MuPC runtime system. In addition, this implementation achieved speedup without bulk memory copy operations and the associated programming complexity of message passing.

MODULARITY BASED FUZZY COMMUNITY DETECTION IN SOCIAL NETWORKS

Fuzzy community detection is to identify fuzzy communities in a network, which are groups of vertices in the network such that the membership of a vertex in one community is in [0,1] and that the sum of memberships of vertices in all communities equals to 1. Fuzzy communities are pervasive in social networks, but only a few works have been done for fuzzy community detection. Recently, a one-step forward extension of Newman’s Modularity, the most popular quality function for disjoint community detection, results into the Generalized Modularity (GM) that demonstrates good performance in finding well-known fuzzy communities. Thus, GMis chosen as the quality function in our research. We first propose a generalized fuzzy t-norm modularity to investigate the effect of different fuzzy intersection operators on fuzzy community detection, since the introduction of a fuzzy intersection operation is made feasible by GM. The experimental results show that the Yager operator with a proper parameter value performs better than the product operator in revealing community structure. Then, we focus on how to find optimal fuzzy communities in a network by directly maximizing GM, which we call it Fuzzy Modularity Maximization (FMM) problem. The effort on FMM problem results into the major contribution of this thesis, an efficient and effective GM-based fuzzy community detection method that could automatically discover a fuzzy partition of a network when it is appropriate, which is much better than fuzzy partitions found by existing fuzzy community detection methods, and a crisp partition of a network when appropriate, which is competitive with partitions resulted from the best disjoint community detections up to now. We address FMM problem by iteratively solving a sub-problem called One-Step Modularity Maximization (OSMM). We present two approaches for solving this iterative procedure: a tree-based global optimizer called Find Best Leaf Node (FBLN) and a heuristic-based local optimizer. The OSMM problem is based on a simplified quadratic knapsack problem that can be solved in linear time; thus, a solution of OSMM can be found in linear time. Since the OSMM algorithm is called within FBLN recursively and the structure of the search tree is non-deterministic, we can see that the FMM/FBLN algorithm runs in a time complexity of at least O (n2). So, we also propose several highly efficient and very effective heuristic algorithms namely FMM/H algorithms. We compared our proposed FMM/H algorithms with two state-of-the-art community detection methods, modified MULTICUT Spectral Fuzzy c-Means (MSFCM) and Genetic Algorithm with a Local Search strategy (GALS), on 10 real-world data sets. The experimental results suggest that the H2 variant of FMM/H is the best performing version. The H2 algorithm is very competitive with GALS in producing maximum modularity partitions and performs much better than MSFCM. On all the 10 data sets, H2 is also 2-3 orders of magnitude faster than GALS. Furthermore, by adopting a simply modified version of the H2 algorithm as a mutation operator, we designed a genetic algorithm for fuzzy community detection, namely GAFCD, where elite selection and early termination are applied. The crossover operator is designed to make GAFCD converge fast and to enhance GAFCD’s ability of jumping out of local minimums. Experimental results on all the data sets show that GAFCD uncovers better community structure than GALS.

Evaluation of reproducibility of protein identification results after multidimensional human serum protein separation

We developed a gel- and label-free proteomics platform for comparative studies of human serum. The method involves the depletion of the six most abundant proteins, protein fractionation by Off-Gel IEF and RP-HPLC, followed by tryptic digestion, LC-MS/MS, protein identification, and relative quantification using probabilistic peptide match score summation (PMSS). We evaluated performance and reproducibility of the complete platform and the individual dimensions, by using chromatograms of the RP-HPLC runs, PMSS based abundance scores and abundance distributions as objective endpoints. We were interested if a relationship exists between the quantity ratio and the PMSS score ratio. The complete analysis was performed four times with two sets of serum samples containing different concentrations of spiked bovine beta-lactoglobulin (0.1 and 0.3%, w/w). The two concentrations resulted in significantly differing PMSS scores when compared to the variability in PMSS scores of all other protein identifications. We identified 196 proteins, of which 116 were identified four times in corresponding fractions whereof 73 qualified for relative quantification. Finally, we characterized the PMSS based protein abundance distributions with respect to the two dimensions of fractionation and discussed some interesting patterns representing discrete isoforms. We conclude that combination of Off-Gel electrophoresis (OGE) and HPLC is a reproducible protein fractionation technique, that PMSS is applicable for relative quantification, that the number of quantifiable proteins is always smaller than the number of identified proteins and that reproducibility of protein identifications should supplement probabilistic acceptance criteria.

Electrolysis of Molten Mixtures of Galena and Lead Chloride.

Electrolysis of molten mixtures of lead chloride and galena was carried out under various conditions of temperature, time, composition, and current densities; without a diaphram, and with various diaphrams. Continuous runs, with necessary additions of lead sulfide and lead chloride to maintain a melt of the proper composition, were attempted on a small scale.

