Electronic Cigarette Nicotine Research Articles

Nicotine in electronic cigarettes

AbstractElectronic cigarettes (ECs) are battery-powered gadgets that heat liquid to produce an aerosol. Nicotine is a primary ingredient in some e-liquids; however, due to a lack of quality control regulations, the nicotine may become tainted, or the measured and labelled values may not correspond. To avoid such issues, it is essential to identify the components that contribute to erroneous nicotine quantification. Herein, the differences between free-base nicotine and nicotine salts are discussed, highlighting the lower volatility of nicotine salts and their longer persistence in the body. Discrepancies were noted in the concentration of nicotine salts in some e-liquid samples, with labelled and measured values of 48 and 68.8 mg/mL, respectively, in one sample, and 24 and 33.1 mg/mL, respectively, in another. Inconsistencies were also observed in e-liquids labelled as nicotine-free: one sample had a nicotine concentration of 21.80 mg/cartridge, while another had a concentration of 23.91 mg/mL. The review also covers differences in the potency, flavour, and storage of nicotine under various conditions. Additionally, the literature suggests that the components in ECs are separated into the liquid and vapour phases; thus, phase selection should be considered to ensure optimal experimental outcomes. For instance, the vapour phase comprises the greatest quantities of volatile organic compounds, even though nicotine has been detected in all phases. Finally, the role of ECs in smoking cessation is discussed. The reviewed findings underscore the need for further research on e-liquids, particularly regarding their long-term clinical effects.

A Quick Method for the Determination of the Fraction of Freebase Nicotine in Electronic Cigarettes.

Recently, many electronic cigarettes (ECIGs) manufacturers have begun offering e-liquids, known as "nicotine salts". These salts that have started gaining big popularity among users can be formed by adding weak acid to e-liquid mixtures consisting of propylene glycol (PG), vegetable glycerin (VG), flavors, and nicotine. The latter can exist in two forms: monoprotonated (mp) and freebase (fb) based on the pH of the matrix. Over the years, the determination of the fraction of fb was found important to policymakers as the prevalence of this form in ECIGs has been associated with the harshness sensory of inhalable aerosols. Liquid-liquid extraction (LLE), 1H NMR, and Henderson-Hasselback have been developed to deduce the fraction of fb; however, these methods were found to be time-consuming and have shown some challenges mainly due to the presence of a non-aqueous matrix consisting of PG and VG. This paper presents a quick non-aqueous pH measurement-based method that allows a quick determination of the fraction fb by just measuring the pH and the dielectric constant of the e-liquid. Then, by inputting these values into an established mathematical relationship, the fraction fb can be deduced. The relationship between pH, dielectric constant, and fb relies on knowing the values of the acidity dissociation constants of nicotine, which were determined for the first time in various PG/VG mixtures using a non-aqueous potentiometric titration. To validate the proposed method, the fraction fb was determined for commercials and lab-made nicotine salts utilizing the pH and LLE methods. The variation between the two methods was (<8.0%) for commercial e-liquids and lab-made nicotine salts containing lactic acid and salicylic acid. A larger discrepancy of up to 22% was observed for lab-made nicotine salts containing benzoic acid, which can be attributed to the stronger affinity of benzoic acid to toluene in the LLE method.

Electronic Cigarette Users’ Reactions and Responses to a Hypothetical Nicotine Concentration Reduction in Electronic Cigarette Liquids

