Adaptive sampling method to monitor low-risk pathways with limited surveillance resources.

The rise of globalization has led to a sharp increase in international trade with high volumes of containers, goods, and items moving across the world. Unfortunately, these trade pathways also facilitate the movement of unwanted pests, weeds, diseases, and pathogens. Each item could contain biosecurity risk material, but it is impractical to inspect every item. Instead, inspection efforts typically focus on high-risk items. However, low risk does not imply no risk. It is crucial to monitor the low-risk pathways to ensure that they are and remain low risk. To do so, many approaches would seek to estimate the risk to some precision, but increasingly lower risks require more samples. On a low-risk pathway that can be afforded only limited inspection resources, it makes more sense to assign fewer samples to the lower risk activities. We approach the problem by introducing two thresholds. Our method focuses on letting us know whether the risk is below certain thresholds, rather than estimating the risk precisely. This method also allows us to detect a significant change in risk. Our approach typically requires less sampling than previous methods, while still providing evidence to regulators to help them efficiently and effectively allocate inspection effort.

Characterization of hyperpolarization-activated cyclic nucleotide-gated channels in oligodendrocytes.

Mature oligodendrocytes (OLG) are the myelin-forming cells of the central nervous system. Recent work has shown a dynamic role for these cells in the plasticity of neural circuits, leading to a renewed interest in voltage-sensitive currents in OLG. Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and their respective current (Ih) were recently identified in mature OLG and shown to play a role in regulating myelin length. Here we provide a biochemical and electrophysiological characterization of HCN channels in cells of the oligodendrocyte lineage. We observed that mice with a nonsense mutation in the Hcn2 gene (Hcn2ap/ap) have less white matter than their wild type counterparts with fewer OLG and fewer oligodendrocyte progenitor cells (OPCs). Hcn2ap/ap mice have severe motor impairments, although these deficits were not observed in mice with HCN2 conditionally eliminated only in oligodendrocytes (Cnpcre/+; Hcn2F/F). However, Cnpcre/+; Hcn2F/F mice develop motor impairments more rapidly in response to experimental autoimmune encephalomyelitis (EAE). We conclude that HCN2 channels in OLG may play a role in regulating metabolism.

Efficient border biosecurity inspection leverages superspreading to reduce biological invasion risk.

Biological invasions are a growing threat to biodiversity, food security, and economies. Rising pressure from increased global trade requires improving border inspection efficiency. Here, we depart from the conventional consignment-by-consignment approach advocated in current inspection standards. Instead, we suggest a broader perspective: evaluating border inspection regimes based on their ability to reduce propagule pressure across entire pathways. Additionally, we demonstrate that most biosecurity pathways exhibit superspreading behavior, that is, consignments from the same pathway have varying infestation rates and contain rare right-tail events (also called overdispersion). We show that greater overdispersion leads to more pronounced diminishing returns, with consequences on the optimal allocation of sampling effort. We leverage these two insights to develop a simple and efficient border inspection regime that can significantly reduce propagule pressure compared to current standards. Our analysis revealed that consignment size is a key driver of biosecurity risk and that sampling proportional to the square root of consignment size is near optimal. In testing, our framework reduced propagule pressure by 31 to 38% compared to current standards. We also identified opportunities to further improve inspection efficiency by considering additional pathway characteristics (i.e., overdispersion parameters, zero inflation, relative risk, sampling cost, detectability) and developed solutions for these more complex scenarios. We anticipate our result will mitigate biological invasion risk with significant implications for biodiversity conservation, food security, and economies worldwide.

Optimal allocation of resources among general and species-specific tools for plant pest biosecurity surveillance.

