bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhanced parameter estimation in multiparametric arterial spin labeling using artificial neural networks
Authors: Ishida Shota , Fujiwara Yasuhiro , Matta Yuki , Takei Naoyuki , Kanamoto Masayuki , Kimura Hirohiko , Tsujikawa Tetsuya 
Published: June 2024

AbstractPurposeMultiparametric arterial spin labeling (MP‐ASL) can quantify cerebral blood flow (CBF) and arterial cerebral blood volume (CBVa). However, its accuracy is compromised owing to its intrinsically low SNR, necessitating complex and time‐consuming parameter estimation. Deep neural networks (DNNs) offer a solution to these limitations. Therefore, we aimed to develop simulation‐based DNNs for MP‐ASL and compared the performance of a supervised DNN (DNNSup), physics‐informed unsupervised DNN (DNNUns), and the conventional lookup table method (LUT) using simulation and in vivo data.MethodsMP‐ASL was performed twice during resting state and once during the breath‐holding task. First, the accuracy and noise immunity were evaluated in the first resting state. Second, CBF and CBVa values were statistically compared between the first resting state and the breath‐holding task using the Wilcoxon signed‐rank test and Cliff's delta. Finally, reproducibility of the two resting states was assessed.ResultsSimulation and first resting‐state analyses demonstrated that DNNSup had higher accuracy, noise immunity, and a six‐fold faster computation time than LUT. Furthermore, all methods detected task‐induced CBF and CBVa elevations, with the effect size being larger with the DNNSup (CBF, p = 0.055, Δ = 0.286; CBVa, p = 0.008, Δ = 0.964) and DNNUns (CBF, p = 0.039, Δ = 0.286; CBVa, p = 0.008, Δ = 1.000) than that with LUT (CBF, p = 0.109, Δ = 0.214; CBVa, p = 0.008, Δ = 0.929). Moreover, all the methods exhibited comparable and satisfactory reproducibility.ConclusionDNNSup outperforms DNNUns and LUT with respect to estimation performance and computation time.
ssVERDICT: Self‐supervised VERDICT‐MRI for enhanced prostate tumor characterization
Authors: Sen Snigdha , Singh Saurabh , Pye Hayley , Moore Caroline M. , Whitaker Hayley C. , Punwani Shonit , Atkinson David , Panagiotaki Eleftheria , Slator Paddy J. 
Published: June 2024

AbstractPurposeDemonstrating and assessing self‐supervised machine‐learning fitting of the VERDICT (vascular, extracellular and restricted diffusion for cytometry in tumors) model for prostate cancer.MethodsWe derive a self‐supervised neural network for fitting VERDICT (ssVERDICT) that estimates parameter maps without training data. We compare the performance of ssVERDICT to two established baseline methods for fitting diffusion MRI models: conventional nonlinear least squares and supervised deep learning. We do this quantitatively on simulated data by comparing the Pearson's correlation coefficient, mean‐squared error, bias, and variance with respect to the simulated ground truth. We also calculate in vivo parameter maps on a cohort of 20 prostate cancer patients and compare the methods' performance in discriminating benign from cancerous tissue via Wilcoxon's signed‐rank test.ResultsIn simulations, ssVERDICT outperforms the baseline methods (nonlinear least squares and supervised deep learning) in estimating all the parameters from the VERDICT prostate model in terms of Pearson's correlation coefficient, bias, and mean‐squared error. In vivo, ssVERDICT shows stronger lesion conspicuity across all parameter maps, and improves discrimination between benign and cancerous tissue over the baseline methods.ConclusionssVERDICT significantly outperforms state‐of‐the‐art methods for VERDICT model fitting and shows, for the first time, fitting of a detailed multicompartment biophysical diffusion MRI model with machine learning without the requirement of explicit training labels.
A decay‐modeled compressed sensing reconstruction approach for non‐Cartesian hyperpolarized 129Xe MRI
Authors: Plummer Joseph W. , Hussain Riaz , Bdaiwi Abdullah S. , Soderlund Stephanie A. , Hoyos Xavier , Lanier John M. , Garrison William J. , Parra‐Robles Juan , Willmering Matthew M. , Niedbalski Peter J. , Cleveland Zackary I. , Walkup Laura L. 
Published: June 2024

