Starter Kit Research Articles

Progressing towards personalised medicine: the Genomic Data Infrastructure (GDI) project

Abstract Funded by the European Commission under the Digital Europe Programme and through co-funding from participating Member States, the European Genomic Data Infrastructure (GDI) aims to support the 1+Million Genome initiative for establishing an effective data infrastructure for genomic data. GDI has the potential to fill the gap between genomic research and clinical practice, promoting the implementation of data-driven precision medicine in Europe with the harmonisation of genomic and related phenotypic and clinical data across adhering countries. Launched in November 2022, the GDI project is a collaborative effort involving partners from 20 European countries, divided into 8 Work Packages across three Pillars. GDI is structured with the development of a framework (Pillar I Long-term sustainability) and the necessary tools (Pillar II 1+MG infrastructure deployment), with the implementations of use cases (Pillar III Application and innovation solution) to support research and innovation, integrate findings into the clinic and healthcare, and improve public health measures. In the first 2 years, we completed the starter kit which we are currently testing with real data. Over the subsequent years, the GDI project aims to provide a federated and sustainable infrastructure for facilitating research that use genomic data. Through authorized secure access, clinicians and researchers can leverage genomic insights for faster and more precise clinical decision-making, diagnosis, and treatments. The GDI project represents a significant opportunity to improve healthcare outcomes and public health measures by leveraging the potential of genomics. By providing secure access to extensive genomic datasets combined with phenotyped data, the infrastructure sets the foundation for international partnerships in personalized medicine. Ultimately, this initiative holds the promise of advancing medical understanding, enhancing patient care, and fostering economic growth across Europe. Key messages • GDI drives personalised medicine via international collaboration, building a sustainable infrastructure. Harmonizing data accelerates innovation, improving outcomes and fostering growth in Europe. • GDI aims to revolutionize healthcare by collecting and harmonizing genomic and clinical data in Europe. It facilitates faster and more precise decisions and treatments, improving healthcare outcomes.

The Languages of Love Support Group: Exploring quality of life and relationship satisfaction among couples experiencing cancer.

206 Background: Based on Dr. Gary Chapman’s The Five Love Languages (5LL), love is given and received in different ways. By identifying preferences for reciprocating love, relationships are enhanced through strengthened bonds and improved communication. Study goals were to optimize quality of life and reduce pain through improved dyadic communication via support group curriculum adapted from Dr. Chapman’s work. Methods: A research collaboration was established between an academic pharmacy research team and a large community oncology practice. A group of Masters prepared Social Workers (MSWs) within the oncology practice developed a virtual 6-week, cancer specific curriculum targeting the patient-partner couple (dyad). Participants completed 5LL quiz to determine their preferred love language. In each group session facilitated by MSWs, dyads were educated on each love language meaning (words of affirmation, acts of service, receiving gifts, quality time, physical touch) and potential impact following a cancer diagnosis. Weekly sessions included collective discussion and breakout groups consisting of patients and partners separately. Participants took a researcher-designed, pre- and post-test survey. Participants shared their preferred love language and were encouraged to perform actions accordingly. Dyads were mailed infographics with application examples for each love language and received a welcome starter kit including $50 of items. Results: A pilot group of 24 dyads consisting of 3 cohorts were enrolled in the 6-week intervention. Eleven dyads completed pre- and post-tests (45.8%); 100% of dyads were married, greater than 50% more than 20 years. Greater than 80% of participants were 50 years or older, greater than 70% White; 81.8% of patients female and 63.3% of partners male. Patient relationship satisfaction increased significantly (p<0.10) while trend for improved partner relationship satisfaction was not significant. There was a trend of decreased patient depression and anxiety despite patients’ reported pain increasing significantly (p<0.10). The comments regarding intervention were overwhelmingly positive. Conclusions: Educating dyads within the 5LL virtual support group demonstrated a novel and effective way to provide emotional support and enhance intimate relationships. Through this innovative group, participants learned to identify and express partners’ love language. Pilot intervention shows how this approach is useful in improving relationship satisfaction during the cancer journey. Following group participation, patients also reported increased quality of life and decreased depression and anxiety even while reporting increased pain. Based on this evidence, a couples support group constructed from the 5LL paradigm is a promising approach to improve the quality of life of cancer patients.

