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PubMed2007

Dynamics of lysozyme structure network: probing the process of unfolding.

Recently we showed that the three-dimensional structure of proteins can be investigated from a network perspective, where the amino acid residues represent the nodes in the network and the noncovalent interactions between them are considered for the edge formation. In this study, the dynamical behavior of such networks is examined by considering the example of T4 lysozyme. The equilibrium dynamics and the process of unfolding are followed by simulating the protein at 300 K and at higher temperatures (400 K and 500 K), respectively. The snapshots of the protein structure from the simulations are represented as protein structure networks in which the strength of the noncovalent interactions is considered an important criterion in the construction of edges. The profiles of the network parameters, such as the degree distribution and the size of the largest cluster (giant component), were examined as a function of interaction strength at different temperatures. Similar profiles are seen at all the temperatures. However, the critical strength of interaction (Icritical) and the size of the largest cluster at all interaction strengths shift to lower values at 500 K. Further, the folding/unfolding transition is correlated with contacts evaluated at Icritical and with the composition of the top large clusters obtained at interaction strengths greater than Icritical. Finally, the results are compared with experiments, and predictions are made about the residues, which are important for stability and folding. To summarize, the network analysis presented in this work provides insights into the details of the changes occurring in the protein tertiary structure at the level of amino acid side-chain interactions, in both the equilibrium and the unfolding simulations. The method can also be employed as a valuable tool in the analysis of molecular dynamics simulation data, since it captures the details at a global level, which may elude conventional pairwise interaction analysis.

Algorithms↗

PubMed2004

What do we learn from high-throughput protein interaction data?

The biological significance of protein interactions, their method of generation and reliability is briefly reviewed. Protein interaction networks adopt a scale-free topology that explains their error tolerance or vulnerability, depending on whether hubs or peripheral proteins are attacked. Networks also allow the prediction of protein function from their interaction partners and therefore, the formulation of analytical hypotheses. Comparative network analysis predicts interactions for distantly related species based on conserved interactions, even if sequences are only weakly conserved. Finally, the medical relevance of protein interaction analysis is discussed and the necessity for data integration is emphasized.

Animals↗

PubMed1999

Epidemiological methods for research with drug misusers: review of methods for studying prevalence and morbidity.

Epidemiological studies of drug misusers have until recently relied on two main forms of sampling: probability and convenience. The former has been used when the aim was simply to estimate the prevalence of the condition and the latter when in depth studies of the characteristics, profiles and behaviour of drug users were required, but each method has its limitations. Probability samples become impracticable when the prevalence of the condition is very low, less than 0.5% for example, or when the condition being studied is a clandestine activity such as illicit drug use. When stratified random samples are used, it may be difficult to obtain a truly representative sample, depending on the quality of the information used to develop the stratification strategy. The main limitation of studies using convenience samples is that the results cannot be generalised to the whole population of drug users due to selection bias and a lack of information concerning the sampling frame. New methods have been developed which aim to overcome some of these difficulties, for example, social network analysis, snowball sampling, capture-recapture techniques, privileged access interviewer method and contact tracing. All these methods have been applied to the study of drug misuse. The various methods are described and examples of their use given, drawn from both the Brazilian and international drug misuse literature.

Epidemiologic Methods↗

PubMed2026

Metabolic-cell-death gene trio predicts survival and cuproptosis sensitivity in colorectal cancer.

BACKGROUND: Metabolic cell death (MCD) modulates colorectal cancer (CRC) progression, yet its prognostic value remains unexplored. We aimed to build an MCD-centred gene signature for outcome prediction and precision therapy. METHODS: Transcriptomes of 1,174 CRC patients were integrated. Weighted gene co-expression network analysis, differential expressions and least absolute shrinkage and selection operator (LASSO) + random survival forest were successively applied to derive a three-gene (CDKN2A/MPC1/AHCY) risk model. Functional, immune-infiltration, drug-sensitivity and genomic analyses were performed, followed by validation in fresh clinical specimens and cell lines. RESULTS: Integrative metabolic-death transcriptomics identified CDKN2A, MPC1 and AHCY as the hub drivers of CRC. Their three-gene signature robustly stratified patients into high- and low-risk subsets [3-year area under the curve (AUC) 0.83-0.85, P<0.001]. High-risk tumors were enriched for extracellular matrix (ECM)-receptor-interaction pathways, displayed abundant myeloid-derived suppressor cell (MDSC) infiltration and were more vulnerable to AZD8186, AZ960 and JAK inhibitors. Guided by these in-silico findings, we functionally confirmed that CDKN2A silencing markedly repressed proliferation, invasion and migration of SW480/HCT116 cells and potentiated cuproptosis via up-regulation of lipoylated DLAT/DLST and CTR1. CONCLUSIONS: We report the first MCD-derived prognostic platform for CRC that simultaneously predicts survival and therapeutic response. Targeting CDKN2A-enhanced cuproptosis represents a promising metabolic-precision strategy for high-risk patients.

