Colossal anisotropic absorption of spin currents induced by chirality.

The chiral induced spin selectivity (CISS) effect, in which the structural chirality of a material determines the preference for the transmission of electrons with one spin orientation over that of the other, is emerging as a design principle for creating next-generation spintronic devices. CISS implies that the spin preference of chiral structures persists upon injection of pure spin currents and can act as a spin analyzer without the need for a ferromagnet. Here, we report an anomalous spin current absorption in chiral metal oxides that manifests a colossal anisotropic nonlocal Gilbert damping with a maximum-to-minimum ratio of up to 1000%. A twofold symmetry of the damping is shown to result from differential spin transmission and backscattering that arise from chirality-induced spin splitting along the chiral axis. These studies reveal the rich interplay of chirality and spin dynamics and identify how chiral materials can be implemented to direct the transport of spin current.

[Risk factors for embolism in children with refractory Mycoplasmapneumoniae pneumonia and construction of a nomogram model for prediction of embolism]. / éš¾æ²»æ€§è‚ºç‚Žæ”¯åŽŸä½“è‚ºç‚Žæ‚£å„¿åˆå¹¶æ “å¡žçš„å±é™©å› ç´ åˆ†æžåŠåˆ—çº¿å›¾é¢„æµ‹æ¨¡åž‹çš„æž„å»º.

OBJECTIVES: To study the risk factors for embolism in children with refractory Mycoplasma pneumoniae pneumonia (RMPP) and to construct a nomogram model for prediction of embolism. METHODS: This retrospective study included 175 children diagnosed with RMPP at Children's Hospital Affiliated toZhengzhou University from January 2019 to October 2023. They were divided into two groups based on the presence of embolism: the embolism group (n=62) and the non-embolism group (n=113). Multivariate logistic regression analysis was used to screen for risk factors of embolism in children with RMPP, and the R software was applied to construct the nomogram model for prediction of embolism. RESULTS: Multivariate logistic regression analysis indicated that higher levels of D-dimer, interleukin-6 (IL-6) and neutrophil to lymphocyte ratio (NLR), lung necrosis, and pleural effusion were risk factors for embolism in children with RMPP (P<0.05). The area under the curve of the nomogram model for prediction of embolism constructed based on the aforementioned risk factors was 0.912 (95%CI: 0.871-0.952, P<0.05). The Hosmer-Lemeshow goodness-of-fit test showed that the model had a good fit with the actual situation (P<0.05). Calibration and decision curve analysis indicated that the model had high predictive efficacy and clinical applicability. CONCLUSIONS: Higher levels of D-dimer, IL-6 and NLR, lung necrosis, and pleural effusion are risk factors for embolism in children with RMPP. The nomogram model based on these risk factors has high clinical value for predicting embolism in children with RMPP.

Minor envelope proteins from GP2a to GP4 contribute to the spread pattern and yield of type 2 PRRSV in MARC-145 cells.

In China, porcine reproductive and respiratory syndrome virus (PRRSV) vaccines are widely used. These vaccines, which contain inactivated and live attenuated vaccines (LAVs), are produced by MARC-145 cells derived from the monkey kidney cell line. However, some PRRSV strains in MARC-145 cells have a low yield. Here, we used two type 2 PRRSV strains (CH-1R and HuN4) to identify the genes responsible for virus yield in MARC-145 cells. Our findings indicate that the two viruses have different spread patterns, which ultimately determine their yield. By replacing the viral envelope genes with a reverse genetics system, we discovered that the minor envelope proteins, from GP2a to GP4, play a crucial role in determining the spread pattern and yield of type 2 PRRSV in MARC-145 cells. The cell-free transmission pattern of type 2 PRRSV appears to be more efficient than the cell-to-cell transmission pattern. Overall, these findings suggest that GP2a to GP4 contributes to the spread pattern and yield of type 2 PRRSV.

NFTest: automated testing of Nextflow pipelines.

