Inspiratory flow shape clustering: an automated method to monitor upper airway performance during sleep

We describe an automated method for monitoring airflow dynamics in the upper airway of a sleeping subject. Its main task is to determine a set of inspiratory flow shape representatives and their relative incidence in a given respiratory airflow material. The flow shape clustering aims at reducing redundant information in the data, and thereby decreases the time needed to score overnight sleep recordings. Compared with previous computer-assisted systems, built on a pre-defined classification of prototype shapes, we require no a priori assumptions of the flow shape clusters to be discovered. The intrinsic flow shape clustering is performed with a modification of the Isodata algorithm, and the K-means clustering is used as a reference in comparison studies. The operation of the method is demonstrated on clinical sleep recordings both from patients with nocturnal breathing disorders and from non-symptomatic individuals. The feasible results obtained in the practical research design suggest that application of clustering algorithms to respiratory airflow measurements could give important insights into the subtle flow shape abnormalities underlying obstructive sleep-disordered breathing.     

Dithering design for measurement of slowly varying signals

The personal computer equipped with a data acquisition board is a powerful tool for research and for routine data collection. Interference and noise often corrupt the data acquisition. This noise can be used as a dither signal for improving the resolution of the A/D converter. This paper discusses possibilities to decrease the uncertainty of measurement in cases when the measurand moves slowly enough to allow for averaging several dithered results.     

Dendrimer intercalation in layered double hydroxides

New organic/inorganic (O/I) hybrid assemblies based on Layered Double Hydroxide (LDH) with polyamide amine dendrimer (PAMAM, generation −0.5 and generation +0.5) were prepared by two different routes using either the direct coprecipitation at constant pH or the anion exchange procedure in double surfactant S⁺S⁻ phases. The obtained materials were characterized by means of powder X-ray diffraction, thermal gravimetric analysis associated with mass spectrometry, and Fourier-transform infrared spectroscopy. X-ray powder diffraction pattern of the O/I LDH assembly exhibit characteristic profiles of LDH-based materials with basal spacing depending on the nature of the dendrimer. Indeed, for both synthetic procedures, interleaved PAMAM −0.5 gives rise to an interlayer space in agreement with a perpendicular molecular arrangement against the layer of the host structure. For PAMAM+0.5, considering its spherical dimension, a much smaller basal spacing was observed. This observation was interpreted as shrinkage of the molecule to accommodate the interlayer LDH gap, which was rendered possible by the bond angle twisting within PAMAM−0.5. FTIR spectra confirm the presence of both moieties inside both Zn₂Al/PAMAM G−0.5 and Zn₂Al/PAMAM G+0.5 assemblies. Finally, thermal analysis associated with mass spectrometry confirm this composition, and in situ temperature XRD data reveal that the highly constrained arrangement for the generation +0.5 is not accompanied by a gain in thermal structural stability; in fact, the assembly prepared from PAMAM −0.5 is more stable. Both O/I PAMAM LDH assemblies constitute well-defined materials which are candidate for catalytic applications.     

Identification of β-lactam antibiotics using bioluminescent Escherichia coli and a support vector machine classifier algorithm

We propose the use of bioluminescent whole cell biosensor combined with a pattern classification algorithm to automatically detect and identify β-lactam antibiotic substances. Escherichia coli cells with a plasmid harboring luxCDABE genes under the β-lactam sensitive promoter element are used as sensors. We present experimental measurements of light production of bioluminescent bacteria subject to 11 antibiotic substances. The patterns of measured light production are classified using a support vector machine classifier. The accuracy and reliability of the classification suggests that this method can be used in the future to probe for new antibiotic substances.     

Bone morphogenetic protein 15 and growth differentiation factor 9 co-operate to regulate granulosa cell function

The oocyte-secreted polypeptide growth factors, growth differentiation factor 9 (GDF9) and bone morphogenetic protein 15 (BMP15, also known as GDF9B) have both been shown to be essential for ovarian follicular growth and function. The effects of murine (m) and ovine (o) GDF9 as well as oBMP15, alone or together, on 3H-thymidine uptake and progesterone and inhibin production by granulosa cells from rats were determined. Murine GDF9 stimulated thymidine incorporation by granulosa cells whereas oGDF9 and oBMP15 alone had no effect. However, oBMP15 given together with mGDF9 or oGDF9 was very potent in stimulating 3H-thymidine incorporation by granulosa cells with a greater than 3-fold stimulation compared with any growth factor alone. The synergistic effect of oBMP15 and oGDF9 was almost completely blocked by antibodies generated against these growth factors when administered either alone or in combination. While neither GDF9 (murine or ovine) nor oBMP15 were able to modulate FSH-stimulated progesterone production on their own, FSH-stimulated progesterone production by granulosa cells was potently inhibited when BMP15 and GDF9 were administered together. Immunoreactive alpha-inhibin levels increased more than 15-fold from granulosa cells when BMP15 and GDF9 were given together whereas consistent stimulatory effects of either growth factor alone were not observed. The effects of GDF9 and BMP15, when added together, were different than those observed for the growth factors alone. Therefore, we hypothesize that within the ovary, these oocyte-secreted growth factors co-operate to regulate proliferation and gonadotropin-induced differentiation of granulosa cells in mammals.     

