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Five cases of patients with systemic connective tissue diseases (CTD) who developed connective tissue disease-associated interstitial lung disease (CTD-ILD) with progressive pulmonary fibrosis (PPF) are reported here. Unspecified ILD was diagnosed using high-resolution computed tomography (HRCT). Histologically, all cases were usual interstitial pneumonia (UIP) with findings of advanced (3/5) to diffuse (2/5) fibrosis, with a partially (4/5) to completely (1/5) formed image of a honeycomb lung. The fibrosis itself spread subpleurally and periseptally to more central parts (2/5) of the lung, around the alveolar ducts (2/5), or even without predisposition (1/5). Simultaneously, there was architectural reconstruction based on the mutual fusion of fibrosis without compression of the surrounding lung parenchyma (1/5), or with its compression (4/5). The whole process was accompanied by multifocal (1/5), dispersed (2/5), or organized inflammation in aggregates and lymphoid follicles (2/5). As a result of continuous fibroproduction and maturation of the connective tissue, the alveolar septa thickened, delimiting groups of alveoli that merged into air bullae. Few indistinctly visible (2/5), few clearly visible (1/5), multiple indistinctly visible (1/5), and multiple clearly visible (1/5) fibroblastic foci were present. Among the concomitant changes, areas of emphysema, bronchioloectasia, and bronchiectasis, as well as bronchial and vessel wall hypertrophy, and mucostasis in the alveoli and edema were observed. The differences in the histological appearance of usual interstitial pneumonia associated with systemic connective tissue diseases (CTD-UIP) versus the pattern associated with idiopathic pulmonary fibrosis (IPF-UIP) are discussed here. The main differences lie in spreading lung fibrosis, architectural lung remodeling, fibroblastic foci, and inflammatory infiltrates.
- MeSH
- dospělí MeSH
- idiopatická plicní fibróza patologie komplikace MeSH
- intersticiální plicní nemoci * patologie komplikace MeSH
- lidé středního věku MeSH
- lidé MeSH
- nemoci pojiva * patologie komplikace MeSH
- plíce patologie diagnostické zobrazování MeSH
- počítačová rentgenová tomografie MeSH
- senioři MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- kazuistiky MeSH
PURPOSE: Fuchs endothelial corneal dystrophy (FECD) is a common, age-related cause of visual impairment. This systematic review synthesizes evidence from the literature on artificial intelligence (AI) models developed for the diagnosis and management of FECD. METHODS: We conducted a systematic literature search in MEDLINE, PubMed, Web of Science, and Scopus from January 1, 2000, to June 31, 2024. Full-text studies utilizing AI for various clinical contexts of FECD management were included. Data extraction covered model development, predicted outcomes, validation, and model performance metrics. We graded the included studies using the Quality Assessment of Diagnostic Accuracies Studies 2 tool. This review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) recommendations. RESULTS: Nineteen studies were analyzed. Primary AI algorithms applied in FECD diagnosis and management included neural network architectures specialized for computer vision, utilized on confocal or specular microscopy images, or anterior segment optical coherence tomography images. AI was employed in diverse clinical contexts, such as assessing corneal endothelium and edema and predicting post-corneal transplantation graft detachment and survival. Despite many studies reporting promising model performance, a notable limitation was that only three studies performed external validation. Bias introduced by patient selection processes and experimental designs was evident in the included studies. CONCLUSIONS: Despite the potential of AI algorithms to enhance FECD diagnosis and prognostication, further work is required to evaluate their real-world applicability and clinical utility. TRANSLATIONAL RELEVANCE: This review offers critical insights for researchers, clinicians, and policymakers, aiding their understanding of existing AI research in FECD management and guiding future health service strategies.
