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.

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

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

India's national research capacity and infrastructure are unevenly distributed across states and union territories (UTs), contributing to geographic variation in academic publication output. We developed Indiapub, an open-access web application that quantitatively enumerates and visually displays geographic and temporal publication patterns for research products with at least one author affiliated with an Indian institution, using OpenAlex data. The app is designed for ease of use, with automated data retrieval, cleaning, and aggregation. Indiapub allows users to filter publications by topic, publication year range, author position, publication type, minimum citation count, state/UT, and population size of the state/UT where the author institution is located. The app also provides downloadable tables and ranked institution lists by publication count. Its interactive dashboard includes five modules: (i) a map of publication distribution, (ii) time trend plots for nation and state/UT, (iii) publication-share versus population-share plots highlighting over- and underrepresentation, (iv) stacked bar charts of state/UT contributions over time with population benchmarks, and (v) bubble plots relating the Human Development Index to publication volume over time. This tool may support resource prioritization and identification of institutional strengths for trainees, researchers, higher education administrators, and policymakers. To illustrate its utility, we present sample findings derived from the app. For publications across all topics from 2014 to 2025, the largest research participation footprints were observed in Tamil Nadu, Maharashtra, Delhi, Uttar Pradesh, and Karnataka. Tamil Nadu and Delhi were home to three of the highest-publishing institutions nationally: Vellore Institute of Technology, All India Institute of Medical Sciences, and Indian Institute of Technology Delhi. We also examined six curated case studies of broad scientific interest: electronic health records (EHR), genome-wide association studies (GWAS), artificial intelligence (AI), development economics, environmental science, and COVID-19. Findings from these case studies revealed over- and underrepresentation in publication output across states and UTs. For example, in EHR publications among high-population states, Tamil Nadu's publication share exceeded its population share by 31.3 percentage points (pp), whereas Bihar's was 12.8 pp lower. Our tool offers insights into India's research landscape across states and UTs with easy-to-digest visuals. Such interactive tools have the potential to serve as a starting point for fostering a more inclusive research ecosystem supporting targeted research policy and planning.

The rising demand for outdoor recreation worldwide may be undermining the conservation objectives of protected areas (PAs). We leveraged a natural experiment, in which two adjacent PAs were closed to the public for different durations during the COVID-19 pandemic. Using detections from 39 camera traps in Joffre Lakes and Garibaldi Parks, Canada, from 2020-2022, we examined how recreation influenced mammal habitat use and diversity. Bayesian regression showed weak evidence that, when recreation was higher, detections declined for black bear, mule deer, and marten, while detections of bobcat and hoary marmot shifted closer to trails. Accumulation curves revealed that species richness and diversity were higher in the closed vs. open PA in 2020 (mean differences of -5.04 for richness and -0.33 for Shannon diversity). However, diversity did not decline consistently despite increases in recreation in 2021 and 2022. Notably, several rare species were only detected in the lower-recreation PA, suggesting they may be filtered out of the higher-recreation PA. This emphasizes the need for long-term monitoring to detect delayed and cumulative effects of recreation on mammal communities. Given growing global pressures on biodiversity, we urge PA managers to prioritize adaptive management to assess and balance outdoor recreation with conservation goals.

