PeerJ

Understanding how anthropogenic disturbance and vegetation structure influence bird abundance is important for biodiversity conservation in rapidly changing tropical landscapes. This study evaluated the effects of anthropogenic and vegetation-related variables on the abundance of the Red-cheeked Cordon-bleu (Uraeginthus bengalus) in human settlements and surrounding farmlands in Laminga Village, Jos-East Local Government Area, Plateau State, Nigeria. Bird surveys were conducted using line transects and quadrat-based vegetation assessments during November 2024. Poisson Generalized Linear Models (GLMs) were used to examine the influence of anthropogenic and vegetation predictors on abundance. Among anthropogenic variables, building density significantly reduced abundance ({beta} = -0.141, SE = 0.060, z = -2.333, p = 0.020), whereas human presence ({beta} = -0.073, p = 0.141) and noise level ({beta} = 0.009, p = 0.592) did not significantly influence abundance. Average grass height showed a marginal positive relationship with abundance ({beta} = 2.008, SE = 1.051, z = 1.910, p = 0.056), while hedgerow presence, hedgerow height, grass cover, and bare ground cover were not significant predictors. The vegetation model produced the lowest residual deviance (91.19) and AIC value (297.66), indicating comparatively stronger explanatory performance. The results suggest that structural habitat characteristics and building density may play more important roles in shaping Red-cheeked Cordon-bleu abundance than human activity or noise levels alone. These findings provide insight into species responses to environmental disturbance in human-modified savanna ecosystems.

Plants, as structural elements of habitats, contribute greatly to the maintenance of local biodiversity through their biological interactions. In this study we explore whether their rarity, according to Rabinowitzs (1981) three criteria, is related to the richness and diversity of arthropods and other plants they are associated to, in a gypsum-rich steppe. We first analysed whether the geographic abundance and ecological specialisation of 32 characteristic and dominant plant species are related to the diversity (richness and phylogenetic diversity (MPD)) and degree of local specialisation of arthropods associated with them (1,694 taxa). Then, we focused on a non endemic and non specialized plant in the study area (Krascheninnikovia ceratoides) to explore the effect of population size on two types of interactions: aerial arthropods and plant facilitation. Results indicate that: 1) plant species abundance (geographical range) is not related to the richness or MPD of communities of associated arthropods, 2) plant species ecological specialization (edaphic endemisms or gypsophiles) do not contribute differentially to the maintenance of singular arthropod communities, and 3) the community of aerial arthropods and plants interacting with K. ceratoides in a small population are not necessarily less diverse than those in patches of similar size in a large population. Results also revealed that the two plant species with fewer interactions (one rare, one widespread) do show the highest singularity in their interactions with arthropods. Our study illustrates the important contribution of rare plants to the conservation of local biodiversity.

Xenoglossa cressoniana, also known as Tetraloniella cressoniana or Xenoglossodes cressoniana, is a eucerine bee known mainly from the US Great Plains. The species was described from a female collected somewhere in Texas in the early 1900s. Here, we report rediscovery of this species in Texas after over a century with no intervening observations. While surveying north Texas ranches, we collected six specimens, including both males and females, at four sites northwest of the Dallas-Fort Worth Metroplex. Xenoglossa cressonianas range, the Great Plains and parts of the deep South, covers a large proportion of the United States. The southern and northern Great Plains, and deep South, have been historically overlooked by most bee researchers. Our results show the urgent need to increase data from under-sampled regions, even within a heavily sampled country such as the US.

Habitat modification is a major driver of avian population change in tropical savanna ecosystems. This study investigated habitat-related variation in the abundance of the Red-cheeked Cordon-bleu (Uraeginthus bengalus) across human settlements and surrounding farmlands in Laminga Village, Jos-East Local Government Area, Plateau State, Nigeria. Field surveys were conducted over a three-week period in November 2024 using 21 line transects sampled during peak bird activity periods. Bird abundance data were analysed using a Poisson Generalized Linear Model (GLM). Results showed that habitat type significantly influenced abundance, with significantly lower abundance recorded in human settlements compared to farmlands ({beta} = -0.836, SE = 0.192, z = -4.359, p < 0.001). Transect length positively influenced abundance ({beta} = 0.028, SE = 0.008, z = 3.600, p < 0.001). Model performance improved substantially from the null deviance (159.88) to the residual deviance (125.85), with an Akaike Information Criterion (AIC) value of 306.32. The findings suggest that farmlands provide more favourable habitat conditions for the species, likely due to greater vegetation availability and reduced structural disturbance relative to settlement areas. The study highlights the ecological importance of low-intensity agricultural landscapes in supporting avian persistence within human-modified savanna environments.