Background: Regulations limiting nicotine in electronic cigarettes (e-cigarettes) have been proposed or implemented. Little is known about e-cigarette users’ reactions to reducing e-cigarette liquid nicotine concentration. Methods: We used concept mapping to describe e-cigarette users’ reactions to a 50% reduction in the nicotine concentration of their e-cigarette liquids. In 2019, current e-cigarette users who used e-cigarette liquid with greater than 0 mg/ml nicotine concentration completed an online study. Participants (n = 71, mean age = 34.9 (SD = 11.0), 50.7% women), brainstormed statements completing a prompt: “If the e-liquid that I use now in my e-cigarette/vaping device was only available in half the nicotine concentration or amount that I use now, a specific action I would take or a specific reaction I would have is…”, Participants then sorted a final list of 67 statements into piles of similar content and rated statements on how true the statements would be for them. Multidimensional scaling and hierarchical cluster analyses identified thematic clusters. Results: Eight clusters were identified: (1) Replacement Product Seeking, (2) Mental Preparations and Expectations, (3) Use the New Liquid, (4) Information Seeking, (5) Compensation Behaviors, (6) Opportunity for E-Cigarette Reduction, (7) Physical and Psychological Effects, and (8) Replacement with non-E-Cigarette Products and Behaviors. Cluster ratings suggested many participants would search for other e-cigarette products/liquids to replace their current liquids, but using other tobacco products (e.g., cigarettes) may be less likely. Conclusions: If nicotine concentrations were decreased in e-cigarette liquids, e-cigarette users may attempt to purchase different e-cigarette products or modify their products to achieve desired effects.

Electronic Cigarette Nicotine Flux, Nicotine Yield, and Particulate Matter Emissions: Impact of Device and Liquid Heterogeneity.

Electronic cigarettes (ECIGs) heat a nicotine-containing liquid to produce an inhalable aerosol. ECIG power (wattage) and liquid nicotine concentration are two factors that predict nicotine emission rate ("flux"). These factors can vary greatly across devices and users. The purpose of this study was to examine ECIG device and liquid heterogeneity in "real world" settings and the association with predicted nicotine flux, nicotine yield, and total particulate matter (TPM) emissions. Past 30-day ECIG users (n = 84; mean age = 23.8 years [SD = 9.6]) reported device and liquid characteristics. Device power was measured via multimeter, device display screens, or obtained via labeling. Liquid nicotine concentration was obtained via labeling or through chemical analysis. Predicted nicotine flux, nicotine yield, and TPM associated with 10 4-second puffs were calculated for participants' primary devices. Participants' primary devices were box mods (42.9%), disposable vapes (20.2%), and pod mods (36.9%). Most participants (65.5%) reported not knowing their primary device wattage. Rebuildable/box mods had the greatest power range (11.1-120.0 W); pod mod power also varied considerably (4.1-21.7 W). Unlike device wattage, most participants (95.2%) reported knowing their liquid nicotine concentration, which ranged from 3.0 to 86.9 mg/ml (M = 36.0, SD = 29.3). Predicted nicotine flux varied greatly across products (range =12.0-160.1 μg/s, M = 85.6 μg/s, SD = 34.3). Box mods had the greatest variability in wattage and predicted nicotine flux, nicotine yield, and TPM yield. ECIG device and liquid heterogeneity influence nicotine and other toxicant emissions. Better measurement of ECIG device and liquid characteristics is needed to understand nicotine and toxicant emissions and to inform regulatory policy. ECIG device and liquid heterogeneity cause great variability in nicotine flux and toxicants emitted. These data demonstrate the need to examine device and liquid characteristics to develop empirically informed, health-promoting regulatory policies. Policies may include setting product standards such that ECIG products cannot (1) have nicotine fluxes much greater than that of a cigarette to decrease the risk of dependence, (2) have nicotine fluxes that are very low and thus would have minimal appeal to cigarette smokers and may serve as starter products for youth or nontobacco users, and (3) emit large amounts of particulate matter and other toxicants.

