Biology subjects

Thompson, P.

Publications and source records attributed to Thompson, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Multimodal imaging reveals surface degradation of voice prosthesis implants resulting from colonisation by polymicrobial biofilms

Total laryngectomy is performed for advanced laryngeal and hypopharyngeal cancers. Following the surgery, the insertion of indwelling silicone-based voice prosthesis (VP) implants is considered the gold standard for speech rehabilitation. However, early VP failure due to biofilm formation and invasion of the VP surface can lead to routine use of nystatin and the need for frequent valve changes. Despite these burdens, the composition and impact of colonising pathogens on VP integrity are poorly understood. We have developed a rapid pipeline which permitted the transfer, fixation, staining, and imaging of explanted VPs from patients within 90 minutes of sample collection. Using this pipeline, we demonstrate a multimodal reflection contrast and fluorescence confocal laser scanning microscopy technique to simultaneously map the VP surface and visualise the biofilms in situ, providing new insights into the role of pathogens on VP failure. Our results reveal that complex fungal and bacterial biofilms form polymicrobial biofilms on the VP surface. We demonstrate that biofilms not only reside on the VP surface but can invade the device, releasing silicone particles that are visible within the volume of the biofilms and are separate from the VP surface. Our findings highlight the complexity of the biofilms that form on speech valves; complex polymicrobial biofilms require more advanced treatment than what is conventionally used. Work should focus both on the patient factors that may influence this and the material properties of the valve.

microbiology↗

bioRxiv2026

Structural brain alterations in autism: A large-scale voxel-based morphometry mega-analysis

BackgroundPrevious large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity and may obscure subtle focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision to identify and localize previously undetected neuroanatomical alterations. PurposeTo rigorously identify voxel-wise GM and white matter (WM) volume differences in autism in the largest VBM mega-analysis to date. Materials and MethodsThis retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (15.0 {+/-} 8.2 yrs; 76.8% male; 1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates ResultsAutism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions (peak t=7.39, peak {beta}=0.13); such GM differences were most notably detected in the bilateral orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts (peak t=6.74, peak {beta}=0.08), including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including covarying for full-scale IQ and the application of increasingly strict motion exclusion criteria. ConclusionAutism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. This high-resolution identification and localization of structural brain differences support the involvement of distributed neural systems in autism that underlie reward processing, sensory integration, and motor functioning in autism. Summary statementIn the largest voxel-based morphometry study of autism to date, widespread smaller gray and white matter volumes were identified across distributed brain regions implicated in reward and sensorimotor function. Key ResultsO_LIOur largest voxel-based morphometry mega-analysis to date in autism (N=3,051), identified widespread gray and white matter alterations (peak t=7.39, peak {beta}=0.13). C_LIO_LIWe reveal novel associations within thalamic mediodorsal nuclei by leveraging finer voxel-wise volumetric analyses. C_LIO_LIAdditional associations in orbitofrontal cortex, amygdala, and cerebellum, along with extensive white matter alterations across projection, commissural, association fibers, reinforce reward-processing, sensory and motor development theories in autism. C_LI

neuroscience↗

bioRxiv2026

Trustworthy ML/AI for Aging Clocks: Preventing Systematic Prediction Bias in Biological Age Estimation

Machine learning (ML)- and artificial intelligence (AI)-based aging clocks are increasingly used to quantify physiological and molecular aging from omics and medical imaging data as distinct from chronological age. Here, we characterize a fundamental but underappreciated statistical limitation of commonly used ML/AI regression models for continuous outcomes: systematic prediction bias and its propagation to downstream association estimates. This issue becomes more challenging when the true outcome, biological age, is latent and therefore unobserved during ML/AI model training. We demonstrate that systematic prediction bias can distort and, in some cases, even reverse downstream association analyses that use aging clocks as ML/AI-predicted outcomes to assess their associations with exposures or clinical factors. For example, it can produce spurious associations suggesting that older predicted brain age is linked to better cognitive performance, or that older epigenetic age is associated with better kidney function. To address this problem, we introduce a principled and broadly applicable ML/AI regression framework based on constrained optimization, yielding better calibrated aging-clock estimates and valid downstream inference.

