PeerJ

Dams can significantly alter natural riverine systems, but their impact on movement across rivers for most terrestrial vertebrates is poorly known. The completion of Glen Canyon and Flaming Gorge dams in Arizona and Utah (southwestern United States) profoundly changed the Colorado and Green Rivers and have altered habitat for many species. The common side-blotched lizard (Uta stansburiana) offers an excellent opportunity to examine the effects of riverine impoundments on migration and gene flow in terrestrial biodiversity. To assess these effects, we collected tissue samples from 241 Uta stansburiana above and below Glen Canyon Dam and on both sides of the Colorado river at three separate study areas. We used eight microsatellite loci to estimate genetic exchange in the context of genetic diversity and structure. One study area below Flaming Gorge Dam and above Glen Canyon Dam has annual periods of warmer water temperatures and lower flows that are closer to pre-dam conditions, whereas two study areas below Glen Canyon Dam have cold water temperatures year-round, and less pronounced seasonal low flow episodes. We predicted that warmer water temperatures above Glen Canyon Dam would promote greater genetic exchange among populations than below the dam. However, we found evidence for low levels of genetic exchange between sites both above and below Glen Canyon Dam, and a moderate amount of exchange at a site below this dam where lizards could conceivably move from one side to the other. Our results imply that 1) the changes in water temperature and hydrology in dam-altered rivers are a barrier for this species even when the distance from the dam is great; and 2) genetic exchange may be dependent on river morphology. These results are relevant to other small vertebrates, particularly ectotherms, that occupy habitat proximal to a dammed river and has implications for the conservation management of impounded river systems.

Increasing human activities along the US west coast are of concern for populations of cetaceans and particularly for a number of large whale species that are recovering from overexploitation during the era of commercial whaling. New rapid monitoring tools, such as satellite imagery analysis powered by recent advances in artificial intelligence, have potential to provide additional broad-scale and near real-time capacities for survey and monitoring. This paper investigates and demonstrates the feasibility of automatic detection of gray whales in sub-meter satellite imagery off the coast of California, USA. Observations and statistical analysis of regional imagery allowed not only an assessment of their detectability but also the development of robust signal processing and machine learning-based solutions for automated detection. To that end, a regional dataset of 221 gray whales was created using signal processing to inform a deep-learning-based detection framework, and 20 different large neural network architectures for feature extraction followed by a support vector machine algorithm for classification were evaluated for their detection performance. Neural network backbones included 19 convolutional neural networks and 1 transformer network. The best architecture generally achieved satisfying performance with an average balanced accuracy reaching up to 99.90%. It is also demonstrated that panchromatic imagery, in spite of the lesser amount of information provided, can be used to perform detection with a relatively high accuracy of 87.05%, allowing wider spatial and temporal coverage. Large-scale deployment of the best performing models over a broad range of regional satellite imagery resulted in the detection of 3353 gray whales, as well as opportunistic detections of humpback, blue and fin whales, in and going from December 28th 2009 to March 26th 2023. It also provided meaningful data points concerning the migration routes of gray whales within the Channel Islands and Southern California Bight. The large number of high-confidence detections indicates the capacity for a large-scale monitoring approach to support state and federal conservation policies such as gear mitigation, vessel speed reduction programs, or shipping lane redefinition that could also be expanded to other areas and for other species.

Widow spiders of the genus Latrodectus are important animals for biomedical, pest and conservation research. Here, we present the assembled genomes of two closely related Latrodectus species: the Australian L. hasselti and the New Zealand endemic L. katipo. The genome of L. katipo consists of 13 scaffolds likely corresponding to chromosomes (90% of the total length) and 1267 short scaffolds (10%). It has a total length of 1.5 Gbp and BUSCO of 94.9%. The genome of L. hasselti consists of 379 scaffolds and has a total length of 1.7 Gbp and a BUSCO score of 95.4%. The repeat content is very similar in both genomes with a total proportion of 37.2% for L. katipo and 39.9% for L. hasselti. Genome annotation predicted 12706 and 15111 genes for L. katipo and L. hasselti respectively. An ortholog analysis shows large overlap between orthogroups suggesting either duplication events in L. hasselti or loss of genes in L. katipo.

