Search Results (862)

Aims: Sinus tachycardia after heart transplantation (HTX) due to cardiac graft denervation is associated with reduced post-transplant survival and requires adequate treatment. We analyzed the long-term effects of heart rate control with ivabradine or metoprolol succinate in HTX recipients. Methods: This observational retrospective single-center study analyzed the ten-year results of 110 patients receiving ivabradine (n = 54) or metoprolol succinate (n = 56) after HTX. Analysis included comparison of demographics, medications, heart rates, blood pressure values, echocardiographic features, cardiac catheterization data, cardiac biomarkers, and post-transplant survival including causes of death. Results: Both groups showed no significant differences concerning demographics or medications (except for ivabradine and metoprolol succinate). At 10-year follow-up, HTX recipients with ivabradine showed a significantly lower heart rate (72.7 ± 8.5 bpm) compared to baseline (88.8 ± 7.6 bpm; p < 0.001) and to metoprolol succinate (80.1 ± 8.1 bpm; p < 0.001), a significantly lower NT-proBNP level (588.4 ± 461.4 pg/mL) compared to baseline (3849.7 ± 1960.0 pg/mL; p < 0.001) and to metoprolol succinate (1229.0 ± 1098.6 pg/mL; p = 0.005), a significantly lower overall mortality (20.4% versus 46.4%; p = 0.004), and mortality due to graft failure (1.9% versus 21.4%; p = 0.001). Multivariate analysis showed a significantly decreased risk of death within 10 years after HTX in patients with post-transplant use of ivabradine (HR 0.374, CI 0.182–0.770; p = 0.008). Conclusions: In this single-center trial, patients with ivabradine revealed a significantly more pronounced heart rate reduction, a lower NT-proBNP level, and a superior 10-year survival after HTX. Full article

Background: The education process for newly diagnosed Type 1 diabetes mellitus (T1D) patients and their families, primarily led by diabetes specialist nurses, is essential for gaining knowledge about the disease and its management. However, few assessment tools have been employed to evaluate long-term knowledge retention among T1D patients years after diagnosis. Methods: We developed a 20-question test to assess the knowledge of patients and their families at the conclusion of the initial education process and again 6–12 months later. Demographic and clinical data were also collected. Statistical analyses included comparisons between the first and second test results, as well as evaluation of potential contributing factors. The internal consistency and construct validity of the questionnaire were evaluated. Results: Forty-four patients completed both assessments, with a median interval of 11.5 months between them. The average score on the first test was 88.6, which declined to 82.7 on the second assessment (p < 0.001). In univariate analysis, factors positively associated with higher scores included Jewish ethnicity, lower HbA1c levels, and shorter hospitalization duration. Multivariate analysis revealed that parents had lower odds of experiencing a significant score decline compared to patients. Cronbach’s alpha was 0.69, and Principal Component Analysis (PCA) identified eight components accounting for 67.1% of the total variance. Conclusions: Healthcare providers should consider offering re-education to patients and their families approximately one year after diagnosis, with particular attention to high-risk populations during the initial education phase. Further studies are needed to examine this tool’s performance in larger cohorts. Full article

Background/Objectives: Pulmonary embolism (PE) remains a major cause of morbidity and mortality. Despite advances in care, its nonspecific symptoms pose diagnostic and therapeutic challenges. Emerging evidence suggests sex-based differences in PE presentation, management, and outcomes, yet real-world data from European settings remain scarce. This study aimed to investigate sex differences in clinical presentation, diagnostic workup, therapeutic interventions, and outcomes among hospitalized PE patients. Methods: We conducted a retrospective cohort study including all adult patients (≥18 years) admitted with a main diagnosis of acute PE at the Cantonal Hospital Baselland between January 2018 and December 2020. Data were extracted from electronic medical records and included demographics, comorbidities, symptoms, diagnostics, treatments, and outcomes. Sex-based comparisons were performed using univariate analyses. Results: Among 197 patients, 54% were women. Compared to men, women were more often admitted by ambulance (42% n = 45 vs. 24% n = 22, p = 0.009), had more frequent tachycardia (38% n = 41 vs. 23% n = 21, p = 0.024), and received lysis therapy more often (10% n = 11 vs. 2% n = 2, p = 0.023). DVT was more frequently diagnosed in women when sonography was performed (82% n = 49 vs. 64% n = 34, p = 0.035). Men had higher rates of B symptoms, smoking, and family history of PE. Women had longer hospital stays and were more frequently discharged to rehabilitation facilities. No sex differences were found in in-hospital mortality, 6-month rehospitalization, or adherence to diagnostic guidelines. Conclusions: This study reveals sex-based differences in PE presentation and management, suggesting potential disparities in care pathways. Further research is needed to promote equitable, personalized treatment strategies. Full article

