bluuebunny/crossref_metadata_2025_split huggingface dataset:
Opportunities for narrative medicine in dental education and practice, a narrative review
Authors: Soni Mehar , Eidelman Alec Saul 
Published: October 2021

AbstractPurpose/objectivesReflection is one of four components of the experiential learning cycle and is often the one overlooked. This practice can be used in graduate‐level health care education, such as medicine and dentistry. This metacognitive practice allows students to conceptualize learning in a clinical setting and apply this knowledge to new scenarios. Reflective practice can be taught using different modalities of narrative medicine, and several studies have studied its effectiveness in areas such as professional development, collaboration, communication among others. Most of these studies, however, have been conducted solely in the medical setting, and narrative medicine may have useful application in the practice and teaching of dentistry.MethodsThis literature review examined the outcomes of narrative medicine in medical studies concerning reflection and hypothesized their benefits to dental education. The studies reviewed were chosen by utilizing key term searches of the National Center for Biotechnology Information PubMed library and qualitative factor analysis by study team investigators. Elective‐based, prospective enrollment and whole cohort participation programs were analyzed for potential effectiveness in dental education.ResultsThe most feasible programs for potential integration into dental curricula are elective‐based, small‐group, graduate‐level courses with a level of evaluation such as residency competencies, as demonstrated by Arntfield et al.Conclusion(s)These programs should be investigated further to evaluate their potential in improving reflective skills of students, and ultimately in improving their experiential learning experience.
Quantifying nonlinear temporal effects of ethanol preservation on round goby (Neogobius melanostomus) anatomical traits
Authors: Lorencen Bailey M. , Homola Jared J. , Robinson John D. , Scribner Kim T. 
Published: October 2021

AbstractGeometric morphometrics provides a powerful means of evaluating differences in phenotypic traits among specimens. However, inferences of trait variability can be confounded when measurements are based on preserved samples. We evaluated effects of ethanol preservation on morphology over a 22‐week time period for a Laurentian Great Lakes invasive fish, round goby (Neogobius melanostomus, Pallas 1814), using sets of 17 lateral and six dorsal landmarks. We tested whether ethanol preservation affected the magnitude of inter‐population variation between individuals collected from lake and river habitats. Generalized least square regression determined that length did not significantly vary through the preservation time series for fish from either population, while mass decreased significantly. Body shape variation was summarized using principal component analysis, which revealed that most preservation‐associated changes occurred in the first 14 days. The lateral shape experienced a large magnitude change during the first 24 h in ethanol then only minor changes for the remainder of the study. The dorsal shape began to revert to pre‐preservation measurements about 14 days following preservation. Additionally, differences in shape were apparent between the two populations throughout the experiment; however, the magnitude of differences between populations varied depending on whether dorsal or lateral landmarks were considered. Our study demonstrates that tissue responses to ethanol preservation can be more complex than a simple loss of mass, resulting in difficult to predict consequences for geometric morphometric analyses, including variable responses depending on the anatomical region being analyzed.
Intra‐abdominal lymph node flaps in lymphedema therapy: An anatomical guide to donor site selection
Authors: Daniel Bassem W. , Sonnenberg Anna M. , Stern Josef E. , Tannapfel Andrea , Yamamoto Takumi , Ring Andrej 
Published: October 2021

AbstractBackgroundSecondary lymphedema is a leading sequela of cancer surgery and radiotherapy. The microsurgical transfer of lymph node flaps (LNFs) to affected limbs can improve the symptoms. The intra‐abdominal cavity contains an abundant heterogenic source. The aim of this study is to aid selection among intra‐abdominal LNFs.MethodsEight LNFs were harvested in a microsurgical fashion at five sites in 16 cadavers: gastroepiploic, jejunal, ileal, ileocolic, and appendicular. These flaps were compared regarding size, weight, arterial diameter, and lymph node (LN) count after histologic verification.ResultsOne hundred and sixteen flaps were harvested. The exposed area correlated with the flap weight and volume (r2 = 0.86, r = 0.9). While gastroepiploic LNFs (geLNFs) showed the highest median weight of 99 ml, the jejunal LNFs (jLNFs) had the highest density with 3.8 LNs per 10 ml. The most reliable jLNF was 60 cm from the ligament of Treitz. Three or more LNs were contained in 94% of the jejunal, 88% of the ileal/ileocolic, and 63% of the omental LNs. The ileocolic LNF had the largest arterial diameter of 3 mm, yet the smallest volume.ConclusionsjLNF and ileal LNF provide a reliable, high LN density for simultaneous, smaller recipient sites. geLNFs are more suitable for larger recipient sites.
Electromagnetic Interference Shielding Foams Based on Poly(vinylidene fluoride)/Carbon Nanotubes Composite
Authors: Dun Dongxing , Luo Jingyun , Wang Minghao , Wang Xingran , Zhou Hongfu , Wang Xiangdong , Wen Bianying , Zhang Yuxia 
Published: October 2021

