Key Predictor Research Articles

Machine learning provides insights for spatially explicit pest management strategies by integrating information on population connectivity and habitat use in a key agricultural pest.

Insect pests have garnered increasing interest because of anthropogenic global change, and their sustainable management requires knowledge of population habitat use and spread patterns. To enhance this knowledge for the prevalent tea pest Empoasca onukii, we utilized a random forest algorithm and a bivariate map to develop and integrate models of its habitat suitability and genetic connectivity across China. Our modeling revealed heterogeneous spatial patterns in suitability and connectivity despite the common key environmental predictor of isothermality. Analyses indicated that tea cultivation in areas surrounding the Tibetan Plateau and the southern tip of China may be at low risk of population outbreaks because of their predicted low suitability and connectivity. However, regions along the middle and lower reaches of the Yangtze River should consider the high abundance and high recolonization potential of E. onukii, and thus the importance of control measures. Our results also emphasized the need to prevent dispersal from outside regions in the areas north of the Yangtze River and highlighted the effectiveness of internal management efforts in southwestern China and along the southeastern coast. Further projections under future conditions suggested the potential for increased abundance and spread in regions north of the Yangtze River and the southern tip of China, and indicated the importance of long-term monitoring efforts in these areas. These findings highlighted the significance of combining information on habitat use and spread patterns for spatially explicit pest management planning. In addition, the approaches we used have potential applications in the management of other pest systems and the conservation of endangered biological resources. © 2024 Society of Chemical Industry.

Black Americans' Diminished Health Returns of Professional Occupations: A Thirty-Year Follow-Up Study of Middle-Aged and Older Adults.

Occupational classes exert substantial effects on both subjective and objective health outcomes. However, it remains unclear whether the health impact of similar occupational classes varies across racial groups among middle-aged and older adults in the United States. Grounded in the theory of Minorities' Diminished Returns (MDRs), which posits that health benefits from resources such as employment are systematically weaker for racial minority populations, particularly Non-Latino Black individuals, this study tested Black-White disparities in the effects of similar occupational classes on health outcomes in middle-aged and older adults. Utilizing data from the Health and Retirement Study (HRS), we employed a 30-year longitudinal design with a nationally representative sample of middle-aged and older adults in the United States. Six occupational classes-operator, managerial, professional specialty, sales, clerical/admin, and service-served as the key predictor variables (independent variables), with race as the moderator. Various health outcomes, including self-rated health, chronic disease, body mass index (BMI), activities of daily living (ADL), and cognitive function, were measured longitudinally from wave 1 to wave 15 (from baseline to 30 years later). Statistical analyses, incorporating logistic regression models, were conducted to assess associations between occupational class and health outcomes overall and based on race. Our analysis included 7538 Non-Latino White or Non-Latino Black participants followed for up to 30 years. Initial findings revealed positive health effects of professional occupations on cognitive function and self-rated health over 30 years of follow-uWe also identified significant interactions between race and professional occupational class on all health outcomes, indicating notable racial differences in the effects of professional occupations on health outcomes across domains. The effects of professional occupational class were weaker for Non-Latino Black individuals than for Non-Latino White individuals. Consistent with the Minorities' Diminished Returns theory, our findings indicated less pronounced positive effects of professional occupations on a wide range of health outcomes for Non-Latino Black individuals compared to Non-Latino Whites. These disparities emphasize the critical need to address structural factors that contribute to the diminished returns of prestigious occupations for Non-Latino Black populations.

The statistical and dynamic modeling of the first part of the 2013-2014 Euromaidan protests in Ukraine: The Revolution of Dignity and preceding times.

Ukraine's tug-of-war between Russia and the West has had significant and lasting consequences for the country. In 2013, Viktor Yanukovych, the Ukrainian president aligned with Russia, opted against signing an association agreement with the European Union. This agreement aimed to facilitate trade and travel between the EU and Ukraine. This decision sparked widespread protests that coalesced in Kyiv's Maidan Square, eventually becoming known as the Euromaidan protests. In this study, we analyze the protest data from 2013, sourced from Ukraine's Center for Social and Labor Research. Despite the dataset's limitations and occasional inconsistencies, we demonstrate the extraction of valuable insights and the construction of a descriptive model from such data. Our investigation reveals a pre-existing state of self-excitation within the system even before the onset of the Euromaidan protests. This self-excitation intensified during the Euromaidan protests. A statistical analysis indicates that the government's utilization of force correlates with increased future protests, exacerbating rather than quelling the protest movement. Furthermore, we introduce the implementation of Hawkes process models to comprehend the spatiotemporal dynamics of the protest activity. Our findings highlight that, while protest activities spread across the entire country, the driving force behind the dynamics of these protests was the level of activity in Kyiv. Furthermore, in contrast to prior research that emphasized geographical proximity as a key predictor of event propagation, our study illustrates that the political alignment among oblasts, which are the distinct municipalities comprising Ukraine, had a more profound impact than mere geographic distance. This underscores the significance of social and cultural factors in molding the trajectory of political movements.