- MeSH
- Fuchsova endoteliální dystrofie * diagnóza terapie MeSH
- lidé MeSH
- optická koherentní tomografie metody MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- systematický přehled MeSH
Digital transformation is widely understood as a process where technology is used to modify an organization's products and services and to create new ones. It is rapidly advancing in all sectors of society. Researchers have shown that it is a multidimensional process determined by human decisions based on ideologies, ideas, beliefs, goals, and the ways in which technology is used. In health care and health, the end result of digital transformation is digital health. In this study, a detailed literature review covering 560 research articles published in major journals was performed, followed by an analysis of ideas, beliefs, and goals guiding digital transformation and their possible consequences for privacy, human rights, dignity, and autonomy in health care and health. Results of literature analyses demonstrated that from the point of view of privacy, dignity, and human rights, the current laws, regulations, and system architectures have major weaknesses. One possible model of digital health is based on the dominant ideas and goals of the business world related to the digital economy and neoliberalism, including privatization of health care services, monetization and commodification of health data, and personal responsibility for health. These ideas represent meaningful risks to human rights, privacy, dignity, and autonomy. In this paper, we present an alternative solution for digital health called human-centric digital health (HCDH). Using system thinking and system modeling methods, we developed a system model for HCDH. It uses 5 views (ideas, health data, principles, regulation, and organizational and technical innovations) to align with human rights and values and support dignity, privacy, and autonomy. To make HCDH future proof, extensions to human rights, the adoption of the principle of restricted informational ownership of health data, and the development of new duties, responsibilities, and laws are needed. Finally, we developed a system-oriented, architecture-centric, ontology-based, and policy-driven approach to represent and manage HCDH ecosystems.
- MeSH
- digitální technologie MeSH
- digitální zdraví * MeSH
- lidé MeSH
- lidská práva MeSH
- péče orientovaná na pacienta * MeSH
- soukromí MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
Neurons rely on the microtubule cytoskeleton to create and maintain their sophisticated cellular architectures. Advances in cryogenic electron microscopy, expansion microscopy, live imaging, and gene editing have enabled novel insights into mechanisms of centrosomal and acentrosomal microtubule nucleation, the key process generating new microtubules. This has paved the way for the functional dissection of distinct microtubule networks that regulate various processes during neuronal development, including neuronal delamination, polarization, migration, maturation, and synapse function. We review recent progress in understanding the molecular concepts of microtubule nucleation, how these concepts underlie neurodevelopmental processes, and pinpoint the open questions. Since microtubules play a pivotal role in axon regeneration within the adult central nervous system, understanding the processes of microtubule nucleation could inform strategies to enhance the regenerative capabilities of neurons in the future.
- MeSH
- centrozom * metabolismus fyziologie MeSH
- lidé MeSH
- mikrotubuly * metabolismus fyziologie MeSH
- neurogeneze * fyziologie MeSH
- neurony * fyziologie metabolismus MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
INTRODUCTION: Warthin's tumour (WT) is the second most common salivary gland neoplasm. With classic cytomorphological features of WT, the diagnostic accuracy is over 95%. WT is usually categorized as benign neoplasm according to the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC). METHODS: Database search at the Department of Pathology, Fimlab Laboratories, Tampere, Finland, revealed 146 WTs during a 10-year period (January 1, 2013-December 31, 2022). Diagnostic accuracy was calculated for the entire study period, and the study period divided in half to pre-MSRSGC years (2013-2017) and MSRSGC years (2018-2022). In addition, a separate cytomorphology analysis of false-negative cases that were classified according to the MSRSGC was performed. RESULTS: Diagnostic accuracy was 96.4%, sensitivity was 68.5%, and specificity was 99.8%. Sensitivities and specificities were almost equal during the pre-MSRSGC years and the MSRSGC years. The number of true-positive cases was 113. Fifty-five cases (52 false-negative and 3 false-positive cases) were not accurately diagnosed. Risk of malignancy and risk of neoplasm were 0.0% and 98.3% of cases that were cytologically diagnosed as WT. Cytomorphological analysis showed that lack of papillae, the presence of small groups, and cystic degeneration led to false diagnoses. In addition, necrosis and diffuse hypercellularity increased the suspicion of malignancy and led to classification of fine-needle aspirations as salivary gland neoplasm of uncertain malignant potential. CONCLUSION: The MSRSGC is useful in WT diagnostics, and it improves communication between cytopathologists and clinicians. In this study, the most useful cytomorphological feature that led to accurate WT diagnoses was papillary architecture in cell block specimens and the most significant pitfall was necrosis followed by diffuse hypercellularity.