Colorectal cancer (CRC)↗

PubMed2026

RECQL correlates with immune infiltration and serves as a prognostic biomarker and therapeutic predictor in gastric cancer.

BACKGROUND: RecQ-like helicase (RECQL), a member of the RecQ-like DNA helicase family, plays a crucial role in maintaining genomic stability. However, its relevance in gastric cancer (GC) has not been fully investigated. This study aimed to explore the clinical significance, biological functions, and potential role of RECQL in the tumor immune microenvironment of GC through comprehensive bioinformatics analyses and in vitro experiments. METHODS: Weighted gene co-expression network analysis (WGCNA), differential expression analysis, and least absolute shrinkage and selection operator (LASSO) regression were performed using public datasets [The Cancer Genome Atlas Stomach Adenocarcinoma (TCGA-STAD), GSE150290] to identify key genes associated with GC progression. Subsequently, key pathways were identified through functional enrichment analysis, while immune infiltration and spatial transcriptomic analyses were conducted to characterize RECQL expression and its association with the tumor immune microenvironment. Finally, the effects of RECQL knockdown on the biological function of GC cells were assessed through Cell Counting Kit-8 (CCK-8), colony formation, scratch, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assays. RESULTS: RECQL was significantly upregulated in GC tissues and correlated with advanced clinical stage and poor prognosis. Gene set enrichment analysis (GSEA) revealed a strong association between high RECQL expression and DNA repair pathway. Immune infiltration analysis indicated significant enrichment of M2 macrophages in the high-RECQL group, along with upregulation of immune checkpoint molecules including PDCD1, CTLA4, and CD274. Spatial transcriptomics further demonstrated co-localization of RECQL with myeloid cell-enriched regions in tumor parenchymal areas. Furthermore, in vitro experimental results indicated that RECQL was highly expressed in GC cell lines, and its knockdown effectively inhibited the viability, proliferation, and migration capabilities of HGC-27 cells, while enhancing their apoptosis. CONCLUSIONS: RECQL serves as a promising biomarker and potential therapeutic target in GC.

DNA repair↗

PubMed2026

A three-gene radioresistance signature predicts tumor progression in cervical cancer.

BACKGROUND: As a primary curative treatment for locally advanced cervical cancer, radiotherapy is frequently undermined by radioresistant tumor cells that evade cell death and subsequently drive post-treatment tumor progression. This study aimed to identify candidate genes associated with radioresistance in cervical cancer and to explore their potential in predicting unfavorable outcomes among radioresistant patients, thereby providing a reference for future research. METHODS: We screened for co-expressed genes using transcriptomic data from radiation non-complete response (NCR) cervical cancer patients in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Cox regression analyses were conducted to identify the most significant radioresistance-associated genes for constructing a prognostic model. The predictive performance of this model was further validated through logistic regression, weighted gene co-expression network analysis (WGCNA), and pan-cancer analyses. Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was performed to quantify the expression levels of key genes in cervical cancer tissue samples from radiosensitive and radioresistant patients. RESULTS: The resulting prognostic model comprised three genes: MTMR11, VANGL1, and CD46. This gene panel was significantly associated with the prognosis of cervical cancer patients receiving radiotherapy and showed acceptable predictive performance across multiple cancer types. qRT-PCR analysis revealed that the expression patterns of MTMR11 and VANGL1 were generally consistent with radioresistance of cervical cancer, whereas CD46 exhibited an unexpected expression trend. CONCLUSIONS: Our findings indicate that MTMR11, VANGL1, and CD46 are associated with radioresistance and prognosis in cervical cancer. Their potential clinical utility, especially in predicting radiotherapy response at the individual patient level, requires further validation in larger, independent, and prospective cohorts.