AbstractPurposeHyperpolarized 129Xe MRI benefits from non‐Cartesian acquisitions that sample k‐space efficiently and rapidly. However, their reconstructions are complex and burdened by decay processes unique to hyperpolarized gas. Currently used gridded reconstructions are prone to artifacts caused by magnetization decay and are ill‐suited for undersampling. We present a compressed sensing (CS) reconstruction approach that incorporates magnetization decay in the forward model, thereby producing images with increased sharpness and contrast, even in undersampled data.MethodsRadio‐frequency, T1, and decay processes were incorporated into the forward model and solved using iterative methods including CS. The decay‐modeled reconstruction was validated in simulations and then tested in 2D/3D‐spiral ventilation and 3D‐radial gas‐exchange MRI. Quantitative metrics including apparent‐SNR and sharpness were compared between gridded, CS, and twofold undersampled CS reconstructions. Observations were validated in gas‐exchange data collected from 15 healthy and 25 post‐hematopoietic‐stem‐cell‐transplant participants.ResultsCS reconstructions in simulations yielded images with threefold increases in accuracy. CS increased sharpness and contrast for ventilation in vivo imaging and showed greater accuracy for undersampled acquisitions. CS improved gas‐exchange imaging, particularly in the dissolved‐phase where apparent‐SNR improved, and structure was made discernable. Finally, CS showed repeatability in important global gas‐exchange metrics including median dissolved‐gas signal ratio and median angle between real/imaginary components.ConclusionA non‐Cartesian CS reconstruction approach that incorporates hyperpolarized 129Xe decay processes is presented. This approach enables improved image sharpness, contrast, and overall image quality in addition to up‐to threefold undersampling. This contribution benefits all hyperpolarized gas MRI through improved accuracy and decreased scan durations.
A reusable 3D printed brain‐like phantom for benchmarking electrical properties tomography reconstructions
Authors: Meerbothe T. G. , Florczak S. , van den Berg C. A. T. , Levato R. , Mandija S. 
Published: June 2024

AbstractPurposeIn MR electrical properties tomography (MR‐EPT), electrical properties (EPs, conductivity and permittivity) are reconstructed from MR measurements. Phantom measurements are important to characterize the performance of MR‐EPT reconstruction methods, since they allow knowledge of reference EPs values. To assess reconstruction methods in a more realistic scenario, it is important to test the methods using phantoms with realistic shapes, internal structures, and dielectric properties. In this work, we present a 3D printing procedure for the creation of realistic brain‐like phantoms to benchmark MR‐EPT reconstructions.MethodsWe created two brain‐like geometries with three different compartments using 3D printing. The first geometry was filled once, while the second geometry was filled three times with different saline‐gelatin solutions, resulting in a total of four phantoms with different EPs. The saline solutions were characterized using a probe. 3D MR‐EPT reconstructions were performed from MR measurements at 3T. The reconstructed conductivity values were compared to reference values of the saline‐gelatin solutions. The measured fields were also compared to simulated fields using the same phantom geometry and electrical properties.ResultsThe measured fields were consistent with simulated fields. Reconstructed conductivity values were consistent with the reference (probe) conductivity values. This indicated the suitability of such phantoms for benchmarking MR‐EPT reconstructions.ConclusionWe presented a new workflow to 3D print realistic brain‐like phantoms in an easy and affordable way. These phantoms are suitable to benchmark MR‐EPT reconstructions, but can also be used for benchmarking other quantitative MR methods.
Identifying critical demand scenarios for the robust capacitated network design problem using principal component analysis
Authors: Bley Andreas , Hahn Philipp 
Published: June 2024

AbstractIn this paper, we consider the single‐commodity robust network design problem. Given an undirected graph with capacity installation costs on its edges and a set of scenarios with associated flow balance vectors that represent different scenarios of node supplies and demands, the goal is to find integer edge capacities that minimize the total installation cost and permit a feasible single commodity flow for each scenario. This problem arises, for example, in the design of power networks, which are dimensioned to accommodate many different load scenarios. We propose a new method to identify a small subset of the given scenarios, such that solving the robust network design problem for the smaller scenario set leads to almost the same capacities as solving it for the full scenario set . By considering only the scenarios in , the size of the model that needs to be solved can be reduced substantially, while the error introduced by neglecting the remaining scenarios is kept very small. Our method only employs simple techniques from statistical data analysis, namely principal component analysis (PCA), and convex hull computations in low dimensions. Thus, its computational effort is very small and it is easily applicable to more complex network design problems. We evaluate the effectiveness of the method in computational experiments for instances stemming from offshore power grid planning and telecommunication networks. Our results show that the proposed techniques are indeed well suited to identify small scenario subsets that lead to significantly reduced models with high quality solutions.
Psychological Status as an Effect Modifier of the Association Between Allergy Symptoms and Allergy Testing
Authors: Kim Minjee , Li Anne , Prince Anthony A. , Nadkarni Ashwini , Louisias Margee , Corrales Carleton Eduardo , Gilani Sapideh , Shin Jennifer J. 
Published: June 2024