A determination of the aerosolization efficiency of drugs of abuse in a eutectic mixture with nicotine in electronic cigarettes

Characterize the effects of drug interactions with nicotine in the electronic cigarette (e-cigarette). E-liquids are composed of vegetable glycerin (VG), propylene glycol (PG), an active ingredient such as nicotine, and flavorings (Mulder, H.A., et al., Sci Rep., 2019, 9, 102201). Users can adulterate e-liquids with other pharmacologically active substances (Varlet, V. Toxics, 2016, 4, 29). The interaction between the diluent and nicotine forms a eutectic mixture, reducing the melting point to a temperature lower than the individual compounds and promoting aerosolization of the drugs (Gala, U., et al. J Dev Drugs., 2013, 2, e130). The purpose of this study was to evaluate the effect of nicotine on the aerosolization efficiency and recovery of methadone and cocaine using an aerosol capture method adopted from the established Cooperation Centre for the Scientific Research Relative to Tobacco (CORESTA) E-cigarette Task Force industry method. Individual e-liquids were prepared with 12 mg/mL nicotine, methadone, and cocaine in 1:1 PG:VG and drug-free. Aerosol capture was performed using parameters adopted from the CORESTA method. The puff profile was an inhale duration of 3 seconds, an exhale duration of 10 seconds, and a puff volume of 60 mL for a total of 15 puffs. A method for quantitation was validated on a Gas Chromatograph-Mass Spectrometer over five days. The linear range for nicotine was determined to be 500–20,000 ng/mL. Bias and precision were evaluated using quality controls prepared at 1500, 8000, and 16,000 ng/mL. The linear range for methadone and cocaine was 50–5000 ng/mL. Bias and precision were evaluated using quality controls prepared at 150, 1500, and 4000 ng/mL. Carryover was determined for all compounds by evaluating a blank after the injection of the highest calibrator. Aerosol samples were analyzed for drug recovery and dose. Samples were also evaluated for the pyrolytic products of nicotine, methadone, and cocaine: β-nicotyrine (nicotine), EDDP (methadone), and benzoic acid and anhydroecgonine methyl ester (cocaine). The average linear regression ( n = 5) for nicotine, methadone, and cocaine had an r2 > 0.996. Bias and precision for all analytes were within ± 9% and ± 12%CV, respectively. No carryover was observed. In the single drug e-liquids prepared at 12 mg/mL ( n = 3), 1.6 ± 0.2 mg of nicotine, 2.7 ± 0.1 mg of methadone, and 0.94 ± 0.04 mg of cocaine were aerosolized. In the nicotine/methadone mixture ( n = 3), nicotine and methadone increased to 3.7 ± 0.5 mg and 3.7 ± 0.1 mg, respectively. In the nicotine/cocaine mixture ( n = 3), nicotine and cocaine increased to 5.7 ± 2 mg and 2.7 ± 0.2 mg, respectively. In the 15 puffs of the nicotine, methadone, and cocaine e-liquids, 0.22 ± 0.02 g, 0.31 ± 0.01 g, and 0.15 ± 0.02 g ( n = 3) were aerosolized, respectively. In the nicotine/methadone mixture, 0.37 ± 0.01 g ( n = 3) of e-liquid was aerosolized. In the nicotine/cocaine mixture, 0.38 ± 0.02 g ( n = 3) was aerosolized. Pyrolytic products were identified in the e-liquids and aerosol samples, and therefore were not a result of aerosolization. E-liquids containing nicotine and other drugs create a eutectic mixture and can increase the amount of drug delivered in the aerosol. Increases in dose from combining drugs in an e-liquid may result in adverse reactions. The formation of pyrolytic products did not impact the aerosolization efficiency of the parent drugs; however, their presence may cause unexpected effects. The eutectic mixture can result in an increase in aerosolized drug doses.

A determination of the aerosolization efficiency of drugs of abuse in a eutectic mixture with nicotine in electronic cigarettes.

