Reliable prediction of difficult airway for tracheal intubation from patient preoperative photographs by machine learning methods

BACKGROUND

Estimating the risk of a difficult tracheal intubation should help clinicians in better anaesthesia planning, to maximize patient safety. Routine bedside screenings suffer from low sensitivity.

OBJECTIVE

To develop and evaluate machine learning (ML) and deep learning (DL) algorithms for the reliable prediction of intubation risk, using information about airway morphology.

METHODS

Observational, prospective cohort study enrolling n=623 patients who underwent tracheal intubation: 53/623 difficult cases (prevalence 8.51%). First, we used our previously validated deep convolutional neural network (DCNN) to extract 2D image coordinates for 27 + 13 relevant anatomical landmarks in two preoperative photos (frontal and lateral views). Here we propose a method to determine the 3D pose of the camera with respect to the patient and to obtain the 3D world coordinates of these landmarks. Then we compute a novel set of dM=59 morphological features (distances, areas, angles and ratios), engineered with our anaesthesiologists to characterize each individual's airway anatomy towards prediction. Subsequently, here we propose four ad hoc ML pipelines for difficult intubation prognosis, each with four stages: feature scaling, imputation, resampling for imbalanced learning, and binary classification (Logistic Regression, Support Vector Machines, Random Forests and eXtreme Gradient Boosting). These compound ML pipelines were fed with the dM=59 morphological features, alongside dD=7 demographic variables. Here we trained them with automatic hyperparameter tuning (Bayesian search) and probability calibration (Platt scaling). In addition, we developed an ad hoc multi-input DCNN to estimate the intubation risk directly from each pair of photographs, i.e. without any intermediate morphological description. Performance was evaluated using optimal Bayesian decision theory. It was compared against experts' judgement and against state-of-the-art methods (three clinical formulae, four ML, four DL models).

RESULTS

Our four ad hoc ML pipelines with engineered morphological features achieved similar discrimination capabilities: median AUCs between 0.746 and 0.766. They significantly outperformed both expert judgement and all state-of-the-art methods (highest AUC at 0.716). Conversely, our multi-input DCNN yielded low performance due to overfitting. This same behaviour occurred for the state-of-the-art DL algorithms. Overall, the best method was our XGB pipeline, with the fewest false negatives at the optimal Bayesian decision threshold.

CONCLUSIONS

We proposed and validated ML models to assist clinicians in anaesthesia planning, providing a reliable calibrated estimate of airway intubation risk, which outperformed expert assessments and state-of-the-art methods. Our novel set of engineered features succeeded in providing informative descriptions for prognosis.

Functional ultrasound imaging of the human spinal cord

Utilizing the first in-human functional ultrasound imaging (fUSI) of the spinal cord, we demonstrate the integration of spinal functional responses to electrical stimulation. We record and characterize the hemodynamic responses of the spinal cord to a neuromodulatory intervention commonly used for treating pain and increasingly used for the restoration of sensorimotor and autonomic function. We found that the hemodynamic response to stimulation reflects a spatiotemporal modulation of the spinal cord circuitry not previously recognized. Our analytical capability offers a mechanism to assess blood flow changes with a new level of spatial and temporal precision in vivo and demonstrates that fUSI can decode the functional state of spinal networks in a single trial, which is of fundamental importance for developing real-time closed-loop neuromodulation systems. This work is a critical step toward developing a vital technique to study spinal cord function and effects of clinical neuromodulation.

Cost-sensitive ordinal classification methods to predict SARS-CoV-2 pneumonia severity

OBJECTIVE

To study the suitability of costsensitive ordinal artificial intelligence-machine learning (AIML) strategies in the prognosis of SARS-CoV-2 pneumonia severity.

MATERIALS & METHODS

Observational, retrospective, longitudinal, cohort study in 4 hospitals in Spain. Information regarding demographic and clinical status was supplemented by socioeconomic data and air pollution exposures. We proposed AI-ML algorithms for ordinal classification via ordinal decomposition and for cost-sensitive learning via resampling techniques. For performance-based model selection, we defined a custom score including per-class sensitivities and asymmetric misprognosis costs. 260 distinct AI-ML models were evaluated via 10 repetitions of 5×5 nested cross-validation with hyperparameter tuning. Model selection was followed by the calibration of predicted probabilities. Final overall performance was compared against five well-established clinical severity scores and against a 'standard' (non-cost sensitive, non-ordinal) AI-ML baseline. In our best model, we also evaluated its explainability with respect to each of the input variables.

RESULTS

The study enrolled n = 1548 patients: 712 experienced low, 238 medium, and 598 high clinical severity. d = 131 variables were collected, becoming d ' = 148 features after categorical encoding. Model selection resulted in our best-performing AI-ML pipeline having: a) no imputation of missing data, b) no feature selection (i.e. using the full set of d ' features), c) 'Ordered Partitions' ordinal decomposition, d) cost-based reimbalance, and e) a Histogram-based Gradient Boosting classifier. This best model (calibrated) obtained a median accuracy of 68.1% [67.3%, 68.8%] (95% confidence interval), a balanced accuracy of 57.0% [55.6%, 57.9%], and an overall area under the curve (AUC) 0.802 [0.795, 0.808]. In our dataset, it outperformed all five clinical severity scores and the 'standard' AI-ML baseline.

DISCUSSION & CONCLUSION

We conducted an exhaustive exploration of AI-ML methods designed for both ordinal and cost-sensitive classification, motivated by a real-world application domain (clinical severity prognosis) in which these topics arise naturally. Our model with the best classification performance exploited successfully the ordering information of ground truth classes, coping with imbalance and asymmetric costs. However, these ordinal and cost-sensitive aspects are seldom explored in the literature.

Clinical and technical factors in endoscopic skull base surgery associated with reconstructive success

BACKGROUND

In this study, we identified key discrete clinical and technical factors that may correlate with primary reconstructive success in endoscopic skull base surgery (ESBS).

METHODS

ESBS cases with intraoperative cerebrospinal fluid (CSF) leaks at four tertiary academic rhinology programs were retrospectively reviewed. Logistic regression identified factors associated with surgical outcomes by defect subsite (anterior cranial fossa [ACF], suprasellar [SS], purely sellar, posterior cranial fossa [PCF]).