Background: Wearable movement sensors can measure upper limb (UL) activity, but single variables may not capture the full picture. This study aimed to replicate prior work identifying five multivariate categories of UL activity performance in people with stroke and controls and expand those findings to other UL conditions. Methods: Demographic, self-report, and wearable sensor-based UL activity performance variables were collected from 324 participants (stroke n = 49, multiple sclerosis n = 19, distal UL fracture n = 40, proximal UL pain n = 55, post-breast cancer n = 23, control n = 138). Principal component (PC) analyses (12, 9, 7, or 5 accelerometry input variables) were followed by cluster analyses and numerous assessments of model fit across multiple subsets of the total sample. Results: Two PCs explained 70–90% variance: PC1 (overall UL activity performance) and PC2 (preferred-limb use). A five-variable, five-cluster model was optimal across samples. In comparison to clusters, two PCs and individual accelerometry variables showed higher convergent validity with self-report outcomes of UL activity performance and disability. Conclusions: A five-variable, five-cluster model was replicable and generalizable. Convergent validity data suggest that UL activity performance in daily life may be better conceptualized on a continuum, rather than categorically. These findings highlight a unified, data-driven approach to tracking functional changes across UL conditions and severity of functional deficits. Full article

Background and Objectives: This study aimed to compare the effects of HIPEC procedures using oxaliplatin and mitomycin C on serum electrolyte, glucose, and lactate levels, with a specific focus on the carrier solutions employed. Materials and Methods: A retrospective analysis was performed on 82 patients who underwent cytoreductive surgery and hyperthermic intraperitoneal chemotherapy (HIPEC) for colorectal peritoneal metastases. Patients were assigned to one of two groups based on the chemotherapeutic agent used: oxaliplatin (n = 63) or mitomycin C (MMC, n = 19). The oxaliplatin group was further subdivided based on the carrier solution used: 5% dextrose (D5W, n = 29) or peritoneal dialysate (n = 34). The assignment of regimens was based on institutional protocols and surgeon preference. Pre- and post-HIPEC serum levels of sodium, potassium, bicarbonate, glucose, and lactate were compared. Results: Significant biochemical changes were observed across groups, depending on both the chemotherapeutic agent and carrier solution. In the MMC group (peritoneal dialysate), only lactate increased significantly post-HIPEC (p = 0.001). In the oxaliplatin–peritoneal dialysate group, significant changes were observed in bicarbonate (p = 0.009), glucose (p = 0.001), and lactate (p < 0.001), whereas sodium and potassium remained stable. The oxaliplatin–D5W group showed significant changes in all parameters: sodium (p = 0.001), potassium (p = 0.001), bicarbonate (p = 0.001), glucose (p < 0.001), and lactate (2.4 → 7.6 mmol/L, p < 0.001). Between-group comparisons revealed significant differences in sodium, potassium, glucose, and lactate changes (p < 0.05), but not in bicarbonate (p = 0.099). Demographic and clinical characteristics—including age, sex, primary disease, ICU stay, and 90-day mortality were similar across groups. Conclusions: The use of dextrose-containing solutions with oxaliplatin was associated with marked metabolic disturbances, including clinically meaningful hyponatremia, hypokalemia, and hyperglycemia in the early postoperative period. These findings suggest that the choice of carrier solution is as important as the chemotherapeutic agent in terms of perioperative safety. Closer postoperative electrolyte monitoring is recommended when using dextrose-based regimens. The retrospective design and sample size imbalance between groups are acknowledged limitations. Nonetheless, this study offers clinically relevant insights and lays the groundwork for future prospective research. Full article

