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Chemical Structure| 611-92-7

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Standley, Troy ; Putruele, Carissa ; Lambert, Gwladys ; Kelly, Corin ; Liechti, Jana ; Redshaw, Zara , et al.

Abstract: Smokeless powders (SLPs) are easily available energetic materials that are often used in the construction of improvised explosive devices. Following a bombing incident, hand swabs are routinely collected from persons of interest (POIs) to assess potential SLP handling. However, the evidential significance of analytical findings remains difficult to assign due to the lack of systematic data on residue transfer. This study aimed to address this gap by determining the quantities transferred to hands (qT) of three common SLP additives – diphenylamine (DPA), dibutyl phthalate (DBP), and ethyl centralite (EC) – following direct handling of bulk samples, with the specific goal of enabling the estimation of expected qT ranges on a POI’s hands under the hypothesis that they had handled SLP. A streamlined filter-and-shoot method was developed for residue collection and analysis, allowing direct chromatographic analysis without preconcentration steps. The results showed that qT values typically ranged from the high nanogram to low microgram level, with DBP exhibiting the highest values and EC the lowest, mirroring their relative concentrations in the SLP formulations. The total mass of SLP handled (MSLP) and the handler variability (HID) were identified as significant factors influencing qT, whereas the type of SLP (TSLP) had a much weaker effect. Notably, a strong linear dependence between qT and MSLP was observed for all the three compounds. Based on these findings, regression models were developed to estimate expected qT ranges (including means and standard deviations) at different MSLP values, providing a practical tool to refine interpretation where information on the amount of SLP handled is available. By establishing empirical data on SLP residue transfer, this study fills a critical knowledge gap in the literature, enhancing the ability to assess the significance of forensic findings and ultimately contributing to more robust interpretations in cases involving suspected SLP handling.

Keywords: Explosive analysis ; Smokeless powder ; Primary transfer ; Activity level ; Evidential assessment

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Vander Pyl, Courtney ; Feeney, William ; Arroyo, Luis ; Trejos, Tatiana ;

Abstract: This study assesses the capabilities and limitations of liquid chromatog.-tandem mass spectrometry (LC-MS/MS) and gas chromatog.-mass spectrometry (GC-MS) for the trace detection of organic gunshot residue (OGSR), at a time when forensic scientific organizations in the U.S are developing standards to facilitate their adoption. Here, recommendations are provided to aid managers and practitioners with strategies for incorporating OGSR in their workflow. Limits of detection (LODs), limits of quantitation (LOQs), and measurement variability are reported for top eight analytes of interest: nitroglycerin, 2,4-dinitrotoluene, akardite II, methyl centralite, Et centralite, diphenylamine, 2-nitrodiphenylamine, and 4-nitrodiphenylamine. Both techniques detected the targeted analytes with LODs as low as 0.3 ppb for LC-MS/MS and 40 ppb for GC-MS. The methods' performance rates were evaluated using 50 shooter sets, including four different ammunition types. Background specimens were collected from individuals who had not handled a gun in the last 24 h. The solvent extracts were split in half for a direct comparison of the methods on the same specimens. For the ammunition used here, enhanced sensitivity was observed for the triple quadrupole configuration (LC-MS/MS), with accuracies as high as 80%. However, under the extraction and EI-quadrupole instrumental configuration used in this study, GC-MS could not detect enough characteristic compounds to identify OGSR, especially in lower calibers. As a result, the GC-MS anal. displayed accuracies only as high as 35%, raising a flag that GC-MS alone is not recommended for OGSR detection unless combined with LC-MS/MS, or used with alternative pre-concentration methods or high-resolution configurations.

Keywords: Gunshot residues ; Liquid chromatography -tandem mass spec ; trometry ; Gas chromatography -mass spectrometry ; Method validation ; Authentic shooter samples ; Performance rates

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Alternative Products

Product Details of [ 611-92-7 ]

CAS No. :611-92-7
Formula : C15H16N2O
M.W : 240.30
SMILES Code : O=C(N(C)C1=CC=CC=C1)N(C)C2=CC=CC=C2
MDL No. :MFCD00025642
InChI Key :ADCBKYIHQQCFHE-UHFFFAOYSA-N
Pubchem ID :11917

Safety of [ 611-92-7 ]

GHS Pictogram:
Signal Word:Warning
Hazard Statements:H302-H315-H319-H335
Precautionary Statements:P261-P305+P351+P338

Computational Chemistry of [ 611-92-7 ] Show Less

Physicochemical Properties

Num. heavy atoms 18
Num. arom. heavy atoms 12
Fraction Csp3 0.13
Num. rotatable bonds 4
Num. H-bond acceptors 1.0
Num. H-bond donors 0.0
Molar Refractivity 74.97
TPSA ?

Topological Polar Surface Area: Calculated from
Ertl P. et al. 2000 J. Med. Chem.

23.55 Ų

Lipophilicity

Log Po/w (iLOGP)?

iLOGP: in-house physics-based method implemented from
Daina A et al. 2014 J. Chem. Inf. Model.

2.64
Log Po/w (XLOGP3)?

XLOGP3: Atomistic and knowledge-based method calculated by
XLOGP program, version 3.2.2, courtesy of CCBG, Shanghai Institute of Organic Chemistry

2.8
Log Po/w (WLOGP)?

WLOGP: Atomistic method implemented from
Wildman SA and Crippen GM. 1999 J. Chem. Inf. Model.

3.38
Log Po/w (MLOGP)?

MLOGP: Topological method implemented from
Moriguchi I. et al. 1992 Chem. Pharm. Bull.
Moriguchi I. et al. 1994 Chem. Pharm. Bull.
Lipinski PA. et al. 2001 Adv. Drug. Deliv. Rev.

