bluuebunny/crossref_metadata_2025_split huggingface dataset:
Deep learning-based defacing tool for CT angiography: CTA-DEFACE
Authors: Mahmutoglu Mustafa Ahmed , Rastogi Aditya , Schell Marianne , Foltyn-Dumitru Martha , Baumgartner Michael , Maier-Hein Klaus Hermann , Deike-Hofmann Katerina , Radbruch Alexander , Bendszus Martin , Brugnara Gianluca , Vollmuth Philipp 
Published: October 2024

Abstract
The growing use of artificial neural network (ANN) tools for computed tomography angiography (CTA) data analysis underscores the necessity for elevated data protection measures. We aimed to establish an automated defacing pipeline for CTA data. In this retrospective study, CTA data from multi-institutional cohorts were utilized to annotate facemasks (n = 100) and train an ANN model, subsequently tested on an external institution’s dataset (n = 50) and compared to a publicly available defacing algorithm. Face detection (MTCNN) and verification (FaceNet) networks were applied to measure the similarity between the original and defaced CTA images. Dice similarity coefficient (DSC), face detection probability, and face similarity measures were calculated to evaluate model performance. The CTA-DEFACE model effectively segmented soft face tissue in CTA data achieving a DSC of 0.94 ± 0.02 (mean ± standard deviation) on the test set. Our model was benchmarked against a publicly available defacing algorithm. After applying face detection and verification networks, our model showed substantially reduced face detection probability (p < 0.001) and similarity to the original CTA image (p < 0.001). The CTA-DEFACE model enabled robust and precise defacing of CTA data. The trained network is publicly accessible at www.github.com/neuroAI-HD/CTA-DEFACE.

Relevance statement
The ANN model CTA-DEFACE, developed for automatic defacing of CT angiography images, achieves significantly lower face detection probabilities and greater dissimilarity from the original images compared to a publicly available model. The algorithm has been externally validated and is publicly accessible.

Key Points

The developed ANN model (CTA-DEFACE) automatically generates facemasks for CT angiography images.

CTA-DEFACE offers superior deidentification capabilities compared to a publicly available model.

By means of graphics processing unit optimization, our model ensures rapid processing of medical images.

Our model underwent external validation, underscoring its reliability for real-world application.

Graphical Abstract
Association between cannabis use and physical activity in the United States based on legalization and health status
Authors: Merrill Ray M. , Ashton-Hwang Kendyll , Gallegos Liliana 
Published: October 2024

Abstract
Background
Studies investigating the association between cannabis use and physical activity have had mixed results. This study provided a population-based assessment while determining how the relationship is affected by variables such as cannabis legalization status and chronic medical conditions.

Methods
Behavior Risk Factor Surveillance System (BRFSS) data were used to evaluate the association between cannabis use and physical activity among adults ages 18 years and older in several states and territories of the U.S. during 2016–2022. Adjusted odds ratios (ORs) measuring the relationship between physical activity in the past 30 days (yes vs. no) and cannabis use in the past 30 days (yes vs. no) based on legalization and health status were estimated using logistic regression.

Results
Physical activity increased from 73.16% in 2016 to 75.72% in 2022 (3.5% increase) and current cannabis use increased from 7.48% in 2016 to 14.71% in 2022 (96.7% increase). Current cannabis use was 6.5% higher in areas of legalized recreational cannabis (vs. not legal) and 0.7% higher in areas of legalized medical cannabis (vs. not legal). For the combined years, the OR measuring the association between cannabis use and physical activity was 1.24 (95% CI 1.10–1.41), after adjusting for age, sex, race/ethnicity, marital status, employment status, education, smoking status, weight classification, legal status, and chronic medical condition. The adjusted OR was 1.47 (95% CI 1.34–1.62) in areas with legalized recreational and medical cannabis (vs. illegal) and 1.05 (95% CI 0.98–1.12) in areas with legalized medical cannabis only (vs. illegal). Having a medical condition was significantly associated with lower prevalence of physical activity in the adjusted models (overall adjusted OR = 0.79, 95% CI 0.73–0.85). However, this significantly lower odds ratio was insignificant for current cannabis users.

