Culpin
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| Category | Antibiotics |
| Catalog number | BBF-01091 |
| CAS | 125213-21-0 |
| Molecular Weight | 242.31 |
| Molecular Formula | C16H18O2 |
| Purity | ≥ 98% |
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Description
It is produced by the strain of Preussia sp. It has weak antibacterial and antifungal activity.
Specification
| Synonyms | 2-(3-Methyl-2-butenyl)-5-(3-methyl-3-buten-1-ynyl)-1,4-benzenediol |
| IUPAC Name | 2-(3-methylbut-2-enyl)-5-(3-methylbut-3-en-1-ynyl)benzene-1,4-diol |
| Canonical SMILES | CC(=CCC1=CC(=C(C=C1O)C#CC(=C)C)O)C |
| InChI | InChI=1S/C16H18O2/c1-11(2)5-7-13-9-16(18)14(10-15(13)17)8-6-12(3)4/h6,9-10,17-18H,1,8H2,2-4H3 |
| InChI Key | QMYWKFZKRYCUMA-UHFFFAOYSA-N |
Properties
| Appearance | Off-white Crystal |
| Antibiotic Activity Spectrum | Fungi |
| Boiling Point | 400.7 °C at 760 mmHg |
| Melting Point | 98-100 °C |
| Density | 1.10 g/cm3 |
| Solubility | Soluble in Methanol |
Reference Reading
1. A route to 1,4-disubstituted aromatics and its application to the synthesis of the antibiotic culpin
Rajesh Sunasee, Derrick L J Clive J Org Chem. 2008 Oct 17;73(20):8016-20. doi: 10.1021/jo8015192. Epub 2008 Sep 25.
A method is described for converting tert-butyl benzoates or tert-butyl 1-naphthoates into derivatives having an alkyl or substituted alkyl group in a 1,4-relationship to an alkyl, aryl, alkenyl, or alkynyl group. Key steps in the sequence are (i) addition of an organometallic species to a cross-conjugated cyclohexadienone obtained by Birch alkylation of a tert-butyl benzoate or a tert-butyl 1-naphthoate, followed by allylic oxidation, and (ii) treatment with BiCl3 x H2O, which results in removal of the tert-butyl group and spontaneous decarboxylative aromatization. The method was applied to the synthesis of the antimicrobial fungal metabolite culpin.
2. External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study
Abdurrahman I Islim, Christopher P Millward, Rory J Piper, et al. BMJ Open. 2022 Jan 18;12(1):e052705. doi: 10.1136/bmjopen-2021-052705.
Introduction: Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model. Methods and analysis: IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods. Ethics and dissemination: Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media.
3. Recognizing the Problem of Suicidality in Autism Spectrum Disorder
Jeremy Veenstra-VanderWeele J Am Acad Child Adolesc Psychiatry. 2018 May;57(5):302-303. doi: 10.1016/j.jaac.2018.03.003.
Until recently, suicidality in autism spectrum disorder (ASD) was rarely discussed. A cluster of recent articles, including an article by Culpin et al.1 in this issue, has highlighted not only that suicidal thoughts and suicide attempts can occur in adolescents and young adults with ASD, but also that suicidality is likely more common in ASD than in the general population. Retrospectively, the lack of focus on suicidality in ASD seems surprising when self-injurious behavior has long been a focus of attention in ASD.2 The emerging studies indicate that the increased risk of self-injurious behavior in younger and less cognitively able children with ASD3,4 is matched by an increased risk of suicidality in those at a more advanced developmental level.
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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 ╳
