IET Systems Biology
Volume 14, Issue 5, October 2020
Volumes & issues:
Volume 14, Issue 5
October 2020
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- Author(s): Abhilash Patel and Shaunak Sen
- Source: IET Systems Biology, Volume 14, Issue 5, p. 217 –222
- DOI: 10.1049/iet-syb.2019.0123
- Type: Article
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p.
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Understanding constraints on the functional properties of biomolecular circuit dynamics, such as the possible variations of amplitude and timescale of a pulse, is an important part of biomolecular circuit design. While the amplitude-timescale co-variations of the pulse in an incoherent feedforward loop have been investigated computationally using mathematical models, experimental support for any such constraints is relatively unclear. Here, the authors address this using experimental measurement of an existing pulse generating incoherent feedforward loop circuit realisation in the context of a standard mathematical model. They characterise the trends of co-variation in the pulse amplitude and rise time computationally by randomly exploring the parameter space. They experimentally measured the co-variation by varying inducers and found that larger amplitude pulses have a slower rise time. They discuss the gap between the experimental measurements and predictions of the standard model, highlighting model additions and other biological factors that might bridge the gap.
- Author(s): Muhammad Waleed Khan ; Muhammad Abid ; Abdul Qayyum Khan ; Ghulam Mustafa ; Muzamil Ali ; Asifullah Khan
- Source: IET Systems Biology, Volume 14, Issue 5, p. 223 –229
- DOI: 10.1049/iet-syb.2020.0030
- Type: Article
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223
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By providing the generalisation of integration and differentiation, and incorporating the memory and hereditary effects, fractional-order modelling has gotten significant attention in the past few years. One of the extensively studied and utilised models to describe the glucose–insulin system of a human body is Bergman's minimal model. This non-linear model comprises of integer-order differential equations. However, comparison with the experimental data shows that the fractional-order version of Bergman's minimal model is a better representative of the glucose–insulin system than its original integer-order model. To design a control law for an artificial pancreas for a diabetic patient using a fractional-order model, different techniques, including feedback linearisation, have been applied in the literature. The authors’ previous work shows that the fractional-order version of Bergman's model describes the glucose–insulin system in a better way than the integer-order model. This study applies the sliding mode control technique and then compares the obtained simulation results with the ones obtained using feedback linearisation.
- Author(s): Dhruba Jyoti Bora and Rajdeep Dasgupta
- Source: IET Systems Biology, Volume 14, Issue 5, p. 230 –240
- DOI: 10.1049/iet-syb.2020.0049
- Type: Article
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230
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The skin is a complex biological tissue whose impedance varies with frequency. The properties and structure of skin changes with the location on the body, age, geographical location and other factors. Considering these factors, skin impedance analysis is a sophisticated data analysis. However, despite all these variations, various researchers have always worked to develop an equivalent electrical model of the skin. The two most important categories of electrical models are RC-based model and CPE-based model which focus on the physiological stratification and biological properties of skin, respectively. In this work, experimental skin impedance data is acquired from ten sites on the body to find the fitting model. It is observed that a hybrid of fractional-order CPE-based model and higher-order RC layered-based model can provide the best fitting electrical model of skin. A new model is developed with this hybrid orders. Genetic algorithm is used for the extraction of parameter components. Least error of fitting has been observed for the proposed model as compared with the other models. This model can be used in correlating many skin problems and in the development of diagnostic tools. It will offer an additional supportive tool in-vitro to the medical specialist.
- Author(s): Cifha Crecil Dias ; Surekha Kamath ; Sudha Vidyasagar
- Source: IET Systems Biology, Volume 14, Issue 5, p. 241 –251
- DOI: 10.1049/iet-syb.2020.0053
- Type: Article
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The complete automated control and delivery of insulin and glucagon in type 1 diabetes is the developing technology for artificial pancreas. This improves the quality of life of a diabetic patient with the precise infusion. The amount of infusion of these hormones is controlled using a control algorithm, which has the prediction property. The control algorithm model predictive control (MPC) predicts one step ahead and infuses the hormones continuously according to the necessity for the regulation of blood glucose. In this research, the authors propose a MPC control algorithm, which is novel for a dual hormone infusion, for a mathematical model such as Sorenson model, and compare it with the insulin alone or single hormone infusion developed with MPC. Since they aim for complete automatic control and regulation, unmeasured disturbances at a random time are integrated and the performance evaluation is projected through statistical analysis. The blood glucose risk index (BGRI) and control variability grid analysis (CVGA) plot gives the additional evaluation for the comparative results of the two controllers claiming 88% performance by dual hormone evaluated through CVGA plot and 2.05 mg/dl average tracking error, 2.20 BGRI. The MPC developed for dual hormone significantly performs better and the time spent in normal glycaemia is longer while eliminating the risk of hyperglycaemia and hypoglycaemia.