How do people quit smoking using e-cigarettes? A mixed-methods exploration of participant smoking pathways following receiving an opportunistic e-cigarette-based smoking cessation intervention.

Pathways of transitioning from tobacco smoking to vaping after receiving an e-cigarette-based smoking cessation intervention have been minimally explored. 1) identify pathways between intervention delivery and final follow-up; 2) describe baseline and post-intervention statistical data in relation to smoking/vaping behaviour of the different pathway groups; 3) explore qualitative participant perspectives contextualising pathway groups. Embedded mixed-methods analysis of data collected for the Cessation of Smoking Trial in the Emergency Department (COSTED) randomised controlled trial. Recruitment from 6 Emergency Departments (5 in England and 1 in Scotland) between January and August 2022. 366 adult smokers who were randomised to receive the COSTED intervention and provided data at 6-month follow-up. Qualitative subsample of 24 participants interviewed after follow-up. Brief smoking cessation advice, provision of an e-cigarette starter kit and referral to the local Stop Smoking Service. Descriptive statistical reporting of identified pathways and smoking/vaping behaviour at baseline and 6-month follow-up. Semi-structured phone/video interviews analysed thematically. 13.4% (n = 49) of participants quit smoking within 1month of receiving the intervention, 19.1% (n = 70) quit between 1 and 6months, 24.9% (n = 91) reduced cigarettes per day (CPD) by at least 50%, and 42.6% did not experience a significant smoking reduction. Approximately a third of participants who quit reported not vaping at follow-up. Reporting dual use was associated with a reduction in CPD. Appoximately athird reported experimenting with a different device to the one provided as part of the intervention. Quitters reported themes of satisfaction with vaping, changes in environment facilitating quitting and motivation to quit. Dual use of cigarettes and e-cigarettes can result in a reduction of smoking and may preclude quitting smoking. Sustained e-cigarette use is not always necessary for quitting success. Success depends on personal context as well satisfaction with vaping.

Engagement With Stop Smoking Services After Referral or Signposting: A Mixed Methods Study.

Screening for smoking when people interact with healthcare services and referral of those who smoke to stop smoking services (SSSs) is a key component of efforts to tackle tobacco use. However, little is known about what happens after someone is referred or signposted to SSSs. As part of the Cessation of Smoking Trial in the Emergency Department (NCT04854616), those randomised to intervention (n= 505) were referred to local SSSs (along with receiving brief advice and an e-cigarette starter kit) and those randomised to control (n= 502) were given contact details for the same services (signposted). SSS engagement data was collected: 1) directly from participants and 2) from SSS, additional qualitative data came from 33 participant interviews. Engagement with SSSs was very low. 3.2% (n=16) of those in the intervention group and 2.4% (n=12) in the control group reported attending a one-to-one support session. From SSS data, engagement was also low with 8.9% (n=43) of those referred engaging and 3.1% (n=15) going on to quit with SSS support. The majority of the 24 intervention participants interviewed did not recall being contacted by an SSS. Referral or signposting to stop smoking services within an Emergency Department based trial resulted in very low levels of engagement. Barriers to engagement identified included participants not being contacted by SSSs and the support offered not meeting their needs. Referral or signposting of those who smoke to Stop smoking services from the Emergency Department resulted in low rates of engagement in this large multi-centre randomised controlled trial. In order to better support those who smoke it may be more effective for smoking cessation advice to be offered 'in the moment' within clinical settings, and follow-up to be proactively offered rather than relying on people being motivated to contact the services themselves or engaging when contacted.