Eutectic mixtures can be formed by adding drugs other than nicotine (DOTNs) to nicotine-based e-liquids in electronic cigarettes (e-cigarettes). Thus, the interaction between nicotine e-liquids and DOTNs must be evaluated. Presented is the change in e-cigarette aerosolization of nicotine and methadone alone versus a 1:1 nicotine:methadone mixture to evaluate the possible formation of a eutectic mixture that can result in an increase of drug delivery. E-liquids were prepared in-house using 1:1 propylene glycol (PG):vegetable glycerin (VG) as a base plus nicotine, methadone hydrochloride, or 1:1 nicotine:methadone hydrochloride. The e-liquids were aerosolized via an automated vaping machine using parameters adopted from the Cooperation Centre for Scientific Research Relative to Tobacco (CORESTA) E-cigarette Task Force method. Drug recovery was determined by capturing the aerosol from 15 puffs generated by the e-cigarette. Concentrations of nicotine and methadone aerosolized were determined by gas chromatography-mass spectrometry using nicotine (n = 3), methadone (n = 3), and combined nicotine/methadone e-liquids (n = 3), each prepared in-house at 12 mg/ml. The concentration of nicotine and methadone in 15 puffs of the single drug e-liquids were determined to be 1.60 ± 0.20 and 2.67 ± 0.12 mg, respectively. The concentration of nicotine and methadone in 15 puffs of the multidrug e-liquid were determined to be 3.66 ± 0.49 and 3.65 ± 0.10mg, respectively. The single nicotine and methadone e-liquids had recoveries of 70 ± 0.1% and 84 ± 0.1%, respectively. In the 1:1 mixture, the recovery of both drugs increased. The development of a eutectic mixture can promote aerosolization of the drug and deliver a greater dose to the user.

Early Chemistry of Nicotine Degradation in Heat-Not-Burn Smoking Devices and Conventional Cigarettes: Implications for Users and Second- and Third-Hand Smokers

Nicotine exposure results in health risks not only for smokers but also for second- and third-hand smokers. Unraveling nicotine’s degradation mechanism and the harmful chemicals that are produced under different conditions is vital to assess exposure risks. We performed a theoretical study to describe the early chemistry of nicotine degradation by investigating two important reactions that nicotine can undergo: hydrogen abstraction by hydroxyl radicals and unimolecular dissociation. The former contributes to the control of the degradation mechanism below 800 K due to a non-Arrhenius kinetics, which implies an enhancement of reactivity as temperature decreases. The latter becomes important at higher temperatures due to its larger activation energy. This change in the degradation mechanism is expected to affect the composition of vapors inhaled by smokers and room occupants. Conventional cigarettes, which operate at temperatures higher than 1000 K, are more prone to yield harmful pyridinyl radicals via nicotine dissociation, while nicotine in electronic cigarettes and vaporizers, with operating temperatures below 600 K, will be more likely degraded by hydroxyl radicals, resulting in a vapor with a different composition. Although low-temperature nicotine delivery devices have been claimed to be less harmful due to their nonburning operating conditions, the non-Arrhenius kinetics that we observed for the degradation mechanism below 873 K suggests that nicotine degradation may be more rapidly initiated as temperature is reduced, indicating that these devices may be more harmful than it is commonly assumed.

Acute Nicotine Poisoning due to Electronic Cigarette Liquid: Systematic Review of Case Reports

Purpose: Acute nicotine poisoning by liquid nicotine in electronic cigarettes is becoming an increasing problem worldwide. The current systematic review aimed to determine the harm of acute nicotine poisoning by reviewing published case reports. Methods: An online literature search with PubMed, Embase, Cochrane Library, and KoreaMed database was performed to identify relevant studies addressing acute nicotine poisoning with electronic cigarettes. Two investigators searched the case reports written in English or Korean. Results: Twenty-six cases were included in this study. The routes of intoxication included ingestion in 18 cases, intravenous injection in three cases, subcutaneous injection in two cases, and ocular exposure in two cases. Ten cases had a cardiac arrest, and seven of them died. Seven out of 12 cases with intentional poisoning had a cardiac arrest. Nine children under 18 years were reported, and three of them had a cardiac arrest. Sixteen cases without a cardiac arrest recovered well, except for one case with sudden sensorineural hearing loss. Conclusion: The authors reviewed the risks of electronic cigarette liquid in terms of acute poisoning through a systematic review. The nicotine solution of an e-cigarette can be life-threatening in cases of acute poisoning. Therefore, active emergency treatment with early recognition is necessary. In addition, various management methods and regulations for preventing acute nicotine poisoning, such as restriction of distribution and nicotine concentration, should be considered.