Background/Objectives: The COVID-19 pandemic disrupted global cancer care. This study compared gastric cancer surgical outcomes before and during the pandemic in Turkey. We also aimed to analyze the impact of the pandemic and factors on survival and mortality in gastric cancer patients. Materials and Methods: This retrospective, multicenter cohort study included 324 patients from three tertiary centers in Turkey who underwent gastric cancer surgery between January 2018 and December 2022. Patients were stratified into Pre-COVID-19 (n = 150) and COVID-19 Era (n = 174) groups. Comprehensive demographic, surgical, pathological, and survival data were analyzed. To identify factors independently associated with postoperative mortality, a multivariable logistic regression model was applied. For evaluating predictors of long-term survival, multivariable Cox proportional hazards regression analysis was conducted. Results: The median time from diagnosis to surgery was comparable between groups, while the time from surgery to pathology report was significantly prolonged during the pandemic (p = 0.012). Laparoscopic surgery (p = 0.040) and near-total gastrectomy (p = 0.025) were more frequently performed in the Pre-COVID-19 group. Although survival rates between groups were similar (p = 0.964), follow-up duration was significantly shorter in the COVID-19 Era (p < 0.001). Comparison between survivor and non-survivor groups showed that several variables were significantly associated with mortality, including larger tumor size (p < 0.001), greater number of metastatic lymph nodes (p < 0.001), elevated preoperative CEA (p = 0.001), CA 19-9 (p < 0.001), poor tumor differentiation (p = 0.002), signet ring cell histology (p = 0.003), lymphovascular invasion (p < 0.001), and perineural invasion (p < 0.001). Multivariable logistic regression identified total gastrectomy (OR: 2.14), T4 tumor stage (OR: 2.93), N3 nodal status (OR: 2.87), and lymphovascular invasion (OR: 2.87) as independent predictors of postoperative mortality. Cox regression analysis revealed that combined tumor location (HR: 1.73), total gastrectomy (HR: 1.56), lymphovascular invasion (HR: 2.63), T4 tumor stage (HR: 1.93), N3 nodal status (HR: 1.71), and distant metastasis (HR: 1.74) were independently associated with decreased overall survival. Conclusions: Although gastric cancer surgery continued during the COVID-19 pandemic, some delays in pathology reporting were observed; however, these did not significantly affect the timing of adjuvant therapy or patient outcomes. Importantly, pandemic timing was not identified as an independent risk factor for mortality in multivariable logistic regression analysis, nor for survival in multivariable Cox regression analysis. Instead, tumor burden and aggressiveness—specifically advanced stage, lymphovascular invasion, and total gastrectomy—remained the primary independent determinants of poor prognosis. While pandemic-related workflow delays occurred, institutional adaptability preserved oncologic outcomes. Full article

Introduction: Traumatic brain injury (TBI) is a leading cause of morbidity worldwide, with the Glasgow Coma Scale (GCS) serving as a tool to measure injury severity. This study aimed to investigate the relationship between GCS admission scores and various socio-demographic, clinical, injury-related, and hospital-related variables in patients with TBI across two tertiary care centers in Eastern Europe, a region that remains underrepresented in the literature. Methods: A retrospective observational study was conducted using data from 119 TBI patients admitted between March 2020 and June 2023 at Cluj County Emergency Hospital (Romania) and Saint Vincent Hospital (Poland). GCS scores were analyzed as both categorical and continuous variables. Statistical analyses included Wilcoxon and Kruskal–Wallis tests for group comparisons and Spearman correlations for continuous variables. Results: Most patients included suffered a mild TBI (GCS score between 13 and 15). There were significant associations between GCS scores and post-traumatic amnesia (p < 0.05), discharge status (p < 0.01), discharge destination (p < 0.01), and education level (p < 0.01). GCS scores at admission were linked to survival, absence of post-traumatic amnesia, higher education levels, and home discharge. No significant differences observed across sex, residence, employment status, injury type, cause, or mechanism of injury. A weak but significant negative correlation was observed between GCS and length of hospital stay (rho = −0.229, p > 0.05), while age showed a non-significant correlation. Conclusions: The GCS score at admission is significantly associated with various clinical and socio-demographic outcomes in TBI patients, supporting the utility of the GCS score as a prognostic tool. The predominance of mild cases and the absence of radiological data, such as cerebral contusions or epidural or subdural hematomas, limit the generalizability of the findings. Further studies with larger samples and comprehensive imaging data are necessary to validate these findings. Full article

