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PubMed2001

Use of artificial neural networks (computer analysis) in the diagnosis of microcalcifications on mammography.

INTRODUCTION/OBJECTIVE: The purpose of this study was to evaluate a computer based method for differentiating malignant from benign clustered microcalcifications, comparing it with the performance of three physicians. METHODS AND MATERIAL: Materials for the study are 240 suspicious microcalcifications on mammograms from 220 female patients who underwent breast biopsy, following hook wire localization under mammographic guidance. The histologic findings were malignant in 108 cases (45%) and benign in 132 cases (55%). Those clusters were analyzed by a computer program and eight features of the calcifications (density, number, area, brightness, diameter average, distance average, proximity average, perimeter compacity average) were quantitatively estimated by a specific artificial neural network. Human input was limited to initial identification of the calcifications. Three physicians-observers were also evaluated for the malignant or benign nature of the clustered microcalcifications. RESULTS: The performance of the artificial network was evaluated by receiver operating characteristics (ROC) curves. ROC curves were also generated for the performance of each observer and for the three observers as a group. The ROC curves for the computer and for the physicians were compared and the results are:area under the curve (AUC) value for computer is 0.937, for physician-1 is 0.746, for physician-2 is 0.785, for physician-3 is 0.835 and for physicians as a group is 0.810. The results of the Student's t-test for paired data showed statistically significant difference between the artificial neural network and the physicians' performance, independently and as a group. DISCUSSION AND CONCLUSION: Our study showed that computer analysis achieves statistically significantly better performance than that of physicians in the classification of malignant and benign calcifications. This method, after further evaluation and improvement, may help radiologists and breast surgeons in better predictive estimation of suspicious clustered microcalcifications and reduce the number of biopsies for non-palpable benign lesions.

Adult↗

PubMed2003

[Ecological footprint calculation and development capacity analysis of China in 1999].

The ecological footprint method put forward and improved by William Rees and Mathis Wackernagel presents a methodologically simple but integrated framework for national natural capital accounting, which is capable of measuring the impact of Human's consumption on ecosystem. Based on the ecological footprint theory and calculation method, a flow network analysis method was introduced to illuminate the structure of complex ecological economic system, and the relationship among ecological footprint, diversity and development capacity was analyzed. In this paper, the ecological footprints of China and its provinces was calculated and compared with the national and local ecological carrying capacity. The results showed that the ecological footprints of China and most of its provinces were beyond the available ecological capacity, and China and its most provinces run 'national or regional ecological deficit'. In case of China, the national ecological deficit was 0.645 hm2 per cap in 1999. Secondly, we introduced a flow network analysis method, taking various ecological productive area as note, and adopted Ulanowicz's development capacity formula to analyze the relationship among ecological footprint diversity, development capacity and output. The results demonstrated that Ulanowicz's development capacity was a good predictor of economic system output. At the same time, two distinct ways to change development capacity were produced. Increasing ecological footprint or increasing ecological footprint's diversity would both increase development capacity. Due to the fact that the ecological footprints had already been beyond bio-capacities, the only way to increase development capacity was to increase ecological footprint's diversity. The positive relationship between ecological footprint diversity and resources utilization efficiency demonstrated that there was no conflict between increasing ecological footprint's diversity and reducing footprints while not comprising our quality of life.

China↗

PubMed2006

Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data.

As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data.

Computational Biology↗

PubMed2003

Lung function interpolation by means of neural-network-supported analysis of respiration sounds.

Respiration sounds of individual asthmatic patients were analysed in the scope of the development of a method for computerised recognition of the degree of airways obstruction. Respiration sounds were recorded during laboratory sessions of allergen provoked airways obstruction, during several stages of advancing obstruction. The technique of artificial neural networks was applied for relating sound spectra and simultaneously measured lung function values (spirometry parameter FEV(1)). The ability of feedforward neural networks was tested to interpolate obstruction levels of FEV(1)-classes of which no members were included in the set used for training a network. In this way, a situation was simulated of an existing network recognising a new asthmatic attack under the same physiological conditions. It appeared to be possible to interpolate FEV(1) values, and it is concluded that a deterministic relationship exists between sound spectra and lung function parameter FEV(1). Variance optimisation appeared to be important in optimising the neural network configuration.

Asthma↗

PubMed1988

Effect of plasma protein binding on drug disposition in muscle tissue: application of statistical moment analysis and network theory to in situ local single-pass perfusion system.