Effective monitoring of the critically endangered European eel (Anguilla anguilla) is essential for conservation planning and regulatory decision-making, particularly in heavily fragmented rivers. Environmental DNA (eDNA) methods offer sensitive alternatives to traditional surveys, but there is uncertainty around whether targeted assays or community-wide approaches are better suited to achieve monitoring objectives. We compared eDNA metabarcoding and species-specific quantitative PCR (qPCR) for detecting A. anguilla across 145 pumped catchments in the Fens, East Anglia, England. All sites were sampled once initially, and sites negative for A. anguilla were re-sampled based on metabarcoding results. This allowed comparison of detection rates from a single water sample and site-level retrospective identification of sites where qPCR could have identified A. anguilla in earlier samples. The findings were also set in the context of the wider biodiversity information generated by metabarcoding. From the initial (single) water sample, qPCR detected A. anguilla at seven more sites than metabarcoding (17 versus 10). With repeated sampling, metabarcoding detected A. anguilla at 43 sites, including all but one of the sites where qPCR detected A. anguilla, and ten sites where qPCR did not detect A. anguilla within the same number of samples. Indeed, the additional sampling effort required to detect A. anguilla with metabarcoding at sites also positive with qPCR was small relative to the overall sampling effort. Furthermore, metabarcoding additionally detected 28 non-target fish species alongside fish, amphibian and mammal species of conservation concern. Our results highlight trade-offs between target-species sensitivity and the broader ecological information provided by each method, and support metabarcoding as an effective tool for a holistic conservation approach, with the additional community data outweighing the marginally increased sensitivity of qPCR.

O_LISubmerged macrophytes are central to freshwater ecosystems functioning but are declining globally under multiple anthropogenic stressors. We aimed to identify general patterns in physiological responses and interaction types, and to assess whether a mechanistic understanding of stressor interactions can be developed from published evidence. C_LIO_LIWe systematically reviewed 12,858 records, identified 172 relevant papers, and extracted effect sizes from 124 experiments included in the meta-analysis. C_LIO_LIMost studies examined combinations of nutrient enrichment, shading, toxic trace metals, warming, and emerging contaminants such as PFAS and microplastics, typically under simplified 2 x 2 factorial laboratory designs. Additive effects dominated (50%), while synergistic interactions were relatively infrequent (14%). Antagonistic interactions often reflected dominance of a single stressor or compensatory responses, whereas synergisms were most frequent with metals combined with co-stressors enhancing bioavailability. C_LIO_LIOur synthesis suggests that accumulated stressors cause negative, but not necessarily amplified, responses, although the limited number of experiments testing more than two stressors means synergistic effects may be underestimated. We propose Stuckenia pectinata as a model organism because of its cosmopolitan distribution, experimental tractability, and available genomic resources, and argue that expanding stressor complexity, duration, and taxonomic breadth will strengthen predictions of macrophyte responses and inform freshwater conservation under global change. C_LI

Objective To map the presence, public availability, and content of clinical trial data sharing policies (DSP), data management and sharing plans (DMSP), and data use agreements (DUA) among the most prolific public and private clinical trial sponsors operating in the European Union, and to identify key areas of convergence, divergence, and constraint in the context of General Data Protection Regulation (GDPR). Eligibility criteria We included organisation-level documents describing approaches to clinical trial data sharing or data management from the top 20 public and top 20 private sponsors ranked by the number of trials registered in the EU Clinical Trials Information System (CTIS). Eligible materials comprised publicly available or sponsor-shared policies, guidelines, statements, templates, and agreements relevant to clinical trial data sharing or management. Sources of evidence Evidence was identified through systematic searches of sponsors' public websites, structured Google searches, and major data management plan platforms (DMPTool, DMPonline, DMP Assistant), complemented by direct contact with sponsors to verify findings and request missing documentation. All sources were archived and catalogued. Charting methods Two reviewers independently extracted data using a structured form, capturing the existence, accessibility, and content of data sharing policies, data management and sharing plans, and data use agreements. Quantitative data were summarised descriptively, and a non-interpretive descriptive content analysis was conducted to characterise recurring policy elements and areas of heterogeneity. Results Among 40 sponsors, private sponsors were substantially more likely than public sponsors to make trial-specific data sharing policies and data use agreements publicly accessible, often via established data sharing platforms. Public sponsors more frequently referenced data management and sharing plans, but these were heterogeneous in scope and often embedded within broader institutional governance documents rather than tailored to clinical trials. Across sectors, GDPR compliance, data protection, and legal safeguards were emphasised, while operational aspects such as dataset readiness, review criteria, and downstream responsibilities varied widely. Overall response rate to sponsor verification was 37.5%. Conclusion Clinical trial data sharing governance in the EU shows a marked sectoral imbalance among the top sponsors. Private sponsors tend to provide more detailed and operationally explicit documentation, whereas public sponsors often articulate high-level commitments without trial-specific guidance. Greater clarity and standardisation, particularly among public sponsors, could improve transparency and facilitate responsible data reuse, while remaining compatible with GDPR requirements.

