[Human and nursing models. 4. Johnson's behavior system model--selection and introduction of a nursing model].
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Behavioral Sciences↗
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[Cognitive modeling in psychiatry: from symbolic models to parallel and distributed models].
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Artificial Intelligence↗
Evaluating the impact of modeling choices on the performance of integrated genetic and clinical models.
The value of genetic information for improving the performance of clinical risk prediction models has yielded variable conclusions. Many methodological decisions have the potential to contribute to differential results across studies. Here, we performed multiple modeling experiments integrating clinical and demographic data from electronic health records (EHR) and genetic data to understand which decision points may affect performance. Clinical data in the form of structured diagnostic codes, medications, procedural codes, and demographics were extracted from two large independent health systems and polygenic risk scores (PRS) were generated across all patients with genetic data in the corresponding biobanks. Crohn's disease was used as the model phenotype based on its substantial genetic component, established EHR-based definition, and sufficient prevalence for model training and testing. We investigated the impact of PRS integration method, as well as choices regarding training sample, model complexity, and performance metrics. Overall, our results show that including PRS resulted in higher performance by some metrics but the gain in performance was only robust when combined with demographic data alone. Improvements were inconsistent or negligible after including additional clinical information. The impact of genetic information on performance also varied by PRS integration method, with a small improvement in some cases from combining PRS with the output of a clinical model (late-fusion) compared to its inclusion an additional feature (early-fusion). The effects of other modeling decisions varied between institutions though performance increased with more compute-intensive models such as random forest. This work highlights the importance of considering methodological decision points in interpreting the impact on prediction performance when including PRS information in clinical models.
Preprint↗
Learning-forgetting independence, unidimensional memory models, and feature models: comment on Bogartz (1990).
In his recent articles, Bogartz offered a definition of what it means for forgetting rate to be independent of degree of original learning. He showed that, given this definition, independence is confirmed by extant data. Bogartz also criticized Loftus's (1985b) proposed method for testing independence. In this commentary, we counter Bogartz's criticisms and then offer two observations. First, we show that Loftus's horizontal-parallelism test distinguishes between two interesting class of memory models: unidimensional models wherein the memory system's state can be specified by a single number and multidimensional models wherein at least two numbers are required to specify the memory system's state. Independence by Loftus's definition is implied by a unidimensional model. Bogartz's definition, in contrast, is consistent with either model. Second, to better understand the constraints on memory mechanisms dictated by the mathematics of the models under consideration, we develop a simple but general feature model of learning and forgetting. We demonstrate what constraints must be placed on this model to make learning and forgetting rate independent by Loftus's and by Bogartz's definitions.
Humans↗
A trainable language model with potential to modulate translation rates in non-model organisms by generating upstream untranslated region sequence libraries.
Tuning protein expression in non-model organisms is often constrained by the lack of validated genetic parts and predictive design tools. Translational tuning through the modulation of upstream untranslated regions (5'-UTRs) offers a potentially organism-agnostic route, but existing methods typically rely on mechanistic assumptions, prior knowledge that may not be available in non-model contexts, or the screening of sequence libraries. Here, we present a simple generative approach for creating synthetic 5'-UTR libraries based solely on the genomic sequence statistics of any desired organism. The method uses a sliding-window n-gram language model applied to native 5'-UTR sequences to produce novel sequences that preserve organism-specific base distributions and motifs without hard-coding specific motifs or mechanistic rules into inflexible statistical templates. We have applied this approach to the model bacterium Escherichia coli and the non-model probiotic Limosilactobacillus reuteri. Libraries of approximately 1,000 sequences were generated for each organism, from which about 100 unique sequences were experimentally tested for translation of a fluorescent reporter protein. In both organisms, the synthetic libraries yielded a broad range of translation levels from this relatively small number of tested variants. Sequences derived from an organism's own genomic statistics provided a more uniformly distributed range of translation rates in that organism than sequences derived from the other species. Correlations of individual sequence performance across the two species were weak, and thermodynamic predictions of ribosome binding strength showed very little predictive power, especially in the non-model L. reuteri. The results demonstrate that simple statistical language model approaches applied to genomic data can generate functional translational regulatory sequence libraries without detailed mechanistic knowledge or explicit reference to consensus motifs. The approach requires minimal computational resources, avoids reproducing native sequences, and can be readily applied to any organism with a sequenced genome. This strategy may lower technical barriers to expression tuning in non-model organisms.