Specialist vape store audit reveals poor compliance with new e-cigarette regulations

aim: Regulations announced in mid-2023 aimed to reduce youth vaping by curtailing the availability of cheap high-nicotine e-cigarettes (vapes). This study tested compliance with the new regulations for single-use vapes, which came into force on 21 December 2023. methods: A 20-year-old “mystery shopper” visited 96% of specialist vape retailers (SVRs) in Wellington, Porirua, Lower Hutt and Upper Hutt (N=74) in January 2024, and observed i) R18 signage, ii) age verification practices, and ii) prices and brands of the cheapest available vaping products. Low-price vapes were purchased and inspected for compliance with new nicotine limits and safety regulations. results: All but three stores (96%) displayed an R18 sign; however, signage in 29 stores (39%) was suboptimal. Only one store (1.4%) requested age identification (ID) on entry to the R18 premises. In 50% of stores, ID was requested when a purchase was made; however, a third of those retailers proceeded with the sale despite the buyer not providing ID. Single-use vapes remained available for NZ$10 or less in most stores, and reusable starter kits were also widely available for NZ$10–20. Discounted high-nicotine products were sold for as little as NZ$2.50 each. Most low-price products did not comply with the updated regulations. conclusion: Cheap, high-nicotine vaping products remained widely available following the introduction of stricter regulations in December 2023; products for sale included discounted and non-compliant vapes. The majority of SVRs had poor age verification practices. There is an urgent need to clarify rules, increase enforcement efforts and disallow discounting and giveaways of vapes.

Promoting planting in front gardens: a systematic approach to intervention development.

Planting in front gardens is associated with a range of human and environmental health benefits. Effective interventions aimed at cultivating this practice are, however, hampered by the paucity of theory- and evidence-based behavioural research in this context. This study aims to systematically determine a set of behaviour change interventions likely to be effective at promoting planting in front gardens amongst UK householders. The Behaviour Change Wheel framework was applied. Behavioural systems mapping was used to identify community actors relevant to front gardening. Potential behavioural influences on householders' front gardening were identified using the Capability, Opportunity, Motivation, Behaviour model. Using peer-reviewed scientific findings as evidence, behavioural influences were systematically linked to potential intervention strategies, behaviour change techniques and real-world implementation options. Finally, intervention recommendations were refined through expert evaluations and local councillor and public stakeholder feedback, evaluating them against the Acceptability, Practicability, Effectiveness, Affordability, Side effects and Equity criteria in a UK implementation context. This study formulated 12 intervention recommendations, implementable at a community level, to promote front gardening. Stakeholder feedback revealed a preference for educational and supportive (social and practical) strategies (e.g., community gardening workshops, front gardening 'starter kits') over persuasive and motivational approaches (e.g., social marketing, motivational letters from the council to householders). Householders' front gardening behaviour is complex and influenced by the behaviour of many other community actors. It also needs to be understood as a step in a continuum of other behaviours (e.g., clearing land, gardening, waste disposal). This study demonstrates the application of behavioural science to an understudied implementation context, that is, front gardening promotion, drawing on a rigorous development process promoting a transparent approach to intervention design. Stakeholder consultation allowed relevance, feasibility and practical issues to be considered. These improve the likely effectiveness of interventions in practice. The next steps include evaluating the proposed interventions in practice.

FPGA Implementation of Deep Learning Model Utilizing Different Normalization Algorithms for COVID-19 Diagnosis

Normalization is utilized to remove outliers from the dataset and address network bias. In this research, Mean-Variance-Softmax-Rescale (MVSR) and Min-Max normalizations are employed in various combinations for the diagnosis of COVID-19 using a Convolutional Neural Network (CNN)-based Deep Learning (DL) model, aimed at enhancing network accuracy. To accomplish this, the CNN model is developed within the Google Colab environment and trained using a publicly available dataset consisting of chest X-ray images related to COVID-19. The dataset is normalized using different combinations of the MVSR and Min-Max normalization algorithms to compare model accuracy. Each normalized dataset is used for model training, and subsequently, each trained model is integrated into the Kria KV260 Vision AI Starter Kit FPGA for the testing phase. The most accurate results are obtained when both MVSR and Min-Max normalizations are applied simultaneously. This high-performing scenario is re-evaluated with real-time camera and FPGA configuration. During real-time implementations, Min-Max normalization is performed within the Colab environment, while the MVSR normalization algorithm is executed using the Kria KV260 Vision AI Starter FPGA Kit. Experimentally, the highest accuracy is achieved in real-time with the MVSR+Min-Max scenario, reaching 93%. The model's precision, recall, and F1-Score values are determined as 0.91, 0.96, and 0.93, respectively.

