FACETS

Invasive round goby Neogobius melanostomus have advanced eastward through the state of New York and provinces of Ontario and Quebec over the past two decades and are approaching Lake Champlain, one of the largest lakes in North America. This manuscript describes international efforts to monitor round goby populations during 2021-2025 on (a) the southern approach to Lake Champlain via the Hudson River and Champlain Canal, and (b) the northern approach to Lake Champlain via the Saint Lawrence River and Richelieu River. Monitoring utilized environmental DNA (eDNA), backpack electrofishing, beach seining, benthic trawling, and viral hemorrhagic septicemia virus (VHSV) testing. In the Champlain Canal, round goby were captured as far north as the downstream side of the C1 dam (97 kilometers [km] from Lake Champlain) while eDNA detections occurred as far north as the upstream side of the C2 dam (90 km from Lake Champlain). In the Richelieu River, round goby were captured as far south as Saint-Marc-sur-Richelieu (82 km from Lake Champlain) while the southern-most eDNA detections occurred near the Canadian side of the international border (4 km from Lake Champlain). Water temperature influenced habitat usage of round goby in the Champlain Canal, with catch rates in near-shore areas declining at < 10 {degrees}C. All VHSV test results were non-detections at the mouth of the Richelieu River, while one positive and two inconclusive results occurred along the Champlain Canal. Together, these data have informed multiple mitigation measures and have implications for management of aquatic invasive species across North America.

BackgroundCase-based infectious disease surveillance is subject to ascertainment bias when testing intensity varies across time and population subgroups. We previously developed a regression-based test adjustment methodology using Standardized Testing Ratios (STRs) to correct for differential testing patterns in COVID-19 surveillance data. Wastewater-based surveillance (WWS) measures viral burden in the community independently of diagnostic testing behavior, making it a valuable external validation tool for test-adjusted case estimates. MethodsWe analyzed 111 weeks of paired wastewater and case surveillance data from Ontario, Canada (July 19, 2020 to August 28, 2022). Wastewater SARS-CoV-2 signals from 107 sewersheds across 34 public health units were normalized within sewersheds and aggregated using population-weighted averages. We compared wastewater correlations with crude reported and test-adjusted case counts using Spearman rank correlations, linear regression, and negative binomial distributed lag nonlinear models (DLNM), stratified by epidemic period. ResultsTest-adjusted cases correlated substantially more strongly with wastewater signals than crude reported cases overall (Spearman {rho} = 0.849 vs. 0.679; linear R{superscript 2} = 0.609 vs. 0.191). The advantage of test adjustment was greatest during the Omicron wave, when population-level diagnostic testing contracted sharply following PCR eligibility restrictions ({rho} = 0.924 vs. 0.604; R{superscript 2} = 0.815 vs. 0.470). DLNM incorporating the wastewater signal explained substantially more variance in test-adjusted than crude reported cases (McFadden pseudo-R{superscript 2} 0.898 vs. 0.776), despite similar lag-response structure for both outcomes. ConclusionsWastewater surveillance provides compelling independent validation of a previously described test adjustment methodology for COVID-19 case surveillance. The agreement between wastewater signals and test-adjusted cases was strongest precisely when testing scarcity was most severe, supporting the use of test adjustment to recover accurate infection dynamics from case surveillance data during periods of changing testing access and policy.

Canadas ambition for mineral security and its responsibilities to protect at-risk species and uphold Indigenous rights clash in the case of the Grays Bay Road and Port (GBRP) in Nunavut, an infrastructure project intended to unlock critical mineral deposits. We compiled Indigenous and Western science through a density analysis of caribou harvesting data near the proposed project site. We identified three consistently used harvesting hotspots, with the most significant hotspot lying directly in the path of the proposed GBRP project. These results indicate that the GBRP project will have significant and unmitigable negative effects on caribou conservation, food security, and Inuit harvesting rights. Prime Minister Carney claims that middle power countries must act consistently in this era of geopolitical rupture; this commitment must transfer to natural resource development reviews so that decision-making may be consistent and rooted in cross-legislation responsibilities and values, including the land claims agreements between Indigenous groups and the Government of Canada.