Effect of free-base and protonated nicotine on nicotine yield from electronic cigarettes with varying power and liquid vehicle

Nicotine in electronic cigarette (ECIG) liquids can exist in a free-base or protonated (or “salt”) form. Protonated nicotine is less aversive upon inhalation than free-base nicotine, and many ECIG manufacturers have begun marketing protonated nicotine products, often with high nicotine concentrations. Regulations intended to control ECIG nicotine delivery limit nicotine concentration but do not consider nicotine form. In this study, we systematically examined the effect of nicotine form on nicotine yield for varying powers and liquid vehicles. A Kanger Subox Mini-C tank ECIG (0.5 Ω) was used to generate aerosols at varying powers (5–45 W) from liquid solutions that contained either free-base or protonated nicotine at 15 mg/g concentration, with a liquid vehicle consisting of either propylene glycol (PG) or vegetable glycerin (VG), resulting in four different solutions (free-base/PG, free-base/VG, protonated/PG, and protonated/VG). Nicotine yield was quantified using gas chromatography-mass spectrometry. Nicotine yields were not influenced by nicotine form under any condition investigated. At each power level, PG-based liquids resulted in approximately double the nicotine yield of VG-based liquids. Nicotine concentrations in the aerosols matched those of the parent liquids for both the PG and VG conditions. Increasing power led to greater nicotine yield across all conditions. The amount of nicotine emitted by an ECIG is independent of whether the nicotine is free-base or protonated, however the liquid vehicle has a strong effect on yield. Regulations intended to limit nicotine emissions must consider not only nicotine concentration, but also liquid vehicle and device power.

What factors reliably predict electronic cigarette nicotine delivery?

BackgroundThe ability of an electronic cigarette (e-cigarette) to deliver nicotine effectively may be dependent on features of the device, the liquid and the user. Some of these features have been...

Influence of Electronic Cigarette Characteristics on Susceptibility, Perceptions, and Abuse Liability Indices among Combustible Tobacco Cigarette Smokers and Non-Smokers.

This study assessed how electronic cigarette (ECIG) characteristics amenable to regulation—namely nicotine content, flavor, and modified risk messages—impact ECIG use susceptibility, harm/addiction perceptions, and abuse liability indices among combustible tobacco cigarette (CTC) smokers and non-smokers. CTC smokers and non-smokers varying in ECIG use recruited via Amazon Mechanical Turk (MTurk) completed an online survey in 2016 (analytic n = 706). Participants were randomly assigned to one of eight conditions differing in ECIG characteristics: nicotine content (no, low, high), flavor (menthol, tobacco, fruit), or modified risk message (reduced harm, reduced carcinogen exposure). Regressions assessed ECIG susceptibility, harm/addiction perceptions, and abuse liability indices (purchase task measures of breakpoint/intensity) within each regulatory domain (nicotine content, flavor, message) and their interactions with CTC/ECIG status. Differential effects on ECIG susceptibility, harm/addiction perceptions, and abuse liability indices were observed by regulatory domain with many effects moderated by CTC/ECIG status. ECIG nicotine content and flavor conditions were the most influential across outcomes. Greater nicotine content, tobacco-flavored and reduced carcinogen exposure ECIGs were more highly preferred by CTC smokers with some differing preferences for non-users. Findings reinforce consideration of discrete ECIG preferences across tobacco use status to improve regulatory efficacy.