ObjectiveTo assess the number, timing of publication, characteristics, and scientific impact of secondary publications generated using individual participant-level data (IPD) from a portfolio of Johnson & Johnson-sponsored clinical trials shared with external investigators through a data sharing platform. DesignCross-sectional study. SettingYale University Open Data Access (YODA) Project platform. ParticipantsJohnson & Johnson-sponsored clinical trials listed on the YODA Project platform with IPD available for external sharing as of December 31, 2021, and with a full-length, peer-reviewed publication (i.e., primary publication) reporting primary endpoint results by the original trial investigators. Main outcome measuresNumber, timing of publication, research objectives, analysis type, and scientific impact of secondary publications using IPD from these trials identified through citation searches of primary publications in Web of Science through June 2025. Scientific impact metrics included journal impact factor, annual citation count, annual Altmetric Attention Score, and annual Mendeley reader count. Secondary publications were classified as internal (authored by at least one original trial investigator) or external. ResultsAmong 336 eligible trials, 265 (78.9%) had at least one associated secondary publication, totaling 1,167 secondary publications, of which 209 (17.9%) were external. Among external secondary publications for which the data access mechanism was reported (n=190; 90.9%), most obtained access through data sharing platforms (n=161; 84.7%), primarily the YODA Project (n=157; 82.6%). All secondary publications published from 3 years before through the first 2 years after the primary publication (n=161) were internal (100%). Over time, however, external publications increased steadily, exceeding 50% of all secondary publications by year 11 and thereafter. External secondary publications were more frequently pooled analyses (151/209 [72.2%] vs 534/958 [55.7%]; P<0.001). Predictive or prognostic modelling (108/209 [51.7%] vs 322/958 [33.6%]; P<0.001), development of statistical models or algorithms (60/209 [28.7%] vs 114/958 [11.9%]; P<0.001), and validation of existing methods, models, or risk scores (32/209 [15.3%] vs 66/958 [6.9%]; P<0.001) were more frequent among external than internal secondary publications. Compared to internal secondary publications, external secondary publications were published in journals with higher impact factors (median, 6.7 [IQR, 3.4-16.6] vs 4.6 [2.9-10.2]; P=0.002) and had higher annual Altmetric Attention Scores (median, 2.1 [0.7-7.1] vs 0.6 [0.3-2.3]; P<0.001), but lower annual citation counts (median, 2.7 [1.1-5.6] vs 3.4 [1.6-7.5]; P<0.001) and were less likely to be cited in clinical guidelines (21/184 [11.4%] vs 235/805 [29.2%], P<0.001) or policy documents (14/184 [7.6%] vs 206/805 [25.6%], P<0.001); there was no difference in annual Mendeley reader counts (median, 7.4 [3.9-13.0] vs 8.0 [5.1-13.6], P=0.13). ConclusionsClinical trial data shared with external investigators through a data sharing platform generated substantial and sustained secondary research by both original trial investigators and external investigators. The proportion of secondary publications from any clinical trial generated by external investigators increased over time as external investigators pursued complementary research objectives that achieved a comparable scientific impact. Structured data sharing mechanisms may further enhance the scientific impact of clinical trials. What is already known on this topicO_LISharing individual participant-level data (IPD) from clinical trials can promote transparency, reproducibility, and secondary research. C_LIO_LISeveral initiatives, including the Yale University Open Data Access (YODA) Project and government-supported data sharing platforms, provide external investigators with access to clinical trial data. C_LIO_LIWhile prior evaluations of secondary research generated from shared clinical trial data suggest that external investigators publications have citation impacts comparable to those of original trial investigators, overall evidence remains limited. C_LI What this study addsO_LIAnalysis of 336 industry-sponsored clinical trials with IPD shared through the YODA Project showed that most generated secondary publications, by both original trial investigators and external investigators. C_LIO_LIThe proportion of secondary publications from any clinical trial generated by external investigators increased over time, and compared with those generated by the original trial investigators, these publications more frequently use pooled analyses and focus on predictive or prognostic modelling and the development and validation of statistical methods. C_LIO_LISecondary publications generated by external investigators were more often published in higher-impact journals and received higher Altmetric Attention Scores, but had lower annual citation counts and were less likely to be cited in clinical guidelines or policy documents than those generated by the original trial investigators. C_LI

