Size- and stage-dependence in cause-specific mortality of migratory brown trout

Evidence‐based management of natural populations under strong human influence frequently requires not only estimates of survival but also knowledge about how much mortality is due to anthropogenic vs. natural causes. This is the case particularly when individuals vary in their vulnerability to different causes of mortality due to traits, life history stages, or locations. Here, we estimated harvest and background (other cause) mortality of landlocked migratory salmonids over half a century. In doing so, we quantified among‐individual variation in vulnerability to cause‐specific mortality resulting from differences in body size and spawning location relative to a hydropower dam. We constructed a multistate mark–recapture model to estimate harvest and background mortality hazard rates as functions of a discrete state (spawning location) and an individual time‐varying covariate (body size). We further accounted for among‐year variation in mortality and migratory behaviour and fit the model to a unique 50‐year time series of mark–recapture–recovery data on brown trout (Salmo trutta ) in Norway. Harvest mortality was highest for intermediate‐sized trout, and outweighed background mortality for most of the observed size range. Background mortality decreased with body size for trout spawning above the dam and increased for those spawning below. All vital rates varied substantially over time, but a trend was evident only in estimates of fishers' reporting rate, which decreased from over 50% to less than 10% throughout the study period. We highlight the importance of body size for cause‐specific mortality and demonstrate how this can be estimated using a novel hazard rate parameterization for mark–recapture models. Our approach allows estimating effects of individual traits and environment on cause‐specific mortality without confounding, and provides an intuitive way to estimate temporal patterns within and correlation among different mortality sources

Shift Work Including Night Work and Long Working Hours in Industrial Plants Increases the Risk of Atherosclerosis

There is an abundance of literature reporting an association between shift work and cardiovascular disease (CVD). Few studies have examined early manifestation of CVD using advanced modern methodology. We established a group of 65 shift workers and 29 day workers (controls) in two industrial plants. For the shift workers, the shift schedule includes rotating shifts with day, evening and nightshifts, some day and nightshifts lasting for 12 h. The current paper describes cross-sectional data in a study running for three years. We collected background data by questionnaire and measured blood pressure, heart rate, lipids, glycosylated hemoglobin (HbA1c) and C-reactive protein (CRP). We examined arterial stiffness (central blood pressure, augmentation pressure and index, and pulse wave velocity) by the use of SphygmoCor® (AtCor Medical Pty Ltd, Sydney, Australia) and the carotid arteries by ultrasound. We assessed VO2max by bicycle ergometry. We applied linear and logistic regression to evaluate associations between total number of years in shift work and cardiovascular outcome measures. The day workers were older and had more pronounced arterial stiffness compared to the shift workers. Number of years as a shift worker was associated with increased carotid intima media thickness (max IMT) (B = 0.015, p = 0.009) and an elevated CRP (B = 0.06, p = 0.03). Within the normal range for this age group, VO2max was 41 (9) ml/kg/min. Rotating shift work including day and night shifts lasting up to 12 h and evening shifts are associated with CVD-risk factors. This could imply an increased risk for coronary heart disease and stroke among these workers. Therefore, preventive measures should be considered for these groups of workers in order to prevent such diseases.publishedVersio

Effect of instruction and motivation in the use of electric and manual toothbrushes in periodontal patients: a comparative study

The aim of the present study was to evaluate the efficacy of manual and electric toothbrushes in plaque control in periodontal patients after proper instructions. Thirty six periodontal patients (mean age of 49 years, 21 females and 15 males) were included and completed the study (100% compliance). A single-blinded, randomized, controlled, cross-over clinical design was adopted, with the patients using during 2 periods of 14 days each the manual and/or electric toothbrush. Four subgroups of 9 individuals were studied: A1 - used manual toothbrush in both experimental periods; A2 - used the manual toothbrush during the first period and the electrical toothbrush during the second period; B1 - used electrical toothbrush during both periods; B2 - used the electrical toothbrush in the first period and the manual one in the second period. Brushing was performed during 14 days and at day 14 and 28 it was performed in the clinic, and timing of brushing was recorded without patients being aware. The Plaque Index (Silness, Löe, 1964) was used. Intra-group comparisons were performed by paired t-test and inter-group comparisons by independent sample t-test, with an alpha level of 0.05. The results showed no difference between the tested brushes neither for plaque nor for timing. However, re-instruction was detected as an important factor, since for all groups the second period, after reinstruction, showed lower plaque scores. It is concluded that professional advice and instruction and re-instruction seem more important in order to obtain good plaque control than the choice of toothbrush in subjects with periodontal disease

Long-term mark-recapture and growth data for large-sized migratory brown trout (Salmo trutta) from Lake Mjøsa, Norway

Long-term data from marked animals provide a wealth of opportunities for studies with high relevance to both basic ecological understanding and successful management in a changing world. The key strength of such data is that they allow us to quantify individual variation in vital rates (e.g. survival, growth, reproduction) and then link it mechanistically to dynamics at the population level. However, maintaining the collection of individual-based data over long time periods comes with large logistic efforts and costs and studies spanning over decades are therefore rare. This is the case particularly for migratory aquatic species, many of which are in decline despite their high ecological, cultural and economical value.publishedVersio

Establishment of a tear protein biomarker panel differentiating between Graves' disease with or without orbitopathy