Associations of Electronic Cigarette Nicotine Concentration With Subsequent Cigarette Smoking and Vaping Levels in Adolescents

Research indicates that electronic cigarette (e-cigarette) use (vaping) among adolescents is associated with the initiation and progression of combustible cigarette smoking. The reasons for this association are unknown. To evaluate whether use of e-cigarettes with higher nicotine concentrations is associated with subsequent increases in the frequency and intensity of combustible cigarette smoking and vaping. In this prospective cohort study involving students from 10 high schools in the Los Angeles, California, metropolitan area, surveys were administered during 10th grade in the spring (baseline) and 11th grade in the fall (6-month follow-up) of 2015 to students who reported using e-cigarettes within the past 30 days and the nicotine concentration level they used at baseline. Self-report of baseline e-cigarette nicotine concentration of none (0 mg/mL), low (1-5 mg/mL), medium (6-17 mg/mL), or high (≥18 mg/mL) typically used during the past 30 days. Frequency of combustible cigarette smoking and e-cigarette use within the past 30 days (0 days [none], 1-2 days [infrequent], or ≥3 days [frequent]) and daily intensity of smoking and vaping (number of cigarettes smoked per day, number of vaping episodes per day, and number of puffs per vaping episode) at the 6-month follow-up. The analytic sample included 181 students (96 boys [53.0%] and 85 girls [47.0%]; mean [SD] age, 16.1 [0.4] years). Each successive increase in nicotine concentration (none to low, low to medium, and medium to high) vaped was associated with a 2.26 (95% CI, 1.28-3.98) increase in the odds of frequent (vs no) smoking and a 1.65 (95% CI, 1.09-2.51) increase in the odds of frequent (vs no) vaping at follow-up after adjustment for baseline frequency of smoking and vaping and other relevant covariates. Use of e-cigarettes with high (vs no) nicotine concentration was associated with a greater number of cigarettes smoked per day at follow-up (adjusted rate ratio [RR], 7.03; 95% CI, 6.11-7.95). An association with a significantly greater number of vaping episodes per day was found with use of low (adjusted RR, 3.32; 95% CI, 2.61-4.03), medium (adjusted RR, 3.32; 95% CI, 2.54-4.10), and high (adjusted RR, 2.44; 95% CI, 1.63-3.24) nicotine concentrations (vs no nicotine) at baseline. Similar results were found for the number of puffs per vaping episode for low (adjusted RR, 2.05; 95% CI, 1.41-2.70), medium (adjusted RR, 3.39; 95% CI, 2.66-4.11), and high (adjusted RR, 2.23; 95% CI, 1.42-3.03) nicotine concentrations. The results of this study provide preliminary evidence that use of e-cigarettes with higher nicotine concentrations by youths may increase subsequent frequency and intensity of smoking and vaping.

Electronic cigarette user plasma nicotine concentration, puff topography, heart rate, and subjective effects: Influence of liquid nicotine concentration and user experience.

Electronic cigarette (ECIG) nicotine delivery and other effects may depend on liquid nicotine concentration and user experience. This study is the first to systematically examine the influence of ECIG liquid nicotine concentration and user experience on nicotine delivery, heart rate, puff topography, and subjective effects. Thirty-three ECIG-experienced individuals and 31 ECIG-naïve cigarette smokers completed 4 laboratory conditions consisting of 2, 10-puff bouts (30-sec interpuff interval) with a 3.3-V ECIG battery attached to a 1.5-Ω "cartomizer" (7.3 W) filled with 1 ml ECIG liquid. Conditions differed by liquid nicotine concentration: 0, 8, 18, or 36 mg/ml. Participants' plasma nicotine concentration was directly related to liquid nicotine concentration and dependent on user experience, with significantly higher mean plasma nicotine increases observed in ECIG-experienced individuals relative to ECIG-naïve smokers in each active nicotine condition. When using 36 mg/ml, mean plasma nicotine increase for ECIG-experienced individuals was 17.9 ng/ml (SD = 17.2) and 6.9 (SD = 7.1; p < .05) for ECIG-naïve individuals. Between-group differences were likely due to longer puffs taken by experienced ECIG users: collapsed across condition, mean puff duration was 5.6 sec (SD = 3.0) for ECIG-experienced and 2.9 (SD = 1.5) for ECIG-naïve individuals. ECIG use also suppressed nicotine/tobacco abstinence symptoms in both groups; the magnitude of abstinence symptom suppression depended on liquid nicotine concentration and user experience. These and other recent results suggest that policies intended to limit ECIG nicotine delivery will need to account for factors in addition to liquid nicotine concentration (e.g., device power and user behavior). (PsycINFO Database Record