Cervical cancer↗

PubMed1993

Activating communities for health promotion: a process evaluation method.

OBJECTIVES: To date, evaluations of community-based prevention programs have focused on assessing outcomes, not the process of organizing communities for health promotion. An approach was developed to analyze community organization efforts aimed at advancing community health objectives. These organizational processes are referred to as community activation. METHODS: Information was gathered from 762 informants through a key informant survey conducted in 28 western communities. The data collected included informant ratings of community activation and information about interorganizational activities analyzed through network analytic techniques. RESULTS: Activation levels, as measured by informant ratings, varied across communities. Program coordination, as measured by network analysis, occurred, on average, approximately 30% of the time. Higher income communities tended to be more activated than lower income communities. CONCLUSIONS: There is a widely recognized need for improved information about health-related community organization activities. It appears possible to gather such information through key informant surveys and to develop measures of community organization status that can be used in the evaluation of community health promotion programs.

Community Participation↗

PubMed2026

Decoding age-stratified clinical and molecular heterogeneity in male breast cancer through multiomic profiling.

OBJECTIVE: Age-associated molecular heterogeneity is well described in female breast cancer but remains insufficiently characterized in male breast cancer (MBC). We profiled age-stratified clinical and molecular differences between younger (≤55 years) male breast cancer (YMBC) and older (>55 years) male breast cancer (OMBC). METHODS: We retrospectively analyzed 347 patients with MBC diagnosed at Fudan University Shanghai Cancer Center by integrating clinicopathological data, RNA sequencing, and whole-exome sequencing (WES). Survival, differential expression, and mutational signature analyses were performed. Tumor microenvironment features were inferred using xCell and ESTIMATE, and weighted gene co-expression network analysis (WGCNA) was conducted to identify age-associated co-expression modules. Candidate therapeutics were prioritized using the Genomics of Drug Sensitivity in Cancer (GDSC) resource and evaluated using patient-derived organoids (PDOs). RESULTS: Compared with OMBC, YMBC more frequently had human epidermal growth factor receptor 2 (HER2)-positive status (14.91% vs. 4.02%) and triple-negative tumors (4.92% vs. 1.78%), and had worse 5-year recurrence-free survival (hazard ratio=2.19, P=0.018). Transcriptomic analyses indicated enrichment of neural-related programs and reduced immune-related signaling in YMBC, and xCell/ESTIMATE supported lower immune infiltration. Consistently, WGCNA identified age-associated modules linking neural-related programs with reduced immune infiltration. Immunohistochemistry supported increased perineural invasion and lower CD8+ T cell infiltration in YMBC. GDSC-guided prioritization with PDO testing nominated sepantronium bromide (YM155) as a candidate vulnerability in YMBC. WES showed a higher NBPF10 mutation frequency in YMBC (54.5% vs. 14.3%, P<0.05). CONCLUSIONS: Integrated multi-omics profiling revealed age-stratified clinical and molecular heterogeneity in MBC. YMBC patients demonstrated inferior recurrence-free survival, neural signaling enrichment, an immune-cold microenvironment, and enriched NBPF10 mutations. These findings support age as a meaningful stratification variable in MBC risk assessment and treatment planning, and highlight the need for caution when considering treatment de-escalation in younger patients, while nominating YM155 as a candidate agent for prospective evaluation.

Male breast cancer↗

PubMed2026

ARL6IP1 Inhibits Breast Cancer Tumor Progression by Targeting OLFM4 to Regulate Glycolysis.