Gastropods are a highly diverse and often overlooked taxonomic group of significant ecological and economic importance. Some terrestrial gastropods are critical pests of commercial agriculture and home gardens worldwide. Malacopathogenic nematodes offer an effective biological control method of managing pest slugs and snails as a natural enemy. Pellioditis (syn. Phasmarhabditis) hermaphrodita and Pellioditis (syn. Phasmarhabditis) californica are two species of biocontrol nematodes that have been commercialized, sold as Nemaslug(R) and Nemaslug(R) 2.0 respectively on three continents. Although there is interest in bringing Nemaslug(R) products to the US, they are currently not permitted due to limited knowledge on their North American distribution and effects on non-target and native species. In this study, we investigated the impact of P. hermaphrodita and P. californica on Ariolimax columbianus across two slug-host life stages, in laboratory infectivity assays. The objectives were to 1. determine whether P. hermaphrodita and P. californica nematodes impact survival of A. columbianus, and 2. evaluate whether there are differential effects on survival in juvenile and adult life stages of A. columbianus, in laboratory infectivity trials. We found that P. hermaphrodita caused significant mortality in A. columbianus with 100% mortality observed in both juvenile and adult slug hosts. The P. californica treatment had significant effects on the juvenile A. columbianus group only, with 80% mortality. By contrast, only 16% of unexposed control juveniles and 4% of control adult slugs died during the experiment. These results indicate that P. hermaphrodita and P. californica are lethal to the native, non-target Pacific banana slug (A. columbianus) under laboratory conditions, with mortality differing between juvenile and adult host life stages. Given the ecological importance of A. columbianus, these findings raise concerns for potential non-target effects of P. californica and P. hermaphrodita on terrestrial gastropod communities and emphasize the need for testing biocontrol agents against multiple life stages.

Background & AimsColorectal cancer liver metastasis is the leading cause of mortality in affected patients, with liver sinusoidal endothelial cells playing a pivotal role in metastatic niche formation. Proprotein convertase subtilisin/kexin type 9 has emerged as a regulator of tumor biology, but its function in the hepatic microenvironment remains poorly defined. This study aimed to characterize the role and subcellular localization of PCSK9 in liver sinusoidal endothelial cells and to evaluate the therapeutic potential of its endothelial-specific inhibition in colorectal liver metastasis. MethodsIn vitro studies were performed using human and murine liver sinusoidal endothelial cells stimulated with conditioned media from metastatic colorectal cancer cells and cancer stem cells. Subcellular localization was assessed by immunofluorescence, immunogold electron microscopy, and biochemical fractionation. Protein interactions were investigated using co-immunoprecipitation and proteomic analyses. For in vivo validation, a murine model of colorectal liver metastasis was generated by intrasplenic injection of tumor cells, followed by systemic administration of chondroitin sulfate-targeted nanoparticles delivering PCSK9 siRNA every 5 days for 18 days. ResultsPCSK9 was consistently expressed in liver sinusoidal endothelial cells and displayed a predominant nuclear localization, which increased upon tumor-induced activation. Proteomic integration identified multiple candidate interacting proteins involved in metabolic and tumor-related pathways. Targeted nanoparticle-mediated delivery achieved efficient PCSK9 silencing in vitro. In vivo, endothelial-specific PCSK9 inhibition significantly reduced liver metastatic tumor burden compared with control groups, whereas free siRNA showed no significant effect. ConclusionsPCSK9 exhibits a novel nuclear localization in liver sinusoidal endothelial cells and potentially interacts with proteins implicated in tumor mediated pathways. Selective inhibition of endothelial PCSK9 using targeted nanoparticles significantly reduces colorectal liver metastasis, highlighting a novel therapeutic strategy focused on the hepatic microenvironment. Impact and ImplicationsThis study provides mechanistic insight into how PCSK9 contributes to colorectal liver metastasis by identifying its novel nuclear localization and potential function in liver sinusoidal endothelial cells. These findings are important for researchers and clinicians seeking to understand microenvironment-driven metastasis and resistance to current therapies. The demonstration that endothelial-specific targeting of PCSK9 reduces metastatic burden suggests a new avenue for therapeutic development beyond systemic inhibition. Such strategies could be translated into precision nanomedicine approaches to improve outcomes in patients with metastatic colorectal cancer while minimizing off-target effects.