This study employs a machine learning approach to identify a small-molecule-based signature capable of predicting Alzheimer’s disease (AD). Utilizing metabolomics data from the plasma of a well-characterized cohort of 94 AD patients and 62 healthy controls; metabolite levels were assessed using the Biocrates MxP^® Quant 500 platform. Data preprocessing involved removing low-quality samples, selecting relevant biochemical groups, and normalizing metabolite data based on demographic variables such as age, sex, and fasting time. Linear regression models were used to identify concomitant parameters that consisted of the data for a given metabolite within each of the biochemical families that were considered. Detection of these “concomitant” metabolites facilitates normalization and allows sample comparison. Residual analysis revealed distinct metabolite profiles between AD patients and controls across groups, such as amino acid-related compounds, bile acids, biogenic amines, indoles, carboxylic acids, and fatty acids. Correlation heatmaps illustrated significant interdependencies, highlighting specific molecules like carnosine, 5-aminovaleric acid (5-AVA), cholic acid (CA), and indoxyl sulfate (Ind-SO₄) as promising indicators. Linear Discriminant Analysis (LDA), validated using Leave-One-Out Cross-Validation, demonstrated that combinations of four or five molecules could classify AD with accuracy exceeding 75%, sensitivity up to 80%, and specificity around 79%. Notably, optimal combinations integrated metabolites with both a tendency to increase and a tendency to decrease in AD. A multivariate strategy consistently identified included 5-AVA, carnosine, CA, and hypoxanthine as having predictive potential. Overall, this study supports the utility of combining data of plasma small molecules as predictors for AD, offering a novel diagnostic tool and paving the way for advancements in personalized medicine. Full article

Background: Sarcopenia significantly affects the health and quality of life in older adults. Exercise combined with nutritional interventions is widely recognized as an effective strategy for improving sarcopenia outcomes. However, current studies rarely focus on differential effects across subpopulations with distinct demographic and health characteristics. This study aimed to explore the effects of combined exercise and nutrition interventions on sarcopenia-related outcomes, considering the variations in population characteristics. Methods: A systematic search was conducted across PubMed, Embase, the Web of Science, and Cochrane Library, covering the literature published between January 2010 and March 2025. Only randomized controlled trials (RCTs) evaluating combined exercise and nutritional interventions for sarcopenia were included. The primary outcomes were handgrip strength (HS), the skeletal muscle mass index (SMI), gait speed (GS), and the five-times sit-to-stand test (5STS). The mean differences (MD) with 95% confidence intervals (CIs) were calculated. Random-effects models were used for the meta-analysis and subgroup comparisons. Results: Fifteen RCTs involving 1258 participants in the intervention group and 1233 in the control group were included. Exercise combined with nutritional interventions significantly improved sarcopenia-related outcomes. HS improved with a pooled MD of 1.77 kg (95% CI: 0.51 to 3.03, p = 0.006); SMI increased by 0.22 kg/m² (95% CI: 0.09 to 0.35, p = 0.0007); GS improved by 0.09 m/s (95% CI: 0.04 to 0.14, p = 0.0002); and 5STS performance improved with a time reduction of −1.38 s (95% CI: −2.47 to −0.28, p = 0.01). Subgroup analyses indicated that the intervention effects varied according to age, BMI, and living environment. Conclusions: Exercise combined with nutrition is effective in improving key outcomes associated with sarcopenia in older adults. The magnitude of these effects differed across population subgroups, underscoring the importance of tailoring interventions to specific demographic and health profiles. Full article

Background: Neuroendocrine tumors (NETs) remain a problematic area in endocrine oncology due to their non-specific symptoms and lack of reliable biomarkers. Visfatin/eNAMPT’s involvement in tumorigenesis has been described in several malignancies. In NETs, NAMPT inhibition was explored as a potential therapeutic option; however, serum visfatin and its role as a biomarker have not been studied. Objectives: We aimed to measure serum visfatin concentrations in NETs and evaluate visfatin’s potential as a diagnostic biomarker. Methods: We conducted a single-center, cross-sectional study of 77 patients with NETs (33 pancreatic and 44 small intestinal) and 29 controls. Patient demographics, tumor characteristics, and clinical data were analyzed, and serum visfatin levels were measured using ELISA. Statistical analyses were performed in Python, including Mann–Whitney U and Kruskal–Wallis tests, Spearman’s correlation, multiple linear regression, and ROC curve analysis. Results: Serum visfatin was higher in NETs compared to controls (median [IQR]: 6.94 [2.11–236.17] vs. 1.59 [1.1–9.24] ng/mL, p = 0.004). ROC curves showed moderate diagnostic performance (AUC = 0.68), with concentrations above 2.11 ng/mL achieving 75.3% sensitivity and 58.6% specificity. In NETs, visfatin did not differ based on WHO grade (G1/G2, p = 0.31), primary site (pancreas/small intestine, p = 0.95), sex (p = 0.89), age (p = 0.13), and when stratified by primary site and grade (p = 0.18). Multiple linear regression confirmed no association between visfatin and the study variables (R-squared = 0.036, all p > 0.2). Conclusions: This is the first study examining serum visfatin as a diagnostic biomarker in NETs. Visfatin concentrations show moderate discriminatory ability between NETs and controls, independent of tumor and clinical characteristics. Further research should involve larger cohorts and comparisons to established biomarkers. Full article