MOTIVATION: The ongoing expansion in the volume of biomedical data has contributed to a growing complexity in the tools and technologies used in research with an increased reliance on complex workflows written in orchestration languages such as Nextflow to integrate algorithms into processing pipelines. The growing use of workflows involving various tools and algorithms has led to increased scrutiny of software development practices to avoid errors in individual tools and in the connections between them. RESULTS: To facilitate test-driven development of Nextflow pipelines, we created NFTest, a framework for automated pipeline testing and validation with customizability options for Nextflow features. It is open-source, easy to initialize and use, and customizable to allow for testing of complex workflows with test success configurable through a broad range of assertions. NFTest simplifies the testing burden on developers by automating tests once defined and providing a flexible interface for running tests to validate workflows. This reduces the barrier to rigorous biomedical workflow testing and paves the way toward reducing computational errors in biomedicine. AVAILABILITY AND IMPLEMENTATION: NFTest is an open-source Python framework under the GPLv2 license and is freely available at https://github.com/uclahs-cds/tool-NFTest. The call-sSNV Nextflow pipeline is available at: https://github.com/uclahs-cds/pipeline-call-sSNV.

The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

Objective: The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). Materials and methods: A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. Conclusion: The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

Sustainable remediation of Cr(VI)-contaminated soil by soil washing and subsequent recovery of washing agents using biochar supported nanoscale zero-valent iron.

Soil contamination by Cr(VI) has attracted widespread attention globally in recent years, but it remains a significant challenge in developing an environmentally friendly and eco-sustainable technique for the disposal of Cr(VI)-contaminated soil. Herein, a sustainable cyclic soil washing system for Cr(VI)-polluted soil remediation and the recovery of washing agents using biochar supported nanoscale zero-valent iron (nZVI-BC) was established. Citric acid (CA) was initially screened to desorb Cr(VI) from contaminated soil, mobilizing Cr from the highly bioaccessible fractions. The nZVI-BC exhibited superior properties for Cr(VI) and Cr(total) removal from spent effluent, allowing effective recovery of the washing agents. The elimination mechanism of Cr(total) by nZVI-BC involved the coordinated actions of electrostatic adsorption, reduction, and co-precipitation. The contributions to Cr(VI) reduction by Fe0, surface-bound Fe(II), and soluble Fe(II) were 0.6 %, 39.8 %, and 59.6 %, respectively. Meanwhile, CA favored the activity of surface-bound Fe(II) and Fe0 in nZVI-BC, enhancing the production of soluble Fe(II) to strengthen Cr(VI) removal. Finally, the recovered washing agent was proven to be reused three times. This study showcases that the combined soil washing using biodegradable chelant CA and effluent treatment by nZVI-BC could be a sustainable and promising strategy for Cr(VI)-contaminated soil remediation.

Kinetically Controlled Synthesis of Metallic Glass Nanoparticles with Expanded Composition Space.

Nanoscale metallic glasses offer opportunities for investigating fundamental properties of amorphous solids and technological applications in biomedicine, microengineering, and catalysis. However, their top-down fabrication is limited by bulk counterpart availability, and bottom-up synthesis remains underexplored due to strict formation conditions. Here, a kinetically controlled flash carbothermic reaction is developed, featuring ultrafast heating (>105 K s-1) and cooling rates (>104 K s-1), for synthesizing metallic glass nanoparticles within milliseconds. Nine compositional permutations of noble metals, base metals, and metalloid (M1─M2─P, M1 = Pt/Pd, M2 = Cu/Ni/Fe/Co/Sn) are synthesized with widely tunable particle sizes and substrates. Through combinatorial development, a substantially expanded composition space for nanoscale metallic glass is discovered compared to bulk counterpart, revealing that the nanosize effect enhances glass forming ability. Leveraging this, several nanoscale metallic glasses are synthesized with composition that have never, to the knowledge, been synthesized in bulk. The metallic glass nanoparticles exhibit high activity in heterogeneous catalysis, outperforming crystalline metal alloy nanoparticles.

Nomogram model for predicting invasive placenta in patients with placenta previa: integrating MRI findings and clinical characteristics.

This study aims to validate a nomogram model that predicts invasive placenta in patients with placenta previa, utilizing MRI findings and clinical characteristics. A retrospective analysis was conducted on a training cohort of 269 patients from the Second Affiliated Hospital of Fujian Medical University and a validation cohort of 41 patients from Quanzhou Children's Hospital. Patients were classified into noninvasive and invasive placenta groups based on pathological reports and intraoperative findings. Three clinical characteristics and eight MRI signs were collected and analyzed to identify risk factors and develop the nomogram model. The mode's performance was evaluated in terms of its discrimination, calibration, and clinical utility. Independent risk factors incorporated into the nomogram included the number of previous cesarean sections ≥ 2 (odds ratio [OR] 3.32; 95% confidence interval [CI] 1.28-8.59), type-II placental bulge (OR 17.54; 95% CI 3.53-87.17), placenta covering the scar (OR 2.92; CI 1.23-6.96), and placental protrusion sign (OR 4.01; CI 1.06-15.18). The area under the curve (AUC) was 0.908 for the training cohort and 0.803 for external validation. The study successfully developed a highly accurate nomogram model for predicting invasive placenta in placenta previa cases, based on MRI signs and clinical characteristics.

