Complex Patterns of Excitability and Oscillations in a Biochemical System

1986 ◽  
pp. 291-305 ◽  
Author(s):  
A. Goldbeter ◽  
F. Moran
Keyword(s):  
Biochemical System ◽  
Complex Patterns

Art and Iconography

2019 ◽  
pp. 348-369
Author(s):  
Eric Gubel
Keyword(s):  
Bronze Age ◽  
North Africa ◽  
Sixth Century ◽  
Late Bronze Age ◽  
Cultural Interaction ◽  
First Millennium ◽  
Complex Patterns

Rooted in Late Bronze Age Levantine traditions, Phoenician art emerges in the early first millennium bce, spiced with new elements adopted and adapted from contemporary Egyptian models, while also permeable to influence from artistic trends popular with neighboring cultures and overseas recipients of Phoenician luxurious exports. During its acme between the late ninth and early seventh centuries bce, the art shared a common repertoire of motifs among sculptors, metalsmiths, ivory carvers, and seal cutters in a predominantly Egyptianizing style. Mass-produced terracotta plaques, figurines, and the minor arts displayed a more diversified array of autochthonous characteristics. In line with the evolution of sculpture, the Cypriot component was definitely replaced by Greek idioms from the later sixth century bce onward. If Punic art cannot possibly be defined as a mere perpetuation of the Phoenician production, and was impacted by more complex patterns of cultural interaction (e.g. North Africa, Iberia), the latter’s heritage is undeniable in many artistic media.

Complex patterns of Gondwanan biogeography revealed in a dispersal‐limited arachnid

2021 ◽  
Author(s):  
Shahan Derkarabetian ◽  
Caitlin M. Baker ◽  
Gonzalo Giribet
Keyword(s):  
Complex Patterns

scholarly journals Complex patterns of sequence variation and multiple 5‘ and 3‘ ends are found among transcripts of the erythroid ankyrin gene

1993 ◽  
Vol 268 (13) ◽  
pp. 9533-9540
Author(s):  
C.S. Birkenmeier ◽  
R.A. White ◽  
L.L. Peters ◽  
E.J. Hall ◽  
S.E. Lux ◽  
...  
Keyword(s):  
Sequence Variation ◽  
Complex Patterns

scholarly journals Complex patterns of circulating fatty acid levels in gestational diabetes mellitus subclasses across pregnancy

2021 ◽  
Author(s):  
Ting Zhang ◽  
Wen-Rong Jiang ◽  
Yin-Yin Xia ◽  
Toby Mansell ◽  
Richard Saffery ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Fatty Acid ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Complex Patterns

scholarly journals Speciation and Antibiotic Susceptibilities of Coagulase Negative Staphylococci Isolated from Ocular Infections

Antibiotics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 721
Author(s):  
John E. Romanowski ◽  
Shannon V. Nayyar ◽  
Eric G. Romanowski ◽  
Vishal Jhanji ◽  
Robert M. Q. Shanks ◽  
...  
Keyword(s):  
Empiric Therapy ◽  
Species Level ◽  
Opportunistic Pathogens ◽  
Coagulase Negative Staphylococci ◽  
Biochemical System ◽  
Ocular Infections ◽  
Antibiotic Susceptibilities ◽  
System 2 ◽  
Intravitreal Treatment ◽  
Susceptibility Profiles

Coagulase-negative staphylococci (CoNS) are frequently occurring ocular opportunistic pathogens that are not easily identifiable to the species level. The goal of this study was to speciate CoNS and document antibiotic susceptibilities from cases of endophthalmitis (n = 50), keratitis (n = 50), and conjunctivitis/blepharitis (n = 50) for empiric therapy. All 150 isolates of CoNS were speciated using (1) API Staph (biochemical system), (2) Biolog GEN III Microplates (phenotypic substrate system), and (3) DNA sequencing of the sodA gene. Disk diffusion antibiotic susceptibilities for topical and intravitreal treatment were determined based on serum standards. CoNS identification to the species level by all three methods indicated that S. epidermidis was the predominant species of CoNS isolated from cases of endophthalmitis (84–90%), keratitis (80–86%), and conjunctivitis/blepharitis (62–68%). Identifications indicated different distributions of CoNS species among endophthalmitis (6), keratitis (10), and conjunctivitis/blepharitis (13). Antibiotic susceptibility profiles support empiric treatment of endophthalmitis with vancomycin, and keratitis treatment with cefazolin or vancomycin. There was no clear antibiotic choice for conjunctivitis/blepharitis. S. epidermidis was the most frequently found CoNS ocular pathogen, and infection by other CoNS appears to be less specific and random. Antibiotic resistance does not appear to be a serious problem associated with CoNS.

scholarly journals Novel domain expansion methods to improve the computational efficiency of the Chemical Master Equation solution for large biological networks

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Rahul Kosarwal ◽  
Don Kulasiri ◽  
Sandhya Samarasinghe
Keyword(s):  
Master Equation ◽  
State Space ◽  
Performance Management ◽  
Numerical Solutions ◽  
De Novo ◽  
Exact Analytical Solution ◽  
Chemical Master Equation ◽  
The State ◽  
Biochemical System ◽  
Biochemical Systems

Abstract Background Numerical solutions of the chemical master equation (CME) are important for understanding the stochasticity of biochemical systems. However, solving CMEs is a formidable task. This task is complicated due to the nonlinear nature of the reactions and the size of the networks which result in different realizations. Most importantly, the exponential growth of the size of the state-space, with respect to the number of different species in the system makes this a challenging assignment. When the biochemical system has a large number of variables, the CME solution becomes intractable. We introduce the intelligent state projection (ISP) method to use in the stochastic analysis of these systems. For any biochemical reaction network, it is important to capture more than one moment: this allows one to describe the system’s dynamic behaviour. ISP is based on a state-space search and the data structure standards of artificial intelligence (AI). It can be used to explore and update the states of a biochemical system. To support the expansion in ISP, we also develop a Bayesian likelihood node projection (BLNP) function to predict the likelihood of the states. Results To demonstrate the acceptability and effectiveness of our method, we apply the ISP method to several biological models discussed in prior literature. The results of our computational experiments reveal that the ISP method is effective both in terms of the speed and accuracy of the expansion, and the accuracy of the solution. This method also provides a better understanding of the state-space of the system in terms of blueprint patterns. Conclusions The ISP is the de-novo method which addresses both accuracy and performance problems for CME solutions. It systematically expands the projection space based on predefined inputs. This ensures accuracy in the approximation and an exact analytical solution for the time of interest. The ISP was more effective both in predicting the behavior of the state-space of the system and in performance management, which is a vital step towards modeling large biochemical systems.

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