The Use of Substances Other Than Nicotine in Electronic Cigarettes Among College Students.

Introduction:Electronic cigarettes (e-cigarettes) have grown in popularity, especially among youth and young adults. Although e-cigarettes were originally intended to vaporize a liquid mixture containing nicotine, there appears to be an increasing trend in other substance use in e-cigarettes (OSUE).Materials and methods:Cross-sectional data from 1542 undergraduate college student e-cigarette users from a large Midwestern university were collected via online survey to assess prevalence of e-cigarette use, reasons for use, perceived harm, and prevalence and predictors of OSUE.Results:Nearly 7% (6.94%) reported using an e-cigarette to vaporize and inhale a substance other than nicotine. Current tobacco cigarette smokers were significantly more likely to report OSUE (51.0%) as compared with never (33.7%) and former (15.4%) smokers. Among respondents reporting OSUE, the primary reason for e-cigarette use was “safer than cigarettes” (21.7%), followed by “experimentation” (18.9%) and “friends use” (17.0%). Most (77.9%) reported using cannabis or some derivative of cannabis in an e-cigarette. Binomial logistic regression found that women were less likely to report OSUE by a factor of 0.60, former tobacco cigarette smokers as compared with never smokers were more likely to report OSUE by a factor of 1.87, and e-cigarette users who reported using e-cigarettes for “cool or trendy” reasons were more likely to report OSUE by a factor of 2.89.Discussion:Little is known regarding the health effects of cannabis and cannabis derivatives delivered through e-cigarettes. Concern may also be warranted regarding the potential dangers of this young population using substances more dangerous than cannabis in e-cigarettes. Knowledge is limited regarding the public health impact of vaping cannabis or other illicit substances among college student populations. This study stresses the need for continued research regarding the vaping of cannabis and other illicit substances among college students.

Transport phenomena governing nicotine emissions from electronic cigarettes: model formulation and experimental investigation.

Electronic cigarettes (ECIGs) electrically heat and aerosolize a liquid containing propylene glycol (PG), vegetable glycerin (VG), flavorants, water, and nicotine. ECIG effects and proposed methods to regulate them are controversial. One regulatory focal point involves nicotine emissions. We describe a mathematical model that predicts ECIG nicotine emissions. The model computes the vaporization rate of individual species by numerically solving the unsteady species and energy conservation equations. To validate model predictions, yields of nicotine, total particulate matter, PG, and VG were measured while manipulating puff topography, electrical power, and liquid composition across 100 conditions. Nicotine flux, the rate at which nicotine is emitted per unit time, was the primary outcome. Across conditions, the measured and computed nicotine flux were highly correlated (r = 0.85, p<.0001). As predicted, device power, nicotine concentration, PG/VG ratio, and puff duration influenced nicotine flux (p<.05), while water content and puff velocity did not. Additional empirical investigation revealed that PG/VG liquids act as ideal solutions, that liquid vaporization accounts for more than 95% of ECIG aerosol mass emissions, and that as device power increases the aerosol composition shifts towards the less volatile components of the parent liquid. To the extent that ECIG regulations focus on nicotine emissions, mathematical models like this one can be used to predict ECIG nicotine emissions and to test the effects of proposed regulation of factors that influence nicotine flux.