bioinformatics↗

bioRxiv2026

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimers disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies ({beta}-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic changes from clinical data, biofluid assays (e.g., CSF), and neuroimaging. Here we evaluated automated machine learning models trained on data curated by the AD Sequencing Project Phenotype Harmonization Consortium (N=7,894 individuals), to predict 26 autopsy-confirmed neuropathological outcomes. Predictors included in vivo clinical and cognitive composite scores, brain measures from 3D structural MRI and diffusion tensor imaging, image-derived measures of white matter hyperintensities (WMH), and CSF biomarkers. Predictive models were trained using ensemble learning with stratified cross-validation. We assessed performance using Spearmans rank correlation and Matthews correlation coefficient, to accommodate co-occurring pathologic changes. The added value of neuroimaging and CSF versus clinical features alone was quantified. Braak stage was among the most consistently predicted outcomes. CSF biomarkers best predicted {beta}-amyloid and tau pathology, but diffusion MRI metrics best captured vascular brain injury and white matter injury, and outperformed clinical and cognitive measures and anatomical MRI in predicting Lewy body disease. Anatomical measures from structural MRI outperformed standard clinical assessments in assessing neurodegeneration and hippocampal sclerosis, and WMH complemented cognitive measures in predicting TDP-43 pathology. These results establish a baseline for comparing modalities for inferring neuropathology.

neuroscience↗

bioRxiv2026

Long-Term Human Skin Platform for Modeling Chronic Inflammation, Environmental Stress, and Therapeutic Intervention

Chronic inflammation drives tissue dysfunction and aging, yet the dynamic interplay between persistent inflammatory signaling and structural deterioration remains difficult to study in human-relevant systems. Here, an advanced long-term human skin platform is presented that preserves native tissue architecture and epidermal, stromal, and immune-associated molecular programs for up to 4 weeks. Using this system, sustained cytokine-driven inflammation was modeled, demonstrating chronic inflammatory transcriptional programs, progressive histopathological changes, and persistent inflammatory mediator secretion that were broadly suppressed by the JAK inhibitor tofacitinib. Using aged donor tissue, prolonged senolytic-associated treatment attenuated inflammatory and remodeling pathways. Finally, UVB exposure triggered coordinated stress and inflammatory responses that were partially mitigated using topical sunscreen, demonstrating compatibility with environmental stress modeling and topical intervention within preserved tissue architecture. Together, these findings establish a versatile human skin platform for modeling chronic inflammation, aging-associated tissue remodeling, and environmental stress, providing a translational framework for investigating skin tissue dysfunction and evaluating therapeutic interventions.

bioengineering↗

bioRxiv2026

Reciprocal regulation between the protein arginine deiminases and mSWI/SNF chromatin remodelers controls skeletal muscle differentiation and regeneration

Protein arginine deiminases (PADs) post-translationally convert arginine to citrulline on target proteins and serve as regulators of multiple cellular functions. PAD enzymes have been implicated in autoimmune disorders, cancer, and other diseases. Inhibiting PAD activity is currently being pursued clinically for therapeutic purposes. However, little is known about PAD function in normal developmental or homeostatic processes. Here we show that multiple PAD isoforms contribute to primary myoblast differentiation by binding to regulatory regions of target genes. Furthermore, we demonstrate a novel, reciprocal requirement for PADs and mammalian SWI/SNF (mSWI/SNF) chromatin remodeling enzymes; PAD enzymes are required for the expression and binding of specific mSWI/SNF enzyme subunits to target gene regulatory sequences while mSWI/SNF enzymes are required for the expression and binding of PAD enzymes. In vivo, the PADs contribute to mouse skeletal muscle regeneration after injury, with PAD4 specifically identified as a required regulator. This work identifies the PADs as critical cofactors in the initiation of skeletal muscle differentiation and reveals previously unappreciated connections between two major co-activator families during normal tissue development. Moreover, the results reveal important considerations for ongoing therapeutic approaches to myriad human diseases that utilize inhibitors of each enzyme family.