- MeSH
- adenolymfom * patologie diagnóza MeSH
- dospělí MeSH
- falešně negativní reakce MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- nádory slinných žláz * patologie diagnóza MeSH
- prediktivní hodnota testů MeSH
- reprodukovatelnost výsledků MeSH
- retrospektivní studie MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- tenkojehlová biopsie MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mladiství MeSH
- mladý dospělý MeSH
- mužské pohlaví MeSH
- senioři nad 80 let MeSH
- senioři MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
Alzheimer's disease (AD), a leading cause of dementia worldwide, is a multifactorial neurodegenerative disorder characterized by amyloid-beta plaques, tauopathy, neuronal loss, neuro-inflammation, brain atrophy, and cognitive deficits. AD manifests as familial early-onset (FAD) with specific gene mutations or sporadic late-onset (LOAD) caused by various genetic and environmental factors. Numerous transgenic rodent models have been developed to understand AD pathology development and progression. The TgF344-AD rat model is a double transgenic model that carries two human gene mutations: APP with the Swedish mutation and PSEN-1 with delta exon 9 mutations. This model exhibits a complete repertoire of AD pathology in an age-dependent manner. This review summarizes multidisciplinary research insights gained from studying TgF344-AD rats in the context of AD pathology. We explore neuropathological findings; electrophysiological assessments revealing disrupted synaptic transmission, reduced spatial coding, network-level dysfunctions, and altered sleep architecture; behavioral studies highlighting impaired spatial memory; alterations in excitatory-inhibitory systems; and molecular and physiological changes in TgF344-AD rats emphasizing their age-related effects. Additionally, the impact of various interventions studied in the model is compiled, underscoring their role in bridging gaps in understanding AD pathogenesis. The TgF344-AD rat model offers significant potential in identifying biomarkers for early detection and therapeutic interventions, providing a robust platform for advancing translational AD research. Key words Alzheimer's disease, Transgenic AD models, TgF344-AD rats, Spatial coding.
- MeSH
- Alzheimerova nemoc * genetika patologie metabolismus MeSH
- amyloidový prekurzorový protein beta genetika metabolismus MeSH
- krysa rodu rattus MeSH
- lidé MeSH
- modely nemocí na zvířatech * MeSH
- mozek patologie metabolismus MeSH
- potkani inbrední F344 MeSH
- potkani transgenní * MeSH
- presenilin-1 genetika MeSH
- zvířata MeSH
- Check Tag
- krysa rodu rattus MeSH
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
The collection on Methods and Models in Mammary Gland Biology and Breast Cancer Research showcases recent advances in tools and models that enhance our understanding of mammary gland development and breast cancer. This collection includes sixteen articles, collectively addressing approaches to investigate key aspects of mammary gland biology and tumorigenesis, including hormonal signaling, tissue architecture, tumor microenvironment, and species-specific mammary development. The issue highlights innovations such as optimized progesterone receptor reporters, improved menopause models, and 3D-printed mammary epithelial structures. It also features advancements in organoid-based studies, in situ labeling of epithelial proliferation in large animals, preclinical models for breast cancer prevention, and high-resolution imaging techniques. Methodologies for studying macrophage-cancer cell interactions and lysosomal function are provided as step-by-step protocols. Additionally, review articles provide insights into diverse mammalian organoid systems, rat mammary tumor models, and strategies for modeling breast cancer metastasis. Together, these contributions advance mammary gland research by refining experimental approaches, expanding model diversity, and fostering translational applications in breast cancer.
