A generalized mover-stayer model for panel data

A generalized mover-stayer model is described for conditionally Markov processes under panel observation. Marginally the model represents a mixture of nested continuous-time Markov processes in which sub-models are defined by constraining some transition intensities to zero between two or more states of a full model. A Fisher scoring algorithm is described which facilitates maximum likelihood estimation based only on the first derivatives of the transition probability matrices. The model is fit to data from a smoking prevention study and is shown to provide a significant improvement in fit over a time-homogeneous Markov model. Extensions are developed which facilitate examination of covariate effects on both the transition intensities and the mover-stayer probabilities.     

Fecundibility and social development in China: changes in the distribution of the first conception interval

Supporting evidence was generated to show that the hazard of conception in China increases with the duration of marriage in the first years of marriage, with controls for heterogeneity. The authors suggest that this positive duration dependence reflects a "honeymoon" effect for older cohorts and more rural, traditional areas and a change in social norms. Specifically, in Hebei the shape parameter was larger for older cohorts and it decreased from 1.15 in the model with Gamma mixing and from 1.09 to .95 in the mover-stayer model. This may mean that the "late honeymoon" effect has been decreasing over the past 30 years. Changes were not evident in Shanghai municipality. In the 12 models produced there was positive duration dependence in 10 of the models allowing for heterogeneity, but not all models were significant. The shortening of waiting time to first conception was concluded not to be caused by changes in the marriage age, selection biases, a decline in involuntary childlessness, data defects, or an increase in premarital conceptions. Data were obtained from the 1986 In-Depth Fertility Survey in China for Hebei and Shaanxi provinces and Shanghai municipality. Analysis was with time hazard models: the mover-stayer mixture model, where stayers are the proportion sterile in the population, and the nonparametric model. Data were stratified by place of residence and marriage date. Heterogeneity was treated as a "nuisance" parameter, which indicated unobserved biological, behavioral, and social differences between couples. The distribution of fecundability was not addressed     

A Vaccination Model for a Multi-City System

A modelling approach is used for studying the effects of population vaccination on the epidemic dynamics of a set of n cities interconnected by a complex transportation network. The model is based on a sophisticated mover-stayer formulation of inter-city population migration, upon which is included the classical SIS dynamics of disease transmission which operates within each city. Our analysis studies the stability properties of the Disease-Free Equilibrium (DFE) of the full n-city system in terms of the reproductive number R (0). Should vaccination reduce R (0) below unity, the disease will be eradicated in all n-cities. We determine the precise conditions for which this occurs, and show that disease eradication by vaccination depend on the transportation structure of the migration network in a very direct manner. Several concrete examples are presented and discussed, and some counter-intuitive results found.     

A stochastic model for survival of early prostate cancer with adjustments for leadtime, length bias, and over-detection

To compare the survival between screen-detected and clinically detected cancers, we applied a series of non-homogeneous stochastic processes to deal with leadtime, length bias, and over-detection by using full information on detection modes obtained from the Finnish randomized controlled trial for prostate cancer screening. The results show after 9-year follow-up the hazard ratio of prostate cancer death for screen-detected cases against clinically detected cases increased from 0.24 (95% CI: 0.16-0.35) without correction for these biases, to 0.76 after correction for leadtime and length biases, and finally to 1.03 (95% CI: 0.79-1.33) for a further adjustment for over-detection. Adjustment for leadtime and length bias but no over-detection led to a 24% reduction in prostate cancer death as a result of prostate-specific antigen test. The further calibration of over-detection indicates no gain in survival of screen-detected prostate cancers (excluding over-detected case as stayer considered in the mover-stayer model) as compared with the control group in the absence of screening that is considered as the mover. However, whether the model assumption on over-detection is robust should be validated with other data sets and longer follow-up.     

Viscoelastic behavior of a lung alveolar duct model

A study is conducted into the oscillatory behavior of a finite element model of an alveolar duct. Its load-bearing components consist of a network of elastin and collagen fibers and surface tension acting over the air-liquid interfaces. The tissue is simulated using a visco-elastic model involving nonlinear quasi-static stress-strain behavior combined with a reduced relaxation function. The surface tension force is simulated with a time- and area-dependent model of surfactant behavior. The model was used to simulate lung parenchyma under three surface tension cases: air-filled, liquid-filled, and lavaged with 3-dimenthyl siloxane, which has a constant surface tension of 16 dyn/cm. The dynamic elastance (Edyn) and tissue resistance (Rti) were computed for sinusoidal tidal volume oscillations over a range of frequencies from 0.16-2.0 Hz. A comparison of the variation of Edyn and Rti with frequency between the model and published experimental data showed good qualitative agreement. Little difference was found in the model between Rti for the air-filled and lavaged models; in contrast, published data revealed a significantly higher value of Rti in the lavaged lung. The absence of a significant increase in Rti for the lavaged model can be attributed to only minor changes in the individual fiber bundle resistances with changes in their configuration. The surface tension was found to make an important contribution to both Edyn and Rti in the air-filled duct model. It was also found to amplify any existing tissue dissipative properties, despite exhibiting none itself over the small tidal volume cycles examined.     