molecular biology↗

bioRxiv2026

Meta-learning is expressed through altered prefrontal cortical dynamics

Learning where and when rewards like food and water are available is essential for survival1,2. In the simplest cases where resource availability is stable, animals can learn reward contingencies by integrating outcomes across repeated samples of each possible action. In more natural settings, however, reward availability is governed by structured higher-order rules such as depletion and repletion over time. To adapt flexibly to such changing environments, optimal choices require meta-learning wherein animals learn how to learn from external feedback, ultimately enabling them to infer the underlying reward structure from abstract, generalizable rules rather than relying solely on recent outcomes3,4. The existence of meta-learning in animal behavior is well established3-8, yet the neural circuits and computations that implement it remain poorly understood9-11. Here we investigated meta-learning using a spatial foraging task in which rats acquired a depletion-repletion rule that regulated reward availability, and carried out longitudinal, high-density recordings from the medial prefrontal cortex (mPFC). We show that meta-learning engages specific, systematic changes in mPFC neural dynamics that embed the learned rule and thereby alter how the network learns action values from reward outcomes. These dynamics are based on mixed coding of task structure and value in individual mPFC neurons. At the population level, this coding organizes into low-dimensional dynamical motifs that generalize across task conditions. As meta-learning progresses, these motifs are reshaped to instantiate both rule-guided inference of future states before outcome delivery and rule-based value updating during the outcome period. These results indicate that meta-learning sculpts pre-existing prefrontal dynamics to support the acquisition of new, generalizable reward-learning strategies.

neuroscience↗

bioRxiv2025

Patient induced pluripotent stem cells identify specificities of a reticular pseudodrusen phenotype in age-related macular degeneration

BackgroundAge-related macular degeneration (AMD) is a leading cause of vision loss. Reticular pseudodrusen (RPD), deposits on the apical side of the retinal pigment epithelium (RPE), signify a distinctive and critical AMD phenotype. Yet, their molecular basis and relationship to the conventional drusen seen in AMD remain unclear. ResultsWe generated induced pluripotent stem cell-derived RPE cells from a clinically phenotyped cohort comprising only individuals with conventional drusen (AMD/RPD-) or drusen coexisting with RPD (AMD/RPD+). From these cells, we generated single-cell transcriptomics, proteomics, and functional data to identify differences between the two cohorts. We show that AMD/RPD+ RPE cells exhibit enrichment in extracellular matrix (ECM) remodelling, cytoskeletal, and hypoxia-responsive programs, whereas AMD/RPD- RPE cells display a relatively greater representation of mitochondrial and protein homeostasis pathways. Both subtypes engaged pathways classically linked to ageing, including ECM remodelling and mitochondrial function, but differed in the direction and extent of these changes. Expression and protein quantitative trait loci (QTLs) highlight shared genetic influences on mitochondrial and iron-handling pathways, while disease-interacting eQTLs and transcriptome-wide association study identify regulatory signals that are distinctive of the RPD subtype within AMD, including through regulation of ECM. Functionally, all iPSC-derived RPE formed drusen-like deposits in vitro: AMD/RPD-lines generated more basal deposits, whereas AMD/RPD+ cells exhibited greater structural instability under bisretinoid-induced stress. ConclusionsThese findings indicate that AMD with and without RPD represent mechanistically distinct entities and provide novel insight into the molecular mechanisms underlying disease heterogeneity in AMD.

genetics↗

bioRxiv2025

The changing status of imperiled species in British Columbia over the last 15 years in the absence of a dedicated species at risk law

Gaps in biodiversity protection occur in Canada due to limited jurisdiction of federal species-at-risk laws and the absence of dedicated legislation in many provinces, including British Columbia (B.C.). While lacking legal protection, B.C. maintains Red, Blue, and Yellow Lists of threatened, special-concern, and secure species, respectively, using a NatureServe ranking system. We compiled historical data on species status in B.C. between 2008 and 2024 from the B.C. Conservation Data Centre. B.C. is home to 5,485 Yellow, 1,116 Blue, 491 Red-listed species. Changes in status over this time period were reported for 967 animal species, with an even split in uplistings (more imperiled) and downlistings (less imperiled). More status changes were reported for plants (2,902), mainly due to updated methodology leading to a lower risk status. Analysing the accompanying explanation for each status change revealed that most changes were non-genuine (e.g., new information, taxonomy, or methodology) rather than genuine (e.g., true changes in population size, range, or threats). Genuine improvements in the status of species in B.C. have been exceedingly rare. This analysis indicates that current laws and regulations have been insufficient to recover species at risk within B.C. Plain-language summaryBritish Columbia is the most biodiverse province in Canada, yet 1,607 species are imperiled in the province. We analysed trends, finding a 16% rise in the number of species at risk since 2008. By analysing the provided explanations, we found that status improvements were mostly "non-genuine", caused by changing methodology and/or new data. Strengthening legal protections is essential to prevent biodiversity loss in the province.