Conclusions
Public policy and personal health behaviors may improve with the findings that legal medical cannabis promotes greater physical activity in those experiencing chronic medical conditions and legal recreational cannabis promotes (even more so) greater physical activity in those not experiencing chronic medical conditions.
Socioeconomic factors and COVID-19 mortality in immune-mediated rheumatic diseases patients: regional analysis from Argentina, Mexico and Brazil
Authors: Martinez-Martinez Marco Ulises , Isnardi Carolina Ayelen , Alpizar-Rodriguez Deshiré , Pons-Estel Guillermo Javier , Virasoro Belén María , Alfaro María Agustina , Petkovic Ingrid , Quintana Rosana , Berbotto Guillermo , Salinas María Jezabel Haye , Ornella Sofía , Pera Mariana , Colunga-Pedraza Iris Jazmín , Irazoque-Palazuelos Fedra , Reyes-Cordero Greta , Rodriguez-Reyna Tatiana S , Veloz-Aranda Jose Antonio , Skinner-Taylor Cassandra Michele , Juárez-Mora Ingrid Maribel , Silveira Luis H. , Marques Claudia Diniz Lopes , Xavier Ricardo Machado , Kakehasi Adriana Maria , Gomides Ana Paula , dos Reis-Neto Edgard Torres , Pileggi Gecilmara Salviato , Ferreira Gilda Aparecida , da Mota Licia Maria Henrique , Pinheiro Marcelo Medeiros , Calderaro Débora Cerqueira 
Published: October 2024

Abstract
Background
SARS-CoV-2 infection has become a major international issue, not only from a medical point of view, but also social, economic and political. Most of the available information comes from the United States, Europe, and China, where the population and the socioeconomic status are very different from Latin American countries. This study evaluates the effect of regional socioeconomic characteristics on mortality due SARS-CoV-2 infection in patients with immune-mediated rheumatic diseases (IMRD) from Argentina, Mexico and Brazil.

Methods
Data from three national registries, SAR-COVID (Argentina), CMR-COVID (Mexico) and ReumaCoV-Brasil (Brazil), were combined. Adult IMRD patients with SARS-CoV-2 infection were recruited. National data for each province/state, including population density, number of physicians per inhabitant, income, unemployment, GINI index, Municipal Human Development Index (MHDI), stringency index, vaccination rate and most frequent viral strains per period were assessed as risk factors for mortality due to COVID-19.

Results
A total of 4744 patients were included, 2534 (53.4%) from SAR-COVID, 1166 (24.6%) from CMRCOVID and 1044 (22.0%) from ReumaCoV-Brasil. Mortality due to COVID-19 was 5.4%. In the multivariable analysis, higher number of physicians per 1000 inhabitants and being infected during the vaccination period of each country were associated with lower mortality. After adjustment for socioeconomic factors, there was no association with country of residence and mortality.

Conclusion
These findings corroborate the complex interplay between socioeconomic factors, rheumatic disease activity, and regional disparities as determinants of death due to COVID-19 in Argentina, Brazil and Mexico. Thus, this research provides valuable insights for guiding public health policies and clinical practice in the ongoing fight against the COVID-19 pandemic.
Face and face pareidolia in patients with temporal lobe epilepsy indicates different neural processing: an event-related potential study
Authors: Akdeniz Gülsüm , Gumusyayla Sadiye , Vural Gonul , Deniz Orhan , Özışık Pınar 
Published: October 2024

Abstract
Background
Visual perception of face images or face pareidolia can be evaluated with event-related potentials (ERP) for healthy subjects and patients with neurological conditions. In this study, we aimed to analyse event-related potential components such as P100, N100, N170, and vertex-positive potential (VPP) in response to face pareidolia perception in temporal lobe epilepsy (TLE) patients.

Methods
ERPs were recorded during the pareidolia test. Waveforms were analzyed and current source density (CSD) maps were generated.

Results
CSD profiles were shown to be interpretable when face and face pareidolia conditions. N100, P100, and N170 components showed larger amplitudes and longer latency in epilepsy patients in response to face pareidolia stimuli compared to real face images. However, the N170 component latency did not differ significantly between epilepsy patients and healthy participants, while the larger amplitude and longer latency of N100 and P100 responses were evoked in healthy patients.

Conclusions
Our results indicate a difference in the neural mechanisms of processing real face information and pareidolia face-like information in TLE patients.
An Updated Systematic Review and Meta-Analysis of Unimodal Prehabilitation with Exercise Intervention to Enhance Postoperative Outcomes in Cancer Surgery
Authors: Steffens Daniel , Hancock Mark , Jiang Wilson , Solomon Michael , Koh Cherry , Hirst Nicholas , Riedel Bernhard 
Published: October 2024

BACKGROUND:
The objective of this systematic review and meta-analysis was to update the body of evidence on the efficacy of prehabilitation with exercise interventions, in reducing postoperative complications and length of hospital stay after cancer surgery.