The local disposition characteristics of mitomycin C (MMC) and five lipophilic prodrugs in rabbit hind leg muscle were examined using an in situ single-pass perfusion experiment. Test compounds inputted into a perfusion line as a rectangular function (unit pulse) were perfused with or without albumin and their outflow patterns were analyzed by statistical moment analysis. In interpretation of statistical moment parameters, the well-stirred model was applied to the local perfusion system based on the plate theory of a chromatographic system and some general pharmacokinetic parameters (the disposition parameters) were derived from the moments. A new theory which elucidates the relationships among the moments for plasma protein binding, unbound (free), and total drug fraction was established based on network theory. Using this system, the following conclusions were made for mitomycin C and its five lipophilic derivatives: (i) In the absence of albumin, an increase in lipophilicity led to an increase in organ clearance and distribution volume; (ii) drug bound to albumin did not transfer to the extravascular space; (iii) in the presence of albumin, an increase in lipophilicity results in a decrease in clearance.

Animals↗

PubMed2001

Attachment styles in older European American and African American adults.

OBJECTIVES: Differential attachment styles have been linked to differential emotion regulation and ability to cope with stress in samples of young adults. There are few data on attachment styles in older adults despite the fact that attachment relationships are said to play a significant role in psychological well-being throughout the life span. The goal of the study was to examine attachment patterns in older adults. METHODS: Participants were 800 community-dwelling older European Americans and African Americans (M = 74 years) living in a large urban community. Attachment measures included the family and friend intimacy subscales from the Network Analysis Profile and the Relationship Scales Questionnaire. RESULTS: In contrast to findings with younger individuals, where the majority of respondents have been found to be secure (i.e., comfortable with closeness and dependency), the majority of the present sample were found to be dismissing/avoidant (i.e., uncomfortable with closeness, compulsively self-reliant). European Americans scored higher than African Americans on attachment security, whereas African Americans scored higher than European Americans on dismissing attachment. However, the assessment of relatedness based on the Network Analysis Profile, where respondents named their closest kin, indicated that African Americans had higher scores than European Americans, though their networks were smaller. DISCUSSION: Age and ethnicity differences appear to reflect cohort effects related to the impact of economic hardship on families earlier this century and racial prejudice. The high rates of dismissing attachment and low rates of secure attachment in this large urban population suggest that these individuals may be at risk for social isolation and poor health as they become older and more frail.

Adaptation, Psychological↗

PubMed2006

Interpretation of metabolic flux maps by limitation potentials and constrained limitation sensitivities.

Two new concepts, "Limitation Potential" and "Constraint Limitation Sensitivity" are introduced that use definitions derived from metabolic flux analysis (MFA) and metabolic network analysis (MNA). They are applied to interpret a measured flux distribution in the context of all possible flux distributions and thus combine MFA with MNA. The proposed measures are used to quantify and compare the influence of intracellular fluxes on the production yield. The methods are purely based on the stoichiometry of the network and constraints that are given from irreversible fluxes. In contrast to metabolic control analysis (MCA), within this approach no information about the kinetic mechanisms are needed. A limitation potential (LP) is defined as the reduction of the reachable (theoretical) maximum by a measured flux. Measured fluxes that strongly narrow the reachable maximum are assumed to be limiting as the network has no ability to counterbalance the restriction due to the observed flux. In a second step, the sensitivity of the reduced maximum is regarded. This measure provides information about the necessitated changes to reach higher yields. The methods are applied to interpret the capabilities of a network based on measured fluxes for a L-phenylalanine producer. The strain was examined by a series of experiments and three flux maps of the production phase are analyzed. It can be shown that the reachable yield is drastically reduced by the measured efflux into the TCA cycle, while the oxidative pentose-phosphate pathway only plays a secondary role on the reachable maximum.

Carbon Isotopes↗

PubMed2026

Network pharmacology insights into the mechanistic basis of Taohe Chengqi Decoction in the treatment of constipation.