Relationship Between Product Features and the Prices of e-Cigarette Devices Sold in Web-Based Vape Shops: Comparison Study Using a Linear Regression Model.

Open-system electronic cigarette (EC) product features, such as battery capacity, maximum output wattage, and so forth, are major components that drive product costs and may influence use patterns. Moreover, continued innovation and monitoring of product features and prices will provide critical information for designing appropriate taxation policies and product regulations. This study will examine how product features are associated with the prices of devices sold in web-based vape shops. We draw samples from 5 popular, US-based, web-based vape shops from April to August 2022 to examine starter kits, device-only products, and e-liquid container-only products. We implemented a linear regression model with a store-fixed effect to examine the association between device attributes and prices. EC starter kits or devices vary significantly by type, with mod prices being much higher than pod and vape pen prices. The prices of mod starter kits were even lower than those of mod devices, suggesting that mod starter kits are discounted in web-based vape shops. The price of mod kits, mod device-only products, and pod kits increased as the battery capacity and output wattage increased. For vape pens, the price was positively associated with the volume size of the e-liquid container. On the other hand, the price of pod kits was positively associated with the number of containers. A unit-based specific tax, therefore, will impose a higher tax burden on lower-priced devices such as vape pens or pod systems and a lower tax burden on mod devices. A volume- or capacity-based specific tax on devices will impose a higher tax burden on vape pens with a larger container size. Meanwhile, ad valorem taxes pegged to wholesale or retail prices would apply evenly across device types, meaning those with advanced features such as higher battery capacities and output wattage would face higher rates. Therefore, policy makers could manipulate tax rates by device type to discourage the use of certain device products.

A comparative analysis of Senegalese farm schools: unveiling effective practices for agroecology training

ABSTRACT This paper assesses the value of agroecological farm schools by analyzing 4 Senegalese cases. Pedagogical quality is measured by: (1) feedback from former learners, (2) acquisition of fundamental knowledge, and (3) professionalization. Beyond globally positive opinions about training, our results show that farm schools display distinct performances. Developing a systemic perspective is not an easy task, but having trainers with more advanced agroecological expertise is an asset. Effective training builds on active pedagogy. Post-training business establishment is facilitated when farm schools create networks in agroecology and/or offer a consequent starter kit. Farm schools could thus contribute to agroecological transitions.

Development of a Project Based Arduino Uno R3- Assisted Robotic Training Design

This type of research and development aims to create designs and products for robotics training, as well as robotic training design feasibility through expert validation and eval-uation by respondents. Based on a survey of 49 people surveyed, 28.3% said they did not master the microcontroller material, 10.8% said they had learned it very well, and 17.4% said they didn't know. This suggests that a lower level of competence compared to the SKKNI makes robotics training necessary. A self-training model is used for this training. The study uses a branch version of the ADDIE development model, which is carried out in five stages: 1. analysis, 2. design, 3. development, 4. implementation, and 5. evaluation. This media produces starter kits and video learning, The ADDIE method is a research method that runs from the stage of analysis to its evaluation, the analysis researchers must know the gap of competence from students to industry, search for in-tuitive needs, make the need and the gap into the design of training until the last evalua-tion process, this is finally the reason why Addie is used in this research. Students of SMKN 1 Cilegon and students of Professional Education Electrical Engineering Universi-tas Sultan Ageng Tirtayasa were used in this research. The analytical techniques used are qualitative and quantitative descriptive analysis. Evaluation results from starter kits, learning videos, and learning materials are used to determine the level of eligibility for robotic training designs. The results of the starter kit evaluation showed that the media starter kit was in the category "Very Fit" with an average score of 40.7 with a range x33. In the respondent assessment, it was known that the average rating of the nine-teen respondents was 60.3 with the range x 51, suggesting that the Arduino Uno R3 project-based robotic training design containing a starter kit, video learning modules, and learning materials belonged to the category of "Very Feasible." In other words, this robotics training deserves to be done.