METHODS:
A comprehensive literature search was conducted on MEDLINE, Embase, The Cochrane Library, CINAHL, AMED, and PsycINFO to identify randomized controlled trials investigating the impact of prehabilitation with exercise interventions for patients undergoing cancer surgery. Primary and secondary outcomes assessed were postoperative complications and length of hospital stay, respectively. Risk of bias was evaluated using the Cochrane risk of bias tool, and Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) methodology was used to determine the strength of evidence. Relative risk and mean difference were calculated using random-effects meta-analysis.

RESULTS:
In this updated review, 32 trials (n = 2304 participants) were identified, with 5 trials focused on patients undergoing surgery for genitourinary cancer (n = 422 participants), 9 for lower gastrointestinal cancer (n = 639 participants), 6 for upper gastrointestinal cancer (n = 526), and 11 for lung cancer (n = 717 participants). The majority of included trials exhibited some risk of bias. Evidence of low-to-moderate quality indicated that prehabilitation with preoperative exercise significantly reduced postoperative complication rates by approximately 50% and decreased the length of hospital stay by 2.5 days in patients undergoing lung resection. Preoperative exercise did not demonstrate effectiveness in reducing postoperative complications or length of hospital stay for other cancer populations.

CONCLUSIONS:
Evidence supports the efficacy of prehabilitation with exercise in reducing postoperative complications and length of hospital stay in patients undergoing lung cancer surgery. Further research is warranted to establish the efficacy of unimodal prehabilitation with exercise in genitourinary, lower gastrointestinal, and upper gastrointestinal cancer populations having cancer surgery.
Identification and Verification of Key Genes in Colorectal Cancer Liver Metastases Through Analysis of Single-Cell Sequencing Data and TCGA Data
Authors: Zhang Hui , Zhuo Changhua , Lin Ruirong , Ke Fayong , Wang Ming , Yang Chunkang 
Published: October 2024

Abstract
Background
Colorectal cancer (CRC) is highly prevalent worldwide, with more patients experiencing colorectal cancer liver metastases (CRLM). This study aimed to identify key genes in CRLM through single-cell sequencing data reanalysis and experimental validation.

Methods
The study analyzed single-cell RNA-sequencing (scRNA-seq) data from the Gene Expression Omnibus (GEO) database. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for gene functional enrichment analysis. The Cancer Genome Atlas (TCGA) data enabled bulk-RNA expression and survival prognosis analysis. Real-time polymerase chain reaction (qPCR) detected mRNA expression, whereas Western blot determined protein levels. Cell function experiments assessed SPARC’s impact on CRC cell behavior.

Results
Cluster analysis showed 23 classes among 17 CRLM samples, representing six cell types. A GO and KEGG analysis identified interleukin-1 beta (IL1B), CD2 molecule (CD2), and C-X-C motif chemokine ligand 8 (CXCL8) as significant prognostic factors in CRC. Secreted protein acidic and cysteine rich (SPARC) was one of the top differentially expressed genes (DEGs) in tissue stem cells, confirmed in primary and metastatic lesions. Metastatic lesions showed higher expression of SPARC and CRC stem cell marker leucine-rich repeat containing G protein-coupled receptor 5 (LGR5), which was significantly correlated positively with LGR5 expression. Knockdown of SPARC reduced CRC cell sphere- and colony-formation, invasion, and migration abilities. Overexpression of SPARC significantly increased the malignancy of CRC cells.

Conclusions
Several key genes were identified in the process of CRLM. In CRLM samples and those corresponding to CRC stem cells, SPARC was significantly upregulated. In the therapy of CRLM, SPARC might be a potential target.
The RETurn to work After stroKE (RETAKE) trial: Findings from a mixed-methods process evaluation of the Early Stroke Specialist Vocational Rehabilitation (ESSVR) intervention
Authors: Clarke David James , Powers Katie , Trusson Diane , Craven Kristelle , Phillips Julie , Holmes Jain , McKevitt Christopher , Bowen Audrey , Watkins Caroline Leigh , Farrin Amanda J. , Wright-Hughes Alexandra , Sach Tracey , Chambers Rachel , Radford Kate 
Published: October 2024

Introduction
A key goal for working age stroke survivors is to return to work, yet only around 50% achieve this at 12 months. Currently, there is limited evidence of effectiveness of early stroke-specialist vocational rehabilitation (ESSVR) interventions from randomised controlled trials. This study examined fidelity to ESSVR and explored social and structural factors which may have influenced implementation in the RETurn to work After stroKE (RETAKE) randomised controlled trial.