5' Untranslated Regions↗
Analysis of pharmacokinetic data using parametric models--1: Regression models.
This is the first in a series of tutorial articles discussing the analysis of pharmacokinetic data using parametric models. In this article, the purposes of modelling are discussed; regression models for individuals and populations are defined; and structural and variance models are discussed as the two required submodels of the overall regression model. Topics of future articles are: point estimates of parameters; interval estimates of parameters; model criticism and choosing among contending models; population kinetic models and estimation; and elements of optimal design.
Humans↗
Applied muscle modelling: implementation of muscle-specific models.
Recent work in musculoskeletal modelling has seen the use of models which represent individual muscles in the human system. This paper presents a model of forearm supination in which models generate specific muscular forces to produce external supinator torque. The model output is compared to measured external torque for isometric and dynamic loading conditions. These data are used to construct isometric torque-angle and torque-angular velocity graphs for both model and experimental output. The discussion focuses on specific topics regarding implementation of muscle models in applied situations. These topics are demonstrated by observing the effect of parameter alteration on model output.
Computer Simulation↗
X-ray diffraction studies of 14-filament models of deoxygenated sickle cell hemoglobin fibers. II. Models based on the deoxygenated sickle hemoglobin crystal structure.
The calculated transforms of a number of crystal-based models of the deoxygenated sickle cell hemoglobin fiber have been compared with X-ray diffraction data of 15 A (1 A = 0.1 nm) resolution. The fiber models consist of 14 single strands of sickle cell hemoglobin (HbS) molecules, which associate into seven protofilaments arranged similarly to those present in the crystal structure. Six of the protofilaments are arranged in three crystallographic until cells extending in the c-axis direction with the seventh protofilament positioned so as to provide an elliptical cross-section when the assemblage is viewed down the fiber axis. Models were generated by systematically and independently translating each of the model's three subcells in steps of 3.5 A along the fiber axis. The seventh protofilament was kept fixed as a point of reference. Each translation of a subcell corresponded to a different fiber model whose transform was then compared with observed data. In all, over 46,000 transforms were computed; of these, three models with minimal residuals were identified. The free energy of packing for all crystal-based models was evaluated to find configurations of protofilaments possessing minimal free energies. The results of the calculations support the subcell configurations of two of the three models with minimal residuals.
Hemoglobin, Sickle↗
Models of the biological age of the rat. II. Multiple regression models in the study on influencing aging.
The study of influences on multicellular aging requires mathematical models of biological age (BA) as a standard against which deviations from "normal aging" can be measured. A long-term cohort study with initially 1100 male Sprague-Dawley rats served to establish multiple regression models of BA and to test the effects of fast days, physical training, a combination of fast days plus physical training, and the long-term action of subcutaneously applied lyophilized heterologous fetal testis material. All influences started after the attainment of maturity. The models were calculated on the basis of an exponential decrease in vitality during senescence. Twenty-three parameters from a total number of 42 were selected for a general model. By means of a factor analysis, the general model was subdivided into five factor models of BA to distinguish between primary and various types of secondary aging changes. All experimental conditions showed clearly detectable but not dramatic effects on the general model of BA in the sense of a revitalizaion. The most pronounced effect was found in the group pretreated with testis lyophilisate. The results obtained with the factor models suggest that this effect might be due to influences on primary aging as well as on some secondary changes.
Aging↗
Modelling of parasite populations: gastrointestinal nematode models.
This paper surveys models of nematode parasites of veterinary importance. A distinction is drawn between generic models which are usually simple formulations applicable to whole classes of parasite and specific models which are often more complex and designed to address questions concerning a particular species. Most of the models considered employ a deterministic framework. Four main groups are considered: generic models of trichostrongylid infection of domestic ruminants, specific models of trichostrongylid infection of domestic ruminants, specific models of experimental laboratory infections of rodents, and a specific model of nematode infections in wildlife.
Animals↗
Sartwell's incubation period model revisited in the light of dynamic modeling.