The bidirectional longitudinal associations between fear of negative evaluation and suicidal ideation among Chinese adolescents: The mediating role of interpersonal needs factors

Based on previous theories and studies, fear of negative evaluation (FNE) may be a key predictor of suicidal ideation in adolescents. However, few studies examined the longitudinal relationships between FNE and suicidal ideation. This study aimed to explore the bidirectional longitudinal relationships between FNE and suicidal ideation. Meanwhile, based on the Interpersonal Theory of Suicide, this study would examine the longitudinal mediating role of interpersonal needs factors (thwarted belongingness and perceived burdensomeness) on the relationship between FNE and suicidal ideation.A sample of 515 adolescents (Mage = 12.309, SD = 0.807; 49.3 % girls) completed questionnaires on 4 waves, 6 months apart. The Random Intercept Cross-Lagged Panel Models (RI-CLPMs) were utilized to estimate the associations among study variables. The results showed that: (1) there was a significant bidirectional longitudinal relationship between FNE and suicidal ideation; (2) thwarted belongingness and perceived burdensomeness independently and serially mediated the relationship between FNE and suicidal ideation.This study contributed to understanding the complex relationship between FNE and suicidal ideation, emphasizing the critical roles of thwarted belongingness and perceived burdensomeness. The findings underscore the bidirectional nature of these associations and provide insights into the potential pathways involved in the development of suicidal ideation among adolescents.

The effects of resilience and basic personality traits on subjective well-being in elderly

The aim of this research was to examine the prediction of aspects of subjective well-being based on resilience and seven basic personality traits in users of gerontological centers, and the incremental contribution of basic personality traits in explaining adaptation to old age, beyond the variance explained by resilience. The sample consisted of 151 participants (54.3% female) with an average age of 80 years. Satisfaction with life, as cognitive indicator, and emotional distress (anxiety, depression, and stress) were used as indicators of subjective well-being. The results showed that resilience, neuroticism (in the negative direction) and positive valence predicted life satisfaction in the elderly. In predicting emotional distress, neuroticism stood out as a key predictor, while the significant contribution of resilience is dimnished by introducing personality traits into the model. The results provide a more complete picture of the relationships between resilience, personality traiits, and subjective well-being in a sample of the elderly in Serbia, and confirm the importance of studying these relationships from a developmental perspective.

#2379 Acute kidney injury as a key predictor of major adverse cardiovascular events in chronic kidney disease patients