INTRODUCTION: ARL6IP1 has been linked to cancer progression, but its precise role in BC, particularly in metabolism and its interaction with an OLFM4, remains unclear. AIMS: This study aimed to investigate the role of ADP-ribosylation factor-like 6 interacting protein 1 (ARL6IP1) in breast cancer (BC) cell behavior and metabolism and explore its interaction with an olfactomedin-4 (OLFM4) as a potential therapeutic target. OBJECTIVE: The objective of this study was to determine the effects of ARL6IP1 knockdown on BC cell proliferation, invasion, migration, apoptosis, oxidative stress, and glycolysis. Additionally, this study also explored the interaction between ARL6IP1 and OLFM4 and their combined role in BC progression and metabolism. METHODS: Key gene modules in the GSE73540 dataset were identified through weighted gene co-expression network analysis (WGCNA). Three BC-related datasets (GSE73540, GSE22820, and GSE36295) and The Cancer Genome Atlas (TCGA) were applied for additional examination of differentially expressed genes (DEGs). Intersection analysis selected ARL6IP1 as a hub gene for prognostic analysis. In vitro experiments investigated how ARL6IP1 knockdown influences BC cell proliferation, invasion, migration, apoptosis, epithelial-mesenchymal transition (EMT), oxidative stress, and glycolysis. The connection between ARL6IP1 and an OLFM4 was confirmed using Co-immunoprecipitation (Co-IP), and their roles in BC tumor progression and glycolysis were evaluated. RESULTS: ARL6IP1 was elevated in BC datasets and linked with poor BC prognosis. Experiments demonstrated that knockdown of ARL6IP1 significantly reduced BC cell growth while promoting apoptosis and oxidative stress. Besides, ARL6IP1 knockdown reduced glycolysis, as manifested by decreased extracellular acidification rate (ECAR), glucose consumption, adenosine triphosphate (ATP) levels, and lactate production while increasing mitochondrial respiration (OCR). Co-IP validated the connection between ARL6IP1 and OLFM4, and OLFM4 overexpression partially counteracted the suppression of glycolysis and cell behavior resulting from ARL6IP1 knockdown. CONCLUSION: ARL6IP1 is a critical regulator of BC progression, influencing glycolysis, mitochondrial function, and key cellular behaviors. Targeting the ARL6IP1-OLFM4 axis offers a promising therapeutic strategy for managing BC.

Humans↗

PubMed2026

Exploring the Potential Molecular Targets of Cyanidin-3-O-glucoside for Type 2 Diabetes Mellitus Treatment.

INTRODUCTION: This study aims to elucidate the multi-target molecular mechanism of cyanidin-3-O-glucoside (C3G) in treating Type 2 Diabetes (T2DM) through network pharmacology methods. METHODS: The study was designed to predict the targets of C3G through public databases and to screen for T2DM-related targets. Protein-protein interaction (PPI) network analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the common targets. Core targets were further validated through molecular docking and molecular dynamics (MD) simulations. RESULTS: This research identified a total of 57 potential targets of C3G in the treatment of T2DM. Subsequent PPI analysis identified ALB (Degree=43), AKT1 (Degree=41), and TNF (Degree=41) as the top three hub proteins. Pathway analysis indicated significant involvement in the insulin signaling pathway (P = 4.205×10-9), AMPK signaling pathway (P = 9.582×10-7), and FoxO signaling pathway (P = 1.315×10-6). Molecular docking revealed strong binding affinities between C3G and NOS3 (-9.5 kcal/mol), PPARG (-9.0 kcal/mol), TNF (-8.5 kcal/mol), and INSR (-8.4 kcal/mol). MD simulations further confirmed that the C3G-target complex has excellent binding stability. DISCUSSION: C3G may intervene in the pathological progression of T2DM by regulating key pathways such as insulin sensitivity, inflammatory responses, and oxidative stress. Further studies suggest that INSR and NOS3 may be new targets through which C3G exerts its effects, but their specific mechanisms and in vivo biological functions still need to be elucidated by subsequent experiments. CONCLUSION: C3G may intervene in the progression of T2DM in a multi-pathway synergistic manner by targeting key molecules such as INSR and NOS3.

Anthocyanins↗

PubMed2002

Pathological peptide folding in Alzheimer's disease and other conformational disorders.

Main neuropathological hallmarks of Alzheimer's disease (AD) and other neurodegenerative disorders are the deposition of neurofibrillary tangles consisting of abnormally phosphorylated protein tau and of senile plaques largely containing insoluble beta-amyloid peptides (A beta), containing up to 43 amino acid residues derived from the beta-amyloid precursor protein. Such A beta-sheets become visible by using suitable histochemical methods. Molecular simulation showed that the central, alpha-helical, lipophilic, antigenic folding domain of the A beta-peptide loop is a promising molecular target of beta-sheet breakers that thus prevent the polymerization of A beta into aggregates. It seems that di- and tetramers of A beta-peptides have a beta-barrel- like structure. In the present review, an optimized neural network analysis was applied to recognize possible structure-activity relationships of peptidomimetic beta-sheet breakers. The anti-aggregatory potency of beta-sheet breakers largely depends upon their total, electrostatic, and hydration energy as derived from their geometry-optimized conformations using the hybrid Gasteiger-molecular mechanics approach. Moreover, we also summarize peptide misfolding in several disorders with distinct clinical symptoms, including prion diseases and a broad variety of systemic amyloidoses, as the common pathogenic step driving these disorders. In particular, conversion of nontoxic alpha-helix/random-coils to beta-sheet conformation was recognized as being critical in producing highly pathogenic peptide assemblies. Whereas conventional pharmacotherapy of AD is mainly focused on restoring cholinergic activity and diminishing inflammatory responses as a consequence of amyloid accumulation, we here survey potential approaches aimed at preventing or reserving the transition of neurotoxic peptide species from alpha-helical/random coil to beta-sheet conformation and thus abrogating their effects in a broad variety of disorders.

