Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Transformer model”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18Linked to original sources
PubMed1990

A generalized state-vector model for radiation-induced cellular transformation.

A mathematical model is developed, detailing the manner in which radiation brings about the transformation of cells to a state of uncontrolled growth. The model is based on the concepts of initiation and promotion, with the irradiation acting both to damage intracellular structures and to change the state of cells surrounding a damaged (initiated) cell. The complete model requires that the radiation produce two forms of damage within a cell, with at least one of the forms requiring an interaction which is a function of time since irradiation. Some form of contact inhibition must be removed, with this step being a function of the probability that a cell in an initiated state will be surrounded by n dead cells. The cell then must divide, with the probability of moving the cell to the final transformed state being a function of the number of cellular divisions. Prior to irradiation, it is assumed that cells may be characterized by an initial state vector describing the probability that any given cell is in one of the states specified by the model. The resulting model then is used to explain data concerning in vitro irradiation of cells by acute doses of X-rays, alpha particles and neutrons. Limited tests of the theory under conditions of fractionated irradiation are also provided. A controlling factor in such studies is the number of cells already in intermediate states prior to the irradiation.

Alpha Particles↗
PubMed1997

A synergetic model for the verbal transformation effect.

We describe a nonlinear dynamical model based on synergetics for the auditory perceptual illusion known as the verbal transformation effect. The model is an extension of a synergetic model of perceptual oscillations of visual ambiguous figures. The main extension is connected to the number of reported alternative phonemic structures, which is typically much greater than the two or three alternatives usually reported in experiments with visual ambiguous figures. The properties of the model, which are derived using basic psychophysical principles, are presented and evaluated on the basis of the fit to earlier empirical work. It will be shown that there is very good agreement between the empirically observed properties of the verbal transformation effect and the properties detected by the model.

Attention↗
PubMed2002

Carbon tetrachloride transformation in a model iron-reducing culture: relative kinetics of biotic and abiotic reactions.

Contributions of biotic (cell-mediated) and abiotic (mineral-mediated) reactions to carbon tetrachloride (CT) transformation were studied in a model iron-reducing system that used hydrous ferric oxide (HFO) as the electron acceptor, acetate as the substrate, and Geobacter metallireducens as a representative dissimilative iron-reducing bacteria (DIRB). Over a period of 2-3 weeks, nanoscale magnetite particles, Fe3O4, were consistently formed as a product of iron respiration in this system. CT transformation rates were measured independently in resting cell suspensions of G. metallireducens or in suspensions of washed magnetite particles recovered from spent cultures. Protein and surface area-normalized expressions were derived for the biotic and abiotic reaction rates, respectively. Using the yield of total protein and magnetite surface area formed during growth in the model system as a basis for comparison, the mineral-mediated (abiotic) reaction was estimated to be 60-260-fold faster than the biotic reaction throughout the incubation period. We conclude that G. metallireducens induces CT transformation in this system primarily through the formation of reactive mineral surfaces rather than via co-metabolic mechanisms. The findings indicate that reactive biogenic minerals could play a significant role in the natural attenuation of chlorinated solvents in iron-reducing environments. A novel approach for stimulating reductive transformation of contaminants may be to enhance the formation of reactive biogenic minerals in situ.

Biotransformation↗
PubMed2004

Modelling relative survival using transformation methods.

Patient survival is often assessed as a measure of effectiveness of treatment in cancer clinical trials. The relative survival rate is a measure of patient survival corrected for the effect of other causes of death. We incorporate an additive hazards model for the overall force of mortality focusing attention on the form of the underlying disease process. Transformation models for the cause-specific hazard rate describing the disease process are considered. We demonstrate a method for estimating the transformation parameter providing insight into the appropriate choice of model structure. The models include the additive and multiplicative structures as special cases. We write the models in the generalized linear model framework and demonstrate ease of fitting via existing statistical software. The methodology is applied to a Hodgkin's disease data set to assess the effect of clinical trial results on population survival. Our analysis concludes that the multiplicative structure provides a more appropriate description of the data as compared to the additive structure.

Clinical Trials as Topic↗
PubMed1993

A critique of Fawcett's 'Conceptual models and nursing practice: the reciprocal relationship'.

