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PubMed2026

Screening of biomarkers related to lung adenocarcinoma based on construction of ceRNA regulation network.

BACKGROUND: Lung adenocarcinoma (LUAD) is a common malignant tumor with a poor prognosis and limited effective therapeutic targets. The underlying molecular regulatory mechanisms driving its progression remain largely unclear. The study objectives were to build a circRNA-miRNA-mRNA ceRNA regulation network of LUAD and to identify miRNAs and mRNAs significantly related to the prognosis . METHODS: The gene expression data and GSE101684 were downloaded from the UCSC Xene and NCBI-GEO databases, respectively. The differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs; DERs) were obtained by the Limma package in R. Then, the differential LUAD-related genes were identified, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of the differential LUAD-related genes were analyzed. Moreover, the circRNA-miRNA-mRNA ceRNA network of LUAD was built. The Kaplan-Meier (K-M) survival curve analysis of ceRNA network nodes was performed. In addition, the proliferation-related ceRNA network was built. RESULTS: A total of 382 DEcircRNAs, 1907 DEmRNAs and 156 DEmiRNAs were acquired. A total of 245 differential LUAD-related genes were acquired, which were significantly associated with 189 GO biological processes (BP) and 17 KEGG pathways. Moreover, the ceRNA network of LUAD was built. The K-M survival curve analysis of ceRNA network nodes revealed that a total of 2 miRNAs (hsa-miR-96-5p and hsa-miR-125b-2-3p) and 22 mRNAs (CGNL1, CTHRC1, TK1, etc) were significantly related to the prognosis. mRNAs were significantly enriched in 92 GO BPs (such as cell division, cell adhesion) and 9 KEGG pathways (such as cell cycle, HTLV-1 infection). In addition, the proliferation-related ceRNA network was built. CONCLUSION: This research built a ceRNA regulation network of LUAD and is of great significance for identifying biomarkers related to the prognosis in LUAD.

Humans↗
PubMed1992

Malaria eradication and the selective approach to health care: some lessons from Ethiopia.

Analysis of the failure of the World Health Organization's global malaria campaign has contributed to the formulation of the primary health care concept as the basic international strategy for health improvement. The Primary Health Care Conference held in Alma-Ata in 1978 was to have ended the period of vertical disease control programs, such as the one against malaria, stressing instead the integration of these programs into horizontal community-based health systems. Malaria control programs, however, have not been integrated well--or in some cases at all--into primary health care networks. An analysis of the Ethiopian experience, as part of the worldwide malaria eradication program, illustrates the political and economic forces that have worked against the move from vertical to integrated malaria control activities, and from vertical to integrated health programs more generally.

Delivery of Health Care↗
PubMed2007

Image analysis by pulse coupled neural networks (PCNN)--a novel approach in granule size characterization.

A biologically inspired spiking neural network model, the pulse coupled neural network (PCNN), has been applied for the first time in bulk particle characterization, and specifically in the characterization of pharmaceutical granule size distributions. The PCNN was trained on surface images of pharmaceutical granule beds, and the adjustable parameters (radius neuron interconnection, r0, linking weight coefficient, beta, local threshold potential, VTheta, and number of iterations) were successfully optimized using design of experiments. As demonstrated with size fractions of granules, it was found that the PCNN produced granule size-dependent signals. In general, a first highest and relatively narrow peak located in the region of two to twelve iterations corresponded to smaller particle size, while larger particles resulted in wider peaks and in highest (not first) peak at a range between 13 and 25 iterations. Better predictions, i.e. lower RMSEP (root mean squared error of prediction) values, were obtained using high beta value, low r0 and VTheta values, while the number of iterations had to exceed 110 and the optimized model (RMSEP lower than 5) corresponded to PCNN variables: r0=1, beta=0.4, VTheta=2, and number of iterations=150. The coefficient of determination (R2) of the model was 0.94 and the predicted variation (Q2) was 0.91, while the Pearson correlation coefficient between the predicted and the measured mean particle size by sieving for eight test batches was 0.98. These findings could be characterized as promising and encouraging for the further use of image analysis by PCNNs in pharmaceutical bulk particle size and shape characterization.

Image Processing, Computer-Assisted↗
PubMed2006

Lost in translation: a genealogy of the "social capital" concept in public health.