ecology↗

bioRxiv2025

Evolutionary Genomics Guides Scalable Coral Probiotics for Climate Resilience

A universal bottleneck limiting probiotic efficacy in medicine, aquaculture, agriculture, and wildlife conservation is uncertain long-term colonization, necessitating repeated administration. We present an evolution-guided framework for probiotic identification based on genomic hallmarks of emerging host dependency, including widespread pseudogenization and insertion sequence proliferation driving genomic restructuring. Applied to coral reefs, we screened over 1,200 coral-associated bacterial isolates and identified Ruegeria MC10 as exhibiting these signatures. Its presence was associated with increased thermal tolerance of a model cnidarian. Following nursery application, MC10 persisted in reef corals for an 8-month monitoring period through a natural bleaching event, improving color retention and retaining algal photosynthesis performance. This work establishes a predictive, scalable pipeline for selecting persistent probiotics, directly addressing a central constraint on microbiome-based interventions across host systems.

microbiology↗

bioRxiv2025

A Robust Fluorogenic Substrate for Chikungunya Virus Protease (nsP2) Activity

Chikungunya virus (CHIKV) is an emerging pathogen with pandemic potential. CHIKV infection in humans is transmitted by mosquitoes and induces common symptoms of high fever, arthralgia and myalgia. Because no specific antiviral drugs for treatment of CHIKV infection are available, drug development remains a central goal. The chikungunya virus protease nsP2 (CHIKVP) has emerged as a key drug target due to its indispensable role in viral replication via cleavage of the viral polyprotein. To date, effective tools for screening for CHIKVP inhibitors that reflect the most critical polyprotein cleavage sites have been lacking, hampering drug-development efforts. We found that the recognition ability of CHIKVP is sensitive to the length of peptide substrates. In this study, we report a robust fluorogenic substrate comprising a 15-mer peptide derived from the nsP3/4 junction from the CHIKV polyprotein. This peptide is flanked by an ACC-Lys(dnp) donor-quencher pair. Our new substrate acc-CHIK15-dnp shows a 20-fold improved signal-to-noise ratio as compared to the previously reported edab8 substrate, which is also based on the nsP3/4 junction. We found acc-CHIK15-dnp is recognized only by CHIKVP but not by other alphavirus proteases. This is surprising due to the high level of sequence conservation in the alpha virus polyprotein junctions and indicates that the P-side residues are more important than the P-side sequence for effective CHIKVP cleavage. The robust signal-to-noise ratio obtained using acc-CHIK15-dnp derived from the nsP3/4 cleavage site enabled much improved small molecule HTS on CHIKV relative to other fluorogenic reporters.

biochemistry↗

bioRxiv2024

RNA-programmable cell type monitoring and manipulation in the human cortex with CellREADR

Reliable and systematic access to diverse cell types is necessary for understanding the organization, function, and pathophysiology of human neural circuits. Methods for targeting human neural populations are scarce and currently center on identifying transcriptional enhancers and engineering viral capsids. Here we demonstrate the utility of CellREADR, a programmable RNA sensor-effector technology that couples cellular RNA sensing to effector protein translation, for accessing, monitoring, and manipulating specific neuron types in human cortex, ex vivo. We designed CellREADRs to target two subpopulations, CALB2 GABAergic interneurons and FOXP2 glutamatergic projection neurons, then validated targeting specificity using histological, electrophysiological, and transcriptomic methods. CellREADR expression of channelrhodopsin and GCamp enabled the manipulation and monitoring of these populations in live cortical microcircuits. By demonstrating specific, reliable, and programmable experimental access to human neuronal subpopulations, our results highlight CellREADRs potential for studying neural circuits and treating brain disorders.

neuroscience↗

bioRxiv2024

The embryo-derived protein PDI is highly conserved among placental mammals and alters the function of the endometrium in species with different implantation strategies.