Research on automatic recognition radiomics algorithm for early sacroiliac arthritis based on sacroiliac MRI imaging.

OBJECTIVE: To create an automated machine learning model using sacroiliac joint MRI imaging for early sacroiliac arthritis detection, aiming to enhance diagnostic accuracy. METHODS: We conducted a retrospective analysis involving 71 patients with early sacroiliac arthritis and 85 patients with normal sacroiliac joint MRI scans. Transverse T1WI and T2WI sequences were collected and subjected to radiomics analysis by two physicians. Patients were randomly divided into training and test groups at a 7:3 ratio. Initially, we extracted the region of interest on the sacroiliac joint surface using ITK-SNAP 3.6.0 software and extracted radiomic features. We retained features with an Intraclass Correlation Coefficient > 0.80, followed by filtering using max-relevance and min-redundancy (mRMR) and LASSO algorithms to establish an automatic identification model for sacroiliac joint surface injury. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was calculated. Model performance was assessed by accuracy, sensitivity, and specificity. RESULTS: We evaluated model performance, achieving an AUC of 0.943 for the SVM-T1WI training group, with accuracy, sensitivity, and specificity values of 0.878, 0.836, and 0.943, respectively. The SVM-T1WI test group exhibited an AUC of 0.875, with corresponding accuracy, sensitivity, and specificity values of 0.909, 0.929, and 0.875, respectively. For the SVM-T2WI training group, the AUC was 0.975, with accuracy, sensitivity, and specificity values of 0.933, 0.889, and 0.750. The SVM-T2WI test group produced an AUC of 0.902, with accuracy, sensitivity, and specificity values of 0.864, 0.889, and 0.800. In the SVM-bimodal training group, we achieved an AUC of 0.974, with accuracy, sensitivity, and specificity values of 0.921, 0.889, and 0.971, respectively. The SVM-bimodal test group exhibited an AUC of 0.964, with accuracy, sensitivity, and specificity values of 0.955, 1.000, and 0.875, respectively. CONCLUSION: The radiomics-based detection model demonstrates excellent automatic identification performance for early sacroiliitis.

Surgical Treatment of Brucellar Cervical Epidural Abscess.

OBJECTIVES: Brucellar cervical epidural abscess (CEA) is a rare condition with potentially permanent neurological damage if left untreated. This study aims to define the clinical presentation of brucellar CEA and evaluate the outcome of surgical treatment, specifically decompression and fusion surgery. The findings will contribute to understanding whether all patients with brucellar CEA could benefit from this surgical intervention. METHODS: A retrospective study on brucellar spondylitis was conducted at the First Hospital of Jilin University from August 2018 to August 2022. During this period, a total of 37 patients were diagnosed with brucellar spondylitis at the hospital. Out of the 37 cases, six patients (16.2%) were confirmed to have CEA through cervical magnetic resonance imaging examination and serology test results.. RESULTS: Six patients were diagnosed with brucellar CEA (16.2%), of whom 5 successfully underwent anterior cervical decompression and fusion surgery. One patient had a large prevertebral abscess that could only be drained. In combination with effective antibiotic therapy, the clinical performance of the 5 patients who underwent surgery improved after the surgery. The remaining one patient required delayed surgery due to instability of the cervical spine. The follow-up period of all the 6 patients was 6 months. CONCLUSIONS: Brucellosis should be considered as a potential cause of CEA, especially in endemic areas. Timely detection and effective management of this condition are crucial in order to minimize the associated morbidity and mortality. For patients with detectable brucellar CEA, we recommend decompression and fusion surgery.

Bispecific antibodies promote natural killer cell-mediated elimination of HIV-1 reservoir cells.

