Smoothing Spline Research Articles

Antibody Response after COVID-19 Vaccination in Healthy Adults Exposed to Perfluoroalkyl Substances in Ronneby, Sweden

Background & Aims: Per- and polyfluoroalkyl substances (PFAS) are widely used, environmentally ubiquitous chemicals. Inhabitants in Ronneby, Sweden, have had long-term, moderate to high PFAS-exposure through drinking water contaminated by firefighting foams. PFAS has been associated with decreased vaccine-induced antibody responses in children. Effects in adults have been poorly investigated, in part owing to lack of well-designed trials of primary immunizations in PFAS exposed populations. The novelty of vaccination against COVID-19 and the associated clinical trials, offers a unique opportunity to investigate if PFAS decrease vaccine-induced antibody response in adults. Methods: Healthy, COVID-19 unvaccinated adults, 20-60 years old, from Ronneby (n=319; Perfluorooctanesulfonic acid (PFOS) median 46 ng/mL, range 1-543) and referents from neighboring Karlshamn (n=41; PFOS median 4 mg/mL, range 1-36), were vaccinated with two doses of the mRNA vaccine Spikevax® (Moderna). Seven PFAS were measured in serum before vaccination. Serum IgG antibodies against the spike antigen were measured before vaccination, and at five weeks (n=350) and six months (n=329) after the second vaccination. Regression analyses of antibodies were fitted against serum PFAS levels, quartile groups, smooth splines and between exposed and reference areas, adjusting for sex, age, smoking and previous SARS-CoV-2-infection. Results: Participants from Ronneby and referents had similar, high antibody levels (100% positive) five weeks and six months post vaccination, with waning levels over time. Regression models showed no clear pattern between antibody levels at five weeks or six months after vaccination and PFAS exposure. Results were replicated using different exposure indices, covariate adjustments and sensitivity analyses, and consistent for seven different PFAS compounds. Conclusions: In this clinical trial, with a wide PFAS exposure range and a low dropout rate, we assessed no indication that moderate to high PFAS exposure adversely affected antibody production in adults after COVID-19 mRNA vaccination. Keywords: PFAS, Immunotoxicity, Antibody, COVID-19 Vaccination

Robust Permutation Tests for Penalized Splines

Penalized splines are frequently used in applied research for understanding functional relationships between variables. In most applications, statistical inference for penalized splines is conducted using the random effects or Bayesian interpretation of a smoothing spline. These interpretations can be used to assess the uncertainty of the fitted values and the estimated component functions. However, statistical tests about the nature of the function are more difficult, because such tests often involve testing a null hypothesis that a variance component is equal to zero. Furthermore, valid statistical inference using the random effects or Bayesian interpretation depends on the validity of the utilized parametric assumptions. To overcome these limitations, I propose a flexible and robust permutation testing framework for inference with penalized splines. The proposed approach can be used to test omnibus hypotheses about functional relationships, as well as more flexible hypotheses about conditional relationships. I establish the conditions under which the methods will produce exact results, as well as the asymptotic behavior of the various permutation tests. Additionally, I present extensive simulation results to demonstrate the robustness and superiority of the proposed approach compared to commonly used methods.

Nonlinear statistical spline smoothers for critical spherical black hole solutions in 4-dimension

This paper focuses on self-similar gravitational collapse solutions of the Einstein–axion–dilaton configuration for two conjugacy classes of SL(2, R) transformations. These solutions are invariant under spacetime dilation, combined with internal transformations. For the first time in Einstein–axion–dilaton literature, we apply the nonlinear statistical spline regression methods to estimate the critical spherical black hole solutions in four dimensions. These spline methods include truncated power basis, natural cubic spline and penalized B-spline. The prediction errors of the statistical models, on average, are almost less than 10−2, so all the developed models can be considered unbiased estimators for the critical collapse functions over their entire domains. In addition to this excellence, we derived closed forms and continuously differentiable estimators for all the critical collapse functions.

