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Early detection is invaluable for the cost‐effective control and eradication of invasive species, yet many traditional sampling techniques are ineffective at the low population abundances found at the onset of the invasion process. Environmental DNA (eDNA) is a promising and sensitive tool for early detection of some invasive species, but its efficacy has not yet been evaluated for many taxonomic groups and habitat types. We evaluated the ability of eDNA to detect the invasive rusty crayfish Orconectes rusticus and to reflect patterns of its relative abundance, in upper Midwest, USA, inland lakes. We paired conventional baited trapping as a measure of crayfish relative abundance with water samples for eDNA, which were analysed in the laboratory with a qPCR assay. We modelled detection probability for O. rusticus eDNA using relative abundance and site characteristics as covariates and also tested the relationship between eDNA copy number and O. rusticus relative abundance. We detected O. rusticus eDNA in all lakes where this species was collected by trapping, down to low relative abundances, as well as in two lakes where trap catch was zero. Detection probability of O. rusticus eDNA was well predicted by relative abundance of this species and lake water clarity. However, there was poor correspondence between eDNA copy number and O. rusticus relative abundance estimated by trap catches. Synthesis and applications. Our study demonstrates a field and laboratory protocol for eDNA monitoring of crayfish invasions, with results of statistical models that provide guidance of sampling effort and detection probabilities for researchers in other regions and systems. We propose eDNA be included as a tool in surveillance for invasive or imperilled crayfishes and other benthic arthropods.

From anecdotal evidence that traditional African sorghum and millet foods are filling and provide sustained energy, we hypothesized that gastric emptying rates of sorghum and millet foods are slow, particularly compared to non-traditional starchy foods (white rice, potato, wheat pasta). A human trial to study gastric emptying of staple foods eaten in Bamako, Mali was conducted using a carbon-13 (13C)-labelled octanoic acid breath test for gastric emptying, and subjective pre-test and satiety response questionnaires. Fourteen healthy volunteers in Bamako participated in a crossover design to test eight starchy staples. A second validation study was done one year later in Bamako with six volunteers to correct for endogenous 13C differences in the starches from different sources. In both trials, traditional sorghum and millet foods (thick porridges and millet couscous) had gastric half-emptying times about twice as long as rice, potato, or pasta (p < 0.0001). There were only minor changes due to the 13C correction. Pre-test assessment of millet couscous and rice ranked them as more filling and aligned well with postprandial hunger rankings, suggesting that a preconceived idea of rice being highly satiating may have influenced subjective satiety scoring. Traditional African sorghum and millet foods, whether viscous in the form of a thick porridge or as non-viscous couscous, had distinctly slow gastric emptying, in contrast to the faster emptying of non-traditional starchy foods, which are popular among West African urban consumers.

Identifying critical habitats is challenging for a relatively rare species like green sturgeon (Acipenser medirostris), which spends most of its life at sea. We used a fixed array and an autonomous underwater vehicle (Slocum glider) as monitoring platforms to detect acoustically tagged green sturgeon in the coastal ocean. For 1 month in 2018 during spring (May) and again in fall (September–October), both methods were used simultaneously to detect sturgeon bearing uniquely coded transmitters. For the fixed array, nine acoustic receivers were interspersed with three sentinel transmitters along a single line of latitude off Winchester Bay, OR. For the glider, two 3-week deployments were completed along the coast of Oregon from nearshore to the 200-m depth contour. For both deployments, the glider flew a zig-zag course southward as it profiled the water column and collected water quality information. Tagged green sturgeon and sentinel transmitters were successfully detected by both the fixed array and the glider. The fixed array provided indications of onshore and offshore movement, while the glider indicated along-shore movement. Although more green sturgeon were detected by the fixed array, the glider provided information on potential sturgeon aggregation areas. In addition, this application of the underwater glider may provide a unique opportunity for public engagement, teaching, and outreach.