Geology and Ore Deposits of the Clinton Mining District

This report includes the results of geological investigation of the Clinton Mining District and the Hidden Treasure Mine.The Clinton Mining District is an unorganized mining dis­trict situated in the Garnet Range two and one-half miles northeast of the town of Clinton, Montana, which is on the Northern Pacific Railway and the Chicago, Milwaukee, St. Paul, and Pacific Railroad seventeen miles east of the city of Missoula. The district is in the same range of mountains as the Gar­net Mining District and the drainage from the district covered is to the south into the Hell Gate or Clarks Fork of the Colum­bia River. The main stream is known as Trail creek, which runs in a southerly direction from the area studied.

Assessments and Computational Simulations in Support of a Time-Varying Mass Flow Rate Measurement Technique for Pulsatile Gas Flow

This thesis covers the correction, and verification, development, and implementation of a computational fluid dynamics (CFD) model for an orifice plate meter. Past results were corrected and further expanded on with compressibility effects of acoustic waves being taken into account. One dynamic pressure difference transducer measures the time-varying differential pressure across the orifice meter. A dynamic absolute pressure measurement is also taken at the inlet of the orifice meter, along with a suitable temperature measurement of the mean flow gas. Together these three measurements allow for an incompressible CFD simulation (using a well-tested and robust model) for the cross-section independent time-varying mass flow rate through the orifice meter. The mean value of this incompressible mass flow rate is then corrected to match the mean of the measured flow rate( obtained from a Coriolis meter located up stream of the orifice meter). Even with the mean and compressibility corrections, significant differences in the measured mass flow rates at two orifice meters in a common flow stream were observed. This means that the compressibility effects associated with pulsatile gas flows is significant in the measurement of the time-varying mass flow rate. Future work (with the approach and initial runs covered here) will provide an indirect verification of the reported mass flow rate measurements.

Revegetation and Bird Trends, Silver Bow Creek Superfund Remediation and Restoration

Silver Bow Creek runs approximately 25 miles from Butte to Warm Springs, where it joins Warm Springs Creek to form the Clark Fork River. This historic creek was terribly contaminated with mine wastes around the turn of the 20th century, leaving many "slickens" that persisted into the 21st century, when it became a Superfund remediation project. More than 5.5 million cubic yards of stream-deposited mine waste have been removed and 1,650 acres revegetated. Chief contaminants are copper, zinc, and arsenic, but acidic soils are often equally or more limiting to plants. The stream was relocated, and mine wastes were replaced with biologically inert cover soil. Richard A. Prodgers is currently a plant ecologist with Bighorn Environmental Sciences in Dillon, Montana.

[The comatose child]

The child who presents with acute coma runs a high risk of cardiopulmonary insufficiency, direct brain injury or even cerebral herniation. The case-management of such child requires a coma-specific emergent evaluation, immediate treatment of any hypoxicischemic insults and of the underlying cause. The coma-specific examination includes performance of child-adapted Glasgow Coma Score, the evaluation of brain stem functions such as pupillary response to light, cough- and gag reflex, and determination of all vital signs including body temperature. Treatment of hypoxicischemic insults includes control of airways and ventilation in patient with coma defined as GCS <8; liberal treatment of impaired cardiovascular states with isotonic fluids such as 0.9% sodium chloride; and treatment of cerebral herniation with head elevation, mannitol, hypertonic sodium chlorid fluids, steroids and hyperventilation. Immediately treatable causes are hypoglycemia, meningitis/encephalitis, opioid overdose and status epilepticus. Exclusion of rapidly progressive intracranial lesions almost always requires referral to the tertiary centre with head CT-scan facilities. Finally, an extensive etiology search of the stable coma is performed by looking for disease or trauma of the brain, for metabolic causes, for intoxications and for cardiopulmonary problems.

High-resolution paleoclimatology of the last millennium: a review of current status and future prospects

This review of late-Holocene palaeoclimatology represents the results from a PAGES/CLIVAR Intersection Panel meeting that took place in June 2006. The review is in three parts: the principal high-resolution proxy disciplines (trees, corals, ice cores and documentary evidence), emphasizing current issues in their use for climate reconstruction; the various approaches that have been adopted to combine multiple climate proxy records to provide estimates of past annual-to-decadal timescale Northern Hemisphere surface temperatures and other climate variables, such as large-scale circulation indices; and the forcing histories used in climate model simulations of the past millennium. We discuss the need to develop a framework through which current and new approaches to interpreting these proxy data may be rigorously assessed using pseudo-proxies derived from climate model runs, where the `answer' is known. The article concludes with a list of recommendations. First, more raw proxy data are required from the diverse disciplines and from more locations, as well as replication, for all proxy sources, of the basic raw measurements to improve absolute dating, and to better distinguish the proxy climate signal from noise. Second, more effort is required to improve the understanding of what individual proxies respond to, supported by more site measurements and process studies. These activities should also be mindful of the correlation structure of instrumental data, indicating which adjacent proxy records ought to be in agreement and which not. Third, large-scale climate reconstructions should be attempted using a wide variety of techniques, emphasizing those for which quantified errors can be estimated at specified timescales. Fourth, a greater use of climate model simulations is needed to guide the choice of reconstruction techniques (the pseudo-proxy concept) and possibly help determine where, given limited resources, future sampling should be concentrated.