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PubMed1990

Picture archiving and communication system design issues: the importance of modelling and simulation.

Picture archiving communication system (PACS) development turns out to be very complex. Due to both the vast amount of data and the complexity of hospital organizations, currently only small-scale systems have been realized. And although the experiences obtained with these systems are essential, there is a risk for underestimating the complexity and requirements inherent in hospital-wide PACS systems. In this paper, it is advocated that modelling and simulation be used as tools to obtain insight into the behavior and structure of future PACS systems. Modelling and simulation can also be used to actively support the design of PACS, especially its software. In order to capture the full complexity of PACS in a simulation model, and to take full advantage of simulation as a design tool, the development of a new modelling method has begun. This method is based on semantic data models and decision processes, and can be used for both system analysis and design. The first systems modelled with this method were imaging procedures in a hospital and a computer network. The resulting simulation models are a direct reflection of reality, and have a high degree of modularity. Consequently, in spite of the complexity of the systems, their models are easy to understand and maintain.

Computer Simulation↗

PubMed1977

Heterogeneity of the kinetoplast DNA molecules of Trypanosoma cruzi.

Kinetoplast DNA (kDNA) of the culture form of Trypanosoma cruzi is cleaved by restriction endonucleases (HpaII, HindII, EcoRI, and HaeIII). The analysis of the cleavage patterns proves that the minicircles (free circulargenome units) are heterogeneous in base sequences. The same results are obtained with the complex kDNA network which is composed of the association of minicircles and linear molecules. Kinetic studies of the renaturation of kDNA previously cleaved by HpaII into fragments of the genome unit size show at least two populations of molecules. About 75% of these molecules correspond to the fast renaturing population having the molecular complexity of the minicircles. The molecules of the slow renaturing population have a much higher molecular complexity than the minicircles and do not seem to be related to the majority of the long linear molecules.

Chemical Phenomena↗

PubMed1979

Health-seeking behavior and social networks of the aged living in single-room occupancy hotels.

The elderly who reside in single-room occupancy (SRO) hotels often have been depicted as "isolates," lacking the interest or ability to engage primary or secondary support systems. This characterization has not enhanced understanding of how the SRO aged are able to survive in the community. With the use of network analysis techniques, this study demonstrates the inaccuracy of the assertion that these old persons lack significant social support. The data pointed to differences in network size, complexity, intensity, connectedness, and directionality in relation to varying degrees of physical and psychiatric health.

Aged↗

PubMed1979

[Quantitation of myelofibrosis in blood diseases by electronic image analysis (author's transl)].

Normal and pathologic reticulin networks colored black by silver nitrate can be automatically quantitated by electronic image analysis. By using this technique, different parameters can be obtained, such as the average density, the surface of network meshes, the thickness of the fibers, the complexity of the reticulum, and the heterogeneity of the myelofibrosis distribution. All of these parameters were obtained in 83 osteomedullar biopsies of blood diseases (primary splenomegaly, chronic myeloid leukemia, polycythermia vera, acute leukemia, and aplastic anemia). We have shown that there is no relation between the different parameters obtained and the medullary richness, hematopoietic center, or patient survival. On the other hand, the histomorphometric parameters can be used to distinguish acute leukemia and chronic myeloid leukemia myelofibrosis, while the parameters in primary splenomegaly are shown to be very heterogeneous.

Acute Disease↗

PubMed1992

Isolated cells in the study of the molecular mechanisms of reperfusion injury.

Isolated cells make it possible to study mechanisms of cell and tissue injury under well-defined conditions, including the interaction of different cells in coculture experiments. Isolated cells, either in suspension or in monolayer cultures, have also been used to study the mechanism of reperfusion injury--in this case better termed as reoxygenation injury in view of the experimental approach taken. In hepatocytes, Kupffer, and endothelial cells, reoxygenation injury resulted in necrosis primarily mediated by reactive oxygen species released by various sources such as mitochondria (hepatocytes) and NADPH oxidase (Kupffer cells). In contrast, contracture was a characteristic feature of reoxygenation injury occurring in cardiomyocytes without loss of cytosolic enzymes. Beside reactive oxygen species, Kupffer cells were activated to release prostanoids and a decrease in endothelial cell-mediated fibrinolysis occurred upon reoxygenation. Reoxygenation injury in endothelial cells was significantly increased when neutrophils were added at the time of reoxygenation, presumably due to additional generation of reactive oxygen species and the release of proteases. As exemplified for the liver, these experiments suggest a mechanism of reperfusion injury in which the various cell types of a given tissue differ significantly in their response to hypoxia-reoxygenation but in which they interact with each other in a complex pathobiochemical network via various mediators such as cytokines, and tissue damaging effector molecules such as reactive oxygen species. Future experiments with isolated cells will allow detailed analysis of the underlying molecular mechanisms.

