Impact of GLP-1 Receptor Agonist Use in Patients With Steatotic Liver Disease and Type 2 Diabetes: A Retrospective Cohort Study.

Background: Glucagon-like peptide 1 receptor agonists (GLP-1 RAs) help manage type 2 diabetes (T2DM) and may have efficacy in steatotic liver disease. Objective: To determine the prevalence and clinical impact of GLP-1 RA use in patients with T2DM and liver disease. Methods: This was a retrospective study of adult patients with T2DM and nonalcoholic fatty liver disease (NAFLD), nonalcoholic fatty liver (NAFL), or nonalcoholic steatohepatitis (NASH) between 1/1/21-12/31/21. Patients with hepatitis B or C, or on pioglitazone were excluded. Eligible patients treated with a GLP-1 RA were compared to controls. The primary outcome was change in Fibrosis-4 (FIB-4) score, with NAFLD Fibrosis Score (NFS) as a secondary outcome. Follow-up scores were calculated from labs within 3 to 15 months after baseline. Results: Of 242 eligible patients, 79 patients (32.6%) were treated with a GLP-1 RA. At baseline, FIB-4 score was lower and NFS was higher in the GLP-1 RA group vs controls (1.80 vs 2.33; P = .101, .36 vs -.47, P < .001; respectively). At follow up, FIB-4 score decreased to 1.77 in the GLP-1 RA group and increased to 2.71 in controls (P = .045). Follow up NFS was stable in the GLP-1 RA group and increased in the control group (.36 vs -.43; P = .308). Conclusion: Patients treated with GLP-1 RAs had less evidence of liver fibrosis progression compared to no treatment, although the differences were small. These results suggest that treatment with GLP-1 RAs may have clinical impact on slowing liver fibrosis, however results should be confirmed in a larger, more diverse sample.

A century of statistical Ecology.

As data and computing power have surged in recent decades, statistical modeling has become an important tool for understanding ecological patterns and processes. Statistical modeling in ecology faces two major challenges. First, ecological data may not conform to traditional methods, and second, professional ecologists often do not receive extensive statistical training. In response to these challenges, the journal Ecology has published many innovative statistical ecology papers that introduced novel modeling methods and provided accessible guides to statistical best practices. In this paper, we reflect on Ecology's history and its role in the emergence of the subdiscipline of statistical ecology, which we define as the study of ecological systems using mathematical equations, probability, and empirical data. We showcase 36 influential statistical ecology papers that have been published in Ecology over the last century and, in so doing, comment on the evolution of the field. As data and computing power continue to increase, we anticipate continued growth in statistical ecology to tackle complex analyses and an expanding role for Ecology to publish innovative and influential papers, advancing the discipline and guiding practicing ecologists.

Journals must expand access to peer review data.

Empirical studies on peer review bias are primarily conducted by people from privileged groups and with affiliations with the journals studied. Data access is one major barrier to conducting peer review research. Accordingly, we propose pathways to broaden access to peer review data to people from more diverse backgrounds.

Integrated community models: A framework combining multispecies data sources to estimate the status, trends and dynamics of biodiversity.

Data deficiencies among rare or cryptic species preclude assessment of community-level processes using many existing approaches, limiting our understanding of the trends and stressors for large numbers of species. Yet evaluating the dynamics of whole communities, not just common or charismatic species, is critical to understanding and the responses of biodiversity to ongoing environmental pressures. A recent surge in both public science and government-funded data collection efforts has led to a wealth of biodiversity data. However, these data collection programmes use a wide range of sampling protocols (from unstructured, opportunistic observations of wildlife to well-structured, design-based programmes) and record information at a variety of spatiotemporal scales. As a result, available biodiversity data vary substantially in quantity and information content, which must be carefully reconciled for meaningful ecological analysis. Hierarchical modelling, including single-species integrated models and hierarchical community models, has improved our ability to assess and predict biodiversity trends and processes. Here, we highlight the emerging 'integrated community modelling' framework that combines both data integration and community modelling to improve inferences on species- and community-level dynamics. We illustrate the framework with a series of worked examples. Our three case studies demonstrate how integrated community models can be used to extend the geographic scope when evaluating species distributions and community-level richness patterns; discern population and community trends over time; and estimate demographic rates and population growth for communities of sympatric species. We implemented these worked examples using multiple software methods through the R platform via packages with formula-based interfaces and through development of custom code in JAGS, NIMBLE and Stan. Integrated community models provide an exciting approach to model biological and observational processes for multiple species using multiple data types and sources simultaneously, thus accounting for uncertainty and sampling error within a unified framework. By leveraging the combined benefits of both data integration and community modelling, integrated community models can produce valuable information about both common and rare species as well as community-level dynamics, allowing for holistic evaluation of the effects of global change on biodiversity.