Abstract Background and Aims Chronic kidney disease (CKD) significantly raises cardiovascular event risks. The influence of acute-on-chronic kidney incidents is less understood. This study examines the link between acute kidney injury (AKI) episodes and subsequent Major Adverse Cardiovascular Events (MACE) in CKD patients. Method From 2013 to 2016, the CKD-REIN cohort enrolled 3033 adults with CKD stages 3-5 (average age 67; 66% male; mean eGFR 33 mL/min/1.73m²) from 40 French outpatient nephrology clinics, reflecting national geographic and legal diversity. During a 5-year follow-up, all AKI episodes, whether inpatient or outpatient, were identified, confirmed, and categorized per KDIGO-AKI standards by an expert panel. Cardiovascular events were evaluated using clinical trial Cardiovascular and Stroke Endpoint Definitions. MACE cumulative incidences (myocardial infarction, stroke, heart failure hospitalization, cardiovascular death) post-AKI were calculated using Aalen-Johansen methods, accounting for kidney failure and death risks. The impact of the first AKI episode on MACE risk was analyzed using a multivariable Cox model, treating AKI as a time-variable and stratifying by characteristics (in/outpatient status, AKI stage, pre-renal causes, renal recovery at discharge). Factors like demographics, cardiovascular risks, CKD severity, and treatments were considered. Interaction and sensitivity analyses were performed, excluding those with prior AKI or cardiovascular disease. Results During a median follow-up of 5.2 years, 530 patients experienced an incident AKI episode. The cumulative incidence of MACE at 1 year following this initial episode of AKI was 8.1% [95% confidence interval, 6.1; 10.8], with a median time to occurrence of 6.7 months after AKI. After adjustment for multiple confounders, we observed a substantial increased hazard of MACE associated with a first episode of AKI (HR = 5.99 [4.63; 7.76], p < 0.001), and this association remained significant for each MACE component (Fig. 1A). A dose-response relationship was observed, with higher risks in more severe AKI cases (KDIGO grades 2-3) and among hospitalized versus non-hospitalized patients (Fig. 1B). This association was also observed across all subgroups, without any interaction with age, sex, nor major comorbidities (diabetes, history of AKI, or cardiovascular events), as well as in various sensitivity analyses. Overall, we estimated an attributable risk fraction of 18.1% [13.6; 22.4] for MACE associated with AKI episodes within this population. Conclusion Our study highlights a strong dose-response relationship between incident AKI events and the risk of subsequent major cardiovascular events in CKD patients. These findings suggest that AKI may not only be a marker of increased cardiovascular risk but also a potential mediator of this risk. From a clinical perspective, these results underscore the importance of close monitoring and management of AKI in CKD patients to reduce the risk of MACE. This study improves our understanding of the interplay between renal and cardiovascular health, emphasizing the need for integrated care approaches in this high-risk population.

Is Stimulated Thyroglobulin Before Radioiodine Therapy a Useful Tool in Predicting Response to Initial Therapy in Patients with Differentiated Thyroid Carcinoma?

Thyroglobulin (Tg) is an important tool to evaluate the persistence and recurrence risk in differentiated thyroid cancer (DTC). We aimed to evaluate the correlation between pre-radioiodine therapy stimulated Tg (pre-RAI Tg) levels and the first response to treatment evaluation, and to establish a cut-off pre-RAI Tg threshold for predicting an initial excellent response. Retrospective cohort study of DTC patients who underwent total thyroidectomy and radioiodine therapy. Response to therapy was evaluated 6 to 24 months after initial therapy, and patients were classified as: excellent response (ER); indeterminate response (IndR) and incomplete response (IncR). Total patients: 166 among which 85.5% female with mean age of 47.6 ± 13 years. The ER had a significantly lower pre-RAI Tg in comparison to IndR (p<0.001) and IncR (p<0.001), and pre-RAI Tg were different between the IndR and IncR (p=0.02). A cut-off pre-RAI Tg value at 7.55ng/ml was obtained by receiver operating characteristics curve for differentiating ER from IndR and IncR. The area under curve was 0.832 (95% CI 0.76-0.91). In multivariate analysis, ATA low-risk (RR 1.61, 95% CI 1.06-2.43, p=0.025) and Tg below 7.55ng/ml (RR 2.17, 95% CI 1.52-3.10, p<0.001) were associated with ER. After a median of 7.4-year follow-up, 124 (74.7%) patients were allocated into ER, 22 (13.2%) into IndR, and 20 (12%) into IncR. In conclusion, pre-RAI Tg predicts first evaluation of treatment response. Pre-RAI Tg cut-off was a key predictor of initial excellent response to therapy and may be an important tool in the follow-up of DTC patients.

Development and internal validation of machine-learning models for predicting survival in patients who underwent surgery for spinal metastases.