Aquatic invasive plant species cause negative impacts to economies and ecosystems worldwide. Traditional survey methods, while necessary, often do not result in timely detections of aquatic invaders, which can be cryptic, difficult to identify, and exhibit very rapid growth and reproduction rates. Environmental DNA (eDNA) is a relatively new method that has been used to detect multiple types of animals in freshwater and marine ecosystems through tissues naturally shed from the organism into the water column or sediment. While eDNA detection has proven highly effective in the detection of aquatic animals, we know less about the efficacy of eDNA as an effective surveillance tool for aquatic plants. To address this disparity, we designed mesocosm experiments with Elodea species to determine the ability to detect accumulation and degradation of the DNA signal for aquatic plants, followed by field surveillance of the highly invasive Hydrilla verticillata in freshwaters across several U.S. geographic regions. In both lab and field experiments, we designed a high sensitivity quantitative PCR assay to detect the aquatic plant species. In both experiments, plant eDNA detection was successful; we saw accumulation of DNA when plants were introduced to tanks and a decrease in DNA over time after plants were removed. We detected eDNA in the field in areas of known Hydrilla distribution. Employing eDNA detection for aquatic plants will strengthen efforts for early detection and rapid response of invaders in global freshwater ecosystems.

Therapy for Clostridioides difficile infections includes the use of antibiotics, immunosuppressors, and fecal microbiota transplantation. However, these treatments have several drawbacks, including the loss of colonization resistance, the promotion of autoimmune disorders, and the potential for unknown pathogens in donor samples. To date, the potential benefits of microbial metabolites in CDI-induced colitis have not been fully investigated. Here, we report for the first time that the microbial metabolite urolithin A has the potential to block toxin production from C. difficile and enhance gut barrier function to mitigate CDI-induced colitis.

IntroductionInequities in COVID-19 infection and vaccine uptake among historically marginalised racial and ethnic groups in the USA persist. Individuals with rheumatic conditions, especially those who are immunocompromised, are especially vulnerable to severe infection, with significant racialised inequities in infection outcomes and in vaccine uptake. Structural racism, historical injustices and misinformation engender racial and ethnic inequities in vaccine uptake. The Popular Opinion Lleader (POL) model, a community-based intervention that trains trusted community leaders to disseminate health information to their social network members (eg, friends, family and neighbours), has been shown to reduce stigma and improve care-seeking behaviours.Methods and analysisThis is a community-based cluster randomised controlled trial led by a team of community and academic partners to compare the efficacy of training POLs with rheumatic or musculoskeletal conditions using a curriculum embedded with a racial justice vs a biomedical framework to increase COVID-19 vaccine uptake and reduce vaccine hesitancy. This trial began recruitment in February 2024 in Boston, Massachusetts and Chicago, Illinois, USA. Eligible POLs are English-speaking adults who identify as Black and/or of African descent, have a diagnosis of a rheumatic or musculoskeletal condition and have received >=1 COVID-19 vaccine after 31 August 2022. POLs will be randomised to a 6-module virtual educational training; the COVID-19 and vaccine-related content will be the same for both groups however the framing for arm 1 will be with a racial justice lens and for arm 2, a biomedical preventative care-focused lens. Following the training, POLs will disseminate the information they learned to 12–16 social network members who have not received the most recent COVID-19 vaccine, over 4 weeks. The trial’s primary outcome is social network member COVID-19 vaccine uptake, which will be compared between intervention arms.Ethics and disseminationThis trial has ethical approval in the USA. This has been approved by the Mass General Brigham Institutional Review Board (IRB, 2023P000686), the Northwestern University IRB (STU00219053), the Boston University/Boston Medical Center IRB (H-43857) and the Boston Children’s Hospital IRB (P00045404). Results will be published in a publicly accessible peer-reviewed journal.Trial registration numberNCT05822219.

The unprecedented COVID-19 pandemic has drawn great attention to the issue of vaccine hesitancy, as the acceptance of the innovative RNA vaccine is relatively low. Studies have addressed multiple factors, such as socioeconomic, political, and racial backgrounds. These studies, however, rely on survey data from participants as part of the population. This study utilizes the actual data from the U.S. Census Bureau as well as actual 2020 U.S. presidential election results to generate four major category of factors that divide the population: socioeconomic status, race and ethnicity, access to technology, and political identification. This study then selects a region in a traditionally democratic state (Capital Region in New York) and a region in a traditionally republican state (Houston metropolitan area in Texas). Statistical analyses such as correlation and geographically weighted regression reveal that factors such as political identification, education attainment, and non-White Hispanic ethnicity in both regions all impact vaccine acceptance significantly. Other factors, such as poverty and particular minority races, have different influences in each region. These results also highlight the necessity of addressing additional factors to further shed light on vaccine hesitancy and potential solutions according to identified factors.