Community-Centered Assessment to Inform Pandemic Response in Georgia (US).

The Georgia Community Engagement Alliance (CEAL) Against COVID-19 Disparities Project conducts community-engaged research and outreach to address misinformation and mistrust, to promote inclusion of diverse racial and ethnic populations in clinical trials and increase testing and vaccination uptake. Guided by its Community Coalition Board, The GEORGIA CEAL Survey was administered among Black and Latinx Georgia 18 years and older to learn about community knowledge, perceptions, understandings, and behaviors regarding COVID-19 testing and vaccines. Survey dissemination occurred using survey links generated through Qualtrics and disseminated among board members and other statewide networks. Characteristics of focus counties were (a) highest proportion of 18 years and older Black and Latinx residents; (b) lowest COVID-19 testing rates; and (c) highest SVI values. The final sample included 2082 surveyed respondents. The majority of participants were men (57.1%) and Latinx (62.8%). Approximately half of the sample was aged 18-30 (49.2%); the mean age of the sample was 33.2 years (SD = 9.0), ranging from 18 to 82 years of age. Trusted sources of COVID-19 information that significantly predicted the likelihood of vaccination included their doctor/health care provider (p-value: 0.0054), a clinic (p-value: 0.006), and university hospitals (p-value: 0.0024). Latinx/non-Latinx, Blacks vs. Latinx, Whites were significantly less likely to get tested and/or vaccinated. Non-Latinx, Blacks had higher mean knowledge scores than Latinx, Whites (12.1 vs. 10.9, p < 0.001) and Latinx, Blacks (12.1 vs. 9.6, respectively, p < 0.001). The mean knowledge score was significantly lower in men compared to women (10.3 vs. 11.0, p = 0.001), in those who had been previously tested for COVID-19 compared to those who had never been tested (10.5 vs. 11.5, respectively, p = 0.005), and in those who did not receive any dose of vaccination compared to those who were fully vaccinated (10.0 vs. 11.0, respectively, p < 0.001). These data provide a benchmark for future comparisons of the trajectory of public attitudes and practices related to the COVID-19 pandemic. They also point to the importance of tailoring communication strategies to specific cultural, racial, and ethnic groups to ensure that community-specific barriers to and determinants of health-seeking behaviors are appropriately addressed.

Peer review perpetuates barriers for historically excluded groups.

Peer review is central to the scientific process and scientists' career advancement, but bias at various stages of the review process disadvantages some authors. Here we use peer review data from 312,740 biological sciences manuscripts across 31 studies to (1) examine evidence for differential peer review outcomes based on author demographics, (2) evaluate the efficacy of solutions to reduce bias and (3) describe the current landscape of peer review policies for 541 ecology and evolution journals. We found notably worse review outcomes (for example, lower overall acceptance rates) for authors whose institutional affiliations were in Asia, for authors whose country's primary language is not English and in countries with relatively low Human Development Indices. We found few data evaluating efficacy of interventions outside of reducing gender bias through double-blind review or diversifying reviewer/editorial boards. Despite evidence for review outcome gaps based on author demographics, few journals currently implement policies intended to mitigate bias (for example, 15.9% of journals practised double-blind review and 2.03% had reviewer guidelines that mentioned social justice issues). The lack of demographic equity signals an urgent need to better understand and implement evidence-based bias mitigation strategies.

Miro GTPase domains regulate the assembly of the mitochondrial motor-adaptor complex.