Geometrically designed variable knot splines in generalized (non-)linear models

In this paper we extend the GeDS methodology, recently developed by Kaishev et al. [18] for the Normal univariate spline regression case, to the more general GNM/GLM context. Our approach is to view the (non-)linear predictor as a spline with free knots which are estimated, along with the regression coefficients and the degree of the spline, using a two stage algorithm. In stage A, a linear (degree one) free-knot spline is fitted to the data applying iteratively re-weighted least squares. In stage B, a Schoenberg variation diminishing spline approximation to the fit from stage A is constructed, thus simultaneously producing spline fits of second, third and higher degrees. We demonstrate, based on a thorough numerical investigation that the nice properties of the Normal GeDS methodology carry over to its GNM extension and GeDS favourably compares with other existing spline methods.The proposed GeDS GNM/GLM methodology is extended to the multivariate case of more than one independent variable by utilizing tensor product splines and their related shape preserving variation diminishing property.

Elevated gamma-glutamyl transferase to high-density lipoprotein cholesterol ratio has a non-linear association with incident diabetes mellitus: A second analysis of a cohort study.

Evidence regarding the association between the GGT/HDL-c ratio and incident diabetes is still limited. On that account, our research aims to survey the link of the GGT/HDL-c ratio with the risk of diabetes. In this retrospective cohort study, data of 15,171 participants who participated in the medical examination program were collected in Murakami Memorial Hospital in Japan from 2004 to 2015. The independent and dependent variables were the baseline GGT/HDL-c ratio and diabetes during the follow-up, respectively. The Cox proportional-hazards regression model was used to explore the association between the GGT/HDL-c ratio and diabetes risk. A Cox proportional hazards regression with the cubic spline smoothing was used to recognize non-linear relationships between the GGT/HDL-c ratio and incident diabetes. After adjusting covariates, the results showed that the GGT/HDL-c ratio was positively associated with incident diabetes (HR = 1.013, 95% CI: 1.002, 1.024). There was also a non-linear relationship between the GGT/HDL-c ratio and the risk of diabetes, and the inflection point of the GGT/HDL-c ratio was 6.477. The HR on the left and right sides of the inflection point was 2.568 (1.157, 5.699) and 1.012 (1.001, 1.023), respectively. The sensitivity analysis demonstrated the robustness of the results. Besides, the performance of the FPG + GGT/HDL-c ratio was better than FPG + GGT, FPG + HDL-c, and FPG in predicting diabetes. This study demonstrates a positive and non-linear relationship between the GGT/HDL-c ratio and incident diabetes in the Japanese population. The GGT/HDL-c ratio is strongly related to diabetes risk when it is <6.477.

849P Time from primary melanoma to first distant recurrence in relation to survival outcomes in metastatic melanoma

Since the introduction of novel systemic therapies, the prognosis of advanced melanoma has greatly improved. Melanoma is known for its remarkably long time to first distant recurrence (TFDR), which can be decades in some patients and is attributed to immune-surveillance. We investigated the relationship between TFDR and outcomes upon systemic treatment for advanced melanoma. Analyses were performed on prospectively registered data from advanced cutaneous melanoma patients treated with first line BRAF(/MEK) inhibition or immune checkpoint inhibition (ICI) from the nationwide Dutch Melanoma Treatment Registry. Patients with a known primary tumor date were included. The association between TFDR and progression free survival (PFS) and overall survival (OS) was assessed by Cox proportional hazard regression models with adjustment for age and type of therapy, both continuously (modelled linearly as well as flexibly using restricted cubic splines) and categorically. Patients received anti-PD-1-based treatment (n=1361 monotherapy and 483 in combination with anti-CTLA4) or BRAF(/MEK) inhibition (n=1618). Median follow-up was 32.8 months. Patients with a longer TFDR (>5 years) had a longer PFS (Hazard ratio (HR) 0.89, 95% confidence interval (CI) 0.81-0.98) and OS (HR 0.83, 95%CI 0.75-0.92) than patients with TFDR <2 years. When stratifying for treatment, patients with a TFDR > 5 years (Table) had a longer median OS in both treatment cohorts. Based on a flexible spline fit and compared to synchronous disease, the hazard of dying rapidly decreased with increasing TFDR until approximately 5 years (HR 0.87), after which the hazard of dying further decreased with increasing TFDR, but less strongly (HR 0.82 for a TFDR of 10 years and HR 0.79 for a TFDR of 15 years).Table: 849PMedian PFS and OS stratified by systemic treatment for the different TFDR categoriesTime to first distant recurrenceLogrank P-value< 2 years2-5 years>5 yearsImmune checkpoint inhibitionMedian PFS, months (95%CI)7.3 (5.7-9.1)9.2 (7.4-12.2)10.0 (8.4-12.4)0.412Median OS, months (95%CI)25.0 (21.3-30.4)29.2 (30.6-35.7)37.3 (29.4-46.3)0.014BRAF(/MEK) inhibitionMedian PFS, months (95%CI)5.7 (5.4-6.2)5.8 (5.4-6.3)7.3 (6.4-8.1)0.006Median OS, months (95%CI)8.6 (7.4-9.8)8.1 (7.4-9.0)11.1 (10.2-12.2)0.004 Open table in a new tab Patients with longer TFDR have a prolonged PFS and OS, irrespective of being treated with first line ICI or targeted therapy.