- MeSH
- lidé MeSH
- mléčné žlázy lidské * patologie růst a vývoj fyziologie MeSH
- mléčné žlázy zvířat * patologie růst a vývoj fyziologie MeSH
- modely nemocí na zvířatech MeSH
- nádorové mikroprostředí fyziologie MeSH
- nádory prsu * patologie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- zvířata MeSH
- Publikační typ
- úvodní články MeSH
- úvodníky MeSH
Diet, stress, genetics, and a sedentary lifestyle may all contribute to heart disease rates. Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more complete approach that considers all of these factors can improve the efficiency of a cardiac prediction system. This study uses an appropriate strategy to overcome potential network design problems, design challenges, overfitting, and lack of robustness that can interfere with system performance. The research introduces an ideally designed deep trust network called ID-DTN to improve system performance. The Ruzzo-Tompa method is used to eliminate noncontributory features. The Seagull Optimization Algorithm (SOA) is introduced to optimize the trust depth network to achieve optimal network design. The study scrutinizes the deep trust network (ID-DTN) and the restricted Boltzmann machine (RBM) and sheds light on the system's operation. This proposal can optimize both network architecture and feature selection, which is the main novelty. The proposed method is analyzed using the below-mentioned metrics: Matthew's correlation coefficient, F1 score, accuracy, sensitivity, specificity, and accuracy. ID-DTN performs well compared to other state-of-the-art methods. The validation results confirm that the proposed method improves the prediction accuracy to 97.11% and provides reliable recommendations for patients with cardiovascular disease.
- MeSH
- algoritmy * MeSH
- lidé MeSH
- nemoci srdce * diagnóza MeSH
- neuronové sítě MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
OBJECTIVE: Idiopathic inflammatory myopathies (IIMs, myositis) are rare systemic autoimmune disorders that lead to muscle inflammation, weakness, and extramuscular manifestations, with a strong genetic component influencing disease development and progression. Previous genome-wide association studies identified loci associated with IIMs. In this study, we imputed data from two prior genome-wide myositis studies and analyzed the largest myositis data set to date to identify novel risk loci and susceptibility genes associated with IIMs and its clinical subtypes. METHODS: We performed association analyses on 14,903 individuals (3,206 patients and 11,697 controls) with genotypes and imputed data from the Trans-Omics for Precision Medicine reference panel. Fine-mapping and expression quantitative trait locus colocalization analyses in myositis-relevant tissues indicated potential causal variants. Functional annotation and network analyses using the random walk with restart (RWR) algorithm explored underlying genetic networks and drug repurposing opportunities. RESULTS: Our analyses identified novel risk loci and susceptibility genes, such as FCRLA, NFKB1, IRF4, DCAKD, and ATXN2 in overall IIMs; NEMP2 in polymyositis; ACBC11 in dermatomyositis; and PSD3 in myositis with anti-histidyl-transfer RNA synthetase autoantibodies (anti-Jo-1). We also characterized effects of HLA region variants and the role of C4. Colocalization analyses suggested putative causal variants in DCAKD in skin and muscle, HCP5 in lung, and IRF4 in Epstein-Barr virus (EBV)-transformed lymphocytes, lung, and whole blood. RWR further prioritized additional candidate genes, including APP, CD74, CIITA, NR1H4, and TXNIP, for future investigation. CONCLUSION: Our study uncovers novel genetic regions contributing to IIMs, advancing our understanding of myositis pathogenesis and offering new insights for future research.
Gold nanoparticles represent nanosized colloidal entities with high relevance for both basic and applied research. When gold nanoparticles are functionalized with polymer-molecule ligands, hybrid nanoparticles emerge whose interactions with the environment are controlled by the polymer coating layer: Colloidal stability and structure formation on the single particle level as well as at the supracolloidal scale can be enabled and engineered by tailoring the composition and architecture of this polymer coating. These possibilities in controlling structure formation may lead to synergistic and/or emergent functional properties of such hybrid colloidal systems. Eventually, the responsivity of the polymer coating to external triggers also enables the formation of hybrid supracolloidal systems with specific dynamic properties. This review provides an overview of fundamentals and recent developments in this vibrant domain of materials science.