Pregnancy establishment in mammals requires a complex sequence of events, including bi-lateral embryo-maternal communication, leading up to implantation. This is the time when most pregnancy loss occurs in mammals (including humans and food production species) and dysregulation in embryo-maternal communication contributes to pregnancy loss. Embryo-derived factors modify the function of the endometrium for pregnancy success. We hypothesise that these previously unexplored conceptus-derived proteins may be involved in altering the function of the endometrium to facilitate early pregnancy events in mammals with different early pregnancy phenotypes. Here, we show that protein disulphide-isomerase (PDI) is a highly conserved protein among mammals, and provide evidence for a species-specific roles for PDI in endometrial function in mammals with different implantation strategies. We show how PDI alters the endometrial transcriptome in human and bovine in vitro in a species-specific manner, and using a microfluidic approach we demonstrate that it alters the secretome capability of the endometrium. We also provide evidence from in vitro assays using human-derived cells that MNS1, a transcript commonly downregulated in response to PDI in human and bovine endometrial epithelial cells, may be involved in the attachment (but not invasion) phase of implantation. We propose that the trophoblast-derived protein PDI, is involved in supporting the modulation of the uterine luminal fluid secreted by the endometrium to support conceptus nourishment, and also in the process of embryo attachment to the uterine lumen for pregnancy success in mammals. SIGNIFICANCE STATEMENTWe provide evidence that a highly conserved protein (PDI) alters the endometrial transcriptome in a species- and cell-specific manner. Exposure of endometrial epithelia to PDI altered genes belonging to immune modulatory, pro-inflammatory, and adhesion-pathways. One transcript, MNS1, was commonly downregulated in endometrial epithelia from species with superficial (bovine) and invasive (human) implantation morphologies. Knockdown of MNS1 expression in humans epithelia altered the ability of human trophoblast BeWo spheroids to attach suggesting a mechanism by which PDI affects implantation in human and bovine. In addition, using a microfluidics approach we have shown that PDI alters the secretome in a species-specific manner demonstrating PDI alters a key function of the endometrium in mammals.

developmental biology↗

bioRxiv2024

A site-wise reliability analysis of the ABCD diffusion fractional anisotropy data, impact of the scanner and analytical pipeline

The Adolescent Brain and Cognitive Development (ABCD) project is the largest study of adolescent brain development. ABCD longitudinally tracks 11,868 participants aged 9-10 years from 21 sites using standardized protocols for multi-site MRI data collection and analysis. While the multi-site and multi-scanner study design enhances the robustness and generalizability of analysis results, it may also introduce non-biological variances including scanner-related variations, subject motion, and deviations from protocols. ABCD imaging data were collected biennially within a period of ongoing maturation in cortical thickness and integrity of cerebral white matter. These changes can bias the classical test-retest methodologies, such as intraclass correlation coefficients (ICC). We developed a site-wise adaptive ICC (AICC) to evaluate the reliability of imaging-derived phenotypes while accounting for ongoing brain development. AICC iteratively estimates the population-level age-related brain development trajectory using a weighted mixed model and updates age-corrected site-wise reliability until convergence. We evaluated the test-retest reliability of regional fractional anisotropy (FA) measures from diffusion tensor imaging and cortical thickness (CT) from structural MRI data for each site. The mean AICC for 20 FA tracts across sites was 0.61{+/-}0.19, lower than the mean AICC for CT in 34 regions across sites, 0.76{+/-}0.12. Remarkably, sites using Siemens scanners consistently showed significantly higher AICC values compared to those using GE/Philips scanners for both FA (AICC=0.71{+/-}0.12 vs 0.46{+/-}0.17, p<0.001) and CT (AICC=0.80{+/-}0.10 vs 0.69{+/-}0.11, p<0.001). These findings demonstrate site-and-scanner related variations in data quality and underscore the necessity for meticulous data curation in subsequent association analyses.

neuroscience↗

bioRxiv2024

Regional specialization manifests in the reliability of neural population codes

The brain has the remarkable ability to learn and guide the performance of complex tasks. Decades of lesion studies suggest that different brain regions perform specialized functions in support of complex behaviors1-3. Yet recent large-scale studies of neural activity reveal similar patterns of activity and encoding distributed widely throughout the brain4-6. How these distributed patterns of activity and encoding are compatible with regional specialization of brain function remains unclear. Two frontal brain regions, the dorsal medial prefrontal cortex (dmPFC) and orbitofrontal cortex (OFC), are a paradigm of this conundrum. In the setting complex behaviors, the dmPFC is necessary for choosing optimal actions2,7,8, whereas the OFC is necessary for waiting for3,9 and learning from2,7,9-12 the outcomes of those actions. Yet both dmPFC and OFC encode both choice- and outcome-related quantities13-20. Here we show that while ensembles of neurons in the dmPFC and OFC of rats encode similar elements of a cognitive task with similar patterns of activity, the two regions differ in when that coding is consistent across trials ("reliable"). In line with the known critical functions of each region, dmPFC activity is more reliable when animals are making choices and less reliable preceding outcomes, whereas OFC activity shows the opposite pattern. Our findings identify the dynamic reliability of neural population codes as a mechanism whereby different brain regions may support distinct cognitive functions despite exhibiting similar patterns of activity and encoding similar quantities.