This paper offers a critique of Fawcett's paper 'Conceptual models and nursing practice: the reciprocal relationship' published in 1992, in which it is argued that 'conceptual models inform and transform nursing practice by informing and transforming the way in which nursing is experienced and understood, and that nursing practice informs and transforms conceptual models by informing and transforming the content of the conceptual model'. The critique begins by locating Fawcett's view of the relationship of nursing models to nursing practice within the intellectual tradition of positivism. For the purposes of the critique, Fawcett's positivism is not taken as being problematic in itself; however, it is argued that the standards of evidence upon which some of her arguments are based are not compatible with the practice of positivist social science, with the result that the paper is internally inconsistent. In particular, Fawcett's suggestion that nursing models are validated as evidence accumulates in their favour is contrasted with Popper's view that the validity of theoretical statements is established as they withstand attempts to demonstrate their falsity; and Fawcett's belief that nursing models are models in the scientific sense, which can be inferred from her adoption of the terminology of Kuhnian epistemology, is not found to be justified. If, for the positivist, the validity of practice is directly proportional to the validity of the theory upon which it is based, then nursing models which lack 'scientific' validity cannot be regarded as a proper basis for nursing practice. Finally, Fawcett has been criticized for failing to produce evidence of any kind to demonstrate that nursing models have a beneficial effect upon nursing outcomes.

Models, Nursing↗
PubMed1996

From coiled tubules to a secretory canaliculus: a new model for membrane transformation and acid secretion by gastric parietal cells.

The acid-secreting gastric parietal cell has a unique secretory membrane system. This membrane system exists in an inactive (non-secreting) and an active (secreting) form. The current accepted model to explain the transformation events associated with the conversion of the non-secreting membrane to the secreting membrane, and vice versa, invokes membrane recycling of elongated vesicle structures. However, recent studies employing cryopreparation have shown that the non-secreting membrane in these cells is actually a complex network of helically coiled tubules. Here, we present an alternative model to explain how the membrane in parietal cells is activated to secrete HCl.

Journal Article↗
PubMed2025

Foundation model based multimodal transformer framework for survival analysis in HER2 stratified breast cancer.

Objective. To improve survival prediction for HER2-positive breast cancer by integrating histopathological, molecular, and clinical data using a multimodal transformer framework.Approach. We propose a multimodal transformer framework for breast cancer survival prediction using HER2 stratified (SurvMBC), a foundation model-enhanced architecture that fuses three data modalities: whole-slide images, clinical narratives, and molecular features. Tumor microenvironment features are extracted using a pathology language and image pre-training (PLIP), clinical narratives are processed with BioBERT, and miRNA expression plus DNA methylation data are embedded using Gen2Vec. These representations are integrated through a cross-modal transformer with attention mechanisms for survival prediction.Main results. The model was evaluated on 1,095 HER2-positive breast cancer patients from The Cancer Genome Atlas. SurvMBC achieved a concordance index (C-index) of 0.857 (95% CI: 0.834, 0.880), a low integrated Brier score, and a strong inverse negative binomial log-likelihood. Risk stratification based on model outputs significantly separated high- and low-risk groups (log-rankp< 0.01) and showed strong associations with tumor stage, grade, and hormone receptor status (allp< 0.05).Significance. SurvMBC demonstrates the effectiveness of multimodal fusion in addressing tumor heterogeneity and improving prognostic accuracy. The attention-based integration enables context-aware learning of survival-relevant features across modalities, supporting individualized risk stratification and risk-adaptive treatment planning for HER2 stratified breast cancer patients.

Breast Neoplasms↗
PubMed2001

Interatomic potential parameters for potassium tetrachlorozincate and their application to modelling its phase transformations.

An empirical fitting procedure is applied to derive interatomic potential parameters for a model phase transition system, namely potassium tetrachlorozincate (K(2)ZnCl(4)). The derived potential is found to reliably model the known crystallographic structure for the ferroelectric and paraelectric phases of this compound. Potential transferability is demonstrated by applying the parameters derived to the optimization of the known molecular structure for a similar inorganic system (rubidium tetrachlorozincate).

Journal Article↗
PubMedDate not supplied

[Aneuploid model of meiotic transformation mechanisms in wheat. 1. Mechanism of chromosome shift from mitosis to meiosis].

