Effects Of Multiple Interactions Research Articles

A theoretical simulation of carbon dioxide adsorption capture on amine-functionalized graphene oxides

Amine-functionalized graphene oxides (AFGOs) are potential candidates for CO2 capture applications, as the amine functional groups could act as effective sites, promoting CO2 adsorption strength and selectivity. However, the CO2 adsorption mechanism on AFGO appears to be ambiguous, particularly with no explicit identification of the chemically bonded species. In this work, density functional theory and microkinetic simulations were carried out to investigate the physical and chemical adsorption mechanisms and behavior between AFGO and CO2. Our findings indicate that the van der Waals and hydrogen bonding (HB) interactions constitute physical binding modes between the aminated GO and CO2. The chemical adsorption pathways on AFGO materials have been revealed by the transition state search method, in which the relevant CO2 adsorption species, including carbamic acid and carbamate, and their formation conditions were theoretically identified on AFGOs. The chemisorption mechanisms have been recognized to be the nucleophilic interaction between GO-supported amines and CO2, simultaneously assisted by the cooperative effect of multiple HB interactions. More specifically, the surface hydroxyl groups and water molecules can serve as proton transfer media and offer HB interactions, thus regulating the reaction activity and chemical adsorption species. This theoretical work presents a new insight into CO2-AFGO interaction mechanisms, which is valuable for designing aminated GO adsorbents.

Immersion tourism context: scale development and influence mechanism of tourist multiple interactions

ABSTRACT This research aims to clarify the core attributes of tourist multiple interactions, and how it may be possible to promote tourist well-being and citizenship behavior when traveling in an immersion tourism context. A mixed method with two studies was conducted to answer these questions. Study 1 developed and validated a scale for tourist multiple interactions through a mixed qualitative and quantitative research methodology, strictly following the steps of scale development. Survey data were acquired from travel notes, semi-structured interviews, and questionnaires in China. The results showed that tourist multiple interactions scale includes 3 dimensions and 18 items, including technology interactions, narrative empathy, and social interaction. To further verify the influence mechanism of scale, study 2 used a survey to explore the effect of tourist multiple interactions from the perspectives of both tourists and destinations. Survey data were acquired from 311 questionnaires in China. The results indicated that tourist multiple interactions were positively associated with well-being and tourist citizenship behavior. Tourist engagement mediated this relationship. Destination familiarity positively moderated the relationships between tourist multiple interactions and tourist engagement. Theoretically, the research provides extensive implications to tourist interaction and immersion tourism; whilst offering some actionable insights to tourism context.

Association of the panimmune-inflammatory value (PIV) with all-cause and cardiovascular mortality in maintenance hemodialysis patients: a propensity score matching retrospective study.

The panimmune-inflammatory value (PIV) is a novel inflammatory indicator. However, its role in maintenance hemodialysis (MHD) remains unclear. Our goal was to explore the predictive value of PIV for cardiovascular and all-cause mortality in MHD patients. In this retrospective cohort study, 507 patients receiving MHD between November 2017 and December 2022 were enrolled. The PIV value was calculated as follows: neutrophil count × monocyte count × platelet count/lymphocyte count. Patients were divided into two groups on the basis of the median PIV. Propensity score matching (PSM) was used to adjust for imbalances in baseline information between groups. Kaplan‒Meier curves, Cox regression, the Fine‒Gray competing risk model, and restricted cubic spline (RCS) curves were used to analyze the relationship between PIV and mortality. By the end of follow-up, 126 deaths had occurred, 91 of which were due to cardiovascular disease. The Kaplan‒Meier curves demonstrated that MHD patients with higher PIV levels had a poorer prognosis for all-cause death (p = 0.019). PIV levels were linked to all-cause death in multivariate Cox proportional risk regression (HR = 1.76; 95% CI 1.14, 2.72; p = 0.011). The Fine‒Gray model revealed a greater cumulative incidence of cardiovascular death in the higher PIV group (p = 0.035). PIV levels were linked to cardiovascular mortality in the Fine‒Gray competing risk model (HR = 2.06; 95% CI 1.25, 3.42; p = 0.005). The RCS revealed a nonlinear relationship between PIV and mortality risk (p < 0.05). Using 63years of age as the threshold, we observed a multiplicative interaction effect between age and PIV for all-cause mortality (p = 0.006). In MHD patients, PIV is an independent hazard factor for cardiovascular-related mortality and all-cause mortality.