Constipation is a common gastrointestinal disorder associated with impaired motility, inflammation, and altered neuro-intestinal regulation. Taohe Chengqi Decoction, a classical prescription from Shang Han Lun, has been widely applied in the treatment of constipation, yet its pharmacological mechanisms remain insufficiently understood. We integrated systems pharmacology and network analysis to elucidate the therapeutic mechanisms of Taohe Chengqi Decoction against constipation. Active compounds and their putative targets were retrieved from traditional Chinese medicine systems pharmacology and PubChem, while constipation-related genes were collected from GeneCards and OMIM. Shared targets were identified and subsequently analyzed using STRING to construct a protein-protein interaction network. Hub proteins were ranked by degree centrality. A drug-disease-target network was built to map the interactions between Taohe Chengqi Decoction and constipation. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses were performed to uncover functional modules and signaling pathways. A total of 188 common targets were identified. Protein-protein interaction network analysis highlighted AKT1, interleukin-6 (IL6), IL1B, and JUN as hub proteins, suggesting central roles in regulating inflammation, apoptosis, and signal transduction. Additional nodes with high connectivity, such as caspase-3, PTGS2, signal transducer and activator of transcription 3, hypoxia-inducible factor-1α, estrogen receptor 1, and epidermal growth factor receptor, were implicated in apoptosis, oxidative stress, and transcriptional regulation. The drug-disease-target network revealed a dense and highly interconnected structure, reflecting the multicomponent, multi-target nature of Taohe Chengqi Decoction. Kyoto encyclopedia of genes and genomes enrichment indicated significant involvement of the advanced glycation end-product binding to their receptor signaling pathway, along with IL-17, TNF, and HIF-1 pathways, underscoring the contribution of inflammatory and oxidative stress-related processes. This study, based on computational pharmacology analysis, predicts that Taohe Chengqi Decoction may exert therapeutic effects on constipation through an integrated regulation involving multiple components, targets, and pathways. The potential mechanisms are likely associated with the modulation of inflammatory responses, apoptosis, and oxidative stress, with the advanced glycation end-product binding to their receptor signaling pathway possibly acting as a key mediator. These findings provide theoretical insights and future directions for elucidating the molecular mechanisms underlying the therapeutic effects of Taohe Chengqi Decoction against constipation.

Drugs, Chinese Herbal↗

PubMed1998

Analysis of quantitative EEG with artificial neural networks and discriminant analysis--a methodological comparison.

Artificial neural networks (ANN) are widely used to solve problems of differentiating between groups. However, serious comparisons of this method with the traditional procedure for such tasks (discriminant analysis) are rare. Discussing the results of both methods with the example of highly topical data, we try to demonstrate advantages and drawbacks of both methods. For this purpose, quantitative EEGs of 78 alcoholics were investigated in order to determine whether it is possible to predict relapse of these patients at the beginning of treatment. ANN software is available in Kassel (Institute for Computer Sciences and Mathematics).

Alcoholism↗

PubMed2006

A network-based analysis of polyanion-binding proteins utilizing yeast protein arrays.

The high affinity of certain cellular polyanions for many proteins (polyanion-binding proteins (PABPs)) has been demonstrated previously. It has been hypothesized that such polyanions may be involved in protein structure stabilization, stimulation of folding through chaperone-like activity, and intra- and extracellular protein transport as well as intracellular organization. The purpose of the proteomics studies reported here was to seek evidence for the idea that the nonspecific but high affinity interactions of PABPs with polyanions have a functional role in intracellular processes. Utilizing yeast protein arrays and five biotinylated cellular polyanion probes (actin, tubulin, heparin, heparan sulfate, and DNA), we identified proteins that interact with these probes and analyzed their structural and amino acid sequence requirements as well as their predicted functions in the yeast proteome. We also provide evidence for the existence of a network-like system for PABPs and their potential roles as critical hubs in intracellular behavior. This investigation takes a first step toward achieving a better understanding of the nature of polyanion-protein interactions within cells and introduces an alternative way of thinking about intracellular organization.

Amino Acid Sequence↗

PubMed2026

Lesion-specific oral microbiome signatures and predicted carcinogenic pathways in oral squamous cell carcinoma: a paired-site study in Pakistan.

BACKGROUND: Oral squamous cell carcinoma accounts for over 90% of oral neoplasms. Despite therapeutic advances, the lack of reliable, non-invasive biomarkers and delayed diagnosis continues to impede effective clinical management. By combining paired lesion and non-lesion sampling with predictive metagenomics analysis, our study addresses this gap and advances the current understanding of microbiome‒tumor interactions. METHODS: We analyzed 92 buccal swab samples from 39 OSCC patients and 14 healthy controls using 16S rRNA gene (V3-V4) sequencing. Taxonomic profiling was conducted using QIIME2 and SILVA/eHOMD databases, functional pathways were predicted using PICRUSt2, and hub taxa were identified through co-abundance network analysis. RESULTS: Microbial community structure differed significantly across lesion, non-lesion, and healthy sites (PERMANOVA, p = 0.001). Lesions were enriched with Selenomonas infelix and Treponema vincentii, while healthy controls harbored Streptococcus oralis and Gemella haemolysans. Co-abundance network analysis revealed lesion-specific hub species, notably T. vincentii, strongly correlated with predicted activation of pyrimidine biosynthesis pathways (r = 0.69, q < 1E-6), suggesting predicted metabolic alterations in the tumor microenvironment. Non-lesion sites were also characterized by two hub species, Prevotella melaninogenica and Segatella oulorum. CONCLUSION: Our findings define a lesion-specific microbial signature of OSCC characterized by the depletion of health-associated taxa, enrichment of pro-inflammatory pathobionts, and predicted associations with metabolic pathways implicated in carcinogenesis. These alterations reflect a predicted functionally altered tumor microenvironment.