A retrospective study. This study aimed to develop machine-learning algorithms for predicting survival in patients who underwent surgery for spinal metastasis. This study develops machine-learning models to predict postoperative survival in spinal metastasis patients, filling the gaps of traditional prognostic systems. Utilizing data from 389 patients, the study highlights XGBoost and CatBoost algorithms̓ effectiveness for 90, 180, and 365-day survival predictions, with preoperative serum albumin as a key predictor. These models offer a promising approach for enhancing clinical decision-making and personalized patient care. A registry of patients who underwent surgery (instrumentation, decompression, or fusion) for spinal metastases between 2004 and 2018 was used. The outcome measure was survival at postoperative days 90, 180, and 365. Preoperative variables were used to develop machine-learning algorithms to predict survival chance in each period. The performance of the algorithms was measured using the area under the receiver operating characteristic curve (AUC). A total of 389 patients were identified, with 90-, 180-, and 365-day mortality rates of 18%, 41%, and 45% postoperatively, respectively. The XGBoost algorithm showed the best performance for predicting 180-day and 365-day survival (AUCs of 0.744 and 0.693, respectively). The CatBoost algorithm demonstrated the best performance for predicting 90-day survival (AUC of 0.758). Serum albumin had the highest positive correlation with survival after surgery. These machine-learning algorithms showed promising results in predicting survival in patients who underwent spinal palliative surgery for spinal metastasis, which may assist surgeons in choosing appropriate treatment and increasing awareness of mortality-related factors before surgery.

Can I Discharge This Adult Patient with Abnormal Vital Signs From the Emergency Department?

BackgroundVital signs are an essential component of the emergency department (ED) assessment. Vital sign abnormalities are associated with adverse events in the ED setting and may indicate a risk of poor outcomes after ED discharge. Clinical questionWhat is the risk of adverse events among adult patients with abnormal vital signs at the time of ED discharge? Evidence reviewStudies retrieved included 6 retrospective studies with adult patients discharged from the ED. These studies evaluated adverse outcomes in adult patients discharged from the ED with abnormal vital signs. Hypotension at discharge was associated with the highest odds of adverse events after discharge. Tachycardia was also a key predictor of adverse events after discharge and may be easily missed by ED clinicians. ConclusionBased on the available evidence, the specific vital sign abnormality and the number of total abnormalities influence the risk of adverse outcomes after discharge. Vital sign abnormalities at the time of discharge also increase the risk of ED revisit. The most common abnormal vital sign at the time of discharge is tachycardia.

Arterial Stiffness Is an Important Predictor of Heart Failure with Preserved Ejection Fraction (HFpEF)—The Effects of Phosphate Retention

Heart failure with preserved ejection fraction (HFpEF) is a major health concern. There is a growing recognition of the causal interplay between arterial stiffness and HFpEF. We recently reported that phosphate retention is a trigger for arterial stiffness. This study focuses on whether arterial stiffness due to phosphate retention could be a predictor for HFpEF. Methods: The subjects of this study were 158 patients (68 males and 90 females, mean age 74.8 ± 11.2). HFpEF was defined according to the guidelines of the ESC 2019. Pulse wave velocity (PWV) and central systolic blood pressure (CSBP) were used as markers for arterial stiffness and afterload, respectively. We measured serum levels of fibroblast growth factor 23 (FGF23) as a marker of phosphate retention. Results: The serum levels of FGF23 had a significant relationship with PWV. PWV had significant relationships with LV mass index, plasma BNP levels, and relative wall thickness, e′, and E/e′ (p &lt; 0.001, respectively). Multivariate logistic regression analysis revealed that higher PWV values and hypertension were significant predictors for the dependent factor (HFpEF). Arterial stiffness amplified afterload, leading to LV concentric hypertrophy and diastolic dysfunction. This study presents that arterial stiffness is a key predictor of HFpEF, and that phosphate retention is involved in the pathology of HFpEF.

Dispersal restriction and facilitation in species with differing tolerance to development: A landscape genetics study of native and introduced lizards

AbstractAimThe development of natural habitats into urban land uses has greatly accelerated in the recent past due to human activities. This habitat development disrupts species' natural dispersal processes and can lead to both direct and indirect impacts on dispersal. Whether human activities result in restricted or facilitated dispersal may depend on a species' development tolerance; however, this premise has not been tested. We examined the impact of urbanization and road networks on the dispersal of three lizard species in the context of their development tolerance.LocationCuraçao.MethodsTo quantify species' development tolerance, we modelled three lizard species abundances at sites based on surrounding landscape development. Using microsatellite genotypes, we conducted individual‐based resistance surface analyses and modelled the effect of habitat development on genetic admixture to assess indirect dispersal restriction and facilitation. We explored direct facilitation of dispersal using network analysis of mitochondrial haplotypes.ResultsPhyllodactylus martini, a native gecko species, was the least tolerant of development and experienced indirect dispersal restriction due to roads, according to resistance surface analyses. Anolis lineatus, a native anole species, exhibited a neutral relationship with development. Resistance surfaces and Structure analyses showed that A. lineatus faced indirect dispersal restrictions from roads and developed areas, while mitochondrial haplotype networks suggested they benefited from occasional human‐facilitated long‐distance dispersal events. Hemidactylus mabouia, an introduced gecko species, was the most tolerant of development, and experienced no dispersal restriction, but mitochondrial haplotypes suggest direct long‐distance dispersal facilitation.Main ConclusionsOur findings highlight development tolerance as a key predictor of dispersal impact for these species and future work should test whether these patterns are upheld in other systems. Understanding how human activities affect species' dispersal will aid in managing introduced species while promoting connectivity for native species navigating dispersal challenges in dynamic landscapes.

