Submarine groundwater springs are characterized by distinct fish communities

The inflow of terrestrial groundwater into the ocean is increasingly recognized as an important local source of nutrients and pollutants to coastal ecosystems. Although there is evidence of a link between fresh submarine groundwater discharge (SGD)‐derived nutrients and primary producer and primary consumer abundances, the effects of fresh SGD on the productivity of higher trophic levels such as ichthyofaunal communities remain unclear. To further investigate this relationship, we sampled three sites inside a coral reef lagoon in Mauritius: One site entailing six distinct groundwater springs, a site highly influenced by freshwater influx through the springs, and a strictly marine control site. Using remote underwater video surveys, we found that fish abundances were significantly higher at the groundwater springs than at the other two sampling sites.Principal component analyses showed that the springs and the spring‐influenced part of the lagoon were best described by elevated water nutrient loadings, whereas the control site was characterized by higher water salinity and pH. Macroalgae cover was highest at the control site and the springs. Herbivores and invertivores dominated the fish community at the springs, in contrast to generalists at the control site. At the spring‐influenced site, we mainly encountered high coral/turf algae cover and high abundances of associated fish feeding groups (territorial farmers, corallivores). Our results provide evidence of a fresh SGD‐driven relationship between altered hydrography and distinct fish communities with elevated abundances at groundwater springs in a coral reef lagoon. These findings suggest that the management and assessment of secondary consumer productivity in tropical lagoons should take into account the effects of groundwater springs

De novo implantation vs. upgrade cardiac resynchronization therapy: a systematic review and meta-analysis

Patients with conventional pacemakers or implanted defibrillators are often considered for cardiac resynchronization therapy (CRT). Our aim was to summarize the available evidences regarding the clinical benefits of upgrade procedures. A systematic literature search was performed from studies published between 2006 and 2017 in order to compare the outcome of CRT upgrade vs. de novo implantations. Outcome data on all-cause mortality, heart failure events, New York Heart Association (NYHA) Class, QRS narrowing and echocardiographic parameters were analysed. A total of 16 reports were analysed comprising 489,568 CRT recipients, of whom 468,205 patients underwent de novo and 21,363 upgrade procedures. All-cause mortality was similar after CRT upgrade compared to de novo implantations (RR 1.19, 95% CI 0.88-1.60, p = 0.27). The risk of heart failure was also similar in both groups (RR 0.96, 95% CI 0.70-1.32, p = 0.81). There was no significant difference in clinical response after CRT upgrade compared to de novo implantations in terms of improvement in left ventricular ejection fraction (DeltaEF de novo - 6.85% vs. upgrade - 9.35%; p = 0.235), NYHA class (DeltaNYHA de novo - 0.74 vs. upgrade - 0.70; p = 0.737) and QRS narrowing (DeltaQRS de novo - 9.6 ms vs. upgrade - 29.5 ms; p = 0.485). Our systematic review and meta-analysis of currently available studies reports that CRT upgrade is associated with similar risk for all-cause mortality compared to de novo resynchronization therapy. Benefits on reverse remodelling and functional capacity improved similarly in both groups suggesting that CRT upgrade may be safely and effectively offered in routine practice. CLINICAL TRIAL REGISTRATION: Prospero Database-CRD42016043747

Calculating Stage Duration Statistics in Multistage Diseases

Many human diseases are characterized by multiple stages of progression. While the typical sequence of disease progression can be identified, there may be large individual variations among patients. Identifying mean stage durations and their variations is critical for statistical hypothesis testing needed to determine if treatment is having a significant effect on the progression, or if a new therapy is showing a delay of progression through a multistage disease. In this paper we focus on two methods for extracting stage duration statistics from longitudinal datasets: an extension of the linear regression technique, and a counting algorithm. Both are non-iterative, non-parametric and computationally cheap methods, which makes them invaluable tools for studying the epidemiology of diseases, with a goal of identifying different patterns of progression by using bioinformatics methodologies. Here we show that the regression method performs well for calculating the mean stage durations under a wide variety of assumptions, however, its generalization to variance calculations fails under realistic assumptions about the data collection procedure. On the other hand, the counting method yields reliable estimations for both means and variances of stage durations. Applications to Alzheimer disease progression are discussed