Usporedna analiza utjecaja klimatskih čimbenika na radijalni rast autohtonih vrsta borova (Pinus spp.) u središnjoj Bosni i Hercegovini

In central Bosnia and Herzegovina, in the Zavidovići-Teslić area, the study of the radial growth of Austrian and Scots pine (autochthonous pine species) trees was conducted using the dendrochronological method in order to identify the differences between the species in terms of the influence of climatic variables on the tree ring formation. Trees were sampled in five experimental areas or five sites. The first site had a Scots pine stand, while the second had an Austrian pine stand, and the other three sites had mixed stands of Scots and Austrian pine. Cross-dating was conducted using visual on-screen techniques of CDendro software and statistical methods using Cofecha software. The tree ring series were standardized using the Arstan program and cubic smoothing spline. It produced Scots pine regional chronology, 145 years long (1870-2014), and Austrian pine regional chronology, 180 years long (1835-2014). Correlation analysis of the relationship between the index of tree-ring width and precipitation and temperature in the characteristic periods of the year showed a negative effect of temperature (except in winter months) and a positive effect of precipitation on the tree ring formation. The statistically significant dependence of the tree-ring width index on the SPEI indices indicates a significant impact of moisture deficiency on the tree ring formation in the period from June to August (r = 0.33 in June, r = 0.45 in July and r = 0.47 in August) for Scots pine and in the period from June to September (r = 0.36 in June, r = 0.43 in July, r = 0.47 in August and r = 0.30 in September) for Austrian pine. The analysis of the relationship between climatic parameters and the chronologies of Scots and Austrian pine shows similar relationships between radial growth and climate but the influence of climate is somewhat more pronounced in Austrian pine. In the study area, the radial growth of both tree species is significantly determined by climate conditions. In other words, the chronology of these species has a good climatic signal, especially the drought signal in the summer months.

A Cross-Sectional Age Group Study of Coarticulatory Resistance: The Case of Late-Acquired Voiceless Fricatives in English.

