3,904 research outputs found
Promotive effects of hyperthermia on the Ρytostatic activity to ehrlich ascites tumor cells by diverse delta-alkyllactones
To evaluate promotive effects of hyperthermia on antitumor activity of new delta-alkyllactones (DALs) of low molecular weight (184β254 Da), chemically synthesized, which are different from natural macrocyclic lactones of high molecular weight (348β439 Da), such as camptothecin and sultriecin. Methods: A suspension of Ehrlich ascites tumor (EAT) cells was mixed with a DAL in a glass tube, heated at 37 or 42 Β°C for 30 min in a water bath, and cultured at 37 Β°C for 20 or 72 h. Cell viability was measured by the mitochondrial dehydrogenase- based WST-1 assay. DALs incorporated into EAT cells was extracted and measured by gas-liquid chromatography. Results: The reduction of cell viability by DALs was markedly enhanced upon the treatment at 42 Β°C compared to that at 37 oC. At 37 oC, delta-hexadecalactone (DH16 : 0) and delta-tetradecalactone (DTe14 : 0) displayed cytostatic activity (at 100 Β΅M survival level: 20.7%, 66.1%; at 50 Β΅M β 41.2%, 82.4%, respectively). Their activity was more marked at 42 Β°C (at 100 Β΅M 10.6%, 27.6%; at 50 Β΅M 30.6, 37.5 %, ibid). The other DALs, delta-undecalactone (DU11 : 0), delta-dodecalactone (DD12 : 0), and delta-tridecanolactone (DTr13 : 0) were almost ineffective. Evaluation of survival rate in the cells treated for 30 min by DALs with the next culturing of EAT cells for 72 h resulted in the enhanced carcinostatic activity of DH16:0 and DTe14:0 even at concentrations as low as 25 Β΅M at either 37 Β°C (18.5%, 78.5%, ibid) or 42 Β°C (5.0%, 42.0%, ibid), but the others exhibited slight activity or none. DH16 : 0 was effective at either 37 Β°C (36.0%) or 42 Β°C (23.0%) even at a lower dose of 10 Β΅M. At the same time only the most cytostatic DH16 : 0 was incorporated into EAT cells and the rate of incorporation was more at 42 Β°C than at 37 Β°C. Conclusion: Delta-hexadecanolactone (DH16 : 0) exhibited the most cytostatic effect that was significantly enhanced by hyperthermia. It allows to consider it as a potent antitumor agent, especially in combination with hyperthermia.Π¦Π΅Π»Ρ: ΠΎΡΠ΅Π½ΠΈΡΡ ΠΏΡΠΎΠΌΠΎΡΠΎΡΠ½ΡΠΉ ΡΡΡΠ΅ΠΊΡ Π³ΠΈΠΏΠ΅ΡΡΠ΅ΡΠΌΠΈΠΈ Π½Π° ΠΏΡΠΎΡΠΈΠ²ΠΎΠΎΠΏΡΡ