STUDY OBJECTIVE: To examine the genealogy of the social capital concept in public health, with attention to the epistemological concerns and academic practices that shaped the way in which this concept was translated into public health. DESIGN: A citation-network path analysis of the public health literature on social capital was used to generate a genealogy of the social capital concept in public health. The analysis identifies the intellectual sources, influential texts, and developments in the conceptualisation of social capital in public health. PARTICIPANTS: The population of 227 texts (articles, books, reports) was selected in two phases. Phase 1 texts were articles in the PubMed database with "social capital" in their title published before 2003 (n = 65). Phase 2 texts are those texts cited more than once by phase 1 articles (n = 165). MAIN RESULTS: The analysis shows how the scholarship of Robert Putnam has been absorbed into public health research, how three seminal texts appearing in 1996 and 1997 helped shape the communitarian form that the social capital concept has assumed in public health, and how both were influenced by the epistemological context of social epidemiology at the time. CONCLUSIONS: Originally viewed in public health research as an ecological level, psychosocial mechanism that might mediate the income inequality-health pathway, the dominance of the communitarian approach to social capital has given disproportionate attention to normative and associational properties of places. Network approaches to social capital were lost in this translation. Recovering them is key to a full translation and conceptualisation of social capital in public health.

Health Services Research↗
PubMed2025

Molecular mechanism of HaiZao-YuHu decoction in breast cancer treatment via network pharmacology and molecular docking: Computational pharmacology.

BACKGROUND: The molecular biological mechanisms of HaiZao-YuHu decoction were investigated using network pharmacology and molecular docking. METHODS: TCMSP database was used to collect the active ingredients and action targets of HaiZao-YuHu decoction, through the OMIM, PharmGkb, GeneCards, TDD, and DurgBank database query targets for breast cancer. Then, using the intersecting targets, the protein-protein interaction network of HaiZao-YuHu decoction was constructed using the STRING website. Network topology analysis was performed using Cytoscape 3.9.0 to identify the core targets. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed with the R package. The Autodock software was used for molecular docking. RESULTS: Thirty-four active ingredients, 219 intersection targets and 4 key targets were obtained. gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis get 2152 biological processes and 186 pathways. Molecular docking showed that the 4 core targets could combine well with the 5 main active components. CONCLUSION: HaiZao-YuHu decoction can play a role in the treatment of breast cancer through multi-targets, multi-components, and multi-pathways.

Molecular Docking Simulation↗
PubMed2003

Crucial role of the counteranion on the templation of metallomacrocycles and a 3D network: synthesis, characterization, and structural analysis.

Two novel supramolecular architectures, [[Ag(2)L(1)(2)][X](2)] with X = CF(3)SO(3)(-) (2a) or X = NO(3)(-) (2b) and [[AgL(1)(2)][X]](n) with X = BF(4)(-) (3), were constructed by self-assembly and obtained in quantitative yields, using AgX as a building block and L(1) as the bridging ligand (L(1) = 1,3-bis(benzimidazol-1-ylmethyl)benzene). The X-ray molecular structures of 2a and 3 are reported. Complex 2a was identified as a metallomacrocycle in which one ligating triflate anion is coordinated to each of the two unsaturated Ag(I) ions. 2a crystallizes in monoclinic unit cell P2(1)/n with a = 9.728(6) A, b = 17.303(4) A, c = 13.268(3) A, beta = 92.52(4) degrees, V = 2231(2) A(3), and Z = 2. Remarkably, the X-ray structure of 2a shows a layered network structure consisting of infinite metallomacrocycles held together through pi-pi interactions between benzimidazole rings. In dramatic contrast, the product 3 prepared from AgBF(4) and L(1) lacks metal-counterion bonding, leading to a supramolecular 3D network with the following three outstanding features: (i) in one dimension, metallomacrocycles containing two Ag centers and two bridging ligands form infinite, double-stranded chains; (ii) neighboring chains are arranged by two distinct pi-pi interactions, one between substituted benzene rings and the other between benzimidazole rings, leading to a 3D structure; (iii) cavities within the 3D network contain BF(4)(-) counteranions. 3 crystallizes in monoclinic unit cell C2/c with a = 25.33(3) A, b = 11.655(6) A, c = 18.466(8) A, beta = 123.00(8) degrees, V = 4572(8) A(3), and Z = 4. Interestingly, electrospray mass spectroscopy suggests in either case that the identified elemental subunit [AgL(1)(2)](+) is the key building block which self-assembles and subsequent anion templation provides either the macrocycles 2a, b or the inorganic polymer 3. Remarkably, in dichloromethane solvent ligand-to-metal stoichiometries of 2:1 in 3 and 1:1 in 2a, b are obtained even with excess ligand, showing the power of metal-anion interactions in determining the overall supramolecular structure. Anion metathesis, showing supramolecular structural rearrangements from 2a to 2b and more spectacularly from 3 to 2b, smoothly occurred. The crucial effect and the nature of coordinating counteranions (BF(4)(-), CF(3)SO(3)(-), NO(3)(-)) on the supermolecule design are presented and discussed.

