A multiscale cell‐based model of tumor growth for chemotherapy assessment and tumor‐targeted therapy through a 3D computational approach

ObjectivesComputational modeling of biological systems is a powerful tool to clarify diverse processes contributing to cancer. The aim is to clarify the complex biochemical and mechanical interactions between cells, the relevance of intracellular signaling pathways in tumor progression and related events to the cancer treatments, which are largely ignored in previous studies.Materials and MethodsA three‐dimensional multiscale cell‐based model is developed, covering multiple time and spatial scales, including intracellular, cellular, and extracellular processes. The model generates a realistic representation of the processes involved from an implementation of the signaling transduction network.ResultsConsidering a benign tumor development, results are in good agreement with the experimental ones, which identify three different phases in tumor growth. Simulating tumor vascular growth, results predict a highly vascularized tumor morphology in a lobulated form, a consequence of cells'' motile behavior. A novel systematic study of chemotherapy intervention, in combination with targeted therapy, is presented to address the capability of the model to evaluate typical clinical protocols. The model also performs a dose comparison study in order to optimize treatment efficacy and surveys the effect of chemotherapy initiation delays and different regimens.ConclusionsResults not only provide detailed insights into tumor progression, but also support suggestions for clinical implementation. This is a major step toward the goal of predicting the effects of not only traditional chemotherapy but also tumor‐targeted therapies.     

Intrabasin variation in allometry coefficients of Lenkoran Capoeta capoeta gracilis (Keyserling, 1861) in the Gorganroud basin,southeast Caspian Sea,Iran

It is believed that streams of a basin may contribute to stream‐specific variation in allometry coefficients related to between‐habitat differences. To test intra‐basin variation of the allometry coefficients of Lenkorn Capoeta capoeta gracilis (Keyserling, 1861), a total of 1731 individuals were sampled in six streams of the Gorganroud basin (southeast Caspian Sea) between April and May 2008. Values of b ranged from 2.647 for males of Chelchai to 2.964 for females of Madarsou, indicating negative allometric growth for the fish in the basin. There were variations in the allometry coefficient among the considered groups, which can be interpreted as species’ response to different habitats. To the best knowledge of the authors, this study documents the comparative reference on variation of allometry coefficient of Capoeta capoeta gracilis in southeast Caspian streams.     

Identification of genes associated with kernel size in almond [Prunus dulcis (Mill.) D.A. Webb] using RNA-Seq

Plant Growth Regulation - Almond is a stone fruit crop belonging to the Rosaceae family, cultivated in the temperate region of the world for its high nutritive valued fruits. In today’s...     

Sodium nitroprusside: its beneficial role in drought stress tolerance of “Mexican lime” (Citrus aurantifolia (Christ.) Swingle) under in vitro conditions

In Vitro Cellular & Developmental Biology - Plant - As a novel antioxidant, sodium nitroprusside (SNP) can be used to reduce the adverse effects of various abiotic stresses, especially drought...     

microRNAs: New prognostic,diagnostic, and therapeutic biomarkers in cervical cancer

Cervical cancer is as a kind of cancer beginning from the cervix. Given that cervical cancer could be observed in women who infected with papillomavirus, regular oral contraceptives, and multiple pregnancies. Early detection of cervical cancer is one of the most important aspects of the therapy of this malignancy. Despite several efforts, finding and developing new biomarkers for cervical cancer diagnosis are required. Among various prognostic, diagnostic, and therapeutic biomarkers, miRNA have been emerged as powerful biomarkers for detection, treatment, and monitoring of response to therapy in cervical cancer. Here, we summarized various miRNAs as an employable platform for prognostic, diagnostic, and therapeutic biomarkers in the treatment of cervical cancer.     