RESULTS

Of 706 patients (50.4% female), 61.9% had pituitary adenomas, 73.4% had sellar or SS defects, and 20.5% had high-flow intraoperative CSF leaks. The postoperative CSF leak rate was 7.8%. Larger defect size predicted ACF postoperative leaks; use of rigid reconstruction and older age protected against sellar postoperative leaks; and use of dural sealants compared to fibrin glue protected against PCF postoperative leaks. SS postoperative leaks occurred less frequently with the use of dural onlay. Body-mass index, intraoperative CSF leak flow rate, and the use of lumbar drain were not significantly associated with postoperative CSF leak. Meningitis was associated with larger tumors in ACF defects, nondissolvable nasal packing in SS defects, and high-flow intraoperative leaks in PCF defects. Sinus infections were more common in sellar defects with synthetic grafts and nondissolvable nasal packing.

CONCLUSIONS

Depending on defect subsite, reconstructive success following ESBS may be influenced by factors, such as age, defect size, and the use of rigid reconstruction, dural onlay, and tissue sealants.

Classification of longitudinal profiles using semi-parametric nonlinear mixed models with P-Splines and the SAEM algorithm

In this work, we propose an extension of a semiparametric nonlinear mixed-effects model for longitudinal data that incorporates more flexibility with penalized splines (P-splines) as smooth terms. The novelty of the proposed approach consists of the formulation of the model within the stochastic approximation version of the EM algorithm for maximum likelihood, the so-called SAEM algorithm. The proposed approach takes advantage of the formulation of a P-spline as a mixed-effects model and the use of the computational advantages of the existing software for the SAEM algorithm for the estimation of the random effects and the variance components. Additionally, we developed a supervised classification method for these non-linear mixed models using an adaptive importance sampling scheme. To illustrate our proposal, we consider two studies on pregnant women where two biomarkers are used as indicators of changes during pregnancy. In both studies, information about the women's pregnancy outcomes is known. Our proposal provides a unified framework for the classification of longitudinal profiles that may have important implications for the early detection and monitoring of pregnancy-related changes and contribute to improved maternal and fetal health outcomes. We show that the proposed models improve the analysis of this type of data compared to previous studies. These improvements are reflected both in the fit of the models and in the classification of the groups.

Multidimensional adaptive P-splines with application to neurons' activity studies

The receptive field (RF) of a visual neuron is the region of the space that elicits neuronal responses. It can be mapped using different techniques that allow inferring its spatial and temporal properties. Raw RF maps (RFmaps) are usually noisy, making it difficult to obtain and study important features of the RF. A possible solution is to smooth them using P-splines. Yet, raw RFmaps are characterized by sharp transitions in both space and time. Their analysis thus asks for spatiotemporal adaptive P-spline models, where smoothness can be locally adapted to the data. However, the literature lacks proposals for adaptive P-splines in more than two dimensions. Furthermore, the extra flexibility afforded by adaptive P-spline models is obtained at the cost of a high computational burden, especially in a multidimensional setting. To fill these gaps, this work presents a novel anisotropic locally adaptive P-spline model in two (e.g., space) and three (space and time) dimensions. Estimation is based on the recently proposed SOP (Separation of Overlapping Precision matrices) method, which provides the speed we look for. Besides the spatiotemporal analysis of the neuronal activity data that motivated this work, the practical performance of the proposal is evaluated through simulations, and comparisons with alternative methods are reported.

Automated location of orofacial landmarks to characterize airway morphology in anaesthesia via deep convolutional neural networks

BACKGROUND

A reliable anticipation of a difficult airway may notably enhance safety during anaesthesia. In current practice, clinicians use bedside screenings by manual measurements of patients' morphology.

OBJECTIVE

To develop and evaluate algorithms for the automated extraction of orofacial landmarks, which characterize airway morphology.

METHODS

We defined 27 frontal + 13 lateral landmarks. We collected n=317 pairs of pre-surgery photos from patients undergoing general anaesthesia (140 females, 177 males). As ground truth reference for supervised learning, landmarks were independently annotated by two anaesthesiologists. We trained two ad-hoc deep convolutional neural network architectures based on InceptionResNetV2 (IRNet) and MobileNetV2 (MNet), to predict simultaneously: (a) whether each landmark is visible or not (occluded, out of frame), (b) its 2D-coordinates (x,y). We implemented successive stages of transfer learning, combined with data augmentation. We added custom top layers on top of these networks, whose weights were fully tuned for our application. Performance in landmark extraction was evaluated by 10-fold cross-validation (CV) and compared against 5 state-of-the-art deformable models.

RESULTS

With annotators' consensus as the 'gold standard', our IRNet-based network performed comparably to humans in the frontal view: median CV loss L=1.277·10^-3, inter-quartile range (IQR) [1.001, 1.660]; versus median 1.360, IQR [1.172, 1.651], and median 1.352, IQR [1.172, 1.619], for each annotator against consensus, respectively. MNet yielded slightly worse results: median 1.471, IQR [1.139, 1.982]. In the lateral view, both networks attained performances statistically poorer than humans: median CV loss L=2.141·10^-3, IQR [1.676, 2.915], and median 2.611, IQR [1.898, 3.535], respectively; versus median 1.507, IQR [1.188, 1.988], and median 1.442, IQR [1.147, 2.010] for both annotators. However, standardized effect sizes in CV loss were small: 0.0322 and 0.0235 (non-significant) for IRNet, 0.1431 and 0.1518 (p<0.05) for MNet; therefore quantitatively similar to humans. The best performing state-of-the-art model (a deformable regularized Supervised Descent Method, SDM) behaved comparably to our DCNNs in the frontal scenario, but notoriously worse in the lateral view.

CONCLUSIONS

We successfully trained two DCNN models for the recognition of 27 + 13 orofacial landmarks pertaining to the airway. Using transfer learning and data augmentation, they were able to generalize without overfitting, reaching expert-like performances in CV. Our IRNet-based methodology achieved a satisfactory identification and location of landmarks: particularly in the frontal view, at the level of anaesthesiologists. In the lateral view, its performance decayed, although with a non-significant effect size. Independent authors had also reported lower lateral performances; as certain landmarks may not be clear salient points, even for a trained human eye.