- Author(s): Da-Ping Yang ; Hui-Ping Lu ; Gang Chen ; Jie Yang ; Li Gao ; Jian-Hua Song ; Shang-Wei Chen ; Jun-Xian Mo ; Jin-Liang Kong ; Zhong-Qing Tang ; Chang-Bo Li ; Hua-Fu Zhou ; Lin-Jie Yang
- Source: IET Systems Biology, Volume 14, Issue 5, p. 252 –260
- DOI: 10.1049/iet-syb.2020.0063
- Type: Article
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This study aimed to investigate the clinicopathological significance and prospective molecular mechanism of RUNX family transcription factor 2 (RUNX2) in lung squamous cell carcinoma (LUSC). The authors used immunohistochemistry (IHC), RNA-seq, and microarray data from multi-platforms to conduct a comprehensive analysis of the clinicopathological significance and molecular mechanism of RUNX2 in the occurrence and development of LUSC. RUNX2 expression was significantly higher in 16 LUSC tissues than in paired non-cancerous tissues detected by IHC (P < 0.05). RNA-seq data from the combination of TCGA and genotype-tissue expression (GTEx) revealed significantly higher expression of RUNX2 in 502 LUSC samples than in 476 non-cancer samples. The expression of RUNX2 protein was also significantly higher in pathologic T3-T4 than in T1-T2 samples (P = 0.031). The pooled standardised mean difference (SMD) for RUNX2 was 0.87 (95% CI, 0.58–1.16), including 29 microarrays from GEO and one from ArrayExpress. The co-expression network of RUNX2 revealed complicated connections between RUNX2 and 45 co-expressed genes, which were significantly clustered in pathways including ECM-receptor interaction, focal adhesion, protein digestion and absorption, human papillomavirus infection and PI3K-Akt signalling pathway. Overexpression of RUNX2 plays an essential role in the clinical progression of LUSC.
- Author(s): Mostafa Nazari ; Morteza Nazari ; Mohammad Hadi Noori Skandari
- Source: IET Systems Biology, Volume 14, Issue 5, p. 261 –270
- DOI: 10.1049/iet-syb.2020.0054
- Type: Article
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A mixed chemotherapy–immunotherapy treatment protocol is developed for cancer treatment. Chemotherapy pushes the trajectory of the system towards the desired equilibrium point, and then immunotherapy alters the dynamics of the system by affecting the parameters of the system. A co-existing cancerous equilibrium point is considered as the desired equilibrium point instead of the tumour-free equilibrium. Chemotherapy protocol is derived using the pseudo-spectral (PS) controller due to its high convergence rate and simple implementation structure. Thus, one of the contributions of this study is simplifying the design procedure and reducing the controller computational load in comparison with Lyapunov-based controllers. In this method, an infinite-horizon optimal control problem is proposed for a non-linear cancer model. Then, the infinite-horizon optimal control of cancer is transformed into a non-linear programming problem. The efficient Legendre PS scheme is suggested to solve the proposed problem. Then, the dynamics of the system is modified by immunotherapy is another contribution. To restrict the upper limit of the chemo-drug dose based on the age of the patients, a Mamdani fuzzy system is designed, which is not present yet. Simulation results on four different dynamics cases how the efficiency of the proposed treatment strategy.
- Author(s): Sa'ed Abed ; Adnan Rashid ; Osman Hasan
- Source: IET Systems Biology, Volume 14, Issue 5, p. 271 –283
- DOI: 10.1049/iet-syb.2020.0026
- Type: Article
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Synthetic biology is an interdisciplinary field that uses well-established engineering principles for performing the analysis of the biological systems, such as biological circuits, pathways, controllers and enzymes. Conventionally, the analysis of these biological systems is performed using paper-and-pencil proofs and computer simulation methods. However, these methods cannot ensure accurate results due to their inherent limitations. Higher-order-logic (HOL) theorem proving is proposed and used as a complementary approach for analysing linear biological systems, which is based on developing a mathematical model of the genetic circuits and the bio-controllers used in synthetic biology based on HOL and analysing it using deductive reasoning in an interactive theorem prover. The involvement of the logic, mathematics and the deductive reasoning in this method ensures the accuracy of the analysis. It is proposed to model the continuous dynamics of the genetic circuits and their associated controllers using differential equations and perform their transfer function-based analysis using the Laplace transform in a theorem prover. For illustration, the genetic circuits of activated and repressed expressions and autoactivation of protein, and phase lag and lead controllers, which are widely used in cancer-cell identifiers and multi-input receptors for precise disease detection, are formally analyzed.