Estimating taxonomic profiles is a central task in microbiome research. Several bioinformatic tools have been developed for this purpose, differing in algorithmic strategy, reference database flexibility, sensitivity parameters, and the type of abundance they estimate. As a result, taxonomic profiles carry an unwanted methodological signal whose driving characteristics remains understudied. While benchmarks have evaluated the performance of some of these tools, they rely on simulated data; little work has been done to compare them using real metagenomes in the presence of noise and uncharacterised diversity. Overall, the impact of taxonomic profiler choice and parameterisation on scientific conclusions remains poorly understood. Here, we provide a much-needed characterisation of four taxonomic profilers to help researchers better understand the available bioinformatic tools and inform their methodological choices. Then, we leverage 1,211 shotgun metagenomes from eight datasets to compare these taxonomic profilers across 13 methodological designs. Based on diversity indices, we found substantial variability in estimated taxonomic composition depending on methodological features such as reference database and algorithmic strategy. Alpha diversity and its analysis varied substantially with tool choice (particularly among k-mer-based tools) and with reference database. Beta diversity showed sensitivity to both database and parameter choices, yet this variability barely affected statistical inference. This work raises awareness about the causes of variability in metagenome analysis attributable to choices in taxonomic profiling methodology. Our findings highlight the sensitivity of taxonomic diversity analyses to these choices and the importance for researchers to consider assessing the robustness of their results to choice of tool, parameter, and reference database. Crucially, differences in sample diversity across methodologies are symptomatic of differences in estimated taxonomic composition, which can affect any analysis based on taxonomic abundances. Overall, this study underscores the importance of tool selection and parametrisation, and of conducting sensitivity analyses to support robust and reliable scientific conclusions.

Cities are characterized by elevated temperatures, increased pollution, and high-density human populations which often are accompanied by changes in available resources, like food. These shifts have the potential to drive phenotypic divergence in urban wildlife. Functional morphological traits, like body size, can mediate interactions between wildlife and habitat and are closely tied to life history and fitness. While examples of functional morphological variation associated with urbanization are increasing, variation in such traits as a response to urbanization remains unexplored for most taxa. Here, we investigated morphological divergence between urban and rural populations of house mice (Mus musculus domesticus). House mice are globally distributed in diverse habitats and are a model system with a wealth of phenotypic data, making them useful for the study of the impacts of urbanization on morphology. Using a paired replicate design, we sampled urban and rural populations in three distinct metropolitan regions in the eastern United States. We found that body size was smaller in urban populations. Using 3D geometric morphometrics, we also analyzed variation in cranial shape across habitats. Differences in cranial shape were largely allometric, that is, driven by differences in body size. However, we also uncovered evidence of cranial shape variation between habitats not explained by size. In contrast, we did not find evidence for habitat-driven differences in cranial capacity independent of size. Overall, our results suggest a key role for body size in mediating morphological responses to urbanization and highlight the potential of house mice as a globally-distributed model for urbanization.

Research and scholarship are shaped by article citations, which underpin the communication of ideas, assignment of credit, journal impact factors, and author career progression. Given their key influence on author and journal metrics, citations can be intentionally manipulated to inflate the reputation of journals and researchers. Paper mills, unethical organisations that produce and sell manuscripts and publishing services, may also be manipulating citations, but the extent of this manipulation is unknown. Here, we show that molecular cancer articles sharing features with retracted papers from paper mills display citation patterns that suggest systematic inflation. These articles were published in journals in the top decile of journal rankings. Suspected paper mill articles received 50 to 100% more citations than other papers 1 to 3 years after publication, while paradoxically attracting fewer readers and online accesses. Suspected paper mill articles also cited - and were cited by - other suspected paper mill articles and appeared in journals previously reported as paper mill targets. The resulting citations from suspected paper mill articles measurably inflated journal citation metrics. These findings suggest that paper mills inflate the citation metrics of supported publications and affected journals. The manipulation of citation metrics at scale may amplify unreliable findings, slowing scientific progress, and providing unreasonable citation benchmarks for research articles, journals and authors. Our findings highlight new risks in relying on citation metrics for research and journal evaluation and support the use of more robust metrics to describe article and journal quality.