Parathyroid hormone-related peptide (PTHrP), encoded by PTHLH, has been implicated in tumor progression through its involvement in epithelial-mesenchymal transition (EMT), angiogenesis, and tumor cell migration. Previous experimental studies suggest that PTHrP may promote these processes in colorectal cancer (CRC), partly through the modulation of factors such as secreted protein acidic and rich in cysteine (SPARC) and vascular endothelial growth factor (VEGFA). These events play a key role in the acquisition of an aggressive phenotype in our experimental models. In this study, we performed an integrative in silico analysis of multiple transcriptomic datasets to investigate the potential role of PTHLH in CRC. Differential expression analysis identified a set of consistently dysregulated genes across independent datasets. Functional enrichment and network analyses revealed that PTHLH expression is associated with biological processes related to extracellular matrix remodeling, EMT, and angiogenesis. Correlation analyses showed a positive association between PTHLH and SPARC expression, while network-based approaches suggested a potential functional connection with VEGFA. To assess the clinical relevance of these findings, survival analysis was performed using publicly available datasets. High expression levels of PTHLH, SPARC, and VEGFA were significantly associated with reduced overall survival in patients. Notably, a combined gene signature based on these three factors demonstrated a stronger prognostic effect than individual genes, indicating enhanced predictive value. These findings suggest that PTHrP is associated with molecular pathways involved in tumor progression and, together with SPARC and VEGF, may contribute to a coordinated regulatory axis with prognostic relevance in CRC, warranting further experimental validation.

High level of protein expression is usually welcomed in industry and research, and codon optimization is widely used to achieve high expression. Methods of implementing codon optimization can be divided into two branches, one is classical methods which develop cost functions based on empirical law, another is AI methods which learn the codon choice principles from endogenous genes with neural networks. Here we develop two codon optimization tools based on two branches respectively, namely OptimWiz 2.1 and OptimWiz 3.0. Results of fusion protein fluorescence detection indicate that both OptimWiz 2.1 and OptimWiz 3.0 are superior to all the other commercially available codon optimization tools. Principles of codon optimization are revealed in the process of machine learning on both tools.

Introduction: Physical inactivity and sedentary behaviour are significant risk factors for noncommunicable diseases. Engaging in regular physical activity (PA) during childhood is crucial for preventing long-term health burdens. This study examined PA levels and associated factors among upper primary school children in Lusaka, Zambia. Methodology: A cross-sectional survey was conducted from August to October 2022 among 638 children aged 9-18 years from six public and six private schools. Data were collected using the Physical Activity Questionnaire for Children (PAQ-C), Youth Risk Behaviour Survey (YRBS), Model of Youth Physical Activity Questionnaire (MYPA), and 3-Day Physical Activity Recall Questionnaire (3DPAR). Analyses included descriptive statistics, Chi-square, Fishers exact tests and multivariable binary logistic regression at a 0.05 significance level and 95% confidence interval. Results: Most participants (82%) were insufficiently active, with only 18% achieving sufficient PA. Reported barriers included lack of playgrounds or parks near home (p=0.012), neighbourhood safety concerns (p=0.041), and limited parental supervision (p=0.006). Watching television reduced the odds of PA by 69% (aOR=0.31; 95% CI: 0.13-0.75). Conversely, peer support increased activity by 15% (aOR=1.15, 95% CI: 0.67-1.97), while not being concerned about showering or fixing hair after PA increased activity by 94% (aOR=1.94; 95% CI: 1.21-3.11). Conclusion: The majority of school children in this study did not meet recommended PA levels. Barriers to activity included personal, parental, and environmental factors. Interventions should prioritise safe play spaces, increased parental and peer support, and reduced screen time to curb future non-communicable disease risks.

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.

