bluuebunny/crossref_metadata_2025_split huggingface dataset:
A patient-specific deep learning framework for 3D motion estimation and volumetric imaging during lung cancer radiotherapy
Authors: Hindley Nicholas , Shieh Chun-Chien , Keall Paul 
Published: June 2023

Abstract

Objective. Respiration introduces a constant source of irregular motion that poses a significant challenge for the precise irradiation of thoracic and abdominal cancers. Current real-time motion management strategies require dedicated systems that are not available in most radiotherapy centers. We sought to develop a system that estimates and visualises the impact of respiratory motion in 3D given the 2D images acquired on a standard linear accelerator. Approach. In this paper we introduce Voxelmap, a patient-specific deep learning framework that achieves 3D motion estimation and volumetric imaging using the data and resources available in standard clinical settings. Here we perform a simulation study of this framework using imaging data from two lung cancer patients. Main results. Using 2D images as input and 3D–3D Elastix registrations as ground-truth, Voxelmap was able to continuously predict 3D tumor motion with mean errors of 0.1 ± 0.5, −0.6 ± 0.8, and 0.0 ± 0.2 mm along the left–right, superior–inferior, and anterior–posterior axes respectively. Voxelmap also predicted 3D thoracoabdominal motion with mean errors of −0.1 ± 0.3, −0.1 ± 0.6, and −0.2 ± 0.2 mm respectively. Moreover, volumetric imaging was achieved with mean average error 0.0003, root-mean-squared error 0.0007, structural similarity 1.0 and peak-signal-to-noise ratio 65.8. Significance. The results of this study demonstrate the possibility of achieving 3D motion estimation and volumetric imaging during lung cancer treatments on a standard linear accelerator.
A simulation study of 1D U-Net-based inter-crystal scatter event recovery of PET detectors
Authors: Zou Jiaxuan , Ye Jianbo , Yu Jintao , Cui Ke 
Published: June 2023

Abstract
To achieve high spatial resolution of reconstructed images in positron emission tomography (PET), the size of the scintillation crystal element is set small in current PET systems, which greatly increases the inter-crystal scattering (ICS) frequency. The ICS is a type of Compton scattering of the gamma photons from one crystal element to its neighborhood element, which obscures the determination of the first interaction position. In this study, we propose a 1D U-Net convolutional neural network to predict the first interaction position, which provides a universal way to efficiently solve the ICS recovery problem. The network is trained using the dataset collected from the GATE Monte Carlo simulation. The 1D U-Net structure is applied due to its capability of synthesizing both low-level and high-level information, which shows superiority in solving the ICS recovery problem. After being well trained, the 1D U-Net can generate a prediction accuracy of 78.1%. Compared to the coincidence events only composed from two photoelectric gamma photons, the sensitivity is improved by 149%. The contrast-to-noise ratio of the reconstructed contrast phantom increases from 6.973 to 10.795 for the 16 mm hot sphere. Compared to the take-energy-centroid method, the spatial resolution of the reconstructed resolution phantom can obtain the best improvement of 33.46%. Compared with the previous deep learning method based on the fully connected network, the proposed 1D U-Net can work more stably with considerably fewer network parameters. The 1D U-Net network model shows good universality when predicting different phantoms, and the computation speed is fast.
Energy harvesting using ferroelectric/ferroelastic switching: the effect of pre-poling
Authors: Kang Wenbin , Cain Cameron , Wang Fan , Huber John E 
Published: June 2023

Abstract
Improved power output and energy density have been achieved in piezoelectric transducers by exploiting ferroelectric/ferroelastic switching. However, a problem is that stable working cycles with polarization switching normally cannot be driven by stress alone. This problem has been addressed by using internal bias fields in a partially poled ferroelectric: the material state is engineered such that compressive stress drives ferroelastic switching during mechanical loading, while residual fields restore the polarized state during unloading. However, although this method has been verified, the devices in engineering material states with the best performance have not been explored systematically. In this work, internal bias fields in a partially poled (pre-poled) ferroelectric are used to guide polarization switching, producing an effective energy harvesting cycle. Devices are tested and optimized in the frequency range 1–20 Hz, and the influence of the degree of pre-poling in the fabrication process on energy harvesting performance is explored systematically. It is found that pre-poling the ferroelectric ceramic to about 25% of the fully poled state results in a device that can generate a power density up to about 26 mW cm−3 of active material at 20 Hz, an improvement on prior work and an order of magnitude advance over conventional piezoelectrics. However, maximizing the power density can result in residual stresses that risk damage to the device during preparation or in service. The relationship between fabrication success rate and pre-poling level is studied, indicating that greater degrees of pre-poling correlate with higher survival rate. This provides a basis for balancing energy conversion with device robustness.
Magnetic-driven 3D-printed biodegradable swimming microrobots
Authors: Chen Jingfan , Hu Hanwen , Wang Ya 
Published: June 2023

Abstract
A magnetic object subject to an external rotating magnetic field would be rotated due to the alignment tendency between its internal magnetization and the field. Based on this principle, 12 shapes of swimming microrobots around 1 mm long were designed and 3D-printed using biodegradable materials Poly (ethylene glycol) diacrylate (PEDGA). Their surface was decorated with superparamagnetic iron oxide nanoparticles to provide magnetic responsivity. An array of 12 permanent magnets generated a rotating uniform magnetic field (∼100 mT) to impose magnetic torque, which induces a tumbling motion in the microrobot. We developed a dynamic model that captured the behavior of swimming microrobots of different shapes and showed good agreement with experimental results. Among these 12 shapes, we found that microrobots with equal length, width, and depth performed better. The observed translational speed of the hollow cube microrobot can exceed 17.84 mm s−1 (17.84 body lengths/s) under a rotating magnetic field of 5.26 Hz. These microrobots could swim to the targeted sites in a simplified vessel branch. And a finite element model was created to simulate the motion of the swimming microrobot under a flow rate of 0.062 m s−1.
Fractional order interdependent nonlinear chaotic spatiotemporal calcium and Aβ dynamics in a neuron cell
Authors: Pawar Anand , Pardasani Kamal Raj 
Published: June 2023

Abstract
The formation of β-amyloid (Aβ) and its accumulation depend on the calcium ([Ca2+]) signaling in neurons. The individual and independent dynamics of calcium and β-amyloid give very limited information about different cellular mechanisms. Some researchers have explored the interdependent system dynamics of integer-order calcium and β-amyloid, which provides some more crucial information on different regulatory and dysregulatory processes in neurons. However, these integer-order systems are not capable of generating the information on the superdiffusion, cell memory and Brownian motion effects in neuron cells. A nonlinear mathematical model has been framed to explore the fractional-order interdependent chaotic spatiotemporal [Ca2+] and Aβ dynamics in neurons. The proposed model integrates the two-way feedback mechanism between [Ca2+] and Aβ dynamics in neurons. The Crank-Nicolson scheme with the Grunwald approximation is employed for space fractional derivatives and the L1 formula is employed for time fractional derivatives. The Gauss-Seidel iterations are utilized to solve the resultant system of nonlinear algebraic equations. The effects of cell memory, Brownian motion and superdiffusion phenomena with different crucial mechanisms like buffer, source influx, ryanodine receptor, etc on the spatiotemporal interdependent [Ca2+] and Aβ dynamics have been explored in neurons. The numerical findings give novel insights on the regulatory and dysregulatory effects of cell memory, Brownian motion and superdiffusion on the system dynamics of [Ca2+] and Aβ in neuron cells and the conditions that may cause the different neurodegenerative illnesses like Alzheimer’s disease.
001 Does atopic dermatitis in childhood impact later educational attainment? A UK birth cohort study
Authors: Iskandar Rita , Schmidt Sigrún , Mulick Amy , Abuabara Katrina , Langan Sinéad 
Published: June 2023