The persistence of CD4+ T cells carrying latent human immunodeficiency virus-1 (HIV-1) proviruses is the main barrier to a cure. New therapeutics to enhance HIV-1-specific immune responses and clear infected cells will probably be necessary to achieve reduction of the latent reservoir. In the present study, we report two single-chain diabodies (scDbs) that target the HIV-1 envelope protein (Env) and the human type III Fcγ receptor (CD16). We show that the scDbs promoted robust and HIV-1-specific natural killer (NK) cell activation and NK cell-mediated lysis of infected cells. Cocultures of CD4+ T cells from people with HIV-1 on antiretroviral therapy (ART) with autologous NK cells and the scDbs resulted in marked elimination of reservoir cells that was dependent on latency reversal. Treatment of human interleukin-15 transgenic NSG mice with one of the scDbs after ART initiation enhanced NK cell activity and reduced reservoir size. Thus, HIV-1-specific scDbs merit further evaluation as potential therapeutics for clearance of the latent reservoir.

Computer-Aided Diagnosis of Laryngeal Cancer Based on Deep Learning with Laryngoscopic Images.

Laryngeal cancer poses a significant global health burden, with late-stage diagnoses contributing to reduced survival rates. This study explores the application of deep convolutional neural networks (DCNNs), specifically the Densenet201 architecture, in the computer-aided diagnosis of laryngeal cancer using laryngoscopic images. Our dataset comprised images from two medical centers, including benign and malignant cases, and was divided into training, internal validation, and external validation groups. We compared the performance of Densenet201 with other commonly used DCNN models and clinical assessments by experienced clinicians. Densenet201 exhibited outstanding performance, with an accuracy of 98.5% in the training cohort, 92.0% in the internal validation cohort, and 86.3% in the external validation cohort. The area under the curve (AUC) values consistently exceeded 92%, signifying robust discriminatory ability. Remarkably, Densenet201 achieved high sensitivity (98.9%) and specificity (98.2%) in the training cohort, ensuring accurate detection of both positive and negative cases. In contrast, other DCNN models displayed varying degrees of performance degradation in the external validation cohort, indicating the superiority of Densenet201. Moreover, Densenet201's performance was comparable to that of an experienced clinician (Clinician A) and outperformed another clinician (Clinician B), particularly in the external validation cohort. Statistical analysis, including the DeLong test, confirmed the significance of these performance differences. Our study demonstrates that Densenet201 is a highly accurate and reliable tool for the computer-aided diagnosis of laryngeal cancer based on laryngoscopic images. The findings underscore the potential of deep learning as a complementary tool for clinicians and the importance of incorporating advanced technology in improving diagnostic accuracy and patient care in laryngeal cancer diagnosis. Future work will involve expanding the dataset and further optimizing the deep learning model.

The smoking and vaping model, A user-friendly model for examining the country-specific impact of nicotine VAPING product use: application to Germany.

BACKGROUND: Simulation models play an increasingly important role in tobacco control. Models examining the impact of nicotine vaping products (NVPs) and smoking tend to be highly specialized and inaccessible. We present the Smoking and Vaping Model (SAVM),a user-friendly cohort-based simulation model, adaptable to any country, that projects the public health impact of smokers switching to NVPs. METHODS: SAVM compares two scenarios. The No-NVP scenario projects smoking rates in the absence of NVPs using population projections, deaths rates, life expectancy, and smoking prevalence. The NVP scenario models vaping prevalence and its impact on smoking once NVPs became popular. NVP use impact is estimated as the difference in smoking- and vaping-attributable deaths (SVADs) and life-years lost (LYLs) between the No-NVP and NVP scenarios. We illustrate SAVM's adaptation to the German adult ages 18+ population, the Germany-SAVM by adjusting the model using population, mortality, smoking and NVP use data. RESULTS: Assuming that the excess NVP mortality risk is 5% that of smoking, Germany-SAVM projected 4.7 million LYLs and almost 300,000 SVADs averted associated with NVP use from 2012 to 2060. Increasing the excess NVP mortality risk to 40% with other rates constant resulted in averted 2.8 million LYLs and 200,000 SVADs during the same period. CONCLUSIONS: SAVM enables non-modelers, policymakers, and other stakeholders to analyze the potential population health effects of NVP use and public health interventions.

Impact of ecological reserves on the local residents' health: Evidence from a natural experiment in China.

The potential influence of natural ecosystems on human health has been widely acknowledged globally. Nevertheless, the causality of such a correlation among the middle-aged and older populations in developing countries awaits further investigations. This study aims to understand how a specific natural ecosystem change, namely the establishment of ecological reserves, improves the physical and mental health of middle-aged and older residents in China. Two batches of national key eco-function zones (NKEFZs) in 2011 and 2016 are selected as a quasi-experiment; and a total of 128,755 middle-aged and older residents from a combined data set from the China Family Panel Studies (CFPS) and China Health and Retirement Longitudinal Studies (CHARLS) from 2010 to 2020. A difference-in-differences method was used to identify the causal effects of the natural ecosystem improvement on human health outcomes. The results indicate significant and sustained improvements in the physical health of local middle-aged and elderly residents following the implementation of the NKEFZs policy. Notably, ecological reserves with a water conservation function and those in Karst area have the most salient effects on physical health. Furthermore, this study shows that the creation of ecological reserves improves the mental health of middle-aged and older residents, with the effect varying based on changes in physical health. This study provides new insights into the positive impact of natural ecosystem improvement on human health outcomes, in particular physical and mental health.