Objective Tracking perinatal mood and anxiety disorders is championed by the American Psychiatric Association and the International Marcé Society for Perinatal Mental Health. We conducted this study to examine trajectories of monthly depressive and anxiety symptoms through pregnancy and postpartum. Methods This is a prospective longitudinal observational cohort study of pregnant women interviewed at baseline (≤18th gestational week), every four weeks through delivery and at 6 and 14 weeks postpartum at three urban academic medical centers (N = 85) and a single rural health center (N = 3) from 2016 to 2020. Pregnant women had at least one prior episode of major depressive disorder, were not in a current episode, and were treated with sertraline, fluoxetine, citalopram, or escitalopram. Of 192 women screened, 88 (46%) women enrolled, and 77 (88%) women completed the postpartum follow‐up. Symptom trajectories were generated with scores from the Edinburgh Postnatal Depression Scale, the Quick Inventory of Depressive Symptoms, the Generalized Anxiety Disorder Scale, 7‐item, and the Patient‐Reported Outcomes Measurement Information System Global Health measure. A semi‐parametric, group‐based mixture model (trajectory analysis) was applied. Results Three relatively stable depression trajectories emerged, described as Minimal, Mild, and Subthreshold, in each group across pregnancy. Two of the four anxiety trajectories were stable, including Asymptomatic and Minimal, while the third, termed Breakthrough, was ascending with increasing symptoms and the fourth trajectory, described as Mild, had descending symptoms. Conclusions Screening for anxiety with depression for pregnant women will yield a comprehensive view of psychiatric symptoms and treatment targets in perinatal women. Highlights Question: What are the trajectories of depression and anxiety symptoms across pregnancy and postpartum in women who continue to take Selective serotonin reuptake inhibitor (SSRI) antidepressants? Findings: In this prospective longitudinal observational cohort study of pregnant women with antidepressant‐treated remitted depression (N = 88), a substantive proportion of women had mild depression (32%) or anxiety (23%). Three trajectories were observed for depression, all relatively stable across time, and four were observed for anxiety, three stable and one increasing across time. Meaning: There is a relative stability of mild symptoms at study entry and across gestation in depression and anxiety symptom course, with three depression and four anxiety trajectories. There was one unique trajectory in anxiety symptom course with one group with ascending symptoms. Clinicians may use measures that are already part of perinatal visits to track and treat those women who fall into these trajectories to improve their mental health.