Abstract
Atopic dermatitis (AD) may impair educational attainment in numerous ways, including poor attention due to itching and disrupted sleep quality. Educational attainment is a social determinant of health; thus, any association with AD, a prevalent chronic disease, is important to understand. We aimed to determine whether AD is associated with lower educational attainment using data collected between 1990 and 2009 on children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) and linked to the National Pupil Database. Participants were 13,956 children alive at 1 year of age and followed up with repeated measures of AD until 11.5 years of age. The outcome was educational attainment, defined as achieving at least five General Certificates of Secondary Education (GCSEs) at grades A*–C by 16 years of age. Using multivariable logistic regression, we assessed the effect of AD on educational attainment, adjusting for potential confounders. We included 7577 children in a complete record analysis: 3258 (43.0%) with evidence of AD (two positive AD reports) and 4319 (57.0%) without AD reports (comparator group). Compared with children without AD, children with AD had 30% increased odds of attaining ≥ 5 A*–C GCSEs [adjusted odds ratio (aOR) 1.30, 95% confidence interval (CI) 1.17–1.45]. Children with AD had a 9.9% absolute excess probability of achieving ≥ 5 A*–C GCSEs vs. children without AD. In a stratified analysis, asthma was shown to enhance the strength of the association of AD with educational attainment [probability in AD vs. no AD groups: 62.7% vs. 47.3%; aOR 1.58, 95% CI 1.19–2.10 (P = 0.04 for interaction)]. AD appeared to be associated with higher educational attainment in English children. Despite the magnitude and strength of the findings, cautious interpretation is required due to the dichotomous outcome measure, poor generalizability and potential unmeasured confounding. Further investigations should evaluate reproducibility in other populations, stratify by AD trajectory–severity phenotypes and use quantitative test scores.
004 Does methotrexate affect treatment persistence or effectiveness of adalimumab for psoriasis? A trial emulation cohort study
Authors: Yiu Zenas , Smith Catherine , Laws Philip , Hampton Philip , Griffiths Christopher , Warren Richard 
Published: June 2023

Abstract
It is unclear whether concomitant methotrexate enhances the effectiveness and/or persistence of adalimumab in treating psoriasis. The OPTIMAP study (Optimizing Adalimumab Treatment in Psoriasis with Concomitant Methotrexate), a randomized controlled trial testing adalimumab against adalimumab + methotrexate, could not adequately answer this question due to under-recruitment. The aim of the current study is to replicate key aspects of the OPTIMAP trial design in a cohort study to provide a more precise estimate for the effect of concomitant methotrexate on adalimumab persistence and effectiveness. We conducted a cohort study using the British Association of Dermatologists Biologics and Immunomodulators Register, a national pharmacovigilance registry for people on systemic treatments for psoriasis, between 2007 and 2021. We included participants ≥ 18 years old who had at least one record of a Psoriasis Area and Severity Index (PASI) ≥ 8 and were naïve to adalimumab. We used the same exclusion criteria as in the OPTIMAP study. Participants received either adalimumab (Humira®) in the comparison arm or adalimumab (Humira) in addition to methotrexate and folic acid, with dosage as determined by the clinician in the intervention arm from initiation at cohort entry, and were censored if they deviated from the treatment strategy. The primary outcome is in the difference in the survival function for adalimumab at 1 year. The secondary outcome was the difference in the proportion of patients achieving a 75% reduction in PASI (PASI 75) at 1 year. We used inverse probability treatment weighting to correct for known differences in participant characteristics precomparison. Missing outcomes were accounted for using inverse probability of censoring weighting. We fitted a flexible parametric survival model and a generalized linear model with an identity link for the primary and secondary outcomes, respectively. There were 219 and 1376 participants in the intervention and comparison arms, respectively. Drug survival for the monotherapy arm at 1 year was 77.5% [95% confidence interval (CI) 75.3–79.8], and for the intervention arm, it was 75.3% (95% CI 66.9–84.7), with a difference of −2.3% (95% CI −11.4 to 6.9). The risk difference for PASI 75 at 1 year was −10.7% (95% CI −29.3 to 8.0), with a PASI 75 rate of 43.5% for the intervention arm (95% CI 25.4–61.9) and 54.2% for the comparison arm (95% CI 49.6–58.7). We did not find any significant difference for the persistence and effectiveness of adalimumab in people with psoriasis on methotrexate vs. those who were not on methotrexate in this study. This result is in keeping with the reported first-year outcomes of OPTIMAP. Clinicians and patients should consider alternative strategies to improve treatment outcomes in people with severe psoriasis.
007 Vitiligo is associated with a reduction in incidence of melanoma and nonmelanoma skin cancer: UK population-based cohort study
Authors: Ferguson John , Eleftheriadou Viktoria , Nesnas John 
Published: June 2023