A model of chromosome shift from mitosis to meiosis based on analysis of univalent behavior in meiotic anaphase I in the complete series of monosomic lines of Milturum 553 wheat cultivar is proposed. According to the model, chromosomes of homologous pairs change their pole orientation by two different mechanisms. Such co-orientation is achieved through segregation of initial pole zone in one haploid set and through synapsis of homologues in the other.

Aneuploidy↗
PubMed2001

Dimer interface of transmembrane domains for neu/erbB-2 receptor dimerization and transforming activation: a model revealed by molecular dynamics simulations.

The specific point mutation Val-->Glu664 within the transmembrane domain of the neu/erbB-2 receptor is associated with increased receptor dimerization and increased receptor tyrosine kinase activity resulting in malignant transformation of cells. It is well established that Glu and residues in proximity are necessary for receptor dimerization but many studies suggest that other intramembrane constraints, not yet elucidated, are determinant for transformation. In this work, we investigated dimer models both to understand the structural role of the Glu mutation in the transmembrane domain association and to determine helix-helix contacts required for oncogenic transformation. Different types of helix-helix association based on data resulting from Cys mutational studies of the full wild receptor and spectroscopic data of transmembrane neu peptides have been explored by molecular dynamics simulations. The study leads to propose a model for the dimeric association of the transmembrane domains of the oncogenic neu receptor showing left-handed interactions of the two helices stabilized by symmetrical hydrogen bonding interactions involving the Glu side chain on one helix and the facing carbonyl of Ala661 on the second helix. Contacting residues observed in the symmetric interface explain the transforming activity or the non transforming activity of many neu mutants. Moreover the left-handed coiled coil structure is fully consistent with recent results proving the role of rotational linkage of the transmembrane domain with the kinase domain. Comparison between the predicted dimer model and those presumed from experiments strongly suggests helix flexibility in the extracellular juxtamembrane region.

Amino Acid Sequence↗
PubMed2000

The transformative process of residency education.

The author explores a model for transformative learning proposed by the education scholar Victoria Marsick. He begins by outlining Marsick's eight principles (or outcomes) of transformative learning: increased autonomy; increased independence; the ability to separate one's feelings and opinions from those of others; the ability to critically and respectfully examine the views of others; the ability to set personal and professional goals; the ability to see how one's actions affect the system in which one works; the ability to balance and choose among conflicting priorities and at some point transcend self-interest; and the ability to acknowledge one's role in constructing one's reality. Using illustrative examples from his experiences as a resident and a teacher of residents, the author describes each principle of the transformative model. He then suggests how educators can use these principles to ensure a transformative residency experience by which novice professionals become reflective and confident practitioners.

Clinical Competence↗
PubMed1984

Improving the measurement of temporal change in regression models used for county population estimates.

The ratio-correlation method of population estimation is shown to contain an inconsistent temporal relationship between the model's empirical structure and its actual application. A simple transformation of the model's variables is provided that eliminates the inconsistency. Two tests of the relative accuracy of the original and transformed models show that the transformed model achieves accuracy levels equal to or higher than the original. In one test, all nine years show a higher degree of accuracy, of which four are statistically significant. Several possible reasons are given for the increased accuracy shown by the transformed model. The transformation, termed the "rate-correlation" model, is recommended as a logical starting point in the examination of coefficient stability and spatial autocorrelation as well as a method for estimating small populations.

Adult↗
PubMed2026

Deep generative models in biological sequence and structure analysis and design.

Deep generative models have transformed biological sequence modeling from predictive analysis toward increasingly controllable design. Early biological applications of Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs) established latent representation learning and sequence synthesis, while recent advances in transformer-based language models, discrete diffusion, flow-matching, and multimodal generative frameworks have substantially expanded the scope of biological design. This review examines generative models for DNA, RNA, and protein sequence design, emphasizing how different model classes represent biological constraints, operate over discrete and continuous spaces, and integrate sequence, structure, and function. We compare VAEs, GANs, autoregressive and masked language models, diffusion models, and flow-based approaches across genomics, transcriptomics, and proteomics, with particular attention to controllability, long-range dependency modeling, structural grounding, generalization, and experimental utility. We further examine evaluation strategies, out-of-distribution generalization, and closed-loop design-build-test-learn workflows that connect in silico generation with empirical validation. We distinguish fundamental modality-dependent constraints including sequence discreteness, context length, structural coupling, and physical or thermodynamic requirements from architecture-dependent advantages that reflect the current state of the field. Current studies suggest that long-context models are particularly useful for genome-scale representation and sequence modeling, whereas structure-aware diffusion, flow-based, and inverse-folding approaches provide better frameworks for geometry-constrained RNA and protein design. This perspective provides a critical framework for understanding the present capabilities, limitations, and convergence of generative approaches toward reliable and experimentally grounded biological design.

