Background and Purpose
Although botulinum toxin type A (BoNT/A) is approved for chronic migraine treatment, its mechanism of action is still unknown. Dural neurogenic inflammation (DNI) commonly used ...to investigate migraine pathophysiology can be evoked by trigeminal pain. Here, we investigated the reactivity of cranial dura to trigeminal pain and the mechanism of BoNT/A action on DNI.
Experimental Approach
Because temporomandibular disorders are highly comorbid with migraine, we employed a rat model of inflammation induced by complete Freund's adjuvant, followed by treatment with BoNT/A injections or sumatriptan p.o. DNI was assessed by Evans blue‐plasma protein extravasation, cell histology and RIA for CGRP. BoNT/A enzymatic activity in dura was assessed by immunohistochemistry for cleaved synaptosomal‐associated protein 25 (SNAP‐25).
Key Results
BoNT/A and sumatriptan reduced the mechanical allodynia and DNI, evoked by complete Freund's adjuvant. BoNT/A prevented inflammatory cell infiltration and inhibited the increase of CGRP levels in dura. After peripheral application, BoNT/A‐cleaved SNAP‐25 colocalized with CGRP in intracranial dural nerve endings. Injection of the axonal transport blocker colchicine into the trigeminal ganglion prevented the formation of cleaved SNAP‐25 in dura.
Conclusions and Implications
Pericranially injected BoNT/A was taken up by local sensory nerve endings, axonally transported to the trigeminal ganglion and transcytosed to dural afferents. Colocalization of cleaved SNAP‐25 and the migraine mediator CGRP in dura suggests that BoNT/A may prevent DNI by suppressing transmission by CGRP. This might explain the effects of BoNT/A in temporomandibular joint inflammation and in migraine and some other headaches.
Cardiac arrhythmias during or after epileptic seizures are one of the possible pathomechanisms of sudden unexpected death in epilepsy. These arrhythmogenic epilepsies are most commonly associated ...with sinus tachycardia, but atrioventricular block and asystole can also be seen. Although a rare occurrence, these arrhythmias can lead to significant morbidity and mortality, but also can be potentially preventable with pacemaker implantation. Here we describe a patient with recurrent epileptic seizures, diagnosed with ictal third-degree atrioventricular block and asystole during seizure, which required a permanent cardiac pacemaker.
(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regenerate and produce different types of cells with the ability to initiate tumor growth and ...dissemination. Chemotherapy resistance, caused by numerous mechanisms by which tumor tissue manages to overcome the effects of drugs, remains the main problem in cancer treatment. The identification of markers on the cell surface specific to CSCs is important for understanding this phenomenon. (2) Methods: The expression of markers CD24, CD44, ALDH1, and ABCG2 was analyzed on the surface of CSCs in two cancer cell lines, MDA-MB-231 and HCT-116, after treatment with 5-fluorouracil (5-FU) using flow cytometry analysis. A machine learning model (ML)-genetic algorithm (GA) was used for the in silico simulation of drug resistance. (3) Results: As evaluated through the use of flow cytometry, the percentage of CD24-CD44+ MDA-MB-231 and CD44, ALDH1 and ABCG2 HCT-116 in a group treated with 5-FU was significantly increased compared to untreated cells. The CSC population was enriched after treatment with chemotherapy, suggesting that these cells have enhanced drug resistance mechanisms. (4) Conclusions: Each individual GA prediction model achieved high accuracy in estimating the expression rate of CSC markers on cancer cells treated with 5-FU. Artificial intelligence can be used as a powerful tool for predicting drug resistance.
•A new algorithm for harmonic state estimation (HSE) in power systems is presented.•Application of Kron reduction matrix and heuristic method provides satisfactory results in the HSE.•High accuracy ...of HSE is achieved even when using partially known data about the monitored PS.•Sensitivity analysis for HSE demonstrates efficiency of the algorithm.