Current Perceptions of Virtual Reality Technology

User experience is a key predictor of future use of goods and services. The presented study collected a combination of qualitative and quantitative data from both experienced users and novices about their perceptions of virtual reality (VR) equipment, any concerns surrounding the data collected by the equipment, and facets that needed to be taken into consideration for future developments. The purpose of this research was to understand the current user experience of VR and ways in which it can be improved. The findings indicated that the majority of people have used VR, albeit infrequently, and that the most common use for it was for entertainment purposes. The most important characteristics of VR systems were judged to be the available content and price. While it was reported to be enjoyable to use, the ways in which it was suggested to be improved were through a reduction in size and weight of the headsets, and incorporating wireless capabilities. Concerns about the use of VR were the potential for sickness, discomfort, and eye strain, the disconnect from the real world and the subsequent risks that this poses, as well as the use and privacy of user data. The findings from this research can be used as a stepping stone toward the advancement of VR technologies.

Comparison of Cardiorespiratory Fitness Prediction Equations and Generation of New Predictive Model for Patients with Obesity.

Cardiorespiratory fitness (CRF) is a critical marker of overall health and a key predictor of morbidity and mortality, but the existing prediction equations for CRF are primarily derived from general populations and may not be suitable for patients with obesity. Predicted CRF from different non-exercise prediction equations was compared with measured CRF of patients with obesity who underwent maximal cardiopulmonary exercise testing (CPET). Multiple linear regression was used to develop a population-specific nonexercise CRF prediction model for treadmill exercise including age, sex, weight, height, and physical activity level as determinants. Six hundred sixty patients underwent CPET during the study period. Within the entire cohort, R2 values had a range of 0.24 to 0.46. Predicted CRF was statistically different from measured CRF for 19 of the 21 included equations. Only 50% of patients were correctly classified into the measured CRF categories according to predicted CRF. A multiple model for CRF prediction (mL·min -1 ) was generated ( R2 = 0.78) and validated using two cross-validation methods. Most used equations provide inaccurate estimates of CRF in patients with obesity, particularly in cases of severe obesity and low CRF. Therefore, a new prediction equation was developed and validated specifically for patients with obesity, offering a more precise tool for clinical CPET interpretation and risk stratification in this population.

Political Skill of B to B Sales Team as a Dynamic Capability: A Strategic Resource Perspective

ABSTRACT Purpose To identify the key internal and external collective conditions and determinants for sales managers in the B to B context, which would allow the articulation of Team Political Skill as a firm’s dynamic capability at organizational and strategical level. Methodology/approach This study employs qualitative methods based on grounded theory, with an exploratory discovery, which jointly used in-depth interviews and online focus groups targeting sales management positions (Sales managers, sales supervisors) and CEOs of 24 B to B different firms in Chile and Peru. Findings The study reports that the political skill of B to B sales teams is articulated as a dynamic capacity when it is capable of generating organizational co-creation routines and an identification culture based on innovation, which translates into intrafirm collaborative organizational learning, strengthening its strategic intelligence, customer orientation and providing a distinctive and differentiating seal in the market at organizational level. Research implications This research suggests from the perspective of resource-based theory that B to B salespeople team political skills not only is a tactical resource to achieve sales results but also becomes an active differentiator of high strategic value for B to B firms in their organizational performance. Therefore, the sales team acts as a key predictor of higher social effectiveness and work performance. Additionally, this study highlights the pivotal role of the sales supervision role and competitive environment in the evolution of individual salespersons’ political skills toward group consolidation. Practical implications The current work offers initial strategies regarding for B to B sales managers can establish political skill development plans in their salespeople and to incorporate innovative supervision and supporting mechanisms that bolster the B to B sales team as a strategic resource in an ever-increasing competitive and complex environment, as seen in the recent post pandemic environment. Originality/value/contribution of the paper To identify unexplored dimensions and collaborative processes in B to B salespersons’ individual and collective team political skills and how these potentially consolidate themselves as a distinctive firm’s dynamic capability in their sales performance.