As a class, fricatives are more "resistant" to consonant-vowel coarticulation than other English sounds. This study investigates the relative coarticulatory resistance of /θ, s, ʃ/ in child and adult speech to better understand the acquisition of individuated speech sounds. Ten 5-year-old children, seven 8-year-old children, and nine college-age adults produced [əFV] sequences in carrier phrases, where F was /θ/, /s/, or /ʃ/ and V was /æ/, /i/, or /u/. In Experiment 1, coarticulation was perceptually indexed: 65 adults predicted the target stressed vowel based on forward-gated audiovisual speech samples for a subset of four speakers from each age group. In Experiment 2, dynamic spectral measures of the /əFV/ sequences were analyzed using smoothing spline analysis of variance to again test for vowel effects on fricative articulation across age groups. The perceptual results indicated that fricatives blocked vowel-vowel coarticulation across speaker age groups. Contrary to expectation, vowels were most accurately predicted when F was /s/ and not when it was /ʃ/ or /θ/ across age groups. Acoustic results indicated the expected biomechanically motivated /ʃ/ > /s/ > /θ/ coarticulatory resistance hierarchy in adults' speech. By contrast, /ʃ/ > /s/ were similarly influenced by context in 8-year-olds' speech, and the results from 5-year-olds' speech suggested an influence of order of acquisition in that /θ/ was surprisingly resistant to coarticulation. The study results are taken to suggest that a temporal constraint on fricative articulation interacts with biomechanical constraints during development to influence patterns of coarticulation in school-age children's speech.

Characteristic Analysis of the Spatio-Temporal Distribution of Key Variables of the Soil Freeze–Thaw Processes over Heilongjiang Province, China

The soil freeze–thaw phenomenon is one of the most outstanding characteristics of the soil in Heilongjiang Province. Quantitative analysis of the characteristics of changes in key variables of the soil freeze–thaw processes is of great scientific importance for understanding climate change, as well as ecological and hydrological processes. Based on the daily surface temperature and air temperature data in Heilongjiang Province for the past 50 years, the spatial–temporal distribution characteristics of key variables and their correlations with air temperature and latitude in the freeze–thaw process of soil were analyzed using linear regression, the Mann–Kendall test, the local thin disk smooth spline function interpolation method, and correlation analysis; additionally, the spatial–temporal distribution of key variables and the changes in the surface temperature during the freeze–thaw process are discussed under different vegetation types. The results show that there is a trend of delayed freezing and early melting of key variables of the soil freeze–thaw process from north to south. From 1971 to 2019 a, the freezing start date (FSD) was delayed at a rate of 1.66 d/10 a, the freezing end date (FED) advanced at a rate of 3.17 d/10 a, and the freezing days (FD) were shortened at a rate of 4.79 d/10 a; with each 1 °C increase in temperature, the FSD was delayed by about 1.6 d, the FED was advanced by about 3 d, and the FD was shortened by about 4.6 d; with each 1° increase in latitude, the FSD was delayed by about 2.6 d, the FED was advanced by about 2.8 d, and the FD was shortened by about 5.6 d. The spatial variation in key variables of the soil freeze–thaw process under the same vegetation cover was closely related to latitude and altitude, where the lower the latitude and altitude, the more obvious the variation trend; among them, the interannual variation trend of key variables of soil freeze–thaw under meadow cover was the most obvious, which varied by 9.65, 16.86, and 26.51 d, respectively. In addition, the trends of ground temperature under different vegetation types were generally consistent, with the longest period of unstable freeze–thaw and the shortest period of stable freeze in coniferous forests, compared to the shortest period of unstable freeze–thaw and the longest period of stable freeze in meadows. The results of the study are important for our understanding of soil freeze–thaw processes and changes in Heilongjiang Province, as well as the evolution of high-latitude permafrost; they also promote further exploration of the impact of soil freeze–thaw on agricultural production and climate change.

Map composition framework for synthetic P morphology

In this work we address the data privacy concerns and the need of extensive data sets by the deep learning models. We account the need of low computational frame work along with flexible architecture and diverse requirements. We use a novel approach to generate extensive synthetic P wave morphology sets from fifteen cycles of the real ECG record (MIT-BIH Arrhythmia dataset). Our approach is based on development of Python framework of algorithms. It consists of a composition of a variability trend of discrete realistic ECG record samples. We used regression modalities (polynomial fit and spline fit) in a novel way in R2 vector space. The space thus formed is an interspersion of real and synthetic vectors. The space indexed with each real index in the range (0–14) produced a new synthetic P morphology. We introduced a robust approach by developing threshold invariance in R peak detection. We developed R–R interval extraction and subsequently P contour extraction algorithm as part of frame-work. A similarity metric is proposed in order to compare morphologies and address the realism feel of synthetic morphology. The similarity score of generated wave is 0.72. We have observed the scope for enhancement in P contour extraction algorithm and accounting P width variability. We noted that the method used for synthetic generation is linked to the end use case application for different trade-offs. Thus there is a scope for different methods and novelty. Our method produced extensive morphologies from a fifteen cycle snapshot of the real ECG record. We also developed a GAN P wave setup to estimate the compute complexity of GAN for comparison with map composition framework. The compute complexity was found to be best case O(25K) for the Keras (P wave GAN) sequential model architecture. For map composition frame work the compute complexity is O(67K), however the compute cost is significant in case of P wave GAN which is approximately (32∗106) operations, where as for map composition the cost is approximately (0.67∗106)operations.