Mitochondrial transport relies on a motor-adaptor complex containing Miro1, a mitochondrial outer membrane protein with two GTPase domains, and TRAK1/2, kinesin-1, and dynein. Using a peroxisome-directed Miro1, we quantified the ability of GTPase mutations to influence the peroxisomal recruitment of complex components. Miro1 whose N-GTPase is locked in the GDP state does not recruit TRAK1/2, kinesin, or P135 to peroxisomes, whereas the GTP state does. Similarly, the expression of the MiroGAP VopE dislodges TRAK1 from mitochondria. Miro1 C-GTPase mutations have little influence on complex recruitment. Although Miro2 is thought to support mitochondrial motility, peroxisome-directed Miro2 did not recruit the other complex components regardless of the state of its GTPase domains. Neurons expressing peroxisomal Miro1 with the GTP-state form of the N-GTPase had markedly increased peroxisomal transport to growth cones, whereas the GDP-state caused their retention in the soma. Thus, the N-GTPase domain of Miro1 is critical for regulating Miro1's interaction with the other components of the motor-adaptor complex and thereby for regulating mitochondrial motility.

Errors in aerial survey count data: Identifying pitfalls and solutions.

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double-observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.

Photocatalytic hydrogen evolution from biomass conversion.

Biomass has incredible potential as an alternative to fossil fuels for energy production that is sustainable for the future of humanity. Hydrogen evolution from photocatalytic biomass conversion not only produces valuable carbon-free energy in the form of molecular hydrogen but also provides an avenue of production for industrially relevant biomass products. This photocatalytic conversion can be realized with efficient, sustainable reaction materials (biomass) and inexhaustible sunlight as the only energy inputs. Reported herein is a general strategy and mechanism for photocatalytic hydrogen evolution from biomass and biomass-derived substrates (including ethanol, glycerol, formic acid, glucose, and polysaccharides). Recent advancements in the synthesis and fundamental physical/mechanistic studies of novel photocatalysts for hydrogen evolution from biomass conversion are summarized. Also summarized are recent advancements in hydrogen evolution efficiency regarding biomass and biomass-derived substrates. Special emphasis is given to methods that utilize unprocessed biomass as a substrate or synthetic photocatalyst material, as the development of such will incur greater benefits towards a sustainable route for the evolution of hydrogen and production of chemical feedstocks.

Begging behavior as an honest signal of need and parent-offspring association during the postfledging dependency period.

Honest signaling mechanisms can function to appropriate care to hungry offspring and avoid misdirected care of unrelated offspring. Begging, the behavior by which offspring solicit food and parental care, may be an honest signaling mechanism for need, as well as association of parents and offspring. Roseate terns (Sterna dougallii) exhibit prolonged parental care during the postbreeding staging period, offering an ideal system in which to study begging as an honest signaling mechanism. We conducted focal sampling during two premigratory staging seasons (2014 and 2015) at Cape Cod National Seashore, Massachusetts, USA to determine whether postfledging tern begging behavior was an honest signal for need and parent-offspring association. Based on honest signaling theory, we expected begging behavior to be highest during times of high perceived need, and we expected to see a decrease in begging behavior as young terns became increasingly independent of the care-giving parent. Also, we predicted that young terns would be more likely to beg at parents than nonparents. We found that young roseate terns begged at their parents more often than nonparents; however, they did not always beg at parents. Model predictions of begging probability showed a linear relationship between begging and time of day and date of season, such that begging increased with time of day and decreased with date of season, respectively. Our results provide evidence for honest parent-offspring interactions and are inconsistent with parent-offspring conflict theory but suggest that begging may play a complex role in postfledging parent-offspring interactions. OPEN RESEARCH BADGES: This article has been awarded Open Data, Open materials Badges. All materials and data are publicly accessible via the Open Science Framework at https://doi.org/10.5281/zenodo.2656718.

Diagnostic accuracy of ultrasound for rotator cuff tears.

Ultrasonography (US) is an inexpensive, convenient, and effective tool that can be used to evaluate the shoulder. It does not expose the patient to harmful radiation and can be used to evaluate the musculoskeletal system dynamically. Additionally, US is not subject to metal artifacts when evaluating patients with previously placed hardware. Over the years, US has been found to be reliable and accurate for diagnosing rotator cuff tears (RCTs), despite its operatordependence. The usage of US for diagnosing RCTs in orthopedic practice varies depending on practitioners' familiarity with the exam and the availability of experienced technicians. The purpose of this article is to review the diagnostic accuracy of US for identifying RCTs.