Background: Obesity is a global health crisis, contributing to chronic diseases such as diabetes, cardiovascular disease, and metabolic syndrome. Traditional Chinese Medicine (TCM) has been used in East Asia to manage obesity, but evidence on its efficacy and safety remains limited. This systematic review and meta-analysis assess clinical evidence from randomized controlled trials (RCTs) on TCM for obesity treatment. Methods: We systematically searched PubMed, EMBASE, Cochrane Library, and Web of Science from inception to April 2026. Eligible RCTs compared TCM interventions with placebo or conventional treatments in obese patients. Two reviewers independently conducted screening, data extraction, and quality assessment. Meta-analysis was conducted using a random-effects model to calculate pooled weighted mean differences (WMD) and odds ratios (OR) for body weight, BMI, waist-to-hip ratio (WHR), lipid profiles, and adverse events. Results: A total of 33 randomized controlled trials (RCTs) involving 3,053 participants were included in the analysis. TCM significantly reduced body weight (WMD = -5.86 kg, 95% CI: -7.51 to -4.21), BMI (WMD = -2.82 kg/m{superscript 2}, 95% CI: -3.38 to -2.25), and WHR (WMD = -0.04, 95% CI: -0.06 to -0.02). Lipid profiles improved, with reductions in total cholesterol (WMD = -0.82 mmol/L), triglycerides (WMD = -0.65 mmol/L), LDL-C (WMD = -0.39 mmol/L), and increased HDL-C (WMD = 0.29 mmol/L) (all p < 0.001). Adverse events were infrequent, with no significant difference observed between TCM and control groups (OR = 0.51, 95% CI: 0.24 to 1.08). Funnel plots indicated no publication bias. Conclusion: TCM appears effective in reducing body weight and improving lipid profiles in obese patients, with a low incidence of adverse events. It may serve as a complementary treatment for obesity, though further high-quality RCTs are needed to confirm these findings and assess long-term outcomes.

Numbers of research articles studying circRNAs have increased rapidly since 2017. Previous analyses of human circRNA articles in two high impact factor cancer research journals identified papers with wrongly identified nucleotide sequence reagents and circRNAs whose identities could not be independently verified. In the present study, verification of human nucleotide sequence reagent and cell line identities in retracted circRNA articles published from 2017-2021 in high impact factor journals found wrongly identified nucleotide sequences and/or cell lines in all 13 retracted papers. Similar analyses of human circRNA papers published in high impact factor journals in 2022 found wrongly identified, non-verifiable and/or questionable reagents in 71% (84/118) papers, where 51% (60/118) papers described at least one wrongly identified reagent. When individual error types and features of concern were considered, 2022 circRNA papers described wrongly identified nucleotide sequence reagents (52/118, 44%), questionable circRNA probes that did not meet accepted targeting requirements (34/118, 29%), non-verifiable nucleotide sequences (25/118, 21%), wrongly identified cell lines (22/118, 19%), and/or non-verifiable cell line identifiers (6/118, 5%). In summary, wrongly identified, non-verifiable and/or questionable reagents were unexpectedly frequent in human circRNA papers in high impact journals, highlighting the need for critical engagement with the circRNA literature.