Abstract
Vitiligo is a common, acquired depigmenting skin disease. There have been concerns that vitiligo and its treatment may increase the risks of skin cancer. In a large UK population-based study, we aimed to establish whether vitiligo is associated with an increased risk of skin cancer. We used routinely collected electronic medical records of adults contributing to the Optimum Patient Care Research Database (2010–2020). Cases of vitiligo were identified using specific diagnosis codes. Those with other depigmenting conditions were excluded. Vitiligo cases were age and sex matched with up to four controls registered at the same general practice and with at least one primary care interaction in the preceding year. The primary outcome was risk of skin cancer; comprisied of melanoma, squamous cell carcinoma (SCC) and basal cell carcinoma (BCC). Individual skin cancers and actinic keratoses (AK) were included as secondary outcomes. Associations between vitiligo and skin cancer were estimated using Cox regression, with adjustment for age, sex, socioeconomic deprivation, ethnicity, body mass index, smoking and alcohol status, immunotherapy, phototherapy and 13 common comorbidities. Prespecified subgroup analysis comprised stratification by sex, age group (18–45 years, 45–65 years and &gt; 65 years), ethnicity (White and non-White) and socioeconomic deprivation. In total, 14 976 patients with vitiligo were matched to 54 392 controls. Over the 10-year study period, 133 patients with vitiligo and 783 controls developed new-onset skin cancer. Vitiligo was associated with a 38% reduced risk of any new-onset skin cancer [adjusted hazard ratio (aHR) 0.62, 95% confidence interval (CI) 0.51–0.74; P &lt; 0.001]. This risk reduction was observed for all individual skin cancer types: melanoma (aHR 0.38, 95% CI 0.23–0.64; P &lt; 0.001), SCC (aHR 0.65, 95% CI 0.48–0.87; P = 0.004), BCC (aHR 0.65, 95% CI 0.51–0.83; P &lt; 0.001) and AK (aHR 0.86, 95% CI 0.75–0.98; P = 0.028). In a subgroup analysis, vitiligo was associated with a reduction in skin cancer risk in people identifying as White (aHR 0.68, 95% CI 0.55–0.84; P &lt; 0.001), but there was no association in those identifying as non-White (aHR 0.93, 95% CI 0.44–1.98). Vitiligo-associated reductions in skin cancer risk were consistently observed in the other prespecified subgroups. Vitiligo is associated with a strong protective effect against common types of skin cancer. Vitiligo-associated risk reduction is most marked for melanoma (62% lower risk). Protective effects associated with vitiligo may be restricted to people with light skin, although skin cancers in the those with darker skin were uncommon, which requires further study.
FundingThis research was sponsored by Pfizer. Medical writing and statistical support was provided by Momentum Data and was funded by Pfizer.
010 Enhanced outcome prediction in cutaneous squamous cell carcinoma using deep-learning and computational histopathology (cSCCnet)
Authors: Peleva Emilia , Chen Yue , Rizvi Hasan , Harwood Catherine , Wang Jun 
Published: June 2023