Background and Objectives: Excessive social media use is repeatedly linked to negative body image outcomes, yet its association with muscle dysmorphia, especially in athletic youth, remains underexplored. We investigated how social media exposure, comparison behavior, and platform engagement relate to muscle dysmorphia symptomatology in young German athletes. Materials and Methods: An anonymous, web-based cross-sectional survey was conducted (July–October 2024) of 540 individuals (45% female; mean age = 24.6 ± 5.3 years; 79% ≥ 3 h sport/week) recruited via Instagram. The questionnaire comprised demographics, sport type, detailed social media usage metrics, and the validated German Muscle Dysmorphic Disorder Inventory (MDDI-1, 15 items). Correlations (Spearman’s ρ, Kendall’s τ) were calculated; multivariate importance was probed with classification-and-regression trees and CatBoost gradient boosting, interpreted via SHAP values. Results: Median daily social media time was 76 min (IQR 55–110). Participants who spent ≥ 60 min per day on social media showed higher MDDI scores (mean 38 ± 7 vs. 35 ± 6; p = 0.010). The strongest bivariate link emerged between perceived social media-induced body dissatisfaction and felt pressure to attain a specific body composition (Spearman ρ = 0.748, Kendall τ = 0.672, p < 0.001). A CatBoost gradient-boosting model out-performed linear regression in predicting elevated MDDI. The three most influential features (via SHAP values) were daily social media time, frequency of comparison with fitness influencers, and frequency of “likes”-seeking behavior. Conclusions: Intensive social media exposure substantially heightens muscle dysmorphia risk in young German athletes. Machine-learning interpretation corroborates time on social media and influencer comparisons as primary drivers. Interventions should combine social media literacy training with sport-specific psychoeducation to mitigate maladaptive comparison cycles and prevent downstream eating disorder pathology. Longitudinal research is warranted to clarify causal pathways and to test targeted digital media interventions. Full article

The integration of artificial intelligence (AI) into educational environments is fundamentally transforming the learning process, raising new questions regarding student engagement and motivation. This empirical study investigates the relationship between AI-based learning support and the experience of flow, defined as the optimal state of deep attention and intrinsic motivation, among university students. Building on Csíkszentmihályi’s flow theory and current models of technology-enhanced learning, we applied a validated, purposefully developed AI questionnaire (AIFLQ) to 142 students from two Hungarian universities: the Ludovika University of Public Service and Eszterházy Károly Catholic University. The participants used generative AI tools (e.g., ChatGPT 4, SUNO) during their academic tasks. Based on the results of the Mann–Whitney U test, significant differences were found between students from the two universities in the immersion and balance factors, as well as in the overall flow score, while the AI-related factor showed no statistically significant differences. The sustainability of the flow experience appears to be linked more to pedagogical methodological factors than to institutional ones, highlighting the importance of instructional support in fostering optimal learning experiences. Demographic variables also influenced the flow experience. In gender comparisons, female students showed significantly higher values for the immersion factor. According to the Kruskal–Wallis test, educational attainment also affected the flow experience, with students holding higher education degrees achieving higher flow scores. Our findings suggest that through the conscious design of AI tools and learning environments, taking into account instructional support and learner characteristics, it is possible to promote the development of optimal learning states. This research provides empirical evidence at the intersection of AI and motivational psychology, contributing to both domestic and international discourse in educational psychology and digital pedagogy. Full article

Background/Objectives: Injury prevention programs (IPPs) are evidence-based interventions that reduce musculoskeletal injuries in youth sports. Despite their proven benefits, the adoption of IPPs by coaches remains limited. This study aimed to evaluate the awareness, usage, and perceptions of IPPs among youth sports coaches in Poland and to identify factors associated with their implementation. Methods: A cross-sectional study was conducted using a web-based survey tailored to youth sports coaches in Poland. Coaches of athletes aged 9–17 were recruited through targeted outreach to clubs and professional networks. The survey assessed IPP awareness, implementation, perceptions, and sources of information. Statistical analyses included chi-square tests, non-parametric comparisons, Firth’s logistic regression, and cluster profiling. Results: Only 54.6% of coaches (59 out of 108) were aware of IPPs, and among them, just 47.5% reported using them. No significant associations were found between IPP use and demographic variables such as gender, sport, or place of residence. Coaches who were aware of IPPs were significantly younger than those who were unaware (p = 0.029). The information source was the strongest predictor of IPP implementation: coaches trained via formal courses were over 20 times more likely to use IPPs compared to those learning from peers (OR = 20.4, p < 0.001). While coaches generally perceived IPPs as beneficial for fitness and recovery, 28.6% expressed doubts about their effectiveness in reducing injury risk. Conclusions: Despite broadly positive beliefs, only 47.5% of coaches who were aware of IPPs reported using them. Formal training significantly enhances the likelihood of adoption. These findings emphasize the need for structured educational efforts and improved dissemination strategies to promote evidence-based injury prevention in youth sports settings. Full article