BackgroundMicrosatellite stability status determination is important for prognostication and therapeutic decision making in colorectal cancer management, but the conventional methods for this assessment are not readily available, especially in low- and middle-income countries. Deep learning (DL) models have been proposed for addressing this problem; however, potential computational cost due to model complexity and inadequate explainability may limit their adoption in low-resource settings. This study explored the potential of explainable lightweight models for detection of microsatellite instability in colorectal cancer. MethodsDL models were trained using a public dataset of colorectal cancer histology images and then used to classify a set of test images into one of two classes: microsatellite instability or microsatellite stability. The models were compared for efficiency. Gradient-weighted class activation mapping (Grad-CAM) was used to interpret the models decision making. ResultsThe simpler convolutional neural network (CNN) trained from scratch had modest performance (accuracy=0.757, area under receiver-operating characteristic curve [AUROC]=0.840). With an attention mechanism added, these values increased, but specificity and sensitivity reduced. Pretrained models performed better than the ones trained from scratch, and EfficientNet_B0 had the best balance of high performance and low computational requirements (accuracy=0.936, AUROC=0.990, negative predictive value=0.923, specificity=0.953, 4,010,000 trainable parameters, 0.38 gigaFLOPs). However, a simple CNN model with attention mechanism had the best interpretability based on Grad-CAM. ConclusionThis study demonstrated that DL models that are lightweight when compared to previously proposed ones can be useful for colorectal cancer microsatellite instability screening in resource-limited settings while balancing performance and computational efficiency.

BackgroundPsilocybin is a classic psychedelic that acutely alters brain functional connectivity. These changes are linked to therapeutic doses and subjective effects, with some evidence that changes persist beyond acute drug administration. However, the effects of lower doses on sustained connectivity changes remain unclear. MethodsTen healthy volunteers received three psilocybin doses (between 5 and 20 mg) in a randomized and blinded order, with at least one week between doses. Resting-state functional magnetic resonance imaging was completed at baseline and one week after a single dose. Functional connectivity changes were analyzed in relation to dose and altered conscious states at both the level of individual brain region connections (edges) and resting-state networks. ResultsDose-dependent changes in 77 edges (76 increases, 1 decrease, of 1275 possible) were observed, but none survived multiple-comparison correction. At the network level, we observed one dose-dependent between-network increase (of 21 possible), and one dose-dependent within-network increase (of seven possible); the latter surviving correction. Alterations in conscious state were positively associated with widespread connectivity changes (dose-adjusted), with many network-level associations surviving correction. These directional patterns showed that lower doses and smaller conscious state alterations were linked to decreased connectivity, whereas higher doses and greater conscious state alterations were linked to increased connectivity. ConclusionsDose level and acute subjective effects were positively associated with multiple functional connectivity changes one week after a low-to-moderate psilocybin dose. Further research is warranted to characterize these sustained effects and their therapeutic relevance to inform studies adopting similar dosing regimens in clinical cohorts. Trial RegistrationAustralian New Zealand Clinical Trials Registry: ACTRN12621000560897 Date registered: 12 May 2021 URL: https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=381526&isReview=true

Natural forests are increasingly being replaced by plantation forests, highlighting an urgent need to reconcile forest use and biodiversity conservation. Coastal forests serve as refugia for species of conservation concern, but they have been globally replaced by plantations, and conversion remains ongoing. As natural coastal forests become increasingly scarce, opportunities for direct biodiversity comparisons with coastal plantations are also disappearing. This scarcity leads to underestimation of the conservation value of natural coastal forests, while effective management measures to conserve biodiversity within coastal plantations remain poorly developed. By focusing on the largest natural coastal forests in Japan, we assessed whether plantation coastal forests can substitute for natural coastal habitats across multiple taxonomic groups, functional groups, and threatened species. We found that plantations supported bird species richness comparable to natural forests at the community level and for threatened species. Surveyed plantation forests supported 7% of global breeding populations of the endangered Brown Shrike. However, plantations hosted lower forest plant species and higher introduced plant species richness. Plantations also significantly altered coastal zonation patterns in plant communities: forest species distribution shifted seaward, whereas coastal and introduced species shifted landward. Coastal plantations are unlikely to be complete substitutes for natural coastal forests for plant species, yet still have the potential for restoring historically lost coastal forest ecosystems. Confining further plantation activities to landward areas and plantations with low canopy cover will mitigate the negative impacts of plantations and further conserve unique coastal communities where forest and grassland species can coexist. Highlight{checkmark} Coastal forests have been historically disturbed and converted to plantations {checkmark}We test whether coastal plantations can substitute for natural forests across taxa {checkmark}Bird species richness in plantations was comparable to that in natural forests {checkmark}Plant species richness was lower in plantations and zonation patterns were altered {checkmark}Considering zonation patterns can turn plantations into restoration opportunities

IntroductionColorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide, despite advances in conventional oncological therapies. In recent years, various studies have made advances in integrative oncology, such as investigating the use of Chinese Herbal Medicine (CHM) as a complementary therapy alongside conventional oncological therapies to alleviate treatment-related adverse effects, improve quality of life, and potentially enhance therapeutic outcomes. Despite this, clinical practice in this area remains highly heterogeneous, with limited standardized guidelines on key areas of concern such as (1) optimal intervention, (2) recommended stage and duration of intervention, (3) safety considerations, and (4) possible herb-drug interactions. Hence, this study aims to establish expert consensus on the usage of CHM as a complementary therapy in the management of CRC, to support safe, consistent, and evidence-informed clinical practice. Methods and AnalysisWe will employ a modified Delphi technique to achieve consensus amongst a panel of international experts in various fields related to integrative oncology. Prior to the study, a list of questionnaire items was developed based on a systematic review of existing clinical practice guidelines on CRC. An international panel will be invited based on established international profile in integrative oncology research and clinical practice, and by peer referral. Two rounds of Delphi will be conducted using anonymous online questionnaires. Consensus will be considered reached if at least 50% of the panel strongly agree/disagree that an item should be included or excluded while strong consensus will be set at 76%. Items which achieve strong consensus after Round 1 will be removed, before being sent out for Round 2 with a summary of Round 1 responses for a final consensus. Ethics and DisseminationEthics approval has been obtained from the Institutional Review Board of Nanyang Technological University (IRB-2025-1222). Our findings will be disseminated through peer-reviewed publications and conference presentations. Strengths and limitations of this studyO_LIThis study will develop an expert consensus which aims to guide future integration of Chinese Herbal Medicine (CHM) as a complementary therapy into colorectal cancer (CRC) management. C_LIO_LIKey concerns in areas such as determining the (1) optimal intervention, (2) recommended stage and duration of intervention, (3) safety considerations, and (4) possible herb-drug interactions, thereby laying the groundwork for potential future incorporation of CHM into CRC treatment protocols alongside conventional oncology approaches has been identified, thus limiting implementation in clinical practice. C_LIO_LIDesigning a study e-guide, followed by the consensus rounds study online will facilitate participants responses and the dissemination of information from previous rounds. C_LI

The molecular basis of triple-negative breast cancer (TNBC), a highly aggressive and therapy-resistant subtype of breast cancer, is poorly understood. This study aims to identify key genes and pathways involved in TNBC development and progression using a systems biology approach followed by experimental validation. Here, two transcriptome microarray datasets from the GEO database were analysed using the R package LIMMA to detect differentially expressed genes (DEGs) in TNBC tumors. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses using the DAVID database were performed to identify DEGs regulated biological functions and pathways. Further, a protein-protein interaction (PPI) network was constructed using the STRING online database, and the topological properties were determined using MCODE and Cytohubba plug-ins. The expression and the prognostic value of the hub genes were validated using the Cancer Genome Atlas (TCGA) survival analysis. We found 727 DEGs, of which 473 were downregulated and 254 were upregulated in TNBC vs. non-TNBC samples. The GO and KEGG analyses indicated that the DEGs were mainly related to cell adhesion, tumorigenesis, and cellular immunity. The PPI network had shown six hub genes, namely CCND1, CDH1, ESR1, FN1, IL6, and PPARG, as the top key regulators. All these genes were validated by quantitative real-time PCR in the TNBC cell line using non-TNBC cell line as a calibrator, and the obtained results were in accordance with the bioinformatics data. This information may contribute to understanding the various molecular mechanisms that drive the development and progression of TNBC tumors.