Phylogenomics-driven host test list selection for weed biological control

A concern in weed biological control research is the potential for candidate biocontrol agents to impact not only the target weed but also native or economically important flora. The degree of evolutionary relatedness between the target weed species and a non-target species is a key predictor of the susceptibility of the non-target to the biocontrol agent. To manage this risk, biocontrol practitioners need to understand the phylogenetic position of the host weed relative to non-target plant species. However, comprehensively sampled phylogenetic trees are often unavailable, with incomplete information scattered across multiple publications. Further, older published phylogenies based on Sanger sequence data often lack branch resolution and support, which increases uncertainty in biocontrol decision making. Decreasing sequencing cost and technological advances have led to phylogenomic approaches being more widely used to understand evolutionary relationships between species. For example, target capture sequencing methods using bait kits such as Angiosperms353 enable cost-effective and timely phylogenomic-level analysis of flowering plant groups at different scales. Here, we introduce a workflow to embed a comprehensive understanding of evolutionary relationships into the efficient development of host test lists in weed biological control. We demonstrate the effectiveness of the workflow through a case study on the major crop weed flaxleaf fleabane (Erigeron bonariensis). Phylogenomic analysis was conducted on 280 species of the tribe Astereae (family Asteraceae) occurring in Australia and New Zealand, clarifying relationships between the target species and related clades of native and non-native Astereae. We consider the phylogenetic tree in the context of a previously proposed host test list and discuss taxonomic implications, highlighting avenues of future molecular-based work to uncover the origin of Australian fleabanes. This study provides a workflow and demonstrates the practical application of target sequence capture for phylogenomic inference to support risk analysis and decision making in classical weed biological control.

Predicting hematoma expansion using machine learning: An exploratory analysis of the ATACH 2 trial

IntroductionHematoma expansion (HE) in patients with intracerebral hemorrhage (ICH) is a key predictor of poor prognosis and potentially amenable to treatment. This study aimed to build a classification model to predict HE in patients with ICH using deep learning algorithms without using advanced radiological features. MethodsData from the ATACH-2 trial (Antihypertensive Treatment of Acute Cerebral Hemorrhage) was utilized. Variables included in the models were chosen as per literature consensus on salient variables associated with HE. HE was defined as increase in either >33% or 6 mL in hematoma volume in the first 24 h. Multiple machine learning algorithms were employed using iterative feature selection and outcome balancing methods. 70% of patients were used for training and 30% for internal validation. We compared the ML models to a logistic regression model and calculated AUC, accuracy, sensitivity and specificity for the internal validation models respective models. ResultsAmong 1000 patients included in the ATACH-2 trial, 924 had the complete parameters which were included in the analytical cohort. The median [interquartile range (IQR)] initial hematoma volume was 9.93.mm3 [5.03–18.17] and 25.2% had HE. The best performing model across all feature selection groups and sampling cohorts was using an artificial neural network (ANN) for HE in the testing cohort with AUC 0.702 [95% CI, 0.631–0.774] with 8 hidden layer nodes The traditional logistic regression yielded AUC 0.658 [95% CI, 0.641–0.675]. All other models performed with less accuracy and lower AUC. Initial hematoma volume, time to initial CT head, and initial SBP emerged as most relevant variables across all best performing models. ConclusionWe developed multiple ML algorithms to predict HE with the ANN classifying the best without advanced radiographic features, although the AUC was only modestly better than other models. A larger, more heterogenous dataset is needed to further build and better generalize the models.