Kalanchoe pinnata is a perennial plant that grows wild in tropical regions and is traditionally used as a medicinal plant. Plants of the Kalanchoe genus have been shown to possess several effects, including antibacterial and antihypertensive properties. However, effects such as the induction of apoptosis in cancer cells have not been reported for any substance other than leaf extracts of this plant and remain unexplained. Therefore, in this study, we investigated the effects of extracts from various parts of K. pinnata (flowers, leaves, and roots) on human colon cancer cell death. We conducted the study using three colorectal cancer cell lines (HT-29, SW620, and DLD-1) and three types of extracts derived from the flowers, leaves, and roots of this plant. Each K. pinnata extract significantly reduced cell viability in a dose-dependent manner in all colon cancer cells. In particular, the root extract induced cancer cell death and inhibited proliferation at lower concentrations than the other extracts. For the colon cancer cells examined, caspase-dependent apoptosis was suggested as the primary mechanism, although cell death was observed in some cells without detectable caspase activation. K. pinnata extracts induced both apoptosis and necrosis in colorectal cancer cells. In addition, K. pinnata extracts increased protein level of cleaved caspase-9, caspase-3, and PARP in SW620 and DLD-1 cells. The decrease in mitochondrial membrane potential was confirmed for all extracts, however caspase-mediated apoptosis was not observed in all cell lines, indicating the need for further investigation. Taken together, our results indicate the potential of the plant K. pinnata and the bioactive compounds it contains as new candidates for adjuvant therapy in colorectal cancer. In the future, it will be necessary to examine the relationship with genetic mutations in each cell line and to investigate the details of the cell death mechanism.

Metabarcoding is a powerful tool for biodiversity comparisons, where standard-size DNA barcodes (>500 bases) offer better taxonomic resolution than shorter ones. Still, the choice of sequencing platforms and bioinformatics pipelines may strongly affect inferred diversity due to various technical biases. We assessed the relative performance of Illumina MiSeq i100 (2x500 paired-end), PacBio Revio and Oxford Nanopore MinION sequencing and bioinformatics pipelines, using full-length ITS amplicon sequencing datasets from a 103-species mock community and 45 composite soil samples. Despite numerous low-quality reads, PacBio yielded the lowest overall error rate and highest number of taxa. Illumina revealed the highest proportion of chimeric and index-switched reads, along with a strong bias towards shorter amplicons. MinION data analysed using PRONAME and Minovar - a bioinformatics pipeline presented here - had the largest proportion of low-quality data, and rare taxa were lost during data filtering and read polishing steps. Although Minovar enabled amplicon sequence variant (ASV) level precision for common taxa, we recommend clustering ASVs into OTUs. For PacBio, standard filtering approaches outperformed the ASV approach because they retained rare taxa. For Illumina, a stringent ASV approach or removal of rare OTUs would limit artefacts. Across all platforms, excess PCR cycles promoted chimeric and low-quality reads and lost quantitativity in biodiversity assessments. With moderate differences in effect sizes, all analytical approaches supported the conclusion that sampling design determines how we see soil biodiversity responses to land use. For biodiversity surveys based on the full-length ITS metabarcoding, we recommend using PacBio sequencing with standard, non-ASV pipelines.

Interactions between cleaner fish Labroides dimidiatus and client fish, from which cleaners remove ectoparasites and mucus, represent a textbook example of mutualism involving sophisticated strategic decision-making. However, cleaners must also face intraspecific social challenges within a size-based hierarchy, where the largest females may eventually change sex and become males with higher reproductive rates. Following 540 individuals over 11 months, we found that, contrary to expectations, slow-growing females spent more time cleaning and cheated more frequently, without causing more negative client responses than fast-growing females did. Instead, variation in growth was best explained by social factors: fast-growing individuals experienced reduced social control, while slow growers spent more time in proximity to dominant individuals. As there was no evidence that spawning activity affected growth patterns, it appears that fast growth as a viable strategy for becoming a male largely depends on the lack of control by dominants.

ContextThe decline, extirpation and extinction of Australias mammal fauna is without peer. In recent decades long term monitoring has revealed tragic patterns in iconic locations such as Kakadu National Park. AimsPast studies have described universal patterns across multiple national parks in the Northern Territory, linking the declines to fire management; however, much of the data in Nitmiluk National Park do not cover the period that encompasses this decline. We examine this data separately to look for patterns with respect to fire history. MethodsWe examined standardised mammal survey data collected in Nitmiluk from 2005 to 2018, to look for correlates with year of survey, time since last burnt, and the frequency of early season and late season burns. Key resultsDespite subtle difference in methods over the years, we found there were some annual changes in the mammals, but little discernible pattern of change correlated to fire regime (which itself indicated an improvement in seasonality, and the extent of burning overall over this period). Instead, there was a distinct reduction in the survey effort. ConclusionsOur study provides further support for the pitfalls of ecological monitoring losing focus, being decoupled from management actions, and allowing ill-conceived changes in design. We recommend that future monitoring at Nitmiluk should focus on key management questions (i.e., fire), best methods for target taxa (i.e. camera traps), more regular and flexible sampling linked to a conceptual model, and integration and co-design with the local land managers, rangers and Traditional Owners. Short SummaryRe-examination of the mammal data collected in monitoring sites at Nitmiluk National Park between 2005 to 2018 indicated little pattern with fire regime over time, and instead indicated that a reduction in effort, had reduced the ability to find pattern With sparse and declining mammal population in northern Australia, future monitoring needs to be focused on key management questions.