A Computational Model of Aging and Calcification in the Aortic Heart Valve

The aortic heart valve undergoes geometric and mechanical changes over time. The cusps of a normal, healthy valve thicken and become less extensible over time. In the disease calcific aortic stenosis (CAS), calcified nodules progressively stiffen the cusps. The local mechanical changes in the cusps, due to either normal aging or pathological processes, affect overall function of the valve. In this paper, we propose a computational model for the aging aortic valve that connects local changes to overall valve function. We extend a previous model for the healthy valve to describe aging. To model normal/uncomplicated aging, leaflet thickness and extensibility are varied versus age according to experimental data. To model calcification, initial sites are defined and a simple growth law is assumed. The nodules then grow over time, so that the area of calcification increases from one model to the next model representing greater age. Overall valve function is recorded for each individual model to yield a single simulation of valve function over time. This simulation is the first theoretical tool to describe the temporal behavior of aortic valve calcification. The ability to better understand and predict disease progression will aid in design and timing of patient treatments for CAS.     

Exploratory Bayesian model selection for serial genetics data

Characterizing the process by which molecular and cellular level changes occur over time will have broad implications for clinical decision making and help further our knowledge of disease etiology across many complex diseases. However, this presents an analytic challenge due to the large number of potentially relevant biomarkers and the complex, uncharacterized relationships among them. We propose an exploratory Bayesian model selection procedure that searches for model simplicity through independence testing of multiple discrete biomarkers measured over time. Bayes factor calculations are used to identify and compare models that are best supported by the data. For large model spaces, i.e., a large number of multi-leveled biomarkers, we propose a Markov chain Monte Carlo (MCMC) stochastic search algorithm for finding promising models. We apply our procedure to explore the extent to which HIV-1 genetic changes occur independently over time.     

Modeling the adaptive potential of isolated populations: experimental simulations using Drosophila

The genetic variability underlying many morphological and stress resistance traits may largely depend on the effects of genetic drift balanced by polygenic mutation. This model of adaptive potential has played a central role in the minimum viable population size concept and has been used to predict the effective population size necessary to prevent extinction within changing environments. However, there have been few long-term experimental studies of adaptive potential within isolated populations, and no study has thus far provided an experimental test of the drift-mutation model of quantitative genetic variation. Using the sternopleural bristle number of Drosophila melanogaster as a model quantitative trait, we performed repeated measurements of adaptive potential on 15 replicate populations of two and 10 male-female pairs over 30 and 77 generations, respectively. Declines in adaptive potential were analyzed by comparing observed and expected changes in realized heritability over time. The only significant model deviation occurred immediately after bottlenecks of two pairs, in which greater than expected declines in realized heritability were observed. This result suggests that changes in allelic diversity during bottleneck events may be as important as changes in heterozygosity in determining adaptive potential. Drift-mutation model expectations were otherwise realized over all generations. Our results validate the use of the drift-mutation model as a tool for understanding the dynamics of adaptive potential for peripheral fitness characters, but suggest caution in applying this model to recently bottlenecked populations.     

The North Atlantic Oscillation and regional phenology prediction over Europe

We present an integrated modeling study designed to investigate changes in ecosystem level phenology over Europe associated with changes in climate pattern, by the North Atlantic Oscillation (NAO). We derived onset dates from processed NDVI data sets and used growing degree day (GDD) summations from the NCEP re‐analysis to calibrate and validate a phenology model to predict the onset of the growing season over Europe. In a cross‐validation hindcast, the model (PHENOM) is able to explain 63% of the variance in onset date for grid cells containing at least 50% mixed and boreal forest. Using a model developed from previous work we performed climate change scenarios, generating synthetic temperature and GDD distributions under a hypothetically increasing NAO. These new distributions were used to drive PHENOM and project changes in the timing of onset for forested cells over Europe. Results from the climate change scenarios indicate that, if the current trend in the NAO continues, there is the potential for a continued advance to the start of the growing season by as much as 13 days in some areas.     