The burden of injuries according to maturity status and timing: A two-decade study with 110 growth curves in an elite football academy

Injuries have a negative impact on the development of football players. Maturation is a potential risk factor for football injuries but available data on this topic provide limited evidence due to methodological shortcomings. The aim of this study was to describe the injury burden of male academy football players according to growth curve-derived maturity status and timing. Injury and growth data were collected from 2000 to 2020. Longitudinal height records for 110 individual players were fitted with the Super-Imposition by Translation and Rotation model to estimate age at peak height velocity (PHV). Players were clustered according to maturity status (pre-, circa-, post-PHV, or adults) and timing (early, on-time, late maturers). Overall and specific injury burdens (days lost/player-season) and rate ratios for comparisons between groups were calculated. Overall injury burden increased with advanced maturity status; pre-PHV players had 3.2-, 3.7-, and 5.5-times lower burden compared with circa-PHV, post-PHV, and adult players, respectively. Growth-related injuries were more burdensome circa-PHV, while muscle and joint/ligament injuries had a higher impact post-PHV and in adults. Further, in the pre-PHV period, late maturers showed lower burden of overall, growth-related, anterior inferior iliac spine osteochondrosis, and knee joint/ligament injuries compared with on-time maturers. In adult players, however, injuries were less burdensome for early maturers than on-time and late maturers. In addition, joint/ligament injuries of adult late maturers were 4.5-times more burdensome than those of early maturers. Therefore, monitoring maturity seems crucial to define each player's maturation profile and facilitate design of targeted injury prevention programmes.Highlights Injury burden is significantly lower in football players at pre-peak height velocity (PHV). Growth-related injuries are most burdensome circa-PHV, while muscle and joint/ligament injuries are more burdensome post-PHV and especially in adults.Before PHV, growth-related and knee joint/ligament injuries have lower burden in players who mature late than those who mature on-time. Adult late maturers have greater burden of overall and joint/ligament injuries than early maturers.Football academies should regularly assess the maturity status and timing of young football players, as the impact of injuries varies with maturation status and timing.Management of the maturity-related injury risk profile, in combination with other relevant factors (training load, neuromuscular and biomechanical factors, physiotherapy, coaching, communication, psychosocial factors …), might help improve the success of player development programmes and protect the health of young football players.

Peak Height Velocity Affects Injury Burden in Circa-PHV Soccer Players

Growth and maturation are potential risk factors for soccer injuries. This research sought to describe how peak height velocity (PHV) affects overall and specific injury burden in circa- and post-PHV elite academy soccer players. Injuries and growth data collected from 2000 to 2020 were studied retrospectively. Longitudinal height records for 124 players were fitted with the Super-Imposition by Translation and Rotation model to calculate PHV (cm/year) and age at PHV. Players were classified according to PHV percentile (fast:≥75th; average: 25-75th; slow:≤25th) and maturity status (circa- or post-PHV). Overall and specific injury burden (days lost/player-season) and rate ratios for comparisons between groups were calculated based on zero-inflated negative binomial models. Confidence intervals were calculated at the 95% confidence level (CI) and the significance level was set at<0.05. In circa-PHV, players with fast PHV had 2.6 (CI: 1.4-4.8)- and 3.3 (CI:1.3-6.7)-times higher overall burden and 2.9 (CI:1.1-7.1)- and 4.1 (CI: 1.4-15.2)-times higher for growth-related injury burden compared to players with average and slow PHV, respectively. Regular monitoring of growth seems important to detect players at higher risk for being disrupted by growth-related injuries.

Extracting relevant predictive variables for COVID-19 severity prognosis: An exhaustive comparison of feature selection techniques

With the COVID-19 pandemic having caused unprecedented numbers of infections and deaths, large research efforts have been undertaken to increase our understanding of the disease and the factors which determine diverse clinical evolutions. Here we focused on a fully data-driven exploration regarding which factors (clinical or otherwise) were most informative for SARS-CoV-2 pneumonia severity prediction via machine learning (ML). In particular, feature selection techniques (FS), designed to reduce the dimensionality of data, allowed us to characterize which of our variables were the most useful for ML prognosis. We conducted a multi-centre clinical study, enrolling n = 1548 patients hospitalized due to SARS-CoV-2 pneumonia: where 792, 238, and 598 patients experienced low, medium and high-severity evolutions, respectively. Up to 106 patient-specific clinical variables were collected at admission, although 14 of them had to be discarded for containing ⩾60% missing values. Alongside 7 socioeconomic attributes and 32 exposures to air pollution (chronic and acute), these became d = 148 features after variable encoding. We addressed this ordinal classification problem both as a ML classification and regression task. Two imputation techniques for missing data were explored, along with a total of 166 unique FS algorithm configurations: 46 filters, 100 wrappers and 20 embeddeds. Of these, 21 setups achieved satisfactory bootstrap stability (⩾0.70) with reasonable computation times: 16 filters, 2 wrappers, and 3 embeddeds. The subsets of features selected by each technique showed modest Jaccard similarities across them. However, they consistently pointed out the importance of certain explanatory variables. Namely: patient's C-reactive protein (CRP), pneumonia severity index (PSI), respiratory rate (RR) and oxygen levels -saturation Sp O2, quotients Sp O2/RR and arterial Sat O2/Fi O2-, the neutrophil-to-lymphocyte ratio (NLR) -to certain extent, also neutrophil and lymphocyte counts separately-, lactate dehydrogenase (LDH), and procalcitonin (PCT) levels in blood. A remarkable agreement has been found a posteriori between our strategy and independent clinical research works investigating risk factors for COVID-19 severity. Hence, these findings stress the suitability of this type of fully data-driven approaches for knowledge extraction, as a complementary to clinical perspectives.

Modeling latent spatio-temporal disease incidence using penalized composite link models

Epidemiological data are frequently recorded at coarse spatio-temporal resolutions to protect confidential information or to summarize it in a compact manner. However, the detailed patterns followed by the source data, which may be of interest to researchers and public health officials, are overlooked. We propose to use the penalized composite link model (Eilers PCH (2007)), combined with spatio-temporal P-splines methodology (Lee D.-J., Durban M (2011)) to estimate the underlying trend within data that have been aggregated not only in space, but also in time. Model estimation is carried out within a generalized linear mixed model framework, and sophisticated algorithms are used to speed up computations that otherwise would be unfeasible. The model is then used to analyze data obtained during the largest outbreak of Q-fever in the Netherlands.