Diet choices determine mercury exposure risks for people living in gold mining regions of Peru

Artisanal and small-scale gold mining (ASGM) is the largest global anthropogenic mercury (Hg) source and is widespread in the Peruvian Amazon. Consuming Hg-laden foods exposes people to this potent neurotoxin. While numerous studies have examined fish Hg content near ASGM, Hg accumulation in other commonly consumed animal-and plant-based foods from terrestrial environments is often overlooked. In this study, we aim to address understudied dietary Hg exposures.To understand Hg exposure from food staples in the Peruvian Amazon, we measured total and methyl Hg in local crops, fish, chicken meat, chicken feathers, and eggs from ASGM-impacted and upstream (reference) communities. Diet surveys were used to estimate probable weekly Hg intake from each food. Fish and chicken stable carbon and nitrogen isotope signatures were analyzed to evaluate trophic magnification.Though few crops exceeded food safety recommendations, rice methyl Hg proportions were high (84%). Trophic level was an expected key predictor of fish Hg content. 81% (17 of 21) of local carnivorous fish exceeded WHO and EPA recommendations. Compared to upstream communities, mining-impacted communities demonstrated elevated total Hg in crops (1.55 (interquartile ranges (IQR): 0.60–3.03) μg kg−1 upstream versus 3.38 (IQR: 1.62–11.58) in mining areas), chicken meats (2.69 (IQR: BDL–9.96) μg kg−1 versus 19.68 (IQR: 6.33–48.1)), and feathers (91.20 (IQR: 39.19–216.13) μg kg−1 versus 329.99 (IQR: 173.22–464.99)). Chicken meats from mining areas exhibited over double the methyl Hg concentrations of those upstream. Methyl Hg fractions in chicken muscle tissue averaged 93%. Egg whites and livers exceeded Hg recommendations most frequently. Proximity to mining, but not trophic position, was a predictor of chicken Hg content.Our results demonstrate that terrestrial and aquatic foods can accumulate Hg from mining activity, introducing additional human Hg exposure routes. However, locally sourced carnivorous fish was the largest contributor to an estimated three-fold exceedance of the provisional tolerable weekly Hg intake.

Mechanical and electrical uncoupling: the role of cardiac magnetic resonance imaging in arrhythmogenic cardiomyopathy proof of concept

Abstract Funding Acknowledgements None. Introduction Arrhythmogenic Cardiomyopathy (ACM) has a high risk of sudden cardiac death, especially under 60 years old (1:5,000 prevalence). ACM involves the replacement of normal heart tissue with fibro-adipose tissue in specific areas of the right ventricle (RV). Cardiac Magnetic Resonance Imaging (CMR) is vital for ACM stratification and prognosis, focusing on RV volume and ejection fraction. Simulations suggest that ACM's abnormal deformation patterns are primarily due to mechanical changes like reduced contractility and increased stiffness, rather than electrical issues. Ventriculo-arterial coupling (VAC) is a valuable metric for assessing RV efficiency, with the TAPSE/sPAP index reflecting the RV's length-force relationship. CMR assists in ACM stratification and prognosis, with VAC potentially serving as a key predictor of outcomes based on mechanical and structural abnormalities identified through CMR. Purpose Examine and establish a relationship between mechanical uncoupling, ventricular arrhythmias, and findings from CMR in patients with ACM. Methods We examined 25 ACM patients (median age 34, 72% men) using the 2019 Modified Task Force and Padua criteria. We investigated two key factors in ACM: Right ventricular-arterial coupling (TAPSE/SPAP ratio) and clinically relevant ventricular tachycardia (requiring cardioversion). We compared clinical, ECG, and imaging data (transthoracic echocardiogram and CMR as the gold standard). We used Spearman rank tests for correlations, Fisher exact tests for nominal characteristics, and Mann-Whitney-U tests for group comparisons. In predefined regression models involving left ventricular ejection fraction (LVEF) and right ventricular ejection fraction (RVEF) function with VAC, we used flexible nonparametric regressions. A p-value &amp;lt;0.05 was considered statistically significant. The analysis was conducted using SPSSv22 and SAS-University-Edition. Results A positive association of VAC with LVEF (ρ=0.472, p=0.023), RVEF (ρ=0.522, p=0.038) and RV indexed stroke volume (ρ=0.79, p&amp;lt;0.001) was found. Low-rank regression splines showed a mainly positive association of LVEF (df=3 F=20.75 p&amp;lt;0.001), RVEF (df=4 F=24.34 p&amp;lt;0.001) and the RV indexed stroke volume, a positive linear association (df=1 F=31.67 p&amp;lt;0.001). In comparison with patients without crVT, those with crVT had a positive correlation with RV shortening, reduced RVEF (39.6 vs. 32.2%. p=0.025), higher LV mass (38.99 vs. 45.55, p=0.045), and LV end-diastolic volume (LVEDV) (56.99 vs. 68.15 ml/m2, p=0.045) by echocardiogram and CMR respectively; notwithstanding positive associations for VAC were seen with LVEDV (p=0.039), LV mass (p=0.039); and negative with RVEF by CMR (p=0.023), and RV shortening by echo (p=0.026). Conclusions We found that right VAC by echo correlates with RV and LV EF by CMR and RV stroke volume in patients with ACM. RVEF, LV mass, and end-diastolic volume correlate with clinically relevant arrhythmias.