O_LIPlants and fungi are major sources of natural products beneficial to society, making the study of distinct species essential for discovering new drugs and bioactive compounds. The medicinal mushroom "Lingzhi" or "Reishi" (Ganoderma lingzhi) is widely used in traditional medicine and extensively studied for its bioactive triterpenoids, yet it is commonly identified as Ganoderma lucidum, the type species of the genus, which lacks a type specimen. C_LIO_LIWe sequenced a G. lucidum specimen preserved in the Kew fungarium, which agreed with the original description and was collected from wood of Corylus avellana in southern England. Using this reference specimen, we compiled genomic and ITS barcoding datasets to explore the genetic and geographic variation within this species. C_LIO_LIWe showed that G. lingzhi and G. lucidum diverged more than 12 million years ago and that all seven "G. lucidum" genomes deposited in public databases belong to other species. More than 1000 barcoding sequences showed that the widely used homology-based ITS barcoding is not working in this group, which can be mitigated by a phylogenetic placement approach. The 149 sequences assigned to G. lucidum with high confidence showed a Eurasian distribution and introductions to North and South America and Africa. C_LIO_LIOur study underscores the importance of accurate species identification and provides guidance for a group of pharmaceutical and socially significant species. To further support future studies and the wider public in differentiating between G. lingzhi and G. lucidum, we propose using "False Lingzhi" as the English name for G. lucidum. C_LI Societal Impact StatementTraditional Chinese Medicine has expanded far beyond Asia, with growing markets in North America and Europe for supplements and functional foods. Lingzhi or Reishi (Ganoderma lingzhi), a well-known medicinal mushroom, is valued for its anti-inflammatory and anticancer properties. However, it is often misidentified with species that may not provide the same health benefits. This confusion poses risks to consumer safety, product regulation, and research. Here, we establish a reference using morphological and molecular tools for the most commonly misidentified species (Ganoderma lucidum) and propose the name "False Lingzhi" to distinguish it, supporting accurate identification, safer product development, and reliable research.

BackgroundFor pancreatic cancer, practical blood-based tests for early detection and postoperative surveillance remain elusive. We sought to develop a qPCR-measurable serum microRNA (miRNA) panel that robustly discriminates pancreatic cancer from non-cancer controls and other malignancies. MethodsWe profiled 255 serum miRNAs in batch 1 (n=72) and selected 27 candidates. Candidates were refined in batch 2 (n=552) and cross-batch evaluation was performed with batch 3 (n=391) to derive a miRNA model. Independent validation used batch 4 (n=616). Clinical relevance was assessed in an independent clinical cohort of resection patients with samples obtained preoperatively and at 1 and 12 months postoperatively. ResultsThe miRNA model trained on batches 2 and 3 achieved an area under the curve (AUC) of 0.91 and 0.83 for pancreatic cancer versus non-cancer controls and non-cancer plus other cancers, respectively, when independently validated in batch 4. Stage-wise AUCs in batch 4 were 0.91 (I), 0.94 (II), 0.86 (III) and 0.90 (IV). In the clinical batch, the score decreased postoperatively (preoperative vs month 1; p<0.01) and was higher in recurrence than non-recurrence (p<0.001). ConclusionsThe developed compact miRNA qPCR assay discriminated pancreatic cancer across independent assay batches and showed clinical relevance for postoperative surveillance. Clinical Trial RegistrationNot applicable.

