AmyloGraph : a comprehensive database of amyloid-amyloid interactions

Information about the impact of interactions between amyloid proteins on their fibrillization propensity is scattered among many experimental articles and presented in unstructured form. We manually curated information located in almost 200 publications (selected out of 562 initially considered), obtaining details of 883 experimentally studied interactions between 46 amyloid proteins or peptides. We also proposed a novel standardized terminology for the description of amyloid-amyloid interactions, which is included in our database, covering all currently known types of such a cross-talk, including inhibition of fibrillization, cross-seeding and other phenomena. The new approach allows for more specific studies on amyloids and their interactions, by providing very well-defined data. AmyloGraph, an online database presenting information on amyloid-amyloid interactions, is available at (). Its functionalities are also accessible as the R package (). AmyloGraph is the only publicly available repository for experimentally determined amyloid-amyloid interactions

KM-408, a novel phenoxyalkyl derivative as a potential anticonvulsant and analgesic compound for the treatment of neuropathic pain

BACKGROUND: Epilepsy frequently coexists with neuropathic pain. Our approach is based on the search for active compounds with multitarget profiles beneficial in terms of potential side effects and on the implementation of screening for potential multidirectional central activity. METHODS: Compounds were synthesized by means of chemical synthesis. After antiseizure and neurotoxicity screening in vivo, KM-408 and its enantiomers were chosen for analgesic activity evaluations. Further safety studies included acute toxicity in mice, the effect on normal electrocardiogram and on blood pressure in rats, whole body plethysmography in rats, and in vitro and biochemical assays. Pharmacokinetics has been studied in rats after iv and po administration. Metabolism has been studied in vivo in rat serum and urine. Radioligand binding studies were performed as part of the mechanism of action investigation. RESULTS: Selected results for KM-408: K(i) sigma = 7.2*10(–8); K(i) 5-HT(1A) = 8.0*10(–7); ED(50) MES (mice, ip) = 13.3 mg/kg; formalin test (I phase, mice, ip)—active at 30 mg/kg; SNL (rats, ip)—active at 6 mg/kg; STZ-induced pain (mice, ip)—active at 1 mg/kg (von Frey) and 10 mg/kg (hot plate); hot plate test (mice, ip)—active at 30 mg/kg; ED(50) capsaicin test (mice, ip) = 18.99 mg/kg; tail immersion test (mice)—active at 0.5%; corneal anesthesia (guinea pigs)—active at 0.125%; infiltration anesthesia (guinea pigs)—active at 0.125%. CONCLUSIONS: Within the presented study a novel compound, R,S-2-((2-(2-chloro-6-methylphenoxy)ethyl)amino)butan-1-ol hydrochloride (KM-408) with dual antiseizure and analgesic activity has been developed for potential use in neuropathic pain treatment. GRAPHICAL ABSTRACT: [Image: see text] SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s43440-022-00431-7

Comparison of recent S-wave indicating methods

Seismic event consists of surface waves and body waves. Due to the fact that the body waves are faster (P-waves) and more energetic (S-waves) in literature the problem of their analysis is taken more often. The most universal information that is received from the recorded wave is its moment of arrival. When this information is obtained from at least four seismometers in different locations, the epicentre of the particular event can be estimated [1]. Since the recorded body waves may overlap in signal, the problem of wave onset moment is considered more often for faster P-wave than S-wave. This however does not mean that the issue of S-wave arrival time is not taken at all. As the process of manual picking is time-consuming, methods of automatic detection are recommended (these however may be less accurate). In this paper four recently developed methods estimating S-wave arrival are compared: the method operating on empirical mode decomposition and Teager-Kaiser operator [2], the modification of STA/LTA algorithm [3], the method using a nearest neighbour-based approach [4] and the algorithm operating on characteristic of signals’ second moments. The methods will be also compared to wellknown algorithm based on the autoregressive model [5]. The algorithms will be tested in terms of their S-wave arrival identification accuracy on real data originating from International Research Institutions for Seismology (IRIS) database

Comparison of recent S-wave indicating methods

Seismic event consists of surface waves and body waves. Due to the fact that the body waves are faster (P-waves) and more energetic (S-waves) in literature the problem of their analysis is taken more often. The most universal information that is received from the recorded wave is its moment of arrival. When this information is obtained from at least four seismometers in different locations, the epicentre of the particular event can be estimated [1]. Since the recorded body waves may overlap in signal, the problem of wave onset moment is considered more often for faster P-wave than S-wave. This however does not mean that the issue of S-wave arrival time is not taken at all. As the process of manual picking is time-consuming, methods of automatic detection are recommended (these however may be less accurate). In this paper four recently developed methods estimating S-wave arrival are compared: the method operating on empirical mode decomposition and Teager-Kaiser operator [2], the modification of STA/LTA algorithm [3], the method using a nearest neighbour-based approach [4] and the algorithm operating on characteristic of signals’ second moments. The methods will be also compared to wellknown algorithm based on the autoregressive model [5]. The algorithms will be tested in terms of their S-wave arrival identification accuracy on real data originating from International Research Institutions for Seismology (IRIS) database