AbstractPolymeric electromagnetic interference (EMI) shielding foaming materials are found and applied in many frontier fields such as aerospace, transportation, and portable electronics. In this paper, a foam based on a composite system of poly(vinylidene fluoride) (PVDF) filled with carbon nanotubes (CNTs) is prepared for EMI shielding properties by using a solid‐state supercritical CO2 foaming strategy. PVDF is chosen as the matrix because of its excellent chemical resistance, thermal stability, and flame retardancy. The inclusion of CNTs renders this composite system enhanced complex viscosity and storage modulus by about two orders of magnitude. The electrical conductivity and EMI specific shielding effectiveness of obtained foams can be adjusted and reached the optimum value of 0.024 S m−1 and 29.1 dB cm3 g−1, respectively, originating from the gradual development of interconnected CNTs and conductive CNTs network as well as the introduction of cell structure in PVDF matrix. Interestingly, the reorientation of CNTs caused by foaming process results in electrical conductivity percolation threshold of PVDF/CNTs foams markedly decreases, in comparison to their unfoamed samples. This study provides a facile, efficient, green, and economic route for the preparation of EMI shielding foams consisted of fluorinated polymers and carbonaceous fillers.
Rational Design of Polycationic Hydrogel with Excellent Combination Functions for Flexible Wearable Electronic Devices
Authors: Liu Xiaoqing , Huang Peng , Wang Jinqing , Wang Xiangyuan , He Yufeng , Song Pengfei , Wang Rongmin 
Published: October 2021

AbstractWith the popularization of intelligent terminals and the improvement of medical level, the development of flexible wearable electronic devices (FWEDs) with high sensitivity and excellent mechanical properties plays a vital role in human motion and health monitoring. But most of FWEDs still stuck in a difficult choice of mechanical, functional, and sensory properties. In this work, it is found a strategy for extricating such plight. Using zwitterionic and quaternary ammonium salt, a novel polycationic hydrogel [P(ImSL‐AmC)] with excellent performance is synthesized by copolymerization under photoinitiation. After optimizing conditions of synthesis, its structure and properties are characterized. It is found that the electrostatic interaction enhances the mechanical applicability of P(ImSL‐AmC), which combines high stretchability (≈500% strain) with perfect strength (≈900 kPa) successfully. It is exciting that P(ImSL‐AmC) not only exhibits excellent antibacterial activities against both E. coli and S. aureus, but also maintains transparency and flexibility at −10 °C. This polycationic hydrogel also has superior conductivity as a stretchable pressure‐strain sensor, which can accurately monitor human motion. In summary, the obtained polycationic hydrogel possesses excellent combination functions, including intelligent conductivity, mechanical adaptability, antibacterial, frost resistance, and transparency. Furthermore, the practical strategy can be applied in preparation of intelligent wearable devices and human–computer interaction.
Automated segmentation of lung, liver, and liver tumors from Tc‐99m MAA SPECT/CT images for Y‐90 radioembolization using convolutional neural networks
Authors: Chaichana Anucha , Frey Eric C. , Teyateeti Ajalaya , Rhoongsittichai Kijja , Tocharoenchai Chiraporn , Pusuwan Pawana , Jangpatarapongsa Kulachart 
Published: October 2021