3.46
Log Po/w (SILICOS-IT)?

SILICOS-IT: Hybrid fragmental/topological method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

1.65
Consensus Log Po/w?

Consensus Log Po/w: Average of all five predictions

2.79

Water Solubility

Log S (ESOL):?

ESOL: Topological method implemented from
Delaney JS. 2004 J. Chem. Inf. Model.

-3.32
Solubility 0.114 mg/ml ; 0.000475 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble
Log S (Ali)?

Ali: Topological method implemented from
Ali J. et al. 2012 J. Chem. Inf. Model.

-2.95
Solubility 0.269 mg/ml ; 0.00112 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Soluble
Log S (SILICOS-IT)?

SILICOS-IT: Fragmental method calculated by
FILTER-IT program, version 1.0.2, courtesy of SILICOS-IT, http://www.silicos-it.com

-4.32
Solubility 0.0116 mg/ml ; 0.0000482 mol/l
Class?

Solubility class: Log S scale
Insoluble < -10 < Poorly < -6 < Moderately < -4 < Soluble < -2 Very < 0 < Highly

Moderately soluble

Pharmacokinetics

GI absorption?

Gatrointestinal absorption: according to the white of the BOILED-Egg

High
BBB permeant?

BBB permeation: according to the yolk of the BOILED-Egg

Yes
P-gp substrate?

P-glycoprotein substrate: SVM model built on 1033 molecules (training set)
and tested on 415 molecules (test set)
10-fold CV: ACC=0.72 / AUC=0.77
External: ACC=0.88 / AUC=0.94

No
CYP1A2 inhibitor?

Cytochrome P450 1A2 inhibitor: SVM model built on 9145 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.83 / AUC=0.90
External: ACC=0.84 / AUC=0.91

Yes
CYP2C19 inhibitor?

Cytochrome P450 2C19 inhibitor: SVM model built on 9272 molecules (training set)
and tested on 3000 molecules (test set)
10-fold CV: ACC=0.80 / AUC=0.86
External: ACC=0.80 / AUC=0.87

Yes
CYP2C9 inhibitor?

Cytochrome P450 2C9 inhibitor: SVM model built on 5940 molecules (training set)
and tested on 2075 molecules (test set)
10-fold CV: ACC=0.78 / AUC=0.85
External: ACC=0.71 / AUC=0.81

Yes
CYP2D6 inhibitor?

Cytochrome P450 2D6 inhibitor: SVM model built on 3664 molecules (training set)
and tested on 1068 molecules (test set)
10-fold CV: ACC=0.79 / AUC=0.85
External: ACC=0.81 / AUC=0.87

No
CYP3A4 inhibitor?

Cytochrome P450 3A4 inhibitor: SVM model built on 7518 molecules (training set)
and tested on 2579 molecules (test set)
10-fold CV: ACC=0.77 / AUC=0.85
External: ACC=0.78 / AUC=0.86

No
Log Kp (skin permeation)?

Skin permeation: QSPR model implemented from
Potts RO and Guy RH. 1992 Pharm. Res.

-5.78 cm/s

Druglikeness

Lipinski?

Lipinski (Pfizer) filter: implemented from
Lipinski CA. et al. 2001 Adv. Drug Deliv. Rev.
MW ≤ 500
MLOGP ≤ 4.15
N or O ≤ 10
NH or OH ≤ 5

0.0
Ghose?

Ghose filter: implemented from
Ghose AK. et al. 1999 J. Comb. Chem.
160 ≤ MW ≤ 480
-0.4 ≤ WLOGP ≤ 5.6
40 ≤ MR ≤ 130
20 ≤ atoms ≤ 70

None
Veber?

Veber (GSK) filter: implemented from
Veber DF. et al. 2002 J. Med. Chem.
Rotatable bonds ≤ 10
TPSA ≤ 140

0.0
Egan?

Egan (Pharmacia) filter: implemented from
Egan WJ. et al. 2000 J. Med. Chem.
WLOGP ≤ 5.88
TPSA ≤ 131.6

0.0
Muegge?

Muegge (Bayer) filter: implemented from
Muegge I. et al. 2001 J. Med. Chem.
200 ≤ MW ≤ 600
-2 ≤ XLOGP ≤ 5
TPSA ≤ 150
Num. rings ≤ 7
Num. carbon > 4
Num. heteroatoms > 1
Num. rotatable bonds ≤ 15
H-bond acc. ≤ 10
H-bond don. ≤ 5

0.0
Bioavailability Score?

Abbott Bioavailability Score: Probability of F > 10% in rat
implemented from
Martin YC. 2005 J. Med. Chem.

0.55

Medicinal Chemistry

PAINS?

Pan Assay Interference Structures: implemented from
Baell JB. & Holloway GA. 2010 J. Med. Chem.

0.0 alert
Brenk?

Structural Alert: implemented from
Brenk R. et al. 2008 ChemMedChem

0.0 alert: heavy_metal
Leadlikeness?

Leadlikeness: implemented from
Teague SJ. 1999 Angew. Chem. Int. Ed.
250 ≤ MW ≤ 350
XLOGP ≤ 3.5
Num. rotatable bonds ≤ 7

No; 1 violation:MW<1.0
Synthetic accessibility?

Synthetic accessibility score: from 1 (very easy) to 10 (very difficult)
based on 1024 fragmental contributions (FP2) modulated by size and complexity penaties,
trained on 12'782'590 molecules and tested on 40 external molecules (r2 = 0.94)

1.8
 

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