Objectives: Introducing a new covariate adjustment method for hierarchical outcomes using ordinal logistic regression, comparing it with existing approaches, and assessing whether adjustment improves power in randomized trials with hierarchical outcomes. Methods: We developed an ordinal regression-based method for covariate adjustment of the win ratio and compared it with three alternatives: probability index models, inverse probability weighting, and a randomization-based estimator. Methods were applied to the EMPEROR-Preserved rial and tested through extensive simulations involving two common hierarchical outcome structures: time-to-event composites, and composites combining time-to-event with quantitative measures. Simulations assessed impacts on estimates, standard errors, and power across prognostic and non-prognostic settings. Results: In RCT data and simulations, covariate adjustment consistently increased power when adjusting for prognostic baseline variables. Gains were comparable to or greater than those in conventional Cox models, with no power loss for non-prognostic covariates. Our ordinal approach performed similarly to existing methods while providing interpretable covariate effect estimates. Adjusting for baseline values of quantitative components yielded power gains according to the baseline-to-follow-up correlation. Conclusions: Covariate adjustment for prognostic variables meaningfully improves efficiency in win ratio analyses for hierarchical outcomes. Our ordinal method is easily implemented and facilitates covariate effect interpretation. We recommend the broader adoption of covariate adjustment and our ordinal method in randomized trials using hierarchical outcomes.

Comprehensive geographic data are essential to accurately model geographic accessibility to healthcare and to guide equitable health system planning and implementation. In low-income countries, however, incomplete road and building data in global databases such as OpenStreetMap (OSM) limit the precision and operational applications of geographic accessibility models. Following a successful pilot in one district of Madagascar, we evaluated the scalability of an exhaustive mapping approach to produce highly granulated household-level accessibility estimates at regional and national levels. Using satellite imagery and the OSM platform, we mapped all buildings, roads, footpaths, and rice fields across seven additional districts in southeastern Madagascar. We estimated travel routes, distance and travel time between each household and the nearest primary health center (PHC) or community health site (CHS) using the OSM Routing Machine, combined with predictions of travel speed from a locally calibrated statistical model. We then assessed population density and mapping completeness for roads and buildings in our study area and across Madagascar using AI-generated reference datasets (Microsoft and Facebook/MapWithAI) and estimated corresponding mapping times. Finally, we estimated the resources required in person-years to scale this approach across Madagascar using two different extrapolation methods. Nearly one and a half million buildings and 197,000 km of footpaths were added to OSM across the eight mapped districts, for a total area of about 30,200 km2. Between 24% and 65% of the population lived within one hour of a PHC depending on the district, and 87%-99% lived within one hour of a CHS. Most Malagasy districts were classified as having low completeness for both buildings and roads. Scaling up the approach to cover the entire country would require between 220 and 350 person-years depending on the extrapolation method and assumptions used. Mapping an entire country with sufficient detail to precisely model healthcare accessibility for every household is feasible but resource-intensive. Combining human mapping, participatory approaches, and AI-assisted datasets can substantially improve OSM completeness and generate actionable, high-resolution travel-time data for health planning. Our findings provide a roadmap for Madagascar and other countries seeking to develop national-scale geospatial infrastructure for sustainable development and universal health coverage.