AbstractPurpose90Y selective internal radiation therapy (SIRT) has become a safe and effective treatment option for liver cancer. However, segmentation of target and organ‐at‐risks is labor‐intensive and time‐consuming in 90Y SIRT planning. In this study, we developed a convolutional neural network (CNN)‐based method for automated lungs, liver, and tumor segmentation on 99mTc‐MAA SPECT/CT images for 90Y SIRT planning.Methods99mTc‐MAA SPECT/CT images and corresponding clinical segmentations were retrospectively collected from 56 patients who underwent 90Y SIRT. The collected data were used to train three CNN‐based segmentation algorithms for lungs, liver, and tumor segmentation. Segmentation performance was evaluated using the Dice similarity coefficient (DSC), surface DSC, and average symmetric surface distance (ASSD). Dosimetric parameters (volume, counts, and lung shunt fraction) were measured from the segmentation results and were compared with clinical reference segmentations.ResultsThe evaluation results show that the method can accurately segment lungs, liver, and tumor with median [interquartile range] DSCs of 0.98 [0.97–0.98], 0.91 [0.83–0.93], and 0.85 [0.71–0.88]; surface DSCs of 0.99 [0.97–0.99], 0.86 [0.77–0.93], and 0.85 [0.62–0.93], and ASSDs of 0.91 [0.69–1.5], 4.8 [2.6‐8.4], and 4.7 [3.5–9.2] mm, respectively. Dosimetric parameters from the three segmentation networks show relationship with those from the reference segmentations. The overall segmentation took about 1 min per patient on an NVIDIA RTX‐2080Ti GPU.ConclusionThis work presents CNN‐based algorithms to segment lungs, liver, and tumor from 99mTc‐MAA SPECT/CT images. The results demonstrated the potential of the proposed CNN‐based segmentation method for assisting 90Y SIRT planning while drastically reducing operator time.
Exploring a new paradigm for the fetal anomaly ultrasound scan: Artificial intelligence in real time
Authors: Matthew Jacqueline , Skelton Emily , Day Thomas G. , Zimmer Veronika A. , Gomez Alberto , Wheeler Gavin , Toussaint Nicolas , Liu Tianrui , Budd Samuel , Lloyd Karen , Wright Robert , Deng Shujie , Ghavami Nooshin , Sinclair Matthew , Meng Qingjie , Kainz Bernhard , Schnabel Julia A. , Rueckert Daniel , Razavi Reza , Simpson John , Hajnal Jo 
Published: October 2021

AbstractObjectiveAdvances in artificial intelligence (AI) have demonstrated potential to improve medical diagnosis. We piloted the end‐to‐end automation of the mid‐trimester screening ultrasound scan using AI‐enabled tools.MethodsA prospective method comparison study was conducted. Participants had both standard and AI‐assisted US scans performed. The AI tools automated image acquisition, biometric measurement, and report production. A feedback survey captured the sonographers' perceptions of scanning.ResultsTwenty‐three subjects were studied. The average time saving per scan was 7.62 min (34.7%) with the AI‐assisted method (p < 0.0001). There was no difference in reporting time. There were no clinically significant differences in biometric measurements between the two methods. The AI tools saved a satisfactory view in 93% of the cases (four core views only), and 73% for the full 13 views, compared to 98% for both using the manual scan. Survey responses suggest that the AI tools helped sonographers to concentrate on image interpretation by removing disruptive tasks.ConclusionSeparating freehand scanning from image capture and measurement resulted in a faster scan and altered workflow. Removing repetitive tasks may allow more attention to be directed identifying fetal malformation. Further work is required to improve the image plane detection algorithm for use in real time.
Advanced photoluminescence imaging using non‐uniform excitation
Authors: Nie Shuai , Zhu Yan , Kunz Oliver , Trupke Thorsten , Hameiri Ziv 
Published: October 2021

AbstractPhotoluminescence (PL) imaging is a powerful inspection technique for research laboratories and photovoltaic production lines. Common PL imaging systems have two limitations: (a) due to the non‐uniformities of the measured samples, the acquired images are affected by lateral carrier flow, resulting in inaccurate lifetime analysis and image blurring; (b) samples' non‐uniformities are measured at locally different injection levels. In this paper, we present a PL imaging system that is not affected by these effects. By adaptively adjusting the light intensity at each pixel, we achieve a uniform excess carrier density across the sample, thereby eliminating any lateral currents. The non‐uniformity of the minority carrier lifetime can then be extracted from the spatial inverse of the illumination intensity. The advantages of the proposed system are demonstrated using silicon wafers with and without a diffusion layer that contain non‐uniform defects. This approach presents a significant improvement in accuracy and sharpness compared to conventional PL imaging techniques and, therefore, is expected to be beneficial for any quantitative PL‐based analysis.
Living ring‐opening metathesis polymerization of norbornenes bay‐functionalized perylene diimides
Authors: Podiyanachari Santhosh Kumar , Barłóg Maciej , Comí Marc , Attar Salahuddin , Al‐Meer Saeed , Al‐Hashimi Mohammed , Bazzi Hassan S. 
Published: October 2021