Biological sequence analysis↗
PubMed2002

The distribution of caveolin-3 immunofluorescence in skeletal muscle fibre membrane defined by dual channel confocal laser scanning microscopy, fast Fourier transform and image modelling.

Membrane domains rich in caveolin-3 overlie sarcomeric actin in skeletal muscle. The membrane exhibits a regular array of caveolin-3 immunofluorescence using confocal laser scanning microscopy (CLSM). Fourier analysis of tissue imaged by CLSM accurately defines a repeating intensity with a long-axis spacing of 1.48 microm confirmed by measurement of direct images. Reverse fast Fourier transform (FFT) and image-modelling allow reconstruction of the pattern. Mathematical modelling has allowed replication of several features of the FFT, including the second order maxima that confirm the relatively high information content of the original images. Measurements of membrane-pattern primary long-axis spacings are consistent with our measurements of the I-band sarcomere repeat in similarly prepared specimens labelled with fluorescent phalloidin or imaged using differential interference contrast microscopy. Dual-channel CLSM analysis of the sarcomeric banding pattern of actin and the repeating pattern of muscle fibre membrane caveolin showed that caveolae overlie the I-band. The anti-caveolin immunofluorescence is deficient over the Z-disc and maximal toward each of the I-band extremities. A mechanism of membrane shape change in which membrane-lipid molecules are interposed between more stable anchored rafts associated with caveolae can be envisaged. Thus, increasing girth and reducing length of the sarcolemma in rapid contraction may be explained.

Animals↗
PubMedDate not supplied

Snake modeling and distance transform approach to vascular centerline extraction and quantification.

A new method for fully automated centerline extraction and quantification of microvascular structures in confocal microscopy (CM) images is presented. Our method uses the idea of active contour models as well as path planning and distance transforms for the three-dimensional centerline extraction of elongated objects such as vessels. The proposed approach is especially efficient for centerline extraction of complex branching structures. The method performance is validated in several CM images of both normal and stroked rat brains as well as simulated objects. The results confirm the efficiency of the proposed method in extracting the medial curve of vessels, which is essential for the computation of quantitative parameters.

Algorithms↗
PubMed2007

A model for phosphorus transformation and runoff loss for surface-applied manures.

Agricultural P transport in runoff is an environmental concern. An important source of P runoff is surface-applied, unincorporated manures, but computer models used to assess P transport do not adequately simulate P release and transport from surface manures. We developed a model to address this limitation. The model operates on a daily basis and simulates manure application to the soil surface, letting 60% of manure P infiltrate into soil if manure slurry with less than 15% solids is applied. The model divides manure P into four pools, water-extractable inorganic and organic P, and stable inorganic and organic P. The model simulates manure dry matter decomposition, and manure stable P transformation to water-extractable P. Manure dry matter and P are assimilated into soil to simulate bioturbation. Water-extractable P is leached from manure when it rains, and a portion of leached P can be transferred to surface runoff. Eighty percent of manure P leached into soil by rain remains in the top 2 cm, while 20% leaches deeper. This 2-cm soil layer contributes P to runoff via desorption. We used data from field studies in Texas, Pennsylvania, Georgia, and Arkansas to build and validate the model. Validation results show the model accurately predicted cumulative P loads in runoff, reflecting successful simulation of the dynamics of manure dry matter, manure and soil P pools, and storm-event runoff P concentrations. Predicted runoff P concentrations were significantly related to (r2=0.57) but slightly less than measured concentrations. Our model thus represents an important modification for field or watershed scale models that assess P loss from manured soils.

Alum Compounds↗