Abstract
Cutaneous squamous cell carcinoma (cSCC) is a common skin cancer and leads to a significant disease burden. Although metastases occur in &lt; 5% of patients, effective treatments are limited and 5-year survival is poor, with mortality rates equivalent to those of melanoma in some regions of the world. Despite recent advances in understanding the molecular pathogenesis of cSCC, patient risk stratification is limited and based on clinicopathological staging, with few validated prognostic biomarkers available to guide management [de Jong E, Lammerts MUPA, Genders RE, Bowes Bavinck JN. Update of advanced cutaneous squamous cell carcinoma. J Eur Acad Dermatol Venereol 2022; 36(Suppl. 1):6–10]. In this study, we aimed to use artificial intelligence technology to develop a deep learning model using digitized whole-slide images of cSCC to quantify the risk of metastasis. Routine haematoxylin and eosin-stained slides of 256 primary cSCCs from immunocompetent patients at four collaborating centres were scanned. The area of interest encompassing tumour and peritumoral stroma was annotated, and 512 × 512 pixel tiles were generated from each slide. High-quality tiles (containing sufficient tumour content) were pooled together, with patient-level labels inherited by tiles. We trained multiple models using an 80:10:10 split for training, validation and testing, and the model achieving the highest tile- and slide-level validation accuracy was identified (ResNet50). The final model, namely, cSCCnet, achieved 88% sensitivity, 73% specificity, 64% positive predictive value and 92% negative predictive values on the independent test set. Blinded review of the top predictive tiles by three histopathologists suggested that the predictive features identified by cSCCnet were distinct from histopathological features commonly used by clinicians to estimate metastatic risk. We have demonstrated that it is possible to train a deep learning model using digital pathology to predict the risk of metastasis. cSCCnet surpassed the published performance of currently used staging systems, as well as commercially available gene panel testing (de Jong et al.; Wysong A, Newman JG, Covington KR et al. Validation of a 40-gene expression profile test to predict metastatic risk in localized high-risk cutaneous squamous cell carcinoma. J Am Acad Dermatol 2021; 84:361–9). The morphological features and patterns identified by cSCCnet are different from established histopathological high-risk criteria, indicating that this technology can enhance current practice. Although further validation in a prospective cohort is pending, this is an important step toward creating a risk stratification tool that can be incorporated into routine pathology workflows, significantly improving patient outcomes for this common cancer.
RF03 Lentigo maligna 2013–2019 in England: incidence and survival of 18,377 cases
Authors: Karponis Dimitrios , Mistry Khaylen , van Bodegraven Birgitta , Levell Nicholas J , Venables Zoe 
Published: June 2023

Abstract
Lentigo maligna (LM) is a common melanoma in situ with limited national epidemiological data. National data on LM incidence, age groups and 5-year survival in England from 2013 to 2019 were explored using report-level data published openly on the ‘Get Data Out’ National Disease Registration Service (NDRS) programme. In total, 18 377 new cases (49% male, 51% female) of LM were registered in England, with a mean of 2625 new diagnoses per year. The crude incidence rate of LM increased from 4.33/100 000 [95% confidence interval (CI) 4.16–4.51] in 2013 to 4.69/100 000 (95% CI 4.52–4.87) in 2019. The average crude incidence rate of LM per year was 23.4/100 000 [95% CI 22.7–24.9; 35.2 male (95% CI 33.2–37.4), 15.4 female (95% CI 15.2–17.5)] in those aged &gt; 80 years vs. 0.59/100 000 [95% CI 0.55–0.62; 0.65 male (95% CI 0.59–0.71), 0.53 female (95% CI 0.47–0.59)] in those aged &lt; 60 years. Overall, 5-year Kaplan–Meier survival was 83.1% (95% CI 81.5–84.6) for LM diagnosed in 2013, while 5-year overall net survival was 103.7% (95% CI 101.2–106.2) in 2014. By comparison, for invasive melanoma, 5-year overall Kaplan–Meier survival was 79.1% (95% CI 78.3–79.8) and 5-year overall net survival was 88.6% (95% CI 87.6–89.6) for 2013 diagnoses. Important limitations are that registered LM is based on histopathological data or multidisciplinary team discussions; hence, LM treated topically without biopsy or untreated LM were not included. Privately treated patients were also under-represented, as there was no requirement for private laboratory data to be submitted to NDRS, unlike data from National Health Service laboratories. The apparent 5-year LM-specific survival advantage is likely due to fewer frail patients seeking medical attention, being referred or undergoing histological confirmation. We report the largest series of data on LM in Europe to date. The observed increase in the incidence of LM and its excellent 5-year net survival supports further discussion on current clinical practice and treatment options.