Visible Near-Infrared Hyperspectral Soil Organic Matter Prediction Based on Combinatorial Modeling

Non-destructive, fast, and accurate prediction of soil organic matter content in farmland is of great significance for soil fertility assessment and rational fertilization. In the process of soil organic matter prediction, it is important to give full play to the advantages of different prediction models and to integrate different prediction models to innovatively construct a combined prediction model of soil organic matter content so as to improve the prediction accuracy and generalization ability of the model. In this study, the soil organic matter content of agricultural soils was taken as the research object, and the visible near-infrared hyperspectral curves of soils were measured by the Starter Kit indoor mobile scanning platform (Headwall Photonics, Bolton, MA, USA), and the original spectral curves were firstly de-noised by Savitzky–Golay (S-G) smoothing. Secondly, the smoothed and denoised spectral data were subjected to a first-order differential transform, and the features were selected based on the first-order differential transformed spectral data using the L1-paradigm algorithm features. Then, secondly, eight algorithms based on the selected feature bands, such as LASSO Regression (LASSO) (Model 1), Multilayer Perceptron (MLP) (Model 2), Random Forest (RF) (Model 3), Gaussian Kernel Regression (GKR) (Model 4), Ridge Regression (Model 5), Long Short-Term Memory (LSTM) (Model 6), Convolutional Neural Networks (CNN) (Model 7), and Support Vector Regression (SVR) (Model 8), were applied to construct a single-prediction model of soil organic matter content. Finally, a superior linear combination-prediction model was proposed by the eight single-prediction models constructed, and the standard deviation-based prediction validity was added to test the model. The results showed the following: (1) the weights of the eight single-prediction models in the combined prediction model were ω1*=0.099, ω2*=0.202, ω3*=0.000, ω4*=0.357, ω5*=0.088, ω6*=0.089, ω7*=0.000, ω8*=0.165, respectively; (2) The average precision E of the predicted values of soil organic matter content constructed based on the eight single-prediction models was 0.856; the average standard deviation σ was 0.181, and the average prediction validity M was 0.702; (3) The accuracy E of the predicted value of soil organic matter content of the combined model was 0.893, which was 4.322% higher than the average accuracy of the single model; the standard deviation of the combined model was 0.129, which was 28.333% lower than the average standard deviation of the single model, and the prediction validity M of the combined model was 0.778, which was 10.826% higher than the average prediction validity of the single model. The combined model can be used for the effective estimation of soil organic matter content in farmland with visible near-infrared spectral data, which can provide a basis and reference for the rapid detection of soil organic matter content in farmland.

Switching Away From Smoking and Reduction in Cigarette Consumption Among U.S. Adult Purchasers of the JUUL System Across 24 Months Including Diverse Subpopulations Disproportionately Affected by Cigarette Smoking.