Cells, Cultured↗

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↗

PubMed2025

FACS-Proteomics strategy toward extracellular vesicles single-phenotype characterization in biological fluids: exploring the role of leukocyte-derived EVs in multiple sclerosis.

BACKGROUND: The isolation and proteomics characterization of extracellular vesicles (EVs) from body fluids is challenging due to their vast heterogeneity. We have recently demonstrated that Fluorescence-activated Cell Sorting (FACS) efficiently isolates the whole EV circulating compartment directly from untouched body fluids enabling a comprehensive EV proteomics analysis. RESULTS: Here, we characterized, for the first time, a single-phenotype EV subset by sorting leukocyte-derived EVs (Leuko EVs) from peripheral blood and tears of healthy volunteers. Using an optimized and patented staining protocol of the whole EV compartment we identified and excluded non-EV particles, debris and damaged EVs. We further isolated, using an anti-CD45 antibody, Leuko EVs (CD45+ EVs), reaching a high level of purity (> 90%). Purified Leuko EVs were characterized using atomic force microscopy, nanoparticle tracking, and shotgun proteomics analysis revealing a similar coded protein cargo in both biological fluids. Subsequently, the same workflow was applied to tears from Relapsing-Remitting Multiple Sclerosis (RRMS) patients, revealing a Leuko EVs protein cargo enrichment that reflects the neuroinflammatory condition characteristics of RRMS. This enrichment was evidenced by the activation of upstream regulators TGFB1 and NFE2L2, which are associated with inflammatory responses. Additionally, the analysis identified markers indicative of endothelial cell proliferation and the development of enhanced vascular networks, with AGNPT2 and VEGF emerging as activated upstream regulators. These findings indicate the complex interplay between inflammation and angiogenesis in RRMS. CONCLUSIONS: In conclusion, our combined FACS-Proteomics strategy offers a promising approach for biomarker discovery, analysing cell-specific EV phenotypes directly from untouched body fluids, advancing the clinical value of tears EVs and improving the understanding of EV-mediated processes in vivo. Data are available via ProteomeXchange with the identifier PXD049036 and in EV-TRACK knowledgebase with ID: EV240150.

Humans↗

PubMed2026

Genes associated with translation and oxidative phosphorylation as components of the translational response in nodulated and water-restricted soybean.

BACKGROUND: Soybean primarily acquires nitrogen through symbiosis with nitrogen-fixing bacteria. Water deficit (WD) is a major stress limiting crop yield. Nodulation may enhance drought tolerance in legumes by modulating nitrogen and hormone metabolism, osmotic adjustment, and antioxidant defenses; however, the molecular basis underlying the differential WD responses between N-fix and N-fed plants remain unclear. Translational control of gene expression is a key regulatory mechanism during stress. RESULTS: We compared the transcriptome and translatome of soybean roots from N-fix and N-fed plants exposed to WD across four combined treatments. N-fix plants under WD exhibited more complex responses in terms of total differentially expressed genes (DEGs) compared to N-fed plants. This increased complexity was also evident among translationally regulated DEGs and differentially expressed transcription factors, whose involvement in WD responses of N-fix plants is novel. Co-expression network analysis identified modules associated with core biological processes encompassing nodulation, WD, and notably, their interplay was particularly prominent in Module 1, which was enriched in genes related to ribosomal protein synthesis and oxidative phosphorylation (OXPHOS). Guilt-by-Association analysis enabled the prediction of novel functions for differentially expressed, uncharacterized hub genes related to stress and/or nodulation responses. CONCLUSIONS: Translational regulation of genes involved in OXPHOS and translation initiation emerged as a central response in N-fix plants under WD. These findings reveal distinct molecular adaptations in N-fix soybean roots facing WD and highlight translational control as a key regulatory layer. We also identified promising candidate genes-including transcription factors and uncharacterized hub genes under translational regulation-that represent potential targets for improving drought tolerance in legumes once validated functionally.