The objective is to look into the well-known robustness of Sartwell's disease incubation period (IP) lognormal model. A new approach is proposed that embeds the pathogenesis of infection into the framework of percolation theory derived from the physical sciences. A two-step model of the individual disease process is proposed. The first step has a stochastic basis: it is aimed at establishing the threshold position of subjects bound to be diseased. Agent and host factors entertain and help the process reach the threshold. They include all the biologic risk factors (age, exposure dose and intensity, route of inoculation, etc.) to which Sartwell's model is usually found robust. The threshold is the point of no return of the disease process. The threshold provides the initial conditions of the second step. The second step traces the evolution of the pathologic process until disease onset: it is based on a nonlinear deterministic model that progressively unfolds the individual fates. As a chaotic regime is embedded into the model and as chaos unavoidably develops at some time entailing disease onset, the IP distribution becomes independent of the initial conditions laid out at the threshold. Unpredictable disease time courses and onsets are obtained. Biological examples supporting the model are provided. A simulation of 1000 pathologic processes is undertaken according to a simple birth-and-death process of microorganisms or cancer cells. As expected, a lognormal fits the IP distribution over a wide range. A lack of lengthy IPs is, however, observed. A simple multiplicative process coincides exactly with a lognormal model, but a multiplicative-competitive process such as that which is embedded in the nonlinear deterministic model has a narrower distribution. Large sample sizes are, however, needed to uncover this departure from the lognormal. Biologically, at least two phases of the empiric IP should be told apart: lengthy IPs should be distinguished from short and median IPs. Lengthy IPs emphasize interaction (complexity) between the disease progression and the immunological defenses of the host. Simulated distributions involving process complexity closely fit selected cancer data sets. Process complexity of the host pathologic unfolding can actually be recognized and quantified.
Disease↗
Dynamic life table model for Aedes aegypti (Diptera: Culicidae): analysis of the literature and model development.
The container-inhabiting mosquito simulation model (CIMSiM) is a weather-driven, dynamic life table simulation model of Aedes aegypti (L.). It is designed to provide a framework for related models of similar mosquitoes which inhibit artificial and natural containers. CIMSiM is an attempt to provide a mechanistic, comprehensive, and dynamic accounting of the multitude of relationships known to play a role in the life history of these mosquitoes. Development rates of eggs, larvae, pupae, and the gonotrophic cycle are based on temperature using an enzyme kinetics approach. Larval weight gain and food depletion are based on the differential equations of Gilpin & McClelland compensated for temperature. Survivals are a function of weather, habitat, and other factors. The heterogeneity of the larval habitat is depicted by modeling the immature cohorts within up to nine different containers, each of which represents an important type of mosquito-producing container in the field. The model provides estimates of the age-specific density of each life stage within a representative 1-ha area. CIMSiM is interactive and runs on IBM-compatible personal computers. The user specifies a region of the world of interest; the model responds with lists of countries and associated cities where historical data on weather, larval habitat, and human densities are available. Each location is tied to an environmental file containing a description of the significant mosquito-producing containers in the area and their characteristics. In addition to weather and environmental information, CIMSiM uses biological files that include species-specific values for each of the parameters used in the model. Within CIMSiM, it is possible to create new environmental and biological files or modify existing ones to allow simulations to be tailored to particular locations or to parameter sensitivity studies. The model also may be used to evaluate any number and combination of standard and novel control methods.
Aedes↗
Refining sequence-to-activity models by increasing model resolution.
Decoding the cis-regulatory syntax that controls gene expression is essential for improving our understanding of cell differentiation and disease. To identify regulatory motifs and their regulatory syntax, deep learning based sequence-to-activity (S2A) models learn transcription factor binding motifs and their combinations from DNA sequence by modeling measured chromatin accessibility. Previously, we developed AI-TAC, a S2A model that predicts chromatin accessibility across various immune cell types in multi-task fashion, effectively decoding the regulatory syntax underlying immune cell differentiation. While ATAC-seq is commonly used to measure regional accessibility, it also provides high-resolution profiles, the distribution of Tn5 insertion sites, that offer additional insights into the precise location and strength of TF binding sites. Here we demonstrate that modeling ATAC-seq profiles alongside accessibility consistently improves predictions of differential chromatin accessibility across cell types. Moreover, we also find that multi-task learning across related immune cell types consistently outperforms single-task models. To understand what additional information bpAITAC learns from ATAC-seq profiles, we systematically compare sequence attributions from models trained with and without ATAC-seq profiles. We identify novel motifs with strong effect sizes that emerge only when profile data is included. Our findings suggest that modeling ATAC-seq at base-pair resolution enables the model to learn a more nuanced and sensitive representation of the cis-regulatory syntax driving immune cell-specific chromatin landscapes.
