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PubMed2005

Evaluating the effectiveness of community-based dementia care networks: the Dementia Care Networks' Study.

PURPOSE: The Dementia Care Networks' Study examined the effectiveness of four community-based, not-for-profit dementia networks. The study involved assessing the relationship between the types of administrative and service-delivery exchanges that occurred among the networked agencies and the network members' perception of the effectiveness of these exchanges. DESIGN AND METHODS: With the use of a case-study method, the evolution, structure, and processes of each network were documented. Social network analysis using a standardized questionnaire completed by member agencies identified patterns of administrative and clinical exchanges among networked agencies. RESULTS: Differences were found between the four networks in terms of their perceptions of service-delivery effectiveness; perceptions of administrative effectiveness did not factor significantly. Exchanges between groups of agencies (cliques) within each of the four networks were found to be more critical than those between individual agencies within each network. IMPLICATIONS: Integration-measured by the types of exchanges within as opposed to across networks-differentiated the four networks studied. This research contributes to our understanding of the use of multiple measures to evaluate the inner workings of service delivery and their impact on elder health and elder health care.

Aged↗

PubMed1997

Design of a recognition system to predict movement during anesthesia.

The need for a reliable method of predicting movement during anesthesia has existed since the introduction of anesthesia. This paper proposes a recognition system, based on the autoregressive (AR) modeling and neural network analysis of the electroencephalograph (EEG) signals, to predict movement following surgical stimulation. The input to the neural network will be the AR parameters, the hemodynamic parameters blood pressure (BP) and heart rate (HR), and the anesthetic concentration in terms of the minimum alveolar concentration (MAC). The output will be the prediction of movement. Design of the system and results from the preliminary tests on dogs are presented in this paper. The experiments were carried out on 13 dogs at different levels of halothane. Movement prediction was tested by monitoring the response to tail clamping, which is considered to be a supramaximal stimulus in dogs. The EEG data obtained prior to tail clamping was processed using a tenth-order AR model and the parameters obtained were used as input to a three-layer perceptron feedforward neural network. Using only AR parameters the network was able to correctly classify subsequent movement in 85% of the cases as compared to 65% when only hemodynamic parameters were used as the input to the network. When both the measures were combined, the recognition rate rose to greater than 92%. When the anesthetic concentration was added as an input the network could be considerably simplified without sacrificing classification accuracy. This recognition system shows the feasibility of using the EEG signals for movement during anesthesia.

Anesthesiology↗

PubMed1999

Mapping genotype to phenotype for linkage analysis.

We model functions that use genetic information as input and trait information as output to understand genetic linkage in complex diseases. Using simulated data from GAW11, we have applied categorical classification methods and neural network analysis. We use sharing at selected markers as input, and the classification of the sib pair (for example, affected-affected or affected-unaffected) as output. In addition, our methods include environmental risk factors as predictors of phenotype. Categorical and neural network methods each led to results consistent with findings from other methods such as the logistic regression method of Rice et al. [this issue]. Post-analysis comparison with the GAW11 answers showed that these methods are capable of detecting correct signals in a single replicate. One advantage of our methods is that they allow analysis of the entire genome at once, so that interactions among multiple trait-influencing loci may be detected. Furthermore, these methods can use a variety of sib pairs rather than affected pairs only.

Chromosome Mapping↗

PubMed1984

Social-network considerations in the alcohol field.

This chapter reviews the literature on social networks in the alcohol field. The review focuses on the dynamics of the social-network system and network analysis. Stressors to recently urbanized persons are also examined in a discussion of social adaptation, social identity, and networks. The findings of several studies that are summarized indicate that there is a crisis in changing cultural styles and social values that develops after migration and resettlement. An aspect of this review suggests that social networks may be utilized as stress-buffering strategies in both a constructive and a destructive fashion during these periods of crisis. The author describes these networks as pathways to care and illustrates how they might play a significant role in alcoholism-treatment and recovery programs. Finally, the author concludes with some possible directions for future research on the systematic study of social bonds.

Alcohol Drinking↗

PubMed2005

Y chromosome haplotype analysis in purebred dogs.