BackgroundIncomplete dissemination of clinical trial results remains an important challenge for research transparency and evidence synthesis. Although prior studies have quantified the overall extent of non-dissemination, less is known about whether trial characteristics observable at registration are associated with subsequent dissemination within sponsor portfolios. Methods and findingsWe conducted a retrospective cohort study of 17,537 completed interventional clinical trials registered on ClinicalTrials.gov between 2007 and 2024 across the 20 largest global pharmaceutical companies. We developed the Operational Complexity Index (OCI), a composite measure derived from planned enrollment, facility count, and geographic scope, and examined its association with trial dissemination using multivariable logistic regression and time-to-event analyses. Higher OCI was associated with greater odds of dissemination (adjusted odds ratio [aOR] = 2.40, 95% CI 2.23-2.60; p < 0.001), with dissemination increasing from 47% in the lowest OCI decile to 95% in the highest. Higher operational complexity was also associated with earlier dissemination; over a 1,095-day horizon, high-OCI trials were disseminated a mean of 310.88 days earlier than low-OCI trials (RMST difference, 310.88 days; 95% CI 300.59-320.96; p < 0.001). This pattern was observed across sponsors, clinical phases, and therapeutic areas. In predictive analyses using registration-time variables, the structural model achieved a cross- validated AUC of 0.816 and a holdout AUC of 0.814, whereas the full model, including sponsor identity, achieved a cross-validated AUC of 0.858 and a holdout AUC of 0.857. Using benchmark phase-based costing assumptions, the 5,019 non-disseminated trials corresponded to an estimated US$10.94-15.26 billion in sunk research investment. ConclusionsAmong trials conducted by the 20 largest pharmaceutical sponsors, greater operational complexity at registration was associated with a higher likelihood of dissemination and earlier dissemination. These findings suggest that aggregate sponsor-level transparency metrics may mask important heterogeneity within sponsor portfolios. Future work should assess whether registration-time trial characteristics can help identify trial subgroups at higher risk of non-dissemination. AUTHOR SUMMARYO_ST_ABSWhy was this study done?C_ST_ABSO_LIIncomplete dissemination of clinical trial results reduces the completeness of the medical evidence base and the public value of research participation. C_LIO_LIPrevious studies have described overall rates of trial non-dissemination, but less is known about whether dissemination varies systematically across different types of trials within sponsor portfolios. C_LIO_LIWe examined whether trial characteristics available at registration were associated with later dissemination of results among large pharmaceutical sponsors. C_LI What did the researchers do and find?O_LIWe analyzed 17,537 completed interventional clinical trials sponsored by the 20 largest pharmaceutical companies and registered on ClinicalTrials.gov between 2007 and 2024. C_LIO_LIWe developed an Operational Complexity Index (OCI) based on planned enrollment, number of facilities, and geographic scope to measure trial operational scale at registration. C_LIO_LIHigher OCI was associated with a greater likelihood of dissemination and earlier dissemination. Dissemination ranged from 47% in the lowest OCI decile to 95% in the highest. C_LIO_LIThis pattern was observed across sponsor portfolios, clinical phases, and therapeutic areas, with an average within-sponsor dissemination gap of 40 percentage points between lower- and higher-complexity trials. C_LIO_LIIn manual validation of 344 sampled trials, the automated dissemination-classification pipeline achieved 92.1% accuracy. C_LIO_LIUsing benchmark phase-based costing assumptions, the 5,019 non-disseminated trials corresponded to an estimated US$10.9-15.3 billion in sunk research investment. C_LI What do these findings mean?O_LIDissemination was not uniform across trial types within sponsor portfolios; trials with lower operational complexity were less likely to be disseminated than trials with higher operational complexity. C_LIO_LIAggregate sponsor-level transparency measures may therefore miss important differences within portfolios. C_LIO_LIRegistration-time trial characteristics showed predictive signal for non-dissemination, but whether such information could support monitoring strategies would require prospective validation. C_LIO_LIMore complete dissemination of trial results would strengthen the scientific record and improve the public value of clinical research. C_LI

Peer reviewers provide a critical service to NIH by evaluating the scientific and technical merit of grant applications. While the tangible rewards for this service are limited, many reviewers feel review service makes them better applicants, improving their grant competitiveness. However, empirical evidence for this claim is limited. This study evaluates relationships between early career peer review service and subsequent application behavior and funding outcomes. Using NIH administrative data, applicants who served as Early Career Reviewers (ECRs) during the 2020 - 2021 council years were compared to a matched group of ECR-eligible applicants who had not served as reviewers (n=1,120 per group). To address non-random selection of ECRs, propensity score matching was used to balance groups on research field, demographics, productivity, career stage, and institutional resources. Outcomes, assessed over a three-year follow-up period, included submission volume, peer review scores, and funding outcomes for R01 and R01-equivalent applications. ECRs submitted more applications, were more likely to have their applications discussed, and were more likely to receive a high review score than matched controls. They were also more likely to receive R01 funding. While peer review scores do not solely determine award outcomes, these findings indicate that peer review service among ECRs is associated with improved grant application outcomes.