ATAC-seq↗
The influence of muscle model complexity in musculoskeletal motion modeling.
A comparative study of four different muscle models in a musculoskeletal motion problem is made. The models vary in complexity from the simple input-output model to the more complex model of Hatze [1]. These models are used to solve a minimum time kicking problem using an optimal control algorithm. The results demonstrate the strong influence of the model choice on the various predicted kinematic and kinetic parameters in the problem. The study illustrates some of the advantages and disadvantages involved in trade-offs between model complexity and practicability in musculoskeletal motion studies. The results also illustrate the importance of appropriate detailed parameter estimation studies in the mathematical modeling of the musculoskeletal system.
Humans↗
[Therapeutic study on biofilm of the urinary tract using a severely complicated bladder model (biofilm model of the urinary tract)--experimental study using an automatic simulator of urinary antimicrobial agent concentration, and clinical study].
For the purpose of conducting a therapeutic study on biofilm of the urinary tract, we devised a computer-controlled severely complicated bladder model (biofilm model of the urinary tract) enabling us to simulate the time-course of the concentration of antimicrobial agents in the urine. Using this model, we investigated clarithromycin (CAM), which has been reported to have anti-biofilm action, at concentrations close to its urinary levels at the time of clinical use in order to predict its effect on biofilm of the urinary tract. On the basis of those experimental results, we also conducted a clinical examination. The following results were obtained. 1. The action of ciprofloxacin (CPFX, MIC: 8 micrograms/ml) alone, which shows anti-P. aeruginosa activity, caused apparent elimination of P. aeruginosa from the model. However, regrowth of the microbes occurred when CPFX was removed from the bladder model. Moreover, the biofilm was not eliminated by the antimicrobial action of CPFX, and this was surmised to be the cause of the regrowth. 2. CAM (MIC: above 128 micrograms/ml), which has no anti-P. aeruginosa activity, was similarly tested as anti-biofilm agent when added alone to the biofilm model. The P. aeruginosa recovered to its initial concentration within 48 hours, but the biofilm disappeared due to the action of CAM. 3. The combined action of CPFX and CAM caused microbial elimination from the bladder model without microbial regrowth, even after these antimicrobial agents were removed from the bladder model. After the action of CPFX and CAM, the biofilm disappeared, and no microbial adherence was noted. 4. Measurement of time-course of the alginate content, which is the main component of P. aeruginosa biofilm, in the presence of CAM found that the alginate content decreased below the limit of detection after day 5. 5. The clinical study of complicated urinary tract infection revealed the microbial elimination rate and the efficacy rate to be higher in the combined CPFX-CAM administration group than in the CPFX-only administration group. 6. Based on the above results, we surmise that the combined use of an antimicrobial agent which is active against the causative microbe and anti-biofilm agent such as CAM will show some degree of efficacy in eliminating biofilm of the urinary tract.
Ciprofloxacin↗
Energetics of the time-varying elastance model, a visco-elastic model, matches Mommaerts' unifying concept of the Fenn effect of muscle.
It is generally believed that the Fenn effect contradicts all visco-elastic models of muscle, including the new elastic body and the time-varying elastance models. Although it is clear that the new elastic body model can be discarded, the Fenn effect does not preclude the time-varying elastance model. Although no visco-elastic models can simulate the extra energy utilization for work above the level of the energy utilized for the maximal isometric contraction, the extra energy observed by Fenn is not generally observed, even in skeletal muscles. However, work-related extra energy utilization, above the isometric energy utilization at equivalent force (Mommaerts' unifying concept of the Fenn effect), is generally observed in both skeletal and cardiac muscles. This unifying concept of the Fenn effect in cardiac muscle can be simulated by a simple time-varying elastance model. This study demonstrates the essential difference in energetics between the new elastic body model and the time-varying elastance model.