Electronic nicotine-delivery systems (ENDS) can reduce tobacco-related health risks for adults who smoke cigarettes (AWS) by facilitating complete switching away from cigarettes. However, little is known about ENDS use and switching among subpopulations that have been disproportionately affected by smoking. AWS (age ≥ 21 years) were recruited following their first purchase of a JUUL Starter Kit in 2018. Participants who self-reported switching (no past-30-day cigarette smoking) at 1-, 2-, 3-, 6-, 9-, 12-, 15-, 18-, 21-, and 24-month follow-ups. Percent switched and percent with substantial smoking reduction (≥50% decrease in cigarettes per day among those who continued smoking) were calculated. Analyses focused on racial and ethnic minorities, persons with low income and education levels, sexual minorities, and those with mental and physical health conditions. Overall rates of switching away from cigarettes increased across follow-ups to 51.2% (month-12) to 58.6% (month-24, 87% of whom used ENDS). Among those who continued to smoke at 24 months, 45.4% reduced cigarettes per day by ≥ 50%. Rates of switching and substantial smoking reduction were largely similar across subgroups, with some statistically significant, but small, differences in month-24 switching rates (eg, education, mental and physical health conditions; switch rate range: 42%-57%). AWS demonstrated progressively increasing switching rates over 2 years after purchasing JUUL products. Similar trends in switching and smoking reduction were observed across populations disproportionately affected by smoking. By facilitating switching and smoking reduction, ENDS products such as JUUL may provide an opportunity to reduce smoking-related harm among some populations disproportionately affected by smoking, potentially reducing tobacco-related health disparities. ENDS have the potential to benefit population health if they can replace cigarettes. This benefit must extend to populations disproportionately affected by smoking. In this real-world study, 59% of JUUL purchasers reported complete switching 2 years later (no past-30-day smoking, with most continuing to use ENDS). Furthermore, 45% of those who continued to smoke reduced cigarette consumption by at least half. These rates of switching and smoking reduction were largely comparable across populations disproportionately affected by smoking (defined, eg, by ethnicity and income). ENDS can serve as an effective harm reduction strategy to complement current efforts to reduce tobacco-related disparities.

Implementation, enrollment, and engagement in an opt-out telehealth pharmacist-assisted tobacco treatment program for patients seen in oncology outpatient clinics.

To describe the workflow, reach, cost, and self-reported quit rates for an opt-out tobacco treatment program (TTP) for patients seen in 43 oncology outpatient clinics. Between May 25, 2021, and December 31, 2022, adult patients (≥18 years) visiting clinics affiliated with the Medical University of South Carolina Hollings Cancer Center were screened for smoking status. Those currently smoking were referred to a telehealth pharmacy-assisted TTP. An attempt was made to contact referred patients by phone. Patients reached were offered free smoking cessation counseling and a 2-week starter kit of nicotine replacement medication. A random sample of 420 patients enrolled in the TTP were selected to participate in a telephone survey to assess smoking status 4 to 12 months after enrollment. During the reference period 35,756 patients were screened and 9.3% were identified as currently smoking. Among the 3319 patients referred to the TTP at least once, 2393 (72.1%) were reached by phone, of whom 426 (12.8%) were ineligible for treatment, 458 (13.8%) opted out of treatment, and 1509 (45.5%) received treatment. More than 90% of TTP enrollees smoked daily, with an average of 13.1 cigarettes per day. Follow-up surveys were completed on 167 of 420 patients, of whom 23.4% to 33.5% reported not smoking; if all nonresponders to the survey are counted as smoking, the range of quit rates is 9.3% to 13.3%. The findings demonstrate the feasibility of reaching and delivering smoking cessation treatments to patients from a diverse set of geographically dispersed oncology clinics.

Current thinking about the effects of e-cigarettes on oral cancer risk.

In the last decade there has been a significant increase in the appeal and popularity of e-cigarettes. Recent national news headlines outline that one million smokers will be given a free vaping starter kit to encourage them to give up tobacco products. An independent report commissioned by the UK Government has cited promotion of vaping as a critical recommendation to ensuring England is smoke-free by 2030. Undoubtedly, the dental team will now encounter many more questions from patients keen to know more regarding the safety of electronic nicotine delivery systems and their effects on the oral cavity. However, it is often difficult to answer these questions due to a lack of evidence regarding their impact. Although there are some preliminary animal and in vitro data, additional well-designed, long-term studies are required to investigate oral health outcomes of e-cigarette use.We aim to summarise the latest evidence to better inform clinicians about the effects of vaping on oral health, particularly regarding the risks of oral cancer, so they can better inform their patients.