Bone morphogenetic protein 15 and growth differentiation factor 9 co-operate to regulate granulosa cell function in ruminants

The oocyte-secreted polypeptide growth factors, growth differentiation factor 9 (GDF9) and bone morphogenetic protein 15 (BMP15, also known as GDF9B) have both been shown to be essential for ovarian follicular development and ovulation rate. In addition, it is known from both in vivo and in vitro studies that these factors co-operate in some manner. To date, most studies examining the in vitro effects of these growth factors have used the rodent model. However, the evidence suggests that these growth factors have somewhat different roles between rodents and ruminants. Therefore, the objectives of these studies were to examine the effects of GDF9 and BMP15, alone and together, on the functions of ovine and bovine granulosa cells under in vitro conditions. Ovine (o)BMP15 given together with murine (m)GDF9 or oGDF9 was more potent in stimulating (3)H-thymidine incorporation by ovine granulosa cells compared with each growth factor alone. For bovine granulosa cells, there appeared to be little or no co-operativity between oBMP15 and oGDF9 as oBMP15 alone was as potent as any combination of the two growth factors in stimulating (3)H-thymidine uptake. The species of origin of GDF9 affected the progesterone response in ovine granulosa cells with mGDF9 stimulating and oGDF9 inhibiting progesterone production. Ovine BMP15 alone had no effect on progesterone production by ovine granulosa cells and these growth factors did not appear to co-operate. FSH-stimulated progesterone production by bovine granulosa cells was most potently inhibited when oBMP15 and murine or ovine GDF9 were administered together. As was observed for progesterone, the species of origin of GDF9 affected inhibin production by ovine granulosa cells where mGDF9 inhibited while oGDF9 stimulated production. Murine GDF9 also inhibited inhibin production from bovine granulosa cells. For both ovine and bovine granulosa cells, BMP15 alone had no effect on inhibin production and there did not appear to be any co-operation between GDF9 and BMP15. These results indicate that the effects of BMP15 and GDF9 varied with respect to the species of origin of the growth factor. Moreover, the effects of GDF9 and BMP15 together were often co-operative and not always the same as those observed for these growth factors alone.     

Grouping PCB Assembly Jobs with Feeders of Several Types

A variant of the classical job grouping problem (JGP) in printed circuit board (PCB) assembly is considered. Studies on JGPs have assumed a single feeder from which the components are retrieved and then placed on the PCB. Recent advances in technology have made it possible to use several different kinds (types) of feeders at the same time. In a JGP, the aim is to group the PCBs so that the cardinality of the grouping is minimal and each group can be processed without rearranging the contents of the feeder. In the job grouping problem with several feeder types (JGP-T) the goal is the same but instead of one linear feeder we have several feeders and each component is associated with a given feeder type which restricts its placement. We give a mathematical formulation for the JGP-T and show that it is hard to solve to optimality for problems of practical size. The connections of JGP-T to known problems are discussed. We also propose several efficient heuristics and compare their results against optimal solutions.     

Microbiology, chemistry and biofilm development in a pilot drinking water distribution system with copper and plastic pipes

We studied the changes in water quality and formation of biofilms occurring in a pilot-scale water distribution system with two generally used pipe materials: copper and plastic (polyethylene, PE). The formation of biofilms with time was analysed as the number of total bacteria, heterotrophic plate counts and the concentration of ATP in biofilms. At the end of the experiment (after 308 days), microbial community structure, viable biomass and gram-negative bacterial biomass were analysed via lipid biomarkers (phospholipid fatty acids and lipopolysaccharide 3-hydroxy fatty acids), and the numbers of virus-like particles and total bacteria were enumerated by SYBR Green I staining. The formation of biofilm was slower in copper pipes than in the PE pipes, but after 200 days there was no difference in microbial numbers between the pipe materials. Copper ion led to lower microbial numbers in water during the first 200 days, but thereafter there were no differences between the two pipe materials. The number of virus-like particles was lower in biofilms and in outlet water from the copper pipes than PE pipes. Pipe material influenced also the microbial and gram-negative bacterial community structure in biofilms and water.     

Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes.