Multi-sensors data acquisition and information fusion for manned submersible vehicle

本文介绍了一种用于载人潜水器的导航传感器的数据采集及信息融合技术。航行控制计算机通过基于工业以太网的数据通信系统对各传感器进行数据采集,采用卡尔曼滤波器完成对各传感器数据信息的融合,以便提高数据的精度和控制系统的性能,并将结果送给监控计算机,用于载人潜水器的姿态显示。

Purification and characterization of recombinant truncated human interleukin-11 expressed as fusion protein in Escherichia coli

Mature human interleukin-11 (HuIL-11) is a cytokine consisting of 178 amino acid residues that results from scission of the N-terminal signal peptide, consisting of 21 amino acid residaues, from the corresponding nascent polypeptide. A DNA fragment encoding a truncated HuIL-11 (trHuIL-11), with an additional 5 amino acid residues removed from the N-terminus, was cloned into vector pGEX-2T between the BamHI site and the EcoRI site. Upon transformation with Escherichia coli BL21, the construct over-produced a glutathione S-transferase (GST)-fused protein in a soluble form after IPTG induction. The fusion protein was initially fractionated with butyl-Sepharose 4 fast flow column and by affinity chromatography using a GSH-Sepharose 4B column. On-site enzymatic release with thrombin gave the target protein at 96% purity as judged by SDS-PAGE and HPLC. Expression of the interleukin as a GST-fused protein thus greatly improved downstream processing. Subsequent biological activity assay suggested that trHuIL-11 had similar activity profile to the naturally produced sample and may be a promising candidate for further development as biopharmaceutical.

Heat capacity and enthalpy of fusion of fenoxycarb

Fenoxycarb was synthesized and its heat capacities were precisely measured with an automated adiabatic calorimeter over the temperature range from 79 to 360 K. The sample was observed to melt at (326.31 +/- 0.14) K. The molar enthalpy and entropy of fusion as well as the chemical purity of the compound were determined to be (26.98 +/- 0.04) kJ-mol(-1), (82.69 +/- 0.09) J-K-1-mol(-1) and 99.53% +/- 0.01%, respectively. The thermodynamic functions relative to the reference temperature (298.15 K) were calculated based on the heat capacity measurements in the temperature range between 80 and 360 K. The extrapolated melting temperature for the absolutely pure compound obtained from fractional melting experiments was (326.62 +/- 0.06) K. Further research on the melting process of this compound was carried out by means of differential scanning calorimetry technique. The result was in agreement with that obtained from the measurements of heat capacities.

Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. Information fusion methods help resolve inconsistencies in order to distinguish correct from incorrect answers, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods developed here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an objects class is car, vehicle, or man-made. Underlying relationships among objects are assumed to be unknown to the automated system of the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchial knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples.

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.

Fusion Artmap: A Neural Network Architecture for Multi-Channel Data Fusion and Classification

Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Single-channel Fusion ARTMAP is functionally equivalent to Fuzzy ART during unsupervised learning and to Fuzzy ARTMAP during supervised learning. The network has a symmetric organization such that each channel can be dynamically configured to serve as either a data input or a teaching input to the system. An ART module forms a compressed recognition code within each channel. These codes, in turn, become inputs to a single ART system that organizes the global recognition code. When a predictive error occurs, a process called paraellel match tracking simultaneously raises vigilances in multiple ART modules until reset is triggered in one of them. Parallel match tracking hereby resets only that portion of the recognition code with the poorest match, or minimum predictive confidence. This internally controlled selective reset process is a type of credit assignment that creates a parsimoniously connected learned network. Fusion ARTMAP's multi-channel coding is illustrated by simulations of the Quadruped Mammal database.

Fusion ARTMAP: An Adaptive Fuzzy Network for Multi-Channel Classification

Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Fusion ARTMAP generalizes the fuzzy ARTMAP architecture in order to adaptively classify multi-channel data. The network has a symmetric organization such that each channel can be dynamically configured to serve as either a data input or a teaching input to the system. An ART module forms a compressed recognition code within each channel. These codes, in turn, beco1ne inputs to a single ART system that organizes the global recognition code. When a predictive error occurs, a process called parallel match tracking simultaneously raises vigilances in multiple ART modules until reset is triggered in one of thmn. Parallel match tracking hereby resets only that portion of the recognition code with the poorest match, or minimum predictive confidence. This internally controlled selective reset process is a type of credit assignment that creates a parsimoniously connected learned network.

Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis.

As more diagnostic testing options become available to physicians, it becomes more difficult to combine various types of medical information together in order to optimize the overall diagnosis. To improve diagnostic performance, here we introduce an approach to optimize a decision-fusion technique to combine heterogeneous information, such as from different modalities, feature categories, or institutions. For classifier comparison we used two performance metrics: The receiving operator characteristic (ROC) area under the curve [area under the ROC curve (AUC)] and the normalized partial area under the curve (pAUC). This study used four classifiers: Linear discriminant analysis (LDA), artificial neural network (ANN), and two variants of our decision-fusion technique, AUC-optimized (DF-A) and pAUC-optimized (DF-P) decision fusion. We applied each of these classifiers with 100-fold cross-validation to two heterogeneous breast cancer data sets: One of mass lesion features and a much more challenging one of microcalcification lesion features. For the calcification data set, DF-A outperformed the other classifiers in terms of AUC (p < 0.02) and achieved AUC=0.85 +/- 0.01. The DF-P surpassed the other classifiers in terms of pAUC (p < 0.01) and reached pAUC=0.38 +/- 0.02. For the mass data set, DF-A outperformed both the ANN and the LDA (p < 0.04) and achieved AUC=0.94 +/- 0.01. Although for this data set there were no statistically significant differences among the classifiers' pAUC values (pAUC=0.57 +/- 0.07 to 0.67 +/- 0.05, p > 0.10), the DF-P did significantly improve specificity versus the LDA at both 98% and 100% sensitivity (p < 0.04). In conclusion, decision fusion directly optimized clinically significant performance measures, such as AUC and pAUC, and sometimes outperformed two well-known machine-learning techniques when applied to two different breast cancer data sets.

Utility of telomerase-pot1 fusion protein in vascular tissue engineering.

While advances in regenerative medicine and vascular tissue engineering have been substantial in recent years, important stumbling blocks remain. In particular, the limited life span of differentiated cells that are harvested from elderly human donors is an important limitation in many areas of regenerative medicine. Recently, a mutant of the human telomerase reverse transcriptase enzyme (TERT) was described, which is highly processive and elongates telomeres more rapidly than conventional telomerase. This mutant, called pot1-TERT, is a chimeric fusion between the DNA binding protein pot1 and TERT. Because pot1-TERT is highly processive, it is possible that transient delivery of this transgene to cells that are utilized in regenerative medicine applications may elongate telomeres and extend cellular life span while avoiding risks that are associated with retroviral or lentiviral vectors. In the present study, adenoviral delivery of pot1-TERT resulted in transient reconstitution of telomerase activity in human smooth muscle cells, as demonstrated by telomeric repeat amplification protocol (TRAP). In addition, human engineered vessels that were cultured using pot1-TERT-expressing cells had greater collagen content and somewhat better performance in vivo than control grafts. Hence, transient delivery of pot1-TERT to elderly human cells may be useful for increasing cellular life span and improving the functional characteristics of resultant tissue-engineered constructs.

An immunoglobulin C kappa-reactive single chain antibody fusion protein induces tolerance through receptor editing in a normal polyclonal immune system.

Understanding immune tolerance mechanisms is a major goal of immunology research, but mechanistic studies have generally required the use of mouse models carrying untargeted or targeted antigen receptor transgenes, which distort lymphocyte development and therefore preclude analysis of a truly normal immune system. Here we demonstrate an advance in in vivo analysis of immune tolerance that overcomes these shortcomings. We show that custom superantigens generated by single chain antibody technology permit the study of tolerance in a normal, polyclonal immune system. In the present study we generated a membrane-tethered anti-Igkappa-reactive single chain antibody chimeric gene and expressed it as a transgene in mice. B cell tolerance was directly characterized in the transgenic mice and in radiation bone marrow chimeras in which ligand-bearing mice served as recipients of nontransgenic cells. We find that the ubiquitously expressed, Igkappa-reactive ligand induces efficient B cell tolerance primarily or exclusively by receptor editing. We also demonstrate the unique advantages of our model in the genetic and cellular analysis of immune tolerance.

Mitochondrial fusion is regulated by Reaper to modulate Drosophila programmed cell death.

In most multicellular organisms, the decision to undergo programmed cell death in response to cellular damage or developmental cues is typically transmitted through mitochondria. It has been suggested that an exception is the apoptotic pathway of Drosophila melanogaster, in which the role of mitochondria remains unclear. Although IAP antagonists in Drosophila such as Reaper, Hid and Grim may induce cell death without mitochondrial membrane permeabilization, it is surprising that all three localize to mitochondria. Moreover, induction of Reaper and Hid appears to result in mitochondrial fragmentation during Drosophila cell death. Most importantly, disruption of mitochondrial fission can inhibit Reaper and Hid-induced cell death, suggesting that alterations in mitochondrial dynamics can modulate cell death in fly cells. We report here that Drosophila Reaper can induce mitochondrial fragmentation by binding to and inhibiting the pro-fusion protein MFN2 and its Drosophila counterpart dMFN/Marf. Our in vitro and in vivo analyses reveal that dMFN overexpression can inhibit cell death induced by Reaper or γ-irradiation. In addition, knockdown of dMFN causes a striking loss of adult wing tissue and significant apoptosis in the developing wing discs. Our findings are consistent with a growing body of work describing a role for mitochondrial fission and fusion machinery in the decision of cells to die.

Outer Membrane Vesicle Production in Escherichia coli Relieves Envelope Stress and is Modulated by Changes in Peptidoglycan

Bacterial outer membrane vesicles (OMVs) are spherical buds of the outer membrane (OM) containing periplasmic lumenal components. OMVs have been demonstrated to play a critical part in the transmission of virulence factors, immunologically active compounds, and bacterial survival, however vesiculation also appears to be a ubiquitous physiological process for Gram-negative bacteria. Despite their characterized biological roles, especially for pathogens, very little is known about their importance for the originating organism as well as regulation and mechanism of production. Only when we have established their biogenesis can we fully uncover their roles in pathogenesis and bacterial physiology. The overall goal of this research was to characterize bacterial mutants which display altered vesiculation phenotypes using genetic and biochemical techniques, and thereby begin to elucidate the mechanism of vesicle production and regulation. One part of this work elucidated a synthetic genetic growth defect for a strain with reduced OMV production (ΔnlpA, inner membrane lipoprotein with a minor role in methionine transport) and envelope stress (ΔdegP, dual function periplasmic chaperone/ protease responsible for managing proteinaceous waste). This research showed that the growth defect of ΔnlpAΔdegP correlated with reduced OMV production with respect to the hyprevesiculator ΔdegP and the accumulation of protein in the periplasm and DegP substrates in the lumen of OMVs. We further demonstrated that OMVs do not solely act as a stress response pathway to rid the periplasm of otherwise damaging misfolded protein but also of accumulated peptidoglycan (PG) fragments and lipopolysaccharide (LPS), elucidating OMVs as a general stress response pathway critical for bacterial well-being. The second part of this work, focused on the role of PG structure, turnover and covalent crosslinks to the OM in vesiculation. We established a direct link between PG degradation and vesiculation: Mutations in the OM lipoprotein nlpI had been previously established as a very strong hypervesiculation phenotype. In the literature NlpI had been associated with another OM lipoprotein, Spr that was recently identified as a PG hydrolase. The data presented here suggest that NlpI acts as a negative regulator of Spr and that the ΔnlpI hypervesiculation phenotype is a result of rampantly degraded PG by Spr. Additionally, we found that changes in PG structure and turnover correlate with altered vesiculation levels, as well as non-canonical D-amino acids, which are secreted by numerous bacteria on the onset of stationary phase, being a natural factor to increase OMV production. Furthermore, we discovered an inverse relationship between the concentration of Lpp-mediated, covalent crosslinks and the level of OMV production under conditions of modulated PG metabolism and structure. In contrast, situations that lead to periplasmic accumulation (protein, PG fragments, and LPS) and consequent hypervesiculation the overall OM-PG crosslink concentration appears to be unchanged. Form this work, we conclude that multiple pathways lead to OMV production: Lpp concentration-dependent and bulk driven, Lpp concentration-independent.