Methods
Mixed-methods process evaluation assessing intervention fidelity and incorporating longitudinal case-studies exploring stroke survivors’ experiences of support to return to work. Normalisation Process Theory, and the Conceptual Model for Implementation Fidelity, informed data collection and analysis.

Results
Sixteen sites across England and Wales participated in RETAKE. Forty-eight occupational therapists (OTs), supported by 6 mentors experienced in vocational rehabilitation (VR), delivered the intervention (duration 12 months) between February 2018 and April 2022. Twenty-six participants (15 ESSVR, 11 usual care (UC)) were included in longitudinal case-studies. An additional 18 participants (8 ESSVR and 10 UC) were interviewed once. Nineteen OTs, 6 mentors and 19 service managers were interviewed. Fidelity was measured for 39 ESSVR participants; mean fidelity score was 78.8% (SD:19.2%, range 31–100%). Comparison of the experiences of ESSVR and UC participants indicated duration and type of support to return to work were perceived to be better for ESSVR participants. They received early, co-ordinated support including employer liaison and workplace adjustments where appropriate. In contrast, UC participants reported limited or no VR or return to work support from health professionals. Typically, UC support lasted 2–8 weeks, with poor communication and co-ordination between rehabilitation providers. Mentor support for OTs appeared to increase fidelity. Service managers indicated ESSVR would enhance post-stroke services.

Conclusions
ESSVR was valued by participants and was delivered with fidelity; implementation appeared to be facilitated by mentor support for OTs.
Effect of Adopting a Gluten-Free Diet on Exposure to Arsenic and Other Heavy Metals in Children With Celiac Disease: A Prospective Cohort Study
Authors: Du Nan , Chang Denis , Boisvert Jason , Hron Bridget , Rosen Rachel , Punshon Tracy , Silvester Jocelyn 
Published: October 2024

INTRODUCTION:
Lifelong adherence to a gluten-free diet (GFD) is the primary treatment of celiac disease (CeD), a gluten-driven enteropathy. Concerns have been raised about increased exposure to arsenic from a GFD because rice, which naturally bioaccumulates arsenic, is commonly used as a substitute for gluten-containing grains such as wheat. We hypothesize that arsenic exposure increases in newly diagnosed children with CeD after they adopt a GFD.

METHODS:
This is a single-center prospective longitudinal cohort study of children (age 2–18 years) with elevated celiac serology who underwent a diagnostic endoscopy before initiation of a GFD between January and May 2022. The primary outcome was change in urinary arsenic concentration between endoscopy and after 6 months on a GFD.

RESULTS:
Of the 67 recruited participants, 50 had a biopsy diagnostic of CeD and were invited to continue the study. Thirty-five participants completed sample collection. Participants were from a middle-class, well-educated population that was predominantly White with presenting symptoms of abdominal pain (51%) and diarrhea (29%). After 6 months on a GFD, there was a significant increase in the median urinary arsenic concentration (3.3 µg/L vs 13.6 µg/L, P = 0.000004). In regression models, family history of CeD and Hispanic ethnicity were associated with having a higher urinary arsenic concentration after 6 months on a GFD.

DISCUSSION:
Children with newly diagnosed CeD have increased arsenic exposure shortly after transitioning to a GFD. While the arsenic levels were well below acutely toxic concentrations, the clinical impact of chronic exposure to mildly elevated arsenic levels is unknown.
A alfabetização e o texto
Authors: Pinheiro de Lacerda Mitsi 
Published: October 2024