Knowledge and Perceptions about Nicotine, Nicotine Replacement Therapies and Electronic Cigarettes among Healthcare Professionals in Greece

Introduction. The purpose of this study was to evaluate the knowledge and perceptions of Greek healthcare professionals about nicotine, nicotine replacement therapies and electronic cigarettes. Methods. An online survey was performed, in which physicians and nurses working in private and public healthcare sectors in Athens-Greece were asked to participate through email invitations. A knowledge score was calculated by scoring the correct answers to specific questions with 1 point. Results. A total of 262 healthcare professionals were included to the analysis. Most had daily contact with smokers in their working environment. About half of them considered that nicotine has an extremely or very important contribution to smoking-related disease. More than 30% considered nicotine replacement therapies equally or more addictive than smoking, 76.7% overestimated their smoking cessation efficacy and only 21.0% would recommend them as long-term smoking substitutes. For electronic cigarettes, 45.0% considered them equally or more addictive than smoking and 24.4% equally or more harmful than tobacco cigarettes. Additionally, 35.5% thought they involve combustion while the majority responded that nicotine in electronic cigarettes is synthetically produced. Only 14.5% knew about the pending European regulation, but 33.2% have recommended them to smokers in the past. Still, more than 40% would not recommend electronic cigarettes to smokers unwilling or unable to quit smoking with currently approved medications. Cardiologists and respiratory physicians, who are responsible for smoking cessation therapy in Greece, were even more reluctant to recommend electronic cigarettes to this subpopulation of smokers compared to all other participants. The knowledge score of the whole study sample was 7.7 (SD: 2.4) out of a maximum score of 16. Higher score was associated with specific physician specialties. Conclusions. Greek healthcare professionals appear to overestimate the adverse effects of nicotine, and many would not recommend any nicotine-containing product as a long-term smoking substitute. Additionally, they have poor knowledge about the function and characteristics of electronic cigarettes.

Does electronic cigarette liquid nicotine concentration and user experience influence plasma nicotine concentration?

Does electronic cigarette liquid nicotine concentration and user experience influence plasma nicotine concentration?

Content analysis of cannabis smartphone applications

Content analysis of cannabis smartphone applications

Electronic cigarette nicotine delivery can exceed that of combustible cigarettes: a preliminary report

IntroductionElectronic cigarettes (ECIGs) aerosolise a liquid that usually contains propylene glycol and/or vegetable glycerine, flavourants and the dependence-producing drug, nicotine, in various concentrations. This laboratory study examined the relationship between...

Determination of Nicotine in Cartridge-Based Electronic Cigarettes

Electronic cigarettes are a relatively new form of nicotine delivery and their popularity is increasing rapidly. One concern regarding the safety of electronic cigarette is quality control during their manufacture, including whether the nicotine concentration matches the labelling. An assay was developed to evaluate the concentration of nicotine in electronic cigarette cartridges. For nicotine extraction, the pad was removed from the cartridge. Deuterated nicotine solution (1 µg), used as the external standard, was added to the pad and allowed to penetrate into the matrix. The pad was treated with 50 mL of 50% (v/v) methanol/deionized water in an ultrasonic bath for fifteen minutes at ambient temperature. After sonication, the extract was further diluted with deionized water and then analyzed by ultra-high performance liquid chromatography–tandem mass spectrometry. The recovery of nicotine-d4 was 81.5 ± 3.7%. Based on the recovery, the nicotine concentration in the electronic cigarette cartridges was 11.9 ± 1.3 mg, which was lower than the labelled concentration (16 mg). The nicotine concentration did not vary significantly between cartridges within one pack or between packs. The nicotine concentration in the electronic cigarette cartridges was determined by this assay. Differences between labelled and actual nicotine concentrations may affect clinical trials.