Seabirds are largely used as indicators of Ocean health and are final hosts of several helminth parasites. However, the helminth fauna of seabirds is still poorly studied. Here, we quantified the diversity of gastrointestinal parasites in 52 individuals belonging to 10 seabird species with different habitat preferences and feeding strategies from the North-East Atlantic and Antarctica. Fresh carcasses were collected in Northern France and at Svarthamaren (Dronning Maud Land, Antarctica), helminth parasites were extracted from the gastrointestinal tract, and were identified by morphological inspection and DNA barcoding. In total, we identified 13 helminth taxa. North-East Atlantic seabirds hosted parasites from four helminth groups (Acanthocephala, Cestoda, Nematoda, Trematoda), while Antarctic seabirds hosted Acanthocephala and Cestoda only. The largest parasite diversity was found in northern fulmars Fulmarus glacialis (9 species), European shags Gulosus aristotelis (5 species), razorbills Alca torda (4 species), and black-legged kittiwakes Rissa tridactyla (4 species). Co-infections with multiple parasite species in single hosts were common. Oceanic diving species were found to be the most parasite-poor, with common guillemots Uria aalge and Atlantic puffins Fratercula arctica hosting no parasites. In contrast, oceanic surface-feeding seabirds had a large parasite diversity, which notably included trematodes, and was comparable to that of coastal species. To the best of our knowledge, this study identified 9 new host-parasite associations: Andracantha sp. in northern fulmars and south polar skuas Stercorarius maccormicki, C. septentrionale in northern fulmars and black-legged kittiwakes, a species of Microphallidae in black-legged kittiwakes, Cardiocephaloides longicollis in European shags, Cryptocotyle lingua in Sandwich terns Thalasseus sandvicensis, and a clophyllidean species in south polar skuas and Antarctic petrels Thalassoica antarctica.

Phenolic compounds may reduce oxidative stress and inflammation, but evidence on inflammatory markers is limited. This study investigated associations between phenolic compounds intake and ten inflammatory markers in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). The cross-sectional analysis included participants from the full cohort (n= 14,151) and a São Paulo subsample (n= 681). Food intake was assessed using a semiquantitative food frequency questionnaire, and phenolic content was estimated from Phenol-Explorer and Brazilian Food Composition Database. Logistic regressions models compared the highest versus lowest tertiles of phenolic intake for high-sensitivity C-reactive protein (hs-CRP), glycoprotein acetylation (GlycA), monocyte chemoattractant protein-1 (MCP-1), E-selectin, transforming growth factor β1, tumor necrosis factor α, interleukin-6, interleukin-10, fibrinogen, and leptin levels. Inflammatory markers were dichotomized as low (tertiles 1–2) or high (tertile 3), except hs-CRP (>3 mg/L). Multiple testing was corrected using p<0.0036. Mean age was 52.1 years for hs-CRP/GlycA and 45.6 years for other markers. Compared with T1, participants in T3 of total phenolics, phenolic acids, and flavonoids had 14%, 18%, and 18% lower odds of elevated hs-CRP, respectively. For GlycA, higher intakes of phenolic acids, stilbenes and other phenolics were associated to 18-48% lower odds of high levels (all p≤0.003). Higher intake of hydroxybenzoic acids and stilbenes was associated with lower E-selectin levels, while phenolic acid intake showed an inverse association with MCP-1. No associations were observed for other markers. Higher intakes of phenolic compounds were associated with lower systemic inflammation, suggesting a role in preventing inflammation-related chronic diseases.

Urinary iodine concentration (UIC) is the principal biomarker for assessing iodine status; however, it is subject to marked fluctuations and practical challenges. This proof-of-concept study evaluated protein-corrected salivary iodide (SI/P) as a potential alternative biomarker, comparing it with spot UIC in distinguishing between iodine-deficient and iodine-adequate individuals, assessing its responsiveness to short-term dietary iodine restriction, and exploring its correlation with 24-hour urinary iodine excretion (UIE). Twenty-six participants were categorised into low-iodine (n = 17) and high-iodine (n = 9) groups based on 24 h UIE collected on Day-1. Postprandial spot urine and unstimulated saliva samples were collected under habitual diet (Day-1) and low-iodine diet (Day-2). SI/P was significantly higher in the high-iodine group at all time points on both Day-1 (post-breakfast [1-PB]: 61.28 vs. 27.89 µg/g, p = 0.03; post-lunch [1-PL]: 71.03 vs. 27.4 µg/g, p = 0.003; post-dinner [1-PD]: 114.13 vs. 31.58 µg/g, p = 0.002) and Day-2 (2-PB: 81.86 vs. 26.51 µg/g, p = 0.013; 2-PL: 54.56 vs. 18.83 µg/g, p < 0.001; 2-PD: 38.2 vs. 18.79 µg/g, p = 0.043), whereas UIC only differed significantly post-dinner on Day-1 (156.15 vs. 36.63 µg/L, p = 0.009). SI/P also showed stronger correlation with 24 h UIE (1-PB: r = 0.65, p = 0.001; 1-PL: r = 0.70, p < 0.001; 1-PD: r = 0.67, p < 0.001; 2-PB: r = 0.70, p < 0.001; 2-PL: r = 0.65, p = 0.001; 2-PD: r = 0.50, p = 0.01) compared with UIC (1-PB: r = 0.49, p = 0.011; 1-PL: r = 0.38, p = 0.055; 1-PD: r = 0.58, p = 0.002; 2-PB: r = 0.68, p < 0.001; 2-PL: r = 0.52, p = 0.007; 2-PD: r = 0.44, p = 0.027). Receiver operating characteristic analysis indicated that post-lunch SI/P achieved the highest accuracy (AUC = 0.891; 95%CI: 0.791–0.991; p < 0.0001). Unlike UIC, which is primarily suited for population-level monitoring, SI/P demonstrated stable performance irrespective of diet/sampling time, suggesting utility as a reliable, individual-level biomarker of iodine status.

Anorexia nervosa (AN) is an eating disorder that is mediated by psychological and metabolic factors, yet it is unclear how these factors interact. The NAMA trial objective is to clarify the metabo-psychiatric interaction and identify how it affects AN-patients’ behavior. This randomized trial will recruit 36 treatment-naïve female AN patients, 13–18 years of age, and 36 matched healthy controls. Participants will undergo psychiatric assessments followed by 12-hour overnight fasting. In the next morning baseline assessments of outcomes will be performed. Patients will be randomly allocated 1:1 to receive a mixture with calories or receive a mixture without calories. Healthy controls will also be allocated to receive mixtures with/without calories. Mixtures will be standardized for taste and appearance and allocation will be masked. Primary outcome measure is resting-state functional magnetic resonance brain imaging 60 minutes post-consumption of the mixture. Secondary outcomes include: 1. Blood samples to study markers reflecting metabolic states, hunger/satiety, and stress responses, 2. psychometric evaluations of subjective experiences, and 3. In a second meal 3 hours later, effects of previous calorie intake on subsequent food consumption will be assessed. This article describes the study protocol, including analysis plan, for a randomized controlled trial to comprehensively evaluate the effects of calorie intake in AN. The trial will distinguish psychological and metabolic neuronal networks associated with food intake and uncover how their integration affects food intake and other hallmark symptoms in AN. The aim is to accelerate treatment development by identifying brain mechanisms that drive AN. Clinicaltrials.gov identifier: NCT06814002.