Glycine max↗

PubMed2025

Target and biomarker exploration portal for drug discovery.

MOTIVATION: The discovery of novel drug targets and precision biomarkers remains a major challenge in drug development, with traditional differential expression analysis often overlooking key regulatory proteins. Here, we present a novel, web-based bioinformatics tool, the Target and Biomarker Exploration Portal (TBEP), designed to accelerate the drug discovery process by integrating large-scale biomedical data with network analysis techniques. RESULTS: TBEP harnesses machine-learning approaches to mine and combine multimodal datasets, including human genetics, functional genomics, and protein-protein interaction networks, to decode causal disease mechanisms and uncover novel therapeutic targets and precision biomarkers for specific phenotypes. A unique feature of the tool is its ability to process large-scale data in real-time, facilitated by an efficient cloud-based architecture. Additionally, the tool incorporates an integrated large language model (LLM), which assists researchers in exploring and interpreting complex biological relationships within the generated networks and multi-omics data using natural language (English). By offering an intuitive, interactive interface, the LLM enhances the exploration of biological insights, making it easier for scientists to derive actionable conclusions. This powerful integration of network analysis, multi-omics data, and LLM provides a robust framework for accelerating the identification of novel drug targets. AVAILABILITY AND IMPLEMENTATION: The tool is publicly available at https://tbep.missouri.edu. The source code, documentation and installation instructions are available at GitHub repository: https://github.com/mizzoudbl/tbep.

Drug Discovery↗

PubMed2025

GE-IA-NAM: gene-environment interaction analysis via imaging-assisted neural additive model.

MOTIVATION: Gene-environment (G-E) interaction analysis is crucial in cancer research, offering insights into how genetic and environmental factors jointly influence cancer outcomes. Most existing G-E interaction methods are regression-based, which may lack flexibility to capture complex data patterns. Recent advances have investigated deep neural network-based G-E models. However, these methods may be more vulnerable to information deficiency due to challenges such as limited sample size and high dimensionality. Apart from genetic and environmental data, pathological images have emerged as a widely accessible and informative resource for cancer modeling, presenting its potential to enhance G-E modeling. RESULTS: We propose the pathological imaging-assisted neural additive model for G-E analysis (GE-IA-NAM). The flexible and interpretable additive network architecture is adopted to account for individualized effects associated with genetic factors, environmental factors, and their interactions. To improve G-E modeling, an assisted-learning strategy is investigated, which adopts a joint analysis to integrate information from pathological images. Simulations and the analysis of lung and skin cancer datasets from The Cancer Genome Atlas demonstrate the competitive performance of the proposed method. AVAILABILITY AND IMPLEMENTATION: Python code implementing the proposed method is available at https://github.com/Mr-maoge/NAM-IA-GE. The data that support the findings in this article are openly available in TCGA (The Cancer Genome Atlas) at https://portal.gdc.cancer.gov/.

Gene-Environment Interaction↗

PubMed1992

Evolution of the capsid protein genes of foot-and-mouth disease virus: antigenic variation without accumulation of amino acid substitutions over six decades.

The genetic diversification of foot-and-mouth disease virus (FMDV) of serotype C over a 6-decade period was studied by comparing nucleotide sequences of the capsid protein-coding regions of viruses isolated in Europe, South America, and The Philippines. Phylogenetic trees were derived for VP1 and P1 (VP1, VP2, VP3, and VP4) RNAs by using the least-squares method. Confidence intervals of the derived phylogeny (significance levels of nodes and standard deviations of branch lengths) were placed by application of the bootstrap resampling method. These procedures defined six highly significant major evolutionary lineages and a complex network of sublines for the isolates from South America. In contrast, European isolates are considerably more homogeneous, probably because of the vaccine origin of several of them. The phylogenetic analysis suggests that FMDV CGC Ger/26 (one of the earliest FMDV isolates available) belonged to an evolutionary line which is now apparently extinct. Attempts to date the origin (ancestor) of the FMDVs analyzed met with considerable uncertainty, mainly owing to the stasis noted in European viruses. Remarkably, the evolution of the capsid genes of FMDV was essentially associated with linear accumulation of silent mutations but continuous accumulation of amino acid substitutions was not observed. Thus, the antigenic variation attained by FMDV type C over 6 decades was due to fluctuations among limited combinations of amino acid residues without net accumulation of amino acid replacements over time.

