Subthreshold Nanosecond Laser

Zusammenfassung Ziel Diese Studie zielt darauf ab, die klinische Entwicklung von Symptomen und Komplikationen bei Patienten mit früher und mittelschwerer AMD (altersbedingte Makuladegeneration) zu bewerten, die mit einer unterschwelligen Nanosekunden-Lasertherapie (SNL) behandelt werden. Die SNL-Therapie ist eine nicht-invasive, schmerzfreie Behandlungsmethode mit einem frequenzverdoppelten Nanosekunden-Pulslaser mit diskontinuierlicher Strahlenergieverteilung. Methoden An einer einzigen Institution wurde eine Kohort-studie durchgeführt. Zwischen 2015 und 2018 wurden 438 Patienten mit früher und mittlerer AMD (Alter 55-80) identifiziert. 160 Patienten wurden nach der Ausschlusskriterien identifiziert. Die Patienten, die der SNL- Therapie zustimmten, waren 64 Patienten, die anderen Patienten lehnten die SNL-Therapie ab und wurden als Kontrollgruppe eingeschlossen. Die Patienten mit Pseudodrusen wurden identifiziert und ausgeschlossen. Die primären Endpunkte waren die Verringerung der Anzahl und Drusenfläche als Umkehrung früher klinischer Indikatoren für AMD. Die sekundären Endpunkte waren die Veränderung der mittleren Sehschärfe nach dem 6. Monat und das Fortschreiten zu einer fortgeschrittenen altersbedingten Makuladegeneration (AMD) im behandelten Auge. Um teilnahmeberechtigt zu sein, sollten die Patienten zuvor keine anderen Augenerkrankungen haben, die die interessierenden Ergebnisse beeinflussen könnten, wie z. B. diabetische Retinopathie, Katarakt, schweres Glaukom oder Behandlung während der Studie. Ergebnisse Es wurde eine Umkehrung früher klinischer Anzeichen von AMD dokumentiert, die sich in einer Verringerung der Anzahl und Größe der Drusen zeigten (jeweils p < 0,001). Innerhalb des 6-monatigen Follow-up war die Progressionsrate der Drusengröße und -anzahl in der SNL-Gruppe signifikant niedriger (26 %) als in der Kontrollgruppe (69 %; p < 0,001). Keine Verbesserung der Sehschärfe (LogMar) wurde in der SNL-Gruppe im Vergleich zur Nicht- SNL-Gruppe dokumentiert (jeweils p 0,59). Fazit Diese Studie hebt die SNL-Therapie als mögliche Therapieoption hervor, um die frühen klinischen Anzeichen von AMD umzukehren. Die vorliegende Studie liefert neue Hinweise darauf, dass Patienten mit früher und mittlerer AMD von der minimal-invasiven SNL- Therapie profitieren könnte

Rule-based multi-level modeling of cell biological systems

<p>Abstract</p> <p>Background</p> <p>Proteins, individual cells, and cell populations denote different levels of an organizational hierarchy, each of which with its own dynamics. Multi-level modeling is concerned with describing a system at these different levels and relating their dynamics. Rule-based modeling has increasingly attracted attention due to enabling a concise and compact description of biochemical systems. In addition, it allows different methods for model analysis, since more than one semantics can be defined for the same syntax.</p> <p>Results</p> <p>Multi-level modeling implies the hierarchical nesting of model entities and explicit support for downward and upward causation between different levels. Concepts to support multi-level modeling in a rule-based language are identified. To those belong rule schemata, hierarchical nesting of species, assigning attributes and solutions to species at each level and preserving content of nested species while applying rules. Further necessities are the ability to apply rules and flexibly define reaction rate kinetics and constraints on nested species as well as species that are nested within others. An example model is presented that analyses the interplay of an intracellular control circuit with states at cell level, its relation to cell division, and connections to intercellular communication within a population of cells. The example is described in ML-Rules - a rule-based multi-level approach that has been realized within the plug-in-based modeling and simulation framework JAMES II.</p> <p>Conclusions</p> <p>Rule-based languages are a suitable starting point for developing a concise and compact language for multi-level modeling of cell biological systems. The combination of nesting species, assigning attributes, and constraining reactions according to these attributes is crucial in achieving the desired expressiveness. Rule schemata allow a concise and compact description of complex models. As a result, the presented approach facilitates developing and maintaining multi-level models that, for instance, interrelate intracellular and intercellular dynamics.</p