ΠΎΠ»Π΅Π²ΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Π½ΠΎΠ²ΡΡ
Π½ΠΈΠ·ΠΊΠΎΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΡΡ
(184β254 ΠΠ°)
Π΄Π΅Π»ΡΡΠ°-Π°Π»ΠΊΠΈΠ»Π»Π°ΠΊΡΠΎΠ½ΠΎΠ² (DALs), Ρ
ΠΈΠΌΠΈΡΠ΅ΡΠΊΠΈ ΡΠΈΠ½ΡΠ΅Π·ΠΈΡΠΎΠ²Π°Π½Π½ΡΡ
ΠΈΠ· ΡΠ°Π·Π½ΡΡ
ΠΌΠ°ΠΊΡΠΎΡΠΈΠΊΠ»ΠΈΡΠ΅ΡΠΊΠΈΡ
Π²ΡΡΠΎΠΊΠΎΠΌΠΎΠ»Π΅ΠΊΡΠ»ΡΡΠ½ΡΡ
(348β439ΠΠ°)
Π»Π°ΠΊΡΠΎΠ½ΠΎΠ² Π΅ΡΡΠ΅ΡΡΠ²Π΅Π½Π½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΡΡ
ΠΎΠΆΠ΄Π΅Π½ΠΈΡ, ΡΠ°ΠΊΠΈΡ
ΠΊΠ°ΠΊ ΠΊΠ°ΠΌΠΏΡΠΎΡΠ΅ΡΠΈΠ½ ΠΈ ΡΠ°Π»ΡΡΠΈΠ΅ΡΠΈΠ½. ΠΠ΅ΡΠΎΠ΄Ρ: ΡΡΡΠΏΠ΅Π½Π·ΠΈΡ ΠΊΠ»Π΅ΡΠΎΠΊ Π°ΡΡΠΈΡΠ½ΠΎΠΉ ΠΎΠΏΡΡ
ΠΎΠ»ΠΈ
ΠΡΠ»ΠΈΡ
Π° (EAT) ΡΠΌΠ΅ΡΠΈΠ²Π°Π»ΠΈ Ρ DAL Π² ΡΡΠ΅ΠΊΠ»ΡΠ½Π½ΠΎΠΉ ΠΏΡΠΎΠ±ΠΈΡΠΊΠ΅, Π½Π°Π³ΡΠ΅Π²Π°Π»ΠΈ Π΄ΠΎ 37 Β°C ΠΈΠ»ΠΈ 42 Β°C Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 30 ΠΌΠΈΠ½ Π½Π° Π²ΠΎΠ΄ΡΠ½ΠΎΠΉ Π±Π°Π½Π΅
ΠΈ Π΄Π°Π»Π΅Π΅ ΠΊΡΠ»ΡΡΠΈΠ²ΠΈΡΠΎΠ²Π°Π»ΠΈ ΠΏΡΠΈ 37 Β°C Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 20 ΠΈΠ»ΠΈ 72 Ρ. ΠΡΠ΅Π½ΠΊΡ ΠΆΠΈΠ·Π½Π΅ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΠΈ ΠΊΠ»Π΅ΡΠΎΠΊ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Ρ ΠΏΠΎΠΌΠΎΡΡΡ WST-1
Π°Π½Π°Π»ΠΈΠ·Π°, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π½Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΈ ΠΌΠΈΡΠΎΡ
ΠΎΠ½Π΄ΡΠΈΠ°Π»ΡΠ½ΠΎΠΉ Π΄Π΅Π³ΠΈΠ΄ΡΠΎΠ³Π΅Π½Π°Π·Ρ. ΠΠ½ΠΊΠΎΡΠΏΠΎΡΠΈΡΠΎΠ²Π°Π½Π½ΡΠ΅ Π² EAT-ΠΊΠ»Π΅ΡΠΊΠΈ DALs ΡΠΊΡΡΡΠ°Π³ΠΈΡΠΎΠ²Π°Π»ΠΈ,
ΠΈΡ
ΡΡΠΎΠ²Π΅Π½Ρ ΠΈΠ·ΠΌΠ΅ΡΡΠ»ΠΈ Ρ ΠΏΠΎΠΌΠΎΡΡΡ Π³Π°Π·ΠΎ-ΠΆΠΈΠ΄ΠΊΠΎΡΡΠ½ΠΎΠΉ Ρ
ΡΠΎΠΌΠ°ΡΠΎΠ³ΡΠ°ΡΠΈΠΈ. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ: DALs Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΡΠ½ΠΈΠΆΠ°Π»ΠΈ
ΠΆΠΈΠ·Π½Π΅ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡΡ ΠΊΠ»Π΅ΡΠΎΠΊ ΠΏΠΎΡΠ»Π΅ ΠΏΡΠ΅Π΄Π²Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΏΡΠΈ 42 Β°C ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ Ρ 37 Β°C. ΠΡΠΈ 37 Β°C Π±ΡΠ»ΠΈ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΌΠΈ
Π΄Π΅Π»ΡΡΠ°-Π³Π΅ΠΊΡΠ°Π΄Π΅ΠΊΠ°Π»Π°ΠΊΡΠΎΠ½ (DH16 : 0) ΠΈ Π΄Π΅Π»ΡΡΠ°-ΡΠ΅ΡΡΠ°Π΄Π΅ΠΊΠ°Π»Π°ΠΊΡΠΎΠ½ (DTe14 : 0) (ΠΏΡΠΈ 100 ΞΌM ΡΡΠΎΠ²Π΅Π½Ρ Π²ΡΠΆΠΈΠ²Π°Π΅ΠΌΠΎΡΡΠΈ: 20,7; 66,1%;
ΠΏΡΠΈ 50 ΞΌM β 41,2; 82,4% ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ). ΠΡΠΎΡ ΡΡΡΠ΅ΠΊΡ Π±ΡΠ» Π±ΠΎΠ»Π΅Π΅ Π²ΡΡΠ°ΠΆΠ΅Π½Π½ΡΠΌ ΠΏΡΠΈ 42 Β°C (ΠΏΡΠΈ 100 ΞΌM 10,6; 27,6%; ΠΏΡΠΈ
50ΞΌM 30,6; 37,5% ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ). ΠΡΡΠ³ΠΈΠ΅ DALs, Π° ΠΈΠΌΠ΅Π½Π½ΠΎ Π΄Π΅Π»ΡΡΠ°-ΡΠ½Π΄Π΅ΠΊΠ°Π»Π°ΠΊΡΠΎΠ½ (DU11 : 0), Π΄Π΅Π»ΡΡΠ°-Π΄ΠΎΠ΄Π΅ΠΊΠ°Π»Π°ΠΊΡΠΎΠ½ (DD12 : 0)
