68 research outputs found
Evaluation of microvascular disturbances in rheumatic diseases by analysis of skin blood flow oscillations
Laser Doppler flowmetry (LDF), tissue reflectance oximetry (TRO) and pulse oximetry (PO) and cold pressor test (CPT) were used to assess the microcirculation parameters and the activation of regulatory mechanisms. LDF and TRO samples wavelet transform in the frequency bands 0.01-2 Hz was used to evaluate microvascular disturbances in rheumatic diseases and to assess the vascular involvement in the pathological process. The spectral components of LDF and TRO signals associated with endothelial, adrenergic, intrinsic smooth muscle, respiratory and cardiac activities were analyzed. Significant difference between healthy and rheumatology subjects was identified in perfusion parameters. Spectral analysis of the LDF signal revealed significant difference between two group of high (<0.1 Hz) frequency pulsations. Based on the analysed of the perfusion and amplitudes oscillation in the frequency band the decision rule for detection microvascular disturbances were synthesized. The perfusion parameter and amplitude oscillation associated with cardiac activities included in the decision rule. Based on the measured parameters and the result of wavelet transform LDF- and TRO-signals the parameters for detection of complications associated with microvascular disturbances and their possible causes were proposed
Study of Molecular and Ionic Vapor Composition over CeI3 by Knudsen Effusion Mass Spectrometry
The molecular and ionic composition of vapor over cerium triiodide was studied by Knudsen effusion mass spectrometry. In the saturated vapor over CeI3 the monomer, dimer, and trimer molecules and the negative ions Iβ, CeI4β, and Ce2I7β were identified in the temperature range of 753β994 K. The partial pressures of CeI3, Ce2 I6, and Ce3I9 were determined and the enthalpies of sublimation, Ξ
Detection of angiospastic disorders in the microcirculatory bed using laser diagnostics technologies
The evaluation of the microcirculatory bed functional state and the identification of angiospastic disorders with related complications, when the pathological changes are reversible, have an important role in medical practice. The aim of this study was to evaluate the possibility of using optical noninvasive methods and the cold pressor test to solve this problem. A total of 33 patients with rheumatological diseases and 32 healthy volunteers were included in the study. Laser Doppler flowmetry, tissue reflectance oximetry and pulse oximetry were used as optical noninvasive methods. The parameters were recorded before, immediately after and 20(Formula presented.)min after the cold pressor test. Based on the measured parameters, the complex parameters of the microcirculatory bed were calculated. A detailed statistical analysis of the parameter changes for each individual in the two groups displayed diverse microcirculatory bed parameter responses upon cold exposure, with differing recovery of parameters after CPT. New diagnostic criteria were proposed for the identification of angiospastic disorders. According to the proposed criteria, 27 people of the volunteers group were confirmed to not display any disorders. In the patient group, however, 18 people were observed to have a relatively normal functional state of the microcirculatory bed, while 15 people were observed to have a possible tendency to angiospasm. To highlight the differences between a relatively normal state and presence of angiospastic disorders, statistical analysis of experimental data was carried out, which revealed significant differences. Further analysis of data with angiospastic disorders identified a relationship between their diagnoses and the results of laboratory studies. Thus, the evaluation of combined noninvasive optical diagnostic method use, the cold pressor test and proposed diagnostic criteria showed a positive result. This approach can be used to detect the presence of possible angiospastic disorders and related complications, as well as microcirculatory bed disorders against the background of other diseases