Modeling GPCR active state conformations: the β(2)-adrenergic receptor

The recent publication of several G protein-coupled receptor (GPCR) structures has increased the information available for homology modeling inactive class A GPCRs. Moreover, the opsin crystal structure shows some active features. We have therefore combined information from these two sources to generate an extensively validated model of the active conformation of the β(2)-adrenergic receptor. Experimental information on fully active GPCRs from zinc binding studies, site-directed spin labeling, and other spectroscopic techniques has been used in molecular dynamics simulations. The observed conformational changes reside mainly in transmembrane helix 6 (TM6), with additional small but significant changes in TM5 and TM7. The active model has been validated by manual docking and is in agreement with a large amount of experimental work, including site-directed mutagenesis information. Virtual screening experiments show that the models are selective for β-adrenergic agonists over other GPCR ligands, for (R)- over (S)-β-hydroxy agonists and for β(2)-selective agonists over β(1)-selective agonists. The virtual screens reproduce interactions similar to those generated by manual docking. The C-terminal peptide from a model of the stimulatory G protein, readily docks into the active model in a similar manner to which the C-terminal peptide from transducin, docks into opsin, as shown in a recent opsin crystal structure. This GPCR-G protein model has been used to explain site-directed mutagenesis data on activation. The agreement with experiment suggests a robust model of an active state of the β(2)-adrenergic receptor has been produced. The methodology used here should be transferable to modeling the active state of other GPCRs.     

Kinetic models for detection of toxicity in a microbial fuel cell based biosensor

Currently available models describing microbial fuel cell (MFC) polarization curves, do not describe the effect of the presence of toxic components. A bioelectrochemical model combined with enzyme inhibition kinetics, that describes the polarization curve of an MFC-based biosensor, was modified to describe four types of toxicity. To get a stable and sensitive sensor, the overpotential has to be controlled. Simulations with the four modified models were performed to predict the overpotential that gives the most sensitive sensor. These simulations were based on data and parameter values from experimental results under non-toxic conditions. Given the parameter values from experimental results, controlling the overpotential at 250 mV leads to a sensor that is most sensitive to components that influence the whole bacterial metabolism or that influence the substrate affinity constant (Km). Controlling the overpotential at 105 mV is the most sensitive setting for components influencing the ratio of biochemical over electrochemical reaction rate constants (K1), while an overpotential of 76 mV gives the most sensitive setting for components that influence the ratio of the forward over backward biochemical rate constants (K2). The sensitivity of the biosensor was also analyzed for robustness against changes in the model parameters other than toxicity. As an example, the tradeoff between sensitivity and robustness for the model describing changes on K1 (IK1) is presented. The biosensor is sensitive for toxic components and robust for changes in model parameter K2 when overpotential is controlled between 118 and 140 mV under the simulated conditions.     

A modified U-net-based architecture for segmentation of satellite images on a novel dataset

The remote-sensing-based satellite images have been providing a wealth of information to the scientists for study of environmental changes caused by climate changes or human activities such as destructive cyclones and earthquakes etc. This paper proposes a deep learning-based segmentation model for agriculture images captured from satellites and a novel agriculture-based satellite dataset. The segmentation has been performed on the satellite images into five categories of cultivated land, uncultivated land, residences, water, and forest. The dataset has been created using Sentinel-2 satellite data over the Panipat district in Haryana, India having diversity in crops and land usage. The dataset consists of 16,720 images and their corresponding masks over the years ranging from 2018 to 2020. The proposed model consists of a six-phase encoder-decoder network with a total of 33 convolution layers. The proposed segmentation model has been evaluated on proposed dataset and obtained an efficient metric of 72% IoU score which is better than state-of-the-art models such as U-Net, Link-Net, FPN and DeeplabV3+ score 51%, 46%, 49%, 67% IoU respectively.     

Age-related changes in crossing over in Drosophila resemble the picture of interchromosomal effect of chromosome rearrangement on crossing over