Journal Article↗
PubMed1998

Neural dynamics of short and medium-term motor control effects of levodopa therapy in Parkinson's disease.

A neural network model of movement control in normal and Parkinson's disease (PD) conditions is proposed to simulate the time-varying dose-response relationship underlying the effects of levodopa on movement amplitude and movement duration in PD patients. Short and long-term dynamics of cell activations and neurotransmitter mechanisms underlying the differential expression of neuropeptide messenger RNA within the basal ganglia striatum are modeled to provide a mechanistic account for the effects of levodopa medication on motor performance (e.g. the pharmacodynamics). Experimental and neural network simulation data suggest that levodopa therapy in Parkinson's disease has differential effects on cell activities, striatal neuropeptides, and motor behavior. In particular, it is shown how dopamine depletion in the striatum may modulate differentially the level of substance P and enkephalin messenger RNA in the direct and indirect basal ganglia pathways. This dissociation in the magnitude and timing of peptide expression causes an imbalance in the opponently organized basal ganglia pathways which results in Parkinsonian motor deficits. The model is validated with experimental data obtained from handwriting movements performed by PD subjects before and after medication intake. The results suggest that fine motor control analysis and network modeling of the effects of dopamine in motor control are useful tools in drug development and in the optimization of pharmacological therapy in PD patients.

Aged↗
PubMed2026

Targeting EGFR in cancer using Terminalia arjuna: An integrated In Silico, molecular dynamics, experimental validation, and network pharmacology study.

The Epidermal Growth Factor Receptor (EGFR) plays a pivotal role in 20-60% of cancer cases, including glioblastoma, lung adenocarcinoma, and head and neck squamous cell carcinoma, as reported in The Cancer Genome Atlas (TCGA) dataset. The present study employed an integrated in silico and experimental workflow to evaluate EGFR-targeted compounds from Terminalia arjuna. Drug-likeness and ADMET screening were performed, followed by molecular docking and 1000 ns molecular dynamics simulations. In vitro validation was conducted using cancer cell-based assays and network pharmacology to explore the molecular mechanisms associated with the identified compound. Screening shortlisted eight compounds from T. arjuna. Molecular docking identified Arjunaside C (-8.2 kcal/mol), Arjunapthanoloside (-7.7 kcal/mol), and Beta-sitosterol (-7.4 kcal/mol) as potential EGFR inhibitors compared to Erlotinib (-6.6 kcal/mol). Arjunapthanoloside formed more H-bonds and exhibited most stable interactions with EGFR. MD simulations at 1000 ns revealed lower RMSD, RMSF, SASA, and Rg values for the Arjunapthanoloside-EGFR complex, indicating enhanced stability. Direct binding validation was limited by the unavailability of purified Arjunapthanoloside; therefore, Arjuna extract was evaluated, which demonstrated potent cytotoxicity with an IC₅₀ of 9 µg/mL in H357 oral cancer cells. Flow cytometry confirmed apoptosis-mediated cell death by increased early- and late-apoptotic cell populations. Network pharmacology analysis further identified additional targets (MMP3, MMP7, MMP9, and HRAS) that are directly involved in various cancers. Overall, the findings provide new insights into the therapeutic potential of Arjunapthanoloside as a stable compound that interacts with EGFR from T. arjuna, highlighting its significance in EGFR-targeted anticancer research.