ΠΠ΅Ρ Π°Π½ΠΈΠ·ΠΌΡ ΡΠΈΡΠΎΡΠΎΠΊΡΠΈΡΠ΅ΡΠΊΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ ΠΏΠΈΡΡΠΎΠ»-ΠΊΠ°ΡΠ±ΠΎΠΊΡΠ°ΠΌΠΈΠ΄ΠΎΠ² Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΎΠΏΡΡ ΠΎΠ»Π΅Π²ΡΡ ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΡ ΡΡΠ±Π»ΠΈΠ½ΠΈΠΉ Ρ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡΡ
Introduction. Mitotic poisoning agents (MPAs) affecting the dynamic state of the microtubules, are the well-known and effective chemotherapeutic agents. Mitotic poisoning agents are binding to the microtubules, and thereby interfere with tubulin polymerization or depolymerization dynamic state, resulting in the cell cycle arrest in M-phase (mitotic catastrophe) and subsequent apoptotic cell death. We reported previously about potent cytotoxic activities against the pyrrole-carboxamides (PCs) (PC-61 and PC-84) against broad spectrum of cancer cell lines, including triple negative breast cancer, lung and prostate cancer.Aim. To examine the cytotoxic activities of PC-61 and PC-84 against multidrug-resistant cancer cell lines indicated above.Materials and methods. StudΡ was performed on the triple-negative paclitaxel-resistant breast cancer cell line HCC1806 Tx-R and doxorubicin-resistant osteosarcoma SaOS-2 Dox-R cell line.Results. The cytotoxic activity of PCs was due to the inhibition of tubulin polymerization. Immunofluorescence staining data revealed PCβs ability to interfere with tubulinβs assembly in multidrug-resistant cancer cell lines. As an outcome of inhibition of tubulin polymerization, PCs induced cell cycle arrest in M-phase, and further led to apoptotic cell death of cancer cells.Conclusion. Collectively, we demonstrated potent cytotoxic activity of PCs against cancer cell lines with multidrug-resistant phenotype, which arising the possibilities to develop novel and effective anti-tumor agents that belongs to mitotic poisoning agentsΠΠ²Π΅Π΄Π΅Π½ΠΈΠ΅. ΠΠ΅ΡΠ΅ΡΡΠ²Π°, ΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠ΅ ΠΌΠΈΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠ΄Π°ΠΌΠΈ ΠΈ Π²Π»ΠΈΡΡΡΠΈΠ΅ Π½Π° Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΡΠΎΡΡΠΎΡΠ½ΠΈΠ΅ ΠΌΠΈΠΊΡΠΎΡΡΡΠ±ΠΎΡΠ΅ΠΊ Π²Π΅ΡΠ΅ΡΠ΅Π½Π° Π΄Π΅Π»Π΅Π½ΠΈΡ, ΡΠ²Π»ΡΡΡΡΡ Ρ
ΠΎΡΠΎΡΠΎ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΠΌΠΈ ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΌΠΈ Ρ
ΠΈΠΌΠΈΠΎΡΠ΅ΡΠ°ΠΏΠ΅Π²ΡΠΈΡΠ΅ΡΠΊΠΈΠΌΠΈ ΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ°ΠΌΠΈ. ΡΡΠΈ Π²Π΅ΡΠ΅ΡΡΠ²Π° ΡΠ²ΡΠ·ΡΠ²Π°ΡΡΡΡ Ρ ΠΌΠΈΠΊΡΠΎΡΡΡΠ±ΠΎΡΠΊΠ°ΠΌΠΈ, Π²Π»ΠΈΡΡ ΡΠ΅ΠΌ ΡΠ°ΠΌΡΠΌ Π½Π° ΠΏΡΠΎΡΠ΅ΡΡΡ ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈΠ»ΠΈ Π΄Π΅ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ±ΡΠ»ΠΈΠ½Π°, ΡΡΠΎ Π² ΠΊΠΎΠ½Π΅ΡΠ½ΠΎΠΌ ΡΡΠ΅ΡΠ΅ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ ΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠ΅ ΠΊΠ»Π΅ΡΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Π° Π² M-ΡΠ°Π·Π΅ (ΠΌΠΈΡΠΎΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΊΠ°ΡΠ°ΡΡΡΠΎΡΠ°) ΠΈ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠ΅ΠΉ Π³ΠΈΠ±Π΅Π»ΠΈ ΠΊΠ»Π΅ΡΠΎΠΊ ΠΏΠΎ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΡ Π°ΠΏΠΎΠΏΡΠΎΠ·Π°. Π ΠΏΡΠ΅Π΄ΡΠ΄ΡΡΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
ΠΌΡ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ Π²ΡΡΠΎΠΊΡΡ ΡΠΈΡΠΎΡΠΎΠΊΡΠΈΡΠ΅ΡΠΊΡΡ ΠΈ ΠΏΡΠΎΡΠΈΠ²ΠΎΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΠΈΡΡΠΎΠ»-ΠΊΠ°ΡΠ±ΠΎΠΊΡΠ°ΠΌΠΈΠ΄ΠΎΠ² (ΠΏΠΊ) (ΠΏΠΊ-61 ΠΈ ΠΏΠΊ-84) Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΡΠΈΡΠΎΠΊΠΎΠ³ΠΎ ΡΠΏΠ΅ΠΊΡΡΠ° ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΡ
Π»ΠΈΠ½ΠΈΠΉ ΡΠΏΠΈΡΠ΅Π»ΠΈΠ°Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΡΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ, Π²ΠΊΠ»ΡΡΠ°Ρ ΡΡΠΈΠΆΠ΄Ρ Π½Π΅Π³Π°ΡΠΈΠ²Π½ΡΠΉ ΡΠ°ΠΊ ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ, ΡΠ°ΠΊ Π»Π΅Π³ΠΊΠΈΡ
ΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°ΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ β ΠΈΠ·ΡΡΠΈΡΡ ΡΠΈΡΠΎΡΠΎΠΊΡΠΈΡΠ΅ΡΠΊΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΠΊ-61 ΠΈ ΠΏΠΊ-84 Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΡ
Π»ΠΈΠ½ΠΈΠΉ Ρ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡΡ.ΠΠ°ΡΠ΅ΡΠΈΠ°Π»Ρ ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π½Π° ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΡ
Π»ΠΈΠ½ΠΈΡΡ
ΡΡΠΈΠΆΠ΄Ρ Π½Π΅Π³Π°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ°ΠΊΠ° ΠΌΠΎΠ»ΠΎΡΠ½ΠΎΠΉ ΠΆΠ΅Π»Π΅Π·Ρ, ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΎΠ³ΠΎ ΠΊ ΠΏΠ°ΠΊΠ»ΠΈΡΠ°ΠΊΡΠ΅Π»Ρ (HCC1806 Tx-R), ΠΈ ΠΎΡΡΠ΅ΠΎΡΠ°ΡΠΊΠΎΠΌΡ, ΡΠ΅Π·ΠΈΡΡΠ΅Π½ΡΠ½ΠΎΠΉ ΠΊ Π΄ΠΎΠΊΡΠΎΡΡΠ±ΠΈΡΠΈΠ½Ρ (SaOS-2 Dox-R). Π‘ΠΎΠ³Π»Π°ΡΠ½ΠΎ ΡΠ°Π½Π΅Π΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½Π½ΡΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΠΌ ΠΎΠ±Π΅ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΠ΅ ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΠ΅ ΡΡΠ±Π»ΠΈΠ½ΠΈΠΈ ΠΈΠΌΠ΅Π»ΠΈ ΡΠ΅Π½ΠΎΡΠΈΠΏ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΠΈ.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΏΡΠΎΡΠΈΠ²ΠΎΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²Π°Ρ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΠΊ ΠΎΠ±ΡΡΠ»ΠΎΠ²Π»Π΅Π½Π° ΠΈΡ
ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡΡ ΠΈΠ½Π³ΠΈΠ±ΠΈΡΠΎΠ²Π°ΡΡ ΠΏΡΠΎΡΠ΅ΡΡΡ ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ±ΡΠ»ΠΈΠ½Π°. ΠΠ°Π½Π½ΡΠ΅ ΠΈΠΌΠΌΡΠ½ΠΎΡΠ»ΡΠΎΡΠ΅ΡΡΠ΅Π½ΡΠ½ΠΎΠΉ ΠΌΠΈΠΊΡΠΎΡΠΊΠΎΠΏΠΈΠΈ ΠΏΠΎΠΊΠ°Π·Π°Π»ΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡ ΠΏΠΊ Π½Π°ΡΡΡΠ°ΡΡ ΠΏΡΠΎΡΠ΅ΡΡΡ ΡΠ±ΠΎΡΠΊΠΈ ΡΡΠ±ΡΠ»ΠΈΠ½Π° Π² ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΊΠ°Ρ
. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΠΈΠ½Π³ΠΈΠ±ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠΎΠ»ΠΈΠΌΠ΅ΡΠΈΠ·Π°ΡΠΈΠΈ ΡΡΠ±ΡΠ»ΠΈΠ½Π° Π² ΡΡΠΈΡ
ΠΊΠ»Π΅ΡΠΊΠ°Ρ
ΠΏΡΠΎΠΈΡΡ
ΠΎΠ΄ΠΈΡ ΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠ° ΠΊΠ»Π΅ΡΠΎΡΠ½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Π° Π² Π-ΡΠ°Π·Π΅, ΡΡΠΎ ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡ ΠΊ Π½Π°ΠΊΠΎΠΏΠ»Π΅Π½ΠΈΡ ΠΌΠΈΡΠΎΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΊΠ»Π΅ΡΠΎΠΊ ΠΈ ΠΈΠ½Π΄ΡΡΠΈΡΡΠ΅Ρ Π°ΠΏΠΎΠΏΡΠΎΠ·.ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΠΎΠΊΠ°Π·ΡΠ²Π°ΡΡ Π²ΡΡΠΎΠΊΡΡ ΡΠΈΡΠΎΡΠΎΠΊΡΠΈΡΠ΅ΡΠΊΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠΎΠ΅Π΄ΠΈΠ½Π΅Π½ΠΈΠΉ ΠΏΠΊ-61 ΠΈ ΠΏΠΊ-84 Π² ΠΎΡΠ½ΠΎΡΠ΅Π½ΠΈΠΈ ΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΠΊΠ»Π΅ΡΠΎΡΠ½ΡΡ
Π»ΠΈΠ½ΠΈΠΉ Ρ ΠΌΠ½ΠΎΠΆΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠΉ Π»Π΅ΠΊΠ°ΡΡΡΠ²Π΅Π½Π½ΠΎΠΉ ΡΡΡΠΎΠΉΡΠΈΠ²ΠΎΡΡΡΡ, ΡΡΠΎ ΠΎΡΠΊΡΡΠ²Π°Π΅Ρ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Ρ Π΄Π»Ρ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ Π½ΠΎΠ²ΡΡ
ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΡ
ΠΏΡΠΎΡΠΈΠ²ΠΎΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ
ΡΡΠ΅Π΄ΡΡΠ² Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ ΠΏΠΊ
Modelling spatial patterns of correlations between concentrations of heavy metals in mosses and atmospheric deposition in 2010 across Europe
BackgroundThis paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.ResultsCorrelations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75-100km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of <40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (=above-average) or low (=below-average) correlation coefficients.ConclusionsLDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites
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