Alzheimer Disease↗

PubMed2026

Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

BACKGROUND: Predicting enterocutaneous fistula (ECF)-associated sepsis and mortality poses significant challenges in digital health care due to the disease's complexity and heterogeneous clinical manifestations. Current approaches that rely on single-modal data or traditional scoring systems often fail to capture the intricate immune-inflammatory dynamics and multisystem involvement in patients with ECF. OBJECTIVE: This study aims to develop an artificial intelligence (AI)-driven multimodal fusion model integrating clinical, imaging, and transcriptomic data for early prediction of ECF-associated sepsis and 28-day mortality, addressing the limitations of conventional single-dimensional models. METHODS: This study leveraged publicly available datasets (Medical Information Mart for Intensive Care III [MIMIC-III], electronic Intensive Care Unit [eICU], and The Cancer Genome Atlas) to construct a multimodal framework. Clinical parameters were processed using Extreme Gradient Boosting, abdominal imaging features were extracted via convolutional neural networks, and transcriptomic profiles were analyzed with variational autoencoders. A Transformer-based fusion network was employed for joint prediction and validated through cross-validation and external testing. Key features were identified using Shapley Additive Explanations and Local Interpretable Model-Agnostic Explanations interpretability algorithms, while immune regulatory mechanisms were explored via weighted gene co-expression network analysis. RESULTS: The multimodal model achieved an area under the curve (AUC) of 0.89 for predicting sepsis and 28-day mortality, outperforming unimodal models (clinical-only model, AUC 0.72, and imaging-only model, AUC 0.78). Critical predictors included Sequential Organ Failure Assessment score, lactate levels, intra-abdominal free fluid on imaging, and immunoregulatory genes (programmed death-ligand 1 [PD-L1] and indoleamine 2,3-dioxygenase 1 [IDO1]). Mechanistic analysis revealed distinct immune reprogramming in patients with sepsis, characterized by increased regulatory T cells and M2 macrophages, along with downregulated cluster of differentiation 8+ (CD8+) T cells. CONCLUSIONS: This multimodal AI model offers an innovative digital solution in medical informatics, enabling precise early risk stratification for ECF-associated sepsis. By integrating multisource data and providing interpretable insights into immune-inflammatory pathways, the model enhances health care quality for patients with ECF and paves the way for personalized intervention strategies.

Humans↗

PubMed1990

The social epidemiology of international drug trafficking: comparison of source of supply and distribution networks.

A variety of strategies have been implemented in an attempt to limit or prevent drug trafficking. Efforts have focused on reducing the supply of drugs, but they have not been very effective. There has been a shift recently to demand-reduction activities, but it is uncertain whether this approach will prove to be valuable. Most of the strategies that are employed are based upon the law enforcement approach. Alternative perspectives, based on principles of epidemiology and social network analysis, are presented and discussed in the context of studying drug trafficking on a global scale. More research and better sources of data and information are needed to delineate the relationship between availability and use, so that we might more effectively focus prevention activities.

Cross-Cultural Comparison↗

PubMed1989

Low Reynolds number steady state flow through a branching network of rigid vessels: I. A mixture theory.

A mixture theory has been used to formulate a theory of blood perfusion. By means of a formal averaging procedure the discrete network of microvessels is transformed into a continuum. During this procedure, the distinction between arterioles, capillaries and venules is preserved by means of an arteriovenous parameter. In this paper, two equations are derived for the case of low Reynolds number steady-state flow through a rigid vessel network: the extended Darcy equation and the continuity equation. A verification of the theory is presented, on the basis of a network analysis.