ΠΈ Π΄Π΅Π»ΡΡΠ°-ΡΡΠΈΠ΄Π΅ΠΊΠ°Π»Π°ΠΊΡΠΎΠ½ (DTr13 : 0) Π±ΡΠ»ΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π½Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Ρ. ΠΡΠ΅Π½ΠΊΠ° ΡΡΠΎΠ²Π½Ρ Π²ΡΠΆΠΈΠ²Π°Π΅ΠΌΠΎΡΡΠΈ EAT-ΠΊΠ»Π΅ΡΠΎΠΊ, 30 ΠΌΠΈΠ½
ΠΎΠ±ΡΠ°Π±ΠΎΡΠ°Π½Π½ΡΡ
DALs Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠΈΠΌ ΠΊΡΠ»ΡΡΠΈΠ²ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 72 Ρ, ΠΏΠΎΠΊΠ°Π·Π°Π»Π° ΠΏΠΎΠ²ΡΡΠ΅Π½Π½ΡΡ ΠΊΠ°Π½ΡΠ΅ΡΠΎΡΡΠ°ΡΠΈΡΡΠ΅ΠΊΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ
DH16 : 0 ΠΈ DTe14 :0 Π΄Π°ΠΆΠ΅ ΠΏΡΠΈ 25 ΞΌM ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ, ΠΊΠ°ΠΊ ΠΏΡΠΈ 37 Β°C (18,5; 78,5% ΡΠΎΠΎΡΠ²Π΅ΡΡΠ²Π΅Π½Π½ΠΎ), ΡΠ°ΠΊ ΠΈ ΠΏΡΠΈ 42 Β°C (5,0; 42,0%
ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²Π΅Π½Π½ΠΎ). ΠΠ»Ρ Π΄ΡΡΠ³ΠΈΡ
DALs Π΄Π°Π½Π½ΡΠΉ ΡΡΡΠ΅ΠΊΡ Π±ΡΠ» Π½Π΅Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΡΠΉ Π»ΠΈΠ±ΠΎ ΠΎΡΡΡΡΡΡΠ²ΠΎΠ²Π°Π». DH16 : 0 ΠΎΡΡΠ°Π²Π°Π»ΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΌ
ΠΊΠ°ΠΊ ΠΏΡΠΈ 37 Β°C (36,0%), ΡΠ°ΠΊ ΠΈ ΠΏΡΠΈ 42 Β°C (23,0%) Π² 10 ΞΌM ΠΊΠΎΠ½ΡΠ΅Π½ΡΡΠ°ΡΠΈΠΈ. Π ΡΠΎ ΠΆΠ΅ Π²ΡΠ΅ΠΌΡ ΡΠΎΠ»ΡΠΊΠΎ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠΉ
DAL β DH16 : 0 ΠΈΠ½ΠΊΠΎΡΠΏΠΎΡΠΈΡΠΎΠ²Π°Π»ΡΡ Π² ΠΊΠ»Π΅ΡΠΊΠΈ EAT, ΠΈ ΡΡΠΎΠ²Π΅Π½Ρ ΠΈΠ½ΠΊΠΎΡΠΏΠΎΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π±ΡΠ» Π²ΡΡΠ΅ ΠΏΡΠΈ 42 Β°C, ΡΠ΅ΠΌ ΠΏΡΠΈ 37 Β°C. ΠΡΠ²ΠΎΠ΄Ρ:
Π΄Π΅Π»ΡΡΠ°-Π³Π΅ΠΊΡΠ°Π΄Π΅ΠΊΠ°Π½ΠΎΠ»Π°ΠΊΡΠΎΠ½ (DH16 : 0) ΠΏΠΎΠΊΠ°Π·Π°Π» Π½Π°ΠΈΠ±ΠΎΠ»ΡΡΡΡ ΡΠΈΡΠΎΡΡΠ°ΡΠΈΡΠ΅ΡΠΊΡΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ, ΠΊΠΎΡΠΎΡΠ°Ρ Π·Π½Π°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎ ΡΡΠΈΠ»ΠΈΠ²Π°Π»Π°ΡΡ
Π² ΠΊΠΎΠΌΠ±ΠΈΠ½Π°ΡΠΈΠΈ Ρ Π³ΠΈΠΏΠ΅ΡΡΠ΅ΡΠΌΠΈΠ΅ΠΉ. ΠΡΠΎΡ DAL ΠΌΠΎΠΆΠ½ΠΎ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡ ΠΊΠ°ΠΊ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΠΉ ΡΠΈΡΠΎΡΡΠ°ΡΠΈΠΊ, Π΄Π΅ΠΉΡΡΠ²ΠΈΠ΅ ΠΊΠΎΡΠΎΡΠΎΠ³ΠΎ ΡΡΠΈΠ»ΠΈΠ²Π°Π΅ΡΡΡ
ΠΏΡΠΈ Π³ΠΈΠΏΠ΅ΡΡΠ΅ΡΠΌΠΈΠΈ
Multi-Cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space
Cells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction
Dynamic ordering of driven vortex matter in the peak effect regime of amorphous MoGe films and 2H-NbSe2 crystals
Dynamic ordering of driven vortex matter has been investigated in the peak