ErbB Receptors↗
PubMed2003

The prediction of methylmercury elimination half-life in humans using animal data: a neural network/rough sets analysis.

Artificial neural networks and Rough Sets methodology have been utilized to predict human pharmacokinetic elimination half-life data based on animal data training sets. Methylmercury (Hg) pharmacokinetic data was obtained from 37 literature references, which provided data on species, gender, age, weight, route of administration, dose, dose frequency, and elimination half-life based on either whole-body Hg analysis or blood Hg analysis. Data were categorized into various formats for analysis comparisons. Rough Sets methodology was utilized to identify and remove redundant independent variables. Artificial neural networks were used to produce models based on the animal data, which were in turn used to predict and compare to the human elimination half-life values. These neural network predictions were compared to allometric graphical plots of the same data. The best artificial neural network prediction was based on a "thermometer" categorical representation of the data.

Adolescent↗
PubMed2006

Stability analysis for stochastic Cohen-Grossberg neural networks with mixed time delays.

In this letter, the global asymptotic stability analysis problem is considered for a class of stochastic Cohen-Grossberg neural networks with mixed time delays, which consist of both the discrete and distributed time delays. Based on an Lyapunov-Krasovskii functional and the stochastic stability analysis theory, a linear matrix inequality (LMI) approach is developed to derive several sufficient conditions guaranteeing the global asymptotic convergence of the equilibrium point in the mean square. It is shown that the addressed stochastic Cohen-Grossberg neural networks with mixed delays are globally asymptotically stable in the mean square if two LMIs are feasible, where the feasibility of LMIs can be readily checked by the Matlab LMI toolbox. It is also pointed out that the main results comprise some existing results as special cases. A numerical example is given to demonstrate the usefulness of the proposed global stability criteria.

Algorithms↗
PubMed2025

Integration of multi-source gene interaction networks and omics data with graph attention networks to identify novel disease genes.

MOTIVATION: The pathogenesis of diseases is closely associated with genes, and the discovery of disease genes holds significant importance for understanding disease mechanisms and designing targeted therapeutics. However, biological validation of all genes for diseases is expensive and challenging. RESULTS: In this study, we propose DGP-AMIO, a computational method based on graph attention networks, to rank all unknown genes and identify potential novel disease genes by integrating multi-omics and gene interaction networks from multiple data sources. DGP-AMIO outperforms other methods significantly on 20 disease datasets, with an average AUROC and AUPR exceeding 0.9. The superior performance of DGP-AMIO is attributed to the integration of multiomics and gene interaction networks from multiple databases, as well as triGAT, a proposed GAT-based method that enables precise identification of disease genes in directed gene networks. Enrichment analysis conducted on the top 100 genes predicted by DGP-AMIO and literature research revealed that a majority of enriched GO terms, KEGG pathways and top genes were associated with diseases supported by relevant studies. We believe that our method can serve as an effective tool for identifying disease genes and guiding subsequent experimental validation efforts. AVAILABILITY AND IMPLEMENTATION: DGP-AMIO is publicly available at https://github.com/yangkaiyuan1027/DGP-AMIO.

Gene Regulatory Networks↗
PubMed2006

Computational methodologies for modelling, analysis and simulation of signalling networks.

This article is a critical review of computational techniques used to model, analyse and simulate signalling networks. We propose a conceptual framework, and discuss the role of signalling networks in three major areas: signal transduction, cellular rhythms and cell-to-cell communication. In order to avoid an overly abstract and general discussion, we focus on three case studies in the areas of receptor signalling and kinase cascades, cell-cycle regulation and wound healing. We report on a variety of modelling techniques and associated tools, in addition to the traditional approach based on ordinary differential equations (ODEs), which provide a range of descriptive and analytical powers. As the field matures, we expect a wider uptake of these alternative approaches for several reasons, including the need to take into account low protein copy numbers and noise and the great complexity of cellular organisation. An advantage offered by many of these alternative techniques, which have their origins in computing science, is the ability to perform sophisticated model analysis which can better relate predicted behaviour and observations.

Algorithms↗
PubMed2000

Preoperative assessment of melanoma thickness by ABCD score of dermatoscopy.