16S rRNA gene↗

PubMed1995

Enhancing family advocacy networks: an analysis of the roles of sponsoring organizations.

Family participation in shaping system reforms in children's mental health has increased over the past ten years. In 1990 the National Institute of Mental Health funded the development and enhancement of 15 statewide advocacy organizations that were to be controlled and staffed by families of children who have serious emotional disorders. These family advocacy organizations had three major goals: to establish support networks, to advocate for service system reforms, and to develop statewide family advocacy networks. Seven family advocacy networks worked with sponsoring organizations because they needed assistance and/or could not receive funding directly. State and local chapters of the National Alliance for the Mentally Ill and the National Mental Health Association served in this capacity. Because there were no guidelines to educate sponsoring organizations about their interorganizational roles and responsibilities, staff of some sponsoring organizations used approaches that were supportive and effective, while staff in other organizations used methods that were counterproductive. The information and recommendations discussed in this paper are based on evaluation data and observations of the relationships between seven sponsoring organizations and family advocacy groups over a three-year period. This paper proposes a conceptual framework that includes: (1) a clear definition of the sponsoring organization's roles, and (2) an analysis of the advantages, limitations, and critical issues for the sponsoring organization.

Affective Symptoms↗

PubMed2026

Temporal proteomic analysis reveals a three-phase adaptation strategy in Phytophthora cinnamomi during salinity stress.

Phytophthora cinnamomi, a highly invasive hemibiotrophic oomycete, threatens global agriculture, forestry, and native ecosystems. Although drought and temperature effects on P. cinnamomi-host interactions are well studied, current knowledge of abiotic stress responses in P. cinnamomi remains largely centered on infection and phytopathology, with limited molecular insight into the pathogen's direct response to salinity independent of its host. To address this gap, we combined growth assays, time-resolved proteomics, and network analysis to define how P. cinnamomi responds and adapts to salinity exposure. Growth assays showed that NaCl-modified agar enhanced mycelial expansion in a concentration-dependent manner, with 100 mM NaCl significantly increasing growth at 48, 72, and 96 h compared with controls, while 50 mM NaCl remained comparable to control conditions. Temporal proteomic analysis of 100 mM NaCl treatment at 0, 1, 6, 12, and 24 h post treatment revealed dynamic shifts in protein abundance. Early induction of ROS (Reactive Oxygen Species)-detoxifying enzymes, including glutathione S-transferases and peroxidases, was consistent with ROS-specific staining assays. Network analysis identified modules enriched for redox regulation, ATP generation, ion transport, and translational control, highlighting multi-layered adaptation to elevated NaCl levels. Notably, clusters of conserved hypothetical proteins were strongly upregulated, indicating unexplored stress tolerance components in Phytophthora species. Here, we propose that P. cinnamomi rapidly activates a three-phase strategy involving metabolism readjustments, redox defenses, and cellular structure alterations under salinity conditions. With increasing soil salinization due to climate change, our study provides first mechanistic insights into P. cinnamomi's adaptive plasticity and ecological resilience to abiotic stress. SIGNIFICANCE: This study represents the first temporal proteomic analysis of salinity stress adaptation in Phytophthora cinnamomi, revealing a sophisticated three-phase adaptation strategy. This research fundamentally advances our understanding of how this globally destructive plant pathogen, P. cinnamomi, maintains environmental resilience. Our findings reveal proteome remodelling as a mechanistic framework for understanding stress tolerance in oomycetes, a group of microorganisms responsible for some of the world's most destructive agricultural and forest diseases. Our results show proteins involved in emergency damage control through metabolic recalibration to sustained adaptation. These findings have relevance for predicting pathogen behavior under climate change scenarios, where increasing soil salinity threatens agricultural productivity while simultaneously enhancing pathogen survival and virulence. Understanding how P. cinnamomi responds to prolonged salinity exposure may inform targeted biocontrol strategies and improve predictive models of disease pressure in salt-affected agricultural regions. The temporal analysis framework we present offers a broadly applicable approach for understanding microbial stress adaptation, with implications extending beyond plant pathology to environmental microbiology and biotechnology applications where stress tolerance is paramount.