Objectives: The aim of mammographic screening is the early detection of invasive cancers. In the era of artificial intelligence (AI), this tool may improve diagnosis of earlier stages. The purpose of this study was to assess the impact on selected quality indicators retrospectively. Method: The data source was the Breast Cancer Screening Registry using data from one Screening Unit that currently uses AI routinely. The indicators of the cancer detection rate (CDR), further assessment rate (FAR), and recall rate (RR) in the year 2023, when AI was used, and the year 2022, without AI, in women aged 45-69 were compared. The statistical evaluation used the chi-square test and logistic regression adjusting for the effects of age, a woman's risk level, and the screening round at a 5% significance level. Results: In 2022, without AI, 4,034 women aged 45-69 were included, compared with 4,049 women in 2023 when AI was used. This study showed a non-significant increase in CDR from 5.0 breast cancers detected per 1,000 women (non-AI assessment) to 5.2 (AI-assisted assessment), p = 0.919; OR (95% CI): 1.034 (0.542-1.974), a significant decrease in the FAR from 5.2% to 3.9%, p < 0.001; OR (95% CI): 0.665 (0.529-0.836), and a decrease in RR from 2.4% to 1.9%, p = 0.083; OR (95% CI): 0.754 (0.548-1.037). Conclusion: AI has the potential to be a useful tool in the early detection of breast cancer by improving quality through a decrease in FAR and RR, while probably maintaining CDR.

Fall-run Atlantic Sturgeon occupy riverine habitat for extensive periods of up to several months during periods of spawning. It is generally not feasible to eliminate potential anthropogenic stressors during the entire time Atlantic Sturgeon are on spawning habitat. If data were available to accurately predict when eggs and larvae are in the water column, potential impacts could be minimized for this relatively short timeframe, compared to the entire season of freshwater residency by adults. This research used acoustic telemetry data for adult female sturgeon, along with water temperature and discharge, to predict when females were likely releasing eggs versus merely staging in spawning habitat waiting to spawn. The descriptive and Bayesian model results predict that egg release is associated with water temperatures ranging from 20-26{degrees}C and pulses in river discharge, often confining egg release to a few days or weeks. By using weather data that predict relatively short periods of when egg release occurs versus longer periods that includes staging, resource managers can more feasibly collaborate with water usage groups to ameliorate egg/larvae survival.

Machine learning (ML) has emerged as a transformative technology across biomedical and life science sectors, with applications spanning drug discovery, medical imaging, genomics, and clinical decision support (Goecks et al., 2020; Patel et al., 2020). Despite exponential growth in ML-related publications, from fewer than 100 articles in 2003 to nearly 25,000 by 2021 (NCBI, 2022), adoption among industry professionals remains uneven and sector-dependent. Understanding what drives or inhibits this adoption is critical for organisations seeking to leverage ML capabilities in research and clinical practice. Technology adoption in organisational contexts has been extensively studied through the Technology Acceptance Model (TAM), originally proposed by Davis (1989) and subsequently extended to incorporate external variables influencing perceived usefulness (PU) and perceived ease of use (PEU) (Venkatesh & Davis, 1996). While TAM has been applied across multiple industries, its application within biomedical and life science contexts remains limited, and the industry-specific factors that shape ML acceptance in this sector have not been systematically examined. Two external variables are particularly relevant to life science professionals. First, the bibliometric journal impact factor (JIF) functions as a cognitive signal of scientific credibility, a sector where evidence-based decision-making is culturally embedded, and publication quality serves as a proxy for technological legitimacy (Garfield, 1996). Second, technology hype, operationalised through the Gartner Hype Cycle framework, represents a social influence variable that shapes organisational expectations and investment decisions around emerging technologies (Gartner Inc., 2018). Whether these variables influence ML acceptance among life science professionals, alongside individual knowledge and experience, has not been empirically tested. This study addresses that gap by investigating ML technology acceptance among 213 biomedical and life science professionals across EMEA, LATAM, and North America, using a cross-sectional quantitative survey and PLS-SEM analysis. The TAM model is extended with three external variables, JIF, technology hype, and prior knowledge and experience, to test their influence on PU and PEU in this specific professional context. Additionally, the study examines demographic and regional differences in ML acceptance, with particular attention to variation between academic researchers and healthcare professionals. The findings contribute a validated, sector-specific extension of TAM for life sciences, provide actionable insights for organisations seeking to accelerate ML implementation, and establish a framework for future subsector-specific research.