AbstractObjectivePatient‐reported outcome measures, while valuable, may not correlate with diagnostic test results. To better understand this potential discrepancy, our objective was to determine whether psychological health is an effect modifier of the association between patient‐reported allergy outcome scores and allergy test results.Study DesignProspective outcomes study.SettingTertiary care hospital and community‐based clinic.MethodsThis study included 600 patients at least 18 years of age who presented for symptoms related to allergic rhinitis and completed the related sinonasal outcome test (SNOT), which includes validated nasal, allergy, and psychological domains. Stratified analyses of odds ratios and Spearman correlation coefficients were utilized to assess for effect modification by psychological status.ResultsWorse patient‐reported allergic rhinitis symptoms were significantly associated with positive allergy test results (odds ratio [OR] 1.69, 95% confidence interval [CI] 1.22‐2.34, P = .002) in patients with better psychological health. In contrast, there was no association in patients with worse psychological health (OR 1.06, 95% CI 0.36‐3.10, P = .92). These findings were corroborated by assessments of correlation: allergy domain scores were positively correlated with allergy testing scores (Spearman rho 0.18, 95% CI 0.10‐0.25, P < .001) in patients with better psychological health, while there was no correlation in patients with worse psychological health (−0.02, 95% CI −0.16‐0.12, P = .77).ConclusionsPsychological status was an effect modifier of the association between allergy domain and allergy testing data. When assessing the relationship between subjective measures, such as sinonasal validated instruments, and objective measures, such as allergy test results, accounting for effect modifiers such as psychological state can provide clinical and research‐related insights.
Ultra‐high bonding strength of carbon fiber–doped polyamide–aluminum alloy composite structure achieved by changing crystallinity
Authors: Zhao Wei , Qiu Jianhui , Sakai Eiichi , Wu Haonan , Zhao Yang , Feng Huixia , Guo Shaoyun , Wu Hong 
Published: June 2024

AbstractLightweight and high‐strength polymer–metal hybrid structures are favored for reducing material and energy consumption. In this study, carbon fiber‐reinforced polyamide 6 (CFPA) composite materials were prepared through melt blending, and 30 wt% CFPA exhibited the highest shear strength and lowest shrinkage rate among other carbon fiber contents. With pretreatments of anodizing and etching treatment, injection molded direct joining was employed to create polyamide 6 (PA)/CFPA–Aluminum alloy (Al) composites. The impacts of the injection temperature and speed on the bonding strength of the PA/CFPA–Al composite materials were investigated. The characterization results confirmed that carbon fiber doping reduces the coefficient of linear thermal expansion (CLTE) and enhances crystallization ability of PA. The higher injection temperatures and lower injection speed significantly increase the crystallinity of PA and the infiltration of the molten polymer into the nanoporous anodic aluminum oxide films. When the injection temperature was 270°C and the speed was 6 mm/s, the bonding strength of the PA–Al hybrid structure reached a maximum of 36.6 MPa. When the injection temperature was 300°C, the bonding strength of the CFPA–Al hybrid structure reached a maximum of 40.8 MPa. Adhesive parts with high shear bonding strength are critical to satisfying engineering requirements and have significant potential, particularly in polymer–metal composite structures. The polymer‐metal hybrid structure can meet the high interfacial bonding strength required in most engineering applications.Highlights
Injection temperature and speed in IMDJ affect PA crystallinity.
Carbon fiber doping reduces the CLTE of PA and increases the shear strength.
High temperatures and low injection speeds are beneficial to adhesives.
The bonding strength of PA–Al reached a maximum of 36.6 MPa.
The bonding strength of CFPA–Al reached a maximum of 40.8 MPa.
Nocturnal enuresis in early adolescence and neurodevelopmental delay in infancy: A population‐based study
Authors: Kanata Sho , Ando Shuntaro , Yamasaki Syudo , Fujikawa Shinya , Morimoto Yuko , Kiyono Tomoki , Morita Masaya , Hiraiwa‐Hasegawa Mariko , Nishida Atsushi , Kasai Kiyoto 
Published: June 2024