Background Graves' orbitopathy (GO) is an autoimmune inflammatory ocular complication and one of the most frequent manifestations of Graves' disease (GD). Clinical judgment of GO is subjective sometimes leading to clinical and therapeutic challenges. Better tools to diagnose this severe complication are warranted. Patients and methods The aim of the present study was to evaluate tear levels of LYZ, LACRT and AZGP1 in GD patients with or without GO, as possible biomarkers for GO. Tear samples were collected from GD patients with moderate-to-severe GO (n = 21) and no clinical signs of GO (n = 21). Additionally, 18 GD patients with mild GO and 9 patients without GO were included in a further part of the study. Results Tear levels of LYZ (p < 0.001), LACRT (p = 0.004) and AZGP1 (p = 0.001) were significantly elevated in GD patients with moderate-to-severe GO compared to GD patients without GO. The discriminatory power of the three biomarkers, combined in a panel was confirmed by ROC plot analysis, with an AUC value of 0.93 (sensitivity of 95%; specificity of 80%). Since LYZ showed the best performance in discriminating between GD patients with (moderateto-severe) and without GO (in combination with limited sample volume available), LYZ levels were also measured in tears from GD patients with mild GO and without GO. Significantly higher levels of LYZ were measured in GD patients with mild GO compared to those without GO (p = 0.003)

A Cease in Shift Work Reverses Arterial Stiffness but Increases Weight and Glycosylated Hemoglobin A 5-Month Follow-Up in Industry

Background: Literature suggests an association between shift work and cardiovascular disease (CVD). Limited evidence is available on how a cessation of shift work affects CVD risk factors. Aim: We investigated whether a five-month plant shutdown affected CVD risk factors in 30 industrial shift workers. Methods: We collected demographic data, self-reported data on physical activity (PA) and medical history by questionnaire. Pre- and post-plant shutdown, we measured blood pressure (BP), heart rate, lipids, glycosylated hemoglobin (HbA1c) and C-reactive protein (CRP). Additionally, we collected markers of inflammation, Matrix metalloproteinase-9 (MMP-9), Interleukin-6 (IL-6), Monocyte chemoattractant protein-1 (MCP-1), Tumor necrosis factor-alpha (TNF-&alpha;), P-selectin, Interleukin-1 beta (IL-1&beta;), and Interleukin-23 (IL-23). We also examined arterial stiffness (central blood pressure, augmentation pressure, and pulse wave velocity) by means of SphygmoCor&reg; (AtCor Medical Pty Ltd., Sydney, Australia). We monitored sleep by actigraphy prior to and after plant shutdown, with additional registration of sleep quality and assessment of insomnia symptoms. Results: After five months of plant shutdown, we found that HbA1c increased by 1.9 mmol/mol, weight by 1 kg and MCP-1 by 27.3 pg/mL, all unexpectedly. The other markers of inflammation did not change during shutdown, but CRP decreased close to significant levels. There were no changes in lipids during follow-up. Pulse-wave velocity (PWV) was reduced from 8.1 m/s (SD = 1.5) to 7.6 m/s (SD = 1.5), p = 0.03. The workers reported fewer signs of insomnia after shutdown. Conclusions: Our findings suggest that a five-month cessation in shift work increases weight and HbA1c, but also improves insomnia symptoms and reverses arterial stiffening

Individual heterogeneity and early life conditions shape growth in a freshwater top predator

Body size can have profound impacts on survival, movement, and reproductive schedules shaping individual fitness, making growth a central process in ecological and evolutionary dynamics. Realized growth is the result of a complex interplay between life history schedules, individual variation, and environmental influences. Integrating all of these aspects into growth models is methodologically difficult, depends on the availability of repeated measurements of identifiable individuals, and consequently represents a major challenge in particular for natural populations. Using a unique 30‐yr time series of individual length measurements inferred from scale year rings of wild brown trout, we develop a Bayesian hierarchical model to estimate individual growth trajectories in temporally and spatially varying environments. We reveal a gradual decrease in average juvenile growth, which has carried over to adult life and contributed to decreasing sizes observed at the population level. Commonly studied environmental drivers like temperature and water flow did not explain much of this trend and overall persistent and among‐year individual variation dwarfed temporal variation in growth patterns. Our model and results are relevant to a wide range of questions in ecology and evolution requiring a detailed understanding of growth patterns, including conservation and management of many size‐structured populations

Individual heterogeneity and early life conditions shape growth in a freshwater top predator

Body size can have profound impacts on survival, movement, and reproductive schedules shaping individual fitness, making growth a central process in ecological and evolutionary dynamics. Realized growth is the result of a complex interplay between life history schedules, individual variation, and environmental influences. Integrating all of these aspects into growth models is methodologically difficult, depends on the availability of repeated measurements of identifiable individuals, and consequently represents a major challenge in particular for natural populations. Using a unique 30‐yr time series of individual length measurements inferred from scale year rings of wild brown trout, we develop a Bayesian hierarchical model to estimate individual growth trajectories in temporally and spatially varying environments. We reveal a gradual decrease in average juvenile growth, which has carried over to adult life and contributed to decreasing sizes observed at the population level. Commonly studied environmental drivers like temperature and water flow did not explain much of this trend and overall persistent and among‐year individual variation dwarfed temporal variation in growth patterns. Our model and results are relevant to a wide range of questions in ecology and evolution requiring a detailed understanding of growth patterns, including conservation and management of many size‐structured populations