Background SARS-CoV-2 genomic surveillance data remain limited in most low and middle-income countries (LMICs), resulting in significant gaps in the understanding of variant circulation and evolution. Wastewater-based epidemiology (WBE) presents a non-invasive, cost-effective, and population-representative surveillance approach that can complement clinical testing, particularly in densely populated urban informal settlements with limited healthcare access. This study aimed to pilot wastewater-based genomic surveillance as a multifaceted public health tool in Kenya. Methods A prospective study was conducted using wastewater samples collected from two WHO-validated environmental surveillance sites -- Eastleigh A (Kamukunji sub-county) and Mathare (Starehe sub-county) -- in Nairobi, Kenya, between December 2022 and October 2023. A total of 272 samples were collected using Moore swabs at a frequency of two to three times per week. Samples were concentrated using Nanotrap(R) Magnetic Virus Particles, and nucleic acid was extracted using the Qiagen QIAamp Viral RNA Mini Kit. SARS-CoV-2 was detected using RT-PCR (TaqPath COVID-19 CE-IVD RT-PCR Kit). Library preparation for whole-genome sequencing was performed using the Illumina COVIDSeq kit, and sequencing was conducted on the Illumina MiSeq platform. Bioinformatic analysis was performed using Terra.bio and RStudio, and phylogenetic analysis included sequences abstracted from GISAID. Results Of 272 samples, 238 (87.5%) tested positive with a cycle threshold (Ct) value of less than 36. Genomic analysis of 181 sequences identified Omicron as the predominant circulating variant, detected in 59% of samples. Other variants included XBB (16%), XBB.2.3(10%), XBB.1.9.X (5%), and additional minor variants. These findings were concordant with clinical sequencing data from Kenya over the same period. Conclusions Wastewater-based genomic surveillance reliably reflected SARS-CoV-2 variant trends observed in clinical data. This approach provides early signals of variant emergence and evolution, offering a cost-effective complement to clinical surveillance in resource-limited settings.

Background Following the end of a public health emergency of international concern, divergence emerged between reported coronavirus disease 2019 (COVID-19) cases and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater. Exploring viral, clinical, patient, and surveillance-related factors underlying this divergence, we developed models to predict clinically confirmed infections, hospitalizations, and severe cases. Methods In this observational study, we analyzed ~2 years of data from January 2022 in Kanagawa Prefecture, Japan, assessing associations between wastewater SARS-CoV-2 RNA concentrations and confirmed, hospitalized, and severe cases, adjusting for wave and variant effects. Findings Our models based on wastewater viral RNA concentrations showed high predictive accuracy (R^2 = 0.8199-0.9961), closely tracking confirmed, hospitalized, and severe cases. Models derived from earlier waves were applied to subsequent waves with residual correction based on prior prediction errors and maintained good predictive performance (root mean square error = 0.0665-0.2065). Divergence between wastewater viral RNA concentrations and reported cases was not explained by changes in viral shedding. Declines in patients' healthcare-seeking behavior and testing were associated with trends in confirmed cases, whereas milder clinical presentation was associated with severe case trends. The lineages XBB.1.9.2 and BA.2.86 were identified as candidates associated with reduced virulence. Interpretation By incorporating understanding of viral, clinical, and surveillance-related mechanisms, wastewater surveillance may enable prediction of case trends approximately one week earlier than official reporting and inform healthcare capacity planning.

