Deflectin 2a
* Please be kindly noted products are not for therapeutic use. We do not sell to patients.
| Category | Antibiotics |
| Catalog number | BBF-00797 |
| CAS | 79495-62-8 |
| Molecular Weight | 398.49 |
| Molecular Formula | C24H30O5 |
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Description
Deflectin 2a is an antibiotic produced by Aspergillus deflectus. It has the activity of lysing bacteria, lysing red blood cells and inhibiting Ehrlich ascites cancer cells, and its activity can be offset by adding serum or serum albumin.
Specification
| Synonyms | Deflctin 2a |
| IUPAC Name | (6aR)-3,6a-dimethyl-9-[(2S)-2-methyldecanoyl]furo[2,3-h]isochromene-6,8-dione |
| Canonical SMILES | CCCCCCCCC(C)C(=O)C1=C2C3=COC(=CC3=CC(=O)C2(OC1=O)C)C |
| InChI | InChI=1S/C24H30O5/c1-5-6-7-8-9-10-11-15(2)22(26)20-21-18-14-28-16(3)12-17(18)13-19(25)24(21,4)29-23(20)27/h12-15H,5-11H2,1-4H3/t15-,24-/m0/s1 |
| InChI Key | HEDXHFZUZSYLJP-OWJWWREXSA-N |
Properties
| Melting Point | 122°C |
Reference Reading
1. Periodic Patchy Spheres Self-Assembled by AmBCAn' Multiblock Terpolymers
Xiaohui Zhang, Weihua Li Langmuir. 2022 Apr 12;38(14):4407-4414. doi: 10.1021/acs.langmuir.2c00139. Epub 2022 Mar 30.
We have designed AmBCAn' multiblock terpolymers and studied their self-assembly using self-consistent field theory, aiming to generate the periodically arranged patchy spheres and thus to clarify the regulation mechanism of the number of patches. A number of two-dimensional phase diagrams are constructed for three typical architectures A2BCA2', A2BCA3', and A3BCA2'. Four kinds of stable patchy spheres with the number of patches as 2 (S2), 4 (S4), 5 (S5), and 6 (S6) are obtained. These phases follow a common transition sequence of S2 → S4 → S5 → S6 along with the increasing of the volume fraction of C-block (fC), which forms the core sphere patched with B-domains. Moreover, the S6 phase exhibits the widest stability window, while S5 has the narrowest one. The increased arms of A'-blocks in A2BCA3' architecture deflect the phase boundaries toward large fC and accordingly expand the regions of these patchy spheres due to the amplified effect of spontaneous curvature. In contrast, the increased arms of A-blocks in A3BCA2' remarkably expands the window of S6 but narrows those of the other patchy spheres, which is mainly caused by increased packing frustration resulting from the reduced extension of the more divided A-blocks. The widest window of the S6 phase reaches ΔfC ~ 0.13, which is readily accessed by experiment. Our work not only demonstrates a self-assembly strategy to engineer the patchy spheres, but also sheds light on the regulation mechanism of the patchy number.
2. Multimodal influences on learning walks in desert ants (Cataglyphis fortis)
Jose Adrian Vega Vermehren, Cornelia Buehlmann, Ana Sofia David Fernandes, Paul Graham J Comp Physiol A Neuroethol Sens Neural Behav Physiol. 2020 Sep;206(5):701-709. doi: 10.1007/s00359-020-01431-9. Epub 2020 Jun 15.
Ants are excellent navigators using multimodal information for navigation. To accurately localise the nest at the end of a foraging journey, visual cues, wind direction and also olfactory cues need to be learnt. Learning walks are performed at the start of an ant's foraging career or when the appearance of the nest surrounding has changed. We investigated here whether the structure of such learning walks in the desert ant Cataglyphis fortis takes into account wind direction in conjunction with the learning of new visual information. Ants learnt to travel back and forth between their nest and a feeder, and we then introduced a black cylinder near their nest to induce learning walks in regular foragers. By doing this across days with different wind directions, we were able to probe how ants balance different sensory modalities. We found that (1) the ants' outwards headings are influenced by the wind direction with their routes deflected such that they will arrive downwind of their target, (2) a novel object along the route induces learning walks in experienced ants and (3) the structure of learning walks is shaped by the wind direction rather than the position of the visual cue.
3. An Electromyographically Driven Cervical Spine Model in OpenSim
Jeff M Barrett, Colin D McKinnon, Clark R Dickerson, Jack P Callaghan J Appl Biomech. 2021 Oct 1;37(5):481-493. doi: 10.1123/jab.2020-0384. Epub 2021 Sep 20.
Relatively few biomechanical models exist aimed at quantifying the mechanical risk factors associated with neck pain. In addition, there is a need to validate spinal-rhythm techniques for inverse dynamics spine models. Therefore, the present investigation was 3-fold: (1) the development of a cervical spine model in OpenSim, (2) a test of a novel spinal-rhythm technique based on minimizing the potential energy in the passive tissues, and (3) comparison of an electromyographically driven approach to estimating compression and shear to other cervical spine models. The authors developed ligament force-deflection and intervertebral joint moment-angle curves from published data. The 218 Hill-type muscle elements, representing 58 muscles, were included and their passive forces validated against in vivo data. Our novel spinal-rhythm technique, based on minimizing the potential energy in the passive tissues, disproportionately assigned motion to the upper cervical spine that was not physiological. Finally, using kinematics and electromyography collected from 8 healthy male volunteers, the authors calculated the compression at C7-T1 as a function of the head-trunk Euler angles. Differences from other models varied from 25.5 to 368.1 N. These differences in forces may result in differences in model geometry, passive components, number of degrees of freedom, or objective functions.
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Bio Calculators
* Our calculator is based on the following equation:
Concentration (start) x Volume (start) = Concentration (final) x Volume (final)
It is commonly abbreviated as: C1V1 = C2V2
* Total Molecular Weight:
g/mol
Tip: Chemical formula is case sensitive. C22H30N4O √ c22h30n40 ╳