Cardiovascular Outcomes in Hypertension-Treated Patients With Peripheral Artery Disease: The VALUE Trial.

Systolic blood pressure (BP) is a key predictor of cardiovascular events, but patients with peripheral artery disease (PAD) are rarely included in hypertension trials. The VALUE trial (Valsartan Antihypertensive Long-Term Use Evaluation) investigated the long-term effects of valsartan- or amlodipine-based treatments on cardiovascular outcomes in patients with hypertension with a high cardiovascular risk. The aim of this subanalysis was to clarify the relationship between achieved BP on treatment and cardiovascular outcomes in patients with hypertension with PAD. Patients were followed for 4 to 6 years, and BP was measured regularly. The primary end point was time to the first major adverse cardiovascular event, including myocardial infarction, stroke, cardiovascular death, and heart failure requiring hospitalization. Statistical analyses were performed using Cox regression, adjusting for various baseline covariates. Of the 13 803 participants, 1898 (13.8%) had PAD. During a median follow-up of 4.5 years, patients with PAD had a 23% increased risk of major adverse cardiovascular events compared with patients without PAD. Patients with an achieved systolic BP <130 mm Hg and 130 to 139 mm Hg, compared with those with systolic BP ≥140 mm Hg, were associated with a decreased risk of a major adverse cardiovascular event (hazard ratio, 0.65 [95% CI, 0.43-0.97]; P=0.037; 0.85 [95% CI, 0.74-0.97]; P=0.016, respectively). Additionally, systolic BP <130 mm Hg was associated with a decreased risk of cardiovascular death (hazard ratio, 0.33 [95% CI, 0.12-0.92]; P=0.034). The incidence of the primary outcome did not differ between antihypertensive treatment regimens (P=0.365). Our results indicate that more intensive BP control is associated with a reduction in cardiovascular morbidity and mortality in patients with hypertensive PAD.

Maternal metabolic conditions as predictors of breastfeeding outcomes: Insights from an Australian cohort study.

Breastfeeding represents an important opportunity to optimize health outcomes for both mother and infant, particularly in the context of maternal metabolic conditions such as diabetes and polycystic ovary syndrome. However, evidence suggests that women affected by these conditions breastfeed at reduced rates and durations. Our aim was to use the large, prospective, community-based Australian Longitudinal Study on Women's Health (ALSWH) to conduct an in-depth exploratory analysis of breastfeeding outcomes in Australian women affected by key maternal metabolic conditions. Data from 12 920 pregnancies to 5605 women from the 1973-1978 birth cohort of the ALSWH were examined. Univariable and multivariable regression using generalized estimating equation models were applied to assess breastfeeding initiation and duration (outcome measures) in relation to key self-reported maternal metabolic diagnoses (pre-gestational type 1 and type 2 diabetes, gestational diabetes, and polycystic ovary syndrome; main explanatory variables). Key sociodemographic and clinical covariates were also considered. Results showed no significant association between specific maternal metabolic diagnoses (pre-gestational or gestational diabetes, or polycystic ovary syndrome) and breastfeeding outcomes. However, maternal body mass index emerged as a key predictor of suboptimal breastfeeding outcomes. Pregnancies affected by maternal obesity were associated with a 2.1-fold increase in the odds of not initiating breastfeeding, after adjusting for other key variables (95% CI 1.67 to 2.60, p < 0.01). Maternal overweight and obesity were, respectively, associated with an adjusted 1.4-fold (95% CI 1.20 to 1.55, p < 0.01) and 1.8-fold increase (95% CI 1.60 to 2.10, p < 0.01) in the odds of a breastfeeding duration less than 6 months. Maternal obesity, rather than any specific maternal metabolic condition, appears to be a key predictor of breastfeeding outcomes in Australian women.