A Non-Contact Detection Method for Multi-Person Vital Signs Based on IR-UWB Radar.

With the vigorous development of ubiquitous sensing technology, an increasing number of scholars pay attention to non-contact vital signs (e.g., Respiration Rate (RR) and Heart Rate (HR)) detection for physical health. Since Impulse Radio Ultra-Wide Band (IR-UWB) technology has good characteristics, such as non-invasive, high penetration, accurate ranging, low power, and low cost, it makes the technology more suitable for non-contact vital signs detection. Therefore, a non-contact multi-human vital signs detection method based on IR-UWB radar is proposed in this paper. By using this technique, the realm of multi-target detection is opened up to even more targets for subjects than the more conventional single target. We used an optimized algorithm CIR-SS based on the channel impulse response (CIR) smoothing spline method to solve the problem that existing algorithms cannot effectively separate and extract respiratory and heartbeat signals. Also in our study, the effectiveness of the algorithm was analyzed using the Bland–Altman consistency analysis statistical method with the algorithm’s respiratory and heart rate estimation errors of 5.14% and 4.87%, respectively, indicating a high accuracy and precision. The experimental results showed that our proposed method provides a highly accurate, easy-to-implement, and highly robust solution in the field of non-contact multi-person vital signs detection.

The Recognition of Different Odor Using Convolutional Neural Networks Extracted From Time and Temperature Features

In this paper, we propose a dataset processing method for odor recognition using neural networks, which extracts the sensor multi-dimensional temperature information and high-dimensional time series information during the response process. In this “sniffing” system, 4 different Micro-Electro-Mechanical System (MEMS) Metal-Oxide-Semiconductor (MOX) gas sensors are utilized, and 4 different heating voltages are applied to the sensor array. After classifying 6 chemical gases closely related to food at 3 different concentrations each, we introduced 10 kinds of food for classification. To construct an abstract odor factor map as a feature map of odor samples, we process each group of different relatively low-bandwidth sensor signals with smoothing spline, Gaussian window, etc. By Inputting the feature map into a specific convolutional neural network, we successfully achieve 98.7% accuracy in chemical gas recognition and 95.8% accuracy in food classification.

Eikonal surface wave tomography of central and eastern China

SUMMARY Eikonal tomography has become a key approach to image lithospheric structures with surface waves recorded by dense regional arrays. Its main advantage is that phase velocities can be determined directly from phase measurements without resolving a tomographic inverse problem. Here, we apply a new smoothing spline eikonal tomography approach to a selection of 40 large (Mw larger than 6.5) teleseismic events recorded by the permanent seismic stations of the CEArray. We first apply a time–frequency filter to isolate the fundamental mode of Rayleigh waves and cross-correlate the cleaned and isolated surface wave records to measure precise relative traveltimes. The phase measurements are then unwrapped and corrected for cycle skipping. Finally, we derive phase-velocity maps from the gradient of the reconstructed traveltime fields, using the eikonal equation. We obtain finely resolved phase-velocity maps from 25 to 150 s period that are inverted to obtain a 3-D shear wave velocity model which is in good agreement with previous tomographic studies. The lithospheric architecture emerging from the phase-velocity maps and 3-D S-wave velocities correlates with surface geology and major tectonic provinces. In particular, the architecture of the narrow rift systems, the South China Craton, and the North China Craton (NCC) are revealed with unprecedented details. The South China Craton is characterized by very high velocities beneath the Sichuan Basin. The NCC shows more complex structures with two high-velocity anomalies beneath the Ordos Basin and the southeastern NCC and low-velocity anomalies beneath the Cenozoic rift systems.