BackgroundPancreatic adenocarcinoma (PDAC) is an abysmal disease, with a poor clinical outcome, largely due to limited life-extending treatments for patients. Notoriously, PDAC displays a T cell-suppressive tumor microenvironment where underlying molecular mechanisms that lead to this phenotype remain poorly understood. To unravel specific mechanisms, we utilized bioinformatic analyses with functional studies and revealed the cytolinker protein plectin (PLEC) as a novel player in regulating the T cell-suppressive tumor microenvironment of PDAC. MethodsUtilizing the TCGA-PAAD dataset, tumor samples were separated by PLEC expression to evaluate patient survival, and pathway analyses associated with increased tumorigenesis. Evaluation of immune infiltration and subsequent immune deconvolution was performed using tidyestimate and CIBERSORTx R packages. Single-cell RNA-seq (scRNA-seq) analysis from 229 PDAC patients was analyzed to investigate signaling dynamics and immune cell infiltration in PLECHigh patients. Functional validation was provided using a monoclonal antibody (mAb) against cell surface plectin (CSP) in two murine PDAC models to examine changes in tumor growth and immune cell subset abundance. ResultsOur studies revealed that high plectin expression results in an overall worse survival associated with activation of pro-tumorigenic pathways and decreased anti-tumor immune signature in PDAC patients. Analysis via GSEA indicates PLECHigh patients display an aggressive phenotype and suppressed pro-inflammatory signaling pathways. Immune ESTIMATE scores were significantly decreased in PLECHigh patients, and scRNA-seq analysis revealed that PLECHigh tumors display a decrease in anti-tumor CD8+ T cells. In vivo analyses using an anti-CSP mAb revealed a reduction in tumor growth kinetics compared to IgG control corresponding with a significant increase in proliferating and activated cytotoxic CD8+ T cells. Anti-CSP-mediated tumor suppression was inhibited when CD8+ T cells were depleted, indicating that anti-CSP treatment is contingent on cytotoxic T cell functionality. ConclusionOur findings identify plectin as a biomarker of aggressive disease in PDAC, with high plectin expression associated with decreased T cell infiltration, and that treatment with anti-CSP mAb reinstates anti-tumor immunity and decreases tumor volume in vivo. These findings position plectin as a high-priority therapeutic target, with the potential to fundamentally reshape immune responses in PDAC and improve outcomes for patients with few remaining options.

While vaccination conflicts have become apparent, physicians' attitudes toward those with differing views remain unclear. Through an online survey of 492 physicians and 5,252 members of the general public in Japan in February 2026, we investigated attitudes toward four vaccines (influenza, measles, HPV, and COVID-19). Intergroup bias was assessed as ingroup minus outgroup attitudes using a feeling thermometer. Multilevel regression examined associations with agreement group and physician status. Intergroup bias was significantly positive in both agreement and disagreement groups across all vaccine types, and was higher in the agreement group. Physicians exhibited higher intergroup bias than the general public. These findings indicate that vaccination conflict is bidirectional: physicians, often viewed as targets of hostility from vaccine-hesitant individuals, themselves exhibit greater intergroup bias toward those with opposing views. Interventions to raise physicians' awareness of their own bias, alongside communication strategies for vaccine-hesitant individuals, are needed.