In order to evaluate the genetic structure of purebred dogs, six Y chromosome microsatellite markers were used to analyze DNA samples from 824 unrelated dogs from 50 recognized breeds. A relatively small number of haplotypes (67) were identified in this large sample set due to extensive sharing of haplotypes between breeds and low haplotype diversity within breeds. Fifteen breeds were characterized by a single Y chromosome haplotype. Breed-specific haplotypes were identified for 26 of the 50 breeds, and haplotype sharing between some breeds indicated a common history. A molecular variance analysis (AMOVA) demonstrated significant genetic variation across breeds (63.7%) and with geographic origin of the breeds (11.5%). A network analysis of the haplotypes revealed further relationships between the breeds as well as deep rooting of many of the breed-specific haplotypes, particularly among breeds of African origin.

Analysis of Variance↗

PubMed2026

Phenotypic, physiological and transcriptomic analysis of graded salt stress responses in Pyrus betulifolia Bunge and functional characterization of the hub gene PbSTY46.

Pyrus betulifolia Bunge is a salt‑tolerant rootstock for pear, but its salt‑tolerance mechanisms remain largely unknown. In this study, P. betulifolia seedlings were subjected to graded NaCl stress at concentrations of 0 (CK), 50 (T1), 100 (T2), and 200 (T3) mM. We integrated phenotypic observation, physiological assessment, transcriptomic profiling, and functional gene validation to systematically elucidate its salt tolerance mechanisms. Salt stress inhibited seedling growth and root traits in a concentration-dependent manner, and T3 caused the most severe damage. Osmotic solutes responded differentially: soluble sugars peaked under T2, while proline peaked under T3. Antioxidant enzymes showed tissue-specific biphasic responses and declined after prolonged T3 stress. Meanwhile, chlorophyll and photosynthesis decreased, whereas anthocyanin increased, indicating a metabolic shift from photosynthesis to photoprotection. Transcriptome analysis revealed distinct responses depending on stress intensity: mild stress induced membrane lipid remodeling, moderate stress activated circadian rhythm and hormone signaling, and severe stress enhanced phenylpropanoid biosynthesis and thiamine metabolism. Gene Set Enrichment Analysis (GSEA) further highlighted progressive enrichment of phenylpropanoid biosynthesis, heme binding, and oxidoreductase activity. Weighted Gene Co‑expression Network Analysis (WGCNA) identified a blue module significantly positively correlated with root traits, from which the hub gene PbSTY46 was identified. Functional validation via overexpression, loss‑of‑function mutants, and pharmacological interventions (MeJA/DIECA) confirmed that PbSTY46 acts through JA signaling to enhance antioxidant enzyme activities and thereby confer salt tolerance. Collectively, P. betulifolia adopts a "survival‑first" strategy that coordinates growth arrest, osmotic homeostasis, and ROS scavenging. These findings establish PbSTY46 as a key regulator that links JA signaling to antioxidant defense. Thus, PbSTY46 represents a promising candidate for marker‑assisted breeding of salt‑tolerant pear cultivars.

Salt Stress↗

PubMed1990

[A method for recording the network topology of human retinal vessels].

Network analysis of the human retinal vessels must be based on a thorough knowledge of the topology of the network. This derives from the numerical composition of the network's individual components. Using histologic specimens, centrifugal and centripetal ordering methods were compared. It was found necessary to use an ordering system which takes both dichotomous as well as lateral branching into account, and Strahler's centripetal ordering system was found to be suitable. For various representative areas of human retinae it could be shown that the number of segments of each Strahler order forms an inverse geometric sequence which enables the Horton branching quotient RB to be calculated. It is thus possible to predict the number of vessel segments within the individual orders. Although the method ignores detailed vessel morphology, with knowledge of the vessel lengths and diameters determined in the same manner it enables the conductivity and resistance of human retinal vessels to be measured.

Blood Viscosity↗

PubMed2003

Global snapshot of a protein interaction network-a percolation based approach.

MOTIVATION: Biologically significant information can be revealed by modeling large-scale protein interaction data using graph theory based network analysis techniques. However, the methods that are currently being used draw conclusions about the global features of the network from local connectivity data. A more systematic approach would be to define global quantities that measure (1) how strongly a protein ties with the other parts of the network and (2) how significantly an interaction contributes to the integrity of the network, and connect them with phenotype data from other sources. In this paper, we introduce such global connectivity measures and develop a stochastic algorithm based upon percolation in random graphs to compute them. RESULTS: We show that, in terms of global connectivities, the distribution of essential proteins is distinct from the background. This observation highlights a fundamental difference between the essential and the non-essential proteins in the network. We also find that the interaction data obtained from different experimental methods such as immunoprecipitation and two-hybrid techniques contribute differently to network integrities. Such difference between different experimental methods can provide insight into the systematic bias present among these techniques. SUPPLEMENTARY INFORMATION: The full list of our results can be found in the supplemental web site http://www.nas.nasa.gov/Groups/SciTech/nano/msamanta/projects/percolation/index.php

Algorithms↗

PubMed1978

Herpes simplex virus necleic acid synthesis following infection of non-permissive XC cells.

DNA hybridization kinetic analysis of cellular DNA following high multiplicity infection of non-permissive XC cells by herpes simplex virus type I showed that HSV DNA penetrates to the nucleus of the cell but that the number of virus DNA copies present in each cell quickly begins to decline. There did not appear to be any net virus DNA synthesis and the loss of virus DNA copies continued until there was approximately one per haploid genome equivalent. HSV-2 likewise did not show any detectable virus DNA replication. The residual virus information was stable for more than 48 h. CsCl density gradient analysis of the infected cell DNA suggested an association between the HSV DNA and that of the cells. Network analysis also supported the suggestion that a stable association between the virus DNA and host DNA begins shortly after infection. Cell division resulted in the segregation of the virus DNA but not its loss from the cell population. Virus-specific RNA synthesis was easily detectable and 40 to 50% of a labelled DNA probe was converted to an RNA:DNA hybrid.

Cell Line↗

PubMed1993

Psychiatric networks: they make sense, but do they work?

With a trend toward coordinated networks of mental health services, it is necessary to be able to assess their impact. This paper outlines an approach to network analysis, using a variety of methodologies to come up with a composite picture. Areas to examine include the network processes, such as its goals, functions, structures, outcomes, and the satisfaction of all involved.

Canada↗

PubMed2006

Neuronal networks and synaptic plasticity: understanding complex system dynamics by interfacing neurons with silicon technologies.

Information processing in the central nervous system is primarily mediated through synaptic connections between neurons. This connectivity in turn defines how large ensembles of neurons may coordinate network output to execute complex sensory and motor functions including learning and memory. The synaptic connectivity between any given pair of neurons is not hard-wired; rather it exhibits a high degree of plasticity, which in turn forms the basis for learning and memory. While there has been extensive research to define the cellular and molecular basis of synaptic plasticity, at the level of either pairs of neurons or smaller networks, analysis of larger neuronal ensembles has proved technically challenging. The ability to monitor the activities of larger neuronal networks simultaneously and non-invasively is a necessary prerequisite to understanding how neuronal networks function at the systems level. Here we describe recent breakthroughs in the area of various bionic hybrids whereby neuronal networks have been successfully interfaced with silicon devices to monitor the output of synaptically connected neurons. These technologies hold tremendous potential for future research not only in the area of synaptic plasticity but also for the development of strategies that will enable implantation of electronic devices in live animals during various memory tasks.

Animals↗

PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗

PubMed2026

Mechanistic analysis of rice caryopsis morphogenesis regulated by exogenous hormones and related precursor substances under blue light conditions.

Rice caryopsis morphogenesis is regulated by light signals and hormonal networks. However, the mechanism by which exogenous hormones and related precursor substances modulate rice caryopsis morphogenesis under blue light remains elusive. In the present study, we aimed to elucidate the molecular mechanisms underlying the regulatory effects of exogenous phytohormones and related precursor substances on caryopsis development at 10 days after pollination (10 DAP) in the japonica rice cultivar 'Chujing 27' under blue light conditions. Results showed that tryptamine treatment increased caryopsis cell volume, thereby significantly driving caryopsis expansion; meanwhile, it markedly enhanced the activities of TDC and TAA, the key rate-limiting enzymes mediating the conversion of tryptophan to auxin, leading to a significant elevation in endogenous auxin content (P < 0.05). In comparison, exogenous auxin treatment significantly boosted carbohydrate accumulation and the activities of associated metabolic enzymes (P < 0.05). Integrated transcriptomic and metabolomic analyses revealed that tryptamine treatment led to significant enrichment of the starch and sucrose metabolic pathway, and drove the coordinated enhancement of carbon metabolic flux and auxin biosynthesis by upregulating key auxin biosynthetic genes (e.g., TAA1) and repressing auxin oxidative degradation. Genes Os04g0531100, Os03g0266100 and Os11g0221200 identified by weighted gene co-expression network analysis (WGCNA) may serve as important candidate targets regulating rice caryopsis morphology and physiological traits under blue light conditions. This study first uncovers the critical function of the "tryptamine-auxin axis" in regulating rice caryopsis development under blue light, laying a theoretical foundation for regulating caryopsis morphogenesis via exogenous hormones and their precursors.