Wastewater-based surveillance (WBS) is increasingly used to monitor infectious disease dynamics, yet most evaluations focus on correlation or forecasting - neither of which directly assesses whether wastewater signals can identify the epidemiological events most relevant to public health decision-making. We argue that outbreak onset and epidemic peak detection are the operationally critical use cases of WBS, requiring a fundamentally different evaluation framework. We introduce a classification-based framework that treats WBS as an event-detection problem, defining outbreaks and peaks as discrete events, establishing detection intervals to account for timing uncertainty, and incorporating censoring and data completeness criteria for valid comparisons against imperfect clinical reference outcomes. Within this framework, we apply a Bayesian exponential growth model for outbreak detection - benchmarked against a standard reproductive number (Rt)-based method - and a rule-based algorithm for peak detection, evaluating performance via sensitivity and positive predictive value (PPV). Applied to county-level SARS-CoV-2 wastewater data from 281 U.S. counties (Biobot, 2021-2024), the exponential growth approach substantially outperforms the Rt-based baseline: sensitivity 0.82 and PPV 0.64 versus sensitivity 0.58 and PPV 0.19 for the best-performing Rt variant. Peak detection achieves sensitivity 0.84 and PPV 0.70 at the county level. Both peak and outbreak detection achieve strong and consistent performance against hospitalizations and deaths at the state level. Spatial aggregation yields a statistically significant improvement in peak detection PPV against a curated reference standard ($p < 0.001$), while outbreak detection improvements under aggregation are directionally consistent but not statistically significant. Wastewater leads case-defined outbreaks by 4-6 days but minimally leads epidemic peaks, consistent with wastewater approximating prevalence rather than incidence. These findings demonstrate that wastewater signals can reliably detect outbreak onset and epidemic peaks across spatial scales and clinical outcomes, and that the choice of detection method matters substantially in practice. The classification framework developed here provides a reusable and principled tool for evaluating any surveillance signal as an event-detection system, with direct relevance to how WBS is actually used in public health decision-making.

If youve ever complained about a species name thats a mouthful--say, the soldier fly Parastratiosphecomyia stratiosphecomyioides or the myxobacterium Myxococcus llanfairpwllgwyngyllgogerychwyrndrobwllllantysiliogogogochensis--youre in very good company. But could the readability of binomial scientific names cause more than complaints? Could it influence how much species are studied and talked about? We examined a random sample of 3,019 species names spanning 29 phyla/divisions. We tested whether name length and reading difficulty are associated with species representation in the scientific literature (measured via literature mentions) and their visibility to the public (measured via Wikipedia pageviews). Both species name traits showed significant negative relationships with literature mentions and Wikipedia reads. Increasing name length from 10 to 30 characters is associated with a 66% decrease in expected mentions and a 65% decrease in Wikipedia reads, while shifting from the most to the least readable name in the dataset corresponds to 53% and 76% decreases. These patterns are consistent with something familiar: the fickleness of human attention, responding to features of the world that are far from rational. While creativity in naming is a cherished part of taxonomy, a touch of orthographic restraint may ultimately benefit both science and the species themselves--especially among understudied uncharismatic taxa.

Objectives: To assess the availability of key clinical trial registration data and compliance with legal reporting requirements for all Phase 2-4 drug trials registered on the new European Clinical Trial Information System (CTIS) registry. This study is the first ever assessment of data quality and legal compliance with reporting requirements on CTIS. Design: Cross-sectional observational study of CTIS registry data combined with manual review of results documents. Setting: Cohort of all 7,547 Phase II-IV clinical trials registered on CTIS as of November 2025. Main outcome measures: Number and proportion of missing data points in CTIS registration data. Proportion of completed clinical trials that are compliant with regulatory reporting requirements. Results: Trial registration data quality was high overall with more than 99% of expected data present. Of 234 clinical trials legally required to report results, fewer than half (49.6%) fully reported results within the required timeframe, 20 trials (8.5%) fully reported results late, and 98 trials (41.9%) failed to fully report results. Legal compliance was similar for adult trials (79/158) and paediatric trials (37/76). Conclusions: Sponsor compliance with legal reporting requirements is weak. Current efforts by European regulators to monitor and enforce compliance appear to be insufficient. New results reporting functions currently being set up by trial registries worldwide will require quality assurance processes. Trial registration: Study protocol prospectively registered on OSF: https://osf.io/sn4j2/overview