Exploring the effects of multiple online interaction on emotions of L2 learners in synchronous online classes

The decline in both the quantity and quality of interaction has emerged as a notable challenge in online learning. However, the definition of interaction quality remains unclear. This study clarifies it as a decrease in the breadth of interaction, which refers to interaction that can only cover a smaller number of learners. To address this, a synchronous interaction modality, termed Multiple Online Interaction (MOI), based on Zoom's interactive tools, was introduced. In a quasi-experiment involving 58 Chinese L2 learners (with 30 beginner and 28 intermediate students), emotions were assessed using the Brief Mood Introspection Scale (BMIS) while real-time emotional dynamics were revealed through the analysis of 5129 facial expression images during a 35-min synchronous class. MOI participants reported higher levels of Lively and Happy but also experienced more Nervous and less Calm. These emotional dynamics, tracked through expression recognition technology, demonstrate that MOI's impact is primarily observed during the first Grammar & Practice section of the teaching. The empirical findings of this study provide practical insights for educators aiming to conduct effective online teaching in the future.

Age and Gender Differences in the Relationship Between Chronic Pain and Dementia Among Older Australians

ObjectivesChronic pain is a highly debilitating condition that affects older adults and has the potential to increase their odds of experiencing cognitive impairment. The primary objective of this study was to examine the correlation between chronic pain and dementia. Additionally, this research endeavors to ascertain whether the association between chronic pain and dementia differs by age and gender. MethodsCross-sectional data were derived from the Survey of Disability, Ageing, and Carers. A total of 20 671 and 20 081 participants aged 65 years and older in 2015 and 2018, respectively, were included in this study. The pooled association between chronic pain and dementia was assessed using a multivariable logistic regression model. Furthermore, the study also examined the multiplicative interaction effects between chronic pain and age, as well as chronic pain and gender, with dementia. ResultsThe pooled analysis demonstrated that chronic pain was associated with a heightened odds of dementia (adjusted odds ratio 1.95; 95% CI 1.85-2.05) among older Australians compared with their counterparts without chronic pain. The interaction effect indicated that individuals with chronic pain across all age groups exhibited increased odds of living with dementia. Additionally, women with chronic pain had higher odds of dementia compared with their counterparts without chronic pain and being male. ConclusionsA continuous, coordinated, and tailored healthcare strategy is necessary to determine the pain management goals and explore early treatment options for chronic pain in older adults, particularly in groups with the greatest need.

Decorating Cage-Shaped Cavities with Carboxyl Groups on Two-Dimensional MOF Nanosheet for Trace Uranium(VI) Trapping.

The efficient and complete extraction of uranium from aqueous solutions is crucial for safeguarding human health from potential radiotoxicity and chemotoxicity. Herein, an ultrathin 2D metal-organic framework (MOF) nanosheet with cavity structures was elaborately constructed, based on a calix[4]arene ligand. The large molecular skeleton and cup-shaped feature of the calix[4]arene enabled the as-prepared MOFs with large layer separations, which can be readily delaminated into ultrathin single-layer (∼1.25 nm) nanosheets. The incorporation of permanent cavity structures to the MOF nanosheets can fully utilize their structural features of readily accessible adsorption groups and exposed surface area in uranium removal, reaching ultrafast adsorption kinetics; the functionalized cavity structure endowed MOF nanosheets with the ability to preconcentrate and extract uranium from aqueous solutions with ultrahigh efficiencies, even at extremely low concentrations. As a result, relatively high removal ratios (>95%) can be achieved for uranium within 5 min, even in the ultralow concentration range of 75-250 ppb, and the residual uranium was reduced to below 4.9 ppb. The MOF nanosheets also exhibited extremely high anti-interference ability, which could efficiently remove the low-level uranium (∼150 ppb) from various real samples. The characterizations and density functional theory calculations demonstrated that the synergistic effects of multiple interactions between the carboxylate groups and cage-like cavities with uranyl ions can be responsible for the efficient and selective uranium extraction.