This paper proposes a surveillance model for plant pests that can optimally allocate resources among survey tools with varying properties. While some survey tools are highly specific for the detection of a single pest species, others are more generalized. There is considerable variation in the cost and sensitivity of these tools, but there are no guidelines or frameworks for identifying which tools are most cost-effective when used in surveillance programs that target the detection of newly invaded populations. To address this gap, we applied our model to design a trapping surveillance program in New Zealand for bark- and wood-boring insects, some of the most serious forest pests worldwide. Our findings show that exclusively utilizing generalized traps (GTs) proves to be highly cost-effective across a wide range of scenarios, particularly when they are capable of capturing all pest species. Implementing surveillance programs that only employ specialized traps (ST) is cost-effective only when these traps can detect highly damaging pests. However, even in such cases, they significantly lag in cost-effectiveness compared to GT-only programs due to their restricted coverage. When both GTs and STs are used in an integrated surveillance program, the total expected cost (TEC) generally diminishes when compared to programs relying on a single type of trap. However, this relative reduction in TEC is only marginally larger than that achieved with GT-only programs, as long as highly damaging species can be detected by GTs. The proportion of STs among the optimal required traps fluctuates based on several factors, including the relative pricing of GTs and STs, pest arrival rates, potential damage, and, more prominently, the coverage capacity of GTs. Our analysis suggests that deploying GTs extensively across landscapes appears to be more cost-effective in areas with either very high or very low levels of relative risk density, potential damage, and arrival rate. Finally, STs are less likely to be required when the pests that are detected by those tools have a higher likelihood of successful eradication because delaying detection becomes less costly for these species.

Advanced Preoperative Planning Techniques in the Management of Complex Proximal Humerus Fractures.

This review evaluates the current literature on the recent advances of preoperative planning in the management of complex proximal humerus fractures (PHF). PHFs can pose a considerable challenge for orthopaedic surgeons due to their diversity in presentation and complexity. Poor preoperative planning can lead to prolonged operations, increased blood loss, higher risk of complications, and increased stress on the surgical team. Recent advances have seen the evolution of preoperative planning from conventional methods to computer-assisted virtual surgical technology (CAVST) and three-dimensional (3D) printing, which have been highlighted as transformative tools for improving preoperative planning and postoperative outcomes. CAVST allows the creation of 3D renderings of patient-specific anatomy, clearly demonstrating fracture patterns and facilitating detailed planning for arthroplasty or surgical fixation. The early studies show promising outcomes however the literature calls for more high-quality randomised controlled trials. Using 3D printing for high-fidelity simulation involving patient-specific physical models offers an immersive experience for surgical planning. Preoperative planning with 3D printing reduces operative time, blood loss and use of fluoroscopy. The technology's potential to produce customisable surgical implants further improves its versatility. There is a need for a cost analysis for the use of these technologies within the orthopaedic field, particularly considering the high expense of 3D printing materials and extended hospital stays until the printed models are available. CAVST and 3D printing also show promising applications within high-fidelity simulation surgical training, with CAVST offering possibilities in virtual reality and haptic-enhanced simulations and 3D printing providing physical models for trainee surgeons to hone their skills. Moving forward, a reduction in the cost of 3D printing and the advancement of CAVST using artificial intelligence would lead to future improvement. In conclusion, preoperative planning supported by these innovative technologies will play a pivotal role in improving surgical outcomes and training for complex PHF cases.

Optimisation of the air fraction correction for lung PET/CT: addressing resolution mismatch.

BACKGROUND: Increased pulmonary [Formula: see text]F-FDG metabolism in patients with idiopathic pulmonary fibrosis, and other forms of diffuse parenchymal lung disease, can predict measurements of health and lung physiology. To improve PET quantification, voxel-wise air fractions (AF) determined from CT can be used to correct for variable air content in lung PET/CT. However, resolution mismatches between PET and CT can cause artefacts in the AF-corrected image. METHODS: Three methodologies for determining the optimal kernel to smooth the CT are compared with noiseless simulations and non-TOF MLEM reconstructions of a patient-realistic digital phantom: (i) the point source insertion-and-subtraction method, [Formula: see text]; (ii) AF-correcting with varyingly smoothed CT to achieve the lowest RMSE with respect to the ground truth (GT) AF-corrected volume of interest (VOI), [Formula: see text]; iii) smoothing the GT image to match the reconstruction within the VOI, [Formula: see text]. The methods were evaluated both using VOI-specific kernels, and a single global kernel optimised for the six VOIs combined. Furthermore, [Formula: see text] was implemented on thorax phantom data measured on two clinical PET/CT scanners with various reconstruction protocols. RESULTS: The simulations demonstrated that at [Formula: see text] iterations (200 i), the kernel width was dependent on iteration number and VOI position in the lung. The [Formula: see text] method estimated a lower, more uniform, kernel width in all parts of the lung investigated. However, all three methods resulted in approximately equivalent AF-corrected VOI RMSEs (<10%) at [Formula: see text]200i. The insensitivity of AF-corrected quantification to kernel width suggests that a single global kernel could be used. For all three methodologies, the computed global kernel resulted in an AF-corrected lung RMSE <10%  at [Formula: see text]200i, while larger lung RMSEs were observed for the VOI-specific kernels. The global kernel approach was then employed with the [Formula: see text] method on measured data. The optimally smoothed GT emission matched the reconstructed image well, both within the VOI and the lung background. VOI RMSE was <10%, pre-AFC, for all reconstructions investigated. CONCLUSIONS: Simulations for non-TOF PET indicated that around 200i were needed to approach image resolution stability in the lung. In addition, at this iteration number, a single global kernel, determined from several VOIs, for AFC, performed well over the whole lung. The [Formula: see text] method has the potential to be used to determine the kernel for AFC from scans of phantoms on clinical scanners.

On the use of solid 133Ba sources as surrogate for liquid 131I in SPECT/CT calibration: a European multi-centre evaluation.

INTRODUCTION: Commissioning, calibration, and quality control procedures for nuclear medicine imaging systems are typically performed using hollow containers filled with radionuclide solutions. This leads to multiple sources of uncertainty, many of which can be overcome by using traceable, sealed, long-lived surrogate sources containing a radionuclide of comparable energies and emission probabilities. This study presents the results of a quantitative SPECT/CT imaging comparison exercise performed within the MRTDosimetry consortium to assess the feasibility of using 133Ba as a surrogate for 131I imaging. MATERIALS AND METHODS: Two sets of four traceable 133Ba sources were produced at two National Metrology Institutes and encapsulated in 3D-printed cylinders (volume range 1.68-107.4 mL). Corresponding hollow cylinders to be filled with liquid 131I and a mounting baseplate for repeatable positioning within a Jaszczak phantom were also produced. A quantitative SPECT/CT imaging comparison exercise was conducted between seven members of the consortium (eight SPECT/CT systems from two major vendors) based on a standardised protocol. Each site had to perform three measurements with the two sets of 133Ba sources and liquid 131I. RESULTS: As anticipated, the 131I pseudo-image calibration factors (cps/MBq) were higher than those for 133Ba for all reconstructions and systems. A site-specific cross-calibration reduced the performance differences between both radionuclides with respect to a cross-calibration based on the ratio of emission probabilities from a median of 12-1.5%. The site-specific cross-calibration method also showed agreement between 133Ba and 131I for all cylinder volumes, which highlights the potential use of 133Ba sources to calculate recovery coefficients for partial volume correction. CONCLUSION: This comparison exercise demonstrated that traceable solid 133Ba sources can be used as surrogate for liquid 131I imaging. The use of solid surrogate sources could solve the radiation protection problem inherent in the preparation of phantoms with 131I liquid activity solutions as well as reduce the measurement uncertainties in the activity. This is particularly relevant for stability measurements, which have to be carried out at regular intervals.

Quantitative validation of Monte Carlo SPECT simulation: application to a Mediso AnyScan GATE simulation.

BACKGROUND: Monte Carlo (MC) simulations are used in nuclear medicine imaging as they provide unparalleled insight into processes that are not directly experimentally measurable, such as scatter and attenuation in an acquisition. Whilst MC is often used to provide a 'ground-truth', this is only the case if the simulation is fully validated against experimental data. This work presents a quantitative validation for a MC simulation of a single-photon emission computed tomography (SPECT) system. METHODS: An MC simulation model of the Mediso AnyScan SCP SPECT system installed at the UK National Physical Laboratory was developed in the GATE (Geant4 Application for Tomographic Emission) toolkit. Components of the detector head and two collimator configurations were modelled according to technical specifications and physical measurements. Experimental detection efficiency measurements were collected for a range of energies, permitting an energy-dependent intrinsic camera efficiency correction function to be determined and applied to the simulation on an event-by-event basis. Experimental data were collected in a range of geometries with [Formula: see text]Tc for comparison to simulation. The procedure was then repeated with [Formula: see text]Lu to determine how the validation extended to another isotope and set of collimators. RESULTS: The simulation's spatial resolution, sensitivity, energy spectra and the projection images were compared with experimental measurements. The simulation and experimental uncertainties were determined and propagated to all calculations, permitting the quantitative agreement between simulated and experimental SPECT acquisitions to be determined. Statistical agreement was seen in sinograms and projection images of both [Formula: see text]Tc and [Formula: see text]Lu data. Average simulated and experimental sensitivity ratios of ([Formula: see text]) were seen for emission and scatter windows of [Formula: see text]Tc, and ([Formula: see text]) and ([Formula: see text]) for the 113 and 208 keV emissions of [Formula: see text]Lu, respectively. CONCLUSIONS: MC simulations will always be an approximation of a physical system and the level of agreement should be assessed. A validation method is presented to quantify the level of agreement between a simulation model and a physical SPECT system.

Triple modality image reconstruction of PET data using SPECT, PET, CT information increases lesion uptake in images of patients treated with radioembolization with [Formula: see text] micro-spheres.

PURPOSE: Nuclear medicine imaging modalities like computed tomography (CT), single photon emission CT (SPECT) and positron emission tomography (PET) are employed in the field of theranostics to estimate and plan the dose delivered to tumors and the surrounding tissues and to monitor the effect of the therapy. However, therapeutic radionuclides often provide poor images, which translate to inaccurate treatment planning and inadequate monitoring images. Multimodality information can be exploited in the reconstruction to enhance image quality. Triple modality PET/SPECT/CT scanners are particularly useful in this context due to the easier registration process between images. In this study, we propose to include PET, SPECT and CT information in the reconstruction of PET data. The method is applied to Yttrium-90 ([Formula: see text]Y) data. METHODS: Data from a NEMA phantom filled with [Formula: see text]Y were used for validation. PET, SPECT and CT data from 10 patients treated with Selective Internal Radiation Therapy (SIRT) were used. Different combinations of prior images using the Hybrid kernelized expectation maximization were investigated in terms of VOI activity and noise suppression. RESULTS: Our results show that triple modality PET reconstruction provides significantly higher uptake when compared to the method used as standard in the hospital and OSEM. In particular, using CT-guided SPECT images, as guiding information in the PET reconstruction significantly increases uptake quantification on tumoral lesions. CONCLUSION: This work proposes the first triple modality reconstruction method and demonstrates up to 69% lesion uptake increase over standard methods with SIRT [Formula: see text]Y patient data. Promising results are expected for other radionuclide combination used in theranostic applications using PET and SPECT.

Development of a validation imaging dataset for Molecular Radiotherapy dosimetry multicenter intercomparison exercises based on anthropomorphic phantoms.

Validation of a Molecular Radiotherapy (MRT) dosimetry system requires imaging data for which an accompanying "ground truth" pharmacokinetic model and absorbed dose calculation are known. METHODS: We present a methodology for production of a validation dataset for image based 177Lu dotatate dosimetry calculations. A pharmacokinetic model is presented with activity concentrations corresponding to common imaging timepoints. Anthropomorphic 3D printed phantoms, corresponding to the organs at risk, have been developed to provide SPECT/CT and Whole Body imaging with known organ activities corresponding to common clinical timepoints. RESULTS: Results for the accuracy of phantom filling reproduce the activity concentrations from the pharmacokinetic model for all timepoints and organs within measurement uncertainties, with a mean deviation of 0.6(8)%. The imaging dataset, ancillary data and phantoms designs are provided as a source of well characterized input data for the validation of clinical MRT dosimetry systems. CONCLUSIONS: The combination of pharmacokinetic modelling with the use of anthropomorphic 3D printed phantoms are a promising procedure to provide data for the validation of Molecular Radiotherapy Dosimetry systems, allowing multicentre comparisons.

Robotic-Assisted Knee Arthroplasty: Insights and Implications From Current Literature.

Robotic-assisted knee arthroplasty has emerged as a promising development, aiming to enhance surgical precision and patient outcomes. This literature review examines the clinical efficacy, cost implications, environmental impact, and potential of telesurgery in robotic-assisted total knee arthroplasty (RATKA) and robotic-assisted unicompartmental knee arthroplasty (RAUKA) relative to conventional techniques. A thorough literature search was conducted across medical databases. Clinical and radiological outcomes of RATKA and RAUKA were extracted and analyzed. Direct costs, operating time, surgeon learning curve, environmental implications, and the futuristic concept of telesurgery were also considered. Subjective patient assessments such as WOMAC, Oxford Knee Score, and SF-36, alongside objective measures like HSS score and KSS, were commonly used. Radiological parameters like hip-knee-ankle (HKA) and femorotibial angle provided insights into post-operative alignment. Evidence indicated sporadic high-level design studies, often with limited samples. Cost remains a major constraint with robotic systems, though high-volume cases might offset expenses. Environmental assessments revealed robotic surgeries generate a higher carbon footprint. Telesurgery, an evolving field, could transcend geographical boundaries but is not without challenges, including high costs, latency issues, and cyber threats. While robotic-assisted surgeries may hold promise in the future, substantial barriers, including acquisition costs, potential surgeon deskilling, and environmental concerns, need addressing. Greater robot utilization may drive costs down with more competitors entering the market. Continued research, especially multi-center RCTs, is pivotal to solidifying the role of robotic systems in knee arthroplasty.

Repurposing the cardiac glycoside digoxin to stimulate myelin regeneration in chemically-induced and immune-mediated mouse models of multiple sclerosis.

Multiple sclerosis (MS) is a central nervous system (CNS) autoimmune disease characterized by inflammation, demyelination, and neurodegeneration. The ideal MS therapy would both specifically inhibit the underlying autoimmune response and promote repair/regeneration of myelin as well as maintenance of axonal integrity. Currently approved MS therapies consist of non-specific immunosuppressive molecules/antibodies which block activation or CNS homing of autoreactive T cells, but there are no approved therapies for stimulation of remyelination nor maintenance of axonal integrity. In an effort to repurpose an FDA-approved medication for myelin repair, we chose to examine the effectiveness of digoxin, a cardiac glycoside (Na+ /K+ ATPase inhibitor), originally identified as pro-myelinating in an in vitro screen. We found that digoxin regulated multiple genes in oligodendrocyte progenitor cells (OPCs) essential for oligodendrocyte (OL) differentiation in vitro, promoted OL differentiation both in vitro and in vivo in female naïve C57BL/6J (B6) mice, and stimulated recovery of myelinated axons in B6 mice following demyelination in the corpus callosum induced by cuprizone and spinal cord demyelination induced by lysophosphatidylcholine (LPC), respectively. More relevant to treatment of MS, we show that digoxin treatment of mice with established MOG35-55 -induced Th1/Th17-mediated chronic EAE combined with tolerance induced by the i.v. infusion of biodegradable poly(lactide-co-glycolide) nanoparticles coupled with MOG35-55 (PLG-MOG35-55 ) completely ameliorated clinical disease symptoms and stimulated recovery of OL lineage cell numbers. These findings provide critical pre-clinical evidence supporting future clinical trials of myelin-specific tolerance with myelin repair/regeneration drugs, such as digoxin, in MS patients.

Hybrid kernelised expectation maximisation for Bremsstrahlung SPECT reconstruction in SIRT with 90Y micro-spheres.

BACKGROUND: Selective internal radiation therapy with Yttrium-90 microspheres is an effective therapy for liver cancer and liver metastases. Yttrium-90 is mainly a high-energy beta particle emitter. These beta particles emit Bremsstrahlung radiation during their interaction with tissue making post-therapy imaging of the radioactivity distribution feasible. Nevertheless, image quality and quantification is difficult due to the continuous energy spectrum which makes resolution modelling, attenuation and scatter estimation challenging and therefore the dosimetry quantification is inaccurate. As a consequence a reconstruction algorithm able to improve resolution could be beneficial. METHODS: In this study, the hybrid kernelised expectation maximisation (HKEM) is used to improve resolution and contrast and reduce noise, in addition a modified HKEM called frozen HKEM (FHKEM) is investigated to further reduce noise. The iterative part of the FHKEM kernel was frozen at the 72nd sub-iteration. When using ordered subsets algorithms the data is divided in smaller subsets and the smallest algorithm iterative step is called sub-iteration. A NEMA phantom with spherical inserts was used for the optimisation and validation of the algorithm, and data from 5 patients treated with Selective internal radiation therapy were used as proof of clinical relevance of the method. RESULTS: The results suggest a maximum improvement of 56% for region of interest mean recovery coefficient at fixed coefficient of variation and better identification of the hot volumes in the NEMA phantom. Similar improvements were achieved with patient data, showing 47% mean value improvement over the gold standard used in hospitals. CONCLUSIONS: Such quantitative improvements could facilitate improved dosimetry calculations with SPECT when treating patients with Selective internal radiation therapy, as well as provide a more visible position of the cancerous lesions in the liver.

Assessing the quality of offshore Binomial sampling biosecurity inspections using onshore inspections.

Introduction of pests and diseases through trade is one of the main socio-ecological challenges worldwide. Although Binomial sampling inspection at the border can reduce pest entry risk, it is common for consignments to fail inspection, wasting resources for both exporter and importer. Outsourcing the inspection to the exporting country could reduce the cost of inspection for both parties. However, there is then a need to assess the quality of the offshore inspection. In this paper, we develop an inverse method combining past inspection data on the pathway, an onshore inspection sample, and the Beta-Binomial model to infer the sample size of the offshore inspection. We illustrate the method on two case studies: the importation of live plants through germplasm into Australia and the importation of pelleted seeds in New Zealand. In these case studies, we found that detecting four to five infested units in a single onshore inspection was typically sufficient to significantly doubt the presence of a compliant offshore inspection. We also ran a simulation experiment to quantify the statistical power to reject or accept the presence of compliant offshore inspection in practice: In highly infested pathways, we could detect the absence of offshore inspections after inspecting five consignments onshore. Less infested pathways required inspecting 20 to 60 consignments onshore. Our study demonstrates that Binomial sampling onshore can be used to assess the quality of offshore inspections.

Arthropods on imported plant products: Volumes predict general trends while contextual details enhance predictive power.

Agricultural biosecurity interventions are aimed at minimizing introductions of harmful non-native organisms to new areas via agricultural trade. To prioritize such interventions, historical data on interceptions have been used to elucidate which factors determine the likelihood that a particular import is carrying a harmful organism. Here we use an interception data set of arthropod contaminants recorded on plant imports arriving in South Africa from 2005 to 2019, comprising 13,566 samples inspected for arthropod contaminants, of which 4902 were positive for the presence of at least one arthropod. We tested 29 predictor variables that have previously been used to explain variation in rates of detection and three variables describing possible sources of additional variation and grouped these into six mutually exclusive "factor classes." We used boosted regression trees as a non-parametric stochastic machine-learning method to build models for each factor class and interactions between them. We explored the influence of these variables with data split either randomly or chronologically. While we identified some specific patterns that could be explained post-hoc by historical events, only inspected volumes were reliably correlated with detection of arthropod contaminants across the whole data set. However, inspected volumes could not predict future interceptions of arthropods, which instead relied on contextual factors such as country, crop or year of import. This suggests that, although certain factors may be important in certain circumstances or for particular crops or commodities, there is little general predictive power in the current data. Instead, an idiographic approach would be most beneficial in biosecurity to ascertain the details of why a particular pest arrived on a particular pathway and how it might move (and be stopped) in future.

A field experiment characterizing variable detection rates during plant surveys.

Surveys aimed at finding threatened and invasive species can be challenging due to individual rarity and low and variable individual detection rates. Detection rate in plant surveys typically varies due to differences among observers, among the individual plants being surveyed (targets), and across background environments. Interactions among these 3 components may occur but are rarely estimated due to limited replication and control during data collection. We conducted an experiment to investigate sources of variation in detection of 2 Pilosella species that are invasive and sparsely distributed in the Alpine National Park, Australia. These species are superficially similar in appearance to other yellow-flowered plants occurring in this landscape. We controlled the presence and color of flowers on target Pilosella plants and controlled their placement in plots, which were selected for their variation in cover of non-target yellow flowers and dominant vegetation type. Observers mimicked Pilosella surveys in the plots and reported 1 categorical and 4 quantitative indicators of their survey experience level. We applied survival analysis to detection data to model the influence of both controlled and uncontrolled variables on detection rate. Orange- and yellow-flowering Pilosella in grass- and heath-dominated vegetation were detected at a higher rate than nonflowering Pilosella. However, this detection gain diminished as the cover of other co-occurring yellow-flowering species increased. Recent experience with Pilosella surveys improved detection rate. Detection experiments are a direct and accessible means of understanding detection processes and interpreting survey data for threatened and invasive species. Our detection findings have been used for survey planning and can inform progress toward eradication. Interaction of target and background characteristics determined detection rate, which enhanced predictions in the Pilosella eradication program and demonstrated the difficulty of transferring detection findings into untested environments.

