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Zooplankton species structure and diversity within the seagrass home involving Lawas, Sarawak, Malaysia.
Serum pepsinogens have been widely acknowledged as gastric mucosal biomarkers; however, a multicountry report on the benefits of pepsinogens as biomarkers has not yet been published. We analyzed 1,206 sera and gastric mucosal samples collected from Bangladesh, Bhutan, Indonesia, Myanmar, Nepal and Thailand then assessed the association between gastric mucosal changes and Helicobacter pylori infection. The new cutoff values for serum pepsinogen values were evaluated using a receiver operating characteristic analysis. The participants with H. pylori infection had significantly lower pepsinogen I and higher pepsinogen II values, but a lower pepsinogen I/II ratio than participants without the infection (all P less then .001). The pepsinogen I and pepsinogen I/II values were significantly higher and lower, respectively, in individuals with atrophic gastritis than in those without (both P less then .001). Among uninfected individuals, only the pepsinogen I/II ratio was significantly lower in atrophic individuals. Pepsinogen I/II ratio also were significantly different between disease among H. pylori-positive and H. pylori-negative individuals, suggesting the pepsinogen I/II ratio is a robust biomarker for determining both chronic and atrophic gastritis. The cutoffs for detecting chronic and atrophic gastritis for the pepsinogen I/II ratio were 4.65 and 4.95, respectively. In conclusion, pepsinogen levels are useful biomarker for both chronic gastritis and atrophic gastritis, but they should be used with caution. Population-based validation is necessary to determine the best cutoff values. Among all pepsinogen values, the pepsinogen I/II ratio was the most reliable gastric mucosal-change biomarker.The inability of beef cattle to maintain full term pregnancies has become an economic concern for the beef industry. Herd management and nutritional improvements have alleviated environmental impacts on embryonic and fetal loss, yet additional gains can be made through genomic selection. The objectives of this study were to identify loci and gene-sets in crossbred beef heifers associated with the number of services required to become pregnant (TBRD) and heifer conception rate at first service (HCR1). Heifers (n = 709) from a commercial beef operation underwent one round of artificial insemination, before exposure to bulls for natural service for 50 days. Pregnancy and time of conception was determined by ultrasound 35 days after the breeding season. Heifers were genotyped using the GeneSeek (Lincoln, NE) Bovine GGP50K BeadChip prior to genome-wide association analyses (GWAA) conducted using an EIGENSTRAT-like model to identify loci associated (P less then 1 × 10-5) with TBRD and HCR1. One locus was associatercent calf crop.User-generated content (UGC) is an important data source for tourism GIScience research. However, no effective approach exists for identifying hidden spatiotemporal patterns within multi-scale unstructured UGC. Therefore, we developed an algorithm to measure the tourist destination popularity (TDP) based on a multi-spatiotemporal text granular computing model, called TDPMTGC. To accurately granulate the spatial and temporal information of tourism text, tourism text data granules are used to represent landscape objects. These granules are unified objects that possess multiple attributes, such as spatial and temporal dimensions. The multi-spatiotemporal scales are characterized by the multi-hierarchical structure of granular computing, and transformations of granular layers and data granule size are achieved by scale selection in the spatial and temporal dimensions. Therefore, all scales between the spatial and temporal dimension are related, which allows for the comparability of the data granules of all spatiaanomalies and daily contributions of TDP in a specific year, the distinct weakening of tourist route scale in tourist cognition, and the daily variations of TDP during in-season and off-season times. Selleck Trilaciclib This is the first time that a granular computing model has been introduced to tourism GIScience that provides a feasible scheme for reorganizing large-scale unstructured text and constructing public spatiotemporal UGC tourism datasets. TDPMTGC constitutes a new approach for exploring tourist behaviors and the driving mechanisms of tourism patterns and processes.OBJECTIVE To assess the relationship between opioid therapy for chronic noncancer pain and fracture risk by a meta-analysis of cohort studies and case-control studies. METHODS The included cohort studies and case-control studies were identified by searching the PubMed and EMBASE databases from their inception until May 24, 2019. The outcome of interest was a fracture. This information was independently screened by two authors. When the heterogeneity among studies was significant, a random effects model was used to determine the overall combined risk estimate. RESULTS In total, 12 cohort studies and 6 case-control studies were included. We used the Newcastle-Ottawa Scale (NOS) to evaluate the quality of the included literature, and 14 of the studies were considered high-quality studies. The overall relative risk of opioid therapy and fractures was 1.78 (95% confidence interval (CI) 1.53-2.07). Subgroup analyses revealed sources of heterogeneity, sensitivity analysis was stable, and no publication bias was observed. CONCLUSIONS The meta-analysis showed that the use of opioids significantly increased the risk of fracture.This is a PLOS Computational Biology Education paper. The idea that the brain functions so as to minimize certain costs pervades theoretical neuroscience. Because a cost function by itself does not predict how the brain finds its minima, additional assumptions about the optimization method need to be made to predict the dynamics of physiological quantities. In this context, steepest descent (also called gradient descent) is often suggested as an algorithmic principle of optimization potentially implemented by the brain. In practice, researchers often consider the vector of partial derivatives as the gradient. However, the definition of the gradient and the notion of a steepest direction depend on the choice of a metric. Because the choice of the metric involves a large number of degrees of freedom, the predictive power of models that are based on gradient descent must be called into question, unless there are strong constraints on the choice of the metric. Here, we provide a didactic review of the mathematics of gradient descent, illustrate common pitfalls of using gradient descent as a principle of brain function with examples from the literature, and propose ways forward to constrain the metric.
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