Large-pore covalent organic framework as solid phase extraction absorbentforefficientdetermination of polypeptide antibiotics in animal-derived foods

The precise determination of polypeptide antibiotics (PPTs) in foods has been always challenging because of the interference of various endogenous peptides in complex matrix. Herin, a novel large-pore covalent organic framework (TABPT-SPDA-COF) with accessible pore size of 7.9 nm was synthesized as a solid phase extraction (SPE) absorbent for efficiently enriching four PPTs existed in foods originating from animals. The parameters of SPE process were systematically optimized. Subsequently, four PPTs were determined by UHPLC-MS/MS. Under the optimal conditions, TABPT-SPDA-COF shows outstanding enrichment capacity for PPTs in contrast to commercial absorbents ascribed to size selectivity and multiple interaction effects. The method exhibits excellent linear range (0.005–100 ng mL−1), satisfactory limits of detection (0.1 pg mL–1) as well as relative recoveries (86.2–116 %). This work offers a practicable platform to monitor trace PPTs from complex animal-derived foodstuffs.

Multi-Responsive Peptide-Based Ultrathin Nanosheets Prepared by a Horizontal Monolayer Assembly.

In this study, peptide-based self-assembled nanosheets with a thickness of approximately 1 nm were prepared using a hierarchical covalent physical fabrication strategy. The covalent alternating polymerization of helical peptide E3 with an azobenzene (AZO) structure yielded copolymers CoP(E3-AZO), which physically self-assembled into ultrathin nanosheets in an unanticipated two-dimensional horizontal monolayer arrangement. This special monolayer arrangement enabled the thickness of the nanosheets to be equal to the cross-sectional diameter of a single linear copolymer, which is a rare phenomenon. Molecular dynamics simulations suggested that the synergistic effect of multiple molecular interactions drives the self-assembly of CoP(E3-AZO) into nanosheets and that various methods, including phototreatment, pH adjustment, the addition of additives, and introduction of cosolvents, can alter the molecular interactions and modulate the self-assembly of CoP(E3-AZO), yielding diverse nanostructures. Remarkably, the ultrathin nanosheets selectively inhibited cancer cells at certain concentrations.

Multi‐Responsive Peptide‐Based Ultrathin Nanosheets Prepared by a Horizontal Monolayer Assembly

AbstractIn this study, peptide‐based self‐assembled nanosheets with a thickness of approximately 1 nm were prepared using a hierarchical covalent physical fabrication strategy. The covalent alternating polymerization of helical peptide E3 with an azobenzene (AZO) structure yielded copolymers CoP(E3‐AZO), which physically self‐assembled into ultrathin nanosheets in an unanticipated two‐dimensional horizontal monolayer arrangement. This special monolayer arrangement enabled the thickness of the nanosheets to be equal to the cross‐sectional diameter of a single linear copolymer, which is a rare phenomenon. Molecular dynamics simulations suggested that the synergistic effect of multiple molecular interactions drives the self‐assembly of CoP(E3‐AZO) into nanosheets and that various methods, including phototreatment, pH adjustment, the addition of additives, and introduction of cosolvents, can alter the molecular interactions and modulate the self‐assembly of CoP(E3‐AZO), yielding diverse nanostructures. Remarkably, the ultrathin nanosheets selectively inhibited cancer cells at certain concentrations.