Stress inhibits psychomotor performance differently in simple and complex open field environments

Stress affects psychomotor profiles and exploratory behavior in response to environmental features. Here we investigated psychomotor and exploratory patterns induced by stress in a simple open-field arena and a complex, multi-featured environment. Groups of rats underwent seven days of restraint stress or no-stress conditions and were individually tested in three versions of the ziggurat task (ZT) that varied according to environmental complexity. The hyperactivity of the hypothalamic–pituitary–adrenal (HPA) axis due to stress procedure was evaluated by the pre- and post-stress levels of circulating corticosterone (CORT). Horizontal activity, exploration, and motivation were measured by the number of fields entered, the time spent in the central fields, path length and speed, and stop duration. In addition, vertical exploratory behavior was measured by the times rats climbed onto ziggurats. Stress-induced psychomotor changes were indicated by reduced path length and path speed and increased duration of stops only within the complex arena of the ZT. Rats in stress groups also showed a significant decline in the vertical movements as measured by the number of climbing onto ziggurats. No stress-induced changes were revealed by the simple open-field arena. The exploratory patterns of stressed animals suggest psychomotor inhibition and reduced novelty-seeking behaviors in an environment-dependent manner. Thus, multi-featured arenas that require complex behavioral strategies are ideally suited to reveal the inhibitory effects of stress on psychomotor capabilities in rodents.     

Exploring the generality of associations between plant functional traits: evidence within ecological groups along an altitudinal gradient in Hyrcanian forest

We hypothesized that associations among plant functional traits may differ within different ecological assemblages and plant communities. Association among plant traits including plant maximum height, seed weight, fruit type, pollination mode, mean leaf area, and leaf type were explored within life forms, plant strategy groups along with lowland and montane forest vegetation. In total, 83 sampling plots of 400 m² were placed along a 2400 m altitudinal gradient in Hyrcanian forest. Importance‐values of species within vegetation types were used for weighting data and trait associations were explored using categorical principal component analysis. A G‐test and Fisher's exact test of independence were used to retest significance of the correlations. Different paired trait associations (association lines) including height–leaf, height–seed, height–pollination, leaf–seed, seed–fruit and fruit–pollination were observed and their ecological or physiological basis was discussed. Life forms, strategy types and vegetation types differed based on association lines. Some of the well‐known trade‐offs appear by increasing scale from ecological groups to vegetation types in Hyrcanian forest. The observed patterns of trait associations in Hyrcanian forest and several other ecosystems of the world call the generality of previously accepted trait correlations into question.     

A fuzzy-genetic model for estimating forces from electromyographical activity of antagonistic muscles due to planar lower arm movements: the effect of nonlinear muscle properties

The aim of this paper is to create a model for mapping the surface electromyogram (EMG) signals to the force that generated by human arm muscles. Because the parameters of each person's muscle are individual, the model of the muscle must have two characteristics: (1) The model must be adjustable for each subject. (2) The relationship between the input and output of model must be affected by the force-length and the force-velocity behaviors are proven through Hill's experiments. Hill's model is a kinematic mechanistic model with three elements, i.e. one contractile component and two nonlinear spring elements.In this research, fuzzy systems are applied to improve the muscle model. The advantages of using fuzzy system are as follows: they are robust to noise, they prove an adjustable nonlinear mapping, and are able to model the uncertainties of the muscle.Three fuzzy coefficients have been added to the relationships of force-length (active and passive) and force-velocity existing in Hill's model. Then, a genetic algorithm (GA) has been used as a biological search method that can adjust the parameters of the model in order to achieve the optimal possible fit.Finally, the accuracy of the fuzzy genetic implementation Hill-based muscle model (FGIHM) is invested as following: the FGIHM results have 12.4% RMS error (in worse case) in comparison to the experimental data recorded from three healthy male subjects. Moreover, the FGIHM active force-length relationship which is the key characteristics of muscles has been compared to virtual muscle (VM) and Zajac muscle model. The sensitivity of the FGIHM has been evaluated by adding a white noise with zero mean to the input and FGIHM has proved to have lower sensitivity to input noise than the traditional Hill's muscle model.