effect regime of both amorphous MoGe films and 2H-NbSe2 crystals by mode
locking (ML) and dc transport measurements. ML features allow us to trace how
the shear rigidity of driven vortices evolves with the average velocity.
Determining the onset of ML resonance in different magnetic fields and/or
temperatures, we find that the dynamic ordering frequency (velocity) exhibits a
striking divergence in the higher part of the peak effect regime.
Interestingly, this phenomenon is accompanied by a pronounced peak of dynamic
critical current. Mapping out field-temperature phase diagrams, we find that
divergent points follow well the thermodynamic melting curve of the ideal
vortex lattice over wide field and/or temperature ranges. These findings
provide a link between the dynamic and static melting phenomena which can be
distinguished from the disorder induced peak effect.Comment: 9 pages, 6 figure
The Chang-Refsdal Lens Revisited
This paper provides a complete theoretical treatment of the point-mass lens
perturbed by constant external shear, often called the Chang-Refsdal lens. We
show that simple invariants exist for the products of the (complex) positions
of the four images, as well as moment sums of their signed magnifications. The
image topographies and equations of the caustics and critical curves are also
studied. We derive the fully analytic expressions for precaustics, which are
the loci of non-critical points that map to the caustics under the lens
mapping. They constitute boundaries of the region in the image domain that maps
onto the interior of the caustics. The areas under the critical curves,
caustics and precaustics are all evaluated, which enables us to calculate the
mean magnification of the source within the caustics. Additionally, the exact
analytic expression for the magnification distribution for the source in the
triangular caustics is derived, as well as a useful approximate expression.
Finally, we find that the Chang-Refsdal lens with the convergence greater than
unity can exhibit third-order critical behaviour, if the reduced shear is
exactly equal to \sqrt{3}/2, and that the number of images for N-point masses
with non-zero constant shear cannot be greater than 5N-1.Comment: to appear in MNRAS (including 6 figures, 3 appendices; v2 - minor
update with corrected typos etc.