Elasticity↗
A dynamic life table model of Psorophora columbiae in the southern Louisiana rice agroecosystem with supporting hydrologic submodel. Part 1. Analysis of literature and model development.
During the past decade, the rice agroecosystem and its associated mosquitoes have been the subject of an extensive research effort directed toward the development and implementation of integrated pest management (IPM) strategies. The objective of this work was to synthesize the literature and unpublished data on the rice agroecosystem into a comprehensive simulation model of the key elements of the system known to influence the population dynamics of Psorophora columbiae. Subsequent companion papers will present a validation of these models, provide an in-depth analysis of the population dynamics of Ps. columbiae, and evaluate current and proposed IPM strategies for this mosquito. This paper describes the development of 2 models: WaterMod: Because spatial and temporal distributions of surface water and soil moisture play a decisive role in the dynamics of Ps. columbiae, an essentially hydrological simulator was developed. Its purpose is to provide environmental inputs for a second model (PcSim) which simulates the population dynamics of Ps. columbiae. WaterMod utilizes data on weather, agricultural practices, and soil characteristics for a particular region to generate a data set containing daily estimates of soil moisture and depth of water table for 12 representative areas comprising the rice agroecosystem. This model could be used to provide hydrologic inputs for additional simulation models of other riceland mosquito species. PcSim: This model simulates the population dynamics of Ps. columbiae by using the computer to maintain a daily accounting of the absolute number of mosquitoes within each daily age class for each life stage. The model creates estimates of the number of eggs, larvae, pupae, and adults for a representative l-ha area of a rice agroecosystem.
Actuarial Analysis↗
Criteria for development of animal models of diseases of the respiratory system: the comparative approach in respiratory disease model development.
Advances in the understanding of human respiratory disease can come from careful clinical studies of the diseases as they occur in man, but such studies are naturally limited in terms of experimental manipulation. In the last 2 decades, an increasingly complex plethora of experimental respiratory disease models has been developed and utilized by investigators, but relatively less attention has been paid to the naturally occurring pulmonary diseases of animals as potential models. This paper is aimed at presenting selected examples of spontaneous pulmonary disease in animals that may serve as exploitable models for human chronic bronchitis, bronchiectasis, emphysema, interstitial lung disease, hypersensitivity pneumonitis, hyaline membrane disease, and bronchial asthma. Chronic bronchitis in dogs is characterized by chronic cough, excessive mucus production, and chronic inflammatory changes in bronchial walls. The disease affects mainly smaller-breed dogs of middle age or older. Equine chronic bronchitis tends to be a small airway disease with marked goblet cell proliferation and excessive mucus production, which may be accompanied by alveolar emphysema. Many animals develop bronchiectasis or bronchiolitis obliterans secondary to chronic suppurative bronchopneumonia, but chronic respiratory disease (CRD) of rats may be the most useful model of bronchiectasis. Models for emphysema must include actual alveolar destruction and ideally should be accompanied by appropriate pathophysiologic decrements. Many animals occasionally develop emphysema, but the disease has not been well documented, except possibly in horses. The interstitial lung diseases of man represent a complicated and poorly understood group of entities and near-entities. The same is true for animals, although interstitial lung disease in animals is much less common than bronchopneumonia. Cattle seem prone to develop interstitial lesions. Proliferative interstitial pneumonia of cattle includes many morphologic similarities to the spectrum of human interstitial pneumonitides. Fibrosing alveolitis of cattle is a morphologic end point that may have its origins in different forms of interstitial injury. Hypersensitivity pneumonitis has been best detailed in cattle and in horses and is clinically, etiologically, immunologically, and morphologically similar to the disease in man. Hyaline membrane disease has been poorly documented in animals, with the possible exception of the neonatal respiratory distress syndromes of foals and piglets. Bronchial asthma is similarly not well established as a spontaneous disease in animals, although experimental models exist. Eosinophilic bronchiolitis of cattle may represent a useful asthma model but has been poorly detailed. In order to make them useful as models, more attention should be paid to detailing the clinical, morphologic, and etiologic aspects of these naturally occurring animal pulmonary diseases.
Animals↗