Rhodiosin and herbacetin in Rhodiola rosea preparations: additional markers for quality control?

Context: Rhodiola rosea L. (Crassulaceae) is well-known to contain flavonoids such as the herbacetin derivative rhodiosin. However, flavonoids are not typically used in quality control. Objective: This study analyses two flavonoids of R. rosea rhizomes and roots for their potential as analytical markers. Materials and methods: Two constituents were isolated from ethanolic extracts via HPLC, identified via NMR and quantified via RP-HPLC. Presence and content variation was investigated according to extraction (solvent and repetitions), drying (temperature and duration) and sample origin (homogenously cultivated plants of different provenance, commercial samples). Results: Rhodiosin was identified as a main flavonoid, accompanied by 10-fold lower concentrated herbacetin. Both compounds were best extracted with 70–90% ethanol, but were also detectable in more aqueous extracts. Different drying conditions had no effect on the flavonoid content. These two flavonoids were consistently identified in rhizome and root extracts of over 100 R. rosea samples. Rhizomes tend to contain less flavonoids, with average ratios of rosavins to flavonoids of 1.4 (rhizomes) and 0.4 (roots). Provenance differences were detected in the range (rhodiosin plus herbacetin) of 760–6300 µg/mL extract corresponding to a maximum of approximately 0.5–4.2% (w/w) in the dry drug. Conclusions: For the first time, two main flavonoids present in R. rosea were quantified systematically. Rhodiosin and herbacetin can be detected simultaneously to phenylpropenoids or salidroside in authentic samples, influenced by the plant part examined and the plant origin. Rhodiosin and herbacetin may serve as additional marker to guarantee a consistent content of R. rosea products

Testing the Power-Law Hypothesis of the Inter-Conflict Interval

The severity of war, measured by battle deaths, follows a power-law distribution. Here, we demonstrate that power law also holds in the temporal aspects of interstate conflicts. A critical quantity is the inter-conflict interval (ICI), the interval between the end of a conflict in a dyad and the start of the subsequent conflict in the same dyad. Using elaborate statistical tests, we confirmed that the ICI samples compiled from the history of interstate conflicts from 1816 to 2014 followed a power-law distribution. We propose an information-theoretic model to account for the power-law properties of ICIs. The model predicts that a series of ICIs in each dyad is independently generated from an identical power-law distribution. This was confirmed by statistical examination of the autocorrelation of the ICI series. Our findings help us understand the nature of wars between normal states, the significance of which has increased since the Russian invasion of Ukraine in 2022

Mobility and interaction patterns in social networks

The question of analyzing the predictability of human behavior has been widely studied in literature, to unveil how individuals move, how they can be mobilized and, more philosophically, to understand to what extent our decisions are random or whether we are free to choose. As a consequence of humans relate to each other, we also tend to live in groups at different hierarchies in a social way so it is interesting to analyze how individual features and choices affect the global structure of a society. In this work, we explore the limits of human predictability in terms of shopping behavior, observing that, even when we are constrained to a limited set of possible places where we can make a purchase, predicting where the next purchase will happen is not accurately possible to do by only observing the past. The next question is to study how individual decisions affect emergent phenomena such as the economy or information diffusion across a country. We analyze the contents, temporal and mobility patterns extracted from users’ social media publications to build a profile of the geographical regions that allow to predict the unemployment rate. Finally, we also use a mobile phone call dataset to test whether the dynamics at the urban level, how people create and destroy links within a city, affect the inter-urban diffusion of diseases, virus or rumors. Our results suggest that inter-regional structure is robust and does not vary significantly on time so diffusion processes can be well modeled in terms of static properties of the inter-urban network.Programa Oficial de Doctorado en Ingeniería MatemáticaPresidente: Javier Borge Holthoefer.- Secretario: Rubén Cuevas Rumín.- Vocal: Josep Perelló Palo

Volume 119-20: 1954-55

Annals of the Congregation of the Mission, or collection of edifying letters