The TOG protein Stu2/XMAP215 interacts covalently and noncovalently with SUMO.

Stu2p is the yeast member of the XMAP215/Dis1/ch-TOG family of microtubule-associated proteins that promote microtubule polymerization. However, the factors that regulate its activity are not clearly understood. Here we report that Stu2p in the budding yeast Saccharomyces cerevisiae interacts with SUMO by covalent and noncovalent mechanisms. Stu2p interacted by two-hybrid analysis with the yeast SUMO Smt3p, its E2 Ubc9p, and the E3 Nfi1p. A region of Stu2p containing the dimerization domain was both necessary and sufficient for interaction with SUMO and Ubc9p. Stu2p was found to be sumoylated both in vitro and in vivo. Stu2p copurified with SUMO in a pull-down assay and vice versa. Stu2p also bound to a nonconjugatable form of SUMO, suggesting that Stu2p can interact noncovalently with SUMO. In addition, Stu2p interacted with the STUbL enzyme Ris1p. Stu2p also copurified with ubiquitin in a pull-down assay, suggesting that it can be modified by both SUMO and ubiquitin. Tubulin, a major binding partner of Stu2p, also interacted noncovalently with SUMO. By two-hybrid analysis, the beta-tubulin Tub2p interacted with SUMO independently of the microtubule stressor, benomyl. Together, these findings raise the possibility that the microtubule polymerization activities mediated by Stu2p are regulated through sumoylation pathways.

Effect of acute low body temperature on predatory behavior and prey-capture efficiency in a plethodontid salamander.

The low-temperature limit for feeding in some salamander species (Desmognathus, Plethodontidae) has been inferred from field studies of seasonal variation in salamander activity and gut contents, which could not determine whether feeding is more dependent on environmental conditions influencing salamander foraging behavior or prey availability and movement. We performed two controlled laboratory experiments to examine the effect of short-term (acute) low body temperature on predatory behavior and prey-capture efficiency in a semiaquatic plethodontid salamander (Desmognathus conanti). In the first experiment, we quantified variation in the feeding responses of cold salamanders (at 1, 3, 5 and 7°C) to a video recording of a walking, warm (15°C) cricket to determine the lower thermal limit for predatory behavior, independent of any temperature effect on movement of prey. Experimental-group salamanders exhibited vigorous feeding responses at 5 and 7°C, large variation in feeding responses both among and within individuals (over time) at 3°C, and little to no feeding response at 1°C. Feeding responses at both 1 and 3°C were significantly less than at each higher temperature, whereas responses of control-group individuals at 15°C did not vary over time. In the second experiment, we quantified feeding by cold salamanders (at 3, 5, 7 and 11°C) on live, warm crickets to examine thermal effects on prey-capture ability. The mean feeding response to live crickets was significantly less at 3°C than at higher temperatures; however, 50% of salamanders captured and ingested prey with high efficiency at this temperature. We conclude that many individuals stalk and capture prey at very low temperatures (down to 3°C). Our results support a growing body of data that indicate many plethodontid salamanders feed at temperatures only a few degrees above freezing.

Emerging roles of sumoylation in the regulation of actin, microtubules, intermediate filaments, and septins.

Sumoylation is a powerful regulatory system that controls many of the critical processes in the cell, including DNA repair, transcriptional regulation, nuclear transport, and DNA replication. Recently, new functions for SUMO have begun to emerge. SUMO is covalently attached to components of each of the four major cytoskeletal networks, including microtubule-associated proteins, septins, and intermediate filaments, in addition to nuclear actin and actin-regulatory proteins. However, knowledge of the mechanisms by which this signal transduction system controls the cytoskeleton is still in its infancy. One story that is beginning to unfold is that SUMO may regulate the microtubule motor protein dynein by modification of its adaptor Lis1. In other instances, cytoskeletal elements can both bind to SUMO non-covalently and also be conjugated by it. The molecular mechanisms for many of these new functions are not yet clear, but are under active investigation. One emerging model links the function of MAP sumoylation to protein degradation through SUMO-targeted ubiquitin ligases, also known as STUbL enzymes. Other possible functions for cytoskeletal sumoylation are also discussed.