We developed a model to predict surface water temperature across U.S. lakes using satellite remote sensing and in situ observations to enhance cyanobacterial harmful algal bloom (cyanoHAB) forecasting. The study focused on Sentinel-3 Ocean and Land Colour Instrument (OLCI) sensor resolved lakes. We developed random forest models using both Landsat-derived and in-situ-measured surface water temperature. Landsat models offered broad spatial and temporal coverage of all OLCI resolved lakes, but they were sensitive to cloud cover and required filtering to minimize error. In contrast, the in situ model represented fewer OLCI resolved lakes, but yielded lower mean absolute error and bias. The models predicted lake surface temperature across the entire calendar year, with best performance (RMSEapplied=1.11; biasapplied=0.01; MAEapplied=0.77) from the in situ model. This approach allowed for the continuous prediction of lake surface temperatures from 1.1 to 31.6 {degrees}C for unfrozen, open-water conditions critical for improving the accuracy of cyanoHAB forecasting. A key strength of this study was the use of an extensive dataset and model validation against in situ observations, which improved predictive accuracy throughout the year across all seasons. The predictive model offers a water resource tool for management, ecosystem protection, and public health.

ImportanceFunding of womens health research has been low, with a narrow focus on what is considered womens health. Understanding which lifespan stages and areas of womens health are funded is essential to determine the breadth of womens health research and identify where gaps in research are concentrated. ObjectiveTo examine which lifespan stages and areas of womens health were more likely to be funded in open Canadian grant competitions. Evidence ReviewPublicly available funded Canadian Institutes of Health Research (CIHR) Project Grant abstracts from 2009 and 2023 were coded for mention of a hormonal transition period (puberty, menstrual cycle, pregnancy/postpartum, perimenopause/menopause), exogenous hormone use (hormonal contraception, fertility treatments, menopause hormone therapy), and/or a female-specific health condition. Abstracts were also coded for Indigenous health and Two Spirit, Lesbian, Gay, Bisexual, Trans, Transgender or Trans Identified, Queer, Intersex, Asexual, Plus (S2/LGBTQIA+) populations. Remaining grant abstracts were grouped by common theme.Abstracts were analyzed for changes in research representation and funding over time and whether funding was lower than expected based on population prevalence or proportion of the lifespan spent in that stage. FindingsNearly 50% of female-specific research focused on cancers (breast, gynecologic) or pregnancy and did not significantly increase in funding or representation over time. Of the funded grant abstracts that focused on pregnancy, ~22% examined outcomes pertaining only to the fetus/offspring, not the birthing parent. Over 15 years, 2.37% of all CIHR abstracts over 15 years were devoted to pregnancy, whereas only 0.24% was devoted to other hormonal life stages (menstrual cycles, menopause). For all hormonal transition stages except pregnancy, the proportion of grants and funding devoted to that stage was lower than expected based on the proportion of the lifespan spent in that stage. Conclusions and RelevanceThese findings reflect the narrow breadth of womens health, which largely focused on cancers (breast, gynecologic) or pregnancy, rather than being distributed across key life course stages that shape womens health. To advance science for all, the heterogeneity and complexity in womens health across the lifespan must be embraced and barriers for womens health research must be removed. Key PointsO_ST_ABSQuestionC_ST_ABSWhich areas and life stages of womens health are most likely to be funded in Canadian open grant competitions, and where are funding gaps concentrated? FindingsNearly half of female-specific grants focused on cancer or pregnancy, with little change over time. Pregnancy dominated hormonal-stage research, often excluding maternal outcomes, while menstrual and menopausal stages were rarely funded. For most life stages, funding was lower than expected based on lifespan representation. MeaningWomens health research funding remains narrowly focused. Broader, life-course-inclusive investment is needed to address critical gaps and advance equitable health science.