Elevating the charge separation of MgFe2O4 nanostructures by Zn ions for enhanced photocatalytic and photoelectrochemical water splitting

Magnesium ferrites (MgFe₂O₄) are important class of ferrites that have been receiving greater attention as promising excellent photocatalyst due to its low cost, wide light spectrum response and environment-friendly nature. However, its poor electronic conductivity and fast charge carrier recombination hinders its electrocatalytical applications. Hence, accelerating charge carriers separation efficiency is important to modify the photoelectrochemical performance of MgFe₂O₄. Herein, novel Zn ions doped MgFe₂O₄ nanospheres are fabricated for the first time. Zn ions are doped into MgFe₂O₄ nanostructures from surface to enhance their charge separation efficiency. The doped MgFe₂O₄ nanostructures show significant photocatalytic activity and enhanced photocurrent density than that of pristine MgFe₂O₄.The improved photoelectrocatalytic performance is attributed to doping effect, were Zn ions actually enhance the conductivity. Zn ions enhance the activity of MgFe₂O₄ and accelerate the charge transfer properties in MgFe₂O₄. The results highlight that Zn doped MgFe₂O₄ nanospheres could be a potential candidate for photocatalytic and photoelectrochemical applications.

Self-Management in Persons with Limb Loss: A Systematic Review

BACKGROUND

Self-management is an integral component of managing long-term conditions and diseases. For a person with limb loss, this self-management process involves caring for the residual limb, the prosthesis, and the prosthetic socket-residual limb interface. Failure to properly self-manage can result in unwanted secondary complications such as skin breakdown, falls, or non-use of the prosthesis. However, there is little evidence on what self-management interventions are effective at preventing secondary complications. To understand the impact of self-management after the loss of a limb, it is necessary to determine what the current evidence base supports.

OBJECTIVES

The purpose of this study is to examine the available literature on self-management interventions and/or outcomes for persons with limb loss and describe how it may impact residual limb health or prosthesis use.

METHODOLOGY

A systematic review of multiple databases was carried out using a variety of search terms associated with self-management. The results were reviewed and selected based on the inclusion criteria: self-management interventions or direct outcomes related to self-management, which includes the skin integrity of the residual limb, problem-solving the fit of the prosthesis, and education in the prevention of secondary complications associated with prosthesis use. The Cincinnati Childrens' LEGEND (Let Evidence Guide Every New Decision) appraisal forms were used to analyze the articles and assign grades.

FINDINGS

Out of the 40 articles identified for possible inclusion in this study, 33 were excluded resulting in seven articles being selected for this review. Three out of the seven articles focused on silicone liner management while the other four articles focused on skin issues.

CONCLUSIONS

Self-management for a person with limb loss is a key component of preventing complications associated with loss of limb and prosthesis use. There is a lack of high-quality experimental studies exploring the most appropriate intervention for teaching self-management when compared to other conditions, specifically diabetes. Further research in the area of self-management is necessary to understand how to best prevent unwanted secondary complications.

Neodymium (Nd) based oxide perovskite nanostructures for photocatalytic and photoelectrochemical water splitting functions

Neodymium (Nd) based perovskite (Nd_1-xCo_xFeO₃) nanostructures were processed to address the rising energy and environment crisis through offering solutions by photocatalytic and photoelectrochemical (PEC) water splitting reactions. The impact of cobalt (Co) ions on the physicochemical properties of Nd-perovskites were studied using X-ray diffraction (XRD), Raman and electron microscopic instruments. The interaction of metal ions was studied in depth via X-ray photoelectron spectroscopy (XPS). Absorption and photoluminescence signals inferred the optical band gap to be lowered and defect states to increase upon Co substitution. Improved photocatalytic efficacy in Nd_1-xCo_xFeO₃ was evaluated by comparative studies using NdFeO₃. Secondly, the enhanced conductivities in Nd_1-xCo_xFeO₃ studied via Nyquist plot was found to be advantageous in photoelectrode fabrication for PEC functions. Time-dependent photocurrent density results affirmed the stability in processed devices. Co ions were also inferred to boost the separation of charge carriers effectively. The improved performance in Nd_1-xCo_xFeO₃ nanostructures were well justified to the successful incorporation of Co ions that sway the Nd-O, Co-O and Co-Fe-O bondings and boost the photon absorption and electronic conductivity to facilitate the observed performance.

Clinical and molecular insights into BCG immunotherapy for melanoma

The incidence of cutaneous melanoma and the mortality rate of advanced melanoma patients continue to rise globally. Despite the recent success of immunotherapy including ipilimumab and pembrolizumab checkpoint inhibitors, a large proportion of patients are refractory to such treatment modalities. The application of mycobacteria such as Bacillus Calmette-Guérin (BCG) in the treatment of various malignancies, including cutaneous melanoma, has been clearly demonstrated after almost a century of observations and experimentation. Intralesional BCG (IL-BCG) immunotherapy is a highly efficient and cost-effective treatment option for inoperable stage III in-transit melanoma, as recommended in the National Comprehensive Cancer Network Guidelines. IL-BCG has shown great efficacy in the regression of directly injected metastatic melanoma lesions, as well as distal noninjected nodules in immunocompetent patients. Clinical and preclinical studies have shown that BCG serves as a strong immune modulator, inducing the recruitment of various immune cells that contribute to antitumour immunity. However, the specific mechanism of BCG-mediated tumour immunity remains poorly understood. Comparative genome analyses have revealed that different BCG strains exhibit distinct immunological activity and virulence, which might impact the therapeutic response and clinical outcome of patients. In this review, we discuss the immunostimulatory potential of different BCG substrains and highlight clinical studies utilizing BCG immunotherapy for the treatment of cutaneous melanoma. Furthermore, the review focuses on the cellular and molecular mechanisms of the BCG-induced immune responses of both the innate and adaptive arms of the immune system. Furthermore, the review discussed the administration of BCG as a monotherapy or in combination with other immunotherapeutic or chemotherapeutic agents.

High PD-1/PD-L1 Checkpoint Interaction Infers Tumor Selection and Therapeutic Sensitivity to Anti-PD-1/PD-L1 Treatment

Many cancers are termed immunoevasive due to expression of immunomodulatory ligands. Programmed death ligand-1 (PD-L1) and cluster of differentiation 80/86 (CD80/86) interact with their receptors, programmed death receptor-1 (PD-1) and cytotoxic T-lymphocyte antigen-4 (CTLA-4), respectively, on tumor-infiltrating leukocytes eliciting immunosuppression. Immunotherapies aimed at blocking these interactions are revolutionizing cancer treatments, albeit in an inadequately described patient subset. To address the issue of patient stratification for immune checkpoint intervention, we quantitatively imaged PD-1/PD-L1 interactions in tumor samples from patients, employing an assay that readily detects these intercellular protein-protein interactions in the less than or equal to 10 nm range. These analyses across multiple patient cohorts demonstrated the intercancer, interpatient, and intratumoral heterogeneity of interacting immune checkpoints. The PD-1/PD-L1 interaction was not correlated with clinical PD-L1 expression scores in malignant melanoma. Crucially, among anti-PD-1-treated patients with metastatic non-small cell lung cancer, those with lower PD-1/PD-L1 interaction had significantly worsened survival. It is surmised that within tumors selecting for an elevated level of PD-1/PD-L1 interaction, there is a greater dependence on this pathway for immune evasion and hence, they exhibit more impressive patient response to intervention. SIGNIFICANCE: Quantitation of immune checkpoint interaction by direct imaging demonstrates that immunotherapy-treated patients with metastatic NSCLC with a low extent of PD-1/PD-L1 interaction show significantly worse outcome.