In this paper, a new algorithm for harmonic state estimation in power systems is represented. The algorithm is based on node voltage method, Kron reduction matrix, modeling of power system in frequency domain using phase values and optimization genetic algorithm. The algorithm uses measured voltage and current harmonics as an input data, with partially known data about transmission network. Algorithm estimates RMS and angle values of voltage harmonics in the unmonitored part of power system. Sensitivity analysis of proposed algorithm was conducted on a case study of 110kV transmission network. Admittance matrix of power system is identified by using genetic algorithm with an accuracy of 0.5%, while an error of harmonic voltage estimation is lower than 1.129%.
Nowadays, biomedicine is a multidisciplinary science that requires a very broad approach to the study and analysis of various phenomena essential for a better understanding of human health. This ...study deals with the use of numerical simulations to better understand the processes of cancer viability and apoptosis in treatment with commercial chemotherapeutics. Starting from many experiments examining cell viability in real-time, determining the type of cell death and genetic factors that control these processes, a lot of numerical results were obtained. These in vitro test results were used to create a numerical model that gives us a new angle of observation of the proposed problem. Model systems of colon and breast cancer cell lines (HCT-116 and MDA-MB-231), as well as a healthy lung fibroblast cell line (MRC-5), were treated with commercial chemotherapeutics in this study. The results indicate a decrease in viability and the appearance of predominantly late apoptosis in the treatment, a strong correlation between parameters. A mathematical model was created and employed for a better understanding of investigated processes. Such an approach is capable of accurately simulating the behavior of cancer cells and reliably predicting the growth of these cells.
•Application of LSAs for the reduction of SOVs on voltage uprated transmission lines.•The method for selection of optimum LSA installation locations was developed.•An algorithm that estimates the ...risk of flashover due to SOVs was developed.•Overvoltage protection of the transmission line uprated from 220kV to 400kV.•Compacting of 400kV transmission line by installing LSAs.
This paper discusses the possibility of using line surge arresters (LSAs) for the reduction of switching overvoltages (SOVs) on voltage uprated transmission lines. The method for the selection of LSA energy class and determination of optimum installation locations was proposed. The method was applied in case of improving the overvoltage protection of the transmission line uprated from 220kV to 400kV.
The possibility of compacting a 400kV transmission line by installing LSAs was considered. Since a risk of flashover increases due to the reduction of insulation clearances, an algorithm that estimates the risk of flashover was developed and applied in case of compacting a 400kV transmission line.
•VDR expression is increased in cytoplasm, nuclei and membranes of DRG neurons in diabetes mellitus.•VDR expression occurs in all neurons, although is more prominent in small somata.•VDR signaling ...system could be a potential therapeutic target for diabetic neuropathy.
The effects of vitamin D on the nervous system have been studied extensively. In spite of accumulating data about the substantial changes in the vitamin D receptor (VDR) signaling system, during different types of neuroinflammatory diseases, its role in diabetic neuropathy has not been investigated in detail. To assess the role of VDR signaling in diabetic neuropathy, we examined expression of VDRs in dorsal root ganglia (DRG) neurons in a rat model of streptozotocin-induced diabetes mellitus type 1. Diabetes mellitus (DM) type 1 was induced with streptozotocin in male Sprague-Dawley rats. After two months, expression of VDRs was analyzed immunohistochemically in the cytoplasm of L4 and L5 DRG neurons of diabetic rats. Semi-quantitative analysis for the determination of staining in nuclei and plasma-membranes of DRG neurons was performed. A significant increase in VDR expression was observed in DRG neurons of diabetic rats. Expression of VDRs was increased in the cytoplasm, nuclei and in cell membranes of neurons. An increase in VDR expression occurred in all neurons, but the greatest increase of fluorescence intensity in cytoplasm was observed in neurons of small diameter. Results of the present study indicate that the VDR signaling system could be a potential therapeutic target for diabetic neuropathy.