Mathematics↗

PubMed2026

RPLP0 drives diffuse large B-cell lymphoma cell proliferation through reactive oxygen species-dependent AKT/mTOR activation and inhibition of stress-induced autophagy.

Diffuse large B-cell lymphoma (DLBCL) is a common, aggressive subtype of non-Hodgkin lymphoma with poor outcomes. Identifying the primary molecular causes of DLBCL remains key. The present study examined the function of ribosomal protein lateral stalk subunit P0 (RPLP0) in DLBCL pathogenesis. The Cancer Genome Atlas-DLBCL and GSE12453 datasets overlapping differentially expressed genes were identified. Hub genes were identified via protein-protein interaction network analysis. DLBCL cells were subjected to functional tests following RPLP0 overexpression or knockdown. Reverse transcription-quantitative PCR, western blotting, flow cytometry, transmission electron microscopy, colony formation assay and biochemical analysis were among the tests performed. N-acetylcysteine (NAC), rapamycin (RAPA) and 3-MA were among the medication therapies. In the DLBCL datasets, six ribosome-associated genes were differentially expressed. RPLP0 knockdown inhibited the proliferation of DLBCL cells and caused G2-phase arrest, without impacting apoptosis. Thioredoxin, heat shock protein family A member 1A and heat shock protein family B member 1 expression was downregulated by RPLP0 knockdown, which also increased the NAD+/NADH ratio, promoted reactive oxygen species (ROS) accumulation and caused mitochondrial membrane potential depolarization. Meanwhile, 3-MA reversed the effects of RPLP0 knockdown, which encouraged LC3-II accumulation, autophagy-related gene 5 (ATG5) overexpression and an increase in autophagic vesicles. Autophagy-related indicators were decreased, and AKT/mTOR phosphorylation was increased by RPLP0 overexpression, which RAPA inhibited. NAC therapy preserved the viability of RPLP0-silenced cells, restored p-AKT/p-mTOR levels and restored normal LC3 and ATG5 expression. These findings suggest that RPLP0 regulates stress-induced autophagy through ROS-dependent AKT/mTOR signaling and may represent a potential therapeutic target for DLBCL.

AKT/mTOR signaling pathway↗

PubMed1996

The meaning of sea kayaking for persons with spinal cord injuries.

OBJECTIVES: Research has described benefits of physical, athletic, and avocational activity on improving self-esteem, quality of life, and locus of control in persons with disabilities. The objective of this study was to identify meaningful components of the experience of sea kayaking as described by persons with spinal cord injury (SCI). METHOD: Three subjects with SCI who had participated in recreational kayaking were interviewed. Qualitative research methods included strategies from Guba's model for rigor in qualitative research, Spradley's interviewing guidelines, and Good's method of semantic network analysis. Three interviews of approximately 45 min in length were conducted with each subject. Initial interviews began with a single question: "Tell me about sea kayaking." Subsequent questions contained only concepts and terms used in the subjects' responses. RESULTS: The subjects valued the novelty, challenge, safety, sociability, and natural environment aspects of sea kayaking. Perceptions of the self as able in the eyes of others and the need for support in pursuit of outdoor leisure activities were themes that figured prominently in the subjects' discourse. CONCLUSION: Subjects' comments indicate that meaningful time use and the construction of an identity after injury are linked. This link has also been suggested in the rehabilitation literature. This information suggests the use of therapeutic intervention that supports a person's adjustment to an irreversible SCI.

Adaptation, Psychological↗

PubMedDate not supplied

The use of decision support systems in health facility allocation problems.

Employing Kitchener's Freeport Hospital as a case study, the author introduces decision support systems as possible aids for allocating public health care facilities. The study found that the Dynamic Interactive Network Analysis System (DINAS) was useful in determining Kitchener as the most suitable location for Freeport, based upon a comparison of need throughout Ontario.

Catchment Area, Health↗

PubMed1976

[Dendroarchitectonic study of the inferior colliculus in the cat].

A network analysis of dendritic fields of the cells of the inferior colliculus has been performed in the adult cat. The cells of the dorso-medial nucleus have a smaller volume, less terminal segments and more dendritic spines than the cells of the ventral lateral nucleus. The bifurcation ratio of the different cells makes it possible to separate two different types of cells: order 2 cells with a strictly monochotomous branching on random segment and order 3 cells which dendrites grown by terminal branching on random pendant arcs.

Animals↗