A general framework for prediction in penalized regression

There are two main approaches to carrying out prediction in the context of penalized regression: with low-rank basis and penalties or through the smooth mixed models. In this article, we give further insight in the case of P-splines showing the influence of the penalty on the prediction. In the context of mixed models, we can connect the new predicted values to the observed values through a joint normal distribution, which allows us to compute prediction intervals. In this work, we propose an alternative approach, called the extended mixed model approach, that allows us to fit and predict data simultaneously. The methodology is illustrated with two real datasets, one of them on aboveground biomass and the other on monthly sulphur dioxide ([Formula: see text]) levels in a selection of monitoring sites in Europe.

Integration of imaging and molecular approaches in selective fetal reduction in twin pregnancies with one carrying a pathogenic genomic aberration

BACKGROUND/PURPOSE

With the evolution of assisted fertility and prenatal diagnostic technology, the prevalence of multi-fetal pregnancy increased, followed by the demand for prenatal intervention if genomic aberration was detected. How to distinguish the affected foetus from the normal co-twin before selective fetal reduction is therefore challenging.

OBJECTIVES

We retrospectively reviewed the cases of dichorionic twins at our centre during 2004-2018, where selective fetal reduction was requested because one foetus carried a pathogenic genomic aberration. Five cases were enrolled, including three foetuses with trisomy 21, one foetus with microduplication and one foetus with microdeletion disorders.

METHOD

We labelled the affected foetus by prenatal ultrasound and rapid molecular tools. For the twins without discriminating sonographic features (e.g., the same gender and no distinct placentae), interphase fluorescence in situ hybridization, rapid microarray and short tandem repeat markers were applied to identify the affected foetus.

RESULTS

Selective fetal reduction was allocated accurately for all individuals. Two cases delivered at term, while two delivered preterm, and one developed fetal loss of the co-twin.

CONCLUSION

We proposed a working scheme of integrating imaging and molecular techniques to correctly identify the affected co-twin before selective fetal reduction to ensure the accuracy of the identification.

A synthetic approach to 'click' neoglycoprotein analogues of EPO employing one-pot native chemical ligation and CuAAC chemistry

The clinical significance of batch-wise variability on the pharmacokinetics and potency of commercial erythropoietin (EPO), prepared recombinantly as a heterogeneous mixture of glycoforms, necessitates the development of synthetic strategies to afford homogenous EPO formulations. Herein we present a previously unexplored and divergent route towards 'click' neoglycoprotein analogues of EPO, employing one-pot native chemical ligation (NCL) of alkynylated peptides and copper-catalysed azide-alkyne cycloaddition (CuAAC) with azido monosaccharides. By design, our synthetic platform permits glycosylation at virtually any stage, providing flexibility for the synthesis of various glycoforms for biological analysis. Insights obtained from attempted folding of our 'click' neoglycoprotein EPO analogue, bearing four different neutral sugar moieties, highlight the important role played by the charged oligosaccharides present in native EPO glycoproteins.

A large-aperture strip-grid beam splitter for partially combined two millimeter-wave diagnostics on Korea Superconducting Tokamak Advanced Research

A large-aperture beam splitter has been developed for simultaneous operation of two millimeter-wave diagnostics employing different probe beams in the frequency and polarization, microwave imaging reflectometer (∼85 GHz X-mode), and collective scattering system (300 GHz O-mode), on the Korea Superconducting Tokamak Advanced Research device. The beam splitter was designed based on a polarizer concept (i.e., grid of metal strips on a thin dielectric sheet), and this can be an optimal solution for these two diagnostics. Fabrication of the strips with uniform sub-millimeter width and spacing on a large dielectric sheet was achieved with an etching technique, and the laboratory test results on the reflection and transmission ratio are in good agreement with design values.

A beta-binomial mixed-effects model approach for analysing longitudinal discrete and bounded outcomes

Patient-reported outcomes (PROs) are currently being increasingly used as primary outcome measures in observational and experimental studies since they inform clinicians and researchers about the health-status of patients and generate data to facilitate improved care. PROs usually appear as discrete and bounded with U, J, or inverse J shapes, and hence, exponential family members offer inadequate distributional fits. The beta-binomial distribution has been proposed in the literature to fit PROs. However, the fact that the beta-binomial distribution does not belong to the exponential family limits its applicability in the regression model context, and classical estimation approaches are not straightforward. Moreover, PROs are usually measured in a longitudinal framework in which individuals are followed up for a certain period. Hence, each individual obtains several scores of the PRO over time, which leads to the repeated measures and defines the correlation structure in the data. In this work, we have developed and proposed an estimation procedure for the analysis of correlated discrete and bounded outcomes, particularly PROs, by a beta-binomial mixed-effects model. Additionally, we have implemented the methodology in the PROreg package in R. Because there are similar approaches in the literature to address the same issue, this work also incorporates a comparison study between our proposal and alternative methodologies commonly implemented in R and shows the superior performance of our estimation procedure. This paper was motivated by the analysis of the health-status of patients with chronic obstructive pulmonary disease, where the main objective is the assessment of risk factors that may affect the evolution of the disease. The application of the proposed approach in the study leads to clinically relevant results.

Computer vision–based automatic rod-insulator defect detection in high-speed railway catenary system

Maintenance of catenary system is a crucial task for the safe operation of high-speed railway systems. Catenary system malfunction could interrupt railway service and threaten public safety. This article presents a computer vision algorithm that is developed to automatically detect the defective rod-insulators in a catenary system to ensure reliable power transmission. Two key challenges in building such a robust inspection system are addressed in this work, the detection of the insulators in the catenary image and the detection of possible defects. A two-step insulator detection method is implemented to detect insulators with different inclination angles in the image. The sub-images containing cantilevers and rods are first extracted from the catenary image. Then, the insulators are detected in the sub-image using deformable part models. A local intensity period estimation algorithm is designed specifically for insulator defect detection. Experimental results show that the proposed method is able to automatically and reliably detect insulator defects including the breakage of the ceramic discs and the foreign objects clamped between two ceramic discs. The performance of this visual inspection method meets the strict requirements for catenary system maintenance.