Associations between residential environments and late-onset schizophrenia in UK Biobank: Interaction with genetic risk factor

BackgroundEnvironment and genes both contribute to schizophrenia. However, the impact of different natural environments surrounding residential addresses on schizophrenia in urban settings remains unknown. This study aimed to investigate the association of urbanisation, measured by residential environments, with late-onset schizophrenia and explore whether genetic risk for schizophrenia modified the associations. MethodsWe examined the associations between residential environments and late-onset schizophrenia and its interaction with genetic risk factors in UK Biobank, followed from 2006 to 2010 (baseline) to Dec 2021. Residential environments, including greenspace, domestic garden, blue space, and total natural environment, were evaluated using land use coverage percentage. The polygenic risk score (PRS) of schizophrenia was derived using a Bayesian approach and adjusted it against ancestry. Cox proportional hazard regression model was used to assess the associations between per interquartile (IQR) increase of each type of residential environments and late-onset schizophrenia. Interactive effects of PRS and residential environments on late-onset schizophrenia were assessed on both additive and multiplicative scales. ResultsA total of 393,680 participants were included in the analysis, with 844 cases of late-onset schizophrenia being observed after 12.8 years of follow-up. Within 300 m buffer surrounding the residential addresses, per interquartile increase in greenspace (31.5 %) and total natural environment (34.4 %) were both associated with an 11 % (HR = 0.89, 95 % CI 0.80, 0.99) lower risk of late-onset schizophrenia. Domestic garden and blue space did not show significant protective effects on late-onset schizophrenia. A strong dose-response relationship between schizophrenia PRS and schizophrenia was found, while no additive or multiplicative interaction effects were present between residential environments and PRS on late-onset schizophrenia. ConclusionResidential greenspace and total natural environment may protect against late-onset schizophrenia in older people regardless of genetic risk. These findings shed light on the prevention of schizophrenia and urban planning to optimise ecosystem benefits linked to schizophrenia.

The interaction between estimated glomerular filtration rate and dietary magnesium intake and its effect on stroke prevalence: a cross-sectional study spanning 2003-2018.

Despite the known associations of dietary magnesium intake and estimated glomerular filtration rate (eGFR) with cardiovascular diseases, their combined effects on stroke risk remain unclear. Therefore, this study aims to explore the associations of dietary magnesium intake and eGFR with stroke risk. The National Health and Nutrition Examination Survey (NHANES) data of 37,637 adult participants (≥18 years) from 2003 to 2018 was analyzed. Dietary magnesium intake was categorized as low (≤ 254 mg/day) and normal (> 254 mg/day) based on experimental data. Multiple logistic regression analyses and interaction tests were conducted to assess the associations of dietary magnesium intake and eGFR with stroke risk, with a focus on the interaction between different chronic kidney disease (CKD) stages based on eGFR levels and dietary magnesium intake. Additional analyses included multiplicative interaction analysis, restricted cubic spline analysis, and subgroup evaluations by age, sex, and ethnicity. Dietary magnesium intake and eGFR were inversely correlated with the risk of stroke. Participants with low dietary magnesium intake had a higher stroke risk than those with normal magnesium intake (odds ratio [OR] 1.09, 95% confidence interval [CI]: 1.03-1.42). Likewise, low eGFR was associated with an elevated stroke risk compared with normal eGFR (OR 1.56, 95% CI: 1.15-2.13). Furthermore, the two factors showed a multiplicative interaction effect on stroke risk (OR 1.05, 95% CI: 1.01-1.09). We observed a significant interaction between stage G3 CKD and low dietary magnesium intake (OR 1.05, 95% CI: 1.01-1.09), suggesting a potential association with stroke risk. However, similar associations were not observed for stages G4 and G5, possibly due to the smaller number of participants with G4 and G5 CKD. The restricted cubic spline analysis revealed a non-linear relationship between dietary magnesium intake, eGFR, and stroke risk. The interaction between magnesium deficiency and low eGFR persisted in participants aged >60 years, as well as in females, non-Hispanic Black people, and people of other races. Dietary magnesium intake and eGFR correlate negatively with stroke prevalence. Moreover, there was an interaction between dietary magnesium intake and stroke prevalence across different CKD stages. Further large-scale prospective studies are needed to analyze the potential relationship between dietary magnesium intake, eGFR, and stroke.