Objective: To estimate the adjusted relative risk (RR) of administrative grant disruption faced by first-time and mechanism-first principal investigators (PIs) during the 2025 National Institutes of Health (NIH) grant disruptions. Design: Retrospective cohort study linking NIH RePORTER data to a publicly curated registry of grants disrupted in 2025. Setting: All NIH active research grants in fiscal years 2024 to 2025. Participants: 80,976 active projects: 4,961 disrupted during the wave that peaked in May 2025, 76,015 non-disrupted controls. Main outcome measures: Adjusted RR of disruption by two pre-specified first-time PI constructs: absolute first-time PI (no prior NIH grant) and mechanism-first PI (no prior NIH grant with the same activity code). Modified Poisson regression with institution-clustered standard errors adjusted for project, institutional, and geographic covariates. A pre-specified fiscal year 2024 common-anchor analysis addressed year-of-disruption confounding. Results: Of 4,961 disrupted grants, 237 (4.8%) had an absolute first-time PI and 396 (8.0%) had a mechanism-first PI. After adjustment, absolute first-time PIs faced 77% elevated risk of disruption (RR 1.77, 95% CI 1.34 to 2.32) and mechanism-first PIs faced 57% elevated risk (RR 1.57, 1.16 to 2.11). Under the common-anchor analysis, the absolute first-time effect attenuated to RR 1.22 (0.95 to 1.58); the mechanism-first effect persisted (RR 1.48, 1.07 to 2.06). The elevated risk was concentrated in research-mechanism grants (RR 1.78, 1.26 to 2.52) and was robust across 8 of 9 pre-specified sensitivity analyses. The Track A start-time construct, which asks whether the disrupted project was the PI's debut grant, yielded null estimates (RR 0.98, 0.93 to 1.04), with any effect concentrated entirely in newly started projects. Conclusions: First-time and mechanism-first PIs faced disproportionately elevated risk of disruption during the 2025 NIH wave, concentrated in research-mechanism grants and robust to year-confounding-free identification. The relevant exposure was being early-career at the moment of administrative action, not at project initiation. The findings have direct implications for workforce equity in US biomedical research.

BackgroundImplementing proven vehicle safety standards recommended by the UN World Forum for Harmonization of Vehicle Regulations is among the most cost-effective strategies to reduce road traffic deaths. In 2022, Mexico approved updated vehicle safety standards, including side pole testing, electronic stability control, seatbelts, airbags, side structures, and anchorage child restraint systems. However, pedestrian protection and advanced driver-assistance technologies, such as autonomous emergency braking systems (AEBS), were excluded. These exclusions are critical, given that more than half of road traffic deaths involve vulnerable road users. Local evidence on the expected benefits of implementing comprehensive vehicle safety standards is needed to guide policy decision-making. ObjectiveTo estimate the potential public health impact of increasing the availability of recommended vehicle safety technologies in Mexico. MethodsWe conducted a comparative risk assessment analysis to estimate the impact of improving vehicle safety standards on road traffic deaths, injuries, and disability-adjusted life years. Counterfactual analyses were defined using traffic statistics for 2019 as baseline, relative risk estimates associated with each safety technology, and technology penetration within Mexicos vehicle fleet. Three scenarios were modeled: (1) full implementation of Mexicos 2022 standards; (2) addition of crashworthiness, AEBS, and motorcycle ABS/ESC; and (3) inclusion of expanded AEBS crash configurations, lane departure warning (LDW), and lane keeping assistance (LKA) systems. ResultsScenario 1 reduced deaths by 18%, injuries by 16%, and DALYs by 18%, with the greatest benefits for car occupants. Scenario 2 reduced deaths by 29%, injuries by 27%, and DALYs by 30%, benefiting motorcyclists and pedestrians the most. Scenario 3 reduced deaths, injuries, and DALYs by 41%, 38%, and 41%, respectively, benefiting car occupants and motorcyclists. ConclusionsCurrent vehicle safety standards in Mexico are expected to reduce deaths, injuries, and disabilities, yet existing guidelines focus largely on protecting car occupants. Mexico should strive to update and strengthen its current legislation by adding technologies that protect vulnerable road users, such as pedestrians and cyclists, and to focus on technologies for motorcycle users to further reduce the burden of road traffic injuries.