Phytophthora↗

PubMed2026

Integrative Multiomics and Drug Sensitivity Profiling Reveal Potential Biomarkers and Therapeutic Strategies in Pediatric Solid Tumors.

UNLABELLED: Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors-such as high-risk group 3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas, and high-grade gliomas-and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities and biomarkers and to unravel molecular mechanisms associated with drug response profiles for clinical translation. In this study, we performed a multiomics analysis using drug sensitivity profiles, as well as genomic and transcriptomic data, of 81 pediatric solid tumor samples. The integrative analysis suggested two multiomics signatures associated with drug sensitivity. One signature distinguished neuroblastoma samples with sensitivity to navitoclax, a BCL2 family inhibitor. A second signature was specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation that displayed high expression of MGAM, PTPN14, STAT4, and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis suggested possible molecular interactions between MEK inhibitors and the SIX1 mutation in Wilms tumor samples. In conclusion, the integration of drug sensitivity profiling and multiomics data revealed potential biomarkers that may be associated with drug sensitivity in pediatric solid tumors. Patient-specific causal interaction network analysis further elucidated the interaction between inhibitors and signature biomarkers, providing insights that may inform clinical translation. SIGNIFICANCE: The combination of multiomics analysis and drug sensitivity profiling identified two signatures related to drug sensitivity in pediatric solid tumors, contributing to the advancement of functional precision medicine and personalized treatment strategies. This article is part of a special series: Driving Cancer Discoveries with Computational Research, Data Science, and Machine Learning/AI .

Humans↗

PubMed2026

Comprehensive analysis of mRNA-microRNA-lncRNA expression profiles in post-traumatic elbow heterotopic ossification using RNA sequencing and experimental validation.

BACKGROUND: This study aimed to profile the molecular signatures of post-traumatic elbow heterotopic ossification (HO) to identify key regulators and potential therapeutic targets. METHODS: Total RNA from post-traumatic elbow HO tissues (n=4) and normal bone tissues (n=6) was subjected to high-throughput sequencing to identify differentially expressed mRNAs (DEGs), microRNAs (DEMs), and lncRNAs (DELs). Bioinformatics analyses included Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, protein-protein interaction network construction, and transcription factor (TF)-microRNA-mRNA network analysis. The expression trends of four most upregulated and four most downregulated DEGs were validated by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR). RESULTS: We identified 2,138 DEGs, 40 DEMs, and 905 DELs. DEGs were significantly enriched in biological process "bone mineralization," cellular component "plasma membrane," molecular function "integrin binding," and pathways including PI3K-Akt, NF-κB, JAK-STAT, and TNF signaling pathways. Hub genes with high connectivity included MMP9, IL6, MMP3, CTSK, and BGLAP. Integrated network analysis highlighted the transcription factor JUN and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b). The qRT-PCR results confirmed the expression trends of selected DEGs. CONCLUSIONS: This study, for the first time, profiled the differentially expressed mRNAs, microRNAs, and lncRNAs in post-traumatic elbow HO using high-throughput RNA sequencing. These findings provide valuable insights into the molecular mechanisms of HO following elbow trauma. The identified hub genes (MMP9, IL6, MMP3, CTSK, and BGLAP), key TF (JUN), and key microRNAs (hsa-miR-124-3p, hsa-miR-548c-3p, and hsa-miR-135b) may serve as potential therapeutic targets for preventing and treating post-traumatic elbow HO.

Humans↗

PubMed2026

Polygenic risk score for neurodevelopmental disorders and cognitive impairment at long-term follow-up of first-episode psychosis.