Background: Correctional facilities are vital venues for expanding testing and treatment for hepatitis C virus (HCV) infections, essential components of national hepatitis C elimination plans. Objective: This study characterizes HCV testing and treatment outcomes among individuals entering incarceration into California state prisons, overall, by year, and by key individual-level characteristics. Methods: We analyzed individual-level electronic health record data from all adults entering California prisons ('entrants') between July 1, 2016 and June 30, 2023. We quantified the percentages of entrants receiving an HCV antibody test within four weeks of entry, the percentage antibody positive among tested, the percentage RNA positive among antibody positive, and the percentage initiating direct acting antiviral (DAA) treatment within one year among RNA positive. Results: Of entrants, 133,639 (76%) were tested for HCV antibody, 25,455 (19% of tested) were ever HCV-infected, and 16,738 (66% of ever infected) were currently infected. Among individuals currently infected, 7,479 (45%) initiated DAA treatment within one year. Individuals with identified SUD had 3.2 times higher antibody positivity and 1.3 times higher proportions initiating DAA, compared to individuals not having an identified SUD. Discussion: We show that HCV testing and treatment in California prisons, a central component of national hepatitis C elimination efforts, supported effective and equitable increases in access to hepatitis C treatment, particularly for those with SUD.

The global expansion of highly pathogenic avian influenza (HPAI) virus A(H5N1) underscores the need for rapid surveillance at high-risk wildlife interfaces. Taiaroa Head (45.7828{degrees} S, 170.7333{degrees} E) in the South Island of Aotearoa New Zealand hosts a plethora of aquatic wildlife including a large red-billed gull (Chroicocephalus novaehollandiae scopulinus) colony as well as the only mainland breeding colony of northern royal albatross (Diomedea sanfordi). The Royal Albatross Centre is also a major nature tourism destination, attracting tens of thousands of visitors annually, thereby creating a dense ecological and human-wildlife interface vulnerable to viral incursion. We evaluated the GeneXpert II platform using the Xpert(R) Xpress Flu/RSV cartridge as a field-deployable tool for avian influenza virus detection in environmental and wildlife-associated samples. The assay detected synthetic influenza A viral RNA and multiple endemic low pathogenic avian influenza virus subtypes (A(H3N8), A(H1N9), A(H5N2) and A(H7N7)) circulating in New Zealand birds. Influenza A virus was reliably identified in spiked environmental water samples with no consistent PCR inhibition as well as naturally occurring avian influenza virus in duck pond water. Field deployment demonstrated that the system could be operated by non-laboratory personnel with minimal training in a non-clinical setting. This study establishes the feasibility of near-real-time environmental monitoring. Repurposing clinical cartridge-based point-of-care diagnostics offers a practical early warning approach for avian influenza virus surveillance at ecologically and economically significant locations.

Humans are profoundly reshaping the natural world. These changes are giving rise to complex and mutually risky dynamics between people and large carnivores. In protected areas across North America, bears (Ursus sp.) face rapidly rising recreation pressures that can alter their use of the landscape, either displacing them from high-quality habitats or drawing them into human-wildlife conflicts through habituation or attraction to anthropogenic resources. However, disentangling responses to recreation from other drivers can be difficult because human activity covaries with environmental and seasonal processes that also shape bear activity. We leveraged the partial closure of the popular Berg Lake Trail in Mount Robson Park, British Columbia, Canada, to investigate whether black (Ursus americanus) and grizzly bears (Ursus arctos) showed fear, attraction or neutral behavioural responses to varying recreation levels across multiple spatiotemporal scales. To understand both anticipatory responses to predictable patterns of human activity, and reactive responses to hiker events, we used detections from 43 camera traps over two years (July 2023-June 2025). We compared weekly habitat use, daily activity patterns, and direct responses to hikers (using Avoidance-Attraction Ratios; AARs) among camera sites and between open and closed sections of the trail. Our results revealed that both bear species exhibited patterns consistent with fear responses, while some black bear behaviours were also consistent with attraction responses. Both kinds of responses reflect anticipatory strategies rather than reactionary behaviours (i.e., no AAR effect). Neither species avoided recreation spatially at the weekly scale: black bears were detected more at site-weeks with greater recreation intensity, while grizzly bears were consistently detected more at sites closer to hiking trails. However, both species used daily temporal partitioning to avoid direct encounters with humans. These findings demonstrate scope for human-bear coexistence when recreation levels are managed to be moderate and predictable, and bears have sufficient space to segregate from humans during peak times. Thus, successful coexistence will hinge on co-adaptation by both bears and people. Understanding how recreation influences bear behaviour, and the spatiotemporal scale at which that occurs, is critical for guiding effective adaptive management aimed at fostering human-bear coexistence in high-traffic protected areas.