neuroscience↗

bioRxiv2023

Brain-Age Prediction: Systematic Evaluation of Site Effects, and Sample Age Range and Size

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of site harmonization, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2,101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 years and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1,600 participants. These findings have been incorporated into CentileBrain [https://centilebrain.org/#/brainAGE2], an open-science, web-based platform for individualized neuroimaging metrics.

bioinformatics↗

bioRxiv2023

Localized Rift Valley Fever Virus Persistence Depends on a High Transovarial Transmission Fraction

Rift Valley fever virus (RVFV) has spread beyond continental Africa and threatens to follow West Nile, chikungunya and Zika viruses into the Americas. Its impact in new localities and the capacity to control future outbreaks, depends on whether and how RVFV persists at small spatial scales. Transovarial transmission (TOT) is hypothesized as an important mechanism for local persistence, yet its role in RVFV ecology remains poorly understood. We examine whether RVFV can persist locally via TOT while maintaining a realistic seroprevalence pattern of interepidemic and epidemic transmission. We developed a mechanistic, compartmental model of RVFV dynamics within a single host (sheep) and two vector (mosquito) populations, driven by temperate climatic factors. Decades-long persistence was possible in our simulations, which generally captured the observed outbreak patterns in central South Africa with a mean annual seroprevalence ([~]23%) within the range reported during interepidemic periods (5-40%). Persistence was only possible with a substantial TOT fraction and over a narrow range of parameters. The basic reproduction number (R0) was close to one at mean vector population sizes, suggesting a relatively limited expansion of the infected vector population during outbreaks. This limited expansion provides the system with the flexibility to support both low-level transmission and large outbreaks and, counterintuitively, large outbreaks resulted in smaller infected Aedes egg populations. This has important consequences for control: low-level vaccination may prevent large outbreaks without eliminating RVFV and local control efforts may be most effective immediately following an outbreak, suggesting elimination may be possible after emergence in temperate regions.

ecology↗

bioRxiv2023

The effects of genome size on cell size and the functional composition and morphology of leaves: a case study in Rhododendron (Ericaceae)

Background and AimsDespite the predominance of scaling photosynthetic metabolism by two-dimensional leaf surface area, leaves are three-dimensional structures composed of multiple tissues that directly and indirectly influence photosynthetic metabolism. The structure of leaf surfaces for CO2 diffusion and light transmission and the internal volume of tissues that process energy and matter work together to control rates of resource acquisition and turnover. Here we investigate the influence of cell size and packing density on resource acquisition as measured by surface conductance to CO2 and water vapor and on resource turnover as measured by leaf water turnover time. MethodsWe sampled wild and cultivated congeneric species in the genus Rhododendron (Ericaceae) and measured genome size, anatomical traits related to cell sizes and packing densities, and morphological traits related to water content and dry mass allocation. ResultsAmong Rhododendron, anatomical traits related to cell size and morphological traits related to water content and dry mass investment varied largely orthogonally to each other, allowing for many combinations of leaf traits to exist. However, there was a strong, negative relationship between the leaf water residence time ({tau}) and the maximum leaf surface conductance per leaf volume (gmax,vol), both of which are influenced by cell size and cell packing densities. ConclusionsDespite leaf function being controlled by many potential combinations of leaf cell- and tissue-level traits, cell size has a pervasive effect on leaf function. Small cells allow for higher diffusion of CO2 and water vapor per unit leaf volume (gmax,vol) even at constant leaf thickness, but small cells also result in shorter leaf water residence times ({tau}). The strong tradeoff between gmax,vol and ({tau}) illuminates how genome size-cell size allometry influences the fast-slow continuum of plant carbon and water economy.

plant biology↗