On the Nonparametric Approach to Estimation of Non- Constant Variance Function: An Application to Nairobi Securities Exchange (NSE)

Methods for estimating regression models to data in the areas showing varying variances is considered. The centre of attention is on diverse methods of evaluating varying variances. The nonparametric approach which incorporates the smoothing methods and the choice of the ideal bandwidth is discussed. Normally, the cardinal shortcoming which is of interest is the selection of the smoothing method and picking of the best bandwidth [1], Zhai, C. and Lafferty, J. [2]. The two oftenly used smoothing methods; the Gaussian Kernel and Spline are compared. The two smoothing techniques are illustrated and compared using data obtained from Nairobi Securities exchange (NSE) and found that the Gaussian Kernel outperforms the Spline smoother since it gives the best estimate of the variance.

A novel two-stage data-driven model for ultra-short-term wind speed prediction

Accurate prediction of wind speed and its output power is playing an essential role in the planning and scheduling of wind power grid. This study presents a novel two-stage data-driven model for ultra-short-term wind speed prediction based on the smoothing spline preprocessing (SSP) method and error optimization theory (EOT). Firstly, high-resolution wind data observed from 39 wind turbines are collected and transformed according to the proposed SSP method to eliminate the non-Gaussian and non-stationary features. Then, several individual models are introduced to perform multi-step ahead wind speed prediction for the transformed wind data, and the prediction of transformed data should be recovered to wind speed. Finally, these single models are combined based on the proposed EOT theory for multi-step ahead wind speed prediction, and their accuracy and uncertainty are analyzed and compared with other existing models in depth. The results show that the proposed SSP method can reasonably identify non-Gaussian and non-stationary features of the original wind series, and the transformed data are more favorable for prediction. Furthermore, the suggested two-stage data-driven model can reduce prediction errors by 3%–20% compared with other models mentioned in this study, indicating that it is more effective and stable in terms of providing reasonable ultra-short-term wind speed prediction results.

Online monitoring of profiles via function‐on‐scalar model with an application to industrial busbar

AbstractIn Statistical Process Control, profile monitoring is used for monitoring whether the process is in‐control or not by checking the relationship stability between the process response and covariates. In the industrial process recently, the functional relationship between the process variables is more and more complex, and the profile data are often time‐dependent and subject to within‐profile autocorrelation. We need to use appropriate models to characterize these complex relationships, and design new profile monitoring schemes to ensure satisfactory process monitoring performance. This paper studies a practical nonparametric profile monitoring problem, in which the functional relationship is in the form of function‐on‐scalar and within‐profile data are autocorrelated. A new online profile monitoring scheme is proposed to monitor process anomalies in real time. In Phase Ⅰ, based on the in‐control historical data, the model for the process is established estimated. Then, using the monitoring statistics based on penalty spline smoothing, the function‐on‐scalar monitoring parameters control scheme with a moving window is presented, and is applied to the anomaly monitoring of online sequential profile data. A large number of numerical simulation results show that in the presence of the function‐on‐scalar relationship, the proposed scheme has a superior performance in various cases. Finally, an application example of industrial busbar running process monitoring is given to illustrate the effectiveness of the scheme.