BACKGROUND: Epiluminescence microscopy is a useful tool for the noninvasive diagnosis of malignant melanoma based on criteria that have been correlated with specific histologic characteristics. Previous studies have also shown a good correlation between the frequency of some dermatoscopic criteria based on pattern analysis (pigment network, blue-gray areas, vascular pattern) and tumor thickness. This technique could be useful in the preoperative assessment of tumor thickness as an indication for sentinel node biopsy. OBJECTIVE: Our purpose was to evaluate the possible role of the total dermatoscopy score (TDS) assigned to a series of lesions in accordance with the ABCD rule of dermatoscopy as a preoperative predictor of melanoma thickness. METHODS: For 84 cutaneous melanomas (17 were in situ melanomas; 67 invasive cases with mean thickness 0. 93 mm; range, 0.2-3.9 mm; standard deviation, 0.63) consecutively excised at the Department of Dermatology of Florence, TDS was established by two observers blinded as to the tumor thickness. The performance of different cut-off points of TDS in the diagnosis of melanoma with Breslow's thickness more than 0.75 or 1.00 mm was investigated by receiver operating characteristic (ROC) analysis. Accuracy of classification was evaluated in terms of sensitivity, specificity, and area under ROC curves (AUC). RESULTS: The TDS assigned to cutaneous melanomas by the ABCD rule increased with the thickness of the lesions from in situ melanomas to melanomas of intermediate thickness (0.75-1.50 mm). As a preoperative method for the detection of melanomas with a Breslow thickness greater than 0. 75 mm, a TDS cut-off point of 6.80 showed 80% sensitivity, 84% specificity, and 82% diagnostic accuracy (AUC value, 0.90). TDS performed better in the diagnosis of a thickness threshold of 0.75 than 1.00 mm (higher AUC value). CONCLUSION: The TDS calculated by the ABCD rule of dermatoscopy-a simplified approach to dermatoscopic diagnosis of melanoma-provides useful information for the preoperative assessment of melanoma thickness greater than 0.75 mm.

Humans↗
PubMed2001

Complexity and fragility in ecological networks.

A detailed analysis of three species-rich ecosystem food webs has shown that they display skewed distributions of connections. Such graphs of interaction are, in fact, shared by a number of biological and technological networks, which have been shown to display a very high homeostasis against random removals of nodes. Here, we analyse the responses of these ecological graphs to both random and selective perturbations (directed against the most-connected species). Our results suggest that ecological networks are very robust against random removals but can be extremely fragile when selective attacks are used. These observations have important consequences for biodiversity dynamics and conservation issues, current estimations of extinction rates and the relevance and definition of keystone species.

Ecosystem↗
PubMed2005

Genome-wide monocytic mRNA expression in polytrauma patients for identification of clinical outcome.

Immune activation in multiple trauma is closely linked to the development of multiple organ dysfunction and failure, and consequently, has a profound influence on patient outcome. Although peripheral blood monocytes play a critical role in this immune response, the biological significance of changes in genome-wide expression immediately after traumatic injury have not been explored previously. Thirteen patients presenting with multiple blunt trauma were studied. Peripheral blood monocytes were obtained within 90 min and at 6, 12, 24, 48, and 72 h after trauma. Apparent genome-wide expression was determined with Affymetrix U133A microarrays. Supervised analysis identified 698 probe sets that were differentially expressed in the 13 trauma subjects (P < 0.001) over the 72-h study period. An additional 763 probe sets were differentially expressed in patients who died (n = 3) compared with those who survived (n = 10). The ability of these probe sets to function as a classifier of survival was significantly demonstrated with six prediction models. Using pathway analysis, a network of proinflammatory genes and intracellular signaling pathways leading to c-JUN activation were consistently overexpressed in patients who died. Genome-wide mRNA expression patterns in circulating peripheral blood monocytes from multiple-injured patients can discriminate clinical outcome. The pattern of gene expression in patients who died suggests that in these individuals, there is a reprioritization of gene expression consistent with an early activation of selected genes involved in the initiation and propagation of a proinflammatory response.

Adult↗
PubMed1987

Analysis of vascular pattern and dimensions in arteriolar networks of the retractor muscle in young hamsters.