Genotype-by-environment interaction and stability analysis of grain yield of bread wheat (Triticum aestivum L.) genotypes using AMMI and GGE biplot analyses

Bread wheat is a vital staple crop worldwide; including in Ethiopia, but its production is prone to various environmental constraints and yield reduction associated with adaptation. To identify adaptable genotypes, a total of 12 bread wheat genotypes (G1 to G12) were evaluated for their genotype-environment interaction (GEI) and stability across three different environments for two years using Additive Main Effect and Multiplicative Interaction (AMMI) and genotype main effect plus genotype-by-environment interaction (GGE) biplots analysis. GEI is a common phenomenon in crop improvement and is of significant importance in genotype assessment and recommendation. According to combined analysis of variance, grain yield was considerably impacted by environments, genotypes, and GEI. AMMI and GGE biplots analysis also provided insights into the performance and stability of the genotypes across diverse environmental conditions. Among the 12 genotypes, G6 was selected by AMMI biplot analysis as adaptive and high-yielding genotype; G5 and G7 demonstrated high stability and minimal interaction with the environment, as evidenced by their IPCA1 values. G7 was identified as the most stable and high-yielding genotype. The GGE biplot's polygon view revealed that the highest grain yield was obtained from G6 in environment three (E3). E3 was selected as the ideal environment by the GGE biplot. The top three stable genotypes identified by AMMI stability value (ASV) were G5, G7, and G10, while the most stable genotype determined by Genotype Selection Index (GSI) was G7. Even though G6 was a high yielder, it was found to be unstable according to ASV and ranked third in stability according to GSI. Based on the study's findings, the GGE biplot genotype view for grain yield identified Tay genotype (G6) to be the most ideal genotype due to its high grain yield and stability in diverse environments. G7 showed similar characteristics and was also stable. These findings provide valuable insights to breeders and researchers for selecting high-yielding and stable, as well as high-yielding specifically adapted genotypes.

New Weibull Log-Logistic grey forecasting model for a hard disk drive failures

Forecasting the failure of hard disk drives is important in server operation and has attracted increasing attention. However, current disk drive warning systems suffer from high false positive rates and high resource consumption when dealing with hard disk drive overall failure. Therefore, to accurately and stably predict hard disk drive overall failure, this paper develops a new Weibull Log-Logistic grey forecasting model with multiple interaction effects. Firstly, to capture and fit the trend of hard disk failure data flexibly and reduce the volatility, a new accumulation generation operator is established by introducing the Weibull Log-Logistic mixture distribution. Secondly, the proposed model constructs a multiple interaction term to describe the nonlinear relationship of the dependent variables on the system behavior series and the multiple interaction effects between the independent variables. Then, the parameter estimation method is designed to improve the fitting accuracy of the new model, in which linear estimation method, nonlinear estimation method, and meta-heuristic optimization algorithm are used to calculate the parameter values according to their categories. Finally, four varieties of hard disk drive data sets from BackBlaze are selected as study cases to validate the effectiveness of the proposed model. The results show that the mean MAPE of the proposed method is 2.1181 %, 2.2306 %, 8.1712 %, and 4.3417 %, respectively, corresponding to (hard disk drives ST8000NM0055, ST12000NM0007, ST10000NM0086, and ST14000NM0138), and the average value of the evaluation metrics are optimal in all competing models. Furthermore, it is observed that the number of reallocated sectors has the greatest influence in causing the failure of hard disk drives.

Chirality-selective topological magnon phase transition induced by interplay of anisotropic exchange interactions in honeycomb ferromagnet

A variety of distinct anisotropic exchange interactions commonly exist in one magnetic material due to complex crystal, magnetic and orbital symmetries. Here we investigate the effects of multiple anisotropic exchange interactions on topological magnon in a honeycomb ferromagnet, and find a chirality-selective topological magnon phase transition induced by a complicated interplay of Dzyaloshinsky–Moriya interaction and pseudo-dipolar interaction, accompanied by the bulk gap close and reopen with chiral inversion. Moreover, this novel topological phase transition involves band inversion at high symmetry points K and K′, which can be regarded as a pseudo-orbital reversal, i.e. magnon valley degree of freedom, implying a new manipulation corresponding to a sign change of the magnon thermal Hall conductivity. Indeed, it can be realized in 4d or 5d correlated materials with both spin–orbit coupling and orbital localized states, such as iridates and ruthenates, etc. This novel regulation may have potential applications on magnon devices and topological magnonics.