DancingLines: An Analytical Scheme to Depict Cross-Platform Event Popularity

Nowadays, events usually burst and are propagated online through multiple modern media like social networks and search engines. There exists various research discussing the event dissemination trends on individual medium, while few studies focus on event popularity analysis from a cross-platform perspective. Challenges come from the vast diversity of events and media, limited access to aligned datasets across different media and a great deal of noise in the datasets. In this paper, we design DancingLines, an innovative scheme that captures and quantitatively analyzes event popularity between pairwise text media. It contains two models: TF-SW, a semantic-aware popularity quantification model, based on an integrated weight coefficient leveraging Word2Vec and TextRank; and wDTW-CD, a pairwise event popularity time series alignment model matching different event phases adapted from Dynamic Time Warping. We also propose three metrics to interpret event popularity trends between pairwise social platforms. Experimental results on eighteen real-world event datasets from an influential social network and a popular search engine validate the effectiveness and applicability of our scheme. DancingLines is demonstrated to possess broad application potentials for discovering the knowledge of various aspects related to events and different media

The SGR 1806-20 magnetar signature on the Earth's magnetic field

SGRs denote ``soft $\gamma$-ray repeaters'', a small class of slowly spinning neutron stars with strong magnetic fields. On 27 December 2004, a giant flare was detected from magnetar SGR 1806-20. The initial spike was followed by a hard-X-ray tail persisting for 380 s with a modulation period of 7.56 s. This event has received considerable attention, particularly in the astrophysics area. Its relevance to the geophysics community lies in the importance of investigating the effects of such an event on the near-earth electromagnetic environment. However, the signature of a magnetar flare on the geomagnetic field has not previously been investigated. Here, by applying wavelet analysis to the high-resolution magnetic data provided by the CHAMP satellite, a modulated signal with a period of 7.5 s over the duration of the giant flare appears in the observed data. Moreover, this event was detected by the energetic ion counters onboard the DEMETER satellite.Comment: Science Editors' Choice: http://www.sciencemag.org/content/vol314/issue5798/twil.dt

Mapping global extraction of abiotic and biotic raw materials

Reducing global environmental and social impacts related to final consumption is a significant societal as well as scientific challenge, especially as production and consumption are increasingly geographically disconnected via complex supply chains. Tracing the interlinkages between consumption and production as well as related impacts in a spatially explicit way can contribute to overcoming this challenge. Currently, the spatial resolution of global models of raw material extraction, trade and consumption is limited to the national level. Thus, they fail to link specific supply chains to the actual geographical location of production and related impacts. Detailed global spatiotemporal datasets would allow tracing the heterogeneity of environmental and social conditions within producing countries. In this contribution, we present our preliminary results mapping global biotic and abiotic raw materials extraction in 5-arc-minutes (around 10 km x 10 km at the equator) grid cell level, starting from the year 2000. Our datasets will include around 60 different raw materials, covering crops, fishery, fossil energy resources, metal ores and non-metallic minerals. In the future, our database will also include spatially explicit data on environmental and social impacts related to the extraction of these raw materials. The new database, methods, and algorithms will be openly available to the research community and the wider public, supporting open and reproducible science. Our novel database will allow developing new methods to assess the interlinkages between consumption and various environmental and social impacts related to extraction on a grid cell level. It can boost the spatially explicit assessments of supply chains and consumption patterns in both developed and developing countries, which is crucial for the design of international policy instruments to achieve sustainable production and consumption patterns