Creation of a Muslim Empire: ‘Alid Revolts & the Marwanids in Perspective

This paper will argue that the Umayyad Caliphs of the Marwanid branch, especially but not limited to the Caliph Abd-al Malik ibn Marwan (r. 685-705), forged what would become the idea of (early) ‘Islamic’ identity and orthodoxy. This paper gives reasons for why this happened and how it happened based on a range of sources that examine the socio-religious practices of the time, including legal pronouncements to near contemporary Near Eastern legends; our knowledge of this period needs to be reconstructed delicately due to the relatively few contemporary sources we have. Indeed, the Umayyads, largely castigated in historiography, both modern and pre-modern, as being a ‘corrupt’, ‘impious’ and ‘despotic’, are often overshadowed in the popular imagination by the four Rashidun Caliphs (Abu Bakr, Omar, Uthman, Ali). As this paper will show however, unlike the Rashidun Caliphs based in isolated Arabia, it was the Umayyads of the Marwanid branch who were instrumental in laying the foundations of what would become a Muslim and Arab identity, situated as they were at the heart of a cosmopolitan empire based in Damascus, with strong Christian Byzantine and Zoroastrian Sassanid influences. In other words, it was the Marwanids, following religious policy precedents of their predecessors, established in Late Antiquity, who created what would become a distinctively ‘Muslim’ empire, rather than solely an Arab one. Abd al-Malik and his successors achieved this through an ambitious and dramatic series of institutional reforms and embarked upon monumental construction projects which are still strongly identified with the religion today in the late seventh and early eighth centuries CE. This included the construction of the al-Aqsa Mosque, sumptuary laws demarking Muslims from non-Muslims, and the promulgation of Arabic as the language of not only religion but also administration. The reason for this flurried activity was pressure emanating from messianic inspired ‘Alid revolts (those claiming rulership through descent from Ali). The challenges posed by Abdullah ibn al-Zubayr (r. 683-692) and Mukhtar (r. 685-687) would lead to the Marwanids styling themselves decisively as pious Muslim and Arab rulers, setting the tone for the rest of the Empires elites from the Pyrenees to the Indus. The ‘Arabization’ and ‘Islamization’ of the Empire therefore was not a pre-determined outcome, but a result of a crisis of legitimacy effecting the Umayyad dynasty through a series of pretender revolts

MCMC Bayesian Estimation in FIEGARCH Models

Bayesian inference for fractionally integrated exponential generalized autoregressive conditional heteroskedastic (FIEGARCH) models using Markov Chain Monte Carlo (MCMC) methods is described. A simulation study is presented to access the performance of the procedure, under the presence of long-memory in the volatility. Samples from FIEGARCH processes are obtained upon considering the generalized error distribution (GED) for the innovation process. Different values for the tail-thickness parameter \nu are considered covering both scenarios, innovation processes with lighter (\nu2) tails than the Gaussian distribution (\nu=2). A sensitivity analysis is performed by considering different prior density functions and by integrating (or not) the knowledge on the true parameter values to select the hyperparameter values

A Boolean probabilistic model of metabolic adaptation to oxygen in relation to iron homeostasis and oxidative stress

<p>Abstract</p> <p>Background</p> <p>In aerobically grown cells, iron homeostasis and oxidative stress are tightly linked processes implicated in a growing number of diseases. The deregulation of iron homeostasis due to gene defects or environmental stresses leads to a wide range of diseases with consequences for cellular metabolism that remain poorly understood. The modelling of iron homeostasis in relation to the main features of metabolism, energy production and oxidative stress may provide new clues to the ways in which changes in biological processes in a normal cell lead to disease.</p> <p>Results</p> <p>Using a methodology based on probabilistic Boolean modelling, we constructed the first model of yeast iron homeostasis including oxygen-related reactions in the frame of central metabolism. The resulting model of 642 elements and 1007 reactions was validated by comparing simulations with a large body of experimental results (147 phenotypes and 11 metabolic flux experiments). We removed every gene, thus generating <it>in silico </it>mutants. The simulations of the different mutants gave rise to a remarkably accurate qualitative description of most of the experimental phenotype (overall consistency > 91.5%). A second validation involved analysing the anaerobiosis to aerobiosis transition. Therefore, we compared the simulations of our model with different levels of oxygen to experimental metabolic flux data. The simulations reproducted accurately ten out of the eleven metabolic fluxes. We show here that our probabilistic Boolean modelling strategy provides a useful description of the dynamics of a complex biological system. A clustering analysis of the simulations of all <it>in silico </it>mutations led to the identification of clear phenotypic profiles, thus providing new insights into some metabolic response to stress conditions. Finally, the model was also used to explore several new hypothesis in order to better understand some unexpected phenotypes in given mutants.</p> <p>Conclusions</p> <p>All these results show that this model, and the underlying modelling strategy, are powerful tools for improving our understanding of complex biological problems.</p

Metabolomic profiling of macrophages determines the discrete metabolomic signature and metabolomic interactome triggered by polarising immune stimuli

Priming and activating immune stimuli have profound effects on macrophages, however, studies generally evaluate stimuli in isolation rather than in combination. In this study we have investigated the effects of pro-inflammatory and anti-inflammatory stimuli either alone or in combination on macrophage metabolism. These stimuli include host factors such as IFNγ and ovalbumin-immunoglobulin immune complexes, or pathogen factors such as LPS. Untargeted LC-MS based metabolomics provided an in-depth profile of the macrophage metabolome, and revealed specific changes in metabolite abundance upon either individual stimuli or combined stimuli. Here, by factoring in an interaction term in the linear model, we define the metabolome interactome. This approach allowed us to determine whether stimuli interact in a synergistic or antagonistic manner. In conclusion this study demonstrates a robust approach to interrogate immune-metabolism, especially systems that model host-pathogen interactions