BackgroundTransposable elements (TEs) are repetitive genetic elements that can jump to new loci causing genome expansions, structural rearrangements, and can, ultimately, propel the evolution of genomes. Despite their significance, the role of TEs in the evolution of genomes and phylogenetic groups remains largely understudied in early diverging lineages. Further, the extent to which TE content varies across species is still an open question. Medusozoa, a group within Cnidaria encompassing jellyfish and hydroids, exhibits an exceptional diversity of life history strategies, body plans, and physiological capabilities. These characteristics, along with its early-diverging phylogenetic position, establish Medusozoa as an ideal system for investigating the composition and evolutionary history of TEs within the group. ResultsWe generated a custom repeat library built from annotations of 25 Medusozoan genomes and used it to characterize TEs, aiming to identify lineage-specific TE content and activity that may correlate with the diversity observed within the group. We found that repetitive element percentage and genome size varied considerably, with Hydrozoa exhibiting the most variation among classes in both respects. DNA transposons were the most prevalent TE classification in all but two genomes, averaging 28% of all genomes. Intra-genus comparisons revealed a surprising degree of differences in TE content. In the genus Aurelia, the expansion of a single DNA transposon superfamily accounted for much of the difference in repetitive element percentage between two species, whereas in the genus Turritopsis, a similar divergence resulted from the proliferation of multiple superfamilies. Interestingly, most genomes showed evidence of recent TE expansions, suggesting ongoing activity in many medusozoan species. ConclusionWe present the first comparative analysis of TEs across all medusozoan classes. Our results reveal class-specific TE dynamics and highlight cases of TE proliferations as lineages diverge. This research provides data on TE activity and diversity that can be used as a resource for future study and fills important gaps in our understanding of TEs in early diverging animal lineages.

The practical utility of many modern phylogenetic comparative methods can depend on how accurately mathematical models capture the evolutionary process of traits. Boucher and Demery (2016) described a new quantitative trait model, Brownian motion with reflective limits, that they anticipated might be of use in testing hypotheses about a particular sort of constraint on phenotypic character evolution. Since their analytic solution for the probability function under this bounded evolutionary scenario was not practical to evaluate for reasonably-sized trees, Boucher and Demery (2016) also identified a creative technique for computing the likelihood of their model. The basis of this methodology derives from the convergence of an equal-rates, symmetric, ordered Markov chain and continuous stochastic diffusion in the limit as the number of steps in our chain goes to {infty} (or, alternatively, as their widths decrease towards zero). We refer to this convergence in the limit as the discretized diffusion approximation or (more compactly) the discrete approximation. We realized that this discrete approximation of Boucher and Demery (2016) unlocked a number of additional models for the phylogenetic comparative analysis of discrete and continuous trait data, and we explore several of these in the present article. Specifically, we examine application of this discretized diffusion approximation to the threshold model from evolutionary quantitative genetics, to a new "semi-threshold" trait evolution model, to a joint model of discrete and continuous traits in which the discrete trait influences the rate of evolution of our continuous character, as well as a model where precisely the converse is true, and to a discrete character dependent multi-trend trended continuous trait evolution model. We conclude with some context for the origins of our article and discussion of other possible applications of this powerful approach.

Toxoplasma gondii is a widespread human pathogen that has multiple, clinically relevant stages in its complex life cycle, including fast-replicating tachyzoites and latent bradyzoites. Bradyzoite differentiation is triggered by stress responses that lead to changes in transcription, translation, and metabolism. Two aspects of this process are addressed in this report: first, whether proteins that play roles in bradyzoite differentiation are specific to T. gondii and other bradyzoite-forming parasites of the Sarcocystidae family, and second, whether new bradyzoite differentiation proteins can be identified in T. gondii. To answer these questions, a phylogenetic approach was used, comparing proteomes of select members of the Sarcocystidae family that form morphologically different bradyzoite cysts and members of the Eimeriidae family that do not form cysts. This approach resulted in 8 distinct clusters of T. gondii proteins that reflected different conservation patterns; for example, one cluster showed conservation among all organisms, while another showed conservation in bradyzoite cyst-forming organisms. Known T. gondii proteins involved in bradyzoite differentiation were found in all clusters, indicating that this process uses both highly conserved pathways as well as bradyzoite-specific pathways. Importantly, the cluster containing proteins that are conserved in bradyzoite-forming organisms contained several known regulators of bradyzoites, and will be a source for identifying novel T. gondii proteins that are involved in bradyzoite differentiation.