Analysis of the Temporal and Spatial Changes of Sea Level in Korean Coastal Zone

In this study, the temporal and spatial changes of sea level in Korean coastal zone were analyzed. First, the error value of 1 hour tide data provided by the Korea Hydrographic and Oceanographic Agency was excluded through preprocessing, the analysis of sea level change was performed by considering long period components through low-pass filtering. Using low-pass filtering data, the monthly mean sea level was calculated and the temporal changes of sea level were verified by data fitting using linear fit and multidimensional smoothing spline. The results of linear fit show that the tide tends to rise at most stations. And the results of multidimensional smoothing spline fit show that the increase and decrease of sea level is repeated every year. Although the amounts of change vary every year, sea levels have been repeated seasonally, with sea levels rising in summer and falling in winter. Also, Hovmöller diagram was prepared for the change of sea level in each east, west, and south coast, and the temporal and spatial changes of sea level were analyzed. Compared to the past, recent sea level changes increased in all points. Especially, in the west coast, the sea level increased more in the south (Mokpo) area than in the north (Yeongjong Bridge), and the south (Mokpo) area of the west coast could be a vulnerable area due to the rise in sea level.

Deformable 3D-2D image registration and analysis of global spinal alignment in long-length intraoperative spine imaging.

Spinal deformation during surgical intervention (caused by patient positioning and/or the correction of malalignment) confounds conventional navigation due to the assumptions of rigid transformation. Moreover, the ability to accurately quantify spinal alignment in the operating room would provide an assessment of the surgical product via metrics that correlate with clinical outcomes. A method for deformable 3D-2D registration of preoperative CT to intraoperative long-length tomosynthesis images is reported for an accurate 3D evaluation of device placement in the presence of spinal deformation and automated evaluation of global spinal alignment (GSA). Long-length tomosynthesis ("Long Film," LF) images were acquired using an O-arm imaging system (Medtronic, Minneapolis USA). A deformable 3D-2D patient registration was developed using multi-scale masking (proceeding from the full-length image to local subvolumes about each vertebra) to transform vertebral labels and planning information from preoperative CT to the LF images. Automatic measurement of GSA (main thoracic kyphosis [MThK] and lumbar lordosis [LL]) was obtained using a spline fit to registered labels. The "Known-Component Registration" method for device registration was adapted to the multi-scale process for 3D device localization from orthogonal LF images. The multi-scale framework was evaluated using a deformable spine phantom in which pedicle screws were inserted, and deformations were induced over a range in LL ∼25°-80°. Further validation was carried out in a cadaver study with implanted pedicle screws and a similar range of spinal deformation. The accuracy of patient and device registration was evaluated in terms of 3D translational error and target registration error, respectively, and the accuracies of automatic GSA measurements were compared to manual annotation. Phantom studies demonstrated accurate registration via the multi-scale framework for all vertebral levels in both the neutral and deformed spine: median (interquartile range, IQR) patient registration error was 1.1mm (0.7-1.9mm IQR). Automatic measures of MThK and LL agreed with manual delineation within -1.1°±2.2° and 0.7°±2.0° (mean and standard deviation), respectively. Device registration error was 0.7mm (0.4-1.0mm IQR) at the screw tip and 0.9° (1.0°-1.5°) about the screw trajectory. Deformable 3D-2D registration significantly outperformed conventional rigid registration (p<0.05), which exhibited device registration errors of 2.1mm (0.8-4.1mm) and 4.1° (1.2°-9.5°). Cadaver studies verified performance under realistic conditions, demonstrating patient registration error of 1.6mm (0.9-2.1mm); MThK within -4.2°±6.8° and LL within 1.7°±3.5°; and device registration error of 0.8mm (0.5-1.9mm) and 0.7° (0.4°-1.2°) for the multi-scale deformable method, compared to 2.5mm (1.0-7.9mm) and 2.3° (1.6°-8.1°) for rigid registration (p<0.05). The deformable 3D-2D registration framework leverages long-length intraoperative imaging to achieve accurate patient and device registration over the extended lengths of the spine (up to 64cm) even with strong anatomical deformation. The method offers a new means for the quantitative validation of spinal correction (intraoperative GSA measurement) and the 3D verification of device placement in comparison to preoperative images and planning data.

In vitro susceptibility testing for the emerging pathogenic mould Veronaea botryosa and pharmacokinetic parameters of natamycin in white sturgeon (Acipenser transmontanus).