Soil and water conservation practices are key to agroecosystems sustainability and avoiding diffuse pollution. Here, we compare the impacts of different types of mulch, barley straw (Straw), wooden ...chips (Chip) and tillage (Till) on vegetation mulch cover (VMC); soil properties, bulk density (BD), mean weight diameter (MWD), water stable aggregates (WSA), soil water content (SWC), soil organic matter (SOM), pH and total phosphorous (P), potassium (K), calcium (Ca), chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), Zinc (Zn) and lead (Pb). We also assessed the ponding time (PT), runoff time (RT), runoff, sediment concentration (SC), sediment loss (SL) and chemicals transport (the same studied in soil). A set of rainfall simulation experiments (90 in total) was applied in the different Spring, Summer, and Fall treatments. The results showed that mulch increased VMC in all the seasons, while other properties (BD; MWD, WSA SOM, pH) were not affected, especially in Spring. The biggest impact was observed in Fall, especially in the Till plot, due to the tillage practices applied in Summer. Mulch increased PT, RT and reduced runoff, SL and chemicals transport. Chemical losses were very much associated with SL, and the concentration of P and metals in soil depended on soil Ca and pH. SWC, MWD and runoff were inversely related to PT, RT and SC. Finally, BD, VMC and SOM were highly associated. Overall, tillage practices dramatically impact SL, and diffuse pollution and urgent measures are needed to reverse this. Mulching is excellent and cost-effective to mitigate the impacts of agriculture on land degradation and diffuse pollution.
Display omitted
•Impacts of season and soil management were studied in a hazelnut orchard.•Season had a strong impact on hydrological response.•Water, sediment and chemicals loss were high in Fall.•Tillage increased the chemicals transport.•Sustainable measures are needed to revert the tillage impact.
Aims and background: Mining and energy complexes in Serbia are recognized as a major source of a large number of pollutants. Serbia’s environmental performance reports clearly indicate that large ...mining and energy complexes are the dominant source of air pollution. It is difficult to determine which of them remarkably threaten the quality of the environment, as all the basic elements of the environment (air, water, and soil) are threatened, not just one. Mining and energy complexes significantly reduce the quality of the immediate environment, as the distance areas throughout water and air pollution propagation. Additional motivation for this study lies in the fact that large mining and energy complexes are particularly interesting because they are located in the immediate vicinity or large rivers (mostly the Danube), which are protected in many national and international legislation acts (particularly the Danube). The basis for the preservation of environmental quality is an effective environmental management system (EMS) in mining and energy complexes. The aim of this study is to promote and elaborate the possibility for improving the mining and energy complex environmental protection/management system by applying the basic principles of sustainable development. Methodology: Project management methodology is selected as a tool. Project management is based on the application of a network planning technique (Critical Path Method), because of its suitability for representing the logical structure of environmental protection system. The survey was conducted in the area of the city of Kostolac. The examined area included mining and energy complexes in Kostolac, which incorporate three surface mines (Ćirikovac, Klenovik, and Drmno) and two thermal power stations (TE “Kostolac A” (100 MW) and TE “Kostolac B” (2 × 348.5 MW)). The PSR model (Pressures, State, Response) was used for the organization of the interactions within “society–environment” system as the basis for indicator selection. Results: Procedures to identify and determine the significance of the environmental aspects should be established by executive staff in mining and energy plants and complexes. Identification of environmental aspects is the first part of the planning system of environmental management and the activities related to them. The accomplishment of critical path activities represents the basis for improving the environmental protection system in mining and energy complexes. Discussion: Application of sustainable development principles depends on the country’s energy potential and the application of the adopted environmental policy regarding mining and energy complexes. Strict enforcement of existing laws and regulations presents an opportunity to rectify many shortcomings while providing economic benefits, restoring the usable value of ravaged land, and preserving air and water quality.
Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those ...components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue.
The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations.
We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy.
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