Background/Objectives: Pregnancies complicated by idiopathic polyhydramnios are linked to a heightened risk of numerous maternal and perinatal complications. We aim to study the implications of polyhydramnios in term pregnancies complicated with gestational diabetes mellitus (GDM). Methods: A prospective cohort study including 340 GDM cases was conducted. An ultrasound scan was conducted at term between 37 and 40 weeks and amniotic fluid volume (AFV) was assessed by measuring the amniotic fluid index (AFI) and the single deepest pocket (SDP). Maternal demographics and obstetric and perinatal outcomes were evaluated after delivery. We performed comparisons between groups with normal AFV and polyhydramnios (AFI ≥ 24 cm or SDP ≥ 8 cm), and between groups with normal and increased AFV (AFI or SDP ≥ 75th centile). A multivariate logistic regression analysis was performed to study association between AVF measurements and adverse maternal and perinatal outcomes. Results: We found that women with GDM and polyhydramnios at term had a higher risk of maternal (54.3 vs. 27.5%, p < 0.001) and perinatal adverse outcomes (65.7% vs. 46.5%, p < 0.03). The increased AFV group showed a higher risk of fetal overgrowth (LGA: 21.4% vs. 8.2%, p < 0.001 and macrosomia: 19.8% vs. 5.4%, p < 0.001, respectively) and a lesser risk of delivering an SGA fetus (6.3% vs. 13.6%, respectively). Both AFI and SDP showed a significant correlation with newborn weight (r = 0.27; p < 0.001 and r = 0.28; p < 0.001, respectively) and newborn centile (r = 0.26; p < 0.001 and r = 0.26 for both). Subsequent to conducting a multivariate logistic regression analysis adjusted for pregestational BMI, nulliparity, and insulin treatment, both AFI and SDP were significantly associated with perinatal complications, but AFI showed a stronger association with fetal overgrowth (aOR 1.11; p = 0.004 for a LGA fetus and aOR 1.12; p = 0.002 for macrosomia) and with lower risk of delivering an SGA fetus (aOR 0.89; p = 0.009) or IUGR fetus (aOR 0.86; p = 0.03). ROC analysis showed a poor diagnostic performance of both AFI and SDP for identifying macrosomia (AUC 0.68 for AFI, and 0.65 for SDP). Conclusions: Detection of polyhydramnios at term, whether using AFI or SDP, identifies a subgroup of women with gestational diabetes with higher risks of obstetric and perinatal complications. Cases with increased AFV (AFI ≥ 18 cm or SDP ≥ 6.5 cm) are also associated with an increased risk of fetal overgrowth and may require more intensive monitoring for management and optimal delivery timing, with the aim of improve perinatal outcomes. Full article

Mercury (Hg) pollution is a widespread ecological threat with sublethal effects on wildlife. Birds, due to their ecological diversity and sensitivity, serve as effective models for evaluating the behavioural impacts of Hg exposure. This review applies Tinbergen’s four questions: causation, ontogeny, function, and evolution, as an integrative framework. Mechanistically, Hg disrupts neuroendocrine pathways, gene expression, immune function, and hormone regulation, leading to behavioural changes such as reduced foraging, altered parental care, and impaired predator avoidance. Early-life exposure affects neural development, learning, and social behaviour into adulthood. Functionally, these changes reduce fitness by compromising reproduction and survival. Phylogenetic comparisons show interspecific variability, with piscivorous and insectivorous birds exhibiting high Hg burdens and sensitivity, linked to ecological roles and exposure. Behavioural responses often precede physiological or demographic effects, highlighting their value as early indicators. Both field and laboratory studies show that even low Hg concentrations can alter behaviour, though outcomes vary by species, life stage, and exposure route. Integrating behavioural endpoints into ecotoxicological risk assessments is essential to improve conservation strategies and understanding of sublethal pollutant effects on wildlife. Full article