Base of tongue cancer-is it tongue cancer located at the base of the tongue, or is it a type of lingual tonsil cancer? The perspective from a genomic analysis

The aim of this study was to determine whether base of tongue (BOT) cancer is tongue cancer located at the base of the tongue or lingual tonsil cancer originating from tonsil tissue. This was a retrospective study using data from The Cancer Genome Atlas (TCGA). The genomic patterns of three primary cancers (BOT, oral tongue, and tonsil) were compared to determine their similarities and differences. Gene expression data (n=193; 26 BOT, 125 oral tongue, and 42 tonsil cases), copy number alteration data (n=142; 19 BOT, 96 oral tongue, and 27 tonsil cases), and somatic mutation data (n=187; 25 BOT, 122 oral tongue, and 40 tonsil cases) were analyzed using the t-test, heatmap analysis, and OncoPrint, respectively. Clinical information for the three tumour groups was included in the analyses. When using multiplatform analysis, BOT cancer showed nearly the same genomic pattern as tonsil cancer, but not oral tongue cancer. The χ² test and survival analysis revealed that BOT cancer had the same clinical and survival patterns as tonsil cancer. In conclusion, BOT cancer showed a genomic pattern similar to that of tonsil cancer, but different to that of oral tongue cancer. Further prospective studies are warranted before the results of this study can be applied in a clinical setting.

Ultrasonic-assisted synthesis of ZnTe nanostructures and their structural, electrochemical and photoelectrical properties

Colloidal zinc telluride (ZnTe) nanostructures were successfully processed through a simple and facile ultrasonic (sonochemical) treatment for photoelectronic applications. The particle-like morphological features, phase and nature of valence state of various metal ions existing in ZnTe were examined using electron and X-ray photoelectron spectroscopic tools. Raman spectroscopic measurements revealed the dominance of exciton-phonon coupling and occurrence of TeO₂ traces in ZnTe through the corresponding vibrations. Optical bandgap of the ZnTe suspension was estimated to be around 2.15eV, authenticating the direct allowed transitions. The p-type electrical conductivity and charge carrier density of ZnTe were additionally estimated from the Bode, Nyquist and Mott-Schottky type impedance plots. The photoelectrical properties of ZnTe were investigated by fabricating p-ZnTe/n-Si heterostructures and studying their corresponding current-voltage characteristics under dark and white light illumination. The diodes revealed excellent rectifying behaviour with significant increase in reverse current under illumination. The stability of the devices were also affirmed through the time-dependent photoresponse characteristics, which actually suggested the improved and effective separation of photo generated electron hole pairs across the integrated heterojunctions. The obtained results also augment the potential of sonochemically processed ZnTe for application in photo detection and sensor related functions.

Time resolved amplified FRET identifies protein kinase B activation state as a marker for poor prognosis in clear cell renal cell carcinoma

Purpose

Clear cell Renal Cell Carcinomas (ccRCC), the largest group of renal tumours, are resistant to classical therapies. The determination of the functional state of actionable biomarkers for the assessment of these adenocarcinomas is essential. The dysregulation of the oncoprotein, PKB/Akt has been linked with poor prognoses in human cancers.

Material & methods

We analysed the status of the PKB/Akt pathway in a representative tumour tissue microarray obtained from the primary tumours and their metastases in 60 ccRCC with long term follow up. We sought to define the evolution of this pathway from the primary tumour to the metastatic event and to know the impact of its functional state in tumour aggressiveness and patient survival. Two-site time resolved amplified FRET (A-FRET) was utilised for assessing the activation state of PKB/Akt and this was compared to conventional immunohistochemistry measurements.

Results

Activation state of PKB/Akt in primary tumours defined by A-FRET correlated with poorer overall survival (hazard ratio 0.228; p = 0.002). Whereas, increased protein expression of phosphoPKB/Akt, identified using classical immunohistochemistry, yielded no significant difference (hazard ratio 1.390; p = 0.548).

Conclusions

Quantitative determination of PKB/Akt activation in ccRCC primary tumours alongside other diagnostics tools could prove key in taking oncologists closer to an efficient personalised therapy in ccRCC patients.

General significance

The quantitative imaging technology based on Amplified-FRET can rapidly analyse protein activation states and molecular interactions. It could be used for prognosis and assess drug function during the early cycles of chemotherapy. It enables evaluation of clinical efficiency of personalised cancer treatment.

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Time Resolved Amplified FRET (A-FRET), has been used to quantitatively assess PKB/Akt activation states in ccRCC.

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Increased activation state of PKB/Akt in primary tumours was shown to correlate with poorer prognoses.

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Companion diagnostic tools such as A-FRET will prove valuable for assessing prognostic models and for predicting the response to systemic therapy.

Microfluidic self-assembly of folate-targeted monomolecular siRNA-lipid nanoparticles

Non-viral delivery of nucleic acids for therapies based on RNA interference requires a rational design and optimal self-assembly strategies. Nucleic acid particles need to be small, stable and functional in terms of selective cell uptake and controlled release of encapsulated nucleic acids. Here we report on small (∼38 nm) monomolecular nucleic acid/lipid particles (mNALPs) that contain single molecules of short double-stranded oligonucleotides covered by a tight, highly curved lipid bilayer. The particles consist of DOPE, DOTAP, DOPC and DSPE-PEG(2000) and are assembled with 21 bp double-stranded DNA or small interfering RNA by solvent exchange on a hydrodynamic-focusing microfluidic chip. In comparison to vortex mixing by hand this method increases the encapsulation efficiency by 20%, and yields particles with a narrower size distribution, negligible aggregate formation and high stability in blood plasma and serum. Modification of mNALPs with folate-conjugated PEG-lipids results in specific binding and uptake by epithelial carcinoma KB cells overexpressing folate receptors. Binding is significantly reduced by competitive inhibition using free folate and is not observed with non-targeted mNALPs, revealing high specificity. The functionalized mNALPs show gene silencing in the presence of chloroquine, an endosome-destabilizing agent. Together, the robust self-assembly of small-sized mNALPs with their high stability and receptor-specific cell uptake demonstrate that the tight, PEG-grafted lipid-bilayer encapsulation may offer a promising approach towards the delivery of short double-stranded oligonucleotides.