The impact of the COVID-19 pandemic on the trend of ventilator associated pneumonia incidence in a non-COVID-19 dedicated hospital.

INTRODUCTION: Ventilator associated pneumonia (VAP) is one of the most common hospital-acquired infections for intensive care units in China. Since the COVID-19 outbreak, "Lockdown Wuhan" and other infection control strategies had been implemented in China. The impact of the policies on VAP prevention was estimated in a non-COVID-19 dedicated hospital. METHODOLOGY: We analyzed the VAP trends of 6 intensive care units in a non-COVID-19 dedicated hospital from 2018 to 2020 by Joinpoint regression analysis. The information related to infected VAP patients, VAP surveillance were retrieved from an active surveillance system. RESULTS: There was an obvious decrease in the overall admissions and inpatients of ICUs since January 2020. The overall incidence of VAP was 6.1 episodes per 1000 IMV days. The 30-day case fatality was 16.8%. Generally, the utility rate of IMV ranged from 18.2% to 38.9% respectively, raising with the monthly percent change (MPC): 1.5% [95% confidence interval (CI): 0.8%, 2.2%] from January 2018 to February 2020 by Joinpoint regression analysis. A continuous decline with the MPC: -1.9% (95% CI: -3.2%, -0.5%) of VAP incidence was demonstrated. However, this trend varied among the different ICUs. We found no significant difference neither in 30-day case fatality nor pathogens of VAP patients. CONCLUSIONS: By Joinpoint regression analysis, we can see February 2020 was an important time point. The surveillance indicators were changed, which influenced the VAP incidence.

Synthesis of a covalent organic framework with hetero-environmental pores and its medicine co-delivery application.

The topology type and the functionalization of pores play an important role in regulating the performance of covalent organic frameworks. Herein, we designed and synthesized the covalent organic framework with hetero-environmental pores using predesigned asymmetrical dialdehyde monomer. According to the results of structural characterization, crystallinity investigation, and theoretical calculation, the hetero-environmental pores of the obtained framework are regarded as the alternant arrangement. The distinctive hetero pore structure leads the designed material to show more advantages as compared with control materials in loading both hydrophobic and hydrophilic antibiotics for wound healing. This dual-antibiotic strategy can expand the antibacterial range as compared with the single antibiotic one, and reduce the generation of drug resistance. In summary, this strategy for designing covalent organic frameworks with hetero-environmental pores can extend the structural variety and provide a pathway for improving the practical application performance of these materials.

Effect of a moderate-intensity comprehensive exercise program on body composition, muscle strength, and physical performance in elderly females with sarcopenia.

Objective: This study aimed at examining an eight-week moderate-intensity comprehensive exercise training program on the parameters of sarcopenia in elderly females. Methods: A total of 49 community-dwelling elderly females with sarcopenia (65.5 ± 2.5) were assigned randomly to an experiment group (EG, n = 25) and a control group (CG, n = 24). In the EG, an eight-week comprehensive exercise training program was implemented, in 1 h, 3 times per week, a total of 24 sessions. The CG only received health public education per two weeks, a total of 4 times. Subsequently, the differences between the two groups were tested through two-way repeated ANOVA. Results: ASM, SMM, and SMI in the EG were significantly improved by 0.26 kg, 0.18 kg, and 0.10 kg/m2, respectively. Group-by-time interactions were significantly different on the ASM [F (1,47) = 6.25, η2 = 0.12] and SMI [F (1,47) = 6.77, η2 = 0.13]. Muscle strength was improved 0.8 kg in the EG. Significant group-by-time interaction differences were reported in the handgrip strength [F (1,47) = 6.8, η2 = 0.13] after the eight-week intervention. Compared with the baseline, gait speed was improved a 0.05 m/s and 5-time chair stand was decreased a 0.27 s in the EG. Group-by-time interactions were significantly different in 5-time chair stand [F (1, 47) = 6.35, η2 = 0.12]. Conclusions: The moderate-intensity comprehensive exercise was confirmed as a safe and convenient exercise program. Although a load of training intensity is not sufficient to improve the gait speed, this exercise protocol is promising in delaying overall results in community-dwelling sarcopenia elderly females and contributes to the improvement of muscle mass, handgrip strength, and 5TCS.