A quantitative analysis of the distribution of microvascular blood flow and oxygen delivery requires a detailed description of the vascular network geometry. The distributions of lengths and diameters were determined in terminal arteriolar networks of the cheek pouch retractor muscle of young (34 +/- 2 days) hamsters. We compared the Strahler centripetal vessel ordering scheme, which assigns lowest order to the capillaries and proceeds upstream toward the larger vessels, with the centrifugal ordering scheme, which begins with the input arteriole and proceeds downstream toward the capillaries. The terminal networks of the retractor muscle typically contain 2 to 4 Strahler orders and 2 to 6 centrifugal orders. The coefficients of variation of diameter and length are smaller for Strahler ordering than for centrifugal ordering. In addition, for Strahler ordering, we found that the sequence of number of vessels obeyed Horton's law. We have compared three different methods of calculating the bifurcation, diameter, and length ratios. As an alternative method for analyzing network topology, we also studied the distribution of the number of segments on each pathway from the inlet of a network to a capillary. The information obtained from this analysis is useful for the mathematical modeling of flow in the microvascular network.

Animals↗
PubMed2007

Molecular tectonics of metal-organic frameworks (MOFs): a rational design strategy for unusual mixed-connected network topologies.

To systematically explore the higher-dimensional network structures with mixed connectivity, a series of two-dimensional (2D) and three-dimensional (3D) metal-organic frameworks (MOFs) with unusual (3,6)-connected net topologies are presented. These crystalline materials include [{[Mn(btza)2(H2O)2].2 H2O}n] (1), [{[Zn(btza)2(H2O)2].2 H2O}n] (2), [{[Cu(btza)2].H2O}n] (3), and [{[Cd(btza)2].3 H2O}n] (4), which have been successfully assembled through a predesigned three-connected organic component bis(1,2,4-triazol-1-yl)acetate (btza) with a variety of octahedral metal cores based on the modular synthetic methodology. The topological paradigms shown in this work cover the 2D CdCl2, 3D (4(2).6)2(4(4).6(2).8(7).10(2)), and pyrite (pyr) types. That is, when properly treated with the familiar first-row divalent metal ions, btza may perfectly furnish the coordination spheres for effective connectivity to result in diverse (3,6)-connected nets. Beyond this, a detailed analysis of network topology for all known 3D (3,6)-connected frameworks in both inorganic and inorganic-organic hybrid materials is described. Specific network connectivity of these MOFs indicates that the metal centers represent the most significant and alterable factor in structural assembly, although they show reliable and similar geometries. In this context, the combination of the distinct d10 AgI ion with btza in different solvents affords two isomorphous MOFs [{[Ag(btza)].glycol}n] (5) and [{[Ag(btza)]CH3OH}n] (6) with a binodal 4-connected 3D SrAl2 (sra) topology. The network structures of MOFs 1-3 and 5 turn out to be more complicated and interesting if one considers the hydrogen bonding between the host coordination frameworks and the intercalated solvent molecules. Furthermore, the role of the included solvents in the generation and stabilization of MOFs 1-6 is also investigated.

Journal Article↗
PubMed2026

Mechanistic insights into Claudin-14 dysfunction implicated in veins of Galen malformation.

Claudin-14 (CLDN14) is a key component of tight junctions (TJs) critical for maintaining paracellular barrier function. Variants of CLDN14 have been linked to Vein of Galen malformations (VOGMs), a rare cerebrovascular disorder; however, the molecular mechanisms underlying their pathogenicity remain unknown. Here, we investigate the mechanistic effects of two VOGM-associated mutations, A113P and V143M, using reinforcement-learning driven enhanced sampling molecular dynamics simulations combined with DiffNets-based deep learning and independent trajectory-wide structural analyses. Our analysis reveals that A113P induces broader structural disruption of CLDN14, perturbing paracellular sealing, pore symmetry, and inter-protomer communication, whereas V143M induces structural rearrangements centred around TM3 and the TM3-ECL2 region. In both cases, mutation-specific alterations are observed in structural stability and interfacial organization across oligomeric assemblies. Notably, these effects are qualitatively consistent across different modelled architectures, despite variability in local responses. In the absence of experimentally resolved structures, the structural perturbations reported here provide a mechanistic understanding of how VOGM-associated variants may influence CLDN14 structure and dynamics.

Aneurysm↗