Crossing over in the left arm of chromosome 2 (2L) was studied in successive broods of Drosophila melanogaster females carrying intact chromosomes (+/+), inversion Muller-5 in the X chromosome (M-5/+), and insertion of the Y-chromosome material into region 34A (Is(2L)/+). The regions net-dp, dp-b, b-pr and pr-cn were examined in 14 two-day-old broods of females +/+ and M-5/+ and in 10 broods of females Is(2L)/+. In all lines, the highest level of crossing over was in the first three broods (eggs laid during the first 6 days of oviposition) and the lowest level in the broods 7-8 (eggs laid at days 14-16). A high rate of crossing over in the first broods of females +/+ and M-5/+ was due to an increment of exchanges in the proximal euchromatin regions (b-pr and pr-cn) and to an increase in the number of tetrads with double exchanges. These changes are similar to a pattern of the interchromosomal effect on crossing over (IEC) in structurally normal chromosomes. In Is(2L)/+ females, a high level of crossing over was due to extensive exchanges in the interstitial regions net-dp and dp and an increase in the number of tetrads with single exchanges. These changes resembled the IEC in rearranged chromosomes (in this case, in chromosomes bearing an insertion). Thus, the age changes of crossing over are similar to the consequences of the presence or absence of IEC. Age changes in crossing over in a chromosome depended both on the local rearrangements in this chromosome (the local effect on crossing over, LEC) and on rearrangements in nonhomologous chromosomes (IEC). In the first broods, both LEC and IEC decreased with an increase in the level of crossing over. In subsequent broods, the reduced level of crossing over was accompanied by an increase in both LEC and IEC. This suggests that the mechanisms responsible for the age changes in crossing over and IEC may have common steps. The contact model of crossing over may explain the similarity between the age changes in crossing-over and IEC. It is suggested that both phenomena result from delayed determination of crossing over in a meiotic cell. This may occur due to the retarded formation of the local contacts in one of the homologous chromosome pairs or because a higher number of local contacts is required to trigger crossing over in a meiotic cell (of early age).     

Know thy mouse

In science it is imperative that the basic reagents and materials are defined and uniform. Unlike chemical reagents, which are uniform over time, mice, like all living creatures, have an intrinsic genetic drive to change, with mutations accumulating over time leading to increasing genetic variation and phenotypic change. Such changes compromise the reproducibility of experimental data over time and place. The use of the mouse has expanded rapidly in recent years and many scientists who have turned to the mouse as a research model might be unaware of the profound impact of changes in genetic background. Here we discuss the sources of genetic change and strategies to reduce them with the idea of strengthening international genetic standards for inbred mice.     

Up-down biphasic volume response of human red blood cells to PIEZO1 activation during capillary transits

In this paper we apply a novel JAVA version of a model on the homeostasis of human red blood cells (RBCs) to investigate the changes RBCs experience during single capillary transits. In the companion paper we apply a model extension to investigate the changes in RBC homeostasis over the approximately 200000 capillary transits during the ~120 days lifespan of the cells. These are topics inaccessible to direct experimentation but rendered mature for a computational modelling approach by the large body of recent and early experimental results which robustly constrain the range of parameter values and model outcomes, offering a unique opportunity for an in depth study of the mechanisms involved. Capillary transit times vary between 0.5 and 1.5s during which the red blood cells squeeze and deform in the capillary stream transiently opening stress-gated PIEZO1 channels allowing ion gradient dissipation and creating minuscule quantal changes in RBC ion contents and volume. Widely accepted views, based on the effects of experimental shear stress on human RBCs, suggested that quantal changes generated during capillary transits add up over time to develop the documented changes in RBC density and composition during their long circulatory lifespan, the quantal hypothesis. Applying the new red cell model (RCM) we investigated here the changes in homeostatic variables that may be expected during single capillary transits resulting from transient PIEZO1 channel activation. The predicted quantal volume changes were infinitesimal in magnitude, biphasic in nature, and essentially irreversible within inter-transit periods. A sub-second transient PIEZO1 activation triggered a sharp swelling peak followed by a much slower recovery period towards lower-than-baseline volumes. The peak response was caused by net CaCl₂ and fluid gain via PIEZO1 channels driven by the steep electrochemical inward Ca²⁺ gradient. The ensuing dehydration followed a complex time-course with sequential, but partially overlapping contributions by KCl loss via Ca²⁺-activated Gardos channels, restorative Ca²⁺ extrusion by the plasma membrane calcium pump, and chloride efflux by the Jacobs-Steward mechanism. The change in relative cell volume predicted for single capillary transits was around 10⁻⁵, an infinitesimal volume change incompatible with a functional role in capillary flow. The biphasic response predicted by the RCM appears to conform to the quantal hypothesis, but whether its cumulative effects could account for the documented changes in density during RBC senescence required an investigation of the effects of myriad transits over the full four months circulatory lifespan of the cells, the subject of the next paper.     