AbstractRing‐opening metathesis polymerization (ROMP)‐derived poly(oxanorbornene imide)s bearing bay‐linked mono‐alkoxy‐M1 and 1,7‐di‐alkoxy M2 functionalized perylene diimides (PDIs) were synthesized using Grubb's third (G3) and Hoveyda‐Grubbs second generation (HG2) ruthenium‐alkylidene metathesis initiators. The mono‐alkoxy‐derived PDI‐based non‐ladderphane polymer polyM1 displayed 67% to 77% of the trans olefin content in the polymer chain depending on the initiator used for the polymerization. When using the symmetrical 1,7‐di‐alkoxy‐derived PDI‐based polymer polyM2 having the ladderphane type‐structure, this displayed a significant amount of cis and trans olefin contents in the polymer chains, irrespective of the type of initiators used for the polymerization. ROMP of both monomers M1 and M2 proceeded in a well‐controlled manner with a linear dependence of molecular weight on the monomer/initiator ratio using G3 as initiator. Optical properties of the ladderphane‐based polyM2 and non‐ladderphane‐based polyM1 were characterized in both solution and the film state. X‐ray diffraction (XRD) analysis for all the polymers showed significant π‐stacking in the thin film state with ordered molecular packing and closer values of d‐spacing for both polyM1 and polyM2. Film morphology examined by AFM elucidated homogenous smooth polymer surface for both polymers in general, but with some irregularities observed for polyM1. In addition, CV analysis revealed both polymers could be good candidates as electron‐accepting materials, with excellent film‐forming ability, and thermal stability.
Successful whole lung lavage in a child with pulmonary alveolar proteinosis secondary to hematologic malignancy
Authors: Tsukahara Katharine , Lindell Robert B. , Newman Haley , Lerman Benjamin J. , Kersun Leslie S. , Piccione Joseph 
Published: October 2021

AbstractPulmonary alveolar proteinosis (PAP) describes the accumulation of surfactant in the alveolar space. Secondary PAP has been reported in a variety of diseases, and in rare cases has been associated with hematologic malignancy. Treatment for PAP is based on the underlying disease process, and may include whole lung lavage, inhaled or subcutaneous granulocyte‐macrophage colony‐stimulating factor, or statins. PAP secondary to hematologic malignancy has been reported to demonstrate poor response to whole lung lavage. We report a case of successful treatment of a pediatric patient with acute myeloid leukemia and secondary PAP using whole lung lavage.
Towards a typology of childhood internal mobility: Do children of migrants and non‐migrants differ?
Authors: Kuyvenhoven Joeke , Das Marjolijn , de Valk Helga A. G. 
Published: October 2021

AbstractMoving during childhood is an important life event that is often stressful and potentially disruptive. With the majority of existing studies on childhood internal mobility using a one‐dimensional measure of mobility and focusing on the total population, there is still limited knowledge on differential childhood mobility patterns for children of different migrant origins. In this study, we acknowledge the multidimensional nature of mobility by covering frequency, timing, distance, and change in place type to understand internal mobility patterns for children aged 0–16 without and with different second‐generation migrant backgrounds. Internal mobility is analysed for children born in the Netherlands between 1995 and 2003 using longitudinal full population register data. K‐means cluster analysis reveals five types of mobility: nearby preschool‐aged, nearby school‐aged, long‐distance to more densely populated areas, long‐distance to less densely populated areas, and frequent movers. Results of multinomial logistic regressions show that having a second‐generation migrant background increases the likelihood of being in any of the mobility clusters and reveals variation in types of mobility patterns for different migrant origin groups. We conclude that childhood mobility patterns are diverse and overall more often experienced by children of second‐generation migrant origin potentially adding to a more vulnerable situation and inequality over the life course.
Ensemble Kalman filtering with coloured observation noise
Authors: Raboudi Naila F. , Ait‐El‐Fquih Boujemaa , Ombao Hernando , Hoteit Ibrahim 
Published: October 2021