Un Experimento de Campo que Caracteriza las Tasas Variables de Detección en los Censos de Plantas Resumen Los censos enfocados en encontrar especies amenazadas e invasoras pueden ser un reto debido a la rareza individual y las tasas bajas y variables de detección individual. Las tasas de detección en los censos botánicos varían comúnmente por las diferencias entre los observadores, entre las plantas individuales que se están censando (objetivo de búsqueda) y en el entorno ambiental. La interacción entre estos tres componentes puede ocurrir, pero rara vez se calcula debido a la replicación y control limitados durante la recolección de datos. Realizamos un experimento para investigar el origen de las variaciones en la detección de dos especies de Pilosella que son invasoras y están distribuidas escasamente en el Parque Nacional Alpino en Australia. Estas especies son superficialmente similares en apariencia a otras plantas de flores amarillas que habitan este paisaje. Controlamos la presencia y el color de las flores en las plantas de Pilosella, así como su colocación en lotes, los cuales fueron seleccionados por su variación en la cobertura de flores amarillas y tipos de vegetación circundantes. Los observadores imitaron los censos de Pilosella en los lotes y reportaron un indicador categórico y cuatro cuantitativos de su nivel de experiencia en censos. Aplicamos el análisis de supervivencia a los datos de detección para modelar la influencia de las variables controladas y no controladas sobre la tasa de detección. Las plantas de Pilosella con flores amarillas y anaranjadas en la vegetación dominada por pastos y brezales fueron detectadas con una tasa mayor que las plantas de Pilosella sin flores. Sin embargo, esta ganancia en la detección disminuyó conforme incrementó la cobertura de otras plantas con flores amarillas. La experiencia reciente de los observadores con censos de Pilosella aumentó la tasa de detección. Los experimentos de detección son un medio directo y accesible para entender los procesos de detección e interpretar los datos de los censos de especies amenazadas e invasoras. Nuestros resultados en la detección han sido utilizados para la planeación de censos y pueden guiar el progreso hacia la erradicación. La interacción de las características diana y del entorno determinaron la tasa de detección, la cual mejoró las predicciones en el programa de erradicación de Pilosella y demostró la dificultad de transferir los resultados de detección hacia ambientes sin ensayos.

Optimal allocation of PCR tests to minimise disease transmission through contact tracing and quarantine.

PCR testing is a crucial capability for managing disease outbreaks, but it is also a limited resource and must be used carefully to ensure the information gain from testing is valuable. Testing has two broad uses for informing public health policy, namely to track epidemic dynamics and to reduce transmission by identifying and managing cases. In this work we develop a modelling framework to examine the effects of test allocation in an epidemic, with a focus on using testing to minimise transmission. Using the COVID-19 pandemic as an example, we examine how the number of tests conducted per day relates to reduction in disease transmission, in the context of logistical constraints on the testing system. We show that if daily testing is above the routine capacity of a testing system, which can cause delays, then those delays can undermine efforts to reduce transmission through contact tracing and quarantine. This work highlights that the two goals of aiming to reduce transmission and aiming to identify all cases are different, and it is possible that focusing on one may undermine achieving the other. To develop an effective strategy, the goals must be clear and performance metrics must match the goals of the testing strategy. If metrics do not match the objectives of the strategy, then those metrics may incentivise actions that undermine achieving the objectives.

A multicentre and multi-national evaluation of the accuracy of quantitative Lu-177 SPECT/CT imaging performed within the MRTDosimetry project.