AbstractAimThe neurodevelopmental delay hypothesis may explain the mechanism of nocturnal enuresis (NE), but whether the hypothesis holds in early adolescence remains unknown, considering NE frequency. Therefore, we aimed to identify whether neurodevelopmental delays in infancy were associated with the frequency of NE in early adolescence.MethodsData were extracted from the Tokyo Early Adolescence Survey, in which 4478 children (mean age: 10.2 years) and their parents participated. Twelve developmental delays (eight motor, four verbal) were extracted from the Maternal and Child Health Handbook. The NE frequency was obtained from a parent‐answered questionnaire, which divided children into three categories according to DSM‐5 criteria (none, infrequent [<1 time a week], and frequent [≥2 times a week]). Multinomial logistic regression analysis was performed to determine whether delayed developmental milestones in infancy were predictive of frequent/infrequent NE in early adolescence.ResultsDevelopmental delays, particularly those related to motor development but not verbal, such as holding their head up (odds ratio [95% confidence interval] = 2.1 [1.1–4.2]), crawling (2.1 [1.0–4.4]), walking with support (4.0 [1.9–8.4]), walking independently (5.8 [2.2–15.4]), and drawing a circle (5.0 [2.0–12.3]), were significantly associated with an increased risk of frequent NE in early adolescence (all ps < 0.05). However, an association with infrequent NE was not found.ConclusionThis population‐based epidemiological study revealed that motor developmental delays increased the risk of frequent NE in early adolescence, but not of infrequent NE. This finding reinforces the neurodevelopmental delay hypothesis, which provides a biological explanation for the involuntary nature of enuresis. All children in early adolescence with frequent NE should be evaluated and treated by a medical expert.
Constraints of commercially available seed diversity in restoration: Implications for plant functional diversity
Authors: Andres Samantha E. , Atkinson Joe , Coleman David , Brazill‐Boast James , Wright Ian J. , Allen Stuart , Gallagher Rachael V. 
Published: June 2024

Societal Impact StatementLarge quantities of diverse native seeds are required to scale up global restoration efforts. However, it remains unclear for many ecosystems how the diversity of available seed in commercial stocks reflects the composition of the ecosystems where vegetation is being remade. This study highlights existing shortfalls in the diversity of seed presently available for use in restoration and identifies gaps in the seed supply chain while providing a new method for optimising species selection given these constraints. This work underscores how improved collaboration between stakeholders is required to strengthen the seed supply chain and help remake functionally diverse vegetation.Summary

Restoration using native seed is frequently implemented to restore degraded ecosystems. However, it remains unclear how constraints on the diversity of germplasm available for use in restoration may limit the recovery of both species and plant functional diversity.
Using a dataset of seed availability for Australia's major vegetation types, we explore variation in the diversity and breadth of functional traits (leaf mass per area, seed mass, plant height) for species where seed is available on commercial markets relative to unavailable. Using these data, we simulate theoretical seed mixes derived from two species pools: (1) constrained by the current market of commercially available seed, and (2) assuming all native species can be planted; then we compare differences in functional diversity (dispersion) as an exercise to explore possible limitations within the current seed supply.
Seed from only 12% of Australian plant species (2992 species) is presently available for immediate purchase. Seed was more frequently available for trees and shrubs than for understorey species. Available species were on average taller, with thicker, longer‐lived leaves than unavailable species. Overall, functional dispersion was lower for seed mixes generated using available seed compared with those drawn from all species.
Solutions are required to address seed shortfalls so that plantings are not only species rich but also functionally diverse. We develop two options: (1) quantifying and addressing gaps in the seed supply chain that currently limit the capacity for practitioners to restore diverse vegetation; and (2) applying a trait‐informed species‐selection method to plantings that maximises functional diversity using available seed.
The partnership between statisticians and the Institutional Animal Care and Use Committee (IACUC)
Authors: Potter David , Bradstreet Thomas , Sargsyan Davit , Tan Xiao , Bonato Vinicius , Li Dingzhou , Liang John , Libiger Ondrej , Sendecki Jocelyn , Stansfield John , Tatikola Kanaka , Xu Jialin , Campbell Brandy 
Published: June 2024