BackgroundDespite a disproportionate burden of SLE and disparities in adverse outcomes among Black compared to white individuals, people of color are underrepresented in SLE clinical trials. Our aims were: (1) to leverage a community-academic partnership to develop clinical trial education modules for individuals who self-identify as Black with SLE and (2) to recruit and train trusted Popular Opinion Leaders (POLs) with robust social networks to disseminate this information. Due to COVID-19, we adapted the traditional, in-person, POL model to a virtual platform and assessed feasibility.MethodsAcademic and community leaders in Boston and Chicago developed training modules about clinical trials. POLs age ≥18 years old with and without SLE were recruited through community- or hospital-based networks from Boston and Chicago neighborhoods. To train the POLs, five presentations were delivered using an interactive, virtual platform. Modules included: (1) Description of the POL Model, (2-3) Introduction to Clinical Trials, I/II, (4) History of Racism and Clinical Trials, and (5) Clinical Trials: Barriers, Facilitators, and Mediators. POLs completed pre and post-tests, which were compared using paired t-tests. POLs were taught to use virtual platforms to share information learned with their social networks and reported their dissemination.ResultsNineteen POLs were recruited in Boston and 17 in Chicago (table 1). In Boston, 18 (95%) were female, 13 (68%) self-identified as Black, and mean age was 55.6 years. In Chicago, 14 (82%) were female, 16 (94%) self-identified as Black, and mean age was 52.8 years. Retention of POLs throughout the training was 82% both cities. For the two-part clinical trials module, POLs’ knowledge of clinical trials improved significantly (mean difference of 3.92 points, 95% CI 3.35-5.89). As of May 2021, 7 POLs documented 36 encounters and reached 1,023 total individuals; dissemination is ongoing. Boston POLs reached 233 people, including 122 individuals through a sorority newsletter, 104 through Zoom, 6 through phone calls, and 1 in person. Chicago POLs personally reached 240 individuals, including 163 people in a social media group for SLE patients and families, as well as 550 individuals through email interactions.Abstract 1101 Table 1Characteristics of Popular Opinion Leaders in Boston and Chicago Site Boston Chicago Number of POLs 19 17 Mean (SD) Age 55.6 (11.4) 52.8 (18.2) Sex – N (%) Female 18 (95) 14 (82) Male 1 (5) 3 (18) Self-identified Race/Ethnicity- N (%) Black/African American 13 (68) 16 (94) White 3 (16) 0 Other Race 2 (11) 0 Hispanic 1 (5) 1 (6) Educational attainment (%) High School 6 (32) 1 (6) Technical School/GED 3 (16) 2 (13) Bachelor 4 (21) 6 (38) Master 6 (32) 3 (19) Mean Years of Work Experience (SD) 28.8 (13) 27.4 (10) Marital Status (%) Single 11 (58) 7 (41) Married 4 (21) 6 (35) Divorced 3 (16) 2 (12) Widowed 1 (5) 2 (12) Housing (%) Live with spouse, blood relatives and family 10 (53) 10 (59) Live alone 9 (47) 7 (41) Health Conditions (%) Diagnosed with lupus 12 (63) 13 (77) Diabetes 1 (5) 0 Hypertension 7 (37) 9 (53) Arthritis 12 (63) 12 (71) Obesity 9 (47) 4 (24) Relative with lupus (%) 8 (42) 11 (65) Previous Community-Based Experience (%) Previous training as a health promoter 8 (42) 3 (18) Participated in previous lupus educational training 13 (68) 13 (77) Hosted presentations or community-based events 11 (58) 9 (53) Gave testimony 10 (53) 5 (56) Presented at health fairs 8 (42) 8 (89) Distributed educational materials 10 (53) 8 (89) Contacted stakeholders 6 (32) 3 (33) Participated in patient advocacy 9 (47) 4 (44) Collected information from community members (surveys or other) 6 (32) 3 (33) Patient navigation 5 (26) 3 (33) Social Network (%) Member of a gym/sports club 7 (37) 8 (47) Member of a faith-based organization such as a church or ministry 11 (58) 13 (77) Have places they meet with their social network 10 (53) 8 (47) Abbreviations: POL, Popular Opinion Leader; GED, General Educational Development.ConclusionsThe POL model was effectively adapted to a virtual program in the context of COVID-19. Modules developed jointly by academic and community partners were implemented and successfully improved knowledge regarding clinical trials. POL retention was high, possibly due to the convenience of virtual trainings and the sense of community developed. Further studies are needed to determine impact on the diversity of SLE trial enrollment.

ObjectiveOur objective was to develop algorithms to identify lupus clinical classification criteria attributes using structured data found in the electronic health record (EHR) and determine whether they could be used to describe a cohort of people with lupus and discriminate them from a defined healthy control cohort.MethodsWe created gold standard lupus and healthy patient cohorts that were fully adjudicated for the American College of Rheumatology (ACR), Systemic Lupus International Collaborating Clinics (SLICC) and European League Against Rheumatism/ACR (EULAR/ACR) classification criteria and had matched EHR data. We implemented rule-based algorithms using structured data within the EHR system for each attribute of the three classification criteria. Individual criteria attribute and classification criteria algorithms as a whole were assessed over our combined cohorts and the overall performance of the algorithms was measured through sensitivity and specificity.ResultsIndividual classification criteria attributes had a wide range of sensitivities, 7% (oral ulcers) to 97% (haematological disorders) and specificities, 56% (haematological disorders) to 98% (photosensitivity), but all could be identified in EHR data. In general, algorithms based on laboratory results performed better than those primarily based on diagnosis codes. All three classification criteria systems effectively distinguished members of our case and control cohorts, but the SLICC criteria-based algorithm had the highest overall performance (76% sensitivity, 99% specificity).ConclusionsIt is possible to characterise disease manifestations in people with lupus using classification criteria-based algorithms that assess structured EHR data. These algorithms may reduce chart review burden and are a foundation for identifying subpopulations of patients with lupus based on disease presentation to support precision medicine applications.