Amino Acid Sequence↗

PubMed1992

Parallel distributed processing and neuropsychology: a neural network model of Wisconsin Card Sorting and verbal fluency.

Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.

Attention↗

PubMed1992

Heat shock-induced redistribution of a 160-kDa nuclear matrix protein.

In this paper we describe a 160-kDa protein (p160) which is present in the nuclear matrix of rat, mouse, and human cells. Biochemical and ultrastructural analysis shows that p160 is associated with the internal matrix and is not present in the lamina-pore complex. Immunoelectron microscopy shows that the protein is part of the extranucleolar, fibrogranular network of the nuclear matrix. During an in vivo 42 degrees C heat treatment of HeLa cells, A431 human epidermoid cells, and T24 human bladder carcinoma cells, p160 transiently formed large clusters inside the nucleus. These p160 clusters are associated with the nuclear matrix network, as judged by immunolabeling on isolated nuclear matrices. The percentage of cells showing p160 clusters increased proportionally with longer heat treatments, reaching a maximum after a period of 3 h. At this time 70 +/- 5% of the cells displayed these clusters. Clustering decreased after longer heat treatments and the anti-p160 staining pattern became diffuse granular again. Other nuclear components, such as the A1 antigen of hnRNP (ribonucleoprotein), the Sm antigen of snRNPs, and lamins A and C, did not cluster during the 42 degrees C treatment, indicating that this reallocation is characteristic for the p160 matrix protein. These results demonstrate that p160 is an internal nuclear matrix element with a dynamic spatial distribution.

Animals↗

PubMedDate not supplied

PACS workstation design.

This paper covers some of the recent concepts in designing a digital imaging workstation in a multimodality Picture Archiving and Communications Systems (PACS) network. A workstation in a multimodality PACS network must access, display, and analyze digital images from different imaging modalities with very different formats. The user interface should allow clinicians with minimal or no computer manipulation skills to use complex analysis tools. General guidelines of a graphics oriented user interface, based on windows and icons, are proposed. Instantaneous (real-time) response in the primary display and processing functions is vital for user acceptance. The hardware architectural concepts to achieve such a performance speed are described. Finally, a workstation environment conducive to comfortable viewing by the radiologists is discussed.

Computer Graphics↗

PubMed2026

Genome-wide characterization of the tomato PERK gene family and its expression profiling under abiotic stresses.

UNLABELLED: This study presents the first systematic genome-wide characterization of the proline-rich extensin-like receptor kinases (PERK) gene family in tomato (Solanum lycopersicum) and their transcriptional responses under abiotic stresses. Using the latest SL4.0/ITAG4.0 genome assembly, we identified six SlPERK genes, all harboring the conserved Ser/Thr protein kinase domain. Evolutionary and structural analyses revealed strong purifying selection (Ka/Ks < 1), distinct exon-intron organizations, and the presence of stress- and hormone-responsive cis-regulatory elements in their promoters. Furthermore, post-transcriptional regulation by 57 miRNAs and complex protein-protein interaction networks were predicted. To validate their stress-responsive roles, two tomato cultivars (GMOTL-1 and Roma) were subjected to cold, heat, and salinity treatments. Quantitative RT-PCR analysis revealed cultivar-specific expression dynamics: SlPERK4 exhibited strong transient induction under cold and heat stress, while SlPERK6 was highly responsive to salinity. Notably, the GMOTL-1 cultivar displayed significantly higher and broader stress-responsive expression profiles compared to Roma, indicating a potential role of these SlPERK genes in cultivar-specific stress tolerance. These findings provide a comprehensive genomic resource and establish a critical foundation for the functional validation and molecular breeding for stress-resilience tomato cultivars. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13205-026-05044-y.