AbstractIn this tutorial we explore the valuable partnership between statisticians and Institutional Animal Care and Use Committees (IACUCs) in the context of animal research, shedding light on the critical role statisticians play in ensuring the ethical and scientifically rigorous use of animals in research. Pharmaceutical statisticians have increasingly become vital members of these committees, contributing expertise in study design, data analysis, and interpretation, and working more generally to facilitate the integration of good statistical practices into experimental procedures. We review the “3Rs” principles (Replacement, Reduction, and Refinement) which are the foundation for the humane use of animals in scientific research, and how statisticians can partner with IACUC to help ensure robust and reproducible research while adhering to the 3Rs principles. We also highlight emerging areas of interest, such as the use of virtual control groups.
Spontaneous dual ectopic pregnancies in the ipsilateral fallopian tube and ovary: A case report and literature review
Authors: Young Brenda , Carter Emily , Colletta Kassandra 
Published: June 2024

AbstractBackgroundConcurrent ectopic pregnancies in differing anatomical locations are a rarity. It is imperative to be able to identify these cases as extrauterine pregnancies require emergent evaluation and treatment.CaseWe describe a case of suspected ruptured ectopic pregnancy in a low‐risk multiparous female found to have ipsilateral ovarian and tubal ectopic pregnancies on laparoscopy and subsequent pathology.ConclusionAlthough the co‐occurrence of these pregnancies presented as a diagnostic challenge, preoperative ultrasound imaging increased our suspicion in conjunction with laparoscopic findings. Thorough examination of the uterus and bilateral adnexa during laparoscopy is essential in identifying pathology and reducing morbidity. Furthermore, sampling or removal of suspicious concomitant lesions may aid in diagnosis. Following beta HCG trends may provide additional information in patients with unclear findings on laparoscopy.
COVID‐19 as a risk factor for hypertensive disorders of pregnancy: A retrospective cohort study
Authors: Childs Hannah , Bickerstaff Cayman , Stoikov Teodora , Xu Hongyan , Marino Katherine , Li Cynthia , Nguyen Lina , Rodgers Bailey , Allen Jennifer T. 
Published: June 2024

AbstractObjectiveThe aim of this study was to assess whether coronavirus disease 2019 (COVID‐19) infection during pregnancy is a risk factor for hypertensive disorders of pregnancy.MethodsA retrospective evaluation was conducted on obstetric patients who gave birth between March 2020 and December 2021 at an academic urban referral center. The patients were categorized as COVID‐19‐positive or COVID‐19‐negative during pregnancy. The primary outcome was the development of a hypertensive disorder of pregnancy. Secondary outcomes included preterm delivery, mode of delivery, maternal death, maternal intensive care unit (ICU) admission, neonatal ICU admission, intrauterine fetal demise/stillbirth, fetal growth restriction and prolonged hospital stay. χ2 tests, Fisher's exact tests, Student's two‐sample tests and multiple logistic regressions were used to evaluate the association between COVID‐19 status and outcomes.ResultsOf 2760 reviewed charts, 2426 (87.9%) met the inclusion criteria. Of 2426 patients, 203 were COVID‐positive and 2223 were COVID‐negative. There were no significant demographic differences between the two groups. After adjusting for confounding effects, COVID‐19 was determined to be a risk factor for combined hypertensive disorders of pregnancy (odds ratio [OR] 1.93, 95% confidence interval [CI]: 1.39–2.66) and pre‐eclampsia specifically (OR 2.01, 95% CI 1.38–2.88). COVID‐19 infection during pregnancy was weakly associated with an increased risk of caesarean delivery (p = 0.046) on univariate analysis but not on multivariate analysis, whereas it was associated with an increased risk of maternal ICU admission (p = 0.003), and prolonged hospital stay (p < 0.001) both before and after multivariate analysis.ConclusionThis study suggests that COVID‐19 infection during pregnancy is a risk factor for pre‐eclampsia. The study was unable to draw conclusions about more severe hypertensive conditions of pregnancy hemolysis, elevated liver enzymes and low platelet count; Eclampsia. COVID‐19 was determined to be a risk factor for prolonged hospital stay and maternal ICU admission, but there was no significant correlation between COVID‐19 and caesarean delivery on multivariate analysis.