AMMI and GGE biplot analysis for genotype × environment interactions affecting the yield and quality characteristics of sugar beet.

Sugar beet, an important sugar crop, contributes significantly to the world's sugar production. However, genotype-environment interactions (GEI) often affect the quality characteristics of sugar beet. Hence, understanding the effects of GEI on sugar beet quality can aid in identifying high-quality genotypes that can adapt to different environments. Traditional variance analysis can only be used to examine the yield of a variety and not its specific adaptability to specific conditions. Therefore, more comprehensive analytical methods are required to evaluate the characteristics of the variety under specific environments. Additive main effects and multiplicative interaction (AMMI) and genotype main effect and genotype × environment interaction (GGE) biplot models can be employed to comprehensively evaluate different varieties and address the drawbacks associated with a single evaluation method. Moreover, these models also allow us to explore new varieties more objectively and comprehensively. In this study, the adaptability and stability of 16 sugar beet varieties, in terms of yield and sugar content, were evaluated using AMMI and GGE biplot analysis in seven pilot projects undertaken in 2022. In the assessment of a small but significant proportion of the total GEI variance for the two qualitative traits (yield and sugar content), 80.58% of the variance was explained by the cumulative contribution of IPC1, IPC2, and IPC3. AMMI and GGE biplots clearly highlighted that KWS4207 (G3) exhibited high and stable quality. They also demonstrated that the experiments in Jalaid Banner (Inner Mongolia) (E7) were the most representative. Together, the results suggested that the comprehensive application of AMMI and GGE biplot analysis allowed for a more comprehensive, scientific, and effective evaluation of sugar beet varieties across different regions. The findings offer a theoretical basis for sugar beet breeding and could guide the rational design of experiments for testing new varieties of sugar beet.

Excess winter mortality in Finland, 1971–2019: a register-based study on long-term trends and effect modification by sociodemographic characteristics and pre-existing health conditions

ObjectivesExcess winter mortality is a well-established phenomenon across the developed world. However, whether individual-level factors increase vulnerability to the effects of winter remains inadequately examined. Our aim was to assess...

Mediation effect of antithrombin III between chronic renal insufficiency and chronic coronary artery disease in T2DM patients.

The study aimed to investigate the potential effect of Antithrombin III (ATIII) between chronic renal insufficiency and chronic coronary artery disease (chronic CAD) in type 2 diabetes mellitus (T2DM) patients. T2DM patients hospitalized in ZhongDa Hospital from 2013 to 2018 were enrolled. Relationships between renal function, ATIII, and chronic CAD risk were explored using multivariate regression models. Multiplicative and additive interactions were investigated between ATIII and renal function for CAD risk, and the role of ATIII was determined by bootstrap mediation analysis in patients with chronic renal dysfunction. A total of 4197 patients were included in the study, with a chronic CAD prevalence of 23.02%. Low ATIII level was statistically associated with chronic renal insufficiency and elevated CAD risk even after adjustments (P < 0.05). A positive correlation between renal function and ATIII was demonstrated, and each 1 SD increase in renal function, ATIII increased by 2.947% (2.406-3.488%, P < 0.001) and 0.969% (0.297-1.642%, P < 0.001) in crude and adjusted models respectively. Patients with decreased renal function and ATIII were at the highest chronic CAD risk (OR = 1.51, 95%CI:1.15-1.98, P < 0.05), while no multiplicative and additive interaction effects were significant. Bootstrap mediation analysis estimated that ATIII mediated approximately 4.27% of the effect of chronic renal insufficiency on chronic CAD risk. ATIII may serve as a mediator between chronic renal insufficiency and chronic CAD, providing mechanistic clues for renal-heart association and new insight into clinical therapies.