Oryza↗

PubMed1999

Lipid composition of subcellular membranes of an FY1679-derived haploid yeast wild-type strain grown on different carbon sources.

The aim of the project EUROFAN (European Functional Analysis Network) is to elucidate the function of unknown genes of the yeast Saccharomyces cerevisiae at a large scale. Functional analysis is based on general and specific tests with yeast deletion strains. A prerequisite for these studies is a profound knowledge of the biochemistry and cell biology of the corresponding wild-type strain FY1679. As a contribution from our laboratory we present here a systematic lipid analysis of the major organelles isolated from FY1679 grown in the presence of different carbon sources. Phospholipid, sterol and fatty acid composition are characteristic for each organelle. Moreover, growth of the yeast on glucose, ethanol or lactate causes in some cases marked changes of the organelle lipid pattern. As the most prominent example, cultivation of the yeast on non-fermentable carbon sources results in an increase of mitochondrial cardiolipin. As another example, the ratio of unsaturated to saturated fatty acids is enhanced in cells grown on ethanol or lactate as compared to glucose. Thus, the lipid composition of yeast subcellular membranes reflects in a significant way the nutrient conditions caused by variation of the carbon source.

Adenosine Triphosphatases↗

PubMed1993

A graph theory model of the semantic structure of attitudes.

The semantic structure underlying the attitudes of pretreatment and posttreatment drug addicts was modeled using a network analysis of free word associations. Measures of graph theoretic properties were used to assess structural differences in the associative networks of the two populations. These measures modeled the information processes of associative networks proposed in the spreading activation theory of semantic processing. As expected based on graph theory, the structure of the associative networks of posttreatment subjects was more dense, less constrained, and more hierarchically organized by the self concept. In a test of the network model, the subjects' evaluations of concepts in the associative network were found to be a function of their evaluations of semantically similar concepts. Although preliminary and limited, the results suggest that graph theory may provide a broad mathematical foundation for diverse models of cognitive systems.

Attitude↗

PubMed1992

The roles staff play in the social networks of elderly institutionalized people.

This paper concerns different ways in which nursing home residents interpret their relationships with institution staff. The research on which it is based involved an anthropological social network analysis. Analysis revealed different patterns of resident-staff interaction that are described in relation to four types of personal networks. Their meaning is interpreted in terms of the tensions between residents' common needs for attachment and autonomy and their limited means to achieve satisfaction.

Aged↗

PubMed1996

Nonlinear time series analysis by neural networks: a case study.

This paper presents a neural network approach to time-series analysis of a univariate nonlinear system. Feedforward networks are studied, and an appropriate network size is determined by different criteria computed on the basis of the performance of the models on the training and test sets. The analysis and conclusions drawn are supported by studies of the phase portraits of the models. By a proper choice of network size, the problems of over-parameterization are demonstrated to be avoided. The overfitting observed for larger networks is analyzed and the underlying reasons for their worse generalization capabilities are explained. Finally, some observations are made on the approximation provided by an oversized network with weights determined by an incomplete (interrupted) training and that of the optimal-sized network.

Cybernetics↗

PubMed2004

Investigation of possible neural architectures underlying information-geometric measures.

A novel analytical method based on information geometry was recently proposed, and this method may provide useful insights into the statistical interactions within neural groups. The link between informationgeometric measures and the structure of neural interactions has not yet been elucidated, however, because of the ill-posed nature of the problem. Here, possible neural architectures underlying information-geometric measures are investigated using an isolated pair and an isolated triplet of model neurons. By assuming the existence of equilibrium states, we derive analytically the relationship between the information-geometric parameters and these simple neural architectures. For symmetric networks, the first- and second-order information-geometric parameters represent, respectively, the external input and the underlying connections between the neurons provided that the number of neurons used in the parameter estimation in the log-linear model and the number of neurons in the network are the same. For asymmetric networks, however, these parameters are dependent on both the intrinsic connections and the external inputs to each neuron. In addition, we derive the relation between the information-geometric parameter corresponding to the two-neuron interaction and a conventional cross-correlation measure. We also show that the information-geometric parameters vary depending on the number of neurons assumed for parameter estimation in the log-linear model. This finding suggests a need to examine the information-geometric method carefully. A possible criterion for choosing an appropriate orthogonal coordinate is also discussed. This article points out the importance of a model-based approach and sheds light on the possible neural structure underlying the application of information geometry to neural network analysis.

Action Potentials↗