Systemic phaeohyphomycosis caused by the dematiaceous mould Veronaea botryosa is an important emergent disease affecting captive sturgeons (Acipenser spp.). The disease, colloquially known as "fluid belly," causes morbidity and mortality in adult animals resulting in significant economic losses to the aquaculture industry. Advancements in therapeutic and prophylactic protocols have been partially hampered by the lack of basic protocols to grow and manipulate the fungus in the laboratory. In this study, microbroth kinetic protocols were established to analyse V.botryosa growth in seven nutrient media at different temperatures. Generated area under the curve (AUC) indicates that potato flake dextrose broth (PFD-B) and Sabouraud dextrose broth (SD-B) incubated at 25°C provided the greatest growth. The generated protocol was then used to test the susceptibility of V.botryosa isolates to natamycin, a macrolide polyene antifungal agent used as a food preservative. SD-B and RPMI with l-glutamine (+RPMI-B) containing different concentrations of natamycin were inoculated with V.botryosa conidia and the generated growth curves were compared using cubic smoothing spline model. The non-inhibitory concentration and minimal inhibitory concentration (MIC; decrease of AUC by 90% compared with control) were determined to be <1μg/mL and 16 μg/mL of natamycin in SD-B media. To gain an understanding of the tissue distribution of natamycin in white sturgeon, pharmacokinetics was tested. Based on pharmacokinetic parameters determined in this study and targeting a blood concentration >16 μg/mL for 24 h, an intravenous dose >1g/kg would be needed, making the use of this drug unrealistic. The information presented in this study can be used to investigate susceptibility of pathogenic fungus to antimicrobials and disinfectants as well as support future therapeutic protocols against emerging fungal diseases like fluid belly.

Age-specific growth and maturity estimates for the flatback sea turtle (Natator depressus) by skeletochronology.

To address a major knowledge gap for flatback sea turtles (Natator depressus), a species endemic to Australia and considered ‘Data Deficient’ for IUCN Red List assessment, we present the first-ever skeletochronology-derived age and growth rate estimates for this species. Using a rare collection of bone samples gathered from across northern Australia, we applied skeletochronology and characterized the length-at-age relationship, established baseline growth rates from the hatchling to adult life stages, and produced empirical estimates of age-at- and size-at-sexual-maturation (ASM, SSM). We analyzed humeri from 74 flatback sea turtles ranging in body size from 6.0–96.0 cm curved carapace length (CCL), and recovered from Western Australia (n = 48), Eastern Australia (n = 13), central Australia (n = 8; Northern Territory n = 3, the Gulf of Carpentaria n = 5), and unknown locations (n = 5). We identified the onset of sexual maturity for 29 turtles, based on rapprochement growth patterns in the bones. Estimates for ASM ranged from 12.0 to 23.0 years (mean: 16.3 ± 0.53 SE), SSM ranged from 76.1 to 94.0 cm CCL (mean: 84.9 ± 0.90 SE), and maximum observed reproductive longevity was 31 years for a 45-year old male flatback. Growth was modeled as a smoothing spline fit to the size-at-age relationship and at the mean SSM (84.9 cm CCL) corresponded with a spline-predicted maturity age of 18 years (95% CI: 16 to 24), while mean nesting sizes reported in the literature (86.4 to 94 cm CCL) corresponded to estimated ages of 24+ years. A bootstrapped von Bertalanffy growth model was also applied and showed consistencies with the spline curve, yielding an estimated upper size limit, Linf, at 89.2 ± 0.04 cm (95% CI: 85.5 to 95.9 cm) with the intrinsic growth rate parameter, k, at 0.185 ± 0.0004 (0.16 to 0.22); at the same mean SSM (84.9 cm CCL) the estimated ASM was 16.3 ± 0.05 years (95% CI: 12.8 to 27.7 years). Lastly, four of the samples analyzed were collected from deceased adult females that had previous sizes known from on-going mark/recapture studies at nesting sites in Western Australia. The paired CCL data (measured at nesting and back-calculated) did not significantly differ (p = 0.875). This first skeletochronology study for flatback sea turtles generates valuable empirical estimates for ongoing conservation and management efforts.