Cessation of Smoking Trial in the Emergency Department (COSTED): a multicentre randomised controlled trial

BackgroundSupporting people to quit smoking is one of the most powerful interventions to improve health. The Emergency Department (ED) represents a potentially valuable opportunity to deliver a smoking cessation intervention...

Selecting an e-cigarette for use in smoking cessation interventions and healthcare services: findings from patient and public consultation for the COSTED trial

ObjectivesThe Cessation of Smoking Trial in the Emergency Department (COSTED) trial aims to ascertain whether brief advice, the provision of an e-cigarette starter kit and referral to stop smoking services...

Feasibility of and reactivity to ecological momentary assessment (EMA) during electronic cigarette use initiation in adults who smoke daily

Background and objectivesThis pilot study tested the feasibility of tracking e-cigarette initiation over three months using a burst-of-measurement approach and examined reactivity to the ecological momentary assessment (EMA) data capture technique in this context. MethodsAdults who smoked daily and were interested in trying e-cigarette use received an e-cigarette starter kit and were randomized to complete EMA reports (n = 30) vs. not (n = 29). Participants (Mage=44.1 years [SD=12.6], 61.0 % male, 54.3 % White, 38.9 % Black/African American) smoked 13.0 cigarettes per day on average (SD=8.4) and reported mild-to-moderate nicotine dependence (MFTND=4.0 [SD=2.3]). Biochemical assessment and surveys were conducted at enrollment, e-cigarette initiation (1 week later), and 1-week, 1-month, and 3-month post e-cigarette initiation. ResultsA subset (17 %) of participants did not achieve the minimum 75 % EMA adherence at Week 1. The remaining participants showed excellent adherence with the EMA protocol, with a consistently high response rate to audibly prompted mini-surveys during screening (93 %) and follow-up weeks (93 %, 93 %, and 92 %, respectively). No consistent trend emerged in comparing the two randomized groups, either on variables relevant to the public health impact of e-cigarette initiation (i.e., cigarettes/day, exposure to smoke, exposure to nicotine, motivation to quit smoking), or in e-cigarette use (i.e., bouts/day, puffs/bout), with average Cohen's d values across timepoints ranging from d = 0.02 for exposure to smoke to d = 0.06 for cigarettes per day. ConclusionsConducting EMA with adults who smoke daily and are initiating e-cigarette use appears feasible, with some caveats. Reactivity to EMA during e-cigarette initiation appears to be small or non-significant.

Dissecting antibiotic effects on the cell envelope using bacterial cytological profiling: a phenotypic analysis starter kit.

Phenotypic analysis assays such as bacterial cytological profiling (BCP) have become increasingly popular for antibiotic mode of action analysis. A plethora of dyes, protein fusions, and reporter strains are available and have been used for this purpose, enabling both rapid mode of action categorization and in-depth analysis of antibiotic mechanisms. However, non-expert researchers may struggle choosing suitable assays and interpreting results. This is a particular problem for antibiotics that have multiple or complex targets, such as the bacterial cell envelope. Here, we set out to curate a minimal set of accessible and affordable phenotypic assays that allow distinction between membrane and cell wall targets, can identify dual-action inhibitors, and can be implemented in most research environments. To this end, we employed BCP, membrane potential, fluidity, and cell wall synthesis assays. To assess specificity and ease of interpretation, we tested three well-characterized and commercially available reference antibiotics: the potassium ionophore valinomycin, the lipid II-binding glycopeptide vancomycin, and the dual-action lantibiotic nisin, which binds lipid II and forms a membrane pore. Based on our experiments, we suggest a minimal set of BCP, a membrane-potentiometric probe, and fluorescent protein fusions to MinD and MreB as basic assay set and recommend complementing these assays with Laurdan-based fluidity measurements and a PliaI reporter fusion, where indicated. We believe that our results can provide guidance for researchers who wish to use phenotypic analysis for mode of action studies but do not possess the specialized equipment or expert knowledge to employ the full breadth of possible techniques.IMPORTANCEPhenotypic analysis assays using specialized fluorescence fusions and dyes have become increasingly popular in antibiotic mode of action analysis. However, it can be difficult to implement these methods due to the need for specialized equipment and/or the complexity of bacterial cell biology and physiology, making the interpretation of results difficult for non-experts. This is especially problematic for compounds that have multiple or pleiotropic effects, such as inhibitors of the bacterial cell envelope. In order to make phenotypic analysis assays accessible to labs, whose primary expertise is not bacterial cell biology, or with limited equipment and resources, a set of simple and broadly accessible assays is needed that is easy to implement, execute, and interpret. Here, we have curated a set of assays and strains that does not need highly specialized equipment, can be performed in most labs, and is straightforward to interpret without knowing the intricacies of bacterial cell biology.

