Parasites are ubiquitous, yet their effects on hosts are difficult to quantify and generalize across ecosystems. One promising metric of parasitic impact uses the metabolic theory of ecology (MTE) to calculate energy flux, an estimate of energy lost to parasites. We investigated the feasibility of using metabolic scaling rules to compare the energetic burden of parasitism among individuals. Specifically, we found substantial sensitivity of energy flux estimates to input parameters used in the MTE equation when using available data from a model host-parasite system (Gasterosteus aculeatus and Schistocephalus solidus). Using literature values, size data from parasitized wild fish, and a respirometry experiment, we estimate that a single S. solidus tapeworm may extract up to 32% of its stickleback host's baseline metabolic energy requirement, and that parasites in multiple infections may collectively extract up to 46%. The amount of energy siphoned from stickleback to tapeworms is large but did not instigate an increase in respiration rate in the current study. This emphasizes the importance of future work focusing on how parasites influence ecosystem energetics. The approach of using the MTE to calculate energy flux provides great promise as a quantitative foundation for such estimates and provides a more concrete metric of parasite impact on hosts than parasite abundance alone.

Course-based research pedagogy involves positioning students as contributors to authentic research projects as part of an engaging educational experience that promotes their learning and persistence in science. To develop a model for assessing and grading students engaged in this type of learning experience, the assessment aims and practices of a community of experienced course-based research instructors were collected and analyzed. This approach defines four aims of course-based research assessment—(1) Assessing Laboratory Work and Scientific Thinking; (2) Evaluating Mastery of Concepts, Quantitative Thinking and Skills; (3) Appraising Forms of Scientific Communication; and (4) Metacognition of Learning—along with a set of practices for each aim. These aims and practices of assessment were then integrated with previously developed models of course-based research instruction to reveal an assessment program in which instructors provide extensive feedback to support productive student engagement in research while grading those aspects of research that are necessary for the student to succeed. Assessment conducted in this way delicately balances the need to facilitate students’ ongoing research with the requirement of a final grade without undercutting the important aims of a CRE education.

AbstractIntroductionCovert tobacco advertisements often raise regulatory measures. This paper presents that artificial intelligence, particularly deep learning, has great potential for detecting hidden advertising and allows unbiased, reproducible, and fair quantification of tobacco-related media content.MethodsWe propose an integrated text and image processing model based on deep learning, generative methods, and human reinforcement, which can detect smoking cases in both textual and visual formats, even with little available training data.ResultsOur model can achieve 74% accuracy for images and 98% for text. Further-more, our system integrates the possibility of expert intervention in the form of human reinforcement.ConclusionsUsing the pre-trained multimodal, image, and text processing models available through deep learning makes it possible to detect smoking in different media even with few training data.

How has parasitism changed for Alaskan salmon over the past several decades? Parasitological assessments of salmon are inconsistent across time, which may be an oversight: the landscape of parasite risk is changing for salmon, and long-term data are needed to quantify this change. Parasitic nematodes of the family Anisakidae use salmon as intermediate or paratenic hosts in life cycles that terminate in marine mammal definitive hosts. Alaskan marine mammals have been protected since the 1970s, and as populations recover, the density of definitive hosts in this region has increased. To assess whether anisakid burden has changed in salmon over time, we used a novel data source: salmon that were caught, canned, and thermally processed for human consumption in Alaska, USA. We examined canned fillets of chum (Oncorhynchus keta, n = 42), coho (O. kisutch, n = 22), pink (O. gorbuscha, n = 62), and sockeye salmon (O. nerka, n = 52) processed between 1979 and 2019. We dissected each fillet and quantified the number of worms per gram of salmon tissue. Anisakid burden increased over time in chum and pink salmon, but there was no change in sockeye or coho salmon. This difference may be due to differences in the prey preferences of each species, or time spent in marine systems. Canned fish serve as a window into the past, providing information on change over time in the parasite burden of commercially, culturally, and ecologically important fish species that would otherwise be lost.

Biodiversity collections are experiencing a renaissance fueled by the intersection of informatics, emerging technologies, and the extended use and interpretation of specimens and archived databases. In this article, we explore the potential for transformative research in ecology integrating biodiversity collections, stable isotope analysis (SIA), and environmental informatics. Like genomic DNA, SIA provides a common currency interpreted in the context of biogeochemical principles. Integration of SIA data across collections allows for evaluation of long-term ecological change at local to continental scales. Challenges including the analysis of sparse samples, a lack of information about baseline isotopic composition, and the effects of preservation remain, but none of these challenges is insurmountable. The proposed research framework interfaces with existing databases and observatories to provide benchmarks for retrospective studies and ecological forecasting. Collections and SIA add historical context to fundamental questions in freshwater ecological research, reference points for ecosystem monitoring, and a means of quantitative assessment for ecosystem restoration.

In this paper we examine the relationship between vaccination against COVID-19 and both the death rate from COVID-19 and the rate of COVID-19 spread. Our goal is determine if vaccination is associated with reduced death and/or spread of disease at the local level. This analysis was conducted at the county level in the state of Pennsylvania, United States of America, with data that were collected during the first half of 2022 from the state of Pennsylvania's Covid Dashboard (COVID-19 Data for Pennsylvania (pa.gov). This study finds the vaccines to be highly effective in preventing death from Corona virus, even at a time when there was a mismatch between the vaccines and the prevalent variants. Specifically, a 1% increase in vaccination rate was found to correspond to a 0.751% decrease in death rate (95% confidence interval [0.236%, 1.266%]). Given that, during this time period, the vaccines being used were not geared specifically toward the common variants at that time, we found no statistically significant relationship between disease spread and vaccination rate at the county level. These results support previous findings from across the world that Covid vaccination is highly efficacious in preventing death from the disease. Even during a time when vaccine design was not optimally matched with the prevailing strains, vaccination was found to reduce death rate. Hence, improving global vaccine availability is vitally important, to achieve necessary outcomes.

As cognitive function is critical for muscle coordination, cognitive training may also improve neuromuscular control strategy and knee function following an anterior cruciate ligament reconstruction (ACLR). The purpose of this case-control study was to examine the effects of cognitive training on joint stiffness regulation in response to negative visual stimuli and knee function following ACLR. A total of 20 ACLR patients and 20 healthy controls received four weeks of online cognitive training. Executive function, joint stiffness in response to emotionally evocative visual stimuli (neutral, fearful, knee injury related), and knee function outcomes before and after the intervention were compared. Both groups improved executive function following the intervention (p = 0.005). The ACLR group had greater mid-range stiffness in response to fearful (p = 0.024) and injury-related pictures (p = 0.017) than neutral contents before the intervention, while no post-intervention stiffness differences were observed among picture types. The ACLR group showed better single-legged hop for distance after cognitive training (p = 0.047), while the healthy group demonstrated no improvement. Cognitive training enhanced executive function, which may reduce joint stiffness dysregulation in response to emotionally arousing images and improve knee function in ACLR patients, presumably by facilitating neural processing necessary for neuromuscular control.

ABSTRACT Turkish foreign policy under the Justice and Development Party (AKP) has been the subject of much change, especially as regards relations with the countries of the Middle East and North Africa (MENA). We create and analyze a novel dataset of Turkey’s treaties with MENA countries to offer and assess several arguments empirically. We find that Turkey became more diplomatically active in the MENA and emerged as a ‘trading state’ in the AKP’s first decade. In the wake of the Arab Uprisings, especially after 2016, Turkey became less diplomatically active and more security oriented. However, it did not necessarily lose all of the characteristics of a ‘trading state.’