Variations in the Biological Functions of HIV-1 Clade C Envelope in a SHIV-Infected Rhesus Macaque during Disease Progression

A better understanding of how the biological functions of the HIV-1 envelope (Env) changes during disease progression may aid the design of an efficacious anti-HIV-1 vaccine. Although studies from patient had provided some insights on this issue, the differences in the study cohorts and methodology had make it difficult to reach a consensus of the variations in the HIV-1 Env functions during disease progression. To this end, an animal model that can be infected under controlled environment and reflect the disease course of HIV-1 infection in human will be beneficial. Such an animal model was previously demonstrated by the infection of macaque with SHIV, expressing HIV-1 clade C Env V1-V5 region. By using this model, we examined the changes in biological functions of Env in the infected animal over the entire disease course. Our data showed an increase in the neutralization resistance phenotype over time and coincided with the decrease in the net charges of the V1-V5 region. Infection of PBMC with provirus expressing various Env clones, isolated from the infected animal over time, showed a surprisingly better replicative fitness for viruses expressing the Env from early time point. Biotinylation and ELISA data also indicated a decrease of cell-surface-associated Env and virion-associated gp120 content with disease progression. This decrease did not affect the CD4-binding capability of Env, but were positively correlated with the decrease of Env fusion ability. Interestingly, some of these changes in biological functions reverted to the pre-AIDS level during advance AIDS. These data suggested a dynamic relationship between the Env V1-V5 region with the host immune pressure. The observed changes of biological functions in this setting might reflect and predict those occurring during natural disease progression in human.     

Simulation of human sleep: ultradian dynamics of electroencephalographic slow-wave activity

The typical declining trend of electroencephalographic (EEG) slow-wave activity (SWA) within a sleep period is represented in the two-process model of sleep regulation by an exponentially decaying process (Process S). The model has been further elaborated to simulate not only the global changes of SWA, but also the dynamics within non-rapid-eye-movement (non-REM) sleep episodes. In this new model, the initial intraepisodic buildup of SWA is determined by the combined action of an exponentially increasing process and a saturation process, whereas its fall at the end of an episode is due to an exponentially decreasing process. The global declining trend of SWA over consecutive episodes results from the monotonic decay of the intraepisodic saturation level. In contrast to Process S in the two-process model, this decay is not represented by an exponential function, but is proportional to the momentary level of SWA. REM sleep episodes are triggered by an external function. The model allows one to simulate the ultradian pattern of SWA for baseline nights as well as changes induced by a prolonged waking period, a daytime nap, a partial slow-wave sleep deprivation, or an antidepressant drug.     

A ratio model of perceived speed in the human visual system

The perceived speed of moving images changes over time. Prolonged viewing of a pattern (adaptation) leads to an exponential decrease in its perceived speed. Similarly, responses of neurones tuned to motion reduce exponentially over time. It is tempting to link these phenomena. However, under certain conditions, perceived speed increases after adaptation and the time course of these perceptual effects varies widely. We propose a model that comprises two temporally tuned mechanisms whose sensitivities reduce exponentially over time. Perceived speed is taken as the ratio of these filters' outputs. The model captures increases and decreases in perceived speed following adaptation and describes our data well with just four free parameters. Whilst the model captures perceptual time courses that vary widely, parameter estimates for the time constants of the underlying filters are in good agreement with estimates of the time course of adaptation of direction selective neurones in the mammalian visual system.     

An exploratory model of the impact of rapid climate change on the world food situation

A simple, globally aggregated, stochastic-simulation model was constructed to examine the effects of rapid climatic change on agriculture and the human population. The model calculates population size and the production, consumption and storage of grain under different climate scenarios over a 20-year projection time. In most scenarios, either an optimistic baseline annual increase of agricultural output of 1.7% or a more pessimistic appraisal of 0.9% was used. The rate of natural increase of the human population exclusive of excess hunger-related deaths was set as 1.7% per year and climatic changes with both negative and positive impacts on agriculture were assessed. Analysis of the model suggests that the number of hunger-related deaths could double (with reference to an estimated 200 million deaths in the past two decades) if grain production keeps pace with population growth but climatic conditions are unfavourable. If the rate of increase in grain production is about half that of population growth, the number of hunger-related deaths could increase about fivefold (over past levels); the impact of climatic change is relatively small under this imbalance. Even favourable climatic changes that enhance agricultural production may not prevent a fourfold increase in deaths (over past levels) under scenarios where population growth outpaces production by about 0.8% per annum. These results may foreshadow a fundamental change where, for the first time, absolute global food deficits compound inequities in food production and distribution in causing famine. The model also highlights the effectiveness of reducing population growth rates as a strategy for minimizing the impact of global climate change and maintaining food supplies for everyone.