BackgroundPseudomonas aeruginosa is a major cause of healthcare-associated infections in paediatric settings, where its persistence in moist environments such as hospital water and wastewater systems poses a particular risk to neonates and immunocompromised children. AimThe aim of this study was to showcase the long-term survival and transmission of P. aeruginosa in a large tertiary childrens hospital in England which is crucial to develop strategies for water-safe care. MethodsEnvironmental P. aeruginosa isolates were collected from taps, sinks, showers, and baths in augmented care areas of a 330-bed tertiary childrens hospital built to NHS water-safety standards. Clinical isolates were classified as invasive (blood, cerebrospinal fluid, and bronchoalveolar lavage) or non-invasive (respiratory, urine, ear, abdominal, and rectal surveillance). Variable number tandem repeat (VNTR) profiles and metadata were extracted from PDF reports, de-identified, deduplicated, and curated using Python and R. FindingsThis retrospective study analysed nine-locus VNTR profiles of 457 P. aeruginosa isolates submitted to the UK Health Security Agency from a large tertiary childrens hospital, identifying 56 isolate clusters (each with [&ge;]2 isolates), of which 19 (34%) contained at least one invasive isolate. The most persistent cluster (Cluster 1, n=20) spanned from July 2016 to September 2024, containing environmental and clinical (invasive and non-invasive) isolates. ConclusionThese findings demonstrate long-term persistence of certain genotypes and temporal overlap between environmental and clinical isolates, highlighting the difficulty in detecting and eradicating P. aeruginosa in hospital water and wastewater systems and reinforcing the need for continuous rigorous water system controls.

The prevalence of nitrogen limitation and nitrogen-phosphorus co-limitation (henceforth referred to as nitrogen-related limitation) in Norwegian lakes and their relationships with atmospheric nitrogen deposition, climate, dissolved organic matter (DOM), and catchment characteristics were assessed across space and time. Routine monitoring data from 1,529 lakes in the national Vannmiljo database were analyzed for two multi-year periods (1995-2009 and 2010-2025). Limitation was inferred using the molar NO--N/TP ratio as an indicator of dissolved inorganic nitrogen availability. Nitrogen-related limitation was widespread in both periods and exhibited strong regional structure, with highest prevalence in northern regions and lowest prevalence in southwestern Norway. Overall prevalence increased from 31% to 38% between periods, with significant increases in western regions. Regional-scale models identified climate, forest cover, DOM, agriculture, and atmospheric nitrogen deposition as predictors of limitation probability, whereas study period per se and bog/peatland cover were not significant. At the local scale, atmospheric nitrogen deposition and DOM were the only consistent predictors, with substantially lower explanatory power than at the regional scale. These results indicate that large-scale environmental gradients play a major role in shaping nutrient stoichiometry in Norwegian lakes. Because the monitoring dataset primarily represents lakes affected by human activities, the findings are particularly relevant for water management. The widespread occurrence of nitrogen-related limitation suggests that nitrogen availability may influence phytoplankton growth in many systems and that dual-nutrient management strategies addressing both nitrogen and phosphorus may be required in many regions.

Understanding how warming alters estuarine plankton communities is essential for predicting future changes in biodiversity and ecosystem functioning. We conducted a four-week indoor mesocosm experiment using natural summer plankton from the Elbe River to examine the effects of warming (+2 {degrees}C and +4 {degrees}C) on abiotic conditions and responses of the plankton community. In this study, oxygen concentrations, primary producer biomass (chlorophyll a, microphytoplankton) and microzooplankton abundances declined sharply during the first 10 days across all treatments while mesozooplankton abundances increased. This suggests a strong top-down control by mesozooplankton on lower trophic levels across all temperature treatments. Primary producers biomass and oxygen concentrations recovered after an initial decline, however to lower levels compared to the onset of the experiment while micro- and mesozooplankton remained low during the second half of the experiment. Nutrient dynamics indicated progressive remineralization, with increasing ammonium, NOx, and silicate concentrations, while phosphate concentrations remained low throughout the experiment. Complementary DNA and RNA metabarcoding revealed similar community turnover over time in all treatments and temperature effects became only pronounced at the end of the experiment. Overall, warming effects were subtle relative to the strong internal trophic dynamics likely caused by the artificial mesocosm setup. Our findings of changes in plankton community dynamics indicate that biotic interactions, changes in trophic diversity and other environmental factors, i.e. oxygen concentrations are likely the drivers of this estuarine system rather than warming alone.