O objetivo do artigo, de natureza ensaística, é estabelecer conversação sobre uma proposição presente há décadas no Brasil: a alfabetização com textos. A orientação teórica é proveniente da educação problematizadora e dialógica, da alfabetização sob a perspectiva discursiva, do sócio-interacionismo e da teoria da enunciação. São apresentadas ainda, de forma sucinta, algumas incursões da proposta de alfabetização com textos, em documentos legais do Brasil contemporâneo. O ensaio se inscreve em uma perspectiva freireana, destacando condições ótimas à aprendizagem e desenvolvimento da leitura e da escrita: a escuta, a pronúncia, o diálogo, a legitimidade de temas provenientes da realidade concreta do educando, a libertação da palavra e da consciência. As reflexões presentes sinalizam a relevância do dialogismo, da autoria e da interação em práticas que buscam, ao alfabetizar com textos, tecer metodologias inaugurais – filhas da educação libertadora –, e assegurar que nestas práticas haja sentido.
Capability knowledge base query to allocate process resources for master recipe formulation
Authors: Winter Michael , Klausmann Tobias , Kleinert Tobias 
Published: October 2024

Abstract
We present a method for matching the required capabilities of general recipes with available resources to formulate master recipes. Process elements extracted from BatchML XML files are used to decompose the required capabilities and match them with the capabilities offered by components at distinct levels. A capability OWL ontology with properties aids in querying and matching capabilities with resources, enabling validation via description logic (DL) queries post-inference and integration into the master recipe. DL queries and matching within a knowledge base demonstrate AI-based knowledge processing for production systems.
Towards microstructure control in forging and rolling: combining AI with process models for closed-loop property control
Authors: Reinisch Niklas , Idzik Christian , Bailly David 
Published: October 2024

Abstract
Metal forming processes like open-die forging or hot rolling are well-established for the production of key components in various industries. Nevertheless, the control of the final microstructure and hence mechanical properties is not yet common. To achieve this, the authors propose and discuss a control concept based on reinforcement learning, fast process models (FPM) and an “operator in the loop” approach. The concept is explained and tested using deviating initial ingot temperatures as idealized process disruptions. RL algorithms are trained for both processes and transferred into the controllers that are connected to a simulative environment based on FPM. Within this framework, the online adaption is possible in ∼2 s in rolling and 4–6 s in forging. This highlights the concepts suitability to be used for property control in hot metal forming.
Detektion von Prozessunregelmäßigkeiten beim MSG-Schweißen durch Analyse des Luftschallsignals mittels Convolutional Neural Network (CNN)
Authors: Brückner Julian , Rohe Maximilian , Walther Dominik , Hildebrand Jörg , Bergmann Jean Pierre , Mäder Patrick 
Published: October 2024

Zusammenfassung
Die additive Fertigung mittels DED-Arc-Verfahren ist durch die hohen Fertigungszeiten ein kostenintensiver Prozess. Die klassischen Qualitätsprüfverfahren, die der Fertigung nachgelagert sind, geben erst nach Fertigstellung des Werkstückes Aufschluss über die erreichte Qualität. Nacharbeiten sind häufig ausgeschlossen, sodass bei unzureichender Qualität das Bauteil dem Ausschuss zugeführt wird. Die Anwendung von in situ Qualitätskontrollen ermöglicht es, Unregelmäßigkeiten frühzeitig bereits während des eigentlichen Aufbauprozess zu erkennen und eine direkte Nacharbeit kann stattfinden. Die akustischen Emissionen werden bereits erfolgreich von erfahrenen Schweißern als Qualitätsmerkmal für den Prozess eingesetzt. In diesem Beitrag soll mit Hilfe der akustischen Signale, die während des Schweißens entstehen, die Prozessqualität vorhergesagt werden. Dabei liegt der Fokus auf der Erkennung des Schutzgasflusses und eventuell vorhandener Oberflächenverunreinigung durch Öl. Dies kann maßgeblich zur Bildung von Poren innerhalb der entstehenden Schweißraupen beitragen. Zur Erkennung dieser Parameter wird die Verwendung eines Convolutional Neural Networks (CNN) zur Auswertung des emittierten Luftschalls diskutiert. Als wesentliches Merkmal zur Klassifizierung werden die, in der Sprecher- und Spracherkennung verbreiteten, Mel-Cepstralkoeffizienten (MFCC) herangezogen. Des Weiteren wird der Einfluss der Netzwerkparameter des CNN auf die Klassifizierungsgüte des resultierenden Netzwerkes dargestellt. Es zeigt sich, dass die ausschließliche Verwendung der MFCC dem CNN ermöglicht Prozessabweichungen zu detektieren. Aufgrund der hohen Informationsdichte der MFCC gegenüber dem STFT-Spektrum bieten erstere die Möglichkeit die Größe des verwendeten CNN erheblich zu reduzieren.