Design of a General-Purpose MIMO Predictor with Neural Networks
A new multi-step predictor for multiple-input, multiple-output (MIMO) systems is proposed. The output prediction of such a system is represented as a mapping from its historical data and future inputs to future outputs. A neural network is designed to learn the mapping without re quiring a priori knowledge of the parameters and structure of the system. The major problem in de veloping such a predictor is how to train the neural network. In case of the back propagation algorithm, the network is trained by using the network's output error which is not known due to the unknown predicted future system outputs. To overcome this problem, the concept of updating, in stead of training, a neural network is introduced and verified with simulations. The predictor then uses only the system's historical data to update the configuration of the neural network and always works in a closed loop. If each node can only handle scalar operations, emulation of an MIMO mapping requires the neural network to be excessively large, and it is difficult to specify some known coupling effects of the predicted system. So, we propose a vector-structured, multilayer perceptron for the predictor design. MIMO linear, nonlinear, time-invariant, and time-varying systems are tested via simulation, and all showed very promising performances.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68861/2/10.1177_1045389X9400500206.pd
The Anderson Transition in Two-Dimensional Systems with Spin-Orbit Coupling
We report a numerical investigation of the Anderson transition in
two-dimensional systems with spin-orbit coupling. An accurate estimate of the
critical exponent for the divergence of the localization length in this
universality class has to our knowledge not been reported in the literature.
Here we analyse the SU(2) model. We find that for this model corrections to
scaling due to irrelevant scaling variables may be neglected permitting an
accurate estimate of the exponent
Photon trains and lasing : The periodically pumped quantum dot
We propose to pump semiconductor quantum dots with surface acoustic waves
which deliver an alternating periodic sequence of electrons and holes. In
combination with a good optical cavity such regular pumping could entail
anti-bunching and sub-Poissonian photon statistics. In the bad-cavity limit a
train of equally spaced photons would arise.Comment: RevTex, 5 pages, 1 figur
The ALMA Discovery of the Rotating Disk and Fast Outflow of Cold Molecular Gas in NGC 1275
We present ALMA Band 6 observations of the CO(2-1), HCN(3-2), and
HCO(3-2) lines in the nearby radio galaxy / brightest cluster galaxy
(BCG) of NGC 1275 with the spatial resolution of pc. In the previous
observations, CO(2-1) emission was detected as radial filaments lying in the
east-west direction. We resolved the inner filament and found that the filament
cannot be represented by a simple infalling stream both morphologically and
kinematically. The observed complex nature of the filament resembles the cold
gas structure predicted by recent numerical simulations of cold chaotic
accretion. A crude estimate suggests that the accretion rate of the cold gas
can be higher than that of hot gas. Within the central 100 pc, we detected a
rotational disk of the molecular gas whose mass is \sim10^{8} M_{\sun}. This
is the first evidence of the presence of massive cold gas disk on this spatial
scale for BCGs. The disk rotation axis is approximately consistent with the
axis of the radio jet on subpc scales. This probably suggests that the cold gas
disk is physically connected to the innermost accretion disk which is
responsible for jet launching. We also detected absorption features in the
HCN(3-2) and HCO(3-2) spectra against the radio continuum emission mostly
radiated by -pc size jet. The absorption features are blue-shifted
from the systemic velocity by 300-600~km~s, which suggests the
presence of outflowing gas from the active galactic nucleus (AGN). We discuss
the relation of the AGN feeding with cold accretion, the origin of blue-shifted
absorption, and estimate of black hole mass using the molecular gas dynamics.Comment: Version 2 (accepted version). 18 pages, 16 figures. Accepted for
publication in Ap
Accurate screened exchange band structures for transition metal monoxides MnO, FeO, CoO and NiO
We report calculations of the band structures and density of states of the
four transition metal monoxides MnO, FeO, CoO and NiO using the hybrid density
functional sX-LDA. Late transition metal oxides are prototypical examples of
strongly correlated materials, which pose challenges for electronic structure
methods. We compare our results with available experimental data and show that
our calculations yield accurate predictions for the fundamental band gaps and
valence bands of FeO, CoO and NiO. For MnO, the band gaps are underestimated,
suggesting additional many-body effects that are not captured by our screened
hybrid functional approach.Comment: 9 pages, 3 figures, 3 table
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