Sofia University

About: Sofia University is a education organization based out in Sofia, Bulgaria. It is known for research contribution in the topics: Large Hadron Collider & Laser. The organization has 8533 authors who have published 15730 publications receiving 306320 citations. The organization is also known as: University of Sofia & BFUS.

Delayed fluorescence in photosynthesis

Abstract: Photosynthesis is a very efficient photochemical process. Nevertheless, plants emit some of the absorbed energy as light quanta. This luminescence is emitted, predominantly, by excited chlorophyll a molecules in the light-harvesting antenna, associated with Photosystem II (PS II) reaction centers. The emission that occurs before the utilization of the excitation energy in the primary photochemical reaction is called prompt fluorescence. Light emission can also be observed from repopulated excited chlorophylls as a result of recombination of the charge pairs. In this case, some time-dependent redox reactions occur before the excitation of the chlorophyll. This delays the light emission and provides the name for this phenomenon—delayed fluorescence (DF), or delayed light emission (DLE). The DF intensity is a decreasing polyphasic function of the time after illumination, which reflects the kinetics of electron transport reactions both on the (electron) donor and the (electron) acceptor sides of PS II. Two main experimental approaches are used for DF measurements: (a) recording of the DF decay in the dark after a single turnover flash or after continuous light excitation and (b) recording of the DF intensity during light adaptation of the photosynthesizing samples (induction curves), following a period of darkness. In this paper we review historical data on DF research and recent advances in the understanding of the relation between the delayed fluorescence and specific reactions in PS II. An experimental method for simultaneous recording of the induction transients of prompt and delayed chlorophyll fluorescence and decay curves of DF in the millisecond time domain is discussed.

The Genomic History Of Southeastern Europe

Abstract: Farming was first introduced to southeastern Europe in the mid-7th millennium BCE - brought by migrants from Anatolia who settled in the region before spreading throughout Europe. However, the dynamics of the interaction between the first farmers and the indigenous hunter-gatherers remain poorly understood because of the near absence of ancient DNA from the region. We report new genome-wide ancient DNA data from 204 individuals-65 Paleolithic and Mesolithic, 93 Neolithic, and 46 Copper, Bronze and Iron Age-who lived in southeastern Europe and surrounding regions between about 12,000 and 500 BCE. We document that the hunter-gatherer populations of southeastern Europe, the Baltic, and the North Pontic Steppe were distinctive from those of western Europe, with a West-East cline of ancestry. We show that the people who brought farming to Europe were not part of a single population, as early farmers from southern Greece are not descended from the Neolithic population of northwestern Anatolia that was ancestral to all other European farmers. The ancestors of the first farmers of northern and western Europe passed through southeastern Europe with limited admixture with local hunter-gatherers, but we show that some groups that remained in the region mixed extensively with local hunter-gatherers, with relatively sex-balanced admixture compared to the male-biased hunter-gatherer admixture that we show prevailed later in the North and West. After the spread of farming, southeastern Europe continued to be a nexus between East and West, with intermittent steppe ancestry, including in individuals from the Varna I cemetery and associated with the Cucuteni-Trypillian archaeological complex, up to 2,000 years before the Steppe migration that replaced much of northern Europe9s population.

Chlorophyll fluorescence as a tool for nutrient status identification in rapeseed plants

Abstract: In natural conditions, plants growth and development depends on environmental conditions, including the availability of micro- and macroelements in the soil. Nutrient status should thus be examined not by establishing the effects of single nutrient deficiencies on the physiological state of the plant but by combinations of them. Differences in the nutrient content significantly affect the photochemical process of photosynthesis therefore playing a crucial role in plants growth and development. In this work, an attempt was made to find a connection between element content in (i) different soils, (ii) plant leaves, grown on these soils and (iii) changes in selected chlorophyll a fluorescence parameters, in order to find a method for early detection of plant stress resulting from the combination of nutrient status in natural conditions. To achieve this goal, a mathematical procedure was used which combines principal component analysis (a tool for the reduction of data complexity), hierarchical k-means (a classification method) and a machine-learning method—super-organising maps. Differences in the mineral content of soil and plant leaves resulted in functional changes in the photosynthetic machinery that can be measured by chlorophyll a fluorescent signals. Five groups of patterns in the chlorophyll fluorescent parameters were established: the ‘no deficiency’, Fe-specific deficiency, slight, moderate and strong deficiency. Unfavourable development in groups with nutrient deficiency of any kind was reflected by a strong increase in F o and ΔV/Δt 0 and decline in φ Po, φ Eo δ Ro and φ Ro. The strong deficiency group showed the suboptimal development of the photosynthetic machinery, which affects both PSII and PSI. The nutrient-deficient groups also differed in antenna complex organisation. Thus, our work suggests that the chlorophyll fluorescent method combined with machine-learning methods can be highly informative and in some cases, it can replace much more expensive and time-consuming procedures such as chemometric analyses.

Sphere-to-rod transitions of nonionic surfactant micelles in aqueous solution modeled by molecular dynamics simulations.

Abstract: Control of the size and agglomeration of micellar systems is important for pharmaceutical applications such as drug delivery. Although shape-related transitions in surfactant solutions are studied experimentally, their molecular mechanisms are still not well understood. In this study, we use coarse-grained molecular dynamics simulations to describe micellar assemblies of pentaethylene glycol monododecyl ether (C12E5) in aqueous solution at different concentrations. The obtained size and aggregation numbers of the aggregates formed are in very good agreement with the available experimental data. Importantly, increase of the concentration leads to a second critical micelle concentration where a transition to rod-like aggregates is observed. This transition is quantified in terms of shape anisotropy, together with a detailed structural analysis of the micelles as a function of aggregation number.