PURPOSE: Patient-specific dosimetry is required to ensure the safety of molecular radiotherapy and to predict response. Dosimetry involves several steps, the first of which is the determination of the activity of the radiopharmaceutical taken up by an organ/lesion over time. As uncertainties propagate along each of the subsequent steps (integration of the time-activity curve, absorbed dose calculation), establishing a reliable activity quantification is essential. The MRTDosimetry project was a European initiative to bring together expertise in metrology and nuclear medicine research, with one main goal of standardizing quantitative 177Lu SPECT/CT imaging based on a calibration protocol developed and tested in a multicentre inter-comparison. This study presents the setup and results of this comparison exercise. METHODS: The inter-comparison included nine SPECT/CT systems. Each site performed a set of three measurements with the same setup (system, acquisition and reconstruction): (1) Determination of an image calibration for conversion from counts to activity concentration (large cylinder phantom), (2) determination of recovery coefficients for partial volume correction (IEC NEMA PET body phantom with sphere inserts), (3) validation of the established quantitative imaging setup using a 3D printed two-organ phantom (ICRP110-based kidney and spleen). In contrast to previous efforts, traceability of the activity measurement was required for each participant, and all participants were asked to calculate uncertainties for their SPECT-based activities. RESULTS: Similar combinations of imaging system and reconstruction lead to similar image calibration factors. The activity ratio results of the anthropomorphic phantom validation demonstrate significant harmonization of quantitative imaging performance between the sites with all sites falling within one standard deviation of the mean values for all inserts. Activity recovery was underestimated for total kidney, spleen, and kidney cortex, while it was overestimated for the medulla. CONCLUSION: This international comparison exercise demonstrates that harmonization of quantitative SPECT/CT is feasible when following very specific instructions of a dedicated calibration protocol, as developed within the MRTDosimetry project. While quantitative imaging performance demonstrates significant harmonization, an over- and underestimation of the activity recovery highlights the limitations of any partial volume correction in the presence of spill-in and spill-out between two adjacent volumes of interests.

Approaches for estimating benefits and costs of interventions in plant biosecurity across invasion phases.

Nonnative plant pests cause billions of dollars in damages. It is critical to prevent or reduce these losses by intervening at various stages of the invasion process, including pathway risk management (to prevent pest arrival), surveillance and eradication (to counter establishment), and management of established pests (to limit damages). Quantifying benefits and costs of these interventions is important to justify and prioritize investments and to inform biosecurity policy. However, approaches for these estimations differ in (1) the assumed relationship between supply, demand, and prices, and (2) the ability to assess different types of direct and indirect costs at invasion stages, for a given arrival or establishment probability. Here we review economic approaches available to estimate benefits and costs of biosecurity interventions to inform the appropriate selection of approaches. In doing so, we complement previous studies and reviews on estimates of damages from invasive species by considering the influence of economic and methodological assumptions. Cost accounting is suitable for rapid decisions, specific impacts, and simple methodological assumptions but fails to account for feedbacks, such as market adjustments, and may overestimate long-term economic impacts. Partial equilibrium models consider changes in consumer and producer surplus due to pest impacts or interventions and can account for feedbacks in affected sectors but require specialized economic models, comprehensive data sets, and estimates of commodity supply and demand curves. More intensive computable general equilibrium models can account for feedbacks across entire economies, including capital and labor, and linkages among these. The two major considerations in choosing an approach are (1) the goals of the analysis (e.g., consideration of a single pest or intervention with a limited range of impacts vs. multiple interventions, pests or sectors), and (2) the resources available for analysis such as knowledge, budget and time.

Automating the assessment of biofouling in images using expert agreement as a gold standard.

Biofouling is the accumulation of organisms on surfaces immersed in water. It is of particular concern to the international shipping industry because it increases fuel costs and presents a biosecurity risk by providing a pathway for non-indigenous marine species to establish in new areas. There is growing interest within jurisdictions to strengthen biofouling risk-management regulations, but it is expensive to conduct in-water inspections and assess the collected data to determine the biofouling state of vessel hulls. Machine learning is well suited to tackle the latter challenge, and here we apply deep learning to automate the classification of images from in-water inspections to identify the presence and severity of fouling. We combined several datasets to obtain over 10,000 images collected from in-water surveys which were annotated by a group biofouling experts. We compared the annotations from three experts on a 120-sample subset of these images, and found that they showed 89% agreement (95% CI: 87-92%). Subsequent labelling of the whole dataset by one of these experts achieved similar levels of agreement with this group of experts, which we defined as performing at most 5% worse (p [Formula: see text] 0.009-0.054). Using these expert labels, we were able to train a deep learning model that also agreed similarly with the group of experts (p [Formula: see text] 0.001-0.014), demonstrating that automated analysis of biofouling in images is feasible and effective using this method.