BACKGROUND: One of the most outstanding contributions to the understanding of the etiopathogenesis of schizophrenia spectrum disorders (SSD) was the neurodevelopmental hypothesis. SSD and neurodevelopmental disorders (NDD) share pathogenetic mechanisms and overlapping clinical and cognitive impairment features. METHODS: We investigated whether polygenic risk scores (PRSs) for NDD are associated with cognitive performance in patients with first-episode psychosis (FEP). The sample comprised 127 patients with FEP who were followed up for a mean of 20.9 years. Cognitive examination was performed using the MoCA test at follow-up. Pearson coefficient correlations and multiple regression analyses were performed to examine the contribution of the three PRSs for rare neurodevelopmental conditions (PRSNDD), attention-deficit hyperactivity disorder (PRSADHD) and autism spectrum disorder (PRSASD) to cognitive impairment after allowing for the effect of covariates. Furthermore, we examined the interconnections between the PRS for NDD and cognitive impairment using network analysis (NA), including core premorbid variables. RESULTS: PRSNDD showed significant associations with impairment on visuospatial/executive, attention, and language MoCA subtests, after allowing for the influence of covariates. PRSNDD and PRSADHD, but not PRSASD, were significantly associated with worse performance on the total MoCA score. Moreover, in the network analysis, the relationships between PRSs for NDD and cognitive impairment were highly interconnected with premorbid variables and PRSs for schizophrenia and educational attainment. CONCLUSIONS: These results provide evidence for a possible direct genetic effect on cognitive performance for the PRS of common genetic variations related to neurodevelopment and attention deficit hyperactivity disorder in patients with FEP.

Cognitive impairment↗

PubMed1999

Modeling and simulation of the dynamic behavior of monoliths. Effects of pore structure from pore network model analysis and comparison with columns packed with porous spherical particles.

A mathematical model is presented that could be used to describe the dynamic behavior, scale-up, and design of monoliths involving the adsorption of a solute of interest. The value of the pore diffusivity of the solute in the pores of the skeletons of the monolith is determined in an a priori manner by employing the pore network modeling theory of Meyers and Liapis [J. Chromatogr. A, 827 (1998) 197 and 852 (1999) 3]. The results clearly show that the pore diffusion coefficient, Dmp, of the solute depends on both the pore size distribution and the pore connectivity, nT, of the pores in the skeletons. It is shown that, for a given type of monolith, the film mass transfer coefficient, Kf, of the solute in the monolith could be determined from experiments based on Eq. (3) which was derived by Liapis [Math. Modelling Sci. Comput., 1 (1993) 397] from the fundamental physics. The mathematical model presented in this work is numerically solved in order to study the dynamic behavior of the adsorption of bovine serum albumin (BSA) in a monolith having skeletons of radius r(o) = 0.75x10(-6) m and through-pores having diameters of 1.5x10(-6)-1.8x10(-6) m [H. Minakuchi et al., J. Chromatogr. A, 762 (1997) 135]. The breakthrough curves of the BSA obtained from the monolith were steeper than those from columns packed with porous spherical particles whose radii ranged from 2.50x10(-6) m to 15.00x10(-6) m. Furthermore, and most importantly, the dynamic adsorptive capacity of the monolith was always greater than that of the packed beds for all values of the superficial fluid velocity, Vtp. The results of this work indicate that since in monoliths the size of through-pores could be controlled independently from the size of the skeletons, then if one could construct monolith structures having (a) relatively large through-pores with high through-pore connectivity that can provide high flow-rates at low pressure drops and (b) small-sized skeletons with mesopores having an appropriate pore size distribution (mesopores having diameters that are relatively large when compared with the diameter of the diffusing solute) and high pore connectivity, nT, the following positive results, which are necessary for obtaining efficient separations, could be realized: (i) the value of the pore diffusion coefficient, Dmp, of the solute would be large, (ii) the diffusion path length in the skeletons would be short, (iii) the diffusion velocity, vD, would be high, and (iv) the diffusional response time, t(drt), would be small. Monoliths with such pore structures could provide more efficient separations with respect to (a) dynamic adsorptive capacity and (b) required pressure drop for a given flow-rate, than columns packed with porous particles.

Adsorption↗

PubMed2022

A graph-based approach for the visualisation and analysis of bacterial pangenomes.

BACKGROUND: The advent of low cost, high throughput DNA sequencing has led to the availability of thousands of complete genome sequences for a wide variety of bacterial species. Examining and interpreting genetic variation on this scale represents a significant challenge to existing methods of data analysis and visualisation. RESULTS: Starting with the output of standard pangenome analysis tools, we describe the generation and analysis of interactive, 3D network graphs to explore the structure of bacterial populations, the distribution of genes across a population, and the syntenic order in which those genes occur, in the new open-source network analysis platform, Graphia. Both the analysis and the visualisation are scalable to datasets of thousands of genome sequences. CONCLUSIONS: We anticipate that the approaches presented here will be of great utility to the microbial research community, allowing faster, more intuitive, and flexible interaction with pangenome datasets, thereby enhancing interpretation of these complex data.

Bacteria↗