ObjectivesTo evaluate the effect of surgical hubs on the volume of surgeries, patient waiting times, and length of hospital stay for elective hip and knee replacements in the English NHS. DesignA retrospective longitudinal study using a difference-in-differences approach to compare changes in outcomes at NHS trusts that opened surgical hubs with those that did not. SettingThe study was set in the English NHS, using administrative data from NHS acute trusts providing elective hip and knee replacements between April 2014 and September 2024. ParticipantsThe study included 76 NHS trusts. The treatment group consisted of 29 trusts that opened a surgical hub for trauma and orthopaedic surgery during the study period. The control group consisted of 47 trusts that did not. 48 trusts that performed fewer than 1,000 relevant procedures over the ten-year period or that reported data for fewer than 41 of the 42 quarters in the sample period were excluded. InterventionThe phased introduction of surgical hubs dedicated to elective procedures at 29 NHS trusts between Q1 2020 and Q3 2024. Main outcome measuresThe three main outcomes were, measured at the trust-quarter level: the total number of elective primary hip and knee replacements (surgical volume), the average length of stay in hospital, and the average waiting time from being added to the waiting list to hospital admission. ResultsThe opening of a surgical hub was associated with an increase of 43.75 hip and knee replacement surgeries per quarter (95% CI: 22.22 to 65.28), which represents a 19.1% increase compared to the pre-hub mean. Length of stay was reduced by 0.32 days (95% CI: - 0.48 to -0.16), a 7.8% reduction. There was no statistically significant effect on average waiting times (-14.96 days, 95% CI: -33.11 to 3.19). ConclusionsSurgical hubs appear to be effective at increasing the number of hip and knee replacements and reducing the time patients spend in hospital. However, in this study, they did not lead to a statistically significant reduction in waiting times overall.

BackgroundRandomized controlled trials (RCTs) often have incomplete methods reporting despite widespread adoption of the CONSORT guideline. The editorial process is supposed to detect these shortcomings and request clarifications from authors, which is time-consuming. We developed an LLM-based CONSORT Rohe Nordberg Report that highlights which CONSORT items appear fully or partially reported and checks page references claimed by authors, and then creates follow up questions for authors to more easily correct missing information. MethodsThis parallel-arm, superiority RCT will randomize eligible RCT submissions (after desk screening) 1:1 into intervention (editorial team and authors receive the Rohe Nordberg Report) or control (standard editorial review only). The primary outcome is whether manuscripts improve their reporting of CONSORT items in the Methods and Results sections between the original submission and first revision. This will be assessed by blinded human reviewers who evaluate the textual changes for improvements between the original and revised manuscripts for each relevant CONSORT item. Secondary outcomes include time to editorial decisions, rejection and non-resubmission rates, if authors can correctly identify where CONSORT items are reported, and extent of revisions. Human evaluators will be blinded to whether the manuscript was in the intervention or control group. DiscussionBy providing authors and the editorial team with specific follow up questions for each underreported CONSORT item, we hypothesize that basic underreporting will be more efficiently detected and corrected. Using blinded human reviewers as the primary outcome assessors ensures a rigorous, unbiased evaluation. If successful, this approach may help align manuscripts more closely with CONSORT standards, ultimately benefiting evidence synthesis. Trial Registration[To be registered prior to enrollment; e.g., ClinicalTrials.gov or ISRCTN] 1. Administrative Information1.1 TitleLLM-Generated CONSORT Rohe Nordberg Report for Increased Reporting: Protocol for a Parallel-Arm Randomized Controlled Trial. IRB registered name: LLM-Generated CONSORT Report Phase III Trial 1.2 Trial RegistrationThis trial will be registered before enrollment commences in a publicly accessible registry (e.g., ClinicalTrials.gov or ISRCTN). The trial identifier will be inserted here upon registration. All items from the World Health Organization Trial Registration Data Set will be provided at the time of registration, including: primary registry and trial ID, date of registration, secondary IDs, source of funding, contact for public and scientific queries, title, research ethics review, study design, study setting, interventions, eligibility criteria, primary outcome, key secondary outcomes, target sample size, recruitment status, and results dissemination plan. 1.3 Protocol VersionVersion 1.0 26 March 2026 [Subsequent amendments will be tracked by version number, date, and a summary of changes.] 1.4 FundingOpen Philanthropy, grant title "From Manual to Machine: Validating and Scaling LLM-Based CONSORT Compliance Assessment for Evidence-Based Medicine Publishing" Participating journals provide in-kind editorial resources (staff time, system access) to facilitate trial conduct. 1.5 Roles and ResponsibilitiesO_ST_ABSProtocol contributorsC_ST_ABSAuden Nordberg Krauska (University of Wisconsin-Madison; krauska@wisc.edu): conceived the study design, wrote the initial protocol draft Karl Rohe (University of Wisconsin-Madison): primary investigator, co-developed the LLM-based CONSORT and RoB 2 systems Gary Collins (University of Birmingham): senior methodologist, contributed to trial design and statistical analysis plan Sara Schroter (British Medical Journal): research editor, contributed to trial design and implementation plans Hyunseung Kang (University of Wisconsin-Madison): aided in statistical analysis plan Trial sponsorUniversity of Wisconsin-Madison, Department of Statistics, 1300 University Avenue, Madison, WI 53706. Role of sponsor and fundersThe research team leads trial design, data collection, analysis, interpretation, and reporting. The sponsor and funders have no role in data collection, management, analysis, interpretation of data, writing of the report, or the decision to submit the report for publication. The funder provides financial support only. Participating journal editorial teams are consulted for feasibility and operational feedback but do not have authority over data analysis or reporting. Trial oversight groupsThe trial will be coordinated by Karl Rohe and Auden Nordberg Krauska (University of Wisconsin-Madison), with methodological input from Gary Collins (University of Birmingham). Day-to-day operations, including manuscript tracking, diff file preparation, and data management will be carried out by Auden Nordberg Krauska and trained undergraduate research assistants at UW-Madison. Sara Schroter, Research Editor at The BMJ, will facilitate integration with the journals editorial workflow and monitor recruitment progress. This group will meet as needed to review trial progress and resolve operational issues.