The Mississippi River (MR) is the largest source of freshwater and nutrients to the Gulf of Mexico (GoM), strongly influencing stratification, primary production, and plankton organization. The interaction between buoyant plume waters and denser shelf waters in the northern Gulf of Mexico (nGoM) generates sharp density gradients that can promote fine-scale biological aggregation. We investigated how hydrographic structure associated with the MR plume controls the vertical distribution of plankton during May 2017 using an integrated instrumentation suite that included an in situ digital holographic imaging system (HOLOCAM) coupled with CTD and optical sensors. Phytoplankton thin layers were repeatedly detected at plume-edge stations within or immediately above a compressed pycnocline formed by bottom-trapped saline wedges. These layers were 1.2-3.5 m thick and exhibited chlorophyll-a concentrations up to threefold higher than background levels. The assemblage was dominated by chain-forming diatoms, particularly Chaetoceros debilis and C. socialis, whose local abundance maxima coincided with chlorophyll peaks. In contrast, copepods, appendicularians, and other zooplankton were broadly distributed throughout the upper water column and rarely aggregated within the layers. Redundancy analysis indicated that chlorophyll concentration and stratification intensity were primary drivers of community structure across stations. Satellite imagery revealed rapid short-term variability in plume extent, helping explain differences in stratification and thin layer development among sampling days. Our results demonstrate that salt-wedge dynamics at the plume-shelf interface constitute a key physical mechanism governing transient phytoplankton thin layer formation in the nGoM, while zooplankton responses remain weakly coupled at the temporal scales resolved here.

Astyanax Baird & Girard, 1854 is a widely distributed and species-rich genus of Acestrorhamphidae, whose abundant populations in Neotropical basins play a crucial ecological role at the trophic level. Taxonomic uncertainties persist within the genus, as seen in Astyanax sp. (formerly designated as A. fasciatus) from the Magdalena basin in Colombia. Concerns about its genetic status are heightened due to ecological threats posed by hydroelectric dams, from habitat loss to river connectivity. We isolated and characterized 17 microsatellite loci to assess the population genetics of this species in a broad sample from the middle and lower sections of the Cauca River, now interrupted by the Ituango dam. Furthermore, a multidisciplinary approach integrating phylogenetic analyses of mitochondrial (COI) and nuclear (rag2) markers with geometric morphometric analyses was employed to evaluate potential cryptic diversity within Astyanax sp. Microsatellites revealed two genetic groups in the studied area, strongly supported as distinct lineages by phylogenetic analyses. Unexpectedly, one of these lineages of Astyanax sp. was recovered in an unresolved clade with samples of A. microlepis and allopatric samples of A. viejita from the Maracaibo Lake basin. Each genetic group showed high genetic diversity, but also evidence of recent bottleneck events and significant-high values of inbreeding. Morphometric analyses provided evidence of significant phenotypic differentiation among A. microlepis, Astyanax sp. 1 (Asp1), and Astyanax sp. 2 (Asp2). Morphological patterns ranged from the robust profile of A. microlepis to the streamlined shape of Astyanax sp. 2 (Asp2), with Astyanax sp. 1 (Asp1) displaying intermediate traits and localized differences in head length and fin placement. Statistical support from permutation tests and a high overall classification accuracy (95.65%) underscore the existence of distinct morphospecies, suggesting that phenotypic differentiation is well-established, despite the complex evolutionary history of the group. This study suggests the presence of cryptic diversity within Astyanax sp. and provides valuable genetic information for the conservation and management of their populations in the Magdalena basin.