Tick-borne diseases are now reported from nearly every county in Illinois, and three vector tick species (Amblyomma americanum, Dermacentor variabilis, and Ixodes scapularis) are of particular concern because these are responsible for most of the tick-borne disease transmission in the state. However, active surveillance is patchy, many counties have little or no sampling, and there is no statewide, quantitative map of relative abundance that can be used to anticipate risk in unsampled areas. To address these gaps, we developed Bayesian hierarchical spatial models to estimate the county-level abundance of these three vector tick species in Illinois. Using active surveillance data from 2019-2022, we modeled county-level abundance as a function of climate, land cover, forest fragmentation, and deer habitat suitability. Spatial dependence was captured using a Besag-York-Mollie 2 (BYM2) prior implemented in INLA, along with spatial 5-fold cross-validation to assess predictive performance. A. americanum showed the highest predicted abundance in southern and central Illinois, D. variabilis was widespread but diffuse, and I. scapularis was concentrated in northern and selected central counties. Together, these models provide the first spatial, statewide, uncertainty-aware assessment of tick abundance in Illinois, highlighting priority counties where surveillance lags disease risk.

Patterns in the vegetation across arid and semiarid regions may be explained as a form of self-organization driven by water scarcity, and are often modeled through reaction-diffusion dynamics. Recent work has shown that similar mathematical models generate patterns on networks. However, these studies have focused on idealized topologies with no reference to natural pattern-forming systems. Our study aims at bridging these two fields: we employ a physical reaction-diffusion vegetation model, and gradually modify the topology of the diffusion network by adding random shortcuts over a 2-dimensional grid, interpolating between a regular lattice and a random network. We found that network topology strongly shapes both the resulting vegetation patterns and the precipitation range that supports them. Three behavioral regimes emerge. On a regular lattice, high-regularity patterns develop reflecting local diffusion processes. On a random network, the system is dominated by global pressure towards homogenization yielding either a uniform state or a single patch. In the intermediate shortcut density range, as the network topology resembles a small world network, the interaction between the two scales of diffusion generates two kinds of disordered patterns: low-regularity patterns with a well-defined characteristic wavelength, and irregular patterns characterized by a broad patch size distribution. These disordered patterns resemble real-world observations and, in our model, they show different responses to changing precipitation. Although we focused on dryland vegetation, we suggest that network-mediated diffusion could lead to similar mechanisms in a wide variety of pattern-forming systems. HighlightsO_LIWe study vegetation pattern formation over different diffusion network topologies. C_LIO_LITwo kinds of stable disordered patterns states develop over small world topologies. C_LIO_LILow-regularity patterns with a well-defined characteristic wavelength. C_LIO_LIIrregular patterns characterized by a broad patch size distribution. C_LIO_LIThese different kinds of disordered states show different relations to precipitation. C_LI

This study investigates the seasonal dynamics of the microbiome within the marine sponge Halichondria panicea from Baltic coastal waters, focusing on its symbiotic relationship with Candidatus Halichondribacter symbioticus. Over 16 months, we observed distinct summer and winter microbial communities, transitioning rapidly between these states during spring and fall. Marine sponges host complex microbiomes composed of diverse microbial taxa that play critical roles in host metabolism and nutrient cycling within marine ecosystems. While our understanding of sponge microbiomes has traditionally been based on static characterizations, the temporal dynamics of these associations across seasonal cycles remain poorly understood. In this study, we investigated temporal variation in bacterial symbionts of Halichondria panicea over 16 months in Baltic coastal waters using high-throughput amplicon sequencing of bacterial 16S rRNA gene sequences. The microbiota of H. panicea exhibited host-specific structure and a high degree of stability across seasons, despite fluctuations in environmental factors such as temperature, salinity, photoperiod intensity, and inorganic nutrient availability. In contrast, bacterial communities in surrounding seawater displayed large seasonal shifts which potentially mix with the sponge bacterial community, suggesting that different degrees of ecological pressures act on free-living and symbiotic marine bacteria. These findings establish an empirical baseline for identifying abnormal shifts in symbiont communities, which could be indicative of environmental stress or biological disturbance events.