- Author(s): Fang Yan ; Li Liu ; Qingyun Wang
- Source: IET Systems Biology, Volume 14, Issue 5, p. 284 –291
- DOI: 10.1049/iet-syb.2020.0034
- Type: Article
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The transcription factor NF-κB links immune response and inflammatory reaction and its different oscillation patterns determine different cell fates. In this study, a mathematical model with IκBα protein synthesis time delay is developed based on the experimental evidences. The results show that time delay has the ability to drive oscillation of NF-κB via Hopf bifurcation. Meanwhile, the amplitude and period are sensitive to the time delay. Moreover, the time delay threshold is a function of four parameters characterising the negative feedback loop. Likewise, the parameters also have effects on the amplitude and period of NF-κB oscillation induced by time delay. Therefore, the oscillation patterns of NF-κB are collaborative results of time delay coupled with the negative feedback loop. These results not only enhance the understanding of NF-κB biological oscillation but also provide clues for the development of anti-inflammatory or anti-cancer drugs.
- Author(s): Prithvi Singh ; Mohd Amir ; Upasana Chaudhary ; Fozail Ahmad ; Sachin Bhatt ; Shweta Sankhwar ; Ravins Dohare
- Source: IET Systems Biology, Volume 14, Issue 5, p. 292 –296
- DOI: 10.1049/iet-syb.2020.0039
- Type: Article
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292
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About 30% of the world population is infected with Mycobacterium tuberculosis (MTB). It is wellknown that the gene expression in MTB is highly variable, thus screening of traditional single-genein MTB has been incapable to meet the desires of clinical diagnosis. In this report, the authorssystemically analysed the transcription regulatory network (TRN) in MTB H37Rv. Thecomplex interplay of these gene interactions has been revealed using exhaustive topological andglobal analysis of TRN using parameters including indegree, outdegree, degree, directed andundirected average path length (APL), and randomly performed. Results from indegree analysis reveala set of important genes, including papA5 and Rv0177 which areassociated with high indegree values. Gene ontology analysis suggested their importance in thevirulence of MTB. In addition, APL and analysis of highly significant genes further identified somecritical genes with different APL values. Among the list of genes identified, thecsoR gene has the shortest directed APL score and high outdegree value, thussuggesting their importance in maintaining network topology. This study provides a comprehensiveanalysis of TRN and offers a good basis of understanding for developing experimental study in searchof new therapeutic targets against MTB H37Rv pathogen.
- Author(s): Shenshuang Zhou ; Wei Zhang ; Yuan Zhang ; Xuan Ni ; Zhouhong Li
- Source: IET Systems Biology, Volume 14, Issue 5, p. 297 –306
- DOI: 10.1049/iet-syb.2020.0050
- Type: Article
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p.
297
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Extensive experimental evidence has been demonstrated that the dynamics of CDK1-APC feedback loop play crucial roles in regulating cell cycle processes, but the dynamical mechanisms underlying the regulation of this loop are still not completely understood. Here, the authors systematically investigated the stability and bifurcation criteria for a delayed CDK1-APC feedback loop. They showed that the maximum reaction rate of CDK1 inactivation by APC can drive sustained oscillations of CDK1 activity () and APC activity (), and the amplitude of these oscillations is increasing with the increase of the reaction rate over a wide range; a certain range of the self-activation rate for CDK1 is also significant for generating these oscillations, for too high or too low rates the oscillations cannot be generated. Moreover, they derived the sufficient conditions to determine the stability and Hopf bifurcations, and found that the sum of time delays required for activating CDK1 and APC can induce and to be oscillatory, even when the and settle in a definite stable steady state. Furthermore, they presented an explicit algorithm for the properties of periodic oscillations. Finally, numerical simulations have been presented to justify the validity of theoretical analysis.
Experimental evidence for constraints in amplitude-timescale co-variation of a biomolecular pulse generating circuit design
Sliding mode control for a fractional-order non-linear glucose-insulin system
Estimation of skin impedance models with experimental data and a proposed model for human skin impedance
Design of dual hormone blood glucose therapy and comparison with single hormone using MPC algorithm
Integrated expression analysis revealed RUNX2 upregulation in lung squamous cell carcinoma tissues
Pseudo-spectral method for controlling the drug dosage in cancer
Formal reasoning about synthetic biology using higher-order-logic theorem proving
Combinatorial dynamics of protein synthesis time delay and negative feedback loop in NF-κB signalling pathway
Identification of robust genes in transcriptional regulatory network of Mycobacteriumtuberculosis
Bifurcation and oscillatory dynamics of delayed CDK1-APC feedback loop
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