Comparison of smoking prevalence in Canada before and after nicotine vaping product access using the SimSmoke model.

OBJECTIVES: The public health impact of nicotine vaping products (NVPs) is subject to complex transitions between NVP and cigarette use. To circumvent the data limitations and parameter instability challenges in modeling transitions, we indirectly estimate NVPs' impact on smoking prevalence and resulting smoking-attributable deaths using the SimSmoke simulation model. METHODS: Canada SimSmoke uses age- and sex-specific data on Canadian population, smoking prevalence and tobacco control policies. The model incorporates the impact of cigarette-oriented policies on smoking prevalence but not the explicit contribution of NVPs. The model was calibrated from 1999 to 2012, thereby projecting smoking prevalence before NVPs were widely used in Canada. The NVP impact on smoking prevalence is inferred by comparing projected 2012-2020 smoking trends absent NVPs to corresponding trends from two Canadian national surveys. We further distinguish impacts before and after NVPs became regulated in 2018 and more available. RESULTS: Comparing 2012-2020 survey data of post-NVP to SimSmoke projected smoking prevalence trends, one survey indicated an NVP-related relative reduction of 15% (15%) for males (females) age 15+, but 32% (52%) for those ages 15-24. The other survey indicated a 14% (19%) NVP-related smoking reduction for ages 18+, but 42% (53%) for persons ages 18-24. Much of the gain occurred since Canada relaxed NVP restrictions. NVP-related 2012-2020 smoking reductions yielded 100,000 smoking-attributable deaths averted from 2012 to 2060. CONCLUSION: Smoking prevalence in Canada, especially among younger adults, declined more rapidly once NVPs became readily available. The emergence of NVPs into the Canadian marketplace has not slowed the decline in smoking.

RéSUMé: OBJECTIFS: L'effet des produits de vapotage avec nicotine (PVN) sur la santé publique dépend des transitions complexes entre l'usage des PVN et l'usage de la cigarette. Pour contourner les problèmes du manque de données et de l'instabilité des paramètres dans la modélisation de ces transitions, nous avons estimé indirectement l'effet des PVN sur la prévalence du tabagisme et sur les décès attribuables au tabagisme qui en résultent à l'aide du modèle de simulation SimSmoke. MéTHODE: Le modèle SimSmoke pour le Canada utilise des données par âge et par sexe sur la population canadienne, la prévalence du tabagisme et les politiques antitabac. Il intègre l'effet des politiques axées sur la cigarette sur la prévalence du tabagisme, mais pas explicitement l'apport des PVN. Ce modèle a été étalonné de 1999 à 2012; il prédit donc la prévalence du tabagisme avant l'utilisation des PVN à grande échelle au Canada. Nous avons déduit l'effet des PVN sur la prévalence du tabagisme en comparant les tendances de consommation de tabac projetées pour 2012­2020 sans PVN aux tendances correspondantes de deux enquêtes nationales canadiennes. Nous établissons aussi une autre distinction entre les effets avant et après la réglementation des PVN en 2018 et leur plus grande disponibilité. RéSULTATS: Si l'on compare les données d'enquête de 2012­2020 post-PVN aux tendances de prévalence du tabagisme projetées par SimSmoke, une enquête fait état d'une baisse de 15 % (15 %) liée aux PVN chez les hommes (femmes) de 15 ans et plus, mais de 32 % (52 %) chez les 15 à 24 ans. L'autre enquête fait état d'une baisse du tabagisme de 14 % (19 %) liée aux PVN chez les 18 ans et plus, mais de 42 % (53 %) chez les 18 à 24 ans. Une grande partie de ce gain s'est produit depuis que le Canada a assoupli ses restrictions sur les PVN. Les baisses du tabagisme liées aux PVN survenues entre 2012 et 2020 donnent 100 000 décès attribuables au tabagisme évités entre 2012 et 2060. CONCLUSION: La prévalence du tabagisme au Canada, surtout chez les jeunes adultes, a baissé plus rapidement lorsque les PVN sont devenus facilement accessibles. L'émergence des PVN sur le marché canadien n'a pas ralenti la baisse du tabagisme.