Marketing claims, promotional strategies, and product information on Malaysian e-cigarette retailer websites-a content analysis

BackgroundMarketing and sales of e-cigarettes are unregulated in Malaysia. We analyzed content displayed on e-cigarette retailer websites to identify marketing claims, promotional strategies, and product details in the year 2022.MethodsWe analyzed 30 Malaysia-based retailer websites using a mixed methods approach. Data were extracted as the frequency of occurrences of marketing claims, presence of regulatory information, product types, and flavors of e-juice as per a predefined codebook based on published literature. We also extracted textual details published on the websites about marketing claims, and slogans.ResultsMost retailer websites provided contact information and physical store addresses (83%) but only half had ‘click through’ age verification (57%) that seldom needed any identification proof for age (3%). Marketing claims were related to health (47%), smoking cessation (37%), and modernity/trend (37%) and none had health warnings. Promotional strategies were discounts (80%). starter kits (57%) and email subscriptions (53%). Product types displayed were rechargeable (97%) and disposable (87%) devices and e-liquids (90%) of an array of flavors (> 100). Nicotine presence, its concentration, and “nicotine is an addictive chemical” were displayed in 93%, 53%, and 23% of websites respectively.ConclusionSurveillance of content displayed online on e-cigarette retailer websites and regulation of online marketing and sales should be implemented by the Ministry of Health, Malaysia. Such measures are needed to prevent access to, and initiation of e-cigarette use among the youth and adults who do not smoke.

Adult smokers’ Complete Switching Away from Cigarettes at 6, 9, and 12 Months after Initially Purchasing a JUUL e-Cigarette

Background : Electronic nicotine delivery systems (ENDS) have the potential to benefit public health if smokers completely switch from cigarettes to ENDS. Methods : A cohort of adult smokers (age ≥ 21) who purchased a JUUL Starter Kit was followed for 12 months after the initial purchase. We defined “switching” as past-30-day abstinence from smoking (even if JUUL use had stopped), and analyzed factors associated with achievement and maintenance of self-reported repeated point-prevalence switching (RPPS) at three follow-ups, i.e., no past-30-day smoking at months 6, 9, and 12. Results : RPPS was reported by 21.6% of the 12,537 evaluable smokers. Smokers with lighter smoking history and lower cigarette dependence at baseline were more likely to report RPPS. RPPS was also associated with daily use of JUUL (Month-3: OR = 2.32, 95% CI = 2.02–2.68; Month-6: OR = 1.73, 95% CI = 1.42–2.10), and with greater subjective reinforcing effects from JUUL use (assessed by the mCEQ, Month-3: OR = 1.46, 95% CI = 1.38–1.56; Month-6: OR = 1.11; 95% CI = 1.02–1.20). Even among smokers who did not meet the criteria of RPPS (i.e., who smoked at least once), 35.5% reported past 30-day point-prevalence switching on at least one follow-up, and their cigarette consumption was substantially reduced compared to baseline. Conclusions : Approximately one-fifth of adult smokers reported 30-day point-prevalence abstinence at 6, 9, and 12 months after purchasing JUUL. Greater use of JUUL and stronger subjective reinforcing effects were associated with nonsmoking, validating the potential for ENDS to substitute for smoking, with potential for positive impacts on individual and population health.