Comparative genomics of Eucalyptus and Corymbia reveals low rates of genome structural rearrangement

BACKGROUND

Previous studies suggest genome structure is largely conserved between Eucalyptus species. However, it is unknown if this conservation extends to more divergent eucalypt taxa. We performed comparative genomics between the eucalypt genera Eucalyptus and Corymbia. Our results will facilitate transfer of genomic information between these important taxa and provide further insights into the rate of structural change in tree genomes.

RESULTS

We constructed three high density linkage maps for two Corymbia species (Corymbia citriodora subsp. variegata and Corymbia torelliana) which were used to compare genome structure between both species and Eucalyptus grandis. Genome structure was highly conserved between the Corymbia species. However, the comparison of Corymbia and E. grandis suggests large (from 1-13 MB) intra-chromosomal rearrangements have occurred on seven of the 11 chromosomes. Most rearrangements were supported through comparisons of the three independent Corymbia maps to the E. grandis genome sequence, and to other independently constructed Eucalyptus linkage maps.

CONCLUSIONS

These are the first large scale chromosomal rearrangements discovered between eucalypts. Nonetheless, in the general context of plants, the genomic structure of the two genera was remarkably conserved; adding to a growing body of evidence that conservation of genome structure is common amongst woody angiosperms.

Electronic calculation of quality measures in the EMR and dependence on data capture in structured fields: The OCM quality reporting experience

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Background: Reporting of quality measures is ideally achieved electronically. This is dependent on presence of data elements in structured fields. We report on the variability of quality measure reporting in the OCM for quality measures OCM 8 (adjuvant chemotherapy in stage 3 colon cancer), 9 (adjuvant chemotherapy in HR- breast cancer), 10 (adjuvant trastuzumab for Her2+ breast cancer), and 11 (adjuvant hormonal therapy for HR+ breast cancer). Methods: Quality measures were calculated for 30,524 patients across 35 practices participating in the OCM. We examined the calculation of quality metrics OCM-8, 9, 10, and 11 based on presence or absence of data elements in the medical record. Results: For quality measures OCM-8 and 9 that require documentation of date of surgery, only 1.3% and 1.6%, respectively, of patients could be included in the calculation due to absence of surgical date in a structured field. For quality measures OCM 9 and 11 that require attestation of surgical staging of breast cancer, this data element was documented in 0% of patients. For OCM 9 and 10 that require stage documentation of breast cancer, this data element was documented in 63% and 75%, respectively, of patients (range 12-100%). In cases where staging criteria were not met, 58% and 44%, respectively, of patients were removed due to total absence of staging data in structured fields. Conclusions: Quality measure calculation and reporting is highly dependent on documentation of data elements in structured fields. Lack of documentation of key elements distorts calculation of the measure. Modification of physician workflow or restructuring of measure calculation to optimize use of well documented structured elements will improve generalizability of quality measure reporting. Manual abstraction of data does not represent a feasible alternative.

Implementation of the IOM 13 point care plan by Oncology Care Model (OCM) practices

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Background: The completion of the IOM 13 point care plan is mandatory for all patients enrolled in the OCM. We built an integrated care plan into the electronic medical record, with 9 points being auto-populated by data documented elsewhere in the EMR and 4 points requiring completion by the caregiver. We report on preliminary experience with care plan completion. Methods: Of the 190 practices selected by CMMI for the OCM, 32 practices utilized the embedded care plan. Patient eligibility for the OCM was determined by identification of a qualifying episode by an electronic algorithm. Initiation of a care plan was determined by physician completion of any field in the care plan field. Completion of the care plan was defined by the act of printing and distributing the care plan to the patient. Correlations between number of eligible patients and completion rates were calculated using Pearson’s product moment correlation coefficient (r). P-values were calculated using a t-distribution and null hypothesis of 0. Results: Over the first 6 months, 15,705 patients were identified as eligible for the OCM. At these practices, 69% (10,851) of patients had care plans initiated (range 0-100%) and 34% (5,290) had a care plan printed (range 0-100%). Within the care plans initiated, 53% (5,711) had the advance directive field completed (range 0-87%). There was no correlation between percent of care plans initiated or percent of care plans printed and number of eligible patients in the practice (r = -0.16, p = 0.51 and r = -0.13, p = 0.44); likewise, advance directive field completion percent was not correlated with the number of eligible patients (r = -0.16, p = 0.37). Conclusions: Completion of the IOM care plan has proven challenging for practices in the OCM irrespective of practice size. This suggests technological solutions represent only one component needed for success in this component of the OCM.

Comparison of beta-binomial regression model approaches to analyze health-related quality of life data

Health-related quality of life has become an increasingly important indicator of health status in clinical trials and epidemiological research. Moreover, the study of the relationship of health-related quality of life with patients and disease characteristics has become one of the primary aims of many health-related quality of life studies. Health-related quality of life scores are usually assumed to be distributed as binomial random variables and often highly skewed. The use of the beta-binomial distribution in the regression context has been proposed to model such data; however, the beta-binomial regression has been performed by means of two different approaches in the literature: (i) beta-binomial distribution with a logistic link; and (ii) hierarchical generalized linear models. None of the existing literature in the analysis of health-related quality of life survey data has performed a comparison of both approaches in terms of adequacy and regression parameter interpretation context. This paper is motivated by the analysis of a real data application of health-related quality of life outcomes in patients with Chronic Obstructive Pulmonary Disease, where the use of both approaches yields to contradictory results in terms of covariate effects significance and consequently the interpretation of the most relevant factors in health-related quality of life. We present an explanation of the results in both methodologies through a simulation study and address the need to apply the proper approach in the analysis of health-related quality of life survey data for practitioners, providing an R package.

New compact and efficient local oscillator optic system for the KSTAR electron cyclotron emission imaging system

Electron cyclotron emission imaging (ECEI) diagnostic on Korean Superconducting Tokamak Advanced Research utilizes quasi-optical heterodyne-detection method to measure 2D (vertical and radial) T_e fluctuations from two toroidally separated poloidal cross section of the plasma. A cylindrical lens local oscillator (LO) optics with optical path length (OPL) 2-2.5 m has been used in the current ECEI system to couple the LO source to the 24 vertically aligned array of ECE detectors. For efficient and compact LO optics employing the Powell lens is proposed so that the OPL of the LO source is significantly reduced from ∼2.0 m to 0.4 m with new optics. The coupling efficiency of the LO source is expected to be improved especially at the edge channels. Results from the optical simulation together with the laboratory test of the prototype optics will be discussed in this paper.