AbstractThe Kalman filter (KF) is derived under the assumption of time‐independent (white) observation noise. Although this assumption can be reasonable in many ocean and atmospheric applications, the recent increase in sensor coverage, such as the launching of new constellations of satellites with global spatio‐temporal coverage, will provide high density of oceanic and atmospheric observations which are expected to have time‐dependent (coloured) error statistics. In this situation, the KF update has been shown to generally provide overconfident probability estimates, which may degrade the filter performance. Different KF‐based schemes accounting for time‐correlated observation noise were proposed for small systems by modelling the coloured noise as a first‐order autoregressive model driven by white Gaussian noise. This work introduces new ensemble Kalman filters (EnKFs) which account for coloured observational noises for efficient data assimilation into large‐scale oceanic and atmospheric applications. More specifically, we follow the standard and the one‐step‐ahead smoothing formulations of the Bayesian filtering problem with coloured observational noise, modelled as an autoregressive model, to derive two (deterministic) EnKFs. We demonstrate the relevance of the coloured observational noise‐aware EnKFs and analyze their performances through extensive numerical experiments conducted with the Lorenz‐96 model.
Hair cortisol, perceived stress, and resilience as predictors of coronary arterial disease
Authors: Bergquist Sharon H. , Wang Danyang , Roberts David L. , Moore Miranda A. 
Published: October 2021

AbstractThe widespread prevalence of cardiovascular disease underscores the continuing need for identifying modifiable risk factors and novel targets for therapeutic intervention. Hair cortisol concentration (HCC) is a promising biomarker for evaluating the contribution of chronic stress to the pathogenesis and prognosis of coronary arterial disease (CAD). In this cross‐sectional study of 24 participants, we assessed the risk of CAD associated with HCC and with perceived chronic stress (Perceived Stress Score), controlling for the established risk factors of age, diabetes, hypertension, dyslipidemia, and obesity. In fully adjusted Poisson regression models, we additionally evaluated CAD risk with the simultaneous inclusion of psychological and physiologic resilience measures (CD‐RISC, DHEA‐S). Our results show that HCC, but not PSS, is significantly associated with CAD (incident rate ratio 0.99, confidence interval 0.98–1.00, p = 0.01), but the magnitude of the association is weak and inverse, and less than with dyslipidemia and age. The association remained significant after inclusion of the sum of resilience measures via a combined resiliency score. Resilience was not independently significantly associated with CAD. Our findings indicate the contribution of HCC to CAD risk is small in an average‐risk population and remains after adjustment for multisystem resilience.
Predicting future amyloid biomarkers in dementia patients with machine learning to improve clinical trial patient selection
Authors: Reith Fabian H. , Mormino Elizabeth C. , Zaharchuk Greg 
Published: October 2021

AbstractIntroductionIn Alzheimer's disease, asymptomatic patients may have amyloid deposition, but predicting their progression rate remains a substantial challenge with implications for clinical trial enrollment. Here, we demonstrate an artificial intelligence approach to use baseline clinical information and images to predict changes in quantitative biomarkers of brain pathology on future images.MethodsPatients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who underwent positron emission tomography (PET) with the amyloid radiotracer 18F‐AV45 (florbetapir) were included. We identified important baseline PET image features using a deep convolutional neural network based on ResNet. These were combined with eight clinical, demographic, and genetic markers using a gradient‐boosted decision tree (GBDT) algorithm to predict future quantitative standardized uptake value ratio (SUVR), an established biomarker of brain amyloid deposition. We used this model to better identify individuals with the highest positive change in amyloid deposition on future images and compared this to typical inclusion criteria for clinical trials. We also compared the model's performance to other methods such as multivariate linear regression and GBDT without imaging features.FindingsUsing 2577 PET scans from 1224 unique individuals, we showed that the GBDT with deep image features was significantly more accurate than the other approaches, reaching a root mean squared error of 0.0339 ± 0.0027 for future SUVR prediction. Using this approach, we could identify individuals with the highest 10% SUVR accumulation at rates 2‐ to 4‐fold higher than by random pick or existing inclusion criteria.DiscussionPredicting quantitative biomarkers on future images using machine learning methods consisting of deep image features combined with clinical data may allow better targeting of treatments or enrollment in clinical trials.