Refractive neutrino masses, ultralight dark matter and cosmology

We consider in detail a possibility that the observed neutrino oscillations are due to refraction on ultralight scalar boson dark matter.We introduce the refractive mass squared, m̃2, and study its properties: dependence on neutrino energy,state of the background, etc. If the background is in a state of cold gas of particles, m̃2 shows a resonance dependence on energy. Above the resonance (E ≫ ER ), we find that m̃2 has the same properties as usual vacuum mass squared.Below the resonance, m̃2 decreases with energy, which (if realised) allows to avoid the cosmological bound on the sum of neutrino masses. Also, m̃2 may depend on time. We consider the validity of the results: effects of multiple interactions with scalars, and modification of the dispersion relation. We show that for values of parameters of the system required toreproduce the observed neutrino masses, perturbativity is broken at low energies, which border above the resonance.If the background is in the state of coherent classical field, the refractive mass does not depend on energy explicitly but may showtime dependence. It coincides with the refractive mass in a cold gas at high energies.Refractive nature of neutrino mass can be tested by searches of its dependence on energy and time.

The Combined Effects of Alcohol Consumption and Smoking on Cancer Risk by Exposure Level: A Systematic Review and Meta-Analysis.

Alcohol consumption is a major risk factor for cancer, and when combined with smoking, the risk increases. Nevertheless, few studies have comprehensively evaluated the combined effects of alcohol consumption and smoking on the risk of various cancer types. Therefore, to assess these effects, we conducted a systematic review and meta-analysis. We performed a systematic search of five literature databases, focusing on cohort and case-control studies. Considering exposure levels, we quantified the combined effects of alcohol consumption and smoking on cancer risk and assessed multiplicative interaction effects. Of 4,452 studies identified, 24 (4 cohort studies and 20 case-control studies) were included in the meta-analysis. We detected interaction effect of light alcohol and moderate smoking on head and neck cancer risk (relative risk [RR], 4.26; 95% confidence interval [CI], 2.50-7.26; I² = 65%). A synergistic interaction was observed in heavy alcohol and heavy smoking group (RR, 35.24; 95% CI, 23.17-53.58; I² = 69%). In more detailed cancer types, the interaction effect of heavy alcohol and heavy smoking was noticeable on oral (RR, 36.42; 95% CI, 24.62-53.87; I² = 46%) and laryngeal (RR, 38.75; 95% CI, 19.25-78.01; I² = 69%) cancer risk. Our study provided a comprehensive summary of the combined effects of alcohol consumption and smoking on cancers. As their consumption increased, the synergy effect became more pronounced, and the synergy effect was evident especially for head and neck cancer. These findings provide additional evidence for the combined effect of alcohol and smoking in alcohol guidelines for cancer prevention.

A locally explained heterogeneity model for examining wetland disparity

ABSTRACTIdentifying the factors influencing wetland variations is crucial for understanding the relationship of climate change with wetland conservation and management. The wetland distribution is associated with multiple variables, and the interactions among these variables are complex. In this study, we aim to explore an interpretable and quantitative analysis of factors related to wetland spatiotemporal variations on the Tibetan Plateau (TP). By combining SHapley Additive exPlanations with a spatially stratified heterogeneity model, we propose a locally explained stratified heterogeneity (LESH) model that well reveals the effects of multiple variable interactions on the spatiotemporal variations of wetlands. The results show that topographic variables are the most important variables related to the spatial distribution of wetlands on the TP, and climatic variables are the most relevant factors for the increase in the wetland area on the TP from 2015 to 2019. In addition, the interactions among multiple variables strongly influence wetlands on the TP. Among them, when other geographic variables interact with the evaporation variable, its explanatory power on wetland distribution is significantly increased. Knowledge of wetland distribution determinants can help us understand the evolution of wetlands and the impacts of climate change on wetland variations.