Background and ObjectivesPatient portals have become essential infrastructure for healthcare delivery following the 21st Century Cures Act, yet adoption remains inequitable. Understanding demographic and geographic determinants of portal activation is critical for addressing digital health disparities, particularly among neurology patients who face unique access barriers. We examined the demographic, geographic, and neighborhood-level factors associated with patient portal activation among neurology patients at multiple geographic scales in the Washington, DC metropolitan area. MethodsWe conducted a retrospective cohort study of 72,417 adult neurology patients seen at two academic medical centers sharing an electronic health record in Washington, DC (February 2021-February 2026). We examined portal activation using multivariable logistic regression and geographic analysis at four nested scales: the metropolitan catchment area, DCs eight wards, individual census tracts (via geocoded patient addresses), and individual DC residents. ResultsPortal activation was 64.7% overall. Activation varied by race/ethnicity (Non-Hispanic White 76.1%, Non-Hispanic Black 57.0%, Non-Hispanic Asian 57.6%, Hispanic 55.0%) and geography (DC Ward 2: 82.0% vs. Ward 7: 48.0%). Ward-level educational attainment (r = 0.948), broadband access (r = 0.889), and income (r = 0.811) were strongly correlated with activation. Within individual wards, Non-Hispanic White patients activated at 84-91% while Non-Hispanic Black patients activated at 48-64%, demonstrating that neighborhood resources alone do not explain disparities. DiscussionPatient portal activation is shaped by demographic, socioeconomic, and geographic factors operating at multiple levels. Persistent within-ward racial disparities indicate that geographically targeted interventions must be paired with culturally tailored approaches to achieve digital health equity.

Motivation: Viral surveillance from mixed samples (e.g. wastewater) has become critical in public health efforts to track and contain pathogens. However, existing open-source bioinformatics tools for viral consensus sequence generation are optimized for individual viruses (rather than multiple potential viruses of interest). Results: MultiVirusConsensus is an accurate and efficient open-source pipeline for identification and consensus sequence generation of multiple viruses from mixed samples. It utilizes the memory-efficient ViralConsensus tool via bash process substitution to simultaneously perform consensus sequence calling on all viruses of interest (1) completely in parallel, and (2) by piping datastreams between tools without writing/reading intermediate files (thus eliminating slowdowns related to slow disk accesses). Availability: MultiVirusConsensus is freely available as an open-source software project at: https://github.com/niemasd/MultiVirusConsensus

Research using model organisms to tackle questions in life sciences and biomedical sciences has been in the spotlight of scientific literature for the better part of the twentieth century. This attention has perceptibly faded over the last twenty years, at least. We set to document this process by examining the publication trends of 48 journals encompassing a broad range of topics and impact factors for eight classic model organisms. We found that the representation of model-organism research has been in continuous decline in the last three decades, with a significant acceleration since 2010. We investigated the origin of the change, from the size of research communities to the shifts in topics and in use of model organisms. While model organism communities appear stable, model organism papers are outpaced by the rest of scientific literature. Also, among papers using model organisms, we note a progressive shift toward applied research, with differences between different model organism species. The mouse, in particular, logically remains the preferred system to study diseases, while non-mouse model organisms continue to be used predominantly to dissect mechanisms of life. We reflect on the consequences of the fading representation that we measured for the future of life sciences. Fundamentally, model organisms afford a direct access to causality in life sciences and their fading from the picture may impact life sciences as a whole. More pragmatically, it will also affect funding, and thereby jeopardizes the maintenance of model organism resources such as repositories built over decades.