Repeatability of electro- and acoustic myographic activity during a fatigue test of normal lumbar paraspinal muscles

The repeatability of acoustic myography (AMG) and electromyography (EMG) of the paraspinal muscles of 15 healthy subjects was investigated during a fatigue test involving a sustained horizontal hold of the upper body against gravity. The AMG and EMG signals were full-wave rectified and integrated (IAMG, IEMG). The variability of recordings made during a 60-second isometric contraction performed on three different days was assessed by analysis of variance (ANOVA) and coefficients of variation (CVs) were calculated from the ANOVA. The IAMG: IEMG ratio was calculated to assess electromechanical uncoupling during fatigue and the IAMG and I EMG values were also normalized to a percentage of initial activity. At the beginning of the fatigue test, absolute values for IAMG and the IAMG:IEMG ratio were not as repeatable between days as IEMG (CVs = IAMG 18%, IEMG 11 %, IAMG: IEMG ratio 23.5%). Absolute values at the end of the test showed similar degrees of repeatability for each variable (CVs = IAMG 21 %, IEMG 10%, IAMG: IEMG ratio 24%). Normalized values at the end of the fatigue test were repeatable (CVs = AMG 6%, EMG 6%, AMG : EMG ratio 9%), but variability was observed during the contraction. The present results indicate that absolute values of EMG are more repeatable than AMG for assessing paraspinal muscle activity on different days in healthy subjects. The changes in normalized values were variable during fatiguing activity but repeatable at the end of the test. Further control of the AMG recording technique is required to refine the fatigue test before it can be applied as a clinical assessment tool.

Design of a collective scattering system for small scale turbulence study in Korea Superconducting Tokamak Advanced Research

The design characteristics of a multi-channel collective (or coherent) scattering system for small scale turbulence study in Korea Superconducting Tokamak Advanced Research (KSTAR), which is planned to be installed in 2017, are given in this paper. A few critical issues are discussed in depth such as the Faraday and Cotton-Mouton effects on the beam polarization, radial spatial resolution, probe beam frequency, polarization, and power. A proper and feasible optics with the 300 GHz probe beam, which was designed based on these issues, provides a simultaneous measurement of electron density fluctuations at four discrete poloidal wavenumbers up to 24 cm(-1). The upper limit corresponds to the normalized wavenumber kθρe of ∼0.15 in nominal KSTAR plasmas. To detect the scattered beam power and extract phase information, a quadrature detection system consisting of four-channel antenna/detector array and electronics will be employed.

Bioavailability of the Nano-Unit 14C-Agrochemicals Under Various Water Potential

The study was conducted to investigate the effects of water potential on bioavailability of the nano-unit 14C-cafenstrole, 14C-pretilachlor, 14C-benfuresate, 14C-simetryn and 14C-oxyfluorfen applied with or without dimepiperate or daimuron under various water potential conditions. The highest bioavailable concentration in soil solution (BCSS) was found at 60% soil moisture, while the lowest occurred at 50% soil moisture for soil-applied alone or in combination. All water potential conditions differed significantly from each other with variations in total bioavailable amount in soil solution (TBSS) when either dimepiperate or daimuron were added to the soil, and changes were directly proportional to variations in water potential. Across all treatments, TBSS at 80% soil moisture was three to four times greater than that at 50% soil moisture when applied alone or in combination with dimepiperate or daimuron. Cafenstrole and simetryn had distribution coefficient (Kd) values <64 ml g-1 and a TBSS ranging from 10 to 44 ng g-1 soil, regardless of water potential conditions applied alone or in combination. Pretilachlor and benfuresate had Kd values <15 ml g-1 and a TBSS range of 38 to 255 ng g-1 soil when applied with or without dimepiperate or daimuron.

Association between exposure to household cigarette smoking behavior and cigarette smoking in Hispanic adults: Findings from the Hispanic Community Health Study/Study of Latinos

BACKGROUND

Cigarette smoking behavior is highly determined by social influences during childhood and adolescence. This phenomenon has not been fully evaluated in the Hispanic/Latino population.

PURPOSE

To examine the association between exposure to household cigarette smoking behavior (HCSB) and adult cigarette smoking among a diverse Hispanic/Latino population living in four US urban centers. The effect of acculturation on cigarette smoking was also evaluated.

METHODS

Data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (n=13,231, ages 18-74years, collected between March 2008 and June 2011) were analyzed using logistic regression.

RESULTS

HCSB exposure was an independent risk factor for adult current cigarette smoking in Hispanic/Latinos (OR 1.7; 95% CI 1.4, 2.1) after controlling for relevant confounders including socio-demographic and cultural factors. Cubans and Puerto Ricans had the highest prevalence of HCSB exposure (59% and 47% respectively) and highest prevalence of current cigarette smoking (26% and 32%) compared with other Hispanic/Latino groups, (p<.01).

CONCLUSIONS

Our data suggest that exposure to HCSB in Hispanics/Latinos living in the US is an independent predictor of adult cigarette smoking, and this association appears to be strongest in Cubans and Puerto Ricans.

Screening Eucalyptus cloeziana and E. argophloia Populations for Resistance to Puccinia psidii

Disease screening to determine the threat Puccinia psidii poses to plantation and native eucalypts in Australia was undertaken in half-sib families of two contrasting eucalypt species, Eucalyptus cloeziana and E. argophloia. Artificial inoculation with a single-lesion isolate of P. psidii was used to screen these species for resistance to the biotype of P. psidii established in Australia. The objective was to characterize resistance to P. psidii within these two distinct species: E. argophloia, a vulnerable species with a narrow distribution, and E. cloeziana, a species with a broad and extensive distribution in Queensland. Results for E. cloeziana indicate that inland provenances are more resistant to P. psidii infection than provenances from coastal regions. Heritability estimates for the two assessment systems used (resistance on a 1-to-5 ordinal scale verses resistance on a 0-to-1 binomial scale) were low to high (0.24 to 0.63) for E. argophloia and moderate to high (0.4 to 0.91) for E. cloeziana, indicating a significant level of additive genetic variance for rust resistance within the populations. This study demonstrates the potential to select resistant families within the tested populations and indicates that P. psidii could detrimentally affect these species in native forests, nurseries, and plantations.