NlpI-mediated modulation of outer membrane vesicle production through peptidoglycan dynamics in Escherichia coli.

Outer membrane vesicles (OMVs) are ubiquitously secreted from the outer membrane (OM) of Gram-negative bacteria. These heterogeneous structures are composed of OM filled with periplasmic content from the site of budding. By analyzing mutants that have vesicle production phenotypes, we can gain insight into the mechanism of OMV budding in wild-type cells, which has thus far remained elusive. In this study, we present data demonstrating that the hypervesiculation phenotype of the nlpI deletion mutant of Escherichia coli correlates with changes in peptidoglycan (PG) dynamics. Our data indicate that in stationary phase cultures the nlpI mutant exhibits increased PG synthesis that is dependent on spr, consistent with a model in which NlpI controls the activity of the PG endopeptidase Spr. In log phase, the nlpI mutation was suppressed by a dacB mutation, suggesting that NlpI regulates penicillin-binding protein 4 (PBP4) during exponential growth. The data support a model in which NlpI negatively regulates PBP4 activity during log phase, and Spr activity during stationary phase, and that in the absence of NlpI, the cell survives by increasing PG synthesis. Further, the nlpI mutant exhibited a significant decrease in covalent outer membrane (OM-PG) envelope stabilizing cross-links, consistent with its high level of OMV production. Based on these results, we propose that one mechanism wild-type Gram-negative bacteria can use to modulate vesiculation is by altering PG-OM cross-linking via localized modulation of PG degradation and synthesis.

Modulation of bacterial outer membrane vesicle production by envelope structure and content.

BACKGROUND: Vesiculation is a ubiquitous secretion process of Gram-negative bacteria, where outer membrane vesicles (OMVs) are small spherical particles on the order of 50 to 250 nm composed of outer membrane (OM) and lumenal periplasmic content. Vesicle functions have been elucidated in some detail, showing their importance in virulence factor secretion, bacterial survival, and biofilm formation in pathogenesis. Furthermore, OMVs serve as an envelope stress response, protecting the secreting bacteria from internal protein misfolding stress, as well as external envelope stressors. Despite their important functional roles very little is known about the regulation and mechanism of vesicle production. Based on the envelope architecture and prior characterization of the hypervesiculation phenotypes for mutants lacking the lipoprotein, Lpp, which is involved in the covalent OM-peptidoglycan (PG) crosslinks, it is expected that an inverse relationship exists between OMV production and PG-crosslinked Lpp. RESULTS: In this study, we found that subtle modifications of PG remodeling and crosslinking modulate OMV production, inversely correlating with bound Lpp levels. However, this inverse relationship was not found in strains in which OMV production is driven by an increase in "periplasmic pressure" resulting from the accumulation of protein, PG fragments, or lipopolysaccharide. In addition, the characterization of an nlpA deletion in backgrounds lacking either Lpp- or OmpA-mediated envelope crosslinks demonstrated a novel role for NlpA in envelope architecture. CONCLUSIONS: From this work, we conclude that OMV production can be driven by distinct Lpp concentration-dependent and Lpp concentration-independent pathways.