Abiotic stress↗

PubMed2025

Integrating explainable artificial intelligence with multiomics systems biology and electronic health record data mining for personalized drug repurposing in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by region- and patient-specific molecular heterogeneity, which hinders therapeutic design. In this study, we introduce PRISM-ML (PRecision-medicine using Interpretable Systems and Multiomics with Machine Learning), an open-source integrated analysis pipeline that combines interpretable machine learning with systems biology and electronic health records data mining to elucidate the molecular diversity of AD and predict promising drug repurposing opportunities. First, we integrated and harmonized transcriptomic (bulk RNA-seq) and genomic (genome-wide association study) data from 2105 brain samples, each with matched data from the same individual (1363 AD patients, 742 controls; 9 tissues), sourced from three independent studies. Random forest classifiers with SHapley Additive exPlanations identified patient-specific biomarkers; unsupervised clustering resolved 36 molecularly distinct subtissues (defined as clusters of samples within a brain tissue that share a specific expression pattern); and gene-gene coexpression networks prioritized 262 high-centrality bottleneck genes as putative regulators of dysregulated pathways. Next, knowledge graph-based drug repurposing predicted six Food and Drug Administration (FDA)-approved drugs that simultaneously target multiple bottleneck genes and multiple AD-relevant pathways. Notably, in a large US de-identified insurance-claims database (n = 364 733), exposure to promethazine, one of the candidate drugs, was associated with a 57%-62% lower incidence of AD versus an active antihistamine comparator (adjusted hazard ratio 0.38; inverse-probability weighted 0.43; both P < .001), providing real-world support for its repurposing potential. In summary, PRISM-ML, as an explainable multiomics analysis pipeline, is readily transferable to other complex diseases, advancing precision medicine.

Alzheimer Disease↗

PubMed2026

Bayesian Genome-Wide Association Study of Feed Efficiency Traits in Pigs.

Feed efficiency traits are increasingly important in pig production for improving profitability and environmental sustainability. Understanding their genetic basis is crucial for uncovering underlying biological mechanisms and informing selection strategies. In this study, we analyzed residual feed intake (RFI), feed conversion ratio (FCR), and average daily feed intake (ADFI) in 201 animals. Three separate Bayesian GWASs were conducted using 29,844 SNPs in a case-control design, with the lowest and highest 15% of the phenotypic distribution selected as controls and cases (N = 30 per group), respectively, for each trait. The results confirmed the polygenic nature of the traits, identifying 4 SNPs for RFI on Sus scrofa chromosomes (SSC) 3, 13, and 15 with high posterior probability for the direction of their effects; 4 SNPs for FCR on SSC 8, 14, and 17; and 8 SNPs for ADFI on SSC 1, 2, 6, 8, and 11. A candidate gene search identified 41 potential genes involved in diverse biological processes, including feed efficiency, intestinal development, tissue remodeling and integrity, nutrient transport and absorption, metabolic homeostasis, cellular signaling, energy sensing, and neurological regulation. These genes formed a highly interconnected network, highlighting the complexity of feed efficiency and the interplay among multiple physiological, metabolic, and regulatory pathways.

Bayesian analysis↗

PubMed2026

Emergence and phylogeography of the dengue vector Aedes aegypti in Southeastern Iran.

BACKGROUND: Aedes (Stegomyia) aegypti (Linnaeus) is the primary vector of dengue, chikungunya, Zika, and yellow fever viruses. Its recent detection in southeastern Iran raises public health concerns about arbovirus spread to new regions. This study provides the first genetic and phylogeographic analysis of Ae. aegypti populations from Sistan and Baluchistan Province (SBP), Iran, to infer their origin and invasion pathways. METHODS: Mitochondrial COI and ND4 genes were analysed in newly collected Ae. aegypti specimens from border areas, ports, and urban centres of SBP. Haplotype network analyses were constructed using the TCS method in PopART, and phylogenetic analyses were conducted using global reference sequences. RESULTS: Iranian specimens comprised 7 COI haplotypes (n = 18) and 10 ND4 haplotypes (n = 17). COI phylogeny placed Iranian specimens into two main clades, while ND4 analysis distributed them across several derived clades, mostly clustering with lineages from Latin America (Brazil, Mexico) or Africa. One Iranian specimen showed a close relationship with a Saudi Arabian sequence (bootstrap: 98%) near the basal region. Combined COI + ND4 analysis revealed a monophyletic clade of Iranian specimens with a Sri Lankan specimen, distinct from other global lineages. The global COI network (n = 47) showed a star-like topology with a dominant haplotype 1 shared among 10 Iranian specimens. The ND4 network (n = 31) revealed a complex topology with 18 haplotypes, where a Saudi Arabian and one Iranian specimen (~30 mutational steps) possibly represented the peripheral root. CONCLUSIONS: Detection of diverse Ae. aegypti clades confirm establishment of this vector in southeastern Iran. Results support multiple introductions and genetic connectivity with Latin America, Africa, and South Asia, pointing to an emerging invasion corridor. Continued genomic surveillance and integrated vector monitoring are urgently needed to guide prevention strategies.

Animals↗